Collocation extraction is the task of using a computer to extract collocations automatically from a corpus. The traditional method of performing collocation extraction is to find a formula based on the statistical quantities of those words to calculate a score associated to every word pairs. Proposed formulas are mutual information, t-test, z test, chi-squared test and likelihood ratio. Within the area of corpus linguistics, collocation is defined as a sequence of words or terms which co-occur more often than would be expected by chance. 'Crystal clear', 'middle management', 'nuclear family', and 'cosmetic surgery' are examples of collocated pairs of words. Some words are often found together because they make up a compound noun, for example 'riding boots' or 'motor cyclist' or ‘collocation extraction’ its very self.
Magisto
Magisto provided an online video editing tool (both as a web application and a mobile app) for automated video editing and production. In 2019, the company was acquired by Vimeo for an estimated US$200 million. The Magisto app contained a library of music. The music, largely by independent artists, was sorted by mood and is licensed for in-app use. Magisto had a freemium business model where users can create basic video clips for free. In addition, advanced business, professional and personal service tiers are available via various subscription plans, unlocking more features; such as longer videos, HD, premium themes, customization, and control features. == History == Magisto was founded in 2009 as SightEra (LTD) by Oren Boiman (CEO) and Alex Rav-Acha (CTO). Boiman, frustrated with the amount of time it took editing together videos of his daughter, wanted an easier to use application to capture and share videos. Boiman, a computer scientist that graduated from Tel Aviv University, followed with graduate work in computer vision at the Weizmann Institute of Science. Boiman developed several patent-pending image analysis technologies that analyze unedited videos to identify the most interesting parts. The system recognized faces, animals, landscapes, action sequences, movements and other important content within the video, as well as analyzing speech and audio. These scenes are then edited together, along with music and effects. Magisto was launched publicly on September 20, 2011, as a video editing software web application through which users could upload unedited video footage, choose a title and soundtrack and have their video edited for them automatically. On the following day, Magisto was added to YouTube Create's collection of video production applications. The Magisto iPhone app was launched publicly at the 2012 International Consumer Electronics Show (CES) in Las Vegas. At CES, the company was also awarded first place in the 2012 CES Mobile App Showdown. In August 2012, Magisto launched the Android app on Google Play. In September 2012, Magisto launched a Google Chrome App and announced Google Drive integration. In March 2013, Magisto claimed it had 5 million users. Google listed Magisto as an "Editors’ Choice" on its list of "Best Apps of 2013". In September 2013, the company claimed that 10 million users had downloaded the App. In February 2014, Magisto claimed that they had 20 million users, with 2 million new users per month. The company also confirmed investment from Mail.Ru. In September 2014, Magisto rolled out a feature called 'Instagram Ready' which allowed users to upload 15 second clips that are automatically formatted for Instagram. In the same month, Magisto launched a feature for iOS and Android users, called 'Surprise Me', which created video from still photography on users’ smartphones. In October 2014, Magisto was placed 9th on the 2014 Deloitte Israel Technology Fast 50 list and named as a finalist in the Red Herring's Top 100 Europe award. In July 2015, Magisto released an editing theme dedicated to Jerry Garcia. In April 2019, the company was acquired by Vimeo, the IAC-owned platform for hosting, sharing and monetizing streamed video, for an estimated $200 million. === Financing === In 2011, the company received more than $5.5 million in a Series B venture round funding from Magma Venture Partners and Horizons Ventures. In September 2011, at the same time as the public launch of their web application, Magisto announced a $5.5 million Series B funding round led by Li Ka-shing’s Horizons Ventures. Li Ka-Shing is known for making early-stage investments in companies like Facebook, Spotify, SecondMarket and Siri. In October 2013, the company received $13 million in funding from Qualcomm and Sandisk. In 2014, the company received $2 million in Venture Funding from Magma Venture Partners, Qualcomm Ventures, Horizons Ventures and the Mail.Ru Group. == Awards == Magisto won first place at Technonomy3, an annual Internet Technology start-up competition in Israel. Judges of the competition included Jeff Pulver, TechCrunch editor Mike Butcher, investor Yaron Samid, Bessemer Venture Partners Israel partner Adam Fisher and Brad McCarty of The Next Web. Magisto won first place at CES 2012 Mobile app competition, during the launch of Magisto iOS mobile app. Magisto was awarded twice the Google Play Editor's Choice and was part of iPhone App Store Best App awards for 2013 and 2014, and Wired Essential iPad Apps. Magisto was declared by Deloitte as the 7th fastest growing company in Europe, the Middle East, and Africa in 2016.
