Accepted Papers

Implementation and Realization Issues of Learning Interfaces in Smart Learning Environments

Masashi Katsumata, Department of Information Technology and Media Design, Faculty of Advanced Engineering, Nippon Institute of Technology, Saitama, Japan

ABSTRACT

This study investigates the construction of a smart learning environment that combines smartwatches, smart glasses, and other devices in addition to smartphones and tablets. To understand the learning status of students using this learning environment, we consider the analysis of learning contents using learning logs and measurement of biometric data of learners. In this study, we implemented a function to monitor the students faces captured by the front camera of a tablet used as a learning terminal in a smart learning environment. We examine how learners faces can be captured using this monitoring function and discuss how these data can be used in a smart learning environment.

KEYWORDS

Smart Learning, Intelligent Tutoring Systems, Personalized Learning Environment.

Grai-pho-logy: Integration of Graphology With Artificial Intelligence

Sandhya M N1, Shree Ram Pandey2 and Rituparna Datta1, 1Independent Researcher, Bangalore, India, 2Manager, Indian Ordnance Factory, India

ABSTRACT

Graphology is the study of handwriting and it is used to analyse personality traits and characteristics. It is based on the idea that a persons handwriting has certain physical characteristics that are thought to reflect various aspects of their personality. It has traditionally been a field conducted by human experts who interpret various aspects of handwriting such as stroke patterns, letter formations, and spacing. While graphology relies on subjective interpretation, the introduction of artificial intelligence (AI) has the potential to enhance and automate certain aspects of graphological analysis. In the present work, the intention is to provide an overview in the integration of the concept of graphology with AI and the method is casted as grAIphology (grAI-pho-logy). The word grAIphology is coined by the authors of the present paper.

KEYWORDS

Graphology, Handwriting Analysis, Artificial Intelligence.

Development of a Data Warehouse for Monitoring the Academic Performance of Students at a University Using the Hefesto Methodology

Xenia Andaur Estica1 and Wilson Castillo-Rojas2 and Manuel Monasterio Cortés3, 1Facultad de Ingeniería y Arquitectura, Universidad Arturo Prat, Iquique, Chile, 2Departamento Ing. Informática y Cs. de la Computación, Universidad de Atacama, Copiapó, Chile, 3Departamento Ing. Informática y Cs. de la Computación, Universidad de Atacama, Copiapó, Chile

ABSTRACT

This article describes the design and implementation of a data warehouse that provides indicators on the academic performance of students at a university in northern Chile. The Hefesto methodology was used for its development, which consists of a series of steps that are rigorously followed to obtain optimal results. This data warehouse integrates the history of subjects and student grades, allowing the university to track student progress and analyse indicators such as the current and historical pass/fail rate. In this way, the university can generate early detection mechanisms to ensure equity in the teaching-learning processes and maintain an adequate level of student retention in their academic programs. The result of this work is a multidimensional model that stores key indicators of student academic performance, with visualizations that include integrated graphs and tables. This allows for simple and efficient online analysis using QlikView as an ad-hoc tool to support institutional and academic program decision-making. Finally, both the authorities and the academic community that require and use these tools express their full satisfaction with this work.

KEYWORDS

Business Intelligence, data warehouse, data mart, data warehousing process, Hefesto methodology.

Designing an Educational Online 3d Escape Room:motivating Learning Through Engaging Gameplay

Isabel Wang1, Allison Wang2, John Morris3, 1, 2Interlake High School, 16245 NE 24th St, Bellevue, WA 98008, 3Computer Science Department, California State Polytechnic University, Pomona, CA 91768

ABSTRACT

"Vamoose" is an inventive online 3D escape room game that merges entertainment with STEM education [4]. Motivated by the absence of in-person escape room experiences during the pandemic, the game offers players an engaging platform to learn science, technology, engineering, and mathematics (STEM) while solving captivating puzzles [5]. The game s puzzles, inspired by academic subjects, enable participants to test their knowledge and acquire new insights, fostering motivation and engagement among learners. Despite challenges in implementing a multiplayer feature, the game was refined through rigorous debugging. Extensive playtesting involving diverse age groups and educational backgrounds demonstrated Vamooses effectiveness in transcending age-related differences, engaging learners, and promoting problem-solving skills. Ultimately, Vamoose exemplifies the potential of gamified learning to revolutionize education by seamlessly integrating entertainment and academic enrichment.

KEYWORDS

Escape Room, Multiplayer, Education, Puzzles.

Enhancing Financial Literacy and Decision-making Through Gamified Learning: an Empirical Investigation of User Engagement, Effectiveness, and Feedback

Zhen Ao Wang1, Emmanuel Bruce Loh2, 1Shanghai United International School Wanyuan campus, 248 Hongsong Rd (E), Minhang District, Shanghai, China, 2Computer Science Department, California State Polytechnic University, Pomona, CA 91768

ABSTRACT

This paper presents a comprehensive exploration of gamified financial educations impact on decision-making skills and financial literacy [5]. The introduction contextualizes the significance of effective financial decision-making in a complex economy [4]. The methodology outlines the creation of a gamified financial simulation and the design of an external feedback survey [6]. Two experiments were conducted: the first demonstrated improved decision-making skills through active engagement in the simulation, while the second garnered external perspectives on the programs effectiveness, highlighting increased financial awareness and engagement [7]. Results indicated enhanced postassessment scores and practical application of financial strategies. External feedback emphasized moderate enjoyment and identified areas for improvement, particularly in investment clarity and realism. Collectively, these findings underline the potential of gamified approaches for financial education, suggesting avenues for refinement to optimize user experience and learning outcomes [8].

