ELASTIC: Edge Workload Forecasting based on Collaborative Cloud-Edge Deep Learning

With the rapid development of edge computing in the post-COVID19 pandemic period, precise workload forecasting is considered the basis for making full use of the edge limited resources, and both edge service providers (ESPs) and edge service consumers (ESCs) can benefit significantly from it. Existing paradigms of workload forecasting (i.e., edge-only or cloud-only) are improper, due to failing to consider the inter-site correlations and might suffer from significant data transmission delays. With the increasing adoption of edge platforms by web services, it is critical to balance both accuracy and efficiency in workload forecasting. In this paper, we propose ELASTIC, which is the first study that leverages a cloud-edge collaborative paradigm for edge workload forecasting with multi-view graphs. Specifically, at the global stage, we design a learnable aggregation layer on each edge site to reduce the time consumption while capturing the inter-site correlation. Additionally, at the local stage, we design a disaggregation layer combining both the intra-site correlation and inter-site correlation to improve the prediction accuracy. Extensive experiments on realistic edge workload datasets collected from China's largest edge service provider show that ELASTIC outperforms state-of-the-art methods, decreases time consumption, and reduces communication cost. © 2023 ACM.

Remote care for chronic pain: A qualitative evaluation with managers, practitioners, and patients

The Covid-19 pandemic obliged many healthcare providers to transition rapidly to a remote-only model of care. Concerns have been expressed about patient access to remote services, their appropriateness for sensitive consultations and physical examinations. Pre-pandemic research into telemedicine showed evidence of its effectiveness, but patient, staff and service user perspectives on remote care approaches remain unclear. This study explored the experiences and perceptions of care among patients, practitioners and managers in a single United Kingdom chronic pain organisation whose services were delivered remotely (telephone and online) during the pandemic. Nineteen participants (seven patients, seven practitioners, five managers) took part in in-depth qualitative interviews, conducted via telephone or online. Transcripts were analysed thematically. Five service provider and four service user themes were generated. Service provider themes comprised "The change process," "Accessibility and efficiency," "Effective when remote: Contact, support and education," "Concerns about communication, connection and disembodied work," and "Supporting and sustaining the team." Patients' themes comprised "Preferences, expectations and acceptance of remote care," "Convenience and accessibility," "Sense of support" and "Delivery modality matters." The study provides evidence from the qualitative evaluation of a single remote only service of its benefits and limitations as perceived by stakeholders. Findings suggest that service providers could address limitations, and progress to a blended care package, based on for patient need and choice. Further attention could be paid to services delivered by telephone, and to staff communication skills, resources, time management and wellbeing needs.Copyright © Nova Science Publishers, Inc.

Vaccination in pregnancy: The role of the midwife.

Midwives are the front-line workers providing maternity care for women in many countries. The role of the midwife includes providing information about, and recommendations for, maternal vaccination in pregnancy and for the baby in the postnatal period. Vaccinations recommended in pregnancy include those to prevent influenza, pertussis, tetanus and now COVID-19. Vaccinations for the newborn baby include hepatitis B. Healthcare professionals play an important role in influencing decision-making around vaccination and midwives are key in supporting vaccination uptake. Midwives are strong influencer in women's decisions around vaccination for themselves and their babies. The COVID-19 vaccination programs have shone a light on vaccination in pregnancy especially as SARS-COV-2 infection has significant adverse effects in pregnancy. COVID-19 vaccination has been shown to be safe and effective in pregnancy. Despite this, there is vaccine hesitancy from pregnant women in many countries. Midwives play a unique role in the provision of care to women and families but they need specific support and information regarding vaccination in pregnancy. Targeted education, supportive mentoring and supervision and opportunities to lead innovative ways of ensuring vaccine access is logistically easy and possible are all needed. This Commentary outlines the key vaccinations recommended in pregnancy including COVID-19 vaccination and highlights some strategies to scale-up vaccination programs in pregnancy with a particular focus on the role of midwives.

