Computer Configuration Research Articles

A computational study of the deposition of firebrands between two side-by-side blocks

The deposition of firebrands between two blocks, representing neighboring simplified structures, was investigated by large-eddy simulation and Lagrangian tracking of firebrands. Fire Dynamics Simulator was modified and implemented for simulations. The computational configuration resembled the previous wind-tunnel measurement setup including two blocks and the firebrand generator apparatus, aka NIST Dragon (Suzuki and Manzello 2021). Different wind speeds and frictional coefficients between the sliding firebrands and the ground were considered. Simulations revealed several flow effects influencing the motion of firebrands on the ground, such as re-circulation flow in the wake of the dragon, a crossflow upwind of the blocks, and twin re-circulation regions on leeward and windward sides of the blocks. At lower wind speeds, firebrands were accumulated somewhere between the dragon and the blocks, consistent with observations in the previous measurements. At higher wind speeds, the firebrands tended to accumulate momentarily before the crossflow region and then accelerate through the gap between the blocks. Some accumulated in the leeward corner of the blocks. Firebrands displayed much more dispersion in the streamwise direction compared to the spanwise direction because the normal component of the Reynolds stress was greater in the streamwise direction.

Application of polyhedral meshes in large-eddy simulation of building array flow fields within neutral and unstable boundary layers

Urbanization has intensified the urban heat island phenomenon, a critical concern for human habitation in recent decades. Analyzing flow fields around building arrays is vital for mitigating issues such as heatstroke and air pollution, thereby enhancing human comfort in urban environments. However, challenges in accuracy and computational efficiency persist in simulating urban thermal environments. This study evaluates how boundary layer meshes in polyhedral meshes affect wind and temperature distributions in neutral and unstable boundary layers, utilizing large-eddy simulation (LES). A total of ten cases were examined, including eight with local mesh refinement and two without. The study demonstrates that local mesh refinement is an effective strategy to reduce mesh count by approximately 60 %, thereby reducing computational time by 60 % using the same computational configuration. The performance of the polyhedral meshes was found to be comparable to that of the hexahedral meshes. For the mean velocity and temperature, the discrepancies between the hexahedral and polyhedral cases were within 10 %, while for the second-order statistics, the discrepancies were within 20 %. Within the neutral boundary layer, boundary layer meshes on the ground and building surfaces had minimal impact on the wind field. However, these meshes enhanced the accuracy of low percentile wind speed estimations by approximately 20 % within the unstable boundary layer. Moreover, this study lays the foundation for research on the thermal environment in actual urban areas and contributes to the guidelines for LES with non-isothermal inflow conditions.

Aspects of Symmetry in Petri Nets

Symmetry is a fundamental mathematical property applicable to the description of various shapes both geometrical and representational. Symmetry is central to understanding the nature of various objects. It can be used as a simplifying principle when structures are created. Petri nets are widely covered formalisms, useful for modeling different types of computer systems or computer configurations. Different forms of Petri nets exist along with several forms of representation. Petri nets are useful for i) deterministic and ii) non-deterministic modeling. The aspect of symmetry in Petri nets requires in-depth treatment that is often overlooked. Symmetry is a fundamental property found in Petri nets. This work tries to briefly touch on these properties and explain them with simple examples. Hopefully, readers will be inspired to carry out more work in this direction.

FEATURES OF THE USE OF TECHNICAL MEANS IN THE REMEDIAL WORK WITH PERSONS WITH STUTTERING

The scientific and methodological article considers the problem of using technical means to correct stuttering. The existing approaches to speech therapy work using traditional methods were analyzed as well as the peculiarities of the implementation of acoustic devices. The method of rhythmization as an effective means of overcoming stuttering is considered in detail and the features of its use are determined. Based on the results of the research, it was concluded that modern technical devices allow designing fundamentally new pedagogical technologies. Specialists in special education direct these technologies to the activation and effective functioning of compensatory mechanisms, the formation and development of speech activity of persons with stuttering. The purpose of the study is to analyze the existing approaches to speech therapy work using traditional methods and to outline the role of technical acoustic means in the process of speech correction. The use of technical means in remedial work with persons with speech disorders is a challenge of the times, which reflects progressive changes in the scientific and technical sphere and improves the effectiveness of logocorrective work for various mental and physical disorders. Technical means allow for remedial and developmental work to overcome stuttering, and their implementation requires compliance with certain conditions: compliance of the special software with the computer configuration; use of methodically justified and tested technical means and programs; ensuring the optimal load regime; complex influence in the process of correction of group classes and individual consultations; creation of a comfortable psycho-emotional environment; the use of modern remedial technologies and their differentiated use, taking into account the individual characteristics of a patient. We see the prospect of further research in the development of methods of using information and communication technologies in remedial work with persons with severe speech disorders.

