Abstract: While there are several different factors that contribute to traffic accidents, speeding certainly seems to be one of the more prominent ones. Previous studies have found a strong relationship between speeding and accident risk, with higher speed generally increasing accident propensity. However, there is still no consensus on the best way of measuring speeding behavior. Previous research has utilized various sources of speeding data, such as self-report measures and driving simulators, with each of these sources having their own limitations. In the present study, we explored the behavioral validity of three different assessment methods of speeding – 1) a direct self-report measure (self-reported speeding violations), 2) an indirect self-report measure (self-reported speeding norms), and 3) an objective measure (driving simulator). On a sample of 46 participants, we found that, regardless of the assessment method, traffic offenders exhibited somewhat higher levels of speeding than non-offenders. However, the difference was significant only in the case of the direct self-report measure. Hence, our results suggest that self-reported speeding violations show higher behavioral validity than the other two methods. In the discussion, we offer some ideas that could improve driving simulators and simulator-based studies and contribute to better behavioral validity of such data.

Abstract: By focusing on the demands of a wearable device context, we investigate the possibility of reducing the computational complexity of calculating angular orientation from 3D gyroscope measurements. Our investigation has shown that for an executing microcontroller without an associated floating-point unit and characterized by low-power consumption, relying strictly on integer arithmetic, lookup tables for square root and inverse square root function estimations and small angle approximations for trigonometric function estimations, up to 14 times faster execution of angular orientation calculation can be obtained. Following on the results obtained, we conclude that significant improvement in computational efficiency and reduction of power-consumption can be achieved when computing angular orientation from 3D gyroscope measurements. By adopting the practices presented in this article, motion tracking and analysis can be performed with greater computational efficiency.

Abstract: Security is an inevitable part of every informationsystem. It is a cross-cutting concern that affects every partof the system. There is a constant trade-off between asecured system and convenient security management, andthis management gets more demanding when thepermissions are context dependent. The delegation ofauthorization is one way to make this process moreconvenient, by including and allowing multiple individualsto contribute. We provide a solution for combining multiple security rulessuch that data owners can delegate a part of theirpermissions over their data, and can validate the overallallowed data during the security permissions design process.

Abstract: When Eurovision Song Contest (ESC) first adopted the voting system in which citizens could vote by telephone, also known as televoting, it became possible for large population subgroups with similar biases to directly influence the voting outcome. As a result, region-specific voting trends emerged. In this paper, findings about ESC voting patterns based on data from the televoting period (1998–2008) are presented. Countries were partitioned into eight different regions based on their geographic, demographic, economic and cultural characteristics. Agglomerative hierarchical clustering and visualization of voting distribution using a circos plot were performed to check for the existence of inter-region and intra-region favoritism. Distinct decision tree models were built for votings of countries from different regions. Region-specific voting patterns, connected with demographic, religous, linguistic, economic and geographic relationships between the countries, were examined by analyzing structure of decision tree models. Results indicate that the intra-region favoritism exists in most of the regions, while inter-region favoritism exists between some pairs of regions. Differences in voting patterns between richer and poorer regions were noticed. Countries from richer regions tend to favor countries from which they have numerous economic immigrants, probably due to patriotic voting of these immigrants. Countries from poorer regions tend to give more points to other countries with similar demographic and cultural structure.

Abstract: This paper presents exporting of research domain entities’ metadata from a national publication information service to European research portal. The aim of the presented implementation is to export metadata about researchers, organization units, scientific events, and publications from the Finnish VIRTA publication information service to the OpenAIRE research portal. This export of data is based on the OpenAIRE Guidelines for CRIS managers.

Abstract: Aim of this paper is to describe a new architecture of BISIS system. New architecture is cloud-based and system is deployed on our private cloud solution implemented on dedicated servers. Also, we will give explanation why some decisions are made and what we had to sacrifice in order to move to cloud-based solution.

Abstract: Internet of Things has been changing the world in the last couple of years with a tendency to have an even bigger impact. In the beginning, the vast amount of data was collected, processed and stored in the cloud. Now, more and more of these operations are done on the IoT devices with respect to their limitation in terms of storage and processing power. The responsibility is transferred from the cloud to the IoT devices and that fact raised big security and privacy concerns that can lead to different problems like disclosure of the user’s identity or device location. In this paper, we identify different groups of privacy issues that can occur and try to tackle them through a simple smart healthcare scenario where we propose different solutions for detected issues.

Abstract: Information communication technology has a critical role in changes to the health system and a significant part to play in its improvement. However, the measurable results of health care system improvement are not evident to the extent expected. There is a gap between the potential and realized benefits of health information technology. We conducted a review of the literature in order to describe and explain health information technology gap. We also propose a strategy for upgrade of the current health information technology as a possible solution to overcome this gap. Nowadays, health care system is patient centered. In the health care system enhanced by health information technology environment, we have empowered patients, and the position of practicing physician is significantly changed. Advanced technologies such as the Internet of Things, Cloud computing, Big Data analytics, Wearables, Smart sensors and Artificial Inteligence could reduce the health information technology gap by improving the existing health service delivery and health care system in general. In the last decade, patients and population that actively use listed technologies have become empowered health information technology stakeholder. In accordance to that, it could be a wise solution to also empower physicians by the implementation of these technologies in their everyday medical practice. Referring to the current trends in design of information communication technology solutions such as user centered-design and personalization, we came to the conclusion that changing the position of practicing physician more toward the center of the health care system, technology gap could be significantly minimized. In this way, with optimal application of information communication technology in health care, and also with a slightly different organizational approach, it could be possible to bridge the gap between the potential and realized benefits of health information technology.

