Pub Date : 2018-07-01DOI: 10.1109/ICKII.2018.8569187
Zainal Abideen, H. Tariq, Sajjad Hussain Shah Talha Naqash, Umarah Qaseem
It is certain that the future of the network will be the mobile utter. Google‘s Android platform is a widely forecast open source operating system for mobile phones. This article is about Android‘s security model and seeks to reveal the complexity of secure application development, identifying lessons and opportunities for future enhancements. This article provides a secure way to download an application and managing access permission for using the Android mobile phone. Following article shows how to download an application without virus or secure user android in a convenient way. This application provides user to manage the access permissions both automatically and manually. The user can access permissions when the user installs an application or user can manually go to settings and update the permissions. Thus, we provide a permission system through which uses android devices can propose abstract authorization rules, provide high- level rules and learn user privacy preferences. Therefore, concepts and approaches towards effective privacy management for mobile platforms are reviewed.
{"title":"Android Apps Management System to Ensure Mobile Security","authors":"Zainal Abideen, H. Tariq, Sajjad Hussain Shah Talha Naqash, Umarah Qaseem","doi":"10.1109/ICKII.2018.8569187","DOIUrl":"https://doi.org/10.1109/ICKII.2018.8569187","url":null,"abstract":"It is certain that the future of the network will be the mobile utter. Google‘s Android platform is a widely forecast open source operating system for mobile phones. This article is about Android‘s security model and seeks to reveal the complexity of secure application development, identifying lessons and opportunities for future enhancements. This article provides a secure way to download an application and managing access permission for using the Android mobile phone. Following article shows how to download an application without virus or secure user android in a convenient way. This application provides user to manage the access permissions both automatically and manually. The user can access permissions when the user installs an application or user can manually go to settings and update the permissions. Thus, we provide a permission system through which uses android devices can propose abstract authorization rules, provide high- level rules and learn user privacy preferences. Therefore, concepts and approaches towards effective privacy management for mobile platforms are reviewed.","PeriodicalId":170587,"journal":{"name":"2018 1st IEEE International Conference on Knowledge Innovation and Invention (ICKII)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123761841","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}
Pub Date : 2018-07-01DOI: 10.1109/ICKII.2018.8569209
Maryli F. Rosas, Shaneth C. Ambat, Melvin A. Ballera
Students' insights are very vital in the continuous quality improvement of a university. Students are the primary consumers in higher education institution services [1].One way to measure the quality of education is through the satisfaction level of the students based on students' overall university experience. Implementation of logistic regression and CHAID Algorithm was used to create the recommendation plan.Text analytics was integrated to extract key phrases and compute sentiment score to classify the comments according to satisfaction level.
{"title":"Data Mining of Students' Response on the University Services using Chi-square Automatic Interaction Detector (CHAID) Algorithm","authors":"Maryli F. Rosas, Shaneth C. Ambat, Melvin A. Ballera","doi":"10.1109/ICKII.2018.8569209","DOIUrl":"https://doi.org/10.1109/ICKII.2018.8569209","url":null,"abstract":"Students' insights are very vital in the continuous quality improvement of a university. Students are the primary consumers in higher education institution services [1].One way to measure the quality of education is through the satisfaction level of the students based on students' overall university experience. Implementation of logistic regression and CHAID Algorithm was used to create the recommendation plan.Text analytics was integrated to extract key phrases and compute sentiment score to classify the comments according to satisfaction level.","PeriodicalId":170587,"journal":{"name":"2018 1st IEEE International Conference on Knowledge Innovation and Invention (ICKII)","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122465833","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}
Pub Date : 2018-07-01DOI: 10.1109/ICKII.2018.8569083
K. Yen, Pei-Jung Lee
Taiwan belongs to the sea island type climate. The emergence probability of natural disaster is very high. This research aims to set up the database on the disaster prevention planning particularly for the Hsinchu Science Park, it includes the compiling of information on the disaster prevention spatial ability based on the survey results of the current disaster prevention resources and also aims to obtain the hazard susceptibility spatial information via analysis of the simulation of compound disasters.
