Search Results (277)

This study proposes an optimized approach to address the high computational demands and significant GPU memory consumption commonly associated with Transformer-based models. Building upon the HAT framework, a shallow feature extraction module is enhanced to improve local feature representation, thereby achieving a better balance between computational efficiency and model performance. Furthermore, inspired by self-supervised learning (SSL) techniques and incorporating shift operations, the proposed method effectively reduces both the number of parameters and the overall computational load. The resulting ISR-SHA model is trained and evaluated on the DF2K dataset, achieving approximately a 30% reduction in FLOPs and parameter count compared to the original HAT model, with only marginal declines in PSNR (0.02) and SSIM (0.0006). Experimental results confirm that ISR-SHA outperforms most existing super-resolution models in terms of performance while significantly enhancing computational efficiency without compromising output quality. Full article

With the development of a quantum computer in the near future, classical public-key cryptography will face the challenge of being vulnerable to quantum algorithms, such as Shor’s algorithm. As communication technology advances rapidly, a great deal of personal information is being transmitted over the Internet. Based on our observation that the Kyber algorithm exhibits a significant number of idle cycles during execution when implemented following the conventional software procedure, this paper proposes a high-throughput scheduling for Kyber by parallelizing the SHA-3 function, the sampling algorithm, and the NTT computations to improve hardware utilization and reduce latency. We also introduce the 8-stage pipelined SHA-3 architecture and multi-mode polynomial arithmetic module to increase area efficiency. By also optimizing the hardware architecture of the various computational modules used by Kyber, according to the implementation result, an aggregate throughput of 877.192 kOPS in Kyber KEM can be achieved on TSMC 40 nm. In addition, our design not only achieves the highest throughput among existing studies but also improves the area and power efficiencies. Full article

Digital images have been widely applied in fields such as mobile devices, the Internet of Things, and medical imaging. Although significant progress has been made in image encryption technology, it still faces many challenges, such as attackers using powerful computing resources and advanced algorithms to crack encryption systems. To address these challenges, this paper proposes a novel image encryption algorithm based on one-dimensional sawtooth wave chaotic system (1D-SAW) and the three-strand structure of DNA. Firstly, a new 1D-SAW chaotic system was designed. By introducing nonlinear terms and periodic disturbances, this system is capable of generating chaotic sequences with high randomness and initial value sensitivity. Secondly, a new diffusion rule based on the three-strand structure of DNA is proposed. Compared with the traditional DNA encoding and XOR operation, this rule further enhances the complexity and anti-attack ability of the encryption process. Finally, the security and randomness of the 1D-SAW and image encryption algorithms were verified through various tests. Results show that this method exhibits better performance in resisting statistical attacks and differential attacks. Full article

Rainbow table attacks utilize a time-memory trade-off to efficiently crack passwords by employing precomputed tables containing chains of passwords and hash values. Generating these tables is computationally intensive, and several researchers have proposed utilizing parallel computing to speed up the generation process. This paper introduces a modification to the traditional master-slave parallelization model using the MPI framework, where, unlike previous approaches, the generation of starting points is decentralized, allowing each process to generate its own tasks independently. This design is proposed to reduce communication overhead and improve the efficiency of rainbow table generation. We reduced the number of inter-process communications by letting each process generate chains independently. We conducted three experiments to evaluate the performance of the parallel rainbow tables generation algorithm for four cryptographic hash functions: NTLMv2, MD5, SHA-256 and SHA-512. The first experiment assessed parallel performance, showing near-linear speedup and 95–99% efficiency across varying numbers of nodes. The second experiment evaluated scalability by increasing the number of processed chains from 100 to 100,000, revealing that higher workloads significantly impacted execution time, with SHA-512 being the most computationally intensive. The third experiment evaluated the effect of chain length on execution time, confirming that longer chains increase computational cost, with SHA-512 consistently requiring the most resources. The proposed approach offers an efficient and practical solution to the computational challenges of rainbow tables generation. The findings of this research can benefit key stakeholders, including cybersecurity professionals, ethical hackers, digital forensics experts and researchers in cryptography, by providing an efficient method for generating rainbow tables to analyze password security. Full article

