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"abstract": "Microservices is an architectural style that provides several benefits to develop applications as small, independent, and modular services. Building Microservices Architecture (MSA)-based applications is immensely supported by using software testing fundamentals. With the increasing interest in the development of MSA-based applications, it is important to systematically identify, analyze, and classify the publication trends, research themes, approaches, tools, and challenges in the context of testing MSA-based applications. The search yielded 2,481 articles, and 33 articles were finally selected as the primary studies with snowballing. The key findings are that (i) 5 research themes characterize testing approaches in MSA-based applications; (ii) integration and unit testing are the most popular testing approaches; and (iii) addressing the challenges in automated and inter-communication testing is gaining the interest of the community. Additionally, it emerges that there is a lack of dedicated tools to support testing for MSA-based applications, and the reasons and solutions behind the challenges in testing MSA-based applications need to be further explored.",
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"abstract": "This work introduces a novel surface registration method based on foliation. A foliation decomposes the surface into a family of closed loops, such that the decomposition has local tensor product structure. By projecting each loop to a point, the surface is collapsed into a graph. Two homeomorphic surfaces with consistent foliations can be registered by first matching their foliation graphs, then matching the corresponding leaves. This foliation based method is capable of handling surfaces with complicated topologies and large non-isometric deformations, rigorous with solid theoretic foundation, easy to implement, robust to compute. The result mapping is diffeomorphic. Our experimental results show the efficiency and efficacy of the proposed method.",
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"abstract": "An altered sleep pattern is often one of the general symptoms experienced by people with dementia. The quantity and quality of sleep may be a reflection of their dementia condition and affect the quality of life for people with dementia. In this paper we present our research in using sensor based technology for a telecare service to monitor daily activities over a period of three months for one healthy elderly client and one client with early dementia using assistive technology. We analyze their sleep patterns, propose a set of measures to assess the quantity and quality of sleep, and visualize the sleep patterns for a telecare service provider and carers to support users with dementia. Results show that people with early dementia have more alternations of sleep-wake cycles than healthy elderly people, and assistive technology can provide objective and ubiquitous monitoring of sleep patterns for health care purposes.",
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"content": "An altered sleep pattern is often one of the general symptoms experienced by people with dementia. The quantity and quality of sleep may be a reflection of their dementia condition and affect the quality of life for people with dementia. In this paper we present our research in using sensor based technology for a telecare service to monitor daily activities over a period of three months for one healthy elderly client and one client with early dementia using assistive technology. We analyze their sleep patterns, propose a set of measures to assess the quantity and quality of sleep, and visualize the sleep patterns for a telecare service provider and carers to support users with dementia. Results show that people with early dementia have more alternations of sleep-wake cycles than healthy elderly people, and assistive technology can provide objective and ubiquitous monitoring of sleep patterns for health care purposes.",
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"title": "Participatory design-based requirements elicitation involving people living with dementia towards a home-based platform to monitor emotional wellbeing",
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"abstract": "We are living in an ageing population with an escalation in chronic illnesses including dementia and other age related diseases. People living with dementia often continue to live at home and are supported by caregivers and next of kin. It is often important to monitor the wellbeing of people living with dementia in order to measure their level of independence and to provide proper support at the time of need as well as supporting their quality of life. Some researchers have focused on monitoring physical wellbeing and activities of daily living (ADL). However, there has been a paucity of research focussed on monitoring mood, affect and the emotional wellbeing of people living with dementia, despite these people experiencing frustration, agitation, depression and social isolation to name but a few known effects. As a result, the SenseCare project aims to build an affective computing platform that uses sensors placed in the home environment to monitor moods, affect and the emotional wellbeing of people living with dementia. This platform is being iteratively designed and will likely use plug-n-play sensors such as passive infrared, wearables and camera technologies to infer emotions from facial expressions, voice intonations and physical behaviour and other modalities. However, it is important to interact iteratively with people living with dementia and their caregivers in order to understand their profound needs. In this study, we report on two focus groups that were conducted to elicit user stories and eventual requirements for the SenseCare platform. Since participatory design involving people living with dementia could bring about unique challenges, we adopted a dyad approach where a caregiver and the person living with dementia participate together in the focus group. This ensures that their needs are fully represented and that consent is fully transparent. In this paper, we report the personal stories elicited during these discussions which will ultimately inform the implementation of the SenseCare platform.",
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"content": "We are living in an ageing population with an escalation in chronic illnesses including dementia and other age related diseases. People living with dementia often continue to live at home and are supported by caregivers and next of kin. It is often important to monitor the wellbeing of people living with dementia in order to measure their level of independence and to provide proper support at the time of need as well as supporting their quality of life. Some researchers have focused on monitoring physical wellbeing and activities of daily living (ADL). However, there has been a paucity of research focussed on monitoring mood, affect and the emotional wellbeing of people living with dementia, despite these people experiencing frustration, agitation, depression and social isolation to name but a few known effects. As a result, the SenseCare project aims to build an affective computing platform that uses sensors placed in the home environment to monitor moods, affect and the emotional wellbeing of people living with dementia. This platform is being iteratively designed and will likely use plug-n-play sensors such as passive infrared, wearables and camera technologies to infer emotions from facial expressions, voice intonations and physical behaviour and other modalities. However, it is important to interact iteratively with people living with dementia and their caregivers in order to understand their profound needs. In this study, we report on two focus groups that were conducted to elicit user stories and eventual requirements for the SenseCare platform. Since participatory design involving people living with dementia could bring about unique challenges, we adopted a dyad approach where a caregiver and the person living with dementia participate together in the focus group. This ensures that their needs are fully represented and that consent is fully transparent. In this paper, we report the personal stories elicited during these discussions which will ultimately inform the implementation of the SenseCare platform.",
