Muhammad Umer

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Papers by Muhammad Umer

Sudden Cardiac Death: Vulnerability of Atherosclerotic Plaque in Coronary Arteries

PAFMJ, 2021

Objective: To assess the vulnerability of atherosclerotic plaque in coronary arteries of individu... more Objective: To assess the vulnerability of atherosclerotic plaque in coronary arteries of individuals dying of ischemic heart disease. Study Design: Cross sectional study. Place and Duration of Study: Histopathology department, Combined Military Hospital Lahore, from Nov 2016 to Nov 2017. Methodology: A total of 43 cases were taken in the study. The Autopsy specimens from the bodies of people dying suddenly of ischemic heart disease were taken into the study. Tissues showing autolytic changes and patients dying with coronary artery disease after corrective procedure like stenting and bypass were excluded. Results: Out of 43 cases, 35 (81.4%) cases were positive for cluster of differentiation 68 (CD 68), 34 (79%) cases were positive for cluster of differentiation 105 (CD 105) & 36 (83.6) cases were positive for nuclear factor kappa-light-chain-enhancer of activated B cells (NF-Kb). Conclusion: People who had died of ischemic heart disease have more vulnerable plaque in their coronary ...

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Implementation and Comparative Analysis of Semi-Automated Surveillance Algorithms in Real Time using Fast-NCC

2021 International Conference on Innovative Computing (ICIC), 2021

Chaotic environment, irregular motion of objects creates challenging environment in the field of ... more Chaotic environment, irregular motion of objects creates challenging environment in the field of computer vision. Advance target tracking techniques are used to overcome these problems, but few parameters are considered ideal in those scenarios, or those parameters are ignored. In this research, cross correlation technique is applied for target tracking which is famous for feature extraction in image processing. Further, normalized cross correlation and fast-normalized cross correlation are implemented and results are compared. As enormous computation is required in these techniques, real time target tracking is factual challenge faced by this technique. High performance embedded hardware is required to implement these techniques. In this research, digital signal processor embedded board TMS320DM642 is carefully chosen for this purpose. This board is equipped with evaluation module and video decoder. Above mentioned techniques are implemented on TMS320DM642 and their results are carefully analyzed in this research.

LEVELIW: Learning extreme verification latency with importance weighting

2017 International Joint Conference on Neural Networks (IJCNN), 2017

Nonstationary streaming data are characterized by changes in the underlying distribution between ... more Nonstationary streaming data are characterized by changes in the underlying distribution between subsequent time steps. Learning in such environments becomes even more challenging when labeled data are available only at the initial time step, and the algorithm is provided unlabeled data thereafter, a scenario referred to as extreme verification latency. Our previously introduced COMPOSE framework works very well in such settings. COMPOSE is a semi-supervised approach that iteratively labels strategically chosen instances of the next time step using the instances it labeled in the previous time step. COMPOSE originally assumed a significant distribution overlap at consecutive time steps, allowing instances lying in the center of the feature space to be used as the most representative labeled instances from current time step to help label the new data at the next time step. Such an assumption is also inherent in importance weighting based domain adaptation, but only for a single time step with mismatched train and test data distributions. We explore importance weighting not for a single time step matching training / test distributions, but rather matching distributions between two consecutive time steps, and estimate the posterior distribution of the unlabeled data using importance weighted least squares probabilistic classifier. The estimated labels are then iteratively used as the training data for the next time step. We call this algorithm as LEVELIW, Learning Extreme VErification Latency with Importance Weighting. Our primary goal in doing so is to determine if and when importance weighting provides an advantage over COMPOSE's core support extraction, and whether it provides an alternate solution with reduced parameter sensitivity. Several datasets are used to compare the two approaches, which produced some unique insights.

