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Keyword: FeaturesCorrelation-Based Incremental Learning Network for Gas Sensors Drift Compensation Classification
A gas sensor array is used for gas analysis to aid in an inspection. The signals from the sensor array are fed into machine learning models for learning and classification. These signals are characterized by time series fluctuating according to the environment or drift. When an unseen pattern is entered, the classification may be incorrect,…
Read MoreCustomer Satisfaction Recognition Based on Facial Expression and Machine Learning Techniques
Nowadays, Customer satisfaction is important for businesses and organizations. Manual methods exist, namely surveys and distributing questionnaires to customers. However, marketers and businesses are looking for quick ways to get effective and efficient feedback results for their potential customers. In this paper, we propose a new method for facial emotion detection to recognize customer’s satisfaction…
Read MoreApplication of EARLYBREAK for Line Segment Hausdorff Distance for Face Recognition
The Hausdorff distance (HD) is defined as MAX-MIN distance between two geometric objects for measuring the dissimilarity between two objects. Because MAX-MIN distance is sensitive with the outliers, in face recognition field, average Hausdorff distance is used for measuring the dissimilarity between two sets of features. The computational complexity of HD, and also average HD,…
Read MoreThe Sound of Trust: Towards Modelling Computational Trust using Voice-only Cues at Zero-Acquaintance
Trust is essential in many interdependent human relationships. Trustworthiness is measured via the effectiveness of the relationships involving human perception. The decision to trust others is often made quickly (even at zero acquaintance). Previous research has shown the significance of voice in perceived trustworthiness. However, the listeners’ characteristics were not considered. A system has yet…
Read MoreEffects of Oversampling SMOTE in the Classification of Hypertensive Dataset
Hypertensive or high blood pressure is a medical condition that can be driven by several factors. These factors or variables are needed to build a classification model of the hypertension dataset. In the construction of classification models, class imbalance problems are often found due to oversampling. This research aims to obtain the best classification model…
Read MoreComposition of Methods to Ensure Iris Liveness and Authenticity
In a biometric system technology, a person is authenticated based on processing the unique features of the human biometric signs. One of the well known biometric systems is iris recognition, this technique being considered as one of the most secure authentication solutions in the biometric field. However, several attacks do exist that are able to…
Read MoreA Novel Representative k-NN Sampling-based Clustering Approach for an Effective Dimensionality Reduction-based Visualization of Dynamic Data
Visualization plays a crucial role in the exploratory analysis of Big Data. The direct visualization of Big Data is a challenging task and difficult to analyze. Dimensionality Reduction techniques extract the features in the context of visualization. Due to the unsupervised and non-parametric nature, most of the dimensionality reduction techniques are not evaluated quantitatively and…
Read MoreOffline Signature Recognition and Verification Using ORB Key Point Matching Techniques
An extensive work has been carried out in the field of human transcribe-verification and transcribe-recognition by extensive scholars across the globe from past decades. In order to demeanour immense experiments for considering the performance of the newly intended models and to substantiate the efficacy of the proposed model which is moderately required. This paper monologue…
Read MoreRisk Management: The Case of Intrusion Detection using Data Mining Techniques
Every institution nowadays relies on their online system and framework to do businesses. Such procedures need more attention due to the massive amount of attacks that occurs. These procedures have to go first through the management team of the institution, in order to prevent exploits of the attackers. Thus, the risk management can easily control…
Read MoreRacial Categorization Methods: A Survey
Face explicitly provides the direct and quick way to evaluate human soft biometric information such as race, age and gender. Race is a group of human beings who differ from human beings of other races with respect to physical or social attributes. Race identification plays a significant role in applications such as criminal judgment and…
Read MoreANN Based MRAC-PID Controller Implementation for a Furuta Pendulum System Stabilization
Nowadays, process automation and smart systems have gained increasing importance in a wide variety of sectors, and robotics have a fundamental role in it. Therefore, it has attracted greater research interests; among them, Underactuated Mechanical Systems (UMS) have been the subject of many studies, due to their application capabilities in different disciplines. Nevertheless, control of…
Read MoreLow Carbon Sustainable Building Material: Maximizing Slag Potentials for Improved Lime Mortar Mechanical Properties
Prior to the 19th century discovery of Portland Cement (PC), Lime Based Mortar remained popular due to its flexibility, permeability and more importantly, associated low carbon emissions. However, lime’s characteristic delayed setting/hardening time, low mechanical strength, poor internal cohesion and some volumetric changes have overshadowed significance of its outstanding features particularly, flexibility, and consequently put…
Read MoreReview on Smart Electronic Nose Coupled with Artificial Intelligence for Air Quality Monitoring
