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The advent of the Fifth Industrial Revolution (5IR) establishes a transformation of information centers and Information Professionals (IP). 5IR addresses the deficiencies of the Fourth Industrial Revolution (4IR) with emphasis on renewed direction and development of the roles and skills of IP in the rapidly emerging technological innovations that interplay between humans and technologies from the perspective of Information Professionals and information centers. The roles, skills, and implications of the 5th industrial revolution to information professionals remain unclear. The study establishes a holistic review of roles, skills, and impact of the 5th industrial revolution and proffers working solutions to navigate, survive, and sustain as information professionals. The findings highlight technical skills, soft skills, upskill, re-skilling, and mega-skilling. The study recommends constant learning and adaptability, responsible data stewardship, collaboration across disciplines, human-centric systems, green IT transformation, and goal-oriented information services. By understanding the implications, IP can navigate, survive, and sustain the 5th industrial revolution.
The advent of the Fifth Industrial Revolution (5IR) establishes a transformation of information centers and Information Professionals (IP). 5IR addresses the deficiencies of the Fourth Industrial Revolution (4IR) with emphasis on renewed direction and development of the roles and skills of IP in the rapidly emerging technological innovations that interplay between humans and technologies from the perspective of Information Professionals and information centers. The roles, skills, and implications of the 5th industrial revolution to information professionals remain unclear. The study establishes a holistic review of roles, skills, and impact of the 5th industrial revolution and proffers working solutions to navigate, survive, and sustain as information professionals. The findings highlight technical skills, soft skills, upskill, re-skilling, and mega-skilling. The study recommends constant learning and adaptability, responsible data stewardship, collaboration across disciplines, human-centric systems, green IT transformation, and goal-oriented information services. By understanding the implications, IP can navigate, survive, and sustain the 5th industrial revolution.
The complex experimental procedure involved in TIG welding sequence, selection of ideal input parameters and further challenges during tensile testing to obtain the ultimate tensile strength (UTS) value of a given material may lead to inaccurate output depending on the experimental and test procedures. Moreover, while traditional optimization techniques which is sometimes based on trial and error, or prolonged experimental process may be time-consuming and costly, fuzzy logic-based expert systems offer a more effective solution to optimizing welding input variables for optimal output response. In this study, TIG welding input parameters derived from design of experiment for 20 weld runs were employed in welding AISI 1015 low carbon steel plate, and the welded samples were subjected to tensile testing to determine the UTS values. UTS of the control sample was obtained as 385 MPa, while UTS values of 409.670, 412.265, 410.256, 414.624, 415.563, 413.314, 411.432 and 408.306 MPa were obtained from the tensile test with corresponding welding input parameters (voltage, current, welding speed and gas flow rate, from weld runs No. 4, 5, 7, 8, 13, 14, 15 and 18. However, optimal UTS values of 407.923, 411.186, 408.874, 414.123, 415.116, 411.874, 409.702 and 406.827 MPa were obtained from the fuzzy logic optimization at the same No. of weld runs. Regression plot of the experimental and fuzzy logic predicted output response revealed R2 value of 0.9892 which is very close to 1, indicating the accuracy of the optimization sequence. This was further confirmed from a correlation plot which clearly indicated a strong positive correlation between the experimental and fuzzy optimized UTS values. The robust results of the study demonstrate the effectiveness and reliability of the fuzzy logic-based expert system in optimizing TIG welding parameters for low carbon steel plates.
IntroductionSpeech recognition and multimodal learning are two critical areas in machine learning. Current multimodal speech recognition systems often encounter challenges such as high computational demands and model complexity.MethodsTo overcome these issues, we propose a novel framework-EnglishAL-Net, a Multimodal Fusion-powered English Speaking Robot. This framework leverages the ALBEF model, optimizing it for real-time speech and multimodal interaction, and incorporates a newly designed text and image editor to fuse visual and textual information. The robot processes dynamic spoken input through the integration of Neural Machine Translation (NMT), enhancing its ability to understand and respond to spoken language.Results and discussionIn the experimental section, we constructed a dataset containing various scenarios and oral instructions for testing. The results show that compared to traditional unimodal processing methods, our model significantly improves both language understanding accuracy and response time. This research not only enhances the performance of multimodal interaction in robots but also opens up new possibilities for applications of robotic technology in education, rescue, customer service, and other fields, holding significant theoretical and practical value.
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