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

DFB laser array driver circuit controlled by adjustable signal

Science.gov (United States)

Du, Weikang; Du, Yinchao; Guo, Yu; Li, Wei; Wang, Hao

2018-01-01

In order to achieve the intelligent controlling of DFB laser array, this paper presents the design of an intelligence and high precision numerical controlling electric circuit. The system takes MCU and FPGA as the main control chip, with compact, high-efficiency, no impact, switching protection characteristics. The output of the DFB laser array can be determined by an external adjustable signal. The system transforms the analog control model into a digital control model, which improves the performance of the driver. The system can monitor the temperature and current of DFB laser array in real time. The output precision of the current can reach ± 0.1mA, which ensures the stable and reliable operation of the DFB laser array. Such a driver can benefit the flexible usage of the DFB laser array.

A learning-based autonomous driver: emulate human driver's intelligence in low-speed car following

Science.gov (United States)

Wei, Junqing; Dolan, John M.; Litkouhi, Bakhtiar

2010-04-01

In this paper, an offline learning mechanism based on the genetic algorithm is proposed for autonomous vehicles to emulate human driver behaviors. The autonomous driving ability is implemented based on a Prediction- and Cost function-Based algorithm (PCB). PCB is designed to emulate a human driver's decision process, which is modeled as traffic scenario prediction and evaluation. This paper focuses on using a learning algorithm to optimize PCB with very limited training data, so that PCB can have the ability to predict and evaluate traffic scenarios similarly to human drivers. 80 seconds of human driving data was collected in low-speed (car-following scenarios. In the low-speed car-following tests, PCB was able to perform more human-like carfollowing after learning. A more general 120 kilometer-long simulation showed that PCB performs robustly even in scenarios that are not part of the training set.

Modeling of Driver Steering Operations in Lateral Wind Disturbances toward Driver Assistance System

Science.gov (United States)

Kurata, Yoshinori; Wada, Takahiro; Kamiji, Norimasa; Doi, Shun'ichi

Disturbances decrease vehicle stability and increase driver's mental and physical workload. Especially unexpected disturbances such as lateral winds have severe effect on vehicle stability and driver's workload. This study aims at building a driver model of steering operations in lateral wind toward developing effective driver assistance system. First, the relationship between the driver's lateral motion and its reactive quick steering behavior is investigated using driving simulator with lateral 1dof motion. In the experiments, four different wind patterns are displayed by the simulator. As the results, strong correlation was found between the driver's head lateral jerk by the lateral disturbance and the angular acceleration of the steering wheel. Then, we build a mathematical model of driver's steering model from lateral disturbance input to steering torque of the reactive quick feed-forward steering based on the experimental results. Finally, validity of the proposed model is shown by comparing the steering torque of experimental results and that of simulation results.

Driver's Behavior Modeling Using Fuzzy Logic

Directory of Open Access Journals (Sweden)

Sehraneh Ghaemi

2010-01-01

Full Text Available In this study, we propose a hierarchical fuzzy system for human in a driver-vehicle-environment system to model takeover by different drivers. The driver's behavior is affected by the environment. The climate, road and car conditions are included in fuzzy modeling. For obtaining fuzzy rules, experts' opinions are benefited by means of questionnaires on effects of parameters such as climate, road and car conditions on driving capabilities. Also the precision, age and driving individuality are used to model the driver's behavior. Three different positions are considered for driving and decision making. A fuzzy model called Model I is presented for modeling the change of steering angle and speed control by considering time distances with existing cars in these three positions, the information about the speed and direction of car, and the steering angle of car. Also we obtained two other models based on fuzzy rules called Model II and Model III by using Sugeno fuzzy inference. Model II and Model III have less linguistic terms than Model I for the steering angle and direction of car. The results of three models are compared for a driver who drives based on driving laws.

Driver steering model for closed-loop steering function analysis

Science.gov (United States)

Bolia, Pratiksh; Weiskircher, Thomas; Müller, Steffen

2014-05-01

In this paper, a two level preview driver steering control model for the use in numerical vehicle dynamics simulation is introduced. The proposed model is composed of cascaded control loops: The outer loop is the path following layer based on potential field framework. The inner loop tries to capture the driver's physical behaviour. The proposed driver model allows easy implementation of different driving situations to simulate a wide range of different driver types, moods and vehicle types. The expediency of the proposed driver model is shown with the help of developed driver steering assist (DSA) function integrated with a conventional series production (Electric Power steering System with rack assist servo unit) system. With the help of the DSA assist function, the driver is prevented from over saturating the front tyre forces and loss of stability and controllability during cornering. The simulation results show different driver reactions caused by the change in the parameters or properties of the proposed driver model if the DSA assist function is activated. Thus, the proposed driver model is useful for the advanced driver steering and vehicle stability assist function evaluation in the early stage of vehicle dynamics handling and stability evaluation.

Modeling of driver's collision avoidance maneuver based on controller switching model.

Science.gov (United States)

Kim, Jong-Hae; Hayakawa, Soichiro; Suzuki, Tatsuya; Hayashi, Koji; Okuma, Shigeru; Tsuchida, Nuio; Shimizu, Masayuki; Kido, Shigeyuki

2005-12-01

This paper presents a modeling strategy of human driving behavior based on the controller switching model focusing on the driver's collision avoidance maneuver. The driving data are collected by using the three-dimensional (3-D) driving simulator based on the CAVE Automatic Virtual Environment (CAVE), which provides stereoscopic immersive virtual environment. In our modeling, the control scenario of the human driver, that is, the mapping from the driver's sensory information to the operation of the driver such as acceleration, braking, and steering, is expressed by Piecewise Polynomial (PWP) model. Since the PWP model includes both continuous behaviors given by polynomials and discrete logical conditions, it can be regarded as a class of Hybrid Dynamical System (HDS). The identification problem for the PWP model is formulated as the Mixed Integer Linear Programming (MILP) by transforming the switching conditions into binary variables. From the obtained results, it is found that the driver appropriately switches the "control law" according to the sensory information. In addition, the driving characteristics of the beginner driver and the expert driver are compared and discussed. These results enable us to capture not only the physical meaning of the driving skill but the decision-making aspect (switching conditions) in the driver's collision avoidance maneuver as well.

Traffic Safety through Driver Assistance and Intelligence

Directory of Open Access Journals (Sweden)

Heiner Bubb

2011-05-01

BMW, Daimler, Audi, Citroen, Lexus, VW, Opel, Peugeot, Renault, Chevrolet, Saab and Bosch. Both the contributions of research work concerning driving behavior analysis and driver assistance systems have to be aligned with a permanently updated interaction within the system of driver, vehicle and road traffic environment.

Determinants and Drivers of Infectious Disease Threat Events in Europe.

Science.gov (United States)

Semenza, Jan C; Lindgren, Elisabet; Balkanyi, Laszlo; Espinosa, Laura; Almqvist, My S; Penttinen, Pasi; Rocklöv, Joacim

2016-04-01

Infectious disease threat events (IDTEs) are increasing in frequency worldwide. We analyzed underlying drivers of 116 IDTEs detected in Europe during 2008-2013 by epidemic intelligence at the European Centre of Disease Prevention and Control. Seventeen drivers were identified and categorized into 3 groups: globalization and environment, sociodemographic, and public health systems. A combination of >2 drivers was responsible for most IDTEs. The driver category globalization and environment contributed to 61% of individual IDTEs, and the top 5 individual drivers of all IDTEs were travel and tourism, food and water quality, natural environment, global trade, and climate. Hierarchical cluster analysis of all drivers identified travel and tourism as a distinctly separate driver. Monitoring and modeling such disease drivers can help anticipate future IDTEs and strengthen control measures. More important, intervening directly on these underlying drivers can diminish the likelihood of the occurrence of an IDTE and reduce the associated human and economic costs.

An Overview on Study of Identification of Driver Behavior Characteristics for Automotive Control

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Na Lin

2014-01-01

Full Text Available Driver characteristics have been the research focus for automotive control. Study on identification of driver characteristics is provided in this paper in terms of its relevant research directions and key technologies involved. This paper discusses the driver characteristics based on driver’s operation behavior, or the driver behavior characteristics. Following the presentation of the fundamental of the driver behavior characteristics, the key technologies of the driver behavior characteristics are reviewed in detail, including classification and identification methods of the driver behavior characteristics, experimental design and data acquisition, and model adaptation. Moreover, this paper discusses applications of the identification of the driver behavior characteristics which has been applied to the intelligent driver advisory system, the driver safety warning system, and the vehicle dynamics control system. At last, some ideas about the future work are concluded.

Driver's mental workload prediction model based on physiological indices.

Science.gov (United States)

Yan, Shengyuan; Tran, Cong Chi; Wei, Yingying; Habiyaremye, Jean Luc

2017-09-15

Developing an early warning model to predict the driver's mental workload (MWL) is critical and helpful, especially for new or less experienced drivers. The present study aims to investigate the correlation between new drivers' MWL and their work performance, regarding the number of errors. Additionally, the group method of data handling is used to establish the driver's MWL predictive model based on subjective rating (NASA task load index [NASA-TLX]) and six physiological indices. The results indicate that the NASA-TLX and the number of errors are positively correlated, and the predictive model shows the validity of the proposed model with an R 2 value of 0.745. The proposed model is expected to provide a reference value for the new drivers of their MWL by providing the physiological indices, and the driving lesson plans can be proposed to sustain an appropriate MWL as well as improve the driver's work performance.

A Driver Behavior Learning Framework for Enhancing Traffic Simulation

Directory of Open Access Journals (Sweden)

Ramona Maria Paven

2014-06-01

Full Text Available Traffic simulation provides an essential support for developing intelligent transportation systems. It allows affordable validation of such systems using a large variety of scenarios that involves massive data input. However, realistic traffic models are hard to be implemented especially for microscopic traffic simulation. One of the hardest problems in this context is to model the behavior of drivers, due the complexity of human nature. The work presented in this paper proposes a framework for learning driver behavior based on a Hidden Markov Model technique. Moreover, we propose also a practical method to inject this behavior in a traffic model used by the SUMO traffic simulator. To demonstrate the effectiveness of this method we present a case study involving real traffic collected from Timisoara city area.

Lane-changing model with dynamic consideration of driver's propensity

Science.gov (United States)

Wang, Xiaoyuan; Wang, Jianqiang; Zhang, Jinglei; Ban, Xuegang Jeff

2015-07-01

Lane-changing is the driver's selection result of the satisfaction degree in different lane driving conditions. There are many different factors influencing lane-changing behavior, such as diversity, randomicity and difficulty of measurement. So it is hard to accurately reflect the uncertainty of drivers' lane-changing behavior. As a result, the research of lane-changing models is behind that of car-following models. Driver's propensity is her/his emotion state or the corresponding preference of a decision or action toward the real objective traffic situations under the influence of various dynamic factors. It represents the psychological characteristics of the driver in the process of vehicle operation and movement. It is an important factor to influence lane-changing. In this paper, dynamic recognition of driver's propensity is considered during simulation based on its time-varying discipline and the analysis of the driver's psycho-physic characteristics. The Analytic Hierarchy Process (AHP) method is used to quantify the hierarchy of driver's dynamic lane-changing decision-making process, especially the influence of the propensity. The model is validated using real data. Test results show that the developed lane-changing model with the dynamic consideration of a driver's time-varying propensity and the AHP method are feasible and with improved accuracy.

Student Modeling in an Intelligent Tutoring System

Science.gov (United States)

1996-12-17

Multi-Agent Architecture." Advances in Artificial Intelligence : Proceedings of the 12 th Brazilian Symposium on Aritificial Intelligence , edited by...STUDENT MODELING IN AN INTELLIGENT TUTORING SYSTEM THESIS Jeremy E. Thompson Captain, USAF AFIT/GCS/ENG/96D-27 DIMTVMON* fCKAJWINT A Appr"v*d t=i...Air Force Base, Ohio AFIT/GCS/ENG/96D-27 STUDENT MODELING IN AN INTELLIGENT TUTORING SYSTEM THESIS Jeremy E. Thompson Captain, USAF AFIT/GCS/ENG/96D

Driver's behavioural changes with new intelligent transport system interventions at railway level crossings--A driving simulator study.

Science.gov (United States)

Larue, Grégoire S; Kim, Inhi; Rakotonirainy, Andry; Haworth, Narelle L; Ferreira, Luis

2015-08-01

Improving safety at railway level crossings is an important issue for the Australian transport system. Governments, the rail industry and road organisations have tried a variety of countermeasures for many years to improve railway level crossing safety. New types of intelligent transport system (ITS) interventions are now emerging due to the availability and the affordability of technology. These interventions target both actively and passively protected railway level crossings and attempt to address drivers' errors at railway crossings, which are mainly a failure to detect the crossing or the train and misjudgement of the train approach speed and distance. This study aims to assess the effectiveness of three emerging ITS that the rail industry considers implementing in Australia: a visual in-vehicle ITS, an audio in-vehicle ITS, as well as an on-road flashing beacons intervention. The evaluation was conducted on an advanced driving simulator with 20 participants per trialled technology, each participant driving once without any technology and once with one of the ITS interventions. Every participant drove through a range of active and passive crossings with and without trains approaching. Their speed approach of the crossing, head movements and stopping compliance were measured. Results showed that driver behaviour was changed with the three ITS interventions at passive crossings, while limited effects were found at active crossings, even with reduced visibility. The on-road intervention trialled was unsuccessful in improving driver behaviour; the audio and visual ITS improved driver behaviour when a train was approaching. A trend toward worsening driver behaviour with the visual ITS was observed when no trains were approaching. This trend was not observed for the audio ITS intervention, which appears to be the ITS intervention with the highest potential for improving safety at passive crossings. Copyright © 2015 Elsevier Ltd. All rights reserved.

Automatic intelligent cruise control

OpenAIRE

Stanton, NA; Young, MS

2006-01-01

This paper reports a study on the evaluation of automatic intelligent cruise control (AICC) from a psychological perspective. It was anticipated that AICC would have an effect upon the psychology of driving—namely, make the driver feel like they have less control, reduce the level of trust in the vehicle, make drivers less situationally aware, but might reduce the workload and make driving might less stressful. Drivers were asked to drive in a driving simulator under manual and automatic inte...

A measurement model of multiple intelligence profiles of management graduates

Science.gov (United States)

Krishnan, Heamalatha; Awang, Siti Rahmah

2017-05-01

In this study, developing a fit measurement model and identifying the best fitting items to represent Howard Gardner's nine intelligences namely, musical intelligence, bodily-kinaesthetic intelligence, mathematical/logical intelligence, visual/spatial intelligence, verbal/linguistic intelligence, interpersonal intelligence, intrapersonal intelligence, naturalist intelligence and spiritual intelligence are the main interest in order to enhance the opportunities of the management graduates for employability. In order to develop a fit measurement model, Structural Equation Modeling (SEM) was applied. A psychometric test which is the Ability Test in Employment (ATIEm) was used as the instrument to measure the existence of nine types of intelligence of 137 University Teknikal Malaysia Melaka (UTeM) management graduates for job placement purposes. The initial measurement model contains nine unobserved variables and each unobserved variable is measured by ten observed variables. Finally, the modified measurement model deemed to improve the Normed chi-square (NC) = 1.331; Incremental Fit Index (IFI) = 0.940 and Root Mean Square of Approximation (RMSEA) = 0.049 was developed. The findings showed that the UTeM management graduates possessed all nine intelligences either high or low. Musical intelligence, mathematical/logical intelligence, naturalist intelligence and spiritual intelligence contributed highest loadings on certain items. However, most of the intelligences such as bodily kinaesthetic intelligence, visual/spatial intelligence, verbal/linguistic intelligence interpersonal intelligence and intrapersonal intelligence possessed by UTeM management graduates are just at the borderline.

Theoretical models of drivers behavior on the road

Directory of Open Access Journals (Sweden)

Marcin Piotr Biernacki

2017-06-01

Full Text Available Understanding of mechanisms and factors responsible for the driver behavior on the road is the subject of ongoing interest to transportation psychologists, occupational doctors and engineers. Models of driver behavior are a key point for the understanding the mechanisms and factors which may cause limitations to the optimal functioning on the road. They also systematize knowledge about the factors responsible for the behavior of the driver and thus constitute a starting point for formulating empirical or diagnostic hypotheses. The aim of this study is to present models of driver behavior from the descriptive and functional perspectives. Med Pr 2017;68(3:401–411

The Drivers of Success in Business Model Transformation

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Nenad Savič

2016-01-01

Full Text Available Existing empirical literature on business models is still inconclusive about the key drivers of successful business model transformation. The paper explores this issue by using a single longitudinal case study design in combination with grounded theory approach on a medium-sized, high-tech and globally oriented company. Based on on-site visits, interviews and secondary documentation data analysis, the study identifies six generic drivers of successful business model transformation: transformational leadership, discovery driven decision-making, industry improvement – customer specific orientation, content-oriented communication, self-initiative collaborators, and phased separation strategy. The new drivers supplement our existing knowledge on how successful transformation takes place and add to existing drivers, while extensive discussion of their implications may help the managers to execute business transformations more effectively.

Exploratory multinomial logit model-based driver injury severity analyses for teenage and adult drivers in intersection-related crashes.

Science.gov (United States)

Wu, Qiong; Zhang, Guohui; Ci, Yusheng; Wu, Lina; Tarefder, Rafiqul A; Alcántara, Adélamar Dely

2016-05-18

Teenage drivers are more likely to be involved in severely incapacitating and fatal crashes compared to adult drivers. Moreover, because two thirds of urban vehicle miles traveled are on signal-controlled roadways, significant research efforts are needed to investigate intersection-related teenage driver injury severities and their contributing factors in terms of driver behavior, vehicle-infrastructure interactions, environmental characteristics, roadway geometric features, and traffic compositions. Therefore, this study aims to explore the characteristic differences between teenage and adult drivers in intersection-related crashes, identify the significant contributing attributes, and analyze their impacts on driver injury severities. Using crash data collected in New Mexico from 2010 to 2011, 2 multinomial logit regression models were developed to analyze injury severities for teenage and adult drivers, respectively. Elasticity analyses and transferability tests were conducted to better understand the quantitative impacts of these factors and the teenage driver injury severity model's generality. The results showed that although many of the same contributing factors were found to be significant in the both teenage and adult driver models, certain different attributes must be distinguished to specifically develop effective safety solutions for the 2 driver groups. The research findings are helpful to better understand teenage crash uniqueness and develop cost-effective solutions to reduce intersection-related teenage injury severities and facilitate driver injury mitigation research.

Study on driver model for hybrid truck based on driving simulator experimental results

Directory of Open Access Journals (Sweden)

Dam Hoang Phuc

2018-04-01

Full Text Available In this paper, a proposed car-following driver model taking into account some features of both the compensatory and anticipatory model representing the human pedal operation has been verified by driving simulator experiments with several real drivers. The comparison between computer simulations performed by determined model parameters with the experimental results confirm the correctness of this mathematical driver model and identified model parameters. Then the driver model is joined to a hybrid vehicle dynamics model and the moderate car following maneuver simulations with various driver parameters are conducted to investigate influences of driver parameters on vehicle dynamics response and fuel economy. Finally, major driver parameters involved in the longitudinal control of drivers are clarified. Keywords: Driver model, Driver-vehicle closed-loop system, Car Following, Driving simulator/hybrid electric vehicle (B1

Testing a structural model of young driver willingness to uptake Smartphone Driver Support Systems.

Science.gov (United States)

Kervick, Aoife A; Hogan, Michael J; O'Hora, Denis; Sarma, Kiran M

2015-10-01

There is growing interest in the potential value of using phone applications that can monitor driver behaviour (Smartphone Driver Support Systems, 'SDSSs') in mitigating risky driving by young people. However, their value in this regard will only be realised if young people are willing to use this technology. This paper reports the findings of a study in which a novel structural model of willingness to use SDSSs was tested. Grounded in the driver monitoring and Technology Acceptance (TA) research literature, the model incorporates the perceived risks and gains associated with potential SDSS usage and additional social cognitive factors, including perceived usability and social influences. A total of 333 smartphone users, aged 18-24, with full Irish driving licenses completed an online questionnaire examining willingness or Behavioural Intention (BI) to uptake a SDSS. Following exploratory and confirmatory factor analyses, structural equation modelling indicated that perceived gains and social influence factors had significant direct effects on BI. Perceived risks and social influence also had significant indirect effects on BI, as mediated by perceived gains. Overall, this model accounted for 72.5% of the variance in willingness to uptake SDSSs. Multi-group structural models highlighted invariance of effects across gender, high and low risk drivers, and those likely or unlikely to adopt novel phone app technologies. These findings have implications for our understanding of the willingness of young drivers to adopt and use SDSSs, and highlight potential factors that could be targeted in behavioural change interventions seeking to improve usage rates. Copyright © 2015 Elsevier Ltd. All rights reserved.

FORMALIZATION OF LOCOMOTIVE DRIVER ACTIVITY TENSION INDICATOR BASED ON THE ERGONOMIC MODEL

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O. M. Horobchenko

2017-02-01

Full Text Available Purpose. A key factor contributing to the safety and quality of ergatic system "train-driver" is the intensity of the locomotive crew’s work. The aim of this work is formalization of locomotive driver activity tension indicator. Methodology. One of the characteristics of driver activity tension is the difference between the time allotted to complete the task, and the necessary (external reserve or deficiency time. The sets of major and minor operations in the management of the train locomotive in different train situations were identified. Using the methods of fuzzy logic, the concept of "materiality of the operation of the locomotive control" is presented in the form of a set of linguistic variables. To determine the function membership of the elements of the set "the importance of the operation of the locomotive control" the method of expert evaluations was used. Coefficient of temporary tension is presented in the form of fuzzy number L-R-type. Findings. It was found the value of the relative number of operations of locomotive control according to the distribution using the parameter of operation "importance". To determine the most tensioned mode of the driver ranking the traffic condition according to the parameter of relative amounts of the important management operations was conducted. The most difficult modes are the "front hindrance", "movement in unfavorable weather conditions" and "departure from the station to the running line". Originality. The introduction of the value "conventional importance of the operation" allowed us to more accurately describe the terms of train driving. For the first time the work presents determination of tension of the driver’s work in the form of a unimodal fuzzy number, which will make it possible to use the methods of the theory of artificial intelligence to simulate activity of the locomotive driver and develop intelligent control systems. Practical value. There were obtained the opportunity to

The smartphone and the driver's cognitive workload: A comparison of Apple, Google, and Microsoft's intelligent personal assistants.

Science.gov (United States)

Strayer, David L; Cooper, Joel M; Turrill, Jonna; Coleman, James R; Hopman, Rachel J

2017-06-01

The goal of this research was to examine the impact of voice-based interactions using 3 different intelligent personal assistants (Apple's Siri , Google's Google Now for Android phones, and Microsoft's Cortana ) on the cognitive workload of the driver. In 2 experiments using an instrumented vehicle on suburban roadways, we measured the cognitive workload of drivers when they used the voice-based features of each smartphone to place a call, select music, or send text messages. Cognitive workload was derived from primary task performance through video analysis, secondary-task performance using the Detection Response Task (DRT), and subjective mental workload. We found that workload was significantly higher than that measured in the single-task drive. There were also systematic differences between the smartphones: The Google system placed lower cognitive demands on the driver than the Apple and Microsoft systems, which did not differ. Video analysis revealed that the difference in mental workload between the smartphones was associated with the number of system errors, the time to complete an action, and the complexity and intuitiveness of the devices. Finally, surprisingly high levels of cognitive workload were observed when drivers were interacting with the devices: "on-task" workload measures did not systematically differ from that associated with a mentally demanding Operation Span (OSPAN) task. The analysis also found residual costs associated using each of the smartphones that took a significant time to dissipate. The data suggest that caution is warranted in the use of smartphone voice-based technology in the vehicle because of the high levels of cognitive workload associated with these interactions. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Visual behaviour analysis and driver cognitive model

Energy Technology Data Exchange (ETDEWEB)

Baujon, J.; Basset, M.; Gissinger, G.L. [Mulhouse Univ., (France). MIPS/MIAM Lab.

2001-07-01

Recent studies on driver behaviour have shown that perception - mainly visual but also proprioceptive perception - plays a key role in the ''driver-vehicle-road'' system and so considerably affects the driver's decision making. Within the framework of the behaviour analysis and studies low-cost system (BASIL), this paper presents a correlative, qualitative and quantitative study, comparing the information given by visual perception and by the trajectory followed. This information will help to obtain a cognitive model of the Rasmussen type according to different driver classes. Many experiments in real driving situations have been carried out for different driver classes and for a given trajectory profile, using a test vehicle and innovative, specially designed, real-time tools, such as the vision system or the positioning module. (orig.)

Intelligent structural optimization: Concept, Model and Methods

International Nuclear Information System (INIS)

Lu, Dagang; Wang, Guangyuan; Peng, Zhang

2002-01-01

Structural optimization has many characteristics of Soft Design, and so, it is necessary to apply the experience of human experts to solving the uncertain and multidisciplinary optimization problems in large-scale and complex engineering systems. With the development of artificial intelligence (AI) and computational intelligence (CI), the theory of structural optimization is now developing into the direction of intelligent optimization. In this paper, a concept of Intelligent Structural Optimization (ISO) is proposed. And then, a design process model of ISO is put forward in which each design sub-process model are discussed. Finally, the design methods of ISO are presented

Modeling taxi driver anticipatory behavior

NARCIS (Netherlands)

Zheng, Zhong; Rasouli, S.; Timmermans, H.J.P.

2018-01-01

As part of a wider behavioral agent-based model that simulates taxi drivers’ dynamic passenger-finding behavior under uncertainty, we present a model of strategic behavior of taxi drivers in anticipation of substantial time varying demand at locations such as airports and major train stations. The

Situational Factors of Influencing Drivers to Give Precedence to Jaywalking Pedestrians at Signalized Crosswalk

Directory of Open Access Journals (Sweden)

Xiaobei Jiang

2011-12-01

Full Text Available A large number of fatalities are caused by the vehicle-pedestrian accidents. Under a potential conflict between the vehicle and jaywalking pedestrian, giving precedence to the pedestrian will be a proper decision taken by the driver to avoid collision. Field traffic data has been collected by video recording and image processing at two signalized crosswalks. Vehicle speed performance in the single vehicle-pedestrian encounter and platoon vehicle-pedestrian encounter were analyzed for understanding the driver behavior in the conflict process. Binary logic model was proposed to estimate the drivers' giving precedence influenced by the situational factors and the model was validated to predict the drivers' choices accurately. The vehicle speed, pedestrian speed, pedestrian lateral distance and the vehicle longitudinal distance to the conflict point were proved to affect the drivers' choices in platoon driving. The research results would hopefully be helpful to the design of intelligent vehicles and pedestrian protection systems by the knowledge-based decision making process.

Design, Modelling, and Implementation of a Fuzzy Controller for an Intelligent Road Signaling System

Directory of Open Access Journals (Sweden)

José Manuel Lozano Domínguez

2018-01-01

Full Text Available Crossing points are not always 100% visible for drivers due to different factors (e.g., poor road maintenance, occlusion of vertical signs, and adverse weather conditions. USA estimated in 2015 the number of traffic accidents involving pedestrians and vehicles in 70,000 of whom 5,376 resulted in deceased people. To contribute in this field, this paper presents the design, implementation, and testing of a smart prototype system applied to pedestrian crossings—not regulated by semaphores—which try to reduce the accident rate on roads. The hardware and software system consists of a set of autonomous, intelligent, and wireless low-cost devices that generate a visual warning barrier perceived by drivers from a suitable distance when pedestrians traverse a crosswalk. In this way, drivers can reduce the speed of their vehicles and stop safely. The system’s intelligence is carried out by a fuzzy controller that performs sensory fusion at both low level and high level with various types of sensors from local and neighboring devices. The tests conducted have determined an average success of 94.64% and a precision of 100%, thus corresponding with a very good test according to a ROC analysis. As a result, the system proposed has been patented and extended to international PCT.

Analyzing Vehicle Fuel Saving Opportunities through Intelligent Driver Feedback

Energy Technology Data Exchange (ETDEWEB)

Gonder, J.; Earleywine, M.; Sparks, W.

2012-06-01

Driving style changes, e.g., improving driver efficiency and motivating driver behavior changes, could deliver significant petroleum savings. This project examines eliminating stop-and-go driving and unnecessary idling, and also adjusting acceleration rates and cruising speeds to ideal levels to quantify fuel savings. Such extreme adjustments can result in dramatic fuel savings of over 30%, but would in reality only be achievable through automated control of vehicles and traffic flow. In real-world driving, efficient driving behaviors could reduce fuel use by 20% on aggressively driven cycles and by 5-10% on more moderately driven trips. A literature survey was conducted of driver behavior influences, and pertinent factors from on-road experiments with different driving styles were observed. This effort highlighted important driver influences such as surrounding vehicle behavior, anxiety over trying to get somewhere quickly, and the power/torque available from the vehicle. Existing feedback approaches often deliver efficiency information and instruction. Three recommendations for maximizing fuel savings from potential drive cycle improvement are: (1) leveraging applications with enhanced incentives, (2) using an approach that is easy and widely deployable to motivate drivers, and (3) utilizing connected vehicle and automation technologies to achieve large and widespread efficiency improvements.

Modeling intelligent adversaries for terrorism risk assessment: some necessary conditions for adversary models.

Science.gov (United States)

Guikema, Seth

2012-07-01

Intelligent adversary modeling has become increasingly important for risk analysis, and a number of different approaches have been proposed for incorporating intelligent adversaries in risk analysis models. However, these approaches are based on a range of often-implicit assumptions about the desirable properties of intelligent adversary models. This "Perspective" paper aims to further risk analysis for situations involving intelligent adversaries by fostering a discussion of the desirable properties for these models. A set of four basic necessary conditions for intelligent adversary models is proposed and discussed. These are: (1) behavioral accuracy to the degree possible, (2) computational tractability to support decision making, (3) explicit consideration of uncertainty, and (4) ability to gain confidence in the model. It is hoped that these suggested necessary conditions foster discussion about the goals and assumptions underlying intelligent adversary modeling in risk analysis. © 2011 Society for Risk Analysis.

Steering disturbance rejection using a physics-based neuromusculoskeletal driver model

Science.gov (United States)

Mehrabi, Naser; Sharif Razavian, Reza; McPhee, John

2015-10-01

The aim of this work is to develop a comprehensive yet practical driver model to be used in studying driver-vehicle interactions. Drivers interact with their vehicle and the road through the steering wheel. This interaction forms a closed-loop coupled human-machine system, which influences the driver's steering feel and control performance. A hierarchical approach is proposed here to capture the complexity of the driver's neuromuscular dynamics and the central nervous system in the coordination of the driver's upper extremity activities, especially in the presence of external disturbance. The proposed motor control framework has three layers: the first (or the path planning) plans a desired vehicle trajectory and the required steering angles to perform the desired trajectory; the second (or the musculoskeletal controller) actuates the musculoskeletal arm to rotate the steering wheel accordingly; and the final layer ensures the precision control and disturbance rejection of the motor control units. The physics-based driver model presented here can also provide insights into vehicle control in relaxed and tensed driving conditions, which are simulated by adjusting the driver model parameters such as cognition delay and muscle co-contraction dynamics.

Computational Intelligence, Cyber Security and Computational Models

CERN Document Server

Anitha, R; Lekshmi, R; Kumar, M; Bonato, Anthony; Graña, Manuel

2014-01-01

This book contains cutting-edge research material presented by researchers, engineers, developers, and practitioners from academia and industry at the International Conference on Computational Intelligence, Cyber Security and Computational Models (ICC3) organized by PSG College of Technology, Coimbatore, India during December 19–21, 2013. The materials in the book include theory and applications for design, analysis, and modeling of computational intelligence and security. The book will be useful material for students, researchers, professionals, and academicians. It will help in understanding current research trends and findings and future scope of research in computational intelligence, cyber security, and computational models.

Advanced Emergency Braking Control Based on a Nonlinear Model Predictive Algorithm for Intelligent Vehicles

Directory of Open Access Journals (Sweden)

Ronghui Zhang

2017-05-01

Full Text Available Focusing on safety, comfort and with an overall aim of the comprehensive improvement of a vision-based intelligent vehicle, a novel Advanced Emergency Braking System (AEBS is proposed based on Nonlinear Model Predictive Algorithm. Considering the nonlinearities of vehicle dynamics, a vision-based longitudinal vehicle dynamics model is established. On account of the nonlinear coupling characteristics of the driver, surroundings, and vehicle itself, a hierarchical control structure is proposed to decouple and coordinate the system. To avoid or reduce the collision risk between the intelligent vehicle and collision objects, a coordinated cost function of tracking safety, comfort, and fuel economy is formulated. Based on the terminal constraints of stable tracking, a multi-objective optimization controller is proposed using the theory of non-linear model predictive control. To quickly and precisely track control target in a finite time, an electronic brake controller for AEBS is designed based on the Nonsingular Fast Terminal Sliding Mode (NFTSM control theory. To validate the performance and advantages of the proposed algorithm, simulations are implemented. According to the simulation results, the proposed algorithm has better integrated performance in reducing the collision risk and improving the driving comfort and fuel economy of the smart car compared with the existing single AEBS.

Emotional intelligence is a second-stratum factor of intelligence: evidence from hierarchical and bifactor models.

Science.gov (United States)

MacCann, Carolyn; Joseph, Dana L; Newman, Daniel A; Roberts, Richard D

2014-04-01

This article examines the status of emotional intelligence (EI) within the structure of human cognitive abilities. To evaluate whether EI is a 2nd-stratum factor of intelligence, data were fit to a series of structural models involving 3 indicators each for fluid intelligence, crystallized intelligence, quantitative reasoning, visual processing, and broad retrieval ability, as well as 2 indicators each for emotion perception, emotion understanding, and emotion management. Unidimensional, multidimensional, hierarchical, and bifactor solutions were estimated in a sample of 688 college and community college students. Results suggest adequate fit for 2 models: (a) an oblique 8-factor model (with 5 traditional cognitive ability factors and 3 EI factors) and (b) a hierarchical solution (with cognitive g at the highest level and EI representing a 2nd-stratum factor that loads onto g at λ = .80). The acceptable relative fit of the hierarchical model confirms the notion that EI is a group factor of cognitive ability, marking the expression of intelligence in the emotion domain. The discussion proposes a possible expansion of Cattell-Horn-Carroll theory to include EI as a 2nd-stratum factor of similar standing to factors such as fluid intelligence and visual processing.

Intelligent Metering for Urban Water: A Review

OpenAIRE

Rodney Stewart; Stuart White; Candice Moy; Ariane Liu; Pierre Mukheibir; Damien Giurco; Thomas Boyle

2013-01-01

This paper reviews the drivers, development and global deployment of intelligent water metering in the urban context. Recognising that intelligent metering (or smart metering) has the potential to revolutionise customer engagement and management of urban water by utilities, this paper provides a summary of the knowledge-base for researchers and industry practitioners to ensure that the technology fosters sustainable urban water management. To date, roll-outs of intelligent metering have been ...

Business process intelligence

NARCIS (Netherlands)

Castellanos, M.; Alves De Medeiros, A.K.; Mendling, J.; Weber, B.; Weijters, A.J.M.M.; Cardoso, J.; Aalst, van der W.M.P.

2009-01-01

Business Process Intelligence (BPI,) is an emerging area that is getting increasingly popularfor enterprises. The need to improve business process efficiency, to react quickly to changes and to meet regulatory compliance is among the main drivers for BPI. BPI refers to the application of Business

Life system modeling and intelligent computing. Pt. I. Proceedings

Energy Technology Data Exchange (ETDEWEB)

Li, Kang; Irwin, George W. (eds.) [Belfast Queen' s Univ. (United Kingdom). School of Electronics, Electrical Engineering and Computer Science; Fei, Minrui; Jia, Li [Shanghai Univ. (China). School of Mechatronical Engineering and Automation

2010-07-01

This book is part I of a two-volume work that contains the refereed proceedings of the International Conference on Life System Modeling and Simulation, LSMS 2010 and the International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2010, held in Wuxi, China, in September 2010. The 194 revised full papers presented were carefully reviewed and selected from over 880 submissions and recommended for publication by Springer in two volumes of Lecture Notes in Computer Science (LNCS) and one volume of Lecture Notes in Bioinformatics (LNBI). This particular volume of Lecture Notes in Computer Science (LNCS) includes 55 papers covering 7 relevant topics. The 55 papers in this volume are organized in topical sections on intelligent modeling, monitoring, and control of complex nonlinear systems; autonomy-oriented computing and intelligent agents; advanced theory and methodology in fuzzy systems and soft computing; computational intelligence in utilization of clean and renewable energy resources; intelligent modeling, control and supervision for energy saving and pollution reduction; intelligent methods in developing vehicles, engines and equipments; computational methods and intelligence in modeling genetic and biochemical networks and regulation. (orig.)

FRAMEWORK OF TAILORMADE DRIVING SUPPORT SYSTEMS AND NEURAL NETWORK DRIVER MODEL

Directory of Open Access Journals (Sweden)

Toshiya HIROSE, M.S.

2004-01-01

Nowadays, tailormade medical treatment is receiving much attention in the field of medical care. It is also desirable for driving support systems to reflect the driving characteristics of individuals as much as possible, begin monitoring the driver when a driver starts driving and calculates the driver model, and supports them with a model that makes the driver feel quite normal. That is the construction of Tailormade Driving Support Systems (TDSS. This research proposes a concept and a framework of TDSS, and presents a driver model that uses a neural network to build the system. As for the feasibility of this system, the research selects braking as a typical constituent element, and illustrates and reviews the results of experiments and simulations.

Intelligence and the brain: a model-based approach

NARCIS (Netherlands)

Kievit, R.A.; van Rooijen, H.; Wicherts, J.M.; Waldorp, L.J.; Kan, K.-J.; Scholte, H.S.; Borsboom, D.

2012-01-01

Various biological correlates of general intelligence (g) have been reported. Despite this, however, the relationship between neurological measurements and g is not fully clear. We use structural equation modeling to model the relationship between behavioral Wechsler Adult Intelligence Scale (WAIS)

Driver Performance Model: 1. Conceptual Framework

National Research Council Canada - National Science Library

Heimerl, Joseph

2001-01-01

...'. At the present time, no such comprehensive model exists. This report discusses a conceptual framework designed to encompass the relationships, conditions, and constraints related to direct, indirect, and remote modes of driving and thus provides a guide or 'road map' for the construction and creation of a comprehensive driver performance model.

Modeling of biological intelligence for SCM system optimization.

Science.gov (United States)

Chen, Shengyong; Zheng, Yujun; Cattani, Carlo; Wang, Wanliang

2012-01-01

This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms.

Modeling of Biological Intelligence for SCM System Optimization

Directory of Open Access Journals (Sweden)

Shengyong Chen

2012-01-01

Full Text Available This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms.

Modeling of Biological Intelligence for SCM System Optimization

Science.gov (United States)

Chen, Shengyong; Zheng, Yujun; Cattani, Carlo; Wang, Wanliang

2012-01-01

This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms. PMID:22162724

A vision-based driver nighttime assistance and surveillance system based on intelligent image sensing techniques and a heterogamous dual-core embedded system architecture.

Science.gov (United States)

Chen, Yen-Lin; Chiang, Hsin-Han; Chiang, Chuan-Yen; Liu, Chuan-Ming; Yuan, Shyan-Ming; Wang, Jenq-Haur

2012-01-01

This study proposes a vision-based intelligent nighttime driver assistance and surveillance system (VIDASS system) implemented by a set of embedded software components and modules, and integrates these modules to accomplish a component-based system framework on an embedded heterogamous dual-core platform. Therefore, this study develops and implements computer vision and sensing techniques of nighttime vehicle detection, collision warning determination, and traffic event recording. The proposed system processes the road-scene frames in front of the host car captured from CCD sensors mounted on the host vehicle. These vision-based sensing and processing technologies are integrated and implemented on an ARM-DSP heterogamous dual-core embedded platform. Peripheral devices, including image grabbing devices, communication modules, and other in-vehicle control devices, are also integrated to form an in-vehicle-embedded vision-based nighttime driver assistance and surveillance system.

Can We Model Driver Perceptions? An In-Situ Experiment in Real-World Conditions

Directory of Open Access Journals (Sweden)

Aly M. Tawfik, PhD

2014-06-01

Full Text Available It is clear that perceptions play a significant role in traveler decisions. Consequently, traveler perceptions are a corner stone in the feasibility of traveler information systems; for traveler information systems are only valuable if the drivers are incapable of accurately acquiring the provided information on their own, and if the provided information is relevant for the drivers' decision criteria. Accuracy of traveler perceptions has been repeatedly researched in public transportation, and has been found to vary according to different reasons. However, in spite of the clear significance of traveler perceptions, minimal effort has been put into modeling it. Almost all travel behavior models are based on traveler experiences, which are assumed to reflect traveler perceptions via the addition of some random error component. This works introduces an alternative approach: instead of adding an error component to represent driver perceptions, it proposes to model driver perceptions. This work is based on a real-world route choice experiment of a sample of 20 drivers who made more than 2,000 real-world route choices. Each of the drivers' experiences, perceptions, and choices were recorded, analyzed and cross examined. The paper demonstrates that: i driver experiences are different from driver perceptions, ii driver perceptions explain driver choices better than driver experiences, iii it is possible to model and predict driver perceptions of travel distance, time and speed.

