Advanced Technology Systems Research Articles

VOICE/TEXTUAL BOT MOBILE APP

Abstract This paper describes the design and deployment of a Voice/Textual Bot Mobile App that was aimed at revamping the way people order food using advanced speech recognition, NLP, and real-time cart management. This application allows for users to browse categorized menus and place orders in addition to being able to command and manage shopping carts through voice or text inputs. This app features secure authentication, user-friendly navigation, and real-time cart updates for users of all kinds, even the physically or technologically challenged. It bridges the gap between advanced technology and convenient everyday food delivery systems by focusing on efficiency and user satisfaction. Keywords : Voice/Textual Bot, Android Application, Speech Recognition, Natural Language Processing, Real-Time Cart Management, Food Delivery System.

The mediating effects of perceived usefulness and perceived ease of use on nurses’ intentions to adopt advanced technology

This study explored the role of technology systems in influencing nurses’ intentions to adopt medical applications that enhance their performance and how technology contributes to improvements in hospital systems. The study examines the intention to use technology through the mediating effects of perceived usefulness and perceived ease of use, with technology sophistication. A random sampling method was employed to gather 687 responses from nurses. The statistical analysis was conducted using AMOS version 25.0 and SPSS. The findings indicate a significant association between technology sophistication (TS), perceived usefulness (PU), perceived ease of use (PEU), and intention to use (IU). Additionally, PU and PEU positively mediate the relationship between TS and IU. This research will benefit policymakers aiming to enhance nurses’ performance by adopting modern technology. Authorities should consider introducing advanced technology systems to meet the goals of hospital administration and support nurses effectively.

Adapting Management Control Systems to Organizational Contingency Factors: A Study of Moroccan Industrial Companies

This study investigates how organizational contingency factors, namely company size, environmental uncertainty, technological capacity, and organizational structure, affect the design and effectiveness of management control systems (MCS) in Moroccan industrial companies. Drawing on contingency theory, which emphasizes the alignment of organizational systems with contextual factors, this research applies quantitative methods to a sample of 190 industrial firms in Morocco, achieving a 76% response rate to the distributed surveys. The data are analyzed using correlation and linear regression techniques to explore these relationships. The findings reveal that larger firms, those operating in dynamic and uncertain environments, and those with advanced technological systems tend to implement more sophisticated, integrated, and participative MCS. Furthermore, flexible and decentralized organizational structures significantly enhance the adoption of adaptive control systems. These results underscore the importance of tailoring MCS to organizational characteristics and environmental conditions, particularly in emerging market contexts. This study’s novel contribution lies in its application of contingency theory to a non-Western industrial context, addressing a gap in the literature by demonstrating how specific regional factors influence MCS practices. This research offers practical insights for Moroccan industrial firms seeking to improve their operational efficiency, adaptability, and strategic decision making in volatile markets.

Analisis Prosedur Pelaksanaan Pengadaan Langsung Barang dan Jasa di PT. PLN Nusantara Power Services

This research examines the procedures for direct procurement of goods and services at PT. PLN Nusantara Power Services. Using field research method with a qualitative approach, the research was conducted through a Regular Internship program at the Head Office of PLN Nusantara Power Services Sidoarjo. The research results show that the procurement business process involves several main divisions, particularly the Operation & Maintenance division as the user and the Supply Chain Management division as the executor. There are four main methods in procurement implementation, namely; Direct Procurement, Limited Tender, Open Tender, and Direct Appointment. Direct Procurement becomes the most efficient method for small-value and low-risk procurement. The research recommends implementing advanced technological systems to optimize the procurement process and expanding vendor networks to increase the effectiveness of the company's procurement of goods and services.

Bridging The Gap Between Maritime Education and Industry Needs: Enhancing Human Resource Development

This research explores the critical need for maritime vocational education to align more closely with the evolving demands of the maritime industry, particularly in the areas of technological integration, environmental compliance, and industry collaboration. By analyzing the qualitative perspectives of maritime professionals, educators, graduates, and senior government officers, the study identifies key gaps in the current educational framework. The findings highlight the moderate effectiveness of existing programs, with strengths in regulatory knowledge and industry-academia partnerships, but weaknesses in preparing students for advanced technological systems and practical environmental challenges. The study emphasizes the need for curriculum modernization, increased hands-on training, and deeper, long-term industry partnerships to equip future maritime professionals with the skills necessary to navigate a rapidly changing sector. Ultimately, this research provides actionable insights for improving the responsiveness and agility of maritime vocational schools, ensuring that graduates are better prepared for the technological, regulatory, and environmental challenges facing the maritime industry.

