Path design and optimization with obstacle avoidance via reinforcement learning

For the last couple of decades, finding an optimized drilling path has been one of the key concerns for drilling engineers. It takes a couple of months to plan a well for a large number of people. The motive of this thesis is to find the optimal drilling path based on coordinates. To trace the optimal path, this thesis will apply the reinforcement learning algorithm in Matlab. Another approach for this thesis is to find the shortest path by avoiding collision in a threedimensional grid view

Research Notes : India : Recent advances in mutation-breeding research in soybean in India

In spite of high yielding ability of Birsa Soybean-1 for the plateau re-gion of Bihar, it has not become popular among the farmers because of its black seed-coat color. The seeds of Birsa Soybean-1 were irradiated with different doses of gamma rays at FCI Sindri, Bihar (India) in 1979. Proge-nies of a yellow-seeded 50 Kr. M-2 plant in M-3 gave very promising and inter-esting plant types (Prakash et al., 1984)

Research Notes: Soybean breeding research in India

Soybean (Glycine max (L.) Merrill) is the miracle crop of the twentieth century. It is a new introduction to Indian agriculture. In view of chronic shortage of protein and oil in this country, soybean should be welcome introduction to provide the much needed stability and boost to the production of these two essential items of food (Saxena, 1975)

Enhancement of Web Security Against External Attack

The security of web-based services is currently playing a vital role for the software industry. In recent years, many technologies and standards have emerged in order to handle the security issues related to web services. This paper shows techniques to enhance the security of web services, and some of the recent challenges and recommendations of a proposed model to secure web services. It shows the security process of a real life web application, which includes; HTML5 forms, login security, and a single signon solution. This paper also aim to discuss the ten (10) most common web security vulnerabilities and how to prevent the web application from three (3) of the vulnerabilities. Amongst them are; SQL Injection, Cross Site Scripting and Broken Authentication, and Session Management

A Machine Learning Approach for Driver Identification Based on CAN-BUS Sensor Data

Driver identification is a momentous field of modern decorated vehicles in the controller area network (CAN-BUS) perspective. Many conventional systems are used to identify the driver. One step ahead, most of the researchers use sensor data of CAN-BUS but there are some difficulties because of the variation of the protocol of different models of vehicle. Our aim is to identify the driver through supervised learning algorithms based on driving behavior analysis. To determine the driver, a driver verification technique is proposed that evaluate driving pattern using the measurement of CAN sensor data. In this paper on-board diagnostic (OBD-II) is used to capture the data from the CAN-BUS sensor and the sensors are listed under SAE J1979 statement. According to the service of OBD-II, drive identification is possible. However, we have gained two types of accuracy on a complete data set with 10 drivers and a partial data set with two drivers. The accuracy is good with less number of drivers compared to the higher number of drivers. We have achieved statistically significant results in terms of accuracy in contrast to the baseline algorith

Research Notes : India : Mutation breeding research in soybean in India

Systematic mutation breeding research in India was started at Ranchi Agricultural College, Kanke, Bihar, India, around 1971 by Haque and his co-workers. Choudhary (1972) studied induced polygenic variability in the R-II generation in the variety of \u27Sepaya Black\u27 of soybean. Choudhary (1972) reported that 10 Kr radiation treatment of gamma rays was effective in shifting the mean values in positive direction for various quantitative characters including seed yield

Evaluation of performances and selection response of three indigenous chicken genotypes at seventh-generation

