Computer Engineering Commons^™

การเตือนการพลิกคว่ำแบบทริปเเละแบบอันทริปด้วยโครงข่ายประสาทเเบบเวลาจริง, ไกรฤกษ์ ตรีทิพสุนทร

Chulalongkorn University Theses and Dissertations (Chula ETD)

ระบบป้องกันการพลิกคว่ำสำคัญมากสำหรับความปลอดภัยของผู้ขับขี่ การพัฒนาระบบป้องกันการพลิกคว่ำต้องการการประเมินความเสี่ยงในการพลิกคว่ำ ความยากของการประเมินความเสี่ยงคือ การที่ไม่รู้ความสูงจุดศูนย์ถ่วงของรถ หรือน้ำหนักของรถในขณะนั้น เป็นต้น งานวิจัยนี้จะพัฒนาการคาดเดาการพลิกคว่ำโดยที่ไม่รู้ตัวแปรข้างต้น โดยโครงข่ายประสาทใช้ค่าจากเซนเซอร์ที่ติดตั้งบนรถ การทดลองจะใช้โมเดลของรถยนต์ SUV เนื่องจากมีจุดศูนย์ถ่วงที่สูงกว่ารถยนต์ประเภทอื่น การทดสอบใช้รถทดสอบอัตราส่วน 1:5 โดยใช้ทฤษฎีบักกิงแฮมพาย และรถทดสอบได้ติดตั้งเซนเซอร์วัดความเร่ง 5 จุด และไจโรสโกป 1 จุด การเตือนการพลิกคว่ำ แบ่งเป็น 3 ระดับ ได้แก่ ปลอดภัย, มีความเสี่ยง และมีความเสี่ยงสูง โดยระบบสามารถเตือนการพลิกคว่ำได้ทั้งแบบทริป และอันทริป ทริป คือการเข้าโค้งและสะดุดหลุม หรือสิ่งกีดขวาง อันทริปคือการเข้าโค้งด้วยความเร็วสูง การเตือนการพลิกคว่ำใกล้เคียงกับค่าดัชนีการพลิกคว่ำที่วัดได้จริง การทดลองด้วยข้อมูลจากโปรแกรมจำลอง “CarSim” งานวิจัยนี้ใช้โครงข่ายประสาทแบบวนกลับ โดยใช้ข้อมูลจากเซนเซอร์ที่ติดตั้งบนตัวรถ ผู้วิจัยทดสอบ และเปรียบเทียบ ชนิดของโครงข่ายประสาท โครงสร้างของโครงข่ายประสาท และข้อมูลรับเข้าที่แตกต่างกัน โดยโครงข่ายประสาทที่เหมาะสมกับการคาดเดาแบบทริปคือแทนเจนต์มีรากที่สองของค่าเฉลี่ยความผิดพลาดกำลังสอง (RMSE) อยู่ที่ 3.66x10-4 และ GRU เหมาะสำหรับการคาดเดาแบบอันทริป โดยมีรากที่สองของค่าเฉลี่ยความผิดพลาดกำลังสองอยู่ที่ 0.131x10-2

Person Re-Identification Over Encrypted Outsourced Surveillance Videos, Hang Cheng, Huaxiong Wang, Ximeng Liu, Yan Fang, Meiqing Wang, Xiaojun Zhang

Research Collection School Of Computing and Information Systems

Person re-identification (Re-ID) has attracted extensive attention due to its potential to identify a person of interest from different surveillance videos. With the increasing amount of the surveillance videos, high computation and storage costs have posed a great challenge for the resource-constrained users. In recent years, the cloud storage services have made a large volume of video data outsourcing become possible. However, person Re-ID over outsourced surveillance videos could lead to a security threat, i.e., the privacy leakage of the innocent person in these videos. Therefore, we propose an efFicient privAcy-preseRving peRson Re-ID Scheme (FARRIS) over outsourced surveillance videos, which …

