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Articles 5011 - 5040 of 13043

Full-Text Articles in Computer Engineering

Optimal Svc Allocation In Power Systems Using Lightning Attachment Procedureoptimization, Ayman Awad, Salah Kamel, Heba Youssef, Francisco Jurado Jan 2020

Optimal Svc Allocation In Power Systems Using Lightning Attachment Procedureoptimization, Ayman Awad, Salah Kamel, Heba Youssef, Francisco Jurado

Turkish Journal of Electrical Engineering and Computer Sciences

Flexible AC transmission systems (FACTS) technology is widely adopted and utilized to maintain the performance of power systems. However, the improvements of power system performance achieved by FACTS devices depend on the right sizing and allocation of such devices. For technical and economic considerations, a FACTS device's location and size should be selected very carefully in order to maximize its benefits to the power system. In this paper, the sizing and location of a static VAR compensator (SVC) are optimally determined using a new optimization technique called lightning attachment procedure optimization (LAPO). The optimal allocation of the SVC is determined …

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Asymmetric Slope Compensation For Digital Hybrid Current Mode Control Of Athree-Level Flying Capacitor Buck Converter, Abdulkeri̇m Uğur, Murat Yilmaz Jan 2020

Asymmetric Slope Compensation For Digital Hybrid Current Mode Control Of Athree-Level Flying Capacitor Buck Converter, Abdulkeri̇m Uğur, Murat Yilmaz

Turkish Journal of Electrical Engineering and Computer Sciences

The three-level flying capacitor (3LFC) buck converter has the potential to provide better efficiency and higher power density as compared to the traditional buck converter. However, due to the flying capacitor?s instability issues, control is challenging. In this paper, the digital hybrid current mode (DHCM) control method, which combines the average and peak current mode control techniques, is modified and implemented to a 3LFC buck converter. For flying capacitor (FC) voltage balancing, a novel asymmetric slope compensation (ASC) technique is presented. The proposed ASC technique achieves FC voltage balancing by adjusting the slope compensation of the two switching pairs asymmetrically, …

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Fiber Optic Chemical Sensors For Water Testing By Using Fiber Loop Ringdown Spectroscopy Technique, Mali̇k Kaya Jan 2020

Fiber Optic Chemical Sensors For Water Testing By Using Fiber Loop Ringdown Spectroscopy Technique, Mali̇k Kaya

Turkish Journal of Electrical Engineering and Computer Sciences

Real-time response, low cost, sensitive and easy setup fiber optic chemical sensors were fabricated by etching a part of single mode fiber in hydrofluoric (HF) acid solution and tested in different water samples such as tap water, DI water, salty and sugar water with different concentrations to record ringdown time (RDT) differences between media due to refractive index differences by employing the fiber loop ringdown (FLRD) spectroscopy technique. Baseline stability of 0.63 % and the minimum detectable RDT of $5.05$ $\mu$s for this kind of fiber optic chemical sensors were obtained. Fabricated sensors were coated with N,N-Diethyl-p-phenylenediamine for the first …

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Deep Learning For Digitized Histology Image Analysis, Sudhir Sornapudi Jan 2020

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 …

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Iot Devices In The Public Health Sector, Cayla Young Jan 2020

Iot Devices In The Public Health Sector, Cayla Young

Cybersecurity Undergraduate Research Showcase

In this research, proper attention is drawn to privacy and security concerns with the integration of Internet of Things (IoT) devices in the public health sector. Often, not much attention is given to IoT devices and its vulnerabilities concerning the medical industry. Effects of COVID-19 contact tracing applications are explored through research of various source types. Mitigation techniques for these privacy and security issues is given. Focus is brought to topics outlining the risks associated with genetic testing companies and the vulnerabilities of data collection and data storage. Recommendations are provided to help consumers avoid these risks. Lastly, a comprehensive …

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The Effects Of Mixed-Initiative Visualization Systems On Exploratory Data Analysis, Alvitta Ottley, Adam Kern Jan 2020

The Effects Of Mixed-Initiative Visualization Systems On Exploratory Data Analysis, Alvitta Ottley, Adam Kern

