Binary Digits Research Articles

Optimal Design for Modulated Binary Sensors

A paramount factor limiting the applications of binary sensors is these senors’ on-off property outputting binary digits of “0” or “1”. To overcome this limitation, modulators or obscurants are added to enhance the sensing ability of binary sensors and render them usable in applications such as multi-target tracking and human activity recognition. Obscurants segment the field of interest into subregions and distinguish each subregion by a list of sensor states called signatures. This paper studies two placement scenarios in a two-dimensional planar graph. In the first scenario, we prove upper and lower bounds on the maximum number of achievable signatures. In the second scenario, starting from the placement of sensors and obscurants in which the maximum number of signatures is achievable, we propose a novel mathematical model based on four main metrics: the object space size, the sensor space size, the obscurant space size, and the sizes of individual obscurants. We find the minimum and maximum radiuses that bound the object detection area given the number and sizes of sensors and obscurants. We derive the obscurant space size as a function of the object space size and the size of individual obscurants. We also provide a linear relationship formula between the obscurant space radius, the sensor space radius, and the obscurants’ radiuses and conduct modeling experiments to study the relationship between these metrics. Finally, we deduct an explicit formula for the maximum obscurant space size for the sensor space and the individual obscurant sizes.

DMAV: Enhanced MAV Link Protocol Using Dynamic DNA Coding for Unmanned Aerial Vehicles

In the modern era, new and innovative ways of securing data and communications are continuously developing. One such recent development is using the concept of DNA as a means of data encryption. In this work, we propose a new approach to encrypt data and communications on the MAVLink protocol for unmanned aerial vehicles (UAVs) using a lightweight GIFT algorithm and dynamic DNA coding (with binary bits). MAVLink is a communication protocol for UAVs, which is currently unencrypted and can easily be intercepted by anyone. As such, a secure MAVLink protocol has long been needed in the UAV industry. We describe a novel secure communication protocol for UAVs using dynamic DNA coding to encrypt MAVLink packets, which we call DMAV. Experimental results show that this novel means of securing the MAVLink protocol performs better than the traditional method (i.e., using public and private key cryptography). Therefore, the proposed approach could potentially change the way secure communications are conducted between UAVs in the future.

Using the discovery of fundamental variables by artificial intelligence to unite general relativity and quantum mechanics

Article includes “Linking radioactive dating to origin of the universe” or “How dinosaurs committed scientific heresy & exterminated the Big Bang” Vector-tensor-scalar geometry’s important insights into 1) Cancer, 2) The origin of the moon In a newsletter discussing “Automated discovery of fundamental variables hidden in experimental data” (Chen, B., Huang, K., Raghupathi, S. et al. Automated discovery of fundamental variables hidden in experimental data. Nat Comput Sci 2, 433–442 (2022). Cosmos Magazine attributed the following statement to co-author Qiang Du, “What other laws are we missing simply because we don’t have the variables?” According to Cosmos, another co-author (Hod Lipson) argues that scientists may be misinterpreting or failing to understand many phenomena simply because they don’t have a good set of variables. All of this reminds me of the Hidden Variables associated with Albert Einstein’s doubts about quantum mechanics. I’ve been thinking about hidden variables for perhaps twenty or more years and it seems that their combination with the Mobius strip, figure-8 Klein bottle, base 2 mathematics, vector-tensor-scalar geometry, and Wick rotation might unite quantum mechanics and relativity. The union would result in explanation of particles existing in two or more places at once being due to our frame of reference. It would also explain wave-particle duality and, on a universal scale, why there was no Big Bang. The section on vector-tensor-scalar geometry is very important since it provides insights into 1) cancer, and 2) the origin of the moon. The yet-to-be-discovered underlying physics of the wave function proposed in this comment predicts exactness in outcomes, not probability or randomness. Quantum mechanics says particles can, according to our frame of reference, be in two or more places at once. This frame of reference is necessarily restricted to our present understanding of quantum mechanics which Albert Einstein and his colleagues claimed to be incomplete. Hidden Variables are presently hypothetical factors based on the belief that the theory of quantum mechanics is incomplete. Their identification would lead to exact predictions, not just probabilities, for the outcomes of measurements. Albert Einstein is the most famous proponent of hidden variables. Their existence would vindicate his belief that quantum mechanics is lacking something. It’s proposed here that electronics’ binary digits (1’s and 0’s) are those hidden variables. Despite Bell’s theorem and the more recent Pusey–Barrett–Rudolph theorem, hidden variables can be a valid theory since the following boxed explanation of unification of all time periods allows the existence of both “retarded” waves going forwards in time and the disfavoured “advanced” waves travelling back in time and this permits quantum entanglement of every form of mass if, as shown, gravitational waves interacting with electromagnetic waves is responsible for production of mass. The misperception that the universe is expanding is accounted for by retarded/advanced shift.

