Search results for: Neural network training

Authors: Ruibiao J. Guo, Brad Cain, Pierre Meunier

Abstract:

The Integrated Performance Modelling Environment (IPME) is a powerful simulation engine for task simulation and performance analysis. However, it has no high level cognition such as memory and reasoning for complex simulation. This article introduces a knowledge representation and reasoning scheme that can accommodate uncertainty in simulations of military personnel with IPME. This approach demonstrates how advanced reasoning models that support similarity-based associative process, rule-based abstract process, multiple reasoning methods and real-time interaction can be integrated with conventional task network modelling to provide greater functionality and flexibility when modelling operator performance.

Keywords: Computer-Generated Forces, Human Behaviour Representation, IPME, Modelling and Simulation, Uncertainty Reasoning

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Authors: Yong-Hui Li, Jing-Wen Huang

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As the advancement of technology, online shopping channel develops rapidly in recent years. According to the report of Taiwan Network Information Center, there are almost eighty percents of internet population shopping in online channel. Synthesizing insights from the previous research, this study develops the conceptual model to integrate Theory of Perceived Risk (TPR) and Technology Acceptance Model (TAM) to apply in online shopping. Using data collected from 637 respondents from online survey website, we use structural equation modeling to test measurement and structural models. The results suggest the need for consideration of perceived risk as an antecedent in the Technology Acceptance Model. The limitations and implications are discussed.

Keywords: perceived risk, perceived usefulness, perceived ease of use, behavioral intention, actual purchase behavior

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Authors: S. Shirazian, M.R. Ghayamghamian, G.R. Nouri

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Bridges are one of the main components of transportation networks. They should be functional before and after earthquake for emergency services. Therefore we need to assess seismic performance of bridges under different seismic loadings. Fragility curve is one of the popular tools in seismic evaluations. The fragility curves are conditional probability statements, which give the probability of a bridge reaching or exceeding a particular damage level for a given intensity level. In this study, the seismic performance of a two-span simply supported concrete bridge is assessed. Due to usual lack of empirical data, the analytical fragility curve was developed by results of the dynamic analysis of bridge subjected to the different time histories in near-fault area.

Keywords: Fragility curve, Seismic behavior, Time historyanalysis, Transportation Network.

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Authors: M. Kasumović, A. Hodžić, M. Tešanović

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One way for optimum loading of overdimensioning conveyers is speed (capacity) decrement, with attention for production capabilities and demands. At conveyers which drives with three phase slip-ring induction motor, technically reasonable solution for conveyer (driving motors) speed regulation is using constant torque subsynchronous cascade with static semiconductor converter and transformer for energy reversion to the power network. In the paper is described mathematical model for parameter calculation of two-motors 6 kV subsynchronous cascade. It is also demonstrated that applying of this cascade gave several good properties, foremost in electrical energy saving, also in improving of other energy indexes, and finally that results in cost reduction of complete electrical motor drive.

Keywords: Conveyer with rubber belt, electrical motor drive, sub synchronous cascade

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Authors: Marwan Ihsan Shukur, Lee Sheng Chyan, Vooi Voon Yap

Abstract:

Wireless sensor networks is an emerging technology that serves as environment monitors in many applications. Yet these miniatures suffer from constrained resources in terms of computation capabilities and energy resources. Limited energy resource in these nodes demands an efficient consumption of that resource either by developing the modules itself or by providing an efficient communication protocols. This paper presents a comprehensive summarization and a comparative study of the available MAC protocols proposed for Wireless Sensor Networks showing their capabilities and efficiency in terms of energy consumption and delay guarantee.

Keywords: MAC (Medium Access Control), SEA (Simple EnergyAware), WSNs (Wireless Sensor Nodes or Networks) RTS (RequestTo Send), CTS (Clear To Send), SYNCH (Synchronize), NS2(Network Simulator 2).

