Binary Data Streams Research Articles

Флуктуации корреляционных характеристик в шумовой системе радиосвязи

Ultra-wideband noise communication system using the transmitted reference technique with the time diversity is proposed for a covert data transmission through additive white Gaussian noise channel. Spectrum modulation of transmitted signals is performed as a result from linear superposition between the noise references and informative noise carriers delayed at the time diversity significantly exceeding the coherent time. The delayed noise carriers are multiplied by antipodal symbols at the same rate of binary data stream. Spectral power density of result noise signals is modulated by antipodal harmonic functions with the period in inverse proportion to diversity time delay. The time delay in the correlation receiver corresponds to the diversity time delay of informative noise signals. The correlation estimation problem appears in the case of data transmitting on the base of continuous noise carriers. Fluctuation analysis of correlation estimations with nonstationary trend at the data rate is performed. The intersystem jamming occurring in digital noise communications increase the correlation fluctuations at the receiver output and initiate asymptotic limitation of correlation performances without thermal noise in a wireless channel. Nonstationary trends of output correlation estimations become little if the informative time delay significantly exceeds the coherent times as noise carriers as additive white Gaussian noise. The forming of digital noise carriers is produced by the time window method. Simulation of noise communications shows that utilizing continuously noise carriers with time windows permits to decrease randomly fluctuations of correlation performances in the case when the product of noise signal bandwidth by bit duration exceeds one hundred units.

Hermes, a low-latency transactional storage for binary data streams from remote devices

In many contexts where data is streamed on a large scale, such as video surveillance systems, there is a dual requirement: secure data storage and continuous access to audio and video content by third parties, such as human operators or specific business logic, even while the media files are still being collected. However, using transactions to ensure data persistence often limits system throughput and latency. This paper presents a solution that enables both high ingestion rates with transactional data persistence and near real-time, low-latency access to the stream during collection. This immediate access enables the prompt application of specialized data engineering algorithms during data acquisition. The proposed solution is particularly suitable for binary data sources such as audio and video recordings in surveillance systems, and it can be extended to various big data scenarios via well-defined general interfaces. The scalability of the approach is based on the microservice architecture. Preliminary results obtained with Apache Kafka and MongoDB replica sets show that the proposed solution provides up to 3 times higher throughput and 2.2 times lower latency compared to standard multi-document transactions.

High-throughput DNA synthesis for data storage.

With the explosion of digital world, the dramatically increasing data volume is expected to reach 175 ZB (1 ZB = 1012 GB) in 2025. Storing such huge global data would consume tons of resources. Fortunately, it has been found that the deoxyribonucleic acid (DNA) molecule is the most compact and durable information storage medium in the world so far. Its high coding density and long-term preservation properties make itself one of the best data storage carriers for the future. High-throughput DNA synthesis is a key technology for "DNA data storage", which encodes binary data stream (0/1) into quaternary long DNA sequences consisting of four bases (A/G/C/T). In this review, the workflow of DNA data storage and the basic methods of artificial DNA synthesis technology are outlined first. Then, the technical characteristics of different synthesis methods and the state-of-the-art of representative commercial companies, with a primary focus on silicon chip microarray-based synthesis and novel enzymatic DNA synthesis are presented. Finally, the recent status of DNA storage and new opportunities for future development in the field of high-throughput, large-scale DNA synthesis technology are summarized.

