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A Novel Complexity Scoring Model for Non-Functional Requirements in Request for Proposal in Housing Industry Using FURPS Quality and Moscow Priority Model

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International Journal for Housing science and Its Applications 2024年第4期45卷 30-40页

作者： Rashid, Ekbal Mastorakis, Nikos E. Technical University of Sofia Sofia Bulgaria Sector of Electrical Engineering and Computer Science Hellenic Naval Academy Piraeus Greece English Language Faculty of Engineering Technical University of Sofia Sofia Bulgaria

In this research paper we have attempted to elicit Non-Functional Requirements (NFR) which may or not have been explicitly added to the Request for Proposal (RFP) in housing industry but is important for the success of the program. We have used real time RFPs for the elicitation of NFRs. The sales proposal process, also known as response to RFP process, refers to the methodical steps a vendor takes when developing a proposal in response to a buyer’s RFP which will have details of integrating systems, Software platforms, users, business outcomes, limitations, functional requirements, and may be nonfunctional requirements (NFR). There is some work done by researchers on assessing opaqueness of NFRs and traceability of NFR. But there has been no work on a complexity scoring model for NFRs which enables a vendor to respond to an RFP with best price and schedule. The paper proposes a novel complexity scoring model for NFRs in RFP in Housing industry by using FURPS (Functionality, Usability, Reliability, Performance, Supportability) quality attribute model in conjunction with MoSCoW(Must Have, Should Have, Could Have, Won’t Have) priority model by using mathematical formula. The working model is broken down in steps for Sales and pre-Sales teams of the Vendor and is ready for adoption. © 2024 International Association for Housing science. All rights reserved.

关键词： complexity scoring model construction cost FURPS housing linear regression MoSCoW NFR RFP scatter plot

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Influence of Geometry Effects on Thermo-Mechanical Reliability of Aluminum Bond Wires in Discrete SiC MOSFETs 25

Influence of Geometry Effects on Thermo-Mechanical Reliabili...

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25th International Conference on Thermal, Mechanical and Multi-Physics Simulation and Experiments in Microelectronics and Microsystems, EuroSimE 2024

作者： Kilian, Borja Maniar, Youssef Gleichauf, Jonas Wittler, Olaf Schneider-Ramelow, Martin Robert Bosch GmbH Corporate Sector Research and Advance Engineering Renningen Germany Fraunhofer IZM Department Environmental and Reliability Engineering Berlin Germany Technical University Berlin Faculty IV-Electrical Engineering and Computer Science Berlin Germany

ISBN: (纸本)9798350393637

Bond wire reliability remains as one of the major challenges in power electronics as device miniaturization progresses and demands on performance increase. Physics-of-failure models are commonly formulated to determine the lifetime of wire bonding interconnects. Such approach relies on damage metrics derived from finite element models, often based on simplified geometries and modeling *** paper addresses the influence of various bond wire geometry features on the thermo-mechanical reliability of PCB-mounted discrete SiC power devices. For this purpose, the bond wire geometry is characterized and the component is subjected to active power cycling until failure occurs due to bond wire lift-off. Finite element models are solved using a two-stage simulation approach: First, an upstream wire bonding simulation is performed to obtain a realistic bond foot geometry, and then the active power cycling tests are simulated. A physics-of-failure lifetime model is calibrated using damage quantities derived from the simulation results. Finally, geometry variations of the bond foot and different bond wire positions and rotations are evaluated to determine their significance for the thermo-mechanical reliability of thick Al bond wires. © 2024 IEEE.

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Experimental Evaluation of Covariates Effects on Periocular Biometrics: A Robust Security Assessment Framework

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Journal of Data and Information Quality 2023年第2期15卷 1-25页

作者： Kumar, Gautam Bakshi, Sambit Sangaiah, Arun Kumar Sa, Pankaj Kumar National Institute of Technology Rourkela Sector II Odisha Rourkela769 008 India International Graduate Institute of Ai National Yunlin University of Science and Technology Taiwan Department of Electrical and Computer Engineering Lebanese American University Byblos Lebanon

