Change search
Refine search result
1 - 6 of 6
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1.
    Bru, Thomas
    et al.
    RISE - Research Institutes of Sweden (2017-2019), Materials and Production, SICOMP. Chalmers University of Technology, Sweden.
    Hellström, Peter
    RISE - Research Institutes of Sweden (2017-2019), Materials and Production, SICOMP.
    Gutkin, Renaud
    RISE - Research Institutes of Sweden (2017-2019), Materials and Production, SICOMP.
    Ramantani, Dimitra
    RISE - Research Institutes of Sweden (2017-2019), Materials and Production, SICOMP.
    Peterson, Göran
    Volvo Group Trucks Technology, Sweden.
    Characterisation of the mechanical and fracture properties of a uni-weave carbon fibre/epoxy non-crimp fabric composite2016In: Data in Brief, E-ISSN 2352-3409, Vol. 6, p. 680-695Article in journal (Refereed)
    Abstract [en]

    A complete database of the mechanical properties of an epoxy polymer reinforced with uni-weave carbon fibre non-crimp fabric (NCF) is established. In-plane and through-the-thickness tests were performed on unidirectional laminates under normal loading and shear loading. The response under cyclic shear loading was also measured. The material has been characterised in terms of stiffness, strength, and failure features for the different loading cases. The critical energy release rates associated with different failure modes in the material were measured from interlaminar and translaminar fracture toughness tests. The stress–strain data of the tensile, compressive, and shear test specimens are included. The load–deflection data for all fracture toughness tests are also included. The database can be used in the development and validation of analytical and numerical models of fibre reinforced plastics (FRPs), in particular FRPs with NCF reinforcements.

    Download full text (pdf)
    fulltext
  • 2.
    Hongisto, Valtteri
    et al.
    Turku University of Applied Sciences, Finland.
    Alakoivu, Reijo
    Turku University of Applied Sciences, Finland.
    Virtanen, J
    Turku University of Applied Sciences, Finland.
    Hakala, J.
    Turku University of Applied Sciences, Finland.
    Saarinen, P.
    Turku University of Applied Sciences, Finland.
    Laukka, J.
    Turku University of Applied Sciences, Finland.
    Linderholt, Andreas
    Linnaeus University, Sweden.
    Olsson, Jörgen
    RISE Research Institutes of Sweden, Built Environment, Building and Real Estate.
    Jarnerö, Kirsi
    RISE Research Institutes of Sweden, Built Environment, Building and Real Estate.
    Keränen, J.
    Turku University of Applied Sciences, Finland.
    Sound insulation dataset of 30 wooden and 8 concrete floors tested in laboratory conditions2023In: Data in Brief, E-ISSN 2352-3409, Vol. 49, article id 109393Article in journal (Refereed)
    Abstract [en]

    In a Finnish-Swedish consortium project, a large amount of sound insulation tests was conducted for several intermediate floors in laboratory conditions to serve various scientific research questions. The dataset contains 30 wooden and 8 concrete constructions which are commonly used between apartments in multistorey buildings. Impact sound insulation was determined according to ISO 10140-3 standard using both tapping machine and rubber ball as standard sound sources. Airborne sound insulation was determined according to the ISO 10140-2 standard. The data are special since they have a broad frequency range: 20−5000 Hz. Data are reported in 1/3-octave frequency bands and the single-number values of ISO 717-1 and ISO 717-2 are also reported. Detailed construction drawings are available for all reported constructions. The data are highly valuable for research, education, and development purposes since all data were obtained in the same laboratory (Turku University of Applied Sciences, Turku, Finland), and all the constructions were built by the same installation team. © 2023 The Authors

