BN-DRISHTI: Bangla Document Recognition through Instance-level Segmentation of Handwritten Text Images

Handwriting recognition remains challenging for some of the most spoken languages, like Bangla, due to the complexity of line and word segmentation brought by the curvilinear nature of writing and lack of quality datasets. This paper solves the segmentation problem by introducing a state-of-the-art method (BN-DRISHTI) that combines a deep learning-based object detection framework (YOLO) with Hough and Affine transformation for skew correction. However, training deep learning models requires a massive amount of data. Thus, we also present an extended version of the BN-HTRd dataset comprising 786 full-page handwritten Bangla document images, line and word-level annotation for segmentation, and corresponding ground truths for word recognition. Evaluation on the test portion of our dataset resulted in an F-score of 99.97% for line and 98% for word segmentation. For comparative analysis, we used three external Bangla handwritten datasets, namely BanglaWriting, WBSUBNdb_text, and ICDAR 2013, where our system outperformed by a significant margin, further justifying the performance of our approach on completely unseen samples.Comment: Will be published under the Springer Springer Lecture Notes in Computer Science (LNCS) series, as part of ICDAR WML 202

Challenges and Prospects of Poultry Industry in Bangladesh

Poultry industry is one of the most promising sectors for Bangladesh. This industry can provide various opportunities to increase GDP growth rate plus equitable distribution through arranging food security as well as ensuring self -employment, creating purchasing power and reducing poverty at a large scale. About 44 per cent of daily human intake of animal protein comes from livestock products. The poultry industry has been supplying quality protein to the people of Bangladesh at the lowest price in the world. The study outlined major concerns focusing on the entire problems. The followings points have been finally consider as comprehensive issues; lack of quality chicks, high price of feed, marketing problem, insufficient bank loan, lack of quality vaccine, the vaccine price is very high and bird flu. It is observed that to import poultry related products huge amount of valuable foreign exchange will be spent. We have proposed for providing subsidy to the local industry and protect safeguard to the local entrepreneurs of the poultry industry. Keywords: Poultry, Problem, Prospect, Dropping, Banglades

Coordination and Supply Chain Optimization of Agricultural Products in Bangladesh under Uncertainty

In this study, we developed four different mathematical formulations for the coordination and three stage supply chain optimization of agricultural products in Bangladesh. This research, we assumed that the farmers-retailers-distributors are coordinated by jointly participation their information. To developed a Mixed Integer Linear Programming (MILP) model and analyze the situation of inadequate production capacity for the producer as the reason for shortages. The producers will coverage these shortages by outsourcing, which decided very beginning of the SCN. This plays a very important role in deciding so as to mitigate these challenges and to extend the system performance and individual gain of the SCN. The coordinated mechanism among the participants of the market has been prominent to realize the best answer. The SCN was modeled using a formulation in MILP that maximizes the total profit and also to validate our proposed model, analyzed the total profit for real data and normal distribution data for various parameters. The formulated MILP model were solved by a mathematical programming language (AMPL) and results obtained by appropriate solver MINOS. Numerical example with the sensitivity of several parameters has been deployed to validate the models. We conclude from this study, profit of all participants increased by SCN coordination system without ant additional investment

Coordination and Three-Stage Supply Chain Optimization of Agricultural Products in Bangladesh Under Uncertainties

Abstract- In this study presents three stage supply chain network (SCN) coordination and profit optimization of agricultural products considering several uncertainties. Most of the agricultural products are in general cost expensive with high risk in probability due to its fluctuating prices. To developed a Mixed Integer Linear Programming (MILP) model and analyze the situation of insufficient production capacity for the producer as the reason for shortages. In this study to investigated supply chain network (SCN) are two distinct freelance supply organizations. SCN management has the difficulties for the disconnected and freelance economic people. Further, fast technological changes and high fight build SCN a lot of complicated. The problem of locating distribution centers (DCs) is one among the foremost necessary problems in design of SCN. The models are applied to a real case of optimization the profit before and after coordination and also to analyze the sensitivity under demand and cost uncertainty. The MILP models consider the facilities are coordinated by mutually sharing information with each other among producer, retailer and distributor. The formulated MILP model is solved by using a mathematical programming language (AMPL) and results obtained by appropriate solver MINOS. Numerical example with the sensitivity of various parameters has been deployed to validate the models. Results show that after coordination, the individual profits could be increased without any extra investment

