ABSTRACT
The transformation of classical education into distance education has become increasingly relevant, especially given the challenging conditions posed by the COVID-19 pandemic and military operations in our country. In these circumstances, distance learning requires practical educational materials that are easily accessible to students. This paper proposes criteria and indicators for selecting digital tools that can facilitate group work with educational content in distance learning. We analyzed the tools available on the Microsoft 365, Google Workspace, and Cisco Webex platforms and evaluated their suitability for managing students' group work in distance learning in institutions of higher education at various stages of the learning process including setting tasks, designing the learning environment, facilitating group interaction and communication, managing educational content and files, promoting teamwork and productivity, and presenting results. To obtain expert assessment of the defined criteria and indicators, we engaged seventeen researchers and educators who have practical experience using digital tools in distance learning. Our study identified three important criteria for selecting digital tools for group work with educational content, namely: design, functional-technological, education -communication ones. We determined the weight of the indicators for these criteria and assessed digital tools for group work with educational content in distance learning. Digital tools such as Microsoft 365 and Google Workspace was found to be more suitable for providing group work of students in a distance learning, while Cisco Webex was found to be the most suitable tool for organizing real-time group work. Other digital tools for group work of students in distance learning can be evaluated according to defined criteria and indicators.
ABSTRACT
World Health Organization (WHO) studies indicate that people with pre-existing diseases are prone to suffer the severity of the effects of COVID-19 in case of infection. This work presents a mobile application development through open-source software and machine learning techniques for the prediction of the COVID-19 severity in an individual based on pre-existing disease information. For the prediction of the severity and to determine the possibility that an individual ends up in an intensive care unit (ICU), we set a machine learning algorithm, which resulted in a higher probability of prediction when the user undergoes cases of pre-existing diseases, with an efficiency rate of 98 %. We carried out load and stress testing to verify the processing performance, battery consumption, startup latency, and maximum amount of user connections supported by the application, complemented with a wristband for individual's real-time monitoring to attain low battery consumption when using public cloud services and low-power technologies for the connection. © 2023 IEEE.
ABSTRACT
Cloud technology usage in nowadays companies constantly grows every year. Moreover, the COVID-19 situation caused even a higher acceleration of cloud adoption. A higher portion of deployed cloud services, however, means also a higher number of exploitable attack vectors. For that reason, risk assessment of the cloud environment plays a significant role for the companies. The target of this paper is to present a risk assessment method specialized in the cloud environment that supports companies with the identification and assessments of the cloud risks. The method itself is based on ISO/IEC 27005 standard and addresses a list of predefined cloud risks. Besides, the paper also presents the risk score calculation definition. The risk assessment method is then applied to an accounting company in a form of a case study. As a result, 24 risks are identified and assessed within the case study where each risk included also exemplary countermeasures. Further, this paper includes a description of the selected cloud risks.
ABSTRACT
Development of applications based on open API is becoming increasingly popular today. Innovative projects using these technologies provide new opportunities for real-time human health monitoring. Such opportunities are also implemented using Internet of Things (IoT), artificial intelligence (AI) and cloud computing technologies. In the study, we developed an application based on open APIs using smart gadgets and meteorological geographic information system in the process of generating a message about the dangers to human health associated with: the presence of pollen in the air (grass pollen, birch pollen and olive pollen) indicating the level of its concentration in the air;problems with air quality, if the air quality indicator exceeds the permissible standards. The addition of such functions expands the possibilities to provide timely information about potential risks and threats and, accordingly, is an "anthropo-geo-sensor-digital"prerequisite for effective decision-making, prevailing. The implementation of this IoT system has significant methodological and technological potential that can be used to improve the efficiency of Healthcare, both in extreme conditions and in conditions of sustainable existence. First of all, this is relevant during and after the COVID-19 pandemic. The system we have developed can also be seen as one of the ways to innovate in Healthcare, in the educational process in institutions of higher education and in further scientific research on this topic. Further research in this area may be related to data processing in Healthcare systems based on machine learning, deep learning. © 2023 Copyright for this paper by its authors.
