81. Involving consumers in the programmes of consumption adjustment by using dynamic tariffing within the European Project Flex4GridKristijan Koželj, Anton Kos, Damjan Bobek, objavljeni znanstveni prispevek na konferenci Opis: The distribution company Elektro Celje d.d. as a member of the International Consortium has successfully applied for the European Programme Tender on Research and Innovations Horizon 2020 with Flex4Grid project focusing on solutions that would allow flexibility management of users – the so-called prosumers of the distribution network in the field of consumption as well as power generation. Flex4Grid, a European Development Project, focuses primarily on the development of an open technological system for data management and service provision which would allow managing user or prosumer flexibility of the distribution network in respect of their power consumption as well as power generation. Prosumer flexibility is a capability of prosumers to adjust their consumption or power generation to the needs of other stakeholders within the system, and could be rewarded for such adjustment. The service will be offered in a computer cloud where anonymised data will be collected. Some new business models will be developed and some new incentives for prosumer participation in such projects will be introduced.
Ključne besede: Horizon 2020, Flex4Grid, data management, service provision, distribution networks
Objavljeno v DKUM: 11.10.2017; Ogledov: 1218; Prenosov: 190
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82. Link prediction on TwitterSanda Martinčić-Ipšić, Edvin Močibob, Matjaž Perc, 2017, izvirni znanstveni članek Opis: With over 300 million active users, Twitter is among the largest online news and social networking services in existence today. Open access to information on Twitter makes it a valuable source of data for research on social interactions, sentiment analysis, content diffusion, link prediction, and the dynamics behind human collective behaviour in general. Here we use Twitter data to construct co-occurrence language networks based on hashtags and based on all the words in tweets, and we use these networks to study link prediction by means of different methods and evaluation metrics. In addition to using five known methods, we propose two effective weighted similarity measures, and we compare the obtained outcomes in dependence on the selected semantic context of topics on Twitter. We find that hashtag networks yield to a large degree equal results as all-word networks, thus supporting the claim that hashtags alone robustly capture the semantic context of tweets, and as such are useful and suitable for studying the content and categorization. We also introduce ranking diagrams as an efficient tool for the comparison of the performance of different link prediction algorithms across multiple datasets. Our research indicates that successful link prediction algorithms work well in correctly foretelling highly probable links even if the information about a network structure is incomplete, and they do so even if the semantic context is rationalized to hashtags.
Ključne besede: link prediction, data mining, Twitter, network analysis
Objavljeno v DKUM: 15.09.2017; Ogledov: 1864; Prenosov: 204
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83. Digital spatial data as support for river basin management : the case of Sotla river basinKlemen Prah, Andrej Lisec, Anka Lisec, 2013, izvirni znanstveni članek Opis: Many real-world spatially related problems, including river-basin planning and management, give rise to geographical information system based decision making, since the performance of spatial policy alternatives were traditionally and are still often represented by thematic maps. Advanced technologies and approaches, such as geographical information systems (GIS), offer a unique opportunity to tackle spatial problems traditionally associated with more efficient and effective data collection, analysis, and alternative evaluation. This paper discusses the advantages and challenges of the use of digital spatial data and geographical information systems in river basis management. Spatial data on social, environmental and other spatial conditions for the study area of 451.77 km2, the Slovenian part of the Sotla river basin, are used to study the GIS capabilities of supporting spatial decisions in the framework of river basin management.
Ključne besede: river basin management, spatial data, GIS, spatial evaluation, Sotla river basin
Objavljeno v DKUM: 03.08.2017; Ogledov: 2049; Prenosov: 187
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84. A wearable device and system for movement and biometric data acquisition for sports applicationsMarko Kos, Iztok Kramberger, 2017, izvirni znanstveni članek Opis: This paper presents a miniature wearable device and a system for detecting and recording the movement and biometric information of a user during sport activities. The wearable device is designed to be worn on a wrist and can monitor skin temperature and pulse rate. Furthermore, it can monitor arm movement and detect gestures using inertial measurement unit. The device can be used for various professional and amateur sport applications and for health monitoring. Because of its small size and minimum weight, it is especially appropriate for swing-based sports like tennis or golf, where any additional weight on the arms would most likely disturb the player and have some influence on the player’s performance. Basic signal processing is performed directly on the wearable device but for more complex signal analysis, the data can be uploaded via the Internet to a cloud service, where it can be processed by a dedicated application. The device is powered by a lightweight miniature LiPo battery and has about 6 h of autonomy at maximum performance.
