AR/MR Remote Collaboration on Physical Tasks: A Review

This paper provides a review of research into using Augmented Reality (AR) and Mixed Reality(MR) for remote collaboration on physical tasks. AR/MR-based remote collaboration on physical tasks has recently become more prominent in academic research and engineering applications. It has great potential in many fields, such as real-time remote medical consultation, education, training, maintenance, remote assistance in engineering, and other remote collaborative tasks. However, to the best of our knowledge there has not been any comprehensive review of research in AR/MR remote collaboration on physical tasks. Therefore, this paper presents a comprehensive survey of research between 2000 and 2018 in this domain. We collected 215 papers, more than 80% of which were published between 2010 and 2018, and all relevant works are discussed at length. Then we elaborate on the review from typical architectures, applications (e.g., industry, telemedicine, architecture, teleducation and others), and empathic computing. Next, we made an in-depth review of the papers from seven aspects: (1) collection and classification research, (2) using 3D scene reconstruction environments and live panorama, (3) periodicals and conducting research, (4) local and remote user interfaces, (5) features of user interfaces commonly used, (6) architecture and sharing non-verbal cues, (7) applications and toolkits. We find that most papers (160 articles, 74.4%) are published in conferences, using co-located collaboration to emulate remote collaboration is adopted by more than half (126, 58.6%) of the reviewed papers, the shared non-verbal cues can be mainly classified into five types (Virtual Replicas or Physical Proxy(VRP), AR Annotations or a Cursor Pointer(ARACP), avatar, gesture, and gaze), the local/remote interface is mainly divided into four categories (Head-Mounted Displays(HMD), Spatial Augmented Reality(SAR), Windows-Icon-Menu-Pointer(WIMP) and Hand-Held Displays(HHD)). From this, we can draw ten conclusions. Following this we report on issues for future works. The paper also provides an overall academic roadmap and useful insight into the state-of-the-art of AR/MR remote collaboration on physical tasks. This work will be useful for current and future researchers who are interested in collaborative AR/MR systems.     

Covering problems in facility location: A review

In this study, we review the covering problems in facility location. Here, besides a number of reviews on covering problems, a comprehensive review of models, solutions and applications related to the covering problem is presented after Schilling, Jayaraman, and Barkhi (1993). This survey tries to review all aspects of the covering problems by stressing the works after Schilling, Jayaraman, and Barkhi (1993). We first present the covering problems and then investigate solutions and applications. A summary and future works conclude the paper.     

Collaborative conceptual design—state of the art and future trends

This paper presents a state of the art review of existing research, projects, and applications in the domain of collaborative conceptual design, based on the Internet and Web technologies. The purpose of the review is to understand the needs for conceptual engineering design, to clarify the current conceptual design practice, to classify the available technologies, and to study the future trend in this area. The emphasis of this paper is to briefly outline the methodologies, architectures, and tools developed for the projects reviewed in this paper. It also uncovers approaches to conflict resolution and team/project management, as they are vital to a successful engineering design in a collaborative environment. More than 80 journal and conference papers and about 20 projects are reviewed based on the primary focus mentioned above. The selected research works are further categorised into several areas based on the application domain, design theory, and the technology used for implementation. The selected research projects and applications are basically for, but not limited to, the collaborative conceptual design.     

SGX技术的分析和研究

安全性是云计算中一项极为重要的需求,然而如何保护云计算中关键应用程序和数据的安全、防止云平台管理员泄露用户隐私,仍然是目前没有解决的难题.2013年,Intel公司提出了新的处理器安全技术SGX,能够在计算平台上提供一个可信的隔离空间,保障用户关键代码和数据的机密性和完整性.作为系统安全领域的重大研究进展,SGX对系统安全,尤其是云计算安全保护方面具有非常重要的意义.该文介绍了SGX的原理和特性,分析了SGX的关键技术以及针对SGX的侧信道攻击及防御方法.同时,总结和归纳了该技术的研究成果,分析了SGX技术与其他可信计算技术的异同,并指出了SGX技术的未来研究挑战和应用需求.     

Review and classification of hybrid flow shop scheduling problems from a production system and a solutions procedure perspective

In this paper, an extensive review of recently published papers on hybrid flow shop (HFS) scheduling problems is presented. The papers are classified first according to the HFS characteristics and production limitations considered in the respective papers. This represents a new approach to the classification of papers in the HFS environment. Second, the papers have been classified according to the solution approach proposed. These two classification categories give a comprehensive overview on the state of the art of the problem and can guide the reader with respect to future research work.     

