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Zero watermarking constructs the watermark information according to the characteristics of the original data, without changing the data structure and data accuracy. Maintaining high data accuracy is the premise of building information modelling (BIM) usability, so zero watermarking is a hotspot in the research of BIM data security protection. BIM model is a type of 3D model, however, most of the existing zero watermarking algorithms for 3D models are difficult to be better applied to BIM data due to data structure differences. To solve this problem, a zero-watermarking algorithm for BIM data based on distance partitioning and skewness measure is proposed. Firstly, after spatial partitioning based on element paradigm value, the mapping relationship between different partitions and watermarking bits is established. Then, the skewness of elements is calculated, and the skewness measure sign is used as the feature to obtain the binary sequence. Finally, the dissimilarity operation is performed on the binary sequence and the original watermarking sequence which was disordered to construct the zero watermark of the BIM data. The experimental results show that the zero watermarks constructed from different BIM data are unique and robust to translation, rotation, element deletion, element addition, and format conversion attacks. In addition, the superiority of this paper's algorithm over the comparison algorithm in terms of robustness is compared. Therefore, the proposed algorithm can effectively provide technical support for BIM data copyright protection. [ABSTRACT FROM AUTHOR]

Digital repositories play a crucial role in organizing and preserving vast collections of digital content. Efficiently ingesting large amounts of data into these repositories is a common challenge faced by institutions. This paper explores the use of bulk upload techniques in DSpace, an open-source digital repository software, to streamline the ingestion process and enhance repository management. We discuss the benefits of bulk upload in terms of time savings, metadata consistency, and scalability. Additionally, we delve into the technical aspects of implementing bulk upload in DSpace, covering the Simple Archive Format (SAF), metadata mapping, and handling of digital files. Furthermore, we highlight real-world examples and best practices for utilizing bulk upload in DSpace. By adopting this approach, institutions can significantly improve their efficiency in managing and preserving digital content, ensuring a seamless user experience, and facilitating knowledge dissemination. Here, an experimental method of research/case study technique is utilized to evaluate the efficiency and effectiveness of the design model for implementation of the bulk uploading of documents in Dspace at Bennett University is practiced. The feedback is gathered in order to identify the flaws and make the necessary improvements. Simple Archive Format (SAF) is a utility that converts Bitstream/Content files plus a metadata.csv file into a Simple Archive Format package, making bulk uploads to the DSpace repository simple. All question papers were digitized using a high-quality scanner, an Excel file with Dublin core information was created, and Excel was converted to CSV format in order to import all old question papers in bulk into the Bennett University Digital Repository Services. The study indicates that it is essential to pay close attention to the precise format of metadata leveraging the Dublin core and the file's location. It is an experiment conducted by the Bennett University Library and the research was confined to Bennett University digital repository. [ABSTRACT FROM AUTHOR]

Unpredictable strings are sequences of data with complex and erratic behavior, which makes them an object of interest in various scientific fields. Unpredictable strings related to chaos theory was investigated using a genetic algorithm. This paper presents a new genetic algorithm for converting large binary sequences into their periodic form. The MakePeriod method is also presented, which is aimed at optimizing the search for such periodic sequences, which significantly reduces the number of generations to achieve the result of the problem under consideration. The analysis of the deviation of a nonperiodic sequence from its considered periodic transformation was carried out, and methods of crossover and mutation were investigated. The proposed algorithm and its associated conclusions can be applied to processing large sequences and different values of the period, and also emphasize the importance of choosing the right methods of crossover and mutation when applying genetic algorithms to this task. [ABSTRACT FROM AUTHOR]

Tang–Gong interleaved sequences constructed from the generalized GMW sequence pair are a class of binary sequences with optimal autocorrelation magnitude. In this paper, the symmetric 2-adic complexity of these sequences is investigated. We first derive a lower bound on their 2-adic complexity by extending the method proposed by Hu. Then, by analysing the algebraic structure of these sequences, a lower bound on their symmetric 2-adic complexity is obtained. Our result shows that the symmetric 2-adic complexity of these sequences is large enough to resist attacks with the rational approximation algorithm. [ABSTRACT FROM AUTHOR]

3D point cloud data, as an immersive detailed data source, has been increasingly used in numerous applications. To deal with the computational and storage challenges of this data, it needs to be compressed before transmission, storage, and processing, especially in real-time systems. Instead of decoding the compressed data stream and subsequently conducting downstream tasks on the decompressed data, analyzing point clouds directly in their compressed domain has attracted great interest. In this paper, we dive into the realm of compressed point cloud classification (CPCC), aiming to achieve high point cloud classification accuracy in a bitrate-saving way by ensuring the bit stream contains a high degree of representative information of the point cloud. Edge information is one of the most important and representative attributes of the point cloud because it can display the outlines or main shapes. However, extracting edge points or information from point cloud models is challenging due to their irregularity and sparsity. To address this challenge, we adopt an advanced edge-sampling method that enhances existing state-of-the-art (SOTA) point cloud edge-sampling techniques based on attention mechanisms and consequently develop a novel CPCC method "CPCC-PES" that focuses on point cloud's edge information. The result obtained on the benchmark ModelNet40 dataset shows that our model has superior rate-accuracy trade-off performance than SOTA works. Specifically, our method achieves over 90% Top-1 Accuracy with a mere 0.08 bits-per-point (bpp), marking a remarkable over 96% reduction in BD-bitrate compared with specialized codecs. This means that our method only consumes 20% of the bitrate of other SOTA works while maintaining comparable accuracy. Furthermore, we propose a new evaluation metric named BD-Top-1 Accuracy to evaluate the trade-off performance between bitrate and Top-1 Accuracy for future CPCC research. [ABSTRACT FROM AUTHOR]

