bluuebunny/crossref_metadata_2025 huggingface dataset:
Cultura e biodiversidade: uma comparação entre a gestão do Parque Nacional do Cabo Orange, no Brasil, e a do Parque Nacional da Vanoise, na França
Authors: Kornijezuk Nádia Bandeira Sacenco
Published: November 2012

Este artigo tem como objetivo comparar a gestão de dois parques nacionais: o Parque Nacional do Cabo Orange, no Brasil, e o Parque Nacional da Vanoise, na França. As regiões onde estão localizados esses dois parques nacionais - Amazônia e Alpes, respectivamente - têm um capital ecológico de importância global. O parque Nacional do Cabo Orange é apresentado sob o enfoque do seu contexto regional, das suas particularidades sociais e ambientais e do turismo. O parque Nacional da Vanoise é analisado sob o enfoque do turismo e dos determinantes históricos e geográficos da região onde ele se insere. A comparação entre a gestão do Parque Nacional da Vanoise e a do Parque Nacional do Cabo Orange mostra que tanto seus modelos de gestão quanto seus contextos geopolíticos e ambientais são diversos: a França é mais populosa e sua biodiversidade é antropizada. Já o Brasil é um país de espaços abertos onde a biodiversidade é, em grande parte, resultado do processo evolutivo natural. A metodologia utilizada baseou-se no trabalho de campo e na revisão bibliográfica da literatura. Conclui-se que o Parque Nacional da Vanoise tem sua gestão direcionada à tentativa de conciliação entre o desenvolvimento regional e a preservação dos patrimônios natural e cultural enquanto o Parque Nacional do Cabo Orange é protetor da biodiversidade em sua forma mais prístina possível.
Les difficultés de la filière brésilienne face à la nouvelle organisation mondiale du négoce des pierres de couleur
Authors: Reys Aurélien
Published: November 2012

Les filières des pierres de couleur, à l’image de la plupart des ressources naturelles exploitées, ont longtemps représenté un négoce hiérarchisé largement dominé par les principales puissances occidentales. Leur organisation serait à présent en pleine restructuration notamment sous l’influence croissante d’acteurs originaires d’Asie. La nouvelle division des tâches et la multipolarisation du commerce ne profiteraient toutefois pas à la majorité des pays extracteurs qui connaitraient toujours d’importantes difficultés à jouer un rôle autre que celui strictement en lien avec les activités d’extraction. Le Brésil, considéré comme l’une des plus grandes réserves de pierres de couleur au monde, n’aurait semble-t-il pas réussi à tirer profit de cette réorganisation du commerce. En effet, bien qu’il réussisse, à l’inverse de nombreux autres pays extracteurs, à tailler une partie des pierres extraites, les gemmes à l’état brut continuent de constituer une grande part de ses exportations. Cette situation se traduirait depuis quelques années par une stagnation de ses bénéfices, d’autant plus que les acteurs locaux doivent désormais faire face à de nouvelles sources de concurrence, en provenance d’Afrique de l’Est pour les activités d’extraction et de Chine pour celles de taille et de commerce. Néanmoins, l’élévation du niveau de vie des populations à l’échelle mondiale permet d’envisager à long terme une croissance positive de ce type de négoce. La cartographie mondiale du commerce des gemmes est dès lors certainement loin d’être aboutie, laissant encore une certaine marge de manœuvre pour des pays comme le Brésil, ce dernier pouvant de plus compter sur une classe moyenne nationale en pleine croissance qui pourrait à terme constituer une nouvelle source de demande.
Construction et restructuration territoriale chez les Wayãpi et Teko de la commune de Camopi, Guyane française
Authors: Damien Davy , Tritsch Isabelle , Grenand Pierre
Published: November 2012

Deux peuples amérindiens de langue tupi-guarani, les Teko et les Wayãpi, vivent sur le territoire de Camopi, commune de Guyane française. Dans cet article1 nous nous attachons à retracer la construction historique de leurs territoires actuels, en montrant quand et comment ils se les ont appropriés. Nous explicitons également comment ces territoires sont devenus une commune de la République française. Dans une deuxième partie, nous présentons comment ces peuples s’adaptent aux changements contemporains induits par l’orpaillage illégal ayant lieu sur leur territoire et par le recrû démographique sans précédent qu’ils connaissent. Enfin, après avoir montré l’échec des politiques de regroupement que l’État français leur a imposé depuis 40 ans, nous concluons sur l’importance identitaire de leurs revendications socio-culturelles et territoriales contemporaines.
Les petits exploitants agricoles et l’État brésilien sur la frontière avec la Guyane française
Authors: Laurença Martins-Faure
Published: November 2012

