Intelligent Tutoring System sebagai Upaya Inovatif dalam Pembelajaran untuk Pembelajaran Berbantuan Komputer

Perkembangan teknologi informasi dan komunikasi yang pesat juga telah merambah bidang pendidikan dan pengajaran. Penggunaan pembelajaran berbasis komputer dalam pembelajaran telah diteliti dan memberikan dampak positif dalam pembelajaran. Salah satu pembelaajran berbasis komputer yang saat ini masih terus dikembangkan adalah Intelligent Tutoring System (ITS) yang dikembangkan untuk mengatasi kelemahan pembelajaran berbasis komputer sebelumnya yang belum memperhatikan keberagaman siswa. ITS merupakan sebuah aplikasi komputer yang dibuat untuk meniru mimik manusia dalam memberikan materi pengajaran. ITS menggunakan pendekatan one-to-one. ITS merupakan sistem yang cerdas karena memiliki komponen kecerdasan buatan

Intelligent Tutoring System Sebagai Upaya Inovatif dalam Pembelajaran untuk Pembelajaran Berbantuan Komputer

Perkembangan teknologi informasi dan komunikasi yang pesat juga telah merambah bidang pendidikan dan pengajaran. Penggunaan pembelajaran berbasis komputer dalam pembelajaran telah diteliti dan memberikan dampak positif dalam pembelajaran. Salah satu pembelaajran berbasis komputer yang saat ini masih  terus dikembangkan adalah  Intelligent Tutoring System (ITS) yang dikembangkan untuk mengatasi kelemahan pembelajaranberbasis komputer sebelumnya yang belum memperhatikan keberagaman siswa. ITS merupakan sebuah aplikasi komputer yang dibuat untuk meniru mimik manusia dalam memberikan materi pengajaran. ITS menggunakan pendekatan one-to-one.  ITS merupakan sistem yang cerdas karena memiliki komponen kecerdasan buatan

Developing a system for advanced monitoring and intelligent drug administration in critical care units using ontologies

Selected paper of the 16th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems, 2012 September 10-12, San Sebastian, Spain[Abstract] When a patient enters an intensive care unit (ICU), either after surgery or due to a serious clinical condition, his vital signs are continually changing, forcing the medical experts to make rapid and complex decisions, which frequently imply modifications on the dosage of drugs being administered. Life of patients at critical units depends largely on the wisdom of such decisions. However, the human factor is sometimes a source of mistakes that lead to incorrect or inaccurate actions. This work presents an expert system based on a domain ontology that acquires the vital parameters from the patient monitor, analyzes them and provides the expert with a recommendation regarding the treatment that should be administered. If the expert agrees, the system modifies the drug infusion rates being supplied at the infusion pumps in order to improve the patient's physiological status. The system is being developed at the IMEDIR Center (A Coruña, Spain) and it is being tested at the cardiac intensive care unit (CICU) of the Meixoeiro Hospital (Vigo, Spain), which is a specific type of ICU exclusively aimed to treat patients who have underwent heart surgery or that are affected by a serious coronary disorder.Instituto de Salud Carlos III; FIS-PI10/02180Programa Iberoamericano de Ciencia y Tecnología para el Desarrollo; ref. 209RT0366Galicia. Consellería de Cultura, Educación e Ordenación Universitaria; CN2012/217Galicia. Consellería de Cultura, Educación e Ordenación Universitaria; CN2011/034Galcia. Consellería de Cultura, Educación e Ordenación Universitaria; CN2012/21

Real-time retrieval for case-based reasoning in interactive multiagent-based simulations

The aim of this paper is to present the principles and results about case-based reasoning adapted to real- time interactive simulations, more precisely concerning retrieval mechanisms. The article begins by introducing the constraints involved in interactive multiagent-based simulations. The second section pre- sents a framework stemming from case-based reasoning by autonomous agents. Each agent uses a case base of local situations and, from this base, it can choose an action in order to interact with other auton- omous agents or users' avatars. We illustrate this framework with an example dedicated to the study of dynamic situations in football. We then go on to address the difficulties of conducting such simulations in real-time and propose a model for case and for case base. Using generic agents and adequate case base structure associated with a dedicated recall algorithm, we improve retrieval performance under time pressure compared to classic CBR techniques. We present some results relating to the performance of this solution. The article concludes by outlining future development of our project

RACER : Rule-Associated CasE-based Reasoning for supporting general practitioners in prescription making

Author name used in this manuscript: W.M. WangAuthor name used in this manuscript: S.K. KwokAuthor name used in this manuscript: Albert H.C. Tsang2010-2011 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Hybrid reasoning technique for improving context-aware applications

With the rapid adoption of GPS enabled smart phones and the fact that users are almost permanently connected to the Internet, an evolution is observed toward applications and services that adapt themselves using the user's context, a.o. taking into account location information. To facilitate the development of such new intelligent applications, new enabling platforms are needed to collect, distribute, and exchange context information. An important aspect of such platforms is the derivation of new, high-level knowledge by combining different types of context information using reasoning techniques. In this paper, we present a new approach to derive context information by combining case-based and rule-based reasoning. Two use cases are detailed where both reasoners are used to derive extra useful information. For the desk sharing office use case, the combination of rule-based and case-based reasoning allows to automatically learn typical trajectories of a user and improve localization on such trajects with 42%. In both use cases, the hybrid approach is shown to provide a significant improvement

Improving the Relevance of Cyber Incident Notification for Mission Assurance

Military organizations have embedded Information and Communication Technology (ICT) into their core mission processes as a means to increase operational efficiency, improve decision making quality, and shorten the kill chain. This dependence can place the mission at risk when the loss, corruption, or degradation of the confidentiality, integrity, and/or availability of a critical information resource occurs. Since the accuracy, conciseness, and timeliness of the information used in decision making processes dramatically impacts the quality of command decisions, and hence, the operational mission outcome; the recognition, quantification, and documentation of critical mission-information resource dependencies is essential for the organization to gain a true appreciation of its operational risk. This research identifies existing decision support systems and evaluates their capabilities as a means for capturing, maintaining and communicating mission-to-information resource dependency information in a timely and relevant manner to assure mission operations. This thesis answers the following research question: Which decision support technology is the best candidate for use in a cyber incident notification system to overcome limitations identified in the existing United States Air Force cyber incident notification process

Semantic web system for differential diagnosis recommendations

There is a growing realization that healthcare is a knowledge-intensive field. The ability to capture and leverage semantics via inference or query processing is crucial for supporting the various required processes in both primary (e.g. disease diagnosis) and long term care (e.g. predictive and preventive diagnosis). Given the wide canvas and the relatively frequent knowledge changes that occur in this area, we need to take advantage of the new trends in Semantic Web technologies. In particular, the power of ontologies allows us to share medical research and provide suitable support to physician's practices. There is also a need to integrate these technologies within the currently used healthcare practices. In particular the use of semantic web technologies is highly demanded within the clinicians' differential diagnosis process and the clinical pathways disease management procedures as well as to aid the predictive/preventative measures used by healthcare professionals