In this paper, we proposed a novel deep image coding and decoding model for GMMQI (Gaussian mixture model quartile intervals, GMMQI) and a variable rate bit allocation method to optimize the rate distortion performance and prioritize the transmissions of more significant information. First, to address the problem of bit streams leading to ambiguity during encoding and decoding, we convert the image into a potential tensor, each element of which uses a four-bit parameter dictionary to preserve the parameter bits. Then, the variable rate is calculated using quaternions based on the parameter dictionary, and a hybrid CLM &BAM (Channel latent map & Bit allocation map) approach is designed to assign bits to the potential tensor and encode it, which transforms the problem of finding the optimal encoder-decoder into finding the optimal hyper-parameters in the model and reduces the complexity of the GMMQI model. Finally, a GMMQI approach with variable rate bit allocation is developed in combination with CLM &BAM, to be able to prioritize the transmission of more significant information. The experimental results show that the GMMQI method reaches an advanced level compared to the traditional image compression standards BPG, JPEG2000, and JPEG, and is comparable to the most advanced level compared to the existing deep learning based compression methods. [ABSTRACT FROM AUTHOR]

This research proposes a sensor for tracking the motion of a human head via optical tactile sensing. It implements the use of a fibrescope a non-metal alternative to a webcam. Previous works have included robotics grippers to mimic the sensory features of human skin, that used monochrome cameras and depth cameras. Tactile sensing has shown advantages in feedback-based interactions between robots and their environment. The methodology in this paper is utilised to track motion of objects in physical contact with these sensors to replace external camera based motion capture systems. Our immediate application is related to detection of human head motion during radiotherapy procedures. The motion was analysed in two degrees of freedom, respective to the tactile sensor (translational in z-axis, and rotational around y-axis), to produce repeatable and accurate results. The movements were stimulated by a robot arm, which also provided ground truth values from its end- effector. The fibrescope was implemented to ensure the device's compatibility with electromagnetic waves. The cameras and the ground truth values were time synchronised using robotics operating systems tools. Image processing methods were compared between grayscale and binary image sequences, followed by motion tracking estimation using deterministic approaches. These included Lukas-Kanade Optical Flow and Simple Blob Detection, by OpenCV. The results showed that the grayscale image processing along with the Lukas- Kanade algorithm for motion tracking can produce better tracking abilities, although further exploration to improve the accuracy is still required. [ABSTRACT FROM AUTHOR]

Operational amplifiers (op amps) are fundamental blocks that find wide application both as stand-alone devices and as crucial blocks embedded in various Systems on Chips (SoCs). Achieving high defect coverage, as well as performing defect localization in these circuits, has proven to be a difficult/expensive task, even with sophisticated testing circuitry. The ISO 26262 standard for functional safety (FuSa) includes the stringent requirement that an automotive IC must have a very high defect coverage. This reinforces the need to ensure the functionality of analog and mixed (AMS) circuits, especially in mission critical applications. This paper presents an all-digital op amp defect detection, diagnosis, and localization method that can be used both for production and in-field tests and discusses various implementation of the proposed method. We validated our results using extensive transistor-level simulations of multiple op amp architectures using TSMC 180 nm technology. Across op amp architectures and multiple implementation approaches, we achieved a worst-case and best-case defect coverage of 94.5% and 99%, respectively. Furthermore, in this work, we also propose a defect diagnosis and localization strategy using recorded bit streams from states of digital injectors and detectors. [ABSTRACT FROM AUTHOR]

This paper introduces a low-complexity start–stop true random number generator (TRNG) utilizing jitter in ring oscillators (ROs). Incorporating phase detectors enhances entropy extraction from the same number of ROs. The raw bits undergo online post-processing using the SHA-1 algorithm, which is widely supported by many programming languages. The output bit streams pass all NIST statistical tests (SP 800-22 and SP-90B). Bits are generated on demand, enhancing security by preventing eavesdropping during continuous bit production. The TRNG maintains its performance regardless of the FPGA manufacturer. [ABSTRACT FROM AUTHOR]

This paper presents the overview and rationale behind the Decoder-Side Depth Estimation (DSDE) mode of the MPEG Immersive Video (MIV) standard, using the Geometry Absent profile, for efficient compression of immersive multiview video. A MIV bitstream generated by an encoder operating in the DSDE mode does not include depth maps. It only contains the information required to reconstruct them in the client or in the cloud: decoded views and metadata. The paper explains the technical details and techniques supported by this novel MIV DSDE mode. The description additionally includes the specification on Geometry Assistance Supplemental Enhancement Information which helps to reduce the complexity of depth estimation, when performed in the cloud or at the decoder side. The depth estimation in MIV is a non-normative part of the decoding process, therefore, any method can be used to compute the depth maps. This paper lists a set of requirements for depth estimation, induced by the specific characteristics of the DSDE. The depth estimation reference software, continuously and collaboratively developed with MIV to meet these requirements, is presented in this paper. Several original experimental results are presented. The efficiency of the DSDE is compared to two MIV profiles. The combined non-transmission of depth maps and efficient coding of textures enabled by the DSDE leads to efficient compression and rendering quality improvement compared to the usual encoder-side depth estimation. Moreover, results of the first evaluation of state-of-the-art multiview depth estimators in the DSDE context, including machine learning techniques, are presented. [ABSTRACT FROM AUTHOR]

