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Proknow: Process Knowledge For Safety Constrained And Explainable Question Generation For Mental Health Diagnostic Assistance In The Age Of Large Language Models, Kaushik Roy, Manas Gaur, Misagh Soltani, Vipula Rawte, Ashwin Allen, Amit P. Sheth
Proknow: Process Knowledge For Safety Constrained And Explainable Question Generation For Mental Health Diagnostic Assistance In The Age Of Large Language Models, Kaushik Roy, Manas Gaur, Misagh Soltani, Vipula Rawte, Ashwin Allen, Amit P. Sheth
Publications
Current Virtual Mental Health Assistants (VMHAs) primarily offer counseling and suggestive care but do not assist with patient diagnosis due to their lack of training in safety-constrained and specialized clinical process knowledge, referred to as ProKnow. In this work, we define ProKnow as an ordered set of information aligned with evidence-based guidelines or categories of conceptual understanding used by domain experts. We also introduce a new dataset of diagnostic conversations guided by safety constraints and Pro- Know, known as ProKnow-data. We develop a method for natural language question generation (NLG) designed to interactively gather diagnostic information from patients, termed ProKnow-algo. …
Ml-Based User Identification Through Mouse Dynamics, Rakshit Gupta
Ml-Based User Identification Through Mouse Dynamics, Rakshit Gupta
Master's Projects
User authentication and identification plays a crucial role in ensuring the security and integrity of digital systems. Traditional authentication methods, such as passwords and biometrics, have inherent limitations that can compromise system security. This research proposes a novel approach to user authentication by leveraging machine learning techniques and behavioral biometrics, specifically mouse dynamics. The primary objective is to develop a sophisticated framework that can accurately identify individuals based on their unique mouse behavior patterns. The study explores and compares multiple deep learning architectures, including Convolutional Neural Networks (CNN), Long Short-Term Memory networks (LSTM), and Transformer models, to generate embeddings from …
Distinguishing Chatbot From Human, Gauri Anil Godghase
Distinguishing Chatbot From Human, Gauri Anil Godghase
Master's Projects
There have been many recent advances in the field of Generative Artificial Intelligence and Large Language Models, with GPT 3 or ChatGPT model being one of the frontrunners in this field. These large language models have become so powerful that it has become difficult to differentiate between text written by humans and machine-generated text. This paper proposes a solution to the problem of classification of the origin of data (human or chatbot) by using Machine Learning. In addition, the proposed solution also helps us analyze the text generated by such Language Models and understand the underlying patterns present in the …
การจำแนกและการประเมินประสบการณ์ผู้ใช้จากบทวิจารณ์ของผู้ใช้โมไบล์แอปพลิเคชันโดยใช้การเรียนรู้ของเครื่อง, จิราพร รามจุล
การจำแนกและการประเมินประสบการณ์ผู้ใช้จากบทวิจารณ์ของผู้ใช้โมไบล์แอปพลิเคชันโดยใช้การเรียนรู้ของเครื่อง, จิราพร รามจุล
Chulalongkorn University Theses and Dissertations (Chula ETD)
