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Book ; Online: Sentiment analysis and opinion mining on E-commerce site

Anny, Fatema Tuz Zohra / Islam, Oahidul

2022

Abstract: Sentiment analysis or opinion mining help to illustrate the phrase NLP (Natural Language Processing). Sentiment analysis has been the most significant topic in recent years. The goal of this study is to solve the sentiment polarity classification ... ...

Abstract	Sentiment analysis or opinion mining help to illustrate the phrase NLP (Natural Language Processing). Sentiment analysis has been the most significant topic in recent years. The goal of this study is to solve the sentiment polarity classification challenges in sentiment analysis. A broad technique for categorizing sentiment opposition is presented, along with comprehensive process explanations. With the results of the analysis, both sentence-level classification and review-level categorization are conducted. Finally, we discuss our plans for future sentiment analysis research. Comment: I want to work more so want to withdraw paper
Keywords	Computer Science - Computation and Language ; Computer Science - Machine Learning ; 68T50
Publishing date	2022-11-28
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Genome-wide identification, classification, and characterization of lectin gene superfamily in sweet orange (Citrus sinensis L.).

Fee Faysal Ahmed / Farah Sumaiya Dola / Fatema Tuz Zohra / Shaikh Mizanur Rahman / Jesmin Naher Konak / Md Abdur Rauf Sarkar

PLoS ONE, Vol 18, Iss 11, p e

2023 Volume 0294233

Abstract: Lectins are sugar-binding proteins found abundantly in plants. Lectin superfamily members have diverse roles, including plant growth, development, cellular processes, stress responses, and defense against microbes. However, the genome-wide identification ...

Abstract	Lectins are sugar-binding proteins found abundantly in plants. Lectin superfamily members have diverse roles, including plant growth, development, cellular processes, stress responses, and defense against microbes. However, the genome-wide identification and functional analysis of lectin genes in sweet orange (Citrus sinensis L.) remain unexplored. Therefore, we used integrated bioinformatics approaches (IBA) for in-depth genome-wide identification, characterization, and regulatory factor analysis of sweet orange lectin genes. Through genome-wide comparative analysis, we identified a total of 141 lectin genes distributed across 10 distinct gene families such as 68 CsB-Lectin, 13 CsLysin Motif (LysM), 4 CsChitin-Bind1, 1 CsLec-C, 3 CsGal-B, 1 CsCalreticulin, 3 CsJacalin, 13 CsPhloem, 11 CsGal-Lec, and 24 CsLectinlegB.This classification relied on characteristic domain and phylogenetic analysis, showing significant homology with Arabidopsis thaliana's lectin gene families. A thorough analysis unveiled common similarities within specific groups and notable variations across different protein groups. Gene Ontology (GO) enrichment analysis highlighted the predicted genes' roles in diverse cellular components, metabolic processes, and stress-related regulation. Additionally, network analysis of lectin genes with transcription factors (TFs) identified pivotal regulators like ERF, MYB, NAC, WRKY, bHLH, bZIP, and TCP. The cis-acting regulatory elements (CAREs) found in sweet orange lectin genes showed their roles in crucial pathways, including light-responsive (LR), stress-responsive (SR), hormone-responsive (HR), and more. These findings will aid in the in-depth molecular examination of these potential genes and their regulatory elements, contributing to targeted enhancements of sweet orange species in breeding programs.
Keywords	Medicine ; R ; Science ; Q
Subject code	572
Language	English
Publishing date	2023-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Reported health and social consequences of the COVID-19 pandemic on vulnerable populations and implemented solutions in six West African countries: A media content analysis.

Saalim, Khalida / Sakyi, Kwame S / Fatema-Tuz-Zohra / Morrison, Emily / Owusu, Prince / Dalglish, Sarah L / Kanyangarara, Mufaro

PloS one

2021 Volume 16, Issue 6, Page(s) e0252890

Abstract: Coronavirus has spread worldwide with over 140 million cases and resulting in more than 3 million deaths between November 2019 to April 2021, threatening the socio-economic and psychosocial stability of many families and communities. There has been ... ...

