Pub Date : 2023-06-01DOI: 10.1109/COMPSAC57700.2023.00228
Erika Sugita, Ryosuke Abe, Shigeya Suzuki, K. Uehara, O. Nakamura
To receive effective treatment during emergency response due to seizures or unforeseen accidents, a patient with intractable diseases must disclose information about their disease to an emergency physician. If the patient loses consciousness while traveling, the patient should disclose this information to a companion in advance. However, disclosing this information to a companion is undesirable because the information is confidential. Thus, we propose a system that discloses specific information on intractable diseases only when an emergency physician has verified they possess a medical license. Otherwise, the proposed system only discloses appropriate first aid information. We implemented a prototype of the proposed under the assumption that a physician has a digital medical license based on verifiable credentials (i.e., a standard for digital credentials). With this system, the patient does not disclose confidential information to the patient’s companion but does disclose necessary information to the emergency physician.
{"title":"A System for Selective Disclosure of Information about a Patient with Intractable Disease","authors":"Erika Sugita, Ryosuke Abe, Shigeya Suzuki, K. Uehara, O. Nakamura","doi":"10.1109/COMPSAC57700.2023.00228","DOIUrl":"https://doi.org/10.1109/COMPSAC57700.2023.00228","url":null,"abstract":"To receive effective treatment during emergency response due to seizures or unforeseen accidents, a patient with intractable diseases must disclose information about their disease to an emergency physician. If the patient loses consciousness while traveling, the patient should disclose this information to a companion in advance. However, disclosing this information to a companion is undesirable because the information is confidential. Thus, we propose a system that discloses specific information on intractable diseases only when an emergency physician has verified they possess a medical license. Otherwise, the proposed system only discloses appropriate first aid information. We implemented a prototype of the proposed under the assumption that a physician has a digital medical license based on verifiable credentials (i.e., a standard for digital credentials). With this system, the patient does not disclose confidential information to the patient’s companion but does disclose necessary information to the emergency physician.","PeriodicalId":296288,"journal":{"name":"2023 IEEE 47th Annual Computers, Software, and Applications Conference (COMPSAC)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133854181","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 : 2023-06-01DOI: 10.1109/COMPSAC57700.2023.00066
Hongyi Zhang, Jingya Li, Z. Qi, Anders Aronsson, Jan Bosch, H. H. Olsson
Deep reinforcement learning has advanced signifi-cantly in recent years, and it is now used in embedded systems in addition to simulators and games. Reinforcement Learning (RL) algorithms are currently being used to enhance device operation so that they can learn on their own and offer clients better services. It has recently been studied in a variety of industrial applications. However, reinforcement learning, especially when controlling a large number of agents in an industrial environment, has been demonstrated to be unstable and unable to adapt to realistic situations when used in a real-world setting. To address this problem, the goal of this study is to enable multiple reinforcement learning agents to independently learn control policies on their own in dynamic industrial contexts. In order to solve the problem, we propose a dynamic multi-agent reinforcement learning (dynamic multi-RL) method along with adaptive exploration (AE) and vector-based action selection (VAS) techniques for accelerating model convergence and adapting to a complex industrial environment. The proposed algorithm is tested for validation in emergency situations within the telecommunications industry. In such circumstances, three unmanned aerial vehicles (UAV-BSs) are used to provide temporary coverage to mission-critical (MC) customers in disaster zones when the original serving base station (BS) is destroyed by natural disasters. The algorithm directs the participating agents automatically to enhance service quality. Our findings demonstrate that the proposed dynamic multi-RL algorithm can proficiently manage the learning of multiple agents and adjust to dynamic industrial environments. Additionally, it enhances learning speed and improves the quality of service.
