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  1. Article ; Online: A modified version of diagonal systematic sampling in the presence of linear trend.

    Azeem, Muhammad

    PloS one

    2022  Volume 17, Issue 3, Page(s) e0265179

    Abstract: Systematic sampling is one of the simplest and popular methods for selecting a random sample from a finite population. The diagonal systematic sampling scheme is a type of systematic sampling design which has gained the attention of researchers during ... ...

    Abstract Systematic sampling is one of the simplest and popular methods for selecting a random sample from a finite population. The diagonal systematic sampling scheme is a type of systematic sampling design which has gained the attention of researchers during the last two decades. In this paper, a modification to the conventional diagonal systematic sampling design is proposed for use in situations where population units follow a linear trend. It is found that the proposed strategy reduces the variance of the diagonal systematic sampling thus resulting in an efficient sampling design. The mathematical conditions under which the suggested modified diagonal systematic sampling design is more precise than some of the available sampling designs are derived. With the help of a numerical illustration using milk yield data, it is shown that the proposed sampling scheme is more efficient than some of the available sampling schemes.
    MeSH term(s) Research Design
    Language English
    Publishing date 2022-03-31
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2267670-3
    ISSN 1932-6203 ; 1932-6203
    ISSN (online) 1932-6203
    ISSN 1932-6203
    DOI 10.1371/journal.pone.0265179
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  2. Article ; Online: A neutral comparative analysis of additive, multiplicative, and mixed quantitative randomized response models.

    Azeem, Muhammad / Ali, Sidra

    PloS one

    2023  Volume 18, Issue 4, Page(s) e0284995

    Abstract: In survey sampling, the randomized response technique is a useful tool to collect reliable data in many fields including sociology, education, economics, and psychology etc. Over the past few decades, many variants of quantitative randomized response ... ...

    Abstract In survey sampling, the randomized response technique is a useful tool to collect reliable data in many fields including sociology, education, economics, and psychology etc. Over the past few decades, many variants of quantitative randomized response models have been developed by researchers. The existing literature on randomized response models lacks a neutral comparative study of different models to help the practitioners choose the appropriate model for a given practical problem. In most of the existing studies, the authors tend to show only the favorable results by hiding the cases where their suggested models are inferior to the existing models. This approach often leads to biased comparisons which may badly misguide the practitioners when choosing a randomized response model for a practical problem at hand. This paper attempts a neutral comparison of six existing quantitative randomized response models using separate as well as joint measures of respondent-privacy and model-efficiency. The findings suggest that one model may perform better than the other model in terms of efficiency but may perform worse when other metrics of model quality are taken into account. The current study guides practitioners in choosing the right model for a given problem under a particular situation.
    MeSH term(s) Surveys and Questionnaires ; Random Allocation
    Language English
    Publishing date 2023-04-26
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2267670-3
    ISSN 1932-6203 ; 1932-6203
    ISSN (online) 1932-6203
    ISSN 1932-6203
    DOI 10.1371/journal.pone.0284995
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  3. Article: An efficient estimator of population variance of a sensitive variable with a new randomized response technique.

    Azeem, Muhammad / Salahuddin, Najma / Hussain, Sundus / Ijaz, Musarrat / Salam, Abdul

    Heliyon

    2024  Volume 10, Issue 5, Page(s) e27488

    Abstract: In sampling theory, a majority of the available estimators of population variance are designed for use with non-sensitive variables only. Such estimators cannot perform efficiently when the variable of interest is of sensitive nature, such as use of ... ...

