Search results for: data source.

Authors: Shayan Rezvanigilkolaei, Shayesteh Vefaghnematollahi

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Electrical impedance tomography is a non-invasive medical imaging technique suitable for medical applications. This paper describes an electrical impedance tomography device with the ability to navigate a robotic arm to manipulate a target object. The design of the device includes various hardware and software sections to perform medical imaging and control the robotic arm. In its hardware section an image is formed by 16 electrodes which are located around a container. This image is used to navigate a 3DOF robotic arm to reach the exact location of the target object. The data set to form the impedance imaging is obtained by having repeated current injections and voltage measurements between all electrode pairs. After performing the necessary calculations to obtain the impedance, information is transmitted to the computer. This data is fed and then executed in MATLAB which is interfaced with EIDORS (Electrical Impedance Tomography Reconstruction Software) to reconstruct the image based on the acquired data. In the next step, the coordinates of the center of the target object are calculated by image processing toolbox of MATLAB (IPT). Finally, these coordinates are used to calculate the angles of each joint of the robotic arm. The robotic arm moves to the desired tissue with the user command.

Keywords: Electrical impedance tomography, EIT, Surgeon robot, image processing of Electrical impedance tomography.

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Authors: Akram A. Mustafa

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In this paper an approaches for increasing the effectiveness of error detection in computer network channels with Pulse-Amplitude Modulation (PAM) has been proposed. Proposed approaches are based on consideration of special feature of errors, which are appearances in line with PAM. The first approach consists of CRC modification specifically for line with PAM. The second approach is base of weighted checksums using. The way for checksum components coding has been developed. It has been shown that proposed checksum modification ensure superior digital data control transformation reliability for channels with PAM in compare to CRC.

Keywords: Pulse-Amplitude Modulation, checksum, transmission, discrete.

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Authors: Giovanni Luca Masala

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Pattern recognition is the research area of Artificial Intelligence that studies the operation and design of systems that recognize patterns in the data. Important application areas are image analysis, character recognition, fingerprint classification, speech analysis, DNA sequence identification, man and machine diagnostics, person identification and industrial inspection. The interest in improving the classification systems of data analysis is independent from the context of applications. In fact, in many studies it is often the case to have to recognize and to distinguish groups of various objects, which requires the need for valid instruments capable to perform this task. The objective of this article is to show several methodologies of Artificial Intelligence for data classification applied to biomedical patterns. In particular, this work deals with the realization of a Computer-Aided Detection system (CADe) that is able to assist the radiologist in identifying types of mammary tumor lesions. As an additional biomedical application of the classification systems, we present a study conducted on blood samples which shows how these methods may help to distinguish between carriers of Thalassemia (or Mediterranean Anaemia) and healthy subjects.

Keywords: Computer Aided Detection, mammary tumor, pattern recognition, thalassemia.

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Authors: Meriem Bahij, Ahmed Nafidi, Boujemâa Achchab, Sílvio M. A. Gama, José A. O. Matos

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Stochastic modeling concerns the use of probability to model real-world situations in which uncertainty is present. Therefore, the purpose of stochastic modeling is to estimate the probability of outcomes within a forecast, i.e. to be able to predict what conditions or decisions might happen under different situations. In the present study, we present a model of a stochastic diffusion process based on the bi-Weibull distribution function (its trend is proportional to the bi-Weibull probability density function). In general, the Weibull distribution has the ability to assume the characteristics of many different types of distributions. This has made it very popular among engineers and quality practitioners, who have considered it the most commonly used distribution for studying problems such as modeling reliability data, accelerated life testing, and maintainability modeling and analysis. In this work, we start by obtaining the probabilistic characteristics of this model, as the explicit expression of the process, its trends, and its distribution by transforming the diffusion process in a Wiener process as shown in the Ricciaardi theorem. Then, we develop the statistical inference of this model using the maximum likelihood methodology. Finally, we analyse with simulated data the computational problems associated with the parameters, an issue of great importance in its application to real data with the use of the convergence analysis methods. Overall, the use of a stochastic model reflects only a pragmatic decision on the part of the modeler. According to the data that is available and the universe of models known to the modeler, this model represents the best currently available description of the phenomenon under consideration.

Keywords: Diffusion process, discrete sampling, likelihood estimation method, simulation, stochastic diffusion equation, trends functions, bi-parameters Weibull density function.

