Off-Line Hand Written Thai Character Recognition using Ant-Miner Algorithm

Much research into handwritten Thai character recognition have been proposed, such as comparing heads of characters, Fuzzy logic and structure trees, etc. This paper presents a system of handwritten Thai character recognition, which is based on the Ant-minor algorithm (data mining based on Ant colony optimization). Zoning is initially used to determine each character. Then three distinct features (also called attributes) of each character in each zone are extracted. The attributes are Head zone, End point, and Feature code. All attributes are used for construct the classification rules by an Ant-miner algorithm in order to classify 112 Thai characters. For this experiment, the Ant-miner algorithm is adapted, with a small change to increase the recognition rate. The result of this experiment is a 97% recognition rate of the training set (11200 characters) and 82.7% recognition rate of unseen data test (22400 characters).

Using Malolactic Fermentation with Acid- And Ethanol- Adapted Oenococcus Oeni Strain to Improve the Quality of Wine from Champs Bourcin Grape in Sapa - Lao Cai

Champs Bourcin black grape originated from Aquitaine, France and planted in Sapa, Lao cai provice, exhibited high total acidity (11.72 g/L). After 9 days of alcoholic fermentation at 25oC using Saccharomyces cerevisiae UP3OY5 strain, the ethanol concentration of wine was 11.5% v/v, however the sharp sour taste of wine has been found. The malolactic fermentation (MLF) was carried out by Oenococcus oeni ATCCBAA-1163 strain which had been preadapted to acid (pH 3-4) and ethanol (8-12%v/v) conditions. We obtained the highest vivability (83.2%) upon malolactic fermentation after 5 days at 22oC with early stationary phase O. oeni cells preadapted to pH 3.5 and 8% v/v ethanol in MRS medium. The malic acid content in wine was decreased from 5.82 g/L to 0.02 g/L after MLF (21 days at 22oC). The sensory quality of wine was significantly improved.

Effects of a Nectandra Membranacea Extract on Labeling of Blood Constituents with Technetium-99m and on the Morphology of Red Blood Cells

The aim of this in vitro study was to evaluate the possible interference of a Nectandra membranacea extract (i) on the labeling of blood cells (BC), (ii) on the labeling process of BC and plasma (P) proteins with technetium-99m (Tc-99m) and (iii) on the morphology of red blood cells (RBC). Blood samples were incubated with a Nectandra membranacea crude extract, stannous chloride, Tc- 99m (sodium pertechnetate) was added, and soluble (SF) and insoluble (IF) fractions were isolated. Morphometry studies were performed with blood samples incubated with Nectandra membranacea extract. The results show that the Nectandra membranacea extract does not promote significant alteration of the labeling of BC, IF-P and IF-BC. The Nectandra membranacea extract was able to alter the erythrocyte membrane morphology, but these morphological changes were not capable to interfere on the labeling of blood constituents with Tc-99m.

Knowledge Management in Cross- Organizational Networks as Illustrated by One of the Largest European ICT Associations A Case Study of the “METORA

In networks, mainly small and medium-sized businesses benefit from the knowledge, experiences and solutions offered by experts from industry and science or from the exchange with practitioners. Associations which focus, among other things, on networking, information and knowledge transfer and which are interested in supporting such cooperations are especially well suited to provide such networks and the appropriate web platforms. Using METORA as an example – a project developed and run by the Federal Association for Information Economy, Telecommunications and New Media e.V. (BITKOM) for the Federal Ministry of Economics and Technology (BMWi) – This paper will discuss how associations and other network organizations can achieve this task and what conditions they have to consider.

Modeling and Visualizing Seismic Wave Propagation in Elastic Medium Using Multi-Dimension Wave Digital Filtering Approach

A novel PDE solver using the multidimensional wave digital filtering (MDWDF) technique to achieve the solution of a 2D seismic wave system is presented. In essence, the continuous physical system served by a linear Kirchhoff circuit is transformed to an equivalent discrete dynamic system implemented by a MD wave digital filtering (MDWDF) circuit. This amounts to numerically approximating the differential equations used to describe elements of a MD passive electronic circuit by a grid-based difference equations implemented by the so-called state quantities within the passive MDWDF circuit. So the digital model can track the wave field on a dense 3D grid of points. Details about how to transform the continuous system into a desired discrete passive system are addressed. In addition, initial and boundary conditions are properly embedded into the MDWDF circuit in terms of state quantities. Graphic results have clearly demonstrated some physical effects of seismic wave (P-wave and S–wave) propagation including radiation, reflection, and refraction from and across the hard boundaries. Comparison between the MDWDF technique and the finite difference time domain (FDTD) approach is also made in terms of the computational efficiency.

