Activity Recognition (AR), Internet of Things (IoT), and speech recognition are emerging technologies in the context of wearable devices and Mobile health (mHealth) networks. Applications of mHealth sensors on human bodies can involve the measurement of physiological data, and may be utilized to initiate an alarm in an emergency health situation. AR devices such as accelerometers may also be used for a similar application in determining the activity and posture status of the user. However, there is always the possibility of false alarms, and to avoid these occurrences, we propose a user feedback system for alarm confirmation via a smart device. As users may be unable to physically respond in some situations, such as a state of immobility from injury, this paper proposes to improve the user feedback system with a voice confirmation functionality utilizing speech recognition embedded within smart devices. The potentials of this user feedback system in mHealth can not only contribute towards improve the alarm accuracy, but may reduce the occurrence of false alarms. Its functionality can also be enhanced via real-time communication with their health service provider who can assess the user health status with the data from the sensors.
{"title":"User Feedback System for Emergency Alarms in Mobile Health Networks","authors":"James Jin Kang","doi":"10.1145/3127942.3127964","DOIUrl":"https://doi.org/10.1145/3127942.3127964","url":null,"abstract":"Activity Recognition (AR), Internet of Things (IoT), and speech recognition are emerging technologies in the context of wearable devices and Mobile health (mHealth) networks. Applications of mHealth sensors on human bodies can involve the measurement of physiological data, and may be utilized to initiate an alarm in an emergency health situation. AR devices such as accelerometers may also be used for a similar application in determining the activity and posture status of the user. However, there is always the possibility of false alarms, and to avoid these occurrences, we propose a user feedback system for alarm confirmation via a smart device. As users may be unable to physically respond in some situations, such as a state of immobility from injury, this paper proposes to improve the user feedback system with a voice confirmation functionality utilizing speech recognition embedded within smart devices. The potentials of this user feedback system in mHealth can not only contribute towards improve the alarm accuracy, but may reduce the occurrence of false alarms. Its functionality can also be enhanced via real-time communication with their health service provider who can assess the user health status with the data from the sensors.","PeriodicalId":270425,"journal":{"name":"Proceedings of the 1st International Conference on Algorithms, Computing and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128288220","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}
Recently, a modified zeroing neural network (MZNN) model has been presented for solving quadratic programming problems, which is of noise-tolerant ability. In this paper, we conduct further investigations on such a model and then present a nonlinear function activated model. Finally, the presented nonlinear function activated model is applied to the motion control of robots.
{"title":"Further Investigations on Noise-Tolerant Zeroing Neural Network for Time-Varying Quadratic Programming with Robotic Applications","authors":"Mei Liu, Shuai Li, Yinyan Zhang, Long Jin","doi":"10.1145/3127942.3127956","DOIUrl":"https://doi.org/10.1145/3127942.3127956","url":null,"abstract":"Recently, a modified zeroing neural network (MZNN) model has been presented for solving quadratic programming problems, which is of noise-tolerant ability. In this paper, we conduct further investigations on such a model and then present a nonlinear function activated model. Finally, the presented nonlinear function activated model is applied to the motion control of robots.","PeriodicalId":270425,"journal":{"name":"Proceedings of the 1st International Conference on Algorithms, Computing and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134204001","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}
Web audio technologies have recently been greatly developed by web developers and software companies, providing web audio libraries and frameworks for audio processing and synthesizing using JavaScript. JavaScript has developed into flexible programming language with front end and server side capabilities, providing dynamic interactions with the web. This paper describes a united sound library and framework system developed using web technologies with JavaScript for musical instruments and voice through a web audio API for artistic expression and various musical applications.
