Fitness Sharing Chaotic Particle Swarm Optimization (FSCPSO): A Metaheuristic Approach for Allocating Dynamic Virtual Machine (VM) in Fog Computing Architecture

In recent decades,fog computing has played a vital role in executing parallel computational tasks,specifically,scientific workflow tasks.In cloud data centers,fog computing takes more time to run workflow applications.Therefore,it is essential to develop effective models for Virtual Machine(VM)allocation and task scheduling in fog computing environments.Effective task scheduling,VM migration,and allocation,altogether optimize the use of computational resources across different fog nodes.This process ensures that the tasks are executed with minimal energy consumption,which reduces the chances of resource bottlenecks.In this manuscript,the proposed framework comprises two phases:(i)effective task scheduling using a fractional selectivity approach and(ii)VM allocation by proposing an algorithm by the name of Fitness Sharing Chaotic Particle Swarm Optimization(FSCPSO).The proposed FSCPSO algorithm integrates the concepts of chaos theory and fitness sharing that effectively balance both global exploration and local exploitation.This balance enables the use of a wide range of solutions that leads to minimal total cost and makespan,in comparison to other traditional optimization algorithms.The FSCPSO algorithm’s performance is analyzed using six evaluation measures namely,Load Balancing Level(LBL),Average Resource Utilization(ARU),total cost,makespan,energy consumption,and response time.In relation to the conventional optimization algorithms,the FSCPSO algorithm achieves a higher LBL of 39.12%,ARU of 58.15%,a minimal total cost of 1175,and a makespan of 85.87 ms,particularly when evaluated for 50 tasks.

COMPUTATIONALINTELLECTUAL ANALYTICAL THEORYOF COMPUTATIONAL ANALYTICAL APPROACH TOROTATING FLOW OF NON_NEWTONIAN FLUID

A combination of the computational symbolic calculation, mathematical approach and physico-mechanical model lends to a computational intellectual analytical approach developed by the author. There is a principal difference between the computer proof and the computer derivation completed by the computer, also difference between the numerical and symbolic calculations. In this investigation the computational analytical approach is extended, and an unsteady flow of non-Newtonian fluid in the gap between two rotating coaxial cylinders is studied. The Oldroyd fluid B model is used by which the Weissenberg effects are explained in a good comparison with the experiments. The governing equations are reduced to a partial differential equation of 3 rd order for the dimensionless velocity. Using the computer software Macsyma and an improved variational approach the problem with the initial and boundary conditions is then reduced to a problem of an ordinary differential equation for different approximations. The analytical solutions are given for the 1 st, 2 nd and 3 rd approximations. The present investigation shows the ability of the computational symbolic manipulation in solving the problems of non-Newtonian fluid flows. There is a possibility of that to solve the problems in mathematics and mechanics. An important conclusion can be drawn from the results that the transition from a steady state to another steady state is non-unique.

An Effective Non-Commutative Encryption Approach with Optimized Genetic Algorithm for Ensuring Data Protection in Cloud Computing

Nowadays,succeeding safe communication and protection-sensitive data from unauthorized access above public networks are the main worries in cloud servers.Hence,to secure both data and keys ensuring secured data storage and access,our proposed work designs a Novel Quantum Key Distribution(QKD)relying upon a non-commutative encryption framework.It makes use of a Novel Quantum Key Distribution approach,which guarantees high level secured data transmission.Along with this,a shared secret is generated using Diffie Hellman(DH)to certify secured key generation at reduced time complexity.Moreover,a non-commutative approach is used,which effectively allows the users to store and access the encrypted data into the cloud server.Also,to prevent data loss or corruption caused by the insiders in the cloud,Optimized Genetic Algorithm(OGA)is utilized,which effectively recovers the data and retrieve it if the missed data without loss.It is then followed with the decryption process as if requested by the user.Thus our proposed framework ensures authentication and paves way for secure data access,with enhanced performance and reduced complexities experienced with the prior works.

NOVEL SIMPLIFIED APPROACH TO COMPUTE VOLTAGE STABILITY MARGIN

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Dominance-based rough set approach as a paradigm of knowledge discovery and granular computing

Dominance-based rough set approach(DRSA) permits representation and analysis of all phenomena involving monotonicity relationship between some measures or perceptions.DRSA has also some merits within granular computing,as it extends the paradigm of granular computing to ordered data,specifies a syntax and modality of information granules which are appropriate for dealing with ordered data,and enables computing with words and reasoning about ordered data.Granular computing with ordered data is a very general paradigm,because other modalities of information constraints,such as veristic,possibilistic and probabilistic modalities,have also to deal with ordered value sets(with qualifiers relative to grades of truth,possibility and probability),which gives DRSA a large area of applications.

