A document by Eric J Earley. Click on the document to view its contents.

A document by Shekhar Kumar Yadav. Click on the document to view its contents.

Bit and power loading (BPL) algorithms played a pivotal role in the success of orthogonal frequency division multiplexing (OFDM) in digital transmission, including lightemitting diode (LED) based wireless optical communications. Nevertheless, the conventional BPL algorithms do not distinguish the nonlinear distortion generated in LED transmitters from an additive noise, which leaves room for improvement. This letter presents a novel power loading and two BPL algorithms that maximize the transmission capacity while minimizing the nonlinear distortion generated in LED. The effectiveness of the proposed algorithms is evaluated through simulations and transmission experiments, revealing a throughput increase of up to 10% in comparison to what can be achieved employing classical algorithms.

Environmental movements of the late 20th century resulted in sweeping legislation and regulatory actions to reduce the prevalence of diverse pollutants. Although the consequences of noise pollution to public health, the environment, and the economy have been recognized over the same time period, noise has received far less policy attention. Correspondingly, even while recent decades have seen robust advancements in assessing the impacts of noise pollution, solutions and actual reductions in environmental noise have remained seemingly out of reach. To address this shortcoming, we developed a prospectus for environmental noise reduction through technology-forcing policies. Technology-forcing describes intent to encourage technological solutions for pollution control through policy and regulations, and has been a critical component of national and global progress in reducing environmental pollutants. We take advantage of the unique policy history for noise in the United States - which initially enacted, but then abandoned federal noise regulation. We compare this history against outcomes from contemporaneous environmental legislation for air, water, and occupational pollution control, to demonstrate the potential for technology-forcing to reduce noise pollution. Our review then identifies promising solutions, in the form of existing technologies suitable for innovation and diffusion through technology-forcing regulations and incentives. Based on this review, we outline a program for noise policy development that is intended to support efforts to reduce environmental noise pollution worldwide. The proposed program consists of three steps, 2 which are to (i) identify dominant sources of noise pollution, (ii) combine legislative or regulatory provisions with suitable systems of enforcement and incentives, and (iii) anticipate and prepare for stages of technological change. This work is intended to support and advocate for noise policies designed around technology-forcing, to advance technologies that not only improve public health and sustainable development, but ensure that these benefits are distributed equitably.

Machine learning models are increasingly vital for clinical decision making. However, the integration of these models into health information systems (HISs) poses significant challenges, mainly due to the disparate formats of electronic health records (EHR) in various healthcare facilities. In response to this challenge, we proposed Model Cabinet Architecture (MoCab), a framework designed to leverage fast healthcare interoperability resources (FHIR) as the standard for data storage and retrieval when deploying machine learning models across various HISs. MoCab simplifies the deployment process by importing and configuring saved prediction models, facilitating patient data retrieval from FHIR servers, and transmitting it to the prediction model for analysis. The framework further incorporates Clinical Decision Support (CDS) Hooks for issuing clinical alerts and uses Substitutable Medical Apps Reusable Technologies (SMART) on FHIR to develop Apps for displaying laboratory results. Finally, MoCab offers the ability to continuously fine-tune and enhance the performance of deployed models over time. We demonstrate MoCab's efficacy through the successful integration of three model types, highlighting its potential in streamlining decision making amidst heterogeneous EHRs. Our proposed MoCab framework not only promotes the reusability of machine learning models across multiple EHRs but also contributes to improving clinical decision making, offering a promising solution to the challenges of integrating machine learning models into healthcare settings.

The foundations of nonlinear optics are revisited, and the formalism is applied to waveguide modes. The effect of loss and dispersion are included rigorously along with the vectorial nature of the modes, and a new version of the nonlinear Schrödinger (NLS) equation is derived. This leads to more general expressions for the group index, for the group-index dispersion (GVD), and for the Kerr coefficient. These quantities are essential for the design of waveguides suitable for e.g. the generation of optical frequency combs and all-optical switches. Examples are given using the silicon nitride material platform. Specifically, values are extracted for the coefficients of the chi-3 tensor based on measurements of Kerr coefficients and mode simulations.

A document by Ara A. Assim . Click on the document to view its contents.