All Computer Science and Engineering Research

The primary purpose of information visualization is to act as a window between a user and the data. Historically, this has been accomplished via a single-agent framework: the only decision-maker in the relationship between visualization system and analyst is the analyst herself. Yet this framework arose not from first principles, but a necessity. Before this decade, computers were limited in their decision-making capabilities, especially in the face of large, complex datasets and visualization systems. This paper aims to present the design and evaluation of a mixed-initiative system that aids the user in handling large, complex datasets and dense visualization systems. …

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Improving Pain Management In Patients With Sickle Cell Disease Using Machine Learning Techniques, Fan Yang Jan 2020

Improving Pain Management In Patients With Sickle Cell Disease Using Machine Learning Techniques, Fan Yang

Browse all Theses and Dissertations

Sickle cell disease (SCD) is an inherited red blood cell disorder that can cause a multitude of complications throughout a patient's life. Pain is the most common complication and a significant cause of morbidity. Since pain is a highly subjective experience, both medical providers and patients express difficulty in determining ideal treatment and management strategies for pain. Therefore, the development of objective pain assessment and pain forecasting methods is critical to pain management in SCD. On the other hand, the rapidly increasing use of mobile health (mHealth) technology and wearable devices gives the ability to build a remote health intervention …

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Enabling Static Program Analysis Using A Graph Database, Jialun Liu Jan 2020

Enabling Static Program Analysis Using A Graph Database, Jialun Liu

Browse all Theses and Dissertations

This thesis presents the design, the implementation, and the evaluation of a database-oriented static program analysis engine for the PHP programming language. This engine analyzes PHP programs by representing their semantics using a graph-based data structure, which will be subsequently stored into a graph database. Such scheme will fundamentally facilitate various program analysis tasks such as static taint analysis, visualization, and data mining. Specifically, these complex program analysis tasks can now be translated into built-in declarative graph database operations with rich features. Our engine fundamentally differs from other existing static program analysis systems that mainly leverage intermediate representation (IRs) to …

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Topological Analysis Of Averaged Sentence Embeddings, Wesley J. Holmes Jan 2020

Topological Analysis Of Averaged Sentence Embeddings, Wesley J. Holmes

Browse all Theses and Dissertations

Sentence embeddings are frequently generated by using complex, pretrained models that were trained on a very general corpus of data. This thesis explores a potential alternative method for generating high-quality sentence embeddings for highly specialized corpora in an efficient manner. A framework for visualizing and analyzing sentence embeddings is developed to help assess the quality of sentence embeddings for a highly specialized corpus of documents related to the 2019 coronavirus epidemic. A Topological Data Analysis (TDA) technique is explored as an alternative method for grouping embeddings for document clustering and topic modeling tasks and is compared to a simple clustering …

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Design Of A Novel Wearable Ultrasound Vest For Autonomous Monitoring Of The Heart Using Machine Learning, Garrett G. Goodman Jan 2020

Design Of A Novel Wearable Ultrasound Vest For Autonomous Monitoring Of The Heart Using Machine Learning, Garrett G. Goodman

Browse all Theses and Dissertations

As the population of older individuals increases worldwide, the number of people with cardiovascular issues and diseases is also increasing. The rate at which individuals in the United States of America and worldwide that succumb to Cardiovascular Disease (CVD) is rising as well. Approximately 2,303 Americans die to some form of CVD per day according to the American Heart Association. Furthermore, the Center for Disease Control and Prevention states that 647,000 Americans die yearly due to some form of CVD, which equates to one person every 37 seconds. Finally, the World Health Organization reports that the number one cause of …

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A Tutorial And Future Research For Building A Blockchain-Based Secure Communication Scheme For Internet Of Intelligent Things, Mohammad Wazid, Ashok Kumar Das, Sachin Shetty, Minho Jo Jan 2020

A Tutorial And Future Research For Building A Blockchain-Based Secure Communication Scheme For Internet Of Intelligent Things, Mohammad Wazid, Ashok Kumar Das, Sachin Shetty, Minho Jo

