Terrain Evaluation Method for Hexapod Robot

In this paper a simple terrain evaluation method for hexapod robot is introduced. This method is based on feet coordinate evaluation when all are on the ground. Depending on the feet coordinate differences the local terrain evaluation is possible. Terrain evaluation is necessary for right gait selection and/or body position correction. For terrain roughness evaluation three planes are plotted: two of them as definition points use opposite feet coordinates, third coincides with the robot body plane. The leaning angle of body plane is evaluated measuring gravity force using three-axis accelerometer. Terrain roughness evaluation method is based on angle estimation between normal vectors of these planes. Aim of this work is to present a simple method for embedded robot controller, allowing to find the best further movement settings.

Consumer Insolvency in the Czech Republic

The Czech Republic is a country whose economy has undergone a transformation since 1989. Since joining the EU it has been striving to reduce the differences in its economic standard and the quality of its institutional environment in comparison with developed countries. According to an assessment carried out by the World Bank, the Czech Republic was long classed as a country whose institutional development was seen as problematic. For many years one of the things it was rated most poorly on was its bankruptcy law. The new Insolvency Act, which is a modern law in terms of its treatment of bankruptcy, was first adopted in the Czech Republic in 2006. This law, together with other regulatory measures, offers debtridden Czech economic subjects legal instruments which are well established and in common practice in developed market economies. Since then, analyses performed by the World Bank and the London EBRD have shown that there have been significant steps forward in the quality of Czech bankruptcy law. The Czech Republic still lacks an analytical apparatus which can offer a structured characterisation of the general and specific conditions of Czech company and household debt which is subject to current changes in the global economy. This area has so far not been given the attention it deserves. The lack of research is particularly clear as regards analysis of household debt and householders- ability to settle their debts in a reasonable manner using legal and other state means of regulation. We assume that Czech households have recourse to a modern insolvency law, yet the effective application of this law is hampered by the inconsistencies in the formal and informal institutions involved in resolving debt. This in turn is based on the assumption that this lack of consistency is more marked in cases of personal bankruptcy. Our aim is to identify the symptoms which indicate that for some time the effective application of bankruptcy law in the Czech Republic will be hindered by factors originating in householders- relative inability to identify the risks of falling into debt.

Identifying Impact Factors in Technology Transfer with the Aim of Technology Localization

Technology transfer is a common method for companies to acquire new technology and presents both challenges and substantial benefits. In some cases especially in developing countries, the mere possession of technology does not guarantee a competitive advantage if the appropriate infrastructure is not in place. In this paper, we identify the localization factors needed to provide a better understanding of the conditions necessary for localization in order to benefit from future technology developments. Our theoretical and empirical analyses allow us to identify several factors in the technology transfer process that affect localization and provide leverage in enhancing capabilities and absorptive capacity.The impact factors are categorized within different groups of government, firms, institutes and market, and are verified through the empirical survey of a technology transfer experience. Moreover, statistical analysis has allowed a deeper understanding of the importance of each factor and has enabled each group to prioritize their organizational policies to effectively localize their technology.

Characterization of Responsivity, Sensitivity and Spectral Response in Thin Film SOI photo-BJMOS -FET Compatible with CMOS Technology

Photo-BJMOSFET (Bipolar Junction Metal-Oxide- Semiconductor Field Effect Transistor) fabricated on SOI film was proposed. ITO film is adopted in the device as gate electrode to reduce light absorption. Depletion region but not inversion region is formed in film by applying gate voltage (but low reverse voltage) to achieve high photo-to-dark-current ratio. Comparisons of photoelectriccharacteristics executed among VGK=0V, 0.3V, 0.6V, 0.9V and 1.0V (reverse voltage VAK is equal to 1.0V for total area of 10×10μm2). The results indicate that the greatest improvement in photo-to-dark-current ratio is achieved up to 2.38 at VGK=0.6V. In addition, photo-BJMOSFET is compatible with CMOS integration due to big input resistance

Multimodal Biometric System Based on Near- Infra-Red Dorsal Hand Geometry and Fingerprints for Single and Whole Hands

