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.

Influence of Pomegranate (Punica granatum L.) on Dimethoate Induced Hepatotoxicity in Rats

Pomegranate (Punica granatum L.) is an ancient fruit of great medical interest and rich source of antioxidants. Pesticides as dimethoate play a crucial role in the occurrence many diseases in plants, animal and human. Therefore the ability of Pomegranate (Punica granatum L.) to alleviate hepatotoxicity induced by organophosphate pesticide dimethoate was investigated. Albino male rats were divided randomly into 4 groups and kept at 7 animals per group in an environmentally controlled condition for 6 weeks. The first group was served as a control group (basal diet), the second group fed on basal diet supplemented with 5% freeze dried pomegranate seeds, the third group fed on 20 ppm dimethoate contaminated diet and the last group fed on dimethoate contaminated diet supplemented with 5% freeze dried pomegranate seeds. The results revealed that administration of dimethoate caused high significant increased in liver functions: alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP) activities as well as lipid peroxide (malonaldhyde, MDA); on the other hand high significant decreased on glutathione (GSH), glutathione peroxidase (GPx), albumin and total protein were observed. However addition of 5% freeze dried pomegranate seeds significantly improved all previously mentioned parameters. These results indicate the dimethoate induced hepatotoxicity and highlight the protective effect of pomegranate seeds as a potential protective agent against dimethoate induced hepatotoxicity. This may be attributed to the powerful antioxidants (polyphenols, total phenols, and total flavonoids) which present in high levels in pomegranate as well as improving the immunity by activation of antioxidant enzymes GSH and GPx.

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.

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.

Influence of S. carnosus Bacteria as Biocollector for the Recovery Organic Matter in the Flotation Process

The mineral bioflotation represents a viable alternative for the evaluation of new processes benefit alternative. The adsorption bacteria on minerals surfaces will depend mainly on the type of the microorganism as well as of the studied mineral surface. In the current study, adhesion of S. carnosus on coal was studied. Several methods were used as: DRX, Fourier Transform Infra-Red (FTIR) adhesion isotherms and kinetic. The main goal is to recovery of organic matter by the microflotation process on coal particles with biological reagent (S. carnosus). Adhesion tests revealed that adhesion took place after of 8 h at pH 9. The results suggest that the adhesion of bacteria to solid substrates can be considered an abiotic physicochemical process that is consequently governed by bacterial surface properties such as their specific surface area, hydrophobicity and surface functionalities. The greatest coal fine flotability was of 75%, after 5 min of flotation.

Use of Recycled Aggregates in Current Concretes

The paper a summary of the results of concretes with partial substitution of natural aggregates with recycled concrete is solved. Design formulas of the concretes were characterised with 20, 40 and 60% substitution of natural 8-16mm fraction aggregates with a selected recycled concrete of analogous coarse fractions. With the product samples an evaluation of coarse fraction aggregates influence on fresh concrete consistency and concrete strength in time was carried out. The results of concretes with aggregates substitution will be compared to reference formula containing only the fractions of natural aggregates.

Transient Enhanced LDO Voltage Regulator with Improved Feed Forward Path Compensation

Anultra-low power capacitor less low-dropout voltage regulator with improved transient response using gain enhanced feed forward path compensation is presented in this paper. It is based on a cascade of a voltage amplifier and a transconductor stage in the feed forward path with regular error amplifier to form a composite gainenhanced feed forward stage. It broadens the gain bandwidth and thus improves the transient response without substantial increase in power consumption. The proposed LDO, designed for a maximum output current of 100 mA in UMC 180 nm, requires a quiescent current of 69 )A. An undershot of 153.79mV for a load current changes from 0mA to 100mA and an overshoot of 196.24mV for current change of 100mA to 0mA. The settling time is approximately 1.1 )s for the output voltage undershooting case. The load regulation is of 2.77 )V/mA at load current of 100mA. Reference voltage is generated by using an accurate band gap reference circuit of 0.8V.The costly features of SOC such as total chip area and power consumption is drastically reduced by the use of only a total compensation capacitance of 6pF while consuming power consumption of 0.096 mW.

Intensive Biological Control in Spanish Greenhouses: Problems of the Success

Currently, biological control programs in greenhouse crops involve the use, at the same time, several natural enemies during the crop cycle. Also, large number of plant species grown in greenhouses, among them, the used cultivars are also wide. However, the cultivar effects on entomophagous species efficacy (predators and parasitoids) have been scarcely studied. A new method had been developed, using the factitious prey or host Ephestia kuehniella. It allow us to evaluate, under greenhouse or controlled conditions (semi-field), the cultivar effects on the entomophagous species effectiveness. The work was carried out in greenhouse tomato crop. It has been found the biological and ecological activities of predatory species (Nesidiocoris tenuis) and egg-parasitoid (Trichogramma achaeae) can be well represented with the use of the factitious prey or host; being better in the former than the latter. The data found in the trial are shown and discussed. The developed method could be applied to evaluate new plant materials before making available to farmers as commercial varieties, at low costs and easy use.

