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263 results for “forensics”
Dataset Literature Review digital forensic AND discriminant analysis
<p>data ini digunakan untuk membuat penelitian berdasarkan tinjauan literatur dengan kata kunci "digital forensic" dan discriminant analysis"</p>
Dataset Literature Review Digital Forensic And Methods
<p>Data ini diambil dari website lens.org dengan memasukkan keyword/kata kunci “Digital Forensic””Methods” pada Sholarly Works yang kemudian difilter sebanyak 3 kali. Yang pertama di filter pada bagian Document Type menjadi “Journal Article”. Kedua, di filter pada Years dengan data rate 10 tahun mulai tahun 2002 sampai dengan tahun 2012. Kemudian di filter kembali pada bagian Subject, Subject Matter “Law”. Pada setiap tahapan mulai awal hingga akhir semua data tersebut di export dengan format CSV dan BIBTEX. Selain itu juga dengan mengambil semua gambar analysis pada tahap akhir pemfilteran.</p>
IoT Forensic Analysis: a Family of Experiments with Amazon Echo Devices (ISP diagrams and Teardown videos)
<p>The two zip files (i.e., ISP Diagrams.zip and Teardown videos.zip) contain the ISP diagrams and teardown videos of the Amazon Echo Show IoT devices used in the experiment that we report in our research paper titled "IoT Forensic Analysis: a Family of Experiments with Amazon Echo Devices."</p>
Dataset literature review digital forensic and male
<p>data yang digunakan untuk membuat penelitian berdasarkan tinjauan dengan kata kunci digital forensic and male</p>
Database Publication - Exploring adult age-at-death research in anthropology: Bibliometric mapping and content analysis, Forensic Sciences, 2023
<p>The dataset contains the publications' ID and DOI numbers used in the bibliometric analysis for the paper "Exploring adult age-at-death research in anthropology: Bibliometric mapping and content analysis," which was published in Forensic Sciences. Dimensions only granted the authors permission to disclose the publication IDs and DOIs for this study. However, using the identification codes, it is possible to extract titles' full metadata through Dimensions (<a href="https://www.dimensions.ai/">https://www.dimensions.ai/</a>).</p>
Fig. 1 in The distribution, habitat, diet and forensic significance of the scarab Frankenbergerius forcipatus (Harold, 1881) (Coleoptera: Scarabaeidae)
Fig. 1. Habitat of Frankenbergerius forcipatus near Waainek (a) and Jameson Dam (b). The carcasses were located on the ground amongst vegetation. (Photographs by JMM)
Figure 1 in Formicidae fauna in pig carcasses contaminated by insecticide: implications for forensic entomology
Figure 1 Median (square), quartile range (box) and total range (vertical line) of the species richness in each stage of decomposition in non-contaminated carcasses (A) and in contaminated carcasses (B). Different lowercase letters (a, b, c) indicate significant differences between stages in each treatment (p <0.05). The stages are 1= Fresh; 2= bloated; 3= deterioration; 4= post-deterioration; 5= skeletonization.
Figure 2 in Formicidae fauna in pig carcasses contaminated by insecticide: implications for forensic entomology
Figure 2 Detrended Correspondence Analysis (DCA) using species occurrence to assess the change in the composition of ant species that occurs in both types of carcasses. The numbers correspond to the species appear in Table 1. On the right are those that occur more effectively in noncontaminated carcasses, and on the left are those that occurred in contaminated carcasses.
Figure 3 in Formicidae fauna in pig carcasses contaminated by insecticide: implications for forensic entomology
Figure 3 Nonmetric multidimensional scaling analysis (nMDS), using species occurrence to assess the change in the composition of ant species that act on different types of carcasses, along the different stages of decomposition. The numbers correspond to the species appear in Table 1. On the right are those that occur in contaminated carcasses, and on the left are those that occurred more effectively in non-contaminated carcasses. Noncont. = Non-contaminated and Cont. = Contaminated, I= Fresh; II= bloated; III= deterioration; IV= post-deterioration; V= skeletonization.
