Search results for: Auto tuning; gain scheduling; MIMO Processes; Optimization; PID controller; Process Control.

Authors: Aya Maher, Pakinam Youssef

Abstract:

The objective of this theoretical study is to explore in depth the role of leaders in managing employees’ dysfunctional behavior at workplace in an effort to recommend strategies and solutions for these destructive behaviors that affect employees’ performance. The significance of the study lies in the fact that dysfunctional behavior has been widely spread in almost all organizations, public and private, with its very destructive manifestations. Dysfunctional behavior may be classified into thefts, sabotage, sexual harassment, jealousy, envy, revenge, vulgarity all of which affect employees’ moral, self-esteem and satisfaction level drastically which will be reflected negatively on their performance and productivity. The main research question will focus on the role of leaders in managing employees’ dysfunctional behavior effectively at the workplace through the different strategies and control measures. In this study, the data will be collected from different academic literature and through some primary data by conducting interviews with some public and private employees from different managerial levels and fields.

Keywords: Dysfunctional behavior, employees’ deviant behavior, employees moral, leaders’ role.

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Authors: Fl. Loury, P. Sablonière, C. Lamoureux, G. Magnier, Th. Gutierrez

Abstract:

A method is proposed to extract faithful representative patterns from data set of observations when they are suffering from non-negligible fluctuations. Supposing time interval between measurements to be extremely small compared to observation time, it consists in defining first a subset of intermediate time intervals characterizing coherent behavior. Data projection on these intervals gives a set of curves out of which an ideally “perfect” one is constructed by taking the sup limit of them. Then comparison with average real curve in corresponding interval gives an efficiency parameter expressing the degradation consecutive to fluctuation effect. The method is applied to sunlight data collected in a specific place, where ideal sunlight is the one resulting from direct exposure at location latitude over the year, and efficiency is resulting from action of meteorological parameters, mainly cloudiness, at different periods of the year. The extracted information already gives interesting element of decision, before being used for analysis of plant control.

Keywords: Base Input Reconstruction, Data Mining, Efficiency Factor, Information Pattern Operator.

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Authors: Fawehinmi Olabisi Alaba, Adeniyi O. R.

Abstract:

Farming households faces lots of disaster which contribute to endemic poverty. Anticipated increases in extreme weather events will exacerbate this. Primary data was administered to farming household using multi-stage random sampling technique. The result of the analysis shows that majority of the respondents (69.9%) are male, have mean household size, years of formal education and age of 5±1.14, 6±3.41, and 51.06±10.43 respectively. The major (48.9%) type of disaster experienced is flooding. Major coping mechanism adopted is sourcing for support from family and friends. Age, education, experience, access to extension agent, and mitigation control method contribute significantly to vulnerability to disaster. The major adaptation method (62.3%) is construction of drainage.

The study revealed that the coping mechanisms employed may become less effective as increasingly fragile livelihood systems struggle to withstand disaster shocks. Thus there is need for training of the farmers on measures to adapt to mitigate the shock from disasters

Keywords: Adaptation, Disasters, Flooding, Vulnerability.

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Authors: Ramaswamy Palaniappan

Abstract:

In this paper, a second order autoregressive (AR) model is proposed to discriminate alcoholics using single trial gamma band Visual Evoked Potential (VEP) signals using 3 different classifiers: Simplified Fuzzy ARTMAP (SFA) neural network (NN), Multilayer-perceptron-backpropagation (MLP-BP) NN and Linear Discriminant (LD). Electroencephalogram (EEG) signals were recorded from alcoholic and control subjects during the presentation of visuals from Snodgrass and Vanderwart picture set. Single trial VEP signals were extracted from EEG signals using Elliptic filtering in the gamma band spectral range. A second order AR model was used as gamma band VEP exhibits pseudo-periodic behaviour and second order AR is optimal to represent this behaviour. This circumvents the requirement of having to use some criteria to choose the correct order. The averaged discrimination errors of 2.6%, 2.8% and 11.9% were given by LD, MLP-BP and SFA classifiers. The high LD discrimination results show the validity of the proposed method to discriminate between alcoholic subjects.

