The epileptic power supply in the society today has become a chronic problem in our industrial sector. This inconsistence in power supply can be outwitted by using biological gas like improving biogas electrical power output using fuzzy logic controller. This can be done in this manner, characterizing the network under study, designing a membership function that analyzes the increase of biogas electrical power, designing a fuzzy rule that sticks in the increase of biogas electrical power output, designing a Simulink model for Improving biogas electrical power output using fuzzy logic controller and comparing the percentage biogas electrical power increase with and without fuzzy controller. The result obtained shows that biogas electrical power output without using fuzzy is 8KW while when fuzzy is incorporated is 10.77KW which is 14.78% increase when fuzzy controller is incorporated than when it was not imbibed.

Combined with the advantages of Wavelet threshold denoising method and data fusion technology. A data processing method of thermal measurement based on wavelet transform and data fusion is proposed. After decomposing the thermal measurement signal of each measuring point separately by wavelet decomposition, the high frequency components are first filtered by the threshold noise reduction method, and then the signal of each measuring point after noise reduction is got by wavelet reconstructing to reduce the influence of noise, and then , we normalize the signal of each measuring point, and make the data fusion based on the least mean square of the normalized measuring points, so as to obtain a better reconstructed signal. The experimental results show that this method improves the accuracy and reliability of the measured data and makes the signal features more apparent.

The main objective of this work was to evaluate the physico-chemical and microbiological qualities of dexamethasone sodium phosphate injection in the city of Douala. The experimental type was conducted from December 2016 to June 2017. It consisted of carrying out tests of physic-chemical and microbiological parameters on 14 batches of injectable DSP, conditioning, pH, TLC identification, dosage of active ingredient, the clarity, nominal volume and sterility of the drug were analyzed. The technics used were a visual inspection, thin layer chromatography, UV/visible spectrophotometry and microbiological technics, were that of direct seeding. The results were compared in each sector (formal and informal) and in both. Thus, it was found that the injectable DSP, which came from the formal sector had a non-compliance rate of 12.7%, while that from the informal sector a non-compliance rate of 39.7%. In both sectors, the injectable DSP had a non-compliance rate of around 26.2%. Both formal and informal circuits were all affected by non-compliance, although there is a predominance in the informal circuit.

According to the non-stationary characteristics of wind power, a novel wind power combined multi-step prediction model based on differential auto regressive moving average model in variational mode decomposition and time series analysis is proposed. Firstly, the wind power sequence is subjected to variational mode decomposition to reduce the non-stationary characteristics of the wind power sequence. Secondly, the ARIMA model is established for each component. Finally, the component prediction results are superimposed to obtain the final wind power prediction value. The experimental results show that the proposed combined prediction model has higher prediction accuracy.

The 17-4PH stainless steel (17-4PH SS) parts were fabricated by using a metal injection moulding (MIM) route that utilizes three binder systems comprising of palm stearin (PS), thermoplastic natural rubber (TPNR), polyethylene (PE), paraffin wax (PW) and stearic acid (SA). The 17-4PH SS powder was mixed with binders at powder loading of 65% vol by using a z-blade mixer for 2 hours at a temperature of 180°C to produce a homogeneous feedstock. The feedstock completely filled the mold cavity at a temperature of 180°C and pressure of 400 bars. A two-stage debinding process (solvent and thermal) was performed to remove binders in green parts. Debound parts were sintered at temperature ranging from 1300°C to 1380°C for 2 hours. The microstructures, physical and mechanical properties of the sintered parts were evaluated in order to determine the feasibility of binder. Among the three binder systems considered herein, PW/PE/SA appeared to produce optimum sintered properties while PS/TPNR produced the lowest. Experimental results have also demonstrated that comparable sintered properties could be obtained from the PS/PE at higher sintering temperature. In summary, this work has indicated that bio-composite binder systems, PS/TPNR and PS/PE could be considered as a promising binder in MIM of 17-4PH SS.

In this study, a solid state processing tool for microstructure modification and material properties enhancement; friction stir processing (FSP) was applied on the surface of as-cast Al-Si-Cu-Ni aluminium alloy. Samples were subjected to FSP using fixed tool rotation speed 1400 rpm and traverse speed 42 mm/min, with tool angle tilted 3˚.The influence of the FSP on the microstructure and tensile properties of the cast AlSi-Cu-Ni alloy samples were studied. Microstructural evolution of the samples was investigated using optical microscope (OM) and scanning electron microscope (SEM), tensile test carried out at 1 mm/min cross-head speed. The results showed that FSP improved the tensile strength of the samples by decreasing particles size and porosity. FSP improved the alloy strength by about 54%.

Scheduling the final project is a problem that is often faced by a college. Because there are many criteria that can be used as a reference for preparing the schedule. In the process of schedule preparation has several requirements are needed, such us lecturer teaching schedule should not clash with the schedule of final project. The availability of the chief examiner, timer and rooms for test. Therefore, it need an optimum and efficient method in determining the criteria on scheduling the final project. In this optimization process uses the method of genetic algorithm. Genetic Algorithm (GA) is algorithm that in solving the problem using crossover operator and mutation operator to obtain the desired cross bits. It aims to get the optimal attribute value in terms of fitness equation from chromosome. The result of the training show GA can produce the optimal criteria value of scheduling the final project criteria, so that can be used by the college as the preparation of the final project schedule.