Search results for: Recognition of driving scene.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1179

Search results for: Recognition of driving scene.

249 A Cross-Gender Statistical Analysis of Tuvinian Intonation Features in Comparison With Uzbek and Azerbaijani

Authors: D. Beziakina, E. Bulgakova

Abstract:

The paper deals with cross-gender and cross-linguistic comparison of pitch characteristics for Tuvinian with two other Turkic languages - Uzbek and Azerbaijani, based on the results of statistical analysis of pitch parameter values and intonation patterns used by male and female speakers.

The main goal of our work is to obtain the ranges of pitch parameter values typical for Tuvinian speakers for the purpose of automatic language identification. We also propose a cross-gender analysis of declarative intonation in the poorly studied Tuvinian language.

The ranges of pitch parameter values were obtained by means of specially developed software that deals with the distribution of pitch values and allows us to obtain statistical language-specific pitch intervals.

Keywords: Speech analysis, Statistical analysis, Speaker recognition, Identification of person.

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248 Improved Artificial Immune System Algorithm with Local Search

Authors: Ramin Javadzadeh., Zahra Afsahi, MohammadReza Meybodi

Abstract:

The Artificial immune systems algorithms are Meta heuristic optimization method, which are used for clustering and pattern recognition applications are abundantly. These algorithms in multimodal optimization problems are more efficient than genetic algorithms. A major drawback in these algorithms is their slow convergence to global optimum and their weak stability can be considered in various running of these algorithms. In this paper, improved Artificial Immune System Algorithm is introduced for the first time to overcome its problems of artificial immune system. That use of the small size of a local search around the memory antibodies is used for improving the algorithm efficiently. The credibility of the proposed approach is evaluated by simulations, and it is shown that the proposed approach achieves better results can be achieved compared to the standard artificial immune system algorithms

Keywords: Artificial immune system, Cellular Automata, Cellular learning automata, Cellular learning automata, , Local search, Optimization.

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247 Empirical Study on the Student Satisfaction in Higher Education: Importance-Satisfaction Analysis

Authors: Silva, Fátima, Fernandes, Paula Odete

Abstract:

The future of Higher Education Institutions (HEI) depend on their ability to attract and retain students, increase recognition and prestige. In order to respond to the 'customers' increasingly demanding, HEI need to identify the key factors that influence the satisfaction of a 'customers', thereby creating competitive advantages. These determinants of satisfaction are important elements that guide the strategy of an institution and allow the successful achievement of strategic plans, both teaching and administrative, to offer their ‘costumers’ services and products with higher quality. Following this way of thinking, the purpose of this study was to evaluate the satisfaction with the service quality of the School of Technology and Management of Bragança (ESTiG), of the Polytechnic Institute of Bragança, identifying, thus, the dimensions related to the quality of services that might influence students' satisfaction. The results showed that, in general, the students are satisfied with the performance of ESTiG.

Keywords: Customer Satisfaction, Higher Education Institutions, Importance-Satisfaction Model.

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246 Design and Fabrication of a Programmable Stiffness-Sensitive Gripper for Object Handling

Authors: Mehdi Modabberifar, Sanaz Jabary, Mojtaba Ghodsi

Abstract:

Stiffness sensing is an important issue in medical diagnostic, robotics surgery, safe handling, and safe grasping of objects in production lines. Detecting and obtaining the characteristics in dwelling lumps embedded in a soft tissue and safe removing and handling of detected lumps is needed in surgery. Also in industry, grasping and handling an object without damaging in a place where it is not possible to access a human operator is very important. In this paper, a method for object handling is presented. It is based on the use of an intelligent gripper to detect the object stiffness and then setting a programmable force for grasping the object to move it. The main components of this system includes sensors (sensors for measuring force and displacement), electrical (electrical and electronic circuits, tactile data processing and force control system), mechanical (gripper mechanism and driving system for the gripper) and the display unit. The system uses a rotary potentiometer for measuring gripper displacement. A microcontroller using the feedback received by the load cell, mounted on the finger of the gripper, calculates the amount of stiffness, and then commands the gripper motor to apply a certain force on the object. Results of Experiments on some samples with different stiffness show that the gripper works successfully. The gripper can be used in haptic interfaces or robotic systems used for object handling.

