Abstract: Loss minimization is a long progressing issue mainly in distribution system. Nevertheless its effect led to temperature rise due to significant voltage drop through the distribution line. Thus, compensation scheme should be proper scheduled in the attempt to alleviate the voltage drop phenomenon. Distributed generation has been profoundly known for voltage profile improvement; provided that over-compensation or under-compensation phenomena are avoided. This paper addresses the issue of voltage improvement through different type DG installation. In ensuring optimal sizing and location of the DGs, pre-developed EMEFA technique was made use for this purpose. Incremental loading condition subjected to the system is the concern such that it is beneficial to the power system operator.
Abstract: Monitoring is essential to assessing the effectiveness of air pollution control actions. The goal of the air quality information system is through monitoring, to keep authorities, major polluters and the public informed on the short and long-term changes in air quality, thereby helping to raise awareness. Mathematical models are the best tools available for the prediction of the air quality management. The main objective of the work was to apply a Model that predicts the concentration levels of different pollutants at any instant of time. In this study, distribution of air pollutants concentration such as nitrogen dioxides (NO2), sulphur dioxides (SO2) and total suspended particulates (TSP) of industries are determined by using Gaussian model. Besides that, the effect of wind speed and its direction on the pollutant concentration within the affected area were evaluated. In order to determine the efficiency and percentage of error in the modeling, validation process of data was done. Sampling of air quality was conducted in getting existing air quality around a factory and the concentrations of pollutants in a plume were inversely proportional to wind velocity. The resultant ground level concentrations were then compared to the quality standards to determine if there could be a negative impact on health. This study concludes that concentration of pollutants can be significantly predicted using Gaussian Model. The data base management is developed for the air data of Hubli-Dharwad region.
Abstract: The paper examines the impact of money market on economic growth in Nigeria using data for the period 1980-2012. Econometrics techniques such as Ordinary Least Squares Method, Johanson’s Co-integration Test and Vector Error Correction Model were used to examine both the long-run and short-run relationship. Evidence from the study suggest that though a long-run relationship exists between money market and economic growth, but the present state of the Nigerian money market is significantly and negatively related to economic growth. The link between the money market and the real sector of the economy remains very weak. This implies that the market is not yet developed enough to produce the needed growth that will propel the Nigerian economy because of several challenges. It was therefore recommended that government should create the appropriate macroeconomic policies, legal framework and sustain the present reforms with a view to developing the market so as to promote productive activities, investments, and ultimately economic growth.
Abstract: Urban runoff quality for a mixed residential-commercial land use catchment in Miri, Sarawak was investigated for three storm events in 2011. Samples from the three storm events were tested for five water quality parameters, namely, TSS, COD, BOD5, TP, and Pb. Concentration of the pollutants were found to vary significantly between storms, but were generally influenced by the length of antecedent dry period and the strength of rainfall intensities. Runoff from the study site showed a significant level of pollution for all the parameters investigated. Based on the National Water Quality Standards for Malaysia (NWQS), stormwater quality from the study site was polluted and exceeded class III water for TSS and BOD5, with maximum EMCs of 177 and 24 mg/L, respectively. Design pollutant load based on a design storm of 3-month average recurrence interval (ARI) for TSS, COD, BOD5, TP, and Pb were estimated to be 40, 9.4, 5.4, 1.7, and 0.06 kg/ha, respectively. The design pollutant load for the pollutants can be used to estimate loadings from similar catchments within Miri City.
Abstract: Feet and ankles are parts of human body that receive high-pressure in every day. Feet disorders such as ankle sprain, achilles tendonitis, heel pain, and plantar fasciitis are very common. There are many causes for these feet disorders such as wearing high heels, obesity, sports activity, and standing for a long time. There are many reliefs for feet disorders such as heel insert. However, they come in various shapes and use different materials. There are no specifications in which type is suitable for specific user. This has led to the proposed research to provide guidelines for selecting the appropriate heel insert for ladies who face with long-standing carriers. This research uses contact-measuring techniques to test forces, contact area, and pressure acting on a person’s feet in various standing positions with different insert materials and shapes. The proper material for making insert will be presented and discussed.
