Search results for: Data communication

Authors: Rami Al-Ruzouq, Abdallah Al-Zoubi, Abdel-Rahman Abueladas, Petya Dimitrova

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Protection and proper management of archaeological heritage are an essential process of studying and interpreting the generations present and future. Protecting the archaeological heritage is based upon multidiscipline professional collaboration. This study aims to gather data by different sources (Photogrammetry and Geographic Information System (GIS)) integrated for the purpose of documenting one the of significant archeological sites (Ahl-Alkahf, Jordan). 3D modeling deals with the actual image of the features, shapes and texture to represent reality as realistically as possible by using texture. The 3D coordinates that result of the photogrammetric adjustment procedures are used to create 3D-models of the study area. Adding Textures to the 3D-models surfaces gives a 'real world' appearance to the displayed models. GIS system combined all data, including boundary maps, indicating the location of archeological sites, transportation layer, digital elevation model and orthoimages. For realistic representation of the study area, 3D - GIS model prepared, where efficient generation, management and visualization of such special data can be achieved.

Keywords: Archaeology, close range photogrammetry, ortho-photo, 3D-GIS

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Authors: S. E. Oraby, A.M. Alaskari

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The stochastic nature of tool life using conventional discrete-wear data from experimental tests usually exists due to many individual and interacting parameters. It is a common practice in batch production to continually use the same tool to machine different parts, using disparate machining parameters. In such an environment, the optimal points at which tools have to be changed, while achieving minimum production cost and maximum production rate within the surface roughness specifications, have not been adequately studied. In the current study, two relevant aspects are investigated using coated and uncoated inserts in turning operations: (i) the accuracy of using machinability information, from fixed parameters testing procedures, when variable parameters situations are emerged, and (ii) the credibility of tool life machinability data from prior discrete testing procedures in a non-stop machining. A novel technique is proposed and verified to normalize the conventional fixed parameters machinability data to suit the cases when parameters have to be changed for the same tool. Also, an experimental investigation has been established to evaluate the error in the tool life assessment when machinability from discrete testing procedures is employed in uninterrupted practical machining.

Keywords: Machinability, tool life, tool wear, wear variability

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Authors: Syed Sohaib Bin Hasib, Hiyam Al-Kilidar

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Meeting project deadlines is a major challenge for most construction projects. In this study, perceptions of contractors, clients, and consultants are compared relative to a list of factors derived from the review of the extant literature on project delay. 59 causes (categorized into 8 groups) of project delays were identified from the literature. A survey was devised to get insights and ranking of these factors from clients, consultants & contractors in the Australian construction industry. Findings showed that project delays in the Australian construction industry are mainly the result of skill shortages, interference in execution, and poor coordination and communication between the project stakeholders.

Keywords: Construction, delay factors, time delay, Australian construction industry.

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Authors: Afnan T. Bagasi, Donia M. Bettaieb, Abeer Alsobahi

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The wayfinding system affects the course of a museum journey for visitors, both directly and indirectly. The design aspects of this system play an important role, making it an effective communication system within the museum space. However, translating the concepts that pertain to its design, and which are based on integration and connectivity in museum space design, such as intelligibility, lacks customization in the form of specific design considerations with reference to the most important approaches. These approaches link the organizational and practical aspects to the semiotic and semantic aspects related to the space syntax by targeting the visual and perceived consistency of visitors. In this context, the present study aims to identify how to apply the concept of intelligibility by employing integration and connectivity to design a wayfinding system in museums as a kind of composite interior space. Using the available plans and images to extrapolate the considerations used to design the wayfinding system in the Saudi National Museum as a case study, a descriptive analytical method was used to understand the basic organizational and Morphological principles of the museum space through the main aspects of space design (the Morphological and the pragmatic). The study’s methodology is based on the description and analysis of the basic organizational and Morphological principles of the museum space at the level of the major Morphological and Pragmatic design layers (based on available pictures and diagrams) and inductive method about applied level of intelligibility in spatial layout in the Hall of Islam and Arabia at the National Museum Saudi Arabia within the framework of a case study through the levels of verification of the properties of the concepts of connectivity and integration. The results indicated that the application of the characteristics of intelligibility is weak on both Pragmatic and Morphological levels. Based on the concept of connective and integration, we conclude the following: (1) High level of reflection of the properties of connectivity on the pragmatic level, (2) Weak level of reflection of the properties of Connectivity at the morphological level (3) Weakness in the level of reflection of the properties of integration in the space sample as a result of a weakness in the application at the morphological and pragmatic level. The study’s findings will assist designers, professionals, and researchers in the field of museum design in understanding the significance of the wayfinding system by delving into it through museum spaces by highlighting the most essential aspects using a clear analytical method.

