Abstract: An encrypted search uses hash vectorization (HV) models, which are secure, one-way hash indices that are produced by a compression process, such as a modeling phase of Lempel-Ziv (LZ) parsing. Each HV model includes a hash filter and a chain vector. The hash filter is a Boolean quotient filter similar to Bloom filters, and allows for the quick elimination of negative query assessments. The hash filter is followed by a chain vector, which provides spatial modeling of hashed elements throughout the compressed and encrypted data, thereby providing increased levels of accuracy, efficiency, and query expressiveness as compared with known techniques.

Abstract: A method includes receiving an input data stream at a processor, and for each byte sequence from a plurality of byte sequences of the input data stream, a hash is generated and compared to a hash table to determine whether a match exists. If a match exists, that byte sequence is incrementally expanded to include one or more additional adjacent bytes from the input data stream, to produce multiple expanded byte sequences. Each of the expanded byte sequences is compared to the hash table to identify a maximum-length matched byte sequence from a set that includes the byte sequence and the plurality of expanded byte sequences. A representation of the maximum-length matched byte sequence is stored in the memory. If a match does not exist, a representation of that byte sequence is stored as a byte sequence literal in the memory.

Abstract: An encrypted search uses hash vectorization (HV) models, which are secure, one-way hash indices that are produced by a compression process, such as a modeling phase of Lempel-Ziv (LZ) parsing. Each HV model includes a hash filter and a chain vector. The hash filter is a Boolean quotient filter similar to Bloom filters, and allows for the quick elimination of negative query assessments. The hash filter is followed by a chain vector, which provides spatial modeling of hashed elements throughout the compressed and encrypted data, thereby providing increased levels of accuracy, efficiency, and query expressiveness as compared with known techniques.

Abstract: An encrypted search uses hash vectorization (HV) models, which are secure, one-way hash indices that are produced by a compression process, such as a modeling phase of Lempel-Ziv (LZ) parsing. Each HV model includes a hash filter and a chain vector. The hash filter is a Boolean quotient filter similar to Bloom filters, and allows for the quick elimination of negative query assessments. The hash filter is followed by a chain vector, which provides spatial modeling of hashed elements throughout the compressed and encrypted data, thereby providing increased levels of accuracy, efficiency, and query expressiveness as compared with known techniques.

Abstract: A method includes receiving an input data stream at a processor, and for each byte sequence from a plurality of byte sequences of the input data stream, a hash is generated and compared to a hash table to determine whether a match exists. If a match exists, that byte sequence is incrementally expanded to include one or more additional adjacent bytes from the input data stream, to produce multiple expanded byte sequences. Each of the expanded byte sequences is compared to the hash table to identify a maximum-length matched byte sequence from a set that includes the byte sequence and the plurality of expanded byte sequences. A representation of the maximum-length matched byte sequence is stored in the memory. If a match does not exist, a representation of that byte sequence is stored as a byte sequence literal in the memory.

Abstract: An encrypted search uses hash vectorization (HV) models, which are secure, one-way hash indices that are produced by a compression process, such as a modeling phase of Lempel-Ziv (LZ) parsing. Each HV model includes a hash filter and a chain vector. The hash filter is a Boolean quotient filter similar to Bloom filters, and allows for the quick elimination of negative query assessments. The hash filter is followed by a chain vector, which provides spatial modeling of hashed elements throughout the compressed and encrypted data, thereby providing increased levels of accuracy, efficiency, and query expressiveness as compared with known techniques.

Abstract: A method for searching compressed, encrypted data includes receiving uncompressed data and identifying patterns thereof. Each pattern includes a predetermined number of bytes. Each pattern is hashed into a hash value, producing a set of hash values that is stored in a hash table. Each record of the hash table includes a hash value from the set of hash values and an associated position value. A Boolean filter is generated based on the hash table, each bit of the Boolean filter associated with a different hash value. A search string hash value is calculated based on a received search request. A location in the Boolean filter, having an address equal to the search string hash value, is inspected to determine whether a position stored at the location is true or false. If the position is true, at least a portion of the compressed data is flagged as relevant.

Abstract: A data compression system includes an encoder for receiving a binary string of data which is partitioned into one or more binary segments and assigned Variable Length Codewords (VLCs) to be stored to a file or transmitted over a medium, such as a wired network or a wireless network. The system can also include a decoder for receiving the VLCs from a file or network and reproducing a binary string of data substantially identical to that which was input to the encoder. The system can also include a processor, a memory and/or a coder/decoder (CODEC) for compressing/decompressing a raw or compressed data stream received from a file or network.

Abstract: A 3D scanning toolkit to perform operations that include: accessing a first data stream at a client device, wherein the first data stream comprises at least image data; applying a bit mask to the first data stream, the bit mask identifying a portion of the image data; accessing a second data stream at the client device, the second data stream comprising depth data associated with the portion of the image data; generating a point cloud based on the depth data, the point cloud comprising a set of data points that define surface features of an object depicted in the first data stream; and causing display of a visualization of the point cloud upon a presentation of the first data stream at the client device.

Abstract: A data encoding system includes a non-transitory memory, a processor, a digital-to-analog converter (DAC) and a transmitter. The non-transitory memory stores a predetermined file size threshold. The processor is in operable communication with the memory, and is configured to receive data. The processor detects a file size associated with the data. When the file size is below the predetermined file size threshold, the processor compresses the data using a variable length codeword (VLC) encoder. When the file size is not below the predetermined file size threshold, the processor compresses the data, using a hash table algorithm. The DAC is configured to receive a digital representation of the compressed data from the processor and convert the digital representation of the compressed data into an analog representation of the compressed data. The transmitter is coupled to the DAC and configured to transmit the analog representation of the compressed data.

