Naeem, Huma; Hussain, Mukhtar; Khan, Shoab A
2009-01-01
Surveillance control and reporting (SCR) system for air threats play an important role in the defense of a country. SCR system corresponds to air and ground situation management/processing along with information fusion, communication, coordination, simulation and other critical defense oriented tasks. Threat Evaluation and Weapon Assignment (TEWA) sits at the core of SCR system. In such a system, maximal or near maximal utilization of constrained resources is of extreme importance. Manual TEWA systems cannot provide optimality because of different limitations e.g.surface to air missile (SAM) can fire from a distance of 5Km, but manual TEWA systems are constrained by human vision range and other constraints. Current TEWA systems usually work on target-by-target basis using some type of greedy algorithm thus affecting the optimality of the solution and failing in multi-target scenario. his paper relates to a novel two-staged flexible dynamic decision support based optimal threat evaluation and weapon assignment...
Weekly Fleet Assignment Model and Algorithm
Institute of Scientific and Technical Information of China (English)
ZHU Xing-hui; ZHU Jin-fu; GONG Zai-wu
2007-01-01
A 0-1 integer programming model for weekly fleet assignment was put forward based on linear network and weekly flight scheduling in China. In this model, the objective function is to maximize the total profit of fleet assignment, subject to the constraints of coverage, aircraft flow balance, fleet size, aircraft availability, aircraft usage, flight restriction, aircraft seat capacity,and stopover. Then the branch-and-bound algorithm based on special ordered set was applied to solve the model. At last, a realworld case study on an airline with 5 fleets, 48 aircrafts and 1 786 flight legs indicated that the profit increase was $1591276 one week and the running time was no more than 4 min, which shows that the model and algorithm are fairly good for domestic airline.
Colony location algorithm for assignment problems
Institute of Scientific and Technical Information of China (English)
Dingwei WANG
2004-01-01
A novel algorithm called Colony Location Algorithm (CLA) is proposed. It mimics the phenomena in biotic conmunity that colonies of species could be located in the places most suitable to their growth. The factors working on the species location such as the nutrient of soil, resource competition between species, growth and decline process, and effect on environment were considered in CLA via the nutrient function, growth and decline rates, environment evaluation and fertilization strategy.CLA was applied to solve the classical assignment problems. The computation results show that CLA can achieve the optimal solution with higher possibility and shorter running time.
An Improved Point-track Optimal Assignment Algorithm
Zhonglei Zhang; Weihua Zhang; Li Zhou
2013-01-01
In order to improve the accuracy of data association of the Optimal Assignment (OA) algorithm based on dynamic information, an improved Point-Track Optimal Assignment (IPTOA) algorithm based on multi-source information is proposed. The improved algorithm gets valid 3-tuple of measurement set by solving 3-Dimensional (3-D) assignment problem which is based on dynamic information. Then fuses multi-source information by combination rule of D-S evidence theory and constructs the point-track corre...
An eigenvalue/eigenvector assignment algorithm using output feedback
Mielke, R. R.; Liberty, S. R.
1983-01-01
An eigenvalue/eigenvector assignment algorithm using stationary output feedback is presented. The algorithm permits assignment of min (n, m + r - 1) eigenvalues and max (m-1, r-1) eigenvectors, where n, m, r refer to the system state, input and output dimensions, respectively. An example is given to illustrate the design procedures.
An efficient and impartial online algorithm for kidney assignment network
Institute of Scientific and Technical Information of China (English)
无
2009-01-01
An online algorithm balancing the efficiency and equity principles is proposed for the kidney resource assignment when only the current patient and resource information is known to the assignment network. In the algorithm, the assignment is made according to the priority, which is calculated according to the efficiency principle and the equity principle. The efficiency principle is concerned with the post-transplantation immunity spending caused by the possible post-operation immunity rejection and patient’...
An Improved Point-track Optimal Assignment Algorithm
Directory of Open Access Journals (Sweden)
Zhonglei Zhang
2013-12-01
Full Text Available In order to improve the accuracy of data association of the Optimal Assignment (OA algorithm based on dynamic information, an improved Point-Track Optimal Assignment (IPTOA algorithm based on multi-source information is proposed. The improved algorithm gets valid 3-tuple of measurement set by solving 3-Dimensional (3-D assignment problem which is based on dynamic information. Then fuses multi-source information by combination rule of D-S evidence theory and constructs the point-track correlation matrix between valid 3-tuple of measurement and target track. Compared with the optimal assignment algorithm based on dynamic information, the new algorithm effectively fuses multi-source information to correlate measurement data, which improves the performance of multi-target tracking in different degrees. Simulation results verify the feasibility and effectiveness of the new algorithm.
Localized Algorithm for Channel Assignment in Cognitive Radio Networks
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Harpreet Kaur
2015-12-01
Full Text Available Cognitive Radio has been emerged as a revolutionary solution to migrate the current shortage of spectrum allocation in wireless networks. In this paper, an improved localized channel allocation algorithm based on channel weight is proposed. A factor of channel stability is introduced based on link environment, which efficiently assigns the best channels to the links. Based on the framework, a conflict resolution strategy is used to make the scheme adaptable to different network conditions. Calculations indicate that this algorithm can reduce the conflicts, increase the delivery rate and link assignment rate compared with the basic channel assignment algorithm.
Solving the Quadratic Assignment Problem by a Hybrid Algorithm
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Aldy Gunawan
2011-01-01
Full Text Available This paper presents a hybrid algorithm to solve the Quadratic Assignment Problem (QAP. The proposed algorithm involves using the Greedy Randomized Adaptive Search Procedure (GRASP to obtain an initial solution, and then using a combined Simulated Annealing (SA and Tabu Search (TS algorithm to improve the solution. Experimental results indicate that the hybrid algorithm is able to obtain good quality solutions for QAPLIB test problems within reasonable computation time.
A New Secondary Structure Assignment Algorithm Using Cα Backbone Fragments.
Cao, Chen; Wang, Guishen; Liu, An; Xu, Shutan; Wang, Lincong; Zou, Shuxue
2016-01-01
The assignment of secondary structure elements in proteins is a key step in the analysis of their structures and functions. We have developed an algorithm, SACF (secondary structure assignment based on Cα fragments), for secondary structure element (SSE) assignment based on the alignment of Cα backbone fragments with central poses derived by clustering known SSE fragments. The assignment algorithm consists of three steps: First, the outlier fragments on known SSEs are detected. Next, the remaining fragments are clustered to obtain the central fragments for each cluster. Finally, the central fragments are used as a template to make assignments. Following a large-scale comparison of 11 secondary structure assignment methods, SACF, KAKSI and PROSS are found to have similar agreement with DSSP, while PCASSO agrees with DSSP best. SACF and PCASSO show preference to reducing residues in N and C cap regions, whereas KAKSI, P-SEA and SEGNO tend to add residues to the terminals when DSSP assignment is taken as standard. Moreover, our algorithm is able to assign subtle helices (310-helix, π-helix and left-handed helix) and make uniform assignments, as well as to detect rare SSEs in β-sheets or long helices as outlier fragments from other programs. The structural uniformity should be useful for protein structure classification and prediction, while outlier fragments underlie the structure-function relationship. PMID:26978354
Ant Colony Algorithm and Simulation for Robust Airport Gate Assignment
Directory of Open Access Journals (Sweden)
Hui Zhao
2014-01-01
Full Text Available Airport gate assignment is core task for airport ground operations. Due to the fact that the departure and arrival time of flights may be influenced by many random factors, the airport gate assignment scheme may encounter gate conflict and many other problems. This paper aims at finding a robust solution for airport gate assignment problem. A mixed integer model is proposed to formulate the problem, and colony algorithm is designed to solve this model. Simulation result shows that, in consideration of robustness, the ability of antidisturbance for airport gate assignment scheme has much improved.
An efficient and impartial online algorithm for kidney assignment network
Institute of Scientific and Technical Information of China (English)
Yu-jue Wang; Jia-yin Wang; Pei-jia Tang; Yi-tuo Ye
2009-01-01
An online algorithm balancing the efficiency and equity principles is proposed for the kidney resource assignment when only the current patient and resource information is known to the assignment network. In the algorithm, the assignment is made according to the priority, which is calculated according to the efficiency principle and the equity principle. The efficiency principle is concerned with the post-transplantation- immunity spending caused by the possible post-operation immunity rejection and patient's mental depression due to the HLA mismatch. The equity principle is concerned with three other factors, namely the treatment spending incurred starting from the day of registering with the kidney assignment network, the post-operation immunity spending and the negative effects of waiting for kidney resources on the clinical efficiency. The competitive analysis conducted through computer simulation indicates that the efficiency competitive ratio is between 6. 29 and 10. 43 and the equity competitive ratio is between 1. 31 and 5. 21, demonstrating that the online algorithm is of great significance in application.
Algorithms for selecting informative marker panels for population assignment.
Rosenberg, Noah A
2005-11-01
Given a set of potential source populations, genotypes of an individual of unknown origin at a collection of markers can be used to predict the correct source population of the individual. For improved efficiency, informative markers can be chosen from a larger set of markers to maximize the accuracy of this prediction. However, selecting the loci that are individually most informative does not necessarily produce the optimal panel. Here, using genotypes from eight species--carp, cat, chicken, dog, fly, grayling, human, and maize--this univariate accumulation procedure is compared to new multivariate "greedy" and "maximin" algorithms for choosing marker panels. The procedures generally suggest similar panels, although the greedy method often recommends inclusion of loci that are not chosen by the other algorithms. In seven of the eight species, when applied to five or more markers, all methods achieve at least 94% assignment accuracy on simulated individuals, with one species--dog--producing this level of accuracy with only three markers, and the eighth species--human--requiring approximately 13-16 markers. The new algorithms produce substantial improvements over use of randomly selected markers; where differences among the methods are noticeable, the greedy algorithm leads to slightly higher probabilities of correct assignment. Although none of the approaches necessarily chooses the panel with optimal performance, the algorithms all likely select panels with performance near enough to the maximum that they all are suitable for practical use. PMID:16305328
Dynamic Routing and Resource Assignment Algorithm In sloted optical Networks
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Bisheng Quan
2013-04-01
Full Text Available All-optical wavelength division multiplexing networks are the most promising candidate for the next generation wideband backbone networks. To improve the utilization of wavelength, time division multiplexing technology is introduced. The routing, wavelength and time-slots assignment problem was studied in such time-space switched networks. Two new dynamic algorithms were proposed which distribute slots of the session request on multiple different wavelengths of single fiber separately based on fixed alternate routing and adaptive routing policy. Especially in LLR-MWLB algorithm, network link weights adjust adaptively with the available time slots of each link and load balancing strategy is adopted. The effectiveness of the proposed algorithms is demonstrated by simulations and results show the better performance.
CAD Model Retrieval Based on Graduated Assignment Algorithm
Tao, Songqiao
2015-06-01
A retrieval approach for CAD models based on graduated assignment algorithm is proposed in this paper. First, CAD models are transformed into face adjacency graphs (FAGs). Second, the vertex compatibility matrix and edge compatibility matrix between the FAGs of the query and data models are calculated, and the similarity metric for the two comparison models is established from their compatibility matrices, which serves as the optimization objective function for selecting vertex mapping matrix M between the two comparison models. Finally, Sinkhorn's alternative normalization approach for M's rows and columns is adopted to find the optimal vertex mapping matrix M. Experimental results have shown that the proposed approach supports CAD model retrieval.
Study on Fleet Assignment Problem Model and Algorithm
Directory of Open Access Journals (Sweden)
Yaohua Li
2013-01-01
Full Text Available The Fleet Assignment Problem (FAP of aircraft scheduling in airlines is studied, and the optimization model of FAP is proposed. The objective function of this model is revenue maximization, and it considers comprehensively the difference of scheduled flights and aircraft models in flight areas and mean passenger flows. In order to solve the model, a self-adapting genetic algorithm is supposed to solve the model, which uses natural number coding, adjusts dynamically crossover and mutation operator probability, and adopts intelligent heuristic adjusting to quicken optimization pace. The simulation with production data of an airline shows that the model and algorithms suggested in this paper are feasible and have a good application value.
Some recent results in the analysis of greedy algorithms for assignment problems
Faigle, Ulrich
1994-01-01
We survey some recent developments in the analysis of greedy algorithms for assignment and transportation problems. We focus on the linear programming model for matroids and linear assignment problems with Monge property, on general linear programs, probabilistic analysis for linear assignment and makespan minimization, and on-line algorithms for linear and non-linear assignment problems.
Locomotive assignment problem with train precedence using genetic algorithm
Noori, Siamak; Ghannadpour, Seyed
2012-01-01
This paper aims to study the locomotive assignment problem which is very important for railway companies, in view of high cost of operating locomotives. This problem is to determine the minimum cost assignment of homogeneous locomotives located in some central depots to a set of pre-scheduled trains in order to provide sufficient power to pull the trains from their origins to their destinations. These trains have different degrees of priority for servicing, and the high class of trains should...
Institute of Scientific and Technical Information of China (English)
ZHAO Hui; GAO Ziyou
2005-01-01
This paper presents a unified framework of the nonmonotone convex combination algorithms (such as Frank-Wolfe Algorithm) for solving the traffic assignment problems. Global convergence results are established under mild conditions. The line search procedure used in our algorithm includes the nonmonotone Armijo rule, the nonmonotone Goldstein rule and the nonmonotone Wolfe rule as special cases. So, the new algorithm can be viewed as a generalization of the regular convex combination algorithm.
Inventory Management with Asset-Based Financing
John A. Buzacott; Rachel Q. Zhang
2004-01-01
Most of the traditional models in production and inventory control ignore the financial states of an organization and can lead to infeasible practices in real systems. This paper is the first attempt to incorporate asset-based financing into production decisions. Instead of setting a known, exogenously determined budgetary constraint as most existing models suggest, we model the available cash in each period as a function of assets and liabilities that may be updated periodically according to...
Channel Assignment Algorithms for MRMC Wireless Mesh Networks
Directory of Open Access Journals (Sweden)
Mohammad A Hoque
2011-11-01
Full Text Available The wireless mesh networksare considered as one of the vital elements in today’s converged networks,providing high bandwidth and connectivity over large geographical areas. Mesh routers equipped with multiple radios can significantly overcome the capacity problem and increase the aggregate throughput of the network where single radio nodessuffer from performancedegradation. Moreover, the market availability of cheap radios or network interfaces also makes multi-radio solutions more feasible.A key issue in such networks is how to efficiently design a channel assignmentscheme that utilizes the available channels as well as increases overall performance of the network. This paper provides an overall review on the issues pertaining to the channel assignment in WMNs and the most relevant approaches and solutions developed in the area. They include design challenges, goals and criteria; routing considerations, graph based solutions and challenges of partially overlapped channels. We conclude that the assignment of channels to the radio interfaces continuously poses significant challenges. Many research issues remain open for further investigation.
Directory of Open Access Journals (Sweden)
Avtar Singh Buttar
2013-03-01
Full Text Available The Frequency Assignment Problem is assignment of frequencies or channels to establish link between base station and mobile transmitter in cellular system. To avoid interference, minimum separation between assigned frequencies is required. This problem is NP-hard. Due to limited availability of spectrum and reuse of same frequencies at different geographical locations, an excellent assignment is to be done, which must satisfy electromagnetic constraints with respect to demand in each cell. This paper presents a novel DGWCHD algorithm for frequency assignment problem in cellular radio networks. The objective is to assign the frequency satisfying electromagnetic constraints for given demand with minimum use of frequency bandwidth. The proposed algorithm is based on real wild animal such as dog’s intelligent strategies during chasing and hunting their prey. The proposed algorithm is implemented on benchmark Kunz’s test problems, which are practical FAP problems based on area around 25 regions in Helsinki, Finland. The DGWCHD algorithm has been used for call ordering and FEA strategy for assignment. The performance of the proposed novel DGWCHD algorithm has been compared with other nature inspired techniques. The results obtained are very optimistic and encouraging
Zhu, Liuhong; Guo, Gang
2012-01-01
This study tested an improved fiber tracking algorithm, which was based on fiber assignment using a continuous tracking algorithm and a two-tensor model. Different models and tracking decisions were used by judging the type of estimation of each voxel. This method should solve the cross-track problem. This study included eight healthy subjects, two axonal injury patients and seven demyelinating disease patients. This new algorithm clearly exhibited a difference in nerve fiber direction betwee...
Heuristic file sorted assignment algorithm of parallel I/O on cluster computing system
Institute of Scientific and Technical Information of China (English)
CHEN Zhi-gang; ZENG Bi-qing; XIONG Ce; DENG Xiao-heng; ZENG Zhi-wen; LIU An-feng
2005-01-01
A new file assignment strategy of parallel I/O, which is named heuristic file sorted assignment algorithm was proposed on cluster computing system. Based on the load balancing, it assigns the files to the same disk according to the similar service time. Firstly, the files were sorted and stored at the set I in descending order in terms of their service time, then one disk of cluster node was selected randomly when the files were to be assigned, and at last the continuous files were taken orderly from the set I to the disk until the disk reached its load maximum. The experimental results show that the new strategy improves the performance by 20.2% when the load of the system is light and by 31.6% when the load is heavy. And the higher the data access rate, the more evident the improvement of the performance obtained by the heuristic file sorted assignment algorithm.
A Novel Dynamic Bandwidth Assignment Algorithm for Multi-Services EPONs
Institute of Scientific and Technical Information of China (English)
CHEN Xue; ZHANG Yang; HUANG Xiang; DENG Yu; SUN Shu-he
2005-01-01
In this paper we propose a novel Dynamic Bandwidth Assignment (DBA) algorithm for Ethernet-based Passive Optical Networks (EPON) which offers multiple kinds of services. To satisfy crucial Quality of Service (QoS) requirement for Time Division Multiplexing (TDM) service and achieve fair and high bandwidth utilization simultaneously, the algorithm integrates periodic, for TDM service, and polling granting for Ethernet service. Detailed simulation shows that the algorithm guarantees carrier-grade QoS for TDM service, high bandwidth utilization and good fairness of bandwidth assignment among Optical Network Units (ONU).
Institute of Scientific and Technical Information of China (English)
Wang Yanxia; Qian Longjun; Guo Zhi; Ma Lifeng
2008-01-01
A weapon target assignment (WTA) model satisfying expected damage probabilities with an ant colony algorithm is proposed.In order to save armament resource and attack the targets effectively,the strategy of the weapon assignment is that the target with greater threat degree has higher priority to be intercepted.The effect of this WTA model is not maximizing the damage probability but satisfying the whole assignment result.Ant colony algorithm has been successfully used in many fields,especially in combination optimization.The ant colony algorithm for this WTA problem is described by analyzing path selection,pheromone update,and tabu table update.The effectiveness of the model and the algorithm is demonstrated with an example.
Russomanno, David J.; Joseph Qualls
2011-01-01
The lack of knowledge models to represent sensor systems, algorithms, and missions makes opportunistically discovering a synthesis of systems and algorithms that can satisfy high-level mission specifications impractical. A novel ontological problem-solving framework has been designed that leverages knowledge models describing sensors, algorithms, and high-level missions to facilitate automated inference of assigning systems to subtasks that may satisfy a given mission specification. To demons...
A Comparative Study of Meta-heuristic Algorithms for Solving Quadratic Assignment Problem
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Gamal Abd El-Nasser A. Said
2014-01-01
Full Text Available Quadratic Assignment Problem (QAP is an NP-hard combinatorial optimization problem, therefore, solving the QAP requires applying one or more of the meta-heuristic algorithms. This paper presents a comparative study between Meta-heuristic algorithms: Genetic Algorithm, Tabu Search, and Simulated annealing for solving a real-life (QAP and analyze their performance in terms of both runtime efficiency and solution quality. The results show that Genetic Algorithm has a better solution quality while Tabu Search has a faster execution time in comparison with other Meta-heuristic algorithms for solving QAP.
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
Routing and wavelength assignment for online real-time multicast connection setup is a difficulttask due to the dynamic change of availabilities of wavelengths on links and the consideration of wave-length conversion delay in WDM networks. This paper presents a distributed routing and wavelength as-signment scheme for the setup of real-time multicast connections. It integrates routing and wavelength as-signment as a single process, which greatly reduces the connection setup time. The proposed routingmethod is based on the Prim's MST (Minimum Spanning Tree) algorithm and the K-restricted breadth-first search method, which can produce a sub-minimal cost tree under a given delay bound. The wave-length assignment uses the least-conversion and load balancing strategies. Simulation results show that theproposed algorithm is suitable for online multicast connection establishment in WDM networks.
Institute of Scientific and Technical Information of China (English)
Liuhong Zhu; Gang Guo
2012-01-01
This study tested an improved fiber tracking algorithm, which was based on fiber assignment using a continuous tracking algorithm and a two-tensor model. Different models and tracking decisions were used by judging the type of estimation of each voxel. This method should solve the cross-track problem. This study included eight healthy subjects, two axonal injury patients and seven demyelinating disease patients. This new algorithm clearly exhibited a difference in nerve fiber direction between axonal injury and demyelinating disease patients and healthy control subjects. Compared with fiber assignment with a continuous tracking algorithm, our novel method can track more and longer nerve fibers, and also can solve the fiber crossing problem.
Wang, Zhaocai; Pu, Jun; Cao, Liling; Tan, Jian
2015-01-01
The unbalanced assignment problem (UAP) is to optimally resolve the problem of assigning n jobs to m individuals (m parallel DNA algorithm for solving the unbalanced assignment problem using DNA molecular operations. We reasonably design flexible-length DNA strands representing different jobs and individuals, take appropriate steps, and get the solutions of the UAP in the proper length range and O(mn) time. We extend the application of DNA molecular operations and simultaneity to simplify the complexity of the computation. PMID:26512650
Simulated annealing algorithm for solving chambering student-case assignment problem
Ghazali, Saadiah; Abdul-Rahman, Syariza
2015-12-01
The problem related to project assignment problem is one of popular practical problem that appear nowadays. The challenge of solving the problem raise whenever the complexity related to preferences, the existence of real-world constraints and problem size increased. This study focuses on solving a chambering student-case assignment problem by using a simulated annealing algorithm where this problem is classified under project assignment problem. The project assignment problem is considered as hard combinatorial optimization problem and solving it using a metaheuristic approach is an advantage because it could return a good solution in a reasonable time. The problem of assigning chambering students to cases has never been addressed in the literature before. For the proposed problem, it is essential for law graduates to peruse in chambers before they are qualified to become legal counselor. Thus, assigning the chambering students to cases is a critically needed especially when involving many preferences. Hence, this study presents a preliminary study of the proposed project assignment problem. The objective of the study is to minimize the total completion time for all students in solving the given cases. This study employed a minimum cost greedy heuristic in order to construct a feasible initial solution. The search then is preceded with a simulated annealing algorithm for further improvement of solution quality. The analysis of the obtained result has shown that the proposed simulated annealing algorithm has greatly improved the solution constructed by the minimum cost greedy heuristic. Hence, this research has demonstrated the advantages of solving project assignment problem by using metaheuristic techniques.
Directory of Open Access Journals (Sweden)
Chi-Jen Lin
2015-11-01
Full Text Available This study constructs a practical fuzzy three-dimensional axial assignment model, and proposes two efficient algorithms to solve the model. In our case, the model is applied to team performance management in a company to promote the performance of all members in a team. Two algorithms, namely the index-based branch and bound (B&B algorithm and the f-g trade-off algorithm, which is a hybrid of the trade-off and B&B concepts, are proposed. A numerical example is presented to illustrate these two algorithms. The computational results show that the proposed algorithms are sufficiently efficient and accurate. Two special cases are also discussed.
A fuzzy logic algorithm to assign confidence levels to heart and respiratory rate time series
International Nuclear Information System (INIS)
We have developed a fuzzy logic-based algorithm to qualify the reliability of heart rate (HR) and respiratory rate (RR) vital-sign time-series data by assigning a confidence level to the data points while they are measured as a continuous data stream. The algorithm's membership functions are derived from physiology-based performance limits and mass-assignment-based data-driven characteristics of the signals. The assigned confidence levels are based on the reliability of each HR and RR measurement as well as the relationship between them. The algorithm was tested on HR and RR data collected from subjects undertaking a range of physical activities, and it showed acceptable performance in detecting four types of faults that result in low-confidence data points (receiver operating characteristic areas under the curve ranged from 0.67 (SD 0.04) to 0.83 (SD 0.03), mean and standard deviation (SD) over all faults). The algorithm is sensitive to noise in the raw HR and RR data and will flag many data points as low confidence if the data are noisy; prior processing of the data to reduce noise allows identification of only the most substantial faults. Depending on how HR and RR data are processed, the algorithm can be applied as a tool to evaluate sensor performance or to qualify HR and RR time-series data in terms of their reliability before use in automated decision-assist systems
AN EVOLUTIONARY ALGORITHM FOR CHANNEL ASSIGNMENT PROBLEM IN WIRELESS MOBILE NETWORKS
Directory of Open Access Journals (Sweden)
Yee Shin Chia
2012-12-01
Full Text Available The channel assignment problem in wireless mobile network is the assignment of appropriate frequency spectrum to incoming calls while maintaining a satisfactory level of electromagnetic compatibility (EMC constraints. An effective channel assignment strategy is important due to the limited capacity of frequency spectrum in wireless mobile network. Most of the existing channel assignment strategies are based on deterministic methods. In this paper, an adaptive genetic algorithm (GA based channel assignment strategy is introduced for resource management and to reduce the effect of EMC interferences. The most significant advantage of the proposed optimization method is its capability to handle both the reassignment of channels for existing calls as well as the allocation of channel to a new incoming call in an adaptive process to maximize the utility of the limited resources. It is capable to adapt the population size to the number of eligible channels for a particular cell upon new call arrivals to achieve reasonable convergence speed. The MATLAB simulation on a 49-cells network model for both uniform and nonuniform call traffic distributions showed that the proposed channel optimization method can always achieve a lower average new incoming call blocking probability compared to the deterministic based channel assignment strategy.
Institute of Scientific and Technical Information of China (English)
TIAN Ye; SHENG Min; LI Jiandong
2007-01-01
This Paper presents a novel distributed media access control(MAC)address assignment algorithm,namely virtual grid spatial reusing(VGSR),for wireless sensor networks,which reduces the size of the MAC address efficiently on the basis of both the spatial reuse of MAC address and the mapping of geographical position.By adjusting the communication range of sensor nodes,VGSR algorithm can minimize the size of MAC address and meanwhile guarantee the connectivity of the sensor network.Theoretical analysis and experimental results show that VGSR algorithm is not only of low energy cost,but also scales well with the network ize,with its performance superior to that of other existing algorithms.
Lee, Chankyun; Cao, Xiaoyuan; Yoshikane, Noboru; Tsuritani, Takehiro; Rhee, June-Koo Kevin
2015-10-19
The feasibility of software-defined optical networking (SDON) for a practical application critically depends on scalability of centralized control performance. The paper, highly scalable routing and wavelength assignment (RWA) algorithms are investigated on an OpenFlow-based SDON testbed for proof-of-concept demonstration. Efficient RWA algorithms are proposed to achieve high performance in achieving network capacity with reduced computation cost, which is a significant attribute in a scalable centralized-control SDON. The proposed heuristic RWA algorithms differ in the orders of request processes and in the procedures of routing table updates. Combined in a shortest-path-based routing algorithm, a hottest-request-first processing policy that considers demand intensity and end-to-end distance information offers both the highest throughput of networks and acceptable computation scalability. We further investigate trade-off relationship between network throughput and computation complexity in routing table update procedure by a simulation study. PMID:26480397
Directory of Open Access Journals (Sweden)
Zhaocai Wang
2015-10-01
Full Text Available The unbalanced assignment problem (UAP is to optimally resolve the problem of assigning n jobs to m individuals (m < n, such that minimum cost or maximum profit obtained. It is a vitally important Non-deterministic Polynomial (NP complete problem in operation management and applied mathematics, having numerous real life applications. In this paper, we present a new parallel DNA algorithm for solving the unbalanced assignment problem using DNA molecular operations. We reasonably design flexible-length DNA strands representing different jobs and individuals, take appropriate steps, and get the solutions of the UAP in the proper length range and O(mn time. We extend the application of DNA molecular operations and simultaneity to simplify the complexity of the computation.
An O(NlogN Algorithm for Region Definition Using Channels/Switchboxes and Ordering Assignment
Directory of Open Access Journals (Sweden)
Jin-Tai Yan
1996-01-01
Full Text Available For a building block placement, the routing space can be further partitioned into channels and switchboxes. In general, the definition of switchboxes releases the cyclic channel precedence constraints and further yields a safe routing ordering process. However, switchbox routing is more difficult than channel routing. In this paper, an O(NlogN region definition and ordering assignment (RDAOA algorithm is proposed to minimize the number of switchboxes for the routing phase, where N is the number of vertices in a channel precedence graph. Several examples have been tested on the proposed algorithm, and the experimental results are listed and compared.
A Genetic Algorithm Approach for the TV Self-Promotion Assignment Problem
Pereira, Paulo A.; Fontes, Fernando A. C. C.; Fontes, Dalila B. M. M.
2009-01-01
We report on the development of a Genetic Algorithm (GA), which has been integrated into a Decision Support System to plan the best assignment of the weekly self-promotion space for a TV station. The problem addressed consists on deciding which shows to advertise and when such that the number of viewers, of an intended group or target, is maximized. The GA proposed incorporates a greedy heuristic to find good initial solutions. These solutions, as well as the solutions later obtai...
FPGA implementation of dynamic channel assignment algorithm for cognitive wireless sensor networks
Martínez, Daniela M.; Andrade, Ángel G.
2015-07-01
The reliability of wireless sensor networks (WSNs) in industrial applications can be thwarted due to multipath fading, noise generated by industrial equipment or heavy machinery and particularly by the interference generated from other wireless devices operating in the same spectrum band. Recently, cognitive WSNs (CWSNs) were proposed to improve the performance and reliability of WSNs in highly interfered and noisy environments. In this class of WSN, the nodes are spectrum aware, that is, they monitor the radio spectrum to find channels available for data transmission and dynamically assign and reassign nodes to low-interference condition channels. In this work, we present the implementation of a channel assignment algorithm in a field-programmable gate array, which dynamically assigns channels to sensor nodes based on the interference and noise levels experimented in the network. From the results obtained from the performance evaluation of the CWSN when the channel assignment algorithm is considered, it is possible to identify how many channels should be available in the network in order to achieve a desired percentage of successful transmissions, subject to constraints on the signal-to-interference plus noise ratio on each active link.
A Lagrangian Dual-Based Branch-and-Bound Algorithm for the Generalized Multi-Assignment Problem
June S. Park; Byung Ha Lim; Youngho Lee
1998-01-01
This paper develops a Lagrangian dual-based branch-and-bound algorithm for the generalized multi-assignment problem (GMAP) which includes the well-known generalized assignment problem (GAP) as a special case. In GMAP, an object may be required to be duplicated in multiple locations. We develop a Lagrangian dual ascent algorithm for GMAP. This dual ascent and the subgradient search each possess advantages that can be combined to develop a new Lagrangian dual search algorithm. The latter algori...
Advanced Credit-Assignment CMAC Algorithm for Robust Self-Learning and Self-Maintenance Machine
Institute of Scientific and Technical Information of China (English)
ZHANG Lei(张蕾); LEE Jay; CAO Qixin(曹其新); WANG Lei(王磊)
2004-01-01
Smart machine necessitates self-learning capabilities to assess its own performance and predict its behavior. To achieve self-maintenance intelligence, robust and fast learning algorithms need to be embedded in machine for real-time decision. This paper presents a credit-assignment cerebellar model articulation controller (CA-CMAC) algorithm to reduce learning interference in machine learning. The developed algorithms on credit matrix and the credit correlation matrix are presented. The error of the training sample distributed to the activated memory cell is proportional to the cell's credibility, which is determined by its activated times. The convergence processes of CA-CMAC in cyclic learning are further analyzed with two convergence theorems. In addition, simulation results on the inverse kinematics of 2-degree-of-freedom planar robot arm are used to prove the convergence theorems and show that CA-CMAC converges faster than conventional machine learning.
Energy Technology Data Exchange (ETDEWEB)
Langmead, Christopher James [Dartmouth Computer Science Department (United States); Donald, Bruce Randall [Dartmouth Center for Structural Biology and Computational Chemistry (United States)], E-mail: brd@cs.dartmouth.edu
2004-06-15
We report an automated procedure for high-throughput NMR resonance assignment for a protein of known structure, or of an homologous structure. Our algorithm performs Nuclear Vector Replacement (NVR) by Expectation/Maximization (EM) to compute assignments. NVR correlates experimentally-measured NH residual dipolar couplings (RDCs) and chemical shifts to a given a priori whole-protein 3D structural model. The algorithm requires only uniform {sup 15}N-labelling of the protein, and processes unassigned H{sup N}-{sup 15}N HSQC spectra, H{sup N}-{sup 15}N RDCs, and sparse H{sup N}-H{sup N} NOE's (d{sub NN}s). NVR runs in minutes and efficiently assigns the (H{sup N},{sup 15}N) backbone resonances as well as the sparse d{sub NN}s from the 3D {sup 15}N-NOESY spectrum, in O(n{sup 3}) time. The algorithm is demonstrated on NMR data from a 76-residue protein, human ubiquitin, matched to four structures, including one mutant (homolog), determined either by X-ray crystallography or by different NMR experiments (without RDCs). NVR achieves an average assignment accuracy of over 99%. We further demonstrate the feasibility of our algorithm for different and larger proteins, using different combinations of real and simulated NMR data for hen lysozyme (129 residues) and streptococcal protein G (56 residues), matched to a variety of 3D structural models. Abbreviations: NMR, nuclear magnetic resonance; NVR, nuclear vector replacement; RDC, residual dipolar coupling; 3D, three-dimensional; HSQC, heteronuclear single-quantum coherence; H{sup N}, amide proton; NOE, nuclear Overhauser effect; NOESY, nuclear Overhauser effect spectroscopy; d{sub NN}, nuclear Overhauser effect between two amide protons; MR, molecular replacement; SAR, structure activity relation; DOF, degrees of freedom; nt., nucleotides; SPG, Streptococcal protein G; SO(3), special orthogonal (rotation) group in 3D; EM, Expectation/Maximization; SVD, singular value decomposition.
Heuristic algorithms for a storage location assignment problem in a chaotic warehouse
Quintanilla, Sacramento; Pérez, Ángeles; Ballestín, Francisco; Lino, Pilar
2015-10-01
The extensive application of emerging technologies is revolutionizing warehouse management. These technologies facilitate working with complex and powerful warehouse management models in which products do not have assigned fixed locations (random storage). Random storage allows the utilization of the available space to be optimized. In this context, and motivated by a real problem, this article presents a model that looks for the optimal allocation of goods in order to maximize the storage space availability within the restrictions of the warehouse. For the proposed model a construction method, a local search algorithm and different metaheuristics have been developed. The introduced algorithms can also be used for other purposes such as to assess when and how it is convenient to perform relocation of stored items to improve the current level of storage space availability. Computational tests performed on a set of randomly generated and real warehouse instances show the effectiveness of the proposed methods.
Applying genetic algorithms to the state assignment problem: a case study
Amaral, Jose N.; Tumer, Kagan; Ghosh, Joydeep
1992-08-01
Finding the best state assignment for implementing a synchronous sequential circuit is important for reducing silicon area or chip count in many digital designs. This State Assignment Problem (SAP) belongs to a broader class of combinatorial optimization problems than the well studied traveling salesman problem, which can be formulated as a special case of SAP. The search for a good solution is considerably more involved for the SAP than it is for the traveling salesman problem due to a much larger number of equivalent solutions, and no effective heuristic has been found so far to cater to all types of circuits. In this paper, a matrix representation is used as the genotype for a Generic Algorithm (GA) approach to this problem. A novel selection mechanism is introduced, and suitable genetic operators for crossover and mutation, are constructed. The properties of each of these elements of the GA are discussed and an analysis of parameters that influence the algorithm is given. A canonical form for a solution is defined to significantly reduce the search space and number of local minima. Simulation results for scalable examples show that the GA approach yields results that are comparable to those obtained using competing heuristics. Although a GA does not seem to be the tool of choice for use in a sequential Von-Neumann machine, the results obtained are good enough to encourage further research on distributed processing GA machines that can exploit its intrinsic parallelism.
Analyzing the multiple-target-multiple-agent scenario using optimal assignment algorithms
International Nuclear Information System (INIS)
This work considers the problem of maximum utilization of a set of mobile robots with limited sensor-range capabilities and limited travel distances. The robots are initially in random positions. A set of robots properly guards or covers a region if every point within the region is within the effective sensor range of at least one vehicle. The authors wish to move the vehicles into surveillance positions so as to guard or cover a region, while minimizing the maximum distance traveled by any vehicle. This problem can be formulated as an assignment problem, in which they must optimally decide which robot to assign to which slot of a desired matrix of grid points. The cost function is the maximum distance traveled by any robot. Assignment problems can be solved very efficiently. Solutions times for one hundred robots took only seconds on a Silicon Graphics Crimson workstation. The initial positions of all the robots can be sampled by a central base station and their newly assigned positions communicated back to the robots. Alternatively, the robots can establish their own coordinate system with the origin fixed at one of the robots and orientation determined by the compass bearing of another robot relative to this robot. This paper presents example solutions to the multiple-target-multiple-agent scenario using a matching algorithm. Two separate cases with one hundred agents in each were analyzed using this method. They have found these mobile robot problems to be a very interesting application of network optimization methods, and they expect this to be a fruitful area for future research
Lim, Wee Loon; Wibowo, Antoni; Desa, Mohammad Ishak; Haron, Habibollah
2016-01-01
The quadratic assignment problem (QAP) is an NP-hard combinatorial optimization problem with a wide variety of applications. Biogeography-based optimization (BBO), a relatively new optimization technique based on the biogeography concept, uses the idea of migration strategy of species to derive algorithm for solving optimization problems. It has been shown that BBO provides performance on a par with other optimization methods. A classical BBO algorithm employs the mutation operator as its diversification strategy. However, this process will often ruin the quality of solutions in QAP. In this paper, we propose a hybrid technique to overcome the weakness of classical BBO algorithm to solve QAP, by replacing the mutation operator with a tabu search procedure. Our experiments using the benchmark instances from QAPLIB show that the proposed hybrid method is able to find good solutions for them within reasonable computational times. Out of 61 benchmark instances tested, the proposed method is able to obtain the best known solutions for 57 of them. PMID:26819585
Lim, Wee Loon; Wibowo, Antoni; Desa, Mohammad Ishak; Haron, Habibollah
2016-01-01
The quadratic assignment problem (QAP) is an NP-hard combinatorial optimization problem with a wide variety of applications. Biogeography-based optimization (BBO), a relatively new optimization technique based on the biogeography concept, uses the idea of migration strategy of species to derive algorithm for solving optimization problems. It has been shown that BBO provides performance on a par with other optimization methods. A classical BBO algorithm employs the mutation operator as its diversification strategy. However, this process will often ruin the quality of solutions in QAP. In this paper, we propose a hybrid technique to overcome the weakness of classical BBO algorithm to solve QAP, by replacing the mutation operator with a tabu search procedure. Our experiments using the benchmark instances from QAPLIB show that the proposed hybrid method is able to find good solutions for them within reasonable computational times. Out of 61 benchmark instances tested, the proposed method is able to obtain the best known solutions for 57 of them. PMID:26819585
Evaluation of the Jonker-Volgenant-Castanon (JVC) assignment algorithm for track association
Malkoff, Donald B.
1997-07-01
The Jonker-Volgenant-Castanon (JVC) assignment algorithm was used by Lockheed Martin Advanced Technology Laboratories (ATL) for track association in the Rotorcraft Pilot's Associate (RPA) program. RPA is Army Aviation's largest science and technology program, involving an integrated hardware/software system approach for a next generation helicopter containing advanced sensor equipments and applying artificial intelligence `associate' technologies. ATL is responsible for the multisensor, multitarget, onboard/offboard track fusion. McDonnell Douglas Helicopter Systems is the prime contractor and Lockheed Martin Federal Systems is responsible for developing much of the cognitive decision aiding and controls-and-displays subsystems. RPA is scheduled for flight testing beginning in 1997. RPA is unique in requiring real-time tracking and fusion for large numbers of highly-maneuverable ground (and air) targets in a target-dense environment. It uses diverse sensors and is concerned with a large area of interest. Target class and identification data is tightly integrated with spatial and kinematic data throughout the processing. Because of platform constraints, processing hardware for track fusion was quite limited. No previous experience using JVC in this type environment had been reported. ATL performed extensive testing of the JVC, concentrating on error rates and run- times under a variety of conditions. These included wide ranging numbers and types of targets, sensor uncertainties, target attributes, differing degrees of target maneuverability, and diverse combinations of sensors. Testing utilized Monte Carlo approaches, as well as many kinds of challenging scenarios. Comparisons were made with a nearest-neighbor algorithm and a new, proprietary algorithm (the `Competition' algorithm). The JVC proved to be an excellent choice for the RPA environment, providing a good balance between speed of operation and accuracy of results.
GTSH: A New Channel Assignment Algorithm in Multi-Radio Multi-channel Wireless Mesh Networks
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Zahra Shokouh
2015-07-01
Full Text Available One of the complexities in a wireless mesh networks is its low throughput. For this reason and due to the fact that throughput is highly reduced by increased number of nodes, it is difficult to extend such networks. Therefore, providing a high throughput in these networks is an essential goal. The main lowering cause of efficiency of such networks is interference between wireless links. A high interference leads to a reduced throughput. In this research, two channel assignment methods were presented using genetic and tabu search algorithms and their advantages and disadvantages were assessed. Finally, a new method combining the advantages of both methods was proposed. With the help of NS2 network simulator, our work was simulated and the combination results of the two methods were compared. The results were indicative of the better performance of the hybrid method and significant increase of throughput in the network.
New algorithm for robust H2/H∞ filtering with error variance assignment
Institute of Scientific and Technical Information of China (English)
刘立恒; 邓正隆; 王广雄
2004-01-01
We consider the robust H2/H∞ filtering problem for linear perturbed systems with steady-state error variance assignment. The generalized inverse technique of matrix is introduced, and a new algorithm is developed. After two Riccati equations are solved, the filter can be obtained directly, and the following three performance requirements are simultaneously satisfied: The filtering process is asymptotically stable; the steady-state variance of the estimation error of each state is not more than the individual prespecified upper bound; the transfer function from exogenous noise inputs to error state outputs meets the prespecified H∞ norm upper bound constraint. A numerical example is provided to demonstrate the flexibility of the proposed design approach.
Particle swarm optimization algorithm for optimizing assignment of blood in blood banking system.
Olusanya, Micheal O; Arasomwan, Martins A; Adewumi, Aderemi O
2015-01-01
This paper reports the performance of particle swarm optimization (PSO) for the assignment of blood to meet patients' blood transfusion requests for blood transfusion. While the drive for blood donation lingers, there is need for effective and efficient management of available blood in blood banking systems. Moreover, inherent danger of transfusing wrong blood types to patients, unnecessary importation of blood units from external sources, and wastage of blood products due to nonusage necessitate the development of mathematical models and techniques for effective handling of blood distribution among available blood types in order to minimize wastages and importation from external sources. This gives rise to the blood assignment problem (BAP) introduced recently in literature. We propose a queue and multiple knapsack models with PSO-based solution to address this challenge. Simulation is based on sets of randomly generated data that mimic real-world population distribution of blood types. Results obtained show the efficiency of the proposed algorithm for BAP with no blood units wasted and very low importation, where necessary, from outside the blood bank. The result therefore can serve as a benchmark and basis for decision support tools for real-life deployment. PMID:25815046
International Nuclear Information System (INIS)
A multi-objective genetic algorithm is introduced to predict the assignment of protein solid-state NMR (SSNMR) spectra with partial resonance overlap and missing peaks due to broad linewidths, molecular motion, and low sensitivity. This non-dominated sorting genetic algorithm II (NSGA-II) aims to identify all possible assignments that are consistent with the spectra and to compare the relative merit of these assignments. Our approach is modeled after the recently introduced Monte-Carlo simulated-annealing (MC/SA) protocol, with the key difference that NSGA-II simultaneously optimizes multiple assignment objectives instead of searching for possible assignments based on a single composite score. The multiple objectives include maximizing the number of consistently assigned peaks between multiple spectra (“good connections”), maximizing the number of used peaks, minimizing the number of inconsistently assigned peaks between spectra (“bad connections”), and minimizing the number of assigned peaks that have no matching peaks in the other spectra (“edges”). Using six SSNMR protein chemical shift datasets with varying levels of imperfection that was introduced by peak deletion, random chemical shift changes, and manual peak picking of spectra with moderately broad linewidths, we show that the NSGA-II algorithm produces a large number of valid and good assignments rapidly. For high-quality chemical shift peak lists, NSGA-II and MC/SA perform similarly well. However, when the peak lists contain many missing peaks that are uncorrelated between different spectra and have chemical shift deviations between spectra, the modified NSGA-II produces a larger number of valid solutions than MC/SA, and is more effective at distinguishing good from mediocre assignments by avoiding the hazard of suboptimal weighting factors for the various objectives. These two advantages, namely diversity and better evaluation, lead to a higher probability of predicting the correct
A Genetic Algorithm Approach for the TV Self-Promotion Assignment Problem
Pereira, Paulo A.; Fontes, Fernando A. C. C.; Fontes, Dalila B. M. M.
2009-09-01
We report on the development of a Genetic Algorithm (GA), which has been integrated into a Decision Support System to plan the best assignment of the weekly self-promotion space for a TV station. The problem addressed consists on deciding which shows to advertise and when such that the number of viewers, of an intended group or target, is maximized. The GA proposed incorporates a greedy heuristic to find good initial solutions. These solutions, as well as the solutions later obtained through the use of the GA, go then through a repair procedure. This is used with two objectives, which are addressed in turn. Firstly, it checks the solution feasibility and if unfeasible it is fixed by removing some shows. Secondly, it tries to improve the solution by adding some extra shows. Since the problem faced by the commercial TV station is too big and has too many features it cannot be solved exactly. Therefore, in order to test the quality of the solutions provided by the proposed GA we have randomly generated some smaller problem instances. For these problems we have obtained solutions on average within 1% of the optimal solution value.
