Pub Date : 2023-01-01DOI: 10.24138/jcomss-2022-0050
D. Poljak, A. Šušnjara, A. Fišić
{"title":"Assessment of Transmitted Power Density in the Planar Multilayer Tissue Model due to Radiation from Dipole Antenna","authors":"D. Poljak, A. Šušnjara, A. Fišić","doi":"10.24138/jcomss-2022-0050","DOIUrl":"https://doi.org/10.24138/jcomss-2022-0050","url":null,"abstract":"","PeriodicalId":38910,"journal":{"name":"Journal of Communications Software and Systems","volume":"1 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69099105","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 : 2023-01-01DOI: 10.24138/jcomss-2022-0160
A. Abusukhon
{"title":"IOT Bracelets for Guiding Blind People in an Indoor Environment","authors":"A. Abusukhon","doi":"10.24138/jcomss-2022-0160","DOIUrl":"https://doi.org/10.24138/jcomss-2022-0160","url":null,"abstract":"","PeriodicalId":38910,"journal":{"name":"Journal of Communications Software and Systems","volume":"1 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69099984","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 : 2023-01-01DOI: 10.24138/jcomss-2022-0065
Mohamed El Hadi Benelhadj, Mohamed Mahmoud Deye, Y. Slimani
{"title":"Signature-based Tree for Finding Frequent Itemsets","authors":"Mohamed El Hadi Benelhadj, Mohamed Mahmoud Deye, Y. Slimani","doi":"10.24138/jcomss-2022-0065","DOIUrl":"https://doi.org/10.24138/jcomss-2022-0065","url":null,"abstract":"","PeriodicalId":38910,"journal":{"name":"Journal of Communications Software and Systems","volume":"1 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69099180","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 : 2023-01-01DOI: 10.24138/jcomss-2022-0116
Marija Todorić, Toni Mastelić
—Various distance-based clustering algorithms have been reported, but the core component of all of them is a similarity or distance measure for classification of data. Rather than setting the priority to comparison of the performance of different clustering algorithms, it may be worthy to analyze the influence of different similarity measures on the results of clustering algorithms. The main contribution of this work is a comparative study of the impact of 9 similarity measures on similarity-based trajectory clustering using DBSCAN algorithm for commercial flight dataset. The novelty in this comparison is exploring the robustness of the clustering algorithm with respect to algorithm parameter. We evaluate the accuracy of clustering, accuracy of anomaly detection, algorithmic efficiency, and we determine the behavior profile for each measure. We show that DTW and Frechet distance lead to the best clustering results, while LCSS and Hausdorff Cosine should be avoided for this task.
{"title":"Comparison of Similarity Measures for Trajectory Clustering - Aviation Use Case","authors":"Marija Todorić, Toni Mastelić","doi":"10.24138/jcomss-2022-0116","DOIUrl":"https://doi.org/10.24138/jcomss-2022-0116","url":null,"abstract":"—Various distance-based clustering algorithms have been reported, but the core component of all of them is a similarity or distance measure for classification of data. Rather than setting the priority to comparison of the performance of different clustering algorithms, it may be worthy to analyze the influence of different similarity measures on the results of clustering algorithms. The main contribution of this work is a comparative study of the impact of 9 similarity measures on similarity-based trajectory clustering using DBSCAN algorithm for commercial flight dataset. The novelty in this comparison is exploring the robustness of the clustering algorithm with respect to algorithm parameter. We evaluate the accuracy of clustering, accuracy of anomaly detection, algorithmic efficiency, and we determine the behavior profile for each measure. We show that DTW and Frechet distance lead to the best clustering results, while LCSS and Hausdorff Cosine should be avoided for this task.","PeriodicalId":38910,"journal":{"name":"Journal of Communications Software and Systems","volume":"1 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69099924","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 : 2023-01-01DOI: 10.24138/jcomss-2023-0100
Dorijan Sablic-Nemec, M. Joler
—In this paper, we propose a streamlined design and automation of a horn antenna and its rectangular waveguide-based feeder using computer simulation-based optimizations and additive manufacturing. The approach enables time-effectiveness with a holistic design of the two components, while achieving advantageous results of the antenna parameters. The approach is described in comparison to other works and the results presented and discussed on the antenna models manufactured for two mid-band frequencies: at 2437 MHz and 5250 MHz. The optimum-search algorithm was able to find the parameter values that resulted in more than 25 dB improvement in S 11 -parameter values in comparison to the initial design based on the textbook theory. For the 2437-MHz antenna, the achieved bandwidth, using the optimized parameters, was 16.52% wide comparing to 5.14% bandwidth that was the result based on the analytical expressions. In case of the 5250-MHz antenna, the optimized antenna bandwidth reached 25.47%. The fabricated antenna gain was close to the design value.
