Search results for: absolute efficiency

Authors: G. Dottavio, M. F. Andrade, F. Renard, V. Cheutet, A.-L. Ladier, S. Vercraene, P. Hoang, S. Briet, R. Dachicourt, Y. Baizet

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An important number of technological equipment and high-skilled workers over long periods of time have to be mobilized during nuclear decommissioning processes. The related operations generate complex flows of waste and high inventory levels, associated to information flows of heterogeneous types. Taking into account that more than 10 decommissioning operations are on-going in France and about 50 are expected toward 2025: A big challenge is addressed today. The management of decommissioning and dismantling of nuclear installations represents an important part of the nuclear-based energy lifecycle, since it has an environmental impact as well as an important influence on the electricity cost and therefore the price for end-users. Bringing new technologies and new solutions into decommissioning methodologies is thus mandatory to improve the quality, cost and delay efficiency of these operations. The purpose of our project is to improve decommissioning management efficiency by developing a decision-support framework dedicated to plan nuclear facility decommissioning operations and to optimize waste evacuation by means of a logistic approach. The target is to create an easy-to-handle tool capable of i) predicting waste flows and proposing the best decommissioning logistics scenario and ii) managing information during all the steps of the process and following the progress: planning, resources, delays, authorizations, saturation zones, waste volume, etc. In this article we present our results from waste nuclear flows simulation during decommissioning process, including discrete-event simulation supported by FLEXSIM 3-D software. This approach was successfully tested and our works confirms its ability to improve this type of industrial process by identifying the critical points of the chain and optimizing it by identifying improvement actions. This type of simulation, executed before the start of the process operations on the basis of a first conception, allow ‘what-if’ process evaluation and help to ensure quality of the process in an uncertain context. The simulation of nuclear waste flows before evacuation from the site will help reducing the cost and duration of the decommissioning process by optimizing the planning and the use of resources, transitional storage and expensive radioactive waste containers. Additional benefits are expected for the governance system of the waste evacuation since it will enable a shared responsibility of the waste flows.

Keywords: nuclear decommissioning, logistical optimization, decision-support framework, waste management

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Authors: Milijana N. Miljkovic, Viktorija M. Dragojevic-Simic, Nemanja K. Rancic, Vesna M. Jacevic, Snezana B. Djordjevic, Momir M. Mikov, Aleksandra M. Kovacevic

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Itraconazole (ITZ) is a weak base and extremely lipophilic compound, with water solubility as a rate-limiting step in its absorption from the gastrointestinal tract. Its absolute bioavailability, about 55%, is maximal when its oral formulation, capsules, are taken immediately after a full meal. Peak plasma concentrations (Cmax) are reached within 2 to 5 hrs after their administration. ITZ undergoes extensive hepatic metabolism by human CYP3A4 isoenzyme and more than 30 different metabolites have been identified. One of the main ones is hydroxyitraconazole (HITZ), in which plasma concentrations are almost twice higher than those of ITZ. Gender differences in drug PK (Pharmacokinetics) have already been recognized, but variations in metabolism are believed to be their major cause. The aim of the study was to investigate the influence of gender on ITZ PK parameters after administration of oral capsule formulation, following 100 mg single dosing in healthy adult volunteers under fed conditions. The single-center, open-label PK study was performed. PK analyses included PK parameters obtained after a single 100 mg dose administration of itraconazole capsules to 48 females and 66 males. Blood samples were collected at pre-dose and up to 72.0 h after administration (1.0, 2.0, 3.0, 3.5, 4.0, 4.5, 5.0, 5.5, 6.0, 7.0, 9.0, 12.0, 24.0, 36.0 and 72.0 hrs). The calculated pharmacokinetic parameters, based on the plasma concentrations of itraconazole and hydroxyitraconazole, were Cmax, AUClast, and AUCtot. Plasma concentrations of ITZ and HITZ were determined using a validated liquid chromatographic method with mass spectrometric detection, while pharmacokinetic parameters were estimated using non-compartmental methods. The pharmacokinetic analyses were performed using Kinetica software version 5.0. The mean value of ITZ Cmaxmen was 74.79 ng/ml, and Cmaxwomen was 51.291 ng/ml (independent samples test; p = 0.005). Hydroxyitraconazole had a mean value of Cmaxmen 106.37 ng/ml, and the mean value Cmaxwomen was 70.05 ng/ml. Women had, on average, lower AUClast and Cmax than men. AUClastmen for ITZ was 736.02 ng/mL*h and AUClastwomen was 566.62 ng/mL*h, while AUClastmen for HITZ was 1154.80 was ng/mL*h and AUClastwomen for HITZ was 708.12 ng/mL*h (independent samples test; p = 0.033). The mean values of ITZ AUCtotmen were 884.73 ng/mL*h and AUCtotwomen was 685.10 ng/mL*h. AUCtotmen for HITZ was 1290.41 ng/mL*h, while AUCtotwomen for HIZT was 788.60 ng/mL*h (p < 0.001). The results could point out to lower oral bioavailability of ITZ in women, since values of Cmax, AUClast, and AUCtot of both ITZ and HITZ were significantly lower in women than in men, respectively. The reason may be higher expression and activity of CYP3A4 in women than in men, but there also may be differences in other PK parameters. High variability of both ITZ and HITZ concentrations in both genders confirmed that ITZ is a highly variable drug. Further examinations of its PK are needed to justify strategies for therapeutic drug monitoring in patients treated by this antifungal agent.

