Optically coupled CAMAC analog input output system
International Nuclear Information System (INIS)
Horie, Katsuzo; Kanazawa, Shuhei; Minehara, Eisuke; Hanashima, Susumu
1985-08-01
In an accelerator system, especially in ion sources, signals are exchanged between devices at different potentials. We have four ion sources in the negative ion injector for the JAERI tandem accelerator. Voltage to frequency conversion technic and optical fiber were used in the previous system. When we intended to extend the injector, we decided to revise the system to improve accuracy and reliability. For the purpose, we developed a new CAMAC module. It is an interface device between CAMAC dataway and optical fiber. The module has frequency synthesizers, frequency counters, optical transmitters and optical receivers in it. Accuracy, reliability and maintenability of the system were greatly improved by the module. (author)
INPUT-OUTPUT STRUCTURE OF LINEAR-DIFFERENTIAL ALGEBRAIC SYSTEMS
KUIJPER, M; SCHUMACHER, JM
Systems of linear differential and algebraic equations occur in various ways, for instance, as a result of automated modeling procedures and in problems involving algebraic constraints, such as zero dynamics and exact model matching. Differential/algebraic systems may represent an input-output
Know Your Personal Computer Basic Input-Output System (BIOS)
Indian Academy of Sciences (India)
Home; Journals; Resonance – Journal of Science Education; Volume 2; Issue 7. Know Your Personal Computer Basic Input-Output System (BIOS). Siddhartha Kumar Ghoshal. Series Article Volume 2 Issue 7 July 1997 pp 48-54. Fulltext. Click here to view fulltext PDF. Permanent link:
Advanced information processing system: Input/output network management software
Nagle, Gail; Alger, Linda; Kemp, Alexander
1988-01-01
The purpose of this document is to provide the software requirements and specifications for the Input/Output Network Management Services for the Advanced Information Processing System. This introduction and overview section is provided to briefly outline the overall architecture and software requirements of the AIPS system before discussing the details of the design requirements and specifications of the AIPS I/O Network Management software. A brief overview of the AIPS architecture followed by a more detailed description of the network architecture.
Optimizing Input/Output Using Adaptive File System Policies
Madhyastha, Tara M.; Elford, Christopher L.; Reed, Daniel A.
1996-01-01
Parallel input/output characterization studies and experiments with flexible resource management algorithms indicate that adaptivity is crucial to file system performance. In this paper we propose an automatic technique for selecting and refining file system policies based on application access patterns and execution environment. An automatic classification framework allows the file system to select appropriate caching and pre-fetching policies, while performance sensors provide feedback used to tune policy parameters for specific system environments. To illustrate the potential performance improvements possible using adaptive file system policies, we present results from experiments involving classification-based and performance-based steering.
Input-output analysis for installing renewable energy systems
International Nuclear Information System (INIS)
Itoh, Y.; Nakata, T.
2004-01-01
Renewable energy facilities have been installed in many regions, because of their possibility to be an alternative to fossil fuels for mitigating global warming. Besides the profitability of renewable energy businesses, indirect economic effects of installing renewable energy facilities should be clarified. This study examines the possibility that the renewable energy facilities give renewed impetus to regional economic progress. The economic effects are analysed with input-output techniques in a rural area in Japan. As a consequence, both positive and negative effects on the rural economy are derived. In addition, we will focus on the changes in sectors such as construction, business services, banking, etc. as a result of economic activities for renewable systems. The business benefits of renewable energy system are discussed. (author)
State space and input-output linear systems
Delchamps, David F
1988-01-01
It is difficult for me to forget the mild sense of betrayal I felt some ten years ago when I discovered, with considerable dismay, that my two favorite books on linear system theory - Desoer's Notes for a Second Course on Linear Systems and Brockett's Finite Dimensional Linear Systems - were both out of print. Since that time, of course, linear system theory has undergone a transformation of the sort which always attends the maturation of a theory whose range of applicability is expanding in a fashion governed by technological developments and by the rate at which such advances become a part of engineering practice. The growth of the field has inspired the publication of some excellent books; the encyclopedic treatises by Kailath and Chen, in particular, come immediately to mind. Nonetheless, I was inspired to write this book primarily by my practical needs as a teacher and researcher in the field. For the past five years, I have taught a one semester first year gradu ate level linear system theory course i...
Preliminary Test for Nonlinear Input Output Relations in SISO Systems
DEFF Research Database (Denmark)
Knudsen, Torben
2000-01-01
This paper discusses and develops preliminary statistical tests for detecting nonlinearities in the deterministic part of SISO systems with noise. The most referenced method is unreliable for common noise processes as e.g.\\ colored. Therefore two new methods based on superposition and sinus input...
Study and development of a generalised input-output system for data base management systems
International Nuclear Information System (INIS)
Zidi, Noureddine
1975-01-01
This thesis reports a study which aimed at designing and developing a software for the management and execution of all input-output actions of data base management systems. This software is also an interface between data base management systems and the various operating systems. After a recall of general characteristics of database management systems, the author presents the previously developed GRISBI system (rational management of information stored in an integrated database), and describes difficulties faced to adapt this system to the new access method (VSAM, virtual sequential access method). This lead to the search for a more general solution, the development of which is presented in the second part of this thesis: environment of the input-output generalised system, architecture, internal specifications. The last part presents flowcharts and statements of the various routines [fr
Koliopoulos, T. C.; Koliopoulou, G.
2007-10-01
We present an input-output solution for simulating the associated behavior and optimized physical needs of an environmental system. The simulations and numerical analysis determined the accurate boundary loads and areas that were required to interact for the proper physical operation of a complicated environmental system. A case study was conducted to simulate the optimum balance of an environmental system based on an artificial intelligent multi-interacting input-output numerical scheme. The numerical results were focused on probable further environmental management techniques, with the objective of minimizing any risks and associated environmental impact to protect the quality of public health and the environment. Our conclusions allowed us to minimize the associated risks, focusing on probable cases in an emergency to protect the surrounded anthropogenic or natural environment. Therefore, the lining magnitude could be determined for any useful associated technical works to support the environmental system under examination, taking into account its particular boundary necessities and constraints.
Bastiaans, M.J.; Alieva, T.
2002-01-01
It is shown how all global Wigner distribution moments of arbitrary order in the output plane of a (generally anamorphic) two-dimensional fractional Fourier transform system can be expressed in terms of the moments in the input plane. This general input-output relationship is then broken down into a
Directory of Open Access Journals (Sweden)
Shahrukh Adnan Khan M. D.
2017-01-01
Full Text Available This paper presents a Graphical User Interface (GUI software utility for the input/output characterization of single variable and multivariable nonlinear systems by obtaining the sinusoidal input describing function (SIDF of the plant. The software utility is developed on MATLAB R2011a environment. The developed GUI holds no restriction on the nonlinearity type, arrangement and system order; provided that output(s of the system is obtainable either though simulation or experiments. An insight to the GUI and its features are presented in this paper and example problems from both single variable and multivariable cases are demonstrated. The formulation of input/output behavior of the system is discussed and the nucleus of the MATLAB command underlying the user interface has been outlined. Some of the industries that would benefit from this software utility includes but not limited to aerospace, defense technology, robotics and automotive.
Switched periodic systems in discrete time: stability and input-output norms
Bolzern, Paolo; Colaneri, Patrizio
2013-07-01
This paper deals with the analysis of stability and the characterisation of input-output norms for discrete-time periodic switched linear systems. Such systems consist of a network of time-periodic linear subsystems sharing the same state vector and an exogenous switching signal that triggers the jumps between the subsystems. The overall system exhibits a complex dynamic behaviour due to the interplay between the time periodicity of the subsystem parameters and the switching signal. Both arbitrary switching signals and signals satisfying a dwell-time constraint are considered. Linear matrix inequality conditions for stability and guaranteed H2 and H∞ performances are provided. The results heavily rely on the merge of the theory of linear periodic systems and recent developments on switched linear time-invariant systems.
Detection of no-model input-output pairs in closed-loop systems.
Potts, Alain Segundo; Alvarado, Christiam Segundo Morales; Garcia, Claudio
2017-11-01
The detection of no-model input-output (IO) pairs is important because it can speed up the multivariable system identification process, since all the pairs with null transfer functions are previously discarded and it can also improve the identified model quality, thus improving the performance of model based controllers. In the available literature, the methods focus just on the open-loop case, since in this case there is not the effect of the controller forcing the main diagonal in the transfer matrix to one and all the other terms to zero. In this paper, a modification of a previous method able to detect no-model IO pairs in open-loop systems is presented, but adapted to perform this duty in closed-loop systems. Tests are performed by using the traditional methods and the proposed one to show its effectiveness. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
WORKBENCH FOR CONTROL SYSTEMS TRIALS BASED ON VIPA 300 CONTROLLER AND ADVANTECH INPUT/OUTPUT CARD
Directory of Open Access Journals (Sweden)
M. V. Levinskyi
2015-01-01
Full Text Available The topic is about workbench creation for control systems trials based on VIPA 300 industrial PLC and model of control object which is implemented in MatLab Simulink program on PC. Connection between controller and the PC is provided by the Advantech PCI-1711 input/output card of discrete and analog signals. Object identification,control system synthesis, creation of control device structure and its parametrical identification, as a rule, is done on a PC in a modelling environment, e.g. in MatLab. But often, using this PC modelling, the hardware and software features of algorithms which were obtained during system synthesis are not considered in a specific industrial PLC.It is considered a good idea to use a composite version where obtained algorithms are tested in a real industrial PLC and control object is substituted by a model which is working on a PC in real time scale. In this case software realization of algorithms in a specific PLC are fully taken into account and substitution of real control object by itsmodel considerably reduces the costs for carrying out experiments and allows to study the system behavior when control object parameters and modes of operation vary greatly. The creation of workbench stipulates several stages: configuration and programming of industrial PLC VIPA 313 SC, installation and configuration of Advantech PCI- 1711 input/output card, tuning of Simulink modelling environment for working in real time scale using Real-Time Windows Target Library, testing of workbench by using constant and harmonic signals of different frequencies. Work results of virtual stabilization system are compared with combined version. In virtual stabilization system PID governor and control object are implemented in Simulink. In combined version control object is still implemented in Simulink and PID governor - in VIPA 313 SC controller (using functional block FB58 from Step7 standard library.
International Nuclear Information System (INIS)
Dupuy, R.
1970-01-01
The input-output supervisor is the program which monitors the flow of informations between core storage and peripheral equipments of a computer. This work is composed of three parts: 1 - Study of a generalized input-output supervisor. With sample modifications it looks like most of input-output supervisors which are running now on computers. 2 - Application of this theory on a magnetic drum. 3 - Hardware requirement for time-sharing. (author) [fr
International Nuclear Information System (INIS)
Pan, Haoran; Koehler, Jonathan
2007-01-01
Learning curves have recently been widely adopted in climate-economy models to incorporate endogenous change of energy technologies, replacing the conventional assumption of an autonomous energy efficiency improvement. However, there has been little consideration of the credibility of the learning curve. The current trend that many important energy and climate change policy analyses rely on the learning curve means that it is of great importance to critically examine the basis for learning curves. Here, we analyse the use of learning curves in energy technology, usually implemented as a simple power function. We find that the learning curve cannot separate the effects of price and technological change, cannot reflect continuous and qualitative change of both conventional and emerging energy technologies, cannot help to determine the time paths of technological investment, and misses the central role of R and D activity in driving technological change. We argue that a logistic curve of improving performance modified to include R and D activity as a driving variable can better describe the cost reductions in energy technologies. Furthermore, we demonstrate that the top-down Leontief technology can incorporate the bottom-up technologies that improve along either the learning curve or the logistic curve, through changing input-output coefficients. An application to UK wind power illustrates that the logistic curve fits the observed data better and implies greater potential for cost reduction than the learning curve does. (author)
Development of Input/Output System for the Reactor Transient Analysis System (RETAS)
International Nuclear Information System (INIS)
Suh, Jae Seung; Kang, Doo Hyuk; Cho, Yeon Sik; Ahn, Seung Hoon; Cho, Yong Jin
2009-01-01
A Korea Institute of Nuclear Safety Reactor Transient Analysis System (KINS-RETAS) aims at providing a realistic prediction of core and RCS response to the potential or actual event scenarios in Korean nuclear power plants (NPPs). A thermal hydraulic system code MARS is a pivot code of the RETAS, and used to predict thermal hydraulic (TH) behaviors in the core and associated systems. MARS alone can be applied to many types of transients, but is sometimes coupled with the other codes developed for different objectives. Many tools have been developed to aid users in preparing input and displaying the transient information and output data. Output file and Graphical User Interfaces (GUI) that help prepare input decks, as seen in SNAP (Gitnick, 1998), VISA (K.D. Kim, 2007) and display aids include the eFAST (KINS, 2007). The tools listed above are graphical interfaces. The input deck builders allow the user to create a functional diagram of the plant, pictorially on the screen. The functional diagram, when annotated with control volume and junction numbers, is a nodalization diagram. Data required for an input deck is entered for volumes and junctions through a mouse-driven menu and pop-up dialog; after the information is complete, an input deck is generated. Display GUIs show data from MARS calculations, either during or after the transient. The RETAS requires the user to first generate a set of 'input', two dimensional pictures of the plant on which some of the data is displayed either numerically or with a color map. The RETAS can generate XY-plots of the data. Time histories of plant conditions can be seen via the plots or through the RETAS's replay mode. The user input was combined with design input from MARS developers and experts from both the GUI and ergonomics fields. A partial list of capabilities follows. - 3D display for neutronics. - Easier method (less user time and effort) to generate 'input' for the 3D displays. - Detailed view of data at volume or
Development of Input/Output System for the Reactor Transient Analysis System (RETAS)
Energy Technology Data Exchange (ETDEWEB)
Suh, Jae Seung; Kang, Doo Hyuk; Cho, Yeon Sik [ENESYS, Daejeon (Korea, Republic of); Ahn, Seung Hoon; Cho, Yong Jin [Korea Institute of Nuclear Safety, Daejeon (Korea, Republic of)
2009-05-15
A Korea Institute of Nuclear Safety Reactor Transient Analysis System (KINS-RETAS) aims at providing a realistic prediction of core and RCS response to the potential or actual event scenarios in Korean nuclear power plants (NPPs). A thermal hydraulic system code MARS is a pivot code of the RETAS, and used to predict thermal hydraulic (TH) behaviors in the core and associated systems. MARS alone can be applied to many types of transients, but is sometimes coupled with the other codes developed for different objectives. Many tools have been developed to aid users in preparing input and displaying the transient information and output data. Output file and Graphical User Interfaces (GUI) that help prepare input decks, as seen in SNAP (Gitnick, 1998), VISA (K.D. Kim, 2007) and display aids include the eFAST (KINS, 2007). The tools listed above are graphical interfaces. The input deck builders allow the user to create a functional diagram of the plant, pictorially on the screen. The functional diagram, when annotated with control volume and junction numbers, is a nodalization diagram. Data required for an input deck is entered for volumes and junctions through a mouse-driven menu and pop-up dialog; after the information is complete, an input deck is generated. Display GUIs show data from MARS calculations, either during or after the transient. The RETAS requires the user to first generate a set of 'input', two dimensional pictures of the plant on which some of the data is displayed either numerically or with a color map. The RETAS can generate XY-plots of the data. Time histories of plant conditions can be seen via the plots or through the RETAS's replay mode. The user input was combined with design input from MARS developers and experts from both the GUI and ergonomics fields. A partial list of capabilities follows. - 3D display for neutronics. - Easier method (less user time and effort) to generate 'input' for the 3D displays. - Detailed view
International Nuclear Information System (INIS)
Derrouazin, A.; Aillerie, M.; Mekkakia-Maaza, N.; Charles, J.-P.
2017-01-01
Highlights: • We present a fuzzy smart controller for hybrid renewable and conventional energy system. • The rules are based on human intelligence and implemented in the smart controller. • Efficient tracking capability of the proposed controller is proofed in this paper by an example. • Excess produced renewable energy is converted to hydrogen for household use . • Considerable electric grid energy saving is highlighted in the proposed controller system. - Abstract: This study concerns the conception and development of an efficient multi input-output fuzzy logic smart controller, to manage the energy flux of a sustainable hybrid power system, based on renewable power sources, integrating solar panels and a wind turbine associated with storage, applied to a typical residential habitat. In the suggested topology, the energy surplus is redirected to an electrolysis system to produce hydrogen suitable for household utilities. To assume a constant access to electricity in case of consumption peak, connection to the grid is also considered as an exceptional rescue resource. The objective of the presented controller is to exploit instantaneously the produced renewable electric energy and insure savings of electric grid energy. The proposed multi input-output fuzzy logic smart controller has been achieved and verified, outcome switches command signals are discussed and the renewable energy system integration ratio is highlighted.
Directory of Open Access Journals (Sweden)
Federica Cerina
Full Text Available Production systems, traditionally analyzed as almost independent national systems, are increasingly connected on a global scale. Only recently becoming available, the World Input-Output Database (WIOD is one of the first efforts to construct the global multi-regional input-output (GMRIO tables. By viewing the world input-output system as an interdependent network where the nodes are the individual industries in different economies and the edges are the monetary goods flows between industries, we analyze respectively the global, regional, and local network properties of the so-called world input-output network (WION and document its evolution over time. At global level, we find that the industries are highly but asymmetrically connected, which implies that micro shocks can lead to macro fluctuations. At regional level, we find that the world production is still operated nationally or at most regionally as the communities detected are either individual economies or geographically well defined regions. Finally, at local level, for each industry we compare the network-based measures with the traditional methods of backward linkages. We find that the network-based measures such as PageRank centrality and community coreness measure can give valuable insights into identifying the key industries.
International Nuclear Information System (INIS)
Madlener, Reinhard; Koller, Martin
2007-01-01
This paper reports on an empirical investigation about the economic and CO 2 mitigation impacts of bioenergy promotion in the Austrian federal province of Vorarlberg. We study domestic value-added, employment, and fiscal effects by means of a static input-output analysis. The bioenergy systems analysed comprise biomass district heating, pellet heating, and automated wood chip heating systems, as well as logwood stoves and boilers, ceramic stoves, and buffer storage systems. The results indicate that gross economic effects are significant, regarding both investment and operation of the systems, and that the negative economic effects caused by the displacement of conventional decentralised heating systems might be in the order of 20-40%. Finally, CO 2 mitigation effects are substantial, contributing already in 2004 around 35% of the 2010 CO 2 mitigation target of the Land Vorarlberg for all renewable energy sources
An Analysis of Input/Output Paradigms for Real-Time Systems
1990-07-01
timing and concurrency aspects of real - time systems . This paper illustrates how to build a mathematical model of the schedulability of a real-time...various design alternatives. The primary characteristic that distinguishes real-time system from non- real - time systems is the importance of time. The
Dialog system for automatic data input/output and processing with two BESM-6 computers
International Nuclear Information System (INIS)
Belyaev, Y.N.; Gorlov, Y.P.; Makarychev, S.V.; Monakov, A.A.; Shcherbakov, S.A.
1985-01-01
This paper presents a system for conducting experiments with fully automatic processing of data from multichannel recorders in the dialog mode. The system acquires data at a rate of 2.5 . 10 3 readings/sec, processes in real time, and outputs digital and graphical material in a multitasking environment
Test for Nonlinear Input Output Relations in SISO Systems by Preliminary Data Analysis
DEFF Research Database (Denmark)
Knudsen, Torben
2000-01-01
This paper discusses and develops preliminary statistical tests for detecting nonlinearities in the deterministic part of SISO systems with noise. The most referenced method is unreliable for common noise processes as e.g.\\ colored. Therefore two new methods based on superposition and sinus input...
Modelling Implicit Communication in Multi-Agent Systems with Hybrid Input/Output Automata
Directory of Open Access Journals (Sweden)
Marta Capiluppi
2012-10-01
Full Text Available We propose an extension of Hybrid I/O Automata (HIOAs to model agent systems and their implicit communication through perturbation of the environment, like localization of objects or radio signals diffusion and detection. To this end we decided to specialize some variables of the HIOAs whose values are functions both of time and space. We call them world variables. Basically they are treated similarly to the other variables of HIOAs, but they have the function of representing the interaction of each automaton with the surrounding environment, hence they can be output, input or internal variables. Since these special variables have the role of simulating implicit communication, their dynamics are specified both in time and space, because they model the perturbations induced by the agent to the environment, and the perturbations of the environment as perceived by the agent. Parallel composition of world variables is slightly different from parallel composition of the other variables, since their signals are summed. The theory is illustrated through a simple example of agents systems.
Energy Technology Data Exchange (ETDEWEB)
Song, Young Gi; Kim, Han Sung; Seol, Kyung Tae; Kwon, Hyeok Jung; Cho, Yong Sub [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)
2010-05-15
The Low-Level RF (LLRF) control system of the Proton Engineering Frontier Project (PEFP) was developed for handling the driving frequency for Quadrupole (RFQ) and the Draft Tube Linac (DTL) cavities in 2006. The RF amplitude and phase of the accelerating field were controlled within 1% and 1 degree by stability requirements, respectively. Operators have been using the LLRF control system under the windows based text console mode as an operator interface. The LLRF control system could not be integrated with Experimental Physics Industrial Control System (EPICS) Input Output Controllers (IOC) for each subsection of PEFP facility. The main objective of this study is to supply operators of the LLRF control system with user friendly and convenient operating environment. The new LLRF control system is composed of a Verse Module Eurocard (VME) baseboard, a PCI Mezzanine Card (PMC), Board Support Package (BSP), EPICS software tool and a Real-Time Operating System (RTOS) VxWorks. A test with a dummy cavity of the new LLRF control system shows that operators can control and monitor operation parameters for a desired feedback action by using EPICS Channel Access (CA).
International Nuclear Information System (INIS)
Song, Young Gi; Kim, Han Sung; Seol, Kyung Tae; Kwon, Hyeok Jung; Cho, Yong Sub
2010-01-01
The Low-Level RF (LLRF) control system of the Proton Engineering Frontier Project (PEFP) was developed for handling the driving frequency for Quadrupole (RFQ) and the Draft Tube Linac (DTL) cavities in 2006. The RF amplitude and phase of the accelerating field were controlled within 1% and 1 degree by stability requirements, respectively. Operators have been using the LLRF control system under the windows based text console mode as an operator interface. The LLRF control system could not be integrated with Experimental Physics Industrial Control System (EPICS) Input Output Controllers (IOC) for each subsection of PEFP facility. The main objective of this study is to supply operators of the LLRF control system with user friendly and convenient operating environment. The new LLRF control system is composed of a Verse Module Eurocard (VME) baseboard, a PCI Mezzanine Card (PMC), Board Support Package (BSP), EPICS software tool and a Real-Time Operating System (RTOS) VxWorks. A test with a dummy cavity of the new LLRF control system shows that operators can control and monitor operation parameters for a desired feedback action by using EPICS Channel Access (CA).
1972-01-01
A general view of the remote input/output station installed in building 112 (ISR) and used for submitting jobs to the CDC 6500 and 6600. The card reader on the left and the line printer on the right are operated by programmers on a self-service basis.
Directory of Open Access Journals (Sweden)
Zhixiong Zhong
2013-01-01
Full Text Available The stability analysis and stabilization of Takagi-Sugeno (T-S fuzzy delta operator systems with time-varying delay are investigated via an input-output approach. A model transformation method is employed to approximate the time-varying delay. The original system is transformed into a feedback interconnection form which has a forward subsystem with constant delays and a feedback one with uncertainties. By applying the scaled small gain (SSG theorem to deal with this new system, and based on a Lyapunov Krasovskii functional (LKF in delta operator domain, less conservative stability analysis and stabilization conditions are obtained. Numerical examples are provided to illustrate the advantages of the proposed method.
Koeijer, de T.J.; Wossink, G.A.A.; Ittersum, van M.K.; Struik, P.C.; Renkema, J.
1999-01-01
Environmental legislation is forcing a rethink about desirable crop production systems. The development of new production systems that meet economic and environmental objectives demands knowledge about which input–output combinations are feasible and optimal in practice. A review of concepts in
INPUT-OUTPUT ANALYSIS : THE NEXT 25 YEARS
Dietzenbacher, Erik; Lenzen, Manfred; Los, Bart; Guan, Dabo; Lahr, Michael L.; Sancho, Ferran; Suh, Sangwon; Yang, Cuihong; Sancho, S.
2013-01-01
This year marks the 25th anniversary of the International Input-Output Association and the 25th volume of Economic Systems Research. To celebrate this anniversary, a group of eight experts provide their views on the future of input-output. Looking forward, they foresee progress in terms of data
Optimizing microwave photodetection: input-output theory
Schöndorf, M.; Govia, L. C. G.; Vavilov, M. G.; McDermott, R.; Wilhelm, F. K.
2018-04-01
High fidelity microwave photon counting is an important tool for various areas from background radiation analysis in astronomy to the implementation of circuit quantum electrodynamic architectures for the realization of a scalable quantum information processor. In this work we describe a microwave photon counter coupled to a semi-infinite transmission line. We employ input-output theory to examine a continuously driven transmission line as well as traveling photon wave packets. Using analytic and numerical methods, we calculate the conditions on the system parameters necessary to optimize measurement and achieve high detection efficiency. With this we can derive a general matching condition depending on the different system rates, under which the measurement process is optimal.
Interface Input/Output Automata
DEFF Research Database (Denmark)
Larsen, Kim Guldstrand; Nyman, Ulrik; Wasowski, Andrzej
2006-01-01
Building on the theory of interface automata by de Alfaro and Henzinger we design an interface language for Lynch’s I/O, a popular formalism used in the development of distributed asynchronous systems, not addressed by previous interface research. We introduce an explicit separation of assumptions...... a method for solving systems of relativized behavioral inequalities as used in our setup and draw a formal correspondence between our work and interface automata....
Input/Output linearizing control of a nuclear reactor
International Nuclear Information System (INIS)
Perez C, V.
1994-01-01
The feedback linearization technique is an approach to nonlinear control design. The basic idea is to transform, by means of algebraic methods, the dynamics of a nonlinear control system into a full or partial linear system. As a result of this linearization process, the well known basic linear control techniques can be used to obtain some desired dynamic characteristics. When full linearization is achieved, the method is referred to as input-state linearization, whereas when partial linearization is achieved, the method is referred to as input-output linearization. We will deal with the latter. By means of input-output linearization, the dynamics of a nonlinear system can be decomposed into an external part (input-output), and an internal part (unobservable). Since the external part consists of a linear relationship among the output of the plant and the auxiliary control input mentioned above, it is easy to design such an auxiliary control input so that we get the output to behave in a predetermined way. Since the internal dynamics of the system is known, we can check its dynamics behavior on order of to ensure that the internal states are bounded. The linearization method described here can be applied to systems with one-input/one-output, as well as to systems with multiple-inputs/multiple-outputs. Typical control problems such as stabilization and reference path tracking can be solved using this technique. In this work, the input/output linearization theory is presented, as well as the problem of getting the output variable to track some desired trayectories. Further, the design of an input/output control system applied to the nonlinear model of a research nuclear reactor is included, along with the results obtained by computer simulation. (Author)
Enhancing MINIX 3.X input/output performance
Pessolani, Pablo Andrés; Weisz, Gustavo; Bardus, Marisa; Hein, César
2008-01-01
MINIX 3.X is an open-source operating system designed to be highly reliable, flexible, and secure. The kernel is extremely small and user processes, specialized servers and device driver runs as user-mode insulated processes. These features, the tiny amount of kernel code, and other aspects greatly enhance system reliability. The drawbacks of running device drivers in user-mode are the performance penalties on input/output ports access, kernel data structures access, interrupt indirect man...
An Interface Theory for Input/Output Automata
DEFF Research Database (Denmark)
Larsen, Kim Guldstrand; Nyman, Ulrik; Wasowski, Andrzej
Building on the theory of interface automata by de~Alfaro and Henzinger we design an interface language for Lynch's Input/Output Automata, a popular formalism used in the development of distributed asynchronous systems, not addressed by previous interface research. We introduce an explicit....... We also present a method for solving systems of relativized behavioral inequalities as used in our setup and draw a formal correspondence between our work and interface automata. Proofs are provided in an appendix....
Schluter, Gerald E.; Lee, Chinkook
1996-01-01
Output growth of the U.S. Food System is examined to apportion first the importance of domestic food demand and then the importance of components of domestic food demand. Growth of U.S. food processing output is heavily dependent upon domestic food demand and particularly its personal consumption expenditures components - food purchased for off-premise consumption and purchased meals and beverages.
González-Díaz, Humberto; Arrasate, Sonia; Gómez-SanJuan, Asier; Sotomayor, Nuria; Lete, Esther; Besada-Porto, Lina; Ruso, Juan M
2013-01-01
In general perturbation methods starts with a known exact solution of a problem and add "small" variation terms in order to approach to a solution for a related problem without known exact solution. Perturbation theory has been widely used in almost all areas of science. Bhor's quantum model, Heisenberg's matrix mechanincs, Feyman diagrams, and Poincare's chaos model or "butterfly effect" in complex systems are examples of perturbation theories. On the other hand, the study of Quantitative Structure-Property Relationships (QSPR) in molecular complex systems is an ideal area for the application of perturbation theory. There are several problems with exact experimental solutions (new chemical reactions, physicochemical properties, drug activity and distribution, metabolic networks, etc.) in public databases like CHEMBL. However, in all these cases, we have an even larger list of related problems without known solutions. We need to know the change in all these properties after a perturbation of initial boundary conditions. It means, when we test large sets of similar, but different, compounds and/or chemical reactions under the slightly different conditions (temperature, time, solvents, enzymes, assays, protein targets, tissues, partition systems, organisms, etc.). However, to the best of our knowledge, there is no QSPR general-purpose perturbation theory to solve this problem. In this work, firstly we review general aspects and applications of both perturbation theory and QSPR models. Secondly, we formulate a general-purpose perturbation theory for multiple-boundary QSPR problems. Last, we develop three new QSPR-Perturbation theory models. The first model classify correctly >100,000 pairs of intra-molecular carbolithiations with 75-95% of Accuracy (Ac), Sensitivity (Sn), and Specificity (Sp). The model predicts probabilities of variations in the yield and enantiomeric excess of reactions due to at least one perturbation in boundary conditions (solvent, temperature
Input/output plugin architecture for MDSplus
International Nuclear Information System (INIS)
Stillerman, Joshua; Fredian, Thomas; Manduchi, Gabriele
2014-01-01
The first version of MDSplus was released in 1991 for VAX/VMS. Since that time the underlying file formats have remained constant. The software however has evolved, it was ported to unix, linux, Windows, and Macintosh. In 1997 a TCP based protocol, mdsip, was added to provide network access to MDSplus data. In 2011 a mechanism was added to allow protocol plugins to permit the use of other transport mechanisms such as ssh to access data users. This paper describes a similar design which permits the insertion of plugins to handle the reading and writing of MDSplus data at the data storage level. Tree paths become URIs which specify the protocol, host, and protocol specific information. The protocol is provided by a dynamically activated shared library that can provide any consistent subset of the data store access API, treeshr. The existing low level network protocol called mdsip, is activated by defining tree paths like “host::/directory”. Using the new plugin mechanism this is re-implemented as an instance of the general plugin that replaces the low level treeshr input/output routines. It is specified by using a path like “mdsip://host/directory”. This architecture will make it possible to adapt the MDSplus data organization and analysis tools to other underlying data storage. The first new application of this, after the existing network protocol is implemented, will be a plugin based on a key value store. Key value stores, can provide inexpensive scalable, redundant data storage. An example of this might be an Amazon G3 plugin which would let you specify a tree path such as “AG3://container” to access MDSplus data stored in the cloud
Input/output plugin architecture for MDSplus
Energy Technology Data Exchange (ETDEWEB)
Stillerman, Joshua, E-mail: jas@psfc.mit.edu [Massachusetts Institute of Technology, 175 Albany Street, Cambridge, MA 02139 (United States); Fredian, Thomas, E-mail: twf@psfc.mit.edu [Massachusetts Institute of Technology, 175 Albany Street, Cambridge, MA 02139 (United States); Manduchi, Gabriele, E-mail: gabriele.manduchi@igi.cnr.it [Consorzio RFX, Euratom-ENEA Association, Corso Stati Uniti 4, Padova 35127 (Italy)
2014-05-15
The first version of MDSplus was released in 1991 for VAX/VMS. Since that time the underlying file formats have remained constant. The software however has evolved, it was ported to unix, linux, Windows, and Macintosh. In 1997 a TCP based protocol, mdsip, was added to provide network access to MDSplus data. In 2011 a mechanism was added to allow protocol plugins to permit the use of other transport mechanisms such as ssh to access data users. This paper describes a similar design which permits the insertion of plugins to handle the reading and writing of MDSplus data at the data storage level. Tree paths become URIs which specify the protocol, host, and protocol specific information. The protocol is provided by a dynamically activated shared library that can provide any consistent subset of the data store access API, treeshr. The existing low level network protocol called mdsip, is activated by defining tree paths like “host::/directory”. Using the new plugin mechanism this is re-implemented as an instance of the general plugin that replaces the low level treeshr input/output routines. It is specified by using a path like “mdsip://host/directory”. This architecture will make it possible to adapt the MDSplus data organization and analysis tools to other underlying data storage. The first new application of this, after the existing network protocol is implemented, will be a plugin based on a key value store. Key value stores, can provide inexpensive scalable, redundant data storage. An example of this might be an Amazon G3 plugin which would let you specify a tree path such as “AG3://container” to access MDSplus data stored in the cloud.
Analysis of chaos in high-dimensional wind power system.
Wang, Cong; Zhang, Hongli; Fan, Wenhui; Ma, Ping
2018-01-01
A comprehensive analysis on the chaos of a high-dimensional wind power system is performed in this study. A high-dimensional wind power system is more complex than most power systems. An 11-dimensional wind power system proposed by Huang, which has not been analyzed in previous studies, is investigated. When the systems are affected by external disturbances including single parameter and periodic disturbance, or its parameters changed, chaotic dynamics of the wind power system is analyzed and chaotic parameters ranges are obtained. Chaos existence is confirmed by calculation and analysis of all state variables' Lyapunov exponents and the state variable sequence diagram. Theoretical analysis and numerical simulations show that the wind power system chaos will occur when parameter variations and external disturbances change to a certain degree.
The Economic Impact of Tourism. An Input-Output Analysis
Camelia SURUGIU
2009-01-01
The paper presents an Input-Output Analysis for Romania, an important source of information for the investigation of the inter-relations existing among different industries. The Input-Output Analysis is used to determine the role and importance of different economic value added, incomes and employment and it analyses the existing connection in an economy. This paper is focused on tourism and the input-output analysis is finished for the Hotels and Restaurants Sector.
Water resources and environmental input-output analysis and its key study issues: a review
YANG, Z.; Xu, X.
2013-12-01
Used to study the material and energy flow in socioeconomic system, Input-Output Analysis(IOA) had been an effective analysis tool since its appearance. The research fields of Input-Output Analysis were increasingly expanded and studied in depth with the development of fundamental theory. In this paper, starting with introduction of theory development, the water resources input-output analysis and environmental input-output analysis had been specifically reviewed, and two key study issues mentioned as well. Input-Occupancy-Output Analysis and Grey Input-Output Analysis whose proposal and development were introduced firstly could be regard as the effective complements of traditional IOA theory. Because of the hypotheses of homogeneity, stability and proportionality, Input-Occupancy-Output Analysis and Grey Input-Output Analysis always had been restricted in practical application inevitably. In the applied study aspect, with investigation of abundant literatures, research of water resources input-output analysis and environmental input-output analysis had been comprehensively reviewed and analyzed. The regional water resources flow between different economic sectors had been systematically analyzed and stated, and several types of environmental input-output analysis models combined with other effective analysis tools concluded. In two perspectives in terms of external and inland aspect, the development of water resources and environmental input-output analysis model had been explained, and several typical study cases in recent years listed respectively. By the aid of sufficient literature analysis, the internal development tendency and study hotspot had also been summarized. In recent years, Chinese literatures reporting water resources consumption analysis and virtue water study had occupied a large share. Water resources consumption analysis had always been the emphasis of inland water resources IOA. Virtue water study had been considered as the new hotspot of
Prioritizing Interdependent Production Processes using Leontief Input-Output Model
Directory of Open Access Journals (Sweden)
Masbad Jesah Grace
2016-03-01
Full Text Available This paper proposes a methodology in identifying key production processes in an interdependent production system. Previous approaches on this domain have drawbacks that may potentially affect the reliability of decision-making. The proposed approach adopts the Leontief input-output model (L-IOM which was proven successful in analyzing interdependent economic systems. The motivation behind such adoption lies in the strength of L-IOM in providing a rigorous quantitative framework in identifying key components of interdependent systems. In this proposed approach, the consumption and production flows of each process are represented respectively by the material inventory produced by the prior process and the material inventory produced by the current process, both in monetary values. A case study in a furniture production system located in central Philippines was carried out to elucidate the proposed approach. Results of the case were reported in this work
The concept of parallel input/output processing for an electron linac
International Nuclear Information System (INIS)
Emoto, Takashi
1993-01-01
The instrumentation of and the control system for the PNC 10 MeV CW electron linac are described. A new concept of parallel input/output processing for the linac has been introduced. It is based on a substantial number of input/output processors(IOP) using beam control and diagnostics. The flexibility and simplicity of hardware/software are significant advantages with this scheme. (author)
A Markovian model of evolving world input-output network.
Directory of Open Access Journals (Sweden)
Vahid Moosavi
Full Text Available The initial theoretical connections between Leontief input-output models and Markov chains were established back in 1950s. However, considering the wide variety of mathematical properties of Markov chains, so far there has not been a full investigation of evolving world economic networks with Markov chain formalism. In this work, using the recently available world input-output database, we investigated the evolution of the world economic network from 1995 to 2011 through analysis of a time series of finite Markov chains. We assessed different aspects of this evolving system via different known properties of the Markov chains such as mixing time, Kemeny constant, steady state probabilities and perturbation analysis of the transition matrices. First, we showed how the time series of mixing times and Kemeny constants could be used as an aggregate index of globalization. Next, we focused on the steady state probabilities as a measure of structural power of the economies that are comparable to GDP shares of economies as the traditional index of economies welfare. Further, we introduced two measures of systemic risk, called systemic influence and systemic fragility, where the former is the ratio of number of influenced nodes to the total number of nodes, caused by a shock in the activity of a node, and the latter is based on the number of times a specific economic node is affected by a shock in the activity of any of the other nodes. Finally, focusing on Kemeny constant as a global indicator of monetary flow across the network, we showed that there is a paradoxical effect of a change in activity levels of economic nodes on the overall flow of the world economic network. While the economic slowdown of the majority of nodes with high structural power results to a slower average monetary flow over the network, there are some nodes, where their slowdowns improve the overall quality of the network in terms of connectivity and the average flow of the money.
A Markovian model of evolving world input-output network.
Moosavi, Vahid; Isacchini, Giulio
2017-01-01
The initial theoretical connections between Leontief input-output models and Markov chains were established back in 1950s. However, considering the wide variety of mathematical properties of Markov chains, so far there has not been a full investigation of evolving world economic networks with Markov chain formalism. In this work, using the recently available world input-output database, we investigated the evolution of the world economic network from 1995 to 2011 through analysis of a time series of finite Markov chains. We assessed different aspects of this evolving system via different known properties of the Markov chains such as mixing time, Kemeny constant, steady state probabilities and perturbation analysis of the transition matrices. First, we showed how the time series of mixing times and Kemeny constants could be used as an aggregate index of globalization. Next, we focused on the steady state probabilities as a measure of structural power of the economies that are comparable to GDP shares of economies as the traditional index of economies welfare. Further, we introduced two measures of systemic risk, called systemic influence and systemic fragility, where the former is the ratio of number of influenced nodes to the total number of nodes, caused by a shock in the activity of a node, and the latter is based on the number of times a specific economic node is affected by a shock in the activity of any of the other nodes. Finally, focusing on Kemeny constant as a global indicator of monetary flow across the network, we showed that there is a paradoxical effect of a change in activity levels of economic nodes on the overall flow of the world economic network. While the economic slowdown of the majority of nodes with high structural power results to a slower average monetary flow over the network, there are some nodes, where their slowdowns improve the overall quality of the network in terms of connectivity and the average flow of the money.
Application of computer voice input/output
International Nuclear Information System (INIS)
Ford, W.; Shirk, D.G.
1981-01-01
The advent of microprocessors and other large-scale integration (LSI) circuits is making voice input and output for computers and instruments practical; specialized LSI chips for speech processing are appearing on the market. Voice can be used to input data or to issue instrument commands; this allows the operator to engage in other tasks, move about, and to use standard data entry systems. Voice synthesizers can generate audible, easily understood instructions. Using voice characteristics, a control system can verify speaker identity for security purposes. Two simple voice-controlled systems have been designed at Los Alamos for nuclear safeguards applicaations. Each can easily be expanded as time allows. The first system is for instrument control that accepts voice commands and issues audible operator prompts. The second system is for access control. The speaker's voice is used to verify his identity and to actuate external devices
High-Dimensional Adaptive Particle Swarm Optimization on Heterogeneous Systems
International Nuclear Information System (INIS)
Wachowiak, M P; Sarlo, B B; Foster, A E Lambe
2014-01-01
Much work has recently been reported in parallel GPU-based particle swarm optimization (PSO). Motivated by the encouraging results of these investigations, while also recognizing the limitations of GPU-based methods for big problems using a large amount of data, this paper explores the efficacy of employing other types of parallel hardware for PSO. Most commodity systems feature a variety of architectures whose high-performance capabilities can be exploited. In this paper, high-dimensional problems and those that employ a large amount of external data are explored within the context of heterogeneous systems. Large problems are decomposed into constituent components, and analyses are undertaken of which components would benefit from multi-core or GPU parallelism. The current study therefore provides another demonstration that ''supercomputing on a budget'' is possible when subtasks of large problems are run on hardware most suited to these tasks. Experimental results show that large speedups can be achieved on high dimensional, data-intensive problems. Cost functions must first be analysed for parallelization opportunities, and assigned hardware based on the particular task
Quantum correlation of high dimensional system in a dephasing environment
Ji, Yinghua; Ke, Qiang; Hu, Juju
2018-05-01
For a high dimensional spin-S system embedded in a dephasing environment, we theoretically analyze the time evolutions of quantum correlation and entanglement via Frobenius norm and negativity. The quantum correlation dynamics can be considered as a function of the decoherence parameters, including the ratio between the system oscillator frequency ω0 and the reservoir cutoff frequency ωc , and the different environment temperature. It is shown that the quantum correlation can not only measure nonclassical correlation of the considered system, but also perform a better robustness against the dissipation. In addition, the decoherence presents the non-Markovian features and the quantum correlation freeze phenomenon. The former is much weaker than that in the sub-Ohmic or Ohmic thermal reservoir environment.
An analytical model for an input/output-subsystem
International Nuclear Information System (INIS)
Roemgens, J.
1983-05-01
An input/output-subsystem of one or several computers if formed by the external memory units and the peripheral units of a computer system. For these subsystems mathematical models are established, taking into account the special properties of the I/O-subsystems, in order to avoid planning errors and to allow for predictions of the capacity of such systems. Here an analytical model is presented for the magnetic discs of a I/O-subsystem, using analytical methods for the individual waiting queues or waiting queue networks. Only I/O-subsystems of IBM-computer configurations are considered, which can be controlled by the MVS operating system. After a description of the hardware and software components of these I/O-systems, possible solutions from the literature are presented and discussed with respect to their applicability in IBM-I/O-subsystems. Based on these models a special scheme is developed which combines the advantages of the literature models and avoids the disadvantages in part. (orig./RW) [de
PC-based input/output controllers from a VME perspective
International Nuclear Information System (INIS)
Hill, J.O.
1999-01-01
The Experimental Physics and Industrial Control System (EPICS) has been widely adopted in the accelerator community. Although EPICS is available on many platforms, the majority of sites have deployed VME- or VXI-based input output controllers running the vxWorks real time operating system. Recently, a hybrid approach using vxWorks on both PC and traditional platforms is being implemented at LANL. To illustrate these developments the author compares his recent experience deploying PC-based EPICS input output controllers with experience deploying similar systems based on traditional EPICS platforms
Structural consequences of carbon taxes: An input-output analysis
International Nuclear Information System (INIS)
Che Yuhu.
1992-01-01
A model system is provided for examining for examining the structural consequences of carbon taxes on economic, energy, and environmental issues. The key component is the Iterative Multi-Optimization (IMO) Process model which describes, using an Input-Output (I-O) framework, the feedback between price changes and substitution. The IMO process is designed to assure this feedback process when the input coefficients in an I-O table can be changed while holding the I-O price model. The theoretical problems of convergence to a limit in the iterative process and uniqueness (which requires all IMO processes starting from different initial prices to converge to a unique point for a given level of carbon taxes) are addressed. The empirical analysis also examines the effects of carbon taxes on the US economy as described by a 78 sector I-O model. Findings are compared with those of other models that assess the effects of carbon taxes, and the similarities and differences with them are interpreted in terms of differences in the scope, sectoral detail, time frame, and policy assumptions among the models
A qualitative numerical study of high dimensional dynamical systems
Albers, David James
Since Poincare, the father of modern mathematical dynamical systems, much effort has been exerted to achieve a qualitative understanding of the physical world via a qualitative understanding of the functions we use to model the physical world. In this thesis, we construct a numerical framework suitable for a qualitative, statistical study of dynamical systems using the space of artificial neural networks. We analyze the dynamics along intervals in parameter space, separating the set of neural networks into roughly four regions: the fixed point to the first bifurcation; the route to chaos; the chaotic region; and a transition region between chaos and finite-state neural networks. The study is primarily with respect to high-dimensional dynamical systems. We make the following general conclusions as the dimension of the dynamical system is increased: the probability of the first bifurcation being of type Neimark-Sacker is greater than ninety-percent; the most probable route to chaos is via a cascade of bifurcations of high-period periodic orbits, quasi-periodic orbits, and 2-tori; there exists an interval of parameter space such that hyperbolicity is violated on a countable, Lebesgue measure 0, "increasingly dense" subset; chaos is much more likely to persist with respect to parameter perturbation in the chaotic region of parameter space as the dimension is increased; moreover, as the number of positive Lyapunov exponents is increased, the likelihood that any significant portion of these positive exponents can be perturbed away decreases with increasing dimension. The maximum Kaplan-Yorke dimension and the maximum number of positive Lyapunov exponents increases linearly with dimension. The probability of a dynamical system being chaotic increases exponentially with dimension. The results with respect to the first bifurcation and the route to chaos comment on previous results of Newhouse, Ruelle, Takens, Broer, Chenciner, and Iooss. Moreover, results regarding the high-dimensional
A use-side procedure for estimating trade margins in input-output analysis
Directory of Open Access Journals (Sweden)
Marisa Asensio Pardo
2005-01-01
Full Text Available According to the National Accounting Systems proposed by United Nations (1993 and Eurostat (1996, use and make (or supply matrices should be measured before goods and services are conveyed to the markets (basic values. Actually, the make table is defined in basic values (excluding trade and transport margins and net commodity taxes whereas the use table is in purchasers’ values (including them. In particular, this paper shows how trade margins can be removed from the use table with the purpose of constructing an input-output table. The proposed approach is based on the use-side procedure from the ESA-95 Input-Output Manual (Eurostat, 2002 and is also being applied to the forthcoming 2000 Andalusian Input-Output Framework.
QUALITATIVE DATA AND ERROR MEASUREMENT IN INPUT-OUTPUT-ANALYSIS
NIJKAMP, P; OOSTERHAVEN, J; OUWERSLOOT, H; RIETVELD, P
1992-01-01
This paper is a contribution to the rapidly emerging field of qualitative data analysis in economics. Ordinal data techniques and error measurement in input-output analysis are here combined in order to test the reliability of a low level of measurement and precision of data by means of a stochastic
Crossover Can Be Constructive When Computing Unique Input Output Sequences
DEFF Research Database (Denmark)
Lehre, Per Kristian; Yao, Xin
2010-01-01
Unique input output (UIO) sequences have important applications in conformance testing of finite state machines (FSMs). Previous experimental and theoretical research has shown that evolutionary algorithms (EAs) can compute UIOs efficiently on many FSM instance classes, but fail on others. However...
Economic Input-Output Life Cycle Assessment of Water Reuse Strategies in Residential Buildings
This paper evaluates the environmental sustainability and economic feasibility of four water reuse designs through economic input-output life cycle assessments (EIO-LCA) and benefit/cost analyses. The water reuse designs include: 1. Simple Greywater Reuse System for Landscape Ir...
Statistical mechanics of complex neural systems and high dimensional data
International Nuclear Information System (INIS)
Advani, Madhu; Lahiri, Subhaneil; Ganguli, Surya
2013-01-01
Recent experimental advances in neuroscience have opened new vistas into the immense complexity of neuronal networks. This proliferation of data challenges us on two parallel fronts. First, how can we form adequate theoretical frameworks for understanding how dynamical network processes cooperate across widely disparate spatiotemporal scales to solve important computational problems? Second, how can we extract meaningful models of neuronal systems from high dimensional datasets? To aid in these challenges, we give a pedagogical review of a collection of ideas and theoretical methods arising at the intersection of statistical physics, computer science and neurobiology. We introduce the interrelated replica and cavity methods, which originated in statistical physics as powerful ways to quantitatively analyze large highly heterogeneous systems of many interacting degrees of freedom. We also introduce the closely related notion of message passing in graphical models, which originated in computer science as a distributed algorithm capable of solving large inference and optimization problems involving many coupled variables. We then show how both the statistical physics and computer science perspectives can be applied in a wide diversity of contexts to problems arising in theoretical neuroscience and data analysis. Along the way we discuss spin glasses, learning theory, illusions of structure in noise, random matrices, dimensionality reduction and compressed sensing, all within the unified formalism of the replica method. Moreover, we review recent conceptual connections between message passing in graphical models, and neural computation and learning. Overall, these ideas illustrate how statistical physics and computer science might provide a lens through which we can uncover emergent computational functions buried deep within the dynamical complexities of neuronal networks. (paper)
Enhancing MINIX 3 Input/Output performance using a virtual machine approach
Pessolani, Pablo Andrés; González, César Daniel
2010-01-01
MINIX 3 is an open-source operating system designed to be highly reliable, flexible, and secure. The kernel is extremely small and user processes, specialized servers and device drivers run as user-mode insulated processes. These features, the tiny amount of kernel code, and other aspects greatly enhance system reliability. The drawbacks of running device drivers in usermode are the performance penalties on input/output ports access, kernel data structures access, interrupt indirect manage...
Energy analysis handbook. CAC document 214. [Combining process analysis with input-output analysis
Energy Technology Data Exchange (ETDEWEB)
Bullard, C. W.; Penner, P. S.; Pilati, D. A.
1976-10-01
Methods are presented for calculating the energy required, directly and indirectly, to produce all types of goods and services. Procedures for combining process analysis with input-output analysis are described. This enables the analyst to focus data acquisition cost-effectively, and to achieve a specified degree of accuracy in the results. The report presents sample calculations and provides the tables and charts needed to perform most energy cost calculations, including the cost of systems for producing or conserving energy.
Directory of Open Access Journals (Sweden)
Pei-Luen Patrick Rau
2016-04-01
Full Text Available The development of “smart” residential thermostats—both in terms of wider connectivity and higher intelligence—has revealed great opportunity for energy conservation, as well as providing comfort and convenience. This paper focuses on the interaction design of such a novel system, and analyzed user requirements for input, output, and level of intelligence systematically through both in-depth interviews and a survey.
Modelling Analysis of Forestry Input-Output Elasticity in China
Directory of Open Access Journals (Sweden)
Guofeng Wang
2016-01-01
Full Text Available Based on an extended economic model and space econometrics, this essay analyzed the spatial distributions and interdependent relationships of the production of forestry in China; also the input-output elasticity of forestry production were calculated. Results figure out there exists significant spatial correlation in forestry production in China. Spatial distribution is mainly manifested as spatial agglomeration. The output elasticity of labor force is equal to 0.6649, and that of capital is equal to 0.8412. The contribution of land is significantly negative. Labor and capital are the main determinants for the province-level forestry production in China. Thus, research on the province-level forestry production should not ignore the spatial effect. The policy-making process should take into consideration the effects between provinces on the production of forestry. This study provides some scientific technical support for forestry production.
Directory of Open Access Journals (Sweden)
de Parada, Javier
1964-07-01
Full Text Available Economic development has been the permanent aim of the economic policy of every country. This requires a detailed knowledge of the relationships between the various economic activities, so that available resources can be applied to those activities that will lead to the greatest increase in the total national production, and also to the largest increment in labour vacancies, and exports. This optimum exploitation of available economic resources has been attempted width the introduction of the so called economic development plans. An important instrument in economic planning is the input output analysis. This article gives the basic hypotheses and the theoretical fundamentals underlying this type of analysis. From the latest input output table of Spanish economic activity, a secondary table has been prepared covering the aspects that affect construction most closely, so that the construction industry can also be subjected to this type of analysis. The predetermined variables have been taken to be the state provisions for future subsidies to the housing and road construction industries.Cuando en 1758 el Dr. F. Quesnay, médico de Luis XV, formula su famoso «Tableau Economique», las ideas sobre la interdependencia general de los sectores económicos calaron profundamente en el espíritu de los economistas de la época. La escuela fisiócrata, entonces en boga, consideraba el «dejar obrar» a las leyes naturales como la mejor forma de gobierno. Quesnay intuyó el movimiento natural circulatorio de los bienes económicos, y como fruto de sus investigaciones surgió el celebérrimo «Tableau Economique», que fue aclamado por sus contemporáneos como uno de los más grandes descubrimientos de la Historia.
CONSTRUCTION OF A DYNAMIC INPUT-OUTPUT MODEL WITH A HUMAN CAPITAL BLOCK
Directory of Open Access Journals (Sweden)
Baranov A. O.
2017-03-01
Full Text Available The accumulation of human capital is an important factor of economic growth. It seems to be useful to include «human capital» as a factor of a macroeconomic model, as it helps to take into account the quality differentiation of the workforce. Most of the models usually distinguish labor force by the levels of education, while some of the factors remain unaccounted. Among them are health status and culture development level, which influence productivity level as well as gross product reproduction. Inclusion of the human capital block to the interindustry model can help to make it more reliable for economic development forecasting. The article presents a mathematical description of the extended dynamic input-output model (DIOM with a human capital block. The extended DIOM is based on the Input-Output Model from The KAMIN system (the System of Integrated Analyses of Interindustrial Information developed at the Institute of Economics and Industrial Engineering of the Siberian Branch of the Academy of Sciences of the Russian Federation and at the Novosibirsk State University. The extended input-output model can be used to analyze and forecast development of Russian economy.
Input-output supervisor; Le superviseur d'entree-sortie dans les ordinateurs
Energy Technology Data Exchange (ETDEWEB)
Dupuy, R [Commissariat a l' Energie Atomique, Vaujours (France). Centre d' Etudes Nucleaires
1970-07-01
The input-output supervisor is the program which monitors the flow of informations between core storage and peripheral equipments of a computer. This work is composed of three parts: 1 - Study of a generalized input-output supervisor. With sample modifications it looks like most of input-output supervisors which are running now on computers. 2 - Application of this theory on a magnetic drum. 3 - Hardware requirement for time-sharing. (author) [French] Le superviseur d'entree-sortie est le programme charge de gerer les echanges d'information entre la memoire rapide et les organes peripheriques d'un ordinateur. Ce travail se compose de trois parties: 1 - Etude d'un systeme d'entree-sortie general et theorique qui, en faisant un certain nombre d'hypotheses simplificatrices, permet de retrouver la plupart des superviseurs d'entree-sortie actuels. 2 - Expose d'une realisation concrete, gestion d'un tambour magnetique. 3 - Suggestions hardware en vue de faciliter le timesharing. (auteur)
Input-output supervisor; Le superviseur d'entree-sortie dans les ordinateurs
Energy Technology Data Exchange (ETDEWEB)
Dupuy, R. [Commissariat a l' Energie Atomique, Vaujours (France). Centre d' Etudes Nucleaires
1970-07-01
The input-output supervisor is the program which monitors the flow of informations between core storage and peripheral equipments of a computer. This work is composed of three parts: 1 - Study of a generalized input-output supervisor. With sample modifications it looks like most of input-output supervisors which are running now on computers. 2 - Application of this theory on a magnetic drum. 3 - Hardware requirement for time-sharing. (author) [French] Le superviseur d'entree-sortie est le programme charge de gerer les echanges d'information entre la memoire rapide et les organes peripheriques d'un ordinateur. Ce travail se compose de trois parties: 1 - Etude d'un systeme d'entree-sortie general et theorique qui, en faisant un certain nombre d'hypotheses simplificatrices, permet de retrouver la plupart des superviseurs d'entree-sortie actuels. 2 - Expose d'une realisation concrete, gestion d'un tambour magnetique. 3 - Suggestions hardware en vue de faciliter le timesharing. (auteur)
Fast metabolite identification with Input Output Kernel Regression
Brouard, Céline; Shen, Huibin; Dührkop, Kai; d'Alché-Buc, Florence; Böcker, Sebastian; Rousu, Juho
2016-01-01
Motivation: An important problematic of metabolomics is to identify metabolites using tandem mass spectrometry data. Machine learning methods have been proposed recently to solve this problem by predicting molecular fingerprint vectors and matching these fingerprints against existing molecular structure databases. In this work we propose to address the metabolite identification problem using a structured output prediction approach. This type of approach is not limited to vector output space and can handle structured output space such as the molecule space. Results: We use the Input Output Kernel Regression method to learn the mapping between tandem mass spectra and molecular structures. The principle of this method is to encode the similarities in the input (spectra) space and the similarities in the output (molecule) space using two kernel functions. This method approximates the spectra-molecule mapping in two phases. The first phase corresponds to a regression problem from the input space to the feature space associated to the output kernel. The second phase is a preimage problem, consisting in mapping back the predicted output feature vectors to the molecule space. We show that our approach achieves state-of-the-art accuracy in metabolite identification. Moreover, our method has the advantage of decreasing the running times for the training step and the test step by several orders of magnitude over the preceding methods. Availability and implementation: Contact: celine.brouard@aalto.fi Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307628
The Input-Output Relationship of the Cholinergic Basal Forebrain
Directory of Open Access Journals (Sweden)
Matthew R. Gielow
2017-02-01
Full Text Available Basal forebrain cholinergic neurons influence cortical state, plasticity, learning, and attention. They collectively innervate the entire cerebral cortex, differentially controlling acetylcholine efflux across different cortical areas and timescales. Such control might be achieved by differential inputs driving separable cholinergic outputs, although no input-output relationship on a brain-wide level has ever been demonstrated. Here, we identify input neurons to cholinergic cells projecting to specific cortical regions by infecting cholinergic axon terminals with a monosynaptically restricted viral tracer. This approach revealed several circuit motifs, such as central amygdala neurons synapsing onto basolateral amygdala-projecting cholinergic neurons or strong somatosensory cortical input to motor cortex-projecting cholinergic neurons. The presence of input cells in the parasympathetic midbrain nuclei contacting frontally projecting cholinergic neurons suggest that the network regulating the inner eye muscles are additionally regulating cortical state via acetylcholine efflux. This dataset enables future circuit-level experiments to identify drivers of known cortical cholinergic functions.
