Int. J. Semantic Comput.最新文献_第9页

Effects of the Size of Mixed-Reality Person Representations on Stress and Presence in Telecommunication 电信中混合现实人物表征大小对压力和在场的影响

Int. J. Semantic Comput. Pub Date : 2019-09-01 DOI: 10.1142/s1793351x19400130

M. Joachimczak, Juan Liu, H. Ando

{"title":"Effects of the Size of Mixed-Reality Person Representations on Stress and Presence in Telecommunication","authors":"M. Joachimczak, Juan Liu, H. Ando","doi":"10.1142/s1793351x19400130","DOIUrl":"https://doi.org/10.1142/s1793351x19400130","url":null,"abstract":"We study how mixed reality (MR) telepresence can enhance long-distance human interaction and how altering 3D representations of a remote person can be used to modulate stress and anxiety during social interactions. To do so, we developed an MR telepresence system employing commodity depth sensors and Microsoft’s Hololens. A textured, polygonal 3D model of a person was reconstructed in real time and transmitted over network for rendering in remote location using HoloLens. In this study, we used mock job interview paradigm to induce stress in human–subjects interacting with an interviewer presented as an MR hologram. Participants were exposed to three different types of real-time reconstructed virtual holograms of the interviewer, a natural-sized 3D reconstruction (NR), a miniature 3D reconstruction (SR) and a 2D-display representation (LCD). Participants reported their subjective experience through questionnaires, while their biophysical responses were recorded. We found that the size of 3D representation of a remote interviewer had a significant effect on participants’ stress levels and their sense of presence. The questionnaire data showed that NR condition induced more stress and presence than SR condition and was significantly different from LCD condition. We also found consistent patterns in the biophysical data.","PeriodicalId":217956,"journal":{"name":"Int. J. Semantic Comput.","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129839830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Segmentation-driven Hierarchical RetinaNet for Detecting Protozoa in Micrograph 分割驱动的分层视网膜网用于显微图像中原生动物的检测

Int. J. Semantic Comput. Pub Date : 2019-09-01 DOI: 10.1142/s1793351x19400178

Khoa Pho, Muhamad Kamal Mohammed Amin, A. Yoshitaka

{"title":"Segmentation-driven Hierarchical RetinaNet for Detecting Protozoa in Micrograph","authors":"Khoa Pho, Muhamad Kamal Mohammed Amin, A. Yoshitaka","doi":"10.1142/s1793351x19400178","DOIUrl":"https://doi.org/10.1142/s1793351x19400178","url":null,"abstract":"Protozoa detection and identification play important roles in many practical domains such as parasitology, scientific research, biological treatment processes, and environmental quality evaluation. Traditional laboratory methods for protozoan identification are time-consuming and require expert knowledge and expensive equipment. Another approach is using micrographs to identify the species of protozoans that can save a lot of time and reduce the cost. However, the existing methods in this approach only identify the species when the protozoan are already segmented. These methods study features of shapes and sizes. In this work, we detect and identify the images of cysts and oocysts of various species such as: Giardia lamblia, Iodamoeba butschilii, Toxoplasma gondi, Cyclospora cayetanensis, Balantidium coli, Sarcocystis, Cystoisospora belli and Acanthamoeba, which have round shapes in common and affect human and animal health seriously. We propose Segmentation-driven Hierarchical RetinaNet to automatically detect, segment, and identify protozoans in their micrographs. By applying multiple techniques such as transfer learning, and data augmentation techniques, and dividing training samples into life-cycle stages of protozoans, we successfully overcome the lack of data issue in applying deep learning for this problem. Even though there are at most 5 samples per life-cycle category in the training data, our proposed method still achieves promising results and outperforms the original RetinaNet on our protozoa dataset.","PeriodicalId":217956,"journal":{"name":"Int. J. Semantic Comput.","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123529006","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Learners' Technological Acceptance of VR Content Development: A Sequential 3-Part Use Case Study of Diverse Post-Secondary Students 学习者对VR内容开发的技术接受度:不同大专学生的连续三部分用例研究

