Search results for: molecular identification

Authors: Farzaneh Ahmadzadeh

Abstract:

Quality control charts are very effective in detecting out of control signals but when a control chart signals an out of control condition of the process mean, searching for a special cause in the vicinity of the signal time would not always lead to prompt identification of the source(s) of the out of control condition as the change point in the process parameter(s) is usually different from the signal time. It is very important to manufacturer to determine at what point and which parameters in the past caused the signal. Early warning of process change would expedite the search for the special causes and enhance quality at lower cost. In this paper the quality variables under investigation are assumed to follow a multivariate normal distribution with known means and variance-covariance matrix and the process means after one step change remain at the new level until the special cause is being identified and removed, also it is supposed that only one variable could be changed at the same time. This research applies artificial neural network (ANN) to identify the time the change occurred and the parameter which caused the change or shift. The performance of the approach was assessed through a computer simulation experiment. The results show that neural network performs effectively and equally well for the whole shift magnitude which has been considered.

Keywords: Artificial neural network, change point estimation, monte carlo simulation, multivariate exponentially weighted movingaverage

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Authors: Chih-Hao Chen, Hsing-Chung Lee, Qingdong Ling, Hsiao-Jung Chen, Sun-Chong Wang, Li-Ching Wu, H.C. Lee

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Segmentation, filtering out of measurement errors and identification of breakpoints are integral parts of any analysis of microarray data for the detection of copy number variation (CNV). Existing algorithms designed for these tasks have had some successes in the past, but they tend to be O(N2) in either computation time or memory requirement, or both, and the rapid advance of microarray resolution has practically rendered such algorithms useless. Here we propose an algorithm, SAD, that is much faster and much less thirsty for memory – O(N) in both computation time and memory requirement -- and offers higher accuracy. The two key ingredients of SAD are the fundamental assumption in statistics that measurement errors are normally distributed and the mathematical relation that the product of two Gaussians is another Gaussian (function). We have produced a computer program for analyzing CNV based on SAD. In addition to being fast and small it offers two important features: quantitative statistics for predictions and, with only two user-decided parameters, ease of use. Its speed shows little dependence on genomic profile. Running on an average modern computer, it completes CNV analyses for a 262 thousand-probe array in ~1 second and a 1.8 million-probe array in 9 seconds

Keywords: Cancer, pathogenesis, chromosomal aberration, copy number variation, segmentation analysis.

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Authors: Saad Chakkor, Mostafa Baghouri, Abderrahmane Hajraoui

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ESPRIT-TLS method appears a good choice for high resolution fault detection in induction machines. It has a very high effectiveness in the frequency and amplitude identification. Contrariwise, it presents a high computation complexity which affects its implementation in real time fault diagnosis. To avoid this problem, a Fast-ESPRIT algorithm that combined the IIR band-pass filtering technique, the decimation technique and the original ESPRIT-TLS method was employed to enhance extracting accurately frequencies and their magnitudes from the wind stator current with less computation cost. The proposed algorithm has been applied to verify the wind turbine machine need in the implementation of an online, fast, and proactive condition monitoring. This type of remote and periodic maintenance provides an acceptable machine lifetime, minimize its downtimes and maximize its productivity. The developed technique has evaluated by computer simulations under many fault scenarios. Study results prove the performance of Fast- ESPRIT offering rapid and high resolution harmonics recognizing with minimum computation time and less memory cost.

Keywords: Spectral Estimation, ESPRIT-TLS, Real Time, Diagnosis, Wind Turbine Faults, Band-Pass Filtering, Decimation.

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Authors: Wen-Shyong Tzou, Chih-Ching Huang, Chin-Hwa Hu, Ying-Tsang Lo, Tun-Wen Pai, Chia-Yin Chiang, Chung-Hao Li, Hong-Jyuan Jian

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Plasmin plays an important role in the human circulatory system owing to its catalytic ability of fibrinolysis. The immediate injection of plasmin in patients of strokes has intrigued many scientists to design vectors that can transport plasmin to the desired location in human body. Here we predict the structure of human plasmin and investigate the interaction of plasmin with the gold-nanoparticle. Because the crystal structure of plasminogen has been solved, we deleted N-terminal domain (Pan-apple domain) of plasminogen and generate a mimic of the active form of this enzyme (plasmin). We conducted a simulated annealing process on plasmin and discovered a very large conformation occurs. Kringle domains 1, 4 and 5 had been observed to leave its original location relative to the main body of the enzyme and the original doughnut shape of this enzyme has been transformed to a V-shaped by opening its two arms. This observation of conformational change is consistent with the experimental results of neutron scattering and centrifugation. We subsequently docked the plasmin on the simulated gold surface to predict their interaction. The V-shaped plasmin could utilize its Kringle domain and catalytic domain to contact the gold surface. Our findings not only reveal the flexibility of plasmin structure but also provide a guide for the design of a plasmin-gold nanoparticle.

