Search results for: Information technology

Authors: O. Abiodun Adeyinka, B. Adeyemo Adesesan

Abstract:

The forensic use of handwriting depends on the analysis, comparison, and evaluation decisions made by forensic document examiners. When using biometric technology in forensic applications, it is necessary to compute Likelihood Ratio (LR) for quantifying strength of evidence under two competing hypotheses, namely the prosecution and the defense hypotheses wherein a set of assumptions and methods for a given data set will be made. It is therefore important to know how repeatable and reproducible our estimated LR is. This paper evaluated the accuracy and reproducibility of examiners' decisions. Confidence interval for the estimated LR were presented so as not get an incorrect estimate that will be used to deliver wrong judgment in the court of Law. The estimate of LR is fundamentally a Bayesian concept and we used two LR estimators, namely Logistic Regression (LoR) and Kernel Density Estimator (KDE) for this paper. The repeatability evaluation was carried out by retesting the initial experiment after an interval of six months to observe whether examiners would repeat their decisions for the estimated LR. The experimental results, which are based on handwriting dataset, show that LR has different confidence intervals which therefore implies that LR cannot be estimated with the same certainty everywhere. Though the LoR performed better than the KDE when tested using the same dataset, the two LR estimators investigated showed a consistent region in which LR value can be estimated confidently. These two findings advance our understanding of LR when used in computing the strength of evidence in handwriting using forensics.

Keywords: Logistic Regression LoR, Kernel Density Estimator KDE, Handwriting, Confidence Interval, Repeatability, Reproducibility.

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Authors: Charawee Butbumrung

Abstract:

The purpose of this study is to evaluate the monetary worthiness of investment and the usefulness of risk estimation as a tool employed by a production section of an electronic factory. This study employed the case study of accidents occurring in production areas. Data is collected from interviews with six production of safety coordinators and collect the information from the relevant section. The study will present the ratio of benefits compared with the operation costs for investment. The result showed that it is worthwhile for investment with the safety measures. In addition, the organizations must be able to analyze the causes of accidents about the benefits of investing in protective working process. They also need to quickly provide the manual for the staff to learn how to protect themselves from accidents and how to use all of the safety equipment.

Keywords: Cost and benefit, enterprises in Thailand, investment in safety and health, risk estimation.

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Authors: S.K. Mazloomi, Nasri b. Sulaiman

Abstract:

By analyzing the sources of energy and power loss in PWM (Pulse Width Modulation) controlled drivers of water electrolysis cells, it is possible to reduce the power dissipation and enhance the efficiency of such hydrogen production units. A PWM controlled power driver is based on a semiconductor switching element where its power dissipation might be a remarkable fraction of the total power demand of an electrolysis system. Power dissipation in a semiconductor switching element is related to many different parameters which could be fitted into two main categories: switching losses and conduction losses. Conduction losses are directly related to the built, structure and capabilities of a switching device itself and indeed the conditions in which the element is handling the switching application such as voltage, current, temperature and of course the fabrication technology. On the other hand, switching losses have some other influencing variables other than the mentioned such as control system, switching method and power electronics circuitry of the PWM power driver. By analyzings the characteristics of recently developed power switching transistors from different families of Bipolar Junction Transistors (BJT), Metal Oxide Semiconductor Field Effect Transistors (MOSFET) and Insulated Gate Bipolar Transistors (IGBT), some recommendations are made in this paper which are able to lead to achieve higher hydrogen production efficiency by utilizing PWM controlled water electrolysis cells.

Keywords: Power switch, PWM, Semiconductor switch, Waterelectrolysis

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Authors: Faizal A. Samman, Thomas Hollstein, Manfred Glesner

Abstract:

A synchronous network-on-chip using wormhole packet switching and supporting guaranteed-completion best-effort with low-priority (LP) and high-priority (HP) wormhole packet delivery service is presented in this paper. Both our proposed LP and HP message services deliver a good quality of service in term of lossless packet completion and in-order message data delivery. However, the LP message service does not guarantee minimal completion bound. The HP packets will absolutely use 100% bandwidth of their reserved links if the HP packets are injected from the source node with maximum injection. Hence, the service are suitable for small size messages (less than hundred bytes). Otherwise the other HP and LP messages, which require also the links, will experience relatively high latency depending on the size of the HP message. The LP packets are routed using a minimal adaptive routing, while the HP packets are routed using a non-minimal adaptive routing algorithm. Therefore, an additional 3-bit field, identifying the packet type, is introduced in their packet headers to classify and to determine the type of service committed to the packet. Our NoC prototypes have been also synthesized using a 180-nm CMOS standard-cell technology to evaluate the cost of implementing the combination of both services.