A Secure and Efficient Scheme for Mutual Authentication for Integrity of Exchanged Data in IoMT

The emergence of pandemic diseases like Covid-19 in recent years has made it more important for Internet of Medical Things (IoMT) environments to build contact between patients and doctors in order to control their health state. Patients will be able to send their healthcare data to the cloud server of the medical service provider in remote medical environments through sensors connected to their smart devices, such as watches or smartphones. However, patients' worries surrounding their data privacy protection are still present. In order to ensure the security and privacy of patients' healthcare data in remote medical environments, a number of different schemes have been proposed by researchers. However, these schemes have not been able to take all security requirements into account. Consequently, in this study, we have proposed a secure and effective protocol to safeguard the privacy of patients' medical data when it is sent to the server. This protocol entails two components: mutual authentication of the patient and the server of the medical service provider, as well as the integrity of the exchanged data. Also, our scheme satisfies security requirements and is resistant to well-known attacks. Following this, we used the Scyther tool to formally analyze our proposed scheme. The results showed that the scheme is secure, and in the section on performance analysis, we demonstrated that the proposed scheme performs better than comparable schemes. © 2023 IEEE.

Application of Cloud Computing in an Education Sector through Education and Learning as a Service and its Cost Benefit Analysis

An education sector across the globe is facing numerous challenges. It is being one of the most badly affected sectors due to Covid-19. This paper presents a perspective on applying Cloud Computing technologies in the field of education at several ion levels. In addition, it proposes Education and Learning as a Service model and Decision-Making Matrix for an Organization. © 2023 IEEE.

HanAPP Buhay: Android Java-Based Mobile Commerce Application for Freelance Home Service Providers and Client Job Seekers

Service providers from the informal sectors in the Philippines are left unemployed or want to look for part-time jobs due to the sudden COVID-19 pandemic. With the country on lockdown and as strict restrictions are implemented, people started adopting the e-commerce and m-commerce market. The rise in the Filipino masses using smartphones and participating in mobile commerce to purchase products and services over the Internet has given researchers a potential solution for the arising problem. Thus, the primary objective of the research is to design and develop a user-friendly mobile application that will give a platform where potential home service providers can offer their services to potential clients. HanAPP Buhay, a mobile application that is created in Android Studio with Java as a programming language, is a platform where service providers can offer a variety of home services including laundry, plumbing, cleaning, and electrical works to potential clients. As for the Application Programming Interface (API), Stripe and Firebase are the tools utilized for databases and transaction purposes. The researchers conducted a series of surveys and experiments and have determined that in the 38 trials, the HanAPP Buhay mobile application is functioning 100% accurately as expected, 99.995382330563% and 99.994941213182% working at real-time booking of appointments in the 16 trials for clients and 22 trials for workers respectively, have a reliable user's interface and secured data of both users through the Scrypt algorithm, and effective in its overall specifications in terms of customer's satisfaction. © 2022 IEEE.

Deploying Artificial Intelligence to Combat Covid-19 Misinformation on Social Media: Technological and Ethical Considerations

This paper reports on AI research into online misinformation pertaining to the COVID-19 pandemic within the Canadian context. This is part of our longer-term goal, i.e., development of a machine-learning tool to assist social media platforms, online service providers and government agencies in identifying and responding to misinformation on social media. We report on predictive accuracies accomplished by applying a combination of technologies, including a custom-designed web-crawler, The Dark Crawler, the Posit toolkit, and four different machine-learning models based on Naïve Bayes, Support Vector Machines, LibLinear and LibShortText. Overall, we found that Posit and LibShortText models showed higher levels of correlation to the pre-determined (manual and machine-driven) data classifications than the other machine-learning algorithms tested. We further argue that the harms associated with COVID-19 misinformation - e.g., the social and economic damage, and the deaths and severe illnesses - outweigh the right to personal privacy and freedom of speech considerations. © 2023 IEEE Computer Society. All rights reserved.

Face Mask and Body Temperature Scanning System for Covid-19

Coronavirus illness 2019 has had a major impact on the entire world over the past two to three years. One important approach for people's protection is to wear masks in public. Furthermore, putting on a mask properly Many public service providers demand that users only utilise the service while properly wearing masks. Only a small number of studies have examined face mask identification using image analysis, nevertheless. We suggest Face Mask, a highly accurate and practical face mask detector, in this study. The suggested Face Mask is a one-stage detector that combines a novel context attention module for detecting face masks with a feature pyramid network to fuse high-level semantic information with various feature maps. We also provide a brand-new cross-class object removal method to reject and predictions with a high intersection of union and low confidence. Additionally, we investigate the viability of integrating Face Mask with a portable or embedded neural network called MobileNet. By utilising1)Contactless temperature sensing,2)we create a fack mask detection alarm system to boost COVID-19 indoor safety.Infrared sensor and contactless temperature sensing subsystems rely on Arduino Uno, while computer vision algorithms are used for mask identification. © 2023 IEEE.

