Search results for: intelligent processing

Authors: Chhaya Gangwal, R. N. Bhaumik, Shishir Kumar

Abstract:

Some properties of Intuitionistic Fuzzy (IF) rough relational algebraic operators under an IF rough relational data model are investigated and illustrated using diabetes and heart disease databases. These properties are important and desirable for processing queries in an effective and efficient manner.

 

Keywords: IF Set, Rough Set, IF Rough Relational Database, IF rough Relational Operators.

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Authors: David Kubát

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This paper suggests using smartphones and community GPS application to make alerts more accurate and therefore positively influence the entire warning process. The paper is based on formerly published paper describing a Radio-HELP system. It summarizes existing methods and lists the advantages of proposed solution. The paper analyzes the advantages and disadvantages of each possible input, processing and output of the warning system.

Keywords: e-Call, warning, information, Radio-Help, WAZE

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Authors: Hamid Abdi, Abolfazl Salami, Abolfazl Ahmadi

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Programmable logic controllers are the main controllers in the today's industries; they are used for several applications in industrial control systems and there are lots of examples exist from the PLC applications in industries especially in big companies and plants such as refineries, power plants, petrochemical companies, steel companies, and food and production companies. In the PLCs there are some functions in the function library in software that can be used in PLC programs as basic program elements. The aim of this project are introducing and implementing a new function block of a neural network to the function library of PLC. This block can be applied for some control applications or nonlinear functions calculations after it has been trained for these applications. The implemented neural network is a Perceptron neural network with three layers, three input nodes and one output node. The block can be used in manual or automatic mode. In this paper the structure of the implemented function block, the parameters and the training method of the network are presented by considering the especial method of PLC programming and its complexities. Finally the application of the new block is compared with a classic simulated block and the results are presented.

Keywords: Programmable Logic Controller, PLC Programming, Neural Networks, Perception Network, Intelligent Control.

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Authors: Siti Nor Hafizah bt Mohd Zaid, Mohamed Abdel Maguid, Abdel Hamid Soliman

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Road traffic accidents are a major cause of death worldwide. In an attempt to reduce accidents, some research efforts have focused on creating Advanced Driver Assistance Systems (ADAS) able to detect vehicle, driver and environmental conditions and to use this information to identify cues for potential accidents. This paper presents continued work on a novel Non-intrusive Intelligent Driver Assistance and Safety System (Ni-DASS) for assessing driver point of regard within vehicles. It uses an on-board CCD camera to observe the driver-s face. A template matching approach is used to compare the driver-s eye-gaze pattern with a set of eye-gesture templates of the driver looking at different focal points within the vehicle. The windscreen is divided into cells and comparison of the driver-s eye-gaze pattern with templates of a driver-s eyes looking at each cell is used to determine the driver-s point of regard on the windscreen. Results indicate that the proposed technique could be useful in situations where low resolution estimates of driver point of regard are adequate. For instance, To allow ADAS systems to alert the driver if he/she has positively failed to observe a hazard.

Keywords: Head rotation, Eye-gestures, Windscreen, Template matching.

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Authors: Moulay A. Akhloufi

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In recent years, we see an increase of interest for efficient tracking systems in surveillance applications. Many of the proposed techniques are designed for static cameras environments. When the camera is moving, tracking moving objects become more difficult and many techniques fail to detect and track the desired targets. The problem becomes more complex when we want to track a specific object in real-time using a moving Pan and Tilt camera system to keep the target within the image. This type of tracking is of high importance in surveillance applications. When a target is detected at a certain zone, the possibility of automatically tracking it continuously and keeping it within the image until action is taken is very important for security personnel working in very sensitive sites. This work presents a real-time tracking system permitting the detection and continuous tracking of targets using a Pan and Tilt camera platform. A novel and efficient approach for dealing with occlusions is presented. Also a new intelligent forget factor is introduced in order to take into account target shape variations and avoid learning non desired objects. Tests conducted in outdoor operational scenarios show the efficiency and robustness of the proposed approach.

Keywords: Tracking, surveillance, target detection, Pan and tilt.

