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  • 51.
    Boeva, Veselka
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Lundberg, Lars
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Angelova, Milena
    TU of Sofia, BUL.
    Kohstall, Jan
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Cluster Validation Measures for Label Noise Filtering2018In: 9th International Conference on Intelligent Systems 2018: Theory, Research and Innovation in Applications, IS 2018 - Proceedings / [ed] JardimGoncalves, R; Mendonca, JP; Jotsov, V; Marques, M; Martins, J; Bierwolf, R, Institute of Electrical and Electronics Engineers Inc. , 2018, p. 109-116Conference paper (Refereed)
    Abstract [en]

    Cluster validation measures are designed to find the partitioning that best fits the underlying data. In this paper, we show that these well-known and scientifically proven validation measures can also be used in a different context, i.e., for filtering mislabeled instances or class outliers prior to training in super-vised learning problems. A technique, entitled CVI-based Outlier Filtering, is proposed in which mislabeled instances are identified and eliminated from the training set, and a classification hypothesis is then built from the set of remaining instances. The proposed approach assigns each instance several cluster validation scores representing its potential of being an outlier with respect to the clustering properties the used validation measures assess. We examine CVI-based Outlier Filtering and compare it against the LOF detection method on ten data sets from the UCI data repository using five well-known learning algorithms and three different cluster validation indices. In addition, we study two approaches for filtering mislabeled instances: local and global. Our results show that for most learning algorithms and data sets, the proposed CVI-based outlier filtering algorithm outperforms the baseline method (LOF). The greatest increase in classification accuracy has been achieved by combining at least two of the used cluster validation indices and global filtering of mislabeled instances. © 2018 IEEE.

  • 52.
    Boeva, Veselka
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering. Blekinge Inst Technol, Comp Sci & Engn Dept, Karlskrona, Sweden..
    Lundberg, Lars
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering. Blekinge Inst Technol, Comp Sci & Engn Dept, Karlskrona, Sweden..
    Kota, Sai M. Harsha
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Sköld, Lars
    Telenor , SWE.
    Analysis of Organizational Structure through Cluster Validation Techniques Evaluation of email communications at an organizational level2017In: 2017 17TH IEEE INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOPS (ICDMW 2017) / [ed] Gottumukkala, R Ning, X Dong, G Raghavan, V Aluru, S Karypis, G Miele, L Wu, X, IEEE , 2017, p. 170-176Conference paper (Refereed)
    Abstract [en]

    In this work, we report an ongoing study that aims to apply cluster validation measures for analyzing email communications at an organizational level of a company. This analysis can be used to evaluate the company structure and to produce further recommendations for structural improvements. Our initial evaluations, based on data in the forms of emails logs and organizational structure for a large European telecommunication company, show that cluster validation techniques can be useful tools for assessing the organizational structure using objective analysis of internal email communications, and for simulating and studying different reorganization scenarios.

  • 53.
    Boldt, Martin
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Bala, Jaswanth
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Filtering Estimated Crime Series Based on Route Calculations on Spatio-temporal Data2016In: European Intelligence and Security Informatics Conference / [ed] Brynielsson J.,Johansson F., IEEE, 2016, p. 92-95Conference paper (Refereed)
    Abstract [en]

    Law enforcement agencies strive to link serial crimes, most preferably based on physical evidence, such as DNA or fingerprints, in order to solve criminal cases more efficiently. However, physical evidence is more common at crime scenes in some crime categories than others. For crime categories with relative low occurrence of physical evidence it could instead be possible to link related crimes using soft evidence based on the perpetrators' modus operandi (MO). However, crime linkage based on soft evidence is associated with considerably higher error-rates, i.e. crimes being incorrectly linked. In this study, we investigate the possibility of filtering erroneous crime links based on travel time between crimes using web-based direction services, more specifically Google maps. A filtering method has been designed, implemented and evaluated using two data sets of residential burglaries, one with known links between crimes, and one with estimated links based on soft evidence. The results show that the proposed route-based filtering method removed 79 % more erroneous crimes than the state-of-the-art method relying on Euclidean straight-line routes. Further, by analyzing travel times between crimes in known series it is indicated that burglars on average have up to 15 minutes for carrying out the actual burglary event. © 2016 IEEE.

  • 54.
    Boldt, Martin
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Borg, Anton
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    A statistical method for detecting significant temporal hotspots using LISA statistics2017In: Proceedings - 2017 European Intelligence and Security Informatics Conference, EISIC 2017, IEEE Computer Society, 2017, p. 123-126Conference paper (Refereed)
    Abstract [en]

    This work presents a method for detecting statisticallysignificant temporal hotspots, i.e. the date and time of events,which is useful for improved planning of response activities.Temporal hotspots are calculated using Local Indicators ofSpatial Association (LISA) statistics. The temporal data is ina 7x24 matrix that represents a temporal resolution of weekdaysand hours-in-the-day. Swedish residential burglary events areused in this work for testing the temporal hotspot detectionapproach. Although, the presented method is also useful forother events as long as they contain temporal information, e.g.attack attempts recorded by intrusion detection systems. Byusing the method for detecting significant temporal hotspotsit is possible for domain-experts to gain knowledge about thetemporal distribution of the events, and also to learn at whichtimes mitigating actions could be implemented.

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  • 55.
    Boldt, Martin
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Borg, Anton
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Evaluating Temporal Analysis Methods UsingResidential Burglary Data2016In: ISPRS International Journal of Geo-Information, Special Issue on Frontiers in Spatial and Spatiotemporal Crime Analytics, ISSN 2220-9964, Vol. 5, no 9, p. 1-22Article in journal (Refereed)
    Abstract [en]

    Law enforcement agencies, as well as researchers rely on temporal analysis methods in many crime analyses, e.g., spatio-temporal analyses. A number of temporal analysis methods are being used, but a structured comparison in different configurations is yet to be done. This study aims to fill this research gap by comparing the accuracy of five existing, and one novel, temporal analysis methods in approximating offense times for residential burglaries that often lack precise time information. The temporal analysis methods are evaluated in eight different configurations with varying temporal resolution, as well as the amount of data (number of crimes) available during analysis. A dataset of all Swedish residential burglaries reported between 2010 and 2014 is used (N = 103,029). From that dataset, a subset of burglaries with known precise offense times is used for evaluation. The accuracy of the temporal analysis methods in approximating the distribution of burglaries with known precise offense times is investigated. The aoristic and the novel aoristic_ext method perform significantly better than three of the traditional methods. Experiments show that the novel aoristic_ext method was most suitable for estimating crime frequencies in the day-of-the-year temporal resolution when reduced numbers of crimes were available during analysis. In the other configurations investigated, the aoristic method showed the best results. The results also show the potential from temporal analysis methods in approximating the temporal distributions of residential burglaries in situations when limited data are available.

