Search results for: Traffic Classification.

Authors: M. Ahmadi Baseri, R. Mokhtari Malekabadi, A. Gandomkar

Abstract:

Cities expansion, urban travels increase, the technology development, the automobile price cheapen, and the families' income ascending cause the considerable increase in automobile numbers of the city. This fact has led to the traffic creation and the automobile parking site shortage in the city. Also in Esfahan metropolis, the parking lots shortage has been the great problem of this town; in addition, in designing and constructing of the parking sites the traditional methods are utilized which do not have a reasonable and optimized usage of the valuable urban lands. In this article, by introducing the prefabricate mechanized parking system which is inexpensive, simple and quick, and occupies very small space, therefore provides the high content of parking site for the cities, we can eliminate the parking space shortage difficulty of the cities. The achieved results of this research represent that an optimized utilization of the existent urban spaces for parking site construction has not been accomplished. By employing the new parking site technologies such as mechanization categorized parking sites and the capacity prefabricate mechanized of each parking space have become 8 multiples; in this case, the valuable urban lands can be used in an optimized way.

Keywords: Public parking sites, New parking sites technologies, Prefabricate mechanized parking site, Isfahan City.

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Authors: P. Phokharatkul, K. Sankhuangaw, S. Somkuarnpanit, S. Phaiboon, C. Kimpan

Abstract:

Much research into handwritten Thai character recognition have been proposed, such as comparing heads of characters, Fuzzy logic and structure trees, etc. This paper presents a system of handwritten Thai character recognition, which is based on the Ant-minor algorithm (data mining based on Ant colony optimization). Zoning is initially used to determine each character. Then three distinct features (also called attributes) of each character in each zone are extracted. The attributes are Head zone, End point, and Feature code. All attributes are used for construct the classification rules by an Ant-miner algorithm in order to classify 112 Thai characters. For this experiment, the Ant-miner algorithm is adapted, with a small change to increase the recognition rate. The result of this experiment is a 97% recognition rate of the training set (11200 characters) and 82.7% recognition rate of unseen data test (22400 characters).

Keywords: Hand written, Thai character recognition, Ant-mineralgorithm, distinct feature.

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Authors: S. Onoda, S. Yoshihara, B. J. MacDonald, Y. Okude

Abstract:

Aluminum alloy sheets have several advantages such as the lightweight, high-specific strength and recycling efficiency. Therefore, aluminum alloy sheets in sheet forming have been used in various areas as automotive components and so forth. During the process of sheet forming, wrinkling which is caused by compression stress might occur and the formability of sheets was affected by occurrence of wrinkling. A few studies of uniaxial compressive test by using square tubes, pipes and sheets were carried out to clarify the each wrinkling behavior. However, on uniaxial compressive test, deformation behavior of the sheets hasn-t be cleared. Then, it is necessary to clarify the relationship between the buckling behavior and the forming conditions. In this study, the effect of dimension of the sheet in the buckling behavior on compression test of aluminum alloy sheet was cleared by experiment and FEA. As the results, the buckling deformation was classified by three modes in terms of the distribution of equivalent plastic strain.

Keywords: Sheet forming, Compression test, Aluminum alloy sheet, Buckling behavior

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Authors: Stefanie Rukavina, Sascha Gruss, Steffen Walter, Holger Hoffmann, Harald C. Traue

Abstract:

OPEN_EmoRec_II is an open multimodal corpus with experimentally induced emotions. In the first half of the experiment, emotions were induced with standardized picture material and in the second half during a human-computer interaction (HCI), realized with a wizard-of-oz design. The induced emotions are based on the dimensional theory of emotions (valence, arousal and dominance). These emotional sequences - recorded with multimodal data (facial reactions, speech, audio and physiological reactions) during a naturalistic-like HCI-environment one can improve classification methods on a multimodal level. This database is the result of an HCI-experiment, for which 30 subjects in total agreed to a publication of their data including the video material for research purposes*. The now available open corpus contains sensory signal of: video, audio, physiology (SCL, respiration, BVP, EMG Corrugator supercilii, EMG Zygomaticus Major) and facial reactions annotations.

Keywords: Open multimodal emotion corpus, annotated labels.

