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Internet of Things (IoT)-enabled devices were developed to make everyday life easier. Smart devices are becoming ubiquitous and increasing rapidly in number and applications. The growing popularity of smart devices indicates that the Internet of Things (IoT) technology is becoming more and more prominent in our everyday life. The IoT market was valued at $190 billion in 2018 and is expected to reach

In response to claims that 5G will “change the world,” 5G mobile communications systems have drawn considerable attention, from consumers and practitioners, to policymakers and academics. Amid mass-marketing campaigns and public posturing by early 5G pioneers in the telecom industry, cutting through the hype to understand the actual implications of this new technology is difficult. This article examines

Conducting a risk assessment (RA) for cloud computing platforms presents new challenges in the space of Information Security Management Systems (ISMS). ISO 27001 RA methods have been used for Alcohol Monitoring Systems (AMS) across a portfolio of products and services. Scaling these localized techniques to national and international cloud security standards shows that a ‘one size fits all’ RA approach

The four articles in this special issue focus on communications recovery and resilience. Communications recovery and resiliency is a topic of great concern in current times as disasters have taken a greater toll on society. The current COVID-19 pandemic has made us more dependent on communications networks and this has increased the premium placed on technologies and its operations. Communications

Resilience in telecommunication networks is viewed as a level of connectivity among nodes. This article discusses a preference-based edge weights assignment strategy. Preference values bias the selection of node and edge-related attributes to compute the level of connectivity.

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The datacenter networks we use today are based on a 50-year-old design. While it has served us well, that design no longer meets the needs of today's distributed applications. The result is failures visible to the users of those applications in spite of developers’ best efforts. We believe it is time to provide a new design, one that takes into account what today's applications need. To that end, we

Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers.

Satellite networks have long been regarded as a key enabler for ubiquitous Internet access and global data distribution. However, since they are highly dynamic and much more vulnerable to various failures, how to detour traffic around fault satellites and interrupted links becomes an important but challenging issue. Thanks to the emerging software-defined networking, great controllability can be introduced

In the last three decades, the great powers have become increasingly dependent on satellite communication (SATCOM), very high frequency (VHF), and ultrahigh frequency providing high bandwidth line-of-sight communications. These military communication channels lack resilience because an electronic warfare (EW) campaign can affect both VHF and SATCOM simultaneously. The 1940s preferred spectrum, high

This article explores the information systems involved in disaster relief supply chain for Hurricane Harvey survivors. We interviewed three organizations, the United Way, the BakerRipley, and the American Red Cross, on how information systems were used in this concerted effort of long-term recovery. We found that data sharing is the major challenge, and it is further constrained and complicated by

Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers.

Resilience is an organization's end-to-end capability to handle disruptions and recover postdisruption. This resilience depends on an organization's ability to predict disruptions and the preparedness of the leadership to handle them. Predictability and preparedness are functions of data science in the data-driven world of today's digital business. Artificial Intelligence (AI) within data science is

We propose a new method for life rescue operations after a hazard where the cellular network coverage is limited or nonexistent. The aim is to find survivors quickly by locating them even without their active participation. Our approach is based on deploying unmanned aerial vehicles as parts of the cellular network. We exploit the fact that, increasingly, almost everyone carries cellular mobile devices

A smart city provides significant services to it is inhabitants. Continued operation of these service is critical. This article investigates resilience against failures in a smart city. It classifies applications based on their impact of service degradation. It provides an overview of a wide range of faults and failures that could lead to service degradation. It also explores strengths of existing

Technostress is stress that individuals experience due to their use of information technology. It is associated with critical workplace consequences including reduced productivity. While the negative consequences are well known, what is less understood is how individuals can cope with technostress to alleviate them. We report on two studies that explain how organizational IT users can cope with technostress

Recent years have seen the continuous evolution of technology, which has led to the definition of frameworks such as the internet of things (IoT) and Industry 4.0. These paradigms are producing enormous quantities of data every single day. These data are subject to data analysis, shared publicly or kept secret. Traditionally, this task was carried out using databases. With the advent of Blockchain