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Authors: Travis Morris

Abstract:

The purpose of this study is to measure the intersection of environmental security entities in terrorist propaganda. To the best of author’s knowledge, this is the first study of its kind to examine this intersection within terrorist propaganda. Rosoka, natural language processing software and frame analysis are used to advance our understanding of how environmental frames function as emotive triggers. Violent jihadi demagogues use frames to suggest violent and non-violent solutions to their grievances. Emotive triggers are framed in a way to leverage individual and collective attitudes in psychological warfare. A comparative research design is used because of the differences and similarities that exist between two variants of violent jihadi propaganda that target western audiences. Analysis is based on salience and network text analysis, which generates violent jihadi semantic networks. Findings indicate that environmental frames are used as emotive triggers across both data sets, but also as tactical and information data points. A significant finding is that certain core environmental emotive triggers like “water,” “soil,” and “trees” are significantly salient at the aggregate level across both data sets. All environmental entities can be classified into two categories, symbolic and literal. Importantly, this research illustrates how demagogues use environmental emotive triggers in cyber space from a subcultural perspective to mobilize target audiences to their ideology and praxis. Understanding the anatomy of propaganda construction is necessary in order to generate effective counter narratives in information operations. This research advances an additional method to inform practitioners and policy makers of how environmental security and propaganda intersect.

Keywords: Emotive triggers, environmental security, natural language processing, propaganda analysis.

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Authors: V. Barot, S. McLeod, R. Harrison, A. A. West

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Manufacturing Industries face a crucial change as products and processes are required to, easily and efficiently, be reconfigurable and reusable. In order to stay competitive and flexible, situations also demand distribution of enterprises globally, which requires implementation of efficient communication strategies. A prototype system called the “Broadcaster" has been developed with an assumption that the control environment description has been engineered using the Component-based system paradigm. This prototype distributes information to a number of globally distributed partners via an adoption of the circular-based data processing mechanism. The work highlighted in this paper includes the implementation of this mechanism in the domain of the manufacturing industry. The proposed solution enables real-time remote propagation of machine information to a number of distributed supply chain client resources such as a HMI, VRML-based 3D views and remote client instances regardless of their distribution nature and/ or their mechanisms. This approach is presented together with a set of evaluation results. Authors- main concentration surrounds the reliability and the performance metric of the adopted approach. Performance evaluation is carried out in terms of the response times taken to process the data in this domain and compared with an alternative data processing implementation such as the linear queue mechanism. Based on the evaluation results obtained, authors justify the benefits achieved from this proposed implementation and highlight any further research work that is to be carried out.

Keywords: Broadcaster, circular buffer, Component-based, distributed manufacturing, remote data propagation.

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Authors: S. Arun Rajan, S. Bhavani

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Wireless sensor networks can be tiny, low cost, intelligent sensors connected with advanced communication systems. WSNs have pulled in significant consideration as a matter of fact that, industrial as well as medical solicitations employ these in monitoring targets, conservational observation, obstacle exposure, movement regulator etc. In these applications, sensor hubs are thickly sent in the unattended environment with little non-rechargeable batteries. This constraint requires energy-efficient systems to drag out the system lifetime. There are redundancies in data sent over the network. To overcome this, multiple virtual spine scheduling has been presented. Such networks problems are called Maximum Lifetime Backbone Scheduling (MLBS) problems. Though this sleep wake cycle reduces radio usage, improvement can be made in the path in which the group heads stay selected. Cluster head selection with emphasis on geometrical relation of the system will enhance the load sharing among the nodes. Also the data are analyzed to reduce redundant transmission. Multi-hop communication will facilitate lighter loads on the network.

Keywords: WSN, wireless sensor networks, MLBS, maximum lifetime backbone scheduling.

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Authors: Osman Mohammed Hegazy, Ali Hamed El Bastawissy, Romani Farid Ibrahim

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In this paper, our concern is the management of mobile transactions in the shared area among many servers, when the mobile user moves from one cell to another in online partiallyreplicated distributed mobile database environment. We defined the concept of transaction and classified the different types of transactions. Based on this analysis, we propose an algorithm that handles the disconnection due to moving among sites.

Keywords: Concurrency, mobile database, transaction processing, two phase locking.