Digital Flow in a Pool Induced by a Vertical Jet

Turbulent water jets remain a critical study area, particularly the relation of the water flow with air entrainment and its role in energy dissipation at different hydraulic structures. Plunge pools, formed by the impact of jets on water cushions, play a pivotal role in energy dissipation. Understanding the complex flow dynamics within these pools is essential for designing efficient hydraulic structures. In this research, we present a comprehensive investigation of different numerical simulations, defining two-phase (air-water) in different ways, and them compare with experimental measurements. The primary objective is to analyze the pressure distribution at the bottom of a plunge pool induced by a vertical jet and understand the importance of accurately defining air-water flow in the dynamics of the jet into the pool. Our study bridges the gap between empirical data and computational modeling, shedding light on the intricate behavior of such flows with different method-based solvers: VOF, sub-grid, and multi-phase Euler. Various computational domains, mesh configurations, and analyses spanning different time periods, frequencies, and scales were considered.

Theoretical Prediction of the Reaction Probabilities of H, O, and OH Radicals on the Polypropylene Surface.

To determine the H-abstraction reaction probabilities of H/O/OH radicals with a polypropylene (PP) surface, a first-principles calculation was performed based on the DLPNO-CCSD(T)/CBS//M06-2X-D3/def-TZVP theory level. The PP chain model used in this study was 2,4,6-trimethylheptane. The rate constants of the H/O/OH radicals with the isolated PP chain model were calculated based on the conventional transition-state theory. By comparing the experimental values and considering the error factors and their compensation, it was concluded that the orders of magnitude of the predicted rate constants were accurate. The resulting rate constants were converted to reaction probabilities between the H/O/OH radicals and the PP surface. The method used in this study is applicable for obtaining theoretical values of surface reaction probabilities based on first-principles calculations. The calculation at the DLPNO-CCSD(T)/CBS theory level has high accuracy but consumes a large amount of computational resources. The study also demonstrated that the double-hybrid functionals, wB97x-2-D3(BJ) and rev-DSD-PBEP86-D3(BJ), with a 3-ζ or 4-ζ basis set, could reproduce the electronic energy values obtained from DLPNO-CCSD(T)/CBS while using only approximately 1/100 of the computational resources required by the latter under our computer configuration.

PostGWAS: A web server for deciphering the causality post the genome-wide association studies

While genome-wide association studies (GWAS) have unequivocally identified vast disease susceptibility variants, a majority of them are situated in non-coding regions and are in high linkage disequilibrium (LD). To pave the way of translating GWAS signals to clinical drug targets, it is essential to identify the underlying causal variants and further causal genes. To this end, a myriad of post-GWAS methods have been devised, each grounded in distinct principles including fine-mapping, co-localization, and transcriptome-wide association study (TWAS) techniques. Yet, no platform currently exists that seamlessly integrates these diverse post-GWAS methodologies. In this work, we present a user-friendly web server for post-GWAS analysis, that seamlessly integrates 9 distinct methods with 12 models, categorized by fine-mapping, colocalization, and TWAS. The server mainly helps users decipher the causality hindered by complex GWAS signals, including casual variants and casual genes, without the burden of computational skills and complex environment configuration, and provides a convenient platform for post-GWAS analysis, result visualization, facilitating the understanding and interpretation of the genome-wide association studies. The postGWAS server is available at http://g2g.biographml.com/.

Walking on two legs: Joint service placement and computation configuration for provisioning containerized services at edges

With the development of edge computing and container virtualization, provisioning containerized services at network edges is proposed for high responsiveness and low wide area network (WAN) traffic. However, realizing its full potential faces multiple challenges. First, due to containers’ fine-grained computation resource isolation, finely configuring services’ computation resource requirements is needed, especially for resource-constrained edge nodes. Second, due to edges’ heterogeneity and services’ diversity, system performance highly depends on which edge node to place each service. Third, as the main metric of quality of service, service response time involves the computing-network delay tradeoff and urges to optimize the decisions jointly. Prior works on edge-enabled service placement either ignore computation resource isolation and configuration, or assume computation resource configuration is given manually. To fill this gap, this paper investigates the joint service placement and computation configuration problem for provisioning containerized services at edges. Then based on the convex and submodular optimization techniques, we propose a two-stage greedy and local-search combined algorithm, TeLa for short. Rigorous theoretical analyses demonstrate that TeLa is a polynomial-time algorithm with performance guarantees. Finally, we implement twelve containerized services and an edge computing prototype to realistically evaluate TeLa. The results confirm TeLa’s empirical superiority over state-of-the-art algorithms, in terms of 39% on average reduction on the weighted sum of service response time and WAN traffic.

