Utilization Of Java Reflection In Detecting Object Concept Similarities

This project is about developing a Java reflection application. It utilizes the reflection features in the system package java.lang.reflect of Sun Microsystems’ JDK version 1.2 and above. Reflection, also named as Introspection, has the ability to “look inside” a class or an object (Lemay, 1996). It uses to explore the content of the class tiles. With the help of the analyzer engine, the developed application is capable to produce similarity object’s information between the inputs without referring to the source code. The Object-Oriented Methodology, specifically the Object Modeling Technique, is used to develop this Reflection Application. There are four stages involving analysis, system design, object design, and implementation that are followed in this methodology. The input is the Java object files, and the output contains of similarity information of those object files. The object’s information is divided into five categories including Modifier, Interface, Field, Method, and Constructor. The system address the similar information for each category between two object files to the user, which including the similar used and declared category. The similar items’ frequency will also be an element of the system’s detail output. As a conclusion, this application is an alternative tool to compare a group of object files in fast mode with readable result in application’s output. The example of the application usage is as a contributing tool to help lecturers to evaluate student assignments with an ideal model answer with constant evaluating criteria requirements. It is also suitable to be used in determining student plagiarism

Enhanced Micro Genetic Algorithm-Based Models For Multi-Objective Optimization

Multi-objective Optimization Problems (MOPs) entail multiple conflicting objectives to be satisfied simultaneously. As such, a set of alternative solutions that is able to satisfy all objectives with respect to the Pareto optimality principle is desired. Besides that, the quality of good MOP solutions needs to strike a balance between convergence and diversity against the true Pareto front (i.e. distribution of the ideal Pareto optimal solutions). This research is concerned with how evolutionary algorithms can be employed to undertake MOPs with good convergence and diversity properties of the solutions with respect to the true Pareto front. Masalah pengoptimuman berbilang objektif (Multi-objective Optimization Problem-MOP) melibatkan berbilang objektif yang perlu dipenuhi serentak. Sekumpulan penyelesaian optimuman alternatif diperlukan untuk memenuhi kesemua objektif yang menunju ke arah barisan Pareto

Web-Based Career Path Model for Human Resource Management

Career path modeling and management are essential for building appropriate business strategies to attract and maintain valuable human assets in an organization. The increase of data volume due to globalized employment has increased the challenge to utilize scattered and abundant data which are collected from time to time. In order to ensure efficient top to bottom communication in an organization, this paper proposes a web-based software tool for career path modeling.  It aims to assist employees from different departments to seek advice in terms of their career advancement opportunities, and support managerial decision from the human resource professionals. The proposed model is developed with the consideration of several aspects, i.e., change of job position, department, gender, attended training courses, available mentor, as well as professional and academic qualifications. The concept of cloud computing is adopted to ensure the accessibility of the model from different web-browsers so that employees have the flexibility to obtain career advancement information anytime and anywhere

Application of an evolutionary algorithm-based ensemble model to job-shop scheduling

In this paper, a novel evolutionary algorithm is applied to tackle job-shop scheduling tasks in manufacturing environments. Specifically, a modified micro genetic algorithm (MmGA) is used as the building block to formulate an ensemble model to undertake multi-objective optimisation problems in job-shop scheduling. The MmGA ensemble is able to approximate the optimal solution under the Pareto optimality principle. To evaluate the effectiveness of the MmGA ensemble, a case study based on real requirements is conducted. The results positively indicate the effectiveness of the MmGA ensemble in undertaking job-shop scheduling problems

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe