Use Of Virtual Reality Technology In Medical Training And Patient Rehabilitation,
2019
Wright State University
Use Of Virtual Reality Technology In Medical Training And Patient Rehabilitation, Sankalp Mishra
Browse all Theses and Dissertations
Coaching patients to follow the rehabilitation routines correctly and timely after surgery is often a challenge due to the limited medical knowledge of patients and limited availability of clinicians. Similarly, it is also a challenge to train medical professionals with both the technical and communication skills required in their practices. The recent emergence of VR technologies shines the light on improving the current training practices. In this thesis research, I will look at the development and application of VR-based immersive training games for two particular cases: 1. Post hand surgery rehab; and, 2. Training for Social determinants of health (SDOH) …
Artificial Intelligence In The Assessment Of Transmission And Distribution Systems Under Natural Disasters Using Machine Learning And Deep Learning Techniques In A Knowledge Discovery Framework,
2019
University of Texas at El Paso
Artificial Intelligence In The Assessment Of Transmission And Distribution Systems Under Natural Disasters Using Machine Learning And Deep Learning Techniques In A Knowledge Discovery Framework, Rossana Villegas
Open Access Theses & Dissertations
Warming trends and increasing temperatures have been observed and reported by federal agencies, such as the National Oceanic and Atmospheric Administration (NOAA). Extreme-weather events, especially hurricanes, tornadoes and winter storms, are among the highly devastating natural disasters responsible for massive and prolonged power outages in Electrical Transmission and Distribution Systems (ETDS). Moreover, the failure rate probability of any system component under extreme-weather tends to increase in the impacted geographic area. This Dissertation proposes an Artificial Intelligence (AI) Decision Support System that can predict damage in the ETDS and allow operators to mitigate disastrous extreme weather events. The document reports the …
Active Recall Networks For Multiperspectivity Learning Through Shared Latent Space Optimization,
2019
University of Dayton
Active Recall Networks For Multiperspectivity Learning Through Shared Latent Space Optimization, Theus Aspiras, Ruixu Liu, Vijayan K. Asari
Electrical and Computer Engineering Faculty Publications
Given that there are numerous amounts of unlabeled data available for usage in training neural networks, it is desirable to implement a neural network architecture and training paradigm to maximize the ability of the latent space representation. Through multiple perspectives of the latent space using adversarial learning and autoencoding, data requirements can be reduced, which improves learning ability across domains. The entire goal of the proposed work is not to train exhaustively, but to train with multiperspectivity. We propose a new neural network architecture called Active Recall Network (ARN) for learning with less labels by optimizing the latent space. This …
Blockchain-Based Healthcare: Three Successful Proof-Of-Concept Pilots Worth Considering,
2019
Univ of New Brunswick Fredericton
Blockchain-Based Healthcare: Three Successful Proof-Of-Concept Pilots Worth Considering, Rebecca Angeles
Journal of International Technology and Information Management
This paper features the use of blockchain technology in the healthcare industry, with special focus on healthcare data exchange and interoperability; drug supply chain integrity and remote auditing; and clinical trials and population health research. This study uses the research method of analyzing the published case studies, academic articles, trade articles, and videos on MEDRec, Patientory, and the AmerisourceBergen/Merck alliance with SAP/CryptoWerk. The “blockchain” concept was introduced around October 2008 when a proposal for the virtual currency, bitcoin, was offered. Blockchain is a much broader concept than bitcoin and has the following key attributes: distributed database; peer-to-peer transmission; transparency with …
Neuroengineering Of Clustering Algorithms,
2019
Missouri University of Science and Technology
Neuroengineering Of Clustering Algorithms, Leonardo Enzo Brito Da Silva
Doctoral Dissertations
