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Book ; Online: Developing "Smartness" in Emerging Environments and Applications with Focus on the Internet of Things (IoT)

Mehmood, Rashid / Corchado, Juan M / Yigitcanlar, Tan

2023

Keywords	Technology: general issues ; History of engineering & technology ; artificial intelligence (AI) ; artificially intelligent city ; artificially intelligence commons ; smart city ; smart urban technology ; urban informatics ; sustainable urban development ; climate change ; pandemics ; natural disasters ; sensor city ; City 4.0 ; smart urbanism ; smart governance ; disruptive urban transition ; Internet-of-Things (IoT) ; technology giants ; sensors ; transit ; bus ; transfer ; smart card ; spatial analysis ; mode choice ; internet of everything (IoE) ; 6th generation (6G) networks ; artificial intelligence ; Distributed AI as a Service (DAIaaS) ; fog computing ; edge computing ; cloud computing ; smart airport ; smart districts ; PPE ; OHS ; risk detection ; naive Bayes ; support vector machine ; convolutional neural network ; deep learning ; microcontroller ; edge-fog-cloud computing ; Internet of Things ; robotics ; autonomous driving ; image registration ; smart sensor ; real time big data ; land-use ; air quality ; particulate matter (PM10 PM2.5) ; Intelligent Transportation Systems ; functional requirements ; machine learning ; model actionability ; model evaluation ; cloud server ; customized sensor node ; customized gateway ; FLoRa simulation ; LoRa range radio ; solid waste management ; smart cities ; big data ; event detection ; road traffic ; distributed machine learning ; automatic labeling ; social media ; data analytics ; social media analytics ; Arabic tweets ; 3D microstructure reconstruction ; permeable pavement ; generative adversarial networks ; tiny AI ; tiny ML ; distributed AI as a service (DAIaaS) ; skin disease diagnosis ; healthcare ; smart societies ; smart healthcare ; reference architecture ; TensorFlow ; visually impaired ; smart mobility ; LiDAR ; ultrasonic ; obstacle detection ; obstacle recognition ; assistive tools ; green computing ; sustainability ; Arduino Uno ; smart app ; n/a
Language	English
Size	1 electronic resource (384 pages)
Publisher	MDPI - Multidisciplinary Digital Publishing Institute
Publishing place	Basel
Document type	Book ; Online
Note	English
HBZ-ID	HT030377235
ISBN	9783036561844 ; 3036561846
Database	ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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Article ; Online: CRISPR-based epigenome editing: mechanisms and applications.

Fadul, Shaima M / Arshad, Aleeza / Mehmood, Rashid

Epigenomics

2023 Volume 15, Issue 21, Page(s) 1137–1155

Abstract: Epigenomic anomalies contribute significantly to the development of numerous human disorders. The development of epigenetic research tools is essential for understanding how epigenetic marks contribute to gene expression. A gene-editing technique known ... ...

Abstract	Epigenomic anomalies contribute significantly to the development of numerous human disorders. The development of epigenetic research tools is essential for understanding how epigenetic marks contribute to gene expression. A gene-editing technique known as CRISPR (clustered regularly interspaced short palindromic repeats) typically targets a particular DNA sequence using a guide RNA (gRNA). CRISPR/Cas9 technology has been remodeled for epigenome editing by generating a 'dead' Cas9 protein (dCas9) that lacks nuclease activity and juxtaposing it with an epigenetic effector domain. Based on fusion partners of dCas9, a specific epigenetic state can be achieved. CRISPR-based epigenome editing has widespread application in drug screening, cancer treatment and regenerative medicine. This paper discusses the tools developed for CRISPR-based epigenome editing and their applications.
MeSH term(s)	Humans ; CRISPR-Cas Systems ; Epigenome ; RNA, Guide, CRISPR-Cas Systems ; Gene Editing/methods ; CRISPR-Associated Protein 9/genetics
Chemical Substances	RNA, Guide, CRISPR-Cas Systems ; CRISPR-Associated Protein 9 (EC 3.1.-)
Language	English
Publishing date	2023-11-22
Publishing country	England
Document type	Journal Article ; Review
ZDB-ID	2537199-X
ISSN	1750-192X ; 1750-1911
ISSN (online)	1750-192X
ISSN	1750-1911
DOI	10.2217/epi-2023-0281
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Multi-generational labour markets: Data-driven discovery of multi-perspective system parameters using machine learning.

Alaql, Abeer Abdullah / Alqurashi, Fahad / Mehmood, Rashid

Science progress

2023 Volume 106, Issue 4, Page(s) 368504231213788

Abstract: The impact of aggressive capitalist approaches on social, economic and planet sustainability is significant. Economic issues such as inflation, energy costs, taxes and interest rates persist and are further exacerbated by global events such as wars, ... ...