Keywords: wayfinding system, museum journey, intelligibility, integration, connectivity, interior design

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Authors: Bala Dhandayuthapani Veerasamy

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Rapid steps made in the field of Information and Communication Technology (ICT) has facilitated the development of teaching and learning methods and prepared them to serve the needs of an assorted educational institution. In other words, the information age has redefined the fundamentals and transformed the institutions and method of services delivery forever. The vision is the articulation of a desire to transform the method of teaching and learning could proceed through e-learning. E-learning is commonly deliberated to use of networked information and communications technology in teaching and learning practice. This paper deals the general aspects of the e-leaning with its issues, developments, opportunities and challenges, which can the higher institutions own.

Keywords: 2D & 3D Animations, challenges, E-learning, Flash, HTML, issues, Multimedia, opportunities, VRML

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Authors: P. R. Jayathilaka, K.L. Jayaratne, H.L. Premaratne

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This research presented in this paper is an on-going project of an application of neural network and fuzzy models to evaluate the sociological factors which affect the educational performance of the students in Sri Lanka. One of its major goals is to prepare the grounds to device a counseling tool which helps these students for a better performance at their examinations, especially at their G.C.E O/L (General Certificate of Education-Ordinary Level) examination. Closely related sociological factors are collected as raw data and the noise of these data are filtered through the fuzzy interface and the supervised neural network is being utilized to recognize the performance patterns against the chosen social factors.

Keywords: Education, Fuzzy, neural network, prediction, Sociology

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Authors: Javad Marzbanrad, Mostafa Pahlavani

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This study has investigated a vehicle Lumped Parameter Model (LPM) in frontal crash. There are several ways for determining spring and damper characteristics and type of problem shall be considered as system identification. This study use Genetic Algorithm (GA) procedure, being an effective procedure in case of optimization issues, for optimizing errors, between target data (experimental data) and calculated results (being obtained by analytical solving). In this study analyzed model in 5-DOF then compared our results with 5-DOF serial model. Finally, the response of model due to external excitement is investigated.

Keywords: Vehicle, Lumped-Parameter Model, GeneticAlgorithm, Optimization

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Authors: Nileshkumar Vaishnav, Aditya Tatu

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An algebraic framework for processing graph signals axiomatically designates the graph adjacency matrix as the shift operator. In this setup, we often encounter a problem wherein we know the filtered output and the filter coefficients, and need to find out the input graph signal. Solution to this problem using direct approach requires O(N3) operations, where N is the number of vertices in graph. In this paper, we adapt the spectral graph partitioning method for partitioning of graphs and use it to reduce the computational cost of the filtering problem. We use the example of denoising of the temperature data to illustrate the efficacy of the approach.

Keywords: Graph signal processing, graph partitioning, inverse filtering on graphs, algebraic signal processing.

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Authors: I. M. Abd Rahim, H. Abdul Rahim, R. Ghazali

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There is numerous non-invasive blood glucose measurement technique developed by researchers, and near infrared (NIR) is the potential technique nowadays. However, there are some disagreements on the optimal wavelength range that is suitable to be used as the reference of the glucose substance in the blood. This paper focuses on the experimental data collection technique and also the analysis method used to analyze the data gained from the experiment. The selection of suitable linear and non-linear model structure is essential in prediction system, as the system developed need to be conceivably accurate.

Keywords: Invasive, linear, near-infrared (Nir), non-invasive, non-linear, prediction system.

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Authors: R. Gomathi, D. Sharmila

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The emergence of the Semantic Web technology increases day by day due to the rapid growth of multiple web pages. Many standard formats are available to store the semantic web data. The most popular format is the Resource Description Framework (RDF). Querying large RDF graphs becomes a tedious procedure with a vast increase in the amount of data. The problem of query optimization becomes an issue in querying large RDF graphs. Choosing the best query plan reduces the amount of query execution time. To address this problem, nature inspired algorithms can be used as an alternative to the traditional query optimization techniques. In this research, the optimal query plan is generated by the proposed SAPSO algorithm which is a hybrid of Simulated Annealing (SA) and Particle Swarm Optimization (PSO) algorithms. The proposed SAPSO algorithm has the ability to find the local optimistic result and it avoids the problem of local minimum. Experiments were performed on different datasets by changing the number of predicates and the amount of data. The proposed algorithm gives improved results compared to existing algorithms in terms of query execution time.