A Method for Reducing the Register Effect for Modular Data Formats

The substantiation of the author's method of reducing redundancy from the register effect when placing the components of a tuple representing a numerical value in a modular format designed for storage, transmission and processing in modular arithmetic in a specialized SIMD processor of parallel structure is given. Modular coding allows to obtain parallel execution of ring operations in independent computing paths. This, according to Amdahl's law, accelerates the execution of the computational process on multiprocessor computing systems or on multiple cores. Modular data formats are not consistent with the binary bit grid of a multiprocessor computer. In homogeneous binary registers designed to display modulo deductions, redundancy occurs because not all possible binary combinations in a digital register are used to display data. The method is based on the redistribution of the redundancy of digital registers used to display the components of the modular tuple, which allows to reduce to zero the register effect and redundancy of the representation of the components of the tuple. This makes it possible to obtain a dense packing of components of vector modular formats in homogeneous digital registers, which makes the development of SIMD architecture computers processing data in computer modular formats promising. The simulation results allow us to obtain mutually simple bases of the modular number system that meet the conditions of a new patented method for the complete elimination of redundancy.

STeP-CiM: Strain-Enabled Ternary Precision Computation-In-Memory Based on Non-Volatile 2D Piezoelectric Transistors

We proposed 2D piezoelectric FET (PeFET)–based compute-enabled non-volatile memory for ternary deep neural networks (DNNs). PeFETs hinge on ferroelectricity for bit storage and piezoelectricity for bit sensing, exhibiting inherently amenable features for computation-in-memory of dot products of weights and inputs in the signed ternary regime. PeFETs consist of a material with ferroelectric and piezoelectric properties coupled with a transition metal dichalcogenide channel. We utilized (a) ferroelectricity to store binary bits (0/1) in the form of polarization (−P/+P) and (b) polarization-dependent piezoelectricity to read the stored state by means of strain-induced bandgap change in the transition metal dichalcogenide channel. The unique read mechanism of PeFETs enables us to expand the traditional association of +P (−P) with low (high) resistance states to their dual high (low) resistance depending on read voltage. Specifically, we demonstrated that +P (−P) stored in PeFETs can be dynamically configured in (a) a low (high) resistance state for positive read voltages and (b) their dual high (low) resistance states for negative read voltages, without afflicting a read disturb. Such a feature, which we named as polarization-preserved piezoelectric effect reversal with dual voltage polarity (PiER), is unique to PeFETs and has not been shown in hitherto explored memories. We leveraged PiER to propose a Strain-enabled Ternary Precision Computation-in-Memory (STeP-CiM) cell with capabilities of computing the scalar product of the stored weight and input, both of which are represented with signed ternary precision. Furthermore, using multi-word line assertion of STeP-CiM cells, we achieved massively parallel computation of dot products of signed ternary inputs and weights. Our array-level analysis showed 91% lower delay and improvements of 15% and 91% in energy for in-memory multiply-and-accumulate operations compared to near-memory design approaches based on 2D FET–based SRAM and PeFET, respectively. We also analyzed the system-level implications of STeP-CiM by deploying it in a ternary DNN accelerator. STeP-CiM exhibits 6.11× to 8.91× average improvement in performance and 3.2× average improvement in energy over SRAM-based near-memory design. We also compared STeP-CiM to near-memory design based on PeFETs showing 5.67× to 6.13× average performance improvement and 6.07× average energy savings.