{"title":"Multi-Agent Reinforcement Learning in Dynamic Industrial Context","authors":"Hongyi Zhang, Jingya Li, Z. Qi, Anders Aronsson, Jan Bosch, H. H. Olsson","doi":"10.1109/COMPSAC57700.2023.00066","DOIUrl":"https://doi.org/10.1109/COMPSAC57700.2023.00066","url":null,"abstract":"Deep reinforcement learning has advanced signifi-cantly in recent years, and it is now used in embedded systems in addition to simulators and games. Reinforcement Learning (RL) algorithms are currently being used to enhance device operation so that they can learn on their own and offer clients better services. It has recently been studied in a variety of industrial applications. However, reinforcement learning, especially when controlling a large number of agents in an industrial environment, has been demonstrated to be unstable and unable to adapt to realistic situations when used in a real-world setting. To address this problem, the goal of this study is to enable multiple reinforcement learning agents to independently learn control policies on their own in dynamic industrial contexts. In order to solve the problem, we propose a dynamic multi-agent reinforcement learning (dynamic multi-RL) method along with adaptive exploration (AE) and vector-based action selection (VAS) techniques for accelerating model convergence and adapting to a complex industrial environment. The proposed algorithm is tested for validation in emergency situations within the telecommunications industry. In such circumstances, three unmanned aerial vehicles (UAV-BSs) are used to provide temporary coverage to mission-critical (MC) customers in disaster zones when the original serving base station (BS) is destroyed by natural disasters. The algorithm directs the participating agents automatically to enhance service quality. Our findings demonstrate that the proposed dynamic multi-RL algorithm can proficiently manage the learning of multiple agents and adjust to dynamic industrial environments. Additionally, it enhances learning speed and improves the quality of service.","PeriodicalId":296288,"journal":{"name":"2023 IEEE 47th Annual Computers, Software, and Applications Conference (COMPSAC)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125248751","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 : 2023-06-01DOI: 10.1109/COMPSAC57700.2023.00154
Norihiro Okui, Yusuke Akimoto, A. Kubota, Takuya Yoshida
With the spread of Internet of Things (IoT) devices, countermeasures against cyber-attacks have become an issue. In this study, we focused on anomaly detection using flow data, which can reduce the data volume, and proposed a new anomaly detection method that combines a new graph composition method that represents a sequence of flow data as a graph and a graph neural network (GNN). Various detection methods, including deep learning, have been proposed for identifying malware such as denial-of-service (DoS) attacks, in which the characteristics of traffic deviate significantly from those of benign communications. We conducted an evaluation experiment with the proposed method using the KDDI-IoT-2019 dataset and discussed its effectiveness and limitations.
{"title":"A Graph Construction Method for Anomalous Traffic Detection with Graph Neural Networks Using Sets of Flow Data","authors":"Norihiro Okui, Yusuke Akimoto, A. Kubota, Takuya Yoshida","doi":"10.1109/COMPSAC57700.2023.00154","DOIUrl":"https://doi.org/10.1109/COMPSAC57700.2023.00154","url":null,"abstract":"With the spread of Internet of Things (IoT) devices, countermeasures against cyber-attacks have become an issue. In this study, we focused on anomaly detection using flow data, which can reduce the data volume, and proposed a new anomaly detection method that combines a new graph composition method that represents a sequence of flow data as a graph and a graph neural network (GNN). Various detection methods, including deep learning, have been proposed for identifying malware such as denial-of-service (DoS) attacks, in which the characteristics of traffic deviate significantly from those of benign communications. We conducted an evaluation experiment with the proposed method using the KDDI-IoT-2019 dataset and discussed its effectiveness and limitations.","PeriodicalId":296288,"journal":{"name":"2023 IEEE 47th Annual Computers, Software, and Applications Conference (COMPSAC)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131747869","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 : 2023-06-01DOI: 10.1109/COMPSAC57700.2023.00155
Yongju Lee, Hongzhou Duan, Yuxian Sun
The growing number of large scale RDF Big Data raises a challenging data management problem; how should RDF Big Data be stored, queried and integrated. We propose a novel semantic-based content convergence system which consists of acquisition, RDF storage, ontology learning and mashup subsystems. This system serves as a basis for implementing other more sophisticated applications required in the area of Linked Big Data.