Keywords: Docking, gold nanoparticle, molecular simulation, plasmin.

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Authors: Lara F. Horani, Shurong Tong

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Identification of customer requirements and their preferences are the starting points in the process of product design. Most of design methodologies focus on traditional requirements. But in the previous decade, the green products and the environment requirements have increasingly attracted the attention with the constant increase in the level of consumer awareness towards environmental problems (such as green-house effect, global warming, pollution and energy crisis, and waste management). Determining the importance weights for the customer requirements is an essential and crucial process. This paper used the analytic hierarchy process (AHP) approach to evaluate and rate the customer requirements for green products. With respect to the ultimate goal of customer satisfaction, surveys are conducted using a five-point scale analysis. With the help of this scale, one can derive the weight vectors. This approach can improve the imprecise ranking of customer requirements inherited from studies based on the conventional AHP. Furthermore, the AHP with extent analysis is simple and easy to implement to prioritize customer requirements. The research is based on collected data through a questionnaire survey conducted over a sample of 160 people belonging to different age, marital status, education and income groups in order to identify the customer preferences for green product requirements.

Keywords: Analytic hierarchy process, green product, customer requirements for green design, importance weights for the customer requirements.

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Authors: José Julio de C. Pituba

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This work deals with the initial applications and formulation of an anisotropic plastic-damage constitutive model proposed for non-linear analysis of reinforced concrete structures submitted to a loading with change of the sign. The original constitutive model is based on the fundamental hypothesis of energy equivalence between real and continuous medium following the concepts of the Continuum Damage Mechanics. The concrete is assumed as an initial elastic isotropic medium presenting anisotropy, permanent strains and bimodularity (distinct elastic responses whether traction or compression stress states prevail) induced by damage evolution. In order to take into account the bimodularity, two damage tensors governing the rigidity in tension or compression regimes are introduced. Then, some conditions are introduced in the original version of the model in order to simulate the damage unilateral effect. The three-dimensional version of the proposed model is analyzed in order to validate its formulation when compared to micromechanical theory. The one-dimensional version of the model is applied in the analyses of a reinforced concrete beam submitted to a loading with change of the sign. Despite the parametric identification problems, the initial applications show the good performance of the model.

Keywords: Damage model, plastic strain, unilateral effect.

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Authors: Joseph E. Estevez, Mahdi Ghazizadeh, James G. Ryan, Ajit D. Kelkar

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Radiation shielding is an obstacle in long duration space exploration. Boron Nitride Nanotubes (BNNTs) have attracted attention as an additive to radiation shielding material due to B¹⁰’s large neutron capture cross section. The B¹⁰ has an effective neutron capture cross section suitable for low energy neutrons ranging from 10^-5 to 10⁴ eV and hydrogen is effective at slowing down high energy neutrons. Hydrogenated BNNTs are potentially an ideal nanofiller for radiation shielding composites. We use Molecular Dynamics (MD) Simulation via Material Studios Accelrys 6.0 to model the Young’s Modulus of Hydrogenated BNNTs. An extrapolation technique was employed to determine the Young’s Modulus due to the deformation of the nanostructure at its theoretical density. A linear regression was used to extrapolate the data to the theoretical density of 2.62g/cm³. Simulation data shows that the hydrogenated BNNTs will experience a 11% decrease in the Young’s Modulus for (6,6) BNNTs and 8.5% decrease for (8,8) BNNTs compared to non-hydrogenated BNNT’s. Hydrogenated BNNTs are a viable option as a nanofiller for radiation shielding nanocomposite materials for long range and long duration space exploration.

Keywords: Boron Nitride Nanotube, Radiation Shielding, Young Modulus, Atomistic Modeling.

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Authors: K. E. Oyetade, S. D. Eyono Obono

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Age ratings are very helpful in providing parents with relevant information for the purchase and use of digital technologies by the children; this is why the non-definition of age ratings for the use of ICTs by children in schools is a major concern; and this problem serves as a motivation for this study whose aim is to examine the factors affecting the perceptions of educators on the learners’ youngest age for the introduction of ICTs in schools. This aim is achieved through two types of research objectives: the identification and design of theories and models on age ratings, and the empirical testing of such theories and models in a survey of educators from the Camperdown district of the South African KwaZulu-Natal province. A questionnaire is used for the collection of the data of this survey whose validity and reliability is checked in SPSS prior to its descriptive and correlative quantitative analysis. The main hypothesis supporting this research is the association between the demographics of educators, their personality, and their perceptions on the learners’ youngest age for the introduction of ICTs in schools; as claimed by existing research; except that the present study looks at personality from three dimensions: self-actualized personalities, fully functioning personalities, and healthy personalities. This hypothesis was fully confirmed by the empirical study conducted by this research except for the demographic factor where only the educators’ grade or class was found to be associated with the personality of educators.

