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The transformative impact of modern computational paradigms and technologies, such as high-performance computing (HPC), quantum computing, and cloud computing, has opened up profound new opportunities for scientific simulations. Scalable computational chemistry is one beneficiary of this technological progress. The main focus of this paper is on the performance of various quantum chemical formulations, ranging from low-order methods to high-accuracy approaches, implemented in different computational chemistry packages and libraries, such as NWChem, NWChemEx, Scalable Predictive Methods for Excitations and Correlated Phenomena, ExaChem, and Fermi–Löwdin orbital self-interaction correction on Azure Quantum Elements, Microsoft's cloud services platform for scientific discovery. We pay particular attention to the intricate workflows for performing complex chemistry simulations, associated data curation, and mechanisms for accuracy assessment, which is demonstrated with the Arrows automated workflow for high throughput simulations. Finally, we provide a perspective on the role of cloud computing in supporting the mission of leadership computational facilities. [ABSTRACT FROM AUTHOR]

Cybersecurity is a present and growing concern that needs to be addressed with both behavioral and design-oriented research. Public cloud providers such as Amazon Web Services and federal funding agencies such as the National Science Foundation have invested billions of dollars into developing high-performance computing resources accessible to users through configurable virtual machine (VM) images. This approach offers users the flexibility of changing and updating their environment for their computational needs. Despite the substantial benefits, users often introduce thousands of vulnerabilities by installing open-source software packages and misconfiguring file systems. Given the scale of vulnerabilities, security personnel struggle to identify and prioritize vulnerable assets for remediation. In this research, we designed a novel unsupervised deep learning-based Multi-View Combinatorial-Attentive Autoencoder (MV-CAAE) to capture multi-dimensional vulnerability data and automatically identify groups of similar vulnerable compute instances to help facilitate the development of targeted remediation strategies. We rigorously evaluated the proposed MV-CAAE against state-of-the-art methods in three technical clustering experiments. Experiment results indicate that the MV-CAAE achieves V-measure scores (metric of cluster quality) 8 percent-48 percent higher than benchmark methods. We demonstrated the practical value through a comprehensive case study by clustering vulnerable VMs and gathering qualitative feedback from experienced security professionals through semi-structured interviews. The results indicated that clustering vulnerable assets can help prioritize vulnerable instances for remediation and enhance decision-making tasks. The present design-research work also contributes to our theoretical knowledge of cyber-defense. [ABSTRACT FROM AUTHOR]

Electronic structure theory, i.e., quantum chemistry, is the fundamental building block for many problems in computational chemistry. We present a new distributed computing framework (BigChem), which allows for an efficient solution of many quantum chemistry problems in parallel. BigChem is designed to be easily composable and leverages industry-standard middleware (e.g., Celery, RabbitMQ, and Redis) for distributed approaches to large scale problems. BigChem can harness any collection of worker nodes, including ones on cloud providers (such as AWS or Azure), local clusters, or supercomputer centers (and any mixture of these). BigChem builds upon MolSSI packages, such as QCEngine to standardize the operation of numerous computational chemistry programs, demonstrated here with Psi4, xtb, geomeTRIC, and TeraChem. BigChem delivers full utilization of compute resources at scale, offers a programable canvas for designing sophisticated quantum chemistry workflows, and is fault tolerant to node failures and network disruptions. We demonstrate linear scalability of BigChem running computational chemistry workloads on up to 125 GPUs. Finally, we present ChemCloud, a web API to BigChem and successor to TeraChem Cloud. ChemCloud delivers scalable and secure access to BigChem over the Internet. [ABSTRACT FROM AUTHOR]

The dual-scrambling scheme that combines position transformation and bit-plane transformation is a popular image encryption scheme. However, such schemes need more key information, and the encryption and decryption processes are complicated. In addition, the existing quantum image dual-scrambling schemes mainly deal with square images. In this paper, we propose a hybrid scrambling encryption scheme for multi-mode quantum image representation (MQIR) images based on random permutation, in which the H × W quantum image is represented in MQIR. A random number generator factor s uniquely associates one of the random permutations of integers from 1 to a positive integer, so as to hybrid scramble both the pixel position and the binarized position of each pixel value. Meanwhile, the quantum circuits and some examples of scrambling are given. Furthermore, various analyses of the performance of this scheme were conducted, including effectiveness, key space, and computational complexity. By modifying the random generation factor to construct multiple binary grayscale images, the simulated results on the IBM Quantum Cloud platform demonstrate that the proposed quantum image encryption scheme is effective. In comparison to existing quantum image dual scrambling schemes, it is both simple and effective, offering a large key space, lower computational complexity, and applicability to non-square quantum images. [ABSTRACT FROM AUTHOR]

