Performance Analysis Tools Research Articles

A bibliometric review of functional ingredients and their efficacy in developing functional biscuits

Introduction Numerous studies have concluded that the functional ingredients benefit human health. Similarly, present times have seen exponential growth in functional food in bakery product segments like breads and biscuits. However, there is a lack of information on functional ingredients and their usefulness in developing functional bakery products. This bibliometric study addresses this gap by identifying the current research trends in functional ingredients. Objective To investigate current research trends on functional ingredients and their usefulness in developing functional biscuits. Method The study followed the “Scientific Procedures and Rationales for Systematic Literature Reviews” standards for retrieving literature. The study went through three major stages, “assembling”, “arranging”, and “assessing” to retrieve 612 articles from the Scopus database from 2013 to 2023. Through further filtering, 395 articles were selected. Result The analysis was conducted using R Studio and VOS viewer. The performance analysis and science mapping tools were used to evaluate the articles. The results showed a 5.76% annual growth in publication trends. The most researched functional ingredients were antioxidants, bioactive compounds, and dietary fiber. The review summarized the most studied foods used to develop functional biscuits and highlighted the most experimented technological advancements. Conclusion The study revealed the need for future research studies on functional ingredients with a focus on studying the implications of technical implications of technical advancements in extracting functional ingredients from foods. The study highlights the significance of future studies based on the acceptance of functional biscuits and their sensory properties focusing on the mass population. The study derives the knowledge on possible applicability of functional ingredients in developing new formulations from publications and their usefulness in developing new formulations. This insight on the applicability of functional ingredients provides an opportunity for biscuit/cookie manufacturing to boost consumption among the population to a new ascending graph.

Performance and Latency Efficiency Evaluation of Kubernetes Container Network Interfaces for Built-In and Custom Tuned Profiles

In the era of DevOps, developing new toolsets and frameworks that leverage DevOps principles is crucial. This paper demonstrates how Ansible’s powerful automation capabilities can be harnessed to manage the complexity of Kubernetes environments. This paper evaluates efficiency across various CNI (Container Network Interface) plugins by orchestrating performance analysis tools across multiple power profiles. Our performance evaluations across network interfaces with different theoretical bandwidths gave us a comprehensive understanding of CNI performance and overall efficiency, with performance efficiency coming well below expectations. Our research confirms that certain CNIs are better suited for specific use cases, mainly when tuning our environment for smaller or larger network packets and workload types, but also that there are configuration changes we can make to mitigate that. This paper also provides research into how to use performance tuning to optimize the performance and efficiency of our CNI infrastructure, with practical implications for improving the performance of Kubernetes environments in real-world scenarios, particularly in more demanding scenarios such as High-Performance Computing (HPC) and Artificial Intelligence (AI).

Bibliometric Analysis of Accounting Literature on Artificial Intelligence (AI) Adoption in Organizational Functions

Artificial intelligence (AI) is a powerful technology with a high potentiality of transformative drive from traditional analog to digitalized organizational seamless decision processes efficiently and effectively. AI is an emerging area in organizational decision-making with limited number of studies across the globe. However, AI is now gaining considerable attention from the researcher, both at the local and international level. This study aims at providing a systematic review and biometric analysis on AI adoption in organizational functions using Google Scholar databases as the source of data. The study employs the steps of Prepare Reporting Items for Systematic Literature Review and Meta-Analysis Techniques PRISMA (2020) and bibliometric analysis techniques using VOS-View as a tool for analysis of publications performance over time with a view to determining the most influential articles, publication productivity, and direction of studies on AI Adoption in organizational functions for a period of ten years from 2015 to 2024. The analysis reveals that articles published in 2016 by Sage Journal recorded the highest citation of 2707, followed by MDPI Journal with total citations of 1922 in 2021, while Elsevier presents the lowest citation of 87 citations over the period of 10 years in the database used. These articles were written on more than 20 areas of application of AI in organizational functions.