Keywords: Age ratings, Educators, E-learning, Personality Theories.

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Authors: Chia-Ta Tsai, Wen-Lin Huang, Shinn-Jang Ho, Li-Sun Shu, Shinn-Ying Ho

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Prediction of bacterial virulent protein sequences can give assistance to identification and characterization of novel virulence-associated factors and discover drug/vaccine targets against proteins indispensable to pathogenicity. Gene Ontology (GO) annotation which describes functions of genes and gene products as a controlled vocabulary of terms has been shown effectively for a variety of tasks such as gene expression study, GO annotation prediction, protein subcellular localization, etc. In this study, we propose a sequence-based method Virulent-GO by mining informative GO terms as features for predicting bacterial virulent proteins. Each protein in the datasets used by the existing method VirulentPred is annotated by using BLAST to obtain its homologies with known accession numbers for retrieving GO terms. After investigating various popular classifiers using the same five-fold cross-validation scheme, Virulent-GO using the single kind of GO term features with an accuracy of 82.5% is slightly better than VirulentPred with 81.8% using five kinds of sequence-based features. For the evaluation of independent test, Virulent-GO also yields better results (82.0%) than VirulentPred (80.7%). When evaluating single kind of feature with SVM, the GO term feature performs much well, compared with each of the five kinds of features.

Keywords: Bacterial virulence factors, GO terms, prediction, protein sequence.

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Authors: Iftikhar Ahmed Satti, Wan Ismail Wan Yusoff

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The structural interpretation of a part of eastern Potwar (Missa Keswal) has been carried out with available seismological, seismic and well data. Seismological data contains both the source parameters and fault plane solution (FPS) parameters and seismic data contains ten seismic lines that were re-interpreted by using well data. Structural interpretation depicts two broad types of fault sets namely, thrust and back thrust faults. These faults together give rise to pop up structures in the study area and also responsible for many structural traps and seismicity. Seismic interpretation includes time and depth contour maps of Chorgali Formation while seismological interpretation includes focal mechanism solution (FMS), depth, frequency, magnitude bar graphs and renewal of Seismotectonic map. The Focal Mechanism Solutions (FMS) that surrounds the study area are correlated with the different geological and structural maps of the area for the determination of the nature of subsurface faults. Results of structural interpretation from both seismic and seismological data show good correlation. It is hoped that the present work will help in better understanding of the variations in the subsurface structure and can be a useful tool for earthquake prediction, planning of oil field and reservoir monitoring.

Keywords: Focal mechanism solution (FMS), Fault plane solution (FPS), Reservoir monitoring, earthquake prediction.

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Authors: C. A. Corzo, N. Zhang, F. Corzo

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Insider abuse has recently been reported as one of the more frequently occurring security incidents, suggesting that more security is required for detecting and preventing unauthorised financial transactions entered by authorised users. To address the problem, and based on the observation that all authorised interbanking financial transactions trigger or are triggered by other transactions in a workflow, we have developed a security solution based on a redefined understanding of an audit workflow. One audit workflow where there is a log file containing the complete workflow activity of financial transactions directly related to one financial transaction (an electronic deal recorded at an e-trading system). The new security solution contemplates any two parties interacting on the basis of financial transactions recorded by their users in related but distinct automated financial systems. In the new definition interorganizational and intra-organization interactions can be described in one unique audit trail. This concept expands the current ideas of audit trails by adapting them to actual e-trading workflow activity, i.e. intra-organizational and inter-organizational activity. With the above, a security auditing service is designed to detect integrity drifts with and between organizations in order to detect unauthorised financial transactions entered by authorised users.

Keywords: Intrusion Detection and Prevention, Authentica-transtionand Identification.

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Authors: Hsin-Chang Yang, Chung-Hong Lee, Kuo-Lung Ke

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The self-organizing map (SOM) model is a well-known neural network model with wide spread of applications. The main characteristics of SOM are two-fold, namely dimension reduction and topology preservation. Using SOM, a high-dimensional data space will be mapped to some low-dimensional space. Meanwhile, the topological relations among data will be preserved. With such characteristics, the SOM was usually applied on data clustering and visualization tasks. However, the SOM has main disadvantage of the need to know the number and structure of neurons prior to training, which are difficult to be determined. Several schemes have been proposed to tackle such deficiency. Examples are growing/expandable SOM, hierarchical SOM, and growing hierarchical SOM. These schemes could dynamically expand the map, even generate hierarchical maps, during training. Encouraging results were reported. Basically, these schemes adapt the size and structure of the map according to the distribution of training data. That is, they are data-driven or dataoriented SOM schemes. In this work, a topic-oriented SOM scheme which is suitable for document clustering and organization will be developed. The proposed SOM will automatically adapt the number as well as the structure of the map according to identified topics. Unlike other data-oriented SOMs, our approach expands the map and generates the hierarchies both according to the topics and their characteristics of the neurons. The preliminary experiments give promising result and demonstrate the plausibility of the method.

