State of the art and trends in using smart materials and systems in transportation vehicles

1998 ◽  
Vol 212 (3) ◽  
pp. 149-158 ◽  
Author(s):  
Chr Boller
Keyword(s):  
Situation Awareness ◽  
Smart Materials ◽  
State Of The Art ◽  
Autonomous Driving ◽  
Future Research ◽  
Smart Cameras ◽  
Control Functions ◽  
Research Activities ◽  
Wide Range ◽  
And Control

An overview is given on state-of-the-art development and future trends in integrating sensing, actuation and control functions into transportation vehicles. After categorizing the wide range of smart materials and systems various applications from the aerospace, automotive and railway sector are described, which are either already in use or very much considered for application. This includes systems for damage monitoring and situation awareness using smart sensors and antennae, autonomous driving based on smart cameras, thermal and electrical controlled actuation in engines and for comfort improvement, systems for vibration damping and noise cancellation and much more. Technology gaps to be closed in future research activities are described.

Semantic Information Retrieval on Medical Texts

2022 ◽  
Vol 54 (7) ◽  
pp. 1-38
Author(s):  
Lynda Tamine ◽  
Lorraine Goeuriot
Keyword(s):  
Information Retrieval ◽  
Health Informatics ◽  
Medical Information ◽  
State Of The Art ◽  
Lessons Learned ◽  
Semantic Search ◽  
Future Research ◽  
Cross Model ◽  
Wide Range ◽  
Search Systems

The explosive growth and widespread accessibility of medical information on the Internet have led to a surge of research activity in a wide range of scientific communities including health informatics and information retrieval (IR). One of the common concerns of this research, across these disciplines, is how to design either clinical decision support systems or medical search engines capable of providing adequate support for both novices (e.g., patients and their next-of-kin) and experts (e.g., physicians, clinicians) tackling complex tasks (e.g., search for diagnosis, search for a treatment). However, despite the significant multi-disciplinary research advances, current medical search systems exhibit low levels of performance. This survey provides an overview of the state of the art in the disciplines of IR and health informatics, and bridging these disciplines shows how semantic search techniques can facilitate medical IR. First,we will give a broad picture of semantic search and medical IR and then highlight the major scientific challenges. Second, focusing on the semantic gap challenge, we will discuss representative state-of-the-art work related to feature-based as well as semantic-based representation and matching models that support medical search systems. In addition to seminal works, we will present recent works that rely on research advancements in deep learning. Third, we make a thorough cross-model analysis and provide some findings and lessons learned. Finally, we discuss some open issues and possible promising directions for future research trends.

scholarly journals Mosaic Super-resolution via Sequential Feature Pyramid Networks

2019 ◽  
Author(s):  
Mehrdad Shoeiby ◽  
Mohammad Ali Armin ◽  
Sadegh Aliakbarian ◽  
Saeed Anwar ◽  
Lars petersson
Keyword(s):  
State Of The Art ◽  
Super Resolution ◽  
Autonomous Driving ◽  
Single Shot ◽  
Current State ◽  
Wide Range ◽  
Feature Pyramid ◽  
Novel Method ◽  
Convolutional Lstm ◽  
Mosaic Images

<div>Advances in the design of multi-spectral cameras have</div><div>led to great interests in a wide range of applications, from</div><div>astronomy to autonomous driving. However, such cameras</div><div>inherently suffer from a trade-off between the spatial and</div><div>spectral resolution. In this paper, we propose to address</div><div>this limitation by introducing a novel method to carry out</div><div>super-resolution on raw mosaic images, multi-spectral or</div><div>RGB Bayer, captured by modern real-time single-shot mo-</div><div>saic sensors. To this end, we design a deep super-resolution</div><div>architecture that benefits from a sequential feature pyramid</div><div>along the depth of the network. This, in fact, is achieved</div><div>by utilizing a convolutional LSTM (ConvLSTM) to learn the</div><div>inter-dependencies between features at different receptive</div><div>fields. Additionally, by investigating the effect of different</div><div>attention mechanisms in our framework, we show that a</div><div>ConvLSTM inspired module is able to provide superior at-</div><div>tention in our context. Our extensive experiments and anal-</div><div>yses evidence that our approach yields significant super-</div><div>resolution quality, outperforming current state-of-the-art</div><div>mosaic super-resolution methods on both Bayer and multi-</div><div>spectral images. Additionally, to the best of our knowledge,</div><div>our method is the first specialized method to super-resolve</div><div>mosaic images, whether it be multi-spectral or Bayer.</div><div><br></div>

