Improved chemical identification from sensor arrays using intelligent algorithms

Science.gov (United States)

Roppel, Thaddeus A.; Wilson, Denise M.

2001-02-01

Intelligent signal processing algorithms are shown to improve identification rates significantly in chemical sensor arrays. This paper focuses on the use of independently derived sensor status information to modify the processing of sensor array data by using a fast, easily-implemented "best-match" approach to filling in missing sensor data. Most fault conditions of interest (e.g., stuck high, stuck low, sudden jumps, excess noise, etc.) can be detected relatively simply by adjunct data processing, or by on-board circuitry. The objective then is to devise, implement, and test methods for using this information to improve the identification rates in the presence of faulted sensors. In one typical example studied, utilizing separately derived, a-priori knowledge about the health of the sensors in the array improved the chemical identification rate by an artificial neural network from below 10 percent correct to over 99 percent correct. While this study focuses experimentally on chemical sensor arrays, the results are readily extensible to other types of sensor platforms.

Event Sequence Analysis of the Air Intelligence Agency Information Operations Center Flight Operations

National Research Council Canada - National Science Library

Larsen, Glen

1998-01-01

This report applies Event Sequence Analysis, methodology adapted from aircraft mishap investigation, to an investigation of the performance of the Air Intelligence Agency's Information Operations Center (IOC...

Negated bio-events: analysis and identification

Science.gov (United States)

2013-01-01

Background Negation occurs frequently in scientific literature, especially in biomedical literature. It has previously been reported that around 13% of sentences found in biomedical research articles contain negation. Historically, the main motivation for identifying negated events has been to ensure their exclusion from lists of extracted interactions. However, recently, there has been a growing interest in negative results, which has resulted in negation detection being identified as a key challenge in biomedical relation extraction. In this article, we focus on the problem of identifying negated bio-events, given gold standard event annotations. Results We have conducted a detailed analysis of three open access bio-event corpora containing negation information (i.e., GENIA Event, BioInfer and BioNLP’09 ST), and have identified the main types of negated bio-events. We have analysed the key aspects of a machine learning solution to the problem of detecting negated events, including selection of negation cues, feature engineering and the choice of learning algorithm. Combining the best solutions for each aspect of the problem, we propose a novel framework for the identification of negated bio-events. We have evaluated our system on each of the three open access corpora mentioned above. The performance of the system significantly surpasses the best results previously reported on the BioNLP’09 ST corpus, and achieves even better results on the GENIA Event and BioInfer corpora, both of which contain more varied and complex events. Conclusions Recently, in the field of biomedical text mining, the development and enhancement of event-based systems has received significant interest. The ability to identify negated events is a key performance element for these systems. We have conducted the first detailed study on the analysis and identification of negated bio-events. Our proposed framework can be integrated with state-of-the-art event extraction systems. The

The theory of multiple intelligences in the identification of high-ability students

Directory of Open Access Journals (Sweden)

Daniel Hernández-Torrano

2014-01-01

Full Text Available This study provides a framework to implement the theory of multiple intelligences (MI in the identification of high-ability students in secondary education. The internal structure of three scales to assess students' MI (students, parents and teachers' ratings was analyzed in a sample of 566 students nominated as gifted by their teachers. Participants aged 11 to 16 years (M = 14.85, SD = 1.08. The results indicated differentiated intellectual profiles depending on the informant estimating students' MI. This study provided evidence for two components that allow us to analyze the cognitive competence of high-ability students beyond the areas commonly assessed at school: an academic component composed by the linguistic, logical-mathematical, naturalistic, and visual-spatial intelligences; and a non-academic component statistically loaded by the bodily-kinesthetic, musical and social intelligences. Convergence of the two components in the three scales was evidenced; and correlations between these components and students' objective performance on a psychometric intelligence test were found to be low. Finally, the utility of the MI scales to identify high-ability students in secondary education is discussed.

An intelligent identification algorithm for the monoclonal picking instrument

Science.gov (United States)

Yan, Hua; Zhang, Rongfu; Yuan, Xujun; Wang, Qun

2017-11-01

The traditional colony selection is mainly operated by manual mode, which takes on low efficiency and strong subjectivity. Therefore, it is important to develop an automatic monoclonal-picking instrument. The critical stage of the automatic monoclonal-picking and intelligent optimal selection is intelligent identification algorithm. An auto-screening algorithm based on Support Vector Machine (SVM) is proposed in this paper, which uses the supervised learning method, which combined with the colony morphological characteristics to classify the colony accurately. Furthermore, through the basic morphological features of the colony, system can figure out a series of morphological parameters step by step. Through the establishment of maximal margin classifier, and based on the analysis of the growth trend of the colony, the selection of the monoclonal colony was carried out. The experimental results showed that the auto-screening algorithm could screen out the regular colony from the other, which meets the requirement of various parameters.

Detection, recognition, identification, and tracking of military vehicles using biomimetic intelligence

Science.gov (United States)

Pace, Paul W.; Sutherland, John

2001-10-01

This project is aimed at analyzing EO/IR images to provide automatic target detection/recognition/identification (ATR/D/I) of militarily relevant land targets. An increase in performance was accomplished using a biomimetic intelligence system functioning on low-cost, commercially available processing chips. Biomimetic intelligence has demonstrated advanced capabilities in the areas of hand- printed character recognition, real-time detection/identification of multiple faces in full 3D perspectives in cluttered environments, advanced capabilities in classification of ground-based military vehicles from SAR, and real-time ATR/D/I of ground-based military vehicles from EO/IR/HRR data in cluttered environments. The investigation applied these tools to real data sets and examined the parameters such as the minimum resolution for target recognition, the effect of target size, rotation, line-of-sight changes, contrast, partial obscuring, background clutter etc. The results demonstrated a real-time ATR/D/I capability against a subset of militarily relevant land targets operating in a realistic scenario. Typical results on the initial EO/IR data indicate probabilities of correct classification of resolved targets to be greater than 95 percent.

Feature extraction and sensor selection for NPP initiating event identification

International Nuclear Information System (INIS)

Lin, Ting-Han; Wu, Shun-Chi; Chen, Kuang-You; Chou, Hwai-Pwu

2017-01-01

Highlights: • A two-stage feature extraction scheme for NPP initiating event identification. • With stBP, interrelations among the sensors can be retained for identification. • With dSFS, sensors that are crucial for identification can be efficiently selected. • Efficacy of the scheme is illustrated with data from the Maanshan NPP simulator. - Abstract: Initiating event identification is essential in managing nuclear power plant (NPP) severe accidents. In this paper, a novel two-stage feature extraction scheme that incorporates the proposed sensor type-wise block projection (stBP) and deflatable sequential forward selection (dSFS) is used to elicit the discriminant information in the data obtained from various NPP sensors to facilitate event identification. With the stBP, the primal features can be extracted without eliminating the interrelations among the sensors of the same type. The extracted features are then subjected to a further dimensionality reduction by selecting the sensors that are most relevant to the events under consideration. This selection is not easy, and a combinatorial optimization technique is normally required. With the dSFS, an optimal sensor set can be found with less computational load. Moreover, its sensor deflation stage allows sensors in the preselected set to be iteratively refined to avoid being trapped into a local optimum. Results from detailed experiments containing data of 12 event categories and a total of 112 events generated with a Taiwan’s Maanshan NPP simulator are presented to illustrate the efficacy of the proposed scheme.

Event storm detection and identification in communication systems

International Nuclear Information System (INIS)

Albaghdadi, Mouayad; Briley, Bruce; Evens, Martha

2006-01-01

Event storms are the manifestation of an important class of abnormal behaviors in communication systems. They occur when a large number of nodes throughout the system generate a set of events within a small period of time. It is essential for network management systems to detect every event storm and identify its cause, in order to prevent and repair potential system faults. This paper presents a set of techniques for the effective detection and identification of event storms in communication systems. First, we introduce a new algorithm to synchronize events to a single node in the system. Second, the system's event log is modeled as a normally distributed random process. This is achieved by using data analysis techniques to explore and then model the statistical behavior of the event log. Third, event storm detection is proposed using a simple test statistic combined with an exponential smoothing technique to overcome the non-stationary behavior of event logs. Fourth, the system is divided into non-overlapping regions to locate the main contributing regions of a storm. We show that this technique provides us with a method for event storm identification. Finally, experimental results from a commercially deployed multimedia communication system that uses these techniques demonstrate their effectiveness

A Novel Biometric Identification Based on a User's Input Pattern Analysis for Intelligent Mobile Devices

Directory of Open Access Journals (Sweden)

Hojin Seo

2012-07-01

Full Text Available As intelligent mobile devices become more popular, security threats targeting them are increasing. The resource constraints of mobile devices, such as battery life and computing power, however, make it harder to handle such threats effectively. The existing physical and behavioural biometric identification methods - looked upon as good alternatives - are unsuitable for the current mobile environment. This paper proposes a specially designed biometric identification method for intelligent mobile devices by analysing the user's input patterns, such as a finger's touch duration, pressure level and the touching width of the finger on the touch screen. We collected the input pattern data of individuals to empirically test our method. Our testing results show that this method effectively identifies users with near a 100% rate of accuracy.

Event detection intelligent camera development

International Nuclear Information System (INIS)

Szappanos, A.; Kocsis, G.; Molnar, A.; Sarkozi, J.; Zoletnik, S.

2008-01-01

A new camera system 'event detection intelligent camera' (EDICAM) is being developed for the video diagnostics of W-7X stellarator, which consists of 10 distinct and standalone measurement channels each holding a camera. Different operation modes will be implemented for continuous and for triggered readout as well. Hardware level trigger signals will be generated from real time image processing algorithms optimized for digital signal processor (DSP) and field programmable gate array (FPGA) architectures. At full resolution a camera sends 12 bit sampled 1280 x 1024 pixels with 444 fps which means 1.43 Terabyte over half an hour. To analyse such a huge amount of data is time consuming and has a high computational complexity. We plan to overcome this problem by EDICAM's preprocessing concepts. EDICAM camera system integrates all the advantages of CMOS sensor chip technology and fast network connections. EDICAM is built up from three different modules with two interfaces. A sensor module (SM) with reduced hardware and functional elements to reach a small and compact size and robust action in harmful environment as well. An image processing and control unit (IPCU) module handles the entire user predefined events and runs image processing algorithms to generate trigger signals. Finally a 10 Gigabit Ethernet compatible image readout card functions as the network interface for the PC. In this contribution all the concepts of EDICAM and the functions of the distinct modules are described

An Intelligent Complex Event Processing with D Numbers under Fuzzy Environment

Directory of Open Access Journals (Sweden)

Fuyuan Xiao

2016-01-01

Full Text Available Efficient matching of incoming mass events to persistent queries is fundamental to complex event processing systems. Event matching based on pattern rule is an important feature of complex event processing engine. However, the intrinsic uncertainty in pattern rules which are predecided by experts increases the difficulties of effective complex event processing. It inevitably involves various types of the intrinsic uncertainty, such as imprecision, fuzziness, and incompleteness, due to the inability of human beings subjective judgment. Nevertheless, D numbers is a new mathematic tool to model uncertainty, since it ignores the condition that elements on the frame must be mutually exclusive. To address the above issues, an intelligent complex event processing method with D numbers under fuzzy environment is proposed based on the Technique for Order Preferences by Similarity to an Ideal Solution (TOPSIS method. The novel method can fully support decision making in complex event processing systems. Finally, a numerical example is provided to evaluate the efficiency of the proposed method.

Multivariate algorithms for initiating event detection and identification in nuclear power plants

International Nuclear Information System (INIS)

Wu, Shun-Chi; Chen, Kuang-You; Lin, Ting-Han; Chou, Hwai-Pwu

2018-01-01

Highlights: •Multivariate algorithms for NPP initiating event detection and identification. •Recordings from multiple sensors are simultaneously considered for detection. •Both spatial and temporal information is used for event identification. •Untrained event isolation avoids falsely relating an untrained event. •Efficacy of the algorithms is verified with data from the Maanshan NPP simulator. -- Abstract: To prevent escalation of an initiating event into a severe accident, promptly detecting its occurrence and precisely identifying its type are essential. In this study, several multivariate algorithms for initiating event detection and identification are proposed to help maintain safe operations of nuclear power plants (NPPs). By monitoring changes in the NPP sensing variables, an event is detected when the preset thresholds are exceeded. Unlike existing approaches, recordings from sensors of the same type are simultaneously considered for detection, and no subjective reasoning is involved in setting these thresholds. To facilitate efficient event identification, a spatiotemporal feature extractor is proposed. The extracted features consist of the temporal traits used by existing techniques and the spatial signature of an event. Through an F-score-based feature ranking, only those that are most discriminant in classifying the events under consideration will be retained for identification. Moreover, an untrained event isolation scheme is introduced to avoid relating an untrained event to those in the event dataset so that improper recovery actions can be prevented. Results from experiments containing data of 12 event classes and a total of 125 events generated using a Taiwan’s Maanshan NPP simulator are provided to illustrate the efficacy of the proposed algorithms.

Automatic identification of otological drilling faults: an intelligent recognition algorithm.

Science.gov (United States)

Cao, Tianyang; Li, Xisheng; Gao, Zhiqiang; Feng, Guodong; Shen, Peng

2010-06-01

This article presents an intelligent recognition algorithm that can recognize milling states of the otological drill by fusing multi-sensor information. An otological drill was modified by the addition of sensors. The algorithm was designed according to features of the milling process and is composed of a characteristic curve, an adaptive filter and a rule base. The characteristic curve can weaken the impact of the unstable normal milling process and reserve the features of drilling faults. The adaptive filter is capable of suppressing interference in the characteristic curve by fusing multi-sensor information. The rule base can identify drilling faults through the filtering result data. The experiments were repeated on fresh porcine scapulas, including normal milling and two drilling faults. The algorithm has high rates of identification. This study shows that the intelligent recognition algorithm can identify drilling faults under interference conditions. (c) 2010 John Wiley & Sons, Ltd.

Event Detection Intelligent Camera: Demonstration of flexible, real-time data taking and processing

Energy Technology Data Exchange (ETDEWEB)

Szabolics, Tamás, E-mail: szabolics.tamas@wigner.mta.hu; Cseh, Gábor; Kocsis, Gábor; Szepesi, Tamás; Zoletnik, Sándor

2015-10-15

Highlights: • We present EDICAM's operation principles description. • Firmware tests results. • Software test results. • Further developments. - Abstract: An innovative fast camera (EDICAM – Event Detection Intelligent CAMera) was developed by MTA Wigner RCP in the last few years. This new concept was designed for intelligent event driven processing to be able to detect predefined events and track objects in the plasma. The camera provides a moderate frame rate of 400 Hz at full frame resolution (1280 × 1024), and readout of smaller region of interests can be done in the 1–140 kHz range even during exposure of the full image. One of the most important advantages of this hardware is a 10 Gbit/s optical link which ensures very fast communication and data transfer between the PC and the camera, enabling two level of processing: primitive algorithms in the camera hardware and high-level processing in the PC. This camera hardware has successfully proven to be able to monitoring the plasma in several fusion devices for example at ASDEX Upgrade, KSTAR and COMPASS with the first version of firmware. A new firmware and software package is under development. It allows to detect predefined events in real time and therefore the camera is capable to change its own operation or to give warnings e.g. to the safety system of the experiment. The EDICAM system can handle a huge amount of data (up to TBs) with high data rate (950 MB/s) and will be used as the central element of the 10 camera overview video diagnostic system of Wendenstein 7-X (W7-X) stellarator. This paper presents key elements of the newly developed built-in intelligence stressing the revolutionary new features and the results of the test of the different software elements.

Changing relations between intelligence and brain activity in late childhood: A longitudinal event-related potential study.

NARCIS (Netherlands)

Stauder, J.E.A.; van der Molen, M.W.; Molenaar, P.C.M.

1998-01-01

In studying the relationship between Raven intelligence and event-related brain potentials to a visual oddball task in the same children, at respectively 9, 10 and 11 years of age, dramatic changes were observed with age. The event-related amplitude data suggest a shift in relation between

PROBABILISTIC CROSS-IDENTIFICATION OF COSMIC EVENTS

International Nuclear Information System (INIS)

Budavari, Tamas

2011-01-01

I discuss a novel approach to identifying cosmic events in separate and independent observations. The focus is on the true events, such as supernova explosions, that happen once and, hence, whose measurements are not repeatable. Their classification and analysis must make the best use of all available data. Bayesian hypothesis testing is used to associate streams of events in space and time. Probabilities are assigned to the matches by studying their rates of occurrence. A case study of Type Ia supernovae illustrates how to use light curves in the cross-identification process. Constraints from realistic light curves happen to be well approximated by Gaussians in time, which makes the matching process very efficient. Model-dependent associations are computationally more demanding but can further boost one's confidence.

A review for identification of initiating events in event tree development process on nuclear power plants

International Nuclear Information System (INIS)

Riyadi, Eko H.

2014-01-01

Initiating event is defined as any event either internal or external to the nuclear power plants (NPPs) that perturbs the steady state operation of the plant, if operating, thereby initiating an abnormal event such as transient or loss of coolant accident (LOCA) within the NPPs. These initiating events trigger sequences of events that challenge plant control and safety systems whose failure could potentially lead to core damage or large early release. Selection for initiating events consists of two steps i.e. first step, definition of possible events, such as by evaluating a comprehensive engineering, and by constructing a top level logic model. Then the second step, grouping of identified initiating event's by the safety function to be performed or combinations of systems responses. Therefore, the purpose of this paper is to discuss initiating events identification in event tree development process and to reviews other probabilistic safety assessments (PSA). The identification of initiating events also involves the past operating experience, review of other PSA, failure mode and effect analysis (FMEA), feedback from system modeling, and master logic diagram (special type of fault tree). By using the method of study for the condition of the traditional US PSA categorization in detail, could be obtained the important initiating events that are categorized into LOCA, transients and external events

A review for identification of initiating events in event tree development process on nuclear power plants

Energy Technology Data Exchange (ETDEWEB)

Riyadi, Eko H., E-mail: e.riyadi@bapeten.go.id [Center for Regulatory Assessment of Nuclear Installation and Materials, Nuclear Energy Regulatory Agency (BAPETEN), Jl. Gajah Mada 8 Jakarta 10120 (Indonesia)

2014-09-30

Initiating event is defined as any event either internal or external to the nuclear power plants (NPPs) that perturbs the steady state operation of the plant, if operating, thereby initiating an abnormal event such as transient or loss of coolant accident (LOCA) within the NPPs. These initiating events trigger sequences of events that challenge plant control and safety systems whose failure could potentially lead to core damage or large early release. Selection for initiating events consists of two steps i.e. first step, definition of possible events, such as by evaluating a comprehensive engineering, and by constructing a top level logic model. Then the second step, grouping of identified initiating event's by the safety function to be performed or combinations of systems responses. Therefore, the purpose of this paper is to discuss initiating events identification in event tree development process and to reviews other probabilistic safety assessments (PSA). The identification of initiating events also involves the past operating experience, review of other PSA, failure mode and effect analysis (FMEA), feedback from system modeling, and master logic diagram (special type of fault tree). By using the method of study for the condition of the traditional US PSA categorization in detail, could be obtained the important initiating events that are categorized into LOCA, transients and external events.

Event building in an intelligent network interface card for the LHCb readout network

CERN Document Server

Dufey, J P; Neufeld, N; Zuin, M

2001-01-01

LHCb is an experiment being constructed at CERN's LHC accelerator for the purpose of studying precisely the CP violation parameters in the B-B system. Triggering poses special problems since the interesting events containing B-mesons are immersed in a large background of inelastic p-p reactions. Therefore, a 4 Level Triggering scheme (Level 0 to Level 3) has been implemented. Powerful embedded processors, used in modern intelligent Network Interface Cards (smart NICs), make it attractive to use them to handle the event building protocol in the high-speed data acquisition system of the LHCb experiment. The implementation of an event building algorithm developed for a specific Gigabit Ethernet NIC is presented and performance data are discussed. 5 Refs.

Mobilizing intelligence against nuclear terrorism: a personal perspective

International Nuclear Information System (INIS)

Ne'eman, Y.

1987-01-01

The acquisition of intelligence is best achieved when the following sequence of logical steps controls the process: 1. Definition of essential information. This step consists of identifying the most important items of required information and will be closely tied to the issue under consideration, such as a specific event, evolution, or deployment. It is also important to determine how much warning time is needed prior to an event's occurring. 2. Identification of indicators. This step involves the determination of observable facts or actions that are indicators of the essential information. Sometimes they may be indirect and worth noting but not sufficient in themselves - for example, an interesting characteristic of an envisaged evolution that may be emerging. 3. Intelligence acquisition program. This step can be thought of as a matrix in which the columns list the indicators, and the rows list the various means of acquiring information about them. 4. Ongoing review of the basic premises. Step 1 always involves a set of assumptions. Once the process of intelligence acquisition in underway, it is important to check and recheck whether the basic premises still hold or need to be modified on the basis of new intelligence. This process should be ongoing. Often, however, it is forgotten, albeit at heavy expense. Here the discussion centers mainly on steps 1 and 2

System risk evolution analysis and risk critical event identification based on event sequence diagram

International Nuclear Information System (INIS)

Luo, Pengcheng; Hu, Yang

2013-01-01

During system operation, the environmental, operational and usage conditions are time-varying, which causes the fluctuations of the system state variables (SSVs). These fluctuations change the accidents’ probabilities and then result in the system risk evolution (SRE). This inherent relation makes it feasible to realize risk control by monitoring the SSVs in real time, herein, the quantitative analysis of SRE is essential. Besides, some events in the process of SRE are critical to system risk, because they act like the “demarcative points” of safety and accident, and this characteristic makes each of them a key point of risk control. Therefore, analysis of SRE and identification of risk critical events (RCEs) are remarkably meaningful to ensure the system to operate safely. In this context, an event sequence diagram (ESD) based method of SRE analysis and the related Monte Carlo solution are presented; RCE and risk sensitive variable (RSV) are defined, and the corresponding identification methods are also proposed. Finally, the proposed approaches are exemplified with an accident scenario of an aircraft getting into the icing region

Identification of Initiating Events for PGSFR

International Nuclear Information System (INIS)

Kim, Jintae; Jae, Moosung

2016-01-01

The Sodium-cooled Fast Reactor (SFR) is by far the most advanced reactor of the six Generation IV reactors. The SFR uses liquid sodium as the reactor coolant, which has superior heat transport characteristics. It also allows high power density with low coolant volume fraction and operation at low pressure. In Korea, KAERI has been developing Prototype Generation-IV Sodium-cooled Fast Reactor (PGSFR) that employs passive safety systems and inherent reactivity feedback effects. In order to prepare for the licensing, it is necessary to assess the safety of the reactor. Thus, the objective of this study is to conduct accident sequence analysis that can contribute to risk assessment. The analysis embraces identification of initiating events and accident sequences development. PGSFR is to test and demonstrate the performance of transuranic (TRU)-containing metal fuel required for a commercial SFR, and to demonstrate the TRU transmutation capability of a burner reactor as a part of an advanced fuel cycle system. Initiating events that can happen in PGSFR were identified through the MLD method. This method presents a model of a plant in terms of individual events and their combinations in a systematic and logical way. The 11 identified initiating events in this study include the events considered in the past analysis that was conducted for PRISM-150

Identification of Initiating Events for PGSFR

Energy Technology Data Exchange (ETDEWEB)

Kim, Jintae; Jae, Moosung [Hanyang University, Seoul (Korea, Republic of)

2016-10-15

The Sodium-cooled Fast Reactor (SFR) is by far the most advanced reactor of the six Generation IV reactors. The SFR uses liquid sodium as the reactor coolant, which has superior heat transport characteristics. It also allows high power density with low coolant volume fraction and operation at low pressure. In Korea, KAERI has been developing Prototype Generation-IV Sodium-cooled Fast Reactor (PGSFR) that employs passive safety systems and inherent reactivity feedback effects. In order to prepare for the licensing, it is necessary to assess the safety of the reactor. Thus, the objective of this study is to conduct accident sequence analysis that can contribute to risk assessment. The analysis embraces identification of initiating events and accident sequences development. PGSFR is to test and demonstrate the performance of transuranic (TRU)-containing metal fuel required for a commercial SFR, and to demonstrate the TRU transmutation capability of a burner reactor as a part of an advanced fuel cycle system. Initiating events that can happen in PGSFR were identified through the MLD method. This method presents a model of a plant in terms of individual events and their combinations in a systematic and logical way. The 11 identified initiating events in this study include the events considered in the past analysis that was conducted for PRISM-150.

RA-6 reactor's probabilistic safety evaluation. Identification and selection of starting events

International Nuclear Information System (INIS)

Kay, J.; Chiossi, C.; Felizia, E.; Vallerga, H.; Kalejman, G.; Navarro, R.; Caruso, G.J.

1987-01-01

A summary of the 'Identification and selection of starting events' stage of the previous probabilistic safety evaluation of RA-6 reactor is presented. This evaluation was performed to verify if the safety criteria required for the licensing of RA-6 are met and to promote the diffusion of its meaning and usefulness with educational purposes. At this stage the starting events of RA-6 are determined and the probability that such events occur is calculated. The identification and selection of starting events is performed in two steps: determination of proposed starting events and determination of postulated starting events. The proposed starting events are determined by means of the master logic diagram (MLD) method, while the postulated starting events are obtained by grouping the proposed starting events. The simplifying hypothesis required for the application of MLD to the reactor are also formulated. The probability that the proposed and postulated starting events occur is afterwards calculated, adopting different fault models, in accordance with the nature of events that are considered. Conservative hypothesis on the characteristics of these events and the uncertainty of parameter values of those models are also formulated. The numerical values of the above mentioned probabilities are obtained by giving the parameters suitable values that are extracted from specialized publications. (Author)

The Convolutional Visual Network for Identification and Reconstruction of NOvA Events

Energy Technology Data Exchange (ETDEWEB)

Psihas, Fernanda [Indiana U.

2017-11-22

In 2016 the NOvA experiment released results for the observation of oscillations in the vμ and ve channels as well as ve cross section measurements using neutrinos from Fermilab’s NuMI beam. These and other measurements in progress rely on the accurate identification and reconstruction of the neutrino flavor and energy recorded by our detectors. This presentation describes the first application of convolutional neural network technology for event identification and reconstruction in particle detectors like NOvA. The Convolutional Visual Network (CVN) Algorithm was developed for identification, categorization, and reconstruction of NOvA events. It increased the selection efficiency of the ve appearance signal by 40% and studies show potential impact to the vμ disappearance analysis.

Radio frequency identification enabled wireless sensing for intelligent food logistics.

Science.gov (United States)

Zou, Zhuo; Chen, Qiang; Chen, Qing; Uysal, Ismail; Zheng, Lirong

2014-06-13

Future technologies and applications for the Internet of Things (IoT) will evolve the process of the food supply chain and create added value of business. Radio frequency identifications (RFIDs) and wireless sensor networks (WSNs) have been considered as the key technological enablers. Intelligent tags, powered by autonomous energy, are attached on objects, networked by short-range wireless links, allowing the physical parameters such as temperatures and humidities as well as the location information to seamlessly integrate with the enterprise information system over the Internet. In this paper, challenges, considerations and design examples are reviewed from system, implementation and application perspectives, particularly with focus on intelligent packaging and logistics for the fresh food tracking and monitoring service. An IoT platform with a two-layer network architecture is introduced consisting of an asymmetric tag-reader link (RFID layer) and an ad-hoc link between readers (WSN layer), which are further connected to the Internet via cellular or Wi-Fi. Then, we provide insights into the enabling technology of RFID with sensing capabilities. Passive, semi-passive and active RFID solutions are discussed. In particular, we describe ultra-wideband radio RFID which has been considered as one of the most promising techniques for ultra-low-power and low-cost wireless sensing. Finally, an example is provided in the form of an application in fresh food tracking services and corresponding field testing results.

ARTIFICIAL INTELLIGENCE CAPABILITIES FOR INCREASING ORGANIZATIONAL-TECHNOLOGICAL RELIABILITY OF CONSTRUCTION

Directory of Open Access Journals (Sweden)

Ginzburg Alexander Vital`evich

2018-02-01

Full Text Available The technology of artificial intelligence is actively being mastered in the world but there is not much talk about the capabilities of artificial intelligence in construction industry and this issue requires additional elaboration. As a rule, the decision to invest in a particular construction project is made on the basis of an assessment of the organizational and technological reliability of the construction process. Artificial intelligence can be a convenient quality tool for identifying, analyzing and subsequent control of the “pure” risks of the construction project, which not only will significantly reduce the financial and time expenditures for the investor’s decision-making process but also improve the organizational-technological reliability of the construction process as a whole. Subject: the algorithm of creation of artificial intelligence in the field of identification and analysis of potential risk events is presented, which will facilitate the creation of an independent analytical system for different stages of construction production: from the sketch to the working documentation and conduction of works directly on the construction site. Research objectives: the study of the possibility, methods and planning of the algorithm of works for creation of artificial intelligence technology in order to improve the organizational-technological reliability of the construction process. Materials and methods: the developments in the field of improving the organizational and technological reliability of construction were studied through the analysis and control of potential “pure” risks of the construction project, and the work was also carried out to integrate the technology of artificial intelligence into the area being studied. Results: An algorithm for creating artificial intelligence in the field of identification of potential “pure” risks of construction projects was presented. Conclusions: the obtained results are useful

Identification of events with a secondary vertex in the experiment EXCHARM

International Nuclear Information System (INIS)

Bonyushkina, A.Yu.; Ivanov, V.V.; Potrebenikov, Yu.K.; Progulova, T.B.; Tatishvili, G.T.

1996-01-01

A simple algorithm for identifying events with secondary vertices (signal events) is suggested. The differences R x , R y between the largest and the smallest impact parameters D i of the tracks belonging to each of the events analyzed are used in establishing the identification criteria for signal and background events. An effective method for identifying the tracks associated with a particular secondary vertex in an event is developed. The method is based on the differences between the asymmetries exhibited by the sets D i for individual signal events and background events. The algorithm has been tested using simulated data. 12 refs., 7 figs

Influence of the signer's psychophysiological state on the results of his identification using handwritten pattern by natural and artificial intelligence

Directory of Open Access Journals (Sweden)

Alexey E. Sulavko

2017-11-01

Full Text Available At present, while various mechanisms to ensure information security are actively being improved, particular attention is paid to prevent unauthorized access to information resources.  The human factor and process of identification still remain the most problematic, as well as user authentication. A progress in the technology of information resources protection from internal security threats paves its way towards biometric systems of hidden identification of computer users and their psychophysiological state. A change in psychophysiological state results in the person's handwriting. The influence of the signer’s state of fatigue and excitation on the results of its identification both by a person and by pattern recognition methods on reproduced signatures are studied. Capabilities of human and artificial intelligence are compared in equal conditions. When the state of the signer changes, the probability of erroneous recognition by artificial intelligence increases by factor 3.3 to 3.7. A person identifies a handwritten image with fewer errors in case when the signer is agitated, and with higher error rate if the signer is tired.

Augmented reality enabling intelligence exploitation at the edge

Science.gov (United States)

Kase, Sue E.; Roy, Heather; Bowman, Elizabeth K.; Patton, Debra

2015-05-01

Today's Warfighters need to make quick decisions while interacting in densely populated environments comprised of friendly, hostile, and neutral host nation locals. However, there is a gap in the real-time processing of big data streams for edge intelligence. We introduce a big data processing pipeline called ARTEA that ingests, monitors, and performs a variety of analytics including noise reduction, pattern identification, and trend and event detection in the context of an area of operations (AOR). Results of the analytics are presented to the Soldier via an augmented reality (AR) device Google Glass (Glass). Non-intrusive AR devices such as Glass can visually communicate contextually relevant alerts to the Soldier based on the current mission objectives, time, location, and observed or sensed activities. This real-time processing and AR presentation approach to knowledge discovery flattens the intelligence hierarchy enabling the edge Soldier to act as a vital and active participant in the analysis process. We report preliminary observations testing ARTEA and Glass in a document exploitation and person of interest scenario simulating edge Soldier participation in the intelligence process in disconnected deployment conditions.

Intelligent system for accident identification in NPP; Sistema inteligente para la identificacion de accidentes en centrales nucleares

Energy Technology Data Exchange (ETDEWEB)

Hernandez, J L [Centro Nacional de Seguridad Nuclear, La Habana (Cuba)

1999-12-31

Accidental situations in NPP are great concern for operators, the facility, regulatory bodies and the environmental. This work proposes a design of intelligent system aimed to assist the operator in the process of decision making initiator events with higher relative contribution to the reactor core damage occur. The intelligent System uses the results of the pre-operational Probabilistic safety Assessment and the Thermal hydraulic Safety Analysis of the NPP Juragua as source for building its knowledge base. The nucleus of the system is presented as a design of an intelligent hybrid from the combination of the artificial intelligence techniques fuzzy logic and artificial neural networks. The system works with variables from the process of the first circuit, second circuit and the containment and it is presented as a model for the integration of safety analyses in the process of decision making by the operator when tackling with accidental situations

Crack identification based on synthetic artificial intelligent technique

International Nuclear Information System (INIS)

Shim, Mun Bo; Suh, Myung Won

2001-01-01

It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. To identify the location and depth of a crack in a structure, a method is presented in this paper which uses synthetic artificial intelligent technique, that is, Adaptive-Network-based Fuzzy Inference System(ANFIS) solved via hybrid learning algorithm(the back-propagation gradient descent and the least-squares method) are used to learn the input(the location and depth of a crack)-output(the structural eigenfrequencies) relation of the structural system. With this ANFIS and a Continuous Evolutionary Algorithm(CEA), it is possible to formulate the inverse problem. CEAs based on genetic algorithms work efficiently for continuous search space optimization problems like a parameter identification problem. With this ANFIS, CEAs are used to identify the crack location and depth minimizing the difference from the measured frequencies. We have tried this new idea on a simple beam structure and the results are promising

Intelligent systems

CERN Document Server

Irwin, J David

2011-01-01

Technology has now progressed to the point that intelligent systems are replacing humans in the decision making processes as well as aiding in the solution of very complex problems. In many cases intelligent systems are already outperforming human activities. Artificial neural networks are not only capable of learning how to classify patterns, such images or sequence of events, but they can also effectively model complex nonlinear systems. Their ability to classify sequences of events is probably more popular in industrial applications where there is an inherent need to model nonlinear system

Realization of Personalized Services for Intelligent Residential Space based on User Identification Method using Sequential Walking Footprints

Directory of Open Access Journals (Sweden)

Jin-Woo Jung

2005-04-01

Full Text Available A new human-friendly assistive home environment, Intelligent Sweet Home (ISH, developed at KAIST, Korea for testing advanced concepts for independent living of the elderly/the physically handicapped. The concept of ISH is to consider the home itself as an intelligent robot. ISH always checks the intention or health status of the resident. Therefore, ISH can do actively the most proper services considering the resident's life-style by the detected intention or emergency information. But, when there are more than two residents, ISH cannot consider the residents' characteristics or tastes if ISH cannot identify who he/she is before. To realize a personalized service system in the intelligent residential space like ISH, we deal with a human-friendly user identification method for ubiquitous computing environment, specially focused on dynamic human footprint recognition. And then, we address some case studies of personalized services that have been experienced by Human-friendly Welfare Robot System research center, KAIST.

Early detection and identification of anomalies in chemical regime based on computational intelligence techniques

International Nuclear Information System (INIS)

Figedy, Stefan; Smiesko, Ivan

2012-01-01

This article provides brief information about the fundamental features of a newly-developed diagnostic system for early detection and identification of anomalies being generated in water chemistry regime of the primary and secondary circuit of the VVER-440 reactor. This system, which is called SACHER (System of Analysis of CHEmical Regime), was installed within the major modernization project at the NPP-V2 Bohunice in the Slovak Republic. The SACHER system has been fully developed on MATLAB environment. It is based on computational intelligence techniques and inserts various elements of intelligent data processing modules for clustering, diagnosing, future prediction, signal validation, etc, into the overall chemical information system. The application of SACHER would essentially assist chemists to identify the current situation regarding anomalies being generated in the primary and secondary circuit water chemistry. This system is to be used for diagnostics and data handling, however it is not intended to fully replace the presence of experienced chemists to decide upon corrective actions. (author)

Psychometric intelligence and P3 of the event-related potentials studied with a 3-stimulus auditory oddball task

NARCIS (Netherlands)

Wronka, E.A.; Kaiser, J.; Coenen, A.M.L.

2013-01-01

Relationship between psychometric intelligence measured with Raven's Advanced Progressive Matrices (RAPM) and event-related potentials (ERP) was examined using 3-stimulus oddball task. Subjects who had scored higher on RAPM exhibited larger amplitude of P3a component. Additional analysis using the

Intelligence and P3 Components of the Event-Related Potential Elicited during an Auditory Discrimination Task with Masking

Science.gov (United States)

De Pascalis, V.; Varriale, V.; Matteoli, A.

2008-01-01

The relationship between fluid intelligence (indexed by scores on Raven Progressive Matrices) and auditory discrimination ability was examined by recording event-related potentials from 48 women during the performance of an auditory oddball task with backward masking. High ability (HA) subjects exhibited shorter response times, greater response…

Self-Learning Embedded System for Object Identification in Intelligent Infrastructure Sensors.

Science.gov (United States)

Villaverde, Monica; Perez, David; Moreno, Felix

2015-11-17

The emergence of new horizons in the field of travel assistant management leads to the development of cutting-edge systems focused on improving the existing ones. Moreover, new opportunities are being also presented since systems trend to be more reliable and autonomous. In this paper, a self-learning embedded system for object identification based on adaptive-cooperative dynamic approaches is presented for intelligent sensor's infrastructures. The proposed system is able to detect and identify moving objects using a dynamic decision tree. Consequently, it combines machine learning algorithms and cooperative strategies in order to make the system more adaptive to changing environments. Therefore, the proposed system may be very useful for many applications like shadow tolls since several types of vehicles may be distinguished, parking optimization systems, improved traffic conditions systems, etc.

Self-Learning Embedded System for Object Identification in Intelligent Infrastructure Sensors

Directory of Open Access Journals (Sweden)

Monica Villaverde

2015-11-01

Full Text Available The emergence of new horizons in the field of travel assistant management leads to the development of cutting-edge systems focused on improving the existing ones. Moreover, new opportunities are being also presented since systems trend to be more reliable and autonomous. In this paper, a self-learning embedded system for object identification based on adaptive-cooperative dynamic approaches is presented for intelligent sensor’s infrastructures. The proposed system is able to detect and identify moving objects using a dynamic decision tree. Consequently, it combines machine learning algorithms and cooperative strategies in order to make the system more adaptive to changing environments. Therefore, the proposed system may be very useful for many applications like shadow tolls since several types of vehicles may be distinguished, parking optimization systems, improved traffic conditions systems, etc.

Identification of Age, Temperature and Radiation Effect on Ferritic Steel Microstructure Based on Artificial Intelligence

International Nuclear Information System (INIS)

Mike Susmikanti; Entin Hartini; Antonius Sitompul

2008-01-01

In the construction of nuclear installation, it is important to know the material condition used on it. Considering mechanical properties of these materials, there are some material change affected by ageing, temperature and radiation. For some years, austenitic stainless steel are used as a fuel cladding in fast breeder reactor. However this material will not sufficiently competitive from economic point of view for the next year. Experiment result on ferritic steel gave information of stronger structural properties compared to austenitic stainless steel. Modeling and simulation will support further identification of this material changing caused by such effects. Pattern recognition of these changes base on artificial intelligence is expected to support the research and development activities on nuclear structure materials. Material structure pattern of these materials, observed by SEM, are converted using image processing system. Its characteristic is then analyzed with principal component using perception method, which usually used on identifying and learning neural network system based on artificial intelligence. Specific design and input are needed to identify the change of material structure pattern before and after any applied effect. In this paper, simulation of changing identification on three types ferritic steel F17(17 Cr), EM 12 (9 CR-2 MoNbV), and EMI 0 (9 Cr-I Mo) were done. The microstructure data before and after effect are taken from some references. The whole pattern recognition process are done using MATLAB software package. (author)

The application of artificial intelligence for the identification of the maceral groups and mineral components of coal

Science.gov (United States)

Mlynarczuk, Mariusz; Skiba, Marta

2017-06-01

The correct and consistent identification of the petrographic properties of coal is an important issue for researchers in the fields of mining and geology. As part of the study described in this paper, investigations concerning the application of artificial intelligence methods for the identification of the aforementioned characteristics were carried out. The methods in question were used to identify the maceral groups of coal, i.e. vitrinite, inertinite, and liptinite. Additionally, an attempt was made to identify some non-organic minerals. The analyses were performed using pattern recognition techniques (NN, kNN), as well as artificial neural network techniques (a multilayer perceptron - MLP). The classification process was carried out using microscopy images of polished sections of coals. A multidimensional feature space was defined, which made it possible to classify the discussed structures automatically, based on the methods of pattern recognition and algorithms of the artificial neural networks. Also, from the study we assessed the impact of the parameters for which the applied methods proved effective upon the final outcome of the classification procedure. The result of the analyses was a high percentage (over 97%) of correct classifications of maceral groups and mineral components. The paper discusses also an attempt to analyze particular macerals of the inertinite group. It was demonstrated that using artificial neural networks to this end makes it possible to classify the macerals properly in over 91% of cases. Thus, it was proved that artificial intelligence methods can be successfully applied for the identification of selected petrographic features of coal.

Education for All: Gardner's Multiple Intelligences Theory

Directory of Open Access Journals (Sweden)

Gisela Emst-Slavit

2001-12-01

Full Text Available In the last years the Theory of the Multiple Intelligences developed by Howard Gardner has had a tremendous impact in elementary and secondary classrooms in the United States. Gardner(1983 defines intelligence as the ability to solve a problem or fashion a product that is valued in one or more cultural settings. His definition expands our understanding of "intelligence" beyond the familiar linguistic and Logical-mathematical intelligences, to include the spatial, musical,bodily-kinesthetic, naturalist. interpersonal, and intrapersonal intelligences. This new wayof conceptualizing human intelligence has profound implications for educators whose task needs to include the identification and nourishment of the different talents brought by al students.

The ADEPT Framework for Intelligent Autonomy

National Research Council Canada - National Science Library

Ricard, Michael; Kolitz, Stephan

2003-01-01

...) architecture for intelligent autonomy. Intelligent autonomy is the ability to plan and execute complex activities in a manner that provides rapid, effective response to stochastic and dynamic mission events...

Intelligent Agents in E-Commerce

OpenAIRE

Valentin LITOIU; Amelia BADICA; Cristian ETEGAN

2006-01-01

This paper emphasizes the importance of intelligent agents in e-commerce, with a particular focus on the B2C and B2B context. From the consumer buying behaviour perspective, agents can be used to assist the following stages: need identification, product brokering, buyer coalition formation, merchant brokering and negotiation. Related to B2B commerce, intelligent agents are involved in partnership formation, brokering and negotiation.

Use of a Generic Identification Scheme Connecting Events and Detector Description in the ATLAS Experiment

CERN Document Server

Arnault, C.

2003-01-01

High energy physics detectors can be described hierarchically from the different subsystems to their divisions in r, phi, theta and to the individual readout channels. An identification schema that follows the logical decomposition of the ATLAS detector has been introduced allowing identification of individual readout channels as well as other parts of the detector, in particular detector elements. These identifiers provide a sort of ?glue? allowing, for example, the connection of raw event data to their detector description for position calculation or alignment corrections, as well as fast access to subsets of the event data for event trigger selection. There are two important requirements on the software to support such an identification scheme. First is the possibility to formally specify these identifiers in terms of their structure and allowed values. And second is to generate different forms of the identifiers optimised in terms of access efficiency to information content, compactness or search key effi...

A Review of Intelligent Driving Style Analysis Systems and Related Artificial Intelligence Algorithms.

Science.gov (United States)

Meiring, Gys Albertus Marthinus; Myburgh, Hermanus Carel

2015-12-04

In this paper the various driving style analysis solutions are investigated. An in-depth investigation is performed to identify the relevant machine learning and artificial intelligence algorithms utilised in current driver behaviour and driving style analysis systems. This review therefore serves as a trove of information, and will inform the specialist and the student regarding the current state of the art in driver style analysis systems, the application of these systems and the underlying artificial intelligence algorithms applied to these applications. The aim of the investigation is to evaluate the possibilities for unique driver identification utilizing the approaches identified in other driver behaviour studies. It was found that Fuzzy Logic inference systems, Hidden Markov Models and Support Vector Machines consist of promising capabilities to address unique driver identification algorithms if model complexity can be reduced.

Identification and localization of neutrino events in the OPERA detector

International Nuclear Information System (INIS)

Heritier, C.

2004-07-01

The OPERA experiment is designed for the appearance search of ν μ → ν τ oscillations in the parameters indicated by the atmospheric neutrino anomaly. To prove the appearance of ν τ at 732 km from the CERN, an hybrid detector is under construction at the Gran Sasso laboratory. The target, composed by bricks made of lead plates and emulsion sheets, allows the direct observation of the τ lepton produced in ν τ charged current interactions. The tracking, the localization of neutrino events in the target and the muon identification are allowed by trackers located inside the target (scintillators) and in the spectrometer following the target (RPC). The development of algorithms, based on electronic detectors, is necessary to identify the neutrino interaction and to locate the bricks where the interaction occurred. A classification of neutrino events is performed using the identification of the muon produced in ν μ CC and ν τ CC with τ → μ decay. This classification is optimised with tracking informations and also with topological and calorimetric parameters which describe the nature of the interaction (quasi-elastic, deep inelastic); the algorithm of the localization of neutrino event is performed for each category. A tridimensional brick probability map is built and can be exploited to implement sophisticated extraction brick strategies. To conclude, a feasibility study of a test beam experiment OPERETTE is presented. The project was to install a similar OPERA detector in the COMPASS neutrino beam, in the CERN North Area. It was a good opportunity to prepare OPERA for the scanning emulsion films with neutrino events and to test the analysis procedures. (author)

Intelligent Agents in E-Commerce

Directory of Open Access Journals (Sweden)

Valentin LITOIU

2006-01-01

Full Text Available This paper emphasizes the importance of intelligent agents in e-commerce, with a particular focus on the B2C and B2B context. From the consumer buying behaviour perspective, agents can be used to assist the following stages: need identification, product brokering, buyer coalition formation, merchant brokering and negotiation. Related to B2B commerce, intelligent agents are involved in partnership formation, brokering and negotiation.

The identification and rejection of energy-degraded events in gas ionization counters

International Nuclear Information System (INIS)

Ophel, T.R.; Fifield, L.K.; Catford, W.N.; Orr, N.A.; Woods, C.L.; Harding, A.; Clarkson, G.P.

1988-05-01

A common feature of the measurement of charged particles with gas detectors is the presence of a small fraction of events (∼0.1-0.2%) for which significantly less than total ionization is recorded. These events cause an energy tailing that can seriously impair the identification functions of gas detectors used either to instrument the focal plane of magnetic spectrometers or for accelerator mass spectrometry. The anomalous, energy-degraded events are shown to arise both from reactions between the incident ions and the detector gas and, more importantly from the scattering of ions by the gas. It is demonstrated that an appropriate detector configuration provides the means to reject most of the anomalous events, allowing the measurement of very low cross-section reactions without significant background interference from such events

A Review of Intelligent Driving Style Analysis Systems and Related Artificial Intelligence Algorithms

Directory of Open Access Journals (Sweden)

Gys Albertus Marthinus Meiring

2015-12-01

Full Text Available In this paper the various driving style analysis solutions are investigated. An in-depth investigation is performed to identify the relevant machine learning and artificial intelligence algorithms utilised in current driver behaviour and driving style analysis systems. This review therefore serves as a trove of information, and will inform the specialist and the student regarding the current state of the art in driver style analysis systems, the application of these systems and the underlying artificial intelligence algorithms applied to these applications. The aim of the investigation is to evaluate the possibilities for unique driver identification utilizing the approaches identified in other driver behaviour studies. It was found that Fuzzy Logic inference systems, Hidden Markov Models and Support Vector Machines consist of promising capabilities to address unique driver identification algorithms if model complexity can be reduced.

Power quality event classification: an overview and key issues ...

African Journals Online (AJOL)

... used for PQ events' classifications. Various artificial intelligent techniques which are used in PQ event classification are also discussed. Major Key issues and challenges in classifying PQ events are critically examined and outlined. Keywords: Power quality, PQ event classifiers, artificial intelligence techniques, PQ noise, ...

Intelligent Approach for Analysis of Respiratory Signals and Oxygen Saturation in the Sleep Apnea/Hypopnea Syndrome

Science.gov (United States)

Moret-Bonillo, Vicente; Alvarez-Estévez, Diego; Fernández-Leal, Angel; Hernández-Pereira, Elena

2014-01-01

This work deals with the development of an intelligent approach for clinical decision making in the diagnosis of the Sleep Apnea/Hypopnea Syndrome, SAHS, from the analysis of respiratory signals and oxygen saturation in arterial blood, SaO2. In order to accomplish the task the proposed approach makes use of different artificial intelligence techniques and reasoning processes being able to deal with imprecise data. These reasoning processes are based on fuzzy logic and on temporal analysis of the information. The developed approach also takes into account the possibility of artifacts in the monitored signals. Detection and characterization of signal artifacts allows detection of false positives. Identification of relevant diagnostic patterns and temporal correlation of events is performed through the implementation of temporal constraints. PMID:25035712

Identification of unusual events in multi-channel bridge monitoring data

Science.gov (United States)

Omenzetter, Piotr; Brownjohn, James Mark William; Moyo, Pilate

2004-03-01

Continuously operating instrumented structural health monitoring (SHM) systems are becoming a practical alternative to replace visual inspection for assessment of condition and soundness of civil infrastructure such as bridges. However, converting large amounts of data from an SHM system into usable information is a great challenge to which special signal processing techniques must be applied. This study is devoted to identification of abrupt, anomalous and potentially onerous events in the time histories of static, hourly sampled strains recorded by a multi-sensor SHM system installed in a major bridge structure and operating continuously for a long time. Such events may result, among other causes, from sudden settlement of foundation, ground movement, excessive traffic load or failure of post-tensioning cables. A method of outlier detection in multivariate data has been applied to the problem of finding and localising sudden events in the strain data. For sharp discrimination of abrupt strain changes from slowly varying ones wavelet transform has been used. The proposed method has been successfully tested using known events recorded during construction of the bridge, and later effectively used for detection of anomalous post-construction events.