  • 3.
    Landberg, G.
    et al.
    University of Gothenburg, Sweden.
    Jonasson, E.
    University of Gothenburg, Sweden.
    Gustafsson, A.
    University of Gothenburg, Sweden.
    Fitzpatrick, P.
    University of Gothenburg, Sweden.
    Isakson, P.
    University of Gothenburg, Sweden.
    Karlsson, J.
    University of Gothenburg, Sweden.
    Larsson, E.
    University of Gothenburg, Sweden.
    Svanström, A.
    University of Gothenburg, Sweden.
    Rafnsdottir, S.
    University of Gothenburg, Sweden.
    Persson, E.
    University of Gothenburg, Sweden.
    Andersson, D.
    University of Gothenburg, Sweden.
    Rosendahl, Jennifer
    RISE Research Institutes of Sweden, Materials and Production, Chemistry, Biomaterials and Textiles.
    Petronis, Sarunas
    RISE Research Institutes of Sweden, Materials and Production, Chemistry, Biomaterials and Textiles.
    Ranji, P.
    University of Gothenburg, Sweden.
    Gregersson, P.
    University of Gothenburg, Sweden.
    Magnusson, Y.
    University of Gothenburg, Sweden.
    Håkansson, Joakim
    RISE Research Institutes of Sweden, Materials and Production, Chemistry, Biomaterials and Textiles.
    Ståhlberg, A.
    University of Gothenburg, Sweden; Sahlgrenska University Hospital, Sweden.
    Characterization of cell-free breast cancer patient-derived scaffolds using liquid chromatography-mass spectrometry/mass spectrometry data and RNA sequencing data2020In: Data in Brief, E-ISSN 2352-3409, Vol. 31, article id 105860Article in journal (Refereed)
    Abstract [en]

    Patient-derived scaffolds (PDSs) generated from primary breast cancer tumors can be used to model the tumor microenvironment in vitro. Patient-derived scaffolds are generated by repeated detergent washing, removing all cells. Here, we analyzed the protein composition of 15 decellularized PDSs using liquid chromatography-mass spectrometry/mass spectrometry. One hundred forty-three proteins were detected and their relative abundance was calculated using a reference sample generated from all PDSs. We performed heatmap analysis of all the detected proteins to display their expression patterns across different PDSs together with pathway enrichment analysis to reveal which processes that were connected to PDS protein composition. This protein dataset together with clinical information is useful to investigators studying the microenvironment of breast cancers. Further, after repopulating PDSs with either MCF7 or MDA-MB-231 cells, we quantified their gene expression profiles using RNA sequencing. These data were also compared to cells cultured in conventional 2D conditions, as well as to cells cultured as xenografts in immune-deficient mice. We investigated the overlap of genes regulated between these different culture conditions and performed pathway enrichment analysis of genes regulated by both PDS and xenograft cultures compared to 2D in both cell lines to describe common processes associated with both culture conditions. Apart from our described analyses of these systems, these data are useful when comparing different experimental model systems. Downstream data analyses and interpretations can be found in the research article “Patient-derived scaffolds uncover breast cancer promoting properties of the microenvironment” [1]. © 2020 The Authors

  • 4.
    Pericault, Youen
    et al.
    Luleå University of Technology, Sweden.
    Kärrman, Erik
    RISE - Research Institutes of Sweden (2017-2019), Built Environment, Energy and Circular Economy.
    Viklander, Maria
    Luleå University of Technology, Sweden.
    Hedström, Annelie
    Luleå University of Technology, Sweden.
    Data supporting the life cycle impact assessment and cost evaluation of technical alternatives for providing water and heating services to a suburban development in Gällivare Sweden.2018In: Data in Brief, E-ISSN 2352-3409, Vol. 21, p. 1204-1208Article in journal (Refereed)
    Abstract [en]

    The article presents input data that were used in Pericault et al. (2018) for life cycle impact assessment and total cost assessment of five technical alternatives for heat and water services provision in a suburban development in Sweden. The data consists of a list of environmental impacts (cumulative exergy demand of energy carriers - CExDe, global warming potential - GWP, abiotic depletion potential of elements - ADPE), costs, amortisation periods, lifetimes and output flows of the system processes composing the alternatives. The data was derived from values collected in lifecycle databases, environmental product declarations, scientific publications and personal communications with companies.