Keywords: Network-on-Chip, Parallel Pipeline Router Architecture, Wormhole Switching, Two-Level Priority Service.

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Authors: Guillermo Romero-Jiménez, Luis A. Jiménez-Fraustro, Mayolo Salinas-Camacho, Heriberto Avalos-Valenzuela

Abstract:

A geothermal power plant multiple simulator for operators training is presented. The simulator is designed to be installed in a wireless local area network and has a capacity to train one to six operators simultaneously, each one with an independent simulation session. The sessions must be supervised only by one instructor. The main parts of this multiple simulator are: instructor and operator-s stations. On the instructor station, the instructor controls the simulation sessions, establishes training exercises and supervises each power plant operator in individual way. This station is hosted in a Main Personal Computer (NS) and its main functions are: to set initial conditions, snapshots, malfunctions or faults, monitoring trends, and process and soft-panel diagrams. On the other hand the operators carry out their actions over the power plant simulated on the operator-s stations; each one is also hosted in a PC. The main software of instructor and operator-s stations are executed on the same NS and displayed in PCs through graphical Interactive Process Diagrams (IDP). The geothermal multiple simulator has been installed in the Geothermal Simulation Training Center (GSTC) of the Comisi├│n Federal de Electricidad, (Federal Commission of Electricity, CFE), Mexico, and is being utilized as a part of the training courses for geothermal power plant operators.

Keywords: Geothermal power plant, multiple simulator, training operator.

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Authors: Dimitrios E. Kontaxis, George Litainas, Dimitrios P. Ptochos, Vaggelis P. Ptochos, Sotirios P. Ptochos, Dimitrios Beletsis, Konstantinos Kritikakis, Milan Sunaric

Abstract:

Real-time monitoring of the supply chain conditions and procedures is a critical element for the optimal coordination and safety of the deliveries, as well as for the minimization of the delivery time and cost. Real time monitoring requires IoT data streams, which are related to the conditions of the products and the means of transport (e.g., location, temperature/humidity conditions, kinematic state, ambient light conditions, etc.). These streams are generated by battery-based IoT tracking devices, equipped with appropriate sensors, and are transmitted to a cloud-based back-end system. Proper handling and processing of the IoT data streams, using predictive and artificial intelligence algorithms, can provide significant and useful results, which can be exploited by the supply chain stakeholders in order to enhance their financial benefits, as well as the efficiency, security, transparency, coordination and sustainability of the supply chain procedures. The technology, the features and the characteristics of a complete, proprietary system, including hardware, firmware and software tools - developed in the context of a co-funded R&D program - are addressed and presented in this paper. 

Keywords: IoT embedded electronics, real-time monitoring, tracking device, sensor platform

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Authors: Nitish Sharma, G. G. Karady

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This paper presents a scheme for the protection of loop system from all type of faults using the direction of fault current. The presence of distributed generation in today’s system increases the complexity of fault detection as the power flow is bidirectional. Hence, protection scheme specific to this purpose needs to be developed. This paper shows a fast protection scheme using communication which can be fiber optic or wireless. In this paper, the possibility of wireless communication for protection is studied to exchange the information between the relays. The negative sequence and positive sequence directional elements are used to determine the direction of fault current. A PSCAD simulation is presented and validated using commercial SEL relays.

Keywords: Smart grid protection, pilot protection, power system simulation, wireless communication.