Application of k-person and k-task maximal efficiency assignment algorithm to water piping repair
Directory of Open Access Journals (Sweden)
Su-juan ZHENG
2009-06-01
Full Text Available Solving the absent assignment problem of the shortest time limit in a weighted bipartite graph with the minimal weighted k-matching algorithm is unsuitable for situations in which large numbers of problems need to be addressed by large numbers of parties. This paper simplifies the algorithm of searching for the even alternating path that contains a maximal element using the minimal weighted k-matching theorem and intercept graph. A program for solving the maximal efficiency assignment problem was compiled. As a case study, the program was used to solve the assignment problem of water piping repair in the case of a large number of companies and broken pipes, and the validity of the program was verified.
Application of k-person and k-task maximal efficiency assignment algorithm to water piping repair
Institute of Scientific and Technical Information of China (English)
Su-juan ZHENG; Xiu-ming YU; Li-qing CAO
2009-01-01
Solving the absent assignment problern of the shortest time limit in a weighted bipartite graph with the minimal weighted k-matching algorithm is unsuitable for situations in which large numbers of problems need to be addressed by large numbers of parties. This paper simplifies the algorithm of searching for the even alternating path that contains a maximal element using the minimal weighted k-matching theorem and intercept graph. A program for solving the maximal efficiency assignment problem was compiled. As a case study, the program was used to solve the assignment problem of water piping repair in the case of a large number of companies and broken pipes, and the validity of the program was verified.
Ishikawa, Akio; Kishi, Yoji
2000-09-01
This paper newly proposes a self-healing architecture in all- optical WDM networks based on virtual embedded multiple rings (Virtual Multiple Self Healing Rings: VM-SHR). Focusing upon the network design aspect of the proposed architecture, this paper describes design methodologies for VM-SHR networks. For two major problems in all-optical WDM network design, that is, the connection routing and wavelength assignment problems, we first established solution models based on mathematical programming formulation, each of which can be solved by common integer programming algorithms, respectively. In addition, we also developed an efficient heuristic algorithm for the wavelength assignment problem. Their usefulness and performance are demonstrated through the extensive simulation results.
International Nuclear Information System (INIS)
Rapid analysis of protein structure, interaction, and dynamics requires fast and automated assignments of 3D protein backbone triple-resonance NMR spectra. We introduce a new depth-first ordered tree search method of automated assignment, CASA, which uses hand-edited peak-pick lists of a flexible number of triple resonance experiments. The computer program was tested on 13 artificially simulated peak lists for proteins up to 723 residues, as well as on the experimental data for four proteins. Under reasonable tolerances, it generated assignments that correspond to the ones reported in the literature within a few minutes of CPU time. The program was also tested on the proteins analyzed by other methods, with both simulated and experimental peaklists, and it could generate good assignments in all relevant cases. The robustness was further tested under various situations
Equilibrium model and algorithm of urban transit assignment based on augmented network
Institute of Scientific and Technical Information of China (English)
无
2009-01-01
The passenger flow assignment problem for the urban transit network is relatively complicated due to the complexity of the network structure and many factors influencing the passengers’ route and line choices. In the past three decades, many models have been proposed to solve the passenger flow assignment problem. However, the common-line problem remains challenging in transit flow assignment. In this paper, the characteristics of the urban transit network is analysed and a new technique of augmented network is proposed to represent the urban transit system. The purpose is to eliminate the complex common-line problem when modeling transit passenger flow assignment. Through this augmentation technique, the urban transit system can be represented by an augmented network-it then behaves like a simple network and can be used as a generalized network for traffic assignment or network analysis. This paper presents a user equilibrium model for the urban transit assignment problem based on such a technique. A numerical example is also provided to illustrate the approach.
DEFF Research Database (Denmark)
Robenek, Tomáš; Umang, Nitish; Bierlaire, Michel;
2014-01-01
In this research, two crucial optimization problems of berth allocation and yard assignment in the context of bulk ports are studied. We discuss how these problems are interrelated and can be combined and solved as a single large scale optimization problem. More importantly we highlight the...... differences in operations between bulk ports and container terminals which highlights the need to devise specific solutions for bulk ports. The objective is to minimize the total service time of vessels berthing at the port. We propose an exact solution algorithm based on a branch and price framework to solve......-shaking neighborhood search is presented. The proposed algorithms are tested and validated through numerical experiments based on instances inspired from real bulk port data. The results indicate that the algorithms can be successfully used to solve instances containing up to 40 vessels within reasonable computational...
Artificial Bee Colony Algorithm and Its Application to Generalized Assignment Problem
Baykaso&#;lu, Adil; Özbak&#;r, Lale; Tapkan, P&#;nar
2007-01-01
In this study a relatively new member of swarm intelligence family that is named as "artificial bee colony" is explained in detail. Actually, different names were used in the literature for the algorithms inspired from natural honey bees. Here we prefer to use the name "artificial bee colony" to reflect population characteristic of the algorithm. A very detailed literature review along with a categorization is presented in this study. All accessible previous work on bee based optimization alg...
Celandroni, Nedo; Ferro, Erina; Potort?, Francesco
1995-01-01
Most demand assignment TDMA satellite access protocols use centralised control schemes rather than distributed ones because their simplicity and robustness usually compensate for the longer allocationdelay. In this work the authors define the working details of two different distributed-control protocols, both derived from the FODA/IBEA(*) centralised control protocol, and they presentthe probabilities of disastrous events and the re levantrecovery procedures, whose handling is central to the...
A genetic algorithm for robust berth allocation and quay crane assignment
Rodríguez Molins, Mario; Ingolotti Hetter, Laura Paola; Barber Sanchís, Federico; Salido Gregorio, Miguel Angel; R. Sierra, María; Puente, Jorge
2014-01-01
Scheduling problems usually obtain the optimal solutions assuming that the environment is deterministic. However, actually the environment is dynamic and uncertain. Thus, the initial data could change and the initial schedule obtained might be unfeasible. To overcome this issue, a proactive approach is presented for scheduling problems without any previous knowledge about the incidences that can occur. In this paper, we consider the berth allocation problem and the quay crane assignment probl...
Belief propagation : an asymptotically optimal algorithm for the random assignment problem
Salez, Justin; Shah, Devavrat
2009-01-01
The random assignment problem asks for the minimum-cost perfect matching in the complete $n\\times n$ bipartite graph $\\Knn$ with i.i.d. edge weights, say uniform on $[0,1]$. In a remarkable work by Aldous (2001), the optimal cost was shown to converge to $\\zeta(2)$ as $n\\to\\infty$, as conjectured by M\\'ezard and Parisi (1987) through the so-called cavity method. The latter also suggested a non-rigorous decentralized strategy for finding the optimum, which turned out to be an instance of the B...
Directory of Open Access Journals (Sweden)
Abd El–Naser A. Mohammed
2013-02-01
Full Text Available In simple wavelength-division multiplexed (WDM networks, a connection must be established along a route using a common wavelength on all of the links along the route. The introduction of wavelength converters into WDM cross connects increases the hardware cost and complexity. Given a set of connection requests, the routing and wavelength assignment problem involves finding a route (routing and assigning a wavelength to each request. This paper has presented the WDM technology is being extensively deployed on point to point links within transport networks in the EGYPT. However, WDM promises advantages for switching and routing as well as for transmission. Optical cross connects are currently being developed which can switch an entire wavelength from an input fiber to an output fiber so that large bandwidth circuits can be routed through the network according to wavelength. High speed, fixed bandwidth, end to end connections called lightpaths can then be established between different nodes. Our suggested Trans-Egypt Network (TEGYNET which uses optical cross connects to route lightpaths through the network are referred to as wavelength routing networks. The average setup time, average link utilization, traffic load, blocking probability, and achievable link utilization in the presence of both single path and multi math routing are the major interesting parameters in the design of TEGYNET topology.
Ansari, Elnaz Saberi; Eslahchi, Changiz; Pezeshk, Hamid; Sadeghi, Mehdi
2014-09-01
Decomposition of structural domains is an essential task in classifying protein structures, predicting protein function, and many other proteomics problems. As the number of known protein structures in PDB grows exponentially, the need for accurate automatic domain decomposition methods becomes more essential. In this article, we introduce a bottom-up algorithm for assigning protein domains using a graph theoretical approach. This algorithm is based on a center-based clustering approach. For constructing initial clusters, members of an independent dominating set for the graph representation of a protein are considered as the centers. A distance matrix is then defined for these clusters. To obtain final domains, these clusters are merged using the compactness principle of domains and a method similar to the neighbor-joining algorithm considering some thresholds. The thresholds are computed using a training set consisting of 50 protein chains. The algorithm is implemented using C++ language and is named ProDomAs. To assess the performance of ProDomAs, its results are compared with seven automatic methods, against five publicly available benchmarks. The results show that ProDomAs outperforms other methods applied on the mentioned benchmarks. The performance of ProDomAs is also evaluated against 6342 chains obtained from ASTRAL SCOP 1.71. ProDomAs is freely available at http://www.bioinf.cs.ipm.ir/software/prodomas. PMID:24596179
Post-Processing Techniques to Enhance Reliability of Assignment Algorithm Based Performance Measures
Peeta, Srinivas; Kumar, Amit; Sharma, Sushant
2011-01-01
This study develops an enhanced transportation planning framework by augmenting the sequential four-step planning process with post-processing techniques. The post-processing techniques are incorporated through a feedback mechanism and aim to improve the stability and convergence properties of the solution, thereby improving the reliability of the planning process. There are three building blocks of the proposed post-processing module: slope-based multi-path algorithm or SMPA, perturbation as...
Directory of Open Access Journals (Sweden)
Min Jin
2014-01-01
Full Text Available There is recently a great deal of interest and excitement in understanding the role of inertia and acceleration in the motion equation of discrete particle swarm optimization (DPSO algorithms. It still remains unknown whether the inertia section should be abandoned and how to select the appropriate acceleration in order for DPSO to show the best convergence performance. Adopting channel assignment as a case study, this paper systematically conducts experimental filtering research on this issue. Compared with other channel assignment schemes, the proposed scheme and the selection of inertia and acceleration are verified to have the advantage to channel assignment in three respects of convergence rate, convergence speed, and the independency of the quality of initial solution. Furthermore, the experimental result implies that DSPO might have the best convergence performance when its motion equation includes an inertia section in a less medium weight, a bigger acceleration coefficient for global-search optimum, and a smaller acceleration coefficient for individual-search optimum.
Asset-Based Assessment in Educational Psychology: Capturing Perceptions during a Paradigm Shift
Lubbe, Carien; Eloff, Irma
2004-01-01
Several trends are compelling educational psychologists towards a philosophy of assessment that is asset-based and strength focused. This article shares the results from a study that explored perceptions about asset-based assessment in Educational Psychology in South Africa. Three focus groups were held and four main themes emerged from the…
García Molina, Pablo; Balaguer López, Evelin
2009-04-01
Bed sores among children are an adverse effect provoked by the application of new technology adapted to pediatrics. Special surfaces for managing pressure in pediatrics are a preventive measure effective to avoid the development of these lesions. So that children benefit from this preventive measure, it must be adapted to their specific circumstances. In order for this to occur, it is fundamental to know: the specific characteristics which differentiate children from adults, and the type of special surfaces for managing pressure in pediatrics which are available on the market and to evaluate their appropriateness and effectiveness. The Group of Nurses to Improve Quality in Pediatrics at the University Clinical Hospital in Valencia has developed some tools which make it possible to manage and assign different sizes and types of special surfaces for managing pressure in pediatrics by means of a scientific method (Tarise). These are based on anthropometric measurements (Pediatric Space table) for each age range, the risk to develop a bed sore or skin ulcer due to pressure, the presence of a bed sore, the pathological seriousness and the type of special surfaces for managing pressure in pediatrics. PMID:19554896
Performance Analysis of IMS Network: the Proposal of new Algorithms for S-CSCF Assignment
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Lubos Nagy
2013-01-01
Full Text Available This article is focused on the proposal of three load balancing methods which can be used for a selection of S-CSCF (Serving-Call Session Control Server server in IP Multimedia Subsystem (IMS during the registration procedures of subscribers. All presented methods are implemented and evaluated for various inter-arrival and service times in the mathematical model based on queueing theory. In this article, two methods based on performance parameters (such as utilizations, etc. and one method based on number of registered subscribers to each of available S-CSCF server are described. The main advantage of third method is that all related information is obtained from traffic analysis through I-CSCF (Interrogating-CSCF node. Also, the designed methods are compared with other selection algorithms presented in previous research works by others researchers (Hwang et col., Cho et col. or Tirana et col.. The article shows that the implemented methods can optimize the service latency of whole IMS network.
Intersecting Asset-Based Service, Strengths, and Mentoring for Socially Responsible Leadership.
Hastings, Lindsay
2016-06-01
Grounded in a youth leadership and mentoring program, this chapter discusses the value of asset-based community development from the service-learning literature and the concept of generativity from the leadership development literature. PMID:27150907
Directory of Open Access Journals (Sweden)
Alex D Herbert
Full Text Available Accurate and reproducible quantification of the accumulation of proteins into foci in cells is essential for data interpretation and for biological inferences. To improve reproducibility, much emphasis has been placed on the preparation of samples, but less attention has been given to reporting and standardizing the quantification of foci. The current standard to quantitate foci in open-source software is to manually determine a range of parameters based on the outcome of one or a few representative images and then apply the parameter combination to the analysis of a larger dataset. Here, we demonstrate the power and utility of using machine learning to train a new algorithm (FindFoci to determine optimal parameters. FindFoci closely matches human assignments and allows rapid automated exploration of parameter space. Thus, individuals can train the algorithm to mirror their own assignments and then automate focus counting using the same parameters across a large number of images. Using the training algorithm to match human assignments of foci, we demonstrate that applying an optimal parameter combination from a single image is not broadly applicable to analysis of other images scored by the same experimenter or by other experimenters. Our analysis thus reveals wide variation in human assignment of foci and their quantification. To overcome this, we developed training on multiple images, which reduces the inconsistency of using a single or a few images to set parameters for focus detection. FindFoci is provided as an open-source plugin for ImageJ.
von Maltzahn, Robyn; Durrheim, Kevin
2008-01-01
This paper contests the major emphasis placed on the multidimensional nature of poverty measurement. Instead, it argues that poverty pictures created by different measures and at different units of analysis tend to converge. This argument is derived from a comparison of poverty pictures created using income and asset-based measures at the national…
改进蚁群算法在二次分配问题中的应用%Application of Improved Ant Colony Algorithm for Quadratic Assignment Problems
Institute of Scientific and Technical Information of China (English)
袁东锋; 吕聪颖
2013-01-01
为了解决基本蚁群算法在求解大规模二次分配问题时暴露出的缺陷,本文提出一种改进的蚁群算法.在基本蚂蚁算法中,采用全局信息素更新策略,使用距离及流量作为启发式信息并引入局部优化策略,对每代的最优解进行改进,进一步加快算法的收敛速度.通过对于二次分配问题的3种不同类型的问题进行实验,将改进的蚁群算法与基本蚂蚁算法及混合遗传算法进行比较,结果表明该改进算法具有更优的性能.%In order to solve the problems that the basic ant colony algorithm for solving large scale quadratic assignment has revealed defects, this paper proposes an improved ant colony algorithm. This algorithm adopts the global pheromone update strategy, the use of distance and traffic as heuristic information and the introduction of local optimization strategy. The optimal solution for each generation is to improve and further accelerate the convergence speed. For the quadratic assignment problem through three different types of problems, and improved ant colony algorithm with the basic ant algorithm and the hybrid genetic algorithm are compared, the experiments show that the improved method has better performance.
改进的人工蜂群算法求解任务指派问题%Improved Artificial Bee Colony Algorithm for Assignment Problem
Institute of Scientific and Technical Information of China (English)
孙晓雅; 林焰
2012-01-01
针对指派问题提出了一种改进的人工蜂群算法.该算法充分考虑到指派问题解的离散性特点,给出了食物源位置的离散编码方法,并且采用邻域移动法生成候选食物源,这一方法既保证了解的可行性,又增加了食物源的多样性.实算表明在求解指派问题时,该算法比原人工蜂群算法在求解精度和收敛速度上都有显著地提高,两性能也优于其他粒子群算法.这种改进的离散人工蜂群算法简洁,应用方便,不但是一种有效求解指派问题的新算法,同时也为其他组合优化问题求解提供了一种有益思路.%An improved artificial bee colony（IABC） optimization algorithm is presented for assignment problem.In consideration of the solution＇s discreteness,this algorithm gives a discrete coding method for the food source position.The algorithm adopts neighborhood shift to produce a candidate food position,which can ensure the solution feasible and increase the diversity of food sources.The actual calculation shows that the IABC algorithm can accelerate the convergence process obviously and improve the precision compared with the original artificial bee colony（ABC） algorithm,and this method is also superior to other particle swarm optimization（PSO） algorithms.The principle of this algorithm is simple and its application is flexible and easy.It is a new algorithm for assignment problem and it presents a new vision for other combinatorial optimization problems.
DEFF Research Database (Denmark)
Lee, Jinsik; Kang, Yong Cheol; Muljadi, Edward; Sørensen, Poul Ejnar
2014-01-01
rotor speed, while the same gains of the ROCOF loop are set for all WGs. In addition, the wake wind speed arriving at the WG is calculated by considering the wind direction and cumulative impacts of multiple shadowing. The performance of the algorithm was investigated under various wind conditions using...
metaMatch: un algorithme pour l'assignation taxonomique en métagénomique
Frigerio, Jean-Marc; Chaumeil, Philippe; Gay, Pierre; Kermarrec, Lenaïg; Rimet, Frédéric,; Bouchez, Agnès; Franc, Alain
2012-01-01
Community ecology faces a new challenge as the next-generation sequencing approaches can yield data from hundreds of microbial community samples. This way, combined with accurate and reliable taxonomic assessment, yields hundreds of new data that will contribute to a better understanding of community assemblies formed under various environmental and historical conditions. Algorithms classifying sequences by comparison to a reference library are the most widely used tools for assessing communi...
International Nuclear Information System (INIS)
A new computer program, HYPER, has been developed for automated analysis of protein dihedral angle values and CβH2 stereospecific assignments from NMR data. HYPER uses a hierarchical grid-search algorithm to determine allowed values of φ, Ψ, and χ1 dihedral angles and CβH2 stereospecific assignments based on a set of NMR-derived distance and/or scalar-coupling constraints. Dihedral-angle constraints are valuable for restricting conformational space and improving convergence in three-dimensional structure calculations. HYPER computes the set of φ, Ψ, and χ1dihedral angles and CβH2 stereospecific assignments that are consistent with up to nine intraresidue and sequential distance bounds, two pairs of relative distance bounds, thirteen homo- and heteronuclear scalar coupling bounds, and two pairs of relative scalar coupling constant bounds. The program is designed to be very flexible, and provides for simple user modification of Karplus equations and standard polypeptide geometries, allowing it to accommodate recent and future improved calibrations of Karplus curves. The C code has been optimized to execute rapidly (0.3-1.5 CPU-sec residue-1 using a 5 deg. grid) on Silicon Graphics R8000, R10000 and Intel Pentium CPUs, making it useful for interactive evaluation of inconsistent experimental constraints. The HYPER program has been tested for internal consistency and reliability using both simulated and real protein NMR data sets
State feedback eigenstructure assignment algorithm in direct force control%直接力控制的特征结构配置法
Institute of Scientific and Technical Information of China (English)
朱战霞; 王建培
2001-01-01
以现代控制理论和飞行力学原理为基础，针对直接力控制器设计中存在的模态耦合问题，提出一种应用状态反馈特征结构配置进行解耦的方法，并推导出相应的公式。分析表明，用此方法对系统的极点和特征向量可以进行希望的配置，并能达到设计要求。同时仿真结果说明，用状态反馈特征结构配置法设计的控制系统比用线性二次型调节器（LQR）方法设计的控制系统解耦性能好，响应速度快，并且解决了输出反馈特征结构配置不能确保闭环系统稳定的问题。%In order to solve the problem of the mode-coupling in direct force controller design, an algorithm-state feedback eigenstructure assignment, which is on the bases of flight dynamics and modern control theory, is proposed in this paper. Corresponding formulas are derived. Analysis show that this method can be used to assigned the poles and eigenvectors to the desired places to satisfy the requirement of the design. The simulation results prove that by using this method the decoupling performance of the designed controllers is better than that of LQR, and the problem that the stability of the closed-loop system can't be guaranteed when using output feedback eigenstructure assignment algorithm is also be solved.
Cuckoo Search Algorithm for Quadratic Assignment Problem%二次分配问题的布谷鸟搜索算法
Institute of Scientific and Technical Information of China (English)
许秋艳
2015-01-01
二次分配问题是一种典型的组合优化难题。该问题由于目标函数的非线性而使得问题的求解异常复杂。为求解二次分配问题，设计基于布谷鸟搜索算法的优化方法。布谷鸟搜索算法是一种新型现代启发式算法，具有结构简单和易于编程等特点。针对二次分配问题的特点，给出算法的实现流程。实验结果表明该算法的可行性和有效性。%Quadratic Assignment Problem (QAP) is a typical hard problem in combinatorial optimization. It is hard to solve QAP because of its non-linear objective function. To solve QAP, proposes a method based on Cuckoo Search Algorithm (CSA). CSA is a novel metaheuristic which is simple and easy to program. According the features of QAP, shows the algorithm procedure. The results demonstrate that the presented method is feasible and effective.
A multidimensional assignment data association algorithm based on DNA computing%基于DNA计算的多维分配数据关联算法
Institute of Scientific and Technical Information of China (English)
梁冰; 冯林
2012-01-01
The DNA computing was applied to investigation of the data association, a NP-hard mathematical problem in multitarget tracking, and a multidimensional assignment data association algorithm was realized through utilizing the super parallelism of DNA computation.The algorithm uses the DNA molecular chains containing the palindromic sequence of the restriction endonuclease Haelll to encode the observed sight lines.All target association combinations are obtained through the operation of connection and annealing.In order to select the optimal multidimensional data association solution, the techniques of DNA hairpin structure detection and gel electrophoresis are used to remove the target association combinations that do not satisfy the constraints.The results of the theoretic analysis show that the DNA computation based multidimensional assignment data association algorithm needs the DNA molecular chain number of O(nk!/(c - m)!) (the space complexity), and decreases the time complexity from exponential to 0 ( mn) , where n and m are the sensor number and target number respectively, k is the target localization number.%针对多目标跟踪中的多维分配数据关联这-NP难题,将DNA计算用于数据关联研究,利用DNA分子链生化反应的高度并行性,实现了基于DNA计算的多维分配数据关联算法.该算法利用包含限制性内切酶HaeⅢ回文序列的DNA分子链对观测视线进行编码,通过连接和退火操作获得所有目标关联组合,然后利用检测DNA发夹结构和凝胶电泳技术排除不满足约束条件的目标关联组合,筛选出多维分配数据关联的最优解.分析结果表明:基于DNA计算的多维分配数据关联算法所需的DNA分子链数即空间复杂度为O(nk!/(c-m)!),将多维分配问题的指数级复杂度降低到多项式复杂度O(mn),其中n为传感器数,m为目标数,k为目标定位点数.
Balanced input-output assignment
Gawronski, W.; Hadaegh, F. Y.
1989-01-01
Actuator/sensor locations and balanced representations of linear systems are considered for a given set of controllability and observability grammians. The case of equally controlled and observed states is given special attention. The assignability of grammians is examined, and the conditions for their existence are presented, along with several algorithms for their determination. Although an arbitrary positive semidefinite matrix is not always assignable, the identity grammian is shown to be always assignable. The results are extended to the case of flexible structures.
Guillemin, Victor; Sabatini, Silvia; Zara, Catalin
2013-01-01
The concept of assignments was introduced in [GGK99] as a method for extracting geometric information about group actions on manifolds from combinatorial data encoded in the infinitesimal orbit-type stratification. In this paper we will answer in the affirmative a question posed in [GGK99] by showing that the equivariant cohomology ring of $M$ is to a large extent determined by this data.
Institute of Scientific and Technical Information of China (English)
宋业新; 陈绵云; 张曙红
2001-01-01
Two multi-object generalized assignment problems (MOGAP) are discussed and their multi-object integer linear programming models are presented respectively. By combining the fuzzy theory with Hungary algorithm applied to solving the conventional assignment problem, Fuzzy Hungary Algorithm for solving the MOGAP is proposed. The application in the ordnance material supply illustrates the method.%讨论了两类多目标广义指派问题，给出了它们的多目标整数线性规划数学模型，并结合模糊理论与解决传统指派问题的匈牙利算法提出了一种新的求解算法——模糊匈牙利法.给出了该方法在物资供应中的应用.
International Nuclear Information System (INIS)
Energy surfaces of metal clusters usually show a large variety of local minima. For homo-metallic species the energetically lowest can be found reliably with genetic algorithms, in combination with density functional theory without system-specific parameters. For mixed-metallic clusters this is much more difficult, as for a given arrangement of nuclei one has to find additionally the best of many possibilities of assigning different metal types to the individual positions. In the framework of electronic structure methods this second issue is treatable at comparably low cost at least for elements with similar atomic number by means of first-order perturbation theory, as shown previously [F. Weigend, C. Schrodt, and R. Ahlrichs, J. Chem. Phys. 121, 10380 (2004)]. In the present contribution the extension of a genetic algorithm with the re-assignment of atom types to atom sites is proposed and tested for the search of the global minima of PtHf12 and [LaPb7Bi7]4−. For both cases the (putative) global minimum is reliably found with the extended technique, which is not the case for the “pure” genetic algorithm
Weigend, Florian
2014-10-01
Energy surfaces of metal clusters usually show a large variety of local minima. For homo-metallic species the energetically lowest can be found reliably with genetic algorithms, in combination with density functional theory without system-specific parameters. For mixed-metallic clusters this is much more difficult, as for a given arrangement of nuclei one has to find additionally the best of many possibilities of assigning different metal types to the individual positions. In the framework of electronic structure methods this second issue is treatable at comparably low cost at least for elements with similar atomic number by means of first-order perturbation theory, as shown previously [F. Weigend, C. Schrodt, and R. Ahlrichs, J. Chem. Phys. 121, 10380 (2004)]. In the present contribution the extension of a genetic algorithm with the re-assignment of atom types to atom sites is proposed and tested for the search of the global minima of PtHf12 and [LaPb7Bi7]4-. For both cases the (putative) global minimum is reliably found with the extended technique, which is not the case for the "pure" genetic algorithm.
Institute of Scientific and Technical Information of China (English)
何凡; 任向东; 吴桐
2015-01-01
Genetic algorithm is based on its excellent optimization ability,it is widely used in engineering optimization problem solving after proposed. Based on the actual needs of power grid attack unmanned aerial vehicle squads tasks assignment,solution based on genetic algorithm is proposed,and on the basis of the original algorithm,the population group evolution strategy is used to improve. The basic principle of algorithm and simulation steps in detail and practical examples are given to the simulation,the experimental results prove the algorithm improvement has obtained the good effect.%遗传算法因其出色的寻优能力，自提出后就被广泛用于工程技术上的最优化问题求解。根据电力网攻击无人机分队任务分配的实际需要，提出基于遗传算法思想的解决方案，并在原算法基础上，采用种群分组进化的策略进行改进。详细介绍算法的基本原理和仿真步骤，再举出实际算例进行仿真，实验结果证明算法的改进取得了良好效果。
Institute of Scientific and Technical Information of China (English)
张涛; 胡佳研; 李福娟; 张玥杰
2012-01-01
本文将航班串的飞机指派问题归结为车辆路径问题,考虑连续航班串之间衔接时间、衔接机场的约束、每架飞机的总飞行时间约束,建立了带有飞行时间约束的车辆路径问题的混合整数规划模型.构造了蚁群系统算法,引入基于排序的蚂蚁系统和最大最小蚂蚁系统算法的信息素更新策略.选取某航空公司7组初始航班串集合进行测试,并对算法中的重要参数进行了分析.实验结果表明,本文设计的模型和算法可以有效地减少连续航班串之间的总衔接时间,在可接受的计算时间内获得满意解.%The domestic airlines are relatively small in comparison with the international airlines. Airlines used to make the flight plans using simple and rough methods. The competition among the airlines became stronger with the expansion of airlines, and the opening of the air transportation market. Therefore, flight-planning management becomes more important. Aircraft assigning problem ( AAP) is to assign planes to the proper flight reasonably in order to make full use of the fleet resources. Good flight planning can not only ensure the safety and punctuality of flights, but also improve the utilization rale of fleets and decrease the cost of operation and maintenance so as to maximize the economic benefits of the airlines.The theoretical research on the flight-assigning problem is in its infancy, and most of the research just considers the next day aircraft assignment. However, in practice the airline engineering personnel generally makes aircraft plans every week. Although conducting aircraft assignment daily simplifies the problem and greatly reduces the constraints involved, the assignment method can hardly capture the actual demand. Based on the process of flight planning of the domestic airlines, we transform the aircraft assignment problem into vehicle routing problem (VRP) and study the weekly flight assignment problem. This problem is a kind
Khan, Fouad
2016-01-01
K-means is one of the most widely used clustering algorithms in various disciplines, especially for large datasets. However the method is known to be highly sensitive to initial seed selection of cluster centers. K-means++ has been proposed to overcome this problem and has been shown to have better accuracy and computational efficiency than k-means. In many clustering problems though -such as when classifying georeferenced data for mapping applications- standardization of clustering methodolo...
Institute of Scientific and Technical Information of China (English)
唐苏妍; 梅珊; 朱一凡; 雷永林; 李群
2011-01-01
Based on the description of distributed weapon target assignment (DWTA) , the contract net protocol (CNP) is expended from six aspects: task announcement conditions, the strategies of task announcement,bidding and bid evaluation between managers and contractors, extension of the protocol and contract types, and an extended CNP (ECNP) based DWTA architecture is designed for networked air defense missile systems (NADMS). After that, a DWTA algorithm based on the ECNP is presented, and a comparison is made between CNP based and ECNP based DWTA algorithm in the utility of NADMS, remotes firing times, and number of communications through an operational scenario. Simulation results demonstrate the effectiveness and superiority of the proposed algorithm.%以网络化防空导弹体系为研究背景,对分布式武器目标分配(dynamic weapon target assignment,DWTA)问题进行了描述,从招标条件、招标策略、投标策略、中标策略、协议机制及合同类型六个方面对合同网协议(contract net protocol,CNP)进行了扩展,构建了基于扩展CNP协同机制的DWTA体系结构,提出了基于扩展CNP的DWTA算法.通过某一作战想定,分别从整体效能变化、协同交战次数和通信量三方面对基于CNP和扩展CNP的DWTA算法进行了比较,实验结果证明了后者的有效性和优越性.
Lin, Frank Yeong-Sung; Hsiao, Chiu-Han; Lin, Leo Shih-Chang; Wen, Yean-Fu
2013-01-01
Recent advance in wireless sensor network (WSN) applications such as the Internet of Things (IoT) have attracted a lot of attention. Sensor nodes have to monitor and cooperatively pass their data, such as temperature, sound, pressure, etc. through the network under constrained physical or environmental conditions. The Quality of Service (QoS) is very sensitive to network delays. When resources are constrained and when the number of receivers increases rapidly, how the sensor network can provide good QoS (measured as end-to-end delay) becomes a very critical problem. In this paper; a solution to the wireless sensor network multicasting problem is proposed in which a mathematical model that provides services to accommodate delay fairness for each subscriber is constructed. Granting equal consideration to both network link capacity assignment and routing strategies for each multicast group guarantees the intra-group and inter-group delay fairness of end-to-end delay. Minimizing delay and achieving fairness is ultimately achieved through the Lagrangean Relaxation method and Subgradient Optimization Technique. Test results indicate that the new system runs with greater effectiveness and efficiency. PMID:23493123
Directory of Open Access Journals (Sweden)
Yean-Fu Wen
2013-03-01
Full Text Available Recent advance in wireless sensor network (WSN applications such as the Internet of Things (IoT have attracted a lot of attention. Sensor nodes have to monitor and cooperatively pass their data, such as temperature, sound, pressure, etc. through the network under constrained physical or environmental conditions. The Quality of Service (QoS is very sensitive to network delays. When resources are constrained and when the number of receivers increases rapidly, how the sensor network can provide good QoS (measured as end-to-end delay becomes a very critical problem. In this paper; a solution to the wireless sensor network multicasting problem is proposed in which a mathematical model that provides services to accommodate delay fairness for each subscriber is constructed. Granting equal consideration to both network link capacity assignment and routing strategies for each multicast group guarantees the intra-group and inter-group delay fairness of end-to-end delay. Minimizing delay and achieving fairness is ultimately achieved through the Lagrangean Relaxation method and Subgradient Optimization Technique. Test results indicate that the new system runs with greater effectiveness and efficiency.
Otero, José; Palacios, Ana; Suárez, Rosario; Junco, Luis; Couso, Inés; Sánchez, Luciano
2014-01-01
When selecting relevant inputs in modeling problems with low quality data, the ranking of the most informative inputs is also uncertain. In this paper, this issue is addressed through a new procedure that allows the extending of different crisp feature selection algorithms to vague data. The partial knowledge about the ordinal of each feature is modelled by means of a possibility distribution, and a ranking is hereby applied to sort these distributions. It will be shown that this technique makes the most use of the available information in some vague datasets. The approach is demonstrated in a real-world application. In the context of massive online computer science courses, methods are sought for automatically providing the student with a qualification through code metrics. Feature selection methods are used to find the metrics involved in the most meaningful predictions. In this study, 800 source code files, collected and revised by the authors in classroom Computer Science lectures taught between 2013 and 2014, are analyzed with the proposed technique, and the most relevant metrics for the automatic grading task are discussed. PMID:25114967
Directory of Open Access Journals (Sweden)
José Otero
2014-01-01
Full Text Available When selecting relevant inputs in modeling problems with low quality data, the ranking of the most informative inputs is also uncertain. In this paper, this issue is addressed through a new procedure that allows the extending of different crisp feature selection algorithms to vague data. The partial knowledge about the ordinal of each feature is modelled by means of a possibility distribution, and a ranking is hereby applied to sort these distributions. It will be shown that this technique makes the most use of the available information in some vague datasets. The approach is demonstrated in a real-world application. In the context of massive online computer science courses, methods are sought for automatically providing the student with a qualification through code metrics. Feature selection methods are used to find the metrics involved in the most meaningful predictions. In this study, 800 source code files, collected and revised by the authors in classroom Computer Science lectures taught between 2013 and 2014, are analyzed with the proposed technique, and the most relevant metrics for the automatic grading task are discussed.
Hilburn, Jeremy
2015-01-01
In this qualitative collective case study with 6 high school civics teachers, I found that using an asset-based approach to teaching civics for, with, and by immigrant students enriched teaching and learning for immigrant and native-born students, although participants missed some opportunities for deeper exploration. I used a combined theoretical…
Assigning proctors to exams with scatter search
Ramalhinho-Louren??o, Helena; Mart??, Rafael; Laguna, Manuel
2001-01-01
In this paper we present an algorithm to assign proctors to exams. This NP-hard problem is related to the generalized assignment problem with multiple objectives. The problem consists of assigning teaching assistants to proctor final exams at a university. We formulate this problem as a multiobjective integer program (IP) with a preference function and a workload-fairness function. We then consider also a weighted objective that combines both functions. We develop a scatter ...
Directory of Open Access Journals (Sweden)
Victor F. Suarez Chilma
2013-03-01
Full Text Available The objective of this proposal is to implement a school day agenda focused on the learning rhythms of students of elementary and secondary schools using a genetic algorithm. The methodology of this proposal takes into account legal requirements and constraints on the assignment of teachers and classrooms in public educational institutions in Colombia. In addition, this proposal provides a set of constraints focused on cognitive rhythms and subjects are scheduled at the most convenient times according to the area of knowledge. The genetic algorithm evolves through a process of mutation and selection and builds a total solution based on the best solutions for each group. Sixteen groups in a school are tested and the results of class schedule assignments are presented. The quality of the solution obtained through the established approach is validated by comparing the results to the solutions obtained using another algorithm.El objetivo de esta propuesta es implementar un horario escolar que tenga en cuenta los ritmos de aprendizaje en los estudiantes de educación primaria y secundaria, utilizando un algoritmo genético. La metodología considera los requerimientos legales y las restricciones necesarias para la asignación de maestros y aulas en instituciones educativas públicas de Colombia. Adicionalmente, se establecen un conjunto de restricciones relacionadas con el enfoque en los ritmos cognitivos, determinando las horas de la jornada en las que es más conveniente la ubicación de ciertas materias de acuerdo al área del conocimiento al que pertenecen. El algoritmo genético evoluciona mediante un proceso de mutación y selección, a través del cual se construye una solución completa a partir de la búsqueda de las mejores soluciones por grupo. Se presentan los resultados de las pruebas realizadas para la asignación de una institución con 16 grupos. La calidad de las soluciones obtenidas de acuerdo al enfoque establecido es validada
Institute of Scientific and Technical Information of China (English)
王永泉; 罗建军
2014-01-01
对多UCAV协同攻击目标分配问题进行了研究。以收益指标、消耗指标及航程指标为准则建立数学模型，采用改进的萤火虫优化算法对模型进行求解；对基本萤火虫优化算法进行了改进，给出了新的萤火虫更新策略，引入了局部搜索及全局信息交换机制，并将萤火虫优化算法与混合蛙跳算法融合，实现了多智能群体共同进化，提出了一种基于多群体改进萤火虫优化算法的UCAV目标分配算法；针对UCAV协同攻击决策特点，设计了萤火虫离散编码方式，最终得到多UCAV协同攻击最优分配方案。仿真结果表明，多群体萤火虫优化算法能够稳定快速地给出目标分配最优方案。%A target allocation algorithm based on multi-intelligence improved glowworm swarm optimization ( MIG-SO) algorithm is proposed. A model of decision-making is built up by taking benefit index, loss index and range in-dex as the criteria, and the MIGSO is used to solve the model. Finally the optimal allocation scheme for multi-air-craft cooperative attacking is gotten. According to the characteristics of UCAV attack decision making, a special coding for firefly particle and firefly update strategy is presented. With shuffled frog leaping algorithm (SFLA), glowworms are divided into different ethnic groups, and local search and global information exchange method im-proves GSO performance. SFLA is also combined with GSO, which realize the co-evolution of the two kinds of groups. The simulation results shows that the MIGSO algorithm can give the optimal target assignment solution quickly and effectively.
Institute of Scientific and Technical Information of China (English)
孔凡光; 何建华; 唐奎
2013-01-01
Based on the problem of target assignment in BVR(Beyond Visual Range)air combat, a Shuffled Frog Leaping Algo-rithm(SFLA)and Ant Colony Algorithm(ACA)fusion is presented. A model of decision-making in BVR is built up by taking target threat evaluation as the criterion. According to the characteristic of BVR, a special coding process for frog is presented. An improved SFLA based on mutation idea in Differential Evolution(DE)is proposed, and the aberrance operator for ACA is embedded to reduce the search time. Since shuffled frog leaping algorithm has the capability of taking a global searching rapidly and ant colony algorithm has the positive feedback feature, the fusion algorithms use the SFLA to build optimized group at its initial stage, and then use ACA to search the exact answer at the later stage. With Matlab, simulations are implemented. The simu-lation results show that this method can give a reasonable target allocation plan effectively.%针对未来超视距条件下的多机协同空战，提出了一种基于混合蛙跳融合蚁群算法的目标分配方法。以目标威胁评估值为准则建立空战决策模型，根据空战决策特点对青蛙粒子进行特殊编码处理，在混合蛙跳算法局部搜索过程中加入自适应差分扰动机制、在蚁群算法中引入变异算子以减少算法搜索时间。融合算法利用混合蛙跳算法快速的全局搜索能力生成初始优化解群，利用蚁群算法具有正反馈的特点求精确解，利用Matlab仿真。仿真结果表明该方法能够快速有效地给出合理的目标分配方案。
Chen, Jiahong; Lu, Ning; Shen, Xing; Tang, Qiushi; Zhang, Chijian; Xu, Jun; Sun, Yuanming; Huang, Xin-An; Xu, Zhenlin; Lei, Hongtao
2016-04-01
A polyclonal antibody against the quinolone drug pazufloxacin (PAZ) but with surprisingly broad specificity was raised to simultaneously detect 24 quinolones (QNs). The developed competitive indirect enzyme-linked immunosorbent assay (ciELISA) exhibited limits of detection (LODs) for the 24 QNs ranging from 0.45 to 15.16 ng/mL, below the maximum residue levels (MRLs). To better understand the obtained broad specificity, a genetic algorithm with linear assignment of hypermolecular alignment of data sets (GALAHAD) was used to generate the desired pharmacophore model and superimpose the QNs, and then advanced comparative molecular field analysis (CoMFA) and advanced comparative molecular similarity indices analysis (CoMSIA) models were employed to study the three-dimensional quantitative structure-activity relationship (3D QSAR) between QNs and the antibody. It was found that the QNs could interact with the antibody with different binding poses, and cross-reactivity was mainly positively correlated with the bulky substructure containing electronegative atom at the 7-position, while it was negatively associated with the large bulky substructure at the 1-position of QNs. PMID:26982746
Institute of Scientific and Technical Information of China (English)
吴东华; 夏洪山
2012-01-01
A new method based on multi-objective fuzzy linear optimization algorithm for fleet assignment problem was proposed. The method applied fuzzy theory to optimization concept, turning the fuzzy multi-objective optimization mathematical model with the objective of the balance of aircraft flight time, the balance of the numbers of the aircraft movements and least waiting time first to a linear programming problem according to the maximum degree of membership. The result of the experiment shows the method can rapidly get the desired results.%提出了一种基于多目标模糊线性规划法解决飞机排班问题的新算法.该算法将模糊理论与最优化概念相结合,根据最大隶属度原则,将以飞机飞行时间均衡优先、飞机起降次数均衡优先、飞机等待时间最少优先为目标函数的多目标模糊线性规划数学模型转化为一般的线性规划问题进行求解.实验数据表明,该算法可行、有效,步骤简捷,计算量小,能得到理想的结果.
Foot, G. E.
1992-01-01
To equip electrical engineering students with common and transferable work skills, a program of integrative assignments was created to develop communication and teamwork skills. Discusses assignment components; the log book, a personal account of each assignment; assessment; conversion of "common skills" to competence statements, and performance…
Energy Technology Data Exchange (ETDEWEB)
Zeng Jianyang [Duke University, Department of Computer Science (United States); Zhou Pei [Duke University Medical Center, Department of Biochemistry (United States); Donald, Bruce Randall [Duke University, Department of Computer Science (United States)
2011-08-15
One bottleneck in NMR structure determination lies in the laborious and time-consuming process of side-chain resonance and NOE assignments. Compared to the well-studied backbone resonance assignment problem, automated side-chain resonance and NOE assignments are relatively less explored. Most NOE assignment algorithms require nearly complete side-chain resonance assignments from a series of through-bond experiments such as HCCH-TOCSY or HCCCONH. Unfortunately, these TOCSY experiments perform poorly on large proteins. To overcome this deficiency, we present a novel algorithm, called Nasca (NOE Assignment and Side-Chain Assignment), to automate both side-chain resonance and NOE assignments and to perform high-resolution protein structure determination in the absence of any explicit through-bond experiment to facilitate side-chain resonance assignment, such as HCCH-TOCSY. After casting the assignment problem into a Markov Random Field (MRF), Nasca extends and applies combinatorial protein design algorithms to compute optimal assignments that best interpret the NMR data. The MRF captures the contact map information of the protein derived from NOESY spectra, exploits the backbone structural information determined by RDCs, and considers all possible side-chain rotamers. The complexity of the combinatorial search is reduced by using a dead-end elimination (DEE) algorithm, which prunes side-chain resonance assignments that are provably not part of the optimal solution. Then an A* search algorithm is employed to find a set of optimal side-chain resonance assignments that best fit the NMR data. These side-chain resonance assignments are then used to resolve the NOE assignment ambiguity and compute high-resolution protein structures. Tests on five proteins show that Nasca assigns resonances for more than 90% of side-chain protons, and achieves about 80% correct assignments. The final structures computed using the NOE distance restraints assigned by Nasca have backbone RMSD 0
Institute of Scientific and Technical Information of China (English)
赵军; 陈祥光; 刘春涛; 余向明; 岳彬
2011-01-01
为提高油料保障系统中信息采集的实时性和能量的高效性,使网关及时检测到移动设备的状态,降低无线网络间的干扰,提高网络的容量.以军用机场加油车为研究对象,提出了适用于快速移动节点的集中式信道分配算法和功率分级的能量控制方法.在无线网络节点上安装两个工作在不同频道上的网络接口,通过控制协商动态的切换数据信道,平衡网络负载,以增加总的带宽.实验结果表明,采用3条数据信道便可实现信道的集中式分配和发送功率的分级控制,有效地扩展了网络的容量和提高能量的高效性.%By investigating the working process of tanker trucks in a military airport, this paper proposes a centralized channel assignment algorithm and a power rating control method for fast-moving nodes to improve the real-time property and energy efficiency of the information collection, detect the state of mobile devices promptly, reduce interference between wireless networks and to increase network capacity in oil security systems. Considering the fact that IEEE 802. 11 wireless LAN standard defines a number of non-overlapping channels which could be used at the same time, two wireless network interfaces operating on different channels could be installed to every node. Through the negotiation on the control channel and switching the data channel dynamically, the balance of network loads could be fulfilled so as to increase the total bandwidth. Simulation and application results demonstrate that, only three data channels is needed to realize the centralized channel assignment and the power rating control, and the network capacity and energy efficiency could be improved effectively.
Fleet Assignment Using Collective Intelligence
Antoine, Nicolas E.; Bieniawski, Stefan R.; Kroo, Ilan M.; Wolpert, David H.
2004-01-01
Product distribution theory is a new collective intelligence-based framework for analyzing and controlling distributed systems. Its usefulness in distributed stochastic optimization is illustrated here through an airline fleet assignment problem. This problem involves the allocation of aircraft to a set of flights legs in order to meet passenger demand, while satisfying a variety of linear and non-linear constraints. Over the course of the day, the routing of each aircraft is determined in order to minimize the number of required flights for a given fleet. The associated flow continuity and aircraft count constraints have led researchers to focus on obtaining quasi-optimal solutions, especially at larger scales. In this paper, the authors propose the application of this new stochastic optimization algorithm to a non-linear objective cold start fleet assignment problem. Results show that the optimizer can successfully solve such highly-constrained problems (130 variables, 184 constraints).
Analyzing Tenant Assignment Policies
Kaplan, Edward H.
1987-01-01
This paper discusses two popular policies used by housing authorities to assign applicants to housing projects: first available unit and priority assignment policies. The policies are compared according to their abilities to integrate housing projects, applicant assignment probabilities, and mean waiting times. Our results show that priority policies can successfully integrate public housing projects while first available unit policies can exacerbate segregation. These results support the rep...
