Browsing by Author "Arsan, Taner"

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Citation - WoS: 10
Citation - Scopus: 15
3d Indoor Positioning With Spatial Modulation for Visible Light Communications
(Elsevier, 2023) Sen, Umit; Yesilirmak, Yalin Evrim; Bayman, Irem Ozgur; Arsan, Taner; Panayırcı, Erdal; Stevens, Nobby
In this paper, a novel three-dimensional (3D) indoor visible light positioning (VLP) algorithm is proposed based on the spatial modulation (SM) and its error performance assessed as compared to the conventional received signal strength (RSS)-based 3D VLP systems. As contrasted to the traditional VLP system, the proposed SM-based 3D VLP system first estimates the optical channel gain between the transmitting light-emitting diodes (LEDs) and the two photo detectors (PDs) attached to the user by a pilot-based channel estimation technique. Then, unknown 3D positions of the receiver are determined by the trilateration algorithm with distances computed from the estimates of the channel gains. Consequently, the 3D VLP system achieves an interference -free transmission with increased spectral efficiency and without the need for a demultiplexing process at the receiving end. The algorithm's performance is evaluated regarding positioning error by applying the SM over four LEDs and the number of pilots selected as a function of the environmental signal-to-noise ratios (SNRs). The computer simulation results show that the positioning errors are obtained in an order of magnitude smaller than RSS-based techniques in an indoor industrial environment. This is mainly because the distances involved in determining the 3D positions can be determined more precisely by the pilot-aided channel estimation method without creating any data rate problem in transmission due to the higher spectral efficiency of the SM.
Citation - WoS: 4
Citation - Scopus: 8
Accurate Indoor Positioning With Ultra-Wide Band Sensors
(Tubitak, 2020) Arsan, Taner
Ultra-wide band is one of the emerging indoor positioning technologies. In the application phase, accuracy and interference are important criteria of indoor positioning systems. Not only the method used in positioning, but also the algorithms used in improving the accuracy is a key factor. In this paper, we tried to eliminate the effects of off-set and noise in the data of the ultra-wide band sensor-based indoor positioning system. For this purpose, optimization algorithms and filters have been applied to the raw data, and the accuracy has been improved. A test bed with the dimensions of 7.35 m x 5.41 m and 50 cm x 50 cm grids has been selected, and a total of 27,000 measurements have been collected from 180 test points. The average positioning error of this test bed is calculated as 16.34 cm. Then, several combinations of algorithms are applied to raw data. The combination of Big Bang-Big Crunch algorithm for optimization, and then the Kalman Filter have yielded the most accurate results. Briefly, the average positioning error has been reduced from 16.34 cm to 7.43 cm.
Citation - WoS: 1
Citation - Scopus: 2
Analytical Expense Management System
(IEEE, 2009) Bozkuş, Zeki; Bisson, Christophe; Arsan, Taner
Although the development of communication technologies (e.g: UMTS ADSL) allowed the elaboration of multiple users' web applications (e.g. information storage) there are still many improvements on many applications to be done and uncovered areas. Expense management systems on web application area are still in their infancy. Expense management software is widely spread in companies and most of time supported by their intranet. These solutions are quite simple as they mainly collect the information related to the expenses and may propose a simple aggregation of these figures. The result is close to what an excel sheet provides.
Audience Tracking and Cheering Content Control in Sports Events
(IEEE, 2020) Yeşilyurt, Gözdenur; Dursun, Sefa; Kumas, Osman; Çakir, Nagehan; Arsan, Taner
Swearing cheers encountered in sports competitions do not comply with sports ethics and morals. Even if this kind of cheering is a group, the entire tribune block is penalized in accordance with the current rules. This method is not preventive and individual punishment should be used. The aim of this study is to determine the individuals who cheer with swearing content. In this study, the person detection is made with the multi-task cascaded convolutional neural network. Moreover, facial landmarks representing the facial regions and the regions related to them are determined as a result of this process. The mouth region is also determined by means of these important points removed, and finally the mouth is determined according to the equation. The face recognition is carried out because the person would be in a state of yelling if the mouth opening ratio exceeds the threshold value by determining the rate of opening. Landmarks extracted from the facial regions for the face recognition are transformed into feature vectors by FaceNet, and the model is created by classifying these vectors with classifiers to use in recognition process. When evaluated in terms of industry, face recognition and detection systems find a wide field of study.
