World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering最新文献
Pub Date : 2022-01-01DOI: 10.17706/ijcce.2022.11.1.1-9
M. Watanabe, T. Fujimoto
In this research, we design an application to release user’s daily stress. It is said that contemporary people are in a pretty stressful situation. For example, in recent years, we have suffered from difficulty to meet friends casually and enjoy talking with them to get rid of our daily stress due to the COVID-19 pandemic. In other words, the variation of ways of overcoming stress have been limited. In addition, people have deteriorated relationships with their family members because of the longer stay-at-home time than before. Health problems such as the onset of depression caused by the stress of the pandemic are also becoming more serious. Moreover, people are worrying of increasing the number of suicides. This situation is one of the problems that people consider it important in the society recently. Therefore, there is an urgent need to find solutions to such a situation. In this research, we develop the functions to cope with daily stress easily for the application of the smartphones that anyone has. We include functions in this application we suggest in this research. They are “vent mode”, which is a dynamic de-stressing method by words, “empathy mode”, which is a static de-stressing method, and “physical touch mode”, which is a dynamic de-stressing method that is accompanied with physical exercise. In addition, we design the application for de-stress in order to break through the stressful situation these days.
{"title":"Application Design to Release Stress","authors":"M. Watanabe, T. Fujimoto","doi":"10.17706/ijcce.2022.11.1.1-9","DOIUrl":"https://doi.org/10.17706/ijcce.2022.11.1.1-9","url":null,"abstract":"In this research, we design an application to release user’s daily stress. It is said that contemporary people are in a pretty stressful situation. For example, in recent years, we have suffered from difficulty to meet friends casually and enjoy talking with them to get rid of our daily stress due to the COVID-19 pandemic. In other words, the variation of ways of overcoming stress have been limited. In addition, people have deteriorated relationships with their family members because of the longer stay-at-home time than before. Health problems such as the onset of depression caused by the stress of the pandemic are also becoming more serious. Moreover, people are worrying of increasing the number of suicides. This situation is one of the problems that people consider it important in the society recently. Therefore, there is an urgent need to find solutions to such a situation. In this research, we develop the functions to cope with daily stress easily for the application of the smartphones that anyone has. We include functions in this application we suggest in this research. They are “vent mode”, which is a dynamic de-stressing method by words, “empathy mode”, which is a static de-stressing method, and “physical touch mode”, which is a dynamic de-stressing method that is accompanied with physical exercise. In addition, we design the application for de-stress in order to break through the stressful situation these days.","PeriodicalId":23787,"journal":{"name":"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76849269","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 : 2022-01-01DOI: 10.17706/ijcce.2022.11.2.10-23
Qi Song, Xuanze Xia
: In recent years, deep neural network has continuously renewed its best performance in tasks such as computer vision and natural language processing, and has become the most concerned research direction. Although the performance of deep network model is remarkable, it is still difficult to deploy to the embedded or mobile devices with a limited hardware due to the large number of parameters, high storage and computing costs. It has been found by relevant studies that the depth model based on convolutional neural network has parameter redundancy, and there are parameters that are useless to the final result in the model, which provides theoretical support for the pruning of depth network model. Therefore, how to reduce the model size under the condition of ensuring the model accuracy has become a hot issue. This paper classifies and summarizes the achievements of domestic and foreign scholars in model pruning in recent years, selects several new pruning algorithm methods in different directions, analyzes their functionality through experiments and discusses the current problems of different models and the development direction of pruning model optimization in the future.