{"title":"An Automated Approach to Horn Antenna Impedance Matching and Manufacturing Using 3D Printing","authors":"Dorijan Sablic-Nemec, M. Joler","doi":"10.24138/jcomss-2023-0100","DOIUrl":"https://doi.org/10.24138/jcomss-2023-0100","url":null,"abstract":"—In this paper, we propose a streamlined design and automation of a horn antenna and its rectangular waveguide-based feeder using computer simulation-based optimizations and additive manufacturing. The approach enables time-effectiveness with a holistic design of the two components, while achieving advantageous results of the antenna parameters. The approach is described in comparison to other works and the results presented and discussed on the antenna models manufactured for two mid-band frequencies: at 2437 MHz and 5250 MHz. The optimum-search algorithm was able to find the parameter values that resulted in more than 25 dB improvement in S 11 -parameter values in comparison to the initial design based on the textbook theory. For the 2437-MHz antenna, the achieved bandwidth, using the optimized parameters, was 16.52% wide comparing to 5.14% bandwidth that was the result based on the analytical expressions. In case of the 5250-MHz antenna, the optimized antenna bandwidth reached 25.47%. The fabricated antenna gain was close to the design value.","PeriodicalId":38910,"journal":{"name":"Journal of Communications Software and Systems","volume":"1 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69101152","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 : 2023-01-01DOI: 10.24138/jcomss-2022-0163
Noor Mohammedali, T. Kanakis, Ali Al-Sherbaz, Michael Opoku Agyeman
{"title":"Management and Evaluation of the Performance of end-to-end 5G Inter/Intra Slicing using Machine Learning in a Sustainable Environment","authors":"Noor Mohammedali, T. Kanakis, Ali Al-Sherbaz, Michael Opoku Agyeman","doi":"10.24138/jcomss-2022-0163","DOIUrl":"https://doi.org/10.24138/jcomss-2022-0163","url":null,"abstract":"","PeriodicalId":38910,"journal":{"name":"Journal of Communications Software and Systems","volume":"172 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69100585","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 : 2023-01-01DOI: 10.24138/jcomss-2023-0047
Hrvoje Karna, Maja Braović, L. Vicković, D. Krstinić
— This paper explores the problem of media content data analysis with the focus on the phenomenon of vaccination, closely related to the COVID-19 pandemic. The presented research is an extension of the previous work, but it differs in two main areas. Firstly, the text corpus submitted to the analysis has been considerably increased. Secondly, the previous data analysis was performed on the body part of the posts, while now it is focused on the most prominent part of the news posts, their headlines. This change from body to headline analysis was provoked by significant differences in their characteristics and the fact that most people read only headlines. Described data acquisition uses an advanced content collection approach followed by the modeling process, during which a set of natural language processing algorithms were applied. To enable the comparison, the model uses the same set of algorithms in the modeling phase like in previous work. The main contributions of the work are manifested in: i) approaching the problem from a new perspective, ii) applying more efficient method of data collection, and crucially iii) enabling the comparison of analysis results for individual parts of the content, which ensured a comprehensive insight into the characteristics of news posts.
