Pub Date : 2020-06-01DOI: 10.1109/ECTI-CON49241.2020.9158110
Omer Ali, M. Ishak, Mohamad Adzhar Md Zawawi, Mohamad Tarmizi Abu Seman, Muhammad Kamran Liaquat Bhatti, Zainatul Yushaniza Mohamed Yusoff
Energy conservation and optimization remains the top researched field for wireless sensor networks, which is one of a subsets and the underlying communication medium for Internet of Things (IoT) devices. These constrained IoT devices are mostly battery operated and therefore requires robust and optimized algorithms to improve resources utilization which inherently increases the life-span for these devices without compromising Quality of Service (QoS). The communication radios on these nodes are the most power hogging components. Therefore, a major focus has always been on MAC and cross-layer protocols to optimize the duty cycle of radios for the conservation of energy. This paper presents a unique scheme for dynamically adjusting the duty cycle of nodes based on the arrival of incoming infrequent source node sensor data over which eliminates the need for frequent periodic channel assessment for network activity. The proposed scheme also makes use of ultra-low wakeUp receivers on the receiver nodes to further aid the node in energy conservation. In this paper, we describe the details of our design scheme, implementation and evaluation details in Contiki OS and Cooja simulator. The results are micro-benchmarked with ContikiMAC and X-MAC protocols, and an improvement in radio duty cycle is reported for lighter network traffic.
{"title":"A MAC Protocol for Energy Efficient Wireless Communication Leveraging Wake-Up Estimations on Sender Data","authors":"Omer Ali, M. Ishak, Mohamad Adzhar Md Zawawi, Mohamad Tarmizi Abu Seman, Muhammad Kamran Liaquat Bhatti, Zainatul Yushaniza Mohamed Yusoff","doi":"10.1109/ECTI-CON49241.2020.9158110","DOIUrl":"https://doi.org/10.1109/ECTI-CON49241.2020.9158110","url":null,"abstract":"Energy conservation and optimization remains the top researched field for wireless sensor networks, which is one of a subsets and the underlying communication medium for Internet of Things (IoT) devices. These constrained IoT devices are mostly battery operated and therefore requires robust and optimized algorithms to improve resources utilization which inherently increases the life-span for these devices without compromising Quality of Service (QoS). The communication radios on these nodes are the most power hogging components. Therefore, a major focus has always been on MAC and cross-layer protocols to optimize the duty cycle of radios for the conservation of energy. This paper presents a unique scheme for dynamically adjusting the duty cycle of nodes based on the arrival of incoming infrequent source node sensor data over which eliminates the need for frequent periodic channel assessment for network activity. The proposed scheme also makes use of ultra-low wakeUp receivers on the receiver nodes to further aid the node in energy conservation. In this paper, we describe the details of our design scheme, implementation and evaluation details in Contiki OS and Cooja simulator. The results are micro-benchmarked with ContikiMAC and X-MAC protocols, and an improvement in radio duty cycle is reported for lighter network traffic.","PeriodicalId":371552,"journal":{"name":"2020 17th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132764087","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}
A personalized recommendation has been an active area of research. Many companies such as Facebook, Amazon, and eBay have incorporated such functionality to enhance user experience and engagement. In today’s market, streaming digital contents (e.g., online movies) have become ubiquitous and accessi-ble from anywhere and anytime. The rapid growth of streaming market urges many providers to offer a personalized experience to capture customer loyalty. In this paper, we present a movie recommending system based on our proposed rating prediction algorithm using singular value decomposition (SVD). Empirical evaluation is conducted on two tasks: rating prediction and movie recommendation, using two case studies from MovieLens and Thaiware Movie.