A Case Study of Career Counseling for ICT

ICT Solutions for Improving Smart Communities in Asia, 2021

In the education system, the students may find counselors, but student-to-counselor ratio is high... more In the education system, the students may find counselors, but student-to-counselor ratio is higher, which forces us to implement an automated system for the guidance of the students. Career counseling can be useful for students to evaluate their careers and select the best direction for the future. This chapter aims to explore, develop, and implement the effective means of analyzing student career counseling, guidelines, and decision making. The authors have developed a realistic dataset from a different mindset of students. The research started once the student provides the machine input about the individual choices about taking admission for matriculation, intermediate, and or short course. The machine learning algorithms like logistic model tree, naïve Bayes, J48, and random forest are used to predict career options. In evaluated results, they found the best algorithm based on the accuracy of kappa statistics, mean absolute error, and correctly classified or incorrectly classifi...

RFCNN:Traffic Accident Severity Prediction based on Decision Level Fusion of Machine and Deep Learning Model

IEEE Access, 2021

Traffic accidents on highways are a leading cause of death despite the development of traffic saf... more Traffic accidents on highways are a leading cause of death despite the development of traffic safety measures. The burden of casualties and damage caused by road accidents is very high for developing countries. Many factors are associated with traffic accidents, some of which are more significant than others in determining the severity of accidents. Data mining techniques can help in predicting influential factors related to crash severity. In this study, significant factors that are strongly correlated with the accident severity on highways are identified by Random Forest. Top features affecting accidental severity include distance, temperature, wind_Chill, humidity, visibility, and wind direction. This study presents an ensemble of machine learning and deep learning models by combining Random Forest and Convolutional Neural Network called RFCNN for the prediction of road accident severity. The performance of the proposed approach is compared with several base learner classifiers. The data used in the analysis include accident records of the USA from February 2016 to June 2020. Obtained results demonstrate that the RFCNN enhanced the decision-making process and outperformed other models with 0.991 accuracy, 0.974 precision, 0.986 recall, and 0.980 F-score using the 20 most significant features in predicting the severity of accidents.

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PCR-Free Detection of Long Non-Coding HOTAIR RNA in Ovarian Cancer Cell Lines and Plasma Samples

Cancers, 2020

Long non-coding RNA HOX transcript antisense intergenic RNA (HOTAIR) is one of the promising biom... more Long non-coding RNA HOX transcript antisense intergenic RNA (HOTAIR) is one of the promising biomarkers that has widely been used in determining the stages of many cancers, including ovarian cancer. In cancer diagnostics, the two key analytical challenges for detecting long non-coding RNA biomarkers are i) the low concentration levels (nM to fM range) in which they are found and ii) the analytical method where broad dynamic range is required (four to six orders of magnitude) due to the large variation in expression levels for different HOTAIR RNAs. To meet these challenges, we report on a biosensing platform for the visual (colorimetric) estimation and subsequent electrochemical quantification of ovarian-cancer-specific HOTAIR using a screen-printed gold electrode (SPE-Au). Our assay utilizes a two-step strategy that involves (i) magnetic isolation and purification of target HOTAIR sequences and (ii) subsequent detection of isolated sequences using a sandwich hybridization coupled w...

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Detection of the SARS-CoV-2 humanized antibody with paper-based ELISA

The Analyst, 2020

This work reports the development of a rapid, simple and inexpensive colorimetric paper-based ass... more

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Stock Market Prediction Using Machine Learning(ML)Algorithms

ADCAIJ: ADVANCES IN DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE JOURNAL, 2019

Stocks are possibly the most popular financial instrument invented for building wealth and are th... more Stocks are possibly the most popular financial instrument invented for building wealth and are the centerpiece of any investment portfolio. The advances in trading technology has opened up the markets so that nowadays nearly anybody can own stocks. From last few decades, there seen explosive increase in the average person’s interest for stock market. In a financially explosive market, as the stock market, it is important to have a very accurate prediction of a future trend. Because of the financial crisis and recording profits, it is compulsory to have a secure prediction of the values of the stocks. Predicting a non-linear signal requires progressive algorithms of machine learning with help of Artificial Intelligence (AI).In our research, we are going to use Machine Learning Algorithm specially focus on Linear Regression (LR), Three month Moving Average(3MMA), Exponential Smoothing (ES) and Time Series Forecasting using MS Excel as best statistical tool for graph and tabular repres...

