Query: Sign Language Production using Neural Machine Translation and Generative Adversarial Networks

Relevant passages:
Pixel Recurrent Neural Networks <=SEP=> Modeling the distribution of natural images is a landmark problem in unsupervised learning. This task requires an image model that is at once expressive, tractable and scalable. We present a deep neural network that sequentially predicts the pixels in an image along the two spatial dimensions. Our method models the discrete probability of the raw pixel values and encodes the complete set of dependencies in the image. Architectural novelties include fast twodimensional recurrent layers and an effective use of residual connections in deep recurrent networks. We achieve log-likelihood scores on natural images that are considerably better than the previous state of the art. Our main results also provide benchmarks on the diverse ImageNet dataset. Samples generated from the model appear crisp, varied and globally coherent.

DRAW: A Recurrent Neural Network For Image Generation <=SEP=> This paper introduces the Deep Recurrent Attentive Writer (DRAW) neural network architecture for image generation. DRAW networks combine a novel spatial attention mechanism that mimics the foveation of the human eye, with a sequential variational auto-encoding framework that allows for the iterative construction of complex images. The system substantially improves on the state of the art for generative models on MNIST, and, when trained on the Street View House Numbers dataset, it generates images that cannot be distinguished from real data with the naked eye.

Realtime Multi-person 2D Pose Estimation Using Part Affinity Fields <=SEP=> We present an approach to efficiently detect the 2D pose of multiple people in an image. The approach uses a nonparametric representation, which we refer to as Part Affinity Fields (PAFs), to learn to associate body parts with individuals in the image. The architecture encodes global context, allowing a greedy bottom-up parsing step that maintains high accuracy while achieving realtime performance, irrespective of the number of people in the image. The architecture is designed to jointly learn part locations and their association via two branches of the same sequential prediction process. Our method placed first in the inaugural COCO 2016 keypoints challenge, and significantly exceeds the previous state-of-the-art result on the MPII Multi-Person benchmark, both in performance and efficiency.

Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks <=SEP=> 

Conditional Generative Adversarial Nets <=SEP=> Generative Adversarial Nets [8] were recently introduced as a novel way to train generative models. In this work we introduce the conditional version of generative adversarial nets, which can be constructed by simply feeding the data, y, we wish to condition on to both the generator and discriminator. We show that this model can generate MNIST digits conditioned on class labels. We also illustrate how this model could be used to learn a multi-modal model, and provide preliminary examples of an application to image tagging in which we demonstrate how this approach can generate descriptive tags which are not part of training labels.

Efficiency of low power audio amplifiers and loudspeakers <=SEP=> In this paper we look at the load presented to audio amplifiers by real transducers. We consider the power losses in Class-AB and Class-D amplifier topologies, and determine that in order to predict efficiency it is necessary to consider the amplifier/transducer combination. The ability of the class-D amplifier to recycle quadrature load current offers new ways to improve efficiency. INTRODUCTION Class-D amplifiers are beginning to become viable alternatives to the Class-AB amplifier because of the reducing cost of suitable devices. There is particular interest in developing them for low power applications where their intrinsic efficiency advantages are important. The operation of Class-D amplifiers is very different to Class-AB amplifiers and this has implications for other components in the audio chain. Conventionally the performance of audio amplifiers is considered using a pure resistive load of four or eight ohms. The origin of this lies in the nominal impedance given to electro-magnetic loudspeakers. The true impedance of an electro-magnetic loudspeaker will vary over the operating frequency range, but the variability between individual real transducers makes the definition of a more realistic ‘bench-mark’ load impractical. Other audio transducers also have a complex impedance. Transducers which utilise piezo electric elements have a input impedance that is highly reactive. The load presented to the amplifier is almost entirely capacitive. The power output and efficiency of an amplifier are dependent load impedance and so the resistive load performance may not resemble to the operation of the amplifier in real situations. In this paper we will look at the true load presented to amplifiers by the transducer and derive a more accurate measure of overall efficiency. GENERAL AMPLIFIER EFFICIENCY The electrical efficiency of an amplifier is defined as the ratio of the power developed in the load to the power drawn from the DC supply. Using simple linear analysis we can determine the efficiency of amplifier output stages and the dependence of the efficiency on load parameters. In this section the following symbols are used; Vo Output voltage Vs Supply rail voltage RL Load resistance Ibias Class AB quiescent bias current φ Load phase angle Zload Load impedance L Class D filter inductance Rin Resistance of filter inductor RDson ‘On’ state resistance of switching devices fs Class D Switching frequency Class-AB resistive case A simple Class-AB output stage is shown in figure 1. A complementary pair of output devices operate over their linear region to amplify the signal. When the devices are operated in the linear region there will be current flowing through them whilst there is a voltage across them, this will give rise to power dissipation, and hence reduce efficiency. The devices also need a quiescent bias to reduce crossover distortion as one device takes over from the other. Load

