Sequence Checking and Deduplication for Existing Fingerprint Databases

Biometric technology is a rapidly evolving field with applications that range from access to devices to border crossing and entry/exit processes. Large-scale applications to collect biometric data, such as border crossings result in multimodal biometric databases containing thousands of identities. However, due to human operator error, these databases often contain many instances of image labeling and classification; this is due to the lack of training and throughput pressure that comes with human error. Multiple entries from the same individual may be assigned to a different identity. Rolled fingerprints may be labeled as flat images, a face image entered into a fingerprint field or images entered in incorrect orientation (such as rotated face images, left or right iris, etc.) are common errors found large database records. Ultimately, these enrollment errors make it impossible to identify that individual upon subsequent identification encounters. Sorting through hundreds of images to check for classification errors is a tedious and time-consuming task, especially when several biometric databases are combined. Our goal is to correctly identify misclassified fingerprints using controlled embeddings and thresholds. This work provides a new perspective on image sorting as it focuses not on the traditional aspects of increasing accuracy metrics but provides a look into multiple factors through various embeddings and thresholds to provide a tool that can be used to scour large datasets with ease to provide what percentage of the images need manual correction. The proposed network provides various metric scores which allowed for analysis on the most effective embedding and thresholds to use, resulting in a proof-of-concept to be used for practical purposes in the real world

Nitrogen removal by floating constructed wetland: Decontamination of the Buriganga River

Background: Buriganga is considered as one of the most important river in the country. But, its water quality has changed dramatically, which is responsible for creating unfavorable conditions for aquatic life. The main aim of this study was to investigate the removal capacity of pollutants mainly nitrogen present in the Buriganga river as the most polluted rivers in Bangladesh, by floating constructed wetland. Methods: This study was conducted under constant and variable shock loadings in two phases, namely ‘Phase I’ and ‘Phase II’ during 11 and 10 weeks, respectively, in which about 180 L of raw water was dosed into the tank containing a floating mat, and pollutant concentrations in the river water influent from the system were tested over a period of 21 weeks. Results: Floating treatment wetland (FTW) could sustain and remove about 31.25% and 19.23% of ammonia in the 9th and 10th weeks of Phase I, respectively, and 40.63% and 56.12% in the 17th and 18th weeks of Phase II, respectively. At first, ammonia was converted to ammonium, then, to nitrite, and finally, to nitrate. As the rhizosphere was denser and the biofilm was thicker in this study, so nitrogen removal efficiency during the application of shock loading in the 17th and 18th weeks of Phase II was considerable. The removal percentage of nitrite was 76.12 and 80%, respectively. In regular dosing of raw water in the 11th and 19th weeks in Phase I and Phase II, respectively, the total nitrate removal efficiencies from influent were 31.91 and 43.33%, respectively. Conclusion: As water resources are limited, so improvement of water quality of the polluted Buriganga river would act as an important source of reusable water. Keywords: Nitrogen, Nitrites, Nitrates, Ammonium compounds, Water quality, Wetlands, Banglades

Sustainable Utilization of Fishery Waste in Bangladesh—A Qualitative Study for a Circular Bioeconomy Initiative

Living marine resources are limited; therefore, utilizing them sustainably is essential. Not all resources obtained from the sea are used adequately, causing discards, on-board waste, and by-products and waste on land. Recognition of the limited marine resources and increasing environmental pollution has emphasized the need for better utilization of by-products. Waste may include particles of flesh, skin, bones, entrails, shells or liquid stick water. Unfortunately, no fishery waste and by-product management initiatives or projects exist in Bangladesh; by-products are generally thrown into dustbins, ponds, rivers, and the sea. Bangladesh’s fish-processing waste and fishery by-products could be exported, providing a source of foreign currency earnings. Primary and secondary data were collected through documentary analysis, a literature review, and in-depth interviews (n = 129) with fishers and other relevant stakeholders regarding the challenges of Bangladesh’s sustainable fishery by-products and fish-processing waste. The data were analyzed thematically, guided by the most meaningful stories, and show that fish waste, or fishery by-products, should not be considered less valuable than the fish itself but is a precious and profitable resource capable of bringing health, social, economic, and environmental benefits. Our results reveal that fishery waste can expand local communities’, especially fishers’ and other workers’, potential for jobs or alternative income-generating tasks during fishing ban seasons. Finally, suggestions for managing fishery waste and fishery by-products are made to ensure improved and sustainable utilization via a circular bioeconomy