Keywords: Self-organizing map, topic identification, learning algorithm, text clustering.

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Authors: M. W. Lau, C. O. Ng

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This is a study on numerical simulation of the convection-diffusion transport of a chemical species in steady flow through a small-diameter tube, which is lined with a very thin layer made up of retentive and absorptive materials. The species may be subject to a first-order kinetic reversible phase exchange with the wall material and irreversible absorption into the tube wall. Owing to the velocity shear across the tube section, the chemical species may spread out axially along the tube at a rate much larger than that given by the molecular diffusion; this process is known as dispersion. While the long-time dispersion behavior, well described by the Taylor model, has been extensively studied in the literature, the early development of the dispersion process is by contrast much less investigated. By early development, that means a span of time, after the release of the chemical into the flow, that is shorter than or comparable to the diffusion time scale across the tube section. To understand the early development of the dispersion, the governing equations along with the reactive boundary conditions are solved numerically using the Flux Corrected Transport Algorithm (FCTA). The computation has enabled us to investigate the combined effects on the early development of the dispersion coefficient due to the reversible and irreversible wall reactions. One of the results is shown that the dispersion coefficient may approach its steady-state limit in a short time under the following conditions: (i) a high value of Damkohler number (say Da ≥ 10); (ii) a small but non-zero value of absorption rate (say Γ* ≤ 0.5).

Keywords: Dispersion coefficient, early development of dispersion, FCTA, wall reactions.

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Authors: Gizelle K. Vianna, Gabriel V. Cunha, Gustavo S. Oliveira

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Foliage diseases in plants can cause a reduction in both quality and quantity of agricultural production. Intelligent detection of plant diseases is an essential research topic as it may help monitoring large fields of crops by automatically detecting the symptoms of foliage diseases. This work investigates ways to recognize the late blight disease from the analysis of tomato digital images, collected directly from the field. A pair of multilayer perceptron neural network analyzes the digital images, using data from both RGB and HSL color models, and classifies each image pixel. One neural network is responsible for the identification of healthy regions of the tomato leaf, while the other identifies the injured regions. The outputs of both networks are combined to generate the final classification of each pixel from the image and the pixel classes are used to repaint the original tomato images by using a color representation that highlights the injuries on the plant. The new images will have only green, red or black pixels, if they came from healthy or injured portions of the leaf, or from the background of the image, respectively. The system presented an accuracy of 97% in detection and estimation of the level of damage on the tomato leaves caused by late blight.

Keywords: Artificial neural networks, digital image processing, pattern recognition.

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Authors: Walaa Khalaf, Calogero Pace, Manlio Gaudioso

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We present an Electronic Nose (ENose), which is aimed at identifying the presence of one out of two gases, possibly detecting the presence of a mixture of the two. Estimation of the concentrations of the components is also performed for a volatile organic compound (VOC) constituted by methanol and acetone, for the ranges 40-400 and 22-220 ppm (parts-per-million), respectively. Our system contains 8 sensors, 5 of them being gas sensors (of the class TGS from FIGARO USA, INC., whose sensing element is a tin dioxide (SnO2) semiconductor), the remaining being a temperature sensor (LM35 from National Semiconductor Corporation), a humidity sensor (HIH–3610 from Honeywell), and a pressure sensor (XFAM from Fujikura Ltd.). Our integrated hardware–software system uses some machine learning principles and least square regression principle to identify at first a new gas sample, or a mixture, and then to estimate the concentrations. In particular we adopt a training model using the Support Vector Machine (SVM) approach with linear kernel to teach the system how discriminate among different gases. Then we apply another training model using the least square regression, to predict the concentrations. The experimental results demonstrate that the proposed multiclassification and regression scheme is effective in the identification of the tested VOCs of methanol and acetone with 96.61% correctness. The concentration prediction is obtained with 0.979 and 0.964 correlation coefficient for the predicted versus real concentrations of methanol and acetone, respectively.

Keywords: Electronic nose, Least square regression, Mixture ofgases, Support Vector Machine.