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Authors: Victoria A. Bakhtina

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At a time of growing market turbulence and a strong shifts towards increasingly complex risk models and more stringent audit requirements, it is more critical than ever to maintain the highest quality of financial and credit information. IFC implemented an approach that helps increase data integrity and quality significantly. This approach is called “Screening". Screening is based on linking information from different sources to identify potential inconsistencies in key financial and credit data. That, in turn, can help to ease the trials of portfolio supervision, and improve overall company global reporting and assessment systems. IFC experience showed that when used regularly, Screening led to improved information.

Keywords: Information Integrity, Information Quality, Business Rules, Portfolio Management

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Authors: Udomporn Yingpaisuk, Premwadee Karuhadej

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The purposed of this research was to study the eating habit of teenage pregnancy and its relationship to the knowledge of nutrition during pregnancy. The 100 samples were derived from simple random sampling technique of the teenage pregnancy in Bangkae District. The questionnaire was used to collect data with the reliability of 0.8. The data were analyzed by SPSS for Windows with multiple regression technique. Percentage, mean and the relationship of knowledge of eating and eating behavior were obtained. The research results revealed that their knowledge in nutrition was at the average of 4.07 and their eating habit that they mentioned most was to refrain from alcohol and caffeine at 82% and the knowledge in nutrition influenced their eating habits at 54% with the statistically significant level of 0.001.

Keywords: Teenage pregnancy, knowledge of nutrition, eating habit.

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Authors: Jinseon Song, Yongwan Park

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In this paper, propose method that can user’s position that based on database is built from single camera. Previous positioning calculate distance by arrival-time of signal like GPS (Global Positioning System), RF(Radio Frequency). However, these previous method have weakness because these have large error range according to signal interference. Method for solution estimate position by camera sensor. But, signal camera is difficult to obtain relative position data and stereo camera is difficult to provide real-time position data because of a lot of image data, too. First of all, in this research we build image database at space that able to provide positioning service with single camera. Next, we judge similarity through image matching of database image and transmission image from user. Finally, we decide position of user through position of most similar database image. For verification of propose method, we experiment at real-environment like indoor and outdoor. Propose method is wide positioning range and this method can verify not only position of user but also direction.

Keywords: Positioning, Distance, Camera, Features, SURF (Speed-Up Robust Features), Database, Estimation.

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Authors: Zulaikha Reesha Rashaad

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One of the major factors which can contribute greatly to success of catering businesses is to employ food and beverage staff having sound hygiene knowledge. Individuals having sound knowledge of hygiene has a higher chance of following safe food practices in food production. One of the leading causes of food poisoning and food borne illnesses has been identified as lack of hygiene knowledge among food and beverage staff working in catering establishments and restaurants. This research aims to analyze the hygiene knowledge among food and beverage staff working in top five restaurants of Male’, in relation to their age, educational background, occupation and training. The research uses quantitative and descriptive methods in data collection and in data analysis. Data was obtained through random sampling technique with self-administered survey questionnaires which was completed by 60 respondents working in 5 different restaurants operating at top level in Male’. The respondents of the research were service staff and chefs working in these restaurants. The responses to the questionnaires have been analyzed by using SPSS. The results of the research indicated that age, education level, occupation and training correlated with hygiene knowledge perception scores.

Keywords: Food and beverage staff, food poisoning, food production, hygiene knowledge.

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Authors: Maria E. Manioudaki, Panayiota Poirazi

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Yeast cells live in a constantly changing environment that requires the continuous adaptation of their genomic program in order to sustain their homeostasis, survive and proliferate. Due to the advancement of high throughput technologies, there is currently a large amount of data such as gene expression, gene deletion and protein-protein interactions for S. Cerevisiae under various environmental conditions. Mining these datasets requires efficient computational methods capable of integrating different types of data, identifying inter-relations between different components and inferring functional groups or 'modules' that shape intracellular processes. This study uses computational methods to delineate some of the mechanisms used by yeast cells to respond to environmental changes. The GRAM algorithm is first used to integrate gene expression data and ChIP-chip data in order to find modules of coexpressed and co-regulated genes as well as the transcription factors (TFs) that regulate these modules. Since transcription factors are themselves transcriptionally regulated, a three-layer regulatory cascade consisting of the TF-regulators, the TFs and the regulated modules is subsequently considered. This three-layer cascade is then modeled quantitatively using artificial neural networks (ANNs) where the input layer corresponds to the expression of the up-stream transcription factors (TF-regulators) and the output layer corresponds to the expression of genes within each module. This work shows that (a) the expression of at least 33 genes over time and for different stress conditions is well predicted by the expression of the top layer transcription factors, including cases in which the effect of up-stream regulators is shifted in time and (b) identifies at least 6 novel regulatory interactions that were not previously associated with stress-induced changes in gene expression. These findings suggest that the combination of gene expression and protein-DNA interaction data with artificial neural networks can successfully model biological pathways and capture quantitative dependencies between distant regulators and downstream genes.