Keywords: Gripper, haptic, stiffness, robotic.

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245 Characterization of a Novel Galactose-Binding Lectin Homologue from Tenebrio molitor

Authors: JiEun Jeong, Dong Hyun Kim, Bharat Bhusan Patnaik, Se Won Kang, HeeJu Hwang, Yong Hun Jo, Dae-Hyun Seog, YeonSooHan, Yong Seok Lee

Abstract:

An expressed sequence tag (EST) analysis provideus portions of expressed genes. We have constructed cDNA library and determined randomly sequences from cDNA library clones of T. molitor injected with acholeplasma lysate. We identified the homologous to a galectin gene. As the result of cloning and characterization of novel, we found that the protein has an open reading frame (ORF) of 495 bp, with 164 amino acid residues and molecular weight of 18.5 kDa. To characterize the role of novel Tm-galectin in immune system, we quantified the mRNA level of galectin at different times after treatment with immune elicitors. The galectin mRNA was up-regulated about 7-folds within 18 hrs. This suggests that Tm-galectin is a novel member of animal lectins, and has a role in the process of pathogen recognition. Our study would be helpful for the study on immune defense system and signaling cascade.

Keywords: EST, Innate immunity, Tenebrio molitor, Galectin.

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244 Comparing Hilditch, Rosenfeld, Zhang-Suen,and Nagendraprasad -Wang-Gupta Thinning

Authors: Anastasia Rita Widiarti

Abstract:

This paper compares Hilditch, Rosenfeld, Zhang- Suen, dan Nagendraprasad Wang Gupta (NWG) thinning algorithms for Javanese character image recognition. Thinning is an effective process when the focus in not on the size of the pattern, but rather on the relative position of the strokes in the pattern. The research analyzes the thinning of 60 Javanese characters. Time-wise, Zhang-Suen algorithm gives the best results with the average process time being 0.00455188 seconds. But if we look at the percentage of pixels that meet one-pixel thickness, Rosenfelt algorithm gives the best results, with a 99.98% success rate. From the number of pixels that are erased, NWG algorithm gives the best results with the average number of pixels erased being 84.12%. It can be concluded that the Hilditch algorithm performs least successfully compared to the other three algorithms.

Keywords: Hilditch algorithm, Nagendraprasad-Wang-Guptaalgorithm, Rosenfeld algorithm, Thinning, Zhang-suen algorithm

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243 Negative Temperature Dependence of a Gravity - A Reality

Authors: Alexander L. Dmitriev, Sophia A. Bulgakova

Abstract:

Temperature dependence of force of gravitation is one of the fundamental problems of physics. This problem has got special value in connection with that the general theory of relativity, supposing the weakest positive influence of a body temperature on its weight, actually rejects an opportunity of measurement of negative influence of temperature on gravity in laboratory conditions. Really, the recognition of negative temperature dependence of gravitation, for example, means basic impossibility of achievement of a singularity («a black hole») at a gravitational collapse. Laboratory experiments with exact weighing the heated up metal samples, indicating negative influence temperatures of bodies on their physical weight are described. Influence of mistakes of measurements is analyzed. Calculations of distribution of temperature in volume of the bar, agreed with experimental data of time dependence of weight of samples are executed. The physical substantiation of negative temperature dependence of weight of the bodies, based on correlation of acceleration at thermal movement of micro-particles of a body and its absolute temperature, are given.

Keywords: Gravitation, temperature, weight.