This research examines how a firm's cloud storage implementation affects different types of security breaches in both the short- and long-term. Building on the attention-based view, we find that cloud storage implementation positively relates to a firm's external breaches and accidental internal breaches in the short-term. However, the positive relationship between cloud storage implementation and external breaches diminishes over time and becomes insignificant long-term. Our results demonstrate a long-term security advantage of cloud storage in reducing accidental internal breaches. We did not find a significant association between cloud storage and malicious internal breaches. Findings highlight the need for firms to direct limited resources to different security risks in the short- and long-term of cloud storage implementation over time. This research contributes to our understanding of cloud storage's security implications and explicitly theorizes the role of attention in firm IT security management. We contribute to the attention-based view by contextualizing the theory to IT security. We highlight temporal dynamics through distinct attentional mechanisms, including selective attention, attentional flexibility, and attentional vigilance. [ABSTRACT FROM AUTHOR]

Cloud computing is widely applied in modern industrial areas due to its technological advancement, cost reduction, and applicability. Packets (tasks) belonging to different applications (agents) compete to share the common cloud resource through a series of edge nodes (processors) in pursuit of fast transmission. This paper abstracts the cloud computing system as a multi-agent flow-shop scheduling (MAFS) problem. The objective is to minimise the total completion time of several agents with the restriction that the maximum lateness cannot exceed a given bound. Given the complexity of the considered problem, a branch and bound algorithm combined with several pruning rules and lower bounds is proposed to obtain optimal solutions. Furthermore, the considered problem is generalised to a bi-scenario version, and a bi-population cooperative co-evolutionary (BCCE) algorithm is proposed to solve it. A reinforcement learning-based method is presented to generate the initial population. Several problem-specific intensification strategies are constructed to explore promising solutions. Comprehensive experiments verified the effectiveness of the proposed algorithms. The industrial data from the China Earthquake Network Centre further confirmed the superiority of the BCCE algorithm. Overall, the MAFS model and the proposed algorithms effectively enhance the user experience and reasonably guarantee revenue. [ABSTRACT FROM AUTHOR]

Organisations are having difficulty in determining and integrating Industry 4.0 technologies (I4.0T) to improve social dimensions of sustainable performance. We address this issue by showing how to identify the impact degree and path of I4.0T using the United Nations sustainable development goals (SDGs). First, we identify the SDGs associated with I4.0 and establish an evaluation framework. Second, we introduce an evaluation method that integrates hesitant fuzzy sets, rough sets, decision-making, trial evaluation laboratory (DEMATEL) and interpretative structural modelling methods to identify the impact degree and path of I4.0T on SDGs. Third, we confirm the effectiveness of our framework and method using secondary case data from World Economic Forum reports. The case results show that I4.0T have varying direct and indirect influences on SDGs. Policy makers should consider that 'Big Data and Analytics' and 'Cloud Computing' are central I4.0T that link other technologies and SDGs. The prioritisation of I4.0T can lead to contributions to addressing 'Responsible consumption and production' and indirectly improve SDGs. The findings set an initial stage to help sequence investment in various technologies depending on SDGs. We identify sequential paths that can aid in planning for and investing in adopting I4.0T to better achieve SDGs. [ABSTRACT FROM AUTHOR]

Along with a number of other computing technologies, cloud computing services are increasingly being promoted as a way of enabling openness, reproducibility, and the acceleration of scientific work. While there have been a variety of studies of the cloud in terms of computing performance, there has been little empirical attention to the changes going on around cloud computing at the level of work and practice. Through a qualitative, ethnographic study, we follow a cosmology research group’s transition from a shared high performance computing cluster to a cloud computing service, and examine the cloud service as a coordinative artifact being integrated into a larger ecology of existing practices and artifacts. We find that the transition involves both change and continuity in the group’s coordinative work and maintenance work, and point out some of the effects this adoption has on the group’s larger set of practices. Finally, we discuss practical implications this has for the broader adoption of cloud computing in university-based scientific work.