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"normalizedAbstract": "We are living in an ageing population with an escalation in chronic illnesses including dementia and other age related diseases. People living with dementia often continue to live at home and are supported by caregivers and next of kin. It is often important to monitor the wellbeing of people living with dementia in order to measure their level of independence and to provide proper support at the time of need as well as supporting their quality of life. Some researchers have focused on monitoring physical wellbeing and activities of daily living (ADL). However, there has been a paucity of research focussed on monitoring mood, affect and the emotional wellbeing of people living with dementia, despite these people experiencing frustration, agitation, depression and social isolation to name but a few known effects. As a result, the SenseCare project aims to build an affective computing platform that uses sensors placed in the home environment to monitor moods, affect and the emotional wellbeing of people living with dementia. This platform is being iteratively designed and will likely use plug-n-play sensors such as passive infrared, wearables and camera technologies to infer emotions from facial expressions, voice intonations and physical behaviour and other modalities. However, it is important to interact iteratively with people living with dementia and their caregivers in order to understand their profound needs. In this study, we report on two focus groups that were conducted to elicit user stories and eventual requirements for the SenseCare platform. Since participatory design involving people living with dementia could bring about unique challenges, we adopted a dyad approach where a caregiver and the person living with dementia participate together in the focus group. This ensures that their needs are fully represented and that consent is fully transparent. In this paper, we report the personal stories elicited during these discussions which will ultimately inform the implementation of the SenseCare platform.",
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"abstract": "The fruitful adoption of technology is winding up progressively critical to practical autonomy and independence of elderly people with dementia. A superior comprehension of the technological boundaries and the necessities of cognitively impaired individuals will help the researchers to yield more suitable interventions and will prompt the avoidance of institutionalisation. The purpose of this study is to perceive those technological barriers and needs of people suffering from dementia. A methodology based on a combination of guided questionnaires and experiments with two technological devices, tablet and virtual reality head-mounted display (VR HMD), was applied. Data were collected through individual structured interviews that occurred in a care centre in Athens. Their unfamiliarity with the technology might be the major factor that prevents its utilisation. The positive results of the technological experiment suggest that the technology adoption could be feasible once the benefits are known.",
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"abstract": "Without a cure for dementia, researchers are focusing on reminiscence therapy, which effectively improves patients' quality of life. The use of virtual reality as a complement to this non-pharmacological therapy could help mitigate the loss of oral communication competencies in people with dementia. This systematic literature review aimed to investigate the effect of virtual reality-based reminiscence therapy in people with cognitive impairment or dementia and to understand how the reminiscence program should be designed. The literature search was conducted in the PubMed, Scopus, and Web of Science databases and included results through 31 March 2022. A total of seven articles were included. Overall, the results support the use of virtual reality-based reminiscence therapy in people with cognitive impairment or dementia. In general, virtual reality was found to be pleasant and safe to use, with potential to stimulate communication competencies and lead people to recall positive memories without threatening side effects. However, no changes were observed in behavioral, psychological, or quality of life indicators. In addition, the reminiscence programs were too heterogeneous to trace a clear pattern. The findings of this systematic literature review suggest that virtual reality-based reminiscence therapy for these groups is scarce in literature. It is vital to conduct further research in this area, given that seven articles do neither represent the severity of the conditions nor the possible potential of virtual reality-based reminiscence therapy.",
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"title": "Dementia Scale Classification Based on Ubiquitous Daily Activity and Interaction Sensing",
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"abstract": "This paper investigates the integration of different approaches to automatically predict high/low-score on the dementia scale. We propose two different approaches to predict this value by capturing the following: (1) the participant's interaction behavior with a humanoid robot and (2) the indoor daily activity in the residence using ubiquitous sensors. The interaction and indoor activity data set were obtained by recording 32 participants living in common residences, including 17 with symptoms of dementia, as indicated through a cognitive test (Revised Hasegawa Dementia Scale). To obtain the interaction features, we extracted the turn-taking features of interaction with a mobile-typed humanoid robot. To extract the indoor activity features, we collected the location data of each participant in the residence using the received signal strength indicators (RSSIs) of Bluetooth signals from different access points (e.g., shared spaces or the participant's room). In the experimental evaluation, we trained binary classification models for classifying the score on the dementia scale from these datasets. The results show that the best classification accuracy (0.875) is achieved when interaction and activity features are fused using a random forest classifier.",
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"content": "This paper investigates the integration of different approaches to automatically predict high/low-score on the dementia scale. We propose two different approaches to predict this value by capturing the following: (1) the participant's interaction behavior with a humanoid robot and (2) the indoor daily activity in the residence using ubiquitous sensors. The interaction and indoor activity data set were obtained by recording 32 participants living in common residences, including 17 with symptoms of dementia, as indicated through a cognitive test (Revised Hasegawa Dementia Scale). To obtain the interaction features, we extracted the turn-taking features of interaction with a mobile-typed humanoid robot. To extract the indoor activity features, we collected the location data of each participant in the residence using the received signal strength indicators (RSSIs) of Bluetooth signals from different access points (e.g., shared spaces or the participant's room). In the experimental evaluation, we trained binary classification models for classifying the score on the dementia scale from these datasets. The results show that the best classification accuracy (0.875) is achieved when interaction and activity features are fused using a random forest classifier.",
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"normalizedAbstract": "This paper investigates the integration of different approaches to automatically predict high/low-score on the dementia scale. We propose two different approaches to predict this value by capturing the following: (1) the participant's interaction behavior with a humanoid robot and (2) the indoor daily activity in the residence using ubiquitous sensors. The interaction and indoor activity data set were obtained by recording 32 participants living in common residences, including 17 with symptoms of dementia, as indicated through a cognitive test (Revised Hasegawa Dementia Scale). To obtain the interaction features, we extracted the turn-taking features of interaction with a mobile-typed humanoid robot. To extract the indoor activity features, we collected the location data of each participant in the residence using the received signal strength indicators (RSSIs) of Bluetooth signals from different access points (e.g., shared spaces or the participant's room). In the experimental evaluation, we trained binary classification models for classifying the score on the dementia scale from these datasets. The results show that the best classification accuracy (0.875) is achieved when interaction and activity features are fused using a random forest classifier.",
