Mainframe Computer Research Articles

Streamline-based reactive transport modeling of uranium mining during in-situ leaching: Advantages and drawbacks

Reactive transport modeling is known to be computationally intensive when applied to 3D problems. Transforming sequential computing on the computer processor units (CPU) into parallelized computation on the high-performance parallel graphic processor units (GPU) is a classical approach to increasing computational performance. Another complementary approach is to decompose a complex 3D modeling problem into a set of simpler 1D problems using streamline approaches which can be easily parallelized, therefore reducing computation time. This paper investigates solutions to the equations governing dissolution and transport using streamlines coupled with a parallelization approach. In addition, an analytical solution to the dissolution and transfer equations of uranium describing the In-Situ Leaching (ISL) mining recovery is found using an approximation series to the 2nd order. The analytical solution is compared to the 1D numerical resolution along the streamlines and to the 3D simulation results superimposed on the streamline. Both approaches give similar results with a relative error of <2 % (2%). The proposed methodology is then applied to a case study in which the classical 3D resolution is compared to the newly suggested streamline solution, demonstrating that the streamline approach increases computational performances by a factor ranging from hundred to thousand depending on the complexity of the grid-block model.

CDMetaPOP 2: a multispecies, eco‐evolutionary simulation framework for landscape demogenetics and connectivity

Multispecies approaches to questions in ecology and evolution are at the forefront of many fields spanning both theoretical and applied research. In conservation and landscape genetics, simulation models offer a powerful means to evaluate complex questions, yet most models lack the ability to consider landscape effects on multiple species or to simulate the complex interactions that occur among species and drive eco‐evolutionary processes. Tools are needed that provide a mechanistic framework to explore multiple and simultaneous interspecific interactions and their effects on demogenetic processes for each species. We present a generalized, multispecies version of Cost‐Distance Meta‐Population (CDMetaPOP) that simulates changes in neutral and selection‐driven genotypes across space and time as a function of individual‐based movement, spatial population dynamics, and multiple and dynamic landscape drivers. The number of species in a given simulation is limited only by the number of computer processors available. In addition to simulating multiple species, we use Lotka–Volterra theory to implement interspecific interactions via competition. We validate the competition model and present a real‐world example to demonstrate the potential role of species interactions in landscape connectivity and gene flow. While the example uses fish as the model species, CDMetaPOP ver. 2 is flexible enough to simulate species that span the breadth of the tree of life. The simulation framework presented here provides a novel approach to addressing questions concerning the spatial ecology, evolution, and conservation of diverse taxa, from individual species to whole communities.

Framework of Interaction Design Method Based on Blockchain System

&lt;p&gt;As the fifth subversive and innovative technology for computing paradigm after the mainframe computer, personal computer, internet and mobile/social network, blockchain technology has entered into a new phase of development. Nevertheless, more intrinsic issues remain to be explored. With the usage of cryptography and a distributed database, once a block is recorded, it can no longer be changed. To defeat these issues, more existing techniques have emerged. The blockchain system mainly features decentralization, but as the existing architectures of the blockchain system are mixed up, it is hard to determine whether they are centralized or decentralized. Such hybrid feature is derived from the impact of uncertainty of human demands. In this study, we intend to explore the scientific perception of the blockchain technology after its integration with human activities by adopting the method of interaction design. Furthermore, we plan to establish a set of mechanisms on the method of blockchain system-based interaction design, so as to identify the impact of human uncertainty factors on the design of the blockchain system. In addition, we aim to provide theoretical guidance for establishing the decentralized blockchain systems in both standardized and mixed categories and the centralized blockchain system with decentralization as central node. Through the methods of the observational results, the article is summarized and assessed the methods of the interaction design based on blockchain system. Moreover, the evaluation process consists of the analysis of expert evaluation, practical evaluation and participatory evaluation ferments an efficient outcome.&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;

