Work design improvement at Miroad Rubber Industries Sdn. Bhd.

Erul Food Industries known as Salaiport Industry is a family-owned company and was established on July 2017. Salaiport Industry apparently moved to a new place at Pedas, Negeri Sembilan. Previously, Salaiport Industry operated in-house located at Pagoh, Johor. This small company major business is producing frozen smoked beef, smoked quail, smoke catfish and smoked duck. The main frozen product is smoked beef. The frozen smoked meat produced by Salaiport Industry is depending on customer demands. Usually the company produce 40 kg to 60 kg a day and operated between for four days until five days. Therefore, the company produce approximately around 80 kg to 120 kg per week. The company usually take 2 days for 1 complete cycle for the production as the first day the company will only receive the meat from the supplier and freeze the meat for use of tomorrow

Child labour: the case study in Bangladesh

Child labour involves of person that age below than 17 years old. Child labour often happen in poor countries such as Bangladesh. In Bangladesh, the issue of child labour might be the biggest issue. Bangladesh come up with Bangladesh Labour Act (BLA) that did not allow any person age below from fourteen years old to work (Nawshin et al, 2019). One of the aim or purpose of this act is to prevent teen workers in order to get the proper payment of any work. This is because when organization use child labour, they might be paid at lower rate because children usually do not have much responsible in their family compared to teen workers. This indirectly cause an economic matter in a family

Development of control algorithm for a new 12s-6p single phase field excited flux switching motor

Flux switching motor (FSM) fall into a special category of switch reluctance motors (SRM). One of the key features of FSM is its rotor structure. Generally, it is free from any magnet and winding. Thus, allowing the motor to attain considerably higher speed and more stability then conventional AC motor. However, this simple and robust structure demands more sophisticated driving mechanism mainly due to the absence of rotating magneto motive force (MMF) in the rotor. The main concern of this research is to design algorithms for starting and driving 12 slots and 6 poles (12S-6P) segmental rotor field excited flux switching motor (FEFSM) and evaluate the algorithms efficiency by analyzing motor’s dynamic performance in terms of torque and current consumption. In this research, two algorithms have been proposed in which first algorithm is based on bipolar DC signals while second algorithm is based on field oriented control (FOC) principle. For position detection, algorithms merely need a basic infrared transceiver sensor. Bipolar DC signal algorithm is based on changing the polarity of armature DC voltage on the detection of zero rotor position. On the other hand, FOC algorithm involves detection of rotor zero position to estimate speed and prediction of instantaneous rotor position in real time. Initially, fundamental control principle for 12S-6P FEFSM has been identified through the finite element analysis (FEA) of the model. Afterwards control algorithms have been successfully developed and implemented in the motor control hardware. Compared to Bi-polar DC algorithm, the observations shows that the single phase FOC algorithm results in far less distortion of armature voltage waveforms even at high speed, which results in jittering free motor operation. On the other hand, Bi-polar DC algorithm results in much higher torque production, which is about 50% more than that of the single phase FOC’s yield. In terms of simulation and prototype performance comparison, Bi-polar DC algorithm is about 92% efficient in torque generation in case of initial model of FEFSM and staggering efficiency around 96% in case of optimized motor model

Efficient Encoding of Wireless Capsule Endoscopy Images Using Direct Compression of Colour Filter Array Images

Since its invention in 2001, wireless capsule endoscopy (WCE) has played an important role in the endoscopic examination of the gastrointestinal tract. During this period, WCE has undergone tremendous advances in technology, making it the first-line modality for diseases from bleeding to cancer in the small-bowel. Current research efforts are focused on evolving WCE to include functionality such as drug delivery, biopsy, and active locomotion. For the integration of these functionalities into WCE, two critical prerequisites are the image quality enhancement and the power consumption reduction. An efficient image compression solution is required to retain the highest image quality while reducing the transmission power. The issue is more challenging due to the fact that image sensors in WCE capture images in Bayer Colour filter array (CFA) format. Therefore, standard compression engines provide inferior compression performance. The focus of this thesis is to design an optimized image compression pipeline to encode the capsule endoscopic (CE) image efficiently in CFA format. To this end, this thesis proposes two image compression schemes. First, a lossless image compression algorithm is proposed consisting of an optimum reversible colour transformation, a low complexity prediction model, a corner clipping mechanism and a single context adaptive Golomb-Rice entropy encoder. The derivation of colour transformation that provides the best performance for a given prediction model is considered as an optimization problem. The low complexity prediction model works in raster order fashion and requires no buffer memory. The application of colour transformation yields lower inter-colour correlation and allows the efficient independent encoding of the colour components. The second compression scheme in this thesis is a lossy compression algorithm with a integer discrete cosine transformation at its core. Using the statistics obtained from a large dataset of CE image, an optimum colour transformation is derived using the principal component analysis (PCA). The transformed coefficients are quantized using optimized quantization table, which was designed with a focus to discard medically irrelevant information. A fast demosaicking algorithm is developed to reconstruct the colour image from the lossy CFA image in the decoder. Extensive experiments and comparisons with state-of-the-art lossless image compression methods establish the superiority of the proposed compression methods as simple and efficient image compression algorithm. The lossless algorithm can transmit the image in a lossless manner within the available bandwidth. On the other hand, performance evaluation of lossy compression algorithm indicates that it can deliver high quality images at low transmission power and low computation costs