Mixing Analysis in a Stirred Tank Using Computational Fluid Dynamics

In this study computational fluid dynamics (CFD) approach was used to study mixing in an Industrial gold leaching tank. The objective was to analyze the extent of mixing in the tank by producing visual images of the various mixing zones in the tank domain. Eddy viscosity plots that characterise the extent of mixing in the tank were generated in the flow field obtained by an Eulerian-Eulerian approach. The extent of mixing was found to be greatest in the circulation loops of the impeller discharge region and least at the top and bottom portions of the tank. Trailing vortices that contribute to some level of mixing were identified in between the impeller blades. This approach could be used to enhance optimum design of mixing vessels and to eliminate the need for pilot plants.

Computational Optimization of Manufacturing Batch Size and Shipment for an Integrated EPQ Model with Scrap

This paper employs mathematical modeling and algebraic approach to derive the optimal manufacturing batch size and number of shipment for a vendor-buyer integrated economic production quantity (EPQ) model with scrap. Unlike the conventional method by using differential calculus to determine replenishment lot size and optimal number of shipments for such an integrated system, this paper proposes a straightforward algebraic approach to replace the use of calculus on the total cost function for solving the optimal production- shipment policies. A simpler form for computing long-run average cost for such a vendor- buyer integrated EPQ problem is also provided.

Computing Naval Vessel＇s RCS with High-frequency Approach

For the complex and large targets like naval vessels,the computation for their RCS usu- ally uses high-frequency approach.Presenting the geometry modeling and the computation principle on naval vessel's RCS,this paper puts the emphasis on the key techniques of computing the naval vessel's RCS based on high-frequency approach with the analysis on mast's effect to the total RCS as the example.

Computer Assisted Alerts Using Mental Model Approach for Customer Service Improvement

Warning alerts are specially designed to protect user rights and safety to avoid serious damage caused by overlooking the essence of warning alerts. Today’s world of Information Communication Technology (ICT) needs improvement and to review the decisions of security experts in terms of improving warning designs and dialogues, and timely inform the authorities to take quick action at the right time and choice. Human behaviour is deeply involved in most of the security failures and its poor response. If we are able to check and monitor human behaviour in any organisation, we can achieve quality assurance and provide best services to our customers. We have arranged a study in the Center of Post Graduate Studies, International Islamic University, Malaysia (CPS-IIUM), department of Hajj Services-Makkah, and Hospital Management System-Makkah comprised of Observation, Interviews, Questionnaire and discussion based on organizational structure and job activities of people involved in different scenarios and positions under one umbrella of organizational objectives in order to trap the human error in order to take rapid action and response from the management team. Human behaviour is deeply observed and checked while performing different job activities in order to identify the serious errors at the right time during job performance at various levels. We have applied the concept of Brahm’s Language for the simulation of human behaviour which proves an opportunity to simulate human behaviour while performing job activities. Customer service can be improved easily if necessary measures and decisions are taken at the right time and place in any organisation.

基于全变分展开的低剂量CT重建网络

针对CT迭代展开重建网络仅对数据保真项进行神经网络展开降低了重建网络计算性能的问题,通过对基于全变分的CT迭代重建算法进行神经网络展开,提出一种对数据保真项和全变分正则项全部进行神经网络展开的重建网络,从而改善了CT重建图像的视觉质量。首先,采用原始–对偶算法求解基于全变分的CT重建问题,得到易于神经网络展开的迭代重建算法。然后,对该迭代重建算法进行神经网络展开,尤其是对正则项部分的算法进行神经网络展开,得到迭代展开CT重建网络。在模拟的低剂量CT数据集上验证了该算法的有效性。实验结果表明,与6种低剂量CT重建算法相比,该算法在抑制低剂量CT图像噪声的同时,很好地保留了图像中的结构和细节纹理。重建图像的定量评价分析显示,该算法取得了良好的峰值信噪比和归一化均方误差指标值,验证了提出的低剂量CT重建算法具有较好的噪声抑制能力和较强的鲁棒性。

An edge computing-based embedded traffic information processing approach:application of deep learning in existing traffic systems