A Comprehensive Taxonomy of Dynamic Texture Representation

2023 ◽  
Vol 55 (1) ◽  
pp. 1-39
Author(s):  
Thanh Tuan Nguyen ◽  
Thanh Phuong Nguyen
Keyword(s):  
Large Scale ◽  
Environmental Changes ◽  
State Of The Art ◽  
The State ◽  
Future Research ◽  
Research Activities ◽  
Potential Applications ◽  
Benchmark Datasets ◽  
Negative Impacts ◽  
Made In

Representing dynamic textures (DTs) plays an important role in many real implementations in the computer vision community. Due to the turbulent and non-directional motions of DTs along with the negative impacts of different factors (e.g., environmental changes, noise, illumination, etc.), efficiently analyzing DTs has raised considerable challenges for the state-of-the-art approaches. For 20 years, many different techniques have been introduced to handle the above well-known issues for enhancing the performance. Those methods have shown valuable contributions, but the problems have been incompletely dealt with, particularly recognizing DTs on large-scale datasets. In this article, we present a comprehensive taxonomy of DT representation in order to purposefully give a thorough overview of the existing methods along with overall evaluations of their obtained performances. Accordingly, we arrange the methods into six canonical categories. Each of them is then taken in a brief presentation of its principal methodology stream and various related variants. The effectiveness levels of the state-of-the-art methods are then investigated and thoroughly discussed with respect to quantitative and qualitative evaluations in classifying DTs on benchmark datasets. Finally, we point out several potential applications and the remaining challenges that should be addressed in further directions. In comparison with two existing shallow DT surveys (i.e., the first one is out of date as it was made in 2005, while the newer one (published in 2016) is an inadequate overview), we believe that our proposed comprehensive taxonomy not only provides a better view of DT representation for the target readers but also stimulates future research activities.

Economic Sanctions in Flux: Enduring Challenges, New Policies, and Defining the Future Research Agenda

2020 ◽  
Vol 21 (4) ◽  
pp. 438-477
Author(s):  
Bryan R Early ◽  
Menevis Cilizoglu
Keyword(s):  
Research Agenda ◽  
State Of The Art ◽  
Economic Sanctions ◽  
Future Research ◽  
Factors Affecting ◽  
The Past ◽  
Future Research Agenda ◽  
Policy Tool ◽  
Wide Range ◽  
New Policies

Abstract Policymakers employ economic sanctions to deal with a wide range of international challenges, making them an indispensable foreign policy tool. While scholarship on sanctions has tended to focus on the factors affecting their success, newer research programs have emerged that explore the reasons for why sanctions are threatened and initiated, the ways they are designed and enforced, and their consequences. This scholarship has yielded a wealth of new insights into how economic sanctions work, but most of those insights are based on sanctions observations from the 20th Century. The ways that policymakers employ sanctions have fundamentally changed over the past two decades, though, raising concerns about whether historically derived insights are still relevant to contemporary sanctions policies. In this forum, the contributors discuss the scholarly and policy-relevant insights of existing research on sanctions and then explore what gaps remain in our knowledge and new trends in sanctions policymaking. This forum will inform readers on the state of the art in sanctions research and propose avenues for future research.

scholarly journals Deep Learning-Based Monocular Depth Estimation Methods—A State-of-the-Art Review