With the advent of the Internet of Things Technologies (IOT), smart homes, and smart city applications, E-Nose was created. Almost of gas sensors consisting the electronic nose system suffer from cross sensitivity and lack of selectivity. Coupling smart gas sensors with artificial intelligence algorithms can thus empower conventional gas sensing technologies and increase accuracy in…
Read MoreMethodology for Assessing Synchronization Conditions in Telecommunication Devices
This paper represents analysis of principles providing maximally reliable delay estimation of signal synchronization devices in telecommunication. Clock synchronization schemes on the base of stochastic models, graph-analytic interpretation, analytical functional description and their parameters selection in case of real complex hindrance are analyzed. Dependences between dispersion of maximally reliable estimation of synchronization devices and signal…
Read MoreImprovement of the Natural Self-Timed Circuit Tolerance to Short-Term Soft Errors
The paper discusses the features of the implementation and functioning of digital self-timed circuits. They have a naturally high tolerance to short-term single soft errors caused by various factors, such as nuclear particles, radiation, and others. Combinational self-timed circuits using dual-rail coding of signals are naturally immune to 91% of typical soft errors classified in…
Read MoreOntological and Epistemological Issues of Studying the Development of Uzbekistan in the Context of Globalization from the Point of View of the Paradigm of Civilizations
In this scientific work, the basic synergetic principles of the development of the paradigm of civilizations are substantiated, an assessment of the time boundaries within which civilizations exist, the features of their own path of development of Uzbek culture are revealed. It is especially drawn attention to the sociocultural codes of civilization, a combination of…
Read MoreDesign of Efficient Convolutional Neural Module Based on An Improved Module
In order to further improve the feature extraction performance of the convolutional neural networks, we focus on the selection and reorganization of key features and suspect that simple changes in the pooling layers can cause changes in the performance of neural networks. According to the conjecture, we design a funnel convolution module, which can filter…
Read MoreStress Response Index for Traumatic Childhood Experience Based on the Fusion of Hypothalamus Pituitary Adrenocorticol and Autonomic Nervous System Biomarkers
Stress occurring in the early days of an individual was often assumed to cause several health consequences. A number of reports indicated that having to deal with unfavourable events or distress situation at a young age could tweak stress responses leading to a broad spectrum of poor mental and physical health condition. Therefore, changes identified…
Read MoreRouting Protocols for VANETs: A Taxonomy, Evaluation and Analysis
VANET as a subclass of MANET is composed of a set of vehicles equipped with wireless transceivers, to build dynamic networks without the need of any pre-existing infrastructure. Over the last few decades, the area of routing protocols in VANETs has been extensively studied. Nevertheless, this area remains even more challenging due to some features…
Read MoreMultiscale Texture Analysis and Color Coherence Vector Based Feature Descriptor for Multispectral Image Retrieval
Content Based Image Retrieval (CBIR) for remote sensing image data is a tedious process due to high resolution and complexity of image interpretation. Development of feature extraction technique is a major portion to represent the image content in an optimal way. In this paper, we propose a feature descriptor which combines the color coherent pixel…
Read MoreCurrent Trends and Challenges in Link Prediction Methods in Dynamic Social Networks: A Literature Review
In more recent times, researchers have turned their attention to link prediction and the role link inference can play in better understanding the evolutionary nature of social networking sites. The objective of this paper is to present an in-depth review, analysis, and discussion of the cutting-edge link prediction methods that can be applied to better…
Read MoreQuranic Reciter Recognition: A Machine Learning Approach
Recitation and listening of the Holy Quran with Tajweed is an essential activity as a Muslim and is a part of the faith. In this article, we use a machine learning approach for the Quran Reciter recognition. We use the database of Twelve Qari who recites the last Ten Surah of Quran. The twelve Qari…
Read MoreEKMC: Ensemble of kNN using MetaCost for Efficient Anomaly Detection
Anomaly detection aims at identification of suspicious items, observations or events by differing from most of the data. Intrusion Detection, Fault Detection, and Fraud Detection are some of the various applications of Anomaly Detection. The Machine learning classifier algorithms used in these applications would greatly affect the overall efficiency. This work is an extension of…
Read MoreTransmission Line Restoration Using ERS Structure
In the past decades, various ideas have proposed for reconductoring of overhead lines to enhance power transmission capacity considering growing energy demand. Conventional method of reconductoring is use to take couple of weeks but availability of shutdown for a prolong period is a major constraint in line uprating. Emergency restoration structure (ERS) is effective to…
Read MoreEstimating Academic results from Trainees’ Activities in Programming Exercises Using Four Types of Machine Learning
Predicting trainees’ final academic results in the early stage of programming class is a significant mission in the field of learning analytics. Performing exercises in programming class is hard and it takes a lot of time for trainees. For this reason, careful support with trainees are offered in many classes through classroom assistants (CAs). Even…
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