Pub Date : 2020-12-03DOI: 10.1109/ICSEC51790.2020.9375442
P. Verma
Vehicular Adhoc Network supports numerous applications over the limited bandwidth resource available. To efficiently utilize this available resources, multi-channel operation supported by IEEE 1609.4 protocol is incorporated within vehicular network. Taking into consideration this fact, the paper presents a MAC model supporting multi-channel operation to efficiently utilize the limited bandwidth resource. The proposed model prioritizes safety messages over non-safety messages alongwith an added feature that each non-safety messages are disseminated only when the preceding safety message dissemination is completed, thus supporting multichannel operation. The simulation is performed using MATLAB’15 Simulink. The obtained simulation result provides evidence that the delay experienced by safety messages are negligible as compared to non-safety messages. Also, for the proposed model, a multi-channel utilization of 1 is attained throughout the simulation run.
{"title":"Modeling and Performance Analysis of IEEE 1609.4 Multi-Channel Operation in Vehicular Networks","authors":"P. Verma","doi":"10.1109/ICSEC51790.2020.9375442","DOIUrl":"https://doi.org/10.1109/ICSEC51790.2020.9375442","url":null,"abstract":"Vehicular Adhoc Network supports numerous applications over the limited bandwidth resource available. To efficiently utilize this available resources, multi-channel operation supported by IEEE 1609.4 protocol is incorporated within vehicular network. Taking into consideration this fact, the paper presents a MAC model supporting multi-channel operation to efficiently utilize the limited bandwidth resource. The proposed model prioritizes safety messages over non-safety messages alongwith an added feature that each non-safety messages are disseminated only when the preceding safety message dissemination is completed, thus supporting multichannel operation. The simulation is performed using MATLAB’15 Simulink. The obtained simulation result provides evidence that the delay experienced by safety messages are negligible as compared to non-safety messages. Also, for the proposed model, a multi-channel utilization of 1 is attained throughout the simulation run.","PeriodicalId":158728,"journal":{"name":"2020 24th International Computer Science and Engineering Conference (ICSEC)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130507027","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 : 2020-12-03DOI: 10.1109/ICSEC51790.2020.9375155
Lai Yee Myint, Su Su Maung, Khine Thin Zar
For the study of anatomical structure and image processing of CT images, noise removal techniques have become a vital role in a medical imaging application. In this paper, an automatic unwanted object removing for kidney stone detection is proposed together with 3D visualization. For the removal of surrounding unwanted objects, there are three steps in this proposed scheme. The first step is hypodense and isodense region removing using intensity-based thresholding. In the second step, size-based thresholding is used to remove the bones of the abdomen. In the third step, geometric feature-based thresholding is developed for false-positive reducing. The proposed scheme can effectively provide the structural information of the kidney stone CT image when removing surrounding unwanted objects. It gives the performance with 95.7% in sensitivity. To represent better visual results, simulation experiment results are shown using 3D visualization.
{"title":"Removal of Unwanted Object in 3D CT Kidney Stone Images and 3D Visualization","authors":"Lai Yee Myint, Su Su Maung, Khine Thin Zar","doi":"10.1109/ICSEC51790.2020.9375155","DOIUrl":"https://doi.org/10.1109/ICSEC51790.2020.9375155","url":null,"abstract":"For the study of anatomical structure and image processing of CT images, noise removal techniques have become a vital role in a medical imaging application. In this paper, an automatic unwanted object removing for kidney stone detection is proposed together with 3D visualization. For the removal of surrounding unwanted objects, there are three steps in this proposed scheme. The first step is hypodense and isodense region removing using intensity-based thresholding. In the second step, size-based thresholding is used to remove the bones of the abdomen. In the third step, geometric feature-based thresholding is developed for false-positive reducing. The proposed scheme can effectively provide the structural information of the kidney stone CT image when removing surrounding unwanted objects. It gives the performance with 95.7% in sensitivity. To represent better visual results, simulation experiment results are shown using 3D visualization.","PeriodicalId":158728,"journal":{"name":"2020 24th International Computer Science and Engineering Conference (ICSEC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129625634","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 : 2020-03-01DOI: 10.1109/ICSEC51790.2020.9375226
Pongsaphol Pongsawakul
We consider the tree consensus problem, an important problem in bioinformatics. Given a rooted tree t and another tree T, one would like to incorporate compatible information from T to t. This problem is a subproblem in the tree refinement problem called the RF-Optimal Tree Refinement Problem defined by in Christensen, Molloy, Vachaspati and Warnow [WABI’19] who employ the greedy algorithm by Gawrychowski, Landau, Sung, and Weimann [ICALP’18] that runs in time $O(n^{15}log n)$, where n is the number of leaves. We propose a faster algorithm for this problem that runs in time $O(nlog n)$. Our key ingredient is a bipartition compatibility criteria based on amortized-time leaf counters. While our algorithm gives an improvement to the tree refinement problem, the fastest solution is an algorithm by Jansson, Shen, and Sung [JACM’16] which runs in time $O(n)$. We note that our approach, while slower, is simpler to implement.
{"title":"An Algorithm for Consensus Trees","authors":"Pongsaphol Pongsawakul","doi":"10.1109/ICSEC51790.2020.9375226","DOIUrl":"https://doi.org/10.1109/ICSEC51790.2020.9375226","url":null,"abstract":"We consider the tree consensus problem, an important problem in bioinformatics. Given a rooted tree t and another tree T, one would like to incorporate compatible information from T to t. This problem is a subproblem in the tree refinement problem called the RF-Optimal Tree Refinement Problem defined by in Christensen, Molloy, Vachaspati and Warnow [WABI’19] who employ the greedy algorithm by Gawrychowski, Landau, Sung, and Weimann [ICALP’18] that runs in time $O(n^{15}log n)$, where n is the number of leaves. We propose a faster algorithm for this problem that runs in time $O(nlog n)$. Our key ingredient is a bipartition compatibility criteria based on amortized-time leaf counters. While our algorithm gives an improvement to the tree refinement problem, the fastest solution is an algorithm by Jansson, Shen, and Sung [JACM’16] which runs in time $O(n)$. We note that our approach, while slower, is simpler to implement.","PeriodicalId":158728,"journal":{"name":"2020 24th International Computer Science and Engineering Conference (ICSEC)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123878456","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：