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Because the use of 60-W incandescent lamps is declining in parts of the world, voltage fluctuations' effects on other devices may need to be explicitly considered in international standards. The existence of international standards for measuring interharmonics and the mathematical relationship with periodic amplitude modulation has suggested interharmonics as a potential basis for broadly characterizing...
Based on the method of latent semantic analysis (LSA), a text matching algorithm was proposed in this paper for constructing an automated scoring system of Chinese test papers. Firstly, by fully considering the correlation between terms, texts of examinee's answers and standard answers were represented in lower-dimensional space and the model was improved using the way of singular value decomposition...
With the increasing scale and complexity of the network, how to maintain a level of network performance and robustness for network operators to satisfy customers becomes more and more challenging. Network anomaly detection and localization are critical for ensuring network performance. In this paper, a novel framework for detecting and localizing network anomalies using active measurements is presented...
Most of the existing quantum key distribution protocols do not consider the fact that the source and measuring device cannot be trusted, which causes hidden danger, such as the side channel attack, resulting in unsafe quantum communication. Therefore, it is important to research quantum key distribution protocol under the conditions of non-trusted device. We show a quantum key distribution protocol...
The ECG signal, has attracted more attention due to its importance in diagnosing conditions. Now days T-wave alternans (TWA) has been used to forecast Sudden Cardiac death (SCD). TWA is the beat-to-beat alterations changing in the T-wave amplitude. A new method is used in this paper to detect these alternans waves more exactly and quickly with heart rate calculation by RR-interval in ECG. This algorithm...
Illumination condition is one of the most important factors that affect the face recognition performance. Face image illumination quality assessment can predict the face recognition performance under various illumination conditions, which will improve the accuracy and efficiency of the face recognition system. However, the quality scores calculated by the existing methods are weakly correlated with...
We introduce a new algorithm that maps multiple instance data using both positive and negative target concepts into a data representation suitable for standard classification. Multiple instance data are characterized by bags which are in turn characterized by a variable number of feature vectors or instances. Each bag has a known positive or negative label, but the labels of any given instances within...
In this paper, we focus on describing the method we designed for automatic perceived personality prediction. We present a simple model that uses three different sets of features: nonverbal audio cues, visual cues from video, and facial landmark points. The model uses a random decision forest to do regression from the extracted features. As we discuss in Section 4, this multimodal model performs relatively...
Judgments about personality based on facial appearance are strong effectors in social decision making, and are known to have impact on areas from presidential elections to jury decisions. Recent work has shown that it is possible to predict perception of memorability, trustworthiness, intelligence and other attributes in human face images. The most successful of these approaches require face images...
Multi-replicA decoding using corRelation baSed LocALisAtion (MARSALA) is a recent random access technique designed for satellite return links. It follows the multiple transmission and interference cancellation scheme of Contention Resolution Diversity Slotted Aloha (CRDSA). In addition, at the receiver side, MARSALA uses autocorrelation to localise replicas of a same packet so as to coherently combine...
Sampling through crawling is an important research topic in social network analysis. However there is very little existing work on sampling through crawling in directed networks. In this paper we present a new method of sampling a directed network, with the objective of maximizing the node coverage. Our proposed method, Predicted Max Degree (PMD) Sampling, works by predicting which k open nodes are...
In this paper we present a self-avoiding walk-jump (SAWJ) algorithm for finding a maximum degree node on a large assortative graph. We offer two contributions: i) we use the theory of absorbing Markov chains to effectively approximate the required search time as a function of the number of nodes, the edge density, and the assortativity, and ii) we measure the performance of our algorithm against competing...
We present a density-based Data Pruning method for Deep Reinforcement Learning (DRL) to improve learning stability and long-term memory in rare situations. The method controls density distribution in the experience pool by discarding high correlation data and preserving rare and unique data. We apply our method to Deep Q-networks (DQN) and Deep Deterministic Policy Gradients (DDPG) for testing in...
Due to lack of modern dynamic control over the system, the frequency of Bangladesh Power System varies significantly. This research work was started with an objective of finding common trends and behavior of the variation. Frequency data from national grid was collected for four months. They were analyzed in time domain, Fourier domain, with statistical tools and correlation tools. The results for...
Estimation of distribution algorithms (EDAs) are stochastic optimization techniques that are based on building and sampling a probability model. Copula theory provides methods that simplify the estimation of the probability model. To improve the efficiency of current copula based EDAs (CEDAs) new modifications of parallel CEDA were proposed. We investigated eight variants of island-based algorithms...
Sparse channel estimation (SCE) in orthogonal frequency division multiplexing (OFDM) systems with large number of virtual sub-carriers and regularly spaced pilots is studied in this paper. Such OFDM systems are present in wireless standards like long term evolution (LTE). We numerically evaluate the performance of popular compressive sensing (CS) algorithms and shows that low complexity CS algorithms...
Customer satisfaction is an important factor governing adoption and retention of multimedia products and services, such as Over-The-Top(OTT) video transmission. Quality of Experience involves user-centric evaluation of various services. However, users differ in terms of their ratings of service quality. Some rating differences are due to unreliability (outlier users who are not motivated, or are not...
An increasing number of attacks use advanced tactics, techniques and methods to compromise target systems and environments. Such multi-step attacks are often able to bypass existing prevention and detection systems, such as Intrusion Detection Systems (IDSs), firewalls and anti-virus solutions. These security systems either use an anomaly-based or a signature-based detection approach. For systems...
Multi-source image fusion has been the hotspot of research in recent years, in order to make the fusion results more consistent with human vision and computer processing, many classical algorithms have been proposed, such as contourlet transform, non-subsampled contourlet transform (NSCT)and so on. On this basis, this paper proposes an improved fusion method of infrared and visible images based on...
Many intralogistics systems expose autocorrelated arrival processes with significant influence on the systems' performance. Unfortunately there are no control strategies available which take this into account. Instead standard strategies like First Come First Served are applied which lead to systems tending to exhibit long queues and high volatility, even though these strategies perform well in the...
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