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  • 56.
    Boldt, Martin
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Borg, Anton
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Melander, Ulf
    En strukturerad metod för registrering och automatisk analys av brott2014In: The Past, the Present and the Future of Police Research: Proceedings from the fifth Nordic Police Research seminar / [ed] Rolf Granér och Ola Kronkvist, 2014Conference paper (Refereed)
    Abstract [sv]

    I detta artikel beskrivs en metod som används i polisregionerna Syd, Väst och Stockholm1 för att samla in strukturerade brottsplatsuppgifter från bostadsinbrott, samt hur den insamlade informationen kan analyseras med automatiska metoder som kan assistera brottssamordnare i deras arbete. Dessa automatiserade analyser kan användas som filtrerings- eller selekteringsverktyg för bostadsinbrott och därmed effektivisera och underlätta arbetet. Vidare kan metoden användas för att avgöra sannolikheten att två brott är utförda av samma gärningsman, vilket kan hjälpa polisen att identifiera serier av brott. Detta är möjligt då gärningsmän tenderar att begå brott på ett snarlikt sätt och det är möjligt, baserat på strukturerade brottsplatsuppgifter, att automatiskt hitta dessa mönster. I kapitlet presenteras och utvärderas en prototyp på ett IT-baserat beslutsstödsystem samt två automatiska metoder för brottssamordning.

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  • 57.
    Boldt, Martin
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Borg, Anton
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Svensson, Martin
    Blekinge Institute of Technology, Faculty of Engineering, Department of Industrial Economics.
    Hildeby, Jonas
    Polisen, SWE.
    Predicting burglars' risk exposure and level of pre-crime preparation using crime scene data2018In: Intelligent Data Analysis, ISSN 1088-467X, E-ISSN 1571-4128, Vol. 22, no 1, p. 167-190, article id IDA 322-3210Article in journal (Refereed)
    Abstract [en]

    Objectives: The present study aims to extend current research on how offenders’ modus operandi (MO) can be used in crime linkage, by investigating the possibility to automatically estimate offenders’ risk exposure and level of pre-crime preparation for residential burglaries. Such estimations can assist law enforcement agencies when linking crimes into series and thus provide a more comprehensive understanding of offenders and targets, based on the combined knowledge and evidence collected from different crime scenes. Methods: Two criminal profilers manually rated offenders’ risk exposure and level of pre-crime preparation for 50 burglaries each. In an experiment we then analyzed to what extent 16 machine-learning algorithms could generalize both offenders’ risk exposure and preparation scores from the criminal profilers’ ratings onto 15,598 residential burglaries. All included burglaries contain structured and feature-rich crime descriptions which learning algorithms can use to generalize offenders’ risk and preparation scores from.Results: Two models created by Naïve Bayes-based algorithms showed best performance with an AUC of 0.79 and 0.77 for estimating offenders' risk and preparation scores respectively. These algorithms were significantly better than most, but not all, algorithms. Both scores showed promising distinctiveness between linked series, as well as consistency for crimes within series compared to randomly sampled crimes.Conclusions: Estimating offenders' risk exposure and pre-crime preparation  can complement traditional MO characteristics in the crime linkage process. The estimations are also indicative to function for cross-category crimes that otherwise lack comparable MO. Future work could focus on increasing the number of manually rated offenses as well as fine-tuning the Naïve Bayes algorithm to increase its estimation performance.

  • 58.
    Boldt, Martin
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    jacobsson, andreas
    Malmö University, SWE.
    Baca, Dejan
    Fidesmo AB, SWE.
    Carlsson, Bengt
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Introducing a novel security-enhanced agile software development process2017In: International Journal of Secure Software Engineering, ISSN 1947-3036, E-ISSN 1947-3044, ISSN 1947-3036, Vol. 8, no 2Article in journal (Refereed)
    Abstract [en]

    In this paper, a novel security-enhanced agile software development process, SEAP, is introduced. It has been designed, tested, and implemented at Ericsson AB, specifically in the development of a mobile money transfer system. Two important features of SEAP are 1) that it includes additional security competences, and 2) that it includes the continuous conduction of an integrated risk analysis for identifying potential threats. As a general finding of implementing SEAP in software development, the developers solve a large proportion of the risks in a timely, yet cost-efficient manner. The default agile software development process at Ericsson AB, i.e. where SEAP was not included, required significantly more employee hours spent for every risk identified compared to when integrating SEAP. The default development process left 50.0% of the risks unattended in the software version that was released, while the application of SEAP reduced that figure to 22.5%. Furthermore, SEAP increased the proportion of risks that were corrected from 12.5% to 67.9%, a more than five times increment.

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  • 59.
    Boldt, Martin
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Jacobsson, Andreas
    Carlsson, Bengt
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    On the risk exposure of smart home automation systems2014In: Proceedings 2014 International Conferenceon Future Internet of Things and Cloud, IEEE Computer Society Digital Library, 2014Conference paper (Refereed)
    Abstract [en]

    A recent study has shown that more than every fourth person in Sweden feels that they have poor knowledge and control over their energy use, and that four out of ten would like to be more aware and to have better control over their consumption [5]. A solution is to provide the householders with feedback on their energy consumption, for instance, through a smart home automation system [10]. Studies have shown that householders can reduce energy consumption with up to 20% when gaining such feedback [5] [10]. Home automation is a prime example of a smart environment built on various types of cyber-physical systems generating volumes of diverse, heterogeneous, complex, and distributed data from a multitude of applications and sensors. Thereby, home automation is also an example of an Internet of Things (IoT) scenario, where a communication network extends the present Internet by including everyday items and sensors [22]. Home automation is attracting more and more attention from commercial actors, such as, energy suppliers, infrastructure providers, and third party software and hardware vendors [8] [10]. Among the non-commercial stake-holders, there are various governmental institutions, municipalities, as well as, end-users.

  • 60.
    Boldt, Martin
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Rekanar, Kaavya
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Analysis and text classification of privacy policies from rogue and top-100 fortune global companies2019In: International Journal of Information Security and Privacy, ISSN 1930-1650, E-ISSN 1930-1669, Vol. 13, no 2, p. 47-66Article in journal (Refereed)
    Abstract [en]

    In the present article, the authors investigate to what extent supervised binary classification can be used to distinguish between legitimate and rogue privacy policies posted on web pages. 15 classification algorithms are evaluated using a data set that consists of 100 privacy policies from legitimate websites (belonging to companies that top the Fortune Global 500 list) as well as 67 policies from rogue websites. A manual analysis of all policy content was performed and clear statistical differences in terms of both length and adherence to seven general privacy principles are found. Privacy policies from legitimate companies have a 98% adherence to the seven privacy principles, which is significantly higher than the 45% associated with rogue companies. Out of the 15 evaluated classification algorithms, Naïve Bayes Multinomial is the most suitable candidate to solve the problem at hand. Its models show the best performance, with an AUC measure of 0.90 (0.08), which outperforms most of the other candidates in the statistical tests used. Copyright © 2019, IGI Global.