Keywords: itraconazole, gender, hydroxyitraconazole, pharmacokinetics

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Authors: Tayo P. Ogundunmade, Adedayo A. Adepoju

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Terrorist attacks in liberal democracies bring about a few pessimistic results, for example, sabotaged public support in the governments they target, disturbing the peace of a protected environment underwritten by the state, and a limitation of individuals from adding to the advancement of the country, among others. Hence, seeking for techniques to understand the different factors involved in terrorism and how to deal with those factors in order to completely stop or reduce terrorist activities is the topmost priority of the government in every country. This research aim is to develop an efficient deep learning-based predictive model for the prediction of future terrorist activities in Nigeria, addressing low-quality prediction accuracy problems associated with the existing solution methods. The proposed predictive AI-based model as a counterterrorism tool will be useful by governments and law enforcement agencies to protect the lives of individuals in society and to improve the quality of life in general. A Heterogeneous Bayesian Neural Network (HETBNN) model was derived with Gaussian error normal distribution. Three primary transfer functions (HOTTFs), as well as two derived transfer functions (HETTFs) arising from the convolution of the HOTTFs, are namely; Symmetric Saturated Linear transfer function (SATLINS ), Hyperbolic Tangent transfer function (TANH), Hyperbolic Tangent sigmoid transfer function (TANSIG), Symmetric Saturated Linear and Hyperbolic Tangent transfer function (SATLINS-TANH) and Symmetric Saturated Linear and Hyperbolic Tangent Sigmoid transfer function (SATLINS-TANSIG). Data on the Terrorist activities in Nigeria gathered through questionnaires for the purpose of this study were used. Mean Square Error (MSE), Mean Absolute Error (MAE) and Test Error are the forecast prediction criteria. The results showed that the HETFs performed better in terms of prediction and factors associated with terrorist activities in Nigeria were determined. The proposed predictive deep learning-based model will be useful to governments and law enforcement agencies as an effective counterterrorism mechanism to understand the parameters of terrorism and to design strategies to deal with terrorism before an incident actually happens and potentially causes the loss of precious lives. The proposed predictive AI-based model will reduce the chances of terrorist activities and is particularly helpful for security agencies to predict future terrorist activities.

Keywords: activation functions, Bayesian neural network, mean square error, test error, terrorism

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Authors: Zhang Haitao

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The different size of nanoparticle mordenite zeolites were prepared by adding different soft template during hydrothermal process for carbonylation of dimethyl ether (DME) to methyl acetate (MA). The catalysts were characterized by X-ray diffraction, Ar adsorption-desorption, high-resolution transmission electron microscopy, NH3-temperature programmed desorption, scanning electron microscopy and Thermogravimetric. The characterization results confirmed that mordenite zeolites with small nanoparticle showed more strong acid sites which was the active site for carbonylation thus promoting conversion of DME and MA selectivity. Furthermore, the nanoparticle mordenite had increased the mass transfer efficiency which could suppress the formation of coke.

Keywords: nanoparticle mordenite, carbonylation, dimethyl ether, methyl acetate

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Authors: Mehrnaz Mostafavi

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Perovskite nanocrystals and quantum dots have emerged as leaders in the field of photovoltaic technologies, demonstrating exceptional light-harvesting abilities and stability. This study investigates the substantial progress and potential of these nano-sized materials in transforming solar energy conversion. The research delves into the foundational characteristics and production methods of perovskite nanocrystals and quantum dots, elucidating their distinct optical and electronic properties that render them well-suited for photovoltaic applications. Specifically, it examines their outstanding light absorption capabilities, enabling more effective utilization of a wider solar spectrum compared to traditional silicon-based solar cells. Furthermore, this paper explores the improved durability achieved in perovskite nanocrystals and quantum dots, overcoming previous challenges related to degradation and inconsistent performance. Recent advancements in material engineering and techniques for surface passivation have significantly contributed to enhancing the long-term stability of these nanomaterials, making them more commercially feasible for solar cell usage. The study also delves into the advancements in device designs that incorporate perovskite nanocrystals and quantum dots. Innovative strategies, such as tandem solar cells and hybrid structures integrating these nanomaterials with conventional photovoltaic technologies, are discussed. These approaches highlight synergistic effects that boost efficiency and performance. Additionally, this paper addresses ongoing challenges and research endeavors aimed at further improving the efficiency, stability, and scalability of perovskite nanocrystals and quantum dots in photovoltaics. Efforts to mitigate concerns related to material degradation, toxicity, and large-scale production are actively pursued, paving the way for broader commercial application. In conclusion, this paper emphasizes the significant role played by perovskite nanocrystals and quantum dots in advancing photovoltaic technologies. Their exceptional light-harvesting capabilities, combined with increased stability, promise a bright future for next-generation solar cells, ushering in an era of highly efficient and cost-effective solar energy conversion systems.

