Computer Engineering Commons^™

การปรับปรุงการแยกฉากหลังบนพื้นหลังสีเขียวไม่สม่ำเสมอแบบทันที, วรายุ จริยาวัฒนรัตน์

Chulalongkorn University Theses and Dissertations (Chula ETD)

วัตถุประสงค์หลักของงานวิจัยนี้คือปรับปรุงการแยกฉากหลังบนพื้นหลังสีเขียวที่ไม่สม่ำเสมอแบบทันที ในวิธีการพื้นฐาน แต่ละพิกเซลจะถูกคำนวณว่าเป็นฉากหลังโดยใช้ค่าขีดจำกัดเดียวกันทั้งภาพเพียง 2 ค่า แต่ในความเป็นจริง วิธีการนี้มีปัญหาในหลาย ๆ กรณี เช่น พื้นหลังไม่ได้เป็นสีเดียวกันทั้งหมด หรือมีเงาของนักแสดงทอดลงไปที่พื้นหลัง เป็นต้น ดังนั้นการใช้ค่าขีดจำกัดเดียวกันหมดทั้งภาพจึงไม่เหมาะสมสำหรับกรณีดังกล่าว งานวิจัยนี้จึงใช้การประมาณความหนาแน่นเคอร์เนลมาช่วยในการหาค่าขีดจำกัดของแต่ละพิกเซลในภาพ เพื่อให้ทุก ๆ พิกเซลในภาพมีขีดจำกัดที่เหมาะสม และยังมีความเร็วในการประมวลผลที่สามารถออกอากาศสดได้ที่ 60 เฟรมต่อวินาที สำหรับความละเอียดระดับ Full HD

Epithelium Detection And Cervical Intraepithelial Neoplasia Classification In Digitized Histology Images, Sri Venkata Ravitej Addanki

Masters Theses

“Cervical cancer is one of the most deadly cancers faced by women. It is the second leading cause of cancer death in women aged 20 to 39 years. In order to detect cancer at early stages, pathologists analyze the epithelium region from the cervical histology images. These histology images have a pre-cervical cancer condition called cervical intraepithelial neoplasia (CIN) determined by pathologists. This study deals with automating the process of epithelium detection and epithelium CIN classification in digitized histology images. For epithelium detection, the objective is to detect epithelium regions in microscopy images from non-epithelium regions and background. convolutional neural …

Developing An Energy Efficient Real-Time System, Aamir Aarif Khan

Masters Theses

"Increasing number of battery operated devices creates a need for energy-efficient real-time operating system for such devices. Designing a truly energy-efficient system is a multi-staged effort; this thesis consists of three main tasks that address different aspects of energy efficiency of a real-time system (RTS).

The first chapter introduces an energy-efficient algorithm that alternates processor frequency using DVFS to schedule tasks on cores. Speed profiles is calculated for every task that gives information about how long a task would run for and at what processor speed. We pair tasks with similar speed profiles to give us a resultant merged speed …

Precise Energy Efficient Scheduling Of Mixed-Criticality Tasks & Sustainable Mixed-Criticality Scheduling, Sai Sruti

Masters Theses

"In this thesis, the imprecise mixed-criticality model (IMC) is extended to precise scheduling of tasks, and integrated with the dynamic voltage and frequency scaling (DVFS) technique to enable energy minimization. The challenge in precise scheduling of MC systems is to simultaneously guarantee the timing correctness for all tasks, hi and lo, under both pessimistic and optimistic (less pessimistic) assumptions. To the best of knowledge this is the first work to address the integration of DVFS energy conserving techniques with precise scheduling of lo-tasks of the MC model.