KEYWORDS

Decision Making, Education, Risk Management, Experiential Learning.

Algorithms for the Thief Orienteering Problem on Special Graph Classes

Andrew Bloch-Hansen and Roberto Solis-Oba, Department of Computer Science, Western University, ON, Canada

ABSTRACT

In the thief orienteering problem an agent called a thief is routed through a weighted graph G = (V,E) from a start vertex s to an end vertex t. A set I of items each with weight wi and profit pi is distributed among V \ {s,t}. The thief, who has a knapsack of capacity W, must follow a simple path from s to t within a given time T while packing in the knapsack a set of items taken from the vertices along the path of total weight at most W and maximum profit. The travel time across an edge depends on the edge length and current knapsack load. The thief orienteering problem has a polynomial-time approximation scheme when the input graph is directed and acyclic. We give polynomial-time algorithms for transforming instances of the thief orienteering problem on outerplanar graphs and series-parallel graphs into equivalent instances of the thief orienteering problem on directed acyclic graphs; therefore, yielding polynomial-time approximation schemes for the thief orienteering problem on these graph classes. We also present a fully-polynomialtime approximation scheme for a restricted version of the problem where the input graph is a clique.

KEYWORDS

Thief Orienteering Problem, Outerplanar, Series-Parallel, Clique, DAG, Graph Transformation.

Information Overload: a Conceptual Model

Anasuodei Moko, Maudlyn Victor-Ikoh and Biobele Okardi, Department of Computer Science and Informatics, Federal University Otuoke, Nigeria

ABSTRACT

This age of massive production and usage of information ranging from online resources to print has constantly created the need to educate individuals on Information overload, which happens when one is saddled with the task of processing and accessing excessive information at work and in life generally. Information overload is the abundance of information with limited cognitive processing capacity to the receiver. Despite its widespread discussion, a universally accepted definition or explanation remains elusive due to the diverse terminology employed. This variation in terminology implies differing levels of information overload. There is an urgent need to develop various kinds of models that help designers of information understand, measure and ascertain when an individual is overloaded with information. Drawing on Dubins theory, which provides a systematic framework for conceptual model development, this study utilizes the initial stages of theory building to create a Conceptual Model of information overload and its Primary Components together with their Sub-components. This model serves as a foundation for generating testable hypotheses and operationalizing the concept of information overload for further empirical investigations.

KEYWORDS

Information, Overload, Model, Information Processing, Cognitive Overload.

Designing the M-agri Market Information Services Application to Provide Feedback on the Most Useful and Impactful Services Specific to the Namibian Rural Vegetable Small-scale Farmers

Akot Benjamin Awanda1, Eliazer Mbaeva2, and Professor Hippolyte N. Muyingi3, 1Department of Computer Science, Namibia University of Science and Technology (NUST), Windhoek, Namibia ,2Department of Informatics, NUST, Windhoek, Namibia , 3Department of Computer Science, NUST, Windhoek, Namibia

ABSTRACT

Providing access to agricultural market information (AgriMI) services on best market prices, markets, and value-added services (VAS) like demand, business contacts, addresses, and dates of traders, consumers, transporters, etc., has improved the incomes of most rural small-scale farmers (SSFs). In recent years, while mobile-based agricultural market information services have been designed to primarily send AgriMI services on a push approach i.e., automatic updates via SMS, these have been regarded as not customizable and interactive. As such, this research aims to design the M-Agri Market Information Services Application (i.e., M-AgriMIS App) using the pull approach (m-app). The design results in Agile and Android Native Approach in Kotlin showed that the M-AgriMIS App could allow SSFs to customize their AgriMI services and/or allow App providers to provide services via users’ profiles for the SSFs to receive the most useful and impactful AgriMI services specific to the Namibian Rural SSFs’ actual needs.

KEYWORDS

Agriculture Market Information, Agriculture Market Information Services, Design, Small-Scale Farmers, Agile Dynamic System Development Method, Android Native Approach, Mobile Applications, Android Kotlin.

Using Machine Learning to Identify Software Weaknesses From Software Requirement Specifications

Mounika Vanamala, Sean Loesch and Alexander Caravella, Department of Computer Science, University of Wisconsin-Eau Claire, Eau Claire, Wisconsin 54701, USA

ABSTRACT

Secure software engineering is crucial but can be time-consuming; therefore, methods that could expedite the identification of software weaknesses without reducing the process’ efficacy would benefit the software engineering industry and thus benefit modern life. This study focuses on finding an efficient machine learning algorithm to identify software weaknesses from requirement specifications. The research uses the CWE repository and PROMISE_exp dataset for training. Keywords extracted using latent semantic analysis help map the CWE categories to PROMISE_exp. Naïve Bayes, support vector machine (SVM), decision trees, neural network, and convolutional neural network (CNN) algorithms were tested, with SVM and neural network producing reliable results. The studys unique contribution lies in the mapping technique and algorithm selection. It serves as a valuable reference for the secure software engineering community seeking to expedite the development lifecycle without compromising efficacy. Future work involves testing more algorithms, optimizing existing ones, and improving the training sets’ accuracy.