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"abstract": "Robotic surgical systems have contributed greatly to the advancement of minimally invasive surgery (MIS). More specifically, telesurgical robots have provided enhanced dexterity to surgeons performing MIS procedures. However, current robotic teleoperated systems have only limited situational awareness of the patient anatomy and surgical environment that would typically be available to a surgeon in an open surgery. Although the endoscopic view enhances the visualization of the anatomy, perceptual understanding of the environment and anatomy is still lacking due to the absence of sensory feedback. To address these limitations, we present an algorithmic software framework to provide Complementary Situational Awareness (CSA) in a surgical assistant. This framework aims at improving the human-robot relationship by providing elaborate guidance and sensory feedback capabilities for the surgeon in complex MIS procedures. Unlike traditional teleoperation, this framework enables the user to telemanipulate the situational model in a virtual environment and uses that information to command the slave robot with appropriate admittance gains and environmental constraints. Simultaneously, the situational model is updated based on interaction of the slave robot with the task space environment. We provide various high-level and mid-level components to provide CSA and illustrate the necessary capabilities required for any robotic platform to readily incorporate CSA. We also demonstrate the use of our framework for constrained model-mediated teleoperation using the open-source da Vinci Research Kit (dVRK) hardware.",
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"title": "Depth Sensor-Based In-Home Daily Activity Recognition and Assessment System for Stroke Rehabilitation",
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"abstract": "The existing techniques used for post stroke rehabilitation have sought to offer stroke survivors with upper extremity motor deficits a system for the practice and re-learning of motor tasks. Some studies suggest that the use of Virtual Reality technologies as an assistive technology in combination with conventional therapies can achieve improved results in post stroke rehabilitation. Despite the wealth of ongoing research attempting to build a virtual reality based system for upper extremity rehabilitation, there still exists a need for a training platform that would provide whole arm rehabilitation. In order to be practical this system should ideally be low cost and involve minimal therapist involvement. This paper describes some of the applications of virtual reality that have undergone clinical trials with patients suffering from upper extremity functional motor deficits. A brief description of VR technologies that are in place, providing benefits to the stroke patients with upper extremity motor and functional deficits, alongside a proof of concept of a whole arm rehabilitation platform is presented.",
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"abstract": "The use of Virtual and Augmented Reality systems for motor rehabilitation is increasing mainly due to the new interaction tools which enable interaction through body movements. To improve these systems it is important to provide movement guidance and correction according to the therapeutic description of it. The use of natural interaction can help due the understanding of user's intentions, e.g. analyzing their body movements allows the application to provide information and encouragement to them in real time, improving the interaction and the treatment process as a whole. Thus, the aim of this research is to provide guidance and correction to performed movements based on the therapeutic definition of them. This is applied on motor rehabilitation through the use of the Kinect sensor as interaction support tool for rehabilitation systems. The Kinect sensor gives three-dimensional information about the user body, recognizing skeleton and joint positions, however, it does not provide detection of body specific movements. This way, the correct description of therapeutic movement (upper limbs, for instance) was implemented in a prototype. A scoring mechanism was also developed in order to measure the patient performance, as well as to encourage him/her to improve it by displaying a positive feedback whenever he does a correct movement.",
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"content": "The use of Virtual and Augmented Reality systems for motor rehabilitation is increasing mainly due to the new interaction tools which enable interaction through body movements. To improve these systems it is important to provide movement guidance and correction according to the therapeutic description of it. The use of natural interaction can help due the understanding of user's intentions, e.g. analyzing their body movements allows the application to provide information and encouragement to them in real time, improving the interaction and the treatment process as a whole. Thus, the aim of this research is to provide guidance and correction to performed movements based on the therapeutic definition of them. This is applied on motor rehabilitation through the use of the Kinect sensor as interaction support tool for rehabilitation systems. The Kinect sensor gives three-dimensional information about the user body, recognizing skeleton and joint positions, however, it does not provide detection of body specific movements. This way, the correct description of therapeutic movement (upper limbs, for instance) was implemented in a prototype. A scoring mechanism was also developed in order to measure the patient performance, as well as to encourage him/her to improve it by displaying a positive feedback whenever he does a correct movement.",
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"title": "2018 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)",
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"doi": "10.1109/ICIIBMS.2018.8549932",
"title": "EMG Feature Extractions for Upper-Limb Functional Movement During Rehabilitation",
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"abstract": "Rehabilitation is important treatment for post stroke patient to regain their muscle strength and motor coordination as well as to retrain their nervous system. Electromyography (EMG) has been used by researcher to enhance conventional rehabilitation method as a tool to monitor muscle electrical activity however EMG signal is very stochastic in nature and contains some noise. Special technique is yet to be researched in processing EMG signal to make it useful and effective both to researcher and to patient in general. Feature extraction is among the signal processing technique involved and the best method for specific EMG study needs to be applied. In this works, nine feature extractions techniques are applied to EMG signals recorder from subjects performing upper limb rehabilitation activity based on suggested movement sequence pattern. Three healthy subjects perform the experiment with three trials each and EMG data were recorded from their bicep and deltoid muscle. The applied features for every trials of each subject were analyzed statistically using student T-Test their significant of p-value. The results were then totaled up and compared between the nine features applied and Auto Regressive coefficient (AR) present the best result and consistent with each subjects' data. This feature will be used later in our future research work of Upper-limb Virtual Reality Rehabilitation.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Rehabilitation is important treatment for post stroke patient to regain their muscle strength and motor coordination as well as to retrain their nervous system. Electromyography (EMG) has been used by researcher to enhance conventional rehabilitation method as a tool to monitor muscle electrical activity however EMG signal is very stochastic in nature and contains some noise. Special technique is yet to be researched in processing EMG signal to make it useful and effective both to researcher and to patient in general. Feature extraction is among the signal processing technique involved and the best method for specific EMG study needs to be applied. In this works, nine feature extractions techniques are applied to EMG signals recorder from subjects performing upper limb rehabilitation activity based on suggested movement sequence pattern. Three healthy subjects perform the experiment with three trials each and EMG data were recorded from their bicep and deltoid muscle. The applied features for every trials of each subject were analyzed statistically using student T-Test their significant of p-value. The results were then totaled up and compared between the nine features applied and Auto Regressive coefficient (AR) present the best result and consistent with each subjects' data. This feature will be used later in our future research work of Upper-limb Virtual Reality Rehabilitation.",
