Search results for: Mobile ad hoc network (MANET)

Authors: Sahar Khedr, Dina Sayed, Ayman Hanafy

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Arabic is one of the most ancient and critical languages in the world. It has over than 250 million Arabic native speakers and more than twenty countries having Arabic as one of its official languages. In the past decade, we have witnessed a rapid evolution in smart devices, social network and technology sector which led to the need to provide tools and libraries that properly tackle the Arabic language in different domains. Stemming is one of the most crucial linguistic fundamentals. It is used in many applications especially in information extraction and text mining fields. The motivation behind this work is to enhance the Arabic light stemmer to serve the data mining industry and leverage it in an open source community. The presented implementation works on enhancing the Arabic light stemmer by utilizing and enhancing an algorithm that provides an extension for a new set of rules and patterns accompanied by adjusted procedure. This study has proven a significant enhancement for better search accuracy with an average 10% improvement in comparison with previous works.

Keywords: Arabic data mining, Arabic Information extraction, Arabic Light stemmer, Arabic stemmer.

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Authors: B. Prebreza, I. Krasniqi, G. Kabashi, G. Pula, N. Avdiu

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This paper discusses aspects of outages in the electric transmission network in the Kosovo Power System caused by the atmospheric discharges.

Frequency and location of the atmospheric discharges in Kosovo territory will be provided by a lightning location system ALARM (Automated Lightning Alert and Risk Management) and from the data from the Meteorological Department in Prishtina International Airport. These data will be used to make comparisons with the actual outages registered in the Kosovo Power System from the Kosovo Transmission, systems and market operator (KOSTT) during a specific time period.

The lines with the worst performance determined, regarding the atmospheric discharges, will be choose for further discussions in terms of over voltages caused by the direct or indirect lightning strokes.

Recommendations for protection in terms of insulator coordination and surge arresters will be given at the end and in this stage dynamic simulation will take part.

Keywords: Atmospheric discharges, dynamic simulations, Kosovo Power System, surge arresters.

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Authors: Kwok Tak Kit

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With the growing trend of adoption of advanced technologies like, building information modeling, artificial intelligence, wireless network, the collaboration and integration of these technologies into digital twin become more prominent in architecture, engineering and construction (AEC) industry in view of the nature and scale of AEC industry which efficiently adopted the digital twin. Digital twin is provided to be effective for AEC professions for design and project management. The digital concept is continuously developing and it is vital for AEC professionals and other stakeholders to understand the digital twin concept and the adoption of various advanced building technologies related to the AEC industry. This paper is to review the application of digital twins application in project management in AEC industry and highlight the challenge of AEC partitioners faced by the revolution of technologies including digital twins and building information modelling (BIM) for further research and future study.

Keywords: Digital Twin, AEC, building information modeling, project management, internet of things.

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Authors: Arellano Karina, Diego Avila-Pesántez, Leticia Vaca-Cárdenas, Alberto Arellano, Carmen Mantilla

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Nowadays, security threats in Voice over IP (VoIP) systems are an essential and latent concern for people in charge of security in a corporate network, because, every day, new Denial-of-Service (DoS) attacks are developed. These affect the business continuity of an organization, regarding confidentiality, availability, and integrity of services, causing frequent losses of both information and money. The purpose of this study is to establish the necessary measures to mitigate DoS threats, which affect the availability of VoIP systems, based on the Session Initiation Protocol (SIP). A Security Model called MS-DoS-SIP is proposed, which is based on two approaches. The first one analyzes the recommendations of international security standards. The second approach takes into account weaknesses and threats. The implementation of this model in a VoIP simulated system allowed to minimize the present vulnerabilities in 92% and increase the availability time of the VoIP service into an organization.

Keywords: Denial-of-service SIP attacks, MS-DoS-SIP, security model, VoIP-SIP vulnerabilities.