  • 5.
    Strandberg, Per Erik
    et al.
    Westermo Network Technologies AB, Sweden.
    Söderman, David
    Westermo Network Technologies AB, Sweden.
    Dehlaghi Ghadim, Alireza
    RISE Research Institutes of Sweden, Digital Systems, Industrial Systems. Mälardalen University, Sweden.
    Leon, Miguel
    Mälardalen University, Sweden.
    Markovic, Tijana
    Mälardalen University, Sweden.
    Punnekkat, Sasikumar
    Mälardalen University, Sweden.
    Helali Moghadam, Mahshid
    RISE Research Institutes of Sweden, Digital Systems, Data Science.
    Buffoni, David
    Tietoevry, Sweden.
    The Westermo network traffic data set2023In: Data in Brief, E-ISSN 2352-3409, Vol. 50, article id 109512Article in journal (Refereed)
    Abstract [en]

    There is a growing body of knowledge on network intrusion detection, and several open data sets with network traffic and cyber-security threats have been released in the past decades. However, many data sets have aged, were not collected in a contemporary industrial communication system, or do not easily support research focusing on distributed anomaly detection. This paper presents the Westermo network traffic data set, 1.8 million network packets recorded in over 90 minutes in a network built up of twelve hardware devices. In addition to the raw data in PCAP format, the data set also contains pre-processed data in the form of network flows in CSV files. This data set can support the research community for topics such as intrusion detection, anomaly detection, misconfiguration detection, distributed or federated artificial intelligence, and attack classification. In particular, we aim to use the data set to continue work on resource-constrained distributed artificial intelligence in edge devices. The data set contains six types of events: harmless SSH, bad SSH, misconfigured IP address, duplicated IP address, port scan, and man in the middle attack.

  • 6.
    Svanström, Fredrik
    et al.
    Swedish Armed Forces, Sweden.
    Alonso-Fernandez, Fernando
    Halmstad University, Sweden.
    Englund, Cristofer
    RISE Research Institutes of Sweden, Digital Systems, Mobility and Systems. Halmstad University, Sweden.
    A dataset for multi-sensor drone detection2021In: Data in Brief, E-ISSN 2352-3409, Vol. 39, article id 107521Article in journal (Refereed)
    Abstract [en]

    The use of small and remotely controlled unmanned aerial vehicles (UAVs), referred to as drones, has increased dramatically in recent years, both for professional and recreative purposes. This goes in parallel with (intentional or unintentional) misuse episodes, with an evident threat to the safety of people or facilities [1]. As a result, the detection of UAV has also emerged as a research topic [2]. Most of the existing studies on drone detection fail to specify the type of acquisition device, the drone type, the detection range, or the employed dataset. The lack of proper UAV detection studies employing thermal infrared cameras is also acknowledged as an issue, despite its success in detecting other types of targets [2]. Beside, we have not found any previous study that addresses the detection task as a function of distance to the target. Sensor fusion is indicated as an open research issue as well to achieve better detection results in comparison to a single sensor, although research in this direction is scarce too [3–6]. To help in counteracting the mentioned issues and allow fundamental studies with a common public benchmark, we contribute with an annotated multi-sensor database for drone detection that includes infrared and visible videos and audio files. The database includes three different drones, a small-sized model (Hubsan H107D+), a medium-sized drone (DJI Flame Wheel in quadcopter configuration), and a performance-grade model (DJI Phantom 4 Pro). It also includes other flying objects that can be mistakenly detected as drones, such as birds, airplanes or helicopters. In addition to using several different sensors, the number of classes is higher than in previous studies [4]. The video part contains 650 infrared and visible videos (365 IR and 285 visible) of drones, birds, airplanes and helicopters. Each clip is of ten seconds, resulting in a total of 203,328 annotated frames. The database is complemented with 90 audio files of the classes drones, helicopters and background noise. To allow studies as a function of the sensor-to-target distance, the dataset is divided into three categories (Close, Medium, Distant) according to the industry-standard Detect, Recognize and Identify (DRI) requirements [7], built on the Johnson criteria [8]. Given that the drones must be flown within visual range due to regulations, the largest sensor-to-target distance for a drone in the dataset is 200 m, and acquisitions are made in daylight. The data has been obtained at three airports in Sweden: Halmstad Airport (IATA code: HAD/ICAO code: ESMT), Gothenburg City Airport (GSE/ESGP) and Malmö Airport (MMX/ESMS). The acquisition sensors are mounted on a pan-tilt platform that steers the cameras to the objects of interest. All sensors and the platform are controlled with a standard laptop vis a USB hub.

1 - 6 of 6
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf