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For the sake of improving the precision of speech emotion recognition, this paper proposed a novel speech emotion recognition approach based on Gaussian Kernel Nonlinear Proximal Support Vector Machine (PSVM) to recognize four basic human emotions (angry, joy, sadness, surprise). Firstly, preprocess speech signal containing sampling, quantification, pre-emphasizing, framing, adding window and endpoint...
Remote server vulnerability exploit is one of the most troublesome threat to the Internet security. An effective defense against the remote vulnerability exploit is code randomization, which randomizes the program code address to disrupt the malicious payload execution. Unfortunately, code randomization is particularly susceptible to address exposure vulnerabilities; the leak of a single code or data...
In wireless hostile environments such as tunnels, tall buildings, undergrounds and dense vegetation where Global Positioning System (GPS) signals can be unavailable, vehicles are prevented from exchanging accurate positions. Hence critical information may be lost or misled. To overcome these limitations, this paper proposes an innovative technique for localization estimation called SuPRANO, a Semi-suPervised...
This article discusses the general structure of the CNC control system with the Soft PLC module which was implemented as an external unit. The advantages of reducing the EtherCAT cycle, increasing control system reliability and disadvantages associated with the additional cost of the proposed solution were investigated. The proposed solution also uses the external Soft PLC instead of the safety controller...
Dirty Copy on Write (COW) vulnerability, discovered by Phil Oester on October 2016, it is a serious vulnerability which could escalate unprivileged user to gain full control on devices (Computers, Mobile Smart Phones, Gaming devices that run Linux based operating systems). This means that any user who exploits this bug, would escalate his/her privileges; and can do anything either locally or remotely...
Nowadays high performance computers (HPC) are used to solve increasingly complex problems and process larger amounts of data. The growing computational requirements of applications can be met by utilizing more compute nodes. However, the average I/O performance a compute node can utilize is reduced with increased number of nodes. The performance gap between computation and I/O has long been a primary...
We compare the performance of pipelined and s-step GMRES, respectively referred to as l-GMRES and s-GMRES, on distributed multicore CPUs. Compared to standard GMRES, s-GMRES requires fewer all-reduces, while l-GMRES overlaps the all-reduces with computation. To combine the best features of two algorithms, we propose another variant, (l, t)-GMRES, that not only does fewer global all-reduces than standard...
Growing concerns about increasing world population and limited food resources have been leading researchers to utilize advanced computing technology to improve the efficiency of agricultural fields. Computing technology is expected to increase the productivity, contribute to a better understanding of the relationship between environmental factors and healthy crops, reduce the labor costs for farmers...
Today the technology advancement in communication technology permits a malware author to introduce code obfuscation technique, for example, Application Programming Interface (API) hook, to make detecting the footprints of their code more difficult. A signature-based model such as Antivirus software is not effective against such attacks. In this paper, an API graph-based model is proposed with the...
Recent progress in Thermal and infrared Non-Destructive Testing (IRNDT) in different fields have provided interesting defect detection solutions. Principal Component Analysis (PCA) based K-means clustering have been successfully introduced and used in many clustering applications. However, PCA suffers from being relatively more sensitive to the noise due to having a linear transformation. On the other...
Sparsity in the weights of deep convolutional networks presents a tremendous opportunity to reduce computational requirements. In order to optimize flow of traffic systems, any viable solution must be able to operate at real-time. Existing computation frameworks do not yet realize the full potential speedup afforded by sparse neural networks. Meanwhile, the power consumption for a GPU is too great...
Extreme machine learning and its variants have shown good generalization performance and high leaning speed in many applications through its fast convergence. Despite the parallel and distributed ELM on MapReduce framework able to handle very large scale dataset for bigdata applications, the process of coping up with the rapidly updating data is a challenging one. Among the unified algorithms, the...
As computer systems increase in size and complexity, bugs become ever subtler and more difficult to detect and diagnose. A bug could exist at different layers of computer systems (e.g., applications, shared libraries, file systems, device firmware), or could be caused by the incompatibility among layers. In many cases, bugs would require a very specific combination of events to be triggered and are...
Attacks on an operating system kernel using kernel rootkits pose a particularly serious threat. Detecting an attack is difficult when the operating system kernel is infected with a kernel rootkit. For this reason, handling an attack will be delayed causing an increase in the amount of damage done to a computer system. In this paper, we discuss KRGuard (Kernel Rootkits Guard), which is a new method...
Future avionics is no longer mere close electronic systems with the requirement changed, while it is pervasively controlled by dozens of frequent information exchange, open architecture and highly automatic systems. And this transformation has driven major advancements of security in avionics which contains computing security and communication security. Our team is focused on the security of next...
Successful software is often enhanced and adapted to the needs of new users. During evolution, a software system grows in size, becomes more complex, and costly to maintain. In this paper, we point to big clones—large granular duplicated program structures such as files or directories—as one of many reasons why this happens. Using the Linux kernel as an example, we show that big clones arise in the...
Performance of the PLASMA dense symmetric Eigensolver is optimized for large shared memory computer systems using multiple Householder domains for dense to band reduction and a communication reducing kernel for bulge chasing. The mr3-smp code by Petschow and Bientinesi is used for the tridiagonal eigensolution and the eigenvector back-transformations employ a 1D parallel decomposition. The input matrix,...
The element-by-element computation used in matrix-vector multiplications is the key kernel for attaining highperformance in unstructured implicit low-order finite-element earthquake simulations. We accelerate this CPU-based elementby-element kernel by developing suitable algorithms for GPUs and porting to a GPU-CPU heterogeneous compute environment by OpenACC. Other parts of the earthquake simulation...
The state-of-the-art image classification methods require an intensive learning stage and a considerable amount of training images. Recently, with the introduction of these models (and in particular convolutional neural network (CNN)), it is believed that the best solution to achieve a system with high performance on scene classification is to learn deep scene features using CNN. While this can be...
Online social media networks play important roles for people to share opinions, communicate with others. One of important features behind these activities is trust. This paper investigates the trust model in Online social media networks. Considering the interaction between two users and the reputation in the social networks, this trust model gives a definition about the trust value between two users...
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