Dr. Muhammad Azam

About Dr. Muhammad Azam

Dr. Muhammad Azam, With an exceptional h-index of 50 and a recent h-index of 43 (since 2020), a distinguished researcher at University of Veterinary and Animal Sciences, specializes in the field of Decision Trees, Ensemble Classifiers, Statistical Quality Control and Survey Sampling.

His recent articles reflect a diverse array of research interests and contributions to the field:

A resubmission-based variable control chart

Comparative Assessment of Bioactive Compounds, Fruit Quality Attributes and Sugar Profiling in Early Maturing Table Grape (Vitis Vinifera L.) Cultivars from Pothohar, Pakistan

A Single-Switch Trans-Inverse High Step-Up Semi-Quadratic DC-DC Converter Based on Three-Winding Coupled-Inductor

Modulating plant-soil microcosm with green synthesized ZnONPs in arsenic contaminated soil

Phyto-fabrication of copper oxide nanoparticles (NPs) utilizing the green approach exhibits antioxidant, antimicrobial, and antifungal activity in Diospyros kaki fruit

The Influence of Moderate Leverage Impact of Liquidity Ratios on the Financial Performance of the Sugar Sector in Pakistan

Synergistic partnerships of endophytic fungi for bioactive compound production and biotic stress management in medicinal plants

Ontology-Based Smart Irrigation System: Enhancing Agricultural Water Management: Ontology-Based Smart Irrigation System

Dr. Muhammad Azam Information

University

University of Veterinary and Animal Sciences

Position

Associate Professor/ Chairman Department of Statistics and Computer Science Lahore Pakistan

Citations(all)

10166

Citations(since 2020)

7444

Cited By

4192

hIndex(all)

50

hIndex(since 2020)

43

i10Index(all)

244

i10Index(since 2020)

201

Email

University Profile Page

University of Veterinary and Animal Sciences

Dr. Muhammad Azam Skills & Research Interests

Decision Trees

Ensemble Classifiers

Statistical Quality Control and Survey Sampling

Top articles of Dr. Muhammad Azam

A resubmission-based variable control chart

Authors

Asma Arshad,Muhammad Azam,Muhammad Aslam,Chi-Hyuck Jun

Journal

Communications in Statistics-Theory and Methods

Published Date

2024/1/17

In this paper, an attempt is made to develop a new variable control chart under the resubmitted sampling scheme. The resubmission of a sample allows retaking a sample to pass through inspection/analyzing if there is a question on the inspection of the sample at any stage. The proposed control chart includes the X-bar chart as a special case. The performance of the proposed control chart is assessed by determining the in-control and out-of-control average run lengths for the various parametric settings. For illustrative purposes, a real-life example is presented to explain a detailed implementation of the proposed control chart.

Comparative Assessment of Bioactive Compounds, Fruit Quality Attributes and Sugar Profiling in Early Maturing Table Grape (Vitis Vinifera L.) Cultivars from Pothohar, Pakistan

Authors

Muhammad Tahir Akram,Rashad Qadri,Muhammad Azam Khan,Arif Atak,Mehwish Liaquat,Tanveer Hussain,Muhammad Mumtaz Khan,Muhammad Azam

Journal

Applied Fruit Science

Published Date

2024/3/11

Grape is a highly nutritious and ever-demanded fruit crop that is enriched with premium phytochemicals. Owing to health benefits, its cultivation has shown a continuous upward trend in subtropical areas of the world. In these regions, early maturing grape varieties are preferred as they require lower chilling hours to break the dormancy and bear fruit. However, the agro-climatic conditions significantly affect grape’s phytochemicals and berry quality attributes. Therefore, this study aimed to access phytochemicals and other fruit biochemical quality traits of 11 early maturing cultivars (‘Early White’,‘Regenia’,‘Perlet’,‘King Ruby’,‘NARC Black’,‘Vitro Black’,‘Flame Seedless’,‘Danlas-B’,‘Flame Tokay’,‘White Seedless’, and ‘Sultanina’) grown under distinctive agro-climatic conditions in Pakistan’s Pothohar region at the Barani Agriculture Research Institute (BARI). Pakistan has an annual average temperature of 22.3 C and …