Keywords: Linear Discriminant, Neural Network, VisualEvoked Potential.

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Authors: A. Saghaei, R. Ghasemi

Abstract:

Through 1980s, management accounting researchers described the increasing irrelevance of traditional control and performance measurement systems. The Balanced Scorecard (BSC) is a critical business tool for a lot of organizations. It is a performance measurement system which translates mission and strategy into objectives. Strategy map approach is a development variant of BSC in which some necessary causal relations must be established. To recognize these relations, experts usually use experience. It is also possible to utilize regression for the same purpose. Structural Equation Modeling (SEM), which is one of the most powerful methods of multivariate data analysis, obtains more appropriate results than traditional methods such as regression. In the present paper, we propose SEM for the first time to identify the relations between objectives in the strategy map, and a test to measure the importance of relations. In SEM, factor analysis and test of hypotheses are done in the same analysis. SEM is known to be better than other techniques at supporting analysis and reporting. Our approach provides a framework which permits the experts to design the strategy map by applying a comprehensive and scientific method together with their experience. Therefore this scheme is a more reliable method in comparison with the previously established methods.

Keywords: BSC, SEM, Strategy map.

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Authors: H. T. Barney, G. C. Low

Abstract:

The design of distributed systems involves the partitioning of the system into components or partitions and the allocation of these components to physical nodes. Techniques have been proposed for both the partitioning and allocation process. However these techniques suffer from a number of limitations. For instance object replication has the potential to greatly improve the performance of an object orientated distributed system but can be difficult to use effectively and there are few techniques that support the developer in harnessing object replication. This paper presents a methodological technique that helps developers decide how objects should be allocated in order to improve performance in a distributed system that supports replication. The performance of the proposed technique is demonstrated and tested on an example system.

Keywords: Allocation, Distributed Systems, Replication.

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Authors: G.Kavitha, V.Sankaranarayanan

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Grid computing provides a virtual framework for controlled sharing of resources across institutional boundaries. Recently, trust has been recognised as an important factor for selection of optimal resources in a grid. We introduce a new method that provides a quantitative trust value, based on the past interactions and present environment characteristics. This quantitative trust value is used to select a suitable resource for a job and eliminates run time failures arising from incompatible user-resource pairs. The proposed work will act as a tool to calculate the trust values of the various components of the grid and there by improves the success rate of the jobs submitted to the resource on the grid. The access to a resource not only depend on the identity and behaviour of the resource but also upon its context of transaction, time of transaction, connectivity bandwidth, availability of the resource and load on the resource. The quality of the recommender is also evaluated based on the accuracy of the feedback provided about a resource. The jobs are submitted for execution to the selected resource after finding the overall trust value of the resource. The overall trust value is computed with respect to the subjective and objective parameters.

Keywords: access control, feedback, grid computing, reputation, security, trust, trust parameter.

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Authors: M. Y. Ismail, M. Inam

Abstract:

This paper presents equivalent circuit modeling of active planar reflectors which can be used for the detailed analysis and characterization of reflector performance in terms of lumped components. Equivalent circuit representation has been proposed for PIN diodes and liquid crystal based active planar reflectors designed within X-band frequency range. A very close agreement has been demonstrated between equivalent circuit results, 3D EM simulated results as well as measured scattering parameter results. In the case of measured results, a maximum discrepancy of 1.05dB was observed in the reflection loss performance, which can be attributed to the losses occurred during measurement process.

Keywords: Equivalent circuit modelling, planar reflectors, reflectarray antenna, PIN diode, liquid crystal.

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Authors: Manuela Ciocoiu, Laur Badescu, Oana Badulescu, Magda Badescu

Abstract:

The research focuses on the effects of polyphenols extracted from Sambucus nigra fruit, using an experimental arterial hypertension pattern, as well as their influence on the oxidative stress. The results reveal the normalization of the reduced glutathion concentration, as well as a considerable reduction in the malondialdehide serum concentration by the polyphenolic protection. The rat blood pressure values were recorded using a CODATM system, which uses a non-invasive blood pressure measuring method. All the measured blood pressure components revealed a biostatistically significant (p<0.05) blood pressure drop between the AHT and the AHT+P groups. The results prove that oxidative stress is considerably lower, statistically speaking, in rats with hypertension but also provided with natural polyphenolic protection from Sambucus nigra fruits than in the rats belonging to the control group. In addition to the demonstrated antioxidant effects, natural polyphenols also have other biological properties that might contribute to the cardioprotective effects.