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Authors: Tarek M. Mahmoud

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Selecting the routes and the assignment of link flow in a computer communication networks are extremely complex combinatorial optimization problems. Metaheuristics, such as genetic or simulated annealing algorithms, are widely applicable heuristic optimization strategies that have shown encouraging results for a large number of difficult combinatorial optimization problems. This paper considers the route selection and hence the flow assignment problem. A genetic algorithm and simulated annealing algorithm are used to solve this problem. A new hybrid algorithm combining the genetic with the simulated annealing algorithm is introduced. A modification of the genetic algorithm is also introduced. Computational experiments with sample networks are reported. The results show that the proposed modified genetic algorithm is efficient in finding good solutions of the flow assignment problem compared with other techniques.

Keywords: Genetic Algorithms, Flow Assignment, Routing, Computer network, Simulated Annealing.

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Authors: P. Pongsumpun, I. M. Tang

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Malaria is a serious, acute and chronic relapsing infection to humans. It is characterized by periodic attacks of chills, fever, nausea, vomiting, back pain, increased sweating anemia, splenomegaly (enlargement of the spleen) and often-fatal complications.The malaria disease is caused by the multiplication of protozoa parasite of the genus Plasmodium. Malaria in humans is due to 4 types of malaria parasites such that Plasmodium falciparum, Plasmodium vivax, Plasmodium malariae and Plasmodium ovale. P.vivax malaria differs from P. falciparum malaria in that a person suffering from P. vivax malaria can experience relapses of the disease. Between the relapses, the malaria parasite will remain dormant in the liver of the patient, leading to the patient being classified as being in the dormant class. A mathematical model for the transmission of P. vivax is developed in which the human population is divided into four classes, the susceptible, the infected, the dormant and the recovered. In this paper, we formulate the dynamical model of P. vivax malaria to see the distribution of this disease at the district level.

Keywords: Dynamical model, household, local level, Plasmodium Vivax Malaria.

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Authors: L. Piñeiro, N. Cobas, L. Gómez-Limia, S. Martínez, I. Franco

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The swordfish (Xiphias gladius) is a large oceanic fish of high commercial value, which is widely distributed in waters of the world’s oceans. They are considered to be an important source of high quality proteins, vitamins and essential fatty acids, although only half of the population follows the recommendation of nutritionists to consume fish at least twice a week. Swordfish is consumed worldwide because of its low fat content and high protein content. It is generally sold as fresh, frozen, and as pieces or slices. The aim of this study was to evaluate the effect of salting and frying on the composition of the water-soluble vitamins (B₂, B₃, B₉ and B₁₂) and fat-soluble vitamins (A, D, and E) of swordfish. Three loins of swordfish from Pacific Ocean were analyzed. All the fishes had a weight between 50 and 70 kg and were transported to the laboratory frozen (-18 ºC). Before the processing, they were defrosted at 4 ºC. Each loin was sliced and salted in brine. After cleaning the slices, they were divided into portions (10×2 cm) and fried in olive oil. The identification and quantification of vitamins were carried out by high-performance liquid chromatography (HPLC), using methanol and 0.010% trifluoroacetic acid as mobile phases at a flow-rate of 0.7 mL min^-1. The UV-Vis detector was used for the detection of the water- and fat-soluble vitamins (A and D), as well as the fluorescence detector for the detection of the vitamin E. During salting, water and fat-soluble vitamin contents remained constant, observing an evident decrease in the values of vitamin B₂. The diffusion of salt into the interior of the pieces and the loss of constitution water that occur during this stage would be related to this significant decrease. In general, after frying water-soluble and fat-soluble vitamins showed a great thermolability with high percentages of retention with values among 50–100%. Vitamin B₃ is the one that exhibited higher percentages of retention with values close to 100%. However, vitamin B₉ presented the highest losses with a percentage of retention of less than 20%.

Keywords: Frying, HPLC, salting, swordfish, vitamins.