{"title":"DrSax.js: a JavaScript based Unified Web Audio Library and Framework","authors":"Euyshick Hong, Jun Kim","doi":"10.1145/3127942.3127953","DOIUrl":"https://doi.org/10.1145/3127942.3127953","url":null,"abstract":"Web audio technologies have recently been greatly developed by web developers and software companies, providing web audio libraries and frameworks for audio processing and synthesizing using JavaScript. JavaScript has developed into flexible programming language with front end and server side capabilities, providing dynamic interactions with the web. This paper describes a united sound library and framework system developed using web technologies with JavaScript for musical instruments and voice through a web audio API for artistic expression and various musical applications.","PeriodicalId":270425,"journal":{"name":"Proceedings of the 1st International Conference on Algorithms, Computing and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130253244","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}
Jinseong Kim, Younchang Choi, Miso Ju, J. Sa, Yongwha Chung, Daihee Park, Hakjae Kim
In a surveillance camera environment, detecting pigs in a pig room is an important issue in terms of automatic management. In addition, it is important to analyze the area of lying-pigs in order to estimate the temperature of a pig room. However, it is difficult to recognize whether the pigs are lying or standing from RGB data because the data do not have any height information. In this study, we propose a method to detect lying-pigs by using depth information obtained from a 3D Kinect camera. According to the experimental results, we confirmed that the proposed method could detect lying-pigs by using a difference of the depth information between pigs and floor.
{"title":"Lying-Pig Detection using Depth Information","authors":"Jinseong Kim, Younchang Choi, Miso Ju, J. Sa, Yongwha Chung, Daihee Park, Hakjae Kim","doi":"10.1145/3127942.3127949","DOIUrl":"https://doi.org/10.1145/3127942.3127949","url":null,"abstract":"In a surveillance camera environment, detecting pigs in a pig room is an important issue in terms of automatic management. In addition, it is important to analyze the area of lying-pigs in order to estimate the temperature of a pig room. However, it is difficult to recognize whether the pigs are lying or standing from RGB data because the data do not have any height information. In this study, we propose a method to detect lying-pigs by using depth information obtained from a 3D Kinect camera. According to the experimental results, we confirmed that the proposed method could detect lying-pigs by using a difference of the depth information between pigs and floor.","PeriodicalId":270425,"journal":{"name":"Proceedings of the 1st International Conference on Algorithms, Computing and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115387309","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}
Show-Jane Yen, Yue-Shi Lee, Li-Tien Wang, Yeuan-Kuen Lee
In today's e-commerce environment, Collaborative Filtering (CF) is a widely used algorithm for recommender system, which is to identify the users who have similar preferences to the target user, and to predict the preference of the target user according to the preference ratings of the similar users. However, if the preference ratings of the target user are rare or none, then it cannot effectively identify the users with the similar preferences to the target user. In order to solve the problem of collaborative filtering, this study uses the implicit rating method to automatically calculate the user preference for the items by using the transaction data of the users, and further constructs an item-to-item, user-to-user, and user-to-item relationships, which can be used to calculate the preference rating for the target user, and recommend the products to the target user. The experimental results also show that the recommendation accuracy of our algorithm is higher than the other algorithms on average.
{"title":"A New Approach for Recommender System","authors":"Show-Jane Yen, Yue-Shi Lee, Li-Tien Wang, Yeuan-Kuen Lee","doi":"10.1145/3127942.3127943","DOIUrl":"https://doi.org/10.1145/3127942.3127943","url":null,"abstract":"In today's e-commerce environment, Collaborative Filtering (CF) is a widely used algorithm for recommender system, which is to identify the users who have similar preferences to the target user, and to predict the preference of the target user according to the preference ratings of the similar users. However, if the preference ratings of the target user are rare or none, then it cannot effectively identify the users with the similar preferences to the target user. In order to solve the problem of collaborative filtering, this study uses the implicit rating method to automatically calculate the user preference for the items by using the transaction data of the users, and further constructs an item-to-item, user-to-user, and user-to-item relationships, which can be used to calculate the preference rating for the target user, and recommend the products to the target user. The experimental results also show that the recommendation accuracy of our algorithm is higher than the other algorithms on average.","PeriodicalId":270425,"journal":{"name":"Proceedings of the 1st International Conference on Algorithms, Computing and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121998205","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}
Jerome Domingo, Cara B. Francisco, K. Reyes, M. Sison, I. V. R. Domingo
Machine translation, using the transfer approach, generally follows different phases: morphology, syntax, and semantics. Morphology refers to the study of the structure of words or how words are formed [6]. Syntax deals with how words can be combined together to make larger phrases, such as, sentences. Semantics deals with real world knowledge or the meaning of the sentence [7]. The system compared content of up to thirty essay text files. It has the similarity computations using Prototyping Model as a software engineering paradigm in developing SimC.