Multijam Solutions in Traffic Models with Velocity-Dependent Driver Strategies

DEFF Research Database (Denmark)

Carter, Paul; Christiansen, Peter Leth; Gaididei, Yuri B.

2014-01-01

The optimal-velocity follow-the-leader model is augmented with an equation that allows each driver to adjust their target headway according to the velocity difference between the driver and the car in front. In this more detailed model, which is investigated on a ring, stable and unstable multipu...

Multiple logistic regression model of signalling practices of drivers on urban highways

Science.gov (United States)

Puan, Othman Che; Ibrahim, Muttaka Na'iya; Zakaria, Rozana

2015-05-01

Giving signal is a way of informing other road users, especially to the conflicting drivers, the intention of a driver to change his/her movement course. Other users are exposed to hazard situation and risks of accident if the driver who changes his/her course failed to give signal as required. This paper describes the application of logistic regression model for the analysis of driver's signalling practices on multilane highways based on possible factors affecting driver's decision such as driver's gender, vehicle's type, vehicle's speed and traffic flow intensity. Data pertaining to the analysis of such factors were collected manually. More than 2000 drivers who have performed a lane changing manoeuvre while driving on two sections of multilane highways were observed. Finding from the study shows that relatively a large proportion of drivers failed to give any signals when changing lane. The result of the analysis indicates that although the proportion of the drivers who failed to provide signal prior to lane changing manoeuvre is high, the degree of compliances of the female drivers is better than the male drivers. A binary logistic model was developed to represent the probability of a driver to provide signal indication prior to lane changing manoeuvre. The model indicates that driver's gender, type of vehicle's driven, speed of vehicle and traffic volume influence the driver's decision to provide a signal indication prior to a lane changing manoeuvre on a multilane urban highway. In terms of types of vehicles driven, about 97% of motorcyclists failed to comply with the signal indication requirement. The proportion of non-compliance drivers under stable traffic flow conditions is much higher than when the flow is relatively heavy. This is consistent with the data which indicates a high degree of non-compliances when the average speed of the traffic stream is relatively high.

Forecasting rain events - Meteorological models or collective intelligence?

Science.gov (United States)

Arazy, Ofer; Halfon, Noam; Malkinson, Dan

2015-04-01

Collective intelligence is shared (or group) intelligence that emerges from the collective efforts of many individuals. Collective intelligence is the aggregate of individual contributions: from simple collective decision making to more sophisticated aggregations such as in crowdsourcing and peer-production systems. In particular, collective intelligence could be used in making predictions about future events, for example by using prediction markets to forecast election results, stock prices, or the outcomes of sport events. To date, there is little research regarding the use of collective intelligence for prediction of weather forecasting. The objective of this study is to investigate the extent to which collective intelligence could be utilized to accurately predict weather events, and in particular rainfall. Our analyses employ metrics of group intelligence, as well as compare the accuracy of groups' predictions against the predictions of the standard model used by the National Meteorological Services. We report on preliminary results from a study conducted over the 2013-2014 and 2014-2015 winters. We have built a web site that allows people to make predictions on precipitation levels on certain locations. During each competition participants were allowed to enter their precipitation forecasts (i.e. 'bets') at three locations and these locations changed between competitions. A precipitation competition was defined as a 48-96 hour period (depending on the expected weather conditions), bets were open 24-48 hours prior to the competition, and during betting period participants were allowed to change their bets with no limitation. In order to explore the effect of transparency, betting mechanisms varied across study's sites: full transparency (participants able to see each other's bets); partial transparency (participants see the group's average bet); and no transparency (no information of others' bets is made available). Several interesting findings emerged from

The Development of an Intelligent Leadership Model for State Universities

OpenAIRE

Aleme Keikha; Reza Hoveida; Nour Mohammad Yaghoubi

2017-01-01

Higher education and intelligent leadership are considered important parts of every country’s education system, which could potentially play a key role in accomplishing the goals of society. In theories of leadership, new patterns attempt to view leadership through the prism of creative and intelligent phenomena. This paper aims to design and develop an intelligent leadership model for public universities. A qualitativequantitative research method was used to design a basic model of intellige...

Intelligent Speed Assistance (ISA).

NARCIS (Netherlands)

2015-01-01

Intelligent Speed Assistance (ISA) has been a promising type of advanced driver support system for some decades. From a technical point of view, large scale ISA implementation is possible in the short term. The different types of ISA are expected to have different effects on behaviour and traffic

Employing the intelligence cycle process model within the Homeland Security Enterprise

OpenAIRE

Stokes, Roger L.

2013-01-01

CHDS State/Local The purpose of this thesis was to examine the employment and adherence of the intelligence cycle process model within the National Network of Fusion Centers and the greater Homeland Security Enterprise by exploring the customary intelligence cycle process model established by the United States Intelligence Community (USIC). This thesis revealed there are various intelligence cycle process models used by the USIC and taught to the National Network. Given the numerous differ...

The Actualization of Literary Learning Model Based on Verbal-Linguistic Intelligence

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Nur Ihsan Halil

2017-10-01

Full Text Available This article is inspired by Howard Gardner's concept of linguistic intelligence and also from some authors' previous writings. All of them became the authors' reference in developing ideas on constructing a literary learning model based on linguistic intelligence. The writing of this article is not done by collecting data empirically, but by developing and constructing an existing concept, namely the concept of linguistic intelligence, which is disseminated into a literature-based learning of verbal-linguistic intelligence. The purpose of this paper is to answer the question of how to apply the literary learning model based on the verbal-linguistic intelligence. Then, regarding Gardner's concept, the author formulated a literary learning model based on the verbal-linguistic intelligence through a story-telling learning model with five steps namely arguing, discussing, interpreting, speaking, and writing about literary works. In short, the writer draw a conclusion that learning-based models of verbal-linguistic intelligence can be designed with attention into five components namely (1 definition, (2 characteristics, (3 teaching strategy, (4 final learning outcomes, and (5 figures.

Artificial intelligence support for scientific model-building

Science.gov (United States)

Keller, Richard M.

1992-01-01

Scientific model-building can be a time-intensive and painstaking process, often involving the development of large and complex computer programs. Despite the effort involved, scientific models cannot easily be distributed and shared with other scientists. In general, implemented scientific models are complex, idiosyncratic, and difficult for anyone but the original scientific development team to understand. We believe that artificial intelligence techniques can facilitate both the model-building and model-sharing process. In this paper, we overview our effort to build a scientific modeling software tool that aids the scientist in developing and using models. This tool includes an interactive intelligent graphical interface, a high-level domain specific modeling language, a library of physics equations and experimental datasets, and a suite of data display facilities.

U.S. intelligence system: model for corporate chiefs?

Science.gov (United States)

Gilad, B

1991-01-01

A fully dedicated intelligence support function for senior management is no longer a luxury but a necessity. Companies can enhance their intelligence capabilities by using the government model as a rough blueprint to structure such a program.

Mathematical modeling and computational intelligence in engineering applications

CERN Document Server

Silva Neto, Antônio José da; Silva, Geraldo Nunes

2016-01-01

This book brings together a rich selection of studies in mathematical modeling and computational intelligence, with application in several fields of engineering, like automation, biomedical, chemical, civil, electrical, electronic, geophysical and mechanical engineering, on a multidisciplinary approach. Authors from five countries and 16 different research centers contribute with their expertise in both the fundamentals and real problems applications based upon their strong background on modeling and computational intelligence. The reader will find a wide variety of applications, mathematical and computational tools and original results, all presented with rigorous mathematical procedures. This work is intended for use in graduate courses of engineering, applied mathematics and applied computation where tools as mathematical and computational modeling, numerical methods and computational intelligence are applied to the solution of real problems.

Modelling the influence of sensory dynamics on linear and nonlinear driver steering control

Science.gov (United States)

Nash, C. J.; Cole, D. J.

2018-05-01

A recent review of the literature has indicated that sensory dynamics play an important role in the driver-vehicle steering task, motivating the design of a new driver model incorporating human sensory systems. This paper presents a full derivation of the linear driver model developed in previous work, and extends the model to control a vehicle with nonlinear tyres. Various nonlinear controllers and state estimators are compared with different approximations of the true system dynamics. The model simulation time is found to increase significantly with the complexity of the controller and state estimator. In general the more complex controllers perform best, although with certain vehicle and tyre models linearised controllers perform as well as a full nonlinear optimisation. Various extended Kalman filters give similar results, although the driver's sensory dynamics reduce control performance compared with full state feedback. The new model could be used to design vehicle systems which interact more naturally and safely with a human driver.

Intelligent behaviors through vehicle-to-vehicle and vehicle-to-infrastructure communication

Science.gov (United States)

Garcia, Richard D.; Sturgeon, Purser; Brown, Mike

2012-06-01

The last decade has seen a significant increase in intelligent safety devices on private automobiles. These devices have both increased and augmented the situational awareness of the driver and in some cases provided automated vehicle responses. To date almost all intelligent safety devices have relied on data directly perceived by the vehicle. This constraint has a direct impact on the types of solutions available to the vehicle. In an effort to improve the safety options available to a vehicle, numerous research laboratories and government agencies are investing time and resources into connecting vehicles to each other and to infrastructure-based devices. This work details several efforts in both the commercial vehicle and the private auto industries to increase vehicle safety and driver situational awareness through vehicle-to-vehicle and vehicle-to-infrastructure communication. It will specifically discuss intelligent behaviors being designed to automatically disable non-compliant vehicles, warn tractor trailer vehicles of unsafe lane maneuvers such as lane changes, passing, and merging, and alert drivers to non-line-of-sight emergencies.

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...

Model of key success factors for Business Intelligence implementation

Directory of Open Access Journals (Sweden)

Peter Mesaros

2016-07-01

Full Text Available New progressive technologies recorded growth in every area. Information-communication technologies facilitate the exchange of information and it facilitates management of everyday activities in enterprises. Specific modules (such as Business Intelligence facilitate decision-making. Several studies have demonstrated the positive impact of Business Intelligence to decision-making. The first step is to put in place the enterprise. The implementation process is influenced by many factors. This article discusses the issue of key success factors affecting to successful implementation of Business Intelligence. The article describes the key success factors for successful implementation and use of Business Intelligence based on multiple studies. The main objective of this study is to verify the effects and dependence of selected factors and proposes a model of key success factors for successful implementation of Business Intelligence. Key success factors and the proposed model are studied in Slovak enterprises.

Towards a universal competitive intelligence process model

Directory of Open Access Journals (Sweden)

Rene Pellissier

2013-08-01

Full Text Available Background: Competitive intelligence (CI provides actionable intelligence, which provides a competitive edge in enterprises. However, without proper process, it is difficult to develop actionable intelligence. There are disagreements about how the CI process should be structured. For CI professionals to focus on producing actionable intelligence, and to do so with simplicity, they need a common CI process model.Objectives: The purpose of this research is to review the current literature on CI, to look at the aims of identifying and analysing CI process models, and finally to propose a universal CI process model.Method: The study was qualitative in nature and content analysis was conducted on all identified sources establishing and analysing CI process models. To identify relevant literature, academic databases and search engines were used. Moreover, a review of references in related studies led to more relevant sources, the references of which were further reviewed and analysed. To ensure reliability, only peer-reviewed articles were used.Results: The findings reveal that the majority of scholars view the CI process as a cycle of interrelated phases. The output of one phase is the input of the next phase.Conclusion: The CI process is a cycle of interrelated phases. The output of one phase is the input of the next phase. These phases are influenced by the following factors: decision makers, process and structure, organisational awareness and culture, and feedback.

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.

Traffic modelling validation of advanced driver assistance systems

NARCIS (Netherlands)

Tongeren, R. van; Gietelink, O.J.; Schutter, B. de; Verhaegen, M.

2007-01-01

This paper presents a microscopic traffic model for the validation of advanced driver assistance systems. This model describes single-lane traffic and is calibrated with data from a field operational test. To illustrate the use of the model, a Monte Carlo simulation of single-lane traffic scenarios

Penerapan Model Pembelajaran Atraktif Berbasis Multiple Intelligences Tentang Pemantulan Cahaya pada Cermin

Directory of Open Access Journals (Sweden)

Intan Kusumawati

2016-03-01

Full Text Available Penelitian ini bertujuan untuk mengetahui efektivitas penerapan model pembelajaran atraktif berbasis multiple intelligences dalam meremediasi miskonsepsi siswa tentang pemantulan cahaya pada cermin. Pada penelitian ini digunakan bentuk pre-eksperimental design dengan rancangan one group pretest-post test design. Alat pengumpulan data berupa tes pilihan ganda dengan reasoning. Hasil validitas sebesar 4,08 dan reliabilitas 0,537. Siswa dibagi menjadi lima kelompok kecerdasan, yaitu kelompok linguistic intelligence, mathematical-logical intelligence, visual-spatial intelligence, bodily-khinestetic intelligence, dan musical intelligence. Siswa membahas konsep fisika sesuai kelompok kecerdasannya dalam bentuk pembuatan pantun-puisi, teka-teki silang, menggambar kreatif, drama, dan mengarang lirik lagu. Efektivitas penerapan model pembelajaran multiple intelligences menggunakan persamaan effect size. Ditemukan bahwa skor effect size masing-masing kelompok berkategori tinggi sebesar 5,76; 3,76; 4,60; 1,70; dan 1,34. Penerapan model pembelajaran atraktif berbasis multiple intelligences efektif dalam meremediasi miskonsepsi siswa. Penelitian ini diharapkan dapat digunakan pada materi fisika dan sekolah lainnya.

Continuous traffic flow modeling of driver support systems in multiclass traffic with intervehicle communication and drivers in the loop

NARCIS (Netherlands)

Tampere, C.; Hoogendoorn, S.P.; van Arem, Bart

2009-01-01

This paper presents a continuous traffic-flow model for the explorative analysis of advanced driver-assistance systems (ADASs). Such systems use technology (sensors and intervehicle communication) to support the task of the driver, who retains full control over the vehicle. Based on a review of

An application of artificial intelligence for rainfall–runoff modeling

Indian Academy of Sciences (India)

This study proposes an application of two techniques of artificial intelligence (AI) ... (2006) applied rainfall–runoff modeling using ANN ... in artificial intelligence, engineering and science .... usually be estimated from a sample of observations.

Driver-centred vehicle automation: using network analysis for agent-based modelling of the driver in highly automated driving systems.

Science.gov (United States)

Banks, Victoria A; Stanton, Neville A

2016-11-01

To the average driver, the concept of automation in driving infers that they can become completely 'hands and feet free'. This is a common misconception, however, one that has been shown through the application of Network Analysis to new Cruise Assist technologies that may feature on our roads by 2020. Through the adoption of a Systems Theoretic approach, this paper introduces the concept of driver-initiated automation which reflects the role of the driver in highly automated driving systems. Using a combination of traditional task analysis and the application of quantitative network metrics, this agent-based modelling paper shows how the role of the driver remains an integral part of the driving system implicating the need for designers to ensure they are provided with the tools necessary to remain actively in-the-loop despite giving increasing opportunities to delegate their control to the automated subsystems. Practitioner Summary: This paper describes and analyses a driver-initiated command and control system of automation using representations afforded by task and social networks to understand how drivers remain actively involved in the task. A network analysis of different driver commands suggests that such a strategy does maintain the driver in the control loop.

Does assisted driving behavior lead to safety-critical encounters with unequipped vehicles' drivers?

Science.gov (United States)

Preuk, Katharina; Stemmler, Eric; Schießl, Caroline; Jipp, Meike

2016-10-01

With Intelligent Transport Systems (e.g., traffic light assistance systems) assisted drivers are able to show driving behavior in anticipation of upcoming traffic situations. In the years to come, the penetration rate of such systems will be low. Therefore, the majority of vehicles will not be equipped with these systems. Unequipped vehicles' drivers may not expect the driving behavior of assisted drivers. However, drivers' predictions and expectations can play a significant role in their reaction times. Thus, safety issues could arise when unequipped vehicles' drivers encounter driving behavior of assisted drivers. This is why we tested how unequipped vehicles' drivers (N=60) interpreted and reacted to the driving behavior of an assisted driver. We used a multi-driver simulator with three drivers. The three drivers were driving in a line. The lead driver in the line was a confederate who was followed by two unequipped vehicles' drivers. We varied the equipment of the confederate with an Intelligent Transport System: The confederate was equipped either with or without a traffic light assistance system. The traffic light assistance system provided a start-up maneuver before a light turned green. Therefore, the assisted confederate seemed to show unusual deceleration behavior by coming to a halt at an unusual distance from the stop line at the red traffic light. The unusual distance was varied as we tested a moderate (4m distance from the stop line) and an extreme (10m distance from the stop line) parameterization of the system. Our results showed that the extreme parametrization resulted in shorter minimal time-to-collision of the unequipped vehicles' drivers. One rear-end crash was observed. These results provided initial evidence that safety issues can arise when unequipped vehicles' drivers encounter assisted driving behavior. We recommend that future research identifies counteractions to prevent these safety issues. Moreover, we recommend that system developers

A Stochastic LWR Model with Consideration of the Driver's Individual Property

International Nuclear Information System (INIS)

Tang Tieqiao; Wang Yunpeng; Yu Guizhen; Huang Haijun

2012-01-01

In this paper, we develop a stochastic LWR model based on the influences of the driver's individual property on his/her perceived density and speed deviation. The numerical results show that the driver's individual property has great effects on traffic flow only when the initial density is moderate, i.e., at this time, oscillating traffic flow will occur and the oscillating phenomena in the traffic system consisting of the conservative and aggressive drivers is more serious than that in the traffic system consisting of the conservative (aggressive) drivers.

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.

Continuous traffic flow modeling of driver support systems in multiclass traffic with inter-vehicle communication and drivers in the loop

NARCIS (Netherlands)

Tampere, C.M.J.; Hoogendoorn, S.P.; Arem, B. van

2009-01-01

This paper presents a continuous traffic-flow model for the explorative analysis of advanced driver-assistance systems (ADASs). Such systems use technology (sensors and intervehicle communication) to support the task of the driver, who retains full control over the vehicle. Based on a review of

Life system modeling and intelligent computing. Pt. II. Proceedings

Energy Technology Data Exchange (ETDEWEB)

Li, Kang; Irwin, George W. (eds.) [Belfast Queen' s Univ. (United Kingdom). School of Electronics, Electrical Engineering and Computer Science; Fei, Minrui; Jia, Li [Shanghai Univ. (China). School of Mechatronical Engineering and Automation

2010-07-01

This book is part II of a two-volume work that contains the refereed proceedings of the International Conference on Life System Modeling and Simulation, LSMS 2010 and the International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2010, held in Wuxi, China, in September 2010. The 194 revised full papers presented were carefully reviewed and selected from over 880 submissions and recommended for publication by Springer in two volumes of Lecture Notes in Computer Science (LNCS) and one volume of Lecture Notes in Bioinformatics (LNBI). This particular volume of Lecture Notes in Computer Science (LNCS) includes 55 papers covering 7 relevant topics. The 56 papers in this volume are organized in topical sections on advanced evolutionary computing theory and algorithms; advanced neural network and fuzzy system theory and algorithms; modeling and simulation of societies and collective behavior; biomedical signal processing, imaging, and visualization; intelligent computing and control in distributed power generation systems; intelligent methods in power and energy infrastructure development; intelligent modeling, monitoring, and control of complex nonlinear systems. (orig.)

ISG hybrid powertrain: a rule-based driver model incorporating look-ahead information

Science.gov (United States)

Shen, Shuiwen; Zhang, Junzhi; Chen, Xiaojiang; Zhong, Qing-Chang; Thornton, Roger

2010-03-01

According to European regulations, if the amount of regenerative braking is determined by the travel of the brake pedal, more stringent standards must be applied, otherwise it may adversely affect the existing vehicle safety system. The use of engine or vehicle speed to derive regenerative braking is one way to avoid strict design standards, but this introduces discontinuity in powertrain torque when the driver releases the acceleration pedal or applies the brake pedal. This is shown to cause oscillations in the pedal input and powertrain torque when a conventional driver model is adopted. Look-ahead information, together with other predicted vehicle states, are adopted to control the vehicle speed, in particular, during deceleration, and to improve the driver model so that oscillations can be avoided. The improved driver model makes analysis and validation of the control strategy for an integrated starter generator (ISG) hybrid powertrain possible.

Field tests and machine learning approaches for refining algorithms and correlations of driver's model parameters.

Science.gov (United States)

Tango, Fabio; Minin, Luca; Tesauri, Francesco; Montanari, Roberto

2010-03-01

This paper describes the field tests on a driving simulator carried out to validate the algorithms and the correlations of dynamic parameters, specifically driving task demand and drivers' distraction, able to predict drivers' intentions. These parameters belong to the driver's model developed by AIDE (Adaptive Integrated Driver-vehicle InterfacE) European Integrated Project. Drivers' behavioural data have been collected from the simulator tests to model and validate these parameters using machine learning techniques, specifically the adaptive neuro fuzzy inference systems (ANFIS) and the artificial neural network (ANN). Two models of task demand and distraction have been developed, one for each adopted technique. The paper provides an overview of the driver's model, the description of the task demand and distraction modelling and the tests conducted for the validation of these parameters. A test comparing predicted and expected outcomes of the modelled parameters for each machine learning technique has been carried out: for distraction, in particular, promising results (low prediction errors) have been obtained by adopting an artificial neural network.

Drivers' communicative interactions: on-road observations and modelling for integration in future automation systems.

Science.gov (United States)

Portouli, Evangelia; Nathanael, Dimitris; Marmaras, Nicolas

2014-01-01

Social interactions with other road users are an essential component of the driving activity and may prove critical in view of future automation systems; still up to now they have received only limited attention in the scientific literature. In this paper, it is argued that drivers base their anticipations about the traffic scene to a large extent on observations of social behaviour of other 'animate human-vehicles'. It is further argued that in cases of uncertainty, drivers seek to establish a mutual situational awareness through deliberate communicative interactions. A linguistic model is proposed for modelling these communicative interactions. Empirical evidence from on-road observations and analysis of concurrent running commentary by 25 experienced drivers support the proposed model. It is suggested that the integration of a social interactions layer based on illocutionary acts in future driving support and automation systems will improve their performance towards matching human driver's expectations. Practitioner Summary: Interactions between drivers on the road may play a significant role in traffic coordination. On-road observations and running commentaries are presented as empirical evidence to support a model of such interactions; incorporation of drivers' interactions in future driving support and automation systems may improve their performance towards matching driver's expectations.

Identification of mutated driver pathways in cancer using a multi-objective optimization model.

Science.gov (United States)

Zheng, Chun-Hou; Yang, Wu; Chong, Yan-Wen; Xia, Jun-Feng

2016-05-01

New-generation high-throughput technologies, including next-generation sequencing technology, have been extensively applied to solve biological problems. As a result, large cancer genomics projects such as the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium are producing large amount of rich and diverse data in multiple cancer types. The identification of mutated driver genes and driver pathways from these data is a significant challenge. Genome aberrations in cancer cells can be divided into two types: random 'passenger mutation' and functional 'driver mutation'. In this paper, we introduced a Multi-objective Optimization model based on a Genetic Algorithm (MOGA) to solve the maximum weight submatrix problem, which can be employed to identify driver genes and driver pathways promoting cancer proliferation. The maximum weight submatrix problem defined to find mutated driver pathways is based on two specific properties, i.e., high coverage and high exclusivity. The multi-objective optimization model can adjust the trade-off between high coverage and high exclusivity. We proposed an integrative model by combining gene expression data and mutation data to improve the performance of the MOGA algorithm in a biological context. Copyright © 2016 Elsevier Ltd. All rights reserved.

Uncertainty in predictions of forest carbon dynamics: separating driver error from model error.

Science.gov (United States)

Spadavecchia, L; Williams, M; Law, B E

2011-07-01

We present an analysis of the relative magnitude and contribution of parameter and driver uncertainty to the confidence intervals on estimates of net carbon fluxes. Model parameters may be difficult or impractical to measure, while driver fields are rarely complete, with data gaps due to sensor failure and sparse observational networks. Parameters are generally derived through some optimization method, while driver fields may be interpolated from available data sources. For this study, we used data from a young ponderosa pine stand at Metolius, Central Oregon, and a simple daily model of coupled carbon and water fluxes (DALEC). An ensemble of acceptable parameterizations was generated using an ensemble Kalman filter and eddy covariance measurements of net C exchange. Geostatistical simulations generated an ensemble of meteorological driving variables for the site, consistent with the spatiotemporal autocorrelations inherent in the observational data from 13 local weather stations. Simulated meteorological data were propagated through the model to derive the uncertainty on the CO2 flux resultant from driver uncertainty typical of spatially extensive modeling studies. Furthermore, the model uncertainty was partitioned between temperature and precipitation. With at least one meteorological station within 25 km of the study site, driver uncertainty was relatively small ( 10% of the total net flux), while parameterization uncertainty was larger, 50% of the total net flux. The largest source of driver uncertainty was due to temperature (8% of the total flux). The combined effect of parameter and driver uncertainty was 57% of the total net flux. However, when the nearest meteorological station was > 100 km from the study site, uncertainty in net ecosystem exchange (NEE) predictions introduced by meteorological drivers increased by 88%. Precipitation estimates were a larger source of bias in NEE estimates than were temperature estimates, although the biases partly

Model architecture of intelligent data mining oriented urban transportation information

Science.gov (United States)

Yang, Bogang; Tao, Yingchun; Sui, Jianbo; Zhang, Feizhou

2007-06-01

Aiming at solving practical problems in urban traffic, the paper presents model architecture of intelligent data mining from hierarchical view. With artificial intelligent technologies used in the framework, the intelligent data mining technology improves, which is more suitable for the change of real-time road condition. It also provides efficient technology support for the urban transport information distribution, transmission and display.

Computational Intelligence. Mortality Models for the Actuary

NARCIS (Netherlands)

Willemse, W.J.

2001-01-01

This thesis applies computational intelligence to the field of actuarial (insurance) science. In particular, this thesis deals with life insurance where mortality modelling is important. Actuaries use ancient models (mortality laws) from the nineteenth century, for example Gompertz' and Makeham's

The highly intelligent virtual agents for modeling financial markets

Science.gov (United States)

Yang, G.; Chen, Y.; Huang, J. P.

2016-02-01

Researchers have borrowed many theories from statistical physics, like ensemble, Ising model, etc., to study complex adaptive systems through agent-based modeling. However, one fundamental difference between entities (such as spins) in physics and micro-units in complex adaptive systems is that the latter are usually with high intelligence, such as investors in financial markets. Although highly intelligent virtual agents are essential for agent-based modeling to play a full role in the study of complex adaptive systems, how to create such agents is still an open question. Hence, we propose three principles for designing high artificial intelligence in financial markets and then build a specific class of agents called iAgents based on these three principles. Finally, we evaluate the intelligence of iAgents through virtual index trading in two different stock markets. For comparison, we also include three other types of agents in this contest, namely, random traders, agents from the wealth game (modified on the famous minority game), and agents from an upgraded wealth game. As a result, iAgents perform the best, which gives a well support for the three principles. This work offers a general framework for the further development of agent-based modeling for various kinds of complex adaptive systems.

Design And Implementation of Dsp-Based Intelligent Controller For Automobile Braking System

OpenAIRE

S.N. Sidek and M.J.E. Salami

2012-01-01

An intelligent braking system has great potential applications especially, in developed countries where research on smart vehicle and intelligent highways are receiving ample attention. The system when integrated with other subsystems like automatic traction control, intelligent throttle, and auto cruise systems, etc will result in smart vehicle maneuver. The driver at the end of the day will become the passenger, safety accorded the highest priority and the journey optimized in term of time ...

Introduction to the Special Issue on Intelligent and Cooperative Vehicles

Directory of Open Access Journals (Sweden)

Vicente Milanes

2015-11-01

Full Text Available Intelligent vehicles constitute one of the hot research topics on the Intelligent Transportation Systems (ITS field. The development of Advanced Driver Assistance Systems (ADAS based on multi-fusion information coming from on-board cameras, lidar or radar sensors is leading to more sophisticated passive and active safety systems. Additionally, the growing interest in using wireless communications to connect the vehicle either with other vehicles or the infrastructure is moving the intelligent vehicle research field toward smart interaction, moving to the Cooperative ITS (C-ITS research field. [...

EMOTIONAL INTELLIGENCE AND ORGANIZATIONAL COMPETITIVENESS: MANAGEMENT MODEL APPROACH

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John N. N. Ugoani

2016-09-01

Full Text Available Modern organization theory considers emotional intelligence as the index of competencies that help organizations to develop a vision for competitiveness. It also allows organizational leaders to enthusiastically commit to the vision, and energize organizational members to achieve the vision. To maximize competiveness organizations use models to simplify and clarify thinking, to identify important aspects, to suggest explanations and to predict consequences, and explore other performance areas that would otherwise be hidden in an excess of words. The survey research design was used to explore the relationship between emotional intelligence and organizational competitiveness. The study found that emotional intelligence has strong positive relationship with organizational competitiveness

Modeling the Speed Choice Behaviors of Drivers on Mountainous Roads with Complicated Shapes

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Yiming Shao

2015-02-01

Full Text Available Roadway geometric features and pavement conditions can significantly affect driver behavior, particularly with regard to vehicle speed. This paper presents the development of an algorithm for speed selection for use in automated passenger car travel (without driver input on mountainous roads with complicated shapes. The relationship between favorable driving speed and the geometric features of horizontal curves was established on the basis of driving experiments and spot speed observation data, and speed control models were established for driving on curves, curve approaches/departures, and tangents. The models developed can be used to calculate a driver's desired speed on any roadway with a defined geometry. The model considers the driver's behavior type and the vehicle's dynamic properties. This paper presents the results of simulation experiments on roads with small curve radii and narrow widths. The algorithms developed may be used for assisted and automated driving. Under automated driving conditions, speed control and speed change based on the algorithms developed make drivers feel natural as if they drive the car themselves.

Coping with the worrying complexity of cooperative driver assistance systems

NARCIS (Netherlands)

Ouden, F.C. den; Papp, Z.; Zoutendijk, A.M.; Netten, B.D.; Agovic, K.

2006-01-01

In recent years a clear trend became visible towards vehicles equipped with intelligent driver assistance systems based on cooperation between vehicle and infrastructure. The main reason for this is the high potential cooperative systems show to increase traffic throughput and safety and to decrease

A collision model for safety evaluation of autonomous intelligent cruise control.

Science.gov (United States)

Touran, A; Brackstone, M A; McDonald, M

1999-09-01

This paper describes a general framework for safety evaluation of autonomous intelligent cruise control in rear-end collisions. Using data and specifications from prototype devices, two collision models are developed. One model considers a train of four cars, one of which is equipped with autonomous intelligent cruise control. This model considers the car in front and two cars following the equipped car. In the second model, none of the cars is equipped with the device. Each model can predict the possibility of rear-end collision between cars under various conditions by calculating the remaining distance between cars after the front car brakes. Comparing the two collision models allows one to evaluate the effectiveness of autonomous intelligent cruise control in preventing collisions. The models are then subjected to Monte Carlo simulation to calculate the probability of collision. Based on crash probabilities, an expected value is calculated for the number of cars involved in any collision. It is found that given the model assumptions, while equipping a car with autonomous intelligent cruise control can significantly reduce the probability of the collision with the car ahead, it may adversely affect the situation for the following cars.

Modeling of Agile Intelligent Manufacturing-oriented Production Scheduling System

Institute of Scientific and Technical Information of China (English)

Zhong-Qi Sheng; Chang-Ping Tang; Ci-Xing Lv

2010-01-01

Agile intelligent manufacturing is one of the new manufacturing paradigms that adapt to the fierce globalizing market competition and meet the survival needs of the enterprises, in which the management and control of the production system have surpassed the scope of individual enterprise and embodied some new features including complexity, dynamicity, distributivity, and compatibility. The agile intelligent manufacturing paradigm calls for a production scheduling system that can support the cooperation among various production sectors, the distribution of various resources to achieve rational organization, scheduling and management of production activities. This paper uses multi-agents technology to build an agile intelligent manufacturing-oriented production scheduling system. Using the hybrid modeling method, the resources and functions of production system are encapsulated, and the agent-based production system model is established. A production scheduling-oriented multi-agents architecture is constructed and a multi-agents reference model is given in this paper.

Intelligent Mechatronic Systems Modeling, Control and Diagnosis

CERN Document Server

Merzouki, Rochdi; Pathak, Pushparaj Mani; Ould Bouamama, Belkacem

2013-01-01

Acting as a support resource for practitioners and professionals looking to advance their understanding of complex mechatronic systems, Intelligent Mechatronic Systems explains their design and recent developments from first principles to practical applications. Detailed descriptions of the mathematical models of complex mechatronic systems, developed from fundamental physical relationships, are built on to develop innovative solutions with particular emphasis on physical model-based control strategies. Following a concurrent engineering approach, supported by industrial case studies, and drawing on the practical experience of the authors, Intelligent Mechatronic Systems covers range of topic and includes:  • An explanation of a common graphical tool for integrated design and its uses from modeling and simulation to the control synthesis • Introductions to key concepts such as different means of achieving fault tolerance, robust overwhelming control and force and impedance control • Dedicated chapters ...

Automated feedback to foster safe driving in young drivers : Phase 2.

Science.gov (United States)

2015-12-01

Intelligent Speed Adaptation (ISA) represents a promising approach to reduce speeding. A core principle for ISA systems is that they provide real-time feedback to drivers, prompting them to reduce speed when some threshold at or above the limit is re...

An evolutionary model of bounded rationality and intelligence.

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Thomas J Brennan

Full Text Available BACKGROUND: Most economic theories are based on the premise that individuals maximize their own self-interest and correctly incorporate the structure of their environment into all decisions, thanks to human intelligence. The influence of this paradigm goes far beyond academia-it underlies current macroeconomic and monetary policies, and is also an integral part of existing financial regulations. However, there is mounting empirical and experimental evidence, including the recent financial crisis, suggesting that humans do not always behave rationally, but often make seemingly random and suboptimal decisions. METHODS AND FINDINGS: Here we propose to reconcile these contradictory perspectives by developing a simple binary-choice model that takes evolutionary consequences of decisions into account as well as the role of intelligence, which we define as any ability of an individual to increase its genetic success. If no intelligence is present, our model produces results consistent with prior literature and shows that risks that are independent across individuals in a generation generally lead to risk-neutral behaviors, but that risks that are correlated across a generation can lead to behaviors such as risk aversion, loss aversion, probability matching, and randomization. When intelligence is present the nature of risk also matters, and we show that even when risks are independent, either risk-neutral behavior or probability matching will occur depending upon the cost of intelligence in terms of reproductive success. In the case of correlated risks, we derive an implicit formula that shows how intelligence can emerge via selection, why it may be bounded, and how such bounds typically imply the coexistence of multiple levels and types of intelligence as a reflection of varying environmental conditions. CONCLUSIONS: Rational economic behavior in which individuals maximize their own self interest is only one of many possible types of behavior that

An evolutionary model of bounded rationality and intelligence.

Science.gov (United States)

Brennan, Thomas J; Lo, Andrew W

2012-01-01

Most economic theories are based on the premise that individuals maximize their own self-interest and correctly incorporate the structure of their environment into all decisions, thanks to human intelligence. The influence of this paradigm goes far beyond academia-it underlies current macroeconomic and monetary policies, and is also an integral part of existing financial regulations. However, there is mounting empirical and experimental evidence, including the recent financial crisis, suggesting that humans do not always behave rationally, but often make seemingly random and suboptimal decisions. Here we propose to reconcile these contradictory perspectives by developing a simple binary-choice model that takes evolutionary consequences of decisions into account as well as the role of intelligence, which we define as any ability of an individual to increase its genetic success. If no intelligence is present, our model produces results consistent with prior literature and shows that risks that are independent across individuals in a generation generally lead to risk-neutral behaviors, but that risks that are correlated across a generation can lead to behaviors such as risk aversion, loss aversion, probability matching, and randomization. When intelligence is present the nature of risk also matters, and we show that even when risks are independent, either risk-neutral behavior or probability matching will occur depending upon the cost of intelligence in terms of reproductive success. In the case of correlated risks, we derive an implicit formula that shows how intelligence can emerge via selection, why it may be bounded, and how such bounds typically imply the coexistence of multiple levels and types of intelligence as a reflection of varying environmental conditions. Rational economic behavior in which individuals maximize their own self interest is only one of many possible types of behavior that arise from natural selection. The key to understanding which types of

Model SH intelligent instrument for thickness measuring

International Nuclear Information System (INIS)

Liu Juntao; Jia Weizhuang; Zhao Yunlong

1995-01-01

The authors introduce Model SH Intelligent Instrument for thickness measuring by using principle of beta back-scattering and its application range, features, principle of operation, system design, calibration and specifications

An Intelligent Knowledge Management System from a Semantic Perspective

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Vasile MAZILESCU

2008-01-01

Full Text Available Knowledge Management Systems (KMS are important tools by whichorganizations can better use information and, more importantly, manageknowledge. Unlike other strategies, knowledge management (KM is difficult todefine because it encompasses a range of concepts, management tasks,technologies, and organizational practices, all of which come under the umbrella ofthe information management. Semantic approaches allow easier and more efficienttraining, maintenance, and support knowledge. Current ICT markets are dominatedby relational databases and document-centric information technologies, proceduralalgorithmic programming paradigms, and stack architecture. A key driver of globaleconomic expansion in the coming decade is the build-out of broadbandtelecommunications and the deployment of intelligent services bundling. This paperintroduces the main characteristics of an Intelligent Knowledge ManagementSystem as a multiagent system used in a Learning Control Problem (IKMSLCP,from a semantic perspective. We describe an intelligent KM framework, allowingthe observer (a human agent to learn from experience. This framework makes thesystem dynamic (flexible and adaptable so it evolves, guaranteeing high levels ofstability when performing his domain problem P. To capture by the agent who learnthe control knowledge for solving a task-allocation problem, the control expertsystem uses at any time, an internal fuzzy knowledge model of the (businessprocess based on the last knowledge model.

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.

Systems Intelligence in Knowledge Management Implementation: A Momentum of the SECI Model

OpenAIRE

Sasaki, Yasuo

2014-01-01

This paper discusses the role of systems intelligence in knowledge management implementations, in particular, in the SECI model, a widely acknowledged knowledge creation process in an organization identified by Nonaka and Takeuchi (1995). The SECI model deals with interactions and conversions of tacit knowledge and explicit knowledge and mainly consists of four stages. The author illustrates systems intelligence, a certain kind of human intelligence focusing on systems thinking perspective pr...

Intelligent Cloud Learning Model for Online Overseas Chinese Education

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Yidong Chen

2015-02-01

Full Text Available With the development of Chinese economy, oversea Chinese education has been paid more and more attention. However, the overseas Chinese education resource is relatively lack because of historical reasons, which hindered further development . How to better share the Chinese education resources and provide intelligent personalized information service for overseas student is a key problem to be solved. In recent years, the rise of cloud computing provides us an opportunity to realize intelligent learning mode. Cloud computing offers some advantages by allowing users to use infrastructure, platforms and software . In this paper we proposed an intelligent cloud learning model based on cloud computing. The learning model can utilize network resources sufficiently to implement resource sharing according to the personal needs of students, and provide a good practicability for online overseas Chinese education.

Modeling and simulating human teamwork behaviors using intelligent agents

Science.gov (United States)

Fan, Xiaocong; Yen, John

2004-12-01

Among researchers in multi-agent systems there has been growing interest in using intelligent agents to model and simulate human teamwork behaviors. Teamwork modeling is important for training humans in gaining collaborative skills, for supporting humans in making critical decisions by proactively gathering, fusing, and sharing information, and for building coherent teams with both humans and agents working effectively on intelligence-intensive problems. Teamwork modeling is also challenging because the research has spanned diverse disciplines from business management to cognitive science, human discourse, and distributed artificial intelligence. This article presents an extensive, but not exhaustive, list of work in the field, where the taxonomy is organized along two main dimensions: team social structure and social behaviors. Along the dimension of social structure, we consider agent-only teams and mixed human-agent teams. Along the dimension of social behaviors, we consider collaborative behaviors, communicative behaviors, helping behaviors, and the underpinning of effective teamwork-shared mental models. The contribution of this article is that it presents an organizational framework for analyzing a variety of teamwork simulation systems and for further studying simulated teamwork behaviors.