KEYWORDS

Machine Learning, Software Weakness, Common Weakness Enumeration, Neural Network, Software Requirement Specification.

Computational Study on the Pattern of Change in Heat Dissipation With Change in Convective Surface Area of an Adaptive Structure

Shree Ram Pandey, Bishakh Bhattacharya, and Akkarapakam Suneesh Jacob, Rituparna Datta, Department of Mechanical Engineering, IIT Kanpur, Kanpur-208016, India

ABSTRACT

Artificial Intelligence can be used in design of adaptive structures for data-driven modelling, design of intelligent control algorithms, predictive analytics, and design optimization. Adaptive structures for thermal management of electronic devices refer to systems or components that can dynamically adjust their shape, properties, or configurations to optimize heat dissipation and regulate the temperature in electronic devices. The current study is based on the application of adaptive structures for heat transfer augmentation. These structures are designed to enhance cooling efficiency, prevent overheating, and ensure reliable operation of electronic components. Thermal simulation of adaptive structures is highly interdisciplinary, involving aspects of mechanical engineering, materials science, control systems, and numerical methods. The proposed heat sink changes its shape and hence exposed surface area in accordance with changes in surrounding conditions to cater to variable heat dissipation requirements by various thermal systems. A cylindrical heat sink with radial fins having a unique design feature of variable heat transfer area is studied for thermal performance. The objective of this study includes studying the numerical pattern of the effect on heat dissipation by changing the surface area. Two sets of dimensions of the model are taken for numerical simulation, and the change in heat transfer coefficient with respect to a gradual increase in the surface area is analyzed.

KEYWORDS

Intelligent systems, Adaptive structures, Heat sinks, Variable heat transfer rate, Numerical modelling.

Revolutionizing Personalized Web Presence: Ai Powered Automated Website Generationfor Streamlined Individual Expressionand Accessibility

ZhenYang1, TianchengXu2, 1ShanghaiUnitedInternationalSchoolQingpuCampus,No.32,YejinRoad,QingpuDistrict, Shanghai, 2Computer Science Department, California State Polytechnic University, Pomona,CA91768

ABSTRACT

In the present information technology era, the desire for personalized individual websites is notably significant [1]. The creation of such personal websites necessitates proficient knowledge of HTML-based programming, a skill predominantlypossessedbyprofessionalprogrammers[2].Asanalternative tothislimitedoption, individualsoften resort to purchasing websites from service providers, incurring substantial costs and time investments. In order to address this widespread demand for personalized websites, we propose the implementation of an AI program capable of automatically generating websites based on user instructions [3]. Such a program would considerably reducethefinancialandtemporalexpendituresassociatedwithpurchasingpre-madewebsites.

KEYWORDS

ChatGPT,LargeLanguageModel,PromptEngineering.

A Smart Interactive and Collaborative Online Coding Platform for Programming Educationusing Machine Learning and Websocket

DavidZhang1,AngLi1, 1University HighSchool, 4771CampusDr, Irvine,CA92612 , 2Computer Science Department,California State Polytechnic University, Pomona,CA91768

ABSTRACT

Amidst the swift digital evolution of the 21st century, the incorporation of computer science education across industries has become imperative [13]. This paper addresses the challenges of real-time collaboration and accessibility in programming education, introducing a collaborative coding platform. The platform empowers educators, students, and programmers to seamlessly engage in coding projects while efficiently managing progress and fostering interactive learning. By harnessing cloud databases and real-time editors, the platform provides a unified workspace for collaborative endeavors, communication, and project sharing [14]. Challenges associated with real-time collaboration across devices and compatibility were adeptly handled through Firepad integration and platform-specific optimizations. Through empirical assessment involving students and educators, the platforms efficacy, user satisfaction, and transformative potential were gauged. The findings underscored heightened collaboration efficiency and user contentment with real-time capabilities, while also highlighting the importance of refining accessibility [15]. Ultimately, this platform presents a holistic solution to elevate programming education andcollaboration,renderingitaninvaluableassetacrossdiverse scenarios.

KEYWORDS

WebSocket,Communication,ComputerScience,Education.

Grai-pho-logy: Integration of Graphology With Artificial Intelligence

Sandhya M N1, Shree Ram Pandey2 and Rituparna Datta1, 1Independent Researcher, Bangalore, India, 2Manager, Indian Ordnance Factory, India

ABSTRACT

Graphology is the study of handwriting and it is used to analyse personality traits and characteristics. It is based on the idea that a persons handwriting has certain physical characteristics that are thought to reflect various aspects of their personality. It has traditionally been a field conducted by human experts who interpret various aspects of handwriting such as stroke patterns, letter formations, and spacing. While graphology relies on subjective interpretation, the introduction of artificial intelligence (AI) has the potential to enhance and automate certain aspects of graphological analysis. In the present work, the intention is to provide an overview in the integration of the concept of graphology with AI and the method is casted as grAIphology (grAI-pho-logy). The word grAIphology is coined by the authors of the present paper.

KEYWORDS

Graphology, Handwriting Analysis, Artificial Intelligence.