Secure Digital Evidence Management Systems (DEMSs) ae crucial for law enforcement agencies, because traditional systems are prone to tampering and unauthorised access. Blockchain technology, particularly private blockchains, offers a solution by providing a centralised and tamper-proof system. This study proposes a private blockchain using Proof of Work (PoW) to securely manage digital evidence. Miners are assigned specific nonce ranges to accelerate the mining process, called collaborative mining, to enhance the scalability challenges in DEMSs. Transaction data includes digital evidence to generate a Non-Fungible Token (NFT). Miners use NFTs to solve the puzzle according to the assigned difficulty level d, so as to generate a hash using SHA-256 and add it to the ledger. Users can verify the integrity and authenticity of records by re-generating the hash and comparing it with the one stored in the ledger. Our results show that the data was verified with 100% precision. The mining time was $2.5$ s, and the nonce iterations were as high as $80\times {10}^3$ for $d=5$. This approach improves the scalability and integrity of digital evidence management by reducing the overall mining time. Full article

In tight sandstone gas reservoirs, proppant flowback severely limits stable gas production. This study uses laboratory flowback experiments and field analyses of the ShaXimiao tight sandstone in the Wenxing gas area to investigate the mechanisms controlling sand production. The experiments show that displacing fluid viscosity significantly affects the critical sand-flow velocity: with high-viscous slickwater (5 mPa·s), the critical velocity is 66% lower than with low-viscous formation water (1.15 mPa·s). The critical velocity for coated proppant is three times that of the mixed quartz sand and coated proppant. If the confining pressure is maintained, but the flow rate is further increased after the proppant flowback, a second instance of sand production can be observed. X-ray diffraction (XRD) tests were conducted for sand produced from practical wells to help find the sand production reasons. Based on experimental and field data analysis, sand production in Well X-1 primarily results from proppant detachment during rapid shut-in/open cycling operations, while in Well X-2, it originates from proppant crushing. The risk of formation sand production is low for both wells (the volumetric fraction of calcite tested from the produced sands is smaller than 0.5%). These findings highlight the importance of fluid viscosity, proppant consolidation, and pressure management in controlling sand production. Full article

The rapid expansion of Internet of Things (IoT) devices has heightened the demand for lightweight and secure cryptographic mechanisms suitable for resource-constrained environments. While SHA-256 remains a widely used standard, the emergence of SHA-3 particularly the KangarooTwelve variant offers potential benefits in flexibility and post-quantum resilience for lightweight resource-constrained devices. This paper presents a comparative evaluation of the energy costs associated with SHA-256 and SHA-3 hashing in Contiki 3.0, using three generationally distinct IoT platforms: Sky Mote, Z1 Mote, and Wismote. Unlike previous studies that rely on hardware acceleration or limited scope, our work conducts a uniform, software-only analysis across all motes, employing consistent radio duty cycling, ContikiMAC (a low-power Medium Access Control protocol) and isolating the cryptographic workload from network overhead. The empirical results from the Cooja simulator reveal that while SHA-3 provides advanced security features, it incurs significantly higher CPU and, in some cases, radio energy costs particularly on legacy hardware. However, modern platforms like Wismote demonstrate a more balanced trade-off, making SHA-3 viable in higher-capability deployments. These findings offer actionable guidance for designers of secure IoT systems, highlighting the practical implications of cryptographic selection in energy-sensitive environments. Full article

(1) Background: Urban parks play a critical role in conserving biodiversity within city landscapes, yet the effects of fine-scale microhabitat heterogeneity remain poorly understood. This study examines how land cover and vegetation unit type within parks influence butterfly diversity. (2) Methods: From July to September 2019 and June to September 2020, adult butterflies were surveyed in 27 urban parks across Beijing. We classified vegetation into units based on vertical structure and management intensity, and then applied the patch–matrix framework and landscape metrics to quantify fine-scale heterogeneity in vegetation unit composition and configuration. Generalized linear models (GLM), generalized additive models (GAM), and random forest (RF) models were applied to identify factors influencing butterfly richness (Chao1 index) and abundance. (3) Results: In total, 10,462 individuals representing 37 species, 28 genera, and five families were recorded. Model results revealed that the proportion of park area covered by spontaneous herbaceous areas (SHA), wooded spontaneous meadows (WSM), and the Shannon diversity index (SHDI) of vegetation units were positively associated with butterfly species richness. In contrast, butterfly abundance was primarily influenced by the proportion of park area covered by cultivated meadows (CM) and overall green-space coverage. (4) Conclusions: Fine-scale vegetation patch composition within urban parks significantly influences butterfly diversity. Our findings support applying the patch–matrix framework at intra-park scales and suggest that integrating spontaneous herbaceous zones—especially wooded spontaneous meadows—with managed flower-rich meadows will enhance butterfly diversity in urban parks. Full article

