Search results for: Data analysis

Authors: Wael I. Alnahhal

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It is a major challenge to build a bridge superstructure that has long-term durability and low maintenance requirements. A solution to this challenge may be to use new materials or to implement new structural systems. Fiber Reinforced Polymer (FRP) composites have continued to play an important role in solving some of persistent problems in infrastructure applications because of its high specific strength, light weight, and durability. In this study, the concept of the hybrid FRP-concrete structural systems is applied to a bridge superstructure. The hybrid FRP-concrete bridge superstructure is intended to have durable, structurally sound, and cost effective hybrid system that will take full advantage of the inherent properties of both FRP materials and concrete. In this study, two hybrid FRP-concrete bridge systems were investigated. The first system consists of trapezoidal cell units forming a bridge superstructure. The second one is formed by arch cells. The two systems rely on using cellular components to form the core of the bridge superstructure, and an outer shell to warp around those cells to form the integral unit of the bridge. Both systems were investigated analytically by using finite element (FE) analysis. From the rigorous FE studies, it was concluded that first system is more efficient than the second.

Keywords: Bridge superstructure, hybrid system, fiber reinforced polymer, finite element analysis.

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Authors: Ju-Hong Lee, Chong-Jia Ciou

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This paper deals with the problem of two-dimensional (2-D) recursive two-channel quincunx quadrature mirror filter (QQMF) banks design. The analysis and synthesis filters of the 2-D recursive QQMF bank are composed of 2-D recursive digital allpass lattice filters (DALFs) with symmetric half-plane (SHP) support regions. Using the 2-D doubly complementary half-band (DC-HB) property possessed by the analysis and synthesis filters, we facilitate the design of the proposed QQMF bank. For finding the coefficients of the 2-D recursive SHP DALFs, we present a structure of 2-D recursive digital allpass filters by using 2-D SHP recursive digital all-pass lattice filters (DALFs). The novelty of using 2-D SHP recursive DALFs to construct a 2-D recursive QQMF bank is that the resulting 2-D recursive QQMF bank provides better performance than the existing 2-D recursive QQMF banks. Simulation results are also presented for illustration and comparison.

Keywords: All-pass digital filter, doubly complementary, lattice structure, symmetric half-plane digital filter, quincunx QMF bank.

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Authors: E. Kharaishvili

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The paper analyses the role of small farms in socio-economic development of agriculture in Georgia and evaluates modern concepts regarding the development of the farms of this size. The scale of farms in Georgia is studied and the major problems are revealed. Opportunities and directions of diversification are discussed from the point of increasing the share of Georgian grapes and wine both on domestic and international markets. It’s shown that the size of vineyard areas is directly reflected on the grape and wine production potential. Accordingly, vineyard area and grape production dynamics is discussed. Comparative analysis of small farms in Georgia and Italy is made and the major differences are identified. Diversification is evaluated based on cost-benefit analysis on the one hand and on the other hand, from the point of promoting economic activities, protecting nature and rural area development. The paper provides proofs for the outcomes of diversification. The key hindering factors for the development of small farms are identified and corresponding conclusions are made, based on which recommendations for diversification of the farms of this size are developed.

Keywords: Farm diversification, scale of farms, small farms, viticulture-winemaking.

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Authors: Rita U. Onolemhemhen, Saheed L. Bello, Akin P. Iwayemi

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The effectiveness of energy demand policy depends on identifying the key drivers of energy demand both in the short-run and the long-run. This paper examines the influence of regional differences on the link between energy demand and other explanatory variables for Nigeria, China and USA using the Vector Error Correction Model (VECM) approach. This study employed annual time series data on energy consumption (ED), real gross domestic product (GDP) per capita (RGDP), real energy prices (P) and urbanization (N) for a thirty-six-year sample period. The utilized time-series data are sourced from World Bank’s World Development Indicators (WDI, 2016) and US Energy Information Administration (EIA). Results from the study, shows that all the independent variables (income, urbanization, and price) substantially affect the long-run energy consumption in Nigeria, USA and China, whereas, income has no significant effect on short-run energy demand in USA and Nigeria. In addition, the long-run effect of urbanization is relatively stronger in China. Urbanization is a key factor in energy demand, it therefore recommended that more attention should be given to the development of rural communities to reduce the inflow of migrants into urban communities which causes the increase in energy demand and energy excesses should be penalized while energy management should be incentivized.

Keywords: Economic growth, energy demand, income, real GDP, urbanization, VECM.