Abstract	The impact of aggressive capitalist approaches on social, economic and planet sustainability is significant. Economic issues such as inflation, energy costs, taxes and interest rates persist and are further exacerbated by global events such as wars, pandemics and environmental disasters. A sustained history of financial crises exposes weaknesses in modern economies. The Great Attrition, with many quitting jobs, adds to concerns. The diversity of the workforce poses new challenges. Transformative approaches are essential to safeguard societies, economies and the planet. In this work, we use big data and machine learning methods to discover multi-perspective parameters for multi-generational labour markets. The parameters for the academic perspective are discovered using 35,000 article abstracts from the Web of Science for the period 1958-2022 and for the professionals' perspective using 57,000 LinkedIn posts from 2022. We discover a total of 28 parameters and categorized them into five macro-parameters, Learning & Skills, Employment Sectors, Consumer Industries, Learning & Employment Issues and Generations-specific Issues. A complete machine learning software tool is developed for data-driven parameter discovery. A variety of quantitative and visualization methods are applied and multiple taxonomies are extracted to explore multi-generational labour markets. A knowledge structure and literature review of multi-generational labour markets using over 100 research articles is provided. It is expected that this work will enhance the theory and practice of artificial intelligence-based methods for knowledge discovery and system parameter discovery to develop autonomous capabilities and systems and promote novel approaches to labour economics and markets, leading to the development of sustainable societies and economies.
Language	English
Publishing date	2023-11-29
Publishing country	England
Document type	Journal Article
ZDB-ID	128412-5
ISSN	2047-7163 ; 0036-8504 ; 0302-1785
ISSN (online)	2047-7163
ISSN	0036-8504 ; 0302-1785
DOI	10.1177/00368504231213788
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Psychological Health and Drugs: Data-Driven Discovery of Causes, Treatments, Effects, and Abuses.

Alswedani, Sarah / Mehmood, Rashid / Katib, Iyad / Altowaijri, Saleh M

Toxics

2023 Volume 11, Issue 3

Abstract: Mental health issues can have significant impacts on individuals and communities and hence on social sustainability. There are several challenges facing mental health treatment; however, more important is to remove the root causes of mental illnesses ... ...

Abstract	Mental health issues can have significant impacts on individuals and communities and hence on social sustainability. There are several challenges facing mental health treatment; however, more important is to remove the root causes of mental illnesses because doing so can help prevent mental health problems from occurring or recurring. This requires a holistic approach to understanding mental health issues that are missing from the existing research. Mental health should be understood in the context of social and environmental factors. More research and awareness are needed, as well as interventions to address root causes. The effectiveness and risks of medications should also be studied. This paper proposes a big data and machine learning-based approach for the automatic discovery of parameters related to mental health from Twitter data. The parameters are discovered from three different perspectives: Drugs and Treatments, Causes and Effects, and Drug Abuse. We used Twitter to gather 1,048,575 tweets in Arabic about psychological health in Saudi Arabia. We built a big data machine learning software tool for this work. A total of 52 parameters were discovered for all three perspectives. We defined six macro-parameters (Diseases and Disorders, Individual Factors, Social and Economic Factors, Treatment Options, Treatment Limitations, and Drug Abuse) to aggregate related parameters. We provide a comprehensive account of mental health, causes, medicines and treatments, mental health and drug effects, and drug abuse, as seen on Twitter, discussed by the public and health professionals. Moreover, we identify their associations with different drugs. The work will open new directions for a social media-based identification of drug use and abuse for mental health, as well as other micro and macro factors related to mental health. The methodology can be extended to other diseases and provides a potential for discovering evidence for forensics toxicology from social and digital media.
Language	English
Publishing date	2023-03-20
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2733883-6
ISSN	2305-6304 ; 2305-6304
ISSN (online)	2305-6304
ISSN	2305-6304
DOI	10.3390/toxics11030287
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Discriminatory practices and poor job performance: A study of person-related hostility among nursing staff.

Noor, Nadia / Rehman, Saqib / Ahmed, Yasmeen / Sarmad, Muhammad / Mehmood, Rashid

Heliyon

2023 Volume 9, Issue 3, Page(s) e14351

Abstract: This study highlights the organisational-level factors that become the reason for propagating hostile behaviours among female nurses. Freire's theory of oppression has been used as an underpinning theory for developing the conceptual framework. This ... ...