Impact of a contemplative end-of-life training program: being with dying. <=SEP=> OBJECTIVE
Health care professionals report a lack of skills in the psychosocial and spiritual aspects of caring for dying people and high levels of moral distress, grief, and burnout. To address these concerns, the "Being with Dying: Professional Training Program in Contemplative End-of-Life Care" (BWD) was created. The premise of BWD, which is based on the development of mindfulness and receptive attention through contemplative practice, is that cultivating stability of mind and emotions enables clinicians to respond to others and themselves with compassion. This article describes the impact of BWD on the participants.


METHODS
Ninety-five BWD participants completed an anonymous online survey; 40 completed a confidential open-ended telephone interview.


RESULTS
Four main themes-the power of presence, cultivating balanced compassion, recognizing grief, and the importance of self-care-emerged in the interviews and were supported in the survey data. The interviewees considered BWD's contemplative and reflective practices meaningful, useful, and valuable and reported that BWD provided skills, attitudes, behaviors, and tools to change how they worked with the dying and bereaved.


SIGNIFICANCE OF RESULTS
The quality of presence has the potential to transform the care of dying people and the caregivers themselves. Cultivating this quality within themselves and others allows clinicians to explore alternatives to exclusively intellectual, procedural, and task-oriented approaches when caring for dying people. BWD provides a rare opportunity to engage in practices and methods that cultivate the stability of mind and emotions that may facilitate compassionate care of dying patients, families, and caregivers.

The influence of geometrical deviations of electrical machine systems on the signal quality of the variable reluctance resolver <=SEP=> Variable reluctance resolvers are needed to regulate electrical machines with inverter control. Due to several issues, e.g. discrete windings in the stator and geometric tolerances in the assembly of the electrical machine, the rotors angular position cannot be acquired properly. The subject of this paper is a variable reluctance resolver model to investigate manufacturing induced geometrical tolerances of the electrical machine in means of rotor position. For this purpose, a block diagram of a stator segment is built, connecting 24 segments to one stator core using PLECS. The rotor can be set freely in shape and position. By varying a permeance block the rotation, i.e. the position dependent airgap, is mirrored. The proposed model allows a sensitivity analysis of the sensor signal according to geometrical changes and the absolute position in the electrical machine system. To evaluate the investigations, the results are verified by measurements on a sensor test bench. The simulation results show a similar behavior as the measurement. Although the values differ by a factor of five, this absolute difference is discussed by means of neglected boundary conditions.

A-PNR: Automatic Plate Number Recognition <=SEP=> Automatic Plate Number Recognition (APNR) has important applications in traffic surveillance, toll booth, protected parking lot, No parking zone, etc. It is a challenging problem, especially when the license plates have varying sizes, the number of lines, fonts, background diversity etc. This work aims to address APNR using deep learning method for real-time traffic images. We first extract license plate candidates from each frame using edge information and geometrical properties, ensuring high recall using one class SVM. The verified candidates are used for NP recognition purpose along with a spatial transformer network (STN) for character recognition. Our system is evaluated on several traffic images with vehicles having different license plate formats in terms of tilt, distances, colors, illumination, character size, thickness etc. Also, the background was very challenging. Results demonstrate robustness to such variations and impressive performance in both the localization and recognition.