  • 61.
    BONAM, VEERA VENKATA SIVARAMAKRISHNA
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Multipath TCP and Measuring end-to-end TCP Throughput: Multipath TCP Descriptions and Ways to Improve TCP Performance2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Internet applications make use of the services provided by a transport protocol, such as TCP (a reliable, in-order stream protocol). We use this term Transport Service to mean the end-to- end service provided to application by the transport layer.

     

    That service can only be provided correctly if information about the intended usage is supplied from the application. The application may determine this information at the design time, compile time, or run time, and it may include guidance on whether a feature is required, a preference by the application, or something in between.

    Multipath TCP (MPTCP) adds the capability of using multiple paths to a regular TCP session. Even though it is designed to be totally backward compatible to applications. The data transport differs compared to regular TCP, and there are several additional degrees of freedom that the particular application may want to exploit.

     

    Multipath TCP is particularly useful in the context of wireless networks using both Wi-Fi and a mobile network is a typical use case. In addition to the gains in throughput from inverse multiplexing, links may be added or dropped as the user moves in or out of coverage without disrupting the end-to-end TCP connection. The problem of link handover is thus solved by abstraction in the transport layer, without any special mechanisms at the network or link level.

     

    Handover functionality can then be implemented at the endpoints without requiring special functionality in the sub-networks according to the Internet's end-to-end principle. Multipath TCP can balance a single TCP connection across multiple interfaces and reach very high throughput.

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    BTH2018BonamV
  • 62.
    Borg, Anton
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    On Descriptive and Predictive Models for Serial Crime Analysis2014Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Law enforcement agencies regularly collect crime scene information. There exists, however, no detailed, systematic procedure for this. The data collected is affected by the experience or current condition of law enforcement officers. Consequently, the data collected might differ vastly between crime scenes. This is especially problematic when investigating volume crimes. Law enforcement officers regularly do manual comparison on crimes based on the collected data. This is a time-consuming process; especially as the collected crime scene information might not always be comparable. The structuring of data and introduction of automatic comparison systems could benefit the investigation process. This thesis investigates descriptive and predictive models for automatic comparison of crime scene data with the purpose of aiding law enforcement investigations. The thesis first investigates predictive and descriptive methods, with a focus on data structuring, comparison, and evaluation of methods. The knowledge is then applied to the domain of crime scene analysis, with a focus on detecting serial residential burglaries. This thesis introduces a procedure for systematic collection of crime scene information. The thesis also investigates impact and relationship between crime scene characteristics and how to evaluate the descriptive model results. The results suggest that the use of descriptive and predictive models can provide feedback for crime scene analysis that allows a more effective use of law enforcement resources. Using descriptive models based on crime characteristics, including Modus Operandi, allows law enforcement agents to filter cases intelligently. Further, by estimating the link probability between cases, law enforcement agents can focus on cases with higher link likelihood. This would allow a more effective use of law enforcement resources, potentially allowing an increase in clear-up rates.

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  • 63.
    Borg, Anton
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Boldt, Martin
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Clustering Residential Burglaries Using Modus Operandi and Spatiotemporal Information2016In: International Journal of Information Technology & Decision Making, ISSN 0219-6220, E-ISSN 1793-6845, Vol. 15, no 1, p. 23-42Article in journal (Refereed)
    Abstract [en]

    To identify series of residential burglaries, detecting linked crimes performed by the same constellations of criminals is necessary. Comparison of crime reports today is difficult as crime reports traditionally have been written as unstructured text and often lack a common information-basis. Based on a novel process for collecting structured crime scene information, the present study investigates the use of clustering algorithms to group similar crime reports based on combined crime characteristics from the structured form. Clustering quality is measured using Connectivity and Silhouette index (SI), stability using Jaccard index, and accuracy is measured using Rand index (RI) and a Series Rand index (SRI). The performance of clustering using combined characteristics was compared with spatial characteristic. The results suggest that the combined characteristics perform better or similar to the spatial characteristic. In terms of practical significance, the presented clustering approach is capable of clustering cases using a broader decision basis.

  • 64.
    Borg, Anton
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Boldt, Martin
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Eliasson, Johan
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Detecting Crime Series Based on Route Estimation and Behavioral Similarity2017In: 2017 EUROPEAN INTELLIGENCE AND SECURITY INFORMATICS CONFERENCE (EISIC) / [ed] Brynielsson, J, IEEE , 2017, p. 1-8Conference paper (Refereed)
    Abstract [en]

    A majority of crimes are committed by a minority of offenders. Previous research has provided some support for the theory that serial offenders leave behavioral traces on the crime scene which could be used to link crimes to serial offenders. The aim of this work is to investigate to what extent it is possible to use geographic route estimations and behavioral data to detect serial offenders. Experiments were conducted using behavioral data from authentic burglary reports to investigate if it was possible to find crime routes with high similarity. Further, the use of burglary reports from serial offenders to investigate to what extent it was possible to detect serial offender crime routes. The result show that crime series with the same offender on average had a higher behavioral similarity than random crime series. Sets of crimes with high similarity, but without a known offender would be interesting for law enforcement to investigate further. The algorithm is also evaluated on 9 crime series containing a maximum of 20 crimes per series. The results suggest that it is possible to detect crime series with high similarity using analysis of both geographic routes and behavioral data recorded at crime scenes.

  • 65.
    Borg, Anton
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Boldt, Martin
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Eliasson, Johan
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Detecting Crime Series Based on Route Estimationand Behavioral Similarity2017Conference paper (Refereed)
    Abstract [en]

    A majority of crimes are committed by a minority of offenders. Previous research has provided some support for the theory that serial offenders leave behavioral traces on the crime scene which could be used to link crimes to serial offenders. The aim of this work is to investigate to what extent it is possible to use geographic route estimations and behavioral data to detect serial offenders. Experiments were conducted using behavioral data from authentic burglary reports to investigate if it was possible to find crime routes with high similarity. Further, the use of burglary reports from serial offenders to investigate to what extent it was possible to detect serial offender crime routes. The result show that crime series with the same offender on average had a higher behavioral similarity than random crime series. Sets of crimes with high similarity, but without a known offender would be interesting for law enforcement to investigate further. The algorithm is also evaluated on 9 crime series containing a maximum of 20 crimes per series. The results suggest that it is possible to detect crime series with high similarity using analysis of both geographic routes and behavioral data recorded at crime scenes.