This study investigated the erosive wear of a polyurea coating with a hardness of 95 ShA and a thickness of 3 mm applied to a 3 mm thick plate made of S235 steel. The process of erosive wear was carried out using a stream of compressed air containing abrasive grains of aluminum oxide (Al₂O₃). The erosive wear was studied using different incidence angles (45°, 60° and 90°) and erosive grain sizes. Thus, the effects of the incidence angle and erosive grain size on the erosive wear of the polyurea coating were analyzed. Erosive wear was determined as linear wear: the depth of the wear trace was measured using an optical profilometer. This study showed a non-linear correlation between erosive wear, incidence angle and erosive particle size. In addition, a qualitative study of the surface of the coating after a wear test was carried out using a scanning electron microscope, which made it possible to describe the mechanisms of erosive wear of the polyurea coating. Full article

Conventional public-key cryptographic systems are increasingly threatened by advances in quantum computing, accelerating the need for robust post-quantum cryptographic solutions. Among these, Falcon, a compact lattice-based digital signature scheme, has emerged as a leading candidate in the NIST post-quantum standardization process due to its efficiency and theoretical security grounded in hard lattice problems. This work introduces Falcon-M, a modified version of the Falcon algorithm that significantly reduces implementation complexity. It does so by replacing Falcon’s intricate trapdoor-based key-generation mechanism with a simplified approach that utilizes randomized polynomial Gaussian sampling and fast Fourier transform (FFT) operations. Falcon-M incorporates SHA-512 hashing and discrete Gaussian sampling to preserve cryptographic soundness and statistical randomness while maintaining the core structure of Falcon’s signing and verification processes. We formally specify the Falcon-M algorithm, provide an updated pseudocode, and offer a comparative analysis with the original Falcon in terms of algorithmic complexity, security assumptions, and implementation overhead. Additionally, we present formal lemmas and theorems to ensure correctness and define theoretical bounds on forgery resistance. Although Falcon-M does not rely on a formal cryptographic trapdoor, we demonstrate that it achieves strong practical security based on assumptions related to the Short Integer Solution (SIS) problem. Falcon-M is thus well-suited for lightweight post-quantum applications, particularly in resource-constrained environments, such as embedded systems and Internet-of-Things (IoT) platforms. Full article

(1) While three-dimensional (3D) printing technology is increasingly being used for the fabrication of high-fidelity, patient-specific aortic models, data on the mechanical properties of polymers are sparse. Therefore, the aim of this study was to identify suitable polymers for this purpose. (2) Methods: Eight flexible polymers, with Shore A hardnesses (ShA) of 27–85, were tested to determine their suitability for PolyJet printing technology. They were tested against porcine aortic and bovine pericardial tissue for suture retention strength, uniaxial stress testing according to ISO 37, and burst pressure in a standardized test setting. (3) Results: The polymers with a ShA of 30–50 showed statistically non-inferior suture retention strength, tensile strength, and burst pressure resistance when compared to pericardial and aortic tissue, respectively. (4) Conclusions: This was the first report to analyze the mechanical properties of eight different flexible PolyJet polymers. We found that the polymers with a Shore A hardness of 30–50 most closely mimicked the mechanical properties of aortic tissue. Therefore, they can be recommended for the additive manufacturing (3D printing) of aortic phantoms for simulation and training purposes. Full article

The study analyses at the information level the impact of the main economic indicators on migration and access to services in the European Union, using methods specific to intelligent information systems. The research is based on the correlations between gross value added (GVA), gross fixed capital formation (GFCF), greenhouse gas emissions (GHGE), health expenditure (SHA11), and migration rates (MIGR). The applied methodology includes attribute distribution analysis, identification of hidden patterns through clustering algorithms (K-Means and Expectation-Maximisation) and training of classifiers using regression decision trees with linear leaf models (M5P) corresponding to interdependent data processing and integration modules, exploratory analysis module, machine learning and decision-making modules, oriented to support public policies through explainable scenarios and predictive-evaluative structures. The results highlight the superiority of the EM model in detecting relevant clusters and the usefulness of M5P trees in highlighting complex economic influences on population mobility. The study proposes the integration of these methods into an intelligent analysis framework aimed at reducing disparities and optimising socio-economic sustainability. The EM model demonstrated a superior ability to detect subgroups within the dataset, revealing four distinct clusters with specific characteristics. Furthermore, the M5P tree analysis allowed the extraction of significant non-linear relationships between economic variables and the migration phenomenon. The study emphasises the importance of public policies aimed at reducing regional economic disparities and increasing social and economic sustainability. By integrating these results into a well-structured information system, it provides a robust analytical framework that supports policy makers and researchers in designing effective public policies on population mobility and its related economic impact in the EU Member States. Full article

