Search results for: open innovation networks

Authors: Muhammad Sajjad, Naveed Khattak, Noman Jafri

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World has entered in 21st century. The technology of computer graphics and digital cameras is prevalent. High resolution display and printer are available. Therefore high resolution images are needed in order to produce high quality display images and high quality prints. However, since high resolution images are not usually provided, there is a need to magnify the original images. One common difficulty in the previous magnification techniques is that of preserving details, i.e. edges and at the same time smoothing the data for not introducing the spurious artefacts. A definitive solution to this is still an open issue. In this paper an image magnification using adaptive interpolation by pixel level data-dependent geometrical shapes is proposed that tries to take into account information about the edges (sharp luminance variations) and smoothness of the image. It calculate threshold, classify interpolation region in the form of geometrical shapes and then assign suitable values inside interpolation region to the undefined pixels while preserving the sharp luminance variations and smoothness at the same time. The results of proposed technique has been compared qualitatively and quantitatively with five other techniques. In which the qualitative results show that the proposed method beats completely the Nearest Neighbouring (NN), bilinear(BL) and bicubic(BC) interpolation. The quantitative results are competitive and consistent with NN, BL, BC and others.

Keywords: Adaptive, digital image processing, imagemagnification, interpolation, geometrical shapes, qualitative &quantitative analysis.

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Authors: Srinath Ramakkrushnan, Aswathaman Vijayan

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In conventional seedling production, the seedlings are being grown in the open field under natural conditions. Here they are susceptible to sudden changes in climate were their quality and yield is affected. Quality seedlings are essential for good growth and performance of crops in main field; they serve as a foundation for the economic returns to the farmer. Producing quality seedling demands usage of hybrid seeds as they have the ability to result in better yield, greater uniformity, improved color, disease resistance, and so forth. Hybrid seed production poses major operational challenge and its seed use efficiency plays an important role. Thus in order to overcome the difficulties currently present in conventional seedling production and to efficiently use hybrid seeds, ITC Limited Agri Business Divisions - Sustainability Cell as conceptualized a novel method of seedling production unit for farmers in West Godavari District of Andhra Pradesh. The “Green House based Float Seedling" methodology aims at a protected cultivation technique wherein the micro climate surrounding the plant/seedling body is controlled partially or fully as per the requirement of the species. This paper reports on the techno economic evaluation of green house for cultivation of float based seedling production with experimental results that was attained from the pilot implementation in West Godavari District, Rajahmundry region of India.

Keywords: Economic Assessment, Float Seedling, Green House, ITC Limited, Payback period.

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Authors: Chee-Ming Chan

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In spite of the advent of new materials, clay bricks remain, arguably, the most popular construction materials today. Nevertheless the low cost and versatility of clay bricks cannot always be associated with high environmental and sustainable values, especially in terms of raw material sources and manufacturing processes. At the same time, the worldwide agricultural footprint is fast growing, with vast agricultural land cultivation and active expansion of the agro-based industry. The resulting large quantities of agricultural wastes, unfortunately, are not always well managed or utilised. These wastes can be recycled, such as by retrieving fibres from disposed leaves and fruit bunches, and then incorporated in brick-making. This way the clay bricks are made a 'greener' building material and the discarded natural wastes can be reutilised, avoiding otherwise wasteful landfill and harmful open incineration. This study examined the physical and mechanical properties of clay bricks made by adding two natural fibres to a clay-water mixture, with baked and non-baked conditions. The fibres were sourced from pineapple leaves (PF) and oil palm fruit bunch (OF), and added within the range of 0.25-0.75 %. Cement was added as a binder to the mixture at 5-15 %. Although the two fibres had different effects on the bricks produced, cement appeared to dominate the compressive strength. The non-baked bricks disintegrated when submerged in water, while the baked ones displayed cement-dependent characteristics in water-absorption and density changes. Interestingly, further increase in fibre content did not cause significant density decrease in both the baked and non-baked bricks.

Keywords: natural fibres, clay bricks, strength, water absorption, density.

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Authors: Zahzouh Zoubir, Bouzaouit Azzeddine, Gahgah Mounir

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The use of more and more electronic power switches with a nonlinear behavior generates non-sinusoidal currents in distribution networks, which causes damage to domestic and industrial equipment. The multi-level shunt power active filter is subsequently shown to be an adequate solution to the problem raised. Nevertheless, the difficulty of adjusting the active filter DC supply voltage requires another technology to ensure it. In this article, a photovoltaic generator is associated with the DC bus power terminals of the active filter. The proposed system consists of a field of solar panels, three multi-level voltage inverters connected to the power grid and a non-linear load consisting of a six-diode rectifier bridge supplying a resistive-inductive load. Current control techniques of active and reactive power are used to compensate for both harmonic currents and reactive power as well as to inject active solar power into the distribution network. An algorithm of the search method of the maximum power point of type Perturb and observe is applied. Simulation results of the system proposed under the MATLAB/Simulink environment shows that the performance of control commands that reassure the solar power injection in the network, harmonic current compensation and power factor correction.