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Authors: Mahmood Q.K. Ghaznavi, Martin Perry, Paul Toulson, Keri Logan

Abstract:

The importance of nurturing, accumulating, and efficiently deploying knowledge resources through formal structures and organisational mechanisms is well understood. Recent trends in knowledge management (KM) highlight that the effective creation and transfer of knowledge can also rely upon extra-organisational channels, such as, informal networks. The perception exists that the role of informal networks in knowledge creation and performance has been underestimated in the organisational context. Literature indicates that many managers fail to comprehend and successfully exploit the potential role of informal networks to create value for their organisations. This paper investigates: 1) whether managers share work-specific knowledge with informal contacts within and outside organisational boundaries; and 2) what do they think is the importance of this knowledge collaboration in their learning and work outcomes.

Keywords: Informal network, knowledge management, knowledge sharing, performance.

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Authors: Sujala.D.Shetty, S.Vadivel, Sakshi Vaghella

Abstract:

Data mining is the process of sifting through large volumes of data, analyzing data from different perspectives and summarizing it into useful information. One of the widely used desktop applications for data mining is the Weka tool which is nothing but a collection of machine learning algorithms implemented in Java and open sourced under the General Public License (GPL). A web service is a software system designed to support interoperable machine to machine interaction over a network using SOAP messages. Unlike a desktop application, a web service is easy to upgrade, deliver and access and does not occupy any memory on the system. Keeping in mind the advantages of a web service over a desktop application, in this paper we are demonstrating how this Java based desktop data mining application can be implemented as a web service to support data mining across the internet.

Keywords: desktop application, Weka mining, web service

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Authors: Zoltan Theisz, Gergely Mezei

Abstract:

Modern industrial automation relies on service oriented concepts of Internet of Things (IoT) device modeling in order to provide a flexible and extendable environment for service meta-repository. However, state-of-the-art meta-modeling techniques prefer design-time modeling, which results in a heavy usage of class sometimes unnecessary static subtyping. Although this approach benefits from clear-cut object-oriented design principles, it also seals the model repository for further dynamic extensions. In this paper, a dynamic multi-level modeling approach is introduced that enables dynamic subtyping through a more relaxed partial instantiation mechanism. The approach is demonstrated on a simple sensor network example.

Keywords: Meta-modeling, dynamic subtyping, DMLA, industrial automation, arrowhead.

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Authors: Bremananth R., Veerabadran C. S., Andy W. H. Khong

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Automatic reading of handwritten cheque is a computationally complex process and it plays an important role in financial risk management. Machine vision and learning provide a viable solution to this problem. Research effort has mostly been focused on recognizing diverse pitches of cheques and demand drafts with an identical outline. However most of these methods employ templatematching to localize the pitches and such schemes could potentially fail when applied to different types of outline maintained by the bank. In this paper, the so-called outline problem is resolved by a cheque information tree (CIT), which generalizes the localizing method to extract active-region-of-entities. In addition, the weight based density plot (WBDP) is performed to isolate text entities and read complete pitches. Recognition is based on texture features using neural classifiers. Legal amount is subsequently recognized by both texture and perceptual features. A post-processing phase is invoked to detect the incorrect readings by Type-2 grammar using the Turing machine. The performance of the proposed system was evaluated using cheque and demand drafts of 22 different banks. The test data consists of a collection of 1540 leafs obtained from 10 different account holders from each bank. Results show that this approach can easily be deployed without significant design amendments.

Keywords: Cheque reading, Connectivity checking, Text localization, Texture analysis, Turing machine, Signature verification.

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Authors: Sezen Yildirim, Tahir Çetin Akinci, Serhat Seker, Nazmi Ekren

Abstract:

Ferroresonance is an electrical phenomenon in nonlinear character, which frequently occurs in power system due to transmission line faults and single or more-phase switching on the lines as well as usage of the saturable transformers. In this study, the ferroresonance phenomena are investigated under the modeling of the West Anatolian Electric Power Network of 380 kV in Turkey. The ferroresonance event is observed as a result of removing the loads at the end of the lines. In this sense, two different cases are considered. At first, the switching is applied at 2nd second and the ferroresonance affects are observed between 2nd and 4th seconds in the voltage variations of the phase-R. Hence the ferroresonance and nonferroresonance parts of the overall data are compared with each others using the Fourier transform techniques to show the ferroresonance affects.