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Authors: Dai Zhimei, Hua Chen

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The exploration of urban spatial evolution is an important part of urban development research. Therefore, the evolutionary modern Yangzhou urban spatial texture was taken as the research object, and Spatial Syntax was used as the main research tool, this paper explored Yangzhou spatial evolution law and its driving factors from the urban street network scale, district scale and street scale. The study has concluded that at the urban scale, Yangzhou urban spatial evolution is the result of a variety of causes, including physical and geographical condition, policy and planning factors, and traffic conditions, and the evolution of space also has an impact on social, economic, environmental and cultural factors. At the district and street scales, changes in space will have a profound influence on the history of the city and the activities of people. At the end of the article, the matters needing attention during the evolution of urban space were summarized.

Keywords: Space Syntax, spatial texture, urban space, Yangzhou.

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Authors: P. Subbaraj, V. Rajasekaran

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This paper presents a new approach using Combined Artificial Neural Network (CANN) module for daily peak load forecasting. Five different computational techniques –Constrained method, Unconstrained method, Evolutionary Programming (EP), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA) – have been used to identify the CANN module for peak load forecasting. In this paper, a set of neural networks has been trained with different architecture and training parameters. The networks are trained and tested for the actual load data of Chennai city (India). A set of better trained conventional ANNs are selected to develop a CANN module using different algorithms instead of using one best conventional ANN. Obtained results using CANN module confirm its validity.

Keywords: Combined ANN, Evolutionary Programming, Particle Swarm Optimization, Genetic Algorithm and Peak load forecasting.

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Authors: Ni Hong, Wu Guobin, Wu Gang, Pan Liang

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Interactive push VOD system is a new kind of system that incorporates push technology and interactive technique. It can push movies to users at high speeds at off-peak hours for optimal network usage so as to save bandwidth. This paper presents effective software-based solution for processing mass downstream data at terminals of interactive push VOD system, where the service can download movie according to a viewer-s selection. The downstream data is divided into two catalogs: (1) the carousel data delivered according to DSM-CC protocol; (2) IP data delivered according to Euro-DOCSIS protocol. In order to accelerate download speed and reduce data loss rate at terminals, this software strategy introduces caching, multi-thread and resuming mechanisms. The experiments demonstrate advantages of the software-based solution.

Keywords: DSM-CC, data carousel, Euro-DOCSIS, push VOD.

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Authors: K. M. Doraiswamy, Lakshminarayana Merugu, B. C. Jinaga

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This paper explains the cause of nonlinearity in floor attenuation hither to left unexplained. The performance degradation occurring in air interface for GSM signals is quantitatively analysed using the concept of Radiating Columns of buildings. The signal levels were measured using Wireless Network Optimising Drive Test Tool (E6474A of Agilent Technologies). The measurements were taken in reflected signal environment under usual fading conditions on actual GSM signals radiated from base stations. A mathematical model is derived from the measurements to predict the GSM signal levels in different floors. It was applied on three buildings and found that the predicted signal levels deviated from the measured levels with in +/- 2 dB for all floors. It is more accurate than the prediction models based on Floor Attenuation Factor. It can be used for planning proper indoor coverage in multi storey buildings.

Keywords: GSM air interface, nonlinear attenuation, multistory building, radiating columns, ground conduction and floor attenuation factor.

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Authors: Carlos Machado, José A. Mendes

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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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Authors: Lv Wei-feng, Dai Xi, Zhu Tong-yu

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Dynamic location referencing method is an important technology to shield map differences. These method references objects of the road network by utilizing condensed selection of its real-world geographic properties stored in a digital map database, which overcomes the defections existing in pre-coded location referencing methods. The high attributes completeness requirements and complicated reference point selection algorithm are the main problems of recent researches. Therefore, a dynamic location referencing algorithm combining intersection points selected at the extremities compulsively and road link points selected according to link partition principle was proposed. An experimental system based on this theory was implemented. The tests using Beijing digital map database showed satisfied results and thus verified the feasibility and practicability of this method.

Keywords: Dynamic location referencing, inter-sectionreferencing, road link partition, road link point referencing.