Cultural intelligence: A research landscape

DEFF Research Database (Denmark)

Alon, Ilan; Lankut, Erik; Richter, Nicole Franziska

Purpose: This study identifies reviews the most influential literature streams to cultural intelligence by a bibliometric citation analysis and provides recommendations for future research. Design/methodology/approach: Three bibliometric citation tools are used to analyse a sample of 357 articles...... by 823 scholars in 199 different journals published between 1992-2017. Findings: The analysis reveals 10 research clusters within the topic of cultural intelligence and anables the identification of future research within and at the intercept of clusters....

An analysis of the application of AI to the development of intelligent aids for flight crew tasks

Science.gov (United States)

Baron, S.; Feehrer, C.

1985-01-01

This report presents the results of a study aimed at developing a basis for applying artificial intelligence to the flight deck environment of commercial transport aircraft. In particular, the study was comprised of four tasks: (1) analysis of flight crew tasks, (2) survey of the state-of-the-art of relevant artificial intelligence areas, (3) identification of human factors issues relevant to intelligent cockpit aids, and (4) identification of artificial intelligence areas requiring further research.

Building an intelligence-led security program

CERN Document Server

Liska, Allan

2014-01-01

As recently as five years ago, securing a network meant putting in a firewall, intrusion detection system, and installing antivirus software on the desktop. Unfortunately, attackers have grown more nimble and effective, meaning that traditional security programs are no longer effective. Today's effective cyber security programs take these best practices and overlay them with intelligence. Adding cyber threat intelligence can help security teams uncover events not detected by traditional security platforms and correlate seemingly disparate events across the network. Properly-implemented inte

Crowdedness Mediates the Effect of Social Identification on Positive Emotion in a Crowd: A Survey of Two Crowd Events

Science.gov (United States)

Novelli, David; Drury, John; Reicher, Stephen; Stott, Clifford

2013-01-01

Exposure to crowding is said to be aversive, yet people also seek out and enjoy crowded situations. We surveyed participants at two crowd events to test the prediction of self-categorization theory that variable emotional responses to crowding are a function of social identification with the crowd. In data collected from participants who attended a crowded outdoor music event (n = 48), identification with the crowd predicted feeling less crowded; and there was an indirect effect of identification with the crowd on positive emotion through feeling less crowded. Identification with the crowd also moderated the relation between feeling less crowded and positive emotion. In data collected at a demonstration march (n = 112), identification with the crowd predicted central (most dense) location in the crowd; and there was an indirect effect of identification with the crowd on positive emotion through central location in the crowd. Positive emotion in the crowd also increased over the duration of the crowd event. These findings are in line with the predictions of self-categorization theory. They are inconsistent with approaches that suggest that crowding is inherently aversive; and they cannot easily be explained through the concept of ‘personal space’. PMID:24236079

Crowdedness mediates the effect of social identification on positive emotion in a crowd: a survey of two crowd events.

Directory of Open Access Journals (Sweden)

David Novelli

Full Text Available Exposure to crowding is said to be aversive, yet people also seek out and enjoy crowded situations. We surveyed participants at two crowd events to test the prediction of self-categorization theory that variable emotional responses to crowding are a function of social identification with the crowd. In data collected from participants who attended a crowded outdoor music event (n = 48, identification with the crowd predicted feeling less crowded; and there was an indirect effect of identification with the crowd on positive emotion through feeling less crowded. Identification with the crowd also moderated the relation between feeling less crowded and positive emotion. In data collected at a demonstration march (n = 112, identification with the crowd predicted central (most dense location in the crowd; and there was an indirect effect of identification with the crowd on positive emotion through central location in the crowd. Positive emotion in the crowd also increased over the duration of the crowd event. These findings are in line with the predictions of self-categorization theory. They are inconsistent with approaches that suggest that crowding is inherently aversive; and they cannot easily be explained through the concept of 'personal space'.

Does high intelligence improve prognosis? The association of intelligence with recurrence and mortality among Swedish men with coronary heart disease.

Science.gov (United States)

Sörberg Wallin, Alma; Falkstedt, Daniel; Allebeck, Peter; Melin, Bo; Janszky, Imre; Hemmingsson, Tomas

2015-04-01

Lower intelligence early in life is associated with increased risks for coronary heart disease (CHD) and mortality. Intelligence level might affect compliance to treatment but its prognostic importance in patients with CHD is unknown. A cohort of 1923 Swedish men with a measure of intelligence from mandatory military conscription in 1969-1970 at age 18-20, who were diagnosed with CHD 1991-2007, were followed to the end of 2008. recurrent CHD event. Secondary outcome: case fatality from the first event, cardiovascular and all-cause mortality. National registers provided information on CHD events, comorbidity, mortality and socioeconomic factors. The fully adjusted HRs for recurrent CHD for medium and low intelligence, compared with high intelligence, were 0.98, (95% CIs 0.83 to 1.16) and 1.09 (0.89 to 1.34), respectively. The risks were increased for cardiovascular and all-cause mortality with lower intelligence, but were attenuated in the fully adjusted models (fully adjusted HRs for cardiovascular mortality 1.92 (0.94 to 3.94) and 1.98 (0.89 to 4.37), respectively; for all-cause mortality 1.63 (1.00 to 2.65) and 1.62 (0.94 to 2.78), respectively). There was no increased risk for case-fatality at the first event (fully adjusted ORs 1.06 (0.73 to 1.55) and 0.97 (0.62 to 1.50), respectively). Although we found lower intelligence to be associated with increased mortality in middle-aged men with CHD, there was no evidence for its possible effect on recurrence in CHD. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

[Intelligence and irritable bowel syndrome].

Science.gov (United States)

Díaz-Rubio García, Manuel

2006-01-01

The Syndrome of Irritable Intestine (SII) is a chronic functional dysfunction that it is characterized by abdominal pain and changes of intestinal rhythm without demonstrable organic alteration. It is avery prevelent dysfunction in the developed countries, there being involved in its physiopathology, among other, the psychosocial factors (illness behavior, social situation, stress, vital events, neuroticism, anxiety and somatization). However no study has been carried out on the Rational Intelligence and Experiential Intelligence or Constructive Thought in patient with SII in spite of knowing that the cognitive processes participate in its genesis. On the hypothesis that the patients with SII would have an experiencial intelligence smaller that the fellows controls, 100 cases of SII and 100 controls have been studied, being excluded of both patients groups with intellectual deficit or psychiatric illness in the last year. The cases of SII were distributed in two groups, one of 50 cases that habitually consulted with the doctor and other 50 that didn't make it. All the participants completed specific tests to evaluate all the psychological factors and Rational Intelligence and the Constructive Thought. The results show an alteration of the psychological factors in the SII, expressed by the antecedents of vital events, m even significant of anxiety feature and anxiety and a neuroticism statistically significant. As for Rational Intelligence and Experiential Intelligence in the SII, it was observed that to Rational Intelligence is same in the patients with SII that in the controls. Only in the group of SII that habitually consulted with the doctor a slightly significant decrease of the intellectual coefficient it was observed. As for the Experiential Intelligence a significant decrease of the Constructive Thought was observed in the patients with SII in comparison with the group control. Of their components a decrease of the emotionality exists and of the

Artificial Intelligence Assists Ultrasonic Inspection

Science.gov (United States)

Schaefer, Lloyd A.; Willenberg, James D.

1992-01-01

Subtle indications of flaws extracted from ultrasonic waveforms. Ultrasonic-inspection system uses artificial intelligence to help in identification of hidden flaws in electron-beam-welded castings. System involves application of flaw-classification logic to analysis of ultrasonic waveforms.

Evaluation of Epidemic Intelligence Systems Integrated in the Early Alerting and Reporting Project for the Detection of A/H5N1 Influenza Events

Science.gov (United States)

Barboza, Philippe; Vaillant, Laetitia; Mawudeku, Abla; Nelson, Noele P.; Hartley, David M.; Madoff, Lawrence C.; Linge, Jens P.; Collier, Nigel; Brownstein, John S.; Yangarber, Roman; Astagneau, Pascal; on behalf of the Early Alerting, Reporting Project of the Global Health Security Initiative

2013-01-01

The objective of Web-based expert epidemic intelligence systems is to detect health threats. The Global Health Security Initiative (GHSI) Early Alerting and Reporting (EAR) project was launched to assess the feasibility and opportunity for pooling epidemic intelligence data from seven expert systems. EAR participants completed a qualitative survey to document epidemic intelligence strategies and to assess perceptions regarding the systems performance. Timeliness and sensitivity were rated highly illustrating the value of the systems for epidemic intelligence. Weaknesses identified included representativeness, completeness and flexibility. These findings were corroborated by the quantitative analysis performed on signals potentially related to influenza A/H5N1 events occurring in March 2010. For the six systems for which this information was available, the detection rate ranged from 31% to 38%, and increased to 72% when considering the virtual combined system. The effective positive predictive values ranged from 3% to 24% and F1-scores ranged from 6% to 27%. System sensitivity ranged from 38% to 72%. An average difference of 23% was observed between the sensitivities calculated for human cases and epizootics, underlining the difficulties in developing an efficient algorithm for a single pathology. However, the sensitivity increased to 93% when the virtual combined system was considered, clearly illustrating complementarities between individual systems. The average delay between the detection of A/H5N1 events by the systems and their official reporting by WHO or OIE was 10.2 days (95% CI: 6.7–13.8). This work illustrates the diversity in implemented epidemic intelligence activities, differences in system's designs, and the potential added values and opportunities for synergy between systems, between users and between systems and users. PMID:23472077

Evaluation of epidemic intelligence systems integrated in the early alerting and reporting project for the detection of A/H5N1 influenza events.

Directory of Open Access Journals (Sweden)

Philippe Barboza

Full Text Available The objective of Web-based expert epidemic intelligence systems is to detect health threats. The Global Health Security Initiative (GHSI Early Alerting and Reporting (EAR project was launched to assess the feasibility and opportunity for pooling epidemic intelligence data from seven expert systems. EAR participants completed a qualitative survey to document epidemic intelligence strategies and to assess perceptions regarding the systems performance. Timeliness and sensitivity were rated highly illustrating the value of the systems for epidemic intelligence. Weaknesses identified included representativeness, completeness and flexibility. These findings were corroborated by the quantitative analysis performed on signals potentially related to influenza A/H5N1 events occurring in March 2010. For the six systems for which this information was available, the detection rate ranged from 31% to 38%, and increased to 72% when considering the virtual combined system. The effective positive predictive values ranged from 3% to 24% and F1-scores ranged from 6% to 27%. System sensitivity ranged from 38% to 72%. An average difference of 23% was observed between the sensitivities calculated for human cases and epizootics, underlining the difficulties in developing an efficient algorithm for a single pathology. However, the sensitivity increased to 93% when the virtual combined system was considered, clearly illustrating complementarities between individual systems. The average delay between the detection of A/H5N1 events by the systems and their official reporting by WHO or OIE was 10.2 days (95% CI: 6.7-13.8. This work illustrates the diversity in implemented epidemic intelligence activities, differences in system's designs, and the potential added values and opportunities for synergy between systems, between users and between systems and users.

Evaluation of epidemic intelligence systems integrated in the early alerting and reporting project for the detection of A/H5N1 influenza events.

Science.gov (United States)

Barboza, Philippe; Vaillant, Laetitia; Mawudeku, Abla; Nelson, Noele P; Hartley, David M; Madoff, Lawrence C; Linge, Jens P; Collier, Nigel; Brownstein, John S; Yangarber, Roman; Astagneau, Pascal

2013-01-01

The objective of Web-based expert epidemic intelligence systems is to detect health threats. The Global Health Security Initiative (GHSI) Early Alerting and Reporting (EAR) project was launched to assess the feasibility and opportunity for pooling epidemic intelligence data from seven expert systems. EAR participants completed a qualitative survey to document epidemic intelligence strategies and to assess perceptions regarding the systems performance. Timeliness and sensitivity were rated highly illustrating the value of the systems for epidemic intelligence. Weaknesses identified included representativeness, completeness and flexibility. These findings were corroborated by the quantitative analysis performed on signals potentially related to influenza A/H5N1 events occurring in March 2010. For the six systems for which this information was available, the detection rate ranged from 31% to 38%, and increased to 72% when considering the virtual combined system. The effective positive predictive values ranged from 3% to 24% and F1-scores ranged from 6% to 27%. System sensitivity ranged from 38% to 72%. An average difference of 23% was observed between the sensitivities calculated for human cases and epizootics, underlining the difficulties in developing an efficient algorithm for a single pathology. However, the sensitivity increased to 93% when the virtual combined system was considered, clearly illustrating complementarities between individual systems. The average delay between the detection of A/H5N1 events by the systems and their official reporting by WHO or OIE was 10.2 days (95% CI: 6.7-13.8). This work illustrates the diversity in implemented epidemic intelligence activities, differences in system's designs, and the potential added values and opportunities for synergy between systems, between users and between systems and users.

Intelligent identification of remnant ridge edges in region west of Yongxing Island, South China Sea

Science.gov (United States)

Wang, Weiwei; Guo, Jing; Cai, Guanqiang; Wang, Dawei

2018-02-01

Edge detection enables identification of geomorphologic unit boundaries and thus assists with geomorphical mapping. In this paper, an intelligent edge identification method is proposed and image processing techniques are applied to multi-beam bathymetry data. To accomplish this, a color image is generated by the bathymetry, and a weighted method is used to convert the color image to a gray image. As the quality of the image has a significant influence on edge detection, different filter methods are applied to the gray image for de-noising. The peak signal-to-noise ratio and mean square error are calculated to evaluate which filter method is most appropriate for depth image filtering and the edge is subsequently detected using an image binarization method. Traditional image binarization methods cannot manage the complicated uneven seafloor, and therefore a binarization method is proposed that is based on the difference between image pixel values; the appropriate threshold for image binarization is estimated according to the probability distribution of pixel value differences between two adjacent pixels in horizontal and vertical directions, respectively. Finally, an eight-neighborhood frame is adopted to thin the binary image, connect the intermittent edge, and implement contour extraction. Experimental results show that the method described here can recognize the main boundaries of geomorphologic units. In addition, the proposed automatic edge identification method avoids use of subjective judgment, and reduces time and labor costs.

Emotions and trait emotional intelligence among ultra-endurance runners.

Science.gov (United States)

Lane, Andrew M; Wilson, Mathew

2011-07-01

The aim of this study was to investigate relationships between trait emotional intelligence and emotional state changes over the course of an ultra-endurance foot race covering a route of approximately 175 miles (282 km) and held in set stages over six days. A repeated measures field design that sought to maintain ecological validity was used. Trait emotional intelligence was defined as a relatively stable concept that should predict adaptive emotional states experienced over the duration of the race and therefore associate with pleasant emotions during a 6-stage endurance event. Thirty-four runners completed a self-report measure of trait emotional intelligence before the event started. Participants reported emotional states before and after each of the six races. Repeated measures ANOVA results showed significant variations in emotions over time and a main effect for trait emotional intelligence. Runners high in self-report trait emotional intelligence also reported higher pleasant and lower unpleasant emotions than runners low in trait emotional intelligence. Findings lend support to the notion that trait emotional intelligence associates with adaptive psychological states, suggesting that it may be a key individual difference that explains why some athletes respond to repeated bouts of hard exercise better than others. Future research should test the effectiveness of interventions designed to enhance trait emotional intelligence and examine the attendant impact on emotional responses to intense exercise during multi-stage events. Copyright © 2011. Published by Elsevier Ltd.

Identification of Common Cause Initiating Events Using the NEA IRS Database. Rev 0

International Nuclear Information System (INIS)

Kulig, Maciej; Tomic, Bojan; Nyman, R alph

2007-02-01

The study presented in this report is a continuation of work conducted for SKI in 1998 on the identification of Common Cause Initiators (CCIs) based on operational events documented in the NEA Incident Reporting System (IRS). Based on the new operational experience accumulated in IRS in the period 1995-2006, the project focused on the identification of new CCI events. An attempt was also made to compare the observations made in the earlier study with the results of the current work. The earlier study and the current project cover the events reported in the IRS database with the incident date in the period from 01.01.1980 to 15.11.2006. The review of the NEA IRS database conducted within this project generated a sample of events that provides insights regarding the Common Cause Initiators (CCIs). This list includes certain number of 'real' CCIs but also potential CCIs and other events that provide insights on potential dependency mechanisms. Relevant characteristics of the events were analysed in the context of CCIs. This evaluation was intended to investigate the importance of the CCI issue and also to provide technical insights that could help in the modelling the CCIs in PSAs. The analysis of operational events provided useful engineering insights regarding the potential dependencies that may originate CCIs. Some indications were also obtained on the plant SSCs/areas that are susceptible to common cause failures. Direct interrelations between the accident mitigation systems through common support systems, which can originate a CCI, represent a dominant dependency mechanism involved in the CCI events. The most important contributors of this type are electrical power supply systems and I-and-C systems. Area-related events (fire, flood, water spray), external hazards (lightning, high wind or cold weather) and transients (water hammer, electrical transients both internal and external) have also been found to be important sources of dependency that may originate CCIs

Identification of Common Cause Initiating Events Using the NEA IRS Database. Rev 0

Energy Technology Data Exchange (ETDEWEB)

Kulig, Maciej; Tomic, Bojan (Enconet Consulting, Vienna (Austria)); Nyman, Ralph (Swedish Nuclear Power Inspectorate, Stockholm (Sweden))

2007-02-15

The study presented in this report is a continuation of work conducted for SKI in 1998 on the identification of Common Cause Initiators (CCIs) based on operational events documented in the NEA Incident Reporting System (IRS). Based on the new operational experience accumulated in IRS in the period 1995-2006, the project focused on the identification of new CCI events. An attempt was also made to compare the observations made in the earlier study with the results of the current work. The earlier study and the current project cover the events reported in the IRS database with the incident date in the period from 01.01.1980 to 15.11.2006. The review of the NEA IRS database conducted within this project generated a sample of events that provides insights regarding the Common Cause Initiators (CCIs). This list includes certain number of 'real' CCIs but also potential CCIs and other events that provide insights on potential dependency mechanisms. Relevant characteristics of the events were analysed in the context of CCIs. This evaluation was intended to investigate the importance of the CCI issue and also to provide technical insights that could help in the modelling the CCIs in PSAs. The analysis of operational events provided useful engineering insights regarding the potential dependencies that may originate CCIs. Some indications were also obtained on the plant SSCs/areas that are susceptible to common cause failures. Direct interrelations between the accident mitigation systems through common support systems, which can originate a CCI, represent a dominant dependency mechanism involved in the CCI events. The most important contributors of this type are electrical power supply systems and I-and-C systems. Area-related events (fire, flood, water spray), external hazards (lightning, high wind or cold weather) and transients (water hammer, electrical transients both internal and external) have also been found to be important sources of dependency that may

Muon Reconstruction and Identification for the Event Filter of the ATLAS experiment

CERN Document Server

Ventura, A; Armstrong, S; Baines, J T M; Bee, C P; Bellomo, M; Biglietti, M; Bogaerts, J A C; Bosman, M; Carlino, G; Caron, B; Casado, M P; Cataldi, G; Cavalli, D; Comune, G; Conde, P; Conventi, F; Crone, G; Damazio, D; De Santo, A; Díaz-Gómez, M; Di Mattia, A; Ellis, Nick; Emeliyanov, D; Epp, B; Falciano, S; Garitaonandia, H; George, S; Ghete, V; Goncalo, R; Gorini, E; Grancagnolo, S; Haller, J; Kabana, S; Khomich, A; Kilvington, G; Kirk, N; Konstantinidis, N P; Kootz, A; Lankford, A J; Lowe, A; Luminari, L; Maeno, T; Masik, J; Meessen, C; Mello, A G; Moore, R; Morettini, P; Negri, A; Nikitin, N; Nisati, A; Osuna, C; Padilla, C; Panikashvili, N; Parodi, F; Pasqualucci, E; Pérez-Réale, V; Pinfold, J L; Pinto, P; Primavera, M; Qian, Z; Resconi, S; Rosati, S; Sánchez, C; Santamarina-Rios, C; Scannicchio, D A; Schiavi, C; Segura, E; De Seixas, J M; Sidoti, A; Siragusa, G; Sivoklokov, S Yu; Sobreira, A; Soluk, R A; Spagnolo, S; Stefanidis, E; Sushkov, S; Sutton, M; Tapprogge, S; Tarem, S; Thomas, E; Touchard, F; Usai, G; Venda-Pinto, B; Vercesi, V; Wengler, T; Werner, P; Wheeler, S J; Wickens, F J; Wiedenmann, W; Wielers, M; Zobernig, G; 9th ICATPP Conference on Astroparticle, Particle, Space Physics, Detectors and Medical Physics Applications

2005-01-01

The ATLAS Trigger requires high efficiency and selectivity in order to keep the full physics potential of the experiment and to reject uninteresting processes from the 40 MHz event production rate of the LHC. These goals are achieved with a trigger composed of three sequential levels of increasing accuracy that have to reduce the output event rate down to ~100 Hz. This work focuses on muon reconstruction and identification for the third level (Event Filter), for which specific algorithms from the off-line environment have been adapted to work in the trigger framework. Two different strategies for accessing data (wrapped and seeded modes) are described and their reconstruction potential is then shown in terms of efficiencies, resolutions and fake muon rejection power.

Intelligent Distributed Computing VI : Proceedings of the 6th International Symposium on Intelligent Distributed Computing

CERN Document Server

Badica, Costin; Malgeri, Michele; Unland, Rainer

2013-01-01

This book represents the combined peer-reviewed proceedings of the Sixth International Symposium on Intelligent Distributed Computing -- IDC~2012, of the International Workshop on Agents for Cloud -- A4C~2012 and of the Fourth International Workshop on Multi-Agent Systems Technology and Semantics -- MASTS~2012. All the events were held in Calabria, Italy during September 24-26, 2012. The 37 contributions published in this book address many topics related to theory and applications of intelligent distributed computing and multi-agent systems, including: adaptive and autonomous distributed systems, agent programming, ambient assisted living systems, business process modeling and verification, cloud computing, coalition formation, decision support systems, distributed optimization and constraint satisfaction, gesture recognition, intelligent energy management in WSNs, intelligent logistics, machine learning, mobile agents, parallel and distributed computational intelligence, parallel evolutionary computing, trus...

Vibrotactile Detection, Identification and Directional Perception of signal-Processed Sounds from Environmental Events: A Pilot Field Evaluation in Five Cases

Directory of Open Access Journals (Sweden)

Parivash Ranjbar

2008-09-01

Full Text Available Objectives: Conducting field tests of a vibrotactile aid for deaf/deafblind persons for detection, identification and directional perception of environmental sounds. Methods: Five deaf (3F/2M, 22–36 years individuals tested the aid separately in a home environment (kitchen and in a traffic environment. Their eyes were blindfolded and they wore a headband and holding a vibrator for sound identification. In the headband, three microphones were mounted and two vibrators for signalling direction of the sound source. The sounds originated from events typical for the home environment and traffic. The subjects were inexperienced (events unknown and experienced (events known. They identified the events in a home and traffic environment, but perceived sound source direction only in traffic. Results: The detection scores were higher than 98% both in the home and in the traffic environment. In the home environment, identification scores varied between 25%-58% when the subjects were inexperienced and between 33%-83% when they were experienced. In traffic, identification scores varied between 20%-40% when the subjects were inexperienced and between 22%-56% when they were experienced. The directional perception scores varied between 30%-60% when inexperienced and between 61%-83% when experienced. Discussion: The vibratory aid consistently improved all participants’ detection, identification and directional perception ability.

FY1995 four-terminal-device intelligent LSI system for real-time event recognition; 1995 nendo shunji ninshiki kino wo motta 4 tanshi device chino LSI no kenkyu

Energy Technology Data Exchange (ETDEWEB)

NONE

1997-03-01

Development of an intelligent LSI system having real-time response capability for real-word events. This is accomplished by enhancing the functionality of an elemental device, employing ultra-fine-grain parallelism and merging software directly in the LSI hardware. Intelligent functions are created directly on the LSI hardware, thus enabling real-time recognition by electronic systems. The origin of human intelligence lies in the huge memory data base acquired through one's life and the very fast search mechanism to recall the 'most similar' event to the current input. Based on this principle components of intelligent LSI systems have been developed. An analog EEPROM technology capable of storing 256 levels of data per cell without time-consuming write/verify operations has been developed. In situ monitoring of memory content during writing has allowed us high-accuracy data writing. A high-speed parallel-search engine for the minimum distance vector (an associator) has been developed using neuron MOS technology. The associator has been applied to the motion vector detector as an example, which has shown a very fast detection with an extremely simple hardware configuration. The association architecture has been applied to a real-time motion picture compression system, demonstrating three orders of magnitude higher performance than typical CISC processors (Pentium 166MHz). (NEDO)

Genome wide identification of aberrant alternative splicing events in myotonic dystrophy type 2.

Science.gov (United States)

Perfetti, Alessandra; Greco, Simona; Fasanaro, Pasquale; Bugiardini, Enrico; Cardani, Rosanna; Garcia-Manteiga, Jose M; Manteiga, Jose M Garcia; Riba, Michela; Cittaro, Davide; Stupka, Elia; Meola, Giovanni; Martelli, Fabio

2014-01-01

Myotonic dystrophy type 2 (DM2) is a genetic, autosomal dominant disease due to expansion of tetraplet (CCTG) repetitions in the first intron of the ZNF9/CNBP gene. DM2 is a multisystemic disorder affecting the skeletal muscle, the heart, the eye and the endocrine system. According to the proposed pathological mechanism, the expanded tetraplets have an RNA toxic effect, disrupting the splicing of many mRNAs. Thus, the identification of aberrantly spliced transcripts is instrumental for our understanding of the molecular mechanisms underpinning the disease. The aim of this study was the identification of new aberrant alternative splicing events in DM2 patients. By genome wide analysis of 10 DM2 patients and 10 controls (CTR), we identified 273 alternative spliced exons in 218 genes. While many aberrant splicing events were already identified in the past, most were new. A subset of these events was validated by qPCR assays in 19 DM2 and 15 CTR subjects. To gain insight into the molecular pathways involving the identified aberrantly spliced genes, we performed a bioinformatics analysis with Ingenuity system. This analysis indicated a deregulation of development, cell survival, metabolism, calcium signaling and contractility. In conclusion, our genome wide analysis provided a database of aberrant splicing events in the skeletal muscle of DM2 patients. The affected genes are involved in numerous pathways and networks important for muscle physio-pathology, suggesting that the identified variants may contribute to DM2 pathogenesis.

9th International Symposium on Intelligent Distributed Computing

CERN Document Server

Camacho, David; Analide, Cesar; Seghrouchni, Amal; Badica, Costin

2016-01-01

This book represents the combined peer-reviewed proceedings of the ninth International Symposium on Intelligent Distributed Computing – IDC’2015, of the Workshop on Cyber Security and Resilience of Large-Scale Systems – WSRL’2015, and of the International Workshop on Future Internet and Smart Networks – FI&SN’2015. All the events were held in Guimarães, Portugal during October 7th-9th, 2015. The 46 contributions published in this book address many topics related to theory and applications of intelligent distributed computing, including: Intelligent Distributed Agent-Based Systems, Ambient Intelligence and Social Networks, Computational Sustainability, Intelligent Distributed Knowledge Representation and Processing, Smart Networks, Networked Intelligence and Intelligent Distributed Applications, amongst others.

Strategic Mapping of economic intelligence in the public sector of El Salvador

OpenAIRE

Mónica María Cerritos Ascencio

2016-01-01

This study aims to focus on the implementation and development of economic intelligence as a tool for strategic decision making at the governmental level. Likewise, it is also expected that the identification of key players in economic intelligence will allow to create areas of complementarity and coordination to achieve common goals. The document contains a brief summary of economic intelligence today, a theoretical approach to implementation – as economic intelligence should be implemented ...

The Anti-RFI Design of Intelligent Electric Energy Meters with UHF RFID

Science.gov (United States)

Chen, Xiangqun; Huang, Rui; Shen, Liman; chen, Hao; Xiong, Dezhi; Xiao, Xiangqi; Liu, Mouhai; Xu, Renheng

2018-03-01

In order to solve the existing artificial meter reading watt-hour meter industry is still slow and inventory of common problems, using the uhf radio frequency identification (RFID) technology and intelligent watt-hour meter depth fusion, which has a one-time read multiple tags, identification distance, high transmission rate, high reliability, etc, while retaining the original asset management functions, in order to ensure the uhf RFID and minimum impact on the operation of the intelligent watt-hour meter, proposed to improve the stability of the electric meter system while working at the same time, this paper designs the uhf RFID intelligent watt-hour meter radio frequency interference resistance, put forward to improve intelligent watt-hour meter electromagnetic compatibility design train of thought, and introduced its power and the hardware circuit design of printed circuit board, etc.

Plant intelligence

Science.gov (United States)

Lipavská, Helena; Žárský, Viktor

2009-01-01

The concept of plant intelligence, as proposed by Anthony Trewavas, has raised considerable discussion. However, plant intelligence remains loosely defined; often it is either perceived as practically synonymous to Darwinian fitness, or reduced to a mere decorative metaphor. A more strict view can be taken, emphasizing necessary prerequisites such as memory and learning, which requires clarifying the definition of memory itself. To qualify as memories, traces of past events have to be not only stored, but also actively accessed. We propose a criterion for eliminating false candidates of possible plant intelligence phenomena in this stricter sense: an “intelligent” behavior must involve a component that can be approximated by a plausible algorithmic model involving recourse to stored information about past states of the individual or its environment. Re-evaluation of previously presented examples of plant intelligence shows that only some of them pass our test. “You were hurt?” Kumiko said, looking at the scar. Sally looked down. “Yeah.” “Why didn't you have it removed?” “Sometimes it's good to remember.” “Being hurt?” “Being stupid.”—(W. Gibson: Mona Lisa Overdrive) PMID:19816094

Intelligent monitoring and fault diagnosis for ATLAS TDAQ: a complex event processing solution

CERN Document Server

Magnoni, Luca; Luppi, Eleonora

Effective monitoring and analysis tools are fundamental in modern IT infrastructures to get insights on the overall system behavior and to deal promptly and effectively with failures. In recent years, Complex Event Processing (CEP) technologies have emerged as effective solutions for information processing from the most disparate fields: from wireless sensor networks to financial analysis. This thesis proposes an innovative approach to monitor and operate complex and distributed computing systems, in particular referring to the ATLAS Trigger and Data Acquisition (TDAQ) system currently in use at the European Organization for Nuclear Research (CERN). The result of this research, the AAL project, is currently used to provide ATLAS data acquisition operators with automated error detection and intelligent system analysis. The thesis begins by describing the TDAQ system and the controlling architecture, with a focus on the monitoring infrastructure and the expert system used for error detection and automated reco...

A Location Intelligence System for the Assessment of Pluvial Flooding Risk and the Identification of Storm Water Pollutant Sources from Roads in Suburbanised Areas

Directory of Open Access Journals (Sweden)

Szymon Szewrański

2018-06-01

Full Text Available The interplay of an ever-growing number of inhabitants, sprawl development, soil sealing, changes in urban traffic characteristics, as well as observed climate trends gives rise to more frequent pluvial flooding in cities, a higher run-off of water, and an increasing pollution of surface water. The aim of this research is to develop a location intelligence system for the assessment of pluvial flooding risks and the identification of storm water pollutant sources from roads in newly-developed areas. The system combines geographic information systems and business intelligence software, and it is based on the original Pluvial Flood Risk Assessment tool. The location intelligence system effectively identifies the spatial and temporal distribution of pluvial flood risks, allows to preliminarily evaluate the total run-off from roads, and helps localise potential places for new water management infrastructure. Further improvements concern the modelling of a flow accumulation and drainage system, the application of weather radar precipitation data, and traffic monitoring and modelling.

Technical note: Efficient online source identification algorithm for integration within a contamination event management system

Science.gov (United States)

Deuerlein, Jochen; Meyer-Harries, Lea; Guth, Nicolai

2017-07-01

Drinking water distribution networks are part of critical infrastructures and are exposed to a number of different risks. One of them is the risk of unintended or deliberate contamination of the drinking water within the pipe network. Over the past decade research has focused on the development of new sensors that are able to detect malicious substances in the network and early warning systems for contamination. In addition to the optimal placement of sensors, the automatic identification of the source of a contamination is an important component of an early warning and event management system for security enhancement of water supply networks. Many publications deal with the algorithmic development; however, only little information exists about the integration within a comprehensive real-time event detection and management system. In the following the analytical solution and the software implementation of a real-time source identification module and its integration within a web-based event management system are described. The development was part of the SAFEWATER project, which was funded under FP 7 of the European Commission.

FY1995 four-terminal-device intelligent LSI system for real-time event recognition; 1995 nendo shunji ninshiki kino wo motta 4 tanshi device chino LSI no kenkyu

Energy Technology Data Exchange (ETDEWEB)

NONE

1997-03-01

Development of an intelligent LSI system having real-time response capability for real-word events. This is accomplished by enhancing the functionality of an elemental device, employing ultra-fine-grain parallelism and merging software directly in the LSI hardware. Intelligent functions are created directly on the LSI hardware, thus enabling real-time recognition by electronic systems. The origin of human intelligence lies in the huge memory data base acquired through one's life and the very fast search mechanism to recall the 'most similar' event to the current input. Based on this principle components of intelligent LSI systems have been developed. An analog EEPROM technology capable of storing 256 levels of data per cell without time-consuming write/verify operations has been developed. In situ monitoring of memory content during writing has allowed us high-accuracy data writing. A high-speed parallel-search engine for the minimum distance vector (an associator) has been developed using neuron MOS technology. The associator has been applied to the motion vector detector as an example, which has shown a very fast detection with an extremely simple hardware configuration. The association architecture has been applied to a real-time motion picture compression system, demonstrating three orders of magnitude higher performance than typical CISC processors (Pentium 166MHz). (NEDO)

Multiple Intelligences - Based Planning of EFL Classes

Directory of Open Access Journals (Sweden)

Sanan Shero Malo Zebari

2018-04-01

Full Text Available The present study aimed to set a plan for teaching EFL classes based on the identification of university students’ dominant multiple intelligences in EFL classes, and the differences in the types of intelligence between female and male students in terms of their gender. The problem the present study aimed to address is that the traditional concept that “one size fits all” is still adopted by many EFL teachers, and that EFL students’ differences and preferences are noticeably unheeded. It is believed that identifying students’ dominant intelligences is a sound remedial solution for such a problem before embarking on any teaching program. Moreover, getting students aware of their different types of intelligence will motivate and encourage them in the classroom. The researchers used a questionnaire as a research instrument for data collection.  The results arrived at showed that there were no significant differences in the types of intelligence between female and male students in terms of their gender, except for bodily- kinesthetic intelligence. They also showed that the dominant intelligences were ranked from the highest to the lowest as follows interpersonal, linguistic, spatial, logical-mathematical, bodily kinesthetic, intrapersonal, musical, and naturalistic.

Defense Intelligence Agency

Science.gov (United States)

Management Office Management and Infrastructure Security Science and Technology Pre-Employment Forms Intelligence Community Wounded Warrior Internship Program News Articles Videos Contact DIA DIA in the News observed the legacy of Dr. Martin Luther King, Jr. in an event Jan. 26, at the DIA headquarters. Story DIA

The Relation between Intelligence and Adaptive Behavior: A Meta-Analysis

Science.gov (United States)

Alexander, Ryan M.

2017-01-01

Intelligence tests and adaptive behavior scales measure vital aspects of the multidimensional nature of human functioning. Assessment of each is a required component in the diagnosis or identification of intellectual disability, and both are frequently used conjointly in the assessment and identification of other developmental disabilities. The…

State-of-the-art Machine Learning in event reconstruction and object identification

CERN Document Server

Kagan, Michael; The ATLAS collaboration

2017-01-01

Recent advances in deep learning have seen great success in the realms of computer vision, natural language processing, and broadly in data science. However, these new ideas are only just beginning to be applied to the analysis of High Energy Physics data. In this talk, I will discuss developments in the application of computer vision and deep learning techniques for event reconstruction and particle identification for the LHC .

Identification and selection of initiating events for experimental fusion facilities

International Nuclear Information System (INIS)

Cadwallader, L.C.

1989-01-01

This paper describes the current approaches used in probabilistic risk assessment (PRA) to identify and select accident initiating events for study in either probabilistic safety analysis or PRA. Current methods directly apply to fusion facilities as well as other types of industries, such as chemical processing and nuclear fission. These identification and selection methods include the Master Logic Diagram, historical document review, system level Failure Modes and Effects Analysis, and others. A combination of the historical document review, such as Safety Analysis Reports and fusion safety studies, and the Master Logic Diagram with appropriate quality assurance reviews, is suggested for standardizing US fusion PRA effects. A preliminary set of generalized initiating events applicable to fusion facilities derived from safety document review is presented as a framework to start from for the historical document review and Master Logic Diagram approach. Fusion designers should find this list useful for their design reviews. 29 refs., 2 tabs

Identification and selection of initiating events for experimental fusion facilities

International Nuclear Information System (INIS)

Cadwallader, L.C.

1989-01-01

This paper describes the current approaches used in probabilistic risk assessment (PRA) to identify and select accident initiating events for study in either probabilistic safety analysis or PRA. Current methods directly apply to fusion facilities as well as other types of industries, such as chemical processing and nuclear fission. These identification and selection methods include the Master Logic Diagram, historical document review, system level Failure Modes and Effects Analysis, and others. A combination of the historical document review, such as Safety Analysis Reports and fusion safety studies, and the Master Logic Diagram with appropriate quality assurance reviews, is suggested for standardizing U.S. fusion PRA efforts. A preliminary set of generalized initiating events applicable to fusion facilities derived from safety document review is presented as a framework to start from for the historical document review and Master Logic Diagram approach. Fusion designers should find this list useful for their design reviews. 29 refs., 1 tab

Identification of coronal heating events in 3D simulations

Science.gov (United States)

Kanella, Charalambos; Gudiksen, Boris V.

2017-07-01

dominate the energy release. Most of the energy release happens in the lower corona, while heating drops with height. We find that with a specific identification method large events can be resolved into smaller ones, but at the expense of the total identified energy releases. The energy release that cannot be identified as an event favors a low energy release mechanism. Conclusions: This is the first step to quantitatively identify magnetic reconnection sites and measure the energy released by current sheet formation.

Identification and localization of neutrino events in the OPERA detector; Identification et localisation des evenements neutrino dans le detecteur OPERA

Energy Technology Data Exchange (ETDEWEB)

Heritier, C

2004-07-15

The OPERA experiment is designed for the appearance search of {nu}{sub {mu}} {yields} {nu}{sub {tau}} oscillations in the parameters indicated by the atmospheric neutrino anomaly. To prove the appearance of {nu}{sub {tau}} at 732 km from the CERN, an hybrid detector is under construction at the Gran Sasso laboratory. The target, composed by bricks made of lead plates and emulsion sheets, allows the direct observation of the {tau} lepton produced in {nu}{sub {tau}} charged current interactions. The tracking, the localization of neutrino events in the target and the muon identification are allowed by trackers located inside the target (scintillators) and in the spectrometer following the target (RPC). The development of algorithms, based on electronic detectors, is necessary to identify the neutrino interaction and to locate the bricks where the interaction occurred. A classification of neutrino events is performed using the identification of the muon produced in {nu}{sub {mu}} CC and {nu}{sub {tau}} CC with {tau} {yields} {mu} decay. This classification is optimised with tracking informations and also with topological and calorimetric parameters which describe the nature of the interaction (quasi-elastic, deep inelastic); the algorithm of the localization of neutrino event is performed for each category. A tridimensional brick probability map is built and can be exploited to implement sophisticated extraction brick strategies. To conclude, a feasibility study of a test beam experiment OPERETTE is presented. The project was to install a similar OPERA detector in the COMPASS neutrino beam, in the CERN North Area. It was a good opportunity to prepare OPERA for the scanning emulsion films with neutrino events and to test the analysis procedures. (author)

Emotional Intelligence and Nurse Recruitment: Rasch and confirmatory factor analysis of the trait emotional intelligence questionnaire short form.

Science.gov (United States)

Snowden, Austyn; Watson, Roger; Stenhouse, Rosie; Hale, Claire

2015-12-01

To examine the construct validity of the Trait Emotional Intelligence Questionnaire Short form. Emotional intelligence involves the identification and regulation of our own emotions and the emotions of others. It is therefore a potentially useful construct in the investigation of recruitment and retention in nursing and many questionnaires have been constructed to measure it. Secondary analysis of existing dataset of responses to Trait Emotional Intelligence Questionnaire Short form using concurrent application of Rasch analysis and confirmatory factor analysis. First year undergraduate nursing and computing students completed Trait Emotional Intelligence Questionnaire-Short Form in September 2013. Responses were analysed by synthesising results of Rasch analysis and confirmatory factor analysis. Participants (N = 938) completed Trait Emotional Intelligence Questionnaire Short form. Rasch analysis showed the majority of the Trait Emotional Intelligence Questionnaire-Short Form items made a unique contribution to the latent trait of emotional intelligence. Five items did not fit the model and differential item functioning (gender) accounted for this misfit. Confirmatory factor analysis revealed a four-factor structure consisting of: self-confidence, empathy, uncertainty and social connection. All five misfitting items from the Rasch analysis belonged to the 'social connection' factor. The concurrent use of Rasch and factor analysis allowed for novel interpretation of Trait Emotional Intelligence Questionnaire Short form. Much of the response variation in Trait Emotional Intelligence Questionnaire Short form can be accounted for by the social connection factor. Implications for practice are discussed. © 2015 John Wiley & Sons Ltd.

Patients' identification and reporting of unsafe events at six hospitals in Japan.

Science.gov (United States)

Hasegawa, Tomonori; Fujita, Shigeru; Seto, Kanako; Kitazawa, Takefumi; Matsumoto, Kunichika

2011-11-01

Hospitals and other health care organizations have increasingly recognized the need to engage patients as participants in patient safety. A study was conducted to compare patients' and health care staff's identification and reporting of such events. A questionnaire was administered at six hospitals in Japan to outpatients and inpatients from November 2004 through February 2007. Patients were asked to respond to questions about experiences of possibly unsafe events. Patients experiencing such events were then asked about the events and whether they had reported their experience to health care staff. A specialist panel classified reported events as "uneasy-dissatisfying" or "unsafe." The response rates of outpatients and inpatients were 85.4% (1,506/1,764) and 54.3% (1,738/3,198), respectively. Among the respondents (> or = 20 years of age), 125 (8.7%) of the outpatients and 185 (10.9%) of the inpatients experienced uneasy-dissatisfying or unsafe events; 35 (2.4%) of the outpatients and 67 (4.0%) of the inpatients experienced unsafe events, the percent increasing with hospital stay. Only 38 (30.4%) of the outpatients and 62 (33.5%) of the inpatients reported the unsafe events to health care staff Only 17.1% of unsafe events reported by inpatients were identified by the in-house reporting systems of adverse events and near misses. For the uneasy-dissatisfying or unsafe events that patients did not think necessary to report, the patients often felt they were self-evident or easily identifiable by health care staff, had difficulty evaluating the event, did not expect their report to bring any improvement, or even felt that reporting it would create some disadvantage in their medical treatment. Patient reporting programs and in-house reporting systems, among other detection methods, should be regarded as complementary sources of information.

The Predictive Aspect of Business Process Intelligence

DEFF Research Database (Denmark)

Pérez, Moisés Lima; Møller, Charles

2007-01-01

This paper presents the arguments for a research proposal on predicting business events in a Business Process Intelligence (BPI) context. The paper argues that BPI holds a potential for leveraging enterprise benefits by supporting real-time processes. However, based on the experiences from past...... business intelligence projects the paper argues that it is necessary to establish a new methodology to mine and extract the intelligence on the business level which is different from that, which will improve a business process in an enterprise. In conclusion the paper proposes a new research project aimed...

Spiritual Intelligence and Transformational Leadership: A New Theoretical Framework

OpenAIRE

Stephen R. White; Precious Guramatunhu-Mudiwa; Barbara B. Howard

2009-01-01

The purpose of this paper is to establish a connection between spiritual intelligence and transformational leadership in an effort to encourage further debate about the legitimacy of spiritual intelligence in educational discourse. In this context we define spiritual intelligence as an interconnected configuration of affective orientations intimately linked to create meaning through connecting ideas, events, and persons rather than to a specific religious tradition or orientation. An explorat...

Intelligent, Autonomous Electrical Power System Management and Distribution, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — EPS-MAESTRO (EPS Management through intelligent, AdaptivE, autonomouS, faulT identification and diagnosis, Reconfiguration/replanning/rescheduling Optimization)...

A computer architecture for intelligent machines

Science.gov (United States)

Lefebvre, D. R.; Saridis, G. N.

1992-01-01

The theory of intelligent machines proposes a hierarchical organization for the functions of an autonomous robot based on the principle of increasing precision with decreasing intelligence. An analytic formulation of this theory using information-theoretic measures of uncertainty for each level of the intelligent machine has been developed. The authors present a computer architecture that implements the lower two levels of the intelligent machine. The architecture supports an event-driven programming paradigm that is independent of the underlying computer architecture and operating system. Execution-level controllers for motion and vision systems are briefly addressed, as well as the Petri net transducer software used to implement coordination-level functions. A case study illustrates how this computer architecture integrates real-time and higher-level control of manipulator and vision systems.

Identification of initiating events using a master logic diagram in low-power and shutdown PSA for nuclear power plant

International Nuclear Information System (INIS)

Han, S. J.; Park, J. H.; Kim, T. W.; Ha, J. J.

2003-01-01

It is necessary to apply a formal technique instead of an empirical technique in the identification of initiating events for Low Power and ShutDown (LPSD) Probabilistic Safety Assessment (PSA) of Nuclear Power Plant (NPP). The present study focuses on the examination of Master Logic Diagram (MLD) technique as a formal technique in the identification of initiating events. The MLD technique is a deductive tool using top-down approach for the formal and logical indentification of initiating events. The present study modified the MLD used in the full power PSA considering the characteristics of LPSD operation. The modified MLD introduced a systematic formation in decomposition process of which the MLD for full power PSA lacked. The modified MLD was able to identify initiating events systematic and logical. However, the formal techniques including the MLD have a limitation for precisely identifying all of the initiating events. In order to overcome this limitation, it is necessary to combine it with an empirical technique. We expect that the modified MLD can be used in an upgrade of the current LPSD PSAs

Computational intelligence in nuclear engineering

International Nuclear Information System (INIS)

Uhrig, Robert E.; Hines, J. Wesley

2005-01-01

Approaches to several recent issues in the operation of nuclear power plants using computational intelligence are discussed. These issues include 1) noise analysis techniques, 2) on-line monitoring and sensor validation, 3) regularization of ill-posed surveillance and diagnostic measurements, 4) transient identification, 5) artificial intelligence-based core monitoring and diagnostic system, 6) continuous efficiency improvement of nuclear power plants, and 7) autonomous anticipatory control and intelligent-agents. Several Changes to the focus of Computational Intelligence in Nuclear Engineering have occurred in the past few years. With earlier activities focusing on the development of condition monitoring and diagnostic techniques for current nuclear power plants, recent activities have focused on the implementation of those methods and the development of methods for next generation plants and space reactors. These advanced techniques are expected to become increasingly important as current generation nuclear power plants have their licenses extended to 60 years and next generation reactors are being designed to operate for extended fuel cycles (up to 25 years), with less operator oversight, and especially for nuclear plants operating in severe environments such as space or ice-bound locations

The 2002 Starting Artificial Intelligence Researchers Symposium

OpenAIRE

Vidal, Thierry

2003-01-01

During the 2002 European Conference on Artificial Intelligence (ECAI-02) was introduced the Starting Artificial Intelligence Researchers Symposium STAIRS), the first-ever international symposium specifically aimed at Ph.D. students in AI. The outcome was a thorough, high-quality, and successful event, with all the features one usually finds in the best international conferences: large international committees, comprehensive coverage, published proceedings, renowned speakers and panelists, sub...

7th International Symposium on Intelligent Distributed Computing

CERN Document Server

Jung, Jason; Badica, Costin

2014-01-01

This book represents the combined peer-reviewed proceedings of the Seventh International Symposium on Intelligent Distributed Computing - IDC-2013, of the Second Workshop on Agents for Clouds - A4C-2013, of the Fifth International Workshop on Multi-Agent Systems Technology and Semantics - MASTS-2013, and of the International Workshop on Intelligent Robots - iR-2013. All the events were held in Prague, Czech Republic during September 4-6, 2013. The 41 contributions published in this book address many topics related to theory and applications of intelligent distributed computing and multi-agent systems, including: agent-based data processing, ambient intelligence, bio-informatics, collaborative systems, cryptography and security, distributed algorithms, grid and cloud computing, information extraction, intelligent robotics, knowledge management, linked data, mobile agents, ontologies, pervasive computing, self-organizing systems, peer-to-peer computing, social networks and trust, and swarm intelligence.  .

Incomplete Intelligence: Is the Information Sharing Environment an Effective Platform?

Science.gov (United States)

2012-09-01

Initiative NYFD New York Fire Department NYPD New York Police Department OLAP On Line Analytics Processing OSINT Open Source Intelligence...Intelligence ( OSINT ), from public websites, media sources, and other unclassified events and reports. Although some of these sources do not have a direct

Identification of near surface events using athermal phonon signals in low temperature Ge bolometers for the EDELWEISS experiment

International Nuclear Information System (INIS)

Marnieros, S.; Juillard, A.; Berge, L.; Collin, S.; Dumoulin, L.

2004-01-01

We present a study of a 100 g low temperature Ge detector, allowing identification of surface events down to the energy threshold. The bolometer is fitted with segmented electrodes and two NbSi Anderson insulator thermometric layers. Analysis of the athermal signals amplitudes allows us to identify and reject all events occurring in the first millimeter under the electrodes

Identification of near surface events using athermal phonon signals in low temperature Ge bolometers for the EDELWEISS experiment

Energy Technology Data Exchange (ETDEWEB)

Marnieros, S. E-mail: marniero@csnsm.in2p3.fr; Juillard, A.; Berge, L.; Collin, S.; Dumoulin, L

2004-03-11

We present a study of a 100 g low temperature Ge detector, allowing identification of surface events down to the energy threshold. The bolometer is fitted with segmented electrodes and two NbSi Anderson insulator thermometric layers. Analysis of the athermal signals amplitudes allows us to identify and reject all events occurring in the first millimeter under the electrodes.