Keywords: Ferroresonance, West Anatolian Electric Power System, Power System Modeling, Switching, Spectral Analysis.

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Authors: A. Morsli, A.Tlemçani, N. Ould Cherchali, M. S. Boucherit

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This article presents two methods for the compensation of harmonics generated by a nonlinear load. The first is the classic method P-Q. The second is the controller by modern method of artificial intelligence specifically fuzzy logic. Both methods are applied to a shunt Active Power Filter (sAPF) based on a three-phase voltage converter at five levels NPC topology. In calculating the harmonic currents of reference, we use the algorithm P-Q and pulse generation, we use the intersective PWM. For flexibility and dynamics, we use fuzzy logic. The results give us clear that the rate of Harmonic Distortion issued by fuzzy logic is better than P-Q.

Keywords: Fuzzy logic controller, P-Q method, Pulse Width Modulation (PWM), shunt Active Power Filter (sAPF), Total Harmonic Distortion (THD).

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Authors: Sunitha. S.L., V. Udayashankara

Abstract:

Background noise is particularly damaging to speech intelligibility for people with hearing loss especially for sensorineural loss patients. Several investigations on speech intelligibility have demonstrated sensorineural loss patients need 5-15 dB higher SNR than the normal hearing subjects. This paper describes Discrete Cosine Transform Power Normalized Least Mean Square algorithm to improve the SNR and to reduce the convergence rate of the LMS for Sensory neural loss patients. Since it requires only real arithmetic, it establishes the faster convergence rate as compare to time domain LMS and also this transformation improves the eigenvalue distribution of the input autocorrelation matrix of the LMS filter. The DCT has good ortho-normal, separable, and energy compaction property. Although the DCT does not separate frequencies, it is a powerful signal decorrelator. It is a real valued function and thus can be effectively used in real-time operation. The advantages of DCT-LMS as compared to standard LMS algorithm are shown via SNR and eigenvalue ratio computations. . Exploiting the symmetry of the basis functions, the DCT transform matrix [AN] can be factored into a series of ±1 butterflies and rotation angles. This factorization results in one of the fastest DCT implementation. There are different ways to obtain factorizations. This work uses the fast factored DCT algorithm developed by Chen and company. The computer simulations results show superior convergence characteristics of the proposed algorithm by improving the SNR at least 10 dB for input SNR less than and equal to 0 dB, faster convergence speed and better time and frequency characteristics.

Keywords: Hearing Impairment, DCT Adaptive filter, Sensorineural loss patients, Convergence rate.

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Authors: Ibrahim Shaker, Amr El Hossany, Moustafa Osman, Mohamed El Raey

Abstract:

This paper will explore integration model between GIS–SCADA system and enclosure quantification model to approach the impact of failure-safe event. There are real demands to identify spatial objects and improve control system performance. Nevertheless, the employed methodology is predicting electro-mechanic operations and corresponding time to environmental incident variations. Open processing, as object systems technology, is presented for integration enclosure database with minimal memory size and computation time via connectivity drivers such as ODBC:JDBC during main stages of GIS–SCADA connection. The function of Geographic Information System is manipulating power distribution in contrast to developing issues. In other ward, GIS-SCADA systems integration will require numerical objects of process to enable system model calibration and estimation demands, determine of past events for analysis and prediction of emergency situations for response training.

Keywords: Air dispersion model, integration power system, SCADA systems, GIS system, environmental management.

