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Keyword: LearningUsing Classic Networks for Classifying Remote Sensing Images: Comparative Study
This paper presents a comparative study for using the classic networks in remote sensing images classification. There are four deep convolution models that used in this comparative study; the DenseNet 196, the NASNet Mobile, the VGG 16, and the ResNet 50 models. These learning convolution models are based on the use of the ImageNet pre-trained…
Read MoreInvestment of Classic Deep CNNs and SVM for Classifying Remote Sensing Images
Feature extraction is an important process in image classification for achieving an efficient accuracy for the classification learning models. One of these methods is using the convolution neural networks. The use of the trained classic deep convolution neural networks as features extraction gives a considerable results in the remote sensing images classification models. So, this…
Read MoreReview of Pedagogical Principles of Cyber Security Exercises
Modern digitalized cyber domains are extremely complex ensemble. Cyber attacks or incidents against system may affect capricious effects for another system or even for physical devices. For understanding and training to encounter those effects requires an effective and complex simulation capability. Cyber Security Exercises are an effective expedient for training and learning measures and operations…
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 MoreBayes Classification and Entropy Discretization of Large Datasets using Multi-Resolution Data Aggregation
Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis.…
Read MoreNew Algorithm for the Development of a Musical Words Descriptor for the Artificial Composition of Oriental Music
The Music Composition Library of the great composers constitutes an intellectual heritage. This article introduces an algorithm of artificial Oriental composing music based on the descriptors determined on a large learning base to automatically write Oriental music as the logic identical to any composer. Musical words are called a grammatical alphabet. Each word derived is…
Read MoreEconomic and Environmental Analysis of Life Expectancy in China and India: A Data Driven Approach
A data analytic approach presented in this work covers both data descriptive and predictive modeling with two main objectives: (1) discovering factors related to longevity of populations in the two most populated nations, China and India, and (2) generating life expectancy predictive models for both countries. Descriptive modeling methods to explore major environmental and economic…
Read MoreA Didactic Balance to Solve Equations
Solving equations does not require only to well master the techniques but also to well understand the different underlying concepts and processes. Many of the mistakes made by the students are often due to misinterpretation of the concepts taught, especially the use of letters which the main conceptual obstacle that students have to overcome. We…
Read MoreBISINDO (Bahasa Isyarat Indonesia) Sign Language Recognition Using CNN and LSTM
Sign language is one of the languages which are used to communicate with deaf people. By using it, they can communicate and understand each other. In Indonesia, there are two standards of sign language which are SIBI (Sistem Bahasa Isyarat) and BISINDO (Bahasa Isyarat Indonesia). Deep learning is a model that is used to apply…
Read MoreConvolutional Neural Network Based Classification of Patients with Pneumonia using X-ray Lung Images
Analysis and classification of lung diseases using X-ray images is a primary step in the procedure of pneumonia diagnosis, especially in a critical period as pandemic of COVID-19 that is type of pneumonia. Therefore, an automatic method with high accuracy of classification is needed to perform classification of lung diseases due to the increasing number…
Read MoreFour-Dimensional Sparse Data Structures for Representing Text Data
This paper focuses on a string encoding algorithm, which produces sparse distributed representations of text data. A characteristic feature of the algorithm described here, is that it works without tokenizing the text and can avoid other data preparation steps, such as stemming and lemmatization. The text can be of arbitrary size, whether it is a…
Read MoreThe Ludocreative Expression for the Production of Texts in Children of Early Education
The text’s production carried out in this research aimed to 5-year-old children from the IE 555 Inmaculada Concepción, under the modality dictated to adult, had a design and application of 22 sessions during three months with the experimental group. On their methodological approach was based on the expression ludocreative, articulating the written experience jointly with…
Read MoreEthics as a Motivation Indicator in Second Language Vocational Digital Teaching
The non-selective second language course at vocational colleges and universities makes teachers strive at fostering students’ motivation to learn by choosing from a variety of enhancing factors. Teacher’s personality and skills if they comply with pedagogical ethics are considered to be inspiring for students to learn. The aim of this piloting study was to collect…
Read MoreA Method for Detecting Human Presence and Movement Using Impulse Radar
