Computer Engineering Commons^™

Community Detection In Complex Networks Using A New Agglomerative Approach, Majid Arasteh, Somayeh Alizadeh

Turkish Journal of Electrical Engineering and Computer Sciences

Complex networks are used for the representation of complex systems such as social networks. Graph analysis comprises various tools such as community detection algorithms to uncover hidden data. Community detection aims to detect similar subgroups of networks that have tight interconnections with each other while, there is a sparse connection among different subgroups. In this paper, a greedy and agglomerative approach is proposed to detect communities. The proposed method is fast and often detects high-quality communities. The suggested method has several steps. In the first step, each node is assigned to a separated community. In the second step, a vertex …

Speech Emotion Recognition Using Semi-Nmf Feature Optimization, Surekha Reddy Bandela, T Kishore Kumar

Turkish Journal of Electrical Engineering and Computer Sciences

In recent times, much research is progressing forward in the field of speech emotion recognition (SER). Many SER systems have been developed by combining different speech features to improve their performances. As a result, the complexity of the classifier increases to train this huge feature set. Additionally, some of the features could be irrelevant in emotion detection and this leads to a decrease in the emotion recognition accuracy. To overcome this drawback, feature optimization can be performed on the feature sets to obtain the most desirable emotional feature set before classifying the features. In this paper, semi-nonnegative matrix factorization (semi-NMF) …

Scale-Invariant Mfccs For Speech/Speaker Recognition, Zekeri̇ya Tüfekci̇, Gökay Di̇şken

Turkish Journal of Electrical Engineering and Computer Sciences

The feature extraction process is a fundamental part of speech processing. Mel frequency cepstral coefficients (MFCCs) are the most commonly used feature types in the speech/speaker recognition literature. However, the MFCC framework may face numerical issues or dynamic range problems, which decreases their performance. A practical solution to these problems is adding a constant to filter-bank magnitudes before log compression, thus violating the scale-invariant property. In this work, a magnitude normalization and a multiplication constant are introduced to make the MFCCs scale-invariant and to avoid dynamic range expansion of nonspeech frames. Speaker verification experiments are conducted to show the effectiveness …

A Novel Randomized Recurrent Artificial Neural Network Approach: Recurrent Random Vector Functional Link Network, Ömer Faruk Ertuğrul

Turkish Journal of Electrical Engineering and Computer Sciences

The random vector functional link (RVFL) has successfully been employed in many applications since 1989. RVFL has a single hidden layer feedforward structure that also has direct links between the input layer and the output layer. Although nonlinearity, high generalization capacity, and fast training ability can be provided in RVFL, it can be found from the literature that higher nonlinearity can be obtained by adding recurrent feedback to an artificial neural network. In this paper, the recurrent type of RVFL (R-RVFL), which has both outer feedbacks and also inner feedbacks, is proposed. In order to evaluate and validate the proposed …

A Fine-Grain And Scalable Set-Based Cache Partitioning Through Thread Classification, İsa Ahmet Güney, Gürhan Küçük

Turkish Journal of Electrical Engineering and Computer Sciences

As contemporary processors utilize more and more cores, cache partitioning algorithms tend to preserve cache associativity with a finer-grain of control to achieve higher throughput and fairness goals. In this study, we propose a scalable set-based cache partitioning mechanism, which welds an allocation policy and an enforcement scheme together. We also propose a set-based classifier to better allocate partitions to more deserving threads, a fast set redirection logic to map accesses to dedicated cache sets, and a double access mechanism to overcome the performance penalty due to a repartitioning phase. We compare our work to the best line-grain cache partitioning …

An Optimized Harmonic Elimination Method Based On Synchronized Microcontroller Architecture, Vivek Gopinath, Meenu Nair, Jayanta Biswas, Mukti Barai

Turkish Journal of Electrical Engineering and Computer Sciences

This paper proposes an optimized synchronous PWM method for harmonic elimination in a quasi square wave inverter. The synchronized PWM method enables online harmonic computation and PWM pulse generation in a multitasking digital controller to eliminate lower order harmonics. The multitasking digital controller reduces the look-up table requirement and helps in realizing efficient implementation to eliminate dominant harmonics. This method offers a simple scalable solution for combined fifth and seventh harmonic elimination using two low-cost eight-bit PIC microcontrollers (PIC18F4550, PIC18F452). Experimental results are demonstrated for a single-phase three-level inverter. The proposed method achieves 90$\% $ reduction of fifth and seventh …