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DFT modeling of thermoelectric and optical features of novel MgxSn1-xSe (x = 6%, 12% 18%)

Journal of Molecular Graphics and Modelling, 2019

This is a PDF file of an article that has undergone enhancements after acceptance, such as the ad... more This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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DNA methylation detection: recent developments in bisulfite free electrochemical and optical approaches

The Analyst, 2018

The recent development of optical and electrochemical biosensors for bisulfite treatment free DNA... more

LC-MS/MS based determination of chloramphenicol, thiamphenicol, florfenicol and florfenicol amine in poultry meat from the Punjab-Pakistan

Food additives & contaminants. Part A, Chemistry, analysis, control, exposure & risk assessment, Jan 12, 2018

A simple, reliable and sensitive liquid chromatography-tandem mass spectrometry based confirmator... more A simple, reliable and sensitive liquid chromatography-tandem mass spectrometry based confirmatory method was redeveloped and validated for the simultaneous determination of chloramphenicol, thiamphenicol, florfenicol and florfenicol amine in chicken muscles. The analytes were extracted from minced chicken muscle with acetonitrile and ammoniated water mixture. A second extraction with ethyl acetate was followed by evaporation and dissolution of the residue in ammoniated methanol before defatting with n-hexane. Finally, the extract was further cleaned up by dispersive solid phase extraction using C-18 end-capped dispersive material. The validation protocol was adapted from the European Commission Decision 2002/657/EC and all the performance characteristics were successfully satisfied. The recoveries of all the analytes were found to be in the range of 86.4% to 108.1% and the precision values, within day and between days, ranged from 2.7% to 11% and 4.4% to 16.3%, respectively. The me...

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A Research Review on Tomato Bushy Stunt Virus Disease Complex

Journal of Natural Sciences Research, 2014

Tomato Bushy Stunt Virus (TBSV) was firstly reported on tomatoes by Smith in 1935 in England. The... more Tomato Bushy Stunt Virus (TBSV) was firstly reported on tomatoes by Smith in 1935 in England. The virus belongs to genus Tombusvirus and family Tombusviridae, is a soil-borne virus with isometric particle about 30 nm in diameter. Tomato Bushy Stunt Virus can cause chlorosis, necrosis, stunting, leaf yellowing, leaf mottling, leaf crinkling and fruit setting may be reduced or become zero. These symptoms were depending upon the host morphology. Transmission of this virus is naturally through infected seeds, propagative material and manually by the use of infective cutting tools. A numbers of varieties were affected. But it's also observed that Lycopersicon pimpinellifolium not susceptible host plant. Gel Electropherotic analysis shows that virus distantly related serologically with several other viral species in the genus Tombusvirus. In phosphotungstic acid, the particles show an angular outline and unresolved surface structure but when mounted in uranyl acetate, they exhibit a rounded outline and somewhat knobby surface and edges. The viral genome is monopartite and TBSV-Ch has been completely sequenced and shown to contain 4,776 nucleotides. The protein shell is constructed by 180 subunits, each subunit contain Mr 41,000 and made icosahedral surface lattice. These subunits show a dimeric clustering on the surface of particles, which give rise to 90 morphological units. These were located on the twofold axes of the lattice. Each coat protein subunit contains 387 amino acid residues and has four regions.