Computational Modeling & Simulation Engineering Faculty Publications

The Internet of Intelligent Things (IoIT) communication environment can be utilized in various types of applications (for example, intelligent battlefields, smart healthcare systems, the industrial internet, home automation, and many more). Communications that happen in such environments can have different types of security and privacy issues, which can be resolved through the utilization of blockchain. In this paper, we propose a tutorial that aims in desiging a generalized blockchain-based secure authentication key management scheme for the IoIT environment. Moreover, some issues with using blockchain for a communication environment are discussed as future research directions. The details of different types of …

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Coverage Guided Differential Adversarial Testing Of Deep Learning Systems, Jianmin Guo, Houbing Song, Yue Zhao, Yu Jiang Jan 2020

Coverage Guided Differential Adversarial Testing Of Deep Learning Systems, Jianmin Guo, Houbing Song, Yue Zhao, Yu Jiang

Publications

Deep learning is increasingly applied to safety-critical application domains such as autonomous cars and medical devices. It is of significant importance to ensure their reliability and robustness. In this paper, we propose DLFuzz, the coverage guided differential adversarial testing framework to guide deep learing systems exposing incorrect behaviors. DLFuzz keeps minutely mutating the input to maximize the neuron coverage and the prediction difference between the original input and the mutated input, without manual labeling effort or cross-referencing oracles from other systems with the same functionality. We also design multiple novel strategies for neuron selection to improve the neuron coverage. The …

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Demand-Driven Execution Using Future Gated Single Assignment Form, Omkar Javeri Jan 2020

Demand-Driven Execution Using Future Gated Single Assignment Form, Omkar Javeri

Dissertations, Master's Theses and Master's Reports

This dissertation discusses a novel, previously unexplored execution model called Demand-Driven Execution (DDE), which executes programs starting from the outputs of the program, progressing towards the inputs of the program. This approach is significantly different from prior demand-driven reduction machines as it can execute a program written in an imperative language using the demand-driven paradigm while extracting both instruction and data level parallelism. The execution model relies on an executable Single Assignment Form which serves both as the internal representation of the compiler as well as the Instruction Set Architecture (ISA) of the machine. This work develops the instruction set …

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Selective Personalization And Group Profiles For Improved Web Search Personalization, Samira Karimi Mansoub, Gönenç Ercan, İlyas Çi̇çekli̇ Jan 2020

Selective Personalization And Group Profiles For Improved Web Search Personalization, Samira Karimi Mansoub, Gönenç Ercan, İlyas Çi̇çekli̇

Turkish Journal of Electrical Engineering and Computer Sciences

Personalization is a common technique used in Web search engines to improve the effectiveness of retrieval. While personalizing some queries yields significant improvements in user experience by providing a ranking in line with the user preferences, it fails to improve or even degrades the effectiveness for less ambiguous queries. A potential personalization metric could improve search engines by selectively applying personalization. One such measure, click entropy uses the query history and the clicked documents for the query, which might be sparse for some queries. In this article, the topic entropy measure is improved by integrating the user distribution into the …

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An Alternative Method Of Biomedical Signal Transmission Through The Gsm Voice Channel, Seyedmohsen Dehghan, Mehmet Kaya Jan 2020

An Alternative Method Of Biomedical Signal Transmission Through The Gsm Voice Channel, Seyedmohsen Dehghan, Mehmet Kaya

Turkish Journal of Electrical Engineering and Computer Sciences

In this work, a new solution for online and accurate biomedical data transmission is presented. For this purpose, a global system for mobile (GSM) communication voice channel is, for the first time, used as a communication link between the patient and healthcare provider. Biomedical signals are converted into speech-like signals before being transferred over a GSM voice channel. On the receiver side, speech-like symbols are stored in a symbols bank, and constructed using random stochastic signals. On the receiver end, the index of the symbol with the most similarity to the received signal is selected as the identified sample. This …

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Wavelength Sensitivity Of Indium Tin Oxide On Surface Plasmon Resonance Angles, Antonio Ruiz, Carlos Villa Angulo, Ivan Olaf Hernandez-Fuentes Jan 2020

Wavelength Sensitivity Of Indium Tin Oxide On Surface Plasmon Resonance Angles, Antonio Ruiz, Carlos Villa Angulo, Ivan Olaf Hernandez-Fuentes

