The idea suggested in this paper consists in forensic sketches that have to be drawn and furthermore analyzed from an emotional face recognition point of view. The detection itself is more effective and useful to further identify the future behavior and possible reactions of the suspect based on the emotional analysis of the areas on the face. The study embraces this idea and experiments with forensic like sketch images within a system that is trained on a FER+ database, and executed using two different schemes, ML (Multi-Label learning) and CEL (Cross-Entropy Loss). The conducting experiment resulted that for forensic sketch images, CEL system is more efficient than ML training method 69.77% vs 69.05% for the best test accuracy, even if the experiment on the standard image equivalents proved otherwise.

In this study, drying characteristics of two improved parboiled varieties of rice (FARO 44 and FARO 52) at air temperatures of 36oC, 45oC and 50oC were investigated. The drying data were fitted to seven thin layer drying models, namely, Agbashlo et al., Henderson and Pabis, Logarithmic, Newton, Two Term, Verma et al., and Wang and Singh. The models performances were evaluated by comparing the coefficient of determination (R2), standard error (SE) and relationship between the experimental and predicted moisture ratios through nonlinear regression analysis. The main factor controlling the drying rate was temperature and falling rate period characterized the entire drying process. The moisture content of the parboiled rice samples was found to be in the range of 26.33-27.57% (wb) which reduced to 8.87-9.98% (wb) for FARO 44 and 29.37-30.27% (wb) which reduced to 14.33-14.98% (wb) for FARO 52 after drying for various temperatures of 36°C, 45°C and 50°C for eight hours. The R2 and SE varied between 0.9953 - 0.9997, 0.9917- 0.9998, 0.9991 - 0.9999 and 0.9907 - 0.9994, 0.9986 – 1.0000 0.9300- 1.0000 for FARO 44 and FARO 52 respectively for the seven models. The three best models at 36°C for FARO 44 was the Logarithmic followed by Modified Henderson, Pabis and Newton. At 45°C, the Two term model was the best followed by Verma et al., Modified Henderson and Pabis. While for FARO 52 drying behaviour at each drying temperature of 36°C, the best model was the Two term followed by Wang and Singh and Logarithmic. The Two term model was the best model at 50°C. The Two term drying models satisfactorily described the drying behaviour which produced randomized residual plots with highest R2 and lowest standard error of estimates and gave best fitting curves.

Bangladesh is used to struggle with several natural disasters and has become one of the most earthquake vulnerable countries of the world. The nature and the distribution of the earthquake events in different seismic zones of Bangladesh are related to various man-made factors. This study is dealing with the impact of these factors which are leading to the incidence of earthquakes. Geographic information system (GIS) is used to analyze earthquake data graphically. Bivariate analysis is conducted using t-test approach for hypothesis testing purpose. Availability of gas and oil has been turned out as significant in the results on earthquake occurrences. Three Poisson regression models, along with bivariate analysis, are employed in this study to assess the occurrence of earthquakes in relation with having minerals in Bangladesh. The results give evidence that the presence of minerals is vulnerable to earthquake and production of minerals increases the vulnerability. The presence of gas and oil in the related districts significantly increases the expected number of earthquakes. Keeping similarity with this result, the districts where gas and oil production are running also experience significantly more frequency of earthquakes compared to that of other districts. It is also found from the analysis that the more amount of gas the districts have, the higher the expected number of earthquakes is in that districts. However, neither presence of coal nor running of coal production has any significant effect on earthquake occurrence.

Development of biodegradable metal implants is a complex problem because it combines engineering and medical requirements for a material. This paper discusses the development of magnesium powder using Metal Injection Moulding (MIM) techniques that can help in the design of biodegradable metallic implants. One of the most important factors in the process of biodegradable implants is to study the powder characterization, mixing behaviour and rheological properties of the powder/binder mixture, which should be monitored and controlled to address the medical concern of biocompatibility. Particle size analysis, scanning electron micrograph (SEM), thermogavimetric analysis (TGA) and differential scanning calorimeter (DSC) were performed in order to determine the characteristics of magnesium powder and binder components. The feedstock were prepared using powder loading of 0.61, 0.63, 0.65 and 0.67 with binder formulations of 50% PW-30% PP-10% SA-10%. The flow properties were measured using a capillary rheometer in the shear rate range expected to occur during metal injection molding.

Data protection and transparency are highly recommended modern approaches for any transaction domain. The proposed layer model will provide an improved and secure approach for transporting of goods using crypto currencies and excluding intermediate parties. Paper gives temporarily overview of crypto currency, logistics movement channels, block chain evaluation, challenges, types, applications and layer model that shows movements of good from scratch (source) to delivery (client destination) through secured transactions medium, excluding intermediate parties (banks etc.) storing signatures in distributed ledger.

The economic implications of using solely wind energy or solar photovoltaic (PV) system for electric power generation in Nigeria is considered in this work. Twelve states from the six geopolitical zones of Nigeria were used as case studies for wind energy utilization while 6 states were used for solar energy usage. Wind speed and solar radiation data for the state capitals were used for the analysis. The net present value (NPV) and the levelized cost of electricity (LCOE) for each state for a project lifespan of 20 years was estimated for each power system in the various states using discount rate equivalent to the prevailing interest rate (16%) in Nigeria and lower values. At 16% discount rate for wind energy system, only 4 states gave positive NPV while at 8% discount rate 9 states have positive NPVs. For the solar PV system, the NPVs are negative for all the 6 states at 16% discount rate while only one location with the highest average annual solar radiation of 6.4 kWh/m2 day gave positive NPV at 8% discount rate. The LCOE is smaller for wind energy systems in many of the locations considered. When energy is not discounted, the highest and the lowest LCOE for wind energy system are 0.1937 $/kWh and 0.0167 $/kWh respectively while the respective values for solar PV system are 0.0615 $/kWh and 0.0415 $/kWh. The LCOE when energy is discounted is higher and the average value obtained either system is higher than the price of electricity in Nigeria but lower than the electricity price in the UK and the USA. Thus for wind and solar PV systems to be more economically viable for electricity generation in many locations in Nigeria, the current installation costs should come down and or the price of electricity should go up.

Face recognition presents a challenging problem in the field of image analysis and computer vision as such a large number of face recognition algorithms have been developed in last decade. In this paper firstly I present an overview of face recognition and discuss its application and technical challenges. Thereafter I represent the various face recognition techniques. This includes PCA, LDA, ICA, Gabor wavelet, soft computing tool like ANN for recognition and various hybrid combinations of these techniques. This review investigates face recognition and all these methods of face recognition with parameters that have challenges like illumination, pose variation and facial expressions.