Automated information retrieval and services of graduate school using chatbot system

Automated information retrieval and servicing systems are a priority demand system in today's businesses to ensure instantaneous customer satisfaction. The chatbot system is an incredible technological application that enables communication channels to automatically respond to end-users in real-time and 24 hours a day. By providing effective services for retrieving information and electronic documents continuously and automating the information service system, the coronavirus disease (COVID-19) is challenging to promote graduate school programs, update news, and retrieve student information in this era. This article discusses automated information retrieval and services based on the architecture, components, technology, and experiment of chatbots. The chatbot system's primary functions are to deliver the course and contact information, answer frequency questions, and provide a link menu to apply for our online course platform. We manage the entire functional process of gathering course information and submitting an application for a course online. The final results compare end users' perceptions of chatbot system usage to onsite services to ensure that the chatbot system can be integrated into the university's information system, supporting university-related questions and answers. We may expand our chatbot system's connection to the university's server to provide information services to students in various informative areas for future research

A Practical Model from Multidimensional Layering: Personal Finance Information Framework Using Mobile Software Interface Operations

End user involvement is crucial in improving software development processes. Hence, nowadays user interface (UI) and user experience (UX) are particularly concerned with end user interactions in many software designs as most methodologies have inconsistencies between design and implementation. Besides, it is relatively difficult to make changes in complex software and personal finance application is one of the more complex software to design, develop, and adapt. This paper proposes the development of a mobile personal finance application using informative multidimensional layering. We have separated functional data cutting across the relationships of three categories and datasets showing operational semantics of dimensions, and combined layers of three-dimensional information including aspect elements through components. This study is concerned with the corresponsive composition of end user features using visual interfaces. It is illustrated in a Three-layer User Interface Composition Model to transfer and compose layers, functional data, aspect elements, and components to Graphical User Interfaces (GUIs). Therefore, an integrated view of the software system would make the design and implementation consistent to support our framework in a more straightforward manner. There have been a few studies which presented practical models of mobile informative multidimensional layering. This research applied aspect orientation and informative multidimensional layering to present a better features model for mobile personal finance application. We deliver a practical framework in the application in all four phases of analysis, design, implementation, and evaluation. In addressing the gap, this research proposes a clearer operation of three-dimensional models, functional data, and aspect elements that cut across through informative multidimensional layering

Dynamic Multi-Criteria Decision Making of Graduate Admission Recommender System: AHP and Fuzzy AHP Approaches

The optimal management of personal resources impacts everyone’s quality of life. An investment in graduate education is a sustainable opportunity for improved outcomes in human life, including cognition, behavior, life opportunities, salary, and career. Advanced technology dramatically reduces the risk of personal resources in graduate program admission recommendations that depend on multiple individual needs and preferences. In the digital age, a dynamic recommender system enhances the suitably effective solution for students’ university selections. This study focused on designing, developing, and testing a recommender system for graduate admission using a dynamic multi-criteria AHP and fuzzy AHP approach. The explicit multi-criteria recommender system was a platform as a service (PaaS) web application created to aid in graduate admissions management and decision-making. The design proposed that the bit representation store a dynamic explicit multi-criteria data structure. The recommendations adopting dynamic multi-criteria were validated by comparing them to the programs to which the students were actually admitted and enrolled. They individually ranked the evaluation outcomes of dynamic explicit multi-criteria and alternative preferences to provide graduate admission recommendations. Eighty graduate students in information technology evaluated the recommender system. Using top-1, top-2, and F1-score accuracy, the effective system accuracy performance on the dynamic multi-criteria recommender system was evaluated using AHP and fuzzy AHP approaches. The fuzzy AHP demonstrated marginally greater practical accuracy than the AHP method

Adoption of Environmental Information Chatbot Services Based on the Internet of Educational Things in Smart Schools: Structural Equation Modeling Approach

The Internet of Educational Things (IoET) equips chatbots with real-time environmental information monitoring to prevent student and instructor absences and safeguard their health. Individual behavioral intention toward a chatbot service is essential for better understanding the user’s experience and acceptance of monitoring environmental elements such as PM2.5, temperature, humidity, and carbon monoxide. This study aims to apply an integration of an extended framework for smart schools developing an environmental information chatbot service (ENICS) and various users’ continued behavioral intentions toward the chatbot system based on the unified theory of acceptance and use of technology model to support health and safety in universities. The proposed framework design can incorporate Internet of Things architecture to develop and utilize the chatbot services. The key results of the partial least square test largely support the validity of the proposed model and the significant effects of IoET, performance expectation, effort expectation, social influence, facilitating conditions, health and safety, behavioral intention, and use behavior on personal environmental information chatbot utilization. This study’s findings deal with a better design for environmental system development and understanding the factors influencing an individual’s intention to continue using a chatbot service for IoET applications with low-cost information facilities in safe environmental sustainability

Adoption of Environmental Information Chatbot Services Based on the Internet of Educational Things in Smart Schools: Structural Equation Modeling Approach