{"title":"SGD-Rec: A Matrix Decomposition Based Model for Personalized Movie Recommendation","authors":"Siripen Pongpaichet, Thatchapon Unprasert, Suppawong Tuarob, Petch Sajjacholapunt","doi":"10.1109/ecti-con49241.2020.9158308","DOIUrl":"https://doi.org/10.1109/ecti-con49241.2020.9158308","url":null,"abstract":"A personalized recommendation has been an active area of research. Many companies such as Facebook, Amazon, and eBay have incorporated such functionality to enhance user experience and engagement. In today’s market, streaming digital contents (e.g., online movies) have become ubiquitous and accessi-ble from anywhere and anytime. The rapid growth of streaming market urges many providers to offer a personalized experience to capture customer loyalty. In this paper, we present a movie recommending system based on our proposed rating prediction algorithm using singular value decomposition (SVD). Empirical evaluation is conducted on two tasks: rating prediction and movie recommendation, using two case studies from MovieLens and Thaiware Movie.","PeriodicalId":371552,"journal":{"name":"2020 17th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131847932","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 : 2020-06-01DOI: 10.1109/ecti-con49241.2020.9158322
P. Kranoongon, B. Techaumnat
In recent years, the composite cross-arm is used in the transmission line system. The electric field analysis at the composite cross-arm is very important for the high voltage system. The electric field at corona rings and grading rings must be confirmed that can withstand the corona threshold field. But the geometry of cross-arm is very complicated for computing. Therefore, the objective of this paper is to compute the 3 phase electric field by using ANSYS Maxwell software base on the finite element method (FEM). We separately calculate in each phase in order to reduce the computation time. Firstly, the 3-dimensional (3D) model of composite crossarm is simulated in a close domain. Then the average potential from the 2-dimensional (2D) model is defined as a boundary condition in case of the 3-dimensional model. Finally, the maximum electric field values in each phase are compared. From the results, the highest electric field occurs at phase B, and the electric field of tension-type grading ring is slightly higher than other types of ring. However, all values are lower than the electric field criteria.
{"title":"Electric Field Analysis of the 230 kV AC Transmission Line System for an Limited Area","authors":"P. Kranoongon, B. Techaumnat","doi":"10.1109/ecti-con49241.2020.9158322","DOIUrl":"https://doi.org/10.1109/ecti-con49241.2020.9158322","url":null,"abstract":"In recent years, the composite cross-arm is used in the transmission line system. The electric field analysis at the composite cross-arm is very important for the high voltage system. The electric field at corona rings and grading rings must be confirmed that can withstand the corona threshold field. But the geometry of cross-arm is very complicated for computing. Therefore, the objective of this paper is to compute the 3 phase electric field by using ANSYS Maxwell software base on the finite element method (FEM). We separately calculate in each phase in order to reduce the computation time. Firstly, the 3-dimensional (3D) model of composite crossarm is simulated in a close domain. Then the average potential from the 2-dimensional (2D) model is defined as a boundary condition in case of the 3-dimensional model. Finally, the maximum electric field values in each phase are compared. From the results, the highest electric field occurs at phase B, and the electric field of tension-type grading ring is slightly higher than other types of ring. However, all values are lower than the electric field criteria.","PeriodicalId":371552,"journal":{"name":"2020 17th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134164370","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 : 2020-06-01DOI: 10.1109/ecti-con49241.2020.9158286
W. Nuankaew, Jaree Thongkam
This paper presents methods to improve the prediction of student academic performance using feature selection by removing misclassified instances and Synthetic Minority Over-Sampling Technique. It compares the performance of seven students’ academic performance prediction models, namely Naïve Bayes, Sequential Minimum Optimization, Artificial Neural Network, k-Nearest Neighbor, REPTree, Partial decision trees, and Random Forest. The data were collected from 9,458 students at the Rajabhat Maha Sarakham University, Thailand during 2015 - 2018. The model performances were evaluated with precision, recall, and F-measure. The experimental results indicated that the Random Forest approach significantly improves the performance of students’ academic performance prediction models with precision up to 41.70%, recall up to 41.40% and F-measure up to 41.60%, respectively.
