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Keyword: GradientDeep Deterministic Policy Gradients for Optimizing Simulated PoA Blockchain Networks Based on Healthcare Data Characteristics
Blockchain technology has proven to be the best solution for digital data storage today, which is decentralized and interconnected via cryptography. Many consensus algorithms can be options for implementation. One of them is the PoA consensus algorithm, which is proven to provide high performance and fault tolerance. Blockchain has been implemented in many sectors, including…
Read MoreReal-time Gradient-Aware Indigenous AQI Estimation IoT Platform
Environmental monitoring has gained significant importance in outdoor air quality measurement and assessment for fundamental survival as well as ambient assisted living. In real-time outdoor urban scale, instantaneous air quality index estimation, the electrochemical sensors warm-up time, cross-sensitivity computation-error, geo-location typography, instantaneous capacity or back up time; and energy efficiency are the six major challenges.…
Read MoreMalware Classification Using XGboost-Gradient Boosted Decision Tree
In this industry 4.0 and digital era, we are more dependent on the use of communication and various transaction such as financial, exchange of information by various means. These transaction needs to be secure. Differentiation between the use of benign and malware is one way to make these transactions secure. We propose in this work…
Read MoreMulti-Objective Optimization when Surface Grinding the 3X13 Steel by Combining the General Reduced Gradient Algorithm and Harmonic Mean Method
In this paper, the multi-objective optimization process was applied for the surface grinding process of 3X13 steel using an aluminum oxide grinding wheel (WA46J7V1A). For each experiment, three cutting parameters, including the workpiece velocity, feed rate, and the depth of cut, were controlled to change according to the experimental matrix. At each experiment, surface roughness…
Read More\(L^\infty\)-Estimates for Nonlinear Degenerate Elliptic Problems with p-growth in the Gradient
In this work, we will prove the existence of bounded solutions for the nonlinear elliptic equations \(- div(a(x,u,\nabla u)) = g(x,u,\nabla u) -divf,\) in the setting of the weighted Sobolev space \(W^{1,p}(\Omega,w)\) where \(a\), \(g\) are Caratheodory functions which satisfy some conditions and \(f\) satisfies suitable summability assumption.
Read MoreBoundary gradient exact enlarged controllability of semilinear parabolic problems
The aim of this paper is to study the boundary enlarged gradient controllability problem governed by parabolic evolution equations. The purpose is to find and compute the control \(u\) which steers the gradient state from an initial gradient one \(\nabla y_{_{0}}\) to a gradient vector supposed to be unknown between two defined bounds \(b_1\) and…
Read MoreAn Ensemble Learning Approach for Student Performance Analysis of a Higher Educational Institute using a SHAP-Based Feature Selection and Optuna Optimization
Forecasting and assessing student performance are crucial for allowing educators to pinpoint deficiencies and promote grade improvement. A thorough comprehension of feature contributions is crucial for improving model interpretability and facilitating informed decision-making in academic institutions. Explainable artificial intelligence encompasses methodologies and strategies designed to deliver transparent and accessible rationales for the decisions rendered by…
Read MoreUtilizing 3D models for the Prediction of Work Man-Hour in Complex Industrial Products using Machine Learning
The integration of machine learning techniques in industrial production has the potential to revolutionize traditional manufacturing processes. In this study, we examine the efficacy of gradient-boosting machine learning models, specifically focusing on feature engineering techniques, applied to a novel dataset with 3D product models pertaining to work moan-hours in metal sheet stamping projects, framed as…
Read MoreDevelopment of an Intelligent Road Anomaly Detection System for Autonomous Vehicles
Globally, road transportation has become one of the most reliable means of moving goods and services from one place to the other. It has contributed immensely to the standard of living and modern civilization. However, this means of transportation is characterised by some issues which are poised to be harmful to the human population if…
Read MoreBirds Images Prediction with Watson Visual Recognition Services from IBM-Cloud and Conventional Neural Network
Bird watchers and people obsessed with raising and taming birds make a kind of motivation about our subject. It consists of the creation of an Android application called ”Birds Images Predictor” which helps users to recognize nearly 210 endemic bird species in the world. The proposed solution compares the performance of the python script, which…
Read MoreRegular Tessellation-Based Collective Movement for a Robot Swarm with Varying Densities, Scales, and Shapes
In complex swarm robotic applications that perform different tasks such as transportation and observation, robot swarms should construct and maintain a formation to adapt and move as a single large-scale robot. For example, transportation and observation tasks require unique robot swarms with either high densities to support the weight of the transported objects or low…
Read MoreA New Topology Optimization Approach by Physics-Informed Deep Learning Process
In this investigation, an integrated physics-informed deep learning and topology optimization approach for solving density-based topology designs is presented to accomplish efficiency and flexibility. In every iteration, the neural network generates feasible topology designs, and then the topology performance is evaluated using the finite element method. Unlike the data-driven methods where the loss functions are…
Read MoreEfficient 2D Detection and Positioning of Complex Objects for Robotic Manipulation Using Fully Convolutional Neural Network
