Supply Chain and Decision Making: What is Next for Visualisation?

Supply chain is a hot topic with strong links in the industry and business applications. The overflowing information generation, increasing complexity of businesses, digitalisation of the supply chain, and introduction of advanced analytics capabilities are all topical issues in the supply chain. Visualization of supply chain inform action in this regards is more than ever important and critical: it provides an easy way to understand and act upon solutions for decision makers, reduces the cognitive load and brings strategic benefits to the business. The development of data analytics and visualization techniques have been booming while little attention was given in the academic literature to structure the landscape and draft the road for further development. The present paper addresses this gap by providing a comprehensive review of the current literature in the use of visualisation in this growing area of supply chain and logistics. The paper employs the PRISMA methodology to identify the main theme, particular areas of development and suggests the future directions for research. Such a structural view developed on the basis of top academic and industry publications, leverages its contribution by provision of a brief structural view of available directional developments and links them to practical applications

Online User and Power Allocation in Dynamic NOMA-Based Mobile Edge Computing

This study tackles the online user allocation problem in mobile edge computing (MEC) systems powered by non-orthogonal multiple access. App vendors need to determine a proper wireless channel in a base station/edge server and sufficient transmit power for every user. We consider a stochastic MEC system where users arrive and depart over time. When an edge server runs out of computing resources, some users will have to wait until the resources become available again, which incurs an allocation delay cost. This cost is often not investigated in many studies, which also do not consider a multi-cell, multi-channel system as we do in this work, due to its complexity. We aim to minimize the allocation delay and transmit power costs, increasing the system’s energy efficiency. To achieve this objective while guaranteeing users’ data rate requirements over time, we adopt the Lyapunov framework to convert this long-term optimization problem into a series of subproblems to be solved in every time slot. To solve the aforementioned subproblems efficiently, we present a distributed game theory-based approach. The proposed algorithm is theoretically evaluated and experimentally demonstrated to outperform several baseline and state-of-the-art methods, highlighting the significance of systematic consideration for both computation and communication aspects of this problem

Gravity++: A graph-based framework for constructing interactive visualization narratives

Interactive visualizations play a key part in the exploration and analysis of data, and in the creation of visual data stories. This paper describes a new graph-based framework for developing interactive visualizations for creating coherent visual data stories. We have realized our framework in a prototype tool named Gravity++. Gravity++ uses a novel graph architecture for modeling interaction, data navigation, and changes in visual representation to better communicate findings to an audience. The combination of these graph models provides better support and flexibility for designing interactive visualizations, data navigation, and visual data stories. We demonstrate the applicability of this framework by two example usage scenarios. We also report on an evaluation study conducted with representative participants. All participants successfully created meaningful visual data stories with a high level of complexity. Our results also show that Gravity++ is easy to use and supports the understanding and sense-making of the visual data story creation process

Formulating Cost-Effective Data Distribution Strategies Online for Edge Cache Systems

Formulating Cost-Effective Data Distribution Strategies Online for Edge Cache System

A Bluetooth-Enabled Device for Real-Time Detection of Sitting, Standing, and Walking: Cross-Sectional Validation Study

Background This study assesses the accuracy of a Bluetooth-enabled prototype activity tracker called the Sedentary behaviOR Detector (SORD) device in identifying sedentary, standing, and walking behaviors in a group of adult participants. Objective The primary objective of this study was to determine the criterion and convergent validity of SORD against direct observation and activPAL. Methods A total of 15 healthy adults wore SORD and activPAL devices on their thighs while engaging in activities (lying, reclining, sitting, standing, and walking). Direct observation was facilitated with cameras. Algorithms were developed using the Python programming language. The Bland-Altman method was used to assess the level of agreement. Results Overall, 1 model generated a low level of bias and high precision for SORD. In this model, accuracy, sensitivity, and specificity were all above 0.95 for detecting sitting, reclining, standing, and walking. Bland-Altman results showed that mean biases between SORD and direct observation were 0.3% for sitting and reclining (limits of agreement [LoA]=–0.3% to 0.9%), 1.19% for standing (LoA=–1.5% to 3.42%), and –4.71% for walking (LoA=–9.26% to –0.16%). The mean biases between SORD and activPAL were –3.45% for sitting and reclining (LoA=–11.59% to 4.68%), 7.45% for standing (LoA=–5.04% to 19.95%), and –5.40% for walking (LoA=–11.44% to 0.64%). Conclusions Results suggest that SORD is a valid device for detecting sitting, standing, and walking, which was demonstrated by excellent accuracy compared to direct observation. SORD offers promise for future inclusion in theory-based, real-time, and adaptive interventions to encourage physical activity and reduce sedentary behavior