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Authors: A. Faro, D. Giordano, F. Maiorana

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Data mining uses a variety of techniques each of which is useful for some particular task. It is important to have a deep understanding of each technique and be able to perform sophisticated analysis. In this article we describe a tool built to simulate a variation of the Kohonen network to perform unsupervised clustering and support the entire data mining process up to results visualization. A graphical representation helps the user to find out a strategy to optmize classification by adding, moving or delete a neuron in order to change the number of classes. The tool is also able to automatically suggest a strategy for number of classes optimization.The tool is used to classify macroeconomic data that report the most developed countries? import and export. It is possible to classify the countries based on their economic behaviour and use an ad hoc tool to characterize the commercial behaviour of a country in a selected class from the analysis of positive and negative features that contribute to classes formation.

Keywords: Unsupervised classification, Kohonen networks, macroeconomics, Visual data mining, cluster interpretation.

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Authors: Pedro J. Muñoz Merino, Natividad Martínez Madrid, Ralf E. D. Seepold

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On one hand, SNMP (Simple Network Management Protocol) allows integrating different enterprise elements connected through Internet into a standardized remote management. On the other hand, as a consequence of the success of Intelligent Houses they can be connected through Internet now by means of a residential gateway according to a common standard called OSGi (Open Services Gateway initiative). Due to the specifics of OSGi Service Platforms and their dynamic nature, specific design criterions should be defined to implement SNMP Agents for OSGi in order to integrate them into the SNMP remote management. Based on the analysis of the relation between both standards (SNMP and OSGi), this paper shows how OSGi Service Platforms can be included into the SNMP management of a global enterprise, giving implementation details about an SNMP Agent solution and the definition of a new MIB (Management Information Base) for managing OSGi platforms that takes into account the specifics and dynamic nature of OSGi.

Keywords: MIB, OSGi, Remote Management, SNMP.

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

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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: A. O. Oluwajobi, O. A. Falusi, N. A. Zubbair, T. Owoeye, F. Ladejobi, M. C. Dangana, A. Abubakar

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The technology of mobile telephony has positively enhanced human life and reports on the bio safety of the radiation from their antennae have been contradictory, leading to serious litigations and violent protests by residents in several parts of the world. The crave for more information, as requested by WHO in order to resolve this issue, formed the basis for this study on the effect of the radiation from 900 MHz GSM antenna on the DNA of Hibiscus sabdariffa. Seeds of H. sabdariffa were raised in pots placed in three replicates at 100, 200, 300 and 400 metres from the GSM antennae in three selected test locations and a control where there was no GSM signal. Temperature (˚C) and the relative humidity (%) of study sites were measured for the period of study (24 weeks). Fresh young leaves were harvested from each plant at two, eight and twenty-four weeks after sowing and the DNA extracts were subjected to RAPD-PCR analyses. There were no significant differences between the weather conditions (temperature and relative humidity) in all the study locations. However, significant differences were observed in the intensities of radiations between the control (less than 0.02 V/m) and the test (0.40-1.01 V/m) locations. Data obtained showed that DNA of samples exposed to rays from GSM antenna had various levels of distortions, estimated at 91.67%. Distortions occurred in 58.33% of the samples between 2-8 weeks of exposure while 33.33% of the samples were distorted between 8-24 weeks exposure. Approximately 8.33% of the samples did not show distortions in DNA while 33.33% of the samples had their DNA damaged twice, both at 8 and at 24 weeks of exposure. The study showed that radiation from the 900 MHz GSM antenna is potent enough to cause distortions to DNA of H. sabdariffa even within 2-8 weeks of exposure. DNA damage was also independent of the distance from the antenna. These observations would qualify emissions from GSM mast as environmental hazard to the existence of plant biodiversities and all life forms in general. These results will trigger efforts to prevent further erosion of plant genetic resources which have been threatening food security and also the risks posed to living organisms, thereby making our environment very safe for our existence while we still continue to enjoy the benefits of the GSM technology.

Keywords: Damage, DNA, GSM antenna, radiation.