การทำความเข้าใจประสบการณ์ของผู้ใช้ เป็นสิ่งสำคัญต่อความสำเร็จและการพัฒนาอย่างต่อเนื่องของโมไบล์แอปพลิเคชัน งานวิจัยนี้นำเสนอวิธีการจำแนกบทวิจารณ์ของผู้ใช้ตามลักษณะของประสบการณ์ผู้ใช้ที่มีต่อโมไบล์แอปพลิเคชัน โดยใช้ทั้งอัลกอริทึมการเรียนรู้ของเครื่อง และการเรียนรู้เชิงลึก บทวิจารณ์ของผู้ใช้ถูกจำแนกตามมิติของประสบการณ์ผู้ใช้ในด้านการปฏิบัติและประสบการณ์ผู้ใช้ในด้านความเพลิดเพลิน ซึ่งประกอบด้วยลักษณะของประสบการณ์ผู้ใช้ทั้งหมด 8 รายการ ตามที่นิยามไว้ในแบบสอบถามประสบการณ์ผู้ใช้แบบสั้น ผลลัพธ์การจำแนกบทวิจารณ์ของผู้ใช้สามารถนำไปใช้ร่วมกับการวิเคราะห์ความรู้สึกจากบทวิจารณ์ เพื่อประเมินคะแนนประสบการณ์ผู้ใช้โดยรวมของโมไบล์แอปพลิเคชันได้อย่างอัตโนมัติ จากการทดลองประเมินประสิทธิภาพของโมเดลพบว่าเบิร์ต มีประสิทธิภาพดีกว่าซัพพอร์ตเวกเตอร์แมชีน แรนดอมฟอเรสต์ และ ลอจิสติกรีเกรสชัน โดยมีค่าความเที่ยง เท่ากับ 80%, ค่าเรียกคืน เท่ากับ 74%, ค่าเอฟวัน เท่ากับ 76%, ค่าความแม่น เท่ากับ 78% และค่าเอยูซี เท่ากับ 0.94 นอกจากนี้ค่าคะแนนประสบการณ์ผู้ใช้โดยรวมของโมไบล์แอปพลิเคชันที่คำนวณได้มีค่าสหสัมพันธ์เชิงบวกในระดับปานกลางถึงสูงเป็น 0.68 กับค่าคะแนนการจัดอันดับบนแอปสโตร์ ผลการศึกษานี้ชี้ให้เห็นถึงศักยภาพของการวิเคราะห์และประเมินคะแนนประสบการณ์ผู้ใช้อย่างอัตโนมัติในการเสริมสร้างคุณภาพของโมไบล์แอปพลิเคชันและความพึงพอใจของผู้ใช้
การค้นหาค่าสัมประสิทธ์การปล่อยก๊าซเรือนกระจกบนพื้นฐานแบบจำลองภาษาขนาดใหญ่, สุชานันท์ กระบวนยุทธ
การค้นหาค่าสัมประสิทธ์การปล่อยก๊าซเรือนกระจกบนพื้นฐานแบบจำลองภาษาขนาดใหญ่, สุชานันท์ กระบวนยุทธ
Chulalongkorn University Theses and Dissertations (Chula ETD)
งานวิจัยนี้ดำเนินการเพื่อวิจัยแบบจำลองภาษาขนาดใหญ่และเทคนิคต่างๆ ที่ช่วยเพิ่มศักยภาพของโมเดลเหล่านี้ รวมถึงวิศวกรรมที่รวดเร็วและการขยายความรู้เฉพาะ การศึกษานี้เกี่ยวข้องกับการออกแบบและพัฒนา AI agent เพื่อส่งคืนค่าสัมประสิทธ์ปล่อยก๊าซเรือนกระจกโดยอ้างอิงจากฐานข้อมูลที่ดูแลโดยองค์การบริหารก๊าซเรือนกระจก (องค์การมหาชน) ของประเทศไทย งานวิจัยนี้จะใช้ RAG เพื่อค้นหาข้อมูลที่ถูกจัดเก็บไว้ซึ่งมีความคล้ายคลึงกันมากที่สุดกับข้อมูลรับเข้า จากนั้น AI Agent จะส่งคืนค่าคำตอบเพียงคำตอบเดียวเดียวของค่าสัมประสิทธิ์การปล่อยก๊าซเรือนกระจกที่เกี่ยวข้องกับกิจกรรมที่รับเข้ามา จากการประเมินประสิทธิภาพของ LLM ขนาดกลางและขนาดใหญ่ที่ถูกเลือกทั้งห้าแบบจำลองนั้นมีแนวโน้มที่ดี
Affinity-Based Multi-Character Storyboard Generation Using Rewrite Rules, Ram Sukkirtkijpibul
Affinity-Based Multi-Character Storyboard Generation Using Rewrite Rules, Ram Sukkirtkijpibul
Chulalongkorn University Theses and Dissertations (Chula ETD)
A game story contains interactions between characters as well as the game world. Certain genres of games such as Visual Novels and Role-Playing Games rely on their stories to attract players. There were several proposed algorithms for story generation. They focused mainly on story generation for one main character. To our knowledge, there has not been a generator with support for multiple main characters, where each main character has their own storyline that could overlap with other main characters’ stories. With multiple main characters, players can see the game world through different viewpoints, thus getting more immersed into the game's …
Improving Thai-Dialect Automatic Speech Recognition With Curriculum Learning, Artit Suwanbandit
Improving Thai-Dialect Automatic Speech Recognition With Curriculum Learning, Artit Suwanbandit
Chulalongkorn University Theses and Dissertations (Chula ETD)
Automatic Speech Recognition (ASR) has been the foremost feature and integrated in many real-world usages for decades. The novel deep learning approaches prevail in the ASR field as a model architecture. However, ASR still struggles with low-resource data, especially in the Thai dialectal language. Transfer learning is the conventional approach in the machine learning field for escalating the performance of low-resource settings. In the scenario that additional fine-tuning tasks are not achievable, exerting all efficiency of target data is an accountability. To overcome stagnation, we proposed transfer-based curriculum learning for low-resource dialectal ASR, Phonemetically-induced subword Out-of-vocabulary rate (PhIS-OOV), and Model …
Grammatical Error Correction In Thai Sentences For Deaf Students, Supachan Traitruengsakul
Grammatical Error Correction In Thai Sentences For Deaf Students, Supachan Traitruengsakul
Chulalongkorn University Theses and Dissertations (Chula ETD)
Deaf students encounter challenges in written communication due to errors such as insertion, deletion, disorder, misusage, and misspellings. Grammatical error correction (GEC) technology can help mitigate these issues. However, existing GEC models are primarily trained on online resources from second-language hearing learners. In contrast, sentences written by deaf students suffer from a variety of errors not typically found elsewhere. To address this issue, we create the Thai Deaf Corpus (TDC), focusing on identifying and analyzing errors among deaf students in grades 7-12 across four deaf schools. Additionally, we introduce a two-stage system for the Thai-GEC model, automatically detecting and correcting …
The Conceptual Review On The Effect Of Corporate Governance Monitoring Mechanisms On Tax Avoidance, Eveana Mosuin, Nor Balkish Zakaria, Yvonne Joseph Ason
The Conceptual Review On The Effect Of Corporate Governance Monitoring Mechanisms On Tax Avoidance, Eveana Mosuin, Nor Balkish Zakaria, Yvonne Joseph Ason
ASEAN Journal on Science and Technology for Development
Taxes are the primary source of revenue for many nations in order to increase budget revenues and fund national development. Taxation serves multiple purposes because it can positively impact a nation's investment, education, social and economic development. However, tax authorities require assistance with the issue of tax non-compliance, which impedes tax administration and collection. One of the categories of tax non-compliance is tax avoidance, which is one of the company's strategies for legally reducing its tax burden by exploiting loopholes in tax regulations to minimise tax liability. Tax avoidance is when a company follows a particular tax strategy in the …
Neurosymbolic Value-Inspired Ai (Why, What, And How), Amit Sheth, Kaushik Roy
Neurosymbolic Value-Inspired Ai (Why, What, And How), Amit Sheth, Kaushik Roy
Publications
The rapid progression of Artificial Intelligence (AI) systems, facilitated by the advent of Large Language Models (LLMs), has resulted in their widespread application to provide human assistance across diverse industries. This trend has sparked significant discourse centered around the ever-increasing need for LLM-based AI systems to function among humans as part of human society, sharing human values, especially as these systems are deployed in high-stakes settings (e.g., healthcare, autonomous driving, etc.). Towards this end, neurosymbolic AI systems are attractive due to their potential to enable easy-tounderstand and interpretable interfaces for facilitating valuebased decision-making, by leveraging explicit representations of shared values. …
Ontolog Summit 2024 Talk Report: Healthcare Assistance Challenges-Driven Neurosymbolic Ai, Kaushik Roy
Ontolog Summit 2024 Talk Report: Healthcare Assistance Challenges-Driven Neurosymbolic Ai, Kaushik Roy
Publications
Although Artificial Intelligence technology has proven effective in providing healthcare assistance by analyzing health data, it still falls short in supporting decision-making. This deficiency largely stems from the predominance of opaque neural networks, particularly in mental health care AI applications, which raise concerns about their unpredictable and unverifiable nature. This skepticism hinders the transition from information support to decision support. This presentation will explore neurosymbolic approaches that combine neural networks with symbolic control and verification mechanisms. These approaches aim to unlock AI’s full potential by enhancing information analysis and decision-making support for healthcare assistance1.