  • 66.
    Borg, Anton
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Boldt, Martin
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Lavesson, Niklas
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Melander, Ulf
    Boeva, Veselka
    Detecting serial residential burglaries using clustering2014In: Expert Systems with Applications, ISSN 0957-4174 , Vol. 41, no 11, p. 5252-5266Article in journal (Refereed)
    Abstract [en]

    According to the Swedish National Council for Crime Prevention, law enforcement agencies solved approximately three to five percent of the reported residential burglaries in 2012. Internationally, studies suggest that a large proportion of crimes are committed by a minority of offenders. Law enforcement agencies, consequently, are required to detect series of crimes, or linked crimes. Comparison of crime reports today is difficult as no systematic or structured way of reporting crimes exists, and no ability to search multiple crime reports exist. This study presents a systematic data collection method for residential burglaries. A decision support system for comparing and analysing residential burglaries is also presented. The decision support system consists of an advanced search tool and a plugin-based analytical framework. In order to find similar crimes, law enforcement officers have to review a large amount of crimes. The potential use of the cut-clustering algorithm to group crimes to reduce the amount of crimes to review for residential burglary analysis based on characteristics is investigated. The characteristics used are modus operandi, residential characteristics, stolen goods, spatial similarity, or temporal similarity. Clustering quality is measured using the modularity index and accuracy is measured using the rand index. The clustering solution with the best quality performance score were residential characteristics, spatial proximity, and modus operandi, suggesting that the choice of which characteristic to use when grouping crimes can positively affect the end result. The results suggest that a high quality clustering solution performs significantly better than a random guesser. In terms of practical significance, the presented clustering approach is capable of reduce the amounts of cases to review while keeping most connected cases. While the approach might miss some connections, it is also capable of suggesting new connections. The results also suggest that while crime series clustering is feasible, further investigation is needed.

  • 67.
    Bouhennache, Rafik
    et al.
    Science and technology institute, university center of Mila, DZA.
    Bouden, Toufik
    ohammed Seddik Ben Yahia University of Jijel, DZA.
    Taleb-Ahmed, Abdmalik
    university of V alenciennes, FRA.
    Cheddad, Abbas
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering. Blekinge Institute of Technology.
    A new spectral index for the extraction of built-up land features from Landsat 8 satellite imagery2019In: Geocarto International, ISSN 1010-6049, E-ISSN 1752-0762, Vol. 34, no 14, p. 1531-1551Article in journal (Refereed)
    Abstract [en]

    Extracting built-up areas from remote sensing data like Landsat 8 satellite is a challenge. We have investigated it by proposing a new index referred as Built-up Land Features Extraction Index (BLFEI). The BLFEI index takes advantage of its simplicity and good separability between the four major component of urban system, namely built-up, barren, vegetation and water. The histogram overlap method and the Spectral Discrimination Index (SDI) are used to study separability. BLFEI index uses the two bands of infrared shortwaves, the red and green bands of the visible spectrum. OLI imagery of Algiers, Algeria, was used to extract built-up areas through BLFEI and some new previously developed built-up indices used for comparison. The water areas are masked out leading to Otsu’s thresholding algorithm to automatically find the optimal value for extracting built-up land from waterless regions. BLFEI, the new index improved the separability by 25% and the accuracy by 5%.

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  • 68.
    BRHANIE, BEKALU MULLU
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Multi-Label Classification Methods for Image Annotation2016Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
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  • 69. Brik, Bouziane
    et al.
    Lagraa, Nasreddine
    Abderrahmane, Lakas
    Cheddad, Abbas
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    DDGP: Distributed Data Gathering Protocol for vehicular networks2016In: Vehicular Communications, ISSN 2214-2096, Vol. 4, p. 15-29Article in journal (Refereed)
    Abstract [en]

    Vehicular Ad-Hoc Network (VANet) is an emerging research area, it offers a wide range of applications including safety, road traffic efficiency, and infotainment applications. Recently researchers are studying the possibility of making use of deployed VANet applications for data collection. In this case, vehicles are considered as mobile collectors that gather both real time and delay tolerant data and deliver them to interested entities. In this paper, we propose a novel Distributed Data Gathering Protocol (DDGP) for the collection of delay tolerant as well as real time data in both urban and highway environments. The main contribution of DDGP is a new medium access technique that enables vehicles to access the channel in a distributed way based on their location information. In addition, DDGP implements a new aggregation scheme, which deletes redundant, expired, and undesired data. We provide an analytical proof of correctness of DDGP, in addition to the performance evaluation through an extensive set of simulation experiments. Our results indicate that DDGP enhances the efficiency and the reliability of the data collection process by outperforming existing schemes in terms of several criteria such as delay and message overhead, aggregation ratio, and data retransmission rate. (C) 2016 Elsevier Inc. All rights reserved.

  • 70. Brik, Bouziane
    et al.
    Lagraa, Nasreddine
    Lakas, Abderrahmane
    Cherroun, Hadda
    Cheddad, Abbas
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    ECDGP: extended cluster-based data gathering protocol for vehicular networks2015In: Wireless Communications & Mobile Computing, ISSN 1530-8669, E-ISSN 1530-8677Article in journal (Refereed)
  • 71.
    Britto, Ricardo
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
    Freitas, Vitor
    Mendes, Emilia
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Usman, Muhammad
    Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
    Effort Estimation in Global Software Development: A systematic Literature Review2014In: Proceedings of the 2014 9th IEEE International Conference on Global Software Engineering, 2014, p. 135-144Conference paper (Refereed)
    Abstract [en]

    Nowadays, software systems are a key factor in the success of many organizations as in most cases they play a central role helping them attain a competitive advantage. However, despite their importance, software systems may be quite costly to develop, so substantially decreasing companies’ profits. In order to tackle this challenge, many organizations look for ways to decrease costs and increase profits by applying new software development approaches, like Global Software Development (GSD). Some aspects of the software project like communication, cooperation and coordination are more chal- lenging in globally distributed than in co-located projects, since language, cultural and time zone differences are factors which can increase the required effort to globally perform a software project. Communication, coordination and cooperation aspects affect directly the effort estimation of a project, which is one of the critical tasks related to the management of a software development project. There are many studies related to effort estimation methods/techniques for co-located projects. However, there are evidences that the co-located approaches do not fit to GSD. So, this paper presents the results of a systematic literature review of effort estimation in the context of GSD, which aimed at help both researchers and practitioners to have a holistic view about the current state of the art regarding effort estimation in the context of GSD. The results suggest that there is room to improve the current state of the art on effort estimation in GSD. 

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  • 72.
    Britto, Ricardo
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
    Mendes, Emilia
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Börstler, Jürgen
    Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
    An Empirical Investigation on Effort Estimation in Agile Global Software Development2015In: Proceedings of the 2015 IEEE 10th International Conference on Global Software Engineering, 2015, p. 38-45Conference paper (Refereed)
    Abstract [en]

    Effort estimation is a project management activity that is mandatory for the execution of softwareprojects. Despite its importance, there have been just a few studies published on such activities within the Agile Global Software Development (AGSD) context. Their aggregated results were recently published as part of a secondary study that reported the state of the art on effort estimationin AGSD. This study aims to complement the above-mentioned secondary study by means of anempirical investigation on the state of the practice on effort estimation in AGSD. To do so, a survey was carried out using as instrument an on-line questionnaire and a sample comprising softwarepractitioners experienced in effort estimation within the AGSD context. Results show that the effortestimation techniques used within the AGSD and collocated contexts remained unchanged, with planning poker being the one employed the most. Sourcing strategies were found to have no or a small influence upon the choice of estimation techniques. With regard to effort predictors, globalchallenges such as cultural and time zone differences were reported, in addition to factors that are commonly considered in the collocated context, such as team experience. Finally, many challenges that impact the accuracy of the effort estimates were reported by the respondents, such as problems with the software requirements and the fact that the communication effort between sites is not properly accounted.

