Performance Analysis Of Applications Research Articles

Cultural heritage preservation in the digital age, harnessing artificial intelligence for the future: a bibliometric analysis

PurposeThis study aims to investigate the performance analysis, science mapping and future direction of artificial intelligence (AI) technology, applications, tools and software used to preserve, curate and predict the historical value of cultural heritage.Design/methodology/approachThis study uses the bibliometric research method and utilizes the Scopus database to gather data. The keywords used are “artificial intelligence” and “cultural heritage,” resulting in 718 data sets spanning from 2001 to 2023. The data is restricted to the years 2001−2023, is in English language and encompasses all types of documents, including conference papers, articles, book chapters, lecture notes, reviews and editorials.FindingsThe performance analysis of research on the use of AI to aid in the preservation of cultural heritage has been ongoing since 2001, and research in this area continues to grow. The countries contributing to this research include Italy, China, Greece, Spain and the UK, with Italy being the most prolific in terms of authored works. The research primarily falls under the disciplines of computer science, mathematics, engineering, social sciences and arts and humanities, respectively. Document types mainly consist of articles and proceedings. In the science mapping process, five clusters have been identified. These clusters are labeled according to the contributions of AI tools, software, apps and technology to cultural heritage preservation. The clusters include “conservation assessment,” “exhibition and visualization,” “software solutions,” “virtual exhibition” and “metadata and database.” The future direction of research lies in extended reality, which integrates virtual reality (VR), augmented reality (AR) and mixed reality (MR); virtual restoration and preservation; 3D printing; as well as the utilization of robotics, drones and the Internet of Things (IoT) for mapping, conserving and monitoring historical sites and cultural heritage sites.Practical implicationsThe cultural heritage institution can use this result as a source to develop AI-based strategic planning for curating, preservation, preventing and presenting cultural heritages. Researchers and academicians will get insight and deeper understanding on the research trend and use the interdisciplinary of AI and cultural heritage for expanding collaboration.Social implicationsThis study will help to reveal the trend and evolution of AI and cultural heritage. The finding also will fill the knowledge gap on the research on AI and cultural heritage.Originality/valueSome similar bibliometric studies have been conducted; however, there are still limited studies on contribution of AI to preserve cultural heritage in wider view. The value of this study is the cluster in which AI is used to preserve, curate, present and assess cultural heritages.

Refining HPCToolkit for application performance analysis at exascale

Refining HPCToolkit for application performance analysis at exascale

Artificial intelligence applications for immunology laboratory: image analysis and classification study of IIF photos.

Artificial intelligence (AI) is increasingly being used in medicine to enhance the speed and accuracy of disease diagnosis and treatment. AI-based image analysis is expected to play a crucial role in future healthcare facilities and laboratories, offering improved precision and cost-effectiveness. As technology advances, the requirement for specialized software knowledge to utilize AI applications is diminishing. Our study will examine the advantages and challenges of employing AI-based image analysis in the field of immunology and will investigate whether physicians without software expertise can use MS Azure Portal for ANA IIF test classification and image analysis. This is the first study to perform Hep-2 image analysis using MS Azure Portal. We will also assess the potential for AI applications to aid physicians in interpreting ANA IIF results in immunology laboratories. The study was designed in four stages by two specialists. Stage 1: creation of an image library, Stage 2: finding an artificial intelligence application, Stage 3: uploading images and training artificial intelligence, Stage 4: performance analysis of the artificial intelligence application. In the first training, the average pattern identification accuracy for 72 testing images was 81.94%. After the second training, this accuracy increased to 87.5%. Patterns Precision improved from 71.42 to 79.96% after the second training. As a result, the number of correctly identified patterns and their accuracy increased with the second training process. Artificial intelligence-based image analysis shows promising potential. This technology is expected to become essential in healthcare facility laboratories, offering higher accuracy rates and lower costs.

