Mathematics of Arrays (MoA) concerns the formal description of algorithms working on arrays of data and the efficient and effective implementation in software and hardware. Since (multidimensional) arrays are one of the most important data structures in Fortran, as witnessed by their native support in the language and the numerous operations and functions that take arrays as input and output, it is natural to examine how Fortran can be used as implementation language for MoA. This article presents the first results, both in terms of code and of performance, regarding this union. It may serve as a basis for further research, both with respect to the formal theory of MoA and to improving the practical implementation of array-based algorithms.

This paper’s purpose is to determine whether certain groups of people are more susceptible to Coronary Heart Disease (CHD) based on their age group and gender. The author attempts to determine whether there is an association between age group and increased susceptibility to CHD in both the male and female population using data on maximum heart rate, total cholesterol, and blood pressure. The author built a device that could measure heart rate using a sensor and a microcontroller. This device was used to collect data on 10 male and 10 female subjects. The data was added to another dataset containing 1025 subjects and statistical analysis was conducted to determine whether there is association between age group and CHD susceptibility in both the male and female populations.

As organizations are growing, the same also happens to the quantity of their data and the complexity of storing them. This has called for the need for a system that assures organizations of data correctness, accuracy, and consistency, master data management. Master data management possesses numerous benefits and challenges to organizations. A.Purpose The purpose of this study is to identify the numerous pros and cons of master data management in business organizations. B. Design This study is a literature review of the existing sources from different databases: google scholar, google search, science direct, IET Electronic Library, SciFinder-n, and so much more. C. Findings This study identified numerous pros and cons associated with implementing and using master data management in an organization from the numerous sources used. The pros include elimination of redundancy, effective data editing, improving quality of data, speed of launching new products, and easy backup. On the other hand, the cons include lack of stakeholder engagement, the input of irrelevant information, lack of effective data management, and getting appropriate tooling. D.Originality  The MDM is the epitome of industry’s best practices all over the globe. It is a system that allows the implementation of diverse applications, platforms, and architectures.

Feature attribution explains Artificial Intelligence (AI) at the instance level by providing importance scores of input features’ contributions to model prediction. Integrated Gradients (IG) is the prevalent path attribution method for deep neural networks, involving the integration of gradients along a path from the explained input (explicand) to a counterfactual instance (baseline). Nonetheless, current IG variants exclusively consider the gradient of explicand’s output, but we have discovered that the gradient of the counterfactual output also exerts a substantial influence on feature attribution. To achieve this, we propose Iterative Gradient path Integrated Gradients (IG2), considering both two gradients. IG2 incorporates the counterfactual gradient iteratively into the integration path, consequently obtaining a novel path (GradPath) and a novel baseline (GradCF). These two novel IG components effectively address the issues of attribution noise and arbitrary baseline choice in earlier IG methods. IG2, as a path method, stratifies many desirable axioms, which are theoretically justified in the paper. Experimental results on XAI benchmark, ImageNet, MNIST, TREC questions answering, wafer-map failure patterns, and CelebA face attributes validate that IG2 delivers superior feature attributions compared to the state-of-the-art techniques.

Our paper compares the merits of using both adaptive load resistance and adaptive frequency for impedance compensation of large spatial variations in capacitive power transfer (CPT) systems. We show through an equivalent circuit model how changes to load impedance or changes to frequency can be used to maintain a constant input impedance to the CPT link as the separation distance between the transmit and receive electrodes is varied. In previous works, frequency compensation required continuous adjustment to track spatial changes, thereby requiring broad operating bands for broad spatial ranges. Here, we combine discrete frequency compensation with continuous impedance compensation to keep transmission frequencies within specific narrowband ISM channels. This work presents a practical implementation of spatially robust CPT systems. We consider the limitations of band-limited wireless power channels and apply frequency compensation as discrete frequency changes that are switched between different bands. In this way, frequency compensation offers coarse impedance control for large spatial changes. We then combine the band switching with load impedance compensation methods that offer fine impedance control. Experimental results verify the design concepts using an electrode configuration that is compatible with a differential six-plate CPT system. The results include measurements of the compensated CPT link in isolation as well as an evaluation of compensation applied to an end-to-end system with a class-E amplifier and class-E rectifier. The results show that multi-band operation significantly extends the spatial robustness of the system. Compared to single-band operation, there is a 50\% increase in the compensation gap range in the dual-band system. The choice between multi-band and single-band systems depends on application requirements: multi-band adaptive load compensation works well in systems with large spatial variations, while single-band suffices for applications with modest spatial variation and defined range constraints.