Keywords: perovskite nanocrystals, quantum dots, photovoltaic technologies, light-harvesting, solar energy conversion, stability, device designs

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Authors: Hongkui Li, Tongli Lu , Jianwu Zhang

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This paper focuses on developing an estimation method of clutch drag torque in wet DCT. The modelling of clutch drag torque is investigated. As the main factor affecting the clutch drag torque, dynamic viscosity of oil is discussed. The paper proposes an estimation method of clutch drag torque based on recursive least squares by utilizing the dynamic equations of gear shifting synchronization process. The results demonstrate that the estimation method has good accuracy and efficiency.

Keywords: clutch drag torque, wet DCT, dynamic viscosity, recursive least squares

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Authors: Salomão Manuel Francisco, Manuel António Salgueiro Da Silva, Bento Filipe Barreiras Pinto Cavadas, Teresa Monteiro Seixas

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In bachelor's degrees in Physics Education framework in Angola, and to a certain extent, within the community of Portuguese language countries (CPLP), teaching methodologies rely heavily on theoretical memorization and mathematical demonstrations. This approach often discourages students, particularly the female population, as the reliance on theoretical mathematical demonstrations generates the perception of Physics as an arduous, challenging discipline. To address this challenge and recognize the value of practical application as an evaluative criterion of material truth, we propose a practical activity in Environmental Physics that will be shared with Angolan higher education teachers, who will receive full scaffolding and support from the authors. These teachers, adopting and developing similar activities in a classroom setting, will contribute to the environmental education framework as well. Additionally, this work aligns with different goals of UNESCO's 2030 agenda, namely, specifically, goals 4, 5, 7, 11, 13, and 17. The experimental activity developed in this work is centered around the demonstration of the photovoltaic effect and its application for renewable energy production. The first objective of the activity is to study the variation of electrical power supplied by a photovoltaic system (PV) to an electrical circuit as the angle of light incidence changes. Students can observe that the power supplied to the circuit is greater when light rays fall perpendicularly on the PV. However, as the angle of incidence increases, resulting in a larger area covered by the light rays, the power supplied to the circuit decreases due to lower irradiance. The second objective is to demonstrate that the power output can be maximized by adjusting the circuit load resistance at each irradiance value. In these two parts of the activity, students can analyze experimental data taking into account the irradiance law and the equivalent circuit description of a PV cell. Through detailed data analysis, students are also expected to assess the effects of temperature on PV efficiency degradation and the efficiency enhancement provided by light concentration mechanisms. As a third objective, students can explore how the color of incident light affects the PV output power, considering the quantum nature of light and its interaction with the PV system.

Keywords: experiments, irradiation law, physic teaching, photovoltaic effect

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Authors: Shoji Katagiri, Hugang Han

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This paper clarifies the role of ICT capital in Economic Growth. Albeit ICT remarkably contributes to economic growth, there are few studies on ICT capital in ICT sector from theoretical point of view. In this paper, production function of ICT which is used as input of intermediate good in final good and ICT sectors is incorporated into our model. In this setting, we analyze the role of ICT on balance growth path and show the possibility of general equilibrium solutions for this model. Through the simulation of the equilibrium solutions, we find that when ICT impacts on economy and economic growth increases, it is necessary that increases of efficiency at ICT sector and of accumulation of non-ICT and ICT capitals occur simultaneously.

Keywords: endogenous economic growth, ICT, intensity, capital accumulation

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Authors: Ioannis P. Panapakidis, Marios N. Moschakis

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With the continuous increment of smart meter installations across the globe, the need for processing of the load data is evident. Clustering-based load profiling is built upon the utilization of unsupervised machine learning tools for the purpose of formulating the typical load curves or load profiles. The most commonly used algorithm in the load profiling literature is the K-means. While the algorithm has been successfully tested in a variety of applications, its drawback is the strong dependence in the initialization phase. This paper proposes a novel modified form of the K-means that addresses the aforementioned problem. Simulation results indicate the superiority of the proposed algorithm compared to the K-means.

Keywords: clustering, load profiling, load modeling, machine learning, energy efficiency and quality

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Authors: Jalil ur Rehman, Ramesh C. Tailor, Muhammad Isa Khan, Jahnzeeb Ashraf, Muhammad Afzal, Geofferry S. Ibbott

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Purpose: The purpose of this analysis was to investigate dose distribution of different techniques (3D-CRT, IMRT and VMAT) of head and neck cancer using 3-dimensional dosimeter called PRESAGETM Dosimeter. Materials and Methods: Computer tomography (CT) scans of radiological physics center (RPC) head and neck anthropomorphic phantom with both RPC standard insert and PRESAGETM insert were acquired separated with Philipp’s CT scanner and both CT scans were exported via DICOM to the Pinnacle version 9.4 treatment planning system (TPS). Each plan was delivered twice to the RPC phantom first containing the RPC standard insert having TLD and film dosimeters and then again containing the Presage insert having 3-D dosimeter (PRESAGETM) by using a Varian True Beam linear accelerator. After irradiation, the standard insert including point dose measurements (TLD) and planar Gafchromic® EBT film measurement were read using RPC standard procedure. The 3D dose distribution from PRESAGETM was read out with the Duke Midsized optical scanner dedicated to RPC (DMOS-RPC). Dose volume histogram (DVH), mean and maximal doses for organs at risk were calculated and compared among each head and neck technique. The prescription dose was same for all head and neck radiotherapy techniques which was 6.60 Gy/friction. Beam profile comparison and gamma analysis were used to quantify agreements among film measurement, PRESAGETM measurement and calculated dose distribution. Quality assurances of all plans were performed by using ArcCHECK method. Results: VMAT delivered the lowest mean and maximum doses to organ at risk (spinal cord, parotid) than IMRT and 3DCRT. Such dose distribution was verified by absolute dose distribution using thermoluminescent dosimeter (TLD) system. The central axial, sagittal and coronal planes were evaluated using 2D gamma map criteria(± 5%/3 mm) and results were 99.82% (axial), 99.78% (sagital), 98.38% (coronal) for VMAT plan and found the agreement between PRESAGE and pinnacle was better than IMRT and 3D-CRT plan excludes a 7 mm rim at the edge of the dosimeter. Profile showed good agreement for all plans between film, PRESAGE and pinnacle and 3D gamma was performed for PTV and OARs, VMAT and 3DCRT endow with better agreement than IMRT. Conclusion: VMAT delivered lowered mean and maximal doses to organs at risk and better PTV coverage during head and neck radiotherapy. TLD, EBT film and PRESAGETM dosimeters suggest that VMAT was better for the treatment of head and neck cancer than IMRT and 3D-CRT.

Keywords: RPC, 3DCRT, IMRT, VMAT, EBT2 film, TLD, PRESAGETM

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Authors: Elmo Thiago Lins Cöuras Ford, Valentina Alessandra Carvalho do Vale

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It presents a heating system using low cost alternative solar collectors to promote the disinfection of water in low income communities that take water contaminated by bacteria. The system consists of two solar collectors, with total area of 4 m² and was built using PET bottles and cans of beer and soft drinks. Each collector is made up of 8 PVC tubes, connected in series and work in continuous flow. It will determine the flux the most appropriate to generate the temperature to promote the disinfection. It will be presented results of the efficiency and thermal loss of system and results of analysis of water after undergoing the process of heating.

Keywords: Disinfection of water, solar heating system, poor communities, bioinformatics, biomedicine

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Authors: Arash Dalili, Hamed Tahmouressi, Mina Hoorfar

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Advances in lab-on-a-chip (LOC) devices have led to significant advances in the manipulation, separation, and isolation of particles and cells. Among the different active and passive particle manipulation methods, dielectrophoresis (DEP) has been proven to be a versatile mechanism as it is label-free, cost-effective, simple to operate, and has high manipulation efficiency. DEP has been applied for a wide range of biological and environmental applications. A popular form of DEP devices is the continuous manipulation of particles by using co-planar slanted electrodes, which utilizes a sheath flow to focus the particles into one side of the microchannel. When particles enter the DEP manipulation zone, the negative DEP (nDEP) force generated by the slanted electrodes deflects the particles laterally towards the opposite side of the microchannel. The lateral displacement of the particles is dependent on multiple parameters including the geometry of the electrodes, the width, length and height of the microchannel, the size of the particles and the throughput. In this study, COMSOL Multiphysics® modeling along with experimental studies are used to investigate the effect of the aforementioned parameters. The electric field between the electrodes and the induced DEP force on the particles are modelled by COMSOL Multiphysics®. The simulation model is used to show the effect of the DEP force on the particles, and how the geometry of the electrodes (width of the electrodes and the gap between them) plays a role in the manipulation of polystyrene microparticles. The simulation results show that increasing the electrode width to a certain limit, which depends on the height of the channel, increases the induced DEP force. Also, decreasing the gap between the electrodes leads to a stronger DEP force. Based on these results, criteria for the fabrication of the electrodes were found, and soft lithography was used to fabricate interdigitated slanted electrodes and microchannels. Experimental studies were run to find the effect of the flow rate, geometrical parameters of the microchannel such as length, width, and height as well as the electrodes’ angle on the displacement of 5 um, 10 um and 15 um polystyrene particles. An empirical equation is developed to predict the displacement of the particles under different conditions. It is shown that the displacement of the particles is more for longer and lower height channels, lower flow rates, and bigger particles. On the other hand, the effect of the angle of the electrodes on the displacement of the particles was negligible. Based on the results, we have developed an optimum design (in terms of efficiency and throughput) for three size separation of particles.

