Preference in learning gross anatomy among IIUM students

Both medical (Year I, Year II) and dental (Year I) students in IIUM are exposed to three types of teaching aids in learning gross anatomy. They are cadavers, prosected wet specimens and plastic models. This study aimed at exploring the students’ preference on teaching aids in learning gross anatomy and reasons for their preference. A cross-sectional comparative study was carried out among 185 medical and dental students by using the pretested, semi structured, self administrated questionnaires including open-ended questions. Significance of preferences were analysed by X2 test. Year I (99%) and Year II (97%) medical students preferred the plastic models as the best approach to learn gross anatomy because of their handleability and portability. Year I dental students (96%) preferred the prosected wet specimens because they were real human structures and well preserved. The preferred and less preferred rates were 86% and 4% for plastic model, 84% and 10% for prosected wet specimen and 77% and 17% for cadaver. These differences were statistically significant (p <0.05). Students didn’t prefer the cadavers most but they agreed that the cadavers are more realistic, informative and easier to remember. This study indicates that students prefer all three types of teaching aids while the most preferred one is the plastic model. The quality of teaching aid is the reason for their preference. Students’ suggestion to use the advanced technologies such as three dimensional animations or simulated videos should be considered to get discernable learning outcomes

Anaphora Resolution for Myanmar Text Using K-Nearest Neighbor Algorithm

Anaphora resolution which most commonly appears as pronoun resolution is the problem of resolving references to earlier or later items in the discourse. Anaphora resolution is an active area of research, such as text mining, text summarization, dialogue interpretations, information extraction, and so on. Anaphora resolution in English and other European languages has been well done in early. But Myanmar Language has not sufficiently applied. This paper presents Myanmar anaphora resolution system by using rule-based part of speech tagging and machine learning approach. Rule-based manner with morphological informat ion is used to collect anaphora and possible antecedents. K-Nearest Neighbor (k-NN) approach is used to select the most probable candidate as the antecedent of the anaphor

Myanmar-English Bidirectional Machine Translation System by Using Transfer Based Approach

This paper presents the development ofbidirectional machine translation system of Myanmar-English. This Machine Translation system is based onTransfer Based Approach. It contains three stages: (1)source sentence analysis stages, (2) the structure ofsource sentence to the structure of target sentencetransferstages and (3) target sentence generationstages.In the analysis stage, input source sentence isparsed with the help of existing parsers. To changefrom source sentence structure to target sentencestructure, tree to tree transformation approach isapplied by using Synchronous Context Free Grammar(SCFG) rules. Morphological synthesis is alsoconsidered to improve smooth translationin thegeneration stage because Myanmar language isamorphologically rich language

Implementation of Case-based Reasoning System for Criminal Judgement

Case-Based Reasoning (CBR) is theprocess of solving new problems based on thesolutions of similar past problems. The CBR canbe used to find the specific knowledge ofpreviously experienced problem situations(cases).The purpose of this system is to develop acase-based reasoning system for criminaljudgment. A new problem is solved by finding asimilar past case, and reusing it in the newproblem situation. CBR is also an approach toincremental, sustained learning because a newexperience is retained each time a problem hasbeen solved, making it immediately available forfuture problems. By using the knowledge of expertand documentation, this system applies four tasksof CBR for criminal judgements. The systemproduces the judgment or punishment as caseoutput. The system can also retain the successfulcase solutions for future assistance