2045 research outputs found
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Performing DISC Personal inventory analysis in job postings using artificial intelligence methods
No full textOne of the application fields of DISC selfevaluation analysis was introduced to predict people's performance and orientation in their working life. Each letter in the word DISC represents an essential personal characteristic, dividing the profiles of people in business life into four essential parts. In the current study, DISC analysis is conducted on job postings to match the person with the job posting. The current study was based on the analysis of 3 different datasets with job postings in English, Turkish and Romanian prepared by using web scraping methods and then labeled in accordance with DISC criteria. Several different machine learning algorithms have been performed on the DISC analysis outputs, and they reached the best results with accuracy values of around over 96% on the English dataset, around over 95% on the Turkish dataset, and around over 96% on the Romanian dataset, for both D, I, S, C models.Aralı
Development of a knowledge-based multimodal deep learning system for automatic breast lesion segmentation and diagnosis in MG/DMR images
No full textDeep learning networks (DLNs) rely on labeled training datasets as their fundamental building blocks. While various databases exist worldwide, there is currently no domestic solution available in our country. This project aims to create a domestic database by automatically segmenting breast lesions in MG/DMR images based on their types and developing a knowledge-based multimodal DL-based integrated computer-aided diagnosis system to analyze the images, thereby providing the system with continuous learning capability. Different brands of devices exist for MG/DMR, necessitating the multimodal operation of image processing/artificial intelligence algorithms. To achieve this goal, the network was trained first, and then prelearned data were transferred to enable the training of data from different networks once accurate results are obtained. The developed system has the potential to enable the automatic detection of breast lesions, ensuring fast and high diagnostic accuracy. Additionally, it might also facilitate the retrospective analysis of patients' periodic check-up results.2-s2.0-85177573924Eylü
Unraveling the Links among Witnessing Interparental Conflict, Hopelessness, Psychological Dating Violence Victimization, and Adult Depressive Symptoms
No full textWitnessing interparental conflict in childhood predicts psychological dating violence victimization (PDVV) in adulthood. As found in previous studies, PDVV and hopelessness are associated with depression. However, the associations among these four variables have not been explored in detail. The present study, therefore, examined the association between perceived interparental conflict and depression in adulthood and whether PDVV and hopelessness might operate as sequential mechanisms accounting for the association. Participants (N = 283; M-age = 23.37 years, SD = 4.04 years) in romantic relationships completed measures of perceived interparental conflict, PDVV, hopelessness, and depression. The perceived interparental conflict was related to PDVV and depression but not to hopelessness in adulthood. Moreover, the association between witnessing interparental conflict and depression was serially mediated via PDVV and hopelessness. The results are discussed in regard to previous research, and their implications for future research are presented.WOS:0010464761000012-s2.0-8516782428737565306Social Sciences Citation IndexarticleUluslararası işbirliği ile yapılan - EVETAğustosYÖK - 2022-2
Design and FPGA implementation of UAV simulator for fast prototyping
No full textAs production and advances in motor and battery cell technology progress, unmanned aerial vehicles (UAVs) are gaining more and more acceptance and popularity. Unfortunately, the design and prototyping of UAVs is an expensive and long process. This paper proposes a fast, component based simulation environment for UAVs so that they can be roughly tested without a damage risk. Moreover, the combined effect of individual component choices can be observed with the simulator to reduce design time. The simulator is flexible in the sense that detailed aerodynamic effects and selected components models can be included. In this work, the simulator is proposed, model parameters are extracted for a particular UAV for testing the simulator and it is implemented on an field programmable gate array (FPGA) to increase simulation speed. The simulator calculates battery state of charge (SOC), position, velocity and acceleration of the UAV with gravity, drag, propeller air inflow velocity. The simulator runs on the FPGA fabric of AMD-XCKU13P with simulation steps of 1 ms.Baykon Industrial Weighing Systemset al.
