Master Degree / Yüksek Lisans Tezleri
Permanent URI for this collectionhttps://hdl.handle.net/11147/3008
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Master Thesis Estrus Detection in Cows With Deep Learning Techniques(01. Izmir Institute of Technology, 2024) Arıkan, İbrahim; Ayav, Tolga; Soygazi, FatihAccurately predicting the estrus period is essential for enhancing the efficiency and lowering the costs of artificial insemination in livestock, a crucial sector for global food production. Precisely identifying the estrus period is critical to avoid economic losses such as decreased milk production, delayed calf births, and loss of eligibility for government subsidies. Since the most obvious movement that needs to be detected during the fertilization period is mounting, it is important to detect this movement. Since manual detection of this movement is difficult and costly, automated methods were needed. Therefore, it is thought that deep learning-based methods can be applied to detect the mounting moment. The proposed method detects the estrus period using deep learning and XAI (Explainable Artificial Intelligence) techniques. Deep learning-based mounting detection is performed using CNN, ResNet, VGG-19 and YOLO-v5 models. The ResNet model in this proposed study detects mounting movement with 99% accuracy. Explainability of deep learning models describes features that aid in decision-making in detecting mounting motion. Grad-CAM and Gradient Inputs models, which are XAI techniques, are used for the black box behind the proposed models. The developed deep learning models reveal that they focus on the udder and back area of the cows during the decision-making phase. In addition, how successfully the Grad-CAM and Gradient Inputs models, which are the XAI models used for the explainability of the deep learning models trained in this study, performed the explanation process was measured by calculating the 'faithfulness', 'maximum sensitivity' and 'complexity' metrics.Master Thesis Blackhole Attacks in Iot Networks(01. Izmir Institute of Technology, 2020) Sokat, Barış; Ayav, Tolga; Erten, Yusuf MuratIoT technologies are very popular today, and they are used in almost every field. Therefore, the number of IoT devices used is increasing day by day. Like every field in computer networks, security is quite important in IoT networks. However, the resource-constrained nature of IoT devices makes the study of security measures for IoT networks very challenging. In the literature research conducted before this thesis study, it was seen that it can perform a wide variety of RPL-based attacks on IoT networks. One of these attacks is the blackhole attack. Although the black hole attack is functionally simple, the damage it causes in the network can be extremely destructive. As far as it is known, in addition to the limited number of studies in this field of attack, the black hole attack used in the studies in this field has also basic features. The basic feature mentioned here is that the attacker node that will perform a black hole attack drops all the packets that come to it. When the attacker node drops all incoming packets, it causes the topology to change in the network, the number of control messages to increase and the attacker node to be isolated from the network in a short time. However, blackhole attack can be combined with different attacks. Therefore, in this thesis, the node that will perform the black hole attack is designed to allow control messages to pass, while dropping all other packets. Here, it is aimed that the attacker node remains on the network for a longer time. As a result, as long as the attacker node is active, it will be able to drop more packets and the number of control messages in the network will be controlled since the topology does not change. With the black hole attack developed as a result of the simulation tests, the number of control messages released in the network was taken under control and it was observed that the attacker node could remain in the network throughout the simulation period. Thus, the effect of different types of black hole attacks on the network that can be developed has been revealed.Master Thesis Predictive Maintenance for Smart Industry(01. Izmir Institute of Technology, 2020) Asadzade, Asad; Ayav, TolgaAfter the internet of things developed rapidly, it started to be used in many several industrial areas. Thanks to IoT, data that affect the health of any equipment or other important systems are collected. When these data are processed correctly, important information about the production process is obtained. For example, thanks to this data, systems based on machine learning are created to predict when various components will fail. Thus, maintenance operations are carried out before the component's breakdown, and replacement operations are performed if necessary. This strategy, called predictive maintenance, provides industries with advantages such as maximizing