Arsan, Taner

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Profile URL
https://hdl.handle.net/20.500.12469/6140
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
[email protected]
Main Affiliation
Computer Engineering
Status
Current Staff
Website
ORCID ID
0000-0002-4453-3218
Scopus Author ID
6506505859
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
AAB-2736-2019

Sustainable Development Goals

11

SUSTAINABLE CITIES AND COMMUNITIES
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5

Research Products

10

REDUCED INEQUALITIES
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0

Research Products

9

INDUSTRY, INNOVATION AND INFRASTRUCTURE
INDUSTRY, INNOVATION AND INFRASTRUCTURE Logo

1

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12

RESPONSIBLE CONSUMPTION AND PRODUCTION
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0

Research Products

2

ZERO HUNGER
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0

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3

GOOD HEALTH AND WELL-BEING
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4

Research Products

13

CLIMATE ACTION
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0

Research Products

7

AFFORDABLE AND CLEAN ENERGY
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2

Research Products

5

GENDER EQUALITY
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0

Research Products

6

CLEAN WATER AND SANITATION
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0

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8

DECENT WORK AND ECONOMIC GROWTH
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0

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16

PEACE, JUSTICE AND STRONG INSTITUTIONS
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0

Research Products

4

QUALITY EDUCATION
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0

Research Products

15

LIFE ON LAND
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1

Research Products

1

NO POVERTY
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0

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14

LIFE BELOW WATER
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0

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17

PARTNERSHIPS FOR THE GOALS
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3

Research Products
Documents

54

Citations

428

h-index

9

Go to Scopus profile
Documents

27

Citations

302

Go to WoS profile
Scholarly Output

77

Articles

24

Views / Downloads

103/0

Supervised MSc Theses

15

Supervised PhD Theses

0

WoS Citation Count

235

Scopus Citation Count

344

WoS h-index

7

Scopus h-index

8

Patents

0

Projects

0

WoS Citations per Publication

3.05

Scopus Citations per Publication

4.47

Open Access Source

30

Supervised Theses

15

JournalCount
2023 Innovations in Intelligent Systems and Applications Conference, ASYU 2023 -- 2023 Innovations in Intelligent Systems and Applications Conference, ASYU 2023 -- 11 October 2023 through 13 October 2023 -- Sivas -- 1941534
2024 Innovations in Intelligent Systems and Applications Conference, ASYU 2024 -- 2024 Innovations in Intelligent Systems and Applications Conference, ASYU 2024 -- 16 October 2024 through 18 October 2024 -- Ankara -- 2045623
Symmetry-Culture and Science2
31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023 -- 31st IEEE Conference on Signal Processing and Communications Applications, SIU 2023 -- 5 July 2023 through 8 July 2023 -- Istanbul -- 1920842
TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES2
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Scholarly Output Search Results