Int. J. Semantic Comput. Pub Date : 2019-09-01 DOI: 10.1142/s1793351x19400154

V. Nguyen, R. Hite, Tommy Dang

{"title":"Learners' Technological Acceptance of VR Content Development: A Sequential 3-Part Use Case Study of Diverse Post-Secondary Students","authors":"V. Nguyen, R. Hite, Tommy Dang","doi":"10.1142/s1793351x19400154","DOIUrl":"https://doi.org/10.1142/s1793351x19400154","url":null,"abstract":"Web-based virtual reality (VR) development tools are in ubiquitous use by software developers, and now, university (undergraduate) students, to move beyond using, to creating new and energizing VR content. Web-based VR (WebVR), among other libraries and frameworks, have risen as a low-cost platform for users to create rich and intuitive VR content and applications. However, the success of WebVR as an instructional tool relies on post-secondary students technological acceptance (TA), the intersectionality of a user’s perceived utility (PU) and perceived ease of use (PEOU, or convenience) with said technological tool. Yet, there is a dearth of exploratory studies of students’ experiences with the AR/VR development technologies to infer their TA. To ascertain the viability of WebVR tools for software engineering undergraduates in the classroom, this paper presents a 3-case contextual investigation of 38 undergraduate students tasked with creating VR content. In each use case, students were provided increasing freedom in their VR content development parameters. Results indicated that students demonstrated elements of technological acceptance in their selection of webVR and other platforms, and not only successfully creating rich and robust VR content (PU), but also executing these projects in a short period (PEOU). Other positive externalities observed were students exhibitions of soft skills (e.g. creativity, critical thinking) and different modes of demonstrating coding knowledge, which suggest further study. Discussed are the lessons learned from the WebVR and VR/AR interventions and recommendations for WebVR instruction. This work may be helpful for both learners and teachers using VR/AR in selecting, designing, and developing coursework materials, tools, and libraries.","PeriodicalId":217956,"journal":{"name":"Int. J. Semantic Comput.","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114760418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 24

Ontology Summarization: Graph-Based Methods and Beyond 本体总结:基于图的方法及超越

Int. J. Semantic Comput. Pub Date : 2019-06-25 DOI: 10.1142/S1793351X19300012

Seyedamin Pouriyeh, M. Allahyari, Qingxia Liu, Gong Cheng, H. Arabnia, M. Atzori, F. Mohammadi, K. Kochut

引用次数: 16

ASIC STA Path Verification Using Semi-Supervised Learning 使用半监督学习的ASIC STA路径验证

Int. J. Semantic Comput. Pub Date : 2019-06-25 DOI: 10.1142/S1793351X19400105

James Obert, T. Mannos

引用次数: 0

Gait Pattern Recognition Using a Smartwatch Assisting Postoperative Physiotherapy 使用智能手表辅助术后物理治疗的步态模式识别

Int. J. Semantic Comput. Pub Date : 2019-06-25 DOI: 10.1142/S1793351X19400117

Athanasios I. Kyritsis, G. Willems, Michel Deriaz, D. Konstantas

{"title":"Gait Pattern Recognition Using a Smartwatch Assisting Postoperative Physiotherapy","authors":"Athanasios I. Kyritsis, G. Willems, Michel Deriaz, D. Konstantas","doi":"10.1142/S1793351X19400117","DOIUrl":"https://doi.org/10.1142/S1793351X19400117","url":null,"abstract":"Postoperative rehabilitation is led by physiotherapists and is a vital program that re-establishes joint motion and strengthens the muscles around the joint after an orthopedic surgery. Modern smart devices have affected every aspect of human life. Newly developed technologies have disrupted the way various industries operate, including the healthcare one. Extensive research has been carried out on how smartphone inertial sensors can be used for activity recognition. However, there are very few studies on systems that monitor patients and detect different gait patterns in order to assist the work of physiotherapists during the said rehabilitation phase, even outside the time-limited physiotherapy sessions. In this paper, we are presenting a gait recognition system that was developed to detect different gait patterns. The proposed system was trained, tested and validated with data of people who have undergone lower body orthopedic surgery, recorded by Hirslanden Clinique La Colline, an orthopedic clinic in Geneva, Switzerland. Nine different gait classes were labeled by professional physiotherapists. After extracting both time and frequency domain features from the time series data, several machine learning models were tested including a fully connected neural network. Raw time series data were also fed into a convolutional neural network.","PeriodicalId":217956,"journal":{"name":"Int. J. Semantic Comput.","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125531163","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Evaluation of a Model-driven Knowledge Storage and Retrieval IDE for Interactive HRI Systems 交互式HRI系统中模型驱动的知识存储与检索IDE的评价

