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Augmented reality (AR) and virtual reality (VR) are becoming a part of everyday life with the advance of other technologies such as computer vision systems, sensing technologies, graphics, mobile computing, etc. Their primary goal is to help users achieve their goals effectively and efficiently with satisfaction. This paper describes the trends of how user studies have been incorporated into AR and VR papers published in two major conferences over the past three years. In addition, this paper presents implications on what needs to be taken into account when planning a user study in the field of AR and VR research. [ABSTRACT FROM PUBLISHER]

Whenever a research scholar starts working on some innovative ideas he/she searches for the domain specific technical research articles published as research papers in most of the international journals, conferences or workshops. The problems associated with these papers are similarity in contents and repeated relevant information. Reading these all relatedpapers completely one by one to get the latest research developments in the interested domain is time-consuming, unnecessary, irrelevant, cumbersome and impossible. These problems are solved by developing a innovative solution, which optimizes and summarizes these research papers as an aid for research scholars using various Data Mining strategies. This helps research scholar for getting short, condensed, accurate and most relevant summarized information i.e. overview of domain-specific topic-based contents from research papers. Data mining strategies such as extraction and clustering are used for identifying ‘Research Relevant Novel’ (RRN) terms. Extracting relevant sentences from multiple papers uses ‘Maximal Marginal Relevance’ (MMR) criteria containing RRN terms. In addition to optimized and summarized contents, this paperalso informs earlier and latest research developments, progress, and challenges and future scope in particular field of study through various research categories identified such as research methods/techniques/approaches used, comparisons with existing research and providing starting material for further innovation. [ABSTRACT FROM PUBLISHER]

In the ever growing literature on countering the cyber threat, the so-called JDL model of data fusion, well established in the information fusion community, has been applied to characterize the inner structure of problems within cyber defence and their mutual relationship. The overarching goal is to provide contributions to comprehensive cyber situational awareness by producing timely situation pictures. Cyber situational awareness, however, is prerequisite to taking appropriate actions, i.e. for “defence”. In this review paper, we provide an overview of what has been proposed in this context by various authors and collect basic insights published in the open literature. By doing so, we wish to provide an overview of the current discussion which reflects our own apprehension and prioritization. Moreover, we stress our opinion where relevant research questions are to be expected. [ABSTRACT FROM PUBLISHER]

A conceptual framework is proposed to examine perceived structural constraints of elephant conservation centre and its' effects on participation in visiting activity. A brief discussion on elephant conservation effort is discussed in the earlier part of this paper. The paper then examines some attributes to perceive structural constraints with some effects are examined for participation and overall satisfaction. This paper does not only assist in identifying reasons for not engaging in visiting an animal conservation but also gaining some ideas to overcome the constraints. [ABSTRACT FROM PUBLISHER]

Web based machine translation is now public ally available to Internet users. To address its effectiveness in assisting people in real translation task, this paper presents a controlled user study on how human choose and modify MT results during translating the paper titles. It reveals the translation quality of MT system in certain aspects through an analysis of the translator log. [ABSTRACT FROM PUBLISHER]

As cloud usage continues to increase, new issues with respect to managing and securing resources in the cloud are becoming more apparent. While some people may believe that security and privacy in the cloud can be addressed without the consumer considering the physical location and internal structure of the cloud, we show that this is clearly not the case. Furthermore, we describe a mechanism by which cloud consumers can inform cloud providers of their requirements in a manner that still allows the cloud to remain dynamic and flexible. Specifically, this paper explores the analogy between human migration in the real world and virtual machine migration in an IaaS cloud environment. It addresses issues such as jurisdictional control, zone evolution, migration, and instantiation based on an examination of these analogous real-world scenarios and their applicability to the cloud. [ABSTRACT FROM PUBLISHER]

Recently, paper based biosensors have been studied in the fields of biology, chemistry, pharmacology and medicine. The main advantages of paper based biosensors are low cost, biocompatibility, portability and environmental compatibility. The process of cell immobilization on paper is an important step for the development of disposable paper based biosensors with a whole-cell electrochemical electrode. The major problem of this process is poor cell viability on paper. In this work, we study the viability of HC04 human hepatocyte cells immobilized on filter papers coated with gelatin and fibronectin. HC04 cells were cultured on uncoated and coated papers in a 5% CO2 incubator for 6 and 24 hrs. Cell viability was then detected by tryphan blue and propidium iodide staining. The results show that % cell viability on gelatin and fibronectin coated paper are more than that on uncoated one. Therefore, the developed gelatin and fibronectin coated paper is promising for cell based biosensor applications. [ABSTRACT FROM PUBLISHER]