Keywords: gene modules, artificial neural networks, yeast, stress

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Authors: Münüre Tanur Erkoyuncu, Mustafa Yorgancılar

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Crop improvement through genetic engineering depends on effective and reproducible plant regeneration systems. Immature embryos are the most widely used explant source for in vitro regeneration in barley (Hordeum vulgare L.). However, immature embryos require the continuous growth of donor plants and the suitable stage for their culture is also certainly limited. On the other hand, mature embryos can be procured and stored easily; they can be studied throughout the year. In this study, an effective callus induction and plant regeneration were aimed to develop from mature embryos of different barley genotypes. The effect of medium (MS₁ and MS₂), auxin type (2,4-D, dicamba, picloram and 2,4,5-T) and concentrations (2, 4, 6 mg/l) on callus formation and effect of cytokinin type (TDZ, BAP) and concentrations (0.2, 0.5, 1.0 mg/l) on green plant regeneration were evaluated in mature embryo culture of barley. Callus and shoot formation was successful for all genotypes. By depending on genotype, MS₁ is the best medium, 4 mg/l dicamba is the best growth regulator in the callus induction and MS₁ is the best medium, 1 mg/l BAP is the best growth regulator in the shoot formation were determined.

Keywords: Barley, callus, embryo culture, mature embryo.

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Authors: Sharmina Begum, M. G. Rasul, Delwar Akbar

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Solid waste can be considered as an urban burden or as a valuable resource depending on how it is managed. To meet the rising demand for energy and to address environmental concerns, a conversion from conventional energy systems to renewable resources is essential. For the sustainability of human civilization, an environmentally sound and techno-economically feasible waste treatment method is very important to treat recyclable waste. Several technologies are available for realizing the potential of solid waste as an energy source, ranging from very simple systems for disposing of dry waste to more complex technologies capable of dealing with large amounts of industrial waste. There are three main pathways for conversion of waste material to energy: thermo chemical, biochemical and physicochemical. This paper investigates the thermo chemical conversion of solid waste for energy recovery. The processes, advantages and dis-advantages of various thermo chemical conversion processes are discussed and compared. Special attention is given to Gasification process as it provides better solutions regarding public acceptance, feedstock flexibility, near-zero emissions, efficiency and security. Finally this paper presents comparative statements of thermo chemical processes and introduces an integrated waste management system.

Keywords: Gasification, Incineration, Pyrolysis, Thermo chemical conversion.

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Authors: Jan Sindelar

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The paper presents an applied study of a multivariate AR(p) process fitted to daily data from U.S. commodity futures markets with the use of Bayesian statistics. In the first part a detailed description of the methods used is given. In the second part two BVAR models are chosen one with assumption of lognormal, the second with normal distribution of prices conditioned on the parameters. For a comparison two simple benchmark models are chosen that are commonly used in todays Financial Mathematics. The article compares the quality of predictions of all the models, tries to find an adequate rate of forgetting of information and questions the validity of Efficient Market Hypothesis in the semi-strong form.

Keywords: Vector auto-regression, forecasting, financial, Bayesian, efficient markets.

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Authors: Masoud Hassanzade Novin, Bahloul Salmani

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The process of the translation is not merely the linguistic aspects. It is also considered in the cultural framework of both the source and target text cultures. The translation process and translated texts are confronted the new aspect in 20th century which is considered mostly in the patronage framework and ideological grillwork of the target language. To have these factors scrutinized in the process of the translation both micro-element factors and macro-element factors can be taken into consideration. For the purpose of this study through a qualitative type of research based on critical discourse analysis approach, the case study of the novel “1984” written by George Orwell was chosen as the corpus of the study to have the contrastive analysis by its Persian translated texts. Results of the study revealed some distortions embedded in the target texts which were overshadowed by ideological aspect and patronage network. The outcomes of the manipulated terms were different in various categories which revealed the manipulation aspects in the texts translated.