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242 A New Damage Identification Strategy for SHM Based On FBGs and Bayesian Model Updating Method

Authors: Yanhui Zhang, Wenyu Yang

Abstract:

One of the difficulties of the vibration-based damage identification methods is the nonuniqueness of the results of damage identification. The different damage locations and severity may cause the identical response signal, which is even more severe for detection of the multiple damage. This paper proposes a new strategy for damage detection to avoid this nonuniqueness. This strategy firstly determines the approximates damage area based on the statistical pattern recognition method using the dynamic strain signal measured by the distributed fiber Bragg grating, and then accurately evaluates the damage information based on the Bayesian model updating method using the experimental modal data. The stochastic simulation method is then used to compute the high-dimensional integral in the Bayesian problem. Finally, an experiment of the plate structure, simulating one part of mechanical structure, is used to verify the effectiveness of this approach.

Keywords: Bayesian method, damage detection, fiber Bragg grating, structural health monitoring.

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241 Connect among Green, Sustainability and Hotel Industry: A Prospective Simulation Study

Authors: Leena N. Fukey, Surya S. Issac

Abstract:

This review paper aims at understanding the importance of implementing sustainable green practices in the current hotel industry and the perception of the same from the point of view of the customers as well as the industry experts. Many hotels have benefited from green management such as enhanced reputation of the firm and more worth customers. For the business standing, it reduces business’s cost for posting advertisements and the clear hotel’s orientation shows hotels’ positive image which might increase employees’ recognition toward the business. Sustainability in business is the growth in lively processes which enable people to understand the potential to protect the Earth’s existent support systems. Well, looking to the future today’s green concerns will definitely become facet of more synchronized business environment, perhaps the concerns discussed in this study, may exchange a few words which hotels may consider in near future to widen awareness and improve business model.

Keywords: Environmental Protection, Green Hotel Concept, Hotel Industry, Sustainability.

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240 Developing Damage Assessment Model for Bridge Surroundings: A Study of Disaster by Typhoon Morakot in Taiwan

Authors: Jieh-Haur Chen, Pei-Fen Huang

Abstract:

This paper presents an integrated model that automatically measures the change of rivers, damage area of bridge surroundings, and change of vegetation. The proposed model is on the basis of a neurofuzzy mechanism enhanced by SOM optimization algorithm, and also includes three functions to deal with river imagery. High resolution imagery from FORMOSAT-2 satellite taken before and after the invasion period is adopted. By randomly selecting a bridge out of 129 destroyed bridges, the recognition results show that the average width has increased 66%. The ruined segment of the bridge is located exactly at the most scour region. The vegetation coverage has also reduced to nearly 90% of the original. The results yielded from the proposed model demonstrate a pinpoint accuracy rate at 99.94%. This study brings up a successful tool not only for large-scale damage assessment but for precise measurement to disasters.

Keywords: remote sensing image, damage assessment, typhoon disaster, bridge, ANN, fuzzy, SOM, optimization.

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239 Hand Gesture Recognition: Sign to Voice System (S2V)

Authors: Oi Mean Foong, Tan Jung Low, Satrio Wibowo

Abstract:

Hand gesture is one of the typical methods used in sign language for non-verbal communication. It is most commonly used by people who have hearing or speech problems to communicate among themselves or with normal people. Various sign language systems have been developed by manufacturers around the globe but they are neither flexible nor cost-effective for the end users. This paper presents a system prototype that is able to automatically recognize sign language to help normal people to communicate more effectively with the hearing or speech impaired people. The Sign to Voice system prototype, S2V, was developed using Feed Forward Neural Network for two-sequence signs detection. Different sets of universal hand gestures were captured from video camera and utilized to train the neural network for classification purpose. The experimental results have shown that neural network has achieved satisfactory result for sign-to-voice translation.

Keywords: Hand gesture detection, neural network, signlanguage, sequence detection.