The growing integration of technology into our lives has resulted in unprecedented amounts of data that are being exchanged among devices in an Internet of Things (IoT) environment. Authentication, identification, and device heterogeneities are major security and privacy concerns in IoT. One of the most effective solutions to avoid unauthorized access to sensitive information is biometrics. Deep learning-based biometric systems have been proven to outperform traditional image processing and machine learning techniques. However, the image quality covariates associated with blur, resolution, illumination, and noise predominantly affect recognition performance. Therefore, assessing the robustness of the developed solution is another important concern that still needs to be investigated. This article proposes a periocular region-based biometric system and explores the effect of image quality covariates (artifacts) on the performance of periocular recognition. To simulate the real-time scenarios and understand the consequences of blur, resolution, and bit-depth of images on the recognition accuracy of periocular biometrics, we modeled out-of-focus blur, camera shake blur, low-resolution, and low bit-depth image acquisition using Gaussian function, linear motion, interpolation, and bit plan slicing, respectively. All the images of the UBIRIS.v1 database are degraded by varying strength of image quality covariates to obtain degraded versions of the database. Afterward, deep models are trained with each degraded version of the database. The performance of the model is evaluated by measuring statistical parameters calculated from a confusion matrix. Experimental results show that among all types of covariates, camera shake blur has less effect on the recognition performance, while out-of-focus blur significantly impacts it. Irrespective of image quality, the convolutional neural network produces excellent results, which proves the robustness of the developed model. © 2023 Co

关键词： Image quality

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An automated technique for optic disc detection in retinal fundus images using elephant herding optimization algorithm

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Recent Advances in computer science and Communications 2021年第1期14卷 166-180页

作者： Pruthi, Jyotika Arora, Shaveta Khanna, Kavita Department of Computer Science and Engineering The Northcap University Sector 23-A Gurgaon India Department of Electrical Electronics and Communication Engineering The Northcap University Sector 23-A India

Background: Glaucoma and diabetic retinopathy are known to be the prime reasons for causing irrevocable blindness in the world. However, the complete vision loss can be obstructed through regular screening of the eye to detect the disorder at an early stage. Objective: In this paper, we have presented a novel nonlinear optimization technique that helps in automatic detection of the optic disc boundary from retinal fundus images thereby satisfying the anatomical constraints by using elephant herding optimization algorithm. Methods: In our approach, median filter has been used for the noise removal in retinal images. The pre-processed image is passed to the metaheuristic algorithm known as Elephant Herding Optimization algorithm. Results: The proposed technique for optic disc segmentation has been applied and tested on four standard publicly available datasets namely DRIVE, DIARETDB1, STARE and DRIONS-DB. The ground truth of the optic disc boundary has been collected from two experts of glaucoma: Expert A and Expert B who are specialists of glaucoma. The quantitative and qualitative analysis has been done to evaluate the performance of optic disc segmentation techniques. Conclusion: The proposed technique for optic disc detection helps to obtain the smooth boundaries in retinal fundus images. The aim has been successfully achieved by proposing an approach using EHO to achieve optimized solution. The effectiveness of the approach has been evaluated on for benchmark datasets and the acquired results have shown the accuracy values to be 100% for DRIVE, 100% for DIARETDB1, 99.25% for STARE and 99.99% for DRIONS-DB. © 2021 Bentham science Publishers.

关键词： Median filters

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Optical Satellite Networks

Optical Satellite Networks

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2023 Optical Fiber Communications Conference and Exhibition, OFC 2023

作者： Chan, Vincent W.S. Massachusetts Institute of Technology Research Laboratory of Electronics Steve Schwarzman College of Computing Ai and Decision System Sector Department of Electrical Engineering and Computer Science United States

We will explore the architecture of optical satellite networks at 100G-1Tbps. The challenge is to architect the system and the network protocols with large bandwidth-delay products and the presence of atmospheric turb... 详细信息

ISBN: (纸本)9781957171180

关键词： Atmospheric turbulence

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Harnessing the power of functionalized biochar:progress,challenges,and future perspectives in energy,water treatment,and environmental sustainability

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Biochar 2024年第1期6卷 407-486页

作者： Muhammad Zubair Yameen Salman Raza Naqvi Dagmar Juchelková Muhammad Nouman Aslam Khan Laboratory of Alternative Fuels and Sustainability School of Chemical and Materials Engineering(SCME)National University of Sciences and Technology(NUST)Sector H-12Islamabad 44000Pakistan. Department of Electronics Faculty of Electrical Engineering and Computer ScienceVŠB-Technical University of Ostrava17.Listopadu 2172/1570800 OstravaPorubaCzech Republic. Department of Engineering and Chemical Sciences Karlstad UniversityKarlstadSweden.