{"title":"Data Analysis of the Web News Headlines based on Natural Language Processing","authors":"Hrvoje Karna, Maja Braović, L. Vicković, D. Krstinić","doi":"10.24138/jcomss-2023-0047","DOIUrl":"https://doi.org/10.24138/jcomss-2023-0047","url":null,"abstract":"— This paper explores the problem of media content data analysis with the focus on the phenomenon of vaccination, closely related to the COVID-19 pandemic. The presented research is an extension of the previous work, but it differs in two main areas. Firstly, the text corpus submitted to the analysis has been considerably increased. Secondly, the previous data analysis was performed on the body part of the posts, while now it is focused on the most prominent part of the news posts, their headlines. This change from body to headline analysis was provoked by significant differences in their characteristics and the fact that most people read only headlines. Described data acquisition uses an advanced content collection approach followed by the modeling process, during which a set of natural language processing algorithms were applied. To enable the comparison, the model uses the same set of algorithms in the modeling phase like in previous work. The main contributions of the work are manifested in: i) approaching the problem from a new perspective, ii) applying more efficient method of data collection, and crucially iii) enabling the comparison of analysis results for individual parts of the content, which ensured a comprehensive insight into the characteristics of news posts.","PeriodicalId":38910,"journal":{"name":"Journal of Communications Software and Systems","volume":"4 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69100806","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 : 2023-01-01DOI: 10.24138/jcomss-2023-0052
Lalitha H, Navin Kumar
— The next-generation of wireless local area network systems are being conceptualized with new applications, smart devices and use cases which mandate unprecedented levels of high data rates, spectral efficiency, reliability, low latency and high energy efficiency. The index modulated orthogonal frequency division multiplexing (OFDM-IM) stands out as the most endearing candidate for physical layer modulation technique which provides a smooth transit to green communications. However, OFDM-IM being a multicarrier technique similar to classical OFDM is also very sensitive to frequency synchronization errors and needs to be addressed on priority. In this article, a novel algorithm is proposed which estimates and corrects the carrier frequency offset at the receiver and the algorithm’s performance is compared with two frequency domain variants of OFDM-IM and the classical OFDM under the same channel conditions and the simulation results show that our algorithm is not only capable of meeting the standard requirement of ±20ppm but can handle higher offsets till ±30ppm.
{"title":"Frequency Synchronization in Frequency Domain OFDM-IM based WLAN Systems","authors":"Lalitha H, Navin Kumar","doi":"10.24138/jcomss-2023-0052","DOIUrl":"https://doi.org/10.24138/jcomss-2023-0052","url":null,"abstract":"— The next-generation of wireless local area network systems are being conceptualized with new applications, smart devices and use cases which mandate unprecedented levels of high data rates, spectral efficiency, reliability, low latency and high energy efficiency. The index modulated orthogonal frequency division multiplexing (OFDM-IM) stands out as the most endearing candidate for physical layer modulation technique which provides a smooth transit to green communications. However, OFDM-IM being a multicarrier technique similar to classical OFDM is also very sensitive to frequency synchronization errors and needs to be addressed on priority. In this article, a novel algorithm is proposed which estimates and corrects the carrier frequency offset at the receiver and the algorithm’s performance is compared with two frequency domain variants of OFDM-IM and the classical OFDM under the same channel conditions and the simulation results show that our algorithm is not only capable of meeting the standard requirement of ±20ppm but can handle higher offsets till ±30ppm.","PeriodicalId":38910,"journal":{"name":"Journal of Communications Software and Systems","volume":"1 1","pages":""},"PeriodicalIF":0.7,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"69100812","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 : 2023-01-01DOI: 10.24138/jcomss-2023-0091
Md Ashikur Rahman, Syful Islam, Yusuf Sulistyo Nugroho, Fatah Yasin Al Irsyadi, Md Javed Hossain
Computers have become increasingly vulnerable to malicious attacks with an increase in popularity and the proliferation of open system architectures. There are numerous malware detection technologies available to protect the computer operating system from such attacks. This type of malware detector targets programs based on patterns detected in the properties of computer applications. As the amount of analytical data increases, the computer defense system is adversely affected. The performance of the detection mechanism has been hindered due to the presence of numerous irrelevant characteristics. The goal of this study is to provide a feature selection approach that will help malware detection systems be more accurate by detecting pertinent and significant traits. Furthermore, by selecting the most important features, it is possible to maintain an acceptable level of accuracy in the detection of malware while significantly lowering the computational cost. The proposed method displays the most important features (MIFs) obtained from each machine learning method, including data cleaning and feature selection. Furthermore, the method applies six machine learning classification techniques to the selected feature set. Several classifiers were evaluated based on several characteristics for malware detection, including Support Vector Machines (SVM), Logistic Regression (LR), K-nearest neighbor (K-NN), Decision Tree (DT), Naive Bayes (NB), and Random Forest (RF). Our suggested model was tested on two malware datasets to determine its effectiveness. In terms of accuracy, precision, F1 scores, and recall, the experimental findings show that RF and DT classifiers beat other techniques.