Intelligent System for Diagnosis of a Three-Phase Separator

Directory of Open Access Journals (Sweden)

Irina Ioniţă

2016-03-01

Full Text Available Intelligent systems for diagnosis have been used in a variety of domains: financial evaluation, credit scoring problem, identification of software and hardware problems of mechanical and electronic equipment, medical diagnosis, fault detection in gas-oil production plants etc. The goal of diagnosis systems is to classify the observed symptoms as being caused by some diagnosis class while advising systems perform such a classification and offer corrective remedies (recommendations. The current paper discuss the opportunity to combine more intelligent techniques and methodologies (intelligent agents, data mining and expert systems to increase the accuracy of results obtained from the diagnosis of a three-phase separator. The results indicate that the diagnosis hybrid system benefits from the advantages of each module component: intelligent agent module, data mining module and expert system module.

Management Intelligent Systems : First International Symposium

CERN Document Server

Martínez-López, Francisco; Rodríguez, Juan

2012-01-01

The 2012 International Symposium on Management Intelligent Systems is believed to be the first international forum to present and discuss original, rigorous and significant contributions on Artificial Intelligence-based (AI) solutions—with a strong, practical logic and, preferably, with empirical applications—developed to aid the management of organizations in multiple areas, activities, processes and problem-solving; i.e., what we propose to be named as Management Intelligent Systems (MiS). The three-day event aimed to bring together researchers interested in this promising interdisciplinary field who came from areas as varied as management, marketing, and business in general, computer science, artificial intelligence, statistics, etc. This volume presents the proceedings of these activities in a collection of contributions with many original approaches. They address diverse Management and Business areas of application such as decision support, segmentation of markets, CRM, product design, service person...

Unfamiliar voice identification: Effect of post-event information on accuracy and voice ratings

Directory of Open Access Journals (Sweden)

Harriet Mary Jessica Smith

2014-04-01

Full Text Available This study addressed the effect of misleading post-event information (PEI on voice ratings, identification accuracy, and confidence, as well as the link between verbal recall and accuracy. Participants listened to a dialogue between male and female targets, then read misleading information about voice pitch. Participants engaged in verbal recall, rated voices on a feature checklist, and made a lineup decision. Accuracy rates were low, especially on target-absent lineups. Confidence and accuracy were unrelated, but the number of facts recalled about the voice predicted later lineup accuracy. There was a main effect of misinformation on ratings of target voice pitch, but there was no effect on identification accuracy or confidence ratings. As voice lineup evidence from earwitnesses is used in courts, the findings have potential applied relevance.

Efficient Identification of Timed Automata : Theory and practice

NARCIS (Netherlands)

Verwer, S.E.

2010-01-01

This thesis contains a study in a subfield of artificial intelligence, learning theory, machine learning, and statistics, known as system (or language) identification. System identification is concerned with constructing (mathematical) models from observations. Such a model is an intuitive

Towards intelligent video understanding applied to plasma facing component monitoring

International Nuclear Information System (INIS)

Martin, V.; Travere, J.M.; Moncada, V.; Bremond, F.

2011-01-01

In this paper, we promote intelligent plasma facing component video monitoring for both real-time purposes (machine protection issues) and post event analysis purposes (plasma-wall interaction understanding). We propose a vision-based system able to automatically detect and classify into different pre-defined categories thermal phenomena such as localized hot spots or transient thermal events (e.g. electrical arcing) from infrared imaging data of PFCs. This original computer vision system is made intelligent by endowing it with high level reasoning (i.e. integration of a priori knowledge of thermal event spatio-temporal properties to guide the recognition), self-adaptability to varying conditions (e.g. different thermal scenes and plasma scenarios), and learning capabilities (e.g. statistical modelling of event behaviour based on training samples). (authors)

Radio Frequency Identification

Indian Academy of Sciences (India)

Radio Frequency Identification (RFID) has been around sinceearly 2000. Its use has currently become commonplace as thecost of RFID tags has rapidly decreased. RFID tags have alsobecome more 'intelligent' with the incorporation of processorsand sensors in them. They are widely used now in manyinnovative ways.

A situation-response model for intelligent pilot aiding

Science.gov (United States)

Schudy, Robert; Corker, Kevin

1987-01-01

An intelligent pilot aiding system needs models of the pilot information processing to provide the computational basis for successful cooperation between the pilot and the aiding system. By combining artificial intelligence concepts with the human information processing model of Rasmussen, an abstraction hierarchy of states of knowledge, processing functions, and shortcuts are developed, which is useful for characterizing the information processing both of the pilot and of the aiding system. This approach is used in the conceptual design of a real time intelligent aiding system for flight crews of transport aircraft. One promising result was the tentative identification of a particular class of information processing shortcuts, from situation characterizations to appropriate responses, as the most important reliable pathway for dealing with complex time critical situations.

Perceptions of Usefulness: Using the Holland Code Theory, Multiple Intelligences Theory, and Role Model Identification to Determine a Career Niche in the Fashion Industry for First-Quarter Fashion Students

Science.gov (United States)

Green, Crystal D.

2010-01-01

This action research study investigated the perceptions that student participants had on the development of a career exploration model and a career exploration project. The Holland code theory was the primary assessment used for this research study, in addition to the Multiple Intelligences theory and the identification of a role model for the…

Criteria of reaction identification and selection of badly measured events

International Nuclear Information System (INIS)

Linetskij, A.R.; Lyubarskij, G.Ya.; Sagalovich, N.E.

1979-01-01

Basing on photoemulsion methods of studying channels of multiparticle nuclear reactions the metrological characteristics of a physical technique are described in the process of its development. To increase the accuracy of reaction identification the technique for picture measuring has been complicated by introducing calibration measurements of tracks of stopped in the emulsion primary α-particles. Callibration measurements have support assumptions on energy oscillations of the primary beam and made possible the employment of actual values of this energy instead of rated one during mathematical processing. By using simulation reactions the effect of errors in determining the contraction ratio has been estimated. It has been found that rather a small error in determining the contraction (+-20%) results in additional casting-out 8-15% of measured events

Structural Identification and Comparison of Intelligent Mobile Learning Environment

Science.gov (United States)

Upadhyay, Nitin; Agarwal, Vishnu Prakash

2007-01-01

This paper proposes a methodology using graph theory, matrix algebra and permanent function to compare different architecture (structure) design of intelligent mobile learning environment. The current work deals with the development/selection of optimum architecture (structural) model of iMLE. This can be done using the criterion as discussed in…

Real-time identification of residential appliance events based on power monitoring

Science.gov (United States)

Yang, Zhao; Zhu, Zhicheng; Wei, Zhiqiang; Yin, Bo; Wang, Xiuwei

2018-03-01

Energy monitoring for specific home appliances has been regarded as the pre-requisite for reducing residential energy consumption. To enhance the accuracy of identifying operation status of household appliances and to keep pace with the development of smart power grid, this paper puts forward the integration of electric current and power data on the basis of existing algorithm. If average power difference of several adjacent cycles varies from the baseline and goes beyond the pre-assigned threshold value, the event will be flagged. Based on MATLAB platform and domestic appliances simulations, the results of tested data and verified algorithm indicate that the power method has accomplished desired results of appliance identification.

Identification of multiple intelligences for high school students in theoretical and applied science courses

Science.gov (United States)

Wiseman, D. Kim

Historically educators in the United States have used the Stanford-Binet intelligence test to measure a students' ability in logical/mathematical and linguistic domains. This measurement is being used by a society that has evolved from agrarian and industrial-based economies to what is presently labeled a technological society. As society has changed so have the educational needs of the students who will live in this technological society. This study assessed the multiple intelligences of high school students enrolled in theoretical and applied science (physics and applied physics) courses. Studies have verified that performance and outcomes of students enrolled in these courses are similar in standardized testing but instructional methodology and processes are dissimilar. Analysis of multiple intelligence profiles collected from this study found significant differences in logical/mathematical, bodily/kinesthetic and intrapersonal multiple intelligences of students in theoretical science courses compared to students in applied science courses. Those differences clearly illustrate why it is imperative for educators to expand the definition of intelligence for students entering the new millennium.

Defending the Homeland: The Case for Integrating National Guard Intelligence Personnel into the State Fusion Centers

Science.gov (United States)

2011-02-15

already robust lineup of 57 National Guard Combat Support Teams (CSTs) and 17 CBRNE Enhanced Response Force Packages (CERFPs) to increase the existing...analysis of disparate data sources, identification of intelligence gaps, and proactive collection of intelligence against those gaps which could

Artificial intelligence on the identification of risk groups for osteoporosis, a general review.

Science.gov (United States)

Cruz, Agnaldo S; Lins, Hertz C; Medeiros, Ricardo V A; Filho, José M F; da Silva, Sandro G

2018-01-29

The goal of this paper is to present a critical review on the main systems that use artificial intelligence to identify groups at risk for osteoporosis or fractures. The systems considered for this study were those that fulfilled the following requirements: range of coverage in diagnosis, low cost and capability to identify more significant somatic factors. A bibliographic research was done in the databases, PubMed, IEEExplorer Latin American and Caribbean Center on Health Sciences Information (LILACS), Medical Literature Analysis and Retrieval System Online (MEDLINE), Cumulative Index to Nursing and Allied Health Literature (CINAHL), Scopus, Web of Science, and Science Direct searching the terms "Neural Network", "Osteoporosis Machine Learning" and "Osteoporosis Neural Network". Studies with titles not directly related to the research topic and older data that reported repeated strategies were excluded. The search was carried out with the descriptors in German, Spanish, French, Italian, Mandarin, Portuguese and English; but only studies written in English were found to meet the established criteria. Articles covering the period 2000-2017 were selected; however, articles prior to this period with great relevance were included in this study. Based on the collected research, it was identified that there are several methods in the use of artificial intelligence to help the screening of risk groups of osteoporosis or fractures. However, such systems were limited to a specific ethnic group, gender or age. For future research, new challenges are presented. It is necessary to develop research with the unification of different databases and grouping of the various attributes and clinical factors, in order to reach a greater comprehensiveness in the identification of risk groups of osteoporosis. For this purpose, the use of any predictive tool should be performed in different populations with greater participation of male patients and inclusion of a larger age range for the

Search-based model identification of smart-structure damage

Science.gov (United States)

Glass, B. J.; Macalou, A.

1991-01-01

This paper describes the use of a combined model and parameter identification approach, based on modal analysis and artificial intelligence (AI) techniques, for identifying damage or flaws in a rotating truss structure incorporating embedded piezoceramic sensors. This smart structure example is representative of a class of structures commonly found in aerospace systems and next generation space structures. Artificial intelligence techniques of classification, heuristic search, and an object-oriented knowledge base are used in an AI-based model identification approach. A finite model space is classified into a search tree, over which a variant of best-first search is used to identify the model whose stored response most closely matches that of the input. Newly-encountered models can be incorporated into the model space. This adaptativeness demonstrates the potential for learning control. Following this output-error model identification, numerical parameter identification is used to further refine the identified model. Given the rotating truss example in this paper, noisy data corresponding to various damage configurations are input to both this approach and a conventional parameter identification method. The combination of the AI-based model identification with parameter identification is shown to lead to smaller parameter corrections than required by the use of parameter identification alone.

Determining the Organizational Intelligence Level of Hospitals in Our Region

Directory of Open Access Journals (Sweden)

Khayat Moghadam S

2013-10-01

Full Text Available Objectives: A new and unique tool for survival of organizations among their competitors is the use of organizational intelligence; Organizational intelligence means having a comprehensive knowledge of all the environmental factors that affect on the organization. This research  is one of the few studies with the aim of determine the organizational intelligence level of hospitals and ranking of organizational intelligence components to enable administrators to provide more accurate identification of strengths and weaknesses and take more effective steps to improve service delivery. Materials and Methods: This is a descriptive-analytical and applicable study performed in the 2012 at 12 General Hospital related to Mashhad University of Medical Sciences. Data collection was performed by Albrecht organizational intelligence questionnaire. The data gathering tool was the questionnaire Albrecht Organizational Intelligence. The collected Data were analyzed using T-test and Smirnov test with SPSS-16 software. The significance level for all tests was considered 0.05. Results: All components of organizational intelligence were in the optimum status. Component of Shared fate gained the first rank and component of knowledge Deployment gained the last rank. Conclusion: Ranking of organizational intelligence components is different in hospitals of the province and the county; representing different features and conditions. Considering the importance of organizational intelligence role in the promotion of organization, hospital managers can take active steps to improve organizational intelligence based on done rankings.

Identification of the timing-of-events model with multiple competing exit risks from single-spell data

DEFF Research Database (Denmark)

Drepper, Bettina; Effraimidis, G.

2016-01-01

The identification result of the timing-of-events model (Abbring and Van den Berg, 2003b) is extended to a model with several competing exit risk equations. This extension allows e.g. to simultaneously identify the different effects a benefit sanction has on the rate of finding work and leaving t...

Intelligence in Artificial Intelligence

OpenAIRE

Datta, Shoumen Palit Austin

2016-01-01

The elusive quest for intelligence in artificial intelligence prompts us to consider that instituting human-level intelligence in systems may be (still) in the realm of utopia. In about a quarter century, we have witnessed the winter of AI (1990) being transformed and transported to the zenith of tabloid fodder about AI (2015). The discussion at hand is about the elements that constitute the canonical idea of intelligence. The delivery of intelligence as a pay-per-use-service, popping out of ...

Intelligent energy management; Intelligentes Energiemanagement

Energy Technology Data Exchange (ETDEWEB)

Schmidt, Carsten [Siemens AG, Nuernberg (Germany). Bereich Sales and Marketing; Kunzmann, Geo [Siemens AG, Nuernberg (Germany). Bereich Business Development

2010-03-15

As energy is getting shorter and increasingly expensive while consumption is increasing and legal regulations are getting stricter, intelligent energy management is becoming more necessary than ever. The autors propose an integrated strategy of ''identification - evaluation - saving''. They present a scalable energy management software that works also with existing hardware and helps to develop even savings potentials that are not identifiable at first glance. (orig.)

Muon Identification with the Event Filter of the ATLAS Experiment at CERN LHC's

CERN Document Server

Dos Anjos, A; Baines, J T M; Bee, C P; Biglietti, M; Bogaerts, J A C; Bosman, M; Carlino, G; Caron, B; Casado, M P; Cataldi, G; Cavalli, D; Comune, G; Conde, P; Conventi, F; Crone, G; Damazio, D; De Santo, A; Díaz-Gómez, M; Di Mattia, A; Ellis, Nick; Emeliyanov, D; Epp, B; Falciano, S; Garitaonandia, H; George, S; Ghete, V; Goncalo, R; Gorini, E; Haller, J; Kabana, S; Khomich, A; Kilvington, G; Kirk, J; Konstantinidis, N P; Kootz, A; Lankford, A J; Lowe, A; Luminari, L; Maeno, T; Masik, J; Meessen, C; Mello, A G; Moore, R; Morettini, P; Negri, A; Nikitin, N; Nisati, A; Osuna, C; Padilla, C; Panikashvili, N; Parodi, F; Pasqualucci, E; Pérez-Réale, V; Pinfold, J L; Pinto, P; Primavera, M; Qian, Z; Resconi, S; Rosati, S; Sánchez, C; Santamarina-Rios, C; Scannicchio, D A; Schiavi, C; Segura, E; De Seixas, J M; Sivoklokov, S Yu; Sobreira, A; Soluk, R A; Spagnolo, S; Stefanidis, E; Sushkov, S; Sutton, M; Tapprogge, S; Tarem, S; Thomas, E; Touchard, F; Usai, G; Venda-Pinto, B; Ventura, A; Vercesi, V; Wengler, T; Werner, P; Wheeler, S J; Wickens, F J; Wiedenmann, W; Wielers, M; Zobernig, G; 14th IEEE - NPSS Real Time Conference 2005 Nuclear Plasma Sciences Society

2005-01-01

The Large Hadron Collider at CERN offers unprecedented challenges to the design and construction of detectors and trigger/data acquisition systems. For ATLAS, a three level trigger system has been developed to extract interesting physics signatures with a 10^6 rate reduction. To accomplish this, components of physics analysis traditionally deferred to offline physics analysis must be embedded within the online trigger system. For the Muon trigger, the specific off-line algorithms MOORE (Muon Object Oriented REconstruction) and MuId (Muon Identification) have been adopted so far for the on-line use, imposing an operation in a Bayesian-like environment where only specific hypotheses must be validated. After a short review of the ATLAS trigger, the paper shows the general strategy of the Muon Identification and Selection accessing the full event data, or being seeded from results derived at a previous stage of the trigger chain.

Intelligence and the prevention of nuclear terrorism

International Nuclear Information System (INIS)

Despres, J.

1987-01-01

The paper first defines intelligence and nuclear terrorism and analyzes the nature of the problem from both a specifically US and a more generally Western viewpoint. As used here, intelligence refers broadly to the collection and reporting of information, the production of assessments, and the presentation of judgments by intelligence specialists who work for public and national security authorities. Intelligence encompasses the entire range of investigative and reporting activities at all levels of government - from local police units to allied military commands - that could contribute to the discovery and disarming of nuclear terrorists. Nuclear terrorism, in contrast, refers only to credible threats or acts of extreme violence by forces outside the direct control of any state through false threats or actual use of a nuclear bomb. This definition excludes other highly menacing or damaging activities involving nuclear materials, facilities, weapons, or phobias such as poisoning the air or water supplies with radioactive substances; stealing nuclear materials, sabotaging nuclear powerplants, occupying a facility or seizing a vehicle with nuclear weapons, or inflaming public fears in the event of a nuclear accident. These events can be extremely frightening, as in the case of public reactions throughout Europe to the nuclear accident at Chernobyl in the Ukraine. However, their potential destructiveness and exploitability by terrorists do not match the threat of nuclear explosion

Self-compassion and emotional intelligence in nurses.

Science.gov (United States)

Heffernan, Mary; Quinn Griffin, Mary T; Sister Rita McNulty; Fitzpatrick, Joyce J

2010-08-01

Nurses often provide care for patients and families who are suffering and where emotions are heightened. Compassion is an essential component of the care that nurses provide. Emotions play an important role in the relationship and communication between nurses, patients and families. Self-compassion is the ability to be compassionate to oneself, without this ability nurses might not be prepared to be compassionate to patients. Emotionally intelligent persons perceive themselves as confident, better able to understand, control and manage their emotions. The purpose of this descriptive, correlational study was to examine the relationship between self-compassion and emotional intelligence. Participants were 135 nurses. The setting for this study was a health system with hospitals located in Queens, Nassau and Suffolk counties of New York, USA. Three of the hospitals in the study are located in Queens and/or the Queens/Nassau border. Queens is the most culturally diverse community in the USA. The patients served, as well as the nursing staff, are reflective of this cultural and religious diversity. Results indicated a positive correlation between self-compassion and emotional intelligence (r = 0.55). Recommendations for future research include: exploration of self-compassion and emotional intelligence in nurses, and identification of the benefits of enhancing self-compassion and emotional intelligence in nurses.

Computational Intelligence Techniques for New Product Design

CERN Document Server

Chan, Kit Yan; Dillon, Tharam S

2012-01-01

Applying computational intelligence for product design is a fast-growing and promising research area in computer sciences and industrial engineering. However, there is currently a lack of books, which discuss this research area. This book discusses a wide range of computational intelligence techniques for implementation on product design. It covers common issues on product design from identification of customer requirements in product design, determination of importance of customer requirements, determination of optimal design attributes, relating design attributes and customer satisfaction, integration of marketing aspects into product design, affective product design, to quality control of new products. Approaches for refinement of computational intelligence are discussed, in order to address different issues on product design. Cases studies of product design in terms of development of real-world new products are included, in order to illustrate the design procedures, as well as the effectiveness of the com...

Effects on incidental memory of affective tone in associated past and future episodes: influence of emotional intelligence.

Science.gov (United States)

Toyota, Hiroshi

2011-02-01

The present study examined the effects of emotion elicited by episodes (past events or expected future events) and the relationship between individual differences in emotional intelligence and memory. Participants' emotional intelligence was assessed on the Japanese version of Emotional Skills and Competence Questionnaire. They rated the pleasantness of episodes they associated with targets, and then performed unexpected free recall tests. When the targets were associated with episodes that were past events, all participants recalled more of the targets associated with pleasant and unpleasant episodes than those associated with neutral episodes. However, when the targets were associated with episodes expected to occur in the future, only participants with higher emotional intelligence scores recalled more of the targets associated with pleasant and unpleasant episodes. The participants with lower emotional intelligence scores recalled the three target types with similar accuracy. These results were interpreted as showing that emotional intelligence is associated with the processing of targets associated with future episodes as retrieval cues.

International Conference on Intelligent Unmanned Systems (ICIUS)

CERN Document Server

Kartidjo, Muljowidodo; Yoon, Kwang-Joon; Budiyono, Agus; Autonomous Control Systems and Vehicles : Intelligent Unmanned Systems

2013-01-01

The International Conference on Intelligent Unmanned Systems 2011 was organized by the International Society of Intelligent Unmanned Systems and locally by the Center for Bio-Micro Robotics Research at Chiba University, Japan. The event was the 7th conference continuing from previous conferences held in Seoul, Korea (2005, 2006), Bali, Indonesia (2007), Nanjing, China (2008), Jeju, Korea (2009), and Bali, Indonesia (2010). ICIUS 2011 focused on both theory and application, primarily covering the topics of robotics, autonomous vehicles, intelligent unmanned technologies, and biomimetics. We invited seven keynote speakers who dealt with related state-of-the-art technologies including unmanned aerial vehicles (UAVs) and micro air vehicles (MAVs), flapping wings (FWs), unmanned ground vehicles (UGVs), underwater vehicles (UVs), bio-inspired robotics, advanced control, and intelligent systems, among others. This book is a collection of excellent papers that were updated after presentation at ICIUS2011. All papers ...

Intelligent wear mode identification system for marine diesel engines based on multi-level belief rule base methodology

Science.gov (United States)

Yan, Xinping; Xu, Xiaojian; Sheng, Chenxing; Yuan, Chengqing; Li, Zhixiong

2018-01-01

Wear faults are among the chief causes of main-engine damage, significantly influencing the secure and economical operation of ships. It is difficult for engineers to utilize multi-source information to identify wear modes, so an intelligent wear mode identification model needs to be developed to assist engineers in diagnosing wear faults in diesel engines. For this purpose, a multi-level belief rule base (BBRB) system is proposed in this paper. The BBRB system consists of two-level belief rule bases, and the 2D and 3D characteristics of wear particles are used as antecedent attributes on each level. Quantitative and qualitative wear information with uncertainties can be processed simultaneously by the BBRB system. In order to enhance the efficiency of the BBRB, the silhouette value is adopted to determine referential points and the fuzzy c-means clustering algorithm is used to transform input wear information into belief degrees. In addition, the initial parameters of the BBRB system are constructed on the basis of expert-domain knowledge and then optimized by the genetic algorithm to ensure the robustness of the system. To verify the validity of the BBRB system, experimental data acquired from real-world diesel engines are analyzed. Five-fold cross-validation is conducted on the experimental data and the BBRB is compared with the other four models in the cross-validation. In addition, a verification dataset containing different wear particles is used to highlight the effectiveness of the BBRB system in wear mode identification. The verification results demonstrate that the proposed BBRB is effective and efficient for wear mode identification with better performance and stability than competing systems.

Interactive analysis of geodata based intelligence

Science.gov (United States)

Wagner, Boris; Eck, Ralf; Unmüessig, Gabriel; Peinsipp-Byma, Elisabeth

2016-05-01

When a spatiotemporal events happens, multi-source intelligence data is gathered to understand the problem, and strategies for solving the problem are investigated. The difficulties arising from handling spatial and temporal intelligence data represent the main problem. The map might be the bridge to visualize the data and to get the most understand model for all stakeholders. For the analysis of geodata based intelligence data, a software was developed as a working environment that combines geodata with optimized ergonomics. The interaction with the common operational picture (COP) is so essentially facilitated. The composition of the COP is based on geodata services, which are normalized by international standards of the Open Geospatial Consortium (OGC). The basic geodata are combined with intelligence data from images (IMINT) and humans (HUMINT), stored in a NATO Coalition Shared Data Server (CSD). These intelligence data can be combined with further information sources, i.e., live sensors. As a result a COP is generated and an interaction suitable for the specific workspace is added. This allows the users to work interactively with the COP, i.e., searching with an on board CSD client for suitable intelligence data and integrate them into the COP. Furthermore, users can enrich the scenario with findings out of the data of interactive live sensors and add data from other sources. This allows intelligence services to contribute effectively to the process by what military and disaster management are organized.

Artificial Intelligence and Moral intelligence

OpenAIRE

Laura Pana

2008-01-01

We discuss the thesis that the implementation of a moral code in the behaviour of artificial intelligent systems needs a specific form of human and artificial intelligence, not just an abstract intelligence. We present intelligence as a system with an internal structure and the structural levels of the moral system, as well as certain characteristics of artificial intelligent agents which can/must be treated as 1- individual entities (with a complex, specialized, autonomous or selfdetermined,...

Using artificial intelligence to improve identification of nanofluid gas–liquid two-phase flow pattern in mini-channel

Directory of Open Access Journals (Sweden)

Jian Xiao

2018-01-01

Full Text Available This work combines fuzzy logic and a support vector machine (SVM with a principal component analysis (PCA to create an artificial-intelligence system that identifies nanofluid gas-liquid two-phase flow states in a vertical mini-channel. Flow-pattern recognition requires finding the operational details of the process and doing computer simulations and image processing can be used to automate the description of flow patterns in nanofluid gas-liquid two-phase flow. This work uses fuzzy logic and a SVM with PCA to improve the accuracy with which the flow pattern of a nanofluid gas-liquid two-phase flow is identified. To acquire images of nanofluid gas-liquid two-phase flow patterns of flow boiling, a high-speed digital camera was used to record four different types of flow-pattern images, namely annular flow, bubbly flow, churn flow, and slug flow. The textural features extracted by processing the images of nanofluid gas–liquid two-phase flow patterns are used as inputs to various identification schemes such as fuzzy logic, SVM, and SVM with PCA to identify the type of flow pattern. The results indicate that the SVM with reduced characteristics of PCA provides the best identification accuracy and requires less calculation time than the other two schemes. The data reported herein should be very useful for the design and operation of industrial applications.

Using artificial intelligence to improve identification of nanofluid gas-liquid two-phase flow pattern in mini-channel

Science.gov (United States)

Xiao, Jian; Luo, Xiaoping; Feng, Zhenfei; Zhang, Jinxin

2018-01-01

This work combines fuzzy logic and a support vector machine (SVM) with a principal component analysis (PCA) to create an artificial-intelligence system that identifies nanofluid gas-liquid two-phase flow states in a vertical mini-channel. Flow-pattern recognition requires finding the operational details of the process and doing computer simulations and image processing can be used to automate the description of flow patterns in nanofluid gas-liquid two-phase flow. This work uses fuzzy logic and a SVM with PCA to improve the accuracy with which the flow pattern of a nanofluid gas-liquid two-phase flow is identified. To acquire images of nanofluid gas-liquid two-phase flow patterns of flow boiling, a high-speed digital camera was used to record four different types of flow-pattern images, namely annular flow, bubbly flow, churn flow, and slug flow. The textural features extracted by processing the images of nanofluid gas-liquid two-phase flow patterns are used as inputs to various identification schemes such as fuzzy logic, SVM, and SVM with PCA to identify the type of flow pattern. The results indicate that the SVM with reduced characteristics of PCA provides the best identification accuracy and requires less calculation time than the other two schemes. The data reported herein should be very useful for the design and operation of industrial applications.

ISVASE: identification of sequence variant associated with splicing event using RNA-seq data.

Science.gov (United States)

Aljohi, Hasan Awad; Liu, Wanfei; Lin, Qiang; Yu, Jun; Hu, Songnian

2017-06-28

Exon recognition and splicing precisely and efficiently by spliceosome is the key to generate mature mRNAs. About one third or a half of disease-related mutations affect RNA splicing. Software PVAAS has been developed to identify variants associated with aberrant splicing by directly using RNA-seq data. However, it bases on the assumption that annotated splicing site is normal splicing, which is not true in fact. We develop the ISVASE, a tool for specifically identifying sequence variants associated with splicing events (SVASE) by using RNA-seq data. Comparing with PVAAS, our tool has several advantages, such as multi-pass stringent rule-dependent filters and statistical filters, only using split-reads, independent sequence variant identification in each part of splicing (junction), sequence variant detection for both of known and novel splicing event, additional exon-exon junction shift event detection if known splicing events provided, splicing signal evaluation, known DNA mutation and/or RNA editing data supported, higher precision and consistency, and short running time. Using a realistic RNA-seq dataset, we performed a case study to illustrate the functionality and effectiveness of our method. Moreover, the output of SVASEs can be used for downstream analysis such as splicing regulatory element study and sequence variant functional analysis. ISVASE is useful for researchers interested in sequence variants (DNA mutation and/or RNA editing) associated with splicing events. The package is freely available at https://sourceforge.net/projects/isvase/ .

Identification of unusual events in multichannel bridge monitoring data using wavelet transform and outlier analysis

Science.gov (United States)

Omenzetter, Piotr; Brownjohn, James M. W.; Moyo, Pilate

2003-08-01

Continuously operating instrumented structural health monitoring (SHM) systems are becoming a practical alternative to replace visual inspection for assessment of condition and soundness of civil infrastructure. However, converting large amount of data from an SHM system into usable information is a great challenge to which special signal processing techniques must be applied. This study is devoted to identification of abrupt, anomalous and potentially onerous events in the time histories of static, hourly sampled strains recorded by a multi-sensor SHM system installed in a major bridge structure in Singapore and operating continuously for a long time. Such events may result, among other causes, from sudden settlement of foundation, ground movement, excessive traffic load or failure of post-tensioning cables. A method of outlier detection in multivariate data has been applied to the problem of finding and localizing sudden events in the strain data. For sharp discrimination of abrupt strain changes from slowly varying ones wavelet transform has been used. The proposed method has been successfully tested using known events recorded during construction of the bridge, and later effectively used for detection of anomalous post-construction events.

Intelligence Naturelle et Intelligence Artificielle

OpenAIRE

Dubois, Daniel

2011-01-01

Cet article présente une approche systémique du concept d’intelligence naturelle en ayant pour objectif de créer une intelligence artificielle. Ainsi, l’intelligence naturelle, humaine et animale non-humaine, est une fonction composée de facultés permettant de connaître et de comprendre. De plus, l'intelligence naturelle reste indissociable de la structure, à savoir les organes du cerveau et du corps. La tentation est grande de doter les systèmes informatiques d’une intelligence artificielle ...

Research Algorithm on Building Intelligent Transportation System based on RFID Technology

Directory of Open Access Journals (Sweden)

Chuanqi Chen

2013-05-01

Full Text Available Intelligent transportation system to all aspects of organic integration of human, vehicle, road and environment of the transport system, so that the operation of functional integration and intelligent vehicle, road. Intelligent transportation system (ITS to improve the efficiency of traffic system by increasing the effective use and management of traffic information is mainly composed of information collection and input, output, control strategy, implementation of the subsystems of data transmission and communication subsystem. The RFID reader to wireless communication through the antenna and RFID tag can achieve a write operation on the tag identification codes and memory read data. The paper proposes research on building intelligent transportation system based on RFID technology. Experimental results show that ITS system can effectively improve the traffic situation, improve the utilization rate of the existing road resource and save social cost.

Depression In Gifted Intelligence As Compared With Normal Persons

Directory of Open Access Journals (Sweden)

Raeisi F

2004-08-01

Full Text Available Background: Depression is a common problem and reduces function of persons. Evaluation of this matter in Gifted Intelligence– because superior their beneficial ness– have more importance. Our aim in this study is to determine relative frequency of depression in Gifted Intelligence as compared with Normal persons. Materials and Methods: In the context of a case – control study 90 Normal volunteers and 56 very superior volunteers – aged between 20 and 30 years, so that matched in respect of gender – were investigated by Beck Depression Inventory. IQ identification was performed by both Wechsler Adult Intelligence scaling and Ravens progressive Matrices. Results: out of 90 Normal persons, 36 were depressed (40% and among 56 Gifted Intelligence, 35 were depressed. (62.5% In other words relative frequency of depression in Gifted Intelligence– with significant differences– is more.(P<0.05. Conclusion: Although Gifted Intelligence have more ability in opposition to stress- because higher level of IQ-but in this study was observed that prevalence of depression in Gifted Intelligence is more. This finding may be by reason of higher perception of them and the result of it– actually– more meeting of stress.

Assessing potentially gifted students from lower socioeconomic status with nonverbal measures of intelligence.

Science.gov (United States)

Shaunessy, Elizabeth; Karnes, Frances A; Cobb, Yolanda

2004-06-01

The screening and identification of gifted students has historically been conducted using verbal measures of intelligence. However, the underrepresentation in gifted programs of culturally diverse children, who may have limited English proficiency or cultural values different from those measured in traditional intelligence tests, has prompted researchers to consider other measures. Nonverbal measures of intelligence have been utilized to increase the number of gifted children from diverse backgrounds. Researchers in the current study sought to increase the number of culturally diverse gifted students at a rural public school enrolling predominantly African-American students from low socioeconomic homes. 169 students in Grades 2 through 6 were assessed using three nonverbal measures of intelligence: the Culture-Fair Intelligence Test, the Naglieri Nonverbal Abilities Test, and the Raven Standard Progressive Matrices. The scores on these nonverbal measures indicated that the Culture-Fair Intelligence Test and the Raven Standard Progressive Matrices identified more students than the Naglieri Nonverbal Abilities Test. A discussion of the results and implications for research are presented.

Diagnosis of class using swarm intelligence applied to problem of identification of nuclear transient

Energy Technology Data Exchange (ETDEWEB)

Villas Boas Junior, Manoel; Strauss, Edilberto, E-mail: junior@lmp.ufrj.b [Instituto Federal de Educacao, Ciencia e Tecnologia do Ceara/ Universidade do Estado do Ceara, Itaperi, CE (Brazil). Mestrado Integrado em Computacao Aplicada; Nicolau, Andressa dos Santos; Schirru, Roberto, E-mail: andressa@lmp.ufrj.b [Coordenacao dos Programas de Pos-Graduacao de Engenharia (PEN/COPPE/UFRJ), Rio de Janeiro, RJ (Brazil). Programa de Engenharia Nuclear; Mello, Flavio Luis de [Universidade Federal do Rio de Janeiro (POLI/UFRJ), RJ (Brazil). Escola Politecnica. Dept. de Engenharia Eletronica e Computacao

2011-07-01

This article presents a computational model of the diagnostic system of transient. The model makes use of segmentation techniques applied to support decision making, based on identification of classes and optimized by Particle Swarm Optimization algorithm (PSO). The method proposed aims to classify an anomalous event in the signatures of three classes of the design basis transients postulated for the Angra 2 nuclear plant, where the PSO algorithm is used as a method of separation of classes, being responsible for finding the best centroid prototype vector of each accident/transient, ie equivalent to Voronoi vector that maximizes the number of correct classifications. To make the calculation of similarity between the set of the variables anomalous event in a given time t, and the prototype vector of variables of accident/transients, the metrics of Manhattan, Euclidean and Minkowski were used. The results obtained by the method proposed were compatible with others methods reported in the literature, allowing a solution that approximates the ideal solution, ie the Voronoi vectors. (author)

Diagnosis of class using swarm intelligence applied to problem of identification of nuclear transient

International Nuclear Information System (INIS)

Villas Boas Junior, Manoel; Strauss, Edilberto; Nicolau, Andressa dos Santos; Schirru, Roberto; Mello, Flavio Luis de

2011-01-01

This article presents a computational model of the diagnostic system of transient. The model makes use of segmentation techniques applied to support decision making, based on identification of classes and optimized by Particle Swarm Optimization algorithm (PSO). The method proposed aims to classify an anomalous event in the signatures of three classes of the design basis transients postulated for the Angra 2 nuclear plant, where the PSO algorithm is used as a method of separation of classes, being responsible for finding the best centroid prototype vector of each accident/transient, ie equivalent to Voronoi vector that maximizes the number of correct classifications. To make the calculation of similarity between the set of the variables anomalous event in a given time t, and the prototype vector of variables of accident/transients, the metrics of Manhattan, Euclidean and Minkowski were used. The results obtained by the method proposed were compatible with others methods reported in the literature, allowing a solution that approximates the ideal solution, ie the Voronoi vectors. (author)

Probabilistic Cross-Identification of Cosmic Events

OpenAIRE

Budavari, Tamas

2011-01-01

We discuss a novel approach to identifying cosmic events in separate and independent observations. In our focus are the true events, such as supernova explosions, that happen once, hence, whose measurements are not repeatable. Their classification and analysis have to make the best use of all the available data. Bayesian hypothesis testing is used to associate streams of events in space and time. Probabilities are assigned to the matches by studying their rates of occurrence. A case study of ...

An intelligent signal processing and pattern recognition technique for defect identification using an active sensor network

Science.gov (United States)

Su, Zhongqing; Ye, Lin

2004-08-01

The practical utilization of elastic waves, e.g. Rayleigh-Lamb waves, in high-performance structural health monitoring techniques is somewhat impeded due to the complicated wave dispersion phenomena, the existence of multiple wave modes, the high susceptibility to diverse interferences, the bulky sampled data and the difficulty in signal interpretation. An intelligent signal processing and pattern recognition (ISPPR) approach using the wavelet transform and artificial neural network algorithms was developed; this was actualized in a signal processing package (SPP). The ISPPR technique comprehensively functions as signal filtration, data compression, characteristic extraction, information mapping and pattern recognition, capable of extracting essential yet concise features from acquired raw wave signals and further assisting in structural health evaluation. For validation, the SPP was applied to the prediction of crack growth in an alloy structural beam and construction of a damage parameter database for defect identification in CF/EP composite structures. It was clearly apparent that the elastic wave propagation-based damage assessment could be dramatically streamlined by introduction of the ISPPR technique.

Relationship between general intelligence, emotional intelligence, stress levels and stress reactivity.

Science.gov (United States)

Singh, Yogesh; Sharma, Ratna

2012-07-01

Stressful life events and daily life stresses have both deleterious and cumulative effects on human body. In several studies, stress has been shown to affect various parameter of higher mental function like attention, concentration, learning and memory. Present study was designed to explore the relationship among GI level, EI level, psychological stress levels and acute stress reactivity in young normal healthy subjects. The study was conducted on thirty four healthy male student volunteers to study a) acute stress reactivity in subjects with varying levels of General Intelligence (GI) and Emotional Intelligence (EI) and b) correlation between GI, EI, acute stress and perceived stress. Baseline GI and EI and acute stress and perceived stress scores were measured by standard assessment scales. Using median value of GI and EI scores as cutoff values, subjects were categorized into four groups. Among different GI-EI groups, acute stress reactivity was similar but salivary Cortisol (especially post stressor level) and perceived stress level was a differentiating factor. High level of EI was associated inversely with acute and chronic perceived stress level. Significant correlation was found between acute and chronic perceived stress levels. Level of general intelligence showed no relation to acute or chronic stress levels as well as acute stress reactivity. The differences in various groups of GI and EI had no effect on the baseline and post stress performance on Sternberg memory test and all the three conditions of Stroop test. In conclusion emotional intelligence as an attribute is better suited to handle day to day acute stress and chronic perceived stress.

1st International Conference on Advanced Intelligent System and Informatics

CERN Document Server

Hassanien, Aboul; El-Bendary, Nashwa; Dey, Nilanjan

2016-01-01

The conference topics address different theoretical and practical aspects, and implementing solutions for intelligent systems and informatics disciplines including bioinformatics, computer science, medical informatics, biology, social studies, as well as robotics research. The conference also discuss and present solutions to the cloud computing and big data mining which are considered hot research topics. The conference papers discussed different topics – techniques, models, methods, architectures, as well as multi aspect, domain-specific, and new solutions for the above disciplines. The accepted papers have been grouped into five parts: Part I—Intelligent Systems and Informatics, addressing topics including, but not limited to, medical application, predicting student performance, action classification, and detection of dead stained microscopic cells, optical character recognition, plant identification, rehabilitation of disabled people. Part II—Hybrid Intelligent Systems, addressing topics including, b...

Identification of Tropical-Extratropical Interactions and Extreme Precipitation Events in the Middle East based on Potential Vorticity and Moisture Transport

KAUST Repository

de Vries, A. J.; Ouwersloot, H. G.; Feldstein, S. B.; Riemer, M.; El Kenawy, A. M.; McCabe, Matthew; Lelieveld, J.

2017-01-01

) intrusion reaches deep into the subtropics and forces an incursion of high poleward vertically integrated water vapor transport (IVT) into the Middle East. This study presents an object-based identification method for extreme precipitation events based

Fire Play: ICCARUS--Intelligent Command and Control, Acquisition and Review Using Simulation

Science.gov (United States)

Powell, James; Wright, Theo; Newland, Paul; Creed, Chris; Logan, Brian

2008-01-01

Is it possible to educate a fire officer to deal intelligently with the command and control of a major fire event he will never have experienced? The authors of this paper believe there is, and present here just one solution to this training challenge. It involves the development of an intelligent simulation based upon computer managed interactive…

Why Efforts to Centralize the US Intelligence Community Fail

National Research Council Canada - National Science Library

Jones, Daniel B

2005-01-01

.... The attack on Pearl harbor and other events during that war created a growing consensus that the nation required a central authority to manage national intelligence pertinent to multiple departments of the government...

Initiating events identification of the IS process using the master logic diagram

International Nuclear Information System (INIS)

Cho, Nam Chul; Jae, Moo Sung; Yang, Joon Eon

2005-01-01

Hydrogen is very attractive as a future secondary energy carrier considering environmental problems. It is important to produce hydrogen from water by use of carbon free primary energy source. The thermochemical water decomposition cycle is one of the methods for the hydrogen production process from water. Japan Atomic Energy Research Institute (JAERI) has been carrying out an R and D on the IS (iodine.sulfur) process that was first proposed by GA (General Atomic Co.) focusing on demonstration the 'closed-cycle' continuous hydrogen production on developing a feasible and efficient scheme for the HI processing, and on screening and/or developing materials of construction to be used in the corrosive process environment. The successful continuous operation of the IS-process was demonstrated and this process is one of the thermochemical processes, which is the closest to being industrialized. Currently, Korea has also started a research about the IS process and the construction of the IS process system is planned. In this study, for risk analysis of the IS process, initiating events of the IS process are identified by using the Master Logic Diagram (MLD) that is method for initiating event identification

Combining metric episodes with semantic event concepts within the Symbolic and Sub-Symbolic Robotics Intelligence Control System (SS-RICS)

Science.gov (United States)

Kelley, Troy D.; McGhee, S.

2013-05-01

This paper describes the ongoing development of a robotic control architecture that inspired by computational cognitive architectures from the discipline of cognitive psychology. The Symbolic and Sub-Symbolic Robotics Intelligence Control System (SS-RICS) combines symbolic and sub-symbolic representations of knowledge into a unified control architecture. The new architecture leverages previous work in cognitive architectures, specifically the development of the Adaptive Character of Thought-Rational (ACT-R) and Soar. This paper details current work on learning from episodes or events. The use of episodic memory as a learning mechanism has, until recently, been largely ignored by computational cognitive architectures. This paper details work on metric level episodic memory streams and methods for translating episodes into abstract schemas. The presentation will include research on learning through novelty and self generated feedback mechanisms for autonomous systems.

“TOTTO-CHAN”: INSIGHTS INTO MULTIPLE INTELLIGENCES-BASED ENGLISH TEACHING TO YOUNG LEARNERS

Directory of Open Access Journals (Sweden)

K. M. Widi Hadiyanti

2017-04-01

Full Text Available Children are unique individuals who have their own ways to learn about the world and solve problems. It is supported by Gardner‘s ideas about multiple intelligences. Gardner (1993, 1998 suggested several kinds of intelligences. In their attempt to learn about the world, children make use of all resources, including their multiple intelligences. The application of multiple intelligences in teaching young learner seems to be apparent in Tetsuko Kuroyanagi‘s autobiographical memoir, ―Totto-chan: The Little Girl at the Window‖. This study identified and analyzed the techniques used to apply multiple intelligences in teaching young learners in Totto-chan‘s elementary school, Tomoe Gakuen. Based on the identification and analysis conducted in ―Totto-chan‖, this study elaborated the techniques in teaching English for young learners. In particular, this study proposed teaching techniques for four language skills. This study will be of great benefit for English teachers for young learners to enrich their teaching techniques that accord with the children nature of development.

The use of intelligent systems for risk management in software projects

Directory of Open Access Journals (Sweden)

Oksana A. Gushchina

2017-06-01

Full Text Available Introduction: The article identifies the main risks of a software project, examines the use of different types of intelligent systems in the risk management process for software projects, discusses the basic methods used for process estimation and forecasting in the field of software engineering, identifies currently used empty expert systems, software systems for analysis and risk management of software projects. Materials and Methods: The author describes the peculiarities of risk management in the field of software engineering with involvement of intelligent systems. The intelligent techniques allow solving the control task with expert precision without the involvement of human experts. Results: The result of this work: – identification of the key risks of a software project (tax, legal, financial and commercial risks, IT risks, personnel risks, risks related to competitors, suppliers, marketing and demand and market; – investigation of the current, applied to risk management of software system projects, artificial intelligence, particularly expert systems and software tools for evaluation of the process results; – identification of the most popular empty expert systems (Clips, G2 and Leonardo and software products of the analysis of large databases (Orange, Weka, Rattle GUI, Apache Mahout, SCaViS, RapidMiner, Databionic ESOM Tools, ELKI, KNIME, Pandas and UIMA; – consideration of the cluster, correlation, regression, factor and dispersion analysis methods for the estimation and prediction of the processes of software engineering. Discussion and Conclusions: The results show the feasibility of the application of various intelligent systems in the risk management process. The analysis of methods of evaluating risks and the tendency of their application in the modern systems of intellectual analysis can serve as a start point for creating a unified system of risk management for software projects of medium and high complexity with a

Important Themas in Artificial Intelligence

OpenAIRE

Šudoma, Petr

2013-01-01

The paper studies description logics as a method of field of artificial intelligence, describes history of knowledge representation as series of events leading to founding of description logics. Furthermore the paper compares description logics with their predecessor, the frame systems. Syntax, semantics and description logics naming convention is also presented and algorithms solving common knowledge representation tasks with usage of description logics are described. Paper compares computat...

FTRA 4th International Conference on Mobile, Ubiquitous, and Intelligent Computing

CERN Document Server

Adeli, Hojjat; Park, Namje; Woungang, Isaac

2014-01-01

MUSIC 2013 will be the most comprehensive text focused on the various aspects of Mobile, Ubiquitous and Intelligent computing. MUSIC 2013 provides an opportunity for academic and industry professionals to discuss the latest issues and progress in the area of intelligent technologies in mobile and ubiquitous computing environment. MUSIC 2013 is the next edition of the 3rd International Conference on Mobile, Ubiquitous, and Intelligent Computing (MUSIC-12, Vancouver, Canada, 2012) which was the next event in a series of highly successful International Workshop on Multimedia, Communication and Convergence technologies MCC-11 (Crete, Greece, June 2011), MCC-10 (Cebu, Philippines, August 2010).

Advanced and intelligent computations in diagnosis and control

CERN Document Server

2016-01-01

This book is devoted to the demands of research and industrial centers for diagnostics, monitoring and decision making systems that result from the increasing complexity of automation and systems, the need to ensure the highest level of reliability and safety, and continuing research and the development of innovative approaches to fault diagnosis. The contributions combine domains of engineering knowledge for diagnosis, including detection, isolation, localization, identification, reconfiguration and fault-tolerant control. The book is divided into six parts:  (I) Fault Detection and Isolation; (II) Estimation and Identification; (III) Robust and Fault Tolerant Control; (IV) Industrial and Medical Diagnostics; (V) Artificial Intelligence; (VI) Expert and Computer Systems.

Specimen Identification Errors in Breast Biopsies: Age Matters. Report of Two Near-Miss Events and Review of the Literature.

Science.gov (United States)

Tozbikian, Gary; Gemignani, Mary L; Brogi, Edi

2017-09-01

The consequences of patient identification errors due to specimen mislabeling can be deleterious. We describe two near-miss events involving mislabeled breast specimens from two patients who sought treatment at our institution. In both cases, microscopic review of the slides identified inconsistencies between the histologic findings and patient age, unveiling specimen identification errors. By correlating the clinical information with the microscopic findings, we identified mistakes that had occurred at the time of specimen accessioning at the original laboratories. In both cases, thanks to a timely reassignment of the specimens, the patients suffered no harm. These cases highlight the importance of routine clinical and pathologic correlation as a critical component of quality assurance and patient safety. A review of possible specimen identification errors in the anatomic pathology setting is presented. © 2017 Wiley Periodicals, Inc.

Information gathering, management and transfering for geospacial intelligence

Science.gov (United States)

Nunes, Paulo; Correia, Anacleto; Teodoro, M. Filomena

2017-07-01

Information is a key subject in modern organization operations. The success of joint and combined operations with organizations partners depends on the accurate information and knowledge flow concerning the operations theatre: provision of resources, environment evolution, markets location, where and when an event occurred. As in the past and nowadays we cannot conceive modern operations without maps and geo-spatial information (GI). Information and knowledge management is fundamental to the success of organizational decisions in an uncertainty environment. The georeferenced information management is a process of knowledge management, it begins in the raw data and ends on generating knowledge. GI and intelligence systems allow us to integrate all other forms of intelligence and can be a main platform to process and display geo-spatial-time referenced events. Combining explicit knowledge with peoples know-how to generate a continuous learning cycle that supports real time decisions mitigates the influences of fog of everyday competition and provides the knowledge supremacy. Extending the preliminary analysis done in [1], this work applies the exploratory factor analysis to a questionnaire about the GI and intelligence management in an organization company allowing to identify future lines of action to improve information process sharing and exploration of all the potential of this important resource.

Report order and identification of multidimensional stimuli: a study of event-related brain potentials.