Natural Language Processing in Public-private Partnership Implementation in Rwanda Health Sector

LONGIN DUSENGEYEZU1 AND DR. ISSA KARAMBAL2, 1UNIVERSITY OF RWANDA COLLEGE OF BUSINESS AND ECONOMICS, AFRICAN CENTER OF EXCELLENCE IN DATA SCIENCE, 2AIMS- QUANTUM LEAP AFRICA (QLA)

ABSTRACT

The main goal of this study is to determine whether employing NLP techniques in qualitative research can improve the efficiency and rigor of the research process by enabling researchers to process, analyse, and extract meaningful information from qualitative data. It also aims to determine whether NLP can support researchers in identifying patterns, identifying key themes, and deriving important insights from textual data, facilitating a deeper understanding of the phenomena under investigation. To achieve the above goals this study compares the results of manual coding and Natural Language Processing (NLP) methods. NLP was used in qualitative data analysis activities, such as creating a codebook and finding relevant responses. Those were done with the help of NLP topic modelling techniques, paraphrase mining as well as NLP text summarization. Both results obtained in all three methods evaluated in this study produced conceptual similarity with human codes, neither method was capable of identifying the themes that would be the focus of the final report generated by thematic analysis. At the moment, this study shows that NLP can be used as a supplement to the actual qualitative method, but it doesnt seem to be a good replacement for human analysis in qualitative research.

KEYWORDS

NLP, topic modelling, Paraphrase mining, codebook, public health research, transcript, responses.

Fostering Inclusivity and Body Positivity: an Aidriven Fashion Recommendation System for Mitigating Body Dysmorphic Disorder Effects

Yishen Wei1, Kian Azadi2, 1Tarbut V’ Torah Community Day School, 5 Federation Way, Irvine, CA 92603, 2Computer Science Department, California State Polytechnic University, Pomona, CA 91768

ABSTRACT

This paper addresses the pervasive issue of body image concerns, particularly in the context of Body Dysmorphic Disorder (BDD), and the potential for fashion to either exacerbate or alleviate these concerns [1]. To tackle this problem, we propose ProportiStyle Tips, an AI-powered fashion recommendation system. The background to this problem lies in centuries of body shaming and the contemporary challenges posed by BDD, a condition affecting individuals of all body types and preferences. ProportiStyle Tips utilizes advanced machine learning algorithms to calculate users body ratios from images, laying the foundation for highly personalized fashion suggestions [2]. Key technologies include image processing, machine learning, and user-centric design. Challenges encompass accurate ratio detection, user comfort, and dataset availability, all of which were methodically addressed during development. Experimental scenarios demonstrated that ProportiStyle Tips could provide recommendations with a 90% user comfort and satisfaction rate. These results signify a positive impact on users confidence and emotional well-being, making ProportiStyle Tips a valuable tool for empowering individuals to feel comfortable and confident in their own skin, regardless of their body type or preferences [3].

KEYWORDS

MediaPipe, Flutter, Firebase, AWS.

Cloud Native Network Security Architecture Strategy Under Zero Trust Scenario

ShuoSheng,KunChe, Zenitera Co. Ltd,Shanghai, China

ABSTRACT

Zero Web of trust access is an IT security solution that provides secure remote access to organizational applications, data and services based on Well-defined expression access control policies. But in the cloud native scenario, the load reconfiguration strategy under the zero trust gateway and Microservices side vehicle model architecture needs to be solved urgently. Based on the understanding of the zero trust mechanism of cloud native Microservices system, this paper analyzes the genetic defects in the inherent mechanism of cloud native, especially the service governance framework mechanism, from a new perspective. These genetic defects will not disappear with the intergenerational development of mobile cloud native. Therefore, they are also known as the endogenous security common problems of cloud native. This article presents the endogenous security threats that may be introduced by security flaws such as "default information authenticity" and "ubiquitous data visibility". Guided by the theory of endogenous security in cyberspace, it proposes the idea and method of using "zero trust" to break the "default trust" and using "implicit mapping" to achieve "limited visibility" of user data to solve the common problems of cloud native endogenous security, And a new zero trust gateway architecture ecology and corresponding applicability function quantification load balancing strategy have been reconstructed. Experiments show that the zero trust architecture and quantification function proposed in this paper are progressiveness.

KEYWORDS

Zero trust; Endogenous security;Cloud native.

A Novel Approach to Addressing the Federal Cybersecurity Workforce Gap

Jonathan Luckett, College of Business, Innovation, Leadership, and Technology, Marymount University Arlington, VA 22207

ABSTRACT

The cybersecurity workforce gap is a growing problem in the government. As the number of cyberattacks continues to increase, the demand for cybersecurity professionals has grown exponentially. However, the supply of qualified professionals has not kept up with the demand, leading to a significant workforce gap. This paper recommends a call to action for the government to take steps to address the cybersecurity workforce gap. The novel approach proposed in this paper involves creating a Cyber Force made up of civilian employees who have an interest in cybersecurity. This Cyber Force would be trained and certified in cybersecurity, and would be available to support government agencies with their cybersecurity needs. The government should implement this novel approach to addressing the cybersecurity workforce gap as soon as possible. The cybersecurity threat landscape is constantly evolving, and the government needs to be prepared to meet the challenges of tomorrow.

KEYWORDS

cybersecurity workforce gap, government, Cyber Force, novel approach.