IEEE
IEEE Circuits and Systems Society (CAS)
Isik University, Faculty of Engineering
Savronik2-s2.0-85183581896Aralı
Energy Consumption at Home: Insights for Sustainable Smart Home Marketing
No full textEnergy consumption has been a vital subject for both energy producers and consumers. The intersection of energy consumption and home words are of increasing importance in both literature and practice. Households try to utilize energy in the most efficient and sustainable way. On the other hand, smart home technologies which let the households control their houses are on the rise. Those technologies also help balance the energy consumption and live in a more sustainable way. This study aims to underline the importance of smart home technologies to increase energy efficiency and pave the way for a more sustainable energy management. In line with this purpose, a bibliometric study has been conducted to enlighten the literature development in energy consumption and home subjects. The results are expected to be helpful for both literature and practice as well as energy providers and consumers.Yasar Univ, Inst Res Circular Econ & Environm Ernest LupanWOS:000982537700007Conference Proceedings Citation Index – Science -
Conference Proceedings Citation Index – Social Science & HumanitiesProceedings PaperUluslararası işbirliği ile yapılmayan - HAYIRMayısYÖK - 2022-2
Live demo: design and FPGA implementation of a component level uav simulator
No full textIn this work, we introduce a fast, component based simulation environment for UAVs. The simulator framework is proposed as combination of three sub-models: i. battery, ii. BLDC and propeller, iii. dynamic model. The model parameters are extracted for a particular UAV for testing the simulator. The simulator is implemented on an FPGA to increase simulation speed. The simulator calculates battery SOC, position, velocity and acceleration of the UAV with gravity, drag, propeller air inflow velocity. The simulator runs on the FPGA fabric of XilinxXCKU13P with simulation steps of 1 ms.Baykon Industrial Weighing Systemset al.
IEEE
IEEE Circuits and Systems Society (CAS)
Isik University, Faculty of Engineering
Savronik2-s2.0-85183583043Aralı
Gözetimsiz makine öğrenmesi algoritmaları kullanılarak faktöring müşterilerı için segmentasyon yapılması
No full textGünümüzde teknolojinin veri toplamayı kolaylaştırmasının önemli bir fırsat olmasının yanı sıra tüm bu verilerin yönetimini zorlaştırmakta ve veriler iyi işlenmedikçe bir anlam ifade etmemektedir. Depolanan bu veriler son derece önemlidir ve şirketler, müşterileri tarafından sağlanan verileri kullanır. Değişen dünyanın müşteri profillerinin ihtiyaçlarını yakalamak artık bir zorunluluk haline gelmekte ve firmalar için ilk sırayı almaktadır. Zamanla depolanan verinin artması ile artık veriler arasında ilişki kurmak ve bunları birbirinden ayırmak zor bir hal almıştır. Bu noktada hayatımıza makine öğrenmesi yöntemleri daha fazla dahil olmaya başlamıştır. Bu çalışmada, segmentasyonun ne olduğu ve yıllar içindeki değişiminden bahsedilmiştir. Hangi makine öğrenmesi tekniklerinin veri seçiminde faydalı olacağına değinilmiştir. Ardından olası makine öğrenmesi yöntemleri yerel bir faktoring şirketinin müşteri çek verileri kullanılarak gösterilmiştir. Bu çalışma etiketsiz verilerin gruplanmasını hedeflediğinden gözetimsiz öğrenme teknikleri üzerinde durulmuştur. Bu yöntemler arasında en popular olan K – means algoritmasının yanı sıra Hiyerarşik Kümeleme, DBSCAN, Gauss Karışık Modelleme ve Fuzzy c - Means yöntemleri kullanılmıştır. Her bir algoritma için başarı ölçütleri incelenerek uygun küme sayıları bulunmuş ve bulunan sonuçlar karşılaştırılmıştır. Kümeleme sonuçları incelendiğinde GMM ile optimal küme sayısı oldukça yüksek hesaplanmış, DBSCAN küme atayamamış, Hierarchical clustering ise zaman açısından maliyetli bulunmuştur. En iyi sonuçların K - means ve Fuzzy c - Means algoritmalarıyla elde edildiği gözlemlenmiştir.Nowadays the fact that