Clinical practice guidelines for diagnosis of autism spectrum disorder in adults and children in the UK: a narrative review <=SEP=> BACKGROUND
Research suggests that diagnostic procedures for Autism Spectrum Disorder are not consistent across practice and that diagnostic rates can be affected by contextual and social drivers. The purpose of this review was to consider how the content of clinical practice guidelines shapes diagnoses of Autism Spectrum Disorder in the UK; and investigate where, within those guidelines, social factors and influences are considered.


METHODS
We electronically searched multiple databases (NICE Evidence Base; TRIP; Social Policy and Practice; US National Guidelines Clearinghouse; HMIC; The Cochrane Library; Embase; Global health; Ovid; PsychARTICLES; PsychINFO) and relevant web sources (government, professional and regional NHS websites) for clinical practice guidelines. We extracted details of key diagnostic elements such as assessment process and diagnostic tools. A qualitative narrative analysis was conducted to identify social factors and influences.


RESULTS
Twenty-one documents were found and analysed. Guidelines varied in recommendations for use of diagnostic tools and assessment procedures. Although multidisciplinary assessment was identified as the 'ideal' assessment, some guidelines suggested in practice one experienced healthcare professional was sufficient. Social factors in operational, interactional and contextual areas added complexity to guidelines but there were few concrete recommendations as to how these factors should be operationalized for best diagnostic outcomes.


CONCLUSION
Although individual guidelines appeared to present a coherent and systematic assessment process, they varied enough in their recommendations to make the choices available to healthcare professionals particularly complex and confusing. We recommend a more explicit acknowledgement of social factors in clinical practice guidelines with advice about how they should be managed and operationalised to enable more consistency of practice and transparency for those coming for diagnosis.

Navigation of an omni-directional mobile robot with active caster wheels <=SEP=> This work deals with navigation of an omni-directional mobile robot with active caster wheels. Initially, the posture of the omni-directional mobile robot is calculated by using the odometry information. Next, the position accuracy of the mobile robot is measured through comparison of the odometry information and the external sensor measurement. Finally, for successful navigation of the mobile robot, a motion planning algorithm that employs kinematic redundancy resolution method is proposed. Through experiments for multiple obstacles and multiple moving obstacles, the feasibility of the proposed navigation algorithm was verified.

Examining a hate speech corpus for hate speech detection and popularity prediction <=SEP=> As research on hate speech becomes more and more relevant every day, most of it is still focused on hate speech detection. By attempting to replicate a hate speech detection experiment performed on an existing Twitter corpus annotated for hate speech, we highlight some issues that arise from doing research in the field of hate speech, which is essentially still in its infancy. We take a critical look at the training corpus in order to understand its biases, while also using it to venture beyond hate speech detection and investigate whether it can be used to shed light on other facets of research, such as popularity of hate tweets.

Process integration of a 27nm, 16Gb Cu ReRAM <=SEP=> A 27nm 16Gb Cu based NV Re-RAM chip has been demonstrated. Novel process introduction to enable this technology include a Damascene Cell, Line-SAC Digit Lines filled with Cu, exhumed-silicided array contacts, raised epitaxial arrays, and high-drive buried access devices.