Now showing 1 - 10 of 77
  • Thumbnail Image
    Article
    Citation - WoS: 1
    Chaotic - Deterministic or Random Nature of Earthquakes: a Phase Space Analysis
    (Symmetrion, 2023) Pekcan, Onder; Arsan, Taner
    Using the phase space approach, time series analysis of high EV1 and low EV2 intense two different earthquakes that occurred at the nearly same precise spot, at different times, and were measured with the same sensor of a broadband station were studied. Time series data of strong, large (EV1) and weak, small (EV2) two earthquake events were analyzed by dividing them into three different regions. Fractal dimensions of the EV1 and EV2 were produced using the box-counting algorithm for east-west (BHE), north-south (BHN), and vertical (BHZ) components. The small, weak earthquake, EV2, created a larger fractal dimension in phase space by implying its random nature in all regions. However, EV1 is a strong, large earthquake that presents deterministic oscillatory behavior at a long-time region. Oscillatory behavior can be named surface wave. EV2 exhibits weak, high-frequency ground oscillations similar to fibrillation before and after the earthquake in the long-term areas.
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    Article
    Citation - WoS: 11
    Citation - Scopus: 10
    Early Steps in Automated Behavior Mapping via Indoor Sensors
    (MDPI, 2017) Arsan, Taner; Kepez, Orçun
    Behavior mapping (BM) is a spatial data collection technique in which the locational and behavioral information of a user is noted on a plan layout of the studied environment. Among many indoor positioning technologies we chose Wi-Fi BLE beacon and ultra-wide band (UWB) sensor technologies for their popularity and investigated their applicability in BM. We tested three technologies for error ranges and found an average error of 1.39 m for Wi-Fi in a 36 m(2) test area (6m x 6 m) 0.86 m for the BLE beacon in a 37.44 m(2) test area (9.6 m x 3.9 m) and 0.24 m for ultra-wide band sensors in a 36 m(2) test area (6 m x 6 m). We simulated the applicability of these error ranges for real-time locations by using a behavioral dataset collected from an active learning classroom. We used two UWB tags simultaneously by incorporating a custom-designed ceiling system in a new 39.76 m(2) test area (7.35 m x 5.41 m). We considered 26 observation points and collected data for 180 s for each point (total 4680) with an average error of 0.2072 m for 23 points inside the test area. Finally we demonstrated the use of ultra-wide band sensor technology for BM.
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    Article
    Integrating Stable Diffusion via Remote Server APIs for Enhanced Parametric Design Workflows
    (Sage Publications Ltd, 2026) Gokmen, Sabri; Alsan, Huseyin Fuat; Arsan, Taner; Ozen, Figen; Keskin, Ebru Ece
    The current advancements of deep learning models offer potential applications for computational design through sets of generated images controlled by parametric inputs, yet they remain disconnected from geometry-driven parametric tools. For this reason, we study the implications of text and image-based generation methods to be used in traditional parametric design procedures. We implement this study by integrating Stable Diffusion and ControlNet to Rhino Grasshopper through a Python-based remote-API plug-in. This API allows a direct connection to the diffusion-based image generation methods without any middleware. Our main contribution is to enable architects and designers to interactively generate and investigate new design ideas in their native parametric design environment. We evaluate potential impact on parametric design education with 15 architecture students using a single GPU server running Stable Diffusion v1.5 across three exercises: Text-to-Image, Image-to-Image using Rhinoceros view captures, and Parametric-Model-to-Image with ControlNet. Quantitative results showed that the API-enabled image generation averaged 4-15 seconds per image, allowing seamless integration with parametric workflows for all 15 students in a classroom setting. Performance evaluations show that our approach offers significantly improved efficiency and responsiveness compared to existing diffusion-based tools, highlighting its suitability for seamless integration within parametric design environments. Qualitative feedback indicated improved design ideation, greater fluency in prompt engineering, and enhanced understanding of parametric logic through iterative visual experimentation. These findings demonstrate the potential of real-time AI integration to augment both conceptual design and parametric design education.
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    Master Thesis
    Indoor positioning system development
    (Kadir Has Üniversitesi, 2015) Alp, Ebru; Dağ, Tamer; Arsan, Taner