Low-profile dual-band pixelated defected ground antenna for multistandard IoT devices

A low-profile dual-band pixelated defected ground antenna has been proposed at 3.5 GHz and 5.8 GHz bands. This work presents a flexible design guide for achieving single-band and dual-band antenna using pixelated defected ground (PDG). The unique pixelated defected ground has been designed using the binary particle swarm optimization (BPSO) algorithm. Computer Simulation Technology Microwave Studio incorporated with Matlab has been utilized in the antenna design process. The PDG configuration provides freedom of exploration to achieve the desired antenna performance. Compact antenna design can be achieved by making the best use of designated design space on the defected ground (DG) plane. Further, a V-shaped transfer function based on BPSO with fast convergence allows us to efficiently implement the PDG technique. In the design procedure, pixelization is applied to a small rectangular region of the ground plane. The square pixels on the designated defected ground area of the antenna have been formed using a binary bit string, consisting of 512 bits taken during each iteration of the algorithm. The PDG method is concerned with the shape of the DG and does not rely on the geometrical dimension analysis used in traditional defected ground antennas. Initially, three single band antennas have been designed at 3.5 GHz, 5.2 GHz and 5.8 GHz using PDG technique. Finally, same PDG area has been used to design a dual-band antenna at 3.5 GHz and 5.8 GHz. The proposed antenna exhibits almost omnidirectional radiation performance with nearly 90% efficiency. It also shows dual radiation pattern property with similar patterns having different polarizations at each operational band. The antenna is fabricated on a ROGERS RO4003 substrate with 1.52 mm thickness. Reflection coefficient and radiation patterns are measured to validate its performance. The simulated and measured results of the antenna are closely correlated. The proposed antenna is suitable for different applications in Internet of Things.

The Code Breaker: Jennifer Doudna, Gene Editing, and the Future of the Human Race

The Code Breaker: Jennifer Doudna, Gene Editing, and the Future of the Human Race

Molecular-Scale Hardware Encryption Using Tunable Self-Assembled Nanoelectronic Networks

Nanomaterials are promising alternatives for creating hardware security primitives that are considered more robust and less susceptible to physical attacks compared to standard CMOS-based approaches. Here, nanoscale electronic circuits composed of tunable ratios of molecules and colloidal nanoparticles formed via self-assembly on silicon wafers are investigated for information and hardware security by utilizing device-level physical variations induced during fabrication. Two-terminal electronic transport measurements show variations in current through different parts of the nanoscale network, which are used to define electronic physically unclonable functions. By comparing different current paths, arrays of binary bits are generated that can be used as encryption keys. Evaluation of the keys using Hamming inter-distance values indicates that performance is improved by varying the ratio of molecules to nanoparticles in the network, which demonstrates self-assembly as a potential path toward implementing molecular-scale hardware security primitives. These nanoelectronic networks thus combine facile fabrication with a large variety of possible network building blocks, enabling their utilization for hardware security with additional degrees of freedom that is difficult to achieve using conventional systems.

Point focusing wireless communication: A diffraction limit communication paradigm

A wireless communication scheme named point focusing (PF) wireless communication is proposed for intra-spacecraft wireless transmission. In this scheme, a set of point focusing fields (PFFs) generated by the time reversal (TR) based field shaping method are employed to carry the binary bits. Based on the orthogonality of the non-overlapped focal points of the PFFs, the same spectrum can be spatially reused. The point-to-point spacing between PFFs is half a wavelength, that is, a distance at Rayleigh diffraction limit, which can maximize the spectrum reutilization efficiency in a bounded spatial region. A closed metal cavity is employed to numerically and experimentally demonstrate the performance of the PFFs based wireless communications.

Retraction Note to: A secure medical image transmission algorithm based on binary bits and Arnold map

Retraction Note to: A secure medical image transmission algorithm based on binary bits and Arnold map

Spatial Grid-Based Position Calculation Method for Satellite-Ground Communication Links

With the rapid development of global satellite constellation clusters and the popularity of ground-based intelligent terminals, the interconnection between large-scale low Earth orbit satellites and ground base stations has become more frequent. The calculation of satellite position requires a large number of floating point square calculations and coordinate system conversions, with high computational complexity and long computation time. Based on the grid encoding method of GeoSOT, we propose a GeoSOT-based grid calculation for a satellite-ground position (GCSGP) model. We use binary bit operations instead of complex topological operations and floating point calculations, and use grid distance calculations instead of existing angle calculations. Thus, the relative positions of satellites to the ground can be quickly calculated and thus connected to more suitable satellites quickly. The results of the grid calculation were verified by simulation experiments. The calculation speed was improved by about 82% compared with the traditional method. The test accuracy error of the 10-level grid at a terminal 45° inclination was less than 1% at all heights, and the maximum error of the 10-level grid within a 10–45° inclination was 7.2% at 10,000 km altitude, which provides theoretical support for the subsequent grid space calculation.

