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2019 27th Signal Processing and Communications Applications Conference (SIU)最新文献

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Comparison of Empirical and Ray-Traced Based Channel Modeling on VHF Band 基于VHF波段经验和射线跟踪信道建模的比较
2019 27th Signal Processing and Communications Applications Conference (SIU) Pub Date : 2019-04-01 DOI: 10.1109/SIU.2019.8806487
Gökhan Çelik, Aizat Aitalieva, H. Çelebi
{"title":"Comparison of Empirical and Ray-Traced Based Channel Modeling on VHF Band","authors":"Gökhan Çelik, Aizat Aitalieva, H. Çelebi","doi":"10.1109/SIU.2019.8806487","DOIUrl":"https://doi.org/10.1109/SIU.2019.8806487","url":null,"abstract":"In this paper, we investigate the comparison of empirical and ray-tracing based channel modeling over a dense hilly environment at carrier frequency of 145 MHz VHF band. As the measurement environment, Inozu Valley, Ankara, Turkey, is selected where the dense rocky hills exist alongside the valley. Large-scale statistics, i.e. path loss, path loss exponents, and small-scale statistics, i.e. delay statistics, coherence bandwidth of the channel are obtained for both measurement cases. Wireless InSite electromagnetic propagation simulation software, which is a widely used product of RemCom Inc, is used to ray-tracing based channel modeling. The result for each cases show that the Wireless InSite channel modeling software produces close results to the empirical results with slight differences. The obtained channel statistics are used during the design of a military communication system which is operated at the VHF band over a dense hilly environment.","PeriodicalId":326275,"journal":{"name":"2019 27th Signal Processing and Communications Applications Conference (SIU)","volume":"365 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123503674","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
Sequential Regression with Missing Data Using LSTM Networks 基于LSTM网络的缺失数据序列回归
2019 27th Signal Processing and Communications Applications Conference (SIU) Pub Date : 2019-04-01 DOI: 10.1109/SIU.2019.8806612
S. O. Sahin
{"title":"Sequential Regression with Missing Data Using LSTM Networks","authors":"S. O. Sahin","doi":"10.1109/SIU.2019.8806612","DOIUrl":"https://doi.org/10.1109/SIU.2019.8806612","url":null,"abstract":"We study regression for variable length sequential data suffering from missing samples and introduce a long shortterm memory (LSTM) based sequential regression algorithm. In most sequential regression studies, one considers data sequence is complete, i.e., does not contain any missing data. However, the missing data problem appears in a large number of areas such as finance and medical imaging. The remedies to resolve this problem depends on certain statistical assumptions and imputation techniques. However, the statistical assumptions does not hold in real life and the imputation of artificially generated inputs results in sub-optimal solutions. In our experiments, we achieve significant performance gains with respect to the classical algorithms.","PeriodicalId":326275,"journal":{"name":"2019 27th Signal Processing and Communications Applications Conference (SIU)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123704251","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: 2
Analysis of Price Models in Istanbul Stock Exchange 伊斯坦布尔证券交易所价格模型分析
2019 27th Signal Processing and Communications Applications Conference (SIU) Pub Date : 2019-04-01 DOI: 10.1109/SIU.2019.8806296
S. Tekin, Ethem Çanakoglu
{"title":"Analysis of Price Models in Istanbul Stock Exchange","authors":"S. Tekin, Ethem Çanakoglu","doi":"10.1109/SIU.2019.8806296","DOIUrl":"https://doi.org/10.1109/SIU.2019.8806296","url":null,"abstract":"Equity investments are one of the most important asset classes. Equity investments have high return yield however also high risk due to the variability of share prices. Therefore, precise share price modeling is essential. In this study, we examined the data of 30 leading companies of Borsa ˙Istanbul. We applied ARIMA, Machine learning algorithms and Deep learning techniques (LSTM) to BIST30 stock prices. As a result of the computational analysis, we observed that ARIMA performs better than LSTM and linear regression performs better than other machine learning techniques.","PeriodicalId":326275,"journal":{"name":"2019 27th Signal Processing and Communications Applications Conference (SIU)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124066048","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: 3
SYMPES Character Encoding Algorithm 字符编码算法
2019 27th Signal Processing and Communications Applications Conference (SIU) Pub Date : 2019-04-01 DOI: 10.1109/SIU.2019.8806615
Osman Korkmaz, B. Yarman
