Software Development Standard and Software Engineering Practice: A Case Study of Bangladesh

Improving software process to achieve high quality in a software development organization is the key factor to success. Bangladeshi software firms have not experienced much in this particular area in comparison to other countries. The ISO 9001 and CMM standard has become a basic part of software development. The main objectives of our study are: 1) To understand the software development process uses by the software developer firms in Bangladesh 2) To identify the development practices based on established quality standard and 3) To establish a standardized and coherent process for the development of software for a specific project. It is revealed from this research that software industries of Bangladesh are lacking in target set for software process and improvement, involvement of quality control activities, and standardize business expertise practice. This paper investigates the Bangladeshi software industry in the light of the above challenges.Comment: 13 pages, 3 figures, 11 table

Effects of bottom substratum on survival and growth of early juveniles of blue swimming crab, (Linnaeus, 1758) in captivity

Aim: Cannibalism remains a limiting factor during the nursery culture of crabs. This study was undertaken to improve the rearing techniques by investigating the impact of bottom substratum on crablet survival and growth. The knowledge gained from the research will be useful for the communal seed culture and development of crab farming, which are important factors regarding farmers' job stability in the future. Methodology: Blue swimming crab, Portunus pelagicus (first settled (C1 crabs); initial average weight and SD of 0.02 ± 0.01g) were cultured in glass aquarium (90 x 44 x 34 cm) and their survival and growth were assessed after 22 days of culture in four types of substratum such as control (none), sand, soil, or sand + soil. All treatments had 25 juvenile crabs, each of which was triplicated. Feeding was done twice a day (9 am and 5 pm) to apparent satiation. Results: Survival of early juvenile crabs cultured with sand was substantially higher at 65.33 ± 6.11% than those cultured with soil, sand + soil or control at 29.33 ± 10.07%, 28.00 ± 8.00%, and 21.33 ± 6.11%, respectively. Growth performance (such as final weight, weight gain and specific growth rate) of the early juvenile of P. pelagicus in all treatments were not significantly different (p>0.05). Interpretation: Overall, the best survival was achieved with sand substratum and can be recommended as a mean of reducing cannibalism during the early nursery rearing of blue swimming crab juveniles under captive culture conditions

An Automated System for Garment Texture Design Class Identification

Automatic identification of garment design class might play an important role in the garments and fashion industry. To achieve this, essential initial works are found in the literature. For example, construction of a garment database, automatic segmentation of garments from real life images, categorizing them into the type of garments such as shirts, jackets, tops, skirts, etc. It is now essential to find a system such that it will be possible to identify the particular design (printed, striped or single color) of garment product for an automated system to recommend the garment trends. In this paper, we have focused on this specific issue and thus propose two new descriptors namely Completed CENTRIST (cCENTRIST) and Ternary CENTRIST (tCENTRIST). To test these descriptors, we used two different publically available databases. The experimental results of these databases demonstrate that both cCENTRIST and tCENTRIST achieve nearly about 3% more accuracy than the existing state-of-the art methods

DTCTH: a discriminative local pattern descriptor for image classification

Abstract Despite lots of effort being exerted in designing feature descriptors, it is still challenging to find generalized feature descriptors, with acceptable discrimination ability, which are able to capture prominent features in various image processing applications. To address this issue, we propose a computationally feasible discriminative ternary census transform histogram (DTCTH) for image representation which uses dynamic thresholds to perceive the key properties of a feature descriptor. The code produced by DTCTH is more stable against intensity fluctuation, and it mainly captures the discriminative structural properties of an image by suppressing unnecessary background information. Thus, DTCTH becomes more generalized to be used in different applications with reasonable accuracies. To validate the generalizability of DTCTH, we have conducted rigorous experiments on five different applications considering nine benchmark datasets. The experimental results demonstrate that DTCTH performs as high as 28.08% better than the existing state-of-the-art feature descriptors such as GIST, SIFT, HOG, LBP, CLBP, OC-LBP, LGP, LTP, LAID, and CENTRIST