Muhammad Adeel Abid

Khwaja Fareed University of Engineering and Information Technology

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i-10 index

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Co-Authors

Muhammad Faheem Mushtaq

Islamia University of Bahawalpur

Furqan Rustam

Universidad de Granada

Waqar Ahmed

Superior University

Riley Kiefer

Florida Polytechnic University

Urooj Akram

Islamia University of Bahawalpur

Mahsa Raeisi Ardali

Nova Southeastern University

Ehsan Amjadian

University of Waterloo

Jessica Steen

Nova Southeastern University

Ayesha Mubeen

Superior University

Muhammad Imran

Health Affairs

Cooperative Institutions

Khwaja Fareed University of Engineering and Information Technology

Superior University

COMSATS University Islamabad

Islamia University of Bahawalpur

Tun Hussein Onn University of Malaysia

National University of Computer and Emerging Sciences

University of Lahore

ORCID

University of Engineering and Technology Lahore

Chongqing University

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Impact of Proactive Personality on Affective Commitment: Mediation Effect of Job Satisfaction

iRASD Journal of Management (2022)

Tajammal Hussain Awan Muhammad Adeel Abid Muhammad Shahzad Aslam Muhammad Hafeez Muhammad Shahzad Akram

Organizations are finding it harder and harder to improve their performance amid fierce competition. Globalization is causing markets to transition from traditional to digital, and as new things are developed, product lifecycles are getting shorter. Organizations don't always grow in the same way. The political, social, and environmental factors make doing business in developing nations very challenging. Business studies courses emphasize the role of staff in overcoming issues like this. Proactive workers look for a company that can adapt to their work and environmental situations. According to this study, individuals' proactive personalities under the effect of perceived organizational support result in affective commitment by job satisfaction. Through a Google form, 221 respondents in managerial positions were randomly selected from manufacturing and service firms. SPSS V.20 was employed for the data analysis. Using the Hayes method, mediation and moderated mediation analysis. The findings indicate a connection between proactive personality and emotional commitment through job satisfaction, and that this connection will become stronger as perceived organizational support increases. Proactive personality with affective commitment are partially mediated. Empirically, all three of the study's hypotheses were confirmed. Managers and practitioners will benefit from this study's decision-making advice.

Personality psychology

10.52131/jom.2022.0402.0090

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Citations (3)

Comparative analysis of TF-IDF and loglikelihood method for keywords extraction of twitter data

Mehran University Research Journal of Engineering and Technology (2022)

Muhammad Adeel Abid Muhammad Faheem Mushtaq Urooj Akram Mateen Ahmed Abbasi Furqan Rustam

Twitter has become the foremost standard of social media in today’s world. Over 335 million users are online monthly, and near about 80% are accessing it through their mobiles. Further, Twitter is now supporting 35+ which enhance its usage too much. It facilitates people having different languages. Near about 21% of the total users are from US and 79% of total users are outside of US. A tweet is restricted to a hundred and forty characters; hence it contains such information which is more concise and much valuable. Due to its usage, it is estimated that five hundred million tweets are sent per day by different categories of people including teacher, students, celebrities, officers, musician, etc. So, there is a huge amount of data that is increasing on a daily basis that need to be categorized. The important key feature is to find the keywords in the huge data that is helpful for identifying a twitter for classification. For this purpose, Term Frequency-Inverse Document Frequency (TF-IDF) and Loglikelihood methods are chosen for keywords extracted from the music field and perform a comparative analysis on both results. In the end, relevance is performed from 5 users so that finally we can take a decision to make assumption on the basis of experiments that which method is best. This analysis is much valuable because it gives a more accurate estimation which method’s results are more reliable.

tf–idf

Relevance

10.22581/muet1982.2301.09

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Citations (6)

OJIM 2022 Reviewer List

IEEE Open Journal of Instrumentation and Measurement (2023)

Mohamed Abdelazez Muhammad Adeel Abid

10.1109/ojim.2023.3249419

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Citations (0)

Future time perspective: a review and bibliometric analysis

Quality & Quantity (2023)

Muhammad Mohsin Nadia Nasir Muhammad Adeel Abid Ayesha Mubeen Waqar Ahmed

Viewpoints

Scope (computer science)

Citation analysis

Thematic Analysis

Bibliographic coupling

10.1007/s11135-023-01703-x

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Citations (1)

Spam SMS filtering based on text features and supervised machine learning techniques

Multimedia Tools and Applications (2022)

Muhammad Adeel Abid Saleem Ullah Muhammad Abubakar Siddique Muhammad Faheem Mushtaq Wajdi Aljedaani

tf–idf

Bag-of-words model

10.1007/s11042-022-12991-0

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Citations (28)

Impact of Attributes of Audit Committee on Productivity of Intellectual Capital (Empirical Evidence from Pakistan)

Review of Applied Management and Social Sciences (2022)