{"title":"SYMPES Character Encoding Algorithm","authors":"Osman Korkmaz, B. Yarman","doi":"10.1109/SIU.2019.8806615","DOIUrl":"https://doi.org/10.1109/SIU.2019.8806615","url":null,"abstract":"In this paper, SYMPES Character Encoding Algorithm, which bring a new solution to secure communication, is described. Although SYMPES is not an encryption algorithm, it has an inherently trusted infrastructure. The character data is not send with SYMPES, it is only the indexes which are transmitted over the communication channel. In this way, due to the natural structure of the system, trusted communication infrastructure is provided and the data is compressed.","PeriodicalId":326275,"journal":{"name":"2019 27th Signal Processing and Communications Applications Conference (SIU)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128328919","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
Detection Based Tracking of Unmanned Aerial Vehicles 基于检测的无人机跟踪
2019 27th Signal Processing and Communications Applications Conference (SIU) Pub Date : 2019-04-01 DOI: 10.1109/SIU.2019.8806391
Bedirhan Uzun, O. Eker, Hasan Saribas, Hakan Çevikalp
{"title":"Detection Based Tracking of Unmanned Aerial Vehicles","authors":"Bedirhan Uzun, O. Eker, Hasan Saribas, Hakan Çevikalp","doi":"10.1109/SIU.2019.8806391","DOIUrl":"https://doi.org/10.1109/SIU.2019.8806391","url":null,"abstract":"Object tracking is one of the fundamental problems of computer vision, which has many difficulties such as fast camera motion, occlusion and similar objects. Today, small and lightweight single board computers with very high processing power have been developed. Real-time processing of the computer vision applications on unmanned aerial vehicles has become possible with the integration of such single board computers within UAVs. In this study, a hybrid method is developed to detect and track UAVs by another UAV. A deep learning based approach which is one of the fastest and most accurate method in the literature, YOLOv3 and YOLOv3-Tiny (You Only Look Once), are utilized to detect the UAV at the beginning of the video and when tracking of the UAV is failed. Kernelized Correlation Filter (KCF) is used for real time tracking purpose of the detected UAVs. A dataset is created that consists different UAVs to train and test YOLOv3. Performance of the proposed methods are evaluated on this dataset.","PeriodicalId":326275,"journal":{"name":"2019 27th Signal Processing and Communications Applications Conference (SIU)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128250241","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
Conical, Stair-Shapedand Cylindrical Dielectric Resonator Antenna for Early Breast Cancer Detection Application 锥形、阶梯形和圆柱形介质谐振器天线在早期乳腺癌检测中的应用
2019 27th Signal Processing and Communications Applications Conference (SIU) Pub Date : 2019-04-01 DOI: 10.1109/SIU.2019.8806528
Gwladys Laure Makiela Fokoa, R. Uyguroglu
{"title":"Conical, Stair-Shapedand Cylindrical Dielectric Resonator Antenna for Early Breast Cancer Detection Application","authors":"Gwladys Laure Makiela Fokoa, R. Uyguroglu","doi":"10.1109/SIU.2019.8806528","DOIUrl":"https://doi.org/10.1109/SIU.2019.8806528","url":null,"abstract":"This study is about the design of Dielectric Resonator Antennas (DRAs) in the X-band (8 GHz-12 GHz) having cylindrical, conical and stair shaped dielectrics. The study is carried out using Computer Simulation Technology (CST) Microwave Studio. The simulated DRA's have wide impedance bandwidth; around 37.58% for cylindrical, 48.61% and 55.55% for the conical and the two SSS designs. The two SSS gives the best impedance bandwidth in free space and is used for the simulations on the healthy and malignant breast model in which the return loss is used to analyze its effect.","PeriodicalId":326275,"journal":{"name":"2019 27th Signal Processing and Communications Applications Conference (SIU)","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127510176","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
Meta-Heuristic Algorithms Based Multi-Level Thresholding 基于多级别阈值的元启发式算法
2019 27th Signal Processing and Communications Applications Conference (SIU) Pub Date : 2019-04-01 DOI: 10.1109/SIU.2019.8806265
Büsranur Küçükugurlu, E. Gedi̇kli̇
{"title":"Meta-Heuristic Algorithms Based Multi-Level Thresholding","authors":"Büsranur Küçükugurlu, E. Gedi̇kli̇","doi":"10.1109/SIU.2019.8806265","DOIUrl":"https://doi.org/10.1109/SIU.2019.8806265","url":null,"abstract":"Thresholding is a very important stage in computer vision applications. An ideal single thresholding algorithm is not available for all environments. Multi-level thresholding in environments with multiple objects is constantly being developed for interpretation of images. Kapur entropy and Otsu approaches are among the most successful algorithms in the literature. In this study, it is tried to increase the performance of Otsu and Kapur algorithms by using meta-heuristic optimization approaches. The results of the Firefly Algorithm (FF) and Real Coded Genetic Algorithm (RGA) were evaluated with PSNR, SSIM and CPU processing time criteria.","PeriodicalId":326275,"journal":{"name":"2019 27th Signal Processing and Communications Applications Conference (SIU)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129041193","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
