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 …
Efficient Detection Of Diseases By Feature Engineering Approach From Chest Radiograph,
2019
University at Albany, State University of New York
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,
2019
University at Albany, State University of New York
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 …
Autonomous Spectrum Enforcement : A Blockchain Approach,
2019
University at Albany, State University of New York
Autonomous Spectrum Enforcement : A Blockchain Approach, Maqsood Ahamed Abdul Careem
Legacy Theses & Dissertations (2009 - 2024)
A core limitation in existing wireless technologies is the scarcity of spectrum, to support the exponential increase in Internet-connected and multimedia-capable mobile devices and the increasing demand for bandwidth-intensive services. As a solution, Dynamic Spectrum Access policies are being ratified to promote spectrum sharing for various spectrum bands and to improve the spectrum utilization. This poses an equally challenging problem of enforcing these spectrum policies. The distributed and dynamic nature of policy violations necessitates the use of autonomous agents to implement efficient and agile enforcement systems. The design of such a fully autonomous enforcement system is complicated due to the …
Emotion Forecasting In Dyadic Conversation : Characterizing And Predicting Future Emotion With Audio-Visual Information Using Deep Learning,
2019
University at Albany, State University of New York
Emotion Forecasting In Dyadic Conversation : Characterizing And Predicting Future Emotion With Audio-Visual Information Using Deep Learning, Sadat Shahriar
Legacy Theses & Dissertations (2009 - 2024)
Emotion forecasting is the task of predicting the future emotion of a speaker, i.e., the emotion label of the future speaking turn–based on the speaker’s past and current audio-visual cues. Emotion forecasting systems require new problem formulations that differ from traditional emotion recognition systems. In this thesis, we first explore two types of forecasting windows(i.e., analysis windows for which the speaker’s emotion is being forecasted): utterance forecasting and time forecasting. Utterance forecasting is based on speaking turns and forecasts what the speaker’s emotion will be after one, two, or three speaking turns. Time forecasting forecasts what the speaker’s emotion will …
Communications Using Deep Learning Techniques,
2019
University at Albany, State University of New York
Communications Using Deep Learning Techniques, Priti Gopal Pachpande
Legacy Theses & Dissertations (2009 - 2024)
Deep learning (DL) techniques have the potential of making communication systems
A Novel Resource Clustering Model To Develop An Efficient Wireless Personal Cloud Environment,
2019
TÜBİTAK
A Novel Resource Clustering Model To Develop An Efficient Wireless Personal Cloud Environment, Kowsigan Mohan, Balasubramanie Palanisamy
Turkish Journal of Electrical Engineering and Computer Sciences
In the current era, cloud computing is the major focus of distributed computing and it helps in satisfying the requirements of the business world. It provides facilities on demand under all the parameters of the computing, such as infrastructure, platform, and software, across the globe. One of the major challenges in the cloud environment is to cluster the resources and schedule the jobs among the resource clusters. Many existing approaches failed to provide an optimal solution for job scheduling due to inefficient clustering of resources. In the proposed system, a novel algorithm called resource differentiation based on equivalence node potential …
Evaluation Of Losses In A Secondary-Side Controlled Wireless Battery Charging System,
2019
TÜBİTAK
Evaluation Of Losses In A Secondary-Side Controlled Wireless Battery Charging System, Fahri̇ Gürbüz, Tolga Sürgevi̇l, Mutlu Boztepe
Turkish Journal of Electrical Engineering and Computer Sciences
Secondary-side controlled inductive power transfer (IPT) systems are easy to control compared to primary and dual-side control methods, and more importantly, they do not require wireless communication between primary and secondary sides. In this paper, a wireless battery charging system based on secondary-side controlled IPT is analyzed and presented in detail. The proposed control method relies on the detection of the secondary coil current and the transferred power can be fully controlled by the secondary-side active rectifier with reduced number of power switching devices. The steady-state performance of the IPT system is evaluated using a fundamental harmonic analysis method for …
Vibration Analysis Of A Novel Magnetic-Viscous Nonlinear Passive Isolator Via Finite Element Simulation,
2019
TÜBİTAK
Vibration Analysis Of A Novel Magnetic-Viscous Nonlinear Passive Isolator Via Finite Element Simulation, Ahmad Partovi Meran, Ümi̇t Önen
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, the design and the finite element simulation of a novel magnetic-viscous vibration isolator have been presented. The proposed isolator consists of permanent magnets axially aligned in repulsion position and a viscous damper in parallel with them. The nonlinear spring characteristic of the permanent magnets provides a good damping property with this configuration. Explicit finite element analyses have been conducted to examine the dynamic behavior of the isolator. Output displacements and transmissibility ratios were measured for various magnet configurations, dashpot coefficients, and input displacement excitation frequencies to determine the best damping properties. The results of the finite element …