Sustainable Urban Freight for Energy-Efficient Smart Cities—Systematic Literature Review

Smart cities need energy-efficient and low-emission transportation for people and goods. Most studies focus on sustainable urban-transportation systems for passengers. Freight transportation in cities has increased significantly during the COVID-19 pandemic, leading to greenhouse gases emissions and negative externalities, such as traffic congestion. The purpose of this paper is to identify through a systematic literature review which innovations (hardware and software) applied by logistics service providers (LSPs) in sustainable urban freight (SUF) are suitable to support the transition to energy-efficient smart cities. We propose to classify the existing innovations in last-mile delivery for SUF into categories: (1) urban freight consolidation and/or trans-shipment;(2) the Consumer as a Service Provider (CaaSP);(3) choice of transportation modes. We introduce the concept of CaaSP as an innovative solution in last-mile delivery (LMD), where customers take over some transport operations with the use of smart technologies, and thus reduce the energy demand. We consider the modes of transportation, such as: drones, autonomous delivery robots, autonomous vehicles, cargo bikes (including e-cargo bikes, e-tricycles), electric vehicles (mainly vans), and combined passenger-and-cargo transportation rapid-transit systems. From the analyzed dataset, we find that energy-efficiency in smart cities can be improved by the consolidation of parcels in micro-depots, parcel lockers, and mobile depots. We analyze smart technologies (the Internet of things, big data, artificial intelligence, and digital twins), which enable energy efficiency by reducing the energy demand (fuel) of SUF, due to better operational planning and infrastructure sharing by logistics service providers. We propose a new IEE matrix as an actionable tool for the classification of innovations applied by LSPs in SUF, according to the level of their interconnectivity and energy efficiency. Additionally, this paper contributes to the theory by exploring possible future research directions for SUF in energy-efficient smart cities. © 2023 by the authors.

An exploratory study of organisational and industry drivers for the implementation of emerging technologies in logistics

Purpose: Emerging technologies have the capacity to transform industries offering substantial benefits to users. Given the increasing demand for advanced logistics services, third-party logistic service providers (LSPs) face greater pressure to deploy and realise these technologies, especially given the demands and operational challenges created during the COVID-19 crisis. Drawing upon the diffusion of innovation (DOI) theory and technology–organisation–environment (TOE) framework, this paper goes beyond just identifying drivers and barriers to technology adoption to understanding how LSPs and industry experts perceive these drivers and barriers and simultaneously confront and undertake actions to implement them. Design/methodology/approach: An exploratory study was conducted in three phases: (1) in-depth interviews with twelve stakeholders in the Australian logistics industry;(2) five in-depth interviews conducted with stakeholders during the COVID-19 crisis and (3) a focus group discussion session. All interviews were analysed using content analysis and revealed several drivers for the deployment of emerging technologies, including internal organisational factors that drive supply chain (SC) network optimisation. Findings: The analysis of the three phases identified several drivers for the deployment of emerging technologies in logistics, including internal organisational factors that drive SC network optimisation. Also identified were external drivers including the impact of the COVID-19 crisis, along with barriers and specific actions that were considered and implemented by LSPs for sustainable operations, particularly in a post-COVID-19 environment. Originality/value: This study explores organisational and industry drivers for the implementation of emerging technologies. Explicitly, it extends the extant research by highlighting organisational and industry drivers and enablers that influence adoption and deployment of emerging technologies. Second, it advances the existing perspectives on LSPs in the Australian context on the development and implementation of technology strategies. The paper offers insights around implementation of technologies, directly obtained from industrial application for managers and practitioners. © 2023, Emerald Publishing Limited.

