Electrical plug loads comprise an increasingly larger share of building energy consumption as improvements have been made to Heating, Ventilation, and Air Conditioning (HVAC) and lighting systems. It is anticipated that plug loads will account for a significant portion of the energy consumption of Sustainability Base, a recently constructed high-performance office building at NASA Ames Research Center. Consequently, monitoring plug loads will be critical to achieve energy efficient operations. In this paper we describe the development of a knowledge-based system to analyze data collected from a plug load management system that allows for metering and control of individual loads. Since Sustainability Base was not yet occupied at the time of this investigation, the study was conducted in another building on the Ames campus to prototype the system. The paper focuses on the knowledge engineering and verification of a modular software system that promotes efficient use of office building plug loads. The knowledge-based system generates summary usage reports and alerts building personnel of malfunctioning equipment and unexpected plug load consumption. The system is planned to be applied to Sustainability Base and is expected to identify malfunctioning loads and reduce building energy consumption.

International Journal of Engineering and Advanced Technology Acceptance Rate - ResearchHelpDesk - International Journal of Engineering and Advanced Technology (IJEAT) is having Online-ISSN 2249-8958, bi-monthly international journal, being published in the months of February, April, June, August, October, and December by Blue Eyes Intelligence Engineering & Sciences Publication (BEIESP) Bhopal (M.P.), India since the year 2011. It is academic, online, open access, double-blind, peer-reviewed international journal. It aims to publish original, theoretical and practical advances in Computer Science & Engineering, Information Technology, Electrical and Electronics Engineering, Electronics and Telecommunication, Mechanical Engineering, Civil Engineering, Textile Engineering and all interdisciplinary streams of Engineering Sciences. All submitted papers will be reviewed by the board of committee of IJEAT. Aim of IJEAT Journal disseminate original, scientific, theoretical or applied research in the field of Engineering and allied fields. dispense a platform for publishing results and research with a strong empirical component. aqueduct the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research. seek original and unpublished research papers based on theoretical or experimental works for the publication globally. publish original, theoretical and practical advances in Computer Science & Engineering, Information Technology, Electrical and Electronics Engineering, Electronics and Telecommunication, Mechanical Engineering, Civil Engineering, Textile Engineering and all interdisciplinary streams of Engineering Sciences. impart a platform for publishing results and research with a strong empirical component. create a bridge for a significant gap between research and practice by promoting the publication of original, novel, industry-relevant research. solicit original and unpublished research papers, based on theoretical or experimental works. Scope of IJEAT International Journal of Engineering and Advanced Technology (IJEAT) covers all topics of all engineering branches. Some of them are Computer Science & Engineering, Information Technology, Electronics & Communication, Electrical and Electronics, Electronics and Telecommunication, Civil Engineering, Mechanical Engineering, Textile Engineering and all interdisciplinary streams of Engineering Sciences. The main topic includes but not limited to: 1. Smart Computing and Information Processing Signal and Speech Processing Image Processing and Pattern Recognition WSN Artificial Intelligence and machine learning Data mining and warehousing Data Analytics Deep learning Bioinformatics High Performance computing Advanced Computer networking Cloud Computing IoT Parallel Computing on GPU Human Computer Interactions 2. Recent Trends in Microelectronics and VLSI Design Process & Device Technologies Low-power design Nanometer-scale integrated circuits Application specific ICs (ASICs) FPGAs Nanotechnology Nano electronics and Quantum Computing 3. Challenges of Industry and their Solutions, Communications Advanced Manufacturing Technologies Artificial Intelligence Autonomous Robots Augmented Reality Big Data Analytics and Business Intelligence Cyber Physical Systems (CPS) Digital Clone or Simulation Industrial Internet of Things (IIoT) Manufacturing IOT Plant Cyber security Smart Solutions – Wearable Sensors and Smart Glasses System Integration Small Batch Manufacturing Visual Analytics Virtual Reality 3D Printing 4. Internet of Things (IoT) Internet of Things (IoT) & IoE & Edge Computing Distributed Mobile Applications Utilizing IoT Security, Privacy and Trust in IoT & IoE Standards for IoT Applications Ubiquitous Computing Block Chain-enabled IoT Device and Data Security and Privacy Application of WSN in IoT Cloud Resources Utilization in IoT Wireless Access Technologies for IoT Mobile Applications and Services for IoT Machine/ Deep Learning with IoT & IoE Smart Sensors and Internet of Things for Smart City Logic, Functional programming and Microcontrollers for IoT Sensor Networks, Actuators for Internet of Things Data Visualization using IoT IoT Application and Communication Protocol Big Data Analytics for Social Networking using IoT IoT Applications for Smart Cities Emulation and Simulation