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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14411/21
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Article Citation - Scopus: 1Digital Solutions for Disaster Management: Analyzing the Impact of the February 2023 Earthquake in Türkiye(Ankara University, 2024) Nazlıoğlu, Selma; Kalem, Güler; Yazıcı, AliThis research investigates the involvement of information technologies, including communication platforms and social media solutions, in managing earthquake disasters, specifically focusing on the February 2023 earthquake in Türkiye. In order to achieve this, a comparative framework is constructed, which incorporates four main categories, namely goal, providers, target phase, and platform. The data is gathered from diverse sources, and a total of 130 solutions are identified immediately following the February 2023 earthquake in Türkiye. After conducting a thorough examination of these solutions and removing any duplicates and irrelevant options, the final dataset comprises 89 unique solutions sourced from 82 providers. According to the study's findings, the solutions employed in mitigation and preparedness phases prioritize proactive measures and planning, while the ones in response phase witnesses a significant increase in activities related to aid campaigns, emergency response, information dissemination, and support services. The solutions in recovery phase further intensifies support services to aid affected communities. Web-based platforms are predominantly used during different phases of disaster management, with mobile platforms playing a crucial role in communication and on-the-ground activities. Private organizations exhibit strong involvement in developing IT platforms, while public entities and NGOs contribute to a lesser extent.Article A Practical Distributed Lightweight Multi-Hop Time Synchronization Algorithm for Linear Wireless Sensor Networks Implemented on a Pic Based System With Realistic Experimental Analysis(Sakarya University, 2020) Erpay, A.; Al Imran, M.A.; Kara, A.; Imran, Md Abdullah AlTime synchronization is fundamental in the distributed networked systems, especially in Wireless Sensor Networks where a global time is essential to make sense of the events like collection of data and scheduled sleep/wake-up of nodes. There exists numerous time synchronization algorithms and techniques in the literature. Nonetheless, these proposed methods lack realistic experimentation of the synchronization process which is vital from the realization point of view. This study aims to bridge that gap by presenting a distributed lightweight time synchronization protocol implemented on an inexpensive PIC platform. Furthermore, PIC-based systems hadn’t been investigated before and gives an idea of the simplicity of the algorithm. Experimental analysis was done to see the performance of the protocol. The core motivation of the experiments was to the study the impact of the environment (e.g. indoor, outdoors, temperature variations and interference) on the synchronization. Our findings show that temperature indeed impedes the synchronization accuracy. © 2020, Sakarya University. All rights reserved.Article Citation - WoS: 12Citation - Scopus: 12A Polarity Calculation Approach for Lexicon-Based Turkish Sentiment Analysis(Tubitak Scientific & Technological Research Council Turkey, 2019) Yurtalan, Gökhan; Koyuncu, Murat; Turhan, ÇiğdemSentiment analysis attempts to resolve the senses or emotions that a writer or speaker intends to send across tothe people about an object or event. It generally uses natural language processing and/or artificial intelligence techniquesfor processing electronic documents and mining the opinion specified in the content. In recent years, researchers haveconducted many successful sentiment analysis studies for the English language which consider many words and wordgroups that set emotion polarities arising from the English grammar structure, and then use datasets to test theirperformance. However, there are only a limited number of studies for the Turkish language, and these studies have lowerperformance results compared to those studies for English. The reasons for this can be incorrect translation of datasetsfrom English into Turkish and ignoring the special grammar structures in the latter. In this study, special Turkish wordsand linguistic constructs which affect the polarity of a sentence are determined with the aid of a Turkish linguist, and anappropriate lexicon-based polarity determination and calculation approach is introduced for this language. The proposedmethodology is tested using different datasets collected from Twitter, and the test results show that the proposed systemachieves better accuracy than the previously developed lexical-based sentiment analysis systems for Turkish. The authorsconclude that especially analysis of word groups increases the overall performance of the system significantly.Article Selective Word Encoding for Effective Text Representation(Tubitak Scientific & Technological Research Council Turkey, 2019) Özkan, Savaş; Özkan, AkınDetermining the category of a text document from its semantic content is highly motivated in the literatureand it has been extensively studied in various applications. Also, the compact representation of the text is a fundamental step in achieving precise results for the applications and the studies are generously concentrated to improve itsperformance. In particular, the studies which exploit the aggregation of word-level representations are the mainstreamtechniques used in the problem. In this paper, we tackle text representation to achieve high performance in differenttext classification tasks. Throughout the paper, three critical contributions are presented. First, to encode the wordlevel representations for each text, we adapt a trainable orderless aggregation algorithm to obtain a more discriminativeabstract representation by transforming word vectors to the text-level representation. Second, we propose an effectiveterm-weighting scheme to compute the relative importance of words from the context based on their conjunction with theproblem in an end-to-end learning manner. Third, we present a weighted loss function to mitigate the class-imbalanceproblem between the categories. To evaluate the performance, we collect two distinct datasets as Turkish parliamentrecords (i.e. written speeches of four major political parties including 30731/7683 train and test documents) and newspaper articles (i.e. daily articles of the columnists including 16000/3200 train and test documents) whose data is availableon the web. From the results, the proposed method introduces significant performance improvements to the baselinetechniques (i.e. VLAD and Fisher Vector) and achieves 0.823% and 0.878% true prediction accuracies for the partymembership and the estimation of the category of articles respectively. The performance validates that the proposed contributions (i.e. trainable word-encoding model, trainable term-weighting scheme and weighted loss function) significantlyoutperform the baselines.Article Citation - WoS: 7Citation - Scopus: 10Ann-Assisted Forecasting of Adsorption Efficiency To Remove Heavy Metals(Tubitak Scientific & Technological Research Council Turkey, 2019) Buaısha, Magdi; Balku, Şaziye; Yaman, Şeniz Özalp; Özalp Yaman, ŞenizIn wastewater treatment, scientific and practical models utilizing numerical computational techniques suchas artificial neural networks (ANNs) can significantly help to improve the process as a whole through adsorption systems.In the modeling of the adsorption efficiency for heavy metals from wastewater, some kinetic models have been used such as pseudo first-order and second-order. The present work develops an ANN model to forecast the adsorption efficiency of heavy metals such as zinc, nickel, and copper by extracting experimental data from three case studies. To do this, we apply trial-and-error to find the most ideal ANN settings, the efficiency of which is determined by mean square error (MSE) and coefficient of determination (R2). According to the results, the model can forecast adsorption efficiency percent (AE%) with a tangent sigmoid transfer function (tansig) in the hidden layer with 10 neurons and a linear transferfunction (purelin) in the output layer. Furthermore, the Levenberg–Marquardt algorithm is seen to be most ideal for training the algorithm for the case studies, with the lowest MSE and high R2 . In addition, the experimental results and the results predicted by the model with the ANN were found to be highly compatible with each other.Article Citation - Scopus: 1Faır Prensipleriyle Uyumlu Gözlemlenebilen ve İzlenebilen Sosyal Medya Tabanlı Dijital Habercilik Veri Modeli(Gazi Univ, Fac Engineering Architecture, 2024) Takan, Savaş; Takan, Duygu Ergün; Ergun, DuyguGünümüzde artan veri dolaşımı nedeniyle dijital habercilikte bilgi kirliliği ve dezenformasyon daha önce hiç olmadığı kadar yaygın hale gelmiştir. Eski tarihlerde bilgiye erişim bir hak olarak vurgulanırken, günümüzde bilgi kirliliğinden korunma hakkı ortaya çıkmıştır. Bunun en temel nedeni, dijital ortamda dolaşıma giren çok sayıda haberin takibinin yapılamaması ve dijital haber paylaşımının gerektirdiği sorumlulukları düzenleyecek bir yapının bulunmamasıdır. Bu gibi problemlerin çözümüne yönelik çalışmamızda dijital habercilik veri modeli geliştirilmiştir. Dijital habercilik için önerdiğimiz veri modeli, FAIR prensiplerini sağlamasının yanı sıra, haberlerin birbiriyle mantıksal ilişkiye sahip olmasını ve haberlerin tüm süreçleriyle takip edilebilir olmasını mümkün kılarak, güvenilir bir sosyal medya ağı oluşturur. Herhangi bir veri modelinin gözlemlenebilen ve izlenebilen bir sosyal medya ortamını destekleyebilmesi için, büyük verileri barındıran çizge yapılarıyla çalışabilmesi gerekmektedir. Mevcut blokzinciri teknolojileri, gözlemleyebilme ve izleyebilme özelliklerini sağlasa da bu teknolojiler sosyal medya ağının gerektirdiği çizge veri yapısını desteklememektedir. Bu problemleri çözmek için, önerdiğimiz yapıda model ile veri birbirinden ayrılmış ve indeksleme mekanizmalarının desteklenmesi sağlanmıştır. Önerilen veri modeli, blokzinciri teknolojisinin veri modeli ile karşılaştırılmış ve sonuçta, dijital habercilik için geliştirdiğimiz modelin zaman ve alan karmaşıklığının yanı sıra, sürdürülebilirlik ve bakım maliyetleri açısından blokzinciri teknolojisinin veri modeline göre daha uygun olduğu tespit edilmiştir.Article Citation - WoS: 1Citation - Scopus: 1İki Boyutlu Doğrusal Tek Tip Hücresel Özdevinirlerin Başlangıç Durum Yoğunluklarını Dikkate Alan Sözde Rastgele Sayı Üretimlerinin Başarım Analizi(Gazi Univ, Fac Engineering Architecture, 2024) Kılıç, HürevrenBu çalışmada, iki boyutlu doğrusal tek tip hücresel özdevinirlerin başlangıç durum yoğunluklarının sözde-rastgele sayı üretimlerine olan etkisi deneysel olarak incelenmiştir. Geliştirilen yaklaşım, hücresel