{"title":"Context Comparison of Essay-Type Text Files","authors":"Jerome Domingo, Cara B. Francisco, K. Reyes, M. Sison, I. V. R. Domingo","doi":"10.1145/3127942.3127962","DOIUrl":"https://doi.org/10.1145/3127942.3127962","url":null,"abstract":"Machine translation, using the transfer approach, generally follows different phases: morphology, syntax, and semantics. Morphology refers to the study of the structure of words or how words are formed [6]. Syntax deals with how words can be combined together to make larger phrases, such as, sentences. Semantics deals with real world knowledge or the meaning of the sentence [7]. The system compared content of up to thirty essay text files. It has the similarity computations using Prototyping Model as a software engineering paradigm in developing SimC.","PeriodicalId":270425,"journal":{"name":"Proceedings of the 1st International Conference on Algorithms, Computing and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122321491","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}
Recently, emotion recognition has gained increasing attention in various applications related to Social Signal Processing (SSP) and human affect. The existing research is mainly focused on six basic emotions (happy, sad, fear, disgust, angry, and surprise). However human expresses many kind of emotions, including mix emotion which has not been explored due to its complexity. We model 12 types of mix emotion recognition from facial expression in a sequence of images using two-stages learning which combines Support Vector Machines (SVM) and Conditional Random Fields (CRF) as sequence classifiers. SVM classifies each image frame and produce emotion label output, subsequently it becomes the input for CRF which yields the mix emotion label of the corresponding observation sequence. We evaluate our proposed model on modified image frames of Cohn Kanade+ dataset, and on our own made mix emotion dataset. We also compare our model with the original CRF model, and our model shows a superior performance result.
{"title":"Mix Emotion Recognition from Facial Expression using SVM-CRF Sequence Classifier","authors":"D. Liliana, Chan Basaruddin, M. R. Widyanto","doi":"10.1145/3127942.3127958","DOIUrl":"https://doi.org/10.1145/3127942.3127958","url":null,"abstract":"Recently, emotion recognition has gained increasing attention in various applications related to Social Signal Processing (SSP) and human affect. The existing research is mainly focused on six basic emotions (happy, sad, fear, disgust, angry, and surprise). However human expresses many kind of emotions, including mix emotion which has not been explored due to its complexity. We model 12 types of mix emotion recognition from facial expression in a sequence of images using two-stages learning which combines Support Vector Machines (SVM) and Conditional Random Fields (CRF) as sequence classifiers. SVM classifies each image frame and produce emotion label output, subsequently it becomes the input for CRF which yields the mix emotion label of the corresponding observation sequence. We evaluate our proposed model on modified image frames of Cohn Kanade+ dataset, and on our own made mix emotion dataset. We also compare our model with the original CRF model, and our model shows a superior performance result.","PeriodicalId":270425,"journal":{"name":"Proceedings of the 1st International Conference on Algorithms, Computing and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133856655","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}
This research investigates the large hype surrounding big data (BD) and Analytics (BDA) in both academia and the business world. Initial insights pointed to large and complex amalgamations of different fields, techniques and tools. Above all, BD as a research field and as a business tool found to be under developing and is fraught with many challenges. The intention here in this research is to develop an adoption model of BD that could detect key success predictors. The research finds a great interest and optimism about BD value that fueled this current buzz behind this novel phenomenon. Like any disruptive innovation, its assimilation in organizations oppressed with many challenges at various contextual levels. BD would provide different advantages to organizations that would seriously consider all its perspectives alongside its lifecycle in the pre-adoption or adoption or implementation phases. The research attempts to delineate the different facets of BD as a technology and as a management tool highlighting different contributions, implications and recommendations. This is of great interest to researchers, professional and policy makers.
