scholarly journals Distributed Cooperative Jamming with Neighborhood Selection Strategy for Unmanned Aerial Vehicle Swarms

Electronics ◽  
2022 ◽  
Vol 11 (2) ◽  
pp. 184
Author(s):  
Yongkun Zhou ◽  
Dan Song ◽  
Bowen Ding ◽  
Bin Rao ◽  
Man Su ◽  
...  
Keyword(s):  
Large Scale ◽  
State Transition ◽  
Selection Strategy ◽  
Cooperative Jamming ◽  
Proposed Model ◽  
Neighborhood Selection ◽  
Aerial Vehicle ◽  
Ca Model ◽  
And Performance ◽  
Better Than

In system science, a swarm possesses certain characteristics which the isolated parts and the sum do not have. In order to explore emergence mechanism of a large–scale electromagnetic agents (EAs), a neighborhood selection (NS) strategy–based electromagnetic agent cellular automata (EA–CA) model is proposed in this paper. The model describes the process of agent state transition, in which a neighbor with the smallest state difference in each sector area is selected for state transition. Meanwhile, the evolution rules of the traditional CA are improved, and performance of different evolution strategies are compared. An application scenario in which the emergence of multi–jammers suppresses the radar radiation source is designed to demonstrate the effect of the EA–CA model. Experimental results show that the convergence speed of NS strategy is better than those of the traditional CA evolution rules, and the system achieves effective jamming with the target after emergence. It verifies the effectiveness and prospects of the proposed model in the application of electronic countermeasures (ECM).

scholarly journals Overview of road performance on the tsunami evacuation road during the n-COVID19 pandemic

2021 ◽  
Vol 331 ◽  
pp. 06006
Author(s):  
Yossyafra ◽  
Anyta Ramadhani ◽  
Vina Gusman ◽  
Monica Herimarni
Keyword(s):  
Large Scale ◽  
New Normal ◽  
Tsunami Disaster ◽  
Traffic Conditions ◽  
Normal Period ◽  
Road Performance ◽  
And Performance ◽  
Traffic Disturbance ◽  
The City ◽  
Better Than

The COVID-19 pandemic has changed the world in various sectors and human activities. Limiting human activity and mobility also has an impact on transportation and traffic. This study aims to calculate the capacity and performance of roads under normal pandemic conditions before PSBB (Large-Scale Social Restrictions) in April 2020 and New Normal in July 2002, as well as predict traffic conditions if the Tsunami disaster hits the city during both periods. Tsunami Evacuation roads in Padang City were selected for analysis. The Indonesian Road Capacity Manual 1997 on urban roads is used as a reference for analyzing road performance indicators. The results showed that; road performance during the PSBB period was better than the New Normal period. The effect of volume and side traffic disturbance factors in the New Normal period makes a significant decrease in performance. Through prediction simulations, if a Tsunami occurs in the two study periods, the analyzed roads can relatively serve evacuation movements. However, the capacity needs to be increased for normal conditions.

Enhancing the Security and Performance of Cloud for E-Governance Infrastructure

2022 ◽  
Vol 12 (1) ◽  
pp. 0-0
Keyword(s):  
Large Scale ◽  
Governance System ◽  
Readiness Assessment ◽  
Cloud Data ◽  
Governance Model ◽  
Proposed Model ◽  
And Performance ◽  
Governance Infrastructure ◽  
Hashing Function ◽  
Distributed Infrastructure

E-Governance is getting momentous in India. Over the years, e-Governance has played a major part in every sphere of the economy. In this paper, we have proposed E-MODI (E-governance model for open distributed infrastructure) a centralized e-Governance system for government of India, the implementation of this system is technically based on open distributed infrastructure which comprises of various government bodies in one single centralized unit. Our proposed model identifies three different patterns of cloud computing which are DGC, SGC and CGC. In addition, readiness assessment of the services needs to migrate into cloud. In this paper, we propose energy efficient VM allocation algorithm to achieve higher energy efficiency in large scale cloud data centers when system on optimum mode. Our objectives have been explained in details and experiments were designed to demonstrate the robustness of the multi-layered security which is an integration of High secure lightweight block cipher CSL along with Ultra powerful BLAKE3 hashing function in order to maintain information security triad.

scholarly journals Antonym-Synonym Classification Based on New Sub-Space Embeddings