An approach for selecting seed URLs of focused crawler based on user-interest ontology <=SEP=> Seed URLs selection for focused Web crawler intends to guide related and valuable information that meets a user’s personal information requirement and provide more effective information retrieval. In this paper, we propose a seed URLs selection approach based on user-interest ontology. In order to enrich semantic query, we first intend to apply Formal Concept Analysis to construct user-interest concept lattice with user log profile. By using concept lattice merger, we construct the user-interest ontology which can describe the implicit concepts and relationships between them more appropriately for semantic representation eed URLs ormal concept analysis ser-interest ontology ipartite graph eb crawler and query match. On the other hand, we make full use of the user-interest ontology for extracting the user interest topic area and expanding user queries to receive the most related pages as seed URLs, which is an entrance of the focused crawler. In particular, we focus on how to refine the user topic area using the bipartite directed graph. The experiment proves that the user-interest ontology can be achieved effectively by merging concept lattices and that our proposed approach can select high quality seed URLs collection and improve the average precision of focused Web crawler.

A Comparison of 10 Sampling Algorithms for Configurable Systems <=SEP=> Almost every software system provides configuration options to tailor the system to the target platform and application scenario. Often, this configurability renders the analysis of every individual system configuration infeasible. To address this problem, researchers have proposed a diverse set of sampling algorithms. We present a comparative study of 10 state-of-the-art sampling algorithms regarding their fault-detection capability and size of sample sets. The former is important to improve software quality and the latter to reduce the time of analysis. In a nutshell, we found that sampling algorithms with larger sample sets are able to detect higher numbers of faults, but simple algorithms with small sample sets, such as most-enabled-disabled, are the most efficient in most contexts. Furthermore, we observed that the limiting assumptions made in previous work influence the number of detected faults, the size of sample sets, and the ranking of algorithms. Finally, we have identified a number of technical challenges when trying to avoid the limiting assumptions, which questions the practicality of certain sampling algorithms.

Gaussian Process Regression Networks <=SEP=> We introduce a new regression framework, Gaussian process regression networks (GPRN), which combines the structural properties of Bayesian neural networks with the nonparametric flexibility of Gaussian processes. GPRN accommodates input (predictor) dependent signal and noise correlations between multiple output (response) variables, input dependent length-scales and amplitudes, and heavy-tailed predictive distributions. We derive both elliptical slice sampling and variational Bayes inference procedures for GPRN. We apply GPRN as a multiple output regression and multivariate volatility model, demonstrating substantially improved performance over eight popular multiple output (multi-task) Gaussian process models and three multivariate volatility models on real datasets, including a 1000 dimensional gene expression dataset.

Microplastics in the marine environment. <=SEP=> This review discusses the mechanisms of generation and potential impacts of microplastics in the ocean environment. Weathering degradation of plastics on the beaches results in their surface embrittlement and microcracking, yielding microparticles that are carried into water by wind or wave action. Unlike inorganic fines present in sea water, microplastics concentrate persistent organic pollutants (POPs) by partition. The relevant distribution coefficients for common POPs are several orders of magnitude in favour of the plastic medium. Consequently, the microparticles laden with high levels of POPs can be ingested by marine biota. Bioavailability and the efficiency of transfer of the ingested POPs across trophic levels are not known and the potential damage posed by these to the marine ecosystem has yet to be quantified and modelled. Given the increasing levels of plastic pollution of the oceans it is important to better understand the impact of microplastics in the ocean food web.

Machine Learning and Social Robotics for Detecting Early Signs of Dementia <=SEP=> This paper presents the EACare project, an ambitious multidisciplinary collaboration with the aim to develop an embodied system, capable of carrying out neuropsychological tests to detect early signs of dementia, e.g., due to Alzheimer’s disease. The system will use methods from Machine Learning and Social Robotics, and be trained with examples of recorded clinician-patient interactions. The interaction will be developed using a participatory design approach. We describe the scope and method of the project, and report on a first Wizard of Oz prototype.