An effective feature extraction method for rice leaf disease classification

Our society is getting more and more technology dependent day by day. Nevertheless, agriculture is imperative for our survival. Rice is one of the primary food grains. It provides sustenance to almost fifty percent of the world population and promotes huge amount of employments. Hence, proper mitigation of rice plant diseases is of paramount importance. A model to detect three rice leaf diseases, namely bacterial leaf blight, brown spot, and leaf smut is proposed in this paper. Backgrounds of the images are removed by saturation threshold while disease affected areas are segmented using hue threshold. Distinctive features from color, shape, and texture domain are extracted from affected areas. These features can robustly describe local and global statistics of such images. Trying a couple of classification algorithms, extreme gradient boosting decision tree ensemble is incorporated in this model for its superior performance. Our model achieves 86.58% accuracy on rice leaf diseases dataset from UCI, which is higher than previous works on the same dataset. Class-wise accuracy of the model is also consistent among the classes

Combined allelopathic effect of buckwheat and marsh pepper residues on weed management and crop performance of transplant aman rice

The experiment was conducted at the Agronomy Field Laboratory, Bangladesh Agricultural University, Mymensingh during the period from June to December 2016 to evaluate the suppression of weed growth through combined application of buckwheat and marsh pepper residues in transplant aman rice. The experiment consisted of three cultivars i.e. BRRI dhan56, Binadhan-12 and Nizershail, and five different crop residues with their combination such as no residues, 2.0 t ha-1 buckwheat residues, 2.0 t ha-1 marsh pepper residues, combined 0.5 t ha-1 buckwheat and 1.0 t ha-1 marsh pepper residues, combined 1.0 t ha-1 buckwheat and 0.5 t ha-1 marsh pepper residues. The experiment was laid out in a randomized complete block design with three replications. Weed population and weed dry weight were significantly affected by cultivars and crop residues treatment. The maximum weed growth was noticed with no residues treatment and the minimum was found in combined 0.5 t ha-1 buckwheat and 1.0 t ha-1 marsh pepper residues. The grain yield as well as the yield contributing characters produced at BRRI dhan 56 was the highest among the studied varieties. The highest reduction of grain yield was obtained in no residues) treatment and the lowest was obtained when combined 0.5 t ha-1 buckwheat and 1.0 t ha-1 marsh pepper residues were applied. The highest numbers of effective tillers hill-1, number of grains panicle-1, 1000-grain weight, and grain and straw yields were observed in W3 treatment. BRRI dhan56 under 0.5 t ha-1 buckwheat and 1.0 t ha-1 marsh pepper residues treatment produced the highest grain yield. Results of this study indicates that combination of 0.5 t ha-1 buckwheat and 1.0 t ha-1 marsh pepper residues showed potentiality to suppress weed growth. Therefore, crop residues could be used as an alternative tool for sustainable weed management

Clostridium Difficile Associated Diarrhea in Children with Hematological Malignancy-Experience from a Pediatric Oncologic Centre, Bangladesh

Background: Clostridium difficile Associated Diarrhea (CDAD) is considered to be one of the commonest causes of nosocomial diarrhoea worldwide. Gastrointestinal infections in the form of diarrhoea are common in pediatric oncology patients in Bangabandhu Sheikh Mujib Medical University (BSMMU), Bangladesh. The study was conducted to find out the frequency of Clostridium difficile infection (CDI) among diarrheal children with haematological malignancy. Materials and Methods: This prospective observational study was conducted from April 2012 to March 2013 at the Pediatric Hematology and Oncology Unit, BSMMU, Bangladesh. Total 58 diarrheal episodes occurred in 51 children with various types of haematological malignancies were included consecutively. Faecal samples of the children were sent to International Centre for Diarrheal Disease Research, Bangladesh (ICDDR, B) laboratory for detection of Clostridium difficile antigen (GDH) and toxins (A and/ or B) by Enzyme Immunoassay (EIA). Results: Among 58 diarrheal episodes 22.4% faecal samples were positive for GDH, but none of the faecal samples was positive for toxin A and or B. There were a significant association with leucopenia, severe neutropenia; usage of meropenem plus vancomycin, cefepime plus amikacin, imipenem, cytarabine and omeprazole with GDH positive diarrheal episodes. Conclusion: Positive GDH antigen with a negative result for toxin indicates C. difficile colonization. Among GDH positive episodes, a significantly higher proportion of children had leucopenia, severe neutropenia and usage of some drugs known as risk factors for C. difficile infection. To confirm the CDI advanced tests are needed