{"title":"Improving Student Academic Performance Prediction Models using Feature Selection","authors":"W. Nuankaew, Jaree Thongkam","doi":"10.1109/ecti-con49241.2020.9158286","DOIUrl":"https://doi.org/10.1109/ecti-con49241.2020.9158286","url":null,"abstract":"This paper presents methods to improve the prediction of student academic performance using feature selection by removing misclassified instances and Synthetic Minority Over-Sampling Technique. It compares the performance of seven students’ academic performance prediction models, namely Naïve Bayes, Sequential Minimum Optimization, Artificial Neural Network, k-Nearest Neighbor, REPTree, Partial decision trees, and Random Forest. The data were collected from 9,458 students at the Rajabhat Maha Sarakham University, Thailand during 2015 - 2018. The model performances were evaluated with precision, recall, and F-measure. The experimental results indicated that the Random Forest approach significantly improves the performance of students’ academic performance prediction models with precision up to 41.70%, recall up to 41.40% and F-measure up to 41.60%, respectively.","PeriodicalId":371552,"journal":{"name":"2020 17th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)","volume":"42 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134287800","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 : 2020-06-01DOI: 10.1109/ECTI-CON49241.2020.9158220
S. Wilainuch, T. Kasetkasem, N. Sugino, T. Phatrapornnant, S. Marukatat
The use of machine learning technology with remote sensing image analysis, especially for the land cover mapping requires experts and huge resources because every pixel in the training set must be labeled. This task is time-consuming and tedious. Therefore, a better strategy is to only identify what classes are present in an image without specifying where they are. In this way, a large number of remote sensing images can be labeled quickly. To achieve this goal, we employed the attention layer to create the attention map. The attention map is then further segmented to produce the final l and c over m ap where every pixel in an image will be labeled. We have tested the performance of our proposed algorithm with UC Merced Dataset and achieved 79.7 % in identifying the presence of land cover classes and 71.2 % accuracy in the labeling of all pixels
{"title":"On the Use of Attention Map for Land Cover Mapping","authors":"S. Wilainuch, T. Kasetkasem, N. Sugino, T. Phatrapornnant, S. Marukatat","doi":"10.1109/ECTI-CON49241.2020.9158220","DOIUrl":"https://doi.org/10.1109/ECTI-CON49241.2020.9158220","url":null,"abstract":"The use of machine learning technology with remote sensing image analysis, especially for the land cover mapping requires experts and huge resources because every pixel in the training set must be labeled. This task is time-consuming and tedious. Therefore, a better strategy is to only identify what classes are present in an image without specifying where they are. In this way, a large number of remote sensing images can be labeled quickly. To achieve this goal, we employed the attention layer to create the attention map. The attention map is then further segmented to produce the final l and c over m ap where every pixel in an image will be labeled. We have tested the performance of our proposed algorithm with UC Merced Dataset and achieved 79.7 % in identifying the presence of land cover classes and 71.2 % accuracy in the labeling of all pixels","PeriodicalId":371552,"journal":{"name":"2020 17th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133403420","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 : 2020-06-01DOI: 10.1109/ECTI-CON49241.2020.9158094
Yuzana Hlaing, Nyein Aye Maung Maung
Time-based wireless indoor localization recently stands as the state-of-the-art situation for the up-to-date real time application areas. Synchronizing time among the wireless nodes may still be the major challenging problem for time- based indoor localization on wireless networks. The main reason of this problem is the difficulty and complexity of using standard time synchronization protocols such as Network Time Protocol (NTP), and Coordinated Universal Time (UTC) on wireless networks. Besides, the limitations of the wireless networks restrict the consideration of which time synchronization protocols should be applied on which wireless communication technologies such as WiFi, LiFi, Bluetooth, UWB, Ultrasonic, ZigBee, etc, for wireless time synchronization. Generally, time synchronization schemes support better accuracy if and only if precise random delay model can be implemented for the estimation of random delay caused by the real environmental impacts. In this paper, a ZigBee-based hybrid wireless time synchronization approach, which is required as the first and vital step for time-based wireless indoor localization, is proposed. In order to provide precise synchronization accuracy of the proposed hybrid approach to be more precise, appropriate random delay model is implemented by applying the empirical approach on ZigBee- based test-bed. By using the empirical data obtained from anchor-to-anchor packet communications, random delay is estimated using Gaussian random delay model and then least square regression model is applied to improve synchronization accuracy. In accordance with the experimental evaluation results, it highlights that synchronization performance of the proposed approach is significantly improved.