International Nuclear Information System (INIS)
Laudillay, Y.
1979-01-01
This I/0 software is composed by the set of modules allowing exchanges of data between computer and process to control. It is developed taking several types of problems into account. Particularly the use of I/0 must be easy for the pedestrian and I/0 system should be able to evolve because the number of parameters can increase or lessen and also, the characteristics of some parameters can change. The respect of these conditions requires some particular solutions. For example, it is preferable for the control process software to be written in high level language and the I/0 software to be accessible in this language. It is important, also that hardware and software intermediate levels for exchanges of data be easy for user writing a program. The other problems, typical of the real time check are determined by use of the computer standard I/0. However some further modules are necessary to obtain a real time I/0 system having satisfying performances [fr
Field-Programmable Logic Devices with Optical Input Output
Szymanski, Ted H.; Saint-Laurent, Martin; Tyan, Victor; Au, Albert; Supmonchai, Boonchuay
2000-02-01
A field-programmable logic device (FPLD) with optical I O is described. FPLD s with optical I O can have their functionality specified in the field by means of downloading a control-bit stream and can be used in a wide range of applications, such as optical signal processing, optical image processing, and optical interconnects. Our device implements six state-of-the-art dynamically programmable logic arrays (PLA s) on a 2 mm 2 mm die. The devices were fabricated through the Lucent Technologies Advanced Research Projects Agency Consortium for Optical and Optoelectronic Technologies in Computing (Lucent ARPA COOP) workshop by use of 0.5- m complementary metal-oxide semiconductor self-electro-optic device technology and were delivered in 1998. All devices are fully functional: The electronic data paths have been verified at 200 MHz, and optical tests are pending. The device has been programmed to implement a two-stage optical switching network with six 4 4 crossbar switches, which can realize more than 190 10 6 unique programmable input output permutations. The same device scaled to a 2 cm 2 cm substrate could support as many as 4000 optical I O and 1 Tbit s of optical I O bandwidth and offer fully programmable digital functionality with approximately 110,000 programmable logic gates. The proposed optoelectronic FPLD is also ideally suited to realizing dense, statically reconfigurable crossbar switches. We describe an attractive application area for such devices: a rearrangeable three-stage optical switch for a wide-area-network backbone, switching 1000 traffic streams at the OC-48 data rate and supporting several terabits of traffic.
Counting and classifying attractors in high dimensional dynamical systems.
Bagley, R J; Glass, L
1996-12-07
Randomly connected Boolean networks have been used as mathematical models of neural, genetic, and immune systems. A key quantity of such networks is the number of basins of attraction in the state space. The number of basins of attraction changes as a function of the size of the network, its connectivity and its transition rules. In discrete networks, a simple count of the number of attractors does not reveal the combinatorial structure of the attractors. These points are illustrated in a reexamination of dynamics in a class of random Boolean networks considered previously by Kauffman. We also consider comparisons between dynamics in discrete networks and continuous analogues. A continuous analogue of a discrete network may have a different number of attractors for many different reasons. Some attractors in discrete networks may be associated with unstable dynamics, and several different attractors in a discrete network may be associated with a single attractor in the continuous case. Special problems in determining attractors in continuous systems arise when there is aperiodic dynamics associated with quasiperiodicity of deterministic chaos.
Alternative to Ritt's pseudodivision for finding the input-output equations of multi-output models.
Meshkat, Nicolette; Anderson, Chris; DiStefano, Joseph J
2012-09-01
Differential algebra approaches to structural identifiability analysis of a dynamic system model in many instances heavily depend upon Ritt's pseudodivision at an early step in analysis. The pseudodivision algorithm is used to find the characteristic set, of which a subset, the input-output equations, is used for identifiability analysis. A simpler algorithm is proposed for this step, using Gröbner Bases, along with a proof of the method that includes a reduced upper bound on derivative requirements. Efficacy of the new algorithm is illustrated with several biosystem model examples. Copyright © 2012 Elsevier Inc. All rights reserved.
Directory of Open Access Journals (Sweden)
Keller Alevtina
2017-01-01
Full Text Available The article considers the issue of allocation of depreciation costs in the dynamic inputoutput model of an industrial enterprise. Accounting the depreciation costs in such a model improves the policy of fixed assets management. It is particularly relevant to develop the algorithm for the allocation of depreciation costs in the construction of dynamic input-output model of an industrial enterprise, since such enterprises have a significant amount of fixed assets. Implementation of terms of the adequacy of such an algorithm itself allows: evaluating the appropriateness of investments in fixed assets, studying the final financial results of an industrial enterprise, depending on management decisions in the depreciation policy. It is necessary to note that the model in question for the enterprise is always degenerate. It is caused by the presence of zero rows in the matrix of capital expenditures by lines of structural elements unable to generate fixed assets (part of the service units, households, corporate consumers. The paper presents the algorithm for the allocation of depreciation costs for the model. This algorithm was developed by the authors and served as the basis for further development of the flowchart for subsequent implementation with use of software. The construction of such algorithm and its use for dynamic input-output models of industrial enterprises is actualized by international acceptance of the effectiveness of the use of input-output models for national and regional economic systems. This is what allows us to consider that the solutions discussed in the article are of interest to economists of various industrial enterprises.
Linear stability theory as an early warning sign for transitions in high dimensional complex systems
International Nuclear Information System (INIS)
Piovani, Duccio; Grujić, Jelena; Jensen, Henrik Jeldtoft
2016-01-01
We analyse in detail a new approach to the monitoring and forecasting of the onset of transitions in high dimensional complex systems by application to the Tangled Nature model of evolutionary ecology and high dimensional replicator systems with a stochastic element. A high dimensional stability matrix is derived in the mean field approximation to the stochastic dynamics. This allows us to determine the stability spectrum about the observed quasi-stable configurations. From overlap of the instantaneous configuration vector of the full stochastic system with the eigenvectors of the unstable directions of the deterministic mean field approximation, we are able to construct a good early-warning indicator of the transitions occurring intermittently. (paper)
Straube, Ronny
2017-12-01
Much of the complexity of regulatory networks derives from the necessity to integrate multiple signals and to avoid malfunction due to cross-talk or harmful perturbations. Hence, one may expect that the input-output behavior of larger networks is not necessarily more complex than that of smaller network motifs which suggests that both can, under certain conditions, be described by similar equations. In this review, we illustrate this approach by discussing the similarities that exist in the steady state descriptions of a simple bimolecular reaction, covalent modification cycles and bacterial two-component systems. Interestingly, in all three systems fundamental input-output characteristics such as thresholds, ultrasensitivity or concentration robustness are described by structurally similar equations. Depending on the system the meaning of the parameters can differ ranging from protein concentrations and affinity constants to complex parameter combinations which allows for a quantitative understanding of signal integration in these systems. We argue that this approach may also be extended to larger regulatory networks. Copyright © 2017 Elsevier B.V. All rights reserved.
International Nuclear Information System (INIS)
Llop, Maria; Pie, Laia
2008-01-01
The aim of this paper is to analyze the economic impact of alternative policies implemented on the energy activities of the Catalan production system. Specifically, we analyze the effects of a tax on intermediate energy uses, a reduction in intermediate energy demand, and a tax on intermediate uses combined with a reduction in intermediate energy demand. The methodology involves two versions of the input-output price model: a competitive price formulation and a mark-up price formulation. The input-output price framework will make it possible to evaluate how the alternative measures modify production prices, consumption prices, private real income, and intermediate energy uses. The empirical application is for the Catalan economy and uses economic data for the year 2001. The combination of a tax on energy uses and an improvement in the energy efficiency of the production system is a measure that accomplishes both economic and environmental goals, since it has no effects on prices, it has a positive effect on private real income and, finally, energy consumption is considerably reduced. (author)
Leontief Input-Output Method for The Fresh Milk Distribution Linkage Analysis
Directory of Open Access Journals (Sweden)
Riski Nur Istiqomah
2016-11-01
Full Text Available This research discusses about linkage analysis and identifies the key sector in the fresh milk distribution using Leontief Input-Output method. This method is one of the application of Mathematics in economy. The current fresh milk distribution system includes dairy farmers →collectors→fresh milk processing industries→processed milk distributors→consumers. Then, the distribution is merged between the collectors’ axctivity and the fresh milk processing industry. The data used are primary and secondary data taken in June 2016 in Kecamatan Jabung Kabupaten Malang. The collected data are then analysed using Leontief Input-Output Matriks and Python (PYIO 2.1 software. The result is that the merging of the collectors’ and the fresh milk processing industry’s activities shows high indices of forward linkages and backward linkages. It is shown that merging of the two activities is the key sector which has an important role in developing the whole activities in the fresh milk distribution.
Controlling chaos in low and high dimensional systems with periodic parametric perturbations
International Nuclear Information System (INIS)
Mirus, K.A.; Sprott, J.C.
1998-06-01
The effect of applying a periodic perturbation to an accessible parameter of various chaotic systems is examined. Numerical results indicate that perturbation frequencies near the natural frequencies of the unstable periodic orbits of the chaotic systems can result in limit cycles for relatively small perturbations. Such perturbations can also control or significantly reduce the dimension of high-dimensional systems. Initial application to the control of fluctuations in a prototypical magnetic fusion plasma device will be reviewed
Towards a global multi-regional environmentally extended input-output database
Tukker, Arnold; Poliakov, Evgueni; Heijungs, Reinout; Hawkins, Troy; Neuwahl, Frederik; Rueda-Cantuche, Jose M.; Giljum, Stefan; Moll, Stephan; Oosterhaven, Jan; Bouwmeester, Maaike
2009-01-01
This paper presents the strategy for a large EU-funded Integrated Project: EXIOPOL ("A New Environmental Accounting Framework Using Externality Data and Input-Output Tools for Policy Analysis"), with special attention for its part in environmentally extended (EE) input-output (IO) analysis. The
Multifunction input-output board for the IBM AT/XT (Lab-Master)
Energy Technology Data Exchange (ETDEWEB)
Pilyar, A V
1996-12-31
Multifunction input-output board for the IBM PC AT/XT is described. It consists of a CMOS analog input multiplexer, programmable amplifier, a fast 12-bit ADC, four 10-bit DAC and two 8-bit digital input-output registers. Specifications of analog input and output are given. 6 refs.
Controlling Access to Input/Output Peripheral Devices
Directory of Open Access Journals (Sweden)
E. Y. Rodionov
2010-03-01
Full Text Available In this paper the author proposes a system that manages information security policy on enterprise. Problems related to managing information security policy on enterprise and access to peripheral devices in computer systems functioning under control of Microsoft Windows NT operating systems are considered.
Input/output routines for a hybrid computer
International Nuclear Information System (INIS)
Izume, Akitada; Yodo, Terutaka; Sakama, Iwao; Sakamoto, Akira; Miyake, Osamu
1976-05-01
This report is concerned with data processing programs for a hybrid computer system. Especially pre-data processing of magnetic tapes which are recorded during the dynamic experiment by FACOM 270/25 data logging system in the 50 MW steam generator test facility is described in detail. The magnetic tape is a most effective recording medium for data logging, but recording formats of the magnetic tape are different between data logging systems. In our section, the final data analyses are performed by data in the disk of EAI-690 hybrid computer system, and to transfer all required information in magnetic tapes to the disk, the magnetic tape editing and data transit are necessary by sub-computer NEAC-3200 system. This report is written for users as a manual and reference hand book of pre-data processing between different type computers. (auth.)
Application Of Input-Output Analysis In The Health Care
Directory of Open Access Journals (Sweden)
Jewczak Maciej
2014-12-01
Full Text Available Usage of the economic analysis in the study of the performance of health care system does not surprise anyone nowadays. Trends that are drawn over the years fluctuate from the technology assessment of health programs - in terms of efficiency, costs or utility for patients, through methods to establishing copayment for health services and the demand for medical services. Much of the interest is devoted to analysis of the shape of the health care system: the amount of contributions to the National Health Fund, the managing the system, both at the micro and macro level, or restructuring. Any method that allows to show dependencies, identify weaknesses/strengths of the health care system is appreciated by health policy makers.
Smart mobility solution with multiple input Output interface.
Sethi, Aartika; Deb, Sujay; Ranjan, Prabhat; Sardar, Arghya
2017-07-01
Smart wheelchairs are commonly used to provide solution for mobility impairment. However their usage is limited primarily due to high cost owing from sensors required for giving input, lack of adaptability for different categories of input and limited functionality. In this paper we propose a smart mobility solution using smartphone with inbuilt sensors (accelerometer, camera and speaker) as an input interface. An Emotiv EPOC+ is also used for motor imagery based input control synced with facial expressions in cases of extreme disability. Apart from traction, additional functions like home security and automation are provided using Internet of Things (IoT) and web interfaces. Although preliminary, our results suggest that this system can be used as an integrated and efficient solution for people suffering from mobility impairment. The results also indicate a decent accuracy is obtained for the overall system.
Specification and Aggregation Errors in Environmentally Extended Input-Output Models
Bouwmeester, Maaike C.; Oosterhaven, Jan
This article considers the specification and aggregation errors that arise from estimating embodied emissions and embodied water use with environmentally extended national input-output (IO) models, instead of with an environmentally extended international IO model. Model specification errors result
Understanding virtual water flows: A multiregion input-output case study of Victoria
Lenzen, Manfred
2009-09-01
This article explains and interprets virtual water flows from the well-established perspective of input-output analysis. Using a case study of the Australian state of Victoria, it demonstrates that input-output analysis can enumerate virtual water flows without systematic and unknown truncation errors, an issue which has been largely absent from the virtual water literature. Whereas a simplified flow analysis from a producer perspective would portray Victoria as a net virtual water importer, enumerating the water embodiments across the full supply chain using input-output analysis shows Victoria as a significant net virtual water exporter. This study has succeeded in informing government policy in Australia, which is an encouraging sign that input-output analysis will be able to contribute much value to other national and international applications.
The economic impacts of Lake States forestry: an input-output study.
Larry Pedersen; Daniel E. Chappelle; David C. Lothner
1989-01-01
The report describes 1985 and 1995 levels of forest-related economic activity in the three-state area of Michigan, Minnesota, and Wisconsin, and their impacts on other economic sectors based on a regional input-output model.
Meshkat, Nicolette; Anderson, Chris; Distefano, Joseph J
2011-09-01
When examining the structural identifiability properties of dynamic system models, some parameters can take on an infinite number of values and yet yield identical input-output data. These parameters and the model are then said to be unidentifiable. Finding identifiable combinations of parameters with which to reparameterize the model provides a means for quantitatively analyzing the model and computing solutions in terms of the combinations. In this paper, we revisit and explore the properties of an algorithm for finding identifiable parameter combinations using Gröbner Bases and prove useful theoretical properties of these parameter combinations. We prove a set of M algebraically independent identifiable parameter combinations can be found using this algorithm and that there exists a unique rational reparameterization of the input-output equations over these parameter combinations. We also demonstrate application of the procedure to a nonlinear biomodel. Copyright © 2011 Elsevier Inc. All rights reserved.
Transport coefficient computation based on input/output reduced order models
Hurst, Joshua L.
The guiding purpose of this thesis is to address the optimal material design problem when the material description is a molecular dynamics model. The end goal is to obtain a simplified and fast model that captures the property of interest such that it can be used in controller design and optimization. The approach is to examine model reduction analysis and methods to capture a specific property of interest, in this case viscosity, or more generally complex modulus or complex viscosity. This property and other transport coefficients are defined by a input/output relationship and this motivates model reduction techniques that are tailored to preserve input/output behavior. In particular Singular Value Decomposition (SVD) based methods are investigated. First simulation methods are identified that are amenable to systems theory analysis. For viscosity, these models are of the Gosling and Lees-Edwards type. They are high order nonlinear Ordinary Differential Equations (ODEs) that employ Periodic Boundary Conditions. Properties can be calculated from the state trajectories of these ODEs. In this research local linear approximations are rigorously derived and special attention is given to potentials that are evaluated with Periodic Boundary Conditions (PBC). For the Gosling description LTI models are developed from state trajectories but are found to have limited success in capturing the system property, even though it is shown that full order LTI models can be well approximated by reduced order LTI models. For the Lees-Edwards SLLOD type model nonlinear ODEs will be approximated by a Linear Time Varying (LTV) model about some nominal trajectory and both balanced truncation and Proper Orthogonal Decomposition (POD) will be used to assess the plausibility of reduced order models to this system description. An immediate application of the derived LTV models is Quasilinearization or Waveform Relaxation. Quasilinearization is a Newton's method applied to the ODE operator
A novel algorithm of artificial immune system for high-dimensional function numerical optimization
Institute of Scientific and Technical Information of China (English)
DU Haifeng; GONG Maoguo; JIAO Licheng; LIU Ruochen
2005-01-01
Based on the clonal selection theory and immune memory theory, a novel artificial immune system algorithm, immune memory clonal programming algorithm (IMCPA), is put forward. Using the theorem of Markov chain, it is proved that IMCPA is convergent. Compared with some other evolutionary programming algorithms (like Breeder genetic algorithm), IMCPA is shown to be an evolutionary strategy capable of solving complex machine learning tasks, like high-dimensional function optimization, which maintains the diversity of the population and avoids prematurity to some extent, and has a higher convergence speed.
Pandemic recovery analysis using the dynamic inoperability input-output model.
Santos, Joost R; Orsi, Mark J; Bond, Erik J
2009-12-01
Economists have long conceptualized and modeled the inherent interdependent relationships among different sectors of the economy. This concept paved the way for input-output modeling, a methodology that accounts for sector interdependencies governing the magnitude and extent of ripple effects due to changes in the economic structure of a region or nation. Recent extensions to input-output modeling have enhanced the model's capabilities to account for the impact of an economic perturbation; two such examples are the inoperability input-output model((1,2)) and the dynamic inoperability input-output model (DIIM).((3)) These models introduced sector inoperability, or the inability to satisfy as-planned production levels, into input-output modeling. While these models provide insights for understanding the impacts of inoperability, there are several aspects of the current formulation that do not account for complexities associated with certain disasters, such as a pandemic. This article proposes further enhancements to the DIIM to account for economic productivity losses resulting primarily from workforce disruptions. A pandemic is a unique disaster because the majority of its direct impacts are workforce related. The article develops a modeling framework to account for workforce inoperability and recovery factors. The proposed workforce-explicit enhancements to the DIIM are demonstrated in a case study to simulate a pandemic scenario in the Commonwealth of Virginia.
The UK waste input-output table: Linking waste generation to the UK economy.
Salemdeeb, Ramy; Al-Tabbaa, Abir; Reynolds, Christian
2016-10-01
In order to achieve a circular economy, there must be a greater understanding of the links between economic activity and waste generation. This study introduces the first version of the UK waste input-output table that could be used to quantify both direct and indirect waste arisings across the supply chain. The proposed waste input-output table features 21 industrial sectors and 34 waste types and is for the 2010 time-period. Using the waste input-output table, the study results quantitatively confirm that sectors with a long supply chain (i.e. manufacturing and services sectors) have higher indirect waste generation rates compared with industrial primary sectors (e.g. mining and quarrying) and sectors with a shorter supply chain (e.g. construction). Results also reveal that the construction, mining and quarrying sectors have the highest waste generation rates, 742 and 694 tonne per £1m of final demand, respectively. Owing to the aggregated format of the first version of the waste input-output, the model does not address the relationship between waste generation and recycling activities. Therefore, an updated version of the waste input-output table is expected be developed considering this issue. Consequently, the expanded model would lead to a better understanding of waste and resource flows in the supply chain. © The Author(s) 2016.
Ghosts in high dimensional non-linear dynamical systems: The example of the hypercycle
International Nuclear Information System (INIS)
Sardanyes, Josep
2009-01-01
Ghost-induced delayed transitions are analyzed in high dimensional non-linear dynamical systems by means of the hypercycle model. The hypercycle is a network of catalytically-coupled self-replicating RNA-like macromolecules, and has been suggested to be involved in the transition from non-living to living matter in the context of earlier prebiotic evolution. It is demonstrated that, in the vicinity of the saddle-node bifurcation for symmetric hypercycles, the persistence time before extinction, T ε , tends to infinity as n→∞ (being n the number of units of the hypercycle), thus suggesting that the increase in the number of hypercycle units involves a longer resilient time before extinction because of the ghost. Furthermore, by means of numerical analysis the dynamics of three large hypercycle networks is also studied, focusing in their extinction dynamics associated to the ghosts. Such networks allow to explore the properties of the ghosts living in high dimensional phase space with n = 5, n = 10 and n = 15 dimensions. These hypercyclic networks, in agreement with other works, are shown to exhibit self-maintained oscillations governed by stable limit cycles. The bifurcation scenarios for these hypercycles are analyzed, as well as the effect of the phase space dimensionality in the delayed transition phenomena and in the scaling properties of the ghosts near bifurcation threshold
Geraci, Joseph; Dharsee, Moyez; Nuin, Paulo; Haslehurst, Alexandria; Koti, Madhuri; Feilotter, Harriet E; Evans, Ken
2014-03-01
We introduce a novel method for visualizing high dimensional data via a discrete dynamical system. This method provides a 2D representation of the relationship between subjects according to a set of variables without geometric projections, transformed axes or principal components. The algorithm exploits a memory-type mechanism inherent in a certain class of discrete dynamical systems collectively referred to as the chaos game that are closely related to iterative function systems. The goal of the algorithm was to create a human readable representation of high dimensional patient data that was capable of detecting unrevealed subclusters of patients from within anticipated classifications. This provides a mechanism to further pursue a more personalized exploration of pathology when used with medical data. For clustering and classification protocols, the dynamical system portion of the algorithm is designed to come after some feature selection filter and before some model evaluation (e.g. clustering accuracy) protocol. In the version given here, a univariate features selection step is performed (in practice more complex feature selection methods are used), a discrete dynamical system is driven by this reduced set of variables (which results in a set of 2D cluster models), these models are evaluated for their accuracy (according to a user-defined binary classification) and finally a visual representation of the top classification models are returned. Thus, in addition to the visualization component, this methodology can be used for both supervised and unsupervised machine learning as the top performing models are returned in the protocol we describe here. Butterfly, the algorithm we introduce and provide working code for, uses a discrete dynamical system to classify high dimensional data and provide a 2D representation of the relationship between subjects. We report results on three datasets (two in the article; one in the appendix) including a public lung cancer
Input-output linearizing tracking control of induction machine with the included magnetic saturation
DEFF Research Database (Denmark)
Dolinar, Drago; Ljusev, Petar; Stumberger, Gorazd
2003-01-01
The tracking control design of an induction motor, based on input-output linearisation with magnetic saturation included is addressed. The magnetic saturation is represented by a nonlinear magnetising curve for the iron core and is used in the control, the observer of the state variables......, and in the load torque estimator. An input-output linearising control is used to achieve better tracking performances. It is based on the mixed 'stator current - rotor flux linkage' induction motor model with magnetic saturation considered in the stationary reference frame. Experimental results show...... that the proposed input-output linearising tracking control with saturation included behaves considerably better than the one without saturation, and that it introduces smaller position and speed errors, and better motor stiffness on account of the increased computational complexity....
Impact of magnetic saturation on the input-output linearising tracking control of an induction motor
DEFF Research Database (Denmark)
Dolinar, Drago; Ljusev, Petar; Stumberger, Gorazd
2004-01-01
This paper deals with the tracking control design of an induction motor, based on input-output linearization with magnetic saturation included. Magnetic saturation is represented by the nonlinear magnetizing curve of the iron core and is used in the control design, the observer of state variables......, and in the load torque estimator. An input-output linearising control is used to achieve better tracking performances of the drive. It is based on the mixed ”stator current - rotor flux linkage” induction motor model with magnetic saturation considered in the stationary reference frame. Experimental results show...... that the proposed input-output linearising tracking control with the included saturation behaves considerably better than the one without saturation, and that it introduces smaller position and speed errors, and better motor stiffness on account of the increased computational complexity....
Input-output tables and analyses 2000. Imports, employment and environment
International Nuclear Information System (INIS)
2002-05-01
The publication is primarily designed as a practical reference quide presenting data and in particular analytical results (impact multipliers) on the structural characteristics and developments of the Danish economy. Also readers who are not familiar with the theoretical aspects of input-output analysis may benefit from the contents. In the different chapters of the publication a comprehensive treatment of the basic data material is given together with figures primarily for the year 1998, which is the most recent year for which final national accounts and input-output tables are available. This part is followed by the multipliers, some of which have also been 'forecasted' to the year 2000. The publication presents data for each industrial sector and the household sector in Denmark. It presents data for input-output analyses, environmental accounts, production, employment, energy consumption, and emission of pollutants. (LN)
Input-output model for MACCS nuclear accident impacts estimation¹
Energy Technology Data Exchange (ETDEWEB)
Outkin, Alexander V. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bixler, Nathan E. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Vargas, Vanessa N [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2015-01-27
Since the original economic model for MACCS was developed, better quality economic data (as well as the tools to gather and process it) and better computational capabilities have become available. The update of the economic impacts component of the MACCS legacy model will provide improved estimates of business disruptions through the use of Input-Output based economic impact estimation. This paper presents an updated MACCS model, bases on Input-Output methodology, in which economic impacts are calculated using the Regional Economic Accounting analysis tool (REAcct) created at Sandia National Laboratories. This new GDP-based model allows quick and consistent estimation of gross domestic product (GDP) losses due to nuclear power plant accidents. This paper outlines the steps taken to combine the REAcct Input-Output-based model with the MACCS code, describes the GDP loss calculation, and discusses the parameters and modeling assumptions necessary for the estimation of long-term effects of nuclear power plant accidents.
Forecasting the Romanian sectoral economy using the input-output method
Directory of Open Access Journals (Sweden)
Liliana DUGULEANĂ
2017-07-01
Full Text Available The purpose of this paper is to forecast the sectoral output in 2013 based on the input-output structure of Romanian economy in 2010. Considering that the economic linkage mechanisms do not easily change during certain time periods, the forecasting is possible, even if not in the sequence of the time passing. Using the technical matrix of the sectoral structure described for year 2010 and some known indicators of the economic sectors, as the value added for each sector in 2013, the sectoral output is projected for 2013. The Romanian GDP in 2013 is estimated based on the input-output model. From a managerial perspective, this study is useful to forecast the sectoral output and to understand the sectoral behaviour, based on the input-output analysis of the value added, the compensation for employees and the final demand, which were considered here.
International Nuclear Information System (INIS)
Cloutier, L.M.; DeBresson, C.; Dietzenbacher, E.
2004-01-01
This book presents the recent work of prominent economists who used the latest input-output analysis techniques to examine complex and interdependent problems such as global warming, climate change and greenhouse gas reduction. It proposes solutions to Solow's Paradox regarding information and communication technologies and examines the role of technological and financial flows. It also proposes theoretical applications for use in Quebec and Canada. The work of young economists who participated at the Leontief International Input-Output Association was also presented. The book is mainly intended for analysts of economic policies and for young researchers looking for advanced input-output analysis techniques. It offers a useful, realistic and systematic analysis of various issues facing contemporary companies. refs., tabs., figs
Wang, Zhiping; Chen, Jinyu; Yu, Benli
2017-02-20
We investigate the two-dimensional (2D) and three-dimensional (3D) atom localization behaviors via spontaneously generated coherence in a microwave-driven four-level atomic system. Owing to the space-dependent atom-field interaction, it is found that the detecting probability and precision of 2D and 3D atom localization behaviors can be significantly improved via adjusting the system parameters, the phase, amplitude, and initial population distribution. Interestingly, the atom can be localized in volumes that are substantially smaller than a cubic optical wavelength. Our scheme opens a promising way to achieve high-precision and high-efficiency atom localization, which provides some potential applications in high-dimensional atom nanolithography.
Characterizing the Input-Output Function of the Olfactory-Limbic Pathway in the Guinea Pig
Directory of Open Access Journals (Sweden)
Gian Luca Breschi
2015-01-01
Full Text Available Nowadays the neuroscientific community is taking more and more advantage of the continuous interaction between engineers and computational neuroscientists in order to develop neuroprostheses aimed at replacing damaged brain areas with artificial devices. To this end, a technological effort is required to develop neural network models which can be fed with the recorded electrophysiological patterns to yield the correct brain stimulation to recover the desired functions. In this paper we present a machine learning approach to derive the input-output function of the olfactory-limbic pathway in the in vitro whole brain of guinea pig, less complex and more controllable than an in vivo system. We first experimentally characterized the neuronal pathway by delivering different sets of electrical stimuli from the lateral olfactory tract (LOT and by recording the corresponding responses in the lateral entorhinal cortex (l-ERC. As a second step, we used information theory to evaluate how much information output features carry about the input. Finally we used the acquired data to learn the LOT-l-ERC “I/O function,” by means of the kernel regularized least squares method, able to predict l-ERC responses on the basis of LOT stimulation features. Our modeling approach can be further exploited for brain prostheses applications.
International trade inoperability input-output model (IT-IIM): theory and application.
Jung, Jeesang; Santos, Joost R; Haimes, Yacov Y
2009-01-01
The inoperability input-output model (IIM) has been used for analyzing disruptions due to man-made or natural disasters that can adversely affect the operation of economic systems or critical infrastructures. Taking economic perturbation for each sector as inputs, the IIM provides the degree of economic production impacts on all industry sectors as the outputs for the model. The current version of the IIM does not provide a separate analysis for the international trade component of the inoperability. If an important port of entry (e.g., Port of Los Angeles) is disrupted, then international trade inoperability becomes a highly relevant subject for analysis. To complement the current IIM, this article develops the International Trade-IIM (IT-IIM). The IT-IIM investigates the resulting international trade inoperability for all industry sectors resulting from disruptions to a major port of entry. Similar to traditional IIM analysis, the inoperability metrics that the IT-IIM provides can be used to prioritize economic sectors based on the losses they could potentially incur. The IT-IIM is used to analyze two types of direct perturbations: (1) the reduced capacity of ports of entry, including harbors and airports (e.g., a shutdown of any port of entry); and (2) restrictions on commercial goods that foreign countries trade with the base nation (e.g., embargo).
Numerical simulation of waveguide input/output couplers for a planar mm-wave linac cavity
International Nuclear Information System (INIS)
Kang, Y.W.
1994-01-01
A double-sided planar mm-wave linear accelerating cavity structure has been studied. The input/output couplers for the accelerating cavity structure have been designed using the Hewlett-Packard High Frequency Structure Simulator (HFSS). The program is a frequency domain finite element 3-D field solver and can include matched port boundary conditions. The power transmission property of the structure is calculated in the frequency domain. The dimensions of the, coupling cavities and the irises at the input/output ports are adjusted to have the structure matched to rectangular waveguides. The field distributions in the accelerating structure for the 2π/3-mode traveling wave are shown
High dimensional model representation method for fuzzy structural dynamics
Adhikari, S.; Chowdhury, R.; Friswell, M. I.
2011-03-01
Uncertainty propagation in multi-parameter complex structures possess significant computational challenges. This paper investigates the possibility of using the High Dimensional Model Representation (HDMR) approach when uncertain system parameters are modeled using fuzzy variables. In particular, the application of HDMR is proposed for fuzzy finite element analysis of linear dynamical systems. The HDMR expansion is an efficient formulation for high-dimensional mapping in complex systems if the higher order variable correlations are weak, thereby permitting the input-output relationship behavior to be captured by the terms of low-order. The computational effort to determine the expansion functions using the α-cut method scales polynomically with the number of variables rather than exponentially. This logic is based on the fundamental assumption underlying the HDMR representation that only low-order correlations among the input variables are likely to have significant impacts upon the outputs for most high-dimensional complex systems. The proposed method is first illustrated for multi-parameter nonlinear mathematical test functions with fuzzy variables. The method is then integrated with a commercial finite element software (ADINA). Modal analysis of a simplified aircraft wing with fuzzy parameters has been used to illustrate the generality of the proposed approach. In the numerical examples, triangular membership functions have been used and the results have been validated against direct Monte Carlo simulations. It is shown that using the proposed HDMR approach, the number of finite element function calls can be reduced without significantly compromising the accuracy.
Analysing global value chains using input-output economics : proceed with care
Nomaler, Z.O.; Verspagen, B.
2014-01-01
Input-output economics has become a popular tool to analyse the international fragmentation of value chains, especially now that several multi-regional tables that cover large parts of the global economy have become available. It has been argued that these tables, when analysed with the help of the
Analysing global value chains using input-output economics: Proceed with care
Nomaler, Ö.; Verspagen, B.
2014-01-01
Input-output economics has become a popular tool to analyse the international fragmentation of value chains, especially now that several multi-regional tables that cover large parts of the global economy have become available. It has been argued that these tables, when analysed with the help of the
Input-output and energy demand models for Ireland: Data collection report. Part 1: EXPLOR
Energy Technology Data Exchange (ETDEWEB)
Henry, E W; Scott, S
1981-01-01
Data are presented in support of EXPLOR, an input-output economic model for Ireland. The data follow the listing of exogenous data-sets used by Batelle in document X11/515/77. Data are given for 1974, 1980, and 1985 and consist of household consumption, final demand-production, and commodity prices. (ACR)
Approaches and Tools Used to Teach the Computer Input/Output Subsystem: A Survey
Larraza-Mendiluze, Edurne; Garay-Vitoria, Nestor
2015-01-01
This paper surveys how the computer input/output (I/O) subsystem is taught in introductory undergraduate courses. It is important to study the educational process of the computer I/O subsystem because, in the curricula recommendations, it is considered a core topic in the area of knowledge of computer architecture and organization (CAO). It is…
Deflation of input-output tables from the user's point of view : a heuristic approach
Dietzenbacher, Erik; Hoen, A.R.
This paper considers the problem of deflating an input-output table from the viewpoint of the user. In many practical cases certain margins of this table are readily available in constant prices, whereas the entire table is not. This reduces the problem to estimating the matrix of sectoral
From LCC to LCA Using a Hybrid Input Output Model – A Maritime Case Study
DEFF Research Database (Denmark)
Kjær, Louise Laumann; Pagoropoulos, Aris; Hauschild, Michael Zwicky
2015-01-01
As companies try to embrace life cycle thinking, Life Cycle Assessment (LCA) and Life Cycle Costing (LCC) have proven to be powerful tools. In this paper, an Environmental Input-Output model is used for analysis as it enables an LCA using the same economic input data as LCC. This approach helps...
Zhang, Qiantao; Larkin, Charles; Lucey, Brian M.
2017-01-01
While there has been a long history of modelling the economic impact of higher education institutions (HEIs), little research has been undertaken in the context of Ireland. This paper provides, for the first time, a disaggregated input-output table for Ireland's higher education sector. The picture painted overall is a higher education sector that…
Economic and environmental impacts of dietary changes in Iran : an input-output analysis
Rahmani, R.; Bakhshoodeh, M.; Zibaei, M.; Heijman, W.J.M.; Eftekhari, M.H.
2012-01-01
Iran's simple and environmentally extended commodity by commodity input-output (IO) model was used to determine the impacts of dietary changes on the Iranian economy and on the environmental load. The original model is based on the status-quo diet and was modified to include the World Health
Regional disaster impact analysis: comparing Input-Output and Computable General Equilibrium models
Koks, E.E.; Carrera, L.; Jonkeren, O.; Aerts, J.C.J.H.; Husby, T.G.; Thissen, M.; Standardi, G.; Mysiak, J.
2016-01-01
A variety of models have been applied to assess the economic losses of disasters, of which the most common ones are input-output (IO) and computable general equilibrium (CGE) models. In addition, an increasing number of scholars have developed hybrid approaches: one that combines both or either of
Input-Output model for waste management plan for Nigeria | Njoku ...
African Journals Online (AJOL)
An Input-Output Model for Waste Management Plan has been developed for Nigeria based on Leontief concept and life cycle analysis. Waste was considered as source of pollution, loss of resources, and emission of green house gasses from bio-chemical treatment and decomposition, with negative impact on the ...
ANALYSIS OF THE BANDUNG CHANGES EXCELLENT POTENTIAL THROUGH INPUT-OUTPUT MODEL USING INDEX LE MASNE
Directory of Open Access Journals (Sweden)
Teti Sofia Yanti
2017-03-01
Full Text Available Input-Output Table is arranged to present an overview of the interrelationships and interdependence between units of activity (sector production in the whole economy. Therefore the input-output models are complete and comprehensive analytical tool. The usefulness of input-output tables is an analysis of the economic structure of the national/regional level which covers the structure of production and value-added (GDP of each sector. For the purposes of planning and evaluation of the outcomes of development that is comprehensive both national and smaller scale (district/city, a model for regional development planning approach can use the model input-output analysis. Analysis of Bandung Economic Structure did use Le Masne index, by comparing the coefficients of the technology in 2003 and 2008, of which nearly 50% change. The trade sector has grown very conspicuous than other areas, followed by the services of road transport and air transport services, the development priorities and investment Bandung should be directed to these areas, this is due to these areas can be thrust and be power attraction for the growth of other areas. The areas that experienced the highest decrease was Industrial Chemicals and Goods from Chemistry, followed by Oil and Refinery Industry Textile Industry Except For Garment.
DIMITRI 1.0: Beschrijving en toepassing van een dynamisch input-output model
Wilting HC; Blom WF; Thomas R; Idenburg AM; LAE
2001-01-01
DIMITRI, the Dynamic Input-Output Model to study the Impacts of Technology Related Innovations, was developed in the framework of the RIVM Environment and Economy project to answer questions about interrelationships between economy, technology and the environment. DIMITRI, a meso-economic model,
An improved robust model predictive control for linear parameter-varying input-output models
Abbas, H.S.; Hanema, J.; Tóth, R.; Mohammadpour, J.; Meskin, N.
2018-01-01
This paper describes a new robust model predictive control (MPC) scheme to control the discrete-time linear parameter-varying input-output models subject to input and output constraints. Closed-loop asymptotic stability is guaranteed by including a quadratic terminal cost and an ellipsoidal terminal
The economic impact of multifunctional agriculture in Dutch regions: An input-output model
Heringa, P.W.; Heide, van der C.M.; Heijman, W.J.M.
2013-01-01
Multifunctional agriculture is a broad concept lacking a precise definition. Moreover, little is known about the societal importance of multifunctional agriculture. This paper is an empirical attempt to fill this gap. To this end, an input-output model was constructed for multifunctional agriculture
The economic impact of multifunctional agriculture in The Netherlands: A regional input-output model
Heringa, P.W.; Heide, van der C.M.; Heijman, W.J.M.
2012-01-01
Multifunctional agriculture is a broad concept lacking a precise and uniform definition. Moreover, little is known about the societal importance of multifunctional agriculture. This paper is an empirical attempt to fill this gap. To this end, an input-output model is constructed for multifunctional
Ittersum, van M.K.; Rabbinge, R.
1997-01-01
Definitions and concepts of production ecology are presented as a basis for development of alternative production technologies characterized by their input-output combinations. With these concepts the relative importance of several growth factors and inputs is investigated to explain actual yield
Statistics & Input-Output Measures for School Libraries in Colorado, 2002.
Colorado State Library, Denver.
This document presents statistics and input-output measures for K-12 school libraries in Colorado for 2002. Data are presented by type and size of school, i.e., high schools (six categories ranging from 2,000 and over to under 300), junior high/middle schools (five categories ranging from 1,000-1,999 to under 300), elementary schools (four…
An input-output energy analysis in pistachio nut production: A case ...
African Journals Online (AJOL)
This research examined the energy use pattern and energy input/output analysis of pistachio nut widely grown in the South-eastern Anatolia, Turkey. For this purpose, data from pistachio nut production were collected in 61 farms from ten villages by a questionnaire which was selected according to their regional properties.
Logistics flows and enterprise input-output models: aggregate and disaggregate analysis
Albino, V.; Yazan, Devrim; Messeni Petruzzelli, A.; Okogbaa, O.G.
2011-01-01
In the present paper, we propose the use of enterprise input-output (EIO) models to describe and analyse the logistics flows considering spatial issues and related environmental effects associated with production and transportation processes. In particular, transportation is modelled as a specific
Ma, Xunjun; Lu, Yang; Wang, Fengjiao
2017-09-01
This paper presents the recent advances in reduction of multifrequency noise inside helicopter cabin using an active structural acoustic control system, which is based on active gearbox struts technical approach. To attenuate the multifrequency gearbox vibrations and resulting noise, a new scheme of discrete model predictive sliding mode control has been proposed based on controlled auto-regressive moving average model. Its implementation only needs input/output data, hence a broader frequency range of controlled system is modelled and the burden on the state observer design is released. Furthermore, a new iteration form of the algorithm is designed, improving the developing efficiency and run speed. To verify the algorithm's effectiveness and self-adaptability, experiments of real-time active control are performed on a newly developed helicopter model system. The helicopter model can generate gear meshing vibration/noise similar to a real helicopter with specially designed gearbox and active struts. The algorithm's control abilities are sufficiently checked by single-input single-output and multiple-input multiple-output experiments via different feedback strategies progressively: (1) control gear meshing noise through attenuating vibrations at the key points on the transmission path, (2) directly control the gear meshing noise in the cabin using the actuators. Results confirm that the active control system is practical for cancelling multifrequency helicopter interior noise, which also weakens the frequency-modulation of the tones. For many cases, the attenuations of the measured noise exceed the level of 15 dB, with maximum reduction reaching 31 dB. Also, the control process is demonstrated to be smoother and faster.
Xing, Lizhi; Dong, Xianlei; Guan, Jun
2017-04-01
Input-output table is very comprehensive and detailed in describing the national economic system with lots of economic relationships, which contains supply and demand information among industrial sectors. The complex network, a theory and method for measuring the structure of complex system, can describe the structural characteristics of the internal structure of the research object by measuring the structural indicators of the social and economic system, revealing the complex relationship between the inner hierarchy and the external economic function. This paper builds up GIVCN-WIOT models based on World Input-Output Database in order to depict the topological structure of Global Value Chain (GVC), and assumes the competitive advantage of nations is equal to the overall performance of its domestic sectors' impact on the GVC. Under the perspective of econophysics, Global Industrial Impact Coefficient (GIIC) is proposed to measure the national competitiveness in gaining information superiority and intermediate interests. Analysis of GIVCN-WIOT models yields several insights including the following: (1) sectors with higher Random Walk Centrality contribute more to transmitting value streams within the global economic system; (2) Half-Value Ratio can be used to measure robustness of open-economy macroeconomics in the process of globalization; (3) the positive correlation between GIIC and GDP indicates that one country's global industrial impact could reveal its international competitive advantage.
Demand-driven water withdrawals by Chinese industry: a multi-regional input-output analysis
Zhang, Bo; Chen, Z. M.; Zeng, L.; Qiao, H.; Chen, B.
2016-03-01
With ever increasing water demands and the continuous intensification of water scarcity arising from China's industrialization, the country is struggling to harmonize its industrial development and water supply. This paper presents a systems analysis of water withdrawals by Chinese industry and investigates demand-driven industrial water uses embodied in final demand and interregional trade based on a multi-regional input-output model. In 2007, the Electric Power, Steam, and Hot Water Production and Supply sector ranks first in direct industrial water withdrawal (DWW), and Construction has the largest embodied industrial water use (EWU). Investment, consumption, and exports contribute to 34.6%, 33.3%, and 30.6% of the national total EWU, respectively. Specifically, 58.0%, 51.1%, 48.6%, 43.3%, and 37.5% of the regional EWUs respectively in Guangdong, Shanghai, Zhejiang, Jiangsu, and Fujian are attributed to international exports. The total interregional import/export of embodied water is equivalent to about 40% of the national total DWW, of which 55.5% is associated with the DWWs of Electric Power, Steam, and Hot Water Production and Supply. Jiangsu is the biggest interregional exporter and deficit receiver of embodied water, in contrast to Guangdong as the biggest interregional importer and surplus receiver. Without implementing effective water-saving measures and adjusting industrial structures, the regional imbalance between water availability and water demand tends to intensify considering the water impact of domestic trade of industrial products. Steps taken to improve water use efficiency in production, and to enhance embodied water saving in consumption are both of great significance for supporting China's water policies.
Embodied water analysis for Hebei Province, China by input-output modelling
Liu, Siyuan; Han, Mengyao; Wu, Xudong; Wu, Xiaofang; Li, Zhi; Xia, Xiaohua; Ji, Xi
2018-03-01
With the accelerating coordinated development of the Beijing-Tianjin-Hebei region, regional economic integration is recognized as a national strategy. As water scarcity places Hebei Province in a dilemma, it is of critical importance for Hebei Province to balance water resources as well as make full use of its unique advantages in the transition to sustainable development. To our knowledge, related embodied water accounting analysis has been conducted for Beijing and Tianjin, while similar works with the focus on Hebei are not found. In this paper, using the most complete and recent statistics available for Hebei Province, the embodied water use in Hebei Province is analyzed in detail. Based on input-output analysis, it presents a complete set of systems accounting framework for water resources. In addition, a database of embodied water intensity is proposed which is applicable to both intermediate inputs and final demand. The result suggests that the total amount of embodied water in final demand is 10.62 billion m3, of which the water embodied in urban household consumption accounts for more than half. As a net embodied water importer, the water embodied in the commodity trade in Hebei Province is 17.20 billion m3. The outcome of this work implies that it is particularly urgent to adjust industrial structure and trade policies for water conservation, to upgrade technology and to improve water utilization. As a result, to relieve water shortages in Hebei Province, it is of crucial importance to regulate the balance of water use within the province, thus balancing water distribution in the various industrial sectors.
Santos, Joost R; May, Larissa; Haimar, Amine El
2013-09-01
Outbreaks of contagious diseases underscore the ever-looming threat of new epidemics. Compared to other disasters that inflict physical damage to infrastructure systems, epidemics can have more devastating and prolonged impacts on the population. This article investigates the interdependent economic and productivity risks resulting from epidemic-induced workforce absenteeism. In particular, we develop a dynamic input-output model capable of generating sector-disaggregated economic losses based on different magnitudes of workforce disruptions. An ex post analysis of the 2009 H1N1 pandemic in the national capital region (NCR) reveals the distribution of consequences across different economic sectors. Consequences are categorized into two metrics: (i) economic loss, which measures the magnitude of monetary losses incurred in each sector, and (ii) inoperability, which measures the normalized monetary losses incurred in each sector relative to the total economic output of that sector. For a simulated mild pandemic scenario in NCR, two distinct rankings are generated using the economic loss and inoperability metrics. Results indicate that the majority of the critical sectors ranked according to the economic loss metric comprise of sectors that contribute the most to the NCR's gross domestic product (e.g., federal government enterprises). In contrast, the majority of the critical sectors generated by the inoperability metric include sectors that are involved with epidemic management (e.g., hospitals). Hence, prioritizing sectors for recovery necessitates consideration of the balance between economic loss, inoperability, and other objectives. Although applied specifically to the NCR, the proposed methodology can be customized for other regions. © 2012 Society for Risk Analysis.
Solid wastes integrated management in Rio de Janeiro: input-output analysis
International Nuclear Information System (INIS)
Pimenteira, C.A.P.; Carpio, L.G.T.; Rosa, L.P.; Tolmansquim, M.T.
2005-01-01
This paper analyzes the socioeconomic aspects of solid waste management in Rio de Janeiro. An 'input-output' methodology was used to examine how the secondary product resulting from recycling is re-introduced into the productive process. A comparative profile was developed from the state of recycling and the various other aspects of solid waste management, both from the perspective of its economic feasibility and from the social aspects involved. This was done analyzing the greenhouse gas emissions and the decreased energy consumption. The effects of re-introducing recycled raw materials into the matrix and the ensuing reduction of the demand for virgin raw materials was based on the input-output matrix for the State of Rio de Janeiro. This paper also analyzes the energy savings obtained from recycling and measures the avoided emissions of greenhouse gases
Quantum-optical input-output relations for dispersive and lossy multilayer dielectric plates
International Nuclear Information System (INIS)
Gruner, T.; Welsch, D.
1996-01-01
Using the Green-function approach to the problem of quantization of the phenomenological Maxwell theory, the propagation of quantized radiation through dispersive and absorptive multilayer dielectric plates is studied. Input-output relations are derived, with special emphasis on the determination of the quantum noise generators associated with the absorption of radiation inside the dielectric matter. The input-output relations are used to express arbitrary correlation functions of the outgoing field in terms of correlation functions of the incoming field and those of the noise generators. To illustrate the theory, photons at dielectric tunneling barriers are considered. It is shown that inclusion in the calculations of losses in the photonic band gaps may substantially change the barrier traversal times. copyright 1996 The American Physical Society
EPICS Input/Output Controller (IOC) application developer's guide. APS Release 3.12
International Nuclear Information System (INIS)
Kraimer, M.R.
1994-11-01
This document describes the core software that resides in an Input/Output Controller (IOC), one of the major components of EPICS. The basic components are: (OPI) Operator Interface; this is a UNIX based workstation which can run various EPICS tools; (IOC) Input/Output Controller; this is a VME/VXI based chassis containing a Motorola 68xxx processor, various I/O modules, and VME modules that provide access to other I/O buses such as GPIB, (LAN), Local Area Network; and this is the communication network which allows the IOCs and OPIs to communicate. Epics provides a software component, Channel Access, which provides network transparent communication between a Channel Access client and an arbitrary number of Channel Access servers
International Nuclear Information System (INIS)
Ukidwe, Nandan U.; Bakshi, Bhavik R.
2007-01-01
This paper develops a thermodynamic input-output (TIO) model of the 1997 United States economy that accounts for the flow of cumulative exergy in the 488-sector benchmark economic input-output model in two different ways. Industrial cumulative exergy consumption (ICEC) captures the exergy of all natural resources consumed directly and indirectly by each economic sector, while ecological cumulative exergy consumption (ECEC) also accounts for the exergy consumed in ecological systems for producing each natural resource. Information about exergy consumed in nature is obtained from the thermodynamics of biogeochemical cycles. As used in this work, ECEC is analogous to the concept of emergy, but does not rely on any of its controversial claims. The TIO model can also account for emissions from each sector and their impact and the role of labor. The use of consistent exergetic units permits the combination of various streams to define aggregate metrics that may provide insight into aspects related to the impact of economic sectors on the environment. Accounting for the contribution of natural capital by ECEC has been claimed to permit better representation of the quality of ecosystem goods and services than ICEC. The results of this work are expected to permit evaluation of these claims. If validated, this work is expected to lay the foundation for thermodynamic life cycle assessment, particularly of emerging technologies and with limited information
International Nuclear Information System (INIS)
Liu, Xiuli; Moreno, Blanca; García, Ana Salomé
2016-01-01
A combined forecast of Grey forecasting method and neural network back propagation model, which is called Grey Neural Network and Input-Output Combined Forecasting Model (GNF-IO model), is proposed. A real case of energy consumption forecast is used to validate the effectiveness of the proposed model. The GNF-IO model predicts coal, crude oil, natural gas, renewable and nuclear primary energy consumption volumes by Spain's 36 sub-sectors from 2010 to 2015 according to three different GDP growth scenarios (optimistic, baseline and pessimistic). Model test shows that the proposed model has higher simulation and forecasting accuracy on energy consumption than Grey models separately and other combination methods. The forecasts indicate that the primary energies as coal, crude oil and natural gas will represent on average the 83.6% percent of the total of primary energy consumption, raising concerns about security of supply and energy cost and adding risk for some industrial production processes. Thus, Spanish industry must speed up its transition to an energy-efficiency economy, achieving a cost reduction and increase in the level of self-supply. - Highlights: • Forecasting System Using Grey Models combined with Input-Output Models is proposed. • Primary energy consumption in Spain is used to validate the model. • The grey-based combined model has good forecasting performance. • Natural gas will represent the majority of the total of primary energy consumption. • Concerns about security of supply, energy cost and industry competitiveness are raised.
Using Economic Input/Output Tables to Predict a Country's Nuclear Status
International Nuclear Information System (INIS)
Weimar, Mark R.; Daly, Don S.; Wood, Thomas W.
2010-01-01
Both nuclear power and nuclear weapons programs should have (related) economic signatures which are detectible at some scale. We evaluated this premise in a series of studies using national economic input/output (IO) data. Statistical discrimination models using economic IO tables predict with a high probability whether a country with an unknown predilection for nuclear weapons proliferation is in fact engaged in nuclear power development or nuclear weapons proliferation. We analyzed 93 IO tables, spanning the years 1993 to 2005 for 37 countries that are either members or associates of the Organization for Economic Cooperation and Development (OECD). The 2009 OECD input/output tables featured 48 industrial sectors based on International Standard Industrial Classification (ISIC) Revision 3, and described the respective economies in current country-of-origin valued currency. We converted and transformed these reported values to US 2005 dollars using appropriate exchange rates and implicit price deflators, and addressed discrepancies in reported industrial sectors across tables. We then classified countries with Random Forest using either the adjusted or industry-normalized values. Random Forest, a classification tree technique, separates and categorizes countries using a very small, select subset of the 2304 individual cells in the IO table. A nation's efforts in nuclear power, be it for electricity or nuclear weapons, are an enterprise with a large economic footprint -- an effort so large that it should discernibly perturb coarse country-level economics data such as that found in yearly input-output economic tables. The neoclassical economic input-output model describes a country's or region's economy in terms of the requirements of industries to produce the current level of economic output. An IO table row shows the distribution of an industry's output to the industrial sectors while a table column shows the input required of each industrial sector by a given
Low-carbon building assessment and multi-scale input-output analysis
Chen, G. Q.; Chen, H.; Chen, Z. M.; Zhang, Bo; Shao, L.; Guo, S.; Zhou, S. Y.; Jiang, M. M.
2011-01-01
Presented as a low-carbon building evaluation framework in this paper are detailed carbon emission account procedures for the life cycle of buildings in terms of nine stages as building construction, fitment, outdoor facility construction, transportation, operation, waste treatment, property management, demolition, and disposal for buildings, supported by integrated carbon intensity databases based on multi-scale input-output analysis, essential for low-carbon planning, procurement and supply chain design, and logistics management.
Input/Output of ab-initio nuclear structure calculations for improved performance and portability
International Nuclear Information System (INIS)
Laghave, Nikhil
2010-01-01
Many modern scientific applications rely on highly computation intensive calculations. However, most applications do not concentrate as much on the role that input/output operations can play for improved performance and portability. Parallelizing input/output operations of large files can significantly improve the performance of parallel applications where sequential I/O is a bottleneck. A proper choice of I/O library also offers a scope for making input/output operations portable across different architectures. Thus, use of parallel I/O libraries for organizing I/O of large data files offers great scope in improving performance and portability of applications. In particular, sequential I/O has been identified as a bottleneck for the highly scalable MFDn (Many Fermion Dynamics for nuclear structure) code performing ab-initio nuclear structure calculations. We develop interfaces and parallel I/O procedures to use a well-known parallel I/O library in MFDn. As a result, we gain efficient I/O of large datasets along with their portability and ease of use in the down-stream processing. Even situations where the amount of data to be written is not huge, proper use of input/output operations can boost the performance of scientific applications. Application checkpointing offers enormous performance improvement and flexibility by doing a negligible amount of I/O to disk. Checkpointing saves and resumes application state in such a manner that in most cases the application is unaware that there has been an interruption to its execution. This helps in saving large amount of work that has been previously done and continue application execution. This small amount of I/O provides substantial time saving by offering restart/resume capability to applications. The need for checkpointing in optimization code NEWUOA has been identified and checkpoint/restart capability has been implemented in NEWUOA by using simple file I/O.
The Canadian Defence Input-Output Model DIO Version 4.41
2011-09-01
Request to develop DND tailored Input/Output Model. Electronic communication from AllenWeldon to Team Leader, Defence Economics Team onMarch 12, 2011...and similar contain- ers 166 1440 Handbags, wallets and similar personal articles such as eyeglass and cigar cases and coin purses 167 1450 Cotton yarn...408 3600 Radar and radio navigation equipment 409 3619 Semi-conductors 410 3621 Printed circuits 411 3622 Integrated circuits 412 3623 Other electronic
Economic structure and pollution intensity within the environmental input-output framework
Energy Technology Data Exchange (ETDEWEB)
Llop, Maria [Departament d' Economia, Universitat Rovira i Virgili, Avgda. Universitat no. 1, 43204 Reus (Spain)]. E-mail: maria.llop@urv.cat
2007-06-15
The environmental input-output approach reveals the channels through which the environmental burdens of production activities are transmitted throughout the economy. This paper uses the input-output framework and analyses the changes in Spanish emission multipliers during the period 1995-2000. By decomposing the total changes in multipliers into different components, it is possible to evaluate separately the effects of economic structure and pollution intensity captured by the environmental input-output model. Specifically, in this study, we distinguish between the effects on multipliers caused by changes in emission coefficients (the pollution intensity effects) and the effects on multipliers caused by changes in technical coefficients (the economic structure effects). Our results show a significant reduction in the pollution intensity of production activities, which contributed negatively to changes in emission multipliers. They also show that the economic structure contributed positively to changes in emission multipliers. Together, these two effects lead to a small reduction in multipliers during the period of analysis. My results also show significant differences in the individual behaviour of different sectors in terms of their contribution to multiplier changes. Since there are considerable differences in the way individual sectors affect the changes in emission levels, and in the intensity of these effects, this means that the final effects will basically depend on the activity considered.