Telecommunications service providers build highly available networks using equipment redundancy and overload protection mechanisms. However, because of network equipment misconfiguration or a natural disaster, the network equipment failover could be unsuccessful. This article proposes a linear programming model for determining the optimal distribution of user sessions in a commercial network such that

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Those who sit in C-Suites are responsible for revenue growth and profitability. They are responsible for strategy, marketing, governance, and the management of their lines of business–regardless of the vertical industries they occupy. They are responsible for talent and technology–especially technology, which is often focused on “digital transformation,” which–when done right–is about as holistic an

Much has been written about the benefits of using blockchains for securing transactions in finance, healthcare, supply chain management and more, and some of these benefits are already being realized. But not nearly as much consideration has been given to use blockchains for records of personal transactions. That is, there is great potential for blockchains in certifying and securing the validity,

Functions as a Service (FaaS) is an ultimate expression of cloud computing. FaaS provides a significant business value proposition to users and offloads the security issues of the platform to the provider. The user is responsible for the security of their implementation. FaaS application implementations are typically subject to OWASP top 10 vulnerabilities and require corresponding security controls

Automated Graphical User Interface (GUI) testing is a fundamental part of the Verification and Validation process of every software, but it is often linked to notable maintenance costs, especially for mobile applications. The literature reports a general lack of automated testing adoption among mobile developers in the industry. In this article, we present the outcome of seven interviews centered on

Optimal maintenance is one of the key concerns for asset-intensive industries in terms of reducing downtime and occurring costs. The advancement of data-driven technologies, affordable computing powers, and growing amounts of data introduced a paradigm with the name of predictive maintenance (PdM). PdM seeks to find out an optimal moment for the maintenance of an asset, where no early intervention

The use of commercially available voice assistants (VA) that enable personal data collection on a large scale is on the rise. However, knowledge discovery on such data can lead to the violation of various privacy issues. This article presents the various stakeholders who are a part of this privacy regime, along with a detailed taxonomy of the various privacy issues existing currently in the VA world

DevOps is an emerging paradigm for information technology delivery. However, little research has examined the implications of DevOps on the theoretically based foundations for information technology governance. This article contributes to this new area of discourse by examining the challenges faced by institutions in reimagining their information technology governance mechanisms to accommodate DevOps

The Internet of Things (IoT) brings a set of unique and complex challenges to the field of Quality of Experience (QoE) evaluation. The state-of-the-art research in QoE mainly targets multimedia services, such as voice, video, and the Web, to determine quality perceived by end-users. Therein, main evaluation metrics involve subjective and objective human factors and network quality factors. Emerging

Innovating business processes by means of emerging technologies may lead to significant productivity increases and economic growth. However, each innovation involves risks and creates uncertainties, especially when this is done with still immature technologies. By conducting an expert panel followed by multiple case studies, we have compiled a list of frequently occurring obstacles with lessons learned

With the advancements in enterprise-level business development, the demand for new applications and services is overwhelming. For the development and delivery of such applications and services, enterprise businesses rely on Application Programming Interfaces (APIs). APIs provide interface to enable the communication among different applications. In essence, API is a double-edged sword; on one hand

Advances in artificial intelligence and deep neural networks have led to a rise in synthetic media, i.e., automatically and artificially generated or manipulated photo, audio, and video content. Synthetic media today is highly believable and “true to life”; so much so that we will no longer be able to trust what we see or hear is unadulterated and genuine. Among the different forms of synthetic media

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Classification is a central discipline of machine learning (ML) and classifiers have become increasingly popular to support or replace human decisions. We encounter them as email spam detectors, as decision support systems, for example in healthcare, as aid in interpreting X-rays in breast cancer detection, or in the financial and insurance sector, for financial and risk analysis. For example, Facebook

Infants and toddlers have a dramatic way of communicating their needs—raising their voices. As soon as they raise the alarm, their caretakers receive and interpret the signal and take the desired action to address their concerns. Metaphorically, Internet of Things (IoT) devices are children, enabled and enriched by a 4th industrial revolution, artificial intelligence (AI), and related technologies

