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Keyword: Neural networksCan parallelization save the (computing) world?
As all other laws of the growth in computing, the growth of computing performance also shows a ”logistic curve”-like behavior, rather than an unlimited exponential growth. The stalling of the single-processor performance experienced nearly two decades ago forced computer experts to look for alternative methods, mainly for some kind of parallelization. Solving the task needs…
Read MoreAmplitude-Frequency Analysis of Emotional Speech Using Transfer Learning and Classification of Spectrogram Images
Automatic speech emotion recognition (SER) techniques based on acoustic analysis show high confusion between certain emotional categories. This study used an indirect approach to provide insights into the amplitude-frequency characteristics of different emotions in order to support the development of future, more efficiently differentiating SER methods. The analysis was carried out by transforming short 1-second…
Read MoreDesign of smart chess board that can predict the next position based on FPGA
The abilities of human brain to discover solutions for many problems is a great gift that motivate the scientists to develop the revolution of the artificial intelligence and using it in many areas. This paper proposed an intelligent chessboard which works in a way that similar to the human brain that predicts the next positions…
Read MoreHardware Acceleration on Cloud Services: The use of Restricted Boltzmann Machines on Handwritten Digits Recognition
Cloud computing allows users and enterprises to process their data in high performance servers, thus reducing the need for advanced hardware at the client side. Although local processing is viable in many cases, collecting data from multiple clients and processing them in a server gives the best possible performance in terms of processing rate. In…
Read MoreAnalysis of Wireless Traffic Data through Machine Learning
The paper presents an analytical study on a wireless traffic dataset carried out under the different approaches of machine learning including the backpropagation feedforward neural network, the time-series NARX network, the self-organizing map and the principal component analyses. These approaches are well-known for their usefulness in the modeling and in transforming a high dimensional data…
Read MoreMedical imbalanced data classification
In general, the imbalanced dataset is a problem often found in health applications. In medical data classification, we often face the imbalanced number of data samples where at least one of the classes constitutes only a very small minority of the data. In the same time, it represent a difficult problem in most of machine…
Read MoreEvaluation of Three Evaporation Estimation Techniques In A Semi-Arid Region (Omar El Mukhtar Reservoir Sluge, Libya- As a case Study)
In many semi-arid countries in the world like Libya, drinking water supply is dependent on reservoirs water storage. Since the evaporation rate is very high in semi-arid countries, estimates and forecasts of reservoir evaporation rate can be useful in the management of major water source. Many researchers have been investigating the suitability of estimates evaporation…
Read MoreRecent Trends in ELM and MLELM: A review
Extreme Learning Machine (ELM) is a high effective learning algorithm for the single hidden layer feed forward neural networks. Compared with the existing neural network learning algorithm it solves the slow training speed and over-fitting problems. It has been used in different fields and applications such as biomedical engineering, computer vision, remote sensing, chemical process…
Read MoreA Hybrid Approach for Intrusion Detection using Integrated K-Means based ANN with PSO Optimization
Many advances in computer systems and IT infrastructures increases the risks associated with the use of these technologies. Specifically, intrusion into computer systems by unauthorized users is a growing problem and it is very challenging to detect. Intrusion detection technologies are therefore becoming extremely important to improve the overall security of computer systems. In the…
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