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"Cloud computing Social aspects."
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Becoming Digital
This book examines the convergence of Cloud Computing, Big Data, and the Internet of Things to forge the Next Internet. Ubiquitous computing enables universal communication, concentration of power, privacy erosion, environmental degradation, and massive automation and this title explores solving these issues to create a democratic digital world.
eBook
Genomics: data sharing needs an international code of conduct
Efforts to protect people’s privacy in a massive international cancer project offer lessons for data sharing.
Efforts to protect people’s privacy in a massive international cancer project offer lessons for data sharing.
Coloured scanning electron micrograph of a migrating breast cancer cell
Journal Article
Pan-cancer analysis of whole genomes
Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale
1
–
3
. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4–5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the
TERT
promoter
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; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation
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,
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; analyses timings and patterns of tumour evolution
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; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity
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,
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; and evaluates a range of more-specialized features of cancer genomes
8
,
10
–
18
.
The flagship paper of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium describes the generation of the integrative analyses of 2,658 cancer whole genomes and their matching normal tissues across 38 tumour types, the structures for international data sharing and standardized analyses, and the main scientific findings from across the consortium studies.
Journal Article
Connected and Automated Vehicles: Infrastructure, Applications, Security, Critical Challenges, and Future Aspects
Autonomous vehicles (AV) are game-changing innovations that promise a safer, more convenient, and environmentally friendly mode of transportation than traditional vehicles. Therefore, understanding AV technologies and their impact on society is critical as we continue this revolutionary journey. Generally, there needs to be a detailed study available to assist a researcher in understanding AV and its challenges. This research presents a comprehensive survey encompassing various aspects of AVs, such as public adoption, driverless city planning, traffic management, environmental impact, public health, social implications, international standards, safety, and security. Furthermore, it presents emerging technologies such as artificial intelligence (AI), integration of cloud computing, and solar power usage in automated vehicles. It also presents forensics approaches, tools used, standards involved, and challenges associated with conducting digital forensics in the context of autonomous vehicles. Moreover, this research provides an overview of cyber attacks affecting autonomous vehicles, attack management, traditional security devices, threat modeling, authentication schemes, over-the-air updates, zero-trust architectures, data privacy, and the corresponding defensive strategies to mitigate such risks. It also presents international standards, guidelines, and best practices for AVs. Finally, it outlines the future directions of AVs and the challenges that must be addressed to achieve widespread adoption.
Journal Article
Efficient GPT-4V level multimodal large language model for deployment on edge devices
Multimodal large language models have revolutionized AI research and industry, paving the way toward the next milestone. However, their large sizes and high computational costs restrict deployment to cloud servers, limiting use in mobile, offline, energy-sensitive, or privacy-critical scenarios. We present MiniCPM-V, efficient models for edge devices that integrate advancements in architecture, training, and data. The 8B model outperforms GPT-4V, Gemini Pro, and Claude 3 across 11 public benchmarks, processes high-resolution images at any aspect ratio, achieves robust optical character recognition, exhibits low hallucination rates, and supports over 30 languages while running efficiently on mobile phones. This progress reflects a broader trend: The sizes for high-performing models are rapidly decreasing alongside growing edge computation capacity, enabling advanced multimodal models to operate locally on consumer hardware. Such developments unlock applications across diverse real-world scenarios, from enhanced mobile AI to privacy-preserving solutions, marking a critical step toward democratizing powerful multimodal intelligence.
Multimodal Large Language Models are energy intensive and computationally demanding. Here, the authors developed a series of lightweight Multimodal Large Language Models deployable on edge devices.
Journal Article
Towards better understanding of determinants logistical factors in SMEs for cloud ERP adoption in developing economies
Purpose
The purpose of this paper is to investigate the main determinants logistical factors that have an impact on the adoption of cloud enterprise resource planning (ERP) among small- and medium-sized enterprises (SMEs) in developing economies. By adopting the diffusion of innovation, technological, organizational and environmental model as a theoretical framework, the 14 factors examined in this study are as follows: relative advantage (RA), compatibility, complexity, value creation, technology readiness (TR), security concerns, technical barriers, top management support (TMS), enterprise readiness (ER), enterprise size (ES), enterprise status, competitive advantage, government support and infrastructure/telecommunication.
Design/methodology/approach
Data were collected from 131 respondents’ senior executives and IT managers in SMEs in developing economies (Jordan, Lebanon, King Saudi Arabia, Bahrain, Qatar, Emirates, Egypt, Oman, Kuwait and Turkey). A web-based survey questionnaire was used for data collection process. The research framework and the derived hypotheses were tested by logistic regression analysis.
Findings
The findings indicate that compatibility, TR, technical barriers, TMS, ER, ES and competitive pressure have a significant effect on the adoption of cloud ERP. This conclusion can be utilized in enhancing the strategies for approaching ERP cloud by pinpointing the reasons why some SMEs choose to adopt this technology, while others still do not go forward with this.
Originality/value
This study provides an overview and empirically shows the main determinants logistical factors that might face SMEs in the developing economies. The findings also help SMEs consider their information technologies investments when they think to adopt cloud ERP.
Journal Article
Digital Transformation and Innovation: The Influence of Digital Technologies on Turnover from Innovation Activities and Types of Innovation
In today’s competitive and globalized world, innovation is essential for organizational survival, offering a means for companies to address environmental impacts and social challenges. As innovation processes accelerate, managers need to rethink the entire value-creation chain, with digital transformation emerging as a continuous process of organizational adaptation to the evolving societal landscape. The research question focuses on how digital technologies—such as artificial intelligence, Big Data, cloud computing, industrial and service robots, and the Internet of Things—influence innovation-driven revenues among enterprises within the European Union (EU). The paper examines, using neural network analysis, the specific impact of each digital technology on innovation revenues while exploring how these technologies affect various types of social innovation within organizations. Through cluster analysis, the study identifies patterns among EU countries based on their digital technology adoption, innovation expenditures, and revenues and the proportion of enterprises engaged in innovation activities. The findings highlight the central role of digital technologies in enhancing innovation and competitiveness, with significant implications for managers and policymakers. These results underscore the necessity for companies to strategically integrate digital technologies to sustain long-term competitiveness in the rapidly evolving digital landscape of the EU.
Journal Article
Essential ingredients for the implementation of Quality 4.0
PurposeQuality 4.0 is concerned with managing quality in the Industry 4.0 era. Specifically, its focus is on which digital tools are used to enhance an organization’s ability to reliably give customers high-quality products. The purpose of this paper is to investigate the key ingredients for the effective implementation of Quality 4.0.Design/methodology/approachA narrative literature review was conducted on the extant works to collate and analyse previous studies in this relatively new field.FindingsThe study revealed eight key ingredients for the effective implementation of Quality 4.0 in organizations, namely: (1) handling big data, (2) improving prescriptive analytics, (3) using Quality 4.0 for effective vertical, horizontal and end-to-end integration, (4) using Quality 4.0 for strategic advantage, (5) leadership in Quality 4.0, (6) training in Quality 4.0, (7) organizational culture for Quality 4.0 and, lastly, (8) top management support for Quality 4.0. These findings have provided a steer for the future research agenda of Quality 4.0.Practical implicationsOrganizations can use the eight ingredients to perform a self-assessment on the current state of each element within their own organization. When implementing Quality 4.0, each ingredient should be effectively analysed, and measures taken so that the implementation of Quality 4.0 is effective.Originality/valueThe paper makes the first attempt to present the key ingredients an organization should possess to effectively implement Quality 4.0.
Journal Article