Strategic Information in the Game of Go

We introduce a novel approach to measuring how humans learn based on techniques from information theory and apply it to the oriental game of Go. We show that the total amount of information observable in human strategies, called the strategic information, remains constant for populations of players of differing skill levels for well studied patterns of play. This is despite the very large amount of knowledge required to progress from the recreational players at one end of our spectrum to the very best and most experienced players in the world at the other and is in contrast to the idea that having more knowledge might imply more 'certainty' in what move to play next. We show this is true for very local up to medium sized board patterns, across a variety of different moves using 80,000 game records. Consequences for theoretical and practical AI are outlined.

Motivation Factors in Distance Education

This study describes the relationship between motivation factors and academic performance among distance education students enrolled in a postgraduate nursing course. Students (n=96) participated in a survey that assesses student's motivational orientations from a cognitive perspective using a selfadministered questionnaire based on Pintrich-s Motivation Strategies for Learning Questionnaire (MLSQ). Results showed students- motivational factors are highest on task value (6.44, 0.71); followed by intrinsic goal orientation (6.20, 0.76), control beliefs (6.02, 0.89); extrinsic goal orientation (5.85, 1.13); self-efficacy for learning and performance (5.62, 0.84), and finally, test anxiety (4.21, 1.37). Weak positive correlations were found between academic performance and intrinsic goal orientation (r=0.13), extrinsic goal orientation (r=0.04), task value (r=0.09), control beliefs (r=0.02), and self-efficacy (r=0.05), while there was weak negative correlation with test anxiety (r=-0.04). Conclusions from the study indicate the need to focus on improving tasks and targeting intrinsic goal orientations of students to courses since these were positively correlated with academic performance and downplay the use of tests since these were negatively correlated with academic performance.

Wavelet - Based Classification of Outdoor Natural Scenes by Resilient Neural Network

Natural outdoor scene classification is active and promising research area around the globe. In this study, the classification is carried out in two phases. In the first phase, the features are extracted from the images by wavelet decomposition method and stored in a database as feature vectors. In the second phase, the neural classifiers such as back-propagation neural network (BPNN) and resilient back-propagation neural network (RPNN) are employed for the classification of scenes. Four hundred color images are considered from MIT database of two classes as forest and street. A comparative study has been carried out on the performance of the two neural classifiers BPNN and RPNN on the increasing number of test samples. RPNN showed better classification results compared to BPNN on the large test samples.

The Impact of the Type of Diversification of Listed Construction Enterprises in China on Corporation Performance

The construction industry is the pillar industry in China, accounting for about 6% of the gross domestic product. Along with changes in the external environment of the construction industry in China, the construction firm faces fierce competition. The paper aims to investigate the relationship between diversified types of construction firm and its performance in China. Based on generalist and specialist strategy in organizational ecology, we think a generalist organization can be applied to an enterprise with diversified developments, while specialist groups are extended to professional enterprises .This study takes advantage of annual financial data of listed construction firm to empirically verify the relationship between diversification and corporation performance establishing a regression equation to econometric analysis. We find that: 1) Specialization can significantly improve the level of profitability of listed construction firms, and there is a significant positive relationship with corporate performance; 2) The level of operating performance of listed construction enterprises which engage in unrelated diversification is higher than those with related diversification; 3) The relationship between state-owned construction firms and corporate performance is negative. The more the year of foundation is, the higher performance will be; however, the more the year of being listed, the lower performance will be.

Mainland Chinese Customers' Intention toward Medical Tourism in Taiwan

This study proposes and tests a rescapturing elements of perceived gain and loss that, by perceived value of medical tourism products, influencintention of potential customers. Data from 301 usable qwere tested against the research model using the structmodeling approach. The results indicated that perceivedkey predictor of customer intentions. As for benefimedical quality, service quality and enjoyment wcomponents that significantly influenced the perceptiRegarding sacrifice, the effects of perceived risk on pewere significant. The findings can provide insights intohow destination countries can make medical tourism a wfor themselves and international patients.KeywordsMedical tourism, perceived valueintention.

Carbothermic Reduction of Mechanically Activated Mixtures of Celestite and Carbon

The effect of dry milling on the carbothermic reduction of celestite was investigated. Mixtures of celestite concentrate (98% SrSO4) and activated carbon (99% carbon) was milled for 1 and 24 hours in a planetary ball mill. Un-milled and milled mixtures and their products after carbothermic reduction were studied by a combination of XRD and TGA/DTA experiments. The thermogravimetric analyses and XRD results showed that by milling celestite-carbon mixtures for one hour, the formation temperature of strontium sulfide decreased from about 720°C (in un-milled sample) to about 600°C, after 24 hours milling it decreased to 530°C. It was concluded that milling induces increasingly thorough mixing of the reactants to reduction occurring at lower temperatures

A Preference-Based Multi-Agent Data Mining Framework for Social Network Service Users' Decision Making

Multi-Agent Systems (MAS) emerged in the pursuit to improve our standard of living, and hence can manifest complex human behaviors such as communication, decision making, negotiation and self-organization. The Social Network Services (SNSs) have attracted millions of users, many of whom have integrated these sites into their daily practices. The domains of MAS and SNS have lots of similarities such as architecture, features and functions. Exploring social network users- behavior through multiagent model is therefore our research focus, in order to generate more accurate and meaningful information to SNS users. An application of MAS is the e-Auction and e-Rental services of the Universiti Cyber AgenT(UniCAT), a Social Network for students in Universiti Tunku Abdul Rahman (UTAR), Kampar, Malaysia, built around the Belief- Desire-Intention (BDI) model. However, in spite of the various advantages of the BDI model, it has also been discovered to have some shortcomings. This paper therefore proposes a multi-agent framework utilizing a modified BDI model- Belief-Desire-Intention in Dynamic and Uncertain Situations (BDIDUS), using UniCAT system as a case study.

IKEv1 and IKEv2: A Quantitative Analyses

Key management is a vital component in any modern security protocol. Due to scalability and practical implementation considerations automatic key management seems a natural choice in significantly large virtual private networks (VPNs). In this context IETF Internet Key Exchange (IKE) is the most promising protocol under permanent review. We have made a humble effort to pinpoint IKEv2 net gain over IKEv1 due to recent modifications in its original structure, along with a brief overview of salient improvements between the two versions. We have used US National Institute of Technology NIIST VPN simulator to get some comparisons of important performance metrics.

A Heuristic Based Conceptual Framework for Product Innovation

This research elaborates decision models for product innovation in the early phases, focusing on one of the most widely implemented method in marketing research: conjoint analysis and the related conjoint-based models with special focus on heuristics programming techniques for the development of optimal product innovation. The concept, potential, requirements and limitations of conjoint analysis and its conjoint-based heuristics successors are analysed and the development of conceptual framework of Genetic Algorithm (GA) as one of the most widely implemented heuristic methods for developing product innovations are discussed.

Pleurotus sajor-caju (PSC) Improves Nutrient Contents and Maintains Sensory Properties of Carbohydrate-based Products

The grey oyster mushroom, Pleurotus sajor-caju (PSC), is a common edible mushroom and is now grown commercially around the world for food. This fungus has been broadly used as food or food ingredients in various food products for a long time. To enhance the nutritional quality and sensory attributes of bakery-based products, PSC powder is used in the present study to partially replace wheat flour in baked product formulations. The nutrient content and sensory properties of rice-porridge and unleavened bread (paratha) incorporated with various levels of PSC powder were studied. These food items were formulated with either 0%, 2%, 4% or 6% of PSC powder. Results show PSC powder recorded β-glucan at 3.57g/100g. In sensory evaluation, consumers gave higher score to both rice-porridge and paratha bread containing 2-4% PSC compared to those that are not added with PSC powder. The paratha containing 4% PSC powder can be formulated with the intention in improving overall acceptability of paratha bread. Meanwhile, for rice-porridge, consumers prefer the formulated product added with 4% PSC powder. In conclusion, the addition of PSC powder to partially wheat flour can be recommended for the purpose of enhancing nutritional composition and maintaining the acceptability of carbohydrate-based products.

Plants Cover Effects on Overland Flow and on Soil Erosion under Simulated Rainfall Intensity

The purpose of this article is to study the effects of plants cover on overland flow and, therefore, its influences on the amount of eroded and transported soil. In this investigation, all the experiments were conducted in the LEGHYD laboratory using a rainfall simulator and a soil tray. The experiments were conducted using an experimental plot (soil tray) which is 2m long, 0.5 m wide and 0.15 m deep. The soil used is an agricultural sandy soil (62,08% coarse sand, 19,14% fine sand, 11,57% silt and 7,21% clay). Plastic rods (4 mm in diameter) were used to simulate the plants at different densities: 0 stem/m2 (bared soil), 126 stems/m², 203 stems/m², 461 stems/m² and 2500 stems/m²). The used rainfall intensity is 73mm/h and the soil tray slope is fixed to 3°. The results have shown that the overland flow velocities decreased with increasing stems density, and the density cover has a great effect on sediment concentration. Darcy–Weisbach and Manning friction coefficients of overland flow increased when the stems density increased. Froude and Reynolds numbers decreased with increasing stems density and, consequently, the flow regime of all treatments was laminar and subcritical. From these findings, we conclude that increasing the plants cover can efficiently reduce soil loss and avoid denuding the roots plants.

Semi-Analytic Solution and Hydrodynamics Behavior of Fluid Flow in Micro-Converging plates

The hydrodynamics behavior of fluid flow in microconverging plates is investigated analytically. Effects of Knudsen number () on the microchannel hydrodynamics behavior and the coefficient of friction are investigated. It is found that as  increases the slip in the hydrodynamic boundary condition increases. Also, the coefficient of friction decreases as  increases.

Investigation on the HRSG Installation at South Pars Gas Complex Phases 2&3

In this article the investigation about installation heat recovery steam generation (HRSG) on the exhaust of turbo generators of phases 2&3 at South Pars Gas Complex is presented. The temperature of exhaust gas is approximately 665 degree centigrade, Installation of heat recovery boiler was simulated in ThermoFlow 17.0.2 software, based on test operation data and the equipments site operation conditions in Pars exclusive economical energy area, the affect of installation HRSG package on the available gas turbine and its operation parameters, ambient temperature, the exhaust temperatures steam flow rate were investigated. Base on the results recommended HRSG package should have the capacity for 98 ton per hour high pressure steam generation this refinery, by use of exhaust of three gas turbines for each package in operation condition of each refinery at 30 degree centigrade. Besides saving energy this project will be an Environment-Friendly project. The Payback Period is estimated approximately 1.8 year, with considering Clean Development Mechanism.

Studies on Physiochemical Properties of Tomato Powder as Affected by Different Dehydration Methods and Pretreatments

Tomato powder has good potential as substitute of tomato paste and other tomato products. In order to protect physicochemical properties and nutritional quality of tomato during dehydration process, investigation was carried out using different drying methods and pretreatments. Solar drier and continuous conveyor (tunnel) drier were used for dehydration where as calcium chloride (CaCl2), potassium metabisulphite (KMS), calcium chloride and potassium metabisulphite (CaCl2 +KMS), and sodium chloride (NaCl) selected for treatment.. lycopene content, dehydration ratio, rehydration ratio and non-enzymatic browning in addition to moisture, sugar and titrable acidity were studied. Results show that pre-treatment with CaCl2 and NaCl increased water removal and moisture mobility in tomato slices during drying of tomatoes. Where CaCl2 used along with KMS the NEB was recorded the least compared to other treatments and the best results were obtained while using the two chemicals in combination form. Storage studies in LDPE polymeric and metalized polyesters films showed less changes in the products packed in metallized polyester pouches and even after 6 months lycopene content did not decrease more than 20% as compared to the control sample and provide extension of shelf life in acceptable condition for 6 months. In most of the quality characteristics tunnel drier samples presented better values in comparison to solar drier.

Behavior of Optical Fiber Aged in CTAC Solutions

The evolution of silica optical fiber strength aged in cetyltrimethylammonium chloride solution (CTAC) has been investigated. If the solution containing surfactants presents appreciable changes in physical and chemical properties at the critical micelle concentration (CMC), a non negligible mechanical behavior fiber change is observed for silica fiber aged in cationic surfactants as CTAC which can lead to optical fiber reliability questioning. The purpose of this work is to study the mechanical behavior of silica coated and naked optical fibers in contact with CTAC solution at different concentrations. Result analysis proves that the immersion in CTAC drastically decreases the fiber strength and specially near the CMC point. Beyond CMC point, a small increase of fiber strength is analyzed and commented.