Science.gov (United States)

Shieh, Kong-King; Shen, I-Hsuan

2004-06-01

An experiment was conducted to investigate the effect of order of report on multidimensional stimulus identification. Subjects were required to identify each two-dimensional symbol by pushing corresponding buttons on the keypad on which there were two columns representing the two dimensions. Order of report was manipulated for the dimension represented by the left or right column. Both behavioral data and event-related potentials were recorded from 14 college students. Behavioral data analysis showed that order of report had a significant effect on response times. Such results were consistent with those of previous studies. Analysis of event-related brain potentials showed significant differences in peak amplitude and mean amplitude at time windows of 120-250 msec. at Fz, F3, and F4 and of 350-750 msec. at Fz, F3, F4, Cz, and Pz. Data provided neurophysiological evidence that reporting dimensional values according to natural language habits was appropriate and less cognitively demanding.

Fatigue distribution optimization for offshore wind farms using intelligent agent control

DEFF Research Database (Denmark)

Zhao, Rongyong; Shen, Wen Zhong; Knudsen, Torben

2012-01-01

with its neighbouring downwind turbines and organizes them adaptively into a wind delivery group along the wind direction. The agent attributes and the event structure are designed on the basis of the intelligent agent theory by using the unified modelling language. The control strategy of the intelligent......A novel control approach is proposed to optimize the fatigue distribution of wind turbines in a large‐scale offshore wind farm on the basis of an intelligent agent theory. In this approach, each wind turbine is considered to be an intelligent agent. The turbine at the farm boundary communicates...... coefficient for every wind turbine. The optimization is constrained such that the average fatigue for every turbine is smaller than what would be achieved by conventional dispatch and such that the total power loss of the wind farm is restricted to a few percent of the total power. This intelligent agent...

Probabilistic analysis of external events with focus on the Fukushima event

International Nuclear Information System (INIS)

Kollasko, Heiko; Jockenhoevel-Barttfeld, Mariana; Klapp, Ulrich

2014-01-01

by the SKI guidance 2:27 and have been performed as part of the PSA for new plant designs and for installed based projects. Following the Fukushima event from March 2011, the methodology for screening external events has been reviewed at AREVA with respect to its applicability, limitations and to the identification of enhancement areas. This paper presents the screening analysis methodology to identify relevant external events and external event combinations. In line with the WENRA Position paper, this approach provides valuable input information for the identification of single external events and their combinations to create Fukushima-like rare and severe external hazards which may need to be addressed additionally to the general design basis as design extension hazards by realistic analyses rather than conservative. The analysis is based on a systematic identification of relevant external event combinations which includes earthquake-induced external events and takes into account a deterministic justification of the design basis for external events including beyond design external events. Lessons learnt from the Fukushima accident have been identified and evaluated in order to be considered for reinforcement in the identification, screening and in the detailed probabilistic analysis of external events. (authors)

EEG-Annotate: Automated identification and labeling of events in continuous signals with applications to EEG.

Science.gov (United States)

Su, Kyung-Min; Hairston, W David; Robbins, Kay

2018-01-01

In controlled laboratory EEG experiments, researchers carefully mark events and analyze subject responses time-locked to these events. Unfortunately, such markers may not be available or may come with poor timing resolution for experiments conducted in less-controlled naturalistic environments. We present an integrated event-identification method for identifying particular responses that occur in unlabeled continuously recorded EEG signals based on information from recordings of other subjects potentially performing related tasks. We introduce the idea of timing slack and timing-tolerant performance measures to deal with jitter inherent in such non-time-locked systems. We have developed an implementation available as an open-source MATLAB toolbox (http://github.com/VisLab/EEG-Annotate) and have made test data available in a separate data note. We applied the method to identify visual presentation events (both target and non-target) in data from an unlabeled subject using labeled data from other subjects with good sensitivity and specificity. The method also identified actual visual presentation events in the data that were not previously marked in the experiment. Although the method uses traditional classifiers for initial stages, the problem of identifying events based on the presence of stereotypical EEG responses is the converse of the traditional stimulus-response paradigm and has not been addressed in its current form. In addition to identifying potential events in unlabeled or incompletely labeled EEG, these methods also allow researchers to investigate whether particular stereotypical neural responses are present in other circumstances. Timing-tolerance has the added benefit of accommodating inter- and intra- subject timing variations. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

Hazardous Traffic Event Detection Using Markov Blanket and Sequential Minimal Optimization (MB-SMO

Directory of Open Access Journals (Sweden)

Lixin Yan

2016-07-01

Full Text Available The ability to identify hazardous traffic events is already considered as one of the most effective solutions for reducing the occurrence of crashes. Only certain particular hazardous traffic events have been studied in previous studies, which were mainly based on dedicated video stream data and GPS data. The objective of this study is twofold: (1 the Markov blanket (MB algorithm is employed to extract the main factors associated with hazardous traffic events; (2 a model is developed to identify hazardous traffic event using driving characteristics, vehicle trajectory, and vehicle position data. Twenty-two licensed drivers were recruited to carry out a natural driving experiment in Wuhan, China, and multi-sensor information data were collected for different types of traffic events. The results indicated that a vehicle’s speed, the standard deviation of speed, the standard deviation of skin conductance, the standard deviation of brake pressure, turn signal, the acceleration of steering, the standard deviation of acceleration, and the acceleration in Z (G have significant influences on hazardous traffic events. The sequential minimal optimization (SMO algorithm was adopted to build the identification model, and the accuracy of prediction was higher than 86%. Moreover, compared with other detection algorithms, the MB-SMO algorithm was ranked best in terms of the prediction accuracy. The conclusions can provide reference evidence for the development of dangerous situation warning products and the design of intelligent vehicles.

Toward an Intelligent Event Broker: Automated Transient Classificaiton

Science.gov (United States)

Wozniak, P.

In order to succeed, the massive time-domain surveys of the future must automatically identify actionable information from the torrent of imaging data, classify emerging events, and optimize the follow-up strategy. To address this challenge, we are developing a fully autonomous, distributed event broker that will integrate cutting edge machine learning algorithms with high performance computing infrastructure. The talk will give an overview of this work and recent progress on image level variability detection and spectral classification using low resolution spectra.

Assessing risk from intelligent attacks: A perspective on approaches

International Nuclear Information System (INIS)

Guikema, Seth D.; Aven, Terje

2010-01-01

Assessing the uncertainties in and severity of the consequences of intelligent attacks are fundamentally different from risk assessment for accidental events and other phenomena with inherently random failures. Intelligent attacks against a system involve adaptation on the part of the adversary. The probabilities of the initiating events depend on the risk management actions taken, and they may be more difficult to assess due to high degrees of epistemic uncertainty about the motivations and future actions of adversaries. Several fundamentally different frameworks have been proposed for assessing risk from intelligent attacks. These include basing risk assessment and management on game theoretic modelling of attacker actions, using a probabilistic risk analysis (PRA) approach based on eliciting probabilities of different initiating events from appropriate experts, assessing uncertainties beyond probabilities and expected values, and ignoring the probabilities of the attacks and choosing to protect highest valued targets. In this paper we discuss and compare the fundamental assumptions that underlie each of these approaches. We then suggest a new framework that makes the fundamental assumptions underlying the approaches clear to decision makers and presents them with a suite of results from conditional risk analysis methods. Each of the conditional methods presents the risk from a specified set of fundamental assumptions, allowing the decision maker to see the impacts of these assumptions on the risk management strategies considered and to weight the different conditional results with their assessments of the relative likelihood of the different sets of assumptions.

Constructive thinking, rational intelligence and irritable bowel syndrome.

Science.gov (United States)

Rey, Enrique; Moreno Ortega, Marta; Garcia Alonso, Monica-Olga; Diaz-Rubio, Manuel

2009-07-07

To evaluate rational and experiential intelligence in irritable bowel syndrome (IBS) sufferers. We recruited 100 subjects with IBS as per Rome II criteria (50 consulters and 50 non-consulters) and 100 healthy controls, matched by age, sex and educational level. Cases and controls completed a clinical questionnaire (including symptom characteristics and medical consultation) and the following tests: rational-intelligence (Wechsler Adult Intelligence Scale, 3rd edition); experiential-intelligence (Constructive Thinking Inventory); personality (NEO personality inventory); psychopathology (MMPI-2), anxiety (state-trait anxiety inventory) and life events (social readjustment rating scale). Analysis of variance was used to compare the test results of IBS-sufferers and controls, and a logistic regression model was then constructed and adjusted for age, sex and educational level to evaluate any possible association with IBS. No differences were found between IBS cases and controls in terms of IQ (102.0 +/- 10.8 vs 102.8 +/- 12.6), but IBS sufferers scored significantly lower in global constructive thinking (43.7 +/- 9.4 vs 49.6 +/- 9.7). In the logistic regression model, global constructive thinking score was independently linked to suffering from IBS [OR 0.92 (0.87-0.97)], without significant OR for total IQ. IBS subjects do not show lower rational intelligence than controls, but lower experiential intelligence is nevertheless associated with IBS.

Personality and intelligence: persistence, not self-directedness, cooperativeness or self-transcendence, is related to twins’ cognitive abilities

Directory of Open Access Journals (Sweden)

Fariba Mousavi

2015-08-01

Full Text Available Background. A person-centered approach focusing on the interaction of an individual’s temperament-character-life events is essential in the path of individuals’ well-being. In this context, three character traits, Self-directedness (e.g., self-acceptance, self-control, goal-directed behavior, Cooperativeness (e.g., social affiliation, social tolerance, empathy and helpfulness and Self-transcendence (e.g., spiritual acceptance, transpersonal identification, measured using Cloninger’s model of personality are suggested to help the individual to regulate and resolve the conflicts derived from her/his temperament combinations as a reaction to life events. However, if character is related to the individual’s cognitive ability, then this association might limit any intervention that focuses on character development. We used data from the Child and Adolescent Twin Study in Sweden (CATSS to investigate the relationship between personality and cognitive ability.Method. The sample consisted of 370 15-year-old twins (159 girls/211 boys, 192 of whom screen-positive with various types of mental health problems. We used the Temperament and Character Inventory to measure personality and the Wechsler Intelligence Scales for Children (WISC-IV to measure intelligence. The relationship was investigated using correlation analyses using random-selected twins from each dyad and separately for monozygotic and dizygotic twins. Additional analyses investigated the genetic and environmental effects on personality and cognitive ability in this specific sample.Results. There were no significant correlations between the WISC-IV indices and any of the character traits (i.e., Self-directedness, Cooperativeness, and Self-transcendence. Persistence was significantly related, if weak, to four WISC-IV indices: Verbal Comprehension, Perceptual Reasoning, Working Memory, and the Full WISC-IV Scale. Post-hoc cross-twin/cross-trait analyses showed that the Persistence

Personality and intelligence: persistence, not self-directedness, cooperativeness or self-transcendence, is related to twins' cognitive abilities.

Science.gov (United States)

Mousavi, Fariba; Rozsa, Sandor; Nilsson, Thomas; Archer, Trevor; Anckarsäter, Henrik; Garcia, Danilo

2015-01-01

Background. A person-centered approach focusing on the interaction of an individual's temperament-character-life events is essential in the path of individuals' well-being. In this context, three character traits, Self-directedness (e.g., self-acceptance, self-control, goal-directed behavior), Cooperativeness (e.g., social affiliation, social tolerance, empathy and helpfulness) and Self-transcendence (e.g., spiritual acceptance, transpersonal identification), measured using Cloninger's model of personality are suggested to help the individual to regulate and resolve the conflicts derived from her/his temperament combinations as a reaction to life events. However, if character is related to the individual's cognitive ability, then this association might limit any intervention that focuses on character development. We used data from the Child and Adolescent Twin Study in Sweden (CATSS) to investigate the relationship between personality and cognitive ability. Method. The sample consisted of 370 15-year-old twins (159 girls/211 boys), 192 of whom screen-positive with various types of mental health problems. We used the Temperament and Character Inventory to measure personality and the Wechsler Intelligence Scales for Children (WISC-IV) to measure intelligence. The relationship was investigated using correlation analyses using random-selected twins from each dyad and separately for monozygotic and dizygotic twins. Additional analyses investigated the genetic and environmental effects on personality and cognitive ability in this specific sample. Results. There were no significant correlations between the WISC-IV indices and any of the character traits (i.e., Self-directedness, Cooperativeness, and Self-transcendence). Persistence was significantly related, if weak, to four WISC-IV indices: Verbal Comprehension, Perceptual Reasoning, Working Memory, and the Full WISC-IV Scale. Post-hoc cross-twin/cross-trait analyses showed that the Persistence-cognitive ability

Personality and intelligence: persistence, not self-directedness, cooperativeness or self-transcendence, is related to twins’ cognitive abilities

Science.gov (United States)

Mousavi, Fariba; Rozsa, Sandor; Nilsson, Thomas; Archer, Trevor; Anckarsäter, Henrik

2015-01-01

Background. A person-centered approach focusing on the interaction of an individual’s temperament-character-life events is essential in the path of individuals’ well-being. In this context, three character traits, Self-directedness (e.g., self-acceptance, self-control, goal-directed behavior), Cooperativeness (e.g., social affiliation, social tolerance, empathy and helpfulness) and Self-transcendence (e.g., spiritual acceptance, transpersonal identification), measured using Cloninger’s model of personality are suggested to help the individual to regulate and resolve the conflicts derived from her/his temperament combinations as a reaction to life events. However, if character is related to the individual’s cognitive ability, then this association might limit any intervention that focuses on character development. We used data from the Child and Adolescent Twin Study in Sweden (CATSS) to investigate the relationship between personality and cognitive ability. Method. The sample consisted of 370 15-year-old twins (159 girls/211 boys), 192 of whom screen-positive with various types of mental health problems. We used the Temperament and Character Inventory to measure personality and the Wechsler Intelligence Scales for Children (WISC-IV) to measure intelligence. The relationship was investigated using correlation analyses using random-selected twins from each dyad and separately for monozygotic and dizygotic twins. Additional analyses investigated the genetic and environmental effects on personality and cognitive ability in this specific sample. Results. There were no significant correlations between the WISC-IV indices and any of the character traits (i.e., Self-directedness, Cooperativeness, and Self-transcendence). Persistence was significantly related, if weak, to four WISC-IV indices: Verbal Comprehension, Perceptual Reasoning, Working Memory, and the Full WISC-IV Scale. Post-hoc cross-twin/cross-trait analyses showed that the Persistence-cognitive ability

A New Dimension of Business Intelligence: Location-based Intelligence

OpenAIRE

Zeljko Panian

2012-01-01

Through the course of this paper we define Locationbased Intelligence (LBI) which is outgrowing from process of amalgamation of geolocation and Business Intelligence. Amalgamating geolocation with traditional Business Intelligence (BI) results in a new dimension of BI named Location-based Intelligence. LBI is defined as leveraging unified location information for business intelligence. Collectively, enterprises can transform location data into business intelligence applic...

Identification of the high pt jet events produced by a resolved photon at HERA and reconstruction of the initial state parton kinematics

International Nuclear Information System (INIS)

D'Agostini, G.; Monaldi, D.

1992-01-01

We have studied the possibility offered by the HERA detectors to identify the events where a proton interacts with a parton of the (quasi) real photon. We find that the presence of hadronic fragments of the photon outside of the beam pipe allows the identification of the two jet events produced by a resolved photon, with good efficiency and low background from the direct photon events. We show that it is also possible to reconstruct the fractional momenta of the two incoming partons. (orig.)

Multi-intelligence critical rating assessment of fusion techniques (MiCRAFT)

Science.gov (United States)

Blasch, Erik

2015-06-01

Assessment of multi-intelligence fusion techniques includes credibility of algorithm performance, quality of results against mission needs, and usability in a work-domain context. Situation awareness (SAW) brings together low-level information fusion (tracking and identification), high-level information fusion (threat and scenario-based assessment), and information fusion level 5 user refinement (physical, cognitive, and information tasks). To measure SAW, we discuss the SAGAT (Situational Awareness Global Assessment Technique) technique for a multi-intelligence fusion (MIF) system assessment that focuses on the advantages of MIF against single intelligence sources. Building on the NASA TLX (Task Load Index), SAGAT probes, SART (Situational Awareness Rating Technique) questionnaires, and CDM (Critical Decision Method) decision points; we highlight these tools for use in a Multi-Intelligence Critical Rating Assessment of Fusion Techniques (MiCRAFT). The focus is to measure user refinement of a situation over the information fusion quality of service (QoS) metrics: timeliness, accuracy, confidence, workload (cost), and attention (throughput). A key component of any user analysis includes correlation, association, and summarization of data; so we also seek measures of product quality and QuEST of information. Building a notion of product quality from multi-intelligence tools is typically subjective which needs to be aligned with objective machine metrics.

Tracking and Particle Identification at LHCb and Strange Hadron Production in Events with Z Boson

CERN Document Server

AUTHOR|(INSPIRE)INSPIRE-00392146; Serra, N.; Mueller, K; Steinkamp, O

The Lhcb experiment, located at the Large Hadron Collider at CERN, is a high energy particle physics experiment dedicated to precision measurements of events containing beauty and charm quarks. The detector is built as a single-arm forward spectrometer. It uses tracking stations upstream and downstream of its dipole magnet to measure the trajectories and momenta of charged particles. This thesis describes the improvements to the track reconstruction algorithm, which were implemented for the second run of the LHC that started in spring 2015. Furthermore, the method to confirm the performance numbers on data is presented. In addition to the tracking system, the detector uses two Ring Imaging Cherenkov detectors, upstream and downstream of the dipole magnet, together with the calorimeter and muon system, for particle identification. The detector response for the particle identification is known to be poorly modelled, since the dependence on environmental variables like temperature and pressure inside the gas mo...

Intelligence analysis – the royal discipline of Competitive Intelligence

Directory of Open Access Journals (Sweden)

František Bartes

2011-01-01

Full Text Available The aim of this article is to propose work methodology for Competitive Intelligence teams in one of the intelligence cycle’s specific area, in the so-called “Intelligence Analysis”. Intelligence Analysis is one of the stages of the Intelligence Cycle in which data from both the primary and secondary research are analyzed. The main result of the effort is the creation of added value for the information collected. Company Competiitve Intelligence, correctly understood and implemented in business practice, is the “forecasting of the future”. That is forecasting about the future, which forms the basis for strategic decisions made by the company’s top management. To implement that requirement in corporate practice, the author perceives Competitive Intelligence as a systemic application discipline. This approach allows him to propose a “Work Plan” for Competitive Intelligence as a fundamental standardized document to steer Competitive Intelligence team activities. The author divides the Competitive Intelligence team work plan into five basic parts. Those parts are derived from the five-stage model of the intelligence cycle, which, in the author’s opinion, is more appropriate for complicated cases of Competitive Intelligence.

Corporate Education in perspective of Organizational Intelligence

Directory of Open Access Journals (Sweden)

Kelly Cristina Wilhelm de Toni

2016-12-01

Full Text Available Introduction: To meet the challenges of competitiveness and achieve the conditions for generation of innovation is necessary to ensure that the workforce remains highly qualified. In this context, corporate education is an alternative. Objective: To develop a method to analyze the relationship between process approaches Organizational Intelligence and Corporate Education. Methodology: Theoretical construction performed based on literature review.Construction a methodological approach linked to the problem of this research. Results: Identification of a set of common elements between the approaches: the"Capture" and "Sharing" of knowledge and experience, the "meaning" shared and "Culture" of individual and organizational learning. Conclusions: There is a real connection between the approaches of the study. The proposed method can be seen as a tool to explain and evaluate the process of education in the enterprise from the perspective of organizational intelligence

Spiritual Intelligence, Emotional Intelligence and Auditor’s Performance

OpenAIRE

Hanafi, Rustam

2010-01-01

The objective of this research was to investigate empirical evidence about influence audi-tor spiritual intelligence on the performance with emotional intelligence as a mediator variable. Linear regression models are developed to examine the hypothesis and path analysis. The de-pendent variable of each model is auditor performance, whereas the independent variable of model 1 is spiritual intelligence, of model 2 are emotional intelligence and spiritual intelligence. The parameters were estima...

Intelligent agents for training on-board fire fighting

NARCIS (Netherlands)

Bosch, K. van den; Harbers, M.; Heuvelink, A.; Doesburg, W. van

2009-01-01

Simulation-based training in complex decision making often requires ample personnel for playing various roles (e.g. team mates, adversaries). Using intelligent agents may diminish the need for staff. However, to achieve goal-directed training, events in the simulation as well as the behavior of key

Intelligent Fish Freshness Assessment

Directory of Open Access Journals (Sweden)

Hamid Gholam Hosseini

2008-01-01

Full Text Available Fish species identification and automated fish freshness assessment play important roles in fishery industry applications. This paper describes a method based on support vector machines (SVMs to improve the performance of fish identification systems. The result is used for the assessment of fish freshness using artificial neural network (ANN. Identification of the fish species involves processing of the images of fish. The most efficient features were extracted and combined with the down-sampled version of the images to create a 1D input vector. Max-Win algorithm applied to the SVM-based classifiers has enhanced the reliability of sorting to 96.46%. The realisation of Cyranose 320 Electronic nose (E-nose, in order to evaluate the fish freshness in real-time, is experimented. Intelligent processing of the sensor patterns involves the use of a dedicated ANN for each species under study. The best estimation of freshness was provided by the most sensitive sensors. Data was collected from four selected species of fishes over a period of ten days. It was concluded that the performance can be increased using individual trained ANN for each specie. The proposed system has been successful in identifying the number of days after catching the fish with an accuracy of up to 91%.

The pathways for intelligible speech: multivariate and univariate perspectives.

Science.gov (United States)

Evans, S; Kyong, J S; Rosen, S; Golestani, N; Warren, J E; McGettigan, C; Mourão-Miranda, J; Wise, R J S; Scott, S K

2014-09-01

An anterior pathway, concerned with extracting meaning from sound, has been identified in nonhuman primates. An analogous pathway has been suggested in humans, but controversy exists concerning the degree of lateralization and the precise location where responses to intelligible speech emerge. We have demonstrated that the left anterior superior temporal sulcus (STS) responds preferentially to intelligible speech (Scott SK, Blank CC, Rosen S, Wise RJS. 2000. Identification of a pathway for intelligible speech in the left temporal lobe. Brain. 123:2400-2406.). A functional magnetic resonance imaging study in Cerebral Cortex used equivalent stimuli and univariate and multivariate analyses to argue for the greater importance of bilateral posterior when compared with the left anterior STS in responding to intelligible speech (Okada K, Rong F, Venezia J, Matchin W, Hsieh IH, Saberi K, Serences JT,Hickok G. 2010. Hierarchical organization of human auditory cortex: evidence from acoustic invariance in the response to intelligible speech. 20: 2486-2495.). Here, we also replicate our original study, demonstrating that the left anterior STS exhibits the strongest univariate response and, in decoding using the bilateral temporal cortex, contains the most informative voxels showing an increased response to intelligible speech. In contrast, in classifications using local "searchlights" and a whole brain analysis, we find greater classification accuracy in posterior rather than anterior temporal regions. Thus, we show that the precise nature of the multivariate analysis used will emphasize different response profiles associated with complex sound to speech processing. © The Author 2013. Published by Oxford University Press.

Integrating artificial intelligence with real-time intracranial EEG monitoring to automate interictal identification of seizure onset zones in focal epilepsy.

Science.gov (United States)

Varatharajah, Yogatheesan; Berry, Brent; Cimbalnik, Jan; Kremen, Vaclav; Van Gompel, Jamie; Stead, Matt; Brinkmann, Benjamin; Iyer, Ravishankar; Worrell, Gregory

2018-08-01

An ability to map seizure-generating brain tissue, i.e. the seizure onset zone (SOZ), without recording actual seizures could reduce the duration of invasive EEG monitoring for patients with drug-resistant epilepsy. A widely-adopted practice in the literature is to compare the incidence (events/time) of putative pathological electrophysiological biomarkers associated with epileptic brain tissue with the SOZ determined from spontaneous seizures recorded with intracranial EEG, primarily using a single biomarker. Clinical translation of the previous efforts suffers from their inability to generalize across multiple patients because of (a) the inter-patient variability and (b) the temporal variability in the epileptogenic activity. Here, we report an artificial intelligence-based approach for combining multiple interictal electrophysiological biomarkers and their temporal characteristics as a way of accounting for the above barriers and show that it can reliably identify seizure onset zones in a study cohort of 82 patients who underwent evaluation for drug-resistant epilepsy. Our investigation provides evidence that utilizing the complementary information provided by multiple electrophysiological biomarkers and their temporal characteristics can significantly improve the localization potential compared to previously published single-biomarker incidence-based approaches, resulting in an average area under ROC curve (AUC) value of 0.73 in a cohort of 82 patients. Our results also suggest that recording durations between 90 min and 2 h are sufficient to localize SOZs with accuracies that may prove clinically relevant. The successful validation of our approach on a large cohort of 82 patients warrants future investigation on the feasibility of utilizing intra-operative EEG monitoring and artificial intelligence to localize epileptogenic brain tissue. Broadly, our study demonstrates the use of artificial intelligence coupled with careful feature engineering in

Intelligence analysis – the royal discipline of Competitive Intelligence

OpenAIRE

František Bartes

2011-01-01

The aim of this article is to propose work methodology for Competitive Intelligence teams in one of the intelligence cycle’s specific area, in the so-called “Intelligence Analysis”. Intelligence Analysis is one of the stages of the Intelligence Cycle in which data from both the primary and secondary research are analyzed. The main result of the effort is the creation of added value for the information collected. Company Competiitve Intelligence, correctly understood and implemented in busines...

Event detection for car park entries by video-surveillance

Science.gov (United States)

Coquin, Didier; Tailland, Johan; Cintract, Michel

2007-10-01

Intelligent surveillance has become an important research issue due to the high cost and low efficiency of human supervisors, and machine intelligence is required to provide a solution for automated event detection. In this paper we describe a real-time system that has been used for detecting car park entries, using an adaptive background learning algorithm and two indicators representing activity and identity to overcome the difficulty of tracking objects.

Automation of gender determination in human canines using artificial intelligence

Directory of Open Access Journals (Sweden)

F. Fidya

2017-09-01

Full Text Available Background: Gender determination is an important aspect of the identification process. The tooth represents a part of the human body that indicates the nature of sexual dimorphism. Artificial intelligence enables computers to perform to the same standard the same tasks as those carried out by humans. Several methods of classification exist within an artificial intelligence approach to identifying sexual dimorphism in canines. Purpose: This study aimed to quantify the respective accuracy of the Naive Bayes, decision tree, and multi-layer perceptron (MLP methods in identifying sexual dimorphism in canines. Methods: A sample of results derived from 100 measurements of the diameter of mesiodistal, buccolingual, and diagonal upper and lower canine jaw models of both genders were entered into an application computer program that implements the algorithm (MLP. The analytical process was conducted by the program to obtain a classification model with testing being subsequently carried out in order to obtain 50 new measurement results, 25 each for males and females. A comparative analysis was conducted on the program-generated information. Results: The accuracy rate of the Naive Bayes method was 82%, while that of the decision tree and MLP amounted to 84%. The MLP method had an absolute error value lower than that of its decision tree counterpart. Conclusion: The use of artificial intelligence methods produced a highly accurate identification process relating to the gender determination of canine teeth. The most appropriate method was the MLP with an accuracy rate of 84%.

Access control and personal identification systems

CERN Document Server

Bowers, Dan M

1988-01-01

Access Control and Personal Identification Systems provides an education in the field of access control and personal identification systems, which is essential in selecting the appropriate equipment, dealing intelligently with vendors in purchases of the equipment, and integrating the equipment into a total effective system. Access control devices and systems comprise an important part of almost every security system, but are seldom the sole source of security. In order for the goals of the total system to be met, the other portions of the security system must also be well planned and executed

基于激光传感器的智能车路径识别系统设计%The Design of Intelligent Vehicle Path Identification System Based on Laser Sensor

Institute of Scientific and Technical Information of China (English)

罗强; 徐文城; 刘尧

2012-01-01

The self - tracking intelligent vehicle path identification system is achieved in this paper. The system is based on laser sensors. The hardware and algorithm of the system is designed in this paper. The capability of Previem and Immunity of the Intelligent Vehicle is improved. Experiment shows that this system is much more stable and accurate, can make the Intelligent Vehicle run steadily by 2. 7m/s . By using the system, we have a better result in the race.%实现了一种自主式循迹智能车路径识别系统,设计了基于激光传感器的路径识别系统的硬件和控制算法,提高了光电式智能车的前瞻和抗干扰能力.实践表明,具有较高的稳定性和准确性,可使智能车以2.7 m/s的平均速度稳定运行,已在竞赛中取得了良好的成绩.

Detection and intelligent systems for homeland security

CERN Document Server

Voeller, John G

2014-01-01

Detection and Intelligent Systems for Homeland Security features articles from the Wiley Handbook of Science and Technology for Homeland Security covering advanced technology for image and video interpretation systems used for surveillance, which help in solving such problems as identifying faces from live streaming or stored videos. Biometrics for human identification, including eye retinas and irises, and facial patterns are also presented. The book then provides information on sensors for detection of explosive and radioactive materials and methods for sensing chemical

Web Intelligence and Artificial Intelligence in Education

Science.gov (United States)

Devedzic, Vladan

2004-01-01

This paper surveys important aspects of Web Intelligence (WI) in the context of Artificial Intelligence in Education (AIED) research. WI explores the fundamental roles as well as practical impacts of Artificial Intelligence (AI) and advanced Information Technology (IT) on the next generation of Web-related products, systems, services, and…

The Frasnian-Famennian mass killing event(s), methods of identification and evaluation

Science.gov (United States)

Geldsetzer, H. H. J.

1988-01-01

The absence of an abnormally high number of earlier Devonian taxa from Famennian sediments was repeatedly documented and can hardly be questioned. Primary recognition of the event(s) was based on paleontological data, especially common macrofossils. Most paleontologists place the disappearance of these common forms at the gigas/triangularis contact and this boundary was recently proposed as the Frasnian-Famennian (F-F) boundary. Not unexpectedly, alternate F-F positions were suggested caused by temporary Frasnian survivors or sudden post-event radiations of new forms. Secondary supporting evidence for mass killing event(s) is supplied by trace element and stable isotope geochemistry but not with the same success as for the K/T boundary, probably due to additional 300 ma of tectonic and diagenetic overprinting. Another tool is microfacies analysis which is surprisingly rarely used even though it can explain geochemical anomalies or paleontological overlap not detectable by conventional macrofacies analysis. The combination of microfacies analysis and geochemistry was applied at two F-F sections in western Canada and showed how interdependent the two methods are. Additional F-F sections from western Canada, western United States, France, Germany and Australia were sampled or re-sampled and await geochemical/microfacies evaluation.

Artificial Intelligence and Moral intelligence

Directory of Open Access Journals (Sweden)

Laura Pana

2008-07-01

Full Text Available We discuss the thesis that the implementation of a moral code in the behaviour of artificial intelligent systems needs a specific form of human and artificial intelligence, not just an abstract intelligence. We present intelligence as a system with an internal structure and the structural levels of the moral system, as well as certain characteristics of artificial intelligent agents which can/must be treated as 1- individual entities (with a complex, specialized, autonomous or selfdetermined, even unpredictable conduct, 2- entities endowed with diverse or even multiple intelligence forms, like moral intelligence, 3- open and, even, free-conduct performing systems (with specific, flexible and heuristic mechanisms and procedures of decision, 4 – systems which are open to education, not just to instruction, 5- entities with “lifegraphy”, not just “stategraphy”, 6- equipped not just with automatisms but with beliefs (cognitive and affective complexes, 7- capable even of reflection (“moral life” is a form of spiritual, not just of conscious activity, 8 – elements/members of some real (corporal or virtual community, 9 – cultural beings: free conduct gives cultural value to the action of a ”natural” or artificial being. Implementation of such characteristics does not necessarily suppose efforts to design, construct and educate machines like human beings. The human moral code is irremediably imperfect: it is a morality of preference, of accountability (not of responsibility and a morality of non-liberty, which cannot be remedied by the invention of ethical systems, by the circulation of ideal values and by ethical (even computing education. But such an imperfect morality needs perfect instruments for its implementation: applications of special logic fields; efficient psychological (theoretical and technical attainments to endow the machine not just with intelligence, but with conscience and even spirit; comprehensive technical

Intelligible Artificial Intelligence

OpenAIRE

Weld, Daniel S.; Bansal, Gagan

2018-01-01

Since Artificial Intelligence (AI) software uses techniques like deep lookahead search and stochastic optimization of huge neural networks to fit mammoth datasets, it often results in complex behavior that is difficult for people to understand. Yet organizations are deploying AI algorithms in many mission-critical settings. In order to trust their behavior, we must make it intelligible --- either by using inherently interpretable models or by developing methods for explaining otherwise overwh...

Naturalist Intelligence Among the Other Multiple Intelligences [In Bulgarian

Directory of Open Access Journals (Sweden)

R. Genkov

2007-09-01

Full Text Available The theory of multiple intelligences was presented by Gardner in 1983. The theory was revised later (1999 and among the other intelligences a naturalist intelligence was added. The criteria for distinguishing of the different types of intelligences are considered. While Gardner restricted the analysis of the naturalist intelligence with examples from the living nature only, the present paper considered this problem on wider background including objects and persons of the natural sciences.

Recent advances in swarm intelligence and evolutionary computation

CERN Document Server

2015-01-01

This timely review volume summarizes the state-of-the-art developments in nature-inspired algorithms and applications with the emphasis on swarm intelligence and bio-inspired computation. Topics include the analysis and overview of swarm intelligence and evolutionary computation, hybrid metaheuristic algorithms, bat algorithm, discrete cuckoo search, firefly algorithm, particle swarm optimization, and harmony search as well as convergent hybridization. Application case studies have focused on the dehydration of fruits and vegetables by the firefly algorithm and goal programming, feature selection by the binary flower pollination algorithm, job shop scheduling, single row facility layout optimization, training of feed-forward neural networks, damage and stiffness identification, synthesis of cross-ambiguity functions by the bat algorithm, web document clustering, truss analysis, water distribution networks, sustainable building designs and others. As a timely review, this book can serve as an ideal reference f...

Artificial intelligence

CERN Document Server

Hunt, Earl B

1975-01-01

Artificial Intelligence provides information pertinent to the fundamental aspects of artificial intelligence. This book presents the basic mathematical and computational approaches to problems in the artificial intelligence field.Organized into four parts encompassing 16 chapters, this book begins with an overview of the various fields of artificial intelligence. This text then attempts to connect artificial intelligence problems to some of the notions of computability and abstract computing devices. Other chapters consider the general notion of computability, with focus on the interaction bet

Executive functioning in schizophrenia: Unique and shared variance with measures of fluid intelligence.

Science.gov (United States)

Martin, A K; Mowry, B; Reutens, D; Robinson, G A

2015-10-01

Patients with schizophrenia often display deficits on tasks thought to measure "executive" processes. Recently, it has been suggested that reductions in fluid intelligence test performance entirely explain deficits reported for patients with focal frontal lesions on classical executive tasks. For patients with schizophrenia, it is unclear whether deficits on executive tasks are entirely accountable by fluid intelligence and representative of a common general process or best accounted for by distinct contributions to the cognitive profile of schizophrenia. In the current study, 50 patients with schizophrenia and 50 age, sex and premorbid intelligence matched controls were assessed using a broad neuropsychological battery, including tasks considered sensitive to executive abilities, namely the Hayling Sentence Completion Test (HSCT), word fluency, Stroop test, digit-span backwards, and spatial working memory. Fluid intelligence was measured using both the Matrix reasoning subtest from the Weschler Abbreviated Scale of Intelligence (WASI) and a composite score derived from a number of cognitive tests. Patients with schizophrenia were impaired on all cognitive measures compared with controls, except smell identification and the optimal betting and risk-taking measures from the Cambridge Gambling Task. After introducing fluid intelligence as a covariate, significant differences remained for HSCT suppression errors, and classical executive function tests such as the Stroop test and semantic/phonemic word fluency, regardless of which fluid intelligence measure was included. Fluid intelligence does not entirely explain impaired performance on all tests considered as reflecting "executive" processes. For schizophrenia, these measures should remain part of a comprehensive neuropsychological assessment alongside a measure of fluid intelligence. Copyright © 2015 Elsevier Inc. All rights reserved.

Intelligence Ethics:

DEFF Research Database (Denmark)

Rønn, Kira Vrist

2016-01-01

Questions concerning what constitutes a morally justified conduct of intelligence activities have received increased attention in recent decades. However, intelligence ethics is not yet homogeneous or embedded as a solid research field. The aim of this article is to sketch the state of the art...... of intelligence ethics and point out subjects for further scrutiny in future research. The review clusters the literature on intelligence ethics into two groups: respectively, contributions on external topics (i.e., the accountability of and the public trust in intelligence agencies) and internal topics (i.......e., the search for an ideal ethical framework for intelligence actions). The article concludes that there are many holes to fill for future studies on intelligence ethics both in external and internal discussions. Thus, the article is an invitation – especially, to moral philosophers and political theorists...

#%Applications of artificial intelligence in intelligent manufacturing: a review

Institute of Scientific and Technical Information of China (English)

#

2017-01-01

#%Based on research into the applications of artificial intelligence (AI) technology in the manufacturing industry in recent years, we analyze the rapid development of core technologies in the new era of 'Internet plus AI', which is triggering a great change in the models, means, and ecosystems of the manufacturing industry, as well as in the development of AI. We then propose new models, means, and forms of intelligent manufacturing, intelligent manufacturing system architecture, and intelligent man-ufacturing technology system, based on the integration of AI technology with information communications, manufacturing, and related product technology. Moreover, from the perspectives of intelligent manufacturing application technology, industry, and application demonstration, the current development in intelligent manufacturing is discussed. Finally, suggestions for the appli-cation of AI in intelligent manufacturing in China are presented.

Evaluation of a preschool nutrition education program based on the theory of multiple intelligences.

Science.gov (United States)

Cason, K L

2001-01-01

This report describes the evaluation of a preschool nutrition education program based on the theory of multiple intelligences. Forty-six nutrition educators provided a series of 12 lessons to 6102 preschool-age children. The program was evaluated using a pretest/post-test design to assess differences in fruit and vegetable identification, healthy snack choices, willingness to taste foods, and eating behaviors. Subjects showed significant improvement in food identification and recognition, healthy snack identification, willingness to taste foods, and frequency of fruit, vegetable, meat, and dairy consumption. The evaluation indicates that the program was an effective approach for educating preschool children about nutrition.

Advances in neural networks computational intelligence for ICT

CERN Document Server

Esposito, Anna; Morabito, Francesco; Pasero, Eros

2016-01-01

This carefully edited book is putting emphasis on computational and artificial intelligent methods for learning and their relative applications in robotics, embedded systems, and ICT interfaces for psychological and neurological diseases. The book is a follow-up of the scientific workshop on Neural Networks (WIRN 2015) held in Vietri sul Mare, Italy, from the 20th to the 22nd of May 2015. The workshop, at its 27th edition became a traditional scientific event that brought together scientists from many countries, and several scientific disciplines. Each chapter is an extended version of the original contribution presented at the workshop, and together with the reviewers’ peer revisions it also benefits from the live discussion during the presentation. The content of book is organized in the following sections. 1. Introduction, 2. Machine Learning, 3. Artificial Neural Networks: Algorithms and models, 4. Intelligent Cyberphysical and Embedded System, 5. Computational Intelligence Methods for Biomedical ICT in...

A novel GLM-based method for the Automatic IDentification of functional Events (AIDE) in fNIRS data recorded in naturalistic environments.

Science.gov (United States)

Pinti, Paola; Merla, Arcangelo; Aichelburg, Clarisse; Lind, Frida; Power, Sarah; Swingler, Elizabeth; Hamilton, Antonia; Gilbert, Sam; Burgess, Paul W; Tachtsidis, Ilias

2017-07-15

Recent technological advances have allowed the development of portable functional Near-Infrared Spectroscopy (fNIRS) devices that can be used to perform neuroimaging in the real-world. However, as real-world experiments are designed to mimic everyday life situations, the identification of event onsets can be extremely challenging and time-consuming. Here, we present a novel analysis method based on the general linear model (GLM) least square fit analysis for the Automatic IDentification of functional Events (or AIDE) directly from real-world fNIRS neuroimaging data. In order to investigate the accuracy and feasibility of this method, as a proof-of-principle we applied the algorithm to (i) synthetic fNIRS data simulating both block-, event-related and mixed-design experiments and (ii) experimental fNIRS data recorded during a conventional lab-based task (involving maths). AIDE was able to recover functional events from simulated fNIRS data with an accuracy of 89%, 97% and 91% for the simulated block-, event-related and mixed-design experiments respectively. For the lab-based experiment, AIDE recovered more than the 66.7% of the functional events from the fNIRS experimental measured data. To illustrate the strength of this method, we then applied AIDE to fNIRS data recorded by a wearable system on one participant during a complex real-world prospective memory experiment conducted outside the lab. As part of the experiment, there were four and six events (actions where participants had to interact with a target) for the two different conditions respectively (condition 1: social-interact with a person; condition 2: non-social-interact with an object). AIDE managed to recover 3/4 events and 3/6 events for conditions 1 and 2 respectively. The identified functional events were then corresponded to behavioural data from the video recordings of the movements and actions of the participant. Our results suggest that "brain-first" rather than "behaviour-first" analysis is

Applications of artificial intelligence, including expert systems

International Nuclear Information System (INIS)

Abbott, M.B.

1989-01-01

When Artificial Intelligence is applied to a complex physical system like a nuclear plant it is useful to distinguish between two rather distinct and different intelligent views of such a plant. The first view may be characterised as ''the designer's view''. This is the view of the plant as it was originally conceived and designed; it is essentially a once-and-for-all static view, corresponding to the implicit assumption of an ''ageless plant'', or at most a plant which ages in a preconceived, preset manner. The second view, which may be characterised as ''the operators view'', has to do more with a real-world, ageing plant. It is a more dynamic view, which sees the ageing process as one in which unforeseen, and possibly unforeseeable events may occur at equally unforeseen, and possibly unforeseeable times. The first view is predominantly a way of thinking about the plant, while the second is very often more a way of feeling about it. It should be emphasized that both ways are ways of intelligence. (author)

The Gifts of the 20th Century.

Science.gov (United States)

Hargrove, Kathy

1999-01-01

This article describes critical events that have shaped gifted education, including: intelligence testing, the concept of intelligence, the construct of creativity, greater understanding of brain functions, the work of John Dewey, Jerome Bruner, and Leta Hollingworth, school reform, world change, and the shift from identification to meeting…

Intelligent multimedia surveillance current trends and research

CERN Document Server

Atrey, Pradeep K; Cavallaro, Andrea

2013-01-01

Intelligent multimedia surveillance concerns the analysis of multiple sensing inputs including video and audio streams, radio-frequency identification (RFID), and depth data. These data are processed for the automated detection and tracking of people, vehicles, and other objects. The goal is to locate moving targets, to understand their behavior, and to detect suspicious or abnormal activities for crime prevention. Despite its benefits, there is societal apprehension regarding the use of such technology, so an important challenge in this research area is to balance public safety and privacy.

The Change in The Activity of The American Intelligence Services in The Security Context of the Last 24 Years

Directory of Open Access Journals (Sweden)

Georgescu - Stefan

2014-11-01

Full Text Available The security events dynamics poses an overwhelming challenge for the decision makers’political agenda, priorities. The wide range of risks and rhythm of significant security events determine a difficult enterprise for security theories. A scientific analysis of the security evolutions entails a profound historical introspection and an appropriate understanding of the security events with significant impact over the global evolutions. Probably in the next period of time, hundreds of papers will be written regarding the period since 9/11. The aim of this paper is to provide a perspective over the security context, and the intelligence services activity of the last 15 years, period of time dramatically divided by the unprecedented shock and suffering in the history of the from 9/11. The reorganization of the Western Intelligence Community was ordered as a result of the September 11th attacks and with future counterterrorism efforts in mind. Specifically, the 9/11 terrorists exploited the wall between the U.S.’s foreign and domestic intelligence collection efforts, and yet the IRTPA and EO 12333 avoid the issue of how to best integrate foreign and domestic intelligence while minimizing the threat to civil liberties. This manner in which the Western Countries separates its foreign and domestic intelligence collection is particularly exploitable by terrorists and non-state actors–those currently posing one of the most serious threats to international security. To ensure both the best intelligence integration possible as well as the defense of civil liberties, clear and sensible rules should be formed which dictate how intelligence from these two spheres is collected and in what way and at what level it is integrated and disseminated.

Social intelligence, human intelligence and niche construction.

Science.gov (United States)

Sterelny, Kim

2007-04-29

This paper is about the evolution of hominin intelligence. I agree with defenders of the social intelligence hypothesis in thinking that externalist models of hominin intelligence are not plausible: such models cannot explain the unique cognition and cooperation explosion in our lineage, for changes in the external environment (e.g. increasing environmental unpredictability) affect many lineages. Both the social intelligence hypothesis and the social intelligence-ecological complexity hybrid I outline here are niche construction models. Hominin evolution is hominin response to selective environments that earlier hominins have made. In contrast to social intelligence models, I argue that hominins have both created and responded to a unique foraging mode; a mode that is both social in itself and which has further effects on hominin social environments. In contrast to some social intelligence models, on this view, hominin encounters with their ecological environments continue to have profound selective effects. However, though the ecological environment selects, it does not select on its own. Accidents and their consequences, differential success and failure, result from the combination of the ecological environment an agent faces and the social features that enhance some opportunities and suppress others and that exacerbate some dangers and lessen others. Individuals do not face the ecological filters on their environment alone, but with others, and with the technology, information and misinformation that their social world provides.

Trends in ambient intelligent systems the role of computational intelligence

CERN Document Server

Khan, Mohammad; Abraham, Ajith

2016-01-01

This book demonstrates the success of Ambient Intelligence in providing possible solutions for the daily needs of humans. The book addresses implications of ambient intelligence in areas of domestic living, elderly care, robotics, communication, philosophy and others. The objective of this edited volume is to show that Ambient Intelligence is a boon to humanity with conceptual, philosophical, methodical and applicative understanding. The book also aims to schematically demonstrate developments in the direction of augmented sensors, embedded systems and behavioral intelligence towards Ambient Intelligent Networks or Smart Living Technology. It contains chapters in the field of Ambient Intelligent Networks, which received highly positive feedback during the review process. The book contains research work, with in-depth state of the art from augmented sensors, embedded technology and artificial intelligence along with cutting-edge research and development of technologies and applications of Ambient Intelligent N...

Brain entropy and human intelligence: A resting-state fMRI study

Science.gov (United States)

Calderone, Daniel; Morales, Leah J.

2018-01-01

Human intelligence comprises comprehension of and reasoning about an infinitely variable external environment. A brain capable of large variability in neural configurations, or states, will more easily understand and predict variable external events. Entropy measures the variety of configurations possible within a system, and recently the concept of brain entropy has been defined as the number of neural states a given brain can access. This study investigates the relationship between human intelligence and brain entropy, to determine whether neural variability as reflected in neuroimaging signals carries information about intellectual ability. We hypothesize that intelligence will be positively associated with entropy in a sample of 892 healthy adults, using resting-state fMRI. Intelligence is measured with the Shipley Vocabulary and WASI Matrix Reasoning tests. Brain entropy was positively associated with intelligence. This relation was most strongly observed in the prefrontal cortex, inferior temporal lobes, and cerebellum. This relationship between high brain entropy and high intelligence indicates an essential role for entropy in brain functioning. It demonstrates that access to variable neural states predicts complex behavioral performance, and specifically shows that entropy derived from neuroimaging signals at rest carries information about intellectual capacity. Future work in this area may elucidate the links between brain entropy in both resting and active states and various forms of intelligence. This insight has the potential to provide predictive information about adaptive behavior and to delineate the subdivisions and nature of intelligence based on entropic patterns. PMID:29432427

Brain entropy and human intelligence: A resting-state fMRI study.

Science.gov (United States)

Saxe, Glenn N; Calderone, Daniel; Morales, Leah J

2018-01-01

Human intelligence comprises comprehension of and reasoning about an infinitely variable external environment. A brain capable of large variability in neural configurations, or states, will more easily understand and predict variable external events. Entropy measures the variety of configurations possible within a system, and recently the concept of brain entropy has been defined as the number of neural states a given brain can access. This study investigates the relationship between human intelligence and brain entropy, to determine whether neural variability as reflected in neuroimaging signals carries information about intellectual ability. We hypothesize that intelligence will be positively associated with entropy in a sample of 892 healthy adults, using resting-state fMRI. Intelligence is measured with the Shipley Vocabulary and WASI Matrix Reasoning tests. Brain entropy was positively associated with intelligence. This relation was most strongly observed in the prefrontal cortex, inferior temporal lobes, and cerebellum. This relationship between high brain entropy and high intelligence indicates an essential role for entropy in brain functioning. It demonstrates that access to variable neural states predicts complex behavioral performance, and specifically shows that entropy derived from neuroimaging signals at rest carries information about intellectual capacity. Future work in this area may elucidate the links between brain entropy in both resting and active states and various forms of intelligence. This insight has the potential to provide predictive information about adaptive behavior and to delineate the subdivisions and nature of intelligence based on entropic patterns.

Video Analytics for Business Intelligence

CERN Document Server

Porikli, Fatih; Xiang, Tao; Gong, Shaogang

2012-01-01

Closed Circuit TeleVision (CCTV) cameras have been increasingly deployed pervasively in public spaces including retail centres and shopping malls. Intelligent video analytics aims to automatically analyze content of massive amount of public space video data and has been one of the most active areas of computer vision research in the last two decades. Current focus of video analytics research has been largely on detecting alarm events and abnormal behaviours for public safety and security applications. However, increasingly CCTV installations have also been exploited for gathering and analyzing business intelligence information, in order to enhance marketing and operational efficiency. For example, in retail environments, surveillance cameras can be utilised to collect statistical information about shopping behaviour and preference for marketing (e.g., how many people entered a shop; how many females/males or which age groups of people showed interests to a particular product; how long did they stay in the sho...

A framework for intelligent data acquisition and real-time database searching for shotgun proteomics.