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Authors: Shivakumar, G. S. Vijay, P. Srinivas Pai, B. R. Shrinivasa Rao

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In the present study, RBF neural networks were used for predicting the performance and emission parameters of a biodiesel engine. Engine experiments were carried out in a 4 stroke diesel engine using blends of diesel and Honge methyl ester as the fuel. Performance parameters like BTE, BSEC, Tex and emissions from the engine were measured. These experimental results were used for ANN modeling. RBF center initialization was done by random selection and by using Clustered techniques. Network was trained by using fixed and varying widths for the RBF units. It was observed that RBF results were having a good agreement with the experimental results. Networks trained by using clustering technique gave better results than using random selection of centers in terms of reduced MRE and increased prediction accuracy. The average MRE for the performance parameters was 3.25% with the prediction accuracy of 98% and for emissions it was 10.4% with a prediction accuracy of 80%.

Keywords: Radial Basis Function networks, emissions, Performance parameters, Fuzzy c means.

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Authors: David Tena-Gago, Jose M. Alcaraz Calero, Qi Wang

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The evolution and integration of automated vehicles have become more and more tangible in recent years. State-of-the-art technological advances in the field of camera-based Artificial Intelligence (AI) and computer vision greatly favor the performance and reliability of Advanced Driver Assistance System (ADAS), leading to a greater knowledge of vehicular operation and resembling the human behaviour. However, the exclusive use of this technology still seems insufficient to control the vehicular operation at 100%. To reveal the degree of accuracy of the current camera-based automated driving AI modules, this paper studies the structure and behavior of one of the main solutions in a controlled testing environment. The results obtained clearly outline the lack of reliability when using exclusively the AI model in the perception stage, thereby entailing using additional complementary sensors to improve its safety and performance.

Keywords: Accuracy assessment, AI-Driven Mobility, Artificial Intelligence, automated vehicles.

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Authors: Basma M. Mohammad El-Basioni, Sherine M. Abd El-kader, Hussein S. Eissa

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This paper proposes an implementation for the directed diffusion paradigm aids in studying this paradigm-s operations and evaluates its behavior according to this implementation. The directed diffusion is evaluated with respect to the loss percentage, lifetime, end-to-end delay, and throughput. From these evaluations some suggestions and modifications are proposed to improve the directed diffusion behavior according to this implementation with respect to these metrics. The proposed modifications reflect the effect of local path repair by introducing a technique called Loop-free Local Path Repair (LLPR) which improves the directed diffusion behavior especially with respect to packet loss percentage by about 92.69%. Also LLPR improves the throughput and end-to-end delay by about 55.31% and 14.06% respectively, while the lifetime decreases by about 29.79%.

Keywords: Attribute-value based naming scheme, data gathering, data-centric routing, energy-efficiency, locality, wireless sensor network.

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Authors: Amit Sachan

Abstract:

The purpose of this paper is to acquire the remote electrical parameters like Voltage, Current, and Frequency from Smart grid and send these real time values over GSM network using GSM Modem/phone along with temperature at power station. This project is also designed to protect the electrical circuitry by operating an Electromagnetic Relay. The Relay can be used to operate a Circuit Breaker to switch off the main electrical supply. User can send commands in the form of SMS messages to read the remote electrical parameters. This system also can automatically send the real time electrical parameters periodically (based on time settings) in the form of SMS. This system also send SMS alerts whenever the Circuit Breaker trips or whenever the Voltage or Current exceeds the predefined limits.

Keywords: GSM Modem, Initialization of ADC module of microcontroller, PIC-C compiler for Embedded C programming, PIC kit 2 programmer for dumping code into Micro controller, Express SCH for Circuit design, Proteus for hardware simulation.

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Authors: V. T. S. Dao, T. G. Etoh, C. Vo Le, H. D. Nguyen, K. Takehara, T. Akino, K. Nishi

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We present an explicit expression to estimate driving voltage attenuation through RC networks representation of an ultrahigh- speed image sensor. Elmore delay metric for a fundamental RC chain is employed as the first-order approximation. By application of dimensional analysis to SPICE simulation data, we found a simple expression that significantly improves the accuracy of the approximation. Estimation error of the resultant expression for uniform RC networks is less than 2%. Similarly, another simple closed-form model to estimate 50 % delay through fundamental RC networks is also derived with sufficient accuracy. The framework of this analysis can be extended to address delay or attenuation issues of other VLSI structures.