Methodologies for IoT IoT Applied for Digital Contents 5. Microwaves and Photonics Microwave filter Micro Strip antenna Microwave Link design Microwave oscillator Frequency selective surface Microwave Antenna Microwave Photonics Radio over fiber Optical communication Optical oscillator Optical Link design Optical phase lock loop Optical devices 6. Computation Intelligence and Analytics Soft Computing Advance Ubiquitous Computing Parallel Computing Distributed Computing Machine Learning Information Retrieval Expert Systems Data Mining Text Mining Data Warehousing Predictive Analysis Data Management Big Data Analytics Big Data Security 7. Energy Harvesting and Wireless Power Transmission Energy harvesting and transfer for wireless sensor networks Economics of energy harvesting communications Waveform optimization for wireless power transfer RF Energy Harvesting Wireless Power Transmission Microstrip Antenna design and application Wearable Textile Antenna Luminescence Rectenna 8. Advance Concept of Networking and Database Computer Network Mobile Adhoc Network Image Security Application Artificial Intelligence and machine learning in the Field of Network and Database Data Analytic High performance computing Pattern Recognition 9. Machine Learning (ML) and Knowledge Mining (KM) Regression and prediction Problem solving and planning Clustering Classification Neural information processing Vision and speech perception Heterogeneous and streaming data Natural language processing Probabilistic Models and Methods Reasoning and inference Marketing and social sciences Data mining Knowledge Discovery Web mining Information retrieval Design and diagnosis Game playing Streaming data Music Modelling and Analysis Robotics and control Multi-agent systems Bioinformatics Social sciences Industrial, financial and scientific applications of all kind 10. Advanced Computer networking Computational Intelligence Data Management, Exploration, and Mining Robotics Artificial Intelligence and Machine Learning Computer Architecture and VLSI Computer Graphics, Simulation, and Modelling Digital System and Logic Design Natural Language Processing and Machine Translation Parallel and Distributed Algorithms Pattern Recognition and Analysis Systems and Software Engineering Nature Inspired Computing Signal and Image Processing Reconfigurable Computing Cloud, Cluster, Grid and P2P Computing Biomedical Computing Advanced Bioinformatics Green Computing Mobile Computing Nano Ubiquitous Computing Context Awareness and Personalization, Autonomic and Trusted Computing Cryptography and Applied Mathematics Security, Trust and Privacy Digital Rights Management Networked-Driven Multicourse Chips Internet Computing Agricultural Informatics and Communication Community Information Systems Computational Economics, Digital Photogrammetric Remote Sensing, GIS and GPS Disaster Management e-governance, e-Commerce, e-business, e-Learning Forest Genomics and Informatics Healthcare Informatics Information Ecology and Knowledge Management Irrigation Informatics Neuro-Informatics Open Source: Challenges and opportunities Web-Based Learning: Innovation and Challenges Soft computing Signal and Speech Processing Natural Language Processing 11. Communications Microstrip Antenna Microwave Radar and Satellite Smart Antenna MIMO Antenna Wireless Communication RFID Network and Applications 5G Communication 6G Communication 12. Algorithms and Complexity Sequential, Parallel And Distributed Algorithms And Data Structures Approximation And Randomized Algorithms Graph Algorithms And Graph Drawing On-Line And Streaming Algorithms Analysis Of Algorithms And Computational Complexity Algorithm Engineering Web Algorithms Exact And Parameterized Computation Algorithmic Game Theory Computational Biology Foundations Of Communication Networks Computational Geometry Discrete Optimization 13. Software Engineering and Knowledge Engineering Software Engineering Methodologies Agent-based software engineering Artificial intelligence approaches to software engineering Component-based software engineering Embedded and ubiquitous software engineering Aspect-based software engineering Empirical software engineering Search-Based Software engineering Automated software design and synthesis Computer-supported cooperative work Automated software specification Reverse engineering Software Engineering Techniques and Production Perspectives Requirements engineering Software analysis, design and modelling Software maintenance and evolution Software engineering tools and environments Software engineering decision support Software design patterns Software product lines Process and workflow management Reflection and metadata approaches Program understanding and system maintenance Software domain modelling and analysis Software economics Multimedia and hypermedia software engineering Software engineering case study and experience reports Enterprise software, middleware, and tools Artificial intelligent methods, models, techniques Artificial life and societies Swarm intelligence Smart Spaces Autonomic computing and agent-based systems Autonomic computing Adaptive Systems Agent architectures, ontologies, languages and protocols Multi-agent systems Agent-based learning and knowledge discovery Interface agents Agent-based auctions and marketplaces Secure mobile and multi-agent systems Mobile agents SOA and Service-Oriented Systems Service-centric software engineering Service oriented requirements engineering Service oriented architectures Middleware for service based systems Service discovery and composition Service level