"Cluster analysis can be broadly divided into multivariate data visualization, clustering algorithms, and cluster validation. This dissertation contributes neural network-based techniques to perform all three unsupervised learning tasks. Particularly, the first paper provides a comprehensive review on adaptive resonance theory (ART) models for engineering applications and provides context for the four subsequent papers. These papers are devoted to enhancements of ART-based clustering algorithms from (a) a practical perspective by exploiting the visual assessment of cluster tendency (VAT) sorting algorithm as a preprocessor for ART offline training, thus mitigating ordering effects; and (b) an engineering perspective by designing a family of …
ระบบการจัดการมูลค่าข้อมูลจากเกมสู่เกมด้วยบล็อกเชน,
2019
คณะวิศวกรรมศาสตร์
ระบบการจัดการมูลค่าข้อมูลจากเกมสู่เกมด้วยบล็อกเชน, ชานน ยาคล้าย
Chulalongkorn University Theses and Dissertations (Chula ETD)
แม้ว่าในปัจจุบันบล็อกเชนจะถูกนำมาใช้ประโยชน์ในหลายอุตสาหกรรม แต่ในอุตสาหกรรมเกมนั้น บล็อกเชนไม่ได้ถูกนำไปใช้อย่างกว้างขวางมากนัก นอกจากนี้ แม้ว่าในอุสาหกรรมเกมจะมีผู้เล่นอยู่เป็นจำนวนมาก แต่ก็ยังไม่มีเกมหรือแพลตฟอร์มใดที่ให้สิทธิผู้เล่นในการเป็นเจ้าของสินทรัพย์หรือข้อมูลภายในเกมอย่างแท้จริง โดยแม้จะมีความพยายามในการระดมทุนเพื่อทำเกมหรือแพลตฟอร์มที่ให้ผู้เล่นได้มีโอกาสเป็นเจ้าของสินทรัพย์หรือข้อมูลภายในเกมอยู่บ้าง แต่ก็ยังคงอยู่ในขั้นตอนการทดลองที่ยังไม่เสร็จสมบูรณ์ และผู้เล่นยังต้องพึ่งพาระบบนิเวศน์ของแพลตฟอร์มนั้น ๆ อีกด้วย ในวิทยานิพนธ์ฉบับนี้ ผู้วิจัยจึงประสงค์ที่จะนำเสนอสถาปัตยกรรมกลางที่ทำให้ผู้เล่นเกมสามารถเป็นเจ้าของเวลาที่ตนเองใช้ภายในเกมได้โดยใช้บล็อกเชนสาธารณะ ทั้งผู้เล่นยังสามารถนำเวลาดังกล่าวไปใช้ในเกมอื่นได้ด้วย โดยใช้มาตราฐานโทเคนดิจิทัล ERC-20 บนอีเธอเรี่ยม นอกจากนี้ รูปแบบสถาปัตยกรรมที่นำเสนอดังกล่าวยังสามารถประยุกต์ใช้ได้กับทุกบล็อกเชนสาธารณะ และยังเป็นประโยชน์ต่อทุกองค์ประกอบของระบบนิเวศน์ อาทิเช่น ผู้เล่น บล็อกเชนโหนด และผู้พัฒนาเกม โดยผลการทดลองในงานวิทยานิพนธ์นี้ ยังแสดงว่าแนวความคิดดังกล่าวทำให้ผู้เล่นใช้เวลาในการเล่นเกมนานขึ้น และมีแนวโน้มที่จะอยากเล่นเกมใหม่ๆ ที่สามารถนำมูลค่าในเกมเดิมไปใช้ได้ แต่ทั้งนี้ยังมีปัจจัยหลายอย่างที่มีผล อาทิเช่น ประเภทของเกม การแลกเปลี่ยนค่าของเวลาภายในเกม เป็นต้น
Thai Scene Text Recognition,
2019
Faculty of Engineering
Thai Scene Text Recognition, Thananop Kobchaisawat
Chulalongkorn University Theses and Dissertations (Chula ETD)
Automatic scene text detection and recognition can benefit a large number of daily life applications such as reading signs and labels, and helping visually impaired persons. Reading scene text images becomes more challenging than reading scanned documents in many aspects due to many factors such as variations of font styles and unpredictable lighting conditions. The problem can be decomposed into two sub-problems: text localization and text recognition. The proposed scene text localization works at the pixel level combined with a new text representation and a fully-convolutional neural network. This method is capable of detecting arbitrary shape texts without language limitations. …
Enabling Space Time Division Multiple Access In Ietf 6tisch Protocol,
2019
TÜBİTAK
Enabling Space Time Division Multiple Access In Ietf 6tisch Protocol, Sedat Görmüş, Sercan Külcü
Turkish Journal of Electrical Engineering and Computer Sciences
IETF 6TiSCH standard aims to create reliable, deterministic, and low-power networks by scheduling bandwidth resources in time and frequency domains. The main emphasis of 6TiSCH protocol is that it creates Internet of things (IoT) networks with a deterministic and controllable delay. However, many of its benefits are tied to the ability of the 6TiSCH scheduler to optimally distribute radio resources among wireless nodes which may not be possible when the number of frequency resources are limited and several other wireless technologies share the same frequency band (e.g., WiFi, Bluetooth and IEEE 802.15.4). Here the integration of a low-complexity directional antenna …
Stegogis: A New Steganography Method Using The Geospatial Domain,
2019
TÜBİTAK
Stegogis: A New Steganography Method Using The Geospatial Domain, Ömer Kurtuldu, Mehmet Demi̇rci̇
Turkish Journal of Electrical Engineering and Computer Sciences
Geographic data are used on a variety of computing devices for many different applications including navigation, tracking, location planning, and marketing. The prevalence of geographic data makes it possible to envision new useful applications. In this paper, we propose using geographic data as a medium for secret communication, or steganography. We develop a method called StegoGIS for hiding messages in geographic coordinates in the well-known binary of fast-moving objects and transmitting them secretly. We show that discovering this secret communication is practically impossible for third parties. We also show that a large amount of secret data can be transmitted this …