Development of Methodology for Automated Diagnosis of Skin Lesions Based on Deep Learning

Rahul M Mulajkar and Monika S Nalawade, Department of E&TC Engineering, Jaihind College of Engineering, Kuran, Pune, India

ABSTRACT

Skin lesions are a commonly observed occurrence and can serve as potential indicators of severe medical conditions, such as skin cancer. The conventional approach to diagnosing these lesions relies on the visual examination conducted by a dermatologist. However, this process can be time-consuming and susceptible to human errors. Fortunately, the advent of deep learning technology offers a promising solution for automated skin lesion diagnosis through the utilization of artificial intelligence. This advanced technology enables the training of deep learning models on extensive datasets comprising labeled images of skin lesions. By doing so, these models can effectively identify patterns and accurately classify various types of skin lesions. Consequently, they possess the potential to provide swift and reliable diagnoses with high precision. Moreover, the implementation of automated diagnosis using deep learning has the capacity to improve medical accessibility, particularly in underserved areas. Nevertheless, there are still challenges that must be addressed in the development and application of automated skin lesion diagnosis. These challenges encompass the requirement for vast and diverse datasets for training and testing purposes, the mitigation of biases and fairness concerns, and the ethical usage of AI in the healthcare field. The integration of deep learning into automated skin lesion diagnosis holds tremendous potential in enhancing healthcare outcomes and widening medical accessibility. To realize these benefits, continuous research and development efforts in this domain are crucial. By doing so, we can ensure the ethical and effective utilization of this technology, ultimately leading to improved healthcare services and outcomes for patients.

KEYWORDS

CNN, Deep Learning, Feature Extraction, Image Processing, Image Classification, Skin Cancer, Skin Lesions Detection.

Non-traditional Dynamical System With Negative Stiffness for Damped Primary Structures: Modelling, Optimization,simulation, and Optimal Control

Okba Abid Charef1 and Mayada Bouaoun2, 1Department of Mechanical Engineering, Ecole Nationale Polytechnique de Constantine, Constantine, Algeria, 2Faculty of Process Engineering, University of CONSTANTINE3 SALAH BOUBNIDER, Constantine, Algeria

ABSTRACT

In this paper, a mini-max design of a non-traditional dynamical system with negative stiffness for damped primary structures is investigated to reduce high amplitudes in the resonant range of vibrations. The differential equation is formulated and the analytical solution of the system is derived. The formulation of optimal design parameters of a dynamic vibration absorber (DVA) is a very complicated task when the primary structure is damped. Using the principles of fixed-point theory and under the assumption of a structural damping ratio within the range of light to moderate, the closed-form solution for the optimal tuning coefficient is analytically obtained. Then, the optimal damping ratio and the optimal negative stiffness parameter of the proposed non-traditional DVA with negative stiffness are determined numerically by solving a set of nonlinear equations established using Chebyshev’s equioscillation theorem. Extended simulations are conducted to examine the effectiveness of the optimally designed DVA and the sensitivity of the optimal parameters. Finally, the vibration control performance of the proposed configuration is compared with those of two typical DVAs, which were presented by Liu and Pennestri, respectively. The comparison results demonstrate that the non-traditional DVA with negative stiffness significantly enhances vibration control by reducing the dynamic magnification factor of damped primary systems.

KEYWORDS

Mini-Max Optimization, Vibration Control Performance, Non-Traditional DVA, Damped Primary System, Negative Stiffness.

An Intelligent Mobile Programto Providezerocostbut Effective Golf Coaching by Analyzinggolfer’sswings Using Ai and Machine Learning

Senlin Yang1, Matthew Ngoi2, 1Chadwick School, 26800 S Academy Dr, Palos Verdes Peninsula, CA90274, 2Computer Science Department, California State Polytechnic University, Pomona, CA91768

ABSTRACT

Golf is enjoyed by many individuals, however the high coaching costs hinder golfers, particularly those fromlowerincome backgrounds, from reaching their potential. This issue not only af ects the golfers themselves but alsoimpacts the growth and diversity of its community. To address this, I ve developed the "GolfBud" app in which userscan use their smartphones to record their swing and the app will use algorithms to generate comparisons withprofessional swings in the form of still images: providing personalized feedback for improvement. It has three maincomponents, including a Flutter mobile interface, a server hosting the golf engine analyzer, and Firebase for imagestorage. The videos submitted by users are analyzed frame by frame, and get the body angles using OpenCVandMediapipe [11][12]. These frames are grouped using K-means and then one frame is chosen fromeach group. Lastly, each of those frames are compared with similar frames from a professional swing. Three main challengeswere figuring the methods to analyze golf swings, finding features to group the frames together and devising awayto allow easy access to the golf analyzer [14]. This innovative solution of ers an af ordable way to enhanceagolfers skills without having to pay the high coaching fee. It is af ordable, accessible, and ef ective.

KEYWORDS

Golf, AI, Mobile Application, Swing analyser.