Reconfigurable intelligent surface (RIS) technology and its integration into existing wireless networks have recently attracted much interest. While an important use case of said technology consists in mounting RISs onto unmanned aerial vehicles (UAVs) to support the terrestrial infrastructure in post-disaster scenarios, the current literature lacks an analytical framework that captures the networks’ topological aspects. Therefore, our study borrows stochastic geometry tools to estimate both the average and local coverage probability of a wireless network aided by an aerial RIS (ARIS); in particular, the surviving terrestrial base stations (TBSs) are modeled by means of an inhomogeneous Poisson point process, while the UAV is assumed to hover above the disaster epicenter. Our framework captures important aspects such as the TBSs’ altitude, the fact that they may be in either line-of-sight or non-line-of-sight condition with a given node, and the Nakagami-m fading conditions of wireless links. By leveraging said aspects we accurately evaluate three possible scenarios, where TBSs are either: (i) not aided, (ii) aided by an ARIS, or (iii) aided by an aerial base station (ABS). Our selected numerical results reflect various situations, depending on parameters such as the environment’s urbanization level, disaster radius, and the UAV’s altitude.

Current blood pressure (BP) estimation methods have not achieved an accurate and adaptable approach for application in populations at risk of cardiovascular disease, with generally limited sample sizes. Here, we introduce an algorithm for BP estimation solely reliant on photoplethysmography (PPG) signals and demographic features. Our approach automatically obtains signal features and employs the Markov Blanket (MB) feature selection to discern informative and transmissible features, achieving a robust space adaptable to the population shift. We validated our approach with the Aurora-BP database, compromising ambulatory wearable cuffless BP measurements for over 500 individuals. By evaluating several machine-learning regression methods, Gradient Boosting emerged as the most effective. The comparative assessment encompassed both a generic model (trained on unclassified BP data) and specialized models (tailored to each distinct BP population), with the former demonstrating consistent superiority with MAE  of 10.2 mmHg (0.28) for systolic BP and 6.7 mmHg (0.18) for diastolic BP on the whole dataset. Moreover, a comparison of in-clinic and ambulatory model performance showed a significant decrease in accuracy for the latter of 2.85 mmHg in systolic (p < 0.0001, F-value = 32764.76) and 2.82 mmHg for diastolic (p < 0.0001, F-value = 65675.36) estimation errors. Our work contributes to a resilient BP estimation algorithm from PPG signals, underscoring the advantages of causal feature selection and quantifying the disparities between ambulatory and in-clinic measurements.

The paper presents analysis showing that the earliest structures in the evolution of noninteger dimensionality in a system will be threads and spirals. Before the dimensionality has reached 1, the structures are linear, and thereafter these threads or strings begin to bend and fold to be in accord with fundamental scale-invariance requirements. As the evolution proceeds, threads turn into spirals in a manner that parallels phase changes in a liquid crystal. Evidence is presented that the emergence of threads and spirals is consistent with the findings in bioscience, liquid crystals, galactic center filaments, and early spiral galaxies.

This article introduces an innovative classification methodology for identifying nanowires within scanning electron microscope images. Our approach employs advanced image manipulation techniques in conjunction with machine learning-based recognition algorithms. The effectiveness of our proposed method is demonstrated through its application to the categorization of scanning electron microscopy images depicting nanowires arrays. The method's capability to isolate and distinguish individual nanowires within an array is the primary factor in the observed accuracy. The foundational data set for model training comprises scanning electron microscopy images featuring 240 III-V nanowire arrays grown with metal organic chemical vapor deposition on silicon substrates. Each of these arrays consists of 66 nanowires. The results underscore the model's proficiency in discerning distinct wire configurations and detecting parasitic crystals. Our approach yields an average F1 score of 0.91, indicating high precision and recall. Such a high level of performance and accuracy of the ML methods demonstrate the viability of our technique for not only academic but also practical commercial implementation and usage.

This paper presents COZDAL (Convolutional Octave-band Zooming-in with Depth-kernel Attention Learning), a versatile deep-learning model designed for surface Electromyography (sEMG) motion classification. Specifically focusing on sports movements involving the hamstring muscle, the model employs attention mechanisms across various frequency bands, kernel sizes, and hidden layer depths. The proposed method has been extensively evaluated on the benchmark Ninapro dataset and a custom soccer dataset. The results demonstrate substantial improvements over the existing state-of-the-art models, with an accuracy of 95.30% on Ninapro DB2, outperforming the previous best by 3.29%, and an accuracy of 98.80% on Ninapro DB2-B, a 8.6% enhancement. Remarkably, COZDAL exhibits a performance accuracy of 96.30% on a soccer dataset gathered from 45 elite-level athletes representing two clubs in the English Premier League (EPL). This result, achieved without parameter tuning, highlights the model’s adaptability and exceptional efficacy across diverse motion scenarios, sensors, subjects, and muscle types.

