Automatic Code Homework Grading Based on Concept Extraction

E-learning is taking more roles in the current methods of education. The automatic grading and assessment play a major role in both e-learning and traditional education as a method to reduce educational expenses and relief instructors from some of the lengthy tasks such as grading. In this paper, automatic grading for software code assignments or homework is described. A tool is developed to automatically grade students\u27 code assignments. Concepts or code from Students\u27 answers are first parsed. Key abstractions and keywords are extracted from students\u27 assignments and compared with typical or expected answers. Weights are given to code keywords by the instructor based on their value and importance in the overall answer. Relating this grading with code plagiarism, similarities are also measured between students\u27 assignments and an Euclidean distance method is developed and calculated between each assignment with all other assignments. Results showed that automatic grading for code assignments can be automated due to the nature of expected answers where grader can set and expect a fixed number of possible keywords in each answer. Such formality may not exist for several other types of essay questions

Clustering and Classification of Email Contents

Information users depend heavily on emails\u27 system as one of the major sources of communication. Its importance and usage are continuously growing despite the evolution of mobile applications, social networks, etc. Emails are used on both the personal and professional levels. They can be considered as official documents in communication among users. Emails\u27 data mining and analysis can be conducted for several purposes such as: Spam detection and classification, subject classification, etc. In this paper, a large set of personal emails is used for the purpose of folder and subject classifications. Algorithms are developed to perform clustering and classification for this large text collection. Classification based on NGram is shown to be the best for such large text collection especially as text is Bi-language (i.e. with English and Arabic content)

Issues Related to the Detection of Source Code Plagiarism in Students Assignments

Detecting similarity or plagiarism in the academic research publications, source code, etc. has been a long time complex and time consuming task. Several algorithms, tools and websites exist that try to find plagiarism or possible plagiarism in those human creative products. In this paper we used source code plagiarism detection tools to assess the level of plagiarism in source codes. We also investigated issues related to accuracy and challenges in detecting possible plagiarism in students\u27 assignments. In a second study, we evaluated some tools against detecting possible plagiarism in research papers. Results showed that such process or decision is not binary to make and that subjectivity is high. In addition, there is a need to tune plagiarism detection tools to give criticality or weights by users of those tools to categorize and classify different levels of seriousness for committing plagiarism

Test Cases Selection Based on Source Code Features Extraction

Extracting valuable information from source code automatically was the subject of many research papers. Such information can be used for document traceability, concept or feature extraction, etc. In this paper, we used an Information Retrieval (IR) technique: Latent Semantic Indexing (LSI) for the automatic extraction of source code concepts for the purpose of test cases\u27 reduction. We used and updated the open source FLAT Eclipse add on to try several code stemming approaches. The goal is to check the best approach to extract code concepts that can improve the process of test cases\u27 selection or reduction

MQVC: Measuring Quranic Verses Similarity and Sura Classification Using N-Gram

Extensive research efforts in the area of Information Retrieval were concentrated on developing retrieval systems related to Arabic language for the different natural language and information retrieval methodologies. However, little effort was conducted in those areas for knowledge extraction from the Holly Muslim book, the Quran. In this paper, we present an approach (MQVC) for retrieving the most similar verses in comparison with a user input verse as a query. To demonstrate the accuracy of our approach, we performed a set of experiments and compared the results with an evaluation from a Quran Specialist who manually identified all relevant chapters and verses to the targeted verse in our study. The MQVC approach was applied to 70 out of 114 Quran chapters. We picked 40 verses randomly and calculated the precision to evaluate the accuracy of our approach. We utilized N-gram to extend the work by performing experiment with machine learning algorithm (LibSVM classifier in Weka), to classify Quran chapters based on the most common scholars classification: Makki and Madani chapters

Magnetic study of M type doped barium hexaferrite nanocrystalline particles

Co Ti and Ru Ti substituted barium ferrite nanocrystalline particles BaFe12 2xCoxTixO19 with 0 lt;x lt;1 and BaFe12 2xRuxTixO19 with 0 lt;x lt;0.6 were prepared by ball milling method, and their magnetic properties and their temperature dependencies were studied. The zero field cooled ZFC and field cooled FC processes were recorded at low magnetic fields and the ZFC curves displayed a broad peak at a temperature TM. In all samples under investigation, a clear irreversibility between the ZFC and FC curves was observed below room temperature, and this irreversibility disappeared above room temperature. These results were discussed within the framework of random particle assembly model and associated with the magnetic domain wall motion. The resistivity data show some kind of a transition from insulator to perfect insulator around . At 2 K, the saturation magnetization slightly decreased and the coercivity dropped dramatically with increasing the Co Ti concentration x. With Ru Ti substitution, the saturation magnetization showed small variations, while the coercivity decreased monotonically, recording a reduction of about 73 at x 0.6. These results were discussed in light of the single ion anisotropy model and the cationic distributions based on previously reported neutron diffraction data for the CoTi substituted system, and the results of our Mössbauer spectroscopy data for the RuTi substituted system