A parametric visualization software for the assignment problem
Directory of Open Access Journals (Sweden)
Papamanthou Charalampos
2005-01-01
Full Text Available In this paper we present a parametric visualization software used to assist the teaching of the Network Primal Simplex Algorithm for the assignment problem (AP. The assignment problem is a special case of the balanced transportation problem. The main functions of the algorithm and design techniques are also presented. Through this process, we aim to underline the importance and necessity of using such educational methods in order to improve the teaching of Computer Algorithms.
Genetic spectrum assignment model with constraints in cognitive radio networks
Directory of Open Access Journals (Sweden)
Fang Ye
2011-06-01
Full Text Available The interference constraints of genetic spectrum assignment model in cognitive radio networks are analyzed in this paper. An improved genetic spectrum assignment model is proposed. The population of genetic algorithm is divided into two sets, the feasible spectrum assignment strategies and the randomly updated spectrum assignment strategies. The penalty function is added to the utility function to achieve the spectrum assignment strategy that satisfies the interference constraints and has better fitness. The proposed method is applicable in both the genetic spectrum assignment model and the quantum genetic spectrum assignment mode. It can ensure the randomness of partial chromosomes in the population to some extent, and reduce the computational complexity caused by the constraints-free procedure after the update of population. Simulation results show that the proposed method can achieve better performance than the conventional genetic spectrum assignment model and quantum genetic spectrum assignment model
Historical WBAN ID Assignments
National Oceanic and Atmospheric Administration, Department of Commerce — 4"x6" index cards represent the first written assignments of Weather Bureau Army Navy (WBAN) station identifier numbers by the National Climatic Data Center....
Generalised Assignment Matrix Methodology in Linear Programming
Jerome, Lawrence
2012-01-01
Discrete Mathematics instructors and students have long been struggling with various labelling and scanning algorithms for solving many important problems. This paper shows how to solve a wide variety of Discrete Mathematics and OR problems using assignment matrices and linear programming, specifically using Excel Solvers although the same…
Shibata, Kazuaki; Horio, Yoshihiko; Aihara, Kazuyuki
The quadratic assignment problem (QAP) is one of the NP-hard combinatorial optimization problems. An exponential chaotic tabu search using a 2-opt algorithm driven by chaotic neuro-dynamics has been proposed as one heuristic method for solving QAPs. In this paper we first propose a new local search, the double-assignment method, suitable for the exponential chaotic tabu search, which adopts features of the Lin-Kernighan algorithm. We then introduce chaotic neuro-dynamics into the double-assignment method to propose a novel exponential chaotic tabu search. We further improve the proposed exponential chaotic tabu search with the double-assignment method by enhancing the effect of chaotic neuro-dynamics.
Weapon Target Assignment with Combinatorial Optimization Techniques
Directory of Open Access Journals (Sweden)
Asim Tokgöz
2013-07-01
Full Text Available Weapon Target Assignment (WTA is the assignment of friendly weapons to the hostile targets in order to protect friendly assets or destroy the hostile targets and considered as a NP-complete problem. Thus, it is very hard to solve it for real time or near-real time operational needs. In this study, genetic algorithm (GA, tabu search (TS, simulated annealing (SA and Variable Neighborhood Search (VNS combinatorial optimization techniques are applied to the WTA problem and their results are compared with each other and also with the optimized GAMS solutions. Algorithms are tested on the large scale problem instances. It is found that all the algorithms effectively converge to the near global optimum point(s (a good quality and the efficiency of the solutions (speed of solution might be improved according to the operational needs. VNS and SA solution qualities are better than both GA and TS.
Institute of Scientific and Technical Information of China (English)
刘万俊; 傅裕松; 翁兴伟
2012-01-01
To solve the mission assignment problem for MAV (Manned Aerial Vehicle) and multi-UAV (Unmanned Aerial Vehicle) in cooperation air combat. A DPSO (Discrete Particle Swarm Optimization) is put forward. The research is divided into three situation which includes that one UCAV is assigned one target, one UCAV is assigned two targets regardless of attack order and one UCAV is assigned two targets considering attack order. And then a new particle formation method is proposed. The risk return matrix and cost function of multi-mission assignment which combines air combat capability index and dominant function are designed. The simulation result shows that the arithmetic has good astringency and it has reference value for the Multi-mission assignment for MAV and multi-UAV in cooperation air combat.%针对有人机—无人机群协同空战目标分配问题,运用离散粒子群算法,分为1架UCAV分配1个目标,1架UCAV分配2个目标时不考虑攻击先后影响和考虑攻击先后影响3种情况进行了仿真研究,提出了一种新的粒子构造方法.综合考虑空战能力指数和优势函数,构造了收益风险矩阵和多目标分配的代价函数.仿真结果具有良好收敛性,对有人机—无人机群协同空战目标分配具有参考价值.
Hebert, Margaret; And Others
1991-01-01
Contains seven brief articles which offer assignments designed to help students perform job searches, write job application letters, answer difficult questions, write letters of resignation, alleviate fears of public speaking, use the interview effectively in the business communication, and develop listening skills. (PRA)
Graph-Based Dynamic Assignment Of Multiple Processors
Hayes, Paul J.; Andrews, Asa M.
1994-01-01
Algorithm-to-architecture mapping model (ATAMM) is strategy minimizing time needed to periodically execute graphically described, data-driven application algorithm on multiple data processors. Implemented as operating system managing flow of data and dynamically assigns nodes of graph to processors. Predicts throughput versus number of processors available to execute given application algorithm. Includes rules ensuring application algorithm represented by graph executed periodically without deadlock and in shortest possible repetition time. ATAMM proves useful in maximizing effectiveness of parallel computing systems.
File Assignment Policy in Network Storage System
Institute of Scientific and Technical Information of China (English)
Cao Qiang; Xie Chang-sheng
2003-01-01
Network storage increase capacity and scalability of storage system, data availability and enables the sharing of data among clients. When the developing network technology reduce performance gap between disk and network, however, mismatched policies and access pattern can significantly reduce network storage performance. So the strategy of data placement in system is an important factor that impacts the performance of overall system. In this paper, the two algorithms of file assignment are presented. One is Greed partition that aims at the load balance across all NADs (Network Attached Disk). The other is Sort partition that tries to minimize variance of service time in each NAD. Moreover, we also compare the performance of our two algorithms in practical environment. Our experimental results show that when the size distribution (load characters) of all assigning files is closer and larger, Sort partition provides consistently better response times than Greedy algorithm. However, when the range of all assigning files is wider, there are more small files and access rate is higher, the Greedy algorithm has superior performance in compared with the Sort partition in off-line.
International Nuclear Information System (INIS)
July 1999 The Netherlands Electricity Regulatory Service (DtE) published an Information and Consultation Document on the subject of 'Price Cap Regulation in the Dutch Electricity Sector'. By means of price cap regulation tariffs are determined such that businesses are stimulated continuously to organize their total processes and operation as efficient as possible. In the consultation document a large number of questions with respect to the future organization and planning of the system of economic regulation of the electricity sector in the Netherlands can be found. Many reactions and answers were received, compiled and analyzed. The results are presented in the main report, which forms the framework for the DtE to shape the economic regulation of the Dutch electricity sector. In this background document attention is paid to a method to determine the Regulatory Asset Base (RAB)
Graphical interpretation of Boolean operators for protein NMR assignments
Verdegem, Dries; Dijkstra, Klaas; Hanoulle, Xavier; Lippens, Guy
2008-01-01
We have developed a graphics based algorithm for semi-automated protein NMR assignments. Using the basic sequential triple resonance assignment strategy, the method is inspired by the Boolean operators as it applies "AND"-, "OR"- and "NOT"-like operations on planes pulled out of the classical three-
Three results on frequency assignment in linear cellular networks
Czech Academy of Sciences Publication Activity Database
Chrobak, M.; Sgall, Jiří
2010-01-01
Roč. 411, č. 1 (2010), s. 131-137. ISSN 0304-3975 R&D Projects: GA MŠk(CZ) 1M0545; GA AV ČR IAA100190902 Keywords : frequency assignment * approximation algorithms * online algorithms Subject RIV: BA - General Mathematics Impact factor: 0.838, year: 2010 http://www.sciencedirect.com/science/article/pii/S0304397509006574
Fast assignment reduction in inconsistent incomplete decision systems
Institute of Scientific and Technical Information of China (English)
Min Li; Shaobo Deng; Shengzhong Feng; Jianping Fan
2014-01-01
This paper focuses on fast algorithm for computing the assignment reduct in inconsistent incomplete decision systems. It is quite inconvenient to judge the assignment reduct directly ac-cording to its definition. We propose the judgment theorem for the assignment reduct in the inconsistent incomplete decision system, which greatly simplifies judging this type reduct. On such basis, we derive a novel attribute significance measure and construct the fast assignment reduction algorithm (F-ARA), intended for com-puting the assignment reduct in inconsistent incomplete decision systems. Final y, we make a comparison between F-ARA and the discernibility matrix-based method by experiments on 13 Univer-sity of California at Irvine (UCI) datasets, and the experimental results prove that F-ARA is efficient and feasible.
Flexible taxonomic assignment of ambiguous sequencing reads
Directory of Open Access Journals (Sweden)
Jansson Jesper
2011-01-01
Full Text Available Abstract Background To characterize the diversity of bacterial populations in metagenomic studies, sequencing reads need to be accurately assigned to taxonomic units in a given reference taxonomy. Reads that cannot be reliably assigned to a unique leaf in the taxonomy (ambiguous reads are typically assigned to the lowest common ancestor of the set of species that match it. This introduces a potentially severe error in the estimation of bacteria present in the sample due to false positives, since all species in the subtree rooted at the ancestor are implicitly assigned to the read even though many of them may not match it. Results We present a method that maps each read to a node in the taxonomy that minimizes a penalty score while balancing the relevance of precision and recall in the assignment through a parameter q. This mapping can be obtained in time linear in the number of matching sequences, because LCA queries to the reference taxonomy take constant time. When applied to six different metagenomic datasets, our algorithm produces different taxonomic distributions depending on whether coverage or precision is maximized. Including information on the quality of the reads reduces the number of unassigned reads but increases the number of ambiguous reads, stressing the relevance of our method. Finally, two measures of performance are described and results with a set of artificially generated datasets are discussed. Conclusions The assignment strategy of sequencing reads introduced in this paper is a versatile and a quick method to study bacterial communities. The bacterial composition of the analyzed samples can vary significantly depending on how ambiguous reads are assigned depending on the value of the q parameter. Validation of our results in an artificial dataset confirm that a combination of values of q produces the most accurate results.
Task assignment algorithm of multi-AUV based on self-organizing map%多自治水下机器人多任务分配的自组织算法
Institute of Scientific and Technical Information of China (English)
朱大奇; 李欣; 颜明重
2012-01-01
针对自治水下机器人（AUV）研究中的多机器人多任务分配问题,提出一种基于自组织映射（SOM）神经网络的多AUV多目标分配策略.将目标点的位置坐标作为SOM神经网络的输入向量进行自组织竞争计算,输出为对应的AUV机器人,从而控制一组AUV在不同的地点完成不同的任务,使机器人按照优化的路径规则到达指定的目标位置.为了表明所提出算法的有效性,给出了二维、三维作业环境中的仿真实验结果.%Aiming to the task assignment issue of multi-AUV(autonomous underwater vehicles) system, a self-organizing map(SOM) neural network based strategy of task assignment of multi-AUV and multi-objective is presented. Targets' locations are set as input vectors of SOM neural network. Then self-organizing competitive calculations are carded out. Its output vectors are the corresponding AUV robots' locations, so that a group of AUVs can be controlled to complete different tasks in different locations, and the robots can reach the designated targets in optimized paths. Simulation results in two-dimensional and three-dimensional working environments show the effectiveness of the proposed method.
Three results on frequency assignment in linear cellular networks
Czech Academy of Sciences Publication Activity Database
Chrobak, M.; Sgall, Jiří
Berlin: Springer, 2009 - (Goldbert, A.; Zhou, Y.), s. 129-139. (Lecture Notes in Computer Science. 5564). ISBN 978-3-642-02157-2. [5th International Conference on Algorithmic Aspects in Information and Management. San Francisco (US), 15.06.2009-17.06.2009] R&D Projects: GA MŠk(CZ) 1M0545; GA AV ČR IAA100190902 Keywords : frequency assignment * approximation algorithms * online algorithms Subject RIV: IN - Informatics, Computer Science
Institute of Scientific and Technical Information of China (English)
陈香
2013-01-01
In order to effectively solve Arrange fair and objective interview to interview members of the Group ,in this pa-per ,the issues were discussed ,establish its mathematical model ,the model is a complex non -linear integer programming problem .Proposed a packing code ,simulated annealing genetic ,multi-point crossover ,the search for variability in the field of genetic algorithms to solve the mathematical model ,And with an example :30 experts to interview 300 students each interview group of four experts ,with the genetic algorithm to solve the calculation of the examples ,show that the improved genetic algorithm can be efficient for solving the approximate optimal solution of problem solving can meet the job interview fair and reasonable arrangements required to achieve results .%为了有效求解如何安排面试专家组成员工作使面试公正客观的问题，建立面试安排工作数学模型，该模型为复杂的非线性整数规划问题。提出一种装箱编码、模拟退火遗传、多点交叉、领域搜索变异的遗传算法对数学模型进行求解，并以一个30名专家对300名学生进行面试，且每个面试组4名专家的例子用遗传算法进行求解计算。结果表明，改进后的遗传算法能高效求解出问题的近似最优解，求解结果能满足面试工作安排所提出的要求。
Institute of Scientific and Technical Information of China (English)
Huang; Ling; Liu; Yang; Xu; Jianfeng
2015-01-01
With the transformation of the Chinese economy from an extensive growth to intensive development, city development is also gradually turning from incremental construction to stock management. Community, as a basic unit of human settlements, is an important platform to build and improve the social governance capability. In 2013, Shiyoulu Jiedao Offi ce of Yuzhong District led the 1st urban community development planning, which was a milestone of Chongqing’s city regeneration and governance innovation. This paper focuses on two key issues: how to understand the community values and make the community development planning based on the above, and how to integrate with the local forces so that the community development planning can be integrated into the action plan. Combined with the practice of Minlecun Community Development Planning, using the concept of asset-based community development, a comprehensive survey is conducted on community assets(including three aspects of physical, human, and social capital), and a community comprehensive planning strategy is formulated which covers two parts: the optimization of community spaces and the upgrading of community governance. The paper explores the local-based community planning theories and methods from such aspects as value attitude, public participation, role transformation of urban planners, and others.
Solving multiconstraint assignment problems using learning automata.
Horn, Geir; Oommen, B John
2010-02-01
This paper considers the NP-hard problem of object assignment with respect to multiple constraints: assigning a set of elements (or objects) into mutually exclusive classes (or groups), where the elements which are "similar" to each other are hopefully located in the same class. The literature reports solutions in which the similarity constraint consists of a single index that is inappropriate for the type of multiconstraint problems considered here and where the constraints could simultaneously be contradictory. This feature, where we permit possibly contradictory constraints, distinguishes this paper from the state of the art. Indeed, we are aware of no learning automata (or other heuristic) solutions which solve this problem in its most general setting. Such a scenario is illustrated with the static mapping problem, which consists of distributing the processes of a parallel application onto a set of computing nodes. This is a classical and yet very important problem within the areas of parallel computing, grid computing, and cloud computing. We have developed four learning-automata (LA)-based algorithms to solve this problem: First, a fixed-structure stochastic automata algorithm is presented, where the processes try to form pairs to go onto the same node. This algorithm solves the problem, although it requires some centralized coordination. As it is desirable to avoid centralized control, we subsequently present three different variable-structure stochastic automata (VSSA) algorithms, which have superior partitioning properties in certain settings, although they forfeit some of the scalability features of the fixed-structure algorithm. All three VSSA algorithms model the processes as automata having first the hosting nodes as possible actions; second, the processes as possible actions; and, third, attempting to estimate the process communication digraph prior to probabilistically mapping the processes. This paper, which, we believe, comprehensively reports the
Interactive Assignments for Online Students
Directory of Open Access Journals (Sweden)
Pam Lowry
2009-04-01
Full Text Available Students can experience first hand through interactive assignments what is involved in teaching an online course. Most students develop a whole new appreciation for the student learning process. Faculty are beginning to realize that online instruction is more than a series of readings posted to a course management system. This paper summarizes the faculty member's instructional strategies involved when creating student interaction assignments. The paper also summarizes the assignments, discussion board, and trends in education from the student's perspective. In summary, it concludes with the faculty's overall perspective concerning these assignments and how the assignments could be more effective for the student.
Institute of Scientific and Technical Information of China (English)
赵金宝; 邓卫; 谢秋峰
2011-01-01
路径的感知时间主要受定量和随机两方面因素的影响．在实际的交通网络中，由于时间价值观的不同，道路使用者会根据习惯、偏好、信息而对出行时间、费用、道路拥挤等诸多影响因素做出不同的反应。本文通过综合考虑定量和随机两方面因素的影响效应，建立了基于感知时间的交通分配模型，设计了求解该模型的延迟加载算法。最后结合算例验证了算法的有效性．%The perception time of a path was mainly affected by two factors： the deterministic and the stochastic. In an actual traffic network, for different road users have different acknowledges on the value of time, they react differently to travel time, travel cost and traffic congestion on the basic of their own habit, taste and information. By considering both the deterministic and stochastic effect factors, this paper described amathematicalmodel and it＇s solution algorithm based on perception time. An numerical carried out at the end of this paper to prove the effectiveness of this algorithm experiment was model and it＇s
Towards Automated Structure-Based NMR Resonance Assignment
Jang, Richard; Gao, Xin; Li, Ming
We propose a general framework for solving the structure-based NMR backbone resonance assignment problem. The core is a novel 0-1 integer programming model that can start from a complete or partial assignment, generate multiple assignments, and model not only the assignment of spins to residues, but also pairwise dependencies consisting of pairs of spins to pairs of residues. It is still a challenge for automated resonance assignment systems to perform the assignment directly from spectra without any manual intervention. To test the feasibility of this for structure-based assignment, we integrated our system with our automated peak picking and sequence-based resonance assignment system to obtain an assignment for the protein TM1112 with 91% recall and 99% precision without manual intervention. Since using a known structure has the potential to allow one to use only N-labeled NMR data and avoid the added expense of using C-labeled data, we work towards the goal of automated structure-based assignment using only such labeled data. Our system reduced the assignment error of Xiong-Pandurangan-Bailey-Kellogg's contact replacement (CR) method, which to our knowledge is the most error-tolerant method for this problem, by 5 folds on average. By using an iterative algorithm, our system has the added capability of using the NOESY data to correct assignment errors due to errors in predicting the amino acid and secondary structure type of each spin system. On a publicly available data set for Ubiquitin, where the type prediction accuracy is 83%, we achieved 91% assignment accuracy, compared to the 59% accuracy that was obtained without correcting for typing errors.
An assignment based distributed resource manager
Poore, Aubrey B.; Danford, Scott; Hilt, Matthew J.
2010-04-01
The goal of this paper is to demonstrate the coordination in real-time of the operation of multiple sensors in such a way that those best-equipped for certain missions should perform those missions for the entire network, while other sensors fill in the gaps with their capabilities. The networked system of sensors must search, detect, track, classify, and engage targets of high value in a timely fashion. The information transmitted should be that which contributes the most toward achieving the performance goals (e.g., track accuracy, track completeness, and a consistent operational picture or single integrated air picture (SIAP)) subject to the network bandwidth constraints and the capabilities of the sensors. We present an overview of an assignment based sensor resource manager, a distributed algorithm for coordinating the assignment problem, and simulation results that validate this approach. While the assignment formulation and algorithms could include both sensor resource and bandwidth constraints with versions for single and multiple time periods, i.e., myopic and non-myopic, the distributed prototype formulation and algorithms developed for these experiments were restricted to the tasking of certain sensors to make measurements and transmit them over the network based on the current air picture. The number of measurements put on the network was controlled by limiting the number of sensors that could transmit measurements on each target. The communication loading was then measured to demonstrate that indeed one can design a distributed sensor resource manager capable of achieving the objectives of significantly reducing the communication loading and maintaining SIAP.
Dynamic traffic assignment techniques for general road networks
Han, S.
2000-01-01
Dynamic traffic assignment is widely recognised as being more useful to evaluate traffic management measures than is static counterpart, as it allows us to analyse how congestion forms and dissipates in time-varying conditions. In this thesis, both deterministic and stochastic dynamic assignments are modelled with a proper link performance function, and solved with efficient solution algorithms so that they give rise to high quality solutions. A deterministic dynamic assignm...
Solving Large Quadratic|Assignment Problems in Parallel
DEFF Research Database (Denmark)
Clausen, Jens; Perregaard, Michael
1997-01-01
Quadratic Assignment problems are in practice among the most difficult to solve in the class of NP-complete problems. The only successful approach hitherto has been Branch-and-Bound-based algorithms, but such algorithms are crucially dependent on good bound functions to limit the size of the space...... and recalculation of bounds between branchings when used in a parallel Branch-and-Bound algorithm. The algorithm has been implemented on a 16-processor MEIKO Computing Surface with Intel i860 processors. Computational results from the solution of a number of large QAPs, including the classical Nugent...
Towards an intelligent system for the automatic assignment of domains in globular proteins.
Sternberg, M J; Hegyi, H; Islam, S A; Luo, J; Russell, R B
1995-01-01
The automatic identification of protein domains from coordinates is the first step in the classification of protein folds and hence is required for databases to guide structure prediction. Most algorithms encode a single concept based and sometimes do not yield assignments that are consistent with the generally accepted perception. Our development of an automatic approach to identify reliably domains from protein coordinates is described. The algorithm is benchmarked against a manual identification of the domains in 284 representative protein chains. The first step is the domain assignment by distance (DAD) algorithm that considers the density of inter-residue contacts represented in a contact matrix. The algorithm yields 85% agreement with the manual assignment. The paper then considers how the reliability of these assignments could be evaluated. Finally the use of structural comparisons using the STAMP algorithm to validate domain assignment is reported on a test case. PMID:7584461
New Channel Assignment Method for Access Points in Wireless LANs
Directory of Open Access Journals (Sweden)
Mohammed Fawzi Al-Hunaity
2011-11-01
Full Text Available Wireless LANs topology communicates using radio frequencies. The number of these frequencies is limited and not enough to assign a special frequency for each Access Point, this means that the communication topology should use a e-use mechanism, which allows the system to assign the same frequency that assigned previously for another access point. In this paper, we suggest a method to assign frequency channels to access points in a Wireless LANs system. The goal of this paper is to reach the assignment that prevents interference between access points especially neighbor ones. We used Genetic Algorithm to work on this issue, it is considered as an Expert System and one of the main multi point search technique used in computing to solve optimization and search problems.
Graphical interpretation of Boolean operators for protein NMR assignments.
Verdegem, Dries; Dijkstra, Klaas; Hanoulle, Xavier; Lippens, Guy
2008-09-01
We have developed a graphics based algorithm for semi-automated protein NMR assignments. Using the basic sequential triple resonance assignment strategy, the method is inspired by the Boolean operators as it applies "AND"-, "OR"- and "NOT"-like operations on planes pulled out of the classical three-dimensional spectra to obtain its functionality. The method's strength lies in the continuous graphical presentation of the spectra, allowing both a semi-automatic peaklist construction and sequential assignment. We demonstrate here its general use for the case of a folded protein with a well-dispersed spectrum, but equally for a natively unfolded protein where spectral resolution is minimal. PMID:18762868
Algorithmic approach to diagram techniques
International Nuclear Information System (INIS)
An algorithmic approach to diagram techniques of elementary particles is proposed. The definition and axiomatics of the theory of algorithms are presented, followed by the list of instructions of an algorithm formalizing the construction of graphs and the assignment of mathematical objects to them. (T.A.)
A New Approach to Pointer Analysis for Assignments
Institute of Scientific and Technical Information of China (English)
HUANG Bo; ZANG Binyu; LI Jing; ZHU Chuanqi
2001-01-01
Pointer analysis is a technique to identify at compile-time the po tential values of the pointer expressions in a program, which promises significant benefits for optimizing and parallelizing compilers. In this paper, a new approach to pointer analysis for assignments is presented. In this approach, assignments are clas sified into three categories: pointer assignments, structure (union) assignments and normal assignments which don't affect the point-to information. Pointer analyses for these three kinds of assignments respectively make up the integrated algorithm. When analyzing a pointer assignment, a new method called expression expansion is used to calculate both the left targets and the right targets. The integration of recursive data structure analysis into pointer analysis is a significant originality of this paper, which uniforms the pointer analysis for heap variables and the pointer analysis for stack variables. This algorithm is implemented in Agassiz, an analyzing tool for C programs developed by Institute of Parallel Processing, Fudan University. Its accuracy and effectiveness are illustrated by experimental data.
76 FR 55880 - Recording Assignments
2011-09-09
..., depending on the date they were recorded. The public may also search patent and trademark assignment... United States Patent and Trademark Office Recording Assignments ACTION: Proposed collection; comment request. SUMMARY: The United States Patent and Trademark Office (USPTO), as part of its continuing...
Artificial Bee Colony Optimization for Multiobjective Quadratic Assignment Problem
Eleyan, Haytham Mohammed
2015-01-01
ABSTRACT: Excellent ability of swarm intelligence can be used to solve multi-objective combinatorial optimization problems. Bee colony algorithms are new swarm intelligence techniques inspired from the smart behaviors of real honeybees in their foraging behavior. Artificial bee colony optimization algorithm has recently been applied for difficult real-valued and combinational optimization problems. Multiobjective quadratic assignment problem (mQAP) is a well-known and hard combinational optim...
Institute of Scientific and Technical Information of China (English)
王剑
2011-01-01
For traditional monetary policy instruments,there are many problems about dealing with more and more complicated economic conditions.Asset-based reserve requirements（ABRR） are the feasible choice for monetary policy innovation,which has significant advant%传统的货币政策工具已难以应对日益复杂的经济形势,基于资产的准备金制度在宏观调控、结构调整以及宏观审慎监管等方面都具有显著优势,是货币政策工具创新的一个可行选择。本文对该制度的作用机理、优势与局限性等问题进行了研究,并结合我国货币调控的实践得出一些启示与思考。
Job Assignment with Multivariate Skills
Brilon, Stefanie
2010-01-01
This paper analyzes the job assignment problem faced by a firm when workers' skills are distributed along several dimensions and jobs require different skills to varying extent. I derive optimal assignment rules with and without slot constraints, and show that under certain circumstances workers may get promoted although in their new job they are expected to be less productive than in their old job. This can be interpreted as a version of the Peter Principle which states that workers get prom...
Improving load balance with flexibly assignable tasks
Energy Technology Data Exchange (ETDEWEB)
Pinar, Ali; Hendrickson, Bruce
2003-09-09
In many applications of parallel computing, distribution ofthe data unambiguously implies distribution of work among processors. Butthere are exceptions where some tasks can be assigned to one of severalprocessors without altering the total volume of communication. In thispaper, we study the problem of exploiting this flexibility in assignmentof tasks to improve load balance. We first model the problem in terms ofnetwork flow and use combinatorial techniques for its solution. Ourparametric search algorithms use maximum flow algorithms for probing on acandidate optimal solution value. We describe two algorithms to solve theassignment problem with \\logW_T and vbar P vbar probe calls, w here W_Tand vbar P vbar, respectively, denote the total workload and number ofproce ssors. We also define augmenting paths and cuts for this problem,and show that anyalgorithm based on augmenting paths can be used to findan optimal solution for the task assignment problem. We then consideracontinuous version of the problem, and formulate it as a linearlyconstrained optimization problem, i.e., \\min\\|Ax\\|_\\infty,\\; {\\rms.t.}\\;Bx=d. To avoid solving an intractable \\infty-norm optimization problem,we show that in this case minimizing the 2-norm is sufficient to minimizethe \\infty-norm, which reduces the problem to the well-studiedlinearly-constrained least squares problem. The continuous version of theproblem has the advantage of being easily amenable to parallelization.Our experiments with molecular dynamics and overlapped domaindecomposition applications proved the effectiveness of our methods withsignificant improvements in load balance. We also discuss how ourtechniques can be enhanced for heterogeneous systems.
A new heuristic for the quadratic assignment problem
Zvi Drezner
2002-01-01
We propose a new heuristic for the solution of the quadratic assignment problem. The heuristic combines ideas from tabu search and genetic algorithms. Run times are very short compared with other heuristic procedures. The heuristic performed very well on a set of test problems.
A Stone Resource Assignment Model under the Fuzzy Environment
Directory of Open Access Journals (Sweden)
Liming Yao
2012-01-01
to tackle a stone resource assignment problem with the aim of decreasing dust and waste water emissions. On the upper level, the local government wants to assign a reasonable exploitation amount to each stone plant so as to minimize total emissions and maximize employment and economic profit. On the lower level, stone plants must reasonably assign stone resources to produce different stone products under the exploitation constraint. To deal with inherent uncertainties, the object functions and constraints are defuzzified using a possibility measure. A fuzzy simulation-based improved simulated annealing algorithm (FS-ISA is designed to search for the Pareto optimal solutions. Finally, a case study is presented to demonstrate the practicality and efficiency of the model. Results and a comparison analysis are presented to highlight the performance of the optimization method, which proves to be very efficient compared with other algorithms.
Vannell, Eric C.; Kenny, Sean P.; Maghami, Peiman G.
1995-01-01
The erection and deployment of large flexible structures having thousands of degrees of freedom requires controllers based on new techniques of eigenvalue assignment that are computationally stable and more efficient. Scientists at NASA Langley Research Center have developed a novel and efficient algorithm for the eigenvalue assignment of large, time-invariant systems using full-state and output feedback. The objectives of this research were to improve upon the output feedback version of this algorithm, to produce a toolbox of MATLAB functions based on the efficient eigenvalue assignment algorithm, and to experimentally verify the algorithm and software by implementing controllers designed using the MATLAB toolbox on the phase 2 configuration of NASA Langley's controls-structures interaction evolutionary model, a laboratory model used to study space structures. Results from laboratory tests and computer simulations show that effective controllers can be designed using software based on the efficient eigenvalue assignment algorithm.
Improved Harmony Search with Chaos for Solving Linear Assignment Problems
Directory of Open Access Journals (Sweden)
Osama Abdel-Raouf
2014-04-01
Full Text Available This paper presents an improved version of a harmony meta-heuristic algorithm, (IHSCH, for solving the linear assignment problem. The proposed algorithm uses chaotic behavior to generation a candidate solution in a behavior similar to acoustic monophony. Numerical results show that the IHSCH is able to obtain the optimal results in comparison with traditional methods (the Hungarian method. However, the benefit of the proposed algorithm is its ability to obtain the optimal solution within less computation in comparison with the Hungarian method.
Adaptive protection algorithm and system
Hedrick, Paul [Pittsburgh, PA; Toms, Helen L [Irwin, PA; Miller, Roger M [Mars, PA
2009-04-28
An adaptive protection algorithm and system for protecting electrical distribution systems traces the flow of power through a distribution system, assigns a value (or rank) to each circuit breaker in the system and then determines the appropriate trip set points based on the assigned rank.
Who Benefits from Homework Assignments?
Ronning, Marte
2011-01-01
Using Dutch data on pupils in elementary school this paper is the first empirical study to analyze whether assigning homework has a heterogeneous impact on pupil achievement. Addressing potential biases by using a difference-in-difference approach, I find that the test score gap is larger in classes where everybody gets homework than in classes…
DEFF Research Database (Denmark)
Hougaard, Jens Leth; Moreno-Ternero, Juan D.; Østerdal, Lars Peter Raahave
2014-01-01
minimizing modification of the classic random priority method to solve this class of problems. We also provide some logical relations in our setting among standard axioms in the literature on assignment problems, and explore the robustness of our results to several extensions of our setting....
Probabilistic analysis of power assignments
Graaf, de Maurits; Manthey, Bodo
2014-01-01
A fundamental problem for wireless ad hoc networks is the assignment of suitable transmission powers to the wireless devices such that the resulting communication graph is connected. The goal is to minimize the total transmit power in order to maximize the life-time of the network. Our aim is a prob
Combined automated NOE assignment and structure calculation with CYANA
Energy Technology Data Exchange (ETDEWEB)
Güntert, Peter, E-mail: guentert@em.uni-frankfurt.de; Buchner, Lena [Goethe University Frankfurt am Main, Center for Biomolecular Magnetic Resonance, Institute of Biophysical Chemistry (Germany)
2015-08-15
The automated assignment of NOESY cross peaks has become a fundamental technique for NMR protein structure analysis. A widely used algorithm for this purpose is implemented in the program CYANA. It has been used for a large number of structure determinations of proteins in solution but was so far not described in full detail. In this paper we present a complete description of the CYANA implementation of automated NOESY assignment, which differs extensively from its predecessor CANDID by the use of a consistent probabilistic treatment, and we discuss its performance in the second round of the critical assessment of structure determination by NMR.
Combined automated NOE assignment and structure calculation with CYANA
International Nuclear Information System (INIS)
The automated assignment of NOESY cross peaks has become a fundamental technique for NMR protein structure analysis. A widely used algorithm for this purpose is implemented in the program CYANA. It has been used for a large number of structure determinations of proteins in solution but was so far not described in full detail. In this paper we present a complete description of the CYANA implementation of automated NOESY assignment, which differs extensively from its predecessor CANDID by the use of a consistent probabilistic treatment, and we discuss its performance in the second round of the critical assessment of structure determination by NMR
Stoughton, John W. (Inventor); Mielke, Roland V. (Inventor)
1990-01-01
Computationally complex primitive operations of an algorithm are executed concurrently in a plurality of functional units under the control of an assignment manager. The algorithm is preferably defined as a computationally marked graph contianing data status edges (paths) corresponding to each of the data flow edges. The assignment manager assigns primitive operations to the functional units and monitors completion of the primitive operations to determine data availability using the computational marked graph of the algorithm. All data accessing of the primitive operations is performed by the functional units independently of the assignment manager.
Routing and wavelength assignment for transparent optical networks with QoT estimation inaccuracies
Azodolmolky, Siamak; Pointurier, Yvan; Angelou, Marianna; Solé Pareta, Josep; Tomkos, Ioannis
2010-01-01
We show how inaccuracies of Quality of Transmission (QoT) estimations, caused by imperfect models and lack of monitors in transparent optical networks, can be mitigated using a novel routing and wavelength assignment algorithm. Peer Reviewed
Efficient Credit Assignment through Evaluation Function Decomposition
Agogino, Adrian; Turner, Kagan; Mikkulainen, Risto
2005-01-01
Evolutionary methods are powerful tools in discovering solutions for difficult continuous tasks. When such a solution is encoded over multiple genes, a genetic algorithm faces the difficult credit assignment problem of evaluating how a single gene in a chromosome contributes to the full solution. Typically a single evaluation function is used for the entire chromosome, implicitly giving each gene in the chromosome the same evaluation. This method is inefficient because a gene will get credit for the contribution of all the other genes as well. Accurately measuring the fitness of individual genes in such a large search space requires many trials. This paper instead proposes turning this single complex search problem into a multi-agent search problem, where each agent has the simpler task of discovering a suitable gene. Gene-specific evaluation functions can then be created that have better theoretical properties than a single evaluation function over all genes. This method is tested in the difficult double-pole balancing problem, showing that agents using gene-specific evaluation functions can create a successful control policy in 20 percent fewer trials than the best existing genetic algorithms. The method is extended to more distributed problems, achieving 95 percent performance gains over tradition methods in the multi-rover domain.
Permutation codes for the state assignment of fault tolerant sequential machines
Chen, M.; Trachtenberg, E. A.
1991-01-01
A new fault-tolerant state assignment method is suggested for synchronous sequential machines. It is assumed that the inputs are fault free and that for no input it is possible to reach all or most of the states, whose number may be fairly large. Error correcting codes for the state assignment are generated by permutations of a chosen linear code. A state assignment algorithm is developed and its computational complexity is estimated. Examples are given.
Automated protein backbone assignment using the projection-decomposition approach
International Nuclear Information System (INIS)
Spectral projection experiments by NMR in conjunction with decomposition analysis have been previously introduced for the backbone assignment of proteins; various pulse sequences as well as the behaviour with low signal-to-noise or chemical shift degeneracy have been illustrated. As a guide for routine applications of this combined tool, we provide here a systematic analysis on different types of proteins using welldefined run-time parameters. As a second result of this study, the backbone assignment module SHABBA was extensively rewritten and improved. Calculations on ubiquitin yielded again fully correct and nearly complete backbone and CHβ assignments. For the 128 residue long azurin, missing assignments mostly affect Hα and Hβ. Among the remaining backbone (plus Cβ) nuclei 97.5% could be assigned with 1.0% differences to a reference. Finally, the new SHABBA algorithm was applied to projections recorded for a yeast histone protein domain at room temperature, where the protein is subject to partial unfolding: this leads to unobservable resonances (about a dozen missing signals in a normal 15N-HSQC) and extensive degeneracy among the resonances. From the clearly observable residues, 97.5% of the backbone and CHβresonances could be assigned, of which only 0.8 % showed differences to published shifts. An additional study on the protein MMP20, which exhibits spectral difficulties to an even larger extent, explores the limitations of the approach.
Exploiting image registration for automated resonance assignment in NMR
International Nuclear Information System (INIS)
Analysis of protein NMR data involves the assignment of resonance peaks in a number of multidimensional data sets. To establish resonance assignment a three-dimensional search is used to match a pair of common variables, such as chemical shifts of the same spin system, in different NMR spectra. We show that by displaying the variables to be compared in two-dimensional plots the process can be simplified. Moreover, by utilizing a fast Fourier transform cross-correlation algorithm, more common to the field of image registration or pattern matching, we can automate this process. Here, we use sequential NMR backbone assignment as an example to show that the combination of correlation plots and segmented pattern matching establishes fast backbone assignment in fifteen proteins of varying sizes. For example, the 265-residue RalBP1 protein was 95.4 % correctly assigned in 10 s. The same concept can be applied to any multidimensional NMR data set where analysis comprises the comparison of two variables. This modular and robust approach offers high efficiency with excellent computational scalability and could be easily incorporated into existing assignment software
Analysis and Characterization of State AssignmentTechniques for Sequential Machines
Makki, R. Z.; Su, S.
1994-01-01
In this paper, we study the problem of state assignment as it relates to silicon area, propagation delay time and testability of finite state machines. The results of a study involving various FSM benchmarks show that the simple technique of one-hot encoding often produces better results than those attained by complex state assignment algorithms.
Institute of Scientific and Technical Information of China (English)
刘晓; 刘忠; 孙坤; 许江湖
2013-01-01
To increase the cooperative anti-missile capability of calculating the multi-object weapon target assignment (WTA), an improved algorithm for multi-objective particle swarm optimization (MOPSO) was proposed based on the multi-objective WTA model so as to establish a multi-objective mathematic model. The problems of MOPSO used in the WTA were solved, such as linear inequality constraints and swarm blind search. The calculation process was defined. Simulation experiments show that the improved MOPSO algorithm for WTA multi-object programming model obtains the non-inferior solutions to the Pareto front; the maximum value of the non-inferior solutions in adaptability which varies with the iteration number evolution is stable in convergence. The results show that the improved MOPSO is effective.%为提高协同反导时的多目标火力分配计算能力,首先建立了火力分配多目标数学模型；然后,针对火力分配多目标规划具有的线性不等式约束条件难以使用多目标粒子群优化算法、粒子群算法自身存在的盲目搜索等问题进行了改进,并明确了计算流程；最后,对算法进行了仿真实验,仿真实验表明:改进的多目标粒子群算法求解多目标火力分配规划模型得到的非劣解集可构成Pareto前端,且非劣解集的适应度最大值随迭代步数演变具有稳定的收敛性,验证了改进多目标粒子群算法的有效性.
Genetic Algorithm for Graph Colouring: Exploration of Galinier and Hao's algorithm
Celia A. Glass; Prügel-Bennett, Adam
2003-01-01
This paper examines the best current algorithm for solving the Chromatic Number Problem, due to Galinier and Hao (Journal of Combinatorial Optimization,1999, 3(4), pp 379-397). The algorithm combines a Genetic Algorithm with Tabu Search. We show that the algorithm remains powerful even if the Tabu Search component is eliminated, and explore the reasons for its success where other Genetic Algorithms have failed. In addition we propose a generalized algorithm for the Frequency Assignment Problem.
Who benefits from homework assignments?
Rønning, Marte
2008-01-01
Abstract: Using Dutch data on pupils in elementary school this paper is the first empirical study that analyzes whether assigning homework has an heterogeneous impact on pupil achievement. Addressing potential biases that arise from unobserved school quality, pupil selection by exploiting different methods, I find that the test score gap is larger in classes where everybody gets homework than in classes where nobody gets homework. More precisely pupils belonging to the upper part of the so...
Relevant Explanations: Allowing Disjunctive Assignments
Shimony, Solomon Eyal
2013-01-01
Relevance-based explanation is a scheme in which partial assignments to Bayesian belief network variables are explanations (abductive conclusions). We allow variables to remain unassigned in explanations as long as they are irrelevant to the explanation, where irrelevance is defined in terms of statistical independence. When multiple-valued variables exist in the system, especially when subsets of values correspond to natural types of events, the over specification problem, alleviated by inde...
DNATCO: assignment of DNA conformers at dnatco.org.
Černý, Jiří; Božíková, Paulína; Schneider, Bohdan
2016-07-01
The web service DNATCO (dnatco.org) classifies local conformations of DNA molecules beyond their traditional sorting to A, B and Z DNA forms. DNATCO provides an interface to robust algorithms assigning conformation classes called NTC: to dinucleotides extracted from DNA-containing structures uploaded in PDB format version 3.1 or above. The assigned dinucleotide NTC: classes are further grouped into DNA structural alphabet NTA: , to the best of our knowledge the first DNA structural alphabet. The results are presented at two levels: in the form of user friendly visualization and analysis of the assignment, and in the form of a downloadable, more detailed table for further analysis offline. The website is free and open to all users and there is no login requirement. PMID:27150812
Complexity and Approximation of a Geometric Local Robot Assignment Problem
Bonorden, Olaf; Degener, Bastian; Kempkes, Barbara; Pietrzyk, Peter
We introduce a geometric multi-robot assignment problem. Robots positioned in a Euclidean space have to be assigned to treasures in such a way that their joint strength is sufficient to unearth a treasure with a given weight. The robots have a limited range and thus can only be assigned to treasures in their proximity. The objective is to unearth as many treasures as possible. We investigate the complexity of several variants of this problem and show whether they are in {mathcal P} or are mathcal{ NP}-complete. Furthermore, we provide a distributed and local constant-factor approximation algorithm using constant-factor resource augmentation for the two-dimensional setting with {mathcal O}(log^*n) communication rounds.
The use of meta-heuristics for airport gate assignment
DEFF Research Database (Denmark)
Cheng, Chun-Hung; Ho, Sin C.; Kwan, Cheuk-Lam
2012-01-01
proposed to generate good solutions within a reasonable timeframe. In this work, we attempt to assess the performance of three meta-heuristics, namely, genetic algorithm (GA), tabu search (TS), simulated annealing (SA) and a hybrid approach based on SA and TS. Flight data from Incheon International Airport......Improper assignment of gates may result in flight delays, inefficient use of the resource, customer’s dissatisfaction. A typical metropolitan airport handles hundreds of flights a day. Solving the gate assignment problem (GAP) to optimality is often impractical. Meta-heuristics have recently been...... are collected to carry out the computational comparison. Although the literature has documented these algorithms, this work may be a first attempt to evaluate their performance using a set of realistic flight data....
Equilibrium Assignment Model with Uncertainties in Traffic Demands
Directory of Open Access Journals (Sweden)
Aiwu Kuang
2013-01-01
Full Text Available In this study, we present an equilibrium traffic assignment model considering uncertainties in traffic demands. The link and route travel time distributions are derived based on the assumption that OD traffic demand follows a log-normal distribution. We postulate that travelers can acquire the variability of route travel times from past experiences and factor such variability into their route choice considerations in the form of mean route travel time. Furthermore, all travelers want to minimize their mean route travel times. We formulate the assignment problem as a variational inequality, which can be solved by a route-based heuristic solution algorithm. Some numerical studies on a small test road network are carried out to validate the proposed model and algorithm, at the same time, some reasonable results are obtained.
Phase transition in the assignment problem for random matrices
Esteve, J. G.; Falceto, F.
2005-12-01
We report an analytic and numerical study of a phase transition in a P problem (the assignment problem) that separates two phases whose representatives are the simple matching problem (an easy P problem) and the traveling-salesman problem (a NP-complete problem). Like other phase transitions found in combinatoric problems (K-satisfiability, number partitioning) this can help to understand the nature of the difficulties in solving NP problems an to find more accurate algorithms for them.
Hierarchical method of task assignment for multiple cooperating UAV teams
Institute of Scientific and Technical Information of China (English)
Xiaoxuan Hu; Huawei Ma; Qingsong Ye; He Luo
2015-01-01
The problem of task assignment for multiple cooperat-ing unmanned aerial vehicle (UAV) teams is considered. Multiple UAVs forming several smal teams are needed to perform attack tasks on a set of predetermined ground targets. A hierarchical task assignment method is presented to address the problem. It breaks the original problem down to three levels of sub-problems: tar-get clustering, cluster al ocation and target assignment. The first two sub-problems are central y solved by using clustering algo-rithms and integer linear programming, respectively, and the third sub-problem is solved in a distributed and paral el manner, using a mixed integer linear programming model and an improved ant colony algorithm. The proposed hierarchical method can reduce the computational complexity of the task assignment problem con-siderably, especial y when the number of tasks or the number of UAVs is large. Experimental results show that this method is feasi-ble and more efficient than non-hierarchical methods.
Assigning and visualizing germline genes in antibody repertoires.
