Design of Noise Insulator for Metal Stamping Operation in Manufacturing Sector

Metal stamping is one of the processes involved in metal manufacturing in which dies are used to cut or form flat metal sheets into desired shapes. Consequently, noise is produced from the process. Prolonged exposure to the noise can lead to the health problems, low productivity and low performance of workers. The aim of this study is to design a noise insulator for noise level reduction in a metal stamping operation. This study applied workplace observation, questionnaire survey and noise mapping at the metal stamping workstations.  A prototype design of noise insulator was developed through brainstorming among the metal stamping workers, questionnaire survey and morphological chart. Recycled papers and coconut fibers were used as materials of the noise insulator. Noise level assessment was conducted to determine the effectiveness of the developed noise insulator. The noise levels have been effectively reduced to 70.3 dBA by 17.2%. This study concluded that application of materials such as recycled papers and coconut fibers in making of noise insulator was able to reduce noise levels in metal stamping operation. This study suggests that the real fabrication and application should be implemented in the metal stamping operation to reduce the risk of noise exposure to the workers

Case Study: First-Time Success ASIC Design Methodology Applied to a Multi-Processor System-on-Chip

Achieving first-time success is crucial in the ASIC design league considering the soaring cost, tight time-to-market window, and competitive business environment. One key factor in ensuring first-time success is a well-defined ASIC design methodology. Here we propose a novel ASIC design methodology that has been proven for the RUMPS401 (Rahman University Multi-Processor System 401) Multiprocessor System-on-Chip (MPSoC) project. The MPSoC project is initiated by Universiti Tunku Abdul Rahman (UTAR) VLSI design center. The proposed methodology includes the use of Universal Verification Methodology (UVM). The use of electronic design automation (EDA) software during each step of the design methodology is also presented. The first-time success RUMPS401 demonstrates the use of the proposed ASIC design methodology and the good of using one. Especially this project is carried on in educational environment that is even more limited in budget, resources and know-how, compared to the business and industrial counterparts. Here a novel ASIC design methodology that is tailored to first-time success MPSoC is presented

Magnetic and transport properties of LaMnO3/La0.67Ba0.33MnO3 single and bi-layer thin films

Single and bi-layer thin films of LaMnO3 and La0.67Ba0.33MnO3 were deposited on amorphous fused silica substrate via pulsed laser deposition technique (PLD). In this work, the effect of stacking sequence in bi-layer manganite films of LaMnO3 and La0.67Ba0.33MnO3 was reported. The crystal structure formation, magnetic, resistivity and magnetotransport properties of bi-layer manganite films were studied. The unit cell of LMO undergo negative misfit when growth on LBMO while positive misfit for unit cell of LBMO when growth on LMO. Such changes indirectly alter the magnetism of the system since it governed by the Mn-O-Mn bond angle and Mn-O bond length. Therefore, different magnetic pinning strength was observed between the LMO and LBMO layer coupled in LMO/LBMO and LBMO/LMO respectively. The stronger the magnetic spins pinning effect, the higher the resistivity is and the more scattered the %MR are

Logicpower5: Smart Fan Chip / Muhammad Farhan Abd Halim [et al.]

Our smart chip is for control the speed of every fan connected with the microchip. It is very convenience for every fan in the world. The microchip is very rare because it is made from a combination of electronics component that is very flexible to handle

Highly efficient proliferation and regeneration of protocorm-like bodies (PLBS) of the threatened orchid, phalaenopsis bellina

Phalaenopsis bellina is an important indigenous fragrant orchid threatened with extinction. In this study, we evaluated the effect of medium strength, sucrose, nitrogen (NH4NO3) and potato extract on proliferation of P. bellina protocorm-like bodies (PLBs) to improve micropropagation in this species. Optimal treatment for PLBs proliferation rate with an average fresh weight (FW) of 0.97±0.16 g was obtained through culturing on half strength (½) MS medium containing 20 g/L sucrose, 15 mM NH4NO3 and 20% w/v potato extract supplemented with 0.8 μM 2,4 dichlorophenoxyacetic acid (2,4-D). The optimal treatment produced large, healthy and greenish PLBs with reduction in the occurrence of culture browning. In contrast, treatments with high potato extract (>20% w/v) or NH4NO3 (>30 mM) concentrations tend to have inhibitory effect and resulted in low PLBs proliferation rate, with an average FW of 0.77±0.15 g and 0.69±0.15 g, respectively. Plant regeneration of PLBs was achieved on plant growth regulator (PGR)-free ½ MS medium. In total, 60 healthy PLBs from the optimal treatment were successfully regenerated, acclimatized with 100% survival percentage and grew well in a mixture of soil, sand and vermicompost (8:4:2 (w/w/w)). With the optimal treatment, PLBs proliferation rate was enhanced by 27.63%. Our findings offer an improved micropropagation protocol of the endangered P. bellina for conservation and commercial production