Driver Drowsiness Warning System Using Visual Information for Both Diurnal and Nocturnal Illumination Conditions

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Flores MarcoJavier

2010-01-01

Full Text Available Every year, traffic accidents due to human errors cause increasing amounts of deaths and injuries globally. To help reduce the amount of fatalities, in the paper presented here, a new module for Advanced Driver Assistance System (ADAS which deals with automatic driver drowsiness detection based on visual information and Artificial Intelligence is presented. The aim of this system is to locate, track, and analyze both the drivers face and eyes to compute a drowsiness index, where this real-time system works under varying light conditions (diurnal and nocturnal driving. Examples of different images of drivers taken in a real vehicle are shown to validate the algorithms used.

A Model for Traffic Accidents Prediction Based on Driver Personality Traits Assessment

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Marjana Čubranić-Dobrodolac

2017-12-01

Full Text Available The model proposed in this paper uses four psychological instruments for assessing driver behaviour and personality traits aiming to find a relationship between the considered constructs and the occurrence of traffic accidents. A Barratt Impulsiveness Scale (BIS-11 was used for the assessment of impulsivity, Aggressive Driving Behaviour Questionnaire (ADBQ for assessing the aggressiveness while driving, Manchester Driver Attitude Questionnaire (DAQ and the Questionnaire for self-assessment of driving ability. Besides these instruments, the participants filled out an extensive demographic survey. Within the statistical analysis, in addition to the descriptive indicators, correlation coefficients were calculated and four hierarchical regression analyses were performed to determine the predictive power of personality traits on the occurrence of traffic accidents. Further, to confirm the results and to obtain additional information about the relationship between the considered variables, the structural equation modelling and binary logistic regression have been implemented. A sample of this research covered 305 drivers, of which there were 100 bus drivers and 102 truck drivers, as well as 103 drivers of privately owned vehicles. The results indicate that BIS-11 and ADBQ questionnaires show the best predictive power which means that impulsivity and aggressiveness as personality traits have the greatest influence on the occurrence of traffic accidents. This research could be useful in many fields, such as the design of selection procedures for professional drivers, development of programs for the prevention of traffic accidents and violations of law, rehabilitation of drivers who have been deprived of the driving license, etc.

Modeling safety risk perception due to mobile phone distraction among four wheeler drivers

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Raghunathan Rajesh

2017-04-01

Full Text Available Nowadays, there is an increasing trend in the use of information and communication technology devices in new vehicles. Due to these increasing service facilities, driver distraction has become a major concern for transportation safety. To reduce safety risks, it is crucial to understand how distracting activities affect driver behavior at different levels of vehicle control. The objective of this work is to understand how the vehicle and driver characteristics influence mobile phone usage while driving and associated risk perception of road safety incidents. Based on literature review, a man–machine framework for distracted driving and a mobile phone distraction model is presented. The study highlights the findings from a questionnaire survey conducted in Kerala, India. The questionnaire uses a 5-point Likert scale. Responses from 1203 four-wheeler drivers are collected using random sampling approach. The questionnaire items associated with three driver-drive characteristics are: (i Human Factors (age, experience, emotional state, behavior of driver, (ii Driver space (meter, controls, light, heat, steering, actuators of vehicle, (iii Driving conditions (speed, distance, duration, traffic, signals. This mobile phone distraction model is tested using structural equation modeling procedure. The study indicates that among the three characteristics, ‘Human Factors’ has the highest influence on perceived distraction due to mobile phones. It is also observed that safety risk perception due to mobile phone usage while driving is moderate. The practical relevance of the study is to place emphasis on behavior-based controls and to focus on strategies leveraging perception of distraction due to mobile phones while driving.

Optimizing Cruising Routes for Taxi Drivers Using a Spatio-Temporal Trajectory Model

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Liang Wu

2017-11-01

Full Text Available Much of the taxi route-planning literature has focused on driver strategies for finding passengers and determining the hot spot pick-up locations using historical global positioning system (GPS trajectories of taxis based on driver experience, distance from the passenger drop-off location to the next passenger pick-up location and the waiting times at recommended locations for the next passenger. The present work, however, considers the average taxi travel speed mined from historical taxi GPS trajectory data and the allocation of cruising routes to more than one taxi driver in a small-scale region to neighboring pick-up locations. A spatio-temporal trajectory model with load balancing allocations is presented to not only explore pick-up/drop-off information but also provide taxi drivers with cruising routes to the recommended pick-up locations. In simulation experiments, our study shows that taxi drivers using cruising routes recommended by our spatio-temporal trajectory model can significantly reduce the average waiting time and travel less distance to quickly find their next passengers, and the load balancing strategy significantly alleviates road loads. These objective measures can help us better understand spatio-temporal traffic patterns and guide taxi navigation.

Observed and projected drivers of emerging infectious diseases in Europe.

Science.gov (United States)

Semenza, Jan C; Rocklöv, Joacim; Penttinen, Pasi; Lindgren, Elisabet

2016-10-01

Emerging infectious diseases are of international concern because of the potential for, and impact of, pandemics; however, they are difficult to predict. To identify the drivers of disease emergence, we analyzed infectious disease threat events (IDTEs) detected through epidemic intelligence collected at the European Centre for Disease Prevention and Control (ECDC) between 2008 and 2013, and compared the observed results with a 2008 ECDC foresight study of projected drivers of future IDTEs in Europe. Among 10 categories of IDTEs, foodborne and waterborne IDTEs were the most common, vaccine-preventable IDTEs caused the highest number of cases, and airborne IDTEs caused the most deaths. Observed drivers for each IDTE were sorted into three main groups: globalization and environmental drivers contributed to 61% of all IDTEs, public health system drivers contributed to 21%, and social and demographic drivers to 18%. A multiple logistic regression analysis showed that four of the top five drivers for observed IDTEs were in the globalization and environment group. In the observational study, the globalization and environment group was related to all IDTE categories, but only to five of eight categories in the foresight study. Directly targeting these drivers with public health interventions may diminish the chances of IDTE occurrence from the outset. © 2016 New York Academy of Sciences.

Intelligent transport systems (UTS) and driving behaviour: setting the agenda

NARCIS (Netherlands)

Heijden, R.E.C.M. van der; Marchau, V.A.W.J.; Thissen, W.A.H.; Wieinga, P.; Pantic, M.; Ludema, M.

2004-01-01

The application of intelligent transportation systems (ITS), in particular advanced driver assistance systems (ADAS), is expected to improve the performance of road transportation significantly. Public policy makers, among others, are therefore increasingly interested in the implementation

Programming model for distributed intelligent systems

Science.gov (United States)

Sztipanovits, J.; Biegl, C.; Karsai, G.; Bogunovic, N.; Purves, B.; Williams, R.; Christiansen, T.

1988-01-01

A programming model and architecture which was developed for the design and implementation of complex, heterogeneous measurement and control systems is described. The Multigraph Architecture integrates artificial intelligence techniques with conventional software technologies, offers a unified framework for distributed and shared memory based parallel computational models and supports multiple programming paradigms. The system can be implemented on different hardware architectures and can be adapted to strongly different applications.

A model for Business Intelligence Systems’ Development

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Manole VELICANU

2009-01-01

Full Text Available Often, Business Intelligence Systems (BIS require historical data or data collected from var-ious sources. The solution is found in data warehouses, which are the main technology used to extract, transform, load and store data in the organizational Business Intelligence projects. The development cycle of a data warehouse involves lots of resources, time, high costs and above all, it is built only for some specific tasks. In this paper, we’ll present some of the aspects of the BI systems’ development such as: architecture, lifecycle, modeling techniques and finally, some evaluation criteria for the system’s performance.

Modeling drivers' passing duration and distance in a virtual environment

Directory of Open Access Journals (Sweden)

Haneen Farah

2013-07-01

The main contribution of this paper is in the empirical models developed for passing duration and distance which highlights the factors that affect drivers' passing behavior and can be used to enhance the passing models in simulation programs.

Intelligent judgements over health risks in a spatial agent-based model.

Science.gov (United States)

Abdulkareem, Shaheen A; Augustijn, Ellen-Wien; Mustafa, Yaseen T; Filatova, Tatiana

2018-03-20

Millions of people worldwide are exposed to deadly infectious diseases on a regular basis. Breaking news of the Zika outbreak for instance, made it to the main media titles internationally. Perceiving disease risks motivate people to adapt their behavior toward a safer and more protective lifestyle. Computational science is instrumental in exploring patterns of disease spread emerging from many individual decisions and interactions among agents and their environment by means of agent-based models. Yet, current disease models rarely consider simulating dynamics in risk perception and its impact on the adaptive protective behavior. Social sciences offer insights into individual risk perception and corresponding protective actions, while machine learning provides algorithms and methods to capture these learning processes. This article presents an innovative approach to extend agent-based disease models by capturing behavioral aspects of decision-making in a risky context using machine learning techniques. We illustrate it with a case of cholera in Kumasi, Ghana, accounting for spatial and social risk factors that affect intelligent behavior and corresponding disease incidents. The results of computational experiments comparing intelligent with zero-intelligent representations of agents in a spatial disease agent-based model are discussed. We present a spatial disease agent-based model (ABM) with agents' behavior grounded in Protection Motivation Theory. Spatial and temporal patterns of disease diffusion among zero-intelligent agents are compared to those produced by a population of intelligent agents. Two Bayesian Networks (BNs) designed and coded using R and are further integrated with the NetLogo-based Cholera ABM. The first is a one-tier BN1 (only risk perception), the second is a two-tier BN2 (risk and coping behavior). We run three experiments (zero-intelligent agents, BN1 intelligence and BN2 intelligence) and report the results per experiment in terms of

Modelling speech intelligibility in adverse conditions

DEFF Research Database (Denmark)

Jørgensen, Søren; Dau, Torsten

2013-01-01

Jørgensen and Dau (J Acoust Soc Am 130:1475-1487, 2011) proposed the speech-based envelope power spectrum model (sEPSM) in an attempt to overcome the limitations of the classical speech transmission index (STI) and speech intelligibility index (SII) in conditions with nonlinearly processed speech...... subjected to phase jitter, a condition in which the spectral structure of the intelligibility of speech signal is strongly affected, while the broadband temporal envelope is kept largely intact. In contrast, the effects of this distortion can be predicted -successfully by the spectro-temporal modulation...... suggest that the SNRenv might reflect a powerful decision metric, while some explicit across-frequency analysis seems crucial in some conditions. How such across-frequency analysis is "realized" in the auditory system remains unresolved....

Comparison of learning models based on mathematics logical intelligence in affective domain

Science.gov (United States)

Widayanto, Arif; Pratiwi, Hasih; Mardiyana

2018-04-01

The purpose of this study was to examine the presence or absence of different effects of multiple treatments (used learning models and logical-mathematical intelligence) on the dependent variable (affective domain of mathematics). This research was quasi experimental using 3x3 of factorial design. The population of this research was VIII grade students of junior high school in Karanganyar under the academic year 2017/2018. Data collected in this research was analyzed by two ways analysis of variance with unequal cells using 5% of significance level. The result of the research were as follows: (1) Teaching and learning with model TS lead to better achievement in affective domain than QSH, teaching and learning with model QSH lead to better achievement in affective domain than using DI; (2) Students with high mathematics logical intelligence have better achievement in affective domain than students with low mathematics logical intelligence have; (3) In teaching and learning mathematics using learning model TS, students with moderate mathematics logical intelligence have better achievement in affective domain than using DI; and (4) In teaching and learning mathematics using learning model TS, students with low mathematics logical intelligence have better achievement in affective domain than using QSH and DI.

Traffic control and intelligent vehicle highway systems: a survey

NARCIS (Netherlands)

Baskar, L.D.; Schutter, B. de; Hellendoorn, J.; Papp, Z.

2011-01-01

Traffic congestion in highway networks is one of the main issues to be addressed by today's traffic management schemes. Automation combined with the increasing market penetration of on-line communication, navigation and advanced driver assistance systems will ultimately result in intelligent vehicle

A Novel GMM-Based Behavioral Modeling Approach for Smartwatch-Based Driver Authentication.

Science.gov (United States)

Yang, Ching-Han; Chang, Chin-Chun; Liang, Deron

2018-03-28

All drivers have their own distinct driving habits, and usually hold and operate the steering wheel differently in different driving scenarios. In this study, we proposed a novel Gaussian mixture model (GMM)-based method that can improve the traditional GMM in modeling driving behavior. This new method can be applied to build a better driver authentication system based on the accelerometer and orientation sensor of a smartwatch. To demonstrate the feasibility of the proposed method, we created an experimental system that analyzes driving behavior using the built-in sensors of a smartwatch. The experimental results for driver authentication-an equal error rate (EER) of 4.62% in the simulated environment and an EER of 7.86% in the real-traffic environment-confirm the feasibility of this approach.

Global and Regional Ecosystem Modeling: Databases of Model Drivers and Validation Measurements

Energy Technology Data Exchange (ETDEWEB)

Olson, R.J.

2002-03-19

Understanding global-scale ecosystem responses to changing environmental conditions is important both as a scientific question and as the basis for making policy decisions. The confidence in regional models depends on how well the field data used to develop the model represent the region of interest, how well the environmental model driving variables (e.g., vegetation type, climate, and soils associated with a site used to parameterize ecosystem models) represent the region of interest, and how well regional model predictions agree with observed data for the region. To assess the accuracy of global model forecasts of terrestrial carbon cycling, two Ecosystem Model-Data Intercomparison (EMDI) workshops were held (December 1999 and April 2001). The workshops included 17 biogeochemical, satellite-driven, detailed process, and dynamic vegetation global model types. The approach was to run regional or global versions of the models for sites with net primary productivity (NPP) measurements (i.e., not fine-tuned for specific site conditions) and analyze the model-data differences. Extensive worldwide NPP data were assembled with model driver data, including vegetation, climate, and soils data, to perform the intercomparison. This report describes the compilation of NPP estimates for 2,523 sites and 5,164 0.5{sup o}-grid cells under the Global Primary Production Data Initiative (GPPDI) and the results of the EMDI review and outlier analysis that produced a refined set of NPP estimates and model driver data. The EMDI process resulted in 81 Class A sites, 933 Class B sites, and 3,855 Class C cells derived from the original synthesis of NPP measurements and associated driver data. Class A sites represent well-documented study sites that have complete aboveground and below ground NPP measurements. Class B sites represent more numerous ''extensive'' sites with less documentation and site-specific information available. Class C cells represent estimates of

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...

Low Correlations between Intelligence and Big Five Personality Traits: Need to Broaden the Domain of Personality

Directory of Open Access Journals (Sweden)

Lazar Stankov

2018-05-01

Full Text Available The correlations between the measures of cognitive abilities and personality traits are known to be low. Our data based on the popular Big Five model of intelligence show that the highest correlations (up to r = 0.30 tend to occur with the Openness to Experience. Some recent developments in the studies of intelligence (e.g., emotional intelligence, complex problem solving and economic games indicate that this link may become stronger in future. Furthermore, our studies of the processes in the “no-man’s-land” between intelligence and personality suggest that the non-cognitive constructs are correlated with both. These include the measures of social conservatism and self-beliefs. Importantly, the Big Five measures do not tap into either the dark traits associated with social conservatism or self-beliefs that are known to be good predictors of academic achievement. This paper argues that the personality domain should be broadened to include new constructs that have not been captured by the lexical approach employed in the development of the Big Five model. Furthermore, since the measures of confidence have the highest correlation with cognitive performance, we suggest that the trait of confidence may be a driver that leads to the separation of fluid and crystallized intelligence during development.

A parametric duration model of the reaction times of drivers distracted by mobile phone conversations.

Science.gov (United States)

Haque, Md Mazharul; Washington, Simon

2014-01-01

The use of mobile phones while driving is more prevalent among young drivers-a less experienced cohort with elevated crash risk. The objective of this study was to examine and better understand the reaction times of young drivers to a traffic event originating in their peripheral vision whilst engaged in a mobile phone conversation. The CARRS-Q advanced driving simulator was used to test a sample of young drivers on various simulated driving tasks, including an event that originated within the driver's peripheral vision, whereby a pedestrian enters a zebra crossing from a sidewalk. Thirty-two licensed drivers drove the simulator in three phone conditions: baseline (no phone conversation), hands-free and handheld. In addition to driving the simulator each participant completed questionnaires related to driver demographics, driving history, usage of mobile phones while driving, and general mobile phone usage history. The participants were 21-26 years old and split evenly by gender. Drivers' reaction times to a pedestrian in the zebra crossing were modelled using a parametric accelerated failure time (AFT) duration model with a Weibull distribution. Also tested where two different model specifications to account for the structured heterogeneity arising from the repeated measures experimental design. The Weibull AFT model with gamma heterogeneity was found to be the best fitting model and identified four significant variables influencing the reaction times, including phone condition, driver's age, license type (provisional license holder or not), and self-reported frequency of usage of handheld phones while driving. The reaction times of drivers were more than 40% longer in the distracted condition compared to baseline (not distracted). Moreover, the impairment of reaction times due to mobile phone conversations was almost double for provisional compared to open license holders. A reduction in the ability to detect traffic events in the periphery whilst distracted

An extended continuum model accounting for the driver's timid and aggressive attributions

Energy Technology Data Exchange (ETDEWEB)

Cheng, Rongjun; Ge, Hongxia [Faculty of Maritime and Transportation, Ningbo University, Ningbo 315211 (China); Jiangsu Province Collaborative Innovation Center for Modern Urban Traffic Technologies, Nanjing 210096 (China); National Traffic Management Engineering and Technology Research Centre Ningbo University Sub-centre, Ningbo 315211 (China); Wang, Jufeng, E-mail: wjf@nit.zju.edu.cn [Ningbo Institute of Technology, Zhejiang University, Ningbo 315100 (China)

2017-04-18

Considering the driver's timid and aggressive behaviors simultaneously, a new continuum model is put forwarded in this paper. By applying the linear stability theory, we presented the analysis of new model's linear stability. Through nonlinear analysis, the KdV–Burgers equation is derived to describe density wave near the neutral stability line. Numerical results verify that aggressive driving is better than timid act because the aggressive driver will adjust his speed timely according to the leading car's speed. The key improvement of this new model is that the timid driving deteriorates traffic stability while the aggressive driving will enhance traffic stability. The relationship of energy consumption between the aggressive and timid driving is also studied. Numerical results show that aggressive driver behavior can not only suppress the traffic congestion but also reduce the energy consumption. - Highlights: • A new continuum model is developed with the consideration of the driver's timid and aggressive behaviors simultaneously. • Applying the linear stability theory, the new model's linear stability is obtained. • Through nonlinear analysis, the KdV–Burgers equation is derived. • The energy consumption for this model is studied.

An extended continuum model accounting for the driver's timid and aggressive attributions

International Nuclear Information System (INIS)

Cheng, Rongjun; Ge, Hongxia; Wang, Jufeng

2017-01-01

Considering the driver's timid and aggressive behaviors simultaneously, a new continuum model is put forwarded in this paper. By applying the linear stability theory, we presented the analysis of new model's linear stability. Through nonlinear analysis, the KdV–Burgers equation is derived to describe density wave near the neutral stability line. Numerical results verify that aggressive driving is better than timid act because the aggressive driver will adjust his speed timely according to the leading car's speed. The key improvement of this new model is that the timid driving deteriorates traffic stability while the aggressive driving will enhance traffic stability. The relationship of energy consumption between the aggressive and timid driving is also studied. Numerical results show that aggressive driver behavior can not only suppress the traffic congestion but also reduce the energy consumption. - Highlights: • A new continuum model is developed with the consideration of the driver's timid and aggressive behaviors simultaneously. • Applying the linear stability theory, the new model's linear stability is obtained. • Through nonlinear analysis, the KdV–Burgers equation is derived. • The energy consumption for this model is studied.

#%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.

Business Intelligence Modeling in Launch Operations

Science.gov (United States)

Bardina, Jorge E.; Thirumalainambi, Rajkumar; Davis, Rodney D.

2005-01-01

This technology project is to advance an integrated Planning and Management Simulation Model for evaluation of risks, costs, and reliability of launch systems from Earth to Orbit for Space Exploration. The approach builds on research done in the NASA ARC/KSC developed Virtual Test Bed (VTB) to integrate architectural, operations process, and mission simulations for the purpose of evaluating enterprise level strategies to reduce cost, improve systems operability, and reduce mission risks. The objectives are to understand the interdependency of architecture and process on recurring launch cost of operations, provide management a tool for assessing systems safety and dependability versus cost, and leverage lessons learned and empirical models from Shuttle and International Space Station to validate models applied to Exploration. The systems-of-systems concept is built to balance the conflicting objectives of safety, reliability, and process strategy in order to achieve long term sustainability. A planning and analysis test bed is needed for evaluation of enterprise level options and strategies for transit and launch systems as well as surface and orbital systems. This environment can also support agency simulation .based acquisition process objectives. The technology development approach is based on the collaborative effort set forth in the VTB's integrating operations. process models, systems and environment models, and cost models as a comprehensive disciplined enterprise analysis environment. Significant emphasis is being placed on adapting root cause from existing Shuttle operations to exploration. Technical challenges include cost model validation, integration of parametric models with discrete event process and systems simulations. and large-scale simulation integration. The enterprise architecture is required for coherent integration of systems models. It will also require a plan for evolution over the life of the program. The proposed technology will produce

Business intelligence modeling in launch operations

Science.gov (United States)

Bardina, Jorge E.; Thirumalainambi, Rajkumar; Davis, Rodney D.

2005-05-01

The future of business intelligence in space exploration will focus on the intelligent system-of-systems real-time enterprise. In present business intelligence, a number of technologies that are most relevant to space exploration are experiencing the greatest change. Emerging patterns of set of processes rather than organizational units leading to end-to-end automation is becoming a major objective of enterprise information technology. The cost element is a leading factor of future exploration systems. This technology project is to advance an integrated Planning and Management Simulation Model for evaluation of risks, costs, and reliability of launch systems from Earth to Orbit for Space Exploration. The approach builds on research done in the NASA ARC/KSC developed Virtual Test Bed (VTB) to integrate architectural, operations process, and mission simulations for the purpose of evaluating enterprise level strategies to reduce cost, improve systems operability, and reduce mission risks. The objectives are to understand the interdependency of architecture and process on recurring launch cost of operations, provide management a tool for assessing systems safety and dependability versus cost, and leverage lessons learned and empirical models from Shuttle and International Space Station to validate models applied to Exploration. The systems-of-systems concept is built to balance the conflicting objectives of safety, reliability, and process strategy in order to achieve long term sustainability. A planning and analysis test bed is needed for evaluation of enterprise level options and strategies for transit and launch systems as well as surface and orbital systems. This environment can also support agency simulation based acquisition process objectives. The technology development approach is based on the collaborative effort set forth in the VTB's integrating operations, process models, systems and environment models, and cost models as a comprehensive disciplined

Customer Data Analysis Model using Business Intelligence Tools in Telecommunication Companies

Directory of Open Access Journals (Sweden)

Monica LIA

2015-10-01

Full Text Available This article presents a customer data analysis model in a telecommunication company and business intelligence tools for data modelling, transforming, data visualization and dynamic reports building . For a mature market, knowing the information inside the data and making forecast for strategic decision become more important in Romanian Market. Business Intelligence tools are used in business organization as support for decision making.

INTERACTIVITY OF THE MODERN AUTOMATED SYSTEMS OF THE HELP TO THE DRIVER

OpenAIRE

Svetlana Alekseevna Vasyugova; Andrey Borisovich Nikolaev

2017-01-01

In this article the current technologies in the field of intelligent transportation systems are investigated. The latest systems on control of the safe movement on roads are considered. The analysis of the systems of the help to the driver implemented in cars is carried out. The system concept of the help to the driver of «System help» is offered. Algorithms of work of this system which is based on the principles of interactivity and interaction are investigated. By results of researches expe...

National Water Model: Providing the Nation with Actionable Water Intelligence

Science.gov (United States)

Aggett, G. R.; Bates, B.

2017-12-01

The National Water Model (NWM) provides national, street-level detail of water movement through time and space. Operating hourly, this flood of information offers enormous benefits in the form of water resource management, natural disaster preparedness, and the protection of life and property. The Geo-Intelligence Division at the NOAA National Water Center supplies forecasters and decision-makers with timely, actionable water intelligence through the processing of billions of NWM data points every hour. These datasets include current streamflow estimates, short and medium range streamflow forecasts, and many other ancillary datasets. The sheer amount of NWM data produced yields a dataset too large to allow for direct human comprehension. As such, it is necessary to undergo model data post-processing, filtering, and data ingestion by visualization web apps that make use of cartographic techniques to bring attention to the areas of highest urgency. This poster illustrates NWM output post-processing and cartographic visualization techniques being developed and employed by the Geo-Intelligence Division at the NOAA National Water Center to provide national actionable water intelligence.

Acquisition of business intelligence from human experience in route planning

Science.gov (United States)

Bello Orgaz, Gema; Barrero, David F.; R-Moreno, María D.; Camacho, David

2015-04-01

The logistic sector raises a number of highly challenging problems. Probably one of the most important ones is the shipping planning, i.e. plan the routes that the shippers have to follow to deliver the goods. In this article, we present an artificial intelligence-based solution that has been designed to help a logistic company to improve its routes planning process. In order to achieve this goal, the solution uses the knowledge acquired by the company drivers to propose optimised routes. Hence, the proposed solution gathers the experience of the drivers, processes it and optimises the delivery process. The solution uses data mining to extract knowledge from the company information systems and prepares it for analysis with a case-based reasoning (CBR) algorithm. The CBR obtains critical business intelligence knowledge from the drivers experience that is needed by the planner. The design of the routes is done by a genetic algorithm that, given the processed information, optimises the routes following several objectives, such as minimise the distance or time. Experimentation shows that the proposed approach is able to find routes that improve, on average, the routes made by the human experts.

International Conference on Computational Intelligence, Cyber Security, and Computational Models

CERN Document Server

Ramasamy, Vijayalakshmi; Sheen, Shina; Veeramani, C; Bonato, Anthony; Batten, Lynn

2016-01-01

This book aims at promoting high-quality research by researchers and practitioners from academia and industry at the International Conference on Computational Intelligence, Cyber Security, and Computational Models ICC3 2015 organized by PSG College of Technology, Coimbatore, India during December 17 – 19, 2015. This book enriches with innovations in broad areas of research like computational modeling, computational intelligence and cyber security. These emerging inter disciplinary research areas have helped to solve multifaceted problems and gained lot of attention in recent years. This encompasses theory and applications, to provide design, analysis and modeling of the aforementioned key areas.

Emotional intelligence--essential for trauma nursing.

Science.gov (United States)

Holbery, Natalie

2015-01-01

Patients and their relatives are increasingly considered partners in health and social care decision-making. Numerous political drivers in the UK reflect a commitment to this partnership and to improving the experience of patients and relatives in emergency care environments. As a Lecturer/Practitioner in Emergency Care I recently experienced the London Trauma System as a relative. My dual perspective, as nurse and relative, allowed me to identify a gap in the quality of care akin to emotional intelligence. This paper aims to raise awareness of emotional intelligence (EI), highlight its importance in trauma care and contribute to the development of this concept in trauma nursing and education across the globe. Copyright © 2014 Elsevier Ltd. All rights reserved.

Evaluation of Artificial Intelligence Based Models for Chemical Biodegradability Prediction

Directory of Open Access Journals (Sweden)

Aleksandar Sabljic

2004-12-01

Full Text Available This study presents a review of biodegradability modeling efforts including a detailed assessment of two models developed using an artificial intelligence based methodology. Validation results for these models using an independent, quality reviewed database, demonstrate that the models perform well when compared to another commonly used biodegradability model, against the same data. The ability of models induced by an artificial intelligence methodology to accommodate complex interactions in detailed systems, and the demonstrated reliability of the approach evaluated by this study, indicate that the methodology may have application in broadening the scope of biodegradability models. Given adequate data for biodegradability of chemicals under environmental conditions, this may allow for the development of future models that include such things as surface interface impacts on biodegradability for example.

MODELING DRIVER BEHAVIOR IN THE DRIVING OF THEIR MOTOR VEHICLE

Directory of Open Access Journals (Sweden)

A. V. Skrypnikov

2015-01-01

Full Text Available The article holds the gradual formation of images and actions of the driver. As outlined the author's arguments based on the following assumptions: We consider the motion of the mass, mass-produced currently by the domestic industry of automobiles; considered the motion of single cars as the most common and most dangerous cases, allowing to evaluate the influence of parameters on the road driving mode "pure"; drivers tend to reduce travel times and therefore move with the maximum possible speed; drivers choose speed, visually estimating lying in front of part of the way and given the speed at the time of this evaluation; driver behavior, ceteris paribus determined the influence of visibility limitations and conditions visual perception; considered the motion on the ascent and descent, but the determining factor is the direction of descent. Set of operations, branches off the driver, can be represented as a multi-level system comprising three main groups of psycho-physiological processes, activities analyzers (perception of information; the work of the central nervous system (processing and storage; effective activity (responses to the implementation of the decision. On the basis of the received information in human consciousness formed images of the environment, the totality of which is an information model of the object. Comparing it with the standards (memory engrams, the driver generates the mo st appropriate in the circumstances set of actions. Implementation of the decision is the final stage of human response to the external environment and is expressed in the change of the degree of use of traction engine or braking force; change the steering angle as that does not affect the speed of motion, the algorithm of the driver is not taken into account. Analysis of the schemes of algorithms allows to obtain quantitative characteristics of the vehicle: stereotyped figures, logical complexity.

Heavy-ion driver design and scaling

International Nuclear Information System (INIS)

Bieri, R.; Monsler, M.; Meier, W.; Stewart, L.

1992-01-01

Parametric models for scaling heavy-ion driver designs are described. Scaling of target performance and driver cost is done for driver parameters including driver energy, number of beams, type of superconductor used in focusing magnets, maximum magnetic field allowed at the superconducting windings, linear quadrupole array packing fraction mass, and ion charge state. The cumulative accelerator voltage and beam currents are determined from the Maschke limits on beam current for each choice of driver energy and post-acceleration pulse duration. The heavy-ion driver is optimized over the large available driver parameter space. Parametric studies and the choice of a base driver model are described in a companion paper

A spring-mass-damper system dynamics-based driver-vehicle integrated model for representing heterogeneous traffic

Science.gov (United States)

Munigety, Caleb Ronald

2018-04-01

The traditional traffic microscopic simulation models consider driver and vehicle as a single unit to represent the movements of drivers in a traffic stream. Due to this very fact, the traditional car-following models have the driver behavior related parameters, but ignore the vehicle related aspects. This approach is appropriate for homogeneous traffic conditions where car is the major vehicle type. However, in heterogeneous traffic conditions where multiple vehicle types are present, it becomes important to incorporate the vehicle related parameters exclusively to account for the varying dynamic and static characteristics. Thus, this paper presents a driver-vehicle integrated model hinged on the principles involved in physics-based spring-mass-damper mechanical system. While the spring constant represents the driver’s aggressiveness, the damping constant and the mass component take care of the stability and size/weight related aspects, respectively. The proposed model when tested, behaved pragmatically in representing the vehicle-type dependent longitudinal movements of vehicles.

Automated feedback to foster safe driving in young drivers: phase 2 : traffic tech.

Science.gov (United States)

2015-12-01

Intelligent Speed Adaptation (ISA) provides a promising approach to reduce speeding. A core principle of ISA is real-time feedback that lets drivers know when they are driving over the speed limit. The overall goal of the study was to provide insight...

A Model of Intelligent Fault Diagnosis of Power Equipment Based on CBR

Directory of Open Access Journals (Sweden)

Gang Ma

2015-01-01

Full Text Available Nowadays the demand of power supply reliability has been strongly increased as the development within power industry grows rapidly. Nevertheless such large demand requires substantial power grid to sustain. Therefore power equipment’s running and testing data which contains vast information underpins online monitoring and fault diagnosis to finally achieve state maintenance. In this paper, an intelligent fault diagnosis model for power equipment based on case-based reasoning (IFDCBR will be proposed. The model intends to discover the potential rules of equipment fault by data mining. The intelligent model constructs a condition case base of equipment by analyzing the following four categories of data: online recording data, history data, basic test data, and environmental data. SVM regression analysis was also applied in mining the case base so as to further establish the equipment condition fingerprint. The running data of equipment can be diagnosed by such condition fingerprint to detect whether there is a fault or not. Finally, this paper verifies the intelligent model and three-ratio method based on a set of practical data. The resulting research demonstrates that this intelligent model is more effective and accurate in fault diagnosis.

Driving with intelligent vehicles: driving behaviour with Adaptive Cruise Control and the acceptance by individual drivers

NARCIS (Netherlands)

Hoedemaeker, D.M.

1999-01-01

This thesis focuses on the following research questions: What are the effects of driver support systems on driving behaviour? To what extent will driver support systems be accepted by individual drivers? To what extent will driving behaviour and acceptance be determined by individual differences?

A Theoretical Assessment on Emotional Intelligence as a Competitive Managerial Skill

Directory of Open Access Journals (Sweden)

Burcu Hacioglu

2014-03-01

Full Text Available Emotion as the main motive underlying the human behaviors is a conceptthat has been researched by many disciplines in the social sciences. Derivingfrom behavioral studies on emotions, Emotional Intelligence as acritical concept in organizational behavior studies is attached to theassestment of employee motivation and performance drivers. In this study, atheoretical framework for the emotional intelligence in workplace has beenassessed. The major contribution of the concept in competitive business strategiesfrom managerial scope has been evaluated.

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...

A Binaural Grouping Model for Predicting Speech Intelligibility in Multitalker Environments

Directory of Open Access Journals (Sweden)

Jing Mi

2016-09-01

Full Text Available Spatially separating speech maskers from target speech often leads to a large intelligibility improvement. Modeling this phenomenon has long been of interest to binaural-hearing researchers for uncovering brain mechanisms and for improving signal-processing algorithms in hearing-assistive devices. Much of the previous binaural modeling work focused on the unmasking enabled by binaural cues at the periphery, and little quantitative modeling has been directed toward the grouping or source-separation benefits of binaural processing. In this article, we propose a binaural model that focuses on grouping, specifically on the selection of time-frequency units that are dominated by signals from the direction of the target. The proposed model uses Equalization-Cancellation (EC processing with a binary decision rule to estimate a time-frequency binary mask. EC processing is carried out to cancel the target signal and the energy change between the EC input and output is used as a feature that reflects target dominance in each time-frequency unit. The processing in the proposed model requires little computational resources and is straightforward to implement. In combination with the Coherence-based Speech Intelligibility Index, the model is applied to predict the speech intelligibility data measured by Marrone et al. The predicted speech reception threshold matches the pattern of the measured data well, even though the predicted intelligibility improvements relative to the colocated condition are larger than some of the measured data, which may reflect the lack of internal noise in this initial version of the model.

A Binaural Grouping Model for Predicting Speech Intelligibility in Multitalker Environments.

Science.gov (United States)

Mi, Jing; Colburn, H Steven

2016-10-03

Spatially separating speech maskers from target speech often leads to a large intelligibility improvement. Modeling this phenomenon has long been of interest to binaural-hearing researchers for uncovering brain mechanisms and for improving signal-processing algorithms in hearing-assistive devices. Much of the previous binaural modeling work focused on the unmasking enabled by binaural cues at the periphery, and little quantitative modeling has been directed toward the grouping or source-separation benefits of binaural processing. In this article, we propose a binaural model that focuses on grouping, specifically on the selection of time-frequency units that are dominated by signals from the direction of the target. The proposed model uses Equalization-Cancellation (EC) processing with a binary decision rule to estimate a time-frequency binary mask. EC processing is carried out to cancel the target signal and the energy change between the EC input and output is used as a feature that reflects target dominance in each time-frequency unit. The processing in the proposed model requires little computational resources and is straightforward to implement. In combination with the Coherence-based Speech Intelligibility Index, the model is applied to predict the speech intelligibility data measured by Marrone et al. The predicted speech reception threshold matches the pattern of the measured data well, even though the predicted intelligibility improvements relative to the colocated condition are larger than some of the measured data, which may reflect the lack of internal noise in this initial version of the model. © The Author(s) 2016.

Aligning drivers, contract, and management of IT-outsourcing relationships: a type-dependent model

DEFF Research Database (Denmark)

Arenfeldt, Katrine; Corty Dam, Amalie; Fenger, Kim Harder

2017-01-01

In today’s competitive business environment, information technology outsourcing has become a wide-spread reality across all industries and sectors. Researchers have investigated this complex phenomenon from various angles, and established a sound knowledge base regarding the drivers, management......, and success factors related to IT outsourcing. However, little is known about the relationship between outsourcing drivers and goals on the one hand, and contractual and managerial aspects on the other hand. To overcome this gap, this study presents a synthesized conceptual model of existing literature...... that relates aspects of contractual governance and relationship management to three generic types of IT outsourcing, based on their underlying drivers: task-based, process-based, and partnership-based outsourcing. Our model identifies the specific contractual and managerial factors relevant for each type...

The driver as archetype for driver assistance systems? A driver-model based approach for the development of situation-adaptive DAS; Der Fahrer als Vorbild fuer Fahrerassistenzsysteme? Ein Fahrermodellbasierter Ansatz zur Entwicklung von situationsadaptiven FAS

Energy Technology Data Exchange (ETDEWEB)

Benmimoun, A. [Inst. fuer Kraftfahrwesen, RWTH-Aachen, Aachen (Germany)

2004-07-01

A new approach for the development of advanced driver assistance systems is presented. The keynote of this new approach is to use the driver model of the traffic simulation tool PELOPS as a control algorithm and to apply it to a vehicle. The fact, that the human driving behaviour is the starting point of the development, is the main advantage of this new approach. Thus important aspects for the development of driver assistance systems like a situation-adaptive and reliable control, understandable behaviour and the consideration of driver-individual parameters are integrated in the controller design from the beginning. An application example of the new approach is shown. (orig.)

Model Pembelajaran Berbasis Penstimulasian Multiple Intelligences Siswa

Directory of Open Access Journals (Sweden)

Edy Legowo

2017-03-01

Full Text Available Tulisan ini membahas mengenai penerapan teori multiple intelligences dalam pembelajaran di sekolah. Pembahasan diawali dengan menguraikan perkembangan konsep inteligensi dan multiple intelligences. Diikuti dengan menjelaskan dampak teori multiple intelligences dalam bidang pendidikan dan pembelajaran di sekolah. Bagian selanjutnya menguraikan tentang implementasi teori multiple intelligences dalam praktik pembelajaran di kelas yaitu bagaimana pemberian pengalaman belajar siswa yang difasilitasi guru dapat menstimulasi multiple intelligences siswa. Evaluasi hasil belajar siswa dari pandangan penerapan teori multiple intelligences seharusnya dilakukan menggunakan authentic assessment dan portofolio yang lebih memfasilitasi para siswa mengungkapkan atau mengaktualisasikan hasil belajarnya melalui berbagai cara sesuai dengan kekuatan jenis inteligensinya.

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...

Means-End based Functional Modeling for Intelligent Control: Modeling and Experiments with an Industrial Heat Pump System

DEFF Research Database (Denmark)

Saleem, Arshad

2007-01-01

The purpose of this paper is to present a Multilevel Flow Model (MFM) of an industrial heat pump system and its use for diagnostic reasoning. MFM is functional modeling language supporting an explicit means-ends intelligent control strategy for large industrial process plants. The model is used...... in several diagnostic experiments analyzing different fault scenarios. The model and results of the experiments are explained and it is shown how MFM based intelligent modeling and automated reasoning can improve the fault diagnosis process significantly....

Swarm Intelligence for Urban Dynamics Modelling

International Nuclear Information System (INIS)

Ghnemat, Rawan; Bertelle, Cyrille; Duchamp, Gerard H. E.

2009-01-01

In this paper, we propose swarm intelligence algorithms to deal with dynamical and spatial organization emergence. The goal is to model and simulate the developement of spatial centers using multi-criteria. We combine a decentralized approach based on emergent clustering mixed with spatial constraints or attractions. We propose an extension of the ant nest building algorithm with multi-center and adaptive process. Typically, this model is suitable to analyse and simulate urban dynamics like gentrification or the dynamics of the cultural equipment in urban area.

Swarm Intelligence for Urban Dynamics Modelling

Science.gov (United States)

Ghnemat, Rawan; Bertelle, Cyrille; Duchamp, Gérard H. E.

2009-04-01

In this paper, we propose swarm intelligence algorithms to deal with dynamical and spatial organization emergence. The goal is to model and simulate the developement of spatial centers using multi-criteria. We combine a decentralized approach based on emergent clustering mixed with spatial constraints or attractions. We propose an extension of the ant nest building algorithm with multi-center and adaptive process. Typically, this model is suitable to analyse and simulate urban dynamics like gentrification or the dynamics of the cultural equipment in urban area.

Intelligent Hydraulic Actuator and Exp-based Modelling of Losses in Pumps and .