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Authors: Wasiu O. Ajagbe, Habeeb O. Hamzat, Waris A. Adebisi

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Structural failures occur due to a number of reasons. These may include under design, poor workmanship, substandard materials, misleading laboratory tests and lots more. Reinforcing steel bar is an important construction material, hence its properties must be accurately known before being utilized in construction. Understanding this property involves carrying out mechanical tests prior to design and during construction to ascertain correlation using steel testing machine which is usually not readily available due to the location of project. This study was conducted to determine the reliability of reinforcing steel testing machines. Reconnaissance survey was conducted to identify laboratories where yield and ultimate tensile strengths tests can be carried out. Six laboratories were identified within Ibadan and environs. However, only four were functional at the time of the study. Three steel samples were tested for yield and tensile strengths, using a steel testing machine, at each of the four laboratories (LM, LO, LP and LS). The yield and tensile strength results obtained from the laboratories were compared with the manufacturer’s specification using a reliability analysis programme. Structured questionnaire was administered to the operators in each laboratory to consider their impact on the test results. The average value of manufacturers’ tensile strength and yield strength are 673.7 N/mm² and 559.7 N/mm² respectively. The tensile strength obtained from the four laboratories LM, LO, LP and LS are given as 579.4, 652.7, 646.0 and 649.9 N/mm² respectively while their yield strengths respectively are 453.3, 597.0, 550.7 and 564.7 N/mm². Minimum tensile to yield strength ratio is 1.08 for BS 4449: 2005 and 1.15 for ASTM A615. Tensile to yield strength ratio from the four laboratories are 1.28, 1.09, 1.17 and 1.15 for LM, LO, LP and LS respectively. The tensile to yield strength ratio shows that the result obtained from all the laboratories meet the code requirements used for the test. The result of the reliability test shows varying level of reliability between the manufacturers’ specification and the result obtained from the laboratories. Three of the laboratories; LO, LS and LP have high value of reliability with the manufacturer i.e. 0.798, 0.866 and 0.712 respectively. The fourth laboratory, LM has a reliability value of 0.100. Steel test should be carried out in a laboratory using the same code in which the structural design was carried out. More emphasis should be laid on the importance of code provisions.

Keywords: Reinforcing steel bars, reliability analysis, tensile strength, universal testing machine, yield strength.

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Authors: Petronella Jonck, Freda van der Walt

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Despite the benefits of innovation diffusion in the South African public service, implementation thereof seems to be problematic, particularly with regard to e-governance which would enhance the quality of service delivery, especially accessibility, choice, and mode of operation. This paper reports on differences between the public service and the private sector in terms of innovation diffusion. Innovation diffusion will be investigated to explore identified obstacles that are hindering successful implementation of e-governance. The research inquiry is underpinned by the diffusion of innovation theory, which is premised on the assumption that innovation has a distinct channel, time, and mode of adoption within the organisation. A comparative thematic document analysis was conducted to investigate organisational differences with regard to innovation diffusion. A similar approach has been followed in other countries, where the same conceptual framework has been used to guide document analysis in studies in both the private and the public sectors. As per the recommended conceptual framework, three organisational characteristics were emphasised, namely the external characteristics of the organisation, the organisational structure, and the inherent characteristics of the leadership. The results indicated that the main difference in the external characteristics lies in the focus and the clientele of the private sector. With regard to organisational structure, private organisations have veto power, which is not the case in the public service. Regarding leadership, similarities were observed in social and environmental responsibility and employees’ attitudes towards immediate supervision. Differences identified included risk taking, the adequacy of leadership development, organisational approaches to motivation and involvement in decision making, and leadership style. Due to the organisational differences observed, it is recommended that differentiated strategies be employed to ensure effective innovation diffusion, and ultimately e-governance. It is recommended that the results of this research be used to stimulate discussion on ways to improve collaboration between the mentioned sectors, to capitalise on the benefits of each sector.

Keywords: E-governance, ICT, innovation diffusion, comparative analysis.

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Authors: Ákos Wolf, Richard P. Ray

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Due to the introduction of Eurocode 8, the structural design for seismic and dynamic effects has become more significant in Hungary. This has emphasized the need for more effort to describe the behavior of structures under these conditions. Soil conditions have a significant effect on the response of structures by modifying the stiffness and damping of the soil-structural system and by modifying the seismic action as it reaches the ground surface. Shear modulus (G) and shear wave velocity (v_s), which are often measured in the field, are the fundamental dynamic soil properties for foundation vibration problems, liquefaction potential and earthquake site response analysis. There are several laboratory and in-situ measurement techniques to evaluate dynamic soil properties, but unfortunately, they are often too expensive for general design practice. However, a significant number of correlations have been proposed to determine shear wave velocity or shear modulus from Cone Penetration Tests (CPT), which are used more and more in geotechnical design practice in Hungary. This allows the designer to analyze and compare CPT and seismic test result in order to select the best correlation equations for Hungarian soils and to improve the recommendations for the Hungarian geologic conditions. Based on a literature review, as well as research experience in Hungary, the influence of various parameters on the accuracy of results will be shown. This study can serve as a basis for selecting and modifying correlation equations for Hungarian soils. Test data are taken from seven locations in Hungary with similar geologic conditions. The shear wave velocity values were measured by seismic CPT. Several factors are analyzed including soil type, behavior index, measurement depth, geologic age etc. for their effect on the accuracy of predictions. The final results show an improved prediction method for Hungarian soils

Keywords: CPT correlation, dynamic soil properties, seismic CPT, shear wave velocity.