Les agents de transformation du territoire, tant l’État que les petits exploitants agricoles, s’affrontent pour la reconnaissance de leurs actions dans la zone frontalière entre le Brésil et la Guyane française. Par la création et la mise en œuvre de stratégies d’appropriation de l’espace frontalier, chaque acteur devient agent de transformation du territoire. L’État brésilien est l’acteur principal de cette transformation, soit par l’imposition des règles de protection de la frontière, soit par la diffusion des programmes de développement économique ou, plus récemment, de développement durable. Les petits exploitants, souvent migrants d’autres régions du Brésil, participent de la politique officielle, en respectant les règles imposées, en questionnant leur viabilité, ou en intégrant ces politiques dans leurs stratégies d’agents économiques. Ce construit social est le nœud qui structure les échanges entre acteurs. La mise en lumière de ces échanges permet de cibler plus concrètement les mesures en accompagnement des activités productives agricoles en zone de frontière internationale.
Image Analysis and Understanding Based on Information Theoretical Region Merging Approaches for Segmentation and Cooperative Fusion
Authors: Calderero Felipe , Marqués Ferran
Published: November 2012

This chapter addresses the automatic creation of simplified versions of the image, known as image segmentation or partition, preserving the most semantically relevant information of the image at different levels of analysis. From a semantic and practical perspective, image segmentation is a first and key step for image analysis and pattern recognition since region-based image representations provide a first level of abstraction and a reduction of the number of primitives, leading to a more robust estimation of parameters and descriptors. The proposed solution is based on an important class of hierarchical bottom-up segmentation approaches, known as region merging techniques. These approaches naturally provide a bottom-up hierarchy, more suitable when no a priori information about the image is available, and an excellent compromise between efficiency of computation and representation. The chapter is organized in two parts dealing with the following objectives: (i) provide an unsupervised solution to the segmentation of generic images; (ii) design a generic and scalable scheme to automatically fuse hierarchical segmentation results that increases the robustness and accuracy of the final solution.
Multilevel Image Segmentation by a Multiobjective Genetic Algorithm Based OptiMUSIG Activation Function
Authors: De Sourav , Bhattacharyya Siddhartha , Chakraborty Susanta
Published: November 2012

The proposed chapter is intended to propose a self supervised image segmentation method by a multi-objective genetic algorithm based optimized MUSIG (OptiMUSIG) activation function with a multilayer self organizing neural network architecture to segment multilevel gray scale intensity images. The multiobjective genetic algorithm based parallel version of the OptiMUSIG (ParaOptiMUSIG) activation function with a parallel self organizing neural network architecture is also discussed to segment true color images. These methods are quite efficient enough to overcome the drawbacks of the single objective based OptiMUSIG and ParaOptiMUSIG activation functions to segment gray scale and true color images, respectively. The proposed multiobjective genetic algorithm based optimization methods are applied on three standard objective functions to measure the quality of the segmented images. These functions form the multiple objective criteria of the multiobjective genetic algorithm based image segmentation method.
Evolution of Genetic Algorithms in Classification Rule Mining
Authors: Dutta Dipankar , Sil Jaya
Published: November 2012

Classification is one of the most studied areas of data mining, which gives classification rules during training or learning. Classification rule mining, an important data-mining task, extracts significant rules for classification of objects. In this chapter class specific rules are represented in IF  THEN  form. With the popularity of soft computing methods, researchers explore different soft computing tools for rule discovery. Genetic algorithm (GA) is one of such tools. Over time, new techniques of GA for forming classification rules are invented. In this chapter, the authors focus on an understanding of the evolution of GA in classification rule mining to get an optimal rule set that builds an efficient classifier.
Using Data Masking for Balancing Security and Performance in Data Warehousing
Authors: Santos Ricardo Jorge , Bernardino Jorge , Vieira Marco
Published: November 2012

Data Warehouses (DWs) are the core of sensitive business information, which makes them an appealing target. Encryption solutions are accepted as the best way to ensure strong security in data confidentiality while keeping high database performance. However, this work shows that they introduce massive storage space and performance overheads to a magnitude that makes them unfeasible for DWs. This work proposes a data masking technique for protecting sensitive business data in DWs which balances security strength with database performance, using a Formula based on the mathematical modular operator and simple arithmetic operations. The proposed solution provides apparent randomness in the generation and distribution of the masked values, while introducing small storage space and query execution time overheads. It also enables a false data injection method for misleading attackers and increasing the overall security strength. It can be easily implemented in any DataBase Management System (DBMS) and transparently used, without changes to application source code. Experimental evaluations using a real-world DW and TPC-H decision support benchmark implemented in leading DBMS Oracle 11g and Microsoft SQL Server 2008 demonstrate its overall effectiveness. Results show the substantial savings of its implementation costs when compared with state of the art encryption solutions provided by those DBMS and that it outperforms those solutions in both data querying and insertion of new data.
Particle Swarm Optimization Algorithm and its Hybrid Variants for Feature Subset Selection
Authors: Chakraborty Basabi
Published: November 2012