Keywords: MPPT, active power filter, PV array, perturb and observe algorithm, PWM-control.

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Authors: Abubakar Uba Ibrahim, Ibrahim Haruna Shanono

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Smart metering and demand response are gaining ground in industrial and residential applications. Smart Appliances have been given concern towards achieving Smart home. The success of Smart grid development relies on the successful implementation of Information and Communication Technology (ICT) in power sector. Smart Appliances have been the technology under development and many new contributions to its realization have been reported in the last few years. The role of ICT here is to capture data in real time, thereby allowing bi-directional flow of information/data between producing and utilization point; that lead a way for the attainment of Smart appliances where home appliances can communicate between themselves and provide a self-control (switch on and off) using the signal (information) obtained from the grid. This paper depicts the background on ICT for smart appliances paying a particular attention to the current technology and identifying the future ICT trends for load monitoring through which smart appliances can be achieved to facilitate an efficient smart home system which promote demand response program. This paper grouped and reviewed the recent contributions, in order to establish the current state of the art and trends of the technology, so that the reader can be provided with a comprehensive and insightful review of where ICT for smart appliances stands and is heading to. The paper also presents a brief overview of communication types, and then narrowed the discussion to the load monitoring (Non-intrusive Appliances Load Monitoring ‘NALM’). Finally, some future trends and challenges in the further development of the ICT framework are discussed to motivate future contributions that address open problems and explore new possibilities.

Keywords: Communication technology between appliances, demand response, load monitoring, smart appliances and smart grid.

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Authors: Baghdasaryan Marinka, Ulikyan Azatuhi

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The efficient usage of the compensation abilities of the electrical drive synchronous motors used in production processes can essentially improve the technical and economic indices of the process.  Reducing the flows of the reactive electrical energy due to the compensation of reactive power allows to significantly reduce the load losses of power in the electrical networks. As a result of analyzing the scientific works devoted to the issues of regulating the excitation of the synchronous motors, the need for comprehensive investigation and estimation of the excitation mode has been substantiated. By means of the obtained transmission functions, in the Simulink environment of the software package MATLAB, the transition processes of the excitation mode have been studied. As a result of obtaining and estimating the graph of the Nyquist plot and the transient process, the necessity of developing the Proportional-Integral-Derivative (PID) regulator has been justified. The transient processes of the system of the PID regulator have been investigated, and the amplitude–phase characteristics of the system have been estimated. The analysis of the obtained results has shown that the regulation indices of the developed system have been improved. The developed system can be successfully applied for regulating the excitation voltage of different-power synchronous motors, operating with a changing load, ensuring a value of the power coefficient close to 1.

Keywords: Transient process, synchronous motor, excitation mode, regulator, reactive power.

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Authors: S. Mahmoudi, A. Belhaj Mohamed, M. Saidi, F. Rezgui

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Depositional environment and source potential of the different organic-rich levels of Devonian age (up to 990m thick) from the onshore EC-1 well (Southern Tunisia) were investigated based on the analysis of more than 130 cutting samples by different geochemical techniques (Rock-Eval pyrolysis, GC-MS). The obtained results including Rock Eval Pyrolysis data and biomarker distribution (terpanes, steranes and aromatics) have been used to describe the depositional environment and to assess the thermal maturity of the Devonian organic matter. These results show that the Emsian deposits exhibit poor to fair TOC contents. The associated organic matter is composed of mixed kerogen (type II/III), as indicated by the predominance of C29 steranes over C27 and C28 homologous, that was deposited in a slightly reduced environment favoring organic matter preservation. Thermal maturity assessed from Tmax, TNR and MPI-1 values shows a mature stage of organic matter. The Middle Devonian (Eifelian) shales are rich in type II organic matter that was deposited in an open marine depositional environment. The TOC values are high and vary between 2 and 7% indicating good to excellent source rock. The relatively high HI values (reaching 547 mg HC/g TOC) and the low values of t19/t23 tricyclic terpane ratio (< 0.2) confirm the marine origin of the organic matter (type II). During the Upper Devonian, the organic matter was deposited under variable redox conditions, oxic to suboxic which is clearly indicated by the low C35/C34 hopanes ratio, immature to marginally mature with the vitrinite reflectance ranging from 0.5 to 0.7 Ro and Tmax value of 426°C-436 °C and the TOC values range between 0.8% to 4%.

Keywords: Depositional environment, Devonian, Source rock.

