Search results for: gait identification

Authors: C. Sinescu, M. Negrutiu, R. Negru, M. Romînu, A.G. Podoleanu

Abstract:

The fixed partial dentures are mainly used in the frontal part of the dental arch because of their great esthetics. There are several factors that are associated with the stress state created in ceramic restorations, including: thickness of ceramic layers, mechanical properties of the materials, elastic modulus of the supporting substrate material, direction, magnitude and frequency of applied load, size and location of occlusal contact areas, residual stresses induced by processing or pores, restoration-cement interfacial defects and environmental defects. The purpose of this study is to evaluate the capability of Polarization Sensitive Optical Coherence Tomography (PSOCT) in detection and analysis of possible material defects in metal-ceramic and integral ceramic fixed partial dentures. As a conclusion, it is important to have a non invasive method to investigate fixed partial prostheses before their insertion in the oral cavity in order to satisfy the high stress requirements and the esthetic function.

Keywords: Ceramic Fixed Partial Dentures, Material Defects, Polarization Sensitive Optical Coherence Tomography, Numerical Simulation

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Authors: Delly C. Lestari, Linosefa, Ardiana Kusumaningrum, Andi Yasmon, Anis Karuniawati

Abstract:

The objective of this study is to determine the prevalence of methicillin-resistant Staphylococcus aureus (MRSA) harboring mecA genes from screening isolates among intensive care unit (ICU) patients. All MRSA screening isolates from ICU’s patients of Cipto Mangunkusumo Hospital during 2011 and 2014 were included in this study. Identification and susceptibility test was performed using Vitek2 system (Biomereux®). PCR was conducted to characterize the SCCmec of S. aureus harboring the mecA gene on each isolate. Patient’s history of illness was traced through medical record. 24 isolates from 327 screening isolates were MRSA positive (7.3%). From PCR, we found 17 (70.8%) isolates carrying SCCmec type I, 3 (12.5%) isolates carrying SCCmec type III, and 2 (8.3%) isolates carrying SCCmec type IV. In conclusion, SCCmec type I is the most prevalent MRSA colonization among ICU patients in Cipto Mangunkusumo Hospital.

Keywords: MRSA, mecA genes, ICU, colonization.

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Authors: Sajjad Ahmed, Knut Hinkelmann, Flavio Corradini

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Fake news detection research is still in the early stage as this is a relatively new phenomenon in the interest raised by society. Machine learning helps to solve complex problems and to build AI systems nowadays and especially in those cases where we have tacit knowledge or the knowledge that is not known. We used machine learning algorithms and for identification of fake news; we applied three classifiers; Passive Aggressive, Naïve Bayes, and Support Vector Machine. Simple classification is not completely correct in fake news detection because classification methods are not specialized for fake news. With the integration of machine learning and text-based processing, we can detect fake news and build classifiers that can classify the news data. Text classification mainly focuses on extracting various features of text and after that incorporating those features into classification. The big challenge in this area is the lack of an efficient way to differentiate between fake and non-fake due to the unavailability of corpora. We applied three different machine learning classifiers on two publicly available datasets. Experimental analysis based on the existing dataset indicates a very encouraging and improved performance.

Keywords: Fake news detection, types of fake news, machine learning, natural language processing, classification techniques.

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Authors: Deepak Goswami, Padma Lochan Hazarika, Kandarpa Kumar Sarma

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The customary practice of identifying industrial sickness is a set traditional techniques which rely upon a range of manual monitoring and compilation of financial records. It makes the process tedious, time consuming and often are susceptible to manipulation. Therefore, certain readily available tools are required which can deal with such uncertain situations arising out of industrial sickness. It is more significant for a country like India where the fruits of development are rarely equally distributed. In this paper, we propose an approach based on Artificial Neural Network (ANN) to deal with industrial sickness with specific focus on a few such units taken from a less developed north-east (NE) Indian state like Assam. The proposed system provides decision regarding industrial sickness using eight different parameters which are directly related to the stages of sickness of such units. The mechanism primarily uses certain signals and symptoms of industrial health to decide upon the state of a unit. Specifically, we formulate an ANN based block with data obtained from a few selected units of Assam so that required decisions related to industrial health could be taken. The system thus formulated could become an important part of planning and development. It can also contribute towards computerization of decision support systems related to industrial health and help in better management.