technology facilitates data collection is an important opportunity, as well as making the management of all this data difficult and makes no sense unless it is well processed. This stored data is extremely important, and companies use data provided by their customers. Catching the needs of the customer profiles of the changing world is now a necessity and takes the first place for companies. With the increase in the amount of stored data over time, it has become difficult to establish a relationship between the data and to separate them from each other. At this point, machine learning methods have become more involved in our lives. In this study, what segmentation is and its change over the years are mentioned. It has been mentioned which machine learning techniques will be useful in data selection. Then, possible machine learning methods are shown using the local factoring company's customer check data. Since this study aims to group unlabeled data, unsupervised learning techniques are emphasized. Among these methods, Hierarchical Clustering, DBSCAN, Gaussian Mixed Modeling methods, Fuzzy c - Means were used besides the most popular K-Means. The success criteria for each algorithm were examined and the appropriate cluster numbers were found, and the results were measured. When the clustering outcomes were examined, the optimal number of clusters was calculated very high with GMM, DBSCAN could not assign clusters, and Hierarchical clustering has been found to be very costly in terms of time. It was observed that the best results were obtained with the K - Means and FCM
MQTT protokolü veri güvenliğinin OTP blokzincir tabanlı kimlik ve veri doğrulama ile sağlanması
No full textSon yıllarda teknolojinin hızla gelişmesiyle birlikte, Nesnelerin İnterneti (IoT) adını verdiğimiz akıllı cihazlar ve sistemler hayatımızın her alanında kendine yer bulmaktadır. IoT, akıllı telefonlar, tabletler, PC'ler ve üzerinde sensör bulunan neredeyse her şeyi kapsayan geniş bir kavramdır. Bu kapsamda, IoT cihazları arasında verimli ve güvenli iletişim sağlamak amacıyla MQTT protokolü önemli bir role sahiptir. Bu tezde, MQTT protokolünün güvenlik zafiyetlerini tespit etmek ve bu zafiyetlere karşı etkili önlemler geliştirmek hedeflenmektedir. Tez kapsamında, Raspberry Pi ve bilgisayar arasında MQTT server client mimarisi oluşturulmuştur. MQTT Broker ve yayıncı/abone istemcileri için Python programları geliştirilmiş, sistem üzerinde çeşitli güvenlik açıklarını tespiti sağlanırken Shodan API'sinden ve Wireshark'dan yararlanılmıştır. Bu süreçte, paket ve konu düzeyindeki güvenlik sorunları deneysel olarak incelenmiştir. Akıllı sözleşmeler, dijital imzalar, OTP kullanarak 1883 numaralı portunda bir yapı geliştirilmiştir. Bu, yayıncı ve abone için kimlik doğrulama ve şifreleme sağlayarak yalnızca yetkili kullanıcıların MQTT brokerine bağlanmasına olanak tanır. Kimlik doğrulama, mesaj reddetme, veri bütünlüğü ve seçici gizlilik gibi ek güvenlik önlemleri sunulmaktadır. MQTT brokerına erişim, veri yayınlama veya okuma isteyen bir kullanıcının sadece gerekli yetkiye sahip olması yetmez, aynı zamanda benzersiz OTP (Tek Seferlik Şifre) bilgilerine dayalı olarak dijital imzalı bir mesajı onaylaması da gereklidir. Bu imza Elips Kavisli Dijital İmza Algoritması'na dayanır. Erişim izinlerine sahip kullanıcılar, dijital imzayı genel anahtar ve OTP bilgilerini kullanarak doğrulayabilirler. Dijital imzalar, asimetrik şifreleme tekniklerini kullanarak, iletilen her bir MQTT mesajının bütünlüğünü ve kökenini doğrular. Bu, iletilen verinin değiştirilmediğini ve belirli bir cihaz veya kullanıcıdan geldiğini garantiler. SSL/TLS, bağlantı bazında çalışır ve tüm bağlantıyı şifreler. Geniş ölçekteki sistemlerde, SSL/TLS sertifikalarının yönetimi ve sürekli şifreleme/şifre çözme işlemleri, özellikle düşük kapasiteli IoT cihazlarında ek işlem yükü oluşturabilir. Akıllı sözleşmeler ve dijital imzaların kullanımı, geniş ölçekteki çok sayıda yayınlayıcı ve abone içeren