In this thesis, the utilization based schedulability tests and sufficient conditions for such …

Quantitative Fine-Grained Human Evaluation Of Machine Translation Systems: A Case Study On English To Croatian, Filip Klubicka, Antonio Toral, Victor Manuel Sanchez-Cartagena

Articles

This paper presents a quantitative fine-grained manual evaluation approach to comparing the performance of different machine translation (MT) systems. We build upon the well-established Multidimensional Quality Metrics (MQM) error taxonomy and implement a novel method that assesses whether the differences in performance for MQM error types between different MT systems are statistically significant. We conduct a case study for English-to- Croatian, a language direction that involves translating into a morphologically rich language, for which we compare three MT systems belonging to different paradigms: pure phrase-based, factored phrase-based and neural. First, we design an MQM-compliant error taxonomy tailored to the relevant …

Using Moocs To Promote Digital Accessibility And Universal Design, The Moocap Experience, John Gilligan, W. Chen, J. Darzentas

Articles

The recently completed Massive Open Online Course for Accessibility Partnership project (MOOCAP), had the twin aims of establishing a strategic partnership around the promotion of Universal Design and Accessibility for ICT professionals and of developing a suite of Open Educational resources (OERs) in this domain. MOOCAP's eight university partners from Germany, Norway, Greece, Ireland, the UK and Austria have a significant history in developing and providing courses in the domains of Universal Design and Accessibility, as well as leading research and advocacy roles within Europe. The MOOCAP project consisted of two phases: the development of an introductory MOOC on Digital …

Examining The Effects Of A Virtual Character On Learning And Engagement In Serious Games, Vihanga Gamage, Cathy Ennis

Articles

Virtual characters have been employed for many purposes including interacting with players of serious games, with a purpose to increase engagement. These characters are often embodied conversational agents playing diverse roles, such as demonstrators, guides, teachers or interviewers. Recently, much research has been conducted into properties that affect the realism and plausibility of virtual characters, but it is less clear whether the inclusion of interactive agents in serious applications can enhance a user’s engagement with the application, or indeed increase efficacy. In a first step towards answering these questions, we conducted a study where a Virtual Learning Environment was used …

Investigating The Application Of Deep Convolutional Neural Networks In Semi-Supervised Video Object Segmentation, Jayadeep Sasikumar

Dissertations

This thesis investigates the different approaches to video object segmentation and the current state-of-the-art in the discipline, focusing on the different deep learning techniques used to solve the problem. The primary contribution of the thesis is the investigation of usefulness of Exponential Linear Units as activation functions for deep convolutional neural architectures trained to perform object semi-supervised segmentation in videos. Mask R-CNN was chosen as the base convolutional neural architecture, with the view of extending the image segmentation algorithm to videos. Two models were created, one with Rectified Linear Units and the other with Exponential Linear Units as the respective …

Is It Worth It? Budget-Related Evaluation Metrics For Model Selection, Filip Klubicka, Giancarlo Salton, John D. Kelleher

Conference papers

Projects that set out to create a linguistic resource often do so by using a machine learning model that pre-annotates or filters the content that goes through to a human annotator, before going into the final version of the resource. However, available budgets are often limited, and the amount of data that is available exceeds the amount of annotation that can be done. Thus, in order to optimize the benefit from the invested human work, we argue that the decision on which predictive model one should employ depends not only on generalized evaluation metrics, such as accuracy and F-score, but …

Mitigating The Effect Of Misspeculations In Superscalar Processors, Zhaoxiang Jin

Dissertations, Master's Theses and Master's Reports

Modern superscalar processors highly rely on the speculative execution which speculatively executes instructions and then verifies. If the prediction is different from the execution result, a misspeculation recovery is performed. Misspeculation recovery penalties still account for a substantial amount of performance reduction. This work focuses on the techniques to mitigate the effect of recovery penalties and proposes practical mechanisms which are thoroughly implemented and analyzed.