Preliminary Verification of Key Physical Models in Oxide Fuel Performance Analysis Code FEATURE Based on COMSOL

Nuclear performance analysis is of great significance for fuel design optimization and the safe operation of a reactor. Considering the design requirements of the China initiative Accelerator Driven System (CiADS) project, it is necessary to develop relevant fuel performance analysis tools to predict fuel performance evolution during service. The Fuel Element Analysis Tool for Undercritical Reactor Engineering (FEATURE) code, based on the advanced multiphysics coupling platform COMSOL software, is under development in this context, with a current focus on oxide fuel for fast reactors. This paper mainly conducts preliminary comparative verification of the oxygen redistribution, plutonium redistribution, and fission gas release modules of the FEATURE code through model examples, code-to-code evaluation, and experimental data. The results indicate that the FEATURE code exhibits good accuracy and reliability in simulating oxygen and plutonium redistribution, as well as fission gas release, making it suitable for integrated coupling calculations.

Quantifying Electrolyte Variation through Coupled Molecular Dynamics and Porous Electrode Modeling of Lithium-Ion Battery Cells

Lithium-ion battery cell modeling using physics-based approaches such as porous electrode theory is a powerful tool for battery design and performance analysis both at the beginning and end of life[1]. Cell metrics such as resistance and thermal performance[2-6] can be quickly calculated in a pseudo-two-dimensional (P2D) framework. For engineering of electric vehicle batteries, speed and fidelity of electrochemical models is paramount in a competitive landscape. Physics-based models[7, 8] allow for high fidelity but require detailed knowledge of the cell component material properties. Acquiring these material characteristics typically requires time-consuming and expensive experiments limiting the ability to quickly screen through cell designs. One approach to circumvent costly experiments is to use molecular dynamics[9, 10] to calculate electrolyte transport properties. We demonstrate how cell modeling using simulated transport properties enables predictions of cell level metrics, allowing for experiment-free component screening. We also show how the variation in transport property predictions from molecular dynamics affects the final cell level performance predictions.

Effect of impeller rotational phase on the FDA blood pump velocity fields.

The Food and Drug Administration (FDA) blood pump is an open-source benchmark cardiovascular device introduced for validating computational and experimental performance analysis tools. The time-resolved velocity field for the whole impeller has not been established, as is undertaken in this particle image velocimetry (PIV) study. The level of instantaneous velocity fluctuations is important, to assess the flow-induced rotor vibrations which may contribute to the total blood damage. To document these factors, time-resolved two-dimensional PIV experiments were performed that were precisely phase-locked with the impeller rotation angle. The velocity fields in the impeller and in the volute conformed with the previous single blade passage experiments of literature. Depending on the impeller orientation, present experiments showed that volute outlet nozzle flow can fluctuate up to 34% during impeller rotation, with a maximum standard experimental uncertainty of 2.2%. Likewise, the flow fields in each impeller passage also altered in average 33.5%. Considerably different vortex patterns were observed for different blade passages, with the largest vortical structures reaching an average core radii of 7 mm. The constant volute area employed in the FDA pump design contributes to the observed velocity imbalance, as illustrated in our velocity measurements. By introducing the impeller orientation parameter for the nozzle flow, this study considers the possible uncertainties influencing pump flow. Expanding the available literature data, analysis of inter-blade relative velocity fields is provided here for the first-time to the best of our knowledge. Consequently, our research fills a critical knowledge gap in the understanding of the flow dynamics of an important benchmark cardiovascular device. This study prompts the need for improved hydrodynamic designs and optimized devices to be used as benchmark test devices, to build more confidence and safety in future ventricular assist device performance assessment studies.