{"title":"An Evaluation of Potential Use of Land Resources in Response to Disasters – a Case Study of Hsinchu, Taiwan","authors":"K. Yen, Pei-Jung Lee","doi":"10.1109/ICKII.2018.8569083","DOIUrl":"https://doi.org/10.1109/ICKII.2018.8569083","url":null,"abstract":"Taiwan belongs to the sea island type climate. The emergence probability of natural disaster is very high. This research aims to set up the database on the disaster prevention planning particularly for the Hsinchu Science Park, it includes the compiling of information on the disaster prevention spatial ability based on the survey results of the current disaster prevention resources and also aims to obtain the hazard susceptibility spatial information via analysis of the simulation of compound disasters.","PeriodicalId":170587,"journal":{"name":"2018 1st IEEE International Conference on Knowledge Innovation and Invention (ICKII)","volume":"182 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121753370","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}
Pub Date : 2018-07-01DOI: 10.1109/ICKII.2018.8569113
Minsu Kim, A. Anpalagan
As the amount of network traffic is growing exponentially, traffic analysis and classification are playing a significant role for efficient resource allocation and network management. However, with emerging security technologies, this work is becoming more difficult by encrypted communication such as Tor, which is one of the most popular encryption techniques. This paper proposes an approach to classify Tor traffic using hexadecimal raw packet header and convolutional neural network model. Comparing with competitive machine learning algorithms, our approach shows a remarkable accuracy. To validate this method publicly, we use UNB-CIC Tor network traffic dataset. Based on the experiments, our approach shows 99.3% accuracy for the fractionized Tor/non-Tor traffic classification.
{"title":"Tor Traffic Classification from Raw Packet Header using Convolutional Neural Network","authors":"Minsu Kim, A. Anpalagan","doi":"10.1109/ICKII.2018.8569113","DOIUrl":"https://doi.org/10.1109/ICKII.2018.8569113","url":null,"abstract":"As the amount of network traffic is growing exponentially, traffic analysis and classification are playing a significant role for efficient resource allocation and network management. However, with emerging security technologies, this work is becoming more difficult by encrypted communication such as Tor, which is one of the most popular encryption techniques. This paper proposes an approach to classify Tor traffic using hexadecimal raw packet header and convolutional neural network model. Comparing with competitive machine learning algorithms, our approach shows a remarkable accuracy. To validate this method publicly, we use UNB-CIC Tor network traffic dataset. Based on the experiments, our approach shows 99.3% accuracy for the fractionized Tor/non-Tor traffic classification.","PeriodicalId":170587,"journal":{"name":"2018 1st IEEE International Conference on Knowledge Innovation and Invention (ICKII)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132837177","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}
Pub Date : 2018-07-01DOI: 10.1109/ICKII.2018.8569050
H. Chang, Y. Hsueh, C. Lo
In recent years, the Functional Movement Screen (abbreviation: FMS) has been used to assess athletes’ movement patterns and quality in recent years. However, the score of FMS system are assessed by manual observation. Therefore, the purpose of this study is to develop an automatic Image-capture and angle tracking system to assist and asses the movement pattern for athletes by comparing the results when using self-made angle tracking system and free Kinovea motion analysis system during performing the FMS screen. Twelve volleyball athletes and 12 track and field athletes are recruited in our study. Two webcams were placed in front and on the side of FMS equipment to capture the image and body angles respectively. In addition, one of the researchers manually loaded the recorded image into free motion analysis software (Kinovea, Vision 8.25) to capture and mark the angle. The results were shown that a moderate to high positive correlation of the joint angles between 2 systems in most of the FMS movement patterns $(plt.05)$. When compared with the volleyball and track and field athletes, there were significantly different in the hip and ankle angle of deep squat, the hip and knee angle of the in-line lunge, and shank angle of hurdle step $(plt.05)$. In conclusion, the advantage of the automatic image-capture and angle tracking system applied on FMS are included automatic image recognition and labelled, fast and accuracy of angle tracking, data reports exported, and inexpensive equipment. The automatic image-capture and angle tracking system can assist the FMS to evaluate the bilateral limb or torso deficit or asymmetric in various sports.
