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  1. Teaching engineering ethics using BLOCKS game
    Lau SW, Tan TP, Goh SM
    Sci Eng Ethics, 2013 Sep;19(3):1357-73.
    PMID: 23065541 DOI: 10.1007/s11948-012-9406-3
    The aim of this study was to investigate the use of a newly developed design game called BLOCKS to stimulate awareness of ethical responsibilities amongst engineering students. The design game was played by seventeen teams of chemical engineering students, with each team having to arrange pieces of colored paper to produce two letters each. Before the end of the game, additional constraints were introduced to the teams such that they faced similar ambiguity in the technical facts that the engineers involved in the Challenger disaster had faced prior to the space shuttle launch. At this stage, the teams had to decide whether to continue with their original design or to develop alternative solutions. After the teams had made their decisions, a video of the Challenger explosion was shown followed by a post-game discussion. The students' opinion on five Statements on ethics was tracked via a Five-Item Likert survey which was administered three times, before and after the ethical scenario was introduced, and after the video and post-game discussion. The results from this study indicated that the combination of the game and the real-life incident from the video had generally strengthened the students' opinions of the Statements.
  2. Hybrid transfer learning strategy for cross-subject EEG emotion recognition
    Lu W, Liu H, Ma H, Tan TP, Xia L
    Front Hum Neurosci, 2023;17:1280241.
    PMID: 38034069 DOI: 10.3389/fnhum.2023.1280241
    Emotion recognition constitutes a pivotal research topic within affective computing, owing to its potential applications across various domains. Currently, emotion recognition methods based on deep learning frameworks utilizing electroencephalogram (EEG) signals have demonstrated effective application and achieved impressive performance. However, in EEG-based emotion recognition, there exists a significant performance drop in cross-subject EEG Emotion recognition due to inter-individual differences among subjects. In order to address this challenge, a hybrid transfer learning strategy is proposed, and the Domain Adaptation with a Few-shot Fine-tuning Network (DFF-Net) is designed for cross-subject EEG emotion recognition. The first step involves the design of a domain adaptive learning module specialized for EEG emotion recognition, known as the Emo-DA module. Following this, the Emo-DA module is utilized to pre-train a model on both the source and target domains. Subsequently, fine-tuning is performed on the target domain specifically for the purpose of cross-subject EEG emotion recognition testing. This comprehensive approach effectively harnesses the attributes of domain adaptation and fine-tuning, resulting in a noteworthy improvement in the accuracy of the model for the challenging task of cross-subject EEG emotion recognition. The proposed DFF-Net surpasses the state-of-the-art methods in the cross-subject EEG emotion recognition task, achieving an average recognition accuracy of 93.37% on the SEED dataset and 82.32% on the SEED-IV dataset.
  3. Fulltext Prevalence of Salmonella in poultry processing environments in wet markets in Penang and Perlis, Malaysia
    Nidaullah H, Abirami N, Shamila-Syuhada AK, Chuah LO, Nurul H, Tan TP, et al.
    Vet World, 2017 Mar;10(3):286-292.
    PMID: 28435190 DOI: 10.14202/vetworld.2017.286-292
    AIM: The aim of this study was to determine the prevalence of various Salmonella serotypes in chickens, carcass contact surfaces as well as environmental samples collected from wet markets and small scale processing plant.

    MATERIALS AND METHODS: A total of 182 poultry and environmental samples were collected at random on separate occasions from wet markets and small scale processing plant, during the period of October 2014 to July 2015 in Penang and Perlis, Malaysia. The samples were analyzed for the presence of Salmonella using ISO 6579:2002 conventional culture-based method. Presumptive Salmonella colonies were subjected to various biochemical tests (such as triple sugar iron and lysine iron test), serologically confirmed using polyvalent O and H antisera and further serotyped at Public Health Laboratory, Ministry of Health, Perak, Malaysia.

    RESULTS: Salmonella serotypes were isolated from 161 out of 182 samples (88.46%) with 100% prevalence in the whole chicken carcass and chicken cuts - as well as transport crate, cage, drum, knife, chopping board, display table, floor, bench wash water, wash water, and drain water. Salmonella was isolated from 91.67%, 83.33%, and 66.67% of defeathering machines, drain swabs, and apron, respectively. 17 serotypes were isolated in this study with Salmonella Albany (57/161), Salmonella Corvallis (42/161), and Salmonella Brancaster (37/161) being the predominant serovars.

    CONCLUSION: The most carcass contact and environmental samples collected along the wet market chicken processing line were consistently contaminated with Salmonella. This indicates that Salmonella has established itself in poultry processing environments by colonizing the surfaces of the equipment and survives in these environments by establishing biofilms. Our results highlight the need of implementing strict hygiene and sanitation standards to reduce the incidence of Salmonella. The prevalence of Salmonella in poultry can be reduced effectively by identifying and eliminating the sources and contamination sites during slaughter and processing of poultry.

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