Cooperative Target Tracking In Concentric Formations,
2021
CUNY New York City College of Technology
Cooperative Target Tracking In Concentric Formations, Lili Ma
Publications and Research
This paper considers the problem of coordinating multiple unmanned aerial vehicles (UAVs) in a circular formation around a moving target. The main contribution is allowing for versatile formation patterns on the basis of the following components. Firstly, new uniform spacing control laws are proposed that spread the agents not necessarily over a full circle, but over a circular arc. Uniform spacing formation controllers are proposed, regulating either the separation distances or the separation angles between agents. Secondly, the use of virtual agents is proposed to allow for different radii in agents’ orbits. Thirdly, a hierarchical combination of formation patterns is …
Green Underwater Wireless Communications Using Hybrid Optical-Acoustic Technologies,
2021
Edith Cowan University
Green Underwater Wireless Communications Using Hybrid Optical-Acoustic Technologies, Kazi Y. Islam, Iftekhar Ahmad, Daryoush Habibi, M. Ishtiaque A. Zahed, Joarder Kamruzzaman
Research outputs 2014 to 2021
Underwater wireless communication is a rapidly growing field, especially with the recent emergence of technologies such as autonomous underwater vehicles (AUVs) and remotely operated vehicles (ROVs). To support the high-bandwidth applications using these technologies, underwater optics has attracted significant attention, alongside its complementary technology – underwater acoustics. In this paper, we propose a hybrid opto-acoustic underwater wireless communication model that reduces network power consumption and supports high-data rate underwater applications by selecting appropriate communication links in response to varying traffic loads and dynamic weather conditions. Underwater optics offers high data rates and consumes less power. However, due to the severe …
การสร้างความต้องการเชิงฟังก์ชันและที่ไม่ใช่เชิงฟังก์ชันของซอฟต์แวร์จากการจำแนกบทวิจารณ์ของผู้ใช้งานโมไบล์แอปพลิเคชัน,
2021
คณะวิศวกรรมศาสตร์
การสร้างความต้องการเชิงฟังก์ชันและที่ไม่ใช่เชิงฟังก์ชันของซอฟต์แวร์จากการจำแนกบทวิจารณ์ของผู้ใช้งานโมไบล์แอปพลิเคชัน, ธนัชชา พันธ์ธรรม
Chulalongkorn University Theses and Dissertations (Chula ETD)
บทวิจารณ์ของผู้ใช้งานเป็นแหล่งข้อมูลที่สำคัญสำหรับนักพัฒนาโมไบล์แอปพลิเคชัน เพื่อใช้ในการปรับปรุงและวิวัฒนาการแอปพลิเคชันหลังจากที่ได้ปล่อยให้ใช้งานไปแล้ว เนื่องจากข้อมูลบทวิจารณ์ของผู้ใช้งานมีจำนวนมากจึงเป็นเรื่องยุ่งยากสำหรับทีมนักพัฒนาโมไบล์แอปพลิเคชันที่จะระบุว่าบทวิจารณ์ของผู้ใช้งานใดประกอบไปด้วยข้อมูลที่เป็นประโยชน์ต่อการปรับปรุงและวิวัฒนาการโมไบล์แอปพลิเคชันเพิ่มเติม วิทยานิพนธ์นี้นำเสนอความพยายามที่จะอำนวยความสะดวกให้แก่ทีมนักพัฒนาในขั้นต้นด้วยการสร้างความต้องการเชิงฟังก์ชันและที่ไม่ใช่เชิงฟังก์ชันโดยอัตโนมัติจากข้อมูลบทวิจารณ์ของผู้ใช้งานโมไบล์แอปพลิเคชันบนแอปสโตร์และเพลย์สโตร์ แนวทางที่นำเสนอประกอบด้วยสามขั้นตอน เริ่มจากการใช้อัลกอริทึมการจำแนกข้อความเพื่อจำแนกบทวิจารณ์ของผู้ใช้งานออกเป็นบทวิจารณ์ของผู้ใช้งานเชิงฟังก์ชันหรือที่ไม่ใช่เชิงฟังก์ชัน ขั้นตอนที่สองบทวิจารณ์ของผู้ใช้งานที่ไม่ซ้ำกันจะถูกระบุโดยใช้เทคนิคการจัดกลุ่มและการวิเคราะห์ความคล้ายคลึงกันของข้อความ ในขั้นตอนสุดท้ายข้อมูลที่มีความสำคัญจะถูกสกัดจากบทวิจารณ์ของผู้ใช้งานเพื่อใช้สร้างความต้องการเชิงฟังก์ชันและที่ไม่ใช่เชิงฟังก์ชันโดยใช้แบบรูปข้อมูลบทวิจารณ์ของผู้ใช้งานและแม่แบบความต้องการ ในส่วนของการประเมินผล ความต้องการที่ถูกสร้างขึ้นจากแนวทางที่นำเสนอได้รับคะแนนต่ำถึงสูงแตกต่างกันไปในแง่ของความสามารถในการอ่านได้ง่าย ความไม่กำกวม ความสมบูรณ์ และความสมเหตุสมผล ซึ่งแนวทางที่วิทยานิพนธ์นำเสนอนี้สามารถช่วยทีมนักพัฒนาระบุถึงความต้องการการเปลี่ยนแปลงทั้งในเชิงฟังก์ชันและที่ไม่ใช่เชิงฟังก์ชันจากเสียงสะท้อนโดยตรงของผู้ใช้งานซึ่งควรได้รับการพิจารณาเพื่อใช้ในการปรับปรุงและวิวัฒนาการโมไบล์แอปพลิเคชันต่อไป