Smart Energy Meter with Cloud Connectivity

The main tools for allowing customers to communicate openly and transparently with the company and other stakeholders are their electricity bills. However, last year due to pandemics, some residents petitioned the Madras high court claiming TANGEDCO's technique to measure power was arbitrary and unreasonable during the lockdown that COVID provoked. This was done amid complaints about excessive electricity bills. When compared to bills from other states, TANGEDCO's white meter card for energy bills is found to provide insufficient information on use and rates, according to a survey by the certain associations. Power bills urgently need to be redesigned to include comprehensive billing details and accurate assessments of electricity consumption from closed homes or homes in restricted zones. [4] We proposed and designed a Smart Home Energy Meter Monitoring System to solve this crisis. It consists of three systems. First system: Customized built energy meter with LCD. [6] Second system: Wi-Fi module with the Microcontroller (ATMega328P) and an alert system. Third system: Database (MySQL database). [12] The quantity of power used by the device is measured by an energy meter user and every two months, the final reading of the power consumption is taken by the micro controller where the electricity bill calculation program has been pre-programmed to give the value of power consumed during the two months and amount to be paid by the user and [4] It will be shown on the Energy Meter's LCD. The micro controller with a built-in Wi-Fi module (ESP8266) will send these displayed data to the service provider's database. [2] An alert system has been added to counteract the hefty usage and electricity bills to create awareness to the consumer about the slab-wise tariffs increase in the per-unit cost data that has been set by TANGEDCO. [10] The alert has been set in a way that the consumer receives a message for every 200 unit usage of power. The third system is a database created using MySQL database to transport the data to the service provider. © 2022 IEEE.

Identifying the value of a clinical information system during the COVID-19 pandemic

The COVID-19 pandemic has significantly augmented the urgency for service providers to identify and develop clinically urgent system alterations into healthcare systems to facilitate antibody testing and treatment interventions. However, it has been difficult to determine how users assess the value of an information system in terms of its functionality and features. Conversely, the system development process to address urgent user requirements, for example, developing new functionality for COVID antibody testing, has been beset by a myriad of difficulties as research to understand the value of specific aspects of clinical information systems has been elusive. This study addresses this knowledge gap by identifying specific aspects of a national clinical information system in Wales, UK. Through a series of semi-structured interviews, a quantitative study of 559 clinical users and a focus group, the study deconstructs system-related value into 14 unique attributes that have been found to vary according to different types of user roles and geographic location. Attribution theory is identified in this study as a novel and effective way to study this multifaceted concept of system value. The identification of component attributes of the value of a clinical information system provides insights for service users, system developers, and organization managers to prioritize and focus their system development activity by using an importance ranking identified through this study. © 2021 Elsevier Ltd

Reawakening Digital Innovation and Collaboration Strategy: Strategies to Improve Business Performance

Purpose: The objective of this study is to examine the effect of company resources on digital innovation, collaboration strategy, and business performance, as well as the effect of company resources on business performance through digital innovation and collaboration strategy. Research Design: This study uses a quantitative research approach. Observations were made in a cross-section time horizon, in 2022. The Population of this study is the ISP industry, which amounted to 474 companies, and the unit of observation was the management. Sampling used stratified random sampling. ISPs are grouped based on the size of each company based on the number of customers and branch cities are divided into 3 groups: small, medium, and large. Samples were taken many as 100 respondents. Sampling from each classification is done randomly based on a list of population members. Testing the causality hypothesis in this study used PLS (Partial Least Square). Results: the hypothesis testing reveals that company resources play a significant role in developing digital innovation and collaboration strategies. Company resources do not significantly directly affect business performance, but significantly affect business performance through digital innovation and collaboration strategy. Findings: The study provided managerial implications for ISP company management in Indonesia, that collaboration strategy and digital innovation can increase the influence of the development and utilization of company resources on business performance so that companies no longer have to develop and own all of their resources independently. By elaborating their collaboration strategy and digital innovation, companies can focus on developing key resources and additional digital innovations needed to increase the company's competitive advantage. Limitation: the measurement of variables was carried out based on the management's perception of the conditions and situations faced during the COVID-19 pandemic in 2021-2022. To get a deeper understanding and truly describe the details of the empirical conditions, it is necessary to complement qualitative research through confirmatory and in-depth interviews. © 2023, World Scientific and Engineering Academy and Society. All rights reserved.