Frost, Simon D W; Murrell, Ben; Hossain, A S Md Mukarram; Silverman, Gregg J; Pond, Sergei L Kosakovsky
2015-09-01
Identifying the germline genes involved in immunoglobulin rearrangements is an essential first step in the analysis of antibody repertoires. Based on our prior work in analysing diverse recombinant viruses, we present IgSCUEAL (Immunoglobulin Subtype Classification Using Evolutionary ALgorithms), a phylogenetic approach to assign V and J regions of immunoglobulin sequences to their corresponding germline alleles, with D regions assigned using a simple pairwise alignment algorithm. We also develop an interactive web application for viewing the results, allowing the user to explore the frequency distribution of sequence assignments and CDR3 region length statistics, which is useful for summarizing repertoires, as well as a detailed viewer of rearrangements and region alignments for individual query sequences. We demonstrate the accuracy and utility of our method compared with sequence similarity-based approaches and other non-phylogenetic model-based approaches, using both simulated data and a set of evaluation datasets of human immunoglobulin heavy chain sequences. IgSCUEAL demonstrates the highest accuracy of V and J assignment amongst existing approaches, even when the reassorted sequence is highly mutated, and can successfully cluster sequences on the basis of shared V/J germline alleles. PMID:26194754
BOZDOĞAN, Ali Önder; YILMAZ, Asım Egemen; EFE, Murat
2010-01-01
The aim of this study is to investigate the suitability of selected swarm optimization algorithms to the generalized assignment problem as encountered in multi-target tracking applications. For this purpose, we have tested variants of particle swarm optimization and ant colony optimization algorithms to solve the 2D generalized assignment problem with simulated dense and sparse measurement/track matrices and compared their performance to that of the auction algorithm. We observed tha...
A Statistical Programme Assignment Model
DEFF Research Database (Denmark)
Rosholm, Michael; Staghøj, Jonas; Svarer, Michael
When treatment effects of active labour market programmes are heterogeneous in an observable way across the population, the allocation of the unemployed into different programmes becomes a particularly important issue. In this paper, we present a statistical model designed to improve the present...... duration of unemployment spells may result if a statistical programme assignment model is introduced. We discuss several issues regarding the plementation of such a system, especially the interplay between the statistical model and case workers....
A Useful Metaheuristic for Dynamic Channel Assignment in Mobile Cellular Systems
Directory of Open Access Journals (Sweden)
Deepak Kumar Singh
2012-09-01
Full Text Available The prime objective of a Channel Assignment Problem (CAP is to assign appropriate number of required channels to each cell in a way to achieve both efficient frequency spectrum utilization and minimization of interference effects (by satisfying a number of channel reuse constraints. Dynamic Channel Assignment (DCA assigns the channels to the cells dynamically according to traffic demand, and hence, can provide higher capacity (or lower call blocking probability, fidelity and quality of service than the fixed assignment schemes. Channel assignment algorithms are formulated as combinatorial optimization problems and are NP-hard. Devising a DCA, that is practical, efficient, and which can generate high quality assignments, is challenging. Though Metaheuristic Search techniques like Evolutionary Algorithms, Differential Evolution, Particle Swarm Optimization prove effective in the solution of Fixed Channel Assignment (FCA problems but they still require high computational time and therefore may be inefficient for DCA. A number of approaches have been proposed for the solution of DCA problem but the high complexity of these proposed approaches makes them unsuitable/less efficient for practical use. Therefore, this paper presents an effective and efficient Hybrid Discrete Binary Differential Evolution Algorithm (HDB-DE for the solution of DCA Problem
Automated solid-state NMR resonance assignment of protein microcrystals and amyloids
International Nuclear Information System (INIS)
Solid-state NMR is an emerging structure determination technique for crystalline and non-crystalline protein assemblies, e.g., amyloids. Resonance assignment constitutes the first and often very time-consuming step to a structure. We present ssFLYA, a generally applicable algorithm for automatic assignment of protein solid-state NMR spectra. Application to microcrystals of ubiquitin and the Ure2 prion C-terminal domain, as well as amyloids of HET-s(218–289) and α-synuclein yielded 88–97 % correctness for the backbone and side-chain assignments that are classified as self-consistent by the algorithm, and 77–90 % correctness if also assignments classified as tentative by the algorithm are included
Automated solid-state NMR resonance assignment of protein microcrystals and amyloids
Energy Technology Data Exchange (ETDEWEB)
Schmidt, Elena [Goethe University Frankfurt am Main, Center for Biomolecular Magnetic Resonance, Institute of Biophysical Chemistry (Germany); Gath, Julia [ETH Zurich, Physical Chemistry (Switzerland); Habenstein, Birgit [UMR 5086 CNRS/Universite de Lyon 1, Institut de Biologie et Chimie des Proteines (France); Ravotti, Francesco; Szekely, Kathrin; Huber, Matthias [ETH Zurich, Physical Chemistry (Switzerland); Buchner, Lena [Goethe University Frankfurt am Main, Center for Biomolecular Magnetic Resonance, Institute of Biophysical Chemistry (Germany); Boeckmann, Anja, E-mail: a.bockmann@ibcp.fr [UMR 5086 CNRS/Universite de Lyon 1, Institut de Biologie et Chimie des Proteines (France); Meier, Beat H., E-mail: beme@ethz.ch [ETH Zurich, Physical Chemistry (Switzerland); Guentert, Peter, E-mail: guentert@em.uni-frankfurt.de [Goethe University Frankfurt am Main, Center for Biomolecular Magnetic Resonance, Institute of Biophysical Chemistry (Germany)
2013-07-15
Solid-state NMR is an emerging structure determination technique for crystalline and non-crystalline protein assemblies, e.g., amyloids. Resonance assignment constitutes the first and often very time-consuming step to a structure. We present ssFLYA, a generally applicable algorithm for automatic assignment of protein solid-state NMR spectra. Application to microcrystals of ubiquitin and the Ure2 prion C-terminal domain, as well as amyloids of HET-s(218-289) and {alpha}-synuclein yielded 88-97 % correctness for the backbone and side-chain assignments that are classified as self-consistent by the algorithm, and 77-90 % correctness if also assignments classified as tentative by the algorithm are included.
Parkhurst, John T.; Fleisher, Matthew S.; Skinner, Christopher H.; Woehr, David J.; Hawthorn-Embree, Meredith L.
2011-01-01
After completing the Multidimensional Work-Ethic Profile (MWEP), 98 college students were given a 20-problem math computation assignment and instructed to stop working on the assignment after completing 10 problems. Next, they were allowed to choose to finish either the partially completed assignment that had 10 problems remaining or a new…
Algorithm for structure constants
Paiva, F M
2011-01-01
In a $n$-dimensional Lie algebra, random numerical values are assigned by computer to $n(n-1)$ especially selected structure constants. An algorithm is then created, which calculates without ambiguity the remaining constants, obeying the Jacobi conditions. Differently from others, this algorithm is suitable even for poor personal computer. ------------- En $n$-dimensia algebro de Lie, hazardaj numeraj valoroj estas asignitaj per komputilo al $n(n-1)$ speciale elektitaj konstantoj de strukturo. Tiam algoritmo estas kreita, kalkulante senambigue la ceterajn konstantojn, obeante kondicxojn de Jacobi. Malsimile al aliaj algoritmoj, tiu cxi tauxgas ecx por malpotenca komputilo.
7 CFR 1437.104 - Assigned production.
2010-01-01
... 7 Agriculture 10 2010-01-01 2010-01-01 false Assigned production. 1437.104 Section 1437.104... Determining Yield Coverage Using Actual Production History § 1437.104 Assigned production. (a) When determining losses under this section, assigned production will be used to offset the loss of production...
Lexical Stress Assignment in Italian Developmental Dyslexia
Paizi, Despina; Zoccolotti, Pierluigi; Burani, Cristina
2011-01-01
Stress assignment to Italian polysyllabic words is unpredictable, because stress is neither marked nor predicted by rule. Stress assignment, especially to low frequency words, has been reported to be a function of stress dominance and stress neighbourhood. Two experiments investigate stress assignment in sixth-grade, skilled and dyslexic, readers.…
Szöllösi, Tomáš
2012-01-01
The first part of this work deals with the optimization and evolutionary algorithms which are used as a tool to solve complex optimization problems. The discussed algorithms are Differential Evolution, Genetic Algorithm, Simulated Annealing and deterministic non-evolutionary algorithm Taboo Search.. Consequently the discussion is held on the issue of testing the optimization algorithms through the use of the test function gallery and comparison solution all algorithms on Travelling salesman p...
Optimization of Load Assignment to Boilers in Industrial Boiler Plants
Institute of Scientific and Technical Information of China (English)
CAO Jia-cong; QIU Guang; CAO Shuang-hua; LIU Feng-qiang
2004-01-01
Along with the increasing importance of sustainable energy, the optimization of load assignment to boilers in an industrial boiler plant becomes one of the major projects for the optimal operation of boiler plants. Optimal load assignment for power systems has been a long-lasting subject, while it is quite new for industrial boiler plants. The existing methods of optimal load assignment for boiler plants are explained and analyzed briefly in the paper. They all need the fuel cost curves of boilers. Thanks to some special features of the curves for industrial boilers, a new model referred to as minimized departure model (MDM) of optimization of load assignment for boiler plants is developed and proposed in the paper. It merely relies upon the accessible data of two typical working conditions to build the model, viz. the working conditions with the highest efficiency of a boiler and with no-load. Explanation of the algorithm of computer program is given, and effort is made so as to determine in advance how many and which boilers are going to work. Comparison between the results using MDM and the results reported in references is carried out, which proves that MDM is preferable and practicable.
An Investigation of the Partial-Assignment Completion Effect on Students' Assignment Choice Behavior
Hawthorn-Embree, Meredith L.; Skinner, Christopher H.; Parkhurst, John; Conley, Elisha
2011-01-01
This study was designed to investigate the partial assignment completion effect. Seventh-grade students were given a math assignment. After working for 5 min, they were interrupted and their partially completed assignments were collected. About 20 min later, students were given their partially completed assignment and a new, control assignment…
Block-decoupling vibration control using eigenstructure assignment
Wei, Xiaojun; Mottershead, John E.
2016-06-01
A theoretical study is presented on the feasibility of applying active control for the purpose of vibration isolation in lightweight structures by block diagonalisation of the system matrices and at the same time assigning eigenvalues (natural frequencies and damping) to the chosen substructures separately. The methodology, based on eigenstructure assignment using the method of receptances, is found to work successfully when the eigenvalues of the open-loop system are controllable and the open- and closed-loop eigenvalues are distinct. In the first part of the paper results are obtained under the restriction that the mass matrix is diagonal (lumped). This is certainly applicable in the case of numerous engineering systems consisting of discrete masses with flexible interconnections of negligible mass. Later in the paper this restriction is lifted to allow bandedness of the mass matrix. Several numerical examples are used to illustrate the working of the proposed algorithm.
A tracked approach for automated NMR assignments in proteins (TATAPRO)
International Nuclear Information System (INIS)
A novel automated approach for the sequence specific NMR assignments of 1HN, 13Cα, 13Cβ, 13C'/1Hα and 15N spins in proteins, using triple resonance experimental data, is presented. The algorithm, TATAPRO (Tracked AuTomated Assignments in Proteins) utilizes the protein primary sequence and peak lists from a set of triple resonance spectra which correlate 1HN and 15N chemical shifts with those of 13Cα, 13Cβ and 13C'/1Hα. The information derived from such correlations is used to create a 'masterlist' consisting of all possible sets of 1HNi, 15Ni, 13Cαi, 13Cβi, 13C'i/1Hαi, 13Cαi-1, 13Cβi-1 and 13C'i-1/ 1Hαi-1 chemical shifts. On the basis of an extensive statistical analysis of 13Cα and 13Cβ chemical shift data of proteins derived from the BioMagResBank (BMRB), it is shown that the 20 amino acid residues can be grouped into eight distinct categories, each of which is assigned a unique two-digit code. Such a code is used to tag individual sets of chemical shifts in the masterlist and also to translate the protein primary sequence into an array called ppsarray. The program then uses the masterlist to search for neighbouring partners of a given amino acid residue along the polypeptide chain and sequentially assigns a maximum possible stretch of residues on either side. While doing so, each assigned residue is tracked in an array called assigarray, with the two-digit code assigned earlier. The assigarray is then mapped onto the ppsarray for sequence specific resonance assignment. The program has been tested using experimental data on a calcium binding protein from Entamoeba histolytica (Eh-CaBP, 15 kDa) having substantial internal sequence homology and using published data on four other proteins in the molecular weight range of 18-42 kDa. In all the cases, nearly complete sequence specific resonance assignments (> 95%) are obtained. Furthermore, the reliability of the program has been tested by deleting sets of chemical shifts randomly from the masterlist
National Aeronautics and Space Administration — SSCI proposes to develop and test a Configuration Optimization for Balanced Runway/Route Assignments (COBRA) tool, which includes analysis and planner algorithms...
Eremeev, Anton V.
2015-01-01
This manuscript contains an outline of lectures course "Evolutionary Algorithms" read by the author in Omsk State University n.a. F.M.Dostoevsky. The course covers Canonic Genetic Algorithm and various other genetic algorithms as well as evolutioanry algorithms in general. Some facts, such as the Rotation Property of crossover, the Schemata Theorem, GA performance as a local search and "almost surely" convergence of evolutionary algorithms are given with complete proofs. The text is in Russian.
The Mechanism Design Approach to Student Assignment
Pathak, Parag A.
2011-01-01
The mechanism design approach to student assignment involves the theoretical, empirical, and experimental study of systems used to allocate students into schools around the world. Recent practical experience designing systems for student assignment has raised new theoretical questions for the theory of matching and assignment. This article reviews some of this recent literature, highlighting how issues from the field motivated theoretical developments and emphasizing how the dialogue may be a...
Job Assignments, Intrinsic Motivation and Explicit Incentives
Nafziger, Julia
2008-01-01
This paper considers the interplay of job assignments with the intrinsic and extrinsic motivation of an agent. Job assignments influence the self confidence of the agent, and thereby his intrinsic motivation. Monetary reward allow the principal to complement intrinsic motivation with extrinsic incentives. The main result is that the principal chooses an inefficient job assignment rule to enhance the agent's intrinsic motivation even though she can motivate him with monetary rewards. This show...
PhosphoScore: An Open-Source Phosphorylation Site Assignment Tool for MSn Data
Ruttenberg, Brian E.; Pisitkun, Trairak; Knepper, Mark A.; Jason D. Hoffert
2008-01-01
Correct phosphorylation site assignment is a critical aspect of phosphoproteomic analysis. Large-scale phosphopeptide data sets that are generated through liquid chromatography-coupled tandem mass spectrometry (LC-MS/MS) analysis often contain hundreds or thousands of phosphorylation sites that require validation. To this end, we have created PhosphoScore, an open-source assignment program that is compatible with phosphopeptide data from multiple MS levels (MSn). The algorithm takes into acco...
Ramires, Ana; Soares, João
2005-01-01
In this article we decribe how to compute a lower bound for the asymmetric traveling salesman problem that dominates the bound that comes from the assignment relaxation, through the solving of a sequence of assignment problems. The algorithm that we propose is a first-order method based on the exponential penalty function. Directions of movement are derived from a disjunctive relaxation that we proposed as being one of two possible classes, one based on cycles, the other based on cliques.
Arbitrary eigenvalue assignments for linear time-varying multivariable control systems
Nguyen, Charles C.
1987-01-01
The problem of eigenvalue assignments for a class of linear time-varying multivariable systems is considered. Using matrix operators and canonical transformations, it is shown that a time-varying system that is 'lexicography-fixedly controllable' can be made via state feedback to be equivalent to a time-invariant system whose eigenvalues are arbitrarily assignable. A simple algorithm for the design of the state feedback is provided.
Java bytecode verification via static single assignment form
DEFF Research Database (Denmark)
Gal, Andreas; Probst, Christian W.; Franz, Michael
2008-01-01
Java Virtual Machines (JVMs) traditionally perform bytecode verification by way of an iterative data-flow analysis. Bytecode verification is necessary to ensure type safety because temporary variables in the JVM are not statically typed. We present an alternative verification mechanism that trans...... the additional benefit of generating SSA as a side effect, which may be immediately useful for a subsequent dynamic compilation stage....... transforms JVM bytecode into Static Single Assignment Form (SSA) and thereby propagates definitions directly to uses. Type checking at control flow merge points can then be performed in a single pass. Our prototype implementation of the new algorithm is faster than the standard JVM bytecode verifier. It has...
Integrated consensus-based frameworks for unmanned vehicle routing and targeting assignment
Barnawi, Waleed T.
Unmanned aerial vehicles (UAVs) are increasingly deployed in complex and dynamic environments to perform multiple tasks cooperatively with other UAVs that contribute to overarching mission effectiveness. Studies by the Department of Defense (DoD) indicate future operations may include anti-access/area-denial (A2AD) environments which limit human teleoperator decision-making and control. This research addresses the problem of decentralized vehicle re-routing and task reassignments through consensus-based UAV decision-making. An Integrated Consensus-Based Framework (ICF) is formulated as a solution to the combined single task assignment problem and vehicle routing problem. The multiple assignment and vehicle routing problem is solved with the Integrated Consensus-Based Bundle Framework (ICBF). The frameworks are hierarchically decomposed into two levels. The bottom layer utilizes the renowned Dijkstra's Algorithm. The top layer addresses task assignment with two methods. The single assignment approach is called the Caravan Auction Algorithm (CarA) Algorithm. This technique extends the Consensus-Based Auction Algorithm (CBAA) to provide awareness for task completion by agents and adopt abandoned tasks. The multiple assignment approach called the Caravan Auction Bundle Algorithm (CarAB) extends the Consensus-Based Bundle Algorithm (CBBA) by providing awareness for lost resources, prioritizing remaining tasks, and adopting abandoned tasks. Research questions are investigated regarding the novelty and performance of the proposed frameworks. Conclusions regarding the research questions will be provided through hypothesis testing. Monte Carlo simulations will provide evidence to support conclusions regarding the research hypotheses for the proposed frameworks. The approach provided in this research addresses current and future military operations for unmanned aerial vehicles. However, the general framework implied by the proposed research is adaptable to any unmanned
Directory of Open Access Journals (Sweden)
Sorana D. BOLBOACĂ
2011-06-01
Full Text Available Aim: The properness of random assignment of compounds in training and validation sets was assessed using the generalized cluster technique. Material and Method: A quantitative Structure-Activity Relationship model using Molecular Descriptors Family on Vertices was evaluated in terms of assignment of carboquinone derivatives in training and test sets during the leave-many-out analysis. Assignment of compounds was investigated using five variables: observed anticancer activity and four structure descriptors. Generalized cluster analysis with K-means algorithm was applied in order to investigate if the assignment of compounds was or not proper. The Euclidian distance and maximization of the initial distance using a cross-validation with a v-fold of 10 was applied. Results: All five variables included in analysis proved to have statistically significant contribution in identification of clusters. Three clusters were identified, each of them containing both carboquinone derivatives belonging to training as well as to test sets. The observed activity of carboquinone derivatives proved to be normal distributed on every. The presence of training and test sets in all clusters identified using generalized cluster analysis with K-means algorithm and the distribution of observed activity within clusters sustain a proper assignment of compounds in training and test set. Conclusion: Generalized cluster analysis using the K-means algorithm proved to be a valid method in assessment of random assignment of carboquinone derivatives in training and test sets.
Predicting Assignment Submissions in a Multiclass Classification Problem
Directory of Open Access Journals (Sweden)
Bogdan Drăgulescu
2015-08-01
Full Text Available Predicting student failure is an important task that can empower educators to counteract the factors that affect student performance. In this paper, a part of the bigger problem of predicting student failure is addressed: predicting the students that do not complete their assignment tasks. For solving this problem, real data collected by our university’s educational platform was used. Because the problem consisted of predicting one of three possible classes (multi-class classification, the appropriate algorithms and methods were selected. Several experiments were carried out to find the best approach for this prediction problem and the used data set. An approach of time segmentation is proposed in order to facilitate the prediction from early on. Methods that address the problems of high dimensionality and imbalanced data were also evaluated. The outcome of each approach is shown and compared in order to select the best performing classification algorithm for the problem at hand.
Comparing of the Deterministic Simulated Annealing Methods for Quadratic Assignment Problem
Directory of Open Access Journals (Sweden)
Mehmet Güray ÜNSAL
2013-08-01
Full Text Available In this study, Threshold accepting and Record to record travel methods belonging to Simulated Annealing that is meta-heuristic method by applying Quadratic Assignment Problem are statistically analyzed whether they have a significant difference with regard to the values of these two methods target functions and CPU time. Between the two algorithms, no significant differences are found in terms of CPU time and the values of these two methods target functions. Consequently, on the base of Quadratic Assignment Problem, the two algorithms are compared in the study have the same performance in respect to CPU time and the target functions values
Joux, Antoine
2009-01-01
Illustrating the power of algorithms, Algorithmic Cryptanalysis describes algorithmic methods with cryptographically relevant examples. Focusing on both private- and public-key cryptographic algorithms, it presents each algorithm either as a textual description, in pseudo-code, or in a C code program.Divided into three parts, the book begins with a short introduction to cryptography and a background chapter on elementary number theory and algebra. It then moves on to algorithms, with each chapter in this section dedicated to a single topic and often illustrated with simple cryptographic applic
Detecting Plagiarism in MS Access Assignments
Singh, Anil
2013-01-01
Assurance of individual effort from students in computer-based assignments is a challenge. Due to digitization, students can easily use a copy of their friend's work and submit it as their own. Plagiarism in assignments puts students who cheat at par with those who work honestly and this compromises the learning evaluation process. Using a…
12 CFR 25.28 - Assigned ratings.
2010-01-01
... DEPOSIT PRODUCTION REGULATIONS Regulations Standards for Assessing Performance § 25.28 Assigned ratings... a rating of “outstanding,” “satisfactory,” “needs to improve,” or “substantial noncompliance” based... 12 Banks and Banking 1 2010-01-01 2010-01-01 false Assigned ratings. 25.28 Section 25.28 Banks...
Online Discussion Assignments Improve Students' Class Preparation
Lineweaver, Tara T.
2010-01-01
To increase the number of students who read the text before class and to promote student interaction centering on text material, I developed an online discussion assignment as a required component of a cognitive psychology course. Across 2 studies, this assignment had a limited effect on examination performance, but students completing online…
Protein secondary structure: category assignment and predictability
DEFF Research Database (Denmark)
Andersen, Claus A.; Bohr, Henrik; Brunak, Søren
2001-01-01
structures. Single sequence prediction of the new three category assignment gives an overall prediction improvement of 3.1% and 5.1%, compared to the DSSP assignment and schemes where the helix category consists of a-helix and 3(10)-helix, respectively. These results were achieved using a standard feed...
Stress Assignment in Reading Italian Polysyllabic Pseudowords
Sulpizio, Simone; Arduino, Lisa S.; Paizi, Despina; Burani, Cristina
2013-01-01
In 4 naming experiments we investigated how Italian readers assign stress to pseudowords. We assessed whether participants assign stress following distributional information such as stress neighborhood (the proportion and number of existent words sharing orthographic ending and stress pattern) and whether such distributional information affects…
Individualized Assignments in an Experimental Psychology Course.
Hovancik, John R.
1984-01-01
A computer is used to individualize student assignments in statistics. The principal benefit of individualized activities is that they emphasize decision-making processes rather than correct answers. Students in an individualized assignment group scored higher on an examination than those in a comparison group. (RM)
Airport Gate Assignment: New Model and Implementation
Li, Chendong
2008-01-01
Airport gate assignment is of great importance in airport operations. In this paper, we study the Airport Gate Assignment Problem (AGAP), propose a new model and implement the model with Optimization Programming language (OPL). With the objective to minimize the number of conflicts of any two adjacent aircrafts assigned to the same gate, we build a mathematical model with logical constraints and the binary constraints, which can provide an efficient evaluation criterion for the Airlines to estimate the current gate assignment. To illustrate the feasibility of the model we construct experiments with the data obtained from Continental Airlines, Houston Gorge Bush Intercontinental Airport IAH, which indicate that our model is both energetic and effective. Moreover, we interpret experimental results, which further demonstrate that our proposed model can provide a powerful tool for airline companies to estimate the efficiency of their current work of gate assignment.
Asset-Based Measurement of Poverty
Brandolini, Andrea; Magri, Silvia; Smeeding, Timothy M.
2010-01-01
Poverty is generally defined as income or expenditure insufficiency, but the economic condition of a household also depends on its real and financial asset holdings. This paper investigates measures of poverty that rely on indicators of household net worth. We review and assess two main approaches followed in the literature: income-net worth…
A rule-based algorithm for automatic bond type perception
Zhang Qian; Zhang Wei; Li Youyong; Wang Junmei; Zhang Liling; Hou Tingjun
2012-01-01
Abstract Assigning bond orders is a necessary and essential step for characterizing a chemical structure correctly in force field based simulations. Several methods have been developed to do this. They all have advantages but with limitations too. Here, an automatic algorithm for assigning chemical connectivity and bond order regardless of hydrogen for organic molecules is provided, and only three dimensional coordinates and element identities are needed for our algorithm. The algorithm uses ...
Cooperative distributed target tracking algorithm in mobile wireless sensor networks
Institute of Scientific and Technical Information of China (English)
无
2011-01-01
The paper proposes a cooperative distributed target tracking algorithm in mobile wireless sensor networks.There are two main components in the algorithm:distributed sensor-target assignment and sensor motion control.In the key idea of the sensor-target assignment,sensors are considered as autonomous agents and the defined objective function of each sensor concentrates on two fundamental factors:the tracking accuracy and the tracking cost.Compared with the centralized algorithm and the noncooperative distrib...
Tel, G.
1993-01-01
We define the notion of total algorithms for networks of processes. A total algorithm enforces that a "decision" is taken by a subset of the processes, and that participation of all processes is required to reach this decision. Total algorithms are an important building block in the design of distri
Target assignment for security officers to K targets (TASK)
International Nuclear Information System (INIS)
A probabilistic algorithm is developed to provide an optimal Target Assignment for Security officers to K targets (TASK) using a maximin criterion. Under the assumption of only a limited number (N) of security officers, the TASK computer model determines deployment assignments which maximize the system protection against sabotage by an adversary who may select any link in the system, including the weakest, for the point of attack. Applying the TASK model to a hypothetical nuclear facility containing a nine-level building reveals that aggregate targets covering multiple vital areas should be utilized to reduce the number of possible target assignments to a value equal to or only slightly larger than N. The increased probability that a given aggregate target is covered by one or more security officers offsets the slight decrease in interruption probability due to its occurring earlier in the adversary's path. In brief, the TASK model determines the optimal maximin deployment strategy for limited numbers of security officers and calculates a quantitative measure of the resulting system protection
Garlick, Robert
2014-01-01
This paper studies the relative academic performance of students tracked or randomly assigned to South African university dormitories. Tracked or streamed assignment creates dormitories where all students obtained similar scores on high school graduation examinations. Random assignment creates dormitories that are approximately representative of the population of students. Tracking lowers ...
A New Algorithm for Minimum Cost MRGAP
Directory of Open Access Journals (Sweden)
Lutfu Sagbansua
2009-10-01
Full Text Available This paper introduces an algorithm based on independent and combined strategies of surrogate constraint relaxation and scatter search coupled with simple Tabu search, subgradient optimization, and Lagrangean relaxation. The key contribution of this research is the development of effective RAMP and Primal-Dual RAMP algorithms for the MRGAP. Assignment problems involve assigning a set of jobs at hand to another set of agents which are limited in resources. Depending on the number of constraints, several different types of assignment problems can be formulated. The paper discusses the formulation of such a problem and an algorithm produced to solve these problems. Computational results are provided as a basis of comparison with several algorithms.
A New Algorithm for Minimum Cost MRGAP
Directory of Open Access Journals (Sweden)
Lutfu Sagbansua
2016-01-01
Full Text Available This paper introduces an algorithm based on independent and combined strategies of surrogate constraint relaxation and scatter search coupled with simple Tabu search, subgradient optimization, and Lagrangian relaxation. The key contribution of this research is the development of effective RAMP and Primal-Dual RAMP algorithms for the MRGAP. Assignment problems involve assigning a set of jobs at hand to another set of agents which are limited in resources. Depending on the number of constraints, several different types of assignment problems can be formulated. The paper discusses the formulation of such a problem and an algorithm produced to solve these problems. Computational results are provided as a basis of comparison with several algorithms.
Automated assignment of NMR chemical shifts based on a known structure and 4D spectra.
Trautwein, Matthias; Fredriksson, Kai; Möller, Heiko M; Exner, Thomas E
2016-08-01
Apart from their central role during 3D structure determination of proteins the backbone chemical shift assignment is the basis for a number of applications, like chemical shift perturbation mapping and studies on the dynamics of proteins. This assignment is not a trivial task even if a 3D protein structure is known and needs almost as much effort as the assignment for structure prediction if performed manually. We present here a new algorithm based solely on 4D [(1)H,(15)N]-HSQC-NOESY-[(1)H,(15)N]-HSQC spectra which is able to assign a large percentage of chemical shifts (73-82 %) unambiguously, demonstrated with proteins up to a size of 250 residues. For the remaining residues, a small number of possible assignments is filtered out. This is done by comparing distances in the 3D structure to restraints obtained from the peak volumes in the 4D spectrum. Using dead-end elimination, assignments are removed in which at least one of the restraints is violated. Including additional information from chemical shift predictions, a complete unambiguous assignment was obtained for Ubiquitin and 95 % of the residues were correctly assigned in the 251 residue-long N-terminal domain of enzyme I. The program including source code is available at https://github.com/thomasexner/4Dassign . PMID:27484442
An Approach In Optimization Of Ad-Hoc Routing Algorithms
Directory of Open Access Journals (Sweden)
Sarvesh Kumar Sharma
2012-06-01
Full Text Available In this paper different optimization of Ad-hoc routing algorithm is surveyed and a new method using training based optimization algorithm for reducing the complexity of routing algorithms is suggested. A binary matrix is assigned to each node in the network and gets updated after each data transfer using the protocols. The use of optimization algorithm in routing algorithm can reduce the complexity of routing to the least amount possible.
Performance-driven assignment and mapping for reliable networks-on-chips
Institute of Scientific and Technical Information of China (English)
Qian-qi LE; Guo-wu YANG; William N.N.HUNG; Xiao-yu SONG; Fu-you FAN
2014-01-01
Network-on-chip (NoC) communication architectures present promising solutions for scalable communication re-quests in large system-on-chip (SoC) designs. Intellectual property (IP) core assignment and mapping are two key steps in NoC design, significantly affecting the quality of NoC systems. Both are NP-hard problems, so it is necessary to apply intelligent algorithms. In this paper, we propose improved intelligent algorithms for NoC assignment and mapping to overcome the draw-backs of traditional intelligent algorithms. The aim of our proposed algorithms is to minimize power consumption, time, area, and load balance. This work involves multiple conflicting objectives, so we combine multiple objective optimization with intelligent algorithms. In addition, we design a fault-tolerant routing algorithm and take account of reliability using comprehensive perfor-mance indices. The proposed algorithms were implemented on embedded system synthesis benchmarks suite (E3S). Experimental results show the improved algorithms achieve good performance in NoC designs, with high reliability.
Computerized fetal heart rate analysis in labor: detection of intervals with un-assignable baseline
International Nuclear Information System (INIS)
The fetal heart rate (FHR) is monitored during labor to assess fetal health. Both visual and computerized interpretations of the FHR depend on assigning a baseline to detect key features such as accelerations or decelerations. However, it is sometimes impossible to assign a baseline reliably, by eye or by numerical methods. To address this issue, we used the Oxford Intrapartum FHR Database to derive an algorithm based on the distribution of the FHR that detects heart rate intervals without a clear baseline. We aimed to recognize when a fetus cannot maintain its heart rate baseline and use this to assist computerized FHR analysis. Twenty-three FHR windows (15 min long) were used to develop the method. The algorithm was then validated by comparison with experts who classified 50 FHR windows into two groups: baseline assignable or un-assignable. The average agreement between experts (κ = 0.76) was comparable to the agreement between method and experts (κ = 0.67). The algorithm was used in 22 559 patients with intrapartum FHR records to retrospectively determine the incidence of intervals (defined as 15 min windows) that had un-assignable baselines. Sixty-six percent had one or more such episodes at some stage, most commonly after the onset of pushing (55%) and least commonly pre-labor (16%). These episodes are therefore relatively common. Their detection should improve the reliability of computerized analysis and allow further studies of what they signify clinically
Reading assignment 10 - Linguistics 8806 (group 3)
Muñoz Baell, Irma María
2010-01-01
Reading assignment 10 - PART II. AN INTRODUCTION TO THE HISTORY OF LINGUISTICS. Key topic: Nineteenth-century linguistics: Historical linguistics. Academic year 2009-2010 (Course credits: 12 (15 ECTS)).
Quantum probability assignment limited by relativistic causality.
Han, Yeong Deok; Choi, Taeseung
2016-01-01
Quantum theory has nonlocal correlations, which bothered Einstein, but found to satisfy relativistic causality. Correlation for a shared quantum state manifests itself, in the standard quantum framework, by joint probability distributions that can be obtained by applying state reduction and probability assignment that is called Born rule. Quantum correlations, which show nonlocality when the shared state has an entanglement, can be changed if we apply different probability assignment rule. As a result, the amount of nonlocality in quantum correlation will be changed. The issue is whether the change of the rule of quantum probability assignment breaks relativistic causality. We have shown that Born rule on quantum measurement is derived by requiring relativistic causality condition. This shows how the relativistic causality limits the upper bound of quantum nonlocality through quantum probability assignment. PMID:26971717
Diagnosis code assignment: models and evaluation metrics
Perotte, Adler; Pivovarov, Rimma; Natarajan, Karthik; Weiskopf, Nicole; Wood, Frank; Elhadad, Noémie
2013-01-01
Background and objective The volume of healthcare data is growing rapidly with the adoption of health information technology. We focus on automated ICD9 code assignment from discharge summary content and methods for evaluating such assignments. Methods We study ICD9 diagnosis codes and discharge summaries from the publicly available Multiparameter Intelligent Monitoring in Intensive Care II (MIMIC II) repository. We experiment with two coding approaches: one that treats each ICD9 code indepen...
On pole structure assignment in linear systems
Czech Academy of Sciences Publication Activity Database
Loiseau, J.-J.; Zagalak, Petr
2009-01-01
Roč. 82, č. 7 (2009), s. 1179-1192. ISSN 0020-7179 R&D Projects: GA ČR(CZ) GA102/07/1596 Institutional research plan: CEZ:AV0Z10750506 Keywords : linear systems * linear state feedback * pole structure assignment Subject RIV: BC - Control Systems Theory Impact factor: 1.124, year: 2009 http://library.utia.cas.cz/separaty/2009/AS/zagalak-on pole structure assignment in linear systems.pdf
Competitive Traffic Assignment in Road Networks
Directory of Open Access Journals (Sweden)
Krylatov Alexander Y.
2016-09-01
Full Text Available Recently in-vehicle route guidance and information systems are rapidly developing. Such systems are expected to reduce congestion in an urban traffic area. This social benefit is believed to be reached by imposing the route choices on the network users that lead to the system optimum traffic assignment. However, guidance service could be offered by different competitive business companies. Then route choices of different mutually independent groups of users may reject traffic assignment from the system optimum state. In this paper, a game theoretic approach is shown to be very efficient to formalize competitive traffic assignment problem with various groups of users in the form of non-cooperative network game with the Nash equilibrium search. The relationships between the Wardrop’s system optimum associated with the traffic assignment problem and the Nash equilibrium associated with the competitive traffic assignment problem are investigated. Moreover, some related aspects of the Nash equilibrium and the Wardrop’s user equilibrium assignments are also discussed.
Multi-input partial eigenvalue assignment for high order control systems with time delay
Zhang, Lei
2016-05-01
In this paper, we consider the partial eigenvalue assignment problem for high order control systems with time delay. Ram et al. (2011) [1] have shown that a hybrid method can be used to solve partial quadratic eigenvalue assignment problem of single-input vibratory system. Based on this theory, a rather simple algorithm for solving multi-input partial eigenvalue assignment for high order control systems with time delay is proposed. Our method can assign the expected eigenvalues and keep the no spillover property. The solution can be implemented with only partial information of the eigenvalues and the corresponding eigenvectors of the matrix polynomial. Numerical examples are given to illustrate the efficiency of our approach.
Directory of Open Access Journals (Sweden)
de Brevern Alexandre G
2005-09-01
Full Text Available Abstract Background A number of methods are now available to perform automatic assignment of periodic secondary structures from atomic coordinates, based on different characteristics of the secondary structures. In general these methods exhibit a broad consensus as to the location of most helix and strand core segments in protein structures. However the termini of the segments are often ill-defined and it is difficult to decide unambiguously which residues at the edge of the segments have to be included. In addition, there is a "twilight zone" where secondary structure segments depart significantly from the idealized models of Pauling and Corey. For these segments, one has to decide whether the observed structural variations are merely distorsions or whether they constitute a break in the secondary structure. Methods To address these problems, we have developed a method for secondary structure assignment, called KAKSI. Assignments made by KAKSI are compared with assignments given by DSSP, STRIDE, XTLSSTR, PSEA and SECSTR, as well as secondary structures found in PDB files, on 4 datasets (X-ray structures with different resolution range, NMR structures. Results A detailed comparison of KAKSI assignments with those of STRIDE and PSEA reveals that KAKSI assigns slightly longer helices and strands than STRIDE in case of one-to-one correspondence between the segments. However, KAKSI tends also to favor the assignment of several short helices when STRIDE and PSEA assign longer, kinked, helices. Helices assigned by KAKSI have geometrical characteristics close to those described in the PDB. They are more linear than helices assigned by other methods. The same tendency to split long segments is observed for strands, although less systematically. We present a number of cases of secondary structure assignments that illustrate this behavior. Conclusion Our method provides valuable assignments which favor the regularity of secondary structure segments.
2013-01-01
Background Ligand‐based virtual screening plays a fundamental part in the early drug discovery stage. In a virtual screening, a chemical library is searched for molecules with similar properties to a query molecule by means of a similarity function. The optimal assignment of chemical graphs has proven to be a valuable similarity function for many cheminformatic tasks, such as virtual screening. The optimal assignment assumes all atoms of a query molecule to be equally important, which is not realistic depending on the binding mode of a ligand. The importance of a query molecule’s atoms can be integrated in the optimal assignment by weighting the assignment edges. We optimized the edge weights with respect to the virtual screening performance by means of evolutionary algorithms. Furthermore, we propose a visualization approach for the interpretation of the edge weights. Results We evaluated two different evolutionary algorithms, differential evolution and particle swarm optimization, for their suitability for optimizing the assignment edge weights. The results showed that both optimization methods are suited to optimize the edge weights. Furthermore, we compared our approach to the optimal assignment with equal edge weights and two literature similarity functions on a subset of the Directory of Useful Decoys using sophisticated virtual screening performance metrics. Our approach achieved a considerably better overall and early enrichment performance. The visualization of the edge weights enables the identification of substructures that are important for a good retrieval of ligands and for the binding to the protein target. Conclusions The optimization of the edge weights in optimal assignment methods is a valuable approach for ligand‐based virtual screening experiments. The approach can be applied to any similarity function that employs the optimal assignment method, which includes a variety of similarity measures that have proven to be valuable in various
Unifying Temporal and Structural Credit Assignment Problems
Agogino, Adrian K.; Tumer, Kagan
2004-01-01
Single-agent reinforcement learners in time-extended domains and multi-agent systems share a common dilemma known as the credit assignment problem. Multi-agent systems have the structural credit assignment problem of determining the contributions of a particular agent to a common task. Instead, time-extended single-agent systems have the temporal credit assignment problem of determining the contribution of a particular action to the quality of the full sequence of actions. Traditionally these two problems are considered different and are handled in separate ways. In this article we show how these two forms of the credit assignment problem are equivalent. In this unified frame-work, a single-agent Markov decision process can be broken down into a single-time-step multi-agent process. Furthermore we show that Monte-Carlo estimation or Q-learning (depending on whether the values of resulting actions in the episode are known at the time of learning) are equivalent to different agent utility functions in a multi-agent system. This equivalence shows how an often neglected issue in multi-agent systems is equivalent to a well-known deficiency in multi-time-step learning and lays the basis for solving time-extended multi-agent problems, where both credit assignment problems are present.
Flow Oriented Channel Assignment for Multi-radio Wireless Mesh Networks
Directory of Open Access Journals (Sweden)
Niu Zhisheng
2010-01-01
Full Text Available We investigate channel assignment for a multichannel wireless mesh network backbone, where each router is equipped with multiple interfaces. Of particular interest is the development of channel assignment heuristics for multiple flows. We present an optimization formulation and then propose two iterative flow oriented heuristics for the conflict-free and interference-aware cases, respectively. To maximize the aggregate useful end-to-end flow rates, both algorithms identify and resolve congestion at instantaneous bottleneck link in each iteration. Then the link rate is optimally allocated among contending flows that share this link by solving a linear programming (LP problem. A thorough performance evaluation is undertaken as a function of the number of channels and interfaces/node and the number of contending flows. The performance of our algorithm is shown to be significantly superior to best known algorithm in its class in multichannel limited radio scenarios.
A tracked approach for automated NMR assignments in proteins (TATAPRO)
Energy Technology Data Exchange (ETDEWEB)
Atreya, H.S.; Sahu, S.C.; Chary, K.V.R.; Govil, Girjesh [Tata Institute of Fundamental Research, Department of Chemical Sciences (India)
2000-06-15
A novel automated approach for the sequence specific NMR assignments of {sup 1}H{sup N}, {sup 13}C{sup {alpha}}, {sup 13}C{sup {beta}}, {sup 13}C'/{sup 1}H{sup {alpha}} and {sup 15}N spins in proteins, using triple resonance experimental data, is presented. The algorithm, TATAPRO (Tracked AuTomated Assignments in Proteins) utilizes the protein primary sequence and peak lists from a set of triple resonance spectra which correlate {sup 1}H{sup N} and {sup 15}N chemical shifts with those of {sup 13}C{sup {alpha}}, {sup 13}C{sup {beta}} and {sup 13}C'/{sup 1}H{sup {alpha}}. The information derived from such correlations is used to create a 'master{sub l}ist' consisting of all possible sets of {sup 1}H{sup N}{sub i}, {sup 15}N{sub i}, {sup 13}C{sup {alpha}}{sub i}, {sup 13}C{sup {beta}}{sub i}, {sup 13}C'{sub i}/{sup 1}H{sup {alpha}}{sub i}, {sup 13}C{sup {alpha}}{sub i-1}, {sup 13}C{sup {beta}}{sub i-1} and {sup 13}C'{sub i-1}/ {sup 1}H{sup {alpha}}{sub i-1} chemical shifts. On the basis of an extensive statistical analysis of {sup 13}C{sup {alpha}} and {sup 13}C{sup {beta}} chemical shift data of proteins derived from the BioMagResBank (BMRB), it is shown that the 20 amino acid residues can be grouped into eight distinct categories, each of which is assigned a unique two-digit code. Such a code is used to tag individual sets of chemical shifts in the master{sub l}ist and also to translate the protein primary sequence into an array called pps{sub a}rray. The program then uses the master{sub l}ist to search for neighbouring partners of a given amino acid residue along the polypeptide chain and sequentially assigns a maximum possible stretch of residues on either side. While doing so, each assigned residue is tracked in an array called assig{sub a}rray, with the two-digit code assigned earlier. The assig{sub a}rray is then mapped onto the pps{sub a}rray for sequence specific resonance assignment. The program has been tested using
Abrams, Daniel S.
This thesis describes several new quantum algorithms. These include a polynomial time algorithm that uses a quantum fast Fourier transform to find eigenvalues and eigenvectors of a Hamiltonian operator, and that can be applied in cases (commonly found in ab initio physics and chemistry problems) for which all known classical algorithms require exponential time. Fast algorithms for simulating many body Fermi systems are also provided in both first and second quantized descriptions. An efficient quantum algorithm for anti-symmetrization is given as well as a detailed discussion of a simulation of the Hubbard model. In addition, quantum algorithms that calculate numerical integrals and various characteristics of stochastic processes are described. Two techniques are given, both of which obtain an exponential speed increase in comparison to the fastest known classical deterministic algorithms and a quadratic speed increase in comparison to classical Monte Carlo (probabilistic) methods. I derive a simpler and slightly faster version of Grover's mean algorithm, show how to apply quantum counting to the problem, develop some variations of these algorithms, and show how both (apparently distinct) approaches can be understood from the same unified framework. Finally, the relationship between physics and computation is explored in some more depth, and it is shown that computational complexity theory depends very sensitively on physical laws. In particular, it is shown that nonlinear quantum mechanics allows for the polynomial time solution of NP-complete and #P oracle problems. Using the Weinberg model as a simple example, the explicit construction of the necessary gates is derived from the underlying physics. Nonlinear quantum algorithms are also presented using Polchinski type nonlinearities which do not allow for superluminal communication. (Copies available exclusively from MIT Libraries, Rm. 14- 0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)
Writing Assignments that Promote Active Learning
Narayanan, M.
2014-12-01
Encourage students to write a detailed, analytical report correlating classroom discussions to an important historical event or a current event. Motivate students interview an expert from industry on a topic that was discussed in class. Ask the students to submit a report with supporting sketches, drawings, circuit diagrams and graphs. Propose that the students generate a complete a set of reading responses pertaining to an assigned topic. Require each student to bring in one comment or one question about an assigned reading. The assignment should be a recent publication in an appropriate journal. Have the students conduct a web search on an assigned topic. Ask them to generate a set of ideas that can relate to classroom discussions. Provide the students with a study guide. The study guide should provide about 10 or 15 short topics. Quiz the students on one or two of the topics. Encourage the students to design or develop some creative real-world examples based on a chapter discussed or a topic of interest. Require that students originate, develop, support and defend a viewpoint using a specifically assigned material. Make the students practice using or utilizing a set of new technical terms they have encountered in an assigned chapter. Have students develop original examples explaining the different terms. Ask the students to select one important terminology from the previous classroom discussions. Encourage the students to explain why they selected that particular word. Ask them to talk about the importance of the terminology from the point of view of their educational objectives and future career. Angelo, T. A. (1991). Ten easy pieces: Assessing higher learning in four dimensions. In T. A. Angelo (Ed.), Classroom research: Early lessons from success (pp. 17-31). New Directions for Teaching and Learning, No. 46. San Francisco: Jossey-Bass.
Radio labeling with pre-assigned frequencies
Bodlaender, H.L.; Broersma, H.J.; Fomin, F.V.; Pyatkin, A.V.; Woeginer, G.J.
2007-01-01
A radio labeling of a graph G is an assignment of pairwise distinct, positive integer labels to the vertices of G such that labels of adjacent vertices differ by at least 2. The radio labeling problem (RL) consists in determining a radio labeling that minimizes the maximum label that is used (the so-called span of the labeling). RL is a well-studied problem, mainly motivated by frequency assignment problems in which transmitters are not allowed to operate on the same frequency channel. We con...