Spatial Domain-based Face Recognition using MSB, and MLTP with ANN Classifier

The human face images are an essential biometric trait in the authentication of individuals as the face images can be taken without the knowledge and physical contact of the person leading to several recent applications. We propose Spatial Domain-based Face Recognition using MSB and MLTP with ANN Classifier in this paper. The benchmarked face datasets are considered for testing the proposed method by converting color images into greyscale images and uniform image sizes. The 8-bit binary of each pixel is segmented into two groups viz., Most Significant Bits (MSB) and Least Significant Bits (LSB). The important information is available only in MSBs than LSBs hence MSBs are considered for feature extraction leading to compression of binary bits. The MSB four bits are converted to decimal values, and Histogram Equalization (HE) is used to enhance the contrast level of images and resize them. The Modified Local Ternary Pattern (MLTP) is applied to an image to extract compelling features. The Artificial Neural Network (ANN) classifies face images to recognize human beings. It is noticed that the proposed method's recognition results are better than the existing techniques. Keywords: Artificial Neural Network (ANN), Biometrics, Face Recognition, Histogram Equalization, MSB, MLTP.

A Novel Hybrid Modulation Scheme for Molecular Communication: Performance Analysis

A molecular communication (MC) system as compared to the traditional communication system differs in terms of signalling and the medium of communication. Design and selection of modulation scheme is one of the important aspect in realisation of a reliable communication system. In this letter, we propose a novel binary bit addition modulation scheme for diffusion based MC system which utilizes the simple binary addition principle and reduces the effective number of molecules which are released from the transmitter. We study the performance analysis in terms of the bit error rate (BER) and derive the closed-form expressions for the probabilities of symbol detection. We compare the proposed modulation scheme with the binary concentration shift keying scheme and show that the proposed scheme has a lower BER and the gap in the BER increases as the number of molecules increases showing the effectiveness when the number of transmitted molecules is large. Furthermore, through extensive simulation results, we show the performance of the proposed modulation scheme for the diffusion based MC system.

A Coverless Text Steganography by Encoding the Chinese Characters' Component Structures

The current coverless text steganography methods have a low steganographic capacity, and yet some of them cannot assure a message can be concealed. How to achieve a high steganographic capacity has become the research hotspot in text steganography. This paper proposes a text coverless steganography method by encoding the Chinese characters’ component structures. Its main idea is that a binary bit string can be conveyed by the Chinese characters’ component structures. The positions of Chinese characters that carry a secret message will be expressed in two systems of the linear remainder equations, whose solutions will be secretly sent to the receiver to extract the secret message. In the method, a single Chinese character can express p bits. The analyses and statistics show that its capacity will be much higher when the same Chinese character is used more than once than existing methods, and it can conceal any message successfully. In addition, this method can also be employed in other languages.

A Proposed Method for Synthesizing the Radiation Pattern of Linear Antenna Arrays

The design of antenna arrays is one of the most challenging optimization problems in recent research interests. In this research work a new method of optimization proposed. This method called “Characteristics Evolution Optimization” is based on parallel processing of streams of binary digits, and hence it can perform well in parallel processing digital systems. In this article, a 16 - element linear antenna array has been taken into consideration, and the performance of the proposed technique for synthesizing the radiation pattern of the array has been investigated and compared with other existing techniques, such as DE (Differential Evolution), IWO (Invasive Weed Optimization), and PSO (Particle Swarm Optimization). Various variants of Invasive Weed Optimization have been investigated as well. It has been observed that the proposed method (Characteristics Evolution optimization) outperforms the other optimization techniques significantly in different aspects.

Encoding–decoding strategy based resilient state estimation for bias-corrupted stochastic nonlinear systems

This paper is concerned with the resilient state estimation problem for a type of stochastic nonlinear systems, in which the possible dynamical bias is considered that is depicted by a dynamical equation. In pursuit of enhancing the robustness of the propagated data, a binary encoding strategy (BES) is exploited in the binary symmetric channel (BSC). While the random bit errors caused by the channel noise may take place during the propagation of the binary bit string via the memoryless BSC. To characterize the occurrence of the bit errors, a series of Bernoulli distributed random variables is adopted. More specifically, in order to deal with the possible gain fluctuation of the estimator in the execution process, a resilient state estimator is employed. This paper intends to put forward a novel resilient estimation scheme under the BES, which can assure that the estimation error dynamics is exponentially ultimately bounded in mean square. A sufficient criterion is first acquired for the existence of the expected resilient estimator and the estimator parameter is achieved by solving a convex optimization problem. Finally, an illustrative simulation example is provided to verify the validity of the theoretical results.