DEFF Research Database (Denmark)

Zhang, Muzhi

A intelligent fuzzy logic self-organising PD+I controller for a gearrotor hydraulic motor was developed and evaluated. Furthermore, a experimental-based modelling methods with a new software tool 'Dynamodata' for modelling of losses in hydraulic motors and pumps was developed.......A intelligent fuzzy logic self-organising PD+I controller for a gearrotor hydraulic motor was developed and evaluated. Furthermore, a experimental-based modelling methods with a new software tool 'Dynamodata' for modelling of losses in hydraulic motors and pumps was developed....

Modeling the prediction of business intelligence system effectiveness.

Science.gov (United States)

Weng, Sung-Shun; Yang, Ming-Hsien; Koo, Tian-Lih; Hsiao, Pei-I

2016-01-01

Although business intelligence (BI) technologies are continually evolving, the capability to apply BI technologies has become an indispensable resource for enterprises running in today's complex, uncertain and dynamic business environment. This study performed pioneering work by constructing models and rules for the prediction of business intelligence system effectiveness (BISE) in relation to the implementation of BI solutions. For enterprises, effectively managing critical attributes that determine BISE to develop prediction models with a set of rules for self-evaluation of the effectiveness of BI solutions is necessary to improve BI implementation and ensure its success. The main study findings identified the critical prediction indicators of BISE that are important to forecasting BI performance and highlighted five classification and prediction rules of BISE derived from decision tree structures, as well as a refined regression prediction model with four critical prediction indicators constructed by logistic regression analysis that can enable enterprises to improve BISE while effectively managing BI solution implementation and catering to academics to whom theory is important.

A new lattice model of traffic flow with the consideration of the driver's forecast effects

Energy Technology Data Exchange (ETDEWEB)

Peng, G.H., E-mail: pengguanghan@yahoo.com.cn [College of Physics and Electronic Science, Hunan University of Arts and Science, Changde 415000 (China); Cai, X.H.; Liu, C.Q.; Cao, B.F. [College of Physics and Electronic Science, Hunan University of Arts and Science, Changde 415000 (China)

2011-05-30

In this Letter, a new lattice model is presented with the consideration of the driver's forecast effects (DFE). The linear stability condition of the extended model is obtained by using the linear stability theory. The analytical results show that the new model can improve the stability of traffic flow by considering DFE. The modified KdV equation near the critical point is derived to describe the traffic jam by nonlinear analysis. Numerical simulation also shows that the new model can improve the stability of traffic flow by adjusting the driver's forecast intensity parameter, which is consistent with the theoretical analysis. -- Highlights: → A new driver's forecast lattice model of traffic flow has been presented. → The driver's forecast effects on the stability of traffic flow have been explored. → The modified KdV equation near the critical point is derived to describe the traffic jam by nonlinear analysis. → The analytical and numerical results show that the driver's forecast effect can improve the stability of traffic flow.

Modeling speech intelligibility in adverse conditions

DEFF Research Database (Denmark)

Dau, Torsten

2012-01-01

) in conditions with nonlinearly processed speech. Instead of considering the reduction of the temporal modulation energy as the intelligibility metric, as assumed in the STI, the sEPSM applies the signal-to-noise ratio in the envelope domain (SNRenv). This metric was shown to be the key for predicting...... understanding speech when more than one person is talking, even when reduced audibility has been fully compensated for by a hearing aid. The reasons for these difficulties are not well understood. This presentation highlights recent concepts of the monaural and binaural signal processing strategies employed...... by the normal as well as impaired auditory system. Jørgensen and Dau [(2011). J. Acoust. Soc. Am. 130, 1475-1487] proposed the speech-based envelope power spectrum model (sEPSM) in an attempt to overcome the limitations of the classical speech transmission index (STI) and speech intelligibility index (SII...

The Actualization of Literary Learning Model Based on Verbal-Linguistic Intelligence

Science.gov (United States)

Hali, Nur Ihsan

2017-01-01

This article is inspired by Howard Gardner's concept of linguistic intelligence and also from some authors' previous writings. All of them became the authors' reference in developing ideas on constructing a literary learning model based on linguistic intelligence. The writing of this article is not done by collecting data empirically, but by…

Systems in Science: Modeling Using Three Artificial Intelligence Concepts.

Science.gov (United States)

Sunal, Cynthia Szymanski; Karr, Charles L.; Smith, Coralee; Sunal, Dennis W.

2003-01-01

Describes an interdisciplinary course focusing on modeling scientific systems. Investigates elementary education majors' applications of three artificial intelligence concepts used in modeling scientific systems before and after the course. Reveals a great increase in understanding of concepts presented but inconsistent application. (Author/KHR)

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...

Description and manual for the use of DRIVER - an interactive modelling aid

CSIR Research Space (South Africa)

Furniss, PR

1977-09-01

Full Text Available The modelling aid DRIVER is described. It permits the interactive manipulation of the parameters and variables of difference models which are implemented as FORTRAN subroutines. Relationships in the model can be expressed as arbitrary functions. A...

Model Pembelajaran Berbasis Penstimulasian Multiple Intelligences Siswa

OpenAIRE

Edy Legowo

2017-01-01

Tulisan ini membahas mengenai penerapan teori multiple intelligences dalam pembelajaran di sekolah. Pembahasan diawali dengan menguraikan perkembangan konsep inteligensi dan multiple intelligences. Diikuti dengan menjelaskan dampak teori multiple intelligences dalam bidang pendidikan dan pembelajaran di sekolah. Bagian selanjutnya menguraikan tentang implementasi teori multiple intelligences dalam praktik pembelajaran di kelas yaitu bagaimana pemberian pengalaman belajar siswa yang difasilita...

Driver fatigue alarm based on eye detection and gaze estimation

Science.gov (United States)

Sun, Xinghua; Xu, Lu; Yang, Jingyu

2007-11-01

The driver assistant system has attracted much attention as an essential component of intelligent transportation systems. One task of driver assistant system is to prevent the drivers from fatigue. For the fatigue detection it is natural that the information about eyes should be utilized. The driver fatigue can be divided into two types, one is the sleep with eyes close and another is the sleep with eyes open. Considering that the fatigue detection is related with the prior knowledge and probabilistic statistics, the dynamic Bayesian network is used as the analysis tool to perform the reasoning of fatigue. Two kinds of experiments are performed to verify the system effectiveness, one is based on the video got from the laboratory and another is based on the video got from the real driving situation. Ten persons participate in the test and the experimental result is that, in the laboratory all the fatigue events can be detected, and in the practical vehicle the detection ratio is about 85%. Experiments show that in most of situations the proposed system works and the corresponding performance is satisfying.

Modeling Crossing Behavior of Drivers at Unsignalized Intersections with Consideration of Risk Perception

Directory of Open Access Journals (Sweden)

Liu Miaomiao

2016-01-01

Full Text Available Drivers’ risk perception is vital to driving behavior and traffic safety. In the dynamic interaction of a driver-vehicle-environment system, drivers’ risk perception changes dynamically. This study focused on drivers’ risk perception at unsignalized intersections in China and analyzed drivers’ crossing behavior. Based on cognitive psychology theory and an adaptive neuro-fuzzy inference system, quantitative models of drivers’ risk perception were established for the crossing processes between two straight-moving vehicles from the orthogonal direction. The acceptable risk perception levels of drivers were identified using a self-developed data analysis method. Based on game theory, the relationship among the quantitative value of drivers’ risk perception, acceptable risk perception level, and vehicle motion state was analyzed. The models of drivers’ crossing behavior were then established. Finally, the behavior models were validated using data collected from real-world vehicle movements and driver decisions. The results showed that the developed behavior models had both high accuracy and good applicability. This study would provide theoretical and algorithmic references for the microscopic simulation and active safety control system of vehicles.

Bayesian Model Averaging of Artificial Intelligence Models for Hydraulic Conductivity Estimation

Science.gov (United States)

Nadiri, A.; Chitsazan, N.; Tsai, F. T.; Asghari Moghaddam, A.

2012-12-01

This research presents a Bayesian artificial intelligence model averaging (BAIMA) method that incorporates multiple artificial intelligence (AI) models to estimate hydraulic conductivity and evaluate estimation uncertainties. Uncertainty in the AI model outputs stems from error in model input as well as non-uniqueness in selecting different AI methods. Using one single AI model tends to bias the estimation and underestimate uncertainty. BAIMA employs Bayesian model averaging (BMA) technique to address the issue of using one single AI model for estimation. BAIMA estimates hydraulic conductivity by averaging the outputs of AI models according to their model weights. In this study, the model weights were determined using the Bayesian information criterion (BIC) that follows the parsimony principle. BAIMA calculates the within-model variances to account for uncertainty propagation from input data to AI model output. Between-model variances are evaluated to account for uncertainty due to model non-uniqueness. We employed Takagi-Sugeno fuzzy logic (TS-FL), artificial neural network (ANN) and neurofuzzy (NF) to estimate hydraulic conductivity for the Tasuj plain aquifer, Iran. BAIMA combined three AI models and produced better fitting than individual models. While NF was expected to be the best AI model owing to its utilization of both TS-FL and ANN models, the NF model is nearly discarded by the parsimony principle. The TS-FL model and the ANN model showed equal importance although their hydraulic conductivity estimates were quite different. This resulted in significant between-model variances that are normally ignored by using one AI model.

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.

Inertial confinement fusion driver enhancements: Final focusing systems and compact heavy-ion driver designs

International Nuclear Information System (INIS)

Bieri, R.L.

1991-01-01

Required elements of an inertial confinement fusion power plant are modeled and discussed. A detailed analysis of two critical elements of candidate drivers is done, and new component designs are proposed to increase the credibility and feasibility of each driver system. An analysis of neutron damage to the final elements of a laser focusing system is presented, and multilayer -- dielectric mirrors are shown to have damage lifetimes which axe too short to be useful in a commercial power plant. A new final-focusing system using grazing incidence metal mirrors to protect sensitive laser optics is designed and shown to be effective in extending the lifetime of the final focusing system. The reflectivities and damage limits of grazing incidence metal mirrors are examined in detail, and the required mirror sizes are shown to be compatible with the beam sizes and illumination geometries currently envisioned for laser drivers. A detailed design and analysis is also done for compact arrays of superconducting magnetic quadrupoles, which are needed in a multi-beam heavy-ion driver. The new array model is developed in more detail than some previous conceptual designs and models arrays which are more compact than arrays scaled from existing single -- quadrupole designs. The improved integrated model for compact arrays is used to compare the effects of various quadrupole array design choices on the size and cost of a heavy-ion driver. Array design choices which significantly affect the cost of a heavy-ion driver include the choice of superconducting material and the thickness of the collar used to support the winding stresses. The effect of these array design choices on driver size and cost is examined and the array model is used to estimate driver cost savings and performance improvements attainable with aggressive quadrupole array designs with high-performance superconductors

INTERACTIVITY OF THE MODERN AUTOMATED SYSTEMS OF THE HELP TO THE DRIVER

Directory of Open Access Journals (Sweden)

Svetlana Alekseevna Vasyugova

2017-09-01

Full Text Available In this article the current technologies in the field of intelligent transportation systems are investigated. The latest systems on control of the safe movement on roads are considered. The analysis of the systems of the help to the driver implemented in cars is carried out. The system concept of the help to the driver of «System help» is offered. Algorithms of work of this system which is based on the principles of interactivity and interaction are investigated. By results of researches experiment on quality of work of system concept of «System help» is made.

Drivers of stability of climate coalitions in the STACO model

NARCIS (Netherlands)

Dellink, R.B.

2011-01-01

This paper investigates which drivers affect the formation and stability of international climate agreements (ICAs). The applied model STACO is used to project costs and benefits of an international agreement on climate change mitigation activities. The simulation results show that an

Dynamic intelligent cleaning model of dirty electric load data

International Nuclear Information System (INIS)

Zhang Xiaoxing; Sun Caixin

2008-01-01

There are a number of dirty data in the load database derived from the supervisory control and data acquisition (SCADA) system. Thus, the data must be carefully and reasonably adjusted before it is used for electric load forecasting or power system analysis. This paper proposes a dynamic and intelligent data cleaning model based on data mining theory. Firstly, on the basis of fuzzy soft clustering, the Kohonen clustering network is improved to fulfill the parallel calculation of fuzzy c-means soft clustering. Then, the proposed dynamic algorithm can automatically find the new clustering center (the characteristic curve of the data) with the updated sample data; At last, it is composed with radial basis function neural network (RBFNN), and then, an intelligent adjusting model is proposed to identify the dirty data. The rapid and dynamic performance of the model makes it suitable for real time calculation, and the efficiency and accuracy of the model is proved by test results of electrical load data analysis in Chongqing

Swarm Intelligence-Based Hybrid Models for Short-Term Power Load Prediction

Directory of Open Access Journals (Sweden)

Jianzhou Wang

2014-01-01

Full Text Available Swarm intelligence (SI is widely and successfully applied in the engineering field to solve practical optimization problems because various hybrid models, which are based on the SI algorithm and statistical models, are developed to further improve the predictive abilities. In this paper, hybrid intelligent forecasting models based on the cuckoo search (CS as well as the singular spectrum analysis (SSA, time series, and machine learning methods are proposed to conduct short-term power load prediction. The forecasting performance of the proposed models is augmented by a rolling multistep strategy over the prediction horizon. The test results are representative of the out-performance of the SSA and CS in tuning the seasonal autoregressive integrated moving average (SARIMA and support vector regression (SVR in improving load forecasting, which indicates that both the SSA-based data denoising and SI-based intelligent optimization strategy can effectively improve the model’s predictive performance. Additionally, the proposed CS-SSA-SARIMA and CS-SSA-SVR models provide very impressive forecasting results, demonstrating their strong robustness and universal forecasting capacities in terms of short-term power load prediction 24 hours in advance.

Dynamical Intention: Integrated Intelligence Modeling for Goal-directed Embodied Agents

Directory of Open Access Journals (Sweden)

Eric Aaron

2016-11-01

Full Text Available Intelligent embodied robots are integrated systems: As they move continuously through their environments, executing behaviors and carrying out tasks, components for low-level and high-level intelligence are integrated in the robot's cognitive system, and cognitive and physical processes combine to create their behavior. For a modeling framework to enable the design and analysis of such integrated intelligence, the underlying representations in the design of the robot should be dynamically sensitive, capable of reflecting both continuous motion and micro-cognitive influences, while also directly representing the necessary beliefs and intentions for goal-directed behavior. In this paper, a dynamical intention-based modeling framework is presented that satisfies these criteria, along with a hybrid dynamical cognitive agent (HDCA framework for employing dynamical intentions in embodied agents. This dynamical intention-HDCA (DI-HDCA modeling framework is a fusion of concepts from spreading activation networks, hybrid dynamical system models, and the BDI (belief-desire-intention theory of goal-directed reasoning, adapted and employed unconventionally to meet entailments of environment and embodiment. The paper presents two kinds of autonomous agent learning results that demonstrate dynamical intentions and the multi-faceted integration they enable in embodied robots: with a simulated service robot in a grid-world office environment, reactive-level learning minimizes reliance on deliberative-level intelligence, enabling task sequencing and action selection to be distributed over both deliberative and reactive levels; and with a simulated game of Tag, the cognitive-physical integration of an autonomous agent enables the straightforward learning of a user-specified strategy during gameplay, without interruption to the game. In addition, the paper argues that dynamical intentions are consistent with cognitive theory underlying goal-directed behavior, and

Modeling and analyses for an extended car-following model accounting for drivers' situation awareness from cyber physical perspective

Science.gov (United States)

Chen, Dong; Sun, Dihua; Zhao, Min; Zhou, Tong; Cheng, Senlin

2018-07-01

In fact, driving process is a typical cyber physical process which couples tightly the cyber factor of traffic information with the physical components of the vehicles. Meanwhile, the drivers have situation awareness in driving process, which is not only ascribed to the current traffic states, but also extrapolates the changing trend. In this paper, an extended car-following model is proposed to account for drivers' situation awareness. The stability criterion of the proposed model is derived via linear stability analysis. The results show that the stable region of proposed model will be enlarged on the phase diagram compared with previous models. By employing the reductive perturbation method, the modified Korteweg de Vries (mKdV) equation is obtained. The kink-antikink soliton of mKdV equation reveals theoretically the evolution of traffic jams. Numerical simulations are conducted to verify the analytical results. Two typical traffic Scenarios are investigated. The simulation results demonstrate that drivers' situation awareness plays a key role in traffic flow oscillations and the congestion transition.

Towards a social psychology-based microscopic model of driver behavior and decision-making : modifying Lewin's field theory

Science.gov (United States)

2014-01-01

Central to effective roadway design is the ability to understand how drivers behave as they traverse a segment of : roadway. While simple and complex microscopic models have been used over the years to analyse driver behaviour, : most models: 1.) inc...

An Analytical Model / Emotional Intelligence Quotient and QOL in Mothers with Infants in Japan.

Science.gov (United States)

Ohashi, Junko; Katsura, Toshiki; Hoshino, Akiko; Usui, Kanae

2013-01-01

The purpose of this study was to examine the relationship between the emotional intelligence quotient and health-related quality of life using structural equation modeling. A self-administered questionnaire survey was conducted among 1,911 mothers who visited the Health Center for an infant medical examination. A hypothetical model was constructed using variables of the emotional intelligence quotient, social support, coping, parenting stress, and perceived health competence. There were a total of 1,104 valid responses (57.8%). Significant standardized estimates were obtained, confirming the goodness of fit issues with the model. The emotional intelligence quotient had a strong impact on physical and psychological quality of life, and showed the greatest association with coping. This study differed from previous studies in that, due to the inclusion of social support and explanatory variables in coping, an increase in coping strategies was more highly associated with emotional intelligence quotient levels than with social support. An enhanced emotional intelligence quotient should be considered a primary objective to promote the health of mothers with infant children.

Generic Model Predictive Control Framework for Advanced Driver Assistance Systems

NARCIS (Netherlands)

Wang, M.

2014-01-01

This thesis deals with a model predictive control framework for control design of Advanced Driver Assistance Systems, where car-following tasks are under control. The framework is applied to design several autonomous and cooperative controllers and to examine the controller properties at the

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.

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.

Is it reliable that speed-calming solutions as ISA can reach the drivers, who needed it most?

DEFF Research Database (Denmark)

Agerholm, Niels

A significant number of trials with Intelligent Speed Adaptation (ISA) have been carried out within the last two decades. Almost all with a promising result; the drivers reduce their proportion of speeding and are in general positive to ISA. However, two tings question this offhand success story; 1......: there has been no commercial break through for ISA so far, even though estimated has shown that ISA can reduce the n. of fatalities in traffic accidents with up to 59%, and 2: in the only ISA trial included drivers, who not participated voluntary in the trial, ISA had virtually no effect on these drivers...

The Construction of Intelligent English Teaching Model Based on Artificial Intelligence

Directory of Open Access Journals (Sweden)

Xiaoguang Li

2017-12-01

Full Text Available In order to build a modernized tool platform that can help students improve their English learning efficiency according to their mastery of knowledge and personality, this paper develops an online intelligent English learning system that uses Java and artificial intelligence language Prolog as the software system. This system is a creative reflection of the thoughts of expert system in artificial intelligence. Established on the Struts Spring Hibernate lightweight JavaEE framework, the system modules are coupled with each other in a much lower degree, which is convenient to future function extension. Combined with the idea of expert system in artificial intelligence, the system developed appropriate learning strategies to help students double the learning effect with half the effort; Finally, the system takes into account the forgetting curve of memory, on which basis the knowledge that has been learned will be tested periodically, intending to spare students’ efforts to do a sea of exercises and obtain better learning results.

Study on driving control behavior for lane change maneuver. Analysis of expert driver using neural network system; Shasen henkoji no driver sosa tokusei. Neural network system ni yoru jukuren driver no kaiseki

Energy Technology Data Exchange (ETDEWEB)

Yang, Z; Okayama, T; Katayama, T [Japan Automobile Research Institute Inc., Tsukuba (Japan); Kageyama, I [Nihon University, Tokyo (Japan)

1997-10-01

In order to study driver steering control behavior for vehicle, a driver model for single-lane change maneuver is constructed by a neural network system concerned with the man-machine-environment system. And, using sensitivity analysis, it is found that the model represent the driver control behavior, and the relation between the driver control behavior and vehicle responses. The sensitivity analysis is also examined by applying to the 2nd order predictive driver model. The validity of the sensitivity analysis is confirmed. 5 refs., 8 figs.

A Theoretical Assessment on Emotional Intelligence as a Competitive Managerial Skill

Directory of Open Access Journals (Sweden)

Burcu Hacioglu

2016-01-01

Full Text Available Emotion as the main motive underlying the human behaviors is a concept that has been researched by many disciplines in the social sciences. Deriving from behavioral studies on emotions, Emotional Intelligence as a critical concept in organizational behavior studies is attached to the assestment of employee motivation and performance drivers. In this study, a theoretical framework for the emotional intelligence in workplace has been assessed. The major contribution of the concept in competitive business strategies from managerial scope has been evaluated.

Heavy-ion driver parametric studies and choice of a base 5 mega-joule driver design

International Nuclear Information System (INIS)

Bieri, R.; Meier, W.

1992-01-01

Parametric studies to optimize heavy-ion driver designs are described and an optimized 5 MJ driver design is described. Parametric studies are done on driver parameters including driver energy, number of beams, type of superconductor used in focusing magnets, maximum magnetic field allowed at the superconducting windings, axial quadrupole field packing fraction, ion mass, and ion charge state. All modeled drivers use the maximum beam currents allowed by the Maschke limits; driver scaling is described in a companion paper. The optimized driver described is conservative and cost effective. The base driver direct costs are only $120/Joule, and the base driver uses no recirculation, beam combination, or beam separation. The low driver cost achieved is due, in part, to the use of compact Nb 3 Sn quadrupole arrays, but results primarily from optimization over the large, multi-dimensional, parameter space available for heavy-ion drivers

The effect of learning models and emotional intelligence toward students learning outcomes on reaction rate

Science.gov (United States)

Sutiani, Ani; Silitonga, Mei Y.

2017-08-01

This research focused on the effect of learning models and emotional intelligence in students' chemistry learning outcomes on reaction rate teaching topic. In order to achieve the objectives of the research, with 2x2 factorial research design was used. There were two factors tested, namely: the learning models (factor A), and emotional intelligence (factor B) factors. Then, two learning models were used; problem-based learning/PBL (A1), and project-based learning/PjBL (A2). While, the emotional intelligence was divided into higher and lower types. The number of population was six classes containing 243 grade X students of SMAN 10 Medan, Indonesia. There were 15 students of each class were chosen as the sample of the research by applying purposive sampling technique. The data were analyzed by applying two-ways analysis of variance (2X2) at the level of significant α = 0.05. Based on hypothesis testing, there was the interaction between learning models and emotional intelligence in students' chemistry learning outcomes. Then, the finding of the research showed that students' learning outcomes in reaction rate taught by using PBL with higher emotional intelligence is higher than those who were taught by using PjBL. There was no significant effect between students with lower emotional intelligence taught by using both PBL and PjBL in reaction rate topic. Based on the finding, the students with lower emotional intelligence were quite hard to get in touch with other students in group discussion.

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.

Artificial Intelligence Software Engineering (AISE) model

Science.gov (United States)

Kiss, Peter A.

1990-01-01

The American Institute of Aeronautics and Astronautics has initiated a committee on standards for Artificial Intelligence. Presented are the initial efforts of one of the working groups of that committee. A candidate model is presented for the development life cycle of knowledge based systems (KBSs). The intent is for the model to be used by the aerospace community and eventually be evolved into a standard. The model is rooted in the evolutionary model, borrows from the spiral model, and is embedded in the standard Waterfall model for software development. Its intent is to satisfy the development of both stand-alone and embedded KBSs. The phases of the life cycle are shown and detailed as are the review points that constitute the key milestones throughout the development process. The applicability and strengths of the model are discussed along with areas needing further development and refinement by the aerospace community.

Research on Evaluation Model for Secondary Task Driving Safety Based on Driver Eye Movements

Directory of Open Access Journals (Sweden)

Lisheng Jin

2014-01-01

Full Text Available This study was designed to gain insight into the influence of performing different types of secondary task while driving on driver eye movements and to build a safety evaluation model for secondary task driving. Eighteen young drivers were selected and completed the driving experiment on a driving simulator. Measures of fixations, saccades, and blinks were analyzed. Based on measures which had significant difference between the baseline and secondary tasks driving conditions, the evaluation index system was built. Method of principal component analysis (PCA was applied to analyze evaluation indexes data in order to obtain the coefficient weights of indexes and build the safety evaluation model. Based on evaluation scores, the driving safety was grouped into five levels (very high, high, average, low, and very low using K-means clustering algorithm. Results showed that secondary task driving severely distracts the driver and the evaluation model built in this study could estimate driving safety effectively under different driving conditions.

Analyzing the Influence of Mobile Phone Use of Drivers on Traffic Flow Based on an Improved Cellular Automaton Model

Directory of Open Access Journals (Sweden)

Yao Xiao

2015-01-01

Full Text Available This paper aimed to analyze the influence of drivers’ behavior of phone use while driving on traffic flow, including both traffic efficiency and traffic safety. An improved cellular automaton model was proposed to simulate traffic flow with distracted drivers based on the Nagel-Schreckenberg model. The driving characters of drivers using a phone were first discussed and a value representing the probability to use a phone while driving was put into the CA model. Simulation results showed that traffic flow rate was significantly reduced if some drivers used a phone compared to no phone use. The flow rate and velocity decreased as the proportion of drivers using a phone increased. While, under low density, the risk of traffic decreased first and then increased as the distracted drivers increased, the distracted behavior of drivers, like using a phone, could reduce the flow rate by 5 percent according to the simulation.

The Train Driver Recovery Problem - a Set Partitioning Based Model and Solution Method

DEFF Research Database (Denmark)

Rezanova, Natalia Jurjevna; Ryan, David

2010-01-01

The need to recover a train driver schedule occurs during major disruptions in the daily railway operations. Based on data from the Danish passenger railway operator DSB S-tog A/S, a solution method to the train driver recovery problem (TDRP) is developed. The TDRP is formulated as a set...... branching strategy using the depth-first search of the Branch & Bound tree. The LP relaxation of the TDRP possesses strong integer properties. We present test scenarios generated from the historical real-life operations data of DSB S-tog A/S. The numerical results show that all but one tested instances...... partitioning problem. We define a disruption neighbourhood by identifying a small set of drivers and train tasks directly affected by the disruption. Based on the disruption neighbourhood, the TDRP model is formed and solved. If the TDRP solution provides a feasible recovery for the drivers within...

Associating Crash Avoidance Maneuvers with Driver Attributes and Accident Characteristics: A Mixed Logit Model Approach

DEFF Research Database (Denmark)

Kaplan, Sigal; Prato, Carlo Giacomo

2012-01-01

as from the key role of the ability of drivers to perform effective corrective maneuvers for the success of automated in-vehicle warning and driver assistance systems. The analysis is conducted by means of a mixed logit model that accommodates correlations across alternatives and heteroscedasticity. Data...

World modeling for cooperative intelligent vehicles

NARCIS (Netherlands)

Papp, Z.; Brown, C.; Bartels, C.

2008-01-01

Cooperative intelligent vehicle systems constitute a promising way to improving traffic throughput, safety and comfort. The state-of-the-art intelligent-vehicle applications usually can be described as a collection of interacting, highly autonomous, complex dynamical systems (the individual

Evaluation of intelligent transport systems impact on school transport safety

Directory of Open Access Journals (Sweden)

Jankowska-Karpa Dagmara

2017-01-01

Full Text Available The integrated system of safe transport of children to school using Intelligent Transport Systems was developed and implemented in four locations across Europe under the Safeway2School (SW2S project, funded by the EU. The SW2S system evaluation included speed measurements and an eye-tracking experiment carried out among drivers who used the school bus route, where selected elements of the system were tested. The subject of the evaluation were the following system elements: pedestrian safety system at the bus stop (Intelligent Bus Stop and tags for children, Driver Support System, applications for parents’ and students’ mobile phones, bus stop inventory tool and data server. A new sign designed for buses and bus stops to inform about child transportation/children waiting at the bus stop was added to the system. Training schemes for system users were also provided. The article presents evaluation results of the impact of selected elements of the SW2S system on school transport safety in Poland.

FRIB driver linac vacuum model and benchmarks

CERN Document Server

Durickovic, Bojan; Kersevan, Roberto; Machicoane, Guillaume

2014-01-01

The Facility for Rare Isotope Beams (FRIB) is a superconducting heavy-ion linear accelerator that is to produce rare isotopes far from stability for low energy nuclear science. In order to achieve this, its driver linac needs to achieve a very high beam current (up to 400 kW beam power), and this requirement makes vacuum levels of critical importance. Vacuum calculations have been carried out to verify that the vacuum system design meets the requirements. The modeling procedure was benchmarked by comparing models of an existing facility against measurements. In this paper, we present an overview of the methods used for FRIB vacuum calculations and simulation results for some interesting sections of the accelerator. (C) 2013 Elsevier Ltd. All rights reserved.

Evaluating the Risk of Metabolic Syndrome Based on an Artificial Intelligence Model

Directory of Open Access Journals (Sweden)

Hui Chen

2014-01-01

Full Text Available Metabolic syndrome is worldwide public health problem and is a serious threat to people's health and lives. Understanding the relationship between metabolic syndrome and the physical symptoms is a difficult and challenging task, and few studies have been performed in this field. It is important to classify adults who are at high risk of metabolic syndrome without having to use a biochemical index and, likewise, it is important to develop technology that has a high economic rate of return to simplify the complexity of this detection. In this paper, an artificial intelligence model was developed to identify adults at risk of metabolic syndrome based on physical signs; this artificial intelligence model achieved more powerful capacity for classification compared to the PCLR (principal component logistic regression model. A case study was performed based on the physical signs data, without using a biochemical index, that was collected from the staff of Lanzhou Grid Company in Gansu province of China. The results show that the developed artificial intelligence model is an effective classification system for identifying individuals at high risk of metabolic syndrome.

A Multidisciplinary Model for Development of Intelligent Computer-Assisted Instruction.

Science.gov (United States)

Park, Ok-choon; Seidel, Robert J.

1989-01-01

Proposes a schematic multidisciplinary model to help developers of intelligent computer-assisted instruction (ICAI) identify the types of required expertise and integrate them into a system. Highlights include domain types and expertise; knowledge acquisition; task analysis; knowledge representation; student modeling; diagnosis of learning needs;…

VEHIL: a full-scale test methodology for intelligent transport systems, vehicles and subsystems

NARCIS (Netherlands)

Verhoeff, L.; Verburg, D.J.; Lupker, H.A.; Kusters, L.J.J.

2000-01-01

To enhance the efficiency and safety of today's road transport, the application of driver support systems and fully automated, intelligent transport systems becomes increasingly important. The safety and reliability requirements of these systems and their complexity are high, which results in a

Machine learning methods for locating re-entrant drivers from electrograms in a model of atrial fibrillation

Science.gov (United States)

McGillivray, Max Falkenberg; Cheng, William; Peters, Nicholas S.; Christensen, Kim

2018-04-01

Mapping resolution has recently been identified as a key limitation in successfully locating the drivers of atrial fibrillation (AF). Using a simple cellular automata model of AF, we demonstrate a method by which re-entrant drivers can be located quickly and accurately using a collection of indirect electrogram measurements. The method proposed employs simple, out-of-the-box machine learning algorithms to correlate characteristic electrogram gradients with the displacement of an electrogram recording from a re-entrant driver. Such a method is less sensitive to local fluctuations in electrical activity. As a result, the method successfully locates 95.4% of drivers in tissues containing a single driver, and 95.1% (92.6%) for the first (second) driver in tissues containing two drivers of AF. Additionally, we demonstrate how the technique can be applied to tissues with an arbitrary number of drivers. In its current form, the techniques presented are not refined enough for a clinical setting. However, the methods proposed offer a promising path for future investigations aimed at improving targeted ablation for AF.

Driver's Behavior and Decision-Making Optimization Model in Mixed Traffic Environment

Directory of Open Access Journals (Sweden)

Xiaoyuan Wang

2015-02-01

Full Text Available Driving process is an information treating procedure going on unceasingly. It is very important for the research of traffic flow theory, to study on drivers' information processing pattern in mixed traffic environment. In this paper, bicycle is regarded as a kind of information source to vehicle drivers; the “conflict point method” is brought forward to analyze the influence of bicycles on driving behavior. The “conflict” is studied to be translated into a special kind of car-following or lane-changing process. Furthermore, the computer clocked scan step length is dropped to 0.1 s, in order to scan and analyze the dynamic (static information which influences driving behavior in a more exact way. The driver's decision-making process is described through information fusion based on duality contrast and fuzzy optimization theory. The model test and verification show that the simulation results with the “conflict point method” and the field data are consistent basically. It is feasible to imitate driving behavior and the driver information fusion process with the proposed methods. Decision-making optimized process can be described more accurately through computer precision clocked scan strategy. The study in this paper can provide the foundation for further research of multiresource information fusion process of driving behavior.

Incorporating driver distraction in car-following models: Applying the TCI to the IDM

OpenAIRE

Hoogendoorn, R.G.; van Arem, B.; Hoogendoorn, S.P.

2013-01-01

ITS can play a significant role in the improvement of traffic flow, traffic safety and greenhouse gas emissions. However, the implementation of Advanced Driver Assistance Systems may lead to adaptation effects in longitudinal driving behavior following driver distraction. It was however not yet clear how to model these adaptation effects in driving behavior mathematically and on which theoretical framework this should be grounded. To this end in this contribution we introduce a theoretical fr...

Artificial intelligence and exponential technologies business models evolution and new investment opportunities

CERN Document Server

Corea, Francesco

2017-01-01

Artificial Intelligence is a huge breakthrough technology that is changing our world. It requires some degrees of technical skills to be developed and understood, so in this book we are going to first of all define AI and categorize it with a non-technical language. We will explain how we reached this phase and what historically happened to artificial intelligence in the last century. Recent advancements in machine learning, neuroscience, and artificial intelligence technology will be addressed, and new business models introduced for and by artificial intelligence research will be analyzed. Finally, we will describe the investment landscape, through the quite comprehensive study of almost 14,000 AI companies and we will discuss important features and characteristics of both AI investors as well as investments. This is the “Internet of Thinks” era. AI is revolutionizing the world we live in. It is augmenting the human experiences, and it targets to amplify human intelligence in a future not so distant from...

Parking guidance - modelling, simulation and impact assessment

NARCIS (Netherlands)

Jonkers, E.; Noort, M. van; Veen, J.L. van der

2011-01-01

Intelligent parking services that help drivers with reservation of a parking spot, navigation and automated payment have reached the deployment phase. These services may provide significant benefits to drivers and municipalities. Drivers may experience an increase in comfort and lower and more

Intelligence Is What the Intelligence Test Measures. Seriously

Directory of Open Access Journals (Sweden)

Han L. J. van der Maas

2014-02-01

Full Text Available The mutualism model, an alternative for the g-factor model of intelligence, implies a formative measurement model in which “g” is an index variable without a causal role. If this model is accurate, the search for a genetic of brain instantiation of “g” is deemed useless. This also implies that the (weighted sum score of items of an intelligence test is just what it is: a weighted sum score. Preference for one index above the other is a pragmatic issue that rests mainly on predictive value.

Artificial intelligence based models for stream-flow forecasting: 2000-2015

Science.gov (United States)

Yaseen, Zaher Mundher; El-shafie, Ahmed; Jaafar, Othman; Afan, Haitham Abdulmohsin; Sayl, Khamis Naba

2015-11-01

The use of Artificial Intelligence (AI) has increased since the middle of the 20th century as seen in its application in a wide range of engineering and science problems. The last two decades, for example, has seen a dramatic increase in the development and application of various types of AI approaches for stream-flow forecasting. Generally speaking, AI has exhibited significant progress in forecasting and modeling non-linear hydrological applications and in capturing the noise complexity in the dataset. This paper explores the state-of-the-art application of AI in stream-flow forecasting, focusing on defining the data-driven of AI, the advantages of complementary models, as well as the literature and their possible future application in modeling and forecasting stream-flow. The review also identifies the major challenges and opportunities for prospective research, including, a new scheme for modeling the inflow, a novel method for preprocessing time series frequency based on Fast Orthogonal Search (FOS) techniques, and Swarm Intelligence (SI) as an optimization approach.

Hidden Hearing Loss and Computational Models of the Auditory Pathway: Predicting Speech Intelligibility Decline

Science.gov (United States)

2016-11-28

Title: Hidden Hearing Loss and Computational Models of the Auditory Pathway: Predicting Speech Intelligibility Decline Christopher J. Smalt...representation of speech intelligibility in noise. The auditory-periphery model of Zilany et al. (JASA 2009,2014) is used to make predictions of...auditory nerve (AN) responses to speech stimuli under a variety of difficult listening conditions. The resulting cochlear neurogram, a spectrogram

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...

The experiment of cooperative learning model type team assisted individualization (TAI) on three-dimensional space subject viewed from spatial intelligence

Science.gov (United States)

Manapa, I. Y. H.; Budiyono; Subanti, S.

2018-03-01

The aim of this research is to determine the effect of TAI or direct learning (DL) on student’s mathematics achievement viewed from spatial intelligence. This research was quasi experiment. The population was 10th grade senior high school students in Alor Regency on academic year of 2015/2016 chosen by stratified cluster random sampling. The data were collected through achievement and spatial intelligence test. The data were analyzed by two ways, ANOVA with unequal cell and scheffe test. This research showed that student’s mathematics achievement used in TAI had better results than DL models one. In spatial intelligence category, student’s mathematics achievement with high spatial intelligence has better result than the other spatial intelligence category and students with high spatial intelligence have better results than those with middle spatial intelligence category. At TAI, student’s mathematics achievement with high spatial intelligence has better result than those with the other spatial intelligence category and students with middle spatial intelligence have better results than students with low spatial intelligence. In DL model, student’s mathematics achievement with high and middle spatial intelligence has better result than those with low spatial intelligence, but students with high spatial intelligence and middle spatial intelligence have no significant difference. In each category of spatial intelligence and learning model, mathematics achievement has no significant difference.

MACRO MODEL OF SEAT BELT USE BY CAR DRIVERS AND PASSENGERS

Directory of Open Access Journals (Sweden)

Kazimierz JAMROZ

2013-12-01

Full Text Available The article presents some problems of seat belt use by car drivers and passengers. It looks in particular at seat belt use and effectiveness in selected countries. Next, factors of seat belt use are presented and methodology of model development. A macro model of seat belt use is presented based on data from around fifty countries from different continents.

Spatially-explicit modeling of multi-scale drivers of aboveground forest biomass and water yield in watersheds of the Southeastern United States.

Science.gov (United States)

Ajaz Ahmed, Mukhtar Ahmed; Abd-Elrahman, Amr; Escobedo, Francisco J; Cropper, Wendell P; Martin, Timothy A; Timilsina, Nilesh

2017-09-01

Understanding ecosystem processes and the influence of regional scale drivers can provide useful information for managing forest ecosystems. Examining more local scale drivers of forest biomass and water yield can also provide insights for identifying and better understanding the effects of climate change and management on forests. We used diverse multi-scale datasets, functional models and Geographically Weighted Regression (GWR) to model ecosystem processes at the watershed scale and to interpret the influence of ecological drivers across the Southeastern United States (SE US). Aboveground forest biomass (AGB) was determined from available geospatial datasets and water yield was estimated using the Water Supply and Stress Index (WaSSI) model at the watershed level. Our geostatistical model examined the spatial variation in these relationships between ecosystem processes, climate, biophysical, and forest management variables at the watershed level across the SE US. Ecological and management drivers at the watershed level were analyzed locally to identify whether drivers contribute positively or negatively to aboveground forest biomass and water yield ecosystem processes and thus identifying potential synergies and tradeoffs across the SE US region. Although AGB and water yield drivers varied geographically across the study area, they were generally significantly influenced by climate (rainfall and temperature), land-cover factor1 (Water and barren), land-cover factor2 (wetland and forest), organic matter content high, rock depth, available water content, stand age, elevation, and LAI drivers. These drivers were positively or negatively associated with biomass or water yield which significantly contributes to ecosystem interactions or tradeoff/synergies. Our study introduced a spatially-explicit modelling framework to analyze the effect of ecosystem drivers on forest ecosystem structure, function and provision of services. This integrated model approach facilitates

Modeling Speech Intelligibility in Hearing Impaired Listeners

DEFF Research Database (Denmark)

Scheidiger, Christoph; Jørgensen, Søren; Dau, Torsten

2014-01-01

speech, e.g. phase jitter or spectral subtraction. Recent studies predict SI for normal-hearing (NH) listeners based on a signal-to-noise ratio measure in the envelope domain (SNRenv), in the framework of the speech-based envelope power spectrum model (sEPSM, [20, 21]). These models have shown good...... agreement with measured data under a broad range of conditions, including stationary and modulated interferers, reverberation, and spectral subtraction. Despite the advances in modeling intelligibility in NH listeners, a broadly applicable model that can predict SI in hearing-impaired (HI) listeners...... is not yet available. As a firrst step towards such a model, this study investigates to what extent eects of hearing impairment on SI can be modeled in the sEPSM framework. Preliminary results show that, by only modeling the loss of audibility, the model cannot account for the higher speech reception...