A Topic Modeling Approach For Code Clone Detection, Mohammed Salman Khan

UNF Graduate Theses and Dissertations

In this thesis work, the potential benefits of Latent Dirichlet Allocation (LDA) as a technique for code clone detection has been described. The objective is to propose a language-independent, effective, and scalable approach for identifying similar code fragments in relatively large software systems. The main assumption is that the latent topic structure of software artifacts gives an indication of the presence of code clones. It can be hypothesized that artifacts with similar topic distributions contain duplicated code fragments and to prove this hypothesis, an experimental investigation using multiple datasets from various application domains were conducted. In addition, CloneTM, an LDA-based …

Improve Operating Room Utilization Through Distributed Scheduling Workflow And Automation, Miteshkumar Mahendrabhai Vasoya

Browse all Theses and Dissertations

Operating room (OR) plays a crucial role in health care, contributing more than 50% of the hospital’s revenue and incurring over 35% of the hospital’s expense, ultimately determining the hospital’s profitability. Moreover, because the OR is a primary source of admissions, it is virtually impossible to streamline hospital‐wide workflow without first streamlining patient flow through the OR. Unfortunately, current OR scheduling practices often limit the utilization of OR, one of the most expensive resources in the health care industry, to around 60%. On the other hand, many patients have to wait an excessively long time before their surgeries can be …

The Global Disinformation Order: 2019 Global Inventory Of Organised Social Media Manipulation, Samantha Bradshaw, Philip N. Howard

Copyright, Fair Use, Scholarly Communication, etc.

Executive Summary

Over the past three years, we have monitored the global organization of social media manipulation by governments and political parties. Our 2019 report analyses the trends of computational propaganda and the evolving tools, capacities, strategies, and resources.

1. Evidence of organized social media manipulation campaigns which have taken place in 70 countries, up from 48 countries in 2018 and 28 countries in 2017. In each country, there is at least one political party or government agency using social media to shape public attitudes domestically.

2.Social media has become co-opted by many authoritarian regimes. In 26 countries, computational propaganda …

On Spectral Analysis Of The Internet Delay Space And Detecting Anomalous Routing Paths, Gonca Gürsun

Turkish Journal of Electrical Engineering and Computer Sciences

Latency is one of the most critical performance metrics for a wide range of applications. Therefore, it is important to understand the underlying mechanisms that give rise to the observed latency values and diagnose the ones that are unexpectedly high. In this paper, we study the Internet delay space via robust principal component analysis (RPCA). Using RPCA, we show that the delay space, i.e. the matrix of measured round trip times between end hosts, can be decomposed into two components: the estimated latency between end hosts with respect to the current state of the Internet and the inflation on the …

Classification Of Generic System Dynamics Model Outputs Via Supervised Time Series Pattern Discovery, Mert Edali, Mustafa Gökçe Baydoğan, Gönenç Yücel

Turkish Journal of Electrical Engineering and Computer Sciences

System dynamics (SD) is a simulation-based approach for analyzing feedback-rich systems. An ideal SD modeling cycle requires evaluating the qualitative pattern characteristics of a large set of time series model output for testing, validation, scenario analysis, and policy analysis purposes. This traditionally requires expert judgement, which limits the extent of experimentation due to time constraints. Although time series recognition approaches can help to automate such an evaluation, utilization of them has been limited to a hidden Markov model classifier, namely the Indirect Structure Testing Software (ISTS) algorithm. Despite being used within several automated model-analysis tools, ISTS has several shortcomings. In …

Graph Analysis Of Network Flow Connectivity Behaviors, Hangyu Hu, Xuemeng Zhai, Mingda Wang, Guangmin Hu

Turkish Journal of Electrical Engineering and Computer Sciences

Graph-based approaches have been widely employed to facilitate in analyzing network flow connectivity behaviors, which aim to understand the impacts and patterns of network events. However, existing approaches suffer from lack of connectivity-behavior information and loss of network event identification. In this paper, we propose network flow connectivity graphs (NFCGs) to capture network flow behavior for modeling social behaviors from network entities. Given a set of flows, edges of a NFCG are generated by connecting pairwise hosts who communicate with each other. To preserve more information about network flows, we also embed node-ranking values and edge-weight vectors into the original …

