Suggested topics in JAIKE include, but are not limited to, the following areas:

  • Artificial Intelligence (AI) : prototype applications; performance evaluation large-scale or domain-specific knowledge bases or ontologies; development of domain or task focused tools, techniques, or methods; evaluations of AI tools, techniques or methods for domain suitability; system architectures that work; scalability of techniques; integration of AI with other technologies; development methodologies; validation and verification; lessons learned; social and other technology transition issues.
  • Knowledge Mining and Discovery (KMD) – include definition of intelligent objects, knowledge elements, rules definition, rules management, Ontology and Semantic web, capturing intellectual property, security, etc.
  • Knowledge Acquisition (KA) – include knowledge capture, knowledge-based modeling, social network analysis & modeling, knowledge processing, human-computer interactions, learning and adaptation, and knowledge visualization,
  • Knowledge Intelligence (KI): Innovative Computing, Intelligent Communication and Smart Electrical Systems, Recent Trends
  • Knowledge-based Engineering (KBE) – include knowledge and data engineering, methods of capturing rules & heuristics, concepts of knowledge advisor, knowledge expert and product knowledge templates, process knowledge templates, business knowledge templates, technological objects and tools in Product-life cycle management.
  • Knowledge-Based Systems (KBS) – include software architecture for developing general-purpose tools and progressive systems, SmartPart concepts and product configurators. Use of demand-driven constructs in building dynamical systems.
  • Knowledge Management (KM) – include knowledge sharing and warehousing, knowledge-base processing, intelligent information retrieval, knowledge distribution, methods to exchange knowledge across intelligent objects. Use of computational techniques in KM: such as soft computing (including neural nets, fuzzy logic, probabilistic reasoning, evolutionary computing, hybrid computing, agent architectures and systems, genetic algorithms).
  • Internet-of-Things (IOTs) –Next generation of the Internet Protocols (IP). Global system of Internet Protocol (IP), Connected computer networks, sensors, actuators, machines and devices, Sensors and actuators embedded in physical objects – from roadways to pacemakers, Wireless networks, networked interconnection of everyday objects, Ubiquitous intelligence. IoT interaction via embedded systems, distributed network of devices communicating with human beings as well as other devices.
  • “IoT refers to the networked interconnection of everyday objects, which are often equipped with ubiquitous intelligence. IoT will increase the ubiquity of the Internet by integrating every object for interaction via embedded systems, which lead to a highly distributed network of devices communicating with human beings as well as other devices” (Xia et al., 2012). At the core of the Internet of Things lays the smart product—equipped with RFID technology
  • Smart Products: At the core of the Internet of Things lays the smart product – equipped with RFID technology. Three typical elements of smart products. Physical components, smart components and connectivity components. The physical component is the product’s mechanical and electrical parts. The smart components are the product’s software, sensors, data storage and other similar features. The last component is the connectivity components. It consists of the protocols or ports that enable the connection between products or human beings.
  • Generative AI: This can able to create something entirely new, including text, images, audio, synthetic data and many more. Deep learning models, multi-modal AI technologies, real-time perception and response to content, AI comprises machine learning, natural language processing (NLP), image processing, and computer vision
  • Knowledge-driven Automation (KDA) – include decision-based design, decision support systems, knowledge-based optimization, sales configurations, Expert Systems: Neural networks-based applications, biomedical systems, geographical systems, enterprise software systems, and emerging applications (such as Internet technologies, search engines, and digital libraries)
  • Knowledge Architecture & IOTs Platforms; high performance computing systems, distributed intelligent systems, embedded systems, mobile systems, real-time systems, techniques to provide interoperability and knowledge re-usability across enterprise applications,
  • AIKE Application: We solicit submissions of original research, and AI/KBE/KBS/KM/KDA/IOTs application papers that address and utilize those topics and themes.

Accepted papers are grouped for publication so that individual issues focus on a small number of theme areas. In addition to archival papers, the journal also conducts reviews in a timely fashion and informs authors of decisions with a target turnaround time of 3-6 months.