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2272 ◽  
Author(s):  
Faisal Khan ◽  
Saqib Salahuddin ◽  
Hossein Javidnia
Keyword(s):  
Deep Learning ◽  
State Of The Art ◽  
Research Work ◽  
Depth Estimation ◽  
Autonomous Driving ◽  
Estimation Methods ◽  
Future Research ◽  
Comprehensive Overview ◽  
Ill Posed ◽  
Monocular Depth

Monocular depth estimation from Red-Green-Blue (RGB) images is a well-studied ill-posed problem in computer vision which has been investigated intensively over the past decade using Deep Learning (DL) approaches. The recent approaches for monocular depth estimation mostly rely on Convolutional Neural Networks (CNN). Estimating depth from two-dimensional images plays an important role in various applications including scene reconstruction, 3D object-detection, robotics and autonomous driving. This survey provides a comprehensive overview of this research topic including the problem representation and a short description of traditional methods for depth estimation. Relevant datasets and 13 state-of-the-art deep learning-based approaches for monocular depth estimation are reviewed, evaluated and discussed. We conclude this paper with a perspective towards future research work requiring further investigation in monocular depth estimation challenges.

Real-Time Burst Signal Removal Using Multicolor Pyrometry Based Filter for Improved Jet Engine Control

2015 ◽  
Vol 137 (8) ◽  
Author(s):  
Guanghua Wang ◽  
Jordi Estevadeordal ◽  
Nirm Nirmalan ◽  
Sean P. Harper
Keyword(s):  
Real Time ◽  
Operating Conditions ◽  
Engine Control ◽  
Jet Engines ◽  
Jet Engine ◽  
Root Cause ◽  
Control Functions ◽  
Wide Range ◽  
Voltage Signal ◽  
And Control

Online line-of-sight (LOS) pyrometer is used on certain jet engines for diagnosis and control functions such as hot-blade detection, high-temperature limiting, and condition-based monitoring. Hot particulate bursts generated from jet engine combustor at certain running conditions lead to intermittent high-voltage signal outputs from the LOS pyrometer which is ultimately used by the onboard digital engine controller (DEC). To study the nature of hot particulates and enable LOS pyrometer functioning under burst conditions, a multicolor pyrometry (MCP) system was developed under DARPA funded program and tested on an aircraft jet engine. Soot particles generated as byproduct of combustion under certain conditions was identified as the root cause for the signal burst in a previous study. The apparent emissivity was then used to remove burst signals. In current study, the physics based filter with MCP algorithm using apparent emissivity was further extended to real-time engine control by removing burst signals at real time (1 MHz) and at engine DEC data rate. Simulink models are used to simulate the performances of the filter designs under engine normal and burst conditions. The results are compared with current LOS pyrometer results and show great advantage. The proposed model enables new LOS pyrometer design for improved engine control over wide range of operating conditions.

scholarly journals Cybersecurity of Microgrid: State-of-the-Art Review and Possible Directions of Future Research

2021 ◽  
Vol 11 (21) ◽  
pp. 9812
Author(s):  
Norziana Jamil ◽  
Qais Saif Qassim ◽  
Farah Aqilah Bohani ◽  
Muhamad Mansor ◽  
Vigna Kumaran Ramachandaramurthy
Keyword(s):  
Critical Infrastructure ◽  
State Of The Art ◽  
Advanced Technology ◽  
Future Research ◽  
Electrical System ◽  
Comprehensive Review ◽  
Electrical Systems ◽  
Wide Range ◽  
Future Work ◽  
The Impact