A Novel Cipher-Based Data Encryption with Galois Field Theory

Both the act of keeping information secret and the research on how to achieve it are included in the broad category of cryptography. When people refer to "information security," they are referring to the study and use of methods that make data transfers harder to intercept. When we talk about "information security," this is what we have in mind. Using private keys to encrypt and decode messages is a part of this procedure. Because of its vital role in modern information theory, computer security, and engineering, cryptography is now considered to be a branch of both mathematics and computer science. Because of its mathematical properties, the Galois field may be used to encrypt and decode information, making it relevant to the subject of cryptography. The ability to encrypt and decode information is one such use. In this case, the data may be encoded as a Galois vector, and the scrambling process could include the application of mathematical operations that involve an inverse. While this method is unsafe when used on its own, it forms the foundation for secure symmetric algorithms like AES and DES when combined with other bit shuffling methods. A two-by-two encryption matrix is used to protect the two data streams, each of which contains 25 bits of binary information which is included in the proposed work. Each cell in the matrix represents an irreducible polynomial of degree 6. Fine-tuning the values of the bits that make up each of the two 25-bit binary data streams using the Discrete Cosine Transform (DCT) with the Advanced Encryption Standard (AES) Method yields two polynomials of degree 6. Optimization is carried out using the Black Widow Optimization technique is used to tune the key generation in the cryptographic processing. By doing so, we can produce two polynomials of the same degree, which was our original aim. Users may also use cryptography to look for signs of tampering, such as whether a hacker obtained unauthorized access to a patient's medical records and made any changes to them. Cryptography also allows people to look for signs of tampering with data. Indeed, this is another use of cryptography. It also has the added value of allowing users to check for indications of data manipulation. Users may also positively identify faraway people and objects, which is especially useful for verifying a document's authenticity since it lessens the possibility that it was fabricated. The proposed work achieves higher accuracy of 97.24%, higher throughput of 93.47%, and a minimum decryption time of 0.0047 s.

Experiments on direct chaotic differentially coherent data transmission in a wired communication channel

Methods of differentially coherent information transmission using noise signals are of interest because of the impossibility of implementing the known methods of correlation reception for such signals. With a potentially higher noise immunity compared to the methods of information transmission based on chaotic synchronization, however, they have a feature that does not allow transceivers to be implemented in practice. The transmitter and receiver of the scheme, based on already known methods of differentially coherent transmission, require a time delay comparable to the duration of the transmitted bits. With an analog implementation of the scheme this leads to a physical length of the delay line of tens of meters or more. Previously, the authors proposed and studied a differentially coherent transmission scheme in which there are no long delays. In this scheme, the duration of delays in the transmitter and receiver is determined not by the duration of the bit, but by the decay time of the autocorrelation function of the chaotic signal. Purpose of this work is to experimentally demonstrate the possibility of physical implementation of a direct-chaotic differentially coherent information transmission scheme in a wired communication channel. Methods. For this, a layout of the communication scheme, transmitting a binary data stream in the frequency range from 200 to 500 MHz, was designed and assembled. The layout is an ultrawideband differentially coherent transmitter and receiver connected via a wired channel. Results of the experiment are in full agreement with the previously obtained results of the analytical evaluations, as well as with the data of computer simulation. Conclusion. In the course of the research, a transceiver layout of a differentially coherent ultra-wideband direct chaotic communication scheme was developed, designed and manufactured. For the first time, experiments on the transmission of digital information were carried out on it, and thereby the practical feasibility and operability of the proposed direct chaotic differentially coherent transmission scheme were proved.

Online monitoring of high-dimensional binary data streams with application to extreme weather surveillance

With the rapid development of modern sensor technology, high-dimensional data streams appear frequently nowadays, bringing urgent needs for effective statistical process control (SPC) tools. In such a context, the online monitoring problem of high-dimensional and correlated binary data streams is becoming very important. Conventional SPC methods for monitoring multivariate binary processes may fail when facing high-dimensional applications due to high computational complexity and the lack of efficiency. In this paper, motivated by an application in extreme weather surveillance, we propose a novel pairwise approach that considers the most informative pairwise correlation between any two data streams. The information is then integrated into an exponential weighted moving average (EWMA) charting scheme to monitor abnormal mean changes in high-dimensional binary data streams. Extensive simulation study together with a real-data analysis demonstrates the efficiency and applicability of the proposed control chart.

Hellinger Distance Weighted Ensemble for imbalanced data stream classification

The imbalanced data classification remains a vital problem. The key is to find such methods that classify both the minority and majority class correctly. The paper presents the classifier ensemble for classifying binary, non-stationary and imbalanced data streams where the Hellinger Distance is used to prune the ensemble. The paper includes an experimental evaluation of the method based on the conducted experiments. The first one checks the impact of the base classifier type on the quality of the classification. In the second experiment, the Hellinger Distance Weighted Ensemble (HDWE) method is compared to selected state-of-the-art methods using a statistical test with two base classifiers. The method was profoundly tested based on many imbalanced data streams and obtained results proved the HDWE method's usefulness.

