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Corrections To ‘‘Glaciernet: A Deep-Learning Approach For Debris-Covered Glacier Mapping’’, Zhiyuan Xie, Umesh K. Haritashya, Vijayan K. Asari, Brennan W. Young, Michael P. Bishop, Jeffrey S. Kargel 2020 University of Dayton

Corrections To ‘‘Glaciernet: A Deep-Learning Approach For Debris-Covered Glacier Mapping’’, Zhiyuan Xie, Umesh K. Haritashya, Vijayan K. Asari, Brennan W. Young, Michael P. Bishop, Jeffrey S. Kargel

Electrical and Computer Engineering Faculty Publications

In the above article [1], Figure 2 was incorrect. Unfortunately, we mixed the color label of "CONV $\to $ BN $\to $ ReLu" and "Unpooling" in the CNN structure section of Figure 2. The color label of "CONV $\to $ BN $\to $ ReLu" should be orange while the color label of "Unpooling" should be green. Also, the word "Decoder" is misspelled. That same figure with the same error is also used for the graphic abstract. The corrected figure is given here. None of the sections in the figure is modified. The only change is in the color label of …


Development Of The Payload System And Obc Microcontroller Coding For A Cubic Satellite Performing An Additive Self-Repair Experiment In Space, Eduardo Macias-Zugasti 2020 University of Texas at El Paso

Development Of The Payload System And Obc Microcontroller Coding For A Cubic Satellite Performing An Additive Self-Repair Experiment In Space, Eduardo Macias-Zugasti

Open Access Theses & Dissertations

Additive manufacturing, which is also known as three-dimensional printing, in space is one of the most promising technologies advancing current capabilities for in-orbit space manufacturing and assembly. Additive manufacturing contributes to the reduction of cost per kilogram and number of launches, thus facilitating extraterrestrial colonization and deep-space exploration. The state of the art includes advancing efforts inside the International Space Station (ISS). However, the ISS is a controlled environment and, to the best of our knowledge, no spacecraft or satellite has performed additive manufacturing tasks in the extreme environment of outer space. In this work a 1U CubeSat named Orbital …


การสกัดตารางและรายการบนเว็บเป็นอาร์ดีเอฟ, จุลเทพ นันทขว้าง 2020 คณะวิศวกรรมศาสตร์

การสกัดตารางและรายการบนเว็บเป็นอาร์ดีเอฟ, จุลเทพ นันทขว้าง

Chulalongkorn University Theses and Dissertations (Chula ETD)

ทุกวันนี้ ลิงก์เดต้าได้เติบโตเพิ่มขึ้นอย่างรวดเร็วตามการเติบโตของเว็บ นอกเหนือจากข้อมูลใหม่ที่สร้างขึ้นในรูปแบบซีแมนติกโดยเฉพาะ ส่วนหนึ่งมาจากการแปลงข้อมูลโครงสร้างที่มีอยู่ให้อยู่ในรูปแบบของข้อมูลเปิดระดับห้าดาว อย่างไรก็ตามยังคงมีข้อมูลจำนวนมากในรูปแบบโครงสร้างและกึ่งโครงสร้าง ตัวอย่างเช่นตารางและรายการซึ่งเป็นรูปแบบหลักที่มนุษย์ใช้อ่าน ยังรอการแปลงอยู่ งานวิจัยนี้กล่าวถึงงานวิจัยต่าง ๆ ที่เกี่ยวกับการแปลงตารางและรายการมาเป็นข้อมูลในรูปแบบต่าง ๆ เพื่อให้เครื่องสามารถอ่านได้ นอกจากนี้ยังเสนอวิธีการในการแปลงตารางและรายการเป็นรูปแบบ Resource Description Framework และยังคงเก็บโครงสร้างต้นฉบับที่จำเป็นไว้อย่างละเอียด ซึ่งทำให้สามารถที่จะสร้างข้อมูลโครงสร้างเดิมกลับมาได้ ระบบ TULIP ถูกสร้างขึ้นเพื่อเป็นเครื่องมือสำหรับการพัฒนาซีแมนติกเว็บ วิธีการที่เสนอมีความยืดหยุ่นมากกว่าเมื่อเทียบกับงานอื่น ๆ เดต้าโมเดลของ TULIP สามารถรองรับการเก็บข้อมูลต้นฉบับอย่างครบถ้วน และสามารถนำมาแสดงใหม่ในมุมมองที่แตกต่างไปจากเดิม เครื่องมือนี้สามารถใช้สร้างข้อมูลจำนวนมหาศาลสำหรับเครื่องคอมพิวเตอร์เพื่อให้ใช้งานได้กว้างมากขึ้นกว่าเดิม