The basic building blocks and evolution of CRISPR-CAS systems. <=SEP=> CRISPR (clustered regularly interspaced short palindromic repeats)-Cas (CRISPR-associated) is an adaptive immunity system in bacteria and archaea that functions via a distinct self/non-self recognition mechanism that involves unique spacers homologous with viral or plasmid DNA and integrated into the CRISPR loci. Most of the Cas proteins evolve under relaxed purifying selection and some underwent dramatic structural rearrangements during evolution. In many cases, CRISPR-Cas system components are replaced either by homologous or by analogous proteins or domains in some bacterial and archaeal lineages. However, recent advances in comparative sequence analysis, structural studies and experimental data suggest that, despite this remarkable evolutionary plasticity, all CRISPR-Cas systems employ the same architectural and functional principles, and given the conservation of the principal building blocks, share a common ancestry. We review recent advances in the understanding of the evolution and organization of CRISPR-Cas systems. Among other developments, we describe for the first time a group of archaeal cas1 gene homologues that are not associated with CRISPR-Cas loci and are predicted to be involved in functions other than adaptive immunity.

An algorithmic approach to multimodality midfacial rejuvenation using a new classification system for midfacial aging. <=SEP=> Midfacial aging is the result of the complex interplay between the osseous skeleton, facial retaining ligaments, soft tissues envelope, facial fat compartments, and the overlying skin elasticity. As a result of the many anatomic components involved in midfacial aging, the authors proposed a classification system based on distinct anatomic factors to direct surgical treatment. Evidence based data suggest that midface rejuvenation often requires a multimodality approach to obtain desired results, especially in patients with more advanced aging and poor tissue elasticity, or those with hypoplastic midfacial skeletal structure.

A Robust Mid-Level Representation for Harmonic Content in Music Signals <=SEP=> When considering the problem of audio-to-audio matching, determining musical similarity using low-level features such as Fourier transforms and MFCCs is an extremely difficult task, as there is little semantic information available. Full semantic transcription of audio is an unreliable and imperfect task in the best case, an unsolved problem in the worst. To this end we propose a robust mid-level representation that incorporates both harmonic and rhythmic information, without attempting full transcription. We describe a process for creating this representation automatically, directly from multi-timbral and polyphonic music signals, with an emphasis on popular music. We also offer various evaluations of our techniques. Moreso than most approaches working from raw audio, we incorporate musical knowledge into our assumptions, our models, and our processes. Our hope is that by utilizing this notion of a musically-motivated mid-level representation we may help bridge the gap between symbolic and audio research.

Roman-txt: forms and functions of roman urdu texting <=SEP=> In this paper, we present a user study conducted on students of a local university in Pakistan and collected a corpus of Roman Urdu text messages. We were interested in forms and functions of Roman Urdu text messages. To this end, we collected a mobile phone usage dataset. The data consists of 116 users and 346, 455 text messages. Roman Urdu text, is the most widely adopted style of writing text messages in Pakistan. Our user study leads to interesting results, for instance, we were able to quantitatively show that a number of words are written using more than one spelling; most participants of our study were not comfortable in English and hence they write their text messages in Roman Urdu; and the choice of language adopted by the participants sometimes varies according to who the message is being sent. Moreover we found that many young students send text messages(SMS) of intimate nature.

OCR and RFID enabled vehicle identification and parking allocation system <=SEP=> The available parking management systems require human efforts for recording entries of coming and leaving vehicles from parking in sheets. For huge parking it is difficult to keep track of the information. Use of Radio Frequency Identification known as RFID technology reduces human efforts and Optical Character Recognition known as OCR, enabled system will provide an automated system for parking management. And also it will provide the control over the access of parking space by the use of boom barriers. For huge parking it will be an effective system. Parking can be a commercial one or can be a Very Important Person (VIP) parking. Depending on the usage system can be used. Vehicle cannot be parked in parking if it is not registered. OCR acts as a solution for vehicles which are not registered. To keep track of the happenings in parking cameras are used. Places where automated systems are required, the proposed system is an answer. System combines the two strong technologies RFID and OCR.

The REVIVE (REal Women's VIews of Treatment Options for Menopausal Vaginal ChangEs) survey in Europe: Country-specific comparisons of postmenopausal women's perceptions, experiences and needs. <=SEP=> OBJECTIVES
To achieve a better comprehension of the variability of perceptions, experiences and needs in terms of sexual and vaginal health in postmenopausal women (PMW) from four different European countries.