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Authors: Mohammad Shoyaib, M. Abdullah-Al-Wadud, Oksam Chae

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Proteomics is one of the largest areas of research for bioinformatics and medical science. An ambitious goal of proteomics is to elucidate the structure, interactions and functions of all proteins within cells and organisms. Predicting Protein-Protein Interaction (PPI) is one of the crucial and decisive problems in current research. Genomic data offer a great opportunity and at the same time a lot of challenges for the identification of these interactions. Many methods have already been proposed in this regard. In case of in-silico identification, most of the methods require both positive and negative examples of protein interaction and the perfection of these examples are very much crucial for the final prediction accuracy. Positive examples are relatively easy to obtain from well known databases. But the generation of negative examples is not a trivial task. Current PPI identification methods generate negative examples based on some assumptions, which are likely to affect their prediction accuracy. Hence, if more reliable negative examples are used, the PPI prediction methods may achieve even more accuracy. Focusing on this issue, a graph based negative example generation method is proposed, which is simple and more accurate than the existing approaches. An interaction graph of the protein sequences is created. The basic assumption is that the longer the shortest path between two protein-sequences in the interaction graph, the less is the possibility of their interaction. A well established PPI detection algorithm is employed with our negative examples and in most cases it increases the accuracy more than 10% in comparison with the negative pair selection method in that paper.

Keywords: Interaction graph, Negative training data, Protein-Protein interaction, Support vector machine.

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Authors: M. Nakisa, A. Maimun, Yasser M. Ahmed, F. Behrouzi, A. Tarmizi

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The practical application of the Computational Fluid Dynamics (CFD), for predicting the flow pattern around Multipurpose Amphibious Vehicle (MAV) hull has made much progress over the last decade. Today, several of the CFD tools play an important role in the land and water going vehicle hull form design. CFD has been used for analysis of MAV hull resistance, sea-keeping, maneuvering and investigating its variation when changing the hull form due to varying its parameters, which represents a very important task in the principal and final design stages. Resistance analysis based on CFD (Computational Fluid Dynamics) simulation has become a decisive factor in the development of new, economically efficient and environmentally friendly hull forms. Three-dimensional finite volume method (FVM) based on Reynolds Averaged Navier-Stokes equations (RANS) has been used to simulate incompressible flow around three types of MAV hull bow models in steady-state condition. Finally, the flow structure and streamlines, friction and pressure resistance and velocity contours of each type of hull bow will be compared and discussed.

Keywords: RANS Simulation, Multipurpose Amphibious Vehicle, Viscous Flow Structure.

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Authors: J. Hrabovský, M. Chabičovský, J. Horský

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Water spray cooling is a technique typically used in heat treatment and other metallurgical processes where controlled temperature regimes are required. Water spray cooling is used in static (without movement) or dynamic (with movement of the steel plate) regimes. The static regime is notable for the fixed position of the hot steel plate and fixed spray nozzle. This regime is typical for quenching systems focused on heat treatment of the steel plate. The second application of spray cooling is the dynamic regime. The dynamic regime is notable for its static section cooling system and moving steel plate. This regime is used in rolling and finishing mills. The fixed position of cooling sections with nozzles and the movement of the steel plate produce nonhomogeneous water distribution on the steel plate. The length of cooling sections and placement of water nozzles in combination with the nonhomogeneity of water distribution lead to discontinued or interrupted cooling conditions. The impact of static and dynamic regimes on cooling intensity and the heat transfer coefficient during the cooling process of steel plates is an important issue. Heat treatment of steel is accompanied by oxide scale growth. The oxide scale layers can significantly modify the cooling properties and intensity during the cooling. The combination of static and dynamic (section) regimes with the variable thickness of the oxide scale layer on the steel surface impact the final cooling intensity. The study of the influence of the oxide scale layers with different cooling regimes was carried out using experimental measurements and numerical analysis. The experimental measurements compared both types of cooling regimes and the cooling of scale-free surfaces and oxidized surfaces. A numerical analysis was prepared to simulate the cooling process with different conditions of the section and samples with different oxide scale layers.

Keywords: Heat transfer coefficient, numerical analysis, oxide layer, spray cooling.