Cisco Packet Tracer modeling in the course of computer networks

The computer networking course is usually taught in a mixed mode, which includes a lecture and a practical lesson, and in addition to a full-time theoretical lesson, students must take practical classes to evaluate technologies and content. Nevertheless, the abstractions of the computer networking course, such as the multilevel complexity of the TCP/IP network, the connection and configuration of client and server infrastructure, as well as the differences in static and dynamic configuration of IP addresses, set students a huge task to understand and master the basic concept of computer networking technologies. Thus, the approach based on the use of computer network modeling and visualization tools when teaching the computer networks course is considered useful for teachers and students. In this study, Cisco Packet Tracer computer network simulation software was used in the Computer Networking Course (KJ2212). Students (N=55) got acquainted with the Cisco Packet Tracer program, on the basis of which they developed a global network (WAN) consisting of personal computer (PC) configuration operations, servers and switches in accordance with the Cisco standard. Subsequently, with the help of a survey, the opinions of students and their understanding of the effectiveness of Cisco packet Tracer in teaching computer networks were studied. All feedback was statistically studied using SPSS 16.0. From the analysis of descriptive results, all students agreed that Cisco Packet Tracer successfully helped them understand several key concepts of computer networks and at the same time eliminate some abstractions they encountered during the course (N=32: totally agree; N=23: I agree). Cisco Packet Tracer has established itself as a modeling and visualization tool as an effective software that supports computer networking course training.networking course training.

A Shingled Glass Envelope System Constructed from Reclaimed Insulated Glass

This paper presents a new approach to the design and construction of glazed building envelopes using salvaged insulated glazing units from demolition sites or surplus supply. Typically, Insulated Glazing Units (IGUs) are sent to landfill. Contemporary Architectural glazing is floated using virgin sand melted at 1700°C, a high energy extractive process. Obsolete architectural glass sent to recycling plants is not fed back into new float glass, rather it is downcycled to products such as glass bottles. This paper introduces a pathway for reusing obsolete and irregular Insulated Glazing Units into new curtainwalls; a pathway that currently does not exist. We demonstrate that the carbon footprint of glazed curtainwall could be halved by utilizing reclaimed IGUs. The system is a high-performance enclosure with weather tight compression gaskets and overlapping IGUs for thermal insulation and operational energy advantages over typical curtainwall systems. The system involves a computational configuration process for determining the best fit assembly of salvaged glass from a digitized inventory. The shingled glass façade system could be used in various applications, ranging from corporate offices to storefronts. This paper presents a one-to-one proof of concept, made from reclaimed IGUs of irregular size, collected in Lewes (UK).

A Novel Equivalent Method for Computing Mechanical Properties of Random and Ordered Hyperelastic Cellular Materials.

Simulating the mechanical behavior of cellular materials stands as a pivotal step in their practical application. Nonetheless, the substantial multitude of unit cells within these materials necessitates a considerable finite element mesh, thereby leading to elevated computational expenses and requisites for formidable computer configurations. In order to surmount this predicament, a novel and straightforward equivalent calculation method is proposed for the computation of mechanical properties concerning both random and ordered hyper-elastic cellular materials. By amalgamating the classical finite element approach with the distribution attributes of cells, the proposed equivalent calculation method adeptly captures the deformation modes and force-displacement responses exhibited by cell materials under tensile and shear loads, as predicted through direct numerical simulation. This approach reflects the deformation characteristics induced by micro-unit cells, elucidates an equivalent principle bridging cellular materials and equivalent materials, and substantially curtails exhaustive computational burdens. Ultimately, this method furnishes an equivalent computational strategy tailored for the engineering applications of cellular materials.

