Search results for: Effective band inference based power control algorithm (EBIA)

Authors: Liangliang Tang, Chang Xu, Xingying Chen

Abstract:

GaInAsSb cells probably show better performance than GaSb cells in low-temperature thermophotovoltaic systems due to lower bandgap; however, few experiments proved this phenomenon so far. In this paper, numerical simulation is used to evaluate GaInAsSb and GaSb cells with similar structures under different radiation temperatures. We found that GaInAsSb cells with n-type emitters show slightly higher output power densities compared with that of GaSb cells with n-type emitters below 1,550 K-blackbody radiation, and the power density of the later cells will suppress the formers above this temperature point. During the temperature range of 1,000~2,000 K, the efficiencies of GaSb cells are about twice of GaInAsSb cells if perfect filters are used to prevent the emission of the non-absorbed long wavelength photons. Several parameters that affect the GaInAsSb cell were analyzed, such as doping profiles, thicknesses of GaInAsSb epitaxial layer and surface recombination velocity. The non-p junctions, i.e., n-type emitters are better for GaInAsSb cell fabrication, which is similar to that of GaSb cells.

Keywords: Thermophotovoltaic cell, GaSb, GaInAsSb, diffused emitters.

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Authors: Eu Tteum Ha, Kwang Ryel Ryu

Abstract:

As smartphones are equipped with various sensors, there have been many studies focused on using these sensors to create valuable applications. Human activity recognition is one such application motivated by various welfare applications, such as the support for the elderly, measurement of calorie consumption, lifestyle and exercise patterns analyses, and so on. One of the challenges one faces when using smartphone sensors for activity recognition is that the number of sensors should be minimized to save battery power. In this paper, we show that a fairly accurate classifier can be built that can distinguish ten different activities by using only a single sensor data, i.e., the smartphone accelerometer data. The approach that we adopt to deal with this twelve-class problem uses various methods. The features used for classifying these activities include not only the magnitude of acceleration vector at each time point, but also the maximum, the minimum, and the standard deviation of vector magnitude within a time window. The experiments compared the performance of four kinds of basic multi-class classifiers and the performance of four kinds of ensemble learning methods based on three kinds of basic multi-class classifiers. The results show that while the method with the highest accuracy is ECOC based on Random forest.

Keywords: Ensemble learning, activity recognition, smartphone accelerometer.

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Authors: Andrei Ursachi, Dorin Bordeasu

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The Smart Grid Simulator is a computer software based on advance algorithms which has as the main purpose to lower the energy bill in the most optimized price efficient way as possible for private households, companies or energy providers. It combines the energy provided by a number of solar modules and wind turbines with the consumption of one household or a cluster of nearby households and information regarding weather conditions and energy prices in order to predict the amount of energy that can be produced by renewable energy sources and the amount of energy that will be bought from the distributor for the following day. The user of the system will not only be able to minimize his expenditures on energy factures, but also he will be informed about his hourly consumption, electricity prices fluctuation and money spent for energy bought as well as how much money he saved each day and since he installed the system. The paper outlines the algorithm that supports the Smart Grid Simulator idea and presents preliminary test results that supports the discussion and implementation of the system.

Keywords: Applied Science, Renewable energy sources, Smart Grid, Sustainable energy.

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Authors: Ren-Jieh Kuo, Chun-Shou Huang

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The research of juice flavor forecasting has become more important in China. Due to the fast economic growth in China, many different kinds of juices have been introduced to the market. If a beverage company can understand their customers’ preference well, the juice can be served more attractive. Thus, this study intends to introducing the basic theory and computing process of grapes juice flavor forecasting based on support vector regression (SVR). Applying SVR, BPN, and LR to forecast the flavor of grapes juice in real data shows that SVR is more suitable and effective at predicting performance.

Keywords: Flavor forecasting, artificial neural networks, support vector regression, grape juice flavor.

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Authors: D. Krishnaveni, M. Geetha Priya

Abstract:

Application of reversible logic in integrated circuits results in the improved optimization of power consumption. This technology can be put into use in a variety of low power applications such as quantum computing, optical computing, nano-technology, and Complementary Metal Oxide Semiconductor (CMOS) Very Large Scale Integrated (VLSI) design etc. Logic gates are the basic building blocks in the design of any logic network and thus integrated circuits. In this paper, reversible Dual Key Gate (DKG) and Dual key Gate Pair (DKGP) gates that work singly as full adder/full subtractor are used to realize the basic building blocks of logic circuits. Reversible full adder/subtractor and parallel adder/ subtractor are designed using other reversible gates available in the literature and compared with that of DKG & DKGP gates. Efficient performance of reversible logic circuits relies on the optimization of the key parameters viz number of constant inputs, garbage outputs and number of reversible gates. The full adder/subtractor and parallel adder/subtractor design with reversible DKGP and DKG gates results in least number of constant inputs, garbage outputs, and number of reversible gates compared to the other designs. Thus, this paper provides a threshold to build more complex arithmetic systems using these reversible logic gates, leading to the enhanced performance of computing systems.

Keywords: Low power CMOS, quantum computing, reversible logic gates, full adder, full subtractor, parallel adder/subtractor, basic gates, universal gates.

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Authors: Amir Saber Gharamaleki, Beitollah Alipour, Zeinab Faghfoori, Ahmad YariKhosroushahi

Abstract:

Colorectal cancer (CRC) is one of the most prevalent cancers and intestinal microbial community plays an important role in colorectal tumorigenesis. Probiotics have recently been assessed as effective anti-proliferative agents and thus this study was performed to examine whether CRC undergo apoptosis by treating with isolated Iranian native dairy yeast, Kluyveromyces marxianus YAS, secretion metabolites. The cytotoxicity assessments on cells (HT-29, Caco-2) were accomplished through 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay as well as qualitative DAPI (4',6-diamidino-2-phenylindole staining) and quantitative (flow cytometry assessments) evaluations of apoptosis. To evaluate the main mechanism of apoptosis, Real time PCR method was applied. Kluyveromyces marxianus YAS secretions (IC50) showed significant cytotoxicity against HT-29 and Caco-2 cancer cell lines (66.57 % and 66.34 % apoptosis) similar to 5-Fluorouracil (5-FU) while apoptosis only was developed in 27.57 % of KDR normal cells. The prophylactic effects of Kluyveromyces marxianus (PTCC 5195), as a reference yeast, was not similar to Kluyveromyces marxianus YAS indicating strain dependency of bioactivities on CRC disease prevention. Based on real time PCR results, the main cytotoxicity is related to apoptosis phenomenon and the core related mechanism is depended on the overexpression of BAX, CASP 9, CASP 8 and CASP 3 inducing apoptosis genes. However, several investigations should be conducted to precisely determine the effective compounds to be used as anticancer therapeutics in the future.

Keywords: Anticancer, anti-proliferative, apoptosis, cytotoxicity, yeast.

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Authors: Yu-Shuai Chen , Chien-Ching Chiu , Chung-Hsin Huang, Chien-Hung Chen

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The bit error rate (BER) performance for ultra-wide band (UWB) indoor communication with impact of metallic furniture is investigated. The impulse responses of different indoor environments for any transmitter and receiver location are computed by shooting and bouncing ray/image and inverse Fourier transform techniques. By using the impulse responses of these multipath channels, the BER performance for binary pulse amplitude modulation (BPAM) impulse radio UWB communication system are calculated. Numerical results have shown that the multi-path effect by the metallic cabinets is an important factor for BER performance. Also the outage probability for the UWB multipath environment with metallic cabinets is more serious (about 18%) than with wooden cabinets. Finally, it is worth noting that in these cases the present work provides not only comparative information but also quantitative information on the performance reduction.

Keywords: UWB, multipath, outage probability.

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Authors: Jian Yao

Abstract:

The purpose of this paper is to investigate the adjust- ment of solar shading devices in office buildings in two different seasons by occupants, and its influence on the lighting control and indoor illuminance levels. The results show that occupants take inappropriate measures both in reducing solar radiation in summer and in admitting solar gains in winter, resulting in an increase in lighting energy and a reduction in indoor illuminance. Therefore, movable shading devices, controlled automatically, are suitable for building applications to reduce energy consumption.

Keywords: Solar shading, adjustment, lighting control, indoor illuminance.

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Authors: Kandpal M. , Gundampati R. K , Debnath M.

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Microbial contamination, most of which are fecal born in drinking water and food industry is a serious threat to humans. Escherichia coli is one of the most common and prevalent among them. We have developed a sensor for rapid and an early detection of contaminants, taking E.coli as a threat indicator organism. The sensor is based on co-polymerizations of aniline and formaldehyde in form of thin film over glass surface using the vacuum deposition technique. The particular doping combination of thin film with Fe-Al and Fe-Cu in different concentrations changes its non conducting properties to p- type semi conductor. This property is exploited to detect the different contaminants, believed to have the different surface charge. It was found through experiments that different microbes at same OD (0.600 at 600 nm) have different conductivity in solution. Also the doping concentration is found to be specific for attracting microbes on the basis of surface charge. This is a simple, cost effective and quick detection method which not only decreases the measurement time but also gives early warnings for highly contaminated samples.

Keywords: Sensor, Vacuum deposition technique, thin film, E.coli detection, doping concentration.

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Authors: S. Saisundar, Shan Jiang, Kevin T. C. Chai, David Nuttman, Minkyu Je

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Keywords: Analog to digital converter, cyclic, gain-boosting, pipelined.

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Authors: R. Sharma, M. Gopal

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Markov games can be effectively used to design controllers for nonlinear systems. The paper presents two novel controller design algorithms by incorporating ideas from gametheory literature that address safety and consistency issues of the 'learned' control strategy. A more widely used approach for controller design is the H∞ optimal control, which suffers from high computational demand and at times, may be infeasible. We generate an optimal control policy for the agent (controller) via a simple Linear Program enabling the controller to learn about the unknown environment. The controller is facing an unknown environment and in our formulation this environment corresponds to the behavior rules of the noise modeled as the opponent. Proposed approaches aim to achieve 'safe-consistent' and 'safe-universally consistent' controller behavior by hybridizing 'min-max', 'fictitious play' and 'cautious fictitious play' approaches drawn from game theory. We empirically evaluate the approaches on a simulated Inverted Pendulum swing-up task and compare its performance against standard Q learning.

Keywords: Fictitious Play, Cautious Fictitious Play, InvertedPendulum, Controller, Markov Games, Mobile Robot.

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Authors: Bharat Raj Singh, Onkar Singh

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This paper details a new concept of using compressed air as a potential zero pollution power source for motorbikes. In place of an internal combustion engine, the motorbike is equipped with an air turbine transforms the energy of the compressed air into shaft work. The mathematical modeling and performance evaluation of a small capacity compressed air driven vaned type novel air turbine is presented in this paper. The effect of isobaric admission and adiabatic expansion of high pressure air for different rotor diameters, casing diameters and ratio of rotor to casing diameters of the turbine have been considered and analyzed. It is concluded that the work output is found optimum for some typical values of rotor / casing diameter ratios. In this study, the maximum power works out to 3.825 kW (5.20 HP) for casing diameter of 200 mm and rotor to casing diameter ratio of 0.65 to 0.60 which is sufficient to run motorbike.

Keywords: zero pollution, compressed air, air turbine, injectionangle, rotor / casing diameter ratio.

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Authors: Kyaw Myo Lin

Abstract:

This paper presents small signal stability study carried over the 140-Bus, 31-Machine, 5-Area MEPE system and validated on free and open source software: PSAT. Well-established linearalgebra analysis, eigenvalue analysis, is employed to determine the small signal dynamic behavior of test system. The aspects of local and interarea oscillations which may affect the operation and behavior of power system are analyzed. Eigenvalue analysis is carried out to investigate the small signal behavior of test system and the participation factors have been determined to identify the participation of the states in the variation of different mode shapes. Also, the variations in oscillatory modes are presented to observe the damping performance of the test system.

Keywords: Eigenvalue analysis, Mode shapes, MEPE test system, Participation factors, Power System oscillations.

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Authors: Sambit Prasad Kar, P.Palanisamy

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In this paper a novel method for multiple one dimensional real valued sinusoidal signal frequency estimation in the presence of additive Gaussian noise is postulated. A computationally simple frequency estimation method with efficient statistical performance is attractive in many array signal processing applications. The prime focus of this paper is to combine the subspace-based technique and a simple peak search approach. This paper presents a variant of the Propagator Method (PM), where a collaborative approach of SUMWE and Propagator method is applied in order to estimate the multiple real valued sine wave frequencies. A new data model is proposed, which gives the dimension of the signal subspace is equal to the number of frequencies present in the observation. But, the signal subspace dimension is twice the number of frequencies in the conventional MUSIC method for estimating frequencies of real-valued sinusoidal signal. The statistical analysis of the proposed method is studied, and the explicit expression of asymptotic (large-sample) mean-squared-error (MSE) or variance of the estimation error is derived. The performance of the method is demonstrated, and the theoretical analysis is substantiated through numerical examples. The proposed method can achieve sustainable high estimation accuracy and frequency resolution at a lower SNR, which is verified by simulation by comparing with conventional MUSIC, ESPRIT and Propagator Method.

Keywords: Frequency estimation, peak search, subspace-based method without eigen decomposition, quadratic convex function.

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Authors: Raksha Sharma, Vishnu Kant Soni, Manoj Kumar Mishra, Prachet Bhuyan, Utpal Chandra Dey

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Grid computing is a group of clusters connected over high-speed networks that involves coordinating and sharing computational power, data storage and network resources operating across dynamic and geographically dispersed locations. Resource management and job scheduling are critical tasks in grid computing. Resource selection becomes challenging due to heterogeneity and dynamic availability of resources. Job scheduling is a NP-complete problem and different heuristics may be used to reach an optimal or near optimal solution. This paper proposes a model for resource and job scheduling in dynamic grid environment. The main focus is to maximize the resource utilization and minimize processing time of jobs. Grid resource selection strategy is based on Max Heap Tree (MHT) that best suits for large scale application and root node of MHT is selected for job submission. Job grouping concept is used to maximize resource utilization for scheduling of jobs in grid computing. Proposed resource selection model and job grouping concept are used to enhance scalability, robustness, efficiency and load balancing ability of the grid.

Keywords: Agent, Grid Computing, Job Grouping, Max Heap Tree (MHT), Resource Scheduling.

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Authors: Chukwudi Henry Dike

Abstract:

We explore targeted subsidy in a set-up for which manufacturing firms in a waste-spillover network make endogenous production decisions. Here, games of substitution in digraphs arises where waste-producing firms internalise negative externality in a quadratic fashion. We find neutrality in intervention policies that create or reduce spillover links. Most importantly, we observe centrality distinction in asymmetric digraphs so that the dependence and power of each firm play unique roles. Here we see that in targeted subsidy, a firm with greater centrality guarantees optimal welfare improvement. This centrality however measures the weakness of each firm’s Nash-based link to other neighbourhood firms i.e., lower negative externality.

Keywords: Centrality, externality, key-player, Nash-Equilibrium.

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Authors: I. Omerhodzic, S. Avdakovic, A. Nuhanovic, K. Dizdarevic

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In this paper, a wavelet-based neural network (WNN) classifier for recognizing EEG signals is implemented and tested under three sets EEG signals (healthy subjects, patients with epilepsy and patients with epileptic syndrome during the seizure). First, the Discrete Wavelet Transform (DWT) with the Multi-Resolution Analysis (MRA) is applied to decompose EEG signal at resolution levels of the components of the EEG signal (δ, θ, α, β and γ) and the Parseval-s theorem are employed to extract the percentage distribution of energy features of the EEG signal at different resolution levels. Second, the neural network (NN) classifies these extracted features to identify the EEGs type according to the percentage distribution of energy features. The performance of the proposed algorithm has been evaluated using in total 300 EEG signals. The results showed that the proposed classifier has the ability of recognizing and classifying EEG signals efficiently.

Keywords: Epilepsy, EEG, Wavelet transform, Energydistribution, Neural Network, Classification.

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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: Y. Abdelrazig

Abstract:

Evolutionary optimization methods such as genetic algorithms have been used extensively for the construction site layout problem. More recently, ant colony optimization algorithms, which are evolutionary methods based on the foraging behavior of ants, have been successfully applied to benchmark combinatorial optimization problems. This paper proposes a formulation of the site layout problem in terms of a sequencing problem that is suitable for solution using an ant colony optimization algorithm. In the construction industry, site layout is a very important planning problem. The objective of site layout is to position temporary facilities both geographically and at the correct time such that the construction work can be performed satisfactorily with minimal costs and improved safety and working environment. During the last decade, evolutionary methods such as genetic algorithms have been used extensively for the construction site layout problem. This paper proposes an ant colony optimization model for construction site layout. A simple case study for a highway project is utilized to illustrate the application of the model.

Keywords: Construction site layout, optimization, ant colony.

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Authors: Basak Oguz Yolcular

Abstract:

A large amount of valuable information is available in plain text clinical reports. New techniques and technologies are applied to extract information from these reports. In this study, we developed a domain based software system to transform 600 Otorhinolaryngology discharge notes to a structured form for extracting clinical data from the discharge notes. In order to decrease the system process time discharge notes were transformed into a data table after preprocessing. Several word lists were constituted to identify common section in the discharge notes, including patient history, age, problems, and diagnosis etc. N-gram method was used for discovering terms co-Occurrences within each section. Using this method a dataset of concept candidates has been generated for the validation step, and then Predictive Apriori algorithm for Association Rule Mining (ARM) was applied to validate candidate concepts.

Keywords: association rule mining, otorhinolaryngology, predictive apriori, text mining

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Authors: S. Ge, T. Wu, HY. Tang, X. Xiao, K. Iramina, W. Wu

Abstract:

It is crucial to quantitatively evaluate the treatment of epilepsy patients. This study was undertaken to test the hypothesis that compared to the healthy control subjects, the epilepsy patients have abnormal resting-state connectivity. In this study, we used the imaginary part of coherency to measure the resting-state connectivity. The analysis results shown that compared to the healthy control subjects, epilepsy patients tend to have abnormal rhythm brain connectivity over their epileptic focus.

Keywords: Coherence, connectivity, resting-state, epilepsy

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Authors: Nelson K. Lujara

Abstract:

The performance characteristics of a photovoltaic induction motor drive water pumping system with and without maximum power tracker is analyzed and presented. The analysis is done through determination and assessment of critical loss components in the system using computer aided design (CAD) tools for optimal operation of the system. The results can be used to formulate a well-calibrated computer aided design package of photovoltaic water pumping systems based on the induction motor drive. The results allow the design engineer to pre-determine the flow rate and efficiency of the system to suit particular application.

Keywords: Photovoltaic, water pumping, losses, induction motor.

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Authors: Vedansh Gupta, Allyson Lutz, Ameen Razavi, Fatemeh Shirazi

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The agriculture industry is especially vulnerable to forecasted water shortages. In the fresh and fresh-cut produce sector, conventional flume-based washing with recirculation exhibits high water demand. This leads to a large water footprint and possible cross-contamination of pathogens. These can be alleviated through advanced water reuse processes, such as membrane technologies including reverse osmosis (RO). Water reuse technologies effectively remove dissolved constituents but can easily foul without pre-treatment. Biological treatment is effective for the removal of organic compounds responsible for fouling, but not at the low temperatures encountered at most produce processing facilities. This study showed that the Microvi MicroNiche Engineering (MNE) technology effectively removes organic compounds (> 80%) at low temperatures (6-8 °C) from wash water. The MNE technology uses synthetic microorganism-material composites with negligible solids production, making it advantageously situated as an effective bio-pretreatment for RO. A preliminary technoeconomic analysis showed 60-80% savings in operation and maintenance costs (OPEX) when using the Microvi MNE technology for organics removal. This study and the accompanying economic analysis indicated that the proposed technology process will substantially reduce the cost barrier for adopting water reuse practices, thereby contributing to increased food safety and furthering sustainable water reuse processes across the agricultural industry.

Keywords: Biological pre-treatment, innovative technology, vegetable processing, water reuse, agriculture, reverse osmosis, MNE biocatalysts.

