Search results for: real time data analysis

Authors: P. Azimi, B. Behtoiy

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One of the most famous techniques which affect the efficiency of a production line is the assembly line balancing (ALB) technique. This paper examines the balancing effect of a whole production line of a real auto glass manufacturer in three steps. In the first step, processing time of each activity in the workstations is generated according to a practical approach. In the second step, the whole production process is simulated and the bottleneck stations have been identified, and finally in the third step, several improvement scenarios are generated to optimize the system throughput, and the best one is proposed. The main contribution of the current research is the proposed framework which combines two famous approaches including Assembly Line Balancing and Optimization via Simulation technique (OvS). The results show that the proposed framework could be applied in practical environments, easily.

Keywords: Assembly line balancing problem, optimization via simulation, production planning.

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Authors: Avellino I. Mondlane, Karin Hansson, Oliver Popov

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This paper discusses the application of extreme events distribution taking the Limpopo River Basin at Xai-Xai station, in Mozambique, as a case analysis. We analyze the extreme value concepts, namely Gumbel, Fréchet, Weibull and Generalized Extreme Value Distributions and then extrapolate the original data to 1000, 5000 and 10000 figures for further simulations and we compare their outcomes based on these three main distributions.

Keywords: Catastrophes, extreme event, disasters, mathematical models, simulation.

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Authors: Zhiyong Li, Zhigang Chen, Chao Fu, Shipeng Zhang

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Load forecasting has always been the essential part of an efficient power system operation and planning. A novel approach based on support vector machines is proposed in this paper for annual power load forecasting. Different kernel functions are selected to construct a combinatorial algorithm. The performance of the new model is evaluated with a real-world dataset, and compared with two neural networks and some traditional forecasting techniques. The results show that the proposed method exhibits superior performance.

Keywords: combinatorial algorithm, data mining, load forecasting, support vector machines

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Authors: Amir Tosson, Mohammad Reza, Christian Gutt

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Metadata is one of the most important aspects for advancing data management practices within all research communities. Definitions and schemes of metadata are inter alia of particular significance in the domain of neutron and photon scattering experiments covering a broad area of different scientific disciplines. The demand of describing continuously evolving highly non-standardized experiments, including the resulting processed and published data, constitutes a considerable challenge for a static definition of metadata. Here, we present the concept of dynamic metadata for the neutron and photon scientific community, which enriches a static set of defined basic metadata. We explore the idea of dynamic metadata with the help of the use case of X-ray Photon Correlation Spectroscopy (XPCS), which is a synchrotron-based scattering technique that allows the investigation of nanoscale dynamic processes. It serves here as a demonstrator of how dynamic metadata can improve data acquisition, sharing, and analysis workflows. Our approach enables researchers to tailor metadata definitions dynamically and adapt them to the evolving demands of describing data and results from a diverse set of experiments. We demonstrate that dynamic metadata standards yield advantages that enhance data reproducibility, interoperability, and the dissemination of knowledge.

Keywords: Big data, metadata, schemas, XPCS, X-ray Photon Correlation Spectroscopy.

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Authors: Kyoung-Jong Park, Woong-Gi Jeon, Hee-Cheol Kim, Dong-Eog Kim, Heung-Kook Choi

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The brain MR imaging-based clinical research and analysis system were specifically built and the development for a large-scale data was targeted. We used the general clinical data available for building large-scale data. Registration period for the selection of the lesion ROI and the region growing algorithm was used and the Mesh-warp algorithm for matching was implemented. The accuracy of the matching errors was modified individually. Also, the large ROI research data can accumulate by our developed compression method. In this way, the correctly decision criteria to the research result was suggested. The experimental groups were age, sex, MR type, patient ID and smoking which can easily be queries. The result data was visualized of the overlapped images by a color table. Its data was calculated by the statistical package. The evaluation for the utilization of this system in the chronic ischemic damage in the area has done from patients with the acute cerebral infarction. This is the cause of neurologic disability index location in the center portion of the lateral ventricle facing. The corona radiate was found in the position. Finally, the system reliability was measured both inter-user and intra-user registering correlation.

