Energy Efficient Clustering Algorithm with Global and Local Re-clustering for Wireless Sensor Networks

Wireless Sensor Networks consist of inexpensive, low power sensor nodes deployed to monitor the environment and collect data. Gathering information in an energy efficient manner is a critical aspect to prolong the network lifetime. Clustering  algorithms have an advantage of enhancing the network lifetime. Current clustering algorithms usually focus on global re-clustering and local re-clustering separately. This paper, proposed a combination of those two reclustering methods to reduce the energy consumption of the network. Furthermore, the proposed algorithm can apply to homogeneous as well as heterogeneous wireless sensor networks. In addition, the cluster head rotation happens, only when its energy drops below a dynamic threshold value computed by the algorithm. The simulation result shows that the proposed algorithm prolong the network lifetime compared to existing algorithms.

Monte Carlo Simulation of Copolymer Heterogeneity in Atom Transfer Radical Copolymerization of Styrene and N-Butyl Acrylate

A high-performance Monte Carlo simulation, which simultaneously takes diffusion-controlled and chain-length-dependent bimolecular termination reactions into account, is developed to simulate atom transfer radical copolymerization of styrene and nbutyl acrylate. As expected, increasing initial feed fraction of styrene raises the fraction of styrene-styrene dyads (fAA) and reduces that of n-butyl acrylate dyads (fBB). The trend of variation in randomness parameter (fAB) during the copolymerization also varies significantly. Also, there is a drift in copolymer heterogeneity and the highest drift occurs in the initial feeds containing lower percentages of styrene, i.e. 20% and 5%.

A New Technique for Multi Resolution Characterization of Epileptic Spikes in EEG

A technique proposed for the automatic detection of spikes in electroencephalograms (EEG). A multi-resolution approach and a non-linear energy operator are exploited. The signal on each EEG channel is decomposed into three sub bands using a non-decimated wavelet transform (WT). The WT is a powerful tool for multi-resolution analysis of non-stationary signal as well as for signal compression, recognition and restoration. Each sub band is analyzed by using a non-linear energy operator, in order to detect spikes. A decision rule detects the presence of spikes in the EEG, relying upon the energy of the three sub-bands. The effectiveness of the proposed technique was confirmed by analyzing both test signals and EEG layouts.

High Speed Video Transmission for Telemedicine using ATM Technology

In this paper, we study statistical multiplexing of VBR video in ATM networks. ATM promises to provide high speed realtime multi-point to central video transmission for telemedicine applications in rural hospitals and in emergency medical services. Video coders are known to produce variable bit rate (VBR) signals and the effects of aggregating these VBR signals need to be determined in order to design a telemedicine network infrastructure capable of carrying these signals. We first model the VBR video signal and simulate it using a generic continuous-data autoregressive (AR) scheme. We carry out the queueing analysis by the Fluid Approximation Model (FAM) and the Markov Modulated Poisson Process (MMPP). The study has shown a trade off: multiplexing VBR signals reduces burstiness and improves resource utilization, however, the buffer size needs to be increased with an associated economic cost. We also show that the MMPP model and the Fluid Approximation model fit best, respectively, the cell region and the burst region. Therefore, a hybrid MMPP and FAM completely characterizes the overall performance of the ATM statistical multiplexer. The ramifications of this technology are clear: speed, reliability (lower loss rate and jitter), and increased capacity in video transmission for telemedicine. With migration to full IP-based networks still a long way to achieving both high speed and high quality of service, the proposed ATM architecture will remain of significant use for telemedicine.

Faculty Stress at Higher Education: A Study on the Business Schools of Pakistan

Job stress is one of the most important concepts for the today-s corporate as well as institutional world. The current study is conducted to identify the causes of faculty stress at Higher Education in Pakistan. For the purpose, Public & Private Business Schools of Punjab is selected as representative of Pakistan. A sample of 300 faculty members (214 males, 86 females) responded to the survey. Regression analysis shows that the Workload, Student Related issues and Role Conflicts are the major sources contributing significantly towards producing stress. The study also revealed that Private sector faculty members experienced more stress as compared to faculty in Public sector Business Schools. Moreover, females, younger ages, lower designation & low qualification faculty members experience more stress as compared to males, older ages, higher designation and high qualification. The study yield many significant results for the policy makers of Business Institutions.

Binding of miR398 to mRNA of Chaperone and Superoxide Dismutase Genes in Plants

Among all microRNAs (miRNAs) in 12 plant species investigated in this study, only miR398 targeted the copper chaperone for superoxide dismutase (CCS). The nucleotide sequences of miRNA binding sites were located in the mRNA protein-coding sequence (CDS) and were highly homologous. These binding sites in CCS mRNA encoded a conservative GDLGTL hexapeptide. The binding sites for miR398 in the CDS of superoxide dismutase 1 mRNA encoded GDLGN pentapeptide. The conservative miR398 binding site located in the CDS of superoxide dismutase 2 mRNA encoded the GDLGNI hexapeptide. The miR398 binding site in the CDS of superoxide dismutase 3 mRNA encoded the GDLGNI or GDLGNV hexapeptide. Gene expression of the entire superoxide dismutase family in the studied plant species was regulated only by miR398. All members of the miR398 family, i.e. miR398a,b,c were connected to one site for each CuZnSOD and chaperone mRNA.

