Repairing and commissioning of an AC motor speed controller for a centrifugal pump

A centrifugal pump was installed in 1984 in the Fluid Mechanics Laboratory of Mechanical Engineering Department of Rajshahi University of Engineering & Technology. The motor of the centrifugal pump was dc motor and was not working. It could not be commissioned for a long time because of the damaged speed controller. The main shaft (rotor) was also jammed. In this project work, the dc motor was tried to repair. But it could not be run because the specification of the motor and the operating manual was not available. To complete the project successfully, the dc motor was replaced by an ac induction motor. After replacing the motor, the speed of the new motor was controlled by a variable frequency drive (VFD). Using this device, the speed was controlled from 600 rpm to 3000 rpm smoothly. After the replacement, the testing of the centrifugal pump was successfully performed and the motor was controlled in various speeds. Experiment on the performance test of the centrifugal pump was carried out satisfactorily running the pump in various speeds operated by the VFD

Smartphone-based Calorie Estimation From Food Image Using Distance Information

Personal assistive systems for diet control can play a vital role to combat obesity. As smartphones have become inseparable companions for a large number of people around the world, designing smartphone-based system is perhaps the best choice at the moment. Using this system people can take an image of their food right before eating, know the calorie content based on the food items on the plate. In this paper, we propose a simple method that ensures both user flexibility and high accuracy at the same time. The proposed system employs capturing food images with a fixed posture and estimating the volume of the food using simple geometry. The real world experiments on different food items chosen arbitrarily show that the proposed system can work well for both regular and liquid food items

Kotha Bondhu

Sign languages are the only communication medium for mute and deaf people all over the world, but all the general people are not familiar with it. It is really tough for these people to make other people understand their voices. In the context of Bangladesh, we have studied these community people specifically from the Tablighi Jamaat community who use different sign language to communicate with people. By studying them we have gathered the local signs along with global standard sign languages in an application named Kotha Bondhu. It is a very simpler application that is understandable to any community people and is able to translate the sign languages into Bengali voic

Computational formulation of a multiepitope vaccine unveils an exceptional prophylactic candidate against Merkel cell polyomavirus

Merkel cell carcinoma (MCC) is a rare neuroendocrine skin malignancy caused by human Merkel cell polyomavirus (MCV), leading to the most aggressive skin cancer in humans. MCV has been identified in approximately 43%–100% of MCC cases, contributing to the highly aggressive nature of primary cutaneous carcinoma and leading to a notable mortality rate. Currently, no existing vaccines or drug candidates have shown efficacy in addressing the ailment caused by this specific pathogen. Therefore, this study aimed to design a novel multiepitope vaccine candidate against the virus using integrated immunoinformatics and vaccinomics approaches. Initially, the highest antigenic, immunogenic, and non-allergenic epitopes of cytotoxic T lymphocytes, helper T lymphocytes, and linear B lymphocytes corresponding to the virus whole protein sequences were identified and retrieved for vaccine construction. Subsequently, the selected epitopes were linked with appropriate linkers and added an adjuvant in front of the construct to enhance the immunogenicity of the vaccine candidates. Additionally, molecular docking and dynamics simulations identified strong and stable binding interactions between vaccine candidates and human Toll-like receptor 4. Furthermore, computer-aided immune simulation found the real-life-like immune response of vaccine candidates upon administration to the human body. Finally, codon optimization was conducted on the vaccine candidates to facilitate the in silico cloning of the vaccine into the pET28+(a) cloning vector. In conclusion, the vaccine candidate developed in this study is anticipated to augment the immune response in humans and effectively combat the virus. Nevertheless, it is imperative to conduct in vitro and in vivo assays to evaluate the efficacy of these vaccine candidates thoroughly. These evaluations will provide critical insights into the vaccine’s effectiveness and potential for further development

Perception, our freedom of action versus consciousness regarding social media and website