Selecting an optimum subset of features from a large set of features is an important pre- processing step for pattern classification, data mining, or machine learning applications. Feature subset selection basically comprises of defining a criterion function for evaluation of the feature subset and developing a search strategy to find the best feature subset from a large number of feature subsets. Lots of mathematical and statistical techniques have been proposed so far. Recently biologically inspired computing is gaining popularity for solving real world problems for their more flexibility compared to traditional statistical or mathematical techniques. In this chapter, the role of Particle Swarm Optimization (PSO), one of the recently developed bio-inspired evolutionary computational (EC) approaches in designing algorithms for producing optimal feature subset from a large feature set, is examined. A state of the art review on Particle Swarm Optimization algorithms and its hybrids with other soft computing techniques for feature subset selection are presented followed by author’s proposals of PSO based algorithms. Simple simulation experiments with benchmark data sets and their results are shown to evaluate their respective effectiveness and comparative performance in selecting best feature subset from a set of features.
An Evolving System in the Text Classification Problem
Authors: Oliveira Elias , Ciarelli Patrick Marques , Salles Evandro Ottoni Teatini
Published: November 2012

Traditional machine learning techniques have been successful in yielding good results when the data are stable along the time horizon. However, in many cases, these techniques may be inefficient for data that are constantly expanding and changing over time. To address this problem, new learning techniques have been proposed in the literature. In this chapter, the authors discuss some improvements on their technique, called Evolving Probabilistic Neural Network (ePNN), and present the aspects of this recent learning paradigm. This technique is based on the Probabilistic Neural Networks. In this chapter the authors compare their technique against two other competitive techniques that can be found in the literature: Incremental Probabilistic Neural Network (IPNN) and Evolving Fuzzy Neural Network (EFuNN). To show the better performance of their technique, the authors present and discuss a series of experiments that demonstrate the efficiency of ePNN over both the IPNN and EFuNN approaches.
Fuzzy Based Modeling, Control, and Fault Diagnosis of Permanent Magnet Synchronous Generator
Authors: Selvaganesan N.
Published: November 2012

This chapter presents the design methodology of fuzzy based modeling, control, and fault diagnosis of Permanent Magnet Synchronous Generator (PMSG) system. The fuzzy based modeling scheme for PMSG is developed using the general Takagi-Sugeno fuzzy model. Subsequently, fuzzy controller is designed and simulated to maintain three phase output voltage as constant by controlling the speed of generator. The feasibility of the fuzzy model and control scheme is demonstrated using various operating conditions by MATLAB simulation. Also, fuzzy based fault detection scheme for PMSG is developed and presented. The positive and negative sequence currents are used as fault indicators and given as inputs to fuzzy fault detector. The fuzzy inference system is created, and rule base is evaluated, relating the sequence current component to the type of faults. The feasibility of this scheme is demonstrated for different types of fault under various operating conditions using MATLAB/Simulink.
Algorithms and Principles for Intelligent Design of Flapping Wing Micro Aerial Vehicles
Authors: Harish Ajay Bangalore , Harursampath Dineshkumar
Published: November 2012

Almost all Micro Aerial Vehicles (MAVs) designed so far facilitate the flapping motion of their wings by means of a mounted actuating mechanism, driven, for example, by a piezoelectric crystal. The developments over the past decade or so in smart material technologies like the invention of Piezoelectric Fiber Reinforced Composite (PFRC) materials and innovative manufacturing techniques to reduce cost have resulted in favorable materials for dynamic actuating applications. Thus, the concept of actively deformable wings to produce combined flapping and feathering actions is evolving as an attractive enabler for design of future MAVs. A smart material like PFRC can both sense and actuate in a collocated fashion, thus building an additional level of computational intelligence into the MAV itself. Such a promising opportunity indicates an urgent need for reliable design tools to accelerate development of MAVs. In this work, the authors propose a modular design tool specifically for design of self-actuating flapping wing MAVs.
Fuzzy-Controlled Energy-Conservation Technique (FET) for Mobile ad hoc Networks
Authors: Banerjee Anuradha
Published: November 2012

Nodes in ad hoc networks have limited battery power; hence, they require energy efficient techniques to improve average node lifetime and network performance. Maintaining energy efficiency in network communication is really challenging because highest energy efficiency is achieved if all the nodes are switched off and maximum network throughput is obtained if all the nodes are fully operational, i.e. always turned on. A promising energy conservation technique for the ad hoc networks must maintain effective packet forwarding capacity while turning off the network interface of very busy nodes for some time and redirecting the traffic through some comparatively idle nodes roaming around them. This also helps in fair load distribution in the network and maintenance of network connectivity by reducing the death rate (complete exhaustion of nodes). The present chapter proposes a fuzzy-controlled energy conservation technique (FET) that identifies the busy and idle nodes to canalize some traffic of busy nodes through the idle ones. In simulation section, the FET embedded versions of several state-of-the-art routing protocols in ad hoc networks are compared with their ordinary versions and the results quite emphatically establish the superiority of FET-embedded versions in terms of packet delivery ratio, message cost, and network energy consumption. End-to-end delay also reduces significantly.
Decision Fusion of Multisensor Images for Human Face Identification in Information Security
Authors: Bhowmik Mrinal Kanti , Saha Priya , Majumder Goutam , Bhattacharjee Debotosh
Published: November 2012