This paper discusses the auto-correlation functions of chaotic binary sequences obtained by a one-dimensional chaotic map and two binary functions. The two binary functions are alternately used to obtain a binary sequence from a chaotic real-valued sequence. We consider two similar methods and give the theoretical auto-correlation functions of the new binary sequences, which are expressed by the auto-/cross-correlation functions of the two chaotic binary sequences generated by a single binary function. Furthermore, some numerical experiments are performed to confirm the validity of the theoretical auto-correlation functions. [ABSTRACT FROM AUTHOR]

In this paper, a low-power Injection-Locked Clock and Data Recovery (ILCDR) using a 28 nm Ultra-Thin Body and Box-Fully Depleted Silicon On Insulator (UTBB-FDSOI) technology is presented. The back-gate auto-biasing of UTBB-FDSOI transistors enables the creation of a Quadrature Ring Oscillator (QRO) reducing both size and power consumption compared to an LC tank oscillator. By injecting a digital signal into this circuit, we realize an Injection-Locked Oscillator (ILO) with low jitter. Thanks to the good performance of this oscillator, we propose a low-power ILCDR with fast locking time and low jitter for burst-mode applications. The main novelty consists of the implementation of a complementary QRO based on back-gate control using FDSOI technology to realize a simple and efficient ILCDR circuit. With a Pseudo-Random Binary Sequence (PRBS7) at 868 Mbps, the recovered clock jitter is 26.7 ps (2.3% UIp-p) and the recovered data jitter is 11.9 ps (1% UIp-p). With a 0.6 V power supply, the power consumption is 318μW. All the results presented here are based on post-layout simulations, as no prototypes have been produced. Similarly, we can estimate the surface area of the chip (without the pad ring) at around 6600 μm2. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel encryption method for JPEG bitstreams in which encrypted data can preserve the JPEG file format with the same size as that without encryption. Accordingly, data encrypted with the method can be decoded without any modification of header information by using a standard JPEG decoder. In addition, the method makes two contributions that conventional methods allowing bitstream-level encryption do not: spatially partial encryption and block-permutation-based encryption. To achieve this, we propose using a code called restart marker for the first time, which can be inserted at regular intervals between minimum coded units (MCUs) for encryption. This allows us to define extended blocks separated by restart markers, so the two contributions are possible with restart markers. In experiments, the effectiveness of the method is verified in terms of file size preservation and the visibility of encrypted images. [ABSTRACT FROM AUTHOR]

A gearbox compound fault intelligent diagnosis method based on the period group sparse model is proposed for the problem that the fault features are coupled with each other and the fault components are superimposed on each other and difficult to be separated in the gearbox compound fault signal. Firstly, a binary sequence is constructed to embed the fault pulse period as a priori knowledge into the group sparse model to decouple and separate the composite fault signal while maintaining the amplitude and sparsity of the extracted features. Secondly, the wavelet packet energy features of the decoupled signals are extracted to improve the data quality while enhancing the characterization ability of the dictionary in the classification model. Finally, the wavelet packet energy features are imported into the sparse dictionary classification model, and the fault diagnosis is completed by outputting the fault categories using the self-driven characteristics of the data. The results show that the fault identification accuracy using the proposed method is 97%. In addition, the experimental validation under different states and working conditions with different rotational speeds allows the superiority and effectiveness of the algorithm in this paper to be tested and has the feasibility of a practical application in engineering. [ABSTRACT FROM AUTHOR]

Let p be an odd prime with p ≡ 7 (mod 12), p-1/2 be the least integer such that 2p-1/2 ≡ 1 (mod p), and q = 2p-1/2. Let α be a primitive element of the finite field Fq and β = αq-1/p. Suppose that ω = Σi =0² βmζ3i ∈ F*q, where m ∈ F*p and ζ3 is a 3rd root of unity in Fp. Let {ui} = (Trq/2(σβi))i=0q-2 be a binary sequence of period q - 1. In this paper, we obtained the cross correlation distribution between two sequences {ui} and its q-1/p -decimation sequence, which is two-valued. [ABSTRACT FROM AUTHOR]

Image steganography is a scheme that hides secret information in a cover image without being perceived. Most of the existing steganography methods are more concerned about the visual similarity between the stego image and the cover image, and they ignore the recovery accuracy of secret information. In this paper, the steganography method based on invertible neural networks is proposed, which can generate stego images with high invisibility and security and can achieve lossless recovery for secret information. In addition, this paper introduces a mapping module that can compress information actually embedded to improve the quality of the stego image and its antidetection ability. In order to restore message and prevent loss, the secret information is converted into a binary sequence and then embedded in the cover image through the forward operation of the invertible neural networks. This information will then be recovered from the stego image through the inverse operation of the invertible neural networks. Experimental results show that the proposed method in this paper has achieved competitive results in the visual quality and safety of stego images and achieved 100% accuracy in information extraction. [ABSTRACT FROM AUTHOR]

This paper presents the modified HEVC Screen Content Coding (SCC) that was adapted to be more efficient as an internal video coding of the MPEG Immersive Video (MIV) codec. The basic, unmodified SCC is already known to be useful in such an application. However, in this paper, we propose three additional improvements to SCC to increase the efficiency of immersive video coding. First, we analyze using the quarter-pel accuracy in the intra block copy technique to provide a more effective search of the best candidate block to be copied in the encoding process. The second proposal is the use of tiles to allow inter-view prediction inside MIV atlases. The last proposed improvement is the addition of the MIV bitstream parser in the HEVC encoder that enables selecting the most efficient coding configuration depending on the type of currently encoded data. The experimental results show that the proposal increases the compression efficiency for natural content sequences by almost 7% and simultaneously decreases the computational time of encoding by more than 15%, making the proposal very valuable for further research on immersive video coding. [ABSTRACT FROM AUTHOR]