Abstract	This study highlights the organisational-level factors that become the reason for propagating hostile behaviours among female nurses. Freire's theory of oppression has been used as an underpinning theory for developing the conceptual framework. This study empirically verifies the conceptual framework of the study that gender discrimination and lack of administrative support are the antecedents of person-related hostility, which is the reason for poor job performance in the healthcare sector. We applied a quantitative research approach, using questionnaires to collect data. Total of 707 survey forms were collected from female nurses working in public sector hospitals in four main cities of Pakistan. The software SPSS 20 and SmartPLS 3 were used for the final data analysis. All hypotheses regarding the direct and indirect relationship of variables were accepted. Gender discrimination and lack of administrative support were positively associated with person-related hostility. Moreover, person-related hostility also mediated the relationship between independent variables (gender discrimination, lack of administrative support) and dependent variable (poor job performance). Future research is directed to study person-related hostility among nursing staff of semi-urban areas and small towns with low literacy rates, considering other dependent variables like burnout, mental well-being, and mental health. HR strategies and policies for fair performance evaluation and timely promotions of nursing professionals are proposed in the study for building an overall healthy environment.
Language	English
Publishing date	2023-03-07
Publishing country	England
Document type	Journal Article
ZDB-ID	2835763-2
ISSN	2405-8440
ISSN	2405-8440
DOI	10.1016/j.heliyon.2023.e14351
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Crosswise Stream of Cu-H

Mehmood, Rashid / Tabassum, Rabil / Ali, Mohamed R / Muhammad, Taseer

Nanomaterials (Basel, Switzerland)

2023 Volume 13, Issue 3

Abstract: The present study focuses on a crosswise stream of liquid-holding nano-sized particles over an elongating (stretching) surface. Tiny particles of copper are added into base liquid (water). The influence of the micro rotation phenomenon is also considered. ...

Abstract	The present study focuses on a crosswise stream of liquid-holding nano-sized particles over an elongating (stretching) surface. Tiny particles of copper are added into base liquid (water). The influence of the micro rotation phenomenon is also considered. By means of appropriate transformations non-linear coupled ordinary differential equations are attained that govern the flow problem. The Runge-Kutta-Fehlberg scheme, together with the shooting method, is engaged to acquire results numerically. Micropolar coupling parameter, microelements concentration and nanoparticles volume fraction effects are examined over the profiles of velocity, temperature and micro-rotation. Moreover, heat flux and shear stress are computed against pertinent parameters and presented through bar graphs. Outcomes revealed that material constant has increasing effects on normal components of flow velocity; however, it decreasingly influences the tangential velocity, micro-rotation components and temperature profile. Temperature profile appeared to be higher for weak concentration of microelements. It is further noticed that normal velocity profile is higher in magnitude for the case of strong concentration (n = 0) of microelements, whereas tangential velocity profile is higher near the surface for the case of weak concentration (n = 0.5) of microelements. An increase of 3.74% in heat flux is observed when the volume fraction of nanoparticles is increased from 1 to 5%.
Language	English
Publishing date	2023-01-24
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2662255-5
ISSN	2079-4991
ISSN	2079-4991
DOI	10.3390/nano13030471
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Reading habits of medical practitioners: Young doctors in Pakistan, a case study.

Raza, Muhammad Ali / Nor, Faizah Mohamad / Mehmood, Rashid

Journal of Taibah University Medical Sciences

2022 Volume 17, Issue 5, Page(s) 844–852

Abstract: Objective: This study attempted to investigate the reading preferences and habits among young Pakistani medical doctors. The reading time, preferred source of information, preferred medical journals, and ways of reading medical journals were explored.!## ...

Abstract	Objective: This study attempted to investigate the reading preferences and habits among young Pakistani medical doctors. The reading time, preferred source of information, preferred medical journals, and ways of reading medical journals were explored. Methods: A survey approach was used for data collection. The study participants were young medical professionals in Pakistan. An online survey was sent to more than 300 individuals through various physicians and their professional groups/bodies. A total of 155 responded to the questionnaire, and 128 of the questionnaires were considered worthy of data analysis. Results: Among respondents, 40% read printed journals, 49% read online journals, 60% read case reports, and 55% read newspapers for 1-5 h per week. Continuing medical education was the preferred source of information, and the Pakistan Journal of Cardiology & Thoracic Surgery was the preferred medical journal. Reading the abstract and the conclusion was the preferred way of reading journal articles. Conclusion: Young physicians are enthusiastic in participating in research activities and spending time gaining updated information. Physicians read articles methodically. Online sources of information are preferred over printed sources.
Language	English
Publishing date	2022-05-11
Publishing country	Saudi Arabia
Document type	Journal Article
ZDB-ID	2817396-X
ISSN	1658-3612 ; 1658-3612
ISSN (online)	1658-3612
ISSN	1658-3612
DOI	10.1016/j.jtumed.2022.04.007
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Developing Smartness in Emerging Environments and Applications with a Focus on the Internet of Things.

