Search results for: Performance Assessment.

Authors: Wai Yee Lin, Masahiro Yamao

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Food control measures are critical in fostering food safety management of a nation. However, no academic study has been undertaken to assess the food control system of Myanmar up to now. The objective of this research paper was to assess the food control system with in depth examination of five key components using desktop analysis and short survey from related food safety program organizations including regulators and inspectors. Study showed that the existing food control system is conventional, mainly focusing on primary health care approach while relying on reactive measures. The achievements of food control work have been limited to a certain extent due to insufficienttechnical capacity that is needed to upgrade staffs, laboratory equipment and technical assistance etc. associated with various sectors. Assessing food control measures is the first step in the integration of food safety management, this paper could assist policy makers in providing information for enhancing the safety and quality of food produced and consumed in Myanmar.

Keywords: Food Control, Food Policy, Legislation, Management

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Authors: C. R. Danielle, S. Erik, T. Patrick, M. Hugh

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In the last decade there has been an increase in demand for fine grinding due to the depletion of coarse-grained orebodies and an increase of processing fine disseminated minerals and complex orebodies. These ores have provided new challenges in concentrator design because fine and ultra-fine grinding is required to achieve acceptable recovery rates. Therefore, the correct design of a grinding circuit is important for minimizing unit costs and increasing product quality. The use of ball mills for grinding in fine size ranges is inefficient and, therefore, vertical stirred grinding mills are becoming increasingly popular in the mineral processing industry due to its already known high energy efficiency. This work presents a hypothesis of a methodology to predict the product size distribution of a vertical stirred mill using a Bond ball mill. The Population Balance Model (PBM) was used to empirically analyze the performance of a vertical mill and a Bond ball mill. The breakage parameters obtained for both grinding mills are compared to determine the possibility of predicting the product size distribution of a vertical mill based on the results obtained from the Bond ball mill. The biggest advantage of this methodology is that most of the minerals processing laboratories already have a Bond ball mill to perform the tests suggested in this study. Preliminary results show the possibility of predicting the performance of a laboratory vertical stirred mill using a Bond ball mill.

Keywords: Bond ball mill, population balance model, product size distribution, vertical stirred mill.

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Authors: F. I. Belheouane, M. Bensaibi

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The seismic feedback experiences in Algeria have shown higher percentage of damages for non-code conforming reinforced concrete (RC) buildings. Furthermore, the vulnerability of these buildings was further aggravated due to presence of many factors (e.g. weak the seismic capacity of these buildings, shorts columns, Pounding effect, etc.). Consequently Seismic risk assessments were carried out on populations of buildings to identify the buildings most likely to undergo losses during an earthquake. The results of such studies are important in the mitigation of losses under future seismic events as they allow strengthening intervention and disaster management plans to be drawn up. Within this paper, the state of the existing structures is assessed using "the vulnerability index" method. This method allows the classification of RC constructions taking into account both, structural and non structural parameters, considered to be ones of the main parameters governing the vulnerability of the structure. Based on seismic feedback from past earthquakes DPM (damage probability matrices) were developed too.

Keywords: Seismic vulnerability, Reinforced concrete buildings, Earthquake, DPM, Algeria.

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Authors: Susmita Sahoo, Madhumanti Datta, Rajib Kar

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Fast delay estimation methods, as opposed to simulation techniques, are needed for incremental performance driven layout synthesis. On-chip inductive effects are becoming predominant in deep submicron interconnects due to increasing clock speed and circuit complexity. Inductance causes noise in signal waveforms, which can adversely affect the performance of the circuit and signal integrity. Several approaches have been put forward which consider the inductance for on-chip interconnect modelling. But for even much higher frequency, of the order of few GHz, the shunt dielectric lossy component has become comparable to that of other electrical parameters for high speed VLSI design. In order to cope up with this effect, on-chip interconnect has to be modelled as distributed RLCG line. Elmore delay based methods, although efficient, cannot accurately estimate the delay for RLCG interconnect line. In this paper, an accurate analytical delay model has been derived, based on first and second moments of RLCG interconnection lines. The proposed model considers both the effect of inductance and conductance matrices. We have performed the simulation in 0.18μm technology node and an error of as low as less as 5% has been achieved with the proposed model when compared to SPICE. The importance of the conductance matrices in interconnect modelling has also been discussed and it is shown that if G is neglected for interconnect line modelling, then it will result an delay error of as high as 6% when compared to SPICE.