Human-Ai Teams In Aviation: Considerations From Human Factors And Team Science, Jenna Korentsides, Joseph R. Keebler, Crystal M. Fausett, Sabina M. Patel, Elizabeth H. Lazzara
Human-Ai Teams In Aviation: Considerations From Human Factors And Team Science, Jenna Korentsides, Joseph R. Keebler, Crystal M. Fausett, Sabina M. Patel, Elizabeth H. Lazzara
Journal of Aviation/Aerospace Education & Research
Artificial Intelligence (AI) has transformed the way human-computer interaction (HCI) teams can collaborate and coordinate in various domains, including aviation and crew resource management (CRM). AI's transformative capabilities enhance teamwork, efficiency, and safety, particularly in risk management. AI's ability to process vast amounts of data and provide real-time insights enables informed decision-making and automation of repetitive tasks in aviation. By combining the strengths of AI and humans, outlined in our modified version of the ‘HABA-MABA’ framework, a dynamic teamwork relationship emerges, provided roles are successfully allocated. AI systems are able to act as intelligent assistants, offering timely recommendations, fostering effective …
Low-Resource Automatic Speech Recognition Domain Adaptation – A Case-Study In Aviation Maintenance, Nadine Amin, Tracy L. Yother, Julia Rayz
Low-Resource Automatic Speech Recognition Domain Adaptation – A Case-Study In Aviation Maintenance, Nadine Amin, Tracy L. Yother, Julia Rayz
Journal of Aviation/Aerospace Education & Research
With timeliness and efficiency being critical in the aviation maintenance industry, the need has been growing for smart technological solutions that optimize and streamline the different underlying tasks (Bergkvist & Sabbagh, 2021). One such task is the technical documentation of the performed maintenance operations (Chandola et al., 2022). Instead of manual documentation, voice tools that transcribe spoken logbook entries allow technicians to document their work right away in a hands-free and time efficient manner. However, an accurate automatic speech recognition (ASR) model requires large training corpora (Siyaev & Jo, 2021a), which are lacking in the domain of aviation maintenance. In …
Understanding Of Risky Determinants Affecting The Success Of Design-Build Airport Projects Using Computational Clustering Techniques, Ramy Khalef, Islam El-Adaway
Understanding Of Risky Determinants Affecting The Success Of Design-Build Airport Projects Using Computational Clustering Techniques, Ramy Khalef, Islam El-Adaway
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
The current delivery practices of airport projects are traditionally outdated, lacking innovative and modern techniques which provide overall better cost, schedule, among other performance metrics. Design-build (DB) is an alternative and viable option for the effective delivery of airport projects. Previous studies have lacked in focusing on studying the determinants that affect the success of DB airport projects. This study aims to fill this gap. The goal of this research is to explore these determinants by computationally analyzing the perception of relevant experts. This goal is achieved by: (1) developing a survey to gather valid data on the likelihood of …
A Fuzzy Model And Decision-Support Tool For Assessing And Predicting The Probability Of Bankruptcy Of Construction Companies, Rayan H. Assaad, Ghiwa Assaf, Islam H. El-Adaway
A Fuzzy Model And Decision-Support Tool For Assessing And Predicting The Probability Of Bankruptcy Of Construction Companies, Rayan H. Assaad, Ghiwa Assaf, Islam H. El-Adaway
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
Construction firms face considerable risks that might lead to business bankruptcy. Failed construction companies leave behind unfinished projects, which leads to huge losses to project owners. While previous studies were conducted to understand the factors that contribute to the bankruptcy of construction organizations, little to no research was performed to quantitatively assess the risk of construction business bankruptcy. Hence, this paper addresses this knowledge gap by developing a fuzzy model for predicting the probability of business bankruptcy of construction companies. First, the following six failure warning signs were considered: financial management system, borrowed credit, estimating and job-cost reporting, project management, …
A Chinese Power Text Classification Algorithm Based On Deep Active Learning, Song Deng, Qianliang Li, Renjie Dai, Siming Wei, Di Wu, Yi He, Xindong Wu
A Chinese Power Text Classification Algorithm Based On Deep Active Learning, Song Deng, Qianliang Li, Renjie Dai, Siming Wei, Di Wu, Yi He, Xindong Wu
Computer Science Faculty Publications