Structural, optical, and electrical characteristics of HPMC/PVA-I2O5 composites: Fabrication and performance analysis for energy storage applications

Polymer composites (PCs) are increasingly utilized in energy storage applications, notably in dielectric capacitors, due to their distinct properties and advantages over conventional liquid electrolytes. In this study, we investigate the structural, optical, electrical, and dielectric properties of hydroxypropyl methylcellulose (HPMC)/polyvinyl alcohol (PVA) composite films filled with varying concentrations of iodine pentoxide (I2O5), prepared via a solution casting method. Incorporating I2O5 into the polymer matrix significantly impacted the composite's properties. FTIR and XRD analyses revealed disturbances in molecular structure, crystallization order, and the presence of I2O5 crystal phases in the composite films. Calculations of crystallinity percentage indicated a reduction with I2O5 addition, leading to increased amorphous phase content suitable for enhancing electrical conductivity (σ). UV/vis spectroscopy studies demonstrated decreased optical energy gaps, suggesting improved charge storage capability. The σ analysis revealed enhanced values with I2O5 addition, indicative of improved charge mobility within the composite films. Frequency-dependent behaviors in complex permittivity (ε′ and ε″) highlighted the potential of these composites for efficient charge storage across different frequency ranges. Impedance analysis provided insights into space charges and conductive paths within the composites, influencing their electrical characteristics. Capacitors fabricated from the HPMC/PVA-I2O5 composites exhibited enhanced energy storage capacity and controlled conductance characteristics, demonstrating promising performance for energy storage applications. Our findings demonstrate that the HPMC/PVA-I2O5 composites are potential dielectric materials for capacitor technology.

Defining Service Quality of BRI Merchant Application Using Importance Performance Analysis

The COVID-19 pandemic has changed people's habits worldwide, accelerating the adoption of cashless payment transactions, especially in Indonesia. This situation allows Financial Technology companies and Conventional Banks to increase competition. This thesis focuses on the Digital Payments Industry in Indonesia, emphasizing the Merchant Acceptance Business, which has a crucial role as a catalyst for Cashless Payments. This research is based on previous studies regarding service quality, business model canvas, and the importance of performance analysis of the BRI Merchant Application. This research aims to define a service quality strategy for BRI merchant applications through a critical performance analysis approach. The study found that the quality of BRI merchant application services consists of changing merchant data, adding EDC, Checking transactions, reconciling Payments, filing complaints, and monitoring complaints.

Energy efficiency and performance analysis of a legacy atomic scale materials modeling simulator (VASP)

This work tackles the performance and energy consumption analysis of a legacy scientific application, the VASP (Vienna Ab-initio Simulation Package), an application commonly used by physicists and chemists for modeling materials at the atomic scale. Many of these scientific applications have been implemented in Fortran, where energy metrics instrumentation is not straightforward. We obtained performance figures (execution time and energy consumption) by instrumenting the source code using EML. This energy measurement library has been modified to introduce Fortran interfaces for these metrics. The analysis was carried out using different matrix algebra libraries, parallelization techniques, and hardware platforms, emphasizing on the MPI, OpenMP, and CUDA parallel implementations of the algorithms used in VASP. We employ various material specifications (atomic structures) and molecular sizes of a silicon-based crystal to create a set of benchmarks for these specifications, leading to some recommendations for final users regarding performance improvements. The proposed benchmarking technique assists the user in selecting the right combination of problem size, compilers, and parallelization options available in VASP. For a given system platform, the user will be able to determine not only the architecture to use (GPU or multicore processors), but also the appropriate library and parallelization according to the atomic structure and molecular size.

Performance Analysis of Application of BIM Technology and Two-Way Progressive Optimization Algorithm in Energy-Saving Design of Residential Buildings Based on BIM Technology

The current residential energy-saving design is lagging behind, and lack of systematic design methods and scientific technical means seriously restricts process of improving quality of residential buildings in China. With development and application of digital information technology in construction field, BIM technology has brought new opportunities construction industry, and building performance data has become information basis for scientific promotion of energy conservation. This paper uses BIM technology as a platform to establish an information base of common building materials and components in Chongqing through literature research, field studies, summarization, and application practice, and to help architects make wise decisions at early design stage by using "one-click" scheme comparison and design evaluation to avoid a large number of potential energy consumption problems at a later stage, It greatly improves energy efficiency and design quality of buildings.

Performance Analysis of Duct Vane Application on Patrol Boats Using Computational Fluid Dynamics

Performance Analysis of Duct Vane Application on Patrol Boats Using Computational Fluid Dynamics

Study on the impact of soil environment organic substances on the ageing of urban PE gas pipes in service

PurposeThe service environment of urban polyethylene (PE) pipes has a crucial influence on their long-term safety and performance. Based on the application and structural performance analysis of PE pipe failure cases, this study aims to investigate the impact of organic substances in the soil on the aging behavior of PE pipes by designing organic solutions with different concentrations, which are based on the composition of organic substances in the soil environment, and periodic immersion tests.Design/methodology/approachSoil samples in the vicinity of the failed pipes were analyzed by gas chromatography-mass spectrometry, sensitive organic substances were screened and soaking solutions of different concentrations were designed. After the soaking test, the PE pipe samples were analyzed using differential scanning calorimetry, Fourier-transform infrared spectroscopy and other testing methods.FindingsThe performance difference between the outer surface and the middle of the cross section of PE pipes highlights the influence of the soil service environment on their aging. Different organic solutions can have varying impacts on the aging behavior of PE pipes when immersed. For instance, when exposed to amine organic solutions, PE pipes may have an increased weight and decreased material yield strength, although there is no reduction in their thermal or oxygen stability. On the contrary, when subjected to ether organic solutions, the surface of PE pipe specimens may be affected, leading to a reduction in material fracture elongation and a decrease in their thermal and oxygen stability. Furthermore, immersion in either amine or ether organic solutions may result in the production of hydroxyl and other aging groups on the surface of the material.Originality/valueUnderstanding the potential impact of organic substances in the soil environment on the aging of PE pipe ensures the long-term performance and safety of urban PE pipe. This research approach will provide valuable insights into improving the durability and reliability of urban PE pipes in soil environments.

Performance analysis of web applications created in the Spring and Laravel frameworks

The article compares the performance of two test applications created using the Spring Boot and Laravel application frameworks. The aim of the study is to find an answer to the research question: which framework offers better time performance. Twelve test scenarios were created for the analysis, and they were used to conduct performance tests using the Apache JMeter tool. Additionally, application metrics and community support for both frameworks were compared. The research confirmed that the application built on the Spring Boot framework has better performance.

Performance Analysis of Family Welfare Empowerment Application: A Kanban Method Approach

This research examines the application of the Kanban method in testing a family welfare empowerment application. The Kanban method, initially developed by Toyota in manufacturing, has been effectively applied in software development. This study involves a series of tests involving various features within the application, such as user registration, village data collection, processing of the family welfare empowerment data at the Village/District level, and more. The test results show that most tests were successful, highlighting the application's success in executing essential functions such as user registration and event scheduling. However, some tests failed, primarily in inputting village, hamlet, and community unit data. These results indicate that using the Kanban method in testing a family welfare empowerment application can potentially enhance development and testing efficiency. Metrics such as testing time, test success, and time efficiency have provided valuable insights into the application's performance. In conclusion, this testing provides a foundation for further application development, focusing on improving the areas that experienced testing failures. This research also opens up opportunities for further studies on using the Kanban method in software testing in various other application development contexts.

Performance analysis of parallel composite service-based applications in clouds

When processing composite service application jobs containing parallel tasks, service providers can optimize their quality of services (QoS) based on refined parallelism settings and resource allocation schemes by leveraging analytical models. However, building such analytical models is particularly challenging due to the fact that an accurate model is required to capture the dependence among sequential or concurrent services and predict response time of each service with varying degrees of parallelism (DoPs). Faced with these challenges, we propose a novel multiclass multi-pool analytical model for composite service applications deployed in clouds. Specifically, we consider embarrassingly parallel services, which do not require additional overhead to split tasks into multiple independent subtasks. We first establish a multi-pool queue network that takes into account the dependence among services and analyze task parameters of each service. To optimize the QoS of embarrassingly parallel services, we present a differentiated parallel processing mechanism which can set varying DoPs for tasks. We also propose an original modulating partition method to predict important performance indicators of each service. By leveraging the proposed model, service providers can obtain optimal settings for the DoPs, resource allocation, and the number of cloud servers, to achieve specific performance levels. Through extensive experiments based on the rendering service dataset and Alibaba’s open cluster traces, we demonstrate that the proposed model can not only provide accurate prediction results but also significantly reduce jobs’ response time by at least 20%.