Radio labeling with pre-assigned frequencies
Bodlaender, H.L.; Broersma, H.J.; Fomin, F.V.; Pyatkin, A.V.; Woeginger, G.J.
2002-01-01
A radio labeling of a graph $G$ is an assignment of pairwise distinct, positive integer labels to the vertices of $G$ such that labels of adjacent vertices differ by at least $2$. The radio labeling problem (\\mbox{\\sc RL}) consists in determining a radio labeling that minimizes the maximum label that is used (the so-called span of the labeling). \\mbox{\\sc RL} is a well-studied problem, mainly motivated by frequency assignment problems in which transmitters are not allowed to operate on the sa...
Evolving Networks with Nonlinear Assignment of Weight
Institute of Scientific and Technical Information of China (English)
TANG Chao; TANG Yi
2006-01-01
We propose a weighted evolving network model in which the underlying topological structure is still driven by the degree according to the preferential attachment rule while the weight assigned to the newly established edges is dependent on the degree in a nonlinear form. By varying the parameter α that controls the function determining the assignment of weight, a wide variety of power-law behaviours of the total weight distributions as well as the diversity of the weight distributions of edges are displayed. Variation of correlation and heterogeneity in the network is illustrated as well.
An Optimal Online Algorithm for Halfplane Intersection
Institute of Scientific and Technical Information of China (English)
WU Jigang; JI Yongchang; CHEN Guoliang
2000-01-01
The intersection of N halfplanes is a basic problem in computational geometry and computer graphics. The optimal offiine algorithm for this problem runs in time O(N log N). In this paper, an optimal online algorithm which runs also in time O(N log N) for this problem is presented. The main idea of the algorithm is to give a new definition for the left side of a given line, to assign the order for the points of a convex polygon, and then to use binary search method in an ordered vertex set. The data structure used in the algorithm is no more complex than array.
75 FR 55352 - Delegation of Authorities and Assignment of Responsibilities
2010-09-10
... of the Secretary Delegation of Authorities and Assignment of Responsibilities Secretary's Order 5-2010 Subject: Delegation of Authorities and Assignment of Responsibilities to the Administrator, Wage and Hour Division. 1. Purpose. To delegate authorities and assign responsibilities to...
Systematic evaluation of combined automated NOE assignment and structure calculation with CYANA
International Nuclear Information System (INIS)
The automated assignment of NOESY cross peaks has become a fundamental technique for NMR protein structure analysis. A widely used algorithm for this purpose is implemented in the program CYANA. It has been used for a large number of structure determinations of proteins in solution but a systematic evaluation of its performance has not yet been reported. In this paper we systematically analyze the reliability of combined automated NOESY assignment and structure calculation with CYANA under a variety of conditions on the basis of the experimental NMR data sets of ten proteins. To evaluate the robustness of the algorithm, the original high-quality experimental data sets were modified in different ways to simulate the effect of data imperfections, i.e. incomplete or erroneous chemical shift assignments, missing NOESY cross peaks, inaccurate peak positions, inaccurate peak intensities, lower dimensionality NOESY spectra, and higher tolerances for the matching of chemical shifts and peak positions. The results show that the algorithm is remarkably robust with regard to imperfections of the NOESY peak lists and the chemical shift tolerances but susceptible to lacking or erroneous resonance assignments, in particular for nuclei that are involved in many NOESY cross peaks
A New Page Ranking Algorithm Based On WPRVOL Algorithm
Directory of Open Access Journals (Sweden)
Roja Javadian Kootenae
2013-03-01
Full Text Available The amount of information on the web is always growing, thus powerful search tools are needed to search for such a large collection. Search engines in this direction help users so they can find their desirable information among the massive volume of information in an easier way. But what is important in the search engines and causes a distinction between them is page ranking algorithm used in them. In this paper a new page ranking algorithm based on "Weighted Page Ranking based on Visits of Links (WPRVOL Algorithm" for search engines is being proposed which is called WPR'VOL for short. The proposed algorithm considers the number of visits of first and second level in-links. The original WPRVOL algorithm takes into account the number of visits of first level in-links of the pages and distributes rank scores based on the popularity of the pages whereas the proposed algorithm considers both in-links of that page (first level in-links and in-links of the pages that point to it (second level in-links in order to calculation of rank of the page, hence more related pages are displayed at the top of search result list. In the summary it is said that the proposed algorithm assigns higher rank to pages that both themselves and pages that point to them be important.
Genetic Algorithms Principles Towards Hidden Markov Model
Directory of Open Access Journals (Sweden)
Nabil M. Hewahi
2011-10-01
Full Text Available In this paper we propose a general approach based on Genetic Algorithms (GAs to evolve Hidden Markov Models (HMM. The problem appears when experts assign probability values for HMM, they use only some limited inputs. The assigned probability values might not be accurate to serve in other cases related to the same domain. We introduce an approach based on GAs to find
out the suitable probability values for the HMM to be mostly correct in more cases than what have been used to assign the probability values.
Tabu search for target-radar assignment
DEFF Research Database (Denmark)
Hindsberger, Magnus; Vidal, Rene Victor Valqui
2000-01-01
In the paper the problem of assigning air-defense illumination radars to enemy targets is presented. A tabu search metaheuristic solution is described and the results achieved are compared to those of other heuristic approaches, implementation and experimental aspects are discussed. It is argued...... that tabu search could be used in near real-time decision making systems...
Teaching Historical Analysis through Creative Writing Assignments
Peterson, Janine Larmon; Graham, Lea
2015-01-01
Incorporating creative writing exercises in history courses can heighten students' critical reading and analytical skills in an active learning model. We identify and define two types of possible assignments that use model texts as their locus: centripetal, which focuses on specific context and disciplinary terms, and centrifugal, which address…
24 CFR 221.255 - Assignment option.
2010-04-01
... DEVELOPMENT MORTGAGE AND LOAN INSURANCE PROGRAMS UNDER NATIONAL HOUSING ACT AND OTHER AUTHORITIES LOW COST AND MODERATE INCOME MORTGAGE INSURANCE-SAVINGS CLAUSE Contract Rights and Obligations-Low Cost Homes § 221.255... 24 Housing and Urban Development 2 2010-04-01 2010-04-01 false Assignment option. 221.255...
24 CFR 221.770 - Assignment option.
2010-04-01
... DEVELOPMENT MORTGAGE AND LOAN INSURANCE PROGRAMS UNDER NATIONAL HOUSING ACT AND OTHER AUTHORITIES LOW COST AND... 24 Housing and Urban Development 2 2010-04-01 2010-04-01 false Assignment option. 221.770 Section 221.770 Housing and Urban Development Regulations Relating to Housing and Urban Development...
Experimental results on quadratic assignment problem
Directory of Open Access Journals (Sweden)
N.P. Nikolov
1999-08-01
Full Text Available The paper presents experimental results on quadratic assignment problem. The "scanning area" method formulated for radioelectronic equipment design is applied. For all more complex tests ours results are better or coincident with the ones known in literature. Conclusion concerning the effectiveness of method are given.
12 CFR 345.28 - Assigned ratings.
2010-01-01
...,” “satisfactory,” “needs to improve,” or “substantial noncompliance” based on the bank's performance under the... 12 Banks and Banking 4 2010-01-01 2010-01-01 false Assigned ratings. 345.28 Section 345.28 Banks and Banking FEDERAL DEPOSIT INSURANCE CORPORATION REGULATIONS AND STATEMENTS OF GENERAL...
Incentivized optimal advert assignment via utility decomposition
F. Kelly; P. Key; N. Walton
2014-01-01
We consider a large-scale Ad-auction where adverts are assigned over a potentially infinite number of searches. We capture the intrinsic asymmetries in information between advertisers, the advert platform and the space of searches: advertisers know and can optimize the average performance of their a
Tabu search for target-radar assignment
DEFF Research Database (Denmark)
Hindsberger, Magnus; Vidal, Rene Victor Valqui
2000-01-01
In the paper the problem of assigning air-defense illumination radars to enemy targets is presented. A tabu search metaheuristic solution is described and the results achieved are compared to those of other heuristic approaches, implementation and experimental aspects are discussed. It is argued...
Strategy-Proof Assignment Of Multiple Resources
DEFF Research Database (Denmark)
Erlanson, Albin; Szwagrzak, Karol
2015-01-01
We examine the strategy-proof allocation of multiple resources; an application is the assignment of packages of tasks, workloads, and compensations among the members of an organization. In the domain of multidimensional single-peaked preferences, we find that any allocation mechanism obtained by ......), some of which date back to the Babylonian Talmud....
On Online Assignments in a Calculus Class
Jungic, Veselin; Kent, Deborah; Menz, Petra
2012-01-01
In this paper, we describe our experience with the creation and utilization of online assignments for several calculus classes at Simon Fraser University (SFU). We present our findings regarding available software by considering the needs and perspectives of the instructors, students, and administrators. We provide a list of questions that guide…
Systematic Sorting: Teacher Characteristics and Class Assignments
Kalogrides, Demetra; Loeb, Susanna; Beteille, Tara
2013-01-01
Although prior research has documented differences in the distribution of teacher characteristics across schools serving different student populations, few studies have examined the extent to which teacher sorting occurs within schools. This study uses data from one large urban school district and compares the class assignments of teachers who…
Hromkovic, Juraj
2009-01-01
Explores the science of computing. This book starts with the development of computer science, algorithms and programming, and then explains and shows how to exploit the concepts of infinity, computability, computational complexity, nondeterminism and randomness.
Assignment and Correspondence Tracking System - Tactical / Operational Reporting
Social Security Administration — Reporting data store for the Assignment and Correspondence Tracking System (ACT). ACT automates the assignment and tracking of correspondence processing within the...
Artificial intelligence applied to assigned merchandise location in retail sales systems
Directory of Open Access Journals (Sweden)
Cruz-Domínguez, O.
2016-05-01
Full Text Available This paper presents an option for improving the process of assigning storage locations for merchandise in a warehouse. A disadvantage of policies in the literature is that the merchandise is assigned allocation only according to the volume of sales and the rotation it presents. However, in some cases it is necessary to deal with other aspects such as family group membership, the physical characteristics of the products, and their sales pattern to design an integral policy. This paper presents an alternative to the afore- mentioned process using Flexsim®, artificial neural networks, and genetic algorithms.
Dominant pole and eigenstructure assignment for positive systems with state feedback
Li, Zhao; Lam, James
2016-09-01
In this paper, the dominant pole assignment problem, the dominant eigenstructure assignment problem and the robust dominant pole assignment problem for linear time-invariant positive systems with state feedback are considered. The dominant pole assignment problem is formulated as a linear programming problem, and the dominant eigenstructure problem is formulated as a quasiconvex optimisation problem with linear constraints. The robust dominant pole assignment problem is formulated as a non-convex optimisation problem with non-linear constraints which is solved using particle swarm optimisation (PSO) with an efficient scheme which employs the dominant eigenstructure assignment technique to accelerate the convergence of the PSO procedure. Each of the three problems can be further constrained by requiring that the controller has a pre-specified structure, or the gain matrix have both elementwise upper and lower bounds. These constraints can be incorporated into the proposed scheme without increasing the complexity of the algorithms. Both the continuous-time case and the discrete-time case are treated in the paper.
Capacity constrained assignment in spatial databases
DEFF Research Database (Denmark)
U, Leong Hou; Yiu, Man Lung; Mouratidis, Kyriakos;
2008-01-01
Given a point set P of customers (e.g., WiFi receivers) and a point set Q of service providers (e.g., wireless access points), where each q 2 Q has a capacity q.k, the capacity constrained assignment (CCA) is a matching M Q × P such that (i) each point q 2 Q (p 2 P) appears at most k times (at most...
Total Synthesis and Stereochemical Assignment of Callyspongiolide.
Zhou, Jingjing; Gao, Bowen; Xu, Zhengshuang; Ye, Tao
2016-06-01
Total synthesis of four callyspongiolide stereoisomers led to unambiguous assignment of relative and absolute stereochemistry of the natural product. Key features of the convergent, fully stereocontrolled route include the use of Krische allylation, Kiyooka Aldol reaction, Kociénski-Julia olefination, Still-Gennari olefination, Yamaguchi macrocyclization, and Sonogashira coupling reaction. Biological evaluation of the synthesized compounds against an array of cancer cells revealed that the stereochemistry of the macrolactone core played an important role. PMID:27227371
Online Ad Assignment with an Ad Exchange
Dvořák, Wolfgang; Henzinger, Monika
2016-01-01
Ad exchanges are becoming an increasingly popular way to sell advertisement slots on the internet. An ad exchange is basically a spot market for ad impressions. A publisher who has already signed contracts reserving advertisement impressions on his pages can choose between assigning a new ad impression for a new page view to a contracted advertiser or to sell it at an ad exchange. This leads to an online revenue maximization problem for the publisher. Given a new impression to sell decide whe...
Incentivized optimal advert assignment via utility decomposition
Kelly, F.; Key, P.; Walton, N.
2014-01-01
We consider a large-scale Ad-auction where adverts are assigned over a potentially infinite number of searches. We capture the intrinsic asymmetries in information between advertisers, the advert platform and the space of searches: advertisers know and can optimize the average performance of their advertisement campaign; the platform knows and can optimize on each search instance; and, neither party knows the distribution of the infinite number of searches that can occur. We look at maximizin...
Autocorrelation Measures for the Quadratic Assignment Problem
Chicano, Francisco; Luque, Gabriel; Alba, Enrique
2012-01-01
In this article we provide an exact expression for computing the autocorrelation coefficient $\\xi$ and the autocorrelation length $\\ell$ of any arbitrary instance of the Quadratic Assignment Problem (QAP) in polynomial time using its elementary landscape decomposition. We also provide empirical evidence of the autocorrelation length conjecture in QAP and compute the parameters $\\xi$ and $\\ell$ for the 137 instances of the QAPLIB. Our goal is to better characterize the difficulty of this impor...
Automated feedback generation for introductory programming assignments
Singh, Rishabh; Gulwani, Sumit; Solar-Lezama, Armando
2013-01-01
We present a new method for automatically providing feedback for introductory programming problems. In order to use this method, we need a reference implementation of the assignment, and an error model consisting of potential corrections to errors that students might make. Using this information, the system automatically derives minimal corrections to student's incorrect solutions, providing them with a measure of exactly how incorrect a given solution was, as well as feedback about what they...
Optimal State Assignment for Finite State Machines
Micheli, Giovanni De; Brayton, Robert K.; Sangiovanni-Vincentelli, Alberto
1985-01-01
Computer-Aided synthesis of sequential functions of VLSI systems, such as microprocessor control units, must include design optimization procedures to yield area-effective circuits. We model sequential functions as deterministic synchronous Finite State Machines (FSM's), and we consider a regular and structured implementation by means of Programmable Logic Arrays (PLA's) and feedback registers. State assignment, i.e., binary encoding of the internal states of the finite state machine, affects...
28 CFR 301.103 - Inmate work assignments.
2010-07-01
... COMPENSATION General § 301.103 Inmate work assignments. The unit team of each inmate, which ordinarily designates work assignments, or whoever makes work assignments, shall review appropriate medical records... 28 Judicial Administration 2 2010-07-01 2010-07-01 false Inmate work assignments. 301.103...
49 CFR 821.35 - Assignment, duties and powers.
2010-10-01
... SAFETY BOARD RULES OF PRACTICE IN AIR SAFETY PROCEEDINGS Law Judges § 821.35 Assignment, duties and powers. (a) Assignment of law judge and duration of assignment. The chief law judge shall assign a law... addressed to the Case Manager for handling by the chief law judge, who may handle these matters...
The Fast Fibonacci Decompression Algorithm
Baca, R; Platos, J; Kratky, M; El-Qawasmeh, E
2007-01-01
Data compression has been widely applied in many data processing areas. Compression methods use variable-size codes with the shorter codes assigned to symbols or groups of symbols that appear in the data frequently. Fibonacci coding, as a representative of these codes, is used for compressing small numbers. Time consumption of a decompression algorithm is not usually as important as the time of a compression algorithm. However, efficiency of the decompression may be a critical issue in some cases. For example, a real-time compression of tree data structures follows this issue. Tree's pages are decompressed during every reading from a secondary storage into the main memory. In this case, the efficiency of a decompression algorithm is extremely important. We have developed a Fast Fibonacci decompression for this purpose. Our approach is up to $3.5\\times$ faster than the original implementation.
Hu, T C
2002-01-01
Newly enlarged, updated second edition of a valuable text presents algorithms for shortest paths, maximum flows, dynamic programming and backtracking. Also discusses binary trees, heuristic and near optimums, matrix multiplication, and NP-complete problems. 153 black-and-white illus. 23 tables.Newly enlarged, updated second edition of a valuable, widely used text presents algorithms for shortest paths, maximum flows, dynamic programming and backtracking. Also discussed are binary trees, heuristic and near optimums, matrix multiplication, and NP-complete problems. New to this edition: Chapter 9
Anna Bourmistrova; Milan Simic; Reza Hoseinnezhad; Jazar, Reza N.
2011-01-01
The autodriver algorithm is an intelligent method to eliminate the need of steering by a driver on a well-defined road. The proposed method performs best on a four-wheel steering (4WS) vehicle, though it is also applicable to two-wheel-steering (TWS) vehicles. The algorithm is based on coinciding the actual vehicle center of rotation and road center of curvature, by adjusting the kinematic center of rotation. The road center of curvature is assumed prior information for a given road, while th...
QoS Aware Wavelength Assignment in Wavelength Division Multiplexing Based Optical Networks
Directory of Open Access Journals (Sweden)
U. Mahmud
2015-01-01
Full Text Available Wavelength Division Multiplexing (WDM is used in optical networks to implement data circuits. These circuits allow exchange of information as a measure of wavelength in optical domain. Quality of Service (QoS provisioning is one of the issues in WDM optical networks. This paper discusses different QoS aware Routing and Wavelength Assignment (RWA algorithms. Some unaddressed issues are identified that include the effects of degraded performance, traffic patterns and type of QoS service for users. A software module is proposed that calculates a ‘D’ factor facilitating in the wavelength assignment for QoS provisioning. This module is designed to work in conjunction with existing RWA algorithms.
Hawthorn-Embree, Meredith L.; Taylor, Emily P.; Skinner, Christopher H.; Parkhurst, John; Nalls, Meagan L.
2014-01-01
After students acquire a skill, mastery often requires them to choose to engage in assigned academic activities (e.g., independent seatwork, and homework). Although students may be more likely to choose to work on partially completed assignments than on new assignments, the partial assignment completion (PAC) effect may not be very powerful. The…
Directory of Open Access Journals (Sweden)
Anna Bourmistrova
2011-02-01
Full Text Available The autodriver algorithm is an intelligent method to eliminate the need of steering by a driver on a well-defined road. The proposed method performs best on a four-wheel steering (4WS vehicle, though it is also applicable to two-wheel-steering (TWS vehicles. The algorithm is based on coinciding the actual vehicle center of rotation and road center of curvature, by adjusting the kinematic center of rotation. The road center of curvature is assumed prior information for a given road, while the dynamic center of rotation is the output of dynamic equations of motion of the vehicle using steering angle and velocity measurements as inputs. We use kinematic condition of steering to set the steering angles in such a way that the kinematic center of rotation of the vehicle sits at a desired point. At low speeds the ideal and actual paths of the vehicle are very close. With increase of forward speed the road and tire characteristics, along with the motion dynamics of the vehicle cause the vehicle to turn about time-varying points. By adjusting the steering angles, our algorithm controls the dynamic turning center of the vehicle so that it coincides with the road curvature center, hence keeping the vehicle on a given road autonomously. The position and orientation errors are used as feedback signals in a closed loop control to adjust the steering angles. The application of the presented autodriver algorithm demonstrates reliable performance under different driving conditions.
Algorithms for worst-case tolerance optimization
DEFF Research Database (Denmark)
Schjær-Jacobsen, Hans; Madsen, Kaj
1979-01-01
New algorithms are presented for the solution of optimum tolerance assignment problems. The problems considered are defined mathematically as a worst-case problem (WCP), a fixed tolerance problem (FTP), and a variable tolerance problem (VTP). The basic optimization problem without tolerances is d...
Algorithms and theoretical topics on selected combinatorial optimization problems
Kaveh, Arman
2010-01-01
We study the Quadratic Assignment Problem (QAP), Three Dimensional Assignment Problem (3AP) and Quadratic Three Dimensional Assignment Problem (Q3AP), which combines aspects of both QAP and 3AP. The three problems are known to be NP-hard. We propose new algorithms for obtaining near optimal solutions of QAP and 3AP and present computational results. Our algorithms obtain improved solutions in some benchmark instances of QAP and 3AP. We also discuss theoretical results on 3AP and Q3AP such as ...
Karipidis, Eleftherios; Sidiropoulos, Nicholas; Tassiulas, Leandros
2008-01-01
The joint power control and base station (BS) assignment problem is considered under Quality-of-Service (QoS) constraints. If a feasible solution exists, the problem can be efficiently solved using existing distributed algorithms. Infeasibility is often encountered in practice, however, which brings up the issue of optimal admission control. The joint problem is NP-hard, yet important for QoS provisioning and bandwidth-efficient operation of existing and emerging cellular and overlay/underlay...
Research on bulk-cargo-port berth assignment based on priority of resource allocation
Directory of Open Access Journals (Sweden)
Chunfang Guo
2013-03-01
Full Text Available Purpose: The purpose of this paper is to propose a Priority of Resource Allocation model about how to utilize the resources of the port efficiently, through the improvement of traditional ant colony algorithm, the ship-berth matching relation constraint matrix formed by ontology reasoning. Design/methodology/approach: Through questionnaires?Explore factor analysis (EFA and principal component analysis, the authors extract the importance of the goods, the importance of customers, and type of trade as the main factors of the ship operating priority. Then the authors combine berth assignment problem with the improved ant colony algorithm, and use the model to improve ship scheduling quality. Finally, the authors verify the model with physical data in a bulk-cargo-port in China. Findings: Test by the real data of bulk cargo port, it show that ships’ resource using priority and the length of waiting time are consistent; it indicates that the priority of resource allocation play a prominent role in improving ship scheduling quality. Research limitations: The questionnaires is limited in only one port group, more related Influence factors should be considered to extend the conclusion. Practical implications: The Priority of Resource Allocation model in this paper can be used to improve the efficiency of the dynamic berth assignment. Originality: This paper makes the time of ship in port minimized as the optimization of key indicators and establishes a dynamic berth assignment model based on improved ant colony algorithm and the ontology reasoning model.
The K-modes algorithm for clustering
Carreira-Perpiñán, Miguel Á.; Wang, Weiran
2013-01-01
Many clustering algorithms exist that estimate a cluster centroid, such as K-means, K-medoids or mean-shift, but no algorithm seems to exist that clusters data by returning exactly K meaningful modes. We propose a natural definition of a K-modes objective function by combining the notions of density and cluster assignment. The algorithm becomes K-means and K-medoids in the limit of very large and very small scales. Computationally, it is slightly slower than K-means but much faster than mean-...
DEFF Research Database (Denmark)
Markham, Annette
This paper takes an actor network theory approach to explore some of the ways that algorithms co-construct identity and relational meaning in contemporary use of social media. Based on intensive interviews with participants as well as activity logging and data tracking, the author presents a richly...... layered set of accounts to help build our understanding of how individuals relate to their devices, search systems, and social network sites. This work extends critical analyses of the power of algorithms in implicating the social self by offering narrative accounts from multiple perspectives. It also...... contributes an innovative method for blending actor network theory with symbolic interaction to grapple with the complexity of everyday sensemaking practices within networked global information flows....
Efficient routing and spectrum assignment in elastic optical networks with time scheduled traffic
Qiu, Yang; Fan, Zheyu; Chan, Chun-Kit
2016-07-01
Elastic optical networks (EONs) employ dynamic routing and spectrum assignment (RSA) algorithms to support diverse services and heterogeneous requests. However, these RSA algorithms may possibly induce spectrum fragments when allocating spectrum to accommodate different service requests. Therefore, such induced spectrum fragments should also be regarded as spectrum consumption besides the allocated spectrum by RSA algorithms. In this paper, by additionally considering the holding times of lightpaths and service connections, we first introduce a comprehensive spectrum consumption model to simultaneously investigate both the allocated and the fragmented spectrum consumptions. Then we solve this model in both static and dynamic traffic scenarios, by either formulating the RSA problem with time-scheduled traffic or introducing a time-aware spectrum-efficient heuristics algorithm. Since no defragmentation is executed in spectrum allocation, the proposed RSA algorithm requires no traffic disruption and can be realized more easily in reality. Simulation results show that the proposed algorithm reduces the comprehensive spectrum consumption and has lower bandwidth blocking probability than the typical first-fit RSA algorithm.
Directory of Open Access Journals (Sweden)
Pascale Minet
2013-07-01
Full Text Available Convergecast is the transmission paradigm used by data gathering applications in wireless sensor networks (WSNs. For efficiency reasons, a collision-free slotted medium access is typically used: time slots are assigned to non-conflicting transmitters. Furthermore, in any slot, only the transmitters and the corresponding receivers are awake, the other nodes sleeping in order to save energy. Since a multichannel network increases the throughput available to the application and reduces interference, multichannel slot assignment is an emerging research domain in WSNs. First, we focus on a multichannel time slot assignment that minimizes the data gathering delays. We compute the optimal time needed for a raw data convergecast in various multichannel topologies. Then, we focus on how to adapt such an assignment to dynamic demands of transmissions (e.g., alarms, temporary additional application needs and retransmissions. We formalize the problem using linear programming, and we propose an incremental technique that operates on an optimized primary schedule to provide bonus slots to meet new transmission needs. We propose AMSA, an Adaptive Multichannel Slot Assignment algorithm, which takes advantage of bandwidth spatial reuse, and we evaluate its performances in terms of the number of slots required, slot reuse, throughput and the number of radio state switches.
WDM Multicast Tree Construction Algorithms and Their Comparative Evaluations
Makabe, Tsutomu; Mikoshi, Taiju; Takenaka, Toyofumi
We propose novel tree construction algorithms for multicast communication in photonic networks. Since multicast communications consume many more link resources than unicast communications, effective algorithms for route selection and wavelength assignment are required. We propose a novel tree construction algorithm, called the Weighted Steiner Tree (WST) algorithm and a variation of the WST algorithm, called the Composite Weighted Steiner Tree (CWST) algorithm. Because these algorithms are based on the Steiner Tree algorithm, link resources among source and destination pairs tend to be commonly used and link utilization ratios are improved. Because of this, these algorithms can accept many more multicast requests than other multicast tree construction algorithms based on the Dijkstra algorithm. However, under certain delay constraints, the blocking characteristics of the proposed Weighted Steiner Tree algorithm deteriorate since some light paths between source and destinations use many hops and cannot satisfy the delay constraint. In order to adapt the approach to the delay-sensitive environments, we have devised the Composite Weighted Steiner Tree algorithm comprising the Weighted Steiner Tree algorithm and the Dijkstra algorithm for use in a delay constrained environment such as an IPTV application. In this paper, we also give the results of simulation experiments which demonstrate the superiority of the proposed Composite Weighted Steiner Tree algorithm compared with the Distributed Minimum Hop Tree (DMHT) algorithm, from the viewpoint of the light-tree request blocking.
Fast automated protein NMR data collection and assignment by ADAPT-NMR on Bruker spectrometers
Lee, Woonghee; Hu, Kaifeng; Tonelli, Marco; Bahrami, Arash; Neuhardt, Elizabeth; Glass, Karen C.; Markley, John L.
2013-11-01
ADAPT-NMR (Assignment-directed Data collection Algorithm utilizing a Probabilistic Toolkit in NMR) supports automated NMR data collection and backbone and side chain assignment for [U-13C, U-15N]-labeled proteins. Given the sequence of the protein and data for the orthogonal 2D 1H-15N and 1H-13C planes, the algorithm automatically directs the collection of tilted plane data from a variety of triple-resonance experiments so as to follow an efficient pathway toward the probabilistic assignment of 1H, 13C, and 15N signals to specific atoms in the covalent structure of the protein. Data collection and assignment calculations continue until the addition of new data no longer improves the assignment score. ADAPT-NMR was first implemented on Varian (Agilent) spectrometers [A. Bahrami, M. Tonelli, S.C. Sahu, K.K. Singarapu, H.R. Eghbalnia, J.L. Markley, PLoS One 7 (2012) e33173]. Because of broader interest in the approach, we present here a version of ADAPT-NMR for Bruker spectrometers. We have developed two AU console programs (ADAPT_ORTHO_run and ADAPT_NMR_run) that run under TOPSPIN Versions 3.0 and higher. To illustrate the performance of the algorithm on a Bruker spectrometer, we tested one protein, chlorella ubiquitin (76 amino acid residues), that had been used with the Varian version: the Bruker and Varian versions achieved the same level of assignment completeness (98% in 20 h). As a more rigorous evaluation of the Bruker version, we tested a larger protein, BRPF1 bromodomain (114 amino acid residues), which yielded an automated assignment completeness of 86% in 55 h. Both experiments were carried out on a 500 MHz Bruker AVANCE III spectrometer equipped with a z-gradient 5 mm TCI probe. ADAPT-NMR is available at http://pine.nmrfam.wisc.edu/ADAPT-NMR in the form of pulse programs, the two AU programs, and instructions for installation and use.
Xia, Yan; Zeng, Yingzhi
2016-02-01
This paper proposed a broadcast Channel Assignment Mechanism on base of optimized Broadcast Tree for wireless Mesh network (WMN), which is created by Branch and Bound Method. The simulations show that our algorithm not only reduces the broadcast redundancy but also avoids the potential channel interferences produced by unnecessary relay nodes.
A New RWA Algorithm Based on Multi-Objective
Institute of Scientific and Technical Information of China (English)
无
2003-01-01
In this article, we studied the associated research problems and challenges on routing and wavelength assignment (RWA) in WDM (wavelength division multiplexing) networks. Various RWA approaches are examined and compared. We proposed a new RWA algorithm based on multi-objective. In this new algorithm, we consider multiple network optimizing objectives to setup a lightpath with maximize profit and shortest path under the limited resources. By comparing and analyzing, the proposed algorithm is much better ...
Assignment of uncertainties to scientific data
International Nuclear Information System (INIS)
Long-standing problems of uncertainty assignment to scientific data came into a sharp focus in recent years when uncertainty information ('covariance files') had to be added to application-oriented large libraries of evaluated nuclear data such as ENDF and JEF. Question arouse about the best way to express uncertainties, the meaning of statistical and systematic errors, the origin of correlation and construction of covariance matrices, the combination of uncertain data from different sources, the general usefulness of results that are strictly valid only for Gaussian or only for linear statistical models, etc. Conventional statistical theory is often unable to give unambiguous answers, and tends to fail when statistics is bad so that prior information becomes crucial. Modern probability theory, on the other hand, incorporating decision information becomes group-theoretic results, is shown to provide straight and unique answers to such questions, and to deal easily with prior information and small samples. (author). 10 refs
Diagnosis code assignment: models and evaluation metrics
Perotte, Adler; Pivovarov, Rimma; Natarajan, Karthik; Weiskopf, Nicole; Wood, Frank; Elhadad, Noémie
2014-01-01
Background and objective The volume of healthcare data is growing rapidly with the adoption of health information technology. We focus on automated ICD9 code assignment from discharge summary content and methods for evaluating such assignments. Methods We study ICD9 diagnosis codes and discharge summaries from the publicly available Multiparameter Intelligent Monitoring in Intensive Care II (MIMIC II) repository. We experiment with two coding approaches: one that treats each ICD9 code independently of each other (flat classifier), and one that leverages the hierarchical nature of ICD9 codes into its modeling (hierarchy-based classifier). We propose novel evaluation metrics, which reflect the distances among gold-standard and predicted codes and their locations in the ICD9 tree. Experimental setup, code for modeling, and evaluation scripts are made available to the research community. Results The hierarchy-based classifier outperforms the flat classifier with F-measures of 39.5% and 27.6%, respectively, when trained on 20 533 documents and tested on 2282 documents. While recall is improved at the expense of precision, our novel evaluation metrics show a more refined assessment: for instance, the hierarchy-based classifier identifies the correct sub-tree of gold-standard codes more often than the flat classifier. Error analysis reveals that gold-standard codes are not perfect, and as such the recall and precision are likely underestimated. Conclusions Hierarchy-based classification yields better ICD9 coding than flat classification for MIMIC patients. Automated ICD9 coding is an example of a task for which data and tools can be shared and for which the research community can work together to build on shared models and advance the state of the art. PMID:24296907
Methods of using the quadratic assignment problem solution
Directory of Open Access Journals (Sweden)
Izabela Kudelska
2012-09-01
Full Text Available Background: Quadratic assignment problem (QAP is one of the most interesting of combinatorial optimization. Was presented by Koopman and Beckamanna in 1957, as a mathematical model of the location of indivisible tasks. This problem belongs to the class NP-hard issues. This forces the application to the solution already approximate methods for tasks with a small size (over 30. Even though it is much harder than other combinatorial optimization problems, it enjoys wide interest because it models the important class of decision problems. Material and methods: The discussion was an artificial intelligence tool that allowed to solve the problem QAP, among others are: genetic algorithms, Tabu Search, Branch and Bound. Results and conclusions: QAP did not arise directly as a model for certain actions, but he found its application in many areas. Examples of applications of the problem is: arrangement of buildings on the campus of the university, layout design of electronic components in systems with large scale integration (VLSI, design a hospital, arrangement of keys on the keyboard.
Robust Scheduling for Berth Allocation and Quay Crane Assignment Problem
Directory of Open Access Journals (Sweden)
M. Rodriguez-Molins
2014-01-01
Full Text Available Decision makers must face the dynamism and uncertainty of real-world environments when they need to solve the scheduling problems. Different incidences or breakdowns, for example, initial data could change or some resources could become unavailable, may eventually cause the infeasibility of the obtained schedule. To overcome this issue, a robust model and a proactive approach are presented for scheduling problems without any previous knowledge about incidences. This paper is based on proportionally distributing operational buffers among the tasks. In this paper, we consider the berth allocation problem and the quay crane assignment problem as a representative example of scheduling problems. The dynamism and uncertainty are managed by assessing the robustness of the schedules. The robustness is introduced by means of operational buffer times to absorb those unknown incidences or breakdowns. Therefore, this problem becomes a multiobjective combinatorial optimization problem that aims to minimize the total service time, to maximize the buffer times, and to minimize the standard deviation of the buffer times. To this end, a mathematical model and a new hybrid multiobjective metaheuristic is presented and compared with two well-known multiobjective genetic algorithms: NSGAII and SPEA2+.
Assignment Choice: Do Students Choose Briefer Assignments or Finishing What They Started?
Hawthorn-Embree, Meredith L.; Skinner, Christopher H.; Parkhurst, John; O'Neil, Michael; Conley, Elisha
2010-01-01
Academic skill development requires engagement in effortful academic behaviors. Although students may be more likely to choose to engage in behaviors that require less effort, they also may be motivated to complete assignments that they have already begun. Seventh-grade students (N = 88) began a mathematics computation worksheet, but were stopped…
System optimal traffic assignment with departure time choice
Chow, A. H. F.
2007-01-01
This thesis investigates analytical dynamic system optimal assignment with departure time choice in a rigorous and original way. Dynamic system optimal assignment is formulated here as a state-dependent optimal control problem. A fixed volume of traffic is assigned to departure times and routes such that the total system travel cost is minimized. Although the system optimal assignment is not a realistic representation of traffic, it provides a bound on performance and shows how...
24 CFR 255.2 - GNMA right to assignment.
2010-04-01
... will have the right to perfect an assignment of the mortgage to itself. However, before exercising this right, GNMA will attempt to have the Mortgage assigned to another eligible coinsuring lender (unless... defaulting lender-issuer, GNMA will have the right to perfect an assignment of the Coinsured...
24 CFR 252.2 - GNMA right to assignment.
2010-04-01
....2 GNMA right to assignment. If the lender-issuer defaults on its obligations under the GNMA Mortgage... defaulting lender-issuer, GNMA will have the right to perfect an assignment of the mortgage to itself. However, before exercising this right, GNMA will attempt to have the Mortgage assigned to another...
24 CFR 251.2 - GNMA right to assignment.
2010-04-01
... right to assignment. If the lender-issuer defaults on its obligations under the GNMA Mortgage-Backed...-issuer, GNMA will have the right to perfect an assignment of the mortgage to itself. However, before exercising this right, GNMA will attempt to have the Mortgage assigned to another eligible coinsuring...
Solving the k-cardinality assignment problem by transformation
A. Volgenant
2004-01-01
The k-cardinality Linear Assignment Problem (k-LAP) with k a given integer is a generalization of the linear assignment problem: one wants to assign k rows (a free choice out of more rows) to k columns (a free choice out of more columns) minimizing the sum of the corresponding costs. For this polyno
75 FR 55354 - Delegation of Authority and Assignment of Responsibilities
2010-09-10
... of the Secretary Delegation of Authority and Assignment of Responsibilities Secretary's Order 3-2010 Subject: Delegation of Authority and Assignment of Responsibilities to the Employee Benefits Security Administration. 1. Purpose. To delegate authority and assign responsibilities for the administration of...
Optimal assignment of incoming flights to baggage carousels at airports
DEFF Research Database (Denmark)
Barth, Torben C.
The problem considered in this report is an assignment problem occurring at airports. This problem concerns the assignment of baggage carousels in baggage claim halls to arriving aircraft (baggage carousel assignment problem). This is a highly dynamic problem since disruptions frequently occur du...
Learning through Writing: Teaching Critical Thinking Skills in Writing Assignments
Cavdar, Gamze; Doe, Sue
2012-01-01
Traditional writing assignments often fall short in addressing problems in college students' writing as too often these assignments fail to help students develop critical thinking skills and comprehension of course content. This article reports the use of a two-part (staged) writing assignment with postscript as a strategy for improving critical…
Assessment of a Diversity Assignment in a PR Principles Course
Gallicano, Tiffany Derville; Stansberry, Kathleen
2012-01-01
This study assesses an assignment for incorporating diversity into the principles of public relations course. The assignment is tailored to the challenges of using an active learning approach in a large lecture class. For the assignment, students write a goal, objectives, strategies, an identification of tactics, and evaluation plans for either…
Jang, Richard
2011-03-01
In NMR resonance assignment, an indispensable step in NMR protein studies, manually processed peaks from both N-labeled and C-labeled spectra are typically used as inputs. However, the use of homologous structures can allow one to use only N-labeled NMR data and avoid the added expense of using C-labeled data. We propose a novel integer programming framework for structure-based backbone resonance assignment using N-labeled data. The core consists of a pair of integer programming models: one for spin system forming and amino acid typing, and the other for backbone resonance assignment. The goal is to perform the assignment directly from spectra without any manual intervention via automatically picked peaks, which are much noisier than manually picked peaks, so methods must be error-tolerant. In the case of semi-automated/manually processed peak data, we compare our system with the Xiong-Pandurangan-Bailey- Kellogg\\'s contact replacement (CR) method, which is the most error-tolerant method for structure-based resonance assignment. Our system, on average, reduces the error rate of the CR method by five folds on their data set. In addition, by using an iterative algorithm, our system has the added capability of using the NOESY data to correct assignment errors due to errors in predicting the amino acid and secondary structure type of each spin system. On a publicly available data set for human ubiquitin, where the typing accuracy is 83%, we achieve 91% accuracy, compared to the 59% accuracy obtained without correcting for such errors. In the case of automatically picked peaks, using assignment information from yeast ubiquitin, we achieve a fully automatic assignment with 97% accuracy. To our knowledge, this is the first system that can achieve fully automatic structure-based assignment directly from spectra. This has implications in NMR protein mutant studies, where the assignment step is repeated for each mutant. © Copyright 2011, Mary Ann Liebert, Inc.
APPLYING REINFORCEMENT LEARNING TO THE WEAPON ASSIGNMENT PROBLEM IN AIR DEFENCE
Directory of Open Access Journals (Sweden)
Herman Le Roux
2011-11-01
Full Text Available The modern battlefield is a fast-paced, information-rich environment, where discovery of intent, situation awareness and the rapid evolution of concepts of operation and doctrine are critical success factors. A combination of the techniques investigated and tested in this work, together with other techniques in Artificial Intelligence (AI and modern computational techniques, may hold the key to relieving the burden of the decision-maker and aiding in better decision-making under pressure. The techniques investigated in this article were two methods from the machine-learning subfield of reinforcement learning (RL, namely a Monte Carlo (MC control algorithm with exploring starts (MCES, and an off-policy temporal-difference (TD learning-control algorithm, Q-learning. These techniques were applied to a simplified version of the weapon assignment (WA problem in air defence. The MCES control algorithm yielded promising results when searching for an optimal shooting order. A greedy approach was taken in the Q-learning algorithm, but experimentation showed that the MCES-control algorithm still performed significantly better than the Q-learning algorithm, even though it was slower.
A Bayesian approach to simultaneously quantify assignments and linguistic uncertainty
Energy Technology Data Exchange (ETDEWEB)
Chavez, Gregory M [Los Alamos National Laboratory; Booker, Jane M [BOOKER SCIENTIFIC FREDERICKSBURG; Ross, Timothy J [UNM
2010-10-07
Subject matter expert assessments can include both assignment and linguistic uncertainty. This paper examines assessments containing linguistic uncertainty associated with a qualitative description of a specific state of interest and the assignment uncertainty associated with assigning a qualitative value to that state. A Bayesian approach is examined to simultaneously quantify both assignment and linguistic uncertainty in the posterior probability. The approach is applied to a simplified damage assessment model involving both assignment and linguistic uncertainty. The utility of the approach and the conditions under which the approach is feasible are examined and identified.
Abbas, Ahmed
2014-04-19
Despite significant advances in automated nuclear magnetic resonance-based protein structure determination, the high numbers of false positives and false negatives among the peaks selected by fully automated methods remain a problem. These false positives and negatives impair the performance of resonance assignment methods. One of the main reasons for this problem is that the computational research community often considers peak picking and resonance assignment to be two separate problems, whereas spectroscopists use expert knowledge to pick peaks and assign their resonances at the same time. We propose a novel framework that simultaneously conducts slice picking and spin system forming, an essential step in resonance assignment. Our framework then employs a genetic algorithm, directed by both connectivity information and amino acid typing information from the spin systems, to assign the spin systems to residues. The inputs to our framework can be as few as two commonly used spectra, i.e., CBCA(CO)NH and HNCACB. Different from the existing peak picking and resonance assignment methods that treat peaks as the units, our method is based on \\'slices\\', which are one-dimensional vectors in three-dimensional spectra that correspond to certain (N, H) values. Experimental results on both benchmark simulated data sets and four real protein data sets demonstrate that our method significantly outperforms the state-of-the-art methods while using a less number of spectra than those methods. Our method is freely available at http://sfb.kaust.edu.sa/Pages/Software.aspx. © 2014 Springer Science+Business Media.
Optimal Index Assignment for Multiple Description Scalar Quantization
Zhang, Guoqiang; Kleijn, W Bastiaan
2011-01-01
We provide a method for designing an optimal index assignment for scalar K-description coding. The method stems from a construction of translated scalar lattices, which provides a performance advantage by exploiting a so-called staggered gain. Interestingly, generation of the optimal index assignment is based on a lattice in K-1 dimensional space. The use of the K-1 dimensional lattice facilitates analytic insight into the performance and eliminates the need for a greedy optimization of the index assignment. It is shown that that the optimal index assignment is not unique. This is illustrated for the two-description case, where a periodic index assignment is selected from possible optimal assignments and described in detail. The new index assignment is applied to design of a K-description quantizer, which is found to outperform a reference K-description quantizer at high rates. The performance advantage due to the staggered gain increases with increasing redundancy among the descriptions.
Improved Multi-objective Evolutionary Algorithm for Multi-agent Coalition Formation
Directory of Open Access Journals (Sweden)
Bo Xu
2013-12-01
Full Text Available one of the key problems in multi-agent coalition formation is to optimally assign and schedule resources. An improved multi-objective evolutionary Algorithm (IMOEA is proposed to solve this problem. Compared with several well-known algorithms such as NSGA、MOEA, experimental results show the algorithm is very suitable for coalition formation problem.
A tabu search approach for the NMR protein structure-based assignment problem.
Cavuşlar, Gizem; Çatay, Bülent; Apaydın, Mehmet Serkan
2012-01-01
Spectroscopy is an experimental technique which exploits the magnetic properties of specific nuclei and enables the study of proteins in solution. The key bottleneck of NMR studies is to map the NMR peaks to corresponding nuclei, also known as the assignment problem. Structure-Based Assignment (SBA) is an approach to solve this computationally challenging problem by using prior information about the protein obtained from a homologous structure. NVR-BIP used the Nuclear Vector Replacement (NVR) framework to model SBA as a binary integer programming problem. In this paper, we prove that this problem is NP-hard and propose a tabu search (TS) algorithm (NVR-TS) equipped with a guided perturbation mechanism to efficiently solve it. NVR-TS uses a quadratic penalty relaxation of NVR-BIP where the violations in the Nuclear Overhauser Effect constraints are penalized in the objective function. Experimental results indicate that our algorithm finds the optimal solution on NVRBIP’s data set which consists of seven proteins with 25 templates (31 to 126 residues). Furthermore, it achieves relatively high assignment accuracies on two additional large proteins, MBP and EIN (348 and 243 residues, respectively), which NVR-BIP failed to solve. The executable and the input files are available for download at http://people.sabanciuniv.edu/catay/NVR-TS/NVR-TS.html. PMID:23221084
On Maximizing the Lifetime of Wireless Sensor Networks by Optimally Assigning Energy Supplies
Directory of Open Access Journals (Sweden)
Francisco Javier González-Castano
2013-08-01
Full Text Available The extension of the network lifetime of Wireless Sensor Networks (WSN is an important issue that has not been appropriately solved yet. This paper addresses this concern and proposes some techniques to plan an arbitrary WSN. To this end, we suggest a hierarchical network architecture, similar to realistic scenarios, where nodes with renewable energy sources (denoted as primary nodes carry out most message delivery tasks, and nodes equipped with conventional chemical batteries (denoted as secondary nodes are those with less communication demands. The key design issue of this network architecture is the development of a new optimization framework to calculate the optimal assignment of renewable energy supplies (primary node assignment to maximize network lifetime, obtaining the minimum number of energy supplies and their node assignment. We also conduct a second optimization step to additionally minimize the number of packet hops between the source and the sink. In this work, we present an algorithm that approaches the results of the optimization framework, but with much faster execution speed, which is a good alternative for large-scale WSN networks. Finally, the network model, the optimization process and the designed algorithm are further evaluated and validated by means of computer simulation under realistic conditions. The results obtained are discussed comparatively.