The paper deals with the problem of distinguishing Internet law from Information Law and IT Law, establishing its place among other branches of law, reveals the main criteria for legal regulation of IT Law and fixing the basic principles of its functioning. Attention is focused on the fact that IT and the Internet network are interrelated, since the latter is the habitat of the former, and at the same time, the latter does not make any sense without tools with which any information can be processed. Thus, when considering the definitions of „information", „іnformation technologies" and „Internet network" in the context of the digital space, it was determined that they are interrelated - information is the main element, information technologies are used to work with information (for collecting, storing, processing), and the Internet network is used for transmitting and exchanging data. Such a conclusion can provide a complete picture of how and in accordance with what hierarchy these concepts should be displayed from the point of view of Information Law, IT Law and Internet Law. It was found that Information Law is essentially a broader concept than IT Law and undoubtedly includes it, however, given the specifics of the environment in which the relevant legal relations arise and the subject performing various operations with information, it would be more expedient to separate it into a separate institution of the former. This division is due in particular to the emergence of new areas of development, such as the institute of artificial intelligence, the institute of cloud technologies, the institute of digital signature and the globalization of the Internet network. Thus, Information Law and IT Law regulate a homogeneous range of public relations and are essentially related as an industry and an institution, but they have certain differences that are due to the environment of the emergence of regulatory relations. In turn, Internet Law is a separate branch of law that should regulate public relations that arise in the appropriate environment and consolidate fundamental digital rights and obligations, based on an international character. [ABSTRACT FROM AUTHOR]

Summary: Cloud computing is commonly utilized in remote contexts to handle user demands for resources and services. Each assignment has unique processing needs that are determined by the time it takes to complete. However, if load balancing is not properly managed, the effectiveness of resources may suffer dramatically. Consequently, cloud service providers have to emphasize rapid and precise load balancing as well as proper resource supply. This paper proposes a novel enhanced deep network‐based load predictor and load balancing in cloud‐fog services. In prior, the workload is predicted using a deep network called Multiple Layers Assisted in LSTM (MLA‐LSTM) model that considers the capacity of virtual machine (VM) and task as input and predicts the target label as underload, overload and equally balanced. According to this prediction, the optimal load balancing is performed through a hybrid optimization named Osprey Assisted Pelican Optimization Algorithm (OAPOA) while taking into account several parameters such as makespan, execution cost, resource consumption, and server load. Additionally, a process known as load migration is carried out, in which machines with overload tasks are assigned to machines with underload tasks. This migration is applied optimally via the OAPOA strategy under the consideration of constraints including migration cost and migration efficiency. [ABSTRACT FROM AUTHOR]

With ongoing advancements in financial technology, digital finance has experienced rapid development in China, leveraging big data, cloud computing, and social platforms. Service consumption plays a crucial role as an indicator of households' ability to achieve consumption upgrades and overall happiness. Internet financing and payment represent two primary types of digital finance. This article aims to assess their impacts on household service consumption. Both types of digital finance have a significant potential to increase household service consumption, which is categorized into seven distinct categories in this article. Digital finance demonstrates a notable ability to enhance consumption in various categories, including daily services, transportation and communication, healthcare, education, entertainment, and tourism. However, it has no significant impact on medical consumption. Finally, the empirical results reveal that digital finance exhibits heterogeneous effects on the service consumption of households with different characteristics. [ABSTRACT FROM AUTHOR]

This study explored the adoption of cloud computing in selected academic libraries. A survey research design was used for the study. A sample size of 152 was randomly selected from 250 academic librarians and library officers for the study. A questionnaire was used as the instrument of data collection. The data collected were analyzed using descriptive statistics (frequency count, percentage, mean, and standard deviation). The study found that library personnel are aware of cloud computing technology which could enhance effective implementation of the technology in the libraries in Lagos and Ogun States. Furthermore, cloud computing technology was adopted for the purpose of collaboration among staff and users, accessibility, storage digital resources etc. The study revealed a significant number of challenges to adopting cloud computing, such as lack of financial resources, concern for data security, lack of in-house experts, and, most importantly, staff resistance to change. The study recommended that library management address the lack of in-house experts and improve internet connectivity to ensure effective implementation of cloud computing technology. [ABSTRACT FROM AUTHOR]