Agricultural Autonomous Robotic Platform Motion Control

A model of the movement of a robotic platform adapted to the conditions of an industrial orchard is proposed. (Research purpose) Development of a motion control system for an autonomous robotic wheeled platform based on inertial and satellite navigation and traversed path calculation, which will allow it to move in an apple orchard and automatically perform various technological operations, such as fertilization, growth diseases control of, fruit harvesting. (Materials and methods) A mathematical model was developed to control the movement of a robotic platform, taking into account the turning radii of three types, the length of the arc of the performed circle, the speed of movement in the garden plantation rows using a garden electronic map. The method used allows implementing a program for the robotic platform automatic movement around a typical orchard using a minimum set of sensors, significantly reducing the load on the onboard computer processor and memory. Software, developed in the Python programming language, enables plotting the robotic platform route, displaying the movement trajectory, and indicating the positioning accuracy at each point in relation to the trees in the garden plantation rows, the movement speed and the wheel rotation angle. (Results and discussion) The robotic platform managed to autonomously pass the preset routes, while the interaction of the software and the robotic platform hardware was provided. A field testing of the developed software was performed. (Conclusions) The specified accuracy of the robotic platform positioning was confirmed for the 3.5-meter aisles of intensive orchards. The maximum deviation from the task map using satellite and inertial navigation system was 164 millimeters, which complies with the agrotechnical requirements for mechanized fruit harvesting.

An X-ray Microscopy Study of the Microstructural Effects on Thermal Conductivity in Cast Aluminum-Copper Compounds

A metallurgical joint between aluminum and copper established by compound casting provides for high thermal conductivity, which is required for lightweight cooling solutions in applications such as high-power light-emitting diodes or computer processors. If casting is employed in a silane-doped inert gas atmosphere whose oxygen partial pressure is adequate to extreme high vacuum, reoxidation of the active surfaces of aluminum and copper is prevented, and thus a metallurgical bond can be created directly between aluminum and copper. With this approach, thermal conductivities as high as 88.3 W/m·K were realized. In addition, X-ray microscopy was used to shed light on the microstructure–thermal property relationship. It is demonstrated that both porosity and non-bonded areas have a substantial impact on the thermophysical properties of the compound zone. Based on the data obtained, casting parameters can be developed that provide for defect-free bonding zones and optimal heat transfer between the joining partners.

Covalent framework derived internal-doped porous carbon supported SnO2 composite: Construction of a 10 V asymmetric supercapacitor and selective electrochemical determination of N-(4-Hydroxyphenyl) acetamide

A hydrothermal technique was used to make tin oxide (SnO2) hetero-atom doped porous carbon (HPC) composite electrode material for an asymmetric supercapacitor and N-(4-Hydroxyphenyl) acetamide (4-HPA) sensor. As regards the electrochemical capacitor, the SnO2 @HPC composite exhibited a capacity of 268 C g−1 in an aqueous electrolyte (1.0 M H2SO4) at a current density of 2.0 A g−1 in a three-electrode setup. Over 5,000 consecutive cycles at 6.0 A g−1, the electrode maintained 92.3% of its original capacity, suggesting good cyclic stability. In addition, we constructed a 10 V asymmetric supercapacitor (SnO2 @HPC (10%)/AC) and used it to operate light emitting diodes for 10 min and run a computer central processing unit fan for 40 s after being charged for 68 s at 10 V. The SnO2 @HPC composite electrode detected (4-HPA) linearly from 0.5 to 1000 µM with a LOD of 0.005 µM and exhibited significant stability, reproducibility, and selectivity for (4-HPA). Thus, the synthesized electrode material demonstrated outstanding capacity and excellent sensing for (4-HPA).