The Internet of Educational Things (IoET) equips chatbots with real-time environmental information monitoring to prevent student and instructor absences and safeguard their health. Individual behavioral intention toward a chatbot service is essential for better understanding the user’s experience and acceptance of monitoring environmental elements such as PM2.5, temperature, humidity, and carbon monoxide. This study aims to apply an integration of an extended framework for smart schools developing an environmental information chatbot service (ENICS) and various users’ continued behavioral intentions toward the chatbot system based on the unified theory of acceptance and use of technology model to support health and safety in universities. The proposed framework design can incorporate Internet of Things architecture to develop and utilize the chatbot services. The key results of the partial least square test largely support the validity of the proposed model and the significant effects of IoET, performance expectation, effort expectation, social influence, facilitating conditions, health and safety, behavioral intention, and use behavior on personal environmental information chatbot utilization. This study’s findings deal with a better design for environmental system development and understanding the factors influencing an individual’s intention to continue using a chatbot service for IoET applications with low-cost information facilities in safe environmental sustainability

User Acceptance Factors Related to Biometric Recognition Technologies of Examination Attendance in Higher Education: TAM Model

Identity recognition is influenced at all educational levels by biometric technology. The invention of facial recognition technology has added new efficiencies to the traditional method of tracking student examination attendance. This study aims to determine whether biometric recognition technologies could be utilized to enhance undergraduate examination attendance systems. The study examined the perceptions of first-year college students regarding the system’s use of face recognition technologies. Based on the proposed framework, experimental results were obtained by developing and deploying unimodal and multimodal face recognition methods. Using a quasi-practical design with sample groups, undergraduate students’ perceptions of traditional and biometric examination attendance were compared. Adopting the Theory for Reasoned Action and the Technology Acceptance Model, a questionnaire was distributed and analyzed to determine perception factors. The findings reveal that perceived ease of use, and trust and security significantly impact perceived usefulness. It was discovered that perceived usefulness significantly affects behavioral intention to use a system. According to the research findings, multimodal biometric recognition receives significantly more positive ratings than unimodal biometric recognition. This study proposes that universities utilize biometric technology, particularly facial recognition, to assess users’ acceptance of the system

User Acceptance Factors Related to Biometric Recognition Technologies of Examination Attendance in Higher Education: TAM Model

Identity recognition is influenced at all educational levels by biometric technology. The invention of facial recognition technology has added new efficiencies to the traditional method of tracking student examination attendance. This study aims to determine whether biometric recognition technologies could be utilized to enhance undergraduate examination attendance systems. The study examined the perceptions of first-year college students regarding the system’s use of face recognition technologies. Based on the proposed framework, experimental results were obtained by developing and deploying unimodal and multimodal face recognition methods. Using a quasi-practical design with sample groups, undergraduate students’ perceptions of traditional and biometric examination attendance were compared. Adopting the Theory for Reasoned Action and the Technology Acceptance Model, a questionnaire was distributed and analyzed to determine perception factors. The findings reveal that perceived ease of use, and trust and security significantly impact perceived usefulness. It was discovered that perceived usefulness significantly affects behavioral intention to use a system. According to the research findings, multimodal biometric recognition receives significantly more positive ratings than unimodal biometric recognition. This study proposes that universities utilize biometric technology, particularly facial recognition, to assess users’ acceptance of the system

IoT-Based Mushroom Cultivation System with Solar Renewable Energy Integration: Assessing the Sustainable Impact of the Yield and Quality

The conventional method of mushroom cultivation can be labor-intensive and produce limited yields. Due to the humidity and temperature in the summer season, mushroom production is significantly diminished. The growth of each mushroom species depends on the consistency of care, the skill of experienced farmers, and crucial cultivation parameters such as temperature, humidity, irrigation, and exposure to sunlight. This study aims to implement an IoT-enabled cultivation system to control and monitor the environmental parameters of Indian mushroom cultivation within the proposed innovative framework, as compared to conventional methods. The IoT-based cultivation system consists of hardware components, circuit connections, software, and algorithms. This study confirms that consistent control of environmental parameters, such as temperature and relative humidity, by a dynamic climate promotes mushroom growth that is superior to conventional cultivation. Our findings reveal a substantial increase in the yield and quality of mushrooms, demonstrating the tangible advantages of applying an innovative approach. Traditional cultivation yielded an average of 4.118 kg, whereas IoT-based cultivation systems produced an average of 5.306 kg. The t-test statistic comparing yields has highlighted the significance of the observed differences with a p-value of 0.0000. The research contributions are to design and demonstrate the IoT-enabled system innovation with solar renewable energy, illustrating the effect of mushroom production and quality on the economic market analysis of mushroom cultivation in the direction of environmentally sustainable and green agricultural practices. This study’s comprehensive perspective can provide farmers, agricultural professionals, and policymakers with valuable insights regarding the future of mushroom cultivation, particularly the reduction of carbon emissions and energy consumption