ABSTRACT
Mobile Financial Services (MFS) has gained significant popularity during the COVID-19 pandemic, especially among marginalized and low-income, low-literate communities around the world. Such communities have not been traditionally considered while designing MFS services via smartphone apps or USSD services in featurephones. Financial constraints limit such end-users towards basic featurephones, where recent appstore support has made it possible to deploy app-based MFS solutions beyond USSD. This new featurephone platform is a relatively underexplored area in terms of addressing design issues related to aforementioned end-users while developing MFS solutions. Our work addresses this gap by presenting qualitative findings on barriers to technology access focused on MFS solutions in marginal communities. We present a prototype non-USSD, app-based solution on an appstore-supported featurephone platform designed via a human-centered approach. This work has the potential to increase the financial inclusivity of marginalized communities in cashless MFS transactions via low-cost, appstore-enabled featurephones. © 2023 ACM.
ABSTRACT
The availability of resources is vital when rapid changes and updated medical information in the provision of care are needed, such as in the fight against COVID-19, which is not a conventional disease. Continuing medical education plays an essential role in preparing for and responding to such emergencies. Workflow has improved based on the virtual meetings, online trainings, and remote detailing conducted by medical representatives in order to deliver educational content instantly through digital tools, such as salesforce automation (SFA), webinars, etc. In terms of its regulatory barriers, the pharmaceutical industry mainly targets healthcare professionals, unlike most businesses that reach end users directly. Medical representatives are equipped with an SFA to enhance customer relationship management (CRM) and closed loop marketing (CLM) capabilities in pharmaceutical companies. This study aimed to fill a gap in the literature by investigating the use of SFA in work patterns, such as health professionals' loyalty and involvement in their medical knowledge in Turkey, and how it allows for differentiating training from marketing. This study intended to compare the data on internists and medical products gathered from a well-known pharmaceutical company's SFA. The data covered the first three months of the year 2020, when medical representatives had a normal daily routine, and that of 2021, when Turkey experienced the most powerful surge of the COVID-19 pandemic. The analysis was based on simple correspondence analysis (SCA) and multiple correspondence analysis (MCA) for 11 variables. Monitoring product, physician's segment, and medical representatives' behaviors with SFA had a significant influence on the pharma-physician relationship strategy, as expected. The findings supported the view that SFA technologies can be deployed to advance the medical knowledge of physicians, in addition to managing and designing superior CRM and CLM capabilities.
ABSTRACT
This study presents internet of things (IOT) and artificial intelligence technologies that are critical in reducing the harmful effects of this illness and assisting its recovery. It explores COVID-19's economic impacts before learning about new technologies and potential solutions. The research objective was to propose a solution for self-diagnosis, self-monitoring, and self-management of COVID-19 with personal mobiles and personal data using cloud solutions and mobile applications with the help of an intelligent IoT system, artificial intelligence, machine learning, and 5G technologies. The proposed solution based on self-diagnosis without any security risk for users' data with low cost of cloud-based data analytics by using handsets only is an innovative approach. Since the COVID-19 outbreak, the global social, economic, religious, and cultural frameworks and schedules have been affected adversely. The fear and panic associated with the new disease, which the world barely knew anything about, amplified the situation. Scientists and epidemiologists have traced the first outbreak of COVID-19 at Wuhan, China. A close examination of the genetic makeup of the virus showed that the virus is zoonotic, meaning that the virus changed hosts from animals to humans. The uncertainty associated with the above features and characteristics of the virus, as well as the high mortality rates witnessed in many parts of the globe, significantly contributed to the widespread global panic that brought the world to a standstill. Different authorities and agencies associated with securing the public have implemented different means and methods to try and mitigate the transmission of the infection as scientists and medical practitioners work on remedies to curb the spread of COVID-19. Owing to different demographics, different parts of the globe have attempted to effectively implement locally available resources to efficiently fight and mitigate the adverse effects of the COVID-19 pandemic. The general framework provided by the World Health Organization (WHO) has been implemented or enhanced in different parts of the globe by locally available resources and expertise to effectively mitigate the impact of COVID-19. There is currently no effective vaccine for COVID-19, but new technology can be available within weeks to reduce the spread of the disease;current approaches such as contact tracing and testing are not secure, and the cost of testing is high for end users. The proposed solution based on self-diagnosis without any security risk for users' data with low cost of cloud-based data analytics functions by using an intelligent internet of things (IOT) system for collecting sensors data and processing them with artificial intelligence to improve efficiency and reduce the spread of COVID-19.