Keywords: Delay Modelling; On-Chip Interconnect; RLCGInterconnect; Ramp Input; Damping; VLSI

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Authors: Nyeng P. Gyang

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Even though past, current and future trends suggest that multicore and cloud computing systems are increasingly prevalent/ubiquitous, this class of parallel systems is nonetheless underutilized, in general, and barely used for research on employing parallel Delaunay triangulation for parallel surface modeling and generation, in particular. The performances, of actual/physical and virtual/cloud multicore systems/machines, at executing various algorithms, which implement various parallelization strategies of the incremental insertion technique of the Delaunay triangulation algorithm, were evaluated. T-tests were run on the data collected, in order to determine whether various performance metrics differences (including execution time, speedup and efficiency) were statistically significant. Results show that the actual machine is approximately twice faster than the virtual machine at executing the same programs for the various parallelization strategies. Results, which furnish the scalability behaviors of the various parallelization strategies, also show that some of the differences between the performances of these systems, during different runs of the algorithms on the systems, were statistically significant. A few pseudo superlinear speedup results, which were computed from the raw data collected, are not true superlinear speedup values. These pseudo superlinear speedup values, which arise as a result of one way of computing speedups, disappear and give way to asymmetric speedups, which are the accurate kind of speedups that occur in the experiments performed.

Keywords: Cloud computing systems, multicore systems, parallel delaunay triangulation, parallel surface modeling and generation.

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Authors: Tonislav Ivanov, Oleksii Nedashkivskyi, Denis Babeshko, Vadim Pinskiy, Matthew Putman

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Training a machine learning model for object detection that generalizes well is known to benefit from a training dataset with diverse examples. However, training datasets usually contain many repeats of common examples of a class and lack rarely seen examples. This is due to the process commonly used during human annotation where a person would proceed sequentially through a list of images labeling a sufficiently high total number of examples. Instead, the method presented involves an active process where, after the initial labeling of several images is completed, the next subset of images for labeling is selected by an algorithm. This process of algorithmic image selection and manual labeling continues in an iterative fashion. The algorithm used for the image selection is a deep learning algorithm, based on the U-shaped architecture, which quantifies the presence of unseen data in each image in order to find images that contain the most novel examples. Moreover, the location of the unseen data in each image is highlighted, aiding the labeler in spotting these examples. Experiments performed using semiconductor wafer data show that labeling a subset of the data, curated by this algorithm, resulted in a model with a better performance than a model produced from sequentially labeling the same amount of data. Also, similar performance is achieved compared to a model trained on exhaustive labeling of the whole dataset. Overall, the proposed approach results in a dataset that has a diverse set of examples per class as well as more balanced classes, which proves beneficial when training a deep learning model.

Keywords: Computer vision, deep learning, object detection, semiconductor.

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Authors: Qasem A. Al-Radaideh, Emad Abu-Shanab, Shaima Hamam, Hani Abu-Salem

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Online news websites are one of the main and wide areas of Mass Media. Since the nineties several Jordanian newspapers were introduced to the World Wide Web to reach various and large numbers of audiances. Examples of these newspapers that have online version are Al-Rai, Ad-Dustor and AlGhad. Other pure online news websites include Ammon and Rum. The main aim of this study is to evaluate online newspaper websites using two assessment measures; usability and web content. This aim is achieved by using a questionnaire based evaluation which is based on the definition of usability and web content in the ISO document as the standard number 9241-part 11. The results are obtained based on 204 audiences- responses. The results of the research showed that the usability factor is relatively good for all Jordanian online newspapers whereas the web content factor is moderate.

Keywords: Communication and mass media, Jordanian online news websites, website content, website usability.

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Authors: Nazira Kakulia, Tsotne Zhghenti

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The institutional development is one of the actual topics in economics science. New trends and directions of institutional development mostly depend on its structure and framework. Transformation of institutions is an important problem for every economy, especially for developing countries. The first research goal is to determine the importance and interactions between different institutions in Georgia. Using World Governance Indicators and Economic Freedom indexes it can be calculated the size for each institutional group. The second aim of this research is to evaluate Georgian institutional backwardness in comparison to other post-communist economies. We use statistical and econometric methods to evaluate the difference between the levels of institutional development in Georgia and in leading post-communist economies. Within the scope of this research, major findings are coefficients which are an assessment of their deviation (i.e. lag) of institutional indicators between Georgia and leading post-communist country which should be compared. The last part of the article includes analysis around the selected coefficients.

Keywords: Post-communist transition, institutions, economic growth, institutional development.