A state of the art literature review of VIKOR and its fuzzy extensions on applications

Multi criteria decision making (MCDM) is one of the research areas of operations research and management science which has widely studied by researchers and practitioners. It finds a compromise solution for evaluating and ranking alternatives from the best to the worst under conflicting criteria with respect to decision maker(s) preferences. In a compromise approach, the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR; that means multi-criteria optimization and compromise solution) continues to be applied satisfactorily across different application areas. This paper conducts a state-of-the-art literature review to categorize, analyze and interpret the current research on VIKOR applications. It also discusses the extensions of VIKOR applied in fuzzy environments. A total of 343 papers are classified into 13 different application areas and a number of sub-application areas. Furthermore, all papers are also categorized with respect to publication year, published journal, country of origin, application type (real case study vs empirical study), and version of fuzzy sets used. This comprehensive literature review provides an insight for researchers and practitioners on VIKOR applications in terms of showing current state and potential areas for future attempts to be focused in the future.     

SGX应用支持技术研究进展

安全与可信是云计算中极为重要的需求,如何保护用户在云平台上托管的应用程序代码和数据的安全、防止云服务提供商和其他攻击者窃取用户机密数据,一直是个难题.2013年,Intel公司提出了新的处理器安全技术SGX,能够在计算平台上提供一个用户空间的可信执行环境,保证用户关键代码和数据的机密性和完整性.SGX技术自提出以来,成为云计算安全问题的重要解决方案.如何有效地应用SGX技术来保护用户的应用程序,成为了近年来的研究热点.本文介绍了SGX的相关机制和SDK,概括了SGX应用面临的安全问题、性能瓶颈问题、开发困难问题和功能局限性问题等瓶颈,总结并归纳了SGX应用支持技术的研究进展,包括：SGX应用安全防护技术、SGX应用性能优化技术、SGX应用辅助开发技术和SGX功能扩展技术,并展望了未来的发展方向.     

Applications,databases and open computer vision research from drone videos and images: a survey

Analyzing videos and images captured by unmanned aerial vehicles or aerial drones is an emerging application attracting significant attention from researchers in various areas of computer vision. Currently, the major challenge is the development of autonomous operations to complete missions and replace human operators. In this paper, based on the type of analyzing videos and images captured by drones in computer vision, we have reviewed these applications by categorizing them into three groups. The first group is related to remote sensing with challenges such as camera calibration, image matching, and aerial triangulation. The second group is related to drone-autonomous navigation, in which computer vision methods are designed to explore challenges such as flight control, visual localization and mapping, and target tracking and obstacle detection. The third group is dedicated to using images and videos captured by drones in various applications, such as surveillance, agriculture and forestry, animal detection, disaster detection, and face recognition. Since most of the computer vision methods related to the three categories have been designed for real-world conditions, providing real conditions based on drones is impossible. We aim to explore papers that provide a database for these purposes. In the first two groups, some survey papers presented are current. However, the surveys have not been aimed at exploring any databases. This paper presents a complete review of databases in the first two groups and works that used the databases to apply their methods. Vision-based intelligent applications and their databases are explored in the third group, and we discuss open problems and avenues for future research.

     

A comprehensive survey on multimodal medical signals fusion for smart healthcare systems

Smart healthcare is a framework that utilizes technologies such as wearable devices, the Internet of Medical Things (IoMT), sophisticated machine learning algorithms, and wireless communication technology to seamlessly access health records, link individuals, resources, and organizations, and then effectively handle and react to health environment demands intelligently. One of the main ingredients of smart healthcare is medical sensors or IoMT. Due to the complex nature of diseases, in many cases, there is a need for multimodal medical signals for their diagnoses. While using multimodal signals, the most important issue is how to fuse them – an area of burgeoning interest within the research community. This paper presents a comprehensive survey of multimodal medical signals fusion schemes that have been proposed for smart healthcare applications. Research works included in major repositories, such as IEEE Xplore, Science Direct, Springer Link, and ACM digital library have been surveyed to address several related research questions. Focus is placed on recent developments, thus only works published between 2014-2020 are considered. Finally, key research challenges and possible future directions are also provided.     