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  • 73.
    Britto, Ricardo
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
    Mendes, Emilia
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Wohlin, Claes
    Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
    A Specialized Global Software Engineering Taxonomy for Effort Estimation2016In: International Conference on Global Software Engineering, IEEE Computer Society, 2016, p. 154-163Conference paper (Refereed)
    Abstract [en]

    To facilitate the sharing and combination of knowledge by Global Software Engineering (GSE) researchers and practitioners, the need for a common terminology and knowledge classification scheme has been identified, and as a consequence, a taxonomy and an extension were proposed. In addition, one systematic literature review and a survey on respectively the state of the art and practice of effort estimation in GSE were conducted, showing that despite its importance in practice, the GSE effort estimation literature is rare and reported in an ad-hoc way. Therefore, this paper proposes a specialized GSE taxonomy for effort estimation, which was built on the recently proposed general GSE taxonomy (including the extension) and was also based on the findings from two empirical studies and expert knowledge. The specialized taxonomy was validated using data from eight finished GSE projects. Our effort estimation taxonomy for GSE can help both researchers and practitioners by supporting the reporting of new GSE effort estimation studies, i.e. new studies are to be easier to identify, compare, aggregate and synthesize. Further, it can also help practitioners by providing them with an initial set of factors that can be considered when estimating effort for GSE projects.

  • 74.
    Britto, Ricardo
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
    Usman, Muhammad
    Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
    Mendes, Emilia
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    A TAXONOMY OF WEB EFFORT PREDICTORS2017In: Journal of Web Engineering, ISSN 1540-9589, E-ISSN 1544-5976, Vol. 16, no 7-8, p. 541-570Article in journal (Refereed)
    Abstract [en]

    Web engineering as a field has emerged to address challenges associated with developing Web applications. It is known that the development of Web applications differs from the development of non-Web applications, especially regarding some aspects such as Web size metrics. The classification of existing Web engineering knowledge would be beneficial for both practitioners and researchers in many different ways, such as finding research gaps and supporting decision making. In the context of Web effort estimation, a taxonomy was proposed to classify the existing size metrics, and more recently a systematic literature review was conducted to identify aspects related to Web resource/effort estimation. However, there is no study that classifies Web predictors (both size metrics and cost drivers). The main objective of this study is to organize the body of knowledge on Web effort predictors by designing and using a taxonomy, aiming at supporting both research and practice in Web effort estimation. To design our taxonomy, we used a recently proposed taxonomy design method. As input, we used the results of a previously conducted systematic literature review (updated in this study), an existing taxonomy of Web size metrics and expert knowledge. We identified 165 unique Web effort predictors from a final set of 98 primary studies; they were used as one of the basis to design our hierarchical taxonomy. The taxonomy has three levels, organized into 13 categories. We demonstrated the utility of the taxonomy and body of knowledge by using examples. The proposed taxonomy can be beneficial in the following ways: i) It can help to identify research gaps and some literature of interest and ii) it can support the selection of predictors for Web effort estimation. We also intend to extend the taxonomy presented to also include effort estimation techniques and accuracy metrics.

  • 75.
    Britto, Ricardo
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
    Usman, Muhammad
    Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
    Mendes, Emilia
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Effort Estimation in Agile Global Software Development Context2014In: Agile Methods. Large-Scale Development, Refactoring, Testing, and Estimation: XP 2014 International Workshops, Rome, Italy, May 26-30, 2014, Revised Selected Papers, Springer, 2014, Vol. 199, p. 182-192Conference paper (Refereed)
    Abstract [en]

    Both Agile Software Development (ASD) and Global Software Development (GSD) are 21st century trends in the software industry. Many studies are reported in the literature wherein software companies have applied an agile method or practice GSD. Given that effort estimation plays a remarkable role in software project management, how do companies perform effort estimation when they use agile method in a GSD context? Based on two effort estimation Systematic Literature Reviews (SLR) - one in within the ASD context and the other in a GSD context, this paper reports a study in which we combined the results of these SLRs to report the state of the art of effort estimation in agile global software development (ASD) context.

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  • 76.
    Britto, Ricardo
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
    Wohlin, Claes
    Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
    Mendes, Emilia
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    An Extended Global Software Engineering Taxonomy2016In: Journal of Software Engineering Research and Development, ISSN 2195-1721, Vol. 4, no 3Article in journal (Refereed)
    Abstract [en]

    In Global Software Engineering (GSE), the need for a common terminology and knowledge classification has been identified to facilitate the sharing and combination of knowledge by GSE researchers and practitioners. A GSE taxonomy was recently proposed to address such a need, focusing on a core set of dimensions; however its dimensions do not represent an exhaustive list of relevant GSE factors. Therefore, this study extends the existing taxonomy, incorporating new GSE dimensions that were identified by means of two empirical studies conducted recently.

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  • 77.
    Budda, Shiva Tarun
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Performance Analysis of Proxy based Encrypted communication in IoT environments: Security and Privacy ~ Distributed Systems Security2017Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
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  • 78.
    Cardellini, Valeria
    et al.
    Universita degli Studi di Roma Tor Vergata, ITA.
    Casalicchio, Emiliano
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Grassi, Vincenzo
    Universita degli Studi di Roma Tor Vergata, ITA.
    Iannucci, Stefano
    Universita degli Studi di Roma Tor Vergata, ITA.
    Lo Presti, F.
    Universita degli Studi di Roma Tor Vergata, ITA.
    Mirandola, Raffaela
    Politecnico di Milano, ITA.
    MOSES: A platform for experimenting with qos-driven self-adaptation policies for service oriented systems2017In: Lecture Notes in Computer Science, Springer Verlag , 2017, Vol. 9640, p. 409-433Conference paper (Refereed)
    Abstract [en]

    Architecting software systems according to the service-oriented paradigm, and designing runtime self-adaptable systems are two relevant research areas in today’s software engineering. In this chapter we present MOSES, a software platform supporting QoS-driven adaptation of service-oriented systems. It has been conceived for service-oriented systems architected as composite services that receive requests generated by different classes of users. MOSES integrates within a unified framework different adaptation mechanisms. In this way it achieves a greater flexibility in facing various operating environments and the possibly conflicting QoS requirements of several concurrent users. Besides providing its own self-adaptation functionalities, MOSES lends itself to the experimentation of alternative approaches to QoS-driven adaptation of service-oriented systems thanks to its modular architecture. © Springer International Publishing AG 2017.