Efficiency of the Use of Computer Memories and Execution Time in Structural Analysis

The use of computer programming provides accurate and speedy analyses of structural systems. The accuracy&lt;br /&gt;and the speed of the analysis are due to the novelty of the computer, i.e., the speed in storing and retrieving large size&lt;br /&gt;of data, and the speed and the accuracy in the numerical computation. However, in old days, due to the limited&lt;br /&gt;storage capacities of old generations of the computers, and the use of limited main frame computers, used by so&lt;br /&gt;many parties, the efficient use of computer memory became an important issue. Moreover, the use of rented base of&lt;br /&gt;computer time necessitated the efficient use of computer run time. The paper discusses the efforts to efficiently use&lt;br /&gt;the computer memory and computer run times. These issues seem to remain important issues, even though to date,&lt;br /&gt;the tendency is to use of personal computers and laptops instead the use of rented main frame computers.

Quantum Volume for Photonic Quantum Processors.

Defining metrics for near-term quantum computing processors has been an integral part of the quantum hardware research and development efforts. Such quantitative characteristics are not only useful for reporting the progress and comparing different quantum platforms but also essential for identifying the bottlenecks and designing a technology road map. Most metrics such as randomized benchmarking and quantum volume were originally introduced for circuit-based quantum computers and were not immediately applicable to measurement-based quantum computing (MBQC) processors such as in photonic devices. In this Letter, we close this long-standing gap by presenting a framework to map physical noises and imperfections in MBQC processes to logical errors in equivalent quantum circuits, whereby enabling the well-known metrics to characterize MBQC. To showcase our framework, we study a continuous-variable cluster state based on the Gottesman-Kitaev-Preskill (GKP) encoding as a near-term candidate for photonic quantum computing, and derive the effective logical gate error channels and calculate the quantum volume in terms of the GKP squeezing and photon transmission rate.

Will Artificial Intelligence be Useful (or Misused) in Environmental Toxicology and Chemistry?

No This article is protected by copyright. All rights reserved. Environ Toxicol Chem 2023;00:0-0. © 2023 SETAC.

ID Asks/Kenneth Werner

ID Asks/Kenneth Werner

Thermo-hydraulic investigation of open micro prism pin fin heat sink having varying prism sides

The current trend of miniaturization in many electronic devices, like computer processors, high-speed servers, MEMS devices, etc., has shown augmented performance. Still, thermal management is a significant concern for them. The present work performed a numerical analysis on the microchannel heat sink's open micro prism pin fin configuration (MCHS). The influence of prism pin fin sides (3 to 9) has been studied for copper substrate and working fluid water (single phase fluid flow). Finite volume-based commercial code has been opted to perform the numerical simulations. The present configurations simulated different Reynolds numbers (50–300) under the heat flux of 500 kW/m2. Observation revealed that the four-side arrangements have the best performance due to prominent secondary flow leading to efficient fluid mixing, whereas three-side configurations have the worst performance. Further, an increase in pin fin sides from 5 to 9 has almost negligible variation in thermal and hydraulic characteristics because of similar fluid flow characteristics. The four-side micro prism pin fin configuration has been further analysed by varying the prism radius from 0.175 mm to 0.325 mm. It was observed that a prism radius between 0.250 mm and 0.275 mm led to optimum overall performance due to more stable secondary fluid flow.

Large Scale Data Using K-Means

Because of the exponential growth of high-layered datasets, conventional database querying strategies are inadequate for extracting useful information, and analysts must now devise novel techniques to meet these demands. Such massive articulation data results in a plethora of new computational triggers as a result of both the rise in data protests and the increase of elements/ascribes. Preprocessing the data with a reliable dimensionality reduction method improves the efficacy and precision of mining operations on densely layered data. Therefore, we have compiled the opinions of numerous academics. Cluster analysis is a data analysis tool that has recently acquired prominence in a number of different disciplines. K-means, a common parceling-based clustering algorithm, looks for a fixed number of clusters that can be identified using only their centroids. However, the outcomes depend heavily on the starting points of the clusters' focuses. Again, there is a dramatic rise in the number of distance calculations with increasing data complexity. This is due to the fact that assembling a detailed model typically calls for a substantial and distributed amount of preliminary data. There may be a substantial time commitment involved in preparing a broad collection of ingredients. For huge data sets in particular, there is a cost/benefit analysis to consider when deciding how to create orders: speed vs. accuracy. The k-means method is commonly used to compress and sum vector data, as well as cluster it. For precautious k-means (ASB K-means), we present No Concurrent Specific Clumped K-means, a fast and memory-effective GPU-based method. Our method can be adjusted to use much less GPU RAM than the size of the full dataset, which is a significant improvement over earlier GPU-based k-means methods. Datasets that are too large to fit in RAM may be clustered. The approach uses a clustered architecture and applies the triangle disparity in each k-means focus to remove a data point if its enrollment task or cluster it belongs to remains unaltered, allowing it to efficiently handle big datasets. This reduces the number of data guides that must be transferred between the CPU's Slam and the GPU's global memory.