Higher education in engineering must cope with rapidly changing industrial environment. Activities of engineers in lifecycle product management projects are being integrated in increasingly sophisticated virtual systems where product model is built and applied for coordinated simulations and equipment control. Knowledge is being moved into product models for simple development and product information change. The authors of this paper tracked development of this engineering technology during the past decade and produced new and new evaluations for practical application of always recent virtual technology in higher education. In this paper, they report their recent results in concepts and approaches for higher education of engineers considering knowledge driven engineering technology. New challenges and possibilities are surveyed and the expected trend in characteristics and programs of higher education courses are outlined. Following this, concept is introduced for joining of higher engineering course programs to engineering systems. Finally, expected characteristics of course models and their implementations to cope with new demands are analyzed. [ABSTRACT FROM PUBLISHER]

Pedestrian detection is of much importance for its practical applications. This paper develops a novel pedestrian detection system which consists of three stages: motion region detection based on background modeling, feature extraction in the guidance of prior information, and map-based classification applying support vector machine (SVM) and Adaboost. First of all, an adaptive Gaussian Mixture Model is proposed to reduce the search for human targets in the background region. Secondly, the paper extracts a variant of HOG (Histograms of Oriented Gradients) and Haar-like feature to describe pedestrians, according to the prior information of human's relatively stable head-shoulder structure in various views. Thirdly, for the best performance of feature descriptors, this paper applies the combination of SVM (Support Vector Machine) and Adaboost, separately for HOG and Haar-like feature, as the final classifier. Experiment results validate the effectiveness of our method. [ABSTRACT FROM PUBLISHER]

Several concepts from traditional research on Artificial Intelligence (AI) need to be trained before they can be used. For example, when applied to a computer game, its AI framework has to “learn” how the game should be played. However, such trainings may not be trivial due to the often complex game world environments. This paper presents a novel training approach for game AI frameworks where, instead of manually a priori defining game playing rules at design time, training of the AI system takes place interactively while sample games are being played. Additionally this paper provides an example of modeling the game world so that game objects, such as Non-Playing Characters (NPCs), can be trained interactively. We also give an outlook to our ongoing research on the incorporation of the presented interactive training approach to a real-world game, namely an autonomous controller for the arcade Ms. Pac Man video game using Case-Based Planning. [ABSTRACT FROM PUBLISHER]

This paper is to discuss the B2C e-commerce companies' service quality evaluation from the entire service process. It puts three process as the first layer indicators. They are human-computer interaction, human-human interaction and purchase results. At the same time it divides into 17 factors as the second layer. This paper collects data from goods comments about Jing dong Mall and Dang dang. Combining the AHP method with those data, we can analyze the various factors of the index and their scores. Through comparative analysis, we can find business problems and provide appropriate recommendations. [ABSTRACT FROM PUBLISHER]

Human motion prediction is becoming more and more important issue in the filed of wearable robots or biorobotics. This paper provides an initial experimental result for human motion prediction. In detail, the prediction method for ternary choice among rock-paper-scissors is presented using temporal patterns of muscle activations (Electromyography, in short EMG) controlling hand motion of subject. Initial burst part of EMG is prior to the onset of actual movement by dozens to hundreds milliseconds. Using this property, the proposed method makes the ternary choice prediction among rock-paper-scissors as soon as 10% motion variation of any finger is detected. It is shown experimentally that the success rate of the proposed prediction method is over 95%. [ABSTRACT FROM PUBLISHER]

Agent-based systems are deployed in distributed data and control environments where resources usage are claimed to be more efficient. Researches have shown that intelligent agents offer excellent performance in distributed environments influenced by their autonomous or semi-autonomous actions with minimal human intervention. Assigned with roles, these agents are thus viewed as human-like societies that are capable of planning, coordinating, and executing tasks to achieve their goals. In a similar fashion, we model agents in our work based on the peculiarities of human society to achieve optimum performance in a dynamic multi-skills environment. Due to time and task constraints, agents are assigned with multiple roles and perform various other tasks. In this paper, we discuss a framework for dynamic task assignment and delegation in handling multi-task problems for a society of agents to achieve a common goal in allocated time. To test the framework, we adopt and animate the Final Examination Paper Preparation (FEPP) process in a multi-agent system that involves a number of faculty branches where multiple and dynamic task delegations are possible. [ABSTRACT FROM PUBLISHER]

