A Framework for Research Supervision

One of the main challenges that are encountered in research development is the management of research activities. Supervisors often have difficulties in managing schedules, issues and supervision of different research activities. This is compounded by students’ poor research skills. Consequently, in this paper, we propose a knowledge management framework to point out, track, and monitor various research supervision activities. The proposed framework consists of two layers, abstract and detail. The abstract layer consists of six stages which are; basement stage, review stage, data collection stage, data analysis stage, development stage, and testing and validation stage. These stages, according to our framework, are mandatory; in other words, any research must go through the stages. To complete the task of each stage, a number of steps are defined, which constitute the detail layer. A supervisor is able to pick up appropriate steps (and not all suggested steps) from the detail layer since the complexity varies from one research to another. We discuss the results of our findings in conceiving the framework. Keywords: research development, development stage, research activities, supervision managemen

An Investigation on Measuring Accuracy of Explicit Knowledge Sources in Universities

At present, e-libraries contain huge volumes of articles that may be irrelevant or inaccurate to academics’ research areas. The academics may spend extensive time and efforts to retrieve knowledge contents from these articles. Thus, universities need to manage their articles’ libraries effectively to deliver the most suitable explicit contents based on academics’ research areas. Consequently, in this paper, we identify potential factors that could contribute to candidate relevant and accurate articles that meet employees need. These factors work on measuring the accuracy of articles to identify the most relevant articles from the huge resources of online articles. Therefore, the search time and efforts could be reduced through classifying articles based on the contents’ knowledge using practical measurement factors. To address the objectives of this research, quantitative and qualitative studies are made to collect data using questionnaire survey and interview of experts in knowledge management. The results of the data analysis are used to identify the relevant factors and to compute the accuracy of articles based on these factors. Keywords: knowledge management, explicit knowledge, knowledge measurement

A Solution Generator Algorithm for Decision Making based Automated Negotiation in the Construction Domain

In this paper, we present our work-in-progress of a proposed framework for automated negotiation in the construction domain. The proposed framework enables software agents to conduct negotiations and autonomously make value-based decisions. The framework consists of three main components which are, solution generator algorithm, negotiation algorithm, and conflict resolution algorithm. This paper extends the discussion on the solution generator algorithm that enables software agents to generate solutions and rank them from 1st to nth solution for the negotiation stage of the operation. The solution generator algorithm consists of three steps which are, review solutions, rank solutions, and form ranked solutions. For validation purpose, we present a scenario that utilizes the proposed algorithm to rank solutions. The validation shows that the algorithm is promising, however, it also highlights the conflict between different parties that needs further negotiation action

An Automated Negotiation-based Framework via Multi-Agent System for the Construction Domain

In this paper, we propose an automated multi-agent negotiation framework for decision making in the construction domain. It enables software agents to conduct negotiations and autonomously make decisions. The proposed framework consists of two types of components, internal and external. Internal components are integrated into the agent architecture while the external components are blended within the environment to facilitate the negotiation process. The internal components are negotiation algorithm, negotiation style, negotiation protocol, and solution generators. The external components are the negotiation base and the conflict resolution algorithm. We also discuss the decision making process flow in such system. There are three main processes in decision making for specific projects, which are propose solutions, negotiate solutions and handling conflict outcomes (conflict resolution). We finally present the proposed architecture that enables software agents to conduct automated negotiation in the construction domain

Research Supervision Management Via A Multi-Agent Framework

In this paper, we propose an agent-based framework to enhance, control and manage the research supervision process. The proposed framework consists of three phases which are Research Development Activities, Performance and Completion Measurement, and Tracking Activities. The Research Development Activities phase proposes a number of activities to develop a research. Performance and Completion Measurement phase works on measuring a student performance and expected completion date. The Tracking Activities phase presents the proposed activities to track and trigger a student’s tasks. Four actors constitute the proposed framework which are, a supervisor, a student, a system administrator and a software agent. Each actor has a role and is authorized to perform specific functions. We discuss the components of the framework as possible implementation for a general application of research supervision management.</p