ABSTRACT
Mobile broadband (MBB) penetration has deepened globally over the last twenty years. This is largely due to the adoption of smart devices, improved mobile communications network coverage, and the perpetual drive to develop ever faster mobile and wireless communication technologies. However, information on the quality of service (QoS) delivered by MBB operators to the end users remains an issue of concern. This has driven independent researchers and mobile communication industry regulators to develop methodologies for independent and unbiased evaluation of the QoS offered by MBB networks. This paper provides a detailed review of MBB adoption and penetration across several regions of the world. It also includes the existing methodologies for evaluating the performance of MBB systems as experienced by the end user. Specifically, methodologies such as the drive and walk tests, crowd-sourced mobile device-based methods and the software applications they employ, and the dedicated measurement testbeds are reviewed. Based on this, the challenges of adopting each of the methods are discussed in order to make a case for the development of more robust, partially autonomous and scalable MBB measurement platforms for the future.
ABSTRACT
During the current COVID-19 pandemic, the large number of positive cases of infection has resulted in medical institutions lacking personnel to treat patients who continue to arrive. As a result of these problems, supervision and monitoring of room conditions is still lacking or even non-existent, so that the recovery process can be hampered or can facilitate the transmission of the virus to other people. It takes a device or tool that can monitor conditions and regulate the isolation room so that the temperature and humidity remain in the optimal zone so that recovery can be optimal and also reduce the risk of virus transmission. Based on this description, the author applies the concept of IoT by utilizing the IoT platform system and designing a system and tool that can monitor and regulate the COVID-19 isolation room and convey this information quickly and concisely. In addition, this study also examines how well and easily understood the system is when used by end-users by using the System Usability Scale or SUS as its usability testing method. The results obtained from this study are that the system and equipment function properly, the automation system and the method used are able to mitigate changes in temperature and humidity in the isolation room, and through the SUS method, the level of usability for end-users is deemed quite sufficient. © 2022 IEEE.
ABSTRACT
Data profiling is a "set of statistical data analysis activities to determine properties of a dataset". Historically, it was aimed at data (not meta-data), but at scale, the tables' meta-data (i.e. title, attribute names, types) becomes abundant, hence its profiling becomes vital, especially in order to understand the contents of large-scale structured datasets.Here we describe and evaluate the algorithms and models behind our scalable Meta-data profiler. It is capable of learning Meta-profiles for a topic of interest in extreme-scale structured datasets, such as WDC [1] or CORD-19 [2] having millions of tables and hundreds of thousands of sources. A 3D Meta-profile visualizes a specific topic (e.g. COVID-19 vaccine side-effects) present in a large-scale structured dataset and simplifies access and comparison for data scientists and end-users. © 2022 IEEE.
ABSTRACT
Since the beginning of the COVID-19 pandemic, images of faces with obscured bottom halves have become more common due to masking. Now more than ever, end-users are looking toward machine learning and data science to create high-quality replacements for missing facial data. For face completion, we evaluate multiple machine learning algorithms, including Decision Trees, K-Nearest Neighbors, and Support Vector Machines. Since most of the existing work in this field uses deep learning, we explore the impact of using multiple deep learning techniques and use them as a point of comparison. Our study indicates that despite the conventional norm that deep learning algorithms outperform their machine learning counterparts, the non-deep learning techniques perform better for this application.11Code is available at https://github.com/nickfons/fcwmoe. © 2022 IEEE.
ABSTRACT
The Covid-19 pandemic influenced the way that buildings are used and experienced. In particular, educational facilities were among the most affected by the pandemic in terms of use processes. This paper presents a methodology developed to reorganise spaces in a school building, a real case study, to allow safe reopening. Social distancing and availability of learning spaces were taken into account to simulate the use of the educational facility according to the emergency protocols. Based on a digital survey of the existing building, a building information model was generated and used as a basis for spatial analysis and crowd and agent-based simulations. Additionally, interactive games and training videos were developed as communication tools to inform end users about the new rules to be respected inside the building. The digital approach adopted for the analysis of use processes as well as for communicating the results to the end users allowed them to experience the school fruition processes within a virtual environment before the school reopening. Future works could deal with the application of the same methodology in other schools, as well as in different contexts, going beyond the specificity of the pandemic emergency, and for other types of buildings. © 2023 ICE Publishing: All rights reserved.