Multiple encryption
Multiple encryption is the process of encrypting an already encrypted message one or more times, either using the same or a different algorithm. It is also known as cascade encryption, cascade ciphering, cipher stacking, multiple encryption, and superencipherment. Superencryption refers to the outer-level encryption of a multiple encryption. Some cryptographers, like Matthew Green of Johns Hopkins University, say multiple encryption addresses a problem that mostly doesn't exist: Modern ciphers rarely get broken... You’re far more likely to get hit by malware or an implementation bug than you are to suffer a catastrophic attack on Advanced Encryption Standard (AES). However, from the previous quote an argument for multiple encryption can be made, namely poor implementation. Using two different cryptomodules and keying processes from two different vendors requires both vendors' wares to be compromised for security to fail completely. == Independent keys == Picking any two ciphers, if the key used is the same for both, the second cipher could possibly undo the first cipher, partly or entirely. This is true of ciphers where the decryption process is exactly the same as the encryption process (a reciprocal cipher) – the second cipher would completely undo the first. If an attacker were to recover the key through cryptanalysis of the first encryption layer, the attacker could possibly decrypt all the remaining layers, assuming the same key is used for all layers. To prevent that risk, one can use keys that are statistically independent for each layer (e.g. independent RNGs). Ideally each key should have separate and different generation, sharing, and management processes. == Independent Initialization Vectors == For en/decryption processes that require sharing an Initialization Vector (IV) / nonce these are typically, openly shared or made known to the recipient (and everyone else). Its good security policy never to provide the same data in both plaintext and ciphertext when using the same key and IV. Therefore, its recommended (although at this moment without specific evidence) to use separate IVs for each layer of encryption. == Importance of the first layer == With the exception of the one-time pad, no cipher has been theoretically proven to be unbreakable. Furthermore, some recurring properties may be found in the ciphertexts generated by the first cipher. Since those ciphertexts are the plaintexts used by the second cipher, the second cipher may be rendered vulnerable to attacks based on known plaintext properties (see references below). This is the case when the first layer is a program P that always adds the same string S of characters at the beginning (or end) of all ciphertexts (commonly known as a magic number). When found in a file, the string S allows an operating system to know that the program P has to be launched in order to decrypt the file. This string should be removed before adding a second layer. To prevent this kind of attack, one can use the method provided by Bruce Schneier: Generate a random pad R of the same size as the plaintext. Encrypt R using the first cipher and key. XOR the plaintext with the pad, then encrypt the result using the second cipher and a different (!) key. Concatenate both ciphertexts in order to build the final ciphertext. A cryptanalyst must break both ciphers to get any information. This will, however, have the drawback of making the ciphertext twice as long as the original plaintext. Note, however, that a weak first cipher may merely make a second cipher that is vulnerable to a chosen plaintext attack also vulnerable to a known plaintext attack. However, a block cipher must not be vulnerable to a chosen plaintext attack to be considered secure. Therefore, the second cipher described above is not secure under that definition, either. Consequently, both ciphers still need to be broken. The attack illustrates why strong assumptions are made about secure block ciphers and ciphers that are even partially broken should never be used. == The Rule of Two == The Rule of Two is a data security principle from the NSA's Commercial Solutions for Classified Program (CSfC). It specifies two completely independent layers of cryptography to protect data. For example, data could be protected by both hardware encryption at its lowest level and software encryption at the application layer. It could mean using two FIPS-validated software cryptomodules from different vendors to en/decrypt data. The importance of vendor and/or model diversity between the layers of components centers around removing the possibility that the manufacturers or models will share a vulnerability. This way if one components is compromised there is still an entire layer of encryption protecting the information at rest or in transit. The CSfC Program offers solutions to achieve diversity in two ways. "The first is to implement each layer using components produced by different manufacturers. The second is to use components from the same manufacturer, where that manufacturer has provided NSA with sufficient evidence that the implementations of the two components are independent of one another." The principle is practiced in the NSA's secure mobile phone called Fishbowl. The phones use two layers of encryption protocols, IPsec and Secure Real-time Transport Protocol (SRTP), to protect voice communications. The Samsung Galaxy S9 Tactical Edition is also an approved CSfC Component.