Objectives: Apart from the benefits, social media also brings threats to teenagers. They are at risk if they access the internet under the age they are not allowed without their parent’s permission. Children and teenagers widely use social media and recent studies have shown that they spend the majority of their time daily on social media pages. This study aimed to evaluate whether our freedom of action has increased but not consciousness regarding social media and websites. Materials and Methods: This descriptive cross-sectional study was conducted among the students, teachers, and clinical doctors of East-West Medical College and Hospital and elite society of some areas at Uttara Model Town, Dhaka during the period from January 2018 to April 2018. A total of 365 purposively selected respondents were included in this study. After taking consent from the respondent data were collected by self-administered written questionnaire. Data were checked, cleaned, and edited to find any inconsistencies before entering into the computer. Analyses of data were done using computer software SPSS version 23.0. Analyzed data are presented by appropriate tables and charts. For qualitative data frequency distribution was shown. For the quantitative variables, different statistics (mean, median, mode, standard deviation, etc.) were calculated. Results: There were altogether 23 statements and it was seen that most of the respondents agreed with the statements. The proportion of consent ranged from 52% to almost 99%. In the cases of 12 statements, it was above 90%. In cases of 6 statements, it was from 80% to 89%. In cases of 3 statements, it was from 70% to 79%. Only one statement had a proportion of consent of 69.3% and only one had 52.1%. Most (95.6%) of the respondents mentioned that one major mental fluctuation of the young due to excessive smartphone use was ‘detachment from family and society. Another important mental fluctuation was ‘aggressive attitude’ as mentioned by 68.8% of the respondents. Nearly half (47.1%) of the respondents mentioned ‘depression’. Other mental fluctuations of the young due to excessive smartphone use were ‘apathy’, ‘jealousy’, and ‘lack of love and respect for elders’ as mentioned by 26.6%, 19.2%, and 5.2% of the respondents respectively. Conclusion: There are positive and negative impacts of using the internet and different social media. But problems start when someone indiscriminately uses the internet or social media or when one uses those excessively. Aggressive attitude, detachment from family and society, apathy, depression, jealousy, lack of love, and respect for elders may be due to excessive social media use. However, it is clear that social media affects people differently, depending on preexisting conditions and personality traits. But at the same time, it would be wrong to say that social media are universally bad things because it brings myriad benefits to our lives

Potentially toxic elemental contamination in Wainivesi River, Fiji impacted by gold - mining activities using chemometric tools and SOM analysis

Potentially toxic element (PTE) contamination in Wainivesi River, Fiji triggered by gold-mining activities is a major public health concern deserving attention. However, chemometric approaches and pattern recognition of PTEs in surface water and sediment are yet hardly studied in Pacific Island countries like Fijian urban River. In this study, twenty-four sediment and eight water sampling sites from the Wainivesi River, Fiji were explored to evaluate the spatial pattern, eco-environmental pollution, and source apportionment of PTEs. This analysis was done using an integrated approach of self-organizing map (SOM), principle component analysis (PCA), hierarchical cluster analysis (HCA), and indexical approaches. The PTE average concentration is decreasing in the order of Fe > Pb > Zn > Ni > Cr > Cu > Mn > Co > Cd for water and Fe > Zn > Pb > Mn > Cr > Ni > Cu > Co > Cd for sediment, respectively. Outcomes of eco-environmental indices including contamination and enrichment factors, and geo-accumulation index differed spatially indicated that majority of the sediment sites were highly polluted by Zn, Cd, and Ni. Cd and Ni contents can cause both ecological and human health risks. According to PCA, both mixed sources (geogenic and anthropogenic such as mine wastes discharge and farming activities) of PTEs for water and sediment were identified in the study area. The SOM analysis identified three spatial patterns, e.g., Cr–Co–Zn–Mn, Fe–Cd, and Ni–Pb–Cu in water and Zn–Cd–Cu–Mn, Cr–Ni and Fe, Co–Pb in sediment. Spatial distribution of entropy water quality index (EWQI) values depicted that northern and northwestern areas possess “poor” to “extremely poor” quality water. The entropy weights indicated Zn, Cd, and Cu as the major pollutants in deteriorating the water quality. This finding provides a baseline database with eco-environmental and health risk measures for the Wainivesi river contamination

