Abstract:The P vs NP problem is one of the central unsolved questions in theoretical computer science. Traditionally formulated within the framework of Turing machines, “time” represents the number of discrete computation steps. This paper explores the speculative idea that reinterpreting time as a dynamic, controllable parameter—rather than a fixed measure—could suggest alternative models of computation that challenge or extend classical complexity boundaries. By drawing connections between causality, temporal dynamics, and computational processes, we outline potential for future research that unites concepts from theoretical physics and computation.
Abstract:New lactobionamidoalkyl thiol-disulfide compounds were synthesized using lactobionolactone and aminoalkylthiols via amidation ring opening of the cyclic lactobionolactone to give compounds di(n-lactobionamidoalkyl) disulfides (2a-4a), and nlactobionamidoalkyl thiols (2c-4c). These compounds were acetylated to form acetylated di(n-lactobionamidoalkyl) disulfides (2b-4b), and acetylated n-lactobionamidoalkyl thiols (2d-4d), and subsequently utilized to stabilized gold nanoparticles (LAuNPs1-17). These compounds were characterized by spectroscopic methods (NMR, Infrared and GCMS), microanalysis, Transmission Electron Microscope (TEM) and Zetasizer. The lactobionamidoalkyl thiol and disulfide compounds were effective capping agents of gold nanoparticles via direct and substitution methods except substitution with unacetylated thiols (2c-4c) and disulfides (2a-4a) which decomposed within minutes. In-vitro anticancer screening of selected LAuNPs using acetylated and un-acetylated demonstrated moderate activity against human lung adenocarcinoma epithelial cell line and weak activity against human normal peripheral blood mononuclear cells, except LAuNPs 11 which showed moderate activities towards both cells lines with IC50s of 14.79±3.84 µg/mL and 13.26±6.48 µg/mL respectively.
Abstract:Goal – This study proposes an integrated model for improving equipment availability in maintenance management by considering the relationship between Mean Time Between Failures (MTBF) and Mean Time To Repair (MTTR). These indicators are typically evaluated individually for decision-making in maintenance management. Methodology – The proposed integrated method uses widely adopted tools in industrial management, such as reliability statistical analysis, Lean Manufacturing, M-VSM (Material and Value Stream Mapping), FMEA (Failure Mode and Effects Analysis), and criticality analysis. Results – The proposed integrated method has proven effective after implementation in the fertilizer industry, increasing the availability of the prioritized equipment as determined by reliability statistical analysis. The improvement in equipment availability was achieved through a 15.5% reduction in MTTR and a 20.6% increase in MTBF, assuming the correct application of the proposed tools. Limitations – The article was limited to investigating the MTBF and MTTR indicators, as the determination of MTTF was impossible due to data unavailability. Practical implications – The article results can be used as a reference for the strategic decision making in maintenance management within industry. Originality – The study presents the modeling of an integrated method that utilizes consolidated tools and validates it through a case study, demonstrating practical results in a company.
Abstract:The efficiency of an 8-bit flash analog-to-digital converter (ADC) is influenced by factors such as power consumption, area, and timing. As technology advances, the demand for better performance and higher standards in chip design technologies is increasing. As technology continues to advance, the standards for chip performance will likely rise, motivating researchers and manufacturers to strive for 5G and even greater achievements. The aim of this work is to study and analyse the performance requirements in terms of area, power consumption, and speed of 8-bit flash analogto-Digital Converter. Compared to other kind of analog-to-digital converters, flash converters have a significantly greater conversion rate. The number of comparators needed for flash converters is more 2 N -1 for N-bit in the conventional design architecture and consumes more power and area. In order to reduce the design complexity, power, area and noise for high bit resolution in the high-speed flash analog-to-digital converter architecture, this new design focuses on employing multiplexers to reduce the number of comparators and parameters. The traditional Flash type ADC uses more power and takes up more chip space since it needs 255 comparators for 8-bit flash. Therefore, reducing the number of comparators and noise are the design's primary goal. Only 65 comparators are needed for the construction of the 8-bit resolution Flash ADC employing multiplexers with evolution parameters such power dissipation 21uW, maximum noise 1.251nv**2/Hz, offset voltage 69.2103mv, SNDR 49.2dB, SFDR 61.3dB, differential non-linearity 0.41 LSB and INL (Integral non-linearity) 0.5 LSB. The design simulation carried out using cadence virtuoso. The work focused on backend design using 180nm CMOS process Technology.
Abstract:The use of information technology -in agriculture- plays an important role in Smart-Pest Management. Particularly, Artificial intelligence helps to identify, monitor, control and make decisions about pests in crops. In this paper, we present a new metacognitive architecture, called Metacognitive Architecture for a SmartPest Management of Cotton. Especially, this paper presents several contributions: (1) a new architecture that implements several metacognitive tasks (meta-memory, meta-learning, meta-reasoning, meta-comprehension, meta-knowledge); (2) a case study of the architecture for predictive and prescriptive problems, in the context of integrated pest management in cotton; (3) an integrated approach of data analytics and metacognition in smart systems.