sistemlerde, SSL/TLS'ye göre daha ölçeklenebilir bir çözüm sunabilir. Tez çalışması sonucunda, geliştirilen güvenlik önlemleri sayesinde Broker'ın saldırılara karşı bağışık olduğu tespit edilmiştir. Bu tez, MQTT protokolündeki güvenlik tutarsızlıklarının ve alınabilecek önlemlerin özlü bir incelemesini sunarak, alanındaki çalışmalara katkı sağlamayı hedeflemektedir. Bu sayede, IoT sistemlerinde veri iletişiminin daha güvenli ve etkin bir şekilde gerçekleştirilmesine yardımcı olunacaktır.The widespread Internet of Thing presence in almost every aspect of our lives has been made possible by the fast development of technology these past few years. The internet of things is in a wide area. For example cell phones, tablets, computers and all other devices with sensors. Among the technologies used to facilitate efficient communication, between these IoT devices the MQTT protocol stands out. Exposure of security vulnerabilities existing in MQTT, and the development of effective countermeasures is a key objective of this thesis. The MQTT server's client architecture was built between the Raspberry Pi and the computer. To be used by MQTT Broker and publisher subscribers, Python programs have been developed. The use of the wireshark API has been recommended to check for system security vulnerabilities. During that process, the safety issues at packet and module level have been examined in an experimental manner. The MQTT protocol has been found to be vulnerable to attacks. Although encryption can be performed on port 8388 with Secure Sockets (SSL) and Transport Layer Security (TLS) protocols to address the security vulnerabilities found in the standard MQTT configuration, this is not preferred and is not scalable. Instead, a structure has been developed on port 1883 again, using smart contracts, digital signatures to only allow authorized users to connect to the MQTT broker, providing authentication and encryption for the publisher and subscriber. Extra security measures are offered with authentication, message denial, data integrity, and selective privacy. In the area of Smart Contracts major progress has been made. A smart contract, ensuring transparency and traceability in every transaction offering benefits, plays an important role. Smart contracts consist of an automated set of instructions which, when certain conditions have been fulfilled, shall be executed automaticly. Users' permissions as well as Digital Signatures could be included in these conditions. Better scalability is also provided by this system. Using A system has been developed using Smart Contract technology to perform user authentication and permission management for users connected to an MQTT broker. Authorization processes such as adding, removing, granting, or denying user permissions can be executed through a smart contract. Similarly, a user seeking to access and publish or read data on the MQTT broker must not only possess the necessary authorization but also approve a digitally signed message based on their unique OTP (One-Time Password) information. The Elliptic Curve digital signature algorithm is used for this signature. Users with access permissions can verify the digital signature using their public key and OTP information. Once the smart contract confirms the user's permission to publish data, they can proceed with their publication or perform encrypted data readings This design is intended to stop entry and manipulation of data, within the system. In contrast with the data security offered by SSL or TLS, this new and effective method provides additional protection against attacks on data centre such as potential Distributed Denial of Service attack from Sybil. Upon completion of this thesis, it was determined that the Broker gained immunity against attacks due to the implemented security measures.Consequently the thesis offers an examination of MQTT in relation, to attacks and suggests an enhanced security mechanism to counteract these attacks