Dean, Faculty computer and information technology, Al Madianh International University, Malaysia
Speech Title: Important of Data Management in 4 Industrial Revolution (4 IR)
Speech Abstract: The concept of data management is the practice of storing, validating and processing required data to accessibility and reliability of data for its users. The data sources come across web and social services, IoT, sensing, transactions of any online organizations, machines, so on. These huge amounts of data can be found in the servers into structured, unstructured and semi-structured. Moreover, these data are stored few categories such, graph based, documents based, key value based and column based. The purpose of data management is not a goal in itself, rather than the key to innovation and knowledge discovery and to integration and reuse after the data publication process. Many organizations and governmental agencies are beginning to require data management and plans for various experiments. Beyond the collection of data and archival, it includes to ‘long-term care’ that is valuable digital assets .
Organizations gather unstructured data such internal sources (e.g., sensor data) and external sources (e.g., social media). Therefore, from the emergence of data management technologies and analytics enabled the organizations to process data in their business and innovative processes. One of the techniques is facial recognition technology that empowers to acquire intelligence about store traffic, composition of customers, and store movement patterns. These information’s are invaluable of leveraged to decisions product promotions, staffs and for placement . In fact, the traditional data management systems assuming by a user query, that they have enough knowledge of the schema, contents and meaning, and certain the query they wanted to pose, thereafter, the system tries to produce complete and correct results. To handle the sensor data in structural monitoring applications, traditional relational database management systems (RDBMS) employs, however little efforts devoted of data management for fundamental issues. For storing, managing and retrieving large scale of data, Apache H-Base, Apache Cassandra, and MongoDB noted as NoSQL (Not only SQL) database tools have designed to handle unstructured data. NoSQL database systems are significant rather than RDBMS for flexibility and scalability. For sensor network data to handling and managing, Apache Cassandra shown a better performance of scalability from massive IoT data which is NoSQL system . Apache Cassandra supports large scale of data management and processing as well. In this talk, will talk about the important of data management and the technquies that help in data mining and discover the insight from huge amount of data.
Dr.Mahmoud Ahmad Al-Khasawneh
Al-Madinah International University / Faculty of Computer and Information Technology
Speech Title: IOT Opportunities and Challenges
Speech Abstract: The Internet of Things (IoT) entails a connectivity extension into a bigger range of human environment. It allows more data comprehensions, analytics as well as competences of control of the world. In many ways, IoT has impacted the lives of man. Indeed, the possible prospects of IoT have been explored by many. As IoT has greater capacity and interconnectedness, many have begun to employ IoT as replacement of previous technologies. Accordingly, among the novel initiatives driven by IoT technologies include Society 5.0 in Japan, Smart and Connected Communities in USA, and PICASSO (ICT Policy, Research, and Innovation for a Smart Society) in EU. All these initiatives are part of the scrutiny of future concepts that are important to both the culture and the society made possible with the technologies of IOT.
Through IoT, consumers are presented with services and products that are innovative, at the time, place and in the manner that they desire. As IoT technologies improve in terms of reliability, affordability, extend of coverage, and in terms of its customization ability, the trend is expected to accelerate. Somehow, there are foundational obstacles currently facing IoT. Among these obstacles include the demand for scientific principles for the creation of IoT system design that is strong, hardy, and foreseeable, in addition to the demand for engineering principles for the construction of IoT open-systems that are scalable, verifiable, and trusted, as well as the need for human-centric principles for system engineering with the application of IOT.
Prof.Zainab Abu Bakar
Al-Madinah International University, Computer Science
Speech Title: Empowering Information Retrieval in Semantic Web
Speech Abstract: Information Retrieval was the center of stage for the library until the inception of Web 1.0 that was defined as search and passive in nature. Then the emergence of Web 2.0 that encouraged community, social interaction and user-generated content. Web 3.0 is a recent phenomenon and is known as “3D Web or Semantic Web”. The term "Semantic Web" is often used more specifically to refer to the formats and technologies that enable it. While, Web 4.0: Ultra Intelligent Electronic Agents Interaction between humans and machines.
Semantic technology encodes meanings separately from data and content files, and as well as separately from application codes. This enables machines as well as people to understand, share and reason with them at execution time. With semantic technologies, adding, changing and implementing new relationships or interconnecting programs in a different way can be just as simple as changing the external model that these programs share. Given an information need, semantic technologies can directly search, capture, aggregate, and make deduction in order to satisfy the need.
This paper present a theoretical and developmental framework of knowledge representation for ensemble semantic technology base on ontology, semantic Web, and logical model, a connectivity framework and technology of distributed communicating system formalism based on ensemble intelligent agents to share knowledge through message passing technique and a theoretical and developmental framework for knowledge discovery which include knowledge aggregation engine to combine, normalize and summarize related information from various disparate sources to serve information needs.
These theoretical and developmental frameworks empowers Web 3.0 and embrace Web 4.0. We might still well be in Web 3.0 but 4.0 is coming and it's coming fast.
A Prof.Wan Fatimah Wan Ahmad
Universiti Kebangsaan Malaysia
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