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238 Night-Time Traffic Light Detection Based On SVM with Geometric Moment Features

Authors: Hyun-Koo Kim, Young-Nam Shin, Sa-gong Kuk, Ju H. Park, Ho-Youl Jung

Abstract:

This paper presents an effective traffic lights detection method at the night-time. First, candidate blobs of traffic lights are extracted from RGB color image. Input image is represented on the dominant color domain by using color transform proposed by Ruta, then red and green color dominant regions are selected as candidates. After candidate blob selection, we carry out shape filter for noise reduction using information of blobs such as length, area, area of boundary box, etc. A multi-class classifier based on SVM (Support Vector Machine) applies into the candidates. Three kinds of features are used. We use basic features such as blob width, height, center coordinate, area, area of blob. Bright based stochastic features are also used. In particular, geometric based moment-s values between candidate region and adjacent region are proposed and used to improve the detection performance. The proposed system is implemented on Intel Core CPU with 2.80 GHz and 4 GB RAM and tested with the urban and rural road videos. Through the test, we show that the proposed method using PF, BMF, and GMF reaches up to 93 % of detection rate with computation time of in average 15 ms/frame.

Keywords: Night-time traffic light detection, multi-class classification, driving assistance system.

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237 GA Based Optimal Feature Extraction Method for Functional Data Classification

Authors: Jun Wan, Zehua Chen, Yingwu Chen, Zhidong Bai

Abstract:

Classification is an interesting problem in functional data analysis (FDA), because many science and application problems end up with classification problems, such as recognition, prediction, control, decision making, management, etc. As the high dimension and high correlation in functional data (FD), it is a key problem to extract features from FD whereas keeping its global characters, which relates to the classification efficiency and precision to heavens. In this paper, a novel automatic method which combined Genetic Algorithm (GA) and classification algorithm to extract classification features is proposed. In this method, the optimal features and classification model are approached via evolutional study step by step. It is proved by theory analysis and experiment test that this method has advantages in improving classification efficiency, precision and robustness whereas using less features and the dimension of extracted classification features can be controlled.

Keywords: Classification, functional data, feature extraction, genetic algorithm, wavelet.

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236 An Efficient Technique for Extracting Fuzzy Rulesfrom Neural Networks

Authors: Besa Muslimi, Miriam A. M. Capretz, Jagath Samarabandu

Abstract:

Artificial neural networks (ANN) have the ability to model input-output relationships from processing raw data. This characteristic makes them invaluable in industry domains where such knowledge is scarce at best. In the recent decades, in order to overcome the black-box characteristic of ANNs, researchers have attempted to extract the knowledge embedded within ANNs in the form of rules that can be used in inference systems. This paper presents a new technique that is able to extract a small set of rules from a two-layer ANN. The extracted rules yield high classification accuracy when implemented within a fuzzy inference system. The technique targets industry domains that possess less complex problems for which no expert knowledge exists and for which a simpler solution is preferred to a complex one. The proposed technique is more efficient, simple, and applicable than most of the previously proposed techniques.

Keywords: fuzzy rule extraction, fuzzy systems, knowledgeacquisition, pattern recognition, artificial neural networks.

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235 Automatic Light Control in Domotics using Artificial Neural Networks

Authors: Carlos Machado, José A. Mendes

Abstract:

Home Automation is a field that, among other subjects, is concerned with the comfort, security and energy requirements of private homes. The configuration of automatic functions in this type of houses is not always simple to its inhabitants requiring the initial setup and regular adjustments. In this work, the ubiquitous computing system vision is used, where the users- action patterns are captured, recorded and used to create the contextawareness that allows the self-configuration of the home automation system. The system will try to free the users from setup adjustments as the home tries to adapt to its inhabitants- real habits. In this paper it is described a completely automated process to determine the light state and act on them, taking in account the users- daily habits. Artificial Neural Network (ANN) is used as a pattern recognition method, classifying for each moment the light state. The work presented uses data from a real house where a family is actually living.

Keywords: ANN, Home Automation, Neural Systems, PatternRecognition, Ubiquitous Computing.

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234 Eyeball Motion Controlled Wheelchair Using IR Sensors

Authors: Monika Jain, Shikhar Puri, Shivali Unishree

Abstract:

This paper presents the ‘Eye Ball Motion Controlled Wheelchair using IR Sensors’ for the elderly and differently abled people. In this eye tracking based technology, three Proximity Infrared (IR) sensor modules are mounted on an eye frame to trace the movement of the iris. Since, IR sensors detect only white objects; a unique sequence of digital bits is generated corresponding to each eye movement. These signals are then processed via a micro controller IC (PIC18F452) to control the motors of the wheelchair. The potential and efficiency of previously developed rehabilitation systems that use head motion, chin control, sip-n-puff control, voice recognition, and EEG signals variedly have also been explored in detail. They were found to be inconvenient as they served either limited usability or non-affordability. After multiple regression analyses, the proposed design was developed as a cost-effective, flexible and stream-lined alternative for people who have trouble adopting conventional assistive technologies.

Keywords: Eye tracking technology, Intelligent wheelchair, IR module, rehabilitation technology.

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233 Real-World PM, PN and NOx Emission Differences among DOC+CDPF Retrofit Diesel-, Diesel- and Natural Gas-Fueled Buses

Authors: Zhiwen Yang, Jingyuan Li, Zhenkai Xie, Jian Ling, Jiguang Wang, Mengliang Li

Abstract:

To reflect the influence of after-treatment system retrofit and natural gas-fueled vehicle replace on exhaust emissions emitted by urban buses, a portable emission measurement system (PEMS) was employed herein to conduct real driving emission measurements. This study investigated the differences in particle number (PN), particle mass (PM), and nitrogen oxides (NOx) emissions from a China IV diesel bus retrofitted by catalyzed diesel particulate filter (CDPF), a China IV diesel bus, and a China V natural gas bus. The results show that both tested diesel buses possess markedly advantages in NOx emission control when compared to the lean-burn natural gas bus equipped without any NOx after-treatment system. As to PN and PM, only the DOC+CDPF retrofitting diesel bus exhibits enormous benefits on emission control related to the natural gas bus, especially the normal diesel bus. Meanwhile, the differences in PM and PN emissions between retrofitted and normal diesel buses generally increase with the increase in vehicle specific power (VSP). Furthermore, the differences in PM emissions, especially those in the higher VSP ranges, are more significant than those in PN. In addition, the maximum peak PN particle size (32 nm) of the retrofitted diesel bus was significantly lower than that of the normal diesel bus (100 nm). These phenomena indicate that the CDPF retrofitting can effectively reduce diesel bus exhaust particle emissions, especially those with large particle sizes.

Keywords: CDPF, diesel, natural gas, real-world emissions.

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232 Information and Communication Technologies in Collaboration Projects via the Internet

Authors: Murat Öztok, Nesrin Özdener

Abstract:

The aim of this study is to determine the basic information and communication technology (ICT) skills that may be needed by students studying in the 8th grade of the primary education in their cooperative project works implemented via the Internet. Within the scope of the study, the curriculum used for European Computer Driving License (ECDL) and the curriculum used in Turkey are also compared in terms of the ability to use ICT, which is aimed to be provided to the students. The research population of the study, during which the pre test – post test control group experimental model was used, consisted of 40 students from three different schools. In the first stage of the study, the skills that might be needed by students for their cooperative project works implemented via the Internet were determined through examination of the completed Comenious, e – twinning and WorldLinks projects. In the second stage of the study, the curriculums of the Turkish Ministry of National Education (MEB) and ECDL were evaluated by seven different teachers in line with these skills. Also in this study the ECDL and MEB curriculums were compared in terms of capability to provide the skills to implement cooperative projects via the Internet. In line with the findings of the study, the skills that might be needed by students to implement cooperative projects via the Internet were outlined, and existence of a significant difference was established in favor of the ECDL curriculum upon comparison of both curriculums in accordance with this outline (U = 50,500; p <0,05). The findings of the study also suggested that the students had considerable deficiencies in implementation of cooperative projects via the Internet without the ICT infrastructure.

Keywords: Collaboration Projects, Comenius, Curriculum, ICT.