การสรุปใจความสำคัญของข้อความแบบสกัดสำหรับข่าวท่องเที่ยวภาษาไทย, ศรัญญา นาทองห่อ 2020 คณะวิศวกรรมศาสตร์

การสรุปใจความสำคัญของข้อความแบบสกัดสำหรับข่าวท่องเที่ยวภาษาไทย, ศรัญญา นาทองห่อ

Chulalongkorn University Theses and Dissertations (Chula ETD)

ปัจจุบันเทคโนโลยีทางด้านคอมพิวเตอร์มีความสำคัญต่อการดำเนินชีวิตประจำวันของมนุษย์เป็นอย่างมากและยังถือว่าเป็นเครื่องมือที่ใช้ในการอำนวยความสะดวกให้แก่มนุษย์มากมายโดยเฉพาะทางด้านการสื่อสารผ่านสังคมออนไลน์ เพื่อลดเวลาในการอ่านข่าวหรืออ่านบทความและข่าวออนไลน์ต่างๆ จากการวิจัยที่ผ่านมามีการศึกษาและพัฒนาการสรุปใจความสำคัญของภาษาไทยเป็นจำนวนมาก ในงานวิจัยนี้ได้นำเสนอวิธีการสรุปใจความสำคัญจากข่าวการท่องเที่ยวภาษาไทย 2 วิธีคือการเลือกประโยคจากการจัดกลุ่มประโยคด้วยเคมีนและการเลือกประโยคด้วยวิธีหาคำสำคัญประโยคจากหัวข้อข่าว โดยมีการพัฒนาและสร้างคลังข้อมูลรายการคำประสมเพื่อช่วยเพิ่มประสิทธิภาพในการตัดคำ โดยการทดลองนี้ใช้ข้อมูลข่าวการท่องเที่ยวไทย ทั้งหมด 400 ข่าวสำหรับใช้ทดลองในการสรุปใจความสำคัญ และ 5,000 ข่าวสำหรับการสร้างคลังข้อมูลรายการคำประสม การวัดประสิทธิภาพของวิธีการที่นำเสนอ มีการวัดประสิทธิภาพการสรุปใจความสำคัญโดยการเปรียบเทียบผลจากการสรุปที่ได้จากผู้เชี่ยวชาญด้านภาษาไทยเทียบกับผลสรุปที่ได้จากวิธีการที่นำเสนอ จากงานวิจัยนี้ในขั้นตอนการสร้างคำประสมได้คำประสมทั้งหมด จำนวน 2,340 คำ ผลการทดลองพบว่าวิธีตัดคำด้วยคัตคำร่วมกับตัดคำประสมได้ผลดีกว่าการตัดคำจากคัตคำเพียงอย่างเดียว และการสรุปใจความสำคัญโดยใช้การคำนวณค่าน้ำหนักของคำสำคัญโดยหาค่าความถี่ของคำจากหัวข้อข่าวเพียงอย่างเดียวและเลือกประโยคเรียงลำดับจากผลรวมความถี่ของคำสำคัญจากหัวข้อข่าวมีประสิทธิภาพและความแม่นยำสูงสุดโดยมีค่าความแม่นยำ ค่าความระลึกและค่าวัดประสิทธิภาพอยู่ที่ 0.8097 0.8367 และ 0.8216 ตามลำดับและเมื่อใช้คัตคำร่วมกับการตัดคำแบบเอ็นแกรมโดยวิธีการสรุปใจความสำคัญแบบเดียวกันได้ค่าความแม่นยำ ค่าความระลึกและค่าวัดประสิทธิภาพอยู่ที่ 0.8119 0.8398 และ 0.8242 ตามลำดับที่อัตราการบีบอัดร้อยละ 20


Semantic Segmentation Using Modified U-Net Architecture For Crack Detection, Michael Sun 2020 South Dakota State University

Semantic Segmentation Using Modified U-Net Architecture For Crack Detection, Michael Sun