Sysomos
Sysomos Inc. is a Toronto-based social media analytics company owned by Outside Insight market leaders Meltwater. The company developed text analytics and machine learning technologies for user generated content, and served 80% of the top agencies and Fortune 500. == History == Sysomos was founded by Nilesh Bansal and Nick Koudas. The company is a spinoff of the University of Toronto research project BlogScope. The BlogScope project, which started in 2005, resulted in creation of the underlying content aggregation and analysis engine commercialized by Sysomos. The company raised venture capital in 2008 and was acquired by Marketwire in 2010. The company's original flagship product, Media Analysis Platform (MAP), mines and analyzes content from social media or user-generated content to create a picture of media coverage. Sysomos launched its flagship offering MAP in Sept 2007, followed by addition of Heartbeat to its product suite in 2009. In addition to the two main products, the company released FourWhere, a free location-based social search service that mashes up Foursquare in March 2010. The company also offers Sysomos Heartbeat which provides social media monitoring and engagement capabilities to communication professionals, brand managers and customer support groups. In 2013, Heartbeat was extended to add publishing components to deliver a complete end-to-end social media marketing platform. On July 6, 2010, it was announced that Marketwire, a press release distribution company, had acquired Sysomos. After the acquisition, Sysomos founders Nick Koudas and Nilesh Bansal, left Sysomos to start Aislelabs. In February 2015, Sysomos split from Marketwired, as an independent company, and appointed Adnan Ahmed as the new CEO. In March 2015, newly independent Sysomos launched a redesign for its Heartbeat product and a new API for its MAP product. In the same year, the company acquired Expion. In September 2016, Peter Heffring was announced as the new CEO. In April 2017, Sysomos showcased a new unified platform offering new insights. In April 2018, media monitoring firm Meltwater announced it had acquired Sysomos. The CEO of Sysomos, Peter Heffring, said the company will continue to operate as an independent unit of Meltwater. Heffring will run the social analytics division of Meltwater. == Reports == Inside Twitter series of reports is the most extensive third-party survey on Twitter's growth and demographics. Another extensive survey regarding the top 5% of most active Twitter users found that over 25% of all tweets are machine created. The report also confirms Twitter's international growth. Inside Facebook Pages report found that only four percent of pages have more than 10,000 fans, 0.76% of pages have more than 100,000 fans, and 0.05% of pages (or 297 in total) have more than a million fans. Inside YouTube reports focus more on video hosting services and YouTube.
SCinet
SCinet is the high-performance network built annually by volunteers in support of SC (formerly Supercomputing, the International Conference for High Performance Computing, Networking, Storage and Analysis). SCinet is the primary network for the yearly conference and is used by attendees and exhibitors to demonstrate and test high-performance computing and networking applications. == International Community == SCinet is also a hub for the international networking community. It provides a platform to share the latest research, technologies, and demonstrations for networks, network technology providers, and even software developers who are in charge of supporting HPC communities at their own institutions or organizations. == Volunteers == Nearly 200 volunteers from educational institutions, high performance computing sites, equipment vendors, research and education networks, government agencies and telecommunications carriers collaborate via technology and in-person to design, build and operate SCinet. While many of these credentialed individuals have volunteered at SCinet for years, first timers join the team each year. They include international students and participants in the National Science Foundation-funded Women in IT Networking at SC (WINS) program. The 2017 SCinet team included women and men from high performance computing institutions in the U.S. and throughout the world. == History == Originated in 1991 as an initiative within the SC conference to provide networking to attendees, SCinet has grown to become the "World's Fastest Network" during the duration of the conference. For 29 years, SCinet has provided SC attendees and the high performance computing (HPC) community with the innovative network platform necessary to internationally interconnect, transport, and display HPC research during SC. Historically, SCinet has been used as a platform to test networking technology and applications which have found their way into common use. == Research and development == In the past years, SCinet deployed conference wide networking technologies such as ATM, FDDI, HiPPi before they were deployed commercially.