This paper presents the first steps toward going from human data to formal controller design to experimental realization in the context of underactuated bipedal robots. Specifically, by studying experimental human walking data, we find that specific outputs of the human, i.e., functions of the kinematics, appear to be canonical to walking and are all characterized by a single function of time, termed a human walking function. Using the human outputs and walking function, we design a human-inspired controller that drives the output of the robot to the output of the human as represented by the walking function. The main result of the paper is an optimization problem that determines the parameters of this controller so as to guarantee stable underactuated walking that is as “close” as possible to human walking. This result is demonstrated through the simulation of a physical underactuated 2D bipedal robot, AMBER. Experimentally implementing this control on AMBER through “feed-forward” control, i.e., trajectory tracking, repeatedly results in 5–10 steps. [ABSTRACT FROM PUBLISHER]

Software is a digital form of solving problems we encounter in our daily life in whatever way ubiquitously. The understanding of products in terms of product life cycle management has been studied for about half of a century, and software as a special group of products may be applied. Further, software life cycle management has been undergoing studies within software engineering discipline for more than forty years. The question of how software life cycle management should be done is confronting us just as the same as forty years ago if not more urgently. This paper tries to address the question in a novel perspective in order to aid our understanding of software and to improve the productivity of creating software products. Based on the recent survey of state of the art software methodologies and technologies, this paper attempts to model software maturity by putting an emphasis on the importance of maintenance in software engineering. The intention here is to expose the misleading or unnecessary steps in separating the development from the maintenance of software products. It makes sense to view software as one life and one product in a holistic life cycle management approach. [ABSTRACT FROM PUBLISHER]

PET and CT image registration is an important tool of clinical diagnosis of diseases. For PET and CT images, a preprocessing algorithm of medical image registration is proposed in this paper. The algorithm process includes image normalization, CT image adaptive threshold adjustment and automatic extraction of tissues based on morphology, edge detection and statistical analysis theory, and improved PET image interpolation based on physical spacing of pixels. The experiment results indicate that the preprocessing methods proposed in this paper have a great effect on PET and CT image registration research because of the exclusion of redundant information and the improvement of the registration algorithm efficiency. [ABSTRACT FROM PUBLISHER]

Text Summarization is the process of identifying and extracting the most vital information in a document. It has been seen as an effective method for dealing with increasing amount of information on the Internet nowadays. In this paper, we present an application of Genetic Programming to the problem of Automatic Text Summarization. Genetic Programming was used to evolve the function that ranks the sentences in a document based on their importance. The summary was extracted by selecting the sentences that have the highest rankings. The experiment was conducted on a number of Vietnamese news documents. The result showed that the summaries created by Genetic Programming are better than those created by a number of statistic based methods and even by human (non-experts). [ABSTRACT FROM PUBLISHER]

3D human model is widely used in various fields, especially real human model. Along with the development of 3D scanning techniques, real human body data can be acquired by 3D scanner. But the number of point cloud data is huge. Human model data processing requires massive calculation although the computer hardware performance is better and better. In order to overcome the problem, this paper presents a rapid surface remodeling of human body based on scanned data. The results show that this method can quickly and effectively simplify large point cloud data and get satisfied real human models. This method can be applied to reconstruct a large number of human models and display their human figure in real time. [ABSTRACT FROM PUBLISHER]

In order to solve the problem that the information sharing and exchange lack uniform information exchange standards and information cannot be timely exchanged and shared, this paper proposes XML-based HR Information System under eterogeneous Enviornment. Simutaniously, considering the information chara1 cteristics of HR outsourcing and the related industry standards, this paper also designs the XML structure for HR outsourcing enterprises. The information management system not only realizes the standardization of information management and the quick-and-easy information change between heterogeneous systems, but also provides a reference to the design of other information exchange system in other related industrys. [ABSTRACT FROM PUBLISHER]