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Authors: M. T. Becerra, F. Martín, P. Gutiérrez, S. Cubo, E. Iglesias, A. A. Sáenz del Castillo, P. Cañamero

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The consolidation of the European Higher Education Area (EHEA) in universities has led to significant changes in student training. This paper, part of a Teaching Innovation Project, starts from new training requirements that are fit within Undergraduate Thesis Project, a subject that culminate student learning. Undergraduate Thesis Project is current assessment system that weigh the student acquired training in university education. Students should develop a range of cross curricular competences such as public presentation of ideas, problems and solutions both orally and writing in Undergraduate Thesis Project. Specifically, we intend with our innovation proposal to provide resources that enable university students from Teacher Degree in Education Faculty of University of Extremadura (Spain) to develop the cross curricular competence of public speaking.

Keywords: Interaction, Public Speaking, Student, University.

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Authors: M. Yosofi, S. Ezeddini, A. Ollivier, V. Lavaste, C. Mayousse

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Additive manufacturing processes have changed significantly in a wide range of industries and their application progressed from rapid prototyping to production of end-use products. However, their environmental impact is still a rather open question. In order to support the growth of this technology in the industrial sector, environmental aspects should be considered and predictive models may help monitor and reduce the environmental footprint of the processes. This work presents predictive models based on a previously developed methodology for the environmental impact evaluation combined with a technical and economical assessment. Here we applied the methodology to the Fused Deposition Modeling process. First, we present the predictive models relative to different types of machines. Then, we present a decision-making tool designed to identify the optimum manufacturing strategy regarding technical, economic, and environmental criteria.

Keywords: Additive manufacturing, decision-makings, environmental impact, predictive models.

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Authors: A.C. Duarte, C.I.L. Justino, K. Duarte, A.C. Freitas, R. Pereira, P. Chaves, P. Bettencourt, S. Cardoso, T.A.P. Rocha-Santos

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This paper aims at overviewing the topics of a research project (CARDIOSENSOR) on the field of health sciences (biomaterials and biomedical engineering). The project has focused on the development of a nanosensor for the assessment of the risk of cardiovascular diseases by the monitoring of C-reactive protein (CRP), which has been currently considered as the best validated inflammatory biomarker associated to cardiovascular diseases. The project involves tasks such as: 1) the development of sensor devices based on field effect transistors (FET): assembly, optimization and validation; 2) application of sensors to the detection of CRP in standard solutions and comparison with enzyme-linked immunosorbent assay (ELISA); and 3) application of sensors to real samples such as blood and saliva and evaluation of their ability to predict the risk of cardiovascular disease.

Keywords: Carbon nanotubes field effect transistors, cardiovascular diseases, C-reactive protein, sensor.

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Authors: Yanping Liao, Zenan Wu, Ruigang Zhao

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Frequency diverse array (FDA) beamforming is a technology developed in recent years, and its antenna pattern has a unique angle-distance-dependent characteristic. However, the beam is always required to have strong concentration, high resolution and low sidelobe level to form the point-to-point interference in the concentrated set. In order to eliminate the angle-distance coupling of the traditional FDA and to make the beam energy more concentrated, this paper adopts a multi-carrier FDA structure based on proposed power exponential frequency offset to improve the array structure and frequency offset of the traditional FDA. The simulation results show that the beam pattern of the array can form a dot-shape beam with more concentrated energy, and its resolution and sidelobe level performance are improved. However, the covariance matrix of the signal in the traditional adaptive beamforming algorithm is estimated by the finite-time snapshot data. When the number of snapshots is limited, the algorithm has an underestimation problem, which leads to the estimation error of the covariance matrix to cause beam distortion, so that the output pattern cannot form a dot-shape beam. And it also has main lobe deviation and high sidelobe level problems in the case of limited snapshot. Aiming at these problems, an adaptive beamforming technique based on exponential correction for multi-carrier FDA is proposed to improve beamforming robustness. The steps are as follows: first, the beamforming of the multi-carrier FDA is formed under linear constrained minimum variance (LCMV) criteria. Then the eigenvalue decomposition of the covariance matrix is ​​performed to obtain the diagonal matrix composed of the interference subspace, the noise subspace and the corresponding eigenvalues. Finally, the correction index is introduced to exponentially correct the small eigenvalues ​​of the noise subspace, improve the divergence of small eigenvalues ​​in the noise subspace, and improve the performance of beamforming. The theoretical analysis and simulation results show that the proposed algorithm can make the multi-carrier FDA form a dot-shape beam at limited snapshots, reduce the sidelobe level, improve the robustness of beamforming, and have better performance.

Keywords: Multi-carrier frequency diverse array, adaptive beamforming, correction index, limited snapshot, robust.

