AI-Powered Innovations in High-Tech Research and Development: From Theory to Practice

This comparative review explores the dynamic and evolving landscape of artificial intelligence(AI)-powered innovations within high-tech research and development(R&D).It delves into both theoreticalmodels and practical applications across a broad range of industries,including biotechnology,automotive,aerospace,and telecom-munications.By examining critical advancements in AI algorithms,machine learning,deep learning models,simulations,and predictive analytics,the review underscores the transformative role AI has played in advancing theoretical research and shaping cutting-edge technologies.The review integrates both qualitative and quantitative data derived from academic studies,industry reports,and real-world case studies to showcase the tangible impacts of AI on product innovation,process optimization,and strategic decision-making.Notably,it discusses the challenges of integrating AI within complex industrial systems,such as ethical concerns,technical limitations,and the need for regulatory oversight.The findings reveal a mixed landscape where AI has significantly accelerated R&D processes,reduced costs,and enabled more precise simulations and predictions,but also highlighted gaps in knowledge transfer,skills adaptation,and cross-industry standardization.By bridging the gap between AI theory and practice,the review offers insights into the effectiveness,successes,and obstacles faced by organizations as they implement AI-driven solutions.Concluding with a forward-looking perspective,the review identifies emerging trends,future challenges,and promising opportunities inAI-poweredR&D,such as the rise of autonomous systems,AI-driven drug discovery,and sustainable energy solutions.It offers a holistic understanding of how AI is shaping the future of technological innovation and provides actionable insights for researchers,engineers,and policymakers involved in high-tech Research and Development(R&D).

Wearable Healthcare and Continuous Vital Sign Monitoring with IoT Integration

Technical and accessibility issues in hospitals often prevent patients from receiving optimal mental and physical health care,which is essential for independent living,especially as societies age and chronic diseases like diabetes and cardiovascular disease become more common.Recent advances in the Internet of Things(IoT)-enabled wearable devices offer potential solutions for remote health monitoring and everyday activity recognition,gaining significant attention in personalized healthcare.This paper comprehensively reviews wearable healthcare technology integrated with the IoT for continuous vital sign monitoring.Relevant papers were extracted and analyzed using a systematic numerical review method,covering various aspects such as sports monitoring,disease detection,patient monitoring,and medical diagnosis.The review highlights the transformative impact of IoTenabled wearable devices in healthcare,facilitating real-time monitoring of vital signs,including blood pressure,temperature,oxygen levels,and heart rate.Results from the reviewed papers demonstrate high accuracy and efficiency in predicting health conditions,improving sports performance,enhancing patient care,and diagnosing diseases.The integration of IoT in wearable healthcare devices enables remote patient monitoring,personalized care,and efficient data transmission,ultimately transcending traditional boundaries of healthcare and leading to better patient outcomes.

A Comprehensive Overview of the ELECTRE Method in Multi-Criteria Decision-Making

The ELECTRE(ELimination Et Choix Traduisant la REalite)method has gained widespread recognition as one of the most effective multi-criteria decision-making(MCDM)methods.Its versatility allows it to be applied in a wide range of areas such as engineering,economics,business,environmental management and many others.This paper aims to provide an overview of the ELECTRE method,including its fundamental concepts,applications,advantages,and limitations.At its core,the ELECTRE method is an outranking family of MCDM techniques,which allows for the direct comparison of alternatives based on a set of criteria.The method takes into account the preferences and importance of decision-makers and generates a ranking of the alternatives based on their relative strengths and weaknesses.The ELECTRE method is a powerful tool for decision-making,and its applicability to a wide range of fields demonstrates its versatility and adaptability.By understanding its concepts,applications,merits,and demerits,decision-makers can use the ELECTRE method to make informed and effective decisions in a variety of contexts.

Understanding Applications and Best Practices of DEMATEL:A Method for Prioritizing Key Factors in Multi-Criteria Decision-Making

Decision Making Trial and Evaluation Laboratory(DEMATEL)method is a powerful tool for understanding and visualizing the causal relationships among factors in complex decision-making problems.The method uses diagrams and matrixes to map out the causal relationships and interdependencies among factors,allowing decision-makers to identify key drivers and potential solutions to the problem.DEMATEL has a wide range of application areas,including supply chain management,environmental planning,healthcare,finance,and engineering,among others.The DEMATEL method is a valuable tool for decision-makers who need to understand the complex causal relationships among factors in order to make informed decisions.The method provides a structured approach for analyzing and prioritizing factors and for identifying potential solutions to complex problems.This paper describes the main features of this method,its application areas as well as the main process steps in the DEMATEL method.

VIKOR Method-An Effective Compromising Ranking Technique for Decision Making

The VIKOR(VlseKriterijumska Optimizacija I Kompromisno Resenje)method,which is a multi-criteria decision-making method,is examined in this paper.The VIKOR method,like other MCDM techniques such as the Technique for Order of Preference by Similarity to Ideal Solution(TOPSIS),is widely used to solve complex decision-making problems in various fields such as engineering,management,and finance.This paper provides an overview of the VIKOR method,including its application areas,advantages,and disadvantages.Besides,in this survey paper,the process steps of the VIKOR method are described,including determining the decision matrix,normalizing the matrix,determining the weights of the criteria,calculating the utility and regret values,calculating the VIKOR index,and finally ranking the alternatives.By providing an overview of the VIKOR method and its process steps,this paper aims to provide a better understanding of the method and its potential application in different decision-making contexts.