Detecting pedestrian accurately from natural scenes makes the important impact on intelligent video surveillance. In this paper, we combine motion information, human skin color information, human shape information and variation of ambient lighting to detect pedestrians for the application of automated video surveillance. The moving objects in the video sequence images are extracted using the multi-frame differencing method with adaptive ambient illumination changes. The adaptive ambient illumination human skin feature extraction algorithm extracts human skin color in different lighting changes in order to tackle the problem that skin color is susceptible to illumination. Improve Hough transform is used to automatically determine the size of human head in different scenes. The experimental results show that the method presented in this paper is feasible and is suitable for online applications in moving human detection in natural scenes. [ABSTRACT FROM PUBLISHER]

Over the last decade organisations have taken a keen interest in retaining tacit knowledge as it is a very important asset for organisations. This has led to the adoption of knowledge management practices that provide innovation in decision making, product and process efficiency. However as organisational knowledge is greatly dependant on the tacit knowledge that its employees possess, it is important to dwell upon some human resource functional strategies to encourage sharing of employees' knowledge and also enhance employee retention. The focus of this paper is predominantly on tacit knowledge sharing. Strategies that organisations can take to share, retain and reuse tacit knowledge have been recommended. The role of the human resource function, as a key enabler of tacit knowledge transfer, has been highlighted. Employee rewards management plays a key part in promoting, creating, sharing and preserving knowledge and its vitality has been discussed. The paper also elucidates some learning and development strategies that will fundamentally aid in tacit knowledge transfer. [ABSTRACT FROM PUBLISHER]

In this paper we present an original implementation of a compact saliency model for image sensors. The saliency model combines two features: motion and the central fixation bias. Its implementation was designed for low complexity: it relies on compact operators and requires merely about one frame memory. On-the-fly computation allows for low latency processing of "scanline" readout of image sensors. The results show that the proposed model is suitable for video-rate computation and exhibits better performance than the state-of-the-art model in predicting the human fixation. Moreover, a variant of the proposed model further reduce required memory by a factor of 256 while providing results similar to the state-of-the-art algorithm. [ABSTRACT FROM PUBLISHER]

The temporal annotation scheme Time ML was developed to support research in complex temporal question answering (QA). Given the complexity of temporal QA, most of the efforts have focused, so far, on extracting temporal information, which has been evaluated with corpus-based evaluation. However, the QA task represents a natural way to evaluate temporal information understanding, and creating question sets is less costly for humans than manually annotating temporal information, which is required to perform corpus-based evaluation. Additionally, QA performance better captures the understanding of important temporal information as compared to corpus-based evaluation where all information is equally important for scoring. This paper presents a temporal QA system that performs temporal reasoning. It can be used to answer temporal questions (factoid, list and yes/no), about any document annotated in Time ML. In the paper, we show how this system can be used to evaluate automated temporal information understanding. Our QA-based evaluation results suggest that (i) the available temporal annotations are not complete, and (ii) QA provides a less costly and more reliable way of evaluating temporal understanding systems. To favour replicability, we made the temporal QA system and the question set used in the evaluation available. [ABSTRACT FROM PUBLISHER]

This paper proposes a human interface device framework for interactive applications including educational contents in ubiquitous environments. Recently, mobile and portable devices such as iPad, iPhone and Android tablet PC have become common and popular. We should use these devices for providing learners with more attractive educational contents supporting various intuitive interfaces. Using the proposed framework, it becomes possible to easily develop such educational contents. Furthermore, the combined use of the framework with WebIB, which is a software development system for Web 3D contents, it also becomes possible to develop more attractive educational contents using 3D graphics that run on Web and Digital TV. To clarify the usefulness of the framework, this paper introduces interactive application examples including 3D educational contents available on Web and Digital TV actually developed using the proposed framework and WebIB. [ABSTRACT FROM PUBLISHER]

This paper proposes a general learning framework for robots to learn behaviors through imitation and interaction. A modified codebook based method is used for robots to segment and recognize new objects in the environment. Task related semantic information is learned by robots through the speech communication with humans. Dynamic Movement Primitive method is used to generate similar behaviors to complete similar but slightly different tasks. Experimental results are given to verify the effectiveness of this framework. [ABSTRACT FROM PUBLISHER]

This paper summarizes the design optimization of a parallel mechanism using on human hip joint power assisting. Manipulability Inclusive Principle (MIP) evaluation criterion for evaluating assisting mechanism's assisting feasibility and assisting effect is proposed. The design of parallel assisting mechanism and building kinematical Jacobian are discussed. Moreover, as an important part of this paper, in order to finding out a architecture, which can satisfy assisting feasibility and realize higher assisting efficiency, more assisting ability and better feature on assisting isotropy, design optimization MIP is shown in this paper. [ABSTRACT FROM PUBLISHER]

