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Error assessment of laser cutting predictions by semi-supervised learning

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Journal of Central South University 2014年第10期21卷 3736-3745页

作者： Mustafa Zaidi Imran Amin Ahmad Hussain Nukman Yusoff Department of Computing Shaheed Zulfikar Ali Bhutto Institute of Science & Technology (SZABIST) Department of Nuclear Engineering King Abdulaziz University Manufacturing Systems Integration Department of Mechanical Engineering University of Malaya

Experimentation data of perspex glass sheet cutting, using CO2 laser, with missing values were modelled with semi-supervised artificial neural networks. Factorial design of experiment was selected for the verification of orthogonal array based model prediction. It shows improvement in modelling of edge quality and kerf width by applying semi-supervised learning algorithm, based on novel error assessment on simulations. The results are expected to depict better prediction on average by utilizing the systematic randomized techniques to initialize the neural network weights and increase the number of initialization. Missing values handling is difficult with statistical tools and supervised learning techniques; on the other hand, semi-supervised learning generates better results with the smallest datasets even with missing values.

关键词： semi-supervised learning training algorithm kerf width edge quality laser cutting process artificial neural network(ANN)

Multi-Level Knowledge Engineering Approach for Mapping Implicit Aspects to Explicit Aspects

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Computers, Materials & Continua 2022年第2期70卷 3491-3509页

作者： Jibran Mir Azhar Mahmood Shaheen Khatoon Computer science Department Shaheed Zulfikar Ali Bhutto Institute of Science and Technology(SZABIST)Faculty of Computing and Engineering SciencesIslamabadPakistan Department of Computer science Capital University of Science&TechnologyFaculty of ComputingIslamabad College of Computer science and Information technology King Faisal UniversitySaudi Arabia

Aspect’s extraction is a critical task in aspect-based sentiment analysis,including explicit and implicit aspects *** extensive research has identified explicit aspects,little effort has been put forward on implicit aspects extraction due to the complexity of the ***,existing research on implicit aspect identification is widely carried out on product reviews targeting specific aspects while neglecting sentences’dependency ***,in this paper,a multi-level knowledge engineering approach for identifying implicit movie aspects is *** proposed method first identifies explicit aspects using a variant of BiLSTM and CRF(Bidirectional Long Short Memory-Conditional Random Field),which serve as a memory to process dependent sentences to infer implicit *** can identify implicit aspects from four types of sentences,including independent and three types of dependent *** study is evaluated on a largemovie reviews dataset with 50k *** experimental results showed that the explicit aspect identification method achieved 89%F1-score and implicit aspect extraction methods achieved 76%*** addition,the proposed approach also performs better than the state-of-the-art techniques(NMFIAD andML-KB+)on the product review dataset,where it achieved 93%precision,92%recall,and 93%F1-score.

关键词： Movie NEs(named entities) aspects opinion words annotation process memory implicit aspects implicit aspects mapping word embedding and BiLSTM

A Simple Human Vulnerability Index to Climate Change Hazards for Pakistan

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International Journal of Disaster Risk science 2012年第3期3卷 163-176页

作者： Fazal ali Khan ali Salman Social science and Economics Department Shaheed Zulfikar Ali Bhutto Institute of Science and Technology(SZABIST)Islamabad 44000Pakistan Rural Support Programmes Network(RSPN) Islamabad 44000Pakistan Development Pool Islamabad 44000Pakistan

This article explores the spatial pattern of vulnerability to climate change hazards in Pakistan by developing a Human Vulnerability Index(HVI). For this purpose, we use Population Census 1998 and Agriculture Census 2000 data. The HVI places the 103 districts of Pakistan in rank order and looks at whether there is a correlation between human vulnerability and exposure to disaster of the districts with respect to climate change hazards such as floods. The HVI is further validated using an independent flood recovery data set. The study found that the HVI is a useful tool for identifying vulnerable regions and districts for resource allocation. But the HVI is a poor tool for vulnerability assessment at community and household levels. For this purpose we used logistic regression analysis, which indicates that the adult literacy rate, ownership of livestock, and access to electricity are the three(out of six) key variables that play a critical positive role in recovery after the 2010 floods. The primary data collected from households also reveal that the 2010 Pakistan floods have equally affecte d standing crops, livestock, and house structures. More than two-thirds of sample households had rebuilt their house structures, whereas livestock recovery was negligible since the floods. We also found that the 2010 floods affected some of the poverty regions of the country, but that there is a very weak systematic correlation between human vulnerability and disaster exposure.