Optimising the flight turnaround schedules: An improved sliding time windows approach based on MILP and CP models

This paper addresses the scheduling of turnaround operations for flights in civil airports. A series of complex issues, including the heterogeneity of flights and operators, resource constraints on turnaround operations, temporal restrictions and alternative service patterns of turnaround operations, multi-functional operators, multi-trip services and multi-to-one services, are jointedly considered. We propose two formulations for the problem: A mixed-integer linear programming (MILP) model, and a constraint programming (CP) model. For comparison purpose, we also present simplified versions of the models in which the multi-to-one services are prohibited. The uncertainty are incorporated by modifying the models based on robust optimisation principles. The numerical experiments are conducted using instances generated based on real flight data at Beijing Capital International Airport. It is shown that under current computer configurations, small-scale instances can be solved to the optimum by CPLEX within an acceptable period of time using the MILP model, while moderate-scale instances can be tackled using the CP formulation. To cope with large-scale instances, an improved sliding time window method is developed, and evaluated with different parameter combinations, showing that practical turnaround schedule would best be updated two to three times per hour. Besides, after a case study in both static and stochastic scenarios, we illustrate that multi-to-one services should be specifically considered and highlighted, for their existence could significantly improve the operator utilisation rate and reduce flight delay, especially when the uncertainties are taken into account.

Introduction to the Monte Carlo dose engine COMPASS for BNCT.

The Monte Carlo method is the most commonly used dose calculation method in the field of boron neutron capture therapy (BNCT). General-purpose Monte Carlo (MC) code (e.g., MCNP) has been used in most treatment planning systems (TPS) to calculate dose distribution, which takes overmuch time in radiotherapy planning. Based on this, we developed COMPASS (COMpact PArticle Simulation System), an MC engine specifically for BNCT dose calculation. Several optimization algorithms are used in COMPASS to make it faster than general-purpose MC code. The parallel computation of COMPASS is performed by the message passing interface (MPI) library and OpenMP commands, which allows the user to increase computational speed by increasing the computer configurations. The physical dose of each voxel is calculated for developing a treatment plan. Comparison results show that the computed dose distribution of COMPASS is in good agreement with MCNP, and the computational efficiency is better than MCNP. These results validate that COMPASS has better performance than MCNP in BNCT dose calculation.

Statistical Review of Health Monitoring Models for Real-Time Hospital Scenarios

Health Monitoring System Models (HMSMs) need speed, efficiency, and security to work. Cascading components ensure data collection, storage, communication, retrieval, and privacy in these models. Researchers propose many methods to design such models, varying in scalability, multidomain efficiency, flexibility, usage and deployment, computational complexity, cost of deployment, security level, feature usability, and other performance metrics. Thus, HMSM designers struggle to find the best models for their application-specific deployments. They must test and validate different models, which increases design time and cost, affecting deployment feasibility. This article discusses secure HMSMs' application-specific advantages, feature-specific limitations, context-specific nuances, and deployment-specific future research scopes to reduce model selection ambiguity. The models based on the Internet of Things (IoT), Machine Learning Models (MLMs), Blockchain Models, Hashing Methods, Encryption Methods, Distributed Computing Configurations, and Bioinspired Models have better Quality of Service (QoS) and security than their counterparts. Researchers can find application-specific models. This article compares the above models in deployment cost, attack mitigation performance, scalability, computational complexity, and monitoring applicability. This comparative analysis helps readers choose HMSMs for context-specific application deployments. This article also devises performance measuring metrics called Health Monitoring Model Metrics (HM3) to compare the performance of various models based on accuracy, precision, delay, scalability, computational complexity, energy consumption, and security.

Analysis of Differences Across Types of Interior Parts of Computer and Computer Price

The enhancement of digital computers takes an active part in promoting the development of different aspects of the world. In the meantime, interior parts of computers are also rapidly enhanced and refined. Various combinations of inner parts of a computer would play a decisive factor in the cost so the aim of this article would discuss the relationship between the performance parameters of computers and the prices. This article divides the performance parameters of computers into nine aspects, such as speed, RAM size, etc., With an emphasis on the connection between the price of the computer and its performance parameters. This article employs a multiple linear regression and a logistic regression model to estimate the pricing using computer configuration parameters. The MSE, AIC and other parameters are established to measure the goodness of fit for models. In order to forecast prices for computers with certain performance specifications, an optimal model is finally developed.

Categorization of Arabic posts using Artificial Neural Network and hash features

Sentiment analysis is an important study topic with diverse application domains including social network monitoring and automatic analysis of the body of natural language communication. Existing research on sentiment analysis has already utilised substantial domain knowledge available online comprising users’ opinion in various areas such as business, education, and social media. There is however limited literature available on Arabic language sentiment analysis. Furthermore, datasets used in majority of these studies have poor classification. In the present study, we utilised a primary dataset comprising 2122 sentences and 15,331 words compiled from 206 publicly available online posts to perform sentiment classification by using advanced machine learning technique based on Artificial Neural Networks. Unlike lexicon-based techniques that suffer from low accuracy due to their computational nature and parameter configuration, Artificial Neural Networks were used to classify people opinion posts into three categories including conservative, reform and revolution, accompanied by multiple hasher vector size to benchmark the performance of the proposed model. Extensive simulation results indicated an accuracy of 93.33%, 100%, and 100% for the classification of conservation, reform, and revolutionary classes, respectively.