The chapter is mainly focused on theoretical discussions and experimental observations on decision fusion along with feature level multisensor fusion technique for human face identification especially useful in information security system in order to obtain better recognition rate. Feature level multisensor fusion of optical and infrared images is performed to resolve the difficulties of individual interpretation of visual and infrared images as a first step of the face identification system. ROC curve analysis is also reported to verify the recognition accuracy after classification of fused images using Support Vector Machine (SVM). The authors have performed experiments on IRIS face database in three different groups: full dataset, and two subsets with variation in expression and illumination. Classification accuracy was obtained in two subsets and full dataset as 95%, 94.12%, and 99.08%, respectively after decision fusion.
Quantum Backpropagation Neural Network Approach for Modeling of Phenol Adsorption from Aqueous Solution by Orange Peel Ash
Authors: Bhattacharjee Siddhartha , Bhattacharyya Siddhartha , Mondal Naba Kumar
Published: November 2012

The chapter describes a multilayer quantum backpropagation neural network (QBPNN) architecture to predict the removal of phenol from aqueous solution by orange peel ash, guided by the application of three types of activation functions and characterized by backpropagation of errors. These activation functions are Sigmoid function, tanh function and tan1.5h function. First by a classical multilayer neural network architecture with three types of activation functions is discussed in this chapter. It takes 6000000 iterations to train the network with a learning rate of 0.01. Among these three types of activation functions tan1.5 function shows the best prediction result. Next, QBPNN is discussed in this chapter. It takes 22000 iterations to train the network with the same learning rate. Here also tan1.5h function shows the best result in prediction of removal of phenol. Thus QBPNN is much faster than the classical multilayer neural network architecture. Different graphs are also given for comparison between the experimental output and network output using different activation functions. This particular chapter basically deals with a model application by which experimental results can be comparing with the model output. Because of their reliable, robust, and salient characteristics in capturing the non-linear relationships existing between variables (multi-input/output) in complex systems, it has become apparent that numerous applications of ANNs/QBNN have been successfully conducted in various parts of environmental engineering. Fuzzy Logic is also used as alternate method to predict the removal of phenol from aqueous solution by orange peel ash, but QBPNN shows the best result.
Computational Intelligence for Pathological Issues in Precision Agriculture
Authors: Sannakki Sanjeev S. , Rajpurohit Vijay S. , Nargund V. B. , Kumar Arun R. , Yallur Prema S.
Published: November 2012

Plant Pathology is the scientific study of plant diseases, caused by pathogens and environmental conditions (physiological factors). Detection and grading of plant diseases by machine vision is an essential research topic as it may prove useful in monitoring large fields of crops. This can be of great benefit to those users, who have little or no information about the crop they are growing. Also, in some developing countries, farmers may have to go long distances to contact experts to dig up information which is expensive and time consuming. Therefore, looking for a fast, automatic, less expensive, and accurate method to detect plant diseases is of great realistic significance. Such an efficient system can be modeled by integrating the various tools/techniques of information and communication technology (ICT) in agriculture. The objective of the present chapter is to model an intelligent decision support system for detection and grading of plant diseases which encompasses image processing techniques and soft computing/machine learning techniques.
Computer Intelligence in Healthcare
Authors: Ghosh Pramit , Bhattacharjee Debotosh , Nasipuri Mita , Basu Dipak Kumar
Published: November 2012

Low cost solutions for the development of intelligent bio-medical devices that not only assist people to live in a better way but also assist physicians for better diagnosis are presented in this chapter. Two such devices are discussed here, which are helpful for prevention and diagnosis of diseases. Statistical analysis reveals that cold and fever are the main culprits for the loss of man-hours throughout the world, and early pathological investigation can reduce the vulnerability of disease and the sick period. To reduce this cold and fever problem a household cooling system controller, which is adaptive and intelligent in nature, is designed. It is able to control the speed of a household cooling fan or an air conditioner based on the real time data, namely room temperature, humidity, and time for which system is active, which are collected from environment. To control the speed in an adaptive and intelligent manner, an associative memory neural network (Kramer) has been used. This embedded system is able to learn from training set; i.e., the user can teach the system about his/her feelings through training data sets. When the system starts up, it allows the fan to run freely at full speed, and after certain interval, it takes the environmental parameters like room temperature, humidity, and time as inputs. After that, the system takes the decision and controls the speed of the fan.
Intelligence in Web Technology
Authors: Maitra Sourav , Mondal A. C.
Published: November 2012

