Ethnobotany and Distribution of Dioscoreahispida Dennst. (Dioscoreaceae) in Besut, Marang and Setiu Districts of Terengganu, Peninsular Malaysia

Dioscorea species or commonly named as yam is reported to be one of the major food sources worldwide. This ethnobotanical study was conducted to document local knowledge and potentials of DioscoreahispidaDennst. and to investigate and record its distribution in three districts of Terengganu. Information was gathered from 23 villagers from three districts of Besut, Marang and Setiu by using semi-structured questionnaire. The villagers were randomly selected and no appointment was made prior to the visits. For distribution, the location of Dioscoreahispida was recorded by using the Global Positioning System (GPS). The villagers identified Dioscoreahispida or locally named ubigadong by looking at the physical characteristics that include its leaf shape, stem and the color of the tuber-s flesh. The villagers used Dioscoreahispida in many ways in their life such as for food, medicinal purposes and fish poison.

Nonlinear Seismic Dynamic Response of Continuous Curved Highway Viaducts with Different Bearing Supports

The results show that the bridge equipped with seismic isolation bearing system shows a high amount of energy dissipation. The purpose of the present study is to analyze the overall performance of continuous curved highway viaducts with different bearing supports, with an emphasis on the effectiveness of seismic isolation based on lead rubber bearing and hedge reaction force bearing system consisted of friction sliding bearing and rubber bearing. The bridge seismic performance has been evaluated on six different cases with six bearing models. The effects of the different arrangement of bearing on the deck superstructure displacements, the seismic damage at the bottom of the piers, movement track at the pier-s top and the total and strain energies absorbed by the structure are evaluated. In conclusion, the results provide sufficient evidence of the effectiveness on the use of seismic isolation on steel curved highway bridges.

Combining Similarity and Dissimilarity Measurements for the Development of QSAR Models Applied to the Prediction of Antiobesity Activity of Drugs

In this paper we study different similarity based approaches for the development of QSAR model devoted to the prediction of activity of antiobesity drugs. Classical similarity approaches are compared regarding to dissimilarity models based on the consideration of the calculation of Euclidean distances between the nonisomorphic fragments extracted in the matching process. Combining the classical similarity and dissimilarity approaches into a new similarity measure, the Approximate Similarity was also studied, and better results were obtained. The application of the proposed method to the development of quantitative structure-activity relationships (QSAR) has provided reliable tools for predicting of inhibitory activity of drugs. Acceptable results were obtained for the models presented here.

Pregnancy Myths and Early Chilcare: Research Reflections from the Rural Punjab, Pakistan

Pregnancy is considered a special period in a woman’s life. There are myths about pregnancy that describe gender predictions, dietary beliefs, pregnancy signs, and risk of magic or witchcraft. Majority of these myths is in connection with the early childcare. In traditional societies midwives and experienced women practice and teach these myths to young mothers. Mother who feel special and vulnerable, at the same time feel secure in following these socially transmitted myths. Rural Punjab, a province of Pakistan has a culture rich with beliefs and myths. Myths about pregnancy are significant in rural culture and pregnancy care is seen as mother and childcare. This paper presents my research reflections that I did as a part of my Ph.D studies about early childcare beliefs and rituals practiced in rural Punjab, Pakistan.

Authentic Leadership, Trust and Work Engagement

The issue of leadership has been investigated from several perspectives; however, very less from ethical perspective. With the growing number of corporate scandals and unethical roles played by business leaders in several parts of the world, the need to examine leadership from ethical perspective cannot be over emphasized. The importance of leadership credibility has been discussed in the authentic model of leadership. Authentic leaders display high degree of integrity, have deep sense of purpose, and committed to their core values. As a result they promote a more trusting relationship in their work groups that translates into several positive outcomes. The present study examined how authentic leadership contribute to subordinates- trust in leadership and how this trust, in turn, predicts subordinates- work engagement. A sample of 395 employees was randomly selected from several local banks operating in Malaysia. Standardized tools such as ALQ, OTI, and EEQ were employed. Results indicated that authentic leadership promoted subordinates- trust in leader, and contributed to work engagement. Also, interpersonal trust predicted employees- work engagement as well as mediated the relationship between this style of leadership and employees- work engagement.

Flat Miniature Heat Pipes for Electronics Cooling: State of the Art, Experimental and Theoretical Analysis

An experimental study is realized in order to verify the Mini Heat Pipe (MHP) concept for cooling high power dissipation electronic components and determines the potential advantages of constructing mini channels as an integrated part of a flat heat pipe. A Flat Mini Heat Pipe (FMHP) prototype including a capillary structure composed of parallel rectangular microchannels is manufactured and a filling apparatus is developed in order to charge the FMHP. The heat transfer improvement obtained by comparing the heat pipe thermal resistance to the heat conduction thermal resistance of a copper plate having the same dimensions as the tested FMHP is demonstrated for different heat input flux rates. Moreover, the heat transfer in the evaporator and condenser sections are analyzed, and heat transfer laws are proposed. In the theoretical part of this work, a detailed mathematical model of a FMHP with axial microchannels is developed in which the fluid flow is considered along with the heat and mass transfer processes during evaporation and condensation. The model is based on the equations for the mass, momentum and energy conservation, which are written for the evaporator, adiabatic, and condenser zones. The model, which permits to simulate several shapes of microchannels, can predict the maximum heat transfer capacity of FMHP, the optimal fluid mass, and the flow and thermal parameters along the FMHP. The comparison between experimental and model results shows the good ability of the numerical model to predict the axial temperature distribution along the FMHP.

Humor Roles of Females in a Product Color Matrix

Healthcare providers sometimes use the power of humor as a treatment and therapy for buffering mental health or easing mental disorders because humor can provide relief from distress and conflict. Humor is also very suitable for advertising because of similar benefits. This study carefully examines humor's widespread use in advertising and identifies relationships among humor mechanisms, female depictions, and product types. The purpose is to conceptualize how humor theories can be used not only to successfully define a product as fitting within one of four color categories of the product color matrix, but also to identify compelling contemporary female depictions through humor in ads. The results can offer an idealization for marketing managers and consumers to help them understand how female role depictions can be effectively used with humor in ads. The four propositions developed herein are derived from related literature, through the identification of marketing strategy formulations that achieve product memory enhancement by adopting humor mechanisms properly matched with female role depictions.

Navigation and Self Alignment of Inertial Systems using Nonlinear H∞ Filters

Micro electromechanical sensors (MEMS) play a vital role along with global positioning devices in navigation of autonomous vehicles .These sensors are low cost ,easily available but depict colored noises and unpredictable discontinuities .Conventional filters like Kalman filters and Sigma point filters are not able to cope with nonwhite noises. This research has utilized H∞ filter in nonlinear frame work both with Kalman filter and Unscented filter for navigation and self alignment of an airborne vehicle. The system is simulated for colored noises and discontinuities and results are compared with not robust nonlinear filters. The results are found 40%-70% more robust against colored noises and discontinuities.

Improving Air Temperature Prediction with Artificial Neural Networks

The mitigation of crop loss due to damaging freezes requires accurate air temperature prediction models. Previous work established that the Ward-style artificial neural network (ANN) is a suitable tool for developing such models. The current research focused on developing ANN models with reduced average prediction error by increasing the number of distinct observations used in training, adding additional input terms that describe the date of an observation, increasing the duration of prior weather data included in each observation, and reexamining the number of hidden nodes used in the network. Models were created to predict air temperature at hourly intervals from one to 12 hours ahead. Each ANN model, consisting of a network architecture and set of associated parameters, was evaluated by instantiating and training 30 networks and calculating the mean absolute error (MAE) of the resulting networks for some set of input patterns. The inclusion of seasonal input terms, up to 24 hours of prior weather information, and a larger number of processing nodes were some of the improvements that reduced average prediction error compared to previous research across all horizons. For example, the four-hour MAE of 1.40°C was 0.20°C, or 12.5%, less than the previous model. Prediction MAEs eight and 12 hours ahead improved by 0.17°C and 0.16°C, respectively, improvements of 7.4% and 5.9% over the existing model at these horizons. Networks instantiating the same model but with different initial random weights often led to different prediction errors. These results strongly suggest that ANN model developers should consider instantiating and training multiple networks with different initial weights to establish preferred model parameters.