Keywords: Semantic web, RDF, Query optimization, Nature inspired algorithms, PSO, SA.

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Authors: Cheng Yuan Hung, Min Hang Weng, Siang Wen Lan, Wei Yu Chen, Hung Wei Wu, Chun Yueh Huang

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In this paper, a low noise microwave bandpass filter (BPF) is presented. This filter is fabricated by modifying the conventional cross-coupled structure. The spurious response is improved by using the end open coupled lines, and the influence of the noise is minimized. Impedance matrix of the open end coupled circuit clarifies the characteristic of the suppression of the spurious response. The rejection of spurious suppression region of the proposed filter is greater than 20 dB from 3-13 GHz. The measured results of the fabricated filter confirm the concepts of the proposed design and exhibits high performance.

Keywords: Low noise, signal transmission, bandpass filter, end open coupled line, communication system.

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Authors: N. Haghjou, M. J. Abdekhodaie, Y. L. Cheng, M. Saadatmand

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Intravitreal injection (IVI) is the most common treatment for eye posterior segment diseases such as endopthalmitis, retinitis, age-related macular degeneration, diabetic retinopathy, uveitis, and retinal detachment. Most of the drugs used to treat vitreoretinal diseases, have a narrow concentration range in which they are effective, and may be toxic at higher concentrations. Therefore, it is critical to know the drug distribution within the eye following intravitreal injection. Having knowledge of drug distribution, ophthalmologists can decide on drug injection frequency while minimizing damage to tissues. The goal of this study was to develop a computer model to predict intraocular concentrations and pharmacokinetics of intravitreally injected drugs. A finite volume model was created to predict distribution of two drugs with different physiochemical properties in the rabbit eye. The model parameters were obtained from literature review. To validate this numeric model, the in vivo data of spatial concentration profile from the lens to the retina were compared with the numeric data. The difference was less than 5% between the numerical and experimental data. This validation provides strong support for the numerical methodology and associated assumptions of the current study.

Keywords: Posterior segment, Intravitreal injection (IVI), Pharmacokinetic, Modelling, Finite volume method.

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Authors: Hongmin Deng, Qionghua Wang

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A modified two dimensional (2D) logistic map based on cross feedback control is proposed. This 2D map exhibits more random chaotic dynamical properties than the classic one dimensional (1D) logistic map in the statistical characteristics analysis. So it is utilized as the pseudo-random (PN) sequence generator, where the obtained real-valued PN sequence is quantized at first, then applied to radio frequency identification (RFID) communication system in this paper. This system is experimentally validated on a cortex-M₀ development board, which shows the effectiveness in key generation, the size of key space and security. At last, further cryptanalysis is studied through the test suite in the National Institute of Standards and Technology (NIST).

Keywords: Chaos encryption, logistic map, pseudo-random sequence, RFID.

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Authors: Soon Jai Yi, Sun-Hong Kim, Hang-Geun Jeong, Seong-Ik Cho

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This paper presents a method of reducing the feedback delay time of DWA(Data Weighted Averaging) used in sigma-delta modulators. The delay time reduction results from the elimination of the latch at the quantizer output and also from the falling edge operation. The designed sigma-delta modulator improves the timing margin about 16%. The sub-circuits of sigma-delta modulator such as SC(Switched Capacitor) integrator, 9-level quantizer, comparator, and DWA are designed with the non-ideal characteristics taken into account. The sigma-delta modulator has a maximum SNR (Signal to Noise Ratio) of 84 dB or 13 bit resolution.

Keywords: Sigma-delta modulator, multibit, DWA

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Authors: S. Moein, S. A. Monadjemi, P. Moallem

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In this paper, application of artificial neural networks in typical disease diagnosis has been investigated. The real procedure of medical diagnosis which usually is employed by physicians was analyzed and converted to a machine implementable format. Then after selecting some symptoms of eight different diseases, a data set contains the information of a few hundreds cases was configured and applied to a MLP neural network. The results of the experiments and also the advantages of using a fuzzy approach were discussed as well. Outcomes suggest the role of effective symptoms selection and the advantages of data fuzzificaton on a neural networks-based automatic medical diagnosis system.

Keywords: Artificial Neural Networks, Fuzzy Logic, MedicalDiagnosis, Symptoms, Fuzzification.