In this publication, we analyze how the performance of propagation parameter estimation for THz channel sounding can be improved by the power spectrum design of a multicarrier waveform. To this end, we discuss the Fisher information of the propagation parameters and the corresponding deterministic Cramèr-Rao lower bound (CRB) as well as their relation to the carrier powers of the excitation signal. We use these quantities to design waveforms that improve range estimation. In practice, optimizing the power spectrum requires prior knowledge of the propagation scenario which is usually not available. Hence, we propose two solutions which we compare numerically to the classical approach of equal power distribution. The numerical evaluation shows that an optimized power distribution can improve the CRB comparable up to a 4 dB gain in SNR depending on whether knowledge about the scenario can be acquired in advance with an additional measurement. © 2023 IEEE.  Personal use of this material is permitted.  Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Status: Accepted for presentation at the EuCAP conference 2024 https://www.eucap2024.org/.

Nearly ideal vertical AlxGa1-xN (\(0.7\ \le x<1.0\)) p-n diodes are fabricated on an AlN substrate. Distributed polarization doping (DPD) was employed for both p-type and n-type layers of the p-n junction, instead of conventional impurity doping, to overcome the major bottleneck of AlN-based material: the control of conductivity. Capacitance-voltage measurements revealed that the net charge concentration agreed well with the DPD charge concentration expected from the device layer structure. The fabricated devices exhibited a low turn-on voltage of 6.5 V, a low differential specific ON-resistance of 3 mΩ cm2, electroluminescence (maximum at 5.1 eV), and an ideality factor of 2 for a wide range of temperatures (room temperature-573 K). Moreover, the breakdown electric field was 7.3 MV cm-1, which was almost twice as high as the reported critical electric field of GaN at the same doping concentration. These results clearly demonstrate the usefulness of DPD in the fabrication of high-performance AlN-based power devices.

Late-life balance disorders remain a severe problem with fatal consequences. Perturbation-based balance training (PBT), a form of rehabilitation that intentionally introduces small, unpredictable disruptions to an individual's gait cycle, can improve balance. The Tethered Pelvic Assist Device (TPAD) is a cable-driven robotic trainer that applies perturbations to the user's pelvis during treadmill walking. Earlier work showcased improved gait stability and the first evidence of increased cognition acutely. The mobile Tethered Pelvic Assist Device (mTPAD), a portable version of the TPAD, applies perturbations to a pelvic belt via a posterior walker during overground gait, as opposed to treadmill walking. Forty healthy older adults were randomly assigned to a control group (CG, n = 20) without mTPAD PBT or an experimental group (EG, n = 20) with mTPAD PBT for a two-day study. Day 1 consisted of baseline anthropometrics, vitals, and functional and cognitive measurements. Day 2 consisted of training with the mTPAD and post-interventional cognitive and functional measurements. Results revealed that the EG significantly outperformed the CG in several cognitive (SDMT-C and TMT-B) and functional (BBS and 4-Stage Balance: one-foot stand) measurements while showcasing increased confidence in mobility based on FES-I. To our knowledge, our study is the first randomized, large group (n = 40) clinical study exploring new mobile perturbation-based robotic gait training technology.

We propose a method to extract the equivalent material parameters and circuit models for all-metallic tensor metamaterials. The metamaterials consist of an arrangement of sub-wavelength metallic pins affixed to the bottom plate of an air-filled parallel plate waveguide (PPW). Isotropic and anisotropic configurations are studied, which are implemented with cylindrical and elliptical pins, respectively. The effective permittivity and permeability tensor of an equivalent lossless, homogeneous PPW are extracted. An equivalent circuit model consisting of series inductances and a shunt capacitance is also extracted. An analytical procedure to perform the extraction is outlined. The procedure is validated using full-wave simulations and circuit theory. Finally, representative designs are presented to show the effectiveness and potential applications of the proposed homogenization technique. The extraction of effective material parameters enables the control of the properties of all-metal metamaterials, enabling the design of perfectly-matched, anisotropic unit cells. Ultimately, the accurate mapping between all-metal metamaterials and their equivalent circuit networks could be exploited to accelerate the inverse design of multi-functional metastructures.

We introduce a new construction method of diffusion layers for Substitution Permutation Network (SPN) structures along with its security proofs. The new method can be used in block ciphers, stream ciphers, hash functions, and sponge constructions. Moreover, we define a new stream cipher mode of operation through a fixed pseudorandom permutation and provide its security proofs in the indistinguishability model. We refer to a stream cipher as a Small Internal State Stream (SISS) cipher if its internal state size is less than twice its key size. There are not many studies about how to design and analyze SISS ciphers due to the criterion on the internal state sizes, resulting from the classical tradeoff attacks. We utilize our new mode and diffusion layer construction to design an SISS cipher having two versions, which we call DIZY. We further provide security analyses and hardware implementations  of DIZY. In terms of area cost, power, and energy consumption, the hardware performance is among the best when compared to some prominent stream ciphers, especially for frame-based encryptions that need frequent initialization. Unlike recent SISS ciphers such as Sprout, Plantlet, LILLE, and Fruit; DIZY does not have a keyed update function, enabling efficient key changing.Â

A document by Pablo Mateos-Ruiz . Click on the document to view its contents.