Abstract	Coronavirus has spread worldwide with over 140 million cases and resulting in more than 3 million deaths between November 2019 to April 2021, threatening the socio-economic and psychosocial stability of many families and communities. There has been limited research to understand the consequences of COVID-19 on vulnerable populations in West Africa, and whether such consequences differ by countries' previous experience with Ebola. Using a media analysis of leading online news sources, this study identified the populations particularly vulnerable to the threats of the COVID-19 pandemic, described the consequences of COVID-19 experienced by these populations, and reported on the solutions to address them. All articles from the selected news sources published between January 1 and June 30, 2020 on 6 West African countries were imported into Dedoose. A total of 4,388 news articles were coded for excerpts on vulnerable populations, only 285 excerpts of which mentioned the existing effects of COVID-19 on vulnerable populations or implemented solutions. News articles from countries with past experience with Ebola were more likely to mention the pandemic's effects on vulnerable populations, especially on incarcerated people. Vulnerable groups were reported to have experienced a range of effects including economic disruptions, heightened domestic and sexual abuse, arbitrary arrests, health care inaccessibility, and educational challenges throughout the pandemic. With implications for the achievement of the Sustainable Development Goals (SDG) for 2030 in West Africa, these countries should consider and focus more strategic efforts on vulnerable populations to overcome their fight against the COVID-19 pandemic and to achieve the SDG for 2030.
Language	English
Publishing date	2021-06-16
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ISSN	1932-6203
ISSN (online)	1932-6203
DOI	10.1371/journal.pone.0252890
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Farmers' agrochemicals usage and willingness to adopt organic inputs

Md. Najmol Hoque / Sourav Mohan Saha / Shahin Imran / Afsana Hannan / Md. Mahdi Hasan Seen / Syed Sakib Thamid / Fatema Tuz-zohra

Environmental Challenges, Vol 7, Iss , Pp 100451- (2022)

Watermelon farming in Bangladesh

2022

Abstract: Extensive and improper use of agrochemicals by the farmers is disrupting environmental conditions and endangering human health. The use of organic inputs is the most reasonable solution for ecological sustainability. This study assessed the use of ... ...

Abstract	Extensive and improper use of agrochemicals by the farmers is disrupting environmental conditions and endangering human health. The use of organic inputs is the most reasonable solution for ecological sustainability. This study assessed the use of various agrochemicals in watermelon farming in the southern region of Bangladesh and evaluated farmers' willingness to adopt organic inputs. Primary data were collected from 120 watermelon farmers of Khulna district. Adoption Quotient Index was employed to assess farmers' usage of agrochemicals, and a Tobit model was used to determine the factors influencing their usage. In addition, determinants of farmers' willingness to adopt organic inputs were identified through logistic regression. Results revealed that no farmers received any training on the use of agrochemicals. They used overdoses of different fertilizers and crop protective chemicals. The farmers' educational level, farming experience, and extension positively affected the use of agrochemicals, whereas farm size had a negative effect. About 65.8% of the watermelon farmers were willing to adopt organic inputs, and anticipated loss of production is the primary cause for unwillingness in adoption. Farmers' educational level, watermelon farming experience, and training positively influenced their willingness, while annual income had a negative impact. This study suggests conducting proper economic evaluation of watermelon production considering environmental and social costs, educating and providing training to the farmers on appropriate agrochemicals usage and organic inputs for sustainable watermelon production.
Keywords	Agrochemicals ; Watermelon ; Organic farming ; Adoption ; Bangladesh ; Environmental sciences ; GE1-350
Subject code	910
Language	English
Publishing date	2022-04-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Remote Monitoring of Vital Signs in Diverse Non-Clinical and Clinical Scenarios Using Computer Vision Systems

Fatema-Tuz-Zohra Khanam / Ali Al-Naji / Javaan Chahl

Applied Sciences, Vol 9, Iss 20, p

A Review

2019 Volume 4474

Abstract: Techniques for noncontact measurement of vital signs using camera imaging technologies have been attracting increasing attention. For noncontact physiological assessments, computer vision-based methods appear to be an advantageous approach that could be ... ...

Abstract	Techniques for noncontact measurement of vital signs using camera imaging technologies have been attracting increasing attention. For noncontact physiological assessments, computer vision-based methods appear to be an advantageous approach that could be robust, hygienic, reliable, safe, cost effective and suitable for long distance and long-term monitoring. In addition, video techniques allow measurements from multiple individuals opportunistically and simultaneously in groups. This paper aims to explore the progress of the technology from controlled clinical scenarios with fixed monitoring installations and controlled lighting, towards uncontrolled environments, crowds and moving sensor platforms. We focus on the diversity of applications and scenarios being studied in this topic. From this review it emerges that automatic multiple regions of interest (ROIs) selection, removal of noise artefacts caused by both illumination variations and motion artefacts, simultaneous multiple person monitoring, long distance detection, multi-camera fusion and accepted publicly available datasets are topics that still require research to enable the technology to mature into many real-world applications.
Keywords	vital signs ; contactless ; video camera imaging ; imaging photoplethysmography (ippg) ; region of interest (roi) ; noise artefacts ; Technology ; T ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Biology (General) ; QH301-705.5 ; Physics ; QC1-999 ; Chemistry ; QD1-999
Language	English
Publishing date	2019-10-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Non-Contact Automatic Vital Signs Monitoring of Infants in a Neonatal Intensive Care Unit Based on Neural Networks.

