Biologically inspired evolutionary temporal neural circuits

Biological neural networks have always motivated creation of new artificial neural networks, and in this case a new autonomous temporal neural network system. Among the more challenging problems of temporal neural networks are the design and incorporation of short and long-term memories as well as the choice of network topology and training mechanism. In general, delayed copies of network signals can form short-term memory (STM), providing a limited temporal history of events similar to FIR filters, whereas the synaptic connection strengths as well as delayed feedback loops (ER circuits) can constitute longer-term memories (LTM). This dissertation introduces a new general evolutionary temporal neural network framework (GETnet) through automatic design of arbitrary neural networks with STM and LTM. GETnet is a step towards realization of general intelligent systems that need minimum or no human intervention and can be applied to a broad range of problems. GETnet utilizes nonlinear moving average/autoregressive nodes and sub-circuits that are trained by enhanced gradient descent and evolutionary search in terms of architecture, synaptic delay, and synaptic weight spaces. The mixture of Lamarckian and Darwinian evolutionary mechanisms facilitates the Baldwin effect and speeds up the hybrid training. The ability to evolve arbitrary adaptive time-delay connections enables GETnet to find novel answers to many classification and system identification tasks expressed in the general form of desired multidimensional input and output signals. Simulations using Mackey-Glass chaotic time series and fingerprint perspiration-induced temporal variations are given to demonstrate the above stated capabilities of GETnet

Determination of vitality from a non-invasive biomedical measurement for use in integrated biometric devices

Personal identification is a very important issue in today\u27s mobile and electronically networked societies. Among the available measures, fingerprints are the oldest and most widely used. Unfortunately, it is usually possible to deceive automatic fingerprint identification systems by presenting a well-duplicated synthetic or dismembered finger. This project is one method to provide fingerprint vitality authentication in order to solve this problem. Using a sensor that is composed of an array of capacitors, this method identifies the vitality of a fingerprint by detecting a specific changing pattern over the human skin. Mapping the two-dimensional images into one-dimensional signals, two ensembles of measures, namely static and dynamic measures, are used for classification. Static patterns as well as temporal changes in dielectric mosaic structure of the skin demonstrate themselves in these signals. Using these measures, this algorithm quantifies this specific pattern and makes a final decision about vitality of the fingerprint by a neural network trained by examples

Modern Tools for Noninvasive Analysis of Brainwaves: Applications in Assistive Technologies and Medical Diagnostics

Advances in Biomaterials and Medical Devices PanelDigital signal processing is arguably one of the most important segments of any modern medical equipment. Recent advances in intelligence signal processing have married machine learning methods to traditional signal analysis and classification practices. In this talk, I will review state of the art brainwave analysis methods and our related advances in quantitative electroencephalogram (qEEG) analysis for brain computer interfaces (thought translation devices), as well as cerebral ischemia localization (e.g. for clamp monitoring during inetroperative carotid endarterectomy). The presentation will conclude with a discussion on corresponding R&D trends, especially near infrared spectroscopy (NIRS) as a new complementary modality to EEG for portable and affordable monitoring of brain functions

Conjunctival scanning for biometric identification

Researchers at UMKC have developed a biometric device which recognizes the physical characteristics of sclera veins which are visible through the conjunctival membrane in the human eye. The vascular structures of the conjunctiva and episclera are rich with specific details that are useful in identifying individuals. Unlike retinal scans, the vascular structures of the conjunctiva and episclera provide extensive and unique information that can be obtained from various and selected regions of the eye and processed to authenticate or identify individuals. The technology can work with less light, on non-compliant targets, and from much greater distances than currently employed methods. It can function as a stand-alone biometric or could be used in conjunction with exiting ocular-based biometrics to achieve enhanced performance and spoof-proofing. Potential Areas of Applications: * Airport /border security * Law enforcement * Casinos * Private security Patent Status: U.S. Patent no. 7,327,860 Inventor(s): Reza Derakhshani; Arun Ross Contact Info: 0James Brazeal - [email protected] (816) 235-509

Revolutionizing Groundwater Management with Hybrid AI Models: A Practical Review

Developing precise soft computing methods for groundwater management, which includes quality and quantity, is crucial for improving water resources planning and management. In the past 20 years, significant progress has been made in groundwater management using hybrid machine learning (ML) models as artificial intelligence (AI). Although various review articles have reported advances in this field, existing literature must cover groundwater management using hybrid ML. This review article aims to understand the current state-of-the-art hybrid ML models used for groundwater management and the achievements made in this domain. It includes the most cited hybrid ML models employed for groundwater management from 2009 to 2022. It summarises the reviewed papers, highlighting their strengths and weaknesses, the performance criteria employed, and the most highly cited models identified. It is worth noting that the accuracy was significantly enhanced, resulting in a substantial improvement and demonstrating a robust outcome. Additionally, this article outlines recommendations for future research directions to enhance the accuracy of groundwater management, including prediction models and enhance related knowledge

Elucidating fault-related fold mechanics: a 2D finite element analysis of bending, slip, and buckling mechanisms

