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Integrated knowledge management model and system for construction projects

In the past there has been no structured approach to learning from construction projects once they are completed. Now, however, the construction industry is adapting concepts of tacit and explicit knowledge management to improve the situation. Top managers generally assume that professionals in enterprises already possess tacit knowledge and experience for specific types of projects. Such knowledge is extremely important to organisations because, once a project is completed, professionals tend to forget it and start something new. Therefore, knowledge multifold utilisation is a key factor in productively executing a construction project. This paper discusses the benefits of knowledge management to construction industry organisations and projects and emphasises the significance of tacit knowledge. The main purpose of this paper is to present the integrated knowledge management model for the construction industry as well as system architecture and system of the Knowledge Based Decision Support System for Construction Projects Management (KDSS-CPM) which the authors of this paper have developed. Different knowledge management models that are presented in scientific literature are discussed and compared, and the proposed new, KDSS-CPM model, as developed by this papers authors, is introduced.

Biometric and Intelligent Self-Assessment of Student Progress system

All distance learning participants (students, professors, instructors, mentors, tutors and the rest) would like to know how well the students have assimilated the study materials being taught. The analysis and assessment of the knowledge students have acquired over a semester are an integral part of the independent studies process at the most advanced universities worldwide. A formal test or exam during the semester would cause needless stress for students. To resolve this problem, the authors of this article have developed a Biometric and Intelligent Self-Assessment of Student Progress (BISASP) System. The obtained research results are comparable with the results from other similar studies. This article ends with two case studies to demonstrate practical operation of the BISASP System. The first case study analyses the interdependencies between microtremors, stress and student marks. The second case study compares the marks assigned to students during the e-self-assessment, prior to the e-test and during the e-test. The dependence, determined in the second case study, between the student marks scored for the real examination and the marks based on their self-evaluation is statistically significant (the significance >0.99%). The original contribution of this article, compared to the research results published earlier, is as follows: the BISASP System developed by the authors is superior to the traditional self-assessment systems due to the use of voice stress analysis and a special algorithm, which permits a more detailed analysis of the knowledge attained by a student.

Web-based Biometric Computer Mouse Advisory System to Analyze a User's Emotions and Work Productivity

This chapter describes the analysis of emotional state and work productivity using a Web-based Biometric Computer Mouse Advisory System to Analyze a User’s Emotions and Work Productivity (Advisory system hereafter) developed by author in conjunction with colleagues. The Advisory system determines the level of emotional state and work productivity integrally by employing three main biometric techniques (physiological, psychological and behavioral). By using these three biometric techniques, the Advisory system can analyze a person’s eleven states of being (stress, work productivity, mood, interest in work) and seven emotions (self-control, happiness, anger, fear, sadness, surprise and anxiety) during a realistic timeframe. Furthermore, to raise the reliability of the Advisory system even more, it also integrated the data supplied by the Biometric Finger (blood pressure and pulse rates). Worldwide research includes various scientists who conducted in-depth studies on the different and very important areas of biometric mouse systems. However, biometric mouse systems cannot generate recommendations. The Advisory system determines a user’s physiological, psychological and behavioral/movement parameters based on that user’s real-time needs and existing situation. It then generates thousands of alternative stress management recommendations based on the compiled Maslow’s Pyramid Tables and selects out the most rational of these for the user’s specific situation. The information compiled for Maslow’s Pyramid Tables consists of a collection of respondent surveys and analyses of the best global practices. Maslow’s Pyramid Tables were developed for an employee working with a computer in a typical organization. The Advisory system provides a user with a real-time assessment of his/her own productivity and emotional state. This chapter presents the Advisory system, a case study and a scenario used to test and validate the developed Advisory system and its composite parts to demonstrate its validity, efficiency and usefulness.

Recommender System to Analyze Student's Academic Performance

A sufficient amount of studies worldwide prove an interrelation linking student learning productivity and interest in learning to physiological parameters. An interest in learning affects learning productivity, while physiological parameters demonstrate such changes. Since the research by the authors of the present article confirmed these interdependencies, a Recommender System to Analyze Students Academic Performance (Recommender System hereafter) has been developed. The Recommender System determines the level of learning productivity integrally by employing three main techniques (physiological, psychological and behavioral). This Recommender System, developed by these authors, uses motivational, educational persistence and social learning theories and the database of best global practices based on above theories to come up with recommendations for students on how to improve their learning efficiency. The Recommender System can pick learning materials taking into account a students learning productivity and the degree to which learning is interesting. Worldwide research includes various scientists who conducted in-depth studies on the different and very important areas of physiological measurements and intelligent systems. We did not manage to find any physiological measurements or any intelligent or integrated system that would take physiological parameters of students, analyze their learning efficiency and, in turn, provide recommendations.

Student progress assessment with the help of an intelligent pupil analysis system

Students and lecturers would like to know how well students have learned the study materials being taught. A formal test or exam would cause needless stress for students. To resolve this problem, the authors of this article have developed an Intelligent Pupil Analysis (IPA) System. A sufficient amount of studies worldwide prove an interrelation between pupil size and a persons cognitive load. The obtained research results are comparable with the results from other similar studies. The original contribution of this article, compared to the research results published earlier, is as follows: the IPA System developed by the authors is superior to the traditional pupil analysis research due to the integration of pupil analysis with subsystems of decision support, recommender and intelligent tutoring systems and innovative Models of the Model-base, which permit a more detailed analysis of the knowledge attained by a student. This article ends with a case study to demonstrate the practical operation of the IPA System.

intelligent library and tutoring system for brita in the PuBs project

As digital libraries become more popular, information and knowledge overload has become a pressing yet required literature searching problem. Problems with searching in digital libraries will become more complex as the amount of information/knowledge increases. Traditional digital libraries often index words and documents while learners think in terms of topics and subjects. As a result, learners cannot determine how well a particular topic and/or subject is covered, or what types of search methods will provide the required information and knowledge without problems. in order to increase the efficiency and quality of the Brita in PuBs projects activities, an intelligent Library and Tutoring System for the Brita in PuBs project (iLTS-BP) was developed. iLTS-BP has the ability to personalize, maximize reuse, index, analyse and integrate valuable information and knowledge from a wide selection of existing sources. Also, the authors have integrated iLTS-BP with a Voice Stress Analyser Subsystem. iLTS-BP is briefly analysed in this paper.

Biometric Mouse Intelligent System for Student's Emotional and Examination Process Analysis

This paper describes the Web-based Biometric Mouse Intelligent System for Student’s Emotional and Examination Process Analysis (BMIS). BMIS is an online system and allows for more physiological, psychological and behavioural data to be generated from a larger pool of students for further analysis and research. Data is accumulated in individual student modules based on the student’s mouse movements, palm state and e-self-reports. The system extracts physiological and motor-behavioural parameters from mouse actions and hand characteristics, and the user fills in the psychological (e-self-reports) data, which can be used to analyse correlations with user’semotional state and labour productivity. Main features of the BMIS System are discussed, and the final recommendations for future research and improvement are included.

Biometric and Intelligent Student Progress Assessment System

A number of methodologies (Big Five Factors and Five Factor Model, intelligence quotient tests, self-assessment) and strategies for web-based formative assessment are used in an effort to predict a student’s academic motivation, achievements and performance. These methodologies, biometric voice analysis technologies and 13 years of authors’ experience in distance learning were used in development of the Biometric and Intelligent Student Progress Assessment System for psychological assessment of student progress. Also the BISPA system was developed in consideration of worldwide research results involving the interrelation between a person’s knowledge, self-assessment and voice stress along with instances of available decision support, recommender and intelligent tutoring systems.

Voice Stress Analyser System for E-testing

Three e-learning Master degree studies were introduced at Vilnius Gediminas Technical University in 1999. In order to increase the efficiency and quality of e-learning studies, Voice Stress Analyser Intelligent System for e-Testing (VSA-IST VSA-IST) was also developed. The aim of this paper is to report on the contribution of new integrated technologies (Voice Stress analysis and decision support systems) to e-Testing Systems. The article briefly describes the use of these integrated newest technologies in e-Testing. The authors of the article have developed a voice stress database, which contains students’ answers that are given during an Testing, and a specific algorithm, which is the core of the VSA-IST and which can evaluate a student’s knowledge by giving a precise mark after a psychological test, which is performed prior to the Testing. In order to demonstrate the validity, efficiency and usefulness of the developed VSA-IST, the article also presents a case study.