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Authors: Stefanie Rukavina, Sascha Gruss, Steffen Walter, Holger Hoffmann, Harald C. Traue

Abstract:

OPEN_EmoRec_II is an open multimodal corpus with experimentally induced emotions. In the first half of the experiment, emotions were induced with standardized picture material and in the second half during a human-computer interaction (HCI), realized with a wizard-of-oz design. The induced emotions are based on the dimensional theory of emotions (valence, arousal and dominance). These emotional sequences - recorded with multimodal data (facial reactions, speech, audio and physiological reactions) during a naturalistic-like HCI-environment one can improve classification methods on a multimodal level. This database is the result of an HCI-experiment, for which 30 subjects in total agreed to a publication of their data including the video material for research purposes*. The now available open corpus contains sensory signal of: video, audio, physiology (SCL, respiration, BVP, EMG Corrugator supercilii, EMG Zygomaticus Major) and facial reactions annotations.

Keywords: Open multimodal emotion corpus, annotated labels.

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Authors: V. Gomathi, Dr. K. Ramar, A. Santhiyaku Jeevakumar

Abstract:

Facial expression analysis plays a significant role for human computer interaction. Automatic analysis of human facial expression is still a challenging problem with many applications. In this paper, we propose neuro-fuzzy based automatic facial expression recognition system to recognize the human facial expressions like happy, fear, sad, angry, disgust and surprise. Initially facial image is segmented into three regions from which the uniform Local Binary Pattern (LBP) texture features distributions are extracted and represented as a histogram descriptor. The facial expressions are recognized using Multiple Adaptive Neuro Fuzzy Inference System (MANFIS). The proposed system designed and tested with JAFFE face database. The proposed model reports 94.29% of classification accuracy.

Keywords: Adaptive neuro-fuzzy inference system, Facialexpression, Local binary pattern, Uniform Histogram

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Authors: M. Debyeche, J.P Haton, A. Houacine

Abstract:

The paper presents a complete discrete statistical framework, based on a novel vector quantization (VQ) front-end process. This new VQ approach performs an optimal distribution of VQ codebook components on HMM states. This technique that we named the distributed vector quantization (DVQ) of hidden Markov models, succeeds in unifying acoustic micro-structure and phonetic macro-structure, when the estimation of HMM parameters is performed. The DVQ technique is implemented through two variants. The first variant uses the K-means algorithm (K-means- DVQ) to optimize the VQ, while the second variant exploits the benefits of the classification behavior of neural networks (NN-DVQ) for the same purpose. The proposed variants are compared with the HMM-based baseline system by experiments of specific Arabic consonants recognition. The results show that the distributed vector quantization technique increase the performance of the discrete HMM system.

Keywords: Hidden Markov Model, Vector Quantization, Neural Network, Speech Recognition, Arabic Language

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Authors: Yao-Tien Wang, Hsiang-Fu Yu, Dung Chen Chiou

Abstract:

In wireless and mobile communications, this progress provides opportunities for introducing new standards and improving existing services. Supporting multimedia traffic with wireless networks quality of service (QoS). In this paper, a grey-fuzzy controller for radio resource management (GF-RRM) is presented to maximize the number of the served calls and QoS provision in wireless networks. In a wireless network, the call arrival rate, the call duration and the communication overhead between the base stations and the control center are vague and uncertain. In this paper, we develop a method to predict the cell load and to solve the RRM problem based on the GF-RRM, and support the present facility has been built on the application-level of the wireless networks. The GF-RRM exhibits the better adaptability, fault-tolerant capability and performance than other algorithms. Through simulations, we evaluate the blocking rate, update overhead, and channel acquisition delay time of the proposed method. The results demonstrate our algorithm has the lower blocking rate, less updated overhead, and shorter channel acquisition delay.

Keywords: radio resource management, grey prediction, fuzzylogic control, wireless networks, quality of service.

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Authors: Y. Obikane , M.Kaneko, K.Kakioka, K.Ogura

Abstract:

The fine structure of supercavitation in the wake of a symmetrical cylinder is studied with high-speed video cameras. The flow is observed in a cavitation tunnel at the speed of 8m/sec when the sidewall and the wake are partially filled with the massive cavitation bubbles. The present experiment observed that a two-dimensional ripple wave with a wave length of 0.3mm is propagated in a downstream direction, and then abruptly increases to a thicker three-dimensional layer. IR-photography recorded that the wakes originated from the horseshoe vortexes alongside the cylinder. The wake was developed to inside the dead water zone, which absorbed the bubbly wake propelled from the separated vortices at the center of the cylinder. A remote sensing classification technique (maximum most likelihood) determined that the surface porosity was 0.2, and the mean speed in the mixed wake was 7m/sec. To confirm the existence of two-dimensional wave motions in the interface, the experiments were conducted at a very low frequency, and showed similar gravity waves in both the upper and lower interfaces.