Knowledge discovery in medicine: Current issue and future trend

Data mining is a powerful method to extract knowledge from data. Raw data faces various challenges that make traditional method improper for knowledge extraction. Data mining is supposed to be able to handle various data types in all formats. Relevance of this paper is emphasized by the fact that data mining is an object of research in different areas. In this paper, we review previous works in the context of knowledge extraction from medical data. The main idea in this paper is to describe key papers and provide some guidelines to help medical practitioners. Medical data mining is a multidisciplinary field with contribution of medicine and data mining. Due to this fact, previous works should be classified to cover all users’ requirements from various fields. Because of this, we have studied papers with the aim of extracting knowledge from structural medical data published between 1999 and 2013. We clarify medical data mining and its main goals. Therefore, each paper is studied based on the six medical tasks: screening, diagnosis, treatment, prognosis, monitoring and management. In each task, five data mining approaches are considered: classification, regression, clustering, association and hybrid. At the end of each task, a brief summarization and discussion are stated. A standard framework according to CRISP-DM is additionally adapted to manage all activities. As a discussion, current issue and future trend are mentioned. The amount of the works published in this scope is substantial and it is impossible to discuss all of them on a single work. We hope this paper will make it possible to explore previous works and identify interesting areas for future research.     

A review of hierarchical facility location models

In this study, we review the hierarchical facility location models. Although there have been a number of review papers on hierarchical facility problems, a comprehensive treatment of models has not been provided since the mid-80s. This review fills the gap in the literature. We first classify the hierarchical facility problems according to the features of systems studied, which are based on flow pattern, service availability at each level of the hierarchy, and spatial configuration of services in addition to the objectives to locate facilities. We then investigate the applications, mixed integer programming models, and solution methods presented for the problem. With an overview of the selected works, we consolidate the main results in the literature.     

A comprehensive study of visual event computing

This paper contains a survey on aspects of visual event computing. We start by presenting events and their classifications, and continue with discussing the problem of capturing events in terms of photographs, videos, etc, as well as the methodologies for event storing and retrieving. Later, we review an extensive set of papers taken from well-known conferences and journals in multiple disciplines. We analyze events, and summarize the procedure of visual event actions. We introduce each component of a visual event computing system, and its computational aspects, we discuss the progress of each component and review its overall status. Finally, we suggest future research trends in event computing and hope to introduce a comprehensive profile of visual event computing to readers.     

A systematic review of UML model consistency management

Information System (IS) development has been beset by consistency problems since its infancy. These problems are greater still in UML software development, and are principally caused by the existence of multiple views (models) for the same system, and may involve potentially contradictory system specifications. Since a considerable amount of work takes place within the scope of model consistency management, this paper presents a systematic literature review (SLR) which was carried out to discover the various current model consistency conceptions, proposals, problems and solutions provided. To do this, a total of 907 papers related to UML model consistency published in literature and extracted from the most relevant scientific sources (IEEE Computer Society, ACM Digital Library, Google Scholar, ScienceDirect, and the SCOPUS Database) were considered, of which 42 papers were eventually analyzed. This systematic literature review resulted in the identification of the current state-of-the-art with regard to UML model consistency management research along with open issues, trends and future research within this scope. A formal approach for the handling of inconsistency problems which fulfils the identified limitations is also briefly presented.     

问题生成研究综述

问题生成是给定文本,自动生成内容通顺、语义相关的自然语言问题。问题生成可应用于教育领域的阅读理解、辅助问答系统和对话系统,因此近年来引起了研究者的广泛关注和兴趣。该文对问题生成的相关研究进行了综述。首先阐释了问题生成的研究意义与应用场景,继而简略概述了基于规则的问题生成方法,然后从输入文本是句子/段落、有/无答案信息等不同角度全面阐述了基于神经网络的问题生成模型。该文还介绍了问题生成的评价方法,分析讨论了现有工作的不足,并展望了未来可能的研究方向。     

Reviewing high-level control techniques on robot-assisted upper-limb rehabilitation

