Experimental investigation on the production of biogas from waste food

The production of biogas has been a substantial target to be utilized globally, especially in the agricultural sector. Most organic waste that is being produced from other forms of renewable energy systems is mainly used to reduce greenhouse emission (GHG), which as well reduces the daily consumption of fossil fuels. Anaerobic Digestion (AD) has been studied widely in recent years where its implementation in the industry has seen a mitigating impact on greenhouse gases. Unrestricted discharge of the big amount of waste food (WF) has become the main effect of severe environmental pollution worldwide. Among the various treatment methods, anaerobic digestion (AD) of waste food allows its valorization and the biogas produced can be used as biofuel enhancing the gas supply. In this study, a mechanical pre-treatment with Hollander beater has been applied to break down the particle size of waste food in the way to increase feedstock specific surface areas in other to enhance biogas production. Following, the pre-treatment of waste food during 30 min beating time, the biogas yield achieved a value of about 610.33 ml/gTS. Accordingly, a response surface methodology (RSM) can be used to critically evaluate the effects of process parameter (beating time and temperature) to the output response (biogas production). Pre-treated waste food by Hollander beater at beating time of 30 min enhances biogas production by 80%. An optimum biogas yield was achieved with pre-treatment of waste food at a beating time of 30 min.     

Fault isolation in manufacturing systems based on learning algorithm and fuzzy rule selection

Neural Computing and Applications - This paper addresses the fault detection and isolation problem in manufacturing systems. Some of these systems can be affected by several faults, a first way of...     

Robust palm and knuckle ROI extraction in unconstrained environment

Pattern Analysis and Applications - Palm and knuckle prints can be extracted from a hand using a low-cost camera in a contactless manner. This makes the process of palm and knuckle recognition fast...     

2D/3D Shaped Radiation Patterns of Sunflower and Conformal Antenna Arrays Using Phase Synthesis

2D and 3D beam synthesis from different antenna array arrangements are investigated in this paper. Planar sunflower, conformal cylinderical and spherical helical array arrangements are studied. The particle swarm optimization (PSO) technique is used to predict the phase distribution on the array elements. The beam synthesis is achieved by comparing the array factor with a predetermined mask with both upper and lower limits according to the intented application requirements. Different 2D and 3D masks are used in beam synthesis as pencil, flat-top, and cosecant single beam are predicted. The planar sunflower antenna array is investigated due to its high gain, low side-lobe level (SLL) below ??20 dB and its compact size. The phase distribution of sunflower array is estimated using PSO to radiate dual-beams in different planes. Dual-beam with pencil, flat-top, and cosecant beams are obtained with different half-power beam widths. 3D conformal antenna arrays of cylindrical and spherical helical arrangements are studied. Each 3D conformal array consists of four arms shifted in position by 90° orintation angle. Each arm is designed to radiate single beam in a specific direction. Four-beams are considered to radiate in the directions of θ_1,2,3,4?=?30°, and ?₁?=?0°, ?₂?=?90°, ?₃?=?180°, and ?₄?=?270° with SLL optimized below ??17 dB. The array arrangements analysis is based on the array theory formulation, through the implemention of the estimiated equation using a home programmed MATLAB code.

     

Improving the reconstruction efficiency of sparsity adaptive matching pursuit based on the Wilkinson matrix

Sparsity adaptive matching pursuit (SAMP) is a greedy reconstruction algorithm for compressive sensing signals. SAMP reconstructs signals without prior information of sparsity and presents better reconstruction performance for noisy signals compared to other greedy algorithms. However, SAMP still suffers from relatively poor reconstruction quality especially at high compression ratios. In the proposed research, the Wilkinson matrix is used as a sensing matrix to improve the reconstruction quality and to increase the compression ratio of the SAMP technique. Furthermore, the idea of block compressive sensing (BCS) is combined with the SAMP technique to improve the performance of the SAMP technique. Numerous simulations have been conducted to evaluate the proposed BCS-SAMP technique and to compare its results with those of several compressed sensing techniques. Simulation results show that the proposed BCS-SAMP technique improves the reconstruction quality by up to six decibels (dB) relative to the conventional SAMP technique. In addition, the reconstruction quality of the proposed BCS-SAMP is highly comparable to that of iterative techniques. Moreover, the computation time of the proposed BCS-SAMP is less than that of the iterative techniques, especially at lower measurement fractions.     

Natural convection mass transfer behaviour of vertical and horizontal cylinders embedded in an inert fixed bed of Raschig rings

Natural convection mass transfer at vertical and horizontal cylinders embedded in a fixed bed of Raschig rings was studied by an electrochemical technique which involves measuring the limiting current of copper deposition from acidified CuSO₄ solution. Variables studied were Raschig ring diameter, physical properties of the solution and cylinder height in case of vertical cylinders or cylinder diameter in case of horizontal cylinders. Under the present conditions where high porosity beds were used, a slight decrease in the rate of mass transfer was observed in the case of vertical cylinders whereas no rate decrease was observed in the case of horizontal cylinders in the bed. Implication of the present results for the design of fixed bed reactors operating at low feed rates and containing a vertical or horizontal array of tubes for heat exchange with the bed was noted.     

Arrangement of Reactive Power Compensation Units in the Radial Distribution Network of Moscow Oblast

Distribution networks are the direct end-consumer connection part of an electric power system. With the development of technology, advent of new current-using equipment, and increasing population density, these networks are becoming increasingly more and more complex, elements more loaded, and power and voltage losses on the line more significant, which leads to violations of standard requirements. These problems are considered using the example of a section of the Moscow oblast network. The study presented in this article is part of the research project aimed to improve the quality of electric power in the distribution network by analyzing the current state and elaborating corrective steps. The measurements were taken using electric power quality analyzers at maximal and minimal loads. To overcome a high negative voltage deviation, the reactive power compensation unit is proposed. The procedure proposed in this article to solve the given problem consists of two phases. In phase one, loss sensitivity factors (LSFs) are defined and candidate nodes selected for installing the compensation units. This makes it possible to considerably reduce the area of searching for the optimization algorithm and, therefore, cut down the calculation time and improve the algorithm’s convergence. In phase two, the hybrid particle swarm technique is applied to optimally arrange the compensation units among the selected nodes, and choose their capacity. The hybrid optimization technique includes the particle swarm technique (PST) and the quasi-Newtonian algorithm applied after meeting the PST stopping criterion. The quasi-Newtonian algorithm is applied to cut down the time for executing iterations and making the PST more convergent. Numerical modelling is performed in the MATLAB software environment. The measurements in the distribution network of the Moscow oblast served to construct a design model with 111 nodes. According to the measurement results, the voltage level in the consumer coupling nodes considerably overrides the limits defined by GOST (State Standard) 32144–2013. Serious problems with electric power in the mains are connected with inadmissible values of established voltage deviation. The proposed hybrid algorithm of arranging reactive power compensation units makes it possible to reduce the losses of electric power in the mains, reduce the voltage deviation, and increase the line power factor.     

Performance Evaluation of Sleep Mode on Power Saving in WiMAX IEEE 802.16m and LTE DRX

Power saving represents a vital role in mobile communications networks such as IEEE 802.16m and LTE. Modern user equipment (UE_s) require high data rates and low power consumption. It is found that arranging sleep mode mechanisms ensures UE battery longer lifetime. In this paper, different sleep mode mechanisms are investigated for both IEEE 802.16m and LTE networks. The analyses are based on Markov and Semi-Markov chains. It is focused on the determination of UE transition state. Web traffic model parameters were considered in MATLAB simulation and a comparison assessment was conducted between WiMAX IEEE 802.16m and LTE DRX. It was found that LTE DRX sleep mode provides more power saving than WiMAX IEEE 802.16m sleep mode. The study is now implemented for 5G networks with encouraging results.     

Hybrid wavelet measurement matrices for improving compressive imaging

Compressive sensing principle claims that a compressible signal can be recovered from a small number of random linear measurements. However, the design of efficient measurement basis in compressive imaging remains as a challenging problem. In this paper, a new set of hybrid wavelet measurement matrices is proposed to improve the quality of the compressive imaging, increase the compression ratio and reduce the processing time. The performance of these hybrid wavelet matrices for image modeling and reconstruction is evaluated and compared with other traditional measurement matrices such as the random measurement matrices, Walsh and DCT matrices. The compressive imaging approach chosen in this study is the block compressive sensing with smoothed projected Landweber reconstruction technique. The simulation results indicate that the imaging performance of the proposed hybrid wavelet measurement matrices is approximately 2–3 dB better than that obtained using Gaussian matrix especially at higher compression ratios.