As Bangladesh is an agricultural country, cows have a great influence on our economy. However, there is no cow-related work or dataset accessible online in the fields of machine learning and artificial intelligence. This study aims to predict cow price ranges using any cow picture. Cow images were collected from different online e-commerce sites which are selling cows and mainly attempted to predict the price range of cows based on the images of the cows. Cows are divided into four classes based on their price range namely low, medium, high, and very high classes. A machine learning-driven approach has been taken for the prediction where convolutional neural network (CNN) is used as an image classifier and linear regression is used for predicting the prices. Our result shows that the price range of a cow can be predicted with an accuracy of 70%

The economic growth of Bangladesh largely depends on the petroleum industry. The most important part of petroleum industry is the production system. However, accident is a common scenario in the petroleum industry. In fact, several risks may be involved during the drilling, production, and transportation phase of this industry. In the case of comprehension, these risks associated at an early stage may acquire the appropriate measures aligned to them. This study investigates personnel perceptions about risk and safety involved in production system of the petroleum industry. To perform this research, the data were collected from three fields Kailashtila, Haripur & MSTE Plant operated by Sylhet Gas Fields Limited (SFGL), Bangladesh. The collected data were analyzed by IBM SPSS 20. The frequency analysis performed and risk matrix generated in this study. The Frequency analysis shows that the overall safety situations. Moreover, the results of the risk matrix pointed out the risk level as low, medium or high. At the end of study, based on the implicit risks, the necessary measures are recommended for the future security of the industry.

Exponential growth of urbanization increases the unused rooftop space in the city area. The rooftop fish culture is the alternative way to utilized rooftop space and increases the production. In rooftop fish culture foremost challenge is to maintain water quality deteriorated by feces and leftover feed. The study aim was to identify the suitable plants for evaluating the ability of the plants as a part of the biological filter by extracting toxic compound from the fish tank. Research was designed by setup seven treatments (Tws, Tc, Tts, Tcs,Twc, Tip and Tm) with three replicates each by using seven locally accessible plants (water spinach, coriander, taro stem, Ceylon spinach, water cress, Indian pennywort and mint) for biological filtration. Plant beds of the filter system were prepared by using sand, brick, coal and coir. In each fish tank 50 post larvae (PL) of prawn was stocked properly and 35-40 plants in each treatment bed. Water samples were collected to measure pH, DO, temperature, ammonia, phosphate and ammonium. The water temperature (24oC to 26°C), pH (7.78 to 8.8) and dissolve oxygen (DO) were in the optimum range for fish culture. Results showed that the significantly (P<0.05) highest phosphate absorption was observed in Tws (0.96 0.89 mg/l) which was followed by Tm (0.57 0.33 mg/l), Tcs (0.54 0.47 mg/l), Tts (0.38 0.35 mg/l), Twc (0.37 0.23 mg/l), Tc (0.26 0.21 mg/l) and Tip (0.18 0.11 mg/l), respectively. In case of ammonia, the significantly highest ammonia was observed in Twc (0.18 0.19) where lowest in Tws (0.04 0.05) mg/l. On the other hand the highest ammonium was observed in Twc where lowest in Tws & Tc. It was also found that the Tws (water spinach) was absorbed high amounts of phosphate, while Twc (water cress) absorbed high amount of ammonia and ammonium. The Tcs showed high yield of plants vegetables (3000 gm/bed), it might be the cause of higher nutrient absorption. The highest yield of the prawn was found in the Twc (321 gm/tank), because this treatment showed highest amount of ammonia and ammonium absorption the most toxic part for fish production. This research demonstrates that using of plants as biological filter provide significant nutrient recycling and increase the prawn and vegetables production.

The IoT (Internet of Things) is now a trendy technology with its numerous apps in multiple areas. It includes a heterogeneous amount of Internet and mutually linked devices. Since the IoT network is characterized by tiny assets that produce less energy and are more flexible, this number of machines is difficult to monitor. SDN (Software Defined Network) is a new network model that facilitates the creation and introduction of fresh networking abstractions, simplifies the management of network and facilitates network development. In this paper, by leveraging the fundamental characteristics represented by Software Defined Networks (SDN), we present an ontological security architecture for IoT networks. Our security architecture restricts access to independently verified IoT devices via the network. To secure the flows in the IoT network infrastructure, we introduced an extra layer and provide a lightweight protocol to authenticate IoT systems. Such an advanced strategy to protection containing IoT device authentication and allowing approved flows can assist secure IoT networks against malicious IoT devices and threats.

The experiment was conducted over 120 days from March to June 2019 in Bagerhat sadar upazila, Bagerhat. The study was categorized into four treatments indicated as T1 (ACI feed), T2 (Quality feed), T3 (Mega feed) and T4 (control) with three replicates. The experimental ponds were stocked with shrimp PL at same density of 4 nos./m2. Ponds were treated with agricultural lime based on soil and water pH and fertilized with urea and Triple Super Phosphate depending on water transparency and depth. Different water quality parameters were determined at ten-day intervals. Parameters of water were within acceptable ranges of shrimp culture. Higher growth (30.36 g) of shrimp was achieved in T2 compared to T1 (28.53 g), T3 (27.43 g) and T4 (22.85 g). Growth and survival rate of shrimp were comparatively lower in T4 at the same stocking density. Significantly (p<0.05) higher production of shrimp was obtained in T2 (971.52 kg/ha) than those of T1 (855.90 kg/ha), T3 (757.07 kg/ha) and T4 (566.68 kg/ha). Highest net profit (US$ 2570.2/ha) of shrimp farming was found in T2 than that of T1 (US$ 2105.7), T3 (US$ 1786.6) and T4 (US$ 1298.1). Results of the study indicate that among different commercial feeds Quality feed (T2) is better than other feeds in respect of survival rate, growth, production and net profit. So, farmers may be encouraged to use Quality feed for getting higher production and significant return in a short period of time.

Natural gas is one of the primary energy sources of Bangladesh. Demand of natural gas in Bangladesh increasing day by day in various sectors. But, due to limited resources, energy crisis increasing gradually. This research work deigned to find out the natural gas crisis via forecasting gas demand and production. At the end, it also analyzed the future of CNG and LPG based vehicles in Bangladesh as an alternative of natural gas dependency. The prediction of gas demand and production has been conducted based on the data from Petrobangla. And the future of CNG and LPG based vehicles were analyzed based on different CNG & LPG conversion company data. Demand forecasting presented three scenarios; “scenario A, scenario B and scenario C” and production forecasting has been displayed as three cases; “case A, case B, case C”. The Comparison of CNG and LPG has been made based on different parameters like conversion cost, calorific fuel value, fuel cost, mileage, risk of explosion of fuel cylinder, carbon emission etc. The outcomes of gas demand forecasting represented that gas demand is growing in every scenario. The results of production forecasting denoted as existing gas fields production is decreasing gradually. It also indicated, if new reserves would be discovered, then the production will be maximized. On the other hand, CNG conversion rate will be declined due to the shortage of natural gas. In conclusion, the investigation of different parameter of CNG & LPG confirmed, LPG is suitable for cope up with the future crisis. Hence LPG based vehicles need to take place of CNG based vehicles.