Identification of Binding Proteins That Interact with BVDV E2 Protein in Bovine Trophoblast Cell

Bovine viral diarrhea virus (BVDV) can cause lifelong persistent infection. One reason for the phenomena is attributed to BVDV infection to placenta tissue. However the mechanisms that BVDV invades into placenta tissue remain unclear. To clarify the molecular mechanisms, we investigated the possible means that BVDV entered into bovine trophoblast cells (TPC). Yeast two-hybrid system was used to identify proteins extracted from TPC, which interact with BVDV envelope glycoprotein E2. A PGbkt7-E2 yeast expression vector and TPC cDNA library were constructed. Through two rounds of screening, three positive clones were identified. Sequencing analysis indicated that all the three positive clones encoded the same protein clathrin. Physical interaction between clathrin and BVDV E2 protein was further confirmed by coimmunoprecipitation experiments. This result suggested that the clathrin might play a critical role in the process of BVDV entry into placenta tissue and might be a novel antiviral target for preventing BVDV infection.

Automatic Choice of Topics for Seminars by Clustering Students According to Their Profile

The new framework the Higher Education is immersed in involves a complete change in the way lecturers must teach and students must learn. Whereas the lecturer was the main character in traditional education, the essential goal now is to increase the students' participation in the process. Thus, one of the main tasks of lecturers in this new context is to design activities of different nature in order to encourage such participation. Seminars are one of the activities included in this environment. They are active sessions that enable going in depth into specific topics as support of other activities. They are characterized by some features such as favoring interaction between students and lecturers or improving their communication skills. Hence, planning and organizing strategic seminars is indeed a great challenge for lecturers with the aim of acquiring knowledge and abilities. This paper proposes a method using Artificial Intelligence techniques to obtain student profiles from their marks and preferences. The goal of building such profiles is twofold. First, it facilitates the task of splitting the students into different groups, each group with similar preferences and learning difficulties. Second, it makes it easy to select adequate topics to be a candidate for the seminars. The results obtained can be either a guarantee of what the lecturers could observe during the development of the course or a clue to reconsider new methodological strategies in certain topics.

Introducing the Main Factors of Accidents on the Roads of Iran and Studying its Causes and Strategies Applied to Decrease it

Road transportation system is the most important method of transporting the goods. Considering the most suitable geographical situation of Iran to transport the goods between Europe and Asia and placement of this country in direction of international corridors (east- west) , (north-south) and Asian land transport to infrastructure development “A.L.T.I.D" and Transport corridor Europe - Caucasus - Asia “T.R.A.C.E.C.A", noticing the security of road transportation system in this country is so important. In this paper the main factors of accidents on the roads of Iran are categorized regarding the rate of accidents occurred. Then apart from studying the main reasons of accidents of every category, the main factors of these events are studied and its strategies in Iran are introduced.

Near-Field Robust Adaptive Beamforming Based on Worst-Case Performance Optimization

The performance of adaptive beamforming degrades substantially in the presence of steering vector mismatches. This degradation is especially severe in the near-field, for the 3-dimensional source location is more difficult to estimate than the 2-dimensional direction of arrival in far-field cases. As a solution, a novel approach of near-field robust adaptive beamforming (RABF) is proposed in this paper. It is a natural extension of the traditional far-field RABF and belongs to the class of diagonal loading approaches, with the loading level determined based on worst-case performance optimization. However, different from the methods solving the optimal loading by iteration, it suggests here a simple closed-form solution after some approximations, and consequently, the optimal weight vector can be expressed in a closed form. Besides simplicity and low computational cost, the proposed approach reveals how different factors affect the optimal loading as well as the weight vector. Its excellent performance in the near-field is confirmed via a number of numerical examples.

Automatically-generated Concept Maps as a Learning Tool

Concept maps can be generated manually or automatically. It is important to recognize differences of the two types of concept maps. The automatically generated concept maps are dynamic, interactive, and full of associations between the terms on the maps and the underlying documents. Through a specific concept mapping system, Visual Concept Explorer (VCE), this paper discusses how automatically generated concept maps are different from manually generated concept maps and how different applications and learning opportunities might be created with the automatically generated concept maps. The paper presents several examples of learning strategies that take advantages of the automatically generated concept maps for concept learning and exploration.

Inter-Organizational Knowledge Transfer Through Malaysia E-government IT Outsourcing: A Theoretical Review

The main objective of this paper is to contribute the existing knowledge transfer and IT Outsourcing literature specifically in the context of Malaysia by reviewing the current practices of e-government IT outsourcing in Malaysia including the issues and challenges faced by the public agencies in transferring the knowledge during the engagement. This paper discusses various factors and different theoretical model of knowledge transfer starting from the traditional model to the recent model suggested by the scholars. The present paper attempts to align organizational knowledge from the knowledge-based view (KBV) and organizational learning (OL) lens. This review could help shape the direction of both future theoretical and empirical studies on inter-firm knowledge transfer specifically on how KBV and OL perspectives could play significant role in explaining the complex relationships between the client and vendor in inter-firm knowledge transfer and the role of organizational management information system and Transactive Memory System (TMS) to facilitate the organizational knowledge transferring process. Conclusion is drawn and further research is suggested.

Performance Assessment of Computational Gridon Weather Indices from HOAPS Data

Long term rainfall analysis and prediction is a challenging task especially in the modern world where the impact of global warming is creating complications in environmental issues. These factors which are data intensive require high performance computational modeling for accurate prediction. This research paper describes a prototype which is designed and developed on grid environment using a number of coupled software infrastructural building blocks. This grid enabled system provides the demanding computational power, efficiency, resources, user-friendly interface, secured job submission and high throughput. The results obtained using sequential execution and grid enabled execution shows that computational performance has enhanced among 36% to 75%, for decade of climate parameters. Large variation in performance can be attributed to varying degree of computational resources available for job execution. Grid Computing enables the dynamic runtime selection, sharing and aggregation of distributed and autonomous resources which plays an important role not only in business, but also in scientific implications and social surroundings. This research paper attempts to explore the grid enabled computing capabilities on weather indices from HOAPS data for climate impact modeling and change detection.

Neural Network Control of a Biped Robot Model with Composite Adaptation Low

this paper presents a novel neural network controller with composite adaptation low to improve the trajectory tracking problems of biped robots comparing with classical controller. The biped model has 5_link and 6 degrees of freedom and actuated by Plated Pneumatic Artificial Muscle, which have a very high power to weight ratio and it has large stoke compared to similar actuators. The proposed controller employ a stable neural network in to approximate unknown nonlinear functions in the robot dynamics, thereby overcoming some limitation of conventional controllers such as PD or adaptive controllers and guarantee good performance. This NN controller significantly improve the accuracy requirements by retraining the basic PD/PID loop, but adding an inner adaptive loop that allows the controller to learn unknown parameters such as friction coefficient, therefore improving tracking accuracy. Simulation results plus graphical simulation in virtual reality show that NN controller tracking performance is considerably better than PD controller tracking performance.

The Effect of High-speed Milling on Surface Roughness of Hardened Tool Steel

The objective of this research was to study factors, which were affected on surface roughness in high speed milling of hardened tool steel. Material used in the experiment was tool steel JIS SKD 61 that hardened on 60 ±2 HRC. Full factorial experimental design was conducted on 3 factors and 3 levels (3 3 designs) with 2 replications. Factors were consisted of cutting speed, feed rate, and depth of cut. The results showed that influenced factor affected to surface roughness was cutting speed, feed rate and depth of cut which showed statistical significant. Higher cutting speed would cause on better surface quality. On the other hand, higher feed rate would cause on poorer surface quality. Interaction of factor was found that cutting speed and depth of cut were significantly to surface quality. The interaction of high cutting speed associated with low depth of cut affected to better surface quality than low cutting speed and high depth of cut.

