Abstract: For those who have lost the ability to move their hand, going through repetitious motions with the assistance of a therapist is the main method of recovery. We have been developed a robotic assistive device to rehabilitate the hand motions in place of the traditional therapy. The developed assistive device (RAD-HR) is comprised of four degrees of freedom enabling basic movements, hand function, and assists in supporting the hand during rehabilitation. We used a nonlinear computed torque control technique to control the RAD-HR. The accuracy of the controller was evaluated in simulations (MATLAB/Simulink environment). To see the robustness of the controller external disturbance as modelling uncertainty (±10% of joint torques) were added in each joints.
Abstract: The present study investigated approaches and techniques to enhance strategic management governance and decision making within the framework of a performance-based balanced scorecard. The review of best practices from strategic, program, process, and systems engineering management provided for a holistic approach toward effective outcome-based capability management. One technique, based on factorial experimental design methods, was used to develop an empirical model. This model predicted the degree of capability effectiveness and is dependent on controlled system input variables and their weightings. These variables represent business performance measures, captured within a strategic balanced scorecard. The weighting of these measures enhances the ability to quantify causal relationships within balanced scorecard strategy maps. The focus in this study was on the performance of tangible assets within the scorecard rather than the traditional approach of assessing performance of intangible assets such as knowledge and technology. Tangible assets are represented in this study as physical systems, which may be thought of as being aboard a ship or within a production facility. The measures assigned to these systems include project funding for upgrades against demand, system certifications achieved against those required, preventive maintenance to corrective maintenance ratios, and material support personnel capacity against that required for supporting respective systems. The resultant scorecard is viewed as complimentary to the traditional balanced scorecard for program and performance management. The benefits from these scorecards are realized through the quantified state of operational capabilities or outcomes. These capabilities are also weighted in terms of priority for each distinct system measure and aggregated and visualized in terms of overall state of capabilities achieved. This study proposes the use of interactive controls within the scorecard as a technique to enhance development of alternative solutions in decision making. These interactive controls include those for assigning capability priorities and for adjusting system performance measures, thus providing for what-if scenarios and options in strategic decision-making. In this holistic approach to capability management, several cross functional processes were highlighted as relevant amongst the different management disciplines. In terms of assessing an organization’s ability to adopt this approach, consideration was given to the P3M3 management maturity model.
Abstract: The present work illustrates a parametric study for the effect of stiffeners on the performance of slender built up steel I-columns. To achieve the desired analysis, finite element technique is used to develop nonlinear three-dimensional models representing the investigated columns. The finite element program (ANSYS 13.0) is used as a calculation tool for the necessary nonlinear analysis. A validation of the obtained numerical results is achieved. The considered parameters in the study are the column slenderness ratio and the horizontal stiffener's dimensions as well as the number of stiffeners. The dimensions of the stiffeners considered in the analysis are the stiffener width and the stiffener thickness. Numerical results signify a considerable effect of stiffeners on the performance and failure load of slender built up steel I-columns.
Abstract: In this paper, we have analyzed and compared the performance of various coding schemes. The basic ID prime sequence codes are unique in only dimension, i.e. time slots, whereas 2D coding techniques are not unique by their time slots but with their wavelengths also. In this research, we have evaluated and compared the performance of 1D and 2D coding techniques constructed using prime sequence coding pattern for Optical Code Division Multiple Access (OCDMA) system on a single platform. Analysis shows that 2D prime code supports lesser number of active users than 1D codes, but they are having large code family and are the most secure codes compared to other codes. The performance of all these codes is analyzed on basis of number of active users supported at a Bit Error Rate (BER) of 10-9.
Abstract: Public health is one of the most critical issues today;
therefore, there is great interest to improve technologies in the area
of diseases detection. With machine learning and feature selection,
it has been possible to aid the diagnosis of several diseases such
as cancer. In this work, we present an extension to the Heat Map
Based Feature Selection algorithm, this modification allows automatic
threshold parameter selection that helps to improve the generalization
performance of high dimensional data such as mass spectrometry.