Electronic Theses and Dissertations

The visual inspection of a concrete crack is essential to maintaining its good condition during the service life of the bridge. The visual inspection has been done manually by inspectors, but unfortunately, the results are subjective. On the other hand, automated visual inspection approaches are faster and less subjective. Concrete crack is an important deficiency type that is assessed by inspectors. Recently, various Convolutional Neural Networks (CNNs) have become a prominent strategy to spot concrete cracks mechanically. The CNNs outperforms the traditional image processing approaches in accuracy for the high-level recognition task. Of them, U-Net, a CNN based semantic segmentation …


Kernel-Controlled Dqn Based Cnn Pruning For Model Compression And Acceleration, Romancha Khatri 2020 South Dakota State University

Kernel-Controlled Dqn Based Cnn Pruning For Model Compression And Acceleration, Romancha Khatri

Electronic Theses and Dissertations

Apart from the accuracy, the size of convolutional neural networks (CNN) models is another principal factor for facilitating the deployment of models on memory, power and budget constrained devices. However, conventional model compression techniques require human experts to setup parameters to explore the design space which is suboptimal and time consuming. Various pruning techniques are implemented to gain compression, trading off speed and accuracy. Given a CNN model [11], we propose an automated deep reinforcement learning [9] based model compression technique that can effectively turned off kernels on each layer by observing its significance on decision making. By observing accuracy, …


Determinants Of Startup Funding: The Interaction Between Web Attention And Culture, Jie Ren, Viju Raghupathi, Wullianallur Raghupathi 2020 Fordham University

Determinants Of Startup Funding: The Interaction Between Web Attention And Culture, Jie Ren, Viju Raghupathi, Wullianallur Raghupathi

Journal of International Technology and Information Management

Technology empowers entrepreneurs to pursue alternative funding through platforms like crowdfunding. This research explores significant startup funding factors using Crunchbase. Controlling for common factors (acquisition/funding-rounds/IPO), the research uniquely focuses on web attention - the visibility on social media - and its impact on funding. It also examines the moderating influence of startup’s home country culture (individualism/collectivism). Findings show stronger positive impact of web attention on startup funding for collectivist countries. While individualistic investors value personal goals, collectivists value collaborative goals - inclinations that align with crowdfunding behavior. Therefore while increasing web attention, crowdfunding efforts can be targeted towards collectivist countries.


Food Printing: Evolving Technologies, Challenges, Opportunities, And Best Adoption Strategies, Sharmin Attarin, Mohsen Attaran 2020 Bryant University

Food Printing: Evolving Technologies, Challenges, Opportunities, And Best Adoption Strategies, Sharmin Attarin, Mohsen Attaran

Journal of International Technology and Information Management

3D printing is a process of making three-dimensional objects using additive processes where layers are laid down in succession to create a complete object. Companies across the globe are actively piloting and leveraging the inherent benefits of 3D printing technology. Today, 3D printing can revolutionize food innovation and production through better creativity, customizability, and sustainability. This article highlights 3D printing evolving technologies and trends and identifies its applications and implementation challenges. In this paper, we conducted a literature review to explore 3D printing's current technologies and applications in the food industry, including its advantages, its potential implications, and its obstacles …


Evaluating Students Information System Success Using Delone And Mclean’S Model: Student’S Perspective, Majaliwa Mkinga, Herman Mandari 2020 Tanzania National Roads Agency

Evaluating Students Information System Success Using Delone And Mclean’S Model: Student’S Perspective, Majaliwa Mkinga, Herman Mandari

Journal of International Technology and Information Management

System success is considered to be an important element in accomplishing the goals of the organization; therefore evaluation of system success needs to be done in order to ensure that investment in Information System is successful. Most of Higher Learning Institutions (HLIs) in Tanzania have adopted the use of IS in providing service to their customers. Nevertheless, there is less evidence that system success evaluation has been done in order to identify the desired characteristics which could make IS more effective. Due to that, this study evaluates the effectiveness of Student Information System (SIS) used at the Institute of Finance …


An Integrated View Of Data: Application Of Knowledge Modeling To Data Management, Sung-kwan Kim, Wenjun Wang 2020 University of Arkansas at Little Rock

An Integrated View Of Data: Application Of Knowledge Modeling To Data Management, Sung-Kwan Kim, Wenjun Wang

Journal of International Technology and Information Management

Data management has become an important challenge. Good data management requires an effective approach to collecting, storing, and accessing data across the enterprise. In this paper, a knowledge modeling approach to data management is introduced with an emphasis on data requirements analysis. A knowledge model can provide a high-level view of organizational data by specifying the structure and relationships of the knowledge contents used in business processes. The proposed knowledge modeling approach is business process oriented and decision oriented. The description of the knowledge contents in the model is based on ontological specification. The model is comprised of five elements: …


