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Research Article
Robots Communicate at the Speed of Light: Revolutionary Milestones in the Development of Human Speech
Issue:
Volume 9, Issue 2, June 2025
Pages:
69-78
Received:
12 March 2025
Accepted:
1 April 2025
Published:
14 April 2025
Abstract: This first lecture by Tibor Mező explores key revolutionary milestones in the evolution of human speech. Beginning with the initial emergence of simple vocalizations among early hominins, the discussion highlights the gradual development of complex linguistic structures and symbolic communication. Significant anatomical changes, such as the lowered larynx position, supported the diversification of speech sounds (phonemes), facilitating the formation of structured language systems with grammar and syntax. The lecture emphasizes the critical role social cooperation played in speech evolution, suggesting that communities with enhanced communication skills had adaptive advantages. It further discusses the relationship between language and cognitive development, illustrating how symbolic language transformed human thought and social structures by enabling abstract idea transmission and cultural accumulation. The transition from oral to written communication marked another revolutionary milestone, profoundly impacting knowledge preservation, dissemination, and civilization’s evolution. The invention of writing approximately 5,000 years ago allowed information to surpass the limits of human memory, establishing new modes of collective knowledge storage and analysis. Despite the rise of literacy, oral traditions persisted, continuing to serve as essential vehicles for cultural cohesion and social interaction. Mező’s lecture portrays the evolution of speech as a continuous, complex interplay between biological adaptation, cognitive development, social dynamics, and technological innovations. This second lecture by Tibor Mező explores the revolutionary development and implications of robot-to-robot communication. Beginning with historical machine-to-machine (M2M) interactions, such as telemetry and early GSM-based modules, the talk highlights the significant transition brought by the Internet of Things (IoT), where devices began autonomously exchanging information. Technical aspects are discussed, emphasizing foundational network protocols like TCP/IP and UDP, alongside specialized communication frameworks such as Robot Operating System (ROS) and Agent Communication Languages (ACL) like KQML and FIPA ACL. Recent advances illustrate how robots autonomously evolve their unique languages through machine learning, optimizing communication beyond human comprehension. The lecture addresses social impacts, showcasing benefits such as industrial efficiency, increased safety, and convenience in everyday life. However, it also acknowledges emerging challenges, including transparency, trust issues, and ethical dilemmas, particularly concerning oversight and security. Finally, Tibor Mező highlights current practical applications of robot-to-robot communication across industries, from autonomous vehicles and smart cities to warehouse logistics and swarm robotics. The lecture concludes by exploring future opportunities, including the convergence of human and machine languages, and underscores the necessity of managing the ethical and societal implications of this rapidly evolving technological landscape.
Abstract: This first lecture by Tibor Mező explores key revolutionary milestones in the evolution of human speech. Beginning with the initial emergence of simple vocalizations among early hominins, the discussion highlights the gradual development of complex linguistic structures and symbolic communication. Significant anatomical changes, such as the lowered...
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Research Article
Compromise Between Topology Connection, Load Balance and Wireless Sensor Networks’Anomalies (WSN)
Serhii Perepelitsyn*
,
Andriy Perepelitsyn
Issue:
Volume 9, Issue 2, June 2025
Pages:
79-86
Received:
24 March 2025
Accepted:
6 May 2025
Published:
22 May 2025
DOI:
10.11648/j.ajist.20250902.12
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Abstract: The article addresses the challenge of ensuring a compromise between topological connectivity, load balancing, and anomaly detection in Wireless Sensor Networks (WSN). It analyzes current methods and approaches for optimizing the performance of sensor networks under dynamic conditions. The goal of this work is to analyze the interrelationship between these compromise aspects and propose an optimal approach for their integration. The article proposes a combined approach, which enables an optimal trade-off between these characteristics and enhances network interaction efficiency. To ensure the efficient operation of wireless sensor networks (WSN), it is essential to balance three key factors: topological connectivity and stable connectivity, even load distribution and security. Anomaly detection in wireless sensor networks (WSN) is critically important for ensuring their security and reliability. Modern anomaly detection methods include statistical analysis and machine learning techniques. Statistical traffic analysis enables the identification of deviations from normal network behavior, which may indicate anomalies existence. This approach is based on collecting and analyzing network traffic data, such as transmitted data volume, packet frequency, and other parameters. Deviations from established norms can signal potential issues or attacks. Further research in this domain should focus on the development of intelligent algorithms capable of adapting to real-time network changes. The integration of artificial intelligence and machine learning in WSN systems opens new opportunities for improving their efficiency and resilience to environmental changes.