In general, we can divide the misspeculation penalty into four parts: misspeculation detection delay; stale instruction elimination delay; state restoration delay and pipeline fill delay. This dissertation does not consider the detection delay, instead, we …

Applications Of Robot Operating System (Ros) To Mobile Microgrid Formation Outdoors, John Naglak

Dissertations, Master's Theses and Master's Reports

Application of mobile robots to microgrid formation has value for disaster response and service of forward operating bases. This thesis describes the development, testing and demonstration of broad effort across multiple disciplines to enable outdoor positioning and connection of mobile microgrids for the first time. This work includes an outdoor waypoint controller for a UGV agent, specifically the Clearpath Husky. It details sensor fusion of 2D LiDAR and stereo vision, and fusion of odometry sources using an Extended Kalman Filter. Development of these software tools entails integration of many of the packages available through the Robot Operating System (ROS), with …

ระบบนำทางหุ่นยนต์ด้วยหลายตัวนำทางย่อยและหลายแผนที่ย่อย, สุขุม สัตตรัตนามัย

Chulalongkorn University Theses and Dissertations (Chula ETD)

การใช้งานหุ่นยนต์อัตโนมัติในเขตเมืองที่มีความหลากหลายของลักษณะพื้นที่สูงเป็นงานท้าทายที่ต้องการโปรแกรมนำทางและรูปแบบแผนที่ที่แตกต่างกันในแต่ละบริเวณ การปฏิบัติงานของหุ่นยนต์ในโลกจริงต้องเจอกับสิ่งแวดล้อมที่มีการเปลี่ยนแปลงอย่างต่อเนื่อง เช่น ฝนตกหรือความคับคั่งของบริเวณที่ต้องนำทาง ส่งผลให้ต้องปรับแผนเส้นทาง ในงานวิจัยนี้นำเสนอระบบนำทางหุ่นยนต์ในโลกจริงซึ่งเป็นรูปแบบใหม่ของการสลับการทำงานระหว่างโปรแกรมนำทางหลายตัวอย่างเหมาะสม เพื่อให้สามารถจัดการกับพฤติกรรมของหุ่นยนต์และสภาพแวดล้อมที่ท้าทายได้ ระบบที่นำเสนอในงานวิจัยนี้เป็นผลลัพธ์ของการติดตั้งหุ่นยนต์จริงในระบบซึ่งมีผู้ใช้งานและสภาพแวดล้อมจริง

Matrix Effect Study And Immunoassay Detection Using Electrolyte-Gated Graphene Biosensor, Jianbo Sun, Yuxin Liu

Faculty & Staff Scholarship

Significant progress has been made on the development of electrolyte-gated graphene field effect transistor (EGGFET) biosensors over the last decade, yet they are still in the stage of proof-of-concept. In this work, we studied the electrolyte matrix effects, including its composition, pH and ionic strength, and demonstrate that variations in electrolyte matrices have a significant impact on the Fermi level of the graphene channel and the sensitivity of the EGGFET biosensors. This is attributed to the polarization-induced interaction between the electrolyte and the graphene at the interface which can lead to considerable modulation of the Fermi level of the graphene …

An Efficient Method For Online Identification Of Steady State For Multivariate System, Honglun None Xu

Open Access Theses & Dissertations

Most of the existing steady state detection approaches are designed for univariate signals. For multivariate signals, the univariate approach is often applied to each process variable and the system is claimed to be steady once all signals are steady, which is computationally inefficient and also not accurate. The article proposes an efficient online method for multivariate steady state detection. It estimates the covariance matrices using two different approaches, namely, the mean-squared-deviation and mean-squared-successive-difference. To avoid the usage of a moving window, the process means and the two covariance matrices are calculated recursively through exponentially weighted moving average. A likelihood ratio …

Knowing When Not To Answer: Positional Peptide Sequencing With Encoder-Decoder Networks, Korrawe Karunratanakul

Chulalongkorn University Theses and Dissertations (Chula ETD)