To address traffic congestion,this study improves Mobile Netv2-you only look once version 4(YOLOv4)target detection algorithm(Mobile Netv2-YOLOv4-K++F)and introduces an embedded traffic information processing solution based on edge computing.We transition models initially designed for large-scale graphics processing units(GPUs)to edge computing devices,maximizing the strengths of both deep learning and edge computing technologies.This approach integrates embedded devices with the current traffic system,eliminating the need for extensive equipment updates.The solution enables real-time traffic flow monitoring and license plate recognition at the edge,synchronizing instantaneously with the cloud,allowing for intelligent adjustments of traffic signals and accident forewarnings,enhancing road utilization,and facilitating traffic flow optimization.Through on-site testing using the RK3399PRO development board and the Mobile Netv2-YOLOv4-K++F object detection algorithm,the upgrade costs of this approach are less than one-tenth of conventional methods.Under favorable weather conditions,the traffic flow detection accuracy reaches as high as 98%,with license plate recognition exceeding 80%.

Thermodynamic model for deoxidation of liquid steel considering strong metal-oxygen interaction in the quasichemical model framework

Herein,a thermodynamic model aimed at describing deoxidation equilibria in liquid steel was developed.The model provides explicit forms of the activity coefficient of solutes in liquid steel,eliminating the need for the minimization of internal Gibbs energy preliminarily when solving deoxidation equilibria.The elimination of internal Gibbs energy minimization is particularly advantageous during the coupling of deoxidation equilibrium calculations with computationally intensive approaches,such as computational fluid dynamics.The model enables efficient calculations through direct embedment of the explicit forms of activity coefficient in the computing code.The proposed thermodynamic model was developed using a quasichemical approach with two key approximations:random mixing of metallic elements(Fe and oxidizing metal) and strong nonrandom pairing of metal and oxygen as nearest neighbors.Through these approximations,the quasichemical approach yielded the activity coefficients of solutes as explicit functions of composition and temperature without requiring the minimization of internal Gibbs energy or the coupling of separate programs.The model was successfully applied in the calculation of deoxidation equilibria of various elements(Al,B,C,Ca,Ce,Cr,La,Mg,Mn,Nb,Si,Ti,V,and Zr).The limitations of the model arising from these assumptions were also discussed.

Conditional selection with CNN augmented transformer for multimodal affective analysis

Attention mechanism has been a successful method for multimodal affective analysis in recent years. Despite the advances, several significant challenges remain in fusing language and its nonverbal context information. One is to generate sparse attention coefficients associated with acoustic and visual modalities, which helps locate critical emotional se-mantics. The other is fusing complementary cross‐modal representation to construct optimal salient feature combinations of multiple modalities. A Conditional Transformer Fusion Network is proposed to handle these problems. Firstly, the authors equip the transformer module with CNN layers to enhance the detection of subtle signal patterns in nonverbal sequences. Secondly, sentiment words are utilised as context conditions to guide the computation of cross‐modal attention. As a result, the located nonverbal fea-tures are not only salient but also complementary to sentiment words directly. Experi-mental results show that the authors’ method achieves state‐of‐the‐art performance on several multimodal affective analysis datasets.

Computational Approaches and Challenges in Spatial Transcriptomics

The development of spatial transcriptomics(ST)technologies has transformed genetic research from a single-cell data level to a two-dimensional spatial coordinate system and facilitated the study of the composition and function of various cell subsets in different environments and organs.The large-scale data generated by these ST technologies,which contain spatial gene expression information,have elicited the need for spatially resolved approaches to meet the requirements of computational and biological data interpretation.These requirements include dealing with the explosive growth of data to determine the cell-level and gene-level expression,correcting the inner batch effect and loss of expression to improve the data quality,conducting efficient interpretation and in-depth knowledge mining both at the single-cell and tissue-wide levels,and conducting multi-omics integration analysis to provide an extensible framework toward the in-depth understanding of biological processes.However,algorithms designed specifically for ST technologies to meet these requirements are still in their infancy.Here,we review computational approaches to these problems in light of corresponding issues and challenges,and present forward-looking insights into algorithm development.

基于改进交替方向乘子法的配电网柔性负荷分层集群调控方法

可调负荷、电动汽车等各种负荷侧资源快速发展,对其进行精准调控是目前重要的研究热点。为充分发挥配电网柔性负荷的调节能力,提出一种基于改进交替方向乘子法的配电网柔性负荷分层集群调控方法。首先,采用综合层次聚类算法对柔性负荷进行分层集群;其次,基于纳什谈判理论,将原问题分解为成本最小化和收益分配2个子问题,建立配电网柔性负荷集群调控模型;然后,引入自适应变参数加速因子,提出改进的交替方向乘子法;最后,通过模拟算例验证所提方法的有效性。结果表明,所提方法能够有效实现大规模柔性负荷接入情况下的集群调控,收敛性能较常规方法有所提高。