Keywords: Industrial, Health, Classification, ANN, MLP, MSE.

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Authors: Lalitchandra J. Shah, Katarzyna Bialek, Melinda L. Clarke, Jessica L. Jansson

Abstract:

Handwriting is essential to academic success; however, the current literature is limited in the identification of pre-handwriting skills. The purpose of this study was to identify the pre-handwriting skills, which occupational therapy practitioners deem important to handwriting success, as well as those which aid in intervention planning. The online survey instrument consisted of 33 questions that assessed various skills related to the development of handwriting, as well as captured demographic information. Both occupational therapists and occupational therapy assistants were included in the survey study. The survey found that the respondents were in agreement that purposeful scribbling, the ability of a child to copy (vertical/horizontal lines, circle, squares, and triangles), imitating an oblique cross, cognitive skills (attention, praxis, self-regulation, sequencing), grasp patterns, hand dominance, in hand manipulation skills (shift, translation, rotation), bilateral integration, stabilization of paper, crossing midline, and visual perception were important indicators of handwriting readiness. The results of the survey support existing research regarding the skills necessary for the successful development of handwriting in children.

Keywords: Development, handwriting, occupational therapy, visual perceptual skills.

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Authors: Zahra Morshedi

Abstract:

Environmental considerations have become an integral part of developmental thinking and decision making in many countries. It is growing rapidly in importance as a discipline of its own. Preventive approaches have been used at the evolutional process of environmental management as a broad and dynamic system for dealing with pollution and environmental degradation. In this regard, Environmental Assessment as an activity for identification and prediction of project’s impacts carried out in the world and its legal significance dates back to late 1960. In Iran, according to the Article 2 of Environmental Protection Act, Environmental Impact Assessment (EIA) should be prepared for seven categories of project. This article has been actively implementing by Department of Environment at 1997. World Bank in 1989 attempted to introducing application of Environmental Assessment for making decision about projects which are required financial assistance in developing countries. So, preparing EIA for obtaining World Bank loan was obligated. Alborz Project is one of the World Bank Projects in Iran which is environmentally significant. Seven out of ten W.B safeguard policies were considered at this project. In this paper, Alborz project, objectives, safeguard policies and role of environmental management will be elaborated

Keywords: AILWMP, EIA, Environmental Management, Safeguard Policies.

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Authors: Insung Jung, Gi-Nam Wang

Abstract:

The objective of this paper is to a design of pattern classification model based on the back-propagation (BP) algorithm for decision support system. Standard BP model has done full connection of each node in the layers from input to output layers. Therefore, it takes a lot of computing time and iteration computing for good performance and less accepted error rate when we are doing some pattern generation or training the network. However, this model is using exclusive connection in between hidden layer nodes and output nodes. The advantage of this model is less number of iteration and better performance compare with standard back-propagation model. We simulated some cases of classification data and different setting of network factors (e.g. hidden layer number and nodes, number of classification and iteration). During our simulation, we found that most of simulations cases were satisfied by BP based using exclusive connection network model compared to standard BP. We expect that this algorithm can be available to identification of user face, analysis of data, mapping data in between environment data and information.

Keywords: Neural network, Back-propagation, classification.

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Authors: Vishal Awasthi, Atul Kumar Agnihotri

Abstract:

Face is a non-intrusive strong biometrics for identification of original and dummy facial by different artificial means. Face recognition is extremely important in the contexts of computer vision, psychology, surveillance, pattern recognition, neural network, content based video processing. The availability of a widespread face database is crucial to test the performance of these face recognition algorithms. The openly available face databases include face images with a wide range of poses, illumination, gestures and face occlusions but there is no dummy face database accessible in public domain. This paper presents a face detection algorithm based on the image segmentation in terms of distance from a fixed point and template matching methods. This proposed work is having the most appropriate number of nodal points resulting in most appropriate outcomes in terms of face recognition and detection. The time taken to identify and extract distinctive facial features is improved in the range of 90 to 110 sec. with the increment of efficiency by 3%.

