Different Kinds Of Users Research Articles

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.

Cloud storage–based personalized sports activity management in Internet plus O2O sports community

Cloud storage–based personalized sports activity management in Internet plus O2O sports community

User-Centered Predictive Model for Improving Cultural Heritage Augmented Reality Applications: An HMM-Based Approach for Eye-Tracking Data

Today, museum visits are perceived as an opportunity for individuals to explore and make up their own minds. The increasing technical capabilities of Augmented Reality (AR) technology have raised audience expectations, advancing the use of mobile AR in cultural heritage (CH) settings. Hence, there is the need to define a criteria, based on users’ preference, able to drive developers and insiders toward a more conscious development of AR-based applications. Starting from previous research (performed to define a protocol for understanding the visual behaviour of subjects looking at paintings), this paper introduces a truly predictive model of the museum visitor’s visual behaviour, measured by an eye tracker. A Hidden Markov Model (HMM) approach is presented, able to predict users’ attention in front of a painting. Furthermore, this research compares users’ behaviour between adults and children, expanding the results to different kind of users, thus providing a reliable approach to eye trajectories. Tests have been conducted defining areas of interest (AOI) and observing the most visited ones, attempting the prediction of subsequent transitions between AOIs. The results demonstrate the effectiveness and suitability of our approach, with performance evaluation values that exceed 90%.

Business driven automation testing framework

Due to versatile growth of software industry, we need to invent and adapt new technologies to reduce the production cost and to increase the quality. Now a days the industry is moving towards the 100% of automation testing and is being done by the different kind of users. The same test script will be executed by the domain expert instead of a technical expert, so we can’t expect him to understand the complexity of scripts and to relate the test script with business scenarios. To simply the users view of automation testing we need a layer to hide the technical implementation and to introduce some simplified way to understand the test script and relate with business scenarios, if needed he should be able to modify the test scripts without having the technical knowledge. The gap between the customers’ expectations and the actual product behavior will be reduced using this proposed approach.

A flexible data acquisition system for storing the interactions on mashup user interfaces

Nowadays, mashups applications are growing in popularity. They are accessible by cross-device applications, supporting multiple forms of interaction in cloud environments. In general, mashups manage a huge amount of heterogeneous data from different sources and handle different kinds of users. In this respect, mashup User Interfaces are becoming one of the most important pieces in many kinds of current management systems, such as for certain geographic or environmental information systems working on the Internet. In this type of systems, the user interface plays a particular role due to the huge variety of components or apps that the users need to manage at the same time. However, currently, there has been scant attention paid to the management of the user’s interaction with mashups interfaces. This goal involves the need of having important, well-constructed tools and methods conducting the data acquisition process for managing properly: (a) the interaction over the mashup user interfaces, at the front-end side; (b) the storage of the interaction in relational databases; and (c) well-supported microservices structures handled in the cloud. The fact of having valuable and flexible data acquisition processes encourages the deployment of others important issues of the interaction management, i.e., data searching, data mining, marketing, security, accessibility, usability or traceability of interaction data, among others. In this article, we present a flexible Data Acquisition System capable of capturing the human-computer interactions performed by users over mashup (User) Interfaces with the aim of storing them in a relational database. Firstly, the morphology of traditional mashup applications, their specifications and the relevant information that surrounds an interaction have been studied. Thereupon, a data acquisition system that stores user interaction on mashup based on such specifications was constructed. To achieve that purpose, an architecture of microservices was also designed in the cloud to detect, acquire, and collect the interactions performed over this kind of interfaces. The whole process is ready for acquiring internal data of the information system as well as context information and location awareness. To validate the data acquisition system, some tests on empirical case studies have been developed. Efficiency and effectiveness have also been determined by evaluating the performance of the acquisition system during different load tests. Finally, in order to ensure the software quality, a continuous integration strategy for software development and an easy management of the code have been used, facilitating the software maintenance alongside the microservice architecture, where functionalities are well encapsulated.

An energy information system for retrofitting smart urban areas

This paper presents the ENERSI platform, an energy information system that provides advanced energy services by means of integrating energy related data from multiple domains and formats using Semantic Web technologies. The platform services can provide qualified information at different scales – from building to district, city and region – to different kind of users – such as building owners, city planner, energy agencies, architects, contractors and consultants – to take decisions aimed at improving the building energy performance in their respective decision-making realms.

A Buffering and Switching Scheme for Admission Control in Cognitive Radio Networks

Cognitive radio users (i.e., secondary users) experience a lot of performance degradation due to the continuous appearance of primary users in the cognitive radio networks. To minimize the effect of this phenomenon, we propose a buffering and switching scheme for admission control to enhance the performance of the secondary users. In the proposed scheme, the secondary users are competing for the available channels (i.e., licensed and unlicensed) with two different kinds of users and utilizing different kinds of buffers to reduce the blocking probability for newly arriving users and dropping probability for ongoing connection. The system is modeled using a multi-dimensional continuous-time Markov chain, where the performance metrics are obtained. The numerical results are verified using a discrete event simulations.