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Authors: Ryuya Uda

Abstract:

On existing online shopping on the web, SSL and password are usually used to achieve the secure trades. SSL shields communication from the third party who is not related with the trade, and indicates that the trader's web site is authenticated by one of the certification authority. Password certifies a customer as the same person who has visited the trader's web site before, and protects the customer's privacy such as what the customer has bought on the site. However, there is no forensics for the trades in those cased above. With existing methods, no one can prove what is ordered by customers, how many products are ordered and even whether customers have ordered or not. The reason is that the third party has to guess what were traded with logs that are held by traders and by customers. The logs can easily be created, deleted and forged since they are electronically stored. To enhance security with digital forensics for electronic commerce on the web, I indicate a secure method with cellular phones.

Keywords: Cellular Phone, Digital Forensics, ElectronicCommerce, Information Security

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Authors: Adnan Muharemovic, Hidajet Salkic, Mario Klaric, Irfan Turkovic, Aida Muharemovic

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In nature, electromagnetic fields always appear like atmosphere static electric field, the earth's static magnetic field and the wide-rang frequency electromagnetic field caused by lightening. However, besides natural electromagnetic fields (EMF), today human beings are mostly exposed to artificial electromagnetic fields due to technology progress and outspread use of electrical devices. To evaluate nuisance of EMF, it is necessary to know field intensity for every frequency which appears and compare it with allowed values. Low frequency EMF-s around transmission and distribution lines are time-varying quasi-static electromagnetic fields which have conservative component of low frequency electrical field caused by charges and eddy component of low frequency magnetic field caused by currents. Displacement current or field delay are negligible, so energy flow in quasi-static EMF involves diffusion, analog like heat transfer. Electrical and magnetic field can be analyzed separately. This paper analysis the numerical calculations in ELF-400 software of EMF in distribution substation in shopping center. Analyzing the results it is possible to specify locations exposed to the fields and give useful suggestion to eliminate electromagnetic effect or reduce it on acceptable level within the non-ionizing radiation norms and norms of protection from EMF.

Keywords: Electromagnetic Field, Density of Electromagnetic Flow, Place of Proffesional Exposure, Place of Increased Sensitivity

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Authors: Irene Luque Ruiz, Manuel Urbano Cuadrado, Miguel Ángel Gómez-Nieto

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New graph similarity methods have been proposed in this work with the aim to refining the chemical information extracted from molecules matching. For this purpose, data fusion of the isomorphic and nonisomorphic subgraphs into a new similarity measure, the Approximate Similarity, was carried out by several approaches. The application of the proposed method to the development of quantitative structure-activity relationships (QSAR) has provided reliable tools for predicting several pharmacological parameters: binding of steroids to the globulin-corticosteroid receptor, the activity of benzodiazepine receptor compounds, and the blood brain barrier permeability. Acceptable results were obtained for the models presented here.

Keywords: Graph similarity, Nonisomorphic dissimilarity, Approximate similarity, Drug activity prediction.

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Authors: Ryoko Yoshida, Jyunpei Yoshida, Hua Fang Yu, Yasushi Sasaki, Tetsuya Nagasaka

Abstract:

Phosphorous is an important element for agriculture and industry and is a non-renewable resource. Especially, yellow phosphorus is an essential material in advanced industrial technology, but phosphorus resources were not produced in Japan at all, and all depend on imports. It has been suggested, however, that the remaining accessible reserves of phosphate ore will be depleted within 50 years. Therefore, alternative resources for phosphate ore must be found. In this research, we have developed a process that enables the production of high-purity yellow phosphorus from domestic unused phosphorus resources such as steelmaking slags. The process consists of two parts: (1) the production of crude phosphoric acid from wastes such as steelmaking slag; (2) producing high-purity yellow phosphorus by low-temperature carbothermic reduction of phosphoric acid (H₃PO₄). The details of the carbothermic reduction of phosphoric acid are presented in this paper. Yellow phosphorus is commercially produced by carbothermic reduction of phosphate ore in an electric arc furnace at more than 1673K. In the newly developed system, gaseous P₄O₁₀ evaporated from H₃PO₄ is successfully reduced to yellow phosphorus by using carbon packed bed at less than 1273K. To meet the depletion of phosphate ore, the proposed process in this study to produce yellow phosphorus by carbothermic reduction of H₃PO₄ that are extracted from dephosphorization slags will be one of the effective and economical solutions.