A Bayesian Hau-Kashyap Approach for Hepatitis Disease Detection

World Health Organization reported that viral hepatitis affects 400 million people globally. Every year, 610 million people are newly infected. In this research, we integrate a Bayesian theory and Hau-Kashyap approach for detecting hepatitis and displaying the result of calculation process. The basic idea of the Bayesian theory is using the known prior probability and conditional probability density parameter based on the Bayes theorem to calculate the corresponding posterior probability and then obtain the posterior probability to infer and make decisions. Bayesian methods combine present knowledge, prior probabilities, with additional knowledge derived from new data, the likelihood function. Hau-Kashyap presented an alternative Dempster-Shafer combination rule, and the alternative combination rule is that with the use of this alternative rule, the intersection conflict is put into the union. In this chapter, we get basic possibility assignment value from Bayesian probability. The result reveals that a Bayesian Hau-Kashyap approach has successfully identified the existence of hepatitis

Resolving conflicts between personal and normative goals in normative agent systems

In this paper, we present a framework for resolving conflicts between personal and normative goals in normative agent systems. The conflicts occur in the decision making process of time-constrained tasks of those goals. The agents observe the environment, generate the tasks based on their obligation to an authority, their desires, and intentions. They select and execute the tasks from a set of pre-compiled tasks based on their beliefs of the reward and penalty associated with the selected tasks. To resolve the conflicts within the constraint of the tasks’ duration, we supplement the agents’ normative capacity with two essential functions: Sacrifice and Diligence. The Sacrifice function enables an agent to reason and discard any tasks that have lower priorities to make way for accomplishment of the normative goal. The Diligence function enables an agent to increase its effort in accomplishing the normative goal in time-constrained situations. We simulate these situations and present the results

Multi-perspective evaluation of integrated active cooling systems using fuzzy decision making model

As global median temperatures continue to rise, the demand for active cooling systems (ACs) is increasing. These systems are particularly prevalent in developed countries for maintaining comfort during hot weather. Various ACs technologies are available, and assessing their performance in multi-perspective settings is necessary to determine the best option for intended usage. This requires an evaluation platform for assessment. This paper presents a novel multi-criteria decision-making (MCDM) model based on a new integrated 2-tuple linguistic Pythagorean fuzzy-weighted zero-inconsistency (2 TLP-FWZIC) and modified 2-tuple linguistic Pythagorean fuzzy multi-attributive border approximation area comparison (2TLPF-MABAC). The former is used to determine the importance of assessment criteria, while the latter is employed for selecting the optimal ACs using the obtained weights. The first-level weighting results reveal that performance criteria were predominantly favored for assessment, with ‘energy performance’ acquiring the most significant weight (0.2487) among all performance criteria. In terms of ACs selection results, among the 20 tested and assessed systems, the ‘geothermal borehole electricity-based ACs’ obtained the highest score value (0.1296), while the ‘window packaged electricity-based ACs’ had the lowest score (-0.0515). The robustness of the results was confirmed through sensitivity analysis

Building norms-adaptable agents from Potential Norms Detection Technique (PNDT)

This paper presents a contribution to research on norms detection by proposing a technique, which is called the Potential Norms Detection Technique (PNDT). The literature proposes that an agent changes or updates its norms based on the variables of the local environment and the amount of thinking about its behaviour. Consequently, any changes on these two variables cause the agent to use the PNDT to update the norms in complying with the domain’s normative protocol. This technique enables an agent to update its norms even in the absence of sanctions from a third-party enforcement authority as found in some work, which entail sanctions by a third-party to detect and identify the norms. The PNDT consists of five components: agent’s belief base; observation process; Potential Norms Mining Algorithm (PNMA) to detect the potential norms and identify the normative protocol; verification process, which verifies the detected potential norms; and updating process, which updates the agent’s belief base with new normative protocol. The authors then demonstrate the operation of the algorithm by testing it on a typical scenario and analyse the results on several issues