Imu-Based Estimation Of Body Posture In Commercial Fishing,
2021
Northern Illinois University
Imu-Based Estimation Of Body Posture In Commercial Fishing, Umme Kawsar Alam
Graduate Research Theses & Dissertations
According to the U.S. Bureau of Labor Statistics (BLS), work-related musculoskeletaldisorders (WMSDs) account for 33% of all occupational injuries and illnesses in the U.S. In addition, one of the most strenuous occupations in which musculoskeletal disorders are common is known to be commercial fishing. The first step to address this issue is to precisely measure the working postures of workers so that the relation between WMSDs and nonneutral working postures can be systematically investigated. Although the inertial measurement unit (IMU) has recently gained attention in posture measurement due to its portability, it is highly limited to the use as an …
Human-Robot Collaboration Enabled By Real-Time Vision Tracking,
2021
South Dakota State University
Human-Robot Collaboration Enabled By Real-Time Vision Tracking, Travis Deegan
Electronic Theses and Dissertations
The number of robotic systems in the world is growing rapidly. However, most industrial robots are isolated in caged environments for the safety of users. There is an urgent need for human-in-the-loop collaborative robotic systems since robots are very good at performing precise and repetitive tasks but lack the cognitive ability and soft skills of humans. To fill this need, a key challenge is how to enable a robot to interpret its human co-worker’s motion and intention. This research addresses this challenge by developing a collaborative human-robot interface via innovations in computer vision, robotics, and system integration techniques. Specifically, this …
Human Activity Recognition Based On Wearable Flex Sensor And Pulse Sensor,
2021
South Dakota State University
Human Activity Recognition Based On Wearable Flex Sensor And Pulse Sensor, Xiaozhu Jin
Electronic Theses and Dissertations
In order to fulfill the needs of everyday monitoring for healthcare and emergency advice, many HAR systems have been designed [1]. Based on the healthcare purpose, these systems can be implanted into an astronaut’s spacesuit to provide necessary life movement monitoring and healthcare suggestions. Most of these systems use acceleration data-based data record as human activity representation [2,3]. But this data attribute approach has a limitation that makes it impossible to be used as an activity monitoring system for astronavigation. Because an accelerometer senses acceleration by distinguishing acceleration data based on the earth’s gravity offset [4], the accelerometer cannot read …
Research Framework Of Human Factors Interactions With Technical And Security Factors In Cloud Computing,
2021
Butler University
Research Framework Of Human Factors Interactions With Technical And Security Factors In Cloud Computing, Hongjiang Xu, Sakthi Mahenthiran
Scholarship and Professional Work - Business
There are many advantages to adopt cloud computing, however, some important issues need to be addressed, such as cybersecurity, cost-saving, trust, implementation complexity, and cloud provider’s reliability. This study developed a research framework to study the human factors that interact with technical and cybersecurity factors to affect the cloud-computing provider’s performance from the user’s perspective. Research hypotheses were developed and a survey was conducted to test the hypotheses and validate the research framework.