Keywords: Arterial hypertension, Oxidative stress, Sambucus nigra

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Authors: A. Chaikittiratana, S. Koetniyom, S. Lakkam

Abstract:

The feasibility of applying a simple and cost effective sliding friction testing apparatus to study the friction behaviour of a clutch facing material, effected by the variation of temperature and contact pressure, was investigated. It was found that the method used in this work was able to give a convenient and cost effective measurement of friction coefficients and their transitions of a clutch facing material. The obtained results will be useful for the development process of new facing materials.

Keywords: Static/kinetic friction, sliding friction testing apparatus, contact pressure and temperature dependent of friction coefficients.

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Authors: Natália B. Pompermayer, Mariana B. Porto, Elizabeth F. Souza

Abstract:

Nanophotocatalysts such as titanium (TiO2), zinc (ZnO), and iron (Fe2O3) oxides can be used in organic pollutants oxidation, and in many other applications. But among the challenges for technological application (scale-up) of the nanotechnology scientific developments two aspects are still little explored: research on environmental risk of the nanomaterials preparation methods, and the study of nanomaterials properties and/or performance variability. The environmental analysis was performed for six different methods of ZnO nanoparticles synthesis, and showed that it is possible to identify the more environmentally compatible process even at laboratory scale research. The obtained ZnO nanoparticles were tested as photocatalysts, and increased the degradation rate of the Rhodamine B dye up to 30 times.

Keywords: Environmental impact analysis, inorganic nanoparticles, photocatalysts.

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Authors: Reinhold Decker, Christian Holsing, Sascha Lerke

Abstract:

This paper presents a new growing neural network for cluster analysis and market segmentation, which optimizes the size and structure of clusters by iteratively checking them for multivariate normality. We combine the recently published SGNN approach [8] with the basic principle underlying the Gaussian-means algorithm [13] and the Mardia test for multivariate normality [18, 19]. The new approach distinguishes from existing ones by its holistic design and its great autonomy regarding the clustering process as a whole. Its performance is demonstrated by means of synthetic 2D data and by real lifestyle survey data usable for market segmentation.

Keywords: Artificial neural network, clustering, multivariatenormality, market segmentation, self-organization

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Authors: Wajid A. Chishty, Stephen D. Lepera, Uri Vandsburger

Abstract:

Thermoacoustic instabilities in combustors have remained a topic of investigation for over a few decades due to the challenges it posses to the operation of low emission gas turbines. For combustors burning liquid fuel, understanding the cause-andeffect relationship between spray combustion dynamics and thermoacoustic oscillations is imperative for the successful development of any control methodology for its mitigation. The paper presents some very unique operating characteristics of a kerosene-fueled diffusion type combustor undergoing limit-cycle oscillations. Combustor stability limits were mapped using three different-sized injectors. The results show that combustor instability depends on the characteristics of the fuel spray. A simple analytic analysis is also reported in support of a plausible explanation for the unique combustor behavior. The study indicates that high amplitude acoustic pressure in the combustor may cause secondary breakdown of fuel droplets resulting in premixed pre-vaporized type burning of the diffusion type combustor.

Keywords: Secondary droplet breakup, Spray dynamics, Taylor Analogy Breakup Model, Thermoacoustic instabilities.

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Authors: L. Steponavičiūtė, L. Steponavičienė

Abstract:

Despite the rapid nanotechnology progress and recognition, its potential impact in ecosystems and health of humans is still not fully known. In this paper, the study of ecotoxicological dangers of nanomaterials is presented. By chemical reduction method, silver (AgNPs) and gold (AuNPs) nanoparticles were synthesized, characterized and used in experiments to examine their impact on microorganisms (Escherichia coli, Staphylococcus aureus and Candida albicans) and terrestrial flora (Phaseolus vulgaris and Lepidium sativum). The results collected during experiments with terrestrial flora show tendentious growth stimulations caused by gold nanoparticles. In contrast to these results, silver nanoparticle solutions inhibited growth of beans and garden cress, compared to control samples. The results obtained from experiments with microorganisms show similarities with ones collected from experiments with terrestrial plants. Samples treated with AuNPs of size 13 nm showed stimulation in the growth of the colonies compared with 3,5 nm size nanoparticles.