Evaluating the impact of MeSH (Medical Subject Headings) terms on different types of searchers

To what extent do MeSH terms improve search effectiveness for different kinds of users? We observed four different kinds of information seekers using an experimental information retrieval system: (1) search novices; (2) domain experts; (3) search experts and (4) medical librarians. Participants searched using either a version of the system in which MeSH terms were displayed or another version in which they had to formulate their own terms. The information needs were a subset of the relatively difficult topics originally created for the Text REtrieval Conference (TREC). Effectiveness of retrieval was based on the relevance judgments provided by TREC. The results of the study provide experimental evidence of the usefulness of MeSH terms and further identify the significant relationship between the user characteristics of domain knowledge and search training and the search performance in an interactive search environment.

Passive and active methods for Radon pollution measurements in historical heritage buildings

Radon is a dangerous pollutant causing lung cancer. The main protection against it is the monitoring. Recent literature has highlighted that historical buildings and archeological sites could be polluted by Radon not only due to the geological site but also due to the building materials and usage. In this paper, measurement techniques for the evaluation of Radon’s concentration level (222Rn) are compared. This evaluation allows to determine most appropriate technique to be used in this type of buildings. The study is justified by the fact that the buildings are often attended not only by specialists but also by tourist that with their behaviour could misstate Radon gas measurement. The study is effectuated analyzing the situation of three old churches located in San Giovanni in Fiore (Cosenza, south of Italy). The measurement results are compared with the ones obtained by performing the same monitoring in public buildings attended by different kind of users. The monitored sites, churches and public buildings, are erected on the common granite massif of Sila (South Italy), by using local granite stone.

How do collaboration and investments in knowledge management affect process innovation in services?

Purpose Despite the keen interest in radical and incremental innovation, few studies have tested the varying impact of firm-level factors in service sectors. This paper analyses how collaboration with existing and prospective users and investments in knowledge management (KM) practices can be adapted to maximise the outputs of radical and incremental process innovation in a knowledge-intensive business service industry. Design/methodology/approach Original survey data from 166 information technology service firms and interviews with 13 executives provide the empirical evidence. Partial least squares-structural equation modelling is used to analyse the data. Findings Collaboration with different types of users, and investments in KM practices affect radical versus incremental process innovation differently. Collaboration with existing users influences incremental process innovation directly, but not radical innovation; and prospective user collaboration matters for radical, but not incremental innovation. Furthermore, for radical innovation, investments in KM practices mediate the impact of prospective user collaboration on innovation. Research limitations/implications While collaboration with existing users for incremental process innovations does not appear to generate significant managerial challenges, to pursue radical innovations firms must engage in intensive collaboration with prospective users. Higher involvement with prospective users requires higher investment in KM practices to promote efficient intra- and inter-firm knowledge flows. Originality/value This study is based on a large-scale survey, together with management interviews. Radical and incremental innovations in the service industry require engagements with different kinds of users, and the use of KM tools.

Towards Prognostics & Health Management in Lighting Applications

Philips Lighting’s revenue is largely influenced by the change from component supplier to supplier of systems, solutions and services. Philips Lighting differentiates from competition by providing high quality and reliable products as we learned in our traditional lighting business and which we continue in our actual LED lighting business. Reliable products start with understanding the physics-of-failure by using accelerated test approaches such as (Highly) Accelerated Life Testing. A classical reliability approach is to use the results from these tests, verified by failure analysis, to obtain conservative bounds from the failure models, and predict failure rates on a system level. A next step beyond this classical approach is to use data analytics in our installed base to determine degraded performance. The data for this analysis can come either from live connections to ‘intelligent’ systems, or from actively retracted (working) products from the field. This allows us to move into the prognostics (PHM) regime where a detailed understanding of failure mechanisms, usage scenarios, technology and design come together.Until recently costs for implementing PHM in Lighting products or systems was outranging possible cost benefits. Nowadays this is reversing rapidly by the exponential increasing impact of digitization and connectivity of the Lighting Systems. The impact is far beyond the impact on single products, but extends to an ever larger amount of connected systems. Continuously, more intelligent interfacing with the technical environment and with different kind of users is being built-in by using more and different kind of sensors, (wireless) communication, and different kind of interacting or interfacing devices. Especially in professional systems, where many years of use has to be warranted and where system size, cost and complexity are continuously increasing, PHM is required. Where online debugging and adding new features or functions is already common practice, PHM should provide tools to keep the system within its quality and reliability targets. In the presentation we show our road towards prognostics and demonstrate PHM work being done in different professional Lighting applications as Public Lighting, Office & Industry Lighting and Retail Lighting. While data analytic tools are still premature, first results are achieved and improvement tracks are being defined. We will conclude with our strategy and vision on how to embed cost-effective PHM into lighting applications.

