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Öğe Detection of the Quality of Zivzik Pomegranate Grown in Siirt Using Deep Learning Methods(Institute of Electrical and Electronics Engineers Inc., 2025) Yusuf Bilgen; Mahmut KayaThis study aims to determine the quality of the Zivzik pomegranate, a fruit unique to the Siirt region whose quality can only be understood by experts engaged in this business with deep learning methods. Since there is no existing database of Zivzik pomegranate, we first visited the Şirvan district of Siirt, where Zivzik pomegranate grows, many times to create a database, and over a thousand pomegranate photographs were taken and labeled. After the Zivzik pomegranate quality dataset was created, the aim was to determine the quality of Zivzik pomegranate using deep learning methods. AlexNet, VGG-16, VGG-19, ResNet, Inception, XCeption, EfficientNet, and MobileNet deep learning models were applied, and the results were evaluated. As a result of the study, the best accuracy value was obtained from the EfficientNetV2 B0 model at 81.83%. In addition to contributing to the scientific literature, our study is expected to contribute positively to the recognition of the Zivzik pomegranate, the regional economy, and the awareness of consumers and producers about agriculture 4.0 applications.Öğe Performance Comparison of Static Malware Analysis Tools Versus Antivirus Scanners To Detect Malware(2017-11) Aslan, ömerAny software which executes malicious payloads on victim machines is considered as a malware such as the following: Viruses, worms, Trojan horses, rootkits, backdoor and ransomware. In recent years, the number and the severity of these malicious software have been increasing rapidly. The harm that malware inflicts on the world economy and private companies’ assets is increasing every day. Thus, there is an urgent need to detect and prevent malware before damaging to the important assets in world wide. There are lots of different methods and tools to combat against malware. In this paper, static malware analysis tools such as (Peid, PEview, Bintext, MD5deep, Dependency walker, and IDA Pro) and antivirus scanner tools such as (Norton, McAfee, Kaspersky, Avast, Avira, Bitdefender, and ClamAV) have been examined. In a test case, 200 malware and benign were collected from different sources and analyzed under different version of Window machines. Test results show that for existing malware, antivirus software detect malware fast and efficient when compared to static analysis tools. However, for unknown malware static analysis tools performed reasonably better than antivirus software.Öğe How to Decrease Cyber Threats by Reducing Software Vulnerabilities and Bugs(2016-10) Aslan, ömerAs a result of technological improvements, computer systems facing not only traditional security attacks, but also facing new cyber attacks which are more sophisticated and harmful threats such as Stuxnet, and Dragonfly. These attacks may cause enormous destruction to victim machine, steal confidential information or use infected machine to attack other computerized systems. Every year, the whole world lose millions of dollars because of the cyber attack and its consequences. Each year, these kinds of attacks and impact of the cyber attacks increase rapidly. In most cases, attackers carried out direct penetration to the system or use malware to carry out malicious intents. Most of the threats and attacks that exploit existing vulnerabilities which are found in hardware, software, and network layers. Absolute security is not possible and not necessary, instead we need to provide good enough security. To protect computer system from cyber threats, deep protection mechanism such as encryption, firewall, intrusion detection, prevention and response system has been used for many years, but some new malware types bypass through those security protection, so there is an urgent need to develop new security mechanism. The goal of this study is understanding core of the attacks in advance and provide a conceptual framework to implement secure software and specify vulnerable programs automatically.Öğe Bilgisayarlı Görü Sistemi Kullanılarak Siirt Fıstığının Otomatik Olarak Sınıflandırılması(2015-09-15) Ataş, MusaToday, machine vision systems are used successfully and effectively on many areas including production, medical, military, robotic and agriculture. Delivery of agricultural foods, scrutinized before packaging, boosts the competitiveness of the organizations in the context of the quality standards and non-destructive testing. Turkey is the third pistachio producer in the world. According to 2010 data, Siirt province is the third producer in the Turkey and supplied 14 % of the national pistachio production. Siirt pistachios are consumed as a fresh nut, desired more than Antep pistachios in the market since, Siirt pistachios have coarser grains, contain low oil levels and higher nutrients properties. Hence, economic income would be better. According to Tigris Reconstruction Agency (TRA), a project of a modern plant in Siirt province with the processing capacity of 15.000 tons Siirt pistachios annually has been supported by IPA (Instrument for Pre-accession Assistance). It is expected that this modern plant will be active in the next three years. During the processing stages of the pistachios, there are three significant steps. These are detection of un cracked kernels, separation of empty pistachios from filled ones and classification of the pistachios according to their size, shape, healthy, morphological and aesthetical properties. Current technologies carry out these duties in a mechanical and physical manner at the expense of deterioration in the quality of the nuts. For example, separation of the empty kernels