Kerangka E-pembelajaran TVET Kursus Kemahiran Praktikal: E-Learning Framework of TVET Practical Skills Courses

Pengajaran dan Pembelajaran (PdP) dalam talian adalah salah satu transformasi pendidikan ke arah digital dan kini merupakan keperluan terutama semasa pandemik. PdP di institusi Latihan Teknikal dan Vokasional (TVET) mengutamakan kepada kemahiran praktikal, yang menjadi salah satu Pelan Pembangunan Pendidikan Malaysia 2015-2025 (Pendidikan Tinggi). Perlaksanaan PdP kurang berkesan jika kursus kemahiran praktikal dijalankan secara dalam talian tanpa panduan yang dirangka khas. Justeru, kajian ini akan membangunkan kerangka e- pembelajaran TVET bagi kursus kemahiran praktikal yang ditawarkan di institusi TVET. Objektif bagi kajian ini adalah untuk mengenal pasti komponen dalam kerangka e-pembelajaran TVET kursus kemahiran praktikal dan menguji penerimaan kerangka memalui prototaip aplikasi. Responden bagi kajian ini adalah pensyarah pakar daripada Diploma Pengurusan Peruncitan Politeknik Nilai yang melaksanakan pengajaran dan pembelajaran TVET. Kajian ini dibahagikan kepada dua fasa iaitu mengenalpasti elemen daripada kajian lepas dan fasa kedua adalah penilaian penerimaan kerangka oleh sepuluh orang pakar bidang yang bertujuan untuk melihat kesesuaian serta penerimaan kerangka untuk dijadikan panduan oleh tenaga pengajar TVET. Dapatan hasil kajian dianalisis untuk memenuhi objektif kajian. Kerangka kajian ini berasaskan model Komuniti Inkuiri dan Kerangka Kelayakan Malaysia (MQF) serta penggunaan realiti terimbuh. Hasil analisis menunjukkan pakar bidang bersetuju terhadap elemen yang digunakan bagi kerangka pembelajaran. Daripada analisis menunjukkan kerangka ini boleh dilaksanakan dalam proses PdP dalam talian serta mampu membantu tenaga pengajar TVET untuk melaksanakan pengajaran berbentuk kemahiran praktikal selain itu juga ianya berfungsi sebagai panduan yang dapat digunakan oleh tenaga pengajar untuk meningkatkan kreativiti, penglibatan dan komunikasi pelajar bersama tenaga pengajar.  Online teaching and learning (TnL) is one of the transformation of education towards digital it is a necessity now especially during a pandemic. The TnL in Technical and Vocational Training (TVET) institutions prioritizes on the practical, which is one of the Malaysia Education Development Plan 2015-2025 (Higher Education). The implementation of TnL is less effective if the practical course is conducted online without a guide specially designed for the practical subject. Thus, this study will develop an TVET e-learning framework for practical courses offered in TVET institution. The objective of this study is to identify components in the TVET e-learning framework of practical skills courses and test the acceptance of the framework through application prototypes. Respondents for this study are specialist lecturers from Nilai Polytechnic Retail Management Diploma who implement TVET teaching and learning. This study is divided into two phases which is identify elements from the previous study and the second phase is the assessment of the acceptance of the framework by ten experts in the field which aims to see the suitability and acceptance of the framework to be used as a guide by TVET teaching staff. The results of the study were analyzed to meet the objectives of the study. This research framework is based on the Community of Inquiry model and the Malaysian Qualifications Framework (MQF) also use of augmented reality. The results of the analysis show that experts agree on the elements used for the learning framework. From analysis,this framework can be implemented in the online TnL process and is capable of helping TVET instructors to implement practical skills teaching in addition it functions as a guide for lecturer to increase creativity, engagement and communication of students with lecturer

Effects of temperature and airflow on volume development during baking and its influence on quality of cake