Turkish Journal of Electrical Engineering and Computer Sciences

Surface plasmon resonance (SPR) is a charge-density oscillation that occurs when a beam of p-polarized monochromatic light impinges with a greater angle than the critical angle in a dielectric-metal interface. Because of the high losses related to metals, the generated surface plasmon waves propagate with high attenuation in the visible and near-infrared spectral regions in most of the dielectric-metal interfaces. An alternative to reduce such losses is to use a transparent indium tin oxide (ITO) film. In this paper, we compared theoretical calculations and experimental measurements of the SPR angle $\theta_{SPR}$ on the interfaces of a borosilicate prism (Bp) and …

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Technological Challenges And Innovations In Cybersecurity And Networking Technology Program, Syed R. Zaidi, Ajaz Sana, Aparicio Carranza Jan 2020

Technological Challenges And Innovations In Cybersecurity And Networking Technology Program, Syed R. Zaidi, Ajaz Sana, Aparicio Carranza

Publications and Research

This era is posing a unique challenge to the Cybersecurity and related Engineering Technology areas, stimulated by the multifaceted technological boom expressed in accelerated globalization, digital transformation, the cloud, mobile access apps, and the Internet of Things (IoT)—where more and more devices are connected to the Internet every day. As the use of new Internet-based technologies increase; so does the risk of theft and misuse of sensitive information. This demands the awareness of cyber-criminality and the need for cyber hygiene in corporations, small businesses, and the government. As the need for experienced cybersecurity specialists has skyrocketed in recent years and …

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Image Instance Segmentation: Using The Cirsy System To Identify Small Objects In Low Resolution Images, Orghomisan William Omatsone Jan 2020

Image Instance Segmentation: Using The Cirsy System To Identify Small Objects In Low Resolution Images, Orghomisan William Omatsone

Dissertations

The CIRSY system (or Chick Instance Recognition System) is am image processing system developed as part of this research to detect images of chicks in highly-populated images that uses the leading algorithm in instance segmentation tasks, called the Mask R-CNN. It extends on the Faster R-CNN framework used in object detection tasks, and this extension adds a branch to predict the mask of an object along with the bounding box prediction. Mask R-CNN has proven to be effective ininstance segmentation and object de-tection tasks after outperforming all existing models on evaluation of the Microsoft Common Objects in Context (MS COCO) …

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Content-Based Filtering Recommendation Approach To Label Irish Legal Judgements, Sandesh Gangadhar Jan 2020

Content-Based Filtering Recommendation Approach To Label Irish Legal Judgements, Sandesh Gangadhar

Dissertations

Machine learning approaches are applied across several domains to either simplify or automate tasks which directly result in saved time or cost. Text document labelling is one such task that requires immense human knowledge about the domain and efforts to review, understand and label the documents. The company Stare Decisis summarises legal judgements and labels them as they are made available on Irish public legal source www.courts.ie. This research presents a recommendation-based approach to reduce the time for solicitors at Stare Decisis by reducing many numbers of available labels to pick from to a concentrated few that potentially contains the …

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Machine Learning Assisted Gait Analysis For The Determination Of Handedness In Able-Bodied People, Hugh Gallagher Jan 2020

Machine Learning Assisted Gait Analysis For The Determination Of Handedness In Able-Bodied People, Hugh Gallagher

Dissertations

This study has investigated the potential application of machine learning for video analysis, with a view to creating a system which can determine a person’s hand laterality (handedness) from the way that they walk (their gait). To this end, the convolutional neural network model VGG16 underwent transfer learning in order to classify videos under two ‘activities’: “walking left-handed” and “walking right-handed”. This saw varying degrees of success across five transfer learning trained models: Everything – the entire dataset; FiftyFifty – the dataset with enough right-handed samples removed to produce a set with parity between activities; Female – only the female …

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An Examination Of The Smote And Other Smote-Based Techniques That Use Synthetic Data To Oversample The Minority Class In The Context Of Credit-Card Fraud Classification, Eduardo Parkinson De Castro Jan 2020

An Examination Of The Smote And Other Smote-Based Techniques That Use Synthetic Data To Oversample The Minority Class In The Context Of Credit-Card Fraud Classification, Eduardo Parkinson De Castro