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Authors: Bahdja Guerfi, N. Hadhoum, I. Azouz, M. Bendoumia, S. Bouafia, F. Z. Hadjadj Aoul

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Background: 'Penicillin V' is a narrow, bactericidal antibiotic of the beta-lactam family of the naturally occurring penicillin group. It is limited to infections due to the germs defined as sensitive. The objective of this work was to identify and to characterize Penicillin V acid and its related compounds by High-performance liquid chromatography (HPLC). Methods: Firstly phenoxymethylpenicillin was identified by an infrared absorption. The organoleptic characteristics, pH, and determination of water content were also studied. The dosage of Penicillin V acid active substance and the determination of its related compounds were carried on waters HPLC, equipped with a UV detector at 254 nm and Discovery HS C18 column (250 mm X 4.6 mm X 5 µm) which is maintained at room temperature. The flow rate was about 1 ml per min. A mixture of water, acetonitrile and acetic acid (65:35:01) was used as mobile phase for phenoxyacetic acid ‘impurity B' and a mixture of water, acetonitrile and acetic acid (650:150:5.75) for the assay and 4-hydroxypenicillin V 'impurity D'. Results: The identification of Penicillin V acid active substance and the evaluation of its chemical quality showed conformity with USP 35th edition. The Penicillin V acid content in the raw material is equal to 1692.22 UI/mg. The percentage content of phenoxyacetic acid and 4-hydroxypenicillin V was respectively: 0.035% and 0.323%. Conclusion: Through these results, we can conclude that the Penicillin V acid active substance tested is of good physicochemical quality.

Keywords: Penicillin V acid, characterization, related substances, HPLC.

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Authors: Sharareh Sharifi, Pargol Ghavam Mostafavi, Ali Mashinchian Moradi, Mohammad Hadi Givianrad, Hassan Niknejad

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Marine organisms such as soft coral, sponge, ascidians, and tunicate containing rich source of natural compound have been studied in last decades because of their special chemical compounds with anticancer properties. The aim of this study was to investigate anti-cancer property of ethyl acetate extracted from marine sea pen Virgularia gustaviana found from Persian Gulf coastal (Bandar Abbas). The extraction processes were carried out with ethyl acetate for five days. Thin layer chromatography (TLC) and high-performance liquid chromatography (HPLC) were used for qualitative identification of crude extract. The viability of HeLa and MDA-Mb-231 cancer cells was investigated using MTT assay at the concentration of 25, 50, and a 100 µl/ml of ethyl acetate is extracted. The crude extract of Virgularia gustaviana demonstrated ten fractions with different Retention factor (Rf) by TLC and Retention time (Rt) evaluated by HPLC. The crude extract dose-dependently decreased cancer cell viability compared to control group. According to the results, the ethyl acetate extracted from Virgularia gustaviana inhibits the growth of cancer cells, an effect which needs to be further investigated in the future studies.

Keywords: Virgularia gustaviana, Cembrane Diterpene, anti-cancer, HeLa cancer Cell, MDA-Md-231 Cancer cell.

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Authors: Fariba Shavakhi Zavareh, Hadi Fotoohabadi, Reza Sedaghati

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Due to the continuous increment of the load demand, identification of weaker buses, improvement of voltage profile and power losses in the context of the voltage stability problems has become one of the major concerns for the larger, complex, interconnected power systems. The objective of this paper is to review the impact of Flexible AC Transmission System (FACTS) controller in Wind generators connected electrical network for maintaining voltage stability. Wind energy could be the growing renewable energy due to several advantages. The influence of wind generators on power quality is a significant issue; non uniform power production causes variations in system voltage and frequency. Therefore, wind farm requires high reactive power compensation; the advances in high power semiconducting devices have led to the development of FACTS. The FACTS devices such as for example SVC inject reactive power into the system which helps in maintaining a better voltage profile. The performance is evaluated on an IEEE 14 bus system, two wind generators are connected at low voltage buses to meet the increased load demand and SVC devices are integrated at the buses with wind generators to keep voltage stability. Power flows, nodal voltage magnitudes and angles of the power network are obtained by iterative solutions using MIPOWER.

Keywords: Voltage Profile, FACTS Device, SVC, Distributed Generation.

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Authors: Arnaud Nougues

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This paper describes a two-stage methodology derived from IMC (Internal Model Control) for tuning a PID (Proportional-Integral-Derivative) controller for levels or other integrating processes in an industrial environment. Focus is ease of use and implementation speed which are critical for an industrial application. Tuning can be done with minimum effort and without the need of time-consuming open-loop step tests on the plant. The first stage of the method applies to levels only: the vessel residence time is calculated from equipment dimensions and used to derive a set of preliminary PI (Proportional-Integral) settings with IMC. The second stage, re-tuning in closed-loop, applies to levels as well as other integrating processes: a tuning correction mechanism has been developed based on a series of closed-loop simulations with model errors. The tuning correction is done from a simple closed-loop step test and application of a generic correlation between observed overshoot and integral time correction. A spin-off of the method is that an estimate of the vessel residence time (levels) or open-loop process gain (other integrating process) is obtained from the closed-loop data.

Keywords: closed-loop model identification, IMC-PID tuning method, integrating process control, on-line PID tuning adaptation

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Authors: M. J. Pourvaghar, M. E. Bahram

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Obesity and overweight is one of the most common metabolic disorders in industrialized countries and in developing countries. One consequence of pathological obesity is cardiovascular disease and metabolic syndrome. Chemerin is an adipocyne that plays a role in the regulation of the adipocyte function and the metabolism of glucose in the liver and musculoskeletal system. Most likely, chemerin is involved in obesity-related disorders such as type 2 diabetes and cardiovascular disease. Aerobic exercises reduce the level of chemerin and cause macrophage penetration into fat cells and inflammatory factors. Several efforts have been made to clarify the cellular and molecular mechanisms of hypertrophy and muscular atrophy. Myostatin, a new member of the TGF-β family, is a transforming growth factor β that its expression negatively regulates the growth of the skeletal muscle; and the increase of this hormone has been observed in conditions of muscular atrophy. While in response to muscle overload, its levels decrease after the atrophy period, TGF-β is the most important cytokine in the development of skeletal muscle. Myostatin plays an important role in muscle control, and animal and human studies show a negative role of myostatin in the growth of skeletal muscle. Separation of myostatin from Golgi begins on the ninth day of the onset period and continues until birth at all times of muscle growth. Higher levels of myostatin are found in obese people. Resistance training for 10 weeks could reduce levels of plasma myostatin.

Keywords: Chemerin, myostatin, obesity, physical activity.

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Authors: Fatma El-zahraa El-taher, Ayman Taha, Jane Courtney, Susan Mckeever

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Understanding road networks plays an important role in navigation applications such as self-driving vehicles and route planning for individual journeys. Intersections of roads are essential components of road networks. Understanding the features of an intersection, from a simple T-junction to larger multi-road junctions is critical to decisions such as crossing roads or selecting safest routes. The identification and profiling of intersections from satellite images is a challenging task. While deep learning approaches offer state-of-the-art in image classification and detection, the availability of training datasets is a bottleneck in this approach. In this paper, a labelled satellite image dataset for the intersection recognition  problem is presented. It consists of 14,692 satellite images of Washington DC, USA. To support other users of the dataset, an automated download and labelling script is provided for dataset replication. The challenges of construction and fine-grained feature labelling of a satellite image dataset are examined, including the issue of how to address features that are spread across multiple images. Finally, the accuracy of detection of intersections in satellite images is evaluated.

Keywords: Satellite images, remote sensing images, data acquisition, autonomous vehicles, robot navigation, route planning, road intersections.

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Authors: Sayyed R Mousavi

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The Far From Most Strings Problem (FFMSP) is to obtain a string which is far from as many as possible of a given set of strings. All the input and the output strings are of the same length, and two strings are said to be far if their hamming distance is greater than or equal to a given positive integer. FFMSP belongs to the class of sequences consensus problems which have applications in molecular biology. The problem is NP-hard; it does not admit a constant-ratio approximation either, unless P = NP. Therefore, in addition to exact and approximate algorithms, (meta)heuristic algorithms have been proposed for the problem in recent years. On the other hand, in the recent years, hybrid algorithms have been proposed and successfully used for many hard problems in a variety of domains. In this paper, a new metaheuristic algorithm, called Constructive Beam and Local Search (CBLS), is investigated for the problem, which is a hybridization of constructive beam search and local search algorithms. More specifically, the proposed algorithm consists of two phases, the first phase is to obtain several candidate solutions via the constructive beam search and the second phase is to apply local search to the candidate solutions obtained by the first phase. The best solution found is returned as the final solution to the problem. The proposed algorithm is also similar to memetic algorithms in the sense that both use local search to further improve individual solutions. The CBLS algorithm is compared with the most recent published algorithm for the problem, GRASP, with significantly positive results; the improvement is by order of magnitudes in most cases.

Keywords: Bioinformatics, Far From Most Strings Problem, Hybrid metaheuristics, Matheuristics, Sequences consensus problems.

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Authors: M. Dezvarei, S. Morovati

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In recent years, increasing usage of electrical energy provides a widespread field for investigating new methods to produce clean electricity with high reliability and cost management. Fuel cells are new clean generations to make electricity and thermal energy together with high performance and no environmental pollution. According to the expansion of fuel cell usage in different industrial networks, the identification and optimization of its parameters is really significant. This paper presents optimization of a proton exchange membrane fuel cell (PEMFC) parameters based on modified particle swarm optimization with real valued mutation (RVM) and clonal algorithms. Mathematical equations of this type of fuel cell are presented as the main model structure in the optimization process. Optimized parameters based on clonal and RVM algorithms are compared with the desired values in the presence and absence of measurement noise. This paper shows that these methods can improve the performance of traditional optimization methods. Simulation results are employed to analyze and compare the performance of these methodologies in order to optimize the proton exchange membrane fuel cell parameters.

Keywords: Clonal algorithm, proton exchange membrane fuel cell, particle swarm optimization, real valued mutation.

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Authors: Andrii Shalaginov, Katrin Franke, Xiongwei Huang

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One of the leading problems in Cyber Security today is the emergence of targeted attacks conducted by adversaries with access to sophisticated tools. These attacks usually steal senior level employee system privileges, in order to gain unauthorized access to confidential knowledge and valuable intellectual property. Malware used for initial compromise of the systems are sophisticated and may target zero-day vulnerabilities. In this work we utilize common behaviour of malware called ”beacon”, which implies that infected hosts communicate to Command and Control servers at regular intervals that have relatively small time variations. By analysing such beacon activity through passive network monitoring, it is possible to detect potential malware infections. So, we focus on time gaps as indicators of possible C2 activity in targeted enterprise networks. We represent DNS log files as a graph, whose vertices are destination domains and edges are timestamps. Then by using four periodicity detection algorithms for each pair of internal-external communications, we check timestamp sequences to identify the beacon activities. Finally, based on the graph structure, we infer the existence of other infected hosts and malicious domains enrolled in the attack activities.

Keywords: Malware detection, network security, targeted attack.

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Authors: Fan Li, Chun-Hsien Chen, Li Pheng Khoo

Abstract:

Operators of vessel traffic service (VTS) center provides three different types of services; namely information service, navigational assistance and traffic organization to vessels. To provide these services, operators monitor vessel traffic through computer interface and provide navigational advice based on the information integrated from multiple sources, including automatic identification system (AIS), radar system, and closed circuit television (CCTV) system. Therefore, this information is crucial in VTS operation. However, what information the VTS operator actually need to efficiently and properly offer services is unclear. The aim of this study is to investigate into information requirements for VTS operation. To achieve this aim, field observation was carried out to elicit the information requirements for VTS operation. The study revealed that the most frequent and important tasks were handling arrival vessel report, potential conflict control and abeam vessel report. Current location and vessel name were used in all tasks. Hazard cargo information was particularly required when operators handle arrival vessel report. The speed, the course, and the distance of two or several vessels were only used in potential conflict control. The information requirements identified in this study can be utilized in designing a human-computer interface that takes into consideration what and when information should be displayed, and might be further used to build the foundation of a decision support system for VTS.

Keywords: Vessel traffic service, information requirements, hierarchy task analysis, field observation.

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Authors: Sarkar M. A. Kawsar, Sarkar M. A. Mamun, Md S. Rahman, Hidetaro Yasumitsu, Yasuhiro Ozeki

Abstract:

The present study has been taken to explore the screening of in vitro antimicrobial activities of D-galactose-binding sponge lectin (HOL-30). HOL-30 was purified from the marine demosponge Halichondria okadai by affinity chromatography. The molecular mass of the lectin was determined to be 30 kDa with a single polypeptide by SDS-PAGE under non-reducing and reducing conditions. HOL-30 agglutinated trypsinized and glutaraldehydefixed rabbit and human erythrocytes with preference for type O erythrocytes. The lectin was subjected to evaluation for inhibition of microbial growth by the disc diffusion method against eleven human pathogenic gram-positive and gram-negative bacteria. The lectin exhibited strong antibacterial activity against gram-positive bacteria, such as Bacillus megaterium and Bacillus subtilis. However, it did not affect against gram-negative bacteria such as Salmonella typhi and Escherichia coli. The largest zone of inhibition was recorded of Bacillus megaterium (12 in diameter) and Bacillus subtilis (10 mm in diameter) at a concentration of the lectin (250 μg/disc). On the other hand, the antifungal activity of the lectin was investigated against six phytopathogenic fungi based on food poisoning technique. The lectin has shown maximum inhibition (22.83%) of mycelial growth of Botrydiplodia theobromae at a concentration of 100 μg/mL media. These findings indicate that the lectin may be of importance to clinical microbiology and have therapeutic applications.

Keywords: Antibacterial, Halichondria okadai, Inhibition zone, Lectin.

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Authors: Valentina Di Maria, Anton Ianakiev

Abstract:

The use OF adhesive anchors for wooden constructions is an efficient technology to connect and design timber members in new timber structures and to rehabilitate the damaged structural members of historical buildings. Due to the lack of standard regulation in this specific area of structural design, designers’ choices are still supported by test analysis that enables knowledge, and the prediction, of the structural behaviour of glued in rod joints. The paper outlines an experimental research activity aimed at identifying the tensile resistance capacity of several new adhesive joint prototypes made of epoxy resin, steel bar and timber, Oak and Douglas Fir species. The development of new adhesive connectors has been carried out by using epoxy to glue stainless steel bars into pre-drilled holes, characterised by smooth and rough internal surfaces, in timber samples. The realization of a threaded contact surface using a specific drill bit has led to an improved bond between wood and epoxy. The applied changes have also reduced the cost of the joints’ production. The paper presents the results of this parametric analysis and a Finite Element analysis that enables identification and study of the internal stress distribution in the proposed adhesive anchors.

Keywords: Glued in rod joints, adhesive anchors, timber, epoxy, rough contact surface, threaded hole shape.

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Authors: Balgaisha G. Mukanova, Yelbek B. Utepov, Aida G. Nazarova, Alisher Z. Imanov

Abstract:

The problem of identifying local noise sources on a construction site using a sensor system is considered. Mathematical modeling of detected signals on sensors was carried out, considering signal decay and signal delay time between the source and detector. Recordings of noises produced by construction tools were used as a dependence of noise on time. Synthetic sensor data was constructed based on these data, and a model of the propagation of acoustic waves from a point source in the three-dimensional space was applied. All sensors and sources are assumed to be located in the same plane. A source localization method is checked based on the signal time delay between two adjacent detectors and plotting the direction of the source. Based on the two direct lines' crossline, the noise source's position is determined. Cases of one dominant source and the case of two sources in the presence of several other sources of lower intensity are considered. The number of detectors varies from three to eight detectors. The intensity of the noise field in the assessed area is plotted. The signal of a two-second duration is considered. The source is located for subsequent parts of the signal with a duration above 0.04 sec; the final result is obtained by computing the average value.

Keywords: Acoustic model, direction of arrival, inverse source problem, sound localization, urban noises.

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Authors: Aisha Othman, Crinela Pislaru, Ahmed Impes

Abstract:

This paper provides an identification of the existing practical skills gap between school-based learning (SBL) and laboratory based learning (LBL) in the Computing Department within the Faculty of Science at Omar Al-Mukhtar University in Libya. A survey has been conducted and the first author has elicited the responses of two groups of stakeholders, namely the academic teachers and students.

The primary goal is to review the main strands of evidence available and argue that there is a gap between laboratory and school-based learning in terms of opportunities for experiment and application of skills. In addition, the nature of experimental work within the laboratory at Omar Al-Mukhtar University needs to be reconsidered. Another goal of our study was to identify the reasons for students’ poor performance in the laboratory and to determine how this poor performance can be eliminated by the modification of teaching methods. Bloom’s taxonomy of learning outcomes has been applied in order to classify questions and problems into categories, and the survey was formulated with reference to third year Computing Department students. Furthermore, to discover students’ opinions with respect to all the issues, an exercise was conducted. The survey provided questions related to what the students had learnt and how well they had learnt. We were also interested in feedback on how to improve the course and the final question provided an opportunity for such feedback.

Keywords: Bloom’s taxonomy, e-learning, Omar Al-Mukhtar University.

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Authors: Hafizah Che Hasan, Fateen Nazwa Yusof, Maslina Daud

Abstract:

Internet of Things (IoT) is a powerful industry system, which end-devices are interconnected and automated, allowing the devices to analyze data and execute actions based on the analysis. The IoT technology leverages the technology of Radio-Frequency Identification (RFID) and Wireless Sensor Network (WSN), including mobile and sensor. These technologies contribute to the evolution of IoT. However, due to more devices are connected each other in the Internet, and data from various sources exchanged between things, confidentiality of the data becomes a major concern. This paper focuses on one of the major challenges in IoT; authentication, in order to preserve data integrity and confidentiality are in place. A few solutions are reviewed based on papers from the last few years. One of the proposed solutions is securing the communication between IoT devices and cloud servers with Elliptic Curve Cryptograhpy (ECC) based mutual authentication protocol. This solution focuses on Hyper Text Transfer Protocol (HTTP) cookies as security parameter.  Next proposed solution is using keyed-hash scheme protocol to enable IoT devices to authenticate each other without the presence of a central control server. Another proposed solution uses Physical Unclonable Function (PUF) based mutual authentication protocol. It emphasizes on tamper resistant and resource-efficient technology, which equals a 3-way handshake security protocol.

Keywords: Internet of Things, authentication, PUF ECC, keyed hash scheme protocol.

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