The rapid evolution of information and communicationtechnology (ICT) in recent decades has triggeredprofound transformations across the global economiclandscape. A key driver of this transformation is theInternet of Everything (IoE), which integrates objects,data, people, a nd processes to create interconnectedecosystems that generate unprecedented value. The riseof IoE has not only revolutionized technologicalinnovation but has also played a critical role in reshapingglobal economies by fostering competitiveness andunlocking new economic opportunities. This articleexamines the economic impacts and technologicalbreakthroughs driven by IoE in six selected countries—spanning developed, developing, and neighboringeconomies. By analyzing their experiences, wehighlight how these nations have utilized IoE toachieve sustainable growth, strengthen marketpositions, and accelerate their technologicaladvancement. Countries venturing into the realm of IoEbenefit from two key aspects. Firstly, they gain newvalue from technological innovation, and secondly, theysecure competitive advantages and market shares againstnations that have yet to invest and adapt to the IoEmarket. Studying pioneering and trailblazing countriesin the realm of this technology, unveiling their patterns, visions, and key achievements, not only providesclear insights, identifies needs, and fostersadvancements, but also critically examines andanalyzes the subject matter. The findings offer essentialinsights for policymakers, business leaders, and innovators, providing a roadmap for leveraging IoE tomaximize economic benefits and drive digitaltransformation on a global scale.
Archives for December 2024
RECONCEPTUALIZING COGNITIVE FRAMEWORKS: AN INNOVATIVE APPROACH TO ADDRESSING CHALLENGES IN ECOLOGICAL AESTHETICS
This paper discusses the implementation of theB.S. degree in Robotics Engineering offered at theWorcester Polytechnic Institute (WPI). Robotics isfundamentally multi-disciplinary, drawing onElectrical Engineering, Mechanical Engineering,Computer Science and many other academicdisciplines. While many programs includerobotics as an element within a discipline such asElectrical Engineering, Mechanical Engineeringor Computer Science, the Robotics EngineeringProgram at WPI took a decidedly differentapproach by introducing robotics as a newengineering discipline.
PHILOSOPHICAL PERSPECTIVES ON ECONOMICS IN THE CONTEXT OF INFORMATION THEORY
Computer-game development is immenselypopular with undergraduate computer-science andcomputer-engineering students. More importantly,the design and development of computer-games isan excellent pedagogical opportunity: developinggames integrates a great number of the subjectsstudents learn throughout their undergraduateexperience[1]. This integration of topics, coupledwith student driven motivation to learn, is animportant step for students allowing them toutilize tools from programming and graphics tocalculus and physics; from data structures andalgorithms to computer hardware to name just afew subjects[2]. From a teaching perspective,computer-game development is great fun to teachas the students are highly motivated and thesubject matter, while very challenging, is fun!
A FEATURE-BASED MODEL FOR FEAR DETECTION INSPIRED BY BIOLOGY
Facial expressions determine the inner emotional statesof people. Different emotional states such as anger, fear,happiness, etc. can be recognized on people's faces. Oneof the most important emotional states is the state of fearbecause it is used to diagnose many diseases such aspanic syndrome, post-traumatic stress disorder, etc. Theface is one of the biometrics that has been proposed todetect fear because it contains small features thatincrease the recognition rate. In this paper, a biologicalmodel inspired an early biological model is proposed toextract effective features for optimal fear detection. Thismodel is inspired by the model of the brain and nervoussystem involved with the human brain, so it shows asimilar function compare to brain. In this model, fourcomputational layers were used. In the first layer, theinput images will be pyramidal in six scales from largeto small. Then the whole pyramid entered the next layerand Gabor filter was applied for each image and theresults entered the next layer. In the third layer, a laterreduction in feature extraction is performed. In the lastlayer, normalization will be done on the images. Finally,the outputs of the model are given to the svm classifierto perform the recognition operation. Experiments willbe performed on JAFFE database images. In theexperimental results, it can be seen that the proposedmodel shows better performance compared to othercompeting models such as BEL and Naive Bayes modelwith recognition accuracy, precision and recall of99.33%, 99.71% and 99.5%, respectively.