Analysis of Simple Additive Weighting Method(SAW)as a MultiAttribute Decision-Making Technique:A Step-by-Step Guide

The simple additive weighting(SAW)method is one of the oldest and most widely used decision-making methods.It has a simple process that can be utilized in different subject areas such as engineering,environmental sciences,and energy.The main concepts of the SAW method are introduced in this paper and then a step-by-step guide to using SAW technique for decision-making and ranking purposes in multi-attribute cases is presented.

The Impact of Leadership on the Growth of ICT Companies

Nowadays,one of the major purposes of any company is to survive in the competitive business markets.This purpose would be achievable through improving and developing growth in most cases.Prior studies suggest that leadership is a vitally important factor in achieving growth in any company.Some researchers studied leadership topics as one of the significant motivations for developing and improving the growth of a company and agreed that understanding the role of leadership and its effect on the growth of the company is influential.In all countries,Information Communication Technology(ICT)companies are recognized as significant growth drivers by leaving considerable impacts on that.According to the literature,growth is a determining factor for the productivity of any company.Based on the literature of the ICTs,weak and insufficient leadership skills are considered as the main factors that cause failure in achieving the planned growth and development of ICT.Consequently,the goal of this study is to clarify how leadership affects the development of ICT enterprises.

What are Different Research Approaches?Comprehensive Review of Qualitative,Quantitative,and Mixed Method Research,Their Applications,Types,and Limitations

There are different ways to examine and explain a study and its findings based on using numbers as a measure,a descriptive style,or a mixture of both.These three research approaches are quantitative,qualitative,and mixed methods that are commonly used by researchers in various research studies.However,with many options regarding the research design,it seems challenging for researchers to select the most appropriate approach based on the study and realize differences.This study provides a comprehensive review of qualitative,quantitative,and mixed-method research methods.Each method is clearly defined and specifically discussed based on applications,types,advantages,and limitations to help researchers identify select the most relevant type based on each study and navigate accordingly.

Role of Effective Leadership on Empowerment,Effective Communication,and Motivation in Customer Service

Customer service is the act of supporting customers of a business that can break a business or generate profit in the competitive environment with growing customers’expectations.Regarding the critical role of customer service to differentiate between businesses,it is considered as one of the top considerations in businesses.However,there is a range of key factors that are tied to the success of a customer service provider in offering quality customer service that will eventually lead the business through exceeding or falling short in responding to customers’expectations.Besides,businesses are prone to face some challenges in the employment of customer services that are required to be addressed.This paper aims to discuss the importance of customer service and the establishment of an efficient customer service strategy in business considering different influential factors that affect offering quality customer services.It also explains challenges that businesses may face in providing amazing customer services and how to address them.

Gathering Data, Providing Theoretical Foundations and Proposing Practical Pollution Reducing Measures to Strengthen the Global Fight against a Warming Atmosphere

An extensive and accurate knowledge of atmospheric disturbances such as turbulence,wind veering and other unexpected weather changes that are becoming frequent,violent and unpredictable,and which generate tropical cyclones and other intense weather situations is essential.Such unstable atmospheric happenings are occurring with increasing frequency[1].They include periodic collusion of unstable air parcels,uncertain wind trajectories some of which tend to veer and assume violent tendencies,precip­itation events that are becoming more erratic and rising temperatures.These atmospheric disturbances not only lead to catastrophic events,but they hamper our ability to predict with accuracy and certainty upcoming weather and climate events as well as their,magnitudes and intensities.

Navigating the ethical and privacy concerns of big data and machine learning in decision making

In recent years,the fields of big data and machine learning have gained significant attention for their potential to revolutionize decision-making processes.The vast amounts of data generated by various sources can provide valuable insights to inform decisions across a range of domains,from business and finance to healthcare and social policy.Machine learning algorithms enable computers to learn from data and improve their performance over time,thereby enhancing their ability to make predictions and identify patterns.This article provides a comprehensive overview of how big data and machine learning can improve decision-making processes between 2017-2022.It covers key concepts and techniques involved in these tools,including data collection,data preprocessing,feature selection,model training,and evaluation.The article also discusses the potential benefits and limitations of these tools and explores the ethical and privacy concerns associated with their use.In particular,it highlights the need for transparency and fairness in decision-making algorithms and the importance of protecting individuals’privacy rights.The review concludes by highlighting future research opportunities and challenges in this rapidly evolving field,including the need for more robust and interpretable models,as well as the integration of human decision making with machine learning algorithms.Ultimately,this review aims to provide insights for researchers and practitioners seeking to leverage big data and machine learning to improve decision-making processes in various domains.