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"fno": "08549932",
"keywords": [
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"authors": [
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"affiliation": "AiCOS Research Lab, School of Mechatronic, Universiti Malaysia Perlis, Perlis, Malaysia",
"fullName": "Mohd Saiful Hazam Majid",
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"fullName": "W. Khairunizam",
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"affiliation": "AiCOS Research Lab, School of Mechatronic, Universiti Malaysia Perlis, Perlis, Malaysia",
"fullName": "A.B. Shahriman",
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"affiliation": "Technopreneur at UniMAP Sdn. Bhd., Perlis, 01000, Malaysia",
"fullName": "I. Zunaidi",
"givenName": "I.",
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"affiliation": "AiCOS Research Lab, School of Mechatronic, Universiti Malaysia Perlis, Perlis, Malaysia",
"fullName": "B.N. Sahyudi",
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"title": "Lower Limb Balance Rehabilitation of Post-stroke Patients Using an Evaluating and Training Combined Augmented Reality System",
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"abstract": "Augmented/virtual reality applications can provide immersive and interactive virtual environment for motor rehabilitation using the collaborative stimulations of multiple sensory channels such as sight, hearing, and movement, enhance the rehabilitation effect through repetitions, feedbacks, and encouragement. In this paper, we propose an evaluating and training integrated application for the rehabilitation of patients with lower limb balance disorder. The AR-based evaluation module visualizes the limits of lower limbs patients' balance abilities and provides quantitative data to their therapists, then rehabilitation therapists can customize personalized VR training games accordingly.",
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"Augmented Reality",
"Medical Computing",
"Patient Rehabilitation",
"Patient Treatment",
"Serious Games Computing",
"Post Stroke Patients",
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"Games",
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"Human Computer Interaction HCI",
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"Mixed Augmented Reality",
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"Computing Technology Policy",
"Medical Information Policy",
"Medical Technologies"
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"affiliation": "Beihang University,State Key Laboratory of Virtual Reality Technology and Systems",
"fullName": "Shuwei Chen",
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"affiliation": "Beihang University,State Key Laboratory of Virtual Reality Technology and Systems",
"fullName": "Ben Hu",
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"surname": "Hu",
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{
"affiliation": "Research Institute of Frontier Science, Beihang University,State Key Laboratory of Virtual Reality Technology and Systems",
"fullName": "Yang Gao",
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"affiliation": "Zhejiang University School of Medicine,Sir Run Run Shaw Hospital",
"fullName": "Zhiping Liao",
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"affiliation": "Zhejiang University School of Medicine,Sir Run Run Shaw Hospital",
"fullName": "Jianhua Li",
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"affiliation": "Research Institute of Frontier Science, Beihang University,State Key Laboratory of Virtual Reality Technology and Systems",
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"affiliation": "Microsoft Research, Asia",
"fullName": "Lin Liang",
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"doi": "10.1109/IM.2001.924483",
"title": "3D Modeling System of Human Face and Full 3D Facial Caricaturing",
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"abstract": "Kouta Fujimura, Hitoshi Kihara, Yoshiaki Noguchi, Naoya Ishikawa, SANYO Electric Co, Ltd.This paper proposes a method for modeling 3D face from the 3D facial images captured from the surrounding 2D cameras by which the color texture and surface shape information of the face are synchronously measured. And 3D facial caricature is proposed by applying 2.5D PICASSO system to the proposed surrounding 3D face model. Automatic method for extracting regions of the facial parts is technically maintained and the composition strategies for integrating a few 2.5D facial caricatures into surrounding 3D caricature are also proposed.",
"abstracts": [
{
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"content": "Kouta Fujimura, Hitoshi Kihara, Yoshiaki Noguchi, Naoya Ishikawa, SANYO Electric Co, Ltd.This paper proposes a method for modeling 3D face from the 3D facial images captured from the surrounding 2D cameras by which the color texture and surface shape information of the face are synchronously measured. And 3D facial caricature is proposed by applying 2.5D PICASSO system to the proposed surrounding 3D face model. Automatic method for extracting regions of the facial parts is technically maintained and the composition strategies for integrating a few 2.5D facial caricatures into surrounding 3D caricature are also proposed.",
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"fullName": "T. Fujiwara",
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"fullName": "H. Koshimizu",
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"title": "Facial Metrical and Caricature-Pattern-Based Learning in Neural Network System for Face Recognition",
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"abstract": "Face recognition technology has been an increasingly important module in security systems. A challenging problem is how to extract features tolerant to the appearance variables such as changes in shape, illumination, and occlusion. Extracted metrical features of facial caricatures that are combined with their facial photographs in the training set are examined. The facial caricature is a personal representative amplifying perceptually significant information of individuals. Unlike Eigenfaces, Fisherfaces, and Laplacianfaces, the twenty-nine metrical features that used in this study do not depend upon illumination and occlusion variables. Our results show that facial caricature-trained neural networks outperform significantly of those only facial photograph-trained neural networks.",
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"content": "Face recognition technology has been an increasingly important module in security systems. A challenging problem is how to extract features tolerant to the appearance variables such as changes in shape, illumination, and occlusion. Extracted metrical features of facial caricatures that are combined with their facial photographs in the training set are examined. The facial caricature is a personal representative amplifying perceptually significant information of individuals. Unlike Eigenfaces, Fisherfaces, and Laplacianfaces, the twenty-nine metrical features that used in this study do not depend upon illumination and occlusion variables. Our results show that facial caricature-trained neural networks outperform significantly of those only facial photograph-trained neural networks.",
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"normalizedAbstract": "Face recognition technology has been an increasingly important module in security systems. A challenging problem is how to extract features tolerant to the appearance variables such as changes in shape, illumination, and occlusion. Extracted metrical features of facial caricatures that are combined with their facial photographs in the training set are examined. The facial caricature is a personal representative amplifying perceptually significant information of individuals. Unlike Eigenfaces, Fisherfaces, and Laplacianfaces, the twenty-nine metrical features that used in this study do not depend upon illumination and occlusion variables. Our results show that facial caricature-trained neural networks outperform significantly of those only facial photograph-trained neural networks.",