Sustainable Utilization of Fishery Waste in Bangladesh—A Qualitative Study for a Circular Bioeconomy Initiative

Living marine resources are limited; therefore, utilizing them sustainably is essential. Not all resources obtained from the sea are used adequately, causing discards, on-board waste, and by-products and waste on land. Recognition of the limited marine resources and increasing environmental pollution has emphasized the need for better utilization of by-products. Waste may include particles of flesh, skin, bones, entrails, shells or liquid stick water. Unfortunately, no fishery waste and by-product management initiatives or projects exist in Bangladesh; by-products are generally thrown into dustbins, ponds, rivers, and the sea. Bangladesh’s fish-processing waste and fishery by-products could be exported, providing a source of foreign currency earnings. Primary and secondary data were collected through documentary analysis, a literature review, and in-depth interviews (n = 129) with fishers and other relevant stakeholders regarding the challenges of Bangladesh’s sustainable fishery by-products and fish-processing waste. The data were analyzed thematically, guided by the most meaningful stories, and show that fish waste, or fishery by-products, should not be considered less valuable than the fish itself but is a precious and profitable resource capable of bringing health, social, economic, and environmental benefits. Our results reveal that fishery waste can expand local communities’, especially fishers’ and other workers’, potential for jobs or alternative income-generating tasks during fishing ban seasons. Finally, suggestions for managing fishery waste and fishery by-products are made to ensure improved and sustainable utilization via a circular bioeconomy

Unveiling the gut bacteriome diversity and distribution in the national fish hilsa (Tenualosa ilisha) of Bangladesh

The field of fish microbiome research has rapidly been advancing, primarily focusing on farmed or laboratory fish species rather than natural or marine fish populations. This study sought to reveal the distinctive gut bacteriome composition and diversity within the anadromous fish species Tenualosa ilisha (hilsa), which holds the status of being the national fish of Bangladesh. We conducted an analysis on 15 gut samples obtained from 15 individual hilsa fishes collected from three primary habitats (e.g., freshwater = 5, brackish water = 5 and marine water = 5) in Bangladesh. The analysis utilized metagenomics based on 16S rRNA gene sequencing targeting the V3-V4 regions. Our comprehensive identification revealed a total of 258 operational taxonomic units (OTUs). The observed OTUs were represented by six phyla, nine classes, 19 orders, 26 families and 40 genera of bacteria. Our analysis unveiled considerable taxonomic differences among the habitats (freshwater, brackish water, and marine water) of hilsa fishes, as denoted by a higher level of shared microbiota (p = 0.007, Kruskal-Wallis test). Among the identified genera in the gut of hilsa fishes, including Vagococcus, Morganella, Enterobacter, Plesiomonas, Shigella, Clostridium, Klebsiella, Serratia, Aeromonas, Macrococcus, Staphylococcus, Proteus, and Hafnia, several are recognized as fish probiotics. Importantly, some bacterial genera such as Sinobaca, Synechococcus, Gemmata, Serinicoccus, Saccharopolyspora, and Paulinella identified in the gut of hilsa identified in this study have not been reported in any aquatic or marine fish species. Significantly, we observed that 67.50% (27/40) of bacterial genera were found to be common among hilsa fishes across all three habitats. Our findings offer compelling evidence for the presence of both exclusive and communal bacteriomes within the gut of hilsa fishes, exhibiting potential probiotic properties. These observations could be crucial for guiding future microbiome investigations in this economically significant fish species