Keywords: COMSOL Multiphysics, Dielectrophoresis, Microfluidics, Particle separation

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Authors: Mansoureh Ghiasabadi Farahani, Samira Kalantary, Sara Taghi-Pour, Mahboubeh Shamsi

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Nowadays, the development of computers technology and its recent applications provide access to new types of data, which have not been considered by the traditional data analysts. Two particularly interesting characteristics of such data sets include their huge size and streaming nature .Incremental learning techniques have been used extensively to address the data stream classification problem. This paper presents a concise survey on the obstacles and the requirements issues classifying data streams with using decision tree. The most important issue is to maintain a balance between accuracy and efficiency, the algorithm should provide good classification performance with a reasonable time response.

Keywords: big data, data streams, classification, decision tree

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Authors: Shaoxi Wang, Pouya Rezai

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High aspect ratio is the necessary parts of complex microstructures. Some methods available to achieve high aspect ratio requires expensive materials or complex process; others is difficult to research simple high aspect ratio structures. The paper presents a simple and cheap two-step Polydimethylsioxane (PDMS) transferring process to get high aspect ratio single pillars, which only requires covering the PDMS mold with Brij@52 surface solution. The experimental results demonstrate the method efficiency and effective.

Keywords: high aspect ratio, microstructure, PDMS, Brij

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Authors: Sarah Abdourraziq

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To improve the efficiency of photovoltaic pumping system, more attention has been paid to their setting up. This paper presents an optimal technique to establish an efficient system under different conditions of irradiance and temperature. The state of place should be carefully studied before stage of installation of the over system: local climate, boreholes, soil, crops and water resources. The studied system consists of a PV panel, a DC-DC boost converter, a DC motor-pump, and storage tank. The concepts shown in this paper presents a support for an optimal installation of each solar pump.

Keywords: photovoltaic pumping system, optimal implementation, boost converter, motor-pump

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Authors: B. Sellami, Y. Laskri, M. Belloufi

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Conjugate gradient methods are an important class of methods for unconstrained optimization, especially for large-scale problems. Recently, they have been much studied. In this paper, a new family of conjugate gradient method is proposed for unconstrained optimization. This method includes the already existing two practical nonlinear conjugate gradient methods, which produces a descent search direction at every iteration and converges globally provided that the line search satisfies the Wolfe conditions. The numerical experiments are done to test the efficiency of the new method, which implies the new method is promising. In addition the methods related to this family are uniformly discussed.

Keywords: conjugate gradient method, global convergence, line search, unconstrained optimization

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Authors: Saidi Nabiha, Khaled Zaatouri, Walid Fajraoui, Tahar Ezzeddine

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The market of Wireless Sensor Network WSN has a great potential and development opportunities. Researchers are focusing on optimization in many fields like efficient deployment and routing protocols. In this article, we will concentrate on energy efficiency for WSN because WSN nodes are habitually deployed in severe No Man’s Land with batteries are not rechargeable, so reducing energy consumption represents an important challenge to extend the life of the network. We will present the design of new WSN mote based on ultra low power STM32L microcontrollers and the ZIGBEE transceiver CC2520. We will compare it to existent motes and we will conclude that our mote is promising in energy consumption.

Keywords: component, WSN mote, power consumption, STM32L, sensors, CC2520

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Authors: Bharti Verma, Chandrajit Balomajumder

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Water pollution is escalated owing to industrialization and random ejection of one or more toxic heavy metal ions from the semiconductor industry, electroplating, metallurgical, mining, chemical manufacturing, tannery industries, etc., In semiconductor industry various kinds of chemicals in wafers preparation are used . Fluoride, toxic solvent, heavy metals, dyes and salts, suspended solids and chelating agents may be found in wastewater effluent of semiconductor manufacturing industry. Also in the chrome plating, in the electroplating industry, the effluent contains heavy amounts of Chromium. Since Cr(VI) is highly toxic, its exposure poses an acute risk of health. Also, its chronic exposure can even lead to mutagenesis and carcinogenesis. On the contrary, Cr (III) which is naturally occurring, is much less toxic than Cr(VI). Discharge limit of hexavalent chromium and trivalent chromium are 0.05 mg/L and 5 mg/L, respectively. There are numerous methods such as adsorption, chemical precipitation, membrane filtration, ion exchange, and electrochemical methods for the heavy metal removal. The present study focuses on the removal of Chromium ions by using flat sheet UF5kDa membrane. The Ultra filtration membrane process is operated above micro filtration membrane process. Thus separation achieved may be influenced due to the effect of Sieving and Donnan effect. Ultrafiltration is a promising method for the rejection of heavy metals like chromium, fluoride, cadmium, nickel, arsenic, etc. from effluent water. Benefits behind ultrafiltration process are that the operation is quite simple, the removal efficiency is high as compared to some other methods of removal and it is reliable. Polyamide membranes have been selected for the present study on rejection of Cr(VI) from feed solution. The objective of the current work is to examine the rejection of Cr(VI) from aqueous feed solutions by flat sheet UF5kDa membranes with different parameters such as pressure, feed concentration and pH of the feed. The experiments revealed that with increasing pressure, the removal efficiency of Cr(VI) is increased. Also, the effect of pH of feed solution, the initial dosage of chromium in the feed solution has been studied. The membrane has been characterized by FTIR, SEM and AFM before and after the run. The mass transfer coefficients have been estimated. Membrane transport parameters have been calculated and have been found to be in a good correlation with the applied model.