{"title":"Semantically Enabled Content Convergence System for Large Scale RDF Big Data","authors":"Yongju Lee, Hongzhou Duan, Yuxian Sun","doi":"10.1109/COMPSAC57700.2023.00155","DOIUrl":"https://doi.org/10.1109/COMPSAC57700.2023.00155","url":null,"abstract":"The growing number of large scale RDF Big Data raises a challenging data management problem; how should RDF Big Data be stored, queried and integrated. We propose a novel semantic-based content convergence system which consists of acquisition, RDF storage, ontology learning and mashup subsystems. This system serves as a basis for implementing other more sophisticated applications required in the area of Linked Big Data.","PeriodicalId":296288,"journal":{"name":"2023 IEEE 47th Annual Computers, Software, and Applications Conference (COMPSAC)","volume":"227 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133231441","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 : 2023-06-01DOI: 10.1109/compsac57700.2023.00140
Sze Chit Au, J. Keung
In computational intelligence, Gerald Appel designed MACD, short for Moving Average Convergence /Divergence in the 1970s, a popular trading indicator used in the business data analysis of stock prices to predict future trends. While it is easy to read, MACD has two distinct disadvantages, the time lagging problem and the fake signals problem, resulting in delays in buying or selling signals and decisions. Besides, three parameters input are required for the calculation model, which is not user-friendly for new learners. This study proposes a new methodology – Volume Square-Weighted Moving Average Convergence & Divergence (VSWMACD). It aims to improve MACD performance and apply various evaluation tools to verify the enhancements. Five datasets with 200 stocks from Hong Kong Stock Market in each have been applied to the testing. The outcome shows that compared to MACD, the average Return On Investment of VSWMACD increased by around 15%, and the average Maximum Drawdown decreased by about 5%. VSWMACD is proven to reduce fake signals while earning a higher return with a lower risk than MACD. A better portfolio management can be formed.
在计算智能领域，杰拉尔德•阿佩尔(Gerald Appel)设计了MACD，即上世纪70年代的移动平均收敛/偏离(Moving Average Convergence /Divergence)的缩写，是一种流行的交易指标，用于股票价格的商业数据分析，以预测未来趋势。虽然MACD很容易阅读，但它有两个明显的缺点，时间滞后问题和假信号问题，导致买卖信号和决策的延迟。此外，计算模型需要输入三个参数，这对初学者来说不是很方便。本研究提出了一种新的方法——成交量平方加权移动平均收敛和偏离(VSWMACD)。它旨在提高MACD性能，并应用各种评估工具来验证增强功能。我们使用了5个数据集，每个数据集包含200只香港股票。结果显示，与MACD相比，VSWMACD的平均投资回报率增加了约15%，平均最大回撤率下降了约5%。VSWMACD被证明可以减少虚假信号，同时获得比MACD更高的回报和更低的风险。可以形成更好的项目组合管理。
{"title":"New Technique for Stock Trend Analysis – Volume-weighted Squared Moving Average Convergence & Divergence","authors":"Sze Chit Au, J. Keung","doi":"10.1109/compsac57700.2023.00140","DOIUrl":"https://doi.org/10.1109/compsac57700.2023.00140","url":null,"abstract":"In computational intelligence, Gerald Appel designed MACD, short for Moving Average Convergence /Divergence in the 1970s, a popular trading indicator used in the business data analysis of stock prices to predict future trends. While it is easy to read, MACD has two distinct disadvantages, the time lagging problem and the fake signals problem, resulting in delays in buying or selling signals and decisions. Besides, three parameters input are required for the calculation model, which is not user-friendly for new learners. This study proposes a new methodology – Volume Square-Weighted Moving Average Convergence & Divergence (VSWMACD). It aims to improve MACD performance and apply various evaluation tools to verify the enhancements. Five datasets with 200 stocks from Hong Kong Stock Market in each have been applied to the testing. The outcome shows that compared to MACD, the average Return On Investment of VSWMACD increased by around 15%, and the average Maximum Drawdown decreased by about 5%. VSWMACD is proven to reduce fake signals while earning a higher return with a lower risk than MACD. A better portfolio management can be formed.","PeriodicalId":296288,"journal":{"name":"2023 IEEE 47th Annual Computers, Software, and Applications Conference (COMPSAC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117298203","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 : 2023-06-01DOI: 10.1109/COMPSAC57700.2023.00076
Kazunori Fujiwara, Shuji Sannomiya, Akira Sato, K. Yoshida
IP anycast is widely used for root and TLD DNS servers to reduce latency. DNS operators need to perform measurements to understand and improve their service quality. Although it is vital to measure the effect of IP anycast, the measurement requires enough worldwide measurement points to send queries. In this paper, we try a more manageable approach, i.e., analyzing the existing capture data to reveal the response delays between resolvers and authoritative DNS servers. There are two packet capture datasets, the DITL and JP datasets. The DITL dataset is collected by Root server operators and maintained by DNS-OARC. The JP dataset is collected for JP TLD operations. Specifically, we extracted communication delay information from TCP session data in these datasets.Our analysis that uses multiple datasets, i.e., DITL and JP datasets, reveals: 1) Approximately 30% of IPv4 addresses seen at the M-Root & JP DNS server have RTT information and come from over 200 countries. 2) JP DNS servers offer RTT of less than 20ms for 80% of queries from Japan, and RTT of less than 100ms for 80% of queries from outside of Japan. 3) The newly installed M-root Brisbane node offers shorter RTTs in Australia.