การถอดรหัสเปปไทด์นั้นเป็นองค์ประกอบสำคัญสำหรับการศึกษาโปรตีน โดยทั่วไปแล้วการวิเคราะห์ข้อมูล mass spectrum นั้นจะศึกษาเพียงสายของกรดอะมิโนที่ปรากฏอยู่ในฐานข้อมูลเท่านั้น ทำให้การค้นหาสายเปปไทด์แบบใหม่ที่อาจเกิดจากการกลายพันธุ์นั้นทำได้ยาก วิถีการถอดรหัสด้วยดีโนโวแก้ไขข้อจำกัดนี้ด้วยการถอดรหัสสายเปปไทด์โดยตรงจากข้อมูล mass spectrum โดยใช้ความรู้เกี่ยวกับกระบวนการแตกตัวของไอออน ทำให้ไม่จำเป็นต้องใช้ฐานข้อมูลโปรตีนช่วย อย่างไรก็ดี วิธีดังกล่าวยังมีข้อจำกัดด้านความแม่นยำและต้องการการตรวจทานโดยผู้เชี่ยวชาญ วิทยานิพนธ์ฉบับนี้นำเสนอวิธีการถอดรหัสเปปไทด์ด้วยวิธีการดีโนโวแบบใหม่ชื่อ SMSNet โดยใช้โมเดล deep learning เข้าช่วย โดยยังสามารถทำนายกรดอะมิโนได้อย่างครอบคลุมในระดับความแม่นยำของกรดอะมิโนที่ 95% งานฉบับนี้เสนอขั้นตอน ถอดรหัส ตัดออก และสืบค้น เพื่อตัดผลทำนายในตำแหน่งที่มีความกำกวมออกและใช้ข้อมูลจากฐานข้อมูลโปรตีนช่วยเพื่อให้ทำนายสายเปปไทด์ได้ถูกต้องทั้งเส้น นอกจากนี้ งานนี้ได้นำเสนอการใช้ rescorer ในการแก้ไขคะแนนความมั่นใจสำหรับผลทำนายในแต่ละตำแหน่ง ซึ่งส่งผลให้สามารถแยกกลุ่มคะแนนความมั่นใจสำหรับคำตอบที่ถูกต้องและคำตอบที่ผิดได้ดียิ่งขึ้น เมื่อประกอบทุกขั้นตอนวิธีในงานวิจัยฉบับนี้เข้าด้วยกันพบว่า SMSNet สามารถทำนายสายเปปไทด์ได้ในประสิทธิภาพที่ใกล้เคียงกับการทำนายด้วยฐานข้อมูลในการทดลองจริง

Human Performance Modelling For Adaptive Automation, Maria Chiara Leva, M. Wilkins, F. Coster

Conference papers

The relentless march of technology is increasingly opening new possibilities for the application of automation and new horizons for human machine interaction. However there is insufficient scientific evidence on human factors for modern socio-technical systems supporting the guidelines currently used to design Human Machine Interfaces (HMI) (ISA 2014). This dearth of knowledge presents a particular risk in safety critical industries. The continuing 60–90% of accidents currently that are rooted in Human Factors (HF) and the rapid developments in the Internet of Things (IoT) and its novel automation archetypes means that the requirements for new interfaces are becoming more demanding, and …

A Stochastic Petri Net Reverse Engineering Methodology For Deep Understanding Of Technical Documents, Giorgia Rematska

Browse all Theses and Dissertations

Systems Reverse Engineering has gained great attention over time and is associated with numerous different research areas. The importance of this research derives from several technological necessities. Security analysis and learning purposes are two of them and can greatly benefit from reverse engineering. More specifically, reverse engineering of technical documents for deeper automatic understanding is a research area where reverse engineering can contribute a lot. In this PhD dissertation we develop a novel reverse engineering methodology for deep understanding of architectural description of digital hardware systems that appear in technical documents. Initially, we offer a survey on reverse engineering of …

Building An Abstract-Syntax-Tree-Oriented Symbolic Execution Engine For Php Programs, Jin Huang

Browse all Theses and Dissertations

This thesis presents the design, implementation, and evaluation of an abstract-syntax-tree-oriented symbolic execution engine for the PHP programming language. As a symbolic execution engine, our system emulate the execution of a PHP program by assuming that all inputs are with symbolic rather than concrete values. While our system inherits the basic definition of symbolic execution, it fundamentally differs from existing symbolic execution implementations that mainly leverage intermediate representation (IRs) to operate. Specifically, our system directly takes the abstract syntax tree (AST) of a program as input and subsequently interprets this AST. Performing symbolic execution using AST offers unique advantages. First, …