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Authors: Jeff Clarine, Chang-Shyh Peng, Daisy Sang

Abstract:

Bioassay is the measurement of the potency of a chemical substance by its effect on a living animal or plant tissue. Bioassay data and chemical structures from pharmacokinetic and drug metabolism screening are mined from and housed in multiple databases. Bioassay prediction is calculated accordingly to determine further advancement. This paper proposes a four-step preprocessing of datasets for improving the bioassay predictions. The first step is instance selection in which dataset is categorized into training, testing, and validation sets. The second step is discretization that partitions the data in consideration of accuracy vs. precision. The third step is normalization where data are normalized between 0 and 1 for subsequent machine learning processing. The fourth step is feature selection where key chemical properties and attributes are generated. The streamlined results are then analyzed for the prediction of effectiveness by various machine learning algorithms including Pipeline Pilot, R, Weka, and Excel. Experiments and evaluations reveal the effectiveness of various combination of preprocessing steps and machine learning algorithms in more consistent and accurate prediction.

Keywords: Bioassay, machine learning, preprocessing, virtual screen.

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Authors: Hoda Molavi, Alireza Zahiri, Katayoon Anvarizadeh

Abstract:

Dissolved gas analysis has been accepted as a sensitive, informative and reliable technique for incipient faults detection in power transformers and is widely used. In the last few years this method, which has been recommended by IEEE Power & Energy society, has been applied for fault detection in load tap changers. Regarding the critical role of load tap changers in electrical network and essential of catastrophic failures prevention, it is necessary to choose "condition based preventative maintenance strategy" which leads to reduction in costs, the number of unnecessary visits as well as the probability of interruptions and also increment in equipment reliability. In current work, considering the condition based preventative maintenance strategy, condition assessment of an Elin tap changer was carried out using dissolved gas analysis.

Keywords: Condition Assessment, Dissolved Gas Analysis, Load Tap Changer

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Authors: Tessy Badriyah, Jim S. Briggs, Dave R. Prytherch

Abstract:

It is well known that Logistic Regression is the gold standard method for predicting clinical outcome, especially predicting risk of mortality. In this paper, the Decision Tree method has been proposed to solve specific problems that commonly use Logistic Regression as a solution. The Biochemistry and Haematology Outcome Model (BHOM) dataset obtained from Portsmouth NHS Hospital from 1 January to 31 December 2001 was divided into four subsets. One subset of training data was used to generate a model, and the model obtained was then applied to three testing datasets. The performance of each model from both methods was then compared using calibration (the χ2 test or chi-test) and discrimination (area under ROC curve or c-index). The experiment presented that both methods have reasonable results in the case of the c-index. However, in some cases the calibration value (χ2) obtained quite a high result. After conducting experiments and investigating the advantages and disadvantages of each method, we can conclude that Decision Trees can be seen as a worthy alternative to Logistic Regression in the area of Data Mining.

Keywords: Decision Trees, Logistic Regression, clinical outcome, risk of mortality.

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Authors: Ankit Sinha, Soham Banerjee, Pratik Chattopadhyay

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Automated product recognition in retail stores is an important real-world application in the domain of Computer Vision and Pattern Recognition. In this paper, we consider the problem of automatically identifying the classes of the products placed on racks in retail stores from an image of the rack and information about the query/product images. We improve upon the existing approaches in terms of effectiveness and memory requirement by developing a two-stage object detection and recognition pipeline comprising of a Faster-RCNN-based object localizer that detects the object regions in the rack image and a ResNet-18-based image encoder that classifies  the detected regions into the appropriate classes. Each of the models is fine-tuned using appropriate data sets for better prediction and data augmentation is performed on each query image to prepare an extensive gallery set for fine-tuning the ResNet-18-based product recognition model. This encoder is trained using a triplet loss function following the strategy of online-hard-negative-mining for improved prediction. The proposed models are lightweight and can be connected in an end-to-end manner during deployment to automatically identify each product object placed in a rack image. Extensive experiments using Grozi-32k and GP-180 data sets verify the effectiveness of the proposed model.

