Applying Artificial Intelligence Technologies Research Articles

Application of AI in Halal Marketing: Navigating the Ethical Crossroads

This article examines the intricate process of applying Artificial Intelligence (AI) in the Halal marketing landscape, situated at a critical ethical crossroads. It explores the integration of AI technologies within Halal marketing strategies, emphasizing the importance of aligning with ethical, legal, and Islamic principles. Highlighting AI's potential to transform consumer engagement and trust, the paper advocates for a proactive approach in developing AI applications that respect Islamic values, consumer privacy, and fairness. It calls for collaborative efforts in crafting regulatory frameworks and ethical AI algorithms that are congruent with Halal standards, thus ensuring technology acts as a catalyst for ethical growth and integrity within the industry. The discussion underscores the dual aspects of opportunities and challenges presented by AI, urging a balanced embrace of technological advancements while safeguarding Islamic ethical and legal norms to foster the ethical expansion of the Halal industry globally.

What's in the box? A toolbox for safe deployment of artificial intelligence in veterinary medicine.

This report describes a comprehensive framework for applying artificial intelligence (AI) in veterinary medicine. Our framework draws on existing research on AI implementation in human medicine and addresses the challenges of limited technology expertise and the need for scalability. The critical components of this framework include assembling a diverse team of experts in AI, promoting a foundational understanding of AI among veterinary professionals, identifying relevant use cases and objectives, ensuring data quality and availability, creating an effective implementation plan, providing team training, fostering collaboration, considering ethical and legal obligations, integrating AI into existing workflows, monitoring and evaluating performance, managing change effectively, and staying up-to-date with technological advancements. Incorporating AI into veterinary medicine requires addressing unique ethical and legal considerations, including data privacy, owner consent, and the impact of AI outputs on decision-making. Effective change management principles aid in avoiding disruptions and building trust in AI technology. Furthermore, continuous evaluation of AI's relevance in veterinary practice ensures that the benefits of AI translate into meaningful improvements in patient care.

The investigation of artificial intelligence-based applications in music education

The field of music education has garnered significant attention due to the burgeoning advancements in artificial intelligence technology. Currently, there are many works on applying Artificial Intelligence (AI) technology to the field of music education, and this review aims to comprehensively summarize the application of AI methods in multiple subfields of music education. In this paper, according to the focus of AI technology, the areas of music education to which it has been applied are divided into four modules, namely personalized learning, automatic assessment, composition assistance and interactive teaching. Firstly, representative AI methods applied to each of these four subfields are introduced, including but not limited to: the principle of the AI method, the improvement brought by the application. The text then describes the current status of the application of these methods in their domains, discusses the limitations of the application, and makes brief conjectures on how to break through these limitations. The research in this review paper is important for the development of AI technology applied to the field of music education. At the same time, this review also provides directions and suggestions for future research to promote the further development of AI in the field of music education.

The impact of AI technology adoption on operational decision-making in competitive heterogeneous ports☆

Artificial Intelligence (AI) technology is changing the industrial paradigm and has been widely adopted in port operations. Although AI technology can improve the efficiency of port operations and service quality, ports need to bear some costs. Discussing the role of applying AI technology to ports in complex competitive environments has become an important issue in the operations of ports and shipping. In this study, we construct a game-theoretic model of competitive heterogeneous ports. The research conclusions indicate that the adoption of AI technology by heterogeneous ports can enhance port profits. Unfortunately, simultaneous adoption exacerbates homogenized competition, posing a threat to profit realization. Furthermore, while the hub port can leverage AI-empowered capabilities to strengthen own competitiveness, it can undermine the performance of competitors and society at large. Surprisingly, the adoption of AI technology by feeder port is more advantageous in achieving social welfare and achieving multiple benefits such as carbon reduction.

Expert consensus on fundus photograph-based cardiovascular risk assessment using artificial intelligence technology

Cardiovascular risk assessment is a basic tenet of the prevention of cardiovascular disease. Conventional risk assessment models require measurements of blood pressure, blood lipids, and other health-related information prior to assessment of risk via regression models. Compared with traditional approaches, fundus photograph-based cardiovascular risk assessment using artificial intelligence (AI) technology is novel, and has the advantages of immediacy, non-invasiveness, easy performance, and low cost. The Health Risk Assessment and Control Committee of the Chinese Preventive Medicine Association, in collaboration with the Chinese Society of Cardiology and the Society of Health Examination, invited multi-disciplinary experts to form a panel to develop the present consensus, which includes relevant theories, progress in research, and requirements for AI model development, as well as applicable scenarios, applicable subjects, assessment processes, and other issues associated with applying AI technology to assess cardiovascular risk based on fundus photographs. A consensus was reached after multiple careful discussions on the relevant research, and the needs of the health management industry in China and abroad, in order to guide the development and promotion of this new technology.