Keywords: heavy metal removal, membrane process, waste water treatment, ultrafiltration

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Authors: Raymond Treacy, Paul Humphreys, Ronan McIvor, Trevor Cadden, Alan McKittrick

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This study employed event study methodology to examine the role of institutions, resources and dynamic capabilities in the relationship between the Environmental Management System ISO 14001 adoption and firm performance. Utilising financial data from 140 ISO 14001 certified firms and 320 non-certified firms, the results of the study suggested that the UK and Irish manufacturers were not implementing ISO 14001 solely to gain legitimacy. In contrast, the results demonstrated that firms were fully integrating the ISO 14001 standard within their operations as certified firms were able to improve both financial and operating performance when compared to non-certified firms. However, while there were significant and long lasting improvements for employee productivity, manufacturing cost efficiency, return on assets and sales turnover, the sample firms operating cycle and fixed asset efficiency displayed evidence of diminishing returns in the long-run, underlying the observation that no operating advantage based on incremental improvements can be everlasting. Hence, there is an argument for investing in dynamic capabilities which help renew and refresh the resource base and help the firm adapt to changing environments. Indeed, the results of the regression analysis suggest that dynamic capabilities for innovation acted as a moderator in the relationship between ISO 14001 certification and firm performance. This, in turn, will have a significant and symbiotic influence on sustainability practices within the participating organisations. The study not only provides new and original insights, but demonstrates pragmatically how firms can take advantage of environmental management systems as a moderator to significantly enhance firm performance. However, while it was shown that firm innovation aided both short term and long term ROA performance, adaptive market capabilities only aided firms in the short-term at the marketing strategy deployment stage. Finally, the results have important implications for firms operating in an economic recession as the results suggest that firms should scale back investment in R&D while operating in an economic downturn. Conversely, under normal trading conditions, consistent and long term investments in R&D was found to moderate the relationship between ISO 14001 certification and firm performance. Hence, the results of the study have important implications for academics and management alike.

Keywords: supply chain management, environmental management systems, quality management, sustainability, firm performance

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Authors: Ammar Khader Almasri

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The software processes play a vital role for delivering a high quality software system that meets the user’s needs. There are many software development models which are used by most system developers, which can be categorized into two categories (traditional and new methodologies). Mobile applications like other desktop applications need appropriate and well-working software development process. Nevertheless, mobile applications have different features which limit their performance and efficiency like application size, mobile hardware features. Moreover, this research aims to help developers in using a standardized model for developing mobile applications.

Keywords: software development process, agile methods , moblile application development, traditional methods

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Authors: Sana Almi, Djamel Barkat

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The solvent extraction of cobalt (II) and nickel (II) from aqueous sulfate solutions were investigated with the analytical methods of slope analysis using salicylidene aniline and the three isomeric o-, m- and p-salicylidene toluidine diluted with chloroform at 25°C. By a statistical analysis of the extraction data, it was concluded that the extracted species are CoL2 with CoL2(HL) and NiL2 (HL denotes HSA, HSOT, HSMT, and HSPT). The extraction efficiency of Co(II) was higher than Ni(II). This tendency is confirmed from numerical extraction constants for each metal cations. The best extraction was according to the following order: HSMT > HSPT > HSOT > HSA for Co2+ and Ni2+.

Keywords: solvent extraction, nickel(II), cobalt(II), salicylidene aniline, o-, m-, and p-salicylidene toluidine

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Authors: Xiangtuo Chen, Paul-Henry Cournéde