Keywords: Face recognition, Principal Component Analysis, PCA, Linear Discriminant Analysis, LDA, Improved Support Vector Machine, iSVM, elastic bunch mapping technique.

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Authors: J. K. Adedeji, M. O. Oyekanmi

Abstract:

This paper has critically examined the use of Machine Learning procedures in curbing unauthorized access into valuable areas of an organization. The use of passwords, pin codes, user’s identification in recent times has been partially successful in curbing crimes involving identities, hence the need for the design of a system which incorporates biometric characteristics such as DNA and pattern recognition of variations in facial expressions. The facial model used is the OpenCV library which is based on the use of certain physiological features, the Raspberry Pi 3 module is used to compile the OpenCV library, which extracts and stores the detected faces into the datasets directory through the use of camera. The model is trained with 50 epoch run in the database and recognized by the Local Binary Pattern Histogram (LBPH) recognizer contained in the OpenCV. The training algorithm used by the neural network is back propagation coded using python algorithmic language with 200 epoch runs to identify specific resemblance in the exclusive OR (XOR) output neurons. The research however confirmed that physiological parameters are better effective measures to curb crimes relating to identities.

Keywords: Biometric characters, facial recognition, neural network, OpenCV.

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Authors: A. Kasmi, N. E. Abriak, M. Benzerzour, I. Shahrour

Abstract:

Large volumes of river sediments are dredged each year in Europe in order to maintain harbour activities and prevent floods. The management of this sediment has become increasingly complex. Several European projects were implemented to find environmentally sound solutions for these materials. The main objective of this study is to show the ability of river sediment to be used in road. Since sediments contain a high amount of water, then a dehydrating treatment by addition of the flocculation aid has been used. Firstly, a lot of physical characteristics are measured and discussed for a better identification of the raw sediment and this dehydrated sediment by addition the flocculation aid. The identified parameters are, for example, the initial water content, the density, the organic matter content, the grain size distribution, the liquid limit and plastic limit and geotechnical parameters. The environmental impacts of the used material were evaluated. The results obtained show that there is a slight change on the physical-chemical and geotechnical characteristics of sediment after dehydration by the addition of polymer. However, these sediments cannot be used in road construction.

Keywords: River sediment, dehydration, flocculation aid, characteristics, environmental impacts, road construction.

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Authors: Hyun-Woo Cho

Abstract:

Real-time or in-line process monitoring frameworks are designed to give early warnings for a fault along with meaningful identification of its assignable causes. In artificial intelligence and machine learning fields of pattern recognition various promising approaches have been proposed such as kernel-based nonlinear machine learning techniques. This work presents a kernel-based empirical monitoring scheme for batch type production processes with small sample size problem of partially unbalanced data. Measurement data of normal operations are easy to collect whilst special events or faults data are difficult to collect. In such situations, noise filtering techniques can be helpful in enhancing process monitoring performance. Furthermore, preprocessing of raw process data is used to get rid of unwanted variation of data. The performance of the monitoring scheme was demonstrated using three-dimensional batch data. The results showed that the monitoring performance was improved significantly in terms of detection success rate of process fault.

Keywords: Process Monitoring, kernel methods, multivariate filtering, data-driven techniques, quality improvement.

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Authors: Apirada Chinprateep

Abstract:

The ASEAN Economic Community (AEC) is the goal of regional economic integration by 2015. In the region, tourism is an activity that is important, especially as a source of foreign currency, a source of employment creation and a source of income bringing to the region. Given the complexity of the issues entailing the concept of sustainable tourism, this paper tries to assess tourism sustainability with the ASEAN, based on a number of quantitative indicators for all the ten economies, Thailand, Myanmar, Laos, Vietnam, Malaysia, Singapore, Indonesia, Philippines, Cambodia, and Brunei. The methodological framework will provide a number of benchmarks of tourism activities in these countries. They include identification of the dimensions; for example, economic, socio-ecologic, infrastructure and indicators, method of scaling, chart representation and evaluation on Asian countries. This specification shows that a similar level of tourism activity might introduce different implementation in the tourism activity and might have different consequences for the socioecological environment and sustainability. The heterogeneity of developing countries exposed briefly here would be useful to detect and prepare for coping with the main problems of each country in their tourism activities, as well as competitiveness and value creation of tourism for ASEAN economic community, and will compare with other parts of the world.