{"title":"Determinants of Big Data Adoption and Success","authors":"N. Al-Qirim, A. Tarhini, K. Rouibah","doi":"10.1145/3127942.3127961","DOIUrl":"https://doi.org/10.1145/3127942.3127961","url":null,"abstract":"This research investigates the large hype surrounding big data (BD) and Analytics (BDA) in both academia and the business world. Initial insights pointed to large and complex amalgamations of different fields, techniques and tools. Above all, BD as a research field and as a business tool found to be under developing and is fraught with many challenges. The intention here in this research is to develop an adoption model of BD that could detect key success predictors. The research finds a great interest and optimism about BD value that fueled this current buzz behind this novel phenomenon. Like any disruptive innovation, its assimilation in organizations oppressed with many challenges at various contextual levels. BD would provide different advantages to organizations that would seriously consider all its perspectives alongside its lifecycle in the pre-adoption or adoption or implementation phases. The research attempts to delineate the different facets of BD as a technology and as a management tool highlighting different contributions, implications and recommendations. This is of great interest to researchers, professional and policy makers.","PeriodicalId":270425,"journal":{"name":"Proceedings of the 1st International Conference on Algorithms, Computing and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132940883","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 last few years, a musical application has developed by developer and computer software company such as sound effects, midi controller, musical instrument for music playing and collaborate musical works in mobile, tablet PC with iPhone or Android. Especially, by Web technologies, Web audio application with Web Audio API have expeditiously studied thought JavaScript that possibility of novel and flexible language. The Webxophone is a web wind instrument designed for mobile with the web and mobile technologies that microphone input (for blowing), multitouch (for fingering button), Gyro sensors, sound processing and synthesis in real-time on the web without install. This paper aims to present a web wind instrument application like saxophone through Web Audio API with JavaScript for musical expression and various musical performance.
{"title":"Webxophone: Web Audio wind instrument","authors":"Euyshick Hong, Jun Kim","doi":"10.1145/3127942.3127954","DOIUrl":"https://doi.org/10.1145/3127942.3127954","url":null,"abstract":"In last few years, a musical application has developed by developer and computer software company such as sound effects, midi controller, musical instrument for music playing and collaborate musical works in mobile, tablet PC with iPhone or Android. Especially, by Web technologies, Web audio application with Web Audio API have expeditiously studied thought JavaScript that possibility of novel and flexible language. The Webxophone is a web wind instrument designed for mobile with the web and mobile technologies that microphone input (for blowing), multitouch (for fingering button), Gyro sensors, sound processing and synthesis in real-time on the web without install. This paper aims to present a web wind instrument application like saxophone through Web Audio API with JavaScript for musical expression and various musical performance.","PeriodicalId":270425,"journal":{"name":"Proceedings of the 1st International Conference on Algorithms, Computing and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131973210","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}
This paper presents a natural language processing (NLP) approach to construct signs and symptoms corpus in order to identify signs and symptoms recoded in a Thai chief complains (CCs) based on the International Statistical Classification of Diseases and Related Health Problems 10th Revision (ICD-10) form. We define our native language "Thai language" as the natural language in our works thus the challenge is how to apply NLP concept that is originally designed for English language. We start from tokenization to extract Thai token from Thai chief complains, and then the tokens is analyzed in order to assigning a specific tag in terms of ICD-10 code.
{"title":"Signs and Symptoms Tagging for Thai Chief Complaints Based on ICD-10","authors":"Pawin Saeku, Jarunee Duangsuwan","doi":"10.1145/3127942.3127957","DOIUrl":"https://doi.org/10.1145/3127942.3127957","url":null,"abstract":"This paper presents a natural language processing (NLP) approach to construct signs and symptoms corpus in order to identify signs and symptoms recoded in a Thai chief complains (CCs) based on the International Statistical Classification of Diseases and Related Health Problems 10th Revision (ICD-10) form. We define our native language \"Thai language\" as the natural language in our works thus the challenge is how to apply NLP concept that is originally designed for English language. We start from tokenization to extract Thai token from Thai chief complains, and then the tokens is analyzed in order to assigning a specific tag in terms of ICD-10 code.","PeriodicalId":270425,"journal":{"name":"Proceedings of the 1st International Conference on Algorithms, Computing and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134161097","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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