A Comparative Analysis of Zotero and Mendeley Reference Management Software

This paper presents a comparison of the reference management software between Zotero and Mendeley and the results were drawn by comparing the two software’s. The novelty of this paper is the comparative analysis of the software and it has shown that Mendeley can import more information from the Google Scholar for the researchers. This finding can help to know researchers to use the reference management software.

Exploiting Kinetic and Kinematic Data to Plot Cyclograms for Managing the Rehabilitation Process of BKAs by Applying Neural Networks

Kinematic data wisely correlate vector quantities in space to scalar parameters in time to assess the degree of symmetry between the intact limb and the amputated limb with respect to a normal model derived from the gait of control group participants. Furthermore, these particular data allow a doctor to preliminarily evaluate the usefulness of a certain rehabilitation therapy. Kinetic curves allow the analysis of ground reaction forces (GRFs) to assess the appropriateness of human motion. Electromyography (EMG) allows the analysis of the fundamental lower limb force contributions to quantify the level of gait asymmetry. However, the use of this technological tool is expensive and requires patient’s hospitalization. This research work suggests overcoming the above limitations by applying artificial neural networks.

Antibacterial and Antifungal Activity of Essential Oil of Eucalyptus camendulensis on a Few Bacteria and Fungi

Red River Gum (Eucalyptus camaldulensis) is a tree of the genus Eucalyptus widely distributed in Algeria and in the world. The value of its aromatic secondary metabolites offers new perspectives in the pharmaceutical industry. This strategy can contribute to the sustainable development of our country. Preliminary tests performed on the essential oil of Eucalyptus camendulensis showed that this oil has antibacterial activity vis-à-vis the bacterial strains (Enterococcus feacalis, Enterobacter cloaceai, Proteus microsilis, Escherichia coli, Klebsiella pneumonia, and Pseudomonas aeruginosa) and antifungic (Fusarium sporotrichioide and Fusarium graminearum). The culture medium used was nutrient broth Muller Hinton. The interaction between the bacteria and the essential oil is expressed by a zone of inhibition with diameters of MIC indirectly expression of. And we used the PDA medium to determine the fungal activity. The extraction of the aromatic fraction (essentially oilhydrolat) of the fresh aerian part of the Eucalyptus camendulensis was performed by hydrodistillation. The average essential oil yield is 0.99%. The antimicrobial and fungal study of the essential oil and hydrosol showed a high inhibitory effect on the growth of pathogens.

Teaching Speaking Skills to Adult English Language Learners through ALM

Audio-lingual Method (ALM) is a teaching approach that is claimed that ineffective for teaching second/foreign languages. Because some linguists and second/foreign language teachers believe that ALM is a rote learning style. However, this study is done on a belief that ALM will be able to solve Thais’ English speaking problem. This paper aims to report the findings on teaching English speaking to adult learners with an “adapted ALM”, one distinction of which is to use Thai as the medium language of instruction. The participants are consisted of 9 adult learners. They were allowed to speak English more freely using both the materials presented in the class and their background knowledge of English. At the end of the course, they spoke English more fluently, more confidently, to the extent that they applied what they learnt both in and outside the class.

Comparative Analysis of Diverse Collection of Big Data Analytics Tools

Over the past era, there have been a lot of efforts and studies are carried out in growing proficient tools for performing various tasks in big data. Recently big data have gotten a lot of publicity for their good reasons. Due to the large and complex collection of datasets it is difficult to process on traditional data processing applications. This concern turns to be further mandatory for producing various tools in big data. Moreover, the main aim of big data analytics is to utilize the advanced analytic techniques besides very huge, different datasets which contain diverse sizes from terabytes to zettabytes and diverse types such as structured or unstructured and batch or streaming. Big data is useful for data sets where their size or type is away from the capability of traditional relational databases for capturing, managing and processing the data with low-latency. Thus the out coming challenges tend to the occurrence of powerful big data tools. In this survey, a various collection of big data tools are illustrated and also compared with the salient features.

Production and Mechanical Characterization of Ballistic Thermoplastic Composite Materials

In this study, first thermoplastic composite materials /plates that have high ballistic impact resistance were produced. For this purpose, the thermoplastic prepreg and the vacuum bagging technique were used to produce a composite material. Thermoplastic prepregs (resin-impregnated fiber) that are supplied ready to be used, namely high-density polyethylene (HDPE) was chosen as matrix and unidirectional glass fiber was used as reinforcement. In order to compare the fiber configuration effect on mechanical properties, unidirectional and biaxial prepregs were used. Then the microstructural properties of the composites were investigated with scanning electron microscopy (SEM) analysis. Impact properties of the composites were examined by Charpy impact test and tensile mechanical tests and then the effects of ultraviolet irradiation were investigated on mechanical performance.