    Abstract In sampling theory, a majority of the available estimators of population variance are designed for use with non-sensitive variables only. Such estimators cannot perform efficiently when the variable of interest is of sensitive nature, such as use of drugs, illegal income, abortion, cheating in examination, the amount of income tax payable, and the violation of rules by employees, etc. In the current literature, the shortage of research studies on variance estimators of a sensitive variable has created a big research gap and a room for improvement in the efficiency of such estimators. In this paper, a new randomized scrambling technique is proposed, along with a new estimator of population variance. The new estimator achieves improvement in efficiency over the available variance estimators. The proposed estimator is designed for use with simple random sampling and uses the information on an auxiliary variable. The improvement in efficiency is shown for different choices of constants. Besides efficiency, improvement in the unified measure of estimator quality is also achieved with the proposed estimator under the new randomized response model.
    Language English
    Publishing date 2024-03-06
    Publishing country England
    Document type Journal Article
    ZDB-ID 2835763-2
    ISSN 2405-8440
    ISSN 2405-8440
    DOI 10.1016/j.heliyon.2024.e27488
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  4. Article: SkinLesNet: Classification of Skin Lesions and Detection of Melanoma Cancer Using a Novel Multi-Layer Deep Convolutional Neural Network.

    Azeem, Muhammad / Kiani, Kaveh / Mansouri, Taha / Topping, Nathan

    Cancers

    2023  Volume 16, Issue 1

    Abstract: Skin cancer is a widespread disease that typically develops on the skin due to frequent exposure to sunlight. Although cancer can appear on any part of the human body, skin cancer accounts for a significant proportion of all new cancer diagnoses ... ...

    Abstract Skin cancer is a widespread disease that typically develops on the skin due to frequent exposure to sunlight. Although cancer can appear on any part of the human body, skin cancer accounts for a significant proportion of all new cancer diagnoses worldwide. There are substantial obstacles to the precise diagnosis and classification of skin lesions because of morphological variety and indistinguishable characteristics across skin malignancies. Recently, deep learning models have been used in the field of image-based skin-lesion diagnosis and have demonstrated diagnostic efficiency on par with that of dermatologists. To increase classification efficiency and accuracy for skin lesions, a cutting-edge multi-layer deep convolutional neural network termed SkinLesNet was built in this study. The dataset used in this study was extracted from the PAD-UFES-20 dataset and was augmented. The PAD-UFES-20-Modified dataset includes three common forms of skin lesions: seborrheic keratosis, nevus, and melanoma. To comprehensively assess SkinLesNet's performance, its evaluation was expanded beyond the PAD-UFES-20-Modified dataset. Two additional datasets, HAM10000 and ISIC2017, were included, and SkinLesNet was compared to the widely used ResNet50 and VGG16 models. This broader evaluation confirmed SkinLesNet's effectiveness, as it consistently outperformed both benchmarks across all datasets.
    Language English
    Publishing date 2023-12-24
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2527080-1
    ISSN 2072-6694
    ISSN 2072-6694
    DOI 10.3390/cancers16010108
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  5. Article ; Online: Farmers' beliefs and concerns about climate change, and their adaptation behavior to combat climate change in Saudi Arabia.

    Azeem, Muhammad I / Alhafi Alotaibi, Bader

    PloS one

    2023  Volume 18, Issue 1, Page(s) e0280838

    Abstract: Climate change threatens the existence of humankind on the planet Earth. Owing to its arid climate and poor natural resources base, Saudi Arabia is particularly susceptible to the negative impact of ongoing climate change. Farmers' understanding of this ... ...