The existing one-factor cancellable biometrics algorithms generally require random sequences to reorder the biometrics, which reduces the discrimination of the transformed biometrics. Some algorithms hide and transmit the random sequence by XORing the random sequence with original biometrics, which may cause the leakage of the original biometrics. Therefore, this paper proposes a one-factor cancellable fingerprint template protection based on index self-encoding. First, the integer sequence generated by the hash function is used as the index. The random sequence is automatically encoded directly by the index value, and the generated binary sequence retains the original biological characteristics to the greatest extent. Second, self-encoding binary sequence and random binary sequence are XORed to obtain the encoded key without directly storing binary factor sequences. Experiments are implemented on the fingerprint database of FVC2002 and FVC2004, the results show that the recognition rate is enhanced; meanwhile, it fits the design criteria of cancellable biometrics. [ABSTRACT FROM AUTHOR]

Federated learning has been widely applied because it enables a large number of IoT devices to conduct collaborative training while maintaining private data localization. However, the security risks and threats faced by federated learning in IoT applications are becoming increasingly prominent. Except for direct data leakage, there is also a need to face threats that attackers interpret gradients and infer private information. This paper proposes a Privacy Robust Aggregation Based on Federated Learning (PBA), which can be applied to multiple server scenarios. PBA filters outliers by using the approximate Euclidean distance calculated from binary sequences and the 3 σ criterion. Then, this paper provides correctness analysis and computational complexity analysis on the aggregation process of PBA. Moreover, the performance of PBA is evaluated concerning ensuring privacy and robustness in this paper. The results indicate that PBA can resist Byzantine attacks and a state-of-the-art privacy inference, which means that PBA can ensure privacy and robustness. [ABSTRACT FROM AUTHOR]

This paper presents a model of binary random sequence with probabilities depending on previous sequence values as well as on a set of covariates. Both these dependencies are expressed via the logistic regression model, such a choice enables an easy and reliable model parameters estimation. Further, a model with time-depending parameters is considered and method of solution proposed. The main objective is then the application dealing with both artificial and real data cases, illustrating the method of model evaluation and its use. [ABSTRACT FROM AUTHOR]

Entropy estimation is a fundamental problem in information theory that has applications in various fields, including physics, biology, and computer science. Estimating the entropy of discrete sequences can be challenging due to limited data and the lack of unbiased estimators. Most existing entropy estimators are designed for sequences of independent events and their performances vary depending on the system being studied and the available data size. In this work, we compare different entropy estimators and their performance when applied to Markovian sequences. Specifically, we analyze both binary Markovian sequences and Markovian systems in the undersampled regime. We calculate the bias, standard deviation, and mean squared error for some of the most widely employed estimators. We discuss the limitations of entropy estimation as a function of the transition probabilities of the Markov processes and the sample size. Overall, this paper provides a comprehensive comparison of entropy estimators and their performance in estimating entropy for systems with memory, which can be useful for researchers and practitioners in various fields. [ABSTRACT FROM AUTHOR]

Currently, distributed real-time control systems need the creation of devices that perform online computing operations close to the sensor. The proposed online-computers of elementary mathematical functions can be used as components for the functional conversion of signals in the form of pulse streams received from measuring sensors with frequency output. Objective. The objective of the study is the development of mathematical, architectural and automata models for the design of bit-stream online-computers of elementary mathematical functions in order to create a unified approach to their design, due to which the accuracy of calculating functions can be increased, functional capabilities expanded, hardware costs reduced, and design efficiency increased. Method. Mathematical models of devices were developed using the method of forming increments of ascending step functions based on inverse functions with minimization of calculation error. Automata models of online-computers based on Moore’s Finite State Machine have been developed, the graph diagrams of which made it possible to ensure the clarity of function implementation algorithms, to increase visibility and invariance of implementation in formal languages of programming and hardware description. Results. The paper presents the results of research, development and practical approbation of design models of bit-stream onlinecomputers of power functions and root extraction function. A generalized architecture of an online-computer was proposed. Conclusions. The considered functional online-computers are effective from the point of view of calculation accuracy, simplicity of technical implementation, and universality of the architecture. [ABSTRACT FROM AUTHOR]

This paper proposes an inductor-less D-latch. In the proposed D-latch, negative feedback is used that makes input impedance appears to be inductive for the high-frequency input signal. The bandwidth is increased by around 23% due to this effect. Two applications are shown in this paper to verify the proposed latch operation: a pseudo-random binary sequence (PRBS) generator and a serializer. The speed of the PRBS generator and serializer has improved by 15.8% and 23% using the proposed latch, respectively. The post-layout simulation results in 90 nm CMOS technology with a power supply of 1 V prove the concept. To study functional correctness and scalability of the proposed architecture to lower technology nodes, 22 nm PTM model is used and verified the correct operation of the proposed architecture. [ABSTRACT FROM AUTHOR]