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Authors: Saman Ghaffarian, Ilgın Gökasar

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This paper presents a new automatic vehicle detection method from very high resolution aerial images to measure traffic density. The proposed method starts by extracting road regions from image using road vector data. Then, the road image is divided into equal sections considering resolution of the images. Gradient vectors of the road image are computed from edge map of the corresponding image. Gradient vectors on the each boundary of the sections are divided where the gradient vectors significantly change their directions. Finally, number of vehicles in each section is carried out by calculating the standard deviation of the gradient vectors in each group and accepting the group as vehicle that has standard deviation above predefined threshold value. The proposed method was tested in four very high resolution aerial images acquired from Istanbul, Turkey which illustrate roads and vehicles with diverse characteristics. The results show the reliability of the proposed method in detecting vehicles by producing 86% overall F1 accuracy value.

Keywords: Aerial images, intelligent transportation systems, traffic density measurement, vehicle detection.

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Authors: Li Li, Kai-Hsuan Chu

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It is well known that the real estate price depends on a lot of factors. Each house current value is dependent on the location, room number, transportation, living convenience, year and surrounding environments. Although, there are different experienced models for housing agent to estimate the price, it is a case by case study without overall dynamic variation investigation. However, many economic parameters may more or less influence the real estate price variation. Here, the influences of most macroeconomic parameters on real estate price are investigated individually based on least-square scheme and grey correlation strategy. Then those parameters are classified into leading indices, simultaneous indices and laggard indices. In addition, the leading time period is evaluated based on least square method. The important leading and simultaneous indices can be used to establish an artificial intelligent neural network model for real estate price variation prediction. The real estate price variation of Taipei, Taiwan during 2005 ~ 2017 are chosen for this research data analysis and validation. The results show that the proposed method has reasonable prediction function for real estate business reference.

Keywords: Real estate price, least-square, grey correlation, macroeconomics.

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Authors: Taehyun Yoon, Keechul Jung

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There are many researches to detect collision between real object and virtual object in 3D space. In general, these techniques are need to huge computing power. So, many research and study are constructed by using cloud computing, network computing, and distribute computing. As a reason of these, this paper proposed a novel fast 3D collision detection algorithm between real and virtual object using 2D intersection area. Proposed algorithm uses 4 multiple cameras and coarse-and-fine method to improve accuracy and speed performance of collision detection. In the coarse step, this system examines the intersection area between real and virtual object silhouettes from all camera views. The result of this step is the index of virtual sensors which has a possibility of collision in 3D space. To decide collision accurately, at the fine step, this system examines the collision detection in 3D space by using the visual hull algorithm. Performance of the algorithm is verified by comparing with existing algorithm. We believe proposed algorithm help many other research, study and application fields such as HCI, augmented reality, intelligent space, and so on.

Keywords: Collision Detection, Computer Vision, Human Computer Interaction, Visual Hull

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Authors: Hamdi Amroun, Yacine Benziani, Mehdi Ammi

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In this paper, we want to determine whether the accurate prediction of nicotine concentration can be obtained by using a network of smart objects and an e-cigarette. The approach consists of, first, the recognition of factors influencing smoking cessation such as physical activity recognition and participant’s behaviors (using both smartphone and smartwatch), then the prediction of the configuration of the e-cigarette (in terms of nicotine concentration, power, and resistance of e-cigarette). The study uses a network of commonly connected objects; a smartwatch, a smartphone, and an e-cigarette transported by the participants during an uncontrolled experiment. The data obtained from sensors carried in the three devices were trained by a Long short-term memory algorithm (LSTM). Results show that our LSTM-based model allows predicting the configuration of the e-cigarette in terms of nicotine concentration, power, and resistance with a root mean square error percentage of 12.9%, 9.15%, and 11.84%, respectively. This study can help to better control consumption of nicotine and offer an intelligent configuration of the e-cigarette to users.

Keywords: Iot, activity recognition, automatic classification, unconstrained environment, deep neural networks.

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Authors: Mohamed Yousef, Magdy Samuel, Maha El-Meligy, Taher El-Bitar