End users also start days with Internet. This has become the scenario. One of the most burgeoning needs of computer science research is research on web technologies and intelligence, as that has become one of the most emerging nowadays. A big area of other research areas like e-marketing, e-learning, e-governance, searching technologies, et cetera will be highly benefited if intelligence can be added to the Web. The objective of this chapter is to create a clear understanding of Web technology research and highlight the ways to implement Semantic Web. The chapter also discusses the tools and technologies that can be applied to develop Semantic Web. This new research area needs enough care as sometimes data are open. Thus, software engineering issues are also a focus.
Performance Comparison of Different Intelligent Techniques Applied on Detecting Proportion of Different Component in Manhole Gas Mixture
Authors: Ojha Varun Kumar , Dutta Paramartha
Published: November 2012

This chapter deals with the comparison of performances of different intelligent techniques for detecting proportion of different component gases present in manhole gas mixture. Toxic gases found in manhole gas mixture are Hydrogen Sulfide (H2S), Ammonia (NH3), Methane (CH4), Carbon Dioxide (CO2), Nitrogen Oxide (NOx), Carbon Monoxide (CO), etcetera. Detection of these toxic gases is essential since these gases influence human health even due to very short exposure. This study is centered on design issues of an intelligent sensory system for detecting proportion of different components in manhole gas mixture and comparison of different intelligent techniques applied for this. The investigation encompasses linear regression based statistical technique, backpropagation algorithm, neuro genetic techniques (using genetic algorithm to train neural network), and neuro swarm techniques (using particle swarm optimization algorithm to train neural network).
Niche Genetic Algorithm Based on Sexual Reproduction and Multimodal Function Optimization Problem
Authors: Tian Yulong , Gao Tao , Zhai Weifang , Hu Yaying , Li Xinfeng
Published: November 2012

In this paper, a genetic algorithm with sexual reproduction and niche selection technology is proposed. Simple genetic algorithm has been successfully applied to many evolutionary optimization problems. But there is a problem of premature convergence for complex multimodal functions. To solve it, the frame and realization of niche genetic algorithm based on sexual reproduction are presented. Age and sexual structures are given to the individuals referring the sexual reproduction and “niche” phenomena, importing the niche selection technology. During age and sexual operators, different evolutionary parameters are given to the individuals with different age and sexual structures. As a result, this genetic algorithm can combat premature convergence and keep the diversity of population. The testing for Rastrigin function and Shubert function proves that the niche genetic algorithm based on sexual reproduction is effective.
Coordination Performance Evaluation of Supply Logistics in JIT Environment
Authors: Li Guo , Zhang Xiang , Wang Zhaohua , Gao Tao
Published: November 2012

In JIT assembly system, any supplier’s postponement of delivery or incorrect delivery quantity will result in the manufacturer’s incapability of assembling on schedule, which will not only damage the interests of other suppliers but also jeopardize the interests of enterprises and reduce the competitiveness of the supply chain. In this article, coordination of the upstream supply logistics from internal and external aspects is taken as the research object. In external supply system, three aspects of cost, quality and time are used to evaluate the coordination of supply logistics in JIT environment. From the internal aspect, reliability, flexibility, responsiveness, customer service and system suitability are selected for the performance evaluation. The eight indexes construct an index system and each performance index is described and analyzed. Finally, Analytic Hierarchy Process is used to evaluate the coordinated performance of supply logistics in JIT environment. An example is provided, which illustrate the method used in this paper is feasible and meaningful.
The WiMap
Authors: Xu Junjun , Luo Haiyong , Zhao Fang , Tao Rui , Lin Yiming , Li Hui
Published: November 2012

As positioning technology is an important foundation of the Internet of Things, a dynamic indoor WLAN localization system is proposed in this paper. This paper mainly concentrates on the design and implementation of the WiMap-a dynamic indoor WLAN localization system, which employs grid-based localization method using RSS (received signal strength). To achieve high localization accuracy and low computational complexity, Gaussian mixture model is applied to approximate the signal distribution and a ROI (region of interest) is defined to limit the search region. The authors also discuss other techniques like AP selection and threshold control, which affects the localization accuracy. The experimental results indicate that an accuracy of 3m with 73.8% probability can be obtained in WiMap. Moreover, the running time is reduced greatly with limited ROI method.
Identifying Disease Genes Based on Functional Annotation and Text Mining
Authors: Yuan Fang , Li Mingliang , Li Jing
Published: November 2012

The identification of disease genes from candidated regions is one of the most important tasks in bioinformatics research. Most approaches based on function annotations cannot be used to identify genes for diseases without any known pathogenic genes or related function annotations. The authors have built a new web tool, DGHunter, to predict genes associated with these diseases which lack detailed function annotations. Its performance was tested with a set of 1506 genes involved in 1147 disease phenotypes derived from the morbid map table in the OMIM database. The results show that, on average, the target gene was in the top 13.60% of the ranked lists of candidates, and the target gene was in the top 5% with a 40.70% chance. DGHunter can identify disease genes effectively for those diseases lacking sufficient function annotations.
TB-WPRO
Authors: Chen Qihua , Wang Xiangdong , Qian Yueliang
Published: November 2012