Model predictive control of legged and humanoid robots: models and algorithms

ABSTRACT Model predictive control (MPC) of legged and humanoid robotic systems has been an active research topic in the past decade. While MPC for robotic systems has a long history, its paradigm such as problem formulations and algorithms has changed along with the recent drastic progress in robot hardware, computational processors, and algorithms. This survey paper reviews recent progress on MPC for legged and humanoid robotics from the following three points of view. First, we review a variety of dynamical models of robotic systems used in the MPC formulation. Second, we give an overview of MPC algorithms, particularly focusing on suitable ones for robotic problems. Finally, we introduce methods and applications of MPC for practical robotic problems from MPC based on reduced-order models to recent progress on MPC based on whole-body models.

Comparison of Processors for Real-time Homography Computation

Comparison of Processors for Real-time Homography Computation

Design and Mode Matching Analysis of Stepped Substrate Integrated Waveguide and Filters

This paper presents a stepped substrate integrated waveguide. The generalized scattering properties of the cascaded H -plane discontinuity in a substrate integrated waveguide operating in various frequency bands are obtained using mode-matching techniques (MMT) from the respective field equations at four different step discontinuities. The scattering parameters ( S ) obtained from the individual regions are cascaded to obtain the S -parameters of the overall structure. The processor computation time and memory used by MMT are compared to those of commercial simulators like high-frequency structure simulator (HFSS) and computer simulation technology microwave studio (CST-MWS), and the S-parameters obtained using MMT are compared with HFSS and CST-MWS simulated and measured S-parameters. Due to periodicity in the designed structure, a filter-like property has been observed. The S -parameters generated from mathematical formulations, simulations, and measurements show very good agreement.

A Sub-mW Cortex-M4 Microcontroller Design for IoT Software-Defined Radios

We present an Internet-of-Things (IoT) software-defined radio platform based on an ultra low-power microcontroller. Whereas conventional wireless IoT radios often implement a single protocol, we demonstrate that general-purpose microcontrollers running software implementations of wireless physical layers are a promising solution to increase interoperability of IoT devices. Yet, since IoT devices are often energy-constrained, the underlying challenge is to implement the digital signal processing of the radio in software while maintaining an overall very low power consumption. To overcome this problem, we propose an ultra low-power microcontroller architecture with an ARM Cortex-M4 processor for the protocol-specific computations and a hardware digital front-end for the generic signal processing. The proposed architecture has been prototyped in 28nm FDSOI and the physical layers of the well-known LoRa and Sigfox protocols have been implemented in software. Thanks to the efficient hardware/software partitioning and an ultra-low power digital implementation, experimental evaluations of the microcontroller prototype show sub-mW power consumptions (32 – 332 μW) for the digital signal processing of the software-defined radios.

Research on terrain grids generation in computational fluid dynamics software

Traditional research of environmental impact of natural draft cooling tower in nuclear power plant is based on diffusion model or tunnel experiment, and with the development of modern mainframe computers and turbulence models, it is possible to use CFD method to simulate plume drift. The CFD software, due to its powerful computing ability, can simulate and display the plume drift more accurately. This paper presents an effective way of generating terrain grids which can be used in StarCD, a CFD software. The SRTM terrain data is obtained from internet and IDW interpolation method is used in the co-ordinates translation process. A powerful program named GridInter is developed using Fortran90 to convert terrain data to StarCD vertex file, terrain grids generation process in StarCD including nuclear power plant building grids combination is also introduced, this model can be directly used in the numerical simulation of plume dispersion.