Improving Undersampling-Based Ensemble With Rotation Forest For Imbalanced Problem,
2019
TÜBİTAK
Improving Undersampling-Based Ensemble With Rotation Forest For Imbalanced Problem, Huaping Guo, Xiaoyu Diao, Hongbing Liu
Turkish Journal of Electrical Engineering and Computer Sciences
As one of the most challenging and attractive issues in pattern recognition and machine learning, the imbalanced problem has attracted increasing attention. For two-class data, imbalanced data are characterized by the size of one class (majority class) being much larger than that of the other class (minority class), which makes the constructed models focus more on the majority class and ignore or even misclassify the examples of the minority class. The undersampling-based ensemble, which learns individual classifiers from undersampled balanced data, is an effective method to cope with the class-imbalance data. The problem in this method is that the size …
The Social Presence Of Jibo,
2019
Northern Illinois University
The Social Presence Of Jibo, Parisa Farhadi
Graduate Research Theses & Dissertations
This research is an attempt to investigate how a social robot is perceived by users at the first encounter. And to find out whether a social robot like Jibo is understood merely as a kind of a technological object or a social entity. Previous studies in Human-Robot Interaction have considered social presence as a mediator in users’ social responses toward robots; however, the focus of this study is the social presence itself and investigates whether Jibo produces a sense of presence during initial encounters. To this end, the current study examines individuals’ perceptions of and responses to Jibo. Participants (N=8) …
A Graph-Based Reinforcement Learning Method With Converged State Exploration And Exploitation,
2019
Wenzhou University
A Graph-Based Reinforcement Learning Method With Converged State Exploration And Exploitation, Han Li, Tianding Chen, Hualiang Teng, Yingtao Jiang
Civil and Environmental Engineering and Construction Faculty Research
In any classical value-based reinforcement learning method, an agent, despite of its continuous interactions with the environment, is yet unable to quickly generate a complete and independent description of the entire environment, leaving the learning method to struggle with a difficult dilemma of choosing between the two tasks, namely exploration and exploitation. This problem becomes more pronounced when the agent has to deal with a dynamic environment, of which the configuration and/or parameters are constantly changing. In this paper, this problem is approached by first mapping a reinforcement learning scheme to a directed graph, and the set that contains all …
Improve Operating Room Utilization Through Distributed Scheduling Workflow And Automation,
2019
Wright State University
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 …
Evaluation Of Suas Education And Training Tools,
2019
Embry-Riddle Aeronautical University
Evaluation Of Suas Education And Training Tools, Brent Terwilliger, Scott Burgess, James Solti, Kristine Kiernan, Christian Janke, Andrew Shepherd
Publications
The wide distribution and demographic composition of students seeking small unmanned aircraft system (sUAS) education presents a need to fully understand the capabilities, limitations, and dependencies of effective training tools. Concepts, practices, and technologies associated with modeling and simulation, immersive gaming, augmented and mixed-reality, and remote operation have demonstrated efficacy to support engaged student learning and objective satisfaction. Identification and comparison of key attributes critical to an aviation educational framework, such as competency-based training, enables educational designers to identify those tools with the highest potential to support successful learning. A series of factors, such as system performance, regulatory compliance, environmental …
Deep Temporal Convolutional Networks For Short-Term Traffic Flow Forecasting,
2019
Nanjing Tech University