For cell phone users and blind people using non-visual browsers, browsing Web by common browsers is quite inefficient due to the problem of information overload. This paper presents the TB-WPRO (Title-Block based Web Page Re-Organization) method, which hierarchically segments web pages into blocks using visual and layout information reflecting the web designers’ intent. TB-WPRO segments the web pages with a clear goal to extract self-described title blocks. To reorganize web pages, the segmentation result is transformed to a serial of small web pages that could be easily accessed. Compared to current methods, the proposed approach obtains a promising segmentation result where blocks are visually and semantically consistent with original web pages.
Constructing the Collaborative Supply Logistics Operation Mode in Assembly System under JIT Environment
Authors: Li Guo , Gao Tao , Ran Lun
Published: November 2012

In the JIT assembly system, if any supplier does not deliver the raw materials or components on time, or in the right quantity, the core manufacturers will not assemble on the schedule, which will bring great loss to the whole supply chain and greatly reduce the competitiveness and collaboration of the entire supply chain. Based on a survey on supply chain collaboration and operation model, supply logistics in JIT environment are analyzed from both the inside and outside system with the research goal of coordinating the upstream supply logistics. In order to help manufacturers implement the JIT production, the VMI-Hub operation mode is proposed from the aspect of inside system, and from outside system, cross-docking dispatch operation mode is considered to coordinate the supply logistics in assembly system.
Construction Competitiveness Evaluation System of Regional BioPharma Industry and Case Study
Authors: Zhao Bing , Zhang Dong Sheng , Zhao Yong Zheng
Published: November 2012

Biological pharmaceutical industry not only has the continuous pulling action to region economy, also makes a positive contribution on the human productivity and quality of life. Biological pharmaceutical industry will become the leading industry of the century in quite a long time in the future. Taking Shijiazhuang as an example, according to the regional biopharmaceutical industry planning needs, building the industry competitiveness evaluation system, this paper analyzes the comparative advantage of Shijiazhuang in developing bio-pharmaceutical industry from 4 level evaluation index, including: the industry environment and policy, R & D capability, competitiveness of economic scale and industry support system. Provide a reference for local governments and business.
Image Fusion of ECT/ERT for Oil-Gas-Water Three-Phase Flow
Authors: Zhang Lifeng
Published: November 2012

The tomographic imaging of process parameters for oil-gas-water three-phase flow can be obtained through different sensing modalities, such as electrical resistance tomography (ERT) and electrical capacitance tomography (ECT), both of which are sensitive to specific properties of the objects to be imaged. However, it is hard to discriminate oil, gas and water phases merely from reconstructed images of ERT or ECT. In this paper, the feasibility of image fusion based on ERT and ECT reconstructed images was investigated for oil-gas-water three-phase flow. Two cases were discussed and pixel-based image fusion method was presented. Simulation results showed that the cross-sectional reconstruction images of oil-gas-water three-phase flow can be obtained using the presented methods.
The Design of Portable Integration Strengthening Machine
Authors: Yuan Li , Lu Ximing , Huang Ruifang
Published: November 2012

This paper investigates briefly the integrated portable reinforcement machine structure design and introduces its design and train of thought. The authors also discuss design methods in engineering applications, as well as how to achieve good heat dissipation effect and enhance the electromagnetic compatibility. The whole machine, with its small volume, good adaptability to environment, and electromagnetic compatibility, can be used as a reference for similar engineering design.
Dynamic Spectrum Auction and Load Balancing Algorithm in Heterogeneous Network
Authors: Jiang Yan
Published: November 2012

Mobile communication plays an important role in the future of communication systems. To meet personalized and intelligent requirements, mobile communication has evolved from single wireless cellular network to heterogeneous mobile communication network, including wireless cellular network, wireless local network, and wireless personal network. In the heterogeneous communication system, to entirely fulfill the spectrum resource complementary advantages of such a heterogeneous wireless network, the spectrum resource trade algorithm has attracted tremendous research efforts. In this paper, the advantages and disadvantages of dynamic spectrum allocation and load balancing are discussed and spectrum auction takes the place of spectrum allocation to maximize the operation revenue. The authors design a joint spectrum auction and load balancing algorithm (SALB) based on heterogeneous network environment to develop a more flexible and efficient spectrum management. The simulation result shows that SALB increases the operation profit significantly.
A Novel Detection Method of Paper Defects Based on Visual Attention Mechanism
Authors: Jiang Ping , Gao Tao
Published: November 2012