Keywords: Software tool design, Cerebral infarction, Brain MR image, Registration

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Authors: Muslihah Wook, Zawiyah M. Yusof, Mohd Zakree Ahmad Nazri

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Data mining has been integrated into application systems to enhance the quality of the decision-making process. This study aims to focus on the integration of data mining technology and Knowledge Management System (KMS), due to the ability of data mining technology to create useful knowledge from large volumes of data. Meanwhile, KMS vitally support the creation and use of knowledge. The integration of data mining technology and KMS are popularly used in business for enhancing and sustaining organizational performance. However, there is a lack of studies that applied data mining technology and KMS in the education sector; particularly students- academic performance since this could reflect the IHL performance. Realizing its importance, this study seeks to integrate data mining technology and KMS to promote an effective management of knowledge within IHLs. Several concepts from literature are adapted, for proposing the new integrative data mining technology and KMS framework to an IHL.

Keywords: Data mining, Institutions of Higher Learning, Knowledge Management System, Students' academic performance.

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Authors: M.J. Sharifi

Abstract:

Several models have been introduced so far for single electron box, SEB, which all of them were restricted to DC response and or low temperature limit. In this paper we introduce a new time dependent, high temperature analytical model for SEB for the first time. DC behavior of the introduced model will be verified against SIMON software and its time behavior will be verified against a newly published paper regarding step response of SEB.

Keywords: Single electron box, SPICE, SIMON, Timedependent, Circuit model.

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Authors: Anjana Goen, D. C. Tiwari

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Electromyography (EMG) is the study of muscles function through analysis of electrical activity produced from muscles. This electrical activity which is displayed in the form of signal is the result of neuromuscular activation associated with muscle contraction. The most common techniques of EMG signal recording are by using surface and needle/wire electrode where the latter is usually used for interest in deep muscle. This paper will focus on surface electromyogram (SEMG) signal. During SEMG recording, several problems had to been countered such as noise, motion artifact and signal instability. Thus, various signal processing techniques had been implemented to produce a reliable signal for analysis. SEMG signal finds broad application particularly in biomedical field. It had been analyzed and studied for various interests such as neuromuscular disease, enhancement of muscular function and human-computer interface.

Keywords: Evolvable hardware (EHW), Functional Electrical Simulation (FES), Hidden Markov Model (HMM), Hjorth Time Domain (HTD).

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Authors: Alexander J. Severinsky

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Radiative forces of greenhouse gases (GHG) increase the temperature of the Earth's surface, more on land, and less in oceans, due to their thermal capacities. Given this inertia, the temperature increase is delayed over time. Air temperature, however, is not delayed as air thermal capacity is much lower. In this study, through analysis and synthesis of multidisciplinary science and data, an estimate of atmospheric temperature increase is made. Then, this estimate is used to shed light on current observations of ice and snow loss, desertification and forest fires, and increased extreme air disturbances. The reason for this inquiry is due to the author’s skepticism that current changes cannot be explained by a "~1 ^oC" global average surface temperature rise within the last 50-60 years. The only other plausible cause to explore for understanding is that of atmospheric temperature rise. The study utilizes an analysis of air temperature rise from three different scientific disciplines: thermodynamics, climate science experiments, and climactic historical studies. The results coming from these diverse disciplines are nearly the same, within ± 1.6%. The direct radiative force of GHGs with a high level of scientific understanding is near 4.7 W/m² on average over the Earth’s entire surface in 2018, as compared to one in pre-Industrial time in the mid-1700s. The additional radiative force of fast feedbacks coming from various forms of water gives approximately an additional ~15 W/m². In 2018, these radiative forces heated the atmosphere by approximately 5.1 ^oC, which will create a thermal equilibrium average ground surface temperature increase of 4.6 ^oC to 4.8 ^oC by the end of this century. After 2018, the temperature will continue to rise without any additional increases in the concentration of the GHGs, primarily of carbon dioxide and methane. These findings of the radiative force of GHGs in 2018 were applied to estimates of effects on major Earth ecosystems. This additional force of nearly 20 W/m² causes an increase in ice melting by an additional rate of over 90 cm/year, green leaves temperature increase by nearly 5 ^oC, and a work energy increase of air by approximately 40 Joules/mole. This explains the observed high rates of ice melting at all altitudes and latitudes, the spread of deserts and increases in forest fires, as well as increased energy of tornadoes, typhoons, hurricanes, and extreme weather, much more plausibly than the 1.5 ^oC increase in average global surface temperature in the same time interval. Planned mitigation and adaptation measures might prove to be much more effective when directed toward the reduction of existing GHGs in the atmosphere.