Hardware Centric Machine Vision for High Precision Center of Gravity Calculation

We present a hardware oriented method for real-time measurements of object-s position in video. The targeted application area is light spots used as references for robotic navigation. Different algorithms for dynamic thresholding are explored in combination with component labeling and Center Of Gravity (COG) for highest possible precision versus Signal-to-Noise Ratio (SNR). This method was developed with a low hardware cost in focus having only one convolution operation required for preprocessing of data.

Face Localization Using Illumination-dependent Face Model for Visual Speech Recognition

A robust still image face localization algorithm capable of operating in an unconstrained visual environment is proposed. First, construction of a robust skin classifier within a shifted HSV color space is described. Then various filtering operations are performed to better isolate face candidates and mitigate the effect of substantial non-skin regions. Finally, a novel Bhattacharyya-based face detection algorithm is used to compare candidate regions of interest with a unique illumination-dependent face model probability distribution function approximation. Experimental results show a 90% face detection success rate despite the demands of the visually noisy environment.

Prerequisites to Increase the Purchase Intent fora Socially Responsible Company –Development of a Scale

Increasing attention has been given in academia to the concept of corporate social responsibility. Also, the number of companies that undertake social responsibility initiatives has been boosting day by day since behaving in a socially responsible manner brings a lot to the companies. Literature provides various benefits of social responsibility and under which situations these benefits could be realized. However, most of these studies focus on one aspect of the consequences of behaving in a socially responsible manner and there is no study that unifies the conditions that a company should fulfill to make customers prefer its brand. This study aims to fill this gap. More specifically, the purpose of this study is to identify the conditions that a socially responsible company should fulfill in order to attract customers. To this end, a scale is developed and its reliability and validity is assessed through the method of Multitrait- Multimethod Matrix.

Problems that Impede Sustainable Tourism Development in Egypt

This paper analysis the tourism development on the Red Sea in Egypt (west bank) and the needed ongoing action toward a sustainable approach. It addresses, at the first, the development's evolution occurred in the coastal area, the environmental effects it left, and how to minimize those impacts in the future. The second main point is dealing with the most important issues that hinder the achievement of sustainable tourism development on the Red Sea coast and how we can overcome them in the future.

Coalescing Data Marts

OLAP uses multidimensional structures, to provide access to data for analysis. Traditionally, OLAP operations are more focused on retrieving data from a single data mart. An exception is the drill across operator. This, however, is restricted to retrieving facts on common dimensions of the multiple data marts. Our concern is to define further operations while retrieving data from multiple data marts. Towards this, we have defined six operations which coalesce data marts. While doing so we consider the common as well as the non-common dimensions of the data marts.

Islam and Kazakh Society before Soviet Era

The article considers religious aspects of Kazakh society pre-Soviet times. Studying the mental, political and spiritual content of Islam, the reasons for its wide distribution among the ancestors of the Kazakhs is analyzed. Interested Russians since the accession of the Kazakh Khanate to the Russian Empire more than once pointed out that Islam is a synthesis of Islam and Shamanism. But shamanism is a generalization of the name of religion, which took place prior to Islam in the land of the Kazakh people. Here we can see the elements of Zoroastrianism, Tengrianism, etc. This shows that the ancestors of the Kazakhs - Turkic people - not renounced the ancient beliefs completely and leave some portion of these religions as an integral part of the worldview of the people, by the device. Therefore, the founder of the Turkic Sufi Yasaui still has a huge impact on the religiosity of the Kazakhs. He managed elements of the ancient religion, which formed the basis of the Kazakhs world, interpreted in the Muslim perspective. The Russian authorities tried to quell by Islamization Kazakh people. But it was Islam that has revived the national consciousness of the Kazakh people.

Designing of Multi-Agent Rescue Robot: Development and Basic Experiments of Master-Slave Type Rescue Robots

A multi-agent type robot for disaster response in calamity scene is proposed in this paper. The proposed grouped rescue robots can perform cooperative reconnaissance and surveillance to achieve a given rescue mission. The multi-agent rescue of dual set robot consists of one master set and three slave units. The research for this rescue robot system is going to detect at harmful environment where human is unreachable, such as the building is infected with virus or the factory has hazardous liquid in effluent. As a dual set robot, with Bluetooth and communication network, the master set can connect with slave units and send information back to computer by wireless and monitor. Therefore, rescuer can be informed the real-time information in a calamity area. Furthermore, each slave robot is able to obstacle avoidance by ultrasonic sensors, and encodes distance and location by compass. The master robot can integrate every devices information to increase the efficiency of prospected and research unknown area.

Novel Methods for Desulfurization of Fuel Oils

Because of the requirement for low sulfur content of fuel oils, it is necessary to develop alternative methods for desulfurization of heavy fuel oil. Due to the disadvantages of HDS technologies such as costs, safety and green environment, new methods have been developed. Among these methods is ultrasoundassisted oxidative desulfurization. Using ultrasound-assisted oxidative desulfurization, compounds such as benzothiophene and dibenzothiophene can be oxidized. As an alternative method is sulfur elimination of heavy fuel oil by using of activated carbon in a packed column in batch condition. The removal of sulfur compounds in this case to reach about 99%. The most important property of activated carbon is ability of it for adsorption, which is due to high surface area and pore volume of it.