Slim Embedding Layers For Recurrent Neural Language Models, Zhongliang Li

Browse all Theses and Dissertations

Recurrent neural language (RNN) models are the state-of-the-art method for language modeling. When the vocabulary size is large, the space taken to store the model parameters becomes the bottleneck for the use of these type of models. We introduce a simple space compression method that stochastically shares the structured parameters at both the input and output embedding layers of RNN models to significantly reduce the size of model parameters, but still compactly represents the original input and the output embedding layers. The method is easy to implement and tune. Experiments on several data sets show that the new method achieves …

Masquerading Techniques In Ieee 802.11 Wireless Local Area Networks, Omar Nakhila

Electronic Theses and Dissertations

The airborne nature of wireless transmission offers a potential target for attackers to compromise IEEE 802.11 Wireless Local Area Network (WLAN). In this dissertation, we explore the current WLAN security threats and their corresponding defense solutions. In our study, we divide WLAN vulnerabilities into two aspects, client, and administrator. The client-side vulnerability investigation is based on examining the Evil Twin Attack (ETA) while our administrator side research targets Wi-Fi Protected Access II (WPA2). Three novel techniques have been presented to detect ETA. The detection methods are based on (1) creating a secure connection to a remote server to detect the …

A Reliable Data Provenance And Privacy Preservation Architecture For Business-Driven Cyber-Physical Systems Using Blockchain, Xueping Liang, Sachin Shetty, Deepak K. Tosh, Juan Zhao, Danyi Li, Jihong Liu

VMASC Publications

Cyber-physical systems (CPS) including power systems, transportation, industrial control systems, etc. support both advanced control and communications among system components. Frequent data operations could introduce random failures and malicious attacks or even bring down the whole system. The dependency on a central authority increases the risk of single point of failure. To establish an immutable data provenance scheme for CPS, the authors adopt blockchain and propose a decentralized architecture to assure data integrity. In business-driven CPS, end users are required to share their personal information with multiple third parties. To prevent data leakage and preserve user privacy, the authors isolate …

Special Issue: Neutrosophic Information Theory And Applications, Florentin Smarandache, Jun Ye

Branch Mathematics and Statistics Faculty and Staff Publications

Neutrosophiclogic,symboliclogic,set,probability,statistics,etc.,are,respectively,generalizations of fuzzy and intuitionistic fuzzy logic and set, classical and imprecise probability, classical statistics, and so on. Neutrosophic logic, symbol logic, and set are gaining significant attention in solving many real-life problems that involve uncertainty, impreciseness, vagueness, incompleteness, inconsistency, and indeterminacy. A number of new neutrosophic theories have been proposed and have been applied in computational intelligence, multiple-attribute decision making, image processing, medical diagnosis, fault diagnosis, optimization design, etc. This Special Issue gathers original research papers that report on the state of the art, as well as on recent advancements in neutrosophic information theory in soft computing, artificial intelligence, …

Application For Position And Load Reference Generation Of A Simulated Mechatronic Chain, Florentin Smarandache, V. Vladareanu, S.B. Cononovici, M. Migdalovici, H. Wang, Y. Feng

Branch Mathematics and Statistics Faculty and Staff Publications

The paper presents the position and load reference generation for a motor stand simulating a mechatronic chain, in this case a three degree of freedom robot leg. The task is accomplished using three PLC controlled motors in position as the robot joint actuators coupled with three controlled in torque, simulating the load at each simulation time-step. The paper briefly discusses the mathematical model and presents the visual interface used in the simulation, which is then to be further integrated into a virtual environment robot control application.

Fundamentals Of Neutrosophic Logic And Sets And Their Role In Artificial Intelligence (Fundamentos De La Lógica Y Los Conjuntos Neutrosóficos Y Su Papel En La Inteligencia Artificial ), Florentin Smarandache, Maykel Leyva-Vazquez

Branch Mathematics and Statistics Faculty and Staff Publications

Neutrosophy is a new branch of philosophy which studies the origin, nature and scope of neutralities. This has formed the basis for a series of mathematical theories that generalize the classical and fuzzy theories such as the neutrosophic sets and the neutrosophic logic. In the paper, the fundamental concepts related to neutrosophy and its antecedents are presented. Additionally, fundamental concepts of artificial intelligence will be defined and how neutrosophy has come to strengthen this discipline.