Enhancing Trap Shooting Proficiency Throughdynamic Home Practice Simulation: Anovel Approach for Precision and Consistency Improvement

Spencer Yuan1, John Morris2, 1Seattle Academy, 1201 E Union St, Seattle, WA 98122, 2Computer Science Department, California State Polytechnic University, Pomona, CA91768

ABSTRACT

I noticed that most trap shooters practice dry firing towards a wall, pretending that there is a target on the wall, going right or left [1]. However, they are not aware if they have come close to or “hit” the target by just imaginingit. It is very dull to lift a gun toward a wall with nothing on it. I decided to create a Python programto haveaperson practice and shoot as if at a range [2]. The program lets a person practice the correct technique whichinvolves not moving the gun with their arms, but with their core. The shooters can practice peripheral vision, pulling the trigger at the right time and following the target. Results have shown that people were more engagedusing the program while lifting a gun, than only lifting a gun towards the wall.

KEYWORDS

Trap Shooting, Trap Shooting practice, Clay Target Practice, Target Following Practice.

A Helmet Detection and Speed Reminder Systemforenhanced Safety in Electric Scooter Usage

Ming Yin1, Jonathan Sahagun2, 1Shanghai No.54 High School, 34 Kangping Rd, Xuhui District, Shanghai, China, 2Computer Science Department, California State Polytechnic University, Pomona, CA91768

ABSTRACT

The rising popularity of electric scooters has raised safety concerns due to inadequate helmet usage and high-speeddriving [4]. This study introduces a solution to address these issues by proposing a Helmet Detection and SpeedReminder System [5]. Implemented on a Raspberry Pi platform, the system employs artificial intelligence techniquesto detect helmet usage and monitor riding speeds [6]. Real-time video analysis and accelerometer data enablehelmet detection and speed monitoring [7]. The system of ers audio alerts to encourage helmet usage andsafespeeds. Experiments were conducted to evaluate accuracy, robustness, and user satisfaction. The helmet detectionmodule achieved 90.4% accuracy, while users expressed high satisfaction and willingness to adopt the system. Challenges included intricate helmet designs, addressed by a diverse training dataset. The proposed systemnot onlyenhances rider safety but also promotes responsible riding, contributing to a safer urban mobility landscape.

KEYWORDS

Helmet Detection, Speed Reminder, Raspberry Pi, Intelligent.

Development of a Tesla Music Coil From Signal Processing

Samaniego José, Rosero Jorge and Lorena Luzcando, School of Telecommunications Engineering, Escuela Superior Politécnica de Chimborazo, Riobamba, Ecuador enrique

ABSTRACT

This paper presents a practical and theoretical model for the operation of the Tesla coil using digital signal processing. The research is based on the analysis of ten scientific papers exploring the development and operation of the Tesla coil. Starting from the Testa coil, several modifications were carried out on the Tesla coil, with the aim of amplifying the digital signal by making use of digital signal processing. To achieve this, an amplifier with a transistor and digital filters provided by MATLAB software were used, which were chosen according to the characteristics of the signals in question.

KEYWORDS

Signal Process, Signal Modulation, Tesla Coil, Audio Equalizer.

An Intelligent System to Enhance Mental and Physical Health Through Sleep Monitoring and Recommendations Using Motion Detection and Environmental Sensors

DuojiaChen1, WyattL.Bodle2, 1The WebbSchools, FrontEntrance, 1175WBaseline Rd,Claremont,CA91711 , 2

ABSTRACT

This study introduces a new approach to tackling insomnia aimed at international students. It offers a comprehensive solution using environmental sensors and an integrated app. The motivation for this comes from many young students who have insomnia triggered by a new environment. The absence of sleep due to moving aroundandjoining a new culture make it hard to accomplish many things. This apprecords sleep variablessuch as motion, light, ambient light, temperature, humidity, and sound. The data is then sent to a database to be pulled and analyzed.Theappallowsuserstoquicklyandeasily viewsleepdataandtrendsinrealtime with acalendarfordate selection and viewing trends. When an environmental variable is deemed out of the range of widely accepted ideal sleepvalues,theappwill givetheusersuggestionsonwhatto correct.Experimentaltesting wasconductedto assess the accuracy of the sensors and the algorithms used to translate that to viewable qualitative data for the user. We found that with using a frame differencing algorithm, there would need to be no motion of the physical camera throughout the night. A second discovery was that multiple people within the frame may affect the users sleep data. Compared to existing methodologies, the app distinguishes itself by considering a range of environmental factors thatoffersubjectiveaswellasobjectivesleepqualitytracking. Italsogivesuserstheopportunitytoformbondsand help each other on the community page. In conclusion, this product presents a reliable, cheap, and easy-to-use methodtoevaluateandcorrect sleephealthaswellastacklesleep-relatedmedicalissuessuchasinsomnia.

KEYWORDS

Firebase,Flutter, Insomnia,SleepEfficiency,SleepDeprivation.