High-Efficiency Design Of A Grid-Connected Pv Inverter Based On Interleaved Flyback Converter Topology, Bünyami̇n Tamyürek, Bi̇lgehan Kirimer

Turkish Journal of Electrical Engineering and Computer Sciences

The importance of efficiency in photovoltaic (PV) inverter applications makes the topology selection as the critical first step. Due to the low efficiency concern, flyback converter is not the preferred topology in kilowatt range in spite of its galvanic isolation, low cost, and small size advantages. Therefore, the objective of this research is to change the perception in favor of flyback converter by designing a flyback-topology-based PV inverter at 2.5 kW with high efficiency. The enhancement in efficiency is achieved mainly by using silicon carbide switching devices, designing ultrahigh-efficiency flyback transformers with extremely low leakage inductance and by implementing a …

Mobility And Traffic-Aware Resource Scheduling For Downlink Transmissions In Lte-A Systems, Önem Yildiz, Radosveta İvanova Sokullu

Turkish Journal of Electrical Engineering and Computer Sciences

As new cellular networks support not only voice services but also many multimedia applications, the requirements for reliable data transmission at high speeds create heavy load on the system. Even though LTE/LTE-A technology takes action towards alleviating this load, it is still necessary to manage resources effectively because of the inadequacy of the available radio resources. Thus, the scheduler at the MAC layer of the base station plays a very important role in resource allocation to the user. In this study a novel algorithm for resource allocation in mobile environments is presented, with two variations addressing different input traffic. The …

A Beaconing-Based Roadside Services Discovery Protocol For Vehicular Ad Hoc Networks, Kifayat Ullah, Ali Sayyed, Muhammad Aziz, Edson Moreira

Turkish Journal of Electrical Engineering and Computer Sciences

Recently, research on vehicular ad hoc networks (VANETs) has gained momentum all over the world. These emerging networks promise to make our driving experience more efficient, safer, comfortable, and enjoyable. VANETs have the potential to support a wide range of interesting applications. One such promising application area is the discovery of roadside services on the highways. Drivers need an efficient way to find these services during their journeys. However, due to the unique features of VANETs, the design and implementation of such applications is a challenging task. In this paper, we propose an application layer beaconing-based roadside services discovery protocol …

Energy And Economic Assessment Of Major Free Cooling Retrofits For Data Centers In Turkey, Ozan Gözcü, Hamza Sali̇h Erden

Turkish Journal of Electrical Engineering and Computer Sciences

Mechanical cooling is responsible for a significant fraction of the energy consumption of data centers (DCs). Free cooling systems take advantage of ambient conditions to reduce the need for compressor-based cooling. This study utilizes thermodynamic models of major free cooling systems such as the direct air-side economizer (ASE), indirect air-side economizer (IASE), indirect evaporative cooler (IEC), and indirect water-side economizer (WSE) integrated with the existing cooling infrastructure of a typical 1 MW IT load DC. Proposed models utilize hourly weather data of various cities in Turkey to compute annual energy consumption and cost-saving potentials of each free cooling method with …

An Adaptive Scheduling Scheme For Inhomogeneously Distributed Wireless Ad Hocnetworks, Adnan Fazil, Aamir Hasan, Muhammad Atique Ur Rehman, Ijaz Mansoor Qureshi

Turkish Journal of Electrical Engineering and Computer Sciences

An efficient scheduling strategy guarantees the simultaneous transmission and successful reception by the scheduled nodes even inside a congested wireless ad hoc network. Owing to the dispersed nature of ad hoc networks, the node packing algorithm needs to be implementable without having network-wide channel state information and should additionally be able to pack the optimum number of successful transmissions. The proposed algorithm, for a network with nonhomogeneously distributed nodes, makes the decision to either inhibit or permit an active interferer around an active receiver based on the interferer?s transmission power. The analysis evidenced that the suggested scheme provides an estimated …

Qpsk-Dual Carrier Modulation For Ultra-Wideband Communication In Body Areanetwork Channels, Yasi̇n Karan, Sali̇m Kahveci̇

Turkish Journal of Electrical Engineering and Computer Sciences

Dual carrier modulation (DCM) using orthogonal frequency-division multiplexing (OFDM) improves the performance in multipath fading channels. In the literature DCM is proposed with 16-quadrature amplitude modulation (16QAM) for ultra-wideband (UWB) communication, with four bits per symbol to keep reliable high date transmission over longer distances. Body area network (BAN) standards address transmission reliability more than data rate. UWB is one of the physical layers proposed in BAN standards. In this study, DCM is used with quadrature phase shift keying (QPSK) instead of 16QAM to have better performance in reliable transmission. The performance of QPSK-DCM is analyzed and compared with 16QAM-DCM, …