ABSTRACT
The supply chain in the construction industry faces numerous constraints such as a lack of coordination, communication, collaboration, and technological advancement. Supply chain management is critical when products are transferred from one organization to another until they reach end users or consumers without being damaged, counterfeited, or delayed. Despite extensive research, little is known about the factors that will lead to better construction supply chain management. The reason for this examination is to make a bibliometric investigation in light of the verifiable solidification of distributions and branches of knowledge. It intends to recognize research trends, authers, nations, and organizations utilizing VOSviewer. The construction project all over the world have been uncovered in different manner by the COVID-19 pandemic. This paper makes sense of how it is feasible to proceed with development work in this present circumstance. The relevant literature in the field of Blockchain in construction supply chain management is retrieved using the Scopus, Web of Science database as the research object. If the construction work carry on, the economic downturn will be decreased and unemployment will also be decreased. The mapping of Blockchain Construction Supply Chain Management scientific production enabled the visualization of networks of co-occurrence of keywords. © 2022 IEEE.
ABSTRACT
Management, operations, and planning in water resources management are required to respond to a multitude of challenging problems that may arise due to rapid change in climate conditions, extreme weather events, frequent and unforeseen incidents or on the other hand, long-term structured management decisions. This paper reports on deployment of a decision support system (DSS) for Greater Sydney supply systems known as the CARM Greater Sydney Project. Development and deployment of the DSS tool currently being undertaken by WaterNSW is based on integrated hydrological-hydrodynamic water quality models. The system architecture of the tool is underpinned by a set of baseline catchment models developed using eWater's Source modelling suite. Catchment modelling outputs are then fed into reservoir models as input which are housed in the AEM3D (a 3-Dimensional coupled Hydrodynamic- Aquatic Ecosystem Model) platform;providing a set of base cases to represent the fundamental catchment/lake conditions. Mike Workbench - an application developed by DHI is used as the DSS tool. Building on the baseline model, users can generate multiple scenarios with varying complexity by manipulating different parameters of the tool specific to a problem at a scale and level of complexity suited to the problem and needs of decision makers via Mike Workbench. Users can also compare the outcomes between different scenarios, facilitating the decision making for increasingly complex water resources management issues. An integral part of the project is to roll out a suit of comprehensive training on using this tool to different groups of users/stakeholders tailored by their needs and interest. The training and deployment of the new system were started during COVID shutdowns. The paper will provide an overview of the new system and how training was developed as part of the project and embedded through the deployment of the new DSS tool in a fully on-line mode. The lessons learned include providing training specific to user needs, time for practice and one on one support, but also cover planning and integration of the training throughout the project development and deployment. © Hydrology and Water Resources Symposium, HWRS 2022. All rights reserved.
ABSTRACT
With the emergence of coronavirus and the rapidly increasing number of cases, we observed that people were suffering from a lack of information about where to source critical requirements such as oxygen cylinders, beds, ambulance service, and ventilators. In this research paper and project, the authors have designed and developed an interactive information dashboard to access the availability of these resources and requirements at different locations across India from myriad sources. The information dashboard will show information for all the states across India. The dashboard visualizes the number of corona cases, hospital beds, blood bank, etc. The end-users and the COVID-19 support team can imagine all the requirements in the dashboard that is factual and credible within their vicinity from multiple information sources. The user need not search various information sites to search for different conditions. The project collates the data of other requirements from primary sources of information like Twitter and government websites and lists them on the dashboard. The authors used open-source programming and database technologies to display the data per user requirements. The dashboard was helpful to the end-users during COVID-19 times in terms of convenient accessibility and efficiency. © 2022 IEEE.
ABSTRACT
The outbreak of Covid-19 pandemic has caused millions of people infected and dead, resulting in global economy depression. Lessons learned to minimize the damage in an emerging pandemic is that timely tracking and reasonable trend prediction are required to help the society (e.g., municipality, institutions, and industries) with timely planning for efficient resource preparation and allocation. This paper presents a system to monitor the pandemic trends, analyze the correlation and impacts, predict the evolution, and visualize the prediction results to end users as social indicators. The significance lies in the fact that tracing online information collection for pandemic related prediction has less time lag, cheaper cost, and more potential information indicators. © 2022 IEEE.