Questgenius: an Intelligent Questionnaire Generation and Result Analyzing System for Investigation and Research Using Artificial Intelligence and Nature Language

Tianchen Du1, Ang Li2, 1Crean Lutheran High School, 12500 Sand Canyon Ave, Irvine, CA 92618, 2Computer Science Department, California State Polytechnic University, Pomona, CA 91768

ABSTRACT

Addressing the complexities of survey creation, response collection, and accurate data analysis, this project aims to enhance the accessibility and quality of survey-based insights [1]. The background centers on the challenges faced in generating effective surveys, avoiding biases, and employing comprehensive analytics [2]. The proposal involves a web-based platform equipped with AI-driven survey generation, unbiased question design, and professional statistical analysis. Key program components encompass user-friendly interfaces built with HTML, CSS, and JavaScript, seamlessly integrated with AI models for prompt generation and response synthesis. Challenges were met by refining AI prompts for robustness and implementing stringent user input validation. Experimental scenarios included evaluating AI response resilience to user-crafted prompts, leading to insights on potential vulnerabilities and AIs adaptability [3]. Results demonstrated that well-crafted user prompts influenced AI outputs without compromising core functionality. Ultimately, this innovative solution offers beginners and users unfamiliar with statistics a powerful survey tool empowered by AI [4]. The ability to create comprehensive surveys, mitigate biases, and access professional insights positions this platform as a valuable resource for informed decision-making across diverse fields.

KEYWORDS

AI Generate survey, Sample selection, Analyze results, Online Survey link.

A Convenient Mobile Application to Modify High-sugar Baking Recipes to Diabetic-friendly Using Text Recognition and Artificial Intelligence

Julia Yili Shang1, Julian Avellaneda2, 1Diamond Bar High School, 21400 Pathfinder Rd, Diamond Bar, CA 91765, 2Computer Science Department, California State Polytechnic University, Pomona, CA 91768

ABSTRACT

Previous research demonstrated that an average American adult could easily over consume the daily suggested amount of added sugar. Our team realized that a typical dessert contains way more sugar than suggested amount, which can be potentially harmful to obese and diabetic patients. We decided to develop a mobile application scans conventional baking recipe, recognize the and generates a healthier recipe reduced in sugar using AI to replace some of the ingredients to healthier ones. The three major technical components are authentication service, AI, and text recognition and matching function. We integrated OpenAI to build the template, Spacy function and image.scan for text recognition, and firebase authentication for login functions. Two experiments were conducted to test the accuracy of AI and text recognition. All the testing’s suggested that the app is able to adjust any baking recipe to a healthier alternative, while guaranteeing the basic tastes.

KEYWORDS

Diabetes, Baking, Mobile Application, Health.

Game4good: a Community-based and Interactive Gameplatform for Social Impact Using Game Engine and Big Data Analysis

Yize Wang1, Moddwyn Andaya2, 1Crean Lutheran High School, 12500 Sand Canyon Ave, Irvine, CA 92620, 2Computer Science Department, California State Polytechnic University, Pomona, CA 91768

ABSTRACT

This paper introduces a novel approach to education through game-based learning by merging chemistry and traffic planning concepts into interactive experiences [1]. The project addresses challenges in comprehending chemical reactions and traffic congestion issues [2][3]. A Unity Engine-based game was developed for each subject [4]. The chemistry game enabled players to simulate real-life chemical reactions and compound combinations, enhancing practical understanding [5]. The traffic planning game offered scenarios to design effective traffic flow, fostering awareness and knowledge of traffic management. Both experiments demonstrated significant post-test score improvements in the experimental groups compared to controls. Results underscore the efficacy of game-based learning in promoting experiential comprehension. The immersive and interactive nature of the games facilitated engagement, enabling participants to apply theoretical knowledge to practical situations. These findings contribute to innovative educational tools that bridge theoretical gaps and provide effective learning avenues.

KEYWORDS

Modeling, Data Science, Machine Learning, Game Engine.

Quantum Theory of Music and Languages

Mballa Abanda Luc Aurelien Serge ; Henda Gnakaté Biba

ABSTRACT

Quantum entanglement defies understanding, even Einstein one of the founding fathers were astonished. The Entanglement is a quantum phenomenon in which two or more particles share the same properties. So that the state of one of them changes, that of its twin changes instantly, as if it were a single system or a phantom action at a distance. To say these laws are strange is an understatement. The main hypotheses proposed around the definition of the syllable and of music, of the common origin of music and language, should lead the reader to reflect on the cross-cutting questions raised by the philosophical debate on the notions of universal in linguistics and musicology. These are objects of controversy and there lies its interest: the debate raises questions that are at the heart of theories on language. [Saying and singing were once the same thing.] J.J. Rousseau 1776; this is called quantum entanglement. Having reconstituted the [Say and Sing] which are the properties of the mother language of humanity, from a tonal language, daughter language of the said language, according to a quantum approach, it is necessary to ask the one and only question; Is there an entanglement between music and language?My work opens the way to a new field of interdisciplinary knowledge, giving rise to the practice of interlocution between the social, cognitive, experimental sciences, the activities of artistic creation and the question of modeling in the human sciences: mathematics, computer science, automatic translation and artificial intelligence.

An Attention Free Long Short-term Memory for Time Series Forecasting

Hugo Inzirillo1 and Ludovic De Villelongue2, 1Department of Finance and Insurance, CREST IP-PARIS, 2Department of Ecnomics and Finance, Université Paris Dauphine

ABSTRACT

Deep learning is playing an increasingly important role in time series analysis. We focused on time series forecasting using attention free mechanism, a more efficient framework, and proposed a new architecture for time series prediction for which linear models seem to be unable to capture the time dependence. We proposed an architecture built using attention free LSTM layers that overcome linear models for conditional variance prediction. Our findings confirm the validity of our model, which also allowed to improve the prediction capacity of a LSTM, while improving the efficiency of the learning task.

KEYWORDS

Deep Learning Architecture, Time series, Forecasting.