A Comparative Study Of Author Gender Identification, Tuğba Yildiz

Turkish Journal of Electrical Engineering and Computer Sciences

In recent years, author gender identification has gained considerable attention in the fields of information retrieval and computational linguistics. In this paper, we employ and evaluate different learning approaches based on machine learning (ML) and neural network language models to address the problem of author gender identification. First, several ML classifiers are applied to the features obtained by bag-of-words. Secondly, datasets are represented by a low-dimensional real-valued vector using Word2vec, GloVe, and Doc2vec, which are on par with ML classifiers in terms of accuracy. Lastly, neural networks architectures, the convolution neural network and recurrent neural network, are trained and their …

Multiscanning Mode Laser Scanning Confocal Microscopy System, Mert Aktürk, Gökhan Gümüş, Baykal Sarioğlu, Yi̇ği̇t Dağhan Gökdel

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a table-top, reflective mode, laser scanning confocal microscopy system that is capable of scanning the target specimen alternately through various scanning devices and methods is proposed. We have developed a laser scanning confocal microscopy system to utilize combinations of various scanning devices and methods and to be able to characterize the optical performance of different scanners and micromirrors that are frequently used in scanning microscopy systems such as multiphoton microscopy, optical coherence tomography, or confocal microscopy. By integrating the scanner to be characterized on the same optical path with a galvanometric scan mirror, which is the conventional …

Hybrid Self-Controlled Precharge-Free Cam Design For Low Power And High Performance, V V Satyanarayana Satti, Sridevi Sriadibhatla

Turkish Journal of Electrical Engineering and Computer Sciences

Content-addressable memory (CAM) is a prominent hardware for high-speed lookup search, but consumes larger power. Traditional NOR and NAND match-line (ML) architectures suffer from a short circuit current path sharing and charge sharing respectively during precharge. The recently proposed precharge-free CAM suffers from high search delay and the subsequently proposed self-controlled precharge-free CAM suffers from high power consumption. This paper presents a hybrid self-controlled precharge-free (HSCPF) CAM architecture, which uses a novel charge control circuitry to reduce search delay as well as power consumption. The proposed and existing CAM ML architectures were developed using CMOS 45nm technology node with a …

Structure Tensor Adaptive Total Variation For Image Restoration, Surya Prasath, Dang Nh Thanh

Turkish Journal of Electrical Engineering and Computer Sciences

Image denoising and restoration is one of the basic requirements in many digital image processing systems. Variational regularization methods are widely used for removing noise without destroying edges that are important visual cues. This paper provides an adaptive version of the total variation regularization model that incorporates structure tensor eigenvalues for better edge preservation without creating blocky artifacts associated with gradient-based approaches. Experimental results on a variety of noisy images indicate that the proposed structure tensor adaptive total variation obtains promising results and compared with other methods, gets better structure preservation and robust noise removal.

A Kalman Filter Application For Rainfall Estimation Using Radar Reflectivity Measurements, Engi̇n Maşazade, Ali̇ Kemal Bakir, Pinar Kirci

Turkish Journal of Electrical Engineering and Computer Sciences

The rainfall amount observed at a given location mostly depend on the cloud density, which can be quantified with the reflectivity values observed by meteorology weather radars. In this study, we aim to estimate the rainfall amount using a Kalman filter with radar reflectivity measurements. We first assume that the amount of rainfall observed at automatic weather observation stations (AWOSs) are elements of an unknown state vector and consider the Kalman filter process model as the true rainfall amounts observed at these AWOSs over time. For the measurement model of the Kalman filter, we use the radar reflectivity values observed …

Probabilistic Small-Signal Stability Analysis Of Power System With Solar Farm Integration, Samundra Gurung, Sumate Naetiladdanon, Anawach Sangswang

Turkish Journal of Electrical Engineering and Computer Sciences

Currently, large-scale solar farms are being rapidly integrated in electrical grids all over the world. However, the photovoltaic (PV) output power is highly intermittent in nature and can also be correlated with other solar farms located at different places. Moreover, the increasing PV penetration also results in large solar forecast error and its impact on power system stability should be estimated. The effects of these quantities on small-signal stability are difficult to quantify using deterministic techniques but can be conveniently estimated using probabilistic methods. For this purpose, the authors have developed a method of probabilistic analysis based on combined cumulant …