{"title":"A Survey on Pruning Algorithm Based on Optimized Depth Neural Network","authors":"Qi Song, Xuanze Xia","doi":"10.17706/ijcce.2022.11.2.10-23","DOIUrl":"https://doi.org/10.17706/ijcce.2022.11.2.10-23","url":null,"abstract":": In recent years, deep neural network has continuously renewed its best performance in tasks such as computer vision and natural language processing, and has become the most concerned research direction. Although the performance of deep network model is remarkable, it is still difficult to deploy to the embedded or mobile devices with a limited hardware due to the large number of parameters, high storage and computing costs. It has been found by relevant studies that the depth model based on convolutional neural network has parameter redundancy, and there are parameters that are useless to the final result in the model, which provides theoretical support for the pruning of depth network model. Therefore, how to reduce the model size under the condition of ensuring the model accuracy has become a hot issue. This paper classifies and summarizes the achievements of domestic and foreign scholars in model pruning in recent years, selects several new pruning algorithm methods in different directions, analyzes their functionality through experiments and discusses the current problems of different models and the development direction of pruning model optimization in the future.","PeriodicalId":23787,"journal":{"name":"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88586837","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 : 2021-01-01DOI: 10.17706/ijcce.2021.10.2.28-36
Kotaro Nagahiro, Sho Ooi, Mutsuo Sano
Recently, research on generative adversarial networks (GANs) in deep learning has advanced rapidly. For instance, in the field of image recognition, using a GAN, the number of training data was increased. GAN have also been used to create new similar images using training images, which can help designers such as car designer, character designer, game designer and more. We have been researching a method to automatically generate a game stage based on a dot-picture using GAN. So far, we have been studying game stage generation using GAN. In this study, we consider an evaluation method for generated game stages. Specifically, we consider using the A * search algorithm to evaluate the playability of the generated game stage from the number of jumps and the clear time. As a result, the jumping count of an automatically player using the A * algorithm was 17 times for the original stage, 12 times for stage No.1, 16 times for stage No.2, and 18 times for stage No.3. Next, the clear time was 9 seconds for the original stage, 8 seconds for stage No.1, 10 seconds for stage No.2, and 11 seconds for stage No.3. In other words, we suggest stage No.1 is simpler than the original stage, and stage 2 and stage 3 are a little more difficult than the original stage.
{"title":"Study on Stages Evaluation for 2D Action Game Generated by DC-GAN Based on Artificial Intelligence","authors":"Kotaro Nagahiro, Sho Ooi, Mutsuo Sano","doi":"10.17706/ijcce.2021.10.2.28-36","DOIUrl":"https://doi.org/10.17706/ijcce.2021.10.2.28-36","url":null,"abstract":"Recently, research on generative adversarial networks (GANs) in deep learning has advanced rapidly. For instance, in the field of image recognition, using a GAN, the number of training data was increased. GAN have also been used to create new similar images using training images, which can help designers such as car designer, character designer, game designer and more. We have been researching a method to automatically generate a game stage based on a dot-picture using GAN. So far, we have been studying game stage generation using GAN. In this study, we consider an evaluation method for generated game stages. Specifically, we consider using the A * search algorithm to evaluate the playability of the generated game stage from the number of jumps and the clear time. As a result, the jumping count of an automatically player using the A * algorithm was 17 times for the original stage, 12 times for stage No.1, 16 times for stage No.2, and 18 times for stage No.3. Next, the clear time was 9 seconds for the original stage, 8 seconds for stage No.1, 10 seconds for stage No.2, and 11 seconds for stage No.3. In other words, we suggest stage No.1 is simpler than the original stage, and stage 2 and stage 3 are a little more difficult than the original stage.","PeriodicalId":23787,"journal":{"name":"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88042680","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 : 2021-01-01DOI: 10.17706/ijcce.2021.10.3.52-67
Rongbo Zhang, Kaiyu Cai
The High-Definition map (HD map) is a key technology to achieve automatic driving above the grade of L3, with the amount of data comes to more than 105 times that of traditional navigation map. With the arrival of 5G communication and the rapid development of Internet of Things, each autonomous vehicle will request HD map service by accessing the Internet. The service of traditional navigation map under “cloud-end” mode may not be well adapted to future HD map application, so the paper proposes a MEC proposal for HD map application, deploying HD map server under “cloud-edge-end” mode to mitigate the high latency and improve low reliability caused by the faraway physical distance rather than “cloud-end” mode. The HD map is divided according to the latitude and longitude regions, being pushed to local edge computing node servers respectively to realize the interaction between autonomous vehicles and edge servers, which makes more convenient and reliable HD map services available. The experimental results show that the proposed proposal can cut off the communication delay effectively, ensuring the reliability of the HD map service, and providing high-quality HD map service for autonomous vehicles.