Comparing the Performance of Optical Communication Links using G.652 and G.655 Fiber in Python Packages

This study investigates and compares the performance of a 10 Gbps optical communication link utilizing two prevalent single-mode fibers: G.652 and G.655. The analysis employs both theoretical calculations and Python-based simulations to assess the effectiveness of each fiber type in this high-speed transmission scenario. With the ever-growing demand for bandwidth in communication networks, 10 Gbps transmission systems are becoming increasingly commonplace. Single-mode fibers like G.652 and G.655 play a vital role in these systems, offering low signal attenuation for long-distance data transmission. However, each fiber type exhibits distinct dispersion characteristics, which can impact signal integrity over extended distances. This investigation adopts a two method for performance evaluation. Firstly, link power budget calculations are performed to determine the optical signal power before and after propagating through a 50-kilometer fiber span. The received power serves as the foundation for subsequent Q-factor and Bit Error Rate (BER) analysis. These calculations establish the theoretical limitations of the system based on well-defined formulas. Secondly, Python-based simulations are conducted to corroborate the theoretical findings and provide a more comprehensive performance assessment. This approach leverages the capabilities of two prominent Python packages: Opticomlib and OpticommPy. Opticomlib excels at analyzing the behavior of individual optical pulses within the system, enabling an understanding of the signal propagation. On the other hand, OpticommPy specializes in parameter sweep analysis, allowing for the investigation of how critical parameters like received power influence the Q-factor. By combining these functionalities, the simulations provide a detailed picture of the system's performance under various conditions. The calculated BER and Q-factor values for both G.652 and G.655 fiber links surpass the industry-accepted performance standards. These results demonstrate the effectiveness of using Python-based tools for comprehensive performance analysis of optical communication systems. However, it's important to note that slight discrepancies exist between the calculated and simulated results.

Technical performance differences amongst international netball teams at the Commonwealth Games 2022

ABSTRACT Team and opposition quality are factors that can influence netball performance. Although these effects are present within domestic netball, there is currently no assessment of these at the international level. The aim of this study was to assess performance differences between teams during all competition stages and matches at the 2022 Commonwealth Games. Thirty-six fixtures from all 12 teams were analysed, with performance indicators (PIs) relating to centre passes, turnovers and goal scoring assessed. Teams were split into three groups based on their finishing position in the competition (top 4, middle 4, bottom 4). When assessing team quality differences, significant differences were revealed for all but three PIs between groups (total number of restart and live turnovers and the total number of these combined). The quality of the opponent was also found to affect teams differently, with top-quality teams performing more consistently than lower-quality teams and being able to beat these teams by large winning margins (average of 55 goals and 26 goals versus bottom-quality and middle-quality teams respectively). Therefore, lower-quality teams should focus on implementing clear and effective tactical plans prior to matches, and performance analysis tools should be created for these teams to raise the quality of international netball.

A bibliometric review of functional ingredients and their efficacy in developing functional biscuits

Introduction Recent studies have found that functional biscuits are becoming increasingly popular as a convenient and nutritious food option. Numerous studies have concluded that the functional ingredients which impart functional properties to biscuits are beneficial for human consumption and can be incorporated into functional biscuits. However, there is a lack of information on essential functional ingredients that can be used to develop functional biscuits. This bibliometric study addresses this gap by identifying the current research trends in functional ingredients to develop functional biscuits. Objective To investigate current research trends on functional ingredients and their effectiveness in developing functional biscuits. Method The study followed the “Scientific Procedures and Rationales for Systematic Literature Reviews” standards for retrieving literature. The study went through three major stages, “assembling”, “arranging”, and “assessing” to retrieve 612 articles from the Scopus database from 2013 to 2023. Through further filtering, 395 articles were selected. Result The analysis was conducted using R Studio and VOS viewer. The performance analysis and science mapping tools were used to evaluate the articles. The results showed a 5.76% annual growth in publication trends. The most researched functional ingredients were antioxidants, bioactive compounds, and dietary fiber. The review summarized the most studied foods to develop functional biscuits and highlighted the most experimented technological advancements. Conclusion The study revealed an increasing interest in developing functional biscuits and the need for further research to improve their effectiveness and sensory properties. Further, there is a need to determine the impact of technology on extracting functional ingredients from foods, so they can be incorporated into functional biscuits.