关键词： floods disaster district

Smart Healthcare Using Data-Driven Prediction of Immunization Defaulters in Expanded Program on Immunization (EPI)

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Computers, Materials & Continua 2021年第1期66卷 589-602页

作者： Sadaf Qazi Muhammad Usman Azhar Mahmood Aaqif Afzaal Abbasi Muhammad Attique Yunyoung Nam Predicitive Analytics Laboratory Shaheed Zulfikar Ali Bhutto Institute of Science and TechnologyIslamabad44000Pakistan Department of Software Engineering Foundation University IslamabadIslamabad44000Pakistan Department of Software Sejong UniversitySeoul05006Korea Department of Computer science and Engineering Soonchunhyang UniversityAsan31538Korea

Immunization is a noteworthy and proven tool for eliminating lifethreating infectious diseases,child mortality and *** Program on Immunization(EPI)is a nation-wide program in Pakistan to implement immunization activities,however the coverage is quite low despite the accessibility of free *** study proposes a defaulter prediction model for accurate identification of *** proposed framework classifies defaulters at five different stages:defaulter,partially high,partially medium,partially low,and unvaccinated to reinforce targeted interventions by accurately predicting children at high risk of defaulting from the immunization *** machine learning algorithms are applied on Pakistan Demographic and Health Survey(2017–18)*** Perceptron yielded 98.5%accuracy for correctly identifying children who are likely to default from immunization series at different risk stages of being *** this paper,the proposed defaulters’prediction framework is a step forward towards a data-driven approach and provides a set of machine learning techniques to take advantage of predictive ***,predictive analytics can reinforce immunization programs by expediting targeted action to reduce ***,the accurate predictions support targeted messages sent to at-risk parents’and caretakers’consumer devices(e.g.,smartphones)to maximize healthcare outcomes.

关键词： Smart healthcare routine immunization predictive analytics defaulters vaccination machine learning targeted messaging

Visibility Enhancement of Scene Images Degraded by Foggy Weather Condition: An Application to Video Surveillance

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Computers, Materials & Continua 2021年第9期68卷 3465-3481页

作者： Ghulfam Zahra Muhammad Imran Abdulrahman M.Qahtani Abdulmajeed Alsufyani Omar Almutiry Awais Mahmood Fayez Eid Alazemi Department of Computer science Shaheed Zulfikar Ali Bhutto Institute of Science and TechnologyIslamabad44000Pakistan Department of Computer science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia College of Applied Computer science King Saud University(Almuzahmiyah Campus)Riyadh11543Saudi Arabia Department of Computer science and Information Systems College of Business StudiesPAAET12062Kuwait

:In recent years,video surveillance application played a significant role in our daily *** taken during foggy and haze weather conditions for video surveillance application lose their authenticity and hence reduces the *** reason behind visibility enhancement of foggy and haze images is to help numerous computer and machine vision applications such as satellite imagery,object detection,target killing,and *** remove fog and enhance visibility,a number of visibility enhancement algorithms and methods have been proposed in the ***,these techniques suffer from several limitations that place strong obstacles to the real world outdoor computer vision *** existing techniques do not perform well when images contain heavy fog,large white region and strong atmospheric *** research work proposed a new framework to defog and dehaze the image in order to enhance the visibility of foggy and haze *** proposed framework is based on a Conditional generative adversarial network(CGAN)with two networks;generator and discriminator,each having distinct *** generator network generates fog-free images from foggy images and discriminator network distinguishes between the restored image and the original fog-free *** are conducted on FRIDA dataset and haze *** assess the performance of the proposed method on fog dataset,we use PSNR and SSIM,and for Haze dataset use e,r−,andσas performance *** results shows that the proposed method achieved higher values of PSNR and SSIM which is 18.23,0.823 and lower values produced by the compared method which are 13.94,0.791 and so *** results demonstrated that the proposed framework Has removed fog and enhanced the visibility of foggy and hazy images.