{"title":"The Key Technology of High-Definition Maps Distribution Based on Edge Computing","authors":"Rongbo Zhang, Kaiyu Cai","doi":"10.17706/ijcce.2021.10.3.52-67","DOIUrl":"https://doi.org/10.17706/ijcce.2021.10.3.52-67","url":null,"abstract":"The High-Definition map (HD map) is a key technology to achieve automatic driving above the grade of L3, with the amount of data comes to more than 105 times that of traditional navigation map. With the arrival of 5G communication and the rapid development of Internet of Things, each autonomous vehicle will request HD map service by accessing the Internet. The service of traditional navigation map under “cloud-end” mode may not be well adapted to future HD map application, so the paper proposes a MEC proposal for HD map application, deploying HD map server under “cloud-edge-end” mode to mitigate the high latency and improve low reliability caused by the faraway physical distance rather than “cloud-end” mode. The HD map is divided according to the latitude and longitude regions, being pushed to local edge computing node servers respectively to realize the interaction between autonomous vehicles and edge servers, which makes more convenient and reliable HD map services available. The experimental results show that the proposed proposal can cut off the communication delay effectively, ensuring the reliability of the HD map service, and providing high-quality HD map service for autonomous vehicles.","PeriodicalId":23787,"journal":{"name":"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76888927","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 : 2021-01-01DOI: 10.17706/IJCCE.2021.10.1.17-27
Piyumini Wijenayake, D. Alahakoon, Daswin De Silva, S. Kirigeeganage
: This paper introduces a novel technique to generate brand personalities for organizations from social media text data using a deep bi - directional Long Short - Term Memory (BiLSTM) neural network model in combination with an accepted brand personality scale model. Brand Personality has evolved into an indispensable element in modern business organizations. Currently brand personality of an organization is generated using traditional techniques such as stakeholder interviews, questionnaires, which are time and resource intensive and limited in efficacy. However, the rise of the internet and social media have provided a platform for stakeholders to frequently and freely express their opinions and experiences related to organizations. Such social media data while now successfully being used for customer analytics have not yet been fully investigated and used to understand brand personalities. Our research investigated how this data can be effectively leveraged by organizations to generate and monitor their brand in near real time. Our technique has been successfully demonstrated on Higher Education Institutes, as Higher Education is an industry that is increasingly being exposed to business competition over the last few decades.
{"title":"Deep LSTM for Generating Brand Personalities Using Social Media: A Case Study from Higher Education Institutions","authors":"Piyumini Wijenayake, D. Alahakoon, Daswin De Silva, S. Kirigeeganage","doi":"10.17706/IJCCE.2021.10.1.17-27","DOIUrl":"https://doi.org/10.17706/IJCCE.2021.10.1.17-27","url":null,"abstract":": This paper introduces a novel technique to generate brand personalities for organizations from social media text data using a deep bi - directional Long Short - Term Memory (BiLSTM) neural network model in combination with an accepted brand personality scale model. Brand Personality has evolved into an indispensable element in modern business organizations. Currently brand personality of an organization is generated using traditional techniques such as stakeholder interviews, questionnaires, which are time and resource intensive and limited in efficacy. However, the rise of the internet and social media have provided a platform for stakeholders to frequently and freely express their opinions and experiences related to organizations. Such social media data while now successfully being used for customer analytics have not yet been fully investigated and used to understand brand personalities. Our research investigated how this data can be effectively leveraged by organizations to generate and monitor their brand in near real time. Our technique has been successfully demonstrated on Higher Education Institutes, as Higher Education is an industry that is increasingly being exposed to business competition over the last few decades.","PeriodicalId":23787,"journal":{"name":"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75555141","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}
The detection and recognition of information in natural scenes has always been a difficult problem in computer vision. Digital instrument character recognition is one of the more representative and valuable things. In recent years, there is a lot of research work on this problem, but the solutions rely on string location, character segmentation and other preprocessing processes, the results of these preprocessing processes directly affect the final character recognition results. In contrast, the character recognition method of digital instrument based on convolution neural network (CNN) omits the complex preprocessing process through graph to graph prediction, and the character recognition result is obtaind directly. And has a strong generalization ability, can identify multiple types of instruments. At the same time, through the weighted fusion of muti-scale and multi-level features in the CNN, a better ability of feature extraction and information integration is obtained. The experimental results show that the method can directly and accurately recognize the characters in the Vernier caliper.