{"title":"Latency analysis of JP and Root DNS servers from packet capture data","authors":"Kazunori Fujiwara, Shuji Sannomiya, Akira Sato, K. Yoshida","doi":"10.1109/COMPSAC57700.2023.00076","DOIUrl":"https://doi.org/10.1109/COMPSAC57700.2023.00076","url":null,"abstract":"IP anycast is widely used for root and TLD DNS servers to reduce latency. DNS operators need to perform measurements to understand and improve their service quality. Although it is vital to measure the effect of IP anycast, the measurement requires enough worldwide measurement points to send queries. In this paper, we try a more manageable approach, i.e., analyzing the existing capture data to reveal the response delays between resolvers and authoritative DNS servers. There are two packet capture datasets, the DITL and JP datasets. The DITL dataset is collected by Root server operators and maintained by DNS-OARC. The JP dataset is collected for JP TLD operations. Specifically, we extracted communication delay information from TCP session data in these datasets.Our analysis that uses multiple datasets, i.e., DITL and JP datasets, reveals: 1) Approximately 30% of IPv4 addresses seen at the M-Root & JP DNS server have RTT information and come from over 200 countries. 2) JP DNS servers offer RTT of less than 20ms for 80% of queries from Japan, and RTT of less than 100ms for 80% of queries from outside of Japan. 3) The newly installed M-root Brisbane node offers shorter RTTs in Australia.","PeriodicalId":296288,"journal":{"name":"2023 IEEE 47th Annual Computers, Software, and Applications Conference (COMPSAC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114958630","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 : 2023-06-01DOI: 10.1109/COMPSAC57700.2023.00195
Nobuhiro Kobayashi
While the introduction of cyber physical systems (CPS) into society is progressing toward the realization of Society 5.0, the threat of cyberattacks on IoT devices(IoT actuators) that have actuator functions to bring about physical changes in the real world among the IoT devices that constitute the CPS is increasing. In order to prepare for unauthorized control of IoT actuators caused by cyberattacks that are evolving daily, such as zero-day attacks that exploit unknown vulnerabilities in programs, it is an urgent issue to strengthen the CPS, which will become the social infrastructure of the future. In this paper, I explain, in particular, the security requirements for IoT actuators that exert physical action as feedback from cyberspace to the physical space, and a security framework for control that changes the real world, based on changes in cyberspace, where attackers are persistently present. And, I propose a security scheme for IoT actuators that integrates a new concept of security known as Zero Trust, as the Zero Trust IoT Security Framework (ZeTiots-FW).