Economic structure and pollution intensity within the environmental input-output framework
International Nuclear Information System (INIS)
Llop, Maria
2007-01-01
The environmental input-output approach reveals the channels through which the environmental burdens of production activities are transmitted throughout the economy. This paper uses the input-output framework and analyses the changes in Spanish emission multipliers during the period 1995-2000. By decomposing the total changes in multipliers into different components, it is possible to evaluate separately the effects of economic structure and pollution intensity captured by the environmental input-output model. Specifically, in this study, we distinguish between the effects on multipliers caused by changes in emission coefficients (the pollution intensity effects) and the effects on multipliers caused by changes in technical coefficients (the economic structure effects). Our results show a significant reduction in the pollution intensity of production activities, which contributed negatively to changes in emission multipliers. They also show that the economic structure contributed positively to changes in emission multipliers. Together, these two effects lead to a small reduction in multipliers during the period of analysis. My results also show significant differences in the individual behaviour of different sectors in terms of their contribution to multiplier changes. Since there are considerable differences in the way individual sectors affect the changes in emission levels, and in the intensity of these effects, this means that the final effects will basically depend on the activity considered
From water use to water scarcity footprinting in environmentally extended input-output analysis.
Ridoutt, Bradley George; Hadjikakou, Michalis; Nolan, Martin; Bryan, Brett A
2018-05-18
Environmentally extended input-output analysis (EEIOA) supports environmental policy by quantifying how demand for goods and services leads to resource use and emissions across the economy. However, some types of resource use and emissions require spatially-explicit impact assessment for meaningful interpretation, which is not possible in conventional EEIOA. For example, water use in locations of scarcity and abundance is not environmentally equivalent. Opportunities for spatially-explicit impact assessment in conventional EEIOA are limited because official input-output tables tend to be produced at the scale of political units which are not usually well aligned with environmentally relevant spatial units. In this study, spatially-explicit water scarcity factors and a spatially disaggregated Australian water use account were used to develop water scarcity extensions that were coupled with a multi-regional input-output model (MRIO). The results link demand for agricultural commodities to the problem of water scarcity in Australia and globally. Important differences were observed between the water use and water scarcity footprint results, as well as the relative importance of direct and indirect water use, with significant implications for sustainable production and consumption-related policies. The approach presented here is suggested as a feasible general approach for incorporating spatially-explicit impact assessment in EEIOA.
Modeling the short-run effect of fiscal stimuli on GDP : A new semi-closed input-output model
Chen, Quanrun; Dietzenbacher, Erik; Los, Bart; Yang, Cuihong
In this study, we propose a new semi-closed input-output model, which reconciles input-output analysis with modern consumption theories. It can simulate changes in household consumption behavior when exogenous stimulus policies lead to higher disposable income levels. It is useful for quantifying
Modeling the short-run effect of fiscal stimuli on GDP : A new semi-closed input-output model
Chen, Quanrun; Dietzenbacher, Erik; Los, Bart; Yang, Cuihong
2016-01-01
In this study, we propose a new semi-closed input-output model, which reconciles input-output analysis with modern consumption theories. It can simulate changes in household consumption behavior when exogenous stimulus policies lead to higher disposable income levels. It is useful for quantifying
Las redes sociales como herramienta de análisis estructural input-output.
Directory of Open Access Journals (Sweden)
García Muñiz, Ana Salomé
2003-06-01
Full Text Available Uno de los aspectos fundamentales que posibilita el conocimiento en profundidad de una economía es la realización de un análisis de su estructura productiva. Dicho análisis supone una importante ayuda no sólo en la toma de decisiones de política económica, sino también constituye un requisito indispensable y previo a las tareas de predicción necesarias en un contexto empresarial.El estudio de una economía puede abordarse desde muy diversas ópticas, una de las cuales es el enfoque input-output, el cual permite analizar conjuntamente las relaciones intersectoriales de una economía y su demanda agregada, con lo cual se dispone de un conocimiento integrado de la actividad económica. Consideramos la teoría de redes como una importante “herramienta”, a nuestro juicio poco explotada en el ámbito económico, que constituye un marco general de estudio dentro del cual podemos encuadrar el análisis input-output. Esta teoría permite simplificar el esquema de relaciones surgido entre los sectores de una economía y, por lo tanto, favorecer la comprensión del mismo. El objetivo del presente trabajo es analizar las relaciones interindustriales bajo la óptica de la teoría de las redes sociales y, al mismo tiempo, efectuar una comparación entre los resultados así obtenidos y los que se derivan de la aplicación de los métodos input-output clásicos.
Runtime analysis of the (1+1) EA on computing unique input output sequences
DEFF Research Database (Denmark)
Lehre, Per Kristian; Yao, Xin
2010-01-01
Computing unique input output (UIO) sequences is a fundamental and hard problem in conformance testing of finite state machines (FSM). Previous experimental research has shown that evolutionary algorithms (EAs) can be applied successfully to find UIOs for some FSMs. However, before EAs can...... in the theoretical analysis, and the variability of the runtime. The numerical results fit well with the theoretical results, even for small problem instance sizes. Together, these results provide a first theoretical characterisation of the potential and limitations of the (1 + 1) EA on the problem of computing UIOs....
Priority economic sector and household income in Indonesia (an analysis of input output)
Subanti, S.; Mulyanto; Hakim, A. R.; Mafruhah, I.; Hakim, I. M.
2018-03-01
This purpose of study aims to identify the roles of priority economic sectors on household incomes in Indonesia. Analyse in this paper used nine economic sectors, that representing result of classification from input output table. This study found that (1) priority economic sector are manufacturing sector & trade hotel and restaurant; (2) sector that have looking forward orientation included agriculture, mining & quarrying, and financial ownership & business services; and (3) electricity, gas, and water supply sector give the biggest impact to household income in Indonesia. The suggestion that policies aimed at increasing productivity and raising skills while encouraging individual participation in the formal labour market are essential.
¿Cómo transformar los modelos input-output para calcular multiplicadores netos?
Directory of Open Access Journals (Sweden)
Pereira López, Xesús
2015-11-01
Full Text Available The aim of this paper is to calculate net input-output multipliers using different adjustments on the Leontief inverse, without simply removing part of its elements. Moreover, in order to increase the accuracy of the estimation, a standardization of the inverse is offered. The empirical application is presented for the Galician economy, based on the year 2011. A comparison between the proposed extended methodology and the traditional I-O techniques is shown, throughout the results obtained in the estimation of the backward and forward sectoral linkages. With this new approach, some of the conventional key sectors will not appear as such, like the case of the construction sector.
International Nuclear Information System (INIS)
Lenzen, M.
1998-01-01
Input-output modeling of primary energy and greenhouse gas embodiments in goods and services is a useful technique for designing greenhouse gas abatement policies. The present paper describes direct and indirect primary energy and greenhouse gas requirements for a given set of Australian final consumption. It considers sectoral disparities in energy prices, capital formation and international trade flows and it accounts for embodiments in the Gross National Expenditure as well as the Gross Domestic Product. Primary energy and greenhouse gas intensities in terms of MJ/$ and kg CO 2 -e/$ are reported, as well as national balance of primary energy consumption and greenhouse gas emissions. (author)
'Key' sectors in final energy consumption: an input-output application to the Spanish case
International Nuclear Information System (INIS)
Alcantara, Vicent; Padilla, Emilio
2003-01-01
In this paper we analyze the determination of 'key' sectors in the final energy consumption. We approach this issue from an input-output perspective and we design a methodology based on the elasticities of the demands of final energy consumption. As an exercise, we apply the proposed methodology to the Spanish economy. The analysis allows us to indicate the greater or lesser relevance of the different sectors in the consumption of final energy, pointing out which sectors deserve greater attention in the Spanish case and showing the implications for energy policy
Input-output model of regional environmental and economic impacts of nuclear power plants
International Nuclear Information System (INIS)
Johnson, M.H.; Bennett, J.T.
1979-01-01
The costs of delayed licensing of nuclear power plants calls for a more-comprehensive method of quantifying the economic and environmental impacts on a region. A traditional input-output (I-O) analysis approach is extended to assess the effects of changes in output, income, employment, pollution, water consumption, and the costs and revenues of local government disaggregated among 23 industry sectors during the construction and operating phases. Unlike earlier studies, this model uses nonlinear environmental interactions and specifies environmental feedbacks to the economic sector. 20 references
Trade in value added in the West Pacific: An input-output analysis
Nakamura, Yoichi
2015-01-01
The evolution of trade between the four regions in the West Pacific in both gross and value added terms is analyzed using international input-output tables. It is found that value added exports of computers and electronic equipment of the Asian economies are very limited in comparison with their gross exports, and that the largest shares of value added exports were accounted for by the services sectors in every region, particularly so in Japan and the US. Surpluses and deficits in bilateral t...
Data-driven forecasting of high-dimensional chaotic systems with long short-term memory networks.
Vlachas, Pantelis R; Byeon, Wonmin; Wan, Zhong Y; Sapsis, Themistoklis P; Koumoutsakos, Petros
2018-05-01
We introduce a data-driven forecasting method for high-dimensional chaotic systems using long short-term memory (LSTM) recurrent neural networks. The proposed LSTM neural networks perform inference of high-dimensional dynamical systems in their reduced order space and are shown to be an effective set of nonlinear approximators of their attractor. We demonstrate the forecasting performance of the LSTM and compare it with Gaussian processes (GPs) in time series obtained from the Lorenz 96 system, the Kuramoto-Sivashinsky equation and a prototype climate model. The LSTM networks outperform the GPs in short-term forecasting accuracy in all applications considered. A hybrid architecture, extending the LSTM with a mean stochastic model (MSM-LSTM), is proposed to ensure convergence to the invariant measure. This novel hybrid method is fully data-driven and extends the forecasting capabilities of LSTM networks.
Energy prices and the post oil/energy crisis Brazilian inflation: an input-output study
Energy Technology Data Exchange (ETDEWEB)
Lara-Resende, M.deM.
1982-01-01
This study is an attempt to understand the implications of the OPEC-induced severalfold increase in the international price of oil for average and sectoral domestic prices in Brazil, a large oil-importing open developing economy. Rather than using a Keynesian model (focusing on the universal characteristics of an economy), the study makes use of an open-price input-output model (capturing the structural characteristics of the Brazilian economy). The first three chapters, descriptive in nature, place in perspective the following three, which detail the model and the empirical results. The main conclusion is that, despite the significant increase observed in the post-crisis period, the relative percentage contribution of primary energy to wholesale inflation in Brazil is still relatively minor. A conservative estimate suggests that, in the years of substantial acceleration (1974 and 1979), approximately 15% of the wholesale inflation was due to energy (basically crude oil and oil derivatives). Though such low estimates are partly due to the limitations and assumptions underlying input-output analysis, it seems that the acceleration of inflation is related to more than cost increases originating in energy prices. It also seems to be related to agricultural and labor prices, as well as to the government's decision to abruptly and inopportunely raise several important product prices.
The Input-output Status and Farmers’Willingness to Choose Ecological Operation of Hickory
Institute of Scientific and Technical Information of China (English)
LIU Qiang; LI Shi-yong; WU Wei-guang
2012-01-01
This study takes Lin’an City which early carries out the experiment of ecological operation of hickory as the study site.On the basis of the input-output data on hickory and farmers’ land,we analyze the input-output status of hickory land which practises ecological operation,the operators’ willingness to accept ecological operation and the influencing factors.The results show that in the short term,ecological operation of hickory will have a certain negative impact on the economic benefits;within the experimental area,the degree of operators’ willingness to accept ecological operation of hickory is high,and the operators have a clear understanding of long-term comprehensive benefits which may be brought by ecological operation;the ecological experiment and demonstration of hickory have achieved certain results;family income level,characteristics of householders,education and training,and so on,are the main factors that affect the operators’ willingness to choose ecological operation.Finally,for how to further improve the promotion efficiency of ecological operation of hickory,we put forth some constructive recommendations.
IMPORT COMPONENTS AND IMPORT MULTIPLIERS IN INDONESIAN ECONOMY: WORLD INPUT-OUTPUT ANALYSIS
Directory of Open Access Journals (Sweden)
Muchdie Muchdie
2018-03-01
Full Text Available This paper calculates, presents and discusses on import components and the impact of final demand change on Indonesian imports using Indonesian 36 sector input-output tables of years: 2000, 2005, 2010 and 2014 from World Input-Output Tables. The results showed that firstly, Indonesian import components of input were, on average, more than 20 percent; meaning that input that locally provided were less than 80 percent. Secondly, Indonesian import of input had increased significantly from US$ 36,011 million in 2000 to US$ 151,505 million in 2014. Thirdly, Indonesian imports have been dominated by Sector-3: Manufacture of food products, beverages and tobacco products, Sector-4: Manufacture of textiles, wearing apparel and leather products, Sector-24: Construction, Sector-25: Wholesale and retail trade and repair, and Sector-26: Transportation and post services. Fourthly, by country of origin, Indonesian imports have been dominated by Japan, Korea, the USA, Australia, and China. Imports from Australia, Japan, and the US have been decreased significantly, but import from China has steadily increased. Finally, highest sectoral import multipliers occurred if final demands change in Sector-1: Crop and animal production, forestry, fishing and aquaculture, Sector-2: Mining and quarrying, Sector-23: Water collection; sewerage; waste collection, treatment and disposal activities, and Sector-30: Real estate activities, but there was no significant difference of import multipliers for country origin of import.
Snapshot Views of the Romanian Economy on Regional Level Using Input-Output Methodology
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BORÓKA-JÚLIA BÍRÓ
2014-06-01
Full Text Available Our present paper proposes to give snapshot views on the status-quo of the Romanian economy at the level of development regions. From a methodological perspective, the study is based on the construction of an aggregated national Input-Output table from the more detailed one of the National Institute of Statistics, followed by the derivation of regional tables using the non-survey GRIT technique. Quantitative sectoral interrelationships are going to be analysed based on multipliers, backward and forward linkages in order to identify key sectors within regional economies. This could serve as a baseline for assessing the impact of several policies of the European Union on the Romanian economy, such as the Cohesion Policy and the Common Agricultural Policy. The lower territorial approach – i.e. the construction of regional Input-Output models – used within the present study is in accordance with the European Union’s NUTS2 level policy design and planning philosophy on the one hand. On the other hand, this analytic direction makes possible the use of the results as a base for regional economic development strategy design, highlighting structural specificities and discrepancies among regions of the same country.
A Water-Withdrawal Input-Output Model of the Indian Economy.
Bogra, Shelly; Bakshi, Bhavik R; Mathur, Ritu
2016-02-02
Managing freshwater allocation for a highly populated and growing economy like India can benefit from knowledge about the effect of economic activities. This study transforms the 2003-2004 economic input-output (IO) table of India into a water withdrawal input-output model to quantify direct and indirect flows. This unique model is based on a comprehensive database compiled from diverse public sources, and estimates direct and indirect water withdrawal of all economic sectors. It distinguishes between green (rainfall), blue (surface and ground), and scarce groundwater. Results indicate that the total direct water withdrawal is nearly 3052 billion cubic meter (BCM) and 96% of this is used in agriculture sectors with the contribution of direct green water being about 1145 BCM, excluding forestry. Apart from 727 BCM direct blue water withdrawal for agricultural, other significant users include "Electricity" with 64 BCM, "Water supply" with 44 BCM and other industrial sectors with nearly 14 BCM. "Construction", "miscellaneous food products"; "Hotels and restaurants"; "Paper, paper products, and newsprint" are other significant indirect withdrawers. The net virtual water import is found to be insignificant compared to direct water used in agriculture nationally, while scarce ground water associated with crops is largely contributed by northern states.
Impact of the Smart City Industry on the Korean National Economy: Input-Output Analysis
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Kyunam Kim
2016-07-01
Full Text Available The characteristics of the smart city industry and its effects on the national economy of Korea are investigated using input-output analysis. The definition and industrial classification of a smart city are established using the Delphi technique for experts in various fields, from information and communication technologies (ICT to governmental policies for urban matters. The results of the analysis, including the production, value added and employment induction effects, show that the smart city industry has intermediate characteristics between ICT and urban construction industries, indicating that acquisition of the competitive edge of both the ICT and construction industries is the key to the success of the smart city industry. The crucial industries related to the smart city industry are identified based on an analysis of the forward and backward linkage effects, the results of which suggest the importance of the relevant service industries. The economic effects on the national economy induced by the governmental program for smart city demonstration are estimated using input-output analysis results. Overall, the results of this study indicate that facilitation of the smart city industry plays a key role not only in the sustainable city, but also in the growth of the national economy.
Input-output analysis in fertilizers sector. A case study of Turkey
International Nuclear Information System (INIS)
Karkacier, O.; Guelse, H.S.; Sayili, M.; Akca, H.
1999-01-01
The types of structural analysis in the input-output model known are forward and backwards ties. Fertilizer sector is tied forwardly agriculture, agri-business, chemistry, petro-chemistry and glass sector. In addition, it tied backwardly mining, chemistry, petro-chemistry, electricity, gas, water and transportation. The effect of backward tie of fertilizer sector is more important than its effect of the forward ties. In this study, by means of the year of 1979, 1985 and 1990 input-output table of Turkey the own situation of fertilizer industry and the production relation with other sectors of the economy have been tired to explain with forward and backwards ties. According to the result of the research it was determined that in 1990, (u j ) input coefficient of fertilizer sector is 69 %. That is, 69 percent of the product of fertilizer sector was used as an intermediate goods by other sectors. Therefore, 31 percent of goods produced by fertilizer sector was consumed as a final good. In addition, in this year, (w i ) intermediate use coefficient of fertilizer sector is 52 %. (w i ) intermediate use coefficient of fertilizer sector decreased from 1973 to 1990, as a result of this final use coefficient (1-w i ) increased. Refs. 5 (author)
Input-output analysis of CO2 emissions embodied in trade. The effects of spatial aggregation
International Nuclear Information System (INIS)
Su, Bin; Ang, B.W.
2010-01-01
Energy-related CO 2 emissions embodied in international trade have been widely studied by researchers using the environmental input-output analysis framework. It is well known that both sector aggregation and spatial aggregation affect the results obtained in such studies. With regard to the latter, past studies are often conducted at the national level irrespective of country or economy size. For a large economy with the needed data, studies may be conducted at different levels of spatial aggregation. We examine this problem analytically by extending the work of Su et al. ([Su, B., Huang, H.C., Ang, B.W., Zhou, P., 2010. Input-output analysis of CO 2 emissions embodied in trade: The effects of sector aggregation. Energy Economics 32 (1), 166-175.]) on sector aggregation. We present a numerical example using the data of China and by dividing the country into eight regions. It is found that the results are highly dependent on spatial aggregation. Our study shows that for a large country like China it is meaningful to look into the effect of spatial aggregation. (author)
Environmental impact assessment including indirect effects--a case study using input-output analysis
International Nuclear Information System (INIS)
Lenzen, Manfred; Murray, Shauna A.; Korte, Britta; Dey, Christopher J.
2003-01-01
Environmental impact assessment (EIA) is a process covered by several international standards, dictating that as many environmental aspects as possible should be identified in a project appraisal. While the ISO 14011 standard stipulates a broad-ranging study, off-site, indirect impacts are not specifically required for an Environmental Impact Statement (EIS). The reasons for this may relate to the perceived difficulty of measuring off-site impacts, or the assumption that these are a relatively insignificant component of the total impact. In this work, we describe a method that uses input-output analysis to calculate the indirect effects of a development proposal in terms of several indicator variables. The results of our case study of a Second Sydney Airport show that the total impacts are considerably higher than the on-site impacts for the indicators land disturbance, greenhouse gas emissions, water use, emissions of NO x and SO 2 , and employment. We conclude that employing input-output analysis enhances conventional EIA, as it allows for national and international effects to be taken into account in the decision-making process
Multiregional input-output model for the evaluation of Spanish water flows.
Cazcarro, Ignacio; Duarte, Rosa; Sánchez Chóliz, Julio
2013-01-01
We construct a multiregional input-output model for Spain, in order to evaluate the pressures on the water resources, virtual water flows, and water footprints of the regions, and the water impact of trade relationships within Spain and abroad. The study is framed with those interregional input-output models constructed to study water flows and impacts of regions in China, Australia, Mexico, or the UK. To build our database, we reconcile regional IO tables, national and regional accountancy of Spain, trade and water data. Results show an important imbalance between origin of water resources and final destination, with significant water pressures in the South, Mediterranean, and some central regions. The most populated and dynamic regions of Madrid and Barcelona are important drivers of water consumption in Spain. Main virtual water exporters are the South and Central agrarian regions: Andalusia, Castile-La Mancha, Castile-Leon, Aragon, and Extremadura, while the main virtual water importers are the industrialized regions of Madrid, Basque country, and the Mediterranean coast. The paper shows the different location of direct and indirect consumers of water in Spain and how the economic trade and consumption pattern of certain areas has significant impacts on the availability of water resources in other different and often drier regions.
Directory of Open Access Journals (Sweden)
Janković Marko
2013-01-01
Full Text Available In this paper, we analyze the possibilities of the diagnosis of Parkinson's disease at an early stage, based on characteristics of the input-output curve. The input-output (IO curve was analyzed in two ways: we analyzed the gain of the curve for low-level transcranial stimulation and we analyzed the overall 'quality' of the IO curve. The 'quality' of the curve calculation is based on basic concepts from quantum mechanics and calculation of Tsallis entropy.
ProMC: Input-output data format for HEP applications using varint encoding
Chekanov, S. V.; May, E.; Strand, K.; Van Gemmeren, P.
2014-10-01
A new data format for Monte Carlo (MC) events, or any structural data, including experimental data, is discussed. The format is designed to store data in a compact binary form using variable-size integer encoding as implemented in the Google's Protocol Buffers package. This approach is implemented in the PROMC library which produces smaller file sizes for MC records compared to the existing input-output libraries used in high-energy physics (HEP). Other important features of the proposed format are a separation of abstract data layouts from concrete programming implementations, self-description and random access. Data stored in PROMC files can be written, read and manipulated in a number of programming languages, such C++, JAVA, FORTRAN and PYTHON.
Application of a Linear Input/Output Model to Tankless Water Heaters
Energy Technology Data Exchange (ETDEWEB)
Butcher T.; Schoenbauer, B.
2011-12-31
In this study, the applicability of a linear input/output model to gas-fired, tankless water heaters has been evaluated. This simple model assumes that the relationship between input and output, averaged over both active draw and idle periods, is linear. This approach is being applied to boilers in other studies and offers the potential to make a small number of simple measurements to obtain the model parameters. These parameters can then be used to predict performance under complex load patterns. Both condensing and non-condensing water heaters have been tested under a very wide range of load conditions. It is shown that this approach can be used to reproduce performance metrics, such as the energy factor, and can be used to evaluate the impacts of alternative draw patterns and conditions.
Input-output analysis of high-speed axisymmetric isothermal jet noise
Jeun, Jinah; Nichols, Joseph W.; Jovanović, Mihailo R.
2016-04-01
We use input-output analysis to predict and understand the aeroacoustics of high-speed isothermal turbulent jets. We consider axisymmetric linear perturbations about Reynolds-averaged Navier-Stokes solutions of ideally expanded turbulent jets with jet Mach numbers 0.6 parabolized stability equations (PSE), and this mode dominates the response. For subsonic jets, however, the singular values indicate that the contributions of sub-optimal modes to noise generation are nearly equal to that of the optimal mode, explaining why the PSE do not fully capture the far-field sound in this case. Furthermore, high-fidelity large eddy simulation (LES) is used to assess the prevalence of sub-optimal modes in the unsteady data. By projecting LES source term data onto input modes and the LES acoustic far-field onto output modes, we demonstrate that sub-optimal modes of both types are physically relevant.
Input-output analysis of high-speed turbulent jet noise
Jeun, Jinah; Nichols, Joseph W.
2015-11-01
We apply input-output analysis to predict and understand the aeroacoustics of high-speed isothermal turbulent jets. We consider axisymmetric linear perturbations about Reynolds-averaged Navier-Stokes solutions of ideally expanded turbulent jets with Mach numbers 0 . 6 parabolized stability equations (PSE), and this mode dominates the response. For subsonic jets, however, the singular values indicate that the contributions of suboptimal modes to noise generation are nearly equal to that of the optimal mode, explaining why PSE misses some of the farfield sound in this case. Finally, high-fidelity large eddy simulation (LES) is used to assess the prevalence of suboptimal modes in the unsteady data. By projecting LES data onto the corresponding input modes, the weighted gain of each mode is examined.
Tourism and Economic Development in Romania: Input-Output Analysis Perspective
Directory of Open Access Journals (Sweden)
MARIUS SURUGIU
2010-12-01
Full Text Available Tourism provides a lot of opportunities for sustainable economic development. At local level, by its triggering effect it could represent a factor of economic recovery, by putting to good use the local material and human potential. By its position of predominantly final-branch, tourism exercises to a large impact on national economy by the vector of final demand, for which the possible and/or desirable variant for the future is an economic-social demand that must be satisfied by variants of total output. Using the input-output model (IO model a comparison was made of the matrix of direct technical coefficients (aij and the one of the total requirement coefficients (bij with the assistance of which the direct and propagated effects were determined for this activity by the indicators defining the dimensions of national economy.
Input-output analysis of CO2 emissions embodied in trade. The effects of sector aggregation
International Nuclear Information System (INIS)
Su, Bin; Huang, H.C.; Ang, B.W.; Zhou, P.
2010-01-01
Energy-related CO 2 emissions embodied in international trade have been widely studied by researchers using the input-output analysis framework. These studies are often conducted at a specific level of sector aggregation and the choice made to a large extent is dictated by economic and energy data availability. We investigate analytically the possible effects of sector aggregation on the study results. We conduct empirical studies using the data of China and Singapore where energy-related CO 2 emissions embodied in their exports are estimated at different levels of sector aggregation. A finding from the studies is that levels around 40 sectors appear to be sufficient to capture the overall share of emissions embodied in a country's exports. Another finding is that in approximating the 'ideal' situation the hybrid data treatment approach produces better results than the uniformly distributed data treatment approach. Other findings and some recommendations are also presented. (author)
Relating the environmental impact of consumption to household expenditures. An input-output analysis
International Nuclear Information System (INIS)
Kerkhof, Annemarie C.; Nonhebel, Sanderine; Moll, Henri C.
2009-01-01
In this paper we evaluate the relationships between household expenditures and the environmental impact categories climate change, acidification, eutrophication and smog formation, by combining household expenditures with environmentally extended input-output analysis. Expenditure elasticities are examined with regression analysis, and are compared and interpreted on the basis of insight at the product level. With data from the Netherlands in the year 2000, we find that environmental impact increases with increasing household expenditures, although the degree to which the environmental impact increases differs per impact category. Climate change and eutrophication increase less than proportionally with increasing expenditures. Acidification increases nearly proportionally with increasing expenditures, whereas smog formation increases more than proportionally. It appears that the mix of necessities and luxuries to which an environmental impact is related is essential in explaining the relationship. (author)
Use of microinterrupts to provide an instrument oriented input/output structure
International Nuclear Information System (INIS)
Zaky, S.G.
1981-01-01
This paper describes the design of a bit-slice based computer, which has been developed for use in data acquisition and control applications. The main design goals have been to provide fast response to external events, and sufficient processing capability to perform data reduction in real time. The initial application of this computer has been in airborne, geophysical surveying, where such instruments as Gamma-ray spectrometers, magnetometers and navigation equipment are involved. In order to meet the response requirement mentioned above, a microinterrupt facility has been incorporated. Microinterrupts are serviced in microcodes routines which can be initiated within a maximum of two microinstruction cycle times from an external event. This facility makes it possible to implement powerful input/output control functions without the need for complex and specialized hardware interfaces for each instrument. (orig.)
Torque ripple reduction of brushless DC motor based on adaptive input-output feedback linearization.
Shirvani Boroujeni, M; Markadeh, G R Arab; Soltani, J
2017-09-01
Torque ripple reduction of Brushless DC Motors (BLDCs) is an interesting subject in variable speed AC drives. In this paper at first, a mathematical expression for torque ripple harmonics is obtained. Then for a non-ideal BLDC motor with known harmonic contents of back-EMF, calculation of desired reference current amplitudes, which are required to eliminate some selected harmonics of torque ripple, are reviewed. In order to inject the reference harmonic currents to the motor windings, an Adaptive Input-Output Feedback Linearization (AIOFBL) control is proposed, which generates the reference voltages for three phases voltage source inverter in stationary reference frame. Experimental results are presented to show the capability and validity of the proposed control method and are compared with the vector control in Multi-Reference Frame (MRF) and Pseudo-Vector Control (P-VC) method results. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
The change of CO2 emission on manufacturing sectors in Indonesia: An input-output analysis
Putranti, Titi Muswati; Imansyah, Muhammad Handry
2017-12-01
The objective of this paper is to evaluate the change of CO2 emission on manufacturing sectors in Indonesia using input-output analysis. The method used supply perspective can measure the impact of an increase in the value added of different productive on manufacturing sectors on total CO2 emission and can identify the productive sectors responsible for the increase in CO2 emission when there is an increase in the value added of the economy. The data used are based on Input-Output Energy Table 1990, 1995 and 2010. The method applied the elasticity of CO2 emission to value added. Using the elasticity approach, one can identify the highest elasticity on manufacturing sector as the change of value added provides high response to CO2 emission. Therefore, policy maker can concentrate on manufacturing sectors with the high response of CO2 emission due to the increase of value added. The approach shows the contribution of the various sectors that deserve more consideration for mitigation policy. Five of highest elasticity of manufacturing sectors of CO2 emission are Spinning & Weaving, Other foods, Tobacco, Wearing apparel, and other fabricated textiles products in 1990. Meanwhile, the most sensitive sectors Petroleum refinery products, Other chemical products, Timber & Wooden Products, Iron & Steel Products and Other non-metallic mineral products in 1995. Two sectors of the 1990 were still in the big ten, i.e. Spinning & weaving and Other foods in 1995 for the most sensitive sectors. The six sectors of 1995 in the ten highest elasticity of CO2 emission on manufacturing which were Plastic products, Other chemical products,Other fabricated metal products, Cement, Iron & steel products, Iron & steel, still existed in 2010 condition. The result of this research shows that there is a change in the most elastic CO2 emission of manufacturing sectors which tends from simple and light manufacturing to be a more complex and heavier manufacturing. Consequently, CO2 emission jumped
Input-output relation and energy efficiency in the neuron with different spike threshold dynamics.
Yi, Guo-Sheng; Wang, Jiang; Tsang, Kai-Ming; Wei, Xi-Le; Deng, Bin
2015-01-01
Neuron encodes and transmits information through generating sequences of output spikes, which is a high energy-consuming process. The spike is initiated when membrane depolarization reaches a threshold voltage. In many neurons, threshold is dynamic and depends on the rate of membrane depolarization (dV/dt) preceding a spike. Identifying the metabolic energy involved in neural coding and their relationship to threshold dynamic is critical to understanding neuronal function and evolution. Here, we use a modified Morris-Lecar model to investigate neuronal input-output property and energy efficiency associated with different spike threshold dynamics. We find that the neurons with dynamic threshold sensitive to dV/dt generate discontinuous frequency-current curve and type II phase response curve (PRC) through Hopf bifurcation, and weak noise could prohibit spiking when bifurcation just occurs. The threshold that is insensitive to dV/dt, instead, results in a continuous frequency-current curve, a type I PRC and a saddle-node on invariant circle bifurcation, and simultaneously weak noise cannot inhibit spiking. It is also shown that the bifurcation, frequency-current curve and PRC type associated with different threshold dynamics arise from the distinct subthreshold interactions of membrane currents. Further, we observe that the energy consumption of the neuron is related to its firing characteristics. The depolarization of spike threshold improves neuronal energy efficiency by reducing the overlap of Na(+) and K(+) currents during an action potential. The high energy efficiency is achieved at more depolarized spike threshold and high stimulus current. These results provide a fundamental biophysical connection that links spike threshold dynamics, input-output relation, energetics and spike initiation, which could contribute to uncover neural encoding mechanism.
Input-output energy analysis in dry apricot production of Turkey
International Nuclear Information System (INIS)
Esengun, Kemal; Guenduez, Orhan; Erdal, Guelistan
2007-01-01
The aims of this study were to determine the amount of input-output energy used in dry apricot production, to investigate the efficiency of energy consumption and to make an economic analysis of dry apricot production in Malatya, Turkey. Data used in this study were obtained from 97 farmers using a face to face questionnaire method. The sample farms were selected through a stratified random sampling technique. The population investigated was divided into two strata based on the size of apricot farms as 0.1-3.0 ha (66 farms) and larger than 3.1 ha (31 farms). The results revealed that 28647.03 MJ ha -1 energy were consumed by the first group and 17884.72 MJ ha -1 by the second group of farmers. The input-output ratio and productivities were 1.24 and 0.24 in the first strata and 1.31 and 0.25 in the second strata, respectively. Results further indicated that in both types of farms, 3/4 of the total energy cost was in non-renewable energy forms, and only 1/4 was in renewable forms. The economic analyses showed that the profit-cost ratios of the farms were 1.11 and 1.19, respectively. Net returns calculated were 414.51 $ ha -1 and 495.59 $ ha -1 in the farms investigated. It was concluded that extension activities are needed to improve the efficiency of energy consumption in dry apricot production and to employ environmentally friendly agricultural management practices and production methods
van der Voort, M; Van Meensel, J; Lauwers, L; Van Huylenbroeck, G; Charlier, J
2016-02-01
Efficiency analysis is used for assessing links between technical efficiency (TE) of livestock farms and animal diseases. However, previous studies often do not make the link with the allocation of inputs and mainly present average effects that ignore the often huge differences among farms. In this paper, we studied the relationship between exposure to gastrointestinal (GI) nematode infections, the TE and the input allocation on dairy farms. Although the traditional cost allocative efficiency (CAE) indicator adequately measures how a given input allocation differs from the cost-minimising input allocation, they do not represent the unique input allocation of farms. Similar CAE scores may be obtained for farms with different input allocations. Therefore, we propose an adjusted allocative efficiency index (AAEI) to measure the unique input allocation of farms. Combining this AAEI with the TE score allows determining the unique input-output position of each farm. The method is illustrated by estimating efficiency scores using data envelopment analysis (DEA) on a sample of 152 dairy farms in Flanders for which both accountancy and parasitic monitoring data were available. Three groups of farms with a different input-output position can be distinguished based on cluster analysis: (1) technically inefficient farms, with a relatively low use of concentrates per 100 l milk and a high exposure to infection, (2) farms with an intermediate TE, relatively high use of concentrates per 100 l milk and a low exposure to infection, (3) farms with the highest TE, relatively low roughage use per 100 l milk and a relatively high exposure to infection. Correlation analysis indicates for each group how the level of exposure to GI nematodes is associated or not with improved economic performance. The results suggest that improving both the economic performance and exposure to infection seems only of interest for highly TE farms. The findings indicate that current farm recommendations
Fernandez, Fernando R.; Malerba, Paola; White, John A.
2015-01-01
The presence of voltage fluctuations arising from synaptic activity is a critical component in models of gain control, neuronal output gating, and spike rate coding. The degree to which individual neuronal input-output functions are modulated by voltage fluctuations, however, is not well established across different cortical areas. Additionally, the extent and mechanisms of input-output modulation through fluctuations have been explored largely in simplified models of spike generation, and with limited consideration for the role of non-linear and voltage-dependent membrane properties. To address these issues, we studied fluctuation-based modulation of input-output responses in medial entorhinal cortical (MEC) stellate cells of rats, which express strong sub-threshold non-linear membrane properties. Using in vitro recordings, dynamic clamp and modeling, we show that the modulation of input-output responses by random voltage fluctuations in stellate cells is significantly limited. In stellate cells, a voltage-dependent increase in membrane resistance at sub-threshold voltages mediated by Na+ conductance activation limits the ability of fluctuations to elicit spikes. Similarly, in exponential leaky integrate-and-fire models using a shallow voltage-dependence for the exponential term that matches stellate cell membrane properties, a low degree of fluctuation-based modulation of input-output responses can be attained. These results demonstrate that fluctuation-based modulation of input-output responses is not a universal feature of neurons and can be significantly limited by subthreshold voltage-gated conductances. PMID:25909971
2017-01-01
The input-output table is comprehensive and detailed in describing the national economic system with complex economic relationships, which embodies information of supply and demand among industrial sectors. This paper aims to scale the degree of competition/collaboration on the global value chain from the perspective of econophysics. Global Industrial Strongest Relevant Network models were established by extracting the strongest and most immediate industrial relevance in the global economic system with inter-country input-output tables and then transformed into Global Industrial Resource Competition Network/Global Industrial Production Collaboration Network models embodying the competitive/collaborative relationships based on bibliographic coupling/co-citation approach. Three indicators well suited for these two kinds of weighted and non-directed networks with self-loops were introduced, including unit weight for competitive/collaborative power, disparity in the weight for competitive/collaborative amplitude and weighted clustering coefficient for competitive/collaborative intensity. Finally, these models and indicators were further applied to empirically analyze the function of sectors in the latest World Input-Output Database, to reveal inter-sector competitive/collaborative status during the economic globalization. PMID:28873432
Guan, Jun; Xu, Xiaoyu; Xing, Lizhi
2018-03-01
The input-output table is comprehensive and detailed in describing national economic systems with abundance of economic relationships depicting information of supply and demand among industrial sectors. This paper focuses on how to quantify the degree of competition on the global value chain (GVC) from the perspective of econophysics. Global Industrial Strongest Relevant Network models are established by extracting the strongest and most immediate industrial relevance in the global economic system with inter-country input-output (ICIO) tables and then have them transformed into Global Industrial Resource Competition Network models to analyze the competitive relationships based on bibliographic coupling approach. Three indicators well suited for the weighted and undirected networks with self-loops are introduced here, including unit weight for competitive power, disparity in the weight for competitive amplitude and weighted clustering coefficient for competitive intensity. Finally, these models and indicators were further applied empirically to analyze the function of industrial sectors on the basis of the latest World Input-Output Database (WIOD) in order to reveal inter-sector competitive status during the economic globalization.
Xing, Lizhi
2017-01-01
The input-output table is comprehensive and detailed in describing the national economic system with complex economic relationships, which embodies information of supply and demand among industrial sectors. This paper aims to scale the degree of competition/collaboration on the global value chain from the perspective of econophysics. Global Industrial Strongest Relevant Network models were established by extracting the strongest and most immediate industrial relevance in the global economic system with inter-country input-output tables and then transformed into Global Industrial Resource Competition Network/Global Industrial Production Collaboration Network models embodying the competitive/collaborative relationships based on bibliographic coupling/co-citation approach. Three indicators well suited for these two kinds of weighted and non-directed networks with self-loops were introduced, including unit weight for competitive/collaborative power, disparity in the weight for competitive/collaborative amplitude and weighted clustering coefficient for competitive/collaborative intensity. Finally, these models and indicators were further applied to empirically analyze the function of sectors in the latest World Input-Output Database, to reveal inter-sector competitive/collaborative status during the economic globalization.
Directory of Open Access Journals (Sweden)
Lizhi Xing
Full Text Available The input-output table is comprehensive and detailed in describing the national economic system with complex economic relationships, which embodies information of supply and demand among industrial sectors. This paper aims to scale the degree of competition/collaboration on the global value chain from the perspective of econophysics. Global Industrial Strongest Relevant Network models were established by extracting the strongest and most immediate industrial relevance in the global economic system with inter-country input-output tables and then transformed into Global Industrial Resource Competition Network/Global Industrial Production Collaboration Network models embodying the competitive/collaborative relationships based on bibliographic coupling/co-citation approach. Three indicators well suited for these two kinds of weighted and non-directed networks with self-loops were introduced, including unit weight for competitive/collaborative power, disparity in the weight for competitive/collaborative amplitude and weighted clustering coefficient for competitive/collaborative intensity. Finally, these models and indicators were further applied to empirically analyze the function of sectors in the latest World Input-Output Database, to reveal inter-sector competitive/collaborative status during the economic globalization.
Garashchuk, Sophya; Rassolov, Vitaly A
2008-07-14
Semiclassical implementation of the quantum trajectory formalism [J. Chem. Phys. 120, 1181 (2004)] is further developed to give a stable long-time description of zero-point energy in anharmonic systems of high dimensionality. The method is based on a numerically cheap linearized quantum force approach; stabilizing terms compensating for the linearization errors are added into the time-evolution equations for the classical and nonclassical components of the momentum operator. The wave function normalization and energy are rigorously conserved. Numerical tests are performed for model systems of up to 40 degrees of freedom.
Accounting for the biogeochemical cycle of nitrogen in input-output life cycle assessment.
Singh, Shweta; Bakshi, Bhavik R
2013-08-20
Nitrogen is indispensable for sustaining human activities through its role in the production of food, animal feed, and synthetic chemicals. This has encouraged significant anthropogenic mobilization of reactive nitrogen and its emissions into the environment resulting in severe disruption of the nitrogen cycle. This paper incorporates the biogeochemical cycle of nitrogen into the 2002 input-output model of the U.S. economy. Due to the complexity of this cycle, this work proposes a unique classification of nitrogen flows to facilitate understanding of the interaction between economic activities and various flows in the nitrogen cycle. The classification scheme distinguishes between the mobilization of inert nitrogen into its reactive form, use of nitrogen in various products, and nitrogen losses to the environment. The resulting inventory and model of the US economy can help quantify the direct and indirect impacts or dependence of economic sectors on the nitrogen cycle. This paper emphasizes the need for methods to manage the N cycle that focus not just on N losses, which has been the norm until now, but also include other N flows for a more comprehensive view and balanced decisions. Insight into the N profile of various sectors of the 2002 U.S. economy is presented, and the inventory can also be used for LCA or Hybrid LCA of various products. The resulting model is incorporated in the approach of Ecologically-Based LCA and available online.
Impact of the Sugar Import Reduction on Iran Economic Value Added (Input- Output Approach
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Fateme Hayatgheibi
2014-06-01
Full Text Available The present study aimed at understanding interactions and linkages between the sugar sector with other economic sectors, and the influence of sugar import reduction on the economic value added. To achieve the purpose, the Input-Output table of Iran for the year 2006, Leontief inverse matrix and hypothetical extraction method were used. Based on the results, sugar industry has the most forward linkages with “Manufacture of food products and beverages,…”, “husbandry, aviculture,…”, “cultivation, horticulture”, “bakery products” and “restaurants”. This sector has also strong backward linkages with “cultivation, horticulture”, “chemicals and chemical products”, “other services”, “transport and telecommunication” and “financial services, insurance and bank”. Furthermore, either one unit increase in the final demand of sugar or one unit decrease in the sugar import increases the output of whole economic, agricultural and fishing, industry and mining, and services sectors by 2.3060, 0.6019, 1.4331, and 0.2710 unit, respectively. The increasing coefficients of the value added for the above sectors are 0.4308, 0.3700, and 0.1992 unit, respectively.
China’s Carbon Footprint Based on Input-Output Table Series: 1992–2020
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Haitao Zheng
2017-03-01
Full Text Available Reducing carbon emissions is a major concern for China’s future. This paper explores the embodied carbon footprint of Chinese final demand from the point of view of industries. It uses the Matrix Transformation Technique (MTT to update the input-output table series from 1992 to 2020 in China. Then, we measure the embodied carbon emissions for the period 1992–2020 from 29 industry producers to the final demand, covering urban and rural residential consumption, government consumption, fixed capital formation, and net exports. The results show that construction, other services, wholesale, retail trade, accommodation and catering, industrial machinery and equipment, transport, storage and postal services, and manufacture of foods and tobacco are the industries with the greatest carbon emissions from producers, while fixed capital formation and urban consumption are the largest emitters from the perspective of final demand. The embodied carbon emission multipliers for most of the industries are decreasing, while the total carbon emissions are increasing each year. The ratio of emissions from residential consumption in terms of total emissions is decreasing. Each industry has a different main final demand-driven influencing factor on emission and, for each type of final demand, there are different industries with higher emissions.
Prell, Christina; Sun, Laixiang; Feng, Kuishuang; He, Jiaying; Hubacek, Klaus
2017-05-15
Land-use change is increasingly driven by global trade. The term "telecoupling" has been gaining ground as a means to describe how human actions in one part of the world can have spatially distant impacts on land and land-use in another. These interactions can, over time, create both direct and spatially distant feedback loops, in which human activity and land use mutually impact one another over great expanses. In this paper, we develop an analytical framework to clarify spatially distant feedbacks in the case of land use and global trade. We use an innovative mix of multi-regional input-output (MRIO) analysis and stochastic actor-oriented models (SAOMs) for analyzing the co-evolution of changes in trade network patterns with those of land use, as embodied in trade. Our results indicate that the formation of trade ties and changes in embodied land use mutually impact one another, and further, that these changes are linked to disparities in countries' wealth. Through identifying this feedback loop, our results support ongoing discussions about the unequal trade patterns between rich and poor countries that result in uneven distributions of negative environmental impacts. Finally, evidence for this feedback loop is present even when controlling for a number of underlying mechanisms, such as countries' land endowments, their geographical distance from one another, and a number of endogenous network tendencies. Copyright © 2017 Elsevier B.V. All rights reserved.
Reliability of LCI considering the uncertainties of energy consumptions in input-output analyses
International Nuclear Information System (INIS)
Yoshida, Y.; Ishitani, H.; Kudoh, Y.; Okuma, H.; Kobayashi, O.
2002-01-01
The dispersion of input-coefficients in input-output (I-O) tables and the effect on LCA results are evaluated, utilizing the data for compiling the I-O tables. CO 2 emission intensity and its variance with each commodity and service categorized in the I-O tables are estimated and applied to the LCA of a specific passenger car. Calculated results show that coefficients of variation (CV) of CO 2 -emission intensity are about 0.8 for the intermediate commodities which are frequently assessed in LCA. CO 2 emissions induced by the production of the passenger car and the CV of the emissions are estimated at 1.3 Mg-C and 0.14, respectively. The value of CV is smaller than that of the most intermediate commodities since the CV of total emissions decreases as the number of components of the passenger car increases. Although emissions intensity itself given by I-O tables has large variance, I-O tables are still useful tools for LCA if the number of components of a product is large enough. (author)
Optimizing production with energy and GHG emission constraints in Greece: An input-output analysis
International Nuclear Information System (INIS)
Hristu-Varsakelis, D.; Karagianni, S.; Pempetzoglou, M.; Sfetsos, A.
2010-01-01
Under its Kyoto and EU obligations, Greece has committed to a greenhouse gas (GHG) emissions increase of at most 25% compared to 1990 levels, to be achieved during the period 2008-2012. Although this restriction was initially regarded as being realistic, information derived from GHG emissions inventories shows that an increase of approximately 28% has already taken place between 1990 and 2005, highlighting the need for immediate action. This paper explores the reallocation of production in Greece, on a sector-by-sector basis, in order to meet overall demand constraints and GHG emissions targets. We pose a constrained optimization problem, taking into account the Greek environmental input-output matrix for 2005, the amount of utilized energy and pollution reduction options. We examine two scenarios, limiting fluctuations in sectoral production to at most 10% and 15%, respectively, compared to baseline (2005) values. Our results indicate that (i) GHG emissions can be reduced significantly with relatively limited effects on GVP growth rates, and that (ii) greater cutbacks in GHG emissions can be achieved as more flexible production scenarios are allowed.
Modeling imbalanced economic recovery following a natural disaster using input-output analysis.
Li, Jun; Crawford-Brown, Douglas; Syddall, Mark; Guan, Dabo
2013-10-01
Input-output analysis is frequently used in studies of large-scale weather-related (e.g., Hurricanes and flooding) disruption of a regional economy. The economy after a sudden catastrophe shows a multitude of imbalances with respect to demand and production and may take months or years to recover. However, there is no consensus about how the economy recovers. This article presents a theoretical route map for imbalanced economic recovery called dynamic inequalities. Subsequently, it is applied to a hypothetical postdisaster economic scenario of flooding in London around the year 2020 to assess the influence of future shocks to a regional economy and suggest adaptation measures. Economic projections are produced by a macro econometric model and used as baseline conditions. The results suggest that London's economy would recover over approximately 70 months by applying a proportional rationing scheme under the assumption of initial 50% labor loss (with full recovery in six months), 40% initial loss to service sectors, and 10-30% initial loss to other sectors. The results also suggest that imbalance will be the norm during the postdisaster period of economic recovery even though balance may occur temporarily. Model sensitivity analysis suggests that a proportional rationing scheme may be an effective strategy to apply during postdisaster economic reconstruction, and that policies in transportation recovery and in health care are essential for effective postdisaster economic recovery. © 2013 Society for Risk Analysis.
Multiregional input-output model for China's farm land and water use.
Guo, Shan; Shen, Geoffrey Qiping
2015-01-06
Land and water are the two main drivers of agricultural production. Pressure on farm land and water resources is increasing in China due to rising food demand. Domestic trade affects China's regional farm land and water use by distributing resources associated with the production of goods and services. This study constructs a multiregional input-output model to simultaneously analyze China's farm land and water uses embodied in consumption and interregional trade. Results show a great similarity for both China's farm land and water endowments. Shandong, Henan, Guangdong, and Yunnan are the most important drivers of farm land and water consumption in China, even though they have relatively few land and water resource endowments. Significant net transfers of embodied farm land and water flows are identified from the central and western areas to the eastern area via interregional trade. Heilongjiang is the largest farm land and water supplier, in contrast to Shanghai as the largest receiver. The results help policy makers to comprehensively understand embodied farm land and water flows in a complex economy network. Improving resource utilization efficiency and reshaping the embodied resource trade nexus should be addressed by considering the transfer of regional responsibilities.
DAMPAK SUB-SEKTOR UNGGULAN TERHADAP PEREKONOMIAN KOTA SAMARINDA: PENDEKATAN INPUT-OUTPUT
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Jerry Pahlevy Mahakam
2015-01-01
Full Text Available In this paper, the writer would like to investigate the sub-sectors of the economy categorized as superior, potential, and non-superior, determine the magnitude of multiplier income arising from these sub-sector on household income and job opportunities, and identify the sub-sector of the economy which can be placed as a superior in Samarinda. This study employed Input-Output approach which later discovered several factors which were considered as superior, namely food and beverage industry; Paper and printing industry; electricity; construction / building; land transportation; and other services, while the sub-sectors which were included in non-superior categories were rice, cassava, vegetables, fruits, other staple food crops, plantation crops, timber and forest products, fisheries, mining, timber industry, chemical industry, hotels, telecommunications, insurance, government, education services. In addition, the results of forward and backward linkages analysis and multiplier income calculating of household income and job opportunities found that those sub-sectors of food and beverage industry, building/ construction, other services, and land transportation were categorized into major sub-sectors.
CO2 emissions vs. CO2 responsibility: An input-output approach for the Turkish economy
International Nuclear Information System (INIS)
Ipek Tunc, G.; Tueruet-Asik, Serap; Akbostanci, Elif
2007-01-01
Recently, global warming (greenhouse effect) and its effects have become one of the hottest topics in the world agenda. There have been several international attempts to reduce the negative effects of global warming. The Kyoto Protocol can be cited as the most important agreement which tries to limit the countries' emissions within a time horizon. For this reason, it becomes important to calculate the greenhouse gas emissions of countries. The aim of this study is to estimate the amount of CO 2 -the most important greenhouse gas-emissions, for the Turkish economy. An extended input-output model is estimated by using 1996 data in order to identify the sources of CO 2 emissions and to discuss the share of sectors in total emission. Besides, 'CO 2 responsibility', which takes into account the CO 2 content of imports, is estimated for the Turkish economy. The sectoral CO 2 emissions and CO 2 responsibilities are compared and these two notions are linked to foreign trade volume. One of the main conclusions is that the manufacturing industry has the first place in both of the rankings for CO 2 emissions and CO 2 responsibilities, while agriculture and husbandry has the last place
Energy-dominated local carbon emissions in Beijing 2007: inventory and input-output analysis.
Guo, Shan; Liu, J B; Shao, Ling; Li, J S; An, Y R
2012-01-01
For greenhouse gas (GHG) emissions by Beijing economy 2007, a concrete emission inventory covering carbon dioxide (CO(2)), methane (CH(4)), and nitrous oxide (N(2)O) is presented and associated with an input-output analysis to reveal the local GHG embodiment in final demand and trade without regard to imported emissions. The total direct GHG emissions amount to 1.06E + 08 t CO(2)-eq, of which energy-related CO(2) emissions comprise 90.49%, non-energy-related CO(2) emissions 6.35%, CH(4) emissions 2.33%, and N(2)O emissions 0.83%, respectively. In terms of energy-related CO(2) emissions, the largest source is coal with a percentage of 53.08%, followed by coke with 10.75% and kerosene with 8.44%. Sector 26 (Construction Industry) holds the top local emissions embodied in final demand of 1.86E + 07 t CO(2)-eq due to its considerable capital, followed by energy-intensive Sectors 27 (Transport and Storage) and 14 (Smelting and Pressing of Ferrous and Nonferrous Metals). The GHG emissions embodied in Beijing's exports are 4.90E + 07 t CO(2)-eq, accounting for 46.01% of the total emissions embodied in final demand. The sound scientific database totally based on local emissions is an important basis to make effective environment and energy policies for local decision makers.
Economic input-output life-cycle assessment of trade between Canada and the United States.
Norman, Jonathan; Charpentier, Alex D; MacLean, Heather L
2007-03-01
With increasing trade liberalization, attempts at accounting for environmental impacts and energy use across the manufacturing supply chain are complicated by the predominance of internationally supplied resources and products. This is particularly true for Canada and the United States, the world's largest trading partners. We use an economic input-output life-cycle assessment (EIO-LCA) technique to estimate the economy-wide energy intensity and greenhouse gas (GHG) emissions intensity for 45 manufacturing and resource sectors in Canada and the United States. Overall, we find that U.S. manufacturing and resource industries are about 1.15 times as energy-intensive and 1.3 times as GHG-intensive as Canadian industries, with significant sector-specific discrepancies in energy and GHG intensity. This trend is mainly due to a greater direct reliance on fossil fuels for many U.S. industries, in addition to a highly fossil-fuel based electricity mix in the U.S. To account for these differences, we develop a 76 sector binational EIO-LCA model that implicitly considers trade in goods between Canada and the U.S. Our findings show that accounting for trade can significantly alter the results of life-cycle assessment studies, particularly for many Canadian manufacturing sectors, and the production/consumption of goods in one country often exerts significant energy- and GHG-influences on the other.
Greenhouse gas emissions in China 2007: Inventory and input-output analysis
International Nuclear Information System (INIS)
Chen, G.Q.; Zhang Bo
2010-01-01
For greenhouse gas (GHG) emissions by the Chinese economy in 2007 with the most recent statistics availability, a concrete inventory covering CO 2 , CH 4 , and N 2 O is composed and associated with an input-output analysis to reveal the emission embodiment in final consumption and international trade. The estimated total direct GHG emission amounts to 7456.12 Mt CO 2 -eq by the commonly referred IPCC global warming potentials, with 63.39% from energy-related CO 2 , 22.31% from non-energy-related CO 2 , 11.15% from CH 4 and 3.15% from N 2 O. Responsible for 81.32% of the total GHG emissions are the five sectors of the Electric Power/Steam and Hot Water Production and Supply, Smelting and Pressing of Ferrous and Nonferrous Metals, Nonmetal Mineral Products, Agriculture, and Coal Mining and Dressing, with distinctive emission structures. The sector of Construction holds the top GHG emissions embodied in both domestic production and consumption, and the emission embodied in gross capital formation is prominently more than those in other components of the final consumption characterized by extensive investment in contrast to limited household consumption. China is a net exporter of embodied GHG emissions, with emissions embodied in exports of 3060.18 Mt CO 2 -eq, in magnitude up to 41.04% of the total direct emission.
International Nuclear Information System (INIS)
Lixon, Benoit; Thomassin, Paul J.; Hamaide, Bertrand
2008-01-01
The objective of this paper is to assess the economic impacts of reducing greenhouse gas emissions by decreasing industrial output in Canada to a level that will meet the target set out in the Kyoto Protocol. The study uses an ecological-economic Input-Output model combining economic components valued in monetary terms with ecologic components - GHG emissions - expressed in physical terms. Economic and greenhouse gas emissions data for Canada are computed in the same sectoral disaggregation. Three policy scenarios are considered: the first one uses the direct emission coefficients to allocate the reduction in industrial output, while the other two use the direct plus indirect emission coefficients. In the first two scenarios, the reduction in industrial sector output is allocated uniformly across sectors while it is allocated to the 12 largest emitting industries in the last one. The estimated impacts indicate that the results vary with the different allocation methods. The third policy scenario, allocation to the 12 largest emitting sectors, is the most cost effective of the three as the impacts of the Kyoto Protocol reduces Gross Domestic Product by 3.1% compared to 24% and 8.1% in the first two scenarios. Computed economic costs should be considered as upper-bounds because the model assumes immediate adjustment to the Kyoto Protocol and because flexibility mechanisms are not incorporated. The resulting upper-bound impact of the third scenario may seem to contradict those who claim that the Kyoto Protocol would place an unbearable burden on the Canadian economy. (author)
El Haimar, Amine; Santos, Joost R
2014-03-01
Influenza pandemic is a serious disaster that can pose significant disruptions to the workforce and associated economic sectors. This article examines the impact of influenza pandemic on workforce availability within an interdependent set of economic sectors. We introduce a simulation model based on the dynamic input-output model to capture the propagation of pandemic consequences through the National Capital Region (NCR). The analysis conducted in this article is based on the 2009 H1N1 pandemic data. Two metrics were used to assess the impacts of the influenza pandemic on the economic sectors: (i) inoperability, which measures the percentage gap between the as-planned output and the actual output of a sector, and (ii) economic loss, which quantifies the associated monetary value of the degraded output. The inoperability and economic loss metrics generate two different rankings of the critical economic sectors. Results show that most of the critical sectors in terms of inoperability are sectors that are related to hospitals and health-care providers. On the other hand, most of the sectors that are critically ranked in terms of economic loss are sectors with significant total production outputs in the NCR such as federal government agencies. Therefore, policy recommendations relating to potential mitigation and recovery strategies should take into account the balance between the inoperability and economic loss metrics. © 2013 Society for Risk Analysis.