Ključne besede: biometric data acquisition, inertial sensing, movement detection, pulse rate, sensor fusion, wearable
Objavljeno v DKUM: 03.08.2017; Ogledov: 1416; Prenosov: 541
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85. Contribution of temporal data to predictive performance in 30-day readmission of morbidly obese patientsPetra Povalej Bržan, Zoran Obradović, Gregor Štiglic, 2017, izvirni znanstveni članek Opis: Background: Reduction of readmissions after discharge represents an important challenge for many hospitals and has attracted the interest of many researchers in the past few years. Most of the studies in this field focus on building cross-sectional predictive models that aim to predict the occurrence of readmission within 30-days based on information from the current hospitalization. The aim of this study is demonstration of predictive performance gain obtained by inclusion of information from historical hospitalization records among morbidly obese patients.
Methods: The California Statewide inpatient database was used to build regularized logistic regression models for prediction of readmission in morbidly obese patients (n = 18,881). Temporal features were extracted from historical patient hospitalization records in a one-year timeframe. Five different datasets of patients were prepared based on the number of available hospitalizations per patient. Sample size of the five datasets ranged from 4,787 patients with more than five hospitalizations to 20,521 patients with at least two hospitalization records in one year. A 10-fold cross validation was repeted 100 times to assess the variability of the results. Additionally, random forest and extreme gradient boosting were used to confirm the results.
Results: Area under the ROC curve increased significantly when including information from up to three historical records on all datasets. The inclusion of more than three historical records was not efficient. Similar results can be observed for Brier score and PPV value. The number of selected predictors corresponded to the complexity of the dataset ranging from an average of 29.50 selected features on the smallest dataset to 184.96 on the largest dataset based on 100 repetitions of 10-fold cross-validation.
Discussion: The results show positive influence of adding information from historical hospitalization records on predictive performance using all predictive modeling techniques used in this study. We can conclude that it is advantageous to build separate readmission prediction models in subgroups of patients with more hospital admissions by aggregating information from up to three previous hospitalizations.
Ključne besede: readmission prediction, predictive modelling, temporal data
Objavljeno v DKUM: 02.08.2017; Ogledov: 1962; Prenosov: 381
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86. Security analysis and improvements to the psychopass methodBoštjan Brumen, Marjan Heričko, Ivan Rozman, Marko Hölbl, 2013, izvirni znanstveni članek Opis: Background: In a recent paper, Pietro Cipresso et al proposed the PsychoPass method, a simple way to create strong passwords that are easy to remember. However, the method has some security issues that need to be addressed.
Objective: To perform a security analysis on the PsychoPass method and outline the limitations of and possible improvements to the method.
Methods: We used the brute force analysis and dictionary attack analysis of the PsychoPass method to outline its weaknesses.
Results: The first issue with the Psychopass method is that it requires the password reproduction on the same keyboard layout as was used to generate the password. The second issue is a security weakness: although the produced password is 24 characters long, the password is still weak. We elaborate on the weakness and propose a solution that produces strong passwords. The proposed version first requires the use of the SHIFT and ALT-GR keys in combination with other keys, and second, the keys need to be 1-2 distances apart.
Conclusions: The proposed improved PsychoPass method yields passwords that can be broken only in hundreds of years based on current computing powers. The proposed PsychoPass method requires 10 keys, as opposed to 20 keys in the original method, for comparable password strength.
Ključne besede: passwords, cryptanalysis, data security
Objavljeno v DKUM: 02.08.2017; Ogledov: 1339; Prenosov: 695
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87. Outsourcing medical data analyses : can technology overcome legal, privacy and confidentiality issues?Boštjan Brumen, Marjan Heričko, Andrej Sevčnikar, Jernej Završnik, Marko Hölbl, 2013, izvirni znanstveni članek Opis: Background: Medical data are gold mines for deriving the knowledge that could change the course of a single patient’s life or even the health of the entire population. A data analyst needs to have full access to relevant data, but full access may be denied by privacy and confidentiality of medical data legal regulations, especially when the data analyst is not affiliated with the data owner.
Objective: Our first objective was to analyze the privacy and confidentiality issues and the associated regulations pertaining to medical data, and to identify technologies to properly address these issues. Our second objective was to develop a procedure to protect medical data in such a way that the outsourced analyst would be capable of doing analyses on protected data and the results would be comparable, if not the same, as if they had been done on the original data. Specifically, our hypothesis was there would not be a difference between the outsourced decision trees built on encrypted data and the ones built on original data.
Methods: Using formal definitions, we developed an algorithm to protect medical data for outsourced analyses. The algorithm was applied to publicly available datasets (N=30) from the medical and life sciences fields. The analyses were performed on the original and the protected datasets and the results of the analyses were compared. Bootstrapped paired t tests for 2 dependent samples were used to test whether the mean differences in size, number of leaves, and the accuracy of the original and the encrypted decision trees were significantly different.