Simulation of Laser Structuring by Three Dimensional Heat Transfer Model

In this study, a three dimensional numerical heat transfer model has been used to simulate the laser structuring of polymer substrate material in the Three-Dimensional Molded Interconnect Device (3D MID) which is used in the advanced multifunctional applications. A finite element method (FEM) transient thermal analysis is performed using APDL (ANSYS Parametric Design Language) provided by ANSYS. In this model, the effect of surface heat source was modeled with Gaussian distribution, also the effect of the mixed boundary conditions which consist of convection and radiation heat transfers have been considered in this analysis. The model provides a full description of the temperature distribution, as well as calculates the depth and the width of the groove upon material removal at different set of laser parameters such as laser power and laser speed. This study also includes the experimental procedure to study the effect of laser parameters on the depth and width of the removal groove metal as verification to the modeled results. Good agreement between the experimental and the model results is achieved for a wide range of laser powers. It is found that the quality of the laser structure process is affected by the laser scan speed and laser power. For a high laser structured quality, it is suggested to use laser with high speed and moderate to high laser power.

The Effect of Porous Alkali Activated Material Composition on Buffer Capacity in Bioreactors

With demand for primary energy continuously growing, search for renewable and efficient energy sources has been high on agenda of our society. One of the most promising energy sources is biogas technology. Residues coming from dairy industry and milk processing could be used in biogas production; however, low efficiency and high cost impede wide application of such technology. One of the main problems is management and conversion of organic residues through the anaerobic digestion process which is characterized by acidic environment due to the low whey pH (

A New Method to Estimate the Low Income Proportion: Monte Carlo Simulations

Estimation of a proportion has many applications in economics and social studies. A common application is the estimation of the low income proportion, which gives the proportion of people classified as poor into a population. In this paper, we present this poverty indicator and propose to use the logistic regression estimator for the problem of estimating the low income proportion. Various sampling designs are presented. Assuming a real data set obtained from the European Survey on Income and Living Conditions, Monte Carlo simulation studies are carried out to analyze the empirical performance of the logistic regression estimator under the various sampling designs considered in this paper. Results derived from Monte Carlo simulation studies indicate that the logistic regression estimator can be more accurate than the customary estimator under the various sampling designs considered in this paper. The stratified sampling design can also provide more accurate results.

Heritability and Repeatability Estimates of Some Measurable Traits in Meat Type Chickens Reared for Ten Weeks in Abeokuta, Nigeria

A total of 150 meat type chickens comprising 50 each of Arbor Acre, Marshall and Ross were used for this study which lasted for 10 weeks at the Federal University of Agriculture, Abeokuta, Nigeria. Growth performance data were collected from the third week through week 10 and data obtained were analysed using the Generalized Linear Model Procedure. Heritability estimates (h2) for body dimensions carried out on the chicken strains ranged from low to high. Marshall broiler chicken strain had the highest h2 for body weight 0.46±0.04, followed by Arbor Acre and Ross with h2 being 0.38±0.12 and 0.26±0.06, respectively. The repeatability estimates for body weight in the three broiler strains were high, and it ranged from 0.70 at week 4 to 0.88 at week 10. Relationships between the body weight and linear body measurements in the broiler chicken strains were positive and highly significant (p > 0.05).

The Different Ways to Describe Regular Languages by Using Finite Automata and the Changing Algorithm Implementation

This paper aims at introducing finite automata theory, the different ways to describe regular languages and create a program to implement the subset construction algorithms to convert nondeterministic finite automata (NFA) to deterministic finite automata (DFA). This program is written in c++ programming language. The program reads FA 5tuples from text file and then classifies it into either DFA or NFA. For DFA, the program will read the string w and decide whether it is acceptable or not. If accepted, the program will save the tracking path and point it out. On the other hand, when the automation is NFA, the program will change the Automation to DFA so that it is easy to track and it can decide whether the w exists in the regular language or not.

A Multi-Agent Intelligent System for Monitoring Health Conditions of Elderly People

In this paper, we propose a multi-agent intelligent system that is used for monitoring the health conditions of elderly people. Monitoring the health condition of elderly people is a complex problem that involves different medical units and requires continuous monitoring. Such expert system is highly needed in rural areas because of inadequate number of available specialized physicians or nurses. Such monitoring must have autonomous interactions between these medical units in order to be effective. A multi-agent system is formed by a community of agents that exchange information and proactively help one another to achieve the goal of elderly monitoring. The agents in the developed system are equipped with intelligent decision maker that arms them with the rule-based reasoning capability that can assist the physicians in making decisions regarding the medical condition of elderly people.