n-Butanol as an Extractant for Lactic Acid Recovery

Extraction of lactic acid from aqueous solution using n-butanol as an extractant was studied. Effect of mixing time, pH of the aqueous solution, initial lactic acid concentration, and volume ratio between the organic and the aqueous phase were investigated. Distribution coefficient and degree of lactic acid extraction was found to increase when the pH of aqueous solution was decreased. The pH Effect was substantially pronounced at pH of the aqueous solution less than 1. Initial lactic acid concentration and organic-toaqueous volume ratio appeared to have positive effect on the distribution coefficient and the degree of extraction. Due to the nature of n-butanol that is partially miscible in water, incorporation of aqueous solution into organic phase was observed in the extraction with large organic-to-aqueous volume ratio.

A Hybrid DEA Model for the Measurement of the Enviromental Performance

Data envelopment analysis (DEA) has gained great popularity in environmental performance measurement because it can provide a synthetic standardized environmental performance index when pollutants are suitably incorporated into the traditional DEA framework. Since some of the environmental performance indicators cannot be controlled by companies managers, it is necessary to develop the model in a way that it could be applied when discretionary and/or non-discretionary factors were involved. In this paper, we present a semi-radial DEA approach to measuring environmental performance, which consists of non-discretionary factors. The model, then, has been applied on a real case.

An Anomaly Detection Approach to Detect Unexpected Faults in Recordings from Test Drives

In the automotive industry test drives are being conducted during the development of new vehicle models or as a part of quality assurance of series-production vehicles. The communication on the in-vehicle network, data from external sensors, or internal data from the electronic control units is recorded by automotive data loggers during the test drives. The recordings are used for fault analysis. Since the resulting data volume is tremendous, manually analysing each recording in great detail is not feasible. This paper proposes to use machine learning to support domainexperts by preventing them from contemplating irrelevant data and rather pointing them to the relevant parts in the recordings. The underlying idea is to learn the normal behaviour from available recordings, i.e. a training set, and then to autonomously detect unexpected deviations and report them as anomalies. The one-class support vector machine “support vector data description” is utilised to calculate distances of feature vectors. SVDDSUBSEQ is proposed as a novel approach, allowing to classify subsequences in multivariate time series data. The approach allows to detect unexpected faults without modelling effort as is shown with experimental results on recordings from test drives.

Effect of Personalization on Students' Achievement and Gender Factor in Mathematics Education

The aim of this study is to point out whether personalization of mathematical word problems could affect student achievement or not. The research was applied on two-grades students at spring semester 2008-2009. Before the treatment, students personal data were taken and given to the computer. During the treatment, paper-based personalized problems and paper-based non personalized problems were prepared by computer as the same problems and then these problems were given to students. At the end of the treatment, students- opinion was taken. As a result of this research, it was found out that there were no significant differences between learners through personalized or non-personalized materials, and also there were no significant differences between gender through personalized and non-personalized problems. However, opinion of students was highly positive through the personalized problems.

Application of Process Approach to Evaluate the Information Security Risk and its Implementation in an Iranian Private Bank

Every organization is continually subject to new damages and threats which can be resulted from their operations or their goal accomplishment. Methods of providing the security of space and applied tools have been widely changed with increasing application and development of information technology (IT). From this viewpoint, information security management systems were evolved to construct and prevent reiterating the experienced methods. In general, the correct response in information security management systems requires correct decision making, which in turn requires the comprehensive effort of managers and everyone involved in each plan or decision making. Obviously, all aspects of work or decision are not defined in all decision making conditions; therefore, the possible or certain risks should be considered when making decisions. This is the subject of risk management and it can influence the decisions. Investigation of different approaches in the field of risk management demonstrates their progress from quantitative to qualitative methods with a process approach.

A Formal Implementation of Database Security

This paper is to investigate the impplementation of security mechanism in object oriented database system. Formal methods plays an essential role in computer security due to its powerful expressiveness and concise syntax and semantics. In this paper, both issues of specification and implementation in database security environment will be considered; and the database security is achieved through the development of an efficient implementation of the specification without compromising its originality and expressiveness.