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Identification of Software Bugs by Analyzing Natural Language-Based Requirements Using Optimized Deep Learning Features

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Computers, Materials & Continua 2024年第3期78卷 4379-4397页

作者： Qazi Mazhar ul Haq Fahim Arif Khursheed Aurangzeb noor ul ain Javed Ali Khan Saddaf Rubab Muhammad Shahid Anwar Department of Computer Science and Engineering and International Bachelor’s Program in Informatics Yuan Ze UniversityZhongliTaoyuan320315Taiwan Department of Computer Science National University of PakistanRawalpindiPunjab46000Pakistan Department of Computer Software Engineering MCSNational University of Sciences and TechnologyIslamabad44000Pakistan Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Department of Computer Science School of PhysicsEngineering and Computer ScienceUniversity of HertfordshireHatfieldAL109ABUK Department of Computer Engineering College of Computing and InformaticsUniversity of SharjahSharjah27272United Arab Emirates Department of AI and Software Gachon UniversitySeongnam-SI13120South Korea

Software project outcomes heavily depend on natural language requirements,often causing diverse interpretations and issues like ambiguities and incomplete or faulty requirements.Researchers are exploring machine learning to predict software bugs,but a more precise and general approach is needed.Accurate bug prediction is crucial for software evolution and user training,prompting an investigation into deep and ensemble learning methods.However,these studies are not generalized and efficient when extended to other datasets.Therefore,this paper proposed a hybrid approach combining multiple techniques to explore their effectiveness on bug identification problems.The methods involved feature selection,which is used to reduce the dimensionality and redundancy of features and select only the relevant ones;transfer learning is used to train and test the model on different datasets to analyze how much of the learning is passed to other datasets,and ensemble method is utilized to explore the increase in performance upon combining multiple classifiers in a model.Four National Aeronautics and Space Administration(NASA)and four Promise datasets are used in the study,showing an increase in the model’s performance by providing better Area Under the Receiver Operating Characteristic Curve(AUC-ROC)values when different classifiers were combined.It reveals that using an amalgam of techniques such as those used in this study,feature selection,transfer learning,and ensemble methods prove helpful in optimizing the software bug prediction models and providing high-performing,useful end mode.

关键词： Natural language processing software bug prediction transfer learning ensemble learning feature selection

State of Health Estimation of LiFePO_(4) Batteries for Battery Management Systems

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Computers, Materials & Continua 2022年第11期73卷 3149-3164页

作者： Areeb Khalid Syed Abdul Rahman Kashif noor ul ain Ali Nasir Department of Electrical Engineering University of Engineering and TechnologyLahorePakistan Department of Electrical Engineering University of Central PunjabLahorePakistan

When considering the mechanism of the batteries,the capacity reduction at storage(when not in use)and cycling(during use)and increase of internal resistance is because of degradation in the chemical composition inside the batteries.To optimize battery usage,a battery management system(BMS)is used to estimate possible aging effects while different load profiles are requested from the grid.This is specifically seen in a case when the vehicle is connected to the net(online through BMS).During this process,the BMS chooses the optimized load profiles based on the least aging effects on the battery pack.The major focus of this paper is to design an algorithm/model for lithium iron phosphate(LiFePO4)batteries.The model of the batteries is based on the accelerated aging test data(data from the beginning of life till the end of life).The objective is to develop an algorithm based on the actual battery trend during the whole life of the battery.By the analysis of the test data,the complete trend of the battery aging and the factors on which the aging is depending on is identified,the aging model can then be recalibrated to avoid any differences in the production process during cell manufacturing.The validation of the model was carried out at the end by utilizing different driving profiles at different C-rates and different ambient temperatures.A Linear and non-linear model-based approach is used based on statistical data.The parameterization was carried out by dividing the data into small chunks and estimating the parameters for the individual chunks.Self-adaptive characteristic map using a lookup table was also used.The nonlinear model was chosen as the best candidate among all other approaches for longer validation of 8-month data with real driving data set.