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...

Intelligent Metering for Urban Water: A Review

Directory of Open Access Journals (Sweden)

Rodney Stewart

2013-07-01

Full Text Available This paper reviews the drivers, development and global deployment of intelligent water metering in the urban context. Recognising that intelligent metering (or smart metering has the potential to revolutionise customer engagement and management of urban water by utilities, this paper provides a summary of the knowledge-base for researchers and industry practitioners to ensure that the technology fosters sustainable urban water management. To date, roll-outs of intelligent metering have been driven by the desire for increased data regarding time of use and end-use (such as use by shower, toilet, garden, etc. as well as by the ability of the technology to reduce labour costs for meter reading. Technology development in the water sector generally lags that seen in the electricity sector. In the coming decade, the deployment of intelligent water metering will transition from being predominantly “pilot or demonstration scale” with the occasional city-wide roll-out, to broader mainstream implementation. This means that issues which have hitherto received little focus must now be addressed, namely: the role of real-time data in customer engagement and demand management; data ownership, sharing and privacy; technical data management and infrastructure security, utility workforce skills; and costs and benefits of implementation.

An application of artificial intelligence for rainfall–runoff modeling

Indian Academy of Sciences (India)

This study proposes an application of two techniques of artificial intelligence (AI) for rainfall–runoff modeling: the artificial neural networks (ANN) and the evolutionary computation (EC). Two diff- erent ANN techniques, the feed forward back propagation (FFBP) and generalized regression neural network (GRNN) methods ...

A Model for Organizational Intelligence in Islamic Azad University (Zone 8

Directory of Open Access Journals (Sweden)

Masoumeh Erfani Khanghahi

2013-08-01

Full Text Available Today organizations are faced with the rapidly changeable events in economical, technological, social, cultural and political environment. Successful and dynamic reaction of organizations depends on their ability to provide relevant information and to find, at the same time, adequate solutions to the problems they are faced with. In that sense, the attention of organizational theoreticians is focused on designing of intellectual abilities of organization and new concept in organizational theory has developed organizational intelligence (OI. In two decades ago, theoretical models have been developed and little research has been conducted. Having a model for defining and assessing the organizational status of an organization can be very helpful but the key questions facing every manager are; how can the level of collective intelligence be promoted? And what factors influence OI? Therefore this research carried out in order to assess OI and its factors influencing I.A.U. and provide a structural equation model. The subject of the study was 311 faculty members of I.A.U (Zone 8. Faculty members completed OI questionnaire (Cronbach's alpha=0.98, learning climate (Cronbach's alpha=0.94, multifactor leadership questionnaire (Cronbach's alpha =0.92 and organizational learning audit (Cronbach's alpha =0.94. Findings of this research showed that mean of organizational intelligence, organizational learning and learning culture were less than mean and transformational leadership was more than mean of questionnaire. Lisrel project software was applied for confirmatory factor analysis (CFA and structural equation modeling (SEM. Based on the tested structural equation model, transformational leadership style had direct impact on learning culture $(eta=0.78$, learning culture had a direct impact on OI $(eta=0.46$, organizational learning had a direct impact on OI $(eta=0.34$ and learning culture had a direct impact on organizational learning $(eta=0.96$. The

Neurocognitive Correlates of Young Drivers' Performance in a Driving Simulator.

Science.gov (United States)

Guinosso, Stephanie A; Johnson, Sara B; Schultheis, Maria T; Graefe, Anna C; Bishai, David M

2016-04-01

Differences in neurocognitive functioning may contribute to driving performance among young drivers. However, few studies have examined this relation. This pilot study investigated whether common neurocognitive measures were associated with driving performance among young drivers in a driving simulator. Young drivers (19.8 years (standard deviation [SD] = 1.9; N = 74)) participated in a battery of neurocognitive assessments measuring general intellectual capacity (Full-Scale Intelligence Quotient, FSIQ) and executive functioning, including the Stroop Color-Word Test (cognitive inhibition), Wisconsin Card Sort Test-64 (cognitive flexibility), and Attention Network Task (alerting, orienting, and executive attention). Participants then drove in a simulated vehicle under two conditions-a baseline and driving challenge. During the driving challenge, participants completed a verbal working memory task to increase demand on executive attention. Multiple regression models were used to evaluate the relations between the neurocognitive measures and driving performance under the two conditions. FSIQ, cognitive inhibition, and alerting were associated with better driving performance at baseline. FSIQ and cognitive inhibition were also associated with better driving performance during the verbal challenge. Measures of cognitive flexibility, orienting, and conflict executive control were not associated with driving performance under either condition. FSIQ and, to some extent, measures of executive function are associated with driving performance in a driving simulator. Further research is needed to determine if executive function is associated with more advanced driving performance under conditions that demand greater cognitive load. Copyright © 2016 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

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.

Intelligent Model Management in a Forest Ecosystem Management Decision Support System

Science.gov (United States)

Donald Nute; Walter D. Potter; Frederick Maier; Jin Wang; Mark Twery; H. Michael Rauscher; Peter Knopp; Scott Thomasma; Mayukh Dass; Hajime Uchiyama

2002-01-01

Decision making for forest ecosystem management can include the use of a wide variety of modeling tools. These tools include vegetation growth models, wildlife models, silvicultural models, GIS, and visualization tools. NED-2 is a robust, intelligent, goal-driven decision support system that integrates tools in each of these categories. NED-2 uses a blackboard...

Conceptual Model of Business Value of Business Intelligence Systems

OpenAIRE

Popovič, Aleš; Turk, Tomaž; Jaklič, Jurij

2010-01-01

With advances in the business intelligence area, there is an increasing interest for the introduction of business intelligence systems into organizations. Although the opinion about business intelligence and its creation of business value is generally accepted, economic justification of investments into business intelligence systems is not always clear. Measuring the business value of business intelligence in practice is often not carried out due to the lack of measurement methods and resourc...

An Analytical Model / Emotional Intelligence Quotient and QOL in Mothers with Infants in Japan

OpenAIRE

Ohashi, Junko; Katsura, Toshiki; Hoshino, Akiko; Usui, Kanae

2013-01-01

Objective: The purpose of this study was to examine the relationship between the emotional intelligence quotient and health-related quality of life using structural equation modeling. Methods: A self-administered questionnaire survey was conducted among 1,911 mothers who visited the Health Center for an infant medical examination. A hypothetical model was constructed using variables of the emotional intelligence quotient, social support, coping, parenting stress, and perceived health competen...

An Intelligent Model for Pairs Trading Using Genetic Algorithms.

Science.gov (United States)

Huang, Chien-Feng; Hsu, Chi-Jen; Chen, Chi-Chung; Chang, Bao Rong; Li, Chen-An

2015-01-01

Pairs trading is an important and challenging research area in computational finance, in which pairs of stocks are bought and sold in pair combinations for arbitrage opportunities. Traditional methods that solve this set of problems mostly rely on statistical methods such as regression. In contrast to the statistical approaches, recent advances in computational intelligence (CI) are leading to promising opportunities for solving problems in the financial applications more effectively. In this paper, we present a novel methodology for pairs trading using genetic algorithms (GA). Our results showed that the GA-based models are able to significantly outperform the benchmark and our proposed method is capable of generating robust models to tackle the dynamic characteristics in the financial application studied. Based upon the promising results obtained, we expect this GA-based method to advance the research in computational intelligence for finance and provide an effective solution to pairs trading for investment in practice.

Application of instrument platform based embedded Linux system on intelligent scaler

International Nuclear Information System (INIS)

Wang Jikun; Yang Run'an; Xia Minjian; Yang Zhijun; Li Lianfang; Yang Binhua

2011-01-01

It designs a instrument platform based on embedded Linux system and peripheral circuit, by designing Linux device driver and application program based on QT Embedded, various functions of the intelligent scaler are realized. The system architecture is very reasonable, so the stability and the expansibility and the integration level are increased, the development cycle is shorten greatly. (authors)

Modelling benthic biophysical drivers of ecosystem structure and biogeochemical response

Science.gov (United States)

Stephens, Nicholas; Bruggeman, Jorn; Lessin, Gennadi; Allen, Icarus

2016-04-01

The fate of carbon deposited at the sea floor is ultimately decided by biophysical drivers that control the efficiency of remineralisation and timescale of carbon burial in sediments. Specifically, these drivers include bioturbation through ingestion and movement, burrow-flushing and sediment reworking, which enhance vertical particulate transport and solute diffusion. Unfortunately, these processes are rarely satisfactorily resolved in models. To address this, a benthic model that explicitly describes the vertical position of biology (e.g., habitats) and biogeochemical processes is presented that includes biological functionality and biogeochemical response capturing changes in ecosystem structure, benthic-pelagic fluxes and biodiversity on inter-annual timescales. This is demonstrated by the model's ability to reproduce temporal variability in benthic infauna, vertical pore water nutrients and pelagic-benthic solute fluxes compared to in-situ data. A key advance is the replacement of bulk parameterisation of bioturbation by explicit description of the bio-physical processes responsible. This permits direct comparison with observations and determination of key parameters in experiments. Crucially, the model resolves the two-way interaction between sediment biogeochemistry and ecology, allowing exploration of the benthic response to changing environmental conditions, the importance of infaunal functional traits in shaping benthic ecological structure and the feedback the resulting bio-physical processes exert on pore water nutrient profiles. The model is actively being used to understand shelf sea carbon cycling, the response of the benthos to climatic change, food provision and other societal benefits.

Determining Time-Varying Drivers of Spot Oil Price in a Dynamic Model Averaging Framework

Directory of Open Access Journals (Sweden)

Krzysztof Drachal

2018-05-01

Full Text Available This article presents results from modelling spot oil prices by Dynamic Model Averaging (DMA. First, based on a literature review and availability of data, the following oil price drivers have been selected: stock prices indices, stock prices volatility index, exchange rates, global economic activity, interest rates, supply and demand indicators and inventories level. Next, they have been included as explanatory variables in various DMA models with different initial parameters. Monthly data between January 1986 and December 2015 has been analyzed. Several variations of DMA models have been constructed, because DMA requires the initial setting of certain parameters. Interestingly, DMA has occurred to be robust to setting different values to these parameters. It has also occurred that the quality of prediction is the highest for the model with the drivers solely connected with the stock markets behavior. Drivers connected with macroeconomic fundamental indicators have not been found so important. This observation can serve as an argument favoring the hypothesis of the increasing financialization of the oil market, at least in the short-term period. The predictions from other, slightly different modelling variations based on DMA methodology, have happened to be consistent with each other in general. Many constructed models have outperformed alternative forecasting methods. It has also been found that normalization of the initial data, although not necessary for DMA from the theoretical point of view, significantly improves the quality of prediction.

Resource Aware Intelligent Network Services (RAINS) Final Technical Report

Energy Technology Data Exchange (ETDEWEB)

Lehman, Tom; Yang, Xi

2018-01-16

The Resource Aware Intelligent Network Services (RAINS) project conducted research and developed technologies in the area of cyberinfrastructure resource modeling and computation. The goal of this work was to provide a foundation to enable intelligent, software defined services which spanned the network AND the resources which connect to the network. A Multi-Resource Service Plane (MRSP) was defined, which allows resource owners/managers to locate and place themselves from a topology and service availability perspective within the dynamic networked cyberinfrastructure ecosystem. The MRSP enables the presentation of integrated topology views and computation results which can include resources across the spectrum of compute, storage, and networks. The RAINS project developed MSRP includes the following key components: i) Multi-Resource Service (MRS) Ontology/Multi-Resource Markup Language (MRML), ii) Resource Computation Engine (RCE), iii) Modular Driver Framework (to allow integration of a variety of external resources). The MRS/MRML is a general and extensible modeling framework that allows for resource owners to model, or describe, a wide variety of resource types. All resources are described using three categories of elements: Resources, Services, and Relationships between the elements. This modeling framework defines a common method for the transformation of cyberinfrastructure resources into data in the form of MRML models. In order to realize this infrastructure datification, the RAINS project developed a model based computation system, i.e. “RAINS Computation Engine (RCE)”. The RCE has the ability to ingest, process, integrate, and compute based on automatically generated MRML models. The RCE interacts with the resources thru system drivers which are specific to the type of external network or resource controller. The RAINS project developed a modular and pluggable driver system which facilities a variety of resource controllers to automatically generate

Classification and unification of the microscopic deterministic traffic models.

Science.gov (United States)

Yang, Bo; Monterola, Christopher

2015-10-01

We identify a universal mathematical structure in microscopic deterministic traffic models (with identical drivers), and thus we show that all such existing models in the literature, including both the two-phase and three-phase models, can be understood as special cases of a master model by expansion around a set of well-defined ground states. This allows any two traffic models to be properly compared and identified. The three-phase models are characterized by the vanishing of leading orders of expansion within a certain density range, and as an example the popular intelligent driver model is shown to be equivalent to a generalized optimal velocity (OV) model. We also explore the diverse solutions of the generalized OV model that can be important both for understanding human driving behaviors and algorithms for autonomous driverless vehicles.

The application of neural networks with artificial intelligence technique in the modeling of industrial processes

International Nuclear Information System (INIS)

Saini, K. K.; Saini, Sanju

2008-01-01

Neural networks are a relatively new artificial intelligence technique that emulates the behavior of biological neural systems in digital software or hardware. These networks can 'learn', automatically, complex relationships among data. This feature makes the technique very useful in modeling processes for which mathematical modeling is difficult or impossible. The work described here outlines some examples of the application of neural networks with artificial intelligence technique in the modeling of industrial processes.

Advances in Intelligent Modelling and Simulation Artificial Intelligence-Based Models and Techniques in Scalable Computing

CERN Document Server

Khan, Samee; Burczy´nski, Tadeusz

2012-01-01

One of the most challenging issues in today’s large-scale computational modeling and design is to effectively manage the complex distributed environments, such as computational clouds, grids, ad hoc, and P2P networks operating under  various  types of users with evolving relationships fraught with  uncertainties. In this context, the IT resources and services usually belong to different owners (institutions, enterprises, or individuals) and are managed by different administrators. Moreover, uncertainties are presented to the system at hand in various forms of information that are incomplete, imprecise, fragmentary, or overloading, which hinders in the full and precise resolve of the evaluation criteria, subsequencing and selection, and the assignment scores. Intelligent scalable systems enable the flexible routing and charging, advanced user interactions and the aggregation and sharing of geographically-distributed resources in modern large-scale systems.   This book presents new ideas, theories, models...

Gratitude mediates the effect of emotional intelligence on subjective well-being: A structural equation modeling analysis.

Science.gov (United States)

Geng, Yuan

2016-11-01

This study investigated the relationship among emotional intelligence, gratitude, and subjective well-being in a sample of university students. A total of 365 undergraduates completed the emotional intelligence scale, the gratitude questionnaire, and the subjective well-being measures. The results of the structural equation model showed that emotional intelligence is positively associated with gratitude and subjective well-being, that gratitude is positively associated with subjective well-being, and that gratitude partially mediates the positive relationship between emotional intelligence and subjective well-being. Bootstrap test results also revealed that emotional intelligence has a significant indirect effect on subjective well-being through gratitude.

A New Layered Model on Emotional Intelligence

Science.gov (United States)

Drigas, Athanasios S.

2018-01-01

Emotional Intelligence (EI) has been an important and controversial topic during the last few decades. Its significance and its correlation with many domains of life has made it the subject of expert study. EI is the rudder for feeling, thinking, learning, problem-solving, and decision-making. In this article, we present an emotional–cognitive based approach to the process of gaining emotional intelligence and thus, we suggest a nine-layer pyramid of emotional intelligence and the gradual development to reach the top of EI. PMID:29724021

A review on integration of artificial intelligence into water quality modelling.

Science.gov (United States)

Chau, Kwok-wing

2006-07-01

With the development of computing technology, numerical models are often employed to simulate flow and water quality processes in coastal environments. However, the emphasis has conventionally been placed on algorithmic procedures to solve specific problems. These numerical models, being insufficiently user-friendly, lack knowledge transfers in model interpretation. This results in significant constraints on model uses and large gaps between model developers and practitioners. It is a difficult task for novice application users to select an appropriate numerical model. It is desirable to incorporate the existing heuristic knowledge about model manipulation and to furnish intelligent manipulation of calibration parameters. The advancement in artificial intelligence (AI) during the past decade rendered it possible to integrate the technologies into numerical modelling systems in order to bridge the gaps. The objective of this paper is to review the current state-of-the-art of the integration of AI into water quality modelling. Algorithms and methods studied include knowledge-based system, genetic algorithm, artificial neural network, and fuzzy inference system. These techniques can contribute to the integrated model in different aspects and may not be mutually exclusive to one another. Some future directions for further development and their potentials are explored and presented.

Contributory fault and level of personal injury to drivers involved in head-on collisions: Application of copula-based bivariate ordinal models.

Science.gov (United States)

Wali, Behram; Khattak, Asad J; Xu, Jingjing

2018-01-01

The main objective of this study is to simultaneously investigate the degree of injury severity sustained by drivers involved in head-on collisions with respect to fault status designation. This is complicated to answer due to many issues, one of which is the potential presence of correlation between injury outcomes of drivers involved in the same head-on collision. To address this concern, we present seemingly unrelated bivariate ordered response models by analyzing the joint injury severity probability distribution of at-fault and not-at-fault drivers. Moreover, the assumption of bivariate normality of residuals and the linear form of stochastic dependence implied by such models may be unduly restrictive. To test this, Archimedean copula structures and normal mixture marginals are integrated into the joint estimation framework, which can characterize complex forms of stochastic dependencies and non-normality in residual terms. The models are estimated using 2013 Virginia police reported two-vehicle head-on collision data, where exactly one driver is at-fault. The results suggest that both at-fault and not-at-fault drivers sustained serious/fatal injuries in 8% of crashes, whereas, in 4% of the cases, the not-at-fault driver sustained a serious/fatal injury with no injury to the at-fault driver at all. Furthermore, if the at-fault driver is fatigued, apparently asleep, or has been drinking the not-at-fault driver is more likely to sustain a severe/fatal injury, controlling for other factors and potential correlations between the injury outcomes. While not-at-fault vehicle speed affects injury severity of at-fault driver, the effect is smaller than the effect of at-fault vehicle speed on at-fault injury outcome. Contrarily, and importantly, the effect of at-fault vehicle speed on injury severity of not-at-fault driver is almost equal to the effect of not-at-fault vehicle speed on injury outcome of not-at-fault driver. Compared to traditional ordered probability

Social intelligence of parents with autism spectrum disorders impacts their emotional behaviour: A new proposed model for stabilising emotionality of these parents impacting their social intelligence

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Vidya Bhagat

2017-01-01

Full Text Available Autism spectrum disorder (ASD may affect all spheres of a child's life. Indeed, parents and siblings also live with emotional instabilities in the family. The experience of parents with ASD child can be distressing since they need to make more adjustments to the demanding need to cope with their life situations. Perhaps, their life is drastically exaggerated with their complexities of life. Particularly, their social life is radically affected. The presence of pervasive and severe deficits in children with ASD isolates these parents from their social life; demanding adjustments to their social environment of parents in their life situations shove them into distress and unstable emotions. Finally, they culminate being shattered in their interpersonal relationship, their family and social life. Indeed, these aspects of distress mask social intelligence of these parents, thus narrow down their focus more on the treatment rather than holistic management of their child. Thus, the management of ASD with these parents of the deficit children to reach their fullest abilities remains doubtful. Therefore, the objectives of this study are as follows: (a to examine the impact of emotionality on social intelligence of parents blessed with autistic child, (b to develop awareness regarding social intelligence and its significance among these parents, (c to propose a new model stabilising emotionality of these parents through developing social adaption skills and (d to suggest a new model as a guide in the current intervention regimens to ensure the emotional well-being and better social adoption. This study is made based on the keenly examined past evidence with the correlation of emotionality and its impact on social intelligence of the parents with ASD children. The results reveal that the social intelligence is perceived as lowered evidenced by poor social adjustment reflected in social isolation observed in the parents of children with ASD. A new model

Intelligent speed adaptation as an assistive device for drivers with acquired brain injury: a single-case field experiment.

Science.gov (United States)

Klarborg, Brith; Lahrmann, Harry; NielsAgerholm; Tradisauskas, Nerius; Harms, Lisbeth

2012-09-01

Intelligent speed adaptation (ISA) was tested as an assistive device for drivers with an acquired brain injury (ABI). The study was part of the "Pay as You Speed" project (PAYS) and used the same equipment and technology as the main study (Lahrmann et al., in press-a, in press-b). Two drivers with ABI were recruited as subjects and had ISA equipment installed in their private vehicle. Their speed was logged with ISA equipment for a total of 30 weeks of which 12 weeks were with an active ISA user interface (6 weeks=Baseline 1; 12 weeks=ISA period; 12 weeks=Baseline 2). The subjects participated in two semi-structured interviews concerning their strategies for driving with ABI and for driving with ISA. Furthermore, they gave consent to have data from their clinical journals and be a part of the study. The two subjects did not report any instances of being distracted or confused by ISA, and in general they described driving with ISA as relaxed. ISA reduced the percentage of the total distance that was driven with a speed above the speed limit (PDA), but the subjects relapsed to their previous PDA level in Baseline 2. This suggests that ISA is more suited as a permanent assistive device (i.e. cognitive prosthesis) than as a temporary training device. As ABI is associated with a multitude of cognitive deficits, we developed a conceptual framework, which focused on the cognitive parameters that have been shown to relate to speeding behaviour, namely "intention to speed" and "inattention to speeding". The subjects' combined status on the two independent parameters made up their "speeding profile". A comparison of the speeding profiles and the speed logs indicated that ISA in the present study was more efficient in reducing inattention to speeding than affecting intention to speed. This finding suggests that ISA might be more suited for some neuropsychological profiles than for others, and that customisation of ISA for different neuropsychological profiles may be required

Intelligent control of HVAC systems. Part I: Modeling and synthesis

Directory of Open Access Journals (Sweden)

Adrian TOADER

2013-03-01

Full Text Available This is the first part of a work on intelligent type control of Heating, Ventilating and Air-Conditioning (HVAC systems. The study is performed from the perspective of giving a unitary control method to ensure high energy efficiency and air quality improving. To illustrate the proposed HVAC control technique, in this first part it is considered as benchmark problem a single thermal space HVAC system. The construction of the mathematical model is performed only with a view to obtain a framework of HVAC intelligent control validation by numerical simulations. The latter will be reported in a second part of the study.

Intelligent Models Performance Improvement Based on Wavelet Algorithm and Logarithmic Transformations in Suspended Sediment Estimation

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R. Hajiabadi

2016-10-01

Full Text Available Introduction One reason for the complexity of hydrological phenomena prediction, especially time series is existence of features such as trend, noise and high-frequency oscillations. These complex features, especially noise, can be detected or removed by preprocessing. Appropriate preprocessing causes estimation of these phenomena become easier. Preprocessing in the data driven models such as artificial neural network, gene expression programming, support vector machine, is more effective because the quality of data in these models is important. Present study, by considering diagnosing and data transformation as two different preprocessing, tries to improve the results of intelligent models. In this study two different intelligent models, Artificial Neural Network and Gene Expression Programming, are applied to estimation of daily suspended sediment load. Wavelet transforms and logarithmic transformation is used for diagnosing and data transformation, respectively. Finally, the impacts of preprocessing on the results of intelligent models are evaluated. Materials and Methods In this study, Gene Expression Programming and Artificial Neural Network are used as intelligent models for suspended sediment load estimation, then the impacts of diagnosing and logarithmic transformations approaches as data preprocessor are evaluated and compared to the result improvement. Two different logarithmic transforms are considered in this research, LN and LOG. Wavelet transformation is used to time series denoising. In order to denoising by wavelet transforms, first, time series can be decomposed at one level (Approximation part and detail part and second, high-frequency part (detail will be removed as noise. According to the ability of gene expression programming and artificial neural network to analysis nonlinear systems; daily values of suspended sediment load of the Skunk River in USA, during a 5-year period, are investigated and then estimated.4 years of

The simulation of emergent dispatch of cars for intelligent driving autos

Science.gov (United States)

Zheng, Ziao

2018-03-01

It is widely acknowledged that it is important for the development of intelligent cars to be widely accepted by the majority of car users. While most of the intelligent cars have the system of monitoring itself whether it is on the good situation to drive, it is also clear that studies should be performed on the way of cars for the emergent rescue of the intelligent vehicles. In this study, writer focus mainly on how to derive a separate system for the car caring teams to arrive as soon as they get the signal sent out by the intelligent driving autos. This simulation measure the time for the rescuing team to arrive, the cost it spent on arriving on the site of car problem happens, also how long the queue is when the rescuing auto is waiting to cross a road. This can be definitely in great use when there are a team of intelligent cars with one car immediately having problems causing it's not moving and can be helpful in other situations. Through this way, the interconnection of cars can be a safety net for the drivers encountering difficulties in any time.

Soft optics in intelligent optical networks

Science.gov (United States)

Shue, Chikong; Cao, Yang

2001-10-01

In addition to the recent advances in Hard-optics that pushes the optical transmission speed, distance, wave density and optical switching capacity, Soft-optics provides the necessary intelligence and control software that reduces operational costs, increase efficiency, and enhances revenue generating services by automating optimal optical circuit placement and restoration, and enabling value-added new services like Optical VPN. This paper describes the advances in 1) Overall Hard-optics and Soft-optics 2) Layered hierarchy of Soft-optics 3) Component of Soft-optics, including hard-optics drivers, Management Soft-optics, Routing Soft-optics and System Soft-optics 4) Key component of Routing and System Soft-optics, namely optical routing and signaling (including UNI/NNI and GMPLS signaling). In summary, the soft-optics on a new generation of OXC's enables Intelligent Optical Networks to provide just-in-time service delivery and fast restoration, and real-time capacity management that eliminates stranded bandwidth. It reduces operational costs and provides new revenue opportunities.

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

A driver-adaptive stability control strategy for sport utility vehicles

Science.gov (United States)

Zhu, Shenjin; He, Yuping

2017-08-01

Conventional vehicle stability control (VSC) systems are designed for average drivers. For a driver with a good driving skill, the VSC systems may be redundant; for a driver with a poor driving skill, the VSC intervention may be inadequate. To increase safety of sport utility vehicles (SUVs), this paper proposes a novel driver-adaptive VSC (DAVSC) strategy based on scaling the target yaw rate commanded by the driver. The DAVSC system is adaptive to drivers' driving skills. More control effort would be exerted for drivers with poor driving skills, and vice versa. A sliding mode control (SMC)-based differential braking (DB) controller is designed using a three degrees of freedom (DOF) yaw-plane model. An eight DOF nonlinear yaw-roll model is used to simulate the SUV dynamics. Two driver models, namely longitudinal and lateral, are used to 'drive' the virtual SUV. By integrating the virtual SUV, the DB controller, and the driver models, the performance of the DAVSC system is investigated. The simulations demonstrate the effectiveness of the DAVSC strategy.

Computational intelligence applications in modeling and control

CERN Document Server

Vaidyanathan, Sundarapandian

2015-01-01

The development of computational intelligence (CI) systems was inspired by observable and imitable aspects of intelligent activity of human being and nature. The essence of the systems based on computational intelligence is to process and interpret data of various nature so that that CI is strictly connected with the increase of available data as well as capabilities of their processing, mutually supportive factors. Developed theories of computational intelligence were quickly applied in many fields of engineering, data analysis, forecasting, biomedicine and others. They are used in images and sounds processing and identifying, signals processing, multidimensional data visualization, steering of objects, analysis of lexicographic data, requesting systems in banking, diagnostic systems, expert systems and many other practical implementations. This book consists of 16 contributed chapters by subject experts who are specialized in the various topics addressed in this book. The special chapters have been brought ...

Modeling the safety impacts of driving hours and rest breaks on truck drivers considering time-dependent covariates.

Science.gov (United States)

Chen, Chen; Xie, Yuanchang

2014-12-01

Driving hours and rest breaks are closely related to driver fatigue, which is a major contributor to truck crashes. This study investigates the effects of driving hours and rest breaks on commercial truck driver safety. A discrete-time logistic regression model is used to evaluate the crash odds ratios of driving hours and rest breaks. Driving time is divided into 11 one hour intervals. These intervals and rest breaks are modeled as dummy variables. In addition, a Cox proportional hazards regression model with time-dependent covariates is used to assess the transient effects of rest breaks, which consists of a fixed effect and a variable effect. Data collected from two national truckload carriers in 2009 and 2010 are used. The discrete-time logistic regression result indicates that only the crash odds ratio of the 11th driving hour is statistically significant. Taking one, two, and three rest breaks can reduce drivers' crash odds by 68%, 83%, and 85%, respectively, compared to drivers who did not take any rest breaks. The Cox regression result shows clear transient effects for rest breaks. It also suggests that drivers may need some time to adjust themselves to normal driving tasks after a rest break. Overall, the third rest break's safety benefit is very limited based on the results of both models. The findings of this research can help policy makers better understand the impact of driving time and rest breaks and develop more effective rules to improve commercial truck safety. Copyright © 2014 National Safety Council and Elsevier Ltd. All rights reserved.

Inovační trendy Business Intelligence a Big Data v modelu Design driven Innovation

OpenAIRE

Krčma, Marek

2014-01-01

Business Intelligence plays the crucial role in the question of serching for the truth in organizations. Trend of data growing defines the importance of analytical tools for organizations. Innovation is perceived as the only driver which leads to higher living standards in a society in the longterm run (according to the World Economic Forum). This thesis joins two areas: innovation and analytical field of business informatics (Business Intelligence, Big Data). The main goal of this thesis is ...

A Sensor-Based Visual Effect Evaluation of Chevron Alignment Signs’ Colors on Drivers through the Curves in Snow and Ice Environment

Directory of Open Access Journals (Sweden)

Wei Zhao

2017-01-01

Full Text Available The ability to quantitatively evaluate the visual feedback of drivers has been considered as the primary research for reducing crashes in snow and ice environments. Different colored Chevron alignment signs cause diverse visual effect. However, the effect of Chevrons on visual feedback and on the driving reaction while navigating curves in SI environments has not been adequately evaluated. The objective of this study is twofold: (1 an effective and long-term experiment was designed and developed to test the effect of colored Chevrons on drivers’ vision and vehicle speed; (2 a new quantitative effect evaluation model is employed to measure the effect of different colors of the Chevrons. Fixation duration and pupil size were used to describe the driver’s visual response, and Cohen’s d was used to evaluate the colors’ psychological effect on drivers. The results showed the following: (1 after choosing the proper color for Chevrons, drivers reduced the speed of the vehicle while approaching the curves. (2 It was easier for drivers to identify the road alignment after setting the Chevrons. (3 Cohen’s d related to different colors of Chevrons have different effect sizes. The conclusions provide evident references for freeway warning products and the design of intelligent vehicles.

Estimating likelihood of future crashes for crash-prone drivers

Directory of Open Access Journals (Sweden)

Subasish Das

2015-06-01

Full Text Available At-fault crash-prone drivers are usually considered as the high risk group for possible future incidents or crashes. In Louisiana, 34% of crashes are repeatedly committed by the at-fault crash-prone drivers who represent only 5% of the total licensed drivers in the state. This research has conducted an exploratory data analysis based on the driver faultiness and proneness. The objective of this study is to develop a crash prediction model to estimate the likelihood of future crashes for the at-fault drivers. The logistic regression method is used by employing eight years' traffic crash data (2004–2011 in Louisiana. Crash predictors such as the driver's crash involvement, crash and road characteristics, human factors, collision type, and environmental factors are considered in the model. The at-fault and not-at-fault status of the crashes are used as the response variable. The developed model has identified a few important variables, and is used to correctly classify at-fault crashes up to 62.40% with a specificity of 77.25%. This model can identify as many as 62.40% of the crash incidence of at-fault drivers in the upcoming year. Traffic agencies can use the model for monitoring the performance of an at-fault crash-prone drivers and making roadway improvements meant to reduce crash proneness. From the findings, it is recommended that crash-prone drivers should be targeted for special safety programs regularly through education and regulations.

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

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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.

Neuro-Based Artificial Intelligence Model for Loan Decisions

OpenAIRE

Shorouq F. Eletter; Saad G. Yaseen; Ghaleb A. Elrefae

2010-01-01

Problem statement: Despite the increase in consumer loans defaults and competition in the banking market, most of the Jordanian commercial banks are reluctant to use artificial intelligence software systems for supporting loan decisions. Approach: This study developed a proposed model that identifies artificial neural network as an enabling tool for evaluating credit applications to support loan decisions in the Jordanian Commercial banks. A multi-layer feed-forward neural network with backpr...

Job stress, fatigue, and job dissatisfaction in Dutch lorry drivers: towards an occupation specific model of job demands and control

NARCIS (Netherlands)

Croon, E.M. de; Blonk, R.W.B.; Zwart, B.C.H. de; Frings-Dresen, M.H.W.; Broersen, J.P.J.

2002-01-01

Building on Karasek's model of job demands and control (JD-C model), this study examined the effects of job control, quantitative workload, and two occupation specific job demands on fatigue and job dissatisfaction in Dutch lorry drivers. From 1181 lorry drivers self reported information was

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.

Comparison of Microscopic Drivers' Probabilistic Lane-changing Models With Real Traffic Microscopic Data

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Seyyed Mohammad Sadat Hoseini

2011-07-01

Full Text Available The difficulties of microscopic-level simulation models to accurately reproduce real traffic phenomena stem not only from the complexity of calibration and validation operations, but also from the structural inadequacies of the sub-models themselves. Both of these drawbacks originate from the scant information available on real phenomena because of the difficulty in gathering accurate field data. This paper studies the traffic behaviour of individual drivers utilizing vehicle trajectory data extracted from digital images collected from freeways in Iran. These data are used to evaluate the four proposed microscopic traffic models. One of the models is based on the traffic regulations in Iran and the three others are probabilistic models that use a decision factor for calculating the probability of choosing a position on the freeway by a driver. The decision factors for three probabilistic models are increasing speed, decreasing risk of collision, and increasing speed combined with decreasing risk of collision. The models are simulated by a cellular automata simulator and compared with the real data. It is shown that the model based on driving regulations is not valid, but that other models appear useful for predicting the driver’s behaviour on freeway segments in Iran during noncongested conditions.

Application of Contemporary Intelligence Models in Terms of Transformation and Security Sector Reform

OpenAIRE

Dojcinovski, Metodija; Ackoski, Jugoslav

2011-01-01

This paper presents a new approach to the contemporary methods of organizing, establishing and functioning of intelligence systems in a way of offering solutions against security threats and challenges of the 21st century. The effectiveness of implementing the measures and activities depends on the intelligence models, identified as functioning in relation to the structured elements of the represented and realistically created segments, standard operative procedures, security procedures and m...

An Intelligent Model for Stock Market Prediction

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IbrahimM. Hamed

2012-08-01

Full Text Available This paper presents an intelligent model for stock market signal prediction using Multi-Layer Perceptron (MLP Artificial Neural Networks (ANN. Blind source separation technique, from signal processing, is integrated with the learning phase of the constructed baseline MLP ANN to overcome the problems of prediction accuracy and lack of generalization. Kullback Leibler Divergence (KLD is used, as a learning algorithm, because it converges fast and provides generalization in the learning mechanism. Both accuracy and efficiency of the proposed model were confirmed through the Microsoft stock, from wall-street market, and various data sets, from different sectors of the Egyptian stock market. In addition, sensitivity analysis was conducted on the various parameters of the model to ensure the coverage of the generalization issue. Finally, statistical significance was examined using ANOVA test.

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)

The psychology of intelligence analysis: drivers of prediction accuracy in world politics.

Science.gov (United States)

Mellers, Barbara; Stone, Eric; Atanasov, Pavel; Rohrbaugh, Nick; Metz, S Emlen; Ungar, Lyle; Bishop, Michael M; Horowitz, Michael; Merkle, Ed; Tetlock, Philip

2015-03-01

This article extends psychological methods and concepts into a domain that is as profoundly consequential as it is poorly understood: intelligence analysis. We report findings from a geopolitical forecasting tournament that assessed the accuracy of more than 150,000 forecasts of 743 participants on 199 events occurring over 2 years. Participants were above average in intelligence and political knowledge relative to the general population. Individual differences in performance emerged, and forecasting skills were surprisingly consistent over time. Key predictors were (a) dispositional variables of cognitive ability, political knowledge, and open-mindedness; (b) situational variables of training in probabilistic reasoning and participation in collaborative teams that shared information and discussed rationales (Mellers, Ungar, et al., 2014); and (c) behavioral variables of deliberation time and frequency of belief updating. We developed a profile of the best forecasters; they were better at inductive reasoning, pattern detection, cognitive flexibility, and open-mindedness. They had greater understanding of geopolitics, training in probabilistic reasoning, and opportunities to succeed in cognitively enriched team environments. Last but not least, they viewed forecasting as a skill that required deliberate practice, sustained effort, and constant monitoring of current affairs. PsycINFO Database Record (c) 2015 APA, all rights reserved.

Understanding & modeling bus transit driver availability.

Science.gov (United States)

2014-07-01

Bus transit agencies are required to hire extraboard (i.e. back-up) operators to account for unexpected absences. Incorrect sizing of extra driver workforce is problematic for a number of reasons. Overestimating the appropriate number of extraboard o...

The implementation of multiple intelligences based teaching model to improve mathematical problem solving ability for student of junior high school

Science.gov (United States)

Fasni, Nurli; Fatimah, Siti; Yulanda, Syerli

2017-05-01

This research aims to achieve some purposes such as: to know whether mathematical problem solving ability of students who have learned mathematics using Multiple Intelligences based teaching model is higher than the student who have learned mathematics using cooperative learning; to know the improvement of the mathematical problem solving ability of the student who have learned mathematics using Multiple Intelligences based teaching model., to know the improvement of the mathematical problem solving ability of the student who have learned mathematics using cooperative learning; to know the attitude of the students to Multiple Intelligences based teaching model. The method employed here is quasi-experiment which is controlled by pre-test and post-test. The population of this research is all of VII grade in SMP Negeri 14 Bandung even-term 2013/2014, later on two classes of it were taken for the samples of this research. A class was taught using Multiple Intelligences based teaching model and the other one was taught using cooperative learning. The data of this research were gotten from the test in mathematical problem solving, scale questionnaire of the student attitudes, and observation. The results show the mathematical problem solving of the students who have learned mathematics using Multiple Intelligences based teaching model learning is higher than the student who have learned mathematics using cooperative learning, the mathematical problem solving ability of the student who have learned mathematics using cooperative learning and Multiple Intelligences based teaching model are in intermediate level, and the students showed the positive attitude in learning mathematics using Multiple Intelligences based teaching model. As for the recommendation for next author, Multiple Intelligences based teaching model can be tested on other subject and other ability.

Modeling the Structure and Effectiveness of Intelligence Organizations: Dynamic Information Flow Simulation

National Research Council Canada - National Science Library

Behrman, Robert; Carley, Kathleen

2003-01-01

This paper describes the Dynamic Information Flow Simulation (DIFS), an abstract model for analyzing the structure and function of intelligence support organizations and the activities of entities within...

THE FUZZY OVERLAY STUDENT MODEL IN AN INTELLIGENT TUTORING SYSTEM

Directory of Open Access Journals (Sweden)

D. I. Popov

2015-01-01

Full Text Available The article is devoted to the development of the student model for use in an intelligent tutoring system (ITS designed for the evaluation of students’ competencies in different Higher Education Facilities. There are classification and examples of the various student models, the most suitable for the evaluation of competencies is selected and finalized. The dynamic overlay fuzzy student model builded on the domain model based on the concept of didactic units is described in this work. The formulas, chart and diagrams are provided.

Artificial intelligence in process control: Knowledge base for the shuttle ECS model

Science.gov (United States)

Stiffler, A. Kent

1989-01-01

The general operation of KATE, an artificial intelligence controller, is outlined. A shuttle environmental control system (ECS) demonstration system for KATE is explained. The knowledge base model for this system is derived. An experimental test procedure is given to verify parameters in the model.

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...