近年来，功能性运动量表(Functional Movement Screen，简称FMS)被广泛应用于运动员运动模式和运动质量的评估。然而，FMS系统的评分是通过人工观察来评定的。因此，本研究的目的是开发一种自动图像捕获和角度跟踪系统，通过比较自制角度跟踪系统和免费Kinovea运动分析系统在FMS屏幕表演过程中的结果，来辅助和评估运动员的运动模式。我们的研究招募了12名排球运动员和12名田径运动员。在FMS设备的前部和侧面分别放置两个网络摄像头，分别捕捉图像和身体角度。此外，其中一名研究人员手动将记录的图像加载到自由运动分析软件(Kinovea, Vision 8.25)中，以捕获和标记角度。结果表明，在大多数FMS运动模式中，两个系统之间的关节角具有中等到高度的正相关关系$(plt.05)$。与排球、田径运动员相比，深蹲髋、踝关节角度、直线弓步髋、膝关节角度、跨栏步小腿角度均有显著差异(plt.05)。综上所述，应用于FMS的自动图像捕获和角度跟踪系统具有图像自动识别和标记、角度跟踪快速准确、数据报告输出、设备价格低廉等优点。自动图像捕获和角度跟踪系统可以帮助FMS评估各种运动中的双侧肢体或躯干缺陷或不对称。
{"title":"Automatic Image-Capture and Angle Tracking System Applied on Functional Movement Screening for Athletes","authors":"H. Chang, Y. Hsueh, C. Lo","doi":"10.1109/ICKII.2018.8569050","DOIUrl":"https://doi.org/10.1109/ICKII.2018.8569050","url":null,"abstract":"In recent years, the Functional Movement Screen (abbreviation: FMS) has been used to assess athletes’ movement patterns and quality in recent years. However, the score of FMS system are assessed by manual observation. Therefore, the purpose of this study is to develop an automatic Image-capture and angle tracking system to assist and asses the movement pattern for athletes by comparing the results when using self-made angle tracking system and free Kinovea motion analysis system during performing the FMS screen. Twelve volleyball athletes and 12 track and field athletes are recruited in our study. Two webcams were placed in front and on the side of FMS equipment to capture the image and body angles respectively. In addition, one of the researchers manually loaded the recorded image into free motion analysis software (Kinovea, Vision 8.25) to capture and mark the angle. The results were shown that a moderate to high positive correlation of the joint angles between 2 systems in most of the FMS movement patterns $(plt.05)$. When compared with the volleyball and track and field athletes, there were significantly different in the hip and ankle angle of deep squat, the hip and knee angle of the in-line lunge, and shank angle of hurdle step $(plt.05)$. In conclusion, the advantage of the automatic image-capture and angle tracking system applied on FMS are included automatic image recognition and labelled, fast and accuracy of angle tracking, data reports exported, and inexpensive equipment. The automatic image-capture and angle tracking system can assist the FMS to evaluate the bilateral limb or torso deficit or asymmetric in various sports.","PeriodicalId":170587,"journal":{"name":"2018 1st IEEE International Conference on Knowledge Innovation and Invention (ICKII)","volume":"212 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115508524","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}
Pub Date : 2018-07-01DOI: 10.1109/ICKII.2018.8569117
Chen Li
As the population of older adults in society rises, the importance of ubiquitous technology to assist health management and healthcare is growing with the demographic shift. Smart devices with multiple sensors in everyday life have been the common solution proposed by related projects to fulfil the needs of older users. However, ubiquitous computing can also change the paradigm in which notifications are delivered to users. Notification mechanisms are a key factor in interaction design to provide older adults health awareness. Since older users are both active and sensitive to health problems, good awareness mechanisms should provide seamlessly interactions with technology into their everyday routines. Inspired by influential early visions on ubiquitous computing, we conduct an experimental research within a smart cushion project that reminded older adults‘ sedentary lifestyle in two everyday scenarios through different notification modalities. Based on the experimental results, we introduce a contextual notification mechanism called Calm Sensing. Calm Sensing Design identifies the effectiveness and disruptiveness of notification modalities at varied channels of human sensory, these being heat, odour, sound, vibration and message. we conclude that good notification mechanism should have the ability to switch among older adults‘ multi-sensory for different their daily activities. We suggest that heat and odour have potential to be alternatives instead of familiar sound and vibration to give just-in-time information and avoiding disruptiveness.