Comparative Study of Static Task Scheduling Algorithms for Heterogeneous Systems
Directory of Open Access Journals (Sweden)
Miss. Kalpana A. Manudhane
2013-03-01
Full Text Available On the distributed or parallel heterogeneous computing systems, an application is usually decomposed into several interdependent sets of co-operating subtasks and assigned to a set of available processors for execution. Task scheduling is in general NP-compete problem. Static task scheduling algorithms are categorized as Heuristic based and Guided random search based scheduling algorithms. Heuristic algorithms guaranteed to find near optimal solution in less than polynomial time. Heuristic based list scheduling algorithms are Heterogeneous Earliest Finish Time (HEFT and Critical-Path-On- -Processor (CPOP. Whereas, Guided random search based scheduling algorithms have shown robust performance on verity of schedulingproblems. Typical examples are Multiple Priority Queueing Genetic Algorithm (MPQGA, Tabu Search(TS, Ant Colony System (ACS. This paper gives comparative study of all these static task scheduling algorithms and compares them on the basis of average makespan, schedule length ratio (SLR and speedup and running time of algorithm.
Regulatory focus and the assignment of punishment
Directory of Open Access Journals (Sweden)
Chloe Carmichael
2007-06-01
Full Text Available Regulatory Focus has been demonstrated to influence human behavior in a number of domains, such as object valuation and readiness to commit time or money to social projects. It has also been demonstrated to influence an individual’s approach to mistakes; and a person’s preference for global or local processing of information. The present work seeks to consider how regulatory focus might interact with punitive behaviors, specifically, the assignment of legal punishment. In this study, 240 undergraduates completed a series of written instruments that assessed their regulatory focus. They read a vignette that described a target that commits a crime, is detected by the police, and is arrested due to a careless mistake. Participants were asked what level of legal punishment they deemed appropriate. Participants’ punitive evaluations show that there are significant interactions a between the regulatory focus of the participant and the regulatory focus of the target and b between the regulatory focus of the participant and the level of detail used to describe the target and her behavior. In each case, when the regulatory foci matched, causing ‘fit,’ the participant was more lenient than in the non-fit condition.
Self-tuning algorithms for the assignment of packet control units and handover parameters in GERAN
Toril Genovés, Matías
2007-01-01
Esta tesis aborda el problema de la optimización automática de parámetros en redes de acceso radio basadas en GSM-EDGE Radio Access Network (GERAN). Dada la extensión del conjunto de parámetros que se puede optimizar, este trabajo se centra en dos de los procesos encargados de la gestión de la movilidad: el proceso de (re)selección de celda para servicios por conmutación de paquetes y el proceso de traspaso para servicios de voz por conmutación de circuitos.
A Near-Optimal Optimization Algorithm for Link Assignment in Wireless Ad-Hoc Networks
Institute of Scientific and Technical Information of China (English)
Heng-Chang Liu; Bao-Hua Zhao
2006-01-01
Over the past few years, wireless networking technologies have made vast forays in our daily lives. In wireless ad-hoc networks, links are set up by a number of units without any permanent infrastructures. In this paper, the resource optimization is considered to maximize the network throughput by efficiently using the network capacity, where multi-hop functionality and spatial TDMA (STDMA) access scheme are used. The objective is to find the minimum frame length with given traffic distributions and corresponding routing information. Because of the complex structure of the underlying mathematical problem, previous work and analysis become intractable for networks of realistic sizes. The problem is addressed through mathematical programming approach, the linear integer formulation is developed for optimizing the network throughput, and then the similarity between the original problem and the graph edge coloring problem is shown through the conflict graph concept. A column generation solution is proposed and several enhancements are made in order to fasten its convergence. Numerical results demonstrate that the theoretical limit of the throughput can be efficiently computed for networks of realistic sizes.
Staff assignment using network flow techniques
Varone, Sacha; Schindl, David
2009-01-01
La détermination des horaires du personnel est une tâche à faire dans toute organisation de plusieurs employés. Dans cette recherche, nous revisitons sa modélisation comme un problème de coût minimum à débit maximal dans un réseau. Cette modélisation possède l'avantage de permettre une résolution par un algorithme s'exécutant en temps polynomial. Outre les contraintes de disponibilité et de compétences, nous considérons comme un ensemble de contraintes supplémentaires : la charge contractuell...
Improved MOEA/D for Dynamic Weapon-Target Assignment Problem
Institute of Scientific and Technical Information of China (English)
Ying Zhang∗; Rennong Yang; Jialiang Zuo; Xiaoning Jing
2015-01-01
Conducting reasonable weapon⁃target assignment ( WTA) with near real time can bring the maximum awards with minimum costs which are especially significant in the modern war. A framework of dynamic WTA ( DWTA) model based on a series of staged static WTA ( SWTA) models is established where dynamic factors including time window of target and time window of weapon are considered in the staged SWTA model. Then, a hybrid algorithm for the staged SWTA named Decomposition⁃Based Dynamic Weapon⁃target Assignment ( D⁃DWTA) is proposed which is based on the framework of multi⁃objective evolutionary algorithm based on decomposition ( MOEA/D) with two major improvements:one is the coding based on constraint of resource to generate the feasible solutions, and the other is the tabu search strategy to speed up the convergence. Comparative experiments prove that the proposed algorithm is capable of obtaining a well⁃converged and well diversified set of solutions on a problem instance and meets the time demand in the battlefield environment.
Multiobjective Order Assignment Optimization in a Global Multiple-Factory Environment
Directory of Open Access Journals (Sweden)
Rong-Chang Chen
2014-01-01
Full Text Available In response to radically increasing competition, many manufacturers who produce time-sensitive products have expanded their production plants to worldwide sites. Given this environment, how to aggregate customer orders from around the globe and assign them quickly to the most appropriate plants is currently a crucial issue. This study proposes an effective method to solve the order assignment problem of companies with multiple plants distributed worldwide. A multiobjective genetic algorithm (MOGA is used to find solutions. To validate the effectiveness of the proposed approach, this study employs some real data, provided by a famous garment company in Taiwan, as a base to perform some experiments. In addition, the influences of orders with a wide range of quantities demanded are discussed. The results show that feasible solutions can be obtained effectively and efficiently. Moreover, if managers aim at lower total costs, they can divide a big customer order into more small manufacturing ones.
GPU-based SoftAssign for Maximizing Image Utilization in Photomosaics
Directory of Open Access Journals (Sweden)
Toru Tamaki
2011-07-01
Full Text Available Photomosaic generation is a popular non-photorealistic rendering technique, where a single image is assembled from several smaller ones. Visual responses change depending on the proximity to the photomosaic, leading to many creative prospects for publicity and art. Synthesizing photomosaics typically requires very large image databases in order to produce pleasing results. Moreover, repetitions are allowed to occur which may locally bias the mosaic. This paper provides alternatives to prevent repetitions while still being robust enough to work with coarse image subsets. Three approaches were considered for the matching stage of photomosaics: a greedy-based procedural algorithm, simulated annealing and SoftAssign. It was found that the latter delivers adequate arrangements in cases where only a restricted number of images is available. This paper introduces a novel GPU-accelerated SoftAssign implementation that outperforms an optimized CPU implementation by a factor of 60 times in the tested hardware.
Clonify: unseeded antibody lineage assignment from next-generation sequencing data.
Briney, Bryan; Le, Khoa; Zhu, Jiang; Burton, Dennis R
2016-01-01
Defining the dynamics and maturation processes of antibody clonal lineages is crucial to understanding the humoral response to infection and immunization. Although individual antibody lineages have been previously analyzed in isolation, these studies provide only a narrow view of the total antibody response. Comprehensive study of antibody lineages has been limited by the lack of an accurate clonal lineage assignment algorithm capable of operating on next-generation sequencing datasets. To address this shortcoming, we developed Clonify, which is able to perform unseeded lineage assignment on very large sets of antibody sequences. Application of Clonify to IgG+ memory repertoires from healthy individuals revealed a surprising lack of influence of large extended lineages on the overall repertoire composition, indicating that this composition is driven less by the order and frequency of pathogen encounters than previously thought. Clonify is freely available at www.github.com/briney/clonify-python. PMID:27102563
Stochastic User Equilibrium Traffic Assignment with Turn-delays in Intersections
DEFF Research Database (Denmark)
Nielsen, Otto Anker; Simonsen, Nikolaj; Frederiksen, Rasmus Dyhr
1997-01-01
Turn-delays in intersections contribute significant to travel times and thus route choices in urban networks. However, turns are difficult to handle in traffic assignment models due to the asymmetric Jacobian in the cost functions. The paper describes a model where turn delays have been included in...... the solution algorithm of Sto-chastic User Equilibrium traffic assignment (SUE). When the Jacobian is symme-tric, SUE minimises the road users' 'perceived travel resistance’s'. This equals a probit-model where the links cost-functions are traffic dependent. Hereby, overlap-ping routes are handled in a...... consistent way. However, no theoretical proof of convergence has been given if the Jacobian is asymmetric, although convergence can be shown probable for model data representing realistic road-networks. However, according to the authors knowledge SUE with intersection delays have not prior been tested on a...
Directory of Open Access Journals (Sweden)
Yu-Chi Wang
2015-01-01
Full Text Available This paper presents a unified approach to nonlinear dynamic inversion control algorithm with the parameters for desired dynamics determined by using an eigenvalue assignment method, which may be applied in a very straightforward and convenient way. By using this method, it is not necessary to transform the nonlinear equations into linear equations by feedback linearization before beginning control designs. The applications of this method are not limited to affine nonlinear control systems or limited to minimum phase problems if the eigenvalues of error dynamics are carefully assigned so that the desired dynamics is stable. The control design by using this method is shown to be robust to modeling uncertainties. To validate the theory, the design of a UAV control system is presented as an example. Numerical simulations show the performance of the design to be quite remarkable.
Energy Technology Data Exchange (ETDEWEB)
Fontana, W.
1990-12-13
In this paper complex adaptive systems are defined by a self- referential loop in which objects encode functions that act back on these objects. A model for this loop is presented. It uses a simple recursive formal language, derived from the lambda-calculus, to provide a semantics that maps character strings into functions that manipulate symbols on strings. The interaction between two functions, or algorithms, is defined naturally within the language through function composition, and results in the production of a new function. An iterated map acting on sets of functions and a corresponding graph representation are defined. Their properties are useful to discuss the behavior of a fixed size ensemble of randomly interacting functions. This function gas'', or Turning gas'', is studied under various conditions, and evolves cooperative interaction patterns of considerable intricacy. These patterns adapt under the influence of perturbations consisting in the addition of new random functions to the system. Different organizations emerge depending on the availability of self-replicators.
FellWalker - a Clump Identification Algorithm
Berry, David
2014-01-01
This paper describes the FellWalker algorithm, a watershed algorithm that segments a 1-, 2- or 3-dimensional array of data values into a set of disjoint clumps of emission, each containing a single significant peak. Pixels below a nominated constant data level are assumed to be background pixels and are not assigned to any clump. FellWalker is thus equivalent in purpose to the CLUMPFIND algorithm. However, unlike CLUMPFIND, which segments the array on the basis of a set of evenly-spaced contours and thus uses only a small fraction of the available data values, the FellWalker algorithm is based on a gradient-tracing scheme which uses all available data values. Comparisons of CLUMPFIND and FellWalker using a crowded field of artificial Gaussian clumps, all of equal peak value and width, suggest that the results produced by FellWalker are less dependent on specific parameter settings than are those of CLUMPFIND.
Novel multi-objective optimization algorithm
Institute of Scientific and Technical Information of China (English)
Jie Zeng; Wei Nie
2014-01-01
Many multi-objective evolutionary algorithms (MOEAs) can converge to the Pareto optimal front and work wel on two or three objectives, but they deteriorate when faced with many-objective problems. Indicator-based MOEAs, which adopt various indicators to evaluate the fitness values (instead of the Pareto-dominance relation to select candidate solutions), have been regarded as promising schemes that yield more satisfactory re-sults than wel-known algorithms, such as non-dominated sort-ing genetic algorithm (NSGA-II) and strength Pareto evolution-ary algorithm (SPEA2). However, they can suffer from having a slow convergence speed. This paper proposes a new indicator-based multi-objective optimization algorithm, namely, the multi-objective shuffled frog leaping algorithm based on the ε indicator (ε-MOSFLA). This algorithm adopts a memetic meta-heuristic, namely, the SFLA, which is characterized by the powerful capa-bility of global search and quick convergence as an evolutionary strategy and a simple and effective ε-indicator as a fitness as-signment scheme to conduct the search procedure. Experimental results, in comparison with other representative indicator-based MOEAs and traditional Pareto-based MOEAs on several standard test problems with up to 50 objectives, show thatε-MOSFLA is the best algorithm for solving many-objective optimization problems in terms of the solution quality as wel as the speed of convergence.
Evolutionary Graph Drawing Algorithms
Institute of Scientific and Technical Information of China (English)
Huang Jing-wei; Wei Wen-fang
2003-01-01
In this paper, graph drawing algorithms based on genetic algorithms are designed for general undirected graphs and directed graphs. As being shown, graph drawing algorithms designed by genetic algorithms have the following advantages: the frames of the algorithms are unified, the method is simple, different algorithms may be attained by designing different objective functions, therefore enhance the reuse of the algorithms. Also, aesthetics or constrains may be added to satisfy different requirements.
Liu, Entao; Temlyakov, Vladimir N.
2010-01-01
We study greedy-type algorithms such that at a greedy step we pick several dictionary elements contrary to a single dictionary element in standard greedy-type algorithms. We call such greedy algorithms {\\it super greedy algorithms}. The idea of picking several elements at a greedy step of the algorithm is not new. Recently, we observed the following new phenomenon. For incoherent dictionaries these new type of algorithms (super greedy algorithms) provide the same (in the sense of order) upper...
Storage assignment optimization in a multi-tier shuttle warehousing system
Wang, Yanyan; Mou, Shandong; Wu, Yaohua
2016-03-01
The current mathematical models for the storage assignment problem are generally established based on the traveling salesman problem(TSP), which has been widely applied in the conventional automated storage and retrieval system(AS/RS). However, the previous mathematical models in conventional AS/RS do not match multi-tier shuttle warehousing systems(MSWS) because the characteristics of parallel retrieval in multiple tiers and progressive vertical movement destroy the foundation of TSP. In this study, a two-stage open queuing network model in which shuttles and a lift are regarded as servers at different stages is proposed to analyze system performance in the terms of shuttle waiting period (SWP) and lift idle period (LIP) during transaction cycle time. A mean arrival time difference matrix for pairwise stock keeping units(SKUs) is presented to determine the mean waiting time and queue length to optimize the storage assignment problem on the basis of SKU correlation. The decomposition method is applied to analyze the interactions among outbound task time, SWP, and LIP. The ant colony clustering algorithm is designed to determine storage partitions using clustering items. In addition, goods are assigned for storage according to the rearranging permutation and the combination of storage partitions in a 2D plane. This combination is derived based on the analysis results of the queuing network model and on three basic principles. The storage assignment method and its entire optimization algorithm method as applied in a MSWS are verified through a practical engineering project conducted in the tobacco industry. The applying results show that the total SWP and LIP can be reduced effectively to improve the utilization rates of all devices and to increase the throughput of the distribution center.
A SAT Based Effective Algorithm for the Directed Hamiltonian Cycle Problem
Jäger, Gerold; Zhang, Weixiong
The Hamiltonian cycle problem (HCP) is an important combinatorial problem with applications in many areas. While thorough theoretical and experimental analyses have been made on the HCP in undirected graphs, little is known for the HCP in directed graphs (DHCP). The contribution of this work is an effective algorithm for the DHCP. Our algorithm explores and exploits the close relationship between the DHCP and the Assignment Problem (AP) and utilizes a technique based on Boolean satisfiability (SAT). By combining effective algorithms for the AP and SAT, our algorithm significantly outperforms previous exact DHCP algorithms including an algorithm based on the award-winning Concorde TSP algorithm.
Why the Rhetoric of CS Programming Assignments Matters
Wolfe, Joanna
2004-06-01
Despite the multiple potential benefits of asking students working on programming tasks to consider human factors, most programming assignments narrowly focus on technical details and requirements. Female students in particular may be attracted to assignments that emphasize human as well as technical factors. To assess how students respond to changes in the rhetorical presentation of programming instructions, 81 students completed questionnaires evaluating different assignment instructions. Students generally perceived assignments emphasizing real-world contexts and users as more motivating and enjoyable to program than those that did not emphasize human factors. Moreover, when asked what makes a "good" programming assignment, over half of the students volunteered that they looked for assignments stressing a real-world purpose, use or application.
A Randomized Algorithm for 3-SAT
Ghosh, Subhas Kumar
2009-01-01
In this work we propose and analyze a simple randomized algorithm to find a satisfiable assignment for a Boolean formula in conjunctive normal form (CNF) having at most 3 literals in every clause. Given a k-CNF formula phi on n variables, and alpha in{0,1}^n that satisfies phi, a clause of phi is critical if exactly one literal of that clause is satisfied under assignment alpha. Paturi et. al. (Chicago Journal of Theoretical Computer Science 1999) proposed a simple randomized algorithm (PPZ) for k-SAT for which success probability increases with the number of critical clauses (with respect to a fixed satisfiable solution of the input formula). Here, we first describe another simple randomized algorithm DEL which performs better if the number of critical clauses are less (with respect to a fixed satisfiable solution of the input formula). Subsequently, we combine these two simple algorithms such that the success probability of the combined algorithm is maximum of the success probabilities of PPZ and DEL on eve...
Bayesian Optimisation Algorithm for Nurse Scheduling
Li, Jingpeng
2008-01-01
Our research has shown that schedules can be built mimicking a human scheduler by using a set of rules that involve domain knowledge. This chapter presents a Bayesian Optimization Algorithm (BOA) for the nurse scheduling problem that chooses such suitable scheduling rules from a set for each nurses assignment. Based on the idea of using probabilistic models, the BOA builds a Bayesian network for the set of promising solutions and samples these networks to generate new candidate solutions. Computational results from 52 real data instances demonstrate the success of this approach. It is also suggested that the learning mechanism in the proposed algorithm may be suitable for other scheduling problems.
Issues Challenges and Tools of Clustering Algorithms
Directory of Open Access Journals (Sweden)
Parul Agarwal
2011-05-01
Full Text Available Clustering is an unsupervised technique of Data Mining. It means grouping similar objects together and separating the dissimilar ones. Each object in the data set is assigned a class label in the clustering process using a distance measure. This paper has captured the problems that are faced in real when clustering algorithms are implemented .It also considers the most extensively used tools which are readily available and support functions which ease the programming. Once algorithms have been implemented, they also need to be tested for its validity. There exist several validation indexes for testing the performance and accuracy which have also been discussed here.
Variability of Cranial Nerve Assignment to Speech and Swallow Muscles
Morrey, Kristina
2011-01-01
The object of this study was to examine and document anatomical variability of cranial nerve assignment for muscles of the speech and swallow mechanism. Through means of textbook review, the study’s first purpose was to identify which cranial nerves were attributed to the innervation for muscles associated with the speech and swallow mechanism. The second purpose was to examine if cranial nerve assignment, field of study, or geographic region explained differences in cranial nerve assignment ...
Integrated Project Scheduling and Staff Assignment with Controllable Processing Times
Victor Fernandez-Viagas; Framinan, Jose M.
2014-01-01
This paper addresses a decision problem related to simultaneously scheduling the tasks in a project and assigning the staff to these tasks, taking into account that a task can be performed only by employees with certain skills, and that the length of each task depends on the number of employees assigned. This type of problems usually appears in service companies, where both tasks scheduling and staff assignment are closely related. An integer programming model for the problem is proposed, tog...
CYCLE TIMES ASSIGNMENT OF NONLINEAR DISCRETE EVENT DYNAMIC SYSTEMS
Institute of Scientific and Technical Information of China (English)
CHEN Wende
2000-01-01
In this paper, nonautonomous models of Discrete Event Dynamic Systems (DEDS) are established by min-max function, reachability and observability are defined,the problem on cycle times assignment of DEDS, which corresponds with the important problem on poles assignment of linear systems, is studied. By Gunawardena et al.'Duality Theorem following results are obtained: Cycle times of system can be assigned under state feedback(or output feedback) if and only if system is reachable (or reachable and obserbable).
Electronic marking of mathematics assignments using Microsoft Word 2007
Lowe, Tim; Mestel, Ben; Arrowsmith, Gaynor
2008-01-01
This paper describes on-going work within the Department of Mathematics and Statistics at The Open University to enable distance learning students to electronically submit assignments rich in mathematical notation and diagrams, and for those assignments to be marked and returned electronically by their tutor. A trial is currently underway of a prototype system that enables students to submit assignments in a range of electronic formats, which are then converted to Microsoft Word 2007 format t...
Assigning Wikipedia editing: Triangulation toward understanding university student engagement
Roth, Amy; Davis, Rochelle; Carver, Brian
2013-01-01
Professors across the United States participated in the first direct effort by the Wikimedia Foundation, the non-profit that supports Wikipedia, to engage the academic community and integrate Wikipedia into a class assignment. Three project participants, from different areas of study, conducted independent research into university student motivations for a Wikipedia assignment. We triangulate those data in this paper to describe how student motivations differ for a Wikipedia assignment from a...
28 CFR 524.72 - CIM assignment categories.
2010-07-01
... publicity. Inmates who have received widespread publicity as a result of their criminal activity or... require special management attention, but who do not ordinarily warrant assignment in paragraphs...
Linear Assignment Maps for Correlated System-Environment States
Rodríguez-Rosario, César A; Aspuru-Guzik, Alán
2009-01-01
An assignment map is a mathematical operator that describes initial system-environment states for an open quantum systems. We reexamine the notion of assignments, introduced by Pechukas, and show the conditions for which linear assignments can account for correlations between the system and the environment. We study the role of other conditions, such as consistency and positivity of the map, and show the effects of relaxing these. Finally, we establish a connection between the violation of positivity of linear assignments and the no-broadcasting theorem.
7 CFR 1210.540 - OMB assigned numbers.
2010-01-01
... AGREEMENTS AND ORDERS; MISCELLANEOUS COMMODITIES), DEPARTMENT OF AGRICULTURE WATERMELON RESEARCH AND... Number 0581-0093, except that Board member nominee background information sheets are assigned OMB...
Performance of Power Control Algorithm for DSCDMA on Reverse Link
Directory of Open Access Journals (Sweden)
Chandra Prakash
2013-09-01
Full Text Available In this paper, the performance of smart step closed loop power control (SSPC algorithm and base station assignment method based on minimizing the transmitter power (BSA-MTP technique for direct sequence-code division multiple access (DS-CDMA receiver in a 2D urban environment has been compared. The simulation results indicate that the SSPC algorithm and the BSA-MTP technique can improve the network bit error rate in comparison with other conventional methods. Further, the convergence speed of the SSPC algorithm is faster than that of conventional algorithms
O(1) Delta Component Computation Technique for the Quadratic Assignment Problem
Podolsky, Sergey
2012-01-01
The paper describes a novel technique that allows to reduce by half the number of delta values that were required to be computed with complexity O(N) in most of the heuristics for the quadratic assignment problem. Using the correlation between the old and new delta values, obtained in this work, a new formula of complexity O(1) is proposed. Found result leads up to 25% performance increase in such well-known algorithms as Robust Tabu Search and others based on it.
Probabilistic Cross-Identification in Crowded Fields as an Assignment Problem
Budavari, Tamas
2016-01-01
One of the outstanding challenges of cross-identification is multiplicity: detections in crowded regions of the sky are often linked to more than one candidate associations of similar likelihoods. We map the resulting maximum likelihood partitioning to the fundamental assignment problem of discrete mathematics and efficiently solve the two-way catalog-level matching in the realm of combinatorial optimization using the so-called Hungarian algorithm. We introduce the method, demonstrate its performance in a mock universe where the true associations are known, and discuss the applicability of the new procedure to large surveys.
Petri Net Decomposition Method for Simultaneous Optimization of Task Assignment and Routing for AGVs
Tanaka, Yuki; Nishi, Tatsushi; Inuiguchi, Masahiro
We propose a simultaneous optimization method for task assignment and routing problems with multiple AGVs by the decomposition of Petri Nets. In the proposed method, Petri Net is decomposed into several subnets representing task subproblems and AGV subproblems. Each subproblem is solved by Dijkstra's algorithm. The subproblem on each subnet is repeatedly solved until a feasible solution for the original problem is derived. A solution method for subproblems with no final marking is newly developed. The effectiveness of the proposed method is demonstrated by comparing the performance with CPLEX as well as a nearest neighborhood heuristic method.
New optimal algorithm of data association for multi-passive-sensor location system
Institute of Scientific and Technical Information of China (English)
ZHOU Li; HE You; ZHANG WeiHua
2007-01-01
In dense target and false detection scenario of four time difference of arrival (TDOA)for multi-passive-sensor location system, the global optimal data association algorithm has to be adopted. In view of the heavy calculation burden of the traditional optimal assignment algorithm, this paper proposes a new global optimal assignment algorithm and a 2-stage association algorithm based on a statistic test.Compared with the traditional optimal algorithm, the new optimal algorithm avoids the complicated operations for finding the target position before we calculate association cost; hence, much of the procedure time is saved. In the 2-stage association algorithm, a large number of false location points are eliminated from candidate associations in advance. Therefore, the operation is further decreased, and the correct data association probability is improved in varying degrees. Both the complexity analyses and simulation results can verify the effectiveness of the new algorithms.
Institute of Scientific and Technical Information of China (English)
吕丹; 郑世跃; 欧阳勋志; 郭孝玉
2014-01-01
批量评估具有效率高、费用低且满足大量评估等优点。论文以中龄林为例，将BP神经网络应用于林木资源资产批量评估。通过比较学习算法、隐含层节点数，运用敏感性分析法确定影响因子对评估值的贡献程度，筛选输入层因子，从而优化了林木资源资产批量评估BP神经网络模型结构。结果表明：贝叶斯正则化法优于L-M算法；年龄、利率、蓄积、树种为强影响因子，这4个因子对评估值的贡献度超过60％；最优模型结构为BR 9-10-1，该模型平均绝对误差为32．46元/hm2，平均相对误差为1．28％，决定系数达0．9997，模型拟合精度高，泛化能力强，能够满足中龄林林木资源资产批量评估的要求。%Mass appraisal is of high efficiency,high precision,low cost,satisfies the needs of vast-amount evaluation.In this study,BP neural network was applied to mass appraisal of mid-age forest assets evaluation. By comparing different learning algorithms and the numbers of hidden layer nodes,selecting layer factors,using sensitivity analysis method which revealed the factors’ influence degree to the assessed value,the model struc-ture of BP neural network was optimized.The results showed that Bayesian regularization method was better than L-M algorithm;the contribution to the assessed values of the four factors including age,rate,accumula-tion,tree species was more than 60%;the best model structure was BR9-10-1.Its mean absolute error was 32.46 yuan/hm2 ,mean absolute percentage error was 1.28%,and decision coefficient was 0.999 7.The model has high fitting accuracy and generalization ability thus meets the requirement of mass appraisal of mid-age forest resource assets.
Stang, Jared B; Perez, Sarah; Ives, Joss; Roll, Ido
2016-01-01
Pre-class reading assignments help prepare students for active classes by providing a first exposure to the terms and concepts to be used during class. We investigate if the use of inquiry-oriented PhET-based activities in conjunction with pre-class reading assignments can improve both the preparation of students for in-class learning and student attitudes towards and engagement with pre-class assignments. Over three course modules covering different topics, students were assigned randomly to complete either a textbook-only pre-class assignment or both a textbook pre-class assignment and a PhET-based activity. The assignments helped prepare students for class, as measured by performance on the pre-class quiz relative to a beginning-of-semester pre-test, but no evidence for increased learning due the PhET activity was observed. Students rated the assignments which included PhET as more enjoyable and, for the topic latest in the semester, reported engaging more with the assignments when PhET was included.
DEFF Research Database (Denmark)
This book constitutes the refereed proceedings of the 10th Scandinavian Workshop on Algorithm Theory, SWAT 2006, held in Riga, Latvia, in July 2006. The 36 revised full papers presented together with 3 invited papers were carefully reviewed and selected from 154 submissions. The papers address all...... issues of theoretical algorithmics and applications in various fields including graph algorithms, computational geometry, scheduling, approximation algorithms, network algorithms, data storage and manipulation, combinatorics, sorting, searching, online algorithms, optimization, etc....
Online Assignments in Economics: A Test of Their Effectiveness
Kennelly, Brendan; Considine, John; Flannery, Darragh
2011-01-01
This article compares the effectiveness of online and paper-based assignments and tutorials using summative assessment results. All of the students in a large managerial economics course at National University of Ireland, Galway were asked to do six assignments online using Aplia and to do two on paper. The authors examined whether a student's…
The Pedagogy of Assignments in Social Justice Teacher Education
McDonald, Morva A.
2008-01-01
This article examines the pedagogy of assignments in social justice teacher education programs. Employing a programmatic view, this study aims to understand the collective representation of social justice provided by assignments across multiple courses. Findings come from a qualitative case study of two social justice programs. Drawing on concepts…
Assessing Faculty Bias in Rating Embedded Assurance of Learning Assignments
Kim, Dong-gook; Helms, Marilyn M.
2016-01-01
Assurance of learning (AoL) processes for continuous improvement and accreditation require business schools to assess program goals. Findings from the process can lead to changes in course design or curriculum. Often AoL assignments are embedded into existing courses and assessed at regular intervals. Faculty members may evaluate an assignment in…
Negotiating Languages and Cultures: Enacting Translingualism through a Translation Assignment
Kiernan, Julia; Meier, Joyce; Wang, Xiqiao
2016-01-01
This collaborative project explores the affordances of a translation assignment in the context of a learner-centered pedagogy that places composition students' movement among languages and cultures as both a site for inquiry and subject of analysis. The translation assignment asks students to translate scholarly articles or culture stories from…
14 CFR 1245.109 - Assignment of title to NASA.
2010-01-01
... 14 Aeronautics and Space 5 2010-01-01 2010-01-01 false Assignment of title to NASA. 1245.109... INTELLECTUAL PROPERTY RIGHTS Patent Waiver Regulations § 1245.109 Assignment of title to NASA. (a) The instrument of waiver set forth in § 1245.115(c) shall be voided by NASA with respect to the domestic title...
24 CFR 203.350 - Assignment of mortgage.
2010-04-01
... 24 Housing and Urban Development 2 2010-04-01 2010-04-01 false Assignment of mortgage. 203.350... URBAN DEVELOPMENT MORTGAGE AND LOAN INSURANCE PROGRAMS UNDER NATIONAL HOUSING ACT AND OTHER AUTHORITIES SINGLE FAMILY MORTGAGE INSURANCE Contract Rights and Obligations Assignment of Mortgage §...
On the Use of Writing Assignments in Intermediate Microeconomic Theory
O'Neill, Patrick B.
2009-01-01
A typical writing assignment in upper level required courses is a term paper. However many economics majors, particularly those in business schools, need to develop skill at writing shorter pieces. In this paper I describe numerous examples of shorter writing assignments that I have incorporated into an Intermediate Microeconomic Theory course.…
7 CFR 1530.115 - Paperwork Reduction Act assigned number.
2010-01-01
... 7 Agriculture 10 2010-01-01 2010-01-01 false Paperwork Reduction Act assigned number. 1530.115... SERVICE, DEPARTMENT OF AGRICULTURE THE REFINED SUGAR RE-EXPORT PROGRAM, THE SUGAR CONTAINING PRODUCTS RE-EXPORT PROGRAM, AND THE POLYHYDRIC ALCOHOL PROGRAM § 1530.115 Paperwork Reduction Act assigned...
The Eco-Sculpture Assignment: Using Art to Scaffold Metacognition
Polegato, Rosemary
2014-01-01
The Eco-Sculpture Assignment demonstrates that art may be used as a conduit to scaffold metacognition in marketing courses. Theoretical underpinnings are drawn from the literature on pedagogy used in general, marketing, and art education contexts. The assignment is described in detail, followed by examples of learner response that illustrate…
Graduate Writing Assignments across Faculties in a Canadian University
Shi, Ling; Dong, Yanning
2015-01-01
This study examines 143 graduate assignments across 12 faculties or schools in a Canadian university in order to identify types of writing tasks. Based on the descriptions provided by the instructors, we identified nine types of assignments, with scholarly essay being the most common, followed by summary and response, literature review, project,…
42 CFR 60.38 - Assignment of a HEAL loan.
2010-10-01
... assigned except to another HEAL lender, the Student Loan Marketing Association (popularly known as “Sallie Mae”), or a public entity in the business of purchasing student loans, and except as provided in § 60... responsibility under the HEAL regulations. (d) Bankruptcy. If a lender or holder assigns a HEAL loan to a...
47 CFR 52.111 - Toll free number assignment.
2010-10-01
... 47 Telecommunication 3 2010-10-01 2010-10-01 false Toll free number assignment. 52.111 Section 52...) NUMBERING Toll Free Numbers § 52.111 Toll free number assignment. Toll free numbers shall be made available on a first-come, first-served basis unless otherwise directed by the Commission....
76 FR 34658 - The Internet Assigned Numbers Authority (IANA) Functions
2011-06-14
... of Inquiry, Request for Comments on the Internet Assigned Numbers Authority (IANA) Functions, 76 FR 10569 (Feb. 25, 2011), available at http://www.ntia.doc.gov/frnotices/2011/fr_ianafunctionsnoi_02252011... National Telecommunications and Information Administration The Internet Assigned Numbers Authority...
Evaluation of a UMLS Auditing Process of Semantic Type Assignments
Gu, Huanying; Hripcsak, George; Chen, Yan; Morrey, C. Paul; Elhanan, Gai; Cimino, James J.; Geller, James; Perl, Yehoshua
2007-01-01
The UMLS is a terminological system that integrates many source terminologies. Each concept in the UMLS is assigned one or more semantic types from the Semantic Network, an upper level ontology for biomedicine. Due to the complexity of the UMLS, errors exist in the semantic type assignments. Finding assignment errors may unearth modeling errors. Even with sophisticated tools, discovering assignment errors requires manual review. In this paper we describe the evaluation of an auditing project of UMLS semantic type assignments. We studied the performance of the auditors who reviewed potential errors. We found that four auditors, interacting according to a multi-step protocol, identified a high rate of errors (one or more errors in 81% of concepts studied) and that results were sufficiently reliable (0.67 to 0.70) for the two most common types of errors. However, reliability was low for each individual auditor, suggesting that review of potential errors is resource-intensive. PMID:18693845
Evaluation of a UMLS Auditing Process of Semantic Type Assignments.
Gu, Huanying Helen; Hripcsak, George; Chen, Yan; Morrey, C Paul; Elhanan, Gai; Cimino, James; Geller, James; Perl, Yehoshua
2007-01-01
The UMLS is a terminological system that integrates many source terminologies. Each concept in the UMLS is assigned one or more semantic types from the Semantic Network, an upper level ontology for biomedicine. Due to the complexity of the UMLS, errors exist in the semantic type assignments. Finding assignment errors may unearth modeling errors. Even with sophisticated tools, discovering assignment errors requires manual review. In this paper we describe the evaluation of an auditing project of UMLS semantic type assignments. We studied the performance of the auditors who reviewed potential errors. We found that four auditors, interacting according to a multi-step protocol, identified a high rate of errors (one or more errors in 81% of concepts studied) and that results were sufficiently reliable (0.67 to 0.70) for the two most common types of errors. However, reliability was low for each individual auditor, suggesting that review of potential errors is resource-intensive. PMID:18693845
Directory of Open Access Journals (Sweden)
Md Shamsul Arefin
2012-12-01
Full Text Available This work presents a technique for the chirality (n, m assignment of semiconducting single wall carbon nanotubes by solving a set of empirical equations of the tight binding model parameters. The empirical equations of the nearest neighbor hopping parameters, relating the term (2n, m with the first and second optical transition energies of the semiconducting single wall carbon nanotubes, are also proposed. They provide almost the same level of accuracy for lower and higher diameter nanotubes. An algorithm is presented to determine the chiral index (n, m of any unknown semiconducting tube by solving these empirical equations using values of radial breathing mode frequency and the first or second optical transition energy from resonant Raman spectroscopy. In this paper, the chirality of 55 semiconducting nanotubes is assigned using the first and second optical transition energies. Unlike the existing methods of chirality assignment, this technique does not require graphical comparison or pattern recognition between existing experimental and theoretical Kataura plot.
A New Parallel Partition Prime Multiple Algorithm for Data Mining
Directory of Open Access Journals (Sweden)
Partha Pratim Bhattacharya
2012-12-01
Full Text Available One of the important problems in data mining is discovering association rules from databases. Each transaction contains a set of items. Discovering the frequent itemsets require a lot of computation power, memory and input/output values, which can only be provided by parallel computer. In this paper, we proposed a new Parallel Partition Prime Multiple Algorithm for association rule mining. Proposed algorithm addresses the shortcoming of previously proposed Parallel Buddy Prima Algorithm. The proposed algorithm divides transaction database equally according to their assignment of variable for each processor. The decision of assignment of next transaction to the processor depends on the value of count variable of itemset per transaction. It reduces the time and data complexity.
A two-phase genetic algorithm for the berth and quay crane allocation and scheduling problem
A. PONOMAREV; Dullaert, W.; B. RAA
2010-01-01
This paper presents a hybrid genetic algorithm for a dynamic continuous berth allocation and quay crane scheduling problem. In the first phase of the algorithm, vessels are positioned at berthing locations and quay cranes are assigned to vessels using novel crane assignment heuristics. In the second phase, cranes are scheduled to minimize the distance travelled in repositioning the cranes. The solution approach is tested on benchmarks derived from real-life data, with varying levels of capaci...
C. Kirabo Jackson
2011-01-01
Existing studies on single-sex schooling suffer from biases because students who attend single-sex schools differ in unmeasured ways from those who do not. In Trinidad and Tobago students are assigned to secondary schools based on an algorithm allowing one to address self-selection bias and estimate the causal effect of attending a single-sex school versus a similar coeducational school. While students (particularly females) with strong expressed preferences for single-sex schools benefit, mo...
Memetic Elitist Pareto Evolutionary Algorithm for Virtual Network Embedding
Shahin, Ashraf A.
2015-01-01
Assigning virtual network resources to physical network components, called Virtual Network Embedding, is a major challenge in cloud computing platforms. In this paper, we propose a memetic elitist pareto evolutionary algorithm for virtual network embedding problem, which is called MEPE-VNE. MEPE-VNE applies a non-dominated sorting-based multi-objective evolutionary algorithm, called NSGA-II, to reduce computational complexity of constructing a hierarchy of non-dominated Pareto fronts and assi...
Comparative Analysis of Serial Decision Tree Classification Algorithms
Matthew Nwokejizie Anyanwu; Sajjan Shiva
2009-01-01
Classification of data objects based on a predefined knowledge of the objects is a data mining and knowledge management technique used in grouping similar data objects together. It can be defined as supervised learning algorithms as it assigns class labels to data objects based on the relationship between the data items with a pre-defined class label. Classification algorithms have a wide range of applications like churn prediction, fraud detection, artificial intelligence, and credit card ra...
Scheduling with genetic algorithms
Fennel, Theron R.; Underbrink, A. J., Jr.; Williams, George P. W., Jr.
1994-01-01
In many domains, scheduling a sequence of jobs is an important function contributing to the overall efficiency of the operation. At Boeing, we develop schedules for many different domains, including assembly of military and commercial aircraft, weapons systems, and space vehicles. Boeing is under contract to develop scheduling systems for the Space Station Payload Planning System (PPS) and Payload Operations and Integration Center (POIC). These applications require that we respect certain sequencing restrictions among the jobs to be scheduled while at the same time assigning resources to the jobs. We call this general problem scheduling and resource allocation. Genetic algorithms (GA's) offer a search method that uses a population of solutions and benefits from intrinsic parallelism to search the problem space rapidly, producing near-optimal solutions. Good intermediate solutions are probabalistically recombined to produce better offspring (based upon some application specific measure of solution fitness, e.g., minimum flowtime, or schedule completeness). Also, at any point in the search, any intermediate solution can be accepted as a final solution; allowing the search to proceed longer usually produces a better solution while terminating the search at virtually any time may yield an acceptable solution. Many processes are constrained by restrictions of sequence among the individual jobs. For a specific job, other jobs must be completed beforehand. While there are obviously many other constraints on processes, it is these on which we focussed for this research: how to allocate crews to jobs while satisfying job precedence requirements and personnel, and tooling and fixture (or, more generally, resource) requirements.
Severson, Tracie Andrusiak
The long-term goal of this research is to contribute to the design of a conceptual architecture and framework for the distributed coordination of multifunction radar systems. The specific research objective of this dissertation is to apply results from graph theory, probabilistic optimization, and consensus control to the problem of distributed optimization of resource allocation for multifunction radars coordinating on their search and track assignments. For multiple radars communicating on a radar network, cooperation and agreement on a network resource management strategy increases the group's collective search and track capability as compared to non-cooperative radars. Existing resource management approaches for a single multifunction radar optimize the radar's configuration by modifying the radar waveform and beam-pattern. Also, multi-radar approaches implement a top-down, centralized sensor management framework that relies on fused sensor data, which may be impractical due to bandwidth constraints. This dissertation presents a distributed radar resource optimization approach for a network of multifunction radars. Linear and nonlinear models estimate the resource allocation for multifunction radar search and track functions. Interactions between radars occur over time-invariant balanced graphs that may be directed or undirected. The collective search area and target-assignment solution for coordinated radars is optimized by balancing resource usage across the radar network and minimizing total resource usage. Agreement on the global optimal target-assignment solution is ensured using a distributed binary consensus algorithm. Monte Carlo simulations validate the coordinated approach over uncoordinated alternatives.
NMR Analysis of RNA Bulged Structures: Tabu Search Application in NOE Signal Assignment
International Nuclear Information System (INIS)
Bulges are the most frequently occurring RNA secondary structural elements of high functional importance. At present, they are known to participate in the process of RNA folding, RNA-RNA and RNA-protein interactions. It has been shown that bulges can induce destabilization in RNA duplexes and the extent of the destabilization depends on many factors such as the size of the bulge, the nature of the bulge bases, and the flanking residues. However, relatively very little is known about these structural elements. Only several studies have been performed to address the preferred conformations of bulged residues in DNA and RNA duplexes. The knowledge of spatial structure of RNA bulges in solution requires application of NMR spectroscopy. A considerable part of NMR analytical process of RNA fragment is based on automatic methods. However, manual assistance is still essential in resonance assignment. Thus, there has been a great need to introduce automatic procedures also at this level. We propose a tabu search algorithm being a tool for an automatic resonance assignment. The assignment is determined by NOE pathways, which can be constructed in aromatic/anomeric region of 2D NOESY spectrum generated during NMR experiment. Computational tests demonstrate performance of the tabu search applied to the experimental spectra of RNA bulged duplexes. (author)
Converting online algorithms to local computation algorithms
Mansour, Yishay; Vardi, Shai; Xie, Ning
2012-01-01
We propose a general method for converting online algorithms to local computation algorithms by selecting a random permutation of the input, and simulating running the online algorithm. We bound the number of steps of the algorithm using a query tree, which models the dependencies between queries. We improve previous analyses of query trees on graphs of bounded degree, and extend the analysis to the cases where the degrees are distributed binomially, and to a special case of bipartite graphs. Using this method, we give a local computation algorithm for maximal matching in graphs of bounded degree, which runs in time and space O(log^3 n). We also show how to convert a large family of load balancing algorithms (related to balls and bins problems) to local computation algorithms. This gives several local load balancing algorithms which achieve the same approximation ratios as the online algorithms, but run in O(log n) time and space. Finally, we modify existing local computation algorithms for hypergraph 2-color...
Heuristic for Task-Worker Assignment with Varying Learning Slopes
Directory of Open Access Journals (Sweden)
Wipawee Tharmmaphornphilas
2010-04-01
Full Text Available Fashion industry has variety products, so the multi-skilled workers are required to improve flexibility in production and assignment. Generally the supervisor will assign task to the workers based on skill and skill levels of worker. Since in fashion industry new product styles are launched more frequently and the order size tends to be smaller, the workers always learn when the raw material and the production process changes. Consequently they require less time to produce the succeeding units of a task based on their learning ability. Since the workers have both experience and inexperience workers, so each worker has different skill level and learning ability. Consequently, the assignment which assumed constant skill level is not proper to use. This paper proposes a task-worker assignment considering worker skill levels and learning abilities. Processing time of each worker changes along production period due to a worker learning ability. We focus on a task-worker assignment in a fashion industry where tasks are ordered in series; the number of tasks is greater than the number of workers. Therefore, workers can perform multiple assignments followed the precedence restriction as an assembly line balancing problem. The problem is formulated in an integer linear programming model with objective to minimize makespan. A heuristic is proposed to determine the lower bound (LB and the upper bound (UB of the problem and the best assignment is determined. The performance of the heuristic method is tested by comparing quality of solution and computational time to optimal solutions.
Data requirements for reliable chemical shift assignments in deuterated proteins
International Nuclear Information System (INIS)
The information required for chemical shift assignments in large deuterated proteins was investigated using a Monte Carlo approach (Hitchens et al., 2002). In particular, the consequences of missing amide resonances on the reliability of assignments derived from Cα and CO or from Cα and Cβ chemical shifts was investigated. Missing amide resonances reduce both the number of correct assignments as well as the confidence in these assignments. More significantly, a number of undetectable errors can arise when as few as 9% of the amide resonances are missing from the spectra. However, the use of information from residue specific labeling as well as local and long-range distance constraints improves the reliability and extent of assignment. It is also shown that missing residues have only a minor effect on the assignment of protein-ligand complexes using Cα and CO chemical shifts and Cα inter-residue connectivity, provided that the known chemical shifts of the unliganded protein are utilized in the assignment process
New multi layer data correlation algorithm for multi passive sensor location system
Institute of Scientific and Technical Information of China (English)
Zhou Li; Li Lingyun; He You
2007-01-01
Under the scenario of dense targets in clutter, a multi-layer optimal data correlation algorithm is proposed. This algorithm eliminates a large number of false location points from the assignment process by rough correlations before we calculate the correlation cost, so it avoids the operations for the target state estimate and the calculation of the correlation cost for the false correlation sets. In the meantime, with the elimination of these points in the rough correlation, the disturbance from the false correlations in the assignment process is decreased, so the data correlation accuracy is improved correspondingly. Complexity analyses of the new multi-layer optimal algorithm and the traditional optimal assignment algorithm are given. Simulation results show that the new algorithm is feasible and effective.