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“Human Resource Management Theory and Practices in Small and Medium-Sized Enterprises (Smes) and Enterprises Performance in Pakistan”

Global Journal of Management and Business Research, Jul 30, 2012

Introduction-In the era of globalization, business environment becomes highly dynamic with high r... more Introduction-In the era of globalization, business environment becomes highly dynamic with high risk and uncertainty. This uncertainty decreases market share and increases organizational inefficiency. The increasing attention on human resource management (HRM) in small and medium enterprises (SMEs) is a comparatively recent phenomenon. HR-researchers have largely ignored the SMEs, even though smaller companies could be fruitful subjects for empirical investigation because of their numbers, the growth-rates and not least diversity in the qualitative aspects of management practices.

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Internationalization of Construction Services: A Comparison between Emerging and Developed Economies’ Construction Contracting Firms

ICCREM 2015, 2015

The international services literature lacks research investigating the association between corpor... more The international services literature lacks research investigating the association between corporate size and corporate international experience with the internationalization. Using an integrated theoretical approach, this paper examines the internationalization of construction service corporations (CSCs) with specific emphasis on four dimensions: motives, firm-specific competitive advantages, home country-specific competitive advantages and locational considerations. A quantitative approach was adopted through a postal questionnaire survey. Out of 126 CSCS, 84 usable responses were analyzed giving 66.7% response rate. A comparative analysis was conducted using Mann-Whitney U test between the corporations having different sizes and international experiences. The findings show that CSCs of varied sizes did not concur over several firm-specific competitive advantages and home country-specific competitive advantages, whereas CSCs of varied international experiences were in disagreement over some locational factors. Small CSCs need to form joint ventures or partnerships in order to overcome their limitations. The government support is direly needed to promote internationalization of CSCs especially the younger and smaller ones which stand more vulnerable due to lack of opportunities in their domestic markets. The study will be helpful to managers and regulatory bodies towards creating a balanced playing field to develop the internationalization process for their service corporations.

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Seroprevalence of avian influenza in broilers of district

A study on the seroprevalence of influenza virus in broilers was carried out. A total of 570 from... more A study on the seroprevalence of influenza virus in broilers was carried out. A total of 570 from broilers were randomly collected from 52 poultry farms of Quetta and its surroundings to determine the seroprevalence and antibody titre of avian influenza virus in the sera of broilers. The seroprevalence of avian influenza virus in the sera of was demonstrated by Enzyme Linked Immunosorbent Assay (ELISA). The sero-positive prevalence of avian influenza virus was recorded 14.03% (n=80) in broilers. All the positive sera of boilers determined by ELISA were further tested by using H 5 , H 7 , and H 9 specific strains antigen through Haemagglutination Inhibition and Haemagglutination tests, only H 9 was recognized from the sera of broilers. During present study the antibody titreof H9strain of avian influenza virus in the sera of broilers was investigated. The antibody titre of H 9 strain of avian influenza virus was measured in the sera of broilers ranged from 1:8 to 1:164. It is conclud...

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A Heuristic Approach for Type 2 Assembly Line Balancing Problem

Applied Mechanics and Materials, 2015

An assembly system consists of work stations where specific tasks are carried in such a way that ... more An assembly system consists of work stations where specific tasks are carried in such a way that last station gives the complete product. An assembly line balancing Problem (ALBP) involves optimally assigning tasks among workstations with respect to some performance objective. ALBP problems are of NP hard nature and in literature; many efforts are there to solve the problem efficiently through heuristics. This paper proposes a heuristic algorithm for solving type 2 ALBP for single objective optimization. The proposed algorithm assigns tasks to a fixed no of stations with objective of minimizing cycle time. In literature, type 2 ALBP is mostly solved through Type 1 problem. However, this paper proposes a direct approach to Type 2 ALBP. The effectiveness is tested through application on Gunther problem of 35 tasks with forty five precedence constraints. The task assignment for six stations is computed and it shows competitive performance. The number of fixed stations is varied and cor...