Evaluation of Energy-Aware QoS Routing Protocol for Ad Hoc Wireless Sensor Networks

Many advanced Routing protocols for wireless sensor networks have been implemented for the effective routing of data. Energy awareness is an essential design issue and almost all of these routing protocols are considered as energy efficient and its ultimate objective is to maximize the whole network lifetime. However, the introductions of video and imaging sensors have posed additional challenges. Transmission of video and imaging data requires both energy and QoS aware routing in order to ensure efficient usage of the sensors and effective access to the gathered measurements. In this paper, the performance of the energy-aware QoS routing Protocol are analyzed in different performance metrics like average lifetime of a node, average delay per packet and network throughput. The parameters considered in this study are end-to-end delay, real time data generation/capture rates, packet drop probability and buffer size. The network throughput for realtime and non-realtime data was also has been analyzed. The simulation has been done in NS2 simulation environment and the simulation results were analyzed with respect to different metrics.

Layout Based Spam Filtering

Due to the constant increase in the volume of information available to applications in fields varying from medical diagnosis to web search engines, accurate support of similarity becomes an important task. This is also the case of spam filtering techniques where the similarities between the known and incoming messages are the fundaments of making the spam/not spam decision. We present a novel approach to filtering based solely on layout, whose goal is not only to correctly identify spam, but also warn about major emerging threats. We propose a mathematical formulation of the email message layout and based on it we elaborate an algorithm to separate different types of emails and find the new, numerically relevant spam types.

Microscopic Analysis of Welded Dental Alloys

Microplasma welding is a less expensive alternative to laser welding in dental technology. The aim of the study was to highlight discontinuities present in the microplasma welded joints of dental base metal alloys by visual analysis. Five base metal alloys designated for fixed prostheses manufacture were selected for the experiments. Using these plates, preliminary tests were conducted by microplasma welding in butt joint configuration, without filler material, bilaterally and with filler material, proper for each base metal. Macroscopic visual inspection was performed to assess carefully the irregularities in the welds. Electron microscopy allowed detection of discontinuities that are not visible to the eye and revealing details regarding location, trajectory, morphology and size of discontinuities. Supplementing visual control with microscopic analysis allows to detect small discontinuities, which escapes the macroscopic control and to make a detailed study of the weld.

Text-Mining Approach for Evaluation of Affective Management Practices

The purpose of this paper is to propose a text mining approach to evaluate companies- practices on affective management. Affective management argues that it is critical to take stakeholders- affects into consideration during decision-making process, along with the traditional numerical and rational indices. CSR reports published by companies were collected as source information. Indices were proposed based on the frequency and collocation of words relevant to affective management concept using text mining approach to analyze the text information of CSR reports. In addition, the relationships between the results obtained using proposed indices and traditional indicators of business performance were investigated using correlation analysis. Those correlations were also compared between manufacturing and non-manufacturing companies. The results of this study revealed the possibility to evaluate affective management practices of companies based on publicly available text documents.

Using Copulas to Measure Association between Air Pollution and Respiratory Diseases

Air pollution is still considered as one of the major environmental and health issues. There is enough research evidence to show a strong relationship between exposure to air contaminants and respiratory illnesses among children and adults. In this paper we used the Copula approach to study a potential relationship between selected air pollutants (PM10 and NO2) and hospital admissions for respiratory diseases. Kendall-s tau and Spearman-s rho rank correlation coefficients are calculated and used in Copula method. This paper demonstrates that copulas can be used to provide additional information as a measure of an association when compared to the standard correlation coefficients. The results find a significant correlation between the selected air pollutants and hospital admissions for most of the selected respiratory illnesses.

Optimization of Energy Conservation Potential for VAV Air Conditioning System using Fuzzy based Genetic Algorithm

The objective of this study is to present the test results of variable air volume (VAV) air conditioning system optimized by two objective genetic algorithm (GA). The objective functions are energy savings and thermal comfort. The optimal set points for fuzzy logic controller (FLC) are the supply air temperature (Ts), the supply duct static pressure (Ps), the chilled water temperature (Tw), and zone temperature (Tz) that is taken as the problem variables. Supply airflow rate and chilled water flow rate are considered to be the constraints. The optimal set point values are obtained from GA process and assigned into fuzzy logic controller (FLC) in order to conserve energy and maintain thermal comfort in real time VAV air conditioning system. A VAV air conditioning system with FLC installed in a software laboratory has been taken for the purpose of energy analysis. The total energy saving obtained in VAV GA optimization system with FLC compared with constant air volume (CAV) system is expected to achieve 31.5%. The optimal duct static pressure obtained through Genetic fuzzy methodology attributes to better air distribution by delivering the optimal quantity of supply air to the conditioned space. This combination enhanced the advantages of uniform air distribution, thermal comfort and improved energy savings potential.