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.
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.
Büyük Patlama – Büyük Çöküş Optimizasyon Yöntemi Kullanılarak Bluetooth Tabanlı İç Mekan Konum Belirleme Sisteminin Doğruluğunun İyileştirilmesi
(Süleyman Demirel Üniversitesi, 2018) Arsan, Taner
Düşük enerjili Bluetooth işaretçi (Bluetooth low energy - BLE beacon) teknolojisi, iç mekan konum belirleme sistemlerinde başarılı ve düşük maliyetli çözümler sunan gelişmekte olan bir teknolojidir. Bu çalışmada, BLE işaretçileri (beacons) kullanan bir iç mekan konum belirleme sistemi geliştirilmiş, kullanılan ilave algoritmalarla standart sensörlerden elde edilen konum değerlerinin doğruluğunun artırılması amaçlanmıştır. Bunun için, deneysel iç mekan konum algılama sisteminden elde edilen konum bilgilerine Büyük Patlama – Büyük Çöküş (Big Bang – Big Crunch (BB-BC)) optimizasyon yöntemi uygulanmış ve konum doğruluğunun geliştirildiği yapılan testlerle kanıtlanmıştır. Test alanı olarak, 9,60 m × 3,90 m boyutundaki 37,44 m2'lik alan seçilmiş ve 2,40 m × 1,30 m boyutundaki oniki tane ızgara alanına ayak izi (fingerprinting) algoritması uygulanmıştır. Test alanına dört tane BLE işaretçi (beacon) yerleştirilmiş, on iki test alanından 150 saniye boyunca toplam 9.000 ölçüm yapılmıştır. Ölçüm sonuçları Büyük Patlama – Büyük Çöküş optimizasyon yöntemi ile Öklid uzaklık eşleştirme yöntemi ve Kalman Filtresi kullanılarak iyileştirilmiş, bu sayede konum doğruluğu %26,62'den %75,69'a arttırılmıştır.
Büyük Patlama Büyük Çöküş Optimizasyon Yöntemi ile Ultra Geniş Band Sensörlerinin İç Mekân Konum Belirleme Doğruluklarının İyileştirilmesi
(Pamukkale Üniversitesi, 2018) Arsan, Taner
Ultra geniş band teknolojisi, birçok iç mekân konum belirleme sisteminde başarılı çözümler sunan, diğer yöntemlere kıyasla daha iyi performans gösteren, gelişmekte olan bir teknolojidir. Bu çalışmada, ultra geniş band (Ultra Wide Band-UWB) sensörler kullanılarak bir iç mekân konum belirleme sistemi geliştirilmiş ve kullanılan ek algoritmalarla, standart donanımların sağladığı doğruluk düzeyi arttırılırken aynı zamanda ortalama hatayı azaltmak hedeflenmiştir. Bu amaçla Büyük Patlama - Büyük Çöküş (Big Bang-Big Crunch veya BB-BC) optimizasyon yöntemi deneysel iç mekân konumlandırma sistemine uygulanmış ve ölçüm doğruluğu üzerindeki olumlu etkisi yapılan testlerle kanıtlanmıştır. Test alanı olarak 7.35 m × 5.41 m boyutlarında 39.76 m2 'lik bir alan seçilmiş ve özel olarak tasarlanmış bir tavan sistemine yerden 2.85 m yüksekliğe üç farklı UWB alıcı yerleştirilmiş ve 182 adet test noktasından 60 sn.süreyle toplam 10.920 ölçüm alınmıştır. Ölçüm sonuçları Büyük Patlama - Büyük Çöküş optimizasyon algoritması ile düzeltilerek, ortalama hatası önceki 20.72 cm değerinden 15.02 cm’ye düşürülmüş, böylelikle ölçüm sonuçlarının doğruluğu arttırılmıştır.
