collection curated by Xanthraxxx https://academictorrents.com/collection/i The dataset was used in our painting analysis work. The data is provided for academic research comparison only. You should not redistribute the data. Related Paper: Jia Li, Lei Yao, Ella Hendriks and James Z. Wang, Rhythmic Brushstrokes Distinguish van Gogh from His Contemporaries: Findings via Automated Brushstroke Extraction, IEEE Transactions on Pattern Analysis and Machine Intelligence, DOI: 10.1109/TPAMI.2011.203 online, 2011, print version to appear in 2012. https://academictorrents.com/download/55a8925a8d546b9ca47d309ab438b91f7959e77f There are two folders of data, Faredata_2013 and Tripdata_2013. Each folder contains chunks of data in csv format, ranging from ~1.5 to ~2.5 GB in size. Fare data looks like this, showing medallion, hack_license, vendor_id, pickup date/time, payment type, fare, tip amount (look at all those zeros!), tolls, and total. Trip data (the good stuff!) looks like this. Each file has about 14 million rows, and each row contains medallion, hack license, vendor id, rate code, store and forward flag, pickup date/time dropoff date/time, passenger count, trip time in seconds, trip distance, and latitude/longitude coordinates for the pickup and dropoff locations. The possibilities are endless! I smell a tip analysis coming on! https://academictorrents.com/download/107a7d997f331ef4820cf5f7f654516e1704dccf Here we present a test-retest dataset of functional magnetic resonance imaging (fMRI) data acquired at rest. 22 participants were scanned during two sessions spaced one week apart. Each session includes two 1.5 mm isotropic whole-brain scans and one 0.75 mm isotropic scan of the prefrontal cortex, giving a total of six timepoints. Additionally, the dataset includes measures of mood, sustained attention, blood pressure, respiration, pulse, and the content of self-generated thoughts (mind wandering). This data enables the investigation of sources of both intra- and inter-session variability not only limited to physiological changes, but also including alterations in cognitive and affective states, at high spatial resolution. The dataset is accompanied by a detailed experimental protocol and source code of all stimuli used. Please subscribe to for important annoucements. More information at . https://academictorrents.com/download/5fc2f273123336ee34b9ea635ef8440377a42888 Over 3.5 million monthly domestic flight records from 1990 to 2009. Data are arranged as an adjacency list with metadata. Ready for immediate database import and analysis. ##Fields: |Short name|Type |Description| |-|-|-| |Origin|String|Three letter airport code of the origin airport| |Destination|String|Three letter airport code of the destination airport| |Origin City|String|Origin city name| |Destination City|String|Destination city name| |Passengers|Integer|Number of passengers transported from origin to destination| |Seats|Integer|Number of seats available on flights from origin to destination| |Flights|Integer|Number of flights between origin and destination (multiple records for one month, many with flights > 1)| |Distance|Integer|Distance (to nearest mile) flown between origin and destination| |Fly Date|Integer|The date (yyyymm) of flight| |Origin Population|Integer|Origin city s population as reported by US Census| |Destination Population|Integer|Destination city s population as reported by US Census| ##Snippet: MFRRDMMedford, ORBend, OR001156200810200298157730 AMAEKOAmarillo, TXElko, NV124124185819930820296040259 TUSEKOTucson, AZElko, NV112124165819930871139240259 AMAEKOAmarillo, TXElko, NV115124185819940620631541668 ICTEKOWichita, KSElko, NV1001241100719960755288445034 SPSEKOWichita Falls, TXElko, NV1221241105919960314768345034 ##Source(s) 1. US Census Bureau 2. RITA/Transtats, Bureau of Transportation Statistics https://academictorrents.com/download/a2ccf94bbb4af222bf8e69dad60a68a29f310d9a The list contains every wordlist, dictionary, and password database leak that I could find on the internet (and I spent a LOT of time looking). It also contains every word in the Wikipedia databases (pages-articles, retrieved 2010, all languages) as well as lots of books from Project Gutenberg. It also includes the passwords from some low-profile database breaches that were being sold in the underground years ago. The format of the list is a standard text file sorted in non-case-sensitive alphabetical order. Lines are separated with a newline "\n" character. You can test the list without downloading it by giving SHA256 hashes to the free hash cracker or to @PlzCrack on twitter. Here s a tool for computing hashes easily. Here are the results of cracking LinkedIn s and eHarmony s password hash leaks with the list. The list is responsible for cracking about 30% of all hashes given to CrackStation s free hash cracker, but that figure should be taken with a grain of salt because some people try hashes of really weak passwords just to test the service, and others try to crack their hashes with other online hash crackers before finding CrackStation. Using the list, we were able to crack 49.98% of one