Search results for: Power plant modeling

Authors: A. T. Asutosh, J. Woo, M. Kouhirostami, M. Sam, A. Khantawang, C. Cuales, W. Ryor, C. Kibert

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Climate change and global warming vortex have grown to alarming proportions. Therefore, the need for a shift in the conceptualization of energy production is paramount. Energy practices have been created in the current situation. Fossil fuels continue their prominence, at the expense of renewable sources. Despite this abundance, a large percentage of the world population still has no access to electricity but there have been encouraging signs in global movement from nonrenewable to renewable energy but means to reverse climate change have been elusive. Worldwide, organizations have put tremendous effort into innovation. Conferences and exhibitions act as a platform that allows a broad exchange of information regarding trends in the renewable energy field. The Solar Power International (SPI) conference and exhibition is a gathering of concerned activists, and probably the largest convention of its kind. This study investigates current development in the renewable energy field, analyzing means by which industry is being applied to the issue. In reviewing the 2019 SPI conference, it was found innovations in recycling and assessing the environmental impacts of the solar products that need critical attention. There is a huge movement in the electrical storage but there exists a large gap in the development of security systems. This research will focus on solar energy, but impacts will be relevant to the entire renewable energy market.

Keywords: Climate change, renewable energy, solar, trends, research, SPI.

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Authors: Victor Breux, Jérôme Boutet, Alain Goret, Viviane Cattin

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Early detection of anomalies in data centers is important to reduce downtimes and the costs of periodic maintenance. However, there is little research on this topic and even fewer on the fusion of sensor data for the detection of abnormal events. The goal of this paper is to propose a method for anomaly detection in data centers by combining sensor data (temperature, humidity, power) and deep learning models. The model described in the paper uses one autoencoder per sensor to reconstruct the inputs. The auto-encoders contain Long-Short Term Memory (LSTM) layers and are trained using the normal samples of the relevant sensors selected by correlation analysis. The difference signal between the input and its reconstruction is then used to classify the samples using feature extraction and a random forest classifier. The data measured by the sensors of a data center between January 2019 and May 2020 are used to train the model, while the data between June 2020 and May 2021 are used to assess it. Performances of the model are assessed a posteriori through F1-score by comparing detected anomalies with the data center’s history. The proposed model outperforms the state-of-the-art reconstruction method, which uses only one autoencoder taking multivariate sequences and detects an anomaly with a threshold on the reconstruction error, with an F1-score of 83.60% compared to 24.16%.

Keywords: Anomaly detection, autoencoder, data centers, deep learning.

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Authors: Faezeh Mosallat, Eric L. Bibeau, Tarek El Mekkawy

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Parabolic solar trough systems have seen limited deployments in cold northern climates as they are more suitable for electricity production in southern latitudes. A numerical dynamic model is developed to simulate troughs installed in cold climates and validated using a parabolic solar trough facility in Winnipeg. The model is developed in Simulink and will be utilized to simulate a trigeneration system for heating, cooling and electricity generation in remote northern communities. The main objective of this simulation is to obtain operational data of solar troughs in cold climates and use the model to determine ways to improve the economics and address cold weather issues. In this paper the validated Simulink model is applied to simulate a solar assisted absorption cooling system along with electricity generation using Organic Rankine Cycle (ORC) and thermal storage. A control strategy is employed to distribute the heated oil from solar collectors among the above three systems considering the temperature requirements. This modelling provides dynamic performance results using measured meteorological data recorded every minute at the solar facility location. The purpose of this modeling approach is to accurately predict system performance at each time step considering the solar radiation fluctuations due to passing clouds. Optimization of the controller in cold temperatures is another goal of the simulation to for example minimize heat losses in winter when energy demand is high and solar resources are low. The solar absorption cooling is modeled to use the generated heat from the solar trough system and provide cooling in summer for a greenhouse which is located next to the solar field. The results of the simulation are presented for a summer day in Winnipeg which includes comparison of performance parameters of the absorption cooling and ORC systems at different heat transfer fluid (HTF) temperatures.

Keywords: Absorption cooling, parabolic solar trough, remote community, organic Rankine cycle.

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Authors: J. Cabral, C. Barreto Carvalho, C. da Motta, M. Sousa

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Community integration is a construct that an increasing body of research has shown to have a significant impact on the wellbeing and recovery of people with psychiatric problems. However, there are few studies that explore which factors can be associated and predict community integration. Moreover, community integration has been mostly studied in minority groups, and current literature on the definition and manifestation of community integration in the general population is scarcer. Thus, the current study aims to characterize community integration and explore possible predictor variables in a sample of participants with psychiatric problems (PP, N=183) and a sample of participants from the general population (GP, N=211). Results show that people with psychiatric problems present above average values of community integration, but are significantly lower than their healthy counterparts. It was also possible to observe that community integration does not vary in terms of the sociodemographic characteristics of both groups in this study. Correlation and multiple regression showed that, among several variables that literature present as relevant in the community integration process, only three variables emerged as having the most explanatory value in community integration of both groups: sense of community, basic needs satisfaction and submission. These results also shown that those variables have increased explanatory power in the PP sample, which leads us to emphasize the need to address this issue in future studies and increase the understanding of the factors that can be involved in the promotion of community integration, in order to devise more effective interventions in this field.

Keywords: Community integration, mental illness, predictors.