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Authors: Azza. S. Naik, S. S. Lele

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Indian subcontinent has a plethora of traditional medicine systems that provide promising solutions to lifestyle disorders in an 'all natural way'. Spices and oilseeds hold prominence in Indian cuisine hence the focus of the current study was to evaluate the bioactive molecules from Linum usitatissinum (LU), Lepidium sativum (LS), Nigella sativa (NS) and Guizotia abyssinica (GA) seeds. The seeds were characterized for functional lipids like omega-3 fatty acid, antioxidant capacity, phenolic compounds, dietary fiber and anti-nutritional factors. Analysis of the seeds revealed LU and LS to be a rich source of α-linolenic acid (41.85 ± 0.33%, 26.71 ± 0.63%), an omega 3 fatty acid (using GCMS). While studying antioxidant potential NS seeds demonstrated highest antioxidant ability (61.68 ± 0.21 TEAC/ 100 gm DW) due to the presence of phenolics and terpenes as assayed by the Mass spectral analysis. When screened for anti-nutritional factor cyanogenic glycoside, LS seeds showed content as high as 1674 ± 54 mg HCN / kg. GA is a probable good source of a stable vegetable oil (SFA: PUFA 1:2.3). The seeds showed diversified bioactive profile and hence further studies to use different bio molecules in tandem for the development of a possible 'nutraceutical cocktail' have been initiated..

Keywords: antioxidants, bioactives, functional lipids and oilseeds

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Authors: Dariush Semnani, Mehdi Ahangareianabhari, Hossein Ghayoor

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In recent five decades, textured yarns of polyester fiber produced by false twist method are the most important and mass-produced manmade fibers. There are many parameters of cross section which affect the physical and mechanical properties of textured yarns. These parameters are surface area, perimeter, equivalent diameter, large diameter, small diameter, convexity, stiffness, eccentricity, and hydraulic diameter. These parameters were evaluated by digital image processing techniques. To find trends between production criteria and evaluated parameters of cross section, three criteria of production line have been adjusted and different types of yarns were produced. These criteria are temperature, drafting ratio, and D/Y ratio. Finally the relations between production criteria and cross section parameters were considered. The results showed that the presented technique can recognize and measure the parameters of fiber cross section in acceptable accuracy. Also, the optimum condition of adjustments has been estimated from results of image analysis evaluation.

Keywords: Computer Vision, Cross Section Analysis, Fibers Deformation, Textured Yarn

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Authors: Supachai Tangwongsan, Sathaporn Kassuvan

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The purpose of this research is to develop a security model for voice eavesdropping protection over digital networks. The proposed model provides an encryption scheme and a personal secret key exchange between communicating parties, a so-called voice data transformation system, resulting in a real-privacy conversation. The operation of this system comprises two main steps as follows: The first one is the personal secret key exchange for using the keys in the data encryption process during conversation. The key owner could freely make his/her choice in key selection, so it is recommended that one should exchange a different key for a different conversational party, and record the key for each case into the memory provided in the client device. The next step is to set and record another personal option of encryption, either taking all frames or just partial frames, so-called the figure of 1:M. Using different personal secret keys and different sets of 1:M to different parties without the intervention of the service operator, would result in posing quite a big problem for any eavesdroppers who attempt to discover the key used during the conversation, especially in a short period of time. Thus, it is quite safe and effective to protect the case of voice eavesdropping. The results of the implementation indicate that the system can perform its function accurately as designed. In this regard, the proposed system is suitable for effective use in voice eavesdropping protection over digital networks, without any requirements to change presently existing network systems, mobile phone network and VoIP, for instance.

Keywords: Computer Security, Encryption, Key Exchange, Security Model, Voice Eavesdropping.

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Authors: T. Boonkang, C. Santhaweesuk, N. Pianthong, P. Neeramon, A. Phimhlo, S. Bangphan

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The objective of this research was to apply metakaolin from northeast of Thailand as a binder in the casting process of rice polishing cylinder in replacement of the imported calcined magnesite cement and to reduce the production cost of the cylinder. Metakaolin was obtained from three different regions (Udon Thani, Nakhon Phanom, and Ubon Ratchathani). The design of experiment analysis using the MINITAB Release 14 based on the compressive strength and tensile strength testing was conducted. According to the analysis results, it was found that the optimal proportions were calcined magnesite cement: metakaolin from Udon Thani, Nakhon Phanom and Ubon Ratchathani equal to 63:37, 71:29, and 100:0, respectively. When used this formula to cast the cylinder and test the rice milling, it was found that the average broken rice percent was 32.52 and 38.29 for the cylinder contained the metakaolin from Udon Thani and Nakhon Phanom, respectively, which implied that the cylinder which contained the metakaolin from Udon Thani has higher efficiency than the cylinder which contained the metakaolin from Nakhon Phanom at 0.05 level of statistical significance. Whereas, the average wear rate of cylinder from both resources were 7.27 and 6.53 g/h, respectively.