关键词： Aging model state of health lithium-ion cells battery management system state of charge battery modeling

Nd-doped NiFe_(2)O_(4) and its composite with CNTs to tune photocatalytic activity

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Journal of Rare Earths 2023年第12期41卷 1919-1928,I0004页

作者： Fatimah Mohammed AAlzahrani Amna Irshad Sonia Zulfiqar Z.A.Alrowaili noor ul ain Asima Anwar Muhammad Farooq Warsi M.S.Al-Buriahi Department of Chemistry CollegeofSciencePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabi Institute of Chemistry Baghdad-ul-Jadeed CampusThe Islamia University of BahawalpurBahawalpur6310Pakistan Department of Chemistry Faculty of ScienceUniversity of Ostrava30.Dubna 22Ostrava70103Czech Republic Department of Chemicaland Biological Engineering Iowa State UniversitySweeney Hall618 Bissll RoadAmesIowa 50011United States Department of Physics College of ScienceJouf UniversityPo.Box 2014SakakaSaudi Arabia Institute of Physics Baghdad-ul-Jadeed CampusThe Islamia University of BahawalpurBahawalpur63100Pakistan Department of Physics Sakarya UniversitySakaryaTurkey

Rare earth-doped spinel nano ferrites are attaining importance as heterogeneous nanocatalysts for the degradation of organic effluents.Rare earth metal doping increases the electrical and optical properties,as well as the surface-to-volume ratio of the bare sample.In this work,NiFe_(2)O_(4)(NF) and Nd-NiFe_(2)O_(4)(NF-1) were successfully synthesized via the co-precipitation route.Carbon nanotubes(CNT)-based nanocomposite(NF-2) was prepared using the ultra-sonication method.The prepared materials were analyzed via various physiochemical approaches.The degradation efficiency of these materials was analyzed for the degradation of Rhodamine B,methylene blue,and benzoic acid,NF-2 shows the highest efficiency among all the prepared catalysts.NF-2 shows 83.87%,90.80%,and 66.96% degradation of Rhodamine B,methylene blue,and benzoic acid,respectively.The reason for the superior activity of NF-2 is the existence of rare earth Nd ions and CNTs.The surface area of NF increases due to the presence of carbon nanotubes and enhanced surface area provides more active sites for the degradation reaction.

关键词： XRD Carbon nanotubes Benzoic acid Photo-degradation Visible light Rare earths

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预算管理对企业组织绩效的影响研究

预算管理对企业组织绩效的影响研究

作者： noor ul ain 华北电力大学(北京)

学位级别：硕士

预算编制是对企业组织绩效管控有效的、体系化的方法,应用于组织计划的履行、协同安排和控制,以定量的方式对计划进行概括描述,运用多方面的管理知识,提升企业组织目标的满意度。通过预算编制,可以有效衡量组织计划,在规定的时间跨度之... 详细信息

预算编制是对企业组织绩效管控有效的、体系化的方法,应用于组织计划的履行、协同安排和控制,以定量的方式对计划进行概括描述,运用多方面的管理知识,提升企业组织目标的满意度。通过预算编制,可以有效衡量组织计划,在规定的时间跨度之前策划和支持,清晰掌握在这段时间内要交付的精心安排的工资或可能获得的利用率,以及用于实现既定目标的融资。预算控制使组织能够通过实现这些计划和检查活动来制定未来的组织计划是否符合行动过程;运用预算控制,是组织合理执行支出设计的基本确认和前提。本文重点研究了预算编制和预算控制技术对组织绩效的影响,具体开展了责任会计、零度基预算编制、参与性预算管理等对组织绩效的影响,并进行了差异分析。本文采用有针对性的抽样技术,研究者选取了大约80%的目标人群（纺织业）使用预算控制技术,数据收集的来源主要包括邮件调查和个人调查问卷,并利用SPSS软件对收集到的数据进行数字化转换。此外,本文利用SmartPLS3.0进行数据分析,报告了验证测量和结构模型的标准。

关键词：预算重要性差异分析责任会计零基预算参与式预算企业绩效

基于双芯光子晶体光纤的灵敏度增强型SPR生物传感器

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基于双芯光子晶体光纤的灵敏度增强型SPR生物传感器

作者： noor ul ain（艾恩）北京邮电大学

学位级别：硕士

近年来,基于表面等离子体共振(Surface Plasmon Resonance,SPR)的光子晶体光纤(Photonic crystal fiber,PCF)生物传感器引起了很多研究人员的关注。光纤等离子共振生物传感器被广泛用于病原体、毒素、抗体和蛋白质的检测中,在健康诊断... 详细信息

近年来,基于表面等离子体共振(Surface Plasmon Resonance,SPR)的光子晶体光纤(Photonic crystal fiber,PCF)生物传感器引起了很多研究人员的关注。光纤等离子共振生物传感器被广泛用于病原体、毒素、抗体和蛋白质的检测中,在健康诊断、生物医学、生化分析和环境监控等领域发挥重要作用。相比于基于Kretschmann大棱镜的传统表面等离子体共振生物传感器相比,光纤等离子共振生物传感器可在光纤内部实现折射率检测。现有的光纤等离子共振生物传感器一般利用微弱的光纤消逝场激发等离子共振效应,从而导致光纤等离子共振生物传感器灵敏度差等问题。此外,传统光纤生物传感器在光纤外部使用微流体设备来进行传感实验,因此其尺寸较大,结构也更加复杂。本文提出了一种双芯光纤等离子共振生物传感器。在光纤内部沉积了一层薄银(Ag)膜(20 nm)作为一种等离子体激发金属。与传统的光纤等离子共振生物传感器相比,本文提出的传感器将待测物质引入到光纤的中心空气孔内。这样种结构不仅可实现更小的传感器尺寸,还可以增加激发等离子共振效应的光场能量,从而传感器获得更高的灵敏度。通过仿真表明,当待测物质折射率变化范围为1.340至1.346时,通过波长解调法本文设计的双芯光纤等离子共振生物传感器可达到80,000nm/RIU灵敏度和1×104RIU的分辨率。通过幅度解调法在相同的折射率变化范围内,双芯光纤等离子共振生物传感器的灵敏度值为 997/RIU,分辨率为 1×10-4RIU。相比与传统光纤等离子共振生物传感器,改进后双芯光纤等离子共振生物传感器具有更便携的体积和更高的灵敏度。仿真表明传统基于消逝场方法的光纤等离子共振生物传感器灵敏度为10,000nm/RIU。与其相比,本文提出的双芯光纤等离子共振生物传感器最大灵敏度为80,000nm/RIU。灵敏度的提高可以提升生物传感器对分析物的检测能力。通过对各传感器各指标的比较,如结构、传感方法和折射率范围等,本文有效验证了所设计双芯光纤等离子共振生物传感器具有良好的性能。这种双芯光纤等离子共振生物传感器有望在生化检测、生物医药、环境检测等方面发挥作用。

关键词：光子晶体光纤双芯折射率生物传感器表面等离子体共振高灵敏度

Ougenioxylon chinjiensis sp. nov., a New Fossil Species of the Family Leguminosae from Chinji Formation Salt Range, Punjab Pakistan

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American Journal of Plant Sciences 2014年第26期5卷 3745-3751页

作者： noor-ul-ain Soomro Basir Ahmed Arain Muhammad Tahir Mehmood Rajput Institute of Plant Sciences University of Sindh Jamshoro Pakistan

This work is comprised of anatomical study of fossil wood collected from Chnji formation (72°22'E, 32°41'N) of Miocene age exposed at Chinji National Reservoir. The material consists of a single piece of petrified wood dark brown in colour. The three dimensional sections were prepared by ground thin section technique. Microscopic examination of the characters was compared with modern and fossil wood and found comparable with the family Leguminosae. The closest resemblance of our fossil wood is with the wood of Ougenia. This fossil wood shows close resemblance in respect of vessels, fibers, parenchyma and xylem rays character. Therefore it is considered as new species and it is named Ougenioxylon chienjiensis sp. nov. The specific epithet refers to Chinji formation to which fossil wood belongs.

关键词： Ougenia chinjiensis Fossil Wood Salt Range Punjab Pakistan

Multistage-batch bipolar membrane electrodialysis for base production from high-salinity wastewater

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Frontiers of Chemical Science and Engineering 2022年第5期16卷 764-773页

作者： Arif Hussain Haiyang Yan noor ul Afsar Chenxiao Jiang Yaoming Wang Tongwen Xu Department of Applied Chemistry Anhui Provincial Engineering Laboratory of Functional Membrane Science and TechnologySchool of Chemistry and Materials ScienceUniversity of Science and Technology of ChinaHefei 230026China

