Speech Signal Security Scheme Based on Multiple Chaotic Maps with Deoxyribonucleic Acid Coding Algorithm

This article presents a novel speech cryptosystem by using chaotic maps and Deoxyribonucleic Acid coding. Initially, the speech signal is divided into four equal blocks. Then the speech samples in each block are submitted to confusion/diffusion via four different chaotic maps. The gained ciphered speech samples and the obtained chaotic sequence from Sine map are encoded via DNA rules. The consequent coded sequences from the previous step are merged via DNA/XNOR to get the coded DNA signal. Ultimately, the resulted signal is decoded to acquire the definitive ciphered signal. The experiments prove the efficiency and robustness of the suggested method

Analysis and measurements of the characteristics of fading in the DAB+ single-frequency network

In this article the measurement results and their comparison with simulation results will be shown. The obtained measurement results prove for the first time in the technical literature the real occurrence of many selective fading in the DAB + signal band. The high compliance of the measurement results of the fade characteristics with the simulation results, which were also presented in the article, indicates the possibility of predicting the areas and characteristics of fades on the basis of simulation tests. Thus, on their basis, it will be possible to determine the places where this phenomenon occurs and take it into account in the process of planning the SFN network. &nbsp

Enhancing Research Practices: Digital Technologies in the Social Sciences and Practical Tools for Doctoral Students

The paper is a result of a complementary advanced publication workshop accompanying the curriculum course exercises for PhD students, on the role of ICT in the research work of a scientist. This article discusses the impact of digital technologies on research practices in the social sciences, focusing on tools supporting qualitative data analysis, interview transcription, and knowledge management. It presents a detailed analysis of CAQDAS programs such as NVivo, MAXQDA, and ATLAS.ti, and transcription tools such as Trankriptor and Word. It also discusses the use of the digital Zettelkasten system in knowledge management and academic writing. The article highlights the benefits and challenges of integrating these technologies, offering practical advice for doctoral students

A Systematic Review of Effective Data Augmentation in Cervical Cancer Detection

The rapid progress of AI has made computer-assisted systems essential in medical fields like cervical cytology analysis. Deep learning requires large datasets, but data scarcity and privacy concerns pose challenges. Data augmentation addresses this by generating additional images and improving model accuracy and generalizability. This review examines effective augmentation techniques and top-performing deep-learning models for segmentation and classification in cervical cancer detection. Analyzing 57 articles, we found that hybrid deep feature fusion with augmentation (rotation, flipping, shifting, brightness adjustments) achieved 99.8% accuracy in binary and 99.1% in multiclass classification. Augmentation is vital for enhancing model performance in limited data scenarios

Identifying Three-Dimensional Palmprints With Modified Four-Patch Local Binary Pattern (MFPLBP)

Palmprint biometrics is the best method of identifying an individual with a unique palmprint for every person.The present paper formulates a new methodology towardsthe identification of 3D palmprints using the Modified FourPatch Local Binary Pattern (MFPLBP). It improves upon theconventional Four-Patch Local Binary Pattern (FPLBP) by integrating the adaptive weight with the improved texture extraction.Both approaches are created to support the intricate surfaceinformation of 3D palmprints. The MFPLBP can exactly capturelocal variations and is noise and illumination invariant. Thereare extensive experiments done in this paper and establish thatMFPLBP outperforms traditional LBP methods and other stateof-the-art methods in recognition rates. The experiments establishthat MFPLBP is a efficient and effective method of making useof 3D palmprints in real-world biometric verificatio