Abstract: A bunch of patient data in hospital information systems is kept every day. A part of the data that contains the symptoms, anamnesis, and observations of a doctor can be used for further processing in order to improve public health. This paper describes the algorithm for normalizing medical textual data in order to prepare them for further processing, and within the framework of smart healthcare services. The result of its application is normalized data but also a corpus of stop words specific to the medical domain.

Abstract: Prolonged consumption of virtual reality systems is challenged by induced sickness (commonly termed cybersickness) with a variety of unpleasant symptoms (e.g. disorientation, headache, nausea, salivation, sweating). The development of novel methods to assess cybersickness is required for future improvements in design of virtual environments and driving and aircraft simulators. We propose and explore relatively simple assessment method based on electrogastrography procedure to record and analyze electrical activity of the smooth stomach muscles in order to enable simple and effective quantitative assessment of cybersickness. In order to test the applicability of the proposed method, we recorded signals in three individuals during two roller coaster virtual experiences developed for Oculus Rift platform. The results presented here suggest that electrogastrography is promising procedure for cybersickness assessment. Nevertheless, some precautions in interpretation of results and future combination with other psychophysiological parameters are suggested. In addition, future improvements of the proposed method and possible applications are thoroughly discussed.

Abstract: The pressure map measured under foot by the contact with the ground is an essential tool to provide information how everyone is moving. Among all spatial and temporal data whose values can be measured by pressure gathering systems, the trajectory of the Centre of Pressure (CoP) in each footprint permit us to see a kind of foot signature from an individual. Thus, it is possible to get some level of patterns’ grouping just based on similarity among all CoP trajectories. The problem is the large amount of data for comparing among all pressure maps that become unfeasible a visual inspection task by humans. From the engineering point of view, this research proposes a method applied to gait pattern classification based on Knowledge Discovery in Database (KDD), where the objective is to understand if exists specific patterns which permits to group and to classify footprints by an automatic way. The text also presents an example of application of the method. The database contain data from two testing groups, compound by healthy and unhealthy younger adults and elderly people. The health condition of each one was previously known, and after application of method, the decision tree classified the footprints groups with precision of 95,3% of confidence. The presented method demonstrated that is feasible to define a computational classification criterion based on CoP trajectory in order to assist gait analysis.

Abstract: Biofeedback systems and applications in sports have great potential in accelerated motor learning and injury prevention. Traditional methods with terminal feedback are now being complemented by concurrent feedback methods. In sports, wireless communication systems are preferred. Acquiring and processing sensor data in challenging wireless channel conditions may prove demanding; for example, wireless communication with sensors attached to the body of the swimmer. To address such issues, we have designed and implemented a reliable communication protocol for cyclically interrupted channel, named Block Selective Repeat protocol. By using this protocol in biofeedback systems, we achieve fast and reliable transmission of sensor data and signals to the processing device and back to the biofeedback device. This protocol may prove particularly useful for real-time feedback systems and applications working in challenging environments, especially in such with cyclically interrupted radio channel. The final goal of our work is the development of real-time feedback systems and user-friendly applications for athletes and coaches that will help accelerate motor learning and improve their performance. Index Terms– biofeedback system, cyclically interrupted channel, modified selective repeat protocol, real-time communication, reliable communication protocol.

Abstract: The continuous improvements of technology and its new applications improve our well-being, health, and quality of life in general. Smart sport equipment, smart watches, smart weight scales, and similar devices are more and more frequent. Our idea is to develop and implement a wearable sensor device that can support real-time biofeedback applications in sport and rehabilitation, where short-time events and high-frequency signals need to be detected and processed. In order to assure a wide usability of such devices in various sports, they will have to be small size, light weight, and low cost. MEMS sensors and microcontroller systems meet these demands. Measurements performed on the prototype system show that the implementation of devices with sampling frequencies over 1 kHz is feasible. For example, the maximum attainable sample rate for the SPI prototype is 833 Hz in a sample streaming mode and 2.49 kHz in a block streaming mode. Such devices will open many new research possibilities in different sports or physical rehabilitation that were previously not possible because of low sampling frequencies of affordable devices. Index Terms - wearable sensor device, sensor data acquisition and streaming, real-time biofeedback, high-frequency sensor signals

Abstract: Containers are not new technology. They emerge in the late seventies, but they become more popular in the past decade in various systems and companies to achieve high resource utilization, efficient task-packing, process-level isolation, etc. Those container properties allow large internet companies like Google, Amazon, and Facebook to satisfy an ever-growing number of users who use their applications, services, and big data workloads. These companies can run dozens of tasks at scale, to satisfy all their operational needs. On the other hand, developers can create more efficient software and run it everywhere with the same behavior, almost without any additional work. With emerge of automatic cluster management and cluster schedulers, these containers get used even more on a day to day jobs, making them as easy as possible. In this paper, we present a review of usage of container technologies in the edge computing systems, in domains with constant data flow with processing on the very edge of the network.

Abstract: People are increasingly exposed to stress today, hence the care for their mental health is even more significant. The lack of time often does not allow that people discuss with professionals about stressful situations, but the answers to these problems are searched through the Internet such as the experiences of other people. Definition of a stressful situation is the first question. People react differently to certain stressful situations depending on the moment in which they are happening and their psychological state. The perception of a situation as stressful can be an indicator of the existence of a problem. This paper presents the model of the crowdsourcing platform that serves to gather information of stressful situations, individual reaction to the given situation, the comment of professionals on the problem, as well as the assessment of the psychological state of the user through a psychological test. Such a platform is a unique platform of this type in the Serbian language. The users of this platform get information about the relationship between the stressful situation and the corresponding psychological state. For the purposes of this paper, the platform is developed for the case of postpartum depression.

Abstract: Training at shooting is one of the most important training courses in public or private structures, such as police, military, security companies and the like. Shooting is a discipline where accuracy is the most important. Technologically supported shooting training brings more benefits for trainees and organizations. Trainees spend less time on average for training, but the organization can save funds for shooting ranges, coaches and materials. We designed an application that measures the movement of the gun during aiming, firing, and post firing phases of shots. The acquired sensor signals are evaluated using recorded hits in the target. Measurements comprise 32 subjects of different ages and different shooting skills. The results indicate that the movement of the arms during the aiming phase is strongly related to the accuracy of the shooting. On the basis of the above results, applications with real-time feedback systems and trainers are being developed. A precise shooting practice that includes real-time biofeedback applications or a trainer will lead to accelerated learning, reducing the number of poorly executed shots, and consequently saving time, resources, and money. Keywordswireless sensor, augmented biofeedback system, real-time application, precision shooting practice, coach support system

Abstract: Under influence of open government and data transparency initiatives, a variety of institutions have published a significant number of datasets. In most cases, open data portals are used as tools for publishing purposes. Further, open data portals have the ability to make data more accessible by categorizing datasets based on different criteria like publishers, institutions, formats, and descriptions. For these purposes, portals take advantage of metadata accompanying datasets. However, a part of metadata is often missing which makes it harder for users to find appropriate datasets and obtain the desired information. As the number of available datasets grows, this problem becomes easy to notice. This paper is focused on first step towards decreasing this problem by implementing components capable of suggesting the best match for the category where an uncategorized dataset should belong to. Our approach relies on dataset descriptions provided by users within dataset tags and uses formal concept analysis to reveal shared conceptualization originating from tags' usage. Since tags represent free text metadata entered by users, in this paper we will present a method of optimizing their usage through means of semantic similarity measures based on natural language processing mechanisms. Finally, we will demonstrate the advantage of our proposal by comparing concept lattices generated using formal concept analysis before and after optimization process and use generated structure as a knowledge base to categorize uncategorized open datasets.

Abstract: Facing the fourth industrial revolution, new types of requirements appear, as well as new job positions which are accompanied with new work standards. All of this brings along innovations in technology, but also calls for innovations in strategic management. Software developers are key employees in this industrial revolution and they present new type of workers which indicates a need for innovative approach regarding reducing their fluctuation. Fluctuation can be reduced with adequate motivating, which can be provided only with deep understanding of their work motivation and perception of certain job aspects. In this research job perception of software developers and their work motivation is being discussed.

Abstract: Selection of the multi-sensor data fusion (MSDF) architecture is one of the key tasks in the design of a multi-sensor system. The emergence of systems with large number of sensors, e.g. Internet of things, could bring novelty into this well studied subject. In this study, we address three aspects of MSDF architectures: classification, optimal selection, and standardized presentation. We classify the known architecture types according to all the three of the criteria found in the literature, while previous works only used one or two. We suggest that the optimal selection of MSDF architecture is a multi-objective optimization problem, and qualitatively define the objective and decision spaces. Finally, we suggest that the Systems Modeling Language could be used as a standardized means for presenting MSDF architectures.

Abstract: Big cities show a wide public transportation network, allowing people to travel within cities. However, with the overpopulation of urban areas, the demand for new mobility strategies has increasing. Every day, citizens need to commute fast, easily and comfortable, which is not always easy due to the complexity of the transport network. The main objective of this paper, is to explore the ability of Big Data technologies to cope with data collected from public transportation, by inferring automatically and continuously, complex mobility patterns about human mobility, in the form of insightful indicators (such as connections, transshipments or pendular movements), creating a new perspective in public transports data analytics. The presented work, focus on the Lisbon metropolitan area, aiming to analyze the demand and supply side of transportation network of Lisbon, considering ticketing data transactions provided by the different transportation operators.