Analysis of Vortical Structures Generated by the Swirler of Combustion Chamber

The most important part of modern lean low NOx combustors is a premixer where swirlers are often used for intensification of mixing processes and further formation of required flow pattern in combustor liner. Swirling flow leads to formation of complex eddy structures causing flow perturbations. It is able to cause combustion instability. Therefore, at design phase, it is necessary to pay great attention to aerodynamics of premixers. Analysis based on unsteady CFD modeling of swirling flow in production combustor swirler showed presence of large number of different eddy structures that can be conditionally divided into three types relative to its location of origin and a propagation path. Further, features of each eddy type were subsequently defined. Comparison of calculated and experimental pressure fluctuations spectrums verified correctness of computations.

Kohonen Self-Organizing Maps as a New Method for Determination of Salt Composition of Multi-Component Solutions

The paper presents the results of clusterization by Kohonen self-organizing maps (SOM) applied for analysis of array of Raman spectra of multi-component solutions of inorganic salts, for determination of types of salts present in the solution. It is demonstrated that use of SOM is a promising method for solution of clusterization and classification problems in spectroscopy of multicomponent objects, as attributing a pattern to some cluster may be used for recognition of component composition of the object.

The Gasoil Hydrofining Kinetics Constants Identification

The paper describes the experiments and the kinetic parameters calculus of the gasoil hydrofining. They are presented experimental results of gasoil hidrofining using Mo and promoted with Ni on aluminum support catalyst. The authors have adapted a kinetic model gasoil hydrofining. Using this proposed kinetic model and the experimental data they have calculated the parameters of the model. The numerical calculus is based on minimizing the difference between the experimental sulf concentration and kinetic model estimation.

Application of Adaptive Neural Network Algorithms for Determination of Salt Composition of Waters Using Laser Spectroscopy

In this study, a comparative analysis of the approaches associated with the use of neural network algorithms for effective solution of a complex inverse problem – the problem of identifying and determining the individual concentrations of inorganic salts in multicomponent aqueous solutions by the spectra of Raman scattering of light – is performed. It is shown that application of artificial neural networks provides the average accuracy of determination of concentration of each salt no worse than 0.025 M. The results of comparative analysis of input data compression methods are presented. It is demonstrated that use of uniform aggregation of input features allows decreasing the error of determination of individual concentrations of components by 16-18% on the average.

Using Artificial Neural Networks for Optical Imaging of Fluorescent Biomarkers

The article presents the results of the application of artificial neural networks to separate the fluorescent contribution of nanodiamonds used as biomarkers, adsorbents and carriers of drugs in biomedicine, from a fluorescent background of own biological fluorophores. The principal possibility of solving this problem is shown. Use of neural network architecture let to detect fluorescence of nanodiamonds against the background autofluorescence of egg white with high accuracy - better than 3 ug/ml.

Temperature Investigations in Two Type of Crimped Connection Using Experimental Determinations

In this paper we make a temperature investigations in two type of superposed crimped connections using experimental determinations. All the samples use 8 copper wire 7.1 x 3 mm2 crimped by two methods: the first method uses one crimp indents and the second is a proposed method with two crimp indents. The ferrule is a parallel one. We study the influence of number and position of crimp indents. The samples are heated in A.C. current at different current values until steady state heating regime. After obtaining of temperature values, we compare them and present the conclusion.

Selecting the Best Sub-Region Indexing the Images in the Case of Weak Segmentation Based On Local Color Histograms

Color Histogram is considered as the oldest method used by CBIR systems for indexing images. In turn, the global histograms do not include the spatial information; this is why the other techniques coming later have attempted to encounter this limitation by involving the segmentation task as a preprocessing step. The weak segmentation is employed by the local histograms while other methods as CCV (Color Coherent Vector) are based on strong segmentation. The indexation based on local histograms consists of splitting the image into N overlapping blocks or sub-regions, and then the histogram of each block is computed. The dissimilarity between two images is reduced, as consequence, to compute the distance between the N local histograms of the both images resulting then in N*N values; generally, the lowest value is taken into account to rank images, that means that the lowest value is that which helps to designate which sub-region utilized to index images of the collection being asked. In this paper, we make under light the local histogram indexation method in the hope to compare the results obtained against those given by the global histogram. We address also another noteworthy issue when Relying on local histograms namely which value, among N*N values, to trust on when comparing images, in other words, which sub-region among the N*N sub-regions on which we base to index images. Based on the results achieved here, it seems that relying on the local histograms, which needs to pose an extra overhead on the system by involving another preprocessing step naming segmentation, does not necessary mean that it produces better results. In addition to that, we have proposed here some ideas to select the local histogram on which we rely on to encode the image rather than relying on the local histogram having lowest distance with the query histograms.

Frequent Itemset Mining Using Rough-Sets

Frequent pattern mining is the process of finding a pattern (a set of items, subsequences, substructures, etc.) that occurs frequently in a data set. It was proposed in the context of frequent itemsets and association rule mining. Frequent pattern mining is used to find inherent regularities in data. What products were often purchased together? Its applications include basket data analysis, cross-marketing, catalog design, sale campaign analysis, Web log (click stream) analysis, and DNA sequence analysis. However, one of the bottlenecks of frequent itemset mining is that as the data increase the amount of time and resources required to mining the data increases at an exponential rate. In this investigation a new algorithm is proposed which can be uses as a pre-processor for frequent itemset mining. FASTER (FeAture SelecTion using Entropy and Rough sets) is a hybrid pre-processor algorithm which utilizes entropy and roughsets to carry out record reduction and feature (attribute) selection respectively. FASTER for frequent itemset mining can produce a speed up of 3.1 times when compared to original algorithm while maintaining an accuracy of 71%.