Optimized design and application performance analysis of heat recovery hybrid system for radioisotope thermophotovoltaic based on thermoelectric heat dissipation

Radioisotope thermophotovoltaic (RTPV) generators face a fundamental challenge, which is the significant output loss and energy wastage caused by the substantial thermal deposition resulting from the arrival of infrared radiation from the heat source at the energy conversion unit. This contradiction has gradually become a key limiting factor for its further development in recent years. In this work, a novel hybrid system based on the thermophotovoltaic-thermoelectric (TPV-TE) effect is proposed, in which the Bi2Te3-based I/W-type thermoelectric leg plays both heat dissipation and heat recovery for power supply. The heat recovery thermoelectric legs were prepared using a cold pressing mould and sintering method, and their Seebeck effect was used to convert the unwanted heat recover from InGaAs thermophotovoltaic cells into electrical power. The design preparation scheme of the heat recovery hybrid module and its potential application performance at 700–1000 K heat source temperature were investigated through experimental tests and simulations. The W-type TPV-TE heat recovery hybrid system exhibits good gain of 12.9% at 1000 K, and the output power can be increased by additional 21.6% in series mode. Simulations for environmental applications show better heat recovery in deep space than on Earth, with an output gain of 63.7% and an energy conversion efficiency of 11.23%. The heat recovery design enhances the competitiveness of the RTPV and provides new ideas for optimizing other heat recovery applications for thermal energy conversion systems.

Distributed multi-target tracking and active perception with mobile camera networks

Smart cameras are an essential component in surveillance and monitoring applications, and they have been typically deployed in networks of fixed camera locations. The addition of mobile cameras, mounted on robots, can overcome some of the limitations of static networks such as blind spots or back-lightning, allowing the system to gather the best information at each time by active positioning. This work presents a hybrid camera system, with static and mobile cameras, where all the cameras collaborate to observe people moving freely in the environment and efficiently visualize certain attributes from each person. Our solution combines a multi-camera distributed tracking system, to localize with precision all the people, with a control scheme that moves the mobile cameras to the best viewpoints for a specific classification task. The main contribution of this paper is a novel framework that exploits the synergies that result from the cooperation of the tracking and the control modules, obtaining a system closer to the real-world application and capable of high-level scene understanding. The static camera network provides global awareness of the control scheme to move the robots. In exchange, the mobile cameras onboard the robots provide enhanced information about the people on the scene. We perform a thorough analysis of the people monitoring application performance under different conditions thanks to the use of a photo-realistic simulation environment. Our experiments demonstrate the benefits of collaborative mobile cameras with respect to static or individual camera setups.

Numerical simulation study on shear resistance of anchorage joints considering tensile–shear fracture criterion of 2G-NPR bolt

2G-NPR bolt (the 2nd generation Negative Poisson’s Ratio bolt) is a new type of bolt with high strength, high toughness and no yield platform. It has significant effects on improving the shear strength of jointed rock mass and controlling the stability of surrounding rock. To achieve an accurate simulation of bolted joint shear tests, we have studied a numerical simulation method that takes into account the 2G-NPR bolt's tensile–shear fracture criterion. Firstly, the indoor experimental study on the tensile–shear mechanical properties of 2G-NPR bolt is carried out to explore its mechanical properties under different tensile–shear angles, and the fracture criterion of 2G-NPR bolt considering the tensile–shear angle is established. Then, a three-dimensional numerical simulation method considering the tensile–shear mechanical constitutive and fracture criterion of 2G-NPR bolt, the elastoplastic mechanical behavior of surrounding rock and the damage and deterioration of grouting body is proposed. The feasibility and accuracy of the method are verified by comparing with the indoor shear test results of 2G-NPR bolt anchorage joints. Finally, based on the numerical simulation results, the deformation and stress of the bolt, the distribution of the plastic zone of the rock mass, the stress distribution and the damage of the grouting body are analyzed in detail. The research results can provide a good reference value for the practical engineering application and shear mechanical performance analysis of 2G-NPR bolt.