The infrastructure of and processes involved in a microgrid electrical system require advanced technology to facilitate connection among its various components in order to provide the intelligence and automation that can benefit users. As a consequence, the microgrid has vulnerabilities that can expose it to a wide range of attacks. If they are not adequately addressed, these vulnerabilities may have a destructive impact on a country’s critical infrastructure and economy. While the impact of exploiting vulnerabilities in them is understood, research on the cybersecurity of microgrids is inadequate. This paper provides a comprehensive review of microgrid cybersecurity. In particular, it (1) reviews the state-of-the-art microgrid electrical systems, communication protocols, standards, and vulnerabilities while highlighting prevalent solutions to cybersecurity-related issues in them; (2) provides recommendations to enhance the security of these systems by segregating layers of the microgrid, and (3) identifies the gap in research in the area, and suggests directions for future work to enhance the cybersecurity of microgrids.

scholarly journals Special Issue on Field Robotics with Vision Systems

2021 ◽  
Vol 33 (6) ◽  
pp. 1215-1215
Author(s):  
Takanori Fukao ◽  
Yuichi Tsumaki ◽  
Keita Kurashiki
Keyword(s):  
Disaster Response ◽  
Autonomous Driving ◽  
Future Research ◽  
Rapid Progress ◽  
Special Issue ◽  
Vision Systems ◽  
Underwater Robots ◽  
Field Robotics ◽  
Wide Range ◽  
Outdoor Environments

Field robotics has been undergoing rapid progress in recent years. It addresses a wide range of activities performed in outdoor environments, and its applications are being developed in areas where it was previously considered difficult to apply. This rapid progress is largely supported by AI-based improvements in computer vision systems with monocular cameras, stereo cameras, RGB-D cameras, LiDAR systems, and/or other sensors. Field robotics is impelled by an application-driven approach by its nature, and it contributes to the resolution of social problems and the creation of new innovations, including autonomous driving to reduce casualties, autonomous working machines/robots to resolve the problems of labor shortages or dangers, disaster-response robots to aid rescue parties, various kinds of aerial robots to do searches or make deliveries, underwater robots to perform search missions, etc. In this special issue on “Field Robotics with Vision Systems,” we highlight sixteen interesting papers, including one review paper, fourteen research papers, and one development report. They cover various application areas, ranging from underwater to space environments, and they propose interesting integration methods or element technologies to use in outdoor environments where vision systems and robot systems have great difficulty performing robustly. We thank all authors and reviewers, and we hope that this special issue contributes to future research and development in area of field robotics, which promises new innovations.

Preliminary Experimental Study of SMA Knitted Actuation Architectures

Aerospace ◽  
2006 ◽  
Author(s):  
Julianna Evans ◽  
Diann Brei ◽  
Jonathan Luntz
Keyword(s):  
Experimental Study ◽  
Smart Materials ◽  
Material Properties ◽  
Geometric Parameters ◽  
Design Parameters ◽  
Static Force ◽  
Vast Array ◽  
Material Parameters ◽  
Wide Range ◽  
And Control

Nature builds an immense set of materials exhibiting a wide range of behaviors using only a small number of basic compounds. The range of materials comes about through architecture, giving functional structure to the basic materials. Analogously, a new genre of actuators can be derived from existing smart materials through architecture. This paper presents a preliminary experimental study of knitted actuation architectures that yield high strains (up to 73%) with moderate forces (tens of Newtons or more) from basic contracting smart material fibers. By different combinations of the two primary knit loops – purl and knit – a variety of behaviors can be achieved including contraction, rolling, spirals, accordions, arching, and any combination of these across the fabric. This paper catalogs several basic knit stitches and their actuated form: garter, stockinette, seed, rib and I-cord. These knitted architectures provide performance tailorability (force, strain, stiffness, and motion) by manipulation of key design parameters such as the material properties of the wire, the geometric parameters (wire diameter, loop size, and gauge), and architectural parameters (stitch type and orientation). This is demonstrated via a quasi-static force-deflection experimental study with several shape memory alloy garter prototypes with varying geometric parameters. While the basic architecture of a knit is simple, it affords a vast array of architectural combinations and control of geometrical and material parameters that generate a myriad of gross motion capabilities beyond that of current day actuation strategies.

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