Keywords: Dimensional Analysis, Elmore model, RC network, Signal Attenuation, Ultra-High-Speed Image Sensor.

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Authors: Chien-Chun Hung, Chun-Fong Wu

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It is important for a commander to have real-time information to aware situations and to make decision in the battlefield. Results of modern technique developments have brought in this kind of information for military purposes. Unmanned aerial vehicle (UAV) is one of the means to gather intelligence owing to its widespread applications. It is still not clear whether or not the mini UAV with short-range wireless transmission system is used as a reconnaissance system in Taiwanese. In this paper, previous experience on the research of the sort of aerial vehicles has been applied with a data-relay system using the ZigBee modulus. The mini UAV developed is expected to be able to collect certain data in some appropriate theaters. The omni-directional antenna with high gain is also integrated into mini UAV to fit the size-reducing trend of airborne sensors. Two advantages are so far obvious. First, mini UAV can fly higher than usual to avoid being attacked from ground fires. Second, the data will be almost gathered during all maneuvering attitudes.

Keywords: Mini UAV, reconnaissance, wireless transmission, ZigBee modulus.

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Authors: Sergio Luna, Raquel Rodríguez-Carvajal

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This research examines the effectiveness of a mindfulness-based intervention in optimizing psychological well-being, with a particular focus on self-esteem, due to the rapid growth and consolidation of social network use and the increased frequency and intensity of upward comparisons of the self. The study aims to assess the potential of a mindfulness-based intervention to improve self-esteem and, in particular, to contribute to its greater stability by reducing levels of contingent self-esteem. Results show that an 8-week mindfulness-based stress reduction program was effective in increasing participants' (n = 206) trait mindfulness, explicit self-esteem, and well-being, while decreasing contingent self-esteem. Furthermore, the study found that improvements in both explicit and contingent self-esteem were significantly correlated with increases in psychological well-being, but that contingent self-esteem had a stronger effect on well-being than explicit self-esteem. These findings highlight the importance of considering additional dimensions of self-esteem beyond levels and suggest that mindfulness-based interventions may be a valuable tool for promoting a healthier form of self-esteem that contributes to personal well-being.

Keywords: Mindfulness-based stress reduction, contingent self-esteem, explicit self-esteem, well-being.

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Authors: S. Sendilkumar, B. L. Mathur, Joseph Henry

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A new approach for protection of power transformer is presented using a time-frequency transform known as Wavelet transform. Different operating conditions such as inrush, Normal, load, External fault and internal fault current are sampled and processed to obtain wavelet coefficients. Different Operating conditions provide variation in wavelet coefficients. Features like energy and Standard deviation are calculated using Parsevals theorem. These features are used as inputs to PNN (Probabilistic neural network) for fault classification. The proposed algorithm provides more accurate results even in the presence of noise inputs and accurately identifies inrush and fault currents. Overall classification accuracy of the proposed method is found to be 96.45%. Simulation of the fault (with and without noise) was done using MATLAB AND SIMULINK software taking 2 cycles of data window (40 m sec) containing 800 samples. The algorithm was evaluated by using 10 % Gaussian white noise.

Keywords: Power Transformer, differential Protection, internalfault, inrush current, Wavelet Energy, Db9.

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Authors: Martin Roth, Axel Klarmann, Bogdan Franczyk

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The importance of logistics has changed enormously in the last few decades. While logistics was formerly one of the core functions of most companies, logistics or at least parts of their functions are nowadays outsourced to external logistic service providers in terms of contracts. As a result of this shift new business models like the fourth party logistics provider emerged, which designs, plans and monitors the resulting logistics networks. This new business model and topics such as Synchromodality or Big Data impose new requirements on the underlying IT, which cannot be met with conventional concepts and approaches. In this paper, the challenges of logistics network monitoring are outlined by using a scenario. The most common layers in a logical multilayered architecture for an information system are used to point out the arising challenges for IT. In addition, first appropriate solution approaches are introduced.