Secure and Efficient Agreement Signing Atop Blockchain and Decentralized Identity

In recent years, we have witnessed an exorbitant growth of online interactions, especially during the pandemic of COVID-19, which requires diversified digital agreements in different application scenarios. In essence, multi-party agreement signing (MPAS) can be reckoned as a special case of the multi-party fair exchange (MPFE) for signatures over a digital agreement. However, such general MPAS protocols have not seen wide adoptions in practice, possibly due to the lack of incentives to maintain the signing platform. Practically, monetary-incentivized enterprises exist to act as a trusted third party (TTP) and provide signing services. However, such an agreement signing flow still suffers from certain limitations in terms of insecure and inefficient operations. To this end, we propose a secure and efficient framework for multi-party agreement signing based on decentralized identity, blockchain and decentralized storage network (DSN). The framework consists of two subsystems where the identity subsystem contains an extensible three-tier user identity model atop decentralized identity, and the agreement signing subsystem, empowered by the identity subsystem, DSN and several novel designs, achieves security and efficiency design goals. For the convenience of explanation, we suppose that a centralized signing service provider (SSP) is properly involved, i.e., sensitive information is still protected against the SSP, and acts as a TTP to ensure the crucial properties such as fairness and coordinate the signing activities. Our design is also compatible with other methods, e.g., ensuring fairness via blockchain, which removes the single point of failure of SSP. We prototype the framework and the performance evaluation shows effectiveness and efficiency. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Using integration definition for function modeling to define operational obstacles in cold chain farm-to-consumer delivery during the COVID-19 pandemic: A case study in Thailand

This study responds to the urgent need of how community enterprise logistics service providers in Thailand would cope with pandemic challenges in cold chain farm-to-consumer (F2C) delivery. This case study aimed to reveal the underlying logistical problems, within the unique consumption context of Thailand, during the COVID-19 pandemic. Thailand is experiencing growth in e-commerce and social media-based shopping, especially during the pandemic. To capitalize on this trend, logistical service providers are looking for ways to expand the direct distribution of items like chilled and frozen food. Therefore, there is extraordinary growth of the door-to-door service business, especially F2C delivery. The in-depth interviews and observations of staff performance were conducted with a temperature-controlled logistics agent. Then, business processes were analyzed with a swimlane diagram and an integration definition for function modeling to identify the activities of key stakeholders and the problems of the agent. Next, the causes of poor service levels were analyzed by a causal loop diagram. To enhance productivity and service levels, the agent should establish supply and demand data collection, implement the proper forecasting and inventory management, design a standardized packing program for chilled and frozen products, and optimize the pickup and delivery routes. © 2022 Silpakorn University. All Rights Reserved.

Iran's Struggling Health System in the Policy of Managing the COVID-19 Pandemic.

Background: Infectious diseases are one of the most important problems that affect the whole world. The World Health Organization (WHO), an active health organization, has identified coronavirus disease 19 (COVID-19) as a public health emergency and advises governments not to waste time on effective measures and interventions to attack and suppress the virus. In Iran, so far, the total number of screening tests has exceeded 21 million tests and more than 5 million doses of vaccine have been injected. However, we are still far from controlling the epidemic wave. Given the current situation, it is necessary to identify the challenges of managing the new coronavirus epidemic (COVID-19) in the country's medical universities. Methods: This qualitative study was conducted from January 2020 to January 2021 to explore the views of a group of service providers and staff managers of medical universities who were selected via purposeful sampling (n = 47). Data were collected through semi-structured interviews and analyzed using Graneheim and Lundman's conventional content analysis methods. The trial version of MAXQDA 16 software was used to manage the coding process. Results: Upon analysis of data by service providers and staff managers of medical universities, five main themes including governance and leadership, service delivery, human resources, medicine and technology, and financing and 15 sub-themes including management and leadership, culture and society, process, infrastructure, manpower, training and skills, mental pressure, work pressure, nutrition, safety, employee motivation, medical equipment, medicine, payment, and funds were found. Conclusions: Identification of the most important challenges of service providers and staff managers can play an important role in improving the management of the new coronavirus epidemic (COVID-19). It seems that in order to solve some of these challenges, coordination is needed outside the field of health, and considering the formation of the National Corona Headquarters at the national level, it is possible to use this infrastructure to provide the necessary policies and strategies.