{"title":"Calm Sensing Design: A Contextual Notification Mechanism to Support Older User‘s Health Awareness","authors":"Chen Li","doi":"10.1109/ICKII.2018.8569117","DOIUrl":"https://doi.org/10.1109/ICKII.2018.8569117","url":null,"abstract":"As the population of older adults in society rises, the importance of ubiquitous technology to assist health management and healthcare is growing with the demographic shift. Smart devices with multiple sensors in everyday life have been the common solution proposed by related projects to fulfil the needs of older users. However, ubiquitous computing can also change the paradigm in which notifications are delivered to users. Notification mechanisms are a key factor in interaction design to provide older adults health awareness. Since older users are both active and sensitive to health problems, good awareness mechanisms should provide seamlessly interactions with technology into their everyday routines. Inspired by influential early visions on ubiquitous computing, we conduct an experimental research within a smart cushion project that reminded older adults‘ sedentary lifestyle in two everyday scenarios through different notification modalities. Based on the experimental results, we introduce a contextual notification mechanism called Calm Sensing. Calm Sensing Design identifies the effectiveness and disruptiveness of notification modalities at varied channels of human sensory, these being heat, odour, sound, vibration and message. we conclude that good notification mechanism should have the ability to switch among older adults‘ multi-sensory for different their daily activities. We suggest that heat and odour have potential to be alternatives instead of familiar sound and vibration to give just-in-time information and avoiding disruptiveness.","PeriodicalId":170587,"journal":{"name":"2018 1st IEEE International Conference on Knowledge Innovation and Invention (ICKII)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122033926","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}
Pub Date : 2018-07-01DOI: 10.1109/ICKII.2018.8569207
Jing Su, Yi-Chi Huang, Jia-Li Yin, Bo-Hao Chen, Shenming Qu
With the growing concern for power-hungry on mobile devices, many power constrained contrast enhancement algorithms have been developed in the mobile devices embedded with emissive displays, such as organic light-emitting diodes. However, conventional power constrained contrast enhancement algorithms inevitably degrade the visual aesthetics of images as a trade-off to gain the power-saving for mobile devices. This paper proposes a trainable power-constrained contrast enhancement algorithm based on a saliency-guided deep framework for suppressing the power consumption of an image while preserving its perceptual quality. Our algorithm relies on the fact that imaging features of a displayed image is salient to human visual perception. Hence, we decompose the input image into the imaging features and textual features with a deep convolutional neural networks, and degrade those textual features to achieve the suppression of power consumption. Experimental results demonstrate that our algorithm is able to maintain visual aesthetics of images while reducing the power consumption effectively, outperforming conventional power-constrained contrast enhancement algorithms.
{"title":"Saliency-Guided Deep Framework for Power Consumption Suppressing on Mobile Devices","authors":"Jing Su, Yi-Chi Huang, Jia-Li Yin, Bo-Hao Chen, Shenming Qu","doi":"10.1109/ICKII.2018.8569207","DOIUrl":"https://doi.org/10.1109/ICKII.2018.8569207","url":null,"abstract":"With the growing concern for power-hungry on mobile devices, many power constrained contrast enhancement algorithms have been developed in the mobile devices embedded with emissive displays, such as organic light-emitting diodes. However, conventional power constrained contrast enhancement algorithms inevitably degrade the visual aesthetics of images as a trade-off to gain the power-saving for mobile devices. This paper proposes a trainable power-constrained contrast enhancement algorithm based on a saliency-guided deep framework for suppressing the power consumption of an image while preserving its perceptual quality. Our algorithm relies on the fact that imaging features of a displayed image is salient to human visual perception. Hence, we decompose the input image into the imaging features and textual features with a deep convolutional neural networks, and degrade those textual features to achieve the suppression of power consumption. Experimental results demonstrate that our algorithm is able to maintain visual aesthetics of images while reducing the power consumption effectively, outperforming conventional power-constrained contrast enhancement algorithms.","PeriodicalId":170587,"journal":{"name":"2018 1st IEEE International Conference on Knowledge Innovation and Invention (ICKII)","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124360032","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}
Pub Date : 2018-07-01DOI: 10.1109/ICKII.2018.8569065
Kwangsuk Lee, Jae-Kyeong Kim, Jaehyong Kim, K. Hur, Hagbae Kim
This paper proposes a multi-layered anomaly detection scheme to train feature extraction and to test anomaly prediction by using Convolutional Neural Networks (CNNs) layer, Bidirectional and Unidirectional Long Short-Term Memory (LSTM) Recurrent Neural Networks (RNNs), which is one of a novel deep architecture named stacked convolutional bidirectional LSTM network (SCB-LSTM). In the proposed model, the stacked CNNs perform feature extraction of vibration sensor signal patterns, and the result is used to feature learning with the stacked bidirectional LSTMs (SB-LSTMs). After this procedure, the stacked unidirectional LSTMs (SU-LSTMs) enhance the feature learning, and a regression layer finally predicts anomaly detections. The experimental results of bearing data not only show the accuracy of the proposed model in anomaly detection for rotating machinery diagnostics, but also suggest the better performance than other state-of-the-art algorithms such as a plain uni-LSTM or Bi-LSTM.
