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2022 IEEE Symposium on Wireless Technology & Applications (ISWTA)最新文献

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CW Radar Based Silent Speech Interface Using CNN 基于CNN的连续波雷达静音语音接口
2022 IEEE Symposium on Wireless Technology & Applications (ISWTA) Pub Date : 2022-08-17 DOI: 10.1109/ISWTA55313.2022.9942730
K. K. Mohd Shariff, Auni Nadiah Yusni, Mohd Adli Md Ali, Megat Syahirul Amin Megat Ali, Megat Zuhairy Megat Tajuddin, M. Younis
{"title":"CW Radar Based Silent Speech Interface Using CNN","authors":"K. K. Mohd Shariff, Auni Nadiah Yusni, Mohd Adli Md Ali, Megat Syahirul Amin Megat Ali, Megat Zuhairy Megat Tajuddin, M. Younis","doi":"10.1109/ISWTA55313.2022.9942730","DOIUrl":"https://doi.org/10.1109/ISWTA55313.2022.9942730","url":null,"abstract":"The use of a silent speech interface (SSI) to issue commands is becoming more popular because users can use them without uttering the actual sound. This technique is useful for people with speech neurological problems or environments where a speech-based system would be impractical to use, e.g., in a noisy factory or a quiet library. However, state-of-the-art solutions for SSI is mostly based on vision camera or skin-mounted sensors. These technologies have issues where the camera has privacy concerns and skin sensors are not practical for many applications. Therefore, in this paper, we propose a radar-based SSI which is contactless and protects privacy. For this purpose, we constructed 2-dimensional images of mouth movements from radar echo as a profile of silent command. We propose deep learning-based convolutional neural networks (CNN) to recognize silent commands from 2D images. Our evaluation indicates that the proposed SSI accurately classifies four commands up to 89%.","PeriodicalId":293957,"journal":{"name":"2022 IEEE Symposium on Wireless Technology & Applications (ISWTA)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115633518","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Silent Speech Interface using Continuous-Wave Radar and Optimized AlexNet 基于连续波雷达和优化AlexNet的静音语音接口
2022 IEEE Symposium on Wireless Technology & Applications (ISWTA) Pub Date : 2022-08-17 DOI: 10.1109/ISWTA55313.2022.9942770
K. K. Mohd Shariff, Megat Zuhairy Megat Tajuddin, M. Younis, Megat Syahirul Amin Megat Ali
{"title":"Silent Speech Interface using Continuous-Wave Radar and Optimized AlexNet","authors":"K. K. Mohd Shariff, Megat Zuhairy Megat Tajuddin, M. Younis, Megat Syahirul Amin Megat Ali","doi":"10.1109/ISWTA55313.2022.9942770","DOIUrl":"https://doi.org/10.1109/ISWTA55313.2022.9942770","url":null,"abstract":"Silent speech interface systems enables human-computer interaction via speech, in the absence of an acoustic signal. The applications range from speech recognition in noisy environment to interaction with speech-impaired individuals. This study proposes a state-of-the-art solution to silent speech interface based on continuous-wave radar. Six volunteers have participated in the study. They are required to silently utter four native Malay command words. A total of 1,180 samples have been obtained. The spectrograms of mouth movements from radar echo are constructed as profile of the silent commands. The feature images are used to develop a deep learning model by performing transfer learning on the AlexNet architecture. Different hyperparameter settings are evaluated. The best performance is obtained when the network is trained using Adam optimizer at with batch size of 512. The optimized model attained classification accuracies of 99.8% for training, and 98.3% for validation.","PeriodicalId":293957,"journal":{"name":"2022 IEEE Symposium on Wireless Technology & Applications (ISWTA)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128547644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A Countermeasure Against Adversarial Attacks on Power Allocation in a Massive MIMO Network 大规模MIMO网络中对抗对抗性功率分配攻击的对策
2022 IEEE Symposium on Wireless Technology & Applications (ISWTA) Pub Date : 2022-08-17 DOI: 10.1109/ISWTA55313.2022.9942776
Lu Zhang, S. Lambotharan, G. Zheng
{"title":"A Countermeasure Against Adversarial Attacks on Power Allocation in a Massive MIMO Network","authors":"Lu Zhang, S. Lambotharan, G. Zheng","doi":"10.1109/ISWTA55313.2022.9942776","DOIUrl":"https://doi.org/10.1109/ISWTA55313.2022.9942776","url":null,"abstract":"Deep learning has been emerging as a powerful design tool for the current and future generations of wireless networks. Among many other successful applications, deep learning has been shown to reduce computational complexity in power allocation problems in massive multiple-input and multiple-output (MIMO) networks. Despite its advantages over conventional power allocations, a recent study demonstrated that an imperceptible yet carefully designed feature perturbation