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Authors: Bi-Huei Tsai

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Prior research has not effectively investigated how the profitability of Chinese branches affect FDIs in China [1, 2], so this study for the first time incorporates realistic earnings information to systematically investigate effects of innovation, imitation, and profit factors of FDI diffusions from Taiwan to China. Our nonlinear least square (NLS) model, which incorporates earnings factors, forms a nonlinear ordinary differential equation (ODE) in numerical simulation programs. The model parameters are obtained through a genetic algorithms (GA) technique and then optimized with the collected data for the best accuracy. Particularly, Taiwanese regulatory FDI restrictions are also considered in our modified model to meet the realistic conditions. To validate the model-s effectiveness, this investigation compares the prediction accuracy of modified model with the conventional diffusion model, which does not take account of the profitability factors. The results clearly demonstrate the internal influence to be positive, as early FDI adopters- consistent praises of FDI attract potential firms to make the same move. The former erects a behavior model for the latter to imitate their foreign investment decision. Particularly, the results of modified diffusion models show that the earnings from Chinese branches are positively related to the internal influence. In general, the imitating tendency of potential consumers is substantially hindered by the losses in the Chinese branches, and these firms would invest less into China. The FDI inflow extension depends on earnings of Chinese branches, and companies will adjust their FDI strategies based on the returns. Since this research has proved that earning is an influential factor on FDI dynamics, our revised model explicitly performs superior in prediction ability than conventional diffusion model.

Keywords: diffusion model, genetic algorithms, nonlinear leastsquares (NLS) model, prediction error.

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Authors: Carlo Cernicchiaro, Pedro D. Gaspar, Martim L. Aguiar

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The agricultural sector is becoming more critical than ever in view of the expected overpopulation of the Earth. The introduction of robotic solutions in this field is an increasingly researched topic to make the most of the Earth's resources, thus going to avoid the problems of wear and tear of the human body due to the harsh agricultural work, and open the possibility of a constant careful processing 24 hours a day. This project is realized for a terrestrial autonomous robot aimed to navigate in an orchard collecting fallen peaches below the trees. When it receives the signal indicating the low battery, it has to return to the docking station where it will replace its battery and then return to the last work point and resume its routine. Considering a preset path in orchards with tree rows with variable length by which the robot goes iteratively using the algorithm D*. In case of low battery, the D* algorithm is still used to determine the fastest return path to the docking station as well as to come back from the docking station to the last work point. MATLAB simulations were performed to analyze the flexibility and adaptability of the developed algorithm. The simulation results show an enormous potential for adaptability, particularly in view of the irregularity of orchard field, since it is not flat and undergoes modifications over time from fallen branch as well as from other obstacles and constraints. The D* algorithm determines the best route in spite of the irregularity of the terrain. Moreover, in this work, it will be shown a possible solution to improve the initial points tracking and reduce time between movements.

Keywords: Path planning, fastest return path, agricultural terrestrial robot, autonomous, docking station.

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Authors: A. Asambe, A. K. B. Sackey, L. B. Tekdek

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A serosurveillance study was conducted to detect the presence of antibodies to African swine fever virus (ASFV) and Classical swine fever virus in pigs sampled from piggeries and Makurdi central slaughter slab in Benue State, Nigeria. 416 pigs from 74 piggeries across 12 LGAs and 44 pigs at the Makurdi central slaughter slab were sampled for serum. The sera collected were analysed using Indirect Enzyme Linked Immunosorbent Assay (ELISA) test kit to test for antibodies to ASFV, while competitive ELISA test kit was used to test for antibodies to CSFV. Of the 416 pigs from piggeries and 44 pigs sampled from the slaughter slab, seven (1.7%) and six (13.6%), respectively, tested positive to ASFV antibodies and was significantly associated (p < 0.0001). Out of the 12 LGAs sampled, Obi LGA had the highest ASFV antibody detection rate of (4.8%) and was significantly associated (p < 0.0001). None of the samples tested positive to CSFV antibodies. The study concluded that antibodies to CSFV were absent in the sampled pigs in piggeries and at the Makurdi central slaughter slab in Benue State, while antibodies to ASFV were present in both locations; hence, the need to keep an eye open for CSF too since both diseases may pose great risk in the study area. Further studies to characterise the ASFV circulating in Benue State and investigate the possible sources is recommended. Routine surveillance to provide a comprehensive and readily accessible data base to plan for the prevention of any fulminating outbreak is also recommended.

Keywords: African swine fever, classical swine fever, piggery, slaughter slab, surveillance.

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Authors: Hazem M. El-Bakry

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In this paper, a new technique for fast painting with different colors is presented. The idea of painting relies on applying masks with different colors to the background. Fast painting is achieved by applying these masks in the frequency domain instead of spatial (time) domain. New colors can be generated automatically as a result from the cross correlation operation. This idea was applied successfully for faster specific data (face, object, pattern, and code) detection using neural algorithms. Here, instead of performing cross correlation between the input input data (e.g., image, or a stream of sequential data) and the weights of neural networks, the cross correlation is performed between the colored masks and the background. Furthermore, this approach is developed to reduce the computation steps required by the painting operation. The principle of divide and conquer strategy is applied through background decomposition. Each background is divided into small in size subbackgrounds and then each sub-background is processed separately by using a single faster painting algorithm. Moreover, the fastest painting is achieved by using parallel processing techniques to paint the resulting sub-backgrounds using the same number of faster painting algorithms. In contrast to using only faster painting algorithm, the speed up ratio is increased with the size of the background when using faster painting algorithm and background decomposition. Simulation results show that painting in the frequency domain is faster than that in the spatial domain.