An AIoT-Based Environment Control System for Outdoor Barbecue Restaurant in Penghu, Taiwan

This paper proposes an outdoor barbecue restaurant environment control system based on AIoT technology in Penghu, Taiwan, which provides a more convenient restaurant management method for barbecue restaurant service providers and improves the comfort of diners in barbecue restaurants. The proposed system can automatically adjust the temperature and humidity of the restaurant, which uses image processing technology to count the number of diners in the restaurant and set up cameras in the food storage refrigerator to identify whether there are empty plates in time. In response to the COVID-19 epidemic when entering a restaurant, mask identification is carried out using object recognition so that diners who wear masks abnormally can be detected in time, and the virus infection problem can be reduced. All information can be monitored through the proposed IoT monitoring platform. © 2022 IEEE.

A Dynamic Resource Allocation Framework for Synchronizing Metaverse with IoT Service and Data

Spurred by the severe restrictions on mobility due to the COVID-19 pandemic, there is currently intense interest in developing the Metaverse, to offer virtual services/business online. A key enabler of such virtual service is the digital twin, i.e., a digital replication of real-world entities in the Metaverse, e.g., city twin, avatars, etc. The real-world data collected by IoT devices and sensors are key for synchronizing the two worlds. In this paper, we consider the scenario in which a group of IoT devices are employed by the Metaverse platform to collect such data on behalf of virtual service providers (VSPs). Device owners, who are self-interested, dynamically select a VSP to maximize rewards. We adopt hybrid evolutionary dynamics, in which heterogeneous device owner populations can employ different revision protocols to update their strategies. Extensive simulations demonstrate that a hybrid protocol can lead to evolutionary stable states. © 2022 IEEE.

A Latent Dirichlet Allocation Technique for Opinion Mining of Online Reviews of Global Chain Hotels

The hospitality industry has faced unprecedented challenges with the outbreak of Covid-19, which has changed customers' expectations. Therefore, it is essential to identify customers' new perceptions and expectations that lead to positive and negative opinions towards the service providers. Accordingly, this study aims to perform topic modeling and sentiment analysis on 94,200 online reviews of five global chain hotels in South Asia. Topic modeling as a text mining, unsupervised machine learning technique can decipher topics from a corpus such as online reviews, online reports, news covers, etc. In this study, the data is extracted from Trip Advisor through web scraping. Topic modeling is performed using the Latent Dirichlet Approach (LDA) on the extracted data set to analyze the key topics mentioned by the customers in the online reviews. The analysis depicted that cleanliness, food, staff, and service were the main concerns of the hotel guests. Furthermore, the findings represented that the main issues impacting the hotel guests were service delays. However, food and services were the keywords with the maximum word count as depicted by topic modeling. © 2022 IEEE.

Competence inference from muscle: how and when trainers' muscle mass impacts service purchase of personal fitness training

Purpose>This study aims to examine how and when trainers' muscle mass impacts service purchase of personal fitness training, drawing upon signaling theory. Specifically, the authors investigated (1) the mediating role of perceived competence in the relationship between trainers' muscle mass (highly vs moderately muscular) and customers' service registration intention and (2) the moderating role of customer expertise in this mediating mechanism.Design/methodology/approach>The authors conceptualized trainers' muscle mass, developed its experimental stimuli and validated them through the two pretests (total n = 387). Using the validated stimuli, the authors conducted the two experiments (total n = 802). In both experiments, the authors recruited participants via MTurk using the convenience sampling method and employed a single-factor between-subject design based on random assignment.Findings>Findings supported the authors’ proporsed model. Consumers perceived highly (vs moderately) muscular trainers as more competent, which in turn engendered greater service registration intention. This effect emerged for expert consumers but not for novice consumers.Originality/value>This study is one of the first attempts to empirically test the influence of trainers' muscle mass on consumer acquisition in the context of personal fitness training. It also expands the sport marketing literature to the consumer psychology and behavior fields addressing the characteristics of sport-service providers. The findings also provide fitness organizations with managerial insights into how to effectively leverage trainers' physical appearance as a marketing tool.