named as adversarial examples may drastically degrade the performance of the power allocation system based on deep learning. Hence, in this paper, a defence system called noise-augmented neural network is investigated to mitigate the effect of adversarial attacks, and its performance against white-box fast gradient sign attacks and projected gradient descent attacks is evaluated. It is shown that the proposed noise-augmented neural network could protect power allocation system from the damaging effect of the adversarial perturbations with much greater accuracy as compared to the undefended deep neural network.","PeriodicalId":293957,"journal":{"name":"2022 IEEE Symposium on Wireless Technology & Applications (ISWTA)","volume":"1 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129363163","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Isolated Magnetic Dipole MIMO Antenna Linear Arrangement Port Orientation for Wireless Application 无线应用的隔离磁偶极MIMO天线线性排列端口定向
2022 IEEE Symposium on Wireless Technology & Applications (ISWTA) Pub Date : 2022-08-17 DOI: 10.1109/ISWTA55313.2022.9942773
M. S. Amri Safiai, A. bin Aris, Vincent Yong Kai Loung
{"title":"Isolated Magnetic Dipole MIMO Antenna Linear Arrangement Port Orientation for Wireless Application","authors":"M. S. Amri Safiai, A. bin Aris, Vincent Yong Kai Loung","doi":"10.1109/ISWTA55313.2022.9942773","DOIUrl":"https://doi.org/10.1109/ISWTA55313.2022.9942773","url":null,"abstract":"This paper presents the design of a small, low-profile, Multiple-Input Multiple-Output (MIMO) antenna with 3D G-folded structures and semicircle arc slots for wireless application. Designing the MIMO antenna over a restricted space requires different methodologies for decreasing common coupling, and the pattern of radiation. Numerous procedures have been taken into account to monitor this degrading factor and to boost the MIMO antenna capabilities such as a reasonable increase in gain, and efficiency. In this paper, an investigation on Vertical Isolated Magnetic Dipole MIMO Antenna with multi-point port direction for Wireless Communication is simulated on Computer Simulation Technology (CST) software. The substrate and the copper thickness are 1.575 mm and 0.035 mm, respectively. The FR4 is used as the substrate which gives a relative permittivity of 4.7. The simulated results based on the parameter value have been optimized and presented in this paper. The proposed design will operate at the frequency of 2.4 GHz for Wireless Local Area Network (WLAN) application.","PeriodicalId":293957,"journal":{"name":"2022 IEEE Symposium on Wireless Technology & Applications (ISWTA)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123851257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
DRL based Energy-Efficient Radio Resource Allocation Algorithm in Internet of Robotic Things 基于DRL的机器人物联网节能无线资源分配算法
2022 IEEE Symposium on Wireless Technology & Applications (ISWTA) Pub Date : 2022-08-17 DOI: 10.1109/ISWTA55313.2022.9942743
Homayun Kabir, Mau-Luen Tham, Yoong Choon Chang
{"title":"DRL based Energy-Efficient Radio Resource Allocation Algorithm in Internet of Robotic Things","authors":"Homayun Kabir, Mau-Luen Tham, Yoong Choon Chang","doi":"10.1109/ISWTA55313.2022.9942743","DOIUrl":"https://doi.org/10.1109/ISWTA55313.2022.9942743","url":null,"abstract":"Communications among user equipment (UE) play a pivotal role in the coordination and information sharing in order to accomplish the predefined collaborative tasks of UE via the internet of robotic things (IoRT). Cloud radio access network (C-RAN) emerges as one of the most compelling architectures to ensure the UE demands. However, to optimize the power usage by fulfilling UE demand over a long operational period, the radio resource allocation (RRA) in C-RAN requires to be more visionary. To solve this challenge, we propose a deep reinforcement learning (DRL) based algorithm consisting of two different value-based networks. One network generates the target value for the second network for the purpose of better convergence. Under the same UE demands, simulation results verify that the proposed DRL algorithm outperforms the Deep Q Network (DQN) and conventional approaches in terms of power consumption.","PeriodicalId":293957,"journal":{"name":"2022 IEEE Symposium on Wireless Technology & Applications (ISWTA)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126495032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Wireless Power Transfer for Cardiac Pacemaker 心脏起搏器的无线能量传输
2022 IEEE Symposium on Wireless Technology & Applications (ISWTA) Pub Date : 2022-08-17 DOI: 10.1109/ISWTA55313.2022.9942779
Umeshika Uthayakumar, Yasanthi Jayaweera