A Photonic Recurrent Neuron for Time-Series Classification

Neuromorphic photonics has turned into a key research area for enabling neuromorphic computing at much higher data-rates compared to their electronic counterparts, improving significantly the (multiply-and-accumulate) MAC/sec. At the same time, time-series classification problems comprise a large class of artificial intelligence (AI) applications where speed and latency can have a decisive role in their hardware deployment roadmap, highlighting the need for ultra-fast hardware implementations of simplified recurrent neural networks (RNN) that can be extended in more advanced long-short-term-memory (LSTM) and gated recurrent unit (GRU) machines. Herein, we experimentally demonstrate a novel photonic recurrent neuron (PRN) to classify successfully a time-series vector with 100-psec optical pulses and up to 10 Gb/s data speeds, reporting on the fastest all-optical real-time classifier. Experimental classification of 3-bit optical binary data streams is presented, revealing an average accuracy of >91% and confirming the potential of PRNs to boost speed and latency performance in time-series AI applications.

Human-Inspired Haptic Perception and Control in Robot-Assisted Milling Surgery.

Bone milling is one of the most widely used and high-risk procedures in various types of surgeries, and it is important to be noted that the experienced surgeon can perform such an operation safely. The objective of this article is to enhance the safety of the robot-assisted milling operation with the inspiration of human haptic perception. The emergence, coding and perception of the human haptic are introduced. Following this, a single axis accelerometer that measures the vibration of the surgical power tool is mounted in the robot arm, and the recorded acceleration signal is encoded as parallel stream of binary data. The data are subsequently inputted to the Hopfield network so as to identify the milling state. Inspired by human inference procedure, the fuzzy logic controller is introduced to control the robot to track the desired state when performing bone milling operations. A real-time implementation of the proposed method on a digital signal processing is also described. The experimental results in milling porcine spines prove that the robot accurately discriminates different milling states even when the additive noise is serious, and the safe motion control of the robot is also realized.

Formation of Unique Characteristics of Hiding and Encoding of Data Blocks Based on the Fragmented Identifier of Information Processed by Cellular Automata

Currently, the following applications of the theory of cellular automata are known: symmetric encryption, data compression, digital image processing and some others. There are also studies suggesting the possibility of building a public key system based on cellular automata, but this problem has not been solved. The purpose of the study is to develop an algorithm for hiding and encoding data blocks based on a fragmented identifier of information processed on the basis of cellular automata in the scale of binary data streams using an original method containing an public parameter in the conversion key. A mathematical model of the formation of unique data characteristics is considered, based on the use of patterns that determine the individual neighborhood of elements in cell encryption. A multi-threaded computing scheme has been developed for processing confidential data using the single-key method with a public parameter based on cellular automata and using data segmentation. To study individual chains in data blocks, a software module has been developed that allows one to evaluate the uniformity of information distribution during encryption. A variant of estimating the distribution of bits is proposed that indirectly reflects the cryptographic strength of the method. Based on the developed theoretical principles, a software module is synthesized that implements a transformation rule that takes into account the individual neighborhood of the processed element on the basis of a cellular automata. Experimental studies have shown that this modification made it possible to increase the speed of the method by up to 13 percent due to segmentation and the possibility of parallel processing of the original matrix, as well as to increase cryptographic strength due to the use of a unique chain of pseudo-random neighborhood (hereinafter referred to as PRN) defined by the transformation key. At the same time, it was possible to maintain uniformity of distribution of the output chain at the bit level and to ensure that the number of inversions was included in the confidence interval.

Experimental demonstration of encryption system using two-dimensional pattern for secure free-space optical communication

A secure free-space optical (FSO) communication system that physically introduces a two-dimensional pattern as a key is proposed for further improving the possibility of FSO communication. This paper presents the results of basic experiments conducted with the proposed encryption system for FSO communication that confirm the encryption and restoration of binary data streams in the proposed system configuration. Further, we define a pattern selection measure to improve the quality of the decoded signal in the encryption method by using a spatial pattern, and also evaluate the decoded signal obtained from the experimental results.

