Taner Arsan

Arsan, Taner

Name Variants

A., Taner
Taner Arsan
ARSAN, Taner
Arsan,Taner
Arsan, TANER
A.,Taner
Taner ARSAN
Arsan, Taner
Taner, Arsan
ARSAN, TANER
Arsan, T.
T. Arsan
TANER ARSAN
Arsan,T.
Arsan T.

Job Title

Doç. Dr.

Email Address

arsan@khas.edu.tr

ORCID ID

0000-0002-4453-3218

Scopus Author ID

6506505859

Full item page

Scholarly Output

63

Articles

18

Citation Count

140

Supervised Theses

12 Scholarly Output Search Results

Now showing 1 - 10 of 63

Citation Count: 0
Predictive Maintenance Analysis for Industries
(Institute of Electrical and Electronics Engineers Inc., 2024) Sunetcioglu,S.; Arsan,T.
In this paper, we are focused on deriving conclusions from sensor parameter data that would enable the detection of potential faults and the prediction of failures. We used Random Forest, Decision Tree, Naive Bayes, Logistic Regression, Support Vector Machine, and Long Short-Term Memory models to predict faults for sensor data. This analysis, which predicts the failure, has been examined through the pump sensor dataset from Kaggle. It is a binary classification problem, and it performs time series analysis using historical pump sensor data to predict future observations and classify them into a positive label (normal) or a negative label (broken). The pump system must be in perfect condition to ensure continuous power supply. A failure of one of the pumps in the system can lead to a temporary drop in power generation and even a complete outage. This may be avoided if failures are predicted in advance. Therefore, it is important to anticipate failure early to avoid large financial losses. Predictive maintenance is beneficial for industries to prevent these faults and losses. Despite expectations, the Random Forest algorithm outperforms LSTM, followed by Decision Trees. Support Vector Machine and Naive Bayes algorithms show inferior performance compared to Random Forest and LSTM. © 2024 IEEE.
Citation Count: 0
A Software Component Architecture for Adaptive and Predictive Rate Control of Video Streaming
(Springer, 2008) Arsan, Taner; Saydam, Tuncay
Quality of Service and Transmission Rate Optimization in live and on-demand video streaming is a very important issue in lossy IP networks. Infrastructure of the Internet exhibits variable bandwidths delays congestions and time-varying packet losses. Because of such attributes video streaming applications should not only have good end-to-end transport layer performance but also a robust rate control optimization mechanisms. This paper gives an overview of video streaming applications and proposal of a new software architecture that controls transport QoS and path and bandwidth estimation. Predictive Control is one of the best solutions for difficult problems in control engineering applications that can be used in Internet environment. Therefore we provide an end-to-end software architecture between the video requesting clients their destination servers distant streaming servers and video broadcasters. This architecture contains an important Streaming Server Component with Application Layer QoS Manager and Transport Layer Path and Bandwidth Estimator. QoS Manager considers the necessary parameters such as network delay packet loss distortions round trip time channel errors network discontinuity and session dropping probability to make video streaming more efficient and to provide required video quality. Transport Path and Bandwidth Estimator on the other hand provides transmission rates to Destination Servers for optimum video streaming. The paper provides and discusses a software component model of video streaming.
Citation Count: 2
Subchannel Allocation and Power Control for Uplink Femtocell Radio Networks With Imperfect Channel State Information
(Springer, 2019) Altabbaa, Mhd Tahssin; Arsan, Taner; Panayırcı, Erdal
Femtocell technology is emerging as a key solution for mobile operators for its advantage in coverage and capacity enhancement along with its cost effectiveness. However, densely and randomly deployed femtocells while sharing the frequency spectrum of the macrocell arises a severe interference environment. In femtocells deployment, interference coming from a femtocell user affect other femtocell users and the macrocell users, where maintaining the communication of the users in both tiers is a mandatory. In this paper, a novel power control algorithm is proposed for optimizing the uplink transmission powers of femtocell users in a TDD-OFDM communication model in the presence of a channel estimation error and intra-tier interference. We consider signal to interference and noise ratio as the objective function where the proposed constraints deal with: (1) the aggregated interference coming from femtocell tier and received at the active subchannels by the macrocell tier, and (2) the maximum uplink power a femtocell user equipment is allowed to occupy per admissible subchannel. Based on Lagrangian multipliers, the proposed power control approach grants the priority in subchannel usage for macrocell user, then it allows or prohibits frequency reuse of a subchannel with the femtocell tier. A comparison is then made with a pure isolation method that does not allow femtocell user equipments to occupy the active subchannels at the macrocell tier. The numerical results of the proposed approach show a high total rate of femtocell user equipments and the average uplink power is below the maximum allowable transmission power.
Citation Count: 0
An Integrated Software Architecture for Bandwidth Adaptive Video Streaming
(World Acad Sci Eng & Tech-Waset, 2008) Arsan, Taner
Video streaming over lossy IP networks is very important issues due to the heterogeneous structure of networks. Infrastructure of the Internet exhibits variable bandwidths delays congestions and time-varying packet losses. Because of variable attributes of the Internet video streaming applications should not only have a good end-to-end transport performance but also have a robust rate control furthermore multipath rate allocation mechanism. So for providing the video streaming service quality some other components such as Bandwidth Estimation and Adaptive Rate Controller should be taken into consideration. This paper gives an overview of video streaming concept and bandwidth estimation tools and then introduces special architectures for bandwidth adaptive video streaming. A bandwidth estimation algorithm - pathChirp Optimized Rate Controllers and Multipath Rate Allocation Algorithm are considered as all-in-one solution for video streaming problem. This solution is directed and optimized by a decision center which is designed for obtaining the maximum quality at the receiving side.
