Taiwan Sugar Corporation's Participation in the Mechanism of Payment for Environmental Services (PES)

The Taiwan government has started to promote the “Plain Landscape Afforestation and Greening Program" since 2002. A key task of the program was the payment for environmental services (PES), entitled the “Plain Landscape Afforestation Policy" (PLAP), which was certificated by the Executive Yuan on August 31, 2001 and enacted on January 1, 2002. According to the policy, it is estimated that the total area of afforestation will be 25,100 hectares by December 31, 2007. Until the end of 2007, the policy had been enacted for six years in total and the actual area of afforestation was 8,919.18 hectares. Among them, Taiwan Sugar Corporation (TSC) was accounted for 7,960 hectares (with 2,450.83 hectares as public service area) which occupied 86.22% of the total afforestation area; the private farmland promoted by local governments was accounted for 869.18 hectares which occupied 9.75% of the total afforestation area. Based on the above, we observe that most of the afforestation area in this policy is executed by TSC, and the achievement ratio by TSC is better than by others. It implies that the success of the PLAP is seriously related to the execution of TSC. The objective of this study is to analyze the relevant policy planning of TSC's participation in the PLAP, suggest complementary measures, and draw up effective adjustment mechanisms, so as to improve the effectiveness of executing the policy. Our main conclusions and suggestions are summarized as follows: 1. The main reason for TSC’s participation in the PLAP is based on their passive cooperation with the central government or company policy. Prior to TSC’s participation in the PLAP, their lands were mainly used for growing sugarcane. 2. The main factors of TSC's consideration on the selection of tree species are based on the suitability of land and species. The largest proportion of tree species is allocated to economic forests, and the lack of technical instruction was the main problem during afforestation. Moreover, the method of improving TSC’s future development in leisure agriculture and landscape business becomes a key topic. 3. TSC has developed short and long-term plans on participating in the PLAP for the future. However, there is no great willingness or incentive on budgeting for such detailed planning. 4. Most people from TSC interviewed consider the requirements on PLAP unreasonable. Among them, an unreasonable requirement on the number of trees accounted for the greatest proportion; furthermore, most interviewees suggested that the government should continue to provide incentives even after 20 years. 5. Since the government shares the same goals as TSC, there should be sufficient cooperation and communication that support the technical instruction and reduction of afforestation cost, which will also help to improve effectiveness of the policy.

An Empirical Analysis of Arabic WebPages Classification using Fuzzy Operators

In this study, a fuzzy similarity approach for Arabic web pages classification is presented. The approach uses a fuzzy term-category relation by manipulating membership degree for the training data and the degree value for a test web page. Six measures are used and compared in this study. These measures include: Einstein, Algebraic, Hamacher, MinMax, Special case fuzzy and Bounded Difference approaches. These measures are applied and compared using 50 different Arabic web pages. Einstein measure was gave best performance among the other measures. An analysis of these measures and concluding remarks are drawn in this study.

IDEL - A simple Instructional Design Tool for E-Learning

Today-s Information and Knowledge Society has placed new demands on education and a new paradigm of education is required. Learning, facilitated by educational systems and the pedagogic process, is globally undergoing dramatic changes. The aim of this paper is the development of a simple Instructional Design tool for E-Learning, named IDEL (Instructional Design for Electronic Learning), that provides the educators with facilities to create their own courses with the essential educational material and manage communication with students. It offers flexibility in the way of learning and provides ease in employment and reusability of resources. IDEL is a web-based Instructional System and is designed to facilitate course design process in accordance with the ADDIE model and the instructional design principles with emphasis placed on the use of technology enhanced learning. An example case of using the ADDIE model to systematically develop a course and its implementation with the aid of IDEL is given and some results from student evaluation of the tool and the course are reported.

