Digital Transformation and Archaeology

2020 ◽  
pp. 224-244
Author(s):  
Caterina Paola Venditti ◽  
Paolo Mele
Keyword(s):  
Cloud Computing ◽  
Knowledge Extraction ◽  
Digital Transformation ◽  
Unstructured Data ◽  
Intrinsic Properties ◽  
Emergent Technologies ◽  
Software Applications ◽  
Archaeological Data ◽  
Digital Archaeology ◽  
High Level

In the era of digital archaeology, the communication of archaeological data/contexts/work can be enhanced by Cloud computing, AI, and other emergent technologies. The authors explore the most recent and efficient examples, ranging from some intrinsic properties of AI, i.e. capabilities of sense, comprehend and act, and looking at their application in communication both among specialists of the archaeological sector and from them to other recipients. The chapter will also provide a high-level overview of knowledge extraction solutions from tons of structured and unstructured data, to make it available through software applications that perform automated tasks. Archaeologists must be ready to go down in trenches and communicate their studies with a deep consciousness of chances given by these technologies, and with adequate skills to master them.

Big Data Analysis

2021 ◽  
pp. 208-233
Author(s):  
Arpit Kumar Sharma ◽  
Arvind Dhaka ◽  
Amita Nandal ◽  
Kumar Swastik ◽  
Sunita Kumari
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Analysis ◽  
Knowledge Extraction ◽  
Big Data Analysis ◽  
Unstructured Data ◽  
Data Sets ◽  
Data Handling ◽  
Software And Hardware

The meaning of the term “big data” can be inferred by its name itself (i.e., the collection of large structured or unstructured data sets). In addition to their huge quantity, these data sets are so complex that they cannot be analyzed in any way using the conventional data handling software and hardware tools. If processed judiciously, big data can prove to be a huge advantage for the industries using it. Due to its usefulness, studies are being conducted to create methods to handle the big data. Knowledge extraction from big data is very important. Other than this, there is no purpose for accumulating such volumes of data. Cloud computing is a powerful tool which provides a platform for the storage and computation of massive amounts of data.

scholarly journals Enhanced Round-Robin Algorithm in the Cloud Computing Environment for Optimal Task Scheduling

Computers ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 63
Author(s):  
Fahd Alhaidari ◽  
Taghreed Zayed Balharith
Keyword(s):  
Cloud Computing ◽  
Task Scheduling ◽  
Critical Role ◽  
Turnaround Time ◽  
Round Robin ◽  
Computing Systems ◽  
Time Quantum ◽  
Dynamic Time ◽  
High Level ◽  
Level Performance

Recently, there has been significant growth in the popularity of cloud computing systems. One of the main issues in building cloud computing systems is task scheduling. It plays a critical role in achieving high-level performance and outstanding throughput by having the greatest benefit from the resources. Therefore, enhancing task scheduling algorithms will enhance the QoS, thus leading to more sustainability of cloud computing systems. This paper introduces a novel technique called the dynamic round-robin heuristic algorithm (DRRHA) by utilizing the round-robin algorithm and tuning its time quantum in a dynamic manner based on the mean of the time quantum. Moreover, we applied the remaining burst time of the task as a factor to decide the continuity of executing the task during the current round. The experimental results obtained using the CloudSim Plus tool showed that the DRRHA significantly outperformed the competition in terms of the average waiting time, turnaround time, and response time compared with several studied algorithms, including IRRVQ, dynamic time slice round-robin, improved RR, and SRDQ algorithms.

Users’ attitude on perceived security of enterprise systems mobility: an empirical study

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ramaraj Palanisamy ◽  
Yang Wu
Keyword(s):  
Cloud Computing ◽  
Best Practices ◽  
Empirical Study ◽  
Mobile Systems ◽  
Mobile Technologies ◽  
Content Type ◽  
Security Issues ◽  
Study Results ◽  
Perceived Security ◽  
High Level

Purpose This study/ paper aims to empirically examine the user attitude on perceived security of enterprise systems (ES) mobility. Organizations are adopting mobile technologies for various business applications including ES to increase the flexibility and to gain sustainable competitive advantage. At the same time, end-users are exposed to security issues when using mobile technologies. The ES have seen breaches and malicious intrusions thereby more sophisticated recreational and commercial cybercrimes have been witnessed. ES have seen data breaches and malicious intrusions leading to more sophisticated cybercrimes. Considering the significance of security in ES mobility, the research questions in this study are: What are the security issues of ES mobility? What are the influences of users’ attitude towards those security issues? What is the impact of users’ attitude towards security issues on perceived security of ES mobility? Design/methodology/approach These questions are addressed by empirically testing a security model of mobile ES by collecting data from users of ES mobile systems. Hypotheses were evolved and tested by data collected through a survey questionnaire. The questionnaire survey was administered to 331 users from Chinese small and medium-sized enterprises (SME). The data was statistically analysed by tools such as correlation, factor analysis, regression and the study built a structural equation model (SEM) to examine the interactions between the variables. Findings The study results have identified the following security issues: users’ attitude towards mobile device security issues; users’ attitude towards wireless network security issues; users’ attitude towards cloud computing security issues; users’ attitude towards application-level security issues; users’ attitude towards data (access) level security issues; and users’ attitude towards enterprise-level security issues. Research limitations/implications The study results are based on a sample of users from Chinese SMEs. The findings may lack generalizability. Therefore, researchers are encouraged to examine the model in a different context. The issues requiring further investigation are the role of gender and type of device on perceived security of ES mobile systems. Practical implications The results show that the key security issues are related to a mobile device, wireless network, cloud computing, applications, data and enterprise. By understanding these issues and the best practices, organizations can maintain a high level of security of their mobile ES. Social implications Apart from understanding the best practices and the key issues, the authors suggest management and end-users to work collaboratively to achieve a high level of security of the mobile ES. Originality/value This is an empirical study conducted from the users’ perspective for validating the set of research hypotheses related to key security issues on the perceived security of mobile ES.