Abstract: The object of this study was to investigate several hormones correlated to the reproduction and inhibin A, inhibin B and NO levels in the infertile dairy cows as attempt to illustrate the physiological causes of dairy cows infertility.
40 Holstein cow (21 infertile and 19 fertile) were used at estrous phase of the cycle, Hormones FSH, LH, E2, Testosterone, were measured using ELISA method. inhibin A and B also estimated by ELISA method, Nitric oxide was measured by Greiss reagent method.
The results showed different concentrations of the hormone in which FSH illustrated significantly higher concentration in the infertile cows than fertile cows (P
Abstract: In recent years intrusions on computer network are the major security threat. Hence, it is important to impede such intrusions. The hindrance of such intrusions entirely relies on its detection, which is primary concern of any security tool like Intrusion detection system (IDS). Therefore, it is imperative to accurately detect network attack. Numerous intrusion detection techniques are available but the main issue is their performance. The performance of IDS can be improved by increasing the accurate detection rate and reducing false positive. The existing intrusion detection techniques have the limitation of usage of raw dataset for classification. The classifier may get jumble due to redundancy, which results incorrect classification. To minimize this problem, Principle component analysis (PCA), Linear Discriminant Analysis (LDA) and Local Binary Pattern (LBP) can be applied to transform raw features into principle features space and select the features based on their sensitivity. Eigen values can be used to determine the sensitivity. To further classify, the selected features greedy search, back elimination, and Particle Swarm Optimization (PSO) can be used to obtain a subset of features with optimal sensitivity and highest discriminatory power. This optimal feature subset is used to perform classification. For classification purpose, Support Vector Machine (SVM) and Multilayer Perceptron (MLP) are used due to its proven ability in classification. The Knowledge Discovery and Data mining (KDD’99) cup dataset was considered as a benchmark for evaluating security detection mechanisms. The proposed approach can provide an optimal intrusion detection mechanism that outperforms the existing approaches and has the capability to minimize the number of features and maximize the detection rates.
Abstract: With an increase in the interest in the energy conservation for buildings, and the emergence of many methods and easily-understandable approaches to it, energy conservation has now become the public’s main interest, as compared to in the past when it was only focused upon by experts. This study aims to help the occupants of a building to understand the energy efficiency and consumption of the building by providing them information on the building’s energy efficiency through a mobile application. The energy performance assessment models are proposed on the basis of the actual energy usage and building characteristics such as the architectural scheme and the building equipment. The university buildings in Korea are used as a case to demonstrate the mobile application.
Abstract: The article deals with biomechanics of cyclist with unilateral transtibial amputation. Transtibial amputation completely removes ankle and part of muscles of a lower leg which are responsible for production of force during pedaling and causes significant geometric and power asymmetry between the limbs during cycling movement. The primary goal of this work is to assess the effects of length adjustment of the crank on the kinematics and muscle activity of cyclist. The paper presents experimental work, which aims to find a suitable ratio of the length of kinematic components to improve overall athletic performance. The study presents the results of the kinematic analysis of the cycling movement with different crank length realized by tracking camera system together with the results of muscle activity measurements captured by electromyography and measurement of forces in the cranks by strain gauges.
Abstract: Cyber terrors against specific enterprises or countries have been increasing recently. Such attacks against specific targets are called advanced persistent threat (APT), and they are giving rise to serious social problems. The malicious behaviors of APT attacks mostly affect websites and penetrate enterprise networks to perform malevolent acts. Although many enterprises invest heavily in security to defend against such APT threats, they recognize the APT attacks only after the latter are already in action. This paper discusses the characteristics of APT attacks at each step as well as the strengths and weaknesses of existing malicious code detection technologies to check their suitability for detecting APT attacks. It then proposes a network-based malicious behavior detection algorithm to protect the enterprise or national networks.