Optimal model of economic diplomacy of Republic of Croatia in the contexst of global intelligence revolution

Directory of Open Access Journals (Sweden)

Zdravko Bazdan

2010-12-01

Full Text Available The aim of this study is to point to the fact that economic diplomacy is a relatively new practice in international economics, specifically the expansion of the occurrence of Intelligence Revolution. The history in global relations shows that without economic diplomacy there is no optimal economic growth and social development. It is important to note that economic diplomacy should be important for our country and the political elite, as well as for the administration of Croatian economic subjects that want to compete in international market economy. Comparative analysis are particularly highlighted by French experience. Therefore, Croatia should copy the practice of those countries that are successful in economic diplomacy. And in the curricula - especially of our economic faculties - we should introduce the course of Economic Diplomacy. It is important to note, that in order to form our optimal model of economic diplomacy which would be headed by the President of Republic of Croatia formula should be based on: Intelligence Security Agency (SOA, Intelligence Service of the Ministry of Foreign Affairs and European Integration, Intelligence Service of the Croatian Chamber of Commerce and the Intelligence Service of the Ministry of Economy, Labor and Entrepreneurship. Described model would consist of intelligence subsystem with at least twelve components.

Artificial Intelligence and Moral intelligence

Directory of Open Access Journals (Sweden)

Laura Pana

2008-07-01

means for supplementing the objective decision with a subjective one. Machine ethics can/will be of the highest quality because it will be derived from the sciences, modelled by techniques and accomplished by technologies. If our theoretical hypothesis about a specific moral intelligence, necessary for the implementation of an artificial moral conduct, is correct, then some theoretical and technical issues appear, but the following working hypotheses are possible: structural, functional and behavioural. The future of human and/or artificial morality is to be anticipated.

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

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...

Model and Design of a Power Driver for Piezoelectric Stack Actuators

Directory of Open Access Journals (Sweden)

Chiaberge M

2010-01-01

Full Text Available A power driver has been developed to control piezoelectric stack actuators used in automotive application. An FEM model of the actuator has been implemented starting from experimental characterization of the stack and mechanical and piezoelectric parameters. Experimental results are reported to show a correct piezoelectric actuator driving method and the possibility to obtain a sensorless positioning control.

TARDEC FIXED HEEL POINT (FHP): DRIVER CAD ACCOMMODATION MODEL VERIFICATION REPORT

Science.gov (United States)

2017-11-09

Public Release Disclaimer: Reference herein to any specific commercial company, product , process, or service by trade name, trademark, manufacturer , or...not actively engaged HSI until MSB or the Engineering Manufacturing and Development (EMD) Phase, resulting in significant design and cost changes...and shall not be used for advertising or product endorsement purposes. TARDEC Fixed Heel Point (FHP): Driver CAD Accommodation Model Verification

Intelligent energy management control of vehicle air conditioning system coupled with engine

International Nuclear Information System (INIS)

Khayyam, Hamid; Abawajy, Jemal; Jazar, Reza N.

2012-01-01

Vehicle Air Conditioning (AC) systems consist of an engine powered compressor activated by an electrical clutch. The AC system imposes an extra load to the vehicle's engine increasing the vehicle fuel consumption and emissions. Energy management control of the vehicle air conditioning is a nonlinear dynamic system, influenced by uncertain disturbances. In addition, the vehicle energy management control system interacts with different complex systems, such as engine, air conditioning system, environment, and driver, to deliver fuel consumption improvements. In this paper, we describe the energy management control of vehicle AC system coupled with vehicle engine through an intelligent control design. The Intelligent Energy Management Control (IEMC) system presented in this paper includes an intelligent algorithm which uses five exterior units and three integrated fuzzy controllers to produce desirable internal temperature and air quality, improved fuel consumption, low emission, and smooth driving. The three fuzzy controllers include: (i) a fuzzy cruise controller to adapt vehicle cruise speed via prediction of the road ahead using a Look-Ahead system, (ii) a fuzzy air conditioning controller to produce desirable temperature and air quality inside vehicle cabin room via a road information system, and (iii) a fuzzy engine controller to generate the required engine torque to move the vehicle smoothly on the road. We optimised the integrated operation of the air conditioning and the engine under various driving patterns and performed three simulations. Results show that the proposed IEMC system developed based on Fuzzy Air Conditioning Controller with Look-Ahead (FAC-LA) method is a more efficient controller for vehicle air conditioning system than the previously developed Coordinated Energy Management Systems (CEMS). - Highlights: ► AC interacts: vehicle, environment, driver components, and the interrelationships between them. ► Intelligent AC algorithm which uses

Experimental Exploration of RSSI Model for the Vehicle Intelligent Position System

Directory of Open Access Journals (Sweden)

Zhichao Cao

2015-01-01

Full Text Available Vehicle intelligent position systems based on Received Signal Strength Indicator (RSSI in Wireless Sensor Networks (WSNs are efficiently utilized. The vehicle’s position accuracy is of great importance for transportation behaviors, such as dynamic vehicle routing problems and multiple pedestrian routing choice behaviors and so on. Therefore, a precise position and available optimization is necessary for total parameters of conventional RSSI model. In this papar, we investigate the experimental performance of translating the power measurements to corresponding distance between each pair of nodes. The priori knowledge about the environment interference could impact the accuracy of vehicles’s position and the reliability of paremeters greatly. Based on the real-world outdoor experiments, we compares different regression analysis of the RSSI model, in order to establish a calibration scheme on RSSI model. We showed that the average error of RSSI model is able to decrease throughout the rules of environmental factor n and shadowing factor ? respectively. Moreover, the calculation complexity is reduced. Since variation tendency of environmental factor n, shadowing factor ? with distance and signal strength could be simulated respectively, RSSI model fulfills the precision of the vehicle intelligent position system.

The Research of the Driver Attention Field Modeling

Directory of Open Access Journals (Sweden)

Pengfei Tao

2014-01-01

Full Text Available For expanding the application scope of car-following, based on the basic idea of the noncontact interaction of the objects in physics, establish an attention field model to describe the driving behavior. Firstly, propose the time distance concept to describe the degree of driver perception to the front one-dimensional space and extend its application range to the two-dimensional space. Secondly, connect the point which has the same time distance to constitute the equipotential line of drivers’ attention field equipotent, and establish a model to describe it. Thirdly, define the effective range of the driver’s psychological field with the feature of the driver’s visual distance range increasing and the angle decreasing. Finally, design the calculation method to collect projection of the object in the psychological field scope and calculate the curve points to determine the object’s intensity of psychological field. Preliminarily build the driving behavior model and use the numerical simulation method to simulate the simple transport scenarios; initially verify the validity of the model.

A Vehicle Active Safety Model: Vehicle Speed Control Based on Driver Vigilance Detection Using Wearable EEG and Sparse Representation.

Science.gov (United States)

Zhang, Zutao; Luo, Dianyuan; Rasim, Yagubov; Li, Yanjun; Meng, Guanjun; Xu, Jian; Wang, Chunbai

2016-02-19

In this paper, we present a vehicle active safety model for vehicle speed control based on driver vigilance detection using low-cost, comfortable, wearable electroencephalographic (EEG) sensors and sparse representation. The proposed system consists of three main steps, namely wireless wearable EEG collection, driver vigilance detection, and vehicle speed control strategy. First of all, a homemade low-cost comfortable wearable brain-computer interface (BCI) system with eight channels is designed for collecting the driver's EEG signal. Second, wavelet de-noising and down-sample algorithms are utilized to enhance the quality of EEG data, and Fast Fourier Transformation (FFT) is adopted to extract the EEG power spectrum density (PSD). In this step, sparse representation classification combined with k-singular value decomposition (KSVD) is firstly introduced in PSD to estimate the driver's vigilance level. Finally, a novel safety strategy of vehicle speed control, which controls the electronic throttle opening and automatic braking after driver fatigue detection using the above method, is presented to avoid serious collisions and traffic accidents. The simulation and practical testing results demonstrate the feasibility of the vehicle active safety model.

A generic model for camera based intelligent road crowd control ...

African Journals Online (AJOL)

This research proposes a model for intelligent traffic flow control by implementing camera based surveillance and feedback system. A series of cameras are set minimum three signals ahead from the target junction. The complete software system is developed to help integrating the multiple camera on road as feedback to ...

Estimation of occupational and nonoccupational nitrogen dioxide exposure for Korean taxi drivers using a microenvironmental model

International Nuclear Information System (INIS)

Son, Busoon; Yang, Wonho; Breysse, Patrick; Chung, Taewoong; Lee, Youngshin

2004-01-01

Occupational and nonoccupational personal nitrogen dioxide (NO 2 ) exposures were measured using passive samplers for 31 taxi drivers in Asan and Chunan, Korea. Exposures were also estimated using a microenvironmental time-weighted average model based on indoor, outdoor and inside the taxi area measurements. Mean NO 2 indoor and outdoor concentrations inside and outside the taxi drivers' houses were 24.7±10.7 and 23.3±8.3 ppb, respectively, with a mean indoor to outdoor NO 2 ratio of 1.1. Mean personal NO 2 exposure of taxi drivers was 30.3±9.7 ppb. Personal NO 2 exposures for drivers were more strongly correlated with interior vehicle NO 2 levels (r=0.89) rather than indoor residential NO 2 levels (r=0.74) or outdoor NO 2 levels (r=0.71). The main source of NO 2 exposure for taxi drivers was considered to be occupational driving. Interestingly, the NO 2 exposures for drivers' using LPG-fueled vehicles (26.3±1.3 ppb) were significantly lower than those (38.1±1.3 ppb) using diesel-fueled vehicle (P 2 exposure with indoor and outdoor NO 2 levels of the residence, and interior vehicle NO 2 levels (P 2 levels because they drive diesel-using vehicles outdoors in Korea

Research on application of intelligent computation based LUCC model in urbanization process

Science.gov (United States)

Chen, Zemin

2007-06-01

Global change study is an interdisciplinary and comprehensive research activity with international cooperation, arising in 1980s, with the largest scopes. The interaction between land use and cover change, as a research field with the crossing of natural science and social science, has become one of core subjects of global change study as well as the front edge and hot point of it. It is necessary to develop research on land use and cover change in urbanization process and build an analog model of urbanization to carry out description, simulation and analysis on dynamic behaviors in urban development change as well as to understand basic characteristics and rules of urbanization process. This has positive practical and theoretical significance for formulating urban and regional sustainable development strategy. The effect of urbanization on land use and cover change is mainly embodied in the change of quantity structure and space structure of urban space, and LUCC model in urbanization process has been an important research subject of urban geography and urban planning. In this paper, based upon previous research achievements, the writer systematically analyzes the research on land use/cover change in urbanization process with the theories of complexity science research and intelligent computation; builds a model for simulating and forecasting dynamic evolution of urban land use and cover change, on the basis of cellular automation model of complexity science research method and multi-agent theory; expands Markov model, traditional CA model and Agent model, introduces complexity science research theory and intelligent computation theory into LUCC research model to build intelligent computation-based LUCC model for analog research on land use and cover change in urbanization research, and performs case research. The concrete contents are as follows: 1. Complexity of LUCC research in urbanization process. Analyze urbanization process in combination with the contents

System dynamics modeling of the impact of Internet-of-Things on intelligent urban transportation

OpenAIRE

Marshall, Phil

2015-01-01

Urban transportation systems are at the cusp of a major transformation that capitalizes on the proliferation of the Internet-of-Things (IoT), autonomous and cooperative vehicular and intelligent roadway technologies, advanced traffic management systems, and big data analytics. The benefits of these smart-transportation technologies were investigated using System Dynamics modeling, with particular emphasis towards vehicle sharing, intelligent highway systems, and smart-parking solutions. The m...

THE EFFECTS OF LEARNING MODELS AND LINGUISTIC INTELLIGENCE ON THE PERSUASIVE WRITING SKILL

OpenAIRE

Yusri, Yusri; Emzir, Emzir

2017-01-01

The objective of this study is to know the effects of learning models (problem solving and project based learning) and linguistic intelligence  on the students of persuasive writing skill of the fourth semester students  of English Department, State Polytechnic of Sriwijaya Palembang, in the academic year of 2016-2017. The writer used linguistic intelligence test and persuasive writing test to collect the data. The data was analyzed  statistically by using two-factor ANOVA a...

Development of intelligent model for personalized guidance on wheelchair tilt and recline usage for people with spinal cord injury: methodology and preliminary report.

Science.gov (United States)

Fu, Jicheng; Jones, Maria; Jan, Yih-Kuen

2014-01-01

Wheelchair tilt and recline functions are two of the most desirable features for relieving seating pressure to decrease the risk of pressure ulcers. The effective guidance on wheelchair tilt and recline usage is therefore critical to pressure ulcer prevention. The aim of this study was to demonstrate the feasibility of using machine learning techniques to construct an intelligent model to provide personalized guidance to individuals with spinal cord injury (SCI). The motivation stems from the clinical evidence that the requirements of individuals vary greatly and that no universal guidance on tilt and recline usage could possibly satisfy all individuals with SCI. We explored all aspects involved in constructing the intelligent model and proposed approaches tailored to suit the characteristics of this preliminary study, such as the way of modeling research participants, using machine learning techniques to construct the intelligent model, and evaluating the performance of the intelligent model. We further improved the intelligent model's prediction accuracy by developing a two-phase feature selection algorithm to identify important attributes. Experimental results demonstrated that our approaches held the promise: they could effectively construct the intelligent model, evaluate its performance, and refine the participant model so that the intelligent model's prediction accuracy was significantly improved.

Intelligent Automatic Right-Left Sign Lamp Based on Brain Signal Recognition System

Science.gov (United States)

Winda, A.; Sofyan; Sthevany; Vincent, R. S.

2017-12-01

Comfort as a part of the human factor, plays important roles in nowadays advanced automotive technology. Many of the current technologies go in the direction of automotive driver assistance features. However, many of the driver assistance features still require physical movement by human to enable the features. In this work, the proposed method is used in order to make certain feature to be functioning without any physical movement, instead human just need to think about it in their mind. In this work, brain signal is recorded and processed in order to be used as input to the recognition system. Right-Left sign lamp based on the brain signal recognition system can potentially replace the button or switch of the specific device in order to make the lamp work. The system then will decide whether the signal is ‘Right’ or ‘Left’. The decision of the Right-Left side of brain signal recognition will be sent to a processing board in order to activate the automotive relay, which will be used to activate the sign lamp. Furthermore, the intelligent system approach is used to develop authorized model based on the brain signal. Particularly Support Vector Machines (SVMs)-based classification system is used in the proposed system to recognize the Left-Right of the brain signal. Experimental results confirm the effectiveness of the proposed intelligent Automatic brain signal-based Right-Left sign lamp access control system. The signal is processed by Linear Prediction Coefficient (LPC) and Support Vector Machines (SVMs), and the resulting experiment shows the training and testing accuracy of 100% and 80%, respectively.

Switched Cooperative Driving Model towards Human Vehicle Copiloting Situation: A Cyberphysical Perspective

Directory of Open Access Journals (Sweden)

Yang Li

2018-01-01

Full Text Available Development of highly automated and intelligent vehicles can lead to the reduction of driver workload. However, it also causes the out-of-the-loop problem to drivers, which leaves drivers handicapped in their ability to take over manual operations in emergency situations. This contribution puts forth a new switched driving strategy to avoid some of the negative consequences associated with out-of-the-loop performance by having drivers assume manual control at periodic intervals. To minimize the impact of the transitions between automated and manual driving on traffic operations, a switched cooperative driving model towards human vehicle copiloting situation is proposed by considering the vehicle dynamics and the realistic intervehicle communication in a cyberphysical view. The design method of the switching signal for the switched cooperative driving model is given based on the Lyapunov stability theory with the comprehensive consideration of platoon stability and human factors. The good agreement between simulation results and theoretical analysis illustrates the effectiveness of the proposed methods.

An application of the driver behavior questionnaire to Chinese carless young drivers.

Science.gov (United States)

Zhang, Qian; Jiang, Zuhua; Zheng, Dongpeng; Wang, Yifan; Man, Dong

2013-01-01

Carless young drivers refers to those drivers aged between 18 and 25 years who have a driver's license but seldom have opportunities to practice their driving skills because they do not have their own cars. Due to China's lower private car ownership, many young drivers turn into carless young drivers after licensure, and the safety issue associated with them has become a matter of great concern in China. Because few studies have examined the driving behaviors of these drivers, this study aims to utilize the Driver Behavior Questionnaire (DBQ) to investigate the self-reported driving behaviors of Chinese carless young drivers. A total of 523 Chinese carless young drivers (214 females, 309 males) with an average age of 21.91 years completed a questionnaire including the 27-item DBQ and demographics. The data were first randomized into 2 subsamples for factor analysis and then combined together for the following analyses. Both an exploratory factor analysis (EFA, n = 174) and a confirmatory factor analysis (CFA, n = 349) were performed to investigate the factor structure of the DBQ. Correlation analysis was conducted to examine the relationships between the demographics and the DBQ scales' variables. Multivariate linear regression and logistic regression were performed to investigate the prediction of the DBQ scales and crash involvement in the previous year. The EFA produced a 4-factor structure identified as errors, violations, attention lapses, and memory lapses, and the CFA revealed a good model fit after the removal of one item with a low factor loading and the permission of the error covariance between some items. The Chinese carless young drivers reported a comparatively low level of aberrant driving behaviors. The 3 most frequently reported behaviors were all lapses and the 3 least were all violations. Gender was the only significant predictor of the 2 lapses scales and lifetime mileage was the only significant predictor of the violations scale. Only the

Intelligent diagnosis of jaundice with dynamic uncertain causality graph model*

Science.gov (United States)

Hao, Shao-rui; Geng, Shi-chao; Fan, Lin-xiao; Chen, Jia-jia; Zhang, Qin; Li, Lan-juan

2017-01-01

Jaundice is a common and complex clinical symptom potentially occurring in hepatology, general surgery, pediatrics, infectious diseases, gynecology, and obstetrics, and it is fairly difficult to distinguish the cause of jaundice in clinical practice, especially for general practitioners in less developed regions. With collaboration between physicians and artificial intelligence engineers, a comprehensive knowledge base relevant to jaundice was created based on demographic information, symptoms, physical signs, laboratory tests, imaging diagnosis, medical histories, and risk factors. Then a diagnostic modeling and reasoning system using the dynamic uncertain causality graph was proposed. A modularized modeling scheme was presented to reduce the complexity of model construction, providing multiple perspectives and arbitrary granularity for disease causality representations. A “chaining” inference algorithm and weighted logic operation mechanism were employed to guarantee the exactness and efficiency of diagnostic reasoning under situations of incomplete and uncertain information. Moreover, the causal interactions among diseases and symptoms intuitively demonstrated the reasoning process in a graphical manner. Verification was performed using 203 randomly pooled clinical cases, and the accuracy was 99.01% and 84.73%, respectively, with or without laboratory tests in the model. The solutions were more explicable and convincing than common methods such as Bayesian Networks, further increasing the objectivity of clinical decision-making. The promising results indicated that our model could be potentially used in intelligent diagnosis and help decrease public health expenditure. PMID:28471111

Intelligent diagnosis of jaundice with dynamic uncertain causality graph model.

Science.gov (United States)

Hao, Shao-Rui; Geng, Shi-Chao; Fan, Lin-Xiao; Chen, Jia-Jia; Zhang, Qin; Li, Lan-Juan

2017-05-01

Jaundice is a common and complex clinical symptom potentially occurring in hepatology, general surgery, pediatrics, infectious diseases, gynecology, and obstetrics, and it is fairly difficult to distinguish the cause of jaundice in clinical practice, especially for general practitioners in less developed regions. With collaboration between physicians and artificial intelligence engineers, a comprehensive knowledge base relevant to jaundice was created based on demographic information, symptoms, physical signs, laboratory tests, imaging diagnosis, medical histories, and risk factors. Then a diagnostic modeling and reasoning system using the dynamic uncertain causality graph was proposed. A modularized modeling scheme was presented to reduce the complexity of model construction, providing multiple perspectives and arbitrary granularity for disease causality representations. A "chaining" inference algorithm and weighted logic operation mechanism were employed to guarantee the exactness and efficiency of diagnostic reasoning under situations of incomplete and uncertain information. Moreover, the causal interactions among diseases and symptoms intuitively demonstrated the reasoning process in a graphical manner. Verification was performed using 203 randomly pooled clinical cases, and the accuracy was 99.01% and 84.73%, respectively, with or without laboratory tests in the model. The solutions were more explicable and convincing than common methods such as Bayesian Networks, further increasing the objectivity of clinical decision-making. The promising results indicated that our model could be potentially used in intelligent diagnosis and help decrease public health expenditure.

Multidimensional Learner Model In Intelligent Learning System

Science.gov (United States)

Deliyska, B.; Rozeva, A.

2009-11-01

The learner model in an intelligent learning system (ILS) has to ensure the personalization (individualization) and the adaptability of e-learning in an online learner-centered environment. ILS is a distributed e-learning system whose modules can be independent and located in different nodes (servers) on the Web. This kind of e-learning is achieved through the resources of the Semantic Web and is designed and developed around a course, group of courses or specialty. An essential part of ILS is learner model database which contains structured data about learner profile and temporal status in the learning process of one or more courses. In the paper a learner model position in ILS is considered and a relational database is designed from learner's domain ontology. Multidimensional modeling agent for the source database is designed and resultant learner data cube is presented. Agent's modules are proposed with corresponding algorithms and procedures. Multidimensional (OLAP) analysis guidelines on the resultant learner module for designing dynamic learning strategy have been highlighted.

Finite-element-model updating using computational intelligence techniques applications to structural dynamics

CERN Document Server

Marwala, Tshilidzi

2010-01-01

Finite element models (FEMs) are widely used to understand the dynamic behaviour of various systems. FEM updating allows FEMs to be tuned better to reflect measured data and may be conducted using two different statistical frameworks: the maximum likelihood approach and Bayesian approaches. Finite Element Model Updating Using Computational Intelligence Techniques applies both strategies to the field of structural mechanics, an area vital for aerospace, civil and mechanical engineering. Vibration data is used for the updating process. Following an introduction a number of computational intelligence techniques to facilitate the updating process are proposed; they include: • multi-layer perceptron neural networks for real-time FEM updating; • particle swarm and genetic-algorithm-based optimization methods to accommodate the demands of global versus local optimization models; • simulated annealing to put the methodologies into a sound statistical basis; and • response surface methods and expectation m...

Novice drivers' individual trajectories of driver behavior over the first three years of driving.

Science.gov (United States)

Roman, Gabriela D; Poulter, Damian; Barker, Edward; McKenna, Frank P; Rowe, Richard

2015-09-01

Identifying the changes in driving behavior that underlie the decrease in crash risk over the first few months of driving is key to efforts to reduce injury and fatality risk in novice drivers. This study represented a secondary data analysis of 1148 drivers who participated in the UK Cohort II study. The Driver Behavior Questionnaire was completed at 6 months and 1, 2 and 3 years after licensure. Linear latent growth models indicated significant increases across development in all four dimensions of aberrant driving behavior under scrutiny: aggressive violations, ordinary violations, errors and slips. Unconditional and conditional latent growth class analyses showed that the observed heterogeneity in individual trajectories was explained by the presence of multiple homogeneous groups of drivers, each exhibiting specific trajectories of aberrant driver behavior. Initial levels of aberrant driver behavior were important in identifying sub-groups of drivers. All classes showed positive slopes; there was no evidence of a group of drivers whose aberrant behavior decreased over time that might explain the decrease in crash involvement observed over this period. Male gender and younger age predicted membership of trajectories with higher levels of aberrant behavior. These findings highlight the importance of early intervention for improving road safety. We discuss the implications of our findings for understanding the behavioral underpinnings of the decrease in crash involvement observed in the early months of driving. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Associating crash avoidance maneuvers with driver attributes and accident characteristics: a mixed logit model approach.

Science.gov (United States)

Kaplan, Sigal; Prato, Carlo Giacomo

2012-01-01

The current study focuses on the propensity of drivers to engage in crash avoidance maneuvers in relation to driver attributes, critical events, crash characteristics, vehicles involved, road characteristics, and environmental conditions. The importance of avoidance maneuvers derives from the key role of proactive and state-aware road users within the concept of sustainable safety systems, as well as from the key role of effective corrective maneuvers in the success of automated in-vehicle warning and driver assistance systems. The analysis is conducted by means of a mixed logit model that represents the selection among 5 emergency lateral and speed control maneuvers (i.e., "no avoidance maneuvers," "braking," "steering," "braking and steering," and "other maneuvers) while accommodating correlations across maneuvers and heteroscedasticity. Data for the analysis were retrieved from the General Estimates System (GES) crash database for the year 2009 by considering drivers for which crash avoidance maneuvers are known. The results show that (1) the nature of the critical event that made the crash imminent greatly influences the choice of crash avoidance maneuvers, (2) women and elderly have a relatively lower propensity to conduct crash avoidance maneuvers, (3) drowsiness and fatigue have a greater negative marginal effect on the tendency to engage in crash avoidance maneuvers than alcohol and drug consumption, (4) difficult road conditions increase the propensity to perform crash avoidance maneuvers, and (5) visual obstruction and artificial illumination decrease the probability to carry out crash avoidance maneuvers. The results emphasize the need for public awareness campaigns to promote safe driving style for senior drivers and warning about the risks of driving under fatigue and distraction being comparable to the risks of driving under the influence of alcohol and drugs. Moreover, the results suggest the need to educate drivers about hazard perception, designing

Artificial intelligence and finite element modelling for monitoring flood defence structures

NARCIS (Netherlands)

Pyayt, A.L.; Mokhov, I.I.; Kozionov, A.; Kusherbaeva, V.; Melnikova, N.B.; Krzhizhanovskaya, V.V.; Meijer, R.J.

2011-01-01

We present a hybrid approach to monitoring the stability of flood defence structures equipped with sensors. This approach combines the finite element modelling with the artificial intelligence for real-time signal processing and anomaly detection. This combined method has been developed for the

Corticonic models of brain mechanisms underlying cognition and intelligence

Science.gov (United States)

Farhat, Nabil H.

The concern of this review is brain theory or more specifically, in its first part, a model of the cerebral cortex and the way it: (a) interacts with subcortical regions like the thalamus and the hippocampus to provide higher-level-brain functions that underlie cognition and intelligence, (b) handles and represents dynamical sensory patterns imposed by a constantly changing environment, (c) copes with the enormous number of such patterns encountered in a lifetime by means of dynamic memory that offers an immense number of stimulus-specific attractors for input patterns (stimuli) to select from, (d) selects an attractor through a process of “conjugation” of the input pattern with the dynamics of the thalamo-cortical loop, (e) distinguishes between redundant (structured) and non-redundant (random) inputs that are void of information, (f) can do categorical perception when there is access to vast associative memory laid out in the association cortex with the help of the hippocampus, and (g) makes use of “computation” at the edge of chaos and information driven annealing to achieve all this. Other features and implications of the concepts presented for the design of computational algorithms and machines with brain-like intelligence are also discussed. The material and results presented suggest, that a Parametrically Coupled Logistic Map network (PCLMN) is a minimal model of the thalamo-cortical complex and that marrying such a network to a suitable associative memory with re-entry or feedback forms a useful, albeit, abstract model of a cortical module of the brain that could facilitate building a simple artificial brain. In the second part of the review, the results of numerical simulations and drawn conclusions in the first part are linked to the most directly relevant works and views of other workers. What emerges is a picture of brain dynamics on the mesoscopic and macroscopic scales that gives a glimpse of the nature of the long sought after brain code

Heuristic decision model for intelligent nuclear power systems design

International Nuclear Information System (INIS)

Nassersharif, B.; Portal, M.G.; Gaeta, M.J.

1989-01-01

The objective of this project was to investigate intelligent nuclear power systems design. A theoretical model of the design process has been developed. A fundamental process in this model is the heuristic decision making for design (i.e., selection of methods, components, materials, etc.). Rule-based expert systems do not provide the completeness that is necessary to generate good design. A new method, based on the fuzzy set theory, has been developed and is presented here. A feedwater system knowledge base (KB) was developed for a prototype software experiment to benchmark the theory

Discovery of cancer common and specific driver gene sets

Science.gov (United States)

2017-01-01

Abstract Cancer is known as a disease mainly caused by gene alterations. Discovery of mutated driver pathways or gene sets is becoming an important step to understand molecular mechanisms of carcinogenesis. However, systematically investigating commonalities and specificities of driver gene sets among multiple cancer types is still a great challenge, but this investigation will undoubtedly benefit deciphering cancers and will be helpful for personalized therapy and precision medicine in cancer treatment. In this study, we propose two optimization models to de novo discover common driver gene sets among multiple cancer types (ComMDP) and specific driver gene sets of one certain or multiple cancer types to other cancers (SpeMDP), respectively. We first apply ComMDP and SpeMDP to simulated data to validate their efficiency. Then, we further apply these methods to 12 cancer types from The Cancer Genome Atlas (TCGA) and obtain several biologically meaningful driver pathways. As examples, we construct a common cancer pathway model for BRCA and OV, infer a complex driver pathway model for BRCA carcinogenesis based on common driver gene sets of BRCA with eight cancer types, and investigate specific driver pathways of the liquid cancer lymphoblastic acute myeloid leukemia (LAML) versus other solid cancer types. In these processes more candidate cancer genes are also found. PMID:28168295

Intelligent Integrated System Health Management

Science.gov (United States)

Figueroa, Fernando

2012-01-01

Intelligent Integrated System Health Management (ISHM) is the management of data, information, and knowledge (DIaK) with the purposeful objective of determining the health of a system (Management: storage, distribution, sharing, maintenance, processing, reasoning, and presentation). Presentation discusses: (1) ISHM Capability Development. (1a) ISHM Knowledge Model. (1b) Standards for ISHM Implementation. (1c) ISHM Domain Models (ISHM-DM's). (1d) Intelligent Sensors and Components. (2) ISHM in Systems Design, Engineering, and Integration. (3) Intelligent Control for ISHM-Enabled Systems

Recent progress in competitive intelligence, competitive technical intelligence and knowledge management

Directory of Open Access Journals (Sweden)

Dou Henri

2011-04-01

Full Text Available This paper discusses the role of competitive intelligence and knowledge management to create, maintain and sustain competitive advantages. The triple helix model, based on the integration of the public sector (government, business models (private corporations and universities to promote innovation is examined. Research trends in competitive intelligence are presented. It concludes that the systematic use of the technology monitoring should support the comparison between various business models of companies that hold the market best practices and form a basis to knowledge for the decision making process and strategies development.

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 ...

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

Model analysis of the effects of atmospheric drivers on storage water use in Scots pine

Directory of Open Access Journals (Sweden)

H. Verbeeck

2007-08-01

Full Text Available Storage water use is an indirect consequence of the interplay between different meteorological drivers through their effect on water flow and water potential in trees. We studied these microclimatic drivers of storage water use in Scots pine (Pinus sylvestris L. growing in a temperate climate. The storage water use was modeled using the ANAFORE model, integrating a dynamic water flow and – storage model with a process-based transpiration model. The model was calibrated and validated with sap flow measurements for the growing season of 2000 (26 May–18 October.

Because there was no severe soil drought during the study period, we were able to study atmospheric effects. Incoming radiation and vapour pressure deficit (VPD were the main atmospheric drivers of storage water use. The general trends of sap flow and storage water use are similar, and follow more or less the pattern of incoming radiation. Nevertheless, considerable differences in the day-to-day pattern of sap flow and storage water use were observed. VPD was determined to be one of the main drivers of these differences. During dry atmospheric conditions (high VPD storage water use was reduced. This reduction was higher than the reduction in measured sap flow. Our results suggest that the trees did not rely more on storage water during periods of atmospheric drought, without severe soil drought. The daily minimum tree water content was lower in periods of high VPD, but the reserves were not completely depleted after the first day of high VPD, due to refilling during the night.

Nevertheless, the tree water content deficit was a third important factor influencing storage water use. When storage compartments were depleted beyond a threshold, storage water use was limited due to the low water potential in the storage compartments. The maximum relative contribution of storage water to daily transpiration was also constrained by an increasing tree water content

An extended car-following model considering the appearing probability of truck and driver's characteristics

Science.gov (United States)

Rong, Ying; Wen, Huiying

2018-05-01

In this paper, the appearing probability of truck is introduced and an extended car-following model is presented to analyze the traffic flow based on the consideration of driver's characteristics, under honk environment. The stability condition of this proposed model is obtained through linear stability analysis. In order to study the evolution properties of traffic wave near the critical point, the mKdV equation is derived by the reductive perturbation method. The results show that the traffic flow will become more disorder for the larger appearing probability of truck. Besides, the appearance of leading truck affects not only the stability of traffic flow, but also the effect of other aspects on traffic flow, such as: driver's reaction and honk effect. The effects of them on traffic flow are closely correlated with the appearing probability of truck. Finally, the numerical simulations under the periodic boundary condition are carried out to verify the proposed model. And they are consistent with the theoretical findings.

A multi-resolution envelope-power based model for speech intelligibility

DEFF Research Database (Denmark)

Jørgensen, Søren; Ewert, Stephan D.; Dau, Torsten

2013-01-01

The speech-based envelope power spectrum model (sEPSM) presented by Jørgensen and Dau [(2011). J. Acoust. Soc. Am. 130, 1475-1487] estimates the envelope power signal-to-noise ratio (SNRenv) after modulation-frequency selective processing. Changes in this metric were shown to account well...... to conditions with stationary interferers, due to the long-term integration of the envelope power, and cannot account for increased intelligibility typically obtained with fluctuating maskers. Here, a multi-resolution version of the sEPSM is presented where the SNRenv is estimated in temporal segments...... with a modulation-filter dependent duration. The multi-resolution sEPSM is demonstrated to account for intelligibility obtained in conditions with stationary and fluctuating interferers, and noisy speech distorted by reverberation or spectral subtraction. The results support the hypothesis that the SNRenv...

Towards a value model for collaborative, business intelligence-supported risk assessment

NARCIS (Netherlands)

Liu, L.; Daniëls, H.A.M.; Johannesson, P.

2012-01-01

Collaborative business intelligence supports risk assessment and in return enhances management control on a business network. Nonetheless, it needs an incentive basis in the first place before it can be implemented, that is, the value model. Starting from the managerial challenges which arise from

The ‘magic square’: A roadmap towards emotional business intelligence

OpenAIRE

Terziyan, Vagan; Kaikova, Olena

2015-01-01

Emotions are known to be an important driver in human behaviour and decision-making. In the business world, there is a growing belief that emotions are not an obstacle but rather an enabler for a successful business. Business intelligence (by providing analytical processing and convenient presentation of a business data) traditionally supports rational decision-making. However, opposite to former opinion that all decisions should be ‘cleansed’ of emotions, there are more and more indicators o...

Modeling Common-Sense Decisions in Artificial Intelligence

Science.gov (United States)

Zak, Michail

2010-01-01

A methodology has been conceived for efficient synthesis of dynamical models that simulate common-sense decision- making processes. This methodology is intended to contribute to the design of artificial-intelligence systems that could imitate human common-sense decision making or assist humans in making correct decisions in unanticipated circumstances. This methodology is a product of continuing research on mathematical models of the behaviors of single- and multi-agent systems known in biology, economics, and sociology, ranging from a single-cell organism at one extreme to the whole of human society at the other extreme. Earlier results of this research were reported in several prior NASA Tech Briefs articles, the three most recent and relevant being Characteristics of Dynamics of Intelligent Systems (NPO -21037), NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 48; Self-Supervised Dynamical Systems (NPO-30634), NASA Tech Briefs, Vol. 27, No. 3 (March 2003), page 72; and Complexity for Survival of Living Systems (NPO- 43302), NASA Tech Briefs, Vol. 33, No. 7 (July 2009), page 62. The methodology involves the concepts reported previously, albeit viewed from a different perspective. One of the main underlying ideas is to extend the application of physical first principles to the behaviors of living systems. Models of motor dynamics are used to simulate the observable behaviors of systems or objects of interest, and models of mental dynamics are used to represent the evolution of the corresponding knowledge bases. For a given system, the knowledge base is modeled in the form of probability distributions and the mental dynamics is represented by models of the evolution of the probability densities or, equivalently, models of flows of information. Autonomy is imparted to the decisionmaking process by feedback from mental to motor dynamics. This feedback replaces unavailable external information by information stored in the internal knowledge base. Representation

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)

Modelling intelligence-led policing to identify its potential

NARCIS (Netherlands)

Hengst-Bruggeling, M. den; Graaf, H.A.L.M. de; Scheepstal, P.G.M. van

2014-01-01

lntelligence-led policing is a concept of policing that has been applied throughout the world. Despite some encouraging reports, the effect of intelligence-led policing is largely unknown. This paper presents a method with which it is possible to identify intelligence-led policing's potential to

A survey on computational intelligence approaches for predictive modeling in prostate cancer

OpenAIRE

Cosma, G; Brown, D; Archer, M; Khan, M; Pockley, AG

2017-01-01

Predictive modeling in medicine involves the development of computational models which are capable of analysing large amounts of data in order to predict healthcare outcomes for individual patients. Computational intelligence approaches are suitable when the data to be modelled are too complex forconventional statistical techniques to process quickly and eciently. These advanced approaches are based on mathematical models that have been especially developed for dealing with the uncertainty an...

Application of Artificial Intelligence for Bridge Deterioration Model

Directory of Open Access Journals (Sweden)

Zhang Chen

2015-01-01

Full Text Available The deterministic bridge deterioration model updating problem is well established in bridge management, while the traditional methods and approaches for this problem require manual intervention. An artificial-intelligence-based approach was presented to self-updated parameters of the bridge deterioration model in this paper. When new information and data are collected, a posterior distribution was constructed to describe the integrated result of historical information and the new gained information according to Bayesian theorem, which was used to update model parameters. This AI-based approach is applied to the case of updating parameters of bridge deterioration model, which is the data collected from bridges of 12 districts in Shanghai from 2004 to 2013, and the results showed that it is an accurate, effective, and satisfactory approach to deal with the problem of the parameter updating without manual intervention.

A Framework for Intelligent Instructional Systems: An Artificial Intelligence Machine Learning Approach.

Science.gov (United States)

Becker, Lee A.

1987-01-01

Presents and develops a general model of the nature of a learning system and a classification for learning systems. Highlights include the relationship between artificial intelligence and cognitive psychology; computer-based instructional systems; intelligent instructional systems; and the role of the learner's knowledge base in an intelligent…

From Interactive Open Learner Modelling to Intelligent Mentoring: STyLE-OLM and Beyond

Science.gov (United States)

Dimitrova, Vania; Brna, Paul

2016-01-01

STyLE-OLM (Dimitrova 2003 "International Journal of Artificial Intelligence in Education," 13, 35-78) presented a framework for interactive open learner modelling which entails the development of the means by which learners can "inspect," "discuss" and "alter" the learner model that has been jointly…

An Intelligent System for Modelling, Design and Analysis of Chemical Processes

DEFF Research Database (Denmark)

Gani, Rafiqul

ICAS, Integrated Computer Aided System, is a software that consists of a number of intelligent tools, which are very suitable, among others, for computer aided modelling, sustainable design of chemical and biochemical processes, and design-analysis of product-process monitoring systems. Each...... the computer aided modelling tool will illustrate how to generate a desired process model, how to analyze the model equations, how to extract data and identify the model and make it ready for various types of application. In sustainable process design, the example will highlight the issue of integration...

Multiple Intelligences in Action.

Science.gov (United States)

Campbell, Bruce

1992-01-01

Describes the investigation of the effects of a four-step model program used with third through fifth grade students to implement Gardener's concepts of seven human intelligences--linguistic, logical/mathematical, visual/spatial, musical, kinesthetic, intrapersonal, and interpersonal intelligence--into daily learning. (BB)

Computational Foundations of Natural Intelligence.

Science.gov (United States)

van Gerven, Marcel

2017-01-01

New developments in AI and neuroscience are revitalizing the quest to understanding natural intelligence, offering insight about how to equip machines with human-like capabilities. This paper reviews some of the computational principles relevant for understanding natural intelligence and, ultimately, achieving strong AI. After reviewing basic principles, a variety of computational modeling approaches is discussed. Subsequently, I concentrate on the use of artificial neural networks as a framework for modeling cognitive processes. This paper ends by outlining some of the challenges that remain to fulfill the promise of machines that show human-like intelligence.

DEVELOPING A HUMAN CONTROLLED MODEL FOR SAFE ARTIFICIAL INTELLIGENCE SYSTEMS

OpenAIRE

KÖSE, Utku

2018-01-01

Artificial Intelligence is known as one of the most effective research field of nowadays and the future. But rapid rise of Artificial Intelligence and its potential to solve all real world problems autonomously, it has caused also several anxieties. Some scientists think that intelligent systems can reach to a level, which is dangerous for the humankind so because of that some precautions should be taken. So, many sub-research fields like Machine Ethics or Artificial Intelligence Safety have ...

[The use of biological age on mental work capacity model in accelerated aging assessment of professional lorry-drivers].