Bipolar membrane electrodialysis(BMED)is considered a state-of-the-art technology for the conversion of salts into acids and bases.However,the low concentration of base generated from a traditional BMED process may limit the viability of this technology for a large-scale application.Herein,we report an especially designed multistage-batch(two/three-stage-batch)BMED process to increase the base concentration by adjusting different volume ratios in the acid(Vacid),base(Vbase),and salt compartments(Vsalt).The findings indicated that performance of the two-stage-batch with a volume ratio of Vacid:Vbase:Vsalt=1:1:5 was superior in comparison to the threestage-batch with a volume ratio of Vacid:Vbase:Vsalt=1:1:2.Besides,the base concentration could be further increased by exchanging the acid produced in the acid compartment with fresh water in the second stage-batch process.With the two-stage-batch BMED,the maximum concentration of the base can be obtained up to 3.40 mol∙L^(-1),which was higher than the most reported base production by BMED.The low energy consumption and high current efficiency further authenticate that the designed process is reliable,cost-effective,and more productive to convert saline water into valuable industrial commodities.

关键词： bipolar membrane electrodialysis multistagebatch base production high-salinity wastewater

Female directors in the boardroom and intellectual capital performance:Does the“critical mass”matter?

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Financial Innovation 2023年第1期9卷 1995-2018页

作者： Hafiz Mustansar Javaid Qurat ul ain Rita D’Ecclesia Department of Social and Economic Sciences Sapienza Universitàdi RomaRomeItaly Dipartimento di Scienze Aziendali‑Management&Innovation Systems/DISA‑MIS University of SalernoSalernoItaly School of Economics and Finance Xi’an Jiaotong UniversityXi’anChina

This research aims to investigate the influence of female directors on Intellectual Capital Performance(ICP)using a sample of manufacturing-listed companies in China.Our study investigates the link between having two or more female directors and the Modified Value-Added Intellectual Coefficient(MVAIC)methodology,employing the critical mass theory from 2004–2017.We find that having a critical mass of female directors(three or more)shows a significant positive impact on MVAIC and its components,including human capital efficiency,structural capital efficiency,relational capital efficiency,and physical capital efficiency,with physical capital being the critical driver.Our study reveals that the critical mass participation of female directors substantially influences the IC efficiency of privately owned companies compared to state-owned companies.Moreover,the number of female directors also affects the IC performance of manufacturing companies in multiple regions.Our findings support the validity of group classification identified by Kanter and Critical Mass Theory.To the best of our knowledge,this is one of the few pieces of research that studies the role of female board directors in IC performance and Chinese manufacturing firms using MVAIC as an IC measure.

关键词： Corporate governance Female directors Critical mass Intellectual capital State-owned enterprises(SOEs) China

Recent trends,challenges,and perspectives in piezoelectric-driven self-chargeable electrochemical supercapacitors

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Carbon Energy 2022年第5期4卷 833-855页

作者： Karthikeyan Krishnamoorthy Parthiban Pazhamalai Sindhuja Manoharan noor ul Haq Liyakath Ali Sang-Jae Kim Nanomaterials&System Lab Major of Mechatronics EngineeringFaculty of Applied Energy SystemJeju National UniversityJejuSouth Korea Research Institute of Energy New Industry Jeju National UniversityJejuSouth Korea Nanomaterials&System Lab Major of Mechanical System EngineeringCollege of EngineeringJeju National UniversityJejuSouth Korea

The increasing demand for wearable electronic devices has resulted in tremendous progress in research on energy harvesting and storage devices/technologies.Energy storage devices require a power source to charge them,whereas energy harvesting devices require a storage compartment to store the harvested energy for sustainable delivery.Recently,a piezoelectrically driven self-charging supercapacitor power cell(SCSPC)was developed to harvest and store electrical energy in a solitary system to determine the potential impact of these two types of energy devices for wearable electronic applications.This review describes the recent advances in piezoelectric-driven SCSPCs in terms of device configuration,piezoelectric separator,electrolyte types,electrode materials,current collectors,and system integration.This review focuses specifically on the principles and mechanism of the self-charging process that occurred in the SCSPCs and the use of a promising piezo electrochemical spectroscopic tool to realize the piezo electrochemical energy transfer and storage process in the SCSPCs.Further,the current challenges and new perspectives for future developments in the emerging area of SCSPCs or integrated energy devices are discussed.

关键词： electrospinning integrated energy cell mechanical energy piezoelectric separators piezoelectrochemical spectroscopy self-charging supercapacitor power cell