Investigation Of Control Of Power Flow By Using Phase Shifting Transformers: Turkey Case Study,
2019
TÜBİTAK
Investigation Of Control Of Power Flow By Using Phase Shifting Transformers: Turkey Case Study, Erdi̇ Doğan, Nuran Yörükeren
Turkish Journal of Electrical Engineering and Computer Sciences
Transmission systems are needed to be upgraded based on expected/unexpected load growth factor by years. However, it is not so easy to install and upgrade the transmission system, which requires transmission planning calculation ahead of time. Traditionally, transmission companies built extra transmission lines to meet that load growth, but it is not easy and cost-effective to upgrade the system every time loads increase. Some unexpected load growth may occur for some load points that is not in the part of planning calculation. For those situations, the transmission system may face serious congestion problems. Transmission companies have been looking for a …
Optimal Rescheduling Of Real Power To Mitigate Congestion Using Gravitational Search Algorithm,
2019
TÜBİTAK
Optimal Rescheduling Of Real Power To Mitigate Congestion Using Gravitational Search Algorithm, Kaushik Paul, Niranjan Kumar, Shaligram Agrawal, Kamalendu Paul
Turkish Journal of Electrical Engineering and Computer Sciences
The initiative to manage congestion has gained interest in the current deregulated scenario. The principle commitment of the work in this article is to extend the gravitational search algorithm (GSA) as an efficient metaheuristic optimizing algorithm to diminish the rescheduling cost and efficiently attenuate the overloading of the line with the minimal deviation in the active power generation. The congestion management drive is accomplished by prioritizing the generators based on their sensitivity values. Thereafter, the GSA is introduced to optimally minimize the rescheduling cost along with the minimization of the total amount of active power output and system losses. The …
Generation Rescheduling Using Multiobjective Bilevel Optimization,
2019
TÜBİTAK
Generation Rescheduling Using Multiobjective Bilevel Optimization, Kiran Babu Vakkapatla, Srinivasa Varma Pinni
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents a new multiobjective optimization method that can be used for generation rescheduling in power systems. Generation rescheduling in restructured power systems is performed by the system operator for different operations like congestion management, day-ahead scheduling, and preventive maintenance. The nonlinear nature of the equations involved and the constraints on decision variables pose a challenge to find the global optimum. In order to find the global optimum using a genetic algorithm, a bilevel optimization method is proposed. In the proposed multiobjective optimization method, the objectives are classified as primary and secondary based on their relative importance. The best …
An Analytical Formula For Selecting The Feeding Voltage And Frequency In A Torus-Type Nonslotted Axial Flux Permanent Magnet Machine Design, Reza Mirzahosseini, Ahmad Darabi, Mohsen Assili
Turkish Journal of Electrical Engineering and Computer Sciences
Axial flux permanent magnet (AFPM) motors are usually controlled by drive; therefore, in the design of these machines the feeding voltage and frequency are completely independent parameters. Undoubtedly, the values of these parameters have significant effects on the performance characteristics of the machine. The main objective of this paper is to investigate the effects of these parameters on the efficiency of a double-sided TORUS-type nonslotted (TORUS NS) AFPM motor and propose a formula for selecting the optimal values of the feeding voltage and frequency at the beginning of the design process. To fulfill this goal, different machines with various speeds, …
An Ambient Assisted Living System For Dementia Patients,
2019
TÜBİTAK
An Ambient Assisted Living System For Dementia Patients, Özgün Yilmaz
Turkish Journal of Electrical Engineering and Computer Sciences
Dementia is a major health and social care challenge of today and the near future as a result of increased human lifespan. Currently, there is no therapeutic solution for dementia, but a solution for managing the wandering behavior of dementia patients can be provided by an ambient assisted living system. In this paper, the design and implementation of iCarus, which is an intelligent ambient assisted living system for dealing with wandering behavior in early stages of dementia, is described. The aim of iCarus is to provide independent living for elderly people and a cost-effective way of monitoring them. iCarus is …
Monotone Data Modeling Using Rational Functions,
2019
TÜBİTAK
Monotone Data Modeling Using Rational Functions, Zoha Tariq, Farheen Ibraheem, Malik Zawwar Hussain, Muhammad Sarfraz
Turkish Journal of Electrical Engineering and Computer Sciences
Rational schemes for shape preservation of monotone data both in 2D and 3D setups have been developed. $C^1$ rational cubic and partially blended bicubic functions are employed for this purpose. Monotonicity is achieved by extracting constraints on parameters involved in the description of these rational functions. Monotone curves and surfaces have been obtained, which provide evidence that the algorithm used fits most types of monotone data and produces visually pleasing results.