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Authors: Ben Khayut, Lina Fabri, Maya Avikhana

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The modern Artificial Narrow Intelligence (ANI) models cannot: a) independently, situationally, and continuously function without of human intelligence, used for retraining and reprogramming the ANI’s models, and b) think, understand, be conscious, and cognize under uncertainty and changing of the environmental objects. To eliminate these shortcomings and build a new generation of Artificial Intelligence systems, the paper proposes a Conception, Model, and Method of Computational Psycholinguistic Cognitive Situational-Fuzzy Self-Controlled Brain and Mind System (CPCSFSCBMSUU). This system uses a neural network as its computational memory, and activates functions of the perception, identification of real objects, fuzzy situational control, and forming images of these objects. These images and objects are used for modeling their psychological, linguistic, cognitive, and neural values of properties and features, the meanings of which are identified, interpreted, generated, and formed taking into account the identified subject area, using the data, information, knowledge, accumulated in the Memory. The functioning of the CPCSFSCBMSUU is carried out by its subsystems of the: fuzzy situational control of all processes, computational perception, identifying of reactions and actions, Psycholinguistic Cognitive Fuzzy Logical Inference, Decision Making, Reasoning, Systems Thinking, Planning, Awareness, Consciousness, Cognition, Intuition, and Wisdom. In doing so are performed analysis and processing of the psycholinguistic, subject, visual, signal, sound and other objects, accumulation and using the data, information and knowledge of the Memory, communication, and interaction with other computing systems, robots and humans in order of solving the joint tasks. To investigate the functional processes of the proposed system, the principles of situational control, fuzzy logic, psycholinguistics, informatics, and modern possibilities of data science were applied. The proposed self-controlled system of brain and mind is oriented on use as a plug-in in multilingual subject applications.

Keywords: Computational psycholinguistic cognitive brain and mind system, situational fuzzy control, uncertainty, AI.

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Authors: Francis William S, Imtiaz Ahmed Choudhury, Ananda Kumar Eriki, A. John Rajan

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Diesel Engines emit complex mixtures of inorganic and organic compounds in the form of both solid and vapour phase particles. Most of the particulates released are ultrafine nanoparticles which are detrimental to human health and can easily enter the body by respiration. The emissions standards on particulate matter release from diesel engines are constantly upgraded within the European Union and with future regulations based on the particles numbers released instead of merely mass, the need for effective aftertreatment devices will increase. Standard particulate filters in the form of wall flow filters can have problems with high soot accumulation, producing a large exhaust backpressure. A potential solution would be to combine the standard filter with a flow through filter to reduce the load on the wall flow filter. In this paper soot particle trapping has been simulated in different continuous flow filters of monolithic structure including the use of promoters, at laminar flow conditions. An Euler Lagrange model, the discrete phase model in Ansys used with user defined functions for forces acting on particles. A method to quickly screen trapping of 5 nm and 10 nm particles in different catalysts designs with tracers was also developed. Simulations of square duct monoliths with promoters show that the strength of the vortices produced are not enough to give a high amount of particle deposition on the catalyst walls. The smallest particles in the simulations, 5 and 10 nm particles were trapped to a higher extent, than larger particles up to 1000 nm, in all studied geometries with the predominant deposition mechanism being Brownian diffusion. The comparison of the different filters designed with a wall flow filter does show that the options for altering a design of a flow through filter, without imposing a too large pressure drop penalty are good.

Keywords: Diesel Engine trap, thermophoresis, Exhaust pipe, PM-Simulation modeling.

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Authors: R. Sekula

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Epoxy composites are broadly used as an electrical insulation for the high voltage applications since only such materials can fulfill particular mechanical, thermal, and dielectric requirements. However, properties of the final product are strongly dependent on proper manufacturing process with minimized material failures, as too large shrinkage, voids and cracks. Therefore, application of proper materials (epoxy, hardener, and filler) and process parameters (mold temperature, filling time, filling velocity, initial temperature of internal parts, gelation time), as well as design and geometric parameters are essential features for final quality of the produced components. In this paper, an approach for three-dimensional modeling of all molding stages, namely filling, curing and post-curing is presented. The reactive molding simulation tool is based on a commercial CFD package, and include dedicated models describing viscosity and reaction kinetics that have been successfully implemented to simulate the reactive nature of the system with exothermic effect. Also a dedicated simulation procedure for stress and shrinkage calculations, as well as simulation results are presented in the paper. Second part of the paper is dedicated to recent developments on formulations of functional composites for electrical insulation applications, focusing on thermally conductive materials. Concepts based on filler modifications for epoxy electrical composites have been presented, including the results of the obtained properties. Finally, having in mind tough environmental regulations, in addition to current process and design aspects, an approach for product re-design has been presented focusing on replacement of epoxy material with the thermoplastic one. Such “design-for-recycling” method is one of new directions associated with development of new material and processing concepts of electrical products and brings a lot of additional research challenges. For that, one of the successful products has been presented to illustrate the presented methodology.

Keywords: Curing, epoxy insulation, numerical simulations, recycling.