Dissertations

This research project seeks to investigate some of the different sampling techniques that generate and use synthetic data to oversample the minority class as a means of handling the imbalanced distribution between non-fraudulent (majority class) and fraudulent (minority class) classes in a credit-card fraud dataset. The purpose of the research project is to assess the effectiveness of these techniques in the context of fraud detection which is a highly imbalanced and cost-sensitive dataset. Machine learning tasks that require learning from datasets that are highly unbalanced have difficulty learning since many of the traditional learning algorithms are not designed to cope …

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Transformer Neural Networks For Automated Story Generation, Kemal Araz Jan 2020

Transformer Neural Networks For Automated Story Generation, Kemal Araz

Dissertations

Towards the last two-decade Artificial Intelligence (AI) proved its use on tasks such as image recognition, natural language processing, automated driving. As discussed in the Moore’s law the computational power increased rapidly over the few decades (Moore, 1965) and made it possible to use the techniques which were computationally expensive. These techniques include Deep Learning (DL) changed the field of AI and outperformed other models in a lot of fields some of which mentioned above. However, in natural language generation especially for creative tasks that needs the artificial intelligent models to have not only a precise understanding of the given …

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Identifying Online Sexual Predators Using Support Vector Machine, Yifan Li Jan 2020

Identifying Online Sexual Predators Using Support Vector Machine, Yifan Li

Dissertations

A two-stage classification model is built in the research for online sexual predator identification. The first stage identifies the suspicious conversations that have predator participants. The second stage identifies the predators in suspicious conversations. Support vector machines are used with word and character n-grams, combined with behavioural features of the authors to train the final classifier. The unbalanced dataset is downsampled to test the performance of re-balancing an unbalanced dataset. An age group classification model is also constructed to test the feasibility of extracting the age profile of the authors, which can be used as features for classifier training. The …

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Classification Of Animal Sound Using Convolutional Neural Network, Neha Singh Jan 2020

Classification Of Animal Sound Using Convolutional Neural Network, Neha Singh

Dissertations

Recently, labeling of acoustic events has emerged as an active topic covering a wide range of applications. High-level semantic inference can be conducted based on main audioeffects to facilitate various content-based applications for analysis, efficient recovery and content management. This paper proposes a flexible Convolutional neural network-based framework for animal audio classification. The work takes inspiration from various deep neural network developed for multimedia classification recently. The model is driven by the ideology of identifying the animal sound in the audio file by forcing the network to pay attention to core audio effect present in the audio to generate Mel-spectrogram. …

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Designing Shared Control Strategies For Teleoperated Robots Across Intrinsic User Qualities, Nancy Pham Jan 2020

Designing Shared Control Strategies For Teleoperated Robots Across Intrinsic User Qualities, Nancy Pham

School of Computing: Dissertations, Theses, and Student Research

Accounting for variance in human behavior is an integral part of interacting with robotic systems that share control between users and robots in order to reduce errors, improve performance, and maintain safety. In this work we focus on the shared control of a telepresence robot and how individual user traits may affect a person's performance while navigating the robot. This requires understanding which user qualities impact performance and cause conflicts -- with the ultimate goal of building shared controllers that adapt to those qualities. Toward this goal, we develop novel adaptive shared controllers and integrate the study of intrinsic user …

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Deepmag+ : Sniffing Mobile Apps In Magnetic Field Through Deep Learning, Rui Ning, Cong Wang, Chunsheng Xin, Jiang Li, Hongyi Wu Jan 2020

Deepmag+ : Sniffing Mobile Apps In Magnetic Field Through Deep Learning, Rui Ning, Cong Wang, Chunsheng Xin, Jiang Li, Hongyi Wu

Electrical & Computer Engineering Faculty Publications

This paper reports a new side-channel attack to smartphones using the unrestricted magnetic sensor data. We demonstrate that attackers can effectively infer the Apps being used on a smartphone with an accuracy of over 80%, through training a deep Convolutional Neural Networks (CNN). Various signal processing strategies have been studied for feature extractions, including a tempogram based scheme. Moreover, by further exploiting the unrestricted motion sensor to cluster magnetometer data, the sniffing accuracy can increase to as high as 98%. To mitigate such attacks, we propose a noise injection scheme that can effectively reduce the App sniffing accuracy to only …

