Kinds Of Users Research Articles

Complex PM2.5 Pollution and Hospital Admission for Respiratory Diseases over Big Data in Cloud Environment

With the establishment of China’s national air quality monitoring network, large amounts of monitoring data are available for different kinds of users. How to process and use this big data is a tough problem for users: most users have limited computing power, and new data are collected at every moment. Cloud computing may be an efficient and low-cost way to solve this problem. This paper investigates a problem of a complex system: the impact of PM2.5 on hospitalization for respiratory diseases. A change-point detection method based on grey relation analysis was used to solve this problem. Daily air pollution monitoring data and patient data were used in this study. Our results showed that (1) PM2.5 pollution showed a positive correlation on hospital admission for respiratory disease; (2) most patients went to hospital 2 days after PM2.5 pollution events; and (3) male, children, and old people were significantly affected by PM2.5 pollution. Our study is of great significance to help the government formulate suitable policies to reduce the damage caused by PM2.5 pollution and help hospitals allocate medical resources efficiently.

TraceHub - A Platform to Bridge the Gap between State-of-the-Art Time-Series Analytics and Datasets

In this paper, we present TraceHub - a platform that connects new non-trivial state-of-the-art time-series analytics with datasets from different domains. Analytics owners can run their insights on new datasets in an automated setting to find insight's potential and improve it. Dataset owners can find all possible types of non-trivial insights based on latest research. We provide a plug-n-play system as a set of Dataset, Transformer pipeline, and Analytics APIs for both kinds of users. We show a usefulness measure of generated insights across various types of analytics in the system. We believe that this platform can be used to bridge the gap between time-series analytics and datasets by significantly reducing the time to find the true potential of budding time-series research and improving on it faster.

Online users' attitudes toward fake news: Implications for brand management

AbstractThis study examines brands' vulnerability to fake news. The rapid spread of online misinformation poses challenges to brand managers, whose brands are cocreated online, sometimes to the detriment of the brand. There is a need to identify the information sources that are likely to be trustworthy and to promote positive consumer attitudes toward brands. The data for this study were taken from a Flash Eurobarometer of 26,576 respondents across 28 European countries. Cluster analysis and partial least squares structural equation modeling were used to analyze the data and unveil users' attitudes toward fake news. The findings show that users' attitudes toward fake news differ among European countries. Younger and tech‐savvy users are more likely to recognize fake news and are consequently able to evaluate digital information sources without relying on policy interventions to limit the impact of fake news. Brand managers can use the findings of this study to better understand different kinds of users' susceptibility to fake news and reshape their social media branding strategies accordingly. It is hoped that this paper will encourage further research on brand management in relation to fake news and promote the widespread adoption of best practices in social media communication.

Evaluation of Industry 4.0 Data formats for Digital Twin of Optical Components

A wide range of software and hardware components are present in today’s production systems and plants using a variety of interfaces and data formats for information exchange on different levels of the system. To increase the traceability, the lifecycle management and providing a single point of source of component-specific data, the Digital Twin technology is proposed, linking different data sets tailored to the requirements of different kind of users (e.g., machines, technicians, logistics, manufacturing execution systems). The data exchange between entities in the manufacturing network relies on machine-readable, flexible and self-describing data formats. When implementing or integrating different components into complex systems, the interoperability challenge is a major concern to address by the system designers and becomes a central task for the creation and integration of Digital Twin technology. In this paper, we evaluate different formats that are used in real environments and create a requirements framework for an ideal format for exchanging flexible and self-describing data in context of optical components manufacturing process and their special requirements.

Proposal and testing goals-guided interaction for occasional users

The latest shifts in technology have brought about new kinds of users who occasionally access unfamiliar systems in new scenarios. This way of use should not request any learning curve. There have been many attempts to help this kind of users: agents, floating help, tooltips, direct video demonstrations, etc., elements that support the appealing direct manipulation style (DM), but add indeed an extra layer of supporting material over it. In this paper, we describe an analyse goals-guided Interaction, GGI, as the basis for a different approach. We do not expect the user to understand or use a metaphor but guide them throughout the whole interaction process. This help system is integrated in the interface. The user will be closely guided on the “what to do” and on the “how to do,” always according to their current goal. This no-previous-knowledge-required way of interaction shortens significantly the learning curve. In order to support this proposal, a complete study based on user testing is performed. The results show that, for non-expert occasional users, GGI is more efficient in time and less error prone than the classic Direct Manipulation. Participants also showed a strong preference for GGI. This research offers an alternative way of interaction for designers and developers of human-centric interactive systems who have occasional users as their main target users.