Highly efficient proliferation and regeneration of protocorm-like bodies (PLBS) of the threatened orchid, phalaenopsis bellina

Phalaenopsis bellina is an important indigenous fragrant orchid threatened with extinction. In this study, we evaluated the effect of medium strength, sucrose, nitrogen (NH4NO3) and potato extract on proliferation of P. bellina protocorm-like bodies (PLBs) to improve micropropagation in this species. Optimal treatment for PLBs proliferation rate with an average fresh weight (FW) of 0.97±0.16 g was obtained through culturing on half strength (½) MS medium containing 20 g/L sucrose, 15 mM NH4NO3 and 20% w/v potato extract supplemented with 0.8 μM 2,4 dichlorophenoxyacetic acid (2,4-D). The optimal treatment produced large, healthy and greenish PLBs with reduction in the occurrence of culture browning. In contrast, treatments with high potato extract (>20% w/v) or NH4NO3 (>30 mM) concentrations tend to have inhibitory effect and resulted in low PLBs proliferation rate, with an average FW of 0.77±0.15 g and 0.69±0.15 g, respectively. Plant regeneration of PLBs was achieved on plant growth regulator (PGR)-free ½ MS medium. In total, 60 healthy PLBs from the optimal treatment were successfully regenerated, acclimatized with 100% survival percentage and grew well in a mixture of soil, sand and vermicompost (8:4:2 (w/w/w)). With the optimal treatment, PLBs proliferation rate was enhanced by 27.63%. Our findings offer an improved micropropagation protocol of the endangered P. bellina for conservation and commercial production

Microstructure and magnetic properties of PrMnO3 bulk and thin film

Perovskite PrMnO3 (PMO) had been prepared in bulk by solid state reaction and thin films on corning glass, fused silica and MgO (100) glass substrate by pulsed laser deposition technique. SEM micrographs show that grains with size 2∼3 μm is observed in bulk PMO while thin films PMO show strongly connected grain structure with particle size that not larger than 100 nm. X‐ray diffraction analysis shows that all samples are in single phase with orthorhombic crystal structure. Bulk PMO sample had lattice strain of 0.134% which is the lowest value among others. However, larger lattice strain was observed in thin film samples due to lattice mismatch between film‐substrate and caused the MnO6 to deform. All samples shown paramagnetic or antiferromagnetic behavior, enhancement in magnetization value occurred for all PMO grew as film. We believe that larger lattice strain favor the grain growth of PMO towards more order phase. In summary, formation of structure and microstructure of thin film PMO depends on type of substrate used and it affect the magnetic property

Design of noise insulator for metal stamping operation in manufacturing sector

Metal stamping is one of the processes involved in metal manufacturing industry in which dies are used to cut or form flat metal sheets into desired shapes. Consequently, noise is produced from the process. Prolonged exposure to the noise can lead to the health problems, hinder productivity and low performance of workers. The aim of this study was to design a noise insulator prototype for noise level reduction in a metal stamping operation. This study applied workplace observation, questionnaire survey and noise mapping at the metal stamping workstations. A prototype design of noise insulator was developed through brainstorming among the metal stamping workers, questionnaire survey and morphological chart. Recycled papers and coconut fibers were used as materials of the noise insulator. Noise level assessment was conducted to determine the effectiveness of the developed noise insulator. The noise levels have been effectively reduced to 70.3 dBA by 17.2%. This study concluded that application of materials such as recycled papers and coconut fibers in making of noise insulator was able to reduce noise levels in metal stamping operation. This study suggests that the real fabrication and application should be implemented in the metal stamping operation to reduce the risk of noise exposure to the worker

Gene encoder: a feature selection technique through unsupervised deep learning-based clustering for large gene expression data

© 2020, Springer-Verlag London Ltd., part of Springer Nature. Cancer is a severe condition of uncontrolled cell division that results in a tumor formation that spreads to other tissues of the body. Therefore, the development of new medication and treatment methods for this is in demand. Classification of microarray data plays a vital role in handling such situations. The relevant gene selection is an important step for the classification of microarray data. This work presents gene encoder, an unsupervised two-stage feature selection technique for the cancer samples’ classification. The first stage aggregates three filter methods, namely principal component analysis, correlation, and spectral-based feature selection techniques. Next, the genetic algorithm is used, which evaluates the chromosome utilizing the autoencoder-based clustering. The resultant feature subset is used for the classification task. Three classifiers, namely support vector machine, k-nearest neighbors, and random forest, are used in this work to avoid the dependency on any one classifier. Six benchmark gene expression datasets are used for the performance evaluation, and a comparison is made with four state-of-the-art related algorithms. Three sets of experiments are carried out to evaluate the proposed method. These experiments are for the evaluation of the selected features based on sample-based clustering, adjusting optimal parameters, and for selecting better performing classifier. The comparison is based on accuracy, recall, false positive rate, precision, F-measure, and entropy. The obtained results suggest better performance of the current proposal