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The Artificial University: Decision Support For Universities In The Covid-19 Era, Wesley J. Wildman, Saikou Y. Diallo, George Hodulik, Andrew Page, Andreas Tolk, Neha Gondal Jan 2020

The Artificial University: Decision Support For Universities In The Covid-19 Era, Wesley J. Wildman, Saikou Y. Diallo, George Hodulik, Andrew Page, Andreas Tolk, Neha Gondal

VMASC Publications

Operating universities under pandemic conditions is a complex undertaking. The Artificial University (TAU) responds to this need. TAU is a configurable, open-source computer simulation of a university using a contact network based on publicly available information about university classes, residences, and activities. This study evaluates health outcomes for an array of interventions and testing protocols in an artificial university of 6,500 students, faculty, and staff. Findings suggest that physical distancing and centralized contact tracing are most effective at reducing infections, but there is a tipping point for compliance below which physical distancing is less effective. If student compliance is anything …

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Measuring Decentrality In Blockchain Based Systems, Sarada Prasad Gochhayat, Sachin Shetty, Ravi Mukkamala, Peter Foytik, Georges A. Kamhoua, Laurent Njilla Jan 2020

Measuring Decentrality In Blockchain Based Systems, Sarada Prasad Gochhayat, Sachin Shetty, Ravi Mukkamala, Peter Foytik, Georges A. Kamhoua, Laurent Njilla

VMASC Publications

Blockchain promises to provide a distributed and decentralized means of trust among untrusted users. However, in recent years, a shift from decentrality to centrality has been observed in the most accepted Blockchain system, i.e., Bitcoin. This shift has motivated researchers to identify the cause of decentrality, quantify decentrality and analyze the impact of decentrality. In this work, we take a holistic approach to identify and quantify decentrality in Blockchain based systems. First, we identify the emergence of centrality in three layers of Blockchain based systems, namely governance layer, network layer and storage layer. Then, we quantify decentrality in these layers …

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อัลกอริทึมการระบุการผันกลับของเซลลูลาร์ออโตมาตาหนึ่งมิติด้วยกราฟสับเซตย่อยภายใต้เงื่อนไขการกำหนดขอบเขตแบบไม่มีค่า, วรยุทธ วงศ์นิล Jan 2020

อัลกอริทึมการระบุการผันกลับของเซลลูลาร์ออโตมาตาหนึ่งมิติด้วยกราฟสับเซตย่อยภายใต้เงื่อนไขการกำหนดขอบเขตแบบไม่มีค่า, วรยุทธ วงศ์นิล

Chulalongkorn University Theses and Dissertations (Chula ETD)