Product model enhances engineering work by the application of techniques such as modeling by features, contextual definition of engineering objects, application of active knowledge, and real time analysis of product modification consequence. These achievements are efficient in local product definition where small number of parts is considered. However, decision on a single product object in large structures is made difficult by high number of unorganized relationships and untraceable contextual chains. Simultaneous affect of several humans on a single decision considering consequences on many product objects can not be defined in current modeling systems. The authors recognized that an enhanced knowledge based product object definition is required with product wide decision support. They did researches in this area and introduce recent results in this paper. The aim is to give a better control of product model definition than model representation capability of the currently applied direct object parameter and relationship based control method can provide. In this paper, product information in current product lifecycle management systems is analyzed and main information connections of product model are identified. Following this, the authors introduce their new modeling method in order to contribute to the solution of the above problem. First of all, knowledge communication in the current and the proposed product definitions are explained. The main contribution of this paper includes new findings in requested influence based coordinated product definition process. [ABSTRACT FROM PUBLISHER]

In our previous work, we described a framework called i2Learning for a perpetual learning agent to be engaged in continuous learning to incrementally improve its problem solving performance over time. i2Learning offers an overarching framework that can accommodate various inconsistency-specific learning strategies. In this paper, we report our new results on how learning can be carried out through overcoming inheritance inconsistencies the agent encounters during its problem-solving episodes. Each learning episode causes the agent's knowledge to be refined or augmented so as to overcome the encountered inheritance inconsistency. This will in turn improve the agent's performance at tasks incrementally. The work in this paper is an integral part of the overall effort toward fully developing the i2Learning framework. [ABSTRACT FROM PUBLISHER]

The growing number of textual reports poses a great challenge for investigative analysis. However, text visualization has the potential to address this problem by automating the analysis of text reports, thus reducing workloads and providing new insights for crime analysts. We are developing a crime report visualization system for such investigative analysis. Our system leverages natural language processing and visualization techniques to enhance decision support. To measure its usefulness, we conducted a case study to compare the use of our system with a traditional paper-based approach to identify crime reports discussing the same crime. The crime analyst discovered 4 out of 5 crime reports correctly among 40 reports using either the paper-based or system-based approach. However, less time was spent on the tasks using our system compared to the paper-based approach. Our interface and visualization components such as the highlighting function were rated positively by the crime analyst. [ABSTRACT FROM PUBLISHER]

In this paper, a simple method to extract regions of interest (ROI) from images is proposed. In the field of image processing, intensity, color and orientation are commonly used features for saliency map generation in most visual attention model. However, texture feature can contribute to the guidance of attention in a bottom-up model. We consider texture contrast as a component of final saliency map. Hue, saturation, and value (HSV) color space is also adopted in this paper for its good capability of representing the colors of human perception and simplicity of computation. Moreover, binocular stereo image pair is adopted as source image. The result shows that the proposed saliency computational method can effectively detect salient region, and it is more suitable for environmental perception and cognition, object detection, and mobile robot navigation. [ABSTRACT FROM PUBLISHER]

The background subtraction is an important method to detect the moving objects, and effective background reconstruction is the key for the background subtraction. Based on the idea that the pixel average appearing with high frequency in an image series is the background points, the pixel intensity classification (PIC) algorithm can reconstruct background accurately. In this paper, a new background estimation method based on the PIC algorithm is proposed. Through normalization, quantitative statistic, quantization range extension of the pixels of the chosen image sequence is used to reconstruct the background. Based on the background reconstructed by the improved PIC algorithm, we build a moving object detection system with OpenCV. The experiments results show that the method proposed in this paper can reconstruct the background image quickly and can extract the moving objects from the video sequence successfully. [ABSTRACT FROM PUBLISHER]

This paper provides an overview of how Internet connected objects can lead to a social change towards energy efficiency in areas where people inhabit (cities, buildings or homes). For this aim it is proposed the use of social networks, like Twitter, as an interaction and communication channel between smart objects and human beings. The presented work demonstrates, by means of an experiment, how an augmented everyday object, i.e. a capsule-based coffee machine, may help to reduce the unnecessary consumed energy in electric appliances. The paper opens the discussion of the promising potential of combining people and future smart everyday objects teaming up to promote a more sustainable behaviour on the planet's behalf. [ABSTRACT FROM PUBLISHER]