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Authors: Hanan Ahmed-Hosni Mahmoud, Nadia Al-Ghreimil

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In-place sorting algorithms play an important role in many fields such as very large database systems, data warehouses, data mining, etc. Such algorithms maximize the size of data that can be processed in main memory without input/output operations. In this paper, a novel in-place sorting algorithm is presented. The algorithm comprises two phases; rearranging the input unsorted array in place, resulting segments that are ordered relative to each other but whose elements are yet to be sorted. The first phase requires linear time, while, in the second phase, elements of each segment are sorted inplace in the order of z log (z), where z is the size of the segment, and O(1) auxiliary storage. The algorithm performs, in the worst case, for an array of size n, an O(n log z) element comparisons and O(n log z) element moves. Further, no auxiliary arithmetic operations with indices are required. Besides these theoretical achievements of this algorithm, it is of practical interest, because of its simplicity. Experimental results also show that it outperforms other in-place sorting algorithms. Finally, the analysis of time and space complexity, and required number of moves are presented, along with the auxiliary storage requirements of the proposed algorithm.

Keywords: Auxiliary storage sorting, in-place sorting, sorting.

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Authors: Hatem Hajri, Mohamed-Cherif Rahal

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Both Lidars and Radars are sensors for obstacle detection. While Lidars are very accurate on obstacles positions and less accurate on their velocities, Radars are more precise on obstacles velocities and less precise on their positions. Sensor fusion between Lidar and Radar aims at improving obstacle detection using advantages of the two sensors. The present paper proposes a real-time Lidar/Radar data fusion algorithm for obstacle detection and tracking based on the global nearest neighbour standard filter (GNN). This algorithm is implemented and embedded in an automative vehicle as a component generated by a real-time multisensor software. The benefits of data fusion comparing with the use of a single sensor are illustrated through several tracking scenarios (on a highway and on a bend) and using real-time kinematic sensors mounted on the ego and tracked vehicles as a ground truth.

Keywords: Ground truth, Hungarian algorithm, lidar Radar data fusion, global nearest neighbor filter.

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Authors: J. Alamelu Mangai, Satej Wagle, V. Santhosh Kumar

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The exponential increase in the volume of medical image database has imposed new challenges to clinical routine in maintaining patient history, diagnosis, treatment and monitoring. With the advent of data mining and machine learning techniques it is possible to automate and/or assist physicians in clinical diagnosis. In this research a medical image classification framework using data mining techniques is proposed. It involves feature extraction, feature selection, feature discretization and classification. In the classification phase, the performance of the traditional kNN k nearest neighbor classifier is improved using a feature weighting scheme and a distance weighted voting instead of simple majority voting. Feature weights are calculated using the interestingness measures used in association rule mining. Experiments on the retinal fundus images show that the proposed framework improves the classification accuracy of traditional kNN from 78.57 % to 92.85 %.

Keywords: Medical Image Mining, Data Mining, Feature Weighting, Association Rule Mining, k nearest neighbor classifier.

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Authors: Sh. Shahhosseini, S. Alinia, M. Irani

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In this paper 2D Simulation of catalytic Fixed Bed Reactor in Fischer-Tropsch Synthesis of GTL technology has been performed utilizing computational fluid dynamics (CFD). Synthesis gas (a mixture of carbon monoxide and hydrogen) has been used as feedstock. The reactor was modeled and the model equations were solved employing finite volume method. The model was validated against the experimental data reported in literature. The comparison showed a good agreement between simulation results and the experimental data. In addition, the model was applied to predict the concentration contours of the reactants and products along the length of reactor.

Keywords: GTL, Fischer–Tropsch synthesis, Fixed Bed Reactor, CFD simulation.

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Authors: Qihe Li, Yupin Luo

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Camera calibration plays an important role in the domain of the analysis of sports video. Considering soccer video, in most cases, the cross-points can be used for calibration at the center of the soccer field are not sufficient, so this paper introduces a new automatic camera calibration algorithm focus on solving this problem by using the properties of images of the center circle, halfway line and a touch line. After the theoretical analysis, a practicable automatic algorithm is proposed. Very little information used though, results of experiments with both synthetic data and real data show that the algorithm is applicable.

Keywords: Absolute conic, camera calibration, circular points, line at infinity.