Keywords: Fast Painting, Cross Correlation, Frequency Domain, Parallel Processing

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Authors: Maryam Vafadar, Alireza Behrad, Saeed Akbari

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Nowadays, with the emerging of the new applications like robot control in image processing, artificial vision for visual servoing is a rapidly growing discipline and Human-machine interaction plays a significant role for controlling the robot. This paper presents a new algorithm based on spatio-temporal volumes for visual servoing aims to control robots. In this algorithm, after applying necessary pre-processing on video frames, a spatio-temporal volume is constructed for each gesture and feature vector is extracted. These volumes are then analyzed for matching in two consecutive stages. For hand gesture recognition and classification we tested different classifiers including k-Nearest neighbor, learning vector quantization and back propagation neural networks. We tested the proposed algorithm with the collected data set and results showed the correct gesture recognition rate of 99.58 percent. We also tested the algorithm with noisy images and algorithm showed the correct recognition rate of 97.92 percent in noisy images.

Keywords: Back propagation neural network, Feature vector, Hand gesture recognition, k-Nearest Neighbor, Learning vector quantization neural network, Robot control, Spatio-temporal volume, Visual servoing

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Authors: M. Kosacka, I. Kudelska

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Vehicle is one of the most influential and complex product worldwide, which affects people’s life, state of the environment and condition of the economy (all aspects of sustainable development concept) during each stage of lifecycle. With the increase of vehicles’ number, there is growing potential for management of End of Life Vehicle (ELV), which is hazardous waste. From one point of view, the ELV should be managed to ensure risk elimination, but from another point, it should be treated as a source of valuable materials and spare parts. In order to obtain materials and spare parts, there are established recycling networks, which are an example of sustainable policy realization at the national level. The basic object in the polish recycling network is dismantling facility. The output material streams in dismantling stations include waste, which very often generate costs and spare parts, that have the biggest potential for revenues creation. Both outputs are stored into warehouses, according to the law. In accordance to the revenue creation and sustainability potential, it has been placed a strong emphasis on storage process. We present the concept of storage method, which takes into account the specific of the dismantling facility in order to support decision-making process with regard to the principles of sustainable development. The method was developed on the basis of case study of one of the greatest dismantling facility in Poland.

Keywords: Dismantling, end of life vehicle, sustainability, storage.

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Authors: A. Muthuramalingam, S. Himavathi, E. Srinivasan

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.Hardware realization of a Neural Network (NN), to a large extent depends on the efficient implementation of a single neuron. FPGA-based reconfigurable computing architectures are suitable for hardware implementation of neural networks. FPGA realization of ANNs with a large number of neurons is still a challenging task. This paper discusses the issues involved in implementation of a multi-input neuron with linear/nonlinear excitation functions using FPGA. Implementation method with resource/speed tradeoff is proposed to handle signed decimal numbers. The VHDL coding developed is tested using Xilinx XC V50hq240 Chip. To improve the speed of operation a lookup table method is used. The problems involved in using a lookup table (LUT) for a nonlinear function is discussed. The percentage saving in resource and the improvement in speed with an LUT for a neuron is reported. An attempt is also made to derive a generalized formula for a multi-input neuron that facilitates to estimate approximately the total resource requirement and speed achievable for a given multilayer neural network. This facilitates the designer to choose the FPGA capacity for a given application. Using the proposed method of implementation a neural network based application, namely, a Space vector modulator for a vector-controlled drive is presented

Keywords: FPGA implementation, multi-input neuron, neural network, nn based space vector modulator.

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Authors: R. Reka, R. S. D. Wahidabanu

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The conventional routing protocol designed for MANET fail to handle dynamic movement and self-starting behavior of the node effectively. Every node in MANET is considered as forward as well receiver node and all of them participate in routing the packet from source to the destination. While the interconnection topology is highly dynamic, the performance of the most of the routing protocol is not encouraging. In this paper, a reliable broadcast approach for MANET is proposed for improving the transmission rate. The MANET is considered with asymmetric characteristics and the properties of the source and destination nodes are different. The non-forwarding node list is generated with a downstream node and they do not participate in the routing. While the forwarding and non-forwarding node is constructed in a conventional way, the number of nodes in non-forwarding list is more and increases the load. In this work, we construct the forwarding and non-forwarding node optimally so that the flooding and broadcasting is reduced to certain extent. The forwarded packet is considered as acknowledgements and the non-forwarding nodes explicitly send the acknowledgements to the source. The performance of the proposed approach is evaluated in NS2 environment. Since the proposed approach reduces the flooding, we have considered functionality of the proposed approach with AODV variants. The effect of network density on the overhead and collision rate is considered for performance evaluation. The performance is compared with the AODV variants found that the proposed approach outperforms all the variants.

Keywords: Flooding, Forwarded Nodes, MANET, Non-forwarding nodes, Routing protocols.