Keywords: Supercavitation, density gradient correlation

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Authors: S. Odeh, E. Abdelghani

Abstract:

Collaborative working environments for distance education can be considered as a more generic form of contemporary remote labs. At present, the majority of existing real laboratories are not constructed to allow the involved participants to collaborate in real time. To make this revolutionary learning environment possible we must allow the different users to carry out an experiment simultaneously. In recent times, multi-user environments are successfully applied in many applications such as air traffic control systems, team-oriented military systems, chat-text tools, multi-player games etc. Thus, understanding the ideas and techniques behind these systems could be of great importance in the contribution of ideas to our e-learning environment for collaborative working. In this investigation, collaborative working environments from theoretical and practical perspectives are considered in order to build an effective collaborative real laboratory, which allows two students or more to conduct remote experiments at the same time as a team. In order to achieve this goal, we have implemented distributed system architecture, enabling students to obtain an automated help by either a human tutor or a rule-based e-tutor.

Keywords: Collaboration environment, e-tutor, multi-user environments, socio-technical system.

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Authors: Wern-Yarng Shieh, Chao Qian, Bingnan Pei

Abstract:

A design of communication area for infrared electronic-toll-collection systems to provide an extended communication interval in the vehicle traveling direction and regular boundary between contiguous traffic lanes is proposed. By utilizing two typical low-cost commercial infrared LEDs with different half-intensity angles Φ1/2 = 22◦ and 10◦, the radiation pattern of the emitter is designed to properly adjust the spatial distribution of the signal power. The aforementioned purpose can be achieved with an LED array in a three-piece structure with appropriate mounting angles. With this emitter, the influence of the mounting parameters, including the mounting height and mounting angles of the on-board unit and road-side unit, on the system performance in terms of the received signal strength and communication area are investigated. The results reveal that, for our emitter proposed in this paper, the ideal ”long-and-narrow” characteristic of the communication area is very little affected by these mounting parameters. An optimum mounting configuration is also suggested.

Keywords: Dedicated short-range communication (DSRC), electronic toll collection (ETC), infrared communication, intelligent transportation system (ITS), multilane free flow.

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Authors: P. Moeinzadeh, A. Hajfathaliha

Abstract:

Many firms implemented various initiatives such as outsourced manufacturing which could make a supply chain (SC) more vulnerable to various types of disruptions. So managing risk has become a critical component of SC management. Different types of SC vulnerability management methodologies have been proposed for managing SC risk, most offer only point-based solutions that deal with a limited set of risks. This research aims to reinforce SC risk management by proposing an integrated approach. SC risks are identified and a risk index classification structure is created. Then we develop a SC risk assessment approach based on the analytic network process (ANP) and the VIKOR methods under the fuzzy environment where the vagueness and subjectivity are handled with linguistic terms parameterized by triangular fuzzy numbers. By using FANP, risks weights are calculated and then inserted to the FVIKOR to rank the SC members and find the most risky partner.

Keywords: Analytic network process (ANP), Fuzzy sets, Supply chain risk management (SCRM), VIšekriterijumsko KOmpromisno Rangiranje (VIKOR)

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Authors: Sandya Mummullage, Prasanna Egodawatta, Ashantha Goonetilleke, Godwin A. Ayoko

Abstract:

Urban road dust comprises of a range of potentially  toxic metal elements and plays a critical role in degrading urban  receiving water quality. Hence, assessing the metal composition and  concentration in urban road dust is a high priority. This study  investigated the variability of metal composition and concentrations  in road dust in 4 different urban land uses in Gold Coast, Australia.  Samples from 16 road sites were collected and tested for selected 12  metal species. The data set was analyzed using both univariate and  multivariate techniques. Outcomes of the data analysis revealed that  the metal concentrations inroad dust differs considerably within and  between different land uses. Iron, aluminum, magnesium and zinc are  the most abundant in urban land uses. It was also noted that metal  species such as titanium, nickel, copper and zinc have the highest  concentrations in industrial land use. The study outcomes revealed  that soil and traffic related sources as key sources of metals deposited  on road surfaces.