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Authors: V. Zangeneh, S. Mohammadi

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Today, node-disjoint routing becomes inessential technique in communication of packets among various nodes in networks. Meanwhile AODV (Ad Hoc On-demand Multipath Distance Vector) creates single-path route between a pair of source and destination nodes. Some researches has done so far to make multipath node-disjoint routing based on AODV protocol. But however their overhead and end-to-end delay are relatively high, while the detail of their code is not available too. This paper proposes a new approach of multipath node-disjoint routing based on AODV protocol. Then the algorithm of analytical model is presented. The extensive results of this algorithm will be presented in the next paper.

Keywords: AODV; MANET; Multipath Routing; Node-disjoint;transmission delay.

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Authors: Karen Armstrong

Abstract:

This paper examines the issues, the dangers and the saving graces of life in a transparent global community where there is truly “no place to hide". In recent years, social networks and online groups have transformed issues of privacy and the ways in which we perceive and interact with others. The idea of reputation is critical to this dynamic. The discussion begins with a brief etymological history of the concept of reputation and moves to an exploration of how and why online communication changes our basic nature, our various selves and the Bakhtin idea of the polyphonic nature of truth. The discussion considers the damaging effects of bullying and gossip, both of which constitute an assault on reputation and the latter of which is not limited to the lifetime of the person. It concludes with guidelines and specific recommendations.

Keywords: online reputation, gossip, cyberbullying, privacy

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Authors: R. Manjith, C. Muthukumari

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In this paper, a novel Linear Feedback Shift Register (LFSR) with Look Ahead Clock Gating (LACG) technique is presented to reduce the power consumption in modern processors and System-on-Chip. Clock gating is a predominant technique used to reduce unwanted switching of clock signals. Several clock gating techniques to reduce the dynamic power have been developed, of which LACG is predominant. LACG computes the clock enabling signals of each flip-flop (FF) one cycle ahead of time, based on the present cycle data of the flip-flops on which it depends. It overcomes the timing problems in the existing clock gating methods like datadriven clock gating and Auto-Gated flip-flops (AGFF) by allotting a full clock cycle for the determination of the clock enabling signals. Further to reduce the power consumption in LACG technique, FFs can be grouped so that they share a common clock enabling signal. Simulation results show that the novel grouped LFSR with LACG achieves 15.03% power savings than conventional LFSR with LACG and 44.87% than data-driven clock gating.

Keywords: AGFF, data-driven, LACG, LFSR.

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Authors: Fazıl Gökgöz, Fahrettin Filiz

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Electricity prices have sophisticated features such as high volatility, nonlinearity and high frequency that make forecasting quite difficult. Electricity price has a volatile and non-random character so that, it is possible to identify the patterns based on the historical data. Intelligent decision-making requires accurate price forecasting for market traders, retailers, and generation companies. So far, many shallow-ANN (artificial neural networks) models have been published in the literature and showed adequate forecasting results. During the last years, neural networks with many hidden layers, which are referred to as DNN (deep neural networks) have been using in the machine learning community. The goal of this study is to investigate electricity price forecasting performance of the shallow-ANN and DNN models for the Turkish day-ahead electricity market. The forecasting accuracy of the models has been evaluated with publicly available data from the Turkish day-ahead electricity market. Both shallow-ANN and DNN approach would give successful result in forecasting problems. Historical load, price and weather temperature data are used as the input variables for the models. The data set includes power consumption measurements gathered between January 2016 and December 2017 with one-hour resolution. In this regard, forecasting studies have been carried out comparatively with shallow-ANN and DNN models for Turkish electricity markets in the related time period. The main contribution of this study is the investigation of different shallow-ANN and DNN models in the field of electricity price forecast. All models are compared regarding their MAE (Mean Absolute Error) and MSE (Mean Square) results. DNN models give better forecasting performance compare to shallow-ANN. Best five MAE results for DNN models are 0.346, 0.372, 0.392, 0,402 and 0.409.

Keywords: Deep learning, artificial neural networks, energy price forecasting, Turkey.

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Authors: Anjan Babu G, Sumana G, Rajasekhar M

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Many inherited diseases and non-hereditary disorders are common in the development of renal cystic diseases. Polycystic kidney disease (PKD) is a disorder developed within the kidneys in which grouping of cysts filled with water like fluid. PKD is responsible for 5-10% of end-stage renal failure treated by dialysis or transplantation. New experimental models, application of molecular biology techniques have provided new insights into the pathogenesis of PKD. Researchers are showing keen interest for developing an automated system by applying computer aided techniques for the diagnosis of diseases. In this paper a multilayered feed forward neural network with one hidden layer is constructed, trained and tested by applying back propagation learning rule for the diagnosis of PKD based on physical symptoms and test results of urinalysis collected from the individual patients. The data collected from 50 patients are used to train and test the network. Among these samples, 75% of the data used for training and remaining 25% of the data are used for testing purpose. Further, this trained network is used to implement for new samples. The output results in normality and abnormality of the patient.