Assessing the Impact of Enterprise Architecture on Digital Transformation Success: A Global Perspective

This research paper aims to analyze the significant contributions of enterprise architecture (EA) in leveraging digital transformation (DT) success at an international level. The paper adopts a meta-analytical approach, examining the patterns of EA’s strategic alignment and operational impact. EA plays a crucial role in managing digital ecosystem complexity, which is a key factor in successful DT. The methodology also focuses on the systematic review and meta-analysis of the relationships between EA and other advanced technological systems such as AI, IoT, and Blockchain to reveal how these technologies improve EA’s flexibility and strategic approaches. The paper emphasizes the importance of organizational culture, technological incorporation, and regional economic factors as critical determinants of EA practices in DT activities. It underscores the necessity for customized EA approaches to DT success within different cultural and economic contexts and their impact on sustainable management. This practical insight is a crucial contribution of the paper, providing a strategic roadmap for organizations aiming to optimize their digital transformation strategies through enhanced EA practices.

Deep learning-based proactive fault detection method for enhanced quadrotor safety

The early detection of faults in advanced technological systems is imperative for ensuring operational reliability and safety. While there is a growing interest in using artificial intelligence for fault detection, current methodologies often exhibit limitations in utilizing comprehensive system information and sensor data. Hidden faults within collected data further highlight the need for advanced analysis techniques. This study introduces a novel deep learning-based framework designed to predict faults and extract insights from complex system datasets. The model, consisting of LSTM-autoencoder and BiLSTM classification components, effectively reduces feature dimensions, thereby enhancing fault detection accuracy. The autoencoder’s latent layer identifies prominent features across various dimensions, while BiLSTM classification conducts bidirectional analysis using these features from both healthy and faulty states, facilitating early fault detection. Experimental results demonstrate the model’s efficacy, achieving an accuracy of 79.48% in predicting incipient faults 30 seconds before a serious malfunction occurs. This underscores the significant potential of the proposed framework in enhancing operational safety and reliability in complex systems. Moreover, the study emphasizes the importance of leveraging comprehensive data and advanced analysis techniques for early fault detection.

Harnessing the Power of Large Language Models for Automated Code Generation and Verification

The cost landscape in advanced technology systems is shifting dramatically. Traditionally, hardware costs took the spotlight, but now, programming and debugging complexities are gaining prominence. This paper explores this shift and its implications, focusing on reducing the cost of programming complex robot behaviors, using the latest innovations from the Generative AI field, such as large language models (LLMs). We leverage finite state machines (FSMs) and LLMs to streamline robot programming while ensuring functionality. The paper addresses LLM challenges related to content quality, emphasizing a two-fold approach using predefined software blocks and a Supervisory LLM.

Effect of Emergency Preparedness on Security in Kenyan Universities: A Case Study of Garissa University

Security emergencies and threats have lately been on the increase, with public universities in Kenya reporting many incidents of insecurity. Despite investigation efforts by university management, the high prevalence of insecurity has continued, pointing to the need to determine the relationship between security emergency preparedness and security management in public universities in Kenya. This paper explores the existing types of emergency situations, the existing types of emergency response approaches, and the level of institutional emergency preparedness and their influence on security at Garissa University. Utilizing the emergency Management Theory, the paper points out that the common type of emergency situation in the study institution is terror-related attacks. Training is the common emergency situation response strategy that the university is utilizing in readiness to face emergency situations, and strict checking at the gate is the most common plan that the university has used to deal with emergency situations within its compound and emergency planning in the study institution has enhanced security through control of movement. The study recommends that the university invest in modern and advanced information technology infrastructure and systems to avert incidences of insecurity.

Architecture of Nature‐Based Smart City Introducing BaaS by Utilizing UAF

AbstractSmart cities collaborate with various technological systems, including Internet of Things (IoT), artificial intelligence (AI), and drones, to fulfil the expectations of stakeholders and the needs of individuals and society. The use of such advanced technological systems may impose a burden on the natural environment, posing a risk to the sustainability of nature. We have already proposed the concept of biophilia as a service (BaaS) that is a service contributing to human well‐being and the sustainability of nature by emphasizing the relationship between humans and nature, promoting actions that safeguard nature, and collaborating with various organizations. In this paper, a smart, sustainable, and resilient city in harmony with nature is referred to as a nature‐based smart city (NBSC) and BaaS is introduced to NBSC. We define the architecture of NBSC introducing BaaS using the Unified Architecture Framework (UAF) and extract drivers, opportunities, and challenges of the NBSC. Requirements of BaaS for NBSC are derived from the goals and the capabilities. Also, the iterating operational processes of BaaS in the context of NBSC are described and defined. Furthermore, we discuss some findings from description of the architecture of NBSC introducing BaaS to promote the nature safeguard activity, and necessity to make a balance between human well‐being and sustainable natural environment.