In real life, the text is one of the main carrier forms of information, which carries human civilization, and spreads knowledge to people, and also promotes culture and records history; however, how to read more information in a limited time, that is, to improve reading efficiency, has become a problem to be solved by current technology. The purpose of this paper is to integrate the existing wearable device concept, combined with a wireless intelligent sensor system; design a wearable reading assistance system designed to facilitate the use of blind and partially sighted people, based on the study and comparison of existing text recognition products; improve their functions and implementation platform, combined with wireless network; and design a wearable device that can achieve foreign text recognition and reading cognitive state reading assistance thereby improving reading efficiency. This paper proposes a method to implement foreign text decoding under the embedded platform with relatively few resources and quickly completes image acquisition, binarization, and compressed storage through the bit and storage area and DMA (direct memory access) double buffering mechanism unique to the chip selected in this paper; proposes to use the connected boundary tracking algorithm to find foreign text locators, reducing a large number of floating-point operations; does not rotate the image, instead, the image is directly sampled at the current rotation angle, and then foreign text bitstream information is acquired to realize the decoding of foreign text under the embedded platform with relatively fewer resources. [ABSTRACT FROM AUTHOR]

The fate of stars in the zero-age main-sequence (ZAMS) range ≈8–12 M ⊙ is unclear. They could evolve to form white dwarfs or explode as electron-capture supernovae (SNe) or iron core-collapse SNe (CCSNe). Even though the initial mass function indicates that this mass range should account for over 40% of all CCSN progenitors, few have been observationally confirmed, likely due to the faintness and rapid evolution of some of these transients. In this paper, we present a sample of nine Ca-rich/O-poor Type IIb SNe detected by the Zwicky Transient Facility with progenitors likely in this mass range. These sources have a [Ca ii ] λ λ 7291, 7324/[O i ] λ λ 6300, 6364 flux ratio of ≳2 in their nebular spectra. Comparing the measured [O i ] luminosity (≲1039 erg s−1) and derived oxygen mass (≈0.01 M ⊙) with theoretical models, we infer that the progenitor ZAMS mass for these explosions is less than 12 M ⊙. The ejecta properties (M ej ≲ 1 M ⊙ and E kin ∼ 1050 erg) are also consistent. The low ejecta mass of these sources indicates a class of strongly-stripped SNe that is a transition between the regular stripped-envelope SNe and ultra-stripped SNe. The progenitor could be stripped by a main-sequence companion and result in the formation of a neutron star−main sequence binary. Such binaries have been suggested to be progenitors of neutron star−white dwarf systems that could merge within a Hubble time and be detectable with LISA. [ABSTRACT FROM AUTHOR]

Interpolation-based reversible data hiding (IRDH) is a method for embedding data in a reversible manner into digital images. It is based on the polynomial interpolation to hide the secret data bit stream in the coefficients of the interpolation polynomial. In this paper, an IRDH method that combines a modified neighbor mean interpolation is presented with a new method for reversibly embedding secret data in interpolated pixels. This method uses log base 2 of the decimal value of the interpolated pixel to replace a corresponding number of bits with the bits of the secret data, allowing for a higher bit stream to be embedded with better image quality. The results from experiments show that the introduced method can implant on average, 1300000 bits of secret data with an average PSNR of 28.5 dB, which is a significant improvement over existing and related works. [ABSTRACT FROM AUTHOR]

This paper presents a pseudo-random binary sequence (PRBS) generator using merged XOR-D flip-flop as building blocks. The proposed architecture uses differential cascode voltage switch logic (DCVSL)-based dynamic XOR gate. The cross-coupled architecture of the pull-up network creating positive feedback in the DCVSL XOR gate is used as a latch by adding a transistor to apply a clock signal. This arrangement reduces the requirement of one latch in a master–slave D flip-flop (MS-DFF) from each lane. It reduces the area occupied in the layout and power requirements for the PRBS generator. The post-layout simulation for the PRBS generator operating at 5 Gb/s is performed in the 65 nm CMOS technology with a 1 V supply voltage. The proposed PRBS generator requires 2.4 mW of power. The jitter is 5.6 ps for the worst-case output of the proposed PRBS generator. In the proposed merged XOR-D flip-flop, there is an improvement of 33.3%, 27.4%, 29.1%, and 31.2% in power, area, maximum operating frequency, and the number of transistors, respectively, compared to when both XOR gate and D flip-flop are used separately. The figure of merit is improved by 14.8% for the proposed PRBS generator. [ABSTRACT FROM AUTHOR]

The paper presents the results of the study of the influence of symmetry in the design of bit-stream digital converters. We have shown realizations of the symmetry-based approach at different levels: at the level of basic elements, functional converters, and at the level of processes occurring in bit-streaming devices. Using symmetry in design, we have developed basic bit-stream elements that realize frequently used transformations with good technical performance. As a research result, we present descriptions and implementation results of the designed symmetric bit-stream devices in FPGA chips. Using the proposed elements and the concept of symmetric bit-stream device design, we designed and presented a specialized computing module for a temperature sensor controller. [ABSTRACT FROM AUTHOR]

Digital watermarking technology is an important means to effectively protect three-dimensional (3D) model data. Among them, "blind detection" and "robustness" are key and difficult points in the current research of digital watermarking technology based on 3D models. In order to realize the blind detection of a watermark and improve its robustness against various common attacks at the same time, this paper proposes a dual blind watermarking method based on the normal feature of the centroid of first-ring neighboring points. The local spherical coordinate system is constructed by calculating two different normal vectors, and the first pattern watermark and the second random binary sequence watermark are embedded, respectively. The experimental results show that this method can not only realize the blind detection of dual watermarks, but also have the ability to resist common attacks such as translation, rotation, scaling, cropping, simplification, smoothing, noise, and vertex reordering to a certain extent. [ABSTRACT FROM AUTHOR]