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May Tan May
2018-01-01
Full Text Available In recent years, there has been an increase in crude palm oil (CPO demand, resulting in palm oil mills (POMs seizing the opportunity to increase CPO production to make more profits. A series of equipment are designed to operate in their optimum capacities in the current existing POMs. Some equipment may be limited by their maximum design capacities when there is a need to increase CPO production, resulting in process bottlenecks. In this research, a framework is developed to provide stepwise procedures on identifying bottlenecks and retrofitting a POM process to cater for the increase in production capacity. This framework adapts an algebraic approach known as Inoperability Input-Output Modelling (IIM. To illustrate the application of the framework, an industrial POM case study was solved using LINGO software in this work, by maximising its production capacity. Benefit-to-Cost Ratio (BCR analysis was also performed to assess the economic feasibility. As results, the Screw Press was identified as the bottleneck. The retrofitting recommendation was to purchase an additional Screw Press to cater for the new throughput with BCR of 54.57. It was found the POM to be able to achieve the maximum targeted production capacity of 8,139.65 kg/hr of CPO without any bottlenecks.
Energy-Dominated Local Carbon Emissions in Beijing 2007: Inventory and Input-Output Analysis
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Shan Guo
2012-01-01
Full Text Available For greenhouse gas (GHG emissions by Beijing economy 2007, a concrete emission inventory covering carbon dioxide (CO2, methane (CH4, and nitrous oxide (N2O is presented and associated with an input-output analysis to reveal the local GHG embodiment in final demand and trade without regard to imported emissions. The total direct GHG emissions amount to 1.06E + 08 t CO2-eq, of which energy-related CO2 emissions comprise 90.49%, non-energy-related CO2 emissions 6.35%, CH4 emissions 2.33%, and N2O emissions 0.83%, respectively. In terms of energy-related CO2 emissions, the largest source is coal with a percentage of 53.08%, followed by coke with 10.75% and kerosene with 8.44%. Sector 26 (Construction Industry holds the top local emissions embodied in final demand of 1.86E + 07 t CO2-eq due to its considerable capital, followed by energy-intensive Sectors 27 (Transport and Storage and 14 (Smelting and Pressing of Ferrous and Nonferrous Metals. The GHG emissions embodied in Beijing's exports are 4.90E + 07 t CO2-eq, accounting for 46.01% of the total emissions embodied in final demand. The sound scientific database totally based on local emissions is an important basis to make effective environment and energy policies for local decision makers.
Berg, Matthew; Hartley, Brian; Richters, Oliver
2015-01-01
By synthesizing stock-flow consistent models, input-output models, and aspects of ecological macroeconomics, a method is developed to simultaneously model monetary flows through the financial system, flows of produced goods and services through the real economy, and flows of physical materials through the natural environment. This paper highlights the linkages between the physical environment and the economic system by emphasizing the role of the energy industry. A conceptual model is developed in general form with an arbitrary number of sectors, while emphasizing connections with the agent-based, econophysics, and complexity economics literature. First, we use the model to challenge claims that 0% interest rates are a necessary condition for a stationary economy and conduct a stability analysis within the parameter space of interest rates and consumption parameters of an economy in stock-flow equilibrium. Second, we analyze the role of energy price shocks in contributing to recessions, incorporating several propagation and amplification mechanisms. Third, implied heat emissions from energy conversion and the effect of anthropogenic heat flux on climate change are considered in light of a minimal single-layer atmosphere climate model, although the model is only implicitly, not explicitly, linked to the economic model.
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Ackchai Sirikijpanichkul
2015-01-01
Full Text Available For the agricultural-based countries, the requirement on transportation infrastructure should not only be limited to accommodate general traffic but also the transportation of crop and agricultural products during the harvest seasons. Most of the past researches focus on the development of truck trip estimation techniques for urban, statewide, or nationwide freight movement but neglect the importance of rural freight movement which contributes to pavement deterioration on rural roads especially during harvest seasons. Recently, the Thai Government initiated a plan to construct a network of reservoirs within the northeastern region, aiming at improving existing irrigation system particularly in the areas where a more effective irrigation system is needed. It is expected to bring in new opportunities on expanding the cultivation areas, increasing the economy of scale and enlarging the extent market of area. As a consequence, its effects on truck trip generation needed to be investigated to assure the service quality of related transportation infrastructure. This paper proposes a combinatory input-output commodity-based approach to estimate truck trips on rural highway infrastructure network. The large-scale irrigation project for the northeastern of Thailand is demonstrated as a case study.
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Douw Gert Brand Boshoff
2016-11-01
Full Text Available Input-output analysis is a well known method of analysing specific economic activity and the influence of different sectors on the economy and on one another. This study investigates the ability of input-output analysis to consider the importance of commercial real estate on the economy. It analyses the economic activity, contribution to GDP, employment created and taxes generated with reference to direct, indirect and induced impacts. The research shows the contribution of the specific sector on the economy and highlights the ability of input-output analysis to determine the impact of different types of property and locational analysis. The interaction of property with the economy is discussed, which also enables the use of the analysis reported here for short term future forecasting, whereby expected real estate activity is used to forecast the direct, indirect and induced effects on the economy.
Wu, Xianhua; Wei, Guo; Yang, Lingjuan; Guo, Ji; Lu, Huaguo; Chen, Yunfeng; Sun, Jian
2014-01-01
Concentrating on consuming coefficient, partition coefficient, and Leontief inverse matrix, relevant concepts and algorithms are developed for estimating the impact of meteorological services including the associated (indirect, complete) economic effect. Subsequently, quantitative estimations are particularly obtained for the meteorological services in Jiangxi province by utilizing the input-output method. It is found that the economic effects are noticeably rescued by the preventive strategies developed from both the meteorological information and internal relevance (interdependency) in the industrial economic system. Another finding is that the ratio range of input in the complete economic effect on meteorological services is about 1 : 108.27-1 : 183.06, remarkably different from a previous estimation based on the Delphi method (1 : 30-1 : 51). Particularly, economic effects of meteorological services are higher for nontraditional users of manufacturing, wholesale and retail trades, services sector, tourism and culture, and art and lower for traditional users of agriculture, forestry, livestock, fishery, and construction industries.
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Xianhua Wu
2014-01-01
Full Text Available Concentrating on consuming coefficient, partition coefficient, and Leontief inverse matrix, relevant concepts and algorithms are developed for estimating the impact of meteorological services including the associated (indirect, complete economic effect. Subsequently, quantitative estimations are particularly obtained for the meteorological services in Jiangxi province by utilizing the input-output method. It is found that the economic effects are noticeably rescued by the preventive strategies developed from both the meteorological information and internal relevance (interdependency in the industrial economic system. Another finding is that the ratio range of input in the complete economic effect on meteorological services is about 1 : 108.27–1 : 183.06, remarkably different from a previous estimation based on the Delphi method (1 : 30–1 : 51. Particularly, economic effects of meteorological services are higher for nontraditional users of manufacturing, wholesale and retail trades, services sector, tourism and culture, and art and lower for traditional users of agriculture, forestry, livestock, fishery, and construction industries.
Wu, Xianhua; Yang, Lingjuan; Guo, Ji; Lu, Huaguo; Chen, Yunfeng; Sun, Jian
2014-01-01
Concentrating on consuming coefficient, partition coefficient, and Leontief inverse matrix, relevant concepts and algorithms are developed for estimating the impact of meteorological services including the associated (indirect, complete) economic effect. Subsequently, quantitative estimations are particularly obtained for the meteorological services in Jiangxi province by utilizing the input-output method. It is found that the economic effects are noticeably rescued by the preventive strategies developed from both the meteorological information and internal relevance (interdependency) in the industrial economic system. Another finding is that the ratio range of input in the complete economic effect on meteorological services is about 1 : 108.27–1 : 183.06, remarkably different from a previous estimation based on the Delphi method (1 : 30–1 : 51). Particularly, economic effects of meteorological services are higher for nontraditional users of manufacturing, wholesale and retail trades, services sector, tourism and culture, and art and lower for traditional users of agriculture, forestry, livestock, fishery, and construction industries. PMID:24578666
Greenhouse gas footprinting for small businesses - The use of input-output data
International Nuclear Information System (INIS)
Berners-Lee, M.; Howard, D.C.; Moss, J.; Kaivanto, K.; Scott, W.A.
2011-01-01
To mitigate anthropogenic climate change greenhouse gas emissions (GHG) must be reduced; their major source is man's use of energy. A key way to manage emissions is for the energy consumer to understand their impact and the consequences of changing their activities. This paper addresses the challenge of delivering relevant, practical and reliable greenhouse gas 'footprint' information for small and medium sized businesses. The tool we describe is capable of ascribing parts of the total footprint to specific actions to which the business can relate and is sensitive enough to reflect the consequences of change. It provides a comprehensive description of all emissions for each business and sets them in the context of local, national and global statistics. It includes the GHG costs of all goods and services irrespective of their origin and without double accounting. We describe the development and use of the tool, which draws upon both national input-output data and process-based life cycle analysis techniques; a hybrid model. The use of national data sets the output in context and makes the results consistent with national and global targets, while the life cycle techniques provide a means of reflecting the dynamics of actions. The model is described in some detail along with a rationale and a short discussion of validity. As the tool is designed for small commercial users, we have taken care to combine rigour with practicality; parameterising from readily available client data whilst being clear about uncertainties. As an additional incentive, we also report on the potential costs or savings of switching activities. For users to benefit from the tool, they need to understand the output and know how much confidence they should place in the results. We not only describe an application of non-parametric statistics to generate confidence intervals, but also offer users the option of and guidance on adjusting figures to examine the sensitivity of the model to its
Directory of Open Access Journals (Sweden)
Chandra Darma Permana
2011-08-01
Full Text Available Normal 0 false false false MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman"; mso-ansi-language:#0400; mso-fareast-language:#0400; mso-bidi-language:#0400;} Despite being recovered from economic crisis, the infrastructure development in Indonesia still hasn’t shown a significant improvement. It is reflected from the diminishing government allocation for infrastructure as a percentage of Gross Domestic Products. The main objective of the study is to analyze the role of infrastructure through the linkage analysis, dispersion effect analysis, multiplier effect analysis, and the investment effect analysis. The scope of infrastructure is only referred to electricity, gas and water, and construction sector. The data used for this study is the 2005 Indonesian Input-Output Table. The result of the study has shown that infrastructure has a higher backward linkage than its forward. In addition, all of the infrastructure sectors has shown more than one dispersion coefficient and conversely has revealed less than one value for the dispersion sensitivity. Which means that infrastructure had a better capability to support the development of its upstream sectors than its downstream. Infrastructure has a positive multiplier effect toward the other sectors. The growth of the investment in the electricity, gas and water sector has given the biggest effect toward the change of the total outpu, while the water sector has given the biggest effect toward the change in the total income, and road, bridge and port sector has given the biggest effect toward the change in the total labour.
Modeling DPOAE input/output function compression: comparisons with hearing thresholds.
Bhagat, Shaum P
2014-09-01
Basilar membrane input/output (I/O) functions in mammalian animal models are characterized by linear and compressed segments when measured near the location corresponding to the characteristic frequency. A method of studying basilar membrane compression indirectly in humans involves measuring distortion-product otoacoustic emission (DPOAE) I/O functions. Previous research has linked compression estimates from behavioral growth-of-masking functions to hearing thresholds. The aim of this study was to compare compression estimates from DPOAE I/O functions and hearing thresholds at 1 and 2 kHz. A prospective correlational research design was performed. The relationship between DPOAE I/O function compression estimates and hearing thresholds was evaluated with Pearson product-moment correlations. Normal-hearing adults (n = 16) aged 22-42 yr were recruited. DPOAE I/O functions (L₂ = 45-70 dB SPL) and two-interval forced-choice hearing thresholds were measured in normal-hearing adults. A three-segment linear regression model applied to DPOAE I/O functions supplied estimates of compression thresholds, defined as breakpoints between linear and compressed segments and the slopes of the compressed segments. Pearson product-moment correlations between DPOAE compression estimates and hearing thresholds were evaluated. A high correlation between DPOAE compression thresholds and hearing thresholds was observed at 2 kHz, but not at 1 kHz. Compression slopes also correlated highly with hearing thresholds only at 2 kHz. The derivation of cochlear compression estimates from DPOAE I/O functions provides a means to characterize basilar membrane mechanics in humans and elucidates the role of compression in tone detection in the 1-2 kHz frequency range. American Academy of Audiology.
Economic and Environmental Impacts of Dietary Changes in Iran: An Input-Output Analysis
Directory of Open Access Journals (Sweden)
Roham Rahmani
2012-03-01
Full Text Available Iran's simple and environmentally extended commodity by commodity input-output (IO model was used to determine the impacts of dietary changes on the Iranian economy and on the environmental load. The original model is based on the status-quo diet and was modified to include the World Health Organization (WHO, the World Cancer Research Fund (WCRF and Mediterranean alternative dietary scenarios. A range of impacts occurred depending upon the relative changes in food items. The direction of changes was similar in the three alternative scenarios. The greatest and smallest impact occurred in the WHO and the Mediterranean scenarios respectively. Total changes in output in WHO, WCRF and Mediterranean dietary scenarios were calculated to be 7010.1, 4802.8 and 3330.8 billion Rials respectively. The outputs of rice, vegetables, fruit, bread and macaroni decreased, but those of live and other animal products increased. The output of non-food commodities and services increased as well. The environmental load increased for three dietary scenarios in comparison with the status-quo diet. The greatest and smallest environmental load occurred in WHO and Mediterranean dietary scenarios respectively. Thus, although dietary changes can have positive effects on economic output, in order to avoid negative environmental effects, it is necessary to consider strategies such as applying capabilities, particularly natural resources in an optimal healthy and environmentally diet, planning for improving forest covering and green space simultaneously with increasing economic activities and using indirect incentives, such as taxes and insurance, for promoting sustainable and healthy foods and reducing greenhouse gas emissions.
Syringe-Injectable Electronics with a Plug-and-Play Input/Output Interface.
Schuhmann, Thomas G; Yao, Jun; Hong, Guosong; Fu, Tian-Ming; Lieber, Charles M
2017-09-13
Syringe-injectable mesh electronics represent a new paradigm for brain science and neural prosthetics by virtue of the stable seamless integration of the electronics with neural tissues, a consequence of the macroporous mesh electronics structure with all size features similar to or less than individual neurons and tissue-like flexibility. These same properties, however, make input/output (I/O) connection to measurement electronics challenging, and work to-date has required methods that could be difficult to implement by the life sciences community. Here we present a new syringe-injectable mesh electronics design with plug-and-play I/O interfacing that is rapid, scalable, and user-friendly to nonexperts. The basic design tapers the ultraflexible mesh electronics to a narrow stem that routes all of the device/electrode interconnects to I/O pads that are inserted into a standard zero insertion force (ZIF) connector. Studies show that the entire plug-and-play mesh electronics can be delivered through capillary needles with precise targeting using microliter-scale injection volumes similar to the standard mesh electronics design. Electrical characterization of mesh electronics containing platinum (Pt) electrodes and silicon (Si) nanowire field-effect transistors (NW-FETs) demonstrates the ability to interface arbitrary devices with a contact resistance of only 3 Ω. Finally, in vivo injection into mice required only minutes for I/O connection and yielded expected local field potential (LFP) recordings from a compact head-stage compatible with chronic studies. Our results substantially lower barriers for use by new investigators and open the door for increasingly sophisticated and multifunctional mesh electronics designs for both basic and translational studies.
Energy embodied in the international trade of China. An energy input-output analysis
International Nuclear Information System (INIS)
Liu, Hongtao; Xi, Youmin; Guo, Ju'e; Li, Xia
2010-01-01
Growing international trade has not only positively affected the People's Republic of China's (China's) economic development, but also expanded the exportation of energy embodied in goods during their production. This energy flow out will pose risks to China's rational utilization of natural resources as well as environmental protection. In this paper, we evaluate the energy embodied in goods produced in China during 1992-2005 and use input-output structural decomposition analysis to identify five key factors causing the changes of energy embodied in exports. (Direct primary energy efficiency, primary energy consumption structure, structure of intermediate inputs, structure of exports, and scale of exports.) For the three sub-periods of 1992-1997, 1997-2002, and 2002-2005, results show that China is a net exporter of energy, and the energy embodied in exports tends to increase over time. The expanding total volume of exports and increasing exports of energy-intensive goods tend to enlarge the energy embodied in exports within all three sub-periods, but these driving forces were offset by a considerable improvement of energy efficiency and changes in primary energy consumption structure from 1992 to 2002 and the effects of structure of intermediate input only in the sub-period from 1992 to 1997. From 2002 to 2005, the sharp augmentation of energy embodied in exports was driven by all the five factors. Our research has practical implications for the Chinese economy. Results of this study suggest that the energy embodied in trade should receive special attentions in energy policies design to limit the energy resource out-flow and pollution generation. (author)
Prioritizing towards a green export portfolio for India: An environmental input-output approach
International Nuclear Information System (INIS)
Goldar, Amrita; Bhanot, Jaya; Shimpo, Kazushige
2011-01-01
Proponents of free trade have often hailed international trade as an engine of economic growth. However, the foreign trade sector, like many other sectors in developing countries, frequently involves these countries walking a tightrope between their developmental objectives and environmental goals. In this regard, prioritizing for developing a 'green' yet internationally competitive export portfolio provides a quintessential win-win solution to the problem. This study factors in both environmental benignity (indicated by total CO 2 emission intensity) as well as trade competitiveness (indicated by revealed comparative advantage index) in identifying the 'ideal' Indian export portfolio. The analysis calculates the level of direct and indirect emissions from the foreign trade sector (exports and imports) using the environmental input-output (EIO) matrix for 2003/04 for India that has been jointly developed by researchers from Keio University, Japan, and The Energy and Resources Institute (TERI), New Delhi. The derived basket is compared to the current portfolio to estimate the potential saving from compositional changes and to suggest directions for policymaking to emphasize or de-emphasize the export of certain categories of exports. - Highlights: → India was a net GHG importer (0.064 Gt CO 2 ) in 2003/04. → Emissions from exports and imports were 0.189 and 0.253 Gt CO 2 , respectively. → Prioritizing of exports using IO and RCA shows horticultural exports to be ideal. → Services and gems and jewelry exports were also found suitable. → A composition change in exports leads to reduction in emissions by 30 Mt CO 2 annually.
Directory of Open Access Journals (Sweden)
F. C. Cooper
2013-04-01
Full Text Available The fluctuation-dissipation theorem (FDT has been proposed as a method of calculating the response of the earth's atmosphere to a forcing. For this problem the high dimensionality of the relevant data sets makes truncation necessary. Here we propose a method of truncation based upon the assumption that the response to a localised forcing is spatially localised, as an alternative to the standard method of choosing a number of the leading empirical orthogonal functions. For systems where this assumption holds, the response to any sufficiently small non-localised forcing may be estimated using a set of truncations that are chosen algorithmically. We test our algorithm using 36 and 72 variable versions of a stochastic Lorenz 95 system of ordinary differential equations. We find that, for long integrations, the bias in the response estimated by the FDT is reduced from ~75% of the true response to ~30%.
Modeling and simulation of high dimensional stochastic multiscale PDE systems at the exascale
Energy Technology Data Exchange (ETDEWEB)
Zabaras, Nicolas J. [Cornell Univ., Ithaca, NY (United States)
2016-11-08
Predictive Modeling of multiscale and Multiphysics systems requires accurate data driven characterization of the input uncertainties, and understanding of how they propagate across scales and alter the final solution. This project develops a rigorous mathematical framework and scalable uncertainty quantification algorithms to efficiently construct realistic low dimensional input models, and surrogate low complexity systems for the analysis, design, and control of physical systems represented by multiscale stochastic PDEs. The work can be applied to many areas including physical and biological processes, from climate modeling to systems biology.
He, Ling Yan; Wang, Tie-Jun; Wang, Chuan
2016-07-11
High-dimensional quantum system provides a higher capacity of quantum channel, which exhibits potential applications in quantum information processing. However, high-dimensional universal quantum logic gates is difficult to achieve directly with only high-dimensional interaction between two quantum systems and requires a large number of two-dimensional gates to build even a small high-dimensional quantum circuits. In this paper, we propose a scheme to implement a general controlled-flip (CF) gate where the high-dimensional single photon serve as the target qudit and stationary qubits work as the control logic qudit, by employing a three-level Λ-type system coupled with a whispering-gallery-mode microresonator. In our scheme, the required number of interaction times between the photon and solid state system reduce greatly compared with the traditional method which decomposes the high-dimensional Hilbert space into 2-dimensional quantum space, and it is on a shorter temporal scale for the experimental realization. Moreover, we discuss the performance and feasibility of our hybrid CF gate, concluding that it can be easily extended to a 2n-dimensional case and it is feasible with current technology.
DEFF Research Database (Denmark)
Boyd, Britta; Mangalagiu, Diana; Straatman, Bas
2018-01-01
This paper presents a consumption-based method accounting for greenhouse gas emissions at regional level based on a multi-region input-output model. The method is based on regional consumption and includes imports and exports of emissions, factual emission developments, green investments as well...
Socio-economic effects of a HYSOL CSP plant located in different countries: An input output analysis
Corona, B.; López, A.; San Miguel, G.
2016-01-01
The aim of this paper is to estimate the socioeconomic effects associated with the production of electricity by a CSP plant with HYSOL configuration, using Input Output Analysis. These effects have been estimated in terms of production of Goods and Services (G&S), multiplier effect, value added,
Stadler, K.; Wood, R.; Bulavskaya, T.; Södersten, C.J.; Simas, M.; Schmidt, S.; Usubiaga, A.; Acosta-Fernández, J.; Kuenen, J.; Bruckner, M.; Giljum, S.; Lutter, S.; Merciai, S.; Schmidt, J.H.; Theurl, M.C.; Plutzar, C.; Kastner, T.; Eisenmenger, N.; Erb, K.H.; Koning, A. de; Tukker, A.
2018-01-01
Environmentally extended multiregional input-output (EE MRIO) tables have emerged as a key framework to provide a comprehensive description of the global economy and analyze its effects on the environment. Of the available EE MRIO databases, EXIOBASE stands out as a database compatible with the
Fremdling, Rainer; Staeglin, Reiner
2012-01-01
The objective of this contribution is to present the final results of a long-term research project which aimed at constructing an input-output table for Germany in 1936. Our research can be seen as follow-up of the activities of the German Imperial Statistical Office (Statistisches Reichsamt) which
Computer-Mediated Input, Output and Feedback in the Development of L2 Word Recognition from Speech
Matthews, Joshua; Cheng, Junyu; O'Toole, John Mitchell
2015-01-01
This paper reports on the impact of computer-mediated input, output and feedback on the development of second language (L2) word recognition from speech (WRS). A quasi-experimental pre-test/treatment/post-test research design was used involving three intact tertiary level English as a Second Language (ESL) classes. Classes were either assigned to…
International Nuclear Information System (INIS)
Maeenpaeae, I.; Tervo, H.
1994-01-01
The structures of utilization of primary energy, final consumption of electricity, and the main emissions into the air in Finnish economy in 1990 have been derived in this report on the basis of input-output analysis. By using an input-output model it is possible to calculate what is the productional content of different products, i.e. how much in total, directly or indirectly, work of different fields of production is needed for production of commodities. Energy and emissions into air can be assumed as basic inputs of the production. By using input-output analysis it is possible to follow up how the energy inputs and emissions of different branches are bound into commodity flows of economy. Hence a systematic and expiring figure is obtained of energy and emission contents of different branches. The basic matrix for calculation of primary energy and emission coefficients of different branches are made in the chapter no. 2. The formulae for calculation of the energy and emission contents of commodities are derived from common basic formulae of input-output analysis in the chapter no. 3. The branch-based energy and emission coefficients of commodities are presented in the chapter no. 4. The energies bound into household commodities and emissions into the air are presented in the chapter no. 5. The total presentation of the Finnish national product, the gross national product and the energy and emission contents of the main commodities is made in the chapter no. 6. (11 refs.)
Greenhouse gas footprinting for small businesses--the use of input-output data.
Berners-Lee, M; Howard, D C; Moss, J; Kaivanto, K; Scott, W A
2011-02-01
To mitigate anthropogenic climate change greenhouse gas emissions (GHG) must be reduced; their major source is man's use of energy. A key way to manage emissions is for the energy consumer to understand their impact and the consequences of changing their activities. This paper addresses the challenge of delivering relevant, practical and reliable greenhouse gas 'footprint' information for small and medium sized businesses. The tool we describe is capable of ascribing parts of the total footprint to specific actions to which the business can relate and is sensitive enough to reflect the consequences of change. It provides a comprehensive description of all emissions for each business and sets them in the context of local, national and global statistics. It includes the GHG costs of all goods and services irrespective of their origin and without double accounting. We describe the development and use of the tool, which draws upon both national input-output data and process-based life cycle analysis techniques; a hybrid model. The use of national data sets the output in context and makes the results consistent with national and global targets, while the life cycle techniques provide a means of reflecting the dynamics of actions. The model is described in some detail along with a rationale and a short discussion of validity. As the tool is designed for small commercial users, we have taken care to combine rigour with practicality; parameterising from readily available client data whilst being clear about uncertainties. As an additional incentive, we also report on the potential costs or savings of switching activities. For users to benefit from the tool, they need to understand the output and know how much confidence they should place in the results. We not only describe an application of non-parametric statistics to generate confidence intervals, but also offer users the option of and guidance on adjusting figures to examine the sensitivity of the model to its
Energy and carbon embodied in the international trade of Brazil. An input-output approach
International Nuclear Information System (INIS)
Machado, G; Schaeffer, R.; Worrell, E.
2001-01-01
All goods and services produced in an economy are directly and/or indirectly associated with energy use and, according to the type of fuel utilized, with CO2 emissions as well. International trade is an important factor in shaping the industrial structure of a country and, consequently, in affecting a country's energy use and CO2 emissions. This study applies input-output techniques to the Brazilian economy to evaluate the total impacts of international trade on its energy use and CO2 emissions. A commodity-by-industry IO model in hybrid units (energy commodities in physical units and non-energy commodities in monetary units) is applied to the Brazilian economy in 1995. Results show that total energy embodied in the exports of non-energy goods of Brazil equals 831 PJ, while total carbon embodied is 13.5 MtC. These amounts are larger than the relevant amounts embodied in the imports of non-energy goods, respectively 679 PJ and 9.9 MtC. These figures are better understood by contrasting them with the total energy use and the corresponding total carbon emissions of the Brazilian economy in 1995 estimated by this work: 6781 PJ and 99.4 MtC, respectively. This means that international inflows and outflows of energy embodied in non-energy goods are in the order of 10 and 12% of the total energy use, while inflows and outflows of carbon embodied in non-energy goods are approximately 10 and 14% of the corresponding total carbon emissions of the Brazilian economy in 1995. The general picture is that Brazil is not only a net exporter of energy (153 PJ) and of carbon (3.6 MtC) embodied in the non-energy goods internationally traded by the country in 1995, but also that each dollar earned with exports embodied 40% more energy and 56% more carbon than each dollar spent on imports. These findings suggest that Brazilian policy-makers should be concerned about the extra impacts international trade policy may have on energy use and carbon emissions of the country. 71 refs
Directory of Open Access Journals (Sweden)
Desi Arianti
2014-12-01
Full Text Available Bukittinggi city is one of the city located in the province of West Sumatra . Although it does not have the potential of natural resources that can be exploited , Bukittinggi has another potential, which is a beautiful natural conditions, the air is cool, has a historic heritage places, and is located in a strategic position potentially make this city as tourists visiting the area. Because of the potential of the tourism sector serve as a leading sector in the city of Bukittinggi, which is expected to be the main driver of the city economy. This research was conducted with input-output analysis approach , to examine how the influence of the tourism sector and linkages with other sectors of the economy of the town of Bukittinggi. Moreover it will be seen also how the spatial effect of the tourism sector on the pattern and structure of urban space Bukittinggi. The influence of the tourism sector to the economy of Bukittinggi shows the role of the tourism sector to the total demand is 40.86% when grouped into the business field of agriculture and mining sector, industrial sector, tourism sector and the service sector. Linkages with other sectors of the tourism sector seen from the spread of the power index and the degree of sensitivity, all sectors related to tourism activities have spread of power index > 1. But the degree of sensitivity index > 1 only occurs in large & retail trade sector and the transport, while the hotel secto , restaurants and entertainment and recreation has index < 1. Multiplier effect of all relevant sectors of tourism activities have a relatively large effect on both the output multiplier effects, household income and employment. Application of financial input scenarios, showing the influence of the tourism sector on the economy will be larger Bukittinggi if allocated greater financial inputs to the sectors of tourism, both in the form of government spending and investment spending. The existence of
Sample-Based Motion Planning in High-Dimensional and Differentially-Constrained Systems
2010-02-01
path planning and motion primitives to enable crawling gaits on rough terrain e.g. [Rebula et al., 2007, Kolter et al., 2008,Pongas et al., 2007,Ratliff...demonstrating robust planning and locomotion over quite challenging terrain (e.g., [Rebula et al., 2007, Kolter et al., 2008, Pongas et al., 2007, Zucker, 2009...and Systems. [ Kolter et al., 2008] Kolter , J. Z., Rodgers, M. P., and Ng, A. Y. (2008). A control architecture for quadruped locomotion over rough
Influence of active dendritic currents on input-output processing in spinal motoneurons in vivo.
Lee, R H; Kuo, J J; Jiang, M C; Heckman, C J
2003-01-01
The extensive dendritic tree of the adult spinal motoneuron generates a powerful persistent inward current (PIC). We investigated how this dendritic PIC influenced conversion of synaptic input to rhythmic firing. A linearly increasing, predominantly excitatory synaptic input was generated in triceps ankle extensor motoneurons by slow stretch (duration: 2-10 s) of the Achilles tendon in the decerebrate cat preparation. The firing pattern evoked by stretch was measured by injecting a steady current to depolarize the cell to threshold for firing. The effective synaptic current (I(N), the net synaptic current reaching the soma of the cell) evoked by stretch was measured during voltage clamp. Hyperpolarized holding potentials were used to minimize the activation of the dendritic PIC and thus estimate stretch-evoked I(N) for a passive dendritic tree (I(N,PASS)). Depolarized holding potentials that approximated the average membrane potential during rhythmic firing allowed strong activation of the dendritic PIC and thus resulted in marked enhancement of the total stretch-evoked I(N) (I(N,TOT)). The net effect of the dendritic PIC on the generation of rhythmic firing was assessed by plotting stretch-evoked firing (strong PIC activation) versus stretch-evoked I(N,PASS) (minimal PIC activation). The gain of this input-output function for the neuron (I-O(N)) was found to be ~2.7 times as high as for the standard injected frequency current (F-I) function in low-input conductance neurons. However, about halfway through the stretch, firing rate tended to become constant, resulting in a sharp saturation in I-O(N) that was not present in F-I. In addition, the gain of I-O(N) decreased sharply with increasing input conductance, resulting in much lower stretch-evoked firing rates in high-input conductance cells. All three of these phenomena (high initial gain, saturation, and differences in low- and high-input conductance cells) were also readily apparent in the differences between
Input/output manual of light water reactor fuel analysis code FEMAXI-7 and its related codes
Energy Technology Data Exchange (ETDEWEB)
Suzuki, Motoe; Udagawa, Yutaka; Nagase, Fumihisa [Japan Atomic Energy Agency, Nuclear Safety Research Center, Tokai, Ibaraki (Japan); Saitou, Hiroaki [ITOCHU Techno-Solutions Corporation, Tokyo (Japan)
2013-10-15
A light water reactor fuel analysis code FEMAXI-7 has been developed, as an extended version from the former version FEMAXI-6, for the purpose of analyzing the fuel behavior in normal conditions and in anticipated transient conditions. Numerous functional improvements and extensions have been incorporated in FEMAXI-7, which are fully disclosed in the code model description published in the form of another JAEA-Data/Code report. The present manual, which is the very counterpart of this description document, gives detailed explanations of files and operation method of FEMAXI-7 code and its related codes, methods of input/output, sample Input/Output, methods of source code modification, subroutine structure, and internal variables in a specific manner in order to facilitate users to perform fuel analysis by FEMAXI-7. (author)
Input/output manual of light water reactor fuel analysis code FEMAXI-7 and its related codes
International Nuclear Information System (INIS)
Suzuki, Motoe; Udagawa, Yutaka; Nagase, Fumihisa; Saitou, Hiroaki
2013-10-01
A light water reactor fuel analysis code FEMAXI-7 has been developed, as an extended version from the former version FEMAXI-6, for the purpose of analyzing the fuel behavior in normal conditions and in anticipated transient conditions. Numerous functional improvements and extensions have been incorporated in FEMAXI-7, which are fully disclosed in the code model description published in the form of another JAEA-Data/Code report. The present manual, which is the very counterpart of this description document, gives detailed explanations of files and operation method of FEMAXI-7 code and its related codes, methods of input/output, sample Input/Output, methods of source code modification, subroutine structure, and internal variables in a specific manner in order to facilitate users to perform fuel analysis by FEMAXI-7. (author)
Cavaglieri, Daniele; Bewley, Thomas
2015-04-01
Implicit/explicit (IMEX) Runge-Kutta (RK) schemes are effective for time-marching ODE systems with both stiff and nonstiff terms on the RHS; such schemes implement an (often A-stable or better) implicit RK scheme for the stiff part of the ODE, which is often linear, and, simultaneously, a (more convenient) explicit RK scheme for the nonstiff part of the ODE, which is often nonlinear. Low-storage RK schemes are especially effective for time-marching high-dimensional ODE discretizations of PDE systems on modern (cache-based) computational hardware, in which memory management is often the most significant computational bottleneck. In this paper, we develop and characterize eight new low-storage implicit/explicit RK schemes which have higher accuracy and better stability properties than the only low-storage implicit/explicit RK scheme available previously, the venerable second-order Crank-Nicolson/Runge-Kutta-Wray (CN/RKW3) algorithm that has dominated the DNS/LES literature for the last 25 years, while requiring similar storage (two, three, or four registers of length N) and comparable floating-point operations per timestep.
Attavanich, Witsanu; Mungkung, Rattanawan; Mahathanaseth, Itthipong; Sanglestsawai, Santi; Jirajari, Athiwatr
2016-01-01
There is no indicator measuring Thailand’s green growth by valuing the resource degradation and environmental damage costs. This article aims to estimate Thailand’s green gross domestic (GDP) that takes into account environmental damage costs with the detailed analysis on the agricultural sector using the Economic Input Output - Life Cycle Assessment (EIO-LCA) approach. The representative product in each sector was selected based on the available life cycle inventory data, economic values and...
International Nuclear Information System (INIS)
Abootorabi Zarchi, H.; Arab Markadeh, Gh.R.; Soltani, J.
2010-01-01
In this paper, a nonlinear speed tracking controller is introduced for three-phase synchronous reluctance motor (SynRM) on the basis of input-output feedback linearization (IOFL), considering the different control strategies (maximum torque per Ampere, high efficiency and minimum KVA rating for the inverter) related to this motor. The proposed control approach is capable of decoupling control of stator flux and motor generated torque. The validity and effectiveness of the method is verified by simulation and experimental results.
Zhao, Yang; Onat, Nuri Cihat; Küçükvar, Murat; Tatari, Ömer
2016-01-01
Due to frequent stop-and-go operation and long idling periods when driving in congested urban areas, the electrification of commercial delivery trucks has become an interesting topic nationwide. In this study, environmental impacts of various alternative delivery trucks including battery electric, diesel, diesel-electric hybrid, and compressed natural gas trucks are analyzed. A novel life cycle assessment method, an environmentally-extended multi-region input-output analysis, is utilized to c...
CO2 emissions embodied in China-US trade: Input-output analysis based on the emergy/dollar ratio
International Nuclear Information System (INIS)
Du Huibin; Guo Jianghong; Mao Guozhu; Smith, Alexander M.; Wang Xuxu; Wang, Yuan
2011-01-01
To gain insight into changes in CO 2 emissions embodied in China-US trade, an input-output analysis based on the emergy/dollar ratio (EDR) is used to estimate embodied CO 2 emissions; a structural decomposition analysis (SDA) is employed to analyze the driving factors for changes in CO 2 emissions embodied in China's exports to the US during 2002-2007. The results of the input-output analysis show that net export of CO 2 emissions increased quickly from 2002 to 2005 but decreased from 2005 to 2007. These trends are due to a reduction in total CO 2 emission intensity, a decrease in the exchange rate, and small imports of embodied CO 2 emissions. The results of the SDA demonstrate that total export volume was the largest driving factor for the increase in embodied CO 2 emissions during 2002-2007, followed by intermediate input structure. Direct CO 2 emissions intensity had a negative effect on changes in embodied CO 2 emissions. The results suggest that China should establish a framework for allocating emission responsibilities, enhance energy efficiency, and improve intermediate input structure. - Highlights: → An input-output analysis based on the emergy/dollar ratio estimated embodied CO 2 . → A structural decomposition analysis analyzed the driving factors. → Net export of CO 2 increased from 2002 to 2005 but decreased from 2005 to 2007. → Total export volume was the largest driving factor. → A framework for allocating emission responsibilities.
Clustering high dimensional data
DEFF Research Database (Denmark)
Assent, Ira
2012-01-01
High-dimensional data, i.e., data described by a large number of attributes, pose specific challenges to clustering. The so-called ‘curse of dimensionality’, coined originally to describe the general increase in complexity of various computational problems as dimensionality increases, is known...... to render traditional clustering algorithms ineffective. The curse of dimensionality, among other effects, means that with increasing number of dimensions, a loss of meaningful differentiation between similar and dissimilar objects is observed. As high-dimensional objects appear almost alike, new approaches...... for clustering are required. Consequently, recent research has focused on developing techniques and clustering algorithms specifically for high-dimensional data. Still, open research issues remain. Clustering is a data mining task devoted to the automatic grouping of data based on mutual similarity. Each cluster...
Directory of Open Access Journals (Sweden)
1992-01-01
sistema agroalimenticio de este país. AGRICULTURAL POLICIES AND AGRO-INDUSTRY STRUCTURES: AN APPROACH FROM CHILEAN INPUT-OUTPUT SHEMES. The determination of certain agro-export world power nations to free international agro-feeding exchanges with the purpose to accelerate economic growth and optimize the employment of productive factors, is opposed to the protection and normative policies effective in many countries where agriculture has to accomplish functions, other than those related to only provide consumer or exportation goods, like: self-sufficiency or self-guarantee in the production of foods, employment stability, space regulation, industrial development. Integrated development or re-orientation of the various procedures over a reduced number of production networks, this is in our opinion, the real scope of the new world order related to agriculture. The purpose of this information is to propose -from the analysis in the input-output tables- a methodology which grants an impact acknowledgement of external exchanges over internal structures of the agro-alimentary systems. We promote the hypothesis that indiscriminate application of liberal policies -mainly agro-export-led- leads to the homogenization of techniques, specialization of agriculture and the production networks and concludes finally, to the extraversion of economy. A well-oriented protection leads otherwise, to the diversification of production and inter-industrial exchanges, and contributes to the structure of agro-industrial systems, auspicious to the diffusion of technical progress and the internationalization of the economic growth production. The analysis of the chilean case at a long term basis, is specially relevant to this regard. The new liberal industrialization policies based on the exportation implemented in Chile after 1973 led in a certain way, to the disorganization of the agro-alimentary system in this country.
Sherwood, John; Clabeaux, Raeanne; Carbajales-Dale, Michael
2017-10-01
We developed a physically-based environmental account of US food production systems and integrated these data into the environmental-input-output life cycle assessment (EIO-LCA) model. The extended model was used to characterize the food, energy, and water (FEW) intensities of every US economic sector. The model was then applied to every Bureau of Economic Analysis metropolitan statistical area (MSA) to determine their FEW usages. The extended EIO-LCA model can determine the water resource use (kGal), energy resource use (TJ), and food resource use in units of mass (kg) or energy content (kcal) of any economic activity within the United States. We analyzed every economic sector to determine its FEW intensities per dollar of economic output. This data was applied to each of the 382 MSAs to determine their total and per dollar of GDP FEW usages by allocating MSA economic production to the corresponding FEW intensities of US economic sectors. Additionally, a longitudinal study was performed for the Los Angeles-Long Beach-Anaheim, CA, metropolitan statistical area to examine trends from this singular MSA and compare it to the overall results. Results show a strong correlation between GDP and energy use, and between food and water use across MSAs. There is also a correlation between GDP and greenhouse gas emissions. The longitudinal study indicates that these correlations can shift alongside a shifting industrial composition. Comparing MSAs on a per GDP basis reveals that central and southern California tend to be more resource intensive than many other parts of the country, while much of Florida has abnormally low resource requirements. Results of this study enable a more complete understanding of food, energy, and water as key ingredients to a functioning economy. With the addition of the food data to the EIO-LCA framework, researchers will be able to better study the food-energy-water nexus and gain insight into how these three vital resources are interconnected
Energy Technology Data Exchange (ETDEWEB)
Hoekstra, R.
2003-10-01
Economic processes generate a variety of material flows, which cause resource problems through the depletion of natural resources and environmental issues due to the emission of pollutants. This thesis presents an analytical method to study the relationship between the monetary economy and the 'physical economy'. In particular, this method can assess the impact of structural change in the economy on physical throughput. The starting point for the approach is the development of an elaborate version of the physical input-output table (PIOT), which acts as an economic-environmental accounting framework for the physical economy. In the empirical application, hybrid-unit input-output (I/O) tables, which combine physical and monetary information, are constructed for iron and steel, and plastic products for the Netherlands for the years 1990 and 1997. The impact of structural change on material flows is analyzed using Structural Decomposition Analysis (SDA), whic specifies effects such as sectoral shifts, technological change, and alterations in consumer spending and international trade patterns. The study thoroughly reviews the application of SDA to environmental issues, compares the method with other decomposition methods, and develops new mathematical specifications. An SDA is performed using the hybrid-unit input-output tables for the Netherlands. The results are subsequently used in novel forecasting and backcasting scenario analyses for the period 1997-2030. The results show that dematerialization of iron and steel, and plastics, has generally not occurred in the recent past (1990-1997), and will not occur, under a wide variety of scenario assumptions, in the future (1997-2030)
International Nuclear Information System (INIS)
Hoekstra, R.
2003-01-01
Economic processes generate a variety of material flows, which cause resource problems through the depletion of natural resources and environmental issues due to the emission of pollutants. This thesis presents an analytical method to study the relationship between the monetary economy and the 'physical economy'. In particular, this method can assess the impact of structural change in the economy on physical throughput. The starting point for the approach is the development of an elaborate version of the physical input-output table (PIOT), which acts as an economic-environmental accounting framework for the physical economy. In the empirical application, hybrid-unit input-output (I/O) tables, which combine physical and monetary information, are constructed for iron and steel, and plastic products for the Netherlands for the years 1990 and 1997. The impact of structural change on material flows is analyzed using Structural Decomposition Analysis (SDA), whic specifies effects such as sectoral shifts, technological change, and alterations in consumer spending and international trade patterns. The study thoroughly reviews the application of SDA to environmental issues, compares the method with other decomposition methods, and develops new mathematical specifications. An SDA is performed using the hybrid-unit input-output tables for the Netherlands. The results are subsequently used in novel forecasting and backcasting scenario analyses for the period 1997-2030. The results show that dematerialization of iron and steel, and plastics, has generally not occurred in the recent past (1990-1997), and will not occur, under a wide variety of scenario assumptions, in the future (1997-2030)
Determination of input/output characteristics of full-bridge AC/DC/DC converter for arc welding
Stefanov, Goce; Karadzinov, Ljupco; Sarac, Vasilija; Cingoski, Vlatko; Gelev, Saso
2016-01-01
This paper describes the design and practical implementation of AC/DC/DC converter in mode of arc welding. An analysis of the operation of AC/DC/DC converter and its input/output characteristics are determined with computer simulations. The practical part is consisted of AC/DC/DC converter prototype for arc welding with output power of 3 kW and switching frequency of 64 kHz. The operation of AC/DC/DC converter is validated with experimental measurements.
Directory of Open Access Journals (Sweden)
Jalalifar Mehran
2007-01-01
Full Text Available In this paper using adaptive backstepping approach an adaptive rotor flux observer which provides stator and rotor resistances estimation simultaneously for induction motor used in series hybrid electric vehicle is proposed. The controller of induction motor (IM is designed based on input-output feedback linearization technique. Combining this controller with adaptive backstepping observer the system is robust against rotor and stator resistances uncertainties. In additional, mechanical components of a hybrid electric vehicle are called from the Advanced Vehicle Simulator Software Library and then linked with the electric motor. Finally, a typical series hybrid electric vehicle is modeled and investigated. Various tests, such as acceleration traversing ramp, and fuel consumption and emission are performed on the proposed model of a series hybrid vehicle. Computer simulation results obtained, confirm the validity and performance of the proposed IM control approach using for series hybrid electric vehicle.
Input-output Conformance Testing for Channel-based Service Connectors
N. Kokash (Natallia); F. Arbab (Farhad); B. Changizi (Behnaz); L. Makhnist; L. Aceto (Luca); M.R. Mousavi
2011-01-01
htmlabstractService-based systems are software systems composed of autonomous components or services provided by different vendors, deployed on remote machines and accessible through the web. One of the challenges of modern software engineering is to ensure that such a system behaves as intended
International Nuclear Information System (INIS)
Rhee, Hae-Chun; Chung, Hyun-Sik
2006-01-01
This paper is intended to analyze CO 2 transmission between Japan and South Korea through international trade based on 1990 and 1995 international input-output data. It applied a residual-free structural decomposition method proposed by Chung and Rhee [Chung, H.S., Rhee, H.C., 2001. A residual-free decomposition of the sources of carbon dioxide emissions: a case of the Korean industries. Energy 26 (1), 15-30] to emission-related international input-output analysis for the first time in the decomposition studies. This paper is a case study regarding the manner and the extent to which CO 2 emissions are influenced by international trade between Japan (an Annex I country) and South Korea (a non-Annex I country), which is of particular interest for the carbon leakage issue. In this paper, we attempted to show which factors contributed to the changes in emission of the major greenhouse gas in South Korea and Japan. The changes in emission are analyzed in terms of emission intensity, input techniques, demand composition, and trade structures. According to our analysis, South Korea, a non-Annex I country, has more energy-intensive production structures than Japan, an Annex I country. South Korea's trade pattern with Japan reflects these production features, resulting in the Korea's comparative advantage in emission intensive products, though the degree has somewhat mitigated in 1995 compared to 1990. (author)
Directory of Open Access Journals (Sweden)
Lu Jing
2017-01-01
Full Text Available High-technology enterprises play the leader role in the regional economic progress, but nowadays technological resources have many problems such as division, separation and dispersing. It’s an urgent problem to be solved that how to evaluate input-output productivity of technological resources towards industries and regions scientifically and efficiently. Firstly the article analyzes the input-output efficiency status of technological resources at home and abroad. Then high-technology enterprises in 29 provinces, as the subject of evaluation, are analyzed for their operation efficiency by DEA. The article states the suggestions like balanced development among regions and reasonable structure of input and output by comparing the differences among regions. And the article estimates the technological resources configuration efficiency of 5 leader industries and explains the developmental characteristics and direction among industries. And on these bases the article conducts hypothesis testing for inner elements which might have an influence on the operational efficiency by Tobit model. Finally, the paper proposes many suggestions to the benefits of promoting the productivity of high-technology enterprise according to the comprehensive analysis.
Directory of Open Access Journals (Sweden)
Anggari Marya Kresnowati
2016-11-01
Full Text Available This study aimed to (1 analyze the relationship the manufacturing sector and the trade, hotel, and restaurant sector with other sectors in East Java, (2 to analyze the economic impact caused the two sectors based on the multiplier effect, (3 and analyze the economic impact caused by these two sectors if there additional investment funds. This study uses data analysis input output 2010 East Java 19x19 aggregation sector.The results indicate that base metals subsector has the highest linkages to other sectors. Based on household income multiplier effect, trade subsector has the greatest multiplier. Employment multiplier in trade and industrial sectors are in medium rank. This is indicates that the labor has been absorbed well in both sectors. The output multiplier effect, subsector non-metal goods, except petroleum and coal has the highest multiplier. The last, according to the analysis of investment injection simulations Input-Output East Java in 2010, subsector other processing industries has a best value added. Overall, the manufacturing sector has a better influence to East Java's economy than trade, hotel, and restaurant sector.
International Nuclear Information System (INIS)
Mayer, R.
1989-01-01
Forest damage and decline are the consequence of several stress factors acting upon forest ecosystems in various combinations and degrees. Impact of atmospheric pollutants is certainly one of the most prominent of these factors. Regional comparion is facilitated by considering groups of atmospheric substances. We distinguish: 1. Acids and acidifying substances, 2. Heavy metals and 3. Nutrients: N, P, K, Ca, Mg, S. Forest decline has to be recognized as an expression of changes within the forest ecosystem, changes which must be accompanied by a non-steady state of the material balance. The best way to investigate changes in the material balance is to look at input and output of matter to the ecosystems. A positive balance (input > output) over a period of more than one year means accumulation, negative balance (input < output) means depletion of a substance. Based upon several case studies (Subjects I, K), we come to a typification of the material balance at any individual site which is defined by the immission/deposition situation on the one hand, by the geological-pedological site characteristics on the other hand. (orig.VT)
Directory of Open Access Journals (Sweden)
Mohammad Nowbakht
2015-08-01
Full Text Available In the present study, the comparative effects of comprehensible input, output and corrective feedback on the receptive acquisition of L2 vocabulary items were investigated. Two groups of beginning EFL learners participated in the study. The control group received comprehensible input only, while the experimental group received input and was required to produce written output. They also received corrective feedback on their lexical errors if any. This could result in the production of modified output. The results of the study indicated that (a the group which produced output and received feedback (if necessary outperformed the group which only received input in the post-test, (b within the experimental group, feedback played a greater role in learners’ better performance than output, (c also a positive correlation between the amount of feedback an individual learner received, and his overall performance in the post-test; and also between the amount of feedback given for a specific word and the correct responses given to its related item in the post-test was found. The findings of this study provide evidence for the role of output production along with receiving corrective feedback in enhancing L2 processing by drawing further L2 learners’ attention to their output which in turn may result in improving their receptive acquisition of L2 words. Furthermore, as the results suggested, feedback made a more contribution to L2 development than output. Keywords: comprehensible input, output, interaction, corrective feedback, modified output, receptive vocabulary acquisition
Spectral analysis of the EEG during halothane anaesthesia: Input-output relations
Silva, F.H. Lopes da; Smith, N. Ty; Zwart, Aart; Nichols, W.W.
1. 1. The “Halothane-brain compartment” system was investigated in dogs. The input was the inspired concentration of Halothane. The output was the intensity of EEG spectral components. The EEG was analysed by a hybrid system (analogue filters and digital integration in a small computer). For the
Intelligent input/output subsystem for CAMAC and FASTBUS. Phase 1
International Nuclear Information System (INIS)
Rajala, R.E.
1986-07-01
The authors have addressed the need for flexible and easy-to-use data-acquisition equipment for the nuclear/energy physics fields and others requiring high data rates and real-time data acquisition. Presented is the design of an intelligent, expandible I/O system using CAMAC standards and the new generation Digital Equipment Corporation VAXBI bus. The system offers a potential tenfold increase in the speed of data acquisition over current systems. A concentrated design effort is presented for the CAMAC Parallel Branch. However, the basic central processing unit, memory, and VAXBI configuration can also be used for CAMAC Serial, IEEE-488, and FASTBUS. The system uses a microprocessor-based controller, the J11, that preprocesses data prior to transmission to the VAXBI. This frees the central processor for other tasks. The design eliminates the need for special, dedicated design hardware and provides a software migration path for existing systems currently in use
Tempo: A Toolkit for the Timed Input/Output Automata Formalism
National Research Council Canada - National Science Library
Lynch, Nancy A; Shvartsman, Alex Allister
2008-01-01
Report developed under STTR contract for topic AFO4-T023. This Phase II project developed an integrated development environment, called Tempo, for specifying, analyzing, and verifying complex distributed system designs...
A controls engineering approach for analyzing airplane input-output characteristics
Arbuckle, P. Douglas
1991-01-01
An engineering approach for analyzing airplane control and output characteristics is presented. State-space matrix equations describing the linear perturbation dynamics are transformed from physical coordinates into scaled coordinates. The scaling is accomplished by applying various transformations to the system to employ prior engineering knowledge of the airplane physics. Two different analysis techniques are then explained. Modal analysis techniques calculate the influence of each system input on each fundamental mode of motion and the distribution of each mode among the system outputs. The optimal steady state response technique computes the blending of steady state control inputs that optimize the steady state response of selected system outputs. Analysis of an example airplane model is presented to demonstrate the described engineering approach.
GLOBAL MULTIREGIONAL INPUT-OUTPUT FRAMEWORKS : AN INTRODUCTION AND OUTLOOK INTRODUCTION
Tukker, Arnold; Dietzenbacher, Erik
2013-01-01
This review is the introduction to a special issue of Economic Systems Research on the topic of global multiregional inputoutput (GMRIO) tables, models, and analysis. It provides a short historical context of GMRIO development and its applications (many of which deal with environmental extensions)
CSIR Research Space (South Africa)
Mc
2012-07-01
Full Text Available stream_source_info McLaren_2012.pdf.txt stream_content_type text/plain stream_size 2190 Content-Encoding ISO-8859-1 stream_name McLaren_2012.pdf.txt Content-Type text/plain; charset=ISO-8859-1 High dimensional... entanglement M. McLAREN1,2, F.S. ROUX1 & A. FORBES1,2,3 1. CSIR National Laser Centre, PO Box 395, Pretoria 0001 2. School of Physics, University of the Stellenbosch, Private Bag X1, 7602, Matieland 3. School of Physics, University of Kwazulu...
Economy-wide material input/output and dematerialization analysis of Jilin Province (China).
Li, MingSheng; Zhang, HuiMin; Li, Zhi; Tong, LianJun
2010-06-01
In this paper, both direct material input (DMI) and domestic processed output (DPO) of Jilin Province in 1990-2006 were calculated and then based on these two indexes, a dematerialization model was established. The main results are summarized as follows: (1) both direct material input and domestic processed output increase at a steady rate during 1990-2006, with average annual growth rates of 4.19% and 2.77%, respectively. (2) The average contribution rate of material input to economic growth is 44%, indicating that the economic growth is visibly extensive. (3) During the studied period, accumulative quantity of material input dematerialization is 11,543 x 10(4) t and quantity of waste dematerialization is 5,987 x10(4) t. Moreover, dematerialization gaps are positive, suggesting that the potential of dematerialization has been well fulfilled. (4) In most years of the analyzed period, especially 2003-2006, the economic system of Jilin Province represents an unsustainable state. The accelerated economic growth relies mostly on excessive resources consumption after the Revitalization Strategy of Northeast China was launched.
Replacement of input/output cables of the digital control computers at Gentilly 2
International Nuclear Information System (INIS)
Melancon, P.; Lafreniere, P.
1991-01-01
During the 1990 annual outage at Gentilly 2 the Preventive Maintenance Program inspections on the digital control computers (DCCs) revealed an alarming degradation of cable insulation at several locations. It was found that approximately 20% of the cable connector assemblies inspected showed signs of degradation. These findings raised the concern of an increased risk of random short-circuit faults at the very heart of the station control system. Given the excellent reliability of the Gentilly 2 DCCs and their inherent design robustness, it was decided to proceed with the replacement of all of the complete cable connector assemblies within a reasonable time frame. It is planned to replace all assemblies of DCCX and DCCY during the 1991 annual outage. The degradation of the insulation was traced to a material incompatibility problem originating during cable manufacture. A migration of the plastifier contained in the PVC of the transparent sheaths, surrounding many of the cable conductors to terminal block connections, resulted in the chemical attack of the conductor insulation. This paper summarizes the problem identification and disposition process followed by Gentilly 2 Technical Unit personnel
DEFF Research Database (Denmark)
Kjær, Louise Laumann; Høst-Madsen, Niels Karim Høst-Madsen; Schmidt, Jannick H.
2015-01-01
An increasing number of companies are expanding their environmental impact reduction targets and strategies to include their supply chains or whole product life cycles. In this paper, we demonstrate and evaluate an approach, where we used a hybrid Environmental Input-Output (EIO) database...... as a basis for corporate and product environmental footprint accounts, including the entire supply chain. We present three cases, where this approach was applied. Case study 1 describes the creation of total corporate carbon footprint accounts for three Danish regional healthcare organisations. In case study...... a foundation for decision-making within reasonable time and cost, and for companies with a large upstream environmental footprint, the analysis supports advancing their sustainability agenda to include supply chain impacts. However, there are implications when going from screening to implementing the results...
International Nuclear Information System (INIS)
Eickelkamp, Timo
2013-01-01
Capital goods are not normally taken into consideration in assessing the sustainability of products on the basis of life cycle assessments. Capital goods are machines and buildings that are used for production purposes over the course of a product's life cycle. Using an offshore wind farm as an example the present study shows how capital goods can be taken into account via a methodologically expanded input-output analysis and thus factored into the life cycle assessment. Besides comparing different calculation methods the author performs a detailed analysis of those parameters with the greatest influence on the outcome. The results show that capital goods have a substantial impact on sustainability in both energy-related and environmental terms. Capital goods should therefore be taken into consideration in life cycle assessments.
DEFF Research Database (Denmark)
Jepsen, Morten Løve; Dau, Torsten
To partly characterize the function of cochlear processing in humans, the basilar membrane (BM) input-output function can be estimated. In recent studies, forward masking has been used to estimate BM compression. If an on-frequency masker is processed compressively, while an off-frequency masker...... is transformed more linearly, the ratio between the slopes of growth of masking (GOM) functions provides an estimate of BM compression at the signal frequency. In this study, this paradigm is extended to also estimate the knee-point of the I/O-function between linear rocessing at low levels and compressive...... processing at medium levels. If a signal can be masked by a low-level on-frequency masker such that signal and masker fall in the linear region of the I/O-function, then a steeper GOM function is expected. The knee-point can then be estimated in the input level region where the GOM changes significantly...