Spectrum Knowledge and Real-Time Observing Enabled Smart Spectrum Management

Spectrum is the indispensable resource for 5G wireless systems and beyond. The dynamic spectrum management (DSM) framework with spectrum sharing among different kinds of users is essential to satisfy the sustainable rapid increase of the bandwidth requirement. Based on the analysis of the DSM as well as the latent applications of the machine learning and artificial intelligence (AI) in the spectrum access, this paper will address the problem of incorporating intelligence into the spectrum management. Firstly, the spectrum opportunity (SOP) related information is layered into the spectrum data, the spectrum information and the spectrum knowledge based on the processing and abstractive level. The spectrum knowledge is formally defined as the extendible and scalable information to reason and predict the SOP usability as well as the outcome of the SOP occupancy. Then the smart spectrum model (SSM) is proposed with the spectrum knowledge as the key enabler and the coupled SOP exploration and exploitation as the core feature. Under the SSM framework, the spectrum knowledge and real-time observing (SKRO) enabled SOP exploration scheme is designed, which can make use of both the historical information and the real-time sensing information for smart SOP exploration. Extensive simulations are provided which demonstrate that the SKRO enabled SSM can achieve much better SOP utilization while satisfying the required legacy assurance. Specifically, in the low signal to noise environment, at least 16.55% gains on the SOP utilization ratio can be obtained compared with the DSM.

A QoS-aware virtual resource pricing service based on game theory in federated clouds

Recently, federated cloud platform has become a promising paradigm to provide cloud services for various kinds of users in a distributed manner. To compete for cloud users, it is critically important for each cloud provider to select an optimal price that best corresponds to their service qualities as well as remains attractive to cloud users. In this paper, we first formulate the pricing strategy of individual cloud provider as a constrained optimisation programming problem to analyse the behaviours of both cloud users and cloud providers. Then, we present game-based model which introduces a set of virtual resource agents to help providers adjusting their prices with aiming at achieving a global optimal solution. Theoretical analysis is present to prove the validity and effectiveness of the proposed game model, and extensive experiments are conducted in a real-world cloud platform to evaluate its performance. The experimental results show that the proposed pricing model can significantly improve the resource revenue for cloud providers and provide desirable quality-of-service (QoS) for user tasks in terms of various performance metrics.

A review of marketing and promotion of library and information products and services

Internet is a huge source of information for any kind of users. Today, information is made an essential component in our daily life. The most importantly, it provides the desired information in 24/7 mode without wasting the time and in less efforts. In this connection, the physical libraries have also much and unique collection of different kind of information but the digital age of information brings challenges in front of it. Hence, we need to promote and market the products and services in a better way that a library contains so that the users of the library attract the services and products and use the library.

Distributed vs centralized game theory-based mode selection and power control for D2D communications

The exponential growth cellular networks traffic has driven academia and industry to consider new channel access methods in addition to the conventional infrastructure-based access via cellular nodes. Long-Term Evolution-Advanced (LTE-A) techniques are suggested by the 3rd generation partnership project (3GPP), in order to offer both higher spectrum efficiency and data rate. In fact, LTE-A has attracted a great attention in the cellular domain, since it improves the LTE by proposing a lot of variety in terms of new techniques such as carrier aggregation, multiple-input multiple-output (MIMO), device-to-device (D2D) communications, etc. Notably, D2D communications underlaid offer several advantages for the LTE-A, as wireless peer-to-peer services and higher spectral efficiency. In LTE-A, the power control and resource allocation algorithms can generally be categorized into two classes: centralized and distributed approaches. In fact, power control and resource allocation are performed by the base station in centralized approach and by the UEs in distributed one.In this investigation, we propose first a mode selection approach based on a predetermined SINR threshold, which is required by each kind of user: cellular and D2D users. The amount of minimum and maximum power are then derived to fulfill the predetermined requirements, by limiting the interference created by underlaid D2D users. Unlike the previous works, this paper provides a mathematical demonstration to achieve the minimum amount of power (Pareto power), which satisfies the requirements imposed by both users. Second, a centralized power control approach, which aims to generalize a classical approach for more than one cellular user is proposed. Third, a distributed power control approach is modeled as a non-cooperative pure game between the different types of users in order to maximize the two cellular and D2D utility functions. Finally, these proposed centralized and distributed power control approaches are compared with a classical centralized one, in terms of coverage probabilities for both cellular and D2D users.