Affective virtual reality (VR) gaming systems rely on timely physiological data collection, in order to generate personalized responses that enhance the emotional impact of a video game on its user. In this context, we propose a simple policy for timely data collection from wireless sensor nodes placed on the human body. Our policy is applied at each sensor node. Upon each packet arrival we check whether the buffer is full or not. If the buffer is full, then we empty it before adding the packet. In this very simple way, we avoid buffer congestion and impose timeliness. We simulated this aggressive buffer reset policy using a body area network (BAN) model in OMNeT++. By varying the packet generation rate of each node, we showed that our policy outperforms first come first served (FCFS) and last come first served (LCFS) queueing policies in terms of peak age, while packet reception is barely affected. Buffer resets can be easily integrated into existing random access protocols to support timely data collection.

Paper explaining measured conduction currents in a needle to plane gap in a mineral oil and an ester liquid when applying a high voltage. There are large differences between mineral oil and ester. Please use the accepted manuscript, DOI: 10.1109/TDEI.2024.3377178  

Mathematics is the foundational discipline for all sciences, engineering, and technology, and the pursuit of normed division algebras in all finite dimensions represents a paramount mathematical objective. In the quest for a real three-dimensional, normed, associative division algebra, Hamilton discovered quaternions, constituting a non-commutative division algebra of quadruples. Subsequent investigations revealed the existence of only four division algebras over reals, each with dimensions 1, 2, 4, and 8. This study transcends such limitations by introducing generalized hypercomplex numbers extending across all dimensions, serving as extensions of traditional complex numbers. The space formed by these numbers constitutes a non-distributive normed division algebra extendable to all finite dimensions. The derivation of these extensions involves the definitions of two new $\pi$-periodic functions and a unified multiplication operation, designated as spherical multiplication, that is fully compatible with the existing multiplication structures. Importantly, these new hypercomplex numbers and their associated algebras are compatible with the existing real and complex number systems, ensuring continuity across dimensionalities. Most importantly, like the addition operation, the proposed multiplication in all dimensions forms an Abelian group while simultaneously preserving the norm. In summary, this study presents a comprehensive generalization of complex numbers and the Euler identity in higher dimensions, shedding light on the geometric properties of vectors within these extended spaces. Finally, we elucidate the practical applications of the proposed methodology as a viable alternative for expressing a quantum state through the multiplication of specified quantum states, thereby offering a potential complement to the established superposition paradigm. Additionally, we explore its utility in point cloud image processing.

As the Internet of Things (IoT) evolves rapidly across various industries, the number of IoT protocols and applications is growing with vast number of heterogeneous components and entities. In setups with thousands of IoT devices, manual deployment of applications and device registration become impractical due to their time-consuming and costly nature, as well as the requirement for background knowledge of IoT devices and protocols. Furthermore, IoT devices often have resource constraints that prevent them from running complex software. Therefore, there is a significant need to enhance and optimize edge computing systems for IoT, making them suitable and dynamic for automated IoT device registration and heterogeneous application deployment. In this paper, we present an edge-based framework designed to facilitate the automated registration of diverse wireless IoT devices and the deployment of IoT applications. To validate our approach, we use a smart irrigation system enhanced with a containerized machine learning model as a proof of concept. Our evaluation of the implemented prototype demonstrates that our system is scalable and feasible.

Spectrum sensing technology is a crucial aspect of modern communication technology, serving as one of the essential techniques for efficiently utilizing scarce information resources in tight frequency bands. This paper first introduces three common logical circuit decision criteria in hard decisions and analyzes their decision rigor. Building upon hard decisions, the paper further introduces a method for multi-user spectrum sensing based on soft decisions. Then the paper simulates the false alarm probability and detection probability curves corresponding to the three criteria. The simulated results of multi-user collaborative sensing indicate that the simulation process significantly reduces false alarm probability and enhances detection probability. This approach effectively detects spectrum resources unoccupied during idle periods, leveraging the concept of time-division multiplexing and rationalizing the redistribution of information resources. The entire computation process relies on the calculation principles of power spectral density in communication theory, involving threshold decision detection for noise power and the sum of noise and signal power. It provides a secondary decision detection, reflecting the perceptual decision performance of logical detection methods with relative accuracy.