customer s set of 373,000 human password hashes to motivate their move to a better salting scheme. https://academictorrents.com/download/7ae809ccd7f0778328ab4b357e777040248b8c7f Wikipedia offers free copies of all available content to interested users. These databases can be used for mirroring, personal use, informal backups, offline use or database queries (such as for Wikipedia:Maintenance). All text content is multi-licensed under the Creative Commons Attribution-ShareAlike 3.0 License (CC-BY-SA) and the GNU Free Documentation License (GFDL). Images and other files are available under different terms, as detailed on their description pages. For our advice about complying with these licenses, see Wikipedia:Copyrights. https://academictorrents.com/download/e18b8cce7d9cb2726f5f40dcb857111ec573cad4 # Cat Annotation Dataset The CAT dataset includes 10,000 cat images. For each image, we annotate the head of cat with nine points, two for eyes, one for mouth, and six for ears. The detail configuration of the annotation was shown in Figure 6 of the original paper: Weiwei Zhang, Jian Sun, and Xiaoou Tang, "Cat Head Detection - How to Effectively Exploit Shape and Texture Features", Proc. of European Conf. Computer Vision, vol. 4, pp.802-816, 2008. ### Format The annotation data are stored in a file with the name of the corresponding cat image plus ".cat", one annotation file for each cat image. For each annotation file, the annotation data are stored in the following sequence: 1. Number of points (always 9) 2. Left Eye 3. Right Eye 4. Mouth 5. Left Ear-1 6. Left Ear-2 7. Left Ear-3 8. Right Ear-1 9. Right Ear-2 10. Right Ear-3 ### Training, Validation, and Testing We randomly divide the data into three sets: 5,000 images for training, 2,000 images for validation and 3000 images for testing. ![]() https://academictorrents.com/download/c501571c29d16d7f41d159d699d0e7fb37092cbd Wikipedia offers free copies of all available content to interested users. These databases can be used for mirroring, personal use, informal backups, offline use or database queries (such as for Wikipedia:Maintenance). All text content is multi-licensed under the Creative Commons Attribution-ShareAlike 3.0 License (CC-BY-SA) and the GNU Free Documentation License (GFDL). Images and other files are available under different terms, as detailed on their description pages. For our advice about complying with these licenses, see Wikipedia:Copyrights. https://academictorrents.com/download/9512a1f6d21e5012c06a1c9b8e2dd4796ecc77a9 Almost all P2P crypto-currencies prevent double spending and similar such attacks with a bulky "blockchain" scheme, and the ones which do not typically use some sort of pseudo-centralized solution to manage the transactions. Here I propose a purely P2P crypto-currency scheme with a finite blockchain, dubbed the "mini-blockchain". Each time a new block is solved the oldest block is trimmed from the end of the mini-blockchain so that it always has the same number of blocks. It is argued that the loss of security this trimming process incurs can be solved with a small "proof chain" and the loss of coin ownership data is solved with a database which holds the balance of all non-empty addresses, dubbed the "account tree". The proof chain secures the mini-blockchain and the mini-blockchain secures the account tree. This paper will describe the way in which these three mechanisms can work together to form a system which provides a high level of integrity and security, yet is much slimmer than all other purely P2P currencies. It also offers other potential benefits such as faster transactions and lower fees, quicker network synchronization, support for high levels of traffic, more block space for custom messages, and increased anonymity. https://academictorrents.com/download/4cc072da6bd32eedfec13e235a22ea4054e50554 This paper will go over the technical, economic, and social impact of cryptocurrencies such as Bitcoin and Litecoin. This document will go into a comprehensive level of detail about cryptocurrency technologies and protocols, as this is required to familiarize the reader with the principles behind the rapidly emerging open source economic ecosystem. Furthermore, emerging attack vectors of cryptocurrencies will be discussed, such as custom malware campaigns and targeted exploitation. https://academictorrents.com/download/daaa86689c42e78c4111b74984d5036a426f6cf6 A new type of proof-of-work based on searching for prime numbers is introduced in peer-to-peer cryptocurrency designs. Three types of prime chains known as Cunningham chain of first kind, Cunningham chain of second kind and bi-twin chain are qualified as proof-of-work. Prime chain is linked to block hash to preserve the security property of Nakamoto s Bitcoin, while a continuous difficulty evaluation scheme is designed to allow prime chain to act as adjustable-difficulty proof-of-work in a Bitcoin like cryptocurrency. https://academictorrents.com/download/d0f9accaec8ac9d538fdf9d675105ae1392ea32b A peer-to-peer crypto-currency design derived from Satoshi Nakamoto s Bitcoin. Proof-of-stake replaces proof-of-work