E-GOVERNMENT MATURITY ANALYSIS USING THE LAYNE AND LEE, HILLER AND BELANGER, AND SPBE MODELS

This research aims to analyze the level of e-government maturity in Kupang City using the Layne and Lee and Hiller and Belanger models and combine them with the SPBE model to provide a more comprehensive approach. The method used to develop an audit model involves a literature study to understand the e-government maturity model, identification of specific objectives for analysis of the Kupang City Population and Civil Registration Service (DUKCAPIL) website, determination of scope based on the SPBE model, determination of design audit criteria and benchmarks, collection and data synthesis from the Kupang City DUKCAPIL e-Government site, as well as analysis of audit findings, and using the GT Metrix tool for performance analysis and evaluation of the Kupang City DUKCAPIL website. The research results show that the lowest rating is F out of six, which indicates poor service performance. The Layne and Lee Model assessment gives a score of 18, indicating the technology's lack of integration and complexity. Hiller and Belanger's Model assessment gives a value of 13, indicating an immature level. These findings highlight significant gaps between the models evaluated. Recommendations based on research are to increase citizen participation by improving the Kupang City DUKCAPIL website based on a maturity model and the need for regular audits and ongoing evaluations to improve public services in Kupang City in e-government maturity. In conclusion, this research provides a new contribution to the field of e-government by highlighting the need for audits using several e-government maturity models to improve public services in Kupang City.

Low-Overhead Trace Collection and Profiling on GPU Compute Kernels

While GPUs can bring substantial speedup to compute-intensive tasks, their programming is notoriously hard. From their programming model, to microarchitectural particularities, the programmer may encounter many pitfalls which may hinder performance in obscure ways. Numerous performance analysis tools provide helpful data on the efficiency of the compute kernels, but few allow the programmer to efficiently gather runtime information directly on the device and pinpoint the sections to optimize. We propose in this paper an instrumentation method to collect traces while executing the compute kernel, with a reduced overhead compared to other approaches, by exploiting the inherently parallel behavior of GPUs and compartmentalizing tracing phases. The reference implementation is freely available and induces an average overhead of 1.6 × on a popular scientific computing benchmark and 1.5 × over the kernel execution time. This represents an improvement of an order of magnitude compared to similar work, and proves useful for timing-guided optimizations. The tool generates insightful execution traces and timestamps which can be analyzed to better understand performance issues in the kernel.

Analyzing GPU Performance in Virtualized Environments: A Case Study

The graphics processing unit (GPU) plays a crucial role in boosting application performance and enhancing computational tasks. Thanks to its parallel architecture and energy efficiency, the GPU has become essential in many computing scenarios. On the other hand, the advent of GPU virtualization has been a significant breakthrough, as it provides scalable and adaptable GPU resources for virtual machines. However, this technology faces challenges in debugging and analyzing the performance of GPU-accelerated applications. Most current performance tools do not support virtual GPUs (vGPUs), highlighting the need for more advanced tools. Thus, this article introduces a novel performance analysis tool that is designed for systems using vGPUs. Our tool is compatible with the Intel GVT-g virtualization solution, although its underlying principles can apply to many vGPU-based systems. Our tool uses software tracing techniques to gather detailed runtime data and generate relevant performance metrics. It also offers many synchronized graphical views, which gives practitioners deep insights into GVT-g operations and helps them identify potential performance bottlenecks in vGPU-enabled virtual machines.

A Modular IoT-Based Architecture for Logistics Service Performance Assessment and Real-Time Scheduling towards a Synchromodal Transport System

Logistics is significantly impacted by quality/quantity issues associated with data collection and data sharing restrictions. Nonetheless, public data from national entities and internet-of-things (IoT) solutions enable the development of integrated tools for performance analysis and real-time optimization of logistics networks. This study proposes a three-module data-driven system architecture that covers (a) logistics data collection tools, (b) logistics services performance evaluation, and (c) the transition to synchromodal systems. Module 1 integrates multisource data from national logistics platforms and embedded devices placed within intermodal containers. A multigraph representation of the problem is conceived. Environmental, economic, and operational data are generated and injected into a digital twin. Thus, key performance indicators (KPIs) are computed by simulation or direct transformation of the collected data. Module 2 uses Multi-directional Efficiency Analysis, an optimization algorithm that benchmarks multimodal transportation routes of containers using prior KPIs. Outputs are a technical performance index relevant to logistics clients and improvement measures for logistics service providers. A real case study application of the solution proposed for Module 2 is presented. Module 3 provides real-time scheduling and assignment models using CP-sat solvers, accommodating varying system dynamics and resource availability, minimizing makespan and operational costs.