Keywords: GHG radiative forces, GHG air temperature, GHG thermodynamics, GHG historical, GHG experimental, GHG radiative force on ice, GHG radiative force on plants, GHG radiative force in air.

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Authors: Hai Quang Hong Dam, Hai Ho, Minh Hoang Le Ngo

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This paper investigates the problem of blind speech separation from the speech mixture of two speakers. A voice activity detector employing the Steered Response Power - Phase Transform (SRP-PHAT) is presented for detecting the activity information of speech sources and then the desired speech signals are extracted from the speech mixture by using an optimal beamformer. For evaluation, the algorithm effectiveness, a simulation using real speech recordings had been performed in a double-talk situation where two speakers are active all the time. Evaluations show that the proposed blind speech separation algorithm offers a good interference suppression level whilst maintaining a low distortion level of the desired signal.

Keywords: Blind speech separation, voice activity detector, SRP-PHAT, optimal beamformer.

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Authors: Min Kyung An

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In Wireless Sensor Networks which consist of tiny wireless sensor nodes with limited battery power, one of the most fundamental applications is data aggregation which collects nearby environmental conditions and aggregates the data to a designated destination, called a sink node. Important issues concerning the data aggregation are time efficiency and energy consumption due to its limited energy, and therefore, the related problem, named Minimum Latency Aggregation Scheduling (MLAS), has been the focus of many researchers. Its objective is to compute the minimum latency schedule, that is, to compute a schedule with the minimum number of timeslots, such that the sink node can receive the aggregated data from all the other nodes without any collision or interference. For the problem, the two interference models, the graph model and the more realistic physical interference model known as Signal-to-Interference-Noise-Ratio (SINR), have been adopted with different power models, uniform-power and non-uniform power (with power control or without power control), and different antenna models, omni-directional antenna and directional antenna models. In this survey article, as the problem has proven to be NP-hard, we present and compare several state-of-the-art approximation algorithms in various models on the basis of latency as its performance measure.

Keywords: Data aggregation, convergecast, gathering, approximation, interference, omni-directional, directional.

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Authors: Saeid Gharechelou, Ryutaro Tateishi

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Earthquake is an inevitable catastrophic natural disaster. The damages of buildings and man-made structures, where most of the human activities occur are the major cause of casualties from earthquakes. A comparison of optical and SAR data is presented in the case of Kathmandu valley which was hardly shaken by 2015-Nepal Earthquake. Though many existing researchers have conducted optical data based estimated or suggested combined use of optical and SAR data for improved accuracy, however finding cloud-free optical images when urgently needed are not assured. Therefore, this research is specializd in developing SAR based technique with the target of rapid and accurate geospatial reporting. Should considers that limited time available in post-disaster situation offering quick computation exclusively based on two pairs of pre-seismic and co-seismic single look complex (SLC) images. The InSAR coherence pre-seismic, co-seismic and post-seismic was used to detect the change in damaged area. In addition, the ground truth data from field applied to optical data by random forest classification for detection of damaged area. The ground truth data collected in the field were used to assess the accuracy of supervised classification approach. Though a higher accuracy obtained from the optical data then integration by optical-SAR data. Limitation of cloud-free images when urgently needed for earthquak evevent are and is not assured, thus further research on improving the SAR based damage detection is suggested. Availability of very accurate damage information is expected for channelling the rescue and emergency operations. It is expected that the quick reporting of the post-disaster damage situation quantified by the rapid earthquake assessment should assist in channeling the rescue and emergency operations, and in informing the public about the scale of damage.

Keywords: Sentinel-1A data, Landsat-8, earthquake damage, InSAR, rapid monitoring, 2015-Nepal earthquake.

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Authors: Sidney A. Lima, Hermann J. H. Kux, Elcio H. Shiguemori

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The Unmanned Aircraft Systems (UAS) usually navigate through the Global Navigation Satellite System (GNSS) associated with an Inertial Navigation System (INS). However, GNSS can have its accuracy degraded at any time or even turn off the signal of GNSS. In addition, there is the possibility of malicious interferences, known as jamming. Therefore, the image navigation system can solve the autonomy problem, because if the GNSS is disabled or degraded, the image navigation system would continue to provide coordinate information for the INS, allowing the autonomy of the system. This work aims to evaluate the accuracy of the positioning though photogrammetry concepts. The methodology uses orthophotos and Digital Surface Models (DSM) as a reference to represent the object space and photograph obtained during the flight to represent the image space. For the calculation of the coordinates of the perspective center and camera attitudes, it is necessary to know the coordinates of homologous points in the object space (orthophoto coordinates and DSM altitude) and image space (column and line of the photograph). So if it is possible to automatically identify in real time the homologous points the coordinates and attitudes can be calculated whit their respective accuracies. With the methodology applied in this work, it is possible to verify maximum errors in the order of 0.5 m in the positioning and 0.6º in the attitude of the camera, so the navigation through the image can reach values equal to or higher than the GNSS receivers without differential correction. Therefore, navigating through the image is a good alternative to enable autonomous navigation.