    Abstract Climate change threatens the existence of humankind on the planet Earth. Owing to its arid climate and poor natural resources base, Saudi Arabia is particularly susceptible to the negative impact of ongoing climate change. Farmers' understanding of this global phenomenon is extremely important as it may help determine their adaptation behavior. This study was designed to analyze farmers' beliefs and concerns about climate change as well as their views about adaptation different obstacles. Data were collected from 80 randomly farmers of the Al-Ahsa region in Eastern Province using structured interviews. The findings revealed that farmers believed that climate change is mainly occurring due to anthropogenic activities. Drought, insects, crop diseases, and heat stress were their main concerns regarding adverse impacts of climate change. Lack of knowledge about adaptation practices, and poor government and financial support are perceived as the major obstacles to adaptation. The results of non-parametric analysis identified no significant differences in farmers' climate change beliefs and concerns, and their views about obstacles to adaptation in relation to their demographic characteristics. Based on the findings, we suggest that capacity building programs should be undertaken by the government for enhancing the adaptive capacity of the farmers as well the provision of financial incentives wherever deemed necessary for promoting the adoption of sustainable agricultural practices and building a resilient national food system.
    MeSH term(s) Humans ; Farmers ; Climate Change ; Saudi Arabia ; Agriculture/methods ; Motivation
    Language English
    Publishing date 2023-01-25
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2267670-3
    ISSN 1932-6203 ; 1932-6203
    ISSN (online) 1932-6203
    ISSN 1932-6203
    DOI 10.1371/journal.pone.0280838
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  6. Book ; Online: A Multi-solution Study on GDPR AI-enabled Completeness Checking of DPAs

    Azeem, Muhammad Ilyas / Abualhaija, Sallam

    2023  

    Abstract: Specifying legal requirements for software systems to ensure their compliance with the applicable regulations is a major concern to requirements engineering (RE). Personal data which is collected by an organization is often shared with other ... ...

    Abstract Specifying legal requirements for software systems to ensure their compliance with the applicable regulations is a major concern to requirements engineering (RE). Personal data which is collected by an organization is often shared with other organizations to perform certain processing activities. In such cases, the General Data Protection Regulation (GDPR) requires issuing a data processing agreement (DPA) which regulates the processing and further ensures that personal data remains protected. Violating GDPR can lead to huge fines reaching to billions of Euros. Software systems involving personal data processing must adhere to the legal obligations stipulated in GDPR and outlined in DPAs. Requirements engineers can elicit from DPAs legal requirements for regulating the data processing activities in software systems. Checking the completeness of a DPA according to the GDPR provisions is therefore an essential prerequisite to ensure that the elicited requirements are complete. Analyzing DPAs entirely manually is time consuming and requires adequate legal expertise. In this paper, we propose an automation strategy to address the completeness checking of DPAs against GDPR. Specifically, we pursue ten alternative solutions which are enabled by different technologies, namely traditional machine learning, deep learning, language modeling, and few-shot learning. The goal of our work is to empirically examine how these different technologies fare in the legal domain. We computed F2 score on a set of 30 real DPAs. Our evaluation shows that best-performing solutions yield F2 score of 86.7% and 89.7% are based on pre-trained BERT and RoBERTa language models. Our analysis further shows that other alternative solutions based on deep learning (e.g., BiLSTM) and few-shot learning (e.g., SetFit) can achieve comparable accuracy, yet are more efficient to develop.
    Keywords Computer Science - Software Engineering ; Computer Science - Artificial Intelligence
    Subject code 004
    Publishing date 2023-11-23
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Article ; Online: Relationship between Social Media Use and Development of Crop Production Skills in Saudi Arabia

    Dabiah, Abdulaziz Thabet / Alotibi, Yahya S. / Azeem, Muhammad Imran

    Journal of Agricultural Extension, Vol 28, Iss 1, Pp 19-social media, agricultural skills (2024)

    2024  

    Abstract: The current study examined the information preferences of the subscribers of various agricultural content accounts on social media as well as the perceived impact of social media on crop production skills in Saudi Arabia. Data were collected from the ... ...

    Abstract The current study examined the information preferences of the subscribers of various agricultural content accounts on social media as well as the perceived impact of social media on crop production skills in Saudi Arabia. Data were collected from the subscribers of the agricultural content accounts of Saudi Arabia on social media using an online survey with the help of a structured questionnaire and a convenient sampling methodology. Both descriptive statistics and Pearson correlation analysis were run to analyse the data. The majority (81%) of the respondents preferred agricultural information in the form of videos, followed by photos (75%). Moreover, a moderate to high impact was reported by the respondents on their various agricultural skills. Trust in social media had a significant negative correlation with respondents’ perceived impact on their crop production skills. The respondents’ preferences for a particular type of information had a significant positive correlation with the perceived impact of social media on their crop production skills. We conclude that subscribers’ trust in social media and their preference for agricultural information in the form of videos are the critical factors that may shape their behaviour positively.
    Keywords social media ; agricultural skill ; Agriculture (General) ; S1-972
    Subject code 306
    Language English
    Publishing date 2024-01-01T00:00:00Z
    Publisher Agricultural Extension Society of Nigeria
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Article ; Online: Comment on: Insights into Covid-19 mortality: A comprehensive study of cardiovascular sensitivity, gender, race, and geography trends in the United States (2020-2023).