The Impact of Infrastructure: Considerations of Generative AI in the Classroom

How are we to grapple with the increasing intrusion of technology in the classroom? What considerations need to be addressed before we begin bringing advanced technological systems like ChatGPT into our classroom spaces? A close attention to the infrastructural elements at play within the development and usage of AI gives us a better understanding of what is at stake when we bring AI into the classroom. The social and environmental impacts of AI, in particular, are often overlooked in new technological tools, especially ones that are supposed to frictionlessly improve our lives. Ultimately instructors need to balance the potential benefits and drawbacks of using forms of generative AI in the classroom and have a clear view of the impact of their decisions. For Political Science instructors, the impacts of AI may provide new teaching opportunities as well.

Improving care pathways through BPM and telemedicine: an Italian study

PurposeThe future increase of chronic diseases in the world requires new challenges in the health domain to improve patients' care from the point of view of the organizational processes, clinical pathways and technological solutions of digital health. For this reason, the present paper aims to focus on the study and application of well-known clinical practices and efficient organizational approaches through an innovative model (TALIsMAn) to support new care process redesign and digitalization for chronic patients.Design/methodology/approachIn addition to specific clinical models employed to manage chronic conditions such as the Population Health Management and Chronic Care Model, we introduce a Business Process Management methodology implementation supported by a set of e-health technologies, in order to manage Care Pathways (CPs) digitalization and procedures improvement.FindingsThis study shows that telemedicine services with advanced devices and technologies are not enough to provide significant changes in the healthcare sector if other key aspects such as health processes, organizational systems, interactions between actors and responsibilities are not considered and improved. Therefore, new clinical models and organizational approaches are necessary together with a deep technological change, otherwise, theoretical benefits given by telemedicine services, which often employ advanced Information and Communication Technology (ICT) systems and devices, may not be translated into effective enhancements. They are obtained not only through the implementation of single telemedicine services, but integrating them in a wider digital ecosystem, where clinicians are supported in different clinical steps they have to perform.Originality/valueThe present work defines a novel methodological framework based on organizational, clinical and technological innovation, in order to redesign the territorial care for people with chronic diseases. This innovative ecosystem applied in the Italian research project TALIsMAn is based on the concept of a continuum of care and digitalization of CPs supported by Business Process Management System and telemedicine services. The main goal is to organize the different socio-medical activities in a unique and integrated IT system that should be sustainable, scalable and replicable.

The Emergency Medical Team Operating System — a vision for field hospital data management in following the concepts of predictive, preventive, and personalized medicine

In times where sudden-onset disasters (SODs) present challenges to global health systems, the integration of predictive, preventive, and personalized medicine (PPPM / 3PM) into emergency medical responses has manifested as a critical necessity. We introduce a modern electronic patient record system designed specifically for emergency medical teams (EMTs), which will serve as a novel approach in how digital healthcare management can be optimized in crisis situations. This research is based on the principle that advanced information technology (IT) systems are key to transforming humanitarian aid by offering predictive insights, preventive strategies, and personalized care in disaster scenarios. We aim to address the critical gaps in current emergency medical response strategies, particularly in the context of SODs. Building upon a collaborative effort with European emergency medical teams, we have developed a comprehensive and scalable electronic patient record system. It not only enhances patient management during emergencies but also enables predictive analytics to anticipate patient needs, preventive guidelines to reduce the impact of potential health threats, and personalized treatment plans for the individual needs of patients. Furthermore, our study examines the possibilities of adopting PPPM-oriented IT solutions in disaster relief. By integrating predictive models for patient triage, preventive measures to mitigate health risks, and personalized care protocols, potential improvements to patient health or work efficiency could be established. This system was evaluated with clinical experts and shall be used to establish digital solutions and new forms of assistance for humanitarian aid in the future. In conclusion, to really achieve PPPM-related efforts more investment will need to be put into research and development of electronic patient records as the foundation as well as into the clinical processes along all pathways of stakeholders in disaster medicine.