    Nowadays, smartphone market penetration continues to grow with developing technology. Accordingly, position detection in closed areas has become an important research area. For instance; finding a direct route to the gate based on location at an airport, determining a route to the destination that could be a shop or cafe at a shopping center or informing about sales discount to increase sales using location are several applicable areas of position estimation. In the thesis, I developed triangulation algorithm more efficient using least square method with the developments of Wi-Fi channel fixing, optimized A and n values used in log normal formula and more than 3 access points. I used synthetic data which is created from sample data and estimate location for comparison to analyzing success rate of algorithm. According to the measurement results, triangulation algorithm with least square method, channel fixing, optimized A and n values, more than 3 Access Points gives accurate location in closed areas more than simple triangulation algorithm does. The thesis will lead to detect position in closed areas and use it in daily lives using triangulation algorithm with least square method.
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    Article
    Citation - Scopus: 2
    Trafik Verilerinde Genetik Algoritmalar ve Meta Optimizasyonla Güçlendirilmiş Exponential Smoothing Modeli ile Anomali Tespiti ve Performans Analizi
    (IEEE-Inst Electrical Electronics Engineers inc, 2025) Guler, Ali Kerem; Fuat Alsan, Huseyin; Arsan, Taner
    Bu çalışma, Numenta Anomaly Benchmark'ın (NAB) gerçek zamanlı trafik veri setleri üzerinde tahminleme yapan Third Order Exponential Smoothing modelinin parametrelerini optimize etmek amacıyla genetik algoritma kullanmaktadır. Ayrıca, genetik algoritma optimizasyon sürecini daha verimli hale getirmek için meta-optimizasyon tekniklerinden yararlanılarak anomali tespitindeki doğruluğu önemli ölçüde artıran yenilikçi bir yaklaşım sunmaktadır. Önerilen metodoloji, trafik yönetim sistemlerinde kritik olan veri akışlarındaki sapmaları tespit etmek için çeşitli trafik veri senaryolarına karşı farklı veri setleri üzerinde test edilmiştir. NAB'nin skorlama sistemini kullanarak yapılan karşılaştırmalı performans analizi, bu araştırmada geliştirilen yöntemin mevcut NAB algoritmalarının çoğundan üstün olduğunu ve NAB'nin önde gelen algoritmalarıyla rekabet edebildiğini göstermektedir. 'standart' için 54.32, 'reward_low_FP' için 53.73 ve 'reward_low_FN' için 69.54 skorları elde eden önerilen yaklaşım, sırasıyla NAB algoritmalarının ortalamasına göre %3.13, %2.70 ve %3.24 oranında bir iyileşme sağlamış, önemli bir gelişme kaydetmiştir. Bulgular, önerilen yaklaşımın sadece yüksek hassasiyetle anormallikleri tespit etmekle kalmayıp, aynı zamanda manuel yeniden kalibrasyon gerektirmeden değişen veri özelliklerine dinamik olarak uyum sağladığını göstermektedir. Bu çalışma, güvenilir izleme sağlayan ve potansiyel olarak etkin trafik yönetimi ve planlamayı kolaylaştıran sağlam bir trafik anomali tespit yöntemi önermektedir. Çalışmanın sonuçları, gerçek zamanlı veri izleme ve anormallik tespiti gerektiren diğer alanlara da genişletilebilir, farklı bağlamlar ve gereksinimlere uyum sağlayabilen ölçeklenebilir bir çözüm sunmaktadır.
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    Conference Object
    Citation - WoS: 7
    Big Data Platform Development With a Domain Specific Language for Telecom Industries
    (IEEE, 2013) Şenbalcı, Cüneyt; Altuntaş, Serkan; Bozkuş, Zeki; Arsan, Taner
    This paper introduces a system that offer a special big data analysis platform with Domain Specific Language for telecom industries. This platform has three main parts that suggests a new kind of domain specific system for processing and visualization of large data files for telecom organizations. These parts are Domain Specific Language (DSL) Parallel Processing/Analyzing Platform for Big Data and an Integrated Result Viewer. hi addition to these main parts Distributed File Descriptor (DFD) is designed for passing information between these modules and organizing communication. To find out benefits of this domain specific solution standard framework of big data concept is examined carefully. Big data concept has special infrastructure and tools to perform for data storing processing analyzing operations. This infrastructure can be grouped as four different parts these are infrastructure programming models high performance schema free databases and processing-analyzing. Although there are lots of advantages of Big Data concept it is still very difficult to manage these systems for many enterprises. Therefore this study suggest a new higher level language called as DSL which helps enterprises to process big data without writing any complex low level traditional parallel processing codes a new kind of result viewer and this paper also presents a Big Data solution system that is called Petaminer.
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    Review
    Citation - WoS: 106
    Citation - Scopus: 149
    Transducer Technologies for Biosensors and Their Wearable Applications
    (Mdpi, 2022) Polat, Emre Ozan; Cetin, M. Mustafa; Tabak, Ahmet Fatih; Bilget Guven, Ebru; Uysal, Bengu Ozugur; Arsan, Taner; Kabbani, Anas; Güven, Ebru Bilget; Gul, Sumeyye Berfin