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Authors: P. Mekpruksawong, S. Chuenchooklin, T. Ichikawa

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The aim of research project is to evaluate quantity and quality for conjunctive use of groundwater and surface water in lower in the Lower Nam Kam area, Thailand, even though there have been hints of saline soil and water. The mathematical model named WUSMO and MIKE Basin were applied for the calculation of crop water utilization. Results of the study showed that, in irrigation command area, water consumption rely on various sources; rain water 21.56%, irrigation water 78.29%, groundwater and some small surface storage 0.15%. Meanwhile, for non-irrigation command area, water consumption depends on the Nam Kam and Nambang stream 42%, rain water 36.75% and groundwater and some small surface storage 19.18%. Samples of surface water and groundwater were collected for 2 seasons. The criterion was determined for the assessment of suitable water for irrigation. It was found that this area has very limited sources of suitable water for irrigation.

Keywords: Conjunctive use, Groundwater, Surface water, Saline soil.

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Authors: Miled Amel, Ben Maad Hatem, Askri Faouzi, Ben Nasrallah Sassi

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Metal hydride water pumping system uses hydrogen as working fluid to pump water for low head and high discharge. The principal operation of this pump is based on the desorption of hydrogen at high pressure and its absorption at low pressure by a metal hydride. This work is devoted to study a concept of the dynamic behavior of a metal hydride pump using unsteady model and LaNi5 as hydriding alloy. This study shows that with MHP, it is possible to pump 340l/kg-cycle of water in 15 000s using 1 Kg of LaNi5 at a desorption temperature of 360 K, a pumping head equal to 5 m and a desorption gear ratio equal to 33. This study reveals also that the error given by the steady model, using LaNi5 is about 2%.A dimensional mathematical model and the governing equations of the pump were presented to predict the coupled heat and mass transfer within the MHP. Then, a numerical simulation is carried out to present the time evolution of the specific water discharge and to test the effect of different parameters (desorption temperature, absorption temperature, desorption gear ratio) on the performance of the water pumping system (specific water discharge, pumping efficiency and pumping time). In addition, a comparison between results obtained with steady and unsteady model is performed with different hydride mass. Finally, a geometric configuration of the reactor is simulated to optimize the pumping time.

Keywords: Dynamic behavior, unsteady model, LaNi5, performance of the water pumping system.

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Authors: Tim D. Sass

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The experience of engineers and architects practicing today is typically limited to current building code requirements and modern construction methods and materials. However, many cities have a mix of new and old buildings with many buildings constructed over one hundred years ago when building codes and construction methods were much different. When a brick building sustains damage, a structural engineer is often hired to determine the cause of damage as well as determine the necessary repairs. Forensic studies of dozens of brick buildings shows an appreciation of historical building methods and materials is needed to correctly identify the cause of damage and design an appropriate repair. Damage on an older, brick building can be mistakenly attributed to storms or seismic events when the real source of the damage is deficient original construction. Assessing and remediating damaged brickwork on older brick buildings requires an understanding of the original construction, an understanding of older repair methods, and, an understanding of current building code requirements.

Keywords: Brick, damage, deterioration, facade.

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Authors: Dileep Kumar Gupta, Rajendra Prasad, Pradeep Kumar, Varun Narayan Mishra, Ajeet Kumar Vishwakarma, Prashant Kumar Srivastava

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An approach was evaluated for the retrieval of soil moisture of bare soil surface using bistatic scatterometer data in the angular range of 200 to 700 at VV- and HH- polarization. The microwave data was acquired by specially designed X-band (10 GHz) bistatic scatterometer. The linear regression analysis was done between scattering coefficients and soil moisture content to select the suitable incidence angle for retrieval of soil moisture content. The 250 incidence angle was found more suitable. The support vector regression analysis was used to approximate the function described by the input output relationship between the scattering coefficient and corresponding measured values of the soil moisture content. The performance of support vector regression algorithm was evaluated by comparing the observed and the estimated soil moisture content by statistical performance indices %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE). The values of %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were found 2.9451, 1.0986 and 0.9214 respectively at HHpolarization. At VV- polarization, the values of %Bias, root mean squared error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were found 3.6186, 0.9373 and 0.9428 respectively.

Keywords: Bistatic scatterometer, soil moisture, support vector regression, RMSE, %Bias, NSE.