Science.gov (United States)

Bashkireva, A S

2012-01-01

The studies of biological age, aging rate, mental work capacity in professional drivers were conducted. The examination revealed peculiarities of system organization of functions determining the mental work capacity levels. Dynamics of the aging process of professional driver's organism in relation with calendar age and driving experience were shown using the biological age model. The results point at the premature decrease of the mental work capacity in professional drivers. It was proved, that premature age-related changes of physiologic and psychophysiologic indices in drivers are just "risk indicators", while long driving experience is a real risk factor, accelerating the aging process. The "risk group" with manifestations of accelerating aging was observed in 40-49-year old drivers with 15-19 years of professional experience. The expediency of using the following methods for the age rate estimation according to biologic age indices and necessity of prophylactic measures for premature and accelerated aging prevention among working population was demonstrated.

Education for older drivers in the future

Directory of Open Access Journals (Sweden)

Esko Keskinen

2014-07-01

Five presumptions have to be considered when addressing future education for older drivers: 1. Driving a car will continue to be one element of mobility in the future; 2. Older people want to be able to keep driving; 3. Safety will be an even more important factor in mobility in the future; 4. Ecological values will be more important in the future; and 5. Innovative technological applications will be more important in the future. Hierarchical models of driving are suitable in increasing understanding of older drivers' needs and abilities. The highest levels of the driving hierarchy in the Goals for Driver Education (GDE model are especially important for the safety of both young and elderly drivers. In these highest levels goals for life, skills for living, and social environment affect everyday decision making in general but also driving, which has an impact on driver safety. Giving up driving is very much a social decision and should be taken as such. However, the highest levels of the driving hierarchy are by nature inaccessible to teacher-centered instruction These levels require more coaching-like education methods where the learner takes the central role and the teacher helps the drivers understand their own abilities and limitations in traffic. Testing and selecting older drivers to enhance safety is not, according to research findings, working in a proper way. Older drivers do not so much need more information concerning traffic rules, etc., but rather better understanding of themselves, their health restrictions, their skills, and their abilities to ensure daily mobility. Their closest companions also need tools to help them in discussions of traffic safety issues affecting older drivers.

A review on the integration of artificial intelligence into coastal modeling.

Science.gov (United States)

Chau, Kwokwing

2006-07-01

With the development of computing technology, mechanistic models are often employed to simulate processes in coastal environments. However, these predictive tools are inevitably highly specialized, involving certain assumptions and/or limitations, and can be manipulated only by experienced engineers who have a thorough understanding of the underlying theories. This results in significant constraints on their manipulation as well as large gaps in understanding and expectations between the developers and practitioners of a model. The recent advancements in artificial intelligence (AI) technologies are making it possible to integrate machine learning capabilities into numerical modeling systems in order to bridge the gaps and lessen the demands on human experts. The objective of this paper is to review the state-of-the-art in the integration of different AI technologies into coastal modeling. The algorithms and methods studied include knowledge-based systems, genetic algorithms, artificial neural networks, and fuzzy inference systems. More focus is given to knowledge-based systems, which have apparent advantages over the others in allowing more transparent transfers of knowledge in the use of models and in furnishing the intelligent manipulation of calibration parameters. Of course, the other AI methods also have their individual contributions towards accurate and reliable predictions of coastal processes. The integrated model might be very powerful, since the advantages of each technique can be combined.

Research on driver fatigue detection

Science.gov (United States)

Zhang, Ting; Chen, Zhong; Ouyang, Chao

2018-03-01

Driver fatigue is one of the main causes of frequent traffic accidents. In this case, driver fatigue detection system has very important significance in avoiding traffic accidents. This paper presents a real-time method based on fusion of multiple facial features, including eye closure, yawn and head movement. The eye state is classified as being open or closed by a linear SVM classifier trained using HOG features of the detected eye. The mouth state is determined according to the width-height ratio of the mouth. The head movement is detected by head pitch angle calculated by facial landmark. The driver's fatigue state can be reasoned by the model trained by above features. According to experimental results, drive fatigue detection obtains an excellent performance. It indicates that the developed method is valuable for the application of avoiding traffic accidents caused by driver's fatigue.

Misbehaving Peer Models in the Classroom: An Investigation of the Effects of Social Class and Intelligence.

Science.gov (United States)

Kniveton, Bromley H.

1987-01-01

Investigates the effects on young male students of differing social backgrounds and varying levels of intelligence, of seeing a peer misbehave. Notes that working class boys imitated the misbehaving model significantly more than middle-class boys. Level of intelligence was not found to relate to the amount a student imitated a misbehaving peer.…

Experimental Research in Boost Driver with EDLCs

Science.gov (United States)

Matsumoto, Hirokazu

The supply used in servo systems tends to have a high voltage in order to reduce loss and improve the response of motor drives. We propose a new boost motor driver that comprises EDLCs. The proposed driver has a simple structure, wherein the EDLCs are connected in series to the supply, and comprises a charge circuit to charge the EDLCs. The proposed driver has three advantages over conventional boost drivers. The first advantage is that the driver can easily attain the stable boost voltage. The second advantage is that the driver can reduce input power peaks. In a servo system, the input power peaks become greater than the rated power in order to accelerate the motor rapidly. This implies that the equipments that supply power to servo systems must have sufficient power capacity to satisfy the power peaks. The proposed driver can suppress the increase of the power capacity of supply facilities. The third advantage is that the driver can store almost all of the regenerative energy. Conventional drivers have a braking resistor to suppress the increase in the DC link voltage. This causes a considerable reduction in the efficiency. The proposed driver is more efficient than conventional drivers. In this study, the experimental results confirmed the effectiveness of the proposed driver and showed that the drive performance of the proposed driver is the same as that of a conventional driver. Furthermore, it was confirmed that the results of the simulation of a model of the EDLC module, whose capacitance is dependent on the frequency, correspond well with the experimental results.

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,...

Computational Intelligence Agent-Oriented Modelling

Czech Academy of Sciences Publication Activity Database

Neruda, Roman

2006-01-01

Roč. 5, č. 2 (2006), s. 430-433 ISSN 1109-2777 R&D Projects: GA MŠk 1M0567 Institutional research plan: CEZ:AV0Z10300504 Keywords : multi-agent systems * adaptive agents * computational intelligence Subject RIV: IN - Informatics, Computer Science

Vision based Traffic Sign Detection and Analysis for Intelligent Driver Assistance Systems

DEFF Research Database (Denmark)

Møgelmose, Andreas; Trivedi, Mohan M.; Moeslund, Thomas B.

2012-01-01

In this paper, we provide a survey of the traffic sign detection literature, detailing detection systems for Traffic Sign Recognition (TSR) for driver assistance. We separately describe the contributions of recent works to the various stages inherent in traffic sign detection: segmentation, feature...... extraction, and final sign detection. While TSR is a well-established research area, we highlight open research issues in the literature, including a dearth of use of publicly-available image databases, and the over-representation of European traffic signs. Further, we discuss future directions for TSR...

Modelling how drivers respond to a bicyclist crossing their path at an intersection: How do test track and driving simulator compare?

Science.gov (United States)

Boda, Christian-Nils; Dozza, Marco; Bohman, Katarina; Thalya, Prateek; Larsson, Annika; Lubbe, Nils

2018-02-01

Bicyclist fatalities are a great concern in the European Union. Most of them are due to crashes between motorized vehicles and bicyclists at unsignalised intersections. Different countermeasures are currently being developed and implemented in order to save lives. One type of countermeasure, active safety systems, requires a deep understanding of driver behaviour to be effective without being annoying. The current study provides new knowledge about driver behaviour which can inform assessment programmes for active safety systems such as Euro NCAP. This study investigated how drivers responded to bicyclists crossing their path at an intersection. The influences of car speed and cyclist speed on the driver response process were assessed for three different crossing configurations. The same experimental protocol was tested in a fixed-base driving simulator and on a test track. A virtual model of the test track was used in the driving simulator to keep the protocol as consistent as possible across testing environments. Results show that neither car speed nor bicycle speed directly influenced the response process. The crossing configuration did not directly influence the braking response process either, but it did influence the strategy chosen by the drivers to approach the intersection. The point in time when the bicycle became visible (which depended on the car speed, the bicycle speed, and the crossing configuration) and the crossing configuration alone had the largest effects on the driver response process. Dissimilarities between test-track and driving-simulator studies were found; however, there were also interesting similarities, especially in relation to the driver braking behaviour. Drivers followed the same strategy to initiate braking, independent of the test environment. On the other hand, the test environment affected participants' strategies for releasing the gas pedal and regulating deceleration. Finally, a mathematical model, based on both experiments

The Comparison of Think Talk Write and Think Pair Share Model with Realistic Mathematics Education Approach Viewed from Mathematical-Logical Intelligence

Directory of Open Access Journals (Sweden)

Himmatul Afthina

2017-12-01

Full Text Available The aims of this research to determine the effect of Think Talk Write (TTW and Think Pair Share (TPS model with Realistic Mathematics Education (RME approach viewed from mathematical-logical intelligence. This research employed the quasi experimental research. The population of research was all students of the eight graders of junior high school in Karangamyar Regency in academic year 2016/2017. The result of this research shows that (1 TTW with RME approach gave better mathematics achievement than TPS with RME approach, (2 Students with high mathematical-logical intelligence can reach a better mathematics achievement than those with average and low, whereas students with average mathematical-logical intelligence can reach a better achievement than those with low one, (3 In TTW model with RME approach, students with high mathematical-logical intelligence can reach a better mathematics achievement than those with average and low, whereas students with average and low mathematical-logical intelligence gave same mathematics achievement, and  in TPS model with RME approach students with high mathematical-logical intelligence can reach a better mathematics achievement than those with average and low, whereas students with average mathematical-logical intelligence can reach a better achievement than those with low one (4 In each category of  mathematical-logical intelligence, TTW with RME approach and TPS with RME approach gave same mathematics achievement.

ICT-Supported Gaming for Competitive Intelligence

NARCIS (Netherlands)

Achterbergh, J.M.I.M.; Khosrow-Pour, M.

2005-01-01

Collecting and processing competitive intelligence for the purpose of strategy formulation are complex activities requiring deep insight in and models of the “organization in its environment.” These insights and models need to be not only shared between CI (competitive intelligence) practitioners

STUDY OF BUSINESS INTELLIGENCE SYSTEM QUALITY

OpenAIRE

DENIC Nebojsa; VUJOVIC Vuk; PERENIC Goran; SPASIC Boban

2016-01-01

IT has made remarkable progress over the last years. Business intelligence systems have been developing as an important part of IT. Enterprises often fail to realize importance and necessity of implementation of business intelligence solutions. This paper will deal with the approach for assessment of business intelligence in enterprises, based on maturity models. The significance of this paper is in the development of new conceptual research models which do not apply the usual thesis on ma...

Speech Intelligibility Evaluation for Mobile Phones

DEFF Research Database (Denmark)

Jørgensen, Søren; Cubick, Jens; Dau, Torsten

2015-01-01

In the development process of modern telecommunication systems, such as mobile phones, it is common practice to use computer models to objectively evaluate the transmission quality of the system, instead of time-consuming perceptual listening tests. Such models have typically focused on the quality...... of the transmitted speech, while little or no attention has been provided to speech intelligibility. The present study investigated to what extent three state-of-the art speech intelligibility models could predict the intelligibility of noisy speech transmitted through mobile phones. Sentences from the Danish...... Dantale II speech material were mixed with three different kinds of background noise, transmitted through three different mobile phones, and recorded at the receiver via a local network simulator. The speech intelligibility of the transmitted sentences was assessed by six normal-hearing listeners...

Terrorism Risk Modeling for Intelligence Analysis and Infrastructure Protection

National Research Council Canada - National Science Library

Willis, Henry H; LaTourrette, Tom; Kelly, Terrence K; Hickey, Scot; Neill, Samuel

2007-01-01

...? The Office of Intelligence and Analysis (OI&A) at DHS is responsible for using information and intelligence from multiple sources to identify and assess current and future threats to the United States...

Business Intelligence Issues for Sustainability Projects

Directory of Open Access Journals (Sweden)

Mihaela Muntean

2018-01-01

Full Text Available Business intelligence (BI is an umbrella term for strategies, technologies, and information systems used by the companies to extract from large and various data, according to the value chain, relevant knowledge to support a wide range of operational, tactical, and strategic business decisions. Sustainability, as an integrated part of the corporate business, implies the integration of the new approach at all levels: business model, performance management system, business intelligence project, and data model. Both business intelligence issues presented in this paper represent the contribution of the author in modeling data for supporting further BI approaches in corporate sustainability initiatives. Multi-dimensional modeling has been used to ground the proposals and to introduce the key performance indicators. The démarche is strengthened with implementation aspects and reporting examples. More than ever, in the Big Data era, bringing together business intelligence methods and tools with corporate sustainability is recommended.

Examination of Supplemental Driver Training and Online Basic Driver Education

Science.gov (United States)

2012-06-01

This report describes supplemental driver training programs and online basic driver education. It coves supplemental driver training that : focused on knowledge and skills beyond those normally found in traditional driver education delivered in the U...

A new coupled map car-following model considering drivers' steady desired speed

International Nuclear Information System (INIS)

Zhou Tong; Sun Di-Hua; Li Hua-Min; Liu Wei-Ning

2014-01-01

Based on the pioneering work of Konishi et al., in consideration of the influence of drivers' steady desired speed effect on the traffic flow, we develop a new coupled map car-following model in the real world. By use of the control theory, the stability condition of our model is derived. The validity of the present theoretical scheme is verified via numerical simulation, confirming the correctness of our theoretical analysis. (general)

Are professional drivers less sleepy than non-professional drivers?

Science.gov (United States)

Anund, Anna; Ahlström, Christer; Fors, Carina; Åkerstedt, Torbjörn

2018-01-01

Objective It is generally believed that professional drivers can manage quite severe fatigue before routine driving performance is affected. In addition, there are results indicating that professional drivers can adapt to prolonged night shifts and may be able to learn to drive without decreased performance under high levels of sleepiness. However, very little research has been conducted to compare professionals and non-professionals when controlling for time driven and time of day. Method The aim of this study was to use a driving simulator to investigate whether professional drivers are more resistant to sleep deprivation than non-professional drivers. Differences in the development of sleepiness (self-reported, physiological and behavioral) during driving was investigated in 11 young professional and 15 non-professional drivers. Results Professional drivers self-reported significantly lower sleepiness while driving a simulator than non-professional drivers. In contradiction, they showed longer blink durations and more line crossings, both of which are indicators of sleepiness. They also drove faster. The reason for the discrepancy in the relation between the different sleepiness indicators for the two groups could be due to more experience to sleepiness among the professional drivers or possibly to the faster speed, which might unconsciously have been used by the professionals to try to counteract sleepiness. Conclusion Professional drivers self-reported significantly lower sleepiness while driving a simulator than non-professional drivers. However, they showed longer blink durations and more line crossings, both of which are indicators of sleepiness, and they drove faster.

Computational Foundations of Natural Intelligence

Directory of Open Access Journals (Sweden)

Marcel van Gerven

2017-12-01

Full Text Available New developments in AI and neuroscience are revitalizing the quest to understanding natural intelligence, offering insight about how to equip machines with human-like capabilities. This paper reviews some of the computational principles relevant for understanding natural intelligence and, ultimately, achieving strong AI. After reviewing basic principles, a variety of computational modeling approaches is discussed. Subsequently, I concentrate on the use of artificial neural networks as a framework for modeling cognitive processes. This paper ends by outlining some of the challenges that remain to fulfill the promise of machines that show human-like intelligence.

Artificial Intelligence in Civil Engineering

OpenAIRE

Lu, Pengzhen; Chen, Shengyong; Zheng, Yujun

2012-01-01

Artificial intelligence is a branch of computer science, involved in the research, design, and application of intelligent computer. Traditional methods for modeling and optimizing complex structure systems require huge amounts of computing resources, and artificial-intelligence-based solutions can often provide valuable alternatives for efficiently solving problems in the civil engineering. This paper summarizes recently developed methods and theories in the developing direction for applicati...

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 ...

Development of a real-time prediction model of driver behavior at intersections using kinematic time series data.

Science.gov (United States)

Tan, Yaoyuan V; Elliott, Michael R; Flannagan, Carol A C

2017-09-01

As connected autonomous vehicles (CAVs) enter the fleet, there will be a long period when these vehicles will have to interact with human drivers. One of the challenges for CAVs is that human drivers do not communicate their decisions well. Fortunately, the kinematic behavior of a human-driven vehicle may be a good predictor of driver intent within a short time frame. We analyzed the kinematic time series data (e.g., speed) for a set of drivers making left turns at intersections to predict whether the driver would stop before executing the turn. We used principal components analysis (PCA) to generate independent dimensions that explain the variation in vehicle speed before a turn. These dimensions remained relatively consistent throughout the maneuver, allowing us to compute independent scores on these dimensions for different time windows throughout the approach to the intersection. We then linked these PCA scores to whether a driver would stop before executing a left turn using the random intercept Bayesian additive regression trees. Five more road and observable vehicle characteristics were included to enhance prediction. Our model achieved an area under the receiver operating characteristic curve (AUC) of 0.84 at 94m away from the center of an intersection and steadily increased to 0.90 by 46m away from the center of an intersection. Copyright © 2017 Elsevier Ltd. All rights reserved.

Use of artificial intelligence to identify cardiovascular compromise in a model of hemorrhagic shock.

Science.gov (United States)

Glass, Todd F; Knapp, Jason; Amburn, Philip; Clay, Bruce A; Kabrisky, Matt; Rogers, Steven K; Garcia, Victor F

2004-02-01

To determine whether a prototype artificial intelligence system can identify volume of hemorrhage in a porcine model of controlled hemorrhagic shock. Prospective in vivo animal model of hemorrhagic shock. Research foundation animal surgical suite; computer laboratories of collaborating industry partner. Nineteen, juvenile, 25- to 35-kg, male and female swine. Anesthetized animals were instrumented for arterial and systemic venous pressure monitoring and blood sampling, and a splenectomy was performed. Following a 1-hr stabilization period, animals were hemorrhaged in aliquots to 10, 20, 30, 35, 40, 45, and 50% of total blood volume with a 10-min recovery between each aliquot. Data were downloaded directly from a commercial monitoring system into a proprietary PC-based software package for analysis. Arterial and venous blood gas values, glucose, and cardiac output were collected at specified intervals. Electrocardiogram, electroencephalogram, mixed venous oxygen saturation, temperature (core and blood), mean arterial pressure, pulmonary artery pressure, central venous pressure, pulse oximetry, and end-tidal CO(2) were continuously monitored and downloaded. Seventeen of 19 animals (89%) died as a direct result of hemorrhage. Stored data streams were analyzed by the prototype artificial intelligence system. For this project, the artificial intelligence system identified and compared three electrocardiographic features (R-R interval, QRS amplitude, and R-S interval) from each of nine unknown samples of the QRS complex. We found that the artificial intelligence system, trained on only three electrocardiographic features, identified hemorrhage volume with an average accuracy of 91% (95% confidence interval, 84-96%). These experiments demonstrate that an artificial intelligence system, based solely on the analysis of QRS amplitude, R-R interval, and R-S interval of an electrocardiogram, is able to accurately identify hemorrhage volume in a porcine model of lethal

DRIVER INATTENTION

Directory of Open Access Journals (Sweden)

Richard TAY

2004-01-01

Full Text Available Driver inattention, especially driver distraction, is an extremely influential but generally neglected contributing factor of road crashes. This paper explores some of the common behaviours associated with several common forms of driver inattention, with respect to their perceived crash risks, rates of self-reported behaviours and whether drivers regulate such behaviours depending on the road and traffic environment, and provides some policy recommendations to address issues raised.

Study on intelligent processing system of man-machine interactive garment frame model

Science.gov (United States)

Chen, Shuwang; Yin, Xiaowei; Chang, Ruijiang; Pan, Peiyun; Wang, Xuedi; Shi, Shuze; Wei, Zhongqian

2018-05-01

A man-machine interactive garment frame model intelligent processing system is studied in this paper. The system consists of several sensor device, voice processing module, mechanical parts and data centralized acquisition devices. The sensor device is used to collect information on the environment changes brought by the body near the clothes frame model, the data collection device is used to collect the information of the environment change induced by the sensor device, voice processing module is used for speech recognition of nonspecific person to achieve human-machine interaction, mechanical moving parts are used to make corresponding mechanical responses to the information processed by data collection device.it is connected with data acquisition device by a means of one-way connection. There is a one-way connection between sensor device and data collection device, two-way connection between data acquisition device and voice processing module. The data collection device is one-way connection with mechanical movement parts. The intelligent processing system can judge whether it needs to interact with the customer, realize the man-machine interaction instead of the current rigid frame model.

The Cylindrical Structure of the Wechsler Intelligence Scale for Children--IV: A Retest of the Guttman Model of Intelligence

Science.gov (United States)

Cohen, Arie; Fiorello, Catherine A.; Farley, Frank H.

2006-01-01

A previous study on the underlying structure of the Wechsler intelligence test (WISC-R; [Wechsler, D. (1974). Manual WISC-R: Wechsler intelligence scale for children-Revised. New York: Psychological Corporation]), using smallest space analysis (SSA) [Guttman, L., and Levy, S. (1991). Two structural laws for intelligence tests.…

An Architectural Modelfor Intelligent Network Management

Institute of Scientific and Technical Information of China (English)

罗军舟; 顾冠群; 费翔

2000-01-01

Traditional network management approach involves the management of each vendor's equipment and network segment in isolation through its own proprietary element management system. It is necessary to set up a new network management architecture that calls for operation consolidation across vendor and technology boundaries. In this paper, an architectural model for Intelligent Network Management (INM) is presented. The INM system includes a manager system, which controls all subsystems and coordinates different management tasks; an expert system, which is responsible for handling particularly difficult problems, and intelligent agents, which bring the management closer to applications and user requirements by spreading intelligent agents through network segments or domain. In the expert system model proposed, especially an intelligent fault management system is given.The architectural model is to build the INM system to meet the need of managing modern network systems.

Modelling of agricultural combination driver behaviour from the aspect of safety of movement

Directory of Open Access Journals (Sweden)

Jan Szczepaniak

2014-06-01

Full Text Available Statistics show that the travel of agricultural machinery to a work area and their movement during labour is the source of many serious accidents. The most dangerous in consequences prove to be those that occur during transport and associated with maneuvering tractors and machinery (about 30% of all fatal accidents. It can be assumed that at least some of these accidents were caused indirectly by the specific design features of agricultural machines which adversely affect the driveability. The single- and multi-loop structures of the driver-vehicle system models are formulated to study the contributions of various preview and prediction strategies to the path tracking and dynamic performance of the articulated vehicle. In the presented study the compensatory model of driver utilizes the lateral acceleration of the tractor, roll angle of trailer sprung mass and the articulation rate as the internal motion feedback variables. The control model of steering of an agricultural set has been implemented in the Matlab/Simulink environment. The model has been constructed with the use of stochastic methods and operational transmittances describing the various components of the system. The model operational transmittances has been estimated using Box-Jenkins and continuous-time process models from input-output data. The model has been tested using experimental data from road investigation of the agricultural set.

Forecasting municipal solid waste generation using artificial intelligence modelling approaches.

Science.gov (United States)

Abbasi, Maryam; El Hanandeh, Ali

2016-10-01

Municipal solid waste (MSW) management is a major concern to local governments to protect human health, the environment and to preserve natural resources. The design and operation of an effective MSW management system requires accurate estimation of future waste generation quantities. The main objective of this study was to develop a model for accurate forecasting of MSW generation that helps waste related organizations to better design and operate effective MSW management systems. Four intelligent system algorithms including support vector machine (SVM), adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN) and k-nearest neighbours (kNN) were tested for their ability to predict monthly waste generation in the Logan City Council region in Queensland, Australia. Results showed artificial intelligence models have good prediction performance and could be successfully applied to establish municipal solid waste forecasting models. Using machine learning algorithms can reliably predict monthly MSW generation by training with waste generation time series. In addition, results suggest that ANFIS system produced the most accurate forecasts of the peaks while kNN was successful in predicting the monthly averages of waste quantities. Based on the results, the total annual MSW generated in Logan City will reach 9.4×10(7)kg by 2020 while the peak monthly waste will reach 9.37×10(6)kg. Copyright © 2016 Elsevier Ltd. All rights reserved.

Role of theory of mind and executive function in explaining social intelligence: a structural equation modeling approach.

Science.gov (United States)

Yeh, Zai-Ting

2013-01-01

Social intelligence is the ability to understand others and the social context effectively and thus to interact with people successfully. Research has suggested that the theory of mind (ToM) and executive function may play important roles in explaining social intelligence. The specific aim of the present study was to test with structural equation modeling (SEM) the hypothesis that performance on ToM tasks is more associated with social intelligence in the elderly than is performance on executive functions. One hundred and seventy-seven participants (age 56-96) completed ToM, executive function, and other basic cognition tasks, and were rated with social intelligence scales. The SEM results showed that ToM and executive function were strongly correlated (0.54); however, only the path coefficient from ToM to social intelligence, and not from executive function, was significant (0.37). ToM performance, but not executive function, was strongly correlated with social intelligence among elderly individuals. ToM and executive function might play different roles in social behavior during normal aging; however, based on the present results, it is possible that ToM might play an important role in social intelligence.

SPIDER: A Framework for Understanding Driver Distraction.

Science.gov (United States)

Strayer, David L; Fisher, Donald L

2016-02-01

The objective was to identify key cognitive processes that are impaired when drivers divert attention from driving. Driver distraction is increasingly recognized as a significant source of injuries and fatalities on the roadway. A "SPIDER" model is developed that identifies key cognitive processes that are impaired when drivers divert attention from driving. SPIDER is an acronym standing for scanning, predicting, identifying, decision making, and executing a response. When drivers engage in secondary activities unrelated to the task of driving, SPIDER-related processes are impaired, situation awareness is degraded, and the ability to safely operate a motor vehicle may be compromised. The pattern of interference helps to illuminate the sources of driver distraction and may help guide the integration of new technology into the automobile. © 2015, Human Factors and Ergonomics Society.

Artificial Intelligence (AI) Studies in Water Resources

OpenAIRE

Ay, Murat; Özyıldırım, Serhat

2018-01-01

Artificial intelligence has been extensively used in many areas such as computer science,robotics, engineering, medicine, translation, economics, business, and psychology. Variousstudies in the literature show that the artificial intelligence in modeling approaches give closeresults to the real data for solution of linear, non-linear, and other systems. In this study, wereviewed the current state-of-the-art and progress on the modelling of artificial intelligence forwater variables: rainfall-...

Assessing characteristics related to the use of seatbelts and cell phones by drivers: application of a bivariate probit model.

Science.gov (United States)

Russo, Brendan J; Kay, Jonathan J; Savolainen, Peter T; Gates, Timothy J

2014-06-01

The effects of cell phone use and safety belt use have been an important focus of research related to driver safety. Cell phone use has been shown to be a significant source of driver distraction contributing to substantial degradations in driver performance, while safety belts have been demonstrated to play a vital role in mitigating injuries to crash-involved occupants. This study examines the prevalence of cell phone use and safety belt non-use among the driving population through direct observation surveys. A bivariate probit model is developed to simultaneously examine the factors that affect cell phone and safety belt use among motor vehicle drivers. The results show that several factors may influence drivers' decision to use cell phones and safety belts, and that these decisions are correlated. Understanding the factors that affect both cell phone use and safety belt non-use is essential to targeting policy and programs that reduce such behavior. Copyright © 2014 Elsevier Ltd. All rights reserved.

The experimentation of LC7E learning model on the linear program material in terms of interpersonal intelligence on Wonogiri Vocational School students

Science.gov (United States)

Antinah; Kusmayadi, T. A.; Husodo, B.

2018-03-01

This study aimed to determine the effect of learning model on student achievement in terms of interpersonal intelligence. The compared learning models are LC7E and Direct learning model. This type of research is a quasi-experimental with 2x3 factorial design. The population in this study is a Grade XI student of Wonogiri Vocational Schools. The sample selection had done by stratified cluster random sampling. Data collection technique used questionnaires, documentation and tests. The data analysis technique used two different unequal cell variance analysis which previously conducted prerequisite analysis for balance test, normality test and homogeneity test. he conclusions of this research are: 1) student learning achievement of mathematics given by LC7E learning model is better when compared with direct learning; 2) Mathematics learning achievement of students who have a high level of interpersonal intelligence is better than students with interpersonal intelligence in medium and low level. Students’ mathematics learning achievement with interpersonal level of intelligence is better than those with low interpersonal intelligence on linear programming; 3) LC7E learning model resulted better on mathematics learning achievement compared with direct learning model for each category of students’ interpersonal intelligence level on linear program material.

The experimentation of LC7E learning model on the linear program material in terms of interpersonal intelligence on Wonogiri vocational school students

Science.gov (United States)

Antinah; Kusmayadi, T. A.; Husodo, B.

2018-05-01

This study aims to determine the effect of learning model on student achievement in terms of interpersonal intelligence. The compared learning models are LC7E and Direct learning model. This type of research is a quasi-experimental with 2x3 factorial design. The population in this study is a Grade XI student of Wonogiri Vocational Schools. The sample selection had done by stratified cluster random sampling. Data collection technique used questionnaires, documentation and tests. The data analysis technique used two different unequal cell variance analysis which previously conducted prerequisite analysis for balance test, normality test and homogeneity test. he conclusions of this research are: 1) student learning achievement of mathematics given by LC7E learning model is better when compared with direct learning; 2) Mathematics learning achievement of students who have a high level of interpersonal intelligence is better than students with interpersonal intelligence in medium and low level. Students' mathematics learning achievement with interpersonal level of intelligence is better than those with low interpersonal intelligence on linear programming; 3) LC7E learning model resulted better on mathematics learning achievement compared with direct learning model for each category of students’ interpersonal intelligence level on linear program material.

A conceptual competitive intelligence quality assurance model

Directory of Open Access Journals (Sweden)

Tshilidzi Eric Nenzhelele

2015-12-01

Full Text Available Competitive Intelligence (CI improves the quality of product and service, decision-making and it improves quality of life. However, it has been established that decision makers are not happy about the quality of CI. This is because enterprises fail in quality assurance of CI. It has been concluded that most enterprises are clueless concerning CI quality assurance. Studies that previously attempted to resolve CI quality problem were limited in scope and focused too much on the quality of information than the overall CI quality. The purpose of this study is to propose a conceptual CI quality assurance model which will help in quality assurance of CI. The research was qualitative in nature and used content analysis.

Driving fatigue in professional drivers: a survey of truck and taxi drivers.

Science.gov (United States)

Meng, Fanxing; Li, Shuling; Cao, Lingzhi; Li, Musen; Peng, Qijia; Wang, Chunhui; Zhang, Wei

2015-01-01

Fatigue among truck drivers has been studied extensively; however, less is known regarding the fatigue experience of taxi drivers in heavily populated metropolitan areas. This study aimed to compare the differences and similarities between truck and taxi driver fatigue to provide implications for the fatigue management and education of professional drivers. A sample of 274 truck drivers and 286 taxi drivers in Beijing was surveyed via a questionnaire, which included items regarding work characteristics, fatigue experience, accident information, attitude toward fatigue, and methods of counteracting fatigue. Driver fatigue was prevalent among professional drivers, and it was even more serious for taxi drivers. Taxi drivers reported more frequent fatigue experiences and were involved in more accidents. Among the contributing factors to fatigue, prolonged driving time was the most important factor identified by both driver groups. Importantly, the reason for the engagement in prolonged driving was neither due to the lack of awareness concerning the serious outcome of fatigue driving nor because of their poor detection of fatigue. The most probable reason was the optimism bias, as a result of which these professional drivers thought that fatigue was more serious for other drivers than for themselves, and they thought that they were effective in counteracting the effect of fatigue on their driving performance. Moreover, truck drivers tended to employ methods that require stopping to counteract fatigue, whereas taxi drivers preferred methods that were simultaneous with driving. Although both driver groups considered taking a nap as one of the most effective means to address fatigue, this method was not commonly used. Interestingly, these drivers were aware that the methods they frequently used were not the most effective means to counteract fatigue. This study provides knowledge on truck and taxi drivers' characteristics in fatigue experience, fatigue attitude, and

Addressing diverse learner preferences and intelligences with emerging technologies: Matching models to online opportunities

Directory of Open Access Journals (Sweden)

Ke Zhang

2009-03-01

Full Text Available This paper critically reviews various learning preferences and human intelligence theories and models with a particular focus on the implications for online learning. It highlights a few key models, Gardner’s multiple intelligences, Fleming and Mills’ VARK model, Honey and Mumford’s Learning Styles, and Kolb’s Experiential Learning Model, and attempts to link them to trends and opportunities in online learning with emerging technologies. By intersecting such models with online technologies, it offers instructors and instructional designers across educational sectors and situations new ways to think about addressing diverse learner needs, backgrounds, and expectations. Learning technologies are important for effective teaching, as are theories and models and theories of learning. We argue that more immense power can be derived from connections between the theories, models and learning technologies. Résumé : Cet article passe en revue de manière critique les divers modèles et théories sur les préférences d’apprentissage et l’intelligence humaine, avec un accent particulier sur les implications qui en découlent pour l’apprentissage en ligne. L’article présente quelques-uns des principaux modèles (les intelligences multiples de Gardner, le modèle VAK de Fleming et Mills, les styles d’apprentissage de Honey et Mumford et le modèle d’apprentissage expérientiel de Kolb et tente de les relier à des tendances et occasions d’apprentissage en ligne qui utilisent les nouvelles technologies. En croisant ces modèles avec les technologies Web, les instructeurs et concepteurs pédagogiques dans les secteurs de l’éducation ou en situation éducationnelle se voient offrir de nouvelles façons de tenir compte des divers besoins, horizons et attentes des apprenants. Les technologies d’apprentissage sont importantes pour un enseignement efficace, tout comme les théories et les modèles d’apprentissage. Nous sommes d�

Model of intelligent information searching system

International Nuclear Information System (INIS)

Yastrebkov, D.I.

2004-01-01

A brief description of the technique to search for electronic documents in large archives as well as drawbacks is presented. A solution close to intelligent information searching systems is proposed. (author)

Modeling intelligent agent beliefs in a card game scenario

Science.gov (United States)

Gołuński, Marcel; Tomanek, Roman; WÄ siewicz, Piotr

In this paper we explore the problem of intelligent agent beliefs. We model agent beliefs using multimodal logics of belief, KD45(m) system implemented as a directed graph depicting Kripke semantics, precisely. We present a card game engine application which allows multiple agents to connect to a given game session and play the card game. As an example simplified version of popular Saboteur card game is used. Implementation was done in Java language using following libraries and applications: Apache Mina, LWJGL.

The Effects of Vehicle Redesign on the Risk of Driver Death.

Science.gov (United States)

Farmer, Charles M; Lund, Adrian K

2015-01-01

This study updates a 2006 report that estimated the historical effects of vehicle design changes on driver fatality rates in the United States, separate from the effects of environmental and driver behavior changes during the same period. In addition to extending the period covered by 8 years, this study estimated the effect of design changes by model year and vehicle type. Driver death rates for consecutive model years of vehicle models without design changes were used to estimate the vehicle aging effect and the death rates that would have been expected if the entire fleet had remained unchanged from the 1985 calendar year. These calendar year estimates are taken to be the combined effect of road environment and motorist behavioral changes, with the difference between them and the actual calendar year driver fatality rates reflecting the effect of changes in vehicle design and distribution of vehicle types. The effects of vehicle design changes by model year were estimated for cars, SUVs, and pickups by computing driver death rates for model years 1984-2009 during each of their first 3 full calendar years of exposure and comparing with the expected rates if there had been no design changes. As reported in the 2006 study, had there been no changes in the vehicle fleet, driver death risk would have declined during calendar years 1985-1993 and then slowly increased from 1993 to 2004. The updated results indicate that the gradual increase would have continued through 2006, after which driver fatality rates again would have declined through 2012. Overall, it is estimated that there were 7,700 fewer driver deaths in 2012 than there would have been had vehicle designs not changed. Cars were the first vehicle type whose design safety generally exceeded that of the 1984 model year (starting in model year 1996), followed by SUVs (1998 models) and pickups (2002 models). By the 2009 model year, car driver fatality risk had declined 51% from its high in 1994, pickup driver

A Framework for Analysing Driver Interactions with Semi-Autonomous Vehicles

Directory of Open Access Journals (Sweden)

Siraj Shaikh

2012-12-01

Full Text Available Semi-autonomous vehicles are increasingly serving critical functions in various settings from mining to logistics to defence. A key characteristic of such systems is the presence of the human (drivers in the control loop. To ensure safety, both the driver needs to be aware of the autonomous aspects of the vehicle and the automated features of the vehicle built to enable safer control. In this paper we propose a framework to combine empirical models describing human behaviour with the environment and system models. We then analyse, via model checking, interaction between the models for desired safety properties. The aim is to analyse the design for safe vehicle-driver interaction. We demonstrate the applicability of our approach using a case study involving semi-autonomous vehicles where the driver fatigue are factors critical to a safe journey.

Leader emotional intelligence, transformational leadership, trust and team commitment: Testing a model within a team context

Directory of Open Access Journals (Sweden)

Anton F. Schlechter

2008-06-01

Full Text Available This exploratory study tested a model within a team context consisting of transformational-leadership behaviour, team-leader emotional intelligence, trust (both in the team leader and in the team members and team commitment. It was conducted within six manufacturing plants, with 25 teams participating. Of the 320 surveys distributed to these teams, 178 were received (which equals a 56% response rate. The surveys consisted of the multi-factor leadership questionnaire (MLQ, the Swinburne University emotional intelligence test (SUEIT, the organisational-commitment scale (OCS (adapted for team commitment and the workplace trust survey (WTS. The validity of these scales was established using exploratory factor analysis (EFA and confrmatory factor analysis (CFA. The Cronbach alpha was used to assess the reliability of the scales. The model was tested using structural equation modelling (SEM; an acceptable level of model ft was found. Signifcant positive relationships were further found among all the constructs. Such an integrated model has not been tested in a team context before and the positive fndings therefore add to existing teamwork literature. The fnding that transformational leadership and leader emotional intelligence are positively related to team commitment and trust further emphasises the importance of effective leadership behaviour in team dynamics and performance.

The Impact of Business Intelligence Tools on Performance: A User Satisfaction Paradox?

OpenAIRE

Bernhard Wieder; Maria-Luise Ossimitz; Peter Chamoni

2012-01-01

While Business Intelligence (BI) initiatives have been a top-priority of CIOs around the world for several years, accounting for billions of USD of IT investments per annum (IDC), academic research on the actual benefits derived from BI tools and the drivers of these benefits remain sparse. This paper reports the findings of an exploratory, cross-sectional field study investigating the factors that define and drive benefits associated with the deployment of dedicated BI tools. BI is broadly d...

The Application of Collaborative Business Intelligence Technology in the Hospital SPD Logistics Management Model.

Science.gov (United States)

Liu, Tongzhu; Shen, Aizong; Hu, Xiaojian; Tong, Guixian; Gu, Wei

2017-06-01

We aimed to apply collaborative business intelligence (BI) system to hospital supply, processing and distribution (SPD) logistics management model. We searched Engineering Village database, China National Knowledge Infrastructure (CNKI) and Google for articles (Published from 2011 to 2016), books, Web pages, etc., to understand SPD and BI related theories and recent research status. For the application of collaborative BI technology in the hospital SPD logistics management model, we realized this by leveraging data mining techniques to discover knowledge from complex data and collaborative techniques to improve the theories of business process. For the application of BI system, we: (i) proposed a layered structure of collaborative BI system for intelligent management in hospital logistics; (ii) built data warehouse for the collaborative BI system; (iii) improved data mining techniques such as supporting vector machines (SVM) and swarm intelligence firefly algorithm to solve key problems in hospital logistics collaborative BI system; (iv) researched the collaborative techniques oriented to data and business process optimization to improve the business processes of hospital logistics management. Proper combination of SPD model and BI system will improve the management of logistics in the hospitals. The successful implementation of the study requires: (i) to innovate and improve the traditional SPD model and make appropriate implement plans and schedules for the application of BI system according to the actual situations of hospitals; (ii) the collaborative participation of internal departments in hospital including the department of information, logistics, nursing, medical and financial; (iii) timely response of external suppliers.

A methodology for the design of experiments in computational intelligence with multiple regression models.

Science.gov (United States)

Fernandez-Lozano, Carlos; Gestal, Marcos; Munteanu, Cristian R; Dorado, Julian; Pazos, Alejandro

2016-01-01

The design of experiments and the validation of the results achieved with them are vital in any research study. This paper focuses on the use of different Machine Learning approaches for regression tasks in the field of Computational Intelligence and especially on a correct comparison between the different results provided for different methods, as those techniques are complex systems that require further study to be fully understood. A methodology commonly accepted in Computational intelligence is implemented in an R package called RRegrs. This package includes ten simple and complex regression models to carry out predictive modeling using Machine Learning and well-known regression algorithms. The framework for experimental design presented herein is evaluated and validated against RRegrs. Our results are different for three out of five state-of-the-art simple datasets and it can be stated that the selection of the best model according to our proposal is statistically significant and relevant. It is of relevance to use a statistical approach to indicate whether the differences are statistically significant using this kind of algorithms. Furthermore, our results with three real complex datasets report different best models than with the previously published methodology. Our final goal is to provide a complete methodology for the use of different steps in order to compare the results obtained in Computational Intelligence problems, as well as from other fields, such as for bioinformatics, cheminformatics, etc., given that our proposal is open and modifiable.