A Hybrid Model For The Prediction Of Aluminum Foil Output Thickness In Cold Rolling Process, Ali̇ Öztürk, Ri̇fat Şeherli̇

Turkish Journal of Electrical Engineering and Computer Sciences

This study proposes a hybrid model composed of multiple prediction algorithms and an autoregressive moving average (ARMA) module for the thickness prediction. In order to attain higher accuracy, the prediction algorithms were globally combined by simple voting to reduce the effect of the inductive bias imposed by each algorithm on the dataset. The global multiexpert combination (GMEC) system included the multilayer perceptron neural network (MLPNN), radial basis function network (RBFN), multiple linear regression (MLR), and support vector machines (SVM) algorithms. The proposed hybrid model extends the GMEC system by integrating an ARMA module for the output. On the test dataset, …

Triangular Slotted Ground Plane: A Key To Realizing High-Gain, Cross-Polarization-Free Microstrip Antenna With Improved Bandwidth, Abhijyoti Ghosh, Banani Basu

Turkish Journal of Electrical Engineering and Computer Sciences

A simple rectangular microstrip antenna with triangular slotted ground plane has been studied both theoretically and experimentally to improve shortcomings like low gain (5 - 6 dBi), narrow bandwidth (3% - 4%), and poor copolarization (CP) to cross-polarization (XP) isolation, i.e. polarization purity (typically 10 - 12 dB), of conventional rectangular microstrip patch antennas. By placing two pairs of triangular shaped slots on the ground plane just below the nonradiating edges of the patch, high gain (around 9 dBi) and more than 22 dB polarization purity over a wide elevation angle has been achieved. The proposed antenna covers almost the …

Invisible Watermarking Framework That Authenticates And Prevents The Visualization Of Anaglyph Images For Copyright Protection, David-Octavio Muñoz-Ramirez, Volodymyr Ponomaryov, Rogelio Reyes-Reyes, Clara Cruz-Ramos, Beatriz-Paulina Garcia-Salgado

Turkish Journal of Electrical Engineering and Computer Sciences

In this work, a watermarking framework to authenticate and protect the copyright that prevents the visualization of nonauthorized anaglyph images is proposed. Designed scheme embeds a binary watermark and the Blue channel of the anaglyph image into the discrete cosine transform domain of the original image. The proposed method applies the quantization index modulation-dither modulation algorithm and a combination of Bose-Chaudhuri-Hocquenghem with repetition codes, which permit to increase the capability in recovering the watermark. Additionally, Hash algorithm is used to scramble the component where the watermark should be embedding, guaranteeing a higher security performance of the scheme. This new technique …

Combined Feature Compression Encoding In Image Retrieval, Lu Huo, Leijie Zhang

Turkish Journal of Electrical Engineering and Computer Sciences

Recently, features extracted by convolutional neural networks (CNNs) are popularly used for image retrieval. In CNN representation, high-level features are usually chosen to represent the images in coarse-grained datasets, while mid-level features are successfully applied to describe the images for fine-grained datasets. In this paper, we combine these different levels of features as a joint feature to propose a robust representation that is suitable for both coarse-grained and fine-grained image retrieval datasets. In addition, in order to solve the problem that the efficiency of image retrieval is influenced by the dimensionality of indexing, a unified subspace learning model named spectral …

A Hybrid Of Tropical-Singular Value Decomposition Method For Salt And Pepper Noise Removal, Achmad Abdurrazzaq, Ismail Mohd, Ahmad Kadri Junoh, Zainab Yahya

Turkish Journal of Electrical Engineering and Computer Sciences

The unknown information contained in an image that causes the change of information in the image is called noise. In this paper, we propose a new method for removing salt and pepper noise by using singular value decomposition and the concept of tropical algebra operations. To determine the performance of the proposed method, 20 test images are used as samples. Then three different image quality assessments are used: peak signal-to-noise ratio (PSNR), structural similarity (SSIM), and image enhancement factor (IEF). In addition, six different filtering methods, i.e. MF, DWMF, PSMF, MDBUTM, NAFSM, and BPDF, are used to compare the performance …