  • 79.
    Carlsson, Anders
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Gustavsson, Rune
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Resilient Smart Grids2014In: 2014 FIRST INTERNATIONAL SCIENTIFIC-PRACTICAL CONFERENCE PROBLEMS OF INFOCOMMUNICATIONS SCIENCE AND TECHNOLOGY (PIC S&T), IEEE , 2014, p. 79-82Conference paper (Refereed)
    Abstract [en]

    The usefulness of configurable and shared experiment platforms in design and implementation of future Resilient Smart Grids is demonstrated. A set of antagonistic threats is identified and remotely controlled experiments to harness those are presented and assessed.

  • 80.
    Carlsson, Anders
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Gustavsson, Rune
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    The art of war in the cyber world2018In: 2017 4th International Scientific-Practical Conference Problems of Infocommunications Science and Technology, PIC S and T 2017 - Proceedings, Institute of Electrical and Electronics Engineers Inc. , 2018, p. 42-44Conference paper (Refereed)
    Abstract [en]

    The paper focus on cyber weapons used in Advanced Persistent Threat (ATP) attacks in present and future cyber warfare. The combined use of propaganda and cyber warfare supports military operations on the ground and is exemplified with the ongoing Russian hybrid warfare in Ukraine. New models and methods to develop future trustworthy critical infrastructures in our societies are presented. Some mitigation ideas to meet the challenges of future hybrid warfare are also discussed. © 2017 IEEE.

  • 81.
    Carlsson, Oskar
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Nabhani, Daniel
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    User and Entity Behavior Anomaly Detection using Network Traffic2017Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
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  • 82.
    Casalicchio, Emiliano
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    A study on performance measures for auto-scaling CPU-intensive containerized applications2019In: Cluster Computing, ISSN 1386-7857, E-ISSN 1573-7543, Vol. 22, no 3, p. 995-1006, article id Special Issue: SIArticle in journal (Refereed)
    Abstract [en]

    Autoscaling of containers can leverage performance measures from the different layers of the computational stack. This paper investigate the problem of selecting the most appropriate performance measure to activate auto-scaling actions aiming at guaranteeing QoS constraints. First, the correlation between absolute and relative usage measures and how a resource allocation decision can be influenced by them is analyzed in different workload scenarios. Absolute and relative measures could assume quite different values. The former account for the actual utilization of resources in the host system, while the latter account for the share that each container has of the resources used. Then, the performance of a variant of Kubernetes’ auto-scaling algorithm, that transparently uses the absolute usage measures to scale-in/out containers, is evaluated through a wide set of experiments. Finally, a detailed analysis of the state-of-the-art is presented.

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  • 83.
    Casalicchio, Emiliano
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Cardellini, Valeria
    University of Rome, ITA.
    Interino, Gianluca
    University of Rome, ITA.
    Palmirani, Monica
    University of Bologna, ITA.
    Research challenges in legal-rule and QoS-aware cloud service brokerage2018In: Future generations computer systems, ISSN 0167-739X, E-ISSN 1872-7115, Vol. 78, no Part 1, p. 211-223Article in journal (Refereed)
    Abstract [en]

    Abstract The ICT industry and specifically critical sectors, such as healthcare, transportation, energy and government, require as mandatory the compliance of ICT systems and services with legislation and regulation, as well as with standards. In the era of cloud computing, this compliance management issue is exacerbated by the distributed nature of the system and by the limited control that customers have on the services. Today, the cloud industry is aware of this problem (as evidenced by the compliance program of many cloud service providers), and the research community is addressing the many facets of the legal-rule compliance checking and quality assurance problem. Cloud service brokerage plays an important role in legislation compliance and QoS management of cloud services. In this paper we discuss our experience in designing a legal-rule and QoS-aware cloud service broker, and we explore relate research issues. Specifically we provide three main contributions to the literature: first, we describe the detailed design architecture of the legal-rule and QoS-aware broker. Second, we discuss our design choices which rely on the state of the art solutions available in literature. We cover four main research areas: cloud broker service deployment, seamless cloud service migration, cloud service monitoring, and legal rule compliance checking. Finally, from the literature review in these research areas, we identify and discuss research challenges.

  • 84.
    Casalicchio, Emiliano
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Lundberg, Lars
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Shirinbab, Sogand
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Energy-Aware Adaptation in Managed Cassandra Datacenters2016In: Proceedings - 2016 International Conference on Cloud and Autonomic Computing, ICCAC / [ed] Gupta I.,Diao Y., IEEE, 2016, p. 60-71Conference paper (Refereed)
    Abstract [en]

    Today, Apache Cassandra, an highly scalable and available NoSql datastore, is largely used by enterprises of each size and for application areas that range from entertainment to big data analytics. Managed Cassandra service providers are emerging to hide the complexity of the installation, fine tuning and operation of Cassandra datacenters. As for all complex services, human assisted management of a multi-tenant cassandra datacenter is unrealistic. Rather, there is a growing demand for autonomic management solutions. In this paper, we present an optimal energy-aware adaptation model for managed Cassandra datacenters that modify the system configuration orchestrating three different actions: horizontal scaling, vertical scaling and energy aware placement. The model is built from a real case based on real application data from Ericsson AB. We compare the performance of the optimal adaptation with two heuristics that avoid system perturbations due to re-configuration actions triggered by subscription of new tenants and/or changes in the SLA. One of the heuristic is local optimisation and the second is a best fit decreasing algorithm selected as reference point because representative of a wide range of research and practical solutions. The main finding is that heuristic’s performance depends on the scenario and workload and no one dominates in all the cases. Besides, in high load scenarios, the suboptimal system configuration obtained with an heuristic adaptation policy introduce a penalty in electric energy consumption in the range [+25%, +50%] if compared with the energy consumed by an optimal system configuration.

  • 85.
    Casalicchio, Emiliano
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Lundberg, Lars
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Shirinbab, Sogand
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Energy-aware Auto-scaling Algorithms for Cassandra Virtual Data Centers2017In: Cluster Computing, ISSN 1386-7857, E-ISSN 1573-7543, Vol. 20, no 3, p. 2065-2082Article in journal (Refereed)
    Abstract [en]

    Apache Cassandra is an highly scalable and available NoSql datastore, largely used by enterprises of each size and for application areas that range from entertainment to big data analytics. Managed Cassandra service providers are emerging to hide the complexity of the installation, fine tuning and operation of Cassandra Virtual Data Centers (VDCs). This paper address the problem of energy efficient auto-scaling of Cassandra VDC in managed Cassandra data centers. We propose three energy-aware autoscaling algorithms: \texttt{Opt}, \texttt{LocalOpt} and \texttt{LocalOpt-H}. The first provides the optimal scaling decision orchestrating horizontal and vertical scaling and optimal placement. The other two are heuristics and provide sub-optimal solutions. Both orchestrate horizontal scaling and optimal placement. \texttt{LocalOpt} consider also vertical scaling. In this paper: we provide an analysis of the computational complexity of the optimal and of the heuristic auto-scaling algorithms; we discuss the issues in auto-scaling Cassandra VDC and we provide best practice for using auto-scaling algorithms; we evaluate the performance of the proposed algorithms under programmed SLA variation, surge of throughput (unexpected) and failures of physical nodes. We also compare the performance of energy-aware auto-scaling algorithms with the performance of two energy-blind auto-scaling algorithms, namely \texttt{BestFit} and \texttt{BestFit-H}. The main findings are: VDC allocation aiming at reducing the energy consumption or resource usage in general can heavily reduce the reliability of Cassandra in term of the consistency level offered. Horizontal scaling of Cassandra is very slow and make hard to manage surge of throughput. Vertical scaling is a valid alternative, but it is not supported by all the cloud infrastructures.