Hypertuned Beta parameter SDOT Framework for Robust Forensic File Classification
<p>This dataset contains code for implementing our proposed Forensic File classification system with the help of Guided LDA algorithm and SDOT forensic Framework. Along with the code, we have provided auxiillary files that are used in this research.</p>
A Study of Cognitive Adaptation Training in Inpatient Forensic Environments
ClinicalTrials.gov study NCT04294719. IPD Sharing: NO. Countries: 1. Publications: 18.
Data from: Ecological forensic testing: Using multiple primers for eDNA detection of marine vertebrates in an estuarine lagoon subject to anthropogenic influences
Open the record for dataset details and reuse information.
Data from: Treated like dirt: Robust forensic and ecological inferences from soil eDNA after challenging sample storage
Open the record for dataset details and reuse information.
Human tissue gene expression TPM values for the advanced forensic biology course
<p><strong>Gene expression per tissue</strong></p> <p>This dataset comes from the <a href="https://www.gtexportal.org/home/">Genotype-Tissue Expression (GTEx)</a> database that gathers gene expression data from various human tissues. Specifically, the <strong>GTEx Analysis v7</strong> version was used.</p> <p>The file is called "<a href="https://zenodo.org/api/files/9f872792-6c96-4226-b659-ce0807da66e8/GTEx_Analysis_2016-01-15_v7_RNASeQCv1.1.8_gene_median_tpm.tsv">GTEx_Analysis_2016-01-15_v7_RNASeQCv1.1.8_gene_tpm.tsv</a>" and contains tabulated-separated values of median TPM gene expression by tissue (TPM: transcript per million).</p> <p> </p> <p><strong>Genes with a favored sucutaneous-adipose expression profile</strong></p> <p>This file contains 195 genes that have a statistically (p < 0.01) favored expression profile in subcutaneous adipose tissue compared to other tissues. </p> <p>https://zenodo.org/api/files/7342bbfa-0e4d-49e7-b916-5eff5b638c33/genes_with_a_subcutaneous_adipose_favored_expression.tsv</p>
Random forests for predicting species identity of forensically important blow flies (Diptera: Calliphoridae) and flesh flies (Sarcophagidae) using geometric morphometric data: proof of concept
<p>Wing shape variation has been shown to be useful for delineating forensically important fly species in two Diptera families: Calliphoridae and Sarcophagidae. Compared to DNA-based identification, the cost of geometric morphometric data acquisition and analysis is relatively much lower because the tools required are basic, and stable softwares are available. However, to date, an explicit demonstration of using wing geometric morphometric data for species identity prediction in these two families remains lacking. Here, geometric morphometric data from 19 homologous landmarks on the left wing of males from seven species of Calliphoridae (<em>n</em>=55), and eight species of Sarcophagidae (<em>n</em>=40) were obtained and processed using Generalized Procrustes Analysis. Allometric effect was removed by regressing centroid size (in log10) against the Procrustes coordinates. Subsequently, principal component analysis of the allometry-adjusted Procrustes variables was done, with the first 15 principal components used to train a random forests model for species prediction. Using a real test sample consisting of 33 male fly specimens collected around a human corpse at a crime scene, the estimated percentage of concordance between species identities predicted using the random forests model and those inferred using DNA-based identification was about 80.6% (approximate 95% confidence interval = [68.9%, 92.2%]). In contrast, baseline concordance using naive majority class prediction was 36.4%. The results provide proof of concept that geometric morphometric data has good potential to complement morphological and DNA-based identification of blow flies and flesh flies in forensic work. </p>
Mapping the geographic origin of captive and confiscated Hermann's tortoises: a genetic toolkit for conservation and forensic analyses