Cyclodisparity
In vision science, cyclodisparity is the difference in the rotation angle of an object or scene viewed by the left and right eyes. Cyclodisparity can result from the eyes' torsional rotation (cyclorotation) or can be created artificially by presenting to the eyes two images that need to be rotated relative to each other for binocular fusion to take place. == Human and animal vision == The eyes and visual system can compensate for cyclodisparity up to a certain point; if the cyclodisparity is larger than a threshold, the images cannot be fused, resulting stereoblindness, and in double vision in subjects who otherwise have full stereo vision. When a human subject is presented with images that have artificial cyclodisparity, cyclovergence is evoked, that is, a motor response of the eye muscles that rotates the two eyes in opposite directions, thereby reducing cyclodisparity. Visually-induced cyclovergence of up to 8 degrees has been observed in normal subjects. Furthermore, up to about 8 degrees can usually be compensated by purely sensory means, that is, without physical eye rotation. This means that the normal human observer can achieve binocular image fusion in presence of cyclodisparity of up to approximately 16 degrees. Cyclodisparity due to images having been rotated inward can be compensated better when the gaze is directed downwards, and cyclodisparity due to an outward rotation can be compensated better when the gaze is directed upwards. A proposed explanation for this phenomenon is that the motor system is coordinated in such a way that the eyes perform a torsional movement to reduce the size of the search zones and thus the computational load required for solving the correspondence problem. The resulting cyclovergence at near gaze is smaller than the cyclovergence predicted by Listing's law. == Video processing and computer vision == Active camera torsion can be used in machine and computer vision for several purposes. For instance, camera torsion can be used to make improved use of the search range over which matching detectors or stereo matching algorithms operate, or to make a 3D slanted surface appear frontoparallel for further stereo processing. For image compression purposes, images with cyclodisparity are advantageously encoded using global motion compensation using a rotational motion model.
CANaerospace
CANaerospace is a higher layer protocol based on Controller Area Network (CAN) which has been developed by Stock Flight Systems in 1998 for aeronautical applications. == Background == CANaerospace supports airborne systems employing the Line-replaceable unit (LRU) concept to share data across CAN and ensures interoperability between CAN LRUs by defining CAN physical layer characteristics, network layers, communication mechanisms, data types and aeronautical axis systems. CANaerospace is an open source project, was initiated to standardize the interface between CAN LRUs on the system level. CANaerospace is continuously being developed further and has also been published by NASA as the Advanced General Aviation Transport Experiments Databus Standard in 2001. It found widespread use in aeronautical research worldwide. A major research aircraft that employs several CANaerospace networks for real-time computer interconnection is the Stratospheric Observatory for Infrared Astronomy (SOFIA), a Boeing 747SP with a 2.5m astronomic telescope. CANaerospace is also frequently used in flight simulation and connects entire aircraft cockpits (i.e. in Eurofighter Typhoon simulators) to the simulation host computers. In Italy CANaerospace is used as UAV data bus technology. Furthermore, CANaerospace serves as communication network in several general aviation avionics systems. The CANaerospace interface definition closes the gap between the ISO/OSI layer 1 and 2 CAN protocol (which is implemented in the CAN controller itself) and the specific requirements of distributed systems in aircraft. It may be used as a primary or ancillary avionics network and was designed to meet the following requirements: Democratic network: CANaerospace does not require any master/slave relationships between LRUs or a "bus controller", thereby avoiding a potential single source of failure. Every node in the network has the same rights for participation in the bus traffic. Self-identifying message format: Each CANaerospace message contains information about the type of the data and the transmitting node. This allows the data to be unambiguously recognized at each receiving node. Continuous Message Numbering: Each CANaerospace message contains a continuously incremented number which allows coherent processing of messages in the receiving stations. Message Status Code: Each CANaerospace message contains information about the integrity of the data is conveying. This allows receiving stations to evaluate the quality of the received data and to react accordingly. Emergency Event Signaling: CANaerospace defines a mechanism that allows each node to transmit information about exception or error situations. This information can be used by other stations to determine the network health. Node Service Interface: As an enhancement to CAN, CANaerospace provides a means for individual stations on the network to communicate with each other using connection-oriented and connectionless services. Predefined CAN Identifier Assignment: CANaerospace offers a predefined identifier assignment list for normal operation data. In addition to the predefined list, user-defined identifier assignment lists may be used. Ease of Implementation: The amount of code to implement CANaerospace is very little by design in order