The influence of state-owned property management, the implementation of the State-Owned Property Management Accounting Information System and human resource competency on the quality of government financial reports

This study explores the complex connection between the management of State Property, the utilization of the State Property Accounting Management Information System, the proficiency of personnel, and their combined influence on the accuracy of financial statements in government organizations. This research seeks to investigate the impact of effective State Property management, facilitated by advanced technological systems such as State Property Management and Accounting Information System, and bolstered by skilled human resources, on the dependability and precision of financial reporting in the public sector. The study will analyze scholarly literature and empirical evidence to achieve this objective. By integrating descriptive and verification methodologies, this research study utilizes a quantitative approach to investigate the influence of human resource competence, the administration of State Property, and the implementation of the State Property Accounting Management Information System on the quality of financial statements within government organizations. The variables are operationalized and measured using indicators that pertain to the quality of government financial accounts, management of State Property, implementation of State Property Management and Accounting Information System, and human resource competency. Data is gathered by distributing questionnaires to the personnel of the Regional Office of the National Land Agency of West Java Province. The total population consists of 54 individuals, and a saturated sampling strategy is used. To summarize, this study highlights the significance of efficient management of State Property and the adoption of State Property Management and Accounting Information System in improving the accuracy and reliability of government financial accounts. Nevertheless, a more thorough examination is necessary to ascertain the exact influence of human resource expertise. These findings enhance the existing information on financial management in the public sector and identify areas where government financial reporting standards might be improved.

SISTEMAS EMBARCADOS E AUTOMAÇÃO RESIDENCIAL

The use of technology is increasingly on the rise in modern times. It is possible to find cars that make use of the most advanced technological systems, just as it is possible to find small objects such as a smartphone that are also equipped with various technological features. In this context, the discussion arises about the importance of so-called embedded systems, which constitute programs encapsulated in machines or even other programs and whose interaction with their users occurs through the use of interfaces, with literal access not being possible. In addition to the applications already mentioned, another application that has gained prominence through the use of embedded systems is residential management through automated systems. Embedded systems focused on home automation make extensive use of the internet of things and can be operated in person or remotely, focusing on aspects such as safety, comfort, time savings, among others. The objective of this case study is to discuss the application of embedded systems in home automation applications, as due to the expansion of the real estate market in Brazil, it becomes relevant to address aspects directly or indirectly related to it. The problem question to which we want to obtain an answer is: “What are the advantages of using embedded systems in the possibility of home automation?”. The study methodology applied was bibliographic in nature, seeking the main concepts in specialized literature, as well as discussions on the topic under study. The results demonstrated that there is a tendency for the real estate market to be increasingly adept at using automation and consequently there is also an increase in the use of devices connected to the world wide web through the internet of things and the functionality of systems embedded in devices. and various programs, enabling the enjoyment of certain and specific previously programmed functions. It is concluded that the advantages experienced when using embedded systems are the versatility of applications, efficiency due to the fact that they are endowed with specificity, innovation and reliability of these systems.

Use of Technology for Enhancement of Social Learning through Digital Reward Systems: A Case Study on TCS

In the rapidly evolving corporate landscape, technology has become a linchpin for the survival and growth of companies. Major industry players, including TCS, Apple, and Infosys, have embraced advanced technological systems to streamline their operations, with a particular focus on managing their most valuable asset—human resources. This case study underscores the pivotal role of technology, especially Digital Reward Systems (DRS), in enhancing employee satisfaction, fostering a sense of closeness to the organization, and ultimately contributing to the overall success of companies.

Multi-object real-time tracking for intelligent breeding of animal

Animal intelligent breeding utilizes advanced technology and intelligent systems to monitor, analyze, and optimize animal growth environments and management, which can enhance breeding efficiency and animal health levels. In this paper, we propose a new multi-object real-time tracking within deep framework for intelligent breeding of animal (MRT-IB), which consists of semantic feature extraction module, center point prediction module, and object and trajectory calibration module. MRT-IB reduces the difficulty of modeling animal trajectories by performing animal detection on consecutive frames, resulting in higher robustness in real farming scenarios compared to traditional multi-object tracking schemes that directly model animal motion trajectories.