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  • 86.
    Casalicchio, Emiliano
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Lundberg, Lars
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Shirinbab, Sogand
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Optimal adaptation for Apache Cassandra2016In: SoSeMC workshop at 13th IEEE International Conference on Autonomic Computing / [ed] IEEE, IEEE Computer Society, 2016Conference paper (Refereed)
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  • 87.
    Casalicchio, Emiliano
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Lundberg, Lars
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Shirinbad, Sogand
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    An Energy-Aware Adaptation Model for Big Data Platforms2016In: 2016 IEEE International Conference on Autonomic Computing (ICAC) / [ed] IEEE, IEEE, 2016, p. 349-350Conference paper (Refereed)
    Abstract [en]

    Platforms for big data includes mechanisms and tools to model, organize, store and access big data (e.g. Apache Cassandra, Hbase, Amazon SimpleDB, Dynamo, Google BigTable). The resource management for those platforms is a complex task and must account also for multi-tenancy and infrastructure scalability. Human assisted control of Big data platform is unrealistic and there is a growing demand for autonomic solutions. In this paper we propose a QoS and energy-aware adaptation model designed to cope with the real case of a Cassandra-as-a-Service provider.

  • 88.
    Casalicchio, Emiliano
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Perciballi, Vanessa
    Spindox S.p.A, ITA.
    Auto-scaling of Containers: The Impact of Relative and Absolute Metrics2017In: 2017 IEEE 2nd International Workshops on Foundations and Applications of Self* Systems, FAS*W 2017 / [ed] IEEE, IEEE, 2017, p. 207-214, article id 8064125Conference paper (Refereed)
    Abstract [en]

    Today, The cloud industry is adopting the container technology both for internal usage and as commercial offering. The use of containers as base technology for large-scale systems opens many challenges in the area of resource management at run-time. This paper addresses the problem of selecting the more appropriate performance metrics to activate auto-scaling actions. Specifically, we investigate the use of relative and absolute metrics. Results demonstrate that, for CPU intense workload, the use of absolute metrics enables more accurate scaling decisions. We propose and evaluate the performance of a new autoscaling algorithm that could reduce the response time of a factor between 0.66 and 0.5 compared to the actual Kubernetes' horizontal auto-scaling algorithm.

  • 89.
    Casalicchio, Emiliano
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Perciballi, Vanessa
    University of Rome, ITA.
    Measuring Docker Performance: What a Mess!!!2017In: ICPE 2017 - Companion of the 2017 ACM/SPEC International Conference on Performance Engineering, ACM , 2017, p. 11-16Conference paper (Refereed)
    Abstract [en]

    Today, a new technology is going to change the way platforms for the internet of services are designed and managed. This technology is called container (e.g. Docker and LXC). The internet of service industry is adopting the container technology both for internal usage and as commercial offering. The use of container as base technology for large-scale systems opens many challenges in the area of resource management at run-time, for example: autoscaling, optimal deployment and monitoring. Specifically, monitoring of container based systems is at the ground of any resource management solution, and it is the focus of this work. This paper explores the tools available to measure the performance of Docker from the perspective of the host operating system and of the virtualization environment, and it provides a characterization of the CPU and disk I/O overhead introduced by containers.

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  • 90.
    Chadalapaka, Gayatri
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering. BTH.
    Performance Assessment of Spectrum Sharing Systems: with Service Differentiation2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
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    BTH2018Chadalapaka
  • 91.
    Chai, Yi
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    A novel progressive mesh representation method based on the half-edge data structure and √3 subdivision2015Independent thesis Advanced level (degree of Master (Two Years))Student thesis
    Abstract [en]

    Progressive mesh (PM) representation can perfectly meet the requirements of generating multi-resolutions for a detailed 3D model. This research proposes a new PM representation method to improve the PM representation storage efficiency and reduce PM generation time. In existing PM representation methods, more than 4 adjacent vertices will be stored for one vertex in the PM representation. Furthermore, the methods always use the inefficient vertex and face list representation during the generation process. In our proposed method, only three vertices are stored by using the √3 subdivision scheme and the efficient half-edge data structure replaces the vertex and face list representation. To evaluate the proposed method, a designed experiment is conducted by using three common testing 3D models. The result illustrates the improvements by comparing to other previous methods.

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  • 92.
    Chalasani, Trishala
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    AUTOMATED ASSESSMENT FOR THE THERAPY SUCCESS OF FOREIGN ACCENT SYNDROME: Based on Emotional Temperature2017Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Context. Foreign Accent Syndrome is a rare neurological disorder, where among other symptoms of the patient’s emotional speech is affected. As FAS is one of the mildest speech disorders, there has not been much research done on the cost-effective biomarkers which reflect recovery of competences speech.

    Objectives. In this pilot study, we implement the Emotional Temperature biomarker and check its validity for assessing the FAS. We compare the results of implemented biomarker with another biomarker based on the global distances for FAS and identify the better one.

    Methods. To reach the objective, the emotional speech data of two patients at different phases of the treatment are considered. After preprocessing, experiments are performed on various window sizes and the observed correctly classified instances in automatic recognition are used to calculate Emotional temperature. Further, we use the better biomarker for tracking the recovery in the patient’s speech.

    Results. The Emotional temperature of the patient is calculated and compared with the ground truth and with that of the other biomarker. The Emotional temperature is calculated to track the emergence of compensatory skills in speech.

    Conclusions. A biomarker based on the frame-view of speech signal has been implemented. The implementation has used the state of art feature set and thus is an unproved version of the classical Emotional Temperature. The biomarker has been used to automatically assess the recovery of two patients diagnosed with FAS. The biomarker has been compared against the global view biomarker and has advantages over it. It also has been compared to human evaluations and captures the same dynamics.