A Single-Switch Trans-Inverse High Step-Up Semi-Quadratic DC-DC Converter Based on Three-Winding Coupled-Inductor

Authors

Yuegang Hu,Weishu Zhan,Shunlei Li,Muhammad Adeel Azam

Journal

IEEE Transactions on Power Electronics

Published Date

2024/3/27

This paper introduces a new non-isolated singleswitch trans-inverse high step-up semi-quadratic DC-DC converter with low input current ripple for renewable energy generation systems. In the presented topology, a three-winding coupled-inductor combined with a quadratic boost converter to achieve high voltage gains. The advanced features of the suggested structure are its ultra-high voltage conversion ratio, low voltage stress ratio across the switching components, low input current ripple, zero current switching (ZCS) of the semiconductors and also common ground between the input and output sides. Due to the trans-inverse feature in the proposed circuit, higher voltage gains can be achieved without needing large turns’ ratios of the coupled inductor in comparison to the other typical quadratic converters which decreases the conduction power loss. Furthermore, in this topology, the maximum voltage stress …

Modulating plant-soil microcosm with green synthesized ZnONPs in arsenic contaminated soil

Authors

Asad Rehman,Saeed ur Rahman,Pengli Li,Iftikhar Hussain Shah,Muhammad Aamir Manzoor,Muhammad Azam,Junfeng Cao,Muhammad Sanaullah Malik,Mouna Jeridi,Naveed Ahmad,Khulood Fahad Alabbosh,Qunlu Liu,Muhammad Khalid,Qingliang Niu

Journal

Journal of Hazardous Materials

Published Date

2024/5/15

Biogenic nanoparticle (NP), derived from plant sources, is gaining prominence as a viable, cost-effective, sustainable, and biocompatible alternative for mitigating the extensive environmental impact of arsenic on the interplay between plant-soil system. Herein, the impact of green synthesized zinc oxide nanoparticles (ZnONPs) was assessed on Catharanthus roseus root system-associated enzymes and their possible impact on microbiome niches (rhizocompartments) and overall plant performance under arsenic (As) gradients. The application of ZnONPs at different concentrations successfully modified the arsenic uptake in various plant parts, with the root arsenic levels increasing 1.5 and 1.4-fold after 25 and 50 days, respectively, at medium concentration compared to the control. Moreover, ZnONPs gradients regulated the various soil enzyme activities. Notably, urease and catalase activities showed an increase …

Phyto-fabrication of copper oxide nanoparticles (NPs) utilizing the green approach exhibits antioxidant, antimicrobial, and antifungal activity in Diospyros kaki fruit

Authors

Iftikhar Hussain Shah,Irfan Ali Sabir,Muhammad Ashraf,Asad Rehman,Zishan Ahmad,Muhammad Azam,Ghulam Abbas Ashraf,Haroon ur Rasheed,Guohui Li,Mouna JERIDI,Mohammad Faizan,Muhammad Ahsan Altaf,Awais Shakoor,Cheng Song,Muhammad Aamir Manzoor

Journal

Fruit Research

Published Date

2024

Nanotechnology has emerged as a prominent field in recent times. The fabrication of biocompatible materials has taken on highlighted significance owing to their requisite application in adverse sectors including medicine, water treatment and purification, health, and other related fields. There has been a lot of research done recently on the green synthesis of various nanoparticles (NPs). Copper a high-performance metal used in agriculture to combat pathogenic attacks, has received less attention. The current work demonstrates the successful preparation of green synthesized copper oxide nanoparticles (CuO. NPs) from Mangifera indica (M. indica) leaf extract. The spectral and morphological characterization biosynthesized were observed using, FTIR, XRD, and TEM analysis. The FTIR analysis revealed the functional groups present in plant extracts. XRD was carried out to demonstrate the crystalline nature and …

The Influence of Moderate Leverage Impact of Liquidity Ratios on the Financial Performance of the Sugar Sector in Pakistan