Volume and texture of cake are among the important parameters in measuring the quality of cake. The processing conditions play important roles in producing cakes of good quality. Recent studies focused more on the formulation and the manipulation of baking temperature, humidity and time instead of airflow condition. The objective of this study was to evaluate the effects of baking temperature and airflow on the volume development of cake and final cake quality such as volume development, firmness, springiness and moisture content. The cake was baked at three different temperatures (160°C, 170°C, and 180°C), and two different airflow conditions. Baking time, height changes of batter, texture and moisture content of cake were compared to identify the differences or similarities on the final product as the process conditions varied. Results showed that, airflow has more significant effects towards the product quality compared to baking temperature especially on baking time which was 25.58 - 45.16%, and the rate of height changes which was 0.7 mm/min. However, different baking temperatures had more significant effects towards volume expansion which was 2.86 - 8.37% and the springiness of cake which was 3.44% compared to airflow conditions

Discrimination and authentication of lard blending with palm oil in cosmetic soap formulations

Background: The employment of Fourier transforms infrared (FT-IR) spectroscopy combined with chemometrics for determination and quantification of lard in a binary blend with palm oil in a cosmetic soap formulations. Objective: To determine and quantify lard as an adulterant in a binary blend with palm oil in a cosmetic soap formulations by FT-IR and multivariate analysis. Methods: Fatty acids in lard, palm oil and binary blends were extracted via liquid–liquid extraction and were subjected to FTIR spectrometry, combined with principal component analysis (PCA) and discriminant analysis (DA) for the classification of lard in cosmetic soap formulations via two DA models: Model A (percentage of lard in cosmetic soap) and Model B (porcine and non-porcine cosmetic soap). Linear regression (MLR), partial least square regression (PLS-R) and principal components regression (PCR) were used to assess the degree of adulteration of lard in the cosmetic soap. Findings: The FTIR spectrum of palm oil slightly differed from that of lard at the wavenumber range of 1453 cm−1 and 1415 cm−1 in palm oil and lard, respectively, indicating the bending vibrations of CH2 and CH3 aliphatic groups and OH carboxyl group respectively. Both of the DA models could accurately classify 100% of cosmetic soap formulations. Nevertheless, less than 100% of verification value was obtained when it was further used to predict the unknown cosmetic soap sample suspected of containing lard or a different percentage of lard. The PCA for Model A and Model B explained a similar cumulative variability (CV) of 92.86% for the whole dataset. MLR and PCR showed the highest determination coefficient (R2) of 0.996, and the lowest relative standard error (RSE) and mean square error (MSE), indicating that both regression models were effective in quantifying the lard adulterant in cosmetic soap. Conclusion: FTIR spectroscopy coupled with chemometrics with DA, PCA and MLR or PCR can be used to analyse the presence of lard and quantify its percentage in cosmetic soap formulation

Mortality from gastrointestinal congenital anomalies at 264 hospitals in 74 low-income, middle-income, and high-income countries: a multicentre, international, prospective cohort study