本文提出了一种多层异常检测方案，利用卷积神经网络(cnn)层双向和单向长短期记忆(LSTM)递归神经网络(RNNs)进行特征提取训练和异常预测测试，这是一种新型的深度体系结构，称为堆叠卷积双向LSTM网络(SCB-LSTM)。在该模型中，堆叠cnn对振动传感器信号模式进行特征提取，并将结果用于堆叠双向lstm (sb - lstm)的特征学习。在此过程之后，堆叠的单向lstm (su - lstm)增强了特征学习，并最终通过回归层预测异常检测。轴承数据的实验结果不仅表明了该模型在旋转机械诊断异常检测中的准确性，而且表明该模型的性能优于其他最先进的算法，如普通的uni-LSTM或Bi-LSTM。
{"title":"Stacked Convolutional Bidirectional LSTM Recurrent Neural Network for Bearing Anomaly Detection in Rotating Machinery Diagnostics","authors":"Kwangsuk Lee, Jae-Kyeong Kim, Jaehyong Kim, K. Hur, Hagbae Kim","doi":"10.1109/ICKII.2018.8569065","DOIUrl":"https://doi.org/10.1109/ICKII.2018.8569065","url":null,"abstract":"This paper proposes a multi-layered anomaly detection scheme to train feature extraction and to test anomaly prediction by using Convolutional Neural Networks (CNNs) layer, Bidirectional and Unidirectional Long Short-Term Memory (LSTM) Recurrent Neural Networks (RNNs), which is one of a novel deep architecture named stacked convolutional bidirectional LSTM network (SCB-LSTM). In the proposed model, the stacked CNNs perform feature extraction of vibration sensor signal patterns, and the result is used to feature learning with the stacked bidirectional LSTMs (SB-LSTMs). After this procedure, the stacked unidirectional LSTMs (SU-LSTMs) enhance the feature learning, and a regression layer finally predicts anomaly detections. The experimental results of bearing data not only show the accuracy of the proposed model in anomaly detection for rotating machinery diagnostics, but also suggest the better performance than other state-of-the-art algorithms such as a plain uni-LSTM or Bi-LSTM.","PeriodicalId":170587,"journal":{"name":"2018 1st IEEE International Conference on Knowledge Innovation and Invention (ICKII)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124024364","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}
In recent years in Taiwan, advances in interactive technology, the evolution of interdisciplinary creation trends, digital technology and performances that transcend traditional boundaries have combined to form a new type of technology performances arts field. This study explores connections between visual technology and performance praxis in the technology performance arts of interdisciplinary collaborations, aesthetic characteristics, and possible future trends.
{"title":"Interdisciplinary praxis in Interactive Visual and Dance: A Case Study of Nu Shu GPS","authors":"Yun-Ju Chen, Ping-Yeh Li, Ruey-Sen Chiu, Ya-Kuan Chou","doi":"10.1109/ICKII.2018.8569086","DOIUrl":"https://doi.org/10.1109/ICKII.2018.8569086","url":null,"abstract":"In recent years in Taiwan, advances in interactive technology, the evolution of interdisciplinary creation trends, digital technology and performances that transcend traditional boundaries have combined to form a new type of technology performances arts field. This study explores connections between visual technology and performance praxis in the technology performance arts of interdisciplinary collaborations, aesthetic characteristics, and possible future trends.","PeriodicalId":170587,"journal":{"name":"2018 1st IEEE International Conference on Knowledge Innovation and Invention (ICKII)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125255319","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}
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