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The present work is dealing with 2% Si-steel alloy. The alloy contains 0.05% C as well as 0.85% Al. The alloy under investigation would be used for electrical transformation purposes. A heating (expansion) - cooling (contraction) dilation investigation was executed to detect the a, a+g, and g transformation temperatures at the inflection points of the dilation curve. On heating, primary a  was detected at a temperature range between room temperature and 687 ^oC. The domain of a+g was detected in the range between 687 ^oC and 746 ^oC. g phase exists in the closed g region at the range between 746 ^oC and 1043 ^oC. The domain of a phase appears again at a temperature range between 1043 and 1105 ^oC, and followed by secondary a at temperature higher than 1105 ^oC. A physical simulation of thermo-mechanical processing on the as-cast alloy was carried out. The simulation process took into consideration the hot flat rolling pilot plant parameters. The process was executed on the thermo-mechanical simulator (Gleeble 3500). The process was designed to include seven consecutive passes. The 1^st pass represents the roughing stage, while the remaining six passes represent finish rolling stage. The whole process was executed at the temperature range from 1100 ^oC to 900 ^oC. The amount of strain starts with 23.5% at the roughing pass and decreases continuously to reach 7.5 % at the last finishing pass. The flow curve of the alloy can be abstracted from the stress-strain curves representing simulated passes. It shows alloy hardening from a pass to the other up to pass no. 6, as a result of decreasing the deformation temperature and increasing of cumulative strain. After pass no. 6, the deformation process enhances the dynamic recrystallization phenomena to appear, where the z-parameter would be high.

Keywords: Si-steel, hot deformability, critical transformation temperature, physical simulation, thermo-mechanical processing, flow curve, dynamic softening.

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Authors: Fantazi Walid, Ezzedine Tahar, Bargaoui Zoubeida

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This research presents the main ideas to implement an intelligent system composed by communicating wireless sensors measuring environmental data linked to drought indicators (such as air temperature, soil moisture , etc...). On the other hand, the setting up of a spatio temporal database communicating with a Web mapping application for a monitoring in real time in activity 24:00 /day, 7 days/week is proposed to allow the screening of the drought parameters time evolution and their extraction. Thus this system helps detecting surfaces touched by the phenomenon of drought. Spatio-temporal conceptual models seek to answer the users who need to manage soil water content for irrigating or fertilizing or other activities pursuing crop yield augmentation. Effectively, spatiotemporal conceptual models enable users to obtain a diagram of readable and easy data to apprehend. Based on socio-economic information, it helps identifying people impacted by the phenomena with the corresponding severity especially that this information is accessible by farmers and stakeholders themselves. The study will be applied in Siliana watershed Northern Tunisia.

Keywords: WSN, database spatio-temporal, GIS, web-mapping, indicator of drought.

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Authors: Vasilescu M., Rusu L., Nestianu V., Romanescu F., Dragomir M

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The research was designed to examine the relationship between the development of muscle fatigue and the effect it has on sport performance, specifically during maximal voluntary contraction. This kind of this investigation using simultaneous electrophysiological and mechanical recordings, based on advanced mathematical processing, allows us to get parameters, and indexes in a short time, and finally, the mapping to use for the thorough investigation of the muscle contraction force, respectively the phenomenon of local muscle fatigue, both for athletes and other subjects.

Keywords: Electromyography, mechanomyography, musclefatigue

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Authors: Atanu K Samanta, Asim Ali Khan

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Due to the acquisition of huge amounts of brain tumor magnetic resonance images (MRI) in clinics, it is very difficult for radiologists to manually interpret and segment these images within a reasonable span of time. Computer-aided diagnosis (CAD) systems can enhance the diagnostic capabilities of radiologists and reduce the time required for accurate diagnosis. An intelligent computer-aided technique for automatic detection of a brain tumor through MRI is presented in this paper. The technique uses the following computational methods; the Level Set for segmentation of a brain tumor from other brain parts, extraction of features from this segmented tumor portion using gray level co-occurrence Matrix (GLCM), and the Artificial Neural Network (ANN) to classify brain tumor images according to their respective types. The entire work is carried out on 50 images having five types of brain tumor. The overall classification accuracy using this method is found to be 98% which is significantly good.

Keywords: Artificial neural network, ANN, brain tumor, computer-aided diagnostic, CAD system, gray-level co-occurrence matrix, GLCM, level set method, tumor segmentation.

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Authors: Abdelkader Dekdouk

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In this paper we propose a novel approach for searching eCommerce products using a mobile phone, illustrated by a prototype eCoMobile. This approach aims to globalize the mobile search by integrating the concept of user multilinguism into it. To show that, we particularly deal with English and Arabic languages. Indeed the mobile user can formulate his query on a commercial product in either language (English/Arabic). The description of his information need on commercial products relies on the ontology that represents the conceptualization of the product catalogue knowledge domain defined in both English and Arabic languages. A query expressed on a mobile device client defines the concept that corresponds to the name of the product followed by a set of pairs (property, value) specifying the characteristics of the product. Once a query is submitted it is then communicated to the server side which analyses it and in its turn performs an http request to an eCommerce application server (like Amazon). This latter responds by returning an XML file representing a set of elements where each element defines an item of the searched product with its specific characteristics. The XML file is analyzed on the server side and then items are displayed on the mobile device client along with its relevant characteristics in the chosen language.