Performance analysis of UAV sprayer application in precision agriculture

The effectiveness of the use of spray UAVs in precision agriculture largely depends both on the UAVs chosen for this purpose and their characteristics, and on the organization of the control of the UAV swarm, which requires an analysis of the UAV microprocessor performance in various modes of their use. It is possible to organize a general control of a swarm of UAVs, as well as individual control in offline mode. The article presents a methodology for analyzing the performance of spray UAVs in precision agriculture. A model example of the analysis of the microprocessor performance of a UAV swarm based on the specified system parameters is given. It is shown that the use of models of microprocessor performance of a swarm of UAVs in precision farming makes it possible to obtain the information necessary to make a decision on the development or purchase of UAVs of one type or another, the choice of fertilizer and pesticide spraying systems, the scaling and redundancy of UAVs and elements of the spraying system.

Facilitating the Process of Performance Analysis of HPC Applications

Facilitating the Process of Performance Analysis of HPC Applications

USER SATISFACTION ANALYSIS OF GOJEK APPLICATION USING END-USER COMPUTING SATISFACTION (EUCS)

At the first time, Gojek application is the online transportation services, but now it has various services. Online transportation services in the Gojek application are GoRide and GoCar. Analysis of application performance can be done to determine the user satisfaction. The aim of this research is to analyze the Gojek application user of satisfaction, especially GoRide and GoCar online transportation services. This research consists of 3 steps. The steps are making research model and adopting questionnaire, validity and realibility test and data analysis. Evaluation is done using 5 dimensions of End User Computing Satisfaction (EUCS). It consists of content, accuracy, format, easy of use and timeliness. In addition, the demographic factors of the respondents were also added, namely gender, age and occupation. There are 100 respondents in this research. The result of this research are the user satisfaction of Gojek application, especially GoRide and GoCar, can be categorized as very satisfied. The dimensions of EUCS and demographic factors have positive affect to user satisfaction. Gojek application can develop by increasing the accuracy of information and timeliness.

Cloud benchmarking and performance analysis of an HPC application in Amazon EC2

Cloud computing platforms have been continuously evolving. Features such as the Elastic Fabric Adapter (EFA) in the Amazon Web Services (AWS) platform have brought yet another revolution in the High Performance Computing (HPC) world, further accelerating the convergence of HPC and cloud computing. Other public clouds also support similar features further fueling this change. In this paper, we show how and why the performance of a large-scale computational fluid dynamics (CFD) HPC application on AWS competes very closely with the one on Beskow—a Cray XC40 supercomputer at the PDC Center for High-Performance Computing - in terms of cost-efficiency with strong scaling up to 2304 processes. We perform an extensive set of micro and macro benchmarks in both environments and conduct a comparative analysis. Until as recently as 2020 these benchmarks have notoriously yielded unsatisfactory results for the cloud platforms compared with on-premise infrastructures. Our aim is to access the HPC capabilities of the cloud, and in general to demonstrate how researchers can scale and evaluate the performance of their application in the cloud.

Multicolor tunable luminescence and energy transfer mechanism in Gd2O2S: Dy3+, Sm3+ phosphors

High quality single-phase multicolor emission phosphor is a prerequisite for efficient luminescence devices, but the system design and quantity preparation are still facing substantial challenges. Herein, Gd2O2S-based phosphors with high crystallinity, good dispersibility, and relatively good size uniformity were obtained by optimizing the type and components of flux based on the conventional solid-state method. By single-doping system study, the emission properties of matrix and activated ions are expounded, meanwhile the composition and co-excitation wavelength of co-doping system are designed. In the co-doping system, we mainly realized adjustable emission, interionic energy transfer, and application performance analysis. Firstly, multicolor emission in the range of yellow, orange and white was achieved through the modulation of dopant type and concentration as well as excitation wavelength. Secondly, the phenomena of spectral overlap (between Dy3+ and Sm3+), fluorescence intensity change (606 nm of Sm3+) and the monotonically decreasing fluorescence lifetime (Dy3+ at 578 nm) were evidence of energy transfer in the co-doping system. The theoretical fitting demonstrates that the energy transfer process of Dy3+→Sm3+ is primarily based on the quadrupole-quadrupole interaction mechanism. In addition, the cathodoluminescence spectra, temperature-dependent emission spectra, and magnetic properties tests have demonstrated the characteristics of multicolor adjustable emission (electron-beam excitation), excellent thermal stability, and good paramagnetic properties of the co-doping phosphors, further indicating that the Gd2O2S:Dy3+/Sm3+ system phosphors have potential as an excellent optical-magnetic bifunctional material in the fields of luminescence and bioimaging.