Khanam, Fatema-Tuz-Zohra / Perera, Asanka G / Al-Naji, Ali / Gibson, Kim / Chahl, Javaan

Journal of imaging

2021 Volume 7, Issue 8

Abstract: Infants with fragile skin are patients who would benefit from non-contact vital sign monitoring due to the avoidance of potentially harmful adhesive electrodes and cables. Non-contact vital signs monitoring has been studied in clinical settings in recent ...

Abstract	Infants with fragile skin are patients who would benefit from non-contact vital sign monitoring due to the avoidance of potentially harmful adhesive electrodes and cables. Non-contact vital signs monitoring has been studied in clinical settings in recent decades. However, studies on infants in the Neonatal Intensive Care Unit (NICU) are still limited. Therefore, we conducted a single-center study to remotely monitor the heart rate (HR) and respiratory rate (RR) of seven infants in NICU using a digital camera. The region of interest (ROI) was automatically selected using a convolutional neural network and signal decomposition was used to minimize the noise artefacts. The experimental results have been validated with the reference data obtained from an ECG monitor. They showed a strong correlation using the Pearson correlation coefficients (PCC) of 0.9864 and 0.9453 for HR and RR, respectively, and a lower error rate with RMSE 2.23 beats/min and 2.69 breaths/min between measured data and reference data. A Bland-Altman analysis of the data also presented a close correlation between measured data and reference data for both HR and RR. Therefore, this technique may be applicable in clinical environments as an economical, non-contact, and easily deployable monitoring system, and it also represents a potential application in home health monitoring.
Language	English
Publishing date	2021-07-23
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2824270-1
ISSN	2313-433X ; 2313-433X
ISSN (online)	2313-433X
ISSN	2313-433X
DOI	10.3390/jimaging7080122
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Detection and Localisation of Life Signs from the Air Using Image Registration and Spatio-Temporal Filtering

Asanka G. Perera / Fatema-Tuz-Zohra Khanam / Ali Al-Naji / Javaan Chahl

Remote Sensing, Vol 12, Iss 3, p

2020 Volume 577

Abstract: In search and rescue operations, it is crucial to rapidly identify those people who are alive from those who are not. If this information is known, emergency teams can prioritize their operations to save more lives. However, in some natural disasters the ...

Abstract	In search and rescue operations, it is crucial to rapidly identify those people who are alive from those who are not. If this information is known, emergency teams can prioritize their operations to save more lives. However, in some natural disasters the people may be lying on the ground covered with dust, debris, or ashes making them difficult to detect by video analysis that is tuned to human shapes. We present a novel method to estimate the locations of people from aerial video using image and signal processing designed to detect breathing movements. We have shown that this method can successfully detect clearly visible people and people who are fully occluded by debris. First, the aerial videos were stabilized using the key points of adjacent image frames. Next, the stabilized video was decomposed into tile videos and the temporal frequency bands of interest were motion magnified while the other frequencies were suppressed. Image differencing and temporal filtering were performed on each tile video to detect potential breathing signals. Finally, the detected frequencies were remapped to the image frame creating a life signs map that indicates possible human locations. The proposed method was validated with both aerial and ground recorded videos in a controlled environment. Based on the dataset, the results showed good reliability for aerial videos and no errors for ground recorded videos where the average precision measures for aerial videos and ground recorded videos were 0.913 and 1 respectively.
Keywords	search and rescue ; drone ; breathing detection ; human detection ; Science ; Q
Language	English
Publishing date	2020-02-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Remote Sensing Image Resolution Enlargement Algorithm Based on Wavelet Transformation

Samiul Azam / Fatema Tuz Zohra

International Journal of Image, Graphics and Signal Processing, Vol 6, Iss 6, Pp 19-

2014 Volume 26

Abstract: In this paper, we present a new image resolution enhancement algorithm based on cycle spinning and stationary wavelet subband padding. The proposed technique or algorithm uses stationary wavelet transformation (SWT) to decompose the low resolution (LR) ... ...