 

Keywords: Metals build-up, Pollutant accumulation, Stormwater quality, Urban road dust.

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Authors: Elmi Abu Bakar, Tetsuo Miyake, Zhong Zhang, Takashi Imamura

Abstract:

Knowing the geometrical object pose of products in manufacturing line before robot manipulation is required and less time consuming for overall shape measurement. In order to perform it, the information of shape representation and matching of objects is become required. Objects are compared with its descriptor that conceptually subtracted from each other to form scalar metric. When the metric value is smaller, the object is considered closed to each other. Rotating the object from static pose in some direction introduce the change of value in scalar metric value of boundary information after feature extraction of related object. In this paper, a proposal method for indexing technique for retrieval of 3D geometrical models based on similarity between boundaries shapes in order to measure 3D CAD object pose using object shape feature matching for Computer Aided Testing (CAT) system in production line is proposed. In experimental results shows the effectiveness of proposed method.

Keywords: CAD, rendering, feature extraction, feature classification.

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Authors: Mladen Dragičević, Mirjana Pejić Bach, Vanja Šimičević

Abstract:

The purpose of this paper is to develop models that would enable predicting student success. These models could improve allocation of students among colleges and optimize the newly introduced model of government subsidies for higher education. For the purpose of collecting data, an anonymous survey was carried out in the last year of undergraduate degree student population using random sampling method. Decision trees were created of which two have been chosen that were most successful in predicting student success based on two criteria: Grade Point Average (GPA) and time that a student needs to finish the undergraduate program (time-to-degree). Decision trees have been shown as a good method of classification student success and they could be even more improved by increasing survey sample and developing specialized decision trees for each type of college. These types of methods have a big potential for use in decision support systems.

Keywords: Data mining, knowledge discovery in databases, prediction models, student success.

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Authors: Yao-Hong Tsai

Abstract:

This paper presents a weighted approach to unconstrained iris recognition. In nowadays, commercial systems are usually characterized by strong acquisition constraints based on the subject’s cooperation. However, it is not always achievable for real scenarios in our daily life. Researchers have been focused on reducing these constraints and maintaining the performance of the system by new techniques at the same time. With large variation in the environment, there are two main improvements to develop the proposed iris recognition system. For solving extremely uneven lighting condition, statistic based illumination normalization is first used on eye region to increase the accuracy of iris feature. The detection of the iris image is based on Adaboost algorithm. Secondly, the weighted approach is designed by Gaussian functions according to the distance to the center of the iris. Furthermore, local binary pattern (LBP) histogram is then applied to texture classification with the weight. Experiment showed that the proposed system provided users a more flexible and feasible way to interact with the verification system through iris recognition.

Keywords: Authentication, iris recognition, Adaboost, local binary pattern.

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Authors: A. Nourmohammadzadeh, R. Tavakkoli- Moghaddam

Abstract:

As the air traffic increases at a hub airport, some flights cannot land or depart at their preferred target time. This event happens because the airport runways become occupied to near their capacity. It results in extra costs for both passengers and airlines because of the loss of connecting flights or more waiting, more fuel consumption, rescheduling crew members, etc. Hence, devising an appropriate scheduling method that determines a suitable runway and time for each flight in order to efficiently use the hub capacity and minimize the related costs is of great importance. In this paper, we present a mixed-integer zero-one model for scheduling a set of mixed landing and departing flights (despite of most previous studies considered only landings). According to the fact that the flight cost is strongly affected by the level of airline, we consider different airline categories in our model. This model presents a single objective minimizing the total sum of three terms, namely 1) the weighted deviation from targets, 2) the scheduled time of the last flight (i.e., makespan), and 3) the unbalancing the workload on runways. We solve 10 simulated instances of different sizes up to 30 flights and 4 runways. Optimal solutions are obtained in a reasonable time, which are satisfactory in comparison with the traditional rule, namely First- Come-First-Serve (FCFS) that is far apart from optimality in most cases.