In this paper, an improved paper defects detection method based on visual attention mechanism computation model is presented. First, multi-scale feature maps are extracted by linear filtering. Second, the comparative maps are obtained by carrying out center-surround difference operator. Third, the saliency map is obtained by combining conspicuity maps, which is gained by combining the multi-scale comparative maps. Last, the seed point of watershed segmentation is determined by competition among salient points in the saliency map and the defect regions are segmented from the background. Experimental results show the efficiency of the approach for paper defects detection.
Dynamic and Secure Business Data Exchange Model for SaaS-Based Collaboration Supporting Platform of Industrial Chain
Authors: Wang Shuying , Li Jizi , Ma Shihua
Published: November 2012

In this paper, by analyzing the characteristics of data exchange process of SaaS-based collaboration supporting platform for industrial chain, a dynamic and secure business data exchange model for the platform is established. On this basis, methods for business data automatic obtain and format conversion, client authentication based on encryption lock and SOAP extension, business data encryption based on public key of the platform, and instant key created by client is discussed. The implementation of these methods is studied based on a .NET environment. Furthermore, the dynamic and secure business data exchange model is used in the SaaS platform of the automotive industry chain and SaaS platform of the injection industry chain, as it meets the multi-source and heterogeneous information exchange requirements.
3-D Video based Disparity Estimation and Object Segmentation
Authors: Gao Tao
Published: November 2012

Stereo video object segmentation is a critical technology of the new generation of video coding, video retrieval and other emerging interactive multimedia fields. Determinations of distinctive depth of a frame features have become more popular in everyday life for automation industries like machine vision and computer vision technologies. This paper examines the evaluation of depth cues through dense of two frame stereo correspondence method. Experimental results show that the method can segment the stationary and moving objects with better accuracy and robustness. The contributions have higher accuracy in matching and reducing time of convergence.
Design and Implementation of Bipolar Digital Signal Acquisition and Processing System based on FPGA and ACPL-224
Authors: Lin Guangfu , Yin Zhenxing , Feng Guo
Published: November 2012

This paper proposes new approaches for designing a bipolar DS acquisition system to reduce the harm of external factors on equipment, as well as fulfill system requirements at the veracity and reliability of the equipment to quickly connect. The design method chosen is ACPL-224 for chip of the interface about data acquisition on the FPGA device, including system principle, interface circuit logic, the method of data processing, and so forth. Now that this method has been applied, it has achieved good results, including extending the system’s adaptive range of external signal and enhancing the efficiency of the interface to quickly connect.
Financial Distress Prediction of Chinese-Listed Companies Based on PCA and WNNs
Authors: Xin Xiu , Xiong Xiaoyi
Published: November 2012

The operating status of an enterprise is disclosed periodically in a financial statement. Financial distress prediction is important for business bankruptcy prevention, and various quantitative prediction methods based on financial ratios have been proposed. This paper presents a financial distress prediction model based on wavelet neural networks (WNNs). The transfer functions of the neurons in WNNs are wavelet base functions which are determined by dilation and translation factors. Back propagation algorithm was used to train the WNNs. Principal component analysis (PCA) method was used to reduce the dimension of the inputs of the WNNs. Multiple discriminate analysis (MDA), Logit, Probit, and WNNs were employed to a dataset selected from Chinese-listed companies. The results demonstrate that the proposed WNNs-based model performs well in comparison with the other three models.
Modeling of Across-Chain Network Dynamic Competition for MNC in Industrial Cluster
Authors: Liu Chunling , Li Jizi , Li Guo , Cao Xiaogang
Published: November 2012

The huge market and perfect production system in China are attracting more multi-national companies’ interest to invest in China in the form of Foreign Direct Investment (FDI). Therefore, multi-national companies are willing to integrate and optimize global supply chain networks of their own, which enable them to reduce cost and improve market response. As a result, multi-national companies usually embed into local industrial clusters through financial and technological comparative merits to sharpen their competitive edge. This paper considers the across-chain network equilibrium problem involving process of competition and melting between this new global chain and an already existing local chain. The authors model the optimizing behavior of these two chains, derive the equilibrium conditions, and establish the variational inequality formulation, and solve it by using the modified algorithm. Finally, the authors illustrate the model through numerical example and discuss relationships among the price, quantity, technological progress, and satisfaction among two dynamic phases.
Comprehensive Structure of Novel Voice Priority Queue Scheduling System Model for VoIP over WLANs
Authors: Nisar Kashif , Amphawan Angela , Hassan Suhaidi B.
Published: November 2012