Utilizing a Neutrosophic Fuzzy Logic System with ANN for Short-Term Estimation of Solar Energy

One of the primary sources of renewable energy in the coming years is thought to be solar energy. Solar energy and other renewable energy sources do, moreover, have a disadvantage in that it is hard to forecast when they will be available. The best use of solar energy is impacted by this issue, particularly when it is combined with other sources. As a result, the organization and economy of solar energy depend on accurate solar energy forecasting techniques. Predicting solar energy shortly is the study’s major goal. This paper describes the study of Neutrosophic fuzzy logic with artificial neural networks (NFL-ANN) to anticipate solar photovoltaic (PV) plant output power with the use of specified input factors known as meteorological information, such as sunshine length, humidity levels, temperature, air pressure, and others, artificial neural networks are used to forecast the outcome. NFL represents a generalised logic, which can manage stochasticity learning mistakes and unpredictability that fuzzy logic lacks. It offers the results of the calculation section. Excellent performance computer processors and NFL provide reasonable accuracy estimates of solar plant outputs as well as system reliability to consider environmental factors. The investigation was carried out with the use of MATLAB programming. With the assistance of statistical markers like mean absolute percentage error (MAPE), mean absolute error (MAE), root means square error (RMSE), and determinant coefficient, the suggested NFL-ANN approach is evaluated and compared to other approaches that are already in use. In comparison to existing techniques, the suggested NFL-ANN provides superior accuracy and lesser prediction error, according to the study’s findings. This research will be enhanced to forecast power without any loss.

Dimensional Reduction of Underwater Shrimp Digital Image Using the Principal Component Analysis Algorithm

Shrimps are aquaculture products highly needed by the people and this is the reason their growth needs to be monitored using underwater digital images. However, the large dimensions of the shrimp digital images usually make the processing difficult. Therefore, this research focuses on reducing the dimensions of underwater shrimp digital images without reducing their information through the application of the Principal Component Analysis (PCA) algorithm. This was achieved using 4 digital shrimp images extracted from video data with the number of columns 398 for each image. The results showed that 12 PCs were produced and this means the reduced digital images with new dimensions have 12 variable columns with data diversity distributed based on a total variance of 95.61%. Moreover, the original and reduced digital images were compared and the lowest value of MSE produced was 94.12, the minimum value of RMSE was 9.54, and the highest value of PSNR was 8.06 db, and they were obtained in the 4th digital image. The experiment was conducted using 3 devices which include I3, I7, and Google Colab processor computers and the fastest computational result was produced at 2.1 seconds by the Google Colab processor. This means the PCA algorithm is good for the reduction of digital image dimensions as indicated by the production of 12 PC as the new variable dimensions for the reduced underwater image of shrimps.

Game Online: Ancaman ‘Candu Digital’

The internet as a product of the development of information technology, brings major changes in human life. The internet provides convenience to various aspects of life, ranging from information, education, economy and business, to entertainment. Entertainment provided through internet services also varies, ranging from reading books, video shows, movies and dramas, to online games. Development development is a process to develop a new product or improve an existing product, which can be accounted for. The game that was first created by Steve Russell and his friends was named Spacewar. This game was created using a mainframe computer named MIT PDP-1 in 1961. As for the Playstation (PS), it only appeared in 2000. Until now PS is still often used, but along with technological developments, online games are increasingly in demand and popular in Indonesian society. Online games as a product derived from the internet have brought major changes to the entertainment trend of the current generation. As interactive entertainment, online games are able to attract many internet users to enjoy them as a means of entertainment. Unfortunately, many online game users are complacent to the end of addiction.