The swift advancement of sustainable energy technologies,coupled with the urgent need to address environmental challenges,has generated considerable interest in the multifaceted applications of biochar materials to promote energy,water,and environmental *** comprehensive review examines recent advancements in the production and applications of functionalized biochar materials,emphasizing their pivotal roles in energy conversion and storage,wastewater treatment,CO_(2)reduction,soil amelioration,and the promotion of carbon neutrality within a circular economy *** functionalization of biochar materials involves surface chemistry and porosity modifications,achieved through techniques like templating,chemical activation,metal impregnation,or heteroatom *** modifications substantially enhance the catalytic activity,energy storage capacity,and cycling stability of biochar materials,making them particularly effective in diverse energy applications such as water splitting,fuel cells,and ***,functionalized biochar materials demonstrate remarkable efficacy as catalysts and adsorbents in wastewater treatment,proficiently removing pollutants like heavy metals,organic contaminants,and nutrients,thereby facilitating resource recovery from *** review also underscores the potential of functionalized biochar materials in CO_(2)capture and conversion,exploring innovative strategies to augment their CO_(2)adsorption capacity and state-of-the-art catalytic processes for transforming captured CO_(2)into valuable fuels and *** summary,this review offers valuable insights into the recent advancements in biochar research,underscoring its substantial commercial potential as a versatile material contributing to a cleaner and more sustainable future.

关键词： Engineered biochar Sustainable energy technologies Wastewater treatment Carbon reduction Circular economy

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Assessing aerosol effects on solar irradiance in the NEOM region with the WRF-solar model

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Bulletin of Atmospheric science and Technology 2025年第1期6卷 1-24页

作者： Choudhury, Devanil Computer Electrical Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Mecca Province Thuwal 23955 - 6900 Saudi Arabia National Centre for Medium Range Weather Forecasting A-50 Institutional Area Sector-62 Uttar Pradesh Noida 201309 India

This study demonstrates the usability of the Weather Research and Forecasting (WRF)-Solar model, in predicting solar irradiance in the NEOM region of Saudi Arabia across different sky conditions. This research aims to enhance the accuracy of solar radiation forecasting by systematically evaluating the model's responses to external time-varying two-dimensional (2-D) aerosol optical depth (AOD) data at 550 nm under scenarios with varying cloud cover and aerosol levels. Through experiments representing distinct sky conditions, this study demonstrates consistent trends, with the control experiment (CTRL) consistently producing the highest Global Horizontal Irradiance (GHI) and Direct Normal Irradiance (DNI) due to lower representation of AOD in the model. Notably, experiments incorporating time-varying 2-D AOD from the Copernicus Atmosphere Monitoring Service (CAMS) reanalysis outperform other experiments with NASA’s Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA- 2) analysis, and climatological AOD datasets, particularly on overcast days. Model validation against observations from the Tabuk University station further substantiates these findings. Furthermore, experimental results highlight the importance of dynamic aerosol data over the climatological or no-aerosol data in improving the solar energy predictions, emphasizing the need for accurate representation of aerosol-cloud-radiation interactions in numerical models for precise solar irradiance forecasting. © The Author(s) 2025.

关键词： Aerosol-cloud-radiation interaction AOD CAMS MERRA- 2 Solar irradiance WRF-Solar

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A pplication of machine learning methods for process optimization in electronic packaging processes

A pplication of machine learning methods for process optimiz...

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作者： Niegisch, Corinna Haag, Sabine T. Braun, Tanja Hölck, Ole Schneider-Ramelow, Martin Corporate Sector Research and Advance Engineering Robert Bosch GmbH Renningen Germany Fraunhofer IZM Departement System Integration and Interconnection Technologies Berlin Germany Technical University Berlin Faculty IV Electrical Engineering and Computer Science Berlin Germany

E poxy resins are commonly used as encapsulation materials in electronic packaging processes. F luctuations in the materials lead to both changes in processability and to varying quality. Ideally, these variations should be identified, and measures taken as quickly as possible to reduce scrap parts and thus costs. A promising optimization approach for encapsulation processes are machine learning models, which have already shown good results in quality predictions, especially for injection molding. Subsequent quality measurements are avoided with good quality prediction models. W ith this type of models, not only predictions can be made, but also optimal parameter combinations can be found. In this paper, models for predicting quality criteria warpage and residual enthalpy of the epoxy molding compound were set up, trained and validated. T ime series of in-situ sensors were used, from which relevant features were extracted and which, together with machine parameters, provide a dataset for prediction. T he most promising prediction models are random forest regression and gradient boosting regression. T hey predict warpage with an accuracy of 90 % to 91 % and the residual enthalpy with an accuracy of 95 % . Subsequently, optimization models of the machine parameters were set up. All relevant target variables were considered in a cost function, through the minimization of which an optimal parameter set was found. T he gradient boosted tree and Bayesian optimization were determined to be the most promising models, as they lead to the lowest values of the respective cost function. © 2023 IMAPS-International Microelectronics and Packaging Society. All rights reserved.