Modelo De Recomendación Basado En Conocimiento Y Números Svn, Maykel Leyva-Vazquez, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

Recommendation models are useful in the decision-making process that allow the user a set of options that are expected to meet their expectations. Recommendation models are useful in the decision-making process that offer the user a set of options that are expected to meet their SVN expectations to express linguistic terms.

The Effect Of Data Marshalling On Computation Offloading Decisions, Julio Alberto Reyes Muñoz

Open Access Theses & Dissertations

Computation offloading consists in allowing resource constrained computers, such as smartphones and other mobile devices, to use the network for the remote execution of resource intensive computing tasks in powerful computers. However, deciding whether to offload or not is not a trivial problem, and it depends in several variables related to the environment conditions, the computing devices involved in the process, and the nature of the task to be remotely executed. Furthermore, it comprises the optimal solution to some questions, like how to partition the application and where to execute the tasks.

The computation offloading decision problem has been widely …

Decision Making For Dynamic Systems Under Uncertainty: Predictions And Parameter Recomputations, Leobardo Valera

Open Access Theses & Dissertations

In this Thesis, we are interested in making decision over a model of a dynamic system. We want to know, on one hand, how the corresponding dynamic phenomenon unfolds under different input parameters (simulations). These simulations might help researchers to design devices with a better performance than the actual ones. On the other hand, we are also interested in predicting the behavior of the dynamic system based on knowledge of the phenomenon in order to prevent undesired outcomes. Finally, this Thesis is concerned with the identification of parameters of dynamic systems that ensure a specific performance or behavior.

Understanding the …

A New Approach To Multiplanar, Real-Time Simulation Of Physiological Knee Loads And Synthetic Knee Components Augmented By Local Composition Control In Fused Filament Fabrication, Joshua Taylor Green

Open Access Theses & Dissertations

Despite numerous advances in biomedical engineering, few developments in surgical simulation have been made outside of computational models. Cadavers remain the primary media on which surgical research and simulation is conducted. Most attempts to quantify the effects of orthopedic surgical methods fail to achieve statistical significance due to limited quantities of cadaver specimen, large variations among the cadaver population, and a lack of repeatability among measurement techniques. The general purpose of the research covered in this dissertation is to develop repeatable simulation of physiological loads and develop techniques to fabricate a synthetic-based replacement of cadaver specimens. Future work applying this …

Detecting Contaminated Fiber Connectors Using Sfp Optical Power Data, Christopher A. Mendoza

Open Access Theses & Dissertations

Fiber optic technology is an important part of communication networks enabling high-bandwidth transmissions over long and short distances. They do have their fair share of problems though, contamination being the biggest culprit. Contamination of fiber optic connectors can lead to serious performance degradation or even loss of signal. Detecting contaminated fiber connectors can take weeks or even months using traditional practices. There are standard cleanliness practices when dealing with optical connectors but still the problem seems to persist. This work presents an inequality to solve the detection portion of this problem. The proposed inequality uses power readings from the Small …

Development Of A Desktop Material Extrusion 3d Printer With Wire Embedding Capabilities, Jose Francisco Motta

Open Access Theses & Dissertations

Printed circuit boards (PCB) have been widely used as a permanent solution for generating complex circuitries to power electronic devices. Over the years, PCB boards have proved to be reliable when powering electronic devices. However, when fabricating a printed circuit board, one must outsource to fabricate the boards when in prototype phase. Therefore, the risk of intellectual property theft and long lead time is an issue. The objective of this Thesis is to develop a hybrid multi-tool desktop material extrusion 3D printer that allows for easy integration (modularity) of tools to generate multi-functional 3D printed components.

The addition of an …