scholarly journals Data Beyond the Archive in Digital Archaeology

2018 ◽  
Vol 6 (2) ◽  
pp. 89-92 ◽  
Author(s):  
Sarah Whitcher Kansa ◽  
Eric C. Kansa
Keyword(s):  
Data Management ◽  
Special Section ◽  
Digital Data ◽  
Quality Data ◽  
Annual Conference ◽  
Archaeological Practice ◽  
Archaeological Data ◽  
The Status ◽  
Digital Archaeology ◽  
Virtuous Cycle

ABSTRACTThis special section stems from discussions that took place in a forum at the Society for American Archaeology's annual conference in 2017. The forum, Beyond Data Management: A Conversation about “Digital Data Realities”, addressed challenges in fostering greater reuse of the digital archaeological data now curated in repositories. Forum discussants considered digital archaeology beyond the status quo of “data management” to better situate the sharing and reuse of data in archaeological practice. The five papers for this special section address key themes that emerged from these discussions, including: challenges in broadening data literacy by making instructional uses of data; strategies to make data more visible, better cited, and more integral to peer-review processes; and pathways to create higher-quality data better suited for reuse. These papers highlight how research data management needs to move beyond mere “check-box” compliance for granting requirements. The problems and proposed solutions articulated by these papers help communicate good practices that can jumpstart a virtuous cycle of better data creation leading to higher impact reuses of data.

scholarly journals Entity Type Recognition for Heterogeneous Semantic Graphs

AI Magazine ◽  
2015 ◽  
Vol 36 (1) ◽  
pp. 75-86 ◽  
Author(s):  
Jennifer Sleeman ◽  
Tim Finin ◽  
Anupam Joshi
Keyword(s):  
Machine Learning ◽  
Background Knowledge ◽  
Knowledge Bases ◽  
Heterogeneous Data ◽  
Unstructured Data ◽  
Supervised Machine Learning ◽  
Coreference Resolution ◽  
Multiple Sources ◽  
Fine Grained ◽  
High Level

We describe an approach for identifying fine-grained entity types in heterogeneous data graphs that is effective for unstructured data or when the underlying ontologies or semantic schemas are unknown. Identifying fine-grained entity types, rather than a few high-level types, supports coreference resolution in heterogeneous graphs by reducing the number of possible coreference relations that must be considered. Big data problems that involve integrating data from multiple sources can benefit from our approach when the datas ontologies are unknown, inaccessible or semantically trivial. For such cases, we use supervised machine learning to map entity attributes and relations to a known set of attributes and relations from appropriate background knowledge bases to predict instance entity types. We evaluated this approach in experiments on data from DBpedia, Freebase, and Arnetminer using DBpedia as the background knowledge base.

scholarly journals Calm Before the Storm

2012 ◽  
Vol 4 (2) ◽  
pp. 28-48 ◽  
Author(s):  
George Grispos ◽  
Tim Storer ◽  
William Bradley Glisson
Keyword(s):  
Cloud Computing ◽  
Law Enforcement ◽  
Data Storage ◽  
It Infrastructure ◽  
Software Applications ◽  
Digital Forensic ◽  
Forensic Practice ◽  
New Research ◽  
Key Aspects ◽  
Control And Management

Cloud computing is a rapidly evolving information technology (IT) phenomenon. Rather than procure, deploy, and manage a physical IT infrastructure to host their software applications, organizations are increasingly deploying their infrastructure into remote, virtualized environments, often hosted and managed by third parties. This development has significant implications for digital forensic investigators, equipment vendors, law enforcement, as well as corporate compliance and audit departments, amongst other organizations. Much of digital forensic practice assumes careful control and management of IT assets (particularly data storage) during the conduct of an investigation. This paper summarises the key aspects of cloud computing and analyses how established digital forensic procedures will be invalidated in this new environment, as well as discussing and identifying several new research challenges addressing this changing context.

scholarly journals Buffer Placement and Sizing for High-Performance Dataflow Circuits