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"abstract": "The performance of single-carrier communication systems is seriously degraded by ISI (inter-symbol interference). In order to overcome the ISI Turbo equalization technique was proposed to maximize system performance. Furthermore, Doppler effects are affected to system performance. Turbo equalizer can achieve impressive performance gains over ISI and Doppler channel. In general, Turbo equalizer performs iterative feedback from decoder to equalizer in receiver. Because of iterative feedback, turbo equalizer gets better system performance according to the iteration number. In this paper, we propose a novel turbo equalizer, which is called as blind turbo equalizer for compensating ISI and Doppler effects. Proposed blind turbo equalizer is included with feed-forward filter and feed-back filter. We adopt 2 kinds of blind algorithms at feed-forward filter. One is normal CMA (constant modulus algorithm), another is SAGMCMA (stop-and-go modified constant modulus algorithm). Also, we adopt linear SISO-MMSE (soft-input soft-output minimum mean square error) equalizer at feed-back filter. Therefore, we improve the BER performance through proposed blind turbo equalizer.",
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"abstract": "Next generation mobile terminals will have to support multiuser detection and more than one antenna (Multiple Output Multiple Input - MIMO) to implement the latest high data rate modes of UTRA/3GPP such as HSDPA. Hence, very efficient and flexible detection algorithms are needed. In [1] we have already shown an approach of such an equalizer for multi user detection. In this paper we will present a multi user MIMO linear least squares based equalizer for Space-Time Transmit Diversity (STTD) encoded data, which can make use of the same CORDIC based platform as the multi user equalizer. The paper shows that our approach has got a significant performance increase while maintaining computational complexity in comparison to a standard Rake based equalizer.",
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"abstract": "This paper considers the usage of the fast Recursive Least Squares (RLS) adaptive filtering algorithms for the weights calculation in the combined adaptive unit, which consists of an antenna array and a channel equalizer. The weights of the fractionally-spaced Feed-Forward (FF) filter of the equalizer are split and used simultaneously as the antenna array weights. The array output signal is combined with that of the Feed-Backward (FB) filter of the equalizer. Because the FF filter operates at the up-sampled rate and the FB filter of the equalizer operates at the symbol rate, the multichannel fast RLS algorithms cannot be used in the considered adaptive unit directly. It is proposed to use a polyphase representation of the FF filter to solve this problem. In this case, the architecture of the adaptive unit is presented as a multichannel adaptive filter with unequal number of weights in channels. The paper considers the architecture of the adaptive unit and the details of its FF part. The mathematical details of the multichannel fast RLS algorithm (Fast Kalman, FK), used for the adaptive unit weights calculation, are presented. The simulation of the array/equalizer demonstrates the ability of the proposed unit to steer the main lobe of the antenna array radiation pattern towards the desired signal source without a priory search of the source angular location and, at the same time, to remove the signals of the external interferences and the intersymbol interference in the array output signal. The simulation has been carried out, using a linear array with 16 omnidirectional antennas. It operates in the condition of -30 dB Signal-to-Interference Ratio and 10...30 dB Signal-to-Noise Ratio. The array receives the Phase Shift Keying (8-PSK) desired signal, passed through a two-rays communication channel with about -65 dB gaps in the channel amplitude-frequency response.",
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"content": "This paper considers the usage of the fast Recursive Least Squares (RLS) adaptive filtering algorithms for the weights calculation in the combined adaptive unit, which consists of an antenna array and a channel equalizer. The weights of the fractionally-spaced Feed-Forward (FF) filter of the equalizer are split and used simultaneously as the antenna array weights. The array output signal is combined with that of the Feed-Backward (FB) filter of the equalizer. Because the FF filter operates at the up-sampled rate and the FB filter of the equalizer operates at the symbol rate, the multichannel fast RLS algorithms cannot be used in the considered adaptive unit directly. It is proposed to use a polyphase representation of the FF filter to solve this problem. In this case, the architecture of the adaptive unit is presented as a multichannel adaptive filter with unequal number of weights in channels. The paper considers the architecture of the adaptive unit and the details of its FF part. The mathematical details of the multichannel fast RLS algorithm (Fast Kalman, FK), used for the adaptive unit weights calculation, are presented. The simulation of the array/equalizer demonstrates the ability of the proposed unit to steer the main lobe of the antenna array radiation pattern towards the desired signal source without a priory search of the source angular location and, at the same time, to remove the signals of the external interferences and the intersymbol interference in the array output signal. The simulation has been carried out, using a linear array with 16 omnidirectional antennas. It operates in the condition of -30 dB Signal-to-Interference Ratio and 10...30 dB Signal-to-Noise Ratio. The array receives the Phase Shift Keying (8-PSK) desired signal, passed through a two-rays communication channel with about -65 dB gaps in the channel amplitude-frequency response.",
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"abstract": "One of the major goals of computer vision and machine intelligence is the development of flexible and efficient methods for shape representation. This paper presents an approach for shape retrieval based on sparse representation of scale-invariant heat kernel. We use the Laplace-Beltrami eigen functions to detect a small number of critical points on the shape surface. Then a shape descriptor is formed based on the heat kernels at the detected critical points for different scales, combined with the normalized eigen values of the Lap lace-Beltrami operator. Sparse representation is used to reduce the dimensionality of the calculated descriptor. The proposed descriptor is used for classification via the collaborative representation-based classification with regularized least square algorithm. We compare our approach to two well-known approaches on two different data sets: the nonrigid world data set and the SHREC 2011. The results have indeed confirmed the improved performance of the proposed approach, yet reducing the time and space complicity of the shape retrieval problem.",
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"content": "One of the major goals of computer vision and machine intelligence is the development of flexible and efficient methods for shape representation. This paper presents an approach for shape retrieval based on sparse representation of scale-invariant heat kernel. We use the Laplace-Beltrami eigen functions to detect a small number of critical points on the shape surface. Then a shape descriptor is formed based on the heat kernels at the detected critical points for different scales, combined with the normalized eigen values of the Lap lace-Beltrami operator. Sparse representation is used to reduce the dimensionality of the calculated descriptor. The proposed descriptor is used for classification via the collaborative representation-based classification with regularized least square algorithm. We compare our approach to two well-known approaches on two different data sets: the nonrigid world data set and the SHREC 2011. The results have indeed confirmed the improved performance of the proposed approach, yet reducing the time and space complicity of the shape retrieval problem.",