Latency Minimization for Mobile Edge Computing Networks

The proliferation of data-intensive mobile applications is causing latency to become an issue in mobile edge computing (MEC) systems. In this work, we propose a novel methodology that optimizes communication, computation, and caching configurations in MEC to minimize the mean latency experienced by mobile devices. Transmission and computation processes are modeled using M/G/1 queues to account for service rates and warm-up times. Our caching scheme includes time variables for each file at each edge server in determining when to discard files from storage. We theoretically analyze the latency experienced by mobile devices due to communication, computation, and caching, showing how MEC system latency depends on the offloading decisions of mobile devices, bandwidth and CPU resources, and expiration times of files in the storage of edge servers. Our method for solving the latency minimization problem consists of two main components: iNner cOnVex Approximation (NOVA) to deal with non-convexity in the optimization, and an online algorithm for preventing cache storage violations as new tasks arrive and are serviced by the MEC system. Simulation results show that our algorithm outperforms several baselines in minimizing latency, and verify the benefit of including different resource allocation variables in our optimization.

MC-CIM: Compute-in-Memory With Monte-Carlo Dropouts for Bayesian Edge Intelligence

We propose MC-CIM, a compute-in-memory (CIM) framework for robust, yet low power, Bayesian edge intelligence. Deep neural networks (DNN) with deterministic weights cannot express their prediction uncertainties, thereby pose critical risks for applications where the consequences of mispredictions are fatal such as surgical robotics. To address this limitation, Bayesian inference of a DNN has gained attention. Using Bayesian inference, not only the prediction itself, but the prediction confidence can also be extracted for planning risk-aware actions. However, Bayesian inference of a DNN is computationally expensive, ill-suited for real-time and/or edge deployment. An approximation to Bayesian DNN using Monte Carlo Dropout (MC-Dropout) has shown high robustness along with low computational complexity. Enhancing the computational efficiency of the method, we discuss a novel CIM module that can perform in-memory probabilistic dropout in addition to in-memory weight-input scalar product to support the method. We also propose a compute-reuse reformulation of MC-Dropout where each successive instance can utilize the product-sum computations from the previous iteration. Even more, we discuss how the random instances can be optimally ordered to minimize the overall MC-Dropout workload by exploiting combinatorial optimization methods. Application of the proposed CIM-based MC-Dropout execution is discussed for MNIST character recognition and visual odometry (VO) of autonomous drones. The framework reliably gives prediction confidence amidst non-idealities imposed by MC-CIM to a good extent. Proposed MC-CIM with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$16\times 31$ </tex-math></inline-formula> SRAM array, 0.85 V supply, 16nm low-standby power (LSTP) technology consumes 32 pJ for 30 MC-Dropout instances of probabilistic inference in its most optimal computing and peripheral configuration, saving <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sim 34$ </tex-math></inline-formula> % energy compared to typical execution.

Natural Convection and Irreversibility of Nanofluid Due to Inclined Magnetohydrodynamics (MHD) Filled in a Cavity with Y-Shape Heated Fin: FEM Computational Configuration

Natural Convection and Irreversibility of Nanofluid Due to Inclined Magnetohydrodynamics (MHD) Filled in a Cavity with Y-Shape Heated Fin: FEM Computational Configuration

Influence of Pyrolysis Gas Composition and Reaction Kinetics on Leaf-Scale Fires

ABSTRACT The impact of pyrolysis gas composition and the underlying reaction kinetics on the burning characteristics of a leaf was computationally investigated. The computational configuration resembled a previous experimental setup where vertically oriented manzanita (Arctostaphylos glandulosa) leaves were burned. Different compositions and reaction kinetics for the pyrolysis gas released during the leaf thermal decomposition were examined. The most detailed composition included , , , and , which was suggested by the previous experimental study of pyrolysis products of different plant species. The least involved compositions only included either or . In all considered compositions, in addition to pyrolysis gas, the release of the heavy gas, i.e. tar, was accounted for. Tar breakdown was represented by a single-step reaction with the light gases above and soot as the products where the stoichiometric coefficients were determined by an optimization technique for consistency with the measurements for the tar molecule. The burning simulation results agreed best with the previous experimental data when a mixture of , , was used. The least agreement was noted when pyrolysis gas was represented by only . Inclusion of tar breakdown reaction appreciably increased the overall heat release due to combustion of its products above the leaf.