Keywords: AEC, ASEAN, sustainable, tourism, competitiveness.

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Authors: Mirzaee Mahmoodabadi Reza, Afghah Massih, Saeedi Somaye

Abstract:

Pabdeh shaly formation (Paleocene-Oligomiocene) has been expanded in Fars, Khozestan and Lorestan. The lower lithostratigraphic limit of this formation in Shiraz area is distinguished from Gurpi formation by purple shale. Its upper limit is gradational and conformable with Asmari formation. In order to study sequence stratigraphy and microfacies of Pabdeh formation in Shiraz area, one stratigraphic section have been chosen (Zanjiran section). Petrographic studies resulted in the identification of 9 pelagic and calciturbidite microfacies. The calciturbidite microfacies have been formed when the sea level was high, the rate of carbonate deposition was high and it slumped into the deep marine. Sequence stratigraphy studies show that Pabdeh formation in the studied zone consists of two depositional sequences (DS) that the lower contact is erosional (purple shale - type one, SBI or type two, SB2) and the upper contact is correlative conformity (type two, SB2).

Keywords: Pabdeh formation, Shiraz, Microfacies, Purple Shale, Zanjiran Section, Sequence Stratigraphy

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Authors: Fei Long Wei, Hua Yang, Hai Tao Zhang, Zhou Ping Yin

Abstract:

In this study, an local invariant generalized Houghtransform (LI-GHT) method is proposed for integrated circuit (IC) visual positioning. The original generalized Hough transform (GHT) is robust to external noise; however, it is not suitable for visual positioning of IC chips due to the four-dimensionality (4D) of parameter space which leads to the substantial storage requirement and high computational complexity. The proposed LI-GHT method can reduce the dimensionality of parameter space to 2D thanks to the rotational invariance of local invariant geometric feature and it can estimate the accuracy position and rotation angle of IC chips in real-time under noise and blur influence. The experiment results show that the proposed LI-GHT can estimate position and rotation angle of IC chips with high accuracy and fast speed. The proposed LI-GHT algorithm was implemented in IC visual positioning system of radio frequency identification (RFID) packaging equipment.

Keywords: Integrated Circuit Visual Positioning, Generalized Hough Transform, Local invariant Generalized Hough Transform, ICpacking equipment.

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Authors: Markus Link, Manfred Spraul, Hartmut Schaefer, Fang Fang, Birk Schuetz

Abstract:

High Resolution NMR Spectroscopy offers unique screening capabilities for food quality and safety by combining non-targeted and targeted screening in one analysis.

The objective is to demonstrate, that due to its extreme reproducibility NMR can detect smallest changes in concentrations of many components in a mixture, which is best monitored by statistical evaluation however also delivers reliable quantification results.

The methodology typically uses a 400 MHz high resolution instrument under full automation after minimized sample preparation.

For example one fruit juice analysis in a push button operation takes at maximum 15 minutes and delivers a multitude of results, which are automatically summarized in a PDF report.

The method has been proven on fruit juices, where so far unknown frauds could be detected. In addition conventional targeted parameters are obtained in the same analysis. This technology has the advantage that NMR is completely quantitative and concentration calibration only has to be done once for all compounds. Since NMR is so reproducible, it is also transferable between different instruments (with same field strength) and laboratories. Based on strict SOP`s, statistical models developed once can be used on multiple instruments and strategies for compound identification and quantification are applicable as well across labs.

Keywords: Automated solution, NMR, non-targeted screening, targeted screening.