Summary Background Congenital anomalies are the fifth leading cause of mortality in children younger than 5 years globally. Many gastrointestinal congenital anomalies are fatal without timely access to neonatal surgical care, but few studies have been done on these conditions in low-income and middle-income countries (LMICs). We compared outcomes of the seven most common gastrointestinal congenital anomalies in low-income, middle-income, and high-income countries globally, and identified factors associated with mortality. Methods We did a multicentre, international prospective cohort study of patients younger than 16 years, presenting to hospital for the first time with oesophageal atresia, congenital diaphragmatic hernia, intestinal atresia, gastroschisis, exomphalos, anorectal malformation, and Hirschsprung’s disease. Recruitment was of consecutive patients for a minimum of 1 month between October, 2018, and April, 2019. We collected data on patient demographics, clinical status, interventions, and outcomes using the REDCap platform. Patients were followed up for 30 days after primary intervention, or 30 days after admission if they did not receive an intervention. The primary outcome was all-cause, in-hospital mortality for all conditions combined and each condition individually, stratified by country income status. We did a complete case analysis. Findings We included 3849 patients with 3975 study conditions (560 with oesophageal atresia, 448 with congenital diaphragmatic hernia, 681 with intestinal atresia, 453 with gastroschisis, 325 with exomphalos, 991 with anorectal malformation, and 517 with Hirschsprung’s disease) from 264 hospitals (89 in high-income countries, 166 in middleincome countries, and nine in low-income countries) in 74 countries. Of the 3849 patients, 2231 (58·0%) were male. Median gestational age at birth was 38 weeks (IQR 36–39) and median bodyweight at presentation was 2·8 kg (2·3–3·3). Mortality among all patients was 37 (39·8%) of 93 in low-income countries, 583 (20·4%) of 2860 in middle-income countries, and 50 (5·6%) of 896 in high-income countries (p<0·0001 between all country income groups). Gastroschisis had the greatest difference in mortality between country income strata (nine [90·0%] of ten in lowincome countries, 97 [31·9%] of 304 in middle-income countries, and two [1·4%] of 139 in high-income countries; p≤0·0001 between all country income groups). Factors significantly associated with higher mortality for all patients combined included country income status (low-income vs high-income countries, risk ratio 2·78 [95% CI 1·88–4·11], p<0·0001; middle-income vs high-income countries, 2·11 [1·59–2·79], p<0·0001), sepsis at presentation (1·20 [1·04–1·40], p=0·016), higher American Society of Anesthesiologists (ASA) score at primary intervention (ASA 4–5 vs ASA 1–2, 1·82 [1·40–2·35], p<0·0001; ASA 3 vs ASA 1–2, 1·58, [1·30–1·92], p<0·0001]), surgical safety checklist not used (1·39 [1·02–1·90], p=0·035), and ventilation or parenteral nutrition unavailable when needed (ventilation 1·96, [1·41–2·71], p=0·0001; parenteral nutrition 1·35, [1·05–1·74], p=0·018). Administration of parenteral nutrition (0·61, [0·47–0·79], p=0·0002) and use of a peripherally inserted central catheter (0·65 [0·50–0·86], p=0·0024) or percutaneous central line (0·69 [0·48–1·00], p=0·049) were associated with lower mortality. Interpretation Unacceptable differences in mortality exist for gastrointestinal congenital anomalies between lowincome, middle-income, and high-income countries. Improving access to quality neonatal surgical care in LMICs will be vital to achieve Sustainable Development Goal 3.2 of ending preventable deaths in neonates and children younger than 5 years by 2030

Guided reading and literacy workstation towards reading motivation

Research has widely documented that reading achievement is the most influential determinant of a child's educational success; yet, large gaps still remain for many children (e.g., Butler, Marsh, Sheppard, & Sheppard, 1985; Senechal & LeFevre, 2002; Stainthorp & Hughes, 2004; Wagner el al, 1997). As Asraf and Ahmad (2003) point out, the rural school students' failure rate in national standardized English examination is twice that of the students from urban area.

Review on hypertension diagnosis using expert system and wearable devices

The popularity of smartphones and wearable devices is increasing in the global market. These devices track physical exercise records, heartbeat, medicines, and self-health diagnosis. The wearable devices can also collect personal health parameters include hypertension diagnosis. Hypertension is one of the risk factors for cardiovascular-related diseases among the Malaysian population. Many mobile applications are paired with wearable devices to monitor health conditions, but none of them able to diagnose hypertension. In this study, we reviewed research papers that focused on hypertension using expert systems and wearable devices. We performed a systematic literature review based on hypertension factors, expert systems, and wearable devices. We found 15 specific research papers after the filtering process. The key findings highlighted three main focuses, which are the factors of hypertension, the expert system techniques, and the types of sensors in wearable devices. Blood pressure is the most common factor of hypertension that can be collected by wearable devices. As for the expert system techniques, we determined the three most common techniques are machine learning, neural network, and fuzzy logic. Lastly, the wrist band is the most common sensor for wearable devices in hypertension-related research

Diagnosis of Osteoarthritis at an Early Stage via Infrared Spectroscopy Combined Chemometrics in Human Serum: A Pilot Study

Methods applied for early diagnosis of osteoarthritis (OA) are limited. Early prevention and treatment can effectively reduce the pain of OA patients and save costs. The present study aimed to develop a rapid non-destructive detection method for early diagnosis of OA by evaluating infrared (IR) spectroscopy combined chemometrics. Our cohort consisted of (a) 15 patients with osteoarthritis (OA) and (b) 10 without clinical signs of the disease and they were used as controls. Attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy was used to investigate serum samples (50 µL) collected from these patients. A supervised classification algorithm namely discriminant analysis (DA) was applied to evaluate the diagnostic accuracy spectral processing and chemometrics analysis allowed for detecting spectral biomarkers that discriminated the two cohorts. About 250 infrared spectra were statistically important for separating the groups. Peaks at 1000 cm−1 in OA serum were associated mainly with C–O stretching vibration associated with the changes in the proteoglycan contents previously reported in OA. A good overall classification accuracy of 74.47% was obtained from the DA model. Our findings indicated that this discriminating model, which incorporated the ATR-FTIR spectrum, could provide a rapid and cost-effective blood test, thus facilitating the early diagnosis of human OA