{"title":"Hybrid Time Synchronization for ZigBee Networks: An Empirical Approach","authors":"Yuzana Hlaing, Nyein Aye Maung Maung","doi":"10.1109/ECTI-CON49241.2020.9158094","DOIUrl":"https://doi.org/10.1109/ECTI-CON49241.2020.9158094","url":null,"abstract":"Time-based wireless indoor localization recently stands as the state-of-the-art situation for the up-to-date real time application areas. Synchronizing time among the wireless nodes may still be the major challenging problem for time- based indoor localization on wireless networks. The main reason of this problem is the difficulty and complexity of using standard time synchronization protocols such as Network Time Protocol (NTP), and Coordinated Universal Time (UTC) on wireless networks. Besides, the limitations of the wireless networks restrict the consideration of which time synchronization protocols should be applied on which wireless communication technologies such as WiFi, LiFi, Bluetooth, UWB, Ultrasonic, ZigBee, etc, for wireless time synchronization. Generally, time synchronization schemes support better accuracy if and only if precise random delay model can be implemented for the estimation of random delay caused by the real environmental impacts. In this paper, a ZigBee-based hybrid wireless time synchronization approach, which is required as the first and vital step for time-based wireless indoor localization, is proposed. In order to provide precise synchronization accuracy of the proposed hybrid approach to be more precise, appropriate random delay model is implemented by applying the empirical approach on ZigBee- based test-bed. By using the empirical data obtained from anchor-to-anchor packet communications, random delay is estimated using Gaussian random delay model and then least square regression model is applied to improve synchronization accuracy. In accordance with the experimental evaluation results, it highlights that synchronization performance of the proposed approach is significantly improved.","PeriodicalId":371552,"journal":{"name":"2020 17th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115092587","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}
Topic modeling is an unsupervised learning approach, which can automatically discover the hidden thematic structure in text documents. For text mining, topic modeling is a language-independent technique that disregards grammar and word order. Apart from semantic and structural issues, Thai language is typically considered more complex than others. Due to the lack of word delimiter and a surfeit of composite words. Errors from word tokenization can create significant problems for any post processes of text, such as document retrieval, sentiment analysis, machine translation, etc., adversely decreasing the performance of text applications. Despite a strong correlation between word ordering and semantic meaning, topic modeling has been widely reported that it can extract latent information, aka. latent topic or latent semantic, encoded in documents. Although there were few previous research works on studying topic modeling in Thai language, they mostly focused on upstream processes of Natural Language Processing (NLP) in, for example, applying a refined stop-word list to, or adding N-gram on a single specific topic modeling method. To our knowledge, this paper is the first to explore different topic modeling approaches, i.e., Latent Dirichlet Allocation (LDA) and Nonnegative Metrix Factorization (NMF), in Thai Language to compare their coherence. We also employ and compare a set of state-of-the-art evaluation metrics based on Topic Coherence.