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Authors: V. Viliene, A. Raceviciute-Stupeliene, V. Sasyte, V. Slausgalvis, R. Gruzauskas, J. Al-Saifi

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Animal nutritionists and scientists have searched for alternative measures to improve the production. One of such alternative is use of organic acids as feed additive in animal nutrition. The study was conducted to investigate the impact of butyric acids, calcium formate, organic acids, and its salts (BCOS) additives on rabbit’s productive performance, carcass traits and meat quality. The study was conducted with 14 Californian breed rabbits. The rabbits were assigned to two treatment groups (seven rabbits per each treatment group). The dietary treatments were 1) control diet, 2) diet supplemented with a mixture BCOS - 2 kg/t of feed. Growth performance characteristics (body weight, daily weight gain, daily feed intake, feed conversion ratio, mortality) were evaluated. Rabbits were slaughtered; carcass characteristics and meat quality were evaluated. Samples loin and hind leg meat were analysed to determine carcass characteristics, pH and colour measurements, cholesterol, and malonyldialdehyde (MDA) content in loin and hind leg meat. Differences between treatments were significant for body weight (1.30 vs. 1.36 kg; P<0.05), daily weight gain (16.60 vs. 17.85 g; P<0.05), and daily feed intake (78.25 vs. 80.58 g; P<0.05) for control and experimental group respectively for the entire experimental period (from 28–77 days old). No significant differences were found in feed conversion ratio and mortality. The feed additives insertion in the diets did not significantly influence the carcass yield or the proportions of the various carcass parts and organs. Differences between treatments were significant for pH value after 48h in loin (5.86 vs. 5.74; P<0.05), hind leg meat (6.62 vs. 6.65; P<0.05), more intense colour b* of loin (5.57 vs. 6.06; P<0.05), less intense colour a* (14.99 vs. 13.15; P<0.05) in hind leg meat. Cholesterol content in hind leg meat decreased by 17.67 mg/100g compared to control group (P<0.05). After storage for three months, MDA concentration decreased in loin and hind leg meat by 0.3 μmol/kg and 0.26 μmol/kg respectively compared to that of the control group (P<0.05). The results of this study suggest that BCOS could potentially be used in rabbit nutrition with consequent benefits on the rabbits’ productivity and nutritional quality of rabbit meat for consumers.

Keywords: Butyric acids, calcium formate, meat quality, organic acids salts, rabbits, productivity.

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Authors: S. Pirrello

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Sydney’s booming real estate market has pushed property developers to invest in historically “no-go” areas, which were previously too expensive to develop. These areas are usually near rivers where the sites are underlain by deep alluvial and estuarine sediments. In these ground conditions, conventional bored pile techniques are often not competitive. Contiguous Flight Auger (CFA) and Drilled Displacement (DD) Piles techniques are on the other hand suitable for these ground conditions. This paper deals with the design and construction challenges encountered with these piling techniques for a series of high-rise towers in Sydney’s West. The advantages of DD over CFA piles such as reduced overall spoil with substantial cost savings and achievable rock sockets in medium strength bedrock are discussed. Design performances were assessed with PIGLET. Pile performances are validated in two stages, during constructions with the interpretation of real-time data from the piling rigs’ on-board computer data, and after construction with analyses of results from high strain pile dynamic testing (PDA). Results are then presented and discussed. High Strain testing data are presented as Case Pile Wave Analysis Program (CAPWAP) analyses.

Keywords: Contiguous flight auger, case pile wave analysis, high strain pile, drilled displacement, pile performance.

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Authors: A. A. K. Abou-Arab, M. A. Abou Donia, A. K. Enab

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Lead is among the heavy metals and it is one of the highly toxic metals, recognized in most countries. This metal accumulates in animal organs as liver and kidney. The present investigation provides the concentrations of lead in cow's meat and different animal organs collected from three Egyptian environments. The results revealed that lead levels in muscle, liver, kidney, spleen and heart in industrial areas were higher than those detected in the same organs of other two areas (heavy traffic and rural), which recorded mean values of 3.0091, 1.7070, 1.8609, 0.6401 and 0.5332 mg/kg, respectively, followed by traffic areas, 2.9166, 1.4443, 1.6967, 0.4042 and 0.4103 mg/kg, respectively. The corresponding values of rural areas were 1.8895, 0.9550, 0.9117, 0.3215 and 0.2856 mg/kg, in the same order. It could be recommended that monitoring and evaluation of lead levels in meat at regular intervals are very important.

Keywords: Heavy metals, lead, meats, organs, liver, kidney, spleen, heart, environments.