Optimized Modeling Of Ni-Mh Batteries Primarily Based On Taguchi Approach And Evaluation Of Used Ni-Mh Batteries, Hani Muhsen, Ahmad Al-Muhtady

Turkish Journal of Electrical Engineering and Computer Sciences

This paper aims to generate an optimized model of the Ni-MH battery based on the Taguchi method and it further aims to evaluate used Ni-MH batteries that served in hybrid electric vehicles and electric vehicles. The status of twelve used Ni-MH batteries is studied to determine their usefulness after their life cycle in automotive applications. The status of used batteries is evaluated by investigating their state of charge, remaining useful life, and degradation in performance. Accordingly, the tested batteries are classified into four categories and they are proposed to serve in different applications. The novelty of the work lies in …

Determination Of Distance Between Dc Traction Power Centers In A 1500-V Dc Subway Line With Artificial Intelligence Methods, Mehmet Taci̇ddi̇n Akçay, İlhan Kocaarslan

Turkish Journal of Electrical Engineering and Computer Sciences

The electrification system in rail systems is designed with regard to the operating data and design parameters. While the electrification system is formed, the minimum voltage rating that the traction force requires during the operation needs to be provided. The highest value of the voltage drop occurring on the line is determined by the distance between power centers. This value needs to be kept within certain limits for the continuity of operation. In this study, the determination of the distance between DC traction power centers for a 1500-V DC-fed rail system is done by means of the adaptive neuro-fuzzy inference …

Fuzzy-Logic-Based Robust Speed Control Of Switched Reluctance Motor For Low And High Speeds, Zeki̇ Omaç

Turkish Journal of Electrical Engineering and Computer Sciences

Switched reluctance motor (SRM) is operated at high magnetic saturation to generate large torque. The flux linkage of SRM is a nonlinear function with phase current and rotor position because of the high magnetic saturation. Also, the performance of the speed controller for the SRM driver system can be negatively affected by noise, disturbances, and inertia of load torque. Therefore, the fuzzy speed controller for the SRM driver system was developed in this study. In addition, a dynamic model of SRM was simulated in Matlab/Simulink software. Based on the results obtained in this study, the speed of the SRM was …

Fitting A Recurrent Dynamical Neural Network To Neural Spiking Data: Tackling The Sigmoidal Gain Function Issues, Reşat Özgür Doruk

Turkish Journal of Electrical Engineering and Computer Sciences

This is a continuation of a recent study (Doruk RO, Zhang K. Fitting of dynamic recurrent neural network models to sensory stimulus-response data. J Biol Phys 2018; 44: 449-469), where a continuous time dynamical recurrent neural network is fitted to neural spiking data. In this research, we address the issues arising from the inclusion of sigmoidal gain function parameters to the estimation algorithm. The neural spiking data will be obtained from the same model as that of Doruk and Zhang, but we propose a different model for identification. This will also be a continuous time recurrent neural network, but with …

Turkish Lexicon Expansion By Using Finite State Automata, Mustafa Burak Öztürk, Burcu Can Buğlalilar

Turkish Journal of Electrical Engineering and Computer Sciences

Turkish is an agglutinative language with rich morphology. A Turkish verb can have thousands of different word forms. Therefore, sparsity becomes an issue in many Turkish natural language processing (NLP) applications. This article presents a model for Turkish lexicon expansion. We aimed to expand the lexicon by using a morphological segmentation system by reversing the segmentation task into a generation task. Our model uses finite-state automata (FSA) to incorporate orthographic features and morphotactic rules. We extracted orthographic features by capturing phonological operations that are applied to words whenever a suffix is added. Each FSA state corresponds to either a stem …

Robust Compressed Domain Watermarking Algorithm For Video Protection And Authentication In Noisy Channels, Naveen Cheggoju, Vishal Satpute

Turkish Journal of Electrical Engineering and Computer Sciences

This paper introduces a robust and noise-resilient compressed domain video watermarking technique for data authentication and copyright protection. In recent years, watermarking has emerged as an essential technique to be equipped with data transmission. The main challenge pertaining to transmission is to protect the watermark from noise introduced by the channel. Here, we address this issue by watermark replication and by using the independent pass coding (INPAC) algorithm for compression. A replicated watermark is embedded into the video by the proposed blind video watermarking algorithm and then the watermarked video is compressed by the INPAC algorithm. The compressed video is …