özdevinirlerin kaliteli sözde-rastgele sayı üretimlerinde başlangıç durum yoğunluklarının dikkate alması açısından özgündür. Deneylerde 512 adet iki boyutlu doğrusal hücresel özdevinir (DHÖ) değerleri 0,05 ile 0,95 arasında değişen 19 adet farklı başlangıç durum yoğunlukları (ρ) için (toplam 512*19 = 9728 adet) incelenmiştir. Sayı dizisi üretimlerini takiben deneylerin ilk aşamasında söz konusu DHÖ’ler literatürde bilinen rastgele sayı üreteçleriyle birlikte National Institute of Standards and Technology (NIST) istatistiksel test süiti testlerine tabi tutulmuştur. İkinci aşamada ise, ilk aşamadaki NIST testlerinden başarılı olarak geçen 7 adet farklı yoğunluktaki hücresel özdevinire ve literatürde bilinen üreteçlere AIS31 ve TestU01 test süitlerinde yer alan testler uygulanmıştır. Yapılan karşılaştırmalı çalışma neticesinde, rastgele sayı üretimlerinde başarılı olan 2D doğrusal hücresel özdevinir üreteçlerin doğrudan kriptografik amaçlı uygulamalar için kullanımlarının uygun olmadığı, özellikle literatürde yer alan zorlu (stringent) testlerden olan TestU01 testlerinin uygulanması neticesinde görülmüştür. Bu netice literatürde bilinen sonuçları desteklemektedir. Öte yandan 9728 adet özdevinire uygulanan NIST testleri neticesinde alınan sonuçlara göre özdevinirlerin başlangıç durum yoğunluk oranlarının sözde rastgele sayı üretimlerini etkilemektedir ve literatürde dikkate alınmayan bu durum özdevinir tabanlı sözde rastgele sayı üretimi araştırmalarında dikkate alınmalıdır.Article Citation - WoS: 7Citation - Scopus: 10Comparison of Three Different Learning Methods of Multilayer Perceptron Neural Network for Wind Speed Forecasting(Gazi Univ, 2021) Bulut, Mehmet; Tora, Hakan; Buaisha, Dr.magdi; Buaisha, MagdiIn the world, electric power is the highest need for high prosperity and comfortable living standards. The security of energy supply is an essential concept in national energy management. Therefore, ensuring the security of electricity supply requires accurate estimates of electricity demand. The share of electricity generation from renewables is significantly growing in the world. This kind of energy types are dependent on weather conditions as the wind and solar energies. There are two vital requirements to locate and measure specific systems to utilize wind power: modelling and forecasting of the wind velocity. To this end, using only 4 years of measured meteorological data, the present research attempts to estimate the related speed of wind within the Libyan Mediterranean coast with the help of ANN (artificial neural networking) with three different learning algorithms, which are Levenberg-Marquardt, Bayesian Regularization and Scaled Conjugate Gradient. Conclusions reached in this study show that wind speed can be estimated within acceptable limits using a limited set of meteorological data. In the results obtained, it was seen that the SCG algorithm gave better results in tests in this study with less data.Article An Adaptive Element Division Algorithm for Accurate Evaluation of Singular and Near Singular Integrals in 3d(Tubitak Scientific & Technological Research Council Turkey, 2021) Bayindir, Hakan; Baranoglu, Besim; Yazici, AliAn adaptive algorithm for evaluation of singular and near singular integrals in 3D is presented. The algorithm is based on successive adaptive/selective subdivisions of the element until a prescribed error criteria is met. For evaluating the integrals in each subdivision, Gauss quadrature is applied. The method is computationally simple, memory efficient and can be applied for both triangular and quadrilateral elements, including the elements with nonplanar and/or curved surfaces. To assess the method, several examples are discussed. It has shown that the algorithm performs well for singular and near-singular integral examples presented in the paper and evaluates the integrals with very high accuracy.Article Citation - WoS: 1Citation - Scopus: 1A New Multi-Target Compiler Architecture for Edge-Devices and Cloud Management(Gazi Univ, 2022) Gokcay, ErhanEdge computing is the concept where the computation is handled at edge-devices. The transfer of the computation from servers to edge-devices will decrease the massive amount of data transfer generated by edge-devices. There are several efficient management tools for setup and connection purposes, but these management tools cannot provide a unified programming system from a single source code/project. Even though it is possible to control each device efficiently, a global view of the computation is missing in a programming project that includes several edge-devices for computation and data analysis purposes, and the devices need to be programmed individually. A generic workflow engine might automate part of the problem using standard interfaces and predefined objects miming on edge-devices. Nevertheless, the approach fails in fine-tuning each edge-device since the computation cannot be moved easily among devices. This paper introduces a new compiler architecture to control and program edge-devices from a single source code. The source code can be distributed to multiple edge-devices using simple compiler directives, and the transfer and communication of the source code with multiple devices are handled transparently. Fine-tuning the source code and code movement between devices becomes very efficient in editing and time. The proposed architecture is a lightweight system with fine-tuned computation and distribution among devices.