Keywords: Autonomy, navigation, security, photogrammetry, remote sensing, spatial resection, UAS.

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Authors: Mohamed Elkholy, Ahmed Elfatatry

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Cloud computing has emerged as a flexible computing paradigm that reshaped the Information Technology map. However, cloud computing brought about a number of security challenges as a result of the physical distribution of computational resources and the limited control that users have over the physical storage. This situation raises many security challenges for data integrity and confidentiality as well as authentication and access control. This work proposes a security mechanism for data integrity that allows a data owner to be aware of any modification that takes place to his data. The data integrity mechanism is integrated with an extended Kerberos authentication that ensures authorized access control. The proposed mechanism protects data confidentiality even if data are stored on an untrusted storage. The proposed mechanism has been evaluated against different types of attacks and proved its efficiency to protect cloud data storage from different malicious attacks.

Keywords: Access control, data integrity, data confidentiality, Kerberos authentication, cloud security.

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Authors: Hussam Elias, Ninovic Perez, Holger Hirsch

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The completion of the EMC regulations worldwide is growing steadily as the usage of electronics in our daily lives is increasing more than ever. In this paper, we present a method to perform the final phase of Electromagnetic Compatibility (EMC) measurement and to reduce the required test time according to the norm EN 55032 by using a developed tool and the Conventional Neural Network (CNN). The neural network was trained using real EMC measurements which were performed in the Semi Anechoic Chamber (SAC) by CETECOM GmbH in Essen Germany. To implement our proposed method, we wrote software to perform the radiated electromagnetic interference (EMI) measurements and use the CNN to predict and determine the position of the turntable that meet the maximum radiation value.

Keywords: Conventional neural network, electromagnetic compatibility measurement, mean absolute error, position error.

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Authors: A. Gruzdz, A. Ihnatowicz, J. Siddiqi, B. Akhgar

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MATCH project [1] entitle the development of an automatic diagnosis system that aims to support treatment of colon cancer diseases by discovering mutations that occurs to tumour suppressor genes (TSGs) and contributes to the development of cancerous tumours. The constitution of the system is based on a) colon cancer clinical data and b) biological information that will be derived by data mining techniques from genomic and proteomic sources The core mining module will consist of the popular, well tested hybrid feature extraction methods, and new combined algorithms, designed especially for the project. Elements of rough sets, evolutionary computing, cluster analysis, self-organization maps and association rules will be used to discover the annotations between genes, and their influence on tumours [2]-[11]. The methods used to process the data have to address their high complexity, potential inconsistency and problems of dealing with the missing values. They must integrate all the useful information necessary to solve the expert's question. For this purpose, the system has to learn from data, or be able to interactively specify by a domain specialist, the part of the knowledge structure it needs to answer a given query. The program should also take into account the importance/rank of the particular parts of data it analyses, and adjusts the used algorithms accordingly.

Keywords: Bioinformatics, gene expression, ontology, selforganizingmaps.

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Authors: Kristyanto B.

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Plenty of analyses based on Biomechanics were carried out on many jobs in manufactures or services. Now Biomechanics analysis is being applied on mothers who are giving birth. The analysis conducted in terms of normal condition of the birth process without Gyn Bed (Obstetric Bed). The aim of analysis is to study whether it is risky or not when choosing the position of mother’s postures when delivering the baby. This investigation was applied on two positions that generally appear in common birth process. Results will show the analysis of both positions to support the birth process based on the Biomechanics analysis (Ergonomic approaches). 

Keywords: Biomechanics analysis, Birth process, Position of postures analysis, Ergonomic approaches.