The construction of knowledge graph is beneficial for grid production, electrical safety protection, fault diagnosis and traceability in an observable and controllable way. Highly-precision text classification algorithm is crucial to build a professional knowledge graph in power system. Unfortunately, there are a large number of poorly described and specialized texts in the power business system, and the amount of data containing valid labels in these texts is low. This will bring great challenges to improve the precision of text classification models. To offset the gap, we propose a classification algorithm for Chinese text in the power system based on deep …
Human Gender Classification Using Kinect Sensor: A Review, Hesham Adnan Alabbasi, Florica Moldoveanu, Alin Moldoveanu
Human Gender Classification Using Kinect Sensor: A Review, Hesham Adnan Alabbasi, Florica Moldoveanu, Alin Moldoveanu
BAU Journal - Science and Technology
Human Gender Classification using Kinect sensor aims to classifying people’s gender based on their outward appearance. Application areas of Kinect sensor technology includes security, marketing, healthcare, and gaming. However, because of the changes in pose, attire, and illumination, gender determination with the Kinect sensor is not a trivial task. It is based on a variety of characteristics, including biological, social network, face, and body aspects. In recent years, gender classification that utilizes the Kinect sensor became a popular and essential way for accurate gender classification. A variety of methods and approaches, like machine learning, convolutional neural networks, sport vector machine …
Multi-Mode Regulation Of The Drying Process Of Industrial Gas, Isamidin Xakimovich Sidikov Pr, Nashvandova Gulruxsor Murot Qizi Phd
Multi-Mode Regulation Of The Drying Process Of Industrial Gas, Isamidin Xakimovich Sidikov Pr, Nashvandova Gulruxsor Murot Qizi Phd
Technical science and innovation
Currently, much attention is paid to the issue of energy efficiency of gas processing enterprises. The continuous growth of world prices for energy resources requires constant improvement of the management system, providing the most optimal conditions for the flow of technological processes. A conceptual model of the heat-mass transfer process occurring in the absorber as an object of research has been developed, which characterizes the relationship of the variables involved in the drying process of natural gas, control, measurable and immeasurable, as well as controlled parameters have been selected, which are used to develop and study a mathematical model of …
Improvement Of Calorimetric Quality Analyzers For Substances, Makhfuza Azimovna Radjabova
Improvement Of Calorimetric Quality Analyzers For Substances, Makhfuza Azimovna Radjabova
Chemical Technology, Control and Management
It is noted that the development of intelligent means of measuring qualitative indices is of topical importance. Since the quality of many substances is determined by optical methods, an algorithm for spectrophotometric data processing has been developed, which consists of primary data processing (stage I) and determination of qualitative indices of liquid products (stage II). Since the task of numerical determination of colour characteristics of transmittance coefficients of liquid samples is incorrectly set, it is recommended to use regularization methods of A.N.Tikhonov to improve metrological characteristics of the device. On the basis of regularization methods for solving incorrect problems, algorithms …
Application Of Quantum Algorithms In The Synthesis Of Dynamic Objects, Noilakhon Yakubova
Application Of Quantum Algorithms In The Synthesis Of Dynamic Objects, Noilakhon Yakubova
Chemical Technology, Control and Management
Around the world, the food industry is focusing on achieving energy and resource efficiency. One of the main challenges in the field of process automation is the creation of effective control systems using intelligent technologies to improve the quality of processes and achieve the production of high-quality products with less energy and resources. Therefore, it is necessary to work with a large amount of data. Particular attention is paid to the development of computational algorithms for automated high-speed computational analysis systems for processing this data at high speed. Therefore, the article discusses the use of quantum computing methods in controlling …
A Critical Computing Curriculum Design Case: Exploring Tribal Sovereignty For Middle School Students, Kristin A. Searle, Aubrey Rogowski, Colby Tofel-Grehl, Mengying Jiang
A Critical Computing Curriculum Design Case: Exploring Tribal Sovereignty For Middle School Students, Kristin A. Searle, Aubrey Rogowski, Colby Tofel-Grehl, Mengying Jiang
Journal of Computer Science Integration