Electrical plug loads comprise an increasingly larger share of building energy consumption as improvements have been made to Heating, Ventilation, and Air Conditioning (HVAC) and lighting systems. It is anticipated that plug loads will account for a significant portion of the energy consumption of Sustainability Base, a recently constructed high-performance office building at NASA Ames Research Center. Consequently, monitoring plug loads will be critical to achieve energy efficient operations. In this paper we describe the development of a knowledge-based system to analyze data collected from a plug load management system that allows for metering and control of individual loads. Since Sustainability Base was not yet occupied at the time of this investigation, the study was conducted in another building on the Ames campus to prototype the system. The paper focuses on the knowledge engineering and verification of a modular software system that promotes efficient use of office building plug loads. The knowledge-based system generates summary usage reports and alerts building personnel of malfunctioning equipment and unexpected plug load consumption. The system is planned to be applied to Sustainability Base and is expected to identify malfunctioning loads and reduce building energy consumption.

International journal of machine learning and computing Acceptance Rate - ResearchHelpDesk - International Journal of Machine Learning and Computing - IJMLC is an international academic open access journal which gains a foothold in Singapore, Asia and opens to the world. It aims to promote the integration of machine learning and computing. The focus is to publish papers on state-of-the-art machine learning and computing. Submitted papers will be reviewed by technical committees of the Journal and Association. The audience includes researchers, managers and operators for machine learning and computing as well as designers and developers. All submitted articles should report original, previously unpublished research results, experimental or theoretical, and will be peer-reviewed. Articles submitted to the journal should meet these criteria and must not be under consideration for publication elsewhere. Manuscripts should follow the style of the journal and are subject to both review and editing. IJMLC is an open access journal which focus on publishing original and peer reviewed research papers on all aspects of machine learning and computing. And the topics include but not limited to: Adaptive systems Business intelligence Biometrics Bioinformatics Data and web mining Intelligent agent Financial engineering Inductive learning Geo-informatics Pattern Recognition Logistics Intelligent control Media computing Neural net and support vector machine Hybrid and nonlinear system Fuzzy set theory, fuzzy control and system Knowledge management Information retrieval Intelligent and knowledge based system Rough and fuzzy rough set Networking and information security Evolutionary computation Ensemble method Information fusion Visual information processing Computational life science Abstract & indexing Scopus (since 2017), EI (INSPEC, IET), Google Scholar, Crossref, ProQuest, Electronic Journals Library.