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Authors: Gaetano Zazzaro, Angelo Martone, Roberto V. Montaquila, Luigi Pavone

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Seizure is the main factor that affects the quality of life of epileptic patients. The diagnosis of epilepsy, and hence the identification of epileptogenic zone, is commonly made by using continuous Electroencephalogram (EEG) signal monitoring. Seizure identification on EEG signals is made manually by epileptologists and this process is usually very long and error prone. The aim of this paper is to describe an automated method able to detect seizures in EEG signals, using knowledge discovery in database process and data mining methods and algorithms, which can support physicians during the seizure detection process. Our detection method is based on Artificial Neural Network classifier, trained by applying the multilayer perceptron algorithm, and by using a software application, called Training Builder that has been developed for the massive extraction of features from EEG signals. This tool is able to cover all the data preparation steps ranging from signal processing to data analysis techniques, including the sliding window paradigm, the dimensionality reduction algorithms, information theory, and feature selection measures. The final model shows excellent performances, reaching an accuracy of over 99% during tests on data of a single patient retrieved from a publicly available EEG dataset.

Keywords: Artificial Neural Network, Data Mining, Electroencephalogram, Epilepsy, Feature Extraction, Seizure Detection, Signal Processing.

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Authors: Kyoung-jae Kim

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Recommender systems are usually regarded as an important marketing tool in the e-commerce. They use important information about users to facilitate accurate recommendation. The information includes user context such as location, time and interest for personalization of mobile users. We can easily collect information about location and time because mobile devices communicate with the base station of the service provider. However, information about user interest can-t be easily collected because user interest can not be captured automatically without user-s approval process. User interest usually represented as a need. In this study, we classify needs into two types according to prior research. This study investigates the usefulness of data mining techniques for classifying user need type for recommendation systems. We employ several data mining techniques including artificial neural networks, decision trees, case-based reasoning, and multivariate discriminant analysis. Experimental results show that CHAID algorithm outperforms other models for classifying user need type. This study performs McNemar test to examine the statistical significance of the differences of classification results. The results of McNemar test also show that CHAID performs better than the other models with statistical significance.

Keywords: Customer need type, Data mining techniques, Recommender system, Personalization, Mobile user.

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Authors: Jameela Ali Alkrimi, Hamid A. Jalab, Loay E. George, Abdul Rahim Ahmad, Azizah Suliman, Karim Al-Jashamy

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Red blood cells (RBC) are the most common types of blood cells and are the most intensively studied in cell biology. The lack of RBCs is a condition in which the amount of hemoglobin level is lower than normal and is referred to as “anemia”. Abnormalities in RBCs will affect the exchange of oxygen. This paper presents a comparative study for various techniques for classifying the RBCs as normal or abnormal (anemic) using WEKA. WEKA is an open source consists of different machine learning algorithms for data mining applications. The algorithms tested are Radial Basis Function neural network, Support vector machine, and K-Nearest Neighbors algorithm. Two sets of combined features were utilized for classification of blood cells images. The first set, exclusively consist of geometrical features, was used to identify whether the tested blood cell has a spherical shape or non-spherical cells. While the second set, consist mainly of textural features was used to recognize the types of the spherical cells. We have provided an evaluation based on applying these classification methods to our RBCs image dataset which were obtained from Serdang Hospital - Malaysia, and measuring the accuracy of test results. The best achieved classification rates are 97%, 98%, and 79% for Support vector machines, Radial Basis Function neural network, and K-Nearest Neighbors algorithm respectively.

Keywords: K-Nearest Neighbors, Neural Network, Radial Basis Function, Red blood cells, Support vector machine.

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Authors: Martin Hans Knahl

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The Internet is the global data communications infrastructure based on the interconnection of both public and private networks using protocols that implement Internetworking on a global scale. Hence the control of protocol and infrastructure development, resource allocation and network operation are crucial and interlinked aspects. Internet Governance is the hotly debated and contentious subject that refers to the global control and operation of key Internet infrastructure such as domain name servers and resources such as domain names. It is impossible to separate technical and political positions as they are interlinked. Furthermore the existence of a global market, transparency and competition impact upon Internet Governance and related topics such as network neutrality and security. Current trends and developments regarding Internet governance with a focus on the policy-making process, security and control have been observed to evaluate current and future implications on the Internet. The multi stakeholder approach to Internet Governance discussed in this paper presents a number of opportunities, issues and developments that will affect the future direction of the Internet. Internet operation, maintenance and advisory organisations such as the Internet Corporation for Assigned Names and Numbers (ICANN) or the Internet Governance Forum (IGF) are currently in the process of formulating policies for future Internet Governance. Given the controversial nature of the issues at stake and the current lack of agreement it is predicted that institutional as well as market governance will remain present for the network access and content.