关键词： Video surveillance degraded images image restoration transmission map visibility enhancement

Hybrid Evolutionary Algorithm Based Relevance Feedback Approach for Image Retrieval

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Computers, Materials & Continua 2022年第1期70卷 963-979页

作者： Awais Mahmood Muhammad Imran Aun Irtaza Qammar Abbas Habib Dhahri Esam Mohammed Asem Othman Arif Jamal Malik Aaqif Afzaal Abbasi College of Applied Computer science King Saud University(Almuzahmiyah Campus)Riyadh11543Saudi Arabia shaheed zulfikar ali bhutto institute of science and technology(Islamabad Campus) 44000Pakistan University of Engineering and technology Taxila Pakistan International Islamic University Islamabad44000Pakistan Faculty of sciences and technology University of KairouanSidi Bouzid4352Tunisia Department of Software Engineering Foundation University IslamabadIslamabad44000Pakistan

Searching images fromthe large image databases is one of the potential research areas of multimedia *** most challenging task for nay CBIR system is to capture the high level semantic of *** researchers of multimedia domain are trying to fix this issue with the help of Relevance Feedback(RF).However existing RF based approaches needs a number of iteration to fulfill user’s *** paper proposed a novel methodology to achieve better results in early iteration to reduce the user interaction with the *** previous research work it is reported that SVM based RF approach generating better results for ***,this paper focused on SVM based RF *** enhance the performance of SVM based RF approach this research work applied Particle Swarm Optimization(PSO)and Genetic Algorithm(GA)before applying SVM on user *** main objective of using thesemeta-heuristic was to increase the positive image sample size from *** steps PSO is applied by incorporating the user feedback and secondly GA is applied on the result generated through PSO,finally SVM is applied using the positive sample generated through *** proposed technique is named as Particle Swarm Optimization Genetic Algorithm-Support Vector Machine Relevance Feedback(PSO-G A-SVMRF).Precisions,recall and F-score are used as performance metrics for the assessment and validation of PSO-GA-SVM-RF approach and experiments are conducted on coral image dataset having 10908 *** experimental results it is proved that PSO-GA-SVM-RF approach outperformed then various well known CBIR approaches.

关键词： Feature selection image retrieval particle swarm optimization

Weapons Detection for Security and Video Surveillance Using CNN and YOLO-V5s

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Computers, Materials & Continua 2022年第2期70卷 2761-2775页

作者： Abdul Hanan Ashraf Muhammad Imran Abdulrahman M.Qahtani Abdulmajeed Alsufyani Omar Almutiry Awais Mahmood Muhammad Attique Mohamed Habib Department of Computer science Shaheed Zulfikar Ali Bhutto Institute of Science and TechnologyIslamabad44000Pakistan Department of Computer science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia College of Applied Computer science King Saud University(Almuzahmiyah Campus)Riyadh11543Saudi Arabia Department of Computer science HITEC UniversityTaxila47080Pakistan College of Computing and Informatics Saudi Electronic UniversityRiyadhSaudi Arabia Faculty of Engineering Port Said UniversityPort Fuad CityEgypt