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Authors: Farhad Asadi, S. Hossein Sadati

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Bayesian approach can be used for parameter identification and extraction in state space models and its ability for analyzing sequence of data in dynamical system is proved in different literatures. In this paper, adaptive Kalman filter with Bayesian approach for identification of variances in measurement parameter noise is developed. Next, it is applied for estimation of the dynamical state and measurement data in discrete linear dynamical system. This algorithm at each step time estimates noise variance in measurement noise and state of system with Kalman filter. Next, approximation is designed at each step separately and consequently sufficient statistics of the state and noise variances are computed with a fixed-point iteration of an adaptive Kalman filter. Different simulations are applied for showing the influence of noise variance in measurement data on algorithm. Firstly, the effect of noise variance and its distribution on detection and identification performance is simulated in Kalman filter without Bayesian formulation. Then, simulation is applied to adaptive Kalman filter with the ability of noise variance tracking in measurement data. In these simulations, the influence of noise distribution of measurement data in each step is estimated, and true variance of data is obtained by algorithm and is compared in different scenarios. Afterwards, one typical modeling of nonlinear state space model with inducing noise measurement is simulated by this approach. Finally, the performance and the important limitations of this algorithm in these simulations are explained. 

Keywords: adaptive filtering, Bayesian approach Kalman filtering approach, variance tracking

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Authors: M. Sankari, C. Meena

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Enhancing the quality of two dimensional signals is one of the most important factors in the fields of video surveillance and computer vision. Usually in real-life video surveillance, false detection occurs due to the presence of random noise, illumination and shadow artifacts. The detection methods based on background subtraction faces several problems in accurately detecting objects in realistic environments: In this paper, we propose a noise removal algorithm using neighborhood comparison method with thresholding. The illumination variations correction is done in the detected foreground objects by using an amalgamation of techniques like homomorphic decomposition, curvelet transformation and gamma adjustment operator. Shadow is removed using chromaticity estimator with local relation estimator. Results are compared with the existing methods and prove as high robustness in the video surveillance.

Keywords: Chromaticity Estimator, Curvelet Transformation, Denoising, Gamma correction, Homomorphic, Neighborhood Assessment.

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Authors: Armando Calabrese, Roberta Costa, Tamara Menichini, Francesco Rosati

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A company CSR commitment, as stated in its Social Report is, actually, perceived by its stakeholders?And in what measure? Moreover, are stakeholders satisfied with the company CSR efforts? Indeed, business returns from Corporate Social Responsibility (CSR) practices, such as company reputation and customer loyalty, depend heavily on how stakeholders perceive the company social conduct. In this paper, we propose a methodology to assess a company CSR commitment based on Global Reporting Initiative (GRI) indicators, Content Analysis and a CSR positioning matrix. We evaluate three aspects of CSR: the company commitment disclosed through its Social Report; the company commitment perceived by its stakeholders; the CSR commitment that stakeholders require to the company. The positioning of the company under study in the CSR matrix is based on the comparison among the three commitment aspects (disclosed, perceived, required) and it allows assessment and development of CSR strategies.

Keywords: Corporate Social Responsibility (CSR), CSR Positioning Matrix, Global Reporting Initiative (GRI), Stakeholder Orientation

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Authors: Stella Ouma, M. E. Herselman

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The Application of e-health solutions has brought superb advancements in the health care industry. E-health solutions have already been embraced in the industrialized countries. In an effort to catch up with the growth, the developing countries have strived to revolutionize the healthcare industry by use of Information technology in different ways. Based on a technology assessment carried out in Kenya – one of the developing countries – and using multiple case studies in Nyanza Province, this work focuses on an investigation on how five rural hospitals are adapting to the technology shift. The issues examined include the ICT infrastructure and e-health technologies in place, the knowledge of participants in terms of benefits gained through the use of ICT and the challenges posing barriers to the use of ICT technologies in these hospitals. The results reveal that the ICT infrastructure in place is inadequate for e-health implementations as a result to various challenges that exist. Consequently, suggestions on how to tackle the various challenges have been addressed in this paper.

Keywords: Challenges, e-health, healthcare, information communication technology, rural areas.

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Authors: R. Mehra

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The measurements of 226Ra, 232Th and 40K using gamma spectrometry and radon concentration and exhalation rates measurements using solid state nuclear track (LR-115, Type-II plastic) detectors are used to asses a first order exposure risk for the persons residing in Fatehbad and Hissar districts of Western Haryana, India. The concentration of Radium, Thorium and Potassium in the soil samples varies from 13.37 Bq m-3 to 24.67 Bq m-3, 34.67 Bq m-3 to 67.34 Bq m-3 and 298.78 Bq m-3 to 405.67 Bq m-3 respectively with average values of 18.78, 47.35 and 361.57 Bq m-3 respectively. The radium equivalent activity (Raeq) calculated for the same soil samples varies from 92.72 Bq m-3 to 140.6 Bq m-3 with an average value of 111.80 Bq m-3. The values of absorbed dose and annual effective dose (indoors and outdoors) are found to vary from 44.18 nGy h-1 to 65.23 nGy h-1, 0.22 mSv y-1 to 0.32 mSv y-1 and 0.05 mSv y-1 to 0.08 mSv y-1 respectively. The radon concentration and exhalation rates have also been reported. The radium equivalent activities in all the soil samples were found to be lower than the limit (370 Bq kg-1) set in the Organization for Economic Cooperation and Development (OECD) report and the value of Hex in all the samples is less than unity.