Keywords: Carbothermic reduction, dephosphorization slags, phosphoric acid, yellow phosphorus.

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Authors: C. Gunavathi, K. Premalatha

Abstract:

Microarray technology is universally used in the study of disease diagnosis using gene expression levels. The main shortcoming of gene expression data is that it includes thousands of genes and a small number of samples. Abundant methods and techniques have been proposed for tumor classification using microarray gene expression data. Feature or gene selection methods can be used to mine the genes that directly involve in the classification and to eliminate irrelevant genes. In this paper statistical measures like T-Statistics, Signal-to-Noise Ratio (SNR) and F-Statistics are used to rank the genes. The ranked genes are used for further classification. Particle Swarm Optimization (PSO) algorithm and Shuffled Frog Leaping (SFL) algorithm are used to find the significant genes from the top-m ranked genes. The Naïve Bayes Classifier (NBC) is used to classify the samples based on the significant genes. The proposed work is applied on Lung and Ovarian datasets. The experimental results show that the proposed method achieves 100% accuracy in all the three datasets and the results are compared with previous works.

Keywords: Microarray, T-Statistics, Signal-to-Noise Ratio, FStatistics, Particle Swarm Optimization, Shuffled Frog Leaping, Naïve Bayes Classifier.

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Authors: T. Cholastova, D. Knotova

Abstract:

Utilization of diverse germplasm is needed to enhance the genetic diversity of cultivars. The objective of this study was to evaluate the genetic relationships of 98 alfalfa germplasm accessions using morphological traits and SSR markers. From the 98 tested populations, 81 were locals originating in Europe, 17 were introduced from USA, Australia, New Zealand and Canada. Three primers generated 67 polymorphic bands. The average polymorphic information content (PIC) was very high (> 0.90) over all three used primer combinations. Cluster analysis using Unweighted Pair Group Method with Arithmetic Means (UPGMA) and Jaccard´s coefficient grouped the accessions into 2 major clusters with 4 sub-clusters with no correlation between genetic and morphological diversity. The SSR analysis clearly indicated that even with three polymorphic primers, reliable estimation of genetic diversity could be obtained.

Keywords: genetic diversity, Medicago sativa L., morphological traits, SSR markers

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Authors: Daniela F. Maluf, Fernanda Roters, Luma C. F. Silva

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The goal of this work is to report the main dermatological alterations occurring during pregnancy and actual cosmetic protocols available and recommended for safe use. Throughout pregnancy, woman's body undergoes many transformations such as hormonal changes and weight gain. These alterations can result in undesirable skin aspects that end up affecting the future mother's life. The main complaints of pregnant women involve melasma advent, varicose veins, edema, and natural skin aging. Even if most of the time is recommended to wait for the birth to use cosmetics, there are some alternatives to prevent and to treat these alterations during pregnancy. For all these cases, there is a need to update information about safety and efficacy of new actives and technologies in cosmetic products. The purpose of this study was to conduct a literature review about the main skin alterations during pregnancy and actual recommended treatments, according to the current legislation.

Keywords: Pregnancy, cosmetic, treatment, physiological changes.

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Authors: M. Hajduk-Stelmachowicz

Abstract:

This paper presents results of empirical studies that were conducted in enterprises from Podkarpackie Voivodeship (Poland). It shows the experiences of those enterprises resulting from implementing and improving the eco-innovativeness management that is formal Environmental Management System (EMS). This study shows the expected and obtained internal benefits which are the effects of a functioning EMS. The aim of this paper is to determine whether the information included in international theoretical studies concerning the benefits of implementing, functioning and improving formal EMS (which is based on the international standard ISO 14001) are confirmed by the effects of the enterprises- activities.

Keywords: Eco-innovations, Environmental Management System (EMS), ISO 14001, Podkarpackie Voivodeship (Poland).