Modeling and Simulation of Dynamic Voltage Restorer for Mitigation of Voltage Sags

Voltage sags are the most common power quality disturbance in the distribution system. It occurs due to the fault in the electrical network or by the starting of a large induction motor and this can be solved by using the custom power devices such as Dynamic Voltage Restorer (DVR). In this paper DVR is proposed to compensate voltage sags on critical loads dynamically. The DVR consists of VSC, injection transformers, passive filters and energy storage (lead acid battery). By injecting an appropriate voltage, the DVR restores a voltage waveform and ensures constant load voltage. The simulation and experimental results of a DVR using MATLAB software shows clearly the performance of the DVR in mitigating voltage sags.

The Importance of Issues for the Youth in Voter Decision Making: A Case Study among University Students in Malaysia

In the 13th Malaysia’s General Elections held in 2013, it was observed that large numbers of urban constituencies saw strongly decisive young voters (between 21-39 age group) determine the outcome in their favour. Also, the Elections Commission had approximated that 70% of some 4.2 million unregistered voters at the time were citizens aged between 21 and 40 years old. If they are not already considered an important form of political leverage, 450,000 young Malaysians turn 21 years old each year. Further compounding this fact were the 2.4 million new voters registered in 2012, which at the time constituted almost 30% of the entire voting population. This article discusses the importance of issues for the youth, with reference to the university students in Malaysia in their decision making on polling day.

Protective Effect of Melissa officinalis L. against Malathion Toxicity and Reproductive Impairment in Male Rats

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.

Passivity Analysis of Stochastic Neural Networks With Multiple Time Delays

This paper deals with the problem of passivity analysis for stochastic neural networks with leakage, discrete and distributed delays. By using delay partitioning technique, free weighting matrix method and stochastic analysis technique, several sufficient conditions for the passivity of the addressed neural networks are established in terms of linear matrix inequalities (LMIs), in which both the time-delay and its time derivative can be fully considered. A numerical example is given to show the usefulness and effectiveness of the obtained results.

A Case Study on Suitable Area and Resource for Development of Floating Photovoltaic System

In development of floating photovoltaic generation system, finding a suitable place of installation is as important as development of economically feasible and stable structure. Especially since floating photovoltaic system has its facility floating on water surface, it is extremely important to review the effects of weather conditions such as wind, water flow and floating matters, various factors (such as fogs) that can reduce generation efficiency, possibility of connection with power system, and legal restrictions. The method of investigating suitable area and resource for development of tracking-type floating photovoltaic generation system was proposed in this paper, which can be used for development of floating and ocean photovoltaic system in the future.

In Search of a Suitable Neural Network Capable of Fast Monitoring of Congestion Level in Electric Power Systems

This paper aims at finding a suitable neural network for monitoring congestion level in electrical power systems. In this paper, the input data has been framed properly to meet the target objective through supervised learning mechanism by defining normal and abnormal operating conditions for the system under study. The congestion level, expressed as line congestion index (LCI), is evaluated for each operating condition and is presented to the NN along with the bus voltages to represent the input and target data. Once, the training goes successful, the NN learns how to deal with a set of newly presented data through validation and testing mechanism. The crux of the results presented in this paper rests on performance comparison of a multi-layered feed forward neural network with eleven types of back propagation techniques so as to evolve the best training criteria. The proposed methodology has been tested on the standard IEEE-14 bus test system with the support of MATLAB based NN toolbox. The results presented in this paper signify that the Levenberg-Marquardt backpropagation algorithm gives best training performance of all the eleven cases considered in this paper, thus validating the proposed methodology.

Image Retrieval Using Fused Features

The system is designed to show images which are related to the query image. Extracting color, texture, and shape features from an image plays a vital role in content-based image retrieval (CBIR). Initially RGB image is converted into HSV color space due to its perceptual uniformity. From the HSV image, Color features are extracted using block color histogram, texture features using Haar transform and shape feature using Fuzzy C-means Algorithm. Then, the characteristics of the global and local color histogram, texture features through co-occurrence matrix and Haar wavelet transform and shape are compared and analyzed for CBIR. Finally, the best method of each feature is fused during similarity measure to improve image retrieval effectiveness and accuracy.

The Effect of Outliers on the Economic and Social Survey on Income and Living Conditions

The European Union Survey on Income and Living Conditions (EU-SILC) is a popular survey which provides information on income, poverty, social exclusion and living conditions of households and individuals in the European Union. The EU-SILC contains variables which may contain outliers. The presence of outliers can have an impact on the measures and indicators used by the EU-SILC. In this paper, we used data sets from various countries to analyze the presence of outliers. In addition, we obtain some indicators after removing these outliers, and a comparison between both situations can be observed. Finally, some conclusions are obtained.