METHODS
An internet-based survey was conducted in Italy, Germany, Spain and the United Kingdom with a total surveyed population of 3768 PMW aged between 45 and 75 years.


RESULTS
The UK sample was significantly older, with almost a quarter of participants over 65 years of age, and had the highest proportion of women experiencing recent vulvar and vaginal atrophy (52.8%). The majority of Italian and Spanish participants were receiving VVA treatment, whereas in the UK only 28% of PMW were on medication. The most common menopausal symptom was vaginal/vulvar dryness, with almost 80% of participants reporting it in all the countries except the UK (48%). On the other hand, vaginal/vulvar irritation was more frequently reported in the UK (41%). The percentage of participants with a partner was lower in the UK (71%), as was the monthly rate of sexual activity (49%). In the UK, the proportion of participants who had seen a healthcare professional for gynaecological reasons in the last year was lower than in other countries (27% vs. ≥50%), as was the proportion who has discussed their VVA symptoms with them (45% vs. ∼67%). In this sense, UK PMW waited for a longer before asking for help (especially for pain with intercourse and dryness). The main issues relating to VVA treatment difficulties expressed by participants were administration route in the UK, efficacy in Germany, and side-effects in Italy.


CONCLUSIONS
Although all European women shared the same expectation of improving the quality of their sex lives, the opportunity for that varied among different countries in relation to the healthcare system and to the effective communication achieved with healthcare professionals when managing VVA.

Do burnout and work engagement predict depressive symptoms and life satisfaction? A three-wave seven-year prospective study. <=SEP=> BACKGROUND
Burnout and work engagement have been viewed as opposite, yet distinct states of employee well-being. We investigated whether work-related indicators of well-being (i.e. burnout and work engagement) spill-over and generalize to context-free well-being (i.e. depressive symptoms and life satisfaction). More specifically, we examined the causal direction: does burnout/work engagement lead to depressive symptoms/life satisfaction, or the other way around?


METHODS
Three surveys were conducted. In 2003, 71% of all Finnish dentists were surveyed (n=3255), and the response rate of the 3-year follow-up was 84% (n=2555). The second follow-up was conducted four years later with a response rate of 86% (n=1964). Structural equation modeling was used to investigate the cross-lagged associations between the study variables across time.


RESULTS
Burnout predicted depressive symptoms and life dissatisfaction from T1 to T2 and from T2 to T3. Conversely, work engagement had a negative effect on depressive symptoms and a positive effect on life satisfaction, both from T1 to T2 and from T2 to T3, even after adjusting for the impact of burnout at every occasion.


LIMITATIONS
The study was conducted among one occupational group, which limits its generalizability.


CONCLUSIONS
Work-related well-being predicts general wellbeing in the long-term. For example, burnout predicts depressive symptoms and not vice versa. In addition, burnout and work engagement are not direct opposites. Instead, both have unique, incremental impacts on life satisfaction and depressive symptoms.

Handwriting difficulties in primary school children: a search for underlying mechanisms. <=SEP=> OBJECTIVE
This study investigated the contribution of perceptual-motor dysfunction and cognitive planning problems to the quality or speed of handwriting in children with handwriting problems (HWP).


METHOD
Twenty-nine children with HWP and 20 classroom peers attending regular schools (grade 2 and grade 3) were tested with regard to visual perception, visual-motor integration, fine motor coordination, and cognitive planning abilities.


RESULTS
The HWP group scored significantly lower on visual perception, visual-motor integration, fine motor coordination, and cognitive planning in comparison with classroom controls. Regression analyses showed that visual-motor integration was the only significant predictor for quality of handwriting in the HWP group, whereas fine motor coordination (i.e., unimanual dexterity) was the only significant predictor of quality of handwriting in the control group.