Biodegradation of Lignocellulosic Residues of Water Hyacinth (Eichhornia crassipes) and Response Surface Methodological Approach to Optimize Bioethanol Production Using Fermenting Yeast Pachysolen tannophilus NRRL Y-2460

The objective of this research was to investigate biodegradation of water hyacinth (Eichhornia crassipes) to produce bioethanol using dilute-acid pretreatment (1% sulfuric acid) results in high hemicellulose decomposition and using yeast (Pachysolen tannophilus) as bioethanol producing strain. A maximum ethanol yield of 1.14g/L with coefficient, 0.24g g-1; productivity, 0.015g l-1h-1 was comparable to predicted value 32.05g/L obtained by Central Composite Design (CCD). Maximum ethanol yield coefficient was comparable to those obtained through enzymatic saccharification and fermentation of acid hydrolysate using fully equipped fermentor. Although maximum ethanol concentration was low in lab scale, the improvement of lignocellulosic ethanol yield is necessary for large scale production.

Design and Simulation Interface Circuit for Piezoresistive Accelerometers with Offset Cancellation Ability

This paper presents a new method for read out of the piezoresistive accelerometer sensors. The circuit works based on Instrumentation amplifier and it is useful for reducing offset In Wheatstone Bridge. The obtained gain is 645 with 1μv/°c Equivalent drift and 1.58mw power consumption. A Schmitt trigger and multiplexer circuit control output node. a high speed counter is designed in this work .the proposed circuit is designed and simulated In 0.18μm CMOS technology with 1.8v power supply.

Forecasting of Flash Floods over Wadi Watier –Sinai Peninsula Using the Weather Research and Forecasting (WRF) Model

Flash floods are considered natural disasters that can cause casualties and demolishing of infra structures. The problem is that flash floods, particularly in arid and semi arid zones, take place in very short time. So, it is important to forecast flash floods earlier to its events with a lead time up to 48 hours to give early warning alert to avoid or minimize disasters. The flash flood took place over Wadi Watier - Sinai Peninsula, in October 24th, 2008, has been simulated, investigated and analyzed using the state of the art regional weather model. The Weather Research and Forecast (WRF) model, which is a reliable short term forecasting tool for precipitation events, has been utilized over the study area. The model results have been calibrated with the real data, for the same date and time, of the rainfall measurements recorded at Sorah gauging station. The WRF model forecasted total rainfall of 11.6 mm while the real measured one was 10.8 mm. The calibration shows significant consistency between WRF model and real measurements results.

Multi-Agent Model for Automation of Business Process Management System Based on Service Oriented Architecture

Business process automation is an important task in an enterprise business environment software development. The requirements of processing acceleration and automation level of enterprises are inherently different from one organization to another. We present a methodology and system for automation of business process management system architecture by multi-agent collaboration based on SOA. Design layer processes are modeled in semantic markup language for web services application. At the core of our system is considering certain types of human tasks to their further automation across over multiple platform environments. An improved abnormality processing with model for automation of BPMS architecture by multi-agent collaboration based on SOA is introduced. Validating system for efficiency of process automation, an application for educational knowledge base instance would also be described.

Visual Object Tracking in 3D with Color Based Particle Filter

This paper addresses the problem of determining the current 3D location of a moving object and robustly tracking it from a sequence of camera images. The approach presented here uses a particle filter and does not perform any explicit triangulation. Only the color of the object to be tracked is required, but not any precisemotion model. The observation model we have developed avoids the color filtering of the entire image. That and the Monte Carlotechniques inside the particle filter provide real time performance.Experiments with two real cameras are presented and lessons learned are commented. The approach scales easily to more than two cameras and new sensor cues.

Coordinated Design of TCSC Controller and PSS Employing Particle Swarm Optimization Technique

This paper investigates the application of Particle Swarm Optimization (PSO) technique for coordinated design of a Power System Stabilizer (PSS) and a Thyristor Controlled Series Compensator (TCSC)-based controller to enhance the power system stability. The design problem of PSS and TCSC-based controllers is formulated as a time domain based optimization problem. PSO algorithm is employed to search for optimal controller parameters. By minimizing the time-domain based objective function, in which the deviation in the oscillatory rotor speed of the generator is involved; stability performance of the system is improved. To compare the capability of PSS and TCSC-based controller, both are designed independently first and then in a coordinated manner for individual and coordinated application. The proposed controllers are tested on a weakly connected power system. The eigenvalue analysis and non-linear simulation results are presented to show the effectiveness of the coordinated design approach over individual design. The simulation results show that the proposed controllers are effective in damping low frequency oscillations resulting from various small disturbances like change in mechanical power input and reference voltage setting.