to provide most of the network security. Under this hybrid design proof-of-work mainly provides initial minting and is largely non-essential in the long run. Security level of the network is not dependent on energy consumption in the long term thus providing an energy efficient and more cost-competitive peer-to-peer crypto-currency. Proof-of-stake is based on coin age and generated by each node via a hashing scheme bearing similarity to Bitcoin s but over limited search space. Block chain history and transaction settlement are further protected by a centrally broadcasted checkpoint mechanism. https://academictorrents.com/download/0bc8878760a3105617da3fa9ba6b97cffad6c24f A purely peer-to-peer version of electronic cash would allow online payments to be sent directly from one party to another without going through a financial institution. Digital signatures provide part of the solution, but the main benefits are lost if a trusted third party is still required to prevent double-spending. We propose a solution to the double-spending problem using a peer-to-peer network. The network timestamps transactions by hashing them into an ongoing chain of hash-based proof-of-work, forming a record that cannot be changed without redoing the proof-of-work. The longest chain not only serves as proof of the sequence of events witnessed, but proof that it came from the largest pool of CPU power. As long as a majority of CPU power is controlled by nodes that are not cooperating to attack the network, they ll generate the longest chain and outpace attackers. The network itself requires minimal structure. Messages are broadcast on a best effort basis, and nodes can leave and rejoin the network at will, accepting the longest proof-of-work chain as proof of what happened while they were gone. https://academictorrents.com/download/8c271f4d2e92a3449e2d1bde633cd49f64af888f The Freshwater Ecoregions Of the World (FEOW) provide a global biogeographic regionalization of the Earth s freshwater biodiversity. This version of the FEOW, modified by The Nature Conservancy, includes additional tabular data describing Major Habitat Types (MHTs, similar to terrestrial biomes, but unpublished).You can read more about the FEOW, and obtain the unmodified shapefile at www.feow.org. https://academictorrents.com/download/fb993412755d0bdc8aabd9c6959215293958b220 This is the master spatial data layer for TNC s terrestrial ecoregions of the world, exported from the geodatabase listed above. Note that it includes Mangroves, Inland Water, and Rock and Ice MHTs, although they are not being handled by terrestrial assessments. This layer is based on WWF s ecoregions outside the United States, and loosely based on Bailey s ecoregions (from the USDA Forest Service) within the United States. terr-ecoregions-TNC: tnc_terr_ecoregions.dbf tnc_terr_ecoregions.lyr tnc_terr_ecoregions.prj tnc_terr_ecoregions.sbn tnc_terr_ecoregions.sbx tnc_terr_ecoregions.shp tnc_terr_ecoregions.shp.xml tnc_terr_ecoregions.shx https://academictorrents.com/download/fbfe954c816cf914709d9483134df7448337eb9e The Marine Ecoregions Of the World (MEOW) data set is a biogeographic classification of the world s coasts and shelves. The ecoregions nest within the broader biogeographic tiers of Realms and Provinces. Further details about the MEOW system and PDFs of the BioScience paper the comprehensive listing of sources are available from www.worldwildlife.org/MEOW/ and www.nature.org/MEOW. https://academictorrents.com/download/551952d08103200cf5034fb74adf71643aa0c643 Twitter is a social news website. It can be viewed as a hybrid of email, instant messaging and sms messaging all rolled into one neat and simple package. It s a new and easy way to discover the latest news related to subjects you care about. |Attribute|Value| |-|-| |Number of Nodes: |11316811| |Number of Edges: |85331846| |Missing Values? |no| |Source:| N/A| ##Data Set Information: 1. nodes.csv — it s the file of all the users. This file works as a dictionary of all the users in this data set. It s useful for fast reference. It contains all the node ids used in the dataset 2. edges.csv — this is the friendship/followership network among the users. The friends/followers are represented using edges. Edges are directed. Here is an example. 1,2 This means user with id "1" is followering user with id "2". ##Attribute Information: Twitter is a social news website. It can be viewed as a hybrid of email, instant messaging and sms messaging all rolled into one neat and simple package. It s a new and easy way to discover the latest news related to subjects you care about. https://academictorrents.com/download/2399616d26eeb4ae9ac3d05c7fdd98958299efa9 Version:11 Release Date:June 23rd, 2010 Resolution:592.75 ppd Scale:99.7 mpp Projection:Simple cylindrical, 0E to 360E, 90N to -90N, ocentric Total Size:213391 x 106699 pixels Details:Daytime thermal infrared (12.57um) mosaic. 593 ppd/99m. NASA Mars Odyssey/THEMIS https://academictorrents.com/download/8b89d5825ca251ea355277d1f6e014891aa24875 Dataset Objective: https://academictorrents.com/download/30748b1a7ac99b1c5ff66f0bc5c5f7428ed035c5