Factors Predicting the Explicit and Implicit Attitude Towards Body Scanners

The study aimed at finding variables predicting the implicit and explicit attitude towards body scanners and to assess possible correlations with regard to dual-process. Age, gender, the personality variables technological affinity and systemizing, knowledge about body scanners and media consumption served as predictors. The explicit attitude was operationalized through a questionnaire measuring expectations about a body scan. A Single Target Implicit Association Test assessed the implicit attitude. Gender and knowledge were significant predictors for the explicit attitude: Women worried more about the effects of a body scan and requested more information. People with more knowledge about body scanners worried more about possible discrimination through body scanners. Predicting the implicit attitude there was a trend that people who have more enthusiasm about technology had a worse implicit attitude towards body scanners. Implicit and explicit attitude did not correlate. The findings suggest that it makes sense to integrate different kinds of users in the design and development process of security technologies to account for different opinions, needs and worries.

Algorithms, Interfaces, and the Circulation of Information: Interrogating the Epistemological Challenges of Facebook

As social and political life increasingly takes place on social network sites, new epistemological questions have emerged. How can information disseminated through new media be understood and disentangled? How can potential hidden agendas or sources be identified? And what mechanisms govern what and how information is presented to the user? By drawing on existing research on the algorithms and interfaces underlying social network sites, this paper provides a discussion of Facebook and the epistemological challenges, potentials, and questions raised by the platform. The paper specifically discusses the ways in which interfaces shape how information can be accessed and processed by different kinds of users as well as the role of algorithms in pre-selecting what appears as representable information. A key argument of the paper is that Facebook, as a complex socio-technical network of human and non-human actors, has profound epistemological implications for how information can be accessed, understood, and circulated. In this sense, the user's potential acquisition of information is shaped and conditioned by the technological structure of the platform. Building on these arguments, the paper suggests that new epistemological challenges deserve more scholarly attention, as they hold wide implications for both researchers and users.

Database Challenges for Exploratory Computing

Helping users to make sense of very big datasets is nowadays considered an important research topic. However, the tools that are available for data analysis purposes typically address professional data scientists, who, besides a deep knowledge of the domain of interest, master one or more of the following disciplines: mathematics, statistics, computer science, computer engineering, and programming. On the contrary, in our vision it is vital to support also different kinds of users who, for various reasons, may want to analyze the data and obtain new insight from them. Examples of these data enthusiasts [4, 9] are journalists, investors, or politicians: non-technical users who can draw great advantage from exploring the data, achieving new and essential knowledge, instead of reading query results with tons of records. The term data exploration generally refers to a data user being able to find her way through large amounts of data in order to gather the necessary information. A more technical definition comes from the field of statistics, introduced by Tukey [12]: with exploratory data analysis the researcher explores the data in many possible ways, including the use of graphical tools like boxplots or histograms, gaining knowledge from the way data are displayed. Despite the emphasis on visualization, exploratory data analysis still assumes that the user understands at least the basics of statistics, while in this paper we propose a paradigm for database exploration which is in turn inspired by the exploratory computing vision [2]. We may describe exploratory computing as the step-by-step “conversation” of a user and a system that “help each other” to refine the data exploration process, ultimately gathering new knowledge that concretely fullfils the user needs. The process is seen as a conversation since the system provides active support: it not only answers user’s requests, but also suggests one or more possible actions that may help the user to focus the exploratory session. This activity may entail the use of a wide range of different techniques, including the use of statistics and data analysis, query suggestion, advanced visualization tools, etc. The closest analogy [2] is that of a human-tohuman dialogue, in which two people talk, and continuously make reference to their lives, priorities, knowledge and beliefs, leveraging them in order to provide the best possible contribution to the dialogue. In essence, through the conversation they are exploring themselves as well as the information that is conveyed through their words. This exploration process therefore means investigation, exploration-seeking, comparison-making, and learning altogether. It is most appropriate for big collections of semantically rich data, which typically hide precious knowledge behind their complexity. In this broad and innovative context, this paper intends to make a significant step further: it proposes a model to concretely perform this kind of exploration over a database. The model is general enough to encompass most data models and query languages that have been proposed for data management in the last few years. At the same time, it is precise enough to provide a first formalization of the problem and reason about the research challenges posed to database researchers by this new paradigm of interaction.