We have performed a comparison analysis using multiple cancer
datasets and compare against the well known Recursive Feature
Elimination algorithm and our original proposal, the results show
improved classification performance that is very competitive against
current techniques.
Abstract: We present a robust nonlinear parabolic partial
differential equation (PDE)-based denoising scheme in this article.
Our approach is based on a second-order anisotropic diffusion model
that is described first. Then, a consistent and explicit numerical
approximation algorithm is constructed for this continuous model by
using the finite-difference method. Finally, our restoration
experiments and method comparison, which prove the effectiveness
of this proposed technique, are discussed in this paper.
Abstract: The objective of this study was to investigate the
awareness, knowledge and consumer behavior towards organic
products in Thailand. For this study, a purposive sampling technique
was used to identify a sample group of 2,575 consumers over the age
of 20 years who intended or made purchases from 1) green shops; 2)
supermarkets with branches; and, 3) green markets. A questionnaire
was used for data collection across the country. Descriptive statistics
were used for data analysis. The results showed that more than 92%
of consumers were aware of organic agriculture, but had less
knowledge about it. More than 60% of consumers knew that organic
agriculture production and processing did not allow the use of
chemicals. And about 40% of consumers were confused between the
food safety logo and the certified organic logo, and whether GMO
was allowed in organic agriculture practice or not. In addition, most
consumers perceived that organic agricultural products, good
agricultural practice (GAP) products, agricultural chemicals free
products, and hydroponic vegetable products had the same standard.
In the view of organic consumers, the organic Thailand label was the
most seen and reliable among various organic labels. Less than 3% of
consumers thought that the International Federation of Organic
Agriculture Movements (IFOAM) Global Organic Mark (GOM) was
the most seen and reliable. For the behaviors of organic consumers,
they purchased organic products mainly at the supermarket and green
shop (55.4%), one to two times per month, and with a total
expenditure of about 200 to 400 baht each time. The main reason for
buying organic products was safety and free from agricultural
chemicals. The considered factors in organic product selection were
price (29.5%), convenience (22.4%), and a reliable certification
system (21.3%). The demands for organic products were mainly rice,
vegetables and fruits. Processed organic products were relatively
small in quantity.
Abstract: Elicitation of creative conceptual designing and fabrication of mini bikes is the primary aim of this study. Miniature bikes or pit bikes or simply mini bikes are found to be the recently prevalent trendsetters amongst the younger population around the globe, be it for commuting and sports. This study also focuses on the steps to be put forth in building a self-designed mini bike concept and showcases similar instances.
Abstract: This paper describes an approach to detect the
transmitted signals for 2×2 Multiple Input Multiple Output (MIMO)
setup using roulette wheel based ant colony optimization technique.
The results obtained are compared with classical zero forcing and
least mean square techniques. The detection rates achieved using
this technique are consistently larger than the one achieved using
classical methods for 50 number of attempts with two different
antennas transmitting the input stream from a user. This paves the
path to use alternative techniques to improve the throughput achieved
in advanced networks like Long Term Evolution (LTE) networks.
Abstract: This research seeks to investigate how the globalisation of fast food has affected students’ food choice. A mixed method approach was used in this research; basically involving quantitative and qualitative methods. The quantitative method uses a self-completion questionnaire to randomly sample one hundred and four students; while the qualitative method uses a semi structured interview technique to survey four students on their knowledge and choice to consume fast food. A cross tabulation of variables and the Kruskal Wallis nonparametric test were used to analyse the quantitative data; while the qualitative data was analysed through deduction of themes, and trends from the interview transcribe. The findings revealed that globalisation has amplified the evolution of fast food, popularising it among students. Its global presence has affected students’ food choice and preference. Price, convenience, taste, and peer influence are some of the major factors affecting students’ choice of fast food. Though, students are familiar with the health effect of fast food and the significance of using food information labels for healthy choice making, their preference of fast food is more than homemade food.