Using non-invasive and non-contact sensors to measure a person’s presence or movement helps improve the quality of life for both healthy people and patients. In this paper, a method of measuring the presence and motion of a person is proposed by utilizing UWB Impulse Radar, which is low power consumption and safe to radiate to…
Read MoreTowards Classification of Shrimp Diseases Using Transferred Convolutional Neural Networks
Vietnam is one of the top 5 largest shrimp exporters globally, and Mekong delta of Vietnam contributes more than 80% of total national production. Along with intensive farming and growing shrimp farming area, diseases are a severe threat to productivity and sustainable development. Timely response to emerging shrimp diseases is critical. Early detection and treatment…
Read MoreFuzzy Recognition by Logic-Predicate Network
The paper presents a description and justification of the correctness of fuzzy recognition by a logic-predicate network. Such a network is designed to recognize complex structured objects that can be described by predicate formulas. The NP-hardness of such an object recognition requires to separate the learning process, leaving it exponentially hard, and the recognition process…
Read MoreReal-Time Traffic Sign Detection and Recognition System for Assistive Driving
Road traffic accidents are primarily caused by drivers error. Safer roads infrastructure and facilities like traffic signs and signals are built to aid drivers on the road. But several factors affect the awareness of drivers to traffic signs including visual complexity, environmental condition, and poor drivers education. This led to the development of different ADAs…
Read MoreOverview of Solar Radiation Estimation Techniques with Development of Solar Radiation Model Using Artificial Neural Network
Estimation Solar radiation is the most significant part of the optimization of solar power. This may be achieved if the solar radiation is predicted well in advance. Meteorological stations have radiation measuring devices like pyranometer, pyrheliometer, radiometer, solarimeter, etc. however, it may not be available at the location of interest for researchers. Due to this…
Read MoreArtificial Intelligence Approach for Target Classification: A State of the Art
The classification of static or mobile objects, from a signal or an image containing information as to their structure or their form, constitutes a constant concern of specialists in the electronic field. The remarkable progress made in past years, particularly in the development of neural networks and artificial intelligence systems, has further accentuated this trend.…
Read MoreDistributed Microphone Arrays, Emerging Speech and Audio Signal Processing Platforms: A Review
Given ubiquitous digital devices with recording capability, distributed microphone arrays are emerging recording tools for hands-free communications and spontaneous tele-conferencings. However, the analysis of signals recorded with diverse sampling rates, time delays, and qualities by distributed microphone arrays is not straightforward and entails important considerations. The crucial challenges include the unknown/changeable geometry of distributed arrays,…
Read MoreNonlinear \(\ell_{2,p}\)-norm based PCA for Anomaly Network Detection
Intrusion detection systems are well known for their ability to detect internal and external intrusions, it usually recognizes intrusions through learning the normal behaviour of users or the normal traffic of activities in the network. So, if any suspicious activity or behaviour is detected, it informs the users of the network. Nonetheless, intrusion detection system…
Read MoreDynamic Decision-Making Process in the Opportunistic Spectrum Access
We investigate in this paper many problems related to the decision-making process in the Cognitive Radio (CR), where a Secondary User (SU) tries to maximize its opportunities by finding the most vacant channel. Recently, Multi-Armed Bandit (MAB) problems attracted the attention to help a single SU, in the context of CR, makes an optimal decision…
Read MoreIndustry 4.0 Operators: Core Knowledge and Skills
One of the most important technological changes due to the arrival of Industry 4.0, an initial, gradual, and complex process of technology transfer is taking place, which strongly relies on the integration of universities, industries, and governments. In this context, to make the Industry 4.0 approach a reality, several requirements need to be met. One…
Read MoreNearest Neighbour Search in k-dSLst Tree
In the last few years of research and innovations, lots of spatial data in the form of points, lines, polygons and circles have been made available. Traditional indexing methods are not perfect to store spatial data. To search for nearest neighbour is one of the challenges in different fields like spatiotemporal data mining, computer vision,…
Read MoreOntologic Design of Software Engineering Knowledge Area Knowledge Components
The article sets forth the solution of the educational resources semantic context knowledge components development task, based on the learning technology project-oriented concepts, graduate’s competency model and ontological; engineering. The being considered ontology model and knowledge display formalisms allow, firstly, relevantly image the educational resources semantic context in the support concepts ontology format, and their…
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