主题建模是一种无监督学习方法，可以自动发现文本文档中隐藏的主题结构。对于文本挖掘，主题建模是一种不考虑语法和词序的独立于语言的技术。除了语义和结构问题，泰语通常被认为比其他语言更复杂。由于缺乏词分隔符和过量的复合词。单词标记化产生的错误会给文本的任何后处理(如文档检索、情感分析、机器翻译等)带来严重的问题，从而降低文本应用程序的性能。尽管词序和语义之间有很强的相关性，主题建模已经被广泛报道，它可以提取潜在的信息，即。在文档中编码的潜在主题或潜在语义。虽然之前对泰语主题建模的研究较少，但大多集中在自然语言处理(Natural language Processing, NLP)的上游过程，如将一个精炼的停止词列表应用于，或在单个特定主题建模方法上添加N-gram。据我们所知，本文首次探讨了不同的主题建模方法，即潜伏狄利克雷分配(LDA)和非负矩阵分解(NMF)，并比较了它们在泰语中的一致性。我们还采用并比较了一套基于主题一致性的最先进的评估指标。
{"title":"Discover Underlying Topics in Thai News Articles: A Comparative Study of Probabilistic and Matrix Factorization Approaches","authors":"Pimpitcha Pitichotchokphokhin, Piyawat Chuangkrud, Kongkan Kalakan, B. Suntisrivaraporn, Teerapong Leelanupab, Nont Kanungsukkasem","doi":"10.1109/ecti-con49241.2020.9158065","DOIUrl":"https://doi.org/10.1109/ecti-con49241.2020.9158065","url":null,"abstract":"Topic modeling is an unsupervised learning approach, which can automatically discover the hidden thematic structure in text documents. For text mining, topic modeling is a language-independent technique that disregards grammar and word order. Apart from semantic and structural issues, Thai language is typically considered more complex than others. Due to the lack of word delimiter and a surfeit of composite words. Errors from word tokenization can create significant problems for any post processes of text, such as document retrieval, sentiment analysis, machine translation, etc., adversely decreasing the performance of text applications. Despite a strong correlation between word ordering and semantic meaning, topic modeling has been widely reported that it can extract latent information, aka. latent topic or latent semantic, encoded in documents. Although there were few previous research works on studying topic modeling in Thai language, they mostly focused on upstream processes of Natural Language Processing (NLP) in, for example, applying a refined stop-word list to, or adding N-gram on a single specific topic modeling method. To our knowledge, this paper is the first to explore different topic modeling approaches, i.e., Latent Dirichlet Allocation (LDA) and Nonnegative Metrix Factorization (NMF), in Thai Language to compare their coherence. We also employ and compare a set of state-of-the-art evaluation metrics based on Topic Coherence.","PeriodicalId":371552,"journal":{"name":"2020 17th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115205975","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 : 2020-06-01DOI: 10.1109/ecti-con49241.2020.9158280
R. Punchalard
A constrained adaptive IIR notch filter (c-ANF) using weighted least square (WLS) algorithm (c-ANF-WLS) is introduced for frequency estimation of a single real tone embed in Gaussian noise. As compared with some previous techniques, the proposed algorithm exhibits better performance in terms of both convergence rate and steady state mean square error (MSE). Computer simulation results are provided to assert the claim.
{"title":"Frequency Estimation Based On WLS-Constrained Adaptive Notch Filter","authors":"R. Punchalard","doi":"10.1109/ecti-con49241.2020.9158280","DOIUrl":"https://doi.org/10.1109/ecti-con49241.2020.9158280","url":null,"abstract":"A constrained adaptive IIR notch filter (c-ANF) using weighted least square (WLS) algorithm (c-ANF-WLS) is introduced for frequency estimation of a single real tone embed in Gaussian noise. As compared with some previous techniques, the proposed algorithm exhibits better performance in terms of both convergence rate and steady state mean square error (MSE). Computer simulation results are provided to assert the claim.","PeriodicalId":371552,"journal":{"name":"2020 17th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117128848","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 : 2020-06-01DOI: 10.1109/ECTI-CON49241.2020.9157906
Sathaporn Konjunthes, W. Thaiwirot, P. Akkaraekthalin
This paper presents a wideband circularly polarized stacked patch antenna with truncated corners ground plane for universal UHF RFID reader. The configuration of the antenna composes of a slanted elliptical patch, corner truncated patch, a horizontally meandered strip (HMS), and corner truncated ground plane. One end of the HMS is connected to an SMA connector, while the other end is connected to the radiating patch via probe. In order to improve the bandwidth, the parasitic patch is used by placing above the radiating patch. From the simulated results, the proposed antenna has an impedance bandwidth of about 18.6% (800 – 965 MHz), a 3-dB axial ratio (AR) bandwidth of around 18.3% (816 – 981 MHz), and maximum gain of 8.4 dBi. The proposed antenna can operate in the frequency range of 840 – 960 MHz. Therefore, it is suitable for applying in universal UHF RFID reader.