Sensors are vital components for control and advanced health management techniques. However, sensors continue to be considered the weak link in many engineering applications since often they are less reli- able than the system they are observing. This is in part due to the sensors’ operating principles and their susceptibility to interference from the environment. Detecting and mitigating sensor failure modes are becoming increasingly important in more complex and safety-critical applications. This paper reports on different techniques for sensor fault detection, disambiguation, and mitigation. It presents an expert system that uses a combination of object-oriented modeling, rules, and semantic networks to deal with the most common sensor faults, such as bias, drift, scaling, and dropout, as well as system faults. The paper also describes a sensor correction module that is based on fault parameters extraction (for bias, drift, and scaling fault modes) as well as utilizing partial redundancy for dropout sensor fault modes). The knowledge-based system was derived from the results obtained in a previously deployed Neural Network (NN) application for fault detection and disambiguation. Results are illustrated on an electromechanical actuator application where the system faults are jam and spalling. In addition to the functions implemented in the previous work, system fault detection under sensor failure was also modeled. The paper includes a sensitivity analysis that compares the results previously obtained with the NN. It concludes with a discussion of similarities and differences between the two approaches and how the knowledge based system provides additional functionality compared to the NN implementation.

The dataset contains 600 fully played games of FreeCiv game.

Fuzzy Knowledge-base for 51 different biomarkers and their association with mortality risk factors in community dwelling elderlyIf you use this dataset/KB, please cite the following articles:Rizzo L., Majnaric L., Dondio P., Longo L. (2018) An Investigation of Argumentation Theory for the Prediction of Survival in Elderly Using Biomarkers. In: Iliadis L., Maglogiannis I., Plagianakos V. (eds) Artificial Intelligence Applications and Innovations. AIAI 2018. IFIP Advances in Information and Communication Technology, vol 519. Springer, ChamRizzo L., Majnaric L., Longo L. (2018) A Comparative Study of Defeasible Argumentation and Non-monotonic Fuzzy Reasoning for Elderly Survival Prediction Using Biomarkers. In: Ghidini C., Magnini B., Passerini A., Traverso P. (eds) AI*IA 2018 – Advances in Artificial Intelligence. AI*IA 2018. Lecture Notes in Computer Science, vol 11298. Springer, Cham

Knowledge Base Software Market Outlook

The global market size for Knowledge Base Software was valued at approximately USD 2.5 billion in 2023 and is expected to reach around USD 7.8 billion by 2032, growing at a CAGR of 13.4% during the forecast period. This robust growth is driven by the increasing need for efficient information management and customer support solutions among organizations across various industries.

One of the primary growth factors for the Knowledge Base Software market is the rising demand for customer self-service solutions. With the proliferation of digital platforms, consumers now expect quick and easy access to information without the need to interact with customer service representatives. Knowledge Base Software provides a centralized repository of information that customers can access independently, thereby improving customer satisfaction and reducing operational costs for businesses. Additionally, the integration of advanced technologies such as artificial intelligence (AI) and machine learning (ML) into these systems is enhancing their capabilities, making them more intuitive and efficient.

Furthermore, the growing adoption of remote working and the increasing need for efficient internal knowledge sharing within organizations are significant drivers for market growth. As more companies embrace flexible working arrangements, the necessity for a robust knowledge management system becomes paramount. Knowledge Base Software facilitates seamless information sharing among employees, ensuring that they have access to critical information regardless of their location. This is particularly crucial for maintaining productivity and collaboration in remote and hybrid work environments.

The need to comply with regulatory and compliance requirements is also propelling the demand for Knowledge Base Software. Industries such as healthcare, BFSI, and government are highly regulated and require stringent documentation and information management practices. Knowledge Base Software helps organizations in these sectors manage their documentation processes more effectively, ensuring compliance with industry standards and regulations. This, in turn, mitigates the risk of legal issues and enhances operational efficiency.

Regionally, North America currently holds the largest share of the Knowledge Base Software market, attributed to the early adoption of advanced technologies and the presence of numerous key market players in the region. However, the Asia Pacific region is expected to witness the highest growth rate during the forecast period. The rapid digital transformation across various sectors in countries like China, India, and Japan, coupled with the increasing investments in IT infrastructure, is driving the market growth in this region. Additionally, the growing number of small and medium enterprises (SMEs) and their increasing awareness of the benefits of knowledge management solutions are further contributing to the market expansion in Asia Pacific.

Component Analysis

The Knowledge Base Software market is segmented into Software and Services. The Software segment dominates the market, given the essential role of software solutions in creating, managing, and distributing knowledge content. These software solutions come equipped with various functionalities such as content management, search and retrieval, and analytics, which are critical for efficient knowledge management. The integration of AI and ML technologies into these software solutions is further enhancing their capabilities, making them more intuitive and user-friendly.

Within the Software segment, cloud-based solutions are gaining significant traction due to their flexibility, scalability, and cost-effectiveness. Cloud-based Knowledge Base Software allows organizations to access information from anywhere, at any time, which is particularly beneficial for businesses with a dispersed workforce. Moreover, these solutions offer the advantage of lower upfront costs and reduced IT maintenance, making them an attractive option for SMEs. As a result, the cloud-based segment is expected to witness substantial growth during the forecast period.