With the rapid growth of cities, urban planners are facing with challenges including road congestion, population overburden and so on. Managing such big and complex cities requires better understanding of the urban blocks' property. Traditional ways are mostly based on manual survey, which cost much and take long time. In this paper, we present a method to analyze the urban blocks' property and activity patterns based on cell phone data, which is cheaper, faster. The result has been proved high accuracy. Real world cell phone data from Beijing is used in this paper. [ABSTRACT FROM PUBLISHER]

In this paper, we propose an approach for human activity categorizing based on the use of optical flow direction and magnitude features. The main contribution of this paper is the feature representation that mirrors the geometry of the human body and relationships between its moving regions when performing activities. The features are quantified using a quantization algorithm. We analyze the performance of two well-known classifiers: the Naïve Bayes and the SVM. The results show the effectiveness of our approach. [ABSTRACT FROM PUBLISHER]

This paper proposes a method for estimating the human performance of pedestrian detectability from in-vehicle camera images in order to warn a driver of the positions of pedestrians in an appropriate timing. By introducing features related to visual search and motion of the target, the proposed method estimates the detectability of pedestrians accurately. Support Vector Regression (SVR) is used to estimate the detectability. Here, SVR is trained using features calculated by the proposed method with the ground truth obtained through experiments with human subjects. From experiments using in-vehicle camera images, we confirmed that the proposed features were effective to estimate the detectability of pedestrians. [ABSTRACT FROM PUBLISHER]

This paper proposes a novel nonlinear manifold learning method for addressing the ill-posed problem of occluded human action analysis. As we know, a person can perform a broad variety of movements. To capture the multiplicity of a human action, this paper creates a low-dimensional manifold for capturing the intra-path and inter-path contexts of an event. Then, an action path matching scheme can be applied for seeking the best event path for linking the missed information between occluded persons. After that, a recovering scheme is proposed for repairing an occluded object to a complete one. Then, each action can be converted to a series of action primitives through posture analysis. Since occluded objects are handled, there will be many posture-symbol-converting errors. Instead of using a specific symbol, we code a posture using not only its best matched key posture but also its similarities among other key postures. Then, recognition of an action taken from occlude objects can be modeled as a matrix matching problem. With the matrix representation, different actions can be more robustly and effectively matched by comparing their Kullback-Leibler(KL) distances. [ABSTRACT FROM PUBLISHER]

Word of mouth represents, from historical times, a powerful mechanism employed within human societies for influencing the behavior of their members. Translated into the computational world, the same feedback mechanism preserves or even broadens its impact. This paper presents an intriguing perspective on using reputation systems: reputation is gained by complying with the norms and norms are modified by the agents with high reputation. The aim of the model proposed by this paper is to optimize content distribution within a system. The model achieves this goal by prioritizing the preferences of the highest reputed agents. The reputation of an agent is translated into the influence it gains in altering system norms. The computational reputation model proposed requires minimum resources being thus well suited for agents running on mobile devices. Being completely decentralized, the interaction architecture provided by the model offers a high degree of scalability. [ABSTRACT FROM PUBLISHER]

In this paper a cable-based system is presented for rehabilitation of the wrist movements. The proposed structure consists of one or two cables that allow the movement of abduction-adduction and flexion-extension with different limits of movement and speed. The development of this robotic device is justified by the large number of people with upper limb problems. It starts with a study of the basic movements of wrist joint and the structures actually in use. After, this paper presents a comparison between a mechanical and biomechanical system. The objective of this study is to evaluate the difference between these two models that are applied in a parallel robotic structure actuated by cables for rehabilitation of the human hand. Thus, this paper presents the results of theoretical and experimental forces for the biomechanical and mechanical system. Finally, an analysis concerning the difference between the systems is done. [ABSTRACT FROM PUBLISHER]

