{"id":1992,"date":"2020-11-14T22:30:16","date_gmt":"2020-11-14T22:30:16","guid":{"rendered":"https:\/\/bauet.ac.bd\/research\/current-researches\/"},"modified":"2020-12-22T06:37:44","modified_gmt":"2020-12-22T06:37:44","slug":"current-researches","status":"publish","type":"page","link":"https:\/\/bauet.ac.bd\/research\/current-researches\/","title":{"rendered":"Current Researches"},"content":{"rendered":"

COVID-19 Detection from Chest X-Ray Image using Deep Convolutional Neural Network<\/strong><\/h2>\n

2019 is the year when the novel coronavirus scientifically known as SARS-Cov-2, spread
\ndrastically all over the world, killing millions of people worldwide. No effective antivirus has yet
\nto be discovered. Detecting the virus is crucial for preventing unfortunate deaths. This research
\nproposes a deep convolutional neural network-based model that achieves high accuracy and low
\nfalse-positive rate for detecting covid-19 from a chest x-ray image.<\/p>\n

\"\"<\/a><\/p>\n

High Performance Optical Character Recognition (OCR) Software for Digitizing Bengali Literature<\/strong><\/h2>\n

Bengali, a widely used language spoken by more than 230 million people worldwide,
\nhas a huge inheritance in terms of literature. Almost all of those literature is not digitized. To
\npreserve those literature, and make the information indexed, we need an Optical Character
\nRecognition (OCR) software with high accuracy, so that these literatures can be digitized and
\nmake that information available for the mass people. This research aims at fulfilling this
\nobjective as almost no good OCR software is present for Bangla Language.
\n\"\"<\/a><\/p>\n

PLASTIC WASTE RECYCLING PRACTICE IN NATORE DISTRICT, BANGLADESH<\/strong><\/h2>\n

This study is aimed to find out the plastic waste recycling practice in Natore District as it has
\nbecome the biggest concern for the environment. A questionnaire-based survey at 11 shops was
\nconducted in 4 upazila of Natore district. The study found that the there are three types of plastic
\nwaste is being recycled or processed in Natore area which are pet bottles (PB), hard plastic
\nprocessed (HP 1) and hard plastic non-processed (HP2). The collection shops size is around
\n3777\u00b12160 sq\/ft in whereas the processing shops size is 13513\u00b17686 sq\/ft. On average 6 people
\nwork in each type of shops, aged from 20 to 35 years and women are less involved in this sector.
\nWorker mostly earned 270 BDT on average pay day. Collection shops collect 1400\u00b170.72 kg
\n(1.54 ton) and processing shops collect 970\u00b129.86 kg (1.069 ton) plastic waste every week that
\ncontributes 0.14 % of the total plastic waste recycled in Bangladesh. Price of the products is a bit
\nunstable. However, in general PB, HP1 and HP2 are bought 10-12 20-30 and 5-7 BDT\/kg
\nrespectively and sold to industry on 17-18, 45-50, 10 BDT\/kg respectively, for final recycle.<\/p>\n

Student Name (4 th Batch)
\n1. E.S. SHAFKATH (16101013)
\n2. MD. ASHIKUR RAHMAN (16101015)
\n3. NAZMUSH SADAT (16101020)
\nSupervisor Name:
\nDr. Engr. Md. Mahmudur Rahman
\nAssistant Professor
\nDept. of CE
\n\"\" \"\" \"\"<\/p>\n

Emotion Recognition from EEG signal using Convolutional Neural Network<\/strong><\/h2>\n

Electroencephalogram (EEG) that measures the electrical activity of the brain has been used
\nextensively to recognize emotion. Normally feature based emotion recognition requires a strong
\neffort to design the perfect feature or feature set related to the classification of emotion. To curtail
\nthe manual human effort we designed a model by using a virtual image from EEG with
\nConvolutional Neural Network (CNN). Initially, we planned to calculate Pearson\u2019s correlation
\ncoefficients form different sub-bands of EEG to formulate a virtual image. Later, this virtual image
\nwas fed into a CNN architecture to classify emotion. We made two distinct protocols; between
\nthese, protocol-1 was to classify positive and negative emotion and protocol-2 was to classify four
\ndistinct emotions using internationally authorized DEAP dataset. Our proposed method is helpful in
\nrecognizing emotions efficiently.<\/p>\n

Wearable Technology to Assist the Patients Infected with Novel Coronavirus (COVID-19)<\/strong><\/h2>\n

Wearable technology plays a significant role in our daily life as well as in the healthcare industry.
\nThe recent coronavirus pandemic has taken the world\u2019s healthcare systems by surprise. Although
\ntrials of possible vaccines are underway, it would take a long time before the vaccines are permitted
\nfor public use. Maximum government efforts are currently geared towards preventing the spread of
\nthe coronavirus and predicting probable hot zones. The essential and healthcare workers are the
\nmost vulnerable towards coronavirus infections due to their required proximity to potential
\ncoronavirus patients. Wearable technology can potentially assist in these regards by providing real-
\ntime remote monitoring, symptoms prediction, contact tracing, etc. The goal of this work is to
\ndiscuss the different existing wearable monitoring devices (respiration rate, heart rate, temperature,
\nand oxygen saturation) and respiratory support systems (ventilators, CPAP devices, and oxygen
\ntherapy) which are frequently used to assist the coronavirus affected people. The devices are
\ndescribed based on the services they provide, their working procedures as well as comparative
\nanalysis of their merits and demerits with cost. A comparative discussion with probable future
\ntrends is also drawn to select the best technology for COVID-19 infected patients. It is envisaged
\nthat wearable technology is only capable of providing initial treatment that can reduce the spread of
\nthis pandemic.<\/p>\n","protected":false},"excerpt":{"rendered":"COVID-19 Detection from Chest X-Ray Image using Deep Convolutional Neural Network 2019 is the year when the novel coronavirus scientifically known as SARS-Cov-2, spread drastically all over the world, killing millions of people worldwide. No effective antivirus has yet to be discovered. Detecting the virus is crucial for preventing unfortunate deaths. This research proposes a […]","protected":false},"author":1,"featured_media":0,"parent":1991,"menu_order":1,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-1992","page","type-page","status-publish","hentry"],"yoast_head":"\nCurrent Researches - Bangladesh Army Deltin 7 Aviator গেম টাকা ইনকাম of Engineering & Technology<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/bauet.ac.bd\/research\/current-researches\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Current Researches - Bangladesh Army Deltin 7 Aviator গেম টাকা ইনকাম of Engineering & Technology\" \/>\n<meta property=\"og:description\" content=\"COVID-19 Detection from Chest X-Ray Image using Deep Convolutional Neural Network 2019 is the year when the novel coronavirus scientifically known as SARS-Cov-2, spread drastically all over the world, killing millions of people worldwide. 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