scholarly journals Development of a Test-Bench for Evaluating the Embedded Implementation of the Improved Elephant Herding Optimization Algorithm Applied to Energy-Based Acoustic Localization

Computers ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 87
Author(s):  
Sérgio D. Correia ◽  
João Fé ◽  
Slavisa Tomic ◽  
Marko Beko
Keyword(s):  
Real Time ◽  
Test Bench ◽  
High Reliability ◽  
Low Complexity ◽  
Embedded Processor ◽  
Acoustic Localization ◽  
Metaheuristic Methods ◽  
Real Time Applications ◽  
High Level ◽  
Embedded Implementation

The present work addresses the development of a test-bench for the embedded implementation, validity, and testing of the recently proposed Improved Elephant Herding Optimization (iEHO) algorithm, applied to the acoustic localization problem. The implemented methodology aims to corroborate the feasibility of applying iEHO in real-time applications on low complexity and low power devices, where three different electronic modules are used and tested. Swarm-based metaheuristic methods are usually examined by employing high-level languages on centralized computers, demonstrating their capability in finding global or good local solutions. This work considers iEHO implementation in C-language running on an embedded processor. Several random scenarios are generated, uploaded, and processed by the embedded processor to demonstrate the algorithm’s effectiveness and the test-bench usability, low complexity, and high reliability. On the one hand, the results obtained in our test-bench are concordant with the high-level implementations using MatLab® in terms of accuracy. On the other hand, concerning the processing time and as a breakthrough, the results obtained over the test-bench allow to demonstrate a high suitability of the embedded iEHO implementation for real-time applications due to its low latency.

Image Enhancement Techniques Using Particle Swarm Optimization Technique

2015 ◽  
pp. 327-347 ◽  
Author(s):  
V. Santhi ◽  
B. K. Tripathy
Keyword(s):  
Image Processing ◽  
Pattern Recognition ◽  
Particle Swarm Optimization ◽  
Real Time ◽  
Quality Enhancement ◽  
Swarm Optimization ◽  
Image Processing Techniques ◽  
Real Time Applications ◽  
High Level ◽  
Processing Techniques

The image quality enhancement process is considered as one of the basic requirement for high-level image processing techniques that demand good quality in images. High-level image processing techniques include feature extraction, morphological processing, pattern recognition, automation engineering, and many more. Many classical enhancement methods are available for enhancing the quality of images and they can be carried out either in spatial domain or in frequency domain. But in real time applications, the quality enhancement process carried out by classical approaches may not serve the purpose. It is required to combine the concept of computational intelligence with the classical approaches to meet the requirements of real-time applications. In recent days, Particle Swarm Optimization (PSO) technique is considered one of the new approaches in optimization techniques and it is used extensively in image processing and pattern recognition applications. In this chapter, image enhancement is considered an optimization problem, and different methods to solve it through PSO are discussed in detail.

Image Enhancement Techniques Using Particle Swarm Optimization Technique

2015 ◽  
pp. 860-878
Author(s):  
V. Santhi ◽  
B. K. Tripathy
Keyword(s):  
Image Processing ◽  
Pattern Recognition ◽  
Particle Swarm Optimization ◽  
Real Time ◽  
Quality Enhancement ◽  
Swarm Optimization ◽  
Image Processing Techniques ◽  
Real Time Applications ◽  
High Level ◽  
Processing Techniques

The image quality enhancement process is considered as one of the basic requirement for high-level image processing techniques that demand good quality in images. High-level image processing techniques include feature extraction, morphological processing, pattern recognition, automation engineering, and many more. Many classical enhancement methods are available for enhancing the quality of images and they can be carried out either in spatial domain or in frequency domain. But in real time applications, the quality enhancement process carried out by classical approaches may not serve the purpose. It is required to combine the concept of computational intelligence with the classical approaches to meet the requirements of real-time applications. In recent days, Particle Swarm Optimization (PSO) technique is considered one of the new approaches in optimization techniques and it is used extensively in image processing and pattern recognition applications. In this chapter, image enhancement is considered an optimization problem, and different methods to solve it through PSO are discussed in detail.

Model-Driven Engineering, Services and Interactive Real-Time Applications

2014 ◽  
pp. 178-202
Author(s):  
Luis Costa ◽  
Neil Loughran ◽  
Roy Grønmo
Keyword(s):  
Software Engineering ◽  
Language Development ◽  
Real Time ◽  
Software Systems ◽  
Model Driven Engineering ◽  
Model Driven ◽  
Future Developments ◽  
Real Time Applications ◽  
High Level

Model-driven software engineering (MDE) has the basic assumption that the development of software systems from high-level abstractions along with the generation of low-level implementation code can improve the quality of the systems and at the same time reduce costs and improve time to market. This chapter provides an overview of MDE, state of the art approaches, standards, resources, and tools that support different aspects of model-driven software engineering: language development, modeling services, and real-time applications. The chapter concludes with a reflection over the main challenges faced by projects using the current MDE technologies, pointing out some promising directions for future developments.

Model-Driven Engineering, Services and Interactive Real-Time Applications

2011 ◽  
pp. 16-40
Author(s):  
Luis Costa ◽  
Neil Loughran ◽  
Roy Grønmo
Keyword(s):  
Software Engineering ◽  
Language Development ◽  
Real Time ◽  
Software Systems ◽  
Model Driven Engineering ◽  
Model Driven ◽  
Future Developments ◽  
Real Time Applications ◽  
High Level

Model-driven software engineering (MDE) has the basic assumption that the development of software systems from high-level abstractions along with the generation of low-level implementation code can improve the quality of the systems and at the same time reduce costs and improve time to market. This chapter provides an overview of MDE, state of the art approaches, standards, resources, and tools that support different aspects of model-driven software engineering: language development, modeling services, and real-time applications. The chapter concludes with a reflection over the main challenges faced by projects using the current MDE technologies, pointing out some promising directions for future developments.

scholarly journals ITFDS: Channel-Aware Integrated Time and Frequency-Based Downlink LTE Scheduling in MANET

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3394
Author(s):  
Le Minh Tuan ◽  
Le Hoang Son ◽  
Hoang Viet Long ◽  
L. Rajaretnam Priya ◽  
K. Ruba Soundar ◽  
...  
Keyword(s):  
Frequency Domain ◽  
Real Time ◽  
Industry 4.0 ◽  
High Reliability ◽  
Time Interval ◽  
Proportional Fair ◽  
Time Frequency ◽  
Multiple Users ◽  
Real Time Applications ◽  
4G Lte

One of the crucial problems in Industry 4.0 is how to strengthen the performance of mobile communication within mobile ad-hoc networks (MANETs) and mobile computational grids (MCGs). In communication, Industry 4.0 needs dynamic network connectivity with higher amounts of speed and bandwidth. In order to support multiple users for video calling or conferencing with high-speed transmission rates and low packet loss, 4G technology was introduced by the 3G Partnership Program (3GPP). 4G LTE is a type of 4G technology in which LTE stands for Long Term Evolution, followed to achieve 4G speeds. 4G LTE supports multiple users for downlink with higher-order modulation up to 64 quadrature amplitude modulation (QAM). With wide coverage, high reliability and large capacity, LTE networks are widely used in Industry 4.0. However, there are many kinds of equipment with different quality of service (QoS) requirements. In the existing LTE scheduling methods, the scheduler in frequency domain packet scheduling exploits the spatial, frequency, and multi-user diversity to achieve larger MIMO for the required QoS level. On the contrary, time-frequency LTE scheduling pays attention to temporal and utility fairness. It is desirable to have a new solution that combines both the time and frequency domains for real-time applications with fairness among users. In this paper, we propose a channel-aware Integrated Time and Frequency-based Downlink LTE Scheduling (ITFDS) algorithm, which is suitable for both real-time and non-real-time applications. Firstly, it calculates the channel capacity and quality using the channel quality indicator (CQI). Additionally, data broadcasting is maintained by using the dynamic class-based establishment (DCE). In the time domain, we calculate the queue length before transmitting the next packets. In the frequency domain, we use the largest weight delay first (LWDF) scheduling algorithm to allocate resources to all users. All the allocations would be taken placed in the same transmission time interval (TTI). The new method is compared against the largest weighted delay first (LWDF), proportional fair (PF), maximum throughput (MT), and exponential/proportional fair (EXP/PF) methods. Experimental results show that the performance improves by around 12% compared with those other algorithms.

Embedded Implementation of Second-Order Blind Identification (SOBI) for Real-Time Applications in Neuroscience

2014 ◽  
Vol 7 (1) ◽  
pp. 56-63 ◽  
Author(s):  
Xun Zhang ◽  
François-Benoît Vialatte ◽  
Chen Chen ◽  
Apurva Rathi ◽  
Gérard Dreyfus
Keyword(s):  
Real Time ◽  
Second Order ◽  
Blind Identification ◽  
Real Time Applications ◽  
Embedded Implementation

scholarly journals Erratum: Correia, S.D., et al. Development of a Test-Bench for Evaluating the Embedded Implementation of the Improved Elephant Herding Optimization Algorithm Applied to Energy-Based Acoustic Localization. Computers 2020, 9, 87

Computers ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 41
Author(s):  
Sérgio D. Correia ◽  
João Fé ◽  
Slavisa Tomic ◽  
Marko Beko
Keyword(s):  
Optimization Algorithm ◽  
Test Bench ◽  
Acoustic Localization ◽  
The Third ◽  
Embedded Implementation

The third affiliation of the paper should have been completed in our original article [...]

A Double Interaction Brush Model for Snow Conditions

2019 ◽  
Vol 47 (2) ◽  
pp. 118-140
Author(s):  
Artem Kusachov ◽  
Fredrik Bruzelius ◽  
Mattias Hjort ◽  
Bengt J. H. Jacobson
Keyword(s):  
Low Complexity ◽  
Large Set ◽  
Tire Model ◽  
Vehicle Handling ◽  
Real Time Applications ◽  
Snow Conditions ◽  
Double Interaction ◽  
Tire Models ◽  
Force Characteristics ◽  
Model Approach

ABSTRACT Commonly used tire models for vehicle-handling simulations are derived from the assumption of a flat and solid surface. Snow surfaces are nonsolid and may move under the tire. This results in inaccurate tire models and simulation results that are too far from the true phenomena. This article describes a physically motivated tire model that takes the effect of snow shearing into account. The brush tire model approach is used to describe an additional interaction between the packed snow in tire tread pattern voids with the snow road surface. Fewer parameters and low complexity make it suitable for real-time applications. The presented model is compared with test track tire measurements from a large set of different tires. Results suggest higher accuracy compared with conventional tire models. Moreover, the model is also proven to be capable of correctly predicting the self-aligning torque given the force characteristics.

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