Keywords: Critical discourse analysis, ideology, translated texts, patronage network.

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Authors: Chul H. Jo, Do Y. Kim, Bong K. Cho, Myeong J. Kim

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The exhaustion of oil and the environmental pollution from the use of fossil fuel are increasing. Tidal current power (TCP) has been proposed as an alternative energy source because of its predictability and reliability. By applying a duct and single point mooring (SPM) system, a TCP device can amplify the generating power and keep its position properly. Because the generating power is proportional to cube of the current stream velocity, amplifying the current speed by applying a duct to a TCP system is an effective way to improve the efficiency of the power device. An SPM system can be applied at any water depth and is highly cost effective. Simple installation and maintenance procedures are also merits of an SPM system. In this study, we designed an SPM system for a duct-type TCP device for use in shallow water. Motions of the duct are investigated to obtain the response amplitude operator (RAO) as the magnitude of the transfer function. Parameters affecting the stability of the SPM system such as the fairlead departure angle, current velocity, and the number of clamp weights are analyzed and/or optimized. Wadam and OrcaFlex commercial software is used to design the mooring line.

Keywords: Mooring design, parametric analysis, response amplitude operator, single point mooring.

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Authors: Chutimon Thitipornvanid, Siripun Sanguansintukul

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Choosing the right metadata is a critical, as good information (metadata) attached to an image will facilitate its visibility from a pile of other images. The image-s value is enhanced not only by the quality of attached metadata but also by the technique of the search. This study proposes a technique that is simple but efficient to predict a single human image from a website using the basic image data and the embedded metadata of the image-s content appearing on web pages. The result is very encouraging with the prediction accuracy of 95%. This technique may become a great assist to librarians, researchers and many others for automatically and efficiently identifying a set of human images out of a greater set of images.

Keywords: Metadata, Prediction, Multi-layer perceptron, Human facial image, Image mining.

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Authors: Alexander Y. Vaninsky

Abstract:

Importance of environmental efficiency of electric power industry stems from high demand for energy combined with global warming concerns. It is especially essential for the world largest economies like that of the United States. The paper introduces a Data Envelopment Analysis (DEA) model of environmental efficiency using indicators of fossil fuels utilization, emissions rate, and electric power losses. Using DEA is advantageous in this situation over other approaches due to its nonparametric nature. The paper analyzes data for the period of 1990 - 2006 by comparing actual yearly levels in each dimension with the best values of partial indicators for the period. As positive factors of efficiency, tendency to the decline in emissions rates starting 2000, and in electric power losses starting 2004 may be mentioned together with increasing trend of fuel utilization starting 1999. As a result, dynamics of environmental efficiency is positive starting 2002. The main concern is the decline in fossil fuels utilization in 2006. This negative change should be reversed to comply with ecological and economic requirements.

Keywords: Environmental efficiency, electric power industry, DEA, United States.

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Authors: N. Mahendran, R. Madhuranthi

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Wireless sensor networks (WSNs), are constantly in demand to process information more rapidly with less energy and area cost. Presently, processor based solutions have difficult to achieve high processing speed with low-power consumption. This paper presents a simple and accurate data processing scheme for low power wireless sensor node, based on reduced number of processing element (PE). The presented model provides a simple recursive structure (SRS) to process the sampled data in the wireless sensor environment and to reduce the power consumption in wireless sensor node. Based on this model, to process the incoming samples and produce a smaller amount of data sufficient to reconstruct the original signal. The ModelSim simulator used to simulate SRS structure. Functional simulation is carried out for the validation of the presented architecture. Xilinx Power Estimator (XPE) tool is used to measure the power consumption. The experimental results show the average power consumption of 91 mW; this is 42% improvement compared to the folded tree architecture.

Keywords: Power consumption, energy efficiency, low power WSN node, recursive structure, sleep/wake scheduling.