This paper presents a comprehensive review of high-level control techniques for upper-limb robotic training. It aims to compare and discuss the potentials of these different control algorithms, and specify future research direction. Included studies mainly come from selected papers in four review articles. To make selected studies complete and comprehensive, especially some recently-developed upper-limb robotic devices, a search was further conducted in IEEE Xplore, Google Scholar, Scopus and Web of Science using keywords (‘upper limb*’ or ‘upper body*’) and (‘rehabilitation*’ or ‘treatment*’) and (‘robot*’ or ‘device*’ or ‘exoskeleton*’). The search is limited to English-language articles published between January 2013 and December 2017. Valuable references in related publications were also screened. Comparative analysis shows that high-level interaction control strategies can be implemented in a range of methods, mainly including impedance/admittance based strategies, adaptive control techniques, and physiological signal control. Even though the potentials of existing interactive control strategies have been demonstrated, it is hard to identify the one leading to maximum encouragement from human users. However, it is reasonable to suggest that future studies should combine different control strategies to be application specific, and deliver appropriate robotic assistance based on physical disability levels of human users.     

独立分量分析及其在图像处理中的应用现状

独立分量分析是一种基于高阶统计量的信号分析方法,它可以找到隐含在数据中的独立分量,近年来作为信号处理和图像处理领域的强有力的分析处理工具得到广泛的关注和研究。在介绍了独立分量分析的基本概念和各种实现算法及其性能的基础上,综述了独立分量分析在图像处理上的应用,最后结合作者的研究探索,总结了独立分量分析的研究新进展和发展趋势。     

Simulation for manufacturing system design and operation: Literature review and analysis

This paper provides a comprehensive review of discrete event simulation publications published between 2002 and 2013 with a particular focus on applications in manufacturing. The literature is classified into three general classes of manufacturing system design, manufacturing system operation, and simulation language/package development. The paper further categorizes the literature into 11 subclasses based on the application area. The current review contributes to the literature in three significant ways: (1) it provides a wide coverage by reviewing 290 papers; (2) it provides a detailed analysis of different aspects of the literature to identify research trends through innovative data mining approaches as well as insights derived from the review process; and (3) it updates and extends the existing classification schemes through identification and inclusion of recently emerged application areas and exclusion of obsolete categories. The results of the literature analysis are then used to make suggestions for future research.     

Learning from class-imbalanced data: Review of methods and applications

Rare events, especially those that could potentially negatively impact society, often require humans’ decision-making responses. Detecting rare events can be viewed as a prediction task in data mining and machine learning communities. As these events are rarely observed in daily life, the prediction task suffers from a lack of balanced data. In this paper, we provide an in depth review of rare event detection from an imbalanced learning perspective. Five hundred and seventeen related papers that have been published in the past decade were collected for the study. The initial statistics suggested that rare events detection and imbalanced learning are concerned across a wide range of research areas from management science to engineering. We reviewed all collected papers from both a technical and a practical point of view. Modeling methods discussed include techniques such as data preprocessing, classification algorithms and model evaluation. For applications, we first provide a comprehensive taxonomy of the existing application domains of imbalanced learning, and then we detail the applications for each category. Finally, some suggestions from the reviewed papers are incorporated with our experiences and judgments to offer further research directions for the imbalanced learning and rare event detection fields.     

A survey on high coherence visual media retargeting: recent advances and applications

The numerous works on media retargeting call for a thorough and comprehensive survey for reviewing and categorizing existing works and providing insights that can help future design of retargeting approaches and its applications. First, we present the basic problem of media retargeting and detail state-of-the-art retargeting methods devised to solve it. Second, we review recent works on objective quality assessment of media retargeting, where we find that although these works are designed to make the objective assessment result in accordance with the subjective evaluation, they are only suitable for certain situations. Considering the subjective nature of aesthetics, designing objective assessment metric for media retargeting could be a promising area for investigation. Third, we elaborate on other applications extended from retargeting techniques. We show how to apply the retargeting techniques in other fields to solve their challenging problems, and reveal that retargeting technique is not just a simple scaling algorithm, but a thought or concept, which has great flexibility and is quite useful.We believe this review can help researchers and practitioners to solve the existing problems of media retargeting and bring new ideas in their works.     

Constant round group key agreement protocols: A comparative study

The scope of this paper is to review and evaluate all constant round Group Key Agreement (GKA) protocols proposed so far in the literature. We have gathered all GKA protocols that require 1,2,3,4 and 5 rounds and examined their efficiency. In particular, we calculated each protocol’s computation and communication complexity and using proper assessments we compared their total energy cost. The evaluation of all protocols, interesting on its own, can also serve as a reference point for future works and contribute to the establishment of new, more efficient constant round protocols.