Science.gov (United States)

Graumann, Johannes; Scheltema, Richard A; Zhang, Yong; Cox, Jürgen; Mann, Matthias

2012-03-01

In the analysis of complex peptide mixtures by MS-based proteomics, many more peptides elute at any given time than can be identified and quantified by the mass spectrometer. This makes it desirable to optimally allocate peptide sequencing and narrow mass range quantification events. In computer science, intelligent agents are frequently used to make autonomous decisions in complex environments. Here we develop and describe a framework for intelligent data acquisition and real-time database searching and showcase selected examples. The intelligent agent is implemented in the MaxQuant computational proteomics environment, termed MaxQuant Real-Time. It analyzes data as it is acquired on the mass spectrometer, constructs isotope patterns and SILAC pair information as well as controls MS and tandem MS events based on real-time and prior MS data or external knowledge. Re-implementing a top10 method in the intelligent agent yields similar performance to the data dependent methods running on the mass spectrometer itself. We demonstrate the capabilities of MaxQuant Real-Time by creating a real-time search engine capable of identifying peptides "on-the-fly" within 30 ms, well within the time constraints of a shotgun fragmentation "topN" method. The agent can focus sequencing events onto peptides of specific interest, such as those originating from a specific gene ontology (GO) term, or peptides that are likely modified versions of already identified peptides. Finally, we demonstrate enhanced quantification of SILAC pairs whose ratios were poorly defined in survey spectra. MaxQuant Real-Time is flexible and can be applied to a large number of scenarios that would benefit from intelligent, directed data acquisition. Our framework should be especially useful for new instrument types, such as the quadrupole-Orbitrap, that are currently becoming available.

Creativity in gifted identification: increasing accuracy and diversity.

Science.gov (United States)

Luria, Sarah R; O'Brien, Rebecca L; Kaufman, James C

2016-08-01

Many federal definitions and popular theories of giftedness specify creativity as a core component. Nevertheless, states rely primarily on measures of intelligence for giftedness identification. As minority and culturally diverse students continue to be underrepresented in gifted programs, it is reasonable to ask if increasing the prominence of creativity in gifted identification may help increase balance and equity. In this paper, we explore both layperson and psychometric conceptions of bias and suggest that adding creativity measures to the identification process alleviates both perceptions and the presence of bias. We recognize, however, the logistic and measurement-related challenges to including creativity assessments. © 2016 New York Academy of Sciences.

An application of artificial intelligence theory to reconfigurable flight control

Science.gov (United States)

Handelman, David A.

1987-01-01

Artificial intelligence techniques were used along with statistical hpyothesis testing and modern control theory, to help the pilot cope with the issues of information, knowledge, and capability in the event of a failure. An intelligent flight control system is being developed which utilizes knowledge of cause and effect relationships between all aircraft components. It will screen the information available to the pilots, supplement his knowledge, and most importantly, utilize the remaining flight capability of the aircraft following a failure. The list of failure types the control system will accommodate includes sensor failures, actuator failures, and structural failures.

Advanced intelligent systems

CERN Document Server

Ryoo, Young; Jang, Moon-soo; Bae, Young-Chul

2014-01-01

Intelligent systems have been initiated with the attempt to imitate the human brain. People wish to let machines perform intelligent works. Many techniques of intelligent systems are based on artificial intelligence. According to changing and novel requirements, the advanced intelligent systems cover a wide spectrum: big data processing, intelligent control, advanced robotics, artificial intelligence and machine learning. This book focuses on coordinating intelligent systems with highly integrated and foundationally functional components. The book consists of 19 contributions that features social network-based recommender systems, application of fuzzy enforcement, energy visualization, ultrasonic muscular thickness measurement, regional analysis and predictive modeling, analysis of 3D polygon data, blood pressure estimation system, fuzzy human model, fuzzy ultrasonic imaging method, ultrasonic mobile smart technology, pseudo-normal image synthesis, subspace classifier, mobile object tracking, standing-up moti...

The Cyber Intelligence Challenge of Asyngnotic Networks

Directory of Open Access Journals (Sweden)

Edward M. Roche

2015-09-01

Full Text Available The intelligence community is facing a new type of organization, one enabled by the world’s information and communications infrastructure. These asyngnotic networks operate without leadership and are self-organizing in nature. They pose a threat to national security because they are difficult to detect in time for intelligence to provide adequate warning. Social network analysis and link analysis are important tools but can be supplemented by application of neuroscience principles to understand the forces that drive asyngnotic self-organization and triggering of terrorist events. Applying Living Systems Theory (LST to a terrorist attack provides a useful framework to identify hidden asyngnotic networks. There is some antecedent work in propaganda analysis that may help uncover hidden asyngnotic networks, but computerized SIGINT methods face a number of challenges.

Adaptation of the Wechsler Intelligence Scale for Children-IV (WISC-IV) for Vietnam.

Science.gov (United States)

Dang, Hoang-Minh; Weiss, Bahr; Pollack, Amie; Nguyen, Minh Cao

2012-12-01

Intelligence testing is used for many purposes including identification of children for proper educational placement (e.g., children with learning disabilities, or intellectually gifted students), and to guide education by identifying cognitive strengths and weaknesses so that teachers can adapt their instructional style to students' specific learning styles. Most of the research involving intelligence tests has been conducted in highly developed Western countries, yet the need for intelligence testing is as or even more important in developing countries. The present study, conducted through the Vietnam National University Clinical Psychology CRISP Center , focused on the cultural adaptation of the WISC-IV intelligence test for Vietnam. We report on (a) the adaptation process including the translation, cultural analysis and modifications involved in adaptation, (b) present results of two pilot studies, and (c) describe collection of the standardization sample and results of analyses with the standardization sample, with the goal of sharing our experience with other researchers who may be involved in or interested in adapting or developing IQ tests for non-Western, non-English speaking cultures.

Competitive Intelligence.

Science.gov (United States)

Bergeron, Pierrette; Hiller, Christine A.

2002-01-01

Reviews the evolution of competitive intelligence since 1994, including terminology and definitions and analytical techniques. Addresses the issue of ethics; explores how information technology supports the competitive intelligence process; and discusses education and training opportunities for competitive intelligence, including core competencies…

The CMS Event Builder

CERN Document Server

Brigljevic, V; Cano, E; Cittolin, Sergio; Csilling, Akos; Gigi, D; Glege, F; Gómez-Reino, Robert; Gulmini, M; Gutleber, J; Jacobs, C; Kozlovszky, Miklos; Larsen, H; Magrans de Abril, Ildefons; Meijers, F; Meschi, E; Murray, S; Oh, A; Orsini, L; Pollet, L; Rácz, A; Samyn, D; Scharff-Hansen, P; Schwick, C; Sphicas, Paris; ODell, V; Suzuki, I; Berti, L; Maron, G; Toniolo, N; Zangrando, L; Ninane, A; Erhan, S; Bhattacharya, S; Branson, J G

2003-01-01

The data acquisition system of the CMS experiment at the Large Hadron Collider will employ an event builder which will combine data from about 500 data sources into full events at an aggregate throughput of 100 GByte/s. Several architectures and switch technologies have been evaluated for the DAQ Technical Design Report by measurements with test benches and by simulation. This paper describes studies of an EVB test-bench based on 64 PCs acting as data sources and data consumers and employing both Gigabit Ethernet and Myrinet technologies as the interconnect. In the case of Ethernet, protocols based on Layer-2 frames and on TCP/IP are evaluated. Results from ongoing studies, including measurements on throughput and scaling are presented. The architecture of the baseline CMS event builder will be outlined. The event builder is organised into two stages with intelligent buffers in between. The first stage contains 64 switches performing a first level of data concentration by building super-fragments from fragmen...

Evaluation of the utility of a glycemic pattern identification system.

Science.gov (United States)

Otto, Erik A; Tannan, Vinay

2014-07-01

With the increasing prevalence of systems allowing automated, real-time transmission of blood glucose data there is a need for pattern recognition techniques that can inform of deleterious patterns in glycemic control when people test. We evaluated the utility of pattern identification with a novel pattern identification system named Vigilant™ and compared it to standard pattern identification methods in diabetes. To characterize the importance of an identified pattern we evaluated the relative risk of future hypoglycemic and hyperglycemic events in diurnal periods following identification of a pattern in a data set of 536 patients with diabetes. We evaluated events 2 days, 7 days, 30 days, and 61-90 days from pattern identification, across diabetes types and cohorts of glycemic control, and also compared the system to 6 pattern identification methods consisting of deleterious event counts and percentages over 5-, 14-, and 30-day windows. Episodes of hypoglycemia, hyperglycemia, severe hypoglycemia, and severe hyperglycemia were 120%, 46%, 123%, and 76% more likely after pattern identification, respectively, compared to periods when no pattern was identified. The system was also significantly more predictive of deleterious events than other pattern identification methods evaluated, and was persistently predictive up to 3 months after pattern identification. The system identified patterns that are significantly predictive of deleterious glycemic events, and more so relative to many pattern identification methods used in diabetes management today. Further study will inform how improved pattern identification can lead to improved glycemic control. © 2014 Diabetes Technology Society.

Emotional intelligence, anxiety, and emotional eating: A deeper insight into a recently reported association?

Science.gov (United States)

Zysberg, Leehu

2018-04-01

Recent studies reported a negative association between emotional intelligence (EI: defined here as individual predispositions associated with effective identification and regulation of emotions) and emotional eating. Although theory provides some insights into how the concept represents mechanisms that may serve as protective factors, empirical evidence of the mechanism behind the association has yet to be presented. This study tested a proposed model in which anxiety levels mediate the association between emotional intelligence and emotional-eating patterns in a normative sample of women in Israel. A cross-sectional/correlational design was used to gather data from 208 generally healthy female participants who completed measures of trait emotional intelligence, anxiety, and tendency toward emotional eating, as well as demographics. Anxiety levels mediated the negative association between emotional intelligence and emotional eating. Background variables had only marginal involvement in this model. The results shed light on the mechanisms underlying the association between emotional intelligence and emotional eating. Should future studies corroborate the findings, they may serve as a basis for future screening protocols, prevention and interventions with individuals and groups at risk of EE and eating disorders. Copyright © 2018 Elsevier Ltd. All rights reserved.

An RFID-Based Intelligent Vehicle Speed Controller Using Active Traffic Signals

Directory of Open Access Journals (Sweden)

Joshué Pérez

2010-06-01

Full Text Available These days, mass-produced vehicles benefit from research on Intelligent Transportation System (ITS. One prime example of ITS is vehicle Cruise Control (CC, which allows it to maintain a pre-defined reference speed, to economize on fuel or energy consumption, to avoid speeding fines, or to focus all of the driver’s attention on the steering of the vehicle. However, achieving efficient Cruise Control is not easy in roads or urban streets where sudden changes of the speed limit can happen, due to the presence of unexpected obstacles or maintenance work, causing, in inattentive drivers, traffic accidents. In this communication we present a new Infrastructure to Vehicles (I2V communication and control system for intelligent speed control, which is based upon Radio Frequency Identification (RFID technology for identification of traffic signals on the road, and high accuracy vehicle speed measurement with a Hall effect-based sensor. A fuzzy logic controller, based on sensor fusion of the information provided by the I2V infrastructure, allows the efficient adaptation of the speed of the vehicle to the circumstances of the road. The performance of the system is checked empirically, with promising results.

An RFID-Based Intelligent Vehicle Speed Controller Using Active Traffic Signals

Science.gov (United States)

Pérez, Joshué; Seco, Fernando; Milanés, Vicente; Jiménez, Antonio; Díaz, Julio C.; de Pedro, Teresa

2010-01-01

These days, mass-produced vehicles benefit from research on Intelligent Transportation System (ITS). One prime example of ITS is vehicle Cruise Control (CC), which allows it to maintain a pre-defined reference speed, to economize on fuel or energy consumption, to avoid speeding fines, or to focus all of the driver’s attention on the steering of the vehicle. However, achieving efficient Cruise Control is not easy in roads or urban streets where sudden changes of the speed limit can happen, due to the presence of unexpected obstacles or maintenance work, causing, in inattentive drivers, traffic accidents. In this communication we present a new Infrastructure to Vehicles (I2V) communication and control system for intelligent speed control, which is based upon Radio Frequency Identification (RFID) technology for identification of traffic signals on the road, and high accuracy vehicle speed measurement with a Hall effect-based sensor. A fuzzy logic controller, based on sensor fusion of the information provided by the I2V infrastructure, allows the efficient adaptation of the speed of the vehicle to the circumstances of the road. The performance of the system is checked empirically, with promising results. PMID:22219692

An RFID-based intelligent vehicle speed controller using active traffic signals.

Science.gov (United States)

Pérez, Joshué; Seco, Fernando; Milanés, Vicente; Jiménez, Antonio; Díaz, Julio C; de Pedro, Teresa

2010-01-01

These days, mass-produced vehicles benefit from research on Intelligent Transportation System (ITS). One prime example of ITS is vehicle Cruise Control (CC), which allows it to maintain a pre-defined reference speed, to economize on fuel or energy consumption, to avoid speeding fines, or to focus all of the driver's attention on the steering of the vehicle. However, achieving efficient Cruise Control is not easy in roads or urban streets where sudden changes of the speed limit can happen, due to the presence of unexpected obstacles or maintenance work, causing, in inattentive drivers, traffic accidents. In this communication we present a new Infrastructure to Vehicles (I2V) communication and control system for intelligent speed control, which is based upon Radio Frequency Identification (RFID) technology for identification of traffic signals on the road, and high accuracy vehicle speed measurement with a Hall effect-based sensor. A fuzzy logic controller, based on sensor fusion of the information provided by the I2V infrastructure, allows the efficient adaptation of the speed of the vehicle to the circumstances of the road. The performance of the system is checked empirically, with promising results.

Identifying Students' Characteristic Learning Behaviors in an Intelligent Tutoring System Fostering Self-Regulated Learning

Science.gov (United States)

Bouchet, Francois; Azevedo, Roger; Kinnebrew, John S.; Biswas, Gautam

2012-01-01

Identification of student learning behaviors, especially those that characterize or distinguish students, can yield important insights for the design of adaptation and feedback mechanisms in Intelligent Tutoring Systems (ITS). In this paper, we analyze trace data to identify distinguishing patterns of behavior in a study of 51 college students…

Entropy based file type identification and partitioning

Science.gov (United States)

2017-06-01

energy spectrum,” Proceedings of the Twenty-Ninth International Florida Artificial Intelligence Research Society Conference, pp. 288–293, 2016...ABBREVIATIONS AES Advanced Encryption Standard ANN Artificial Neural Network ASCII American Standard Code for Information Interchange CWT...the identification of file types and file partitioning. This approach has applications in cybersecurity as it allows for a quick determination of

Design of a sentence identification test with pictures (TIS-F based on the pediatric speech intelligibility test

Directory of Open Access Journals (Sweden)

Fernanda Freitas Vellozo

Full Text Available ABSTRACT Purposes: to design a sentence identification test with pictures for adults (Teste de Identificação de Sentenças com Figuras (TIS-F as an alternative for evaluation of auditory figure-background ability for verbal sounds, based on the Pediatric Speech Intelligibility Test and also for assessment of unskillful individuals who cannot accomplish other tests with higher levels of difficulty and greater demands. Methods: the Adobe Illustrator software was used and the image vectorization technique applied for figures creation. The sentences and the competitive message were audio-recorded in a sound treated room by a female announcer, using the software - REAPER - FM Digital Audio Workstation. Results: the TIS-F consisted of a 32 x 45 cm card, containing 10 figures, each one measuring 12 x 12 cm; one compact disc containing a track with the test calibration tone and seven test tracks, each one containing ten sentences and a competitive message and a specific protocol. Conclusion: the TIS-F is composed of a compact disc with dual-channel recording, with seven tracks containing ten sentences and the competitive story, one card containing ten pictures and a labeling protocol for all presentations and S/N in use, as well as the established normality values.

Recent advances in medical device triage technologies for chemical, biological, radiological, and nuclear events.

Science.gov (United States)

Lansdowne, Krystal; Scully, Christopher G; Galeotti, Loriano; Schwartz, Suzanne; Marcozzi, David; Strauss, David G

2015-06-01

In 2010, the US Food and Drug Administration (Silver Spring, Maryland USA) created the Medical Countermeasures Initiative with the mission of development and promoting medical countermeasures that would be needed to protect the nation from identified, high-priority chemical, biological, radiological, or nuclear (CBRN) threats and emerging infectious diseases. The aim of this review was to promote regulatory science research of medical devices and to analyze how the devices can be employed in different CBRN scenarios. Triage in CBRN scenarios presents unique challenges for first responders because the effects of CBRN agents and the clinical presentations of casualties at each triage stage can vary. The uniqueness of a CBRN event can render standard patient monitoring medical device and conventional triage algorithms ineffective. Despite the challenges, there have been recent advances in CBRN triage technology that include: novel technologies; mobile medical applications ("medical apps") for CBRN disasters; electronic triage tags, such as eTriage; diagnostic field devices, such as the Joint Biological Agent Identification System; and decision support systems, such as the Chemical Hazards Emergency Medical Management Intelligent Syndromes Tool (CHEMM-IST). Further research and medical device validation can help to advance prehospital triage technology for CBRN events.

Modelling traffic flows with intelligent cars and intelligent roads

NARCIS (Netherlands)

van Arem, Bart; Tampere, Chris M.J.; Malone, Kerry

2003-01-01

This paper addresses the modeling of traffic flows with intelligent cars and intelligent roads. It will describe the modeling approach MIXIC and review the results for different ADA systems: Adaptive Cruise Control, a special lane for Intelligent Vehicles, cooperative following and external speed

Moral intelligence and its position in nursing profession

Directory of Open Access Journals (Sweden)

Pooneh Yousefi

2015-10-01

Full Text Available Introduction: Moral intelligence is one of the aspects of intelligence which can provide a framework for proper performance of the humans, which is known as a forecaster factor of behavior. MI is a vital intelligence for humans owing to guidance of other shapes of intelligence toward valuable tasks . It is  a combination of knowledge, interest and resolve, also includes the method of thinking, feeding and acting. The role and importance of MI is outstanding because of making balance and improvement in individual's interactions and social terms, especially in occupations related to medical and nursing field which directly deals with people's life. The goal of this study is the definition and identification of MI and its application in medical science, especially nursing. Methods: This research is a retrospective article in which other researchers' study has been investigated and analyzed. Therefore, three main keywords; intelligence, morality, MI, has been searched in different nursing field databases such as SID, CVID, PUBMED, CINAHL, SCIENCE, MAGIRAN DIRECT, GOOGLE SCHOLAR and SCOPUS. Hence, based on these criteria, published articles from 2000  up to the present has been found and abstracted or editors interpretation ones eliminated. Only full text articles have been used. Definitions and applications of MI in nursing, presented in articles has been organized and revised in this article. Results: The results showed that MI education is a revolution and essential requirement in nursing, since changing to a descent nurse not only depends on theoretical knowledge and clinical skills but also needs applying moral knowledge and responsibility. Following moral criterion in nurse's performance is more important than other care issues as moral behavior accompany nurses' responsibility can be an effective factor in patients' remission and recovery. Conclusion: Achievement of MI skills leads to nursing profession advancement by basic changes in nurse

Intelligence.

Science.gov (United States)

Sternberg, Robert J

2012-03-01

Intelligence is the ability to learn from experience and to adapt to, shape, and select environments. Intelligence as measured by (raw scores on) conventional standardized tests varies across the lifespan, and also across generations. Intelligence can be understood in part in terms of the biology of the brain-especially with regard to the functioning in the prefrontal cortex-and also correlates with brain size, at least within humans. Studies of the effects of genes and environment suggest that the heritability coefficient (ratio of genetic to phenotypic variation) is between .4 and .8, although heritability varies as a function of socioeconomic status and other factors. Racial differences in measured intelligence have been observed, but race is a socially constructed rather than biological variable, so such differences are difficult to interpret.

Intelligence

Science.gov (United States)

Sternberg, Robert J.

2012-01-01

Intelligence is the ability to learn from experience and to adapt to, shape, and select environments. Intelligence as measured by (raw scores on) conventional standardized tests varies across the lifespan, and also across generations. Intelligence can be understood in part in terms of the biology of the brain—especially with regard to the functioning in the prefrontal cortex—and also correlates with brain size, at least within humans. Studies of the effects of genes and environment suggest that the heritability coefficient (ratio of genetic to phenotypic variation) is between .4 and .8, although heritability varies as a function of socioeconomic status and other factors. Racial differences in measured intelligence have been observed, but race is a socially constructed rather than biological variable, so such differences are difficult to interpret. PMID:22577301

Combined Intelligent Control (CIC an Intelligent Decision Making Algorithm

Directory of Open Access Journals (Sweden)

Moteaal Asadi Shirzi

2007-03-01

Full Text Available The focus of this research is to introduce the concept of combined intelligent control (CIC as an effective architecture for decision-making and control of intelligent agents and multi-robot sets. Basically, the CIC is a combination of various architectures and methods from fields such as artificial intelligence, Distributed Artificial Intelligence (DAI, control and biological computing. Although any intelligent architecture may be very effective for some specific applications, it could be less for others. Therefore, CIC combines and arranges them in a way that the strengths of any approach cover the weaknesses of others. In this paper first, we introduce some intelligent architectures from a new aspect. Afterward, we offer the CIC by combining them. CIC has been executed in a multi-agent set. In this set, robots must cooperate to perform some various tasks in a complex and nondeterministic environment with a low sensory feedback and relationship. In order to investigate, improve, and correct the combined intelligent control method, simulation software has been designed which will be presented and considered. To show the ability of the CIC algorithm as a distributed architecture, a central algorithm is designed and compared with the CIC.

Ontology-Based High-Level Context Inference for Human Behavior Identification

Science.gov (United States)

Villalonga, Claudia; Razzaq, Muhammad Asif; Khan, Wajahat Ali; Pomares, Hector; Rojas, Ignacio; Lee, Sungyoung; Banos, Oresti

2016-01-01

Recent years have witnessed a huge progress in the automatic identification of individual primitives of human behavior, such as activities or locations. However, the complex nature of human behavior demands more abstract contextual information for its analysis. This work presents an ontology-based method that combines low-level primitives of behavior, namely activity, locations and emotions, unprecedented to date, to intelligently derive more meaningful high-level context information. The paper contributes with a new open ontology describing both low-level and high-level context information, as well as their relationships. Furthermore, a framework building on the developed ontology and reasoning models is presented and evaluated. The proposed method proves to be robust while identifying high-level contexts even in the event of erroneously-detected low-level contexts. Despite reasonable inference times being obtained for a relevant set of users and instances, additional work is required to scale to long-term scenarios with a large number of users. PMID:27690050

Ontology-Based High-Level Context Inference for Human Behavior Identification

Directory of Open Access Journals (Sweden)

Claudia Villalonga

2016-09-01

Full Text Available Recent years have witnessed a huge progress in the automatic identification of individual primitives of human behavior, such as activities or locations. However, the complex nature of human behavior demands more abstract contextual information for its analysis. This work presents an ontology-based method that combines low-level primitives of behavior, namely activity, locations and emotions, unprecedented to date, to intelligently derive more meaningful high-level context information. The paper contributes with a new open ontology describing both low-level and high-level context information, as well as their relationships. Furthermore, a framework building on the developed ontology and reasoning models is presented and evaluated. The proposed method proves to be robust while identifying high-level contexts even in the event of erroneously-detected low-level contexts. Despite reasonable inference times being obtained for a relevant set of users and instances, additional work is required to scale to long-term scenarios with a large number of users.

iAssist: a software framework for intelligent patient monitoring.

Science.gov (United States)

Brouse, Christopher; Dumont, Guy; Yang, Ping; Lim, Joanne; Ansermino, J Mark

2007-01-01

A software framework (iAssist) has been developed for intelligent patient monitoring, and forms the foundation of a clinical monitoring expert system. The framework is extensible, flexible, and interoperable. It supports plugins to perform data acquisition, signal processing, graphical display, data storage, and output to external devices. iAssist currently incorporates two plugins to detect change point events in physiological trends. In 38 surgical cases, iAssist detected 868 events, of which clinicians rated more than 50% as clinically significant and less than 7% as artifacts. Clinicians found iAssist intuitive and easy to use.

Advanced Artificial Intelligence Technology Testbed

Science.gov (United States)

Anken, Craig S.

1993-01-01

The Advanced Artificial Intelligence Technology Testbed (AAITT) is a laboratory testbed for the design, analysis, integration, evaluation, and exercising of large-scale, complex, software systems, composed of both knowledge-based and conventional components. The AAITT assists its users in the following ways: configuring various problem-solving application suites; observing and measuring the behavior of these applications and the interactions between their constituent modules; gathering and analyzing statistics about the occurrence of key events; and flexibly and quickly altering the interaction of modules within the applications for further study.

Intelligence and negotiating

International Nuclear Information System (INIS)

George, D.G.

1990-01-01

This paper discusses the role of US intelligence during arms control negotiations between 1982 and 1987. It also covers : the orchestration of intelligence projects; an evaluation of the performance of intelligence activities; the effect intelligence work had on actual arms negotiations; and suggestions for improvements in the future

Developing emotional intelligence ability in oncology nurses: a clinical rounds approach.

Science.gov (United States)

Codier, Estelle; Freitas, Beth; Muneno, Lynn

2013-01-01

To explore the feasibility and impact of an emotional intelligence ability development program on staff and patient care. A mixed method, pre/post-test design. A tertiary care hospital in urban Honolulu, HI. Rounds took place on a 24-bed inpatient oncology unit. 33 RNs in an oncology unit. After collection of baseline data, the emotional intelligence rounds were conducted in an inpatient oncology nursing unit on all shifts during a 10-month period. Demographic information, emotional intelligence scores, data from rounds, chart reviews of emotional care documentation, and unit-wide satisfaction and safety data. The ability to identify emotions in self and others was demonstrated less frequently than expected in this population. The low test response rate prevented comparison of scores pre- and postintervention. The staff's 94% participation in rounds, the positive (100%) evaluation of rounds, and poststudy improvements in emotional care documentation and emotional care planning suggest a positive effect from the intervention. Additional research is recommended over a longer period of time to evaluate the impact emotional intelligence specifically has on the staff's identification of emotions. Because the intervention involved minimal time and resources, feasibility for continuation of the intervention poststudy was rated "high" by the research team. Research in other disciplines suggests that improvement in emotional intelligence ability in clinical staff nurses may improve retention, performance, and teamwork in nursing, which would be of particular significance in high-risk clinical practice environments. Few research studies have explored development of emotional intelligence abilities in clinical staff nurses. Evidence from this study suggests that interventions in the clinical environment may be used to develop emotional intelligence ability. Impact from such development may be used in the future to not only improve the quality of nursing care, but also

Intelligence and childlessness.

Science.gov (United States)

Kanazawa, Satoshi

2014-11-01

Demographers debate why people have children in advanced industrial societies where children are net economic costs. From an evolutionary perspective, however, the important question is why some individuals choose not to have children. Recent theoretical developments in evolutionary psychology suggest that more intelligent individuals may be more likely to prefer to remain childless than less intelligent individuals. Analyses of the National Child Development Study show that more intelligent men and women express preference to remain childless early in their reproductive careers, but only more intelligent women (not more intelligent men) are more likely to remain childless by the end of their reproductive careers. Controlling for education and earnings does not at all attenuate the association between childhood general intelligence and lifetime childlessness among women. One-standard-deviation increase in childhood general intelligence (15 IQ points) decreases women's odds of parenthood by 21-25%. Because women have a greater impact on the average intelligence of future generations, the dysgenic fertility among women is predicted to lead to a decline in the average intelligence of the population in advanced industrial nations. Copyright © 2014 Elsevier Inc. All rights reserved.

Perceived intelligence is associated with measured intelligence in men but not women.

Science.gov (United States)

Kleisner, Karel; Chvátalová, Veronika; Flegr, Jaroslav

2014-01-01

The ability to accurately assess the intelligence of other persons finds its place in everyday social interaction and should have important evolutionary consequences. We used static facial photographs of 40 men and 40 women to test the relationship between measured IQ, perceived intelligence, and facial shape. Both men and women were able to accurately evaluate the intelligence of men by viewing facial photographs. In addition to general intelligence, figural and fluid intelligence showed a significant relationship with perceived intelligence, but again, only in men. No relationship between perceived intelligence and IQ was found for women. We used geometric morphometrics to determine which facial traits are associated with the perception of intelligence, as well as with intelligence as measured by IQ testing. Faces that are perceived as highly intelligent are rather prolonged with a broader distance between the eyes, a larger nose, a slight upturn to the corners of the mouth, and a sharper, pointing, less rounded chin. By contrast, the perception of lower intelligence is associated with broader, more rounded faces with eyes closer to each other, a shorter nose, declining corners of the mouth, and a rounded and massive chin. By contrast, we found no correlation between morphological traits and real intelligence measured with IQ test, either in men or women. These results suggest that a perceiver can accurately gauge the real intelligence of men, but not women, by viewing their faces in photographs; however, this estimation is possibly not based on facial shape. Our study revealed no relation between intelligence and either attractiveness or face shape.

Intelligent navigation to improve obstetrical sonography.

Science.gov (United States)

Yeo, Lami; Romero, Roberto

2016-04-01

'Manual navigation' by the operator is the standard method used to obtain information from two-dimensional and volumetric sonography. Two-dimensional sonography is highly operator dependent and requires extensive training and expertise to assess fetal anatomy properly. Most of the sonographic examination time is devoted to acquisition of images, while 'retrieval' and display of diagnostic planes occurs rapidly (essentially instantaneously). In contrast, volumetric sonography has a rapid acquisition phase, but the retrieval and display of relevant diagnostic planes is often time-consuming, tedious and challenging. We propose the term 'intelligent navigation' to refer to a new method of interrogation of a volume dataset whereby identification and selection of key anatomical landmarks allow the system to: 1) generate a geometrical reconstruction of the organ of interest; and 2) automatically navigate, find, extract and display specific diagnostic planes. This is accomplished using operator-independent algorithms that are both predictable and adaptive. Virtual Intelligent Sonographer Assistance (VIS-Assistance®) is a tool that allows operator-independent sonographic navigation and exploration of the surrounding structures in previously identified diagnostic planes. The advantage of intelligent (over manual) navigation in volumetric sonography is the short time required for both acquisition and retrieval and display of diagnostic planes. Intelligent navigation technology automatically realigns the volume, and reorients and standardizes the anatomical position, so that the fetus and the diagnostic planes are consistently displayed in the same manner each time, regardless of the fetal position or the initial orientation. Automatic labeling of anatomical structures, subject orientation and each of the diagnostic planes is also possible. Intelligent navigation technology can operate on conventional computers, and is not dependent on specific ultrasound platforms or on the

DARHT Multi-intelligence Seismic and Acoustic Data Analysis

Energy Technology Data Exchange (ETDEWEB)

Stevens, Garrison Nicole [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Van Buren, Kendra Lu [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Hemez, Francois M. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2016-07-21

The purpose of this report is to document the analysis of seismic and acoustic data collected at the Dual-Axis Radiographic Hydrodynamic Test (DARHT) facility at Los Alamos National Laboratory for robust, multi-intelligence decision making. The data utilized herein is obtained from two tri-axial seismic sensors and three acoustic sensors, resulting in a total of nine data channels. The goal of this analysis is to develop a generalized, automated framework to determine internal operations at DARHT using informative features extracted from measurements collected external of the facility. Our framework involves four components: (1) feature extraction, (2) data fusion, (3) classification, and finally (4) robustness analysis. Two approaches are taken for extracting features from the data. The first of these, generic feature extraction, involves extraction of statistical features from the nine data channels. The second approach, event detection, identifies specific events relevant to traffic entering and leaving the facility as well as explosive activities at DARHT and nearby explosive testing sites. Event detection is completed using a two stage method, first utilizing signatures in the frequency domain to identify outliers and second extracting short duration events of interest among these outliers by evaluating residuals of an autoregressive exogenous time series model. Features extracted from each data set are then fused to perform analysis with a multi-intelligence paradigm, where information from multiple data sets are combined to generate more information than available through analysis of each independently. The fused feature set is used to train a statistical classifier and predict the state of operations to inform a decision maker. We demonstrate this classification using both generic statistical features and event detection and provide a comparison of the two methods. Finally, the concept of decision robustness is presented through a preliminary analysis where

Concept development and needs identification for intelligent network flow optimization (INFLO) : concept of operations.

Science.gov (United States)

2012-06-01

The purpose of this project is to develop for the Intelligent Network Flow Optimization (INFLO), which is one collection (or bundle) of high-priority transformative applications identified by the United States Department of Transportation (USDOT) Mob...

Concept development and needs identification for intelligent network flow optimization (INFLO) : test readiness assessment.

Science.gov (United States)

2012-11-01

The purpose of this project is to develop for the Intelligent Network Flow Optimization (INFLO), which is one collection (or bundle) of high-priority transformative applications identified by the United States Department of Transportation (USDOT) Mob...

Is general intelligence little more than the speed of higher-order processing?

Science.gov (United States)

Schubert, Anna-Lena; Hagemann, Dirk; Frischkorn, Gidon T

2017-10-01

Individual differences in the speed of information processing have been hypothesized to give rise to individual differences in general intelligence. Consistent with this hypothesis, reaction times (RTs) and latencies of event-related potential have been shown to be moderately associated with intelligence. These associations have been explained either in terms of individual differences in some brain-wide property such as myelination, the speed of neural oscillations, or white-matter tract integrity, or in terms of individual differences in specific processes such as the signal-to-noise ratio in evidence accumulation, executive control, or the cholinergic system. Here we show in a sample of 122 participants, who completed a battery of RT tasks at 2 laboratory sessions while an EEG was recorded, that more intelligent individuals have a higher speed of higher-order information processing that explains about 80% of the variance in general intelligence. Our results do not support the notion that individuals with higher levels of general intelligence show advantages in some brain-wide property. Instead, they suggest that more intelligent individuals benefit from a more efficient transmission of information from frontal attention and working memory processes to temporal-parietal processes of memory storage. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Artificial Intelligence.

Science.gov (United States)

Information Technology Quarterly, 1985

1985-01-01

This issue of "Information Technology Quarterly" is devoted to the theme of "Artificial Intelligence." It contains two major articles: (1) Artificial Intelligence and Law" (D. Peter O'Neill and George D. Wood); (2) "Artificial Intelligence: A Long and Winding Road" (John J. Simon, Jr.). In addition, it contains two sidebars: (1) "Calculating and…

Application of artificial intelligence to risk analysis for forested ecosystems

Science.gov (United States)

Daniel L. Schmoldt

2001-01-01

Forest ecosystems are subject to a variety of natural and anthropogenic disturbances that extract a penalty from human population values. Such value losses (undesirable effects) combined with their likelihoods of occurrence constitute risk. Assessment or prediction of risk for various events is an important aid to forest management. Artificial intelligence (AI)...

Self-Assessing of the Emotional Intelligence and Organizational Intelligence in Schools

Science.gov (United States)

Dagiene, Valentina; Juškeviciene, Anita; Carneiro, Roberto; Child, Camilla; Cullen, Joe

2015-01-01

The paper presents the results of an evaluation of the Emotional Intelligence (EI) and Organisational Intelligence (OI) competences self-assessment tools developed and applied by the IGUANA project. In the paper Emotional Intelligence and Organisational Intelligence competences are discussed, their use in action research experiments to assess and…

Perceived Intelligence Is Associated with Measured Intelligence in Men but Not Women

Science.gov (United States)

Kleisner, Karel; Chvátalová, Veronika; Flegr, Jaroslav

2014-01-01

Background The ability to accurately assess the intelligence of other persons finds its place in everyday social interaction and should have important evolutionary consequences. Methodology/Principal Findings We used static facial photographs of 40 men and 40 women to test the relationship between measured IQ, perceived intelligence, and facial shape. Both men and women were able to accurately evaluate the intelligence of men by viewing facial photographs. In addition to general intelligence, figural and fluid intelligence showed a significant relationship with perceived intelligence, but again, only in men. No relationship between perceived intelligence and IQ was found for women. We used geometric morphometrics to determine which facial traits are associated with the perception of intelligence, as well as with intelligence as measured by IQ testing. Faces that are perceived as highly intelligent are rather prolonged with a broader distance between the eyes, a larger nose, a slight upturn to the corners of the mouth, and a sharper, pointing, less rounded chin. By contrast, the perception of lower intelligence is associated with broader, more rounded faces with eyes closer to each other, a shorter nose, declining corners of the mouth, and a rounded and massive chin. By contrast, we found no correlation between morphological traits and real intelligence measured with IQ test, either in men or women. Conclusions These results suggest that a perceiver can accurately gauge the real intelligence of men, but not women, by viewing their faces in photographs; however, this estimation is possibly not based on facial shape. Our study revealed no relation between intelligence and either attractiveness or face shape. PMID:24651120

Towards intelligent video understanding applied to plasma facing component monitoring

Energy Technology Data Exchange (ETDEWEB)

Martin, V.; Bremond, F. [INRIA, Pulsa team-project, Sophia Antipolis (France); Travere, J.M. [CEA IRFM, Saint Paul-lez-Durance (France); Moncada, V.; Dunand, G. [Sophia Conseil Company, Sophia Antipolis (France)

2011-07-01

Infrared thermography has become a routine diagnostic in many magnetic fusion devices to monitor the heat loads on the plasma facing components (PFCs) for both physics studies and machine protection. The good results of the developed systems obtained so far motivate the use of imaging diagnostics for control, especially during long pulse tokamak operation (e.g. lasting several minutes). In this paper, we promote intelligent monitoring for both real-time purposes (machine protection issues) and post event analysis purposes (PWI understanding). We propose a vision-based system able to automatically detect and classify into different pre-defined categories phenomena as localized hot spots, transient thermal events (e.g. electrical arcing), and unidentified flying objects (UFOs) as dusts from infrared imaging data of PFCs. This original vision system is made intelligent by endowing it with high-level reasoning (i.e. integration of a priori knowledge of thermal event spatial and temporal properties to guide the recognition), self-adaptability to varying conditions (e.g. different plasma scenarios), and learning capabilities (e.g. statistical modelling of thermal event behaviour based on training samples). This approach has been already successfully applied to the recognition of one critical thermal event at Tore Supra. We present here latest results of its extension for the recognition of others thermal events (e.g., B{sub 4}C flakes, impact of fast particles, UFOs) and show how extracted information can be used during plasma operation at Tore Supra to improve the real time control system, and for further analysis of PFC aging. This document is composed of an abstract followed by the slides of the presentation. (authors)

Nexus between Intelligence Education and Intelligence Training: A South African Perspective

Directory of Open Access Journals (Sweden)

M. A. van den Berg

2015-10-01

Full Text Available This paper examines the nexus of intelligence education and training from a South African perspective with the focus on current practices in light of the country’s transition towards democracy. A brief overview is provided on the history and development of the South African intelligence community with specific focus on the civilian intelligence services from the period prior 1994 to date (2015. The main focus, however, is on intelligence education that is currently available from training institutions and universities in South Africa as registered with the Department of Higher Education as well as private training institutions on the one hand, and the intelligence training practices within the statutory intelligence environment on the other. To this extent, the relations between academic institutions and the intelligence structures in terms of education and training within South Africa are perused against other practices within the African continent and internationally. The approaches to the study of intelligence are also addressed within this paper. Likewise, the how, what as well as to whom – pertaining to intelligence education and training availability and accessibility to students and practitioners within South Africa, is reviewed and analysed with the focus on making recommendations for the enhancement and improvement thereof to enable a focus on preparing the next generation of professional intelligence officers.

Intelligent Membranes: Dream or Reality?

Directory of Open Access Journals (Sweden)

Annarosa Gugliuzza

2013-07-01

Full Text Available Intelligent materials are claimed to overcome current drawbacks associated with the attainment of high standards of life, health, security and defense. Membrane-based sensors represent a category of smart systems capable of providing a large number of benefits to different markets of textiles, biomedicine, environment, chemistry, agriculture, architecture, transport and energy. Intelligent membranes can be characterized by superior sensitivity, broader dynamic range and highly sophisticated mechanisms of autorecovery. These prerogatives are regarded as the result of multi-compartment arrays, where complementary functions can be accommodated and well-integrated. Based on the mechanism of “sense to act”, stimuli-responsive membranes adapt themselves to surrounding environments, producing desired effects such as smart regulation of transport, wetting, transcription, hydrodynamics, separation, and chemical or energy conversion. Hopefully, the design of new smart devices easier to manufacture and assemble can be realized through the integration of sensing membranes with wireless networks, looking at the ambitious challenge to establish long-distance communications. Thus, the transfer of signals to collecting systems could allow continuous and real-time monitoring of data, events and/or processes.

Intelligent home risk assessment systems and integration with biometric identification

Science.gov (United States)

Roper, William E.

2003-08-01

An overview is given of the Home of the 21st Century Laboratory. The laboratory is operated as a joint program with America-On-Line and George Washington University. The program is described with illustrations and discussion of the systems that are part of the laboratory. The concept of application for face recognition systems in the intelligent home of the future is presented and some initial approaches in using biometrics are shown. Issues of privacy and sharing of information within and outside the home are addressed. Issues include safety and security concerns vs. inappropriate observations of activities in and outside the home. Technology options currently available for application in the home are described and assessed.

Hybrid Swarm Intelligence Optimization Approach for Optimal Data Storage Position Identification in Wireless Sensor Networks

Science.gov (United States)

Mohanasundaram, Ranganathan; Periasamy, Pappampalayam Sanmugam

2015-01-01

The current high profile debate with regard to data storage and its growth have become strategic task in the world of networking. It mainly depends on the sensor nodes called producers, base stations, and also the consumers (users and sensor nodes) to retrieve and use the data. The main concern dealt here is to find an optimal data storage position in wireless sensor networks. The works that have been carried out earlier did not utilize swarm intelligence based optimization approaches to find the optimal data storage positions. To achieve this goal, an efficient swam intelligence approach is used to choose suitable positions for a storage node. Thus, hybrid particle swarm optimization algorithm has been used to find the suitable positions for storage nodes while the total energy cost of data transmission is minimized. Clustering-based distributed data storage is utilized to solve clustering problem using fuzzy-C-means algorithm. This research work also considers the data rates and locations of multiple producers and consumers to find optimal data storage positions. The algorithm is implemented in a network simulator and the experimental results show that the proposed clustering and swarm intelligence based ODS strategy is more effective than the earlier approaches. PMID:25734182

DETECT: a MATLAB toolbox for event detection and identification in time series, with applications to artifact detection in EEG signals.

Science.gov (United States)

Lawhern, Vernon; Hairston, W David; Robbins, Kay

2013-01-01

Recent advances in sensor and recording technology have allowed scientists to acquire very large time-series datasets. Researchers often analyze these datasets in the context of events, which are intervals of time where the properties of the signal change relative to a baseline signal. We have developed DETECT, a MATLAB toolbox for detecting event time intervals in long, multi-channel time series. Our primary goal is to produce a toolbox that is simple for researchers to use, allowing them to quickly train a model on multiple classes of events, assess the accuracy of the model, and determine how closely the results agree with their own manual identification of events without requiring extensive programming knowledge or machine learning experience. As an illustration, we discuss application of the DETECT toolbox for detecting signal artifacts found in continuous multi-channel EEG recordings and show the functionality of the tools found in the toolbox. We also discuss the application of DETECT for identifying irregular heartbeat waveforms found in electrocardiogram (ECG) data as an additional illustration.

DETECT: a MATLAB toolbox for event detection and identification in time series, with applications to artifact detection in EEG signals.

Directory of Open Access Journals (Sweden)

Vernon Lawhern

Full Text Available Recent advances in sensor and recording technology have allowed scientists to acquire very large time-series datasets. Researchers often analyze these datasets in the context of events, which are intervals of time where the properties of the signal change relative to a baseline signal. We have developed DETECT, a MATLAB toolbox for detecting event time intervals in long, multi-channel time series. Our primary goal is to produce a toolbox that is simple for researchers to use, allowing them to quickly train a model on multiple classes of events, assess the accuracy of the model, and determine how closely the results agree with their own manual identification of events without requiring extensive programming knowledge or machine learning experience. As an illustration, we discuss application of the DETECT toolbox for detecting signal artifacts found in continuous multi-channel EEG recordings and show the functionality of the tools found in the toolbox. We also discuss the application of DETECT for identifying irregular heartbeat waveforms found in electrocardiogram (ECG data as an additional illustration.

Causal Mathematical Logic as a guiding framework for the prediction of "Intelligence Signals" in brain simulations

Science.gov (United States)

Lanzalaco, Felix; Pissanetzky, Sergio

2013-12-01

A recent theory of physical information based on the fundamental principles of causality and thermodynamics has proposed that a large number of observable life and intelligence signals can be described in terms of the Causal Mathematical Logic (CML), which is proposed to encode the natural principles of intelligence across any physical domain and substrate. We attempt to expound the current definition of CML, the "Action functional" as a theory in terms of its ability to possess a superior explanatory power for the current neuroscientific data we use to measure the mammalian brains "intelligence" processes at its most general biophysical level. Brain simulation projects define their success partly in terms of the emergence of "non-explicitly programmed" complex biophysical signals such as self-oscillation and spreading cortical waves. Here we propose to extend the causal theory to predict and guide the understanding of these more complex emergent "intelligence Signals". To achieve this we review whether causal logic is consistent with, can explain and predict the function of complete perceptual processes associated with intelligence. Primarily those are defined as the range of Event Related Potentials (ERP) which include their primary subcomponents; Event Related Desynchronization (ERD) and Event Related Synchronization (ERS). This approach is aiming for a universal and predictive logic for neurosimulation and AGi. The result of this investigation has produced a general "Information Engine" model from translation of the ERD and ERS. The CML algorithm run in terms of action cost predicts ERP signal contents and is consistent with the fundamental laws of thermodynamics. A working substrate independent natural information logic would be a major asset. An information theory consistent with fundamental physics can be an AGi. It can also operate within genetic information space and provides a roadmap to understand the live biophysical operation of the phenotype

Identification of Tropical-Extratropical Interactions and Extreme Precipitation Events in the Middle East based on Potential Vorticity and Moisture Transport

KAUST Repository

de Vries, A. J.

2017-12-26

Extreme precipitation events in the otherwise arid Middle East can cause flooding with dramatic socioeconomic impacts. Most of these events are associated with tropical-extratropical interactions, whereby a stratospheric potential vorticity (PV) intrusion reaches deep into the subtropics and forces an incursion of high poleward vertically integrated water vapor transport (IVT) into the Middle East. This study presents an object-based identification method for extreme precipitation events based on the combination of these two larger-scale meteorological features. The general motivation for this approach is that precipitation is often poorly simulated in relatively coarse weather and climate models, whereas the synoptic-scale circulation is much better represented. The algorithm is applied to ERA-Interim reanalysis data (1979-2015) and detects 90% (83%) of the 99th (97.5th) percentile of extreme precipitation days in the region of interest. Our results show that stratospheric PV intrusions and IVT structures are intimately connected to extreme precipitation intensity and seasonality. The farther south a stratospheric PV intrusion reaches, the larger the IVT magnitude, and the longer the duration of their combined occurrence, the more extreme the precipitation. Our algorithm detects a large fraction of the climatological rainfall amounts (40-70%), heavy precipitation days (50-80%), and the top 10 extreme precipitation days (60-90%) at many sites in southern Israel and the northern and western parts of Saudi Arabia. This identification method provides a new tool for future work to disentangle teleconnections, assess medium-range predictability and improve understanding of climatic changes of extreme precipitation in the Middle East and elsewhere.

Identification of Tropical-Extratropical Interactions and Extreme Precipitation Events in the Middle East Based On Potential Vorticity and Moisture Transport

Science.gov (United States)

de Vries, A. J.; Ouwersloot, H. G.; Feldstein, S. B.; Riemer, M.; El Kenawy, A. M.; McCabe, M. F.; Lelieveld, J.

2018-01-01

Extreme precipitation events in the otherwise arid Middle East can cause flooding with dramatic socioeconomic impacts. Most of these events are associated with tropical-extratropical interactions, whereby a stratospheric potential vorticity (PV) intrusion reaches deep into the subtropics and forces an incursion of high poleward vertically integrated water vapor transport (IVT) into the Middle East. This study presents an object-based identification method for extreme precipitation events based on the combination of these two larger-scale meteorological features. The general motivation for this approach is that precipitation is often poorly simulated in relatively coarse weather and climate models, whereas the synoptic-scale circulation is much better represented. The algorithm is applied to ERA-Interim reanalysis data (1979-2015) and detects 90% (83%) of the 99th (97.5th) percentile of extreme precipitation days in the region of interest. Our results show that stratospheric PV intrusions and IVT structures are intimately connected to extreme precipitation intensity and seasonality. The farther south a stratospheric PV intrusion reaches, the larger the IVT magnitude, and the longer the duration of their combined occurrence, the more extreme the precipitation. Our algorithm detects a large fraction of the climatological rainfall amounts (40-70%), heavy precipitation days (50-80%), and the top 10 extreme precipitation days (60-90%) at many sites in southern Israel and the northern and western parts of Saudi Arabia. This identification method provides a new tool for future work to disentangle teleconnections, assess medium-range predictability, and improve understanding of climatic changes of extreme precipitation in the Middle East and elsewhere.

Rapid and reliable detection and identification of GM events using multiplex PCR coupled with oligonucleotide microarray.

Science.gov (United States)

Xu, Xiaodan; Li, Yingcong; Zhao, Heng; Wen, Si-yuan; Wang, Sheng-qi; Huang, Jian; Huang, Kun-lun; Luo, Yun-bo

2005-05-18

To devise a rapid and reliable method for the detection and identification of genetically modified (GM) events, we developed a multiplex polymerase chain reaction (PCR) coupled with a DNA microarray system simultaneously aiming at many targets in a single reaction. The system included probes for screening gene, species reference gene, specific gene, construct-specific gene, event-specific gene, and internal and negative control genes. 18S rRNA was combined with species reference genes as internal controls to assess the efficiency of all reactions and to eliminate false negatives. Two sets of the multiplex PCR system were used to amplify four and five targets, respectively. Eight different structure genes could be detected and identified simultaneously for Roundup Ready soybean in a single microarray. The microarray specificity was validated by its ability to discriminate two GM maizes Bt176 and Bt11. The advantages of this method are its high specificity and greatly reduced false-positives and -negatives. The multiplex PCR coupled with microarray technology presented here is a rapid and reliable tool for the simultaneous detection of GM organism ingredients.