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Authors: Mahanijah Md Kamal., Dingli Yu

Abstract:

This paper presents a new method of fault detection and isolation (FDI) for polymer electrolyte membrane (PEM) fuel cell (FC) dynamic systems under an open-loop scheme. This method uses a radial basis function (RBF) neural network to perform fault identification, classification and isolation. The novelty is that the RBF model of independent mode is used to predict the future outputs of the FC stack. One actuator fault, one component fault and three sensor faults have been introduced to the PEMFC systems experience faults between -7% to +10% of fault size in real-time operation. To validate the results, a benchmark model developed by Michigan University is used in the simulation to investigate the effect of these five faults. The developed independent RBF model is tested on MATLAB R2009a/Simulink environment. The simulation results confirm the effectiveness of the proposed method for FDI under an open-loop condition. By using this method, the RBF networks able to detect and isolate all five faults accordingly and accurately.

Keywords: Polymer electrolyte membrane fuel cell, radial basis function neural networks, fault detection, fault isolation.

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Authors: Frank Emmert Streib

Abstract:

The classification of the protein structure is commonly not performed for the whole protein but for structural domains, i.e., compact functional units preserved during evolution. Hence, a first step to a protein structure classification is the separation of the protein into its domains. We approach the problem of protein domain identification by proposing a novel graph theoretical algorithm. We represent the protein structure as an undirected, unweighted and unlabeled graph which nodes correspond the secondary structure elements of the protein. This graph is call the protein graph. The domains are then identified as partitions of the graph corresponding to vertices sets obtained by the maximization of an objective function, which mutually maximizes the cycle distributions found in the partitions of the graph. Our algorithm does not utilize any other kind of information besides the cycle-distribution to find the partitions. If a partition is found, the algorithm is iteratively applied to each of the resulting subgraphs. As stop criterion, we calculate numerically a significance level which indicates the stability of the predicted partition against a random rewiring of the protein graph. Hence, our algorithm terminates automatically its iterative application. We present results for one and two domain proteins and compare our results with the manually assigned domains by the SCOP database and differences are discussed.

Keywords: Graph partitioning, unweighted graph, protein domains.

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Authors: Vít Lédl, Tomáš Vít, Pavel Psota, Roman Doleček

Abstract:

The presented paper shows the possibility of using holographic interferometry for measurement of temperature field in moving fluids. There are a few methods for identification of velocity fields in fluids, such us LDA, PIV, hot wire anemometry. It is very difficult to measure the temperature field in moving fluids. One of the often used methods is Constant Current Anemometry (CCA), which is a point temperature measurement method. Data are possibly acquired at frequencies up to 1000Hz. This frequency should be limiting factor for using of CCA in fluid when fast change of temperature occurs. This shortcoming of CCA measurements should be overcome by using of optical methods such as holographic interferometry. It is necessary to employ a special holographic setup with double sensitivity instead of the commonly used Mach-Zehnder type of holographic interferometer in order to attain the parameters sufficient for the studied case. This setup is not light efficient like the Mach-Zehnder type but has double sensitivity. The special technique of acquiring and phase averaging of results from holographic interferometry is also presented. The results from the holographic interferometry experiments will be compared with the temperature field achieved by methods CCA method.

Keywords: Holographic interferometry, pulsatile flow, temperature measurement, hot-wire anemometry

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Authors: Jafar Ahmadi, Alireza Pour-Aboughadareh

Abstract:

Wheat is the first and the most important grain of the world and its bakery property is due to glutenin and gliadin qualities. Wheat seed proteins were divided into four groups according to solubility including albumin, globulin, glutenin and prolamin or gliadin. Gliadins are major components of the storage proteins in wheat endosperm. It seems that little information is available about gliadin genes in Iranian wild relatives of wheat. Thus, the aim of this study was the evaluation of the wheat wild relatives collected from different origins of Zagros Mountains in Iran, in terms of coding gliadin genes using specific primers. For this, forty accessions of Triticum boeoticum and Triticum urartu were selected for this study. For each accession, genomic DNA was extracted and PCRs were performed in total volumes of 15 μl. The amplification products were separated on 1.5% agarose gels. In results, for Gli-2A locus three allelic variants were detected by Gli-2As primer pairs. The sizes of PCR products for these alleles were 210, 490 and 700 bp. Only five (13%) and two accessions (5%) produced 700 and 490 bp fragments when their DNA was amplified with the Gli.As.2 primer pairs. However, 93% of the accessions carried allele 210 bp, and only 8% did not any product for this marker. Therefore, these germplasm could be used as rich gene pool to broaden the genetic base of bread wheat.