The concept of Digital Twin has recently emerged, which requires the transmission of a massive amount of sensor data with low latency and high reliability. Analog error correction is an attractive method for low-latency communications; hence, in this paper, we propose the use of complex-valued neural networks and Quaternionic Neural Networks (QNNs) to decode analog codes. Furthermore, we propose mapping our codes to the baseband of the frequency domain to enable easy time and frequency synchronization as well as to mitigate frequency-selective fading using robust estimation theory. This is accomplished by applying inverse Discrete Fourier Transform (DFT) modulation, which achieves a significant reduction in hardware complexity, power, and cost as compared to our previously proposed analog coding scheme. Additionally, we introduce a scaled version of our previous analog codes that enables statistical signal processing, something we have not been able to achieve until now. This achieves significant noise immunity with drastic performance improvements at low Signal-to-Noise Ratios (SNR) and a small loss at high SNR.

The main subject of this work is to make a detailed comparison between the performance of free-space optical (FSO) and terahertz (THz) links under different conditions.

Globally distributed microelectronic supply chains have disrupted trust in silicon hardware and have drawn academia’s attention toward different scenarios of malicious circuit modifications, i.e., hardware Trojans. This dynamic hardware environment, including open-source approaches and evermore outsourcing, requires constant reassessment of offensive and defensive aspects. Based on an untrusted foundry model, this work assesses the concrete technical realizations of layout-only modifications via design file editing, mask editing, or in-line alterations. Furthermore, the attack possibility on different modules within a system on a chip is qualitatively evaluated. Consequently, a modification is demonstrated on an SRAM-’PUF’ module. To link the attack point-of-view with a defensive measure, we propose a hardware reverse engineering-based countermeasure, which is non-reliant on a golden layout. Through a novel approach relying on inherent polygon properties, potentially occurring modifications are detected via clustering and a statistical evaluation of the intra-cluster distributions.  Finally, the approach is demonstrated on samples from 7 nm to 150 nm, for which a modification detection rate between 95% and 100% is reached for all evaluated samples.

Robotic Prosthetic Hands (RPH) are made with the aim of assisting amputees with activities of daily living (ADL). Upper limb amputations lead to physical and mental difficulty because of the many uses of the human hand. Researchers have been working to improve sensory feedback and dexterous manipulation in these devices to improve embodiment and reduce the abandonment rates. Efforts to implement sensory feedback have been explored by researchers in the field of biomedical engineering whereas efforts to improve dexterous manipulation are directed towards the fields of mechanical engineering and computer science. There are numerous problems faced in the field of robotic prostheses such as end point control, sensory feedback, the weight/dexterity dilemma, and the implementation of invasive methods. RPH learning to grasp from touch with tactile sensors is an additional area of research that is promising for robotic grippers. The design of RPH requires multidisciplinary knowledge related to physiology, anatomy, electronics, mechanical design, and software which renders it a complex challenge. This body of work offers a holistic review of the state of the art of current RPH and the subsequent opportunities for advancement in the field.

A document by Jinzheng Zhao . Click on the document to view its contents.

Exact explicit results are derived for the distribution of the partial busy period of the M/M/c multi-server queue for a general number of servers. A rudimentary spectral method leads to a representation that is amenable to efficient numerical computation across the entire ergodic region. An alternative algebraic approach yields a representation as a finite sum of Marcum Q-functions depending on the roots of certain polynomials that are explicitly determined for an arbitrary number of servers. Asymptotic forms are derived in the limit of a large number of servers under two scaling regimes, and also for the large-time limit. Connections are made with previous work. The present work is the first to offer tangible exact results for the distribution when the number of servers is greater than two.

An algorithm that solves a linear program with planes exterior to the feasible region is described. Given a linear program in a standard form, a constraint derived from the objective function is added to make the program infeasible, the objective function is removed. The added constraint is incrementally and unidirectionally moved toward the solution vertex in cycles. On reaching the solution vertex the program becomes feasible, this signals both the solution of the program and termination of the algorithm. Because of unidirectionality, the algorithm is guaranteed to terminate. With N variables, B-bit fixed point arithmetic, and feasibility testing complexity of O(f(N)), the complexity of the incremental exterior plane algorithm is 2B O(f(N)). With binary search, the complexity is ~O(B f(N)). Feasibility checking may be done by finding the optimum of a related LP in each cycle. Unlike in established LP methods it is only necessary to know if an intermediate constraint set is feasible or not, neither the optimum of the related LP nor the basic feasible point obtained is used or needed. The algorithm works efficiently with deformed products. Thus with a 43-dimensional Klee-Minty cube (which would require > 1012 pivots with the simplex method) the solution is obtained in less than 100 binary search cycles, similar results are obtained with Goldfarb-Sit cubes. The exterior plane algorithm is compared qualitatively with the simplex, ellipsoid, and interior point algorithms and miscellaneous others. Â

Amazing…..? Negative and positive sum of prime number are equal…very interesting …please see this working so beautiful. New conjectures in number theory I think