Diagnosis of Osteoarthritis at an Early Stage via Infrared Spectroscopy Combined Chemometrics in Human Serum: A Pilot Study

Methods applied for early diagnosis of osteoarthritis (OA) are limited. Early prevention and treatment can effectively reduce the pain of OA patients and save costs. The present study aimed to develop a rapid non-destructive detection method for early diagnosis of OA by evaluating infrared (IR) spectroscopy combined chemometrics. Our cohort consisted of (a) 15 patients with osteoarthritis (OA) and (b) 10 without clinical signs of the disease and they were used as controls. Attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy was used to investigate serum samples (50 &micro;L) collected from these patients. A supervised classification algorithm namely discriminant analysis (DA) was applied to evaluate the diagnostic accuracy spectral processing and chemometrics analysis allowed for detecting spectral biomarkers that discriminated the two cohorts. About 250 infrared spectra were statistically important for separating the groups. Peaks at 1000 cm&minus;1 in OA serum were associated mainly with C&ndash;O stretching vibration associated with the changes in the proteoglycan contents previously reported in OA. A good overall classification accuracy of 74.47% was obtained from the DA model. Our findings indicated that this discriminating model, which incorporated the ATR-FTIR spectrum, could provide a rapid and cost-effective blood test, thus facilitating the early diagnosis of human OA

Diagnosis of osteoarthritis at an early stage via infrared spectroscopy combined chemometrics in human serum: a pilot study

Methods applied for early diagnosis of osteoarthritis (OA) are limited. Early prevention and treatment can effectively reduce the pain of OA patients and save costs. The present study aimed to develop a rapid non-destructive detection method for early diagnosis of OA by evaluating infrared (IR) spectroscopy combined chemometrics. Our cohort consisted of (a) 15 patients with osteoarthritis (OA) and (b) 10 without clinical signs of the disease and they were used as controls. Attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy was used to inves- tigate serum samples (50 μL) collected from these patients. A supervised classification algorithm namely discriminant analysis (DA) was applied to evaluate the diagnostic accuracy spectral pro-cessing and chemometrics analysis allowed for detecting spectral biomarkers that discriminated the two cohorts. About 250 infrared spectra were statistically important for separating the groups. Peaks at 1000 cm−1 in OA serum were associated mainly with C–O stretching vibration associated with the changes in the proteoglycan contents previously reported in OA. A good overall classifi- cation accuracy of 74.47% was obtained from the DA model. Our findings indicated that this dis-criminating model, which incorporated the ATR-FTIR spectrum, could provide a rapid and cost-effective blood test, thus facilitating the early diagnosis of human O

Teamwork Improvement in Group Projects of Professional Software Development

Software engineering (SE) is an essential subject taught in the curriculum of Computing Science (CS) in Higher Education. It trains students in the knowledge of software development life cycle (SDLC), and develops them practical skills on how to efficiently develop software projects. Team-based learning is widely adopted in SE subjects to emulate the real world SDLC scenarios. It provides perceived benefits in teaching students to overcome the challenges that come with teamwork. This paper critiques the current methods of teamwork adopted by two SE modules, Project Software Development (PSD) and Team Project (TP) offered to CS cohorts in our university. Several limitations have been identified in the current framework, including a lack of diverse personalities within teams, lack of a comprehensive peer evaluation scheme and lack of a close relationship with academic supervisors of group projects. We explore alternative learning frameworks to better cultivate teamwork abilities in students. Three proposed ideas aim to address these limitations in teamwork, that are inspired by prior works for similar problems. Experiments and surveys regarding teamwork are conducted among the CS students in these two SE modules. Experiment results approve our three hypotheses on the improvement of teamwork in the learning of PSD and TP