Keywords: Arrival and departure scheduling, Airline level, Mixed-integer model

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Authors: M. Rahmati, S.M. Mirzababaei

Abstract:

With the advance of information technology in the new era the applications of Internet to access data resources has steadily increased and huge amount of data have become accessible in various forms. Obviously, the network providers and agencies, look after to prevent electronic attacks that may be harmful or may be related to terrorist applications. Thus, these have facilitated the authorities to under take a variety of methods to protect the special regions from harmful data. One of the most important approaches is to use firewall in the network facilities. The main objectives of firewalls are to stop the transfer of suspicious packets in several ways. However because of its blind packet stopping, high process power requirements and expensive prices some of the providers are reluctant to use the firewall. In this paper we proposed a method to find a discriminate function to distinguish between usual packets and harmful ones by the statistical processing on the network router logs. By discriminating these data, an administrator may take an approach action against the user. This method is very fast and can be used simply in adjacent with the Internet routers.

Keywords: Data Mining, Firewall, Optimization, Packetclassification, Statistical Pattern Recognition.

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Authors: Yao-Hong Tsai

Abstract:

This paper presents an efficient fusion algorithm for iris images to generate stable feature for recognition in unconstrained environment. Recently, iris recognition systems are focused on real scenarios in our daily life without the subject’s cooperation. Under large variation in the environment, the objective of this paper is to combine information from multiple images of the same iris. The result of image fusion is a new image which is more stable for further iris recognition than each original noise iris image. A wavelet-based approach for multi-resolution image fusion is applied in the fusion process. The detection of the iris image is based on Adaboost algorithm and then local binary pattern (LBP) histogram is then applied to texture classification with the weighting scheme. Experiment showed that the generated features from the proposed fusion algorithm can improve the performance for verification system through iris recognition.

Keywords: Image fusion, iris recognition, local binary pattern, wavelet.

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Authors: Maamar Ali Saud Al Tobi, Geraint Bevan, K. P. Ramachandran, Peter Wallace, David Harrison

Abstract:

Centrifugal pumps are complex machines which can experience different types of fault. Condition monitoring can be used in centrifugal pump fault detection through vibration analysis for mechanical and hydraulic forces. Vibration analysis methods have the potential to be combined with artificial intelligence systems where an automatic diagnostic method can be approached. An automatic fault diagnosis approach could be a good option to minimize human error and to provide a precise machine fault classification. This work aims to introduce an approach to centrifugal pump fault diagnosis based on artificial intelligence and genetic algorithm systems. An overview of the future works, research methodology and proposed experimental setup is presented and discussed. The expected results and outcomes based on the experimental work are illustrated.

Keywords: Centrifugal pump setup, vibration analysis, artificial intelligence, genetic algorithm.

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Authors: D. Latha, V. Sunitha, Samson Mathew

Abstract:

In India, most of the pavement is laid by bituminous road and the consumption of binder is high for pavement construction and also modified binders are used to satisfy any specific pavement requirement. Since the binders are visco-elastic material which is having the mechanical properties of binder transition from viscoelastic solid to visco-elastic fluid. In this paper, two different protocols were used to measure the viscosity property of binder using a Brookfield Viscometer and there is a need to find the appropriate mixing and compaction temperatures of various types of binders which can result in complete aggregate coating and adequate field density of HMA mixtures. The aim of this work is to find the transition temperature from Non-Newtonian behavior to Newtonian behavior of the binder by adopting a steady shear protocol and the shear rate ramp protocol. The transition from non-Newtonian to Newtonian can occur through an increase of temperature and shear of the material. The test has been conducted for unmodified binder VG 30. The transition temperature was found in the unmodified binder VG is 120oC. Therefore, the application of both modified binder and unmodified binder in the pavement construction needs to be studied properly by considering temperature and traffic loading factors of the respective project site.

Keywords: Unmodified and modified binders, Brookfield Viscometer, transition temperature, steady shear, shear rate protocol.

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Authors: Zhongjie Wang, Xiaofei Xu, Dechen Zhan

Abstract:

With deep development of software reuse, componentrelated technologies have been widely applied in the development of large-scale complex applications. Component identification (CI) is one of the primary research problems in software reuse, by analyzing domain business models to get a set of business components with high reuse value and good reuse performance to support effective reuse. Based on the concept and classification of CI, its technical stack is briefly discussed from four views, i.e., form of input business models, identification goals, identification strategies, and identification process. Then various CI methods presented in literatures are classified into four types, i.e., domain analysis based methods, cohesion-coupling based clustering methods, CRUD matrix based methods, and other methods, with the comparisons between these methods for their advantages and disadvantages. Additionally, some insufficiencies of study on CI are discussed, and the causes are explained subsequently. Finally, it is concluded with some significantly promising tendency about research on this problem.