An Evolutionary Study of the Impact of Artificial Intelligence Technology on Foreign Language Education

This study investigates the evolutionary impact of applying artificial intelligence (AI) technology to foreign language education. By employing complex systems thinking, the relationship between foreign language education and AI technology is explored, and dynamic models are employed to analyze the evolutionary patterns of AI technology in foreign language education. Through model analysis and numerical simulations, the interactive effects between foreign language education and AI technology in different modes are revealed. The findings demonstrate that, under different coupling modes, foreign language education and AI technology can achieve self-organizing evolution. When the interaction coefficient between foreign language education and AI technology is appropriately set, AI technology exhibits emergent properties for foreign language education. Lastly, suggestions are presented to promote the sound development of foreign language education and AI technology.

Application of AI Technology in Mergers & Acquisitions and Its Regulation

Applying Artificial Intelligence (AI) brings more possibilities to the Mergers and Acquisitions (M&A) process. However, with the high development of AI, its safety and ethical consequences are gradually emerging. This paper adopts the case analysis method and uses AI's specific application in the due diligence process as an example to analyze the legal risks of its program testing environment, data extraction security, and error tolerance rate. Also, this paper will use contrastive analysis and documentary analysis to explore the legal gaps and prospects of AI in M&A by taking the EU's AI Ethical guidelines, the AI Act, and Guidance for Regulation of Artificial Intelligence Applications from the US as examples, analyzing the regulatory directions and regulations for M&A.

A Study on OLED Cell Simulation and Detection Phases Based on the A2G Algorithm for Artificial Intelligence Application

In this study, we demonstrate the viability of applying artificial intelligence (AI) techniques to conduct inspections at the OLED cell level using simulated data. The implementation of AI technologies necessitates training data, which we addressed by generating an OLED dataset via our proprietary A2G algorithm, integrating the finite element method among concerns over data security. Our A2G algorithm is designed to produce time-dependent datasets and establish threshold conditions for the expansion of dark spots based on OLED parameters and predicted lifespan. We explored the potential integration of AI in the inspection phase, performing cell-based evaluations using three distinct convolutional neural network models. The test results yielded a promising 95% recognition rate when classifying OLED data into pass and fail categories, demonstrating the practical effectiveness of this approach. Through this research, we not only confirmed the feasibility of using simulated OLED data in place of actual data but also highlighted the potential for the automation of manual inspection processes. Furthermore, by introducing OLED defect detection models at the cell level, as opposed to the traditional panel level during inspections, we anticipate higher classification rates and improved yield. This forward-thinking approach underscores significant advancement in OLED inspection processes, indicating a potential shift in industry standards.

IMPROVING CONSTRUCTION PROJECTS AND REDUCING RISK BY USING ARTIFICIAL INTELLIGENCE

Architectural, engineering and construction (AEC) industry has large amounts of data, the analysis of which can predict risks such as project delays, project budget overruns, low resource use efficiency, environmental damage, reduced safety, and the like. Research has shown that 98% of construction projects are realized with the contracted budget and deadline exceeded. This paper aims to show the significant potential and possibilities of applying artificial intelligence (AI) in the AEC industry, pointing out the benefits and obstacles faced by the AEC industry during the implementation of AI. The benefits of applying AI in the AEC industry relate to increasing efficiency, reducing costs, increasing productivity, increasing safety, better planning and providing timely and accurate information. The key obstacles that hinder the implementation of AI in practice are high implementation costs, incomplete data, job loss due to automation, mistrust of AI technology, cyber vulnerability, and lack of understanding field of AI.

The ethics of sustainable AI: Why animals (should) matter for a sustainable use of AI

AbstractTechnologies equipped with artificial intelligence (AI) influence our everyday lives in a variety of ways. Due to their contribution to greenhouse gas emissions, their high use of energy, but also their impact on fairness issues, these technologies are increasingly discussed in the “sustainable AI” discourse. However, current “sustainable AI” approaches remain anthropocentric. In this article, we argue from the perspective of applied ethics that such anthropocentric outlook falls short. We present a sentientist approach, arguing that the normative foundation of sustainability and sustainable development—that is, theories of intra‐ and intergenerational justice—should include sentient animals. Consequently, theories of sustainable AI must also be non‐anthropocentric. Moreover, we investigate consequences of our approach for applying AI technologies in a sustainable way.