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"abstract": "The intrinsic image decomposition aims to retrieve “intrinsic” properties of an image, such as shading and reflectance. To make it possible to quantitatively compare different approaches to this problem in realistic settings, we present a ground-truth dataset of intrinsic image decompositions for a variety of real-world objects. For each object, we separate an image of it into three components: Lambertian shading, reflectance, and specularities. We use our dataset to quantitatively compare several existing algorithms; we hope that this dataset will serve as a means for evaluating future work on intrinsic images.",
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"abstract": "The last few decades have witnessed a significant evolution of technology in different domains, changing the way the world operates, which leads to an overwhelming amount of data generated in an open-ended way as streams. Over the past years, we observed the development of several machine learning algorithms to process big data streams. However, the accuracy of these algorithms is very sensitive to their hyper-parameters, which requires expertise and extensive trials to tune. Another relevant aspect is the high-dimensionality of data, which can causes degradation to computational performance. To cope with these issues, this paper proposes a stream k-nearest neighbors (kNN) algorithm that applies an internal dimension reduction to the stream in order to reduce the resource usage and uses an automatic monitoring system that tunes dynamically the configuration of the kNN algorithm and the output dimension size with big data streams. Experiments over a wide range of datasets show that the predictive and computational performances of the kNN algorithm are improved.",
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"abstract": "Research on increasing the production of crops is increasingly important these days. This research needs a way to quantitatively measure the 3D growth of plants under controlled environments to allow a cost versus benefits analysis. Plant scientists need a non-invasive, non-destructive method to quantitatively measure the 3D growth of plants. Traditional methods, for example, measuring weight, area or volume, often negatively affects the future plant growth. Also the manual nature of this measurement can be quite time consuming, tedious and error prone. Some recent effort have been reported in the literature about the construction of autonomous systems for plant phenotype, but these are not practical for large scale accurate 3D plant growth computation. To the best of our knowledge, we are the first in the world to attempt truly 3D approach via robot assisted plant growth analysis using3D imaging and laser scanning technology. We describe an automated system to perform 3D plant modelling using a laser scanner mounted on a robot arm to capture 3D plant data. We present a detailed overview of the system integration, including the robotic arm, laser scanner and a programmable growth chamber. We also show some results on reconstructing the 3Dmodel of a growing plant which is better than the current state of the art.",
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"title": "A Visualization System for Tomato Plant Modeling",
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"abstract": "Virtual crop models make great significances to the research of quantification of field evapotranspiration, design of plant type, and optimization of cultural practices. Because most existing plant-modeling systems require the user to have specific biological knowledge about plants, thus it is often a hard and laborious task by using these systems to create a three-dimensional plant model. Moreover, there is lack of software tools to specially simulate the structures and growth process of a certain kind of crop. With regard to those statuses of virtual plant modeling, in this article a powerful and convenient tomato plant modeling system is developed with the integrated platform of Visual C++ 6.0 and OpenGL. Based on the growth laws and the topological structure's character of tomato plant, Parametric L-system is used to simulate the topological structures of tomato plant. The technique of parametric triangular meshes is used to model different organs of tomato, and the surface-rendering techniques in Computer Graphics are used to render the created shapes of tomato plant at both organ and individual levels. Based on the accumulated temperature model, the system can predict the growth status of tomato plant, and give some suggestion of tomato planting",
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"content": "Virtual crop models make great significances to the research of quantification of field evapotranspiration, design of plant type, and optimization of cultural practices. Because most existing plant-modeling systems require the user to have specific biological knowledge about plants, thus it is often a hard and laborious task by using these systems to create a three-dimensional plant model. Moreover, there is lack of software tools to specially simulate the structures and growth process of a certain kind of crop. With regard to those statuses of virtual plant modeling, in this article a powerful and convenient tomato plant modeling system is developed with the integrated platform of Visual C++ 6.0 and OpenGL. Based on the growth laws and the topological structure's character of tomato plant, Parametric L-system is used to simulate the topological structures of tomato plant. The technique of parametric triangular meshes is used to model different organs of tomato, and the surface-rendering techniques in Computer Graphics are used to render the created shapes of tomato plant at both organ and individual levels. Based on the accumulated temperature model, the system can predict the growth status of tomato plant, and give some suggestion of tomato planting",
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"abstract": "There are currently around 375000 known species of plants in the world. Expert botanists are able to easily classify and classify them based on either division/phylum, order, class, species, genus or family. But common people like students and new people in the field may find it difficult to classify them appropriately due to lack of experience or exposure to those plants. In the proposed solution, we plan on suggesting a system which would use deep learning models for image processing. This system can be trained on an ample amount of plant leaves images and tree images dataset containing pictures of various plant leaves and trees. Many prominent datasets like Flavia, Swedish Leaf datasets, etc can be used to train the model. The model will be built using a combination of 2-D Convolutional layers, Max Pooling and Dense layers. The system will take the images of the plant or tree as input and the built model will work on and predict the output. The output will be the classification of the plant.",
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"abstract": "Studying the growth dynamics of developing plants is of critical importance in plant sciences. The traditional methods rely on either manual measurement, which involves tedious labor work, or 2D image-based approaches, which cannot fully characterize plants in 3D. Given the advances of scanners and 3D reconstruction methods, scientists begin to pay more attention to 3D models to improve accuracy. However, existing methods mostly focus on the growth of a whole plant rather than its detailed substructures. In this paper, we have developed an end-to-end pipeline to detect the key events on both the whole plant and the specific components. Our method is achieved by building 3D models from images, segmenting individual components, and capturing traits. We implement an experiment on maizes for evaluation and successfully detect events in the process of growth.",
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"affiliation": "University of Nebraska-Lincoln,Department of Agronomy and Horticulture,Lincoln,NE,USA",
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"affiliation": "University of Nebraska-Lincoln,Department of Agronomy and Horticulture,Lincoln,NE,USA",
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"abstract": "An automatic monitoring platform for plant breeding is built to provide accurate environmental parameters and phenotypic parameters for agronomic researchers during breeding experiments. Plant weight, soil humidity, air condition and plant 3D model could be recorded automatically. Plant point cloud could be gathered from multi directions by depth camera and be merged by rotation and ICP registration. Revised point clouds of full plants are used as dataset for measurement and classification. With the help of this platform, agronomy researchers could get plant parameters faster than ever.",