The articles in this special section focus on the significance and growth for artificial intelligence and its applications. AI has become one of the most transformative technologies in the world and a catalyst for systemic changes in industries, societies, and economies in our world. For IT professionals and businesses, AI is playing the same revolutionary role as the steamengine did in the 18th century

Translation ranking is inherently of great significance for machine translation (MT), as it allows the comparison of performances of multiple MT systems as well as for its efficient training. This article demonstrates a mechanism that is used for ranking the translation outputs generated by the MT systems from best to worst. To implement this approach, the system exploits a supervised learning algorithm

Air pollution has caused environmental and health hazards across the globe, particularly in emerging countries such as China. In this article, we propose the use of air quality index and the development of advanced data processing, analysis, and visualization techniques based on the AI-based k-clustering method. We analyze the air quality data based on seven key attributes and discuss its implications

Objective: To investigate the early outcomes following adenotonsillectomy (T&A); to explore the role of facial feature and demographic data in predicting early-persistence of obstructive sleep apnea syndrome (OSAS) after T&A in children with moderate to severe OSAS. Method: Children were included from Beijing Children's Hospital. Craniofacial photograph analysis was applied to analyze facial features

A crowd can be defined as a large gathering of people at a particular place showing different types of attitudes and behaviors. Monitoring and tracking these wide varieties of people is tedious in a real environment. The crowded scenarios have a high tendency to change into an abnormal condition due to sudden external pressures such as gunshots/fire or internal stress such as overcrowding, where things

In the field of machine learning, there exist effective models that achieve remarkable results. However, it is criticized from the perspective of the end user that many successful models behave like “black boxes.” In the desire for achieving excellent performances, the models become more complicated and less explainable. In this context, a major challenge has emerged: it is necessary to provide the

The growing demand for the meaningful use of electronic medical records has led to great interest in medical entities and relation extraction technologies. Most existing methods perform relation extraction based on manually labeled documents and rarely consider incorporating knowledge graphs that include rich, valuable structured knowledge, which will cause semantic ambiguities. To address this problem

Reports on how artificial intelligence (AI) applications are being used to improve economic, social, and environmental performance in developing economies.

Technology should be assessed and piloted in a repeatable way. Teams should be assigned to pursue the following tasks: track technology-driven business models and processes; track existing and emerging digital technologies; conduct technology pilots; and govern the enterprise architecture. Formal teams will ensure a consistent, repeatable and impactful process that leverages current and existing technology

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We provide an overview of the Special Issue on current advances, challenges, and opportunities for AI technologies in agriculture. We illustrate the potential of AI using four major components of the food system: production, distribution, consumption, and uncertainty. We recognize that the transformation of agriculture will require new tools to more precisely manage fields to increase production while

Agriculture has become an information-intensive industry. In the production of crops and animals, precision agriculture approaches have resulted in the collection of spatially and temporally dense datasets by farmers and agricultural researchers. These big datasets, often characterized by extensive nonlinearities and interactions, are often best analyzed using machine learning (ML) or other artificial

The real-time detection of drought stress has major implications for preventing cash crop yield loss due to variable weather conditions and ongoing climate change. The most widely used indicator of drought sensitivity/tolerance in corn and soybean is the presence or absence of leaf wilting during periods of water stress. We develop a low-cost automated drought detection system using computer vision

We describe an AI recommender system (RS) with machine learning to harness past user choices and large volumes of data, yet account for changes in weather and management decisions characteristic of agricultural systems. Our goal is to maximize the use of data relevant to solving agricultural problems and improve the efficiency of the scientific workforce while also improving the accuracy of estimates

Agricultural systems are enormously variable in space and time. New and developing artificial intelligence (AI)-based tools can leverage site-based science and big data to help farmers and land managers make site-specific decisions. These tools are improving information about soils and vegetation that forms the basis for investments in management actions, provides early warning of pest and disease

We compare two approaches to automate carcass quality grading using different artificial intelligence methods. The first is based on image analysis, and the second uses state-of-the-art Rapid Evaporative Ionization Mass Spectrometry. Both employ machine learning (ML) to increase the speed and accuracy of carcass quality evaluation. The image analysis method increased speed and accuracy for all quality