Abstract: Human action is recognized directly from the video sequences. The objective of this work is to recognize various human actions like run, jump, walk etc. Human action recognition requires some prior knowledge about actions namely, the motion estimation, foreground and background estimation. Region of interest (ROI) is extracted to identify the human in the frame. Then, optical flow technique is used to extract the motion vectors. Using the extracted features similarity measure based classification is done to recognize the action. From experimentations upon the Weizmann database, it is found that the proposed method offers a high accuracy.
Abstract: Rendering light shafts is one of the important topics in computer gaming and interactive applications. The methods and models that are used to generate light shafts play crucial role to make a scene more realistic in computer graphics. This article discusses the image-based shadows and geometric-based shadows that contribute in generating volumetric shadows and light shafts, depending on ray tracing, radiosity, and ray marching technique. The main aim of this study is to provide researchers with background on a progress of light scattering methods so as to make it available for them to determine the technique best suited to their goals. It is also hoped that our classification helps researchers find solutions to the shortcomings of each method.
Abstract: Due to the drastic increase of the wind turbines installed capacity; the grid codes are increasing the restrictions aiming to treat the wind turbines like other conventional sources sooner. In this paper, an intensive review has been presented for different techniques used to add low voltage ride through capability to Doubly Fed Induction Generator (DFIG) wind turbine. A system model with 1.5 MW DFIG wind turbine is constructed and simulated using MATLAB/SIMULINK to explore the effectiveness of the reviewed techniques.
Abstract: The present paper aims to investigate the effects of the welding process parameters and cooling state on the weld bead geometry, mechanical properties and microstructure characteristics for weldments of AISI 304L stainless steel. The welding process was carried out using TIG welding with pulsed/non-pulsed current techniques. The cooling state was introduced as an input parameter to investigate the main effects on the structure morphology and thereby the mechanical property. This paper clarifies microstructure- mechanical property relationship of the welded specimens. In this work, the selected pulse frequency levels were 5-500 Hz in order to study the effect of low and high frequencies on the weldment characteristics using filler metal of ER 308LSi. The key findings of this work clarified that the pulse frequency has a significant effect on the breaking of the dendrite arms during the welding process and so strongly influences on the tensile strength and microhardness. The cooling state also significantly affects on the microstructure texture and thereby, the mechanical properties. The most important factor affects the bead geometry and aspect ratio is the travel speed and pulse frequency.
Abstract: Every year, fog formation over the Indo-Gangetic Plains (IGPs) of Indian region during the winter months of December and January is believed to create numerous hazards, inconvenience, and economic loss to the inhabitants of this densely populated region of Indian subcontinent. The aim of the paper is to analyze the spatial and temporal variability of winter fog over IGPs. Long term ground observations of visibility and other meteorological parameters (1971-2010) have been analyzed to understand the formation of fog phenomena and its relevance during the peak winter months of January and December over IGP of India. In order to examine the temporal variability, time series and trend analysis were carried out by using the Mann-Kendall Statistical test. Trend analysis performed by using the Mann-Kendall test, accepts the alternate hypothesis with 95% confidence level indicating that there exists a trend. Kendall tau’s statistics showed that there exists a positive correlation between time series and fog frequency. Further, the Theil and Sen’s median slope estimate showed that the magnitude of trend is positive. Magnitude is higher during January compared to December for the entire IGP except in December when it is high over the western IGP. Decade wise time series analysis revealed that there has been continuous increase in fog days. The net overall increase of 99 % was observed over IGP in last four decades. Diurnal variability and average daily persistence were computed by using descriptive statistical techniques. Geo-statistical analysis of fog was carried out to understand the spatial variability of fog. Geo-statistical analysis of fog revealed that IGP is a high fog prone zone with fog occurrence frequency of more than 66% days during the study period. Diurnal variability indicates the peak occurrence of fog is between 06:00 and 10:00 local time and average daily fog persistence extends to 5 to 7 hours during the peak winter season. The results would offer a new perspective to take proactive measures in reducing the irreparable damage that could be caused due to changing trends of fog.