{"title":"Wireless Power Transfer for Cardiac Pacemaker","authors":"Umeshika Uthayakumar, Yasanthi Jayaweera","doi":"10.1109/ISWTA55313.2022.9942779","DOIUrl":"https://doi.org/10.1109/ISWTA55313.2022.9942779","url":null,"abstract":"Cardiac pacemaker is an electronic device used to regulate the heartbeat of patients suffering with congenital heart defects. Considering the limitations in lifespan of current cardiac pacemaker battery, a wireless charging mechanism for cardiac pacemaker is proposed in this paper. Circuitry model and electromagnetic geometry is developed using Ansys Maxwell and Ansys High-Frequency Structure Simulator (HFSS) software to analyze three main technical issues such as: implantation, efficiency and safety. Specific Absorption Rate (SAR) and induced electric field in a 3-D model human body is evaluated by numerical analysis and simulation to ensure that the developed system adheres to safety limits proposed by Institute of Electrical and Electronics Engineers (IEEE) standard and International Commission on Non-Ionizing Radiation Protection (ICNIRP) guidelines.","PeriodicalId":293957,"journal":{"name":"2022 IEEE Symposium on Wireless Technology & Applications (ISWTA)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129775267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Technical Job Distribution at BSD SHARP Service Center Using Combination of Naïve Bayes and K-Nearest Neighbour 结合Naïve贝叶斯和k近邻的BSD SHARP服务中心技术岗位分配
2022 IEEE Symposium on Wireless Technology & Applications (ISWTA) Pub Date : 2022-08-17 DOI: 10.1109/ISWTA55313.2022.9942772
Dwi Pebrianti, Angga Ariawan, L. Bayuaji, Deni Mahdiana, Rusdah Rusdah
{"title":"Technical Job Distribution at BSD SHARP Service Center Using Combination of Naïve Bayes and K-Nearest Neighbour","authors":"Dwi Pebrianti, Angga Ariawan, L. Bayuaji, Deni Mahdiana, Rusdah Rusdah","doi":"10.1109/ISWTA55313.2022.9942772","DOIUrl":"https://doi.org/10.1109/ISWTA55313.2022.9942772","url":null,"abstract":"Works distribution is a routine carried out every day by the head of the branch in the SHARP Service Center. The accuracy of the labor division is very important to get customer satisfaction. Inappropriate work distribution can increase complaints from customers. Currently, works distribution in SHARP Service Center is carried out manually, where the works received on the selected system is then shared through the document provided. Time taken for this process is about 1.42 minutes on average for each damage reports. Speed of Service also depends on the Head of Department's expertise and experience. In this study, an automatic system based on Machine Learning will be designed for the technicians work distribution by using a combination of k Nearest Neighbor (k-NN) and Naïve Bayes. Naïve Bayes algorithm is used to improve the feature extraction accuracy by considering the feature below the average (α). Meanwhile, k-NN algorithm is used to classify the experimental data. From the study, it is found that the best of k value for k-NN algorithm is 15. It is known that a high number of accuracy values, the labor distribution can be more accurate. The validation of the proposed method is conducted by using a confusion matrix with a composition of 80% training data and 20% test data. The single Classifier test with the Naïve Bayes algorithm produces the highest accuracy value of 72.7%, while using k-NN algorithm is 81.5%. With a combination of Naive Bayes and k-NN algorithms, the accuracy value is increasing to 86%. This result shows that the proposed method improves the accuracy by 13.3% on single Naive Bayes algorithms and 4% on a single k-NN algorithm. The results obtained show that in the manual process, the average time per job is 1.42 minutes, while by using the proposed method, the average processing time is around 0.03 seconds per job. An increase of 2480 times faster is found and confirmed during the implementation of the proposed method.","PeriodicalId":293957,"journal":{"name":"2022 IEEE Symposium on Wireless Technology & Applications (ISWTA)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133066729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Diagnosis of Cardiovascular Diseases Using Classification Algorithms 使用分类算法诊断心血管疾病
2022 IEEE Symposium on Wireless Technology & Applications (ISWTA) Pub Date : 2022-08-17 DOI: 10.1109/ISWTA55313.2022.9942793
Mehmet Akif Tanisik, Emine Yaman, A. Almisreb, N. Tahir