关键词： Optimization

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Application of Machine Learning Methods for Process Optimization in Electronic Packaging Processes 24

Application of Machine Learning Methods for Process Optimiza...

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24th European Microelectronics and Packaging Conference, EMPC 2023

作者： Niegisch, Corinna Haag, Sabine T. Braun, Tanja Hulck, Ole Schneider-Ramelow, Martin Robert Bosch GmbH Corporate Sector Research and Advance Engineering Renningen Germany Fraunhofer IZM Departement System Integration and Interconnection Technologies Berlin Germany Technical University Berlin Faculty IV Electrical Engineering and Computer Science Berlin Germany

ISBN: (纸本)9780956808691

Epoxy resins are commonly used as encapsulation materials in electronic packaging processes. Fluctuations in the materials lead to both changes in processability and to varying quality. Ideally, these variations should be identified, and measures taken as quickly as possible to reduce scrap parts and thus costs. A promising optimization approach for encapsulation processes are machine learning models, which have already shown good results in quality predictions, especially for injection molding. Subsequent quality measurements are avoided with good quality prediction models. With this type of models, not only predictions can be made, but also optimal parameter combinations can be found. In this paper, models for predicting quality criteria warpage and residual enthalpy of the epoxy molding compound were set up, trained and validated. Time series of in-situ sensors were used, from which relevant features were extracted and which, together with machine parameters, provide a dataset for prediction. The most promising prediction models are random forest regression and gradient boosting regression. They predict warpage with an accuracy of 90 % to 91 % and the residual enthalpy with an accuracy of 95 %. Subsequently, optimization models of the machine parameters were set up. All relevant target variables were considered in a cost function, through the minimization of which an optimal parameter set was found. The gradient boosted tree and Bayesian optimization were determined to be the most promising models, as they lead to the lowest values of the respective cost function. © 2023 IMAPS-Europe.

关键词： Optimization

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Diffusive molecular communication for bacterium propagation over human gut track

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International Journal of Information Technology (Singapore) 2024年第5期16卷 3101-3108页

作者： Asim, Masood Jaiswal, Raghvendra Chugh, Urvashi Agarwal, Prabhakar Singh, S. Pratap Galgotia College of Engineering & amp Information Technology KIET Group of Institutions Meerut Road UP Ghaziabad 201206 India Electrical Electronics and Communication Engineering Galgotias University Sector-17A Yamuna Expressway GB Nagar UP Greater Noida 203201 India Symbiosis Institute of Technology Nagpur Campus Department of Computer Science & amp

Diffusive Molecular Communication (DMC), is the most common approach employed in analysis and replication of different types of communication systems existing in nature. Exchange of Molecular Information (MI) using Bacterium, which is based on DMC and may be termed as Bacterial Communication (BC), is being used to model detection and cure processes of various decreases due to the Bacteria. DMC is being developed to serve almost each and every aspect of humanity. Also, various approaches to detect and cure the Bacterial disease are proposed in literature. It is noticeable that the complete Human Gut Track (HGT) is responsible to grade the severity of the disease. And therefore, literature presents the propagation of Bacteria in the HGT. Further, it is most important to mention that the impulse response of the system which characterizes bacteria propagation per unit area (f(y)) plays a major role in modeling viral transmission over the (HGT). In this work we analyzed bacterial concentration (N(y)) at different time points (t = 0.3, 0.5, 0.7, 0.9, 1.2). Our findings show that as time (t) increases, N(y) also increases. Additionally, we examined bacterial distribution (V(y)) for varying values of v (λ = 0.2, 0.3, 0.4, 0.6, 0.8). Results indicate that as v increases, V(y) decreases due to fixed distance, where mucus influences bacterial concentration. Increasing mucus flow rate for a fixed distance results in a decrease in Bacteria distribution. In particular we provided analytical expressions of Bacterial concentration (N(y)) and Bacterial distribution (V(y)) under certain impulse responses. Also, the effect of different physical parameters on (N(y)) and (V(y)) have been quantified with the help of numerical simulation. Presented analysis shows perfect agreement with the theoretical background. © Bharati Vidyapeeth's Institute of computer Applications and Management 2024.

关键词： Bacteria Propagation Bacterial Distribution Bacterium Concentration Diffusive Molecular Communication Human Gut Track

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