2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)最新文献

{"title":"Multilabel Remote Sensing Image Classification with Capsule Networks","authors":"Mücahit Topçu, Abdülkadir Dede, S. Eken, A. Sayar","doi":"10.1109/HORA49412.2020.9152917","DOIUrl":"https://doi.org/10.1109/HORA49412.2020.9152917","url":null,"abstract":"As a result of the developments in remote sensing technologies, the classification of remote sensing images according to user needs has gained great attention in recent years. Deep learning techniques are also known to increase the classification performance of remote sensing. In this study, image classification is made with capsule networks, which are deep artificial neural network model, on the multilabel datasets -Ankara Hyperspectral Image Archive and UC Merced Land Use. The performance of the classification is measured with various performance metrics.","PeriodicalId":166917,"journal":{"name":"2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","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":"126195517","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}

{"title":"The effect of FSMM on the circular patch antenna by etching the antenna substrate with DGS method","authors":"Bülent Urul","doi":"10.1109/HORA49412.2020.9152598","DOIUrl":"https://doi.org/10.1109/HORA49412.2020.9152598","url":null,"abstract":"Microwave antennas used in technologies such as mobile devices, satellite antennas working at microwave frequencies are aimed to be high gain, high directivity and compactness. One method of enhancing antenna performance is to use the metamaterials (MMs) together with the antenna structures. The negative refractive properties of the MMs allow the electromagnetic waves to focus. For this purpose, in this study, firstly, flower Shape Metamaterial (FSMM) structure is designed for Ku band. Then a circular patch antenna is designed for the Ku Band. The effect of the FSMM structure on the performance of the circular patch antenna is investigated by applying the FSMM structure on the metal base of the antenna substrate using defected ground structure method (DGS).","PeriodicalId":166917,"journal":{"name":"2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","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":"126536606","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}

{"title":"Optimal Power Flow for Iraqi Power System","authors":"Afaneen Anwer, A. Almosawi, G. Alshabbani","doi":"10.1109/HORA49412.2020.9152868","DOIUrl":"https://doi.org/10.1109/HORA49412.2020.9152868","url":null,"abstract":"In operating and planning power systems, operators need to make decisions for different goals. As it happened, many tools were developed to assist operators. One of the tools that helps operators operate the system optimally under certain constraints is the optimal power flow (OPF). This paper offers an effective and reliable dynamic approach for solving the problem of optimum power flow. The proposed approach employs the genetic algorithm (GA) to optimize the control variables for the (OPF) issue. The target function is decreasing the cost of generation and the losses of transmission. The proposed algorithm applied to the Iraqi power system 39-bus, and the results showed the strength, durability, and proposed of the effectiveness genetic algorithm in solving the OPF issue.","PeriodicalId":166917,"journal":{"name":"2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","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":"130482386","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}

{"title":"Prevention Of Diabetes By Devising A Prediction Analytics Model","authors":"Lindita Loku, B. Fetaji, M. Fetaji","doi":"10.1109/HORA49412.2020.9152894","DOIUrl":"https://doi.org/10.1109/HORA49412.2020.9152894","url":null,"abstract":"The focus of the research study was analyses of predictive model for prognosis and prediction of type 2 diabetes mellitus (DM) that are investigated during the study. Diabetes mellitus is thought of as one of the vital deadliest and persistent sicknesses which reasons an build up in blood sugar. Many occurrences of death and different health complications happen if diabetes mellitus stays untreated and unidentified. The research study is therefore focused in devising analytical predictive model that can guide decisions of healthcare people more effectively and provide insights into the illness. We have analyzed the Artificial Neural Network (ANN) model and further improved it by adding additional impacting factors and assessing the attributes. In conclusion, the developed machine learning model for the prediction and detection of diabetes is important as the condition continues to increase in prevalence worldwide while simultaneously increasing its economic burden. Insights and guidelines are discussed and recommendations are provided.","PeriodicalId":166917,"journal":{"name":"2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","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":"131390071","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}

{"title":"Improved Manta Ray Foraging Optimization Using Opposition-based Learning for Optimization Problems","authors":"Davut Izci, Serdar Ekinci, Erdal Eker, M. Kayri","doi":"10.1109/HORA49412.2020.9152925","DOIUrl":"https://doi.org/10.1109/HORA49412.2020.9152925","url":null,"abstract":"Manta ray foraging optimization (MRFO) algorithm is a bio-inspired meta-heuristic algorithm. It has been proposed as an alternative optimization approach for real-world engineering problems. However, MRFO is not good at fine-tuning of solutions around optima and suffers from slow convergence speed because of its stochastic nature. It needs to be improved due to latter issues. Therefore, in this study, opposition-based learning (OBL) technique was used together with MRFO in order to obtain an effective structure for optimization problems. The proposed structure has been named as opposition-based Manta ray foraging optimization (OBL-MRFO). In the proposed algorithm, the advantage of OBL in terms of considering the opposite solutions was used to have an algorithm with better performance. The proposed algorithm has been tested on four different benchmark functions such as Sphere, Rosenbrock, Schwefel and Ackley. Statistical analyses were performed through comparing the performance of OBL-MRFO with the other algorithms such as salp swarm algorithm, atom search optimization and original MRFO. The results showed that the proposed algorithm is more effective and has better performance than other algorithms.","PeriodicalId":166917,"journal":{"name":"2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"20 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":"132943154","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}

{"title":"Neural networks for determining affinity functions","authors":"V. Dmitrienko, Alexander Yurievich Zakovorotniy, S. Leonov","doi":"10.1109/HORA49412.2020.9152830","DOIUrl":"https://doi.org/10.1109/HORA49412.2020.9152830","url":null,"abstract":"The Hamming neural network is an effective tool for solving the problems of recognition and classification of discrete objects whose components are encoded with the binary bipolar alphabet, and the difference between the number of identical bipolar components of the compared objects (vectors images) and the Hamming distance between them (Hamming distance is the number of mismatched bits in the binary vectors being compared) is used as the objects proximity measures. However, the Hamming neural network cannot be used to solve these problems in case the components of the compared objects (vectors) are encoded with the binary alphabet. It also cannot be used to evaluate the affinity (proximity) of objects (binary vectors) with Jaccard, Sokal and Michener, Kulzinsky functions, etc. In this regard, a generalized Hamming neural network architecture has been developed. It consists of two main blocks, which can vary being relatively independent on each other. The first block, consisting of one layer of neurons, calculates the proximity measures of the input image and the reference ones stored in the neuron relations weights of this block. Unlike the Hamming neural network, this block can calculate various proximity measures and signals about the magnitude of these proximity measures from the output of the first block neurons which are followed to the inputs of the second block elements. In the Hamming neural network, the Maxnet neural network is used as the second block, which gives out one maximum signal from the outputs of the first block neurons. If the inputs of the Maxnet network receive not only one but several identical maximum signals, then the second block, and, consequently, the Hamming network, cannot recognize the input vector, which is at the same minimum Hamming distance from two or more reference images stored in the first block. The proposed generalized architecture of the Hamming neural network allows using neural networks instead of the Maxnet network, which can give out not only one but also several identical maximum signals. This allows to eliminate the indicated drawback of the Hamming neural network and to expand the application area of discrete neural networks for solving recognition and classification problems using proximity functions for discrete objects with binary coding of their components.","PeriodicalId":166917,"journal":{"name":"2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"10 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":"122566069","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}

{"title":"An Image Processing Framework To Identify Rice Blast","authors":"T. S. Sazzad, A. Anwar, Mahiya Hasan, Md. Ismile Hossain","doi":"10.1109/HORA49412.2020.9152912","DOIUrl":"https://doi.org/10.1109/HORA49412.2020.9152912","url":null,"abstract":"An early detection of rice plant disease especially rice plant leaves disease detection can assist farmers to take necessary precaution at the early stage and can achieve better quality of crops. Rice plant can be affected by various types of fungal infectious diseases and among them rice blast is a common one. There are a numerous image processing approaches available today which can analyze rice plant leaves disease. Existing most approaches considered binary threshold based segmentation approach although input images are always RGB color images. To develop an automated system to identify and classify rice blast diseases it is always beneficial to use RGB color images as input and to provide analysis results in RGB color images as well. This study proposed a suitable frame work where enhancement, filter, color segmentation and color feature for classification steps were incorporated for identification. CNN classifier was applied to increase the identified accuracy rate. Compared to all other existing approaches this study proposed framework provides an acceptable accuracy rate of 97.43%.","PeriodicalId":166917,"journal":{"name":"2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"37 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":"121297351","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}