We report on our efforts to design an integrated computing curriculum for middle school students in Montana that is in line with the Kapor Center’s focus on culturally sustaining-revitalizing pedagogies. Montana provides a unique context for doing this work because a state constitutional mandate requires all K-12 students to learn about tribal histories and cultures through Indian Education For All (IEFA). IEFA centers around seven essential understandings about Indigenous peoples in Montana that are integrated across content areas. In addition, implementation of Montana’s CS standards began in the 2021–2022 school year. In the curricular design, we sought to bring together …
Culturally Responsive-Sustaining Computational Thinking: Enactment In Elementary Classrooms, Victoria Macann, Aman Yadav
Culturally Responsive-Sustaining Computational Thinking: Enactment In Elementary Classrooms, Victoria Macann, Aman Yadav
Journal of Computer Science Integration
Technology has increasingly permeated many aspects of everyday life and this evolution raises the need for individuals to understand how the digital world works and what opportunities and risks it brings (Nouri, Zhang, Mannila & Norén, 2019). For this to be an experience for everyone, we need to rethink how we integrate computational thinking (CT) and provide teachers with tools to center their students’ identities, experiences, and cultures in the classroom. In this paper, we present two case studies of primary (elementary) teachers from a full primary (student ages 5–13) semi-rural school in the North Island of New Zealand that …
The Role Of Young Architects As Entrepreneurship Generational Units In Shaping The Future Of Architecture, Attaa H. Al Obaidi, Anwar. S. Al-Qaraghuli
The Role Of Young Architects As Entrepreneurship Generational Units In Shaping The Future Of Architecture, Attaa H. Al Obaidi, Anwar. S. Al-Qaraghuli
Al-Esraa University College Journal for Engineering Sciences
Youth are the pillar of nations and the secret of their renaissance, thebuilders of their civilization and the line of defense, the main participants inbasic planning processes, and the agents of change to build a world that iscompatible with the aspirations of future generations. This applies to the field ofarchitecture in terms of the importance of young architects in shaping it underthe challenges it faces, which impose interaction in a manner commensuratewith the emerging requirements and needs. This research is based on theconsideration that young architects are an integrated phenomenon thatcontributes to shaping architectural production according to the data of …
Socially Engaged Engineering: A Framework For K-8 Education, Christine M. Cunningham, Gregory J. Kelly, Ashwin Mohan
Socially Engaged Engineering: A Framework For K-8 Education, Christine M. Cunningham, Gregory J. Kelly, Ashwin Mohan
Journal of Pre-College Engineering Education Research (J-PEER)
Socially engaged engineering provides for student learning of the design, analysis, and practices of engineering as well as the ways that engineering is situated in sociocultural contexts. This paper provides a conceptual framework regarding socially engaged engineering for K-8 educators, researchers, and curriculum designers. The framework identifies ways to support youth learning of engineering and considerations of technical, social, environmental, and ethical dimensions of engineering. As engineering enters K-8 educational settings, it is important to introduce the discipline in equity-oriented ways. We draw from the field of engineering for social justice to build this framework for examining engineering at the …
The Unheard Voices Of The Arkansas Delta: Living Through School Desegregation, Tameka D. Williams
The Unheard Voices Of The Arkansas Delta: Living Through School Desegregation, Tameka D. Williams
ATU Theses and Dissertations 2021 - Present
This study was guided by the central research question: What are the lived experiences and perceptions of former African American teachers and students that endured segregation, desegregation, and integration in Arkansas' Delta? The phenomenological study used eight former African American teachers and student participants. Of the participants, there were four former teachers and four former students. In this study, the participants' voices are captured as they share their experiences and perception of each phase of education that influenced their lives and left an everlasting imprint. Through counternarratives, the participants provided insight into education in the Arkansas Delta during school segregation, …
Ncmpy: A Modelling Software For Neutrosophic Cognitive Maps Based On Python Package, Ilanthenral Kandasamy, Divakar Arumugam, Aryan Rathore, Ateeth Arun, Manan Jain, Vasantha .W.B, Florentin Smarandache