<p>The illegal trade has been threatening tortoise populations worldwide for decades. Nowadays, however, DNA typing and forensic genetic approaches allow us to investigate the geographic origin of confiscated animals and to relocate them into the wild, providing that suitable molecular tools and reference data are available. Here we assess the suitability of a small panel of microsatellite markers to investigate patterns of illegal translocations and to assist forensic genetic applications in the endangered Mediterranean land tortoise <em>Testudo hermanni hermanni</em>. Specific allelic ladders were created for each locus and tested on several reference samples. We used the microsatellite panel to (i) increase our understanding of the population genetic structure in wild populations with new data from previously unsampled geographic areas (overall 461 wild individuals from 28 sampling sites); (ii) detect the presence of non-native individuals in wild populations; and (iii) identify the most likely geographic area of origin of 458 confiscated individuals hosted in Italian seizure and recovery centers. Our analysis initially identified six major genetic clusters corresponding to different geographic macro-areas along the Mediterranean range. Long-distance migrants among wild populations, due to translocations, were found and removed from the reference database. Assignment tests allowed us to allocate approximately 70% of confiscated individuals of unknown origin to one of the six Mediterranean macro-areas. Most of the assigned tortoises belonged to the genetic cluster corresponding to the area where the respective captivity center was located. However, we also found evidence of long-distance origins of confiscated individuals, especially in centers along the Adriatic coast and facing the Balkan regions, a well-known source of illegally traded individuals. Our results clearly show that the microsatellite panel and the reference dataset can play a beneficial role in reintroduction and repatriation projects when confiscated individuals need to be re-assigned to their respective macro-area of origin before release, and can assist future forensic genetic applications in detecting the illegal trade and possession of <em>Testudo hermanni</em> individuals.</p>
Brazilian Forensic Letter Database
<p>The BFL database composed of 315 writers, three samples per writer, summing up 945 images. The motivation for using such database is the growing interest of the Brazilian forensic experts as well as the Brazilian Federal Police in writer verification/identification .</p><p>The samples were provided by undergraduate students inthree different sessions during one month. The texts werecollected on an A4 white sheet of paper with no pen-drawbaseline and then scanned in gray level with 300 dpi (3760 X 2448). Each writer was allowed to use his/her own pen, which means that several different pens were used. The text is concise (131 words) and complete in the sense that it contains all characters (letters and numerals) and certain character combinations of interest. This makes it suitable for text-dependent writer identification as well. The image below shows the letter contents and a sample of the database.</p><p> </p><p>The BFL Database may be used for non-commercial research provided you acknowledge the source of the image by citing the following paper in publications about your research:</p><ul><li>C. Freitas, L. S. Oliveira, R. Sabourin, F. Bortolozzi <strong>Brazilian Forensic Letter Database</strong>, 11th International Workshop on Frontiers on Handwriting Recognition (IWFHR-11), Montreal, QC, Canada, August 19-21 2008. (<a href="http://www.cenparmi.concordia.ca/ICFHR2008/Proceedings/papers/cr1011.pdf">pdf</a>).</li></ul><h4>Related Papers:</h4><ul><li>Hanusiak, R. K., Justino, E., Oliviera, L. S., Sabourin, R. Writer Verification Using Texture-based Features, International Journal of Document Analysis and Recognition, 15(3):213-226, 2012. (<a href="http://www.inf.ufpr.br/lesoliveira/download/IJDAR2011.pdf">pdf</a>)</li><li>Bertolini, D.,Oliveira, L. S., Justino, E., Sabourin, R., Texture-based Descriptors for Writer Identification and Verification, Expert Systems With Applications, 40(6):2069-2080, 2013. (<a href="http://www.inf.ufpr.br/lesoliveira/download/ESWA2013a.pdf">pdf</a>).</li></ul>
Figure 2 in The carrion beetle Oxelytrum discicolle (Coleoptera: Silphidae) and the estimative of the minimum post-mortem interval in a forensic case in Brasília, Brazil
Figure 2. Oxelytrum discicolle larvae in the skull.
(PDF-like) An Ontology for Supporting Digital Forensics Controlled Experiments: Early Stages of Development - Figures
<p>Figures from An Ontology for Supporting Digital Forensics Controlled Experiments: Early Stages of Development</p>
Figure 2 in Mites occurring in farm buildings as allergic agents and indicators in forensic analyses
Figure 2 Dominance [%] of the Astigmatina mite species in all examined farm buildings.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.