A methodology for the design of experiments in computational intelligence with multiple regression models

Directory of Open Access Journals (Sweden)

Carlos Fernandez-Lozano

2016-12-01

Full Text Available The design of experiments and the validation of the results achieved with them are vital in any research study. This paper focuses on the use of different Machine Learning approaches for regression tasks in the field of Computational Intelligence and especially on a correct comparison between the different results provided for different methods, as those techniques are complex systems that require further study to be fully understood. A methodology commonly accepted in Computational intelligence is implemented in an R package called RRegrs. This package includes ten simple and complex regression models to carry out predictive modeling using Machine Learning and well-known regression algorithms. The framework for experimental design presented herein is evaluated and validated against RRegrs. Our results are different for three out of five state-of-the-art simple datasets and it can be stated that the selection of the best model according to our proposal is statistically significant and relevant. It is of relevance to use a statistical approach to indicate whether the differences are statistically significant using this kind of algorithms. Furthermore, our results with three real complex datasets report different best models than with the previously published methodology. Our final goal is to provide a complete methodology for the use of different steps in order to compare the results obtained in Computational Intelligence problems, as well as from other fields, such as for bioinformatics, cheminformatics, etc., given that our proposal is open and modifiable.

Intelligent speed adaptation: Preliminary results of on-road study in Penang, Malaysia

Directory of Open Access Journals (Sweden)

S.M.R. Ghadiri

2013-03-01

Full Text Available The first field experiment with intelligent speed adaptation (ISA in Malaysia was held in December 2010 in the State of Penang. Eleven private cars were instrumented with an advisory system. The system used in the present study included a vocal warning message and a visual text message that is activated when the driver attempts to exceed the speed limit. When the driver decreases the speed, the warning stops; otherwise it is continuously repeated. The test drivers drove the vehicles for three months with the installed system, and the speed was continuously logged in all vehicles. The warning was however only activated in the second month of the three month period. The present study aimed to evaluate the effects of an advisory ISA on driving speed, traffic safety, and drivers' attitude, behavior, and acceptance of the system. To examine these effects, both the survey and the logged speed data were analyzed and explored. The results show a significant reduction in the mean, maximum and 85th percentile speed due to the use of the system. However, there was no long-lasting effect on the speed when the system was deactivated. In the post-trial survey, drivers declared that the system helped them well in following the speed limits and that it assisted them in driving more comfortably. Furthermore, the warning method was more accepted compared to a supportive system, such as active accelerator pedal (AAP. After the trial, most drivers were willing to keep an ISA system.

Calculating the Contribution Rate of Intelligent Transportation System in Improving Urban Traffic Smooth Based on Advanced DID Model

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Ming-wei Li

2015-01-01

Full Text Available Recent years have witnessed the rapid development of intelligent transportation system around the world, which helps to relieve urban traffic congestion problems. For instance, many mega-cities in China have devoted a large amount of money and resources to the development of intelligent transportation system. This poses an intriguing and important issue: how to measure and quantify the contribution of intelligent transportation system to the urban city, which is still a puzzle. This paper proposes a matching difference-in-difference model to calculate the contribution rate of intelligent transportation system on traffic smoothness. Within the model, the main effect indicators of traffic smoothness are first identified, and then the evaluation index system is built, and finally the ideas of the matching pool are introduced. The proposed model is illustrated in Guangzhou, China (capital city of Guangdong province. The results show that introduction of ITS contributes 9.25% to the improvement of traffic smooth in Guangzhou. Also, the research explains the working mechanism of how ITS improves urban traffic smooth. Eventually, some strategy recommendations are put forward to improve urban traffic smooth.

Speech Intelligibility Prediction Based on Mutual Information

DEFF Research Database (Denmark)

Jensen, Jesper; Taal, Cees H.

2014-01-01

This paper deals with the problem of predicting the average intelligibility of noisy and potentially processed speech signals, as observed by a group of normal hearing listeners. We propose a model which performs this prediction based on the hypothesis that intelligibility is monotonically related...... to the mutual information between critical-band amplitude envelopes of the clean signal and the corresponding noisy/processed signal. The resulting intelligibility predictor turns out to be a simple function of the mean-square error (mse) that arises when estimating a clean critical-band amplitude using...... a minimum mean-square error (mmse) estimator based on the noisy/processed amplitude. The proposed model predicts that speech intelligibility cannot be improved by any processing of noisy critical-band amplitudes. Furthermore, the proposed intelligibility predictor performs well ( ρ > 0.95) in predicting...

A DISTRIBUTED SMART HOME ARTIFICIAL INTELLIGENCE SYSTEM

DEFF Research Database (Denmark)

Lynggaard, Per

2013-01-01

A majority of the research performed today explore artificial intelligence in smart homes by using a centralized approach where a smart home server performs the necessary calculations. This approach has some disadvantages that can be overcome by shifting focus to a distributed approach where...... the artificial intelligence system is implemented as distributed as agents running parts of the artificial intelligence system. This paper presents a distributed smart home architecture that distributes artificial intelligence in smart homes and discusses the pros and cons of such a concept. The presented...... distributed model is a layered model. Each layer offers a different complexity level of the embedded distributed artificial intelligence. At the lowest layer smart objects exists, they are small cheap embedded microcontroller based smart devices that are powered by batteries. The next layer contains a more...

The comparing analysis of simulation of emergent dispatch of cars for intelligent driving autos in crossroads

Science.gov (United States)

Zheng, Ziao

2018-03-01

It is widely acknowledged that it is important for the development of intelligent cars to be widely accepted by the majority of car users. While most of the intelligent cars have the system of monitoring itself whether it is on the good situation to drive, it is also clear that studies should be performed on the way of cars for the emergent rescue of the intelligent vehicles. In this study, writer focus mainly on how to derive a separate system for the car caring teams to arrive as soon as they get the signal sent out by the intelligent driving autos. This simulation measure the time for the rescuing team to arrive, the cost it spent on arriving on the site of car problem happens, also how long the queue is when the rescuing auto is waiting to cross a road. This can be definitely in great use when there are a team of intelligent cars with one car immediately having problems causing its not moving and can be helpful in other situations. Through this way, the interconnection of cars can be a safety net for the drivers encountering difficulties in any time.

Computational Intelligence in a Human Brain Model

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Viorel Gaftea

2016-06-01

Full Text Available This paper focuses on the current trends in brain research domain and the current stage of development of research for software and hardware solutions, communication capabilities between: human beings and machines, new technologies, nano-science and Internet of Things (IoT devices. The proposed model for Human Brain assumes main similitude between human intelligence and the chess game thinking process. Tactical & strategic reasoning and the need to follow the rules of the chess game, all are very similar with the activities of the human brain. The main objective for a living being and the chess game player are the same: securing a position, surviving and eliminating the adversaries. The brain resolves these goals, and more, the being movement, actions and speech are sustained by the vital five senses and equilibrium. The chess game strategy helps us understand the human brain better and easier replicate in the proposed ‘Software and Hardware’ SAH Model.

Effective Stress Management: A Model of Emotional Intelligence, Self-Leadership, and Student Stress Coping

Science.gov (United States)

Houghton, Jeffery D.; Wu, Jinpei; Godwin, Jeffrey L.; Neck, Christopher P.; Manz, Charles C.

2012-01-01

This article develops and presents a model of the relationships among emotional intelligence, self-leadership, and stress coping among management students. In short, the authors' model suggests that effective emotion regulation and self-leadership, as mediated through positive affect and self-efficacy, has the potential to facilitate stress coping…

Computational intelligence in automotive applications

Energy Technology Data Exchange (ETDEWEB)

Prokhorov, Danil (ed.) [Toyota Motor Engineering and Manufacturing (TEMA), Ann Arbor, MI (United States). Toyota Technical Center

2008-07-01

What is computational intelligence (CI)? Traditionally, CI is understood as a collection of methods from the fields of neural networks (NN), fuzzy logic and evolutionary computation. This edited volume is the first of its kind, suitable to automotive researchers, engineers and students. It provides a representative sample of contemporary CI activities in the area of automotive technology. The volume consists of 13 chapters, including but not limited to these topics: vehicle diagnostics and vehicle system safety, control of vehicular systems, quality control of automotive processes, driver state estimation, safety of pedestrians, intelligent vehicles. All chapters contain overviews of state of the art, and several chapters illustrate their methodologies on examples of real-world systems. About the Editor: Danil Prokhorov began his technical career in St. Petersburg, Russia, after graduating with Honors from Saint Petersburg State University of Aerospace Instrumentation in 1992 (MS in Robotics). He worked as a research engineer in St. Petersburg Institute for Informatics and Automation, one of the institutes of the Russian Academy of Sciences. He came to the US in late 1993 for Ph.D. studies. He became involved in automotive research in 1995 when he was a Summer intern at Ford Scientific Research Lab in Dearborn, MI. Upon his graduation from the EE Department of Texas Tech University, Lubbock, in 1997, he joined Ford to pursue application-driven research on neural networks and other machine learning algorithms. While at Ford, he took part in several production-bound projects including neural network based engine misfire detection. Since 2005 he is with Toyota Technical Center, Ann Arbor, MI, overseeing important mid- and long-term research projects in computational intelligence. (orig.)

Business intelligence tools for radiology: creating a prototype model using open-source tools.

Science.gov (United States)

Prevedello, Luciano M; Andriole, Katherine P; Hanson, Richard; Kelly, Pauline; Khorasani, Ramin

2010-04-01

Digital radiology departments could benefit from the ability to integrate and visualize data (e.g. information reflecting complex workflow states) from all of their imaging and information management systems in one composite presentation view. Leveraging data warehousing tools developed in the business world may be one way to achieve this capability. In total, the concept of managing the information available in this data repository is known as Business Intelligence or BI. This paper describes the concepts used in Business Intelligence, their importance to modern Radiology, and the steps used in the creation of a prototype model of a data warehouse for BI using open-source tools.

Approaches for Intelligent Traffic System: A Survey

OpenAIRE

Pratishtha Gupta; G.N Purohit; Amrita Dadhich

2012-01-01

This survey presents various approaches for intelligent traffic systems. The potential research fields in which Intelligent Traffic System emerges as an important application area are highlighted andvarious issues have been identified which need to be handled while developing such a system for an urban area, where an efficient traffic management has become the need of hour.A model is also proposed capable of managing intelligent traffic system using CCTV cameras and WAN. The proposed model wi...

Estimating likelihood of future crashes for crash-prone drivers

OpenAIRE

Subasish Das; Xiaoduan Sun; Fan Wang; Charles Leboeuf

2015-01-01

At-fault crash-prone drivers are usually considered as the high risk group for possible future incidents or crashes. In Louisiana, 34% of crashes are repeatedly committed by the at-fault crash-prone drivers who represent only 5% of the total licensed drivers in the state. This research has conducted an exploratory data analysis based on the driver faultiness and proneness. The objective of this study is to develop a crash prediction model to estimate the likelihood of future crashes for the a...

Advanced approaches to intelligent information and database systems

CERN Document Server

Boonjing, Veera; Chittayasothorn, Suphamit

2014-01-01

This book consists of 35 chapters presenting different theoretical and practical aspects of Intelligent Information and Database Systems. Nowadays both Intelligent and Database Systems are applied in most of the areas of human activities which necessitates further research in these areas. In this book various interesting issues related to the intelligent information models and methods as well as their advanced applications, database systems applications, data models and their analysis, and digital multimedia methods and applications are presented and discussed both from the practical and theoretical points of view. The book is organized in four parts devoted to intelligent systems models and methods, intelligent systems advanced applications, database systems methods and applications, and multimedia systems methods and applications. The book will be interesting for both practitioners and researchers, especially graduate and PhD students of information technology and computer science, as well more experienced ...

An Intelligence Collection Management Model.

Science.gov (United States)

1984-06-01

classification of inteligence collection requirements in terms of. the a-.- metnodo"c, .ev--e in Chaster Five. 116 APPgENDIX A A METHOD OF RANKING...of Artificial Intelligence Tools and Technigues to!TN’X n~l is n rs aa~emfft-.3-ufnyva: ’A TZ Ashby W. Ecss. An Introduction to Cybernetics. New York

A fuzzy TOPSIS model to evaluate the Business Intelligence competencies of Port Community Systems

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Ghazanfari Mehdi

2014-04-01

Full Text Available Evaluation of the Business Intelligence (BI competencies of port community systems before they are bought and deployed is a vital importance for establishment of a decision-support environment for managers. This study proposes a new model which provides a simple approach to the assessment of the BI competencies of port community systems in organization. This approach helps decision-makers to select an enterprise system with appropriate intelligence requirements to support the managers’ decision-making tasks. Thirtyfour criteria for BI specifications are determined from a thorough review of the literature. The proposed model uses the fuzzy TOPSIS technique, which employs fuzzy weights of the criteria and fuzzy judgments of port community systems to compute the evaluation scores and rankings. The application of the model is realized in the evaluation, ranking and selecting of the needed port community systems in a port and maritime organization, in order to validate the proposed model with a real application. With utilizing the proposed model organizations can assess, select, and purchase port community systems which will provide a better decision-support environment for their business systems.

Primary-context model and ontology: a combined approach for pervasive transportation services

OpenAIRE

Lee, Deirdre; Meier, Rene

2007-01-01

peer-reviewed Advanced pervasive transportation services aim to improve the safety and efficiency of public and private transportation facilities, while reducing operating costs and improving the travel experience for drivers, passengers and other travellers. In order to achieve these goals, such services require access to context information from a myriad of distributed, heterogeneous Intelligent Transportation Systems. A context management scheme that models information in a standa...

Primary-Context Model and Ontology: A Combined Approach for Pervasive Transportation Services

OpenAIRE

MEIER, RENE

2007-01-01

PUBLISHED Advanced pervasive transportation services aim to improve the safety and efficiency of public and private transportation facilities, while reducing operating costs and improving the travel experience for drivers, passengers and other travellers. In order to achieve these goals, such services require access to context information from a myriad of distributed, heterogeneous Intelligent Transportation Systems. A context management scheme that models information in a standard fashion...

Artificial Intelligence in Civil Engineering

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Pengzhen Lu

2012-01-01

Full Text Available Artificial intelligence is a branch of computer science, involved in the research, design, and application of intelligent computer. Traditional methods for modeling and optimizing complex structure systems require huge amounts of computing resources, and artificial-intelligence-based solutions can often provide valuable alternatives for efficiently solving problems in the civil engineering. This paper summarizes recently developed methods and theories in the developing direction for applications of artificial intelligence in civil engineering, including evolutionary computation, neural networks, fuzzy systems, expert system, reasoning, classification, and learning, as well as others like chaos theory, cuckoo search, firefly algorithm, knowledge-based engineering, and simulated annealing. The main research trends are also pointed out in the end. The paper provides an overview of the advances of artificial intelligence applied in civil engineering.

Assessing the utility of TAM, TPB, and UTAUT for advanced driver assistance systems.

Science.gov (United States)

Rahman, Md Mahmudur; Lesch, Mary F; Horrey, William J; Strawderman, Lesley

2017-11-01

Advanced Driver Assistance Systems (ADAS) are intended to enhance driver performance and improve transportation safety. The potential benefits of these technologies, such as reduction in number of crashes, enhancing driver comfort or convenience, decreasing environmental impact, etc., have been acknowledged by transportation safety researchers and federal transportation agencies. Although these systems afford safety advantages, they may also challenge the traditional role of drivers in operating vehicles. Driver acceptance, therefore, is essential for the implementation of these systems into the transportation system. Recognizing the need for research into the factors affecting driver acceptance, this study assessed the utility of the Technology Acceptance Model (TAM), the Theory of Planned Behavior (TPB), and the Unified Theory of Acceptance and Use of Technology (UTAUT) for modelling driver acceptance in terms of Behavioral Intention to use an ADAS. Each of these models propose a set of factors that influence acceptance of a technology. Data collection was done using two approaches: a driving simulator approach and an online survey approach. In both approaches, participants interacted with either a fatigue monitoring system or an adaptive cruise control system combined with a lane-keeping system. Based on their experience, participants responded to several survey questions to indicate their attitude toward using the ADAS and their perception of its usefulness, usability, etc. A sample of 430 surveys were collected for this study. Results found that all the models (TAM, TPB, and UTAUT) can explain driver acceptance with their proposed sets of factors, each explaining 71% or more of the variability in Behavioral Intention. Among the models, TAM was found to perform the best in modelling driver acceptance followed by TPB. The findings of this study confirm that these models can be applied to ADAS technologies and that they provide a basis for understanding driver

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

Multi-scale Drivers of Variations in Atmospheric Evaporative Demand Based on Observations and Physically-based Modeling

Science.gov (United States)

Peng, L.; Sheffield, J.; Li, D.

2015-12-01

Evapotranspiration (ET) is a key link between the availability of water resources and climate change and climate variability. Variability of ET has important environmental and socioeconomic implications for managing hydrological hazards, food and energy production. Although there have been many observational and modeling studies of ET, how ET has varied and the drivers of the variations at different temporal scales remain elusive. Much of the uncertainty comes from the atmospheric evaporative demand (AED), which is the combined effect of radiative and aerodynamic controls. The inconsistencies among modeled AED estimates and the limited observational data may originate from multiple sources including the limited time span and uncertainties in the data. To fully investigate and untangle the intertwined drivers of AED, we present a spectrum analysis to identify key controls of AED across multiple temporal scales. We use long-term records of observed pan evaporation for 1961-2006 from 317 weather stations across China and physically-based model estimates of potential evapotranspiration (PET). The model estimates are based on surface meteorology and radiation derived from reanalysis, satellite retrievals and station data. Our analyses show that temperature plays a dominant role in regulating variability of AED at the inter-annual scale. At the monthly and seasonal scales, the primary control of AED shifts from radiation in humid regions to humidity in dry regions. Unlike many studies focusing on the spatial pattern of ET drivers based on a traditional supply and demand framework, this study underlines the importance of temporal scales when discussing controls of ET variations.

ALGORITHMS FOR TRAFFIC MANAGEMENT IN THE INTELLIGENT TRANSPORT SYSTEMS

Directory of Open Access Journals (Sweden)

Andrey Borisovich Nikolaev

2017-09-01

Full Text Available Traffic jams interfere with the drivers and cost billions of dollars per year and lead to a substantial increase in fuel consumption. In order to avoid such problems the paper describes the algorithms for traffic management in intelligent transportation system, which collects traffic information in real time and is able to detect and manage congestion on the basis of this information. The results show that the proposed algorithms reduce the average travel time, emissions and fuel consumption. In particular, travel time has decreased by about 23%, the average fuel consumption of 9%, and the average emission of 10%.

Narrative theories as computational models: reader-oriented theory and artificial intelligence

Energy Technology Data Exchange (ETDEWEB)

Galloway, P.

1983-12-01

In view of the rapid development of reader-oriented theory and its interest in dynamic models of narrative, the author speculates in a serious way about what such models might look like in computational terms. Researchers in artificial intelligence (AI) have already begun to develop models of story understanding as the emphasis in ai research has shifted toward natural language understanding and as ai has allied itself with cognitive psychology and linguistics to become cognitive science. Research in ai and in narrative theory share many common interests and problems and both studies might benefit from an exchange of ideas. 11 references.

A new hybrid model optimized by an intelligent optimization algorithm for wind speed forecasting

International Nuclear Information System (INIS)

Su, Zhongyue; Wang, Jianzhou; Lu, Haiyan; Zhao, Ge

2014-01-01

Highlights: • A new hybrid model is developed for wind speed forecasting. • The model is based on the Kalman filter and the ARIMA. • An intelligent optimization method is employed in the hybrid model. • The new hybrid model has good performance in western China. - Abstract: Forecasting the wind speed is indispensable in wind-related engineering studies and is important in the management of wind farms. As a technique essential for the future of clean energy systems, reducing the forecasting errors related to wind speed has always been an important research subject. In this paper, an optimized hybrid method based on the Autoregressive Integrated Moving Average (ARIMA) and Kalman filter is proposed to forecast the daily mean wind speed in western China. This approach employs Particle Swarm Optimization (PSO) as an intelligent optimization algorithm to optimize the parameters of the ARIMA model, which develops a hybrid model that is best adapted to the data set, increasing the fitting accuracy and avoiding over-fitting. The proposed method is subsequently examined on the wind farms of western China, where the proposed hybrid model is shown to perform effectively and steadily

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...

Cooperation and the evolution of intelligence.

Science.gov (United States)

McNally, Luke; Brown, Sam P; Jackson, Andrew L

2012-08-07

The high levels of intelligence seen in humans, other primates, certain cetaceans and birds remain a major puzzle for evolutionary biologists, anthropologists and psychologists. It has long been held that social interactions provide the selection pressures necessary for the evolution of advanced cognitive abilities (the 'social intelligence hypothesis'), and in recent years decision-making in the context of cooperative social interactions has been conjectured to be of particular importance. Here we use an artificial neural network model to show that selection for efficient decision-making in cooperative dilemmas can give rise to selection pressures for greater cognitive abilities, and that intelligent strategies can themselves select for greater intelligence, leading to a Machiavellian arms race. Our results provide mechanistic support for the social intelligence hypothesis, highlight the potential importance of cooperative behaviour in the evolution of intelligence and may help us to explain the distribution of cooperation with intelligence across taxa.

Recent Advances on Hybrid Intelligent Systems

CERN Document Server

Melin, Patricia; Kacprzyk, Janusz

2013-01-01

This book presents recent advances on hybrid intelligent systems using soft computing techniques for intelligent control and robotics, pattern recognition, time series prediction and optimization of complex problems. Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be used to produce powerful hybrid intelligent systems. The book is organized in five main parts, which contain groups of papers around a similar subject. The first part consists of papers with the main theme of hybrid intelligent systems for control and robotics, which are basically state of the art papers that propose new models and concepts, which can be the basis for achieving intelligent control and mobile robotics. The second part contains papers with the main theme of hybrid intelligent systems for pattern recognition and time series prediction, which are basically papers using nature-inspired techniques, like evolutionary algo...

Trait Emotional Intelligence and Personality

OpenAIRE

Siegling, Alexander B.; Furnham, Adrian; Petrides, K. V.

2015-01-01

This study investigated if the linkages between trait emotional intelligence (trait EI) and the Five-Factor Model of personality were invariant between men and women. Five English-speaking samples (N = 307-685) of mostly undergraduate students each completed a different measure of the Big Five personality traits and either the full form or short form of the Trait Emotional Intelligence Questionnaire (TEIQue). Across samples, models predicting global TEIQue scores from the Big Five were invari...

Examining the nonparametric effect of drivers' age in rear-end accidents through an additive logistic regression model.

Science.gov (United States)

Ma, Lu; Yan, Xuedong

2014-06-01

This study seeks to inspect the nonparametric characteristics connecting the age of the driver to the relative risk of being an at-fault vehicle, in order to discover a more precise and smooth pattern of age impact, which has commonly been neglected in past studies. Records of drivers in two-vehicle rear-end collisions are selected from the general estimates system (GES) 2011 dataset. These extracted observations in fact constitute inherently matched driver pairs under certain matching variables including weather conditions, pavement conditions and road geometry design characteristics that are shared by pairs of drivers in rear-end accidents. The introduced data structure is able to guarantee that the variance of the response variable will not depend on the matching variables and hence provides a high power of statistical modeling. The estimation results exhibit a smooth cubic spline function for examining the nonlinear relationship between the age of the driver and the log odds of being at fault in a rear-end accident. The results are presented with respect to the main effect of age, the interaction effect between age and sex, and the effects of age under different scenarios of pre-crash actions by the leading vehicle. Compared to the conventional specification in which age is categorized into several predefined groups, the proposed method is more flexible and able to produce quantitatively explicit results. First, it confirms the U-shaped pattern of the age effect, and further shows that the risks of young and old drivers change rapidly with age. Second, the interaction effects between age and sex show that female and male drivers behave differently in rear-end accidents. Third, it is found that the pattern of age impact varies according to the type of pre-crash actions exhibited by the leading vehicle. Copyright © 2014 Elsevier Ltd. All rights reserved.

International Conference on Computational Intelligence 2015

CERN Document Server

Saha, Sujan

2017-01-01

This volume comprises the proceedings of the International Conference on Computational Intelligence 2015 (ICCI15). This book aims to bring together work from leading academicians, scientists, researchers and research scholars from across the globe on all aspects of computational intelligence. The work is composed mainly of original and unpublished results of conceptual, constructive, empirical, experimental, or theoretical work in all areas of computational intelligence. Specifically, the major topics covered include classical computational intelligence models and artificial intelligence, neural networks and deep learning, evolutionary swarm and particle algorithms, hybrid systems optimization, constraint programming, human-machine interaction, computational intelligence for the web analytics, robotics, computational neurosciences, neurodynamics, bioinspired and biomorphic algorithms, cross disciplinary topics and applications. The contents of this volume will be of use to researchers and professionals alike....

The tyre - source of information for driver assistance; Der Reifen - Informationsquelle zur Fahrerassistenz

Energy Technology Data Exchange (ETDEWEB)

Holtschulze, J.; Goertz, H. [Inst. fuer Kraftfahrwesen, RWTH Aachen (Germany); Wunderlich, H.; Maeckle, G. [DaimlerChrysler AG, Stuttgart (Germany); Varpula, T. [VTT Automation, Espoo (Finland); Mancosu, F. [Pirelli S.p.A., Mailand (Italy)

2004-07-01

apollo is a research project funded by the European Commission under the 5th Framework Programme ''information society technologies'' (IST). The objective is to develop a prototype of an intelligent tyre. The overall goals are to increase traffic safety and enable improvements for vehicle dynamics control, advanced driver assistance systems and services for external users by providing data on the tyre and the local tyre-road contact. The basics of the tyre deformation behaviour in operation situations show possibilities which signals can be measured and how to derive a set of data for the applications. Free rolling, cornering and braking/driving have to be distinguished. Optimal sensor locations are studied and determined in order to measure deformation characteristics by different quantities such as accelerations. Acquired signals are processed using models of tyre and vehicle behaviour before they are provided to application systems. To transmit the sensor data to the vehicle controller a wireless communication and power supply system is used. (orig.)

Intelligent Torque Vectoring Approach for Electric Vehicles with Per-Wheel Motors

Directory of Open Access Journals (Sweden)

Alberto Parra

2018-01-01

Full Text Available Transport electrification is currently a priority for authorities, manufacturers, and research centers around the world. The development of electric vehicles and the improvement of their functionalities are key elements in this strategy. As a result, there is a need for further research in emission reduction, efficiency improvement, or dynamic handling approaches. In order to achieve these objectives, the development of suitable Advanced Driver-Assistance Systems (ADAS is required. Although traditional control techniques have been widely used for ADAS implementation, the complexity of electric multimotor powertrains makes intelligent control approaches appropriate for these cases. In this work, a novel intelligent Torque Vectoring (TV system, composed of a neuro-fuzzy vertical tire forces estimator and a fuzzy yaw moment controller, is proposed, which allows enhancing the dynamic behaviour of electric multimotor vehicles. The proposed approach is compared with traditional strategies using the high fidelity vehicle dynamics simulator Dynacar. Results show that the proposed intelligent Torque Vectoring system is able to increase the efficiency of the vehicle by 10%, thanks to the optimal torque distribution and the use of a neuro-fuzzy vertical tire forces estimator which provides 3 times more accurate estimations than analytical approaches.

Driver behavior in traffic.

Science.gov (United States)

2012-02-01

Existing traffic analysis and management tools do not model the ability of drivers to recognize their environment and respond to it with behaviors that vary according to the encountered driving situation. The small body of literature on characterizin...

Leveraging accelerated testing of LED drivers to model the reliability of two-stage and multi-channel drivers

Energy Technology Data Exchange (ETDEWEB)

Davis, Lynn; Perkins, Curtis; Smith, Aaron; Clark, Terry; Mills, Karmann

2017-05-30

The next wave of LED lighting technology is likely to be tunable white lighting (TWL) devices which can adjust the colour of the emitted light between warm white (~ 2700 K) and cool white (~ 6500 K). This type of lighting system uses LED assemblies of two or more colours each controlled by separate driver channels that independently adjust the current levels to achieve the desired lighting colour. Drivers used in TWL devices are inherently more complex than those found in simple SSL devices, due to the number of electrical components in the driver required to achieve this level of control. The reliability of such lighting systems can only be studied using accelerated stress tests (AST) that accelerate the aging process to time frames that can be accommodated in laboratory testing. This paper describes AST methods and findings developed from AST data that provide insights into the lifetime of the main components of one-channel and multi-channel LED devices. The use of AST protocols to confirm product reliability is necessary to ensure that the technology can meet the performance and lifetime requirements of the intended application.

Locomotor diseases among male long-haul truck drivers and other professional drivers

DEFF Research Database (Denmark)

Jensen, Anker; Kaerlev, Linda; Tüchsen, Finn

2007-01-01

-249) and for other truck drivers (SHR: 130, 95% CI: 108-156) compared to bus drivers (SHR: 110, 95% CI: 79-149). All drivers had high SHR for lesions of the ulnar nerve (SHR: 159, 95% CI: 119-207), especially bus drivers (SHR: 197, 95% CI: 116-311). Long-haul truck drivers had high SHRs for synovitis and bursitis...

Goleman-Boyatzis Model of Emotional Intelligence for Dealing with Problems in Project Management

Directory of Open Access Journals (Sweden)

Peter Vincent Livesey

2017-03-01

Full Text Available As projects grow in size and complexity the sizes of teams needed to manage them also increases. This places greater emphasis on the need for the project manager to develop people management skills, commonly called soft skills, of which emotional intelligence (EI has been recognised as an important component. The objective of this research was to investigate the relevance of the Goleman-Boyatzis model of EI in dealing with the problems in large projects identified via a literature review. To achieve this end, a Delphi study using project managers who had been involved in the management of projects in excess of $500 million was used. The responses from the Delphi panel were analysed and the results showed that the competencies contained in the Goleman-Boyatzis model had a relevance of 95% or greater to the problems presented to the panel. A ranking of the various competencies contained within the model was also developed, some competencies being found to be more important than others. By confirming the importance of emotional intelligence, as described by the model, this research adds to the understanding of the necessary skills needed by a project manager to successfully manage large projects.

socio-ec(h)o: Ambient Intelligence and Gameplay

OpenAIRE

Wakkary, Ron

2005-01-01

The socio-ec(h)o project aims to research a generalized ambient intelligent software platform and design models for responsive environments based on the concept of ambient intelligent "ecologies" and group gameplay. The benefits of the research include a software-architecture, ambient intelligence inference engine, and interaction design models for gameplay and responsive environments. The paper will discuss the results of our prototypes for games in responsive environments. These prototypes ...

Design of an Intelligent Support Agent Model for People with a Cognitive Vulnerability

NARCIS (Netherlands)

Aziz, A.A.; Klein, M.C.A.; Zhang, B.; Wang, Y.; Kinser, W.

2010-01-01

This paper presents the design of an intelligent agent application aimed at supporting people with a cognitive vulnerability to prevent the onset of a depression. For this, a computational model of the cognitive processes around depression is used. The agent application uses the principles of

The relationship between security of supply and its drivers

International Nuclear Information System (INIS)

2007-10-01

The relationship between security of supply of natural gas in the UK and three possible drivers were considered. The drivers discussed are (1) supply margin, (2) reliability of supply and (3) diversity of supply. The department for Business Enterprise and Regulatory Reform's gas security of supply model may be applied to estimate 'expected energy unserved (EEU)' according to a range of conditions of supply and demand. Supply margin and mix can be varied in the model, as can the reliability of supply sources. The paper describes work exploring the impact on the EEU of changes in these three drivers

The Application of Collaborative Business Intelligence Technology in the Hospital SPD Logistics Management Model

Science.gov (United States)

LIU, Tongzhu; SHEN, Aizong; HU, Xiaojian; TONG, Guixian; GU, Wei

2017-01-01

Background: We aimed to apply collaborative business intelligence (BI) system to hospital supply, processing and distribution (SPD) logistics management model. Methods: We searched Engineering Village database, China National Knowledge Infrastructure (CNKI) and Google for articles (Published from 2011 to 2016), books, Web pages, etc., to understand SPD and BI related theories and recent research status. For the application of collaborative BI technology in the hospital SPD logistics management model, we realized this by leveraging data mining techniques to discover knowledge from complex data and collaborative techniques to improve the theories of business process. Results: For the application of BI system, we: (i) proposed a layered structure of collaborative BI system for intelligent management in hospital logistics; (ii) built data warehouse for the collaborative BI system; (iii) improved data mining techniques such as supporting vector machines (SVM) and swarm intelligence firefly algorithm to solve key problems in hospital logistics collaborative BI system; (iv) researched the collaborative techniques oriented to data and business process optimization to improve the business processes of hospital logistics management. Conclusion: Proper combination of SPD model and BI system will improve the management of logistics in the hospitals. The successful implementation of the study requires: (i) to innovate and improve the traditional SPD model and make appropriate implement plans and schedules for the application of BI system according to the actual situations of hospitals; (ii) the collaborative participation of internal departments in hospital including the department of information, logistics, nursing, medical and financial; (iii) timely response of external suppliers. PMID:28828316

Convergent Innovation in Food through Big Data and Artificial Intelligence for Societal-Scale Inclusive Growth

Directory of Open Access Journals (Sweden)

Laurette Dubé

2018-02-01

Full Text Available Inclusive innovation has not yet reached societal scale due to a well-entrenched divide between wealth creation and social equity. Taking food as the initial test bed, we have proposed the convergent innovation model to address such challenges still facing 21st century society by bridging sectors and disciplines around an integrated goal on both sides of the social-economic divide for innovations that target wealth creation with an upfront consideration of its externalities. The convergent innovation model is empowered by two key enablers that integrate an advanced digital infrastructure with leading scientific knowledge on the drivers of human behaviour in varying contexts. This article discusses the structure, methods, and development of an artificial intelligence platform to support convergent innovation. Insights are gathered on consumer sentiment and behavioural drivers through the analysis of user-generated content on social media platforms. Empirical results show that user discussions related to marketing, consequences, and occasions are positive. Further regression modelling finds that economic consequences are a strong predictor of consumer global sentiment, but are also sensitive to both the actual price and economic awareness. This finding has important implications for inclusive growth and further emphasizes the need for affordable and accessible foods, as well as for consumer education. Challenges and opportunities inspired by the research results are discussed to inform the design, marketing, and delivery of convergent innovation products and services, while also contributing to dimensions of inclusion and economic performance for equitable health and wealth.

Prediction of pork loin quality using online computer vision system and artificial intelligence model.

Science.gov (United States)

Sun, Xin; Young, Jennifer; Liu, Jeng-Hung; Newman, David

2018-06-01

The objective of this project was to develop a computer vision system (CVS) for objective measurement of pork loin under industry speed requirement. Color images of pork loin samples were acquired using a CVS. Subjective color and marbling scores were determined according to the National Pork Board standards by a trained evaluator. Instrument color measurement and crude fat percentage were used as control measurements. Image features (18 color features; 1 marbling feature; 88 texture features) were extracted from whole pork loin color images. Artificial intelligence prediction model (support vector machine) was established for pork color and marbling quality grades. The results showed that CVS with support vector machine modeling reached the highest prediction accuracy of 92.5% for measured pork color score and 75.0% for measured pork marbling score. This research shows that the proposed artificial intelligence prediction model with CVS can provide an effective tool for predicting color and marbling in the pork industry at online speeds. Copyright © 2018 Elsevier Ltd. All rights reserved.

The role of driver nodes in managing epileptic seizures: Application of Kuramoto model.

Science.gov (United States)

Mohseni, Ali; Gharibzadeh, Shahriar; Bakouie, Fatemeh

2017-04-21

Synchronization is an important global phenomenon which could be found in a wide range of complex systems such as brain or electronic devices. However, in some circumstances the synchronized states are not desirable for the system and should be suppressed. For example, excessively synchronized activities in the brain network could be the root of neuronal disorders like epileptic seizures. According to the controllability theory of the complex networks, a minimum set of driver nodes has the ability to control the entire system. In this study, we examine the role of driver nodes in suppressing the excessive synchronization in a generalized Kuramoto model, which consists of two types of oscillators: contrarian and regular ones. We used two different structural topologies: Barabási-Albert scale-free (BASF) network and Caenorhabditis elegans (C.elegans) neuronal network. Our results show that contrarian driver nodes have the sufficient ability to break the synchronized level of the systems. In this case, the system coherency level is not fully suppressed that is avoiding dysfunctions of normal brain functions which require the neuronal synchronized activities. Moreover, in this case, the oscillators grouped in two distinct synchronized clusters that could be an indication of chaotic behavior of the system known as resting-state activity of the brain. Copyright © 2017 Elsevier Ltd. All rights reserved.

Stupid Tutoring Systems, Intelligent Humans

Science.gov (United States)

Baker, Ryan S.

2016-01-01

The initial vision for intelligent tutoring systems involved powerful, multi-faceted systems that would leverage rich models of students and pedagogies to create complex learning interactions. But the intelligent tutoring systems used at scale today are much simpler. In this article, I present hypotheses on the factors underlying this development,…

Artificial Intelligence and Science Education.

Science.gov (United States)

Good, Ron

1987-01-01

Defines artificial intelligence (AI) in relation to intelligent computer-assisted instruction (ICAI) and science education. Provides a brief background of AI work, examples of expert systems, examples of ICAI work, and addresses problems facing AI workers that have implications for science education. Proposes a revised model of the Karplus/Renner…

A Framework for Knowledge Management and Automated Reasoning Applied on Intelligent Transport Systems

OpenAIRE

Feljan, Aneta Vulgarakis; Karapantelakis, Athanasios; Mokrushin, Leonid; Liang, Hongxin; Inam, Rafia; Fersman, Elena; Azevedo, Carlos R. B.; Raizer, Klaus; Souza, Ricardo S.

2017-01-01

Cyber-Physical Systems in general, and Intelligent Transport Systems (ITS) in particular use heterogeneous data sources combined with problem solving expertise in order to make critical decisions that may lead to some form of actions e.g., driver notifications, change of traffic light signals and braking to prevent an accident. Currently, a major part of the decision process is done by human domain experts, which is time-consuming, tedious and error-prone. Additionally, due to the intrinsic n...

Recent Advances in Intelligent Engineering Systems

CERN Document Server

Klempous, Ryszard; Araujo, Carmen

2012-01-01

This volume is a collection of 19 chapters on intelligent engineering systems written by respectable experts of the fields. The book consists of three parts. The first part is devoted to the foundational aspects of computational intelligence. It consists of 8 chapters that include studies in genetic algorithms, fuzzy logic connectives, enhanced intelligence in product models, nature-inspired optimization technologies, particle swarm optimization, evolution algorithms, model complexity of neural networks, and fitness landscape analysis. The second part contains contributions to intelligent computation in networks, presented in 5 chapters. The covered subjects include the application of self-organizing maps for early detection of denial of service attacks, combating security threats via immunity and adaptability in cognitive radio networks, novel modifications in WSN network design for improved SNR and reliability, a conceptual framework for the design of audio based cognitive infocommunication channels, and a ...

Prediction of vehicle crashes by drivers' characteristics and past traffic violations in Korea using a zero-inflated negative binomial model.

Science.gov (United States)

Kim, Dae-Hwan; Ramjan, Lucie M; Mak, Kwok-Kei

2016-01-01

Traffic safety is a significant public health challenge, and vehicle crashes account for the majority of injuries. This study aims to identify whether drivers' characteristics and past traffic violations may predict vehicle crashes in Korea. A total of 500,000 drivers were randomly selected from the 11.6 million driver records of the Ministry of Land, Transport and Maritime Affairs in Korea. Records of traffic crashes were obtained from the archives of the Korea Insurance Development Institute. After matching the past violation history for the period 2004-2005 with the number of crashes in year 2006, a total of 488,139 observations were used for the analysis. Zero-inflated negative binomial model was used to determine the incident risk ratio (IRR) of vehicle crashes by past violations of individual drivers. The included covariates were driver's age, gender, district of residence, vehicle choice, and driving experience. Drivers violating (1) a hit-and-run or drunk driving regulation at least once and (2) a signal, central line, or speed regulation more than once had a higher risk of a vehicle crash with respective IRRs of 1.06 and 1.15. Furthermore, female gender, a younger age, fewer years of driving experience, and middle-sized vehicles were all significantly associated with a higher likelihood of vehicle crashes. Drivers' demographic characteristics and past traffic violations could predict vehicle crashes in Korea. Greater resources should be assigned to the provision of traffic safety education programs for the high-risk driver groups.