In recent years,the number of Gun-related incidents has crossed over 250,000 per year and over 85%of the existing 1 billion firearms are in civilian hands,manual monitoring has not proven effective in detecting *** is why an automated weapon detection system is *** automated convolutional neural networks(CNN)weapon detection systems have been proposed in the past to generate good ***,These techniques have high computation overhead and are slow to provide real-time detection which is essential for the weapon detection *** models have a high rate of false negatives because they often fail to detect the guns due to the low quality and visibility issues of surveillance *** research work aims to minimize the rate of false negatives and false positives in weapon detection while keeping the speed of detection as a key *** proposed framework is based on You Only Look Once(YOLO)and Area of Interest(AOI).Initially,themodels take pre-processed frames where the background is removed by the use of the Gaussian blur *** proposed architecture will be assessed through various performance parameters such as False Negative,False Positive,precision,recall rate,and F1 *** results of this research work make it clear that due to YOLO-v5s high recall rate and speed of detection are *** reached 0.010 s per frame compared to the 0.17 s of the Faster *** is promising to be used in the field of security and weapon detection.

关键词： Video surveillance weapon detection you only look once convolutional neural networks

Laboratory biosafety and biosecurity related education in Pakistan:Engaging students through the Socratic method of learning

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Journal of Biosafety and Biosecurity 2021年第1期3卷 22-27页

作者： Sahrish Muneer Hammad Afzal Kayani Kashif ali Ehtesham Asif Raheela Rehmat Zohra Furqan Kabir Department of Paediatrics&Child Health Aga Khan UniversityKarachiPakistan Department of Biosciences Shaheed Zulfiqar Ali Bhutto Institute of Science and TechnologyKarachiPakistan Department of Biotechnology University of KarachiPakistan

Background:Laboratory biosafety is currently a major global issue in clinical research and academic *** alleviate these concerns,subject-specific education of standardized laboratory practices is essential and should be delivered in a comprehensible,interactive,and appealing *** objective of the present study was to engage university-level students in laboratory biosafety and biosecurity related education through the Socratic method of learning.A pre/post-test model was implemented to assess the knowledge improvement after the ***:Two workshops were conducted individually at a public and private educational institute in October 2019 and December 2019,*** concepts were delivered in an interactive engagement format to ensure substantive ***-and post-training scores were computed,and a paired t-test was used to assess knowledge ***:Out of the 357 students from both institutes,320(90%)provided consent and completed the preand post-test *** participants lacked a baseline knowledge of laboratory biosafety.A statistically significant increase(14%to 84%)in knowledge was reported among students,with a p-value of<*** improved in the post-test assessment,where 87%were high performers,and only 1%were low-performing *** difference between the pre-and post-test mean scores was indicative of a substantial 70%improvement in *** exhibited high levels of satisfaction with the Socratic method of teaching ***:The study highlighted the significance of the Socratic style of learning for engaging students and improving their knowledge and awareness of laboratory biosafety in academic settings in Pakistan.

关键词： Laboratory biosafety Biosecurity Philosophy of containment Bio-risk management Socratic method of learning

Interconnection of Green Marketing and Green Human Resource Management Functions

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Macro Management & Public Policies 2022年第3期4卷 7-13页

作者： Waseem Ahmed Ibrahim Hussein Ahmed School of Business Administration Zhejiang Gongshang UniversityHangzhouZhejiangChina Zhejiang Gongshang University HangzhouZhejiangChina shaheed zulfikar ali bhutto institute of science and technology Larkana

Over the globe,we are moving to industrialization,which expands business creation,innovation,and different business *** also expands human comfort,yet in addition,builds its way of *** any case,on the opposite side,it likewise increments environmental danger that came about biological dangers to *** article highlights the importance of green HRM practices for effective green *** green human asset(the executives)has to make green mindfulness among the new ability and the current representative working for the association,energize their workers for helping the association to lessen the reasons for ecological debasement through green development,green projects and practices,hold the assets for the group of people yet to *** on extensive literature review,it is found that green HRM can create readiness,motivation and pledge to workers to contribute their endeavors and thoughts to the greening of their association for real reflection to the consumers in endeavors to cope with green skepticism and greenwash for effective green marketing and corporate social identity.

关键词： Greenwash Green skepticism Corporate social responsibility Green trust