Deep Temporal Convolutional Networks For Short-Term Traffic Flow Forecasting, Wentian Zhao, Yanyun Gao, Tingxiang Ji, Xili Wan, Feng Ye, Guangwei Bai
Electrical and Computer Engineering Faculty Publications
To reduce the increasingly congestion in cities, it is essential for intelligent transportation system (ITS) to accurately forecast the short-term traffic flow to identify the potential congestion sites. In recent years, the emerging deep learning method has been introduced to design traffic flow predictors, such as recurrent neural network (RNN) and long short-term memory (LSTM), which has demonstrated its promising results. In this paper, different from existing work, we study the temporal convolutional network (TCN) and propose a deep learning framework based on TCN model for short-term city-wide traffic forecast to accurately capture the temporal and spatial evolution of traffic …
Development Of Semantic Scene Conversion Model For Image-Based Localization At Night,
2019
South Dakota State University
Development Of Semantic Scene Conversion Model For Image-Based Localization At Night, Dongyoun Kim
Electronic Theses and Dissertations
Developing an autonomous vehicle navigation system invariant to illumination change is one of the biggest challenges in vision-based localization field due to the fact that the appearance of an image becomes inconsistent under different light conditions even with the same location. In particular, the night scene images have greatest change in appearance compared to the according day scenes. Moreover, the night images do not have enough information in Image-based localization. To deal with illumination change, image conversion methods have been researched. However, these methods could lose the detail of objects and add fake objects into the output images. In this …
Edge Heterogeneous Hardware Evaluation Based On Real Connected And Autonomous Vehicles (Cavs) Workloads,
2019
Wayne State University
Edge Heterogeneous Hardware Evaluation Based On Real Connected And Autonomous Vehicles (Cavs) Workloads, Mustafa Ahmad
Research Opportunities for Engineering Undergraduates (ROEU) Program 2018-19
There has recently been a wide expansion of hardware to assist in autonomous driving tasks. On this project, we focus on using some state-of-the-art deep learning workloads in connected autonomous vehicle (CAV) scenarios,such as object detection and object tracking to evaluate the heterogeneous hardware.
Pv-Based Off-Board Electric Vehicle Battery Charger Using Bidc,
2019
TÜBİTAK
Pv-Based Off-Board Electric Vehicle Battery Charger Using Bidc, Ankita Paul, Krithiga Subramanian, Sujitha N
Turkish Journal of Electrical Engineering and Computer Sciences
In recent years, the use of renewable energy sources is increasing drastically in several sectors, which leads to its role in the automobile industry to charge electric vehicle (EV) batteries. In this paper, a photovoltaic (PV) array-fed off-board battery charging system using a bidirectional interleaved DC-DC converter (BIDC) is proposed for light-weight EVs. This off-board charging system is capable of operating in dual mode, thereby supplying power to the EV battery from the PV array in standstill conditions and driving the DC load by the EV battery during running conditions. This dual mode operation is accomplished by the use of …
A Control Scheme For Maximizing The Delivered Power To The Load In A Standalonewind Energy Conversion System,
2019
TÜBİTAK
A Control Scheme For Maximizing The Delivered Power To The Load In A Standalonewind Energy Conversion System, Saeed Heshmatian, Davood A. Khaburi, Mahyar Khosravi, Ahad Kazemi
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, a control scheme is proposed for maximum power point tracking (MPPT) in a variable speed standalone wind energy conversion system (WECS) with permanent magnet synchronous generator. A MPPT algorithm is designed trying to eliminate the main deficiency of the conventional perturbation and observation (P&O) method, which is the challenge of choosing a proper step size and the unwanted trade-off between accuracy and speed. The designed algorithm properly addresses this drawback and significantly improves the MPPT performance. Another important issue is to ensure fast and accurate tracking of the optimal reference point obtained from the MPPT algorithm and …
Community Detection In Complex Networks Using A New Agglomerative Approach,
2019
TÜBİTAK
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 …