The exact worst-case convergence rate of the alternating direction method of multipliers

AbstractRecently, semidefinite programming performance estimation has been employed as a strong tool for the worst-case performance analysis of first order methods. In this paper, we derive new non-ergodic convergence rates for the alternating direction method of multipliers (ADMM) by using performance estimation. We give some examples which show the exactness of the given bounds. We also study the linear and R-linear convergence of ADMM in terms of dual objective. We establish that ADMM enjoys a global linear convergence rate if and only if the dual objective satisfies the Polyak–Łojasiewicz (PŁ) inequality in the presence of strong convexity. In addition, we give an explicit formula for the linear convergence rate factor. Moreover, we study the R-linear convergence of ADMM under two scenarios.

A transient heat losses model for two-tank storage systems with molten salts

Concentrating Solar Power (CSP) is a proven and mature technology for energy supply. In recent years, electricity generation based on this technology has increased worldwide, to a large degree due to its high dispatchability when coupled with an energy storage system. Commercially, most plants store the energy in molten salts in a two-tank configuration. This study focuses on this storage configuration and proposes a mathematical model for the thermal losses in these tanks, both at nominal conditions and during transients. With this model at its core, a computational tool for thermal performance analysis in OpenModelica is developed. This dynamic thermal model includes the estimation of local heat loss due to assembly defects, which are heat flows that cannot be determined by theoretical modelling. The development of a semi-empirical correlation for estimating local heat loss is also presented. Simulation results showed that this local heat loss may represent a share about 40% of the total heat loss in a small-scale tank. A comparison of the characteristics of the model proposed in a previous work is also presented to establish the innovation of the model. Two thermal storage systems with different tank designs and sizes were simulated to compare the results using the present model with data available in the literature. Results show good agreement in transient thermal behaviour of heat flows, temperatures, and cooling rates when compared with data from other authors for the same tank.

An Eco-Innovative Green Design Method using the Theory of Inventive Problem Solving and Importance–Performance Analysis Tools—A Case Study of Marker Pen Manufacturing

This study explores innovative designs for the cap of a marker pen, aiming to address the issues of cap loss and ink evaporation during marker pen usage. This study applies intrinsic safety, universal design and TRIZ as research methods. TRIZ has great potential to address most of the Sustainable Development Goals (SDGs) relevant to conflict-oriented problem solving for innovations. The principles of simplification, foolproof design, clarity of states, and tolerance from intrinsic safety were applied to prevent cap loss and minimize the risks associated with ink evaporation. The TRIZ methodology’s contradiction matrix was utilized to identify relevant inventive principles by improving parameters and avoiding worsening parameters, providing a reference basis for product structure design. Lastly, the principles of equitable use, simplicity, intuitiveness, and effortless design from universal design were employed to enhance the marker pen’s usability for the general public. This study creates a SERVQUAL questionnaire to compare the prototype of the designed pen cap with commercially available pen caps. It utilizes the two-dimensional quality model (Kano model) and Importance–Performance Analysis (IPA) for practical design analysis. Finally, the prototype structure is visualized using graphic software. The innovative design features of this study include the following. (1) Concealable pen tip: the sliding seal hides the pen tip inside the pen body when the pen core is slid upwards, preventing cap loss and ink drying. (2) Quick retractable function: using a pressing mechanism, the pen tip can be quickly retracted with a one-handed press and slide motion. (3) Replaceable pen core: the pen core can be replaced by disassembling the pen body, removing the old pen core, and inserting a new one, thereby extending the pen’s lifespan. (4) Satisfaction evaluation of the innovative pen cap design: through questionnaire surveys and cross-analysis using the IPA and the Kano model, this study assesses the product’s manufacturing and mass production value to reduce actual product development costs and time.