System Evaluation of Artificial Intelligence and Virtual Reality Technology in the Interactive Design of Interior Decoration

Applying artificial intelligence (AI) and virtual reality (VR) technology to interior decoration design can effectively shorten the time of communication between customers and the designers, the design time, and the distance between designers, customers, and the space to be designed, which meet contemporary needs. This paper aimed to study how to analyze and design an interactive interior decoration design system based on AI and VR technology. This paper also used the fuzzy comprehensive evaluation (FCE) method to comprehensively verify and evaluate the designed system. According to the system verification experiment in this paper, the sensitivities of the left, right, front, and rear operating handles for 50 times were 99.38%, 99.36%, 99.49%, and 99.21%, respectively. In addition, when the number of users simultaneously using the system was 60, the system’s stability, security, response time, and stuck time were 98.72%, 98.40%, 0.834 s, and 0.322 s, respectively. Based on a series of evaluative tests, the interactive design system for interior decoration presented in this paper is feasible and worthy of further promotion and application. The system designed in this article has reference value for the academic community and boasts certain innovative aspects.

Artificial Intelligence-Assisted Network Slicing: Network Assurance and Service Provisioning in 6G

6G networks are expected to provide instant global connectivity and enable the transition from “connected things” to “connected intelligence,” where promising network slicing can play an important role in network assurance and service provisioning for various demanding vertical application scenarios. On the basis of diversified massive data, artificial intelligence (AI)-assisted techniques are widely considered more suitable than traditional models and algorithms to deal with challenges faced by complex and dynamic slicing problems in 6G. In view of this, we provide a tutorial on AI-assisted 6G network slicing for network assurance and service provisioning, aiming to show the prospect of 6G slicing and the advantages of applying AI technology. Specifically, we propose six typical characteristics of 6G network slicing, analyze the feasibility of AI from different network domains and technical aspects, propose a case study on AI-assisted bandwidth scaling, and, finally, put forward the main challenges and open issues for its future development.

Research on Impact of Artificial Intelligence Orientation on Enterprise Green Innovation

As the core technology to lead the digital future and promote the industrial revolution, artificial intelligence (AI) technology can empower the whole chain of manufacturing enterprises, accelerate the fundamental transformation of production mode and enterprise form, guide enterprises to integrate artificial intelligence with green innovative technology, and improve energy efficiency. Based on the background of green transformation faced by the manufacturing industry, we discuss the mechanism of artificial intelligence to realize green innovation of enterprises through dynamic capabilities. AI orientation refers to the tendency and strategy of enterprises in introducing and applying AI technology. Based on the strategic management theory and the resource-based view, a questionnaire survey for manufacturing enterprises was conducted. Using regression analysis method to conduct empirical research on 204 valid questionnaire data, to test the hypothesis. The result shows that AI has a significant positive effect on the green innovation of enterprises. Both strategic sensing capacity and timely decision-making capacity positively affect the green innovation of enterprises. Strategic sensing capacity and timely decision-making capacity play a partial mediating role between AI and green innovation. AI gives the light to enterprise development to clarify the direction of progress of the production technology. Enterprises need to establish AI-orientated strategies in many aspects to realize green innovation and improve environmental performance.

Smartening up Ports Digitalization with Artificial Intelligence (AI): A Study of Artificial Intelligence Business Drivers of Smart Port Digitalization

Artificial intelligence (AI) is digitalizing transportation at sea, on land, and in the air. It has the potential to cut human error and make operations faster. However, AI is one part of a broader process to digitize and improve port operations. AI digitalization and autonomous shipping are critical in the port world; AI allows human work to be shifted toward digital platforms that are currently not fully capable. Following this, the ports industry can be sketched as a natural fit for applying AI technology, known for its complicated processes and the high proportion of human work intervention. This paper aims to analyze and explore the artificial intelligence Business Drivers of Smart Port Digitalization. This study employs the exploratory Factor Analysis (EFA), Confirmatory factor analysis (CFA), and structural equation modeling (SEM) approaches using Advance Managed Outsourced Solutions (AMOS) based on a ports communities operation management view. Then propose new AI-Ports initiatives. The value-added core tasks of ports are examined to determine the possible utilization of AI technology and the AI adoption within the ports community.

The potential and pitfalls of artificial intelligence in clinical pharmacology.

Artificial intelligence (AI) involves using data and algorithms to perform activities normally achieved through human intelligence. AI and its key component machine learning contextualize data and enhance decision making to transform how we operate, discover, and develop drugs. Transforming clinical pharmacology (CP) as AI-augmented CP (AI/CP) requires an ecosystem including digitized data collection, standardized processes, complementary technologies, and an ethical framework. This commentary aims to highlight the future perspectives of AI/CP in drug development.