Robust Regression and its Application in Financial Data Analysis

This research is aimed to describe the application of robust regression and its advantages over the least square regression method in analyzing financial data. To do this, relationship between earning per share, book value of equity per share and share price as price model and earning per share, annual change of earning per share and return of stock as return model is discussed using both robust and least square regressions, and finally the outcomes are compared. Comparing the results from the robust regression and the least square regression shows that the former can provide the possibility of a better and more realistic analysis owing to eliminating or reducing the contribution of outliers and influential data. Therefore, robust regression is recommended for getting more precise results in financial data analysis.

The Incorporation of In in GaAsN as a Means of N Fraction Calibration

InGaAsN and GaAsN epitaxial layers with similar nitrogen compositions in a sample were successfully grown on a GaAs (001) substrate by solid source molecular beam epitaxy. An electron cyclotron resonance nitrogen plasma source has been used to generate atomic nitrogen during the growth of the nitride layers. The indium composition changed from sample to sample to give compressive and tensile strained InGaAsN layers. Layer characteristics have been assessed by high-resolution x-ray diffraction to determine the relationship between the lattice constant of the GaAs1-yNy layer and the fraction x of In. The objective was to determine the In fraction x in an InxGa1-xAs1-yNy epitaxial layer which exactly cancels the strain present in a GaAs1-yNy epitaxial layer with the same nitrogen content when grown on a GaAs substrate.

Mitigation of Radiation Levels for Base Transceiver Stations based on ITU-T Recommendation K.70

This essay presents applicative methods to reduce human exposure levels in the area around base transceiver stations in a environment with multiple sources based on ITU-T recommendation K.70. An example is presented to understand the mitigation techniques and their results and also to learn how they can be applied, especially in developing countries where there is not much research on non-ionizing radiations.

Classification Influence Index and its Application for k-Nearest Neighbor Classifier

Classification is an important topic in machine learning and bioinformatics. Many datasets have been introduced for classification tasks. A dataset contains multiple features, and the quality of features influences the classification accuracy of the dataset. The power of classification for each feature differs. In this study, we suggest the Classification Influence Index (CII) as an indicator of classification power for each feature. CII enables evaluation of the features in a dataset and improved classification accuracy by transformation of the dataset. By conducting experiments using CII and the k-nearest neighbor classifier to analyze real datasets, we confirmed that the proposed index provided meaningful improvement of the classification accuracy.

Prime(Semiprime) Fuzzy h-ideal in Γ-hemiring

The notions of prime(semiprime) fuzzy h-ideal(h-biideal, h-quasi-ideal) in Γ-hemiring are introduced and some of their characterizations are obtained by using "belongingness(∈)" and "quasi - coincidence(q)". Cartesian product of prime(semiprime) fuzzy h-ideals of Γ-hemirings are also investigated.

Malaysia Folk Literature in Early Childhood Education

Malay Folk Literature in early childhood education served as an important agent in child development that involved emotional, thinking and language aspects. Up to this moment not much research has been carried out in Malaysia particularly in the teaching and learning aspects nor has there been an effort to publish “big books." Hence this article will discuss the stance taken by university undergraduate students, teachers and parents in evaluating Malay Folk Literature in early childhood education to be used as big books. The data collated and analyzed were taken from 646 respondents comprising 347 undergraduates and 299 teachers. Results of the study indicated that Malay Folk Literature can be absorbed into teaching and learning for early childhood with a mean of 4.25 while it can be in big books with a mean of 4.14. Meanwhile the highest mean value required for placing Malay Folk Literature genre as big books in early childhood education rests on exemplary stories for undergraduates with mean of 4.47; animal fables for teachers with a mean of 4.38. The lowest mean value of 3.57 is given to lipurlara stories. The most popular Malay Folk Literature found suitable for early children is Sang Kancil and the Crocodile, followed by Bawang Putih Bawang Merah. Pak Padir, Legends of Mahsuri, Origin of Malacca, and Origin of Rainbow are among the popular stories as well. Overall the undergraduates show a positive attitude toward all the items compared to teachers. The t-test analysis has revealed a non significant relationship between the undergraduate students and teachers with all the items for the teaching and learning of Malay Folk Literature.