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.
Career Center System Software Architecture
(Springer Verlag, 2015) Arsan, Taner; Çimenli, Safa; Güneş, Erhan
In today’s world, thousands of job seekers are looking for a new job. On the other hand, thousands of employers are trying to find new employees. So, this is a chaotic matching problem and it does not have a certain answer. Companies are searching career centers and web-based career software to find an answer for the question of “”Should we find a convenient worker for a certain role and hire this person or not?” Solution is that simple; just have a look at the beginning of the story: university career centers. In this study, a Career Center System Software has been designed and implemented for matching students with their ideal job. Career Center System Software (CCSS) is programmed on C#, MS-SQL and.NET platform. CCSS has been developed on Visual Studio 2010. CCSS is implemented in a way so as to enable the user to apply for the job announcements and to monitor courses and to call for conferences and seminars. Furthermore, CCSS enables companies to view the applicant’s curriculum vitae. All job announcements, educations, seminars and CVs are stored on the database. Software quality and testing shows that CCSS is implemented successfully and ready to use tool as Career Center Software.
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.
Churn Analysis and Prediction With Decision Tree and Artificial Neural Network
(Kadir Has Üniversitesi, 2015) Çimenli, Safa; Arsan, Taner
Nowadays market competition is increased in logistic sector. Retention of customers due to the competition has gained importance. Retention of customers is more advantageous than gaining new customers. Gaining new customer has 5 units more than retention of existing customer. Especially telecommunication companies use churn analyzing and prediction. However competition increased in different sectors and they need churn analysis. In recent years logistic companies increased in Turkey, so retention of customer and churn analysis are important for logistic companies. Some logistic companies have churn committees and work on customer loyalty. This article includes churn analysis and prediction with decision tree and artificial neural network. In addition, this article includes comparison of 2 different methods for churn analysis. Article results show neural network better than decision for prediction. Because decision tree churn prediction rate is %81, Artificial Neural Networks rate is 97%.
Classification of Heart Diseases With Convolutional Neural Networks
(Kadir Has Üniversitesi, 2021) Koç, Bekir Yavuz; Arsan, Taner
Günümüzde kalp hastalıklarının sayısı ve sıklığı artmaktadır. Bu alanda iyileştirmeler yapılabilmesi için yüksek miktarda harcama yapılmaktadır. Kalbin elektriksel iletimindeki atımlar özel cihazlarla kaydedilebilir ve EKG (Elektrokardiyogram) oluşturulabilir. EKG'den üretilen veriler, Taylor Series algoritması ile faz uzaylarına dönüştürülebilir. Kalp hastalığının tespiti için 44 farklı kişiden alınan verilerle MLII sinyallerinden EKG ve faz uzayları oluşturuldu. Bu kayıtların kalp durumunu belirlemek için hem EKG görüntüleri hem de faz uzayı görüntüleri kullanıldı. Kayıtların kalp durumu görüntülere ve sonuçlara Convolutional Neural Networks (CNNs) yöntemi uygulandı ve SVM (Support Vector Machine) algoritması ile karşılaştırılarak başarı oranı ölçüldü. Ayrıca aynı kayıtlar üzerinden eğitim ve test seti değiştirilerek farklı modellerin başarı oranları karşılaştırıldı. EKG ile faz uzayı görüntülerine CNN algoritmasının verdiği sonuçlardaki farklılık tespit edildi. Nowadays, the number and frequency of heart diseases is increasing. High amounts of expenses are incurred in order to make improvements in this area. The beats in the electrical conduction of the heart can be recorded by special devices and ECG (Electrocardiogram) can be created. Data generated from ECG can be transformed into phase spaces with Taylor Series algorithm. In order to determine the detection of heart disease, ECG and phase spaces were created from MLII signals based on 44 different records. Both ECG images and phase space images were used to determine the heart conditions of these recordings. The heart status of the recordings was measured by applying Convolutional Neural Networks (CNNs) method to the images and results compared with the SVM (Support Vector Machine) algorithm. In addition, the success rates of different models were compared by changing the training and test set over the same records. The success rate between ECG and phase space was also determined.