Prior research evidenced that unimodal biometric systems have several tradeoffs like noisy data, intra-class variations, restricted degrees of freedom, non-universality, spoof attacks, and unacceptable error rates. In order for the biometric system to be more secure and to provide high performance accuracy, more than one form of biometrics are required. Hence, the need arise for multimodal biometrics using combinations of different biometric modalities. This paper introduces a multimodal biometric system (MMBS) based on fusion of whole dorsal hand geometry and fingerprints that acquires right and left (Rt/Lt) near-infra-red (NIR) dorsal hand geometry (HG) shape and (Rt/Lt) index and ring fingerprints (FP). Database of 100 volunteers were acquired using the designed prototype. The acquired images were found to have good quality for all features and patterns extraction to all modalities. HG features based on the hand shape anatomical landmarks were extracted. Robust and fast algorithms for FP minutia points feature extraction and matching were used. Feature vectors that belong to similar biometric traits were fused using feature fusion methodologies. Scores obtained from different biometric trait matchers were fused using the Min-Max transformation-based score fusion technique. Final normalized scores were merged using the sum of scores method to obtain a single decision about the personal identity based on multiple independent sources. High individuality of the fused traits and user acceptability of the designed system along with its experimental high performance biometric measures showed that this MMBS can be considered for med-high security levels biometric identification purposes.

Power Distance and Knowledge Management from a Post-Taylorist Perspective

Contact centres have been exemplars of scientific management in the discipline of operations management for more than a decade now. With the movement of industries from a resource based economy to knowledge based economy businesses have started to realize the customer eccentricity being the key to sustainability amidst high velocity of the market. However, as technologies have converged and advanced, so have the contact centres. Contact Centres have redirected the supply chains and the concept of retailing is highly diminished due to over exaggeration of cost reduction strategies. In conditions of high environmental velocity together with services featuring considerable information intensity contact centres will require up to date and enlightened agents to satisfy the demands placed upon them by those requesting their services. In this paper we examine salient factors such as Power Distance, Knowledge structures and the dynamics of job specialisation and enlargement to suggest critical success factors in the domain of contact centres.

Application of Association Rule Mining in Supplier Selection Criteria

In this paper the application of rule mining in order to review the effective factors on supplier selection is reviewed in the following three sections 1) criteria selecting and information gathering 2) performing association rule mining 3) validation and constituting rule base. Afterwards a few of applications of rule base is explained. Then, a numerical example is presented and analyzed by Clementine software. Some of extracted rules as well as the results are presented at the end.

Effects of Bay Leaves on Blood Glucose and Lipid Profiles on the Patients with Type 1 Diabetes

Bay leaves have been shown to improve insulin function in vitro but the effects on people have not been determined. The objective of this study was to determine if bay leaves may be important in the prevention and/or alleviation of type 1 diabetes. Methods: Fifty five people with type 1 diabetes were divided into two groups, 45 given capsules containing 3 g of bay leaves per day for 30 days and 10 given a placebo capsules. Results All the patients consumed bay leaves shows reduced serum glucose with significant decreases 27% after 30 d. Total cholesterol decreased, 21 %, after 30 days with larger decreases in low density lipoprotein (LDL) 24%. High density lipoprotein (HDL) increased 20% and Triglycerides also decreased 26%. There were no significant changes in the placebo group. Conclusion, this study demonstrates that consumption of bay leaves, 3 g/d for 30 days, decreases risk factors for diabetes and cardiovascular diseases and suggests that bay leaves may be beneficial for people with type 1 diabetes.

Direction to Manage OTOP Entrepreneurship Based on Local Wisdom

The OTOP Entrepreneurship that used to create substantial source of income for local Thai communities are now in a stage of exigent matters that required assistances from public sectors due to over Entrepreneurship of duplicative ideas, unable to adjust costs and prices, lack of innovation, and inadequate of quality control. Moreover, there is a repetitive problem of middlemen who constantly corner the OTOP market. Local OTOP producers become easy preys since they do not know how to add more values, how to create and maintain their own brand name, and how to create proper packaging and labeling. The suggested solutions to local OTOP producers are to adopt modern management techniques, to find knowhow to add more values to products and to unravel other marketing problems. The objectives of this research are to study the prevalent OTOP products management and to discover direction to manage OTOP products to enhance the effectiveness of OTOP Entrepreneurship in Nonthaburi Province, Thailand. There were 113 participants in this study. The research tools can be divided into two parts: First part is done by questionnaire to find responses of the prevalent OTOP Entrepreneurship management. Second part is the use of focus group which is conducted to encapsulate ideas and local wisdom. Data analysis is performed by using frequency, percentage, mean, and standard deviation as well as the synthesis of several small group discussions. The findings reveal that 1) Business Resources: the quality of product is most important and the marketing of product is least important. 2) Business Management: Leadership is most important and raw material planning is least important. 3) Business Readiness: Communication is most important and packaging is least important. 4) Support from public sector: Certified from the government is most important and source of raw material is the least important.