Deep Learning in Motion Analysis for False Start Detection in Speedway Racing

Accurately identifying false starts in speedway racing is a very challenging task due to the subtle nature of pre-start movements. Manual detection methods, often dependent on the judgment of race officials, are prone to errors and subjectivity, leading to inconsistencies in decision-making. This paper introduces an automated approach that leverages computer vision methods to enhance detection precision. Here, we have expanded its use to detect false starts in speedway racing. The proposed approach introduces image processing techniques with 3D Convolutional Neural Networks (CNNs) and Long-Short-Term Memory (LSTM) networks to analyze rider movements during the starting procedure. Unlike manual detection, which often misses fine movements at the start line, our method uses 3D CNNs to monitor racer movements and applies LSTM networks to assess time-based motion patterns that signal false starts. The presented results show that the 3D CNN achieved an accuracy of 86.36% with a higher precision when compared to traditional methods. This automated process not only enhances fairness in competitive racing, but also illustrates the broader capability of emerging technologies to refine decision-making in sports

Quantum-safe Forward Secure Password Authenticated Key Life-cycle Management Scheme with Key Update Mechanism

In this paper we construct and consider a new password authenticated key life-cycle management scheme (PAKMS) with key update mechanism, which uses random q-ary lattices as its domain. We justify that the scheme is existentially forward unforgeable under a chosen password attack (fu-cpwda). To this end, we show that breaking this scheme let us to construct a polynomial-time adversary that is able to solve small integer solution (SIS) problem. Since the security of the scheme is based on computational hardness of SIS problem, it tuns out to be resistant to both classical and quantum computations. The key-updating mechanism is based on some properties of binary trees, with a number of leaves being the same as a number of time periods in the scheme. The forward-security is gained under the assumption that one out of two hash functions is modeled as a random oracl

Design of Ultra Compact Optical T Flip Flop in Two Dimensional Photonic Crystals

The research in the field of quantum electronics is gaining more momentum over the solid state physics device design. In the proposed research we have designed an ultra compact optical T flip-flop in two dimensional (2-D) photonic crystals (PhCs) on a rectangular lattice with 16 x 9 dielectric rods in air configuration. The principle mechanism used here is adding an extra input called reference input to achieve logic high for no power applied at the input of T flip-flop. The two junctions are created for guiding the light wave towards the output. The reference input and one refractive index varied dielectric rod placed near the junction to confine the output power along with T input. At the junction of the input-output we have used the constructive and destructive interference method to achieve maximum light confinement in the output. The plane wave expansion (PWE) method is used to compute the photonic band gap (PBG) and the finite difference time domain (FDTD) method is used to analyze electromagnetic (EM) wave propagation inside the waveguides. The time for input arrival at the output also significantly improved with reduction in the chip size. The response time for the proposed T flip-flop is 0.0049 ps and contrast ratio achieved is 13.60 dB with a chip area of 49.5µm2

Digital Image Encryption with Validation by ECC and Embedding at Low-Frequency Region Using Genetic Approach

In the current internet era, the security of digital images has become increasingly important due to their numerous applications and uses. Although many researchers have proposed end-to-end security and authenticity against various attacks, achieving security, validation, and robustness together has been a challenge. This paper proposes a model called Low-Frequency Embedding and Elliptical Curve Cryptography (LFE-ECC), which provides all the necessary requirements for image security.The proposed model achieves image validation for the authentic sender by embedding a secret signature in the low-frequency region of the image. The robustness of the image is achieved by embedding a secret signature at a selected coefficient of the DWT feature. The moth flame optimization genetic algorithm is used for coefficient selection, and the additional security of embedded images is achieved using the elliptical curve cryptography technique. ECC provides encryption and validation for both parties.An experiment is conducted on real and artificial datasets under ideal and attack environments, and the results demonstrate the improved performance of the proposed LFE-ECC model against a range of attacks

DTMOS Based Bandgap Reference Design in CMOS 28nm Process

This paper describes design and simulation results of the bandgap reference source in CMOS 28nm technology. Proposed bandgap reference utilizes DTMOS transistors for providing currents of negative and positive temperature coefficients and is equipped with various techniques for process variation minimization such as common centroid element design and user controlled trimming resistors. This circuit achieves temperature coefficient equal to -18.87 ppm/(°C) with temperature ranging from -20°C to 100°C at 1V power supply, occupies 0.38 mm2 of silicon area, and consumes 3.66  µW of power