Speed-Sensorless Predictive Torque Controlled Induction Motor Drive Withfeed-Forward Control Of Load Torque For Electric Vehicle Applications, Emrah Zerdali̇, Ridvan Demi̇r
Turkish Journal of Electrical Engineering and Computer Sciences
Nowadays, the global trend is towards reducing CO2 emissions and one solution is to replace internal combustion vehicles with electric vehicles. To this end, electric drive system, the most crucial part of an electric vehicle, has gained importance and has become a major research field. The induction motor (IM) is one of the best candidates for electric vehicle applications due to its advantages such as having simple and robust design, its low cost maintenance requirements and the ability to operate in harsh environments. However, it has a highly nonlinear model with timevarying electrical and mechanical parameters making them difficult to …
Optimal Coordination Of Directional Overcurrent Relay Based On Combination Ofimproved Particle Swarm Optimization And Linear Programming Consideringmultiple Characteristics Curve, Suzana Pil Ramli, Hazlie Mokhlis, Wei Ru Wong, Munir Azam Muhammad, Nurulafiqah Nadzirah Mansor, Muhamad Hatta Hussain
Turkish Journal of Electrical Engineering and Computer Sciences
Optimal coordination of directional over-current relays (DOCRs) is a crucial task in ensuring the security and reliability of power system network. In this paper, a hybridization of an improved particle swarm optimization and linear programming (IPSO-LP) is proposed to solve DOCRs coordination problem. The considered decision variables in the optimization are plug setting current, time multiplier setting, type of relay, and type of curve. By considering these parameters in the optimization, the best relay operating time can be determined. Furthermore, the proposed technique also considered the continuous values of pick-up current setting (PSC) and time setting multiplier (TMS). Test on …
Fpga Implementation Of Lsd-Omp For Real-Time Ecg Signal Reconstruction,
2021
TÜBİTAK
Fpga Implementation Of Lsd-Omp For Real-Time Ecg Signal Reconstruction, Önder Polat, Sema Kayhan
Turkish Journal of Electrical Engineering and Computer Sciences
Compressed sensing is widely used to compress electrocardiogram (ECG) signals, but the major challenges of the compressed sensing algorithms are their highly complex signal reconstruction processes. In this paper, a reconfigurable high-speed and low-power field-programmable gate array (FPGA) implementation of the least support denoising-orthogonal matching pursuit (LSD-OMP) algorithm for the real-time reconstruction of the ECG signals is presented. The contribution of this study is two-fold: Firstly, LSD-OMP can pick more than one element at each iteration and reconstruct the sparse signal using less number of iterations as compared to the standard OMP algorithms. Latency of the proposed design is therefore …
A Novel Hybrid Decision-Based Filter And Universal Edge-Based Logical Smoothingadd-On To Remove Impulsive Noise,
2021
TÜBİTAK
A Novel Hybrid Decision-Based Filter And Universal Edge-Based Logical Smoothingadd-On To Remove Impulsive Noise, Rajanbir Singh Ghumaan, Prateek Jeet Singh Sohi, Nikhil Sharma, Bharat Garg
Turkish Journal of Electrical Engineering and Computer Sciences
This paper presents a novel hybrid filter along with a universal extension to remove salt and pepper noise even at a very high noise density. The proposed filter initially specifies a threshold and then denoises the image using a combination of linear, nonlinear, and probabilistic techniques. Furthermore, to improve the quality, a universal add-on is presented which uses edge detection and smoothening techniques to brush out fine details from the restored image. To evaluate the efficacy, the proposed and existing filtering techniques are implemented in MATLAB and simulated with benchmark images. The simulation results show that the proposed filter is …
An Enhanced Bandwidth Disturbance Observer Based Control- S-Filter Approach,
2021
TÜBİTAK
An Enhanced Bandwidth Disturbance Observer Based Control- S-Filter Approach, Mehmet Önder Efe, Coşku Kasnakoğlu
Turkish Journal of Electrical Engineering and Computer Sciences