Abstract: This study focuses on the impact of school building design factors on winter extra energy consumption which mainly includes space heating, water heating and other appliances related to winter indoor thermal conditions. A number of Auckland schools were randomly selected for the study which introduces a method of using real monthly energy consumption data for a year to calculate winter extra energy data of school buildings. The study seeks to identify the relationships between winter extra energy data related to school building design data related to the main architectural features, building envelope and elements of the sample schools. The relationships can be used to estimate the approximate saving in winter extra energy consumption which would result from a changed design datum for future school development, and identify any major energy-efficient design problems. The relationships are also valuable for developing passive design guides for school energy efficiency.
Abstract: A solar powered air heating system using parabolic trough collector was experimentally investigated. In this experimental setup, the reflected solar radiations were focused on absorber tube which was placed at focal length of the parabolic trough. In this setup, air was used as working fluid which collects the heat from absorber tube. To enhance the performance of parabolic trough, collector with different type of reflectors were used. It was observed For Aluminum sheet maximum temperature is 52.3ºC, which 24.22% more than steel sheet as reflector and 8.5% more than Aluminum foil as reflector, also efficiency by using Aluminum sheet as reflector compared to steel sheet as reflector is 61.18% more. Efficiency by using Aluminum sheet as reflector compared to Aluminum foil as reflector is 18.98% more.
Abstract: The production of Dimethyl acetal, Isovaleradehyde and Pyridine were simulated using Aspen Plus simulation. Upgrading cleaning water from wine industrial production is the main objective of the project. The winery waste composes of Acetaldehyde, Methanol, Ethyl Acetate, 1-propanol, water, iso-amyl alcohol and iso-butyl alcohol. The project is separated into three parts; separation, reaction, and purification. Various processes were considered to maximize the profit along with obtaining high purity and recovery of each component with optimum heat duty. The results show a significant value of the product with purity more than 75% and recovery over 98%.
Abstract: Sometimes the amount of time available for testing could be considerably less than the expected lifetime of the component. To overcome such a problem, there is the accelerated life-testing alternative aimed at forcing components to fail by testing them at much higher-than-intended application conditions. These models are known as acceleration models. One possible way to translate test results obtained under accelerated conditions to normal using conditions could be through the application of the “Maxwell Distribution Law.” In this paper we will apply a combined approach of a sequential life testing and an accelerated life testing to a low alloy high-strength steel component used in the construction of overpasses in Brazil. The underlying sampling distribution will be three-parameter Inverse Weibull model. To estimate the three parameters of the Inverse Weibull model we will use a maximum likelihood approach for censored failure data. We will be assuming a linear acceleration condition. To evaluate the accuracy (significance) of the parameter values obtained under normal conditions for the underlying Inverse Weibull model we will apply to the expected normal failure times a sequential life testing using a truncation mechanism. An example will illustrate the application of this procedure.
Abstract: Background: Dimensional and transdiagnostic approaches as a result of high comorbidity among mental disorders have captured researchers and clinicians interests for exploring the latent factors to development and maintenance of some psychological disorders. The goal of present study is comparing some of these common factors between generalized anxiety disorder and unipolar mood disorder. Methods: 27 patients with generalized anxiety disorder, 29 patients with depression disorder were recruited by using SCID-I and 69 non-clinical populations were selected by using GHQ cut off point. MANCOVA was used for analyzing data. Results: The results show that worry, rumination, intolerance of uncertainty, maladaptive metacognitive beliefs, and experiential avoidance were all significantly different between GAD and unipolar mood disorder groups. However, there weren’t any significant differences in difficulties in emotion regulation and neuroticism between GAD and unipolar mood disorder groups. Discussion: Results indicate that although there are some transdiagnostic and common factors in GAD and unipolar mood disorder, there may be some specific vulnerability factors for each disorder. Further study is needed for answering these questions.