ABSTRACT
The refurbishment of building facilities needs to incorporate end-user engagement to ensure refurbished building facilities outcomes that include user-responsive learning spaces and satisfy users’ learning needs. However, existing refurbishment design process frameworks neglect to show the engagement process. A new framework for engaging end users in the refurbishment design of building facilities in higher education is presented. A qualitative research methodology was employed to obtain and analyse interview data from twenty-one design team stakeholders involved in two cases of refurbished building facilities in higher education institutions in Australia and New Zealand. The findings revealed four core themes which indicate the context and phases in the refurbishment design process where end-user engagement should be taken seriously. They are the higher education context, early design, user engagement in the design process and post-design phases. In addition, the findings revealed six specific strategies for end-user engagement in the refurbishment design of building facilities in higher education institutions. They are identifying stakeholder value systems, capturing end-user needs, communicating and integrating. Others are the setting of engagement boundaries and surveying of end users. This study modified the project heartbeat originally developed by Stanford University in 2010 for the refurbishment design process in a higher education context. The new framework bridges the gaps in the current literature between stakeholder theory and refurbishment design, and, by incorporating the refurbishment design processes, the framework can be employed in wider education and other project contexts to facilitate the balanced involvement of end users.
ABSTRACT
This paper addresses the energy efficiency issue in household appliances, which has led to the establishment of policies at a global level in favor of setting minimum energy performance standards (MEPS), which guarantee end users are able to select more efficient equipment. The countries of the United States, Brazil, Mexico, Chile, and the Community of the European Union were taken as references to review their policies and implementation strategies, in order to be compared with the Colombian panorama (at the market, technical and political levels). This allows the establishment of common aspects and differences related to the determination of energy consumption, adjusted volume, and formalization of efficiency ranges, and in the specific case of domestic refrigeration. Managing to distinguish the most relevant aspects for the successful adoption of these policies in Colombia. It is evident that the implementation of these guidelines has a positive impact on the market of the countries and communities of reference. Similarly, the MEPS are shown as a mechanism to regulate energy consumption in the residential sector.
ABSTRACT
Solar and wind power systems have been prime solutions to the challenges centered on reliable power supply, sustainability, and energy costs for several years. However, there are still various challenges in these renewable industries, especially regarding limited peak periods. Solar–wind hybrid technology introduced to mitigate these setbacks has significant drawbacks and suffers from low adoption rates in many geographies. Hence, it is essential to investigate the challenges faced with these technologies and analyze the viable solutions proposed. This work examined solar–wind hybrid plants’ economic and technical opportunities and challenges. In the present work, the pressing challenges solar–wind hybrids face were detailed through extensive case studies, the case study of enabling policies in India, and overproduction in Germany. Presently, the principal challenges of solar–wind hybrids are overproduction, enabling policies, and electricity storage. This review highlights specific, viable, proposed solutions to these problems. As already recorded in the literature, it was discovered that academic research in this space focuses majorly on the techno-economic and seemingly theoretical aspects of these hybrid systems. In contrast, reports and publications from original equipment manufacturers (OEMs) and engineering, procurement, and construction engineers (EPCs) are more rounded, featuring real-life application and implementation.
ABSTRACT
Health information needs to be accessible to all people, especially in emergencies and critical times of need such as the COVID-19 pandemic. Health information needs to be designed to meet the needs of a broad range of people, including Deaf and hard of hearing people who use American Sign Language. An Inclusive Design Thinking framework provides the process and structure for collaborative teams to work together to produce solutions that meet the needs of diverse audiences, including people with disabilities. Design Thinking is a human-centered problem-solving method that puts users at the center of the design process. Inclusive Design Thinking includes the end users throughout the design process, considers barriers users may face when accessing information, and seeks to remove these barriers through information design that is accessible to the intended audience. This case study provides the details of a collaborative effort by Centers for Disease Control and Prevention (CDC), Georgia Tech Center for Inclusive Design and Innovation (CIDI), ASL interpreters, Deaf and hard of hearing community members and advocates, and other community members to design and disseminate health information during the COVID-19 pandemic while addressing health literacy and digital accessibility best practices.