Mehmood, Rashid / Corchado, Juan M / Yigitcanlar, Tan

Sensors (Basel, Switzerland)

2022 Volume 22, Issue 22

Abstract: The smartness that underpins smart cities and societies is defined by our ability to engage with our environments, analyze them, and make decisions, all in a timely manner [ ... ]. ...

Abstract	The smartness that underpins smart cities and societies is defined by our ability to engage with our environments, analyze them, and make decisions, all in a timely manner [...].
MeSH term(s)	Internet of Things ; Cities
Language	English
Publishing date	2022-11-18
Publishing country	Switzerland
Document type	Editorial
ZDB-ID	2052857-7
ISSN	1424-8220 ; 1424-8220
ISSN (online)	1424-8220
ISSN	1424-8220
DOI	10.3390/s22228939
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Book ; Online: Performance Enhancement Strategies for Sparse Matrix-Vector Multiplication (SpMV) and Iterative Linear Solvers

Mohammed, Thaha / Mehmood, Rashid

2022

Abstract: Iterative solutions of sparse linear systems and sparse eigenvalue problems have a fundamental role in vital fields of scientific research and engineering. The crucial computing kernel for such iterative solutions is the multiplication of a sparse matrix ...

Abstract	Iterative solutions of sparse linear systems and sparse eigenvalue problems have a fundamental role in vital fields of scientific research and engineering. The crucial computing kernel for such iterative solutions is the multiplication of a sparse matrix by a dense vector. Efficient implementation of sparse matrix-vector multiplication (SpMV) and linear solvers are therefore essential and has been subjected to extensive research across a variety of computing architectures and accelerators such as central processing units (CPUs), graphical processing units (GPUs), many integrated cores (MICs), and field programmable gate arrays (FPGAs). Unleashing the full potential of an architecture/accelerator requires determining the factors that affect an efficient implementation of SpMV. This article presents the first of its kind, in-depth survey covering over two hundred state-of-the-art optimization schemes for solving sparse iterative linear systems with a focus on computing SpMV. A new taxonomy for iterative solutions and SpMV techniques common to all architectures is proposed. This article includes reviews of SpMV techniques for all architectures to consolidate a single taxonomy to encourage cross-architectural and heterogeneous-architecture developments. However, the primary focus is on GPUs. The major contributions as well as the primary, secondary, and tertiary contributions of the SpMV techniques are first highlighted utilizing the taxonomy and then qualitatively compared. A summary of the current state of the research for each architecture is discussed separately. Finally, several open problems and key challenges for future research directions are outlined. Comment: 41 Pages, 4 Figures, 6 Tables
Keywords	Computer Science - Data Structures and Algorithms ; Mathematics - Numerical Analysis
Subject code	518
Publishing date	2022-12-14
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Book ; Online: Multi-generational labour markets

Alaql, Abeer Abdullah / Alqurashi, Fahad / Mehmood, Rashid

data-driven discovery of multi-perspective system parameters using machine learning

2023

Abstract: Economic issues, such as inflation, energy costs, taxes, and interest rates, are a constant presence in our daily lives and have been exacerbated by global events such as pandemics, environmental disasters, and wars. A sustained history of financial ... ...

Abstract	Economic issues, such as inflation, energy costs, taxes, and interest rates, are a constant presence in our daily lives and have been exacerbated by global events such as pandemics, environmental disasters, and wars. A sustained history of financial crises reveals significant weaknesses and vulnerabilities in the foundations of modern economies. Another significant issue currently is people quitting their jobs in large numbers. Moreover, many organizations have a diverse workforce comprising multiple generations posing new challenges. Transformative approaches in economics and labour markets are needed to protect our societies, economies, and planet. In this work, we use big data and machine learning methods to discover multi-perspective parameters for multi-generational labour markets. The parameters for the academic perspective are discovered using 35,000 article abstracts from the Web of Science for the period 1958-2022 and for the professionals' perspective using 57,000 LinkedIn posts from 2022. We discover a total of 28 parameters and categorised them into 5 macro-parameters, Learning & Skills, Employment Sectors, Consumer Industries, Learning & Employment Issues, and Generations-specific Issues. A complete machine learning software tool is developed for data-driven parameter discovery. A variety of quantitative and visualisation methods are applied and multiple taxonomies are extracted to explore multi-generational labour markets. A knowledge structure and literature review of multi-generational labour markets using over 100 research articles is provided. It is expected that this work will enhance the theory and practice of AI-based methods for knowledge discovery and system parameter discovery to develop autonomous capabilities and systems and promote novel approaches to labour economics and markets, leading to the development of sustainable societies and economies. Comment: 77 Pages, 3 Tables, 13 Figures, Submitted, Under Review
Keywords	Computer Science - Artificial Intelligence
Subject code	006
Publishing date	2023-02-20
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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