{"title":"An Exploratory Analysis of Feature Selection for Malware Detection with Simple Machine Learning Algorithms","authors":"Md Ashikur Rahman, Syful Islam, Yusuf Sulistyo Nugroho, Fatah Yasin Al Irsyadi, Md Javed Hossain","doi":"10.24138/jcomss-2023-0091","DOIUrl":"https://doi.org/10.24138/jcomss-2023-0091","url":null,"abstract":"Computers have become increasingly vulnerable to malicious attacks with an increase in popularity and the proliferation of open system architectures. There are numerous malware detection technologies available to protect the computer operating system from such attacks. This type of malware detector targets programs based on patterns detected in the properties of computer applications. As the amount of analytical data increases, the computer defense system is adversely affected. The performance of the detection mechanism has been hindered due to the presence of numerous irrelevant characteristics. The goal of this study is to provide a feature selection approach that will help malware detection systems be more accurate by detecting pertinent and significant traits. Furthermore, by selecting the most important features, it is possible to maintain an acceptable level of accuracy in the detection of malware while significantly lowering the computational cost. The proposed method displays the most important features (MIFs) obtained from each machine learning method, including data cleaning and feature selection. Furthermore, the method applies six machine learning classification techniques to the selected feature set. Several classifiers were evaluated based on several characteristics for malware detection, including Support Vector Machines (SVM), Logistic Regression (LR), K-nearest neighbor (K-NN), Decision Tree (DT), Naive Bayes (NB), and Random Forest (RF). Our suggested model was tested on two malware datasets to determine its effectiveness. In terms of accuracy, precision, F1 scores, and recall, the experimental findings show that RF and DT classifiers beat other techniques.","PeriodicalId":38910,"journal":{"name":"Journal of Communications Software and Systems","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135440321","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 : 2023-01-01DOI: 10.24138/jcomss-2023-0131
Ahmed N. Jabbar, Samir J. Almuraab, Abdulkareem A. Kadhim
A new upgrade to the SIMâOFDM is suggested to solve a critical problem that crashes the system even over noiseless channel. This problem is the interference of the zeros at the IFFT output with the BOOK's zeros that confuses the receiver during demodulation which leads to BER accumulation. The suggested solution is to use a threshold to differentiate the data carried by the BOOK from the IFFT's symbols. The new system is called Threshold SIMâOFDM (TSIMâOFDM). The mathematical analysis of TSIMâOFDM proves it operates normally and meets the theoretical bounds. The TSIMâOFDM preserves the probability of 1 equal to 1/2. This preservation comes from the direct connection of the ON/OFF switching bits to the subcarrier which overrides the majority condition. This new switching technique simplifies the system operation resulting in higher transmission speed and increased spectral and power efficiency. A simple approach to derive the BER for the SIMâOFDM is presented which proves that the SIMâOFDM will never reach zero BER level unlike the TSIMâOFDM. The simulation results show that the TSIMâOFDM BER reaches zero level and the output power is almost half of the OFDM. Adding the threshold will increase the transmitted power slightly and tends to decrease with the increase of IFFT length.
{"title":"Upgrading SIM–OFDM Using a Threshold for Correct Operation with Analytical Proofs","authors":"Ahmed N. Jabbar, Samir J. Almuraab, Abdulkareem A. Kadhim","doi":"10.24138/jcomss-2023-0131","DOIUrl":"https://doi.org/10.24138/jcomss-2023-0131","url":null,"abstract":"A new upgrade to the SIMâOFDM is suggested to solve a critical problem that crashes the system even over noiseless channel. This problem is the interference of the zeros at the IFFT output with the BOOK's zeros that confuses the receiver during demodulation which leads to BER accumulation. The suggested solution is to use a threshold to differentiate the data carried by the BOOK from the IFFT's symbols. The new system is called Threshold SIMâOFDM (TSIMâOFDM). The mathematical analysis of TSIMâOFDM proves it operates normally and meets the theoretical bounds. The TSIMâOFDM preserves the probability of 1 equal to 1/2. This preservation comes from the direct connection of the ON/OFF switching bits to the subcarrier which overrides the majority condition. This new switching technique simplifies the system operation resulting in higher transmission speed and increased spectral and power efficiency. A simple approach to derive the BER for the SIMâOFDM is presented which proves that the SIMâOFDM will never reach zero BER level unlike the TSIMâOFDM. The simulation results show that the TSIMâOFDM BER reaches zero level and the output power is almost half of the OFDM. Adding the threshold will increase the transmitted power slightly and tends to decrease with the increase of IFFT length.","PeriodicalId":38910,"journal":{"name":"Journal of Communications Software and Systems","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135659127","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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