Abstract: A method for searching compressed, encrypted data includes receiving uncompressed data and identifying patterns thereof. Each pattern includes a predetermined number of bytes. Each pattern is hashed into a hash value, producing a set of hash values that is stored in a hash table. Each record of the hash table includes a hash value from the set of hash values and an associated position value. A Boolean filter is generated based on the hash table, each bit of the Boolean filter associated with a different hash value. A search string hash value is calculated based on a received search request. A location in the Boolean filter, having an address equal to the search string hash value, is inspected to determine whether a position stored at the location is true or false. If the position is true, at least a portion of the compressed data is flagged as relevant.

Abstract: A method for searching compressed, encrypted data includes receiving uncompressed data and identifying patterns thereof. Each pattern includes a predetermined number of bytes. Each pattern is hashed into a hash value, producing a set of hash values that is stored in a hash table. Each record of the hash table includes a hash value from the set of hash values and an associated position value. A Boolean filter is generated based on the hash table, each bit of the Boolean filter associated with a different hash value. A search string hash value is calculated based on a received search request. A location in the Boolean filter, having an address equal to the search string hash value, is inspected to determine whether a position stored at the location is true or false. If the position is true, at least a portion of the compressed data is flagged as relevant.

Abstract: A data encoding system includes a non-transitory memory, a processor, a digital-to-analog converter (DAC) and a transmitter. The non-transitory memory stores a predetermined file size threshold. The processor is in operable communication with the memory, and is configured to receive data. The processor detects a file size associated with the data. When the file size is below the predetermined file size threshold, the processor compresses the data using a variable length codeword (VLC) encoder. When the file size is not below the predetermined file size threshold, the processor compresses the data, using a hash table algorithm. The DAC is configured to receive a digital representation of the compressed data from the processor and convert the digital representation of the compressed data into an analog representation of the compressed data. The transmitter is coupled to the DAC and configured to transmit the analog representation of the compressed data.

Abstract: A data encoding system includes a non-transitory memory, a processor, a digital-to-analog converter (DAC) and a transmitter. The non-transitory memory stores a predetermined file size threshold. The processor is in operable communication with the memory, and is configured to receive data. The processor detects a file size associated with the data. When the file size is below the predetermined file size threshold, the processor compresses the data using a variable length codeword (VLC) encoder. When the file size is not below the predetermined file size threshold, the processor compresses the data, using a hash table algorithm. The DAC is configured to receive a digital representation of the compressed data from the processor and convert the digital representation of the compressed data into an analog representation of the compressed data. The transmitter is coupled to the DAC and configured to transmit the analog representation of the compressed data.

Abstract: A system is disclosed comprising a transceiver, transcoder, memory, and a processor for receiving raw data, partitioning the raw data into substrings of predetermined length, assigning each substring to a corresponding predetermined frequency based upon a data set or first lookup table based on the substring's given pattern, and transmitting said frequency using an antenna. Embodiments include a compression component for receiving raw data as input, breaking the raw data into subsets of predetermined length, comparing the raw data to a second lookup table, the second lookup table comprising all possible bit patterns for a file of the length of the raw data, wherein the possible bit patterns are partitioned in n-bit partitions, the n-bit partitions having a corresponding assigned value, the values of which are assembled by a given function so as to produce a code for each possible bit pattern.

Abstract: Techniques and architecture are disclosed for a multirotor vehicle having a rotor assembly with a plurality of rotors to provide upward thrust. Attached to the rotor assembly is a frame that includes a frame extension having a first end pivotally attached to the rotor assembly. The extension also includes a second end pivotally attached to a frame body. The vehicle further includes first and second actuators. The first actuator pivots the rotor assembly to position it within a horizontal plane to allow thrust generated by the rotor assembly to lift the vehicle. The second actuator pivots the rotor assembly within the horizontal plane so that thrust generated by the rotor assembly lifts the vehicle. The vehicle also includes a harness connected to the frame and configured to secure an operator's torso to the multirotor vehicle.

Abstract: A system includes a non-transitory memory, a processor in operable communication with the memory, a digital-to-analog converter (DAC) and a transmitter. The memory stores bit position information associated with a first data. The bit position information includes absolute position data and relative position data for each bit of a plurality of bits of the first data. The processor can receive a data stream including the first data, and compress the first data to generate a second data representing the first data. The second data has a data structure that is arranged based on: (1) the first data, and (2) the bit position information. The DAC can receive a digital representation of the second data from the processor and convert the digital representation of the second data into an analog representation of the second data. The transmitter can then transmit the analog representation of the second data.

Abstract: A system includes a non-transitory memory, a processor in operable communication with the memory, a digital-to-analog converter (DAC) and a transmitter. The memory stores bit position information associated with a first data. The bit position information includes absolute position data and relative position data for each bit of a plurality of bits of the first data. The processor can receive a data stream including the first data, and compress the first data to generate a second data representing the first data. The second data has a data structure that is arranged based on: (1) the first data, and (2) the bit position information. The DAC can receive a digital representation of the second data from the processor and convert the digital representation of the second data into an analog representation of the second data. The transmitter can then transmit the analog representation of the second data.

Abstract: A system is disclosed comprising a transceiver, transcoder, memory, and a processor for receiving raw data, partitioning the raw data into substrings of predetermined length, assigning each substring to a corresponding predetermined frequency based upon a data set or first lookup table based on the substring's given pattern, and transmitting said frequency using an antenna. Embodiments include a compression component for receiving raw data as input, breaking the raw data into subsets of predetermined length, comparing the raw data to a second lookup table, the second lookup table comprising all possible bit patterns for a file of the length of the raw data, wherein the possible bit patterns are partitioned in n-bit partitions, the n-bit partitions having a corresponding assigned value, the values of which are assembled by a given function so as to produce a code for each possible bit pattern.