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Authors: Lori L. Scarlatos, Ryan Courtney

Abstract:

This paper explores the impact that playing a casual game can have on a player's learning and subsequent behavior. A casual mobile game, Container Chaos, was created to teach undergraduate students about the carbon footprint of various disposable beverage containers. Learning was tested with a short quiz, and behavior was tested by observing which beverage containers players choose when offered a drink and a snack. The game was tested multiple times, under a variety of different circumstances. Findings of these tests indicate that, with extended play over time, players can learn new information and sometimes even change their behavior as a result. This has implications for how other casual games can be used to teach concepts and possibly modify behavior.

Keywords: Behavior, carbon footprint, casual games, environmental impact, material sciences.

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Authors: Osama M. Darwesh, Sahar H. Hassan, Abd El-Raheem R. El-Shanshoury, Shawky Z. Sabae

Abstract:

Nanotechnology as multidisciplinary technology is growing rapidly with important applications in several sectors. Also, nanobiotechnology is known for the use of microorganisms for the synthesis of targeted nanoparticles. The present study deals with the green synthesis of silver nanoparticles using aquatic bacteria and the development of a biogenic nanocomposite for environmental applications. 20 morphologically different colonies were isolated from the collected water samples from eight different locations at the Rosetta branch of the Nile Delta, Egypt. The obtained results illustrated that the most effective bacterial isolate (produced the higher amount of AgNPs after 24 h of incubation time) is isolate R3. Bacillus tequilensis was the strongest extracellular bio-manufactory of AgNPs. Biosynthesized nanoparticles had a spherical shape with a mean diameter of 2.74 to 28.4 nm. The antimicrobial activity of silver nanoparticles against many pathogenic microbes indicated that the produced AgNPs had high activity against all tested multi-antibiotic resistant pathogens. Also, the stabilized prepared AgNPs-SA nanocomposite has greater catalytic activity for the decolourization of some dyes like Methylene blue (MB) and Crystal violet. Such results represent a promising stage for producing eco-friendly, cost-effective, and easy-to-handle devices for the bioremediation of contaminated industrial wastewater.

Keywords: Bioremediation, AgNPs, AgNPs-SA nanocomposite, Bacillus tequilensis, nanobiotechnology.

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Authors: F. Pagliara, F. Mauriello

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The objective of this paper is to investigate the relationship between the increase of accessibility brought by high speed rail (HSR) systems and the tourism market in Italy. The impacts of HSR projects on tourism can be quantified in different ways. In this manuscript, an empirical analysis has been carried out with the aid of a dataset containing information both on tourism and transport for 99 Italian provinces during the 2006-2016 period. Panel data regression models have been considered, since they allow modelling a wide variety of correlation patterns. Results show that HSR has an impact on the choice of a given destination for Italian tourists while the presence of a second level hub mainly affects foreign tourists. Attraction variables are also significant for both categories and the variables concerning security, such as number of crimes registered in a given destination, have a negative impact on the choice of a destination.

Keywords: Tourists, overnights, high speed rail, attractions, security.

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Authors: Hichem Sassi, Tawfik Najeh, Noureddine Liouane

Abstract:

The localization information is crucial for the operation of WSN. There are principally two types of localization algorithms. The Range-based localization algorithm has strict requirements on hardware, thus is expensive to be implemented in practice. The Range-free localization algorithm reduces the hardware cost. However, it can only achieve high accuracy in ideal scenarios. In this paper, we locate unknown nodes by incorporating the advantages of these two types of methods. The proposed algorithm makes the unknown nodes select the nearest anchor using the Received Signal Strength Indicator (RSSI) and choose two other anchors which are the most accurate to achieve the estimated location. Our algorithm improves the localization accuracy compared with previous algorithms, which has been demonstrated by the simulating results.

Keywords: WSN, localization, DV-hop, RSSI.

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Authors: Lilac A. E. Al-Safadi

Abstract:

This paper proposes an auto-classification algorithm of Web pages using Data mining techniques. We consider the problem of discovering association rules between terms in a set of Web pages belonging to a category in a search engine database, and present an auto-classification algorithm for solving this problem that are fundamentally based on Apriori algorithm. The proposed technique has two phases. The first phase is a training phase where human experts determines the categories of different Web pages, and the supervised Data mining algorithm will combine these categories with appropriate weighted index terms according to the highest supported rules among the most frequent words. The second phase is the categorization phase where a web crawler will crawl through the World Wide Web to build a database categorized according to the result of the data mining approach. This database contains URLs and their categories.