Input/output manual of light water reactor fuel performance code FEMAXI-7 and its related codes
Energy Technology Data Exchange (ETDEWEB)
Suzuki, Motoe; Udagawa, Yutaka; Nagase, Fumihisa [Japan Atomic Energy Agency, Nuclear Safety Research Center, Tokai, Ibaraki (Japan); Saitou, Hiroaki [ITOCHU Techno-Solutions Corp., Tokyo (Japan)
2012-07-15
A light water reactor fuel analysis code FEMAXI-7 has been developed for the purpose of analyzing the fuel behavior in normal conditions and in anticipated transient conditions. Numerous functional improvements and extensions have been incorporated in FEMAXI-7, which has been fully disclosed in the code model description published recently as JAEA-Data/Code 2010-035. The present manual, which is the counterpart of this description, gives detailed explanations of operation method of FEMAXI-7 code and its related codes, methods of Input/Output, methods of source code modification, features of subroutine modules, and internal variables in a specific manner in order to facilitate users to perform a fuel analysis with FEMAXI-7. This report includes some descriptions which are modified from the original contents of JAEA-Data/Code 2010-035. A CD-ROM is attached as an appendix. (author)
Input/output manual of light water reactor fuel performance code FEMAXI-7 and its related codes
International Nuclear Information System (INIS)
Suzuki, Motoe; Udagawa, Yutaka; Nagase, Fumihisa; Saitou, Hiroaki
2012-07-01
A light water reactor fuel analysis code FEMAXI-7 has been developed for the purpose of analyzing the fuel behavior in normal conditions and in anticipated transient conditions. Numerous functional improvements and extensions have been incorporated in FEMAXI-7, which has been fully disclosed in the code model description published recently as JAEA-Data/Code 2010-035. The present manual, which is the counterpart of this description, gives detailed explanations of operation method of FEMAXI-7 code and its related codes, methods of Input/Output, methods of source code modification, features of subroutine modules, and internal variables in a specific manner in order to facilitate users to perform a fuel analysis with FEMAXI-7. This report includes some descriptions which are modified from the original contents of JAEA-Data/Code 2010-035. A CD-ROM is attached as an appendix. (author)
Modelo Input-Output de Leontief: teoría de grafos frente a estructuras pretopológicas
Directory of Open Access Journals (Sweden)
Amo Saus, Mª Elisa
2001-01-01
Full Text Available Las relaciones intersectoriales presentes en el Modelo Input-Output han sido objeto de numerosos análisis matemáticos. En una primera etapa, y debido a su propio planteamiento como un sistema de ecuaciones lineales, W. Leontief y su escuela, haciendo uso del álgebra lineal y el cálculo matricial, consiguieron computar el vector de producciones totales a partir del vector de demandas finales. Posteriormente, autores como Kuhn (1956 ó R. Dorfman, P. Samuelson y R. Solow (1958 emplearon técnicas de programación lineal en la resolución del modelo. Más tarde, C. Ponsard (1969 y R. Lantner(1974, entre otros, profundizaron en el análisis estructural del modelo Input-Output, mediante técnicas de grafos, asignándole un grafo de transferencia. En las VIII Jornadas de ASEPUMA, nosotras mismas, siguiendo el planteamiento de M. Mougeot, G. Duru y J. P. Auray (1977, expusimos cómo ciertas relaciones de interdependencia definidas entre las ramas de producción inducían unas estructuras pretoplógicas que permitían determinar su propensión a comprar o vender al resto. Analizados en profundidad estos dos últimos métodos de análisis, descubrimos grandes analogías en ambos planteamientos en sus aportaciones al estudio de las relaciones de interdependencia en el modelo, y que ahora tratamos de exponer brevemente.
International Nuclear Information System (INIS)
Wu, Kuei-Yen; Wu, Jung-Hua; Huang, Yun-Hsun; Fu, Szu-Chi; Chen, Chia-Yon
2016-01-01
Most existing literature focuses on the direct rebound effect on the demand side for consumers. This study analyses direct and indirect rebound effects in Taiwan's industry from the perspective of producers. However, most studies on the producers' viewpoint may overlook inter-industry linkages. This study applies a supply-driven input-output model to quantify the magnitude of rebound effects by explicitly considering inter-industry linkages. Empirical results showed that total rebound effects for most Taiwan's sectors were less than 10% in 2011. A comparison among the sectors yields that sectors with lower energy efficiency had higher direct rebound effects, while sectors with higher forward linkages generated higher indirect rebound effects. Taking the Mining sector (S3) as an example, which is an upstream supplier and has high forward linkages; it showed high indirect rebound effects that are derived from the accumulation of additional energy consumption by its downstream producers. The findings also showed that in almost all sectors, indirect rebound effects were higher than direct rebound effects. In other words, if indirect rebound effects are neglected, the total rebound effects will be underestimated. Hence, the energy-saving potential may be overestimated. - Highlights: • This study quantifies rebound effects by a supply-driven input-output model. • For most Taiwan's sectors, total rebound magnitudes were less than 10% in 2011. • Direct rebound effects and energy efficiency were inverse correlation. • Indirect rebound effects and industrial forward linkages were positive correlation. • Indirect rebound effects were generally higher than direct rebound effects.
Liu, Jingjing; Taylor, Mark; Dorreen, Mark
2018-02-01
In the aluminum electrolysis process, new industrial aluminum/electricity power markets demand a new cell technology to extend the cell heat balance and amperage operating window of smelters by shifting the steady states. The current work investigates the responses of lithium-modified bath system when the input/output balance is shifted in a laboratory analogue to the industrial heat balance shift. Li2CO3 is added to the cryolite-AlF3-CaF2-Al2O3 system as a bath modifier. A freeze deposit is formed on a `cold finger' dipped into the bath and investigated by X-ray diffraction analysis and electron probe X-ray microanalysis. The macro- and micro-structure of the freeze lining varies with the bath superheat (bath temperature minus bath liquidus temperature) and an open crystalline layer with entrapped liquid dominates the freeze thickness. Compared with the cryolite-AlF3-CaF2-Al2O3 bath system, the lithium-modified bath freeze is more sensitive to the heat balance shift. This freeze investigation provides primary information to understand the variation of the side ledge in an industrial cell when the lithium-modified bath system is used.
Directory of Open Access Journals (Sweden)
Louise Laumann Kjaer
2015-08-01
Full Text Available An increasing number of companies are expanding their environmental impact reduction targets and strategies to include their supply chains or whole product life cycles. In this paper, we demonstrate and evaluate an approach, where we used a hybrid Environmental Input-Output (EIO database as a basis for corporate and product environmental footprint accounts, including the entire supply chain. We present three cases, where this approach was applied. Case study 1 describes the creation of total corporate carbon footprint accounts for three Danish regional healthcare organisations. In case study 2, the approach was used as basis for an Environmental Profit and Loss account for the healthcare company, Novo Nordisk A/S. Case study 3 used the approach for life cycle assessment of a tanker ship. We conclude that EIO-based analyses offer a holistic view of environmental performance, provide a foundation for decision-making within reasonable time and cost, and for companies with a large upstream environmental footprint, the analysis supports advancing their sustainability agenda to include supply chain impacts. However, there are implications when going from screening to implementing the results, including how to measure and monitor the effect of the different actions. Thus, future research should include more detailed models to support decision-making.
Energy Technology Data Exchange (ETDEWEB)
Tarancon, Miguel Angel; Callejas Albinana, Fernando [Faculty of Law and Social Sciences, Universidad de Castilla - La Mancha, Ronda de Toledo s/n, 13071 Ciudad Real (Spain); Del Rio, Pablo [Institute for Public Policies and Goods (IPP), Centro de Ciencias Humanas y Sociales, CSIC, C/Albasanz 26-28, 28037 Madrid (Spain)
2010-04-15
The production and consumption of electricity is a major source of CO{sub 2} emissions in Europe and elsewhere. In turn, the manufacturing sectors are significant end-users of electricity. In contrast to most papers in the literature, which focus on the supply-side, this study tackles the demand-side of electricity. An input-output approach combined with a sensitivity analysis has been developed to analyse the direct and indirect consumptions of electricity by eighteen manufacturing sectors in fifteen European countries, with indirect electricity demand related to the purchase of industrial products from other sectors which, in turn, require the consumption of electricity in their manufacturing processes. We identify the industrial transactions and sectors, which account for a greater share of electricity demand. In addition, the impact of an electricity price increase on the costs and prices of manufacturing products is simulated through a price model, allowing us to identify those sectors whose manufacturing costs are most sensitive to an increase in the electricity price. (author)
International Nuclear Information System (INIS)
Li, Ke; Jiang, Zhujun
2016-01-01
Facing with the increasing contradiction of economic growth, energy scarcity and environmental deterioration, energy conservation and emissions abatement have been ambitious targets for the Chinese government. Improving energy efficiency through technological advancement is a primary measure to achieve these targets. However, the existence of energy rebound effects may completely or partially offset energy savings associated with technological advancement. This paper adopted a modified input-output model to estimate the economy-wide energy rebound effects across China's economic sectors with the consideration of energy subsidies. The empirical results show that the aggregate rebound effect of China is about 1.9% in 2007–2010, thus technological advancement significantly restrains energy consumption increasing. Removing energy subsidies will cause the aggregate rebound effect declines to 1.53%. Specifically, removing subsidies for coal and nature gas can reduce the rebound effects signifcantly, while removing the subsidies for oil products has a small impact on rebound effect. The existence of rebound effects implies that technological advancement should be cooperated with energy price reform so as to achieve the energy saving target. In addition, the government should consider the diversity of economic sectors and energy types when design the reform schedule. - Highlights: • Rebound effects with the consideration of energy subsidies are estimated in China. • When considering the interactions among sectors, the aggregate rebound effect become small. • Removing subsidies will reduce energy consumption, thereby declining the rebound effects. • Removing subsidies for different energy types has varies effects on rebound effect.
International Nuclear Information System (INIS)
Shu, Guoxiang; Wang, Jianxun; Liu, Guo; Yang, Liya; Luo, Yong; Wang, Shafei
2015-01-01
Broadband operation is of great importance for the applications of travelling wave tubes such as high-data communication and wideband radar. An input/output (I/O) structure operating with broadband property plays a significant role to achieve these applications. In this paper, a Y-type branch waveguide (YTBW) coupler and its improvements are proposed and utilized to construct an extremely wideband I/O structure to ensure the broadband operation for sheet beam travelling wave tubes (SB-TWTs). Cascaded reflection resonators are utilized to improve the isolation characteristic and transmission efficiency. Furthermore, to minimize the reflectivity of the port connected with the RF circuit, wave-absorbing material (WAM) is loaded in the resonator. Simulation results for the YTBW loaded with WAM predict an excellent performance with a 50.2% relative bandwidth for port reflectivity under −15 dB, transmission up to −1.5 dB, and meanwhile isolation under −20 dB. In addition, the coupler has a relatively compact configuration and the beam tunnel can be widened, which is beneficial for the propagation of the electrons. A Q-band YTBW loaded with two reflection resonators is fabricated and microwave tested. Vector network analyzer (VNA) measured results have an excellent agreement with our simulation, which verify our theoretical analysis and simulation calculation
International Nuclear Information System (INIS)
Tarancon, Miguel Angel; Callejas Albinana, Fernando; Del Rio, Pablo
2010-01-01
The production and consumption of electricity is a major source of CO 2 emissions in Europe and elsewhere. In turn, the manufacturing sectors are significant end-users of electricity. In contrast to most papers in the literature, which focus on the supply-side, this study tackles the demand-side of electricity. An input-output approach combined with a sensitivity analysis has been developed to analyse the direct and indirect consumptions of electricity by eighteen manufacturing sectors in fifteen European countries, with indirect electricity demand related to the purchase of industrial products from other sectors which, in turn, require the consumption of electricity in their manufacturing processes. We identify the industrial transactions and sectors, which account for a greater share of electricity demand. In addition, the impact of an electricity price increase on the costs and prices of manufacturing products is simulated through a price model, allowing us to identify those sectors whose manufacturing costs are most sensitive to an increase in the electricity price. (author)
Chen, G. Q.; Chen, Z. M.
2010-11-01
A 135-sector inventory and embodiment analysis for carbon emissions and resources use by Chinese economy 2007 is presented in this paper by an ecological input-output modeling based on the physical entry scheme. Included emissions and resources belong to six categories as: (1) greenhouse gas (GHG) in terms of CO 2, CH 4, and N 2O; (2) energy in terms of coal, crude oil, natural gas, hydropower, nuclear power, and firewood; (3) water in terms of freshwater; (4) exergy in terms of coal, crude oil, natural gas, grain, bean, tuber, cotton, peanut, rapeseed, sesame, jute, sugarcane, sugar beet, tobacco, silkworm feed, tea, fruits, vegetables, wood, bamboo, pulp, meat, egg, milk, wool, aquatic products, iron ore, copper ore, bauxite, lead ore, zinc ore, pyrite, phosphorite, gypsum, cement, nuclear fuel, and hydropower; (5) and (6) solar and cosmic emergies in terms of sunlight, wind power, deep earth heat, chemical power of rain, geopotential power of rain, chemical power of stream, geopotential power of stream, wave power, geothermal power, tide power, topsoil loss, coal, crude oil, natural gas, ferrous metal ore, non-ferrous metal ore, non-metal ore, cement, and nuclear fuel. Accounted based on the embodied intensities are carbon emissions and resources use embodied in the final use as rural consumption, urban consumption, government consumption, gross fixed capital formation, change in inventories, and export, as well as in the international trade balance. The resulted database is basic to environmental account of carbon emissions and resources use at various levels.
Directory of Open Access Journals (Sweden)
Jong-Hwan Ko
2014-03-01
Full Text Available This study aims to answer two questions using input-output decomposition analysis: 1 Have emerging Asian economies decoupled? 2 What are the sources of structural changes in gross outputs and value-added of emerging Asian economies related to the first question? The main findings of the study are as follows: First, since 1990, there has been a trend of increasing dependence on exports to extra-regions such as G3 and the ROW, indicating no sign of "decoupling", but rather an increasing integration of emerging Asian countries into global trade. Second, there is a contrasting feature in the sources of structural changes between non-China emerging Asia and China. Dependence of non-China emerging Asia on intra-regional trade has increased in line with strengthening economic integration in East Asia, whereas China has disintegrated from the region. Therefore, it can be said that China has contributed to no sign of decoupling of emerging Asia as a whole.
Compilation of an Embodied CO2 Emission Inventory for China Using 135-Sector Input-Output Tables
Directory of Open Access Journals (Sweden)
Qian Zhang
2015-06-01
Full Text Available A high-quality carbon dioxide (CO2 inventory is the cornerstone of climate change mitigation. Most of the previously reported embodied CO2 inventories in China have no more than 42 sectors, and this limitation may introduce apparent inaccuracy into the analysis at the sector level. To improve the quality of input-output (IO-based CO2 inventories for China, we propose a practical energy allocation approach to link the energy statistics to the 135-sector IO tables for China and compiled a detailed embodied CO2 intensity and inventory for 2007 using a single-region IO model. Interpretation of embodied CO2 intensities by fuel category, direct requirement, and total requirement in the sectors were conducted to identify, from different perspectives, the significant contributors. The total embodied CO2 emissions in 2007 was estimated to be 7.1 Gt and was separated into the industrial sector and final demand sector. Although the total CO2 estimations by the 42-sector and 135-sector analyses are equivalent, the allocations in certain groups of sectors differ significantly. Our compilation methodologies address indirect environmental impacts from industrial sectors, including the public utility and tertiary sectors. This method of interpretation could be utilized for better communication with stakeholders.
International Nuclear Information System (INIS)
Yuan, Chaoqing; Liu, Sifeng; Xie, Naiming
2010-01-01
The dependence on foreign trade increased sharply in China, and therefore Chinese economy is obviously export-oriented. The Global Financial Crisis will impact the Chinese economic growth violently. Chinese government has recently adopted some effective measures to fight against the Global Financial Crisis. The most important measure is the 4 trillion Yuan ($586 billion) stimulus plan which was announced on November 9, 2008. This paper discusses the influence on energy consumption and economic growth of Global Financial Crisis and the stimulus plan against it by input-output analysis. The results show that the fall of exports caused by the Global Financial Crisis will lead to a decrease of 7.33% in GDP (Gross Domestic Production) and a reduction of 9.21% in energy consumption; the stimulus plan against the Global Financial Crisis will lead to an increase of 4.43% in economic growth and an increase of 1.83% in energy consumption; In the Global Financial Crisis, energy consumption per unit GDP will fall in China. (author)
International Nuclear Information System (INIS)
Chang Yuan; Ries, Robert J.; Wang Yaowu
2010-01-01
A complete understanding of the resource consumption, embodied energy, and environmental emissions of civil projects in China is difficult due to the lack of comprehensive national statistics. To quantitatively assess the energy and environmental impacts of civil construction at a macro-level, this study developed a 24 sector environmental input-output life-cycle assessment model (I-O LCA) based on 2002 Chinese national economic and environmental data. The model generates an economy-wide inventory of energy use and environmental emissions. Estimates based on the level of economic activity related to planned future civil works in 2015 are made. Results indicate that the embodied energy of construction projects accounts for nearly one-sixth of the total economy's energy consumption in 2007, and may account for approximately one-fifth of the total energy use by 2015. This energy consumption is dominated by coal and oil consumptions. Energy-related emissions are the main polluters of the country's atmosphere and environment. If the industry's energy use and manufacturing techniques remain the same as in 2002, challenges to the goals for total energy consumption in China will appear in the next decade. Thus, effective implementation of efficient energy technologies and regulations are indispensable for achieving China's energy and environmental quality goals.
Energy Technology Data Exchange (ETDEWEB)
Shu, Guoxiang; Wang, Jianxun; Liu, Guo; Yang, Liya; Luo, Yong [School of Physical Electronics, University of Electronic Science and Technology of China, Chengdu 610054 (China); Wang, Shafei [North Electronic Device Research Institution, P.O. Box 947, Beijing 100141 (China)
2015-06-15
Broadband operation is of great importance for the applications of travelling wave tubes such as high-data communication and wideband radar. An input/output (I/O) structure operating with broadband property plays a significant role to achieve these applications. In this paper, a Y-type branch waveguide (YTBW) coupler and its improvements are proposed and utilized to construct an extremely wideband I/O structure to ensure the broadband operation for sheet beam travelling wave tubes (SB-TWTs). Cascaded reflection resonators are utilized to improve the isolation characteristic and transmission efficiency. Furthermore, to minimize the reflectivity of the port connected with the RF circuit, wave-absorbing material (WAM) is loaded in the resonator. Simulation results for the YTBW loaded with WAM predict an excellent performance with a 50.2% relative bandwidth for port reflectivity under −15 dB, transmission up to −1.5 dB, and meanwhile isolation under −20 dB. In addition, the coupler has a relatively compact configuration and the beam tunnel can be widened, which is beneficial for the propagation of the electrons. A Q-band YTBW loaded with two reflection resonators is fabricated and microwave tested. Vector network analyzer (VNA) measured results have an excellent agreement with our simulation, which verify our theoretical analysis and simulation calculation.
Nakamura, Shinichiro; Murakami, Shinsuke; Nakajima, Kenichi; Nagasaka, Tetsuya
2008-05-15
The production process of metals such as copper, lead, and zinc is characterized by mutual interconnections and interdependence, as well as by the occurrence of a large number of byproducts, which include precious or rare metals, such as gold, silver, bismuth, and indium. On the basis of the framework of waste input-output (WIO), we present a hybrid 10 model that takes full account of the mutual interdependence among the metal production processes and the interdependence between them and all the other production sectors of the economy as well. The combination of a comprehensive representation of the whole national economy and the introduction of process knowledge of metal production allows for a detailed analysis of different materials-use scenarios under the consideration of full supply chain effects. For illustration, a hypothetical case study of the introduction of lead-free solder involving the production of silver as a byproduct of copper and lead smelting processes was developed and implemented using Japanese data. To meet the increased demand for the recovery and recycling of silver resources from end-of-life products, the final destination of metal silver in terms of products and user categories was estimated, and the target components with the highest silver concentration were identified.
International Nuclear Information System (INIS)
Kerschner, Christian; Hubacek, Klaus
2009-01-01
Given recent developments on energy markets and skyrocketing oil prices, we argue for an urgent need to study the potential effects of world oil production reaching a maximum (Peak Oil) in order to facilitate the development of adaptation policies. We consider input-output (IO) modelling as a powerful tool for this purpose. However, the standard Leontief type model implicitly assumes that all necessary inputs to satisfy a given demand can and will be supplied. This is problematic if the availability of certain key inputs becomes restricted and it is therefore only of limited usefulness for the study of the phenomenon of Peak Oil. Hence this paper firstly reviews two alternative modelling tools within the IO framework: supply-driven and mixed models. The former has been severely criticised for its problematic assumption of perfect factor substitution and perfect elasticity of demand as revealed by Oosterhaven [Oosterhaven J. On the plausibility of the supply-driven IO model. J Reg Sci 1988; 28:203-17. ]. The supply-constrained model on the other hand proved well suited to analyse the quantity dimension of Peak Oil and is therefore applied empirically in the second part of the paper, using data for the UK, Japanese and Chilean economy. Results show how differences in net-oil exporting and net-oil importing countries are clearly visible in terms of final demand. Industries, most affected in all countries, include transportation, electricity production and financial and trade services. (author)
International Nuclear Information System (INIS)
Carballo Penela, Adolfo; Sebastian Villasante, Carlos
2008-01-01
Nowadays, the achievement of sustainable development constitutes an important constraint in the design of energy policies, being necessary the development of reliable indicators to obtain helpful information about the use of energy resources. The ecological footprint (EF) provides a referential framework for the analysis of human demand for bioproductivity, including energy issues. In this article, the theoretical bases of the footprint analysis are described by applying input-output tables of energy to estimate the Galician energy ecological footprint (EEF). It is concluded that the location of highly polluting industries in Galicia makes the Galician EEF quite higher than more developed regions of Spain. The relevance of the outer component of the Galician EEF is also studied. First, available information seems to indicate that the energy incorporated to the trading of manufactured goods would notably increase the Galician consumption of energy. On the other hand, the inclusion of electricity trade in the EEF analysis, including an adjustment, following the same philosophy as with manufactured goods is proposed. This adjustment would substantially reduce the Galician EEF, as the exported electricity widely exceeds the imported one
Chernozhukov, Victor; Hansen, Christian; Spindler, Martin
2016-01-01
In this article the package High-dimensional Metrics (\\texttt{hdm}) is introduced. It is a collection of statistical methods for estimation and quantification of uncertainty in high-dimensional approximately sparse models. It focuses on providing confidence intervals and significance testing for (possibly many) low-dimensional subcomponents of the high-dimensional parameter vector. Efficient estimators and uniformly valid confidence intervals for regression coefficients on target variables (e...
Wang, Wei; Yang, Jiong
With the rapid growth of computational biology and e-commerce applications, high-dimensional data becomes very common. Thus, mining high-dimensional data is an urgent problem of great practical importance. However, there are some unique challenges for mining data of high dimensions, including (1) the curse of dimensionality and more crucial (2) the meaningfulness of the similarity measure in the high dimension space. In this chapter, we present several state-of-art techniques for analyzing high-dimensional data, e.g., frequent pattern mining, clustering, and classification. We will discuss how these methods deal with the challenges of high dimensionality.
Wang, Changjian; Wang, Fei; Zhang, Xinlin; Deng, Haijun
2017-11-01
It is important to analyze the influence mechanism of energy-related carbon emissions from a regional perspective to effectively achieve reductions in energy consumption and carbon emissions in China. Based on the "energy-economy-carbon emissions" hybrid input-output analysis framework, this study conducted structural decomposition analysis (SDA) on carbon emissions influencing factors in Guangdong Province. Systems-based examination of direct and indirect drivers for regional emission is presented. (1) Direct effects analysis of influencing factors indicated that the main driving factors of increasing carbon emissions were economic and population growth. Carbon emission intensity was the main contributing factor restraining carbon emissions growth. (2) Indirect effects analysis of influencing factors showed that international and interprovincial trades significantly affected the total carbon emissions. (3) Analysis of the effects of different final demands on the carbon emissions of industrial sector indicated that the increase in carbon emission arising from international and interprovincial trades is mainly concentrated in energy- and carbon-intensive industries. (4) Guangdong had to compromise a certain amount of carbon emissions during the development of its export-oriented economy because of industry transfer arising from the economic globalization, thereby pointing to the existence of the "carbon leakage" problem. At the same time, interprovincial export and import resulted in Guangdong transferring a part of its carbon emissions to other provinces, thereby leading to the occurrence of "carbon transfer."
International Nuclear Information System (INIS)
Quirion, Philippe
2013-04-01
We study the impact on employment in France of the implementation of the energy transition scenario built by negaWatt (2011), which provides a massive development of energy savings (through measures of sufficiency and energy efficiency) and renewable energy between 2012 and 2050. Compared to 2010, this scenario results in a halving of CO 2 emissions from energy sources in France in 2030 and a division by 16 in 2050, without capture and storage of CO 2 , without implementation of new nuclear power plant and closing existing plants after 40 years of operation at maximum. We calculate the effect on employment of the implementation of this scenario compared to a baseline scenario that extends recent developments and considers the policies already decided. The method used to calculate the effect on employment of each scenario is to calculate the cost of the main technical and organizational options used, to allocate these costs among the 118 branches of the French economy and multiply these costs by the employment content of each branch. The latter is estimated by input-output analysis, which enables the recording of jobs generated by the production of all inputs. One of two scenarios being more expensive than the other, one must take into account the negative effect on employment of funding such costs. For this, it is assumed that this additional cost is borne by households and that they decrease their consumption accordingly by the same amount. This avoids biasing the results in favour of the most expensive scenario. The implementation of negaWatt scenario leads to a positive effect on employment, on the order of 240 000 full-time equivalent jobs in 2020 and 630,000 in 2030. We study the sensitivity of results to assumptions on prices of imported energy, the evolution of labour productivity, the distribution of costs between households and governments, and finally the consumption-savings decision. The effect on employment is largely positive in all cases. (author)
International Nuclear Information System (INIS)
Mongelli, I.; Tassielli, G.; Notarnicola, B.
2006-01-01
In the Kyoto Protocol the absence of Green House Gases (GHGs) commitments of developing countries (non-Annex I) and the more flexible terms of implementation which are allowed to countries shifting toward a market economy (transition economies) naturally lead to the absence or to less constraining national measures and policies of reduction of the GHGs emissions which, in turn, may determine a comparative advantage in the production of the highest energy/carbon intensive commodities for these countries. These arguments are valid also considering the future implementation of the European Emission Allowance Trading Scheme (EATS). Thus, developing countries may become a haven for the production of not environmental-friendly commodities; in this case, the so-called Pollution Haven Hypothesis, stating that due to freer international trade the comparative advantage may change the economic structure and consequently the trade patterns of the countries linked by trade relationships, could occur. This would lead to the increase of the transfers of energy and carbon embodied in traded commodities from developing countries and transition economies toward Kyoto or EATS constrained countries. The aim of this paper is to verify if for Italy, as a Kyoto and EATS complying country, evidence of a change in the trade patterns, occurred on the basis of the Pollution Haven Hypothesis, does exist and to estimate the magnitude of the under-estimation of the carbon actually emitted: the carbon leakage. The Input-Output model has been used to calculate the intensities of energy consumption and the related Green House Gases emission, for each Italian economic sector
Energy Technology Data Exchange (ETDEWEB)
Chang, Yih F. [Department of Tourism and Management, Chia-Nan University of Pharmacy and Science, Tainan 717 (China); Lewis, Charles [Department of Resources Engineering, National Cheng Kung University, Tainan 701 (China); Lin, Sue J. [Department of Environmental Engineering, National Cheng Kung University, Tainan 701 (China)
2008-07-15
Taiwan currently emits approximately 1% of the world's CO{sub 2} - ranking it 22nd among nations. Herein, we use the input-output (I-O) structural decomposition method to examine the changes in CO{sub 2} emission over a 15-year period. By decomposing the CO{sub 2} emission changes into nine factors for the periods of 1989-1994, 1994-1999, and 1999-2004, we have identified the key factors causing the emission changes, as well as the most important trends regarding the industrial development process in Taiwan. The 5-year increment with the largest increase of CO{sub 2} emission was that of 1999-2004, due to the rapid increase of electricity consumption. From the decomposition, the industrial energy coefficient and the CO{sub 2} emission factors were identified as the most important parameters for the determination of the highway, petrochemical materials, iron and steel, the commercial sector, and electric machinery as the major sources of increased CO{sub 2} emission during the past 15 years. From 1989 to 2004, the level of exports and the level of domestic final demand were the largest contributors to the increase in the total increment of CO{sub 2} change. During 1989-2004, the industrial energy coefficient and CO{sub 2} emission factors, being minimally significant during 1989-1994, became extremely important, joining the domestic final demand and the level of exports factors as the major causes of the increase increment of CO{sub 2}. This indicates a heavy reliance upon high-energy (and CO{sub 2}) intensity for Taiwanese industries; therefore, continuous efforts to improve energy intensity and fuel mix toward lower carbon are important for CO{sub 2} reduction, especially for the electricity and power generation sectors. Relevant strategies for reducing carbon dioxide emissions from major industries are also highlighted. (author)
International Nuclear Information System (INIS)
Chang, Yih F.; Lewis, Charles; Lin, Sue J.
2008-01-01
Taiwan currently emits approximately 1% of the world's CO 2 - ranking it 22nd among nations. Herein, we use the input-output (I-O) structural decomposition method to examine the changes in CO 2 emission over a 15-year period. By decomposing the CO 2 emission changes into nine factors for the periods of 1989-1994, 1994-1999, and 1999-2004, we have identified the key factors causing the emission changes, as well as the most important trends regarding the industrial development process in Taiwan. The 5-year increment with the largest increase of CO 2 emission was that of 1999-2004, due to the rapid increase of electricity consumption. From the decomposition, the industrial energy coefficient and the CO 2 emission factors were identified as the most important parameters for the determination of the highway, petrochemical materials, iron and steel, the commercial sector, and electric machinery as the major sources of increased CO 2 emission during the past 15 years. From 1989 to 2004, the level of exports and the level of domestic final demand were the largest contributors to the increase in the total increment of CO 2 change. During 1989-2004, the industrial energy coefficient and CO 2 emission factors, being minimally significant during 1989-1994, became extremely important, joining the domestic final demand and the level of exports factors as the major causes of the increase increment of CO 2 . This indicates a heavy reliance upon high-energy (and CO 2 ) intensity for Taiwanese industries; therefore, continuous efforts to improve energy intensity and fuel mix toward lower carbon are important for CO 2 reduction, especially for the electricity and power generation sectors. Relevant strategies for reducing carbon dioxide emissions from major industries are also highlighted. (author)
Xu, Z.; Schrama, E.J.O.; Van der Wal, W.; Van den Broeke, M.; Enderlin, E.M.
2015-01-01
In this study, we use satellite gravimetry data from the Gravity Recovery and Climate Experiment (GRACE) to estimate regional mass changes of the Greenland ice sheet (GrIS) and neighbouring glaciated regions using a least-squares inversion approach. We also consider results from the input-output
Logar, I.; van den Bergh, J.C.J.M.
2013-01-01
This article examines the potential effects of peak oil on Spanish tourism and indirectly on the rest of the economy. We construct several scenarios of price increases in oil, related fossil fuels and their inflationary effects. These scenarios provide the context for an input-output (I/O) analysis
Hoseini, Mohammad
2015-01-01
Under the VAT, formal traders report their purchases to the administration for a deduction in their VAT bill. This paper models this third-party reporting feature of the VAT in an input-output economy and quantifies it among different activities using a forward linkages index. The administration can
Ruiz-Felter, Roxanna; Cooperson, Solaman J; Bedore, Lisa M; Peña, Elizabeth D
2016-07-01
Although some investigations of phonological development have found that segmental accuracy is comparable in monolingual children and their bilingual peers, there is evidence that language use affects segmental accuracy in both languages. To investigate the influence of age of first exposure to English and the amount of current input-output on phonological accuracy in English and Spanish in early bilingual Spanish-English kindergarteners. Also whether parent and teacher ratings of the children's intelligibility are correlated with phonological accuracy and the amount of experience with each language. Data for 91 kindergarteners (mean age = 5;6 years) were selected from a larger dataset focusing on Spanish-English bilingual language development. All children were from Central Texas, spoke a Mexican Spanish dialect and were learning American English. Children completed a single-word phonological assessment with separate forms for English and Spanish. The assessment was analyzed for segmental accuracy: percentage of consonants and vowels correct and percentage of early-, middle- and late-developing (EML) sounds correct were calculated. Children were more accurate on vowel production than consonant production and showed a decrease in accuracy from early to middle to late sounds. The amount of current input-output explained more of the variance in phonological accuracy than age of first English exposure. Although greater current input-output of a language was associated with greater accuracy in that language, English-dominant children were only significantly more accurate in English than Spanish on late sounds, whereas Spanish-dominant children were only significantly more accurate in Spanish than English on early sounds. Higher parent and teacher ratings of intelligibility in Spanish were correlated with greater consonant accuracy in Spanish, but the same did not hold for English. Higher intelligibility ratings in English were correlated with greater current English
Whealan George, Kelly
The study provided a detailed description of the interrelatedness of the aviation and aerospace industry with principal industries in Florida and Volusia County (VC) using Input-Output (IO) analysis. Additionally, this research provided an economic impact analysis of the creation of a university research park in Daytona Beach (DB). The economic impact measures included not only direct economic output and industry employment descriptions but also described the multiplier effects in the form of indirect and induced impacts using data for 2012. This research concluded the average labor income of the aviation and aerospace industry was higher than average labor income in Florida and VC. A substantive difference between the Florida and VC average labor income for the aviation and aerospace industry existed because VC's aerospace sector was only concentrated in the search, detection, and navigation instruments manufacturing sector. VC's transport by air sector was one-fifth the size of Florida's. Differences in the aviation and aerospace industry composition between Florida and VC are important because the economic impacts from a shock to the entire aviation and aerospace industry will be distributed differently. Since the aviation and aerospace average labor income is higher than the average labor income in Florida and VC, it would be a positive move for Florida's economy to attract and grow the aviation and aerospace industry. It would be highly unlikely that the entirety of newly created jobs would be resourced from the local population. Nonetheless, growing the aviation and aerospace industry jobs would have a positive influence on the region's economy and tax revenues. It would be a desirable course of action to spur the growth of this sector, as its direct effect would culminate with additional jobs in Florida that would bring higher wage jobs to the state. The interdependencies of the aviation and aerospace industry in Florida and VC with other industries had a
1994-07-01
REQUIRED MIX OF SEGMENTS OR INDIVIDUAL DATA ELEMENTS TO BE EXTRACTED. IN SEGMENT R ON AN INTERROGATION TRANSACTION (LTI), DATA RECORD NUMBER (DRN 0950) ONLY...and zation and Marketing input DICs. insert the Continuation Indicator Code (DRN 8555) in position 80 of this record. Maximum of OF The assigned NSN...for Procurement KFR, File Data Minus Security Classified Characteristics Data KFC 8.5-2 DoD 4100.39-M Volume 8 CHAPTER 5 ALPHABETIC INDEX OF DIC
Directory of Open Access Journals (Sweden)
José Manuel Rueda Cantuche
2000-01-01
Full Text Available El proceso de comparación estructural de una economía a través de la cantidad absoluta de valor añadido y del empleo nos arroja una serie de interrogantes sobre las distintas fuentes de variaciones estructurales en los procesos productivos a nivel sectorial entre dos regiones distintas. El análisis input-output de descomposición estructural estudia dichas fuentes a partir de cuatro diferentes tipos de orígenes: la diferencia de procesos tecnológicos, la demanda final interior, el comercio exterior y la productividad del trabajo. En nuestro documento pretendemos arrojar cierta luz sobre las diferencias estructurales entre regiones caracterizadas por economías de aglomeración Madrid y regiones menos desarrolladas (Andalucía a la luz del análisis input-output.
Diaz-Ruelas, Alvaro; Jeldtoft Jensen, Henrik; Piovani, Duccio; Robledo, Alberto
2016-12-01
It is well known that low-dimensional nonlinear deterministic maps close to a tangent bifurcation exhibit intermittency and this circumstance has been exploited, e.g., by Procaccia and Schuster [Phys. Rev. A 28, 1210 (1983)], to develop a general theory of 1/f spectra. This suggests it is interesting to study the extent to which the behavior of a high-dimensional stochastic system can be described by such tangent maps. The Tangled Nature (TaNa) Model of evolutionary ecology is an ideal candidate for such a study, a significant model as it is capable of reproducing a broad range of the phenomenology of macroevolution and ecosystems. The TaNa model exhibits strong intermittency reminiscent of punctuated equilibrium and, like the fossil record of mass extinction, the intermittency in the model is found to be non-stationary, a feature typical of many complex systems. We derive a mean-field version for the evolution of the likelihood function controlling the reproduction of species and find a local map close to tangency. This mean-field map, by our own local approximation, is able to describe qualitatively only one episode of the intermittent dynamics of the full TaNa model. To complement this result, we construct a complete nonlinear dynamical system model consisting of successive tangent bifurcations that generates time evolution patterns resembling those of the full TaNa model in macroscopic scales. The switch from one tangent bifurcation to the next in the sequences produced in this model is stochastic in nature, based on criteria obtained from the local mean-field approximation, and capable of imitating the changing set of types of species and total population in the TaNa model. The model combines full deterministic dynamics with instantaneous parameter random jumps at stochastically drawn times. In spite of the limitations of our approach, which entails a drastic collapse of degrees of freedom, the description of a high-dimensional model system in terms of a low
International Nuclear Information System (INIS)
1978-07-01
A static model in the form of a regional input-output model was constructed for Eddy and Lea Counties, New Mexico. Besides the WIPP project, the model was also used for several other projects to determine the economic impact of proposed new facilities and developments. Both private and public sectors are covered. Sub-sectors for WIPP below-ground construction, above-ground construction, and operation and transport are included
International Nuclear Information System (INIS)
Ragalie, S.; Gaftea, V.
1996-01-01
This study, regarding the industrial consumption behaviour at low power consumption and under low pollution constraints, making use of the input-output analysis, is based on models for prices, energy demand, and pollution. Numerical applications were developed by use of MATILDA program and the methods of setting the model parameters and data acquisition are presented. The analysis provided prognoses for pollution coefficients for given price and consumption input data and very important data for industrial consumption behavior. (author) 7 refs
Aplicación de la teoría de grafos al análisis input-output: Andalucía 1995
Directory of Open Access Journals (Sweden)
José Antonio Ordaz Sanz
2000-01-01
Full Text Available La Economía Aplicada contemporánea resultaría impensable sin el análisis input-output, por su contribución decisiva al conocimiento de las actividades económicas de los países y a la armonización de sus cuentas. Muchas de las políticas sociales y económicas que se llevan a cabo en nuestros días residen en sus fundamentos, y su aplicación resulta esencial en infinidad de campos: contabilidad nacional y regional, comercio, empleo, desarrollo tecnológico, medio ambiente, ... Las Tablas Input-Output de Andalucía de 1995 constituyen un buen exponente actual de la preocupación de los poderes públicos por conocer con el mayor detalle posible la realidad de la actividad económica de sus ámbitos territoriales, lo que contribuye en gran medida a facilitar la toma de decisiones. El análisis matricial y el establecimiento de condiciones destinadas a asegurar la resolución de sistemas de ecuaciones lineales de soluciones no negativas conforman, sin lugar a dudas, la base sobre la que se ha desarrollado el modelo input-output. Sin embargo, no tienen por qué ser la única. La Teoría de grafos se está revelando de forma creciente como una herramienta cada vez más útil en el estudio de problemas de carácter económico, siendo precisamente las tablas input-output uno de los principales ejemplos de ello.
Taşkin Kaya, Gülşen
2013-10-01
Recently, earthquake damage assessment using satellite images has been a very popular ongoing research direction. Especially with the availability of very high resolution (VHR) satellite images, a quite detailed damage map based on building scale has been produced, and various studies have also been conducted in the literature. As the spatial resolution of satellite images increases, distinguishability of damage patterns becomes more cruel especially in case of using only the spectral information during classification. In order to overcome this difficulty, textural information needs to be involved to the classification to improve the visual quality and reliability of damage map. There are many kinds of textural information which can be derived from VHR satellite images depending on the algorithm used. However, extraction of textural information and evaluation of them have been generally a time consuming process especially for the large areas affected from the earthquake due to the size of VHR image. Therefore, in order to provide a quick damage map, the most useful features describing damage patterns needs to be known in advance as well as the redundant features. In this study, a very high resolution satellite image after Iran, Bam earthquake was used to identify the earthquake damage. Not only the spectral information, textural information was also used during the classification. For textural information, second order Haralick features were extracted from the panchromatic image for the area of interest using gray level co-occurrence matrix with different size of windows and directions. In addition to using spatial features in classification, the most useful features representing the damage characteristic were selected with a novel feature selection method based on high dimensional model representation (HDMR) giving sensitivity of each feature during classification. The method called HDMR was recently proposed as an efficient tool to capture the input-output
Longo, Diane M; Louie, Brent; Ptacek, Jason; Friedland, Greg; Evensen, Erik; Putta, Santosh; Atallah, Michelle; Spellmeyer, David; Wang, Ena; Pos, Zoltan; Marincola, Francesco M; Schaeffer, Andrea; Lukac, Suzanne; Railkar, Radha; Beals, Chan R; Cesano, Alessandra; Carayannopoulos, Leonidas N; Hawtin, Rachael E
2014-06-21
Single-cell network profiling (SCNP) is a multiparametric flow cytometry-based approach that simultaneously measures evoked signaling in multiple cell subsets. Previously, using the SCNP approach, age-associated immune signaling responses were identified in a cohort of 60 healthy donors. In the current study, a high-dimensional analysis of intracellular signaling was performed by measuring 24 signaling nodes in 7 distinct immune cell subsets within PBMCs in an independent cohort of 174 healthy donors [144 elderly (>65 yrs); 30 young (25-40 yrs)]. Associations between age and 9 immune signaling responses identified in the previously published 60 donor cohort were confirmed in the current study. Furthermore, within the current study cohort, 48 additional immune signaling responses differed significantly between young and elderly donors. These associations spanned all profiled modulators and immune cell subsets. These results demonstrate that SCNP, a systems-based approach, can capture the complexity of the cellular mechanisms underlying immunological aging. Further, the confirmation of age associations in an independent donor cohort supports the use of SCNP as a tool for identifying reproducible predictive biomarkers in areas such as vaccine response and response to cancer immunotherapies.
Liu, Changqi; Huang, Yaji; Wang, Xinye; Tai, Yang; Liu, Lingqin; Liu, Hao
2018-01-01
Studies on the environmental analysis of biofuels by fast pyrolysis and hydroprocessing (BFPH) have so far focused only on the environmental impacts from direct emissions and have included few indirect emissions. The influence of ignoring some indirect emissions on the environmental performance of BFPH has not been well investigated and hence is not really understood. In addition, in order to avoid shifting environmental problems from one medium to another, a comprehensive assessment of environmental impacts caused by the processes must quantify the environmental emissions to all media (air, water, and land) in relation to each life cycle stage. A well-to-wheels assessment of the total environmental impacts resulting from direct emissions and indirect emissions of a BFPH system with corn stover is conducted using a hybrid life cycle assessment (LCA) model combining the economic input-output LCA and the process LCA. The Tool for the Reduction and Assessment of Chemical and other environmental Impacts (TRACI) has been used to estimate the environmental impacts in terms of acidification, eutrophication, global climate change, ozone depletion, human health criteria, photochemical smog formation, ecotoxicity, human health cancer, and human health noncancer caused by 1 MJ biofuel production. Taking account of all the indirect greenhouse gas (GHG) emissions, the net GHG emissions (81.8 g CO 2 eq/MJ) of the biofuels are still less than those of petroleum-based fuels (94 g CO 2 eq/MJ). Maize production and pyrolysis and hydroprocessing make major contributions to all impact categories except the human health criteria. All impact categories resulting from indirect emissions except eutrophication and smog air make more than 24% contribution to the total environmental impacts. Therefore, the indirect emissions are important and cannot be ignored. Sensitivity analysis has shown that corn stover yield and bio-oil yield affect the total environmental impacts of the biofuels
High-dimensional covariance estimation with high-dimensional data
Pourahmadi, Mohsen
2013-01-01
Methods for estimating sparse and large covariance matrices Covariance and correlation matrices play fundamental roles in every aspect of the analysis of multivariate data collected from a variety of fields including business and economics, health care, engineering, and environmental and physical sciences. High-Dimensional Covariance Estimation provides accessible and comprehensive coverage of the classical and modern approaches for estimating covariance matrices as well as their applications to the rapidly developing areas lying at the intersection of statistics and mac
Zuhdi, Ubaidillah
2014-03-01
The purpose of this study is to analyze the impacts of final demand changes on total output of Japanese Information and Communication Technologies (ICT) sectors in future time. This study employs one of analysis tool in Input-Output (IO) analysis, demand-pull IO quantity model, in achieving the purpose. There are three final demand changes used in this study, namely (1) export, (2) import, and (3) outside households consumption changes. This study focuses on "pure change" condition, the condition that final demand changes only appear in analyzed sectors. The results show that export and outside households consumption modifications give positive impact while opposite impact could be seen in import change.
Energy Technology Data Exchange (ETDEWEB)
Lucena, Thomas Krisp de; Young, Carlos Eduardo Frickmann [Universidade Federal Fluminense (UFF), Niteroi, RJ (Brazil). Dept. de Economia], e-mail: thomaskl@ig.com.br
2008-07-01
This article analysis the National Program of Biodiesel Production, and presents a methodology to estimate the direct and indirect effects of employment and wages generation using the Input-Output Model developed by Leontief. Four different simulations are carried out, but even in the most optimistic case, the results presented by the Government exceed considerably the estimates obtained using data from the Brazilian national accounts. The main recommendation is that these estimates need to be redone, in order to present more realistic expectations for the job and income generation from the expansion of the bio diesel. (author)
International Nuclear Information System (INIS)
Choi, Jun-Ki; Bakshi, Bhavik R.; Haab, Timothy
2010-01-01
Despite differences in their implementation, most carbon policies aim to have similar outcomes: effectively raising the price of carbon-intensive products relative to non-carbon-intensive products. While it is possible to predict the simple broad-scale economic impacts of raising the price of carbon-intensive products-the demand for non-carbon-intensive products will increase-understanding the economic and environmental impacts of carbon policies throughout the life cycle of both types of products is more difficult. Using the example of a carbon tax, this study proposes a methodology that integrates short-term policy-induced consumer demand changes into the input-output framework to analyze the environmental and economic repercussions of a policy. Environmental repercussions include the direct and the indirect impacts on emissions, materials flow in the economy, and the reliance on various ecosystem goods and services. The approach combines economic data with data about physical flow of fossil fuels between sectors, consumption of natural resources and emissions from each sector. It applies several input-output modeling equations sequentially and uses various levels of aggregation/disaggregation. It is illustrated with the data for the 2002 U.S. economy and physical flows. The framework provides insight into the short-term complex interactions between carbon price and its economic and environmental effects.
Irimoto, Hiroshi; Shibusawa, Hiroyuki; Miyata, Yuzuru
2017-10-01
Damage to transportation networks as a result of natural disasters can lead to economic losses due to lost trade along those links in addition to the costs of damage to the infrastructure itself. This study evaluates the economic damages of transport disruptions such as highways, tunnels, bridges, and ports using a transnational and interregional Input-Output Model that divides the world into 23 regions: 9 regions in Japan, 7 regions in China, and 4 regions in Korea, Taiwan, ASEAN5, and the USA to allow us to focus on Japan's regional and international links. In our simulation, economic ripple effects of both international and interregional transport disruptions are measured by changes in the trade coefficients in the input-output model. The simulation showed that, in the case of regional links in Japan, a transport disruption in the Kanmon Straits causes the most damage to our targeted world, resulting in economic damage of approximately 36.3 billion. In the case of international links among Japan, China, and Korea, damage to the link between Kanto in Japan and Huabei in China causes economic losses of approximately 31.1 billion. Our result highlights the importance of disaster prevention in the Kanmon Straits, Kanto, and Huabei to help ensure economic resilience.
Chen, Mengmeng; Wu, Sanmang; Lei, Yalin; Li, Shantong
2018-03-08
Jing-Jin-Ji region (i.e., Beijing, Tianjin, and Hebei) is China's key development region, but it is also the leading and most serious air pollution region in China. High fossil fuel consumption is the major source of both carbon dioxide (CO 2 ) emissions and air pollutants. Therefore, it is important to reveal the source of CO 2 emissions to control the air pollution in the Jing-Jin-Ji region. In this study, an interregional input-output model was applied to quantitatively estimate the embodied CO 2 transfer between Jing-Jin-Ji region and other region in China using China's interregional input-output data in 2010. The results indicated that there was a significant difference in the production-based CO 2 emissions in China, and furthermore, the Jing-Jin-Ji region and its surrounding regions were the main regions of the production-based CO 2 emissions in China. Hebei Province exported a large amount of embodied CO 2 to meet the investment, consumption, and export demands of Beijing and Tianjin. The Jing-Jin-Ji regions exported a great deal of embodied CO 2 to the coastal provinces of southeast China and imported it from neighboring provinces.
DEFF Research Database (Denmark)
Kowalewski, Borys; Fereczkowski, Michal; MacDonald, Ewen
2016-01-01
system and, potentially, for clinical diagnostics. Computational algorithms are available that mimic the functioning of the nonlinear cochlear processing. One such algorithm is the dual resonance non-linear (DRNL) filterbank [6]. Its parameters can be modified to account for individual hearing loss, e.......g., based on behavioral, temporal masking curves (TMC) data. This approach was used within the framework of the computational auditory signal-processing and perception (CASP) model to account for various aspects of SNHL [4]. However, due to the computational complexity, on-line fitting of the DRNL...
Directory of Open Access Journals (Sweden)
Junko Shindo
2001-01-01
Full Text Available To evaluate the current nitrogen (N status in Japanese forests, field measurements of rainfall, throughfall, litter layer percolation, and soil solution percolation were conducted in a red pine stand (Kannondai and a deciduous stand (Yasato located in central Japan. N input via throughfall was 31 and 14 kg ha–1 year–1and output below rooting zone was 9.6 and 5.5 kg ha1 year–1 in Kannondai and in Yasato, respectively. Two thirds of input N were retained in plant-soil systems. Manipulation of N input was carried out. Ionic constituents were removed from throughfall with ion exchange resin at removal sites and ammonium nitrate containing twice the N of the throughfall was applied at N addition sites periodically. SO42– output below 20-cm soil layer changed depending on the input, while NO3– output was regulated mainly by the internal cycle and effect of manipulation was undetected. These Japanese stands were generally considered to have a larger capacity to assimilate N than NITREX sites in Europe. However, N output fluxes had large spatial variability and some sites in Kannondai showed high N leaching below rooting zone almost balanced with the input via throughfall.
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Javier Sanfélix
2016-07-01
Full Text Available In this paper, the environmental and economic impacts of the life cycle of an advanced lithium based energy storage system (ESS for a battery electric vehicle are assessed. The methodology followed to perform the study is a Multiregional Input–Output (MRIO analysis, with a world IO table that combines detailed information on national production activities and international trade data for 40 countries and a region called Rest of the World. The life cycle stages considered in the study are manufacturing, use and recycling. The functional unit is one ESS with a 150,000 km lifetime. The results of the MRIO analysis show the stimulation that the life cycle of the EES has in the economy, in terms of production of goods and services. The manufacturing is the life cycle stage with the highest environmental load for all the impact categories assessed. The geographical resolution of the results show the relevance that some countries may have in the environmental performance of the assessed product even if they are not directly involved in any of the stages of the life cycle, proving the significance of the indirect effects.
Stelzel, Christine; Schauenburg, Gesche; Rapp, Michael A.; Heinzel, Stephan; Granacher, Urs
2017-01-01
Age-related decline in executive functions and postural control due to degenerative processes in the central nervous system have been related to increased fall-risk in old age. Many studies have shown cognitive-postural dual-task interference in old adults, but research on the role of specific executive functions in this context has just begun. In this study, we addressed the question whether postural control is impaired depending on the coordination of concurrent response-selection processes related to the compatibility of input and output modality mappings as compared to impairments related to working-memory load in the comparison of cognitive dual and single tasks. Specifically, we measured total center of pressure (CoP) displacements in healthy female participants aged 19–30 and 66–84 years while they performed different versions of a spatial one-back working memory task during semi-tandem stance on an unstable surface (i.e., balance pad) while standing on a force plate. The specific working-memory tasks comprised: (i) modality compatible single tasks (i.e., visual-manual or auditory-vocal tasks), (ii) modality compatible dual tasks (i.e., visual-manual and auditory-vocal tasks), (iii) modality incompatible single tasks (i.e., visual-vocal or auditory-manual tasks), and (iv) modality incompatible dual tasks (i.e., visual-vocal and auditory-manual tasks). In addition, participants performed the same tasks while sitting. As expected from previous research, old adults showed generally impaired performance under high working-memory load (i.e., dual vs. single one-back task). In addition, modality compatibility affected one-back performance in dual-task but not in single-task conditions with strikingly pronounced impairments in old adults. Notably, the modality incompatible dual task also resulted in a selective increase in total CoP displacements compared to the modality compatible dual task in the old but not in the young participants. These results suggest
Zhang, Shuying; Wu, Xuquan; Li, Deshan; Xu, Yadong; Song, Shulin
2017-06-01
Based on the input and output data of sandstone reservoir in Xinjiang oilfield, the SBM-Undesirable model is used to study the technical efficiency of each block. Results show that: the model of SBM-undesirable to evaluate its efficiency and to avoid defects caused by traditional DEA model radial angle, improve the accuracy of the efficiency evaluation. by analyzing the projection of the oil blocks, we find that each block is in the negative external effects of input redundancy and output deficiency benefit and undesirable output, and there are greater differences in the production efficiency of each block; the way to improve the input-output efficiency of oilfield is to optimize the allocation of resources, reduce the undesirable output and increase the expected output.
Wu, Sanmang; Li, Shantong; Lei, Yalin
2016-01-01
This paper developed an estimation model for the contribution of exports to a country's regional economy based on the Chenery-Moses model and conducted an empirical analysis using China's multi-regional input-output tables for 1997, 2002, and 2007. The results indicated that China's national exports make significantly different contributions to the provincial economy in various regions, with the greatest contribution being observed in the eastern region and the smallest in the central region. The provinces are also subjected to significantly different export spillover effects. The boosting effect for the eastern provinces is primarily generated from local exports, whereas the western provinces primarily benefit from the export spillover effect from the eastern provinces. The eastern provinces, such as Guangdong, Zhejiang, Jiangsu, and Shanghai, are the primary sources of export spillover effects, and Guangdong is the largest source of export spillover effects for almost all of the provinces in China.
International Nuclear Information System (INIS)
1978-07-01
A static model in the form of a regional input-output model was constructed for Eddy and Lea Counties, New Mexico. This modeling process has been used to assess the economic impacts of the following activities and for the following agencies: San Juan Generating Units Nos. 1, 3, and 4 for Public Service Company of New Mexico, and general economic impacts (an ongoing process) for the Bureau of Business and Economic Research, University of New Mexico. The regional modeling process adjusts a national model by means of location quotients and aggregating techniques. The national model, or base model, used in this process contains 407 economic categories or subsectors of the economy, 389 of which represent the private economy, and 18 of which represent activities mostly dealing with the public sector. The 389 identified sub-sectors were used in the modeling process; the government impact was computed after the private sector analysis
International Nuclear Information System (INIS)
Zuhdi, Ubaidillah
2014-01-01
The purpose of this study is to analyze the impacts of final demand changes on total output of Japanese Information and Communication Technologies (ICT) sectors in future time. This study employs one of analysis tool in Input-Output (IO) analysis, demand-pull IO quantity model, in achieving the purpose. There are three final demand changes used in this study, namely (1) export, (2) import, and (3) outside households consumption changes. This study focuses on ''pure change'' condition, the condition that final demand changes only appear in analyzed sectors. The results show that export and outside households consumption modifications give positive impact while opposite impact could be seen in import change
International Nuclear Information System (INIS)
Hamilton, Thomas Gerard Adam; Kelly, Scott
2017-01-01
Meeting Sub-Saharan African (SSA) human development goals will require economic development to be the priority over the coming decades, but economic development ‘at all cost’ may not be acceptable across these goals. This paper aims to explore five development scenarios for the five largest economies in SSA to understand the implications to CO_2-equivalent emissions (CO_2-e) and off-grid energy modernisation in 2030. Within this scope GDP growth; economic structure; availability of energy resources; international trade; and, the development of distributed generation for remote locations are considered. Regional CO_2 emissions were studied using a Multi-Regional Input-Output Model for Africa. Under the scenarios analysed all five nations will be unable to reduce 2030 CO_2-e emissions below 2012 levels, whilst simultaneously achieving forecast GDP growth and universal access to modernised energy services. 100% off-grid modernisation is estimated to require a three-fold increase in Primary Energy Supply and a 26% (1317 Mt) increase in 2030 CO_2-e emissions. Total regional CO_2-e emissions could be reduced from 45% to 35% by meeting a 50% renewable energy supply target by 2030. Climate Change policy would need to focus on multi-sector reform to reduce regional emissions as the agricultural sector is the largest emitter in Nigeria, Ethiopia and Kenya. - Highlights: • GHG"1 emissions were studied with a Multi-Regional Input-Output Model for Africa. • SSA"2 GDP growth is inextricably linked with access to additional energy supply. • SSA will not attain universal energy access and low carbon growth in parallel. • GHG emissions decline needs both renewable energy adoption and agriculture reform. • SSA Climate Change policy would need to target multiple GHG emitting sector reform.