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"affiliation": "Shanghai Jiaotong University,School of mechanical engineering,Shanghai,China",
"fullName": "Chenhui Lin",
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"affiliation": "Shanghai Academy of Agricultural Sciences,Institute of Facility Horticulture,Shanghai,China",
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"affiliation": "Shanghai Jiaotong University,School of mechanical engineering,Shanghai,China",
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"affiliation": "Shanghai Jiaotong University,School of mechanical engineering,Shanghai,China",
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"title": "Effectiveness of occluded object representations at displaying ordinal depth information in augmented reality",
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"abstract": "An experiment was conducted to investigate the utility of a number of iconographic styles in relaying ordinal depth information at vista space distances of more than 1900m. The experiment consisted of two tasks: distance judgments with respect to discrete zones, and ordinal depth determination in the presence of icon overlap. The virtual object representations were chosen based on their effectiveness, as demonstrated in previous studies. The first task is an adaptation of a previous study investigating distance judgments of occluded objects at medium field distances. We found that only one of the icon styles fared better than guessing. The second is a novel task important to situation awareness and tested two specific cases: ordinal depth of icons with 50% and 100% overlap. We found that the case of full overlap made the task effectively impossible with all icon styles, whereas in the case of partial overlap, the Ground Plane had a clear advantage.",
"abstracts": [
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"content": "An experiment was conducted to investigate the utility of a number of iconographic styles in relaying ordinal depth information at vista space distances of more than 1900m. The experiment consisted of two tasks: distance judgments with respect to discrete zones, and ordinal depth determination in the presence of icon overlap. The virtual object representations were chosen based on their effectiveness, as demonstrated in previous studies. The first task is an adaptation of a previous study investigating distance judgments of occluded objects at medium field distances. We found that only one of the icon styles fared better than guessing. The second is a novel task important to situation awareness and tested two specific cases: ordinal depth of icons with 50% and 100% overlap. We found that the case of full overlap made the task effectively impossible with all icon styles, whereas in the case of partial overlap, the Ground Plane had a clear advantage.",
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"Airports",
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"Brightness",
"Standards",
"Abstracts",
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"Augmented Reality",
"Human Factors Evaluation",
"Situation Awareness",
"Ordinal Depth"
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"affiliation": null,
"fullName": "Mark A. Livingston",
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"affiliation": "Mississippi State Univ., Starkville, MS, USA",
"fullName": "Kenneth R. Moser",
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"title": "Big Data for Social Media Evaluation: A Case of Wechat Platform Rankings in China",
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"abstract": "Social media develop rapidly with a growing number of large-scale data generated. With big data, the demand for premiere content requires professional assessing and ranking system. Wechat, as the most popular social media platform, has become ubiquitous and important in China. Wechat public accounts ranking help business parts, government organs and users to approach high quality information effectively and maintain a sustainable environment for social media development. This paper introduced three different ranking systems in China on Wechat Public Accounts and analyze how they evaluate and assess big data generated though social media with their distinctive features: comprehensive, encouragement, regional. Further suggestions are proposed for the ranking systems with big data generated from social media platforms as well.",
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"abstract": "At present, in the investigation stage, public security organs, procuratorial organs and people's courts often need to conduct electronic data forensics analysis on criminals' WeChat and other social software to obtain sensitive information. This paper proposes a forensic analysis method based on chat history data of Wechat on Android smart phone. By using an Improved Naive Bayes Algorithm with redefinable the weights of the feature words, an improved Naive Bayes Classifier (NBC) model is established. The classifier is used to classify the chatting texts in WeChat, in order to find the sensitive information in the chatting texts efficiently. Experiments show that this model can improve the efficiency of acquiring sensitive information in WeChat, and has obvious effects on saving evidence collection time and improving the efficiency of criminal detection.",
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"abstract": "Permeability of the fabric is an important indicator for the clothing comfort. The raw materials, yarn count tightness, texture, thickness, and density will have some impacts on the permeability of the fabric. The present paper is primarily concerned with the fabric structure parameters of 10 commonly used in pure cotton fabrics. Some tests were made, including the basic properties such as yarns type, yarn count, thickness, tightness, per gram of square meters, water vapor permeability of the fabric and so on. The study shows that the texture, weft-tightness, overall tightness, square meters gram, thickness have significant effects on the permeability of fabric with the same materials. As for the lighter fabric, the breathable performance increases with larger pores. It is vey important to choose the appropriate structure parameters in fabrics designing for desired clothing comfort.",
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"content": "Permeability of the fabric is an important indicator for the clothing comfort. The raw materials, yarn count tightness, texture, thickness, and density will have some impacts on the permeability of the fabric. The present paper is primarily concerned with the fabric structure parameters of 10 commonly used in pure cotton fabrics. Some tests were made, including the basic properties such as yarns type, yarn count, thickness, tightness, per gram of square meters, water vapor permeability of the fabric and so on. The study shows that the texture, weft-tightness, overall tightness, square meters gram, thickness have significant effects on the permeability of fabric with the same materials. As for the lighter fabric, the breathable performance increases with larger pores. It is vey important to choose the appropriate structure parameters in fabrics designing for desired clothing comfort.",
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"abstract": "The destacking and assembly of textile fabric garment components is a process found throughout the clothing industry. The paper considers in particular the example of shirt collar assembly, in which three fabric collar panels have to be separated from their respective stacks, inspected for flaws and then placed one on top of the other before being fed into a fusing press which makes the bond between them. There is a split in the ply. It is explained why handling by contact, by air jet separation and by vacuum pick-up are inappropriate. It is then explained how robotic grippers using electrostatic adhesion are used to accomplish the task. Such gripping devices have many potential uses within the textile (and other) industries.<>",
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"abstract": "In order to overcome the problems that the accuracy of association is greatly affected by the environment and the overall performance of association matching cannot be effectively guaranteed in data association method of simultaneous localization and mapping based on laser radar (Laser-SLAM), from the perspective of reducing the complexity of the algorithm and improving the accuracy of association, a joint data association algorithm based on improved artificial fish swarm algorithm (IAFSA) is proposed, which is abbreviated as IAFSA-JDA algorithm. In IAFSA-JDA algorithm, firstly, the local associated strategy is introduced. Secondly, according to the joint maximum likelihood criterion, the Laser-SLAM data association problem is evolved into a combinatorial optimization problem of how to determine the optimal association set. Finally, the traditional artificial fish swarm algorithm (AFSA) is improved, and the improved AFSA is applied to search the optimal association solution of SLAM. The results based on simulation data show that the proposed association algorithm not only ensures high association accuracy, but also reduces the time-consuming of the association process, thus reducing the overall time complexity of SLAM, and it can provide reliable association results for improving the real-time and accuracy of SLAM for unmanned distribution vehicle.",
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"normalizedAbstract": "In order to overcome the problems that the accuracy of association is greatly affected by the environment and the overall performance of association matching cannot be effectively guaranteed in data association method of simultaneous localization and mapping based on laser radar (Laser-SLAM), from the perspective of reducing the complexity of the algorithm and improving the accuracy of association, a joint data association algorithm based on improved artificial fish swarm algorithm (IAFSA) is proposed, which is abbreviated as IAFSA-JDA algorithm. In IAFSA-JDA algorithm, firstly, the local associated strategy is introduced. Secondly, according to the joint maximum likelihood criterion, the Laser-SLAM data association problem is evolved into a combinatorial optimization problem of how to determine the optimal association set. Finally, the traditional artificial fish swarm algorithm (AFSA) is improved, and the improved AFSA is applied to search the optimal association solution of SLAM. The results based on simulation data show that the proposed association algorithm not only ensures high association accuracy, but also reduces the time-consuming of the association process, thus reducing the overall time complexity of SLAM, and it can provide reliable association results for improving the real-time and accuracy of SLAM for unmanned distribution vehicle.",
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"abstract": "Recent advancement in sensing and software technologies enables us to obtain large scale, yet fine 3D mesh models of cultural assets. However, such large-scale models cannot be displayed interactively on consumer computers because of the performance limitation of the hardware. We propose an interactive rendering system for large scale 3D mesh models, stored on a remote machine through relatively small capacity of networks. Our system uses both model and image based rendering methods for efficient load balance between a server and clients. On the server, the 3D models are rendered by the model-based method using a hierarchical data structure with multi-resolution. On the client, it reconstructs an arbitrary view by using a novel image-based method, referred to as the Grid-Lumigraph, with blending image colors from sampling images received from the server. The resulting rendering system can efficiently render any image in real-time.",
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"abstract": "Instructor's perspective videos are useful for presenting intuitive visual instructions for trainees in medical and industrial settings. In such videos, the instructor's arms often obstruct the trainee's view of the work area. In this article, we present a diminished reality method for visualizing the work area hidden by an instructor's arms by capturing the work area with multiple cameras. To achieve such diminished reality, we propose detour light field rendering (DLFR), in which light rays avoid passing through penalty points set in the unstructured light fields reconstructed from multiple viewpoint images. In DLFR, the camera blending field used in an existing freeviewpoint image generation method known as unstructured lumigraph is re-designed based on our use cases. In this re-design, lesser weights are given to light rays as they pass close to given penalty points. Experimental results demonstrate that using DLFR, the appearance of an undesirable object can be removed from an image in real time.",
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"title": "Compression of Lumigraph with Multiple Reference Frame (MRF) Prediction and Just-in-Time Rendering",
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"abstract": "In the form of 2D image array, Lumigraph captures the complete appearance of an object or a scene, and is able to quickly render a novel view independent of the scene/object complexity. Since the data amount of Lumigraph is huge, the efficient storage and access of Lumigraph are essential.In this paper, we propose a multiple reference frame (MRF) structure to compress the Lumigraph data. By predicting the Lumigraph view from multiple neighbor views, a higher compression ratio is achieved.We also implement the key functionality of just-in-time (JIT) Lumigraph rendering, in which only a small portion of the compressed bitstream necessary for rendering the current view is accessed and decoded. JIT rendering eliminates the need to pre-decode the entire Lumigraph data set, thus greatly reduces the memory requirement of Lumigraph rendering. A decoder cache has been implemented to speed up rendering by reusing the decoded data. The trade off between the computational speed and cache size of the decoder is discussed in the paper.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In the form of 2D image array, Lumigraph captures the complete appearance of an object or a scene, and is able to quickly render a novel view independent of the scene/object complexity. Since the data amount of Lumigraph is huge, the efficient storage and access of Lumigraph are essential.In this paper, we propose a multiple reference frame (MRF) structure to compress the Lumigraph data. By predicting the Lumigraph view from multiple neighbor views, a higher compression ratio is achieved.We also implement the key functionality of just-in-time (JIT) Lumigraph rendering, in which only a small portion of the compressed bitstream necessary for rendering the current view is accessed and decoded. JIT rendering eliminates the need to pre-decode the entire Lumigraph data set, thus greatly reduces the memory requirement of Lumigraph rendering. A decoder cache has been implemented to speed up rendering by reusing the decoded data. The trade off between the computational speed and cache size of the decoder is discussed in the paper.",
"__typename": "ArticleAbstractType"
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"normalizedAbstract": "In the form of 2D image array, Lumigraph captures the complete appearance of an object or a scene, and is able to quickly render a novel view independent of the scene/object complexity. Since the data amount of Lumigraph is huge, the efficient storage and access of Lumigraph are essential.In this paper, we propose a multiple reference frame (MRF) structure to compress the Lumigraph data. By predicting the Lumigraph view from multiple neighbor views, a higher compression ratio is achieved.We also implement the key functionality of just-in-time (JIT) Lumigraph rendering, in which only a small portion of the compressed bitstream necessary for rendering the current view is accessed and decoded. JIT rendering eliminates the need to pre-decode the entire Lumigraph data set, thus greatly reduces the memory requirement of Lumigraph rendering. A decoder cache has been implemented to speed up rendering by reusing the decoded data. The trade off between the computational speed and cache size of the decoder is discussed in the paper.",
"fno": "05920253",
"keywords": [
"Image Based Rendering IBR",
"Lumigraph",
"Multiple Reference Frame MRF Structure",
"Data Compression",
"Just In Time JIT Rendering"
],
"authors": [
{
"affiliation": "Tsinghua University",
"fullName": "Cha Zhang",
"givenName": "Cha",
"surname": "Zhang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Microsoft Research China",
"fullName": "Jin Li",
"givenName": "Jin",
"surname": "Li",
"__typename": "ArticleAuthorType"
}
],
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"pubDate": "2000-03-01T00:00:00",
"pubType": "proceedings",
"pages": "253",
"year": "2000",
"issn": "1068-0314",
"isbn": "0-7695-0592-9",
"notes": null,
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