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Authors: Ahmed A. D. Sarhan, Hong Wan Ping, M. Sayuti

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In this current era of competitive machinery productions, the industries are designed to place more emphasis on the product quality and reduction of cost whilst abiding by the pollution-preventing policy. In attempting to delve into the concerns, the industries are aware that the effectiveness of existing lubrication systems must be improved to achieve power-efficient and pollution-preventing machining processes. As such, this research is targeted to study on a plausible solution to the issue in grinding titanium alloy (Ti-6Al-4V) by using nanolubrication, as an alternative to flood grinding. The aim of this research is to evaluate the optimum condition of grinding force and surface roughness using MQL lubricating system to deliver nano-oil at different level of weight concentration of Silicon Dioxide (SiO₂) mixed normal mineral oil. Taguchi Design of Experiment (DoE) method is carried out using a standard Taguchi orthogonal array of L16(43) to find the optimized combination of weight concentration mixture of SiO₂, nozzle orientation and pressure of MQL. Surface roughness and grinding force are also analyzed using signal-to-noise(S/N) ratio to determine the best level of each factor that are tested. Consequently, the best combination of parameters is tested for a period of time and the results are compared with conventional grinding method of dry and flood condition. The results show a positive performance of MQL nanolubrication.  

Keywords: Grinding, MQL, precision grinding, Taguchi optimization, titanium alloy.

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Authors: N. Mahendran, R. Priya

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The mobile cloud computing (MCC) with wireless sensor networks (WSNs) technology gets more attraction by research scholars because its combines the sensors data gathering ability with the cloud data processing capacity. This approach overcomes the limitation of data storage capacity and computational ability of sensor nodes. Finally, the stored data are sent to the mobile users when the user sends the request. The most of the integrated sensor-cloud schemes fail to observe the following criteria: 1) The mobile users request the specific data to the cloud based on their present location. 2) Power consumption since most of them are equipped with non-rechargeable batteries. Mostly, the sensors are deployed in hazardous and remote areas. This paper focuses on above observations and introduces an approach known as collaborative location-based sleep scheduling (CLSS) scheme. Both awake and asleep status of each sensor node is dynamically devised by schedulers and the scheduling is done purely based on the of mobile users’ current location; in this manner, large amount of energy consumption is minimized at WSN. CLSS work depends on two different methods; CLSS1 scheme provides lower energy consumption and CLSS2 provides the scalability and robustness of the integrated WSN.

Keywords: Sleep scheduling, mobile cloud computing, wireless sensor network, integration, location, network lifetime.

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Authors: Angie M. Wolf, Angie Del Prado Lippman, DeVone Boggan, Caroline Glesmann, Estivaliz Castro

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This paper highlights an innovative and nontraditional violence prevention program that is making a noticeable impact in what was once one of the country’s most violent communities. With unique and tailored strategies, the Operation Peacemaker Fellowship, established in Richmond, California, combines components of evidence-based practices with a community-oriented focus on relationships and mentoring to fill a gap in services and increase community safety. In an effort to highlight these unique strategies and provide a blueprint for other communities with violent crime problems, the authors of this paper hope to clearly delineate how one community is moving forward with vanguard approaches to invest in the lives of young men who once were labeled their community’s most violent, even most deadly, youth. The impact of this program is evidenced through the fellows’ own voices as they illuminate the experience of being in the Fellowship. In interviews, fellows describe how participating in this program has transformed their lives and the lives of those they love. The authors of this article spent more than two years researching this Fellowship program in order to conduct an evaluation of it and, ultimately, to demonstrate how this program is a testament to the power of relationships and love combined with evidence-based practices, consequently enriching the lives of youth and the community that embraces them.

Keywords: Community violence, firearm violence, interventions for violent crime, violence prevention.

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Authors: Sansani Rungrattawatchai

Abstract:

The White Kwao (Pueraria mirifica), a potent phytoestrogenic medicinal plant, has long been use in Thailand as a traditional folkmedicine. However, no scientific information of the direct effect of White Kwao on the development of mammalian embryo was available. Therefore, the purpose of this study was to investigate the effect of White Kwao extract on the in vitro development and implantation rate of mouse embryos. This study was designed into two experiments. In the first experiment, the two-cell stage mouse embryos were collected from the oviduct of superovulated mature female mice, and randomly cultured in three different media, the M16, M16 supplemented with 0.52μg esthinylestradiol-17β, and M16 supplemented with 10 mg/ml White Kwao extract. The culture was incubated in CO2 incubator at 37 oC . After the embryos were cultivated, the developments of embryos were observed every 24 hours for 5 days. The development rate of embryos from the two-cell stage to blastocyst stage in the media was with White Kwao was significantly higher (p<0.05) than those of the control group (68.50% versus 43.50%) but did not differ from the positive control group (68.50% versus 57.66%). In the second experiment, hatched blastocysts, which obtained from three different media, were differently labeled the nuclei with two polynucleotide-specific fluorochromes, the propidium iodide (PI) and the bisbenzimide. The results showed that the number of trophectoderm cells in the blastocysts that cultivated in the media with White Kwao did not significantly differ from the control (80.00 versus 70 cells) and the positive control group (80.00 versus 112.50 cells). The average number of inner cell mass in the White Kwao treated group did not significantly differ from the control group (20.50 versus 16.00 cells) and the positive control group (20.50 versus 20.50 cells). The total cell number including the trophectoderm and the inner cell mass of the individual hatched blastocyst was evaluated. The cell number in the blastocysts obtained from the media with the White Kwao did not significantly differ from the control (94.25 + 9.50 versus 92.33 + 4.05) and the positive control group (94.25 + 9.50 versus 110.33 + 9.16). The results demonstrated that the White Kwao treatment group did have a stimulating effect on the in vitro development of mouse embryos. The exact mechanism that White Kwao stimulated mouse embryo development is not known. The suspect mechanism may in a manner similar to the mechanism that of estrogen stimulated the development of the mouse embryos. Futher studies are needed to transfer the blastocyst into the endometrium of pseudopreagnancy mice to evaluate the effect of White Kwao on implantation

Keywords: White Kwao (Pueraria mirifica), blastocyst.

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Authors: Xiaochuan Chen, Jianguo Yang, Beizhi Li

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Design for cost (DFC) is a method that reduces life cycle cost (LCC) from the angle of designers. Multiple domain features mapping (MDFM) methodology was given in DFC. Using MDFM, we can use design features to estimate the LCC. From the angle of DFC, the design features of family cars were obtained, such as all dimensions, engine power and emission volume. At the conceptual design stage, cars- LCC were estimated using back propagation (BP) artificial neural networks (ANN) method and case-based reasoning (CBR). Hamming space was used to measure the similarity among cases in CBR method. Levenberg-Marquardt (LM) algorithm and genetic algorithm (GA) were used in ANN. The differences of LCC estimation model between CBR and artificial neural networks (ANN) were provided. ANN and CBR separately each method has its shortcomings. By combining ANN and CBR improved results accuracy was obtained. Firstly, using ANN selected some design features that affect LCC. Then using LCC estimation results of ANN could raise the accuracy of LCC estimation in CBR method. Thirdly, using ANN estimate LCC errors and correct errors in CBR-s estimation results if the accuracy is not enough accurate. Finally, economically family cars and sport utility vehicle (SUV) was given as LCC estimation cases using this hybrid approach combining ANN and CBR.

Keywords: case-based reasoning, life cycle cost (LCC), artificialneural networks (ANN), family cars

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Authors: Yong Zhao, Jian He, Cheng Zhang

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Cardiovascular disease resulting from hypertension poses a significant threat to human health, and early detection of hypertension can potentially save numerous lives. Traditional methods for detecting hypertension require specialized equipment and are often incapable of capturing continuous blood pressure fluctuations. To address this issue, this study starts by analyzing the principle of heart rate variability (HRV) and introduces the utilization of sliding window and power spectral density (PSD) techniques to analyze both temporal and frequency domain features of HRV. Subsequently, a hypertension prediction network that relies on HRV is proposed, combining Resnet, attention mechanisms, and a multi-layer perceptron. The network leverages a modified ResNet18 to extract frequency domain features, while employing an attention mechanism to integrate temporal domain features, thus enabling auxiliary hypertension prediction through the multi-layer perceptron. The proposed network is trained and tested using the publicly available SHAREE dataset from PhysioNet. The results demonstrate that the network achieves a high prediction accuracy of 92.06% for hypertension, surpassing traditional models such as K Near Neighbor (KNN), Bayes, Logistic regression, and traditional Convolutional Neural Network (CNN).

Keywords: Feature extraction, heart rate variability, hypertension, residual networks.

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Authors: P. Kowalska, P. Gabka, K. Kamieniarz, M. Kamieniarz, W. Stryla, P. Guzik, T. Krauze

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We have developed a computer program consisting of 6 subtests assessing the children hand dexterity applicable in the rehabilitation medicine. We have carried out a normative study on a representative sample of 285 children aged from 7 to 15 (mean age 11.3) and we have proposed clinical standards for three age groups (7-9, 9-11, 12-15 years). We have shown statistical significance of differences among the corresponding mean values of the task time completion. We have also found a strong correlation between the task time completion and the age of the subjects, as well as we have performed the test-retest reliability checks in the sample of 84 children, giving the high values of the Pearson coefficients for the dominant and non-dominant hand in the range 0.740.97 and 0.620.93, respectively. A new MATLAB-based programming tool aiming at analysis of cardiologic RR intervals and blood pressure descriptors, is worked out, too. For each set of data, ten different parameters are extracted: 2 in time domain, 4 in frequency domain and 4 in Poincaré plot analysis. In addition twelve different parameters of baroreflex sensitivity are calculated. All these data sets can be visualized in time domain together with their power spectra and Poincaré plots. If available, the respiratory oscillation curves can be also plotted for comparison. Another application processes biological data obtained from BLAST analysis.

Keywords: Biomedical data base processing, Computer software, Hand dexterity, Heart rate and blood pressure variability.

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Authors: Fouad Salha , X. Guillaud

Abstract:

Directional over current relays (DOCR) are commonly used in power system protection as a primary protection in distribution and sub-transmission electrical systems and as a secondary protection in transmission systems. Coordination of protective relays is necessary to obtain selective tripping. In this paper, an approach for efficiency reduction of DOCRs nonlinear optimum coordination (OC) is proposed. This was achieved by modifying the objective function and relaxing several constraints depending on the four constraints classification, non-valid, redundant, pre-obtained and valid constraints. According to this classification, the far end fault effect on the objective function and constraints, and in consequently on relay operating time, was studied. The study was carried out, firstly by taking into account the near-end and far-end faults in DOCRs coordination problem formulation; and then faults very close to the primary relays (nearend faults). The optimal coordination (OC) was achieved by simultaneously optimizing all variables (TDS and Ip) in nonlinear environment by using of Genetic algorithm nonlinear programming techniques. The results application of the above two approaches on 6-bus and 26-bus system verify that the far-end faults consideration on OC problem formulation don-t lose the optimality.

Keywords: Backup/Primary relay, Coordination time interval (CTI), directional over current relays, Genetic algorithm, time dial setting (TDS), pickup current setting (Ip), nonlinear programming.

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Authors: Zhiwen Yang, Jingyuan Li, Zhenkai Xie, Jian Ling, Jiguang Wang, Mengliang Li

Abstract:

To reflect the influence of after-treatment system retrofit and natural gas-fueled vehicle replace on exhaust emissions emitted by urban buses, a portable emission measurement system (PEMS) was employed herein to conduct real driving emission measurements. This study investigated the differences in particle number (PN), particle mass (PM), and nitrogen oxides (NOx) emissions from a China IV diesel bus retrofitted by catalyzed diesel particulate filter (CDPF), a China IV diesel bus, and a China V natural gas bus. The results show that both tested diesel buses possess markedly advantages in NOx emission control when compared to the lean-burn natural gas bus equipped without any NOx after-treatment system. As to PN and PM, only the DOC+CDPF retrofitting diesel bus exhibits enormous benefits on emission control related to the natural gas bus, especially the normal diesel bus. Meanwhile, the differences in PM and PN emissions between retrofitted and normal diesel buses generally increase with the increase in vehicle specific power (VSP). Furthermore, the differences in PM emissions, especially those in the higher VSP ranges, are more significant than those in PN. In addition, the maximum peak PN particle size (32 nm) of the retrofitted diesel bus was significantly lower than that of the normal diesel bus (100 nm). These phenomena indicate that the CDPF retrofitting can effectively reduce diesel bus exhaust particle emissions, especially those with large particle sizes.

Keywords: CDPF, diesel, natural gas, real-world emissions.

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Authors: R. Bourziza, A. Hammani, M. Kuper, A. Bouaziz

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In oases, the surface water resources are becoming increasingly scarce and groundwater resources, which generally have a poor quality due to the high levels of salinity, are often overexploited. Water saving have therefore become imperative for better oases sustainability. If drip irrigation is currently recommended in Morocco for saving water and valuing, its use in the sub-desert areas does not keep water safe from high evaporation rates. An alternative to this system would be the use of subsurface drip irrigation. This technique is defined as an application of water under the soil surface through drippers, which deliver water at rates generally similar to surface drip irrigation. As subsurface drip irrigation is a recently introduced in Morocco, a better understanding of the infiltration process around a buried source, in local conditions, and its impact on plant growth is necessarily required. This study aims to contribute to improving the water use efficiency by testing the performance of subsurface irrigation system, especially in areas where water is a limited source. The objectives of this research are performance evaluation in arid conditions of the subsurface drip irrigation system for young date palms compared to the surface drip. In this context, an experimental test is installed at a farmer’s field in the area of Erfoud (Errachidia Province, southeastern Morocco), using the subsurface drip irrigation system in comparison with the classic drip system for young date palms. Flow measurement to calculate the uniformity of the application of water was done through two methods: a flow measurement of drippers above the surface and another one underground. The latter method has also helped us to estimate losses through evaporation for both irrigation techniques. In order to compare the effect of two irrigation modes, plants were identified for each type of irrigation to monitor certain agronomic parameters (cumulative numbers of palms and roots development). Experimentation referred to a distribution uniformity of about 88%; considered acceptable for subsurface drip irrigation while it is around 80% for the surface drip irrigation. The results also show an increase in root development and in the number of palm, as well as a substantial water savings due to lower evaporation losses compared to the classic drip irrigation. The results of this study showed that subsurface drip irrigation is an efficient technique, which allows sustainable irrigation in arid areas.

Keywords: Subsurface drip irrigation, Water conservation, Arid areas, Young date palms.

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Authors: Bhavneet Sidhu, Hardeep Singh, Amit Chhabra

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The world of wireless telecommunications is rapidly evolving. Technologies under research and development promise to deliver more services to more users in less time. This paper presents the emerging technologies helping wireless systems grow from where we are today into our visions of the future. This paper will cover the applications and characteristics of emerging wireless technologies: Wireless Local Area Networks (WiFi-802.11n), Wireless Personal Area Networks (ZigBee) and Wireless Metropolitan Area Networks (WiMAX). The purpose of this paper is to explain the impending 802.11n standard and how it will enable WLANs to support emerging media-rich applications. The paper will also detail how 802.11n compares with existing WLAN standards and offer strategies for users considering higher-bandwidth alternatives. The emerging IEEE 802.15.4 (ZigBee) standard aims to provide low data rate wireless communications with high-precision ranging and localization, by employing UWB technologies for a low-power and low cost solution. WiMAX (Worldwide Interoperability for Microwave Access) is a standard for wireless data transmission covering a range similar to cellular phone towers. With high performance in both distance and throughput, WiMAX technology could be a boon to current Internet providers seeking to become the leader of next generation wireless Internet access. This paper also explores how these emerging technologies differ from one another.

Keywords: MIMO technology, WiFi, WiMAX, ZigBee.

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Authors: J. Chatthong, W. Boonchouytan, R. Burapa

Abstract:

The purpose of study was to design and construction the semi-automatic sliced ginger machine for reduce production times in sheet and slice ginger procedure furthermore, reduced amount of labor of slides and cutting method. Take consider into clean and safety of workers and consumers. The principle of machines, used 1 horsepower motor, rotation speed of sliced blade 967 rpm, the diameter of sliced dish 310 mm, consists of 2 blades for sheet cutting ginger and the power from motor which transfer to rotate the sliced blade roller, rotation speed 440 rpm. The slice cutter roller was sliced ginger from sheet ginger to line ginger. The conveyer could adjustment level of motors, used to the beginning area that sheet ginger was transference to the roller for sheet and sliced cutting in next process. The cover of sliced cutting had channel for 1 tuber of ginger. The semi-automatic sliced ginger machine could produced sheet ginger 81.8 kg/h (6.2 times of labor) and line ginger 17.9 kg/h (2.5 times of labor) compare with, labor work could produced sheet ginger 13.2 kg/h and line ginger 7.1 kg/h, and when timekeeper, the total times of semi auto machine 30.86 kg/h and labor 4.6 kg/h, there for the semi auto machine was 6.7 times of labor. The semiautomatic sliced ginger machine convenient, easy for use and maintain, in addition to reduce fatigue of body and seriousness from works; must be used high skill, and protection accident in slicing procedure. Beside, machine could used with other vegetables for example potato, carrot .etc

Keywords: Sliced Machine, Sliced Ginger, Line Ginger

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Authors: Hamze Torabian, Mohammad Mehrabioun Mohammadi

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Like many other industries, the payment industry has been affected by digital transformation. The importance of digital transformation in the payment industry is very crucial. Because the payment industry is considered a leading industry in digital and emerging technologies, and the digitalization of other industries such as retail, health, and telecommunication, it also depends on the growth rate of digitalized payment systems. One of the technological innovations in service management is Field Service Management (FSM). Despite the widespread use of FSM in various industries such as petrochemical, health, maintenance, etc., this technology can also be recruited in the payment industry, transforming the payment industry into a more agile and efficient one. Accordingly, the present study pays close attention to the application of FSM in the payment industry. Given the importance of merchants' bargaining power in the payment industry, this study aims to use FSM in the digital transformation initiative with a targeted focus on providing real-time services to merchants. The research method consists of three parts. Firstly, conducting the review of past research, applications of FSM in the payment industry are considered. In the next step, merchants' benefits such as emotional, functional, economic, and social benefits in using FSM are identified using in-depth interviews and content analysis methods. The related business model in helping the payment industry transforming into a more agile and efficient industry is considered in the following step. The results revealed the 10 main pillars required to realize the digital transformation of payment systems using FSM.

Keywords: Digital transformation, field service management, merchant support systems, payment industry.

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Authors: Dharmendra Chourishi “Maitraya”, Sridevi Seshadri

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Bluetooth is a personal wireless communication technology and is being applied in many scenarios. It is an emerging standard for short range, low cost, low power wireless access technology. Current existing MAC (Medium Access Control) scheduling schemes only provide best-effort service for all masterslave connections. It is very challenging to provide QoS (Quality of Service) support for different connections due to the feature of Master Driven TDD (Time Division Duplex). However, there is no solution available to support both delay and bandwidth guarantees required by real time applications. This paper addresses the issue of how to enhance QoS support in a Bluetooth piconet. The Bluetooth specification proposes a Round Robin scheduler as possible solution for scheduling the transmissions in a Bluetooth Piconet. We propose an algorithm which will reduce the bandwidth waste and enhance the efficiency of network. We define token counters to estimate traffic of real-time slaves. To increase bandwidth utilization, a back-off mechanism is then presented for best-effort slaves to decrease the frequency of polling idle slaves. Simulation results demonstrate that our scheme achieves better performance over the Round Robin scheduling.

Keywords: Piconet, Medium Access Control, Polling algorithm, Scheduling, QoS, Time Division Duplex (TDD).

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Authors: Chiang Tzu-Chiang, Chang Jia-Lin, Tsai Yue-Fu, Li Sha-Pai

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With the advantage of wireless network technology, there are a variety of mobile applications which make the issue of wireless sensor networks as a popular research area in recent years. As the wireless sensor network nodes move arbitrarily with the topology fast change feature, mobile nodes are often confronted with the void issue which will initiate packet losing, retransmitting, rerouting, additional transmission cost and power consumption. When transmitting packets, we would not predict void problem occurring in advance. Thus, how to improve geographic routing with void avoidance in wireless networks becomes an important issue. In this paper, we proposed a greedy geographical void routing algorithm to solve the void problem for wireless sensor networks. We use the information of source node and void area to draw two tangents to form a fan range of the existence void which can announce voidavoiding message. Then we use source and destination nodes to draw a line with an angle of the fan range to select the next forwarding neighbor node for routing. In a dynamic wireless sensor network environment, the proposed greedy void avoiding algorithm can be more time-saving and more efficient to forward packets, and improve current geographical void problem of wireless sensor networks.

Keywords: Wireless sensor network, internet routing, wireless network, greedy void avoiding algorithm, bypassing void.

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Authors: Chlopicka Joanna, Barton Henryk, Kryczyk Jadwiga, Francik Renata

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Recent studies demonstrated that high-fat diet increases oxidative stress in plasma and in a variety of tissues. Many researchers have been looking for natural products, which can reverse the effect of high fat diet. Recently, buckwheat is becoming common ingredient in functional food because of it properties. In study on buckwheat, it is known that, this plant plays roles as anti-oxidative, anti-inflammatory and anti-hypertensive. Nevertheless still little is known about buckwheat groats. The aim of this study was to investigate the effects of addition of buckwheat groats to the fat diet (30% lard), on some antioxidant and oxidant stress parameters in plasma and selected tissues in Wistar rats. The experiment was carried out with three months old male Wistar rats ca. 250g of body weight fed for 5 weeks with either a high-fat (30% of lard) diet or control diet, with or without addition of buckwheat groats. In plasma biochemistry and the activities of the antioxidant enzymes were measured selected tissues: glutathione peroxidase (GPX), catalase (CAT) and the levels of total and reduced glutathione (GSH), free thiol groups (pSH), antioxidant potential of plasma (FRAP) and oxidant stress indices - proteins carbonyl groups (CO) and malonyldialdehyde concentration (MDA). Activity of catalase (CAT) in plasma of rats was significantly increased in buckwheat groats groups and activity of GPx3 in plasma of rats was decreased in buckwheat groups as compared to control group. The reduced glutathione (GSH) in plasma of rats was significantly increased and protein CO was significantly decreased in buckwheat groups as compared to controls. The lowered concentration of GSH was found in serum of rats fed buckwheat groats addition but it accompanied in 7-fold increase in reduced-to-oxidized glutatione ratio, significant increase in HDL and decrease in nonHDL concentration. Conclusions: Buckwheat groats indicate a beneficial effect in inhibiting protein and lipid peroxidation in rats and improved lipid profile. These results suggest that buckwheat groats exert a significant antioxidant potential and may be used as normal food constituent to ameliorate the oxidant-induced damage in organism. 

Keywords: Antioxidant, buckwheat, high-fat diet, rats.

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Authors: Angelo Corallo, Maria Elena Latino, Marta Menegoli

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Agri-food value chain involves various stakeholders with different roles. All of them abide by national and international rules and leverage marketing strategies to advance their products. Food products and related processing phases carry with it a big mole of data that are often not used to inform final customer. Some data, if fittingly identified and used, can enhance the single company, and/or the all supply chain creates a math between marketing techniques and voluntary traceability strategies. Moreover, as of late, the world has seen buying-models’ modification: customer is careful on wellbeing and food quality. Food citizenship and food democracy was born, leveraging on transparency, sustainability and food information needs. Internet of Things (IoT) and Analytics, some of the innovative technologies of Industry 4.0, have a significant impact on market and will act as a main thrust towards a genuine ‘4.0 change’ for agriculture. But, realizing a traceability system is not simple because of the complexity of agri-food supply chain, a lot of actors involved, different business models, environmental variations impacting products and/or processes, and extraordinary climate changes. In order to give support to the company involved in a traceability path, starting from business model analysis and related business process a Framework to Manage Product Data in Agri-Food Supply Chain for Voluntary Traceability was conceived. Studying each process task and leveraging on modeling techniques lead to individuate information held by different actors during agri-food supply chain. IoT technologies for data collection and Analytics techniques for data processing supply information useful to increase the efficiency intra-company and competitiveness in the market. The whole information recovered can be shown through IT solutions and mobile application to made accessible to the company, the entire supply chain and the consumer with the view to guaranteeing transparency and quality.

Keywords: Agriculture 4.0, agri-food supply chain, Industry 4.0, voluntary traceability.

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Authors: Jalal Haghighat Monfared, Zahra Akbari

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Today, business executives need to have useful information to make better decisions. Banks have also been using information tools so that they can direct the decision-making process in order to achieve their desired goals by rapidly extracting information from sources with the help of business intelligence. The research seeks to investigate whether there is a relationship between the quality of decision making and the business intelligence capabilities of Mellat Bank. Each of the factors studied is divided into several components, and these and their relationships are measured by a questionnaire. The statistical population of this study consists of all managers and experts of Mellat Bank's General Departments (including 190 people) who use commercial intelligence reports. The sample size of this study was 123 randomly determined by statistical method. In this research, relevant statistical inference has been used for data analysis and hypothesis testing. In the first stage, using the Kolmogorov-Smirnov test, the normalization of the data was investigated and in the next stage, the construct validity of both variables and their resulting indexes were verified using confirmatory factor analysis. Finally, using the structural equation modeling and Pearson's correlation coefficient, the research hypotheses were tested. The results confirmed the existence of a positive relationship between decision quality and business intelligence capabilities in Mellat Bank. Among the various capabilities, including data quality, correlation with other systems, user access, flexibility and risk management support, the flexibility of the business intelligence system was the most correlated with the dependent variable of the present research. This shows that it is necessary for Mellat Bank to pay more attention to choose the required business intelligence systems with high flexibility in terms of the ability to submit custom formatted reports. Subsequently, the quality of data on business intelligence systems showed the strongest relationship with quality of decision making. Therefore, improving the quality of data, including the source of data internally or externally, the type of data in quantitative or qualitative terms, the credibility of the data and perceptions of who uses the business intelligence system, improves the quality of decision making in Mellat Bank.

Keywords: Business intelligence, business intelligence capability, decision making, decision quality.

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Authors: A. Majeed, P. Ali

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Before designing an electrical system, the estimation of load is necessary for unit sizing and demand-generation balancing. The system could be a stand-alone system for a village or grid connected or integrated renewable energy to grid connection, especially as there are non–electrified villages in developing countries. In the classical model, the energy demand was found by estimating the household appliances multiplied with the amount of their rating and the duration of their operation, but in this paper, information exists for electrified villages could be used to predict the demand, as villages almost have the same life style. This paper describes a method used to predict the average energy consumed in each two months for every consumer living in a village by Artificial Neural Network (ANN). The input data are collected using a regional survey for samples of consumers representing typical types of different living, household appliances and energy consumption by a list of information, and the output data are collected from administration office of Piramagrun for each corresponding consumer. The result of this study shows that the average demand for different consumers from four villages in different months throughout the year is approximately 12 kWh/day, this model estimates the average demand/day for every consumer with a mean absolute percent error of 11.8%, and MathWorks software package MATLAB version 7.6.0 that contains and facilitate Neural Network Toolbox was used.

Keywords: Artificial neural network, load estimation, regional survey, rural electrification.

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Authors: Andrew Jester, Ross Lee, Pritpal Singh

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As the world transitions to a more sustainable energy economy, the deployment of energy storage technologies is expected to increase to develop a more resilient grid system. However, current technologies are associated with various environmental and safety issues throughout their entire lifecycle; therefore, a new battery technology is desirable for grid applications to curtail these risks. Biological cells, such as human neurons and electrocytes in the electric eel, can serve as a more sustainable design template for a new bio-inspired (i.e., biomimetic) battery. Within biological cells, an electrochemical gradient across the cell membrane forms the membrane potential, which serves as the driving force for ion transport into/out of the cell akin to the charging/discharging of a battery cell. This work serves as the first step for developing such a biomimetic battery cell, starting with the fabrication and characterization of ion-selective membranes to facilitate ion transport through the cell. Performance characteristics (e.g., cell voltage, power density, specific energy, roundtrip efficiency) for the cell under investigation are compared to incumbent battery technologies and biological cells to assess the readiness level for this emerging technology. Using a Na+-Form Nafion-117 membrane, the cell in this work successfully demonstrated behavior like human neurons; these findings will inform how cell components can be re-engineered to enhance device performance.

Keywords: Battery, biomimetic, electrocytes, human neurons, ion-selective membranes, membrane potential.

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Authors: Antonio Vitale, Nicola Genito, Giovanni Cuciniello, Ferdinando Montemari

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The introduction of tilt-rotor aircraft into the existing civilian air transportation system will provide beneficial effects due to tilt-rotor capability to combine the characteristics of a helicopter and a fixed-wing aircraft into one vehicle. The disposability of reliable tilt-rotor simulation models supports the development of such vehicle. Indeed, simulation models are required to design automatic control systems that increase safety, reduce pilot's workload and stress, and ensure the optimal aircraft configuration with respect to flight envelope limits, especially during the most critical flight phases such as conversion from helicopter to aircraft mode and vice versa. This article presents a process to build a simplified tilt-rotor simulation model, derived from the analysis of flight data. The model aims to reproduce the complex dynamics of tilt-rotor during the in-flight conversion phase. It uses a set of scheduled linear transfer functions to relate the autopilot reference inputs to the most relevant rigid body state variables. The model also computes information about the rotor flapping dynamics, which are useful to evaluate the aircraft control margin in terms of rotor collective and cyclic commands. The rotor flapping model is derived through a mixed theoretical-empirical approach, which includes physical analytical equations (applicable to helicopter configuration) and parametric corrective functions. The latter are introduced to best fit the actual rotor behavior and balance the differences existing between helicopter and tilt-rotor during flight. Time-domain system identification from flight data is exploited to optimize the model structure and to estimate the model parameters. The presented model-building process was applied to simulated flight data of the ERICA Tilt-Rotor, generated by using a high fidelity simulation model implemented in FlightLab environment. The validation of the obtained model was very satisfying, confirming the validity of the proposed approach.

Keywords: Flapping Dynamics, Flight Dynamics, System Identification, Tilt-Rotor Modeling and Simulation.

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Authors: Fernanda T. Orsati, Julie Causton

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Discursive practices enacted by educators in kindergarten create a blueprint for how the educational trajectories of students with disabilities are constructed. This two-year ethnographic case study critically examines educators’ relationships with students considered to present challenging behaviors in one kindergarten classroom located in a predominantly White middle class school district in the Northeast of the United States. Focusing on the language and practices used by one special education teacher and three teaching assistants, this paper analyzes how teacher responses to students’ behaviors constructs and positions students over one year of kindergarten education. Using a critical discourse analysis it shows that educators understand students’ behaviors as deficit and needing consequences. This study highlights how educators’ responses reflect students' individual characteristics including family background, socioeconomics and ability status. This paper offers in depth analysis of two students’ stories, which evidenced that the language used by educators amplifies the social positioning of students within the classroom and creates a foundation for who they are constructed to be. Through exploring routine language and practices, this paper demonstrates that educators outlined a blueprint of kindergartners, which positioned students as learners in ways that became the ground for either a limited or a promising educational pathway for them.

Keywords: Behavior, early education, special education, critical discourse analysis.

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Authors: Maziar Ahmad Sharbafi, Caro Lucas, Abolfazel Toroghi Haghighat, Omid AmirGhiasvand, Omid Aghazade

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RoboCup Rescue simulation as a large-scale Multi agent system (MAS) is one of the challenging environments for keeping coordination between agents to achieve the objectives despite sensing and communication limitations. The dynamicity of the environment and intensive dependency between actions of different kinds of agents make the problem more complex. This point encouraged us to use learning-based methods to adapt our decision making to different situations. Our approach is utilizing reinforcement leaning. Using learning in rescue simulation is one of the current ways which has been the subject of several researches in recent years. In this paper we present an innovative learning method implemented for Police Force (PF) Agent. This method can cope with the main difficulties that exist in other learning approaches. Different methods used in the literature have been examined. Their drawbacks and possible improvements have led us to the method proposed in this paper which is fast and accurate. The Brain Emotional Learning Based Intelligent Controller (BELBIC) is our solution for learning in this environment. BELBIC is a physiologically motivated approach based on a computational model of amygdale and limbic system. The paper presents the results obtained by the proposed approach, showing the power of BELBIC as a decision making tool in complex and dynamic situation.

Keywords: Emotional learning, rescue, simulation environment, RoboCup, multi-agent system.

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