Authors

Umar Farooq,Umar Hayat,Muhammad Azam,Uzma Haroon

Journal

Journal of Excellence in Management Sciences

Published Date

2024/1/5

The research investigates the performance of the sugar sector in Pakistan with debt ratio, operating cash flow ratio, current ratio, quick ratio and firm age with moderate leverage impact on the financial performance of the Sugar sector. Focusing specifically on Pakistan, the study collected data on 25 sugar companies from 2012 to 2022. Secondary data was gathered from annual reports and the Pakistan Stock Exchange. When leverage is maintained at a moderate level, the connections between debt ratio and leverage and operating cash flow and leverage ratio prove statistically significant. These findings carry valuable insights within the context of the regression study, suggesting that the extent of business leverage plays a pivotal role in shaping the relationship between these variables and earnings per share (EPS). In contrast, factors such as current ratio and leverage, quick ratio with leverage ratio, and firm age with leverage ratio lack statistical significance at a moderate leverage ratio. The practical effects of certain financial ratios on earnings per share are excessively high debt ratios, which suggests a significant dependence on debt financing, which may result in higher interest costs and greater financial risk, which could lower EPS. In contrast, high current ratios, quick ratios, and strong operational cash flow ratios are often considered positive indications of EPS. In planning for the future, companies must find a middle ground between debt and equity financing, aiming for a sustainable debt ratio that doesn't weigh down earnings with excessive interest expenses. Boosting operating cash flow through efficient operations and careful working …

Synergistic partnerships of endophytic fungi for bioactive compound production and biotic stress management in medicinal plants

Authors

Muhammad Usman,Iftikhar Hussain Shah,Irfan Ali Sabir,M Sanaullah Malik,Abdul Rehman,Ghulam Murtaza,Muhammad Azam,Saeed ur Rahman,Asad Rehman,Ghulam Abbas Ashraf,Muhammad Waheed Riaz,Shams ur Rehman,Mouna Jeridi,Guohui Li,Cheng Song,Muhammad Aamir Manzoor

Published Date

2024/3/9

The fungal endophytes are an understudied area of research with great potential for new bioactive compounds’ discovery. These are the fungal strains that live within the inner compartments of the host plant without causing it any kind of harm. These fungal endophytes, in combination with the host organisms, synthesize many compounds with a range of pharmaceutical values. Most recently, the discovery of fungal endophyte genes which are linked with the biosynthesis of plant metabolites has opened a new field of research. These plant partners assist plants against biotic stress and protect them from pathogenic attacks or diseases with the presence of some important gene families like WRKY and MYB. The bioactive metabolites from this group are known for their anticancer, antimicrobial, antioxidant, antidiabetic, and anti-tubercular properties. Therefore, these bioactive compounds offer new routes for …

Ontology-Based Smart Irrigation System: Enhancing Agricultural Water Management: Ontology-Based Smart Irrigation System

Authors

Maher u Nisa,Muhammad Azam,Tanveer Rafiq,Mohsin Sattar,Sana Zafar

Journal

The Asian Bulletin of Big Data Management

Published Date

2024/3/24

An Ontology-Based Smart Irrigation System is presented in this research with the goal of improving agricultural water management. The main issue discussed is the inefficiency of conventional irrigation techniques, which results in water waste and lower crop yields. The process used entails creating an ontology, which includes defining concepts, establishing relationships, identifying domains, and populating the ontology. In order to facilitate real-time monitoring and decision-making, the irrigation system also incorporates sensors, actuators, and data processing algorithms. The main conclusions show that the ontology-based approach boosts crop output, encourages sustainable farming practices, and enhances water consumption efficiency. The findings of this study imply that ontology-based smart irrigation systems present a viable way to deal with the problems associated with water scarcity, improve agricultural output, and reduce their negative effects on the environment. The research adds to the expanding corpus of information on intelligent irrigation systems and emphasizes the significance of implementing cutting-edge technologies for agriculture's sustainable water management.

Exploring the Ethical and Technical Data of Machine Consciousness: Hazards, Implications, and Future Directions

Authors

Tanveer Rafiq,Muhammad Azam,Maher U Nisa,Mian Mohsin Sattar,Sana Zafar,Hiba Inam

Journal

The Asian Bulletin of Big Data Management

Published Date

2024/4/29

The study of machine consciousness has a wide range of potential and problems as it sits at the intersection of ethics, technology, and philosophy. This work explores the deep issues related to the effort to comprehend and maybe induce awareness in machines. Technically, developments in artificial intelligence, neurology, and cognitive science are required to bring about machine awareness. True awareness is still a difficult to achieve objective, despite significant progress being made in creating AI systems that are capable of learning and solving problems. The implications of machine awareness are profound in terms of ethics. Determining a machine's moral standing and rights would be crucial if it were to become sentient. It is necessary to give careful attention to the ethical issues raised by the development of sentient beings, the abuse of sentient machines, and the moral ramifications of turning off sentient technologies. Philosophically, the presence of machine consciousness may cast doubt on our conceptions of identity, consciousness, and the essence of life. It could cause us to reevaluate how we view mankind and our role in the cosmos. It is imperative that machine awareness grow responsibly in light of these challenges. The purpose of this study is to provide light on the present status of research, draw attention to possible hazards and ethical issues, and offer recommendations for safely navigating this emerging subject. We want to steer the evolution of machine consciousness in a way that is both morally just and technologically inventive by promoting an educated and transparent discourse.

Large-eddy simulation of airflow dynamics around a cluster of buildings

Authors

Sadia Siddiqa,Sahrish Batool Naqvi,Muhammad Azam,Md Mamun Molla

Journal

Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science

Published Date

2024/1

The wind flow around the buildings with different rooftops is studied numerically using large-eddy simulation (LES). The filtered Navier-Stokes equations in LES are used to compute the large eddies, whereas the dynamic Smagorinsky subgrid-scale (SGS) model calculates the small eddies. A turbulent spot method is applied for the synthesis of artificial turbulent fields at the inlet. In this separated and reattached flow, our aim is to analyze the wakes’ vortical structure along with the buildings of different heights and shapes. A large number of engineering applications involve precise predictions of the airflow around buildings to ensure performance and safety. To validate the numerical solver, a comparison is performed with the earlier reported numerical and experimental data. The turbulent flow characteristics are discussed in terms of instantaneous flow structure and time-averaged statistical flow quantities. All the cases …

Real‐Time Laryngeal Cancer Boundaries Delineation on White Light and Narrow‐Band Imaging Laryngoscopy with Deep Learning

Authors

Claudio Sampieri,Muhammad Adeel Azam,Alessandro Ioppi,Chiara Baldini,Sara Moccia,Dahee Kim,Alessandro Tirrito,Alberto Paderno,Cesare Piazza,Leonardo S Mattos,Giorgio Peretti

Journal

The Laryngoscope

Published Date

2024/1/4

Objective To investigate the potential of deep learning for automatically delineating (segmenting) laryngeal cancer superficial extent on endoscopic images and videos. Methods A retrospective study was conducted extracting and annotating white light (WL) and Narrow‐Band Imaging (NBI) frames to train a segmentation model (SegMENT‐Plus). Two external datasets were used for validation. The model's performances were compared with those of two otolaryngology residents. In addition, the model was tested on real intraoperative laryngoscopy videos. Results A total of 3933 images of laryngeal cancer from 557 patients were used. The model achieved the following median values (interquartile range): Dice Similarity Coefficient (DSC) = 0.83 (0.70–0.90), Intersection over Union (IoU) = 0.83 (0.73–0.90), Accuracy = 0.97 (0.95–0.99), Inference Speed = 25.6 (25.1–26.1) frames per second. The external …

Smart Healthcare Management Model for Proactive Patient Monitoring

Authors

Ammad Hussain,Muhammad Azam,Shehr Bano,Ahmad Nasir,Aimen Zara,Saba Parveen

Journal

The Asian Bulletin of Big Data Management

Published Date

2024/2/22

The rapid development of Artificial Intelligence (AI) is leading urban centers to employ AI technologies to improve efficiency and solve urban problems. This research proposes a Centralized System Model for Smart Cities (CSMSC) that centralizes AI-oriented data acquisition, processing, and decision-making. CSMSC uses real-time sensor networks for data collection, sophisticated AI algorithms for nuanced data interpretation, and unified storage for streamlined information management. Additionally, CSMSC integrates AI-based analyzers to autonomously produce alerts, evaluate their urgency, and decide upon suitable responses, enabling quick and targeted city interventions. The paper combines field evidence with theoretical frameworks to highlight the transformative potential of cognitive sensing and machine learning in smart city development. Recent studies have shown that AI on edge is revolutionizing the infrastructure of smart cities by bringing advanced intelligence and real-time analytics closer to the data source. AI on edge enables real-time decision-making, reduces latency, optimizes bandwidth usage, and enhances privacy and security. The potential benefits of using data analytics in smart cities are significant, and future research should focus on developing new algorithms and tools to analyze data and explore new IoT and machine-learning applications.