Fault-related folds are present in most tectonic settings and may serve as structural traps for hydrocarbons. Due to their economic importance, many kinematic models present for them. Unfortunately, most of them have predominantly concentrated on the sliding mechanism parallel to the layering and often ignore the integral role of buckling in folding processes. This study is at the forefront of exploring the interplay among, sliding, buckling, and bending in the formation of the three fundamental types of fault-related folds: detachment, fault-propagation, and fault-bend folds. To this end, we developed five sets of two-dimensional (2D) finite element models, embodying both elastic and elastic-plastic behaviors. Our results indicate that sliding parallel to layering and faults, in conjunction with buckling, are the predominant mechanisms in fault-related folding. The strain ellipse patterns in our models are consistent with those observed in buckling models, thus affirming the significance of buckling in these geological structures. Furthermore, our models demonstrate that fault slip diminishes from the periphery towards the center in all three types of fault-related folds, in contrast to interlayer slip, which intensifies from the edge towards the center. In essence, a diminution in fault slip at the center is balanced by an augmentation in interlayer slip, leading to thickening and buckling. The genesis of all three fault-related fold types is attributed to the reduction in fault slip, with their distinctiveness defined by the location of this reduction: at the detachment fault tip for detachment folds, at the ramp tip for fault-propagation folds, and at the upper flat for fault-bend folds

A High Thrust Force Spoke-Type Linear Permanent Magnet Vernier Machine with Reduced Thrust Force Ripple

Linear permanent magnet vernier machines (LP-MVMs) have become prevalent in direct-drive applications, such as wave energy harvesting systems and traction applications, owing to their distinctive merit of providing high thrust force at low speeds. In this paper, a novel structure of a double-sided spoke-type LPMVM is proposed, which takes advantage of the magnetic gearing effect. The proposed double-sided linear machine exploits spoke-type permanent magnets (PMs) and one of the stators is displaced as half of the stator tooth pitch to obtain the flux-focusing effect. The thrust force ripple of the proposed spoke-type LPMVM can be decreased by adjusting the stator end-teeth and mitigating the detrimental impact of the longitudinal effect. The proposed LPMVM with adjusted end-teeth offers a noteworthy potential in terms of high thrust force density, increased power factor, and reduced thrust force ripple, which makes it a suitable candidate for various direct-drive applications. The proposed LPMVM is compared with a conventional surface-mounted LPMVM and a spoke-type LP-MVM without adjusting end-teeth to verify the superiority of the new structure. Also, transient and steady-state thermal analyses of the proposed LPMVM are conducted to confirm its thermal stability. A two-dimensional finite element analysis (2D-FEA) is adopted to prove the outstanding characteristics of the proposed double-sided spoke-type linear vernier structure

Linear Permanent Magnet Vernier Generators for Wave Energy Applications: Analysis, Challenges, and Opportunities

© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).Harvesting energy from waves as a substantial resource of renewable energy has attracted much attention in recent years. Linear permanent magnet vernier generators (LPMVGs) have been widely adopted in wave energy applications to extract clean energy from oceans. Linear PM vernier machines perform based on the magnetic gearing effect, allowing them to offer high power/force density at low speeds. The outstanding feature of providing high power capability makes linear vernier generators more advantageous compared to linear PM synchronous counterparts used in wave energy conversion systems. Nevertheless, they inherently suffer from a poor power factor arising from their considerable leakage flux. Various structures and methods have been introduced to enhance their performance and improve their low power factor. In this work, a comparative study of different structures, distinguishable concepts, and operation principles of linear PM vernier machines is presented. Furthermore, recent advancements and innovative improvements have been investigated. They are categorized and evaluated to provide a comprehensive insight into the exploitation of linear vernier generators in wave energy extracting systems. Finally, some significant structures of linear PM vernier generators are modeled using two-dimensional finite element analysis (2D-FEA) to compare their electromagnetic characteristics and survey their performance.Peer reviewe

Discontinuous rock slope stability analysis under blocky structural sliding by fuzzy key-block analysis method

This study presents a fuzzy logical decision-making algorithm based on block theory to effectively determine discontinuous rock slope reliability under various wedge and planar slip scenarios. The algorithm was developed to provide rapid response operations without the need for extensive quantitative stability evaluations based on the rock slope sustainability ratio. The fuzzy key-block analysis method utilises a weighted rational decision (multi-criteria decision-making) function to prepare the 'degree of reliability (degree of stability-instability contingency)' for slopes as implemented through the Mathematica software package. The central and analyst core of the proposed algorithm is provided as based on discontinuity network geometrical uncertainties and hierarchical decision-making. This algorithm uses block theory principles to proceed to rock block classification, movable blocks and key-block identifications under ambiguous terms which investigates the sustainability ratio with accurate, quick and appropriate decisions especially for novice engineers in the context of discontinuous rock slope stability analysis. The method with very high precision and speed has particular matches with the existing procedures and has the potential to be utilised as a continuous decision-making system for discrete parameters and to minimise the need to apply common practises. In order to justify the algorithm, a number of discontinuous rock mass slopes were considered as examples. In addition, the SWedge, RocPlane softwares and expert assignments (25-member specialist team) were utilised for verification of the applied algorithm which led to a conclusion that the algorithm was successful in providing rational decision-making

An overview of the current status of engineered therapeutic monoclonal antibodies

Since the commercialization of the first therapeutic monoclonal antibody (mAb) product in 1986, this class of biopharmaceutical products have grown significantly. Due to the enhanced antigen binding and reduced cellular toxicity, they result in more efficacy in treatment of variety of diseases. The global sales of mAbs which was 95.1 b$in 2017 have grown annually due to the dramatic increase in cancer and severe diseases rates and are estimated to reach 131.33 b$ by 2023, this represents a clear accelerating trend with more than 5.53% growth. In this review, we discuss some of these mAbs which have been approved by the FDA as well as others that are experiencing or being evaluated in clinical phases. Global sales of some monoclonal antibodies in 2016 are also considered, suggesting a significant increase in sales of mAbs over the years ahead. &nbsp