Keywords: Retail stores, Faster-RCNN, object localization, ResNet-18, triplet loss, data augmentation, product recognition.

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Authors: Sri Sumartiningsih

Abstract:

In elevating performance in competetive sports, an athlete must continously train in achieving maximum performance,but needs to pay attention to recovery therapy, that is to recover from fatigue as well as injury.The correct recovery therapy will assist in process of recovery and helps in the training in achieving better performace. Binahong (Anredera cordifolia) was proven empirically by the locals in assisting speedy recovery from an injury.Clinical research with lab animals receiving blunt trauma injury, microscopically shown signs of: 1) redness, 2) heatiness, 3) swelling and, 4) lack of activity. There is also microscopic indication of: 1) infiltration of inflame cells (migration of cells to the trauma area), 2) Cells necrosis, 3) Congestion (as a result of dead red blood cells), 4) uedema. On administration of Binahong for 3 days, there is a significant drop of 5% in cell inflammation, 2% increase of fibroblast (cell membrance) count.Conclutin: Binahong do assist in reducing cell inflammation and increase counts of cells fibroblast. Suggestion: In helping athlete's to recover from force injury, we need study about Binahong's roots to inflammation cell and healing of injuried cell.

Keywords: Binahong, sport injury, hematoma

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Authors: Hamed Rahmani, Wim Groot

Abstract:

The term "youth not in employment, education or training (NEET)" refers to a combination of youth unemployment and school dropout. This study investigates the variables that increase the risk of becoming NEET in Iran. A selection bias-adjusted Probit model was employed using machine learning to identify these risk factors. We used cross-sectional data obtained from the Statistical Center of Iran and the Ministry of Cooperatives Labor and Social Welfare that are taken from the labor force survey conducted in the spring of 2021. We look at years of education, work experience, housework, the number of children under the age of 6 years in the home, family education, birthplace, and the amount of land owned by households. Results show that hours spent performing domestic chores enhance the likelihood of youth becoming NEET, and years of education, years of potential work experience decrease the chance of being NEET. The findings also show that female youth born in cities were less likely than those born in rural regions to become NEET.

Keywords: NEET youth, probit, CART, machine learning, unemployment.

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Authors: V. Prapulla, A. Mitra, R. Bhattacharjee, S. Nandi

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We present a simplified equalization technique for a π/4 differential quadrature phase shift keying ( π/4 -DQPSK) modulated signal in a multipath fading environment. The proposed equalizer is realized as a fractionally spaced adaptive decision feedback equalizer (FS-ADFE), employing exponential step-size least mean square (LMS) algorithm as the adaptation technique. The main advantage of the scheme stems from the usage of exponential step-size LMS algorithm in the equalizer, which achieves similar convergence behavior as that of a recursive least squares (RLS) algorithm with significantly reduced computational complexity. To investigate the finite-precision performance of the proposed equalizer along with the π/4 -DQPSK modem, the entire system is evaluated on a 16-bit fixed point digital signal processor (DSP) environment. The proposed scheme is found to be attractive even for those cases where equalization is to be performed within a restricted number of training samples.

Keywords: Adaptive decision feedback equalizer, Fractionally spaced equalizer, π/4 DQPSK signal, Digital signal processor.

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Authors: Praseeda Lekshmi.V, Dr.M.Sasikumar

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Facial recognition and expression analysis is rapidly becoming an area of intense interest in computer science and humancomputer interaction design communities. The most expressive way humans display emotions is through facial expressions. In this paper skin and non-skin pixels were separated. Face regions were extracted from the detected skin regions. Facial expressions are analyzed from facial images by applying Gabor wavelet transform (GWT) and Discrete Cosine Transform (DCT) on face images. Radial Basis Function (RBF) Network is used to identify the person and to classify the facial expressions. Our method reliably works even with faces, which carry heavy expressions.