เซลลูลาร์ออโตมาตาถือเป็นโมเดลทางคณิตศาสตร์ที่สามารถทำงานแบบระบบพลวัต ซึ่งประกอบไปด้วยสถานะจำกัดที่เรียงตัวกันอย่างเป็นระบบเรียกเซลล์ แต่ละเซลล์จะเปลี่ยนสถานะไปยังสถานะใหม่พร้อมกันด้วยการอาศัยกฎการส่งผ่านที่ขึ้นอยู่กับเซลล์รอบ ๆ ด้วยเวลาแบบเต็มหน่วย แม้ว่าเซลลูลาร์ออโตมาตามีโครงสร้างและนิยามในแบบพื้นฐาน แต่สามารถสร้างระบบที่พฤติกรรมมีความซับซ้อนได้ สมบัติในการผันกลับได้ของเซลลูลาร์ออโตมาตาถือเป็นสมบัติสำคัญที่ได้รับความสนใจในหลายงานวิจัยและสามารถนำไปประยุกต์ใช้ได้ในงานหลาย ๆ ด้านในทางวิทยาศาสตร์ แต่สำหรับเซลลูลาร์ออโตมาตาหนึ่งมิติภายใต้เงื่อนไขการกำหนดขอบเขตแบบไม่มีค่ายังถือมีข้อจำกัดของจำนวนกฎที่มีไม่มากที่มีสมบัติดังกล่าว ในงานวิจัยนี้ศึกษาและเสนออัลกอริทึมการระบุการผันกลับของเซลลูลาร์ออโตมาตาหนึ่งมิติด้วยกราฟสับเซตย่อยภายใต้เงื่อนไขการกำหนดขอบเขตแบบไม่มีค่านิยามเซลล์เพื่อนบ้านด้วยเวกเตอร์ ด้วยการแทนเซลลูลาร์ออโตมาตาด้วยกราฟสับเซตย่อยเราเสนอวิธีในการระบุสมบัติการผันกลับได้ในกราฟโดยการพิจารณาเส้นเชื่อมและจุดยอดที่เชื่อมถึงกัน นอกจากนี้งานวิจัยนี้ยังเสนอวิธีในการคำนวณสถานะก่อนหน้าสำหรับสถานะใด ๆ ของเซลลูลาร์ออโตมาตาหนึ่งมิติที่มีสมบัติผันกลับได้ภายใต้เงื่อนไขการกำหนดขอบเขตแบบไม่มีค่า ซึ่งวิธีที่ได้เสนออยู่บนพื้นฐานของการพิจารณาลักษณะของเซลล์เพื่อนบ้านด้วยการคำนวณทางเดินบนกราฟด้วยการดำเนินการของเมตริกซ์

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การวิเคราะห์ข้อความภาษาธรรมชาติตามประมวลกฎหมายอาญา, วีรยุทธ ครั่งกลาง Jan 2020

การวิเคราะห์ข้อความภาษาธรรมชาติตามประมวลกฎหมายอาญา, วีรยุทธ ครั่งกลาง

Chulalongkorn University Theses and Dissertations (Chula ETD)

วิทยานิพนธ์นี้วิเคราะห์การบังคับใช้กฎหมายอาญาของประเทศไทย ในภาค1 บทบัญญัติทั่วไป และภาค2 เฉพาะความผิดเกี่ยวกับชีวิต มาตรา 288 และมาตรา 289 ในลักษณะ10 ความผิดเกี่ยวกับชีวิตและร่างกาย ตามประมวลกฎหมายอาญาของไทย ส่วนแรกของวิทยานิพนธ์นี้ใช้ความรู้ด้านกฎหมายอาญาและคำพิพากษาของศาลฎีกาในการสร้างกฎในการพิจารณาที่มนุษย์สามารถเข้าใจได้ และส่วนที่สองคือการฝึกฝนแบบจำลองด้วยชุดข้อมูลจากคำพิพากษาด้วยเทคนิคการเรียนรู้เชิงลึก โดยแก้ปัญหาความไม่สมดุลของกลุ่มข้อมูลฝึกสอนด้วยการสังเคราะห์ตัวอย่างข้อมูลในกลุ่มอื่น ๆ ให้มีจำนวนเท่ากับกลุ่มที่มากที่สุด และฝึกสอนด้วยโครงข่ายหน่วยความจำระยะสั้นแบบยาวทิศทางเดียวและสองทิศทาง ซึ่งเป็นโครงข่ายประสาทเทียมแบบวกกลับประเภทหนึ่ง และเมื่อวัดประสิทธิภาพแบบจำลองด้วยค่าเฉลี่ยมหภาคเอฟวัน พบว่าแบบจำลองของหน่วยความจำระยะสั้นแบบยาวสองทิศทางให้ประสิทธิภาพสูงกว่าแบบทิศทางเดียว และการใช้ค่าถ่วงน้ำหนักเริ่มต้นจากเรียนรู้ด้วยคลังข้อมูลขนาดใหญ่อื่น ให้ประสิทธิภาพที่สูงกว่าการใช้เฉพาะข้อมูลฝึกสอน และท้ายสุดทำการทดสอบความแม่นยำของแบบจำลองจากข่าวอาชญากรรมด้วยเทคนิคการหาค่าเฉลี่ยความน่าจะเป็น เพื่อใช้เป็นข้อมูลขาเข้าของกฎการพิจารณา พบว่าสอดคล้องกับความเห็นของนักกฎหมาย 59 %

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