to minimize the effort for testing and certification of flight safety critical systems. Openness to Extensions: All CANaerospace definitions are extendable to provide flexibility for future enhancements and to allow adaptions to the requirements of specific applications. Free Availability: No cost whatsoever apply for the use of CANaerospace. The specification can be downloaded from the Internet == Physical interface == To ensure interoperability and reliable communication, CANaerospace specifies the electrical characteristics, bus transceiver requirements and data rates with the corresponding tolerances based on ISO 11898. The bit timing calculation (baud rate accuracy, sample point definition) and robustness to electromagnetic interference are given special emphasis. Also addressed are CAN connector, wiring considerations and design guidelines to maximize electromagnetic compatibility. == Communication layers == The Bosch CAN specification itself allows messages being transmitted both periodically and aperiodically but does not cover issues like data representation, node addressing or connection-oriented protocols. CAN is entirely based on Anyone-to-Many (ATM) communication which means that CAN messages are always received by all stations in the network. The advantage of the CAN concept is inherent data consistency between all stations, the drawback is that it does not allow node addressing which is the basis for Peer-to-Peer (PTP) communication. Using CAN networks in aeronautical applications, however, demands a standard targeted to the specific requirements of airborne systems which implies that communication between individual stations in the network must be possible to enable the required degree of system monitoring. Consequently, CANaerospace defines additional ISO/OSI layer 3, 4 and 6 functions to support node addressing and unified ATM/PTP communication mechanisms. PTP communication allows to set up client/server interactions between individual stations in the network either temporarily or permanently. More than one of these interactions may be in effect at any given time and each node may be client for one operation and server for another at the same time. This CANaerospace mechanism is called "Node Service Concept" and allows i.e. to distribute system functions over several stations in the network or to control dynamic system reconfiguration in case of failure. The Node Service concept supports both connection-oriented and connectionless interactions like with TCP/IP and UDP/IP for Ethernet. Enabling both ATM and PTP communication for CAN requires the introduction of independent network layers to isolate the different types of communication. This is realized for CANaerospace by forming CAN identifier groups as shown in Figure 1. The resulting structure creates Logical Communication Channels (LCCs) and assigns a specific communication type (ATM, PTP) to each of the LCCs. User-defined LCCs provide the necessary freedom for designers and allow the implementation of CANaerospace according to the needs of specific applications. Figure 1: Logical Communication Channels for CANaerospace As a side effect, the CAN identifier groups in Figure 1 affect the priority of the message transmission in case of bus arbitration. The communication channels are therefore arranged according to their relative importance: Emergency Event Data Channel (EED): This communication channel is used for messages which require immediate action (i.e. system degradation or reconfiguration) and have to be transmitted with very high priority. Emergency Event Data uses ATM communication exclusively. High/Low Priority Node Service Data Channel (NSH/NSL): These communication channels are used for client/server interactions using PTP communication. The corresponding services may be of the connection-oriented as well as the connectionless type. NSH/NSL may also be used to support test and maintenance functions. Normal Operation Data Channel (NOD): This communication channel is used for the transmission of the data which is generated during normal system operation and described in the CANaerospace identifier assignment list. These messages may be transmitted periodically or aperiodically as well as synchronously or asynchronously. All messages which cannot be assigned to other communication channels shall use this channel. High/Low Priority User-Defined Data Channel (UDH/UDL): This channel is dedicated to communication which cannot, due to their specific characteristics, be assigned other channels without violating the CANaerospace specification. As long as the defined identifier range is used, the message content and the communication type (ATM, PTP) for these channels may be specified by the system designer. To ensure interoperability it is highly recommended that the use of these channels is minimized. Debug Service Data Channel (DSD): This channel is dedicated to messages which are used temporarily for development and test purposes only and are not transmitted during normal operation. As long as the defined identifier range is used, the message content and the communication type (ATM, PTP) for these channels may be specified by the system designer. == Data representation == The majority of the real-time control systems used in aeronautics employ "big endian" processor architectures. This data representation was therefore specified for CANaerospace as well. With big endian data representation, the most significant bit of any datum is arranged leftmost and transmitted first on CANaerospace as shown in Figure 2. Figure 2: "Big Endian" Data Representation for CANaerospace CANaerospace uses a self-identifying message