Application of a Fracture-Mechanics Approach to Gas Pipelines

This study offers a new simple method for assessing an axial part-through crack in a pipe wall. The method utilizes simple approximate expressions for determining the fracture parameters K, J, and employs these parameters to determine critical dimensions of a crack on the basis of equality between the J-integral and the J-based fracture toughness of the pipe steel. The crack tip constraint is taken into account by the so-called plastic constraint factor C, by which the uniaxial yield stress in the J-integral equation is multiplied. The results of the prediction of the fracture condition are verified by burst tests on test pipes.

Learning an Overcomplete Dictionary using a Cauchy Mixture Model for Sparse Decay

An algorithm for learning an overcomplete dictionary using a Cauchy mixture model for sparse decomposition of an underdetermined mixing system is introduced. The mixture density function is derived from a ratio sample of the observed mixture signals where 1) there are at least two but not necessarily more mixture signals observed, 2) the source signals are statistically independent and 3) the sources are sparse. The basis vectors of the dictionary are learned via the optimization of the location parameters of the Cauchy mixture components, which is shown to be more accurate and robust than the conventional data mining methods usually employed for this task. Using a well known sparse decomposition algorithm, we extract three speech signals from two mixtures based on the estimated dictionary. Further tests with additive Gaussian noise are used to demonstrate the proposed algorithm-s robustness to outliers.

Proposal of a Model Supporting Decision-Making on Information Security Risk Treatment

Management is required to understand all information security risks within an organization, and to make decisions on which information security risks should be treated in what level by allocating how much amount of cost. However, such decision-making is not usually easy, because various measures for risk treatment must be selected with the suitable application levels. In addition, some measures may have objectives conflicting with each other. It also makes the selection difficult. Therefore, this paper provides a model which supports the selection of measures by applying multi-objective analysis to find an optimal solution. Additionally, a list of measures is also provided to make the selection easier and more effective without any leakage of measures.

The Surface Adsorption of Nano-pore Template

This paper aims to fabricated high quality anodic aluminum oxide (AAO) film by anodization method. AAO pore size, pore density, and film thickness can be controlled in 10~500 nm, 108~1011 pore.cm-2, and 1~100 μm. AAO volume and surface area can be computed based on structural parameters such as thickness, pore size, pore density, and sample size. Base on the thetorical calculation, AAO has 100 μm thickness with 15 nm, 60 nm, and 500 nm pore diameters AAO surface areas are 1225.2 cm2, 3204.4 cm2, and 549.7 cm2, respectively. The large unit surface area which is useful for adsorption application. When AAO adsorbed pH indictor of bromphenol blue presented a sensitive pH detection of solution change. This testing method can further be used for the precise measurement of biotechnology, convenience measurement of industrial engineering.

Effect of Oxygen on Biochar Yield and Properties

Air infiltration in mass scale industrial applications of bio char production is inevitable. The presence of oxygen during the carbonization process is detrimental to the production of biochar yield and properties. The experiment was carried out on several wood species in a fixed-bed pyrolyser under various fractions of oxygen ranging from 0% to 11% by varying nitrogen and oxygen composition in the pyrolysing gas mixtures at desired compositions. The bed temperature and holding time were also varied. Process optimization was carried out by Response Surface Methodology (RSM) by employing Central Composite Design (CCD) using Design Expert 6.0 Software. The effect of oxygen ratio and holding time on biochar yield within the range studied were statistically significant. From the analysis result, optimum condition of 15.2% biochar yield of mangrove wood was predicted at pyrolysis temperature of 403 oC, oxygen percentage of 2.3% and holding time of two hours. This prediction agreed well with the experiment finding of 15.1% biochar yield.

Investment Prediction Using Simulation

A business case is a proposal for an investment initiative to satisfy business and functional requirements. The business case provides the foundation for tactical decision making and technology risk management. It helps to clarify how the organization will use its resources in the best way by providing justification for investment of resources. This paper describes how simulation was used for business case benefits and return on investment for the procurement of 8 production machines. With investment costs of about 4.7 million dollars and annual operating costs of about 1.3 million, we needed to determine if the machines would provide enough cost savings and cost avoidance. We constructed a model of the existing factory environment consisting of 8 machines and subsequently, we conducted average day simulations with light and heavy volumes to facilitate planning decisions required to be documented and substantiated in the business case.