Programming industrial robots in a real-life environment is a significant task necessary to be dealt with in modern facilities. The “pick up and place” task is undeniably one of the regular robot programming problems which needs to be solved. At the beginning of the “pick and place” task, the position determination and exact detection of…
Read MoreConvolutional Neural Network Based on HOG Feature for Bird Species Detection and Classification
This work is concerned with the detection and classification of birds that have applications like monitoring extinct and migrated birds. Recent computer vision algorithms can precise this kind of task but still there are some dominant issues like low light, very little differences between subspecies of birds, etc are to be studied. As Convolution Neural…
Read MoreArtificial Neural Network Approach using Mobile Agent for Localization in Wireless Sensor Networks
Wireless sensor networks (WSNs) are having large demands in enormous applications for the decade. The main issue in WSNs is estimating the exact location of unknown nodes. All applications are dependent on the location information of unknown nodes in WSNs. Location information of mobile anchor node is used to estimate the location of unknown nodes.…
Read MoreOptimal Hydrokinetic Turbine Array Placement in Asymmetric Quasigeostrophic Flows
The Coriolis force in the ocean at mid to high latitudes can cause significant deviation of flow over bottom topography, including formation of Taylor columns. Structures in a tidal zone will experience zero inertial current between every tidal change. Around periods of directional change, the Coriolis force may be tapped into for energy. Factors like…
Read MoreStochastic Behaviour Analysis of Adaptive Averaging Step-size Sign Normalised Hammerstein Spline Adaptive Filtering
We introduce a sign algorithm based on the normalised least mean square with Hammerstein adaptive filtering using adaptive averaging step-size mechanism, which is derived by the minimised absolute a posteriori squared error. To improve the performance by reducing computational complexity, we suggest an adaptive averaging using energy of errors to update step-size variant. The analysis…
Read MoreExtending the Classifier Algorithms in Machine Learning to Improve the Performance in Spoken Language Understanding Systems Under Deficient Training Data
One of the open domain challenges for Spoken Dialogue System (SDS) is to maintain a natural conversation for rarely visited domain i.e. domain with fewer data. Spoken Language Understanding (SLU) is a component of SDS that converts user utterance into a semantic form that a computer can understand. If we scale SDS open domain challenge…
Read MoreA Circular Invariant Convolution Model-Based Mapping for Multimodal Change Detection
The large and ever-increasing variety of remote sensing sensors used in satellite imagery today explains why detecting changes between identical locations in images that are captured, at two separate times, from heterogeneous capturing systems is a major and challenging recent research problem in the field of satellite imaging for fast and accurate determination of temporal…
Read MoreA User-Item Collaborative Filtering System to Predict Online Learning Outcome
Education has seen the rapid development of online learning. Many researchers have conducted studies on the use of recommendation systems in online learning. However, until now, several similar studies still focus on the accuracy of the prediction results. Various obstacles were encountered related to changes in the face to face learning process into online learning.…
Read MorePredictive Modelling of Student Dropout Using Ensemble Classifier Method in Higher Education
Currently, one of the challenges of educational institutions is drop-out student issues. Several factors have been found and determined potentially capable to stimulate dropouts. Many researchers have been applied data mining methods to analyze, predict dropout students and also optimize finding dropout variables in advance. The main objective of this study is to find the…
Read MoreHybrid Technique for Enhancing Underwater Image in blurry conditions
Enhancing underwater visualization using hybrid technique is generally employed into oceanic production. Through growing oceanic learning, undersea processing has drawn extra importance owing towards necessary task of picture towards attaining data. Although, suitable to reality of dust-like constituent and beam reduction, undersea descriptions continually experience small contrast and color alteration. In this paper, we estimate…
Read MoreModified HOG Descriptor-Based Banknote Recognition System
This survey paper deals with the structural health monitoring systems on the basis of methodologies involving intelligent techniques. The intelligent techniques are the most popular tools for damage identification in terms of high accuracy, reliable nature and the involvement of low cost. In this critical survey, a thorough analysis of various intelligent techniques is carried…
Read MoreUse of machine learning techniques in the prediction of credit recovery
This paper is an extended version of the paper originally presented at the International Conference on Machine Learning and Applications (ICMLA 2016), which proposes the construction of classifiers, based on the application of machine learning techniques, to identify defaulting clients with credit recovery potential. The study was carried out in 3 segments of a Bank’s…
Read MoreAssessment of the heat sinking effect of a human hand that holds a flexible phototherapy device for use in Kangaroo Mother Care
The heat transfer process from a 6.4 Watt blue light flexible phototherapy mattress to a human hand has been studied. The intended use of the mattress is the provision of neonatal jaundice phototherapy during Kangaroo Mother Care (KMC) or skin-to-skin care. The heat transfer process has been studied with temperature and heat flow sensors inside…
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