Keywords: Diploied wheat, gliadin, Triticum boeoticum, Triticum urartu.

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Authors: Yan Ren, Fei Guo, Jun Qiao, Shengwei Hu, Hui Zhang, Yuanzhi Wang, Pengyan Wang, Jinliang Sheng, Xinli Gu, Xiaojun Liu, Chuangfu Chen

Abstract:

Bovine viral diarrhea virus (BVDV) can cause lifelong persistent infection. One reason for the phenomena is attributed to BVDV infection to placenta tissue. However the mechanisms that BVDV invades into placenta tissue remain unclear. To clarify the molecular mechanisms, we investigated the possible means that BVDV entered into bovine trophoblast cells (TPC). Yeast two-hybrid system was used to identify proteins extracted from TPC, which interact with BVDV envelope glycoprotein E2. A PGbkt7-E2 yeast expression vector and TPC cDNA library were constructed. Through two rounds of screening, three positive clones were identified. Sequencing analysis indicated that all the three positive clones encoded the same protein clathrin. Physical interaction between clathrin and BVDV E2 protein was further confirmed by coimmunoprecipitation experiments. This result suggested that the clathrin might play a critical role in the process of BVDV entry into placenta tissue and might be a novel antiviral target for preventing BVDV infection.

Keywords: Bovine viral diarrhea virus, clathrin, glycoprotein E2, yeast two-hybrid system.

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Authors: Martina Drdlová, Michal Frank, Jaroslav Buchar, Josef Krátký

Abstract:

The main aim of the presented experiments is to improve behaviour of sandwich structures under dynamic loading, such as crash or explosion. Several cellular materials are widely used as core of the sandwich structures and their properties influence the response of the entire element under impact load. To optimize their performance requires the characterisation of the core material behaviour at high strain rates and identification of the underlying mechanism. This work presents the study of high strain-rate characteristics of a specific porous lightweight blast energy absorbing foam using a Split Hopkinson Pressure Bar (SHPB) technique adapted to perform tests on low strength materials. Two different velocities, 15 and 30 m.s-1 were used to determine the strain sensitivity of the material. Foams were designed using two types of porous lightweight spherical raw materials with diameters of 30- 100 *m, combined with polymer matrix. Cylindrical specimens with diameter of 15 mm and length of 7 mm were prepared and loaded using a Split Hopkinson Pressure Bar apparatus to assess the relation between the composition of the material and its shock wave attenuation capacity.

Keywords: Blast, foam, microsphere, resin.

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Authors: Takeshi Takeda

Abstract:

The author conducted post-test analysis with the RELAP5/MOD3.3 code for an experiment using the ROSA/LSTF (rig of safety assessment/large-scale test facility) that simulated a 1% cold leg small-break loss-of-coolant accident under the failure of scram in a pressurized water reactor. The LSTF test assumed total failure of high-pressure injection system of emergency core cooling system. In the LSTF test, natural circulation contributed to maintain core cooling effect for a relatively long time until core uncovery occurred. The post-test analysis result confirmed inadequate prediction of the primary coolant distribution. The author created the phenomena identification and ranking table (PIRT) for each component. The author investigated the influences of uncertain parameters determined by the PIRT on the cladding surface temperature at a certain time during core uncovery within the defined uncertain ranges.

Keywords: LSTF, LOCA, scram, RELAP5.