Simulation and Experimentation on the Contact Width of New Metal Gasket for Asbestos Substitution

The contact width is important design parameter for optimizing the design of new metal gasket for asbestos substitution gasket. The contact width is found have relationship with the helium leak quantity. In the increasing of axial load value, the helium leak quantity is decreasing and the contact width is increasing. This study provides validity method using simulation analysis and the result is compared to experimental using pressure sensitive paper. The results denote similar trend data between simulation and experimental result. Final evaluation is determined by helium leak quantity to check leakage performance of gasket design. Considering the phenomena of position change on the convex contact, it can be developed the optimization of gasket design by increasing contact width.

Emotion Recognition Using Neural Network: A Comparative Study

Emotion recognition is an important research field that finds lots of applications nowadays. This work emphasizes on recognizing different emotions from speech signal. The extracted features are related to statistics of pitch, formants, and energy contours, as well as spectral, perceptual and temporal features, jitter, and shimmer. The Artificial Neural Networks (ANN) was chosen as the classifier. Working on finding a robust and fast ANN classifier suitable for different real life application is our concern. Several experiments were carried out on different ANN to investigate the different factors that impact the classification success rate. Using a database containing 7 different emotions, it will be shown that with a proper and careful adjustment of features format, training data sorting, number of features selected and even the ANN type and architecture used, a success rate of 85% or even more can be achieved without increasing the system complicity and the computation time

Material Density Mapping on Deformable 3D Models of Human Organs

Organ motion, especially respiratory motion, is a technical challenge to radiation therapy planning and dosimetry. This motion induces displacements and deformation of the organ tissues within the irradiated region which need to be taken into account when simulating dose distribution during treatment. Finite element modeling (FEM) can provide a great insight into the mechanical behavior of the organs, since they are based on the biomechanical material properties, complex geometry of organs, and anatomical boundary conditions. In this paper we present an original approach that offers the possibility to combine image-based biomechanical models with particle transport simulations. We propose a new method to map material density information issued from CT images to deformable tetrahedral meshes. Based on the principle of mass conservation our method can correlate density variation of organ tissues with geometrical deformations during the different phases of the respiratory cycle. The first results are particularly encouraging, as local error quantification of density mapping on organ geometry and density variation with organ motion are performed to evaluate and validate our approach.

Detection and Analysis of Deficiencies in Groundnut Plant using Geometric Moments

We propose our genuine research of geometric moments which detects the mineral inadequacy in the frail groundnut plant. This plant is prone to many deficiencies as a result of the variance in the soil nutrients. By analyzing the leaves of the plant, we detect the visual symptoms that are not recognizable to the naked eyes. We have collected about 160 samples of leaves from the nearby fields. The images have been taken by keeping every leaf into a black box to avoid the external interference. For the first time, it has been possible to provide the farmer with the stages of deficiencies. This paper has applied the algorithms successfully to many other plants like Lady-s finger, Green Bean, Lablab Bean, Chilli and Tomato. But we submit the results of the groundnut predominantly. The accuracy of our algorithm and method is almost 93%. This will again pioneer a kind of green revolution in the field of agriculture and will be a boon to that field.

On the Efficient Implementation of a Serial and Parallel Decomposition Algorithm for Fast Support Vector Machine Training Including a Multi-Parameter Kernel

This work deals with aspects of support vector machine learning for large-scale data mining tasks. Based on a decomposition algorithm for support vector machine training that can be run in serial as well as shared memory parallel mode we introduce a transformation of the training data that allows for the usage of an expensive generalized kernel without additional costs. We present experiments for the Gaussian kernel, but usage of other kernel functions is possible, too. In order to further speed up the decomposition algorithm we analyze the critical problem of working set selection for large training data sets. In addition, we analyze the influence of the working set sizes onto the scalability of the parallel decomposition scheme. Our tests and conclusions led to several modifications of the algorithm and the improvement of overall support vector machine learning performance. Our method allows for using extensive parameter search methods to optimize classification accuracy.