A continuous time enhanced bandwidth disturbance observer based control (DOBC) scheme is proposed in this paper. The classical Q -filter is implemented in feedback form and a signum function is inserted into the loop. The loop with this modification becomes capable of detecting small magnitude matched disturbances and we present an in depth discussion of the stability and performance issues comparatively. The proposed approach is called S-filter approach and the results outperform the classical approach under certain conditions. The contribution of the current paper is to advance the subject area to nonlinear filters for DOBC loops with guaranteed stability and …
A Linear Programming Approach To Multiple Instance Learning,
2021
TÜBİTAK
A Linear Programming Approach To Multiple Instance Learning, Emel Şeyma Küçükaşci, Mustafa Gökçe Baydoğan, Zeki̇ Caner Taşkin
Turkish Journal of Electrical Engineering and Computer Sciences
Multiple instance learning (MIL) aims to classify objects with complex structures and covers a wide range of real-world data mining applications. In MIL, objects are represented by a bag of instances instead of a single instance, and class labels are provided only for the bags. Some of the earlier MIL methods focus on solving MIL problem under the standard MIL assumption, which requires at least one positive instance in positive bags and all remaining instances are negative. This study proposes a linear programming framework to learn instance level contributions to bag label without emposing the standart assumption. Each instance of …
Towards An Ontology-Based Approach To The "New Normality" After Covid-19:The Spanish Case During Pandemic First Wave,
2021
TÜBİTAK
Towards An Ontology-Based Approach To The "New Normality" After Covid-19:The Spanish Case During Pandemic First Wave, Evelio Gonzalez
Turkish Journal of Electrical Engineering and Computer Sciences
The impact of the pandemic caused by COVID-19 has been immense in all fields of human activity. In most of the affected countries, the authorities have decreed a series of legal measures to try to stop the growth of the disease and the number of people affected by it. These legal measures involved, in most cases, restrictions on the free movement of people and on work and trade activities, new hygiene procedures, and social distancing. In the particular case of Spain, the rapid evolution of the pandemic led to the declaration of a so-called state of alarm and a period …
A 1-Kw Wireless Power Transfer System For Electric Vehicle Charging Withhexagonal Flat Spiral Coil,
2021
TÜBİTAK
A 1-Kw Wireless Power Transfer System For Electric Vehicle Charging Withhexagonal Flat Spiral Coil, Emrullah Aydin, Mehmet Ti̇mur Aydemi̇r
Turkish Journal of Electrical Engineering and Computer Sciences
Wireless power transfer (WPT) technology is getting more attention in these days as a clean, safe, and easy alternative to charging batteries in several power levels. Different coil types and system structures have been proposed in the literature. Hexagonal coils, which have a common usage for low power applications, have not been well studied for high and mid power applications such as in electric vehicle (EV) battery charging. In order to fill this knowledge gap, the self and mutual inductance equations of a hexagonal coil are obtained, and these equations have been used to design a 1 kW WPT system …
A New Classification Method For Encrypted Internet Traffic Using Machine Learning,
2021
TÜBİTAK
A New Classification Method For Encrypted Internet Traffic Using Machine Learning, Mesut Uğurlu, İbrahi̇m Alper Doğru, Recep Si̇nan Arslan
Turkish Journal of Electrical Engineering and Computer Sciences
The rate of internet usage in the world is over 62% and this rate is increasing day by day. With this increase, it becomes important to ensure the confidentiality of the information in the traffic flowing over the internet. Encryption algorithms and protocols are used for this purpose. This situation, which is beneficial for normal users, is also used by attackers to hide. Cyber attackers or hackers gain the ability to bypass security precautions such as IDS/IPS and antivirus systems with using encrypted traffic. Since payload analysis cannot be performed without deciphering the encrypted traffic, existing commercial security solutions fall …