{"title":"Zero Trust Security Framework for IoT Actuators","authors":"Nobuhiro Kobayashi","doi":"10.1109/COMPSAC57700.2023.00195","DOIUrl":"https://doi.org/10.1109/COMPSAC57700.2023.00195","url":null,"abstract":"While the introduction of cyber physical systems (CPS) into society is progressing toward the realization of Society 5.0, the threat of cyberattacks on IoT devices(IoT actuators) that have actuator functions to bring about physical changes in the real world among the IoT devices that constitute the CPS is increasing. In order to prepare for unauthorized control of IoT actuators caused by cyberattacks that are evolving daily, such as zero-day attacks that exploit unknown vulnerabilities in programs, it is an urgent issue to strengthen the CPS, which will become the social infrastructure of the future. In this paper, I explain, in particular, the security requirements for IoT actuators that exert physical action as feedback from cyberspace to the physical space, and a security framework for control that changes the real world, based on changes in cyberspace, where attackers are persistently present. And, I propose a security scheme for IoT actuators that integrates a new concept of security known as Zero Trust, as the Zero Trust IoT Security Framework (ZeTiots-FW).","PeriodicalId":296288,"journal":{"name":"2023 IEEE 47th Annual Computers, Software, and Applications Conference (COMPSAC)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115234415","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 : 2023-06-01DOI: 10.1109/COMPSAC57700.2023.00215
M. Subu, Mohammad Yousef Alkhawaldeh, F. Ahmed, Nabeel Al-Yateem, J. Dias, S. Rahman, M. AbuRuz, A. Saifan, Amina Al-Marzouqi, Heba H Hijazi, Mohamad Qasim Alshabi, A. Hossain
Introduction The development of internet technology and information and smartphone applications is progressing very rapidly. ON the other hand, accumulating evidence is indicating that excessive use of smartphone can cause mental and emotional health problems among adolescents. Objectives: The purpose of this study was to investigate the association between adolescent smartphone addiction and psychological and emotional health in Indonesia. Methods: This study used a cross-sectional correlational design. The study respondents were 350 adolescents aged 10-22 years and were selected through the convenience sampling method. Data were collected using the adapted and validated psychological wellbeing scale and the Smartphone addiction scale. Results: The study using Kendall's method indicated a significant correlation between the study variables (Sig. = 0.001). The correlation coefficient is -0.255, which denotes a negative, and weak to a moderate relationship. Discussion: Adolescents should exercise, attend school, and volunteer more. During unstable adolescent growth, parents must lead their children, and explain rules and conventions. Adolescents should be encouraged and directed to do more exercise, extra-school activities, and volunteer work among others. In this study it was apparent the issue of technology addiction and its possible negative effects on adolescents9 emotional and mental well-being, therefore individual, group, and community interventions and assertive behavior techniques are needed to decrease adolescent smartphone addiction. Interventions such as group mentoring, counseling, and cognitive behavioral therapy could be useful in this area.
{"title":"Smartphone Addiction and Mental Health Wellbeing Among Indonesian Adolescents","authors":"M. Subu, Mohammad Yousef Alkhawaldeh, F. Ahmed, Nabeel Al-Yateem, J. Dias, S. Rahman, M. AbuRuz, A. Saifan, Amina Al-Marzouqi, Heba H Hijazi, Mohamad Qasim Alshabi, A. Hossain","doi":"10.1109/COMPSAC57700.2023.00215","DOIUrl":"https://doi.org/10.1109/COMPSAC57700.2023.00215","url":null,"abstract":"Introduction The development of internet technology and information and smartphone applications is progressing very rapidly. ON the other hand, accumulating evidence is indicating that excessive use of smartphone can cause mental and emotional health problems among adolescents. Objectives: The purpose of this study was to investigate the association between adolescent smartphone addiction and psychological and emotional health in Indonesia. Methods: This study used a cross-sectional correlational design. The study respondents were 350 adolescents aged 10-22 years and were selected through the convenience sampling method. Data were collected using the adapted and validated psychological wellbeing scale and the Smartphone addiction scale. Results: The study using Kendall's method indicated a significant correlation between the study variables (Sig. = 0.001). The correlation coefficient is -0.255, which denotes a negative, and weak to a moderate relationship. Discussion: Adolescents should exercise, attend school, and volunteer more. During unstable adolescent growth, parents must lead their children, and explain rules and conventions. Adolescents should be encouraged and directed to do more exercise, extra-school activities, and volunteer work among others. In this study it was apparent the issue of technology addiction and its possible negative effects on adolescents9 emotional and mental well-being, therefore individual, group, and community interventions and assertive behavior techniques are needed to decrease adolescent smartphone addiction. Interventions such as group mentoring, counseling, and cognitive behavioral therapy could be useful in this area.","PeriodicalId":296288,"journal":{"name":"2023 IEEE 47th Annual Computers, Software, and Applications Conference (COMPSAC)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115024290","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 : 2023-06-01DOI: 10.1109/COMPSAC57700.2023.00234
Manohar Murikipudi, ABM.Adnan Azmee, Md Abdullah Al Hafiz Khan, Yong Pei
Suicide has become a significant cause of concern worldwide over recent years. The early identification and providing treatment of individuals having suicidal tendencies are necessary for preventing suicides. Past suicidal behavior information of an individual is recorded in the electronic health records (EHR) reports which can help to understand a patient’s current mental health condition. In this paper, to identify the people who are ideating and are anticipating attempting suicide, we propose a novel model named CMTN, which utilizes the textual EHR data for the prediction of suicidal behaviors. The proposed framework employs convolutional and transformer layers to capture local and global relationships in the text and the attention mechanism to assess the significance of various input text components. Overall, the suggested model has achieved the highest precision for the SA class with a score of 0.97 and the highest recall and f1-score of 0.56 and 0.52, respectively, for the SI class, compared with all other state-of-the-art and baseline models. We have also employed different embeddings such as BERT, BioBERT, and PubMedBERT to our state-of-the-art model and illustrated the model’s improved performance. In addition, we have also shared the data alignment and annotation extraction algorithms in this paper, allowing other researchers to generate the dataset, thereby expediting development in the prevention of suicides.