Ansar Abbas Shah Waqar Ahmed Mazhar Iqbal Muhammad Adeel Abid

Aim of this research is to find whether there exists an impact of audit committee characteristics on the intellectual capital of banks in the developing country Pakistan. In this study the independent variable audit committee characteristics contain three components that are independence, size, and meetings while the dependent variable is efficiency of intellectual capital which is measured using modified value-added intellectual coefficient (MVAIC) approach and the control variables utilized in the paper are bank specific. The sample contains 28 banks and total number of observations are 308 which contains data for time period 2010 to 2020. Audit committee helps in improving internal control by overseeing management decisions ultimately resulting in enhancing an institutions overall efficiency. The findings of the paper disclosed that there is a significantly positive influence of audit committee characteristics on intellectual capital efficiency of banks. The outcomes deduced from the research could provide further insights on the association between components of audit committee and intellectual capital efficiency which will be of significance for managers in making decisions regarding AC composition in order to increase IC in developing nations.

Audit Committee

Independence

Sample (material)

Capital (architecture)

Chief audit executive

Audit evidence

10.47067/ramss.v5i4.271

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Citations (1)

Recommending Domain Specific Keywords for Twitter

Advances in intelligent systems and computing (2019)

Muhammad Adeel Abid Muhammad Faheem Mushtaq Urooj Akram Bushra Mughal Maqsood Ahmad

tf–idf

Popularity

Sample (material)

10.1007/978-3-030-36056-6_25

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Citations (2)

IoT-Based Smart Biofloc Monitoring System for Fish Farming Using Machine Learning

IEEE Access (2024)

Muhammad Adeel Abid Madiha Amjad Kashif Munir Hafeez Ur Rehman Siddique Anca Delia Jurcut

Biofloc technology assists in increasing the sustainability of fish farming by reusing and recycling waste water. However, its sophisticated operation makes it very sensitive to environmental conditions. A slight disturbance in one or more parameters can lead to high fish mortality and loss. IoT systems provide an efficient way of closely monitoring the biofloc to avoid catastrophe. The best aqua conditions vary depending on the fish. Therefore, there is a strong need to explore ideal conditions for different fishes. In this work, we have focused on Tilapi fish in the southern Punjab region to find the most suitable parameters. We have developed an IoT solution for monitoring Biofloc and gathering data. We have used low-cost sensors in our product to make it feasible for poor fish farmers. Multiple machine learning algorithms such as decision trees, random forest, support vector machine, logistic regression, Gaussian naive Bayes, XGBoost and ensemble learning are applied to the collected dataset to effectively predict mortality. Our analysis exhibits that the random forest and XGBoost achieved 98% accuracy in estimating mortality. The union of IoT, machine learning, and affordability positions our study at the forefront of advancing sustainable aquaculture practices in southern Punjab, Pakistan.

10.1109/access.2024.3384263

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Citations (2)

A Survey of Glaucoma Detection Algorithms using Fundus and OCT Images

2021 IEEE 12th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON) (2022)

Riley Kiefer Jessica Steen Muhammad Adeel Abid Mahsa Raeisi Ardali Ehsan Amjadian

Glaucoma steals vision silently, but recent artificial intelligence advancements allow for its detection at an earlier stage with higher accuracy. This research updates the status of automated glaucoma detection by providing a literature review of recent technical articles since 2021 that use machine learning techniques. Brief descriptions of the various image types frequently present in glaucoma datasets are provided. At last, the papers have been summed up and sorted according to their most salient findings and the materials they used. Preprocessing methods for deep learning, transfer learning, ensemble approaches, self-organizing models, and hybrid features are among the most significant advances made with fundus images. Use of a public data set, OCT images in the spectral domain, and other novel methodologies are among the most significant advances made with OCT images.

Fundus (uterus)

10.1109/iemcon56893.2022.9946629

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Citations (5)

Automated Fundus Image Standardization Using a Dynamic Global Foreground Threshold Algorithm

2022 7th International Conference on Image, Vision and Computing (ICIVC) (2023)

Riley Kiefer Muhammad Adeel Abid Mahsa Raeisi Ardali Jessica Steen Ehsan Amjadian

A generic fundus foreground extractor is required for the standardization of fundus datasets in machine-learning applications due to the vast range of retinal fundus images. Some fundus images have a large amount of non-essential background data and others have missing data because of clipping. To standardize these varied images for machine learning applications while preserving the aspect resolution, a generalized threshold algorithm is needed to separate the foreground and background. Existing threshold algorithms fail to segment images with low contrast. There is a need for a generalized algorithm to handle varied image conditions in a dynamic manner. The proposed segmentation algorithm uses shifts in histogram frequency using intensity extrema to find the ideal threshold value. The proposed post-processing algorithm crops, pads, and resizes the image to a standardized size of 512x512 pixels using the segmentation map output. To demonstrate the effectiveness of this proposed standardization approach on downstream tasks, an ablation experiment of popular standardization strategies is evaluated on a newly proposed benchmark dataset, EyePACS-light. The experimental results demonstrate the benefits of using this standardization approach for resizing fundus images.

Benchmark (surveying)

Fundus (uterus)

Clipping (morphology)

10.1109/icivc58118.2023.10270429

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Citations (4)