The present study was conducted to assessed the performances of three native chicken genotypes under intensive management. A total of 1042 day-old chicks comprising of 3 types of chicken, namely Naked Neck (NN-381), Hilly (HI-313), and Non-descript Deshi (ND-348), were Hatched for this study. The seventh generation, selection was practiced at 40 weeks of age according to 40-week body weight (BW), egg production (EP) up to 40-week, egg weight (EW) at 40 weeks, and age at maturity (ASM). The data were analyzed in a CRD. Day-old chick weight was significantly (P < 0.001) highest in HI (32.52 ± 0.32 g). Significant (P < 0.001) body weight differences among the genotypes were observed at the 12th week of age. Genotype had a significant effect on chick mortality. The average age at the first egg of ND 145.54days was 8.81 days earlier than that of HI 154.35days. Hatchability on fertile eggs differed significantly (P < 0.05) among the genotypes. The percentage of dead germ was affected (P < 0.001) by genotype. Feed consumption from 9 to 16 weeks showed a significant (P < 0.001) variation in feed intake among the native chicken genotypes. EP of ND, HI, and NN birds were expected to increase by 0.875, 1.585, and 0.255 %, respectively. The EW of ND, HI, and NN birds were expected to increase by 0.205, 0.250, and 0.015g, respectively. Responses to selection for EP and EW for three genotypes (ND, HI, and NN) were expected to be positive (increase). It is concluded that the Hilly genotype may be chosen for meat production and the Non-descript Deshi genotype for egg production

Identification and Characterization of Azo Dye Decolourizing Bacterial Strains, Alcaligenes faecalis E5.Cd and A. faecalis Fal.3 Isolated from Textile Effluents

The study was designed for isolation and characterization of azo dye decolourizing bacteria which is a prerequisite for developing a microorganism-facilitated treatment of polluting dyes. In this study nine types of bacteria which were able to decolourize three types of azo dyes (Blue H/C, Red 3B and Yellow 3R dye) were isolated from textile effluents collected from Gazipur industrial area in Bangladesh. Depending on 16S rDNA analysis, the most efficient decolourizing bacterium for the Blue H/C and the Red 3B dye was identified as Alcaligenesfaecalis strain E5.Cd while that for the Yellow 3R dye was identified as Alcaligenesfaecalis strain Fal.3. After characterization, both A. faecalis E5.Cdand A. faecalis Fal.3 were found to grow optimally at 35 0C and at pH 7 and pH 8, respectively. Both of these strains were sensitive to all antibiotics studied except for Bacitracin. Also, both strains showed maximum decolourization activities after 96 hours incubation in MS media at pH 7 (up to 93%) and pH 8 (up to 94%), at 35 0C temperature ( up to 91%), at 50 ppm initial dye concentration (up to 92%), at 20% inoculum size (up to 93%), and at supplementation of 1% co-substrate (up to 93%)

Bacteriological Evaluation of Drinking Water of Rajshahi City, Bangladesh

Access to pathogen free safe drinking water is one of the major challenges of the 21st century for most of the people of world. According to WHO guidelines, 100 ml sample of safe drinking must be free of total coliform, fecal coliform and E. coli. Hence, this study was designed for bacteriological evaluation of drinking water collected from different restaurant in Rajshahi city, Bangladesh. Among 10 samples, no detectable E. coli was found in 5 water samples (100 ml each) while 8-50 detectable E. coli in 100 ml water sample was found in the remaining 5 samples which exceeded the BDS and WHO standard of drinking water. Four randomly selected isolates (B1, B2, B3 and R) which were isolated from different water samples were subjected to 16S rRNA gene sequencing. It was found  that the 16S rRNA sequence of isolate B1, B2 and B3 had 98% similarity to that of Enterobacter asburiae, Escherichia coli and Acinetobacter sp respectively. Similarly, 16S rRNA sequence of isolate R had 99% similarity to that of Klebsiella pneumonia. Results of biochemical analysis revealed that all four isolates were negative to Catalase, KOH and Oxidase test while variations were found for other tests. Similarly, all four isolates were able to ferment all tested carbohydrates except cellulose. The optimum pH and temperature for the growth of the all isolates was pH 7.0 and 37ºC. It was found that all the isolates were sensitive to majority of the antibiotics used

Path design and optimization with obstacle avoidance via reinforcement learning

For the last couple of decades, finding an optimized drilling path has been one of the key concerns for drilling engineers. It takes a couple of months to plan a well for a large number of people. The motive of this thesis is to find the optimal drilling path based on coordinates. To trace the optimal path, this thesis will apply the reinforcement learning algorithm in Matlab. Another approach for this thesis is to find the shortest path by avoiding collision in a threedimensional grid view