The data classification method based on support vector machine (SVM) has been widely used in various studies as a non-linear, high precision, and good generalization ability machine learning method. Among them, the kernel function and its parameters ...

For the problems of low decoding accuracy, long decoding time, and low quality of decoded video image in the traditional lossless decoding method of compressed coded video, a lossless decoding method of compressed coded video based on inter frame ...

In order to solve the problems of high distortion rate and low decoding efficiency of the decoded video when the current coding and decoding methods are used to encode and decode the remote video monitoring system, considering the local area network, ...

The growing number of vehicles in a densely populated smart city results in a significant lack of parking space. During the implementation of systems for visibility of parking space vacancies for drivers, the bulk of the systems are focused on ...

With the large-scale deployment of solar PV installations, managing the efficiency of the generation system became essential. Generally, the power output is heavily influenced by solar irradiance and sky conditions which are consistently changing. ...

In this paper, an online self-constructing fuzzy neural network (SCFNN) is proposed to solve four kinds of nonlinear dynamic system identification (NDSI) problems in the internet of things (IoTs). The SCFNN is capable of constructing a simple network ...

Nowadays, medical diseases are one of the primary causes of death, and it is one the major concerns of developed countries. So, the disease identification process needs a lot of attention since if the diseases are idenfied at the early stage, the rate ...

In different periods of time, the real-time reasoning tasks generated by autonomous vehicles are scheduled within the tolerance time, which is an important problem to be solved in autonomous driving. Traditionally, tasks are arranged on the on-board unit ...

Cloud computing is the most developing technology, which allow users to access data, software and IT services. Cloud systems are characterized by the uncertainty of the resources availability. For that reason, its performance is greatly affected by the ...

The outlook for cloud computing is growing day by day. It is a developing field which is evolving and giving new ways to build, manage and process data. The most difficult task in cloud computing is to provide best quality parameters like maintaining ...

In image distortion and low adaptive recognition after medical image compression, a high precision medical image lossless compression algorithm based on discrete wavelet transform is proposed. A 3D imaging model of multi-dimensional medical images is ...

In this paper a Big Data Pipeline is presented, taking in consideration both structured and unstructured data made available by the Italian Ministry of Justice, regarding their Telematic Civil Process. Indeed, the complexity and volume of the data ...

For duplicate image detection, the more advanced large-scale image retrieval systems in recent years have mainly used the Bag-of-Feature ( BoF ) model to meet the real-time. However, due to the lack of semantic information in the training process of ...

In order to improve the quality of service operations, it is necessary to take the initiative to prevent service failures and service performance fluctuations, instead of triggering handlers when service errors occur. Effective prediction and analysis ...

This paper proposes a workload and machine categorization based resource allocation framework for balancing the load across active physical machines as well as utilizing their different resource capacities in a balanced manner. The workload, ...

In recent years, machine learning models have exhibited remarkable performance in the fourth industrial revolution. However, especially in the field of stock forecasting, most of the existing models demonstrate either relatively weak interpretability or ...

Cloud computing can speed up the training process of deep learning models. In this process, training data and model parameters stored in the cloud are prone to threats of being stolen. In model protection, model watermarking is a commonly used method. ...

We address the problem of the optimization of sparse matrix-vector product (SpMV) on homogeneous distributed systems. For this purpose, we propose three approaches based on partitioning the matrix into row blocks. These blocks are defined by a set of ...

Currently, redundant data affects the speed of intrusion detection, many intrusion detection systems (IDS) have low detection rates and high false alert rate. Focusing on these weakness, a new intrusion detection model based on rough set and random ...

Cloud Computing is an IT organization concept that places the Internet at the heart of business activity, allowing it to use hardware resources. In recent years, Load Balancing has been an active area of research, and has played a very important role ...