{"title":"Diagnosis of Cardiovascular Diseases Using Classification Algorithms","authors":"Mehmet Akif Tanisik, Emine Yaman, A. Almisreb, N. Tahir","doi":"10.1109/ISWTA55313.2022.9942793","DOIUrl":"https://doi.org/10.1109/ISWTA55313.2022.9942793","url":null,"abstract":"Heart diseases are the most common diseases in the world and will continue to be the number one cause of death for a long time. Each year 17.9 million people die due to cardiovascular diseases (CVDs), an estimated 32% of all deaths worldwide. However, many heart disease factors are preventable or treatable. If these factors are prevented or treated, it is an excellent opportunity to reduce the loss of life due to heart diseases. Nowadays, data science is actively used by people, and the importance of data science is increasing daily. It is vital for humanity that heart diseases and similar medical problems can be predicted using data science. For this reason, early disease detection aims to apply statistical methods in medicine. This research determines the relation between heart diseases and other human body characteristics to early diagnosis of heart diseases. In this research, data mining approaches specifically using different data science algorithms were applied to predict patients' heart diseases, namely Naïve Bayes, Logistic Regression, Multilayer Perceptron, and Random Forest algorithms for classification and diagnosis of cardiovascular diseases prediction. Results showed that the Naïve Bayes algorithm obtained an accuracy of 88.5% and was the best among all other algorithm.","PeriodicalId":293957,"journal":{"name":"2022 IEEE Symposium on Wireless Technology & Applications (ISWTA)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122157208","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Sensitivity Enhancement of CSRR Sensor Using Interdigital Structure in Detecting Ammoniacal Nitrogen for Water Quality Applications 数字间结构CSRR传感器在水质氨态氮检测中的灵敏度增强研究
2022 IEEE Symposium on Wireless Technology & Applications (ISWTA) Pub Date : 2022-08-17 DOI: 10.1109/ISWTA55313.2022.9942787
S. A. Enche Ab Rahim, N. F. Zulkifli, M. F. Sapuri, N. E. Abd Rashid, Z. I. Khan, N. Zakaria
{"title":"Sensitivity Enhancement of CSRR Sensor Using Interdigital Structure in Detecting Ammoniacal Nitrogen for Water Quality Applications","authors":"S. A. Enche Ab Rahim, N. F. Zulkifli, M. F. Sapuri, N. E. Abd Rashid, Z. I. Khan, N. Zakaria","doi":"10.1109/ISWTA55313.2022.9942787","DOIUrl":"https://doi.org/10.1109/ISWTA55313.2022.9942787","url":null,"abstract":"This paper presents the design of a Complementary Split Ring Resonator (CSRR) with sensitivity enhancement to detect ammoniacal nitrogen for water quality applications. Based on the literature review, the lowest concentration of AMN that has been sensed by using the CSRR is 100mg/L, which is beyond the safety level, specified by the National Water Quality Standard for Malaysia (NWQS). According to the standard, extensive water treatment is required for an AMN’s concentration of 0.9mg/L and above. To improve the sensitivity of the CSRR, an interdigital capacitor was introduced at the ring gap of the CSRR. Simulation results show that the maximum shift of the resonance frequency (0.84 GHz) was achieved with 4 fingers interdigital capacitor structure when the thickness of the ammonia layer is 0.5mm, while the initial CSRR resulted in a frequency shift of 0.61 GHz for the same thickness. Therefore, the sensitivity of the CSRR has improved with the addition of the IDS.","PeriodicalId":293957,"journal":{"name":"2022 IEEE Symposium on Wireless Technology & Applications (ISWTA)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127932347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Physical Fitness Inspection System using Deep Learning 基于深度学习的体质检测系统
2022 IEEE Symposium on Wireless Technology & Applications (ISWTA) Pub Date : 2022-08-17 DOI: 10.1109/ISWTA55313.2022.9942742
May Thu Soe, Kyaw Zaw Ye, Aung Zaw Min, Sai Myo Htet, Myo Min Hein, Bawin Aye
{"title":"Physical Fitness Inspection System using Deep Learning","authors":"May Thu Soe, Kyaw Zaw Ye, Aung Zaw Min, Sai Myo Htet, Myo Min Hein, Bawin Aye","doi":"10.1109/ISWTA55313.2022.9942742","DOIUrl":"https://doi.org/10.1109/ISWTA55313.2022.9942742","url":null,"abstract":"Object detection is an important application in deep learning technology, which is used to identify and locate objects in an image or video. It has improvement of accuracy and performance. It is various popular application such as pedestrian detection, medical images, robotics, face detection, self-driving cars, etc. The paper mainly focuses on object detection methods by including one stage object detector. In this paper, described the detection of human pose, localization, and classification of multi-person activity. We propose object detector-based human detection to detect human localization and pose classification of multi-person activity. By using the proposed detection method, obtained good performance of physical fitness inspection in real-time. The accuracy of proposed system is 99.7% and the Intersection over Union (IOU) score is 97% which were tested in real time condition.","PeriodicalId":293957,"journal":{"name":"2022 IEEE Symposium on Wireless Technology & Applications (ISWTA)","volume":"282 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131773417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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