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Authors: Lei Zhang, Wen-jun Ruan, Hao Wang, Peng-xin Wang

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The source of the jet noise is generated by rocket exhaust plume during rocket engine testing. A domain decomposition approach is applied to the jet noise prediction in this paper. The aerodynamic noise coupling is based on the splitting into acoustic sources generation and sound propagation in separate physical domains. Large Eddy Simulation (LES) is used to simulate the supersonic jet flow. Based on the simulation results of the flow-fields, the jet noise distribution of the sound pressure level is obtained by applying the Ffowcs Williams-Hawkings (FW-H) acoustics equation and Fourier transform. The calculation results show that the complex structures of expansion waves, compression waves and the turbulent boundary layer could occur due to the strong interaction between the gas jet and the ambient air. In addition, the jet core region, the shock cell and the sound pressure level of the gas jet increase with the nozzle size increasing. Importantly, the numerical simulation results of the far-field sound are in good agreement with the experimental measurements in directivity.

Keywords: Supersonic gas jet, Large Eddy Simulation(LES), acoustic noise, Ffowcs Williams-Hawkings (FW-H) equations, nozzle size.

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Authors: Ruilian Zhao, Shukai Zhang, Yan Wang, Weiwei Wang

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Repairing broken test cases is an expensive and challenging task in evolving software systems. Although an automated repair technique with intent-preservation has been proposed, it does not take into account the association between test repairs and assertions, leading a large number of irrelevant candidates and decreasing the repair capability. This paper proposes a assertion-driven test repair approach. Furthermore, a intent-oriented priority criterion is raised to guide the repair candidate generation, making the repairs closer to the intent of the test. In more detail, repair targets are determined through post-dominance relations between assertions and the methods that directly cause compilation errors. Then, test repairs are generated from the target in a bottom-up way, guided by the the intent-oriented priority criteria. Finally, the generated repair candidates are prioritized to match the original test intent. The approach is implemented and evaluated on the benchmark of 4 open-source programs and 91 broken test cases. The result shows that the approach can fix 89% (81/91) broken test cases, which are more effective than the existing intent-preserved test repair approach, and our intent-oriented priority criteria work well.

Keywords: Test repair, test intent, software test, test case evolution.

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Authors: Megha Gupta, Nupur Prakash

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Identification of plant diseases has been performed using machine learning and deep learning models on the datasets containing images of healthy and diseased plant leaves. The current study carries out an evaluation of some of the deep learning models based on convolutional neural network architectures for identification of plant diseases. For this purpose, the publicly available New Plant Diseases Dataset, an augmented version of PlantVillage dataset, available on Kaggle platform, containing 87,900 images has been used. The dataset contained images of 26 diseases of 14 different plants and images of 12 healthy plants. The CNN models selected for the study presented in this paper are AlexNet, ZFNet, VGGNet (four models), GoogLeNet, and ResNet (three models). The selected models are trained using PyTorch, an open-source machine learning library, on Google Colaboratory. A comparative study has been carried out to analyze the high degree of accuracy achieved using these models. The highest test accuracy and F1-score of 99.59% and 0.996, respectively, were achieved by using GoogLeNet with Mini-batch momentum based gradient descent learning algorithm.

Keywords: comparative analysis, convolutional neural networks, deep learning, plant disease identification

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Authors: Larbi Omar, Elberrichi Zakaria

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Many research works are carried out on the analysis of traces in a digital learning environment. These studies produce large volumes of usage tracks from the various actions performed by a user. However, to exploit these data, compare and improve performance, several issues are raised. To remedy this, several works deal with this problem seen recently. This research studied a series of questions about format and description of the data to be shared. Our goal is to share thoughts on these issues by presenting our experience in the analysis of trace-based log files, comparing several approaches used in automatic classification applied to e-learning platforms. Finally, the obtained results are discussed.

Keywords: Classification, , e-learning platform, log file, Trace.

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Authors: Martin Lisý, Marek Baláš, Michal Špiláček, Zdeněk Skála

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This paper deals with the issue of biomass and sorted municipal waste gasification and cogeneration using hot-air turbo-set. It brings description of designed pilot plant with electrical output 80 kWe. The generated gas is burned in secondary combustion chamber located beyond the gas generator. Flue gas flows through the heat exchanger where the compressed air is heated and consequently brought to a micro turbine. Except description, this paper brings our basic experiences from operating of pilot plant (operating parameters, contributions, problems during operating, etc.). The principal advantage of the given cycle is the fact that there is no contact between the generated gas and the turbine. So there is no need for costly and complicated gas cleaning which is the main source of operating problems in direct use in combustion engines because the content of impurities in the gas causes operation problems to the units due to clogging and tarring of working surfaces of engines and turbines, which may lead as far as serious damage to the equipment under operation. Another merit is the compact container package making installation of the facility easier or making it relatively more mobile. We imagine, this solution of cogeneration from biomass or waste can be suitable for small industrial or communal applications, for low output cogeneration.

