Abstract Current Conditional Functional Dependency (CFD) discovery algorithms always need a well-prepared training dataset. This condition makes them difficult to apply on large and low-quality datasets. To handle the volume […]
Mining conditional functional dependency rules on big data Read More »
Abstract In order to analyze the big data of people’s livelihood appeal, this paper proposes a time series modeling and algorithm to decompose the time series {x(t)} of data into
Abstract With the explosive growth of the Internet of Things (IoT) using WiFi networks along with their huge data flows (especially Bigdata using TCP connections), the significant challenges are the
Policy-based Bigdata Security and QoS Framework for SDN/IoT: An Analytic Approach Read More »
![Coordination between control layer AI and on-board AI in optical transport networks [Invited]](https://ksra.fr/wp-content/uploads/2020/08/Artificial-Superintelligence-In-Control-300x279.jpg)
Abstract In optical transport networks, the urgent demand for control efficiency and intelligence has become one of the most significant challenges for telecom operators. With the development in control technology,
Abstract Internet of Things (IoT) is a communication paradigm that connects devices and objects in order to harvest and process data produced by several edge devices [1]. It is predicting
An Overview of AI-Enabled Remote Smart- Home Monitoring System Using LoRa Read More »
Abstract This article introduces a time-domain-based artificial intelligence (AI) radar system for gesture recognition using 33-GS/s direct sampling technique. High-speed sampling using a time-extension method allows AI learning to be
Abstract As it is known, in today’s world gross domestic product (GDP) determines the prosperity of a nation. Agriculture directly adds to the GDP, subsequently, incredible endeavors are to be
Classification of Grape Leaves using KNN and SVM Classifiers Read More »
Abstract Rotating machinery fault diagnosis problems have been well-addressed when sufficient supervised data of the tested machine are available using the latest data-driven methods. However, it is still challenging to
Diagnosing Rotating Machines With Weakly Supervised Data Using Deep Transfer Learning Read More »
Abstract Machine learning has been pervasively used in a wide range of applications due to its technical breakthroughs in recent years. It has demonstrated significant success in dealing with various
Machine Learning Security: Threats, Countermeasures, and Evaluations Read More »
Abstract Optimizing the hyper-parameters of a multi-layer perceptron (MLP) artificial neural network (ANN) is not a trivial task, and even today the trial-and-error approach is widely used. Many works have
Extending MLP ANN hyper-parameters Optimization by using Genetic Algorithm Read More »