The event sensor provides high temporal resolution and generates large amounts of raw event data. Efficient low-complexity coding solutions are required for integration into low-power event-processing chips with limited memory. In this paper, a novel lossless compression method is proposed for encoding the event data represented as asynchronous event sequences. The proposed method employs only low-complexity coding techniques so that it is suitable for hardware implementation into low-power event-processing chips. A first, novel, contribution consists of a low-complexity coding scheme which uses a decision tree to reduce the representation range of the residual error. The decision tree is formed by using a triplet threshold parameter which divides the input data range into several coding ranges arranged at concentric distances from an initial prediction, so that the residual error of the true value information is represented by using a reduced number of bits. Another novel contribution consists of an improved representation, which divides the input sequence into same-timestamp subsequences, wherein each subsequence collects the same timestamp events in ascending order of the largest dimension of the event spatial information. The proposed same-timestamp representation replaces the event timestamp information with the same-timestamp subsequence length and encodes it together with the event spatial and polarity information into a different bitstream. Another novel contribution is the random access to any time window by using additional header information. The experimental evaluation on a highly variable event density dataset demonstrates that the proposed low-complexity lossless coding method provides an average improvement of 5.49 % , 11.45 % , and 35.57 % compared with the state-of-the-art performance-oriented lossless data compression codecs Bzip2, LZMA, and ZLIB, respectively. To our knowledge, the paper proposes the first low-complexity lossless compression method for encoding asynchronous event sequences that are suitable for hardware implementation into low-power chips. [ABSTRACT FROM AUTHOR]

nth order Fibonacci word fn is defined recursively by fixing the first two initial letters, namely f0 and f1. W.H. Chaun (1993) proposed a few ways of indexing the Fibonacci words with binary sequences in order to generate the Fibonacci words. Two-dimensional Fibonacci words (or Fibonacci arrays) were first defined in the year 2000 as an infinite sequence of arrays obtained recursively by fixing the four initial letters, namely f0,0, f0,1, f1,0 and f1,1. In 2021, few results on indexed Fibonacci and indexed involutive Fibonacci words have been studied. In this paper, we extend their work to Fibonacci arrays by defining a new way of indexing and proving results based on the indexing. [ABSTRACT FROM AUTHOR]

This paper describes new, simple, recursive methods of construction for orientable sequences, i.e. periodic binary sequences in which any $n$ -tuple occurs at most once in a period in either direction. As has been previously described, such sequences have potential applications in automatic position-location systems, where the sequence is encoded onto a surface and a reader needs only examine $n$ consecutive encoded bits to determine its location and orientation on the surface. The only previously described method of construction (due to Dai et al.) is somewhat complex, whereas the new techniques are simple to both describe and implement. The methods of construction cover both the standard ‘infinite periodic’ case, and also the aperiodic, finite sequence, case. Both the new methods build on the Lempel homomorphism, first introduced as a means of recursively generating de Bruijn sequences. [ABSTRACT FROM AUTHOR]

This paper proposes a novel image encryption algorithm based on an integer form of chaotic mapping and 2-order bit compass diffusion technique. Chaotic mapping has been widely used in image encryption. If the floating-point number generated by chaotic mapping is applied to image encryption algorithm, it will slow encryption and increase the difficulty of hardware implementation. An innovative pseudo-random integer sequence generator is proposed. In chaotic system, the result of one-iteration is used as the shift value of two binary sequences, the original symmetry relationship is changed, and then XOR operation is performed to generate a new binary sequence. Multiple iterations can generate pseudo-random integer sequences. Here integer sequences have been used in scrambling of pixel positions. Meanwhile, this paper demonstrates that there is an inverse operation in the XOR operation of two binary sequences. A new pixel diffusion technique based on bit compass coding is proposed. The key vector of the algorithm comes from the original image and is hidden by image encryption. The efficiency of our proposed method in encrypting a large number of images is evaluated using security analysis and time complexity. The performance evaluation of algorithm includes key space, histogram differential attacks, gray value distribution(GDV),correlation coefficient, PSNR, entropy, and sensitivity. The comparison between the results of coefficient, entropy, PSNR, GDV, and time complexity further proves the effectiveness of the algorithm. [ABSTRACT FROM AUTHOR]

The incorporation of digital modulation into radar systems poses various challenges in the field of radar design, but it also offers a potential solution to the shrinking availability of low-noise operating environments as the number of radar applications increases. Additionally, digital systems have reached a point where available components and technology can support higher speeds than ever before. These advancements present new avenues for radar design, in which digitally controlled phase-modulated continuous wave (PMCW) radar systems can look to support multiple collocated radar systems with low radar-radar interference. This paper proposes a reconfigurable PMCW radar for use in vital sign detection and gesture recognition while utilizing digital carrier modulation and compares the radar responses of various modulation schemes. Binary sequences are used to introduce phase modulation to the carrier wave by use of a field programable gate array (FPGA), allowing for flexibility in the modulation speed and binary sequence. Experimental results from the radar demonstrate the differences between CW and PMCW modes when measuring the respiration rate of a human subject and in gesture detection. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel image coding framework with semantic-aware visual decomposition towards extremely low bitrate compression. In particular, an input image is analyzed into a semantic map as structural representation and semantic-wise texture representation and further compressed into bitstreams at the encoder side. On the decoder side, the received bitstreams of dual-layer representations are decoded and reconstructed for target image synthesis with generative models. Moreover, the attention mechanism is introduced into the model architecture for texture representation modeling and a coherency regularization is proposed to further optimize the texture representation space by aligning the representation space with the source pixel space for higher synthesis quality. Besides, we also propose a cross-channel entropy module and control the quantization scale to facilitate rate-distortion optimization. Upon compressing the decomposed components into the bitstream, the simple yet effective representation philosophy benefits image compression in many aspects. First, in terms of compression performance, compact representations, and high visual synthesis quality can bring remarkable advantages. Second, the proposed framework yields a physically explainable bitstream composed of the structural segment and semantic-wise texture segments. Third and most importantly, subsequent vision tasks (e.g., content manipulation) can receive fundamental support from the semantic-aware visual decomposition and synthesis mechanism. Extensive experimental results demonstrate the superiority of the proposed framework towards efficient visual representation learning, high efficiency image compression ( < 0.1 bpp), and intelligent visual applications (e.g., manipulation and analysis). [ABSTRACT FROM AUTHOR]