{"title":"CMTN: A Convolutional Multi-Level Transformer to Identify Suicidal Behaviors Using Clinical Notes","authors":"Manohar Murikipudi, ABM.Adnan Azmee, Md Abdullah Al Hafiz Khan, Yong Pei","doi":"10.1109/COMPSAC57700.2023.00234","DOIUrl":"https://doi.org/10.1109/COMPSAC57700.2023.00234","url":null,"abstract":"Suicide has become a significant cause of concern worldwide over recent years. The early identification and providing treatment of individuals having suicidal tendencies are necessary for preventing suicides. Past suicidal behavior information of an individual is recorded in the electronic health records (EHR) reports which can help to understand a patient’s current mental health condition. In this paper, to identify the people who are ideating and are anticipating attempting suicide, we propose a novel model named CMTN, which utilizes the textual EHR data for the prediction of suicidal behaviors. The proposed framework employs convolutional and transformer layers to capture local and global relationships in the text and the attention mechanism to assess the significance of various input text components. Overall, the suggested model has achieved the highest precision for the SA class with a score of 0.97 and the highest recall and f1-score of 0.56 and 0.52, respectively, for the SI class, compared with all other state-of-the-art and baseline models. We have also employed different embeddings such as BERT, BioBERT, and PubMedBERT to our state-of-the-art model and illustrated the model’s improved performance. In addition, we have also shared the data alignment and annotation extraction algorithms in this paper, allowing other researchers to generate the dataset, thereby expediting development in the prevention of suicides.","PeriodicalId":296288,"journal":{"name":"2023 IEEE 47th Annual Computers, Software, and Applications Conference (COMPSAC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121503010","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 : 2023-06-01DOI: 10.1109/COMPSAC57700.2023.00214
A. Hossain, Md. Aminul Islam, A. Chowdhury, S. Rahman, Alounoud Salman, J. Dias, M. Subu, Mohammad Yousef Alkhawaldeh, Amina Al-Marzouqi, Heba H Hijazi, Mohamad Qasim Alshabi, Nabeel Al-Yateem
Cyberchondria is a distinct behavioral syndrome that is closely related to health anxiety/hypochondria and excessive online searching for health information and/or digital self-tracking. Despite the reported prevalence of self-medication, cyberchondria research is still in its infancy in Bangladesh. We investigated the relationship between Cyberchondria and self-medication among adults. This was a cross-sectional study conducted with 480 individuals who had internet access and who can read both Bangla and English. The Cyberchondria Severity Scale and the self-medication perception Questionnaire were applied to the participants. Univariate and hierarchical multiple linear regression analyses were used to analyze the data. Of the study group 283 (59%) were male, and 197 (41%), were female. Their ages ranged from 18 to 40 years, with an average of 25.1 (± 5.97) years. The positive perception of self-medication was prevalent in 279 (58.1%) adults. Cyberchondria and perception of self-medication were positively related and in the final model self-medication, age and residence were found to be the significant determinants of cyberchondria. Positive perception of self-medication practice may be a potential risk factor for Cyberchondria. People's health-related actions can be influenced by their cyberchondria behavior, so it's crucial that online health resources are safe. Cyberchondria is a mental health disorder, and this study's findings could inform future research into the causes of this condition.
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