On the other hand, the Services segment includes implementation, training, and support services. These services are crucial for the successful deployment and utilization of Knowledge Base Software. Implementation services ensure that the software is correctly integrated into the existing IT infrastructure of an organization, while training services help employees understand and utilize the software effectively. Support

International Journal of Engineering and Advanced Technology FAQ - ResearchHelpDesk - International Journal of Engineering and Advanced Technology (IJEAT) is having Online-ISSN 2249-8958, bi-monthly international journal, being published in the months of February, April, June, August, October, and December by Blue Eyes Intelligence Engineering & Sciences Publication (BEIESP) Bhopal (M.P.), India since the year 2011. It is academic, online, open access, double-blind, peer-reviewed international journal. It aims to publish original, theoretical and practical advances in Computer Science & Engineering, Information Technology, Electrical and Electronics Engineering, Electronics and Telecommunication, Mechanical Engineering, Civil Engineering, Textile Engineering and all interdisciplinary streams of Engineering Sciences. All submitted papers will be reviewed by the board of committee of IJEAT. Aim of IJEAT Journal disseminate original, scientific, theoretical or applied research in the field of Engineering and allied fields. dispense a platform for publishing results and research with a strong empirical component. aqueduct the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research. seek original and unpublished research papers based on theoretical or experimental works for the publication globally. publish original, theoretical and practical advances in Computer Science & Engineering, Information Technology, Electrical and Electronics Engineering, Electronics and Telecommunication, Mechanical Engineering, Civil Engineering, Textile Engineering and all interdisciplinary streams of Engineering Sciences. impart a platform for publishing results and research with a strong empirical component. create a bridge for a significant gap between research and practice by promoting the publication of original, novel, industry-relevant research. solicit original and unpublished research papers, based on theoretical or experimental works. Scope of IJEAT International Journal of Engineering and Advanced Technology (IJEAT) covers all topics of all engineering branches. Some of them are Computer Science & Engineering, Information Technology, Electronics & Communication, Electrical and Electronics, Electronics and Telecommunication, Civil Engineering, Mechanical Engineering, Textile Engineering and all interdisciplinary streams of Engineering Sciences. The main topic includes but not limited to: 1. Smart Computing and Information Processing Signal and Speech Processing Image Processing and Pattern Recognition WSN Artificial Intelligence and machine learning Data mining and warehousing Data Analytics Deep learning Bioinformatics High Performance computing Advanced Computer networking Cloud Computing IoT Parallel Computing on GPU Human Computer Interactions 2. Recent Trends in Microelectronics and VLSI Design Process & Device Technologies Low-power design Nanometer-scale integrated circuits Application specific ICs (ASICs) FPGAs Nanotechnology Nano electronics and Quantum Computing 3. Challenges of Industry and their Solutions, Communications Advanced Manufacturing Technologies Artificial Intelligence Autonomous Robots Augmented Reality Big Data Analytics and Business Intelligence Cyber Physical Systems (CPS) Digital Clone or Simulation Industrial Internet of Things (IIoT) Manufacturing IOT Plant Cyber security Smart Solutions – Wearable Sensors and Smart Glasses System Integration Small Batch Manufacturing Visual Analytics Virtual Reality 3D Printing 4. Internet of Things (IoT) Internet of Things (IoT) & IoE & Edge Computing Distributed Mobile Applications Utilizing IoT Security, Privacy and Trust in IoT & IoE Standards for IoT Applications Ubiquitous Computing Block Chain-enabled IoT Device and Data Security and Privacy Application of WSN in IoT Cloud Resources Utilization in IoT Wireless Access Technologies for IoT Mobile Applications and Services for IoT Machine/ Deep Learning with IoT & IoE Smart Sensors and Internet of Things for Smart City Logic, Functional programming and Microcontrollers for IoT Sensor Networks, Actuators for Internet of Things Data Visualization using IoT IoT Application and Communication Protocol Big Data Analytics for Social Networking using IoT IoT Applications for Smart Cities Emulation and Simulation Methodologies for IoT IoT Applied for Digital Contents 5. Microwaves and Photonics Microwave filter Micro Strip antenna Microwave Link design Microwave oscillator Frequency selective surface Microwave Antenna Microwave Photonics Radio over fiber Optical communication Optical oscillator Optical Link design Optical phase lock loop Optical devices 6. Computation Intelligence and Analytics Soft Computing Advance Ubiquitous Computing Parallel Computing Distributed Computing Machine Learning Information Retrieval Expert Systems Data Mining Text Mining Data Warehousing Predictive Analysis Data Management Big Data Analytics Big Data Security 7. Energy Harvesting and Wireless Power Transmission Energy harvesting and transfer for wireless sensor networks Economics of energy harvesting communications Waveform optimization for wireless power transfer RF Energy Harvesting Wireless Power Transmission Microstrip Antenna design and application Wearable Textile Antenna Luminescence Rectenna 8. Advance Concept of Networking and Database Computer Network Mobile Adhoc Network Image Security Application Artificial Intelligence and machine learning in the Field of Network and Database Data Analytic High performance computing Pattern Recognition 9. Machine Learning (ML) and Knowledge Mining (KM) Regression and prediction Problem solving and planning Clustering Classification Neural information processing Vision and speech perception Heterogeneous and streaming data Natural language processing Probabilistic Models and Methods Reasoning and inference Marketing and social sciences Data mining Knowledge Discovery Web mining Information retrieval Design and diagnosis Game playing Streaming data Music Modelling and Analysis Robotics and control Multi-agent systems Bioinformatics Social sciences Industrial, financial and scientific applications of all kind 10. Advanced Computer networking Computational Intelligence Data Management, Exploration, and Mining Robotics Artificial Intelligence and Machine Learning Computer Architecture and VLSI Computer Graphics, Simulation, and Modelling Digital System and Logic Design Natural Language Processing and Machine Translation Parallel and Distributed Algorithms Pattern Recognition and Analysis Systems and Software Engineering Nature Inspired Computing Signal and Image Processing Reconfigurable Computing Cloud, Cluster, Grid and P2P Computing Biomedical Computing Advanced Bioinformatics Green Computing Mobile Computing Nano Ubiquitous Computing Context Awareness and Personalization, Autonomic and Trusted Computing Cryptography and Applied Mathematics Security, Trust and Privacy Digital Rights Management Networked-Driven Multicourse Chips Internet Computing Agricultural Informatics and Communication Community Information Systems Computational Economics, Digital Photogrammetric Remote Sensing, GIS and GPS Disaster Management e-governance, e-Commerce, e-business, e-Learning Forest Genomics and Informatics Healthcare Informatics Information Ecology and Knowledge Management Irrigation Informatics Neuro-Informatics Open Source: Challenges and opportunities Web-Based Learning: Innovation and Challenges Soft computing Signal and Speech Processing Natural Language Processing 11. Communications Microstrip Antenna Microwave Radar and Satellite Smart Antenna MIMO Antenna Wireless Communication RFID Network and Applications 5G Communication 6G Communication 12. Algorithms and Complexity Sequential, Parallel And Distributed Algorithms And Data Structures Approximation And Randomized Algorithms Graph Algorithms And Graph Drawing On-Line And Streaming Algorithms Analysis Of Algorithms And Computational Complexity Algorithm Engineering Web Algorithms Exact And Parameterized Computation Algorithmic Game Theory Computational Biology Foundations Of Communication Networks Computational Geometry Discrete Optimization 13. Software Engineering and Knowledge Engineering Software Engineering Methodologies Agent-based software engineering Artificial intelligence approaches to software engineering Component-based software engineering Embedded and ubiquitous software engineering Aspect-based software engineering Empirical software engineering Search-Based Software engineering Automated software design and synthesis Computer-supported cooperative work Automated software specification Reverse engineering Software Engineering Techniques and Production Perspectives Requirements engineering Software analysis, design and modelling Software maintenance and evolution Software engineering tools and environments Software engineering decision support Software design patterns Software product lines Process and workflow management Reflection and metadata approaches Program understanding and system maintenance Software domain modelling and analysis Software economics Multimedia and hypermedia software engineering Software engineering case study and experience reports Enterprise software, middleware, and tools Artificial intelligent methods, models, techniques Artificial life and societies Swarm intelligence Smart Spaces Autonomic computing and agent-based systems Autonomic computing Adaptive Systems Agent architectures, ontologies, languages and protocols Multi-agent systems Agent-based learning and knowledge discovery Interface agents Agent-based auctions and marketplaces Secure mobile and multi-agent systems Mobile agents SOA and Service-Oriented Systems Service-centric software engineering Service oriented requirements engineering Service oriented architectures Middleware for service based systems Service discovery and composition Service level agreements (drafting,