Structures for the evaluation of fast Fourier transforms are important components in several signal-processing applications and communication systems. Their capabilities play a key role in the performance enhancement of the whole system in which they are embedded. In this paper, a novel implementation of the discrete Fourier transform is proposed, based on a bit-slice approach and on the exploitation of the input sequence finite word length. Input samples of the sequence to be transformed are split into binary sequences and each one is Fourier transformed using only complex sums. An FPGA-based solution characterized by low latency and low power consumption is designed. Simulations have been carried out, first in the Matlab environment, then emulated in Quartus IDE with Intel. The hardware implementation of the conceived system and the test for the functional accuracy verification have been performed, adopting the DE2-115 development board from Terasic, which is equipped with the Cyclone IV EP4CE115F29C7 FPGA by Intel. [ABSTRACT FROM AUTHOR]

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In the paper the binary mechanism of the long-distance image transfer in a wire-medium (WM) endoscope is suggested and studied. We have shown that a discrete image formed by a set of point sources TM-polarized with respect to the WM can be transferred from the input to the output of the endoscope in a very broad frequency band. The underlying physics is the formation of local channels by a group of four adjacent wires. It allows the transfer of the near field beyond the Fabry–Perot resonances at which the known canalization mechanism offers the image. Both numerical simulations and experimental measurements confirm the deeply subwavelength resolution on the output WM interface. The binary imaging was studied until the frequencies at which the endoscope length exceeds 5λ. The transfer is possible in the entire investigated frequency range (from 1 up to 4 GHz) except for the frequencies where the Fabry–Perot resonance are not enough suppressed. [ABSTRACT FROM AUTHOR]

This article addresses polynomial computation with unipolar stochastic logic by exploiting correlation between the bit-streams. The AND-OR, double-NAND, OR-AND and double-NOR circuits are presented for polynomials with all positive coefficients whose sum is less than or equal to one by mathematically analyzing the joint probability distribution of coefficient bit-streams. The NAND-AND expansion is also developed for polynomials with alternatively positive and negative coefficients whose absolute values are decreasing by applying the same idea. Unlike the original methods with multiple uncorrelated random number sources (RNSs) for coefficient bit-stream generation, the presented methods only require a single RNS. Since the RNSs take up huge hardware resource in stochastic circuits, the proposed RNS-sharing techniques for polynomial computation result in a significant reduction of hardware complexity. For the factorization technique in the general polynomials, this paper enhances the original stochastic designs for the second-order polynomial and further presents the simple correlation-dependent circuits. Results show that the proposed architectures are superior to the previous ones by reducing the total number of RNSs. [ABSTRACT FROM AUTHOR]

Rapid development in the area of information and embedded technology, mobile communication networks, IoT multimedia applications, compression, and distribution over Internet has led to a significant need to answer the question: "How to protect, secure, and authenticate multimedia documents?" One of the proposed responses to this challenge is digital watermarking, which hides an inaudible watermark in digital multimedia content. Despite the large number of proposed competent watermarking algorithms in the literature, few are suitable for the compression domain, mainly the authentication application. In this context, this paper depicts a new MP3 audio watermarking scheme for copyright protection and content integrity checking operating directly in the compression domain using Huffman data and side information features. This scheme overcomes the problem of computational time as it operates directly on the compressed bitstream. In addition, it provides enough embedding space by using Huffman data features. A strong advantage of our scheme is that it has been used successfully for both authentication and copyright protection applications. Experimental results have revealed that the proposed watermarking schema has achieved very competitive results compared to others from the literature in terms of inaudibility, robustness, and especially capacity ratio. Our approach offers also good values of ODG and NC even after double recompression-StirMark attacks. [ABSTRACT FROM AUTHOR]

Weak grid scenarios and low-inertia systems are emerging issues in power systems, which could lead to voltage and frequency instabilities. Synchronous Condensers (SynCons) have recently drawn renewed attention as a promising solution to provide system strength and inertia support. Even though the exciter control of SynCons is a well-established technology, further developments are required to guarantee the stability of post-fault operations, in particular, in weak grids. This paper proposes a data-driven approach for designing higher-order optimized exciter controllers to meet this requirement. A pseudo-random binary sequence (PRBS)-based system identification method is used to obtain frequency response data of the power system, from the exciter point of view, which is then fed into the proposed optimal control design procedure. The proposed exciter controller is tested for voltage ride-through and fault scenarios in a single machine infinite bus (SMIB) case and the IEEE 39-bus test system to assess its performance compared to the conventional AC1A exciter controller. The results obtained through simulation tests carried out using the PSCAD/EMTDC software verify that the proposed exciter controller guarantees the post-fault stability in both strong and weak grids. [ABSTRACT FROM AUTHOR]