A Systematic Review on Ethical Challenges of Emerging AI in Accounting Using the Ado Model

Introduction: Emerging technologies like AI in the accounting sector present ethical challenges, including concerns over transparency, bias, privacy, and accountability. This study is crucial as accountants play a vital role in providing reliable financial information for decision-making, maintaining stakeholder trust, and upholding the integrity of the profession. This study systematically synthesizes the existing literature on Artificial Intelligence, Ethics, and Accounting to identify various related constructs using the Antecedents, Decisions, and Outcomes (ADO) model. It also highlights research gaps and suggests directions for future research. Methods: The study employs a rigorous systematic literature review (SLR) process, adhering to the PRISMA framework, to select 20 full-text articles relevant to artificial intelligence, ethics, and accounting. The review, conducted for studies published between 2020 and 2024, includes journal, excluding books and conference proceedings, regarding the subject areas of accounting, business, economics and computer science. This review provides an organized overview of the antecedents, decision processes, and outcomes of artificial intelligence, ethics, and accounting. Results: The study delineates critical challenges in the integration of AI within the accounting sector, including technological advancement, ethical dilemmas, regulatory hurdles, and risk management concerns. To mitigate these issues, it advocates for the establishment of comprehensive ethical frameworks, the deployment of advanced technological systems, and the enhancement of education and awareness among professionals. The findings reveal that these interventions significantly elevate ethical standards, boost operational efficiency, enhance profitability, and ensure the effective and responsible deployment of AI technologies in accounting practices. Conclusion: The study highlights the need for policymakers to create flexible frameworks and systems to address specific ethical issues of AI in accounting, while also emphasizing the importance of competency and awareness among professionals. It advocates for a centralized governance body to coordinate global standards and foster collaboration, contributing to a comprehensive understanding of ethical AI integration and advancing responsible practices within the sector.

다문화사회의 상호문화성에 대한 전망

In the history of civilization, the world history of the past 200 years has left a mark in the history of the global expansion of Western civilization and the struggles of non-Western countries. And in the 21st century, Korea's multicultural phenomenon, which was formed at the crossroads of radical globalization economically, politically, and culturally, is also operating surrounded by the axis of Western civilization universalism. Accordingly, in the midst of globalization, ‘practice multiculturalism’ and ‘social integration’ have become important tasks in Korean society due to the influx of labor migrants and marriage migrants. However, in reality, there are social and historical weaknesses in Korea's compressed modernization that prevent the community from maturing as a multicultural society. This is not only because the Western sociality that enables representative politics of civil society, the basis of Western universalism, and the rule of law, that is, rational liberal democracy, has not fully matured in Korean society, but also because of the inherent vulnerability of globalized multiculturalism.
 The term ‘multicultural society’, which is used in various senses, has its origins in the immigration policy managed by the state, and has a large state-led political connotation as it has legal elements at the border management level. In Western history, it is an ideology that was created with the problem of post-colonialism following the immigration crisis. However, the mutual interference between the global economy and cultural activities at an ever-increasing pace is forming a super-complex social system. Among these direct and indirect influences, the movement of population, movement of labor, and flow of goods and capital have brought about rapid cultural transformation and conflict around the world under the advanced information technology system. Therefore, Western universalism requires the fusion of new civilizations from the perspective of the universal history of human civilization.
 This study examines the special characteristics of Korea's multicultural society within the mechanical arrangement of globalization and seeks the possibility of building the integration of a multicultural society based on the ideology of 'interculturality'. We will also highlight that the practice of cultural diversity implies a deep awareness of the diversity of life and the prospect for a universal civilization of humanity.

A hybrid model for lung cancer prediction using patch processing and deeplearning on CT images

AbstractCancer is a common disease with an increasing mortality rate in recent years. Lung cancer is the most common cancer in men and women alike. It is caused by uncontrolled cell development in the lungs. These cells are divided into two types: benign and malignant. Benign tumours are usually harmless, do not spread to other cells, and have a smooth and regular shape, whereas malignant tumours can be dangerous and spread to other body cells to form a new cancerous nodule with an uneven shape. If lung cancer is detected early, it can be treated. Lung cancer symptoms typically appear in the human body when it is in its final stage, but advanced technology and computer-aided systems can detect it at an early stage. Currently, numerous conventional and machine learning techniques are used for such automated detection systems to detect lung cancer in its early stages, but such automated detection systems do not provide accurate detection and the processing of lung cancer detection takes a long time. As a result, a novel method for detecting lung cancer that employs deep learning techniques for accurate detection while requiring less computation time is proposed. CT images are used in this study because they have less noise disturbance than MRI and X-ray images. Median filtering and patch processing are used to improve image quality on such CT scans. These pre-processed images are then subjected to a clustering segmentation process, which segments the image and feeds it to a CNN classifier. For feature extraction and classification, CNN architecture is used. In the future extraction section, various low-level and high-level features are extracted. The classification layer is in charge of determining whether the provided image contains a malignant, benign, or normal tumour. Finally, statistical parameters like MSE, PSNR, Accuracy, Sensitivity, Specificity, and others were computed and combined with the existing system in this work.