Abstract: Wireless Sensor Networks (WSNs) are suitable for many scenarios in the real world. The retrieval of data is made efficient by the data aggregation techniques. Many techniques for the data aggregation are offered and most of the existing schemes are not energy efficient and secure. However, the existing techniques use the traditional clustering approach where there is a delay during the packet transmission since there is no proper scheduling. The presented system uses the Velocity Energy-efficient and Link-aware Cluster-Tree (VELCT) scheme in which there is a Data Collection Tree (DCT) which improves the lifetime of the network. The VELCT scheme and the construction of DCT reduce the delay and traffic. The network lifetime can be increased by avoiding the frequent change in cluster topology. Secure and Efficient Transmission of Aggregated data (SETA) improves the security of the data transmission via the trust value of the nodes prior the aggregation of data. Since SETA considers the data only from the trustworthy nodes for aggregation, it is more secure in transmitting the data thereby improving the accuracy of aggregated data.
Abstract: Diabetic Retinopathy (DR) is a severe retinal disease which is caused by diabetes mellitus. It leads to blindness when it progress to proliferative level. Early indications of DR are the appearance of microaneurysms, hemorrhages and hard exudates. In this paper, an automatic algorithm for detection of DR has been proposed. The algorithm is based on combination of several image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLAHE), Gabor filter and thresholding. Also, Support Vector Machine (SVM) Classifier is used to classify retinal images to normal or abnormal cases including non-proliferative or proliferative DR. The proposed method has been tested on images selected from Structured Analysis of the Retinal (STARE) database using MATLAB code. The method is perfectly able to detect DR. The sensitivity specificity and accuracy of this approach are 90%, 87.5%, and 91.4% respectively.
Abstract: In the field of production, characterization of surface
roughness plays a vital role in assessing the quality of a manufactured
product. The defined parameters for this assessment, each, have their
own drawbacks in describing a profile surface. From the purview of
small-scale and medium-scale industries, an increase in time spent for
manual inspection of a product for various parameters adds to the
cost of the product. In order to reduce this, a uniform and established
standard is necessary for quantifying a profile of a manufactured
product. The inspection procedure in the small and medium-scale
manufacturing units at Jigani Industrial area, Bangalore, was
observed. The parameters currently in use in those industries are
described in the paper and a change in the inspection method is
proposed.
Abstract: Knowledge management (KM) literature has mainly focused on the antecedents of KM. The purpose of this study is to investigate the effect of specific human resource management (HRM) practices on employee knowledge sharing and its outcome as individual knowledge capability. Based on previous literature, a model is proposed for the study and hypotheses are formulated. The cross-sectional dataset comes from a sample of 19 knowledge intensive firms (KIFs). This study has run an item parceling technique followed by Confirmatory Factor Analysis (CFA) on the latent constructs of the research model. Employees’ collaboration and their interpersonal trust can help to improve their knowledge sharing behaviour and knowledge capability within organisations. This study suggests that in future, by using a larger sample, better statistical insight is possible. The findings of this study are beneficial for scholars, policy makers and practitioners. The empirical results of this study are entirely based on employees’ perceptions and make a significant research contribution, given there is a dearth of empirical research focusing on the subcontinent.
Abstract: Data mining and classification of objects is the process of data analysis, using various machine learning techniques, which is used today in various fields of research. This paper presents a concept of hybrid classification model improved with the expert knowledge. The hybrid model in its algorithm has integrated several machine learning techniques (Information Gain, K-means, and Case-Based Reasoning) and the expert’s knowledge into one. The knowledge of experts is used to determine the importance of features. The paper presents the model algorithm and the results of the case study in which the emphasis was put on achieving the maximum classification accuracy without reducing the number of features.