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Crop yield prediction is a paramount issue in agriculture. The main idea of this paper is to find out efficient way to predict the yield of corn based meteorological records. The prediction models used in this paper can be classified into model-driven approaches and data-driven approaches, according to the different modeling methodologies. The model-driven approaches are based on crop mechanistic modeling. They describe crop growth in interaction with their environment as dynamical systems. But the calibration process of the dynamic system comes up with much difficulty, because it turns out to be a multidimensional non-convex optimization problem. An original contribution of this paper is to propose a statistical methodology, Multi-Scenarios Parameters Estimation (MSPE), for the parametrization of potentially complex mechanistic models from a new type of datasets (climatic data, final yield in many situations). It is tested with CORNFLO, a crop model for maize growth. On the other hand, the data-driven approach for yield prediction is free of the complex biophysical process. But it has some strict requirements about the dataset. A second contribution of the paper is the comparison of these model-driven methods with classical data-driven methods. For this purpose, we consider two classes of regression methods, methods derived from linear regression (Ridge and Lasso Regression, Principal Components Regression or Partial Least Squares Regression) and machine learning methods (Random Forest, k-Nearest Neighbor, Artificial Neural Network and SVM regression). The dataset consists of 720 records of corn yield at county scale provided by the United States Department of Agriculture (USDA) and the associated climatic data. A 5-folds cross-validation process and two accuracy metrics: root mean square error of prediction(RMSEP), mean absolute error of prediction(MAEP) were used to evaluate the crop prediction capacity. The results show that among the data-driven approaches, Random Forest is the most robust and generally achieves the best prediction error (MAEP 4.27%). It also outperforms our model-driven approach (MAEP 6.11%). However, the method to calibrate the mechanistic model from dataset easy to access offers several side-perspectives. The mechanistic model can potentially help to underline the stresses suffered by the crop or to identify the biological parameters of interest for breeding purposes. For this reason, an interesting perspective is to combine these two types of approaches.

Keywords: crop yield prediction, crop model, sensitivity analysis, paramater estimation, particle swarm optimization, random forest

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Authors: Ali Mausmi, Ahmed Abbou, Rachid El Akhrif

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This research paper aims to reduce the chattering phenomenon due to control by sliding mode control applied on a wind energy conversion system based on the doubly fed induction generator (DFIG). Our goal is to offset the effect of parametric uncertainties and come as close as possible to the dynamic response solicited by the control law in the ideal case and therefore force the active and reactive power generated by the DFIG to accurately follow the reference values which are provided to it. The simulation results using Matlab / Simulink demonstrate the efficiency and performance of the proposed technique while maintaining the simplicity of control by first order sliding mode.

Keywords: control of speed, correction of the equivalent command, induction generator, sliding mode

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Authors: Aidin Foroutan, David S. Wishart, Leluo L. Guan, Carolyn Fitzsimmons

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Maximizing efficiency and growth potential of beef cattle requires not only genetic selection (i.e. residual feed intake (RFI)) but also adequate nutrition throughout all stages of growth and development. Nutrient restriction during gestation has been shown to negatively affect post-natal growth and development as well as fertility of the offspring. This, when combined with RFI may affect progeny traits. This study aims to investigate the impact of selection for divergent genetic potential for RFI and maternal nutrition during early- to mid-gestation, on bull calf traits such as fertility and muscle development using multiple ‘omics’ approaches. Comparisons were made between High-diet vs. Low-diet and between High-RFI vs. Low-RFI animals. An epigenetics experiment on semen samples identified 891 biomarkers associated with growth and development. A gene expression study on Longissimus thoracis muscle, semimembranosus muscle, liver, and testis identified 4 genes associated with muscle development and immunity of which Myocyte enhancer factor 2A [MEF2A; induces myogenesis and control muscle differentiation] was the only differentially expressed gene identified in all four tissues. An initial metabolomics experiment on serum samples using nuclear magnetic resonance (NMR) identified 4 metabolite biomarkers related to energy and protein metabolism. Once all the biomarkers are identified, bioinformatics approaches will be used to create a database covering all the ‘omics’ data collected from this project. This database will be broadened by adding other information obtained from relevant literature reviews. Association analyses with these data sets will be performed to reveal key biological pathways affected by RFI and maternal nutrition. Through these association studies between the genome and metabolome, it is expected that candidate biomarker genes and metabolites for feed efficiency, fertility, and/or muscle development are identified. If these gene/metabolite biomarkers are validated in a larger animal population, they could potentially be used in breeding programs to select superior animals. It is also expected that this work will lead to the development of an online tool that could be used to predict future traits of interest in an animal given its measurable ‘omics’ traits.

Keywords: biomarker, maternal nutrition, omics, residual feed intake

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Authors: Moh'd Alodat

Abstract:

In this paper, we discuss the power function distribution and derive the maximum likelihood estimator of its parameter as well as the reliability parameter. We derive the large sample properties of the estimators based on the selective order statistic scheme. We conduct simulation studies to investigate the significance of the selective order statistic scheme in our setup and to compare the efficiency of the new proposed estimators.