Keywords: Binder, casting, metakaolin, rice polishing cylinder.

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Authors: Ronal Muresano, Andrea Pagano

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Nowadays, the mathematical/statistical applications are developed with more complexity and accuracy. However, these precisions and complexities have brought as result that applications need more computational power in order to be executed faster. In this sense, the multicore environments are playing an important role to improve and to optimize the execution time of these applications. These environments allow us the inclusion of more parallelism inside the node. However, to take advantage of this parallelism is not an easy task, because we have to deal with some problems such as: cores communications, data locality, memory sizes (cache and RAM), synchronizations, data dependencies on the model, etc. These issues are becoming more important when we wish to improve the application’s performance and scalability. Hence, this paper describes an optimization method developed for Systemic Model of Banking Originated Losses (SYMBOL) tool developed by the European Commission, which is based on analyzing the application's weakness in order to exploit the advantages of the multicore. All these improvements are done in an automatic and transparent manner with the aim of improving the performance metrics of our tool. Finally, experimental evaluations show the effectiveness of our new optimized version, in which we have achieved a considerable improvement on the execution time. The time has been reduced around 96% for the best case tested, between the original serial version and the automatic parallel version.

Keywords: Algorithm optimization, Bank Failures, OpenMP, Parallel Techniques, Statistical tool.

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Authors: Chiung-Ju Huang, Yuan-Hong Ho

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This paper develops the fiscal health index of 21 local governments in Taiwan over the 1984 to 2010 period. A quantile regression analysis was used to explore the extent that economic variables, political budget cycles, and legislative checks and balances, impact different quantiles of fiscal health index for a country over a sample period of time. Our findings suggest that local governments at the lower quantile are significantly benefited from political budget cycles and the increase in central government revenues, while legislative effective checks and balances and the increase in central government expenditures have a significantly negative effect on local fiscal health. When local governments are in the upper tail of the distribution, legislative checks and balances and growth in macroeconomics have significant and adverse effects on the fiscal health of local governments. However, increases in central government revenues have significant and positive effects on the health status of local government in Taiwan.

Keywords: Fiscal health, political budget cycles, legislative checks and balances, quantile regression.

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Authors: Birendra Kumar Bohara

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The hillside building shows different behavior as a flat ground building in lateral loading. Especially the step back building in the sloping ground has different seismic behavior. The hillside building 3D model having different types of structural elements is introduced and analyzed with a seismic effect. The structural elements such as the shear wall, steel, and concrete bracing are used to resist the earthquake load and compared with without using any shear wall and bracing system. The X, inverted V, and diagonal bracing are used. The total nine models are prepared in ETABs finite element coding software. The linear dynamic analysis is the response spectrum analysis (RSA) carried out to study dynamic behaviors in means of top story displacement, story drift, fundamental time period, story stiffness, and story shear. The results are analyzed and made some decisions based on seismic performance. It is also observed that it is better to use the X bracing system for lateral load resisting elements.

Keywords: Step-back buildings, bracing system, hill side buildings, response spectrum method.

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Authors: Narasimham Challa, Jayaram Pradhan

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Cryptographic algorithms play a crucial role in the information society by providing protection from unauthorized access to sensitive data. It is clear that information technology will become increasingly pervasive, Hence we can expect the emergence of ubiquitous or pervasive computing, ambient intelligence. These new environments and applications will present new security challenges, and there is no doubt that cryptographic algorithms and protocols will form a part of the solution. The efficiency of a public key cryptosystem is mainly measured in computational overheads, key size and bandwidth. In particular the RSA algorithm is used in many applications for providing the security. Although the security of RSA is beyond doubt, the evolution in computing power has caused a growth in the necessary key length. The fact that most chips on smart cards can-t process key extending 1024 bit shows that there is need for alternative. NTRU is such an alternative and it is a collection of mathematical algorithm based on manipulating lists of very small integers and polynomials. This allows NTRU to high speeds with the use of minimal computing power. NTRU (Nth degree Truncated Polynomial Ring Unit) is the first secure public key cryptosystem not based on factorization or discrete logarithm problem. This means that given sufficient computational resources and time, an adversary, should not be able to break the key. The multi-party communication and requirement of optimal resource utilization necessitated the need for the present day demand of applications that need security enforcement technique .and can be enhanced with high-end computing. This has promoted us to develop high-performance NTRU schemes using approaches such as the use of high-end computing hardware. Peer-to-peer (P2P) or enterprise grids are proven as one of the approaches for developing high-end computing systems. By utilizing them one can improve the performance of NTRU through parallel execution. In this paper we propose and develop an application for NTRU using enterprise grid middleware called Alchemi. An analysis and comparison of its performance for various text files is presented.