Uga’S Alexander Campbell King Law Library: Phasing In Inclusive Usability Testing, Rachel S. Evans, Marie Mize, Jason Tubinis 2020 University of Georgia School of Law

Uga’S Alexander Campbell King Law Library: Phasing In Inclusive Usability Testing, Rachel S. Evans, Marie Mize, Jason Tubinis

Articles, Chapters and Online Publications

For years we have offered our EBSCO discovery layer service (EDS) as a secondary search tool in addition to our traditional online catalog (GAVEL) linking to both from the library website. However, the traditional catalog search, also known as “Classic GAVEL”, is always listed first while EDS, also known as “GAVEL & Beyond”, is listed second. Although maintenance has continued for populating EDS with library records on a daily basis, customization for this interface and sharing it with our users has not been prioritized. Before making any decisions related to changing the primary location our users experience when searching the …


Deep Learning For Digitized Histology Image Analysis, Sudhir Sornapudi 2020 Missouri University of Science and Technology

Deep Learning For Digitized Histology Image Analysis, Sudhir Sornapudi

Doctoral Dissertations

“Cervical cancer is the fourth most frequent cancer that affects women worldwide. Assessment of cervical intraepithelial neoplasia (CIN) through histopathology remains as the standard for absolute determination of cancer. The examination of tissue samples under a microscope requires considerable time and effort from expert pathologists. There is a need to design an automated tool to assist pathologists for digitized histology slide analysis. Pre-cervical cancer is generally determined by examining the CIN which is the growth of atypical cells from the basement membrane (bottom) to the top of the epithelium. It has four grades, including: Normal, CIN1, CIN2, and CIN3. In …


Trajectory Control Of A Wheeled Robot Using Interaction Forces For Intuitive Overground Human-Robot Interaction, George Leno Holmes Jr. 2020 Missouri University of Science and Technology

Trajectory Control Of A Wheeled Robot Using Interaction Forces For Intuitive Overground Human-Robot Interaction, George Leno Holmes Jr.

Doctoral Dissertations

"Effective and intuitive physical human robot interaction (pHRI) requires an understanding of how humans communicate movement intentions with one another. It has been suggested that humans can guide another human by hand through complex tasks using force information only. However, no clear and applicable paradigm has been set forth to understand these relationships. While the human partner can readily understand and adhere to this expectation, it would be difficult for anyone to explain their intuitive motions with strict rules, algorithms, or steps. Uncovering such a procedural framework for the control of robotic systems to execute expected performance simply from force …


Leveraging Peer-To-Peer Energy Sharing For Resource Optimization In Mobile Social Networks, Aashish Dhungana 2020 Virginia Commonwealth University

Leveraging Peer-To-Peer Energy Sharing For Resource Optimization In Mobile Social Networks, Aashish Dhungana

Theses and Dissertations

Mobile Opportunistic Networks (MSNs) enable the interaction of mobile users in the vicinity through various short-range wireless communication technologies (e.g., Bluetooth, WiFi) and let them discover and exchange information directly or in ad hoc manner. Despite their promise to enable many exciting applications, limited battery capacity of mobile devices has become the biggest impediment to these appli- cations. The recent breakthroughs in the areas of wireless power transfer (WPT) and rechargeable lithium batteries promise the use of peer-to-peer (P2P) energy sharing (i.e., the transfer of energy from the battery of one member of the mobile network to the battery of …


Benefits, Drawbacks, And Risks Of Ai, James M. Donovan 2020 University of Kentucky College of Law

Benefits, Drawbacks, And Risks Of Ai, James M. Donovan

Law Faculty Books and Chapters

The specter of the impact of artificial intelligence [AI] on law and legal education casts a long and uncertain shadow. Its mix of enthusiasm and trepidation can arise from a thin idea of what the label refers to. Four components differentiate AI from even high-end automation: Big data and predictive analytics, deep learning software, cloud computing, and natural language process. From the perspective of the person on the street though, is captured as “the art of creating machines that perform functions that require intelligence when performed by people,” centering on the ability to make independent choices. While that gloss may …