Keywords: Internet Governance, ICANN, Democracy, Security

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Authors: Kostas Siozios, Dimitrios Soudris, Antonios Thanailakis

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Modern applications realized onto FPGAs exhibit high connectivity demands. Throughout this paper we study the routing constraints of Virtex devices and we propose a systematic methodology for designing a novel general-purpose interconnection network targeting to reconfigurable architectures. This network consists of multiple segment wires and SB patterns, appropriately selected and assigned across the device. The goal of our proposed methodology is to maximize the hardware utilization of fabricated routing resources. The derived interconnection scheme is integrated on a Virtex style FPGA. This device is characterized both for its high-performance, as well as for its low-energy requirements. Due to this, the design criterion that guides our architecture selections was the minimal Energy×Delay Product (EDP). The methodology is fully-supported by three new software tools, which belong to MEANDER Design Framework. Using a typical set of MCNC benchmarks, extensive comparison study in terms of several critical parameters proves the effectiveness of the derived interconnection network. More specifically, we achieve average Energy×Delay Product reduction by 63%, performance increase by 26%, reduction in leakage power by 21%, reduction in total energy consumption by 11%, at the expense of increase of channel width by 20%.

Keywords: Design Methodology, FPGA, Interconnection, Low-Energy, High-Performance, CAD tool.

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Authors: A. Zahiri, A. A. Dehghani

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Although many researchers have studied the flow hydraulics in compound channels, there are still many complicated problems in determination of their flow rating curves. Many different methods have been presented for these channels but extending them for all types of compound channels with different geometrical and hydraulic conditions is certainly difficult. In this study, by aid of nearly 400 laboratory and field data sets of geometry and flow rating curves from 30 different straight compound sections and using artificial neural networks (ANNs), flow discharge in compound channels was estimated. 13 dimensionless input variables including relative depth, relative roughness, relative width, aspect ratio, bed slope, main channel side slopes, flood plains side slopes and berm inclination and one output variable (flow discharge), have been used in ANNs. Comparison of ANNs model and traditional method (divided channel method-DCM) shows high accuracy of ANNs model results. The results of Sensitivity analysis showed that the relative depth with 47.6 percent contribution, is the most effective input parameter for flow discharge prediction. Relative width and relative roughness have 19.3 and 12.2 percent of importance, respectively. On the other hand, shape parameter, main channel and flood plains side slopes with 2.1, 3.8 and 3.8 percent of contribution, have the least importance.

Keywords: ANN model, compound channels, divided channel method (DCM), flow rating curve

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Authors: Abdulrahman Abdulrahman

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A side weir is a hydraulic structure set into the side of a channel. This structure is used for water level control in channels, to divert flow from a main channel into a side channel when the water level in the main channel exceeds a specific limit and as storm overflows from urban sewerage system. Computation of water surface over the side weirs is essential to determine the flow rate of the side weir. Analytical solutions for water surface profile along rectangular side weir are available only for the special cases of rectangular and trapezoidal channels considering constant specific energy. In this paper, a rectangular side weir located in a combined (trapezoidal with exponential) channel was considered. Expanding binominal series of integer and fraction powers and the using of reduction formula of cosine function integrals, a general analytical formula was obtained for water surface profile along a side weir in a combined (trapezoidal with exponential) channel. Since triangular, rectangular, trapezoidal and parabolic cross-sections are special cases of the combined cross section, the derived formula, is applicable to triangular, rectangular, trapezoidal cross-sections as analytical solution and semi-analytical solution to parabolic cross-section with maximum relative error smaller than 0.76%. The proposed solution should be a useful engineering tool for the evaluation and design of side weirs in open channel.

Keywords: Analytical solution, combined channel, exponential channel, side weirs, trapezoidal channel, water surface profile.

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Authors: Mohammad Heidari

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Horizontal wells are proven to be better producers because they can be extended for a long distance in the pay zone. Engineers have the technical means to forecast the well productivity for a given horizontal length. However, experiences have shown that the actual production rate is often significantly less than that of forecasted. It is a difficult task, if not impossible to identify the real reason why a horizontal well is not producing what was forecasted. Often the source of problem lies in the drilling of horizontal section such as permeability reduction in the pay zone due to mud invasion or snaky well patterns created during drilling. Although drillers aim to drill a constant inclination hole in the pay zone, the more frequent outcome is a sinusoidal wellbore trajectory. The two factors, which play an important role in wellbore tortuosity, are the inclination and side force at bit. A constant inclination horizontal well can only be drilled if the bit face is maintained perpendicular to longitudinal axis of bottom hole assembly (BHA) while keeping the side force nil at the bit. This approach assumes that there exists no formation force at bit. Hence, an appropriate BHA can be designed if bit side force and bit tilt are determined accurately. The Artificial Neural Network (ANN) is superior to existing analytical techniques. In this study, the neural networks have been employed as a general approximation tool for estimation of the bit side forces. A number of samples are analyzed with ANN for parameters of bit side force and the results are compared with exact analysis. Back Propagation Neural network (BPN) is used to approximation of bit side forces. Resultant low relative error value of the test indicates the usability of the BPN in this area.

Keywords: Artificial Neural Network, BHA, Horizontal Well, Stabilizer.