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Authors: Khalid Ali, Manar Jammal

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In order to meet the stringent latency and reliability requirements of the upcoming 5G networks, Open Radio Access Networks (O-RAN) have been proposed. The virtualization of O-RAN has allowed it to be treated as a Network Function Virtualization (NFV) architecture, while its components are considered Virtualized Network Functions (VNFs). Hence, intelligent Machine Learning (ML) based solutions can be utilized to apply different resource management and allocation techniques on O-RAN. However, intelligently allocating resources for O-RAN VNFs can prove challenging due to the dynamicity of traffic in mobile networks. Network providers need to dynamically scale the allocated resources in response to the incoming traffic. Elastically allocating resources can provide a higher level of flexibility in the network in addition to reducing the OPerational EXpenditure (OPEX) and increasing the resources utilization. Most of the existing elastic solutions are reactive in nature, despite the fact that proactive approaches are more agile since they scale instances ahead of time by predicting the incoming traffic. In this work, we propose and evaluate traffic forecasting models based on the ML algorithm. The algorithms aim at predicting future O-RAN traffic by using previous traffic data. Detailed analysis of the traffic data was carried out to validate the quality and applicability of the traffic dataset. Hence, two ML models were proposed and evaluated based on their prediction capabilities.

Keywords: O-RAN, traffic forecasting, NFV, ARIMA, LSTM, elasticity.

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Authors: Hai Huu Le, Paul Junor, Moshi Geso, Graeme O’Keefe

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In this paper, the authors propose a personal wearable directionally-sensitive radiation dosimeter using multiple semiconductor CdZnTe detectors. The proposed dosimeter not only measures the real-time dose rate but also provide the direction of the radioactive source. A linear relationship between radioactive source direction and the radiation intensity measured by each detectors is established and an equation to determine the source direction is derived by the authors. The efficiency and accuracy of the proposed dosimeter is verified by simulation using Geant4 package. Results have indicated that in a measurement duration of about 7 seconds, the proposed dosimeter was able to estimate the direction of a 10μCi 137/55Cs radioactive source to within 2 degrees.

Keywords: Dose rate, Geant4 package, radiation detectors, radioactive source direction.

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Authors: Mayada AlMeghari

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Recently, grid middlewares have provided large integrated use of network resources as the shared data and the CPU to become a virtual supercomputer. In this work, we present the design and implementation of the middleware for Data Warehouse Signature (DWS) Framework. The aim of using the middleware in the proposed DWS framework is to achieve the high performance by the parallel computing. This middleware is developed on Alchemi.Net framework to increase the security among the network nodes through the authentication and group-key distribution model. This model achieves the key security and prevents any intermediate attacks in the middleware. This paper presents the flow process structures of the middleware design. In addition, the paper ensures the implementation of security for DWS middleware enhancement with the authentication and group-key distribution model. Finally, from the analysis of other middleware approaches, the developed middleware of DWS framework is the optimal solution of a complete covering of security issues.

Keywords: Middleware, parallel computing, data warehouse, security, group-key, high performance.

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Authors: E. Moroydor Derun, P. Gurses, M. Yildirim, A. S. Kipcak, T. Ibroska, S. Piskin

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Due to their strong mechanical and thermal properties magnesium borates have a wide usage area such as ceramic industry, detergent production, friction reducing additive and grease production. In this study, microwave synthesis of magnesium borates from MgCl₂.6H₂O (Magnesium chloride hexahydrate), MgO (Magnesium oxide) and H₃BO₃ (Boric acid) for different reaction times is researched. X-ray Diffraction (XRD) and Fourier Transform Infrared (FT-IR) Spectroscopy are used to find out how the reaction time sways on the products. The superficial properties are investigated with Scanning Electron Microscopy (SEM). According to XRD analysis, the synthesized compounds are 00-041-1407 pdf coded Shabinite (Mg₅(BO₃)₄Cl₂(OH)₅.4(H₂O)) and 01-073-2158 pdf coded Karlite (Mg₇(BO₃)₃(OH,Cl)₅).

Keywords: Magnesium borate, microwave synthesis, XRD, SEM.

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Authors: Göksu Gözen Citak

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The process of constructing a scale measuring the attitudes of youth toward violence on televisions is reported. A 30-item draft attitude scale was applied to a working group of 232 students attending the Faculty of Educational Sciences at Ankara University between the years 2005-2006. To introduce the construct validity and dimensionality of the scale, exploratory and confirmatory factor analysis was applied to the data. Results of the exploratory factor analysis showed that the scale had three factors that accounted for 58,44% (22,46% for the first, 22,15% for the second and 13,83% for the third factor) of the common variance. It is determined that the first factor considered issues related individual effects of violence on televisions, the second factor concerned issues related social effects of violence on televisions and the third factor concerned issues related violence on television programs. Results of the confirmatory factor analysis showed that all the items under each factor are fitting the concerning factors structure. An alpha reliability of 0,90 was estimated for the whole scale. It is concluded that the scale is valid and reliable.