Fister, Iztok; Yang, Xin-She; Fister, Dušan
2013-01-01
Swarm intelligence is a very powerful technique to be used for optimization purposes. In this paper we present a new swarm intelligence algorithm, based on the bat algorithm. The Bat algorithm is hybridized with differential evolution strategies. Besides showing very promising results of the standard benchmark functions, this hybridization also significantly improves the original bat algorithm.
Anaphora Resolution Algorithm for Sanskrit
Pralayankar, Pravin; Devi, Sobha Lalitha
This paper presents an algorithm, which identifies different types of pronominal and its antecedents in Sanskrit, an Indo-European language. The computational grammar implemented here uses very familiar concepts such as clause, subject, object etc., which are identified with the help of morphological information and concepts such as precede and follow. It is well known that natural languages contain anaphoric expressions, gaps and elliptical constructions of various kinds and that understanding of natural languages involves assignment of interpretations to these elements. Therefore, it is only to be expected that natural language understanding systems must have the necessary mechanism to resolve the same. The method we adopt here for resolving the anaphors is by exploiting the morphological richness of the language. The system is giving encouraging results when tested with a small corpus.
Enhancements Of Fuzzy Q-Learning Algorithm
Directory of Open Access Journals (Sweden)
Grzegorz Głowaty
2005-01-01
Full Text Available Fuzzy Q-Learning algorithm combines reinforcement learning techniques with fuzzy modelling. It provides a ﬂexible solution for automatic discovery of rules for fuzzy systems inthe process of reinforcement learning. In this paper we propose several enhancements tothe original algorithm to make it more performant and more suitable for problems withcontinuous-input continuous-output space. Presented improvements involve generalizationof the set of possible rule conclusions. The aim is not only to automatically discover anappropriate rule-conclusions assignment, but also to automatically deﬁne the actual conclusions set given the all possible rules conclusions. To improve algorithm performance whendealing with environments with inertness, a special rule selection policy is proposed.
Energy Technology Data Exchange (ETDEWEB)
Geist, G.A. [Oak Ridge National Lab., TN (United States). Computer Science and Mathematics Div.; Howell, G.W. [Florida Inst. of Tech., Melbourne, FL (United States). Dept. of Applied Mathematics; Watkins, D.S. [Washington State Univ., Pullman, WA (United States). Dept. of Pure and Applied Mathematics
1997-11-01
The BR algorithm, a new method for calculating the eigenvalues of an upper Hessenberg matrix, is introduced. It is a bulge-chasing algorithm like the QR algorithm, but, unlike the QR algorithm, it is well adapted to computing the eigenvalues of the narrowband, nearly tridiagonal matrices generated by the look-ahead Lanczos process. This paper describes the BR algorithm and gives numerical evidence that it works well in conjunction with the Lanczos process. On the biggest problems run so far, the BR algorithm beats the QR algorithm by a factor of 30--60 in computing time and a factor of over 100 in matrix storage space.
Computational Hardness of Enumerating Satisfying Spin-Assignments in Triangulations
Jiménez, Andrea
2011-01-01
Satisfying spin-assignments in triangulations of a surface are states of minimum energy of the antiferromagnetic Ising model on triangulations which correspond (via geometric duality) to perfect matchings in cubic bridgeless graphs. In this work we show that it is NP-complete to decide whether or not a surface triangulation admits a satisfying spin-assignment, and that it is #P-complete to determine the number of such assignments. Both results are derived via an elaborate (and atypical) reduction that maps a Boolean formula in 3-conjunctive normal form into a triangulation of an orientable closed surface.
A Variable Weighted Least-Connection Algorithm for Multimedia Transmission
Institute of Scientific and Technical Information of China (English)
杨立辉; 余胜生
2003-01-01
Under high loads, a multimedia duster server can serve many hundreds of connections concurrently, where a load balancer distributes the incoming connection request to each node according to a preset algorithm. Among existing scheduling algorithms, round-Robin and least-connection do not take into account the difference of service capability of each node and improved algorithms such as weighted round-Robin and weighted least-connection. They also do not consider the fact that the ratio of number of TCP connections and the fixed weight does not reflect the real load of node. In this paper we introduce our attempts in improving the scheduling algorithms and propose a variable weighted least-connection algorithm, which assigns variable weight, instead of fixed weight, to each node according to its real time resource. A validating trial has been performed and the results show that the proposed algorithm has effective load balancing in one central control node scenario.
An Efficient Graph-Coloring Algorithm for Processor Allocation
Directory of Open Access Journals (Sweden)
Mohammed Hasan Mahafzah
2013-06-01
Full Text Available This paper develops an efficient exact graph-coloring algorithm based on Maximum Independent Set (MIS for allocating processors in distributed systems. This technique represents the allocated processors in specific time in a fully connected graph and prevents each processor in multiprocessor system to be assigned to more than one process at a time. This research uses a sequential technique to distribute processes among processors. Moreover, the proposed method has been constructed by modifying the FMIS algorithm. The proposed algorithm has been programmed in Visual C++ and implemented on an Intel core i7. The experiments show that the proposed algorithm gets better performance in terms of CPU utilization, and minimum time for of graph coloring, comparing with the latest FMIS algorithm. The proposed algorithm can be developed to detect defected processor in the system.
Priyamvada Paliwal#1, Meghna Sharma
2013-01-01
The DBSCAN algorithm can identify clusters in large spatial data sets by looking at the local density of database elements, using only one input parameter. This paper presents a comprehensive study of DBSCAN algorithm and the enhanced version of DBSCAN algorithm The salient of this paper to present enhanced DBSCAN algorithm with its implementation with the complexity and the difference between the older version of DBSCAN algorithm. And there are also additional features described with this al...
Algorithmically specialized parallel computers
Snyder, Lawrence; Gannon, Dennis B
1985-01-01
Algorithmically Specialized Parallel Computers focuses on the concept and characteristics of an algorithmically specialized computer.This book discusses the algorithmically specialized computers, algorithmic specialization using VLSI, and innovative architectures. The architectures and algorithms for digital signal, speech, and image processing and specialized architectures for numerical computations are also elaborated. Other topics include the model for analyzing generalized inter-processor, pipelined architecture for search tree maintenance, and specialized computer organization for raster
Overview: Evolutionary Algorithms
Bartz-Beielstein, Thomas (Dr.); Mersmann, Olaf
2014-01-01
Evolutionary algorithm (EA) is an umbrella term used to describe population-based stochastic direct search algorithms that in some sense mimic natural evolution. Prominent representatives of such algorithms are genetic algorithms, evolution strategies, evolutionary programming, and genetic programming. On the basis of the evolutionary cycle, similarities and differences between these algorithms are described. We briefly discuss how EAs can be adapted to work well in case of multiple objective...
Overview: Evolutionary Algorithms
Bartz-Beielstein, Thomas (Dr.); Branke, Jürgen; Mehnen, Jörn; Mersmann, Olaf
2015-01-01
Evolutionary algorithm (EA) is an umbrella term used to describe population-based stochastic direct search algorithms that in some sense mimic natural evolution. Prominent representatives of such algorithms are genetic algorithms, evolution strategies, evolutionary programming, and genetic programming. On the basis of the evolutionary cycle, similarities and differences between these algorithms are described. We briefly discuss how EAs can be adapted to work well in case of multiple objective...
Zawadzka-Kazimierczuk, Anna; Koźmiński, Wiktor; Billeter, Martin
2012-09-01
While NMR studies of proteins typically aim at structure, dynamics or interactions, resonance assignments represent in almost all cases the initial step of the analysis. With increasing complexity of the NMR spectra, for example due to decreasing extent of ordered structure, this task often becomes both difficult and time-consuming, and the recording of high-dimensional data with high-resolution may be essential. Random sampling of the evolution time space, combined with sparse multidimensional Fourier transform (SMFT), allows for efficient recording of very high dimensional spectra (≥4 dimensions) while maintaining high resolution. However, the nature of this data demands for automation of the assignment process. Here we present the program TSAR (Tool for SMFT-based Assignment of Resonances), which exploits all advantages of SMFT input. Moreover, its flexibility allows to process data from any type of experiments that provide sequential connectivities. The algorithm was tested on several protein samples, including a disordered 81-residue fragment of the δ subunit of RNA polymerase from Bacillus subtilis containing various repetitive sequences. For our test examples, TSAR achieves a high percentage of assigned residues without any erroneous assignments. PMID:22806130
Energy Technology Data Exchange (ETDEWEB)
Zawadzka-Kazimierczuk, Anna; Kozminski, Wiktor [University of Warsaw, Faculty of Chemistry (Poland); Billeter, Martin, E-mail: martin.billeter@chem.gu.se [University of Gothenburg, Biophysics Group, Department of Chemistry and Molecular Biology (Sweden)
2012-09-15
While NMR studies of proteins typically aim at structure, dynamics or interactions, resonance assignments represent in almost all cases the initial step of the analysis. With increasing complexity of the NMR spectra, for example due to decreasing extent of ordered structure, this task often becomes both difficult and time-consuming, and the recording of high-dimensional data with high-resolution may be essential. Random sampling of the evolution time space, combined with sparse multidimensional Fourier transform (SMFT), allows for efficient recording of very high dimensional spectra ({>=}4 dimensions) while maintaining high resolution. However, the nature of this data demands for automation of the assignment process. Here we present the program TSAR (Tool for SMFT-based Assignment of Resonances), which exploits all advantages of SMFT input. Moreover, its flexibility allows to process data from any type of experiments that provide sequential connectivities. The algorithm was tested on several protein samples, including a disordered 81-residue fragment of the {delta} subunit of RNA polymerase from Bacillus subtilis containing various repetitive sequences. For our test examples, TSAR achieves a high percentage of assigned residues without any erroneous assignments.
Subcarrier Group Assignment for MC-CDMA Wireless Networks
Directory of Open Access Journals (Sweden)
Tho Le-Ngoc
2007-12-01
Full Text Available Two interference-based subcarrier group assignment strategies in dynamic resource allocation are proposed for MC-CDMA wireless systems to achieve high throughput in a multicell environment. Least interfered group assignment (LIGA selects for each session the subcarrier group on which the user receives the minimum interference, while best channel ratio group assignment (BCRGA chooses the subcarrier group with the largest channel response-to-interference ratio. Both analytical framework and simulation model are developed for evaluation of throughput distribution of the proposed schemes. An iterative approach is devised to handle the complex interdependency between multicell interference profiles in the throughput analysis. Illustrative results show significant throughput improvement offered by the interference-based assignment schemes for MC-CDMA multicell wireless systems. In particular, under low loading conditions, LIGA renders the best performance. However, as the load increases BCRGA tends to offer superior performance.
28 CFR 544.74 - Work assignment limitations.
2010-07-01
... appointment and promotion apply to all inmates, including those exempted from required participation in the... of the assignment. Local Federal Prison Industry (FPI) management may elect to retain the...
Reading Assignment 8 (theory sessions) - 31710 General Linguistics I
Muñoz Baell, Irma María
2012-01-01
Reading Assignment 8 - Driving questions: HOW IS LANGUAGE STUDIED? WHAT DOES IT MEAN THAT LANGUAGE IS STUDIED SCIENTIFICALLY? - Academic year 2011-2012 (ECTS credits: 6 (150 hours)). See the Planned Weekly Schedule (Theory sessions).
Calibrated peer review assignments for the earth sciences
Rudd, J.A., II; Wang, V.Z.; Cervato, C.; Ridky, R.W.
2009-01-01
Calibrated Peer Review ??? (CPR), a web-based instructional tool developed as part of the National Science Foundation reform initiatives in undergraduate science education, allows instructors to incorporate multiple writing assignments in large courses without overwhelming the instructor. This study reports successful implementation of CPR in a large, introductory geology course and student learning of geoscience content. For each CPR assignment in this study, students studied web-based and paper resources, wrote an essay, and reviewed seven essays (three from the instructor, three from peers, and their own) on the topic. Although many students expressed negative attitudes and concerns, particularly about the peer review process of this innovative instructional approach, they also recognized the learning potential of completing CPR assignments. Comparing instruction on earthquakes and plate boundaries using a CPR assignment vs. an instructional video lecture and homework essay with extensive instructor feedback, students mastered more content via CPR instruction.
Frequency Assignment Problem with Net Filter Discrimination Constraints
Yilmaz, H. Birkan; Koo, Bon-Hong; Park, Sung-ho; Park, Hwi-Sung; Ham, Jae-Hyun; Chae, Chan-Byoung
2016-01-01
Managing radio spectrum resources is a crucial issue. The frequency assignment problem (FAP) basically aims to allocate, in an efficient manner, limited number of frequencies to communication links. Geographically close links, however, cause interference, which complicates the assignment, imposing frequency separation constraints. The FAP is closely related to the graph-coloring problem and it is an NP-hard problem. In this paper, we propose to incorporate the randomization into greedy and fa...
Homework assignment and student achievement in OECD countries
Torberg Falch; Marte Rønning
2011-01-01
This paper analyzes the effect of assigning homework on student achievement using data from 16 OECD countries that participated in TIMSS 2007. The model exploits withinstudent variation in homework across subjects in a sample of primary school students who have the same teacher in two related subjects; mathematics and science. Unobserved teacher and student characteristics are thus conditioned out of the model and the identification rests on random relative homework assignment across the subj...
Using graded questions to increase timely reading of assigned material
Uskul, Ayse K.; Eaton, J
2005-01-01
We assigned students in a personality psychology class graded long-answer questions in an attempt to increase their likelihood of reading assigned class material in a timely manner. We evaluated the effectiveness of this technique by examining exam scores and student evaluations. Students performed significantly better on the exam questions that were related to the topics covered by the long-answer questions than they did on exam questions related to other topics. Students also reported havin...
Managing cost uncertainties in transportation and assignment problems
Arsham, H.; Adlakha, V.
1998-01-01
In a fast changing global market, a manager is concerned with cost uncertainties of the cost matrix in transportation problems (TP) and assignment problems (AP).A time lag between the development and application of the model could cause cost parameters to assume different values when an optimal assignment is implemented. The manager might wish to determine the responsiveness of the current optimal solution to such uncertainties. A desirable tool is to construct a perturbation set (PS) of cost...
A delayed flow intersection model for dynamic traffic assignment
DURLIN, T; HENN, V
2005-01-01
Day-to-Day and Within-Day dynamics are classically observed in dynamic traffic assignment, but smaller ones due to traffic lights phases also occur. These micro variations induce flow fluctuations defined at a cycle time scale. Their precise knowledge is irrelevant in a dynamic traffic assignment context. We propose to integrate these micro dynamics into a new intersection model without stages in which their average effects must be taken into account, especially delay and flow restriction ge...
Context-Aware Reviewer Assignment for Trust Enhanced Peer Review.
Directory of Open Access Journals (Sweden)
Lei Li
Full Text Available Reviewer assignment is critical to peer review systems, such as peer-reviewed research conferences or peer-reviewed funding applications, and its effectiveness is a deep concern of all academics. However, there are some problems in existing peer review systems during reviewer assignment. For example, some of the reviewers are much more stringent than others, leading to an unfair final decision, i.e., some submissions (i.e., papers or applications with better quality are rejected. In this paper, we propose a context-aware reviewer assignment for trust enhanced peer review. More specifically, in our approach, we first consider the research area specific expertise of reviewers, and the institution relevance and co-authorship between reviewers and authors, so that reviewers with the right expertise are assigned to the corresponding submissions without potential conflict of interest. In addition, we propose a novel cross-assignment paradigm, and reviewers are cross-assigned in order to avoid assigning a group of stringent reviewers or a group of lenient reviewers to the same submission. More importantly, on top of them, we propose an academic CONtext-aware expertise relevanCe oriEnted Reviewer cross-assignmenT approach (CONCERT, which aims to effectively estimate the "true" ratings of submissions based on the ratings from all reviewers, even though no prior knowledge exists about the distribution of stringent reviewers and lenient reviewers. The experiments illustrate that compared with existing approaches, our proposed CONCERT approach can less likely assign more than one stringent reviewers or lenient reviewers to a submission simultaneously and significantly reduce the influence of ratings from stringent reviewers and lenient reviewers, leading to trust enhanced peer review and selection, no matter what kind of distributions of stringent reviewers and lenient reviewers are.
Context-Aware Reviewer Assignment for Trust Enhanced Peer Review.
Li, Lei; Wang, Yan; Liu, Guanfeng; Wang, Meng; Wu, Xindong
2015-01-01
Reviewer assignment is critical to peer review systems, such as peer-reviewed research conferences or peer-reviewed funding applications, and its effectiveness is a deep concern of all academics. However, there are some problems in existing peer review systems during reviewer assignment. For example, some of the reviewers are much more stringent than others, leading to an unfair final decision, i.e., some submissions (i.e., papers or applications) with better quality are rejected. In this paper, we propose a context-aware reviewer assignment for trust enhanced peer review. More specifically, in our approach, we first consider the research area specific expertise of reviewers, and the institution relevance and co-authorship between reviewers and authors, so that reviewers with the right expertise are assigned to the corresponding submissions without potential conflict of interest. In addition, we propose a novel cross-assignment paradigm, and reviewers are cross-assigned in order to avoid assigning a group of stringent reviewers or a group of lenient reviewers to the same submission. More importantly, on top of them, we propose an academic CONtext-aware expertise relevanCe oriEnted Reviewer cross-assignmenT approach (CONCERT), which aims to effectively estimate the "true" ratings of submissions based on the ratings from all reviewers, even though no prior knowledge exists about the distribution of stringent reviewers and lenient reviewers. The experiments illustrate that compared with existing approaches, our proposed CONCERT approach can less likely assign more than one stringent reviewers or lenient reviewers to a submission simultaneously and significantly reduce the influence of ratings from stringent reviewers and lenient reviewers, leading to trust enhanced peer review and selection, no matter what kind of distributions of stringent reviewers and lenient reviewers are. PMID:26090849
Membership Function Assignment for Elements of Single OWL Ontology
Verhodubs, Olegs
2014-01-01
This paper develops the idea of membership function assignment for OWL (Web Ontology Language) ontology elements in order to subsequently generate fuzzy rules from this ontology. The task of membership function assignment for OWL ontology elements had already been partially described, but this concerned the case, when several OWL ontologies of the same domain were available, and they were merged into a single ontology. The purpose of this paper is to present the way of membership function ass...
Teaching and Learning Data Visualization: Ideas and Assignments
Nolan, Deborah; Perrett, Jamis
2015-01-01
This article discusses how to make statistical graphics a more prominent element of the undergraduate statistics curricula. The focus is on several different types of assignments that exemplify how to incorporate graphics into a course in a pedagogically meaningful way. These assignments include having students deconstruct and reconstruct plots, copy masterful graphs, create one-minute visual revelations, convert tables into `pictures', and develop interactive visualizations with, e.g., the v...
Using Open Data as a Material for Introductory Programming Assignments
Coughlan, Tim
2015-01-01
This case study explores why and how open data can be used as a material with which to produce engaging challenges for students as they are introduced to programming. Through describing the process of producing the assignments, and learner responses to them, we suggest that open data is a powerful material for designing learning activities because of its qualities of ease of access and authenticity. We conclude by outlining steps to take in devising and implementing open data-based assignments.
Jackson, C. Kirabo
2011-01-01
Existing studies on single-sex schooling suffer from biases due to student selection to schools and single-sex schools being better in unmeasured ways. In Trinidad and Tobago students are assigned to secondary schools based on an algorithm allowing one to address self-selection bias and cleanly estimate an upper-bound single-sex school effect. The…
Comparison of greedy algorithms for α-decision tree construction
Alkhalid, Abdulaziz
2011-01-01
A comparison among different heuristics that are used by greedy algorithms which constructs approximate decision trees (α-decision trees) is presented. The comparison is conducted using decision tables based on 24 data sets from UCI Machine Learning Repository [2]. Complexity of decision trees is estimated relative to several cost functions: depth, average depth, number of nodes, number of nonterminal nodes, and number of terminal nodes. Costs of trees built by greedy algorithms are compared with minimum costs calculated by an algorithm based on dynamic programming. The results of experiments assign to each cost function a set of potentially good heuristics that minimize it. © 2011 Springer-Verlag.
An algorithm for link restoration of wavelength routing optical networks
DEFF Research Database (Denmark)
Limal, Emmanuel; Stubkjær, Kristian
1999-01-01
We present an algorithm for restoration of single link failure in wavelength routing multihop optical networks. The algorithm is based on an innovative study of networks using graph theory. It has the following original features: it (i) assigns working and spare channels simultaneously, (ii......) prevents the search for unacceptable routing paths by pointing out channels required for restoration, (iii) offers a high utilization of the capacity resources and (iv) allows a trivial search for the restoration paths. The algorithm is for link restoration of networks without wavelength translation. Its...
Quantum Computation and Algorithms
International Nuclear Information System (INIS)
It is now firmly established that quantum algorithms provide a substantial speedup over classical algorithms for a variety of problems, including the factorization of large numbers and the search for a marked element in an unsorted database. In this talk I will review the principles of quantum algorithms, the basic quantum gates and their operation. The combination of superposition and interference, that makes these algorithms efficient, will be discussed. In particular, Grover's search algorithm will be presented as an example. I will show that the time evolution of the amplitudes in Grover's algorithm can be found exactly using recursion equations, for any initial amplitude distribution
New focused crawling algorithm
Institute of Scientific and Technical Information of China (English)
Su Guiyang; Li Jianhua; Ma Yinghua; Li Shenghong; Song Juping
2005-01-01
Focused carawling is a new research approach of search engine. It restricts information retrieval and provides search service in specific topic area. Focused crawling search algorithm is a key technique of focused crawler which directly affects the search quality. This paper first introduces several traditional topic-specific crawling algorithms, then an inverse link based topic-specific crawling algorithm is put forward. Comparison experiment proves that this algorithm has a good performance in recall, obviously better than traditional Breadth-First and Shark-Search algorithms. The experiment also proves that this algorithm has a good precision.
Symplectic algebraic dynamics algorithm
Institute of Scientific and Technical Information of China (English)
2007-01-01
Based on the algebraic dynamics solution of ordinary differential equations andintegration of ,the symplectic algebraic dynamics algorithm sn is designed,which preserves the local symplectic geometric structure of a Hamiltonian systemand possesses the same precision of the na ve algebraic dynamics algorithm n.Computer experiments for the 4th order algorithms are made for five test modelsand the numerical results are compared with the conventional symplectic geometric algorithm,indicating that sn has higher precision,the algorithm-inducedphase shift of the conventional symplectic geometric algorithm can be reduced,and the dynamical fidelity can be improved by one order of magnitude.
L. Finesso; A. Grassi; P. Spreij
2010-01-01
We propose a two-step algorithm for the construction of a Hidden Markov Model (HMM) of assigned size, i.e. cardinality of the state space of the underlying Markov chain, whose n-dimensional distribution is closest in divergence to a given distribution. The algorithm is based on the factorization of
A Bayesian Assignment Method for Ambiguous Bisulfite Short Reads.
Directory of Open Access Journals (Sweden)
Hong Tran
Full Text Available DNA methylation is an epigenetic modification critical for normal development and diseases. The determination of genome-wide DNA methylation at single-nucleotide resolution is made possible by sequencing bisulfite treated DNA with next generation high-throughput sequencing. However, aligning bisulfite short reads to a reference genome remains challenging as only a limited proportion of them (around 50-70% can be aligned uniquely; a significant proportion, known as multireads, are mapped to multiple locations and thus discarded from downstream analyses, causing financial waste and biased methylation inference. To address this issue, we develop a Bayesian model that assigns multireads to their most likely locations based on the posterior probability derived from information hidden in uniquely aligned reads. Analyses of both simulated data and real hairpin bisulfite sequencing data show that our method can effectively assign approximately 70% of the multireads to their best locations with up to 90% accuracy, leading to a significant increase in the overall mapping efficiency. Moreover, the assignment model shows robust performance with low coverage depth, making it particularly attractive considering the prohibitive cost of bisulfite sequencing. Additionally, results show that longer reads help improve the performance of the assignment model. The assignment model is also robust to varying degrees of methylation and varying sequencing error rates. Finally, incorporating prior knowledge on mutation rate and context specific methylation level into the assignment model increases inference accuracy. The assignment model is implemented in the BAM-ABS package and freely available at https://github.com/zhanglabvt/BAM_ABS.
Measuring shareholder value in asset-based lending industries
Franco Fiordelisi; Stefano Monferrà
2009-01-01
Purpose -The purpose of this paper is to analyse the creation of shareholder value (SHV) created by non-depository financial institutions and, especially, by leasing and factoring (L&F) companies. Design/methodology/approach -The cost of capital of both L&F companies is estimated using an accounting procedure and, next, the economic value added (EVA) created by Italian L&F companies over the period 2002-2004 is estimated. Findings -L&F companies display high profitability and EVA levels over ...
International Nuclear Information System (INIS)
Genome wide gene expression data is a rich source for the identification of gene signatures suitable for clinical purposes and a number of statistical algorithms have been described for both identification and evaluation of such signatures. Some employed algorithms are fairly complex and hence sensitive to over-fitting whereas others are more simple and straight forward. Here we present a new type of simple algorithm based on ROC analysis and the use of metagenes that we believe will be a good complement to existing algorithms. The basis for the proposed approach is the use of metagenes, instead of collections of individual genes, and a feature selection using AUC values obtained by ROC analysis. Each gene in a data set is assigned an AUC value relative to the tumor class under investigation and the genes are ranked according to these values. Metagenes are then formed by calculating the mean expression level for an increasing number of ranked genes, and the metagene expression value that optimally discriminates tumor classes in the training set is used for classification of new samples. The performance of the metagene is then evaluated using LOOCV and balanced accuracies. We show that the simple uni-variate gene expression average algorithm performs as well as several alternative algorithms such as discriminant analysis and the more complex approaches such as SVM and neural networks. The R package rocc is freely available at http://cran.r-project.org/web/packages/rocc/index.html
RNA-PAIRS: RNA probabilistic assignment of imino resonance shifts
Energy Technology Data Exchange (ETDEWEB)
Bahrami, Arash; Clos, Lawrence J.; Markley, John L.; Butcher, Samuel E. [National Magnetic Resonance Facility at Madison (United States); Eghbalnia, Hamid R., E-mail: eghbalhd@uc.edu [University of Cincinnati, Department of Molecular and Cellular Physiology (United States)
2012-04-15
The significant biological role of RNA has further highlighted the need for improving the accuracy, efficiency and the reach of methods for investigating RNA structure and function. Nuclear magnetic resonance (NMR) spectroscopy is vital to furthering the goals of RNA structural biology because of its distinctive capabilities. However, the dispersion pattern in the NMR spectra of RNA makes automated resonance assignment, a key step in NMR investigation of biomolecules, remarkably challenging. Herein we present RNA Probabilistic Assignment of Imino Resonance Shifts (RNA-PAIRS), a method for the automated assignment of RNA imino resonances with synchronized verification and correction of predicted secondary structure. RNA-PAIRS represents an advance in modeling the assignment paradigm because it seeds the probabilistic network for assignment with experimental NMR data, and predicted RNA secondary structure, simultaneously and from the start. Subsequently, RNA-PAIRS sets in motion a dynamic network that reverberates between predictions and experimental evidence in order to reconcile and rectify resonance assignments and secondary structure information. The procedure is halted when assignments and base-parings are deemed to be most consistent with observed crosspeaks. The current implementation of RNA-PAIRS uses an initial peak list derived from proton-nitrogen heteronuclear multiple quantum correlation ({sup 1}H-{sup 15}N 2D HMQC) and proton-proton nuclear Overhauser enhancement spectroscopy ({sup 1}H-{sup 1}H 2D NOESY) experiments. We have evaluated the performance of RNA-PAIRS by using it to analyze NMR datasets from 26 previously studied RNAs, including a 111-nucleotide complex. For moderately sized RNA molecules, and over a range of comparatively complex structural motifs, the average assignment accuracy exceeds 90%, while the average base pair prediction accuracy exceeded 93%. RNA-PAIRS yielded accurate assignments and base pairings consistent with imino
Competing Sudakov Veto Algorithms
Kleiss, Ronald
2016-01-01
We present a way to analyze the distribution produced by a Monte Carlo algorithm. We perform these analyses on several versions of the Sudakov veto algorithm, adding a cutoff, a second variable and competition between emission channels. The analysis allows us to prove that multiple, seemingly different competition algorithms, including those that are currently implemented in most parton showers, lead to the same result. Finally, we test their performance and show that there are significantly faster alternatives to the commonly used algorithms.
Borbely, Eva
2007-01-01
A quantum algorithm is a set of instructions for a quantum computer, however, unlike algorithms in classical computer science their results cannot be guaranteed. A quantum system can undergo two types of operation, measurement and quantum state transformation, operations themselves must be unitary (reversible). Most quantum algorithms involve a series of quantum state transformations followed by a measurement. Currently very few quantum algorithms are known and no general design methodology e...
Accurate Finite Difference Algorithms
Goodrich, John W.
1996-01-01
Two families of finite difference algorithms for computational aeroacoustics are presented and compared. All of the algorithms are single step explicit methods, they have the same order of accuracy in both space and time, with examples up to eleventh order, and they have multidimensional extensions. One of the algorithm families has spectral like high resolution. Propagation with high order and high resolution algorithms can produce accurate results after O(10(exp 6)) periods of propagation with eight grid points per wavelength.
Approximate iterative algorithms
Almudevar, Anthony Louis
2014-01-01
Iterative algorithms often rely on approximate evaluation techniques, which may include statistical estimation, computer simulation or functional approximation. This volume presents methods for the study of approximate iterative algorithms, providing tools for the derivation of error bounds and convergence rates, and for the optimal design of such algorithms. Techniques of functional analysis are used to derive analytical relationships between approximation methods and convergence properties for general classes of algorithms. This work provides the necessary background in functional analysis a
Autonomous Star Tracker Algorithms
DEFF Research Database (Denmark)
Betto, Maurizio; Jørgensen, John Leif; Kilsgaard, Søren;
1998-01-01
Proposal, in response to an ESA R.f.P., to design algorithms for autonomous star tracker operations.The proposal also included the development of a star tracker breadboard to test the algorithms performances.......Proposal, in response to an ESA R.f.P., to design algorithms for autonomous star tracker operations.The proposal also included the development of a star tracker breadboard to test the algorithms performances....
Hybridization of evolutionary algorithms
Fister, Iztok; Mernik, Marjan; Brest, Janez
2012-01-01
Evolutionary algorithms are good general problem solver but suffer from a lack of domain specific knowledge. However, the problem specific knowledge can be added to evolutionary algorithms by hybridizing. Interestingly, all the elements of the evolutionary algorithms can be hybridized. In this chapter, the hybridization of the three elements of the evolutionary algorithms is discussed: the objective function, the survivor selection operator and the parameter settings. As an objective function...
Using Genetic Algorithm For Winter Maintenance Operations: Multi Depot K-Chinese Postman Problem
Directory of Open Access Journals (Sweden)
İbrahim Zeki Akyurt
2015-02-01
Full Text Available In this study, the assignment and routing problem of one of Istanbul’s winter maintenance activities, salt pouring, was scrutinized. The starting point of the study considers the high cost of winter maintenance work, a shrinking assigned budget, high numbers of vehicles and streets to service that the increase in difficulty to solve the problem due to their high numbers. In this respect, the problem was modeled as multi depot k-Chinese postman problem, a type of arc routing problem. This mathematical model was solved by genetic algorithm. For comparison, the current solution, Clarke and Wright Algorithm and Sweep Algorithm were used.
Self-adaptive learning based discrete differential evolution algorithm for solving CJWTA problem
Institute of Scientific and Technical Information of China (English)
Yu Xue; Yi Zhuang; Tianquan Ni; Siru Ni; Xuezhi Wen
2014-01-01
Cooperative jamming weapon-target assignment (CJWTA) problem is a key issue in electronic countermeasures (ECM). Some symbols which relevant to the CJWTA are defined firstly. Then, a formulation of jamming fitness is presented. Final y, a model of the CJWTA problem is constructed. In order to solve the CJWTA problem efficiently, a self-adaptive learning based discrete differential evolution (SLDDE) algorithm is proposed by introduc-ing a self-adaptive learning mechanism into the traditional discrete differential evolution algorithm. The SLDDE algorithm steers four candidate solution generation strategies simultaneously in the framework of the self-adaptive learning mechanism. Computa-tional simulations are conducted on ten test instances of CJWTA problem. The experimental results demonstrate that the proposed SLDDE algorithm not only can generate better results than only one strategy based discrete differential algorithms, but also outper-forms two algorithms which are proposed recently for the weapon-target assignment problems.
Compatibility of state assignments and pooling of information
Brun, Todd A.; Hsieh, Min-Hsiu; Perry, Christopher
2015-07-01
We say that two (or more) state assignments for one and the same quantum system are compatible if they could represent the assignments of observers with differing information about the system. A criterion for compatibility was proposed in [Phys. Rev. A 65, 032315 (2002), 10.1103/PhysRevA.65.032315]; however, this leaves unanswered the question of whether there are degrees of compatibility which could be represented by some quantitative measure, and whether there is a straightforward procedure whereby the observers can pool their information to arrive at a unique joint state assignment. We argue that such measures are only sensible given some assumption about what kind of information was used in making the state assignments in the first place, and that in general state assignments do not represent all of the information possessed by the observers. However, we examine one particular measure and show that it has a straightforward interpretation, assuming that the information was acquired from a particular type of measurement, and that in this case there is a natural rule for pooling information. We extend this measure to compatibility of states for k observers and show that the value is the solution to a semidefinite program. Similar compatibility measures can be defined for alternative notions of state compatibility, including post-Peierls and equal support compatibilities.
An integer programming model for assigning students to elective courses
Directory of Open Access Journals (Sweden)
Ivo Beroš
2015-10-01
Full Text Available This paper deals with the problem of assigning students to elective courses according to their preferences. This process of assigning students to elective courses according to their preferences often places before academic institutions numerous obstacles, the most typical being a limited number of students who can be assigned to any particular class. Furthermore, due to financial or technical reasons, the maximum number of the elective courses is determined in advance, meaning that the institution decides which courses to conduct. Therefore, the expectation that all the students will be assigned to their first choice of courses is not realistic (perfect satisfaction. This paper presents an integer programming model that maximizes the total student satisfaction in line with a number of different constraints. The measure of student satisfaction is based on a student's order of preference according to the principle: the more a choice is met the higher the satisfaction. Following the basic model, several versions of the models are generated to cover possible real-life situations, while taking into consideration the manner student satisfaction is measured, as well as the preference of academic institution within set technical and financial constraints. The main contribution of the paper is introducing the concept of the minimal student satisfaction level that reduces the number of students dissatised with the courses to which they were assigned.
Reflective practice: assessment of assignments in English for Specific Purposes
Directory of Open Access Journals (Sweden)
Galina Kavaliauskiené
2007-10-01
Full Text Available The construct alternative assessment has been widely used in higher education. It is often defined as any type of assessment of learners who provide a response to an assignment. The key features of alternative assessment are active participation of learners in self-evaluation of their performance, and the development of reflective thinking through reflective thinking (Schön, 1983. The success of alternative assessment in language teaching is predetermined by student’s performance and demonstrates learner’s language proficiency in contemporary communicative classrooms. This paper aims at researching the influence of students’ evaluations of various assignments for their linguistic development in English for Specific Purposes (ESP. The study uses learners’ assessment of different assignments and learners’ in-course and post-course written reflections on benefits to language mastery. Learners’ assignments included were contributions to portfolios (dossiers, such as essays and summaries, oral presentations, short impromptu talks, creative tasks, tests, and self-assessment notes (reflections on activities in learning ESP. Findings were obtained for two streams of the project participants. Results showed that self-assessment was beneficial for learners’ linguistic development. The context of learners’ reflections reveals that the attitudes to various assignments are affected by success or failure in students’ performance. Reflective practice might help teachers develop ways of dealing with previously identified difficulties and improve the quality of teaching.
DEFF Research Database (Denmark)
Husfeldt, Thore
2015-01-01
This chapter presents an introduction to graph colouring algorithms. The focus is on vertex-colouring algorithms that work for general classes of graphs with worst-case performance guarantees in a sequential model of computation. The presentation aims to demonstrate the breadth of available...... techniques and is organized by algorithmic paradigm....
Improved Parameterized Algorithms for Constraint Satisfaction
Kim, Eun Jung
2010-01-01
Results from inapproximability provide several sharp thresholds on the approximability of important optimization problems. We give several improved parameterized algorithms for solving constraint satisfaction problems above a tight threshold. Our results include the following: - Improved algorithms for any Constraint Satisfaction Problem: Take any boolean Max-CSP with at most $c$ variables per constraint such that a random assignment satisfies a constraint with probability $p$. There is an algorithm such that for every instance of the problem with $m$ constraints, the algorithm decides whether at least $pm+k$ constraints can be satisfied in $O(2^{(c(c+1)/2) k} m)$ time. This improves on results of [Alon et al., SODA 2010] and [Crowston et al., SWAT 2010]. We observe that an $O(2^{\\eps k + \\eps m})$ time algorithm for every $\\eps > 0$ would imply that 3SAT is in subexponential time, so it seems unlikely that our runtime dependence on $k$ can be significantly improved. Our proof also shows that every Max-$c$-CS...
Nature-inspired optimization algorithms
Yang, Xin-She
2014-01-01
Nature-Inspired Optimization Algorithms provides a systematic introduction to all major nature-inspired algorithms for optimization. The book's unified approach, balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with well-chosen case studies to illustrate how these algorithms work. Topics include particle swarm optimization, ant and bee algorithms, simulated annealing, cuckoo search, firefly algorithm, bat algorithm, flower algorithm, harmony search, algorithm analysis, constraint handling, hybrid methods, parameter tuning
Modified Adaptive Weighted Averaging Filtering Algorithm for Noisy Image Sequences
Institute of Scientific and Technical Information of China (English)
LI Weifeng; YU Daoyin; CHEN Xiaodong
2007-01-01
In order to avoid the influence of noise variance on the filtering performances, a modified adaptive weighted averaging (MAWA) filtering algorithm is proposed for noisy image sequences. Based upon adaptive weighted averaging pixel values in consecutive frames, this algorithm achieves the filtering goal by assigning smaller weights to the pixels with inappropriate estimated motion trajectory for noise. It only utilizes the intensity of pixels to suppress noise and accordingly is independent of noise variance. To evaluate the performance of the proposed filtering algorithm, its mean square error and percentage of preserved edge points were compared with those of traditional adaptive weighted averaging and non-adaptive mean filtering algorithms under different noise variances. Relevant results show that the MAWA filtering algorithm can preserve image structures and edges under motion after attenuating noise, and thus may be used in image sequence filtering.
Chandramouli Anandaraman; Arun Vikram Madurai Sankar; Ramaraj Natarajan
2012-01-01
A new evolutionary computation algorithm, Superbug algorithm, which simulates evolution of bacteria in a culture, is proposed. The algorithm is developed for solving large scale optimization problems such as scheduling, transportation and assignment problems. In this work, the algorithm optimizes machine schedules in a Flexible Manufacturing System (FMS) by minimizing makespan. The FMS comprises of four machines and two identical Automated Guided Vehicles (AGVs). AGVs are used for carrying jo...
Smith, Edward M.; Littrell, Jack; Olivier, Michael
2007-01-01
High-throughput SNP genotyping platforms use automated genotype calling algorithms to assign genotypes. While these algorithms work efficiently for individual platforms, they are not compatible with other platforms, and have individual biases that result in missed genotype calls. Here we present data on the use of a second complementary SNP genotype clustering algorithm. The algorithm was originally designed for individual fluorescent SNP genotyping assays, and has been optimized to permit th...
Conformational study and reassessment of the vibrational assignments for Norspermidine
Silva, T. M.; Fiuza, S. M.; Marques, M. P. M.; Batista de Carvalho, L. A. E.; Amado, A. M.
2016-03-01
The present study presents and discusses the conformational preferences of Norspermidine (NSpd). The effects of varying the dielectric constant on the conformational preferences are discussed, with a view to infer which conformation will correspond to the most stable in the pure condensed liquid phase. Within the same context, a set of NSpd-NH3 molecular adducts were simulated in order to determine the relevance of intermolecular hydrogen bonding on the overall stability and relative positioning of the respective vibrational frequencies. The calculations presently performed allowed a reassessment of the vibrational assignments for NSpd. A full assignment of the NSpd vibrational spectra is presented, with special emphasis being given to the vibrational modes that proved to be most affected by hydrogen bonding. The various inconsistencies of a prior study found in the literature were identified and rectified. An incorrect description of the molecular structure and/or electronic distribution will lead to erroneous forecasts of the vibrational frequencies, culminating in inaccurate assignments.
Assigning on-ramp flows to maximize highway capacity
Wang, Qiao-Ming; Jiang, Rui; Sun, Xiao-Yan; Wang, Bing-Hong
2009-09-01
In this paper, we study the capacity of a highway with two on-ramps by using a cellular automata traffic flow model. We investigate how to improve the system capacity by assigning traffic flow to the two ramps. The system phase diagram is presented and different regions are classified. It is shown that in region I, in which both ramps are in free flow and the main road upstream of the ramps is in congestion, assigning a higher proportion of the demand to the upstream on-ramp could improve the overall flow, which is consistent with previous studies. This is explained through studying the spatiotemporal patterns and analytical investigations. In contrast, optimal assignment has not been observed in other regions. We point out that our result is robust and model independent under certain conditions.
Lexical stress assignment as a problem of probabilistic inference.
Jouravlev, Olessia; Lupker, Stephen J
2015-10-01
A new conceptualization of the process of stress assignment, couched in the principles of (Bayesian) probabilistic inference, is introduced in this paper. According to this approach, in deciding where to place stress in a polysyllabic word, a reader estimates the posterior probabilities of alternative stress patterns. This estimation is accomplished by adjusting a prior belief about the likelihoods of alternative stress patterns (derived from experience with the distribution of stress patterns in the language) by using lexical and non-lexical sources of evidence for stress derived from the orthographic input. The proposed theoretical framework was used to compute probabilities of stress patterns for Russian disyllabic words and nonwords which were then compared with the performance of readers. The results showed that the estimated probabilities of stress patterns were reflective of actual stress assignment performance and of naming latencies, suggesting that the mechanisms that are involved in the process of stress assignment might indeed be inferentially-based. PMID:25636917
The ICAP (Interactive Course Assignment Pages Publishing System
Directory of Open Access Journals (Sweden)
Kim Griggs
2008-03-01
Full Text Available The ICAP publishing system is an open source custom content management system that enables librarians to easily and quickly create and manage library help pages for course assignments (ICAPs, without requiring knowledge of HTML or other web technologies. The system's unique features include an emphasis on collaboration and content reuse and an easy-to-use interface that includes in-line help, simple forms and drag and drop functionality. The system generates dynamic, attractive course assignment pages that blend Web 2.0 features with traditional library resources, and makes the pages easier to find by providing a central web page for the course assignment pages. As of December 2007, the code is available as free, open-source software under the GNU General Public License.
Task Assignment Heuristics for Parallel and Distributed CFD Applications
Lopez-Benitez, Noe; Djomehri, M. Jahed; Biswas, Rupak
2003-01-01
This paper proposes a task graph (TG) model to represent a single discrete step of multi-block overset grid computational fluid dynamics (CFD) applications. The TG model is then used to not only balance the computational workload across the overset grids but also to reduce inter-grid communication costs. We have developed a set of task assignment heuristics based on the constraints inherent in this class of CFD problems. Two basic assignments, the smallest task first (STF) and the largest task first (LTF), are first presented. They are then systematically costs. To predict the performance of the proposed task assignment heuristics, extensive performance evaluations are conducted on a synthetic TG with tasks defined in terms of the number of grid points in predetermined overlapping grids. A TG derived from a realistic problem with eight million grid points is also used as a test case.
Efficient Fault-Tolerant Event Query Algorithm in Distributed Wireless Sensor Networks
Rongbo Zhu
2010-01-01
To overcome the faulty data query problem to improve the accuracy of data query, an efficient fault-tolerant event query algorithm (FTEQ) is proposed, which takes the short-term and long-term spatial and temporal similarities between sensors and environment into considerations. An imprecise and missing data correction algorithm based on Kalman filter is proposed to correct fault sensing data, and a score rank algorithm also is proposed to assign each sensor an appropriate value to reflect the...
Probabilistic validation of protein NMR chemical shift assignments
International Nuclear Information System (INIS)
Data validation plays an important role in ensuring the reliability and reproducibility of studies. NMR investigations of the functional properties, dynamics, chemical kinetics, and structures of proteins depend critically on the correctness of chemical shift assignments. We present a novel probabilistic method named ARECA for validating chemical shift assignments that relies on the nuclear Overhauser effect data. ARECA has been evaluated through its application to 26 case studies and has been shown to be complementary to, and usually more reliable than, approaches based on chemical shift databases. ARECA is available online at http://areca.nmrfam.wisc.edu/ http://areca.nmrfam.wisc.edu/
Probabilistic validation of protein NMR chemical shift assignments
Energy Technology Data Exchange (ETDEWEB)
Dashti, Hesam [University of Wisconsin-Madison, Graduate Program in Biophysics, Biochemistry Department (United States); Tonelli, Marco; Lee, Woonghee; Westler, William M.; Cornilescu, Gabriel [University of Wisconsin-Madison, Biochemistry Department, National Magnetic Resonance Facility at Madison (United States); Ulrich, Eldon L. [University of Wisconsin-Madison, BioMagResBank, Biochemistry Department (United States); Markley, John L., E-mail: markley@nmrfam.wisc.edu, E-mail: jmarkley@wisc.edu [University of Wisconsin-Madison, Biochemistry Department, National Magnetic Resonance Facility at Madison (United States)
2016-01-15
Data validation plays an important role in ensuring the reliability and reproducibility of studies. NMR investigations of the functional properties, dynamics, chemical kinetics, and structures of proteins depend critically on the correctness of chemical shift assignments. We present a novel probabilistic method named ARECA for validating chemical shift assignments that relies on the nuclear Overhauser effect data. ARECA has been evaluated through its application to 26 case studies and has been shown to be complementary to, and usually more reliable than, approaches based on chemical shift databases. ARECA is available online at http://areca.nmrfam.wisc.edu/ http://areca.nmrfam.wisc.edu/.