Unsupervised Grouping of Local Components for Object Segmentation

In this paper, we propose a novel object segmentation method for image understanding. Due to challenges such as variations in object size, orientation, illumination etc. object segmentation is extraordinarily difficult task in the domain of image understanding. It is well-founded concept that a small portion of the pixel set in an image contributes most in image description. Based on this concept, we hypothesize that an image consists of many components or parts each of which represent a small local area in the image and they are very meaningful in visual perception. For object segmentation, we propose spatial segmentation method on such prototypical components of images. Given an image this segmentation method acts as coarse to fine search for object(s) iteratively. The proposed method demonstrate its excellence in localizing objects in various complex backgrounds, multiple objects in a single image even if they have variation in size, orientation, lighting conditions etc. The detection efficiency of our object detector on our self-collected image set which consists of images from six different object categories climbs up to 93% in average.

Cultivation and Product Development Study of Commercially Important Seaweeds in South-Eastern Coast of Bangladesh

Seaweeds are predominantly macroscopic, multicellular, and photosynthetic marine algae that grow primarily in the ocean’s rocky littoral zone. About 154 seaweed species are found in our coastal area, of which 34 belong to green (Chlorophyta), 38 brown (Phaeophyta), and 82 red (Rhodophyta). Among them, 26 species are considered economically important based on their availability, abundance, and use. Seaweeds are mainly available in St. Martin Island, Shaporir dip, Inani, Bakkhali, Kutubdia, Patowartek, Pecherdwip, Teknaf, Shaplapur, and Moheshkhali in Cox’s Bazar region of Bangladesh. They are generally found on our Cox’s Bazar coast from October to April, but the highest abundance occurs from January to March. However, in the case of mangrove forests, seaweeds are available throughout the year. Additionally, seven species are considered commercially cultivable species. Their culture techniques were developed in the long-line and net methods at different Cox’s Bazar region sites. St. Martin Island had the highest biomass yield production of seaweed due to its favorable water quality parameters. Several value-added seaweed products were developed from dried seaweed powder. Industries based on seaweed can potentially contribute to the socioeconomic upliftment of the coastal inhabitants in Cox’s Bazar

Integrated bioinformatics and statistical approach to identify the common molecular mechanisms of obesity that are linked to the development of two psychiatric disorders: Schizophrenia and major depressive disorder

Obesity is a chronic multifactorial disease characterized by the accumulation of body fat and serves as a gateway to a number of metabolic-related diseases. Epidemiologic data indicate that Obesity is acting as a risk factor for neuro-psychiatric disorders such as schizophrenia, major depression disorder and vice versa. However, how obesity may biologically interact with neurodevelopmental or neurological psychiatric conditions influenced by hereditary, environmental, and other factors is entirely unknown. To address this issue, we have developed a pipeline that integrates bioinformatics and statistical approaches such as transcriptomic analysis to identify differentially expressed genes (DEGs) and molecular mechanisms in patients with psychiatric disorders that are also common in obese patients. Biomarker genes expressed in schizophrenia, major depression, and obesity have been used to demonstrate such relationships depending on the previous research studies. The highly expressed genes identify commonly altered signalling pathways, gene ontology pathways, and gene-disease associations across disorders. The proposed method identified 163 significant genes and 134 significant pathways shared between obesity and schizophrenia. Similarly, there are 247 significant genes and 65 significant pathways that are shared by obesity and major depressive disorder. These genes and pathways increase the likelihood that psychiatric disorders and obesity are pathogenic. Thus, this study may help in the development of a restorative approach that will ameliorate the bidirectional relation between obesity and psychiatric disorder. Finally, we also validated our findings using genome-wide association study (GWAS) and whole-genome sequence (WGS) data from SCZ, MDD, and OBE. We confirmed the likely involvement of four significant genes both in transcriptomic and GWAS/WGS data. Moreover, we have performed co-expression cluster analysis of the transcriptomic data and compared it with the results of transcriptomic differential expression analysis and GWAS/WGS