Two‐dimensional encryption system for secure free‐space optical communication of time‐series data streams

The importance of encryption in free-space optical communication systems has been increasing due to their widespread use. Herein, for the first time, the authors propose a novel two-dimensional encryption system for free-space optical communication using two spatial patterns as encryption keys. A data stream is physically encrypted with optical signals to reduce the risk of unauthorised third-party intrusion into communication. The encryption and restoration of a binary data stream using the proposed encryption system are confirmed by simulation results. The authors believe that, in the future, the proposed system could be used as an encryption method at the physical layer level to achieve the desired level of safety determined by the user.

Clustering for Binary Data Sets by Using Genetic Algorithm-Incremental K-means

This research was initially driven by the lack of clustering algorithms that specifically focus in binary data. To overcome this gap in knowledge, a promising technique for analysing this type of data became the main subject in this research, namely Genetic Algorithms (GA). For the purpose of this research, GA was combined with the Incremental K-means (IKM) algorithm to cluster the binary data streams. In GAIKM, the objective function was based on a few sufficient statistics that may be easily and quickly calculated on binary numbers. The implementation of IKM will give an advantage in terms of fast convergence. The results show that GAIKM is an efficient and effective new clustering algorithm compared to the clustering algorithms and to the IKM itself. In conclusion, the GAIKM outperformed other clustering algorithms such as GCUK, IKM, Scalable K-means (SKM) and K-means clustering and paves the way for future research involving missing data and outliers.

Color Image Transmission in SPC Channel Encoded Multiuser 5G Compatible Pattern Division Multiple Access (PDMA) Wireless Communication System

Pattern Division Multiple Access (PDMA) is a novel non-orthogonal multiple access scheme proposed to meet up the diverse demands on high capacity and large number of connections in the fifth generation (5G) wireless networks. PDMA uses the characteristic pattern to define the sparse mapping from data to a group of resources, and the sparsity of the pattern gives impacts on the capacity performance and detection complexity. The present thesis emphasizes greatly to develop a simulation model for the 5G compatible downlink Pattern Division Multiple Access (PDMA) scheme implemented wireless communication system. The simulated system incorporates a modern channel coding ((3, 2) SPC) and different low order digital modulation (4-QAM, QPSK and DQPSK) schemes. With implementation of G^[2,3]_PDMA pattern matrix for three users and considering total transmitted power of 40 Watt, 50%, 30% and 20% of total transmitted power have been assigned to first, second and third users and additionally phase shifting factors have been applied in power scaled transmitted signals of second and third users to resolve ambiguity in individual data separation. On consideration of both synthetically generated binary data stream and color image transmission in AWGN and Rayleigh fading channel, it is observable from MATLAB based simulation study that the ((3, 2) SPC) channel encoded simulated system is very much robust and effective in retrieving transmitted data. The impact of applicability of 2-D median image filtering technique in processing of three different identically sized color images and enhancement of image quality has clearly been observed. This thesis elucidates the benefits of multi-user data transmission in power domain.

Demonstration of flexible optical time-division multiplexing system for high-speed free-space optical communications

A high-speed free-space optical communication scheme based on optical time-division multiplexing (OTDM) is experimentally demonstrated. By multiplexing eight 2.5Gb/s base-rate signals, which is generated from a repetition-tunable actively mode-locked fiber ring laser modulated by pseudo-random binary sequence data stream, a 20Gb/s OTDM packet is obtained. After 50 m high-speed FSO system transmission, the 20Gb/s OTDM packet is injected into a highly nonlinear fiber (HNLF) loop to realize polarization-insensitive de-multiplexing based on four-wave mixing (FWM). Experimental results show that the OTDM de-multiplexer bit error rate (BER) can achieve 10−9 level with steady operation over 24 h, proving the practicality of this system.