Design of electro-optic Mach–Zehnder interferometer based all-optical binary half adder and half subtractor

By exploiting the phenomena of optical switching, different logical and arithmetic operations can be performed. This paper presents a novel optimized design structures to perform addition and subtraction of two binary digits using electro-optic effect based Mach–Zehnder interferometer operating at 1460 nm in the S band. The proposed structures are numerically simulated and designed using beam propagation method and MATLAB software. The different performance parameters like extinction ratio, contrast ratio, insertion loss, amplitude modulation and relative eye opening have been evaluated and the optimized structure yields maximum ER of 33.22 dB and 28.76 dB for half adder and half subtractor respectively. Additionally, a comparison of the proposed structures is presented with the previously designed structures.

Kirigami interactive triboelectric mechanologic

Mechanical logic and computation embedded in deployable structures are complementary to conventional digital logic schemes for autonomous sense, decision, and response in artificial intelligence and bio-robots. It is highly desired that responsive and adaptive structures can readily interact with external stimuli to implement mechanologic (e.g., writing, erasing, and rewriting mechanical bit) in an energy-efficient way. Here, we demonstrate kirigami interactive triboelectric mechanologic composed of a deployable kirigami geometry triggered by triboelectric signal for the first time, aiming at developing interactive and programmable mechanical computation. The interactive triboelectric mechanologic is inspired by human somatic reflex arc system to emulate the continual sensation–decision–response loop, which includes a self-powered triboelectric nanogenerator (TENG) mechanoreceptor, a signal transmission/processing module, and an elaborately designed kirigami geometry with bistable resistive states to represent mechanologic. When the mechanoreceptor is imposed to mechanical stimuli, the induced triboelectric signals activate the bistable state conversion in the kirigami geometry and endow it with adaptive capacity to output binary mechanical bits. We successfully demonstrate the application of interactive triboelectric mechanologic as a mechanical flip-flop, register, and asynchronous binary counter. This work provides a new route to self-activation mechanologic computation relying on the extended application of TENG for self-driven sensing and actuation.

Improving the Accuracy of Ensemble Machine Learning Classification Models Using a Novel Bit-Fusion Algorithm for Healthcare AI Systems.

Healthcare AI systems exclusively employ classification models for disease detection. However, with the recent research advances into this arena, it has been observed that single classification models have achieved limited accuracy in some cases. Employing fusion of multiple classifiers outputs into a single classification framework has been instrumental in achieving greater accuracy and performing automated big data analysis. The article proposes a bit fusion ensemble algorithm that minimizes the classification error rate and has been tested on various datasets. Five diversified base classifiers k- nearest neighbor (KNN), Support Vector Machine (SVM), Multi-Layer Perceptron (MLP), Decision Tree (D.T.), and Naïve Bayesian Classifier (N.B.), are used in the implementation model. Bit fusion algorithm works on the individual input from the classifiers. Decision vectors of the base classifier are weighted transformed into binary bits by comparing with high-reliability threshold parameters. The output of each base classifier is considered as soft class vectors (CV). These vectors are weighted, transformed and compared with a high threshold value of initialized δ = 0.9 for reliability. Binary patterns are extracted, and the model is trained and tested again. The standard fusion approach and proposed bit fusion algorithm have been compared by average error rate. The error rate of the Bit-fusion algorithm has been observed with the values 5.97, 12.6, 4.64, 0, 0, 27.28 for Leukemia, Breast cancer, Lung Cancer, Hepatitis, Lymphoma, Embryonal Tumors, respectively. The model is trained and tested over datasets from UCI, UEA, and UCR repositories as well which also have shown reduction in the error rates.

A Fibonacci type sequence with Prouhet–Thue–Morse coefficients

Let , where is the sum of binary digits function. The sequence is the well-known Prouhet–Thue–Morse sequence. In this note we study the sequence , where and for we define recursively as follows: . We prove several results concerning arithmetic properties of the sequence . In particular, we prove non-vanishing of for , automaticity of the sequence for each m, and other results.