The relationship of Emotional Intelligence with Academic Intelligence and the Big Five

NARCIS (Netherlands)

Van der Zee, K.I.; Thijs, Melanie; Schakel, Lolle

The present study examines the relationship of self- and other ratings of emotional intelligence with academic intelligence and personality, as well as the incremental validity of emotional intelligence beyond academic intelligence and personality in predicting academic and social success. A sample

The relationship of emotional intelligence with academic intelligence and the Big Five

NARCIS (Netherlands)

van der Zee, K; Thijs, M; Schakel, L

2002-01-01

The present study examines the relationship of self- and other ratings of emotional intelligence with academic intelligence and personality, as well as the incremental validity of emotional intelligence beyond academic intelligence and personality in predicting academic and social success. A sample

Tuberculosis control, and the where and why of artificial intelligence

Directory of Open Access Journals (Sweden)

Riddhi Doshi

2017-06-01

Full Text Available Countries aiming to reduce their tuberculosis (TB burden by 2035 to the levels envisaged by the World Health Organization End TB Strategy need to innovate, with approaches such as digital health (electronic and mobile health in support of patient care, surveillance, programme management, training and communication. Alongside the large-scale roll-out required for such interventions to make a significant impact, products must stay abreast of advancing technology over time. The integration of artificial intelligence into new software promises to make processes more effective and efficient, endowing them with a potential hitherto unimaginable. Users can benefit from artificial intelligence-enabled pattern recognition software for tasks ranging from reading radiographs to adverse event monitoring, sifting through vast datasets to personalise a patient's care plan or to customise training materials. Many experts forecast the imminent transformation of the delivery of healthcare services. We discuss how artificial intelligence and machine learning could revolutionise the management of TB.

Tuberculosis control, and the where and why of artificial intelligence

Science.gov (United States)

Falzon, Dennis; Thomas, Bruce V.; Temesgen, Zelalem; Sadasivan, Lal; Raviglione, Mario

2017-01-01

Countries aiming to reduce their tuberculosis (TB) burden by 2035 to the levels envisaged by the World Health Organization End TB Strategy need to innovate, with approaches such as digital health (electronic and mobile health) in support of patient care, surveillance, programme management, training and communication. Alongside the large-scale roll-out required for such interventions to make a significant impact, products must stay abreast of advancing technology over time. The integration of artificial intelligence into new software promises to make processes more effective and efficient, endowing them with a potential hitherto unimaginable. Users can benefit from artificial intelligence-enabled pattern recognition software for tasks ranging from reading radiographs to adverse event monitoring, sifting through vast datasets to personalise a patient's care plan or to customise training materials. Many experts forecast the imminent transformation of the delivery of healthcare services. We discuss how artificial intelligence and machine learning could revolutionise the management of TB. PMID:28656130

Tuberculosis control, and the where and why of artificial intelligence.

Science.gov (United States)

Doshi, Riddhi; Falzon, Dennis; Thomas, Bruce V; Temesgen, Zelalem; Sadasivan, Lal; Migliori, Giovanni Battista; Raviglione, Mario

2017-04-01

Countries aiming to reduce their tuberculosis (TB) burden by 2035 to the levels envisaged by the World Health Organization End TB Strategy need to innovate, with approaches such as digital health (electronic and mobile health) in support of patient care, surveillance, programme management, training and communication. Alongside the large-scale roll-out required for such interventions to make a significant impact, products must stay abreast of advancing technology over time. The integration of artificial intelligence into new software promises to make processes more effective and efficient, endowing them with a potential hitherto unimaginable. Users can benefit from artificial intelligence-enabled pattern recognition software for tasks ranging from reading radiographs to adverse event monitoring, sifting through vast datasets to personalise a patient's care plan or to customise training materials. Many experts forecast the imminent transformation of the delivery of healthcare services. We discuss how artificial intelligence and machine learning could revolutionise the management of TB.

Initiating events and accidental sequences taken into account in the CAREM reactor design

International Nuclear Information System (INIS)

Kay, J.M.; Felizia, E.R.; Navarro, N.R.; Caruso, G.J.

1990-01-01

The advance made in the nuclear security evaluation of the CAREM reactor is presented. It was carried out using the Security Probabilistic Analysis (SPA). The latter takes into account the different phases of identification and solution of initiating events and the qualitative development of event trees. The method of identification of initiating events is the Master Logical Diagram (MLD), whose deductive basis makes it appropriate for a new design like the one described. The qualitative development of the event trees associated to the identified initiating events, allows identification of those accidental sequences which are to have the security systems in the reactor. (Author) [es

Effect of task complexity on intelligence and neural efficiency in children: an event-related potential study.

Science.gov (United States)

Zhang, Qiong; Shi, Jiannong; Luo, Yuejia; Liu, Sainan; Yang, Jie; Shen, Mowei

2007-10-08

The present study investigates the effects of task complexity, intelligence and neural efficiency on children's performance on an Elementary Cognitive Task. Twenty-three children were divided into two groups on the basis of their Raven Progressive Matrix scores and were then asked to complete a choice reaction task with two test conditions. We recorded the electroencephalogram and calculated the peak latencies and amplitudes for anteriorly distributed P225, N380 and late positive component. Our results suggested shorter late positive component latencies in brighter children, possibly reflecting a higher processing speed in these individuals. Increased P225 amplitude and increased N380 amplitudes for brighter children may indicate a more efficient allocation of attention for brighter children. No moderating effect of task complexity on brain-intelligence relationship was found.

Intelligence, Belief in the Paranormal, Knowledge of Probability and Aging

Science.gov (United States)

Stuart-Hamilton, Ian; Nayak, Laxman; Priest, Lee

2006-01-01

In young adults, preparedness to accept improbable events as planned rather than due to chance is predictive of the level of belief in the paranormal, possibly underpinned by lower intelligence levels (Musch and Ehrenberg, 2002). The present study, using a sample of 73 older participants aged 60-84 years failed to find any relationship between…

Pollutant source identification model for water pollution incidents in small straight rivers based on genetic algorithm

Science.gov (United States)

Zhang, Shou-ping; Xin, Xiao-kang

2017-07-01

Identification of pollutant sources for river pollution incidents is an important and difficult task in the emergency rescue, and an intelligent optimization method can effectively compensate for the weakness of traditional methods. An intelligent model for pollutant source identification has been established using the basic genetic algorithm (BGA) as an optimization search tool and applying an analytic solution formula of one-dimensional unsteady water quality equation to construct the objective function. Experimental tests show that the identification model is effective and efficient: the model can accurately figure out the pollutant amounts or positions no matter single pollution source or multiple sources. Especially when the population size of BGA is set as 10, the computing results are sound agree with analytic results for a single source amount and position identification, the relative errors are no more than 5 %. For cases of multi-point sources and multi-variable, there are some errors in computing results for the reasons that there exist many possible combinations of the pollution sources. But, with the help of previous experience to narrow the search scope, the relative errors of the identification results are less than 5 %, which proves the established source identification model can be used to direct emergency responses.

[Role of the implicit theories of intelligence in learning situations].

Science.gov (United States)

Da Fonseca, D; Cury, F; Bailly, D; Rufo, M

2004-01-01

Most studies have tried to explain the school difficulties by analysing the intellectual factors that lead to school failure. However in addition to the instrumental capacities, authors also recognize the role played by other factors such as motivation. More specifically, the theory of achievement motivation aims to determine motivational factors involved in achievement situations when the students have to demonstrate their competencies. This paradigm attributes a central place to beliefs in order to explain children's behavior in academic situations. According to Dweck, it seems that beliefs about the nature of intelligence have a very powerful impact on behavior. These implicit theories of intelligence create a meaning system or conceptual framework that influences the individual interpretation of school situations. Thus, an entity theory of intelligence is the belief that intelligence is a fixed trait, a personal quality that cannot be changed. Students who subscribe to this theory believe that although people can learn new things, their underlying intelligence remains the same. In contrast, an incremental theory of intelligence is the belief that intelligence is a malleable quality that can increase through efforts. The identification of these two theories allows us to understand the cognition and behavior of individuals in achievement situations. Many studies carried out in the academic area show that students who hold an entity theory of intelligence (ie they consider intelligence like a stable quality) have a strong tendency to attribute their failures to a fixed trait. They are more likely to blame their intelligence for ne-gative outcomes and to attribute failures to their bad intellectual ability. In contrast, students who hold an incremental theory of intelligence (ie they consider intelligence as a malleable quality) are more likely to understand the same ne-gative outcomes in terms of specific factors: they attribute them to a lack of effort. This

Artificial Intelligence Project

Science.gov (United States)

1990-01-01

Symposium on Aritificial Intelligence and Software Engineering Working Notes, March 1989. Blumenthal, Brad, "An Architecture for Automating...Artificial Intelligence Project Final Technical Report ARO Contract: DAAG29-84-K-OGO Artificial Intelligence LaboratO"ry The University of Texas at...Austin N>.. ~ ~ JA 1/I 1991 n~~~ Austin, Texas 78712 ________k A,.tificial Intelligence Project i Final Technical Report ARO Contract: DAAG29-84-K-0060

Intelligent control of a planning system for astronaut training.

Science.gov (United States)

Ortiz, J; Chen, G

1999-07-01

This work intends to design, analyze and solve, from the systems control perspective, a complex, dynamic, and multiconstrained planning system for generating training plans for crew members of the NASA-led International Space Station. Various intelligent planning systems have been developed within the framework of artificial intelligence. These planning systems generally lack a rigorous mathematical formalism to allow a reliable and flexible methodology for their design, modeling, and performance analysis in a dynamical, time-critical, and multiconstrained environment. Formulating the planning problem in the domain of discrete-event systems under a unified framework such that it can be modeled, designed, and analyzed as a control system will provide a self-contained theory for such planning systems. This will also provide a means to certify various planning systems for operations in the dynamical and complex environments in space. The work presented here completes the design, development, and analysis of an intricate, large-scale, and representative mathematical formulation for intelligent control of a real planning system for Space Station crew training. This planning system has been tested and used at NASA-Johnson Space Center.

Event-by-event particle multiplicity fluctuations in Pb-Pb collisions with ALICE

Energy Technology Data Exchange (ETDEWEB)

Arslandok, Mesut [Institut fuer Kernphysik, Goethe-Universitaet Frankfurt (Germany); Collaboration: ALICE-Collaboration

2014-07-01

The study of event-by-event fluctuations of identified hadrons may reveal the degrees of freedom of the strongly interacting mater created in heavy-ion collisions. Particle identification that is based on the measurement of the specific ionization energy loss dE/dx works well on a statistical basis, however, suffers from ambiguities when applied on the event-by-event level. A novel experimental technique called the ''Identity Method'' was recently proposed to overcome such limitations. The method follows a probabilistic approach using the inclusive dE/dx distributions measured in the ALICE TPC, and determines the moments of the multiplicity distributions by an unfolding procedure. In this contribution, the status of an event-by-event fluctuation analysis that applies the Identity Method to Pb-Pb data from ALICE is presented.

Routledge companion to intelligence studies

CERN Document Server

Dover, Robert; Hillebrand, Claudia

2013-01-01

The Routledge Companion to Intelligence Studies provides a broad overview of the growing field of intelligence studies. The recent growth of interest in intelligence and security studies has led to an increased demand for popular depictions of intelligence and reference works to explain the architecture and underpinnings of intelligence activity. Divided into five comprehensive sections, this Companion provides a strong survey of the cutting-edge research in the field of intelligence studies: Part I: The evolution of intelligence studies; Part II: Abstract approaches to intelligence; Part III: Historical approaches to intelligence; Part IV: Systems of intelligence; Part V: Contemporary challenges. With a broad focus on the origins, practices and nature of intelligence, the book not only addresses classical issues, but also examines topics of recent interest in security studies. The overarching aim is to reveal the rich tapestry of intelligence studies in both a sophisticated and accessible way. This Companion...

Atomic-scale nanoindentation: detection and identification of single glide events in three dimensions by force microscopy

International Nuclear Information System (INIS)

Egberts, P; Bennewitz, R

2011-01-01

Indentation experiments on the nanometre scale have been performed by means of atomic force microscopy in ultra-high vacuum on KBr(100) surfaces. The surfaces yield in the form of discrete surface displacements with a typical length scale of 1 A. These surface displacements are detected in both normal and lateral directions. Measurement of the lateral tip displacement requires a load-dependent calibration due to the load dependence of the effective lateral compliance. Correlation of the lateral and normal displacements for each glide event allow identification of the activated slip system. The results are discussed in terms of the resolved shear stress in indentation experiments and of typical results in atomistic simulations of nanometre-scale indentation.

78 FR 90 - Defense Intelligence Agency National Intelligence University Board of Visitors Closed Meeting

Science.gov (United States)

2013-01-02

... DEPARTMENT OF DEFENSE Office of the Secretary Defense Intelligence Agency National Intelligence University Board of Visitors Closed Meeting AGENCY: National Intelligence University, Defense Intelligence... hereby given that a closed meeting of the National Intelligence University Board of Visitors has been...

REAL-TIME INTELLIGENT MULTILAYER ATTACK CLASSIFICATION SYSTEM

Directory of Open Access Journals (Sweden)

T. Subbhulakshmi

2014-01-01

Full Text Available Intrusion Detection Systems (IDS takes the lion’s share of the current security infrastructure. Detection of intrusions is vital for initiating the defensive procedures. Intrusion detection was done by statistical and distance based methods. A threshold value is used in these methods to indicate the level of normalcy. When the network traffic crosses the level of normalcy then above which it is flagged as anomalous. When there are occurrences of new intrusion events which are increasingly a key part of system security, the statistical techniques cannot detect them. To overcome this issue, learning techniques are used which helps in identifying new intrusion activities in a computer system. The objective of the proposed system designed in this paper is to classify the intrusions using an Intelligent Multi Layered Attack Classification System (IMLACS which helps in detecting and classifying the intrusions with improved classification accuracy. The intelligent multi layered approach contains three intelligent layers. The first layer involves Binary Support Vector Machine classification for detecting the normal and attack. The second layer involves neural network classification to classify the attacks into classes of attacks. The third layer involves fuzzy inference system to classify the attacks into various subclasses. The proposed IMLACS can be able to detect an intrusion behavior of the networks since the system contains a three intelligent layer classification and better set of rules. Feature selection is also used to improve the time of detection. The experimental results show that the IMLACS achieves the Classification Rate of 97.31%.

Survey of artificial intelligence methods for detection and identification of component faults in nuclear power plants

International Nuclear Information System (INIS)

Reifman, J.

1997-01-01

A comprehensive survey of computer-based systems that apply artificial intelligence methods to detect and identify component faults in nuclear power plants is presented. Classification criteria are established that categorize artificial intelligence diagnostic systems according to the types of computing approaches used (e.g., computing tools, computer languages, and shell and simulation programs), the types of methodologies employed (e.g., types of knowledge, reasoning and inference mechanisms, and diagnostic approach), and the scope of the system. The major issues of process diagnostics and computer-based diagnostic systems are identified and cross-correlated with the various categories used for classification. Ninety-five publications are reviewed

Event recognition using signal spectrograms in long pulse experiments

International Nuclear Information System (INIS)

Gonzalez, J.; Ruiz, M.; Barrera, E.; Arcas, G.; Lopez, J. M.; Vega, J.

2010-01-01

As discharge duration increases, real-time complex analysis of the signal becomes more important. In this context, data acquisition and processing systems must provide models for designing experiments which use event oriented plasma control. One example of advanced data analysis is signal classification. The off-line statistical analysis of a large number of discharges provides information to develop algorithms for the determination of the plasma parameters from measurements of magnetohydrodinamic waves, for example, to detect density fluctuations induced by the Alfven cascades using morphological patterns. The need to apply different algorithms to the signals and to address different processing algorithms using the previous results necessitates the use of an event-based experiment. The Intelligent Test and Measurement System platform is an example of architecture designed to implement distributed data acquisition and real-time processing systems. The processing algorithm sequence is modeled using an event-based paradigm. The adaptive capacity of this model is based on the logic defined by the use of state machines in SCXML. The Intelligent Test and Measurement System platform mixes a local multiprocessing model with a distributed deployment of services based on Jini.

Social cognition in bipolar disorder: Focus on emotional intelligence.

Science.gov (United States)

Varo, C; Jimenez, E; Solé, B; Bonnín, C M; Torrent, C; Valls, E; Morilla, I; Lahera, G; Martínez-Arán, A; Vieta, E; Reinares, M

2017-08-01

The present study aims to characterize emotional intelligence (EI) variability in a sample of euthymic bipolar disorder (BD) patients through the Mayer- Salovey-Caruso Emotional Intelligence Test (MSCEIT). A total of 134 euthymic BD outpatients were recruited and divided into three groups according to the total Emotional Intelligence Quotient (EIQ) score of the MSCEIT, following a statistical criterion of scores 1.5SDs above/below the normative group mean, as follows: a low performance (LP) group (EIQ 115). Afterwards, main sociodemographic, clinical, functional and neurocognitive variables were compared between the groups. Three groups were identified: 1) LP group (n=16, 12%), 2) NP group (n=93, 69%) and 3) HP group (n=25, 19%). There were significant differences between the groups in premorbid intelligence quotient (IQ) (p=0.010), axis II comorbidity (p=0.008), subthreshold depressive symptoms (p=0.027), general functioning (p=0.013) and in four specific functional domains: autonomy, occupation, interpersonal relations and leisure time. Significant differences in neurocognitive performance were found between groups with the LP group showing the lowest attainments. The cross-sectional design of the study. Our results suggest that EI variability among BD patients, assessed through MSCEIT, is lower than expected. EI could be associated with premorbid IQ, subthreshold depressive symptoms, neurocognitive performance and general functioning. The identification of different profiles of SC may help guide specific interventions for distinct patient subgroups aimed at improving social cognition, neurocognitive performance and psychosocial functioning. Copyright © 2017 Elsevier B.V. All rights reserved.

Logical Aspects Regarding the Conception of Intelligent Systems

Directory of Open Access Journals (Sweden)

Vasile Mazilescu

2016-07-01

Full Text Available The present paper presents some logical aspects of symbolic AI Systems, applied to the Intelligent Systems design. The basic feature of these systems is represented by the processing of the imprecise and dynamic knowledge involved in the synthesis of some decisions. We consider that the paper tackles an up-to-date and little debated aspect especially in the field of decision fuzzy systems. Knowledge-based systems with real-time functioning bear features that the majority of classic systems do not have: reasoning is evolutionary and non-monotonous due to the dynamic nature of the application, and events can change the status of the expert management system. The management architectures based on symbolic techniques acquire characteristics specific to the domain problem and to the type of intelligent system based on a management knowledge structure.

Intelligent products : A survey

NARCIS (Netherlands)

Meyer, G.G.; Främling, K.; Holmström, J.

This paper presents an overview of the field of Intelligent Products. As Intelligent Products have many facets, this paper is mainly focused on the concept behind Intelligent Products, the technical foundations, and the achievable practical goals of Intelligent Products. A novel classification of

Benefits of collective intelligence: Swarm intelligent foraging, an ethnographic research

Directory of Open Access Journals (Sweden)

Sivave Mashingaidze

2014-12-01

Full Text Available Wisdom of crowds; bees, colonies of ants, schools of fish, flocks of birds, and fireflies flashing synchronously are all examples of highly coordinated behaviors that emerge from collective, decentralized intelligence. This article is an ethnographic study of swarm intelligence foraging of swarms and the benefits derived from collective decision making. The author used using secondary data analysis to look at the benefits of swarm intelligence in decision making to achieve intended goals. Concepts like combined decision making and consensus were discussed and four principles of swarm intelligence were also discussed viz; coordination, cooperation, deliberation and collaboration. The research found out that collective decision making in swarms is the touchstone of achieving their goals. The research further recommended corporate to adopt collective intelligence for business sustainability.

Asymptotic Effectiveness of the Event-Based Sampling According to the Integral Criterion

Directory of Open Access Journals (Sweden)

Marek Miskowicz

2007-01-01

Full Text Available A rapid progress in intelligent sensing technology creates new interest in a development of analysis and design of non-conventional sampling schemes. The investigation of the event-based sampling according to the integral criterion is presented in this paper. The investigated sampling scheme is an extension of the pure linear send-on- delta/level-crossing algorithm utilized for reporting the state of objects monitored by intelligent sensors. The motivation of using the event-based integral sampling is outlined. The related works in adaptive sampling are summarized. The analytical closed-form formulas for the evaluation of the mean rate of event-based traffic, and the asymptotic integral sampling effectiveness, are derived. The simulation results verifying the analytical formulas are reported. The effectiveness of the integral sampling is compared with the related linear send-on-delta/level-crossing scheme. The calculation of the asymptotic effectiveness for common signals, which model the state evolution of dynamic systems in time, is exemplified.

Intelligence: Real or artificial?

OpenAIRE

Schlinger, Henry D.

1992-01-01

Throughout the history of the artificial intelligence movement, researchers have strived to create computers that could simulate general human intelligence. This paper argues that workers in artificial intelligence have failed to achieve this goal because they adopted the wrong model of human behavior and intelligence, namely a cognitive essentialist model with origins in the traditional philosophies of natural intelligence. An analysis of the word “intelligence” suggests that it originally r...

Harnessing Artificial Intelligence the European Way

OpenAIRE

Djeffal, Christian

2018-01-01

Will 10 April 2018 be remembered by many as the day of Mark Zuckerberg’s testimony before the US Senate? The hearing was covered by the media in all aspects down to the tie he was wearing. But that was not the only important event taking place on that day, and maybe not even the most important one: I am talking about the Declaration on Cooperation in Artificial Intelligence, signed on the same day but hardly noticed. And yet its impact in the long term might exceed that of the current scandal...

Active and intelligent packaging: The indication of quality and safety.

Science.gov (United States)

Janjarasskul, Theeranun; Suppakul, Panuwat

2018-03-24

The food industry has been under growing pressure to feed an exponentially increasing world population and challenged to meet rigorous food safety law and regulation. The plethora of media consumption has provoked consumer demand for safe, sustainable, organic, and wholesome products with "clean" labels. The application of active and intelligent packaging has been commercially adopted by food and pharmaceutical industries as a solution for the future for extending shelf life and simplifying production processes; facilitating complex distribution logistics; reducing, if not eliminating the need for preservatives in food formulations; enabling restricted food packaging applications; providing convenience, improving quality, variety and marketing features; as well as providing essential information to ensure consumer safety. This chapter reviews innovations of active and intelligent packaging which advance packaging technology through both scavenging and releasing systems for shelf life extension, and through diagnostic and identification systems for communicating quality, tracking and brand protection.

Intelligence and Security Standards on Industrial Facilities Protection in Case of Terrorism and Military Attack

International Nuclear Information System (INIS)

Stipetic, D.

2007-01-01

Industrial facilities, which use toxic chemicals in their production processes, are tempting targets for military and terrorist strategists. They know that these facilities when attacked could produce effects not realizable with conventional weapons. The resulting legal, policy and political consequences would be minimal as compared to that of disseminating toxic chemicals or chemical agents as weapons on enemy territory. At this time there is no clear definition of the legality or illegality of these types of actions used against specific industrial targets for the purpose of mass destruction or disruption. Without clearly defined international regulations covering these actions, we must depend solely on national defense systems. Not only are these regulation not defined, there are no implementation tools, which would be available if the various treaties (CWC/BWC) etc., were able to incorporate needed legislative action. Consequently we must depend on and put into practice defense security standards for industrial facilities for protection against both possible terrorist and military attacks. Emergency responses to incidents involving violent criminals and terrorists are extremely dangerous. Incidents involving weapons of mass destruction, firearms, and hazardous materials have resulted in the injury and death of many firefighters, police officers and medical personnel. We wish to intend display place and role of intelligence and counter intelligence system to prevention potential target and military attack. Security needs to be incorporated into the public safety culture and it must become the routine for how we operate. The recognition and identification process is an important skill that needs continual refinement. The use of transportation or facility paperwork assists in recognizing what potential hazards. A key factor in the successful command and management of a hazmat incident or terrorism event is the ability of public safety agencies to function as a

Identifying Prominent Life Events on Twitter

OpenAIRE

Dickinson, Thomas; Fernández, Miriam; Thomas, Lisa A.; Mulholland, Paul; Briggs, Pam; Alani, Harith

2015-01-01

Social media is a common place for people to post and share digital reflections of their life events, including major events such as getting married, having children, graduating, etc. Although the creation of such posts is straightforward, the identification of events on online media remains a challenge. Much research in recent years focused on extracting major events from Twitter, such as earthquakes, storms, and floods. This paper however, targets the automatic detection of personal life ev...

Dysregulation in level of goal and action identification across psychological disorders

Science.gov (United States)

Watkins, Edward

2011-01-01

Goals, events, and actions can be mentally represented within a hierarchical framework that ranges from more abstract to more concrete levels of identification. A more abstract level of identification involves general, superordinate, and decontextualized mental representations that convey the meaning of goals, events, and actions, “why” an action is performed, and its purpose, ends, and consequences. A more concrete level of identification involves specific and subordinate mental representations that include contextual details of goals, events, and actions, and the specific “how” details of an action. This review considers three lines of evidence for considering that dysregulation of level of goal/action identification may be a transdiagnostic process. First, there is evidence that different levels of identification have distinct functional consequences and that in non-clinical samples level of goal/action identification appears to be regulated in a flexible and adaptive way to match the level of goal/action identification to circumstances. Second, there is evidence that level of goal/action identification causally influences symptoms and processes involved in psychological disorders, including emotional response, repetitive thought, impulsivity, problem solving and procrastination. Third, there is evidence that the level of goal/action identification is biased and/or dysregulated in certain psychological disorders, with a bias towards more abstract identification for negative events in depression, GAD, PTSD, and social anxiety. PMID:20579789

Intelligent Method for Identifying Driving Risk Based on V2V Multisource Big Data

Directory of Open Access Journals (Sweden)

Jinshuan Peng

2018-01-01

Full Text Available Risky driving behavior is a major cause of traffic conflicts, which can develop into road traffic accidents, making the timely and accurate identification of such behavior essential to road safety. A platform was therefore established for analyzing the driving behavior of 20 professional drivers in field tests, in which overclose car following and lane departure were used as typical risky driving behaviors. Characterization parameters for identification were screened and used to determine threshold values and an appropriate time window for identification. A neural network-Bayesian filter identification model was established and data samples were selected to identify risky driving behavior and evaluate the identification efficiency of the model. The results obtained indicated a successful identification rate of 83.6% when the neural network model was solely used to identify risky driving behavior, but this could be increased to 92.46% once corrected by the Bayesian filter. This has important theoretical and practical significance in relation to evaluating the efficiency of existing driver assist systems, as well as the development of future intelligent driving systems.

Complex Event Detection via Multi Source Video Attributes (Open Access)

Science.gov (United States)

2013-10-03

Complex Event Detection via Multi-Source Video Attributes Zhigang Ma† Yi Yang‡ Zhongwen Xu‡§ Shuicheng Yan Nicu Sebe† Alexander G. Hauptmann...under its International Research Centre @ Singapore Fund- ing Initiative and administered by the IDM Programme Of- fice, and the Intelligence Advanced

Remote Identification of Port Scan Toolchains

NARCIS (Netherlands)

Ghiëtte, Vincent; Blenn, N.; Doerr, C.; Badra, Mohamad; Pau, Giovanni; Vassiliou, Vasos

2016-01-01

Port scans are typically at the begin of a chain of events that will lead to the attack and exploitation of a host over a network. Since building an effective defense relies on information what kind of threat an organization is facing, threat intelligence outlining an actor’s modus operandi is a

Quality control of intelligence research

International Nuclear Information System (INIS)

Lu Yan; Xin Pingping; Wu Jian

2014-01-01

Quality control of intelligence research is the core issue of intelligence management, is a problem in study of information science This paper focuses on the performance of intelligence to explain the significance of intelligence research quality control. In summing up the results of the study on the basis of the analysis, discusses quality control methods in intelligence research, introduces the experience of foreign intelligence research quality control, proposes some recommendations to improve quality control in intelligence research. (authors)

Intelligence Issues for Congress

Science.gov (United States)

2013-04-23

open source information— osint (newspapers...by user agencies. Section 1052 of the Intelligence Reform Act expressed the sense of Congress that there should be an open source intelligence ...center to coordinate the collection, analysis, production, and dissemination of open source intelligence to other intelligence agencies. An Open Source

Intelligent Transportation and Evacuation Planning A Modeling-Based Approach

CERN Document Server

Naser, Arab

2012-01-01

Intelligent Transportation and Evacuation Planning: A Modeling-Based Approach provides a new paradigm for evacuation planning strategies and techniques. Recently, evacuation planning and modeling have increasingly attracted interest among researchers as well as government officials. This interest stems from the recent catastrophic hurricanes and weather-related events that occurred in the southeastern United States (Hurricane Katrina and Rita). The evacuation methods that were in place before and during the hurricanes did not work well and resulted in thousands of deaths. This book offers insights into the methods and techniques that allow for implementing mathematical-based, simulation-based, and integrated optimization and simulation-based engineering approaches for evacuation planning. This book also: Comprehensively discusses the application of mathematical models for evacuation and intelligent transportation modeling Covers advanced methodologies in evacuation modeling and planning Discusses principles a...

Orchestrating Multiple Intelligences

Science.gov (United States)

Moran, Seana; Kornhaber, Mindy; Gardner, Howard

2006-01-01

Education policymakers often go astray when they attempt to integrate multiple intelligences theory into schools, according to the originator of the theory, Howard Gardner, and his colleagues. The greatest potential of a multiple intelligences approach to education grows from the concept of a profile of intelligences. Each learner's intelligence…

Development of an intelligent hydroinformatic system for real-time monitoring and assessment of civil infrastructure

Science.gov (United States)

Cahill, Paul; Michalis, Panagiotis; Solman, Hrvoje; Kerin, Igor; Bekic, Damir; Pakrashi, Vikram; McKeogh, Eamon

2017-04-01

With the effects of climate change becoming more apparent, extreme weather events are now occurring with greater frequency throughout the world. Such extreme events have resulted in increased high intensity flood events which are having devastating consequences on hydro-structures, especially on bridge infrastructure. The remote and often inaccessible nature of such bridges makes inspections problematic, a major concern if safety assessments are required during and after extreme flood events. A solution to this is the introduction of smart, low cost sensing solutions at locations susceptible to hydro-hazards. Such solutions can provide real-time information on the health of the bridge and its environments, with such information aiding in the mitigation of the risks associated with extreme weather events. This study presents the development of an intelligent system for remote, real-time monitoring of hydro-hazards to bridge infrastructure. The solution consists of two types of remote monitoring stations which have the capacity to monitor environmental conditions and provide real-time information to a centralized, big data database solution, from which an intelligent decision support system will accommodate the results to control and manage bridge, river and catchment assets. The first device developed as part of the system is the Weather Information Logging Device (WILD), which monitors rainfall, temperature and air and soil moisture content. The ability of the WILD to monitor rainfall in real time enables flood early warning alerts and predictive river flow conditions, thereby enabling decision makers the ability to make timely and effective decisions about critical infrastructures in advance of extreme flood events. The WILD is complemented by a second monitoring device, the Bridge Information Recording Device (BIRD), which monitors water levels at a given location in real-time. The monitoring of water levels of a river allows for, among other applications

Semantic Business Intelligence - a New Generation of Business Intelligence

Directory of Open Access Journals (Sweden)

Dinu AIRINEI

2012-01-01

Full Text Available Business Intelligence Solutions represents applications used by companies to manage process and analyze data to provide substantiated decision. In the context of Semantic Web develop-ment trend is to integrate semantic unstructured data, making business intelligence solutions to be redesigned in such a manner that can analyze, process and synthesize, in addition to traditional data and data integrated with semantic another form and structure. This invariably leads appearance of new BI solution, called Semantic Business Intelligence.

Review on identification study of driver behavior intention and characteristics

Directory of Open Access Journals (Sweden)

Gang LI

2017-08-01

Full Text Available In order to better improve vehicle active safety and realize personalized driving, aiming at the problem of the identification of driver behavior intention and characteristics, the electronic control systems' important role in the automobile and the importance of the driver behavior intention and characteristic identification are discussed. The relative domestic and foreign research is summarized, and the prospect is put forward. In order to improve the performance of automobile electronic control system and realize the intelligent control for the cars, the identification of driver behavior intention and characteristics needs to be studied. How to rationally classify and on-line identify drivers' characteristics correctly for the steering, braking and acceleration characteristics is a long term research topic.

Development of SPIES (Space Intelligent Eyeing System) for smart vehicle tracing and tracking

Science.gov (United States)

Abdullah, Suzanah; Ariffin Osoman, Muhammad; Guan Liyong, Chua; Zulfadhli Mohd Noor, Mohd; Mohamed, Ikhwan

2016-06-01

SPIES or Space-based Intelligent Eyeing System is an intelligent technology which can be utilized for various applications such as gathering spatial information of features on Earth, tracking system for the movement of an object, tracing system to trace the history information, monitoring driving behavior, security and alarm system as an observer in real time and many more. SPIES as will be developed and supplied modularly will encourage the usage based on needs and affordability of users. SPIES are a complete system with camera, GSM, GPS/GNSS and G-Sensor modules with intelligent function and capabilities. Mainly the camera is used to capture pictures and video and sometimes with audio of an event. Its usage is not limited to normal use for nostalgic purpose but can be used as a reference for security and material of evidence when an undesirable event such as crime occurs. When integrated with space based technology of the Global Navigational Satellite System (GNSS), photos and videos can be recorded together with positioning information. A product of the integration of these technologies when integrated with Information, Communication and Technology (ICT) and Geographic Information System (GIS) will produce innovation in the form of information gathering methods in still picture or video with positioning information that can be conveyed in real time via the web to display location on the map hence creating an intelligent eyeing system based on space technology. The importance of providing global positioning information is a challenge but overcome by SPIES even in areas without GNSS signal reception for the purpose of continuous tracking and tracing capability

Research of Classical and Intelligent Information System Solutions for Criminal Intelligence Analysis

OpenAIRE

Šimović, Vladimir

2001-01-01

The objective of this study is to present research on classical and intelligent information system solutions used in criminal intelligence analysis in Croatian security system theory. The study analyses objective and classical methods of information science, including artificial intelligence and other scientific methods. The intelligence and classical software solutions researched, proposed, and presented in this study were used in developing the integrated information system for the Croatian...

Evaluation of the reliability concerning the identification of human factors as contributing factors by a computer supported event analysis (CEA)

International Nuclear Information System (INIS)

Wilpert, B.; Maimer, H.; Loroff, C.

2000-01-01

The project's objectives are the evaluation of the reliability concerning the identification of Human Factors as contributing factors by a computer supported event analysis (CEA). CEA is a computer version of SOL (Safety through Organizational Learning). Parts of the first step were interviews with experts from the nuclear power industry and the evaluation of existing computer supported event analysis methods. This information was combined to a requirement profile for the CEA software. The next step contained the implementation of the software in an iterative process of evaluation. The completion of this project was the testing of the CEA software. As a result the testing demonstrated that it is possible to identify contributing factors with CEA validly. In addition, CEA received a very positive feedback from the experts. (orig.) [de

USE OF RFID AT LARGE-SCALE EVENTS

Directory of Open Access Journals (Sweden)

Yuusuke KAWAKITA

2005-01-01

Full Text Available Radio Frequency Identification (RFID devices and related technologies have received a great deal of attention for their ability to perform non-contact object identification. Systems incorporating RFID have been evaluated from a variety of perspectives. The authors constructed a networked RFID system to support event management at NetWorld+Interop 2004 Tokyo, an event that received 150,000 visitors. The system used multiple RFID readers installed at the venue and RFID tags carried by each visitor to provide a platform for running various management and visitor support applications. This paper presents the results of this field trial of RFID readability rates. It further addresses the applicability of RFID systems to visitor management, a problematic aspect of large-scale events.

Identification and analysis of external event combinations for Hanhikivi 1PRA

Energy Technology Data Exchange (ETDEWEB)

Helander, Juho [Fennovoima Oy, Helsinki (Finland)

2017-03-15

Fennovoima's nuclear power plant, Hanhikivi 1, Pyhäjoki, Finland, is currently in design phase, and its construction is scheduled to begin in 2018 and electricity production in 2024. The objective of this paper is to produce a preliminary list of safety-significant external event combinations including preliminary probability estimates, to be used in the probabilistic risk assessment of Hanhikivi 1 plant. Starting from the list of relevant single events, the relevant event combinations are identified based on seasonal variation, preconditions related to different events, and dependencies (fundamental and cascade type) between events. Using this method yields 30 relevant event combinations of two events for the Hanhikivi site. The preliminary probability of each combination is evaluated, and event combinations with extremely low probability are excluded from further analysis. Event combinations of three or more events are identified by adding possible events to the remaining combinations of two events. Finally, 10 relevant combinations of two events and three relevant combinations of three events remain. The results shall be considered preliminary and will be updated after evaluating more detailed effects of different events on plant safety.

Artificial Consciousness or Artificial Intelligence

OpenAIRE

Spanache Florin

2017-01-01

Artificial intelligence is a tool designed by people for the gratification of their own creative ego, so we can not confuse conscience with intelligence and not even intelligence in its human representation with conscience. They are all different concepts and they have different uses. Philosophically, there are differences between autonomous people and automatic artificial intelligence. This is the difference between intelligence and artificial intelligence, autonomous versus a...

Accident diagnosis of the Angra-2 nuclear power plant based on intelligent real-time acquisition agents and a logical tree model

Energy Technology Data Exchange (ETDEWEB)

Paiva, Gustavo V.; Schirru, Roberto, E-mail: gustavopaiva@poli.ufrj.br, E-mail: schirru@lmp.ufrj.br [Coordenacao de Pos-Graduacao e Pesquisa de Engenharia (COPPE/UFRJ), Rio de Janeiro, RJ (Brazil). Departamento de Engenharia Nuclear

2017-07-01

This work aims to create a model and a prototype, using the Python language, which with the application of an Expert System uses production rules to analyze the data obtained in real time from the plant and help the operator to identify the occurrence of transients / accidents. In the event of a transient, the program alerts the operator and indicates which section of the Operation Manual should be consulted to bring the plant back to its normal state. The generic structure used to represent the knowledge of the Expert System was a Fault Tree and the data obtained from the plant was done through intelligent acquisition agents that transform the data obtained from the plant into Boolean values used in the Fault Tree, including the use of Fuzzy Logic. In order to test the program, a simplified model of the Almirante Alvaro Alberto 2 Nuclear Power Plant (Angra-2) manuals was used and with this model, simulations were performed to analyze the program's operation and if it leads to the expected results. The results of the tests presented a quick identification of the events and great accuracy, demonstrating the applicability of the model to the problem. (author)

Accident diagnosis of the Angra-2 nuclear power plant based on intelligent real-time acquisition agents and a logical tree model

International Nuclear Information System (INIS)

Paiva, Gustavo V.; Schirru, Roberto

2017-01-01

This work aims to create a model and a prototype, using the Python language, which with the application of an Expert System uses production rules to analyze the data obtained in real time from the plant and help the operator to identify the occurrence of transients / accidents. In the event of a transient, the program alerts the operator and indicates which section of the Operation Manual should be consulted to bring the plant back to its normal state. The generic structure used to represent the knowledge of the Expert System was a Fault Tree and the data obtained from the plant was done through intelligent acquisition agents that transform the data obtained from the plant into Boolean values used in the Fault Tree, including the use of Fuzzy Logic. In order to test the program, a simplified model of the Almirante Alvaro Alberto 2 Nuclear Power Plant (Angra-2) manuals was used and with this model, simulations were performed to analyze the program's operation and if it leads to the expected results. The results of the tests presented a quick identification of the events and great accuracy, demonstrating the applicability of the model to the problem. (author)

Intelligent mechatronics; Intelligent mechatronics

Energy Technology Data Exchange (ETDEWEB)

Hashimoto, H. [The University of Tokyo, Tokyo (Japan). Institute of Industrial Science

1995-10-01

Intelligent mechatronics (IM) was explained as follows: a study of IM essentially targets realization of a robot namely, but in the present stage the target is a creation of new values by intellectualization of machine, that is, a combination of the information infrastructure and the intelligent machine system. IM is also thought to be constituted of computers positively used and micromechatronics. The paper next introduces examples of IM study, mainly those the author is concerned with as shown below: sensor gloves, robot hands, robot eyes, tele operation, three-dimensional object recognition, mobile robot, magnetic bearing, construction of remote controlled unmanned dam, robot network, sensitivity communication using neuro baby, etc. 27 figs.

Brain Intelligence: Go Beyond Artificial Intelligence

OpenAIRE

Lu, Huimin; Li, Yujie; Chen, Min; Kim, Hyoungseop; Serikawa, Seiichi

2017-01-01

Artificial intelligence (AI) is an important technology that supports daily social life and economic activities. It contributes greatly to the sustainable growth of Japan's economy and solves various social problems. In recent years, AI has attracted attention as a key for growth in developed countries such as Europe and the United States and developing countries such as China and India. The attention has been focused mainly on developing new artificial intelligence information communication ...

Business Intelligence Systems

Directory of Open Access Journals (Sweden)

Bogdan NEDELCU

2014-02-01

Full Text Available The aim of this article is to show the importance of business intelligence and its growing influence. It also shows when the concept of business intelligence was used for the first time and how it evolved over time. The paper discusses the utility of a business intelligence system in any organization and its contribution to daily activities. Furthermore, we highlight the role and the objectives of business intelligence systems inside an organization and the needs to grow the incomes and reduce the costs, to manage the complexity of the business environment and to cut IT costs so that the organization survives in the current competitive climate. The article contains information about architectural principles of a business intelligence system and how such a system can be achieved.

Intelligence related upper alpha desynchronization in a semantic memory task.

Science.gov (United States)

Doppelmayr, M; Klimesch, W; Hödlmoser, K; Sauseng, P; Gruber, W

2005-07-30

Recent evidence shows that event-related (upper) alpha desynchronization (ERD) is related to cognitive performance. Several studies observed a positive, some a negative relationship. The latter finding, interpreted in terms of the neural efficiency hypothesis, suggests that good performance is associated with a more 'efficient', smaller extent of cortical activation. Other studies found that ERD increases with semantic processing demands and that this increase is larger for good performers. Studies supporting the neural efficiency hypothesis used tasks that do not specifically require semantic processing. Thus, we assume that the lack of semantic processing demands may at least in part be responsible for the reduced ERD. In the present study we measured ERD during a difficult verbal-semantic task. The findings demonstrate that during semantic processing, more intelligent (as compared to less intelligent) subjects exhibited a significantly larger upper alpha ERD over the left hemisphere. We conclude that more intelligent subjects exhibit a more extensive activation in a semantic processing system and suggest that divergent findings regarding the neural efficiency hypotheses are due to task specific differences in semantic processing demands.

Professionalizing Intelligence Analysis

Directory of Open Access Journals (Sweden)

James B. Bruce

2015-09-01

Full Text Available This article examines the current state of professionalism in national security intelligence analysis in the U.S. Government. Since the introduction of major intelligence reforms directed by the Intelligence Reform and Terrorism Prevention Act (IRTPA in December, 2004, we have seen notable strides in many aspects of intelligence professionalization, including in analysis. But progress is halting, uneven, and by no means permanent. To consolidate its gains, and if it is to continue improving, the U.S. intelligence community (IC should commit itself to accomplishing a new program of further professionalization of analysis to ensure that it will develop an analytic cadre that is fully prepared to deal with the complexities of an emerging multipolar and highly dynamic world that the IC itself is forecasting. Some recent reforms in intelligence analysis can be assessed against established standards of more fully developed professions; these may well fall short of moving the IC closer to the more fully professionalized analytical capability required for producing the kind of analysis needed now by the United States.

Acting in Isolation: Safeguarding and anti-trafficking officers' evidence and intelligence practices at the border

Directory of Open Access Journals (Sweden)

Jennifer K. Lynch

2017-04-01

Full Text Available Internationally, the border has been presented as a site of unique opportunity for the identification and protection of victims of human trafficking. In the UK, the establishment of specialist safeguarding and anti-trafficking (SAT units within the border force has raised questions about the challenges for border force officers (BFOs of balancing the enforcement of strict immigration rules with the protection of victims under anti-trafficking legislation. In this paper we draw on data collected from a study of anti-trafficking initiatives at Heathrow airport to consider a particular area of BFO frustration with SAT work: the collection and use of evidence and intelligence to support investigation and pursuit of potential SAT cases at the border. Our findings focus on the use of intelligence and data to inform initiatives and develop a comprehensive understanding of the trafficking problem; and the scope of BFO powers of evidence-collection on the frontline. The experience of BFOs points to a team often working in isolation as they attempt to traverse gaps in data collection and limits to their powers to gather evidence in pursuit of their duty to identify victims of trafficking at the UK border. We conclude by making proposals for how the border force and central government could improve evidence and intelligence practices in ways that translate into both more coherent anti-trafficking policy and better identification and support for victims.

Adding intelligence to mobile asset management in hospitals: the true value of RFID.

Science.gov (United States)

Castro, Linda; Lefebvre, Elisabeth; Lefebvre, Louis A

2013-10-01

RFID (Radio Frequency Identification) technology is expected to play a vital role in the healthcare arena, especially in times when cost containments are at the top of the priorities of healthcare management authorities. Medical equipment represents a significant share of yearly healthcare operational costs; hence, ensuring an effective and efficient management of such key assets is critical to promptly and reliably deliver a diversity of clinical services at the patient bedside. Empirical evidence from a phased-out RFID implementation in one European hospital demonstrates that RFID has the potential to transform asset management by improving inventory management, enhancing asset utilization, increasing staff productivity, improving care services, enhancing maintenance compliance, and increasing information visibility. Most importantly, RFID allows the emergence of intelligent asset management processes, which is, undoubtedly, the most important benefit that could be derived from the RFID system. Results show that the added intelligence can be rather basic (auto-status change) or a bit more advanced (personalized automatic triggers). More importantly, adding intelligence improves planning and decision-making processes.

Revolutionary Intelligence: The Expanding Intelligence Role of the Iranian Revolutionary Guard Corps

Directory of Open Access Journals (Sweden)

Udit Banerjea

2015-09-01

Full Text Available The Iranian Revolutionary Guard Corps (IRGC is a military and paramilitary organization that is meant to defend the ideals of the Iranian Islamic Revolution in 1979. Since its formation, the IRGC has grown in influence and its intelligence role has expanded. This paper examines the role of the IRGC in Iran’s intelligence system through a comprehensive analysis of the organization of the IRGC’s intelligence arm, along with its operations and capabilities. In doing so, the scope, objectives, resources, customers, and sponsors of the IRGC’s intelligence activities are also analyzed. Additionally, this paper explores how the IRGC interacts with the government of Iran, the Ministry of Intelligence and Security (MOIS, other key internal stakeholders, and foreign client organizations. A key focus of this analysis is the evolution of the relationship between the IRGC and the MOIS and the growing influence of the IRGC in Iran’s intelligence community over the last decade. The paper concludes that the IRGC has now eclipsed the MOIS within Iran’s intelligence community and is one of the most powerful institutions in Iranian politics today, using its intelligence activities as its key means of maintaining power and influence within the country.

Recovery Act. Advanced Load Identification and Management for Buildings

Energy Technology Data Exchange (ETDEWEB)

Yang, Yi [Eaton Corporation, Menomonee Falls, WI (United States); Casey, Patrick [Eaton Corporation, Menomonee Falls, WI (United States); Du, Liang [Eaton Corporation, Menomonee Falls, WI (United States); He, Dawei [Eaton Corporation, Menomonee Falls, WI (United States)

2014-02-12

In response to the U.S. Department of Energy (DoE)’s goal of achieving market ready, net-zero energy residential and commercial buildings by 2020 and 2025, Eaton partnered with the Department of Energy’s National Renewable Energy Laboratory (NREL) and Georgia Institute of Technology to develop an intelligent load identification and management technology enabled by a novel “smart power strip” to provide critical intelligence and information to improve the capability and functionality of building load analysis and building power management systems. Buildings account for 41% of the energy consumption in the United States, significantly more than either transportation or industrial. Within the building sector, plug loads account for a significant portion of energy consumption. Plug load consumes 15-20% of building energy on average. As building managers implement aggressive energy conservation measures, the proportion of plug load energy can increase to as much as 50% of building energy leaving plug loads as the largest remaining single source of energy consumption. This project focused on addressing plug-in load control and management to further improve building energy efficiency accomplished through effective load identification. The execution of the project falls into the following three major aspects; An intelligent load modeling, identification and prediction technology was developed to automatically determine the type, energy consumption, power quality, operation status and performance status of plug-in loads, using electric waveforms at a power outlet level. This project demonstrated the effectiveness of the developed technology through a large set of plug-in loads measurements and testing; A novel “Smart Power Strip (SPS) / Receptacle” prototype was developed to act as a vehicle to demonstrate the feasibility of load identification technology as a low-cost, embedded solution; and Market environment for plug-in load control and management solutions

77 FR 32952 - Defense Intelligence Agency National Intelligence University Board of Visitors Closed Meeting

Science.gov (United States)

2012-06-04

... DEPARTMENT OF DEFENSE Office of the Secretary Defense Intelligence Agency National Intelligence University Board of Visitors Closed Meeting AGENCY: Department of Defense, Defense Intelligence Agency, National Intelligence University. ACTION: Notice of closed meeting. SUMMARY: Pursuant to the provisions of...

Intelligent playgrounds

DEFF Research Database (Denmark)

Larsen, Lasse Juel

2009-01-01

This paper examines play, gaming and learning in regard to intelligent playware developed for outdoor use. The key questions are how does these novel artefacts influence the concept of play, gaming and learning. Up until now play and game have been understood as different activities. This paper...... examines if the sharp differentiation between the two can be uphold in regard to intelligent playware for outdoor use. Play and game activities will be analysed and viewed in conjunction with learning contexts. This paper will stipulate that intelligent playware facilitates rapid shifts in contexts...

Artificial intelligence

CERN Document Server

Ennals, J R

1987-01-01

Artificial Intelligence: State of the Art Report is a two-part report consisting of the invited papers and the analysis. The editor first gives an introduction to the invited papers before presenting each paper and the analysis, and then concludes with the list of references related to the study. The invited papers explore the various aspects of artificial intelligence. The analysis part assesses the major advances in artificial intelligence and provides a balanced analysis of the state of the art in this field. The Bibliography compiles the most important published material on the subject of

Applications Of Artificial Intelligence In Control System Analysis And Design

Science.gov (United States)

Birdwell, J. D.

1987-10-01

To date, applications of artificial intelligence in control system analysis and design are primarily associated with the design process. These applications take the form of knowledge bases incorporating expertise on a design method, such as multivariable linear controller design, or on a field such as identification. My experience has demonstrated that, while such expert systems are useful, perhaps a greater benefit will come from applications in the maintenance of technical databases, as are found in real-time data acquisition systems, and of modeling and design databases, which represent the status of a computer-aided design process for a human user. This reflects the observation that computers are best at maintaining relations about large sets of objects, whereas humans are best at maintaining knowledge of depth, as occurs when a design option involving a sequence of steps is explored. This paper will discuss some of these issues, and will provide some examples which illustrate the potential of artificial intelligence.