Citation - WoS: 12
Citation - Scopus: 16
A Clustering-Based Approach for Improving the Accuracy of Uwb Sensor-Based Indoor Positioning System
(Hindawi LTD, 2019) Arsan, Taner; Hameez, Mohammed Muwafaq Noori
There are several methods which can be used to locate an object or people in an indoor location. Ultra-wideband (UWB) is a specifically promising indoor positioning technology because of its high accuracy, resistance to interference, and better penetration. This study aims to improve the accuracy of the UWB sensor-based indoor positioning system. To achieve that, the proposed system is trained by using the K-means algorithm with an additional average silhouette method. This helps us to define the optimal number of clusters to be used by the K-means algorithm based on the value of the silhouette coefficient. Fuzzy c-means and mean shift algorithms are added for comparison purposes. This paper also introduces the impact of the Kalman filter while using the measured UWB test points as an input for the Kalman filter in order to obtain a better estimation of the position. As a result, the average localization error is reduced by 43.26% (from 16.3442 cm to 9.2745 cm) when combining the K-means algorithm with the Kalman filter in which the Kalman-filtered UWB-measured test points are used as an input for the proposed system.
Dynamic Load Balancing in Distributed Systems: “hands of God” in Parallel Programming With Mpi
(Kadir Has Üniversitesi, 2014) Tabrizi, Aliakbar Sadeghi Khameneh; Arsan, Taner
in today’s technology what really is missing in computer systems is more artificial intelligence and in the same time implanting lots of intelligence in computer systems is not as easy as it sounds but even one step ahead to make computer software to act more efficient and intelligent is noteworthy. MPiCH is a message passing interface framework designed to be the host for parallel programs but like too many other great programming frameworks development of MPiCH is ongoing and once a while we are witnessing new updates which mostly these updates are in order to support more functionality and performance improvement updates are more rare. One of the issues that happened while we were working on Snake in the box problem (more details on this problem could be found in Wikipedia) with my parallel programming Professor Dr Turgay Altilar in Kadir Has University was lack of intelligence in the parallel version of the algorithm of Snake in the box in MPiCH framework. -- Abstract'tan.
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.
Endüstriler için Öngörücü Bakım Analizi
(2023) Sünetçioğlu, Selin; Arsan, Taner
Bu çalışma Rastgele Orman, Karar Ağacı, Naive Bayes, Lojistik Regresyon, Destek Vektör Makinesi ve Uzun Kısa Süreli Bellek algoritmalarını kullanarak sensör verilerine yönelik hataları tahmin etmeyi amaçlamaktadır. Proje, olası hataları tespit edebilme ve sensör verilerini kullanarak arızaları tahmin edebilecek şekilde sensör parametreleri verilerinden sonuçlar çıkarmaya odaklandı. Arızayı öngören bu analiz, Kaggle'ın pompa sensörü veri seti aracılığıyla incelenmiştir. Bu bir ikili sınıflandırma problemidir ve gelecekteki gözlemleri tahmin etmek ve bunları pozitif bir etiket (normal) veya negatif bir etiket (broken) olarak sınıflandırmak için geçmiş pompa sensörü verilerini kullanarak zaman serisi analizi gerçekleştirir. Bir enerji santralinde çok sayıda pompa sistemi bulunur. Bunlar enerji üretiminin ana kaynaklarıdır. Sürekli güç beslemesini sağlamak için pompa sistemi mükemmel durumda tutulmalıdır. Sistemdeki pompalardan birinin arızalanması, elektrik üretiminde geçici bir düşüşe ve hatta tamamen kesintiye neden olabilir. Arızaların önceden öngörülmesi durumunda bu durum önlenebilir. Bu nedenle, büyük mali kayıpları önlemek için başarısızlığı erken tahmin etmek önemlidir. Bu nedenle bu tez, pompa sensörlerindeki kestirimci bakıma odaklanmıştır. Ayrıca amaç, en iyi algoritmayı seçmek için algoritmaların performansının karşılaştırılmasıdır. Kestirimci bakım, endüstrilerin bu hataları önlemesinde faydalıdır.