Keywords: Alchemi, GridNtru, Ntru, PKCS.

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Authors: Samraj Andrews, Ramaswamy Palaniappan, Nidal Kamel

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In single trial analysis, when using Principal Component Analysis (PCA) to extract Visual Evoked Potential (VEP) signals, the selection of principal components (PCs) is an important issue. We propose a new method here that selects only the appropriate PCs. We denote the method as selective eigen-rate (SER). In the method, the VEP is reconstructed based on the rate of the eigen-values of the PCs. When this technique is applied on emulated VEP signals added with background electroencephalogram (EEG), with a focus on extracting the evoked P3 parameter, it is found to be feasible. The improvement in signal to noise ratio (SNR) is superior to two other existing methods of PC selection: Kaiser (KSR) and Residual Power (RP). Though another PC selection method, Spectral Power Ratio (SPR) gives a comparable SNR with high noise factors (i.e. EEGs), SER give more impressive results in such cases. Next, we applied SER method to real VEP signals to analyse the P3 responses for matched and non-matched stimuli. The P3 parameters extracted through our proposed SER method showed higher P3 response for matched stimulus, which confirms to the existing neuroscience knowledge. Single trial PCA using KSR and RP methods failed to indicate any difference for the stimuli.

Keywords: Electroencephalogram, P3, Single trial VEP.

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Authors: Hema C. R., Paulraj M. P., S. Yaacob, A. H. Adom, R. Nagarajan

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Motor imagery classification provides an important basis for designing Brain Machine Interfaces [BMI]. A BMI captures and decodes brain EEG signals and transforms human thought into actions. The ability of an individual to control his EEG through imaginary mental tasks enables him to control devices through the BMI. This paper presents a method to design a four state BMI using EEG signals recorded from the C3 and C4 locations. Principle features extracted through principle component analysis of the segmented EEG are analyzed using two novel classification algorithms using Elman recurrent neural network and functional link neural network. Performance of both classifiers is evaluated using a particle swarm optimization training algorithm; results are also compared with the conventional back propagation training algorithm. EEG motor imagery recorded from two subjects is used in the offline analysis. From overall classification performance it is observed that the BP algorithm has higher average classification of 93.5%, while the PSO algorithm has better training time and maximum classification. The proposed methods promises to provide a useful alternative general procedure for motor imagery classification

Keywords: Motor Imagery, Brain Machine Interfaces, Neural Networks, Particle Swarm Optimization, EEG signal processing.

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Authors: Debasis Sarkar, Jatan Talati

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This paper is an attempt to develop an Integrated Mass Rapid Transit System (MRTS) for a smart city project in Western India. Integrated transportation is one of the enablers of smart transportation for providing a seamless intercity as well as regional level transportation experience. The success of a smart city project at the city level for transportation is providing proper integration to different mass rapid transit modes by way of integrating information, physical, network of routes fares, etc. The methodology adopted for this study was primary data research through questionnaire survey. The respondents of the questionnaire survey have responded on the issues about their perceptions on the ways and means to improve public transport services in urban cities. The respondents were also required to identify the factors and attributes which might motivate more people to shift towards the public mode. Also, the respondents were questioned about the factors which they feel might restrain the integration of various modes of MRTS. Furthermore, this study also focuses on developing a utility equation for respondents with the help of multiple linear regression analysis and its probability to shift to public transport for certain factors listed in the questionnaire. It has been observed that for shifting to public transport, the most important factors that need to be considered were travel time saving and comfort rating. Also, an Integrated MRTS can be obtained by combining metro rail with BRTS, metro rail with monorail, monorail with BRTS and metro rail with Indian railways. Providing a common smart card to transport users for accessing all the different available modes would be a pragmatic solution towards integration of the available modes of MRTS.

Keywords: Mass rapid transit systems, smart city, metro rail, bus rapid transit system, multiple linear regression, smart card, automated fare collection system.

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Authors: Vinay Gautam, Vivek Gautam

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With increase in the unauthorized users access, it is required to increase the security in the Near Field Communication (NFC). In the paper we propose a user behavior based enhanced protocol entitled ‘User Behavior based Enhanced Protocol (UBEP)’ to increase the security in NFC enabled devices. The UBEP works on the history of interaction of a user with system.The propose protocol considers four different factors (touch, time and distance & angle) of user behavior to know the authenticity or authorization of the users. These factors can be same for a user during interaction with the system. The UBEP uses two phase user verification system to authenticate a user. Firstly the acquisition phase is used to acquire and store the user interaction with NFC device and the same information is used in future to detect the authenticity of the user. The second phase (recognition) uses analysis of current and previous scenario of user interaction and digital signature verification system to finally authenticate user. The analysis of user based input makes a NFC transaction more advance and secure. This security is very tactical because it is completely depends on usage of the device.