Keywords: Gamma ray spectrometry, dose, radon, exhalationrate.

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Authors: Xuan Li, Weian Huang, Jinsheng Sun, Fuhao Zhao, Zhiyuan Wang, Jintang Wang

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Natural gas hydrates (NGHs) as promising alternative energy sources have gained increasing attention. Hydrate-bearing formation in marine areas is highly unconsolidated formation and is fragile, which is composed of weakly cemented sand-clay and silty sediments. During the drilling process, the invasion of drilling fluid can easily lead to excessive water content in the formation. It will change the soil liquid plastic limit index, which significantly affects the formation quality, leading to wellbore instability due to the metastable character of hydrate-bearing sediments. Therefore, controlling the filtrate loss into the formation in the drilling process has to be highly regarded for protecting the stability of the wellbore. In this study, the temperature-sensitive nanogel of P(NIPAM-co-AMPS-co-tBA) was prepared by soap-free emulsion polymerization, and the temperature-sensitive behavior was employed to achieve self-adaptive plugging in hydrate sediments. First, the effects of additional amounts of 2-acrylamido-2-methyl-1-propanesulfonic acid (AMPS), tert-butyl acrylate (tBA), and methylene-bis-acrylamide (MBA) on the microgel synthesis process and temperature-sensitive behaviors were investigated. Results showed that, as a reactive emulsifier, AMPS can not only participate in the polymerization reaction but also act as an emulsifier to stabilize micelles and enhance the stability of nanoparticles. The volume phase transition temperature (VPTT) of nanogels gradually decreased with the increase of the contents of hydrophobic monomer tBA. An increase in the content of the cross-linking agent MBA can lead to a rise in the coagulum content and instability of the emulsion. The plugging performance of nanogel was evaluated in a core sample with a pore size distribution range of 100-1000 nm. The temperature-sensitive nanogel can effectively improve the microfiltration performance of drilling fluid. Since a combination of a series of nanogels could have a wide particle size distribution at any temperature, around 200 nm to 800 nm, the self-adaptive plugging capacity of nanogels for the hydrate sediments was revealed. Thermosensitive nanogel is a potential intelligent plugging material for drilling operations in NGH-bearing sediments.

Keywords: Temperature-sensitive nanogel, NIPAM, self-adaptive plugging performance, drilling operations, hydrate-bearing sediments.

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Authors: M.A. Calin, D. Voicu, M.R. Calin, D. Savastru, D. Manea

Abstract:

In this paper we evaluated the efficacy of photodynamic treatment of infected wounds on pig animal model by diffuse reflectance spectrometry. The study was conducted on fifteen wounds contaminated with Staphylococcus aureus bacteria that were incubated for 30 min with methylene blue solution (c = 3.3 x 10-3 M) and exposed to laser radiations (λ = 670 nm, P = 15 mW) for 15 min. The efficiency of photodynamic inactivation of bacteria was evaluated by microbiological exams and diffuse reflectance spectrometry. The results of the microbiological exams showed that the bacterial concentration has decreased from 6.93±0.138 logCFU/ml to 3.12±0.108 logCFU/ml. The spectral examination showed that the diffuse reflectance of wounds contaminated with Staphylococcus aureus has decreased from 5.06±0.036 % to 3.36±0.025 %. In conclusion, photodynamic therapy is an effective method for the treatment of infected wounds and there is a correlation between the CFU count and diffuse reflectance.