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231 Real-Time Testing of Steel Strip Welds based on Bayesian Decision Theory

Authors: Julio Molleda, Daniel F. García, Juan C. Granda, Francisco J. Suárez

Abstract:

One of the main trouble in a steel strip manufacturing line is the breakage of whatever weld carried out between steel coils, that are used to produce the continuous strip to be processed. A weld breakage results in a several hours stop of the manufacturing line. In this process the damages caused by the breakage must be repaired. After the reparation and in order to go on with the production it will be necessary a restarting process of the line. For minimizing this problem, a human operator must inspect visually and manually each weld in order to avoid its breakage during the manufacturing process. The work presented in this paper is based on the Bayesian decision theory and it presents an approach to detect, on real-time, steel strip defective welds. This approach is based on quantifying the tradeoffs between various classification decisions using probability and the costs that accompany such decisions.

Keywords: Classification, Pattern Recognition, ProbabilisticReasoning, Statistical Data Analysis.

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230 A Saltwater Battery Inspired by the Membrane Potential Found in Biological Cells

Authors: Andrew Jester, Ross Lee, Pritpal Singh

Abstract:

As the world transitions to a more sustainable energy economy, the deployment of energy storage technologies is expected to increase to develop a more resilient grid system. However, current technologies are associated with various environmental and safety issues throughout their entire lifecycle; therefore, a new battery technology is desirable for grid applications to curtail these risks. Biological cells, such as human neurons and electrocytes in the electric eel, can serve as a more sustainable design template for a new bio-inspired (i.e., biomimetic) battery. Within biological cells, an electrochemical gradient across the cell membrane forms the membrane potential, which serves as the driving force for ion transport into/out of the cell akin to the charging/discharging of a battery cell. This work serves as the first step for developing such a biomimetic battery cell, starting with the fabrication and characterization of ion-selective membranes to facilitate ion transport through the cell. Performance characteristics (e.g., cell voltage, power density, specific energy, roundtrip efficiency) for the cell under investigation are compared to incumbent battery technologies and biological cells to assess the readiness level for this emerging technology. Using a Na+-Form Nafion-117 membrane, the cell in this work successfully demonstrated behavior like human neurons; these findings will inform how cell components can be re-engineered to enhance device performance.

Keywords: Battery, biomimetic, electrocytes, human neurons, ion-selective membranes, membrane potential.

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229 Human Motion Capture: New Innovations in the Field of Computer Vision

Authors: Najm Alotaibi

Abstract:

Human motion capture has become one of the major area of interest in the field of computer vision. Some of the major application areas that have been rapidly evolving include the advanced human interfaces, virtual reality and security/surveillance systems. This study provides a brief overview of the techniques and applications used for the markerless human motion capture, which deals with analyzing the human motion in the form of mathematical formulations. The major contribution of this research is that it classifies the computer vision based techniques of human motion capture based on the taxonomy, and then breaks its down into four systematically different categories of tracking, initialization, pose estimation and recognition. The detailed descriptions and the relationships descriptions are given for the techniques of tracking and pose estimation. The subcategories of each process are further described. Various hypotheses have been used by the researchers in this domain are surveyed and the evolution of these techniques have been explained. It has been concluded in the survey that most researchers have focused on using the mathematical body models for the markerless motion capture.

Keywords: Human Motion Capture, Computer Vision, Vision based, Tracking.

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228 Data Mining on the Router Logs for Statistical Application Classification

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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227 Precision Control of Single-Phase PWM Inverter Using M68HC11E Microcontroller

Authors: Khaled A. Madi

Abstract:

Induction motors are being used in greater numbers throughout a wide variety of industrial and commercial applications because it provides many benefits and reliable device to convert the electrical energy into mechanical motion. In some application it-s desired to control the speed of the induction motor. Because of the physics of the induction motor the preferred method of controlling its speed is to vary the frequency of the AC voltage driving the motor. In recent years, with the microcontroller incorporated into an appliance it becomes possible to use it to generate the variable frequency AC voltage to control the speed of the induction motor. This study investigates the microcontroller based variable frequency power inverter. the microcontroller is provide the variable frequency pulse width modulation (PWM) signal that control the applied voltage on the gate drive, which is provides the required PWM frequency with less harmonics at the output of the power inverter. The fully controlled bridge voltage source inverter has been implemented with semiconductors power devices isolated gate bipolar transistor (IGBT), and the PWM technique has been employed in this inverter to supply the motor with AC voltage. The proposed drive system for three & single phase power inverter is simulated using Matlab/Simulink. The Matlab Simulation Results for the proposed system were achieved with different SPWM. From the result a stable variable frequency inverter over wide range has been obtained and a good agreement has been found between the simulation and hardware of a microcontroller based single phase inverter.