Intelligent control and maintenance of management integrated system based on multi-agents for coal preparation plant

Energy Technology Data Exchange (ETDEWEB)

Meng, F.; Wang, Y. [China University of Mining and technology, Xuzhou (China). School of Information and Electrical Engineering

2006-06-15

This paper discusses the progress of computer integrated processing (CIPS) of coal preparation and then presents an intelligence controlled production process, device-maintenance and production-management system of coal preparation based on multi-agents (IICMMS-CP). The construction of the IICMMS-CP, the distributed network control system based on live intelligence control stations and the strategy of implementing a distributed intelligence control system are studied in order to overcome the disadvantages brought about by the wide use of the PLC system by coal preparation plants. The software frame, based on a Multi-Agent Intelligence Control and Maintenance Management integrated system, is studied and the implementation methods of IICMMS-CP are discussed. The characteristics of distributed architecture, cooperation and parallel computing meet the needs of integrated control of coal preparation plants with large-scale spatial production distribution, densely-related processes and complex systems. Its application further improves the reliability and precision of process control, accuracy of fault identification and intelligence of production adjustment, establishes a technical basis for system integration and flexible production. The main function of the system has been tested in a coal preparation plant to good effect in stabilizing product quality, improving efficiency and reducing consumption. 17 refs., 4 figs.

Toward Intelligent Hemodynamic Monitoring: A Functional Approach

Directory of Open Access Journals (Sweden)

Pierre Squara

2012-01-01

Full Text Available Technology is now available to allow a complete haemodynamic analysis; however this is only used in a small proportion of patients and seems to occur when the medical staff have the time and inclination. As a result of this, significant delays occur between an event, its diagnosis and therefore, any treatment required. We can speculate that we should be able to collect enough real time information to make a complete, real time, haemodynamic diagnosis in all critically ill patients. This article advocates for “intelligent haemodynamic monitoring”. Following the steps of a functional analysis, we answered six basic questions. (1 What is the actual best theoretical model for describing haemodynamic disorders? (2 What are the needed and necessary input/output data for describing this model? (3 What are the specific quality criteria and tolerances for collecting each input variable? (4 Based on these criteria, what are the validated available technologies for monitoring each input variable, continuously, real time, and if possible non-invasively? (5 How can we integrate all the needed reliably monitored input variables into the same system for continuously describing the global haemodynamic model? (6 Is it possible to implement this global model into intelligent programs that are able to differentiate clinically relevant changes as opposed to artificial changes and to display intelligent messages and/or diagnoses?

Advanced intelligence and mechanism approach

Institute of Scientific and Technical Information of China (English)

ZHONG Yixin

2007-01-01

Advanced intelligence will feature the intelligence research in next 50 years.An understanding of the concept of advanced intelligence as well as its importance will be provided first,and detailed analysis on an approach,the mechanism approach.suitable to the advanced intelligence research will then be flolowed.And the mutual relationship among mechanism approach,traditional approaches existed in artificial intelligence research,and the cognitive informatics will be discussed.It is interesting to discover that mechanism approach is a good one to the Advanced Intelligence research and a tmified form of the existed approaches to artificial intelligence.

Development of INSTEC(INformation System of Trip Event Cases)

International Nuclear Information System (INIS)

Lee, Jeong Woon; Shim, Bong Sik; Park, Keun Oak; Cheon, Se Woo

1996-09-01

In this research, we established an incident analysis procedure based on the concept of interaction between plant components and developed INSTEC(INformation System of Trip Event Cases) which can manage data obtained as the result of incident analysis. The analysis procedure is consisted of the following steps; reconfiguration of incident context, identification of the paths and contents of the interaction between plant components, identification of unit event obstructing normal plant operation, identification of possible erroneous actions, decision of error modes, identification of likely causes, summarization of analysis results. INSTEC was developed to effectively present the result of incident analysis. This system offers the analyzed information such as analysis results of human error cases, operating issues and problems, recommendations to prevent a similar incident, etc. 24 tabs., 18 figs., 10 refs. (Author)

Computational Intelligence in Intelligent Data Analysis

CERN Document Server

Nürnberger, Andreas

2013-01-01

Complex systems and their phenomena are ubiquitous as they can be found in biology, finance, the humanities, management sciences, medicine, physics and similar fields. For many problems in these fields, there are no conventional ways to mathematically or analytically solve them completely at low cost. On the other hand, nature already solved many optimization problems efficiently. Computational intelligence attempts to mimic nature-inspired problem-solving strategies and methods. These strategies can be used to study, model and analyze complex systems such that it becomes feasible to handle them. Key areas of computational intelligence are artificial neural networks, evolutionary computation and fuzzy systems. As only a few researchers in that field, Rudolf Kruse has contributed in many important ways to the understanding, modeling and application of computational intelligence methods. On occasion of his 60th birthday, a collection of original papers of leading researchers in the field of computational intell...

Before and Beyond Anticipatory Intelligence: Assessing the Potential for Crowdsourcing and Intelligence Studies

Directory of Open Access Journals (Sweden)

Alexander Halman

2015-10-01

Full Text Available Crowdsourcing is a new tool for businesses, academics, and now intelligence analysts. Enabled by recent technology, crowdsourcing allows researchers to harness the wisdom of crowds and provide recommendations and insight into complex problems. This paper examines the potential benefits and limitations of crowdsourcing for intelligence analysis and the intelligence community beyond its primary use: anticipatory intelligence. The author constructs a model and compares it to existing crowdsourcing theories in business, information science, and public policy. Finally, he offers advice for intelligence analysis and public policy.

Artificial intelligence-based modeling and control of fluidized bed combustion

Energy Technology Data Exchange (ETDEWEB)

Ikonen, E.; Leppaekoski, K. (Univ. of Oulu, Dept. of Process and Environmental Engineering (Finland)). email: enso.ikonen@oulu.fi

2009-07-01

AI-inspired techniques have a lot to offer when developing methods for advanced identification, monitoring, control and optimization of industrial processes, such as power plants. Advanced control methods have been extensively examined in the research of the Power Plant Automation group at the Systems Engineering Laboratory, e.g., in fuel inventory modelling, combustion power control, modelling and control of flue gas oxygen, drum control, modelling and control of superheaters, or in optimization of flue-gas emissions. Most engineering approaches to artificial intelligence (AI) are characterized by two fundamental properties: the ability to learn from various sources and the ability to deal with plant complexity. Learning systems that are able to operate in uncertain environments based on incomplete information are commonly referred to as being intelligent. A number of other approaches exist, characterized by these properties, but not easily categorized as AI-systems. Advanced control methods (adaptive, predictive, multivariable, robust, etc.) are based on the availability of a model of the process to be controlled. Hence identification of processes becomes a key issue, leading to the use of adaptation and learning techniques. A typical learning control system concerns a selection of learning techniques applied for updating a process model, which in turn is used for the controller design. When design of learning control systems is complemented with concerns for dealing with uncertainties or vaguenesses in models, measurements, or even objectives, particularly close connections exist between advanced process control and methods of artificial intelligence and machine learning. Needs for advanced techniques are typically characterized by the desire to properly handle plant non-linearities, the multivariable nature of the dynamic problems, and the necessity to adapt to changing plant conditions. In the field of fluidized bed combustion (FBC) control, the many promising

The 21st annual intelligent ground vehicle competition: robotists for the future

Science.gov (United States)

Theisen, Bernard L.

2013-12-01

The Intelligent Ground Vehicle Competition (IGVC) is one of four, unmanned systems, student competitions that were founded by the Association for Unmanned Vehicle Systems International (AUVSI). The IGVC is a multidisciplinary exercise in product realization that challenges college engineering student teams to integrate advanced control theory, machine vision, vehicular electronics and mobile platform fundamentals to design and build an unmanned system. Teams from around the world focus on developing a suite of dual-use technologies to equip ground vehicles of the future with intelligent driving capabilities. Over the past 21 years, the competition has challenged undergraduate, graduate and Ph.D. students with real world applications in intelligent transportation systems, the military and manufacturing automation. To date, teams from over 80 universities and colleges have participated. This paper describes some of the applications of the technologies required by this competition and discusses the educational benefits. The primary goal of the IGVC is to advance engineering education in intelligent vehicles and related technologies. The employment and professional networking opportunities created for students and industrial sponsors through a series of technical events over the fourday competition are highlighted. Finally, an assessment of the competition based on participation is presented.

2015 Chinese Intelligent Systems Conference

CERN Document Server

Du, Junping; Li, Hongbo; Zhang, Weicun; CISC’15

2016-01-01

This book presents selected research papers from the 2015 Chinese Intelligent Systems Conference (CISC’15), held in Yangzhou, China. The topics covered include multi-agent systems, evolutionary computation, artificial intelligence, complex systems, computation intelligence and soft computing, intelligent control, advanced control technology, robotics and applications, intelligent information processing, iterative learning control, and machine learning. Engineers and researchers from academia, industry and the government can gain valuable insights into solutions combining ideas from multiple disciplines in the field of intelligent systems.

Intelligence and the machinery of government: conceptualizing the intelligence community

OpenAIRE

Davies, PHJ

2010-01-01

This article argues that the failure to address intelligence agencies as public organizations part and parcel with the overt machinery of government constitutes a significant lacuna both in the specialist study of intelligence and the broader discipline of public administration studies. The role and status of intelligence institutions as aspects of the machinery of central government is examined, along with the prospects of certain key paradigms in the field for understanding those institutio...

Flood AI: An Intelligent Systems for Discovery and Communication of Disaster Knowledge

Science.gov (United States)

Demir, I.; Sermet, M. Y.

2017-12-01

Communities are not immune from extreme events or natural disasters that can lead to large-scale consequences for the nation and public. Improving resilience to better prepare, plan, recover, and adapt to disasters is critical to reduce the impacts of extreme events. The National Research Council (NRC) report discusses the topic of how to increase resilience to extreme events through a vision of resilient nation in the year 2030. The report highlights the importance of data, information, gaps and knowledge challenges that needs to be addressed, and suggests every individual to access the risk and vulnerability information to make their communities more resilient. This project presents an intelligent system, Flood AI, for flooding to improve societal preparedness by providing a knowledge engine using voice recognition, artificial intelligence, and natural language processing based on a generalized ontology for disasters with a primary focus on flooding. The knowledge engine utilizes the flood ontology and concepts to connect user input to relevant knowledge discovery channels on flooding by developing a data acquisition and processing framework utilizing environmental observations, forecast models, and knowledge bases. Communication channels of the framework includes web-based systems, agent-based chat bots, smartphone applications, automated web workflows, and smart home devices, opening the knowledge discovery for flooding to many unique use cases.

Appearance-Based Multimodal Human Tracking and Identification for Healthcare in the Digital Home

Directory of Open Access Journals (Sweden)

Mau-Tsuen Yang

2014-08-01

Full Text Available There is an urgent need for intelligent home surveillance systems to provide home security, monitor health conditions, and detect emergencies of family members. One of the fundamental problems to realize the power of these intelligent services is how to detect, track, and identify people at home. Compared to RFID tags that need to be worn all the time, vision-based sensors provide a natural and nonintrusive solution. Observing that body appearance and body build, as well as face, provide valuable cues for human identification, we model and record multi-view faces, full-body colors and shapes of family members in an appearance database by using two Kinects located at a home’s entrance. Then the Kinects and another set of color cameras installed in other parts of the house are used to detect, track, and identify people by matching the captured color images with the registered templates in the appearance database. People are detected and tracked by multisensor fusion (Kinects and color cameras using a Kalman filter that can handle duplicate or partial measurements. People are identified by multimodal fusion (face, body appearance, and silhouette using a track-based majority voting. Moreover, the appearance-based human detection, tracking, and identification modules can cooperate seamlessly and benefit from each other. Experimental results show the effectiveness of the human tracking across multiple sensors and human identification considering the information of multi-view faces, full-body clothes, and silhouettes. The proposed home surveillance system can be applied to domestic applications in digital home security and intelligent healthcare.

Secular gains in fluid intelligence: evidence from the Culture-Fair intelligence test.

Science.gov (United States)

Colom, Roberto; García-López, Oscar

2003-01-01

There is no doubt about the reality of the secular increase in cognitive test scores. However, there is disagreement about a key issue: does the observed increase reflect a genuine upward trend in intelligence? Evidence from the Raven test is clear, although there are some doubts about its adequacy as a fine-grained measure of fluid intelligence. Evidence from the so-called 'method of correlated vectors' is much less clear. When a crystallized battery is considered, the results leave little doubt: the increase does not reflect gains in general intelligence. However, when a fluid battery is analysed, the increase does reflect gains in general intelligence. The present study uses one of the best available measures of fluid intelligence (the Culture-Fair intelligence test) to provide new evidence for the secular increase in fluid intelligence, beyond the findings from the Raven test and the method of correlated vectors. A total of 4498 Spanish high school students and high school graduates were tested within a time interval of 20 and 23 years, respectively. The results show that there is a clear upward trend in intelligence. Moreover, students show an average increase equivalent to 6 IQ points, while graduates show an average increase of 4 IQ points. Therefore, more selected people (graduates) show a smaller increase than less selected people (students). Some implications are discussed.

Scholastic Success: Fluid Intelligence, Personality, and Emotional Intelligence

Science.gov (United States)

Downey, Luke A.; Lomas, Justine; Billings, Clare; Hansen, Karen; Stough, Con

2014-01-01

The aim of the current study was to examine the role of fluid intelligence, personality traits, and emotional intelligence (EI) in predicting female Year 9 students' grade point average (GPA) and to determine whether any differences in scholastic performance were related to differences in EI or Personality. Two-hundred and forty-three female…

Perceived emotional intelligence, general intelligence and early professional success: predictive and incremental validity

Directory of Open Access Journals (Sweden)

José-Manuel de Haro

2014-05-01

Full Text Available Although the study of factors affecting career success has shown connections between biographical and other aspects related to ability, knowledge and personality, few studies have examined the relationship between emotional intelligence and professional success at the initial career stage. When these studies were carried out, the results showed significant relationships between the dimensions of emotional intelligence (emotional self-awareness, self-regulation, social awareness or social skills and the level of professional competence. In this paper, we analyze the relationship between perceived emotional intelligence, measured by the Trait Meta-Mood Scale (TMMS-24 questionnaire, general intelligence assessed by the Cattell factor "g" test, scale 3, and extrinsic indicators of career success, in a sample of 130 graduates at the beginning of their careers. Results from hierarchical regression analysis indicate that emotional intelligence makes a specific contribution to the prediction of salary, after controlling the general intelligence effect. The perceived emotional intelligence dimensions of TMMS repair, TMMS attention and sex show a higher correlation and make a greater contribution to professional success than general intelligence. The implications of these results for the development of socio-emotional skills among University graduates are discussed.

Domestic Intelligence in the United Kingdom: Applicability of the MI-5 Model to the United States

National Research Council Canada - National Science Library

Masse, Todd

2003-01-01

.... One potential remedy that has been suggested in response to the events of September 11, 2001 is the establishment of a domestic intelligence agency akin to the British Security Service, also known as MI5...

Complementary Machine Intelligence and Human Intelligence in Virtual Teaching Assistant for Tutoring Program Tracing

Science.gov (United States)

Chou, Chih-Yueh; Huang, Bau-Hung; Lin, Chi-Jen

2011-01-01

This study proposes a virtual teaching assistant (VTA) to share teacher tutoring tasks in helping students practice program tracing and proposes two mechanisms of complementing machine intelligence and human intelligence to develop the VTA. The first mechanism applies machine intelligence to extend human intelligence (teacher answers) to evaluate…

Artificial intelligence model for sustain ability measurement

International Nuclear Information System (INIS)

Navickiene, R.; Navickas, K.

2012-01-01

The article analyses the main dimensions of organizational sustain ability, their possible integrations into artificial neural network. In this article authors performing analyses of organizational internal and external environments, their possible correlations with 4 components of sustain ability, and the principal determination models for sustain ability of organizations. Based on the general principles of sustainable development organizations, a artificial intelligence model for the determination of organizational sustain ability has been developed. The use of self-organizing neural networks allows the identification of the organizational sustain ability and the endeavour to explore vital, social, antropogenical and economical efficiency. The determination of the forest enterprise sustain ability is expected to help better manage the sustain ability. (Authors)

A Belief-Space Approach to Integrated Intelligence - Research Area 10.3: Intelligent Networks

Science.gov (United States)

2017-12-05

A Belief-Space Approach to Integrated Intelligence- Research Area 10.3: Intelligent Networks The views, opinions and/or findings contained in this...Technology (MIT) Title: A Belief-Space Approach to Integrated Intelligence- Research Area 10.3: Intelligent Networks Report Term: 0-Other Email: tlp...students presented progress and received feedback from the research group . o wrote papers on their research and submitted them to leading conferences

Artificial Intelligence

CERN Document Server

Warwick, Kevin

2011-01-01

if AI is outside your field, or you know something of the subject and would like to know more then Artificial Intelligence: The Basics is a brilliant primer.' - Nick Smith, Engineering and Technology Magazine November 2011 Artificial Intelligence: The Basics is a concise and cutting-edge introduction to the fast moving world of AI. The author Kevin Warwick, a pioneer in the field, examines issues of what it means to be man or machine and looks at advances in robotics which have blurred the boundaries. Topics covered include: how intelligence can be defined whether machines can 'think' sensory

Bayesian exploration for intelligent identification of textures

Directory of Open Access Journals (Sweden)

Jeremy A. Fishel

2012-06-01

Full Text Available In order to endow robots with humanlike abilities to characterize and identify objects, they must be provided with tactile sensors and intelligent algorithms to select, control and interpret data from useful exploratory movements. Humans make informed decisions on the sequence of exploratory movements that would yield the most information for the task, depending on what the object may be and prior knowledge of what to expect from possible exploratory movements. This study is focused on texture discrimination, a subset of a much larger group of exploratory movements and percepts that humans use to discriminate, characterize, and identify objects. Using a testbed equipped with a biologically inspired tactile sensor (the BioTac® we produced sliding movements similar to those that humans make when exploring textures. Measurement of tactile vibrations and reaction forces when exploring textures were used to extract measures of textural properties inspired from psychophysical literature (traction, roughness, and fineness. Different combinations of normal force and velocity were identified to be useful for each of these three properties. A total of 117 textures were explored with these three movements to create a database of prior experience to use for identifying these same textures in future encounters. When exploring a texture, the discrimination algorithm adaptively selects the optimal movement to make and property to measure based on previous experience to differentiate the texture from a set of plausible candidates, a process we call Bayesian exploration. Performance of 99.6% in correctly discriminating pairs of similar textures was found to exceed human capabilities. Absolute classification from the entire set of 117 textures generally required a small number of well-chosen exploratory movements (median=5 and yielded a 95.4% success rate. The method of Bayesian exploration developed and tested in this paper may generalize well to other

Intelligence of programs

Energy Technology Data Exchange (ETDEWEB)

Novak, D

1982-01-01

A general discussion about the level of artificial intelligence in computer programs is presented. The suitability of various languages for the development of complex, intelligent programs is discussed, considering fourth-generation language as well as the well established structured COBOL language. It is concluded that the success of automation in many administrative fields depends to a large extent on the development of intelligent programs.

Relationships between the Kaufman Brief Intelligence Test and the Wechsler Adult Intelligence Scale-Third Edition.

Science.gov (United States)

Walters, Steven O; Weaver, Kenneth A

2003-06-01

The Kaufman Brief Intelligence Test detects learning problems of young students and is a screen for whether a more comprehensive test of intelligence is needed. A study to assess whether this test was valid as an adult intelligence test was conducted with 20 undergraduate psychology majors. The correlations between the Kaufman Brief Intelligence Test's Composite, Vocabulary, and Matrices test scores and their corresponding Wechsler Adult Intelligence Scale-Third Edition test scores, the Full Scale (r=.88), Verbal (r=.77), and Performance scores (r=.87), indicated very strong relationships. In addition, no significant differences were obtained between the Composite, Vocabulary, and Matrices means of the Kaufman Brief Intelligence Test and the Full Scale, Verbal, and Performance means of the WAIS-III. The Kaufman Brief Intelligence Test appears to be a valid test of intelligence for adults.

A novel approach for intelligent distribution of data warehouses

Directory of Open Access Journals (Sweden)

Abhay Kumar Agarwal

2016-07-01

Full Text Available With the continuous growth in the amount of data, data storage systems have come a long way from flat files systems to RDBMS, Data Warehousing (DW and Distributed Data Warehousing systems. This paper proposes a new distributed data warehouse model. The model is built on a novel approach, for the intelligent distribution of data warehouse. Overall the model is named as Intelligent and Distributed Data Warehouse (IDDW. The proposed model has N-levels and is based on top-down hierarchical design approach of building distributed data warehouse. The building process of IDDW starts with the identification of various locations where DW may be built. Initially, a single location is considered at top-most level of IDDW where DW is built. Thereafter, DW at any other location of any level may be built. A method, to transfer concerned data from any upper level DW to concerned lower level DW, is also presented in the paper. The paper also presents IDDW modeling, its architecture based on modeling, the internal organization of IDDW via which all the operations within IDDW are performed.

Fluid intelligence: A brief history.

Science.gov (United States)

Kent, Phillip

2017-01-01

The concept of fluid and crystallized intelligence was introduced to the psychological community approximately 75 years ago by Raymond B. Cattell, and it continues to be an area of active research and controversy. The purpose of this paper is to provide a brief overview of the origin of the concept, early efforts to define intelligence and uses of intelligence tests to address pressing social issues, and the ongoing controversies associated with fluid intelligence and the structure of intelligence. The putative neuropsychological underpinnings and neurological substrates of fluid intelligence are discussed.

Educational Programs for Intelligence Professionals.

Science.gov (United States)

Miller, Jerry P.

1994-01-01

Discusses the need for education programs for competitive intelligence professionals. Highlights include definitions of intelligence functions, focusing on business intelligence; information utilization by decision makers; information sources; competencies for intelligence professionals; and the development of formal education programs. (38…

From IHE Audit Trails to XES Event Logs Facilitating Process Mining.

Science.gov (United States)

Paster, Ferdinand; Helm, Emmanuel

2015-01-01

Recently Business Intelligence approaches like process mining are applied to the healthcare domain. The goal of process mining is to gain process knowledge, compliance and room for improvement by investigating recorded event data. Previous approaches focused on process discovery by event data from various specific systems. IHE, as a globally recognized basis for healthcare information systems, defines in its ATNA profile how real-world events must be recorded in centralized event logs. The following approach presents how audit trails collected by the means of ATNA can be transformed to enable process mining. Using the standardized audit trails provides the ability to apply these methods to all IHE based information systems.

Harmonizing intelligence terminologies in business: Literature review

Directory of Open Access Journals (Sweden)

Sivave Mashingaidze

2014-11-01

Full Text Available The principal objective of this article is to do a literature review of different intelligence terminology with the aim of establishing the common attributes and differences, and to propose a universal and comprehensive definition of intelligence for common understanding amongst users. The findings showed that Competitive Intelligence has the broadest scope of intelligence activities covering the whole external operating environment of the company and targeting all levels of decision-making for instance; strategic intelligence, tactical intelligence and operative intelligence. Another terminology was found called Cyber IntelligenceTM which encompasses competitor intelligence, strategic intelligence, market intelligence and counterintelligence. In conclusion although CI has the broadest scope of intelligence and umbrella to many intelligence concepts, still Business Intelligence, and Corporate Intelligence are often used interchangeably as CI

Business Intelligence using Software Agents

OpenAIRE

Ana-Ramona BOLOGA; Razvan BOLOGA

2011-01-01

This paper presents some ideas about business intelligence today and the importance of developing real time business solutions. The authors make an exploration of links between business intelligence and artificial intelligence and focuses specifically on the implementation of software agents-based systems in business intelligence. There are briefly presented some of the few solutions proposed so far that use software agents properties for the benefit of business intelligence. The authors then...

78 FR 32241 - Defense Intelligence Agency National Intelligence University Board of Visitors; Notice of Closed...

Science.gov (United States)

2013-05-29

... DEPARTMENT OF DEFENSE Office of the Secretary Defense Intelligence Agency National Intelligence University Board of Visitors; Notice of Closed Meeting AGENCY: National Intelligence University, Defense Intelligence Agency, Department of Defense. ACTION: Notice of closed meeting. SUMMARY: Pursuant to the...

75 FR 76423 - Defense Intelligence Agency National Defense Intelligence College Board of Visitors Closed Meeting

Science.gov (United States)

2010-12-08

... DEPARTMENT OF DEFENSE Office of the Secretary Defense Intelligence Agency National Defense Intelligence College Board of Visitors Closed Meeting AGENCY: National Defense Intelligence College, Defense Intelligence Agency, Department of Defense. ACTION: Notice of Closed Meeting. SUMMARY: Pursuant to the...

76 FR 28960 - Defense Intelligence Agency National Defense Intelligence College Board of Visitors Closed Meeting

Science.gov (United States)

2011-05-19

... DEPARTMENT OF DEFENSE Office of the Secretary Defense Intelligence Agency National Defense Intelligence College Board of Visitors Closed Meeting AGENCY: National Defense Intelligence College, Defense Intelligence Agency, Department of Defense. ACTION: Notice of Closed Meeting. SUMMARY: Pursuant to the...

Open source intelligence, open social intelligence and privacy by design

OpenAIRE

Casanovas, Pompeu; Royal Melbourne Institute of Technology (Austràlia). Centre for Applied Social Research

2014-01-01

Ponència presentada a European Conference on Social Intelligence (ECSI-2014) OSINT stands for Open Source Intelligence, (O)SI for (Open) Social Intelligence, PbD for Privacy by Design. The CAPER project has built an OSINT solution oriented to the prevention of organized crime. How to balance freedom and security? This position paper describes a way to embed the legal and ethical issues raised by the General Data Reform Package (GDRP) in Europe into this kind of surveillance platforms. It f...

Beyond AI: Multi-Intelligence (MI) Combining Natural and Artificial Intelligences in Hybrid Beings and Systems

OpenAIRE

Stephen Fox

2017-01-01

Framing strongly influences actions among technology proponents and end-users. Underlying much debate about artificial intelligence (AI) are several fundamental shortcomings in its framing. First, discussion of AI is atheoretical, and therefore has limited potential for addressing the complexity of causation. Second, intelligence is considered from an anthropocentric perspective that sees human intelligence, and intelligence developed by humans, as superior to all other intelligences. Thus, t...

Artificial Intelligence.

Science.gov (United States)

Wash, Darrel Patrick

1989-01-01

Making a machine seem intelligent is not easy. As a consequence, demand has been rising for computer professionals skilled in artificial intelligence and is likely to continue to go up. These workers develop expert systems and solve the mysteries of machine vision, natural language processing, and neural networks. (Editor)

Deploying swarm intelligence in medical imaging identifying metastasis, micro-calcifications and brain image segmentation.

Science.gov (United States)

al-Rifaie, Mohammad Majid; Aber, Ahmed; Hemanth, Duraiswamy Jude

2015-12-01

This study proposes an umbrella deployment of swarm intelligence algorithm, such as stochastic diffusion search for medical imaging applications. After summarising the results of some previous works which shows how the algorithm assists in the identification of metastasis in bone scans and microcalcifications on mammographs, for the first time, the use of the algorithm in assessing the CT images of the aorta is demonstrated along with its performance in detecting the nasogastric tube in chest X-ray. The swarm intelligence algorithm presented in this study is adapted to address these particular tasks and its functionality is investigated by running the swarms on sample CT images and X-rays whose status have been determined by senior radiologists. In addition, a hybrid swarm intelligence-learning vector quantisation (LVQ) approach is proposed in the context of magnetic resonance (MR) brain image segmentation. The particle swarm optimisation is used to train the LVQ which eliminates the iteration-dependent nature of LVQ. The proposed methodology is used to detect the tumour regions in the abnormal MR brain images.

Estimation of the Intelligence Quotient Using Wechsler Intelligence Scales in Children and Adolescents with Asperger Syndrome

Science.gov (United States)

Merchan-Naranjo, Jessica; Mayoral, Maria; Rapado-Castro, Marta; Llorente, Cloe; Boada, Leticia; Arango, Celso; Parellada, Mara

2012-01-01

Asperger syndrome (AS) patients show heterogeneous intelligence profiles and the validity of short forms for estimating intelligence has rarely been studied in this population. We analyzed the validity of Wechsler Intelligence Scale (WIS) short forms for estimating full-scale intelligence quotient (FSIQ) and assessing intelligence profiles in 29…

Business Intelligence using Software Agents

Directory of Open Access Journals (Sweden)

Ana-Ramona BOLOGA

2011-12-01

Full Text Available This paper presents some ideas about business intelligence today and the importance of developing real time business solutions. The authors make an exploration of links between business intelligence and artificial intelligence and focuses specifically on the implementation of software agents-based systems in business intelligence. There are briefly presented some of the few solutions proposed so far that use software agents properties for the benefit of business intelligence. The authors then propose some basic ideas for developing real-time agent-based software system for business intelligence in supply chain management, using Case Base Reasoning Agents.

Intelligent model-based diagnostics for vehicle health management

Science.gov (United States)

Luo, Jianhui; Tu, Fang; Azam, Mohammad S.; Pattipati, Krishna R.; Willett, Peter K.; Qiao, Liu; Kawamoto, Masayuki

2003-08-01

The recent advances in sensor technology, remote communication and computational capabilities, and standardized hardware/software interfaces are creating a dramatic shift in the way the health of vehicles is monitored and managed. These advances facilitate remote monitoring, diagnosis and condition-based maintenance of automotive systems. With the increased sophistication of electronic control systems in vehicles, there is a concomitant increased difficulty in the identification of the malfunction phenomena. Consequently, the current rule-based diagnostic systems are difficult to develop, validate and maintain. New intelligent model-based diagnostic methodologies that exploit the advances in sensor, telecommunications, computing and software technologies are needed. In this paper, we will investigate hybrid model-based techniques that seamlessly employ quantitative (analytical) models and graph-based dependency models for intelligent diagnosis. Automotive engineers have found quantitative simulation (e.g. MATLAB/SIMULINK) to be a vital tool in the development of advanced control systems. The hybrid method exploits this capability to improve the diagnostic system's accuracy and consistency, utilizes existing validated knowledge on rule-based methods, enables remote diagnosis, and responds to the challenges of increased system complexity. The solution is generic and has the potential for application in a wide range of systems.

Generative Artificial Intelligence : Philosophy and Theory of Artificial Intelligence

NARCIS (Netherlands)

van der Zant, Tijn; Kouw, Matthijs; Schomaker, Lambertus; Mueller, Vincent C.

2013-01-01

The closed systems of contemporary Artificial Intelligence do not seem to lead to intelligent machines in the near future. What is needed are open-ended systems with non-linear properties in order to create interesting properties for the scaffolding of an artificial mind. Using post-structuralistic

International Conference on Grey Systems and intelligent Services (IEEE GSIS 2009)

CERN Document Server

Liu, Sifeng; Advances in Grey Systems Research

2010-01-01

This book contains contributions by some of the leading researchers in the area of grey systems theory and applications. All the papers included in this volume are selected from the contributions physically presented at the 2009 IEEE International Conference on Grey Systems and Intelligent Services, November 11 – 12, 2009, Nanjing, Jiangsu, People’s Republic of China. This event was jointly sponsored by IEEE Systems, Man, and Cybernetics Society, Natural Science Foundation of China, and Grey Systems Society of China. Additionally, Nanjing University of Aeronautics and Astronautics also invested heavily in this event with its direct and indirect financial and administrative supports.

A model-based approach to operational event groups ranking

Energy Technology Data Exchange (ETDEWEB)

Simic, Zdenko [European Commission Joint Research Centre, Petten (Netherlands). Inst. for Energy and Transport; Maqua, Michael [Gesellschaft fuer Anlagen- und Reaktorsicherheit mbH (GRS), Koeln (Germany); Wattrelos, Didier [Institut de Radioprotection et de Surete Nucleaire (IRSN), Fontenay-aux-Roses (France)

2014-04-15

The operational experience (OE) feedback provides improvements in all industrial activities. Identification of the most important and valuable groups of events within accumulated experience is important in order to focus on a detailed investigation of events. The paper describes the new ranking method and compares it with three others. Methods have been described and applied to OE events utilised by nuclear power plants in France and Germany for twenty years. The results show that different ranking methods only roughly agree on which of the event groups are the most important ones. In the new ranking method the analytical hierarchy process is applied in order to assure consistent and comprehensive weighting determination for ranking indexes. The proposed method allows a transparent and flexible event groups ranking and identification of the most important OE for further more detailed investigation in order to complete the feedback. (orig.)

Using artificial intelligence to predict prolonged mechanical ventilation and tracheostomy placement.

Science.gov (United States)

Parreco, Joshua; Hidalgo, Antonio; Parks, Jonathan J; Kozol, Robert; Rattan, Rishi

2018-08-01

Early identification of critically ill patients who will require prolonged mechanical ventilation (PMV) has proven to be difficult. The purpose of this study was to use machine learning to identify patients at risk for PMV and tracheostomy placement. The Multiparameter Intelligent Monitoring in Intensive Care III database was queried for all intensive care unit (ICU) stays with mechanical ventilation. PMV was defined as ventilation >7 d. Classifiers with a gradient-boosted decision trees algorithm were created for the outcomes of PMV and tracheostomy placement. The variables used were six different severity-of-illness scores calculated on the first day of ICU admission including their components and 30 comorbidities. Mean receiver operating characteristic curves were calculated for the outcomes, and variable importance was quantified. There were 20,262 ICU stays identified. PMV was required in 13.6%, and tracheostomy was performed in 6.6% of patients. The classifier for predicting PMV was able to achieve a mean area under the curve (AUC) of 0.820 ± 0.016, and tracheostomy was predicted with an AUC of 0.830 ± 0.011. There were 60.7% patients admitted to a surgical ICU, and the classifiers for these patients predicted PMV with an AUC of 0.852 ± 0.017 and tracheostomy with an AUC of 0.869 ± 0.015. The variable with the highest importance for predicting PMV was the logistic organ dysfunction score pulmonary component (13%), and the most important comorbidity in predicting tracheostomy was cardiac arrhythmia (12%). This study demonstrates the use of artificial intelligence through machine-learning classifiers for the early identification of patients at risk for PMV and tracheostomy. Application of these identification techniques could lead to improved outcomes by allowing for early intervention. Copyright © 2018 Elsevier Inc. All rights reserved.

Progress and Challenge of Artificial Intelligence

Institute of Scientific and Technical Information of China (English)

Zhong-Zhi Shi; Nan-Ning Zheng

2006-01-01

Artificial Intelligence (AI) is generally considered to be a subfield of computer science, that is concerned to attempt simulation, extension and expansion of human intelligence. Artificial intelligence has enjoyed tremendous success over the last fifty years. In this paper we only focus on visual perception, granular computing, agent computing, semantic grid. Human-level intelligence is the long-term goal of artificial intelligence. We should do joint research on basic theory and technology of intelligence by brain science, cognitive science, artificial intelligence and others. A new cross discipline intelligence science is undergoing a rapid development. Future challenges are given in final section.

Extending Galactic Habitable Zone Modeling to Include the Emergence of Intelligent Life.

Science.gov (United States)

Morrison, Ian S; Gowanlock, Michael G

2015-08-01

Previous studies of the galactic habitable zone have been concerned with identifying those regions of the Galaxy that may favor the emergence of complex life. A planet is deemed habitable if it meets a set of assumed criteria for supporting the emergence of such complex life. In this work, we extend the assessment of habitability to consider the potential for life to further evolve to the point of intelligence--termed the propensity for the emergence of intelligent life, φI. We assume φI is strongly influenced by the time durations available for evolutionary processes to proceed undisturbed by the sterilizing effects of nearby supernovae. The times between supernova events provide windows of opportunity for the evolution of intelligence. We developed a model that allows us to analyze these window times to generate a metric for φI, and we examine here the spatial and temporal variation of this metric. Even under the assumption that long time durations are required between sterilizations to allow for the emergence of intelligence, our model suggests that the inner Galaxy provides the greatest number of opportunities for intelligence to arise. This is due to the substantially higher number density of habitable planets in this region, which outweighs the effects of a higher supernova rate in the region. Our model also shows that φI is increasing with time. Intelligent life emerged at approximately the present time at Earth's galactocentric radius, but a similar level of evolutionary opportunity was available in the inner Galaxy more than 2 Gyr ago. Our findings suggest that the inner Galaxy should logically be a prime target region for searches for extraterrestrial intelligence and that any civilizations that may have emerged there are potentially much older than our own.

Intelligence related differences in EEG-bandpower.

Science.gov (United States)

Doppelmayr, Michael; Klimesch, W; Sauseng, P; Hödlmoser, K; Stadler, W; Hanslmayr, S

2005-06-24

Several studies on the relationship between event-related desynchronization/synchronization (ERD/ERS) and cognitive performance revealed contradictory results particularly for the alpha band. Studies from our laboratory have shown that good performers show a larger upper alpha ERD (interpreted in terms of larger cortical activation) than bad performers. In contrast, other researchers found evidence for the neural efficiency hypothesis, which states that more intelligent subjects exhibit a smaller extent of cortical activation, which is assumed to be reflected by a smaller upper alpha ERD. Here we address the question whether these divergent results may be due to differences in general task difficulty. Using a modified version of the RAVEN, individually divided into easy and difficult tasks, a group of average and a group of highly intelligent subjects (IQ- and IQ+) have been investigated. While in the theta frequency IQ+ subjects generally exhibited a significantly stronger activation, we found a significant interaction of task difficulty and IQ group in the upper alpha band, indicating both, a weaker activation for the high IQ group during the easy tasks, and a significant increase from easy to difficult tasks for IQ+ only.

Intelligence and treaty ratification

International Nuclear Information System (INIS)

Sojka, G.L.

1990-01-01

What did the intelligence community and the Intelligence Committee di poorly in regard to the treaty ratification process for arms control? We failed to solve the compartmentalization problem/ This is a second-order problem, and, in general, analysts try to be very open; but there are problems nevertheless. There are very few, if any, people within the intelligence community who are cleared for everything relevant to our monitoring capability emdash short of probably the Director of Central Intelligence and the president emdash and this is a major problem. The formal monitoring estimates are drawn up by individuals who do not have access to all the information to make the monitoring judgements. This paper reports that the intelligence community did not present a formal document on either Soviet incentives of disincentives to cheat or on the possibility of cheating scenarios, and that was a mistake. However, the intelligence community was very responsive in producing those types of estimates, and, ultimately, the evidence behind them in response to questions. Nevertheless, the author thinks the intelligence community would do well to address this issue up front before a treaty is submitted to the Senate for advice and consent

Rural architecture between artificial intelligence and natural intelligence

Energy Technology Data Exchange (ETDEWEB)

Cennamo, M.; Palma, P. di; Ricciardelli, A. [University of Naples Frederico II (Italy). Dept. of Configurazione e Attuazione dell Architettra

2000-02-01

Following the field of research carried out and reported in the Second International Conference for Teachers of Architecture held in Florence on October 16, 17 and 18, 1997, which stated the central position of Architectural project in relation to Human Intelligence, Natural Intelligence and Artificial Intelligence, the present paper suggests a phase of application of the theoretical assumptions to spacial models paradigmatic of the complexity of projects and building technique, as well as of the relationship between man-made environment and natural one. Among the different typologies in architecture, this research focuses on the rural buildings in Campania, mainly on the ones in the Vesuvius area, as those are the most suitable to be studied and salvaged with the help of biology, mathematics and high engineering. (author)

Monitoring osseointegration and developing intelligent systems (Conference Presentation)

Science.gov (United States)

Salvino, Liming W.

2017-05-01

Effective monitoring of structural and biological systems is an extremely important research area that enables technology development for future intelligent devices, platforms, and systems. This presentation provides an overview of research efforts funded by the Office of Naval Research (ONR) to establish structural health monitoring (SHM) methodologies in the human domain. Basic science efforts are needed to utilize SHM sensing, data analysis, modeling, and algorithms to obtain the relevant physiological and biological information for human-specific health and performance conditions. This overview of current research efforts is based on the Monitoring Osseointegrated Prosthesis (MOIP) program. MOIP develops implantable and intelligent prosthetics that are directly anchored to the bone of residual limbs. Through real-time monitoring, sensing, and responding to osseointegration of bones and implants as well as interface conditions and environment, our research program aims to obtain individualized actionable information for implant failure identification, load estimation, infection mitigation and treatment, as well as healing assessment. Looking ahead to achieve ultimate goals of SHM, we seek to expand our research areas to cover monitoring human, biological and engineered systems, as well as human-machine interfaces. Examples of such include 1) brainwave monitoring and neurological control, 2) detecting and evaluating brain injuries, 3) monitoring and maximizing human-technological object teaming, and 4) closed-loop setups in which actions can be triggered automatically based on sensors, actuators, and data signatures. Finally, some ongoing and future collaborations across different disciplines for the development of knowledge automation and intelligent systems will be discussed.

Algorithms in ambient intelligence

NARCIS (Netherlands)

Aarts, E.H.L.; Korst, J.H.M.; Verhaegh, W.F.J.; Weber, W.; Rabaey, J.M.; Aarts, E.

2005-01-01

We briefly review the concept of ambient intelligence and discuss its relation with the domain of intelligent algorithms. By means of four examples of ambient intelligent systems, we argue that new computing methods and quantification measures are needed to bridge the gap between the class of

Artificial Intelligence Research at the Artificial Intelligence Laboratory, Massachusetts Institute of Technology

OpenAIRE

Winston, Patrick H.

1983-01-01

The primary goal of the Artificial Intelligence Laboratory is to understand how computers can be made to exhibit intelligence. Two corollary goals are to make computers more useful and to understand certain aspects of human intelligence. Current research includes work on computer robotics and vision, expert systems, learning and commonsense reasoning, natural language understanding, and computer architecture.

Use of the Hadoop structured storage tools for the ATLAS EventIndex event catalogue

CERN Document Server

Favareto, Andrea; The ATLAS collaboration; Cardenas Zarate, Simon Ernesto; Cranshaw, Jack; Fernandez Casani, Alvaro; Gallas, Elizabeth; Gonzalez de la Hoz, Santiago; Hrivnac, Julius; Malon, David; Prokoshin, Fedor; Salt, Jose; Sanchez, Javier; Toebbicke, Rainer; Yuan, Ruijun; Garcia Montoro, Carlos

2015-01-01

The ATLAS experiment collects billions of events per year of data-taking, and processes them to make them available for physics analysis in several different formats. An even larger amount of events is in addition simulated according to physics and detector models and then reconstructed and analysed to be compared to real events. The EventIndex is a catalogue of all events in each production stage; it includes for each event a few identification parameters, some basic non-mutable information coming from the online system, and the references to the files that contain the event in each format (plus the internal pointers to the event within each file for quick retrieval). Each EventIndex record is logically simple but the system has to hold many tens of billions of records, all equally important. The Hadoop technology was selected at the start of the EventIndex project development in 2012 and proved to be robust and flexible to accommodate this kind of information; both the insertion times and query response tim...

Moral Intelligence in the Schools

Science.gov (United States)

Clarken, Rodney H.

2009-01-01

Moral intelligence is newer and less studied than the more established cognitive, emotional and social intelligences, but has great potential to improve our understanding of learning and behavior. Moral intelligence refers to the ability to apply ethical principles to personal goals, values and actions. The construct of moral intelligence consists…

Modelling intelligent behavior

Science.gov (United States)

Green, H. S.; Triffet, T.

1993-01-01

An introductory discussion of the related concepts of intelligence and consciousness suggests criteria to be met in the modeling of intelligence and the development of intelligent materials. Methods for the modeling of actual structure and activity of the animal cortex have been found, based on present knowledge of the ionic and cellular constitution of the nervous system. These have led to the development of a realistic neural network model, which has been used to study the formation of memory and the process of learning. An account is given of experiments with simple materials which exhibit almost all properties of biological synapses and suggest the possibility of a new type of computer architecture to implement an advanced type of artificial intelligence.

Multiple intelligences: Can they be measured?

OpenAIRE

Kirsi Tirri; Petri Nokelainen; Erkki Komulainen

2013-01-01

This paper is about issues relating to the assessment of multiple intelligences. The first section introduces the authors’ work on building measures of multiple intelligences and moral sensitivities. It also provides a conceptual definition of multiple intelligences based on Multiple Intelligences theory by Howard Gardner (1983). The second section discusses the context specificity of intelligences and alternative approaches to measuring multiple intelligences. The third section analyses the ...

The 20th annual intelligent ground vehicle competition: building a generation of robotists

Science.gov (United States)

Theisen, Bernard L.; Kosinski, Andrew

2013-01-01

The Intelligent Ground Vehicle Competition (IGVC) is one of four, unmanned systems, student competitions that were founded by the Association for Unmanned Vehicle Systems International (AUVSI). The IGVC is a multidisciplinary exercise in product realization that challenges college engineering student teams to integrate advanced control theory, machine vision, vehicular electronics and mobile platform fundamentals to design and build an unmanned system. Teams from around the world focus on developing a suite of dual-use technologies to equip ground vehicles of the future with intelligent driving capabilities. Over the past 20 years, the competition has challenged undergraduate, graduate and Ph.D. students with real world applications in intelligent transportation systems, the military and manufacturing automation. To date, teams from over 80 universities and colleges have participated. This paper describes some of the applications of the technologies required by this competition and discusses the educational benefits. The primary goal of the IGVC is to advance engineering education in intelligent vehicles and related technologies. The employment and professional networking opportunities created for students and industrial sponsors through a series of technical events over the four-day competition are highlighted. Finally, an assessment of the competition based on participation is presented.

[Emotional intelligence and oscillatory responses on the emotional facial expressions].

Science.gov (United States)

Kniazev, G G; Mitrofanova, L G; Bocharov, A V

2013-01-01

Emotional intelligence-related differences in oscillatory responses to emotional facial expressions were investigated in 48 subjects (26 men and 22 women) in age 18-30 years. Participants were instructed to evaluate emotional expression (angry, happy and neutral) of each presented face on an analog scale ranging from -100 (very hostile) to + 100 (very friendly). High emotional intelligence (EI) participants were found to be more sensitive to the emotional content of the stimuli. It showed up both in their subjective evaluation of the stimuli and in a stronger EEG theta synchronization at an earlier (between 100 and 500 ms after face presentation) processing stage. Source localization using sLORETA showed that this effect was localized in the fusiform gyrus upon the presentation of angry faces and in the posterior cingulate gyrus upon the presentation of happy faces. At a later processing stage (500-870 ms) event-related theta synchronization in high emotional intelligence subject was higher in the left prefrontal cortex upon the presentation of happy faces, but it was lower in the anterior cingulate cortex upon presentation of angry faces. This suggests the existence of a mechanism that can be selectively increase the positive emotions and reduce negative emotions.

Semantics-based information extraction for detecting economic events

NARCIS (Netherlands)

A.C. Hogenboom (Alexander); F. Frasincar (Flavius); K. Schouten (Kim); O. van der Meer

2013-01-01

textabstractAs today's financial markets are sensitive to breaking news on economic events, accurate and timely automatic identification of events in news items is crucial. Unstructured news items originating from many heterogeneous sources have to be mined in order to extract knowledge useful for

Reflection on robotic intelligence

NARCIS (Netherlands)

Bartneck, C.

2006-01-01

This paper reflects on the development or robots, both their physical shape as well as their intelligence. The later strongly depends on the progress made in the artificial intelligence (AI) community which does not yet provide the models and tools necessary to create intelligent robots. It is time

Technologies for developing an advanced intelligent ATM with self-defence capabilities

Science.gov (United States)

Sako, Hiroshi

2010-01-01

We have developed several technologies for protecting automated teller machines. These technologies are based mainly on pattern recognition and are used to implement various self-defence functions. They include (i) banknote recognition and information retrieval for preventing machines from accepting counterfeit and damaged banknotes and for retrieving information about detected counterfeits from a relational database, (ii) form processing and character recognition for preventing machines from accepting remittance forms without due dates and/or insufficient payment, (iii) person identification to prevent machines from transacting with non-customers, and (iv) object recognition to guard machines against foreign objects such as spy cams that might be surreptitiously attached to them and to protect users against someone attempting to peek at their user information such as their personal identification number. The person identification technology has been implemented in most ATMs in Japan, and field tests have demonstrated that the banknote recognition technology can recognise more then 200 types of banknote from 30 different countries. We are developing an "advanced intelligent ATM" that incorporates all of these technologies.

Multiple Intelligences and quotient spaces

OpenAIRE

Malatesta, Mike; Quintana, Yamilet

2006-01-01

The Multiple Intelligence Theory (MI) is one of the models that study and describe the cognitive abilities of an individual. In [7] is presented a referential system which allows to identify the Multiple Intelligences of the students of a course and to classify the level of development of such Intelligences. Following this tendency, the purpose of this paper is to describe the model of Multiple Intelligences as a quotient space, and also to study the Multiple Intelligences of an individual in...

Design for interaction between humans and intelligent systems during real-time fault management

Science.gov (United States)

Malin, Jane T.; Schreckenghost, Debra L.; Thronesbery, Carroll G.

1992-01-01

Initial results are reported to provide guidance and assistance for designers of intelligent systems and their human interfaces. The objective is to achieve more effective human-computer interaction (HCI) for real time fault management support systems. Studies of the development of intelligent fault management systems within NASA have resulted in a new perspective of the user. If the user is viewed as one of the subsystems in a heterogeneous, distributed system, system design becomes the design of a flexible architecture for accomplishing system tasks with both human and computer agents. HCI requirements and design should be distinguished from user interface (displays and controls) requirements and design. Effective HCI design for multi-agent systems requires explicit identification of activities and information that support coordination and communication between agents. The effects are characterized of HCI design on overall system design and approaches are identified to addressing HCI requirements in system design. The results include definition of (1) guidance based on information level requirements analysis of HCI, (2) high level requirements for a design methodology that integrates the HCI perspective into system design, and (3) requirements for embedding HCI design tools into intelligent system development environments.