2019 ◽  
Vol 33 ◽  
pp. 6204-6211
Author(s):  
Muhammad Asif Ali ◽  
Yifang Sun ◽  
Xiaoling Zhou ◽  
Wei Wang ◽  
Xiang Zhao
Keyword(s):  
Large Scale ◽  
Semantic Information ◽  
Relation Extraction ◽  
Specific Information ◽  
Lexical Semantic ◽  
Word Level ◽  
Novel Approach ◽  
Proposed Model ◽  
Low Performance ◽  
And Performance

Distinguishing antonyms from synonyms is a key challenge for many NLP applications focused on the lexical-semantic relation extraction. Existing solutions relying on large-scale corpora yield low performance because of huge contextual overlap of antonym and synonym pairs. We propose a novel approach entirely based on pre-trained embeddings. We hypothesize that the pre-trained embeddings comprehend a blend of lexical-semantic information and we may distill the task-specific information using Distiller, a model proposed in this paper. Later, a classifier is trained based on features constructed from the distilled sub-spaces along with some word level features to distinguish antonyms from synonyms. Experimental results show that the proposed model outperforms existing research on antonym synonym distinction in both speed and performance.

scholarly journals Distant Supervision for Relation Extraction with Sentence Selection and Interaction Representation

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Tiantian Chen ◽  
Nianbin Wang ◽  
Hongbin Wang ◽  
Haomin Zhan
Keyword(s):  
Large Scale ◽  
Semantic Information ◽  
State Of The Art ◽  
Relation Extraction ◽  
Semantic Features ◽  
Distant Supervision ◽  
Word Level ◽  
Proposed Model ◽  
Relation Prediction ◽  
Better Than

Distant supervision (DS) has been widely used for relation extraction (RE), which automatically generates large-scale labeled data. However, there is a wrong labeling problem, which affects the performance of RE. Besides, the existing method suffers from the lack of useful semantic features for some positive training instances. To address the above problems, we propose a novel RE model with sentence selection and interaction representation for distantly supervised RE. First, we propose a pattern method based on the relation trigger words as a sentence selector to filter out noisy sentences to alleviate the wrong labeling problem. After clean instances are obtained, we propose the interaction representation using the word-level attention mechanism-based entity pairs to dynamically increase the weights of the words related to entity pairs, which can provide more useful semantic information for relation prediction. The proposed model outperforms the strongest baseline by 2.61 in F1-score on a widely used dataset, which proves that our model performs significantly better than the state-of-the-art RE systems.

scholarly journals LONG-TERM VISUAL LOCALIZATION IN LARGE SCALE URBAN ENVIRONMENTS EXPLOITING STREET LEVEL IMAGERY

2020 ◽  
Vol V-2-2020 ◽  
pp. 57-63
Author(s):  
J. Meyer ◽  
D. Rettenmund ◽  
S. Nebiker
Keyword(s):  
Large Scale ◽  
3D Structure ◽  
Urban Environments ◽  
Visual Localization ◽  
Street Level ◽  
Reference Images ◽  
And Performance ◽  
Localization Approach ◽  
Better Than

Abstract. In this paper, we present our approach for robust long-term visual localization in large scale urban environments exploiting street level imagery. Our approach consists of a 2D-image based localization using image retrieval (NetVLAD) to select reference images. This is followed by a 3D-structure based localization with a robust image matcher (DenseSfM) for accurate pose estimation. This visual localization approach is evaluated by means of the ‘Sun’ subset of the RobotCar seasons dataset, which is part of the Visual Localization benchmark. As the results on the RobotCar benchmark dataset are nearly on par with the top ranked approaches, we focused our investigations on reproducibility and performance with own data. For this purpose, we created a dataset with street-level imagery. In order to have independent reference and query images, we used a road-based and a tram-based mapping campaign with a time difference of four years. The approximately 90% successfully oriented images of both datasets are a good indicator for the robustness of our approach. With about 50% success rate, every second image could be localized with a position accuracy better than 0.25 m and a rotation accuracy better than 2°.

Motivational dynamics underlying competition

2021 ◽  
Author(s):  
Kou Murayama ◽  
Andrew J. Elliot ◽  
Mickaël Jury
Keyword(s):  
Empirical Evidence ◽  
Theoretical Perspectives ◽  
Proposed Model ◽  
And Performance ◽  
Approach Goals ◽  
Avoidance Goals ◽  
Instrumental Role ◽  
Better Than

The chapter delineates motivational mechanisms underlying how competition affects performance. The authors propose an opposing processes model of competition and performance in which competition positively influences performance via the adoption of performance-approach goals (i.e., trying to do better than others), whereas competition impairs performance via the adoption of performance-avoidance goals (i.e., trying to avoid doing worse than others). In competitions, these positive and negative goal processes often cancel each other out, producing a seemingly weak or non-existent relationship between competition and performance. The authors review empirical evidence for the proposed model, discuss the implications of the model in relation to other theoretical perspectives on competition, and speculate on the possibility that competition can play an instrumental role in sustainable engagement in a task.