Automating the execution of workflows (or business processes) on computer resources has been the subject of much research. However, many workflow scenarios still require human involvement, which introduces additional authorization concerns. Role-Based Authorization Control (RBAC), under which the users are assigned to certain roles while the roles are associated with prescribed permissions, is a popular authorisation control scheme. When we allocate resources for workloads and plan system capacities, it is often assumed that when a task is allocated to a resource, the resource will accept the task and start the execution once the processor becomes available. However, the authorization policies impose further constraints on task executions, and therefore may incur performance penalty and affect both application- and system-oriented performance. This paper investigates the issue of allocating resources for running workflows under the role-based authorization control. The resource allocation strategies are developed in this paper for both human resources and computing resources. The allocation strategy for human resources takes into account the authorization constraints and establishes the optimization equation subject to the constraint of the budget available to hire human resources. Then the optimization equation is solved to obtain the number of human resources allocated to each authorization role. The allocation strategy for computing resources also takes into account authorization constraints, calculating not only the number of computing resources, but also the proportion of processing capacity in each resource allocated to serve the tasks assuming each role. The simulation experiments have been conducted to verify the effectiveness of the developed allocation strategies. The experimental results show that the allocation strategy developed in this paper outperforms the traditional allocation strategies, which do not consider authorization constraints, in terms of both average response time and resource utilization. [ABSTRACT FROM PUBLISHER]

This Human-Computer Interaction (HCI) is a field in which the developer makes a user friendly system. In this paper, a real-time Human-Computer Interaction based on the hand data glove and k-NN classifier for gesture recognition is proposed. HCI is becoming more and more natural and intuitive to be used. The important part of body that is hand is most frequently used as interaction in digital environment and thus complexity and flexibility of motion of hand is a research topic. To recognize hand gesture accurately and successfully data glove is used. Here, glove is used to capture current position and angle of hand and fingers, and further classify it using k-NN classifier. The gestures classified are clicking, dragging, rotating, pointing and ideal position. Recognizing these gestures relevant actions are taken, such as air writing and 3D sketching by tracking the path. This can be also used in the controlling of an image browser tool using data glove. The results show that glove used for interaction is better than normal static keyboard and mouse as the interaction process is more accurate and natural. Also it enhances the user's interaction and immersion feeling. [ABSTRACT FROM PUBLISHER]

Due to the development of World Wide Web technologies, people are living in the place flooding trillions of web pages in every moment. The amount of web size has been increasing dramatically. For this reason, it is getting more difficult to find relevant web documents corresponding to what users want to read. Classifying documents into predefined categories is one of the most important tasks in Natural Language Processing field. Over the years, many statistical and linguistical approaches have been applied to overcome traditional classification machine. However, it still remains in unsolved problem. There is a no perfect solution to machine understand human language yet. We have to consider every possibility for making machine think like human does. In this paper, we propose a method for classifying textural document using n-gram co-occurrence statistics which have a great possibility to find similarities between given documents. We also compare our proposed method with traditional method suggested by Keselj. This paper only covers simple approaches and still needs more sophisticated experiments. However, the performance using this method is better than the Keselj approach. [ABSTRACT FROM PUBLISHER]

This paper is one of parts for providing intelligent services. To do so, we focus on user intentions. Lots of researches for human intentions focus on human actions because actions are followed by intentions. So they treat human actions as human intentions. But sometimes there are differences between actions and the intentions. Abraham Maslow, a psychologist, presented the theory of human motivations[1]. He said that all human actions were based on their own needs. Therefore, we think that if we describe human needs and make some proper models to contain them, we can catch human intentions and make devices provide good services. That's the main motive of this paper. [ABSTRACT FROM PUBLISHER]

The future of tele-conferencing is towards multi-party 3D Tele-Immersion (TI) and TI environments that can support realistic inter-personal communications and virtual interaction among participants. In this paper, we address two important issues, pertinent to TI environments. The paper focuses on techniques for the real-time, 3D reconstruction of moving humans from multiple Kinect devices. The off-line generation of real-life 3D scenes from visual data, captured by non-professional users is also addressed. Experimental results are provided that demonstrate the efficiency of the methods, along with an example of mixing real with virtual in a shared space. [ABSTRACT FROM PUBLISHER]

This paper proposes a novel dimensional scaling bilateral control for mobile-hapto. The dimensional scaling bilateral control realizes force feedback between the master and the slave with different motion areas. By this system, an operator can manipulate velocity of the slave, and feel reaction force at the slave. For realizing this system, force and position responses of the master and the slave are transformed to a modal space. And force and position controllers are constructed in the modal space. In the conventional method, however, a precise bilateral controller is not achieved because the dynamics in the modal space is not considered. Therefore, in this paper, the dynamic behaviors in the modal space is described, and a decoupling control system with the disturbance observer in the modal space is realized by the proposed method. Finally, the validity of the proposal is verified by simulation and experimental results. [ABSTRACT FROM PUBLISHER]