Intelligent Decision Technologies : Proceedings of the 4th International Conference on Intelligent Decision Technologies

CERN Document Server

Watanabe, Toyohide; Phillips-Wren, Gloria; Howlett, Robert; Jain, Lakhmi

2012-01-01

The Intelligent Decision Technologies (IDT) International Conference encourages an interchange of research on intelligent systems and intelligent technologies that enhance or improve decision making. The focus of IDT is interdisciplinary and includes research on all aspects of intelligent decision technologies, from fundamental development to real applications. IDT has the potential to expand their support of decision making in such areas as finance, accounting, marketing, healthcare, medical and diagnostic systems, military decisions, production and operation, networks, traffic management, crisis response, human-machine interfaces, financial and stock market monitoring and prediction, and robotics. Intelligent decision systems implement advances in intelligent agents, fuzzy logic, multi-agent systems, artificial neural networks, and genetic algorithms, among others.  Emerging areas of active research include virtual decision environments, social networking, 3D human-machine interfaces, cognitive interfaces,...

Simulating Flaring Events via an Intelligent Cellular Automata Mechanism

Science.gov (United States)

Dimitropoulou, M.; Vlahos, L.; Isliker, H.; Georgoulis, M.

2010-07-01

We simulate flaring events through a Cellular Automaton (CA) model, in which, for the first time, we use observed vector magnetograms as initial conditions. After non-linear force free extrapolation of the magnetic field from the vector magnetograms, we identify magnetic discontinuities, using two alternative criteria: (1) the average magnetic field gradient, or (2) the normalized magnetic field curl (i.e. the current). Magnetic discontinuities are identified at the grid-sites where the magnetic field gradient or curl exceeds a specified threshold. We then relax the magnetic discontinuities according to the rules of Lu and Hamilton (1991) or Lu et al. (1993), i.e. we redistribute the magnetic field locally so that the discontinuities disappear. In order to simulate the flaring events, we consider several alternative scenarios with regard to: (1) The threshold above which magnetic discontinuities are identified (applying low, high, and height-dependent threshold values); (2) The driving process that occasionally causes new discontinuities (at randomly chosen grid sites, magnetic field increments are added that are perpendicular (or may-be also parallel) to the existing magnetic field). We address the question whether the coronal active region magnetic fields can indeed be considered to be in the state of self-organized criticality (SOC).

The Epistemic Status of Intelligence

DEFF Research Database (Denmark)

Rønn, Kira Vrist; Høffding, Simon

2012-01-01

We argue that the majority of intelligence definitions fail to recognize that the normative epistemic status of intelligence is knowledge and not an inferior alternative. We refute the counter-arguments that intelligence ought not to be seen as knowledge because of 1) its action-oriented scope...... and robustness of claims to intelligence-knowledge can be assessed....

Multiple Intelligences: Current Trends in Assessment

Science.gov (United States)

Harman, Marsha J.; Kordinak, S. Thomas; Bruce, A. Jerry

2009-01-01

With his theory of multiple intelligences, Howard Gardner challenged the presumption that intelligence is a single innate entity. He maintained that multiple intelligences exist and are related to specific brain areas and symbol systems. Each of the intelligences has its merits and limits, but by using a multiple intelligences approach, more…

Designing with computational intelligence

CERN Document Server

Lopes, Heitor; Mourelle, Luiza

2017-01-01

This book discusses a number of real-world applications of computational intelligence approaches. Using various examples, it demonstrates that computational intelligence has become a consolidated methodology for automatically creating new competitive solutions to complex real-world problems. It also presents a concise and efficient synthesis of different systems using computationally intelligent techniques.

Investigation and study on each technique and example of intelligent planning; Intelligent planning no kakushu shuho to jirei ni kansuru chosa kenkyu

Energy Technology Data Exchange (ETDEWEB)

NONE

1995-12-11

Various problems on intelligent planning (IP) and the tendency of basic technology were investigated. For each technique of IP, a Petri net and mark graph have been widely used as the modeling and analysis methods of a discrete event system. Moreover, various planning problems were modeled by a traveling salesman problem, and the efficient solution of the traveling salesman problem has been studied simultaneously. The tendency of the basic technology and application system viewed from an example of intelligent plant planning was investigated as an applied field of planning technology, with importance attached to the production system and robot planning. In the scheduling technology of the production system, the activation of an AI study and a new theory (i.e., architecture study) based on natural science information was investigated with the transition in the world as a trigger. A robot system has been planned in a wide range such as the environmental information acquisition planning of a robot. 202 refs., 69 figs., 4 tabs.

Event classification and optimization methods using artificial intelligence and other relevant techniques: Sharing the experiences

Science.gov (United States)

Mohamed, Abdul Aziz; Hasan, Abu Bakar; Ghazali, Abu Bakar Mhd.

2017-01-01

Classification of large data into respected classes or groups could be carried out with the help of artificial intelligence (AI) tools readily available in the market. To get the optimum or best results, optimization tool could be applied on those data. Classification and optimization have been used by researchers throughout their works, and the outcomes were very encouraging indeed. Here, the authors are trying to share what they have experienced in three different areas of applied research.

Alzheimer's disease and intelligence.

Science.gov (United States)

Yeo, R A; Arden, R; Jung, R E

2011-06-01

A significant body of evidence has accumulated suggesting that individual variation in intellectual ability, whether assessed directly by intelligence tests or indirectly through proxy measures, is related to risk of developing Alzheimer's disease (AD) in later life. Important questions remain unanswered, however, such as the specificity of risk for AD vs. other forms of dementia, and the specific links between premorbid intelligence and development of the neuropathology characteristic of AD. Lower premorbid intelligence has also emerged as a risk factor for greater mortality across myriad health and mental health diagnoses. Genetic covariance contributes importantly to these associations, and pleiotropic genetic effects may impact diverse organ systems through similar processes, including inefficient design and oxidative stress. Through such processes, the genetic underpinnings of intelligence, specifically, mutation load, may also increase the risk of developing AD. We discuss how specific neurobiologic features of relatively lower premorbid intelligence, including reduced metabolic efficiency, may facilitate the development of AD neuropathology. The cognitive reserve hypothesis, the most widely accepted account of the intelligence-AD association, is reviewed in the context of this larger literature.

Is Intelligence Artificial?

OpenAIRE

Greer, Kieran

2014-01-01

Our understanding of intelligence is directed primarily at the level of human beings. This paper attempts to give a more unifying definition that can be applied to the natural world in general. The definition would be used more to verify a degree of intelligence, not to quantify it and might help when making judgements on the matter. A version of an accepted test for AI is then put forward as the 'acid test' for Artificial Intelligence itself. It might be what a free-thinking program or robot...

Beyond AI: Multi-Intelligence (MI Combining Natural and Artificial Intelligences in Hybrid Beings and Systems

Directory of Open Access Journals (Sweden)

Stephen Fox

2017-06-01

Full Text Available Framing strongly influences actions among technology proponents and end-users. Underlying much debate about artificial intelligence (AI are several fundamental shortcomings in its framing. First, discussion of AI is atheoretical, and therefore has limited potential for addressing the complexity of causation. Second, intelligence is considered from an anthropocentric perspective that sees human intelligence, and intelligence developed by humans, as superior to all other intelligences. Thus, the extensive post-anthropocentric research into intelligence is not given sufficient consideration. Third, AI is discussed often in reductionist mechanistic terms. Rather than in organicist emergentist terms as a contributor to multi-intelligence (MI hybrid beings and/or systems. Thus, current framing of AI can be a self-validating reduction within which AI development is focused upon AI becoming the single-variable mechanism causing future effects. In this paper, AI is reframed as a contributor to MI.

Artificial Consciousness or Artificial Intelligence

Directory of Open Access Journals (Sweden)

Spanache Florin

2017-05-01

Full Text Available Artificial intelligence is a tool designed by people for the gratification of their own creative ego, so we can not confuse conscience with intelligence and not even intelligence in its human representation with conscience. They are all different concepts and they have different uses. Philosophically, there are differences between autonomous people and automatic artificial intelligence. This is the difference between intelligence and artificial intelligence, autonomous versus automatic. But conscience is above these differences because it is neither conditioned by the self-preservation of autonomy, because a conscience is something that you use to help your neighbor, nor automatic, because one’s conscience is tested by situations which are not similar or subject to routine. So, artificial intelligence is only in science-fiction literature similar to an autonomous conscience-endowed being. In real life, religion with its notions of redemption, sin, expiation, confession and communion will not have any meaning for a machine which cannot make a mistake on its own.

Automated identification and modeling aseismic slip events on Kilauea Volcano, Hawaii

Science.gov (United States)

Desmarais, E. K.; Segall, P.; Miklius, A.

2006-12-01

Several aseismic slip events have been observed on the south flank of Kilauea volcano, Hawaii (Cervelli et al., Nature, 2002; Brooks et al., EPSL, 2006; Segall et al., Nature, 2006). These events are identified as spatially coherent offsets in GPS time series. We have interpreted the events as slip on a sub-horizontal surface at depths consistent with a decollement under Kilauea's south flank. In order to determine whether smaller slow slip events are present in the time series, we developed an algorithm that searches for coherent displacement patterns similar to the known slow slip events. We compute candidate displacements by taking a running difference of the mean position 6 days before and after a window of 6 days centered on the candidate time step. The candidate displacements are placed in a 3N dimensional data vector, where N is the number of stations. We then compute the angle, in the 3N dimensional data space, between the candidate displacement and a reference vector at each time step. The reference vector is a stack of displacements due to the four largest known slow slip events. Small angles indicate similar displacement patterns, regardless of amplitude. The algorithm strongly identifies four events (September 20, 1998, November 9, 2000, December 16, 2002, and January 26, 2005), each separated by approximately 2.11 years. The algorithm also identified one smaller event (March 3, 1998) that preceeded the September 1998 event by ~ 200 days, and another event (July 4, 2003) that followed the December 2002 event by ~ 200 days. These smaller, 'paired' events appear to alternate rupturing of the eastern and western parts of the south flank. Each of the slow slip events is correlated with an increase, sometimes slight, in microseismicity on the south flank of Kilauea. The temporal evolution of the microseismicity for the 2005 event is well explained by increased stress due to the slow slip (Segall et al., Nature, 2006). The microearthquakes, at depths of 6

Design a Smart Control Strategy to Implement an Intelligent Energy Safety and Management System

OpenAIRE

Jing-Min Wang; Ming-Ta Yang

2014-01-01

The energy saving and electricity safety are today a cause for increasing concern for homes and buildings. Integrating the radio frequency identification (RFID) and ZigBee wireless sensor network (WSN) mature technologies, the paper designs a smart control strategy to implement an intelligent energy safety and management system (IESMS) which performs energy measuring, controlling, monitoring, and saving of the power outlet system. The presented RFID and billing module is used to identify user...

Intelligent Design

DEFF Research Database (Denmark)

Hjorth, Poul G.

2005-01-01

Forestillingen om at naturen er designet af en guddommelig 'intelligens' er et smukt filosofisk princip. Teorier om Intelligent Design som en naturvidenskabeligt baseret teori er derimod helt forfærdelig.......Forestillingen om at naturen er designet af en guddommelig 'intelligens' er et smukt filosofisk princip. Teorier om Intelligent Design som en naturvidenskabeligt baseret teori er derimod helt forfærdelig....

Seismology-based early identification of dam-formation landquake events.

Science.gov (United States)

Chao, Wei-An; Zhao, Li; Chen, Su-Chin; Wu, Yih-Min; Chen, Chi-Hsuan; Huang, Hsin-Hua

2016-01-12

Flooding resulting from the bursting of dams formed by landquake events such as rock avalanches, landslides and debris flows can lead to serious bank erosion and inundation of populated areas near rivers. Seismic waves can be generated by landquake events which can be described as time-dependent forces (unloading/reloading cycles) acting on the Earth. In this study, we conduct inversions of long-period (LP, period ≥20 s) waveforms for the landquake force histories (LFHs) of ten events, which provide quantitative characterization of the initiation, propagation and termination stages of the slope failures. When the results obtained from LP waveforms are analyzed together with high-frequency (HF, 1-3 Hz) seismic signals, we find a relatively strong late-arriving seismic phase (dubbed Dam-forming phase or D-phase) recorded clearly in the HF waveforms at the closest stations, which potentially marks the time when the collapsed masses sliding into river and perhaps even impacting the topographic barrier on the opposite bank. Consequently, our approach to analyzing the LP and HF waveforms developed in this study has a high potential for identifying five dam-forming landquake events (DFLEs) in near real-time using broadband seismic records, which can provide timely warnings of the impending floods to downstream residents.

The Coast Guard Intelligence Program Enters the Intelligence Community. A Case Study of Congressional Influence on Intelligence Community Evolution

National Research Council Canada - National Science Library

Wirth, Kevin E

2007-01-01

.... Although the United States Coast Guard has utilized intelligence capabilities since the service's inception in 1790, the Coast Guard was not included as a formal member of the Intelligence Community until December 2002. Mr...

Artificial Intelligence for Controlling Robotic Aircraft

Science.gov (United States)

Krishnakumar, Kalmanje

2005-01-01

A document consisting mostly of lecture slides presents overviews of artificial-intelligence-based control methods now under development for application to robotic aircraft [called Unmanned Aerial Vehicles (UAVs) in the paper] and spacecraft and to the next generation of flight controllers for piloted aircraft. Following brief introductory remarks, the paper presents background information on intelligent control, including basic characteristics defining intelligent systems and intelligent control and the concept of levels of intelligent control. Next, the paper addresses several concepts in intelligent flight control. The document ends with some concluding remarks, including statements to the effect that (1) intelligent control architectures can guarantee stability of inner control loops and (2) for UAVs, intelligent control provides a robust way to accommodate an outer-loop control architecture for planning and/or related purposes.

Toward New-Generation Intelligent Manufacturing

Directory of Open Access Journals (Sweden)

Ji Zhou

2018-02-01

Full Text Available Intelligent manufacturing is a general concept that is under continuous development. It can be categorized into three basic paradigms: digital manufacturing, digital-networked manufacturing, and new-generation intelligent manufacturing. New-generation intelligent manufacturing represents an in-depth integration of new-generation artificial intelligence (AI technology and advanced manufacturing technology. It runs through every link in the full life-cycle of design, production, product, and service. The concept also relates to the optimization and integration of corresponding systems; the continuous improvement of enterprises’ product quality, performance, and service levels; and reduction in resources consumption. New-generation intelligent manufacturing acts as the core driving force of the new industrial revolution and will continue to be the main pathway for the transformation and upgrading of the manufacturing industry in the decades to come. Human-cyber-physical systems (HCPSs reveal the technological mechanisms of new-generation intelligent manufacturing and can effectively guide related theoretical research and engineering practice. Given the sequential development, cross interaction, and iterative upgrading characteristics of the three basic paradigms of intelligent manufacturing, a technology roadmap for “parallel promotion and integrated development” should be developed in order to drive forward the intelligent transformation of the manufacturing industry in China. Keywords: Advanced manufacturing, New-generation intelligent manufacturing, Human-cyber-physical system, New-generation AI, Basic paradigms, Parallel promotion, Integrated development

Intelligence and Prosocial Behavior

DEFF Research Database (Denmark)

Han, Ru; Shi, Jiannong; Yong, W.

2012-01-01

Results of prev ious studies of the relationship between prosocial behav ior and intelligence hav e been inconsistent. This study attempts to distinguish the dif f erences between sev eral prosocial tasks, and explores the way s in which cognitiv e ability inf luences prosocial behav ior. In Study...... One and Two, we reexamined the relationship between prosocial behav ior and intelligence by employ ing a costly signaling theory with f our games. The results rev ealed that the prosocial lev el of smarter children is higher than that of other children in more complicated tasks but not so in simple...... tasks. In Study Three, we tested the moderation ef f ect of the av erage intelligence across classes, and the results did not show any group intelligence ef f ect on the relationship between intelligence and prosocial behav ior....

Intelligence in early adulthood and subclinical atherosclerosis in middle-aged men: the Vietnam Experience Study.

Science.gov (United States)

Gale, Catharine R; Deary, Ian J; Fowkes, F Gerald; Batty, G David

2012-07-01

People with higher intelligence in early life have a lower subsequent risk of coronary heart disease events, but the explanation for these observations is unclear. To examine whether intelligence in early adulthood is associated with risk of subclinical atherosclerosis in mid-life, as indicated by the ankle brachial index (ABI), and investigate its potential mediating role in the association between intelligence and mortality. Participants were 4286 male US veterans whose intelligence was measured on enlistment into military service at a mean age of 20.4 years and whose ABI was measured by Doppler as part of a detailed medical examination at a mean age of 38.3 years. Higher intelligence in early adulthood was associated with a higher ABI in mid-life. For an SD increase in intelligence, after adjusting for age, ABI (× 10) rose by 0.05 (0.02, 0.07), and the OR (95% CI) for having a low ABI (≤ 0.90) was 0.84 (0.72 to 0.98). Further adjustment for smoking, serum cholesterol, triglycerides and glucose concentrations, blood pressure, erythrocyte sedimentation rate, body mass index, alcohol intake, education and measures of socioeconomic position had little or no attenuating effect on these associations. Lower ABI was associated with increased mortality from all causes and cardiovascular disease but it did not account for the associations between IQ and mortality from these causes. Men of lower intelligence may be more susceptible to atherogenesis, though this mechanism does not appear to explain their increased risk of earlier death.

Elementary epistemological features of machine intelligence

OpenAIRE

Horvat, Marko

2008-01-01

Theoretical analysis of machine intelligence (MI) is useful for defining a common platform in both theoretical and applied artificial intelligence (AI). The goal of this paper is to set canonical definitions that can assist pragmatic research in both strong and weak AI. Described epistemological features of machine intelligence include relationship between intelligent behavior, intelligent and unintelligent machine characteristics, observable and unobservable entities and classification of in...

Understanding the use of strategic intelligence as a strategic management tool in the long-term insurance industry in South Africa

Directory of Open Access Journals (Sweden)

René Pellissier

2011-10-01

The paper obtained the qualitative views and opinions of strategic decision makers, on an executive managerial level within the South African long-term insurance industry, on their organisations use of strategic intelligence. It was found that there are marked differences in the conformity and usage of strategic intelligence and its components between the organisations surveyed, with a measurable difference between large and small organisations. It is, however, generally viewed that the use of a strategic intelligence framework could greatly enhance decision-making. Data collection for the research undertaken was limited to the 82 long-term insurance companies, which were registered with the South African Financial Services Board. More specifically the focus was on the organisations listed on the Johannesburg Securities Exchange within the Life Assurance sector, within which a final response rate of 36.1% was achieved, including the 100% response rate from the six listed organisations. By understanding the extent to which strategic intelligence is utilised in the South African longterminsurance industry, and the benefits or problems that are experienced by implementing and using strategic intelligence as an input to the strategic management process we can comprehend the value that strategic intelligence adds in the decision making process. The originality of this work concludes in the identification and utilisation of the most important factors of a strategic intelligence framework that will greatly enhance global corporate decisionmakingand result in competitive advantage and constant innovation within the South African business environment.

Competitive Intelligence in Perspective to be a Source of Competitive Advantage and Strategic Contributions

Directory of Open Access Journals (Sweden)

Felipe Gama Buzzerio

2014-12-01

Full Text Available This article examines the prospect of Competitive Intelligence (CI constitute a source of competitive advantage in light of the Resource Based View and its contribution to the strategic management of the company. Relies on exploratory and descriptive research using the qualitative method. Six managers responsible for CI activities institutionalized in large different business companies were interviewed. Data were processed and analyzed with the application of content analysis. It was concluded that the CI is unable to be a source of competitive advantage but rather as an effective support to decision making process in the surveyed companies. Apparently CI products meet the specific needs of internal customers, facilitate the integration of CI with marketing and operations, help in the identification of risks through the analysis of strategic information, which is a differentiator compared to other types of intelligences.

Intelligence Community Spending: Trends and Issues

Science.gov (United States)

2016-11-08

The Deputy Director CIA manages the CIAP. Funds CIA activities to include HUMINT and OSINT . The CIAP funds everything related to the CIA. It...Human Intelligence (HUMINT); Imagery Intelligence (IMINT); Measurement and Signature Intelligence (MASINT); Open Source Intelligence ( OSINT ); and

Intelligent Design and Earth History

Science.gov (United States)

Elders, W. A.

2001-05-01

clumsy, wasteful works of nature as seen in the suffering caused by parasites and in the delight in cruelty shown by some predators when catching and playing with their prey". The positions of other contemporary proponents of ID are far from uniform. Some, while rejecting unguided evolution, appear to accept the concepts of common descent and an Earth 4.6 billion years old. However, within the ID movement there has been very little discussion of its implications for Earth history. For example, is it valid to ask, "Were the Himalayas intelligently designed?" Or should the question be, "Is the physics of plate tectonics intelligently designed?" As well as contingency in the history of life, there are strong elements of contingency in the history of the Earth, in the history of the solar system and in the history of the cosmos. Does ID matter? From a purely operational viewpoint, the rock record could equally well be interpreted in pattern-based investigations as being the product of either naturalistic processes, or as a sequence of intelligently designed events. For example, in correlating horizons between adjacent oil wells using micropaleontology, or in doing seismic stratigraphy, it makes little difference whether foraminifera or unconformities formed by natural or supernatural agencies. However, ID is an anathema for process-based research and its cultural implications are enormous. While we must be careful in our work to separate methodological naturalism from culturally bound philosophical naturalism, methodological naturalism has been an enormously successful approach in the advancement of knowledge. We have moved from the "demon-haunted" world to the world of the human genome. We must take ID seriously; it is a retrograde step.

GABA predicts visual intelligence.

Science.gov (United States)

Cook, Emily; Hammett, Stephen T; Larsson, Jonas

2016-10-06

Early psychological researchers proposed a link between intelligence and low-level perceptual performance. It was recently suggested that this link is driven by individual variations in the ability to suppress irrelevant information, evidenced by the observation of strong correlations between perceptual surround suppression and cognitive performance. However, the neural mechanisms underlying such a link remain unclear. A candidate mechanism is neural inhibition by gamma-aminobutyric acid (GABA), but direct experimental support for GABA-mediated inhibition underlying suppression is inconsistent. Here we report evidence consistent with a global suppressive mechanism involving GABA underlying the link between sensory performance and intelligence. We measured visual cortical GABA concentration, visuo-spatial intelligence and visual surround suppression in a group of healthy adults. Levels of GABA were strongly predictive of both intelligence and surround suppression, with higher levels of intelligence associated with higher levels of GABA and stronger surround suppression. These results indicate that GABA-mediated neural inhibition may be a key factor determining cognitive performance and suggests a physiological mechanism linking surround suppression and intelligence. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Development of a method of continuous improvement of services using the Business Intelligence tools

Directory of Open Access Journals (Sweden)

Svetlana V. Kulikova

2018-01-01

Full Text Available The purpose of the study was to develop a method of continuous improvement of services using the Business Intelligence tools.Materials and methods: the materials are used on the concept of the Deming Cycle, methods and Business Intelligence technologies, Agile methodology and SCRUM.Results: the article considers the problem of continuous improvement of services and offers solutions using methods and technologies of Business Intelligence. In this case, the purpose of this technology is to solve and make the final decision regarding what needs to be improved in the current organization of services. In other words, Business Intelligence helps the product manager to see what is hidden from the “human eye” on the basis of received and processed data. Development of a method based on the concept of the Deming Cycle and Agile methodologies, and SCRUM.The article describes the main stages of development of method based on activity of the enterprise. It is necessary to fully build the Business Intelligence system in the enterprise to identify bottlenecks and justify the need for their elimination and, in general, for continuous improvement of the services. This process is represented in the notation of DFD. The article presents a scheme for the selection of suitable agile methodologies.The proposed concept of the solution of the stated objectives, including methods of identification of problems through Business Intelligence technology, development of the system for troubleshooting and analysis of results of the introduced changes. The technical description of the project is given.Conclusion: following the work of the authors there was formed the concept of the method for the continuous improvement of the services, using the Business Intelligence technology with the specifics of the enterprises, offering SaaS solutions. It was also found that when using this method, the recommended development methodology is SCRUM. The result of this scientific

The First Workshop on Artificial Intelligence Techniques for Ambient Intelligence (AITAmI '06)

OpenAIRE

Augusto, Juan Carlos; Shapiro, Daniel

2007-01-01

The first annual workshop on the role of AI in ambient intelligence was held in Riva de Garda, Italy, on August 29, 2006. The workshop was colocated with the European Conference on Artificial Intelligence (ECAI 2006). It provided an opportunity for researchers in a variety of AI subfields together with representatives of commercial interests to explore ambient intelligence technology and applications.

Artificial Intelligence and Semantics through the Prism of Structural, Post-Structural and Transcendental Approaches.

Science.gov (United States)

Gasparyan, Diana

2016-12-01

There is a problem associated with contemporary studies of philosophy of mind, which focuses on the identification and convergence of human and machine intelligence. This is the problem of machine emulation of sense. In the present study, analysis of this problem is carried out based on concepts from structural and post-structural approaches that have been almost entirely overlooked by contemporary philosophy of mind. If we refer to the basic definitions of "sign" and "meaning" found in structuralism and post-structuralism, we see a fundamental difference between the capabilities of a machine and the human brain engaged in the processing of a sign. This research will exemplify and provide additional evidence to support distinctions between syntactic and semantic aspects of intelligence, an issue widely discussed by adepts of contemporary philosophy of mind. The research will demonstrate that some aspect of a number of ideas proposed in relation to semantics and semiosis in structuralism and post-structuralism are similar to those we find in contemporary analytical studies related to the theory and philosophy of artificial intelligence. The concluding part of the paper offers an interpretation of the problem of formalization of sense, connected to its metaphysical (transcendental) properties.

Intelligent editor/printer enhancements

Science.gov (United States)

Woodfill, M. C.; Pheanis, D. C.

1983-01-01

Microprocessor support hardware, software, and cross assemblers relating to the Motorola 6800 and 6809 process systems were developed. Pinter controller and intelligent CRT development are discussed. The user's manual, design specifications for the MC6809 version of the intelligent printer controller card, and a 132-character by 64-line intelligent CRT display system using a Motorola 6809 MPU, and a one-line assembler and disassembler are provided.

Ventilator-Related Adverse Events: A Taxonomy and Findings From 3 Incident Reporting Systems.

Science.gov (United States)

Pham, Julius Cuong; Williams, Tamara L; Sparnon, Erin M; Cillie, Tam K; Scharen, Hilda F; Marella, William M

2016-05-01

In 2009, researchers from Johns Hopkins University's Armstrong Institute for Patient Safety and Quality; public agencies, including the FDA; and private partners, including the Emergency Care Research Institute and the University HealthSystem Consortium (UHC) Safety Intelligence Patient Safety Organization, sought to form a public-private partnership for the promotion of patient safety (P5S) to advance patient safety through voluntary partnerships. The study objective was to test the concept of the P5S to advance our understanding of safety issues related to ventilator events, to develop a common classification system for categorizing adverse events related to mechanical ventilators, and to perform a comparison of adverse events across different adverse event reporting systems. We performed a cross-sectional analysis of ventilator-related adverse events reported in 2012 from the following incident reporting systems: the Pennsylvania Patient Safety Authority's Patient Safety Reporting System, UHC's Safety Intelligence Patient Safety Organization database, and the FDA's Manufacturer and User Facility Device Experience database. Once each organization had its dataset of ventilator-related adverse events, reviewers read the narrative descriptions of each event and classified it according to the developed common taxonomy. A Pennsylvania Patient Safety Authority, FDA, and UHC search provided 252, 274, and 700 relevant reports, respectively. The 3 event types most commonly reported to the UHC and the Pennsylvania Patient Safety Authority's Patient Safety Reporting System databases were airway/breathing circuit issue, human factor issues, and ventilator malfunction events. The top 3 event types reported to the FDA were ventilator malfunction, power source issue, and alarm failure. Overall, we found that (1) through the development of a common taxonomy, adverse events from 3 reporting systems can be evaluated, (2) the types of events reported in each database were related

Ventilator-Related Adverse Events: A Taxonomy and Findings From 3 Incident Reporting Systems

Science.gov (United States)

Pham, Julius Cuong; Williams, Tamara L; Sparnon, Erin M; Cillie, Tam K; Scharen, Hilda F; Marella, William M

2016-01-01

BACKGROUND: In 2009, researchers from Johns Hopkins University's Armstrong Institute for Patient Safety and Quality; public agencies, including the FDA; and private partners, including the Emergency Care Research Institute and the University HealthSystem Consortium (UHC) Safety Intelligence Patient Safety Organization, sought to form a public-private partnership for the promotion of patient safety (P5S) to advance patient safety through voluntary partnerships. The study objective was to test the concept of the P5S to advance our understanding of safety issues related to ventilator events, to develop a common classification system for categorizing adverse events related to mechanical ventilators, and to perform a comparison of adverse events across different adverse event reporting systems. METHODS: We performed a cross-sectional analysis of ventilator-related adverse events reported in 2012 from the following incident reporting systems: the Pennsylvania Patient Safety Authority's Patient Safety Reporting System, UHC's Safety Intelligence Patient Safety Organization database, and the FDA's Manufacturer and User Facility Device Experience database. Once each organization had its dataset of ventilator-related adverse events, reviewers read the narrative descriptions of each event and classified it according to the developed common taxonomy. RESULTS: A Pennsylvania Patient Safety Authority, FDA, and UHC search provided 252, 274, and 700 relevant reports, respectively. The 3 event types most commonly reported to the UHC and the Pennsylvania Patient Safety Authority's Patient Safety Reporting System databases were airway/breathing circuit issue, human factor issues, and ventilator malfunction events. The top 3 event types reported to the FDA were ventilator malfunction, power source issue, and alarm failure. CONCLUSIONS: Overall, we found that (1) through the development of a common taxonomy, adverse events from 3 reporting systems can be evaluated, (2) the types of

Classical methods for interpreting objective function minimization as intelligent inference

Energy Technology Data Exchange (ETDEWEB)

Golden, R.M. [Univ. of Texas, Dallas, TX (United States)

1996-12-31

Most recognition algorithms and neural networks can be formally viewed as seeking a minimum value of an appropriate objective function during either classification or learning phases. The goal of this paper is to argue that in order to show a recognition algorithm is making intelligent inferences, it is not sufficient to show that the recognition algorithm is computing (or trying to compute) the global minimum of some objective function. One must explicitly define a {open_quotes}relational system{close_quotes} for the recognition algorithm or neural network which identifies the: (i) sample space, (ii) the relevant sigmafield of events generated by the sample space, and (iii) the {open_quotes}relation{close_quotes} for that relational system. Only when such a {open_quotes}relational system{close_quotes} is properly defined, is it possible to formally establish the sense in which computing the global minimum of an objective function is an intelligent, inference.

Predictive Estimates of Employees’ Intelligence at Workplace with Special Reference to Emotional and Spiritual Intelligence

OpenAIRE

B. K. Punia; Priyanka Yadav

2015-01-01

The piece of writing investigates the relationship between employees’ emotional and Spiritual intelligence. A conversation of spirituality and emotions within the workplace can be an unthinkable topic. However, emotional intelligence and spiritual intelligence are, at present, more widely acknowledged. Drawing a research connected with these construct we suggest that emotional intelligence within the employees in organisations may provide employees with a medium to better understand and mix s...

Artificial Intelligence and Economic Theories

OpenAIRE

Marwala, Tshilidzi; Hurwitz, Evan

2017-01-01

The advent of artificial intelligence has changed many disciplines such as engineering, social science and economics. Artificial intelligence is a computational technique which is inspired by natural intelligence such as the swarming of birds, the working of the brain and the pathfinding of the ants. These techniques have impact on economic theories. This book studies the impact of artificial intelligence on economic theories, a subject that has not been extensively studied. The theories that...

[Identification of the meiotic events in grasshopper spermatogenesis].

Science.gov (United States)

Liu, Meng-Hao; Zhao, Kai-Qiang; Wang, Ya-Dong; Yang, Meng-Ping; Zhao, Ning-Ning; Yang, Da-Xiang

2012-12-01

The grasshoppers are ideal materials to study various meiotic stages of spermatogenesis due to their easy availability, fairly large chromosomes, and fewer numbers of chromosomes. It is easy to make temporary squash preparation of grasshopper testes; however, it is usually difficult for the beginners to differentiate between stages of meiosis. In view of this, we demonstrated the method of identification of meiotic stages by chromosome number and chromosome conformation, taking spermatogonial meiosis of Locusta migratoria manilensis as an example. We described briefly the mitosis of spermatogonia and the spermatogenesis of this species as well.

Reviewing the development of an artificial intelligence based risk program

International Nuclear Information System (INIS)

Dixon, B.W.; Hinton, M.F.

1985-01-01

A successful application of nonconventional programming methods has been achieved in computer-assisted probabilistic risk assessment (PRA). The event tree sequence importance calculator, SQUIMP, provides for prompted data entry, generic expansion, on-line pruning, boolean reductions, and importance factor selection. SQUIMP employs constructs typically found in artificial intelligence (AI) programs. The development history of SQUIMP is outlined and its internal structure described as background for a discussion on the applicability of symbolic programming methods in PRA

Intelligence by consent

DEFF Research Database (Denmark)

Diderichsen, Adam; Rønn, Kira Vrist

2017-01-01

This article contributes to the current discussions concerning an adequate framework for intelligence ethics. The first part critically scrutinises the use of Just War Theory in intelligence ethics with specific focus on the just cause criterion. We argue that using self-defence as justifying cau...

Occurrences in control room equipment, procedures and personnel performances: IRS control room events

International Nuclear Information System (INIS)

Tolstykh, V.

1994-01-01

The IAEA/NEA Incident Reporting System (IRS) was established in the early 1980, its objective being to gain from operating experience achieved in countries with nuclear power programmes by means of exchanging information on events relevant to safety. Among the 2171 events in the database, 175 events (i.e. 8%) were identified as ''control room events''. It was decided to group these into three sets for further study: 65 events with common mode/cause failures (CCFs), 22 events with cognitive errors and 30 events with unforeseen interaction between NPP systems. It is expected that the pitfalls experienced in the IRS and the questions derived from this study will help to gain a better understanding of the needs and interests of specialists in advanced information methods and artificial intelligence in NPP control rooms. (author)

Identification model of gifted students in secondary education

Directory of Open Access Journals (Sweden)

Carmen Ferrándiz

2010-04-01

Full Text Available The aim of this article is to describe the identification and assessment procedure to identify high ability secondary school students in the Spanish region of Murcia. In the screening process questionaires addressed to parents, teachers, and pupils nad based on the Multiple Intelligences Theory were used. In the identification process two other instruments were used: a the Differential Aptitude Test (DAT aimed to assess the following areas: reasoning, verbal abilities, numerical and abstract reasoning, spatial aptitude, mechanical reasoning, attention and perceptive aptitudes, and b the TTCT (Torrance Test of Creative Thinking in order to assess the main abilities of creativity (fluency, flexibility, originality and elaboration. These two assessment tools will allow us to distinguish gifted from talented (Castelló and Batlle, 1998. In a third stage, the socio-emotional characteristics of the identified students are analysed using: c the BFQ-NA whose aim is to assess the personality dimensions (openness, conscientiousness, extraversion; agreeableness and neuroticism, and d emotional intelligence questionnaires (EQ-i:YV and EQ-i:YV-O Barón and Parker, 2000. 565 took part in this research. The students were aged 11-18 (M= 14.6 and SD= 1.08 and attended high schools of Compulsory Secondary Education (ESO of the Murcia Region. The results showed different profiles of gifted and talented stduents. The cognitive-emotional complexity of these exceptional students is discussed.

The application of a Business Intelligence tool for strategic planning in a higher education institution: a case study of the University of the Witwatersrand

Directory of Open Access Journals (Sweden)

Vincent Nyalungu

2011-07-01

Full Text Available This article presents a discussion on the importance of business intelligence (BI and the role that a specific BI tool, Business Intelligence Enterprise Edition, plays in the strategic decision-making processes in an organisation. The University of the Witwatersrand, often referred to as Wits, was used as a case study. The main objective of a business intelligence tool is to improve the quality and timeliness of the input of data to the organisational decision-making process. The quality of the data, which is an organisational asset, is therefore of the utmost importance. Approaches for the identification of business intelligence from corporate information and knowledge management were also assessed. A questionnaire was administered among key informants within the university in order to address some of the pertinent issues at higher education institutions. In addition, the role of a data warehouse within the business intelligence framework was presented. The paper itself covers a wide range of disciplines from information technology, knowledge management to decision sciences. The article also presents a proposed framework to be used in line with the best practices in the implementation of business intelligence solutions. Keywords: Business Intelligence (BI, Business Intelligence Enterprise Edition (BIEE, Data Warehouse, Strategic Decision Making, Strategic Planning, Higher Education Institutions and Knowledge Management. Disciplines: Information Technology, Knowledge Management, Management Sciences, Decision Sciences & Management

Position Paper on Intelligent Supply Chains

DEFF Research Database (Denmark)

Møller, Charles

This paper is intended to present and to analyze the concept of the Intelligent Supply Chain (ISC). The purpose of the paper is to: 1) Clarify the concept of the intelligent supply chain; 2) Identify emerging research opportunities; and 3) Specify a research engagement model for further explorati...... of intelligent supply chains. It is concluded that information management is critical to intelligent supply chains and a research agenda is outlined.......This paper is intended to present and to analyze the concept of the Intelligent Supply Chain (ISC). The purpose of the paper is to: 1) Clarify the concept of the intelligent supply chain; 2) Identify emerging research opportunities; and 3) Specify a research engagement model for further exploration...... the concept of Intelligent Supply Chain and to establish an overall perspective based on information management. The claim made here is that the notion of the intelligent enterprise contributes with a new perspective on supply chain management that addresses the current challenges in an industrial supply...

What Is Artificial Intelligence Anyway?

Science.gov (United States)

Kurzweil, Raymond

1985-01-01

Examines the past, present, and future status of Artificial Intelligence (AI). Acknowledges the limitations of AI but proposes possible areas of application and further development. Urges a concentration on the unique strengths of machine intelligence rather than a copying of human intelligence. (ML)

Competitive Intelligence and Social Advantage.

Science.gov (United States)

Davenport, Elisabeth; Cronin, Blaise

1994-01-01

Presents an overview of issues concerning civilian competitive intelligence (CI). Topics discussed include competitive advantage in academic and research environments; public domain information and libraries; covert and overt competitive intelligence; data diversity; use of the Internet; cooperative intelligence; and implications for library and…

Soft computing in artificial intelligence

CERN Document Server

Matson, Eric

2014-01-01

This book explores the concept of artificial intelligence based on knowledge-based algorithms. Given the current hardware and software technologies and artificial intelligence theories, we can think of how efficient to provide a solution, how best to implement a model and how successful to achieve it. This edition provides readers with the most recent progress and novel solutions in artificial intelligence. This book aims at presenting the research results and solutions of applications in relevance with artificial intelligence technologies. We propose to researchers and practitioners some methods to advance the intelligent systems and apply artificial intelligence to specific or general purpose. This book consists of 13 contributions that feature fuzzy (r, s)-minimal pre- and β-open sets, handling big coocurrence matrices, Xie-Beni-type fuzzy cluster validation, fuzzy c-regression models, combination of genetic algorithm and ant colony optimization, building expert system, fuzzy logic and neural network, ind...

Relationship between Emotional Intelligence and

Directory of Open Access Journals (Sweden)

Vahid Rafieyan

2014-07-01

Full Text Available Language learners’ awareness of target language pragmatic features is influenced by individual difference variables, the least explored one being emotional intelligence. To investigate the relationship between emotional intelligence and pragmatic awareness, the current study was conducted over 120 Iranian senior undergraduates of English as a Foreign Language at a university in Iran. Pragmatic awareness was measured through a 12-scenario contextualized pragmatic judgment task. Emotional intelligence was also measured through the EQ-i. The results of the Pearson correlation revealed a strong positive relationship between emotional intelligence and pragmatic awareness. The pedagogical implications of the findings suggested incorporation of emotion-driven authentic materials in English language classes to invoke emotional intelligence in language learners.

Emotional intelligence of mental health nurses.

Science.gov (United States)

van Dusseldorp, Loes R L C; van Meijel, Berno K G; Derksen, Jan J L

2011-02-01

The aim of this study is to gain insight into the level of emotional intelligence of mental health nurses in the Netherlands. The focus in research on emotional intelligence to date has been on a variety of professionals. However, little is known about emotional intelligence in mental health nurses. The emotional intelligence of 98 Dutch nurses caring for psychiatric patients is reported. Data were collected with the Bar-On Emotional Quotient Inventory within a cross-sectional research design. The mean level of emotional intelligence of this sample of professionals is statistically significant higher than the emotional intelligence of the general population. Female nurses score significantly higher than men on the subscales Empathy, Social Responsibility, Interpersonal Relationship, Emotional Self-awareness, Self-Actualisation and Assertiveness. No correlations are found between years of experience and age on the one hand and emotional intelligence on the other hand. The results of this study show that nurses in psychiatric care indeed score above average in the emotional intelligence required to cope with the amount of emotional labour involved in daily mental health practice. The ascertained large range in emotional intelligence scores among the mental health nurses challenges us to investigate possible implications which higher or lower emotional intelligence levels may have on the quality of care. For instance, a possible relation between the level of emotional intelligence and the quality of the therapeutic nurse-patient relationship or the relation between the level of emotional intelligence and the manner of coping with situations characterised by a great amount of emotional labour (such as caring for patients who self-harm or are suicidal). © 2010 The Authors. Journal compilation © 2010 Blackwell Publishing Ltd.

Intelligent Environmental Nanomaterials

KAUST Repository

Chang, Jian

2018-01-30

Due to the inherent complexity of environmental problems, especially water and air pollution, the utility of single-function environmental nanomaterials used in conventional and unconventional environmental treatment technologies are gradually reaching their limits. Intelligent nanomaterials with environmentally-responsive functionalities have shown potential to improve the performance of existing and new environmental technologies. By rational design of their structures and functionalities, intelligent nanomaterials can perform different tasks in response to varying application scenarios for the purpose of achieving the best performance. This review offers a critical analysis of the design concepts and latest progresses on the intelligent environmental nanomaterials in filtration membranes with responsive gates, materials with switchable wettability for selective and on-demand oil/water separation, environmental materials with self-healing capability, and emerging nanofibrous air filters for PM2.5 removal. We hope that this review will inspire further research efforts to develop intelligent environmental nanomaterials for the enhancement of the overall quality of environmental or human health.

Intelligent Environmental Nanomaterials

KAUST Repository

Chang, Jian; Zhang, Lianbin; Wang, Peng

2018-01-01

Due to the inherent complexity of environmental problems, especially water and air pollution, the utility of single-function environmental nanomaterials used in conventional and unconventional environmental treatment technologies are gradually reaching their limits. Intelligent nanomaterials with environmentally-responsive functionalities have shown potential to improve the performance of existing and new environmental technologies. By rational design of their structures and functionalities, intelligent nanomaterials can perform different tasks in response to varying application scenarios for the purpose of achieving the best performance. This review offers a critical analysis of the design concepts and latest progresses on the intelligent environmental nanomaterials in filtration membranes with responsive gates, materials with switchable wettability for selective and on-demand oil/water separation, environmental materials with self-healing capability, and emerging nanofibrous air filters for PM2.5 removal. We hope that this review will inspire further research efforts to develop intelligent environmental nanomaterials for the enhancement of the overall quality of environmental or human health.

Intelligence system for reactor operator informational support

International Nuclear Information System (INIS)

Prangishvili, I.V.; Pashchenko, F.F.; Saprykin, E.M.

1989-01-01

Problems related to creation and introduction at NPP of highly efficient and reliable systems for monitoring and control of working processes and intelligence-endowed systems of operator informational support (ISOIS) are considered. The main units included in ISOIS are considered. The main units included in ISOIS are described. The unit of current state monitoring provides information for the operator, which is necessary under concrete conditions for the process monitoring and control, so as to avoid emergencies and affers a program of actions in a dialogue mode for the operator. The identification unit is designed for the obtaining of assessed values of process parameters (neutron fields, temperatures, pressures) and basic equipment (reactivity coefficients, fuel rod weights, time of delay). The prediction unit evaluates the behaviour of process parameters and process state in various situations. 9 refs

42 CFR 493.865 - Standard; Antibody identification.

Science.gov (United States)

2010-10-01

... 42 Public Health 5 2010-10-01 2010-10-01 false Standard; Antibody identification. 493.865 Section..., Or Any Combination of These Tests § 493.865 Standard; Antibody identification. (a) Failure to attain... proficiency testing event. (e) Failure to identify the same antibody in two consecutive or two out of three...

Inadequate Evidence for Multiple Intelligences, Mozart Effect, and Emotional Intelligence Theories

Science.gov (United States)

Waterhouse, Lynn

2006-01-01

I (Waterhouse, 2006) argued that, because multiple intelligences, the Mozart effect, and emotional intelligence theories have inadequate empirical support and are not consistent with cognitive neuroscience findings, these theories should not be applied in education. Proponents countered that their theories had sufficient empirical support, were…

Understanding the Globalization of Intelligence

DEFF Research Database (Denmark)

Svendsen, Adam David Morgan

"This book provides an introduction to the complexities of contemporary Western Intelligence and its dynamics during an era of globalization. Towards an understanding of the globalization of intelligence process, Svendsen focuses on the secretive phenomenon of international or foreign intelligence...... cooperation ('liaison'), as it occurs in both theory and practice. Reflecting a complex coexistence plurality of several different and overlapping concepts in action, the challenging process of the globalization of intelligence emerges as essential for complex issue management purposes during a globalized era...

Bulk and surface event identification in p-type germanium detectors

Science.gov (United States)

Yang, L. T.; Li, H. B.; Wong, H. T.; Agartioglu, M.; Chen, J. H.; Jia, L. P.; Jiang, H.; Li, J.; Lin, F. K.; Lin, S. T.; Liu, S. K.; Ma, J. L.; Sevda, B.; Sharma, V.; Singh, L.; Singh, M. K.; Singh, M. K.; Soma, A. K.; Sonay, A.; Yang, S. W.; Wang, L.; Wang, Q.; Yue, Q.; Zhao, W.

2018-04-01

The p-type point-contact germanium detectors have been adopted for light dark matter WIMP searches and the studies of low energy neutrino physics. These detectors exhibit anomalous behavior to events located at the surface layer. The previous spectral shape method to identify these surface events from the bulk signals relies on spectral shape assumptions and the use of external calibration sources. We report an improved method in separating them by taking the ratios among different categories of in situ event samples as calibration sources. Data from CDEX-1 and TEXONO experiments are re-examined using the ratio method. Results are shown to be consistent with the spectral shape method.

Reliability and Validity of the New Tanaka B Intelligence Scale Scores: A Group Intelligence Test

OpenAIRE

Uno, Yota; Mizukami, Hitomi; Ando, Masahiko; Yukihiro, Ryoji; Iwasaki, Yoko; Ozaki, Norio

2014-01-01

OBJECTIVE: The present study evaluated the reliability and concurrent validity of the new Tanaka B Intelligence Scale, which is an intelligence test that can be administered on groups within a short period of time. METHODS: The new Tanaka B Intelligence Scale and Wechsler Intelligence Scale for Children-Third Edition were administered to 81 subjects (mean age ± SD 15.2 ± 0.7 years) residing in a juvenile detention home; reliability was assessed using Cronbach's alpha coefficient, and concurre...

Hybrid-augmented intelligence:collaboration and cognition

Institute of Scientific and Technical Information of China (English)

Nan-ning ZHENG; Zi-yi LIU; Peng-ju REN; Yong-qiang MA; Shi-tao CHEN; Si-yu YU; Jian-ru XUE

2017-01-01

The long-term goal of artificial intelligence (AI) is to make machines learn and think like human beings. Due to the high levels of uncertainty and vulnerability in human life and the open-ended nature of problems that humans are facing, no matter how intelligent machines are, they are unable to completely replace humans. Therefore, it is necessary to introduce human cognitive capabilities or human-like cognitive models into AI systems to develop a new form of AI, that is, hybrid-augmented intelligence. This form of AI or machine intelligence is a feasible and important developing model. Hybrid-augmented intelligence can be divided into two basic models:one is human-in-the-loop augmented intelligence with human-computer collaboration, and the other is cognitive computing based augmented intelligence, in which a cognitive model is embedded in the machine learning system. This survey describes a basic framework for human-computer collaborative hybrid-augmented intelligence, and the basic elements of hybrid-augmented intelligence based on cognitive computing. These elements include intuitive reasoning, causal models, evolution of memory and knowledge, especially the role and basic principles of intuitive reasoning for complex problem solving, and the cognitive learning framework for visual scene understanding based on memory and reasoning. Several typical applications of hybrid-augmented intelligence in related fields are given.

Applying Intelligent Algorithms to Automate the Identification of Error Factors.

Science.gov (United States)

Jin, Haizhe; Qu, Qingxing; Munechika, Masahiko; Sano, Masataka; Kajihara, Chisato; Duffy, Vincent G; Chen, Han

2018-05-03

Medical errors are the manifestation of the defects occurring in medical processes. Extracting and identifying defects as medical error factors from these processes are an effective approach to prevent medical errors. However, it is a difficult and time-consuming task and requires an analyst with a professional medical background. The issues of identifying a method to extract medical error factors and reduce the extraction difficulty need to be resolved. In this research, a systematic methodology to extract and identify error factors in the medical administration process was proposed. The design of the error report, extraction of the error factors, and identification of the error factors were analyzed. Based on 624 medical error cases across four medical institutes in both Japan and China, 19 error-related items and their levels were extracted. After which, they were closely related to 12 error factors. The relational model between the error-related items and error factors was established based on a genetic algorithm (GA)-back-propagation neural network (BPNN) model. Additionally, compared to GA-BPNN, BPNN, partial least squares regression and support vector regression, GA-BPNN exhibited a higher overall prediction accuracy, being able to promptly identify the error factors from the error-related items. The combination of "error-related items, their different levels, and the GA-BPNN model" was proposed as an error-factor identification technology, which could automatically identify medical error factors.

Intelligent indexing

International Nuclear Information System (INIS)

Farkas, J.

1992-01-01

In this paper we discuss the relevance of artificial intelligence to the automatic indexing of natural language text. We describe the use of domain-specific semantically-based thesauruses and address the problem of creating adequate knowledge bases for intelligent indexing systems. We also discuss the relevance of the Hilbert space ι 2 to the compact representation of documents and to the definition of the similarity of natural language texts. (author). 17 refs., 2 figs

Intelligent indexing

Energy Technology Data Exchange (ETDEWEB)