Results: The decision trees built on encrypted data were virtually the same as those built on original data. Out of 30 datasets, 100% of the trees had identical accuracy. The size of a tree and the number of leaves was different only once (1/30, 3%, P=.19).
Conclusions: The proposed algorithm encrypts a file with plain text medical data into an encrypted file with the data protected in such a way that external data analyses are still possible. The results show that the results of analyses on original and on protected data are identical or comparably similar. The approach addresses the privacy and confidentiality issues that arise with medical data and is adherent to strict legal rules in the United States and Europe regarding the processing of the medical data.
Ključne besede: medical data, disclosure control, medical confidentiality, data analysis, data security
Objavljeno v DKUM: 02.08.2017; Ogledov: 1383; Prenosov: 203
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88. Analyzing information seeking and drug-safety alert response by health care professionals as ew methods for surveillanceAlison Callahan, Igor Pernek, Gregor Štiglic, Jurij Leskovec, Howard Strasberg, Nigam Haresh Shah, 2015, izvirni znanstveni članek Opis: Background: Patterns in general consumer online search logs have been used to monitor health conditions and to predict health-related activities, but the multiple contexts within which consumers perform online searches make significant associations difficult to interpret. Physician information-seeking behavior has typically been analyzed through survey-based approaches and literature reviews. Activity logs from health care professionals using online medical information resources are thus a valuable yet relatively untapped resource for large-scale medical surveillance.
Objective: To analyze health care professionals% information-seeking behavior and assess the feasibility of measuring drug-safety alert response from the usage logs of an online medical information resource.
Methods: Using two years (2011-2012) of usage logs from UpToDate, we measured the volume of searches related to medical conditions with significant burden in the United States, as well as the seasonal distribution of those searches. We quantified the relationship between searches and resulting page views. Using a large collection of online mainstream media articles and Web log posts we also characterized the uptake of a Food and Drug Administration (FDA) alert via changes in UpToDate search activity compared with general online media activity related to the subject of the alert.
Results: Diseases and symptoms dominate UpToDate searches. Some searches result in page views of only short duration, while others consistently result in longer-than-average page views. The response to an FDA alert for Celexa, characterized by a change in UpToDate search activity, differed considerably from general online media activity. Changes in search activity appeared later and persisted longer in UpToDate logs. The volume of searches and page view durations related to Celexa before the alert also differed from those after the alert.
Conclusions: Understanding the information-seeking behavior associated with online evidence sources can offer insight into the information needs of health professionals and enable large-scale medical surveillance. Our Web log mining approach has the potential to monitor responses to FDA alerts at a national level. Our findings can also inform the design and content of evidence-based medical information resources such as UpToDate
Ključne besede: internet log analysis, data mining, physicians, information-seeking behavior, drug safety surveillance
Objavljeno v DKUM: 02.08.2017; Ogledov: 1858; Prenosov: 229
Celotno besedilo (4,18 MB)
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89. Environmental data exchanging – the need for managementDrago Vuk, 2000, drugi znanstveni članki Opis: In this paper, the author analyses the beginning of the application of measures imposed by the Slovenian Law on the Environmental Protection and the Environmental Information System. On the basis of his knowledge of the actual state, he proposes a model by means of which it would be possible to systematically assure with EDI environmental balances and environmental accounting, thus providing the basis for the implementation of an applicable environmental information system.
Ključne besede: environmental protection, environmental data, electronic data interchange
Objavljeno v DKUM: 17.07.2017; Ogledov: 1370; Prenosov: 139
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90. From DCOM interfaces to domain-specific modeling language : a case study on the sequencerTomaž Kos, Tomaž Kosar, Jure Knez, Marjan Mernik, 2011, izvirni znanstveni članek Opis: Software development is a demanding process, since it involves different parties to perform a desired task. The same case applies to the development ofmeasurement systems - measurement system producers often provide interfaces to their products, after which the customersć programming engineers use them to build software according to the instructions and requirements of domain experts from the field of data acquisition. Until recently, the customers of the measurement system DEWESoft were building measuring applications, using prefabricated DCOM objects. However, a significant amount of interaction between customersć programming engineers and measurement system producers is necessary to use DCOM objects. Therefore, a domain-specific modeling language has been developed to enable domain experts to program or model their own measurement procedures without interacting with programming engineers. In thispaper, experiences gained during the shift from using the DEWESoft productas a programming library to domain-specific modeling language are provided together with the details of a Sequencer, a domain-specific modeling language for the construction of measurement procedures.
Ključne besede: domain specific modelling language, data acquisition, measurement systems
Objavljeno v DKUM: 06.07.2017; Ogledov: 1574; Prenosov: 188
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