Directory of Open Access Journals (Sweden)
Azizatun Nurhayati
2015-10-01
Full Text Available Pembangunan daerah dilakukan dengan memaksimalkan potensi sumber daya yang ada di suatu daerah. Karena sebagian besar penduduk Indonesia adalah petani, maka penting untuk mengetahui kontribusi sektor pertanian terhadap perekonomian suatu daerah. Makalah ini bertujuan untuk mengetahui kontribusi sektor pertanian terhadap multiplier output, pengganda pendapatan, dan pengganda tenaga kerja. Metode yang digunakan dalam penelitian ini adalah Analisis Input Output yang diperoleh dari Badan Pusat Statistik Provinsi Jawa Timur Tahun 2010. Hasil penelitian menunjukkan bahwa komoditas tebu berada pada kuadran II, Dari keseluruhan data di atas maka dapat disimpulkan bahwa (1 Komoditas tebu dapat mendorong berkembangnya industri gula di Jawa Timur, (2 di sektor peternakan, subsektor yang dapat dikembangkan adalah pakan ternak, pemotongan hewan, sapi, kambing dan domba, serta ayam (3 di sektor pengolahan subsektor pengolahan es krim, beras, dan penggilingan padi serta rokok. ABSTRACTLocal development is held by maximizing potential resources in a particular region. In addition, most of Indonesian people are farmers so it’s important to identify the agriculural contribution in local economic. The aim of this study are to study the contribution of agriculture in ouput multiplier, income multiplier, and employment multiplier. The method which was used in this research was input-output analysis based on Badan Pusat Statistik East Java Province’s data in 2010. From the analysis, we can conclude that the sugarcane was formed in the second quadrant, in which (1sugarcane comodity promoted the sugar industry in East Java Province (2 in livestock subsector, the woof of livestock industry, animals truncation, sheeps, goats, and chicken husbandry (poultry were potentially to be developed (3 in processing subsector which was based on agriculture product, ice cream and processing, rice milling and cigarette were potentially to be developed.
International Nuclear Information System (INIS)
Wu, Ya; Zhang, Wanying
2016-01-01
With the rapid development of economy, especially the constant progress in industrialisation and urbanisation, China's energy consumption has increased annually. Coal consumption, which accounts for about 70% of total energy consumption, is of particular concern. Hence, it is crucial to study the driving factors behind coal demand in China. This work uses an input-output structural decomposition analysis (I-O SDA) model to decompose the increments of coal demand in China from 1997 to 2012 into the sum of the weighted average for eight driving factors from three aspects, including: domestic demand, foreign trade and industrial upgrading. Results show that: during the research period, the demand for coal increases by 153.3%, which is increased by 185.4% and 76.4% respectively due to the driving forces of domestic demand and foreign trade; in addition, industrial upgrading can effectively restrain the growth in coal demand with a contribution rate of −108.6%. On this basis, we mainly studied the driving factors of coal demand in six high energy-consuming industries, namely the electrical power, energy processing, metals, mining, building materials and chemical industries. Finally, we proposed targeted policy suggestions for the realisation of energy conservation and emissions reduction in China. - Highlights: •The driving factors behind coal demand in China from 1997 to 2012 are studied. •An input-output structural decomposition analysis is developed. •A fresh perspective of domestic demand, foreign trade, and industrial upgrading is employed. •The influences of these affecting factors on China's coal demand from six high energy-consuming industries are investigated. •Targeted policy suggestions for energy conservation and emissions reduction are suggested.
Zhao, Xu; Yang, Hong; Yang, Zhifeng; Chen, Bin; Qin, Yan
2010-12-01
The virtual water strategy which advocates importing water intensive products and exporting products with low water intensity is gradually accepted as one of the options for solving water crisis in severely water scarce regions. However, if we count the virtual water embodied in imported products as the water saved for a region, we might overestimate the saving by including the virtual water that is later re-exported in association with the proceeded products made from the originally imported products. This problem can be avoided by accounting for the saved water through calculating water footprint (WF) in domestic final consumptive products. In this paper, an input-output analysis (IOA) based on the water footprint accounting framework is built to account for WF and virtual water trade of final consumptive products in the water stressed Haihe River basin in China for the year 1997, 2000, and 2002. The input-output transaction tables of the three years are constructed. The results show WF of 46.57, 44.52, and 42.71 billion m(3) for the three years, respectively. These volumes are higher than the water used directly in the corresponding years in the basin. A WF intensity (WFI) indicator is then used to assess if the economic activities in the basin are consistent with the virtual water strategy. The temporal change of the WFI is also decomposed by the index number analysis method. The results showed that the basin was silently importing virtual water through the trade of raw and processed food commodities under the background of the whole economic circulation.
Directory of Open Access Journals (Sweden)
Yuya Ono
2017-08-01
Full Text Available Interest in the impacts of water use in the life cycle of products and services are increasing among various stakeholders. The water footprint is a tool to identify critical and effective points for reducing the impact of water use through the entire life cycle of products, services, and organizations. The purpose of this study was to develop a water consumption inventory database that focused on identifying of Asian water consumption using an input-output (IO framework. An Asia International Input-Output table (AIIO was applied in this study. The amount of water consumption required for agricultural products was estimated by modeling; for other sectors it was estimated from statistical reports. The intensities of direct water consumption in each sector were calculated by dividing the amount of water consumption by the domestic production. Based on the IO analysis using Leontief’s inverse matrix, the intensities of water consumption from cradle to gate were estimated for all goods and services. There was high intensity of water consumption in the primary industry sectors, together with a high dependency on rainwater as an input water source. The water consumption intensities generally showed a larger reduction in secondary sectors, in comparison with the tertiary sectors, due to the use of recycled water. There were differences between this study and previous studies due to the use of site-specific production data and the temporal resolution of crop production. By considering site-specific conditions, it is expected that the dataset developed here can be used for estimating the water footprint of products, services, and organizations in nine countries (Japan, South Korea, China, Taiwan, Thailand, the Philippines, Malaysia, Singapore, Indonesia, and USA.
International Nuclear Information System (INIS)
Shapiro, R.E.; Evans, A. Jr.
1981-01-01
This document is intended as an introduction to the use of RMS facilities via Praxis (this interface hereafter called Praxis-RMS). It is presumed that the reader is familiar with Praxis conventions as well as with RMS use (at the MACRO level). Since Praxis-RMS was designed to be functionally equivalent to MACRO-RMS, the explanations follow the pattern of the DEC MACRO-RMS documentation (particularly the programmer's reference manual). A complete list of the procedures that make up Praxis-RMS appears at the end of this document (with parameters), along with the constants (grouped by type) that can be used as actual parameters
Chernozhukov, Victor; Hansen, Chris; Spindler, Martin
2016-01-01
The package High-dimensional Metrics (\\Rpackage{hdm}) is an evolving collection of statistical methods for estimation and quantification of uncertainty in high-dimensional approximately sparse models. It focuses on providing confidence intervals and significance testing for (possibly many) low-dimensional subcomponents of the high-dimensional parameter vector. Efficient estimators and uniformly valid confidence intervals for regression coefficients on target variables (e.g., treatment or poli...
Directory of Open Access Journals (Sweden)
A. Butturini
2005-01-01
Full Text Available Input-output mass balances within stream reaches provide in situ estimates of stream nutrient retention/release under a wide spectrum of hydrological conditions. Providing good estimates of the mass balances for nutrients depends on precise hydrological monitoring and good chemical characterisation of stream water at the input and output ends of the stream reach. There is a need to optimise the hydrological monitoring and the frequencies of water sampling to yield precise annual mass balances, so as to avoid undue cost - high resolution monitoring and subsequent chemical analysis can be labour intensive and costly. In this paper, simulation exercises were performed using a data set created to represent the instantaneous discharge and solute dynamics at the input and output ends of a model stream reach during a one year period. At the output end, stream discharge and water chemistry were monitored continuously, while the input end was assumed to be ungauged; water sampling frequency was changed arbitrarily. Instantaneous discharge at the ungauged sampling point was estimated with an empirical power model linking the discharge to the catchment area (Hooper, 1986. The model thus substitutes for the additional gauge station. Simulations showed that 10 days was the longest chemical sampling interval which could provide reach annual mass balances of acceptable precision. Presently, the relationship between discharge and catchment area is usually assumed to be linear but simulations indicate that small departures from the linearity of this relationship could cause dramatic changes in the mass balance estimations.
Directory of Open Access Journals (Sweden)
Decun Wu
2016-12-01
Full Text Available Rapid development in China has led to imbalances and inequities of ecological resources among the provinces and regions. In this study, an environmentally extended multi-regional input-output (MRIO model was used to analyze the imbalances, inequities and pressures of the ecological footprints (EF of China’s 30 provinces in 2007. In addition, by decomposing the total product consumption coefficients, we calculated the net embodied EF of the flows among the provinces by the total amount, land type and sector. The results showed that most provinces presented EF deficits. Significant differences were observed between the ecological pressure in consumption (EPC and ecological pressure in production (EPP for each province because of the net embodied EF trade; the EPCs of Shanghai (15.16, Beijing (7.81 and Tianjin (7.81 were the largest and presented descending EPPs, whereas the EPCs of Heilongjiang (0.98, Hebei (0.98, Xinjiang (0.98 and Guangxi (0.98 were under the threshold value (1 and presented ascending EPPs. The carbon footprint in the secondary sector was the main embodied EF of the flows among the provinces responsible for inequities. Finally, based on the various conditions of the provinces in different geographical regions, we have provided suggestions for regionally balanced development that can maintain the EPP and EPC values under the threshold for each province.
International Nuclear Information System (INIS)
Suzuki, Kengo; Uchiyama, Yohji
2010-01-01
An increase in the price of imported fossil fuels indirectly increases the producer price in non-energy sectors; however, this indirect influence cannot be taken into account by the traditional portfolio approach. This study proposes an analytical framework combining the input-output (I-O) model and the portfolio approach that can take the indirect influence into account. A risk of an increase in the producer price in Japanese non-energy sectors during the period 1970-2000 is estimated, and the causes of a decrease in the risk through the analysis period are clarified by decomposing an index of the risk. The result indicates that almost all non-energy sectors have decreased this risk during the analysis period. The degree and cause of the decrease depends on a sector's location in the hierarchical structure of Japanese industries. For example, assembly sectors have decreased their risk mainly as the result of improvement in energy usage by upstream sectors, such as material sectors, rather than their own improvements. Proper policies considering such a structure are required to decrease the risk further because the effort taken to do so is seldom motivated by economic profit.
Directory of Open Access Journals (Sweden)
Zohreh Salimian
2012-01-01
Full Text Available Subsidizing energy in Iran has imposed high costs on country's economy. Thus revising energy prices, on the basis of a subsidy reform plan, is a vital remedy to boost up the economy. While the direct consequence of cutting subsidies on electricity generation costs can be determined in a simple way, identifying indirect effects, which reflect higher costs for input factors such as labor, is a challenging problem. In this paper, variables such as compensation of employees and private consumption are endogenized by using extended Input-Output (I-O price model to evaluate direct and indirect effects of electricity and fuel prices increase on economic subsectors. The determination of the short-run marginal generation cost of electricity using I-O technique with taken into account the Iranian targeted subsidy plan's influences is the main goal of this paper. Marginal cost of electricity, in various scenarios of price adjustment of energy, is estimated for three conventional categories of thermal power plants. Our results show that the raising the price of energy leads to an increase in the electricity production costs. Accordingly, the production costs will be higher than 1000 Rials per kWh until 2014 as predicted in the beginning of the reform plan by electricity suppliers.
Nakamura, Shinichiro; Kondo, Yasushi; Matsubae, Kazuyo; Nakajima, Kenichi; Tasaki, Tomohiro; Nagasaka, Tetsuya
2012-09-04
Metals can in theory be infinitely recycled in a closed-loop without any degradation in quality. In reality, however, open-loop recycling is more typical for metal scrap recovered from end-of-life (EoL) products because mixing of different metal species results in scrap quality that no longer matches the originals. Further losses occur when meeting the quality requirement of the target product requires dilution of the secondary material by adding high purity materials. Standard LCA usually does not address these losses. This paper presents a novel approach to quantifying quality- and dilution losses, by means of hybrid input-output analysis. We focus on the losses associated with the recycling of ferrous materials from end-of-life vehicle (ELV) due to the mixing of copper, a typical contaminant in steel recycling. Given the quality of scrap in terms of copper density, the model determines the ratio by which scrap needs to be diluted in an electric arc furnace (EAF), and the amount of demand for EAF steel including those quantities needed for dilution. Application to a high-resolution Japanese IO table supplemented with data on ferrous materials including different grades of scrap indicates that a nationwide avoidance of these losses could result in a significant reduction of CO(2) emissions.
International Nuclear Information System (INIS)
Park, Hi-Chun; Heo, Eunnyeong
2007-01-01
As energy conservation can be realized through changes in the composition of goods and services consumed, there is a need to assess indirect and total household energy requirements. The Korean household sector was responsible for about 52% of the national primary energy requirement in the period from 1980 to 2000. Of this total, more than 60% of household energy requirement was indirect. Thus, not only direct but also indirect household energy requirement should be the target of energy conservation policies. Electricity became the main fuel in household energy use in 2000. Households consume more and more electricity intensive goods and services, a sign of increasing living standards. Increases in household consumption expenditure were responsible for a relatively high growth of energy consumption. Switching to consumption of less energy intensive products and decrease in energy intensities of products in 1990s contributed substantially to reduce the increase in the total household energy requirement. A future Korean study should apply a hybrid method as to reduce errors occurred by using uniform (average) prices in constructing energy input-output tables and as to make energy intensities of different years more comparable. (author)
Schoer, Karl; Wood, Richard; Arto, Iñaki; Weinzettel, Jan
2013-12-17
The mass of material consumed by a population has become a useful proxy for measuring environmental pressure. The "raw material equivalents" (RME) metric of material consumption addresses the issue of including the full supply chain (including imports) when calculating national or product level material impacts. The RME calculation suffers from data availability, however, as quantitative data on production practices along the full supply chain (in different regions) is required. Hence, the RME is currently being estimated by three main approaches: (1) assuming domestic technology in foreign economies, (2) utilizing region-specific life-cycle inventories (in a hybrid framework), and (3) utilizing multi-regional input-output (MRIO) analysis to explicitly cover all regions of the supply chain. While the first approach has been shown to give inaccurate results, this paper focuses on the benefits and costs of the latter two approaches. We analyze results from two key (MRIO and hybrid) projects modeling raw material equivalents, adjusting the models in a stepwise manner in order to quantify the effects of individual conceptual elements. We attempt to isolate the MRIO gap, which denotes the quantitative impact of calculating the RME of imports by an MRIO approach instead of the hybrid model, focusing on the RME of EU external trade imports. While, the models give quantitatively similar results, differences become more pronounced when tracking more detailed material flows. We assess the advantages and disadvantages of the two approaches and look forward to ways to further harmonize data and approaches.
International Nuclear Information System (INIS)
Neuwahl, Frederik; Mongelli, Ignazio; Delgado, Luis; Loeschel, Andreas
2008-01-01
This paper analyses the employment consequences of policies aimed to support biofuels in the European Union. The promotion of biofuel use has been advocated as a means to promote the sustainable use of natural resources and to reduce greenhouse gas emissions originating from transport activities on the one hand, and to reduce dependence on imported oil and thereby increase security of the European energy supply on the other hand. The employment impacts of increasing biofuels shares are calculated by taking into account a set of elements comprising the demand for capital goods required to produce biofuels, the additional demand for agricultural feedstock, higher fuel prices or reduced household budget in the case of price subsidisation, price effects ensuing from a hypothetical world oil price reduction linked to substitution in the EU market, and price impacts on agro-food commodities. The calculations refer to scenarios for the year 2020 targets as set out by the recent Renewable Energy Roadmap. Employment effects are assessed in an input-output framework taking into account bottom-up technology information to specify biofuels activities and linked to partial equilibrium models for the agricultural and energy sectors. The simulations suggest that biofuels targets on the order of 10-15% could be achieved without adverse net employment effects. (author)
Directory of Open Access Journals (Sweden)
Seyhan KÂHYA
2017-02-01
Full Text Available The `Chocolate law’ in Switzerland enables subsidies for dairy and wheat farmers, bound to the condition that their products are exported after processing (Swiss Federation, 2011. Though the Ministerial Conference of the World Trade Organization has decided in December 2015 that this law has to be abolished by 2021 [WTO, 2015]. Cutting subsidies might lead to a demand shock and consequently a cropped domestic production (Miller and Blair, 1985. We analysed in this study the interdependence of the agro-food sectors by a Leontief input-output model and their linkages to other sectors (Chereny and Watanabe, 1958, Leontief 1986 and additionally, the amount, direction and dispersion of the possible demand shock. Hence, non-meat food processors and dairy processing were determined as key sectors as they have strong linkage effects and are rather concentrated to few sectors. Both sectors rely strongly on the output of the raw milk producers and have few sectors to sell their products. Outside of the cut sectors, these sectors will be challenged the most from this new policy.
van der Heijden, Gregory; Legout, Arnaud; Mareschal, Louis; Ranger, Jacques; Dambrine, Etienne
2017-07-01
In terrestrial ecosystems, plant-available pools of magnesium and calcium are assumed to be stored in the soil as exchangeable cations adsorbed on the surface of mineral and/or organic particles. The pools of exchangeable magnesium and calcium are measured by ion-exchange soil extractions. These pools are sustained in the long term by the weathering of primary minerals in the soil and atmospheric inputs. This conceptual model is the base of input-output budgets from which soil acidification and the sustainability of soil chemical fertility is inferred. However, this model has been questioned by data from long-term forest ecosystem monitoring sites, particularly for calcium. Quantifying the contribution of atmospheric inputs, ion exchange and weathering of both primary, secondary and non-crystalline phases to tree nutrition in the short term is challenging. In this study, we developed and applied a novel isotopic dilution technique using the stable isotopes of magnesium and calcium to study the contribution of the different soil phases to soil solution chemistry in a very acidic soil. The labile pools of Mg and Ca in the soil (pools in equilibrium with the soil solution) were isotopically labeled by spraying a solution enriched in 26Mg and 44Ca on the soil. Labeled soil columns were then percolated with a dilute acid solution during a 3-month period and the isotopic dilution of the tracers was monitored in the leaching solution, in the exchangeable (2 sequential 1 mol L-1 ammonium acetate extractions) and non-crystalline (2 sequential soil digestions: oxalic acid followed by nitric acid) phases. Significant amounts of Mg and Ca isotope tracer were recovered in the non-crystalline soil phases. These phases represented from 5% to 25% and from 24% to 50%, respectively, of the Mg and Ca labile pools during the experiment. Our results show that non-crystalline phases act as both a source and a sink of calcium and magnesium in the soil, and contribute directly to soil
Chen, Weiming; Wu, Sanmang; Lei, Yalin; Li, Shantong
2017-04-15
Commodity trade between regions implies a large amount of energy transfer. As an important economic growth pole of China, the Jing-Jin-Ji area (Beijing-Tianjin-Hebei) is also one of the areas with the largest energy consumption in China. Moreover, the primary energy consumer goods in this area are fossil fuels, such as coal. This has led to serious air pollution in the area. Therefore, the reduction of energy consumption under the premise of maintaining sustained economic growth is an important task of the Jing-Jin-Ji area. In this study, an interprovincial input-output model was applied to quantitatively estimate the embodied energy transfer between Jing-Jin-Ji area and other provinces in China. The results indicated that the Metal and nonmetal mineral processing industry and the Electrical, gas and water industry in the Jing-Jin-Ji area exported a large amount of embodied energy to the Yangtze River Delta and the Pearl River Delta. However, the embodied energy export of the Jing-Jin-Ji area mainly exported by Hebei province. Beijing and Tianjin even have some net import of embodied energy. The embodied energy transfer between Tianjin, Hebei and other provinces was mainly driven by investment, while the main media of embodied energy transfer between Beijing and other provinces was consumption. Therefore, we suggest that the Jing-Jin-Ji area should further increase the degree of dependence on other provinces' energy-intensive products and reduce the export of energy-intensive products. In addition, there should be difference in the energy and industrial policies among Beijing, Tianjin and Hebei, and the problems of high energy consumption and high proportion of heavy industry in Hebei should be first resolved. Copyright © 2017 Elsevier B.V. All rights reserved.
Directory of Open Access Journals (Sweden)
Nurul Fajri
2016-11-01
Full Text Available High economic growth is the target of economic development in each area. Economic development should be prioritized in sectors that can be a major driver of the economy so that the economy can grow faster. Economic growth can be seen from the aggregate demand side, namely consumption, investment, government spending, exports and imports, and the aggregate supply side namely labor growth, capital growth and the growth of TFP (Total Factor Productivity. This study uses South Kalimantan’s Input-Output Tables of 2000, 2005 and 2010. The results showed that although the structure of the value-added of the mining sector remains the main economic pillar, but this sector has low linkages with other sectors. The prime mover and driving economic growth sector are manufacturing sector i.e chemical industry, food, beverages and tobacco industry, rubber and plastics industry, paper, printing and publishing industry and industry of metal, machinery, transport equipment and other manufacturing industries. Based Multiplier Product Matrix, manufacturing industry suggest a leading role in the economy so that it can be said that the province of South Kalimantan are heading toward a change in the economic structure. Decomposition of sources of growth based on the Chenery’s model (1960 showed that the main source of economic growth in South Kalimantan is exports by 67 percent in the period 2000-2005 and 73.72 percent in the period 2005-2010, especially the export of coal. Decomposition of productivity growth made by Namura and Kuroda’s model (2004 and suggests that TFP growth and capital have a strong linear relationship and significant Output growth, while labor productivity have no significant correlation with Output growth. Finally, the wealth of the abundant natural resources, industry-oriented economic growth and sustainable development in South Kalimantan Province is agriculture-based industries and mining-based industries with the main strategy is to
Wang, Hao; Chen, Cao-cao; Pan, Tao; Liu, Chun-lan; Chen, Long; Sun, Li
2014-09-01
Distinguishing product-based and consumption-based CO2 emissions in the open economic region is the basis for differentiating the emission responsibility, which is attracting increasing attention of decision-makers'attention. The spatial and temporal characteristics of product-based and consumption-based CO2 emissions, as well as carbon balance, in 1997, 2002 and 2007 of JING- JIN-JI region were analyzed by the Economic Input-Output-Life Cycle Assessment model. The results revealed that both the product- based and consumption-based CO2 emissions in the region have been increased by about 4% annually. The percentage of CO2 emissions embodied in trade was 30% -83% , to which the domestic trading added the most. The territorial and consumption-based CO2 emissions in Hebei province were the predominant emission in JING-JIN-JI region, and the increasing speed and emission intensity were stronger than those of Beijing and Tianjin. JING-JIN-JI region was a net inflow region of CO2 emissions, and parts of the emission responsibility were transferred. Beijing and Tianjin were the net importers of CO2 emissions, and Hebei was a net outflow area of CO2 emissions. The key CO2 emission departments in the region were concentrated, and the similarity was great. The inter-regional mechanisms could be set up for joint prevention and control work. - Production and distribution of electricity, gas and water and smelting and pressing of metals had the highest reliability on CO2 emissions, and took on the responsibility of other departments. The EIO-LCA model could be used to analyze the product-based and consumption-based CO2 emissions, which is helpful for the delicate management of regional CO2 emissions reduction and policies making, and stimulating the reduction cooperation at regional scale.
Xing, Zhencheng; Wang, Jigan; Zhang, Jie
2018-09-01
Due to the increasing environmental burdens caused by dramatic economic expansion, eco-efficiency indicating how efficient the economic activity is with respect to its environmental impacts has become a topic of considerable interest in China. In this context, Economic Input-output Life Cycle Assessment (EIO-LCA) and Data Envelopment Analysis (DEA) are combined to assess the environmental impacts and eco-efficiency of China's 26 economic sectors. The EIO-LCA results indicate that Electricity Production and Supply sector is the largest net exporter in energy usage, CO 2 emission and exhaust emission categories, while Construction sector is the largest net importer for five impact categories except for water withdrawal. Moreover, Construction sector is found to be the destination of the largest sector-to-sector environmental impact flows for the five impact categories and make the most contributions to the total environmental impacts. Another key finding is that Agriculture sector is both the largest net exporter and the greatest contributor for water withdrawal category. DEA results indicate that seven sectors are eco-efficient while over 70% of China's economic sectors are inefficient and require significant improvements. The average target improvements range between 23.30% and 35.06% depending on the impact category. Further sensitivity analysis reveals that the average sensitivity ratios vary from 7.7% to 15.7% among the six impact categories, which are found to be negatively correlated with their improvement potentials. Finally, several policy recommendations are made to mitigate environmental impacts of China's economic sectors and improve their eco-efficiency levels. Copyright © 2018 Elsevier B.V. All rights reserved.
Li, Jiashuo; Luo, Ran; Yang, Qing; Yang, Haiping
2016-12-01
Based on an input-output analysis, this paper compiles inventories of fuel-related CO2 emissions of Hubei economy in the years of 2002, 2005, and 2007. Results show that calculated total direct CO2 emissions rose from 114,462.69 kt (2002) to 196,650.31 kt (2005), reaching 210,419.93 kt in 2007, with an average 22.50% rate of increase. Raw coal was the dominant source of the direct emissions throughout the three years. The sector of Electric Power, Heat Production, and Supply was the main direct emissions contributor, with the largest intensities observed from 2002 (1192.97 g/CNY) to 2007 (1739.15 g/ CNY). From the industrial perspective, the secondary industry, which is characterized as manufacture of finished products, was still the pillar of the Hubei economy during this period concerned, contributing more than 80% of the total direct emissions. As a net exporter of embodied CO2 emissions in 2002 and 2007, Hubei reported net-exported emissions of 4109.00 kt and 17,871.77 kt respectively; however, Hubei was once a net importer of CO2 emissions in 2005 (2511.93 kt). The CO2 emissions embodied in export and fixed capital formation had the two leading fractions of emissions embodied in the final use. The corresponding countermeasures, such as promoting renewable and clean energy and properly reducing the exports of low value added and carbon-intensive products are suggestions for reducing CO2 emissions in Hubei.
Modeling High-Dimensional Multichannel Brain Signals
Hu, Lechuan; Fortin, Norbert J.; Ombao, Hernando
2017-01-01
aspects: first, there are major statistical and computational challenges for modeling and analyzing high-dimensional multichannel brain signals; second, there is no set of universally agreed measures for characterizing connectivity. To model multichannel
International Nuclear Information System (INIS)
Jeeninga, H.; Weber, C.; Maeenpaeae, I.; Rivero Garcia, F.; Wiltshire, V.; Wade, J.
1999-10-01
The relationship between investments in energy efficiency and employment is investigated. The employment effects of several energy conservation schemes implemented in the residential sector are determined by means of a dedicated input/output simulation approach. The employment effects of energy conservation schemes were determined for France, Germany, the Netherlands, Spain and the United Kingdom. Within the time frame of the project, it was not feasible to perform a comparable analysis for Greece, Ireland and Austria. For Finland, the employment effects of energy auditing schemes were investigated by means of a macro economic simulation model. The main driving force behind the positive employment effect of investment in energy efficiency in the residential sector is the fact that the energy sector has a rather low labour intensity. The resulting shift of expenditures from the energy sector to other sectors with higher labour intensity leads to increased employment. The main mechanisms that determine the net shift in employment resulting from investments in energy conservation are: 1. The employment effect related to the initial investment in energy efficiency; 2. The energy saving effect. Due to lower energy bill, a shift in expenditure pattern will occur from the labour extensive energy sector towards sectors with higher labour intensity, thus inducing a net positive effect on employment; 3. The effects of money transfers between sectors. For example, when the investment is subsidised by the government, money is transferred from the governmental sector to the residential sector; 4. Changes in the total government budget as a result of changes in total tax revenue and expenditures on unemployment benefits. Different financing methods for the investment in energy efficiency are analysed. The initial investment can be financed from the general household consumption budget, by means of a loan, using a subsidy or using private savings. The following input parameters
Acquaye, Adolf; Feng, Kuishuang; Oppon, Eunice; Salhi, Said; Ibn-Mohammed, Taofeeq; Genovese, Andrea; Hubacek, Klaus
2017-02-01
Measuring the performance of environmentally sustainable supply chains instead of chain constitute has become a challenge despite the convergence of the underlining principles of sustainable supply chain management. This challenge is exacerbated by the fact that supply chains are inherently dynamic and complex and also because multiple measures can be used to characterize performances. By identifying some of the critical issues in the literature regarding performance measurements, this paper contributes to the existing body of literature by adopting an environmental performance measurement approach for economic sectors. It uses economic sectors and evaluates them on a sectoral level in specific countries as well as part of the Global Value Chain based on the established multi-regional input-output (MRIO) modeling framework. The MRIO model has been used to calculate direct and indirect (that is supply chain or upstream) environmental effects such as CO 2 , SO 2 , biodiversity, water consumption and pollution to name just a few of the applications. In this paper we use MRIO analysis to calculate emissions and resource consumption intensities and footprints, direct and indirect impacts, and net emission flows between countries. These are exemplified by using carbon emissions, sulphur oxide emissions and water use in two highly polluting industries; Electricity production and Chemical industry in 33 countries, including the EU-27, Brazil, India and China, the USA, Canada and Japan from 1995 to 2009. Some of the highlights include: On average, direct carbon emissions in the electricity sector across all 27 member states of the EU was estimated to be 1368 million tons and indirect carbon emissions to be 470.7 million tons per year representing 25.6% of the EU-27 total carbon emissions related to this sector. It was also observed that from 2004, sulphur oxide emissions intensities in electricity production in India and China have remained relatively constant at about 62
High dimensional neurocomputing growth, appraisal and applications
Tripathi, Bipin Kumar
2015-01-01
The book presents a coherent understanding of computational intelligence from the perspective of what is known as "intelligent computing" with high-dimensional parameters. It critically discusses the central issue of high-dimensional neurocomputing, such as quantitative representation of signals, extending the dimensionality of neuron, supervised and unsupervised learning and design of higher order neurons. The strong point of the book is its clarity and ability of the underlying theory to unify our understanding of high-dimensional computing where conventional methods fail. The plenty of application oriented problems are presented for evaluating, monitoring and maintaining the stability of adaptive learning machine. Author has taken care to cover the breadth and depth of the subject, both in the qualitative as well as quantitative way. The book is intended to enlighten the scientific community, ranging from advanced undergraduates to engineers, scientists and seasoned researchers in computational intelligenc...
Asymptotically Honest Confidence Regions for High Dimensional
DEFF Research Database (Denmark)
Caner, Mehmet; Kock, Anders Bredahl
While variable selection and oracle inequalities for the estimation and prediction error have received considerable attention in the literature on high-dimensional models, very little work has been done in the area of testing and construction of confidence bands in high-dimensional models. However...... develop an oracle inequality for the conservative Lasso only assuming the existence of a certain number of moments. This is done by means of the Marcinkiewicz-Zygmund inequality which in our context provides sharper bounds than Nemirovski's inequality. As opposed to van de Geer et al. (2014) we allow...
Hannon, Bruce
2010-01-01
A summary is provided of the early history of research on the flow of nonrenewable energy resources through the economy and of the flow of renewable energy resources through a natural ecosystem. The techniques are similar, and many specific applications are provided. A combined economic and ecological technique is also defined. The early history and people of the International Society Ecological Economic are cited.
Quantifying high dimensional entanglement with two mutually unbiased bases
Directory of Open Access Journals (Sweden)
Paul Erker
2017-07-01
Full Text Available We derive a framework for quantifying entanglement in multipartite and high dimensional systems using only correlations in two unbiased bases. We furthermore develop such bounds in cases where the second basis is not characterized beyond being unbiased, thus enabling entanglement quantification with minimal assumptions. Furthermore, we show that it is feasible to experimentally implement our method with readily available equipment and even conservative estimates of physical parameters.
High-dimensional quantum cloning and applications to quantum hacking.
Bouchard, Frédéric; Fickler, Robert; Boyd, Robert W; Karimi, Ebrahim
2017-02-01
Attempts at cloning a quantum system result in the introduction of imperfections in the state of the copies. This is a consequence of the no-cloning theorem, which is a fundamental law of quantum physics and the backbone of security for quantum communications. Although perfect copies are prohibited, a quantum state may be copied with maximal accuracy via various optimal cloning schemes. Optimal quantum cloning, which lies at the border of the physical limit imposed by the no-signaling theorem and the Heisenberg uncertainty principle, has been experimentally realized for low-dimensional photonic states. However, an increase in the dimensionality of quantum systems is greatly beneficial to quantum computation and communication protocols. Nonetheless, no experimental demonstration of optimal cloning machines has hitherto been shown for high-dimensional quantum systems. We perform optimal cloning of high-dimensional photonic states by means of the symmetrization method. We show the universality of our technique by conducting cloning of numerous arbitrary input states and fully characterize our cloning machine by performing quantum state tomography on cloned photons. In addition, a cloning attack on a Bennett and Brassard (BB84) quantum key distribution protocol is experimentally demonstrated to reveal the robustness of high-dimensional states in quantum cryptography.
Introduction to high-dimensional statistics
Giraud, Christophe
2015-01-01
Ever-greater computing technologies have given rise to an exponentially growing volume of data. Today massive data sets (with potentially thousands of variables) play an important role in almost every branch of modern human activity, including networks, finance, and genetics. However, analyzing such data has presented a challenge for statisticians and data analysts and has required the development of new statistical methods capable of separating the signal from the noise.Introduction to High-Dimensional Statistics is a concise guide to state-of-the-art models, techniques, and approaches for ha
Estimating High-Dimensional Time Series Models
DEFF Research Database (Denmark)
Medeiros, Marcelo C.; Mendes, Eduardo F.
We study the asymptotic properties of the Adaptive LASSO (adaLASSO) in sparse, high-dimensional, linear time-series models. We assume both the number of covariates in the model and candidate variables can increase with the number of observations and the number of candidate variables is, possibly......, larger than the number of observations. We show the adaLASSO consistently chooses the relevant variables as the number of observations increases (model selection consistency), and has the oracle property, even when the errors are non-Gaussian and conditionally heteroskedastic. A simulation study shows...
High dimensional classifiers in the imbalanced case
DEFF Research Database (Denmark)
Bak, Britta Anker; Jensen, Jens Ledet
We consider the binary classification problem in the imbalanced case where the number of samples from the two groups differ. The classification problem is considered in the high dimensional case where the number of variables is much larger than the number of samples, and where the imbalance leads...... to a bias in the classification. A theoretical analysis of the independence classifier reveals the origin of the bias and based on this we suggest two new classifiers that can handle any imbalance ratio. The analytical results are supplemented by a simulation study, where the suggested classifiers in some...
Topology of high-dimensional manifolds
Energy Technology Data Exchange (ETDEWEB)
Farrell, F T [State University of New York, Binghamton (United States); Goettshe, L [Abdus Salam ICTP, Trieste (Italy); Lueck, W [Westfaelische Wilhelms-Universitaet Muenster, Muenster (Germany)
2002-08-15
The School on High-Dimensional Manifold Topology took place at the Abdus Salam ICTP, Trieste from 21 May 2001 to 8 June 2001. The focus of the school was on the classification of manifolds and related aspects of K-theory, geometry, and operator theory. The topics covered included: surgery theory, algebraic K- and L-theory, controlled topology, homology manifolds, exotic aspherical manifolds, homeomorphism and diffeomorphism groups, and scalar curvature. The school consisted of 2 weeks of lecture courses and one week of conference. Thwo-part lecture notes volume contains the notes of most of the lecture courses.
Modeling high dimensional multichannel brain signals
Hu, Lechuan
2017-03-27
In this paper, our goal is to model functional and effective (directional) connectivity in network of multichannel brain physiological signals (e.g., electroencephalograms, local field potentials). The primary challenges here are twofold: first, there are major statistical and computational difficulties for modeling and analyzing high dimensional multichannel brain signals; second, there is no set of universally-agreed measures for characterizing connectivity. To model multichannel brain signals, our approach is to fit a vector autoregressive (VAR) model with sufficiently high order so that complex lead-lag temporal dynamics between the channels can be accurately characterized. However, such a model contains a large number of parameters. Thus, we will estimate the high dimensional VAR parameter space by our proposed hybrid LASSLE method (LASSO+LSE) which is imposes regularization on the first step (to control for sparsity) and constrained least squares estimation on the second step (to improve bias and mean-squared error of the estimator). Then to characterize connectivity between channels in a brain network, we will use various measures but put an emphasis on partial directed coherence (PDC) in order to capture directional connectivity between channels. PDC is a directed frequency-specific measure that explains the extent to which the present oscillatory activity in a sender channel influences the future oscillatory activity in a specific receiver channel relative all possible receivers in the network. Using the proposed modeling approach, we have achieved some insights on learning in a rat engaged in a non-spatial memory task.
Modeling high dimensional multichannel brain signals
Hu, Lechuan; Fortin, Norbert; Ombao, Hernando
2017-01-01
In this paper, our goal is to model functional and effective (directional) connectivity in network of multichannel brain physiological signals (e.g., electroencephalograms, local field potentials). The primary challenges here are twofold: first, there are major statistical and computational difficulties for modeling and analyzing high dimensional multichannel brain signals; second, there is no set of universally-agreed measures for characterizing connectivity. To model multichannel brain signals, our approach is to fit a vector autoregressive (VAR) model with sufficiently high order so that complex lead-lag temporal dynamics between the channels can be accurately characterized. However, such a model contains a large number of parameters. Thus, we will estimate the high dimensional VAR parameter space by our proposed hybrid LASSLE method (LASSO+LSE) which is imposes regularization on the first step (to control for sparsity) and constrained least squares estimation on the second step (to improve bias and mean-squared error of the estimator). Then to characterize connectivity between channels in a brain network, we will use various measures but put an emphasis on partial directed coherence (PDC) in order to capture directional connectivity between channels. PDC is a directed frequency-specific measure that explains the extent to which the present oscillatory activity in a sender channel influences the future oscillatory activity in a specific receiver channel relative all possible receivers in the network. Using the proposed modeling approach, we have achieved some insights on learning in a rat engaged in a non-spatial memory task.
Inoue, Yasushi; Katayama, Arata
2011-09-15
A two-scale evaluation concept of remediation technologies for a contaminated site was expanded by introducing life cycle costing (LCC) and economic input-output life cycle assessment (EIO-LCA). The expanded evaluation index, the rescue number for soil (RN(SOIL)) with LCC and EIO-LCA, comprises two scales, such as risk-cost, risk-energy consumption or risk-CO(2) emission of a remediation. The effectiveness of RN(SOIL) with LCC and EIO-LCA was examined in a typical contamination and remediation scenario in which dieldrin contaminated an agricultural field. Remediation was simulated using four technologies: disposal, high temperature thermal desorption, biopile and landfarming. Energy consumption and CO(2) emission were determined from a life cycle inventory analysis using monetary-based intensity based on an input-output table. The values of RN(SOIL) based on risk-cost, risk-energy consumption and risk-CO(2) emission were calculated, and then rankings of the candidates were compiled according to RN(SOIL) values. A comparison between three rankings showed the different ranking orders. The existence of differences in ranking order indicates that the scales would not have reciprocal compatibility for two-scale evaluation and that each scale should be used independently. The RN(SOIL) with LCA will be helpful in selecting a technology, provided an appropriate scale is determined. Copyright © 2011 Elsevier B.V. All rights reserved.
Mitigating the Insider Threat Using High-Dimensional Search and Modeling
National Research Council Canada - National Science Library
Van Den Berg, Eric; Uphadyaya, Shambhu; Ngo, Phi H; Muthukrishnan, Muthu; Palan, Rajago
2006-01-01
In this project a system was built aimed at mitigating insider attacks centered around a high-dimensional search engine for correlating the large number of monitoring streams necessary for detecting insider attacks...
Clustering high dimensional data using RIA
Energy Technology Data Exchange (ETDEWEB)
Aziz, Nazrina [School of Quantitative Sciences, College of Arts and Sciences, Universiti Utara Malaysia, 06010 Sintok, Kedah (Malaysia)
2015-05-15
Clustering may simply represent a convenient method for organizing a large data set so that it can easily be understood and information can efficiently be retrieved. However, identifying cluster in high dimensionality data sets is a difficult task because of the curse of dimensionality. Another challenge in clustering is some traditional functions cannot capture the pattern dissimilarity among objects. In this article, we used an alternative dissimilarity measurement called Robust Influence Angle (RIA) in the partitioning method. RIA is developed using eigenstructure of the covariance matrix and robust principal component score. We notice that, it can obtain cluster easily and hence avoid the curse of dimensionality. It is also manage to cluster large data sets with mixed numeric and categorical value.
Directory of Open Access Journals (Sweden)
J. Norberto Pires
2007-08-01
Full Text Available Interaction with robot systems for specification of manufacturing tasks and motions needs to be simple, to enable wide-spread use of robots in SMEs. In the best case, existing practices from manual work could be used, to smoothly let current employees start using robot technology as a natural part of their work. Our aim is to simplify the robot programming task by allowing the user to simply make technical drawings on a sheet of paper. Craftsman use paper and raw sketches for several situations; to share ideas, to get a better imagination or to remember the customer situation. Currently these sketches have either to be interpreted by the worker when producing the final product by hand, or transferred into CAD file using an according tool. The former means that no automation is included, the latter means extra work and much experience in using the CAD tool. Our approach is to use the digital pen and paper from Anoto as input devices for SME robotic tasks, thereby creating simpler and more user friendly alternatives for programming, parameterization and commanding actions. To this end, the basic technology has been investigated and fully working prototypes have been developed to explore the possibilities and limitation in the context of typical SME applications. Based on the encouraging experimental results, we believe that drawings on digital paper will, among other means of human-robot interaction, play
Alises Pérez, Ana; Vassallo Magro, José Manuel
2014-01-01
En la mayoría de países industrializados la demanda de transporte de mercancías por carretera ha venido ligada al crecimiento económico. Sin embargo, las últimas décadas se ha visto cómo esta relación se está perdiendo en algunos países y se están registrando caídas del transporte, incluso en periodos de expansión económica. Este artículo propone un análisis Input-Output de descomposición estructural para explicar cuáles son los factores que, además del crecimiento del PIB considerado tradici...
International Nuclear Information System (INIS)
Ko, Jong-Hwan.
1993-01-01
Firstly, this study investigaties the causes of sectoral growth and structural changes in the Korean economy. Secondly, it develops the borders of a consistent economic model in order to investigate simultaneously the different impacts of changes in energy and in the domestic economy. This is done any both the Input-Output-Decomposition analysis and a Computable General Equilibrium model (CGE Model). The CGE Model eliminates the disadvantages of the IO Model and allows the investigation of the interdegenerative of the various energy sectors with the economy. The Social Accounting Matrix serves as the data basis of the GCE Model. Simulated experiments have been comet out with the help of the GCE Model, indicating the likely impact of an oil price shock in the economy-sectorally and generally. (orig.) [de
High-Dimensional Quantum Information Processing with Linear Optics
Fitzpatrick, Casey A.
Quantum information processing (QIP) is an interdisciplinary field concerned with the development of computers and information processing systems that utilize quantum mechanical properties of nature to carry out their function. QIP systems have become vastly more practical since the turn of the century. Today, QIP applications span imaging, cryptographic security, computation, and simulation (quantum systems that mimic other quantum systems). Many important strategies improve quantum versions of classical information system hardware, such as single photon detectors and quantum repeaters. Another more abstract strategy engineers high-dimensional quantum state spaces, so that each successful event carries more information than traditional two-level systems allow. Photonic states in particular bring the added advantages of weak environmental coupling and data transmission near the speed of light, allowing for simpler control and lower system design complexity. In this dissertation, numerous novel, scalable designs for practical high-dimensional linear-optical QIP systems are presented. First, a correlated photon imaging scheme using orbital angular momentum (OAM) states to detect rotational symmetries in objects using measurements, as well as building images out of those interactions is reported. Then, a statistical detection method using chains of OAM superpositions distributed according to the Fibonacci sequence is established and expanded upon. It is shown that the approach gives rise to schemes for sorting, detecting, and generating the recursively defined high-dimensional states on which some quantum cryptographic protocols depend. Finally, an ongoing study based on a generalization of the standard optical multiport for applications in quantum computation and simulation is reported upon. The architecture allows photons to reverse momentum inside the device. This in turn enables realistic implementation of controllable linear-optical scattering vertices for
Input-output rearrangement of isolated converters
DEFF Research Database (Denmark)
Madsen, Mickey Pierre; Kovacevic, Milovan; Mønster, Jakob Døllner
2015-01-01
This paper presents a new way of rearranging the input and output of isolated converters. The new arrangement posses several advantages, as increased voltage range, higher power handling capabilities, reduced voltage stress and improved efficiency, for applications where galvanic isolation...
Modeling High-Dimensional Multichannel Brain Signals
Hu, Lechuan
2017-12-12
Our goal is to model and measure functional and effective (directional) connectivity in multichannel brain physiological signals (e.g., electroencephalograms, local field potentials). The difficulties from analyzing these data mainly come from two aspects: first, there are major statistical and computational challenges for modeling and analyzing high-dimensional multichannel brain signals; second, there is no set of universally agreed measures for characterizing connectivity. To model multichannel brain signals, our approach is to fit a vector autoregressive (VAR) model with potentially high lag order so that complex lead-lag temporal dynamics between the channels can be captured. Estimates of the VAR model will be obtained by our proposed hybrid LASSLE (LASSO + LSE) method which combines regularization (to control for sparsity) and least squares estimation (to improve bias and mean-squared error). Then we employ some measures of connectivity but put an emphasis on partial directed coherence (PDC) which can capture the directional connectivity between channels. PDC is a frequency-specific measure that explains the extent to which the present oscillatory activity in a sender channel influences the future oscillatory activity in a specific receiver channel relative to all possible receivers in the network. The proposed modeling approach provided key insights into potential functional relationships among simultaneously recorded sites during performance of a complex memory task. Specifically, this novel method was successful in quantifying patterns of effective connectivity across electrode locations, and in capturing how these patterns varied across trial epochs and trial types.
High-dimensional single-cell cancer biology.
Irish, Jonathan M; Doxie, Deon B
2014-01-01
Cancer cells are distinguished from each other and from healthy cells by features that drive clonal evolution and therapy resistance. New advances in high-dimensional flow cytometry make it possible to systematically measure mechanisms of tumor initiation, progression, and therapy resistance on millions of cells from human tumors. Here we describe flow cytometry techniques that enable a "single-cell " view of cancer. High-dimensional techniques like mass cytometry enable multiplexed single-cell analysis of cell identity, clinical biomarkers, signaling network phospho-proteins, transcription factors, and functional readouts of proliferation, cell cycle status, and apoptosis. This capability pairs well with a signaling profiles approach that dissects mechanism by systematically perturbing and measuring many nodes in a signaling network. Single-cell approaches enable study of cellular heterogeneity of primary tissues and turn cell subsets into experimental controls or opportunities for new discovery. Rare populations of stem cells or therapy-resistant cancer cells can be identified and compared to other types of cells within the same sample. In the long term, these techniques will enable tracking of minimal residual disease (MRD) and disease progression. By better understanding biological systems that control development and cell-cell interactions in healthy and diseased contexts, we can learn to program cells to become therapeutic agents or target malignant signaling events to specifically kill cancer cells. Single-cell approaches that provide deep insight into cell signaling and fate decisions will be critical to optimizing the next generation of cancer treatments combining targeted approaches and immunotherapy.
Network Reconstruction From High-Dimensional Ordinary Differential Equations.
Chen, Shizhe; Shojaie, Ali; Witten, Daniela M
2017-01-01
We consider the task of learning a dynamical system from high-dimensional time-course data. For instance, we might wish to estimate a gene regulatory network from gene expression data measured at discrete time points. We model the dynamical system nonparametrically as a system of additive ordinary differential equations. Most existing methods for parameter estimation in ordinary differential equations estimate the derivatives from noisy observations. This is known to be challenging and inefficient. We propose a novel approach that does not involve derivative estimation. We show that the proposed method can consistently recover the true network structure even in high dimensions, and we demonstrate empirical improvement over competing approaches. Supplementary materials for this article are available online.
Engineering two-photon high-dimensional states through quantum interference
Zhang, Yingwen; Roux, Filippus S.; Konrad, Thomas; Agnew, Megan; Leach, Jonathan; Forbes, Andrew
2016-01-01
Many protocols in quantum science, for example, linear optical quantum computing, require access to large-scale entangled quantum states. Such systems can be realized through many-particle qubits, but this approach often suffers from scalability problems. An alternative strategy is to consider a lesser number of particles that exist in high-dimensional states. The spatial modes of light are one such candidate that provides access to high-dimensional quantum states, and thus they increase the storage and processing potential of quantum information systems. We demonstrate the controlled engineering of two-photon high-dimensional states entangled in their orbital angular momentum through Hong-Ou-Mandel interference. We prepare a large range of high-dimensional entangled states and implement precise quantum state filtering. We characterize the full quantum state before and after the filter, and are thus able to determine that only the antisymmetric component of the initial state remains. This work paves the way for high-dimensional processing and communication of multiphoton quantum states, for example, in teleportation beyond qubits. PMID:26933685
Multivariate statistics high-dimensional and large-sample approximations
Fujikoshi, Yasunori; Shimizu, Ryoichi
2010-01-01
A comprehensive examination of high-dimensional analysis of multivariate methods and their real-world applications Multivariate Statistics: High-Dimensional and Large-Sample Approximations is the first book of its kind to explore how classical multivariate methods can be revised and used in place of conventional statistical tools. Written by prominent researchers in the field, the book focuses on high-dimensional and large-scale approximations and details the many basic multivariate methods used to achieve high levels of accuracy. The authors begin with a fundamental presentation of the basic
Hierarchical low-rank approximation for high dimensional approximation
Nouy, Anthony
2016-01-01
Tensor methods are among the most prominent tools for the numerical solution of high-dimensional problems where functions of multiple variables have to be approximated. Such high-dimensional approximation problems naturally arise in stochastic analysis and uncertainty quantification. In many practical situations, the approximation of high-dimensional functions is made computationally tractable by using rank-structured approximations. In this talk, we present algorithms for the approximation in hierarchical tensor format using statistical methods. Sparse representations in a given tensor format are obtained with adaptive or convex relaxation methods, with a selection of parameters using crossvalidation methods.
Hierarchical low-rank approximation for high dimensional approximation
Nouy, Anthony
2016-01-07
Tensor methods are among the most prominent tools for the numerical solution of high-dimensional problems where functions of multiple variables have to be approximated. Such high-dimensional approximation problems naturally arise in stochastic analysis and uncertainty quantification. In many practical situations, the approximation of high-dimensional functions is made computationally tractable by using rank-structured approximations. In this talk, we present algorithms for the approximation in hierarchical tensor format using statistical methods. Sparse representations in a given tensor format are obtained with adaptive or convex relaxation methods, with a selection of parameters using crossvalidation methods.
High-dimensional quantum cryptography with twisted light
International Nuclear Information System (INIS)
Mirhosseini, Mohammad; Magaña-Loaiza, Omar S; O’Sullivan, Malcolm N; Rodenburg, Brandon; Malik, Mehul; Boyd, Robert W; Lavery, Martin P J; Padgett, Miles J; Gauthier, Daniel J
2015-01-01
Quantum key distribution (QKD) systems often rely on polarization of light for encoding, thus limiting the amount of information that can be sent per photon and placing tight bounds on the error rates that such a system can tolerate. Here we describe a proof-of-principle experiment that indicates the feasibility of high-dimensional QKD based on the transverse structure of the light field allowing for the transfer of more than 1 bit per photon. Our implementation uses the orbital angular momentum (OAM) of photons and the corresponding mutually unbiased basis of angular position (ANG). Our experiment uses a digital micro-mirror device for the rapid generation of OAM and ANG modes at 4 kHz, and a mode sorter capable of sorting single photons based on their OAM and ANG content with a separation efficiency of 93%. Through the use of a seven-dimensional alphabet encoded in the OAM and ANG bases, we achieve a channel capacity of 2.05 bits per sifted photon. Our experiment demonstrates that, in addition to having an increased information capacity, multilevel QKD systems based on spatial-mode encoding can be more resilient against intercept-resend eavesdropping attacks. (paper)
Explorations on High Dimensional Landscapes: Spin Glasses and Deep Learning
Sagun, Levent
This thesis deals with understanding the structure of high-dimensional and non-convex energy landscapes. In particular, its focus is on the optimization of two classes of functions: homogeneous polynomials and loss functions that arise in machine learning. In the first part, the notion of complexity of a smooth, real-valued function is studied through its critical points. Existing theoretical results predict that certain random functions that are defined on high dimensional domains have a narrow band of values whose pre-image contains the bulk of its critical points. This section provides empirical evidence for convergence of gradient descent to local minima whose energies are near the predicted threshold justifying the existing asymptotic theory. Moreover, it is empirically shown that a similar phenomenon may hold for deep learning loss functions. Furthermore, there is a comparative analysis of gradient descent and its stochastic version showing that in high dimensional regimes the latter is a mere speedup. The next study focuses on the halting time of an algorithm at a given stopping condition. Given an algorithm, the normalized fluctuations of the halting time follow a distribution that remains unchanged even when the input data is sampled from a new distribution. Two qualitative classes are observed: a Gumbel-like distribution that appears in Google searches, human decision times, and spin glasses and a Gaussian-like distribution that appears in conjugate gradient method, deep learning with MNIST and random input data. Following the universality phenomenon, the Hessian of the loss functions of deep learning is studied. The spectrum is seen to be composed of two parts, the bulk which is concentrated around zero, and the edges which are scattered away from zero. Empirical evidence is presented for the bulk indicating how over-parametrized the system is, and for the edges that depend on the input data. Furthermore, an algorithm is proposed such that it would
Global communication schemes for the numerical solution of high-dimensional PDEs
DEFF Research Database (Denmark)
Hupp, Philipp; Heene, Mario; Jacob, Riko
2016-01-01
The numerical treatment of high-dimensional partial differential equations is among the most compute-hungry problems and in urgent need for current and future high-performance computing (HPC) systems. It is thus also facing the grand challenges of exascale computing such as the requirement...
Harnessing high-dimensional hyperentanglement through a biphoton frequency comb
Xie, Zhenda; Zhong, Tian; Shrestha, Sajan; Xu, Xinan; Liang, Junlin; Gong, Yan-Xiao; Bienfang, Joshua C.; Restelli, Alessandro; Shapiro, Jeffrey H.; Wong, Franco N. C.; Wei Wong, Chee
2015-08-01
Quantum entanglement is a fundamental resource for secure information processing and communications, and hyperentanglement or high-dimensional entanglement has been separately proposed for its high data capacity and error resilience. The continuous-variable nature of the energy-time entanglement makes it an ideal candidate for efficient high-dimensional coding with minimal limitations. Here, we demonstrate the first simultaneous high-dimensional hyperentanglement using a biphoton frequency comb to harness the full potential in both the energy and time domain. Long-postulated Hong-Ou-Mandel quantum revival is exhibited, with up to 19 time-bins and 96.5% visibilities. We further witness the high-dimensional energy-time entanglement through Franson revivals, observed periodically at integer time-bins, with 97.8% visibility. This qudit state is observed to simultaneously violate the generalized Bell inequality by up to 10.95 standard deviations while observing recurrent Clauser-Horne-Shimony-Holt S-parameters up to 2.76. Our biphoton frequency comb provides a platform for photon-efficient quantum communications towards the ultimate channel capacity through energy-time-polarization high-dimensional encoding.
Fuzzy parametric uncertainty analysis of linear dynamical systems: A surrogate modeling approach
Chowdhury, R.; Adhikari, S.
2012-10-01
Uncertainty propagation engineering systems possess significant computational challenges. This paper explores the possibility of using correlated function expansion based metamodelling approach when uncertain system parameters are modeled using Fuzzy variables. In particular, the application of High-Dimensional Model Representation (HDMR) is proposed for fuzzy finite element analysis of dynamical systems. The HDMR expansion is a set of quantitative model assessment and analysis tools for capturing high-dimensional input-output system behavior based on a hierarchy of functions of increasing dimensions. The input variables may be either finite-dimensional (i.e., a vector of parameters chosen from the Euclidean space RM) or may be infinite-dimensional as in the function space CM[0,1]. The computational effort to determine the expansion functions using the alpha cut method scales polynomially with the number of variables rather than exponentially. This logic is based on the fundamental assumption underlying the HDMR representation that only low-order correlations among the input variables are likely to have significant impacts upon the outputs for most high-dimensional complex systems. The proposed method is integrated with a commercial Finite Element software. Modal analysis of a simplified aircraft wing with Fuzzy parameters has been used to illustrate the generality of the proposed approach. In the numerical examples, triangular membership functions have been used and the results have been validated against direct Monte Carlo simulations.
Analysing spatially extended high-dimensional dynamics by recurrence plots
Energy Technology Data Exchange (ETDEWEB)
Marwan, Norbert, E-mail: marwan@pik-potsdam.de [Potsdam Institute for Climate Impact Research, 14412 Potsdam (Germany); Kurths, Jürgen [Potsdam Institute for Climate Impact Research, 14412 Potsdam (Germany); Humboldt Universität zu Berlin, Institut für Physik (Germany); Nizhny Novgorod State University, Department of Control Theory, Nizhny Novgorod (Russian Federation); Foerster, Saskia [GFZ German Research Centre for Geosciences, Section 1.4 Remote Sensing, Telegrafenberg, 14473 Potsdam (Germany)
2015-05-08
Recurrence plot based measures of complexity are capable tools for characterizing complex dynamics. In this letter we show the potential of selected recurrence plot measures for the investigation of even high-dimensional dynamics. We apply this method on spatially extended chaos, such as derived from the Lorenz96 model and show that the recurrence plot based measures can qualitatively characterize typical dynamical properties such as chaotic or periodic dynamics. Moreover, we demonstrate its power by analysing satellite image time series of vegetation cover with contrasting dynamics as a spatially extended and potentially high-dimensional example from the real world. - Highlights: • We use recurrence plots for analysing partially extended dynamics. • We investigate the high-dimensional chaos of the Lorenz96 model. • The approach distinguishes different spatio-temporal dynamics. • We use the method for studying vegetation cover time series.