Why Software-Defined Radio (SDR) Matters in Healthcare?

Background: Wireless Body Area Networks (WBANs) have been drawing noteworthy academic and industrial attention. A WBAN states a network dedicated to acquire personal biomedical data via cutting-edge sensors and to transmit healthcare-related commands to particular types of actuators intended for health purposes. Still, different proprietary designs exist, which may lead to biased assessments. This paper studies the role of Software-Defined Radio (SDR) in a WBAN system for inpatient and outpatient monitoring and explains to health professionals the importance of the SDR within WBANs. Methods: A concern related to all wireless networks is their dependence on hardware, which limits reprogramming or reconfiguration alternatives. If an error happens in the equipment, firmware, or software, then, typically, there will be no way to fix system vulnerabilities. SDR solves many fixed-hardware problems with other benefits. Results: SDR entails more healthcare domain dynamics with more network convergence in agreement with the stakeholders involved. Then the SDR perspective can bring in innovation to the healthcare subsystems’ interoperability with recombination/reprogramming of their parts, updating, and malleability. Conclusion: SDR technology has many utilizations in radio environments and is becoming progressively more widespread among all kinds of users. Nowadays, there are many frameworks to manipulate radio signals only with a computer and an inexpensive SDR arrangement. Moreover, providing a very cheap radio receiver/transmitter equipment, SDR devices can be merged with free software to simplify the spectrum analyses, provide interferences detection, deliver efficient frequency distribution assignments, test repeaters' operation while measuring their parameters, identify spectrum intruders and characterize noise according to frequency bands.

Services for Users with Disabilities in Joint Libraries in China

China has a large population with disabilities. In China, there may be varieties of barriers for disabled users to access library resources and services. Joint libraries are a new type of libraries constructed by local government and one or more colleges (universities), playing a dual role as both academic library and public library. Therefore, the users of joint libraries include not only college students and teachers, but also other people from all walks of life. Undoubtedly, the resources and services of these joint libraries must be provided for all kinds of users. Since 1997, more than ten joint libraries have been constructed and opened in China. In this article, we first briefly discussed the causes for the barriers to users with disabilities in libraries. Second, taking joint libraries as a case, we focused on the services to remove barriers and to ensure information equity for disabled people. Provision of equal services for disadvantaged groups is an essential indicator of joint libraries. The present article may provide recommendations for the future sustainable development of joint libraries in China and other developing counties.

How players across gender and age experience Pok\xe9mon Go?

The purpose of this study is to provide insights into player experiences and motivations in Pokémon Go, a relatively new phenomenon of location-based augmented reality games. With the increasing usage and adoption of various forms of digital games worldwide, investigating the motivations for playing games has become crucial not only for researchers but for game developers, designers, and policy makers. Using an online survey (N = 1190), the study explores the motivational, usage, and privacy concerns variations among age and gender groups of Pokémon Go players. Most of the players, who are likely to be casual gamers, are persuaded toward the game due to nostalgic association and word of mouth. Females play Pokémon Go to fulfill physical exploration and enjoyment gratifications. On the other hand, males seek to accomplish social interactivity, achievement, coolness, and nostalgia gratifications. Compared to females, males are more concerned about the privacy aspects associated with the game. With regard to age, younger players display strong connotation with most of the studied gratifications and the intensity drops significantly with an increase in age. With the increasing use of online and mobile games worldwide among all cohorts of society, the study sets the way for a deeper analysis of motivation factors with respect to age and gender. Understanding motivations for play can provide researchers with the analytic tools to gain insight into the preferences for and effects of game play for different kinds of users.