Viability of Free and Alginate–Carrageenan Gum Coated Lactobacillus acidophilus and Lacticaseibacillus casei in Functional Cottage Cheese

Authors

Muhammad Saeed,Rehana Khanam,Hammad Hafeez,Zulfiqar Ahmad,Shahzad Saleem,Muhammad Rizwan Tariq,Waseem Safdar,Muhammad Waseem,Umair Ali,Muhammad Azam,Muhammad Adil Rehman,Faiz-ul-Hassan Shah

Journal

ACS omega

Published Date

2024/3/14

The survivability of encapsulated and nonencapsulated probiotics consisting of Lactobacillus acidophilus and Lacticaseibacillus casei and the nutritional, physicochemical, and sensorial features of cottage cheese were investigated under refrigeration storage at 4 °C for 28 days. Microbeads of L. acidophilus and L. casei were developed using 2% sodium alginate, 1.5% sodium alginate and 0.5% carrageenan, and 1% sodium alginate and 1% carrageenan using an encapsulation technique to assess the probiotic viability in cottage cheese under different gastrointestinal conditions (SGF (simulated gastric juice), SIF (simulated intestinal fluid)), and bile salt) and storage conditions. Scanning electron microscopy (SEM) elucidated the stable structure of microbeads, Fourier transform infrared spectroscopy (FTIR) confirmed the presence probiotics in the microcapsules, and X-ray diffraction (XRD) demonstrated the …

A study on GIS-based spatial analysis of emergency response for disaster management: Focusing on Seoul

Authors

Hyun Soo Park,Seol A Kwon,Muhammad Azam

Journal

Heliyon

Published Date

2024/4/15

This study aims to analyze the operation of fire emergency dispatch, understand the impact of golden time on fire emergency dispatch, and identify factors and improvement measures for effective fire emergency dispatch with in prime time. According to the results of the study, rescue dispatch activities varies depending on the nature of the incident. The summer season had a higher number of calls than other seasons, and Saturday was the day of the week with the highest number of calls (i.e., Spring: 13,189, Summer: 15,652, Fall: 13,128, Winter: 14,545). When analyzing the spatial distribution of rescue incidents, it is found that rescue incidents were concentrated in some areas. In particular, the arrival time tended to be relatively long in areas south of the Han River and in areas where some fire stations or safety centers were not deployed. Results showed that rescue incidents dispatched by the stations other than …

Therapeutic Effect of Chia Seed Oil‐Based Ice Cream against Coronary Heart Disease in Wister Rat Model

Authors

Sabahat Amin,Muhammad Saeed,Iqra Yasmin,Muhammad Waheed Iqbal,Wahab Ali Khan,Muhammad Azam

Journal

Starch‐Stärke

Published Date

2024/1

The present study is designed to explore the therapeutic effect of chia seed oil (CSO) based ice cream against Coronary heart disease (CHD). CSO based ice cream is developed by using different concentrations of CSO (G2 3%, G3 5%, and G4 7%). The incorporation of CSO improves the DPPH activity of ice cream along with the betterment in the level of total phenolic content (TPC) and total flavonoid contet (TFC) without affecting the sensory attributes. The bio‐evaluation trials are carried out on male Wister rats by feeding them with CSO based ice cream for 45 days. Blood serum of rats is taken and analyzed after 0, 15, 30, and 45 day intervals for the determination of total cholesterol (TC), triglycerides (TG), high density lipoprotein (HDL), and low‐density lipoprotein (LDL). The results show a significant (p < 0.05) decrease (51%) in TG level in G3 (109.88–104.74 mg dL−1). HDL level is increased (25.23–35.78 …

A Novel Model of Narrative Memory for Conscious Agents

Authors

Muhammad Azam,Tanveer Rafiq,Falak Gul Naz,Maria Ghafoor,Maher Un Nisa,Hammad Malik