Int. J. Semantic Comput. Pub Date : 2019-06-25 DOI: 10.1142/S1793351X19400099

N. Köster, S. Wrede, P. Cimiano

引用次数: 1

Autonomous Object Pick-and-Sort Procedure for Industrial Robotics Application 应用于工业机器人的自主对象拾取与分拣程序

Int. J. Semantic Comput. Pub Date : 2019-06-01 DOI: 10.1142/S1793351X19400075

Lianjun Li, Yizhe Zhang, M. Ripperger, J. Nicho, M. Veeraraghavan, A. Fumagalli

{"title":"Autonomous Object Pick-and-Sort Procedure for Industrial Robotics Application","authors":"Lianjun Li, Yizhe Zhang, M. Ripperger, J. Nicho, M. Veeraraghavan, A. Fumagalli","doi":"10.1142/S1793351X19400075","DOIUrl":"https://doi.org/10.1142/S1793351X19400075","url":null,"abstract":"This paper describes an industrial robotics application, named Gilbreth, for autonomously picking up objects of different types from a moving conveyor belt and sorting the objects into bins according to their type. The environment, which consists of a moving conveyor belt, a break beam sensor, a 3D camera Kinect sensor, a UR10 industrial robot arm with a vacuum gripper, and different object types such as pulleys, disks, gears, and piston rods, is inspired by the NIST ARIAC competition. A first version of the Gilbreth application is implemented leveraging a number of Robot Operating System (ROS) and ROS-Industrial (ROS-I) packages. The Gazebo package is used to simulate the environment, and six external ROS nodes have been implemented to execute the required functions. Experimental measurements of CPU usage and processing times of the ROS nodes are discussed. In particular, the object recognition ROS package requires the highest processing times and offers an opportunity for designing an iterative method with the aim to fasten completion time. Its processing time is found to be on par with the time required by the robot arm to execute its movement between four poses: pick approach, pick, pick retreat and place.","PeriodicalId":217956,"journal":{"name":"Int. J. Semantic Comput.","volume":"476 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134438821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Simulation of Subjective Closed Captioning Quality Assessment Using Prediction Models 基于预测模型的主观字幕质量评价模拟

Int. J. Semantic Comput. Pub Date : 2019-04-03 DOI: 10.1142/S1793351X19400038

Somang Nam, D. Fels

引用次数: 2

Knowledge Extraction of Adaptive Structural Learning of Deep Belief Network for Medical Examination Data 医学检查数据深度信念网络自适应结构学习的知识提取

Int. J. Semantic Comput. Pub Date : 2019-04-03 DOI: 10.1142/S1793351X1940004X

Shin Kamada, T. Ichimura, T. Harada

{"title":"Knowledge Extraction of Adaptive Structural Learning of Deep Belief Network for Medical Examination Data","authors":"Shin Kamada, T. Ichimura, T. Harada","doi":"10.1142/S1793351X1940004X","DOIUrl":"https://doi.org/10.1142/S1793351X1940004X","url":null,"abstract":"Deep learning has a hierarchical network structure to represent multiple features of input data. The adaptive structural learning method of Deep Belief Network (DBN) can reach the high classification capability while searching the optimal network structure during the training. The method can find the optimal number of hidden neurons for given input data in a Restricted Boltzmann Machine (RBM) by neuron generation–annihilation algorithm, and generate a new hidden layer in DBN by the extension of the algorithm. In this paper, the proposed adaptive structural learning of DBN (Adaptive DBN) was applied to the comprehensive medical examination data for cancer prediction. The developed prediction system showed higher classification accuracy for test data (99.5% for the lung cancer and 94.3% for the stomach cancer) than the several learning methods such as traditional RBM, DBN, Non-Linear Support Vector Machine (SVM), and Convolutional Neural Network (CNN). Moreover, the explicit knowledge that makes the inference process of the trained DBN is required in deep learning. The binary patterns of activated neurons for given input in RBM and the hierarchical structure of DBN can represent the relation between input and output signals. These binary patterns were classified by C4.5 for knowledge extraction. Although the extracted knowledge showed slightly lower classification accuracy than the trained DBN network, it was able to improve inference speed by about 1/40. We report that the extracted IF-THEN rules from the trained DBN for medical examination data showed some interesting features related to initial condition of cancer.","PeriodicalId":217956,"journal":{"name":"Int. J. Semantic Comput.","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130074628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 12