Keywords: Security, Network Field communication, NFC Protocol.

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Authors: R. M. Siddiqui, D. Z. Moghaddam, T. R. Turlapati, S. H. Khan, I. Ul Ahad

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Quality of 2D and 3D cross-sectional images produce by Computed Tomography primarily depend upon the degree of precision of primary and secondary X-Ray intensity detection. Traditional method of primary intensity detection is apt to errors. Recently the X-Ray intensity measurement system along with smart X-Ray sensors is developed by our group which is able to detect primary X-Ray intensity unerringly. In this study a new smart X-Ray sensor is developed using Light-to-Frequency converter TSL230 from Texas Instruments which has numerous advantages in terms of noiseless data acquisition and transmission. TSL230 construction is based on a silicon photodiode which converts incoming X-Ray radiation into the proportional current signal. A current to frequency converter is attached to this photodiode on a single monolithic CMOS integrated circuit which provides proportional frequency count to incoming current signal in the form of the pulse train. The frequency count is delivered to the center of PICDEM FS USB board with PIC18F4550 microcontroller mounted on it. With highly compact electronic hardware, this Demo Board efficiently read the smart sensor output data. The frequency output approaches overcome nonlinear behavior of sensors with analog output thus un-attenuated X-Ray intensities could be measured precisely and better normalization could be acquired in order to attain high resolution.

Keywords: Computed tomography, detector technology, X-Ray intensity measurement

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Authors: Lavanya Srinivasan

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Biometric identification is to identify unique features in a person like fingerprints, iris, ear, and voice recognition that need the subject's permission and physical contact. Gait biometric is used to identify the unique gait of the person by extracting moving features. The main advantage of gait biometric to identify the gait of a person at a distance, without any physical contact. In this work, the gait biometric is used for person re-identification. The person walking naturally compared with the same person walking with bag, coat and case recorded using long wave infrared, short wave infrared, medium wave infrared and visible cameras. The videos are recorded in rural and in urban environments. The pre-processing technique includes human identified using You Only Look Once, background subtraction, silhouettes extraction and synthesis Gait Entropy Image by averaging the silhouettes. The moving features are extracted from the Gait Entropy Energy Image. The extracted features are dimensionality reduced by the Principal Component Analysis and recognized using different classifiers. The comparative results with the different classifier show that Linear Discriminant Analysis outperform other classifiers with 95.8% for visible in the rural dataset and 94.8% for longwave infrared in the urban dataset.

Keywords: biometric, gait, silhouettes, You Only Look Once

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Authors: C. Wan, A. Mita

Abstract:

This paper proposes a novel system for monitoring the health of underground pipelines. Some of these pipelines transport dangerous contents and any damage incurred might have catastrophic consequences. However, most of these damage are unintentional and usually a result of surrounding construction activities. In order to prevent these potential damages, monitoring systems are indispensable. This paper focuses on acoustically recognizing road cutters since they prelude most construction activities in modern cities. Acoustic recognition can be easily achieved by installing a distributed computing sensor network along the pipelines and using smart sensors to “listen" for potential threat; if there is a real threat, raise some form of alarm. For efficient pipeline monitoring, a novel monitoring approach is proposed. Principal Component Analysis (PCA) was studied and applied. Eigenvalues were regarded as the special signature that could characterize a sound sample, and were thus used for the feature vector for sound recognition. The denoising ability of PCA could make it robust to noise interference. One class SVM was used for classifier. On-site experiment results show that the proposed PCA and SVM based acoustic recognition system will be very effective with a low tendency for raising false alarms.

Keywords: One class SVM, pipeline monitoring system, principal component analysis, sound recognition, third party damage.

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Authors: Marlene Weber, Joseph Giacomin, Alessio Malizia, Lee Skrypchuk, Voula Gkatzidou

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Technological and sociological developments in the automotive sector are shifting the focus of design towards developing a better understanding of driver needs, desires and emotions. Human centred design methods are being more frequently applied to automotive research, including the use of systems to detect human emotions in real-time. One method for a non-contact measurement of emotion with low intrusiveness is Facial-Expression Analysis (FEA). This paper describes a research study investigating emotional responses of 22 participants in a naturalistic driving environment by applying a multi-method approach. The research explored the possibility to investigate emotional responses and their frequencies during naturalistic driving through real-time FEA. Observational analysis was conducted to assign causes to the collected emotional responses. In total, 730 emotional responses were measured in the collective study time of 440 minutes. Causes were assigned to 92% of the measured emotional responses. This research establishes and validates a methodology for the study of emotions and their causes in the driving environment through which systems and factors causing positive and negative emotional effects can be identified.