Improving Academic Performance Prediction using Voting Technique in Data Mining

In this paper we compare the accuracy of data mining methods to classifying students in order to predicting student-s class grade. These predictions are more useful for identifying weak students and assisting management to take remedial measures at early stages to produce excellent graduate that will graduate at least with second class upper. Firstly we examine single classifiers accuracy on our data set and choose the best one and then ensembles it with a weak classifier to produce simple voting method. We present results show that combining different classifiers outperformed other single classifiers for predicting student performance.

ABURAS Index: A Statistically Developed Index for Dengue-Transmitting Vector Population Prediction

“Dengue" is an African word meaning “bone breaking" because it causes severe joint and muscle pain that feels like bones are breaking. It is an infectious disease mainly transmitted by female mosquito, Aedes aegypti, and causes four serotypes of dengue viruses. In recent years, a dramatic increase in the dengue fever confirmed cases around the equator-s belt has been reported. Several conventional indices have been designed so far to monitor the transmitting vector populations known as House Index (HI), Container Index (CI), Breteau Index (BI). However, none of them describes the adult mosquito population size which is important to direct and guide comprehensive control strategy operations since number of infected people has a direct relationship with the vector density. Therefore, it is crucial to know the population size of the transmitting vector in order to design a suitable and effective control program. In this context, a study is carried out to report a new statistical index, ABURAS Index, using Poisson distribution based on the collection of vector population in Jeddah Governorate, Saudi Arabia.

Improving the Road Construction Supply Chain by Developing a National Level Performance Measurement System: the Case of Estonia

Transport and logistics are the lifeblood of societies. There is a strong correlation between overall growth in economic activity and growth of transport. The movement of people and goods has the potential for creating wealth and prosperity, therefore the state of transportation infrastructure and especially the condition of road networks is often a governmental priority. The design, building and maintenance of national roads constitute a substantial share of government budgets. Taking into account the magnitude and importance of these investments, the expedience, efficiency and sustainability of these projects are of great public interest. This paper provides an overview of supply chain management principles applied to road construction. In addition, road construction performance measurement systems and ICT solutions are discussed. Road construction in Estonia is analyzed. The authors propose the development of a national performance measurement system for road construction.

Conventional Design and Simulation of an Urban Hybrid Bus

Due to heightened concerns over environmental and economic issues the growing important of air pollution, and the importance of conserving fossil fuel resources in the world, the automotive industry is now forced to produce more fuel efficient, low emission vehicles and new drive system technologies. One of the most promising technologies to receive attention is the hybrid electric vehicle (HEV), which consists of two or more energy sources that supply energy to electric traction motors that in turn drive the wheels. This paper presents the various structures of HEV systems, the basic theoretical knowledge for describing their operation and the general behaviour of the HEV in acceleration, cruise and deceleration phases. The conventional design and sizing of a series HEV is studied. A conventional bus and its series configuration are defined and evaluated using the ADVISOR. In this section the simulation of a standard driving cycle and prediction of its fuel consumption and emissions of the HEV are discussed. Finally the bus performance is investigated to establish whether it can satisfy the performance, fuel consumption and emissions requested. The validity of the simulation has been established by the close conformity between the fuel consumption of the conventional bus reported by the manufacturer to what has achieved from the simulation.

Multi-objective Optimization with Fuzzy Based Ranking for TCSC Supplementary Controller to Improve Rotor Angle and Voltage Stability

Many real-world optimization problems involve multiple conflicting objectives and the use of evolutionary algorithms to solve the problems has attracted much attention recently. This paper investigates the application of multi-objective optimization technique for the design of a Thyristor Controlled Series Compensator (TCSC)-based controller to enhance the performance of a power system. The design objective is to improve both rotor angle stability and system voltage profile. A Genetic Algorithm (GA) based solution technique is applied to generate a Pareto set of global optimal solutions to the given multi-objective optimisation problem. Further, a fuzzy-based membership value assignment method is employed to choose the best compromise solution from the obtained Pareto solution set. Simulation results are presented to show the effectiveness and robustness of the proposed approach.