Keywords: Attitudes toward violence, confirmatory factor analysis, constructing attitude scale, exploratory factor analysis, violence on televisions.

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Authors: Barenten Suciu

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Classical matrix calculus and Routh-Hurwitz stability conditions, applied to the snake-like motion of the conical wheel axle, lead to the conclusion that the hunting mode is inherently unstable, and its natural frequency is a complex number. In order to analytically solve such a complicated vibration model, either the inertia terms were neglected, in the model designated as geometrical, or restrictions on the creep coefficients and yawing diameter were imposed, in the so-called dynamical model. Here, an alternative solution is proposed to solve the hunting mode, based on the observation that the bullet train wheel axle is equipped with cylindrical wheels. One argues that for such wheel treads, the geometrical hunting is irrelevant, since its natural frequency becomes nil, but the dynamical hunting is significant since its natural frequency reduces to a real number. Moreover, one illustrates that the geometrical simplification of the wheel causes the stabilization of the hunting mode, since the characteristic quartic equation, derived for conical wheels, reduces to a quadratic equation of positive coefficients, for cylindrical wheels. Quite simple analytical expressions for the damping ratio and natural frequency are obtained, without applying restrictions into the model of contact. Graphs of the time-depending hunting lateral perturbation, including the maximal and inflexion points, are presented both for the critically-damped and the over-damped wheel axles.

Keywords: Bullet train, dynamical hunting, cylindrical wheels, damping, stability, creep, vibration analysis.

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Authors: DaeWon Lee, HeonChang Yu

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Next generation wireless/mobile networks will be IP based cellular networks integrating the internet with cellular networks. In this paper, we propose a new architecture for a high speed transport system and a mobile management protocol for mobile internet users in a transport system. Existing mobility management protocols (MIPv6, HMIPv6) do not consider real world fast moving wireless hosts (e.g. passengers in a train). For this reason, we define a virtual organization (VO) and proposed the VO architecture for the transport system. We also classify mobility as VO mobility (intra VO) and macro mobility (inter VO). Handoffs in VO are locally managed and transparent to the CH while macro mobility is managed with Mobile IPv6. And, from the features of the transport system, such as fixed route and steady speed, we deduce the movement route and the handoff disruption time of each handoff. To reduce packet loss during handoff disruption time, we propose pre-registration scheme using pre-registration. Moreover, the proposed protocol can eliminate unnecessary binding updates resulting from sequence movement at high speed. The performance evaluations demonstrate our proposed protocol has a good performance at transport system environment. Our proposed protocol can be applied to the usage of wireless internet on the train, subway, and high speed train.

Keywords: Binding update, HMIPv6, packet loss, transport system, virtual organization.

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Authors: Krzysztof J. Czarnocki, E. Czarnocka, K. Szaniawska

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Main goal of the research project is Scaffold Use Risk Assessment Model (SURAM) formulation, developed for the assessment of risk levels as a various construction process stages with various work trades. Finally, in 2016, the project received financing by the National Center for Research and development according to PBS3/A2/19/2015–Research Grant. The presented data, calculations and analyzes discussed in this paper were created as a result of the completion on the first and second phase of the PBS3/A2/19/2015 project. Method: One of the arms of the research project is the assessment of worker visual concentration on the sight zones as well as risky visual point inadequate observation. In this part of research, the mobile eye-tracker was used to monitor the worker observation zones. SMI Eye Tracking Glasses is a tool, which allows us to analyze in real time and place where our eyesight is concentrated on and consequently build the map of worker's eyesight concentration during a shift. While the project is still running, currently 64 construction sites have been examined, and more than 600 workers took part in the experiment including monitoring of typical parameters of the work regimen, workload, microclimate, sound vibration, etc. Full equipment can also be useful in more advanced analyses. Because of that technology we have verified not only main focus of workers eyes during work on or next to scaffolding, but we have also examined which changes in the surrounding environment during their shift influenced their concentration. In the result of this study it has been proven that only up to 45.75% of the shift time, workers’ eye concentration was on one of three work-related areas. Workers seem to be distracted by noisy vehicles or people nearby. In opposite to our initial assumptions and other authors’ findings, we observed that the reflective parts of the scaffoldings were not more recognized by workers in their direct workplaces. We have noticed that the red curbs were the only well recognized part on a very few scaffoldings. Surprisingly on numbers of samples, we have not recognized any significant number of concentrations on those curbs. Conclusion: We have found the eye-tracking method useful for the construction of the SURAM model in the risk perception and worker’s behavior sub-modules. We also have found that the initial worker's stress and work visual conditions seem to be more predictive for assessment of the risky developing situation or an accident than other parameters relating to a work environment.