A Novel Algorithm For Frequency Extraction Of Abs Signals By Using Dtdnns, Mohammad Ali Shafieian, Hamed Banizaman, Shahrzad Sedaghat

Turkish Journal of Electrical Engineering and Computer Sciences

Intelligent transportations system (ITSs) have emerged to increase safety and convenience of people in vehicles. In an ITS, communication devices in the vehicle or along the streets send the information gathered from the vehicle to information management centers as well as sending processed information to the vehicle. Furthermore, it is necessary to locate the exact location of the vehicle on a digital map in order to navigate the vehicle precisely in control and navigation systems. One of the technologies for this purpose is the antilock brake system (ABS), which can avoid accidents effectively and can also be utilized to determine …

Channel Estimation For Ofdm-Im Systems, Yusuf Acar, Sultan Aldirmaz Çolak, Ertuğrul Başar

Turkish Journal of Electrical Engineering and Computer Sciences

Orthogonal frequency division multiplexing with index modulation (OFDM-IM) has been recently proposed to increase the spectral efficiency and improve the error performance of multicarrier communication systems. However, all the OFDM-IM systems assume that the perfect channel state information is available at the receiver. Nevertheless, channel estimation is a challenging problem in practical wireless communication systems for coherent detection at the receiver. In this paper, a novel method based on the pilot symbol-aided channel estimation technique is proposed and evaluated for OFDM-IM systems. Pilot symbols, which are placed equidistantly, allow the regeneration of the response of the channel so that pilot …

Ingan/Gan Tandem Solar Cell Parameter Estimation: A Comparative Stud, Abdelmoumene Benayad, Smail Berrah

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, two hybrid estimation approaches, hybrid genetic algorithm (TR-GA) and hybrid particle swarm optimization (TR-PSO), are used to estimate single-diode model InGaN/GaN solar cell parameters from J?V experimental data under AM0 illumination. These parameters are photocurrent density ($J_{ph}$), reverse saturation current density ($J_{s}$), ideality factor ($A$), series resistance ($R_{s}$), and shunt resistance ($R_{sh}$). The trust region (TR) method used in both approaches provides the initial conditions and helps to avoid the problem of premature convergence (due to local minimum). Simulation results based on the minimization of the mean square error between experimental and theoretical J-V characteristics show that …

A New Failure Protection Algorithm For Circuit Breakers Using The Power Loss Of Switching Arc Incidents, Behnam Feizifar, Ömer Usta

Turkish Journal of Electrical Engineering and Computer Sciences

The principal function of circuit breakers (CBs) is to isolate a portion of the power network from the rest of it in a timely manner following an opening command. Any failure in the opening operation of CBs, especially following a fault condition, will almost certainly result in a catastrophic event. Therefore, the issue of failure detection of CBs is essential and has a vital role in power system protection. This paper presents a novel power-based algorithm for failure detection of CBs. The power loss of CBs due to an arcing event increases as the arcing time gets longer. The arcing …

On Parameter Adjustment Of The Fuzzy Neighborhood-Based Clustering Algorithms, Fatma Günseli̇ Yaşar, Gözde Ulutagay, Semi̇h Utku, Efendi̇ Nasi̇boğlu

Turkish Journal of Electrical Engineering and Computer Sciences

Day by day huge amounts data are produced, and evaluation of these data becomes more difficult. The data obtained should provide meaningful, correct, and accurate information. Therefore, all data must be separated into clusters correctly, and the right information from these clusters must be obtained. Having the correct clusters depends on the clustering algorithm that is used. There are many clustering algorithms. The density-based methods are very important among the groups of clustering methods, as they can find arbitrary shapes. An advanced model of the density-based spatial clustering of applications with noise (DBSCAN) algorithm, called fuzzy neighborhood DBSCAN Gaussian means …

Evolutionary Approaches For Weight Optimization In Collaborative Filtering-Based Recommender Systems, Sevgi̇ Yi̇ği̇t Sert, Yilmaz Ar, Gazi̇ Erkan Bostanci