Keywords: Information Processing on the Web, Data Mining, Document Classification.

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Authors: J. Šejnoha, D. Jarušková, O. Špačková, E. Novotná

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Construction of tunnels is connected with high uncertainty in the field of costs, construction period, safety and impact on surroundings. Risk management became therefore a common part of tunnel projects, especially after a set of fatal collapses occurred in 1990's. Such collapses are caused usually by combination of factors that can be divided into three main groups, i.e. unfavourable geological conditions, failures in the design and planning or failures in the execution. This paper suggests a procedure enabling quantification of the excavation risk related to extraordinary accidents using FTA and ETA tools. It will elaborate on a common process of risk analysis and enable the transfer of information and experience between particular tunnel construction projects. Further, it gives a guide for designers, management and other participants, how to deal with risk of such accidents and how to make qualified decisions based on a probabilistic approach.

Keywords: risk quantification, tunnel collapse, ETA, FTA, geotechnical risk

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Authors: Saulius Minkevicius, Genadijus Kulvietis

Abstract:

The modern queueing theory is one of the powerful tools for a quantitative and qualitative analysis of communication systems, computer networks, transportation systems, and many other technical systems. The paper is designated to the analysis of queueing systems, arising in the networks theory and communications theory (called open queueing network). The authors of this research in the sphere of queueing theory present the theorem about the law of the iterated logarithm (LIL) for the queue length of a customers in open queueing network and its application to the mathematical model of the open message switching system.

Keywords: Models of information systems, open message switching system, open queueing network, queue length of a customers, heavy traffic, a law of the iterated logarithm.

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Authors: Belkacem Selma, Boumediene Selma, Samira Chouraqui, Hanifi Missoum, Tourkia Guerzou

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Natural disasters have occurred and will continue to cause human and material damage. Therefore, the idea of "preventing" natural disasters will never be possible. However, their prediction is possible with the advancement of technology. Even if natural disasters are effectively inevitable, their consequences may be partly controlled. The rapid growth and progress of artificial intelligence (AI) had a major impact on the prediction of natural disasters and risk assessment which are necessary for effective disaster reduction. Earthquake prediction to prevent the loss of human lives and even property damage is an important factor; that, is why it is crucial to develop techniques for predicting this natural disaster. This study aims to analyze the ability of artificial neural networks (ANNs) to predict earthquakes that occur in a given area. The used data describe the problem of high energy (higher than 104 J) seismic bumps forecasting in a coal mine using two long walls as an example. For this purpose, seismic bumps data obtained from mines have been analyzed. The results obtained show that the ANN is able to predict earthquake parameters with  high accuracy; the classification accuracy through neural networks is more than 94%, and the models developed are efficient and robust and depend only weakly on the initial database.

Keywords: Earthquake prediction, artificial intelligence, AI, Artificial Neural Network, ANN, seismic bumps.

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Authors: Jae Chul Cha, Sandeep K. Gupta

Abstract:

The demand for higher performance graphics continues to grow because of the incessant desire towards realism. And, rapid advances in fabrication technology have enabled us to build several processor cores on a single die. Hence, it is important to develop single chip parallel architectures for such data-intensive applications. In this paper, we propose an efficient PIM architectures tailored for computer graphics which requires a large number of memory accesses. We then address the two important tasks necessary for maximally exploiting the parallelism provided by the architecture, namely, partitioning and placement of graphic data, which affect respectively load balances and communication costs. Under the constraints of uniform partitioning, we develop approaches for optimal partitioning and placement, which significantly reduce search space. We also present heuristics for identifying near-optimal placement, since the search space for placement is impractically large despite our optimization. We then demonstrate the effectiveness of our partitioning and placement approaches via analysis of example scenes; simulation results show considerable search space reductions, and our heuristics for placement performs close to optimal – the average ratio of communication overheads between our heuristics and the optimal was 1.05. Our uniform partitioning showed average load-balance ratio of 1.47 for geometry processing and 1.44 for rasterization, which is reasonable.