Keywords: Power, inverter, PWM, microcontroller.

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226 Wildfires Assessed by Remote Sense Images and Burned Land Monitoring

Authors: M. C. Proença

Abstract:

The tools described in this paper enable the location of burned areas where took place the annihilation of natural habitats and establishes a baseline for major changes in forest ecosystems during recovery. Moreover, the result allows the follow up of the surface fuel loading, allowing the evaluation and guidance of restoration measures to remote areas by phased time planning. This case study implements the evaluation of burned areas that suffered successive wildfires in Portugal mainland during the summer of 2017, killing more than 60 people. The goal is to show that this evaluation can be done with remote sense data free of charges in a simple laptop, with open-source software, describing the not-so-simple methodology step by step, to make it accessible for local workers in the areas attained, where the availability of information is essential for the immediate planning of mitigation measures, such as restoring road access, allocate funds for the recovery of human dwellings and assess further needs for restoration of the ecological system. Wildfires also devastate forest ecosystems having a direct impact on vegetation cover and killing or driving away the animal population, besides loss of all crops in rural areas that are essential as local resources. The economic interests are also attained, as the pinewood burned becomes useless for the noblest applications, so its value decreases, and resin extraction ends for several years.

Keywords: Image processing, remote sensing, wildfires, burned areas, SENTINEL-2.

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225 A Quantitative Study on Japanese Internet User's Awareness to Information Security: Necessity and Importance of Education and Policy

Authors: Toshihiko Takemura, Atsushi Umino

Abstract:

In this paper, the authors examine whether or not there Institute for Information and Communications Policy shows are differences of Japanese Internet users awareness to information security based on individual attributes by using analysis of variance based on non-parametric method. As a result, generally speaking, it is found that Japanese Internet users' awareness to information security is different by individual attributes. Especially, the authors verify that the users who received the information security education would have rather higher recognition concerning countermeasures than other users including self-educated users. It is suggested that the information security education should be enhanced so that the users may appropriately take the information security countermeasures. In addition, the information security policy such as carrying out "e- net caravan" and "information security seminars" are effective in improving the users' awareness on the information security in Japan.

Keywords: Information security education, variance of analysis, Internet users, information security policy, Web-based survey.

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224 Using Machine Learning Techniques for Autism Spectrum Disorder Analysis and Detection in Children

Authors: Norah Alshahrani, Abdulaziz Almaleh

Abstract:

Autism Spectrum Disorder (ASD) is a condition related to issues with brain development that affects how a person recognises and communicates with others which results in difficulties with interaction and communication socially and it is constantly growing. Early recognition of ASD allows children to lead safe and healthy lives and helps doctors with accurate diagnoses and management of conditions. Therefore, it is crucial to develop a method that will achieve good results and with high accuracy for the measurement of ASD in children. In this paper, ASD datasets of toddlers and children have been analyzed. We employed the following machine learning techniques to attempt to explore ASD: Random Forest (RF), Decision Tree (DT), Na¨ıve Bayes (NB) and Support Vector Machine (SVM). Then feature selection was used to provide fewer attributes from ASD datasets while preserving model performance. As a result, we found that the best result has been provided by SVM, achieving 0.98% in the toddler dataset and 0.99% in the children dataset.

Keywords: Autism Spectrum Disorder, ASD, Machine Learning, ML, Feature Selection, Support Vector Machine, SVM.