Voice over Internet Protocol (VoIP) has grown quickly in the world of telecommunication. Wireless Local Area Networks (WLANs) are the most performance assuring technology for wireless networks, and WLANs have facilitated high-rate voice services at low cost and good flexibility. In a voice conversation, each client works as a sender or a receiver depending on the direction of traffic flow over the network. A VoIP application requires high throughput, low packet loss, and a high fairness index over the network. The packets of VoIP streaming may experience drops because of the competition among the different kinds of traffic flow over the network. A VoIP application is also sensitive to delay and requires the voice packets to arrive on time from the sender to the receiver side without any delay over WLAN. The scheduling system model for VoIP traffic is an unresolved problem. The objectives of this paper are to identify scheduler issues. This comprehensive structure of Novel Voice Priority Queue (VPQ) scheduling system model for VoIP over WLAN discusses the essential background of the VPQ schedulers and algorithms. This paper also identifies the importance of the scheduling techniques over WLANs.
Ontology Mapping Validation
Authors: Serpeloni Felipe , Moraes Regina , Bonacin Rodrigo
Published: November 2012

The use of ontologies and ontology mappings is increasing in companies. Often the same context is modeled in different ontologies. Mapping is necessary to integrate these ontologies; however, in many cases these mappings are incorrect, i.e., they incorrectly link semantic concepts with different meanings. Tools that validate these mappings are necessary to ensure reliable communication between heterogeneous systems. This validation cannot be done in a completely automatic way, because the mappings are based on human interpretation. This work describes a semi-automatic tool that supports this activity, based on graphs that generate instances validated in a semi-automatic process that aims to ensure mapping robustness. This algorithm deals with an NP-Complete problem in order to generate all the instances. This paper presents a first prototype of the tool and the methodology used to validate the instances automatically generated by the tool.
A Semiotic-Based Approach for Search in Social Network Services
Authors: dos Reis Júlio C. , Bonacin Rodrigo , Baranauskas M. Cecília C.
Published: November 2012

Search mechanisms in Social Network Services (SNSs) should take into account the meanings created, shared, and used by people through the use of the system. This paper investigates a new approach to develop search mechanisms more adequate for SNSs. SNSs represent an opportunity for people access to information in the Web. These systems allow individuals to constitute communities of common interests with wide cultural diversity, sharing information and vocabularies. The search mechanism proposed in this paper is grounded in Semantic Web technologies combined and articulated with Organizational Semiotics methods and artifacts. The authors illustrate a process to create the ontology and techniques to improve semantic search results in SNSs using Semantic Web Rule Language. The paper discusses the practical and technological results that could be achieved using the proposed approach.
Adaptive Ontology-Based Web Information Retrieval
Authors: Pruski Cédric , Guelfi Nicolas , Reynaud Chantal
Published: November 2012

Finding relevant information on the Web is difficult for most users. Although Web search applications are improving, they must be more “intelligent” to adapt to the search domains targeted by queries, the evolution of these domains, and users’ characteristics. In this paper, the authors present the TARGET framework for Web Information Retrieval. The proposed approach relies on the use of ontologies of a particular nature, called adaptive ontologies, for representing both the search domain and a user’s profile. Unlike existing approaches on ontologies, the authors make adaptive ontologies adapt semi-automatically to the evolution of the modeled domain. The ontologies and their properties are exploited for domain specific Web search purposes. The authors propose graph-based data structures for enriching Web data in semantics, as well as define an automatic query expansion technique to adapt a query to users’ real needs. The enriched query is evaluated on the previously defined graph-based data structures representing a set of Web pages returned by a usual search engine in order to extract the most relevant information according to user needs. The overall TARGET framework is formalized using first-order logic and fully tool supported.
Prosumerization of Mobile Service Provision
Authors: Werth Dirk , Emrich Andreas , Chapko Alexandra
Published: November 2012

Prosumerization is the enabling of users to act as producers. Prosumerization of content for the mobile internet, in which users are consumers and producers of content, is a recent trend. However, user-generated mobile services are the next big step for mobile service provision emerging from the prosumerization of content. Benefits for platform and telecommunication providers can be significant, especially if information released by prosumers is used wisely by providers. This article derives implications for providers and their applied information technology. An architectural proposal is described which focuses on the usage of prosumers’ information for internal business adaptations of providers as well as creation of feedback to the prosumers. Since prosumers as additional creative force in the development process move much closer to a provider’s business, user-centricity has to go beyond improved customer relationship management.
Development of Audio Sensing Technology for Ambient Assisted Living
Authors: Vacher Michel , Portet François , Fleury Anthony , Noury Norbert
Published: November 2012

One of the greatest challenges in Ambient Assisted Living is to design health smart homes that anticipate the needs of its inhabitant while maintaining their safety and comfort. It is thus essential to ease the interaction with the smart home through systems that naturally react to voice command using microphones rather than tactile interfaces. However, efficient audio analysis in such noisy environment is a challenging task. In this paper, a real-time audio analysis system, the AuditHIS system, devoted to audio analysis in smart home environment is presented. AuditHIS has been tested thought three experiments carried out in a smart home that are detailed. The results show the difficulty of the task and serve as basis to discuss the stakes and the challenges of this promising technology in the domain of AAL.