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  • 93.
    Cheddad, Abbas
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Structure Preserving Binary Image Morphing using Delaunay Triangulation2017In: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 85, p. 8-14Article in journal (Refereed)
    Abstract [en]

    Mathematical morphology has been of a great significance to several scientific fields. Dilation, as one of the fundamental operations, has been very much reliant on the common methods based on the set theory and on using specific shaped structuring elements to morph binary blobs. We hypothesised that by performing morphological dilation while exploiting geometry relationship between dot patterns, one can gain some advantages. The Delaunay triangulation was our choice to examine the feasibility of such hypothesis due to its favourable geometric properties. We compared our proposed algorithm to existing methods and it becomes apparent that Delaunay based dilation has the potential to emerge as a powerful tool in preserving objects structure and elucidating the influence of noise. Additionally, defining a structuring element is no longer needed in the proposed method and the dilation is adaptive to the topology of the dot patterns. We assessed the property of object structure preservation by using common measurement metrics. We also demonstrated such property through handwritten digit classification using HOG descriptors extracted from dilated images of different approaches and trained using Support Vector Machines. The confusion matrix shows that our algorithm has the best accuracy estimate in 80% of the cases. In both experiments, our approach shows a consistent improved performance over other methods which advocates for the suitability of the proposed method.

  • 94.
    Cheddad, Abbas
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Towards Query by Text Example for pattern spotting in historical documents2016In: Proceedings - CSIT 2016: 2016 7th International Conference on Computer Science and Information Technology, IEEE Computer Society, 2016, article id 7549479Conference paper (Refereed)
    Abstract [en]

    Historical documents are essentially formed of handwritten texts that exhibit a variety of perceptual environment complexities. The cursive and connected nature of text lines on one hand and the presence of artefacts and noise on the other hand hinder achieving plausible results using current image processing algorithm. In this paper, we present a new algorithm which we termed QTE (Query by Text Example) that allows for training-free and binarisation-free pattern spotting in scanned handwritten historical documents. Our algorithm gives promising results on a subset of our database revealing ∌83% success rate in locating word patterns supplied by the user.

  • 95.
    Cheddad, Abbas
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Kusetogullari, Hüseyin
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Grahn, Håkan
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Object recognition using shape growth pattern2017In: Proceedings of the 10th International Symposium on Image and Signal Processing and Analysis, ISPA, IEEE Computer Society Digital Library, 2017, p. 47-52, article id 8073567Conference paper (Refereed)
    Abstract [en]

    This paper proposes a preprocessing stage to augment the bank of features that one can retrieve from binary images to help increase the accuracy of pattern recognition algorithms. To this end, by applying successive dilations to a given shape, we can capture a new dimension of its vital characteristics which we term hereafter: the shape growth pattern (SGP). This work investigates the feasibility of such a notion and also builds upon our prior work on structure preserving dilation using Delaunay triangulation. Experiments on two public data sets are conducted, including comparisons to existing algorithms. We deployed two renowned machine learning methods into the classification process (i.e., convolutional neural network-CNN- and random forests-RF-) since they perform well in pattern recognition tasks. The results show a clear improvement of the proposed approach's classification accuracy (especially for data sets with limited training samples) as well as robustness against noise when compared to existing methods.

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  • 96.
    Chinta, Ruthvik
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Measurement of Game Immersion through Subjective Approach2017Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Context. People in recent times are getting engaged more often in playing video games. Few play for enjoyment, few play for stress relaxation and so on. Generally, the degree of involvement of a player with the game is described as game immersion. People when immersed into playing a game doesn't realize that they are getting dissociated with the outside world and are losing track of time.

    Objectives. In this research, the main objective is to explore the relationship between the game immersion and game experience using the five factors of game immersion. In addition, the study also involves exploring different methods that can be used to measure game immersion.

    Methods. In this research, initially literature review has been conducted to explore the meaning of game immersion and also different methods that can be used to measure it and next user studies in the form an experiment was conducted to measure game immersion. After the experiment was conducted regression analysis was performed on the data obtained from the results to describe the relation between game immersion and game experience.

    Results. After the experiment participants were asked to answer the IEQ questionnaire and the answers obtained from the questionnaire are analyzed using regression analysis. An inverse linear regression was observed between game immersion and game experience.

    Conclusions. After analyzing the data, from the observed inverse linear regression, it is concluded that game immersion levels decrease with the increase in the game experience.

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  • 97.
    Dagala, Wadzani Jabani
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Analysis of Total Cost of Ownership for Medium Scale Cloud Service Provider with emphasis on Technology and Security2017Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Total cost of ownership is a great factor to consider when deciding to deploy cloud computing. The cost to own a data centre or run a data centre outweighs the thought of IT manager or owner of the business organisation.The research work is concerned with specifying the factors that sum the TCO for medium scale service providers with respect to technology and security. A valid analysis was made with respect to the cloud service providers expenses and how to reduce the cost of ownership.In this research work, a review of related articles was used from a wide source, reading through the abstract and overview of the articles to find its relevance to the subject. A further interview was conducted with two medium scale cloud service providers and one cloud user.In this study, an average calculation of the TCO was made and we implemented a proposed cost reduction method. We made a proposal on which and how to decide as to which cloud services users should deploy in terms of cost and security.We conclude that many articles have focused their TCO calculation on the building without making emphasis on the security. The security accumulates huge amount under hidden cost and this research work identified the hidden cost, made an average calculation and proffer a method of reducing the TCO.

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  • 98.
    Dallora Moraes, Ana Luiza
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Supplementary Material of: “Prognosis of dementia with machine learning and microssimulation techniques: a systematic literature review”.2016Other (Other academic)
    Abstract [en]

     This document contains the supplementary material regarding the systematic literature review entitled: “Prognosis of dementia with machine learning and microssimulation techniques: a systematic literature review”.

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  • 99.
    Dallora Moraes, Ana Luiza
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Systematic Literature Review Protocol:  Machine Learning and Microsimulation Techniques on the Prognosis of Dementia: A Systematic Literature Review2016Other (Other academic)
    Abstract [en]

     This document contains the protocol followed to conduct the systematic literature review entitled: “Machine Learning and Microsimulation Techniques on the Prognosis of Dementia: A Systematic Literature Review”.

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    attachment
  • 100.
    Danielsson, Max
    et al.
    Blekinge Institute of Technology, Faculty of Computing, Department of Technology and Aesthetics.
    Grahn, Håkan
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
    Sievert, Thomas
    Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.
    Rasmusson, Jim
    Sony Mobile Communications AB, SWE.
    Comparing Two Generations of Embedded GPUs Running a Feature Detection AlgorithmManuscript (preprint) (Other academic)
    Abstract [en]

    Graphics processing units (GPUs) in embedded mobile platforms are reaching performance levels where they may be useful for computer vision applications. We compare two generations of embedded GPUs for mobile devices when run- ning a state-of-the-art feature detection algorithm, i.e., Harris- Hessian/FREAK. We compare architectural differences, execu- tion time, temperature, and frequency on Sony Xperia Z3 and Sony Xperia XZ mobile devices. Our results indicate that the performance soon is sufficient for real-time feature detection, the GPUs have no temperature problems, and support for large work-groups is important.

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