International Journal of Engineering and Advanced Technology Impact Factor 2024-2025 - ResearchHelpDesk - International Journal of Engineering and Advanced Technology (IJEAT) is having Online-ISSN 2249-8958, bi-monthly international journal, being published in the months of February, April, June, August, October, and December by Blue Eyes Intelligence Engineering & Sciences Publication (BEIESP) Bhopal (M.P.), India since the year 2011. It is academic, online, open access, double-blind, peer-reviewed international journal. It aims to publish original, theoretical and practical advances in Computer Science & Engineering, Information Technology, Electrical and Electronics Engineering, Electronics and Telecommunication, Mechanical Engineering, Civil Engineering, Textile Engineering and all interdisciplinary streams of Engineering Sciences. All submitted papers will be reviewed by the board of committee of IJEAT. Aim of IJEAT Journal disseminate original, scientific, theoretical or applied research in the field of Engineering and allied fields. dispense a platform for publishing results and research with a strong empirical component. aqueduct the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research. seek original and unpublished research papers based on theoretical or experimental works for the publication globally. publish original, theoretical and practical advances in Computer Science & Engineering, Information Technology, Electrical and Electronics Engineering, Electronics and Telecommunication, Mechanical Engineering, Civil Engineering, Textile Engineering and all interdisciplinary streams of Engineering Sciences. impart a platform for publishing results and research with a strong empirical component. create a bridge for a significant gap between research and practice by promoting the publication of original, novel, industry-relevant research. solicit original and unpublished research papers, based on theoretical or experimental works. Scope of IJEAT International Journal of Engineering and Advanced Technology (IJEAT) covers all topics of all engineering branches. Some of them are Computer Science & Engineering, Information Technology, Electronics & Communication, Electrical and Electronics, Electronics and Telecommunication, Civil Engineering, Mechanical Engineering, Textile Engineering and all interdisciplinary streams of Engineering Sciences. The main topic includes but not limited to: 1. Smart Computing and Information Processing Signal and Speech Processing Image Processing and Pattern Recognition WSN Artificial Intelligence and machine learning Data mining and warehousing Data Analytics Deep learning Bioinformatics High Performance computing Advanced Computer networking Cloud Computing IoT Parallel Computing on GPU Human Computer Interactions 2. Recent Trends in Microelectronics and VLSI Design Process & Device Technologies Low-power design Nanometer-scale integrated circuits Application specific ICs (ASICs) FPGAs Nanotechnology Nano electronics and Quantum Computing 3. Challenges of Industry and their Solutions, Communications Advanced Manufacturing Technologies Artificial Intelligence Autonomous Robots Augmented Reality Big Data Analytics and Business Intelligence Cyber Physical Systems (CPS) Digital Clone or Simulation Industrial Internet of Things (IIoT) Manufacturing IOT Plant Cyber security Smart Solutions – Wearable Sensors and Smart Glasses System Integration Small Batch Manufacturing Visual Analytics Virtual Reality 3D Printing 4. Internet of Things (IoT) Internet of Things (IoT) & IoE & Edge Computing Distributed Mobile Applications Utilizing IoT Security, Privacy and Trust in IoT & IoE Standards for IoT Applications Ubiquitous Computing Block Chain-enabled IoT Device and Data Security and Privacy Application of WSN in IoT Cloud Resources Utilization in IoT Wireless Access Technologies for IoT Mobile Applications and Services for IoT Machine/ Deep Learning with IoT & IoE Smart Sensors and Internet of Things for Smart City Logic, Functional programming and Microcontrollers for IoT Sensor Networks, Actuators for Internet of Things Data Visualization using IoT IoT Application and Communication Protocol Big Data Analytics for Social Networking using IoT IoT Applications for Smart Cities Emulation and Simulation Methodologies for IoT IoT Applied for Digital Contents 5. Microwaves and Photonics Microwave filter Micro Strip antenna Microwave Link design Microwave oscillator Frequency selective surface Microwave Antenna Microwave Photonics Radio over fiber Optical communication Optical oscillator Optical Link design Optical phase lock loop Optical devices 6. Computation Intelligence and Analytics Soft Computing Advance Ubiquitous Computing Parallel Computing Distributed Computing Machine Learning Information Retrieval Expert Systems Data Mining Text Mining Data Warehousing Predictive Analysis Data Management Big Data Analytics Big Data Security 7. Energy Harvesting and Wireless Power Transmission Energy harvesting and transfer for wireless sensor networks Economics of energy harvesting communications Waveform optimization for wireless power transfer RF Energy Harvesting Wireless Power Transmission Microstrip Antenna design and application Wearable Textile Antenna Luminescence Rectenna 8. Advance Concept of Networking and Database Computer Network Mobile Adhoc Network Image Security Application Artificial Intelligence and machine learning in the Field of Network and Database Data Analytic High performance computing Pattern Recognition 9. Machine Learning (ML) and Knowledge Mining (KM) Regression and prediction Problem solving and planning Clustering Classification Neural information processing Vision and speech perception Heterogeneous and streaming data Natural language processing Probabilistic Models and Methods Reasoning and inference Marketing and social sciences Data mining Knowledge Discovery Web mining Information retrieval Design and diagnosis Game playing Streaming data Music Modelling and Analysis Robotics and control Multi-agent systems Bioinformatics Social sciences Industrial, financial and scientific applications of all kind 10. Advanced Computer networking Computational Intelligence Data Management, Exploration, and Mining Robotics Artificial Intelligence and Machine Learning Computer Architecture and VLSI Computer Graphics, Simulation, and Modelling Digital System and Logic Design Natural Language Processing and Machine Translation Parallel and Distributed Algorithms Pattern Recognition and Analysis Systems and Software Engineering Nature Inspired Computing Signal and Image Processing Reconfigurable Computing Cloud, Cluster, Grid and P2P Computing Biomedical Computing Advanced Bioinformatics Green Computing Mobile Computing Nano Ubiquitous Computing Context Awareness and Personalization, Autonomic and Trusted Computing Cryptography and Applied Mathematics Security, Trust and Privacy Digital Rights Management Networked-Driven Multicourse Chips Internet Computing Agricultural Informatics and Communication Community Information Systems Computational Economics, Digital Photogrammetric Remote Sensing, GIS and GPS Disaster Management e-governance, e-Commerce, e-business, e-Learning Forest Genomics and Informatics Healthcare Informatics Information Ecology and Knowledge Management Irrigation Informatics Neuro-Informatics Open Source: Challenges and opportunities Web-Based Learning: Innovation and Challenges Soft computing Signal and Speech Processing Natural Language Processing 11. Communications Microstrip Antenna Microwave Radar and Satellite Smart Antenna MIMO Antenna Wireless Communication RFID Network and Applications 5G Communication 6G Communication 12. Algorithms and Complexity Sequential, Parallel And Distributed Algorithms And Data Structures Approximation And Randomized Algorithms Graph Algorithms And Graph Drawing On-Line And Streaming Algorithms Analysis Of Algorithms And Computational Complexity Algorithm Engineering Web Algorithms Exact And Parameterized Computation Algorithmic Game Theory Computational Biology Foundations Of Communication Networks Computational Geometry Discrete Optimization 13. Software Engineering and Knowledge Engineering Software Engineering Methodologies Agent-based software engineering Artificial intelligence approaches to software engineering Component-based software engineering Embedded and ubiquitous software engineering Aspect-based software engineering Empirical software engineering Search-Based Software engineering Automated software design and synthesis Computer-supported cooperative work Automated software specification Reverse engineering Software Engineering Techniques and Production Perspectives Requirements engineering Software analysis, design and modelling Software maintenance and evolution Software engineering tools and environments Software engineering decision support Software design patterns Software product lines Process and workflow management Reflection and metadata approaches Program understanding and system maintenance Software domain modelling and analysis Software economics Multimedia and hypermedia software engineering Software engineering case study and experience reports Enterprise software, middleware, and tools Artificial intelligent methods, models, techniques Artificial life and societies Swarm intelligence Smart Spaces Autonomic computing and agent-based systems Autonomic computing Adaptive Systems Agent architectures, ontologies, languages and protocols Multi-agent systems Agent-based learning and knowledge discovery Interface agents Agent-based auctions and marketplaces Secure mobile and multi-agent systems Mobile agents SOA and Service-Oriented Systems Service-centric software engineering Service oriented requirements engineering Service oriented architectures Middleware for service based systems Service discovery and composition Service level

Personal Knowledge Base AI Market Outlook

According to our latest research, the global Personal Knowledge Base AI market size reached USD 1.36 billion in 2024, demonstrating robust momentum driven by surging adoption across knowledge-intensive domains. The market is expected to expand at a compound annual growth rate (CAGR) of 27.2% from 2025 to 2033, reaching a projected value of USD 11.87 billion by 2033. This remarkable growth is primarily fueled by increasing digital transformation initiatives, the proliferation of AI-powered productivity tools, and the rising demand for personalized knowledge management solutions among individuals, professionals, and enterprises worldwide.

A primary growth driver for the Personal Knowledge Base AI market is the exponential rise in digital information, which has created an urgent need for advanced tools capable of organizing, retrieving, and contextualizing vast amounts of personal and professional data. As individuals and organizations grapple with information overload, AI-powered personal knowledge bases are emerging as indispensable platforms, offering intelligent categorization, semantic search, and personalized recommendations. The integration of natural language processing (NLP), machine learning, and context-aware algorithms enables these systems to deliver tailored insights, streamline workflows, and boost productivity, making them highly attractive to knowledge workers, students, and decision-makers alike.

Another significant factor propelling market growth is the rapid evolution of remote and hybrid work models. With distributed teams and professionals increasingly relying on digital platforms for collaboration, the demand for secure, scalable, and intuitive knowledge management solutions has soared. Personal Knowledge Base AI tools empower users to centralize notes, research, project documentation, and references, facilitating seamless access and sharing across devices and locations. The ability to integrate with popular productivity suites, cloud storage services, and communication tools further enhances their appeal, driving widespread adoption among enterprises seeking to optimize knowledge retention and transfer in an era of workforce mobility.

Furthermore, advancements in AI technologies have lowered the entry barrier for the development and deployment of intelligent personal knowledge management systems. The democratization of AI models, open-source frameworks, and cloud-based deployment options has enabled a new wave of innovative solutions tailored to diverse user segments, from students and academics to business professionals and creative individuals. As AI capabilities continue to mature, features such as automated summarization, intelligent tagging, and context-aware reminders are becoming standard, further differentiating Personal Knowledge Base AI platforms from traditional note-taking or document management tools. This technological progress, coupled with increasing user awareness and digital literacy, is expected to sustain the market’s upward trajectory throughout the forecast period.

From a regional perspective, North America currently dominates the Personal Knowledge Base AI market due to its advanced digital infrastructure, high concentration of tech-savvy professionals, and early adoption of AI-driven productivity solutions. However, Asia Pacific is poised for the fastest growth, supported by rapid digitalization, expanding internet penetration, and a burgeoning population of students and young professionals eager to leverage intelligent knowledge management tools. Meanwhile, Europe and other regions are witnessing steady uptake, driven by enterprise digital transformation and a growing emphasis on individual productivity enhancement. This global expansion underscores the universal relevance of AI-powered personal knowledge bases in today’s information-driven society.

Component Analysis

The Component segment of the Personal Knowledge Base AI market is bifurcated into

CompiAgent is an exploration on building on the edge, privacy first, conversational virtual beings.

Ontology first Artificial Intelligence Agent

Check the reference implementation written in Godot.

Here you can find information about the motivation behind the project: Medium article.

Eibriel https://twitter.com/EibrielBot

References: - Linguistics for the Age of AI - Ontology Development for Machine Translation: Ideology and Methodology - Mikrokosmos Ontology (Archived version)

Knowledge Base Software Market Outlook

According to our latest research, the global Knowledge Base Software market size reached USD 2.1 billion in 2024, reflecting robust adoption across diverse industries. The market is projected to grow at a CAGR of 11.3% from 2025 to 2033, reaching a forecasted value of USD 5.5 billion by 2033. This substantial growth is primarily fueled by increasing enterprise demand for streamlined information management, enhanced customer support, and the rising integration of artificial intelligence and automation in knowledge management systems.

The rapid digital transformation across industries is a significant growth driver for the Knowledge Base Software market. Organizations are increasingly leveraging these solutions to centralize and structure their vast repositories of information, enabling faster access to critical data and facilitating improved decision-making. The proliferation of remote and hybrid work models has further amplified the need for robust knowledge management, as distributed teams require seamless access to organizational knowledge regardless of their location. Additionally, the integration of AI-powered search and content recommendation functionalities is enhancing the efficiency and accuracy of knowledge retrieval, thereby increasing the attractiveness of advanced knowledge base platforms for enterprises seeking operational excellence.

The growing emphasis on exceptional customer experience is another vital factor propelling the growth of the Knowledge Base Software market. Organizations across sectors such as BFSI, healthcare, and retail are deploying knowledge base solutions to empower customer support teams with instant access to accurate information, thereby reducing resolution times and improving customer satisfaction. Furthermore, the trend of self-service portals is gaining traction, as customers increasingly prefer finding solutions independently. Knowledge base software plays a pivotal role in enabling these self-service capabilities, allowing businesses to reduce support costs while simultaneously enhancing service quality. The ongoing evolution of omnichannel customer engagement strategies also necessitates integrated knowledge management tools that can deliver consistent information across various platforms.

Another critical growth factor is the rising need for compliance, security, and regulatory adherence, especially in sectors such as healthcare, BFSI, and government. Knowledge base software helps organizations maintain up-to-date records, standard operating procedures, and best practices, ensuring compliance with evolving regulations. The automation of documentation processes minimizes human errors and enhances audit readiness. Moreover, as cyber threats become more sophisticated, knowledge base solutions are being equipped with advanced security features, such as role-based access controls and data encryption, to safeguard sensitive organizational knowledge. The convergence of these factors is fostering sustained demand and innovation within the global knowledge base software market.

Knowledge Management Software is increasingly becoming a cornerstone for organizations aiming to harness and optimize their internal knowledge assets. This type of software facilitates the systematic organization, storage, and retrieval of information, which is crucial for enhancing productivity and fostering innovation. By implementing robust knowledge management systems, companies can ensure that valuable insights and expertise are easily accessible to employees, thereby reducing redundancy and improving workflow efficiency. Furthermore, the integration of advanced features such as AI-driven analytics and machine learning capabilities within these platforms is enabling businesses to derive actionable insights from their data, ultimately driving strategic decision-making and competitive advantage.