the life of components, reducing extra costs, and time saving. In this study, we applied ARF method, which is based on stream learning, on Turbofan Engine Degradation Simulation Datasets which are provided by NASA to estimate the remaining useful lifetime of jet engines. As a result, we mentioned about the advantages of streaming learning over batch learning and compared our results with other batch learning based studies which are applied on the same datasets.Master Thesis Evaluation of Scheduling Architectures for Osek/Vdx Compliant Hard Real-Time Operating Systems(Izmir Institute of Technology, 2020) Saydam, Berkay; Ayav, TolgaTechnological advancements are reflected to the vehicles as well, but it brings the challenge of adding new functionalities to vehicles without compromising safety. Tasks are used to provide functionalities which are used in car. These tasks have different characterictics. Safety and performance are two main criteria to determine characterictic of tasks. Characteristics of tasks can be classified according to their safety levels which are known as Automotive Safety Integrity Levels. Designing of hardware and software and also testing them is a long progress in automotive industry. Any changes on the design of hardware is quite costly when an ECU began to be used in field. According to my hypothesis, scheduling algorithms which are used by Central Processing Unit to determine sequences of task executions, should be well known. Besides, designing of hardware and software should be done according to these characteristics and algorithms. If not, tasks will cause serious problem like missing deadline for safety-critical component. In this thesis, the scheduling architectures are evaluated and they are determined which scheduling architectures should be used for which purpose. Besides, the advantages and disadvantages are explained.Master Thesis Internet of things simulation using cisco packet tracer(01. Izmir Institute of Technology, 2020) Thera, David; Ayav, Tolga; Erten, Yusuf MuratNowadays, the term IoT (internet of things) have become extremely important in our life. This technology is used in many fields such as education, health, industries, agriculture and infrastructures. In order to learn and understand how this technology works, many practical learning tools are used. The aim of the thesis is to introduce a iot simulation tool, where student can simulate or build and manage the systems for better understanding of the philosophy behind iot networks. The tool used is Cisco packet tracer which is a software developed by Cisco that is used to create and simulate a virtual network, basically a wireless network, without the need for any network hardware. The tool is free of charge, and suitable to work with almost all the operating systems. Cisco packet tracer allows users to have a practical networking technology knowledge. In this thesis, "Cisco packet tracer" is used to design an internet-based home automation system or smart home.Master Thesis Blockchain Application on Loyalty Card(Izmir Institute of Technology, 2020) Sönmeztürk, Osman; Ayav, Tolga; Erten, Yusuf MuratToday, traditional loyalty systems are insufficient to meet the needs of users. The users need to stay within the loyalty system for a long time and accumulate points in order to win prizes and besides, the rewards they receive may be out of their interest. In addition, users usually forget the awards they have won in traditional loyalty systems and have difficulty in following up rewards. In addition to that, users usually do not prefer to share their personal information to join loyalty systems due to privacy concerns. Therefore, the number of customers in the loyalty systems is decreasing day by day. The designed loyalty program mentioned in this thesis works with IZTECH Tokens, which works on the Ethereum chain and are created by following ERC20 standards. Thanks to the new generation loyalty system, users can convert their earned tokens to Ethereum on the stock exchange without accumulating them or can receive services or products with the accumulated tokens according to their interests from a market that has been contracted by the manufacturer. Additionally, users in the designed system do not need to carry many cards, it is adequate to have only one Ethereum wallet. Furthermore, users do not need to share any personal data to join the loyalty system. Markets can request Ether from the manufacturer according to the number of tokens they have accumulated. The loyalty system mentioned in this thesis not only aims to establish a win-win relationship between the manufacturer, market, and client but also to find solutions to the customer problems mentioned above.Master Thesis Block-Chain Based Remote Update for Embedded Devices(Izmir Institute of Technology, 2019) Kaptan, Melike; Ayav, Tolga; Erten, Yusuf MuratThis research work is an attempt to devise a platform to send automatic remote updates for embedded devices. In this