This study presents a novel two-dimensional hyperchaotic map, referred to as the 2D exponent-logarithm-sine chaotic map (2D-ELSCM), which is intricately designed through the interplay of exponential, logarithmic, and sine functions. To comprehensively evaluate the chaotic performance of the 2D-ELSCM, several critical metrics are employed, including the largest Lyapunov exponent (LLE), permutation entropy (PE), sample entropy (SE), Kolmogorov entropy (KE), and the results of the 0–1 test, which yield values of 8.3175, 0.9998, 1.9826, 2.1117, and 0.9970, respectively. Furthermore, the 2D-ELSCM successfully passes the NIST randomness tests, collectively confirming its exceptional randomness and complexity. Building upon this robust chaotic map, we develop a distinctive chaotic image encryption scheme that employs an improved Knuth-Durstenfeld shuffle (IKDS) to rearrange pixel positions, effectively disrupting the correlation between adjacent pixels. Complementing this, we introduce a dynamic diffusion mechanism that integrates DNA encoding with the Zigzag transform, thereby promoting global pixel diffusion and enhancing encryption security. The initial conditions of the chaotic map are generated from the SHA-512 hash of the plaintext image in conjunction with an external key, which not only expands the key space but also significantly improves key sensitivity. Simulation results demonstrate that the proposed encryption scheme achieves correlation coefficients approaching 0 in the encrypted test images, with an average NPCR of 99.6090% and UACI of 33.4707%. These findings indicate a strong resistance to various attacks and showcase excellent encryption quality, thereby underscoring the scheme’s potential for secure image transmission and storage. Full article

The Henan section of the Sha Ying River Basin, as the core agricultural area of the Central Plains Urban Agglomeration (CPUA), plays a significant role in promoting regional green and sustainable development through the coordinated management of water–energy–carbon (WEC). This study takes the Henan section of the Sha Ying River Basin as a case study to analyze the spatiotemporal evolution characteristics of the region from 2010 to 2022, establish an evaluation system to assess the level of coupled coordination development, and utilize the gray correlation model to identify key influencing factors. The results show a fluctuating downward trend in WEC consumption, with low coupling coordination transitioning from high coordination to moderate imbalance. Key factors influencing coupling coordination include water consumption per 10,000 CNY of GDP, agricultural industry structure, and year-end population. Spatial heterogeneity in WEC coupling coordination factors was observed across cities. This research provides a scientific basis for understanding ecosystem dynamics in agricultural cities and supports differentiated environmental policies for sustainable regional development. Full article

The flavor profile of white tea emerges from the natural biochemical composition of its tender leaves, a delicate balance profoundly shaped by seasonal growing conditions and tea cultivars. However, the effects of harvest seasons on biochemical and volatile compounds in white teas in southwestern China have not been fully analyzed at present. This study investigated the sensory characteristics, biochemical components, and volatile compounds of ‘Sanhua1951’ spring white tea (SH-S), ‘Sanhua1951’ autumn white tea (SH-A), ‘Fudingdabai’ spring white tea (FD-S), and ‘Fudingdabai’ autumn white tea (FD-A). The results showed that the sensory quality (appearance, taste, and aroma) scores of spring tea were higher than those of autumn tea. Spring teas exhibited significantly higher epigallocatechin, soluble sugar, and amino acid levels than autumn teas (p < 0.05), whereas autumn teas contained greater contents of epicatechin gallate, catechin, caffeine, and polyphenols (p < 0.05), which were responsible for the differences in taste quality observed between samples with different harvest seasons. A total of 90 volatile compounds in four groups were identified through HS-SPME–GC–MS analysis, and spring white teas contained higher contents of and variability in volatile compounds than autumn white teas. According to the OPLS-DA model, 52 and 57 differential volatile compounds (VIP > 1, p < 0.05, and fold change ≥ 2 or ≤0.5) were identified in SH-S vs. SH-A and FD-S vs. FD-A, including (Z)-linalool oxide, (E)-linalool oxide, styrene, phenylethyl alcohol, (Z)-citral, etc. The odor active value (OAV) results indicated that 30 key differential volatile compounds (OAV > 1) were determined in four groups, among which β-ionone, 5,6-epoxy-β-ionone, linalool, and (E)-linalool oxide exhibited particularly high OAVs and contributed more pekoe aroma and floral sensory characteristics. Notably, (E)-linalool oxide, (Z)-jasmone, and δ-cadinene were identified in each cultivar. These findings suggest their potential as seasonal markers, paving the way for the development of white tea ’Sanhua1951’ and ’Fudingdabai’. Full article