    The development of new biosensor technologies and their active use as wearable devices have offered mobility and flexibility to conventional western medicine and personal fitness tracking. In the development of biosensors, transducers stand out as the main elements converting the signals sourced from a biological event into a detectable output. Combined with the suitable bio-receptors and the miniaturization of readout electronics, the functionality and design of the transducers play a key role in the construction of wearable devices for personal health control. Ever-growing research and industrial interest in new transducer technologies for point-of-care (POC) and wearable bio-detection have gained tremendous acceleration by the pandemic-induced digital health transformation. In this article, we provide a comprehensive review of transducers for biosensors and their wearable applications that empower users for the active tracking of biomarkers and personal health parameters.
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    Book Part
    C# Based Media Center
    (2013) Arsan, Taner; Sen, Rasim; Ersoy, Barkan; Devri, Kadir Kadirhan
    In this paper, we design and implement a novel all-in-one Media Center that can be directly connected to a high-definition television (HDTV). C# programming is used for developing modular structured media center for home entertainment. Therefore it is possible and easy to add new limitless number of modules and software components. The most importantly, user interface is designed by considering two important factors; simplicity and tidiness. Proposed media center provides opportunities to users to have an experience on listening to music/radio, watching TV, connecting to Internet, online Internet videos, editing videos, Internet connection to pharmacy on duty, checking weather conditions, song lyrics, CD/DVD burning, connecting to Wikipedia. All the modules and design steps are explained in details for user friendly cost effective all-in-one media center.
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    Conference Object
    Building Damage Assessment To Facilitate Post-Earthquake Search and Rescue Missions by Leveraging a Machine Learning Algorithm
    (Institute of Electrical and Electronics Engineers Inc., 2024) Zaker, M.; Alsan, H.F.; Arsan, T.
    Earthquakes have a severe impact on people's lives and infrastructure. Many emergency institutes and search and rescue missions need accurate post-earthquake response strategies, particularly in building damage assessment. Traditional methods, relying on manual inspections, are inefficient compared to Machine Learning (ML) algorithms. Thus, Random Forest (RF) algorithms stand out because they handle diverse datasets effectively and minimize overfitting. The study outlines the methodology encompassing data preparation, exploratory analysis, feature engineering, and model building, employing a preprocessing pipeline integrating numerical and categorical features. Additionally, Principal Component Analysis (PCA) is applied to reduce dimensionality. The results of the RF model showed an accuracy of 94% and the highest F1-score of 97% among all the grades, demonstrating its efficacy in predicting damage grades post-earthquake. The results can help support better disaster management plans by helping to prioritize rescue operations and allocate resources wisely. © 2024 IEEE.
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    Master Thesis
    Bandwidth Allocation and Traffic Shaping in Mobile Broadband Networks Using Deep Packet Inspection
    (Kadir Has Üniversitesi, 2015) Özbilen, Ramazan; Arsan, Taner
    In this thesis, it is intended to estimate bandwidth and control mobile data usage by utilizing PCC (Policy and Charging Control) function. According to increase in number of mobile devices, data explosion occurs. It is becoming a must to analyze traffic and sharing resources between subscribers according to their usage habits. It is aimed to provide better a better connected world with service assurance by sharing available bandwidth and estimate it to users according to their needs by protocol level and service based QoS. Due to increase in amount of services like Facebook, Twitter, Mobile TV, in general IP networks, providing service assurance becomes more important day by day. That's why the issue of controlling bandwidth is raised. In the most basic sense, system architecture consists of three main components: A cell phone to generate user based traffic, Gateway GPRS Support Node (GGSN) for Deep Packet Inspection (DPI), and Policy and Charging Rule Function (PCRF) for initiating PCC or Non-PCC rules to GGSN according to services that are needed by user. Shortly, the main idea in this thesis is assigning service based QoS to subscribers to provide better service assurance according to their usage. As thought, the reason of preparing this study is to show the dramatical increase in service based traffic, to explain insufficiency in current bandwidth estimation approaches, and the idea of what can be used in the work of providing better service assurance to an end user. PCRF is the best component for providing required bandwidth when they need.