Keywords: Biomass, combustion, gasification, microcogeneration.

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Authors: Panpan Xu, Qiying Zhang, Hui Qian

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Groundwater is main source of water supply in the Guanzhong Basin, China. To investigate the quality of groundwater for agricultural purposes in Jiaokou Irrigation District located in the east of the Guanzhong Basin, 141 groundwater samples were collected for analysis of major ions (K⁺, Na⁺, Mg²⁺, Ca²⁺, SO₄^2-, Cl^-, HCO₃^-, and CO₃^2-), pH, and total dissolved solids (TDS). Sodium percentage (Na%), residual sodium carbonate (RSC), magnesium hazard (MH), and potential salinity (PS) were applied for irrigation water quality assessment. In addition, multivariate statistical techniques were used to identify the underlying hydrogeochemical processes. Results show that the content of TDS mainly depends on Cl^-, Na⁺, Mg²⁺, and SO₄^2-, and the HCO₃^- content is generally high except for the eastern sand area. These are responsible for complex hydrogeochemical processes, such as dissolution of carbonate minerals (dolomite and calcite), gypsum, halite, and silicate minerals, the cation exchange, as well as evaporation and concentration. The average evaluation levels of Na%, RSC, MH, and PS for irrigation water quality are doubtful, good, unsuitable, and injurious to unsatisfactory, respectively. Therefore, it is necessary for decision makers to comprehensively consider the indicators and thus reasonably evaluate the irrigation water quality.

Keywords: Irrigation water quality, multivariate statistical analysis, groundwater, hydrogeochemical process.

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Authors: Jaroslav Polec, Martin Šimek, Michal Martinovič, Elena Šikudová

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The television multiplex has reserved capacity and therefore we can use only limited number of videos for propagation of it. Appropriate composition of the multiplex has a major impact on how many videos is spread by multiplex. Therefore in this paper is designed a simple algorithm to optimize capacity utilization multiplex. Significant impact on the number of programs in the multiplex has also the fact from which programs is composed. Content of multiplex can be movies, news, sport, animated stories, documentaries, etc. These types have their own specific characteristics that affect their resulting data stream. In this paper is also done an impact analysis of the composition of the multiplex to use its capacity by video content. 

Keywords: Multiplex, content, group of pictures, frame, capacity.

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Authors: G. Poonkuzhali, K.Thiagarajan, K.Sarukesi

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With the enormous growth on the web, users get easily lost in the rich hyper structure. Thus developing user friendly and automated tools for providing relevant information without any redundant links to the users to cater to their needs is the primary task for the website owners. Most of the existing web mining algorithms have concentrated on finding frequent patterns while neglecting the less frequent one that are likely to contain the outlying data such as noise, irrelevant and redundant data. This paper proposes new algorithm for mining the web content by detecting the redundant links from the web documents using set theoretical(classical mathematics) such as subset, union, intersection etc,. Then the redundant links is removed from the original web content to get the required information by the user..

Keywords: Web documents, Web content mining, redundantlink, outliers, set theory.

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Authors: Fiona Browne, Huiru Zheng, Haiying Wang, Francisco Azuaje

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Recent years have seen a growing trend towards the integration of multiple information sources to support large-scale prediction of protein-protein interaction (PPI) networks in model organisms. Despite advances in computational approaches, the combination of multiple “omic" datasets representing the same type of data, e.g. different gene expression datasets, has not been rigorously studied. Furthermore, there is a need to further investigate the inference capability of powerful approaches, such as fullyconnected Bayesian networks, in the context of the prediction of PPI networks. This paper addresses these limitations by proposing a Bayesian approach to integrate multiple datasets, some of which encode the same type of “omic" data to support the identification of PPI networks. The case study reported involved the combination of three gene expression datasets relevant to human heart failure (HF). In comparison with two traditional methods, Naive Bayesian and maximum likelihood ratio approaches, the proposed technique can accurately identify known PPI and can be applied to infer potentially novel interactions.

