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Yazar "Şimşek, Mehmet" seçeneğine göre listele

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    An Analysis of the Characteristics of Verified Twitter Users
    (2019) Kabakus, Abdullah Talha; Şimşek, Mehmet
    Twitter, the most popular microblog, contains a large variety of users as a result of its huge popularity. Twittermanually verifies the accounts which are deemed worthy of public interest. As a natural consequence of beingverified, users trust these verified accounts since they represent legitimate users, and are managed by authorizedusers. To the best of our knowledge, Twitter has never revealed the requirements of being verified. In this study,in order to shed light on the characteristics of verified Twitter users, a software, which is based on Pythonprogramming language that utilizes a recent dataset, which consists of 297,798 verified Twitter users, wasimplemented within the scope of this study. The characteristics of verified Twitter users such as being public, andhaving a customized profile were revealed as a result of the analysis of the utilized dataset.
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    Application Specific Sleep-Awake Strategy for Increasing Network Lifetime in Wireless Sensor Networks
    (2018) Şimşek, Mehmet; Toklu, Sinan
    Wireless Sensor Networks (WSN) is a technology that provides distributed data collection. However, thesenetworks have some limitations. The most important constraint is energy limitations. The lifespan of sensornodes that run on small battery depends on the battery life. Although there are many studies in the field ofenergy efficiency to extend the life of nodes, enough improvement has not been obtained yet. The most basicway to achieve energy efficiency is to sleep and awake the nodes or clusters of nodes. In this study, we proposedan application specific method to wake up and sleep nodes in WSNs. In traditional strategy, the nodes in thecluster sense data and send it to the Cluster Head (CH), if CHs detect redundancy of some data; they remove theduplication and send it to the base station. This is causing energy loss. Our method puts some nodes to sleepstate if there are similar data in a certain period. By this way, the life of the network is extended.
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    ARTIRILMIŞ GERÇEKLİK YÖNTEMLERİ İLE KONUMSAL MOBİL KAMPÜS BİLGİ SİSTEMİ
    (Düzce Üniversitesi, 2018) Sabah, Levent; Şimşek, Mehmet
    Artırılmış gerçeklik (AG) görüntü, grafik, hologram, ses, konum vb. unsurların gerçek zamanlı olarak zenginleştirilerek oluşturulan canlı, doğrudan veya dolaylı fiziksel görünümüdür. Verilerin ve görüntülerin gerçek dünya görüntülerine eklenmesiyle zenginleştirilmiş bir ortam oluşturan AG ilk kullanıma başlandığı yıllarda dijital araçların yetersiz kabiliyetleri sebebiyle gelişimi sınırlı, kullanımı lüks, yapımı zahmetli bir teknoloji olarak görülmekteydi.  Günümüzdeki yazılım ve donanım alanındaki gelişmelerle birlikte uygulama alanı genişleyerek sanayi, eğitim, trafik, sağlık, spor, eğlence ve askeri alanlarda yaygın olarak kullanılmaya başlanmıştır. Bu çalışmada artırılmış gerçeklik yöntemleri kullanılarak kampüs bilgi sistemlerinde kişilerin görsel açıdan daha canlı bir sistem kullanmaları sağlanmıştır. Ayrıca binaların coğrafi konumları işlenerek kişinin bulunduğu konumun anlık koordinat değerlerine göre kampüs içi gezintisini rahat bir şekilde gerçekleştirmesi sağlanmaktadır. Bunun için kişinin mobil cihazına yüklenen bir mobil arayüz yazılımı ile bulunduğu konum ve etrafındaki sisteme konumsal olarak eklenen bina ve diğer önemli nokta (poi – point of interest) bilgileri ekranda gösterilmektedir. İlgili noktaların üzerine tıklandığında detayları görüntülenebilmektedir. Ayrıca görüntüleme mesafe aralığı artırılarak tüm kampüs içindeki noktalar görülebildiği gibi azaltılarak sadece yaklaşılan binaların nokta bilgileri de görüntülenebilmektedir.