High-dimensional model estimation and model selection
CERN. Geneva
2015-01-01
I will review concepts and algorithms from high-dimensional statistics for linear model estimation and model selection. I will particularly focus on the so-called p>>n setting where the number of variables p is much larger than the number of samples n. I will focus mostly on regularized statistical estimators that produce sparse models. Important examples include the LASSO and its matrix extension, the Graphical LASSO, and more recent non-convex methods such as the TREX. I will show the applicability of these estimators in a diverse range of scientific applications, such as sparse interaction graph recovery and high-dimensional classification and regression problems in genomics.
Supporting Dynamic Quantization for High-Dimensional Data Analytics.
Guzun, Gheorghi; Canahuate, Guadalupe
2017-05-01
Similarity searches are at the heart of exploratory data analysis tasks. Distance metrics are typically used to characterize the similarity between data objects represented as feature vectors. However, when the dimensionality of the data increases and the number of features is large, traditional distance metrics fail to distinguish between the closest and furthest data points. Localized distance functions have been proposed as an alternative to traditional distance metrics. These functions only consider dimensions close to query to compute the distance/similarity. Furthermore, in order to enable interactive explorations of high-dimensional data, indexing support for ad-hoc queries is needed. In this work we set up to investigate whether bit-sliced indices can be used for exploratory analytics such as similarity searches and data clustering for high-dimensional big-data. We also propose a novel dynamic quantization called Query dependent Equi-Depth (QED) quantization and show its effectiveness on characterizing high-dimensional similarity. When applying QED we observe improvements in kNN classification accuracy over traditional distance functions. Gheorghi Guzun and Guadalupe Canahuate. 2017. Supporting Dynamic Quantization for High-Dimensional Data Analytics. In Proceedings of Ex-ploreDB'17, Chicago, IL, USA, May 14-19, 2017, 6 pages. https://doi.org/http://dx.doi.org/10.1145/3077331.3077336.
A hybridized K-means clustering approach for high dimensional ...
African Journals Online (AJOL)
International Journal of Engineering, Science and Technology ... Due to incredible growth of high dimensional dataset, conventional data base querying methods are inadequate to extract useful information, so researchers nowadays ... Recently cluster analysis is a popularly used data analysis method in number of areas.
On Robust Information Extraction from High-Dimensional Data
Czech Academy of Sciences Publication Activity Database
Kalina, Jan
2014-01-01
Roč. 9, č. 1 (2014), s. 131-144 ISSN 1452-4864 Grant - others:GA ČR(CZ) GA13-01930S Institutional support: RVO:67985807 Keywords : data mining * high-dimensional data * robust econometrics * outliers * machine learning Subject RIV: IN - Informatics, Computer Science
Inference in High-dimensional Dynamic Panel Data Models
DEFF Research Database (Denmark)
Kock, Anders Bredahl; Tang, Haihan
We establish oracle inequalities for a version of the Lasso in high-dimensional fixed effects dynamic panel data models. The inequalities are valid for the coefficients of the dynamic and exogenous regressors. Separate oracle inequalities are derived for the fixed effects. Next, we show how one can...
Pricing High-Dimensional American Options Using Local Consistency Conditions
Berridge, S.J.; Schumacher, J.M.
2004-01-01
We investigate a new method for pricing high-dimensional American options. The method is of finite difference type but is also related to Monte Carlo techniques in that it involves a representative sampling of the underlying variables.An approximating Markov chain is built using this sampling and
Irregular grid methods for pricing high-dimensional American options
Berridge, S.J.
2004-01-01
This thesis proposes and studies numerical methods for pricing high-dimensional American options; important examples being basket options, Bermudan swaptions and real options. Four new methods are presented and analysed, both in terms of their application to various test problems, and in terms of
Genuinely high-dimensional nonlocality optimized by complementary measurements
International Nuclear Information System (INIS)
Lim, James; Ryu, Junghee; Yoo, Seokwon; Lee, Changhyoup; Bang, Jeongho; Lee, Jinhyoung
2010-01-01
Qubits exhibit extreme nonlocality when their state is maximally entangled and this is observed by mutually unbiased local measurements. This criterion does not hold for the Bell inequalities of high-dimensional systems (qudits), recently proposed by Collins-Gisin-Linden-Massar-Popescu and Son-Lee-Kim. Taking an alternative approach, called the quantum-to-classical approach, we derive a series of Bell inequalities for qudits that satisfy the criterion as for the qubits. In the derivation each d-dimensional subsystem is assumed to be measured by one of d possible measurements with d being a prime integer. By applying to two qubits (d=2), we find that a derived inequality is reduced to the Clauser-Horne-Shimony-Holt inequality when the degree of nonlocality is optimized over all the possible states and local observables. Further applying to two and three qutrits (d=3), we find Bell inequalities that are violated for the three-dimensionally entangled states but are not violated by any two-dimensionally entangled states. In other words, the inequalities discriminate three-dimensional (3D) entanglement from two-dimensional (2D) entanglement and in this sense they are genuinely 3D. In addition, for the two qutrits we give a quantitative description of the relations among the three degrees of complementarity, entanglement and nonlocality. It is shown that the degree of complementarity jumps abruptly to very close to its maximum as nonlocality starts appearing. These characteristics imply that complementarity plays a more significant role in the present inequality compared with the previously proposed inequality.
Automated validation of a computer operating system
Dervage, M. M.; Milberg, B. A.
1970-01-01
Programs apply selected input/output loads to complex computer operating system and measure performance of that system under such loads. Technique lends itself to checkout of computer software designed to monitor automated complex industrial systems.
Distribution of high-dimensional entanglement via an intra-city free-space link.
Steinlechner, Fabian; Ecker, Sebastian; Fink, Matthias; Liu, Bo; Bavaresco, Jessica; Huber, Marcus; Scheidl, Thomas; Ursin, Rupert
2017-07-24
Quantum entanglement is a fundamental resource in quantum information processing and its distribution between distant parties is a key challenge in quantum communications. Increasing the dimensionality of entanglement has been shown to improve robustness and channel capacities in secure quantum communications. Here we report on the distribution of genuine high-dimensional entanglement via a 1.2-km-long free-space link across Vienna. We exploit hyperentanglement, that is, simultaneous entanglement in polarization and energy-time bases, to encode quantum information, and observe high-visibility interference for successive correlation measurements in each degree of freedom. These visibilities impose lower bounds on entanglement in each subspace individually and certify four-dimensional entanglement for the hyperentangled system. The high-fidelity transmission of high-dimensional entanglement under real-world atmospheric link conditions represents an important step towards long-distance quantum communications with more complex quantum systems and the implementation of advanced quantum experiments with satellite links.
High Dimensional Modulation and MIMO Techniques for Access Networks
DEFF Research Database (Denmark)
Binti Othman, Maisara
Exploration of advanced modulation formats and multiplexing techniques for next generation optical access networks are of interest as promising solutions for delivering multiple services to end-users. This thesis addresses this from two different angles: high dimensionality carrierless...... the capacity per wavelength of the femto-cell network. Bit rate up to 1.59 Gbps with fiber-wireless transmission over 1 m air distance is demonstrated. The results presented in this thesis demonstrate the feasibility of high dimensionality CAP in increasing the number of dimensions and their potentially......) optical access network. 2 X 2 MIMO RoF employing orthogonal frequency division multiplexing (OFDM) with 5.6 GHz RoF signaling over all-vertical cavity surface emitting lasers (VCSEL) WDM passive optical networks (PONs). We have employed polarization division multiplexing (PDM) to further increase...
HSM: Heterogeneous Subspace Mining in High Dimensional Data
DEFF Research Database (Denmark)
Müller, Emmanuel; Assent, Ira; Seidl, Thomas
2009-01-01
Heterogeneous data, i.e. data with both categorical and continuous values, is common in many databases. However, most data mining algorithms assume either continuous or categorical attributes, but not both. In high dimensional data, phenomena due to the "curse of dimensionality" pose additional...... challenges. Usually, due to locally varying relevance of attributes, patterns do not show across the full set of attributes. In this paper we propose HSM, which defines a new pattern model for heterogeneous high dimensional data. It allows data mining in arbitrary subsets of the attributes that are relevant...... for the respective patterns. Based on this model we propose an efficient algorithm, which is aware of the heterogeneity of the attributes. We extend an indexing structure for continuous attributes such that HSM indexing adapts to different attribute types. In our experiments we show that HSM efficiently mines...
HIGH DIMENSIONAL COVARIANCE MATRIX ESTIMATION IN APPROXIMATE FACTOR MODELS.
Fan, Jianqing; Liao, Yuan; Mincheva, Martina
2011-01-01
The variance covariance matrix plays a central role in the inferential theories of high dimensional factor models in finance and economics. Popular regularization methods of directly exploiting sparsity are not directly applicable to many financial problems. Classical methods of estimating the covariance matrices are based on the strict factor models, assuming independent idiosyncratic components. This assumption, however, is restrictive in practical applications. By assuming sparse error covariance matrix, we allow the presence of the cross-sectional correlation even after taking out common factors, and it enables us to combine the merits of both methods. We estimate the sparse covariance using the adaptive thresholding technique as in Cai and Liu (2011), taking into account the fact that direct observations of the idiosyncratic components are unavailable. The impact of high dimensionality on the covariance matrix estimation based on the factor structure is then studied.
High-dimensional data in economics and their (robust) analysis
Czech Academy of Sciences Publication Activity Database
Kalina, Jan
2017-01-01
Roč. 12, č. 1 (2017), s. 171-183 ISSN 1452-4864 R&D Projects: GA ČR GA17-07384S Institutional support: RVO:67985556 Keywords : econometrics * high-dimensional data * dimensionality reduction * linear regression * classification analysis * robustness Subject RIV: BA - General Mathematics OBOR OECD: Business and management http://library.utia.cas.cz/separaty/2017/SI/kalina-0474076.pdf
High-dimensional Data in Economics and their (Robust) Analysis
Czech Academy of Sciences Publication Activity Database
Kalina, Jan
2017-01-01
Roč. 12, č. 1 (2017), s. 171-183 ISSN 1452-4864 R&D Projects: GA ČR GA17-07384S Grant - others:GA ČR(CZ) GA13-01930S Institutional support: RVO:67985807 Keywords : econometrics * high-dimensional data * dimensionality reduction * linear regression * classification analysis * robustness Subject RIV: BB - Applied Statistics, Operational Research OBOR OECD: Statistics and probability
High Dimensional Classification Using Features Annealed Independence Rules.
Fan, Jianqing; Fan, Yingying
2008-01-01
Classification using high-dimensional features arises frequently in many contemporary statistical studies such as tumor classification using microarray or other high-throughput data. The impact of dimensionality on classifications is largely poorly understood. In a seminal paper, Bickel and Levina (2004) show that the Fisher discriminant performs poorly due to diverging spectra and they propose to use the independence rule to overcome the problem. We first demonstrate that even for the independence classification rule, classification using all the features can be as bad as the random guessing due to noise accumulation in estimating population centroids in high-dimensional feature space. In fact, we demonstrate further that almost all linear discriminants can perform as bad as the random guessing. Thus, it is paramountly important to select a subset of important features for high-dimensional classification, resulting in Features Annealed Independence Rules (FAIR). The conditions under which all the important features can be selected by the two-sample t-statistic are established. The choice of the optimal number of features, or equivalently, the threshold value of the test statistics are proposed based on an upper bound of the classification error. Simulation studies and real data analysis support our theoretical results and demonstrate convincingly the advantage of our new classification procedure.
A Shell Multi-dimensional Hierarchical Cubing Approach for High-Dimensional Cube
Zou, Shuzhi; Zhao, Li; Hu, Kongfa
The pre-computation of data cubes is critical for improving the response time of OLAP systems and accelerating data mining tasks in large data warehouses. However, as the sizes of data warehouses grow, the time it takes to perform this pre-computation becomes a significant performance bottleneck. In a high dimensional data warehouse, it might not be practical to build all these cuboids and their indices. In this paper, we propose a shell multi-dimensional hierarchical cubing algorithm, based on an extension of the previous minimal cubing approach. This method partitions the high dimensional data cube into low multi-dimensional hierarchical cube. Experimental results show that the proposed method is significantly more efficient than other existing cubing methods.
Reinforcement learning on slow features of high-dimensional input streams.
Directory of Open Access Journals (Sweden)
Robert Legenstein
Full Text Available Humans and animals are able to learn complex behaviors based on a massive stream of sensory information from different modalities. Early animal studies have identified learning mechanisms that are based on reward and punishment such that animals tend to avoid actions that lead to punishment whereas rewarded actions are reinforced. However, most algorithms for reward-based learning are only applicable if the dimensionality of the state-space is sufficiently small or its structure is sufficiently simple. Therefore, the question arises how the problem of learning on high-dimensional data is solved in the brain. In this article, we propose a biologically plausible generic two-stage learning system that can directly be applied to raw high-dimensional input streams. The system is composed of a hierarchical slow feature analysis (SFA network for preprocessing and a simple neural network on top that is trained based on rewards. We demonstrate by computer simulations that this generic architecture is able to learn quite demanding reinforcement learning tasks on high-dimensional visual input streams in a time that is comparable to the time needed when an explicit highly informative low-dimensional state-space representation is given instead of the high-dimensional visual input. The learning speed of the proposed architecture in a task similar to the Morris water maze task is comparable to that found in experimental studies with rats. This study thus supports the hypothesis that slowness learning is one important unsupervised learning principle utilized in the brain to form efficient state representations for behavioral learning.
Hawking radiation of a high-dimensional rotating black hole
Energy Technology Data Exchange (ETDEWEB)
Zhao, Ren; Zhang, Lichun; Li, Huaifan; Wu, Yueqin [Shanxi Datong University, Institute of Theoretical Physics, Department of Physics, Datong (China)
2010-01-15
We extend the classical Damour-Ruffini method and discuss Hawking radiation spectrum of high-dimensional rotating black hole using Tortoise coordinate transformation defined by taking the reaction of the radiation to the spacetime into consideration. Under the condition that the energy and angular momentum are conservative, taking self-gravitation action into account, we derive Hawking radiation spectrums which satisfy unitary principle in quantum mechanics. It is shown that the process that the black hole radiates particles with energy {omega} is a continuous tunneling process. We provide a theoretical basis for further studying the physical mechanism of black-hole radiation. (orig.)
On spectral distribution of high dimensional covariation matrices
DEFF Research Database (Denmark)
Heinrich, Claudio; Podolskij, Mark
In this paper we present the asymptotic theory for spectral distributions of high dimensional covariation matrices of Brownian diffusions. More specifically, we consider N-dimensional Itô integrals with time varying matrix-valued integrands. We observe n equidistant high frequency data points...... of the underlying Brownian diffusion and we assume that N/n -> c in (0,oo). We show that under a certain mixed spectral moment condition the spectral distribution of the empirical covariation matrix converges in distribution almost surely. Our proof relies on method of moments and applications of graph theory....
The additive hazards model with high-dimensional regressors
DEFF Research Database (Denmark)
Martinussen, Torben; Scheike, Thomas
2009-01-01
This paper considers estimation and prediction in the Aalen additive hazards model in the case where the covariate vector is high-dimensional such as gene expression measurements. Some form of dimension reduction of the covariate space is needed to obtain useful statistical analyses. We study...... model. A standard PLS algorithm can also be constructed, but it turns out that the resulting predictor can only be related to the original covariates via time-dependent coefficients. The methods are applied to a breast cancer data set with gene expression recordings and to the well known primary biliary...
High-dimensional quantum channel estimation using classical light
CSIR Research Space (South Africa)
Mabena, Chemist M
2017-11-01
Full Text Available stream_source_info Mabena_20007_2017.pdf.txt stream_content_type text/plain stream_size 960 Content-Encoding UTF-8 stream_name Mabena_20007_2017.pdf.txt Content-Type text/plain; charset=UTF-8 PHYSICAL REVIEW A 96, 053860... (2017) High-dimensional quantum channel estimation using classical light Chemist M. Mabena CSIR National Laser Centre, P.O. Box 395, Pretoria 0001, South Africa and School of Physics, University of the Witwatersrand, Johannesburg 2000, South...
Data analysis in high-dimensional sparse spaces
DEFF Research Database (Denmark)
Clemmensen, Line Katrine Harder
classification techniques for high-dimensional problems are presented: Sparse discriminant analysis, sparse mixture discriminant analysis and orthogonality constrained support vector machines. The first two introduces sparseness to the well known linear and mixture discriminant analysis and thereby provide low...... are applied to classifications of fish species, ear canal impressions used in the hearing aid industry, microbiological fungi species, and various cancerous tissues and healthy tissues. In addition, novel applications of sparse regressions (also called the elastic net) to the medical, concrete, and food...
Scalable Nearest Neighbor Algorithms for High Dimensional Data.
Muja, Marius; Lowe, David G
2014-11-01
For many computer vision and machine learning problems, large training sets are key for good performance. However, the most computationally expensive part of many computer vision and machine learning algorithms consists of finding nearest neighbor matches to high dimensional vectors that represent the training data. We propose new algorithms for approximate nearest neighbor matching and evaluate and compare them with previous algorithms. For matching high dimensional features, we find two algorithms to be the most efficient: the randomized k-d forest and a new algorithm proposed in this paper, the priority search k-means tree. We also propose a new algorithm for matching binary features by searching multiple hierarchical clustering trees and show it outperforms methods typically used in the literature. We show that the optimal nearest neighbor algorithm and its parameters depend on the data set characteristics and describe an automated configuration procedure for finding the best algorithm to search a particular data set. In order to scale to very large data sets that would otherwise not fit in the memory of a single machine, we propose a distributed nearest neighbor matching framework that can be used with any of the algorithms described in the paper. All this research has been released as an open source library called fast library for approximate nearest neighbors (FLANN), which has been incorporated into OpenCV and is now one of the most popular libraries for nearest neighbor matching.
Manifold learning to interpret JET high-dimensional operational space
International Nuclear Information System (INIS)
Cannas, B; Fanni, A; Pau, A; Sias, G; Murari, A
2013-01-01
In this paper, the problem of visualization and exploration of JET high-dimensional operational space is considered. The data come from plasma discharges selected from JET campaigns from C15 (year 2005) up to C27 (year 2009). The aim is to learn the possible manifold structure embedded in the data and to create some representations of the plasma parameters on low-dimensional maps, which are understandable and which preserve the essential properties owned by the original data. A crucial issue for the design of such mappings is the quality of the dataset. This paper reports the details of the criteria used to properly select suitable signals downloaded from JET databases in order to obtain a dataset of reliable observations. Moreover, a statistical analysis is performed to recognize the presence of outliers. Finally data reduction, based on clustering methods, is performed to select a limited and representative number of samples for the operational space mapping. The high-dimensional operational space of JET is mapped using a widely used manifold learning method, the self-organizing maps. The results are compared with other data visualization methods. The obtained maps can be used to identify characteristic regions of the plasma scenario, allowing to discriminate between regions with high risk of disruption and those with low risk of disruption. (paper)
Elucidating high-dimensional cancer hallmark annotation via enriched ontology.
Yan, Shankai; Wong, Ka-Chun
2017-09-01
Cancer hallmark annotation is a promising technique that could discover novel knowledge about cancer from the biomedical literature. The automated annotation of cancer hallmarks could reveal relevant cancer transformation processes in the literature or extract the articles that correspond to the cancer hallmark of interest. It acts as a complementary approach that can retrieve knowledge from massive text information, advancing numerous focused studies in cancer research. Nonetheless, the high-dimensional nature of cancer hallmark annotation imposes a unique challenge. To address the curse of dimensionality, we compared multiple cancer hallmark annotation methods on 1580 PubMed abstracts. Based on the insights, a novel approach, UDT-RF, which makes use of ontological features is proposed. It expands the feature space via the Medical Subject Headings (MeSH) ontology graph and utilizes novel feature selections for elucidating the high-dimensional cancer hallmark annotation space. To demonstrate its effectiveness, state-of-the-art methods are compared and evaluated by a multitude of performance metrics, revealing the full performance spectrum on the full set of cancer hallmarks. Several case studies are conducted, demonstrating how the proposed approach could reveal novel insights into cancers. https://github.com/cskyan/chmannot. Copyright © 2017 Elsevier Inc. All rights reserved.
Directory of Open Access Journals (Sweden)
İlkay DİLBER
2007-01-01
Full Text Available Tourism industry is one of the most important industries in the economic development of Turkish economy. In addition to its usual effects on GDP, tourism revenues can help to reduce the current account deficits. Thus, in order to determine the importance of tourism industry for the Turkish economy, this study uses input-output tables of the Turkish tourism industry in 1998. Calculating the industry’s value added and factor intensity and understanding whether the sector is subject to the dynamic external economies are extremely important for future policy suggestions.
Class prediction for high-dimensional class-imbalanced data
Directory of Open Access Journals (Sweden)
Lusa Lara
2010-10-01
Full Text Available Abstract Background The goal of class prediction studies is to develop rules to accurately predict the class membership of new samples. The rules are derived using the values of the variables available for each subject: the main characteristic of high-dimensional data is that the number of variables greatly exceeds the number of samples. Frequently the classifiers are developed using class-imbalanced data, i.e., data sets where the number of samples in each class is not equal. Standard classification methods used on class-imbalanced data often produce classifiers that do not accurately predict the minority class; the prediction is biased towards the majority class. In this paper we investigate if the high-dimensionality poses additional challenges when dealing with class-imbalanced prediction. We evaluate the performance of six types of classifiers on class-imbalanced data, using simulated data and a publicly available data set from a breast cancer gene-expression microarray study. We also investigate the effectiveness of some strategies that are available to overcome the effect of class imbalance. Results Our results show that the evaluated classifiers are highly sensitive to class imbalance and that variable selection introduces an additional bias towards classification into the majority class. Most new samples are assigned to the majority class from the training set, unless the difference between the classes is very large. As a consequence, the class-specific predictive accuracies differ considerably. When the class imbalance is not too severe, down-sizing and asymmetric bagging embedding variable selection work well, while over-sampling does not. Variable normalization can further worsen the performance of the classifiers. Conclusions Our results show that matching the prevalence of the classes in training and test set does not guarantee good performance of classifiers and that the problems related to classification with class
High-dimensional change-point estimation: Combining filtering with convex optimization
Soh, Yong Sheng; Chandrasekaran, Venkat
2017-01-01
We consider change-point estimation in a sequence of high-dimensional signals given noisy observations. Classical approaches to this problem such as the filtered derivative method are useful for sequences of scalar-valued signals, but they have undesirable scaling behavior in the high-dimensional setting. However, many high-dimensional signals encountered in practice frequently possess latent low-dimensional structure. Motivated by this observation, we propose a technique for high-dimensional...
Variance inflation in high dimensional Support Vector Machines
DEFF Research Database (Denmark)
Abrahamsen, Trine Julie; Hansen, Lars Kai
2013-01-01
Many important machine learning models, supervised and unsupervised, are based on simple Euclidean distance or orthogonal projection in a high dimensional feature space. When estimating such models from small training sets we face the problem that the span of the training data set input vectors...... the case of Support Vector Machines (SVMS) and we propose a non-parametric scheme to restore proper generalizability. We illustrate the algorithm and its ability to restore performance on a wide range of benchmark data sets....... follow a different probability law with less variance. While the problem and basic means to reconstruct and deflate are well understood in unsupervised learning, the case of supervised learning is less well understood. We here investigate the effect of variance inflation in supervised learning including...
Applying recursive numerical integration techniques for solving high dimensional integrals
International Nuclear Information System (INIS)
Ammon, Andreas; Genz, Alan; Hartung, Tobias; Jansen, Karl; Volmer, Julia; Leoevey, Hernan
2016-11-01
The error scaling for Markov-Chain Monte Carlo techniques (MCMC) with N samples behaves like 1/√(N). This scaling makes it often very time intensive to reduce the error of computed observables, in particular for applications in lattice QCD. It is therefore highly desirable to have alternative methods at hand which show an improved error scaling. One candidate for such an alternative integration technique is the method of recursive numerical integration (RNI). The basic idea of this method is to use an efficient low-dimensional quadrature rule (usually of Gaussian type) and apply it iteratively to integrate over high-dimensional observables and Boltzmann weights. We present the application of such an algorithm to the topological rotor and the anharmonic oscillator and compare the error scaling to MCMC results. In particular, we demonstrate that the RNI technique shows an error scaling in the number of integration points m that is at least exponential.
High-dimensional cluster analysis with the Masked EM Algorithm
Kadir, Shabnam N.; Goodman, Dan F. M.; Harris, Kenneth D.
2014-01-01
Cluster analysis faces two problems in high dimensions: first, the “curse of dimensionality” that can lead to overfitting and poor generalization performance; and second, the sheer time taken for conventional algorithms to process large amounts of high-dimensional data. We describe a solution to these problems, designed for the application of “spike sorting” for next-generation high channel-count neural probes. In this problem, only a small subset of features provide information about the cluster member-ship of any one data vector, but this informative feature subset is not the same for all data points, rendering classical feature selection ineffective. We introduce a “Masked EM” algorithm that allows accurate and time-efficient clustering of up to millions of points in thousands of dimensions. We demonstrate its applicability to synthetic data, and to real-world high-channel-count spike sorting data. PMID:25149694
Evaluating Clustering in Subspace Projections of High Dimensional Data
DEFF Research Database (Denmark)
Müller, Emmanuel; Günnemann, Stephan; Assent, Ira
2009-01-01
Clustering high dimensional data is an emerging research field. Subspace clustering or projected clustering group similar objects in subspaces, i.e. projections, of the full space. In the past decade, several clustering paradigms have been developed in parallel, without thorough evaluation...... and comparison between these paradigms on a common basis. Conclusive evaluation and comparison is challenged by three major issues. First, there is no ground truth that describes the "true" clusters in real world data. Second, a large variety of evaluation measures have been used that reflect different aspects...... of the clustering result. Finally, in typical publications authors have limited their analysis to their favored paradigm only, while paying other paradigms little or no attention. In this paper, we take a systematic approach to evaluate the major paradigms in a common framework. We study representative clustering...
Applying recursive numerical integration techniques for solving high dimensional integrals
Energy Technology Data Exchange (ETDEWEB)
Ammon, Andreas [IVU Traffic Technologies AG, Berlin (Germany); Genz, Alan [Washington State Univ., Pullman, WA (United States). Dept. of Mathematics; Hartung, Tobias [King' s College, London (United Kingdom). Dept. of Mathematics; Jansen, Karl; Volmer, Julia [Deutsches Elektronen-Synchrotron (DESY), Zeuthen (Germany). John von Neumann-Inst. fuer Computing NIC; Leoevey, Hernan [Humboldt Univ. Berlin (Germany). Inst. fuer Mathematik
2016-11-15
The error scaling for Markov-Chain Monte Carlo techniques (MCMC) with N samples behaves like 1/√(N). This scaling makes it often very time intensive to reduce the error of computed observables, in particular for applications in lattice QCD. It is therefore highly desirable to have alternative methods at hand which show an improved error scaling. One candidate for such an alternative integration technique is the method of recursive numerical integration (RNI). The basic idea of this method is to use an efficient low-dimensional quadrature rule (usually of Gaussian type) and apply it iteratively to integrate over high-dimensional observables and Boltzmann weights. We present the application of such an algorithm to the topological rotor and the anharmonic oscillator and compare the error scaling to MCMC results. In particular, we demonstrate that the RNI technique shows an error scaling in the number of integration points m that is at least exponential.
Reduced order surrogate modelling (ROSM) of high dimensional deterministic simulations
Mitry, Mina
Often, computationally expensive engineering simulations can prohibit the engineering design process. As a result, designers may turn to a less computationally demanding approximate, or surrogate, model to facilitate their design process. However, owing to the the curse of dimensionality, classical surrogate models become too computationally expensive for high dimensional data. To address this limitation of classical methods, we develop linear and non-linear Reduced Order Surrogate Modelling (ROSM) techniques. Two algorithms are presented, which are based on a combination of linear/kernel principal component analysis and radial basis functions. These algorithms are applied to subsonic and transonic aerodynamic data, as well as a model for a chemical spill in a channel. The results of this thesis show that ROSM can provide a significant computational benefit over classical surrogate modelling, sometimes at the expense of a minor loss in accuracy.
Asymptotics of empirical eigenstructure for high dimensional spiked covariance.
Wang, Weichen; Fan, Jianqing
2017-06-01
We derive the asymptotic distributions of the spiked eigenvalues and eigenvectors under a generalized and unified asymptotic regime, which takes into account the magnitude of spiked eigenvalues, sample size, and dimensionality. This regime allows high dimensionality and diverging eigenvalues and provides new insights into the roles that the leading eigenvalues, sample size, and dimensionality play in principal component analysis. Our results are a natural extension of those in Paul (2007) to a more general setting and solve the rates of convergence problems in Shen et al. (2013). They also reveal the biases of estimating leading eigenvalues and eigenvectors by using principal component analysis, and lead to a new covariance estimator for the approximate factor model, called shrinkage principal orthogonal complement thresholding (S-POET), that corrects the biases. Our results are successfully applied to outstanding problems in estimation of risks of large portfolios and false discovery proportions for dependent test statistics and are illustrated by simulation studies.
High-Dimensional Single-Photon Quantum Gates: Concepts and Experiments.
Babazadeh, Amin; Erhard, Manuel; Wang, Feiran; Malik, Mehul; Nouroozi, Rahman; Krenn, Mario; Zeilinger, Anton
2017-11-03
Transformations on quantum states form a basic building block of every quantum information system. From photonic polarization to two-level atoms, complete sets of quantum gates for a variety of qubit systems are well known. For multilevel quantum systems beyond qubits, the situation is more challenging. The orbital angular momentum modes of photons comprise one such high-dimensional system for which generation and measurement techniques are well studied. However, arbitrary transformations for such quantum states are not known. Here we experimentally demonstrate a four-dimensional generalization of the Pauli X gate and all of its integer powers on single photons carrying orbital angular momentum. Together with the well-known Z gate, this forms the first complete set of high-dimensional quantum gates implemented experimentally. The concept of the X gate is based on independent access to quantum states with different parities and can thus be generalized to other photonic degrees of freedom and potentially also to other quantum systems.
On-chip generation of high-dimensional entangled quantum states and their coherent control.
Kues, Michael; Reimer, Christian; Roztocki, Piotr; Cortés, Luis Romero; Sciara, Stefania; Wetzel, Benjamin; Zhang, Yanbing; Cino, Alfonso; Chu, Sai T; Little, Brent E; Moss, David J; Caspani, Lucia; Azaña, José; Morandotti, Roberto
2017-06-28
Optical quantum states based on entangled photons are essential for solving questions in fundamental physics and are at the heart of quantum information science. Specifically, the realization of high-dimensional states (D-level quantum systems, that is, qudits, with D > 2) and their control are necessary for fundamental investigations of quantum mechanics, for increasing the sensitivity of quantum imaging schemes, for improving the robustness and key rate of quantum communication protocols, for enabling a richer variety of quantum simulations, and for achieving more efficient and error-tolerant quantum computation. Integrated photonics has recently become a leading platform for the compact, cost-efficient, and stable generation and processing of non-classical optical states. However, so far, integrated entangled quantum sources have been limited to qubits (D = 2). Here we demonstrate on-chip generation of entangled qudit states, where the photons are created in a coherent superposition of multiple high-purity frequency modes. In particular, we confirm the realization of a quantum system with at least one hundred dimensions, formed by two entangled qudits with D = 10. Furthermore, using state-of-the-art, yet off-the-shelf telecommunications components, we introduce a coherent manipulation platform with which to control frequency-entangled states, capable of performing deterministic high-dimensional gate operations. We validate this platform by measuring Bell inequality violations and performing quantum state tomography. Our work enables the generation and processing of high-dimensional quantum states in a single spatial mode.
Energy Efficient MAC Scheme for Wireless Sensor Networks with High-Dimensional Data Aggregate
Directory of Open Access Journals (Sweden)
Seokhoon Kim
2015-01-01
Full Text Available This paper presents a novel and sustainable medium access control (MAC scheme for wireless sensor network (WSN systems that process high-dimensional aggregated data. Based on a preamble signal and buffer threshold analysis, it maximizes the energy efficiency of the wireless sensor devices which have limited energy resources. The proposed group management MAC (GM-MAC approach not only sets the buffer threshold value of a sensor device to be reciprocal to the preamble signal but also sets a transmittable group value to each sensor device by using the preamble signal of the sink node. The primary difference between the previous and the proposed approach is that existing state-of-the-art schemes use duty cycle and sleep mode to save energy consumption of individual sensor devices, whereas the proposed scheme employs the group management MAC scheme for sensor devices to maximize the overall energy efficiency of the whole WSN systems by minimizing the energy consumption of sensor devices located near the sink node. Performance evaluations show that the proposed scheme outperforms the previous schemes in terms of active time of sensor devices, transmission delay, control overhead, and energy consumption. Therefore, the proposed scheme is suitable for sensor devices in a variety of wireless sensor networking environments with high-dimensional data aggregate.
Progress in high-dimensional percolation and random graphs
Heydenreich, Markus
2017-01-01
This text presents an engaging exposition of the active field of high-dimensional percolation that will likely provide an impetus for future work. With over 90 exercises designed to enhance the reader’s understanding of the material, as well as many open problems, the book is aimed at graduate students and researchers who wish to enter the world of this rich topic. The text may also be useful in advanced courses and seminars, as well as for reference and individual study. Part I, consisting of 3 chapters, presents a general introduction to percolation, stating the main results, defining the central objects, and proving its main properties. No prior knowledge of percolation is assumed. Part II, consisting of Chapters 4–9, discusses mean-field critical behavior by describing the two main techniques used, namely, differential inequalities and the lace expansion. In Parts I and II, all results are proved, making this the first self-contained text discussing high-dimensiona l percolation. Part III, consist...
Effects of dependence in high-dimensional multiple testing problems
Directory of Open Access Journals (Sweden)
van de Wiel Mark A
2008-02-01
Full Text Available Abstract Background We consider effects of dependence among variables of high-dimensional data in multiple hypothesis testing problems, in particular the False Discovery Rate (FDR control procedures. Recent simulation studies consider only simple correlation structures among variables, which is hardly inspired by real data features. Our aim is to systematically study effects of several network features like sparsity and correlation strength by imposing dependence structures among variables using random correlation matrices. Results We study the robustness against dependence of several FDR procedures that are popular in microarray studies, such as Benjamin-Hochberg FDR, Storey's q-value, SAM and resampling based FDR procedures. False Non-discovery Rates and estimates of the number of null hypotheses are computed from those methods and compared. Our simulation study shows that methods such as SAM and the q-value do not adequately control the FDR to the level claimed under dependence conditions. On the other hand, the adaptive Benjamini-Hochberg procedure seems to be most robust while remaining conservative. Finally, the estimates of the number of true null hypotheses under various dependence conditions are variable. Conclusion We discuss a new method for efficient guided simulation of dependent data, which satisfy imposed network constraints as conditional independence structures. Our simulation set-up allows for a structural study of the effect of dependencies on multiple testing criterions and is useful for testing a potentially new method on π0 or FDR estimation in a dependency context.
Inference for High-dimensional Differential Correlation Matrices.
Cai, T Tony; Zhang, Anru
2016-01-01
Motivated by differential co-expression analysis in genomics, we consider in this paper estimation and testing of high-dimensional differential correlation matrices. An adaptive thresholding procedure is introduced and theoretical guarantees are given. Minimax rate of convergence is established and the proposed estimator is shown to be adaptively rate-optimal over collections of paired correlation matrices with approximately sparse differences. Simulation results show that the procedure significantly outperforms two other natural methods that are based on separate estimation of the individual correlation matrices. The procedure is also illustrated through an analysis of a breast cancer dataset, which provides evidence at the gene co-expression level that several genes, of which a subset has been previously verified, are associated with the breast cancer. Hypothesis testing on the differential correlation matrices is also considered. A test, which is particularly well suited for testing against sparse alternatives, is introduced. In addition, other related problems, including estimation of a single sparse correlation matrix, estimation of the differential covariance matrices, and estimation of the differential cross-correlation matrices, are also discussed.
Efficient Smoothed Concomitant Lasso Estimation for High Dimensional Regression
Ndiaye, Eugene; Fercoq, Olivier; Gramfort, Alexandre; Leclère, Vincent; Salmon, Joseph
2017-10-01
In high dimensional settings, sparse structures are crucial for efficiency, both in term of memory, computation and performance. It is customary to consider ℓ 1 penalty to enforce sparsity in such scenarios. Sparsity enforcing methods, the Lasso being a canonical example, are popular candidates to address high dimension. For efficiency, they rely on tuning a parameter trading data fitting versus sparsity. For the Lasso theory to hold this tuning parameter should be proportional to the noise level, yet the latter is often unknown in practice. A possible remedy is to jointly optimize over the regression parameter as well as over the noise level. This has been considered under several names in the literature: Scaled-Lasso, Square-root Lasso, Concomitant Lasso estimation for instance, and could be of interest for uncertainty quantification. In this work, after illustrating numerical difficulties for the Concomitant Lasso formulation, we propose a modification we coined Smoothed Concomitant Lasso, aimed at increasing numerical stability. We propose an efficient and accurate solver leading to a computational cost no more expensive than the one for the Lasso. We leverage on standard ingredients behind the success of fast Lasso solvers: a coordinate descent algorithm, combined with safe screening rules to achieve speed efficiency, by eliminating early irrelevant features.
Bayesian Subset Modeling for High-Dimensional Generalized Linear Models
Liang, Faming
2013-06-01
This article presents a new prior setting for high-dimensional generalized linear models, which leads to a Bayesian subset regression (BSR) with the maximum a posteriori model approximately equivalent to the minimum extended Bayesian information criterion model. The consistency of the resulting posterior is established under mild conditions. Further, a variable screening procedure is proposed based on the marginal inclusion probability, which shares the same properties of sure screening and consistency with the existing sure independence screening (SIS) and iterative sure independence screening (ISIS) procedures. However, since the proposed procedure makes use of joint information from all predictors, it generally outperforms SIS and ISIS in real applications. This article also makes extensive comparisons of BSR with the popular penalized likelihood methods, including Lasso, elastic net, SIS, and ISIS. The numerical results indicate that BSR can generally outperform the penalized likelihood methods. The models selected by BSR tend to be sparser and, more importantly, of higher prediction ability. In addition, the performance of the penalized likelihood methods tends to deteriorate as the number of predictors increases, while this is not significant for BSR. Supplementary materials for this article are available online. © 2013 American Statistical Association.
The literary uses of high-dimensional space
Directory of Open Access Journals (Sweden)
Ted Underwood
2015-12-01
Full Text Available Debates over “Big Data” shed more heat than light in the humanities, because the term ascribes new importance to statistical methods without explaining how those methods have changed. What we badly need instead is a conversation about the substantive innovations that have made statistical modeling useful for disciplines where, in the past, it truly wasn’t. These innovations are partly technical, but more fundamentally expressed in what Leo Breiman calls a new “culture” of statistical modeling. Where 20th-century methods often required humanists to squeeze our unstructured texts, sounds, or images into some special-purpose data model, new methods can handle unstructured evidence more directly by modeling it in a high-dimensional space. This opens a range of research opportunities that humanists have barely begun to discuss. To date, topic modeling has received most attention, but in the long run, supervised predictive models may be even more important. I sketch their potential by describing how Jordan Sellers and I have begun to model poetic distinction in the long 19th century—revealing an arc of gradual change much longer than received literary histories would lead us to expect.
Energy Technology Data Exchange (ETDEWEB)
Wallmann, R.; Fricke, K. [Ingenieurgemeinschaft Witzenhausen (Germany); Vogtmann, H. [Hessisches Landesamt fuer Regionalentwicklung und Landwirtschaft, Kassel (Germany)
1998-12-31
The study strikes a cumulative input/output balance of an existing waste conditioning plant considering not only operating energy demand but also the required construction materials for erecting the plant. In operation since 1996, the waste conditioning plant is entirely state of the art; hence the data obtained are up to date. The results are compared with relevant results for a waste processing plant and evaluated. (orig.) [Deutsch] Im Rahmen der vorliegenden Untersuchung erfolgt eine kumulative Bilanzierung einer bestehenden MBA-Anlage, wobei neben den betrieblichen Energieaufwendungen auch die Baumaterialien zur Herstellung der Anlage beruecksichtigt werden. Die seit 1996 in Betrieb befindliche Abfallbehandlungsanlage entspricht weitestgehend dem Stand der Technik der MBA, wodurch die Aktualitaet der Daten gegeben ist. Die Ergebnisse der Bilanzierung werden im Vergleich zu einer MVA dargestellt und bewertet. (orig.)
Reducing the Complexity of Genetic Fuzzy Classifiers in Highly-Dimensional Classification Problems
Directory of Open Access Journals (Sweden)
DimitrisG. Stavrakoudis
2012-04-01
Full Text Available This paper introduces the Fast Iterative Rule-based Linguistic Classifier (FaIRLiC, a Genetic Fuzzy Rule-Based Classification System (GFRBCS which targets at reducing the structural complexity of the resulting rule base, as well as its learning algorithm's computational requirements, especially when dealing with high-dimensional feature spaces. The proposed methodology follows the principles of the iterative rule learning (IRL approach, whereby a rule extraction algorithm (REA is invoked in an iterative fashion, producing one fuzzy rule at a time. The REA is performed in two successive steps: the first one selects the relevant features of the currently extracted rule, whereas the second one decides the antecedent part of the fuzzy rule, using the previously selected subset of features. The performance of the classifier is finally optimized through a genetic tuning post-processing stage. Comparative results in a hyperspectral remote sensing classification as well as in 12 real-world classification datasets indicate the effectiveness of the proposed methodology in generating high-performing and compact fuzzy rule-based classifiers, even for very high-dimensional feature spaces.
Tikhonov, Mikhail; Monasson, Remi
2018-01-01
Much of our understanding of ecological and evolutionary mechanisms derives from analysis of low-dimensional models: with few interacting species, or few axes defining "fitness". It is not always clear to what extent the intuition derived from low-dimensional models applies to the complex, high-dimensional reality. For instance, most naturally occurring microbial communities are strikingly diverse, harboring a large number of coexisting species, each of which contributes to shaping the environment of others. Understanding the eco-evolutionary interplay in these systems is an important challenge, and an exciting new domain for statistical physics. Recent work identified a promising new platform for investigating highly diverse ecosystems, based on the classic resource competition model of MacArthur. Here, we describe how the same analytical framework can be used to study evolutionary questions. Our analysis illustrates how, at high dimension, the intuition promoted by a one-dimensional (scalar) notion of fitness can become misleading. Specifically, while the low-dimensional picture emphasizes organism cost or efficiency, we exhibit a regime where cost becomes irrelevant for survival, and link this observation to generic properties of high-dimensional geometry.
High-dimensional statistical inference: From vector to matrix
Zhang, Anru
Statistical inference for sparse signals or low-rank matrices in high-dimensional settings is of significant interest in a range of contemporary applications. It has attracted significant recent attention in many fields including statistics, applied mathematics and electrical engineering. In this thesis, we consider several problems in including sparse signal recovery (compressed sensing under restricted isometry) and low-rank matrix recovery (matrix recovery via rank-one projections and structured matrix completion). The first part of the thesis discusses compressed sensing and affine rank minimization in both noiseless and noisy cases and establishes sharp restricted isometry conditions for sparse signal and low-rank matrix recovery. The analysis relies on a key technical tool which represents points in a polytope by convex combinations of sparse vectors. The technique is elementary while leads to sharp results. It is shown that, in compressed sensing, delta kA 0, delta kA < 1/3 + epsilon, deltak A + thetak,kA < 1 + epsilon, or deltatkA< √(t - 1) / t + epsilon are not sufficient to guarantee the exact recovery of all k-sparse signals for large k. Similar result also holds for matrix recovery. In addition, the conditions delta kA<1/3, deltak A+ thetak,kA<1, delta tkA < √(t - 1)/t and deltarM<1/3, delta rM+ thetar,rM<1, delta trM< √(t - 1)/ t are also shown to be sufficient respectively for stable recovery of approximately sparse signals and low-rank matrices in the noisy case. For the second part of the thesis, we introduce a rank-one projection model for low-rank matrix recovery and propose a constrained nuclear norm minimization method for stable recovery of low-rank matrices in the noisy case. The procedure is adaptive to the rank and robust against small perturbations. Both upper and lower bounds for the estimation accuracy under the Frobenius norm loss are obtained. The proposed estimator is shown to be rate-optimal under certain conditions. The
Approximation of High-Dimensional Rank One Tensors
Bachmayr, Markus
2013-11-12
Many real world problems are high-dimensional in that their solution is a function which depends on many variables or parameters. This presents a computational challenge since traditional numerical techniques are built on model classes for functions based solely on smoothness. It is known that the approximation of smoothness classes of functions suffers from the so-called \\'curse of dimensionality\\'. Avoiding this curse requires new model classes for real world functions that match applications. This has led to the introduction of notions such as sparsity, variable reduction, and reduced modeling. One theme that is particularly common is to assume a tensor structure for the target function. This paper investigates how well a rank one function f(x 1,...,x d)=f 1(x 1)⋯f d(x d), defined on Ω=[0,1]d can be captured through point queries. It is shown that such a rank one function with component functions f j in W∞ r([0,1]) can be captured (in L ∞) to accuracy O(C(d,r)N -r) from N well-chosen point evaluations. The constant C(d,r) scales like d dr. The queries in our algorithms have two ingredients, a set of points built on the results from discrepancy theory and a second adaptive set of queries dependent on the information drawn from the first set. Under the assumption that a point z∈Ω with nonvanishing f(z) is known, the accuracy improves to O(dN -r). © 2013 Springer Science+Business Media New York.
Quality and efficiency in high dimensional Nearest neighbor search
Tao, Yufei; Yi, Ke; Sheng, Cheng; Kalnis, Panos
2009-01-01
Nearest neighbor (NN) search in high dimensional space is an important problem in many applications. Ideally, a practical solution (i) should be implementable in a relational database, and (ii) its query cost should grow sub-linearly with the dataset size, regardless of the data and query distributions. Despite the bulk of NN literature, no solution fulfills both requirements, except locality sensitive hashing (LSH). The existing LSH implementations are either rigorous or adhoc. Rigorous-LSH ensures good quality of query results, but requires expensive space and query cost. Although adhoc-LSH is more efficient, it abandons quality control, i.e., the neighbor it outputs can be arbitrarily bad. As a result, currently no method is able to ensure both quality and efficiency simultaneously in practice. Motivated by this, we propose a new access method called the locality sensitive B-tree (LSB-tree) that enables fast highdimensional NN search with excellent quality. The combination of several LSB-trees leads to a structure called the LSB-forest that ensures the same result quality as rigorous-LSH, but reduces its space and query cost dramatically. The LSB-forest also outperforms adhoc-LSH, even though the latter has no quality guarantee. Besides its appealing theoretical properties, the LSB-tree itself also serves as an effective index that consumes linear space, and supports efficient updates. Our extensive experiments confirm that the LSB-tree is faster than (i) the state of the art of exact NN search by two orders of magnitude, and (ii) the best (linear-space) method of approximate retrieval by an order of magnitude, and at the same time, returns neighbors with much better quality. © 2009 ACM.
Approximation of High-Dimensional Rank One Tensors
Bachmayr, Markus; Dahmen, Wolfgang; DeVore, Ronald; Grasedyck, Lars
2013-01-01
Many real world problems are high-dimensional in that their solution is a function which depends on many variables or parameters. This presents a computational challenge since traditional numerical techniques are built on model classes for functions based solely on smoothness. It is known that the approximation of smoothness classes of functions suffers from the so-called 'curse of dimensionality'. Avoiding this curse requires new model classes for real world functions that match applications. This has led to the introduction of notions such as sparsity, variable reduction, and reduced modeling. One theme that is particularly common is to assume a tensor structure for the target function. This paper investigates how well a rank one function f(x 1,...,x d)=f 1(x 1)⋯f d(x d), defined on Ω=[0,1]d can be captured through point queries. It is shown that such a rank one function with component functions f j in W∞ r([0,1]) can be captured (in L ∞) to accuracy O(C(d,r)N -r) from N well-chosen point evaluations. The constant C(d,r) scales like d dr. The queries in our algorithms have two ingredients, a set of points built on the results from discrepancy theory and a second adaptive set of queries dependent on the information drawn from the first set. Under the assumption that a point z∈Ω with nonvanishing f(z) is known, the accuracy improves to O(dN -r). © 2013 Springer Science+Business Media New York.
Input-output theory and institutional aspects of environmental policy
Steenge, A.E.
1999-01-01
National accounting over the years has developed in close interaction with input–output analysis. However, present developments involving core and satellite accounts seem to suggest that this relation will become less close, with possible negative consequences for analysis and policy. In this paper
Interface Input/Output Automata: Splitting Assumptions from Guarantees
DEFF Research Database (Denmark)
Larsen, Kim Guldstrand; Nyman, Ulrik; Wasowski, Andrzej
2006-01-01
's \\IOAs [11], relying on a context dependent notion of refinement based on relativized language inclusion. There are two main contributions of the work. First, we explicitly separate assumptions from guarantees, increasing the modeling power of the specification language and demonstrating an interesting...
Input-Output Economics : Theory and Applications - Featuring Asian Economies
Ten Raa, T.
2009-01-01
Thijs ten Raa, author of the acclaimed text The Economics of Input–Output Analysis, now takes the reader to the forefront of the field. This volume collects and unifies his and his co-authors' research papers on national accounting, Input–Output coefficients, economic theory, dynamic models,
Input/Output: hoeveelheid en volume compost in de champignonkweek
Leyh, Romain; Blok, Chris
2017-01-01
The conclusion of a previous experiment showed that the compost quantity was the most determining parameter for the production volume of mushrooms, despite the addition of hemi cellulose as carbon source to the compost. The present experiment focuses on the mycelium action with regard to the carbon
Input, Output, and Negotiation of Meaning in Spanish Conversation Classes
Rondon-Pari, Graziela
2014-01-01
This research study is based on the analysis of speech in three Spanish conversation classes. Research questions are: What is the ratio of English and Spanish spoken in class? Is classroom speech more predominant in students or the instructor? And, are teachers' beliefs in regards to the use of English and Spanish consistent with their classroom…
Input-output interactions and optimal monetary policy
DEFF Research Database (Denmark)
Petrella, Ivan; Santoro, Emiliano
2011-01-01
This paper deals with the implications of factor demand linkages for monetary policy design in a two-sector dynamic general equilibrium model. Part of the output of each sector serves as a production input in both sectors, in accordance with a realistic input–output structure. Strategic...... complementarities induced by factor demand linkages significantly alter the transmission of shocks and amplify the loss of social welfare under optimal monetary policy, compared to what is observed in standard two-sector models. The distinction between value added and gross output that naturally arises...... in this context is of key importance to explore the welfare properties of the model economy. A flexible inflation targeting regime is close to optimal only if the central bank balances inflation and value added variability. Otherwise, targeting gross output variability entails a substantial increase in the loss...
Energy Technology Data Exchange (ETDEWEB)
Tahira, Rabia; Ikram, Manzoor; Zubairy, M Suhail [Centre for Quantum Physics, COMSATS Institute of Information Technology, Islamabad (Pakistan); Bougouffa, Smail [Department of Physics, Faculty of Science, Taibah University, PO Box 30002, Madinah (Saudi Arabia)
2010-02-14
We investigate the phenomenon of sudden death of entanglement in a high-dimensional bipartite system subjected to dissipative environments with an arbitrary initial pure entangled state between two fields in the cavities. We find that in a vacuum reservoir, the presence of the state where one or more than one (two) photons in each cavity are present is a necessary condition for the sudden death of entanglement. Otherwise entanglement remains for infinite time and decays asymptotically with the decay of individual qubits. For pure two-qubit entangled states in a thermal environment, we observe that sudden death of entanglement always occurs. The sudden death time of the entangled states is related to the number of photons in the cavities, the temperature of the reservoir and the initial preparation of the entangled states.
International Nuclear Information System (INIS)
Tahira, Rabia; Ikram, Manzoor; Zubairy, M Suhail; Bougouffa, Smail
2010-01-01
We investigate the phenomenon of sudden death of entanglement in a high-dimensional bipartite system subjected to dissipative environments with an arbitrary initial pure entangled state between two fields in the cavities. We find that in a vacuum reservoir, the presence of the state where one or more than one (two) photons in each cavity are present is a necessary condition for the sudden death of entanglement. Otherwise entanglement remains for infinite time and decays asymptotically with the decay of individual qubits. For pure two-qubit entangled states in a thermal environment, we observe that sudden death of entanglement always occurs. The sudden death time of the entangled states is related to the number of photons in the cavities, the temperature of the reservoir and the initial preparation of the entangled states.
Matrix correlations for high-dimensional data: The modified RV-coefficient
Smilde, A.K.; Kiers, H.A.L.; Bijlsma, S.; Rubingh, C.M.; Erk, M.J. van
2009-01-01
Motivation: Modern functional genomics generates high-dimensional datasets. It is often convenient to have a single simple number characterizing the relationship between pairs of such high-dimensional datasets in a comprehensive way. Matrix correlations are such numbers and are appealing since they
High dimensional biological data retrieval optimization with NoSQL technology
2014-01-01
Background High-throughput transcriptomic data generated by microarray experiments is the most abundant and frequently stored kind of data currently used in translational medicine studies. Although microarray data is supported in data warehouses such as tranSMART, when querying relational databases for hundreds of different patient gene expression records queries are slow due to poor performance. Non-relational data models, such as the key-value model implemented in NoSQL databases, hold promise to be more performant solutions. Our motivation is to improve the performance of the tranSMART data warehouse with a view to supporting Next Generation Sequencing data. Results In this paper we introduce a new data model better suited for high-dimensional data storage and querying, optimized for database scalability and performance. We have designed a key-value pair data model to support faster queries over large-scale microarray data and implemented the model using HBase, an implementation of Google's BigTable storage system. An experimental performance comparison was carried out against the traditional relational data model implemented in both MySQL Cluster and MongoDB, using a large publicly available transcriptomic data set taken from NCBI GEO concerning Multiple Myeloma. Our new key-value data model implemented on HBase exhibits an average 5.24-fold increase in high-dimensional biological data query performance compared to the relational model implemented on MySQL Cluster, and an average 6.47-fold increase on query performance on MongoDB. Conclusions The performance evaluation found that the new key-value data model, in particular its implementation in HBase, outperforms the relational model currently implemented in tranSMART. We propose that NoSQL technology holds great promise for large-scale data management, in particular for high-dimensional biological data such as that demonstrated in the performance evaluation described in this paper. We aim to use this new data
High dimensional biological data retrieval optimization with NoSQL technology.
Wang, Shicai; Pandis, Ioannis; Wu, Chao; He, Sijin; Johnson, David; Emam, Ibrahim; Guitton, Florian; Guo, Yike
2014-01-01
High-throughput transcriptomic data generated by microarray experiments is the most abundant and frequently stored kind of data currently used in translational medicine studies. Although microarray data is supported in data warehouses such as tranSMART, when querying relational databases for hundreds of different patient gene expression records queries are slow due to poor performance. Non-relational data models, such as the key-value model implemented in NoSQL databases, hold promise to be more performant solutions. Our motivation is to improve the performance of the tranSMART data warehouse with a view to supporting Next Generation Sequencing data. In this paper we introduce a new data model better suited for high-dimensional data storage and querying, optimized for database scalability and performance. We have designed a key-value pair data model to support faster queries over large-scale microarray data and implemented the model using HBase, an implementation of Google's BigTable storage system. An experimental performance comparison was carried out against the traditional relational data model implemented in both MySQL Cluster and MongoDB, using a large publicly available transcriptomic data set taken from NCBI GEO concerning Multiple Myeloma. Our new key-value data model implemented on HBase exhibits an average 5.24-fold increase in high-dimensional biological data query performance compared to the relational model implemented on MySQL Cluster, and an average 6.47-fold increase on query performance on MongoDB. The performance evaluation found that the new key-value data model, in particular its implementation in HBase, outperforms the relational model currently implemented in tranSMART. We propose that NoSQL technology holds great promise for large-scale data management, in particular for high-dimensional biological data such as that demonstrated in the performance evaluation described in this paper. We aim to use this new data model as a basis for migrating
Shaffer, Patrick; Valsson, Omar; Parrinello, Michele
2016-02-02
The capabilities of molecular simulations have been greatly extended by a number of widely used enhanced sampling methods that facilitate escaping from metastable states and crossing large barriers. Despite these developments there are still many problems which remain out of reach for these methods which has led to a vigorous effort in this area. One of the most important problems that remains unsolved is sampling high-dimensional free-energy landscapes and systems that are not easily described by a small number of collective variables. In this work we demonstrate a new way to compute free-energy landscapes of high dimensionality based on the previously introduced variationally enhanced sampling, and we apply it to the miniprotein chignolin.
Shaffer, Patrick; Valsson, Omar; Parrinello, Michele
2016-01-01
The capabilities of molecular simulations have been greatly extended by a number of widely used enhanced sampling methods that facilitate escaping from metastable states and crossing large barriers. Despite these developments there are still many problems which remain out of reach for these methods which has led to a vigorous effort in this area. One of the most important problems that remains unsolved is sampling high-dimensional free-energy landscapes and systems that are not easily described by a small number of collective variables. In this work we demonstrate a new way to compute free-energy landscapes of high dimensionality based on the previously introduced variationally enhanced sampling, and we apply it to the miniprotein chignolin. PMID:26787868
Dynamic mode decomposition for compressive system identification
Bai, Zhe; Kaiser, Eurika; Proctor, Joshua L.; Kutz, J. Nathan; Brunton, Steven L.
2017-11-01
Dynamic mode decomposition has emerged as a leading technique to identify spatiotemporal coherent structures from high-dimensional data. In this work, we integrate and unify two recent innovations that extend DMD to systems with actuation and systems with heavily subsampled measurements. When combined, these methods yield a novel framework for compressive system identification, where it is possible to identify a low-order model from limited input-output data and reconstruct the associated full-state dynamic modes with compressed sensing, providing interpretability of the state of the reduced-order model. When full-state data is available, it is possible to dramatically accelerate downstream computations by first compressing the data. We demonstrate this unified framework on simulated data of fluid flow past a pitching airfoil, investigating the effects of sensor noise, different types of measurements (e.g., point sensors, Gaussian random projections, etc.), compression ratios, and different choices of actuation (e.g., localized, broadband, etc.). This example provides a challenging and realistic test-case for the proposed method, and results indicate that the dominant coherent structures and dynamics are well characterized even with heavily subsampled data.