Design Development And Performance Analysis Of Distributed Least Square Twinsupport Vector Machine For Binary Classification,
2021
TÜBİTAK
Design Development And Performance Analysis Of Distributed Least Square Twinsupport Vector Machine For Binary Classification, Bakshi Rohit Prasad, Sonali Agarwal
Turkish Journal of Electrical Engineering and Computer Sciences
Machine learning (ML) on Big Data has gone beyond the capacity of traditional machines and technologies. ML for large scale datasets is the current focus of researchers. Most of the ML algorithms primarily suffer from memory constraints, complex computation, and scalability issues.The least square twin support vector machine (LSTSVM) technique is an extended version of support vector machine (SVM). It is much faster as compared to SVM and is widely used for classification tasks. However, when applied to large scale datasets having millions or billions of samples and/or large number of classes, it causes computational and storage bottlenecks. This paper …
Robust And Efficient Ebg-Backed Wearable Antenna For Ism Applications,
2021
TÜBİTAK
Robust And Efficient Ebg-Backed Wearable Antenna For Ism Applications, Ayesha Saeed, Asma Ejaz, Humayun Shahid, Yasar Amin, Hannu Tenhunen
Turkish Journal of Electrical Engineering and Computer Sciences
A structurally compact, semiflexible wearable antenna composed of a distinctively miniaturized electromagnetic band gap (EBG) structure is presented in this work. Designed for body-centric applications in the 5.8 GHz band, the design draws heavily from a novel planar geometry realized on Rogers RT/duroid 5880 laminate with a compact physical footprint spanning lateral dimensions of $0.6$$\lambda$$_0$$\times$$0.06$$\lambda$$_0$. Incorporating a 2$\times$2 EBG structure at the rear of the proposed design ensures sufficient isolation between the body and the antenna, doing away with the performance degradation associated with high permittivity of the tissue layer. The peculiar antenna geometry allows for reduced backward radiation and …
Attention Augmented Residual Network For Tomato Disease Detection Andclassification,
2021
TÜBİTAK
Attention Augmented Residual Network For Tomato Disease Detection Andclassification, Getinet Yilma Abawatew, Seid Belay, Kumie Gedamu, Maregu Assefa, Melese Ayalew, Ariyo Oluwasanmi, Zhiguang Qin
Turkish Journal of Electrical Engineering and Computer Sciences
Deep learning techniques help agronomists efficiently identify, analyze, and monitor tomato health. CNN (convolutional neural network) locality constraint and existing small train sample adversely influenced disease recognition performance. To alleviate these challenges, we proposed a discriminative feature learning attention augmented residual (AAR) network. The AAR network contains a stacked pre-activated residual block that learns deep coarse level features with locality context, whereas the attention block captures salient feature sets while maintaining the global relationship in data points, attention features augment the learning of the residual block. We used conditional variational generative adversarial network (CVGAN) image reconstruction network and augmentation techniques …
Pause For A Cybersecurity Cause: Assessing The Influence Of A Waiting Period On User Habituation In Mitigation Of Phishing Attacks,
2021
Nova Southeastern University
Pause For A Cybersecurity Cause: Assessing The Influence Of A Waiting Period On User Habituation In Mitigation Of Phishing Attacks, Amy Antonucci
CCAC Theses and Dissertations
Social engineering costs organizations billions of dollars a year. Social engineering exploits the weakest link of information security systems, the people who are using them. Phishing is a form of social engineering in which the perpetrator depends on the victim’s instinctual thinking towards an email designed to create a fear or excitement response. It is well-documented in literature that users continue to click on phishing emails costing them and their employers significant monetary resources and data loss. Training does not appear to mitigate the effects of phishing much; other solutions are necessary to mitigate phishing.
Kahneman introduced the concepts of …