Citation - Scopus: 5
Fast Multi-View Face Trackingwith Pose Estimation
(2008) Meynet, Julien; Arsan, Taner; Mota, Javier Cruz; Thiran, Jean-Philippe Philippe H.
In this paper a fast and an effective multi-view face tracking algorithm with head pose estimation is introduced. For modeling the face pose we employ a tree of boosted classifiers built using either Haar-like filters or Gauss filters. A first classifier extracts faces of any pose from the background. Then more specific classifiers discriminate between different poses. The tree of classifiers is trained by hierarchically sub-sampling the pose space. Finally Condensation algorithm is used for tracking the faces. Experiments show large improvements in terms of detection rate and processing speed compared to state-of-the-art algorithms.
Citation - WoS: 1
Citation - Scopus: 1
Flex: a Modular Software Architecture for Flight License Exam
(Springer-Verlag Berlin, 2010) Arsan, Taner; Saka, Hamit Emre; Şahin, Ceyhun
This paper is about the design and implementation of an examination system based on World Wide Web. It is called FLEX-Flight License Exam Software. We designed and implemented flexible and modular software architecture. The implemented system has basic specifications such as appending questions in system building exams with these appended questions and making students to take these exams. There are three different types of users with different authorizations. These are system administrator operators and students. System administrator operates and maintains the system and also audits the system integrity. The system administrator can not be able to change the result of exams and can not take an exam. Operator module includes instructors. Operators have some privileges such as preparing exams entering questions changing the existing questions and etc. Students can log on the system and can be accessed to exams by a certain URL. The other characteristic of our system is that operators and system administrator are not able to delete questions due to the security problems. Exam questions can be inserted on their topics and lectures in the database. Thus
Fractal Analysis of Cardiac Spectra
(Symmetrion, 2024) Pekcan, Onder; Arsan, Taner
Cardiac diseases are one of the main reasons for mortality in modern, industrialized societies, and they cause high expenses in public health systems. Therefore, it is important to develop analytical methods to improve cardiac diagnostics. The heart's electric activity was first modeled using a set of nonlinear differential equations. Variations of cardiac spectra originating from deterministic dynamics are investigated. Analyzing the power spectra of a normal human heart presents the His-Purkinje network, which possesses a fractal-like structure. Phase space trajectories are extracted from the time series graph of ECG. Lower values of fractal dimension, D, indicate dynamics that are more coherent. If D has non-integer values greater than two when the system becomes chaotic or strange attractor. Recently, the development of a fast and robust method, that can be applied to multichannel physiologic signals, was reported. The convolutional Neural Networks (CNNs) method was also applied to patient-specific ECG classification for real-time heart monitoring. This manuscript investigates two different ECG systems produced from normal and abnormal human hearts to introduce an auxiliary phase space method in conjunction with ECG signals for diagnosing heart diseases. Here, the data for each person includes two signals based on V(4 )and modified lead III (MLIII), respectively. The fractal analysis method is employed on the trajectories constructed in phase space, from which the fractal dimension D is obtained using the box-counting method. It is observed that, the second signals (i.e., MLIII) have larger D values than the first signals (i.e., V-4), predicting more randomness yet more information. The lowest value of D (i.e., 1.708) indicates the perfect oscillation of the normal heart, and the highest value of D (i.e., 1.863) presents the abnormal heart's randomness. Our significant finding is that the phase space picture presents the distribution of the peak heights from the ECG spectra, giving valuable information about heart activities in conjunction with ECG.