Predictive model and near infrared spectroscopy in predicting the diesel fuel properties

Monitoring the diesel fuel properties play an important role in the performance of vehicle engines. Near-infrared (NIR) technology has been investigated as an alternative to monitor the diesel fuel properties. NIR spectroscopy shows an enormous potential for quantitative analysis of complex samples by coupling with artificial neural networks (ANNs). Although a single layer ANN shows promising in the establishing better relationship between a component of interest and NIR spectrum, a different algorithm for updating weight that has been proved to improve the performance of the multilayer could further reveal the potential of single linear layer ANN in NIR spectroscopic analysis. Therefore, this study investigates the performance of a single layer ANN that trained with LevenbergMarquardt (SLM) and that trained with Scaled Conjugate Gradient (SSCG) and compares the proposed methods with multilayer ANN that trained with same learning algori thms. Results were evaluated and discussed with previous studies that used the same data sets to establish the relationship between the NIR spectral data and diesel fuel properties. Finding depicts that the proposed SLM and SSCG were capable of predicting the diesel fuel properties using NIR spectrum without data reduction, and achieving better accuracy in predicting the diesel fuel properties compared with other recent methods. In addition, using a proposed genetic algorithm for data reduction to improve the predictive model of the proposed method

Kemahiran boleh pindah dalam kalangan pelajar kejuruteraan di IPTA

Kemahiran boleh pindah didefinisikan sebagai kemahiran yang dimiliki oleh individu yang mempunyai kepelbagaian pengetahuan, nilai-nilai serta kemahiran hidup asas (life skills) yang diperlukan demi mendapatkan dan mengekalkan pekerjaan sedia ada. Kajian berbentuk tinjauan kuantitatif ini bertujuan untuk mengenal pasti persepsi pelajar terhadap tahap kesedaran kepentingan kemahiran boleh pindah dan tahap penguasaannya dari aspek adaptif, pemikiran kritis dan penyelesaian masalah. Di samping itu, kajian ini juga bertujuan untuk mengenal pasti perbezaan persepsi pelajar terhadap tahap kesedaran kepentingan kemahiran boleh pindah dan perbezaan terhadap tahap penguasaannya di antara lelaki dan perempuan. Seramai 297 orang pelajar kejuruteraan tahun tiga lepasan matrikulasi Universiti Tun Hussein Onn Malaysia telah terpilih sebagai responden untuk menjawab borang soal selidik. Data dianalisis dengan mencari nilai skor min dan Ujian-t tidak bersandar menggunakan perisian Statistical Package for Social Science (SPSS). Dapatan kajian menunjukkan bahawa persepsi pelajar terhadap tahap kesedaran kepentingan kemahiran boleh pindah dan tahap penguasaannya berada pada tahap tinggi dengan nilai skor min 4.0864 dan 4.0282. Kajian juga menunjukkan bahawa wujudnya perbezaan yang signifikan dalam skor min persepsi pelajar terhadap tahap kesedaran kepentingan kemahiran boleh pindah antara lelaki dan perempuan dengan nilai t signifikan 0.003. Namun begitu, hasil analisis menunjukkan tiada perbezaan bagi tahap penguasaannya dengan nilai t signifikan 0.327. Secara keseluruhannya, kesedaran yang tinggi akan membantu pelajar untuk menguasai keseluruhan kemahiran dengan sempurna. Ia juga boleh dijadikan panduan bagi pelajar untuk mengenal pasti elemen dan ciri-ciri yang diperlukan oleh majikan pada masa kini

Eliminating xenobiotics organic compounds from greywater through green synthetic nanoparticles

Xenobiotic Organic Compounds (XOCs) have been widely considered to be pollutant compounds due to their harmful impacts on aquatic life. However, there have been few rigorous studies of cutting-edge technology used to eradicate XOCs and their presence in bathroom greywater. The present review provides a comprehensive examination of current methodologies used for removing XOCs by photocatalysis of green nanoparticles. It was appeared that zinc oxide nanoparticles (ZnO NPs) have high efficiency (99%) in photocatalysis process. Green synthesis provides proven processes that do not require dangerous chemicals or expensive equipment, making photocatalysis a potential solution for the status quo. XOCs residue was decomposed, and pollutants were eliminated with varied degrees of efficiency using green synthesis ZnO nanoparticles. It is hypothesized that the utilization of photocatalysis can create a greywater treatment system capable of degrading the toxic XOCs in greywater while increasing the pace of production. Hence, this review will be beneficial in improving greywater quality and photocatalysis using green nanoparticles can be an immediate platform in solving the issue regarding the existence of XOCs in greywater in Malaysia. Researchers in the future may benefit from focusing on optimizing photocatalytic degradation using green-synthesis ZnO. It might also help with the creativity and productivity of the next generation of authoritative concerns, notably water conservation