Keywords: photodynamic inactivation, bacteria, pigs, wounds

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Authors: Fadi Eleiwi, Taous Meriem Laleg-Kirati

Abstract:

This paper presents a complete dynamic modeling of a membrane distillation process. The model contains two consistent dynamic models. A 2D advection-diffusion equation for modeling the whole process and a modified heat equation for modeling the membrane itself. The complete model describes the temperature diffusion phenomenon across the feed, membrane, permeate containers and boundary layers of the membrane. It gives an online and complete temperature profile for each point in the domain. It explains heat conduction and convection mechanisms that take place inside the process in terms of mathematical parameters, and justify process behavior during transient and steady state phases. The process is monitored for any sudden change in the performance at any instance of time. In addition, it assists maintaining production rates as desired, and gives recommendations during membrane fabrication stages. System performance and parameters can be optimized and controlled using this complete dynamic model. Evolution of membrane boundary temperature with time, vapor mass transfer along the process, and temperature difference between membrane boundary layers are depicted and included. Simulations were performed over the complete model with real membrane specifications. The plots show consistency between 2D advection-diffusion model and the expected behavior of the systems as well as literature. Evolution of heat inside the membrane starting from transient response till reaching steady state response for fixed and varying times is illustrated.

Keywords: Membrane distillation, Dynamical modeling, Advection-diffusion equation, Thermal equilibrium, Heat equation.

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Authors: Yitao Lei, Xingxiang Zhai, Burra Venkata Durga Kumar

Abstract:

As the quantity and complexity of computing in large-scale software systems increase, distributed system computing becomes increasingly important. The distributed system realizes high-performance computing by collaboration between different computing resources. If there are no efficient resource scheduling resources, the abuse of distributed computing may cause resource waste and high costs. However, resource scheduling is usually an NP-hard problem, so we cannot find a general solution. However, some optimization algorithms exist like genetic algorithm, ant colony optimization, etc. The large scale of distributed systems makes this traditional optimization algorithm challenging to work with. Heuristic and machine learning algorithms are usually applied in this situation to ease the computing load. As a result, we do a review of traditional resource scheduling optimization algorithms and try to introduce a deep reinforcement learning method that utilizes the perceptual ability of neural networks and the decision-making ability of reinforcement learning. Using the machine learning method, we try to find important factors that influence the performance of distributed system computing and help the distributed system do an efficient computing resource scheduling. This paper surveys the application of deep reinforcement learning on distributed system computing resource scheduling. The research proposes a deep reinforcement learning method that uses a recurrent neural network to optimize the resource scheduling. The paper concludes the challenges and improvement directions for Deep Reinforcement Learning-based resource scheduling algorithms.

Keywords: Resource scheduling, deep reinforcement learning, distributed system, artificial intelligence.

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Authors: Liming Chen, Baoxin Xiu, Zhaoyun Ding, Bin Liu, Xianqiang Zhu

Abstract:

In the era of big data, public investors are faced with more complicated information related to investment decisions than ever before. To survive in the fierce competition, it has become increasingly urgent for investors to combine multi-source knowledge and evaluate the companies’ true value efficiently. For this, a rule-based ontology reasoning method is proposed to support steel companies’ value assessment. Considering the delay in financial disclosure and based on cost-benefit analysis, this paper introduces the supply chain enterprises financial analysis and constructs the ontology model used to value the value of steel company. In addition, domain knowledge is formally expressed with the help of Web Ontology Language (OWL) language and SWRL (Semantic Web Rule Language) rules. Finally, a case study on a steel company in China proved the effectiveness of the method we proposed.

Keywords: Financial ontology, steel company, supply chain, ontology reasoning.

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Authors: Ziad Abdeldayem, Jakub Markiewicz, Kunal Kansara, Laura Edwards

Abstract:

Airborne Laser Scanning (ALS) is one of the main technologies for generating high-resolution digital terrain models (DTMs). DTMs are crucial to several applications, such as topographic mapping, flood zone delineation, geographic information systems (GIS), hydrological modelling, spatial analysis, etc. Laser scanning system generates irregularly spaced three-dimensional cloud of points. Raw ALS data are mainly ground points (that represent the bare earth) and non-ground points (that represent buildings, trees, cars, etc.). Removing all the non-ground points from the raw data is referred to as filtering. Filtering heavily forested areas is considered a difficult and challenging task as the canopy stops laser pulses from reaching the terrain surface. This research presents an approach for removing non-ground points from raw ALS data in densely forested areas. Smoothing splines are exploited to interpolate and fit the noisy ALS data. The presented filter utilizes a weight function to allocate weights for each point of the data. Furthermore, unlike most of the methods, the presented filtering algorithm is designed to be automatic. Three different forested areas in the United Kingdom are used to assess the performance of the algorithm. The results show that the generated DTMs from the filtered data are accurate (when compared against reference terrain data) and the performance of the method is stable for all the heavily forested data samples. The average root mean square error (RMSE) value is 0.35 m.

Keywords: Airborne laser scanning, digital terrain models, filtering, forested areas.

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