Transmitter Macrodiversity in Multihopping- SFN Based Algorithm for Improved Node Reachability and Robust Routing

A novel idea presented in this paper is to combine multihop routing with single-frequency networks (SFNs) for a broadcasting scenario. An SFN is a set of multiple nodes that transmit the same data simultaneously, resulting in transmitter macrodiversity. Two of the most important performance factors of multihop networks, node reachability and routing robustness, are analyzed. Simulation results show that our proposed SFN-D routing algorithm improves the node reachability by 37 percentage points as compared to non-SFN multihop routing. It shows a diversity gain of 3.7 dB, meaning that 3.7 dB lower transmission powers are required for the same reachability. Even better results are possible for larger networks. If an important node becomes inactive, this algorithm can find new routes that a non-SFN scheme would not be able to find. Thus, two of the major problems in multihopping are addressed; achieving robust routing as well as improving node reachability or reducing transmission power.

Design, Implementation and Analysis of Composite Material Dampers for Turning Operations

This paper introduces a novel design for boring bar with enhanced damping capability. The principle followed in the design phase was to enhance the damping capability minimizing the loss in static stiffness through implementation of composite material interfaces. The newly designed tool has been compared to a conventional tool. The evaluation criteria were the dynamic characteristics, frequency and damping ratio, of the machining system, as well as the surface roughness of the machined workpieces. The use of composite material in the design of damped tool has been demonstrated effective. Furthermore, the autoregressive moving average (ARMA) models presented in this paper take into consideration the interaction between the elastic structure of the machine tool and the cutting process and can therefore be used to characterize the machining system in operational conditions.

Improving Classification in Bayesian Networks using Structural Learning

Naïve Bayes classifiers are simple probabilistic classifiers. Classification extracts patterns by using data file with a set of labeled training examples and is currently one of the most significant areas in data mining. However, Naïve Bayes assumes the independence among the features. Structural learning among the features thus helps in the classification problem. In this study, the use of structural learning in Bayesian Network is proposed to be applied where there are relationships between the features when using the Naïve Bayes. The improvement in the classification using structural learning is shown if there exist relationship between the features or when they are not independent.

Functional Lipids and Bioactive Compounds from Oil Rich Indigenous Seeds

Indian subcontinent has a plethora of traditional medicine systems that provide promising solutions to lifestyle disorders in an 'all natural way'. Spices and oilseeds hold prominence in Indian cuisine hence the focus of the current study was to evaluate the bioactive molecules from Linum usitatissinum (LU), Lepidium sativum (LS), Nigella sativa (NS) and Guizotia abyssinica (GA) seeds. The seeds were characterized for functional lipids like omega-3 fatty acid, antioxidant capacity, phenolic compounds, dietary fiber and anti-nutritional factors. Analysis of the seeds revealed LU and LS to be a rich source of α-linolenic acid (41.85 ± 0.33%, 26.71 ± 0.63%), an omega 3 fatty acid (using GCMS). While studying antioxidant potential NS seeds demonstrated highest antioxidant ability (61.68 ± 0.21 TEAC/ 100 gm DW) due to the presence of phenolics and terpenes as assayed by the Mass spectral analysis. When screened for anti-nutritional factor cyanogenic glycoside, LS seeds showed content as high as 1674 ± 54 mg HCN / kg. GA is a probable good source of a stable vegetable oil (SFA: PUFA 1:2.3). The seeds showed diversified bioactive profile and hence further studies to use different bio molecules in tandem for the development of a possible 'nutraceutical cocktail' have been initiated..

ANN Models for Microstrip Line Synthesis and Analysis

Microstrip lines, widely used for good reason, are broadband in frequency and provide circuits that are compact and light in weight. They are generally economical to produce since they are readily adaptable to hybrid and monolithic integrated circuit (IC) fabrication technologies at RF and microwave frequencies. Although, the existing EM simulation models used for the synthesis and analysis of microstrip lines are reasonably accurate, they are computationally intensive and time consuming. Neural networks recently gained attention as fast and flexible vehicles to microwave modeling, simulation and optimization. After learning and abstracting from microwave data, through a process called training, neural network models are used during microwave design to provide instant answers to the task learned.This paper presents simple and accurate ANN models for the synthesis and analysis of Microstrip lines to more accurately compute the characteristic parameters and the physical dimensions respectively for the required design specifications.