With the development of the Internet of Things and devices continuing to scale, using cloud computing resources to process data in real-time is challenging. Edge computing technologies can improve real-time performance in processing data. By introducing the FPGA into the computing node and using the dynamic reconfigurability of the FPGA, the FPGA-based edge node can increase the edge node capability. In this paper, a task-based collaborative method for an FPGA-based edge computing system is proposed in order to meet the collaboration among FPGA-based edge nodes, edge nodes, and the cloud. The modeling of the task includes two parts, task information and task-dependent file. Task information is used to describe the running information and dependency information required for the task execution. Task-dependent file contains the configuration bit-stream of FPGA in running of the task. By analyzing the task behavior, this paper builds four basic behaviors, analyzes the critical attributes of each behavior, and summarizes the task model suitable for FPGA-based edge nodes. Tasks with specific functions can be created by modifying different attributes of model nodes. Finally, the availability of the model and the task-based collaborative method are verified by simulation experiments. The experimental results that the task model proposed in this paper can meet cloud-edge collaboration in the FPGA-based edge computing environment. [ABSTRACT FROM AUTHOR]

This paper presents a study on the use of encoder‐derived features in decoder‐side depth estimation. The scheme of multiview video encoding does not require the transmission of depth maps (which carry the geometry of a three‐dimensional scene) as only a set of input views and their parameters are compressed and packed into the bitstream, with a set of features that could make it easier to estimate geometry in the decoder. The paper proposes novel recursive block splitting for the feature extraction process and evaluates different scenarios of feature‐driven decoder‐side depth estimation, performed by assessing their influence on the bitrate of metadata, quality of the reconstructed video, and time of depth estimation. As efficient encoding of multiview sequences became one of the main scopes of the video encoding community, the experimental results are based on the "geometry absent" profile from the incoming MPEG Immersive video standard. The results show that the quality of synthesized views using the proposed recursive block splitting outperforms that of the state‐of‐the‐art approach. [ABSTRACT FROM AUTHOR]

Dq impedance measurement is of great importance as a part of the impedance-based analysis. At present, impedance of objects in single-phase vehicle-grid system are mainly obtained by injecting the voltage or current disturbance of one single frequency into the system circularly. However, as the number of measurement frequency points increases, there will produce much time-consuming of measurement. In this paper, a quick dq impedance measurement algorithm for single-phase vehicle-grid system based on multi-frequency sweep is proposed. First, pseudo-random binary sequences (PRBS) and ternary sequences are modified as the driving signals rather than directly injecting into the control link. Then three types of disturbance with specific frequency characteristics are introduced into the system and their parameters setting principle are given for the first time. According to the different characteristics of measurement objects, the proposed algorithms are also different to ensure the maximum specificity and sensitivity. Finally, for different objects in vehicle-grid system like traction network, single-phase converter and dual-interleaved converter, simulation and experimental results based on the hardware in the loop real-time simulation platform both show the correctness of the proposed algorithm, and the possible causes of errors are also analyzed in detail. Moreover, the proposed algorithm makes it possible to quickly measure the dq impedance of the single-phase vehicle-grid system, and the correctness of the theoretical and measured value can be judged and used for the stability analysis of electrical systems. [ABSTRACT FROM AUTHOR]

Qinghai-Tibet Plateau has a special geographical location and large lake groups making it an important research subject of global climate change and regional response. Taking its 149 typical lakes as the research subject, using the relevant features of lake area data from 1985 to 2020, the variation of the lake area, the chronological division of climate change, and the impact of climate features on the lake area growth rate are analyzed. The main methods and results include the following: (1) By using the time series clustering algorithm to mine the shape similarity of lake area change, three patterns of area change, C1, C2 and C3 modes, which show a slow growth trend, a strong fluctuation, and a significant growth trend, respectively, are summarized. (2) When the optimal segmentation point index of the binary sequence is proposed and combined with the clustering results of the lake regional climate to find the year of the optimal segmentation point for all lakes, the regional climate segmentation points of lakes are concentrated from 1995 to 2005. (3) When researching the lakes in C3 mode, using the XGBoost model as the regression model to extract the feature importance affecting lake growth rate, the effect of precipitation on lake area is the highest, followed by surface temperature. When a double machine learning model is established to conduct causal analysis to obtain an unbiased estimation of the lake area growth rate influenced climate features, the effect of precipitation is the highest, followed by evaporation. The methods used and the results show a new perspective in understanding climate change and lake response. [ABSTRACT FROM AUTHOR]

Flat-topped one-dimensional maps have been used in the control of chaos in one-dimensional dynamical systems. In these applications, this mechanism is known as simple limiter control. In this paper, we will consider the introduction of simple limiters u in the tent map, according to a time-dependent scheme defined by a binary sequence s, the iteration pattern. We will define local and Milnor attractors in this non-autonomous context and study the dependence of their existence and coexistence on the value of the limiter u and on the pattern s. Using symbolic dynamics, we will be able to characterize the families of pairs (u , s) for which these attractors exist and coexist, as well as fully describe them. We will observe that this non-autonomous context provides a richness of behaviors that are not possible in the autonomous case. [ABSTRACT FROM AUTHOR]

Several studies deal with the development of advanced statistical methods for predicting football match results. These predictions are then used to construct profitable betting strategies. Even if the most popular bets are based on whether one expects that a team will win, lose, or draw in the next game, nowadays a variety of other outcomes are available for betting purposes. While some of these events are binary in nature (e.g. the red cards occurrence), others can be seen as binary outcomes. In this paper we propose a simple framework, based on score-driven models, able to obtain accurate forecasts for binary outcomes in soccer matches. To show the usefulness of the proposed statistical approach, two experiments to the English Premier League and to the Italian Serie A are provided for predicting red cards occurrence, Under/Over and Goal/No Goal events. [ABSTRACT FROM AUTHOR]