is realized based on buoyancy of water principle. However, the moisture content of pistachios and mold growth is increased and lead to aflatoxin contamination. Additionally, grading process is currently accomplished via mechanical sieves while changing the pores of the sieves. So, there is no automatic system that can separate pistachios with foreign materials, including in shell nuts, shells or shells fragments, various types of defects, mold, insect damage, rancidity and decay. Another concern is about cracked/un cracked classification. Detection of cracks in Siirt pistachios are currently performed manually by visual inspection of the workers in a primitive manner. There may be some health problems when considering food hygiene and safety. On the other hand, classification of the huge amount of pistachio nuts in this way may not bring the desired results since this tedious process actually is time consuming, labor intensive in nature and it is not cost effective. Because the amount of non-cracked shells directly influence the customer satisfaction, establishing such a classifier system with high accuracy rate becomes indispensable. Recently, optical, mechanical, electrical and acoustic methods are used for classification of the agricultural products. In this regard, Pearson showed that cracked/un cracked pistachio nuts can be well separated according to impact acoustic sounds. Furthermore, Kalkan et.al. achieved 96.7 % accuracy rate for the classification of the cracked/ un cracked hazelnut kernels. Additionally, Omid et.al showed that cracked Iran pistachios can be separated at a rate of 97.5%. Almost all studies in the literature utilized impact acoustic signal for extracting a feature vector. Nevertheless, the main limitation of the impact acoustic based system is that, they are more easily affected from the environmental noises and is successful only for the specific size range of pistachios. In case of different size and moisture content pistachios, fault rate can also be increased. Besides, for multichannel design in mind, misclassification rate may also increases due to interfering effect of the parallel channels. In order to address this particular problem, image data also can be utilized along with impact acoustic data. In this study, we aim to increase the classification accuracy of the proposed system by two different source of information (sound and image). To keep the impact acoustic data immune to environmental factors, piezoelectric sensor or vibration sensor will be stacked to the steel plate which is used for impact of pistachios. Thus, impact acoustic vibrations can be converted into the electrical signals robust from environmental factors and noises. This enhancement also makes the multichannel processing of pistachio separation feasible. In addition to impact acoustic, classification can be performed based on both spatial and volumetric features. General procedure will be as follows. Raw pistachio nuts will be left from high place within a certain time interval as a free fall motion. Images of these nuts will be acquired by passing them through a tunnel that contains several cameras with different angle of views. Then, pistachio nuts will bump into the steel plate with piezoelectric sensor in order to generate impact acoustic data. Analyzed pistachios based on image and impact acoustic will be grouped into cracked and un cracked groups in general. Un cracked and cracked nuts will be subjected to the quality standards, based on impact acoustic data with filled and un-filled kernels and image data with foreign materials, unmarketable species, moldy, first-second-and third degree quality, respectively. Pistachio samples will be supplied by different pistachio processing organizations in Siirt. By making the train and test set larger than the previous studies, real time performance of the proposed system will be predicted more accurately. As it is known, even 1 % raise in classification performance for industrial applications lead to add value and increase the competitiveness of the organizations. As a result, this productivity enhancement provides positive contributions to our national economy.Öğe Robotlarda Görme ve Ses Algılama Becerilerinin Dinamil Çevre Şartlarında Geliştirilmesi(2007-06-29) Ataş, MusaRobotlar ve Robotik çalışmalar her geçen gün ağırlığını hissettirmektedirler. Bu gelişmeler Bilgisayar Teknolojisinin paralelinde olmaktadır. Yapay Zekâ alanındaki gelişmeler Robotik çalışmalarına katkıda bulanmaktadır. Amaç değişken çevre şartlarına daha kolay adaptasyon sağlayabilen ve insanlığın hizmetinde daha etkin rol oynayabilen sistemler geliştirmektir. Şimdiye kadar yapılan çalışmalarda genelde durağan, statik çevrede işlem yapabilen robotlar geliştirilmiştir. Dolayısıyla yeni üretim modellerine geçildiğinde bütün sistemlerin güncelleştirilmesi ve/veya yeniden yapılmaları gerekmektedir. Biz bu projede, görme temelli insanla karşılıklı satranç oynayabilen bir sistem geliştirdik. Sistem kendi içinde üç ana birim ve bunları koordine eden bir ana programdan oluşmaktadır. Bunlar, görme ve algılama birimi, oyun motoru birimi, robot kolu kinematiği bölümü ve ana birimdir. Yazılım dili olarak, Java’yı ve geliştirme ortamı olarak ta Eclipse 3.2 yi kullandık. Projede kullandığımız teknolojiler sırasıyla, Resim İşleme, Nesne Algılama, Yapay Zekâ, Yapay Sinir Ağları ve Robot Kolu Kinematiğidir. Proje süresince, konunun uzmanlarıyla birebir görüşme ve fikir alışverişi yapma fırsatımız oldu. Ayrıca biz de grup üyeleri olarak hem sanal ortamda hem de fiziksel olarak toplantılar yapmak suretiyle, kazandığımız bilgileri harmanlayıp paylaştık. Sonuç olarak, biz bu projemizle hem ülkemize bilim alanında bir katma değer hem de ileriki projelere zemin hazırlayacak bilgi tabanını kurmuş olduk.