A service recommendation algorithm with the transfer learning based matrix factorization to improve cloud security

Recommendation system (RS) is designed to provide personalized services based on the users’ historical data. It has been applied in various fields and is expected to recommend the suitable services for the different kinds of users. Considering the importance of individual privacy, current users gradually tend not to expose personal information. This means RS may face the highly sparse datasets in the fields of cloud security. In general, the accuracy of recommendation will be improved with the growth of individual data, but the cold start problem is exactly in this contradictory phenomenon: this question evolves to produce sufficiently accurate recommendation result under the data scarcity problem. RS has to recommend services for the rarely historical data users and the latent users might drain along with the production of counter effects. To alleviate data scarcity problem in cloud security environment, this work is to introduce similar domain knowledge based on the transfer learning. Besides, the content and location based methods have been proved that these ideas work under this situation. So, this work also employs latent dirichlet allocation (LDA) to analysis the service descriptions and explore the relationship between the content and location information. In this framework, the suitable combination of LDA and word2vec models will balance the accuracy and speed which benefit service recommendation particularly. The related experiments demonstrate the effectiveness on the real word dataset. It can be found that the transfer learning based word2vec model shows the potentiality to explore the relationship between topic words, and improve the LDA algorithm from the content relationship. This proves that in both cold start environment and warm start environment, the proposed algorithm is more robust than other model-based state-of-art methods.

Internet Addiction Disorder: Internet Gaming Disorder in a Nonclinical Sample Of Moba And Mmorpg Videoplayers

This study concentrates on two kinds of video games, Massive Online Battle Arena and Massive Multiplayer Online Role Play Game, and examines the scores obtained by the subjects in the sample. Score analyses pointed out that they do not exceed the respective cutoff scores for each scale. The sample was divided into three clusters to differentiate three kinds of users: nonproblematic, problematic, and “addicted” players. The study highlights that the variable “video game typology” relates to some personality traits. Players who excessively use them tend to experience relatively more negative emotions (anxiety and depression), avoid socioemotional involvement, and report bizarre and culturally incongruent thoughts (accompanied by the respective behavioral displays).

Online Expert-Based Prediction for Cognitive Radio Secondary Markets

The growing importance of wireless communications drives an increasing interest in dynamic access to spectrum resources. This requires efficient management policies that allow spectrum sharing between licensed primary users (PU) and unlicensed secondary users (SU). On such scenario, PUs shall preserve their usage priority right over any SU. Also, no SU shall interfere on any PU. Technical viability can be achieved through Cognitive Radio devices that adjust their operating parameters adaptively. After discussing several economic and technical models to achieve efficient spectrum sharing, we propose an on-demand secondary market model regulated by a spectrum broker who controls resource allocation. This model provides economic incentives for both kind of users to cooperate: SUs are charged by the broker on behalf of PUs for resource utilization but are indemnified if expelled to ensure PU priority. We describe the main characteristics of such a system and address the question of what allocation decisions should the broker take in order to achieve economic benefit regardless of users behavior. Several online expert-based no-regret algorithms are proposed to guide the decision taking process and evaluated under different user behavior patterns. Their results are compared with the ones achieved by dynamic programming to assess its convenience.

WebGIS-based suitability evaluation system for Chinese table grape production

China is the largest worldwide producer of table grape, and table grape production has expanded throughout the country with technology advance. However, the vineyards in different regions show discrepant performance due to the multiple natural, locational, economic and technological conditions. This paper aims to develop a WebGIS-based suitability evaluation system for table grape production, and implement efficient and real-time assessment for grape production suitability. Firstly, different kinds of users’ requirements were analyzed, base on which the function modules and the system architecture were designed. Analytic Hierarchy Process (AHP) was applied to make the suitability evaluation for the system and the suitability indicators concerning economic benefits, climate, location factors and soil conditions were established. Finally, the system was implemented and then applied in suitability evaluation in sampled areas of China. The system application showed the main functions of the system have been realized and the system can satisfy users’ requirements. The evaluation results show that vineyards with high suitability of table grape production are distributed both in traditional grape planting areas and southern areas where used to be deemed unsuited for grape cultivation. The reasons may be that some areas in south China own superiority in economic conditions, location and the technology.