Keywords: Ecosystems, ecotoxicology, nanomaterials, nanoparticles.

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Authors: Raju Kumar

Abstract:

Information and communication technology (ICT) has become, within a very short time, one of the basic building blocks of modern society. Many countries now understanding the importance of ICT and mastering the basic skills and concepts of it as part of the core of education. Organizations, experts and practitioners in the education sector increasingly recognizing the importance of ICT in supporting educational improvement and reform. This paper addresses the convergence of ICT and education. When two technologies are converging to each other, together they will generate some great opportunities and challenges. This paper focuses on these issues. In introduction section, it explains the ICT, education, and ICT-enhanced education. In next section it describes need of ICT in education, relationship between ICT skills and education, and stages of teaching learning process. The next two sections describe opportunities and challenges in integrating ICT in education. Finally the concluding section summaries the idea and its usefulness.

Keywords: Education, Information and CommunicationTechnology, Learning, Teaching.

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Authors: S. Krustev, V. Angelova, K. Ivanov, P. Zaprjanova

Abstract:

It is generally accepted that only about ten microelements are vitally important to all plants, and approximately ten more elements are proved to be significant for the development of some species. The main methods for their determination in soils are the atomic spectral techniques - AAS and ICP-OAS. Critical stage to obtain correct results for content of heavy metals and nutrients in the soil is the process of mineralization. A comparative study of the most widely spread methods for soil sample preparation for determination of some trace elements was carried out. Three most commonly used methods for sample preparation were used as follows: ISO11466, EPA Method 3051 and BDS ISO 14869-1. Their capabilities were assessed and their bounds of applicability in determining the levels of the most important microelements in agriculture were defined.

Keywords: Comparative study, mineralization methods, trace elements.

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Authors: LI qiu-min, TIAN yi-xiang, ZHANG gao-xun

Abstract:

GMDH algorithm can well describe the internal structure of objects. In the process of modeling, automatic screening of model structure and variables ensure the convergence rate.This paper studied a new GMDH model based on polynomial spline  stimation. The polynomial spline function was used to instead of the transfer function of GMDH to characterize the relationship between the input variables and output variables. It has proved that the algorithm has the optimal convergence rate under some conditions. The empirical results show that the algorithm can well forecast Consumer Price Index (CPI).

Keywords: spline, GMDH, nonparametric, bias, forecast.

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Authors: Rana Th. A. Al-Rubaye

Abstract:

A novel chromium-free protective coating films based on a zeolite coating was growing onto a FeCrAlloy metal using in – situ hydrothermal method. The zeolite film was obtained using in-situ crystallization process that is capable of coating large surfaces with complex shape and in confined spaces has been developed. The zeolite coating offers an advantage of a high mechanical stability and thermal stability. The physicochemical properties were investigated using X-ray diffraction (XRD), Electron Microscopy (SEM), Energy Dispersive X–ray Analysis (EDX) and Thermogravimetric Analysis (TGA). The transition from oxide-on-alloy wires to hydrothermally synthesised uniformly zeolite coated surfaces was followed using SEM and XRD. In addition, the robustness of the prepared coating was confirmed by subjecting these to thermal cycling (ambient to 550oC).

Keywords: FeCrAlloy, Zeolite ZSM-5. Zeolite coating.

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Authors: Yiqin Lin, Liang Bao

Abstract:

This paper is devoted to the numerical solution of large-scale linear ill-posed systems. A multilevel regularization method is proposed. This method is based on a synthesis of the Arnoldi-Tikhonov regularization technique and the multilevel technique. We show that if the Arnoldi-Tikhonov method is a regularization method, then the multilevel method is also a regularization one. Numerical experiments presented in this paper illustrate the effectiveness of the proposed method.

Keywords: Discrete ill-posed problem, Tikhonov regularization, discrepancy principle, Arnoldi process, multilevel method.

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Authors: Anne-Lena Kampen, Øivind Kure

Abstract:

Machine learning (ML) can be implemented in Wireless Sensor Networks (WSNs) as a central solution or distributed solution where the ML is embedded in the nodes. Embedding improves privacy and may reduce prediction delay. In addition, the number of transmissions is reduced. However, quality factors such as prediction accuracy, fault detection efficiency and coordinated control of the overall system suffer. Here, we discuss and highlight the trade-offs that should be considered when choosing between embedding and centralized ML, especially for multihop networks. In addition, we present estimations that demonstrate the energy trade-offs between embedded and centralized ML. Although the total network energy consumption is lower with central prediction, it makes the network more prone for partitioning due to the high forwarding load on the one-hop nodes. Moreover, the continuous improvements in the number of operations per joule for embedded devices will move the energy balance toward embedded prediction.

Keywords: Central ML, embedded machine learning, energy consumption, local ML, Wireless Sensor Networks, WSN.

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Authors: Mónika Bartalné-Berceli, Eszter Izsó, Szilveszter Gergely, András Salgó

Abstract:

Presently a significant portion of the Earth's population does not have access to healthy food. Either because they cannot afford it or because they do not know which one are they. The aim of the VII th Framework Chance project (Nr. 266331) supported by the European Union has been to develop relatively cheap food with favourable nutritional value and it should have acceptable quality for consumers. As one task of the project we manufactured bread products as a basic food. We examined the enrichment of bread products with four kinds of bran, with a special milling product of grain industry (aleurone-rich flour) and with a soy-based sprouted additive. The applied concentration of the six mentioned additives has been optimized and the physical properties of the bread products were monitored. The weight/density of the enriched breads increased a bit, however the volume and height decreased slightly compared to the corresponding data of the control bread. The optimized composition of the final product is favourably affected by these additives having highly preferred composition from nutritional point of view.

Keywords: Aleurone-rich flour, Brans, Bread products, Sprouted soybean, YASO.

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Authors: Juliana Barcelos Cordeiro, Khashayar Mahani, Farbod Farzan, Mohsen A. Jafari

Abstract:

Energy disaggregation has been focused by many energy companies since energy efficiency can be achieved when the breakdown of energy consumption is known. Companies have been investing in technologies to come up with software and/or hardware solutions that can provide this type of information to the consumer. On the other hand, not all people can afford to have these technologies. Therefore, in this paper, we present a methodology for breaking down the aggregate consumption and identifying the highdemanding end-uses profiles. These energy profiles will be used to build the forecast model for optimal control purpose. A facility with high cooling load is used as an illustrative case study to demonstrate the results of proposed methodology. We apply a high level energy disaggregation through a pattern recognition approach in order to extract the consumption profile of its rooftop packaged units (RTUs) and present a forecast model for the energy consumption.  

Keywords: Energy consumption forecasting, energy efficiency, load disaggregation, pattern recognition approach.

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Authors: Michalis Menicou, Stavros Christofi, Niki Chartosia, Vassos Vassiliou, Marios Charalambides

Abstract:

This paper presents preliminary results of a technology assessment analysis for the use of high pressure treatment (HPT) on Halloumi cheese. In particular, it presents the importance of this traditional Cyprus cheese to the island-s economy, explains its production process, and gives a brief introduction to HPT and its application on cheese. More importantly, it offers preliminary results of HPT of Halloumi samples and a preliminary economic feasibility study on the financial implications of the introduction of such technology.

Keywords: Economic feasibility analysis, high pressure treatment, Halloumi cheese, technology assessment

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Authors: Payam Mousavi, Andrew L. Stewart, Huiwen You, Aryeh F. G. Fayerman

Abstract:

We present a decision-support tool to assist an operator in the detection and tracking of a suspect vehicle traveling to an unknown target destination. Multiple data sources, such as traffic cameras, traffic information, weather, etc., are integrated and processed in real-time to infer a suspect’s intended destination chosen from a list of pre-determined high-value targets. Previously, we presented our work in the detection and tracking of vehicles using traffic and airborne cameras. Here, we focus on the fusion and processing of that information to predict a suspect’s behavior. The network of cameras is represented by a directional graph, where the edges correspond to direct road connections between the nodes and the edge weights are proportional to the average time it takes to travel from one node to another. For our experiments, we construct our graph based on the greater Los Angeles subset of the Caltrans’s “Performance Measurement System” (PeMS) dataset. We propose a Bayesian approach where a posterior probability for each target is continuously updated based on detections of the suspect in the live video feeds. Additionally, we introduce the concept of ‘soft interventions’, inspired by the field of Causal Inference. Soft interventions are herein defined as interventions that do not immediately interfere with the suspect’s movements; rather, a soft intervention may induce the suspect into making a new decision, ultimately making their intent more transparent. For example, a soft intervention could be temporarily closing a road a few blocks from the suspect’s current location, which may require the suspect to change their current course. The objective of these interventions is to gain the maximum amount of information about the suspect’s intent in the shortest possible time. Our system currently operates in a human-on-the-loop mode where at each step, a set of recommendations are presented to the operator to aid in decision-making. In principle, the system could operate autonomously, only prompting the operator for critical decisions, allowing the system to significantly scale up to larger areas and multiple suspects. Once the intended target is identified with sufficient confidence, the vehicle is reported to the authorities to take further action. Other recommendations include a selection of road closures, i.e., soft interventions, or to continue monitoring. We evaluate the performance of the proposed system using simulated scenarios where the suspect, starting at random locations, takes a noisy shortest path to their intended target. In all scenarios, the suspect’s intended target is unknown to our system. The decision thresholds are selected to maximize the chances of determining the suspect’s intended target in the minimum amount of time and with the smallest number of interventions. We conclude by discussing the limitations of our current approach to motivate a machine learning approach, based on reinforcement learning in order to relax some of the current limiting assumptions.

Keywords: Autonomous surveillance, Bayesian reasoning, decision-support, interventions, patterns-of-life, predictive analytics, predictive insights.

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Authors: Kati Manskinen, Risto Pöykiö, Hannu Nurmesniemi

Abstract:

In an assessment of the extractability of metals in green liquor dregs from the chemical recovery circuit of semichemical pulp mill, extractable concentrations of heavy metals in artificial gastric fluid were between 10 (Ni) and 717 (Zn) times higher than those in artificial sweat fluid. Only Al (6.7 mg/kg; d.w.), Ni (1.2 mg/kg; d.w.) and Zn (1.8 mg/kg; d.w.) showed extractability in the artificial sweat fluid, whereas Al (730 mg/kg; d.w.), Ba (770 mg/kg; d.w.) and Zn (1290 mg/kg; d.w.) showed clear extractability in the artificial gastric fluid. As certain heavy metals were clearly soluble in the artificial gastric fluid, the careful handling of this residue is recommended in order to prevent the penetration of green liquor dregs across the human gastrointestinal tract.

Keywords: Dregs, non-process elements, pulping, waste.

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Authors: T. M. Mousa-Balabel, M. A. Salama

Abstract:

The effect of shearing date on behaviors and performances of 20 pregnant Rahmani ewes was evaluated in four groups (5each). Ewes were shorn at 70, 100 and 130 days of pregnancy in the first three groups respectively, while the fourth group was maintained unshorn as a control. Some behavioral and physiological data related to ewes in addition, blood cortisol level were recorded. Results revealed a significant increase in the frequencies of comfort and eating behaviors, respiratory rate, pulse rate, lamb birth weight and blood cortisol level in early and mid pregnancy shorn ewes. Also, a slight increase in pregnancy period was observed for those ewes. On the other hand, social behaviors, and core temperature were not affected by shearing. These results conclude that prenatal shearing (early and mid-pregnancy) of ewes increases the frequencies of comfort and eating behaviors, and improves the survival rates of lambs by increasing their birth weights.

Keywords: behavior, blood cortisol, pregnant rahmani ewes, shearing.