Real-Time Streaming Communication With Optical Codes

Optical codes have long been used to carry small amounts of static data, such as URLs, IDs or other short binary sequences. In this paper, we experiment on the use of sequences of optical codes to form a one-way communication channel. In this context, a sender is made of a surface displaying rapidly changing codes, which are picked up by a receiver’s camera and converted back into a binary data stream. After presenting experimental results seeking the combination of frame rate, code size, and error correction level maximizing effective bandwidth, we describe the implementation of a robust communication protocol designed, specifically for lossy, simplex, and low-bandwidth data links. Our findings indicate that such a protocol is sufficient for carrying at least voice-quality audio in real time.

CL-AntInc Algorithm for Clustering Binary Data Streams Using the Ants Behavior

In this paper, we present a new approach using a non-hierarchical method in graph environment and the concept of artificial ants for both clustering and visualization using Tulip framework. This model can be presented to take into account data in blocks in an incremental way. It seems especially interesting to process binary data streaming. In this algorithm, we also suggest to apply swarm intelligence techniques for the incremental processing of this new challenging data type. The main novelty of this research work resides on the adaptation of CL-AntInc to perform clustering binary data streams and building growing graphs increasingly for this type of data.The proposed algorithm performance is evaluated using real world data sets extracted from Machine Learning Repository. Our algorithm is competitive when compared with other stream clustering methods.

Energy-efficient communication in multihop wireless sensor networks using ternary encoding and silent symbols

The ternary-with-silent-symbol TSS energy-efficient data communication technique was earlier proposed in Ghosh et al. 2008 which coupled ternary encoding of data stream with the use of silent periods for transmitting the ternary digits. The performance analysis of TSS using bit-error rate BER, however, is inadequate to capture the transitive error-propagation in the transmitted binary data stream. In this paper, we use the concept of frame-error rate FER to successfully capture the effects of the error-propagation and the message length reduction. Our FER-based analysis shows 23% average saving in transmitter energy compared to the non-coherent BFSK for AWGN channels, rather than 20% saving as in BER-based analysis. For coherent detection-based receiver we show that the average transmitter energy savings are about 30% and 17% relative to the non-coherent and coherent BFSK respectively. Simultaneously, there is energy saving of about 37% in the receiver relative to BFSK, which makes TSS a very suitable scheme for multihop communication in wireless sensor networks.

Algebraic method for blind recovery of punctured convolutional encoders from an erroneous bitstream

To enhance the quality of transmissions, all digital communication systems use error-correcting codes. By introducing some redundancy in the informative binary data stream, they allow one to better withstand channel impairments. The design of new coding schemes leads to a perpetual evolution of the digital communication systems and, thus, cognitive radio receivers have to be designed. Such receivers will be able to blind estimate the transmitter parameters. In this study, an algebraic method dedicated to the blind identification of punctured convolutional encoders is presented. The blind identification of such encoders is of great interest, because convolutional encoders are embedded in most digital transmission systems where the puncturing principle is used to increase the code rate to reduce the loss of the information data rate because of the redundancy introduced by the encoder. After a brief recall of the principle of puncturing codes and the construction of the equivalent punctured code, a new method dedicated to the blind identification of both the mother code and the puncturing pattern is developed when the received bits are erroneous. Finally, case studies are presented to illustrate the performances of our blind identification method.

Proposing a Standardized Protocol for Raw Biosignal Transmission

In this paper, we propose a standardized interface called TiA (TOBI interface A) to transmit raw biosignals, supporting multirate and block-oriented transmission of different kinds of signals from various acquisition devices (e.g., EEG, electrooculogram, near-infrared spectroscopy signals, etc.) at the same time. To facilitate a distinction between those kinds of signals, so-called signal types are introduced. TiA is a single-server, multiple-client system, whereby clients can connect to the server at runtime. Information transfer between client and server is divided into control and data connections. The control connections use transmission control protocol (TCP) and transmit extensible-markup-language (XML)-encoded meta information. The data transmission utilizes a user datagram protocol (UDP) or TCP with a binary data stream. A standardized handshaking procedure for the connection setup and a standardized binary data packet has been defined. Thus, a standardized layer, abstracting used hardware devices and facilitating distributed raw data transmission in a standardized way, has been evolved. A cross-platform library, implemented in C ++, is available for download.