Speech Enhancement Using Adaptive Thresholding Based On Gamma Distribution Of Teager Energy Operated Intrinsic Mode Functions, Özkan Arslan, Erkan Zeki̇ Engi̇n

Turkish Journal of Electrical Engineering and Computer Sciences

This paper introduces a new speech enhancement algorithm based on the adaptive threshold of intrinsic mode functions (IMFs) of noisy signal frames extracted by empirical mode decomposition. Adaptive threshold values are estimated by using the gamma statistical model of Teager energy operated IMFs of noisy speech and estimated noise based on symmetric Kullback--Leibler divergence. The enhanced speech signal is obtained by a semisoft thresholding function, which is utilized by threshold IMF coefficients of noisy speech. The method is tested on the NOIZEUS speech database and the proposed method is compared with wavelet-shrinkage and EMD-shrinkage methods in terms of segmental SNR …

A Novel Hybrid Teaching-Learning-Based Optimization Algorithm For The Classification Of Data By Using Extreme Learning Machines, Ender Sevi̇nç, Tansel Dökeroğlu

Turkish Journal of Electrical Engineering and Computer Sciences

Data classification is the process of organizing data by relevant categories. In this way, the data can be understood and used more efficiently by scientists. Numerous studies have been proposed in the literature for the problem of data classification. However, with recently introduced metaheuristics, it has continued to be riveting to revisit this classical problem and investigate the efficiency of new techniques. Teaching-learning-based optimization (TLBO) is a recent metaheuristic that has been reported to be very effective for combinatorial optimization problems. In this study, we propose a novel hybrid TLBO algorithm with extreme learning machines (ELM) for the solution of …

Mediaeval2019: Flood Detection In Time Sequence Satellite Images, Palavi Jain, Bianca Schoen-Phelan, Robert J. Ross

Conference papers

In this work, we present a flood detection technique from time series satellite images for the City-centered satellite sequences (CCSS) task in the MediaEval 2019 competition [1]. This work utilises a three channel feature indexing technique [13] along with a VGG16 pretrained model for automatic detection of floods. We also compared our result with RGB images and a modified NDWI technique by Mishra et al, 2015 [15]. The result shows that the three channel feature indexing technique performed the best with VGG16 and is a promising approach to detect floods from time series satellite images.

Comprehending The Safety Paradox And Privacy Concerns With Medical Device Remote Patient Monitoring, Marc Doyle

CCAC Theses and Dissertations

Medical literature identifies a number of technology-driven improvements in disease management such as implantable medical devices (IMDs) that are a standard treatment for candidates with specific diseases. Among patients using implantable cardiac defibrillators (ICD), for example, problems and issues are being discovered faster compared to patients without monitoring, improving safety. What is not known is why patients report not feeling safer, creating a safety paradox, and why patients identify privacy concerns in ICD monitoring.

There is a major gap in the literature regarding the factors that contribute to perceived safety and privacy in remote patient monitoring (RPM). To address this …

Multi-Objective Design Optimization Of A Permanent Magnet Axial Flux Eddy Current Brake, Rasul Tarvirdilu Asl, Hüseyi̇n Murat Yüksel, Ozan Keysan

Turkish Journal of Electrical Engineering and Computer Sciences

The main aim of this study is to optimize an axial flux eddy current damper to be used in a specific aviation application. Eddy current dampers are more advantageous compared to conventional mechanical dampers as they are maintenance-free due to contactless structure and have higher reliability, which is very desirable in aerospace applications. An initial eddy current brake prototype is manufactured and the test results are used to verify the 3-D finite element simulations. The effect of temperature on the brake performance is investigated. Finally, a multiobjective genetic algorithm optimization is applied to find the optimum pole number and geometric …

Prioritizing Interdependent Software Requirements Using Tensor And Fuzzy Graphs, Negin Misaghian, Homayun Motameni, Mohsen Rabbani

Turkish Journal of Electrical Engineering and Computer Sciences

Owing to the special stance of prioritizing tasks in requirements engineering processes, and as the requirements are not independent in nature, considering their dependencies is essential during the prioritizing process. Although different classifications of dependency types among requirements exist, only a few approaches in the prioritization process consider such valuable data (dependency among equirements). To achieve a practical prioritization, this study proposes a method based on the effects of the requirement dependencies (increase/decrease cost of) on the value of prioritization provided by the tensor concept. Since the strengths of dependencies are also influential factors in the act of prioritization, The …