Citation Count: 29
Received Signal Strength Based Least Squares Lateration Algorithm for Indoor Localization
(Pergamon-Elsevier Science Ltd, 2018) Dağ, Tamer; Arsan, Taner
Following the success of accurate location estimation for outdoor environments locating targets in indoor environments has become an important research area. Accurate location estimation of targets for indoor environments has the potential for the development of many different applications such as public safety social networking information and mapping services. However the GPS (Global Positioning System) technology used for outdoor environments is not applicable to indoor environments making accurate location estimation a challenging issue for indoor environments. In this paper we propose a received signal strength based least squares lateration algorithm which uses the existing infrastructure. By employing redundancy in the number of access points and applying least squares approximations to the received signal strength values the lateration algorithm increases the accuracy of location estimations. The usage of the existing infrastructure makes the proposed algorithm low cost when compared to other positioning algorithms which need very precise high cost components. (C) 2017 Elsevier Ltd. All rights reserved.
Citation Count: 12
Smart Systems From Design To Implementation of Embedded Smart Systems
(IEEE, 2016) Arsan, Taner
This paper aims to explain the design and implementation procedure of embedded Smart Systems. The idea is supported by four different Smart Systems as Smart Home Smart Agriculture Smart Campus and Seat and Study Module of Smart Library. All designs and implementations contains technological components of embedded systems mobile application development cloud based services and client side graphical user interface. Ultimately this paper gives an overview of current state of the art concerning Smart System Design and discusses several issues and possibilities concerning the implementation of four different systems.
Citation Count: 0
A novel IPTV framework for automatic TV commercials detection, labeling, recognition and replacement
(Springer, 2023) Arsan, Taner; Bulut, Enes Emre; Eren, Berk; Uzgor, Ahmet; Yolcu, Selcuk
Advertisements are one of the most important way for companies to access their customers. In this context, televison commercials are gaining significant importance in many sectors daily, and it is crucial for companies to promote their products in the best way. This creates a big rivalry between companies. From this point of view, we have created an IPTV Framework that can automatically detect commercials of rival companies and replace them with desired commercials for companies to help them highlight their products to their customers. We have benefited from monochrome frames to detect the Livestream commercial block and proposed a fingerprint algorithm to create an automatic commercial database. We can easily recognize the commercials, and we can mask the commercials of rival companies with these techniques. We have tested our algorithm in real-time by streaming a recorded broadcast from a server of a specific TV channel. Experimental results show that our algorithm provides high accuracy in real-time commercial recognition.
Otomatik Varlık Getirisi Tahmini için Topluluk Öğrenme
(2024) Alnahas, Dima; Arsan, Taner
Bu tezin amacı, yeni tahmin modellerinin eğitimi, doğulanması ve test edilmesindeki zorlukları azaltılmış zaman maliyeti ve karmaşıklıkla ele alan bir makine öğrenimi operasyon mimarisi sağlamaktır. Bu mimari, birleştirme teknikleri yoluyla finansal zaman serisi tahmini için çeşitli tahmin modellerini bir araya getirmeye yönelik bir araç sağlar. Önerilen metodoloji, değişen ve ani piyasa davranışları için güvenilir bir tahmin üretmek amacıyla çoklu tahmin sonuçlarının entegrasyonunu araştırmaktadır. Bu mimarinin işlevselliği, Hareketli Ortalama Yakınsama Iraksama, Gizli Markov Modeli, Uzun Kısa Süreli Bellek ve Transformer modelleri gibi teknik analiz ve derin öğrenme teknikleri uygulanarak araştırılmaktadır. Bu çalışma, bu modellerin performansını üç farklı varlık sınıfı için incelemektedir.
Implementation of Pci-Dss V3.0 Information Security Standards
(Kadir Has Üniversitesi, 2015) Taşdemir, Özgür; Arsan, Taner
Way of doing business has changed with rapid spread of the internet and mobile devices and payment systems must keep up with that. Most of the monetary transactions are done electronically and percentage of internet trade is growing rapidly. information is being more important for companies and individuals when it comes to payment systems. Fraudulent transaction rates have been increased significantly with the positioning of payment systems in public networks such as the internet and Wi-Fi which brings along security breaches. information security requirements and raise of online payment card transactions together with payment card industry demands triggered the founding of PCi DSS information security standards. This thesis describes PCi DSS their requirements for compliancy and implementation of the standards to a company which have more than 2000 employee and stores processes and transmits payment card information.
Improving the Accuracy of Indoor Positioning System
(Kadir Has Üniversitesi, 2019) Hameez, Mohammed Muwafaq Noori; Arsan, Taner
Indoor positioning applications needs high accuracy and precision to overcome the existing obstacles and relatively small areas. There are several methods which could be used to locate an object or people in an indoor location. Specifically, Ultra-wide band (UWB) sensor technology is a promising technology in indoor environments because of its high accuracy, resistance of interference and better penetrating. This thesis is focused on improving the accuracy of UWB sensor based indoor positioning system. To achieve that, optimization and machine learning algorithms are implemented. The impact of Kalman Filter (KF) on the accuracy is introduced in the implementation of the algorithms. The average localization error is reduced by approximately 54.53% (from 16.34 cm to 7.43 cm), when combining the big bang - big crunch algorithm (BB-BC) with Kalman Filter. Finally, a Hybrid (BB-BC KF K-Means) algorithm is improved and implemented separately, and the best results are obtained from this Hybrid algorithm. Thus, it has been obtained that the average localization error is reduced significantly by approximately 64.26% (from 16.34 cm to 5.84 cm).