A geofencing-based recent trends identification from twitter data

For facilitating users from information overloading by finding recent trends in twitter, several techniques are proposed. However, most of these techniques need to process extensive data. Therefore, in this paper, a geofencing-based recent trends identification technique is proposed, which acquires data based on a geofence. Afterwards, they are cleaned and the weight of these tweet data is calculated. For that, the frequency of tweet texts and hashtags are taken into account along with a boosting factor. Thereafter, they are ranked to recommend recent trends to the user. This proposed technique is applied in developing a system using Java and python. It is compared with other relevant systems, where it demonstrates that the performance of the proposed system is comparable. Over and above, since the proposed system integrates geofencing feature, it is more preferable over other systems

A Comprehensive Investigation to Cauliflower Diseases Recognition: An Automated Machine Learning Approach

Vegetables, a significant part of agriculture, are necessary for the general good health of human beings. The use of information technology can help vegetable farmers to reach high yields which can contribute to global food security and sustainable cultivation. Cauliflower (Brassica oleracea var. botrytis) is a popular vegetable that is easily affected by various diseases causing loss of production and quality. However, machine learning-based disease recognition has yet to be developed for cauliflowers which can help farmers to identify cauliflower diseases and enable them to take timely actions. In this paper, an online machine vision-based expert system for recognizing cauliflower diseases is proposed, where a captured image via a smartphone or handheld gadget is processed and then classified to identify disease to assist the cauliflower farmers. Based on the feature extraction, the system classifies four types of diseases namely ‘bacterial soft’, ‘white rust’, ‘black rot’, and ‘downy mildew’ in cauliflowers. A total of 776 images are utilized to implement this experiment. K-means clustering algorithm has been applied on captured images to segment the disease-affected regions before two-type features extraction namely statistical and co-occurrence feature. Six classification algorithms namely BayesNet, Kstar, Random Forest, LMT (Logistic Model Tree), BPN (Back propagation neural network), and J48 were used for disease classification, and we evaluated their performance using seven performance metrics. We found the Random Forest classifier outperforms all other classifiers for cauliflower disease recognition with accuracy approaching 89.00%

Environment-friendly Sustainable Rural House Designs for Different Geographic Regions of Bangladesh

International audienceNatural disasters-flood, cyclonic tidal/storm surge, land slide, river bank erosion, drought and earthquakes are the main hindrance to the sustainable development of Bangladesh. In recent years, these have caused extra burden for the marginal people of the country jeopardising country's economic growth as a whole. Although it is a small country, its culture, disaster types, availability of building materials are diverse and the housing practices in different regions vary widely too. A large number of rural houses are damaged due to disaster on a regular basis and cause economic losses and sufferings to the people. Repetitive constructions of such houses also impart deterioration of the environment as much of the construction materials are obtained locally from surrounding nature and thus sustainable development is also hampered significantly. The past experiences on post-disaster shelter response have emphasised the need for more contextual approaches to develop disaster resilient low-cost rural houses. Based on lessons learnt from shelter response after Sidr 2007 and Aila 2009 cyclones, Caritas Bangladesh took an initiative jointly with BUET, Bangladesh and CRAterre-ENSAG of France to develop design of disaster resilient low-cost houses involving local communities. Also, attention was given to develop design of houses that can be built quickly after a disaster. To this context, a seven year project is being carried out in eight different geographic regions of Bangladesh. To develop the design, at first the local practices and availability of local materials were studied. Besides, it was considered essential to understand and accommodate the need and culture of the community. At the same time it is important to consider environmental issues. Three-stage community level meetings attended by people, leaders and local masons were held to gather their views, demand and experience. Properties of the local construction materials were ascertained from laboratory tests. Respecting local affordability and considering the service and environmental loads, designs were finalized based on FEM analyses. Model houses were constructed at the selected locations to demonstrate them to the local community with an aim that new design or at least some features would be replicated. Different treatment schemes for increasing the durability of materials were employed to study their effectiveness. Thirty five designs have been developed in this research for eight different geographic regions of Bangladesh which will be useful for any individual, the Government and NGOs for constructing disaster resilient sustainable rural houses. Performances of these model houses are being monitored. The designs have been found to be accepted by the local community and some features are already replicated