2022 ◽  
Vol 15 (1) ◽  
pp. 1-32
Author(s):  
Lana Josipović ◽  
Shabnam Sheikhha ◽  
Andrea Guerrieri ◽  
Paolo Ienne ◽  
Jordi Cortadella
Keyword(s):  
Performance Optimization ◽  
Optimization Model ◽  
High Performance ◽  
Control Flow ◽  
High Level Synthesis ◽  
Software Applications ◽  
Marked Graphs ◽  
Variable Latency ◽  
High Level ◽  
Strong Contrast

Commercial high-level synthesis tools typically produce statically scheduled circuits. Yet, effective C-to-circuit conversion of arbitrary software applications calls for dataflow circuits, as they can handle efficiently variable latencies (e.g., caches), unpredictable memory dependencies, and irregular control flow. Dataflow circuits exhibit an unconventional property: registers (usually referred to as “buffers”) can be placed anywhere in the circuit without changing its semantics, in strong contrast to what happens in traditional datapaths. Yet, although functionally irrelevant, this placement has a significant impact on the circuit’s timing and throughput. In this work, we show how to strategically place buffers into a dataflow circuit to optimize its performance. Our approach extracts a set of choice-free critical loops from arbitrary dataflow circuits and relies on the theory of marked graphs to optimize the buffer placement and sizing. Our performance optimization model supports important high-level synthesis features such as pipelined computational units, units with variable latency and throughput, and if-conversion. We demonstrate the performance benefits of our approach on a set of dataflow circuits obtained from imperative code.

scholarly journals A Conceptual Model for Cloud Computing Adoption by SMEs in Australia

2016 ◽  
pp. 307-334 ◽  
Author(s):  
Ishan Senarathna ◽  
Matthew Warren ◽  
William Yeoh ◽  
Scott Salzman
Keyword(s):  
Cloud Computing ◽  
Conceptual Model ◽  
Business Service ◽  
Perceived Benefits ◽  
Public Cloud ◽  
Total Cost ◽  
The Public ◽  
Software Applications ◽  
On Demand ◽  
Cloud Computing Adoption

Cloud Computing is an increasingly important worldwide development in business service provision. The business benefits of Cloud Computing usage include reduced IT overhead costs, greater flexibility of services, reduced TCO (Total Cost of Ownership), on-demand services, and improved productivity. As a result, Small and Medium-Sized Enterprises (SMEs) are increasingly adopting Cloud Computing technology because of these perceived benefits. The most economical deployment model in Cloud Computing is called the Public Cloud, which is especially suitable for SMEs because it provides almost immediate access to hardware resources and reduces their need to purchase an array of advanced hardware and software applications. The changes experienced in Cloud Computing adoption over the past decade are unprecedented and have raised important issues with regard to privacy, security, trust, and reliability. This chapter presents a conceptual model for Cloud Computing adoption by SMEs in Australia.

scholarly journals Virtual Machine Selection Algorithm Based on User Requirements in Mobile Cloud Computing Environment

2018 ◽  
Vol 17 (2) ◽  
pp. 7335-7349
Author(s):  
Rashid Alakbarov
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Mobile Cloud Computing ◽  
Virtual Machines ◽  
Mobile User ◽  
Base Stations ◽  
Mobile Cloud ◽  
Software Applications ◽  
Wireless Metropolitan Area Networks ◽  
Cloud Technologies

The article analyzes the advantages of mobile cloud technologies and problems emerging during the use of those. The network infrastructure created based on cloudlets at the second level of mobile cloud computing with hierarchical structure is analyzed. At the same time, the article explores the issues of satisfaction of demand of mobile equipment for computing and memory resources by using these technologies. The article presents one solution for the allocation of mobile user requests in virtual machines created in cloudlets located near base stations of wireless metropolitan area networks (WMAN) in a balanced way by considering the technical capacity of those. Alongside, the article considers the solution of user problem during designated time and the issue of determining virtual machines satisfying other requirements. For this purpose, different characteristics of the stated problem, virtual machines, as well as communication channels between a user and virtual machines are considered. By using possible values determining the importance of cloudlets, conditions for loading software applications of a user to a virtual machine are explored and an appropriate method is proposed.

scholarly journals ALGORITHM FOR TASK CONSOLIDATION IN CLOUD COMPUTING: A COMPARATIVE SURVEY

2018 ◽  
Vol 6 (5) ◽  
pp. 340-345
Author(s):  
Rajat Pugaliya ◽  
Madhu B R
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Resource Utilization ◽  
Service Provider ◽  
Virtual Machines ◽  
Cloud Service ◽  
Cloud Service Provider ◽  
Dynamic Task ◽  
Main Challenge ◽  
High Level

Cloud Computing is an emerging field in the IT industry. Cloud computing provides computing services over the Internet. Cloud Computing demand increasing drastically, which has enforced cloud service provider to ensure proper resource utilization with less cost and less energy consumption. In recent time various consolidation problems found in cloud computing like the task, VM, and server consolidation. These consolidation problems become challenging for resource utilization in cloud computing. We found in the literature review that there is a high level of coupling in resource utilization, cost, and energy consumption. The main challenge for cloud service provider is to maximize the resource utilization, reduce the cost and minimize the energy consumption. The dynamic task consolidation of virtual machines can be a way to solve the problem. This paper presents the comparative study of various task consolidation algorithms.

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