Abstract: Although many factors play a significant role in agricultural production and productivity, the importance of soil fertility cannot be underestimated. The extent to which small farmers are able to manage the fertility of their farmlands is crucial in agricultural development particularly in sub-Saharan Africa (SSA). This paper assesses the nutrient status of selected farmers’ fields in relation to how government policy addresses the allocation of and access to agricultural inputs (e.g. chemical fertilizers) in a unique social-ecological environment of the Okavango Delta in northern Botswana. It also analyses small farmers and soil scientists’ perceptions about the political economy of integrated soil fertility management (ISFM) in the area. A multi-stage sampling procedure was used to elicit quantitative and qualitative information from 228 farmers and 9 soil researchers through the use of interview schedules and questionnaires, respectively. Knowledge validation workshops and focus group discussions (FGDs) were also used to collect qualitative data from farmers. Thirty-three composite soil samples were collected from 30 farmers’ plots in three farming communities of Makalamabedi, Nokaneng and Mohembo for laboratory analysis. While meeting points exist, farmers and scientists have divergent perspectives on soil fertility management. Laboratory analysis carried out shows that most soils in the wetland and the adjoining dry-land/upland surroundings are low in essential nutrients as well as in cation exchange capacity (CEC). Although results suggest the identification and use of appropriate inorganic fertilizers, the low CEC is an indication that holistic cultural practices, which are beyond mere chemical fertilizations, are critical and more desirable for improved soil health and sustainable livelihoods in the area. Farmers’ age (t= -0.728; p≤0.10); their perceptions about the political economy (t = -0.485; p≤0.01) of ISFM; and their preference for the use of local knowledge in soil fertility management (t = -10.254; p≤0.01) had a significant relationship with how they perceived their involvement in the implementation of ISFM.
Abstract: The robust control system objects with interval- undermined parameters is considers in this paper. Initial information about the system is its characteristic polynomial with interval coefficients. On the basis of coefficient estimations of quality indices and criterion of the maximum stability degree, the methods of synthesis of a robust regulator parametric is developed. The example of the robust stabilization system synthesis of the rope tension is given in this article.
Abstract: Modelling is a widely used tool to facilitate the evaluation of disease management. The interest of epidemiological models lies in their ability to explore hypothetical scenarios and provide decision makers with evidence to anticipate the consequences of disease incursion and impact of intervention strategies.
All models are, by nature, simplification of more complex systems. Models that involve diseases can be classified into different categories depending on how they treat the variability, time, space, and structure of the population. Approaches may be different from simple deterministic mathematical models, to complex stochastic simulations spatially explicit.
Thus, epidemiological modelling is now a necessity for epidemiological investigations, surveillance, testing hypotheses and generating follow-up activities necessary to perform complete and appropriate analysis.
The state of the art presented in the following, allows us to position itself to the most appropriate approaches in the epidemiological study.
Abstract: Recent experimental evidences have shown that because
of a fast convergence and a nice accuracy, neural networks training
via extended kalman filter (EKF) method is widely applied. However,
as to an uncertainty of the system dynamics or modeling error, the
performance of the method is unreliable. In order to overcome this
problem in this paper, a new finite impulse response (FIR) filter based
learning algorithm is proposed to train radial basis function neural
networks (RBFN) for nonlinear function approximation. Compared
to the EKF training method, the proposed FIR filter training method
is more robust to those environmental conditions. Furthermore , the
number of centers will be considered since it affects the performance
of approximation.
Abstract: Paper presents an comparative evaluation of features extraction algorithm for a real-time isolated word recognition system
based on FPGA. The Mel-frequency cepstral, linear frequency cepstral, linear predictive and their cepstral coefficients were
implemented in hardware/software design. The proposed system was investigated in speaker dependent mode for 100 different
Lithuanian words. The robustness of features extraction algorithms was tested recognizing the speech records at different signal to noise rates. The experiments on clean records show highest accuracy for Mel-frequency cepstral and linear frequency cepstral coefficients. For records with 15 dB signal to noise rate the linear predictive cepstral coefficients gives best result. The hard and soft part of the system is clocked on 50 MHz and 100 MHz accordingly. For the classification purpose the pipelined dynamic time warping core was implemented. The proposed word recognition system satisfy the real-time requirements and is suitable for applications in embedded systems.