Keywords: Affective computing, case study, emotion recognition, human computer interaction.

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Authors: H. Masaeli, R. Ziaei, F. Khoshnoudian

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Shock response analysis of the soil–structure systems induced by near–fault pulses is investigated. Vibration transmissibility of the soil–structure systems is evaluated by shock response spectra (SRS). Medium–to–high rise buildings with different aspect ratios located on different soil types as well as different foundations with respect to vertical load bearing safety factors are studied. Two types of mathematical near–fault pulses, i.e. forward directivity and fling step, with different pulse periods as well as pulse amplitudes are selected as incident ground shock. Linear versus nonlinear soil–structure interaction (SSI) condition are considered alternatively and the corresponding results are compared. The results show that nonlinear SSI is likely to amplify the acceleration responses when subjected to long–period incident pulses with normalized period exceeding a threshold. It is also shown that this threshold correlates with soil type, so that increased shear–wave velocity of the underlying soil makes the threshold period decrease.

Keywords: Nonlinear soil–structure interaction, shock response spectrum, near–fault ground shock, rocking isolation.

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Authors: Bingchun Liu, Pei-Chann Chang, Natasha Huang, Dun Li

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Machine Learning and Data Mining are the two important tools for extracting useful information and knowledge from large datasets. In machine learning, classification is a wildly used technique to predict qualitative variables and is generally preferred over regression from an operational point of view. Due to the enormous increase in air pollution in various countries especially China, Air Quality Classification has become one of the most important topics in air quality research and modelling. This study aims at introducing a hybrid classification model based on information theory and Support Vector Machine (SVM) using the air quality data of four cities in China namely Beijing, Guangzhou, Shanghai and Tianjin from Jan 1, 2014 to April 30, 2016. China's Ministry of Environmental Protection has classified the daily air quality into 6 levels namely Serious Pollution, Severe Pollution, Moderate Pollution, Light Pollution, Good and Excellent based on their respective Air Quality Index (AQI) values. Using the information theory, information gain (IG) is calculated and feature selection is done for both categorical features and continuous numeric features. Then SVM Machine Learning algorithm is implemented on the selected features with cross-validation. The final evaluation reveals that the IG and SVM hybrid model performs better than SVM (alone), Artificial Neural Network (ANN) and K-Nearest Neighbours (KNN) models in terms of accuracy as well as complexity.

Keywords: Machine learning, air quality classification, air quality index, information gain, support vector machine, cross-validation.

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Authors: Radovan Holubek, Daynier Rolando Delgado Sobrino, Roman Ruzarovsky

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Current trends in manufacturing are characterized by production broadening, innovation cycle shortening, and the products having a new shape, material and functions. The production strategy focused on time needed change from the traditional functional production structure to flexible manufacturing cells and lines. Production by automated manufacturing system (AMS) is one of the most important manufacturing philosophies in the last years. The main goals of the project we are involved in lies on building a laboratory in which will be located a flexible manufacturing system consisting of at least two production machines with NC control (milling machines, lathe). These machines will be linked to a transport system and they will be served by industrial robots. Within this flexible manufacturing system a station for the quality control consisting of a camera system and rack warehouse will be also located. The design, analysis and improvement of this manufacturing system, specially with a special focus on the communication among devices constitute the main aims of this paper. The key determining factors for the manufacturing system design are: the product, the production volume, the used machines, the disposable manpower, the disposable infrastructure and the legislative frame for the specific cases.

Keywords: Paperless manufacturing, flexible manufacturing, robotized manufacturing, material flow, iCIM.

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Authors: Stefan M. Goetz, Thomas Weyh, Hans-Georg Herzog

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The triumph of inductive neuro-stimulation since its rediscovery in the 1980s has been quite spectacular. In lots of branches ranging from clinical applications to basic research this system is absolutely indispensable. Nevertheless, the basic knowledge about the processes underlying the stimulation effect is still very rough and rarely refined in a quantitative way. This seems to be not only an inexcusable blank spot in biophysics and for stimulation prediction, but also a fundamental hindrance for technological progress. The already very sophisticated devices have reached a stage where further optimization requires better strategies than provided by simple linear membrane models of integrate-and-fire style. Addressing this problem for the first time, we suggest in the following text a way for virtual quantitative analysis of a stimulation system. Concomitantly, this ansatz seems to provide a route towards a better understanding by using nonlinear signal processing and taking the nerve as a filter that is adapted for neuronal magnetic stimulation. The model is compact and easy to adjust. The whole setup behaved very robustly during all performed tests. Exemplarily a recent innovative stimulator design known as cTMS is analyzed and dimensioned with this approach in the following. The results show hitherto unforeseen potentials.

Keywords: Theory of magnetic stimulation, inversion, optimization, high voltage oscillator, TMS, cTMS.

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