ABSTRACT
Cloud technology usage in nowadays companies constantly grows every year. Moreover, the COVID-19 situation caused even a higher acceleration of cloud adoption. A higher portion of deployed cloud services, however, means also a higher number of exploitable attack vectors. For that reason, risk assessment of the cloud environment plays a significant role for the companies. The target of this paper is to present a risk assessment method specialized in the cloud environment that supports companies with the identification and assessments of the cloud risks. The method itself is based on ISO/IEC 27005 standard and addresses a list of predefined cloud risks. Besides, the paper also presents the risk score calculation definition. The risk assessment method is then applied to an accounting company in a form of a case study. As a result, 24 risks are identified and assessed within the case study where each risk included also exemplary countermeasures. Further, this paper includes a description of the selected cloud risks. © 2022 Slovak Academy of Sciences. All rights reserved.
ABSTRACT
The widespread adoption of deep learning (DL) solutions in the healthcare organizations is obstructed by their compute intensive nature and dependability on massive datasets. In this regard, cloud-services such as cloud storage and computational resources are emerging as an effective solution. However, when the image data are outsourced to avail such services, there is a privacy concern that the data should be kept protected not only during transmission but during computations as well. To meet these requirements, this study proposed a privacy-preserving DL (PPDL) scheme that enable computations without the need of decryption. The encryption is based on perceptual encryption (PE) that only hides the perceivable information in an image while preserves other characteristics that are necessary for DL computations. Precisely, we have implemented a binary classifier based on EfficientNetV2 for the COVID-19 screening in the chest X-ray (CXR) images. For the PE algorithm, the suitability of two pixel-based and two block-based PE methods was analyzed. The analysis have shown that when global contents are left unmodified (pixel-based PE), then the DL-based model achieved the classification accuracy same as that of the plain images. On the other hand, for block-based PE algorithms, there is up to 3% drop in the model's accuracy and sensitivity scores. © 2023 IEEE.
ABSTRACT
Over the past twelve years, cloud systems have significantly changed business processes in all areas of business. Companies are using cloud services as a key factor in completing their digital transformation, and the COVID pandemic has further accelerated this task. The cloud is emerging as a top management agenda item as companies move from a separate approach to a more holistic, end-to-end digital transformation driven by the cloud. Cloud services save businesses time and money by increasing productivity, improving collaboration, and driving innovation. Now—during the coronavirus crisis, more than ever, cloud services are vital to help companies re-discover, reinvent and overcome uncertainty. Cloud services range from data storage to functional software, including accounting software, customer service tools, and remote desktop hosting. These services can be divided into three groups: infrastructure as a service (IaaS), platform as a service (PaaS) and software as a service (SaaS). This article is devoted to an analytical overview of modern digital cloud services, and the services they provide that can be applied in all areas of business. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
Over the past twelve years, cloud systems have significantly changed business processes in all areas of business. Companies are using cloud services as a key factor in completing their digital transformation, and the COVID pandemic has further accelerated this task. The cloud is emerging as a top management agenda item as companies move from a separate approach to a more holistic, end-to-end digital transformation driven by the cloud. Cloud services save businesses time and money by increasing productivity, improving collaboration, and driving innovation. Now—during the coronavirus crisis, more than ever, cloud services are vital to help companies re-discover, reinvent and overcome uncertainty. Cloud services range from data storage to functional software, including accounting software, customer service tools, and remote desktop hosting. These services can be divided into three groups: infrastructure as a service (IaaS), platform as a service (PaaS) and software as a service (SaaS). This article is devoted to an analytical overview of modern digital cloud services, and the services they provide that can be applied in all areas of business. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
Adoption of cloud services has an increasing trend for many years already and no indication that it should change in close future has occurred. Moreover, cloud consumption has been further enhanced due to the COVID-19 situation since a great number of employees started to work from home and therefore, they need to access resources over the internet. This article describes the performed analysis of official data provided by the European Union on the consumption of cloud services in the member countries. The analysis particularly focused on comparing the cloud consumption in the Czech Republic, Visegrad Group and European Union in total. The consumption was compared based on multiple criteria - primarily on cloud service types, organization types, consumption trends. The analysis was conducted over sets of biannual data (2014, 2016, 2018, and 2020) that are available on the Eurostat site for all the European Union countries. The comparison showed that the level of cloud consumption differs across and that the average consumption for the European Union is higher than in the Czech Republic and in Visegrad Group. Besides, the comparison revealed that consumption in the Czech Republic is slightly higher than in Visegrad Group. Such pattern in the comparison between the three subjects was present in the majority of comparisons and therefore it might be stated that the Czech Republic and Visegrad Group are behind the average cloud consumption in European Union. This article is closely related to the Information Management as one of the aims of the E&M Economics and Management journal.