The Intersection of Facade Engineering and Building Information Modeling: Opportunities and Challenges

Building Information Modeling (BIM) represents a transformative advancement in the architecture, engineering, and construction (AEC) sector, especially in the specialized field of facade engineering. Utilizing a secondary data analysis approach focused on existing case studies, this paper offers a comprehensive examination of the synergistic interaction between BIM and emerging technologies such as generative design, machine learning, performance analysis tools, digital twins, and augmented reality. These technologies are analyzed to understand their impact on the optimization of facade design, detailing, fabrication, as well as long-term maintenance and performance. The study aims to provide a nuanced understanding of the current trends, challenges, and solutions associated with this technological amalgamation. The insights gleaned are invaluable for professionals in the AEC industry, pointing toward an increasingly digitized future where enhanced efficiency, sustainability, and functional efficacy are achievable in building facade engineering.

Using heterogeneous GPU nodes with a Cabana-based implementation of MPCD

The Kokkos based library Cabana, which has been developed in the Co-design Center for Particle Applications (CoPA), is used for the implementation of Multi-Particle Collision Dynamics (MPCD), a particle-based description of hydrodynamic interactions. Cabana allows for a function portable implementation, which has been used to study the interplay between CPU and GPU usage on a multi-node system as well as analysis of said interplay with performance analysis tools. As a result, we see most advantages in a homogeneous GPU usage, but we also discuss the extent to which heterogeneous applications might be more performant, using both CPU and GPU concurrently.

Optimal strategy analysis of a Markovian queue with variable vacation and vacation interruptions under unobservable cases

ABSTRACT This paper makes a game-theoretic analysis of an M/M/1 queue with variable vacation and vacation interruptions. The Nash equilibrium mixed strategy and social utility maximization are derived based on a non-cooperative game theory and an optimization theory under different information precision levels, namely almost unobservable and fully unobservable cases. The explicit solutions of the entrance probabilities and the steady-state probability distribution of the system are investigated using the probability generating function and nonhomogeneous linear difference equations. Furthermore, the effects of the information levels and diverse system parameters on the equilibrium strategies, the arrival rates, and the expected benefits are explicitly illustrated by numerical comparisons. The research results can provide a theoretical basis and performance analysis tool for the optimal design in the wireless transmission and network communication system.

Adaptation of FPGA architecture for accelerated image preprocessing

The work is devoted to the topical problem at the intersection of communications theory, digital electronics and numerical analysis, namely the study of image processing methods implementation time on different architectures of computational devices, which are used for software and hardware acceleration. The subject of this article is the investigation of reconfigurable FPGA processing systems in the image processing area. The goal of this work is to create a reconfigurable FPGA-based image processing system and compare it with existing processing architectures. Task. To fulfill the requirements of this work, it is necessary to prepare a practical experiment as well as theoretical research of the proposed architecture; to investigate the process of creating a ZYNQ SoC-based image processing system; and to develop and benchmark the speed of execution for the given set of algorithms with the specific range of the picture resolution. Methods used: FPGA simulation, C++ parallel programming with OpenMP, NVIDIA CUDA, performance analysis tools. The result of this work is the development of a resilient SoC Zynq7000–based computing system with programmable logic and the possibility to load images to FPGA RAM using the resources of ARM core for further processing and output via HDMI video interface, which enables the change of PL configuration at any time during the processing process. Conclusions. The efficiency of the FPGA approach was compared with a parallel image processing method implementation with OpenMP and CUDA. An overview of the ZYNQ platform with specific details related to media processing is presented. The analysis of algorithm speed testing findings based on various outputs proved the advantage (of over 60 times) of hardware acceleration of image processing over software analogs. The obtained results may be used in the development of embedded SoC-based solutions that require acceleration of big data processing. Also, the achieved findings can be used during the process of finding a suitable embedded platform for a certain image-processing task, where high data throughput is one of the most desired requirements.