An Approximate Engineering Method for Aerodynamic Heating Solution around Blunt Body Nose

This paper is devoted to predict laminar and turbulent heating rates around blunt re-entry spacecraft at hypersonic conditions. Heating calculation of a hypersonic body is normally performed during the critical part of its flight trajectory. The procedure is of an inverse method, where a shock wave is assumed, and the body shape that supports this shock, as well as the flowfield between the shock and body, are calculated. For simplicity the normal momentum equation is replaced with a second order pressure relation; this simplification significantly reduces computation time. The geometries specified in this research, are parabola and ellipsoids which may have conical after bodies. An excellent agreement is observed between the results obtained in this paper and those calculated by others- research. Since this method is much faster than Navier-Stokes solutions, it can be used in preliminary design, parametric study of hypersonic vehicles.

Do Firms Need Strategic Alliances?

This study develops a relation to explore the factors influencing management and technology capabilities in strategic alliances. Alliances between firms are recognizing increasingly popular as a vehicle to create and extract greater value from the market. Firm’s alliance can be described as the collaborative problem solving process to solve problems jointly. This study starts from research questions what factors of firm’s management and technology characteristics affect performance of firms which are formed alliances. In this study, we investigated the effect of strategic alliances on company performance. That is, we try to identify whether firms made an alliance with other organizations are differed by characteristics of management and technology. And we test that alliance type and alliance experiences moderate the relationship between firm’s capabilities and its performance. We employ problem-solving perspective and resource-based view perspective to shed light on this research questions. The empirical work is based on the Survey of Business Activities conducted from2006 to 2008 by Statistics Korea. We verify correlations between to point out that these results contribute new empirical evidence on the effect of strategic alliances on company performance.

Parametric Study of a Vapor Compression Refrigeration Cycle Using a Two-Phase Constant Area Ejector

There are several ways of improving the performance of a vapor compression refrigeration cycle. Use of an ejector as expansion device is one of the alternative ways. The present paper aims at evaluate the performance improvement of a vapor compression refrigeration cycle under a wide range of operating conditions. A numerical model is developed and a parametric study of important parameters such as condensation (30-50°C) and evaporation temperatures (-20-5°C), nozzle and diffuser efficiencies (0.75-0.95), subcooling and superheating degrees (0-15K) are investigated. The model verification gives a good agreement with the literature data. The simulation results revealed that condensation temperature has the highest effect (129%) on the performance improvement ratio while superheating has the lowest one (6.2%). Among ejector efficiencies, the diffuser efficiency has a significant effect on the COP of ejector expansion refrigeration cycle. The COP improvement percentage decreases from 10.9% to 4.6% as subcooling degrees increases by 15K.

Control Improvement of a C Sugar Cane Crystallization Using an Auto-Tuning PID Controller Based on Linearization of a Neural Network

The industrial process of the sugar cane crystallization produces a residual that still contains a lot of soluble sucrose and the objective of the factory is to improve its extraction. Therefore, there are substantial losses justifying the search for the optimization of the process. Crystallization process studied on the industrial site is based on the “three massecuites process". The third step of this process constitutes the final stage of exhaustion of the sucrose dissolved in the mother liquor. During the process of the third step of crystallization (Ccrystallization), the phase that is studied and whose control is to be improved, is the growing phase (crystal growth phase). The study of this process on the industrial site is a problem in its own. A control scheme is proposed to improve the standard PID control law used in the factory. An auto-tuning PID controller based on instantaneous linearization of a neural network is then proposed.

Wavelet Transform and Support Vector Machine Approach for Fault Location in Power Transmission Line

This paper presents a wavelet transform and Support Vector Machine (SVM) based algorithm for estimating fault location on transmission lines. The Discrete wavelet transform (DWT) is used for data pre-processing and this data are used for training and testing SVM. Five types of mother wavelet are used for signal processing to identify a suitable wavelet family that is more appropriate for use in estimating fault location. The results demonstrated the ability of SVM to generalize the situation from the provided patterns and to accurately estimate the location of faults with varying fault resistance.

Massive Lesions Classification using Features based on Morphological Lesion Differences

Purpose of this work is the development of an automatic classification system which could be useful for radiologists in the investigation of breast cancer. The software has been designed in the framework of the MAGIC-5 collaboration. In the automatic classification system the suspicious regions with high probability to include a lesion are extracted from the image as regions of interest (ROIs). Each ROI is characterized by some features based on morphological lesion differences. Some classifiers as a Feed Forward Neural Network, a K-Nearest Neighbours and a Support Vector Machine are used to distinguish the pathological records from the healthy ones. The results obtained in terms of sensitivity (percentage of pathological ROIs correctly classified) and specificity (percentage of non-pathological ROIs correctly classified) will be presented through the Receive Operating Characteristic curve (ROC). In particular the best performances are 88% ± 1 of area under ROC curve obtained with the Feed Forward Neural Network.