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Authors: J. X. Dong, C. J. An, Z. Chen, E. H. Owens, M. C. Boufadel, E. Taylor, K. Lee

Abstract:

Shorelines are vulnerable to significant environmental impacts from oil spills. Stranded oil can cause potential short- to long-term detrimental effects along beaches that include injuries to ecosystem, socio-economic and cultural resources. In this study, a three-dimensional (3D) numerical modeling approach is developed to evaluate the fate and transport of spilled oil for hypothetical oiled shoreline cases under various combinations of beach geomorphology and environmental conditions. The developed model estimates the spatial and temporal distribution of spilled oil for the various test conditions, using the finite volume method and considering the physical transport (dispersion and advection), sinks, and sorption processes. The model includes a user-friendly interface for data input on variables such as beach properties, environmental conditions, and physical-chemical properties of spilled oil. An experimental meso-scale tank design was used to test the developed model for dissolved petroleum hydrocarbon within shorelines. The simulated results for effects of different sediment substrates, oil types, and shoreline features for the transport of spilled oil are comparable to that obtained with a commercially available model. Results show that the properties of substrates and the oil removal by shoreline effects have significant impacts on oil transport in the beach area. Sensitivity analysis, through the application of the one-step-at-a-time method (OAT), for the 3D model identified hydraulic conductivity as the most sensitive parameter. The 3D numerical model allows users to examine the behavior of oil on and within beaches, assess potential environmental impacts, and provide technical support for decisions related to shoreline clean-up operations.

Keywords: dissolved petroleum hydrocarbons, environmental multimedia model, finite volume method, FVM, sensitivity analysis, total petroleum hydrocarbons, TPH

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Authors: Maninder Jeet Kaur, Moin Uddin, Harsh K. Verma

Abstract:

The efficient use of available licensed spectrum is becoming more and more critical with increasing demand and usage of the radio spectrum. This paper shows how the use of spectrum as well as dynamic spectrum management can be effectively managed and spectrum allocation schemes in the wireless communication systems be implemented and used, in future. This paper would be an attempt towards better utilization of the spectrum. This research will focus on the decision-making process mainly, with an assumption that the radio environment has already been sensed and the QoS requirements for the application have been specified either by the sensed radio environment or by the secondary user itself. We identify and study the characteristic parameters of Cognitive Radio and use Genetic Algorithm for spectrum allocation. Performance evaluation is done using MATLAB toolboxes.

Keywords: Cognitive Radio, Fitness Functions, Fuzzy Logic, Quality of Service (QoS)

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Authors: Konstantinos Sofianos, Michael Stefanidakis

Abstract:

Nowadays, advances in information and communication technologies offer a range of opportunities for new approaches, methods, and tools in education and training. Teacher-centered learning has changed to student-centered learning. E-learning has now matured and enables the design and construction of intelligent learning systems. A smart learning system fully adapts to a student's needs and provides them with an education based on their preferences, learning styles, and learning backgrounds. It is a wise friend and available at anytime, anywhere, and with any digital device. In this paper, we propose an intelligent learning system, which includes an ontology with all elements of the learning process (learning objects, learning activities) and a massive open online course (MOOC) system. This intelligent learning system can be used in music education.

Keywords: Intelligent learning systems, e-learning, music education, ontology, semantic web.

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Authors: E. Sobhani-Tehrani, K. Khorasani, N. Meskin

Abstract:

This paper presents a novel integrated hybrid approach for fault diagnosis (FD) of nonlinear systems. Unlike most FD techniques, the proposed solution simultaneously accomplishes fault detection, isolation, and identification (FDII) within a unified diagnostic module. At the core of this solution is a bank of adaptive neural parameter estimators (NPE) associated with a set of singleparameter fault models. The NPEs continuously estimate unknown fault parameters (FP) that are indicators of faults in the system. Two NPE structures including series-parallel and parallel are developed with their exclusive set of desirable attributes. The parallel scheme is extremely robust to measurement noise and possesses a simpler, yet more solid, fault isolation logic. On the contrary, the series-parallel scheme displays short FD delays and is robust to closed-loop system transients due to changes in control commands. Finally, a fault tolerant observer (FTO) is designed to extend the capability of the NPEs to systems with partial-state measurement.

Keywords: Hybrid fault diagnosis, Dynamic neural networks, Nonlinear systems.

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