Certificates for High-Quality Cartographic Products

Abstract. The study is inspired by questions that students and teachers ask during past experiments that the authors have carried out. The users who represent Bulgarian and Croatian schools are invited to evaluate existing maps and draw their own maps. This research focuses on cartographical mistakes and how they impact user’s understanding of the map. We don’t aim to show or explain all cartographic mistakes. The examples are chosen arbitrarily and do not claim to provide an exhaustive list of the problems.Online maps which hold a significant market share provide cartographic information in various thematic areas for different kind of users. Producers of all world map platforms try to cover all necessary information in a similar way and do not consider user’s age, cultural, professional and knowledge diversity. Similar behaviour is observed with the production of traditional maps where various cartographic mistakes can be pointed.To respond to these observations, Bulgarian and Croatian cartographic associations created rules and conditions under which a cartographic product can receive a Certificate for high-quality map / atlas / other cartographic product.

On the Performance of Network NOMA in Uplink CoMP Systems: A Stochastic Geometry Approach

To improve the system throughput, this paper proposes a network non-orthogonal multiple access (N-NOMA) technique for the uplink coordinated multi-point transmission (CoMP). In the considered scenario, multiple base stations collaborate with each other to serve a single user, referred to as the CoMP user, which is the same as for conventional CoMP. However, unlike conventional CoMP, each base station in N-NOMA opportunistically serves an extra user, referred to as the NOMA user, while serving the CoMP user at the same bandwidth. The CoMP user is typically located far from the base stations, whereas users close to the base stations are scheduled as NOMA users. Hence, the channel conditions of the two kinds of users are very distinctive, which facilitates the implementation of NOMA. Compared to the conventional orthogonal multiple access-based CoMP scheme, where multiple base stations serve a single CoMP user only, the proposed N-NOMA scheme can support larger connectivity by serving the extra NOMA users, and improve the spectral efficiency by avoiding the CoMP user solely occupying the spectrum. A stochastic geometry approach is applied to model the considered N-NOMA scenario as a Poisson cluster process, based on which insightful closed-form or quasi closed-form analytical expressions for outage probabilities and ergodic rates are obtained. Numerical results are presented to show the accuracy of the analytical results and also demonstrate the superior performance of the proposed N-NOMA scheme.

Between broadcast yourself and broadcast whatever: YouTube’s homepage as a synthesis of its business strategy

YouTube is a company representative of its original context, Web 2.0, that originally positioned itself as an open and collaborative platform to broadcast videos created by all kinds of users; their slogan was, and remains, Broadcast yourself. The acquisition of YouTube by Google introduced it in the search for profit in the framework of OTT (over the top) communication. The YouTube homepage reveals the successive business policies followed by the platform. In this work we analyze the evolution of the unlogged homepage of YouTube Spain between 2009 and 2018. We observe the gradual disappearance of the videos produced by private users and its replacement by those made by professional users (youtubers) and cultural industries. There is a remarkable parallelism between the implementation of business models and the greater or lesser recommendation of video from one kind of user or another.

Game theory for SINR-based power control in device-to-device communications

Device-to-Device (D2D) communication underlaying cellular network can improve the spectrum efficiency due to both direct proximity communication and frequency reuse. However, such performance improvement is influenced by the co-channel interference and time varying nature of channels. The purpose of this paper is to study and to investigate both pure and mixed games, using two utility functions game for CUE and DUE, in order to enhance the system spectral efficiency and increase the SINR. Unlike previous works which have dealt with potential and dynamic games etc., we propose in this paper a pure and mixed game. The most important, is that the used game and utility function of each user (CUE and DUE) should be appropriately aligned to the global objective for pure and mixed games and can meet this requirement. To tackle this problem, we first define a pure and mixed strategies non-cooperative games, in order to model the interactions between the cellular and D2D users. Indeed, each kind of users (D2D and Cellular users) is modeled as a rational player, aiming at maximizing its own net utility, while a Quality of Service (QoS), in terms of Signal-to-Interference plus-Noise-Ratio (SINR) threshold, should be satisfied for both D2D and cellular users. Second, for each kind of game: pure and mixed, a closed form of NE amount of power is derived, where existence and uniqueness of the Nash equilibrium (NE) are also investigated. Finally, simulations are conducted to compare the proposed framework of the two kinds of proposed PC mechanisms: centralized and distributed according to the two kinds of users: D2D and cellular users.