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223 Downtrend Algorithm and Hedging Strategy in Futures Market

Authors: S. Masteika, A.V. Rutkauskas, A. Tamosaitis

Abstract:

The paper investigates downtrend algorithm and trading strategy based on chart pattern recognition and technical analysis in futures market. The proposed chart formation is a pattern with the lowest low in the middle and one higher low on each side. The contribution of this paper lies in the reinforcement of statements about the profitability of momentum trend trading strategies. Practical benefit of the research is a trading algorithm in falling markets and back-test analysis in futures markets. When based on daily data, the algorithm has generated positive results, especially when the market had downtrend period. Downtrend algorithm can be applied as a hedge strategy against possible sudden market crashes. The proposed strategy can be interesting for futures traders, hedge funds or scientific researchers performing technical or algorithmic market analysis based on momentum trend trading.

Keywords: trading algorithm, chart pattern, downtrend trading, futures market, hedging

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222 A Neuro-Automata Decision Support System for the Control of Late Blight in Tomato Crops

Authors: Gizelle K. Vianna, Gustavo S. Oliveira, Gabriel V. Cunha

Abstract:

The use of decision support systems in agriculture may help monitoring large fields of crops by automatically detecting the symptoms of foliage diseases. In our work, we designed and implemented a decision support system for small tomatoes producers. This work investigates ways to recognize the late blight disease from the analysis of digital images of tomatoes, using a pair of multilayer perceptron neural networks. The networks outputs are used to generate repainted tomato images in which the injuries on the plant are highlighted, and to calculate the damage level of each plant. Those levels are then used to construct a situation map of a farm where a cellular automata simulates the outbreak evolution over the fields. The simulator can test different pesticides actions, helping in the decision on when to start the spraying and in the analysis of losses and gains of each choice of action.

Keywords: Artificial neural networks, cellular automata, decision support system, pattern recognition.

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221 Challenges and Opportunities of Utilization of Social Media by Business Education Students in Nigeria Universities

Authors: Titus Amodu Umoru

Abstract:

Global economy today is full of sophistication. All over the world, business and marketing practices are undergoing unprecedented transformation. In realization of this fact, the federal government of Nigeria has put in place a robust transformation agenda in order to put Nigeria in a better position to be a competitive player and in the process transform all sectors of its economy. New technologies, especially the Internet, are the driving force behind this transformation. However, technology has inadvertently affected the way businesses are done thus necessitating the acquisition of new skills. In developing countries like Nigeria, citizens are still battling with effective application of those technologies. Obviously, students of business education need to acquire relevant business knowledge to be able to transit into the world of work on graduation from school and compete favorably in the labor market. Therefore, effective utilization of social media by both teachers and students can help extensively in empowering students with the needed skills. Social media which is a group of Internet-based applications built on the ideological foundations of Web 2.0, that allow the creation and exchange of user generated content, and if incorporated into the classroom experience may be the needed answer to unemployment and poverty in Nigeria as beneficiaries can easily connect with existing and potential enterprises and customers, engage with them and reinforce mutual business benefits. Challenges and benefits of social media use in education in Nigeria universities were revealed in this study.

Keywords: Challenges, opportunities, utilization, social media, business education.

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220 Context Generation with Image Based Sensors: An Interdisciplinary Enquiry on Technical and Social Issues and their Implications for System Design

Authors: Julia Moehrmann, Gunter Heidemann, Oliver Siemoneit, Christoph Hubig, Uwe-Philipp Kaeppeler, Paul Levi

Abstract:

Image data holds a large amount of different context information. However, as of today, these resources remain largely untouched. It is thus the aim of this paper to present a basic technical framework which allows for a quick and easy exploitation of context information from image data especially by non-expert users. Furthermore, the proposed framework is discussed in detail concerning important social and ethical issues which demand special requirements in system design. Finally, a first sensor prototype is presented which meets the identified requirements. Additionally, necessary implications for the software and hardware design of the system are discussed, rendering a sensor system which could be regarded as a good, acceptable and justifiable technical and thereby enabling the extraction of context information from image data.

Keywords: Context-aware computing, ethical and social issues, image recognition, requirements in system design.

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