scenario there are Original Equipment Manufacturers (OEMs), Software suppliers, Block-Chain nodes, Gateways and embedded devices. OEMs and software suppliers are there to keep their software on IPFS (Inter Planetary File System) and send the meta-data and hashes of their software to the Block-Chain nodes in order to keep this information distributed and ready to be requested and used. There are also gateways which are also the members of the Block-Chain and IPFS network. Gateways are responsible for asking for a specific update for specific devices from IPFS database using the meta-data standing on the Block-Chain. And they will send those hashed secure updates to the devices. In order to provide a traceable data keeping platform gateway update operations are handled as a transactions in the second block-chain network which is the clock-chain of the gateways. In this study implementation of the two block chain shows us that, even though the calculation overhead of the member devices, with regulations specific to the applications block-chains provide applicable platforms.Master Thesis Implementation and Performance Analysis of Contex-Aware Role-Based Access Controls for Cloud-Based Iot Platform(Izmir Institute of Technology, 2019) Döşemeci, Mete Merthan; Ayav, TolgaIoT has received substantial attention in both industry and the scholarly world in the recent years. The main idea is to interconnect the physical world with the digital world. Sensors read physical world and present processible data. This data needs to be secured. Currently, most of the cloud based IoT platforms use some sort of Role-Based Access Control (RBAC) , which is one of the approaches to control access to the devices, hence the data. In some cases RBAC is insufficient for fulfilling constantly changing requirements of IoT. ABAC (Attribute Based Access Control) can be flexible enough for fulfilling. However ABAC requires higher level of maintenance. We wanted to implement a access control method that uses both RBAC’s and ABAC’s advantages. We called it OBAC(Operation Based Access Control). Authorization is being implemented in a plug and play manner. We implemented that way because; It is designed for cloud platforms and we wanted to switch between access control methods easily. The results of the experiment shows that proposed access control(OBAC) had minimum latency and management steps across other access control methods.Master Thesis A Learning-Based Demand Classification Service With Using Xgboost in Institutional Area(Izmir Institute of Technology, 2019) Gürakın, Çağrı; Ayav, TolgaThis study, purposes to explain the development stages and methodology of data classification service that has a text-based adaptable programming interface. One of the successful classification algorithms, XGBoost, was preferred in the study. The dataset that is used in the study obtained by 'Digital Business Tracking Application' of a name anonymized company. The dataset is tested by using different classification algorithms and detailed performance evaluation was conducted. As a result, highest accuracy rate is obtained with 'Data Classification Service' which was developed by using XGBoost algorithm.Master Thesis A Dedicated Server Design for Physical Web Applications(Izmir Institute of Technology, 2019) Abdennebi, Anes; Ayav, TolgaWith the huge impressive technological improvements the world is witnessing where giants like Facebook, Google, Apple, Microsoft and other technology companies are offering different services to millions of clients, services which don’t take usually more than seconds to be within the users’ devices besides the Physical Web applications that makes things interacts, having entities and can be reached based on the proximity context without omitting the incoming IoT infrastructure that would make 20.4 billion devices connected by 2020, the amount of data transferred, and services provided will be enormous and along with that, the big energy consumer standing behind providing clients with the needed data and services instantly, the web servers. Although it has a magnificent performance and responds to billions of queries and requests, however, there is still a crucial point which must be highlighted, the remarkable amounts of energy consumption by these servers. Therefore, this work is proposing a new approach in order to reduce the energy consumption in such a scenario where the 18-core energy efficient computer Parallella board will be used in order to create an energy efficient server that can offer many services triggered by various devices or any ordinary web requests across any environment and to prove also that using a cluster of Parallella supercomputers may perform as other similar servers dealing with web content (e.g. Raspberry Pi server). We will show how would these boards work under low energy feeding where users can access a web content hosted on a Parallella cluster. The source codes of the project are available on GitHub.