Keywords: Face Recognition, Radial Basis Function, Gabor Wavelet Transform, Discrete Cosine Transform

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Authors: Najmeh Abedzadeh, Matthew Jacobs

Abstract:

An intrusion detection system (IDS) is a software application that monitors malicious activities and generates alerts if any are detected. However, most network activities in IDS datasets are normal, and the relatively few numbers of attacks make the available data imbalanced. Consequently, cyber-attacks can hide inside a large number of normal activities, and machine learning algorithms have difficulty learning and classifying the data correctly. In this paper, a comprehensive literature review is conducted on different types of algorithms for both implementing the IDS and methods in correcting the imbalanced IDS dataset. The most famous algorithms are machine learning (ML), deep learning (DL), synthetic minority over-sampling technique (SMOTE), and reinforcement learning (RL). Most of the research use the CSE-CIC-IDS2017, CSE-CIC-IDS2018, and NSL-KDD datasets for evaluating their algorithms.

Keywords: IDS, intrusion detection system, imbalanced datasets, sampling algorithms, big data.

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Authors: Samir Abdelhamid, Noureddine Bouguechal

Abstract:

We report in this paper the model adopted by our system of continuous speech recognition in Arab language SySRA and the results obtained until now. This system uses the database Arabdic-10 which is a corpus of word for the Arab language and which was manually segmented. Phonetic decoding is represented by an expert system where the knowledge base is translated in the form of production rules. This expert system transforms a vocal signal into a phonetic lattice. The higher level of the system takes care of the recognition of the lattice thus obtained by deferring it in the form of written sentences (orthographical Form). This level contains initially the lexical analyzer which is not other than the module of recognition. We subjected this analyzer to a set of spectrograms obtained by dictating a score of sentences in Arab language. The rate of recognition of these sentences is about 70% which is, to our knowledge, the best result for the recognition of the Arab language. The test set consists of twenty sentences from four speakers not having taken part in the training.

Keywords: Continuous speech recognition, lexical analyzer, phonetic decoding, phonetic lattice, vocal signal.

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Authors: A.Shokri, A.Faraahi

Abstract:

Here are many methods for designing and implementation of virtual laboratories, because of their special features. The most famous architectural designs are based on the events. This model of architecting is so efficient for virtual laboratories implemented on a local network. Later, serviceoriented architecture, gave the remote access ability to them and Peer-To-Peer architecture, hired to exchanging data with higher quality and more speed. Other methods, such as Agent- Based architecting, are trying to solve the problems of distributed processing in a complicated laboratory system. This study, at first, reviews the general principles of designing a virtual laboratory, and then compares the different methods based on EDA, SOA and Agent-Based architecting to present weaknesses and strengths of each method. At the end, we make the best choice for design, based on existing conditions and requirements.

Keywords: Virtual Laboratory, Software Engineering, Simulation, EDA, SOA, Agent-Based Architecting.

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Authors: R. Mangiaracina, A. Perego, F. Campari

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Despite the fact that B2c eCommerce has become important in numerous economies, its adoption varies from country to country. This paper aims to identify the factors affecting (enabling or inhibiting) B2c eCommerce and to determine their quantitative impact on the diffusion of online sales across countries. A dynamic panel model analyzing the relationship between 13 factors (Macroeconomic, Demographic, Socio-Cultural, Infrastructural and Offer related) stemming from a complete literature analysis and the B2c eCommerce value in 45 countries over 9 years has been developed. Having a positive correlation coefficient, GDP, mobile penetration, Internet user penetration and credit card penetration resulted as enabling drivers of the B2c eCommerce value across countries, whereas, having a negative correlation coefficient,equal distribution of income and the development of traditional retailing network act as inhibiting factors.

Keywords: B2c eCommerce diffusion, influencing factors, dynamic panel model

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Authors: Peristera Baziana

Abstract:

In this paper, we present a network configuration for a WDM LANs of passive star topology that assume that the set of data WDM channels is split into two separate sets of channels, with different access rights over them. Especially, a synchronous transmission WDMA access algorithm is adopted in order to increase the probability of successful transmission over the data channels and consequently to reduce the probability of data packets transmission cancellation in order to avoid the data channels collisions. Thus, a control pre-transmission access scheme is followed over a separate control channel. An analytical Markovian model is studied and the average throughput is mathematically derived. The performance is studied for several numbers of data channels and various values of control phase duration.