Keywords: Bayesian network, Classification, Data integration, Protein interaction networks.

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Authors: Alexander V. Libin, Manon Schladen, Assya Pascalev, Nawar Shara, Miriam Philmon, Yuri Millo, Joseph Verbalis

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Chronic conditions carry with them strong emotions and often lead to charged relationships between patients and their health providers and, by extension, patients and health researchers. Persons are both autonomous and relational and a purely cognitive model of autonomy neglects the social and relational basis of chronic illness. Ensuring genuine informed consent in research requires a thorough understanding of how participants perceive a study and their reasons for participation. Surveys may not capture the complexities of reasoning that underlies study participation. Contradictory reasons for participation, for instance an initial claim of altruism as rationale and a subsequent claim of personal benefit (therapeutic misconception), affect the quality of informed consent. Individuals apply principles through the filter of personal values and lived experience. Authentic autonomy, and hence authentic consent to research, occurs within the context of patients- unique life narratives and illness experiences.

Keywords: ethical dilemmas, open source technology, patient education, psychology of decision making

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Authors: Firoz Khan

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Privacy of RFID systems is receiving increasing attention in the RFID community. RFID privacy is important as the RFID tags will be attached to all kinds of products and physical objects including people. The possible abuse or excessive use of RFID tracking capability by malicious users can lead to potential privacy violations. In this paper, we will discuss how the different industries use RFID and the potential privacy and security issues while RFID is implemented in these industries. Although RFID technology offers interesting services to customer and retailers, it could also endanger the privacy of end-users. Personal data can be leaked if a protection mechanism is not deployed in the RFID systems. The paper summarizes many different solutions for implementing privacy and security while deploying RFID systems.

Keywords: RFID, privacy, security, encryption.

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Authors: Claude Takenga, Rolf-Dietrich Berndt, Erling Si, Markus Diem, Guohui Qiao, Melanie Gau, Michael Brandstoetter, Martin Kampel, Michael Dworzak

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In patients with acute lymphoblastic leukaemia (ALL), treatment response is increasingly evaluated with minimal residual disease (MRD) analyses. Flow Cytometry (FCM) is a fast and sensitive method to detect MRD. However, the interpretation of these multi-parametric data requires intensive operator training and experience. This paper presents a pipeline-software, as a ready-to-use FCM-based MRD-assessment tool for the daily clinical practice for patients with ALL. The new tool increases accuracy in assessment of FCM-MRD in samples which are difficult to analyse by conventional operator-based gating since computer-aided analysis potentially has a superior resolution due to utilization of the whole multi-parametric FCM-data space at once instead of step-wise, two-dimensional plot-based visualization. The system developed as a telemedical network reduces the work-load and lab-costs, staff-time needed for training, continuous quality control, operator-based data interpretation. It allows dissemination of automated FCM-MRD analysis to medical centres which have no established expertise for the benefit of an even larger community of diseased children worldwide. We established a telemedical network system for analysis and clinical follow-up and treatment monitoring of Leukaemia. The system is scalable and adapted to link several centres and laboratories worldwide.

Keywords: Data security, flow cytometry, leukaemia, telematics platform, telemedicine.

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Authors: Ana Paula Lisboa Sohn, Filipa Dionísio Vieria, Nelson Casarotto, Idaulo José Cunha

Abstract:

This paper aims at identifying and analyzing the knowledge transmission channels in textile and clothing clusters located in Brazil and in Europe. Primary data was obtained through interviews with key individuals. The collection of primary data was carried out based on a questionnaire with ten categories of indicators of knowledge transmission. Secondary data was also collected through a literature review and through international organizations sites. Similarities related to the use of the main transmission channels of knowledge are observed in all cases. The main similarities are: influence of suppliers of machinery, equipment and raw materials; imitation of products and best practices; training promoted by technical institutions and businesses; and cluster companies being open to acquire new knowledge. The main differences lie in the relationship between companies, where in Europe the intensity of this relationship is bigger when compared to Brazil. The differences also occur in importance and frequency of the relationship with the government, with the cultural environment, and with the activities of research and development. It is also found factors that reduce the importance of geographical proximity in transmission of knowledge, and in generating trust and the establishment of collaborative behavior.

Keywords: Industrial clusters, interorganizational learning, knowledge transmission channels, textile and clothing industry.

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