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Authors: Nahid Ardalani, Ahmadreza Khoogar, H. Roohi

Abstract:

In this paper we compare the response of linear and nonlinear neural network-based prediction schemes in prediction of received Signal-to-Interference Power Ratio (SIR) in Direct Sequence Code Division Multiple Access (DS/CDMA) systems. The nonlinear predictor is Multilayer Perceptron MLP and the linear predictor is an Adaptive Linear (Adaline) predictor. We solve the problem of complexity by using the Minimum Mean Squared Error (MMSE) principle to select the optimal predictors. The optimized Adaline predictor is compared to optimized MLP by employing noisy Rayleigh fading signals with 1.8 GHZ carrier frequency in an urban environment. The results show that the Adaline predictor can estimates SIR with the same error as MLP when the user has the velocity of 5 km/h and 60 km/h but by increasing the velocity up-to 120 km/h the mean squared error of MLP is two times more than Adaline predictor. This makes the Adaline predictor (with lower complexity) more suitable than MLP for closed-loop power control where efficient and accurate identification of the time-varying inverse dynamics of the multi path fading channel is required.

Keywords: Power control, neural networks, DS/CDMA mobilecommunication systems.

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Authors: Ali Hajiesmaeili, Mehdi Rahimi, Ehsan Jaberi, Amir Abbas Hosseini

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The purpose of this study is investigating the influences of logistics performance on organizational performance including both marketing & financial aspects, and showing the financial impacts of selecting the right marketing and logistics priorities in line with their supply chain type, and also giving the practitioners an advance identification of their priorities and participation types of supply chain, and the best combination of their strategies and resources in this regard. We made use of the original model’s questionnaire to gather all expert’s data and also SPSS and AMOS Ver.22 to analyze the gathered data. CFA method was also used to test whether a relationship between observed variables and their underlying latent constructs exists. Supply chain strategy implementation leads to logistics performance improvement, and marketing performance will be affected as well. Logistics service providers should focus on enhancement of supply chain performance, since logistics performance has been considered as a basis of evaluation of supply chain management strategy. Consequently, performance of the organization will be enhanced. This case is the first research made in Iran that analyzes the relationship between Logistics & Organizational performance in Home Appliances and Home Entertainment companies.

Keywords: Logistics, organizational performance, supply chain, supply chain strategy.

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Authors: Boram Kim, Shigeyasu Uno, Kazuo Nakazato

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Continuous-time delta-sigma analog digital converter (ADC) for radio frequency identification (RFID) complementary metal oxide semiconductor (CMOS) biosensor has been reported. This delta-sigma ADC is suitable for digital conversion of biosensor signal because of small process variation, and variable input range. As the input range of continuous-time switched current delta-sigma ADC (Dynamic range : 50 dB) can be limited by using current reference, amplification of biosensor signal is unnecessary. The input range is switched to wide input range mode or narrow input range mode by command of current reference. When the narrow input range mode, the input range becomes ± 0.8 V. The measured power consumption is 5 mW and chip area is 0.31 mm^2 using 1.2 um standard CMOS process. Additionally, automatic input range detecting system is proposed because of RFID biosensor applications.

Keywords: continuous time, delta sigma, A/D converter, RFID, biosensor, CMOS

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Authors: Latha Parameswaran, K. Anbumani

Abstract:

Multimedia security is an incredibly significant area of concern. The paper aims to discuss a robust image watermarking scheme, which can withstand geometric attacks. The source image is initially moment normalized in order to make it withstand geometric attacks. The moment normalized image is wavelet transformed. The first level wavelet transformed image is segmented into blocks if size 8x8. The product of mean and standard and standard deviation of each block is computed. The second level wavelet transformed image is divided into 8x8 blocks. The product of block mean and the standard deviation are computed. The difference between products in the two levels forms the watermark. The watermark is inserted by modulating the coefficients of the mid frequencies. The modulated image is inverse wavelet transformed and inverse moment normalized to generate the watermarked image. The watermarked image is now ready for transmission. The proposed scheme can be used to validate identification cards and financial instruments. The performance of this scheme has been evaluated using a set of parameters. Experimental results show the effectiveness of this scheme.

Keywords: Image moments, wavelets, content-based watermarking, moment normalization, geometric attacks.