{"title":"Intelligent Digital Recognition System Based on Vernier Caliper","authors":"Hui Sun, Feng Shan, Xiaoyu Tang, Weiwei Shi, Xiaowei Wang, Xiaofeng Li, Yuan-Chin Cheng, Haiwei Zhang","doi":"10.17706/IJCCE.2021.10.1.1-8","DOIUrl":"https://doi.org/10.17706/IJCCE.2021.10.1.1-8","url":null,"abstract":"The detection and recognition of information in natural scenes has always been a difficult problem in computer vision. Digital instrument character recognition is one of the more representative and valuable things. In recent years, there is a lot of research work on this problem, but the solutions rely on string location, character segmentation and other preprocessing processes, the results of these preprocessing processes directly affect the final character recognition results. In contrast, the character recognition method of digital instrument based on convolution neural network (CNN) omits the complex preprocessing process through graph to graph prediction, and the character recognition result is obtaind directly. And has a strong generalization ability, can identify multiple types of instruments. At the same time, through the weighted fusion of muti-scale and multi-level features in the CNN, a better ability of feature extraction and information integration is obtained. The experimental results show that the method can directly and accurately recognize the characters in the Vernier caliper.","PeriodicalId":23787,"journal":{"name":"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83843418","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 : 2021-01-01DOI: 10.17706/IJCCE.2021.10.1.9-16
Jie Zhang, Haixia Shao, Haijun Wang
In order to facilitate the construction of projectile-carried communication jamming system model, this paper used the methods of literature search, classification and summary, and details sorting, deeply analyzing the communication characteristics of projectile-carried communication jamming object from seven aspects, including communication modulation mode, antenna type, antenna length, antenna transmission gain, sensitivity calculation, jamming tolerance, initial synchronization process and its characteristics. Then, the boundary conditions of projectile-carried communication jamming object were determined. In other words, the modulation mode of projectile-carried communication jamming object was 2FSK, the antenna type was whip antenna, the antenna length was 2 m or 2.4 m, the short wave antenna transmission gain was -10.5912 dBi, the ultrashort wave antenna transmission gain was -1.383 dBi, the jamming tolerance was 32% of the available frequency, and the initial synchronization time was calculated as 182 ms. The relevant conclusions lay a foundation for the follow-up study of projectile-carried communication jamming performance.
{"title":"Analysis of Communication Characteristics of Projectile-Carried Communication Jamming Object","authors":"Jie Zhang, Haixia Shao, Haijun Wang","doi":"10.17706/IJCCE.2021.10.1.9-16","DOIUrl":"https://doi.org/10.17706/IJCCE.2021.10.1.9-16","url":null,"abstract":"In order to facilitate the construction of projectile-carried communication jamming system model, this paper used the methods of literature search, classification and summary, and details sorting, deeply analyzing the communication characteristics of projectile-carried communication jamming object from seven aspects, including communication modulation mode, antenna type, antenna length, antenna transmission gain, sensitivity calculation, jamming tolerance, initial synchronization process and its characteristics. Then, the boundary conditions of projectile-carried communication jamming object were determined. In other words, the modulation mode of projectile-carried communication jamming object was 2FSK, the antenna type was whip antenna, the antenna length was 2 m or 2.4 m, the short wave antenna transmission gain was -10.5912 dBi, the ultrashort wave antenna transmission gain was -1.383 dBi, the jamming tolerance was 32% of the available frequency, and the initial synchronization time was calculated as 182 ms. The relevant conclusions lay a foundation for the follow-up study of projectile-carried communication jamming performance.","PeriodicalId":23787,"journal":{"name":"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75429258","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 : 2021-01-01DOI: 10.17706/ijcce.2021.10.3.68-74
Yuexiao Teng
Mining database aims to discover hidden, yet potentially useful knowledge in database and it has many applications. SQL-based mining relational database is one of its branches, which takes advantage of Standard Query Language to mine datasets. However, due to the little survey research emphasis on this very specific area, currently few literature review has been conducted to investigate, summarize or critique this field. In order to fill this existing gap, in this paper, an original critical review has been carried out, which is based on academic research papers since 1990. To author’s best knowledge, it is the first time to conduct such a review in a critical way regarding SQL-based mining relational database. This review highlights a strong point and a point of improvement and organized in a reversely chronologic order. The review result shows that since 1990, there have been some research work done to mine relational database by SQL. Almost all of it was empirical and some of it was based on the extension of the standard SQL, however all of research or proposed systems did not support distributed relational databases.