Web Search Engine Misinformation Notifier Extension (SEMiNExt): A Machine Learning Based Approach during COVID-19 Pandemic

Misinformation such as on coronavirus disease 2019 (COVID-19) drugs, vaccination or presentation of its treatment from untrusted sources have shown dramatic consequences on public health. Authorities have deployed several surveillance tools to detect and slow down the rapid misinformation spread online. Large quantities of unverified information are available online and at present there is no real-time tool available to alert a user about false information during online health inquiries over a web search engine. To bridge this gap, we propose a web search engine misinformation notifier extension (SEMiNExt). Natural language processing (NLP) and machine learning algorithm have been successfully integrated into the extension. This enables SEMiNExt to read the user query from the search bar, classify the veracity of the query and notify the authenticity of the query to the user, all in real-time to prevent the spread of misinformation. Our results show that SEMiNExt under artificial neural network (ANN) works best with an accuracy of 93%, F1-score of 92%, precision of 92% and a recall of 93% when 80% of the data is trained. Moreover, ANN is able to predict with a very high accuracy even for a small training data size. This is very important for an early detection of new misinformation from a small data sample available online that can significantly reduce the spread of misinformation and maximize public health safety. The SEMiNExt approach has introduced the possibility to improve online health management system by showing misinformation notifications in real-time, enabling safer web-based searching on health-related issues

WaterHyacinth: A comprehensive image dataset of various Water hyacinth species from different regions of Bangladesh

The “WaterHyacinth” dataset, a recently gathered collection of images featuring four distinct species of Water hyacinth from different regions of Bangladesh, is presented in this article. There are four different classifications: Lemna minor, Eichhornia crassipes, Monochoria korsakowii, and Pistia stratiotes. The collection consists of 1790 original images and in addition 4050 augmented photos of Water hyacinth species. Every original picture was captured with the appropriate background and in sufficient natural light. Every image was correctly placed in its corresponding subfolder, providing optimal use of the pictures by various machine learning and deep learning models. Researchers could make major progress in agriculture, environmental monitoring, aquatic science, and remote sensing domains by utilizing this enormous dataset and various machine learning and deep learning approaches. In addition to opening opportunities for significant developments in these domains, it offers an essential asset for further study

Design and Analysis of a Water Distribution Network in a Sub-Urban Zone using EPANET

A number of simulation softwares has been developed to design a pipe network for adequate supply of water and to provide a most safe and suitable distribution system. The present study is carried out to find an approach on designing a water distribution system for a sub-urban zone using EPANET. The population forecast was done to emphasize the durability of the network for long-term use. By exerting a sufficient hydraulic head the network has supplied the adequate flow, pressure and velocity to the nodes at downstream. The approach has been checked to cover the study zone and, so the proposed network can be used for the real application of a water supply system. The overall network went satisfactory fulfilling a balance on supply and demand

Predicting workforce demand and skill development for low-carbon energy sector in Queensland

The climate transition strategy of Queensland Government has targeted low carbon economy includes a greater use of low carbon technologies. This study aims to predict low carbon workforce demand and their skilling need for Queensland. This study used a prediction model to forecast future workforce required for a successful transition to a low carbon electricity generation based on the available secondary data and literature. In addition this study conducted an employer survey on the requirement of the skilled workforce and the level of professional skills. The research results indicated that more than 5,300 new workforce will be required in construction, commissioning and servicing of new and/or existing power plants and facilities, with most of these being located in regional Queensland. The study results also suggest the need for a workforce transition policy and planning that may include retraining and skilling traditional workforce to the newly emerged sector