Keywords: Mobile computing, search engine, multilingualglobal eCommerce, ontology, XML.

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Authors: Li Shoutao, Gordon Lee

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Evolutionary robotics is concerned with the design of intelligent systems with life-like properties by means of simulated evolution. Approaches in evolutionary robotics can be categorized according to the control structures that represent the behavior and the parameters of the controller that undergo adaptation. The basic idea is to automatically synthesize behaviors that enable the robot to perform useful tasks in complex environments. The evolutionary algorithm searches through the space of parameterized controllers that map sensory perceptions to control actions, thus realizing a specific robotic behavior. Further, the evolutionary algorithm maintains and improves a population of candidate behaviors by means of selection, recombination and mutation. A fitness function evaluates the performance of the resulting behavior according to the robot-s task or mission. In this paper, the focus is in the use of genetic algorithms to solve a multi-objective optimization problem representing robot behaviors; in particular, the A-Compander Law is employed in selecting the weight of each objective during the optimization process. Results using an adaptive fitness function show that this approach can efficiently react to complex tasks under variable environments.

Keywords: adaptive fuzzy neural inference, evolutionary tuning

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

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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: Danielle Shackley, Yetunde Folajimi

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As more people turn to the internet seeking health related information, there is more risk of finding false, inaccurate, or dangerous information. Sentiment analysis is a natural language processing technique that assigns polarity scores of text, ranging from positive, neutral and negative. In this research, we evaluate the weight of a sentiment analysis feature added to fake health news classification models. The dataset consists of existing reliably labeled health article headlines that were supplemented with health information collected about COVID-19 from social media sources. We started with data preprocessing, tested out various vectorization methods such as Count and TFIDF vectorization. We implemented 3 Naive Bayes classifier models, including Bernoulli, Multinomial and Complement. To test the weight of the sentiment analysis feature on the dataset, we created benchmark Naive Bayes classification models without sentiment analysis, and those same models were reproduced and the feature was added. We evaluated using the precision and accuracy scores. The Bernoulli initial model performed with 90% precision and 75.2% accuracy, while the model supplemented with sentiment labels performed with 90.4% precision and stayed constant at 75.2% accuracy. Our results show that the addition of sentiment analysis did not improve model precision by a wide margin; while there was no evidence of improvement in accuracy, we had a 1.9% improvement margin of the precision score with the Complement model. Future expansion of this work could include replicating the experiment process, and substituting the Naive Bayes for a deep learning neural network model.

Keywords: Sentiment analysis, Naive Bayes model, natural language processing, topic analysis, fake health news classification model.

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Authors: Xiaoyun Zhao, Rami Darwish, Anna Pernestål

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Automated vehicles (AVs) have the potential to enhance road capacity, improving road safety and traffic efficiency. Research and development on AVs have been going on for many years. However, when the complicated traffic rules and real situations interacted, AVs fail to make decisions on contradicting situations, and are not able to have control in all conditions due to highly dynamic driving scenarios. This limits AVs’ usage and restricts the full potential benefits that they can bring. Furthermore, regulations, infrastructure development, and public acceptance cannot keep up at the same pace as technology breakthroughs. Facing these challenges, this paper proposes automated vehicle traffic control tower (AVTCT) acting as a safe, efficient and integrated solution for AV control. It introduces a concept of AVTCT for control, management, decision-making, communication and interaction with various aspects in transportation. With the prototype demonstrations and simulations, AVTCT has the potential to overcome the control challenges with AVs and can facilitate AV reaching their full potential. Possible functionalities, benefits as well as challenges of AVTCT are discussed, which set the foundation for the conceptual model, simulation and real application of AVTCT.

Keywords: Automated vehicle, connectivity and automation, intelligent transport system, traffic control, traffic safety.

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Authors: Fan Ye

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Adverse weather conditions, particularly those with low visibility, are critical to the driving tasks. However, the direct relationship between visibility distances and traffic flow/roadway safety is uncertain due to the limitation of visibility data availability. The recent growth of deployment of Road Weather Information Systems (RWIS) makes segment-specific visibility information available which can be integrated with other Intelligent Transportation System, such as automated warning system and variable speed limit, to improve mobility and safety. Before applying the RWIS visibility measurements in traffic study and operations, it is critical to validate the data. Therefore, an attempt was made in the paper to examine the validity and viability of RWIS visibility data by comparing visibility measurements among RWIS, airport weather stations, and weather information recorded by police in crash reports, based on Ohio data. The results indicated that RWIS visibility measurements were significantly different from airport visibility data in Ohio, but no conclusion regarding the reliability of RWIS visibility could be drawn in the consideration of no verified ground truth in the comparisons. It was suggested that more objective methods are needed to validate the RWIS visibility measurements, such as continuous in-field measurements associated with various weather events using calibrated visibility sensors.

Keywords: Low visibility, RWIS, traffic safety, visibility.

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Authors: Manisha Dubey, Aalok Dubey

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This paper presents an approach for the design of fuzzy logic power system stabilizers using genetic algorithms. In the proposed fuzzy expert system, speed deviation and its derivative have been selected as fuzzy inputs. In this approach the parameters of the fuzzy logic controllers have been tuned using genetic algorithm. Incorporation of GA in the design of fuzzy logic power system stabilizer will add an intelligent dimension to the stabilizer and significantly reduces computational time in the design process. It is shown in this paper that the system dynamic performance can be improved significantly by incorporating a genetic-based searching mechanism. To demonstrate the robustness of the genetic based fuzzy logic power system stabilizer (GFLPSS), simulation studies on multimachine system subjected to small perturbation and three-phase fault have been carried out. Simulation results show the superiority and robustness of GA based power system stabilizer as compare to conventionally tuned controller to enhance system dynamic performance over a wide range of operating conditions.

Keywords: Dynamic stability, Fuzzy logic power systemstabilizer, Genetic Algorithms, Genetic based power systemstabilizer

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Authors: M. Okeke, A. Blyth

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Industrial Control Systems (ICS) such as Supervisory Control And Data Acquisition (SCADA) can be seen in many different critical infrastructures, from nuclear management to utility, medical equipment, power, waste and engine management on ships and planes. The role SCADA plays in critical infrastructure has resulted in a call to secure them. Many lives depend on it for daily activities and the attack vectors are becoming more sophisticated. Hence, the security of ICS is vital as malfunction of it might result in huge risk. This paper describes how the application of Prey Predator (PP) approach in flocks of birds could enhance the detection of malicious activities on ICS. The PP approach explains how these animals in groups or flocks detect predators by following some simple rules. They are not necessarily very intelligent animals but their approach in solving complex issues such as detection through corporation, coordination and communication worth emulating. This paper will emulate flocking behavior seen in birds in detecting predators. The PP approach will adopt six nearest bird approach in detecting any predator. Their local and global bests are based on the individual detection as well as group detection. The PP algorithm was designed following MapReduce methodology that follows a Split Detection Convergence (SDC) approach.

Keywords: Industrial control systems, prey predator, SCADA, SDC.

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Authors: Safaa Al-Ali, Ahmad Shahin, Fadi Chakik

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Image coding based on clustering provides immediate access to targeted features of interest in a high quality decoded image. This approach is useful for intelligent devices, as well as for multimedia content-based description standards. The result of image clustering cannot be precise in some positions especially on pixels with edge information which produce ambiguity among the clusters. Even with a good enhancement operator based on PDE, the quality of the decoded image will highly depend on the clustering process. In this paper, we introduce an ambiguity cluster in image coding to represent pixels with vagueness properties. The presence of such cluster allows preserving some details inherent to edges as well for uncertain pixels. It will also be very useful during the decoding phase in which an anisotropic diffusion operator, such as Perona-Malik, enhances the quality of the restored image. This work also offers a comparative study to demonstrate the effectiveness of a fuzzy clustering technique in detecting the ambiguity cluster without losing lot of the essential image information. Several experiments have been carried out to demonstrate the usefulness of ambiguity concept in image compression. The coding results and the performance of the proposed algorithms are discussed in terms of the peak signal-tonoise ratio and the quantity of ambiguous pixels.

Keywords: Ambiguity Cluster, Anisotropic Diffusion, Fuzzy Clustering, Image Compression.