Port contact systems for irreversible thermodynamical systems
Eberard, D.; Maschke, B.M.; Schaft, A.J. van der
2005-01-01
In this paper we propose a definition of control contact systems, generalizing input-output Hamiltonian systems, to cope with models arising from irreversible Thermodynamics. We exhibit a particular subclass of these systems, called conservative, that leaves invariant some Legendre submanifold (the
Nam, Julia EunJu; Mueller, Klaus
2013-02-01
Gaining a true appreciation of high-dimensional space remains difficult since all of the existing high-dimensional space exploration techniques serialize the space travel in some way. This is not so foreign to us since we, when traveling, also experience the world in a serial fashion. But we typically have access to a map to help with positioning, orientation, navigation, and trip planning. Here, we propose a multivariate data exploration tool that compares high-dimensional space navigation with a sightseeing trip. It decomposes this activity into five major tasks: 1) Identify the sights: use a map to identify the sights of interest and their location; 2) Plan the trip: connect the sights of interest along a specifyable path; 3) Go on the trip: travel along the route; 4) Hop off the bus: experience the location, look around, zoom into detail; and 5) Orient and localize: regain bearings in the map. We describe intuitive and interactive tools for all of these tasks, both global navigation within the map and local exploration of the data distributions. For the latter, we describe a polygonal touchpad interface which enables users to smoothly tilt the projection plane in high-dimensional space to produce multivariate scatterplots that best convey the data relationships under investigation. Motion parallax and illustrative motion trails aid in the perception of these transient patterns. We describe the use of our system within two applications: 1) the exploratory discovery of data configurations that best fit a personal preference in the presence of tradeoffs and 2) interactive cluster analysis via cluster sculpting in N-D.
Self-dissimilarity as a High Dimensional Complexity Measure
Wolpert, David H.; Macready, William
2005-01-01
For many systems characterized as "complex" the patterns exhibited on different scales differ markedly from one another. For example the biomass distribution in a human body "looks very different" depending on the scale at which one examines it. Conversely, the patterns at different scales in "simple" systems (e.g., gases, mountains, crystals) vary little from one scale to another. Accordingly, the degrees of self-dissimilarity between the patterns of a system at various scales constitute a complexity "signature" of that system. Here we present a novel quantification of self-dissimilarity. This signature can, if desired, incorporate a novel information-theoretic measure of the distance between probability distributions that we derive here. Whatever distance measure is chosen, our quantification of self-dissimilarity can be measured for many kinds of real-world data. This allows comparisons of the complexity signatures of wholly different kinds of systems (e.g., systems involving information density in a digital computer vs. species densities in a rain-forest vs. capital density in an economy, etc.). Moreover, in contrast to many other suggested complexity measures, evaluating the self-dissimilarity of a system does not require one to already have a model of the system. These facts may allow self-dissimilarity signatures to be used a s the underlying observational variables of an eventual overarching theory relating all complex systems. To illustrate self-dissimilarity we present several numerical experiments. In particular, we show that underlying structure of the logistic map is picked out by the self-dissimilarity signature of time series produced by that map
Construction of high-dimensional neural network potentials using environment-dependent atom pairs.
Jose, K V Jovan; Artrith, Nongnuch; Behler, Jörg
2012-05-21
An accurate determination of the potential energy is the crucial step in computer simulations of chemical processes, but using electronic structure methods on-the-fly in molecular dynamics (MD) is computationally too demanding for many systems. Constructing more efficient interatomic potentials becomes intricate with increasing dimensionality of the potential-energy surface (PES), and for numerous systems the accuracy that can be achieved is still not satisfying and far from the reliability of first-principles calculations. Feed-forward neural networks (NNs) have a very flexible functional form, and in recent years they have been shown to be an accurate tool to construct efficient PESs. High-dimensional NN potentials based on environment-dependent atomic energy contributions have been presented for a number of materials. Still, these potentials may be improved by a more detailed structural description, e.g., in form of atom pairs, which directly reflect the atomic interactions and take the chemical environment into account. We present an implementation of an NN method based on atom pairs, and its accuracy and performance are compared to the atom-based NN approach using two very different systems, the methanol molecule and metallic copper. We find that both types of NN potentials provide an excellent description of both PESs, with the pair-based method yielding a slightly higher accuracy making it a competitive alternative for addressing complex systems in MD simulations.
Approximating high-dimensional dynamics by barycentric coordinates with linear programming
Energy Technology Data Exchange (ETDEWEB)
Hirata, Yoshito, E-mail: yoshito@sat.t.u-tokyo.ac.jp; Aihara, Kazuyuki; Suzuki, Hideyuki [Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505 (Japan); Department of Mathematical Informatics, The University of Tokyo, Bunkyo-ku, Tokyo 113-8656 (Japan); CREST, JST, 4-1-8 Honcho, Kawaguchi, Saitama 332-0012 (Japan); Shiro, Masanori [Department of Mathematical Informatics, The University of Tokyo, Bunkyo-ku, Tokyo 113-8656 (Japan); Mathematical Neuroinformatics Group, Advanced Industrial Science and Technology, Tsukuba, Ibaraki 305-8568 (Japan); Takahashi, Nozomu; Mas, Paloma [Center for Research in Agricultural Genomics (CRAG), Consorci CSIC-IRTA-UAB-UB, Barcelona 08193 (Spain)
2015-01-15
The increasing development of novel methods and techniques facilitates the measurement of high-dimensional time series but challenges our ability for accurate modeling and predictions. The use of a general mathematical model requires the inclusion of many parameters, which are difficult to be fitted for relatively short high-dimensional time series observed. Here, we propose a novel method to accurately model a high-dimensional time series. Our method extends the barycentric coordinates to high-dimensional phase space by employing linear programming, and allowing the approximation errors explicitly. The extension helps to produce free-running time-series predictions that preserve typical topological, dynamical, and/or geometric characteristics of the underlying attractors more accurately than the radial basis function model that is widely used. The method can be broadly applied, from helping to improve weather forecasting, to creating electronic instruments that sound more natural, and to comprehensively understanding complex biological data.
Approximating high-dimensional dynamics by barycentric coordinates with linear programming
International Nuclear Information System (INIS)
Hirata, Yoshito; Aihara, Kazuyuki; Suzuki, Hideyuki; Shiro, Masanori; Takahashi, Nozomu; Mas, Paloma
2015-01-01
The increasing development of novel methods and techniques facilitates the measurement of high-dimensional time series but challenges our ability for accurate modeling and predictions. The use of a general mathematical model requires the inclusion of many parameters, which are difficult to be fitted for relatively short high-dimensional time series observed. Here, we propose a novel method to accurately model a high-dimensional time series. Our method extends the barycentric coordinates to high-dimensional phase space by employing linear programming, and allowing the approximation errors explicitly. The extension helps to produce free-running time-series predictions that preserve typical topological, dynamical, and/or geometric characteristics of the underlying attractors more accurately than the radial basis function model that is widely used. The method can be broadly applied, from helping to improve weather forecasting, to creating electronic instruments that sound more natural, and to comprehensively understanding complex biological data
Approximating high-dimensional dynamics by barycentric coordinates with linear programming.
Hirata, Yoshito; Shiro, Masanori; Takahashi, Nozomu; Aihara, Kazuyuki; Suzuki, Hideyuki; Mas, Paloma
2015-01-01
The increasing development of novel methods and techniques facilitates the measurement of high-dimensional time series but challenges our ability for accurate modeling and predictions. The use of a general mathematical model requires the inclusion of many parameters, which are difficult to be fitted for relatively short high-dimensional time series observed. Here, we propose a novel method to accurately model a high-dimensional time series. Our method extends the barycentric coordinates to high-dimensional phase space by employing linear programming, and allowing the approximation errors explicitly. The extension helps to produce free-running time-series predictions that preserve typical topological, dynamical, and/or geometric characteristics of the underlying attractors more accurately than the radial basis function model that is widely used. The method can be broadly applied, from helping to improve weather forecasting, to creating electronic instruments that sound more natural, and to comprehensively understanding complex biological data.
Efficient and accurate nearest neighbor and closest pair search in high-dimensional space
Tao, Yufei; Yi, Ke; Sheng, Cheng; Kalnis, Panos
2010-01-01
Nearest Neighbor (NN) search in high-dimensional space is an important problem in many applications. From the database perspective, a good solution needs to have two properties: (i) it can be easily incorporated in a relational database, and (ii
Rasmussen, Robert D. (Inventor); Manning, Robert M. (Inventor); Lewis, Blair F. (Inventor); Bolotin, Gary S. (Inventor); Ward, Richard S. (Inventor)
1990-01-01
This is a distributed computing system providing flexible fault tolerance; ease of software design and concurrency specification; and dynamic balance of the loads. The system comprises a plurality of computers each having a first input/output interface and a second input/output interface for interfacing to communications networks each second input/output interface including a bypass for bypassing the associated computer. A global communications network interconnects the first input/output interfaces for providing each computer the ability to broadcast messages simultaneously to the remainder of the computers. A meshwork communications network interconnects the second input/output interfaces providing each computer with the ability to establish a communications link with another of the computers bypassing the remainder of computers. Each computer is controlled by a resident copy of a common operating system. Communications between respective ones of computers is by means of split tokens each having a moving first portion which is sent from computer to computer and a resident second portion which is disposed in the memory of at least one of computer and wherein the location of the second portion is part of the first portion. The split tokens represent both functions to be executed by the computers and data to be employed in the execution of the functions. The first input/output interfaces each include logic for detecting a collision between messages and for terminating the broadcasting of a message whereby collisions between messages are detected and avoided.
On High Dimensional Searching Spaces and Learning Methods
DEFF Research Database (Denmark)
Yazdani, Hossein; Ortiz-Arroyo, Daniel; Choros, Kazimierz
2017-01-01
, and similarity functions and discuss the pros and cons of using each of them. Conventional similarity functions evaluate objects in the vector space. Contrarily, Weighted Feature Distance (WFD) functions compare data objects in both feature and vector spaces, preventing the system from being affected by some...
Approximate Dynamic Programming Based on High Dimensional Model Representation
Czech Academy of Sciences Publication Activity Database
Pištěk, Miroslav
2013-01-01
Roč. 49, č. 5 (2013), s. 720-737 ISSN 0023-5954 R&D Projects: GA ČR(CZ) GAP102/11/0437 Institutional support: RVO:67985556 Keywords : approximate dynamic programming * Bellman equation * approximate HDMR minimization * trust region problem Subject RIV: BC - Control Systems Theory Impact factor: 0.563, year: 2013 http://library.utia.cas.cz/separaty/2013/AS/pistek-0399560.pdf
Energy Technology Data Exchange (ETDEWEB)
Avarzad, O; Rikhvitskij, V S
1996-12-31
System of acquisition and analysis of both statistic and dynamic images of neutron radiography includes NM IBM PC XT/AT, super vidicon, telecamera based video detector, color monitor and interface board of image input-output. 2 refs.
Interactive Visualization of Large High-Dimensional Datasets
Ding, Wei; Chen, Ping
Nowadays many companies and public organizations use powerful database systems for collecting and managing information. Huge amount of data records are often accumulated within a short period of time. Valuable information is embedded in these data, which could help discover interesting knowledge and significantly assist in decision-making process. However, human beings are not capable of understanding so many data records which often have lots of attributes. The need for automated knowledge extraction is widely recognized, and leads to a rapidly developing market of data analysis and knowledge discovery tools.
Directory of Open Access Journals (Sweden)
Enkelejda Miho
2018-02-01
Full Text Available The adaptive immune system recognizes antigens via an immense array of antigen-binding antibodies and T-cell receptors, the immune repertoire. The interrogation of immune repertoires is of high relevance for understanding the adaptive immune response in disease and infection (e.g., autoimmunity, cancer, HIV. Adaptive immune receptor repertoire sequencing (AIRR-seq has driven the quantitative and molecular-level profiling of immune repertoires, thereby revealing the high-dimensional complexity of the immune receptor sequence landscape. Several methods for the computational and statistical analysis of large-scale AIRR-seq data have been developed to resolve immune repertoire complexity and to understand the dynamics of adaptive immunity. Here, we review the current research on (i diversity, (ii clustering and network, (iii phylogenetic, and (iv machine learning methods applied to dissect, quantify, and compare the architecture, evolution, and specificity of immune repertoires. We summarize outstanding questions in computational immunology and propose future directions for systems immunology toward coupling AIRR-seq with the computational discovery of immunotherapeutics, vaccines, and immunodiagnostics.
Feature selection for high-dimensional integrated data
Zheng, Charles; Schwartz, Scott; Chapkin, Robert S.; Carroll, Raymond J.; Ivanov, Ivan
2012-01-01
Motivated by the problem of identifying correlations between genes or features of two related biological systems, we propose a model of feature selection in which only a subset of the predictors Xt are dependent on the multidimensional variate Y, and the remainder of the predictors constitute a “noise set” Xu independent of Y. Using Monte Carlo simulations, we investigated the relative performance of two methods: thresholding and singular-value decomposition, in combination with stochastic optimization to determine “empirical bounds” on the small-sample accuracy of an asymptotic approximation. We demonstrate utility of the thresholding and SVD feature selection methods to with respect to a recent infant intestinal gene expression and metagenomics dataset.
Applications of Asymptotic Sampling on High Dimensional Structural Dynamic Problems
DEFF Research Database (Denmark)
Sichani, Mahdi Teimouri; Nielsen, Søren R.K.; Bucher, Christian
2011-01-01
The paper represents application of the asymptotic sampling on various structural models subjected to random excitations. A detailed study on the effect of different distributions of the so-called support points is performed. This study shows that the distribution of the support points has consid...... dimensional reliability problems in structural dynamics.......The paper represents application of the asymptotic sampling on various structural models subjected to random excitations. A detailed study on the effect of different distributions of the so-called support points is performed. This study shows that the distribution of the support points has...... is minimized. Next, the method is applied on different cases of linear and nonlinear systems with a large number of random variables representing the dynamic excitation. The results show that asymptotic sampling is capable of providing good approximations of low failure probability events for very high...
Feature selection for high-dimensional integrated data
Zheng, Charles
2012-04-26
Motivated by the problem of identifying correlations between genes or features of two related biological systems, we propose a model of feature selection in which only a subset of the predictors Xt are dependent on the multidimensional variate Y, and the remainder of the predictors constitute a “noise set” Xu independent of Y. Using Monte Carlo simulations, we investigated the relative performance of two methods: thresholding and singular-value decomposition, in combination with stochastic optimization to determine “empirical bounds” on the small-sample accuracy of an asymptotic approximation. We demonstrate utility of the thresholding and SVD feature selection methods to with respect to a recent infant intestinal gene expression and metagenomics dataset.
Accelerated Sensitivity Analysis in High-Dimensional Stochastic Reaction Networks.
Arampatzis, Georgios; Katsoulakis, Markos A; Pantazis, Yannis
2015-01-01
Existing sensitivity analysis approaches are not able to handle efficiently stochastic reaction networks with a large number of parameters and species, which are typical in the modeling and simulation of complex biochemical phenomena. In this paper, a two-step strategy for parametric sensitivity analysis for such systems is proposed, exploiting advantages and synergies between two recently proposed sensitivity analysis methodologies for stochastic dynamics. The first method performs sensitivity analysis of the stochastic dynamics by means of the Fisher Information Matrix on the underlying distribution of the trajectories; the second method is a reduced-variance, finite-difference, gradient-type sensitivity approach relying on stochastic coupling techniques for variance reduction. Here we demonstrate that these two methods can be combined and deployed together by means of a new sensitivity bound which incorporates the variance of the quantity of interest as well as the Fisher Information Matrix estimated from the first method. The first step of the proposed strategy labels sensitivities using the bound and screens out the insensitive parameters in a controlled manner. In the second step of the proposed strategy, a finite-difference method is applied only for the sensitivity estimation of the (potentially) sensitive parameters that have not been screened out in the first step. Results on an epidermal growth factor network with fifty parameters and on a protein homeostasis with eighty parameters demonstrate that the proposed strategy is able to quickly discover and discard the insensitive parameters and in the remaining potentially sensitive parameters it accurately estimates the sensitivities. The new sensitivity strategy can be several times faster than current state-of-the-art approaches that test all parameters, especially in "sloppy" systems. In particular, the computational acceleration is quantified by the ratio between the total number of parameters over the
Accelerated Sensitivity Analysis in High-Dimensional Stochastic Reaction Networks.
Directory of Open Access Journals (Sweden)
Georgios Arampatzis
Full Text Available Existing sensitivity analysis approaches are not able to handle efficiently stochastic reaction networks with a large number of parameters and species, which are typical in the modeling and simulation of complex biochemical phenomena. In this paper, a two-step strategy for parametric sensitivity analysis for such systems is proposed, exploiting advantages and synergies between two recently proposed sensitivity analysis methodologies for stochastic dynamics. The first method performs sensitivity analysis of the stochastic dynamics by means of the Fisher Information Matrix on the underlying distribution of the trajectories; the second method is a reduced-variance, finite-difference, gradient-type sensitivity approach relying on stochastic coupling techniques for variance reduction. Here we demonstrate that these two methods can be combined and deployed together by means of a new sensitivity bound which incorporates the variance of the quantity of interest as well as the Fisher Information Matrix estimated from the first method. The first step of the proposed strategy labels sensitivities using the bound and screens out the insensitive parameters in a controlled manner. In the second step of the proposed strategy, a finite-difference method is applied only for the sensitivity estimation of the (potentially sensitive parameters that have not been screened out in the first step. Results on an epidermal growth factor network with fifty parameters and on a protein homeostasis with eighty parameters demonstrate that the proposed strategy is able to quickly discover and discard the insensitive parameters and in the remaining potentially sensitive parameters it accurately estimates the sensitivities. The new sensitivity strategy can be several times faster than current state-of-the-art approaches that test all parameters, especially in "sloppy" systems. In particular, the computational acceleration is quantified by the ratio between the total number of
Modeling and Optimization of Phenol Formaldehyde Resin Sand Mould System
Directory of Open Access Journals (Sweden)
Chate G. R.
2017-06-01
Full Text Available Chemical bonded resin sand mould system has high dimensional accuracy, surface finish and sand mould properties compared to green sand mould system. The mould cavity prepared under chemical bonded sand mould system must produce sufficient permeability and hardness to withstand sand drop while pouring molten metal through ladle. The demand for improved values of permeability and mould hardness depends on systematic study and analysis of influencing variables namely grain fineness number, setting time, percent of resin and hardener. Try-error experiment methods and analysis were considered impractical in actual foundry practice due to the associated cost. Experimental matrices of central composite design allow conducting minimum experiments that provide complete insight of the process. Statistical significance of influencing variables and their interaction were determined to control the process. Analysis of variance (ANOVA test was conducted to validate the model statistically. Mathematical equation was derived separately for mould hardness and permeability, which are expressed as a non-linear function of input variables based on the collected experimental input-output data. The developed model prediction accuracy for practical usefulness was tested with 10 random experimental conditions. The decision variables for higher mould hardness and permeability were determined using desirability function approach. The prediction results were found to be consistent with experimental values.
Bayesian Inference of High-Dimensional Dynamical Ocean Models
Lin, J.; Lermusiaux, P. F. J.; Lolla, S. V. T.; Gupta, A.; Haley, P. J., Jr.
2015-12-01
This presentation addresses a holistic set of challenges in high-dimension ocean Bayesian nonlinear estimation: i) predict the probability distribution functions (pdfs) of large nonlinear dynamical systems using stochastic partial differential equations (PDEs); ii) assimilate data using Bayes' law with these pdfs; iii) predict the future data that optimally reduce uncertainties; and (iv) rank the known and learn the new model formulations themselves. Overall, we allow the joint inference of the state, equations, geometry, boundary conditions and initial conditions of dynamical models. Examples are provided for time-dependent fluid and ocean flows, including cavity, double-gyre and Strait flows with jets and eddies. The Bayesian model inference, based on limited observations, is illustrated first by the estimation of obstacle shapes and positions in fluid flows. Next, the Bayesian inference of biogeochemical reaction equations and of their states and parameters is presented, illustrating how PDE-based machine learning can rigorously guide the selection and discovery of complex ecosystem models. Finally, the inference of multiscale bottom gravity current dynamics is illustrated, motivated in part by classic overflows and dense water formation sites and their relevance to climate monitoring and dynamics. This is joint work with our MSEAS group at MIT.
Robust and sparse correlation matrix estimation for the analysis of high-dimensional genomics data.
Serra, Angela; Coretto, Pietro; Fratello, Michele; Tagliaferri, Roberto; Stegle, Oliver
2018-02-15
Microarray technology can be used to study the expression of thousands of genes across a number of different experimental conditions, usually hundreds. The underlying principle is that genes sharing similar expression patterns, across different samples, can be part of the same co-expression system, or they may share the same biological functions. Groups of genes are usually identified based on cluster analysis. Clustering methods rely on the similarity matrix between genes. A common choice to measure similarity is to compute the sample correlation matrix. Dimensionality reduction is another popular data analysis task which is also based on covariance/correlation matrix estimates. Unfortunately, covariance/correlation matrix estimation suffers from the intrinsic noise present in high-dimensional data. Sources of noise are: sampling variations, presents of outlying sample units, and the fact that in most cases the number of units is much larger than the number of genes. In this paper, we propose a robust correlation matrix estimator that is regularized based on adaptive thresholding. The resulting method jointly tames the effects of the high-dimensionality, and data contamination. Computations are easy to implement and do not require hand tunings. Both simulated and real data are analyzed. A Monte Carlo experiment shows that the proposed method is capable of remarkable performances. Our correlation metric is more robust to outliers compared with the existing alternatives in two gene expression datasets. It is also shown how the regularization allows to automatically detect and filter spurious correlations. The same regularization is also extended to other less robust correlation measures. Finally, we apply the ARACNE algorithm on the SyNTreN gene expression data. Sensitivity and specificity of the reconstructed network is compared with the gold standard. We show that ARACNE performs better when it takes the proposed correlation matrix estimator as input. The R
Energy Technology Data Exchange (ETDEWEB)
Dan Maljovec; Bei Wang; Valerio Pascucci; Peer-Timo Bremer; Michael Pernice; Robert Nourgaliev
2013-05-01
The next generation of methodologies for nuclear reactor Probabilistic Risk Assessment (PRA) explicitly accounts for the time element in modeling the probabilistic system evolution and uses numerical simulation tools to account for possible dependencies between failure events. The Monte-Carlo (MC) and the Dynamic Event Tree (DET) approaches belong to this new class of dynamic PRA methodologies. A challenge of dynamic PRA algorithms is the large amount of data they produce which may be difficult to visualize and analyze in order to extract useful information. We present a software tool that is designed to address these goals. We model a large-scale nuclear simulation dataset as a high-dimensional scalar function defined over a discrete sample of the domain. First, we provide structural analysis of such a function at multiple scales and provide insight into the relationship between the input parameters and the output. Second, we enable exploratory analysis for users, where we help the users to differentiate features from noise through multi-scale analysis on an interactive platform, based on domain knowledge and data characterization. Our analysis is performed by exploiting the topological and geometric properties of the domain, building statistical models based on its topological segmentations and providing interactive visual interfaces to facilitate such explorations. We provide a user’s guide to our software tool by highlighting its analysis and visualization capabilities, along with a use case involving dataset from a nuclear reactor safety simulation.
A Comparison of Methods for Estimating the Determinant of High-Dimensional Covariance Matrix
Hu, Zongliang
2017-09-27
The determinant of the covariance matrix for high-dimensional data plays an important role in statistical inference and decision. It has many real applications including statistical tests and information theory. Due to the statistical and computational challenges with high dimensionality, little work has been proposed in the literature for estimating the determinant of high-dimensional covariance matrix. In this paper, we estimate the determinant of the covariance matrix using some recent proposals for estimating high-dimensional covariance matrix. Specifically, we consider a total of eight covariance matrix estimation methods for comparison. Through extensive simulation studies, we explore and summarize some interesting comparison results among all compared methods. We also provide practical guidelines based on the sample size, the dimension, and the correlation of the data set for estimating the determinant of high-dimensional covariance matrix. Finally, from a perspective of the loss function, the comparison study in this paper may also serve as a proxy to assess the performance of the covariance matrix estimation.
A Comparison of Methods for Estimating the Determinant of High-Dimensional Covariance Matrix.
Hu, Zongliang; Dong, Kai; Dai, Wenlin; Tong, Tiejun
2017-09-21
The determinant of the covariance matrix for high-dimensional data plays an important role in statistical inference and decision. It has many real applications including statistical tests and information theory. Due to the statistical and computational challenges with high dimensionality, little work has been proposed in the literature for estimating the determinant of high-dimensional covariance matrix. In this paper, we estimate the determinant of the covariance matrix using some recent proposals for estimating high-dimensional covariance matrix. Specifically, we consider a total of eight covariance matrix estimation methods for comparison. Through extensive simulation studies, we explore and summarize some interesting comparison results among all compared methods. We also provide practical guidelines based on the sample size, the dimension, and the correlation of the data set for estimating the determinant of high-dimensional covariance matrix. Finally, from a perspective of the loss function, the comparison study in this paper may also serve as a proxy to assess the performance of the covariance matrix estimation.
A Comparison of Methods for Estimating the Determinant of High-Dimensional Covariance Matrix
Hu, Zongliang; Dong, Kai; Dai, Wenlin; Tong, Tiejun
2017-01-01
The determinant of the covariance matrix for high-dimensional data plays an important role in statistical inference and decision. It has many real applications including statistical tests and information theory. Due to the statistical and computational challenges with high dimensionality, little work has been proposed in the literature for estimating the determinant of high-dimensional covariance matrix. In this paper, we estimate the determinant of the covariance matrix using some recent proposals for estimating high-dimensional covariance matrix. Specifically, we consider a total of eight covariance matrix estimation methods for comparison. Through extensive simulation studies, we explore and summarize some interesting comparison results among all compared methods. We also provide practical guidelines based on the sample size, the dimension, and the correlation of the data set for estimating the determinant of high-dimensional covariance matrix. Finally, from a perspective of the loss function, the comparison study in this paper may also serve as a proxy to assess the performance of the covariance matrix estimation.
A Hybrid Semi-Supervised Anomaly Detection Model for High-Dimensional Data
Directory of Open Access Journals (Sweden)
Hongchao Song
2017-01-01
Full Text Available Anomaly detection, which aims to identify observations that deviate from a nominal sample, is a challenging task for high-dimensional data. Traditional distance-based anomaly detection methods compute the neighborhood distance between each observation and suffer from the curse of dimensionality in high-dimensional space; for example, the distances between any pair of samples are similar and each sample may perform like an outlier. In this paper, we propose a hybrid semi-supervised anomaly detection model for high-dimensional data that consists of two parts: a deep autoencoder (DAE and an ensemble k-nearest neighbor graphs- (K-NNG- based anomaly detector. Benefiting from the ability of nonlinear mapping, the DAE is first trained to learn the intrinsic features of a high-dimensional dataset to represent the high-dimensional data in a more compact subspace. Several nonparametric KNN-based anomaly detectors are then built from different subsets that are randomly sampled from the whole dataset. The final prediction is made by all the anomaly detectors. The performance of the proposed method is evaluated on several real-life datasets, and the results confirm that the proposed hybrid model improves the detection accuracy and reduces the computational complexity.
Model-based Clustering of High-Dimensional Data in Astrophysics
Bouveyron, C.
2016-05-01
The nature of data in Astrophysics has changed, as in other scientific fields, in the past decades due to the increase of the measurement capabilities. As a consequence, data are nowadays frequently of high dimensionality and available in mass or stream. Model-based techniques for clustering are popular tools which are renowned for their probabilistic foundations and their flexibility. However, classical model-based techniques show a disappointing behavior in high-dimensional spaces which is mainly due to their dramatical over-parametrization. The recent developments in model-based classification overcome these drawbacks and allow to efficiently classify high-dimensional data, even in the "small n / large p" situation. This work presents a comprehensive review of these recent approaches, including regularization-based techniques, parsimonious modeling, subspace classification methods and classification methods based on variable selection. The use of these model-based methods is also illustrated on real-world classification problems in Astrophysics using R packages.
International Nuclear Information System (INIS)
Zhang, Wuhong; Su, Ming; Wu, Ziwen; Lu, Meng; Huang, Bingwei; Chen, Lixiang
2013-01-01
Twisted photons enable the definition of a Hilbert space beyond two dimensions by orbital angular momentum (OAM) eigenstates. Here we propose a feasible entanglement concentration experiment, to enhance the quality of high-dimensional entanglement shared by twisted photon pairs. Our approach is started from the full characterization of entangled spiral bandwidth, and is then based on the careful selection of the Laguerre–Gaussian (LG) modes with specific radial and azimuthal indices p and ℓ. In particular, we demonstrate the possibility of high-dimensional entanglement concentration residing in the OAM subspace of up to 21 dimensions. By means of LabVIEW simulations with spatial light modulators, we show that the Shannon dimensionality could be employed to quantify the quality of the present concentration. Our scheme holds promise in quantum information applications defined in high-dimensional Hilbert space. (letter)
Detection of Subtle Context-Dependent Model Inaccuracies in High-Dimensional Robot Domains.
Mendoza, Juan Pablo; Simmons, Reid; Veloso, Manuela
2016-12-01
Autonomous robots often rely on models of their sensing and actions for intelligent decision making. However, when operating in unconstrained environments, the complexity of the world makes it infeasible to create models that are accurate in every situation. This article addresses the problem of using potentially large and high-dimensional sets of robot execution data to detect situations in which a robot model is inaccurate-that is, detecting context-dependent model inaccuracies in a high-dimensional context space. To find inaccuracies tractably, the robot conducts an informed search through low-dimensional projections of execution data to find parametric Regions of Inaccurate Modeling (RIMs). Empirical evidence from two robot domains shows that this approach significantly enhances the detection power of existing RIM-detection algorithms in high-dimensional spaces.
Fickler, Robert; Lapkiewicz, Radek; Huber, Marcus; Lavery, Martin P J; Padgett, Miles J; Zeilinger, Anton
2014-07-30
Photonics has become a mature field of quantum information science, where integrated optical circuits offer a way to scale the complexity of the set-up as well as the dimensionality of the quantum state. On photonic chips, paths are the natural way to encode information. To distribute those high-dimensional quantum states over large distances, transverse spatial modes, like orbital angular momentum possessing Laguerre Gauss modes, are favourable as flying information carriers. Here we demonstrate a quantum interface between these two vibrant photonic fields. We create three-dimensional path entanglement between two photons in a nonlinear crystal and use a mode sorter as the quantum interface to transfer the entanglement to the orbital angular momentum degree of freedom. Thus our results show a flexible way to create high-dimensional spatial mode entanglement. Moreover, they pave the way to implement broad complex quantum networks where high-dimensionally entangled states could be distributed over distant photonic chips.
Directory of Open Access Journals (Sweden)
Thenmozhi Srinivasan
2015-01-01
Full Text Available Clusters of high-dimensional data techniques are emerging, according to data noisy and poor quality challenges. This paper has been developed to cluster data using high-dimensional similarity based PCM (SPCM, with ant colony optimization intelligence which is effective in clustering nonspatial data without getting knowledge about cluster number from the user. The PCM becomes similarity based by using mountain method with it. Though this is efficient clustering, it is checked for optimization using ant colony algorithm with swarm intelligence. Thus the scalable clustering technique is obtained and the evaluation results are checked with synthetic datasets.
Reduced basis ANOVA methods for partial differential equations with high-dimensional random inputs
Energy Technology Data Exchange (ETDEWEB)
Liao, Qifeng, E-mail: liaoqf@shanghaitech.edu.cn [School of Information Science and Technology, ShanghaiTech University, Shanghai 200031 (China); Lin, Guang, E-mail: guanglin@purdue.edu [Department of Mathematics & School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907 (United States)
2016-07-15
In this paper we present a reduced basis ANOVA approach for partial deferential equations (PDEs) with random inputs. The ANOVA method combined with stochastic collocation methods provides model reduction in high-dimensional parameter space through decomposing high-dimensional inputs into unions of low-dimensional inputs. In this work, to further reduce the computational cost, we investigate spatial low-rank structures in the ANOVA-collocation method, and develop efficient spatial model reduction techniques using hierarchically generated reduced bases. We present a general mathematical framework of the methodology, validate its accuracy and demonstrate its efficiency with numerical experiments.
The validation and assessment of machine learning: a game of prediction from high-dimensional data
DEFF Research Database (Denmark)
Pers, Tune Hannes; Albrechtsen, A; Holst, C
2009-01-01
In applied statistics, tools from machine learning are popular for analyzing complex and high-dimensional data. However, few theoretical results are available that could guide to the appropriate machine learning tool in a new application. Initial development of an overall strategy thus often...... the ideas, the game is applied to data from the Nugenob Study where the aim is to predict the fat oxidation capacity based on conventional factors and high-dimensional metabolomics data. Three players have chosen to use support vector machines, LASSO, and random forests, respectively....
Directory of Open Access Journals (Sweden)
Khayrullin Rustam Zinnatullovich
2013-08-01
Full Text Available Effective logistics management in vertically integrated oil companies (VIOC is an important factor of business success. Losses caused by irrational logistics management may reach hundreds of millions of rubles a year. Therefore, mathematical simulation of VIOC logistics and methods of optimization of high dimensionality systems represent a relevant problem.The author presents a logistics model for VIOCs and their oil products. The model is based on methods applicable to linear programming problems, algorithms of reduction and restoration of high dimensionality matrixes, and the software developed by ILOG Ltd., a leading developer of applied software components.The software package, developed by the author, solve the problem through the optimization of purchases, production, storage, flow and sales of VIOC oil products, in respect of dozens and even hundreds of small companies of the group. The software package takes account of a big variety of types of contracts between companies, delivery service providers, and storage facilities.This solution may be used to generate a wide range of reports both for VIOC as a whole, and for each VIOC constituent company.The software package has been successfully used for 5 years in respect of logistics, operational and strategic planning of purchases, production, storage, flow and sales of oil products, as well as generation and development of an optimal distribution network.The software was integrated into the corporate resource consumption planning system (ERP System. The assessment of the mathematical simulation is also provided and analyzed in the article.Предложен пакет прикладных программ для решения задач линейного программирования высокой размерности. В основе пакета лежат алгоритмы редуцирования и восстановления матриц высокой р
An irregular grid approach for pricing high-dimensional American options
Berridge, S.J.; Schumacher, J.M.
2008-01-01
We propose and test a new method for pricing American options in a high-dimensional setting. The method is centered around the approximation of the associated complementarity problem on an irregular grid. We approximate the partial differential operator on this grid by appealing to the SDE
Can We Train Machine Learning Methods to Outperform the High-dimensional Propensity Score Algorithm?
Karim, Mohammad Ehsanul; Pang, Menglan; Platt, Robert W
2018-03-01
The use of retrospective health care claims datasets is frequently criticized for the lack of complete information on potential confounders. Utilizing patient's health status-related information from claims datasets as surrogates or proxies for mismeasured and unobserved confounders, the high-dimensional propensity score algorithm enables us to reduce bias. Using a previously published cohort study of postmyocardial infarction statin use (1998-2012), we compare the performance of the algorithm with a number of popular machine learning approaches for confounder selection in high-dimensional covariate spaces: random forest, least absolute shrinkage and selection operator, and elastic net. Our results suggest that, when the data analysis is done with epidemiologic principles in mind, machine learning methods perform as well as the high-dimensional propensity score algorithm. Using a plasmode framework that mimicked the empirical data, we also showed that a hybrid of machine learning and high-dimensional propensity score algorithms generally perform slightly better than both in terms of mean squared error, when a bias-based analysis is used.
CSIR Research Space (South Africa)
Giovannini, D
2013-06-01
Full Text Available : QELS_Fundamental Science, San Jose, California United States, 9-14 June 2013 Reconstruction of High-Dimensional States Entangled in Orbital Angular Momentum Using Mutually Unbiased Measurements D. Giovannini1, ⇤, J. Romero1, 2, J. Leach3, A...
High-Dimensional Intrinsic Interpolation Using Gaussian Process Regression and Diffusion Maps
International Nuclear Information System (INIS)
Thimmisetty, Charanraj A.; Ghanem, Roger G.; White, Joshua A.; Chen, Xiao
2017-01-01
This article considers the challenging task of estimating geologic properties of interest using a suite of proxy measurements. The current work recast this task as a manifold learning problem. In this process, this article introduces a novel regression procedure for intrinsic variables constrained onto a manifold embedded in an ambient space. The procedure is meant to sharpen high-dimensional interpolation by inferring non-linear correlations from the data being interpolated. The proposed approach augments manifold learning procedures with a Gaussian process regression. It first identifies, using diffusion maps, a low-dimensional manifold embedded in an ambient high-dimensional space associated with the data. It relies on the diffusion distance associated with this construction to define a distance function with which the data model is equipped. This distance metric function is then used to compute the correlation structure of a Gaussian process that describes the statistical dependence of quantities of interest in the high-dimensional ambient space. The proposed method is applicable to arbitrarily high-dimensional data sets. Here, it is applied to subsurface characterization using a suite of well log measurements. The predictions obtained in original, principal component, and diffusion space are compared using both qualitative and quantitative metrics. Considerable improvement in the prediction of the geological structural properties is observed with the proposed method.
Ferdosi, Bilkis J.; Buddelmeijer, Hugo; Trager, Scott; Wilkinson, Michael H.F.; Roerdink, Jos B.T.M.
2010-01-01
Data sets in astronomy are growing to enormous sizes. Modern astronomical surveys provide not only image data but also catalogues of millions of objects (stars, galaxies), each object with hundreds of associated parameters. Exploration of this very high-dimensional data space poses a huge challenge.
High-Dimensional Exploratory Item Factor Analysis by a Metropolis-Hastings Robbins-Monro Algorithm
Cai, Li
2010-01-01
A Metropolis-Hastings Robbins-Monro (MH-RM) algorithm for high-dimensional maximum marginal likelihood exploratory item factor analysis is proposed. The sequence of estimates from the MH-RM algorithm converges with probability one to the maximum likelihood solution. Details on the computer implementation of this algorithm are provided. The…
Estimating the effect of a variable in a high-dimensional regression model
DEFF Research Database (Denmark)
Jensen, Peter Sandholt; Wurtz, Allan
assume that the effect is identified in a high-dimensional linear model specified by unconditional moment restrictions. We consider properties of the following methods, which rely on lowdimensional models to infer the effect: Extreme bounds analysis, the minimum t-statistic over models, Sala...
Multi-Scale Factor Analysis of High-Dimensional Brain Signals
Ting, Chee-Ming; Ombao, Hernando; Salleh, Sh-Hussain
2017-01-01
In this paper, we develop an approach to modeling high-dimensional networks with a large number of nodes arranged in a hierarchical and modular structure. We propose a novel multi-scale factor analysis (MSFA) model which partitions the massive
Spectrally-Corrected Estimation for High-Dimensional Markowitz Mean-Variance Optimization
Z. Bai (Zhidong); H. Li (Hua); M.J. McAleer (Michael); W.-K. Wong (Wing-Keung)
2016-01-01
textabstractThis paper considers the portfolio problem for high dimensional data when the dimension and size are both large. We analyze the traditional Markowitz mean-variance (MV) portfolio by large dimension matrix theory, and find the spectral distribution of the sample covariance is the main
Berridge, S.J.; Schumacher, J.M.
2004-01-01
We propose a method for pricing high-dimensional American options on an irregular grid; the method involves using quadratic functions to approximate the local effect of the Black-Scholes operator.Once such an approximation is known, one can solve the pricing problem by time stepping in an explicit
Multigrid for high dimensional elliptic partial differential equations on non-equidistant grids
bin Zubair, H.; Oosterlee, C.E.; Wienands, R.
2006-01-01
This work presents techniques, theory and numbers for multigrid in a general d-dimensional setting. The main focus is the multigrid convergence for high-dimensional partial differential equations (PDEs). As a model problem we have chosen the anisotropic diffusion equation, on a unit hypercube. We
An Irregular Grid Approach for Pricing High-Dimensional American Options
Berridge, S.J.; Schumacher, J.M.
2004-01-01
We propose and test a new method for pricing American options in a high-dimensional setting.The method is centred around the approximation of the associated complementarity problem on an irregular grid.We approximate the partial differential operator on this grid by appealing to the SDE
Pricing and hedging high-dimensional American options : an irregular grid approach
Berridge, S.; Schumacher, H.
2002-01-01
We propose and test a new method for pricing American options in a high dimensional setting. The method is centred around the approximation of the associated variational inequality on an irregular grid. We approximate the partial differential operator on this grid by appealing to the SDE
Evaluation of a new high-dimensional miRNA profiling platform
Directory of Open Access Journals (Sweden)
Lamblin Anne-Francoise
2009-08-01
Full Text Available Abstract Background MicroRNAs (miRNAs are a class of approximately 22 nucleotide long, widely expressed RNA molecules that play important regulatory roles in eukaryotes. To investigate miRNA function, it is essential that methods to quantify their expression levels be available. Methods We evaluated a new miRNA profiling platform that utilizes Illumina's existing robust DASL chemistry as the basis for the assay. Using total RNA from five colon cancer patients and four cell lines, we evaluated the reproducibility of miRNA expression levels across replicates and with varying amounts of input RNA. The beta test version was comprised of 735 miRNA targets of Illumina's miRNA profiling application. Results Reproducibility between sample replicates within a plate was good (Spearman's correlation 0.91 to 0.98 as was the plate-to-plate reproducibility replicates run on different days (Spearman's correlation 0.84 to 0.98. To determine whether quality data could be obtained from a broad range of input RNA, data obtained from amounts ranging from 25 ng to 800 ng were compared to those obtained at 200 ng. No effect across the range of RNA input was observed. Conclusion These results indicate that very small amounts of starting material are sufficient to allow sensitive miRNA profiling using the Illumina miRNA high-dimensional platform. Nonlinear biases were observed between replicates, indicating the need for abundance-dependent normalization. Overall, the performance characteristics of the Illumina miRNA profiling system were excellent.
International Nuclear Information System (INIS)
Tripathy, Rohit; Bilionis, Ilias; Gonzalez, Marcial
2016-01-01
Uncertainty quantification (UQ) tasks, such as model calibration, uncertainty propagation, and optimization under uncertainty, typically require several thousand evaluations of the underlying computer codes. To cope with the cost of simulations, one replaces the real response surface with a cheap surrogate based, e.g., on polynomial chaos expansions, neural networks, support vector machines, or Gaussian processes (GP). However, the number of simulations required to learn a generic multivariate response grows exponentially as the input dimension increases. This curse of dimensionality can only be addressed, if the response exhibits some special structure that can be discovered and exploited. A wide range of physical responses exhibit a special structure known as an active subspace (AS). An AS is a linear manifold of the stochastic space characterized by maximal response variation. The idea is that one should first identify this low dimensional manifold, project the high-dimensional input onto it, and then link the projection to the output. If the dimensionality of the AS is low enough, then learning the link function is a much easier problem than the original problem of learning a high-dimensional function. The classic approach to discovering the AS requires gradient information, a fact that severely limits its applicability. Furthermore, and partly because of its reliance to gradients, it is not able to handle noisy observations. The latter is an essential trait if one wants to be able to propagate uncertainty through stochastic simulators, e.g., through molecular dynamics codes. In this work, we develop a probabilistic version of AS which is gradient-free and robust to observational noise. Our approach relies on a novel Gaussian process regression with built-in dimensionality reduction. In particular, the AS is represented as an orthogonal projection matrix that serves as yet another covariance function hyper-parameter to be estimated from the data. To train the
Tripathy, Rohit; Bilionis, Ilias; Gonzalez, Marcial
2016-09-01
Uncertainty quantification (UQ) tasks, such as model calibration, uncertainty propagation, and optimization under uncertainty, typically require several thousand evaluations of the underlying computer codes. To cope with the cost of simulations, one replaces the real response surface with a cheap surrogate based, e.g., on polynomial chaos expansions, neural networks, support vector machines, or Gaussian processes (GP). However, the number of simulations required to learn a generic multivariate response grows exponentially as the input dimension increases. This curse of dimensionality can only be addressed, if the response exhibits some special structure that can be discovered and exploited. A wide range of physical responses exhibit a special structure known as an active subspace (AS). An AS is a linear manifold of the stochastic space characterized by maximal response variation. The idea is that one should first identify this low dimensional manifold, project the high-dimensional input onto it, and then link the projection to the output. If the dimensionality of the AS is low enough, then learning the link function is a much easier problem than the original problem of learning a high-dimensional function. The classic approach to discovering the AS requires gradient information, a fact that severely limits its applicability. Furthermore, and partly because of its reliance to gradients, it is not able to handle noisy observations. The latter is an essential trait if one wants to be able to propagate uncertainty through stochastic simulators, e.g., through molecular dynamics codes. In this work, we develop a probabilistic version of AS which is gradient-free and robust to observational noise. Our approach relies on a novel Gaussian process regression with built-in dimensionality reduction. In particular, the AS is represented as an orthogonal projection matrix that serves as yet another covariance function hyper-parameter to be estimated from the data. To train the
Energy Technology Data Exchange (ETDEWEB)
Tripathy, Rohit, E-mail: rtripath@purdue.edu; Bilionis, Ilias, E-mail: ibilion@purdue.edu; Gonzalez, Marcial, E-mail: marcial-gonzalez@purdue.edu
2016-09-15
Uncertainty quantification (UQ) tasks, such as model calibration, uncertainty propagation, and optimization under uncertainty, typically require several thousand evaluations of the underlying computer codes. To cope with the cost of simulations, one replaces the real response surface with a cheap surrogate based, e.g., on polynomial chaos expansions, neural networks, support vector machines, or Gaussian processes (GP). However, the number of simulations required to learn a generic multivariate response grows exponentially as the input dimension increases. This curse of dimensionality can only be addressed, if the response exhibits some special structure that can be discovered and exploited. A wide range of physical responses exhibit a special structure known as an active subspace (AS). An AS is a linear manifold of the stochastic space characterized by maximal response variation. The idea is that one should first identify this low dimensional manifold, project the high-dimensional input onto it, and then link the projection to the output. If the dimensionality of the AS is low enough, then learning the link function is a much easier problem than the original problem of learning a high-dimensional function. The classic approach to discovering the AS requires gradient information, a fact that severely limits its applicability. Furthermore, and partly because of its reliance to gradients, it is not able to handle noisy observations. The latter is an essential trait if one wants to be able to propagate uncertainty through stochastic simulators, e.g., through molecular dynamics codes. In this work, we develop a probabilistic version of AS which is gradient-free and robust to observational noise. Our approach relies on a novel Gaussian process regression with built-in dimensionality reduction. In particular, the AS is represented as an orthogonal projection matrix that serves as yet another covariance function hyper-parameter to be estimated from the data. To train the
International Nuclear Information System (INIS)
Liu, W; Sawant, A; Ruan, D
2016-01-01
Purpose: The development of high dimensional imaging systems (e.g. volumetric MRI, CBCT, photogrammetry systems) in image-guided radiotherapy provides important pathways to the ultimate goal of real-time volumetric/surface motion monitoring. This study aims to develop a prediction method for the high dimensional state subject to respiratory motion. Compared to conventional linear dimension reduction based approaches, our method utilizes manifold learning to construct a descriptive feature submanifold, where more efficient and accurate prediction can be performed. Methods: We developed a prediction framework for high-dimensional state subject to respiratory motion. The proposed method performs dimension reduction in a nonlinear setting to permit more descriptive features compared to its linear counterparts (e.g., classic PCA). Specifically, a kernel PCA is used to construct a proper low-dimensional feature manifold, where low-dimensional prediction is performed. A fixed-point iterative pre-image estimation method is applied subsequently to recover the predicted value in the original state space. We evaluated and compared the proposed method with PCA-based method on 200 level-set surfaces reconstructed from surface point clouds captured by the VisionRT system. The prediction accuracy was evaluated with respect to root-mean-squared-error (RMSE) for both 200ms and 600ms lookahead lengths. Results: The proposed method outperformed PCA-based approach with statistically higher prediction accuracy. In one-dimensional feature subspace, our method achieved mean prediction accuracy of 0.86mm and 0.89mm for 200ms and 600ms lookahead lengths respectively, compared to 0.95mm and 1.04mm from PCA-based method. The paired t-tests further demonstrated the statistical significance of the superiority of our method, with p-values of 6.33e-3 and 5.78e-5, respectively. Conclusion: The proposed approach benefits from the descriptiveness of a nonlinear manifold and the prediction
Bit-Table Based Biclustering and Frequent Closed Itemset Mining in High-Dimensional Binary Data
Directory of Open Access Journals (Sweden)
András Király
2014-01-01
Full Text Available During the last decade various algorithms have been developed and proposed for discovering overlapping clusters in high-dimensional data. The two most prominent application fields in this research, proposed independently, are frequent itemset mining (developed for market basket data and biclustering (applied to gene expression data analysis. The common limitation of both methodologies is the limited applicability for very large binary data sets. In this paper we propose a novel and efficient method to find both frequent closed itemsets and biclusters in high-dimensional binary data. The method is based on simple but very powerful matrix and vector multiplication approaches that ensure that all patterns can be discovered in a fast manner. The proposed algorithm has been implemented in the commonly used MATLAB environment and freely available for researchers.
Characterization of discontinuities in high-dimensional stochastic problems on adaptive sparse grids
International Nuclear Information System (INIS)
Jakeman, John D.; Archibald, Richard; Xiu Dongbin
2011-01-01
In this paper we present a set of efficient algorithms for detection and identification of discontinuities in high dimensional space. The method is based on extension of polynomial annihilation for discontinuity detection in low dimensions. Compared to the earlier work, the present method poses significant improvements for high dimensional problems. The core of the algorithms relies on adaptive refinement of sparse grids. It is demonstrated that in the commonly encountered cases where a discontinuity resides on a small subset of the dimensions, the present method becomes 'optimal', in the sense that the total number of points required for function evaluations depends linearly on the dimensionality of the space. The details of the algorithms will be presented and various numerical examples are utilized to demonstrate the efficacy of the method.
Non-intrusive low-rank separated approximation of high-dimensional stochastic models
Doostan, Alireza; Validi, AbdoulAhad; Iaccarino, Gianluca
2013-01-01
This work proposes a sampling-based (non-intrusive) approach within the context of low-. rank separated representations to tackle the issue of curse-of-dimensionality associated with the solution of models, e.g., PDEs/ODEs, with high-dimensional random inputs. Under some conditions discussed in details, the number of random realizations of the solution, required for a successful approximation, grows linearly with respect to the number of random inputs. The construction of the separated representation is achieved via a regularized alternating least-squares regression, together with an error indicator to estimate model parameters. The computational complexity of such a construction is quadratic in the number of random inputs. The performance of the method is investigated through its application to three numerical examples including two ODE problems with high-dimensional random inputs. © 2013 Elsevier B.V.
Non-intrusive low-rank separated approximation of high-dimensional stochastic models
Doostan, Alireza
2013-08-01
This work proposes a sampling-based (non-intrusive) approach within the context of low-. rank separated representations to tackle the issue of curse-of-dimensionality associated with the solution of models, e.g., PDEs/ODEs, with high-dimensional random inputs. Under some conditions discussed in details, the number of random realizations of the solution, required for a successful approximation, grows linearly with respect to the number of random inputs. The construction of the separated representation is achieved via a regularized alternating least-squares regression, together with an error indicator to estimate model parameters. The computational complexity of such a construction is quadratic in the number of random inputs. The performance of the method is investigated through its application to three numerical examples including two ODE problems with high-dimensional random inputs. © 2013 Elsevier B.V.
Statistical Analysis for High-Dimensional Data : The Abel Symposium 2014
Bühlmann, Peter; Glad, Ingrid; Langaas, Mette; Richardson, Sylvia; Vannucci, Marina
2016-01-01
This book features research contributions from The Abel Symposium on Statistical Analysis for High Dimensional Data, held in Nyvågar, Lofoten, Norway, in May 2014. The focus of the symposium was on statistical and machine learning methodologies specifically developed for inference in “big data” situations, with particular reference to genomic applications. The contributors, who are among the most prominent researchers on the theory of statistics for high dimensional inference, present new theories and methods, as well as challenging applications and computational solutions. Specific themes include, among others, variable selection and screening, penalised regression, sparsity, thresholding, low dimensional structures, computational challenges, non-convex situations, learning graphical models, sparse covariance and precision matrices, semi- and non-parametric formulations, multiple testing, classification, factor models, clustering, and preselection. Highlighting cutting-edge research and casting light on...
Su, Yapeng; Shi, Qihui; Wei, Wei
2017-02-01
New insights on cellular heterogeneity in the last decade provoke the development of a variety of single cell omics tools at a lightning pace. The resultant high-dimensional single cell data generated by these tools require new theoretical approaches and analytical algorithms for effective visualization and interpretation. In this review, we briefly survey the state-of-the-art single cell proteomic tools with a particular focus on data acquisition and quantification, followed by an elaboration of a number of statistical and computational approaches developed to date for dissecting the high-dimensional single cell data. The underlying assumptions, unique features, and limitations of the analytical methods with the designated biological questions they seek to answer will be discussed. Particular attention will be given to those information theoretical approaches that are anchored in a set of first principles of physics and can yield detailed (and often surprising) predictions. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Minimax Rate-optimal Estimation of High-dimensional Covariance Matrices with Incomplete Data.
Cai, T Tony; Zhang, Anru
2016-09-01
Missing data occur frequently in a wide range of applications. In this paper, we consider estimation of high-dimensional covariance matrices in the presence of missing observations under a general missing completely at random model in the sense that the missingness is not dependent on the values of the data. Based on incomplete data, estimators for bandable and sparse covariance matrices are proposed and their theoretical and numerical properties are investigated. Minimax rates of convergence are established under the spectral norm loss and the proposed estimators are shown to be rate-optimal under mild regularity conditions. Simulation studies demonstrate that the estimators perform well numerically. The methods are also illustrated through an application to data from four ovarian cancer studies. The key technical tools developed in this paper are of independent interest and potentially useful for a range of related problems in high-dimensional statistical inference with missing data.
Minimax Rate-optimal Estimation of High-dimensional Covariance Matrices with Incomplete Data*
Cai, T. Tony; Zhang, Anru
2016-01-01
Missing data occur frequently in a wide range of applications. In this paper, we consider estimation of high-dimensional covariance matrices in the presence of missing observations under a general missing completely at random model in the sense that the missingness is not dependent on the values of the data. Based on incomplete data, estimators for bandable and sparse covariance matrices are proposed and their theoretical and numerical properties are investigated. Minimax rates of convergence are established under the spectral norm loss and the proposed estimators are shown to be rate-optimal under mild regularity conditions. Simulation studies demonstrate that the estimators perform well numerically. The methods are also illustrated through an application to data from four ovarian cancer studies. The key technical tools developed in this paper are of independent interest and potentially useful for a range of related problems in high-dimensional statistical inference with missing data. PMID:27777471
Xu, Chao; Fang, Jian; Shen, Hui; Wang, Yu-Ping; Deng, Hong-Wen
2018-01-25
Extreme phenotype sampling (EPS) is a broadly-used design to identify candidate genetic factors contributing to the variation of quantitative traits. By enriching the signals in extreme phenotypic samples, EPS can boost the association power compared to random sampling. Most existing statistical methods for EPS examine the genetic factors individually, despite many quantitative traits have multiple genetic factors underlying their variation. It is desirable to model the joint effects of genetic factors, which may increase the power and identify novel quantitative trait loci under EPS. The joint analysis of genetic data in high-dimensional situations requires specialized techniques, e.g., the least absolute shrinkage and selection operator (LASSO). Although there are extensive research and application related to LASSO, the statistical inference and testing for the sparse model under EPS remain unknown. We propose a novel sparse model (EPS-LASSO) with hypothesis test for high-dimensional regression under EPS based on a decorrelated score function. The comprehensive simulation shows EPS-LASSO outperforms existing methods with stable type I error and FDR control. EPS-LASSO can provide a consistent power for both low- and high-dimensional situations compared with the other methods dealing with high-dimensional situations. The power of EPS-LASSO is close to other low-dimensional methods when the causal effect sizes are small and is superior when the effects are large. Applying EPS-LASSO to a transcriptome-wide gene expression study for obesity reveals 10 significant body mass index associated genes. Our results indicate that EPS-LASSO is an effective method for EPS data analysis, which can account for correlated predictors. The source code is available at https://github.com/xu1912/EPSLASSO. hdeng2@tulane.edu. Supplementary data are available at Bioinformatics online. © The Author (2018). Published by Oxford University Press. All rights reserved. For Permissions, please
An Unbiased Distance-based Outlier Detection Approach for High-dimensional Data
DEFF Research Database (Denmark)
Nguyen, Hoang Vu; Gopalkrishnan, Vivekanand; Assent, Ira
2011-01-01
than a global property. Different from existing approaches, it is not grid-based and dimensionality unbiased. Thus, its performance is impervious to grid resolution as well as the curse of dimensionality. In addition, our approach ranks the outliers, allowing users to select the number of desired...... outliers, thus mitigating the issue of high false alarm rate. Extensive empirical studies on real datasets show that our approach efficiently and effectively detects outliers, even in high-dimensional spaces....
A Comparison of Machine Learning Methods in a High-Dimensional Classification Problem
Zekić-Sušac, Marijana; Pfeifer, Sanja; Šarlija, Nataša
2014-01-01
Background: Large-dimensional data modelling often relies on variable reduction methods in the pre-processing and in the post-processing stage. However, such a reduction usually provides less information and yields a lower accuracy of the model. Objectives: The aim of this paper is to assess the high-dimensional classification problem of recognizing entrepreneurial intentions of students by machine learning methods. Methods/Approach: Four methods were tested: artificial neural networks, CART ...