Keywords: Accident assessment model, eye tracking, occupational safety, scaffolding.

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Authors: Su Myat Marlar Soe, May Paing Paing Zaw

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It has been defined that the “network is the system". This implies providing levels of service, reliability, predictability and availability that are commensurate with or better than those that individual computers provide today. To provide this requires integrated network management for interconnected networks of heterogeneous devices covering both the local campus. In this paper we are addressing a framework to effectively deal with this issue. It consists of components and interactions between them which are required to perform the service fault management. A real-world scenario is used to derive the requirements which have been applied to the component identification. An analysis of existing frameworks and approaches with respect to their applicability to the framework is also carried out.

Keywords: To diagnose the possible network faults by using thepredetermined rules.

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Authors: Tri Poespowati

Abstract:

Experiments were conducted to characterize fire properties of wood exposed to the certain external heat flux and under variety of wood moisture content. Six kinds of Indonesian wood: keruing, sono, cemara, kamper, pinus, and mahoni were exposed to radiant heat from a conical heater, result in appearance of a stable flame on the wood surface caused by spontaneous ignition. A thermocouple K-type was used to measure the wood surface temperature. Temperature histories were recorded throughout each experiment at 1 s intervals using a TC-08. Data of first ignition time and temperature, end ignition time and temperature, and charring rate have been successfully collected. It was found that the ignition temperature and charring rate depend on moisture content of wood.

Keywords: Fire properties, moisture content, wood, charring rate.

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Authors: Marinela Mircea

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The development of information and communication technology, the increased use of the internet, as well as the effects of the recession within the last years, have lead to the increased use of cloud computing based solutions, also called on-demand solutions. These solutions offer a large number of benefits to organizations as well as challenges and risks, mainly determined by data visualization in different geographic locations on the internet. As far as the specific risks of cloud environment are concerned, data security is still considered a peak barrier in adopting cloud computing. The present study offers an approach upon ensuring the security of cloud data, oriented towards the whole data life cycle. The final part of the study focuses on the assessment of data security in the cloud, this representing the bases in determining the potential losses and the premise for subsequent improvements and continuous learning.

Keywords: cloud computing, data life cycle, data security, security assessment.

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Authors: I. V. Pinto, M. R. Sooriyarachchi

Abstract:

It can be frequently observed that the data arising in our environment have a hierarchical or a nested structure attached with the data. Multilevel modelling is a modern approach to handle this kind of data. When multilevel modelling is combined with a binary response, the estimation methods get complex in nature and the usual techniques are derived from quasi-likelihood method. The estimation methods which are compared in this study are, marginal quasi-likelihood (order 1 & order 2) (MQL1, MQL2) and penalized quasi-likelihood (order 1 & order 2) (PQL1, PQL2). A statistical model is of no use if it does not reflect the given dataset. Therefore, checking the adequacy of the fitted model through a goodness-of-fit (GOF) test is an essential stage in any modelling procedure. However, prior to usage, it is also equally important to confirm that the GOF test performs well and is suitable for the given model. This study assesses the suitability of the GOF test developed for binary response multilevel models with respect to the method used in model estimation. An extensive set of simulations was conducted using MLwiN (v 2.19) with varying number of clusters, cluster sizes and intra cluster correlations. The test maintained the desirable Type-I error for models estimated using PQL2 and it failed for almost all the combinations of MQL. Power of the test was adequate for most of the combinations in all estimation methods except MQL1. Moreover, models were fitted using the four methods to a real-life dataset and performance of the test was compared for each model.

Keywords: Goodness-of-fit test, marginal quasi-likelihood, multilevel modelling, type-I error, penalized quasi-likelihood, power, quasi-likelihood.

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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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