Ncmpy: A Modelling Software For Neutrosophic Cognitive Maps Based On Python Package, Ilanthenral Kandasamy, Divakar Arumugam, Aryan Rathore, Ateeth Arun, Manan Jain, Vasantha .W.B, Florentin Smarandache
Neutrosophic Systems with Applications
Cognitive maps are a vital tool that can be used for knowledge representation and reasoning. Fuzzy Cognitive Maps (FCMs) are popular soft computing techniques used to model large and complex systems, and they can aid in explainable artificial intelligence (AI). FCMs, however, cannot model the indeterminacy that arises in a system due to various uncertainties. Neutrosophic Cognitive Maps (NCMs), upgraded FCMs that could model indeterminacy, were introduced to address this issue. NCMs are a generalization of FCMs, a field of cognitive science firmly based on neural networks. NCMs have been used to solve a wide range of problems. NCMs were …
On B-Anti-Open Sets: A Formal Definition, Proofs, And Examples, Sudeep Dey, Priyanka Paul, Gautam Chandra Ray
On B-Anti-Open Sets: A Formal Definition, Proofs, And Examples, Sudeep Dey, Priyanka Paul, Gautam Chandra Ray
Neutrosophic Systems with Applications
The concepts of open sets, closed sets, the interior of a set, and the exterior of a set are the most basic concepts in the study of topological spaces in any setting. When we turn our attention to the concept of anti-topological spaces, we encounter analogous fundamental concepts, such as the definition of anti-open sets, anti-closed sets, anti-interior, anti-exterior, etc. These concepts have already been introduced and studied by mathematicians worldwide. In this article, we introduce and study the concepts of b-anti-open set, b-anti-closed set, anti-b-interior, and anti-b-closure in the context of anti-topological spaces and investigate some of their basic …
Towards Multi-Modal Interpretable Video Understanding, Quang Sang Truong
Towards Multi-Modal Interpretable Video Understanding, Quang Sang Truong
Graduate Theses and Dissertations
This thesis introduces an innovative approach to video comprehension, which simulates human perceptual mechanisms and establishes a comprehensible and coherent narrative representation of video content. At the core of this approach lies the creation of a Visual-Linguistic (VL) feature for an interpretable video portrayal and an adaptive attention mechanism (AAM) aimed at concentrating solely on principal actors or pertinent objects while modeling their interconnections. Taking cues from the way humans disassemble scenes into visual and non-visual constituents, the proposed VL feature characterizes a scene via three distinct modalities: (i) a global visual environment, providing a broad contextual comprehension of the …
Systematic Literature Review On Ontology-Based Indonesian Question Answering System, Fadhila Tangguh Admojo, Adidah Lajis, Haidawati Nasir
Systematic Literature Review On Ontology-Based Indonesian Question Answering System, Fadhila Tangguh Admojo, Adidah Lajis, Haidawati Nasir
Knowledge Engineering and Data Science
Question-Answering (QA) systems at the intersection of natural language processing, information retrieval, and knowledge representation aim to provide efficient responses to natural language queries. These systems have seen extensive development in English and languages like Indonesian present unique challenges and opportunities. This literature review paper delves into the state of ontology-based Indonesian QA systems, highlighting critical challenges. The first challenge lies in sentence understanding, variations, and complexity. Most systems rely on syntactic analysis and struggle to grasp sentence semantics. Complex sentences, especially in Indonesian, pose difficulties in parsing, semantic interpretation, and knowledge extraction. Addressing these linguistic intricacies is pivotal for …
The Impact Of Language And Culture On Productivity: A Recommendation To Implement An Innovative Spanish Language Track, Jordan J. Price
The Impact Of Language And Culture On Productivity: A Recommendation To Implement An Innovative Spanish Language Track, Jordan J. Price
Construction Management
Productivity is a popular focus of construction research because of its efforts to overcome a multitude of project related challenges. This research explores the intersection of language barriers, cultural differences, and productivity in the construction industry with a focus on the impact of bilingual management. It evaluates the impact of these factors on productivity and its beneficial relationship to multilingual management on diverse construction crews. The impending retirement of 40% of the construction labor force calls for proactive initiatives to manage the demographic shift shown by the growing composition of Hispanics in the workforce. The influence of language barriers on …