{"title":"4 Eksenlі Robot Kolun Kіnematіk Hesaplarinin Gerçek Model Üzerіnde Matlab іle Analіzі ve Testі","authors":"Yavuz Çapkan, C. Fidan","doi":"10.1109/HORA49412.2020.9152851","DOIUrl":"https://doi.org/10.1109/HORA49412.2020.9152851","url":null,"abstract":"Bu çalışmada, 4 eksenli robot kolun kinematik hesapları çıkartılmış, robot kol kinematik hesapları programı kullanılarak hem Simulink programında hem de 3 boyutlu yazıcı ile oluşturulmuş gerçek modelde test edilmiştir. Matlab Simulink programındaki simülasyon testlerinde 3 boyutlu model kullanılmıştır. Bu sayede robot kolun eksen hareketleri kolaylıkla gözlemlenerek gerçek model testleri sorunsuzca gerçekleştirilmiştir. Robot kolun simülasyon ve gerçek model testleri için Matlab Gui programı oluşturulmuştur. Rastgele bir noktaya konulan cismin orta nokta konumu bu programa girilir ve ters kinematik ile eksen açılarına dönüştürülür. Elde edilen eksen açıları ile hem simülasyon çalıştırılır hem de bu açı değerleri mikro denetleyici karta gönderilerek 3 boyutlu yazıcı ile oluşturulmuş robot kolun çalışması gerçekleştirilir. Çalışmada yapılan testlerde çok sayıda rastgele cisim noktası Matlab Gui programına girilmiştir. Bu testlerde hatalı eksen hareketlerinin olup olmadığı ve özellikle eksenlerin -z yönünde (zemine ters) hareketinin olup olmadığı incelenmiştir. Gerçek model ve bilgisayar ortamında yapılan testlerden sonra robot kolun sorunsuz bir şekilde çalıştığı görülmüştür.","PeriodicalId":166917,"journal":{"name":"2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"10 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":"117009530","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}

{"title":"Design and Implementation DWDM Toward Terabit for Long-Haul Transmission System","authors":"Mokhalad Isam Mousa, Galip Cansevera, T. Abd","doi":"10.1109/HORA49412.2020.9152885","DOIUrl":"https://doi.org/10.1109/HORA49412.2020.9152885","url":null,"abstract":"In this paper we present design and implementation of high-speed transmission system toward Terabit/sec based on Denise Wavelength Division Duplexing (DWDM) system. The presenting system consider new solution to carrying rise data rate for long-haul optical transmission system. The system examined for various number of channel (4, 8, 16, and 25). The obtained results show that the propose system immunity for the non-linear impairments. As well as, the performance analysis of different number of optical channels with different data formatting technique such as Return-to-Zero (RZ) and Non-Return-to-Zero (NRZ) is presented.","PeriodicalId":166917,"journal":{"name":"2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"28 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":"115475593","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}

{"title":"Load Balancing In Hybrid WIFI/ LIFI Networks Based on the RSSI of the Load Using Optimized KNN Clustering","authors":"M. Ahmed, Ali Alkahrsan, M. Ilyas","doi":"10.1109/HORA49412.2020.9152887","DOIUrl":"https://doi.org/10.1109/HORA49412.2020.9152887","url":null,"abstract":"Light fidelity or LIF is a new emerging communication technology that works similar to the WIFI network but uses the light rays as a medium, its high speed and dense communicated data make it a promising technology to researchers, yet the physical attributes of the light bring new challenges to the scene, challenges such as light blockage and short range of coverage, in this paper, we aim at solving these issues by balancing the loads connected to the LIFI network using techniques inspired by the handover method in WIFI networks and clustering technique in wireless sensor network WSN, we use the KNN algorithm for its fast classification and decision making, making it a much faster clustering tool that the K-means algorithm and the Fuzzy C-means FCM, and we classify the loads into clusters based on their received signal strength indicator or RSSI, each access point or Aps being the center of that cluster.","PeriodicalId":166917,"journal":{"name":"2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"84 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":"124736840","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}