Cross-blockchain Technology for an Interoperable and Scalable Digital Contact Tracing

Farbod Behnaminia and Saeed Samet, School of Computer Science, University of Windsor, Windsor, Canada

ABSTRACT

The COVID-19 pandemic has highlighted the importance of contact tracing as a tool for controlling the spread of the virus, but it has also raised concerns about the privacy and security of personal information. Blockchain technology, with its immutability and security features, has the potential to address these concerns. However, traditional blockchain solutions may not be sufficient to protect sensitive personal information, especially when it comes to interoperability with other chains that may have different privacy standards. Cross-blockchain technology, such as the interoperability feature of the Polkadot network, allows for the creation of a decentralized and distributed contact tracing system that can be used by multiple organizations and jurisdictions while ensuring privacy. This research examines the technical challenges and potential solutions of using cross-blockchain technology for interoperable and scalable digital contact tracing. In this research, we proposed a solution using the Polkadot network, where the personal and contact information is stored on a blockchain, accessible only to authorized parties. The use of cross- blockchain technology and encryption would ensure that sensitive personal information is protected and that only authorized parties can access the data. Additionally, the data on the private blockchain would be shareable with other health authorities or other blockchain networks by using the interoperability feature of the Polkadot network. Overall, this research seeks to demonstrate the potential benefits and limitations of using cross-blockchain technology for digital contact tracing applications and highlights the importance of further research and development in this area by providing recommendations for implementing this technology. With the right approach, it is possible to create a contact tracing solution that is both effective and respects the privacy of individuals.

KEYWORDS

Cross-blockchain Technology, Interoperability, Scalability, Digital Contact Tracing.

Securing E-commerce Deliveries: an Integrated Mobile Application and Parcel Locker System for Mitigating Porch Piracy

Jonathan Ziqi Chen1, Matthew Xuehao Li2, Jonathan Sahagun3, 1Portola High School, 1001 Cadence, Irvine, CA 92618, 2Portola High School, 1001 Cadence, Irvine, CA 92618, 3Computer Science Department, California State Polytechnic University, Pomona, CA 91768

ABSTRACT

With the rapid surge in porch piracy, largely fueled by the proliferation of online shopping, there is an urgent need for innovative solutions to secure package deliveries [8]. This paper addresses the pressing issue of package theft through the development of a comprehensive solution that integrates a mobile application and a secure parcel locker system. Recognizing the limitations of existing methodologies, our proposed solution places a strong emphasis on technical robustness, user experience, and security. Our approach revolves around a user-friendly mobile application catering to both consumers and couriers. This application seamlessly interfaces with a network of secure parcel lockers, creating a robust ecosystem. Leveraging Google Firebase for data storage and Android Studio Code for programming, our system ensures secure and efficient access [9]. Overcoming challenges like efficient communication with Raspberry Pi and optimal locker design layout, we utilized wireless technology and innovative design concepts [10]. Rigorous experimentation encompassing usability, effectiveness, and user satisfaction assessments has demonstrated the solutions efficacy in thwarting unauthorized access. The results underscore the significance of a user-centered design, technical feasibility, and comprehensive security measures. By offering a multifaceted approach that prioritizes convenience, security, and user-friendliness, our solution presents a compelling remedy to the pervasive problem of porch piracy.

KEYWORDS

Android studio code, Mobile application, Flutter, Online database.

Adoption of Blockchain Technology Framework for Addressing Counterfeit Drugs Circulation

Ohis G. Mega1, Maureen I. Akazue1, JohnPaul A.C. Hampo1, Edith U. Omede1, 1, 2, 4Department of Computer Science, Delta State University, Abraka, 3Department of Computer Science, Federal University of Technology, Owerri

ABSTRACT

Counterfeit drugs are a problem both in developed and developing countries. Nigeria is a developing country experiencing the problem of counterfeit drugs and as such is the use case for this research work. The negative effects counterfeit drugs have on human health and economy of the country calls for urgent attention. One amongst many reasons why counterfeit drugs are still in circulation in Nigeria is the unmonitored drug distribution system. Drugs throughout their shelf life moves from one owner to another, from the importer/manufacturer to Distributor, wholesaler to government/private healthcare sectors and then to the patients. The current drug distribution system in Nigeria is a manually, unmonitored system, where the regulatory agency body National Agency for Food and Drug Administration control (NAFDAC) does not have detailed record on the movement of drugs from either the importer or manufacturer to the patient in the system. In this study blockchain technology framework that can handle the drug distribution chain was discussed, since blockchain technology offers immutability, transparency and tamper proof, it functionalities are what intrigued the study as it can help monitor the movement of drug in the distribution chain. The proposed system is a prototype demonstrating the hashing mechanism with a deployed smart contract and how it can help in showing the authenticity of a drug. The blockchain framework is a private blockchain, where participants on the network are permitted to have access to the network by the regulatory agency. The system was evaluated based on it’s effectiveness from users reports using the security, user friendly, response time, flexibility, data integrity checks, robust, hashing mechanism functional as the benchmark. The actual test result equates the expected test result, showing that the system is efficient.

KEYWORDS

Blockchain Technology; Blockchain Technology Framework; Counterfeit drugs; Counterfeit drug circulation; Drug distribution chain; Traceability, Transparency, Security.

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