Small and Unbalanced Data Set Problem in Classification 分类中的小而不平衡数据集问题
2019 27th Signal Processing and Communications Applications Conference (SIU) Pub Date : 2019-04-01 DOI: 10.1109/SIU.2019.8806497
Öznur Esra Par, E. Sezer, H. Sever
{"title":"Small and Unbalanced Data Set Problem in Classification","authors":"Öznur Esra Par, E. Sezer, H. Sever","doi":"10.1109/SIU.2019.8806497","DOIUrl":"https://doi.org/10.1109/SIU.2019.8806497","url":null,"abstract":"Classification of data is difficult in case of small and unbalanced data set and this problem directly affects the classification performance. Small and / or the imbalance dataset has become a major problem in data mining. Classification algorithms are developed based on the assumption that the data sets are balanced and large enough. The most of the algorithms ignore or misclassify examples of the minority class, focus on the majority class. Small and unbalanced data set problem is frequently encountered in medical data mining due to some limitations. Within the scope of the study, the public accessible data set, hepatitis, was divided into small and imblanced data subsets, each of the data subsets were oversampled by distance based data generation methods. The oversampled data sets were classified by using four different machine learning algorithms (Artificial Neural Networks, Support Vector Machines, Naive Bayes and Decision Tree) and the classification scores were compared.","PeriodicalId":326275,"journal":{"name":"2019 27th Signal Processing and Communications Applications Conference (SIU)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131667469","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: 5
Sperm Detection and Analysis Using Feature Description Algorithms 基于特征描述算法的精子检测与分析
2019 27th Signal Processing and Communications Applications Conference (SIU) Pub Date : 2019-04-01 DOI: 10.1109/SIU.2019.8806287
Mustafa Furkan Keskenler, A. Hasiloglu, Gülsah Tümüklü Özyer, B. Özyer, E. Şimşek
{"title":"Sperm Detection and Analysis Using Feature Description Algorithms","authors":"Mustafa Furkan Keskenler, A. Hasiloglu, Gülsah Tümüklü Özyer, B. Özyer, E. Şimşek","doi":"10.1109/SIU.2019.8806287","DOIUrl":"https://doi.org/10.1109/SIU.2019.8806287","url":null,"abstract":"Computer aided sperm analysis (CASA) systems have been used in recent years to examine the mobility and morphology of human and animal sperm. While these systems detect sperm, they fail to detect more than one sperm image coinciding or overlapping between the motile spermatozoa. In addition, sensitive results can not be obtained against the light factor of the background in sperm detection. In order to improve the above mentioned problems, using the random forest algorithm, sperm detection was performed on the images obtained from the HOG, LBP and color histogram feature extraction methods. When the experimental results were examined, it was observed that 92% success rate was achieved in the images.","PeriodicalId":326275,"journal":{"name":"2019 27th Signal Processing and Communications Applications Conference (SIU)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129187465","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: 3
Human Action Recognition in First Person Videos using Verb-Object Pairs 第一人称视频中使用动物对的人类动作识别
2019 27th Signal Processing and Communications Applications Conference (SIU) Pub Date : 2019-04-01 DOI: 10.1109/SIU.2019.8806562
Zeynep Gökce, Selen Pehlivan
{"title":"Human Action Recognition in First Person Videos using Verb-Object Pairs","authors":"Zeynep Gökce, Selen Pehlivan","doi":"10.1109/SIU.2019.8806562","DOIUrl":"https://doi.org/10.1109/SIU.2019.8806562","url":null,"abstract":"Human action recognition problem is important for distinguishing the rich variety of human activities in first-person videos. While there has been an improvement in egocentric action recognition, the space of action categories is large and it looks impractical to label training data for all categories. In this work, we decompose action models into verb and noun model pairs and propose a method to combine them with a simple fusion strategy. Particularly, we use 3 Dimensional Convolutional Neural Network model, C3D, for verb stream to model video-based features, and we use object detection model, YOLO, for noun stream to model objects interacting with human. We present experiments on the recently introduced large-scale EGTEA Gaze+ dataset with 106 action classes, and show that our model is comparable to the state-of-the-art action recognition models.","PeriodicalId":326275,"journal":{"name":"2019 27th Signal Processing and Communications Applications Conference (SIU)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128791341","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: 2
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