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    Arttırılmış Gerçeklik Yöntemleri İle Konumsal Mobil Kampüs Bilgi Sistemi
    (2018) Sabah, Levent; Şimşek, Mehmet
    Artırılmış gerçeklik (AG) görüntü, grafik, hologram, ses, konum vb. unsurların gerçek zamanlı olarak zenginleştirilerek oluşturulan canlı, doğrudan veya dolaylı fiziksel görünümüdür. Verilerin ve görüntülerin gerçek dünya görüntülerine eklenmesiyle zenginleştirilmiş bir ortam oluşturan AG ilk kullanıma başlandığı yıllarda dijital araçların yetersiz kabiliyetleri sebebiyle gelişimi sınırlı, kullanımı lüks, yapımı zahmetli bir teknoloji olarak görülmekteydi. Günümüzdeki yazılım ve donanım alanındaki gelişmelerle birlikte uygulama alanı genişleyerek sanayi, eğitim, trafik, sağlık, spor, eğlence ve askeri alanlarda yaygın olarak kullanılmaya başlanmıştır. Bu çalışmada artırılmış gerçeklik yöntemleri kullanılarak kampüs bilgi sistemlerinde kişilerin görsel açıdan daha canlı bir sistem kullanmaları sağlanmıştır. Ayrıca binaların coğrafi konumları işlenerek kişinin bulunduğu konumun anlık koordinat değerlerine göre kampüs içi gezintisini rahat bir şekilde gerçekleştirmesi sağlanmaktadır. Bunun için kişinin mobil cihazına yüklenen bir mobil arayüz yazılımı ile bulunduğu konum ve etrafındaki sisteme konumsal olarak eklenen bina ve diğer önemli nokta (poi – point of interest) bilgileri ekranda gösterilmektedir. İlgili noktaların üzerine tıklandığında detayları görüntülenebilmektedir. Ayrıca görüntüleme mesafe aralığı artırılarak tüm kampüs içindeki noktalar görülebildiği gibi azaltılarak sadece yaklaşılan binaların nokta bilgileri de görüntülenebilmektedir.
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    An Augmented Reality Application for Computer Engineering Curriculum
    (2017) Şimşek, Mehmet; Toklu, Sinan; Özsaraç, Hamza; Zavrak, Sultan; Başer, Ekrem; Takgil, Büşra; Kanbur, Zafer
    Today, smart phones and tablet PCs have a huge application area due to their capabilities and ease of use. One of these application areas is education. Especially, supportive technologies have brought big innovations on teaching abstract concepts to the students. One of these technologies is Augmented Reality (AR) which moves graphic&animation usage one step towards. In this study, we shared our experiments on the usage of AR in computer engineering curriculum and presented the application that developed with using AR for supporting the abstract concepts of Discrete Mathematical Structures course
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    Energy Efficiency with Centralized Layering Approach for Multihop Wireless Sensor Networks
    (2020) Şimşek, Mehmet; Toklu, Sinan
    Sensors and Wireless Sensor Networks (WSN) are an important component of the Internet of Things (IoT) era. Sensors can be used in easily accessible areas such as factories; It is also used in places with difficult access, such as cultivated areas, forests etc. The most important constraint of sensors placed in areas where access is difficult is energy. Therefore, sensors need to spend as little energy as possible to communicate with each other. For this purpose, a number of studies were made concerning the optimization of energy in WSNs. Most of the studies are carried out in MAC and Routing Layers. In this study, we developed a new routing protocol called Base-Station Layered LEACH (BLLEACH) based on LEACH (Low Energy Adaptive Clustering Hierarchy) routing protocol, which is one of the most significant benchmarks in WSNs. BLEACH divides the network into clusters in a multi-hop environment. Experimental results show that BLLEACH outperforms LEACH and MDLEACH (Multi-hop dynamic clustering LEACH) in terms of energy efficiency and throughput.
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    Fast and lightweight detection and filtering method for low-rate TCP targeted distributed denial of service (LDDoS) attacks
    (Wiley, 2018) Şimşek, Mehmet; Şentürk, Arafat
    Detection and filtering of low-rate distributed denial of service (LDDoS) attacks is hard since their behavior is similar to legitimate users' behavior. In the literature, there are many filtering approaches and metrics for LDDoS attacks. However, most of the LDDoS detection methods in the literature only monitor congestion state. Actually, precongestion period that the attack has already started has valuable information about the attack. In this study, we proposed a method that uses precongestion period for metric calculation. Also, most of LDDoS filtering approaches have high false-positive and false-negative rates and also require long period of time for detection. Additionally, we developed an efficient method for detection and filtering of LDDoS attacks. According to the experimental results, the proposed LDDoS detection method has zero false-positive and false-negative rates under the scenarios; attack detection time is significantly reduced with using the proposed metric calculation approach. Also, the proposed method has a simple logic, and it requires simple calculations. This increases the applicability of the developed method.
