Leveraging textual properties of bug reports to localize relevant source files

Bug reports are an essential part of a software project's life cycle since resolving them improves the project's quality. When a new bug report is received, developers usually need to reproduce the bug and perform code review to locate the bug and assign it to be fixed. However, the huge number of bug reports and the increasing size of software projects make this process tedious and time-consuming. To solve this issue, bug localization techniques try to rank all the source files of a project with respect to how likely they are to contain a bug. This process reduces the search space of source files and helps developers to find relevant source files quicker. In this paper, we propose a multi-component bug localization approach that leverages different textual properties of bug reports and source files as well as the relations between previously fixed bug reports and a newly received one. Our approach uses information retrieval, textual matching, stack trace analysis, and multi-label classification to improve the performance of bug localization. We evaluate the performance of the proposed approach on three open source software projects (i.e., AspectJ, SWT, and ZXing) and the results show that it can rank appropriate source files for more than 52% of bugs by recommending only one source file and 78% by recommending ten files. It also improves the MRR and MAP values compared to several existing state-of-the-art bug localization approaches.     

The Effects of Onion Consumption on Prevention of Nonalcoholic Fatty Liver Disease

It is well known that dietary intakes play a pivotal role in pathogenesis of nonalcoholic fatty liver disease (NAFLD)/nonalcoholic steatohepatitis (NASH); however, the role of each component of diet has not yet been elucidated. Our objective was to evaluate the effects of onion consumption on prevention of NAFLD/NASH development. Sprague–Dawley rats were fed either high-fat, high sugar diet (model group), or high-fat, high sugar diet plus 7% onion powder (model + onion), or chow diet ad libitum for 7 weeks. Serum levels of fasting glucose, triglyceride, cholesterol, liver enzymes, insulin, and hepatic tumor necrosis factor-alpha (TNF-α) gene expression were determined. Hepatic histology was examined by H&E stain. Model + onion group had significantly lower hepatic steatosis, ballooning, lobular inflammation, and portal inflammation (p < 0.001), lower hepatic TNF-α gene expression (p < 0.001), lower plasma levels of ALT (p = 0.026), AST (p = 0.041), insulin (p < 0.001), TG (p = 0.041), and glucose (p = 0.009) compared with model group; however, weight gain, food intake, plasma total cholesterol and LDL levels were not significantly different between these two groups. Our data indicate that regular consumption of onion can prevent NAFLD even in the presence of the other risk factors such as obesity, hypercholesterolemia, and high energy, fat, and sugar intakes.     

Challenges Faced by Subject Librarians in an Academic Library and Initiatives Toward Overcoming Them: UPM Library Experience

ABSTRACT

Subject Librarians play an important role in an academic library, a role which it is crucial to study. There have been many published studies that have highlighted the lack of evidence on the competencies of Subject Librarians. This paper discusses the challenges faced by the Subject Librarians of the Universiti Putra Malaysia Library. The aim was to gather information from published documents regarding the experiences and practices carried out in efforts to increase the competencies of Subject Librarians. The outcomes from this conceptual paper serve as an important instructional tool for the training and development of Subject Librarians. The results might also provide guidance for the implementation of a similar program or relevant problem-solving plans for other libraries in the region.     

An empirical study of using sequential behavior pattern mining approach to predict learning styles

The learning style of a learner is an important parameter in his learning process. Therefore, learning styles should be considered in the design, development, and implementation of e-learning environments to increase learners’ performance. Thus, it is important to be able to automatically determine learning styles of learners in an e-learning environment. In this paper, we propose a sequential pattern mining approach to extract frequent sequential behavior patterns, which can separate learners with different learning styles. In this research, in order to recognize learners’ learning styles, system uses the Myers-Briggs Type Indicator’s (MBTI). The approach has been implemented and tested in an e-learning environment and the results show that learning styles of learners can be predicted with high accuracy. We show that learners with similar learning styles have similar sequential behavior patterns in interaction with an e-learning environment. A lot of frequent sequential behavior patterns were extracted which some of them have a meaningful relation with MBTI dimensions.     

Probabilistic analysis of linear elastic cracked structures

This paper presents a probabilistic methodology for linear fracture mechanics analysis of cracked structures. The main focus is on probabilistic aspect related to the nature of crack in material. The methodology involves finite element analysis; sta- tistical models for uncertainty in material properties, crack size, fracture toughness and loads; and standard reliability methods for evaluating probabilistic characteristics of linear elastic fracture parameter. The uncertainty in the crack size can have a significant effect on the probability of failure, particularly when the crack size has a large coefficient of variation. Numerical example is presented to show that probabilistic methodology based on Monte Carlo simulation provides accurate estimates of failure prob- ability for use in linear elastic fracture mechanics.     

Investigating the potential of using acoustic frequency on the degradation of linear alkylbenzen sulfonates from aqueous solution

The effectiveness of using acoustical (sonochemical) reactor for degradation of linear alkylbenzen sulfonate (LAS) from aqueous solution was investigated. LASs are anionic surfactants,found in relatively high amounts in domestic and industrial wastewaters. In this study,experiments on LAS solution were performed using methylene blue active substances (MBAS) method. The effectiveness of acoustical processor reactor for LAS degradation is evaluated with emphasis on the effect of treatment time and initial LAS concentration. Experiments were performed at initial concentrations of 0.2,0.5,0.8 and 1.0 mg/L,acoustic fre-quency of 130 kHz,applied power of 500 W and temperature of 18 °C～20 °C. At the conditions involved,LAS degradation was found to increase with increasing sonochemical time. In addition,as the concentration increased,the LAS degradation rate de-creased in the acoustical processor reactor.     

非政府组织在天文学科普方面的作用

古代伊朗科学家曾对科学,特别是天文学做出过重大贡献。当代的伊朗科学家继承了这一传统,并致力于向公众传播科学。21世纪初,由一批科学家、热心科学传播的社会人士和私营企业组成的非政府组织积极筹建马什哈德天文馆、科学中心等科普场馆。本文通过这一案例,讨论了非政府组织在科普场馆建设和科学传播中的作用、问题和可行性,并介绍了马什哈德天文学会为此采取的相应对策。