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Authors: Seyedeh Mozhgan Seyed-Talebi, Javad Beheshtian

Abstract:

The toxicity of lead associated with the lifecycle of perovskite solar cells (PSCs( is a serious concern which may prove to be a major hurdle in the path toward their commercialization. The current proposed lead-free PSCs including Ag(I), Bi(III), Sb(III), Ti(IV), Ge(II), and Sn(II) low-toxicity cations are still plagued with the critical issues of poor stability and low efficiency. This is mainly because of their chemical stability. In the present research, utilization of all inorganic CsSnGeI₃ based materials offers the advantages to enhance resistance of device to degradation, reduce the cost of cells, and minimize the carrier recombination. The presence of inorganic halide perovskite improves the photovoltaic parameters of PCSs via improved surface coverage and stability. The inverted structure of simulated devices using a 1D simulator like solar cell capacitance simulator (SCAPS) version 3308 involves TCOHTL/Perovskite/ETL/Au contact layer. PEDOT:PSS, PCBM, and CsSnGeI₃ used as hole transporting layer (HTL), electron transporting layer (ETL), and perovskite absorber layer in the inverted structure for the first time. The holes are injected from highly stable and air tolerant Sn_0.5Ge_0.5I₃ perovskite composition to HTM and electrons from the perovskite to ETL. Simulation results revealed a great dependence of power conversion efficiency (PCE) on the thickness and defect density of perovskite layer. Here the effect of an increase in operating temperature from 300 K to 400 K on the performance of CsSnGeI₃ based perovskite devices is investigated. Comparison between simulated CsSnGeI₃ based PCSs and similar real testified devices with spiro-OMeTAD as HTL showed that the extraction of carriers at the interfaces of perovskite absorber depends on the energy level mismatches between perovskite and HTL/ETL. We believe that optimization results reported here represent a critical avenue for fabricating the stable, low-cost, efficient, and eco-friendly all-inorganic Cs-Sn-Ge based lead-free perovskite devices.

Keywords: Hole transporting layer, lead-free, perovskite Solar cell, SCAPS-1D, Sn-Ge based material.

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Authors: M Nayeripour, E. Azad, A. Roosta, T. Niknam

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In this paper, the transformers over-load problem of Shiraz substation in Fars Regional Electric Company (FREC) is investigated for a period of three years plan. So the suggestions for using phase shifting transformer (PST) and unified power flow controller (UPFC) in order to solve this problem are examined in details and finally, some economical and practical designs will be given in order to solve the related problems. Practical consideration and using the basic and fundamental concept of powers in transmission lines in order to find the economical design are the main advantages of this research. The simulation results of the integrated overall system with different designs compare them base on economical and practical aspects to solve the over-load and loss-reduction.

Keywords: Congestion management, Phase shifting transformer(PST), Unified power flow controller (UPFC), Transmission lines.

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Authors: Farhan Ismaeel Dakheel, Raoof Smko, K. Negrat, Abdelsalam Almarimi

Abstract:

In this paper we used data mining techniques to identify outlier patients who are using large amount of drugs over a long period of time. Any healthcare or health insurance system should deal with the quantities of drugs utilized by chronic diseases patients. In Kingdom of Bahrain, about 20% of health budget is spent on medications. For the managers of healthcare systems, there is no enough information about the ways of drug utilization by chronic diseases patients, is there any misuse or is there outliers patients. In this work, which has been done in cooperation with information department in the Bahrain Defence Force hospital; we select the data for Cardiac patients in the period starting from 1/1/2008 to December 31/12/2008 to be the data for the model in this paper. We used three techniques for finding the drug utilization for cardiac patients. First we applied a clustering technique, followed by measuring of clustering validity, and finally we applied a decision tree as classification algorithm. The clustering results is divided into three clusters according to the drug utilization, for 1603 patients, who received 15,806 prescriptions during this period can be partitioned into three groups, where 23 patients (2.59%) who received 1316 prescriptions (8.32%) are classified to be outliers. The classification algorithm shows that the use of average drug utilization and the age, and the gender of the patient can be considered to be the main predictive factors in the induced model.

Keywords: Data Mining, Clustering, Classification, Drug Utilization..

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Authors: K.Sedhuraman, S.Himavathi, A.Muthuramalingam

Abstract:

The performance of sensor-less controlled induction motor drive depends on the accuracy of the estimated speed. Conventional estimation techniques being mathematically complex require more execution time resulting in poor dynamic response. The nonlinear mapping capability and powerful learning algorithms of neural network provides a promising alternative for on-line speed estimation. The on-line speed estimator requires the NN model to be accurate, simpler in design, structurally compact and computationally less complex to ensure faster execution and effective control in real time implementation. This in turn to a large extent depends on the type of Neural Architecture. This paper investigates three types of neural architectures for on-line speed estimation and their performance is compared in terms of accuracy, structural compactness, computational complexity and execution time. The suitable neural architecture for on-line speed estimation is identified and the promising results obtained are presented.

Keywords: Sensorless IM drives, rotor speed estimators, artificial neural network, feed- forward architecture, single neuron cascaded architecture.

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Authors: M. M. Seif, F. A. Khalil, A. A. K. Abou Arab, A. S. Abdel- Aziz, M. A. Abou Donia, Sh. R. Mohamed

Abstract:

Malathion (ML) is a well known pesticide commonly used in many agricultural and non-agricultural processes. Its toxicity has been attributed primarily to the accumulation of acetylcholine (Ach) at nerve junctions, due to the inhibition of acetylcholinesterase (AChE). The aim of the current research was to study the protective effect of the melissa plant extract against reproductive impairment induced by malathion in 32 male albino rats, and the biological experiment was divided into four groups (8 in each) that given malathion (27 mg/kg; 1/50 of the LD50 for an oral dose) and/or Melissa officinalis (MO) extract (200mg/kg/day) by gavages technique. The sperm counts, sperm motility, sperm morphology, FSH, LH, and testosterone levels had been determined in testes homogenate at the end of the experiment. It is worthy to report that, rats treated with melissa extract did not show a significant difference when compared with the control group, while rats given malathion alone had significantly lower sperm count, sperm motility, and significantly higher abnormal sperm numbers, than the untreated control rats as well as having significantly lower serum FSH, LH, and testosterone levels compared with the control group. Administrations of melissa extract restore all mentioned histological parameters towards the control group and the melissa extract had a strong positive protective effect against malathion toxicity. Results the of biological parameters were confirmed by the histological examination of rat testes and indicated that, both control and melissa groups showing normal seminiferous tubules, while malathion group testicular tissues had necrosis, edema in the seminiferous tubules and degeneration of spermatogonial cells lining the seminiferous tubules with incomplete spermatogenesis. The use of melissa against malathion improved the histological picture and showing normal seminiferous tubules with complete spermatogenesis and almost there was no histopathological changes could be noted.

Keywords: Malathion, Melissa officinalis L., Reproductive toxicity, Rats.

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Authors: Z. Khoshnood, L. Khoshnood

Abstract:

Pesticides and drugs used in agriculture and veterinary medicine may end up in aquatic environments and bioaccumulate in the food chain, thus causing serious problems for fauna and human health. For determination of the toxic effects of atrazine herbicide on Caspian kutum, Rutilus frisii kutum larvae, the 96-h LC50 of atrazine was measured for newly hatched larvae as 18.53 ppm. Toxicity of atrazine herbicide on Caspian kutum larvae was investigated using concentrations: 9.25ppm, 4.62 ppm and 2.31 ppm for 7 days. Comparison of the length, weight and condition factor showed that no significant differences between atrazine exposed and control groups. The concentration of Na+, K+, Ca2+, Mg2+ and Cl- in whole body of larvae in control and atrazine exposure groups were measured and the results showed that concentrations of all these ions is higher in atrazine exposure group than control group. It is obvious from this study that atrazine negatively affects osmoregulation process and changes ion compositions of the body even at sublethal concentration and acute exposure but have no effects on growth parameters of the body.

Keywords: Atrazine, Caspian Kutum, Acute Toxicity, Body Ions, LC50.

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Authors: Nerijus Remeikis, Ignas Skucas, Vida Melninkaite

Abstract:

Text categorization - the assignment of natural language documents to one or more predefined categories based on their semantic content - is an important component in many information organization and management tasks. Performance of neural networks learning is known to be sensitive to the initial weights and architecture. This paper discusses the use multilayer neural network initialization with decision tree classifier for improving text categorization accuracy. An adaptation of the algorithm is proposed in which a decision tree from root node until a final leave is used for initialization of multilayer neural network. The experimental evaluation demonstrates this approach provides better classification accuracy with Reuters-21578 corpus, one of the standard benchmarks for text categorization tasks. We present results comparing the accuracy of this approach with multilayer neural network initialized with traditional random method and decision tree classifiers.

Keywords: Text categorization, decision trees, neural networks, machine learning.

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