Keywords: Data Partitioning and Placement, Graphics, PIM, Search Space Reduction.

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Authors: Bezuidt O., Lima-Mendez G., Reva O. N.

Abstract:

SeqWord Gene Island Sniffer, a new program for the identification of mobile genetic elements in sequences of bacterial chromosomes is presented. This program is based on the analysis of oligonucleotide usage variations in DNA sequences. 3,518 mobile genetic elements were identified in 637 bacterial genomes and further analyzed by sequence similarity and the functionality of encoded proteins. The results of this study are stored in an open database http://anjie.bi.up.ac.za/geidb/geidbhome. php). The developed computer program and the database provide the information valuable for further investigation of the distribution of mobile genetic elements and virulence factors among bacteria. The program is available for download at www.bi.up.ac.za/SeqWord/sniffer/index.html.

Keywords: mobile genetic elements, virulence, bacterial genomes

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

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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: Laimona Sliburyte

Abstract:

The goal of this study was to disclose the core of the advertising research based on the psychological aspects by acquainting with the nature of advertising research and revealing the importance of psychological aspects of advertising during the advertising research. The growing interest in consumer response to advertisement served as an encouragement to make the analysis of psychological aspects of the advertising research, because the information obtained during the advertising research helps to answer the question how advertising really works. In the research analysis focuses on the nature of advertising research. The place of advertising research in advertisement planning process and the advertising research process are unfolded. Moreover, the importance of psychological aspects in the advertising research is being examined. The certain psychological aspects like the particularities of advertising communication process, psychological process that are active at advertising acceptance and awareness process as well as the advertising effects are analysed in more detail.

Keywords: Advertising, communication process, advertising message, advertising psychology.

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Authors: Fatima Akhmedova, Simon Liao

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One of the most critical decision points in the design of a face recognition system is the choice of an appropriate face representation. Effective feature descriptors are expected to convey sufficient, invariant and non-redundant facial information. In this work we propose a set of Hahn moments as a new approach for feature description. Hahn moments have been widely used in image analysis due to their invariance, nonredundancy and the ability to extract features either globally and locally. To assess the applicability of Hahn moments to Face Recognition we conduct two experiments on the Olivetti Research Laboratory (ORL) database and University of Notre-Dame (UND) X1 biometric collection. Fusion of the global features along with the features from local facial regions are used as an input for the conventional k-NN classifier. The method reaches an accuracy of 93% of correctly recognized subjects for the ORL database and 94% for the UND database.

Keywords: Face Recognition, Hahn moments, Recognition-by-parts, Time-lapse.

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Authors: Motonobu Hattori, Rina Suzuki

Abstract:

In neural networks, when new patters are learned by a network, they radically interfere with previously stored patterns. This drawback is called catastrophic forgetting. We have already proposed a biologically inspired dual-network memory model which can much reduce this forgetting for static patterns. In this model, information is first stored in the hippocampal network, and thereafter, it is transferred to the neocortical network using pseudopatterns. Because temporal sequence learning is more important than static pattern learning in the real world, in this study, we improve our conventional  dual-network memory model so that it can deal with temporal sequences without catastrophic forgetting. The computer simulation results show the effectiveness of the proposed dual-network memory model.  

Keywords: Catastrophic forgetting, dual-network, temporal sequences.

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Authors: Kailash, Rajeev Kumar Saha, Sanjeev Goyal

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Due to day by day competition in the market, the implementation of benchmarking practice is necessary for improving existing internal supply chain management performance of manufacturing industries. The continuous benchmarking practice might be helpful to increase the productivity of middle scale medium enterprises (MSMEs) by reducing the idle time during the flow of raw material/products, funds and information. The objective of this research paper is to provide an overview of benchmarking, benchmarking wheel, benchmarking tool and techniques and its importance through literature review of reputed journals. This concept of benchmarking may be fruitful in the process of gap identification and for improving the performance of internal supply chain management of Indian manufacturing industries.

Keywords: Benchmarking, benchmarking cyclic wheel, supply chain management, types of benchmarking, supply chain management.

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