Need for Sustainable Land Management in Pakistan under the Changing Scenario of Climate

Overall thirty six types of land degradation could be assessed including 4 types emerged in the l... more Overall thirty six types of land degradation could be assessed including 4 types emerged in the last 50 years (pollution, loss of arable land, artificial radioactivity and land use constraints). All these usual (water, wind, mechanical erosion, physical, chemical and biological degradation) and newly emerged types are induced by anthropogenic activities. Climate change is further accelerating such degradation issues. Global extent of land degradation Salt prone area: 953 mha Physical degradation: 83 mha Chemical degradation: 239 mha Wind erosion: 549 mha Water erosion: 1094 mha Extent of land degradation in Pakistan Salt prone area: 6.68 mha Saline 3.77 mha Saline-sodic 2.91mha • References: 1. Brabant, P. 2009. A global land degradation assessment and mapping method. A standard guideline proposal. The briefing notes the CSFD. No Rationale: Over-exploitation and under-utilization of the natural resources especially soil and water, have challenged soil fertility management and hence ...

A cornucopia of screening and diagnostic techniques for human papillomavirus associated cervical carcinomas

Journal of Virological Methods, 2015

Cervical carcinoma is one of the major consequences of Human papillomavirus (HPV) infections. Alt... more Cervical carcinoma is one of the major consequences of Human papillomavirus (HPV) infections. Although HPV infections of cervix do not always progress to cancer, 90% cases of cervical cancer have been found associated with high risk HPV (hrHPV) infection. Usually, HPV infection is asymptomatic; however, this asymptomatic infection can cause abnormal changes in cervix ultimately leading to cancer development. These changes can be detected by the application of screening tests at regular time intervals. For this purpose, morphological, cytological, and DNA based techniques are available. Nevertheless, abnormal screening tests have only the predictive value for precancerous lesions and thus require further evaluation which is usually done by using diagnostic techniques. So far, colposcopy and histological examination alone were considered as the gold standards for cervical cancer diagnosis. Currently, some tests based on expression level of host cell biomarkers are also being used along with histology for diagnostic purpose. Albeit, these tests have significant specificity and sensitivity values but they are unable to suggest a particular viral genotype involved in infection. Diagnostic methods such as PCR, HPV genotyping assays, microarray, and mRNA based assays are useful to predict the genotypes as well as the quantity of viral load in a host cell. Similarly, these diagnostic procedures have high specificity and sensitivity ranges. However, only few of them are practiced commonly, as approval of these tests as routine diagnostic tests requires clinical validation and cost effectiveness.

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Intelligent pheromone up gradation mechanism through Neural augmented Ant Colony Optimization (NaACO) meta heuristic in machine scheduling

Scientia Iranica

The pheromone update phase in Ant Colony Optimization (ACO) has been addressed by various researc... more The pheromone update phase in Ant Colony Optimization (ACO) has been addressed by various researchers in the context of scheduling problems. Various Arti�cial Intelligence (AI) techniques have also been used to investigate and improve the pheromone trail in worker assignment issues at the workshop oor level. This paper proposes a novel way of investigating and analyzing the issue of pheromone assignment through the Neural augmented Ant Colony Optimization (NaACO) technique. The technique thus developed has its roots in combining the strengths of Arti�cial Neural Networks (ANN) and the extra ordinary convergence capabilities of Ant Colony Optimization (ACO), thus, formulating NaACO (Neural Augmented ACO). A set of one hundred problems has been taken and an extensive methodology has been formulated to address the issue of pheromone updates in worker assignments on these problems. The results have been formulated and areas of future research have also been indicated.

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Opportunistic sampling in wireless sensor networks

Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems - GIS '09, 2009

In an active WSN where user queries are regularly processed, a significant proportion of nodes re... more In an active WSN where user queries are regularly processed, a significant proportion of nodes relay and overhear data generated by other nodes in the network. In this paper, we propose to exploit this mode of data communication towards a gradual buildup of global knowledge. We show that by harnessing the multihop and multipath communication advantages, only a few user queries in a WSN can lead to an accumulation of accurate global knowledge at node level. This global knowledge can greatly improve numerous WSN applications when used in data validation, event detection, and query optimization.

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