 

Keywords: Complex Event Processing, Fourth Party Logistics Service Provider, Logistics monitoring, Synchromodality.

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Authors: Mohamed R. Mhereeg

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The paper discusses the design of a .NET Windows Service based agent system called MACS (Multi-Agent Classification System). MACS is a system aims to accurately classify spreadsheet developers competency over a network. It is designed to automatically and autonomously monitor spreadsheet users and gather their development activities based on the utilization of the software multi-agent technology (MAS). This is accomplished in such a way that makes management capable to efficiently allow for precise tailor training activities for future spreadsheet development. The monitoring agents of MACS are intended to be distributed over the WWW in order to satisfy the monitoring and classification of the multiple developer aspect. The Prometheus methodology is used for the design of the agents of MACS. Prometheus has been used to undertake this phase of the system design because it is developed specifically for specifying and designing agent-oriented systems. Additionally, Prometheus specifies also the communication needed between the agents in order to coordinate to achieve their delegated tasks.

Keywords: Classification, Design, MACS, MAS, Prometheus.

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Authors: Sulata Maharana, B Biswas, Adity Ganguly, Ashok Kumar

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In this paper, the requirement for Coke quality prediction, its role in Blast furnaces, and the model output is explained. By applying method of Artificial Neural Networking (ANN) using back propagation (BP) algorithm, prediction model has been developed to predict CSR. Important blast furnace functions such as permeability, heat exchanging, melting, and reducing capacity are mostly connected to coke quality. Coke quality is further dependent upon coal characterization and coke making process parameters. The ANN model developed is a useful tool for process experts to adjust the control parameters in case of coke quality deviations. The model also makes it possible to predict CSR for new coal blends which are yet to be used in Coke Plant. Input data to the model was structured into 3 modules, for tenure of past 2 years and the incremental models thus developed assists in identifying the group causing the deviation of CSR.

Keywords: Artificial Neural Networks, backpropagation, CokeStrength after Reaction, Multilayer Perceptron.

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Authors: K.M. Faraoun, A. Boukelif

Abstract:

This paper describes a new approach of classification using genetic programming. The proposed technique consists of genetically coevolving a population of non-linear transformations on the input data to be classified, and map them to a new space with a reduced dimension, in order to get a maximum inter-classes discrimination. The classification of new samples is then performed on the transformed data, and so become much easier. Contrary to the existing GP-classification techniques, the proposed one use a dynamic repartition of the transformed data in separated intervals, the efficacy of a given intervals repartition is handled by the fitness criterion, with a maximum classes discrimination. Experiments were first performed using the Fisher-s Iris dataset, and then, the KDD-99 Cup dataset was used to study the intrusion detection and classification problem. Obtained results demonstrate that the proposed genetic approach outperform the existing GP-classification methods [1],[2] and [3], and give a very accepted results compared to other existing techniques proposed in [4],[5],[6],[7] and [8].

Keywords: Genetic programming, patterns classification, intrusion detection

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Authors: P. Kumsawat, K. Pasitwilitham, K. Attakitmongcol, A. Srikaew

Abstract:

In this paper, an artificial intelligent technique for robust digital image watermarking in multiwavelet domain is proposed. The embedding technique is based on the quantization index modulation technique and the watermark extraction process does not require the original image. We have developed an optimization technique using the genetic algorithms to search for optimal quantization steps to improve the quality of watermarked image and robustness of the watermark. In addition, we construct a prediction model based on image moments and back propagation neural network to correct an attacked image geometrically before the watermark extraction process begins. The experimental results show that the proposed watermarking algorithm yields watermarked image with good imperceptibility and very robust watermark against various image processing attacks.

Keywords: Watermarking, Multiwavelet, Quantization index modulation, Genetic algorithms, Neural networks.

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