Abstract: The article addresses the challenge of ensuring a compromise between topological connectivity, load balancing, and anomaly detection in Wireless Sensor Networks (WSN). It analyzes current methods and approaches for optimizing the performance of sensor networks under dynamic conditions. The goal of this work is to analyze the interrelationship betwe...
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Research Article
The Path from Software Engineering to System Engineering: Gamification Based S2S-G Framework
Wei Ren*,
Bo Qin
Issue:
Volume 9, Issue 2, June 2025
Pages:
87-93
Received:
24 March 2025
Accepted:
28 April 2025
Published:
19 May 2025
DOI:
10.11648/j.ajist.20250902.13
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Views:
Abstract: System engineering is a multidisciplinary, structured approach designed to manage the lifecycle of complex systems, ensuring their effective design, integration, and retirement. Benefits of system engineering include reduced risks, better stakeholder participation, adaptable systems, and improved documentation. However, as systems become more complex, traditional methodologies are often insufficient, leading to the emergence of Model-Based System Engineering (MBSE). MBSE, using Systems Modeling Language (SysML), offering a feasible pathway for software engineers transitioning to systems engineering through focused training. While software engineering shares similarities with systems engineering, particularly in process and goal alignment, the two disciplines differ significantly in scope and focus. The challenge lies in bridging the knowledge and mindset gaps between the two fields, as software engineers often struggle to transition to systems engineering due to differences in methodologies and focus areas. Gamification, the integration of game design elements into non-game contexts, has gained attention as a tool to facilitate this transition. This study compares software engineering and systems engineering, this work highlights their similarities and differences and proposes the S2S-G Framework, a gamification based framework, as a structured, effective tool to bridge the gap between the two disciplines.
Abstract: System engineering is a multidisciplinary, structured approach designed to manage the lifecycle of complex systems, ensuring their effective design, integration, and retirement. Benefits of system engineering include reduced risks, better stakeholder participation, adaptable systems, and improved documentation. However, as systems become more compl...
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Report
The Fundamental Statistical Data of Chinese Academic Libraries in 2023
Hanhua Wu*,
Hepu Deng
Issue:
Volume 9, Issue 2, June 2025
Pages:
94-110
Received:
18 November 2024
Accepted:
22 April 2025
Published:
26 May 2025
DOI:
10.11648/j.ajist.20250902.14
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Abstract: This study analyzes the development of Chinese academic libraries for identifying the emerging patterns and trends based on the nationwide operational data. By using a stratified sampling method, the annual operational data of the academic libraries from 1323 Chinese universities are collected. Five perspectives are adopted for analyzing the collected data using the common statistics. The study finds that the total fund for developing Chinese academic libraries is increased tremendously compared with that in the previous year. This is exemplified by the average literature resources purchase fee of RMB 2.126 million Yuan, the average electronic resources purchase fee of RMB 3.842 million Yuan, and the average library space of 0.271 million square meters. The study reveals that library directors are mostly senior and associate senior professionals and the average number of positioned librarians at 27.4, which is decreasing in a downward trend. It finds that the education qualification of positioned librarians has been improved significantly, especially with postgraduate degrees. The study discovers that there is only 3.8 percent of positioned librarians who are younger than 29 years old and the average number of young and positioned librarians is 1.05 librarians for each academic library. It shows that the average number of contracted staff is increased with decreased temporary staff and increased part-time students. Furthermore, the study reveals that the utilization rate of library resources is increased significantly based on the average volume of books and periodicals borrowed in academic libraries at 45 thousand volumes, the average cumulative volume of paper books at 1.426 million volumes including 48.9 thousand volumes of Chinese ancient books, and the total volume of ancient books in Chinese undergraduate academic libraries at over 14.437 million volumes.
Abstract: This study analyzes the development of Chinese academic libraries for identifying the emerging patterns and trends based on the nationwide operational data. By using a stratified sampling method, the annual operational data of the academic libraries from 1323 Chinese universities are collected. Five perspectives are adopted for analyzing the collec...
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