Turkish Journal of Electrical Engineering and Computer Sciences

Collaborative filtering is one of the widely adopted approaches in recommender systems used for e-commerce applications, stating that users having similar tastes will have similar preferences in the future. The literature presents a number of similarity metrics such as the extended Jaccard coefficient to quantify these preference similarities. This paper aims to improve prediction accuracy by optimizing the similarity values computed using these metrics by adopting two biologically inspired approaches, namely artificial bee colony and genetic algorithms, with a bottom-up approach, suggesting that any improvement on a single-user basis will reflect on the overall prediction accuracy. Detailed statistical analysis was …

Particle Swarm Optimization-Based Collision Avoidance, Ti̇mur İnan, Ahmet Fevzi̇ Baba

Turkish Journal of Electrical Engineering and Computer Sciences

Collision risk assessment and collision avoidance of vessels have always been an important topic in ocean engineering. Decision support systems are increasingly becoming the focus of many studies in the maritime industry today as vessel accidents are often caused by human error. This study proposes an anticollision decision support system that can determine surrounding obstacles by using the information received from radar systems, obtain the position and speed of obstacles within a certain time period, and suggest possible routes to prevent collisions. In this study we use a neural network to predict the subsequent positions of surrounding vessels, a fuzzy …

Automatic Fault Isolation And Restoration Of Distribution System Using Jade Based Multi-Agents, Indhumathi Chellaswamy, Joy Vasantha Rani Sp

Turkish Journal of Electrical Engineering and Computer Sciences

This paper proposes a solution for automatic service restoration along with automatic fault location and isolation of the faulty sections in feeder in a power distribution system. A Java agent development environment-based multiagent system (MAS) is proposed to solve the problem of automatic service restoration in smart grid distribution systems. The agent-based solution development is discussed in detail and the MAS application to solve power restoration problem is elaborated in this paper. A study is done on a modified IEEE 33 bus system and the solution is implemented in the Velachery substation of the Tamilnadu electricity board. The results prove …

Assessing Wind Energy Potential Using Finite Mixture Distributions, Meli̇h Burak Koca, Muhammet Burak Kiliç, Yusuf Şahi̇n

Turkish Journal of Electrical Engineering and Computer Sciences

Wind has become a popular renewable energy resource in the last two decades. Wind speed modeling is a crucial task for investors to estimate the energy potential of a region. The aim of this paper was to compare the popular unimodal wind speed distributions with their two-component mixture forms. Accordingly, Weibull, gamma, normal, lognormal distributions, and their two-component mixture forms; two-component mixture Weibull, two-component mixture gamma, two-component mixture normal, and two-component mixture lognormal distributions were employed to model wind speed datasets obtained from Belen Wind Power Plant and G??k?ßeada Meteorological Station. This paper also provides the comparison of gradient-based and …

Design Of Area-Efficient Iir Filter Using Fppe, Ramyarani Nallathambi, Subbiah Veerana, Deepa Prabhakaran

Turkish Journal of Electrical Engineering and Computer Sciences

Floating point arithmetic circuits provide wide dynamic range and high precision, and they are widely used in scientific computing and signal processing applications, but the complexity increases in hardware implementations of floating point units. In VLSI design architecture, many applications suffer in size of the components used in logical operations. The aim of reducing architecture is to gain reduction in power loss and also in area, but the reduction in size of the components leads to an increase in delay and memory. Hence, to overcome these limitations and to optimize the area, a novel design of floating point processing element …

Web Personalization Issues In Big Data And Semantic Web: Challenges Andopportunities, Bujar Raufi, Florije Ismaili, Jaumin Ajdari, Xhemal Zenuni

Turkish Journal of Electrical Engineering and Computer Sciences

Web personalization is a process that utilizes a set of methods, techniques, and actions for adapting the linking structure of an information space or its content or both to user interaction preferences. The aim of personalization is to enhance the user experience by retrieving relevant resources and presenting them in a meaningful fashion. The advent of big data introduced new challenges that locate user modeling and personalization community in a new research setting. In this paper, we introduce the research challenges related to Web personalization analyzed in the context of big data and the Semantic Web. This paper also introduces …