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Authors: A. Driouiche, S. Mohareb, A. Hadfi

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In Morocco’s Agadir region, the reuse of treated wastewater for irrigation of green spaces has faced the problem of scaling of the pipes of these waters. This research paper aims at studying the phenomenon of scaling caused by the treated wastewater from the Mzar sewage treatment plant. These waters are used in the irrigation of golf turf for the Ocean Golf Resort. Ocean Golf, located about 10 km from the center of the city of Agadir, is one of the most important recreation centers in Morocco. The course is a Belt Collins design with 27 holes, and is quite open with deep challenging bunkers. The formation of solid deposits in the irrigation systems has led to a decrease in their lifetime and, consequently, a loss of load and performance. Thus, the sprinklers used in golf turf irrigation are plugged in the first weeks of operation. To study this phenomenon, the wastewater used for the irrigation of the golf turf was taken and analyzed at various points, and also samples of scale formed in the circuits of the passage of these waters were characterized. This characterization of the scale was performed by X-ray fluorescence spectrometry, X-ray diffraction (XRD), thermogravimetric analysis (TGA), differential thermal analysis (DTA), and scanning electron microscopy (SEM). The results of the physicochemical analysis of the waters show that they are full of bicarbonates (653 mg/L), chloride (478 mg/L), nitrate (412 mg/L), sodium (425 mg/L) and calcium (199mg/L). Their pH is slightly alkaline. The analysis of the scale reveals that it is rich in calcium and phosphorus. It is formed of calcium carbonate (CaCO₃), silica (SiO₂), calcium silicate (Ca₂SiO₄), hydroxylapatite (Ca₁₀P₆O₂₆), calcium carbonate and phosphate (Ca₁₀(PO₄) 6CO₃) and silicate calcium and magnesium (Ca₅MgSi₃O₁₂).

Keywords: Agadir, irrigation, scaling water, wastewater.

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Authors: Naghmeh Moradpoor Sheykhkanloo

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Thousands of organisations store important and confidential information related to them, their customers, and their business partners in databases all across the world. The stored data ranges from less sensitive (e.g. first name, last name, date of birth) to more sensitive data (e.g. password, pin code, and credit card information). Losing data, disclosing confidential information or even changing the value of data are the severe damages that Structured Query Language injection (SQLi) attack can cause on a given database. It is a code injection technique where malicious SQL statements are inserted into a given SQL database by simply using a web browser. In this paper, we propose an effective pattern recognition neural network model for detection and classification of SQLi attacks. The proposed model is built from three main elements of: a Uniform Resource Locator (URL) generator in order to generate thousands of malicious and benign URLs, a URL classifier in order to: 1) classify each generated URL to either a benign URL or a malicious URL and 2) classify the malicious URLs into different SQLi attack categories, and a NN model in order to: 1) detect either a given URL is a malicious URL or a benign URL and 2) identify the type of SQLi attack for each malicious URL. The model is first trained and then evaluated by employing thousands of benign and malicious URLs. The results of the experiments are presented in order to demonstrate the effectiveness of the proposed approach.

Keywords: Neural Networks, pattern recognition, SQL injection attacks, SQL injection attack classification, SQL injection attack detection.

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Authors: Robson C. Santos, Julio C. P. Ribeiro, Iorran M. de Castro, Luan C. F. Rodrigues, Sandro R. L. Silva, Diego M. Quesada

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The work aims to develop a robot in the form of autonomous vehicle to detect, inspection and mapping of underground pipelines through the ATmega328 Arduino platform. Hardware prototyping is very similar to C / C ++ language that facilitates its use in robotics open source, resembles PLC used in large industrial processes. The robot will traverse the surface independently of direct human action, in order to automate the process of detecting buried pipes, guided by electromagnetic induction. The induction comes from coils that send the signal to the Arduino microcontroller contained in that will make the difference in intensity and the treatment of the information, and then this determines actions to electrical components such as relays and motors, allowing the prototype to move on the surface and getting the necessary information. This change of direction is performed by a stepper motor with a servo motor. The robot was developed by electrical and electronic assemblies that allowed test your application. The assembly is made up of metal detector coils, circuit boards and microprocessor, which interconnected circuits previously developed can determine, process control and mechanical actions for a robot (autonomous car) that will make the detection and mapping of buried pipelines plates. This type of prototype can prevent and identifies possible landslides and they can prevent the buried pipelines suffer an external pressure on the walls with the possibility of oil leakage and thus pollute the environment.

Keywords: Robotic, metal detector, embedded system, pipeline.