新路线方法在全氟和多氟烷基类化合物(PFAS)研究中的应用

随着众多化学品的面世,21世纪以前利用动物实验评估化合物毒性的方法已无法匹配各种化学品的更迭速度。新世纪诞生了很多毒性测试的新路线方法,更好地匹配了新世纪的毒理学研究需求并有效提高测试结果与人类的相关性。本文对部分传统与现代的毒性测试与风险评估手段进行概述,并在此基础上以全氟和多氟烷基类化合物(per-and polyfluoroalkyl substances,PFAS)为例阐述了部分新路线方法的具体使用。最后总结了新路线方法仍需改进之处,以期对之后的毒性测试发展有所帮助。

单侧入路经皮椎体后凸成形术治疗骨质疏松性椎体压缩骨折的术前计算机辅助设计

目的 对于拟行手术单侧入路的经皮椎体后凸成形术(percutaneous kyphoplasty, PKP)的骨质疏松性椎体压缩骨折(osteoporotic vertebral compression fractures, OVCF)患者,基于3D-CT进行术前计算机辅助设计(computer aided design, CAD)穿刺路径,并通过临床实践探究此种术前设计的可行性及有效性。方法 采用回顾性病例对照研究方法,纳入分析了31例患者样本,完成42例椎体手术,手术采用单侧入路PKP。通过3D-CT进行术前CAD,确定皮肤穿刺点、穿刺角度及骨性锚定点,术中在G型臂透视下严格按照术前设计进行操作,记录手术时间、透视次数、对侧补充穿刺次数、骨水泥渗漏率、并发症出现率,比较术前术后视觉模拟评分(visaul anlogue scale, VAS)、Oswestry功能障碍指数(oswestry diablity index, ODI)、椎体高度恢复情况。统计学软件采用SPSS 26.0,计量数据采用均数±标准差表示。结果 (1)手术时间为(26.21±4.19)min,中位数25 min;透视次数为(22.69±6.25)次,中位数21次;对侧补充穿刺数0次;(2)术后3 d、3个月较术前疼痛情况均得到显著改善,VAS评分降低,差值差异有统计学意义(P<0.001),术后3月较术后3 d的VAS评分差异无统计学意义(P>0.05);(3)术后3 d、3个月较术前功能障碍情况均得到显著改善,ODI评分降低,差值差异有统计学意义(P<0.001),术后3月较术后3 d的ODI评分差异无统计学意义(P>0.05);(4)术后3 d、3个月较术前椎体高度比值增加,差值差异有统计学意义(P<0.001),术后3月较术后3 d椎体高度比值降低,差值为0.60,差值存在统计学意义(P<0.001);(5)骨水泥外渗8例,渗漏率为19.0%,无椎体后方渗漏,无症状性渗漏,无其他并发症发生。结论 此种基于3D-CT进行术前CAD的单侧入路PKP方法,穿刺成功率高、操作简单易学、可形成标准化流程。骨性锚定点的引入,可纠正因皮肤延展性导致的移位误差。经临床实践证实,该方法具有可行性及有效性,且不需要使用昂贵的辅助设备,为在基层医院推广提供了可能性,具备实用的临床参考价值。

任务型人机交互系统中的认知技术与发展进路研究

技术变革驱动着人机交互方式的转变。任务型人机交互系统中的人机交互具有多模性,用户可以通过语音、触摸、手势及视觉等多种方式与计算机系统进行交互。其中,命令行和图形等界面的交互使得计算机成为人机沟通的工具。从计算机网络至移动互联,再到元宇宙,人机交互方式不断演变。阐述人机交互的认知技术、演变方式、演变类型和交互体验的优缺点,并展望人机交互的未来前景,以期为了解人机交互提供参考。

“嵌入式智能计算”课程思政的设计与实践

以高校“嵌入式智能计算”课程教学为依托,围绕“实施科教兴国战略,强化现代化建设人才支撑”主题,面向嵌入式智能计算领域人才培养特点和专业能力素质的培养需求,结合课程知识点,提炼思政元素和德育功能。以立德树人为核心,科学合理地设计并融入了思想政治教育内容,同时结合理论课、研讨课、实验课内容给出了具体的实施方案,力图将思想政治内容通过润物无声的方式浸润学生,并同步通过教学感悟提升教师自身品德修养。该教学方式有助于学生树立积极向上的价值观念,成为技术能力与政治品质兼备的社会主义建设者和接班人。