From a regional perspective, North America leads the global knowledge base software market, driven by a mature digital infrastructure, high technology adoption rates, and the presence of major software vendors. Europe follows closely, with increasing investments in enterprise software and regulatory initiatives promoting digital transformation. The Asia Pacific region is witnessing the fastest

Knowledge base from Tinkoff(now T-Bank). You can use it for RAG systems or just fine-tune any LLM. So, data for Question-Answering. If you like it, please upvote. Have a good work with this data

Service Desk Knowledge Base Market Outlook

According to our latest research, the global Service Desk Knowledge Base market size reached USD 2.6 billion in 2024, driven by the rising demand for efficient IT support and self-service solutions across enterprises of all sizes. The market is projected to expand at a CAGR of 13.2% from 2025 to 2033, reaching a forecasted value of USD 7.8 billion by 2033. This robust growth is primarily fueled by digital transformation initiatives, the proliferation of cloud-based solutions, and the increasing emphasis on customer experience and operational efficiency, as per our comprehensive market analysis.

One of the primary growth factors for the Service Desk Knowledge Base market is the escalating adoption of digital transformation strategies among organizations worldwide. Businesses are increasingly recognizing the value of structured knowledge management systems in streamlining IT service management (ITSM) processes, reducing ticket resolution times, and enhancing employee productivity. The integration of artificial intelligence and machine learning into knowledge bases has further revolutionized the market, enabling intelligent search, contextual recommendations, and automated issue resolution. As enterprises continue to prioritize seamless customer and employee experiences, the demand for robust, scalable, and intuitive service desk knowledge base solutions is expected to witness significant acceleration, especially in sectors such as IT, BFSI, healthcare, and retail.

Another key driver propelling the growth of the Service Desk Knowledge Base market is the shift towards remote and hybrid work environments. The COVID-19 pandemic acted as a catalyst, compelling organizations to adopt flexible work models and invest in technologies that support distributed teams. Knowledge bases have become indispensable tools for facilitating self-service, onboarding, and training in remote settings, reducing the dependency on live support agents and minimizing service disruptions. Moreover, the rise of cloud computing has made knowledge base deployment more accessible and cost-effective, allowing even small and medium enterprises to leverage sophisticated knowledge management platforms without significant upfront investment. This democratization of technology is contributing to the rapid expansion of the market across various industry verticals.

Furthermore, the increasing complexity of IT environments and the growing volume of service requests are compelling organizations to seek automated and scalable knowledge management solutions. Service desk knowledge bases, equipped with advanced analytics and reporting capabilities, empower IT teams to identify recurring issues, optimize workflows, and proactively address user needs. The integration of chatbots and virtual assistants with knowledge bases is also enhancing the self-service capabilities of service desks, leading to improved user satisfaction and reduced operational costs. As regulatory compliance and data security concerns continue to rise, vendors are offering robust security features and audit trails, further boosting the adoption of knowledge base solutions in highly regulated sectors such as healthcare, BFSI, and government.

From a regional perspective, North America currently leads the Service Desk Knowledge Base market, accounting for the largest share in 2024, followed by Europe and Asia Pacific. The region’s dominance is attributed to the early adoption of advanced ITSM tools, a strong presence of leading technology vendors, and high digital maturity among enterprises. Asia Pacific, on the other hand, is poised for the fastest growth during the forecast period, driven by rapid digitalization, expanding IT infrastructure, and increasing investments in cloud-based solutions across emerging economies such as China, India, and Southeast Asia. The market in Europe is also witnessing steady growth, supported by stringent regulatory requirements and a growing focus on data-driven decision-making. Latin America and the Middle East & Africa are expected to offer lucrative opportunities as organizations in these regions accelerate their digital transformation journeys.

Component Analysis

The Service Desk Knowledge Base market by component is segmented into software and services, each playing a crucial role in the adoption and functioning of knowledge management systems. The software segment is the cornerstone of the market

Recent advances in high-throughput technologies have resulted in a tremendous increase in the amount of omics data produced in plant science. This increase, in conjunction with the heterogeneity and variability of the data, presents a major challenge to adopt an integrative research approach. We are facing an urgent need to effectively integrate and assimilate complementary datasets to understand the biological system as a whole. The Semantic Web offers technologies for the integration of heterogeneous data and their transformation into explicit knowledge thanks to ontologies. We have developed the Agronomic Linked Data (AgroLD– www.agrold.org), a knowledge-based system relying on Semantic Web technologies and exploiting standard domain ontologies, to integrate data about plant species of high interest for the plant science community e.g., rice, wheat, arabidopsis. We present some integration results of the project, which initially focused on genomics, proteomics and phenomics. AgroLD is now an RDF (Resource Description Format) knowledge base of 100M triples created by annotating and integrating more than 50 datasets coming from 10 data sources–such as Gramene.org and TropGeneDB–with 10 ontologies–such as the Gene Ontology and Plant Trait Ontology. Our evaluation results show users appreciate the multiple query modes which support different use cases. AgroLD’s objective is to offer a domain specific knowledge platform to solve complex biological and agronomical questions related to the implication of genes/proteins in, for instances, plant disease resistance or high yield traits. We expect the resolution of these questions to facilitate the formulation of new scientific hypotheses to be validated with a knowledge-oriented approach.

In silico drug prioritization may be a promising and time-saving strategy to identify potential drugs, standing as a faster and more cost-effective approach than de novo approaches. In recent years, artificial intelligence has greatly evolved the drug development process. Here, we present a novel computational framework for drug prioritization, labyrinth, designed to simulate human knowledge retrieval and inference to identify potential drug candidates for each disease. With the integration of up-to-date clinical trials, literature co-occurrences, drug–target interactions, and disease similarities, our framework achieves over 90% predictive accuracy across clinical trial phases and strong alignment with clinical practice in TCGA cohorts. We have demonstrated effectiveness across 20 different disease categories with robust ROC-AUC metrics and the balance between predictive accuracy and model interpretability. We further demonstrate its effectiveness at both the population and the individual levels. This study not only demonstrates the capacity for its drug prioritization but underscores the importance of aligning computational models with intuitive human reasoning. We have wrapped the core function into an R package named labyrinth, which is freely available on GitHub under the GPL-v2 license (https://github.com/hanjunwei-lab/labyrinth).

This dataset includes codes and dataset about intelligent searching system on resume and legal documents.