    Ali, Azzam / Kumar, Mukesh / Azeem, Muhammad Basit / Khan, Arwa / Arsal, Syed Ali

    Current problems in cardiology

    2024  Volume 49, Issue 5, Page(s) 102465

    MeSH term(s) Humans ; United States/epidemiology ; COVID-19/epidemiology ; Geography
    Language English
    Publishing date 2024-02-16
    Publishing country Netherlands
    Document type Letter
    ZDB-ID 441230-8
    ISSN 1535-6280 ; 0146-2806
    ISSN (online) 1535-6280
    ISSN 0146-2806
    DOI 10.1016/j.cpcardiol.2024.102465
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    In stock of ZB MED Cologne/Königswinter

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  9. Article: Double edge resolving set and exchange property for nanosheet structure.

    Koam, Ali N A / Ahmad, Ali / Ali, Sikander / Jamil, Muhammad Kamran / Azeem, Muhammad

    Heliyon

    2024  Volume 10, Issue 5, Page(s) e26992

    Abstract: The exploration of edge metric dimension and its applications has been an ongoing discussion, particularly in the context of nanosheet graphs formed from the octagonal grid. Edge metric dimension is a concept that involves uniquely identifying the entire ...

    Abstract The exploration of edge metric dimension and its applications has been an ongoing discussion, particularly in the context of nanosheet graphs formed from the octagonal grid. Edge metric dimension is a concept that involves uniquely identifying the entire edge set of a structure with a selected subset from the vertex set, known as the edge resolving set. Let's consider two distinct edge resolving sets, denoted as
    Language English
    Publishing date 2024-02-28
    Publishing country England
    Document type Journal Article
    ZDB-ID 2835763-2
    ISSN 2405-8440
    ISSN 2405-8440
    DOI 10.1016/j.heliyon.2024.e26992
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  10. Article ; Online: Chemical Composition of Essential Oils from Natural Populations of

    Parveen, Amna / Abbas, Muhammad Ghazanfar / Keefover-Ring, Ken / Binyameen, Muhammad / Mozūraitis, Raimondas / Azeem, Muhammad

    Molecules (Basel, Switzerland)

    2024  Volume 29, Issue 6

    Abstract: The current study aimed to evaluate the presence of chemical variations in essential oils (EOs) extracted ... ...

    Abstract The current study aimed to evaluate the presence of chemical variations in essential oils (EOs) extracted from
    MeSH term(s) Female ; Animals ; Oils, Volatile/pharmacology ; Oils, Volatile/chemistry ; Insect Repellents/pharmacology ; Insect Repellents/chemistry ; Altitude ; Scoparia ; Insecticides/chemistry ; Artemisia ; Anti-Bacterial Agents/pharmacology ; Aedes ; Larva ; Plant Oils/chemistry ; Polycyclic Sesquiterpenes
    Chemical Substances Oils, Volatile ; Insect Repellents ; Insecticides ; caryophyllene (BHW853AU9H) ; Anti-Bacterial Agents ; Plant Oils ; Polycyclic Sesquiterpenes
    Language English
    Publishing date 2024-03-19
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 1413402-0
    ISSN 1420-3049 ; 1431-5165 ; 1420-3049
    ISSN (online) 1420-3049
    ISSN 1431-5165 ; 1420-3049
    DOI 10.3390/molecules29061359
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