Abstract:In this article, we first define bi-periodic Pell sequence which is a generalization of Pell numbers consisting of two positive real numbers. We present some various sum formulas for the bi-periodic Pell numbers. After giving the definitions of r-circulant, symmetric rcirculant and geometric circulant matrices, we construct these circulant matrices with the generalized Pell sequence. Then, we investigate some inequalities for the bounds of the spectral norms of r-circulant, symmetric r-circulant and geometric circulant matrices with the generalized Pell numbers by three different ways. Finally, we give several corollaries related to norms of Hadamard and Kronecker products of these circulant matrices. The eigenvalues are also established for the r-circulant matrices whose entries are the generalized Pell numbers.
Abstract:The assessment of artificial neural network models-sigmoid (ANN-sigmoid) and hyperbolic tangent (ANN-tanh) for real-time air pollution forecasting in a Korean coastal city was performed using 15 input independent variables (3 hours' earlier PM, gas and meteorological data influenced by 48 hours’ earlier PM and gas data of a Chinese city). A feed-forward ANN technique of multilayer perception (MLP) with back-propagation training algorithm for error calculation was adopted with 15 hidden nodes and each prediction formula on four output variables was suggested. Root mean square error (RMSE) and the coefficient of determination (R2 ) assess each model’s prediction ability between the predicted and measured values, before, during, and after the Yellow Dust period (March 18~27). Pearson R coefficients from the ANN-sigmoid (or ANN-tanh) model on PM10, PM2.5, NO2, and O3 were 0.907 (0.935), 0.860 (0.942), 0.860 (0.925), and 0.957 (0.946) before the dust period, 0.917 (0.943), 0.959 (0.969), 0.855 (0.853), and 0.954 (0.949) during its period, and 0.920 (0.947), 0.928 (0.938), 0.917 (0.896), and 0.923 (0.952) after its period, showing very high prediction accuracy overall. Scatter plots with empirical formulae and temporal distributions between the predicted and measured values showed excellent prediction performance by two models, and the ANN-tanh model produced more accurate results.
Abstract:In this paper, we propose a pipeline algorithm for analysis of human gait in video for orthopedic diagnostic tasks. It is based on 3D human pose estimation that is used to detect human skeletons in 3D space. Images have depth blur in the third dimension, so obtaining accurate 3D pose estimates is more difficult. In this experiment, pre-training masks the data and uses Transformer based on the addition of parallel temporal and spatial feature modules to complete the 2D pose estimation of 3D pose. For such representations, there is a possibility to calculate angles at the articulation of the joint lines of the skeleton, changing such angles during human motion, and define the pathological direction of motion. This analysis calculates the changing of angles between key points of the constructed skeleton during the walking cycle. Angles are defined as dynamical characteristics. Such characteristics are very important for the diagnostics of orthopedic diseases, the definition of the treatment pipeline, and the determination of the type of corrective footwear.
Abstract:In this study, we present a new Elliptic Curve Cryptosystem using the bi-periodic Fibonacci matrix sequence. We propose a new cryptographic method on elliptic curves over a finite field. We map a plaintext matrix constructed from points corresponding to letters on an elliptic curve. The 2m*2m message matrix M is divided into 2*2 block matrices, Bi, for i=1,...,m^2, and each block is multiplied by the corresponding elements of the bi-periodic Fibonacci matrix sequence. Finally, the resulting matrix is multiplied by a permutation matrix to increase the complexity of the encryption algorithm.
Abstract:Dengue fever is rapidly spreading in many parts of the world and has emerged as a significant public health issue with potential fatal consequences. Information on the spatial distribution and state of dengue risk is necessary for any dengue prevention strategy and for defining the areas for control actions. As a result, an effort was made to map the dengue risk zones based on the geo-environmental and man-made factors that could affect the disease's potential transmission. The GIS platform was used to identify and customise the potential geo-environmental and man-made risk factors that affect dengue transmission. In addition, they contained particular ranges of values, which are said to be favourable for the spread of disease. A standardised dengue transmission risk index (SDTRI) was calculated using appropriate weighted scores for these factors to produce the risk map. In the study area, the SDTRI values varied from 8 to 19. With the rising value of SDTRI, the potential risk rises. A higher risk of dengue transmission in that area is indicated by the risk map's high index values. The correlation between this risk map prediction and past dengue outbreaks was strong (p 0.001), and it was discovered that the disease mostly affects areas with SDTRI values more than or equal to 13. Therefore, this dengue risk map will be helpful for spatial delimitation and for planning the appropriate interventions.