Ifit: An Unsupervised Discretization Method Based On The Ramer-Douglas-Peucker Algorithm,
2019
TÜBİTAK
Ifit: An Unsupervised Discretization Method Based On The Ramer-Douglas-Peucker Algorithm, Alev Mutlu, Furkan Göz, Orhan Akbulut
Turkish Journal of Electrical Engineering and Computer Sciences
Discretization is the process of converting continuous values into discrete values. It is a preprocessing step of several machine learning and data mining algorithms and the quality of discretization may drastically affect the performance of these algorithms. In this study we propose a discretization algorithm, namely line fitting-based discretization (lFIT), based on the Ramer--Douglas--Peucker algorithm. It is a static, univariate, unsupervised, splitting-based, global, and incremental discretization method where intervals are determined based on the Ramer--Douglas--Peucker algorithm and the quality of partitioning is assessed based on the standard error of the estimate. To evaluate the performance of the proposed method, a …
Elimination Of Useless Images From Raw Camera-Trap Data,
2019
TÜBİTAK
Elimination Of Useless Images From Raw Camera-Trap Data, Ulaş Tekeli̇, Yalin Baştanlar
Turkish Journal of Electrical Engineering and Computer Sciences
Camera-traps are motion triggered cameras that are used to observe animals in nature. The number of images collected from camera-traps has increased significantly with the widening use of camera-traps thanks to advances in digital technology. A great workload is required for wild-life researchers to group and label these images. We propose a system to decrease the amount of time spent by the researchers by eliminating useless images from raw camera-trap data. These images are too bright, too dark, blurred, or they contain no animals. To eliminate bright, dark, and blurred images we employ techniques based on image histograms and fast …
Spatial-Aware Global Contrast Representation For Saliency Detection,
2019
TÜBİTAK
Spatial-Aware Global Contrast Representation For Saliency Detection, Dan Xu, Shucheng Huang, Xin Zuo
Turkish Journal of Electrical Engineering and Computer Sciences
Deep learning networks have been demonstrated to be helpful when used in salient object detection and achieved superior performance than the methods that are based on low-level hand-crafted features. In this paper, we propose a novel spatial-aware contrast cube-based convolution neural network (CNN) which can further improve the detection performance. From this cube data structure, the contrast of the superpixel is extracted. Meanwhile, the spatial information is preserved during the transformation. The proposed method has two advantages compared to the existing deep learning-based saliency methods. First, instead of feeding the deep learning networks with raw image patches or pixels, we …
All-Polymer Ultrasonic Transducer Design For An Intravascular Ultrasonographyapplication,
2019
TÜBİTAK
All-Polymer Ultrasonic Transducer Design For An Intravascular Ultrasonographyapplication, Dooyoung Hah
Turkish Journal of Electrical Engineering and Computer Sciences
Intravascular ultrasonography (IVUS), a medical imaging modality, is used to obtain cross-sectional views of blood vessels from inside. In IVUS, transducers are brought to the proximity of the imaging targets so that highresolution images can be obtained at high frequency without much concern of signal attenuation. To eliminate mechanical rotation rendered in conventional IVUS, it is proposed to manufacture a transducer array on a flexible substrate and wrap it around a cylindrical frame. The transducer of consideration is a capacitive micromachined ultrasonic transducer (CMUT). The whole device needs to be made out of polymers to be able to endure a …
A Computational Study On Aging Effect For Facial Expression Recognition,
2019
TÜBİTAK
A Computational Study On Aging Effect For Facial Expression Recognition, Elena Sönmez
Turkish Journal of Electrical Engineering and Computer Sciences
This work uses newly introduced variations of the sparse representation-based classifier (SRC) to challenge the issue of automatic facial expression recognition (FER) with faces belonging to a wide span of ages. Since facial expression is one of the most powerful and immediate ways to disclose individuals? emotions and intentions, the study of emotional traits is an active research topic both in psychology and in engineering fields. To date, automatic FER systems work well with frontal and clean faces, but disturbance factors can dramatically decrease their performance. Aging is a critical disruption element, which is present in any real-world situation and …