Keywords: Access algorithm, channels division, collisions avoidance, wavelength division multiplexing.

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Authors: Nadjah Chergui, Narhimene Boustia

Abstract:

Intrusion Detection Systems are an essential tool for network security infrastructure. However, IDSs have a serious problem which is the generating of massive number of alerts, most of them are false positive ones which can hide true alerts and make the analyst confused to analyze the right alerts for report the true attacks. The purpose behind this paper is to present a formalism model to perform correlation engine by the reduction of false positive alerts basing on vulnerability contextual information. For that, we propose a formalism model based on non-monotonic JClassicδє description logic augmented with a default (δ) and an exception (є) operator that allows a dynamic inference according to contextual information.

Keywords: Context, exception, default, IDS, Non-monotonic Description Logic JClassicδє, vulnerability.

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Authors: Hong Pan, Yaping Zhu, Liang Zheng Xia

Abstract:

We propose a fast and robust hierarchical face detection system which finds and localizes face images with a cascade of classifiers. Three modules contribute to the efficiency of our detector. First, heterogeneous feature descriptors are exploited to enrich feature types and feature numbers for face representation. Second, a PSO-Adaboost algorithm is proposed to efficiently select discriminative features from a large pool of available features and reinforce them into the final ensemble classifier. Compared with the standard exhaustive Adaboost for feature selection, the new PSOAdaboost algorithm reduces the training time up to 20 times. Finally, a three-stage hierarchical classifier framework is developed for rapid background removal. In particular, candidate face regions are detected more quickly by using a large size window in the first stage. Nonlinear SVM classifiers are used instead of decision stump functions in the last stage to remove those remaining complex nonface patterns that can not be rejected in the previous two stages. Experimental results show our detector achieves superior performance on the CMU+MIT frontal face dataset.

Keywords: Adaboost, Face detection, Feature selection, PSO

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Authors: P. Suparada, D. Eakapotch

Abstract:

This research’s objectives were to analyze the using of new media in the form of set up candid clip that affects the product and presenter, to study the effectiveness of using new media in the form of set up candid clip in order to increase the circulation and audience satisfaction and to use the earned information and knowledge to develop the communication for publicizing and advertising via new media. This research is qualitative research based on questionnaire from 50 random sampling representative samples and in-depth interview from experts in publicizing and advertising fields. The findings indicated the positive and negative effects to the brands’ image and presenters’ image of product named “Scotch 100” and “Snickers” that used set up candid clips via new media for publicizing and advertising in Thailand. It will be useful for fields of publicizing and advertising in the new media forms.

Keywords: Candid Clip, Effect, New Media, Social Network.

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Authors: M. Benbouzid, Q. Bresson, A. Duclos, K. Longo, Q. Morel

Abstract:

Currently, electricity suppliers must predict the consumption of their customers in order to deduce the power they need to produce. It is then important in a first step to optimize household consumptions to obtain more constant curves by limiting peaks in energy consumption. Here centralized real time scheduling is proposed to manage the equipments starting in parallel. The aim is not to exceed a certain limit while optimizing the power consumption across a habitat. The Raspberry Pi is used as a box; this scheduler interacts with the various sensors in 6LoWPAN. At the scale of a single dwelling, household consumption decreases, particularly at times corresponding to the peaks. However, it would be wiser to consider the use of a residential complex so that the result would be more significant. So the ceiling would no longer be fixed. The scheduling would be done on two scales, on the one hand per dwelling, and secondly, at the level of a residential complex.

Keywords: Smart grid, Energy box, Scheduling, Gang Model, Energy consumption, Energy management system, and Wireless Sensor Network.

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