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Authors: Svetlana Cojocaru, Mircea Petic, Inga Titchiev

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Humanity faces more and more often with different social disasters, which in turn can generate new accidents and catastrophes. To mitigate their consequences, it is important to obtain early possible signals about the events which are or can occur and to prepare the corresponding scenarios that could be applied. Our research is focused on solving two problems in this domain: identifying signals related that an accident occurred or may occur and mitigation of some consequences of disasters. To solve the first problem, methods of selecting and processing texts from global network Internet are developed. Information in Romanian is of special interest for us. In order to obtain the mentioned tools, we should follow several steps, divided into preparatory stage and processing stage. Throughout the first stage, we manually collected over 724 news articles and classified them into 10 categories of social disasters. It constitutes more than 150 thousand words. Using this information, a controlled vocabulary of more than 300 keywords was elaborated, that will help in the process of classification and identification of the texts related to the field of social disasters. To solve the second problem, the formalism of Petri net has been used. We deal with the problem of inhabitants’ evacuation in useful time. The analysis methods such as reachability or coverability tree and invariants technique to determine dynamic properties of the modeled systems will be used. To perform a case study of properties of extended evacuation system by adding time, the analysis modules of PIPE such as Generalized Stochastic Petri Nets (GSPN) Analysis, Simulation, State Space Analysis, and Invariant Analysis have been used. These modules helped us to obtain the average number of persons situated in the rooms and the other quantitative properties and characteristics related to its dynamics.

Keywords: Lexicon of disasters, modelling, Petri nets, text annotation, social disasters.

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Authors: Kittipong Tissayakorn, Fumio Akagi, Yu Song

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Manufacturers have been exploring innovative strategies to achieve and sustain competitive advantages as they face a new era of intensive global competition. Such strategy is known as Supply Chain Management (SCM), which has gained a tremendous amount of attention from both researchers and practitioners over the last decade. Supply chain management (SCM) is considered as the most popular operating strategy for improving organizational competitiveness in the twenty-first century. It has attracted a lot of attention recently due to its role involving all of the activities in industrial organizations, ranging from raw material procurement to final product delivery to customers. Well-designed supply chain systems can substantially improve efficiency and product quality, and eventually enhance customer satisfaction and profitability. In this paper, a manufacturing engineering perspective on supply chain integration is presented. Research issues discussed include the product and process design for the supply chain, design evaluation of manufacturing in the supply chain, agent-based techniques for supply chain integration, intelligent information for sharing across the supply chain, and a development of standards for product, process, and production data exchange to facilitate electronic commerce. The objective is to provide guidelines and references for manufacturing engineers and researchers interested in supply chain integration.

Keywords: Supply Chain, Supply Chain Management, Supply Chain Integration, Manufacturing Industries.

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Authors: Yen San Yong, Hock Woon Hon

Abstract:

An algorithm for estimating the disparity of objects of interest is proposed. This algorithm uses image shifting and overlapping area to estimate the disparity value; thereby depth of the objects of interest can be obtained. The algorithm is able to perform at different levels of accuracy. However, as the accuracy increases the processing speed decreases. The algorithm is tested with static stereo images and sequence of stereo images. The experimental results are presented in this paper.

Keywords: stereo vision, binocular parallax

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Authors: Sourabh Jain, Sukhvir Singh Jain, Gaurav V. Jain

Abstract:

Intelligent Transportation System is an integrated application of communication, control and monitoring and display process technologies for developing a user–friendly transportation system for urban areas in developing countries. In fact, the development of a country and the progress of its transportation system are complementary to each other. Urban traffic has been growing vigorously due to population growth as well as escalation of vehicle ownership causing congestion, delays, pollution, accidents, high-energy consumption and low productivity of resources. The development and management of urban transport in developing countries like India however, is at tryout stage with very few accumulations. Under the umbrella of ITS, urban corridor management strategy have proven to be one of the most successful system in accomplishing these objectives. The present study interprets and figures out the performance of the 27.4 km long Urban Bus route having six intersections, five flyovers and 29 bus stops that covers significant area of the city by causality analysis. Performance interpretations incorporate Passenger Boarding and Alighting, Dwell time, Distance between Bus Stops and Total trip time taken by bus on selected urban route.

Keywords: Congestion, Dwell time, delay, passengers boarding alighting, travel time.

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