ABSTRACT
A rapid home-diagnostic test for SARS-CoV-2 was developed that automates the reagent delivery and washing steps required for an enzyme-linked immunosorbent assay (ELISA). The device is made of inexpensive polyethylene film and double-sided adhesive that is patterned, cut, and laminated together to create hollow channels. After sample is added, sample, reagents, and washing buffer are sequentially delivered to and washed from a detection zone on a nitrocellulose test strip, giving the end-user a visual readout in <15 minutes. A smartphone camera was used to capture images, and an analytical limit of detection of 35 PFU/mL was determined. When 22 untrained end-users were asked to visually identify a positive result, 95% correctly identified 150 PFU/mL and above as positive. © 2021 MicroTAS 2021 - 25th International Conference on Miniaturized Systems for Chemistry and Life Sciences. All rights reserved.
ABSTRACT
There is an increasing demand for electricity on a global level. Thus, the utility companies are looking for the effective implementation of demand response management (DRM). For this, utility companies should know the energy demand and optimal household consumer classification (OHCC) of the end users. In this regard, data mining (DM) techniques can give better insights and support. This work proposes a DM-technique-based novel methodology for OHCC in the Indian context. This work uses the household electricity consumption (HEC) of 225 houses from three districts of Maharashtra, India. The data sets used are namely questionnaire survey (QS), monthly energy consumption (MEC), and tariff orders. This work addresses the challenges for OHCC in energy meter data sets of the conventional grid and smart grid (SG). This work uses expert classification and clustering-based classification methods for OHCC. The expert classification method provides four new classes for OHCC. The clustering method is employed to develop eight different classification models. The two-stage clustering model, using K-means (KM) and the self-organizing map (SOM), is the best fit among the eight models. The result shows that the two-stage clustering of the SOM with the KM model provides 88% of overlap-free samples and 0.532 of the silhouette score (SS) mean compared to the expert classification method. This study can be beneficial to the electricity distribution companies for OHCC and can offer better services to consumers.
ABSTRACT
It is well documented that, in the United States (U.S.), the availability of Internet access is related to several demographic attributes. Data collected through end user network diagnostic tools, such as the one provided by the Measurement Lab (M-Lab) Speed Test, allows the extension of prior work by exploring the relationship between the quality, as opposed to only the availability, of Internet access and demographic attributes of users of the platform. In this study, we use network measurements collected from the users of Speed Test by M-Lab and demographic data to characterize the relationship between the quality-of-service (QoS) metric download speed, and various critical demographic attributes, such as income, education level, and poverty. For brevity, we limit our focus to the state of California. For users of the M-Lab Speed Test, our study has the following key takeaways: (1) geographic type (urban/rural) and income level in an area have the most significant relationship to download speed;(2) average download speed in rural areas is 2.5 times lower than urban areas;(3) the COVID-19 pandemic had a varied impact on download speeds for different demographic attributes;and (4) the U.S. Federal Communication Commission's (FCC's) broadband speed data significantly over-represents the download speed for rural and low-income communities compared to what is recorded through Speed Test. © 2022 Owner/Author.
ABSTRACT
With the development of technologies and the decrease of prices, the number of end-users that decide to invest in distributed energy resources (DERs) continuously grows. Despite the improvement of financial and environmental aspects of the power system operation, a growing share of DERs can cause numerous technical challenges for distribution system operators (DSOs). Besides the integration of DERs, the novel COVID-19 disease created additional challenges for DSOs in 2020 and 2021. Due to a large number of single-phase loads and DERs, the increased consumption, the number of nonlinear loads, and power electronic devices in a distribution network, many challenges are related to power quality (PQ). In this paper, realistic case studies that consider anomalies caused by the COVID-19 pandemic and integration of DERs are presented. By using pandapower and its newly developed extension, different PQ indicators are calculated and the values of voltage magnitude, voltage unbalance factor (VUF), and total harmonic distortion (THD) are compared through different scenarios. In addition, the impact of a transformer's vector group on the PQ indicators' propagation through the observed distribution network is analyzed. In a conclusion, the optimal vector group, that successfully mitigates or at least decreases the values of PQ indicators and their propagation is proposed. © 2022 IEEE.