Automated Negotiation for Resource Assignment in Wireless Surveillance Sensor Networks
Directory of Open Access Journals (Sweden)
Enrique de la Hoz
2015-11-01
Full Text Available Due to the low cost of CMOS IP-based cameras, wireless surveillance sensor networks have emerged as a new application of sensor networks able to monitor public or private areas or even country borders. Since these networks are bandwidth intensive and the radioelectric spectrum is limited, especially in unlicensed bands, it is mandatory to assign frequency channels in a smart manner. In this work, we propose the application of automated negotiation techniques for frequency assignment. Results show that these techniques are very suitable for the problem, being able to obtain the best solutions among the techniques with which we have compared them.
Zhou, Xiaojun; Gui, Weihua
2012-01-01
In terms of the concepts of state and state transition, a new heuristic random search algorithm named state transition algorithm is proposed. For continuous function optimization problems, four special transformation operators called rotation, translation, expansion and axesion are designed. Adjusting measures of the transformations are mainly studied to keep the balance of exploration and exploitation. Convergence analysis is also discussed about the algorithm based on random search method. In the meanwhile, to strengthen the search ability in high dimensional space, communication strategy is introduced into the basic algorithm and intermittent exchange is presented to prevent premature convergence. Finally, experiments are carried out for the algorithms. With 10 common benchmark unconstrained continuous functions used to test the performance, the results show that state transition algorithms are promising algorithms due to their good global search capability and convergence property when compared with some ...
Robust attitude control design for spacecraft under assigned velocity and control constraints.
Hu, Qinglei; Li, Bo; Zhang, Youmin
2013-07-01
A novel robust nonlinear control design under the constraints of assigned velocity and actuator torque is investigated for attitude stabilization of a rigid spacecraft. More specifically, a nonlinear feedback control is firstly developed by explicitly taking into account the constraints on individual angular velocity components as well as external disturbances. Considering further the actuator misalignments and magnitude deviation, a modified robust least-squares based control allocator is employed to deal with the problem of distributing the previously designed three-axis moments over the available actuators, in which the focus of this control allocation is to find the optimal control vector of actuators by minimizing the worst-case residual error using programming algorithms. The attitude control performance using the controller structure is evaluated through a numerical example. PMID:23618744
Power Assigning Method for Increasing the Number of Users in Time-spreading Optical CDMA Systems
Salehi, Mohammad Reza; Abiri, Ebrahim; Kazemi, Keyvan; Dezfouli, Mehran
2011-04-01
In this paper, a method for increasing the number of supportable users in a time-spreading Optical code division multiple access (OCDMA) system is proposed. In the presented technique, a unique codeword is assigned to a couple of users instead of just one. Different optical powers are employed for such users in order to distinguish them from each other. Other methods use the frequency or the polarization of the optical signals as an additional coding dimension to increase the number of codewords and hence the number of users in the network. It is proposed to employ nonlinear optical regenerators for separating optical pulses with different powers. A comprehensive design algorithm for such regenerators is presented. In order to evaluate the performance of the designed regenerators a TS-OCDMA system is simulated using OptiSystem software. Results indicate an error free transmission in the system employing the proposed technique.
An adaptive grid algorithm for 3-D GIS landform optimization based on improved ant algorithm
Wu, Chenhan; Meng, Lingkui; Deng, Shijun
2005-07-01
The key technique of 3-D GIS is to realize quick and high-quality 3-D visualization, in which 3-D roaming system based on landform plays an important role. However how to increase efficiency of 3-D roaming engine and process a large amount of landform data is a key problem in 3-D landform roaming system and improper process of the problem would result in tremendous consumption of system resources. Therefore it has become the key of 3-D roaming system design that how to realize high-speed process of distributed data for landform DEM (Digital Elevation Model) and high-speed distributed modulation of various 3-D landform data resources. In the paper we improved the basic ant algorithm and designed the modulation strategy of 3-D GIS landform resources based on the improved ant algorithm. By initially hypothetic road weights σi , the change of the information factors in the original algorithm would transform from ˜τj to ∆τj+σi and the weights was decided by 3-D computative capacity of various nodes in network environment. So during the course of initial phase of task assignment, increasing the resource information factors of high task-accomplishing rate and decreasing ones of low accomplishing rate would make load accomplishing rate approach the same value as quickly as possible, then in the later process of task assignment, the load balanced ability of the system was further improved. Experimental results show by improving ant algorithm, our system not only decreases many disadvantage of the traditional ant algorithm, but also like ants looking for food effectively distributes the complicated landform algorithm to many computers to process cooperatively and gains a satisfying search result.
Optimal Register Assignment with Minimum-Path Delay Compensation for Variation-Aware Datapaths
Inoue, Keisuke; Kaneko, Mineo; Iwagaki, Tsuyoshi
For recent and future nanometer-technology VLSIs, static and dynamic delay variations become a serious problem. In many cases, the hold constraint, as well as the setup constraint, becomes critical for latching a correct signal under delay variations. This paper treats the hold constraint in a datapath circuit, and discusses a register assignment in high level synthesis considering delay variations. Our approach to ensure the hold constraint under delay variations is to enlarge the minimum-path delay between registers, which is called minimum-path delay compensation (MDC) in this paper. MDC can be done by inserting delay elements mainly in non-critical paths of a functional unit (FU). One of our contributions is to show that the minimization of the number of minimum-path delay compensated FUs is NP-hard in general, and it is in the class P if the number of FUs is a constant. A polynomial time algorithm for the latter is also shown in this paper. In addition, an integer linear programming (ILP) formulation is also presented. The proposed method generates a datapath having (1) robustness against delay variations, which is ensured partly by MDC technique and partly by SRV-based register assignment, and (2) the minimum possible numbers of MDCs and registers.
GPU-Based Heuristic Solver for Linear Sum Assignment Problems Under Real-time Constraints
Roverso, Roberto; El-Beltagy, Mohammed; El-Ansary, Sameh
2011-01-01
In this paper we modify a fast heuristic solver for the Linear Sum Assignment Problem (LSAP) for use on Graphical Processing Units (GPUs). The motivating scenario is an industrial application for P2P live streaming that is moderated by a central node which is periodically solving LSAP instances for assigning peers to one another. The central node needs to handle LSAP instances involving thousands of peers in as near to real-time as possible. Our findings are generic enough to be applied in other contexts. Our main result is a parallel version of a heuristic algorithm called Deep Greedy Switching (DGS) on GPUs using the CUDA programming language. DGS sacrifices absolute optimality in favor of low computation time and was designed as an alternative to classical LSAP solvers such as the Hungarian and auctioning methods. The contribution of the paper is threefold: First, we present the process of trial and error we went through, in the hope that our experience will be beneficial to adopters of GPU programming for...
2012-07-23
... BOARD Further Amendment to Memorandum Describing Authority and Assigned Responsibilities of the General... Relations Board is amending the memorandum describing the authority and assigned responsibilities of the... amendment to Board memorandum describing the authority and assigned responsibilities of the General...
The Complexity of Approximately Counting Stable Roommate Assignments
Chebolu, Prasad; Martin, Russell
2010-01-01
We investigate the complexity of approximately counting stable roommate assignments in two models: (i) the $k$-attribute model, in which the preference lists are determined by dot products of "preference vectors" with "attribute vectors" and (ii) the $k$-Euclidean model, in which the preference lists are determined by the closeness of the "positions" of the people to their "preferred positions". Exactly counting the number of assignments is #P-complete, since Irving and Leather demonstrated #P-completeness for the special case of the stable marriage problem. We show that counting the number of stable roommate assignments in the $k$-attribute model ($k \\geq 4$) and the $3$-Euclidean model($k \\geq 3$) is interreducible, in an approximation-preserving sense, with counting independent sets (of all sizes) (#IS) in a graph, or counting the number of satisfying assignments of a Boolean formula (#SAT). This means that there can be no FPRAS for any of these problems unless NP=RP. As a consequence, we infer that there ...
Single Assignment C (SAC): High Productivity meets High Performance
C. Grelck
2012-01-01
We present the ins and outs of the purely functional, data parallel programming language SaC (Single Assignment C). SaC defines state- and side-effect-free semantics on top of a syntax resembling that of imperative languages like C/C++/C# or Java: functional programming with curly brackets. In contr
Using Clouds for MapReduce Measurement Assignments
Rabkin, Ariel; Reiss, Charles; Katz, Randy; Patterson, David
2013-01-01
We describe our experiences teaching MapReduce in a large undergraduate lecture course using public cloud services and the standard Hadoop API. Using the standard API, students directly experienced the quality of industrial big-data tools. Using the cloud, every student could carry out scalability benchmarking assignments on realistic hardware,…
31 CFR 306.43 - Voidance of assignments.
2010-07-01
... 31 Money and Finance: Treasury 2 2010-07-01 2010-07-01 false Voidance of assignments. 306.43 Section 306.43 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) FISCAL... affidavit or affidavits should be submitted for consideration explaining why a disclaimer cannot be...
Wavelength and fiber assignment problems on avionic networks
DEFF Research Database (Denmark)
Zhang, Jiang; An, Yi; Berger, Michael Stübert; Clausen, Anders
This paper solves the wavelength and fiber assignment problems with systems' isolation requirements on the avionic ring networks. The experiment results give a general glace of the numbers of the wavelengths and fibers are required under certain scale of networks. At the beginning of increasing...
Semiclassical Assignment of the Vibrational Spectrum of N2O
Waalkens, Holger; Jung, Christof; Taylor, Howard S.
2002-01-01
The vibrational spectrum of N2O as given by an effective spectroscopic Hamiltonian based on the existence of a superpolyad number is analyzed and assigned in terms of classical motions. The effective Hamiltonian includes a large number of resonances of which only one is dominant for low and intermed
A Writing Assignment/A Way of Life.
Martin, Bill
2003-01-01
Explains a writing assignment called "occasional paper," a brief written reflection that is read aloud and discussed but not turned in. Notes that it is important that these papers be easy to write. Contends that since adolescents experience nearly everything as personal, the occasional paper offers them an entry into thinking that is abstract and…
Bargaining Theory over Opportunity Assignments and the Egalitarian Solution
Xu, Yongsheng; Yoshihara, Naoki
2009-01-01
This paper discusses issues of axiomatic bargaining problems over opportunity assignments. The fair arbitrator uses the principle of "equal opportunity" for all players to make the recommendation on resource allocations. A framework in such a context is developed and the egalitarian solution to standard bargaining problems is reformulated and axiomatically characterized.
Understanding and Supporting the Career Implications of International Assignments
Collings, David G.; Doherty, Noeleen; Luethy, Madeleine; Osborn, Derek
2011-01-01
International assignments represent an important form of migration in the global economy. In contrast to most other migrants, international assignees enjoy a relatively privileged position in the labor market. Authored by a diverse team of academics and practitioners, this paper draws on insights from empirical research and unpublished examples…
45 CFR 302.50 - Assignment of rights to support.
2010-10-01
... 45 Public Welfare 2 2010-10-01 2010-10-01 false Assignment of rights to support. 302.50 Section 302.50 Public Welfare Regulations Relating to Public Welfare OFFICE OF CHILD SUPPORT ENFORCEMENT (CHILD SUPPORT ENFORCEMENT PROGRAM), ADMINISTRATION FOR CHILDREN AND FAMILIES, DEPARTMENT OF HEALTH AND HUMAN SERVICES STATE PLAN REQUIREMENTS §...
An optimal query assignment for wireless sensor networks
Mitici, Mihaela; Onderwater, Martijn; Graaf, de Maurits; Ommeren, van Jan-Kees; Dijk, van Nico; Goseling, Jasper
2012-01-01
With the increased use of large-scale real-time embedded sensor networks, new control mechanisms are needed to avoid congestion and meet required Quality of Service (QoS) levels. In this paper, we propose a Markov Decision Problem (MDP) to prescribe an optimal query assignment strategy that achieves
A Competitive and Experiential Assignment in Search Engine Optimization Strategy
Clarke, Theresa B.; Clarke, Irvine, III
2014-01-01
Despite an increase in ad spending and demand for employees with expertise in search engine optimization (SEO), methods for teaching this important marketing strategy have received little coverage in the literature. Using Bloom's cognitive goals hierarchy as a framework, this experiential assignment provides a process for educators who may be…
Concept Maps as Cognitive Visualizations of Writing Assignments
Villalon, Jorge; Calvo, Rafael A.
2011-01-01
Writing assignments are ubiquitous in higher education. Writing develops not only communication skills, but also higher-level cognitive processes that facilitate deep learning. Cognitive visualizations, such as concept maps, can also be used as part of learning activities including as a form of scaffolding, or to trigger reflection by making…
A Randomized Experiment Comparing Random and Cutoff-Based Assignment
Shadish, William R.; Galindo, Rodolfo; Wong, Vivian C.; Steiner, Peter M.; Cook, Thomas D.
2011-01-01
In this article, we review past studies comparing randomized experiments to regression discontinuity designs, mostly finding similar results, but with significant exceptions. The latter might be due to potential confounds of study characteristics with assignment method or with failure to estimate the same parameter over methods. In this study, we…
Developing Team Skills through a Collaborative Writing Assignment
Thomas, Theda Ann
2014-01-01
Employers want students who are able to work effectively as members of a team, and expect universities to develop this ability in their graduates. This paper proposes a framework for a collaborative writing assignment that specifically develops students' ability to work in teams. The framework has been tested using two iterations of an action…
An Improved Approach to Solution of the Faculty Assignment Problem.
Yang, Chin W.
1989-01-01
Examined is the problem of assigning faculty members to teach various courses in an accounting department. Based on selected evaluation information, a zero-one integer programing model was implemented. This approach utilizes readily available data and takes into consideration the learning curve phenomenon, various competing needs, and…
Comparison of Categorical Assignments of the BSRI and the PAQ.
Gaa, John P.; Liberman, Dov
The degree of agreement between the Bem Sex Role Inventory (BSRI) and the Personality Attributes Questionnaire (PAQ) in assigning sex role categories was investigated by administering both instruments to undergraduate education majors. As a result of scoring, subjects were classified as androgynous, masculine, feminine, or undifferentiated. It was…
42 CFR 435.610 - Assignment of rights to benefits.
2010-10-01
... paternity and in obtaining medical support and payments, unless the individual establishes good cause for not cooperating, and except for individuals described in section 1902 (1)(1)(A) of the Act (poverty... cause for not cooperating. (b) The requirements for assignment of rights must be applied uniformly...
15 CFR 2011.208 - Paperwork Reduction Act assigned number.
2010-01-01
... 15 Commerce and Foreign Trade 3 2010-01-01 2010-01-01 false Paperwork Reduction Act assigned number. 2011.208 Section 2011.208 Commerce and Foreign Trade Regulations Relating to Foreign Trade Agreements OFFICE OF THE UNITED STATES TRADE REPRESENTATIVE ALLOCATION OF TARIFF-RATE QUOTA ON IMPORTED SUGARS, SYRUPS AND MOLASSES Specialty Sugar...
PRECONDITIONS OF ORIGIN, ESSENCE AND ASSIGNMENT OF STRATEGIC MANAGERIAL ACCOUNTING
Boiko, I.
2010-01-01
The article is devoted to the research of preconditions and necessity of creation strategic managerial accounting in the accounting system of enterprise. There are investigated economic essence and assignment of strategic managerial accounting and substantiated its importance for making strategic decisions on an enterprise.
20 CFR 422.607 - Limited reopening of assignments.
2010-04-01
... 20 Employees' Benefits 2 2010-04-01 2010-04-01 false Limited reopening of assignments. 422.607 Section 422.607 Employees' Benefits SOCIAL SECURITY ADMINISTRATION ORGANIZATION AND PROCEDURES Administrative Review Process Under the Coal Industry Retiree Health Benefit Act of 1992 § 422.607...
Sources of Information for Stress Assignment in Reading Greek
Protopapas, Athanassios; Gerakaki, Svetlana; Alexandri, Stella
2007-01-01
To assign lexical stress when reading, the Greek reader can potentially rely on lexical information (knowledge of the word), visual-orthographic information (processing of the written diacritic), or a default metrical strategy (penultimate stress pattern). Previous studies with secondary education children have shown strong lexical effects on…
Design of multivariable feedback control systems via spectral assignment
Mielke, R. R.; Tung, L. J.; Marefat, M.
1983-01-01
The applicability of spectral assignment techniques to the design of multivariable feedback control systems was investigated. A fractional representation design procedure for unstable plants is presented and illustrated with an example. A computer aided design software package implementing eigenvalue/eigenvector design procedures is described. A design example which illustrates the use of the program is explained.
Augmenting superpopulation capture-recapture models with population assignment data
Wen, Zhi; Pollock, Kenneth; Nichols, James; Waser, Peter
2011-01-01
Ecologists applying capture-recapture models to animal populations sometimes have access to additional information about individuals' populations of origin (e.g., information about genetics, stable isotopes, etc.). Tests that assign an individual's genotype to its most likely source population are increasingly used. Here we show how to augment a superpopulation capture-recapture model with such information. We consider a single superpopulation model without age structure, and split each entry probability into separate components due to births in situ and immigration. We show that it is possible to estimate these two probabilities separately. We first consider the case of perfect information about population of origin, where we can distinguish individuals born in situ from immigrants with certainty. Then we consider the more realistic case of imperfect information, where we use genetic or other information to assign probabilities to each individual's origin as in situ or outside the population. We use a resampling approach to impute the true population of origin from imperfect assignment information. The integration of data on population of origin with capture-recapture data allows us to determine the contributions of immigration and in situ reproduction to the growth of the population, an issue of importance to ecologists. We illustrate our new models with capture-recapture and genetic assignment data from a population of banner-tailed kangaroo rats Dipodomys spectabilis in Arizona.
Undergraduates Improve upon Published Crystal Structure in Class Assignment
Horowitz, Scott; Koldewey, Philipp; Bardwell, James C.
2014-01-01
Recently, 57 undergraduate students at the University of Michigan were assigned the task of solving a crystal structure, given only the electron density map of a 1.3 Å crystal structure from the electron density server, and the position of the N-terminal amino acid. To test their knowledge of amino acid chemistry, the students were not given the…
37 CFR 1.46 - Assigned inventions and patents.
2010-07-01
... 37 Patents, Trademarks, and Copyrights 1 2010-07-01 2010-07-01 false Assigned inventions and patents. 1.46 Section 1.46 Patents, Trademarks, and Copyrights UNITED STATES PATENT AND TRADEMARK OFFICE, DEPARTMENT OF COMMERCE GENERAL RULES OF PRACTICE IN PATENT CASES National Processing Provisions Who May...
Integrating Video Documentary into the Classroom: A Community Assessment Assignment
Levinson, Samantha G.; Caldwell, Keith; Petracchi, Helen E.; Wexler, Sandra; Engel, Rafael
2016-01-01
Community assessment is a strategy commonly taught to social work students to identify a community's strengths and challenges. This article describes the value of using video documentary as part of a community assessment assignment. We identify the advantages of using video documentary in the assessment process and the reporting of findings. We…
Assigning Main Orientation to an EOH Descriptor on Multispectral Images
Directory of Open Access Journals (Sweden)
Yong Li
2015-07-01
Full Text Available This paper proposes an approach to compute an EOH (edge-oriented histogram descriptor with main orientation. EOH has a better matching ability than SIFT (scale-invariant feature transform on multispectral images, but does not assign a main orientation to keypoints. Alternatively, it tends to assign the same main orientation to every keypoint, e.g., zero degrees. This limits EOH to matching keypoints between images of translation misalignment only. Observing this limitation, we propose assigning to keypoints the main orientation that is computed with PIIFD (partial intensity invariant feature descriptor. In the proposed method, SIFT keypoints are detected from images as the extrema of difference of Gaussians, and every keypoint is assigned to the main orientation computed with PIIFD. Then, EOH is computed for every keypoint with respect to its main orientation. In addition, an implementation variant is proposed for fast computation of the EOH descriptor. Experimental results show that the proposed approach performs more robustly than the original EOH on image pairs that have a rotation misalignment.
A Fast and Exact Algorithm for the Exemplar Breakpoint Distance.
Shao, Mingfu; Moret, Bernard M E
2016-05-01
A fundamental problem in comparative genomics is to compute the distance between two genomes. For two genomes without duplicate genes, we can easily compute a variety of distance measures in linear time, but the problem is NP-hard under most models when genomes contain duplicate genes. Sankoff proposed the use of exemplars to tackle the problem of duplicate genes and gene families: each gene family is represented by a single gene (the exemplar for that family), chosen so as to optimize some metric. Unfortunately, choosing exemplars is itself an NP-hard problem. In this article, we propose a very fast and exact algorithm to compute the exemplar breakpoint distance, based on new insights in the underlying structure of genome rearrangements and exemplars. We evaluate the performance of our algorithm on simulation data and compare its performance to the best effort to date (a divide-and-conquer approach), showing that our algorithm runs much faster and scales much better. We also devise a new algorithm for the intermediate breakpoint distance problem, which can then be applied to assign orthologs. We compare our algorithm with the state-of-the-art method MSOAR by assigning orthologs among five well annotated mammalian genomes, showing that our algorithm runs much faster and is slightly more accurate than MSOAR. PMID:26953781
Lin, Yi-Kuei; Yeh, Cheng-Ta
2013-03-01
Many real-life systems, such as computer systems, manufacturing systems and logistics systems, are modelled as stochastic-flow networks (SFNs) to evaluate network reliability. Here, network reliability, defined as the probability that the network successfully transmits d units of data/commodity from an origin to a destination, is a performance indicator of the systems. Network reliability maximization is a particular objective, but is costly for many system supervisors. This article solves the multi-objective problem of reliability maximization and cost minimization by finding the optimal component assignment for SFN, in which a set of multi-state components is ready to be assigned to the network. A two-stage approach integrating Non-dominated Sorting Genetic Algorithm II and simple additive weighting are proposed to solve this problem, where network reliability is evaluated in terms of minimal paths and recursive sum of disjoint products. Several practical examples related to computer networks are utilized to demonstrate the proposed approach.
Directory of Open Access Journals (Sweden)
Shilpa S. Patil
2015-09-01
Full Text Available In wavelength division multiplexed all optical networks; lightpath establishes a connection between sending and receiving nodes bypassing the electronic processing at intermediate nodes. One of the prime objectives of Routing and Wavelength Assignment (RWA problem is to maximize the number of connections efficiently by choosing the best routes. Although there are several algorithms available, improving the blocking performance in optical networks and finding optimal solutions for RWA problem has still remained a challenging issue. Wavelength conversion can be helpful in restricting the problem of wavelength continuity constraint but it increases complexity in the network. In this paper, we propose new weight dependent routing and wavelength assignment strategy for all optical networks without use of wavelength converters. Proposed weight function reduces blocking probability significantly, improving the network performance at various load conditions. Further, due to absence of wavelength converters, the cost and complexity of network reduces. Results show that the proposed strategy performs better than earlier reported methods.
Jang, Richard
2012-03-21
Background: Chemical shift mapping is an important technique in NMR-based drug screening for identifying the atoms of a target protein that potentially bind to a drug molecule upon the molecule\\'s introduction in increasing concentrations. The goal is to obtain a mapping of peaks with known residue assignment from the reference spectrum of the unbound protein to peaks with unknown assignment in the target spectrum of the bound protein. Although a series of perturbed spectra help to trace a path from reference peaks to target peaks, a one-to-one mapping generally is not possible, especially for large proteins, due to errors, such as noise peaks, missing peaks, missing but then reappearing, overlapped, and new peaks not associated with any peaks in the reference. Due to these difficulties, the mapping is typically done manually or semi-automatically, which is not efficient for high-throughput drug screening.Results: We present PeakWalker, a novel peak walking algorithm for fast-exchange systems that models the errors explicitly and performs many-to-one mapping. On the proteins: hBclXL, UbcH5B, and histone H1, it achieves an average accuracy of over 95% with less than 1.5 residues predicted per target peak. Given these mappings as input, we present PeakAssigner, a novel combined structure-based backbone resonance and NOE assignment algorithm that uses just 15N-NOESY, while avoiding TOCSY experiments and 13C-labeling, to resolve the ambiguities for a one-to-one mapping. On the three proteins, it achieves an average accuracy of 94% or better.Conclusions: Our mathematical programming approach for modeling chemical shift mapping as a graph problem, while modeling the errors directly, is potentially a time- and cost-effective first step for high-throughput drug screening based on limited NMR data and homologous 3D structures. 2012 Jang et al.; licensee BioMed Central Ltd.
Jang, Richard
2011-01-01
Chemical shift mapping is an important technique in NMRbased drug screening for identifying the atoms of a target protein that potentially bind to a drug molecule upon the molecule\\'s introduction in increasing concentrations. The goal is to obtain a mapping of peaks with known residue assignment from the reference spectrum of the unbound protein to peaks with unknown assignment in the target spectrum of the bound protein. Although a series of perturbed spectra help to trace a path from reference peaks to target peaks, a one-to-one mapping generally is not possible, especially for large proteins, due to errors, such as noise peaks, missing peaks, missing but then reappearing, overlapped, and new peaks not associated with any peaks in the reference. Due to these difficulties, the mapping is typically done manually or semi-automatically. However, automated methods are necessary for high-throughput drug screening. We present PeakWalker, a novel peak walking algorithm for fast-exchange systems that models the errors explicitly and performs many-to-one mapping. On the proteins: hBclXL, UbcH5B, and histone H1, it achieves an average accuracy of over 95% with less than 1.5 residues predicted per target peak. Given these mappings as input, we present PeakAssigner, a novel combined structure-based backbone resonance and NOE assignment algorithm that uses just 15N-NOESY, while avoiding TOCSY experiments and 13C- labeling, to resolve the ambiguities for a one-toone mapping. On the three proteins, it achieves an average accuracy of 94% or better. Copyright © 2011 ACM.
Directory of Open Access Journals (Sweden)
Reyha Verma
2015-12-01
Full Text Available Sorting algorithms find its application in many practical fields of Computer Science. Efficient solving of sorting problem has attracted a great deal of research as it optimizes other algorithms also. The main factor which is taken into consideration while determining the efficiency of a sorting algorithm is the time complexity. Mostly the execution time of algorithms is investigated and compared for analyzing time complexity. This paper presents a comparative analysis of deterministic sorting algorithms. Time complexity of six different algorithms namely, Selection sort, Bubble sort, Insertion sort, Quicksort, Heapsort and Mergesort is determined in terms of number of comparisons, swaps and assignment operations in addition to average execution time. Also, the performance of these algorithms on fully and almost sorted lists was also analyzed. The study indicates that determining the operation’s count is essential for analyzing time complexity especially when algorithms are theoretically analyzed.
A LOAD BALANCING MODEL USING FIREFLY ALGORITHM IN CLOUD COMPUTING
Directory of Open Access Journals (Sweden)
A. Paulin Florence
2014-01-01
Full Text Available Cloud computing is a model that points at streamlining the on-demand provisioning of software, hardware and data as services and providing end-users with flexible and scalable services accessible through the Internet. The main objective of the proposed approach is to maximize the resource utilization and provide a good balanced load among all the resources in cloud servers. Initially, a load model of every resource will be derived based on several factors such as, memory usage, processing time and access rate. Based on the newly derived load index, the current load will be computed for all the resources shared in virtual machine of cloud servers. Once the load index is computed for all the resources, load balancing operation will be initiated to effectively use the resources dynamically with the process of assigning resources to the corresponding node to reduce the load value. So, assigning of resources to proper nodes is an optimal distribution problem so that many optimization algorithms such as genetic algorithm and modified genetic algorithm are utilized for load balancing. These algorithms are not much effective in providing the neighbour solutions since it does not overcome exploration and exploration problem. So, utilizing the effective optimization procedure instead of genetic algorithm can lead to better load balancing since it is a traditional and old algorithm. Accordingly, I have planned to utilize a recent optimization algorithm, called firefly algorithm to do the load balancing operation in our proposed work. At first, the index table will be maintained by considering the availability of virtual servers and sequence of request. Then, load index will be computed based on the newly derived formulae. Based on load index, load balancing operation will be carried out using firefly algorithm. The performance analysis produced expected results and thus proved the proposed approach is efficient in optimizing schedules by balancing the
Deductive Algorithmic Knowledge
Pucella, Riccardo
2004-01-01
The framework of algorithmic knowledge assumes that agents use algorithms to compute the facts they explicitly know. In many cases of interest, a deductive system, rather than a particular algorithm, captures the formal reasoning used by the agents to compute what they explicitly know. We introduce a logic for reasoning about both implicit and explicit knowledge with the latter defined with respect to a deductive system formalizing a logical theory for agents. The highly structured nature of ...
Fingerprint Feature Extraction Algorithm
Directory of Open Access Journals (Sweden)
Mehala. G
2014-03-01
Full Text Available The goal of this paper is to design an efficient Fingerprint Feature Extraction (FFE algorithm to extract the fingerprint features for Automatic Fingerprint Identification Systems (AFIS. FFE algorithm, consists of two major subdivisions, Fingerprint image preprocessing, Fingerprint image postprocessing. A few of the challenges presented in an earlier are, consequently addressed, in this paper. The proposed algorithm is able to enhance the fingerprint image and also extracting true minutiae.
Recursive forgetting algorithms
DEFF Research Database (Denmark)
Parkum, Jens; Poulsen, Niels Kjølstad; Holst, Jan
1992-01-01
In the first part of the paper, a general forgetting algorithm is formulated and analysed. It contains most existing forgetting schemes as special cases. Conditions are given ensuring that the basic convergence properties will hold. In the second part of the paper, the results are applied to a...... specific algorithm with selective forgetting. Here, the forgetting is non-uniform in time and space. The theoretical analysis is supported by a simulation example demonstrating the practical performance of this algorithm...
Fingerprint Feature Extraction Algorithm
Mehala. G
2014-01-01
The goal of this paper is to design an efficient Fingerprint Feature Extraction (FFE) algorithm to extract the fingerprint features for Automatic Fingerprint Identification Systems (AFIS). FFE algorithm, consists of two major subdivisions, Fingerprint image preprocessing, Fingerprint image postprocessing. A few of the challenges presented in an earlier are, consequently addressed, in this paper. The proposed algorithm is able to enhance the fingerprint image and also extractin...
Integer factorization algorithms
Bogataj, Polona
2011-01-01
The decomposition of a natural number into a product of prime numbers is called factorization. The main problem with factorization is the fact that there is no known efficient algorithm which would factor a given natural number n in polynomial time. The closest equivalent to such an algorithm is Shor's algorithm for quantum computers, which is still not practically applicable. The difficulties with factorization form the basis for modern cryptosystems—the most renowned among them is the RSA a...
Introduction to Evolutionary Algorithms
Yu, Xinjie
2010-01-01
Evolutionary algorithms (EAs) are becoming increasingly attractive for researchers from various disciplines, such as operations research, computer science, industrial engineering, electrical engineering, social science, economics, etc. This book presents an insightful, comprehensive, and up-to-date treatment of EAs, such as genetic algorithms, differential evolution, evolution strategy, constraint optimization, multimodal optimization, multiobjective optimization, combinatorial optimization, evolvable hardware, estimation of distribution algorithms, ant colony optimization, particle swarm opti
Recursive forgetting algorithms
DEFF Research Database (Denmark)
Parkum, Jens; Poulsen, Niels Kjølstad; Holst, Jan
1992-01-01
In the first part of the paper, a general forgetting algorithm is formulated and analysed. It contains most existing forgetting schemes as special cases. Conditions are given ensuring that the basic convergence properties will hold. In the second part of the paper, the results are applied...... to a specific algorithm with selective forgetting. Here, the forgetting is non-uniform in time and space. The theoretical analysis is supported by a simulation example demonstrating the practical performance of this algorithm...
Spectral Decomposition Algorithm (SDA)
National Aeronautics and Space Administration — Spectral Decomposition Algorithm (SDA) is an unsupervised feature extraction technique similar to PCA that was developed to better distinguish spectral features in...
Explaining algorithms using metaphors
Forišek, Michal
2013-01-01
There is a significant difference between designing a new algorithm, proving its correctness, and teaching it to an audience. When teaching algorithms, the teacher's main goal should be to convey the underlying ideas and to help the students form correct mental models related to the algorithm. This process can often be facilitated by using suitable metaphors. This work provides a set of novel metaphors identified and developed as suitable tools for teaching many of the 'classic textbook' algorithms taught in undergraduate courses worldwide. Each chapter provides exercises and didactic notes fo
Evolutionary Algorithm Definition
Directory of Open Access Journals (Sweden)
Nada M.A. AL-Salami
2009-01-01
Full Text Available Problem statement: Most resent evolutionary algorithms work under weak theoretical basis and thus, they are computationally expensive. Approach: This study discussed the use of new evolutionary algorithm for automatic programming, based on theoretical definitions of program behaviors. Evolutionary process adapted fixed and self-organized input-output specification of the problem, to evolve good finite state machine that efficiently satisfies these specifications. Results: The proposed algorithm enhanced evolutionary process by simultaneously solving multi-parts from the same problem. Conclusion: The probability that the algorithm will converge to the optimal solution was highly enhanced when decomposing the main problem into multi-part.
Parallel Algorithms for Normalization
Boehm, Janko; Laplagne, Santiago; Pfister, Gerhard; Steenpass, Andreas; Steidel, Stefan
2011-01-01
Given a reduced affine algebra A over a perfect field K, we present parallel algorithms to compute the normalization \\bar{A} of A. Our starting point is the algorithm of Greuel, Laplagne, and Seelisch, which is an improvement of de Jong's algorithm. First, we propose to stratify the singular locus Sing(A) in a way which is compatible with normalization, apply a local version of the normalization algorithm at each stratum, and find \\bar{A} by putting the local results together. Second, in the case where K = Q is the field of rationals, we propose modular versions of the global and local algorithms. We have implemented our algorithms in the computer algebra system SINGULAR and compare their performance with that of other algorithms. In the case where K = Q, we also discuss the use of modular computations of Groebner bases, radicals and primary decompositions. We point out that in most examples, the new algorithms outperform the algorithm of Greuel, Laplagne, and Seelisch by far, even if we do not run them in pa...
An Approximation Algorithm for #k-SAT
Thurley, Marc
2011-01-01
We present a simple randomized algorithm that approximates the number of satisfying assignments of Boolean formulas in conjunctive normal form. To the best of our knowledge this is the first algorithm which approximates #k-SAT for any k >= 3 within a running time that is not only non-trivial, but also significantly better than that of the currently fastest exact algorithms for the problem. More precisely, our algorithm is a randomized approximation scheme whose running time depends polynomially on the error tolerance and is mildly exponential in the number n of variables of the input formula. For example, even stipulating sub-exponentially small error tolerance, the number of solutions to 3-CNF input formulas can be approximated in time O(1.5366^n). For 4-CNF input the bound increases to O(1.6155^n). We further show how to obtain upper and lower bounds on the number of solutions to a CNF formula in a controllable way. Relaxing the requirements on the quality of the approximation, on k-CNF input we obtain sign...
Meta-Heuristic Combining Prior Online and Offline Information for the Quadratic Assignment Problem.
Sun, Jianyong; Zhang, Qingfu; Yao, Xin
2014-03-01
The construction of promising solutions for NP-hard combinatorial optimization problems (COPs) in meta-heuristics is usually based on three types of information, namely a priori information, a posteriori information learned from visited solutions during the search procedure, and online information collected in the solution construction process. Prior information reflects our domain knowledge about the COPs. Extensive domain knowledge can surely make the search effective, yet it is not always available. Posterior information could guide the meta-heuristics to globally explore promising search areas, but it lacks local guidance capability. On the contrary, online information can capture local structures, and its application can help exploit the search space. In this paper, we studied the effects of using this information on metaheuristic's algorithmic performances for the COPs. The study was illustrated by a set of heuristic algorithms developed for the quadratic assignment problem. We first proposed an improved scheme to extract online local information, then developed a unified framework under which all types of information can be combined readily. Finally, we studied the benefits of the three types of information to meta-heuristics. Conclusions were drawn from the comprehensive study, which can be used as principles to guide the design of effective meta-heuristic in the future. PMID:23757559
Travel Demand-Based Assignment Model for Multimodal and Multiuser Transportation System
Directory of Open Access Journals (Sweden)
Bingfeng Si
2012-01-01
Full Text Available In this paper, the structural characteristic of urban multimodal transport system is fully analyzed and then a two-tier network structure is proposed to describe such a system, in which the first-tier network is used to depict the traveller’s mode choice behaviour and the second-tier network is used to depict the vehicle routing when a certain mode has been selected. Subsequently, the generalized travel cost is formulated considering the properties of both traveller and transport mode. A new link impedance function is proposed, in which the interferences between different vehicle flows are taken into account. Simultaneously, the bi-equilibrium patterns for multimodal transport network are proposed by extending Wardrop principle. Correspondingly, a bi-level programming model is then presented to describe the bi-equilibrium based assignment for multi-class multimodal transport network. The solution algorithm is also given. Finally, a numerical example is provided to illustrate the model and algorithm.
Multi-objective Evolutionary Algorithms for MILP and MINLP in Process Synthesis
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
Steady-state non-dominated sorting genetic algorithm (SNSGA), a new form of multi-objective genetic algorithm, is implemented by combining the steady-state idea in steady-state genetic algorithms (SSGA) and the fitness assignment strategy of non-dominated sorting genetic algorithm (NSGA). The fitness assignment strategy is improved and a new self-adjustment scheme of σshare is proposed. This algorithm is proved to be very efficient both computationally and in terms of the quality of the Pareto fronts produced with five test problems including GA difficult problem and GA deceptive one. Finally, SNSGA is introduced to solve multi-objective mixed integer linear programming (MILP) and mixed integer non-linear programming (MINLP) problems in process synthesis.
On Nature's Strategy for Assigning Genetic Code Multiplicity.
Gardini, Simone; Cheli, Sara; Baroni, Silvia; Di Lascio, Gabriele; Mangiavacchi, Guido; Micheletti, Nicholas; Monaco, Carmen Luigia; Savini, Lorenzo; Alocci, Davide; Mangani, Stefano; Niccolai, Neri
2016-01-01
Genetic code redundancy would yield, on the average, the assignment of three codons for each of the natural amino acids. The fact that this number is observed only for incorporating Ile and to stop RNA translation still waits for an overall explanation. Through a Structural Bioinformatics approach, the wealth of information stored in the Protein Data Bank has been used here to look for unambiguous clues to decipher the rationale of standard genetic code (SGC) in assigning from one to six different codons for amino acid translation. Leu and Arg, both protected from translational errors by six codons, offer the clearest clue by appearing as the most abundant amino acids in protein-protein and protein-nucleic acid interfaces. Other SGC hidden messages have been sought by analyzing, in a protein structure framework, the roles of over- and under-protected amino acids. PMID:26849571
On Nature’s Strategy for Assigning Genetic Code Multiplicity
Gardini, Simone; Cheli, Sara; Baroni, Silvia; Di Lascio, Gabriele; Mangiavacchi, Guido; Micheletti, Nicholas; Monaco, Carmen Luigia; Savini, Lorenzo; Alocci, Davide; Mangani, Stefano; Niccolai, Neri
2016-01-01
Genetic code redundancy would yield, on the average, the assignment of three codons for each of the natural amino acids. The fact that this number is observed only for incorporating Ile and to stop RNA translation still waits for an overall explanation. Through a Structural Bioinformatics approach, the wealth of information stored in the Protein Data Bank has been used here to look for unambiguous clues to decipher the rationale of standard genetic code (SGC) in assigning from one to six different codons for amino acid translation. Leu and Arg, both protected from translational errors by six codons, offer the clearest clue by appearing as the most abundant amino acids in protein-protein and protein-nucleic acid interfaces. Other SGC hidden messages have been sought by analyzing, in a protein structure framework, the roles of over- and under-protected amino acids. PMID:26849571
Computational Assignment of Chemical Shifts for Protein Residues
Bratholm, Lars A
2013-01-01
Fast and accurate protein structure prediction is one of the major challenges in structural biology, biotechnology and molecular biomedicine. These fields require 3D protein structures for rational design of proteins with improved or novel properties. X-ray crystallography is the most common approach even with its low success rate, but lately NMR based approaches have gained popularity. The general approach involves a set of distance restraints used to guide a structure prediction, but simple NMR triple-resonance experiments often provide enough structural information to predict the structure of small proteins. Previous protein folding simulations that have utilised experimental data have weighted the experimental data and physical force field terms more or less arbitrarily, and the method is thus not generally applicable to new proteins. Furthermore a complete and near error-free assignment of chemical shifts obtained by the NMR experiments is needed, due to the static, or deterministic, assignment. In this ...
Pole assignment for stochastic systems with unknown coefficients
Institute of Scientific and Technical Information of China (English)
陈翰馥[1; 曹希仁[2
2000-01-01
This paper solves the exact pole assignment problem for the single-input stochastic systems with unknown coefficients under the controllability assumption which is necessary and sufficient for the arbitrary pole assignment for systems with known coefficients. The system noise is required to be mutually independent with zero mean and bounded second moment. Two approaches to solving the problem are proposed: One is the iterative learning approach which can be applied when the state at a fixed time can be repeatedly observed with different feedback gains; the other is the adaptive control approach which works when the trajectories satisfy a nondegeneracy condition. Both methods are essentially based on stochastic approximation, and the feedback gains are recursively given without invoking the certainty-equivalency-principle.
Mapping Learning Outcomes and Assignment Tasks for SPIDER Activities
Directory of Open Access Journals (Sweden)
Lyn Brodie
2011-05-01
Full Text Available Modern engineering programs have to address rapidly changing technical content and have to enable students to develop transferable skills such as critical evaluation, communication skills and lifelong learning. This paper introduces a combined learning and assessment activity that provides students with opportunities to develop and practice their soft skills, but also extends their theoretical knowledge base. Key tasks included self directed inquiry, oral and written communication as well as peer assessment. To facilitate the SPIDER activities (Select, Prepare and Investigate, Discuss, Evaluate, Reflect, a software tool has been implemented in the learning management system Moodle. Evidence shows increased student engagement and better learning outcomes for both transferable as well as technical skills. The study focuses on generalising the relationship between learning outcomes and assignment tasks as well as activities that drive these tasks. Trail results inform the approach. Staff evaluations and their views of assignments and intended learning outcomes also supported this analysis.
Method for assigning sites to projected generic nuclear power plants
International Nuclear Information System (INIS)
Pacific Northwest Laboratory developed a method for forecasting potential locations and startup sequences of nuclear power plants that will be required in the future but have not yet been specifically identified by electric utilities. Use of the method results in numerical ratings for potential nuclear power plant sites located in each of the 10 federal energy regions. The rating for each potential site is obtained from numerical factors assigned to each of 5 primary siting characteristics: (1) cooling water availability, (2) site land area, (3) power transmission land area, (4) proximity to metropolitan areas, and (5) utility plans for the site. The sequence of plant startups in each federal energy region is obtained by use of the numerical ratings and the forecasts of generic nuclear power plant startups obtained from the EIA Middle Case electricity forecast. Sites are assigned to generic plants in chronological order according to startup date
Confirmed assignments of isomeric dimethylbenzyl radicals generated by corona discharge.
Yoon, Young Wook; Lee, Sang Kuk
2011-12-01
The controversial vibronic assignments of isomeric dimethylbenzyl radicals were clearly resolved by using different precursors. By employing corresponding dimethylbenzyl chlorides as precursors, we identified the origins of the vibronic bands of the dimethylbenzyl radicals generated by corona discharge of 1,2,4-trimethylbenzene. From the analysis of the spectra observed from the dimethylbenzyl chlorides in a corona excited supersonic expansion, we revised previous assignments of the 3,4-, 2,4-, and 2,5-dimethylbenzyl radicals. Spectroscopic data of electronic transition and vibrational mode frequencies in the ground electronic state of each isomer were accurately determined by comparing them with those obtained by an ab initio calculation and with the known vibrational data of 1,2,4-trimethylbenzene. PMID:22149790
A framework for assessing learning assistants' reflective writing assignments
Cochran, Geraldine L.; Brookes, David T.; Kramer, Laird H.
2013-01-01
At Florida International University we have implemented a learning assistant (LA) program based on the Colorado Learning Assistant Model. [1] As a part of this program, students take a course on science and mathematics education theory and practice in which they are required to submit written reflections. Past anecdotal evidence suggests that students in the LAP at Florida International University are using these writing assignments to reflect on their teaching experiences. The purpose of this study was to a) determine if the writing assignments submitted give evidence that our students are engaging in reflection and b) determine if our students are engaging in deep levels of reflection. In this investigation, we relied on a rubric based on Hatton and Smith's (1995) [2] "Criteria for the Recognition of Evidence for Different Types of Reflective Writing." In this paper, we document a) a system for characterizing student reflections and b) how we give them feedback.
Method for assigning sites to projected generic nuclear power plants
Energy Technology Data Exchange (ETDEWEB)
Holter, G.M.; Purcell, W.L.; Shutz, M.E.; Young, J.R.
1986-07-01
Pacific Northwest Laboratory developed a method for forecasting potential locations and startup sequences of nuclear power plants that will be required in the future but have not yet been specifically identified by electric utilities. Use of the method results in numerical ratings for potential nuclear power plant sites located in each of the 10 federal energy regions. The rating for each potential site is obtained from numerical factors assigned to each of 5 primary siting characteristics: (1) cooling water availability, (2) site land area, (3) power transmission land area, (4) proximity to metropolitan areas, and (5) utility plans for the site. The sequence of plant startups in each federal energy region is obtained by use of the numerical ratings and the forecasts of generic nuclear power plant startups obtained from the EIA Middle Case electricity forecast. Sites are assigned to generic plants in chronological order according to startup date.
Application of Neutrosophic Set Theory in Generalized Assignment Problem
Directory of Open Access Journals (Sweden)
Supriya Kar
2015-09-01
Full Text Available This paper presents the application of Neutrosophic Set Theory (NST in solving Generalized Assignment Problem (GAP. GAP has been solved earlier under fuzzy environment. NST is a generalization of the concept of classical set, fuzzy set, interval-valued fuzzy set, intuitionistic fuzzy set. Elements of Neutrosophic set are characterized by a truth-membership function, falsity and also indeterminacy which is a more realistic way of expressing the parameters in real life problem. Here the elements of the cost matrix for the GAP are considered as neutrosophic elements which have not been considered earlier by any other author. The problem has been solved by evaluating score function matrix and then solving it by Extremum Difference Method (EDM [1] to get the optimal assignment. The method has been demonstrated by a suitable numerical example.