Keywords: fisher information, maximum likelihood estimator, power function distribution, ranked set sampling, selective order statistics sampling

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Authors: Astari Indarsari, Bastian B. Purba, Muhammad Fadlilah

Abstract:

In Indonesian climates that have the tropic climate, one of the potential energy sources is coming from solar energy. From the solar energy, we can convert it into the others energy, such as electrical energy. In this topic, we want to do the research about Dye Sensitized Solar Cell (DSSC). The materials that we use as sensitizer is anthocyanin that we extract from apple skin, because the anthocyanin is one of the most effective as a sensitizer for DSSC. The variable in this research is pH. The pH that we used are pH 0,5; pH 1; pH 1,5; pH 2; pH 2,5. The method is electrolysis, and we use TiO2 as sensitized material. The hypothesis from this research is the smaller pH can make higher the efficiency of the absorbent of the solar energy.

Keywords: anthocyanin, TiO2, DSSC, apple skin

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Authors: Mariana L. de Araújo, Pedro P. M. Menezes

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Research on strategic human resource management (SHRM) has made progress in the last few decades, showing a relationship between policies and practices of human resource management (HRM) and improving organizational results. That's because demonstrating the effectiveness of any HRM or other organizational practice, which means the extent that this can operate as a tool to achieve organizational performance, is a complex and arduous task to execute. Even today, there isn't consensus about "effectiveness," and the tools to measure the effectiveness are disconnected and not convincing. It is not different from the performance management system (PMS) effectiveness. A disproportionate focus on specific criteria adopted and an accumulation of studies that don't relate to the others, which damages the development of the field. Therefore, it aimed to evaluate the effectiveness of the PMS through models, dimensions, criteria, and measures. The objective of this study is to propose a theoretical-integrative model for evaluating PMS based on the literature in the PMS field. So, the PRISMA protocol was applied to carry out a systematic review, resulting in 57 studies. After performing the content analysis, we identified six dimensions: learning, societal impact, reaction, financial results, operational results and transfer, and 22 categories. In this way, a theoretical-integrative model for assessing the effectiveness of PMS was proposed based on the findings of this study, in which it was possible to confirm that the effectiveness construct is somewhat complex when viewing that most of the reviewed studies considered multiple dimensions in their assessment. In addition, we identified that the most immediate and proximal results of PMS are the most adopted by the studies; conversely, the studies adopted less distal outcomes to assess the effectiveness of PMS. Another finding of this research is that the reviewed studies predominantly analyze from the individual or psychological perspective, even when it comes to criteria whose phenomena are at an organizational level. Therefore, this study converges with a trend recently identified when referring to a process of "psychologization" in which GP studies, in general, have demonstrated macro results of the GP system from an individual perspective. Therefore, given the identification of a methodological pattern, the predominant influence of individual and psychological aspects in studies on HRM in administration is highlighted, demonstrated by the reflection on the practically absolute way of measuring the effectiveness of PMS from perceptual and subjective measures. Therefore, based on the recognition of the patterns identified, the model proposed to promote studies on the subject more broadly and profoundly to broaden and deepen the perspective of the field of management's interests so that the evaluation of the effectiveness of PMS can promote inputs on the impact of the PMS system in organizational performance. Finally, the findings encourage reflections on assessing the effectiveness of PMS through the theoretical-integrative model developed so that the field can promote new theoretical and practical perspectives.

Keywords: performance management, strategic human resource management, effectiveness, organizational performance

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Authors: Fethi Benyettou, Abdelkader Aissat, M. A. Benammar

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In this work, we use Silvaco TCAD software for modeling and simulations of standard GaAs solar cell, InAs/GaAs and GaSb/GaAs p-i-n quantum dot solar cell. When comparing 20-layer InAs/GaAs, GaSb/GaAs quantum dots solar cells with standard GaAs solar cell, the conversion efficiency in simulation results increased from 16.48 % to 22.6% and 16.48% to 22.42% respectively. Also, the absorption range edge of photons with low energies extended from 900 nm to 1200 nm.

Keywords: SILVACO TCAD, the quantum dot, simulation, materials engineering

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Authors: Anuradha Banerjee

Abstract:

A mobile ad hoc network is an infrastructure less network, where nodes are free to move independently in any direction. The nodes have limited battery power; hence, we require energy efficient route discovery technique to enhance their lifetime and network performance. In this paper, we propose an energy-efficient route discovery technique CERD that greatly reduces the number of route requests flooded into the network and also gives priority to the route request packets sent from the routers that has communicated with the destination very recently, in single or multi-hop paths. This does not only enhance the lifetime of nodes but also decreases the delay in tracking the destination.

Keywords: ad hoc network, energy efficiency, flooding, node lifetime, route discovery

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Authors: Somveer Singh, Vineet Kumar Singh

Abstract:

We present a new model based on viscoelasticity for the Non-Newtonian fluids.We use a matrix formulated algorithm to approximate solutions of a class of partial integro-differential equations with the given initial and boundary conditions. Some numerical results are presented to simplify application of operational matrix formulation and reduce the computational cost. Convergence analysis, error estimation and numerical stability of the method are also investigated. Finally, some test examples are given to demonstrate accuracy and efficiency of the proposed method.

Keywords: Legendre Wavelets, operational matrices, partial integro-differential equation, viscoelasticity

Procedia PDF Downloads 328