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Authors: Luísa P. Cruz-Lopes, Hugo Costa e Silva, Idalina Domingos, José Ferreira, Luís Teixeira de Lemos, Bruno Esteves

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The liquefaction process of cork based tree barks has led to an increase of interest due to its potential innovation in the lumber and wood industries. In this particular study the bark of Quercus cerris (Turkish oak) is used due to its appreciable amount of cork tissue, although of inferior quality when compared to the cork provided by other Quercus trees. This study aims to optimize alkaline catalysis liquefaction conditions, regarding several parameters. To better comprehend the possible chemical characteristics of the bark of Quercus cerris, a complete chemical analysis was performed. The liquefaction process was performed in a double-jacket reactor heated with oil, using glycerol and a mixture of glycerol/ethylene glycol as solvents, potassium hydroxide as a catalyst, and varying the temperature, liquefaction time and granulometry. Due to low liquefaction efficiency resulting from the first experimental procedures a study was made regarding different washing techniques after the filtration process using methanol and methanol/water. The chemical analysis stated that the bark of Quercus cerris is mostly composed by suberin (ca. 30%) and lignin (ca. 24%) as well as insolvent hemicelluloses in hot water (ca. 23%). On the liquefaction stage, the results that led to higher yields were: using a mixture of methanol/ethylene glycol as reagents and a time and temperature of 120 minutes and 200 ºC, respectively. It is concluded that using a granulometry of <80 mesh leads to better results, even if this parameter barely influences the liquefaction efficiency. Regarding the filtration stage, washing the residue with methanol and then distilled water leads to a considerable increase on final liquefaction percentages, which proves that this procedure is effective at liquefying suberin content and lignocellulose fraction.

Keywords: Liquefaction, alkaline catalysis, optimization, Quercus cerris bark.

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Authors: Vladimir Korovkin, Albert Park, Evgeny Kaganer

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Digital divide, the gap in the access to the world of digital technologies and the socio-economic opportunities that they create is an important phenomenon of the XXI century. This gap may exist between countries, regions within a country or socio-demographic groups, creating the classes of “digital have and have nots”. While the 1st-level divide (the difference in opportunities to access the digital networks) was demonstrated to diminish with time, the issues of 2nd level divide (the difference in skills and usage of digital systems) and 3rd level divide (the difference in effects obtained from digital technology) may grow. The paper offers a systemic review of literature on the measurement of the digital divide, noting the certain conceptual stagnation due to the lack of effective instruments that would capture the complex nature of the phenomenon. As a result, many important concepts do not receive the empiric exploration they deserve. As a solution the paper suggests a composite Digital Life Index, that studies separately the digital supply and demand across seven independent dimensions providing for 14 subindices. The Index is based on Internet-borne data, a distinction from traditional research approaches that rely on official statistics or surveys. The application of the model to the study of the digital divide between Russian regions and between cities in China have brought promising results. The paper advances the existing methodological literature on the 2nd level digital divide and can also inform practical decision-making regarding the strategies of national and regional digital development.

Keywords: Digital transformation, second-level digital divide, composite index, digital policy.

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Authors: Zuhaib Ashfaq Khan, Imran Khan, Nandana Rajatheva

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In this paper, hybrid FDMA-TDMA access technique in a cooperative distributive fashion introducing and implementing a modified protocol introduced in [1] is analyzed termed as Power and Cooperation Diversity Gain Protocol (PCDGP). A wireless network consists of two users terminal , two relays and a destination terminal equipped with two antennas. The relays are operating in amplify-and-forward (AF) mode with a fixed gain. Two operating modes: cooperation-gain mode and powergain mode are exploited from source terminals to relays, as it is working in a best channel selection scheme. Vertical BLAST (Bell Laboratories Layered Space Time) or V-BLAST with minimum mean square error (MMSE) nulling is used at the relays to perfectly detect the joint signals from multiple source terminals. The performance is analyzed using binary phase shift keying (BPSK) modulation scheme and investigated over independent and identical (i.i.d) Rayleigh, Ricean-K and Nakagami-m fading environments. Subsequently, simulation results show that the proposed scheme can provide better signal quality of uplink users in a cooperative communication system using hybrid FDMATDMA technique.

Keywords: Cooperation Diversity, Best Channel Selectionscheme, MIMO relay networks, V-BLAST, QRdecomposition, and MMSE.

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Authors: Chen Chou, Feng-Tyan Lin

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Big Data has been attracted a lot of attentions in many fields for analyzing research issues based on a large number of maternal data. Electronic Toll Collection (ETC) is one of Intelligent Transportation System (ITS) applications in Taiwan, used to record starting point, end point, distance and travel time of vehicle on the national freeway. This study, taking advantage of ETC big data, combined with urban planning theory, attempts to explore various phenomena of inter-city transportation activities. ETC, one of government's open data, is numerous, complete and quick-update. One may recall that living area has been delimited with location, population, area and subjective consciousness. However, these factors cannot appropriately reflect what people’s movement path is in daily life. In this study, the concept of "Living Area" is replaced by "Influence Range" to show dynamic and variation with time and purposes of activities. This study uses data mining with Python and Excel, and visualizes the number of trips with GIS to explore influence range of Tainan city and the purpose of trips, and discuss living area delimited in current. It dialogues between the concepts of "Central Place Theory" and "Living Area", presents the new point of view, integrates the application of big data, urban planning and transportation. The finding will be valuable for resource allocation and land apportionment of spatial planning.

Keywords: Big Data, ITS, influence range, living area, central place theory, visualization.

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