Journal

International Journal of Information Systems and Computer Technologies

Published Date

2024/1/3

The aim of Artificial General Intelligence (AGI) is to build machines with cognitive abilities on par with humans. These abilities include sensing, reasoning, decision-making, and social interaction. Although great strides have been achieved in creating intelligent agents that can observe and form opinions about their surroundings, problems still arise when it comes to their ability to reason and make decisions. The lack of a narrative structure inside these intelligent beings is a major drawback. This study suggests creating a narrative memory model with a dedicated module for use by self-aware agents. The model incorporates narrative memory to improve the agent's perception, understanding, and decision-making capabilities. The conscious agent will be able to create, store, and recall narrative-like representations of prior experiences with the help of the narrative memory module. To help the agent make sense of its surroundings, this narrative structure will give a method for categorizing and linking data. The agent will be able to recognize patterns, determine causal linkages, and extrapolate future outcomes by drawing on its narrative memory. There are several benefits to incorporating narrative memory into the brain of a self-aware agent. First, it'll give the agent a richer context from which to draw insights and make judgments. Second, the agent's perception and interpretation of complicated circumstances, as well as its general reasoning abilities, will be bolstered by the narrative memory module. Thirdly, the agent will be able to develop over time by absorbing new information and incorporating it into its preexisting narrative memory. This study …

Additive engineering enabled non-radiative defect passivation with improved moisture-resistance in efficient and stable perovskite solar cells

Authors

Muhammad Azam,Zhicheng Ke,Junsheng Luo,Zhongquan Wan,Ali Hassan,Chunyang Jia

Journal

Chemical Engineering Journal

Published Date

2024/2/7

Perovskite solar cells have emerged as promising candidates in the photovoltaic industry owing to their high efficiencies and low production costs. However, their commercial viability has been hampered by issues related to long-term environmental and operational stability, and their efficiency is lower than the Shockley–Queisser (SQ) limit. In this study, we explored a groundbreaking approach to enhance the efficiency and stability of CH3NH3PbI3 perovskite solar cells via the additive engineering of tetraphenylphosphonium chloride (TPPP(Cl)). By introduction of TPPP(Cl) into perovskite precursor, we demonstrated a notable amelioration in the photovoltaic performance of respective device. The presence of TPPP(Cl) enhances the crystallinity of the perovskite film, and the Cl from TPPP(Cl) can passivate halide ion defects, resulting in reduced defect density and improved charge carrier mobility. This in turn, leads …

Multi-criteria Radio Frequency Identification Approach for Manufacturing Company Selection Based on Partitioned Maclaurin Symmetric Mean Operators Under Complex Intuitionistic …

Authors

Muhammad Azam,Chiranjibe Jana,Muhammad Sajjad Ali Khan,Madhumangal Pal,Qin Xin,Shilin Yang,Biswajit Sarkar

Journal

International Journal of Fuzzy Systems

Published Date

2024/3/13

The theory of intuitionistic fuzzy sets (IFSs) plays an essential role to deal with uncertainty and ambiguity. However, the IFSs deal only with anticipation, not periodicity. But, complex IFSs (CIFS) can handle both uncertainties and periodicity at a time. Therefore, this paper focuses on a new multi-criteria decision making (MCDM) approach using Maclaurin symmetric mean (MSM) operator in connection with the CIFS setting. Then, we develop some CIF partitioned based MSM (CIFPMSM) operators and their weighted form by considering that all the criteria can be arranged into some groups. The proposed operators not only deal with the interrelationship among criteria but also deal with the partitioned relationship among criteria. We discuss the properties of these proposed operators and investigate their cases. Finally, a decision-making approach for radio frequency identification (RFID) for manufacturing companies is …

Optimization of an ultrasound‐assisted extraction method to obtain gallic acid‐rich extracts from mango seed kernels

Authors

Tuba Riaz,Zafar Hayat,Kinza Saleem,Kashif Akram,Hafeez Ur Rehman,Shafiq ur Rehman,Muhammad Azam

Journal

Food Science & Nutrition

Published Date

2024/4/12

Gallic acid is a widely recognized bioactive compound that falls under the category of secondary polyphenolic metabolites and is fairly found in mango fruit waste, specifically in mango seed kernel (MSK). This study aimed to adopt a green extraction approach to extract this valuable compound via ultrasound‐assisted extraction (UAE) without using organic solvents but only water to obtain hazard‐free extracts, and the cost of extraction can be minimal. pH (2–8), solvent ratio (20–60 mL/g), temperature (30–60°C) and time (30–60 min) of extraction were the independent variables used for extraction optimization. Single‐factor experiments to obtain working ranges for selected extraction variables were carried out. A central composite design using response surface methodology was used to determine the optimum condition to obtain the maximum yield of gallic acid from MSK. The optimized extraction conditions …

Control charts using half-normal and half-exponential power distributions using repetitive sampling

Authors

Muhammad Naveed,Muhammad Azam,Nasrullah Khan,Muhammad Aslam,Muhammad Saleem,Muhammad Saeed

Journal

Scientific Reports

Published Date

2024/1/2

This manuscript presents the development of an attribute control chart (ACC) designed to monitor the number of defective items in manufacturing processes. The charts are specifically tailored using time-truncated life test (TTLT) for two lifetime data distributions: the half-normal distribution (HND) and the half-exponential power distribution (HEPD) under a repetitive sampling scheme (RSS). To assess the effectiveness of the proposed control charts, both in-control (IC) and out-of-control (OOC) scenarios are considered by deriving the average run length (ARL). Various factors, including sample sizes, control coefficients, and truncated constants for shifted phases, are taken into account to evaluate the performance of the charts in terms of ARL. The behavior of ARLs is analyzed in the shifted process by introducing shifts in its parameters. The superiority of the HEPD-based chart is highlighted by comparing it with both …

See List of Professors in Dr. Muhammad Azam University(University of Veterinary and Animal Sciences)

Dr. Muhammad Azam FAQs

What is Dr. Muhammad Azam's h-index at University of Veterinary and Animal Sciences?

The h-index of Dr. Muhammad Azam has been 43 since 2020 and 50 in total.

What are Dr. Muhammad Azam's top articles?

The articles with the titles of

A resubmission-based variable control chart

Comparative Assessment of Bioactive Compounds, Fruit Quality Attributes and Sugar Profiling in Early Maturing Table Grape (Vitis Vinifera L.) Cultivars from Pothohar, Pakistan

A Single-Switch Trans-Inverse High Step-Up Semi-Quadratic DC-DC Converter Based on Three-Winding Coupled-Inductor

Modulating plant-soil microcosm with green synthesized ZnONPs in arsenic contaminated soil

Phyto-fabrication of copper oxide nanoparticles (NPs) utilizing the green approach exhibits antioxidant, antimicrobial, and antifungal activity in Diospyros kaki fruit

The Influence of Moderate Leverage Impact of Liquidity Ratios on the Financial Performance of the Sugar Sector in Pakistan

Synergistic partnerships of endophytic fungi for bioactive compound production and biotic stress management in medicinal plants

Ontology-Based Smart Irrigation System: Enhancing Agricultural Water Management: Ontology-Based Smart Irrigation System

...

are the top articles of Dr. Muhammad Azam at University of Veterinary and Animal Sciences.

What are Dr. Muhammad Azam's research interests?

The research interests of Dr. Muhammad Azam are: Decision Trees, Ensemble Classifiers, Statistical Quality Control and Survey Sampling

What is Dr. Muhammad Azam's total number of citations?

Dr. Muhammad Azam has 10,166 citations in total.

What are the co-authors of Dr. Muhammad Azam?

The co-authors of Dr. Muhammad Azam are Dr Muhammad Aslam, Chien-Wei Wu, Fernando Berzal, Mohammad Saber Fallah Nezhad, Dr. Nasrullah Khan.

    Co-Authors

    H-index: 47
    Dr Muhammad Aslam

    Dr Muhammad Aslam

    King AbdulAziz University

    H-index: 35
    Chien-Wei Wu

    Chien-Wei Wu

    National Tsing Hua University

    H-index: 22
    Fernando Berzal

    Fernando Berzal

    Universidad de Granada

    H-index: 22
    Mohammad Saber Fallah Nezhad

    Mohammad Saber Fallah Nezhad

    Yazd University

    H-index: 21
    Dr. Nasrullah Khan

    Dr. Nasrullah Khan

    University of Veterinary and Animal Sciences

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