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Authors: K. G. Firouzjah, A. Sheikholeslami

Abstract:

The perfect operation of common Active Filters is depended on accuracy of identification system distortion. Also, using a suitable method in current injection and reactive power compensation, leads to increased filter performance. Due to this fact, this paper presents a method based on predictive current control theory in shunt active filter applications. The harmonics of the load current is identified by using o–d–q reference frame on load current and eliminating the DC part of d–q components. Then, the rest of these components deliver to predictive current controller as a Threephase reference current by using Park inverse transformation. System is modeled in discreet time domain. The proposed method has been tested using MATLAB model for a nonlinear load (with Total Harmonic Distortion=20%). The simulation results indicate that the proposed filter leads to flowing a sinusoidal current (THD=0.15%) through the source. In addition, the results show that the filter tracks the reference current accurately.

Keywords: Active filter, predictive current control, low pass filter, harmonic omitting, o–d–q reference frame.

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Authors: Lee Suan Chua

Abstract:

This study investigated the effects of thermal treatment on Tualang honey sample in terms of honey colour and heat-induced small metabolites. The heating process was carried out in a temperature controlled water batch at 90oC for 4 hours. The honey samples were put in cylinder tubes with the dimension of 1 cm diameter and 10 cm length for homogenous heat transfer. The results found that the thermal treatment produced not only hydroxylmethylfurfural, but also other harmful substances such as phthalic anhydride and radiolytic byproducts. The degradation of honey protein was due to the detection of free amino acids such as cysteine and phenylalanine in heat-treated honey samples. Sugar dehydration was also occurred because fragmented di-galactose was identified based on the presence of characteristic ions in the mass fragmentation pattern. The honey colour was found getting darker as the heating duration was increased up to 4 hours. Approximately, 60 mm PFund of increment was noticed for the honey colour with the colour change rate of 14.8 mm PFund per hour. Based on the principal component analysis, the score plot clearly shows that the chemical profile of Tualang honey was significantly altered after 2 hours of heating at 90oC.

Keywords: Honey colour, hydroxylmethylfurfural, thermal treatment, Tualang honey.

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Authors: S. Manzoor, A. Nadeem, M. Javed, ME. Babar

Abstract:

A major goal in animal genetics is to understand the role of common genetic variants in diseases susceptibility and production traits. Sahiwal cattle can be considered as a global animal genetic resource due to its relatively high milk producing ability, resistance against tropical diseases and heat tolerant. CYP11B1 gene provides instructions for making a mitochondrial enzyme called steroid 11-beta-hydroxylase. It catalyzes the 11deoxy-cortisol to cortisol and 11deoxycorticosterone to corticosterone in cattle. The bovine CYP11B1 gene is positioned on BTA14q12 comprises of eight introns and nine exons and protein is associated with mitochondrial epithelium. The present study was aimed to identify the single-nucleotide polymorphisms in CYP11B1 gene in Sahiwal cattle breed of Pakistan. Four polymorphic sites were identified in exon one of CYP11B1 gene through sequencing approach. Significant finding was the incidence of the C→T polymorphism in 5'-UTR, causing amino acid substitution from alanine to valine (A30V) in Sahiwal cattle breed. That Ala/Val polymorphism may serve as a powerful genetic tool for the development of DNA markers that can be used for the particular traits for different local cattle breeds.

Keywords: CYP11B1, single nucleotide polymorphism, sahiwal cattle, Pakistan.

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Authors: Umar Albalawi, Sang C. Suh, Jinoh Kim

Abstract:

As internet continues to expand its usage with an  enormous number of applications, cyber-threats have significantly  increased accordingly. Thus, accurate detection of malicious traffic in  a timely manner is a critical concern in today’s Internet for security.  One approach for intrusion detection is to use Machine Learning (ML)  techniques. Several methods based on ML algorithms have been  introduced over the past years, but they are largely limited in terms of  detection accuracy and/or time and space complexity to run. In this  work, we present a novel method for intrusion detection that  incorporates a set of supervised learning algorithms. The proposed  technique provides high accuracy and outperforms existing techniques  that simply utilizes a single learning method. In addition, our  technique relies on partial flow information (rather than full  information) for detection, and thus, it is light-weight and desirable for  online operations with the property of early identification. With the  mid-Atlantic CCDC intrusion dataset publicly available, we show that  our proposed technique yields a high degree of detection rate over 99%  with a very low false alarm rate (0.4%). 

 

Keywords: Intrusion Detection, Supervised Learning, Traffic Classification.

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