Two Novel Radar Detectors For Spiky Sea Clutter With The Presence Of Thermal Noise And Interfering Targets, NOUH GUIDOUM, FAOUZI SOLTANI, AMAR MEZACHE 2020 TÜBİTAK

Two Novel Radar Detectors For Spiky Sea Clutter With The Presence Of Thermal Noise And Interfering Targets, Nouh Guidoum, Faouzi Soltani, Amar Mezache

Turkish Journal of Electrical Engineering and Computer Sciences

In the context of noncoherent detection and high-resolution maritime radar system with low grazing angle, new Constant False Alarm Rate (CFAR) decision rules are suggested for two Compound Gaussian (CG) clutters namely: The K distribution and the Compound Inverse Gaussian (CIG) distribution, which are considered among the most appropriate models for sea clutter. The proposed decision rules are then modified to deal with the presence of thermal noise and interfering targets. The proposed detectors are investigated on the basis of synthetic data as well as real data of the IPIX radar database. The obtained results exhibit a high probability of …


Detection Of Hand Osteoarthritis From Hand Radiographs Using Convolutionalneural Networks With Transfer Learning, KEMAL ÜRETEN, HASAN ERBAY, HADİ HAKAN MARAŞ 2020 TÜBİTAK

Detection Of Hand Osteoarthritis From Hand Radiographs Using Convolutionalneural Networks With Transfer Learning, Kemal Üreten, Hasan Erbay, Hadi̇ Hakan Maraş

Turkish Journal of Electrical Engineering and Computer Sciences

Osteoarthritis is the most common type of arthritis. Hand osteoarthritis leads to specific structural changes in the joints, such as asymmetric joint space narrowing and osteophytes (bone spurs). Conventional radiography has traditionally been the primary method of visualizing these structural changes and diagnosing osteoarthritis. We aimed to develop a computerized method that is capable of determining the structural changes seen in radiography of the hand and to assist practitioners in interpreting radiographic changes and diagnosing the disease. In this retrospective study, transfer-learning-based convolutional neural networks were trained on a randomly selected dataset containing 332 radiography images of hands from an …


Scalable, Pluggable, And Fault Tolerant Multi-Modal Situational Awareness Data Stream Management Systems, Michael Partin 2020 Wright State University

Scalable, Pluggable, And Fault Tolerant Multi-Modal Situational Awareness Data Stream Management Systems, Michael Partin

Browse all Theses and Dissertations

Features and attributes that describe an event (disasters, social movements, etc.) are heterogeneous in nature. For virtually all events that impact humans, technology enables us to capture a large amount and variety of data from many sources, including humans (i.e., social media) and sensors/internet of things (IoTs). The corresponding modalities of data include text, imagery, voice and video, along with structured data such as gazetteers (i.e., location-based data) and government and statistical data. However, even though there is often an abundance of information produced, this information is fragmented across the various modalities and sources. The DisasterRecord system aims to provide …


Past To Present (P2p): Road Thermal Image Colorization, Yuseong Park 2020 South Dakota State University

Past To Present (P2p): Road Thermal Image Colorization, Yuseong Park

Electronic Theses and Dissertations

Thermal image colorization into realistic RGB image is a challenging task. Thermal cameras are easily to detect objects in particular situation (e.g. darkness and fog) that the human eyes cannot detect. However, it is difficult to interpret the thermal image with human eyes. Enhancing thermal image colorization is an important task to improve these areas. The results of the existing colorization method still have color ambiguities, distortion, and blurriness problems. This paper focused on thermal image colorization using pix2pix network architecture based on Generative Adversarial Net (GAN). Pix2pix is a model that transforms thermal image into RGB image, but our …


Context-Aware System For Glycemic Control In Diabetic Patients Using Neural Networks, OWAIS BHAT, DAWOOD A. KHAN 2020 TÜBİTAK

Context-Aware System For Glycemic Control In Diabetic Patients Using Neural Networks, Owais Bhat, Dawood A. Khan

Turkish Journal of Electrical Engineering and Computer Sciences

Diabetic patients are quite hesitant in engaging in normal physiological activities due to difficulties associated with diabetes management. Over the last few decades, there have been advancements in the computational power of embedded systems and glucose sensing technologies. These advancements have attracted the attention of researchers around the globe developing automatic insulin delivery systems. In this paper, a method of closed-loop control of diabetes based on neural networks is proposed. These neural networks are used for making predictions based on the clinical data of a patient. A neural network feedback controller is also designed to provide a glycemic response by …


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