Keywords: Dialysis, Hereditary, Transplantation, Polycystic, Pathogenesis.

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Authors: Kavita Khairnar, Shikha Nema

Abstract:

DS-CDMA system is well known wireless technology. This system suffers from MAI (Multiple Access Interference) caused by Direct Sequence users. Multi-User Detection schemes were introduced to detect the users- data in presence of MAI. This paper focuses on linear multi-user detection schemes used for data demodulation. Simulation results depict the performance of three detectors viz-conventional detector, Decorrelating detector and Subspace MMSE (Minimum Mean Square Error) detector. It is seen that the performance of these detectors depends on the number of paths and the length of Gold code used.

Keywords: Cross Correlation Matrix, MAI, Multi-UserDetection, Multipath Effect.

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Authors: Yuji Mizuno, Hiroshi Mabuchi

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Initial values of reference vectors have significant influence on recognition accuracy in LVQ. There are several existing techniques, such as SOM and k-means, for setting initial values of reference vectors, each of which has provided some positive results. However, those results are not sufficient for the improvement of recognition accuracy. This study proposes an ACO-used method for initializing reference vectors with an aim to achieve recognition accuracy higher than those obtained through conventional methods. Moreover, we will demonstrate the effectiveness of the proposed method by applying it to the wine data and English vowel data and comparing its results with those of conventional methods.

Keywords: Clustering, LVQ, ACO, SOM, k-means.

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Authors: Jorge Martinez-Garcia, Ingrid Stelzner, Joerg Stelzner, Damian Gwerder, Philipp Schuetz

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Tree-ring analysis is an important part of the quality assessment and the dating of (archaeological) wood samples. It provides quantitative data about the whole anatomical ring structure, which can be used, for example, to measure the impact of the fluctuating environment on the tree growth, for the dendrochronological analysis of archaeological wooden artefacts and to estimate the wood mechanical properties. Despite advances in computer vision and edge recognition algorithms, detection and counting of annual rings are still limited to 2D datasets and performed in most cases manually, which is a time consuming, tedious task and depends strongly on the operator’s experience. This work presents an image processing approach to detect the whole 3D tree-ring structure directly from X-ray computed tomography imaging data. The approach relies on a modified Canny edge detection algorithm, which captures fully connected tree-ring edges throughout the measured image stack and is validated on X-ray computed tomography data taken from six wood species.

Keywords: Ring recognition, edge detection, X-ray computed tomography, dendrochronology.

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Authors: H. Al-Sholigom, Z. Al-Mostafa

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Many associations and experimental models have been developed to estimate solar radiation around the world. The duration of sunshine is the most commonly used parameter for estimating global solar radiation because it can be easily and reliably measured. To estimate the global monthly solar average on horizontal surfaces, we used 52 models with widely available data in Hutat Suder, Saudi Arabia. After testing the models, some were not suitable for use in this area, while others differed in performance. The best models have been identified.

Keywords: Earth, Global solar radiation, Hutat Suder, Saudi Arabia, sunshine, measured data.

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Authors: Supattra Kanchanopast

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The purpose of this research was to identify factors that influenced the success of e-commerce implementation within SMEs businesses. In order to achieve the objectives of this research, the researcher collected data from random firms in Thailand, both the users and those who are not using the e-commerce. The data was comprised of the results of 310 questionnaires, as well as 10 interviews with owner/managers of businesses who are currently using e-commerce successfully. The data were analyzed by using descriptive statistics, which included frequency, percentages, mean, and the standard deviation of pertinent factors. Independent t-test and one-way ANOVA test were also used. The findings of this research revealed that 50% of all the firms surveyed had e-commerce website, whereas, over 20% of all firms surveyed had developing an ecommerce strategy. The result findings also indicate that organizational factors, technological factors and environment factors as significant factors effecting success of e-commerce implementation in SMEs. From the hypotheses testing, the findings revealed that the different level of support use ecommerce by owner/manager had different success in e-commerce implementation. Moreover, the difference in e-commerce management approach affected the success in terms of higher total sales for the business or higher number of retained or returning customers.

Keywords: Electronic commerce, Implementation of ECommerce, small and medium sized enterprises, SMEs, Website, success factors.

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