A new approach to deploy a self-adaptive distributed firewall

Distributed firewall systems emerged with the proposal of protecting individual hosts against attacks originating from inside the network. In these systems, firewall rules are centrally created, then distributed and enforced on all servers that compose the firewall, restricting which services will be available. However, this approach lacks protection against software vulnerabilities that can make network services vulnerable to attacks, since firewalls usually do not scan application protocols. In this sense, from the discovery of any vulnerability until the publication and application of patches there is an exposure window that should be reduced. In this context, this article presents Self-Adaptive Distributed Firewall (SADF). Our approach is based on monitoring hosts and using a vulnerability assessment system to detect vulnerable services, integrated with components capable of deciding and applying firewall rules on affected hosts. In this way, SADF can respond to vulnerabilities discovered in these hosts, helping to mitigate the risk of exploiting the vulnerability. Our system was evaluated in the context of a simulated network environment, where the results achieved demonstrate its viability

Weak or no association of TCF7L2 variants with Type 2 diabetes risk in an Arab population

<p>Abstract</p> <p>Background</p> <p>The rs7903146 and rs12255372 variants of <it>TCF7L2 </it>have been strongly associated with type 2 diabetes (T2D) risk in most populations studied to date. Meta-analysis of 27 different studies has resulted in a global OR of 1.46 [1.42–1.51] (rs7903146 variant). Thus far, despite a high incidence of T2D, the role of this variant in Arabs has not been established.</p> <p>Methods</p> <p>We performed a case-control association study using 522 Saudi T2D patients (WHO criteria), and 346 controls (age > 60; fasting plasma glucose < 7 mmol/L). Genotyping was performed by pyrosequencing. Statistical analyses were performed using SPSS version 13.0 for Windows (SPSS, Chicago, IL, USA).</p> <p>Results</p> <p>For rs7903146, the T allele frequency of the cases (0.415) was not different from that observed in the controls (0.405). The crude odds ratio (OR) was 1.04 with a 95% CI of 0.86–1.27 (P = 0.675). For rs12255372, the T allele frequency of the cases (0.368) was not different from that observed in the controls (0.355). Retrospective power calculations based upon an OR of 1.46 reported in a comprehensive meta-analysis of <it>TCF7L2 </it>risk, indicated this study was sufficiently powered (96.92%; α = 0.05) to detect an effect of similar magnitude to that reported for rs7903146.</p> <p>Conclusion</p> <p>Our study is consistent with weak or no association of T2D in Arabs with the two <it>TCF7L2 </it>variants, however it cannot rule out an effect of other SNPs in this gene. Future studies in this population are required to confirm our findings and may indicate the presence of yet to be defined genetic risk factors for T2D.</p

Replication of TCF7L2 rs7903146 association with type 2 diabetes in an Iranian population

The transcription factor 7-like 2 gene (TCF7L2) rs7903146 T allele is constantly associated with Type 2 diabetes in various populations and ethnic groups. Nevertheless, this has not been observed in two studies involving Arab populations. The aim of the present study was to investigate the association between TCF7L2 rs7903146 in an Iranian population. Type 2 diabetes patients (N = 258) and normal healthy control subjects (N = 168) from the same area, were examined. The ARMS- PCR (Amplification Refractory Mutation System) technique, subsequently validated by direct sequencing, was used for genotyping. Allele and genotype frequencies were significantly different between patients and controls TT vs. CT + CC [p 0.0081 OR 3.4 95%CI (1.27-11.9)] and T vs. C allele [p 0.02 OR 1.4 95%CI (1.03-1.9)]. Our data thus confirm the association between the rs7903146 T allele and T2D in an Iranian population, contrary to previous reports in Arab populations. This can possibly be attributed to differences in ethnic background or the effects of environmental factors