The Influence of Cognitive and Affective Reactions to Feedback on Subsequent Goals

2010 ◽  
Vol 15 (2) ◽  
pp. 121-131 ◽  
Author(s):  
Remus Ilies ◽  
Timothy A. Judge ◽  
David T. Wagner
Keyword(s):  
Performance Feedback ◽  
Business School ◽  
Structural Equation ◽  
Emotional Reactions ◽  
Equation Model ◽  
Proposed Model ◽  
And Performance ◽  
Dispositional Measure ◽  
The Relationship ◽  
Reactions To Feedback

This paper focuses on explaining how individuals set goals on multiple performance episodes, in the context of performance feedback comparing their performance on each episode with their respective goal. The proposed model was tested through a longitudinal study of 493 university students’ actual goals and performance on business school exams. Results of a structural equation model supported the proposed conceptual model in which self-efficacy and emotional reactions to feedback mediate the relationship between feedback and subsequent goals. In addition, as expected, participants’ standing on a dispositional measure of behavioral inhibition influenced the strength of their emotional reactions to negative feedback.

Application Fuzzy Logic System for Accurate Sheet Trim Shower Position

2019 ◽  
Vol 3 (1) ◽  
pp. 186-192
Author(s):  
Yudi Wibawa
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Dc Motor ◽  
Automation System ◽  
Paper Making ◽  
System A ◽  
Accurate Position ◽  
And Performance ◽  
Better Than ◽  
Logic System

This paper aims to study for accurate sheet trim shower position for paper making process. An accurate position is required in an automation system. A mathematical model of DC motor is used to obtain a transfer function between shaft position and applied voltage. PID controller with Ziegler-Nichols and Hang-tuning rule and Fuzzy logic controller for controlling position accuracy are required. The result reference explains it that the FLC is better than other methods and performance characteristics also improve the control of DC motor.

An Analytical Transient Tire Model

2001 ◽  
Vol 29 (2) ◽  
pp. 108-132 ◽  
Author(s):  
A. Ghazi Zadeh ◽  
A. Fahim
Keyword(s):  
Transient Behavior ◽  
Stability Control ◽  
Vehicle Stability ◽  
Tire Model ◽  
Steering Angle ◽  
First Order ◽  
Vehicle Stability Control ◽  
Proposed Model ◽  
Depth Study ◽  
And Performance

Abstract The dynamics of a vehicle's tires is a major contributor to the vehicle stability, control, and performance. A better understanding of the handling performance and lateral stability of the vehicle can be achieved by an in-depth study of the transient behavior of the tire. In this article, the transient response of the tire to a steering angle input is examined and an analytical second order tire model is proposed. This model provides a means for a better understanding of the transient behavior of the tire. The proposed model is also applied to a vehicle model and its performance is compared with a first order tire model.

Model and Method for Contributor’s Quality Assessment in Community Image Tagging Systems

2018 ◽  
pp. 45-51
Author(s):  
A. V. Ponomarev
Keyword(s):  
Large Scale ◽  
Wide Spectrum ◽  
Preference Relation ◽  
Pairwise Comparison ◽  
Ground Truth ◽  
Comparison Method ◽  
Characteristic Matrix ◽  
Image Tagging ◽  
Proposed Model

Introduction: Large-scale human-computer systems involving people of various skills and motivation into the information processing process are currently used in a wide spectrum of applications. An acute problem in such systems is assessing the expected quality of each contributor; for example, in order to penalize incompetent or inaccurate ones and to promote diligent ones.Purpose: To develop a method of assessing the expected contributor’s quality in community tagging systems. This method should only use generally unreliable and incomplete information provided by contributors (with ground truth tags unknown).Results:A mathematical model is proposed for community image tagging (including the model of a contributor), along with a method of assessing the expected contributor’s quality. The method is based on comparing tag sets provided by different contributors for the same images, being a modification of pairwise comparison method with preference relation replaced by a special domination characteristic. Expected contributors’ quality is evaluated as a positive eigenvector of a pairwise domination characteristic matrix. Community tagging simulation has confirmed that the proposed method allows you to adequately estimate the expected quality of community tagging system contributors (provided that the contributors' behavior fits the proposed model).Practical relevance: The obtained results can be used in the development of systems based on coordinated efforts of community (primarily, community tagging systems). 

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