Incorporating Artificial Intelligence Technology in Smart Greenhouses: Current State of the Art

This article presents the current state-of-the-art research on applying artificial intelligence (AI) technology in smart greenhouses to optimize crop yields, water, and fertilizer use efficiency, to reduce pest and disease, and to enhance agricultural sustainability. The key technologies of interest were robotic systems for pesticide application, irrigation, harvesting, bio-inspired algorithms for the automation of greenhouse processes, energy management, machine path planning and operation of UAVs (unmanned aerial vehicles), resolution of scheduling problems, and image signal processing for pest and disease diagnosis. Additionally, the review investigated the cost benefits of various energy-management and AI-based energy-saving technologies, the integration of photovoltaics and dynamic pricing based on real-time and time-of-use metrics, and the cost benefits of LoRa, Wi-Fi, Bluetooth, ZigBee, mobile, and RFID (radiofrequency identification) technologies. The review established that commercially viable AI technologies for agriculture had increased exponentially. For example, AI-based irrigation and soil fertilizer application enabled farmers to realize higher returns on investment on fertilizer application and gross returns above the fertilizer cost, higher yields, and resource use efficiency. Similarly, AI image detection techniques led to the early diagnosis of powdery mildew. The precise operation of agricultural robots was supported by the integration of light imaging, detection, and ranging (LIDAR) optical and electro-optical cameras in place of the traditional GPS (geographic positioning systems) technologies, which are prone to errors. However, critical challenges remained unresolved, including cost, disparities between research and development (R&D) innovations and technology commercialization, energy use, the tradeoff between accuracy and computational speeds, and technology gaps between the Global North and South. In general, the value of this review is that it surveys the literature on the maturity level of various AI technologies in smart greenhouses and offers a state-of-the-art picture of how far the technologies have successfully been applied in agriculture and what can be done to optimize their usability.

Artificial intelligence (AI) for home support interventions in dementia: a scoping review protocol

IntroductionDementia has become one of the significant causes of disability and dependency among older people globally. The proportion of people with dementia who are cared for at home has soared....

Artificial intelligence applications for proactive environmental monitoring and asset management

Two research studies have been implemented to explore the potential of applying artificial intelligence (AI) technologies in works projects and maintenance work of the Drainage Services Department (DSD) for enhancing the efficiency related to environmental monitoring and structural inspection, referred to as the AIEIA and AIBIM projects, respectively. In the AIEIA project, AI technologies were explored to assist observing bird behaviour that would likely be influenced by nearby DSD construction projects. A domain randomisation-enhanced model was built to detect great egrets and little egrets at Penfold Park, Hong Kong, achieving a mean average precision of 87.65%. The detection result was used to analyse the Penfold Park egretry behaviour. In the AIBIM project, AI technologies were used to facilitate the condition assessment of concrete defects in sewage treatment facilities. A classifier was developed with supervised learning for concrete defect detection, attaining recalls of 86.2% and 89.9% for the cracking and spalling classes. Another concrete defect anomaly detector was built using unsupervised learning, achieving balanced results with F2 measures of 85.2% and 76.0% for the cracking and spalling classes. The two research studies render valuable experience for the DSD to integrate AI-enabled analytics into future work to continuously improve the drainage services in Hong Kong.

Artificial intelligence in veterinary medicine.

Artificial intelligence (AI) is a branch of computer science in which computer systems are designed to perform tasks that mimic human intelligence. Today, AI is reshaping day-to-day life and has numerous emerging medical applications poised to profoundly reshape the practice of veterinary medicine. In this Currents in One Health, we discuss the essential elements of AI for veterinary practitioners with the aim to help them make informed decisions in applying AI technologies into their practices. Veterinarians will play an integral role in ensuring the appropriate uses and good curation of data. The expertise of veterinary professionals will be vital to ensuring good data and, subsequently, AI that meets the needs of the profession. Readers interested in an in-depth description of AI and veterinary medicine are invited to explore a complementary manuscript of this Currents in One Health available in the May 2022 issue of the American Journal of Veterinary Research.

Emotions and Colors in a Design Archiving System: Applying AI Technology for Museums

This study proposes a new museum archiving system that uses artificial intelligence (AI) technology. It suggests a new retrieval interface to extract emotional characteristics of the design work to enrich the archiving database. A virtual curation was organized to showcase the proposed archiving system. We focused on finding emotional signals with advanced technology because humans build trust and connect with each other through emotional cues. There are numerous characteristics of a single work of art, but we focused on the emotions that viewers can feel when they appreciate the art and share a connection with the artists who made the work. The research was focused on design works, and the metadata were designed to extract three dominant colors and match them with emotional adjectives to enrich the data on the paintings. The purpose of this study was to provide information for new techniques of color utilization that encapsulate emotional adjectives. Through this research, we developed an image retrieval system based on metadata and transformed intangible emotions of design work into data. With the emotion archiving system, we organized virtual curation, adding a Korean design history collection with emotional words.