Keywords: Business component, component granularity, component identification, reuse performance.

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Authors: Mohammad Syuhaimi Ab-Rahman, Boonchuan Ng, Kasmiran Jumari

Abstract:

This paper presented a new approach for centralized monitoring and self-protected against fiber fault in fiber-to-the-home (FTTH) access network by using Smart Access Network Testing, Analyzing and Database (SANTAD). SANTAD will be installed with optical line terminal (OLT) at central office (CO) for in-service transmission surveillance and fiber fault localization within FTTH with point-to-multipoint (P2MP) configuration downwardly from CO towards customer residential locations based on the graphical user interface (GUI) processing capabilities of MATLAB software. SANTAD is able to detect any fiber fault as well as identify the failure location in the network system. SANTAD enable the status of each optical network unit (ONU) connected line is displayed onto one screen with capability to configure the attenuation and detect the failure simultaneously. The analysis results and information will be delivered to the field engineer for promptly actions, meanwhile the failure line will be diverted to protection line to ensure the traffic flow continuously. This approach has a bright prospect to improve the survivability and reliability as well as increase the efficiency and monitoring capabilities in FTTH.

Keywords: Fiber fault, FTTH, SANTAD, transmission surveillance, MATLAB.

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Authors: Arijit Ghosh, Tony Givargis

Abstract:

Video sensor networks operate on stringent requirements of latency. Packets have a deadline within which they have to be delivered. Violation of the deadline causes a packet to be treated as lost and the loss of packets ultimately affects the quality of the application. Network latency is typically a function of many interacting components. In this paper, we propose ways of reducing the forwarding latency of a packet at intermediate nodes. The forwarding latency is caused by a combination of processing delay and queueing delay. The former is incurred in order to determine the next hop in dynamic routing. We show that unless link failures in a very specific and unlikely pattern, a vast majority of these lookups are redundant. To counter this we propose source routing as the routing strategy. However, source routing suffers from issues related to scalability and being impervious to network dynamics. We propose solutions to counter these and show that source routing is definitely a viable option in practical sized video networks. We also propose a fast and fair packet scheduling algorithm that reduces queueing delay at the nodes. We support our claims through extensive simulation on realistic topologies with practical traffic loads and failure patterns.

Keywords: Sensor networks, Packet latency, Network design, Networkperformance.

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Authors: Monika Chuchro

Abstract:

This paper presents a preliminary attempt to apply classification of time series using meta-clusters in order to improve the quality of regression models. In this case, clustering was performed as a method to obtain subgroups of time series data with normal distribution from the inflow into wastewater treatment plant data, composed of several groups differing by mean value. Two simple algorithms, K-mean and EM, were chosen as a clustering method. The Rand index was used to measure the similarity. After simple meta-clustering, a regression model was performed for each subgroups. The final model was a sum of the subgroups models. The quality of the obtained model was compared with the regression model made using the same explanatory variables, but with no clustering of data. Results were compared using determination coefficient (R2), measure of prediction accuracy- mean absolute percentage error (MAPE) and comparison on a linear chart. Preliminary results allow us to foresee the potential of the presented technique.

Keywords: Clustering, Data analysis, Data mining, Predictive models.

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Authors: Yassamina Berkane, Leïla Kloul, Yoann Demoli

Abstract:

Quality of life, environmental impact, congestion of mobility means, and infrastructures remain significant challenges for urban mobility. Solutions like car sharing, spatial redesign, eCommerce, and autonomous vehicles will likely increase the unit veh-km and the density of cars in urban traffic, thus reducing congestion. However, the impact of such solutions is not clear for researchers. Congestion arises from growing populations that must travel greater distances to arrive at similar locations (e.g., workplaces, schools) during the same time frame (e.g., rush hours). This paper first reviews the research and application cases of urban congestion methods through recent years. Rethinking the question of time, it then investigates people’s willingness and flexibility to adapt their arrival and departure times from workplaces. We use neural networks and methods of supervised learning to apply a methodology for predicting peoples’ intentions from their responses in a questionnaire. We created and distributed a questionnaire to more than 50 companies in the Paris suburb. Obtained results illustrate that our methodology can predict peoples’ intentions to reschedule their activities (work, study, commerce, etc.).