ICF Neutron Detection Techniques Based on Doped ZnO Crystal

Ultrafast doped zinc oxide crystal promised us a good opportunity to build new instruments for ICF fusion neutron measurement. Two pulsed neutron detectors based on ZnO crystal wafer have been conceptually designed, the superfast ZnO timing detector and the scintillation recoil proton neutron detection system. The structure of these detectors was presented, and some characters were studied as well. The new detectors could be much faster than existing systems, and would be more competent for ICF neutron diagnostics.

Physiological and Biochemical Responses to Drought Stress of Chickpea Genotypes

The experimental design was 4 x 5 factorial with three replications in fully controlled research greenhouse in Department of Soil Sciences and Plant Nutrition, Faculty of Agriculture, University of Selcuk in the year of 2009. Determination of tolerant chickpea genotypes to drought was made in the research. Additionally, sophisticated effects of drought on plant growth and development, biochemical and physical properties or physical defense mechanisms were presented. According to the results, the primary genotypes were Ilgın YP (0.0063 g/gh) for leaf water capacity, 22235 70.44(%) for relative water content, 22159 (82.47%) for real water content, 22159 (5.03 mg/l) for chlorophyll a+b, Ilgın YP (125.89 nmol H2O2.dak-1/ mg protein-1) for peroxidase, Yunak YP (769.67 unit/ mg protein-1) for superoxide dismutase, Seydişehir YP (16.74 μg.TA-1) for proline, Gökçe (80.01 nmol H2O2.dak-1/ mg protein-1) for catalase. Consequently, all the genotypes increased their enzyme activity depending on the increasing of drought stress consider with the effects of drought stress on leaf enzyme activity. Chickpea genotypes are increasing enzyme activity against to drought stress.

Information Filtering using Index Word Selection based on the Topics

We have proposed an information filtering system using index word selection from a document set based on the topics included in a set of documents. This method narrows down the particularly characteristic words in a document set and the topics are obtained by Sparse Non-negative Matrix Factorization. In information filtering, a document is often represented with the vector in which the elements correspond to the weight of the index words, and the dimension of the vector becomes larger as the number of documents is increased. Therefore, it is possible that useless words as index words for the information filtering are included. In order to address the problem, the dimension needs to be reduced. Our proposal reduces the dimension by selecting index words based on the topics included in a document set. We have applied the Sparse Non-negative Matrix Factorization to the document set to obtain these topics. The filtering is carried out based on a centroid of the learning document set. The centroid is regarded as the user-s interest. In addition, the centroid is represented with a document vector whose elements consist of the weight of the selected index words. Using the English test collection MEDLINE, thus, we confirm the effectiveness of our proposal. Hence, our proposed selection can confirm the improvement of the recommendation accuracy from the other previous methods when selecting the appropriate number of index words. In addition, we discussed the selected index words by our proposal and we found our proposal was able to select the index words covered some minor topics included in the document set.

Graph-Based Text Similarity Measurement by Exploiting Wikipedia as Background Knowledge

Text similarity measurement is a fundamental issue in many textual applications such as document clustering, classification, summarization and question answering. However, prevailing approaches based on Vector Space Model (VSM) more or less suffer from the limitation of Bag of Words (BOW), which ignores the semantic relationship among words. Enriching document representation with background knowledge from Wikipedia is proven to be an effective way to solve this problem, but most existing methods still cannot avoid similar flaws of BOW in a new vector space. In this paper, we propose a novel text similarity measurement which goes beyond VSM and can find semantic affinity between documents. Specifically, it is a unified graph model that exploits Wikipedia as background knowledge and synthesizes both document representation and similarity computation. The experimental results on two different datasets show that our approach significantly improves VSM-based methods in both text clustering and classification.

Customer-Supplier Collaboration in Casting Industry: a Review on Organizational and Human Aspects

Customer-supplier collaboration enables firms to achieve greater success than acting independently. Nevertheless, not many firms have fully utilized the potential of collaboration. This paper presents organizational and human related success factors for collaboration in manufacturing supply chains in casting industry. Our research approach was a case study including multiple cases. Data was gathered by interviews and group discussions in two different research projects. In the first research project we studied seven firms and in the second five. It was found that the success factors are interrelated, in other words, organizational and human factors together enable success but not any of them alone. Some of the found success factors are a culture of following agreements, and a speed of informing the partner about changes affecting to the product or the delivery chain.