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    Finding Influencers on Twitter with Using Machine Learning Classification Algorithms
    (Aydın KARAPINAR, 2018) Şimşek, Mehmet; Kabakuş, Abdullah Talha
    Microblog sites are environments where people follow people. With this feature, a microblog site is a convenient environment for spreading an opinion or introducing a new product. The key point is determination of individuals who maximize the spreading. This problem is known as Influence Maximization (IM) and has attracted attention of many researchers. Many studies in the literature have modeled IM problem on graphs for different propagation models such as Independent Cascade (IC) and Linear Threshold (LT). However, microblogs like Twitter have their own features. Many works on IM in Twitter derive new metrics from user and tweet features; apply a greedy approach for selecting influencers. In this study, we adopted different approach for IM problem, and we dealt it as a classification problem. Firstly, we collected data on International Women Day 2018; empirically we labeled the users as either influencer candidates or non-influencers; then we applied classification methods for classifying users into one class with using features of users. By this way, we obtained an influencer candidates set, which is very smaller than entire dataset. Experimental results show that making selection with using same heuristic (namely MF) from the reduced influencer candidates set outperforms making selection from entire dataset.
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    HIGHWAYS DISTURBANCE DETECTION with the USE of OPEN SOURCE CODE GEOGRAPHIC INFORMATION SYSTEMS, MOBILE and WEB APPLICATIONS
    (Copernicus GmbH, 2017) Sabah, Levent; Şimşek, Mehmet
    Road disturbances are occurring in our country due to the highway-weighted transportation. These disturbances are caused by human and natural causes. Disturbances in the roads have a negative effect on human life as well as damage to the vehicles. Regardless of how it occurs, it is important to quickly detect and eliminate roadside disturbances. The use of mobile devices has become widespread with developing technologies. Today, many sensors such as GPS and accelerometer are used to detect road disturbances on mobile devices. In this context, it is important to use mobile applications for fast and in-situ detection. In this study, it is investigated the use of mobile devices' location data received from GPS sensors with special mobile interfaces in gathering road data for road disturbances. © Authors 2017.
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    Investigation of spatial data with open source social network analysis and geographic information systems applications
    (International Society for Photogrammetry and Remote Sensing, 2017) Sabah, Levent; Şimşek, Mehmet
    Social networks are the real social experience of individuals in the online environment. In this environment, people use symbolic gestures and mimics, sharing thoughts and content. Social network analysis is the visualization of complex and large quantities of data to ensure that the overall picture appears. It is the understanding, development, quantitative and qualitative analysis of the relations in the social networks of Graph theory. Social networks are expressed in the form of nodes and edges. Nodes are people / organizations, and edges are relationships between nodes. Relations are directional, non-directional, weighted, and weightless. The purpose of this study is to examine the effects of social networks on the evaluation of person data with spatial coordinates. For this, the cluster size and the effect on the geographical area of the circle where the placements of the individual are influenced by the frequently used placeholder feature in the social networks have been studied. © Authors 2017.
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    Misoprostol-Induced Modification of the Notch Signaling Pathway in the Human Cervix
    (Sage Publications Inc, 2019) Avcı, Sema; Şimşek, Mehmet; Soylu, Hakan; Üstünel, İsmail
    The complex and multifactorial mechanisms that initiate and sustain the early labor process in the human uterus and cervix are still not well defined. Cervical maturation or ripening is likely to play a key role in preparing for birth. Prostaglandins have many different functions, including the regulation of uterine contractility and structure during pregnancy. The prostaglandin E1 analogue misoprostol is frequently used as a uterotonic and cervical ripening agent. Notch is a transmembrane receptor family responsible for basic functions such as cell survival, cell-cell communication, and differentiation and decidualization in pregnancy. However, our understanding of the effect of Notch signaling on the cervical ripening process is limited. This study was conducted in 20 pregnant women aged at 12 to 20 weeks of gestation undergoing medical abortion for fetal or maternal indications. True-Cut needle biopsies were taken from the anterior cervix 4 hours after oral ingestion of 200-mu g misoprostol or before the ingestion of misoprostol in the control group. Cervical expression of Notch receptors and ligands changed during the early phase of prostaglandin-induced preterm labor. Four hours after the administration of misoprostol, it was seen that N1 expression increased in muscle, while DLL1 and J2 expression increased in blood vessels, and N4 expression increased in macrophages. Knowing the mechanisms that initiate preterm birth is the most important step in planning the treatments and actions to prevent premature birth. As a signal that affects and perhaps directs preterm labor, Notch is prone to be an important actor in this process.
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    A new fast entropy-based method to generate composite centrality measures in complex networks
    (Wiley, 2023) Sabah, Levent; Şimşek, Mehmet
    Determining the centrality of nodes in complex networks provides practical benefits in many areas such as detecting influencer nodes, viral marketing, and preventing the spread of rumors. On the other hand, there is no consensus for the definition of centrality. Therefore, different centrality measures such as degree, closeness, and betweenness have been developed to measure the centrality of a node. However, each centrality measure highlights the various characteristics of the nodes in the network from its own point of view. This causes each centrality measure to rank the nodes in a different order. In recent years, researchers have focused on approaches that combine multiple centrality measures. Thus, the perspectives of different centrality measures can be considered simultaneously. In this study, we have proposed a fast and efficient method using the analytic hierarchy process and entropy weighting to combine multiple centrality measures. We tested the proposed method with synthetic and real datasets and compared the results with those of state-of-the-art methods. The experimental results showed the proposed method to be competitive with these advanced methods, whereas it performed much better than the other methods in terms of computational speed. This indicated that our proposed method could be applied to large and dynamic complex networks.
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    A new metric for flow-level filtering of low-rate DDoS attacks
    (Wiley-Hindawi, 2015) Şimşek, Mehmet
    Low-rate distributed denial-of-service (LDDoS) attacks dramatically reduce transmission control protocol throughput by exploiting the vulnerability in the transmission control protocol congestion control mechanism. The current study proposes a new metric called mean Internet Protocol (IP) packet delay variation (mipdv) to detect LDDoS flows and a filtering method called ipdv-based LDDoS filtering (ILF) using mipdv. Receiving first seven packets from a flow is sufficient to calculate the mipdv metric. Subsequently, mipdv can be recalculated for each received packet. This makes the detection of LDDoS flows possible in a short time (in a few tens of milliseconds in most cases). Ns2 simulations were conducted to evaluate the performance of ILF. Experimental results show that ILF detects LDDoS flows in a very short time with very high accuracy. Copyright (C) 2015 John Wiley & Sons, Ltd.
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    A New Metric for Flow-Level Filtering of Low-Rate DDoS Attacks (vol 8, pg 3815, 2015)
    (Wiley-Hindawi, 2018) Şimşek, Mehmet
    …
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    Plantar fibromatosis in a mentally challenged man treated with intralesional corticosteroids
    (Pulse Marketing and Communications LLC, 2017) Karadağ, Ayşe Serap; Özlü, Emin; Ceyran, Ayşe Bahar; Şimşek, Mehmet; Uzunçakmak, Tuğba Kevser; Zindancı, İlkin; Akdeniz, Necmettin
    A 21-year-old mentally challenged man presented with a fixed plaque lesion on the right foot, which had been present for 10 years. Dermatologic examination revealed an erythematous, painful, firm, fixed plaque-nodular lesion on the plantar aspect of the right foot (Figure 1A). Nothing of distinction was noted from his family history or his laboratory tests. An incisional biopsy revealed parallel, regular bundles composed of uniform, plump spindle cells. Thin collagen fibers were seen in contact with and located between the spindle cells. This mass was separated from the surrounding soft tissue by an irregular, unclear border (Figure 2A). İmmunohistochemically, the spindle cells showed diffuse, strong reactivity to vimentin (Figure 2B) and smooth muscle actin (Figure 2C). © 2017 Pulse Marketing & Communications, LLC.
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    Two-Layer Approach for Mixed High-Rate and Low-Rate Distributed Denial of Service (DDoS) Attack Detection and Filtering
    (Springer Heidelberg, 2018) Toklu, Sinan; Şimşek, Mehmet
    Distributed denial of service (DDoS) attacks are one of the most important attacks due to reducing the performance of computer networks nowadays. In recent years, the number of devices connected to the internet has been increasing. These devices are not only computers, but also objects of everyday use. The concept of internet has accelerated the increase considerably. Therefore, many problems arise in terms of DDoS attacks. One of them is low-rate DDoS attacks. While high-rate DDoS attacks are often performed with computers, low-rate DDoS attacks can be easily performed by computers and internet-connected objects. Therefore, effective defense mechanism against both attacks must be developed. In this study, new approaches are proposed to filter mixed high-rate DDoS and low-rate DDoS attacks. The ns-2 simulation tool was used to evaluate the performance of the proposed methods. Experimental results show that the proposed methods are successfully filtered mixed DDoS attacks.

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