Survey on Password Quality and Confidentiality

In this paper are presented results of empirical survey on password quality self-assessment and several privacy issues regarding password manipulation among information systems' users. Data was collected by questioning 627 e-mail users that were adults, Croatian national and were using e-mail system on regular basis. Comparisons among different kind of users were done regarding age, gender, technical background knowledge, university degree and experience in usage. Results of statistical analysis have shown that most of the users' passwords are of average quality while 13,8% of all users graded their password as poor. Regarding password manipulation 53,4% of all users said they use the same passwords for most of the information systems they use. In total 20,7% of all users sometimes lend their password and 17,1% of them wrote it down for remembering. Results of this study highlighted importance of using security procedures and guidelines and need of the continuous education on security issues with constant informing and alerting of information systems' users. This study is an example on how to evaluate different users' security awareness in order to adjust courses on security issues and to adapt informing and alerting to different groups of information systems' users. However, there is great need for validated universal questionnaire for this kind of surveys.

Insider Threat Assessment

Security is a major challenge for today's companies, especially ICT ones which manage large scale cyber-critical systems. Amongst the multitude of attacks and threats to which a system is potentially exposed, there are insider attackers i.e., users with legitimate access which abuse or misuse of their power, thus leading to unexpected security violation (e.g., acquire and disseminate sensitive information). These attacks are very difficult to detect and mitigate due to the nature of the attackers, which often are company's employees motivated by socio-economical reasons, and to the fact that attackers operate within their granted restrictions. It is a consequence that insider attackers constitute an actual threat for ICT organizations. In this paper we present our methodology, together with the application of existing supporting libraries and tools from the state-of-the-art, for insider threats assessment and mitigation. The ultimate objective is to define the motivations and the target of an insider, investigate the likeliness and severity of potential violations, and finally identify appropriate countermeasures. The methodology also includes a maintenance phase during which the assessment can be updated to reflect system changes. As case study, we apply our methodology to the crisis management system Secure!, which includes different kinds of users and consequently is potentially exposed to a large set of insider threats.

Formal and informal irrigation in the Andean countries. An overview

<p class="Default">This work is an empiric – theory revision which evidences the existence of two irrigation sectors in the Andean countries: a formal one, mainly located in plain low lands, controlled by the government, mostly directed to agribusiness producers and, in a smaller proportion, to small holders; the other sector, informal irrigation, is directly managed by the producers, usually family farmers, without government control and without being reported in national statistics; this second sector is principally located in the Andean mountains. Nowadays there are several institutions for the access to water which are associated to different stakeholders, so conflicts between different kinds of users emerge.</p>

The Sketch Engine: ten years on

The Sketch Engine is a leading corpus tool, widely used in lexicography. Now, at 10 years old, it is mature software. The Sketch Engine website offers many ready-to-use corpora, and tools for users to build, upload and install their own corpora. The paper describes the core functions (word sketches, concordancing, thesaurus). It outlines the different kinds of users, and the approach taken to working with many different languages. It then reviews the kinds of corpora available in the Sketch Engine, gives a brief tour of some of the innovations from the last few years, and surveys other corpus tools and websites.

A Content-Oriented Image Metadata Model

This paper presents a content-oriented image metadata model. It aims to provide a standard metadata specification focusing on describing the information relevant to contents and topics of images, and enable different kinds of users to label an image in an effective and unified way. The model is also a key part of rich tag system (RTS), with which we can easily use controlled tags to fill metadata properties. RTS and the image metadata model have been applied to some practical applications, and been demonstrated to be effective and worthy of spreading.

Measurement Techniques for Online Battery State of Health Estimation in Vehicle-to-Grid Applications

The evolution of the power grid calls for a smarter infrastructure, capable of integrating different energy sources and all the different kind of users of the grid. In addition, it should be able to dynamically adapt to fluctuations in loads and sources. In the Smart Grid scenario, energy storage systems (ESSs) play a fundamental role, allowing for decoupling production and usage times. Lithium ion batteries are among the most promising technologies in ESSs. They will allow for a full exploitation of renewable energy sources, can be used to shape load curves and constitute the energy reserve in battery electric vehicles. In addition, if such vehicles are plugged into the power grid, they can act as support electricity storage, realizing the so-called vehicle-to-grid (V2G) paradigm. In all these applications, the reliability of the battery system must be guaranteed. Therefore, measurement techniques to assess the state of health of batteries are needed. In this paper, with particular reference to V2G applications, two fast techniques to compute an index representing the state of health of a Li-ion battery are introduced. The first one relies on fuzzy logic, while the second is based on a neural network. In both cases, an early characterization of batteries in the same family of the ones to be monitored is needed. Compared with experimental data, the techniques exhibit good performances without the need for great processing power. Their performances are adequate for the intended V2G fleet management purpose.