{"title":"A Wideband Circularly Polarized Stacked Patch Antenna With Truncated Corners Ground Plane for Universal UHF RFID Reader","authors":"Sathaporn Konjunthes, W. Thaiwirot, P. Akkaraekthalin","doi":"10.1109/ECTI-CON49241.2020.9157906","DOIUrl":"https://doi.org/10.1109/ECTI-CON49241.2020.9157906","url":null,"abstract":"This paper presents a wideband circularly polarized stacked patch antenna with truncated corners ground plane for universal UHF RFID reader. The configuration of the antenna composes of a slanted elliptical patch, corner truncated patch, a horizontally meandered strip (HMS), and corner truncated ground plane. One end of the HMS is connected to an SMA connector, while the other end is connected to the radiating patch via probe. In order to improve the bandwidth, the parasitic patch is used by placing above the radiating patch. From the simulated results, the proposed antenna has an impedance bandwidth of about 18.6% (800 – 965 MHz), a 3-dB axial ratio (AR) bandwidth of around 18.3% (816 – 981 MHz), and maximum gain of 8.4 dBi. The proposed antenna can operate in the frequency range of 840 – 960 MHz. Therefore, it is suitable for applying in universal UHF RFID reader.","PeriodicalId":371552,"journal":{"name":"2020 17th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117173939","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 : 2020-06-01DOI: 10.1109/ecti-con49241.2020.9158252
K. Phaebua, A. Boonpoonga, S. Burintramart
This paper proposes a study of a time-domain ground penetrating radar (GPR) signal by using the time- domain uniform geometrical theory of diffraction (UTD) method. The monostatic GPR system is employed in this study. Rays tracing method is employed to find the reflected ray and diffracted ray paths between the transmitting antenna (Tx) and the receiving antenna (Rx). Moreover, the conventional UTD method is adapted to calculate the frequency-domain transfer function of the electric field between Tx antenna and the Rx antenna. The medium including air, ground and underground objects are taken into account. Finally, the received time-domain GPR signal is obtained by using the inverse fast Fourier transform (iFFT) method. The calculated results found that the time-domain GPR signal can be calculated by using the time-domain UTD method. The ground reflection, object reflection and object diffraction time-domain signal can be separately calculated. The reflected signal from the ground and an underground curved object can be illustrated.
{"title":"Time-Domain GPR Signal Prediction by Using Time-Domain UTD Method","authors":"K. Phaebua, A. Boonpoonga, S. Burintramart","doi":"10.1109/ecti-con49241.2020.9158252","DOIUrl":"https://doi.org/10.1109/ecti-con49241.2020.9158252","url":null,"abstract":"This paper proposes a study of a time-domain ground penetrating radar (GPR) signal by using the time- domain uniform geometrical theory of diffraction (UTD) method. The monostatic GPR system is employed in this study. Rays tracing method is employed to find the reflected ray and diffracted ray paths between the transmitting antenna (Tx) and the receiving antenna (Rx). Moreover, the conventional UTD method is adapted to calculate the frequency-domain transfer function of the electric field between Tx antenna and the Rx antenna. The medium including air, ground and underground objects are taken into account. Finally, the received time-domain GPR signal is obtained by using the inverse fast Fourier transform (iFFT) method. The calculated results found that the time-domain GPR signal can be calculated by using the time-domain UTD method. The ground reflection, object reflection and object diffraction time-domain signal can be separately calculated. The reflected signal from the ground and an underground curved object can be illustrated.","PeriodicalId":371552,"journal":{"name":"2020 17th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117287515","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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