Abstract	In this paper, we present a new image resolution enhancement algorithm based on cycle spinning and stationary wavelet subband padding. The proposed technique or algorithm uses stationary wavelet transformation (SWT) to decompose the low resolution (LR) image into frequency subbands. All these frequency subbands are interpolated using either bicubic or lanczos interpolation, and these interpolated subbands are put into inverse SWT process for generating intermediate high resolution (HR) image. Finally, cycle spinning (CS) is applied on this intermediate high resolution image for reducing blocking artifacts, followed by, traditional Laplacian sharpening filter is used to make the generated high resolution image sharper. This new technique has been tested on several satellite images. Experimental result shows that the proposed technique outperforms the conventional and the state-of-the-art techniques in terms of peak signal to noise ratio, root mean square error, entropy, as well as, visual perspective.
Keywords	Image resolution ; stationary wavelet transformation ; cycle spinning ; wavelet zero padding ; Electronic computers. Computer science ; QA75.5-76.95 ; Instruments and machines ; QA71-90 ; Mathematics ; QA1-939 ; Science ; Q
Subject code	006
Language	English
Publishing date	2014-05-01T00:00:00Z
Publisher	MECS Publisher
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Detection and Localisation of Life Signs from the Air Using Image Registration and Spatio-Temporal Filtering

Perera, Asanka G / Khanam, Fatema-Tuz-Zohra / Al-Naji, Ali / Chahl, Javaan

Remote Sensing. 2020 Feb. 09, v. 12, no. 3

2020

Abstract	In search and rescue operations, it is crucial to rapidly identify those people who are alive from those who are not. If this information is known, emergency teams can prioritize their operations to save more lives. However, in some natural disasters the people may be lying on the ground covered with dust, debris, or ashes making them difficult to detect by video analysis that is tuned to human shapes. We present a novel method to estimate the locations of people from aerial video using image and signal processing designed to detect breathing movements. We have shown that this method can successfully detect clearly visible people and people who are fully occluded by debris. First, the aerial videos were stabilized using the key points of adjacent image frames. Next, the stabilized video was decomposed into tile videos and the temporal frequency bands of interest were motion magnified while the other frequencies were suppressed. Image differencing and temporal filtering were performed on each tile video to detect potential breathing signals. Finally, the detected frequencies were remapped to the image frame creating a life signs map that indicates possible human locations. The proposed method was validated with both aerial and ground recorded videos in a controlled environment. Based on the dataset, the results showed good reliability for aerial videos and no errors for ground recorded videos where the average precision measures for aerial videos and ground recorded videos were 0.913 and 1 respectively.
Keywords	air ; breathing ; data collection ; disasters ; dust ; humans ; image analysis ; remote sensing
Language	English
Dates of publication	2020-0209
Publishing place	Multidisciplinary Digital Publishing Institute
Document type	Article
ZDB-ID	2513863-7
ISSN	2072-4292
ISSN	2072-4292
DOI	10.3390/rs12030577
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Reported health and social consequences of the COVID-19 pandemic on vulnerable populations and implemented solutions in six West African countries

Khalida Saalim / Kwame S Sakyi / Fatema-Tuz-Zohra / Emily Morrison / Prince Owusu / Sarah L Dalglish / Mufaro Kanyangarara

PLoS ONE, Vol 16, Iss 6, p e

A media content analysis.

2021 Volume 0252890

Abstract	Coronavirus has spread worldwide with over 140 million cases and resulting in more than 3 million deaths between November 2019 to April 2021, threatening the socio-economic and psychosocial stability of many families and communities. There has been limited research to understand the consequences of COVID-19 on vulnerable populations in West Africa, and whether such consequences differ by countries' previous experience with Ebola. Using a media analysis of leading online news sources, this study identified the populations particularly vulnerable to the threats of the COVID-19 pandemic, described the consequences of COVID-19 experienced by these populations, and reported on the solutions to address them. All articles from the selected news sources published between January 1 and June 30, 2020 on 6 West African countries were imported into Dedoose. A total of 4,388 news articles were coded for excerpts on vulnerable populations, only 285 excerpts of which mentioned the existing effects of COVID-19 on vulnerable populations or implemented solutions. News articles from countries with past experience with Ebola were more likely to mention the pandemic's effects on vulnerable populations, especially on incarcerated people. Vulnerable groups were reported to have experienced a range of effects including economic disruptions, heightened domestic and sexual abuse, arbitrary arrests, health care inaccessibility, and educational challenges throughout the pandemic. With implications for the achievement of the Sustainable Development Goals (SDG) for 2030 in West Africa, these countries should consider and focus more strategic efforts on vulnerable populations to overcome their fight against the COVID-19 pandemic and to achieve the SDG for 2030.
Keywords	Medicine ; R ; Science ; Q
Subject code	360
Language	English
Publishing date	2021-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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