Extraction And Selection Of Statistical Harmonics Features For Electrical Appliancesidentification Using K-Nn Classifier Combined With Voting Rules Method, Fateh Ghazali, Abdenour Hacine-Gharbi, Philippe Ravier, Tayeb Mohamadi

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we propose a novel framework for electrical appliances identification using statistical harmonic features of current signals and the use of the k-NN classifier combined with a voting rule strategy. Harmonic coefficients are computed over time using short-time Fourier series of the current signals. From these sequences of coefficients, the mean, standard deviation, skewness, and kurtosis are computed, which provide the statistical harmonic features. This framework has three novelties: (i) selecting the best combination of statistical measures in the sense of classification rate (CR); (ii) combining the k-NN classifier with the voting rule method in order to search …

Softswitch: A Centralized Honeypot-Based Security Approach Using Software-Defined Switching For Secure Management Of Vlan Networks, Muhammet Baykara, Resul Daş

Turkish Journal of Electrical Engineering and Computer Sciences

Honeypot systems are traps for intruders which simulate real systems such as web, application, and database servers used in information systems. Using these systems, unauthorized and malicious access can be efficiently detected. Honeypot is an entity which acts as a source of valued information and its behavior can be monitored. The inability or difficulty of intrusion detection is a serious security problem in networks including virtual local area network (VLAN). According to the literature, the use of honeypots for intrusion detection and prevention in networks including VLAN is strongly recommended. In this paper, in order to provide security and to …

Distance,Time And Terms In First Story Detection, Fei Wang

Doctoral

First Story Detection (FSD) is an important application of online novelty detection within Natural Language Processing (NLP). Given a stream of documents, or stories, about news events in a chronological order, the goal of FSD is to identify the very first story for each event. While a variety of NLP techniques have been applied to the task, FSD remains challenging because it is still not clear what is the most crucial factor in defining the “story novelty”. Giventhesechallenges,thethesisaddressedinthisdissertationisthat the notion of novelty in FSD is multi-dimensional. To address this, the work presented has adopted a three dimensional analysis of the …

Music Information Retrieval For Irish Traditional Music Automatic Analysis Of Harmonic, Rhythmic, And Melodic Features For Efficient Key-Invariant Tune Recognition, Pierre Beauguitte

Doctoral

Music making and listening practices increasingly rely on techno logy,and,asaconsequence,techniquesdevelopedinmusicinformation retrieval (MIR) research are more readily available to end users, in par ticular via online tools and smartphone apps. However, the majority of MIRresearchfocusesonWesternpopandclassicalmusic,andthusdoes not address specificities of other musical idioms. Irishtraditionalmusic(ITM)ispopularacrosstheglobe,withregular sessionsorganisedonallcontinents. ITMisadistinctivemusicalidiom, particularly in terms of heterophony and modality, and these character istics can constitute challenges for existing MIR algorithms. The bene fitsofdevelopingMIRmethodsspecificallytailoredtoITMisevidenced by Tunepal, a query-by-playing tool that has become popular among ITM practitioners since its release in 2009. As of today, Tunepal is the state of the art for tune recognition in ITM. The research in …

Efficient Detection Of Diseases By Feature Engineering Approach From Chest Radiograph, Avishek Mukherjee

Legacy Theses & Dissertations (2009 - 2024)

Deep Learning is the new state-of-the-art technology in Image Processing. We applied Deep Learning techniques for identification of diseases from Radiographs made publicly available by NIH. We applied some Feature Engineering approach to augment the data from Anterior-Posterior position to Posterior-Anterior position and vice-versa for all the diseases, at the same point we suppressed ‘No Finding’ radiographs which contributed to more than 50% (approximately 60,000) of the dataset to top 1000 images. We also prepared a model by adding a huge amount of noise to the augmented data, which if need be can be deployed at rural locations which lack …

Design And Simulation Of A Voltage Controlled Current Source For Electrical Impedance Tomography Applications, Farial Nur Maysha

Legacy Theses & Dissertations (2009 - 2024)

Electrical impedance tomography (EIT) is a simple, non-invasive and ionizing radiation-free imaging technology with potential application to medical diagnostics such as lung function, cardiac output, breast cancer, and cysts. Of the above imaging techniques, lung imaging has developed into the prime application for EIT. Because it presents an ill-posed inverse problem, EIT requires high-precision instrumentation and this thesis studies a new method for obtaining a high-precision current source and voltmeter for EIT. This thesis describes various simulation studies performed on the voltage-controlled current source (VCCS). The output impedance (Zo) of various types of Howland current source (HCS) including the basic …