CONCLUSIONS
Results suggest that two different mechanisms underlie the quality of handwriting in children with and without handwriting problems. Poor quality of handwriting of children with HWP seems particularly related to a deficiency in visual-motor integration.

INFORMATION TECHNOLOGY AND ORGANIZATIONAL CHANGE : CAUSAL STRUCTURE IN THEORY AND <=SEP=> JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org. This article concerns theories about why and how information technology affects organizational life. Good theory guides research, which, when applied, increases the likelihood that information technology will be employed with desirable consequences for users, organizations, and other interested parties. But what is a good theory? Theories are often evaluated in terms of their content-the specific concepts used and the human values served. This article examines theories in terms of their structures-theorists' assumptions about the nature and direction of causal influence. Three dimensions of causal structure are considered-causal agency, logical structure, and level of analysis. Causal agency refers to beliefs about the nature of causality: whether external forces cause change, whether people act purposefully to accomplish intended objectives, or whether changes emerge unpredictably from the interaction of people and events. Logical structure refers to the temporal aspect of theory-static versus dynamic-and to the logical relationships between the "causes" and the outcomes. Level of analysis refers to the entities about which the theory poses concepts and relationships-individuals, groups, organizations, and society. While there are many possible structures for good theory about the role of information technology in organizational change, only a few of these structures can be seen in current theorizing. Increased awareness of the options, open discussion of their advantages and disadvantages , and explicit characterization of future theoretical statements in terms of the dimensions and categories discussed here should, we believe, promote the development of better theory.

Mechanical design of a gravity-balancing wearable exoskeleton for the motion enhancement of human upper limb <=SEP=> Powered exoskeletons can provide motion enhancement for both healthy and physically challenged people. Upper limb exoskeletons are required to have multiple degrees-of-freedom and can still produce sufficient force to augment the upper limb motion. The design using serial mechanisms usually results in a complicated and bulky exoskeleton that prevents itself from being wearable. This paper presents a new exoskeleton design aimed to achieve compactness and wearability. We consider a shoulder exoskeleton that consists of a parallel spherical mechanism with two slider crank mechanisms. The actuators can be placed on a stationary platform and attached closely to human body. Thus a better inertia property can be obtained while maintaining lightweight. Through the use of a gravity-balancing mechanism, the required actuator power becomes smaller and with better efficiency. A static model is developed to analyze and optimize the exoskeleton. Through illustrations of a prototype, the exoskeleton is shown to be wearable and can provide adequate motion enhancement of a human's upper limb.

A Virtual Feedback Assistance System for Remote Operation of a 3DOF Micromanipulator in Micro-Nanorobotic Manipulation <=SEP=> Manipulation in micro or nanoscale with robotic manipulators under observation of electron microscopes is a widely used strategy for fabrication of nanodevices and nanoscale material property characterization. These types of manipulation systems can handle the relatively larger scale of objects. However, the complexity of manipulation increases highly for 3D manipulation. Since the manipulation system consists of multiple components including manipulator, microscope, and also some end-effector tools, a proper offline visualization of the system is necessary for operation. Therefore, we propose a web-based virtual interface between the user and the actual manipulator operated under digital microscope initially. It gives the operator 3D positional feedback from the virtual model by mapping data read during remote operation. The same interface is used for remote operation of the manipulator within the SEM chamber and a manipulation task is performed.

Dependence on computer games by adolescents. <=SEP=> As computer game playing is a popular activity among adolescents, a questionnaire study was undertaken with 387 adolescents (12-16 years of age) to establish their "dependence" using a scale adapted from the DSM-III-R criteria for pathological gambling. Analysis indicated that one in five adolescents were currently "dependent" upon computer games. Boys played significantly more regularly than girls and were more likely to be classified as "dependent." The earlier children began playing computer games it appeared the more likely they were to be playing at "dependent" levels. These and other results are discussed in relation to research on other gaming dependencies.