Keywords: Urban mobility, decongestion, machine learning, neural network.

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Authors: Mozhgan Aliakbari, Sara Moridpour

Abstract:

In recent years, much attention has been given to truck drivers’ fatigue management. Long working hours negatively influence truck drivers’ physiology, health, and safety. However, there is little empirical research in the heavy vehicle transport sector in Australia to identify the influence of working hours’ management on drivers’ fatigue and consequently, on the risk of crashes and injuries. There is no national legislation regulating the number of hours or kilometres travelled by truck drivers. Consequently, it is almost impossible to define a standard number of hours or kilometres for truck drivers in a safety management system. This paper reviews the existing studies concerning safe system interventions such as tachographs in relation to fatigue caused by long working hours. This paper also reviews the literature to identify the influence of frequency of rest breaks on the reduction of work-related road transport accidents involving trucks. A framework is presented to manage truck drivers’ fatigue, which may result in the reduction of injuries and fatalities involving heavy vehicles.

Keywords: Fatigue, time management, trucks, traffic safety.

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Authors: Suneel M. Agerwala, Ashley Votta, Briana Hogan, John Yannocone, Steven Samuels, SheilaChiffriller

Abstract:

Road rage is an increasingly prevalent expression of aggression in our society. Its dangers are apparent and understanding its causes may shed light on preventative measures. This study involved a fifteen-minute survey administered to 147 undergraduate students at a North Eastern suburban university. The survey consisted of a demographics section, questions regarding financial investment in respondents- vehicles, experience driving, habits of driving, experiences witnessing role models driving, and an evaluation of road rage behavior using the Driving Vengeance Questionnaire. The study found no significant differences in driving aggression between respondents who were financially invested in their vehicle compared to those who were not, or between respondents who drove in heavy traffic hours compared to those who did not, suggesting internal factors correlate with aggressive driving habits. The study also found significant differences in driving aggression between males versus females, those with more points on their license versus fewer points, and those who witnessed parents driving aggressively very often versus rarely or never. Additional studies can investigate how witnessing parents driving aggressively is related to future driving behaviors.

Keywords: Aggression, college, driving, road rage.

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Authors: Siyao Zhu, Yifang Xu

Abstract:

After natural and man-made disasters, robots can bypass the danger, expedite the search, and acquire unprecedented situational awareness to design rescue plans. Brain-computer interface is a promising option to overcome the limitations of tedious manual control and operation of robots in the urgent search-and-rescue tasks. This study aims to test the feasibility of using electroencephalography (EEG) signals to decode human intentions and detect the level of consensus on robot-provided information. EEG signals were classified using machine-learning and deep-learning methods to discriminate search intentions and agreement perceptions. The results show that the average classification accuracy for intention recognition and consensus assessment is 67% and 72%, respectively, proving the potential of incorporating recognizable users’ bioelectrical responses into advanced robot-assisted systems for emergency response.

Keywords: Consensus assessment, electroencephalogram, EEG, emergency response, human-robot collaboration, intention recognition, search and rescue.

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Authors: J. Bouchard, B. Prosperi, G. Bavre, M. Daudé, E. Jeandupeux

Abstract:

Young patients suffering from Cerebral Palsy are facing difficult choices concerning heavy surgeries. Diagnosis settled by surgeons can be complex and on the other hand decision for patient about getting or not such a surgery involves important reflection effort. Proposed software combining prediction for surgeries and post surgery kinematic values, and from 3D model representing the patient is an innovative tool helpful for both patients and medicine professionals. Beginning with analysis and classification of kinematics values from Data Base extracted from gait analysis in 3 separated clusters, it is possible to determine close similarity between patients. Prediction surgery best adapted to improve a patient gait is then determined by operating a suitable preconditioned neural network. Finally, patient 3D modeling based on kinematic values analysis, is animated thanks to post surgery kinematic vectors characterizing the closest patient selected from patients clustering.

Keywords: Cerebral Palsy, Clustering, Crouch Gait, 3-D Modeling.

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