{"title":"A Critical Review of SQL-Based Mining Relational Database","authors":"Yuexiao Teng","doi":"10.17706/ijcce.2021.10.3.68-74","DOIUrl":"https://doi.org/10.17706/ijcce.2021.10.3.68-74","url":null,"abstract":"Mining database aims to discover hidden, yet potentially useful knowledge in database and it has many applications. SQL-based mining relational database is one of its branches, which takes advantage of Standard Query Language to mine datasets. However, due to the little survey research emphasis on this very specific area, currently few literature review has been conducted to investigate, summarize or critique this field. In order to fill this existing gap, in this paper, an original critical review has been carried out, which is based on academic research papers since 1990. To author’s best knowledge, it is the first time to conduct such a review in a critical way regarding SQL-based mining relational database. This review highlights a strong point and a point of improvement and organized in a reversely chronologic order. The review result shows that since 1990, there have been some research work done to mine relational database by SQL. Almost all of it was empirical and some of it was based on the extension of the standard SQL, however all of research or proposed systems did not support distributed relational databases.","PeriodicalId":23787,"journal":{"name":"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84959998","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 : 2021-01-01DOI: 10.17706/ijcce.2021.10.4.75-84
Wen-Hui Chen, Po-Chuan Cho
Recently, deep learning has emerged as a powerful technique and been successfully employed for various tasks. It has also been applied to human activity recognition and showed better performance than traditional machine learning algorithms. However, the success of deep learning always comes with large labeled datasets when the learning model goes deeper. If the training data is limited, the performance of the classification model may not generally perform well due to overfitting of the networks to the training data, which can be alleviated through data augmentation. Generative adversarial networks (GANs) can be used as a technique to produce data artificially. GAN-based approaches have made rapid progress in generating synthetic data, but they are mostly studied for image data. Comparatively little research has been conducted to examine the effectiveness of generating sensor data using GANs. This study aims to investigate the data scarcity problem by using conditional generative adversarial networks (CGANs) as a data augmentation method. The proposed approach was experimentally evaluated on a benchmark sensor dataset for activity recognition. The experimental results showed that the proposed approach can boost the model accuracy and has better performance when compared with existing approaches.
{"title":"A GAN-Based Data Augmentation Approach for Sensor-Based Human Activity Recognition","authors":"Wen-Hui Chen, Po-Chuan Cho","doi":"10.17706/ijcce.2021.10.4.75-84","DOIUrl":"https://doi.org/10.17706/ijcce.2021.10.4.75-84","url":null,"abstract":"Recently, deep learning has emerged as a powerful technique and been successfully employed for various tasks. It has also been applied to human activity recognition and showed better performance than traditional machine learning algorithms. However, the success of deep learning always comes with large labeled datasets when the learning model goes deeper. If the training data is limited, the performance of the classification model may not generally perform well due to overfitting of the networks to the training data, which can be alleviated through data augmentation. Generative adversarial networks (GANs) can be used as a technique to produce data artificially. GAN-based approaches have made rapid progress in generating synthetic data, but they are mostly studied for image data. Comparatively little research has been conducted to examine the effectiveness of generating sensor data using GANs. This study aims to investigate the data scarcity problem by using conditional generative adversarial networks (CGANs) as a data augmentation method. The proposed approach was experimentally evaluated on a benchmark sensor dataset for activity recognition. The experimental results showed that the proposed approach can boost the model accuracy and has better performance when compared with existing approaches.","PeriodicalId":23787,"journal":{"name":"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91145058","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 : 2021-01-01DOI: 10.17706/ijcce.2021.10.2.37-51
Peng Yang, Xinxin Wan, Guangye Shi, Hao Qu, Juan Li, Lixin Yang
A covert channel is an information channel which is used by computer process to exfiltrate data through bypassing security policies. The domain name system (DNS) protocol is one of the important ways to implement a covert channel. DNS covert channels are easily used by attackers for malicious purposes. Therefore, an effective detection of the DNS covert channels is significant for computer system and network security. Aiming at the difficulty of the DNS covert channel identification, we propose a DNS covert channel detection method based on stacking model. The stacking model is evaluated in a campus network and the experimental results show that the detection based on the stacking model can detect the DNS covert channels effectively. Besides, it can also identify unknown covert channel traffic. The area under the curve (AUC) of the proposed method, reaching 0.9901, outperforms the existed methods.
{"title":"Identification of DNS Covert Channel Based on Stacking Method","authors":"Peng Yang, Xinxin Wan, Guangye Shi, Hao Qu, Juan Li, Lixin Yang","doi":"10.17706/ijcce.2021.10.2.37-51","DOIUrl":"https://doi.org/10.17706/ijcce.2021.10.2.37-51","url":null,"abstract":"A covert channel is an information channel which is used by computer process to exfiltrate data through bypassing security policies. The domain name system (DNS) protocol is one of the important ways to implement a covert channel. DNS covert channels are easily used by attackers for malicious purposes. Therefore, an effective detection of the DNS covert channels is significant for computer system and network security. Aiming at the difficulty of the DNS covert channel identification, we propose a DNS covert channel detection method based on stacking model. The stacking model is evaluated in a campus network and the experimental results show that the detection based on the stacking model can detect the DNS covert channels effectively. Besides, it can also identify unknown covert channel traffic. The area under the curve (AUC) of the proposed method, reaching 0.9901, outperforms the existed methods.","PeriodicalId":23787,"journal":{"name":"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85246511","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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