ABSTRACT
A service (social) robot is defined as the Internet of Things (IoT) consisting of a physical robot body that connects to one or more Cloud services to facilitate human-machine interaction activities to enhance the functionality of a traditional robot. Many studies found that anthropomorphic designs in robots resulted in greater user engagement. Humanoid service robots usually behave like natural social interaction partners for human users, with emotional features such as speech, gestures, and eye-gaze, referring to the users’ cultural and social background. During the COVID-19 pandemic, service robots play a much more critical role in helping to safeguard people in many countries nowadays. This paper gives an overview of the research issues from technical and social-technical perspectives, especially in Human-Robot Interaction (HRI), emotional expression, and cybersecurity issues, with a case study of gamification and service robots. © 2022, Springer Nature Switzerland AG.
ABSTRACT
The development of computer network technology to promote the development of all walks of life, and the rapid development of cloud computing industry is to let a lot of industry see the advantages of the development of network technology, even in COVID - 19 outbreak of the moment, still did not stop the development of cloud computing industry, whether it is a traditional industry, or for the computer industry, Cloud management, cloud services and cloud technology are the main directions of future development. With the rapid development of Internet and information technology, cloud desktop technology based on cloud service technology is becoming more and more mature, and provides strong support for modern mobile office. For the information teaching of colleges and universities, the computer laboratory as the main means at any time should pay attention to the improvement of the degree of information teaching, and the emergence and application of cloud desktop technology can effectively solve the drawbacks of traditional computer laboratory management. This paper focuses on the application of cloud desktop technology in the scientific management of university computer laboratories. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
With the strain on healthcare infrastructure and healthcare workers due to the ongoing COVID'19 pandemic, the need for novel ways to simplify the interaction between patients and physicians has increased. The aim is mainly to reduce face-to-face interactions and free more time and resources for those who urgently need it. This paper presents a Telemedicine system which can be used as an alternative method to a doctor's visit. The proposed system is considered as an interface that remotely connects the patient and the doctor. The system regularly measures and uploads readings from the patient to a database which the doctor can remotely review to decide on the state of the patient. The whole system is based on the internet of medical things (IoMT). In the proposed system, sensors collect and send data over the internet using the WIFI module connected to a node MCU controller. The developed prototype uses two sensors, one is used to measure both the percentage of oxygen in the blood and heart rate while the other sensor measures the temperature of the human body. The aim of this work is to help patients, by offering them this solution which can help them get the care they require from the comfort of their home and at the same time help doctors remotely give them the suitable treatment while reducing the need for unnecessary face-to-face interactions. © 2022 IEEE.
ABSTRACT
In the methodology part of this study, we introduced a combined “AHP(blocks) and Entropy” approach for improving of Multi-Criteria Decision Making (MCDM) for Cloud Services (CS) selection. On this basis, we optimize the combination of professional experts’ opinion and objectivity of entropy criteria weighting. In this second part, we test our findings on an existing universal dataset with Quality of Service (QoS) and Quality of Experience (QoE) criteria and adapting for the needs of individual users and small education organisations under conditions of COVID-19 pandemics. © 2022, Springer Nature Switzerland AG.
ABSTRACT
At present, the world economy is in recession, especially under the impact of the Covid-19 epidemic, China's economy has also been greatly impacted. In this context, the disposable personal income of residents has also declined to varying degrees. More and more people choose economical life. If they can buy a used car in good condition at a good price, they are less likely to buy a brand new one. Under such a consumption concept, China's demand for second-hand cars is increasing. However, although China's second-hand car industry has developed for more than 30 years and the market scale has gradually expanded, there are still many problems behind the prosperity of the second-hand car market. These problems have existed for a long time, leading to a lot of disputes, unhappiness, disappointment, and even threats to the lives of consumers. These long-term problems also affect the virtuous circle of the second-hand car market, and hinder the healthy development of China's economy to a certain extent. In the past, research work mainly focused on the role of new policies, relevant laws and vehicle management and traffic management functions, this paper introduces the blockchain technology, which has the advantages of non tampering, transparency and traceability. This paper attempts to use blockchain technology as an auxiliary means to solve the long-standing problems in the used car market. This paper proposes a framework of used car trading based on blockchain in cloud service environment, and explains the working principle of the framework. Finally, the future research work is prospected. © 2021 IEEE.
ABSTRACT
During the breakout of coronavirus disease (COVID-19), cloud computing applications provide great convenience and assistance for people, enterprises, and government units. So far, studies of the priority of cloud services under disastrous situations are relatively scant. This research thus examines supportive cloud services which influence the sustainability of people and organizations. An empirical study was performed using SMARTER method with data collected from industry experts. The results conclude a relative priority map of the cloud services facing pandemics. Research implications and suggestions are then elaborated. © 2021 International Consortium for Electronic Business. All rights reserved.
ABSTRACT
Cloud computing plays an important role in many applications today. There is a lot of machine learning as a service that provides models for users' prediction online. However, in many problems which involve healthcare or finances, the privacy of the data that sends from users to the cloud server needs to be considered. Machine learning as a service application does not only require accurate predictions but also ensures data privacy and security. In this paper, we present a novel secure protocol that ensures to compute a scalar product of two real number vectors without revealing the origin of themselves. The scalar product is the most common operation that used in the deep neural network so that our proposed protocol can be used to allow a data owner to send her data to a cloud service that hosts a deep model to get a prediction of input data. We show that the cloud service is capable of applying the neural network to make predictions without knowledge of the user's original data. We demonstrate our proposed protocol on an image benchmark dataset MNIST and an real life application dataset - COVID-19. The results show that our model can achieve 98.8% accuracy on MNIST and 95.02% on COVID-19 dataset with very simple network architecture and nearly no reduction in accuracy when compares with the original model. Moreover, the proposed system can make around 120000 predictions per hour on a single PC with low resources. Therefore, they allow high throughput, accurate, and private predictions. © 2021 IEEE.
ABSTRACT
The intensive development of information systems and communication infrastructures has led to the emergence of new approaches and new tools for their management. Cloud services, virtualization technologies and software-based management tools are actively used today for building modern information systems which provides additional opportunities for managing components of these systems and for expanding such systems abilities. The use of such approaches and tools can provide a solution to the complex of problems faced by education institutions today, presenting new methods of distance learning and new forms of practical training. The balanced use of virtualization technologies and software-based control tools allows building distributed laboratory complexes of a new generation which will provide new possibilities for using the equipment that is available in educational institutions. The use of such complexes in the educational process allows not only to instill in students the skills of managing the configurations of communication infrastructures that are especially relevant today, but also to organize, in addition to traditional laboratory work, new forms of contactless practical classes. When conducting such classes, students get the opportunity to fully-functional remote access to the virtual and physical components of the complex, which is especially important for organizing the educational process in modern conditions associated with the COVID-19 pandemic. The article discusses modern approaches to the construction of software-controlled communication infrastructures, tools for software-based management of their components and also, an example of the implementation of these approaches and such tools usage in the construction of a distributed laboratory complex for a higher educational institution. The main advantages of the approach based on the use of hypervisors and emulators are presented, the experience of its deployment in the modernization of the laboratory complex for a IRIT-RTF UrFU is considered. © 2021 Institute of Physics Publishing. All rights reserved.
ABSTRACT
This paper presents a more detailed concept of Human-Robot Interaction systems architecture. One of the main differences between the proposed architecture and other ones is the methodology of information acquisition regarding the robot's interlocutor. In order to obtain as much information as possible before the actual interaction took place, a custom Internet-of-Things-based sensor subsystems connected to Smart Infrastructure was designed and implemented, in order to support the interlocutor identification and acquisition of initial interaction parameters. The Artificial Intelligence interaction framework of the developed robotic system (including humanoid Pepper with its sensors and actuators, additional local, remote and cloud computing services) is being extended with the use of custom external subsystems for additional knowledge acquisition: device-based human identification, visual identification and audio-based interlocutor localization subsystems. These subsystems were deeply introduced and evaluated in this paper, presenting the benefits of integrating them into the robotic interaction system. In this paper a more detailed analysis of one of the external subsystems-Bluetooth Human Identification Smart Subsystem-was also included. The idea, use case, and a prototype, integration of elements of Smart Infrastructure systems and the prototype implementation were performed in a small front office of the Weegree company as a decent test-bed application area.