MIG焊电弧声信号采集与分析系统设计

针对目前制约MIG焊熔透状态自适应控制发展而亟待解决的熔透状态信号获取问题,采用图形化编程语言LabVIEW,设计了一套集电弧声信号采集与分析于一体的系统软件.系统具备身份验证、参数配置与记录、采集预览、数据存盘重载、信号降噪以及特征提取等功能.试验表明,该系统能实时高效地完成对电弧声信号的采集、处理和分析,而且实现简单、界面友好、性能稳定可靠,为利用电弧声信号进行熔透状态自适应控制提供理论和应用基础.     

Bi2O3 vaporization from ZnO-based varistors

Bi₂O₃-doped ZnO ceramic varistors are usually sintered at temperatures near to 1200 °C in the presence of a Bi-rich liquid phase, which is partially vaporized during the sintering process. Volatilization of bismuth oxide depends on the total surface area in direct contact to the reaction atmosphere and this in turn is related to the area/volume ratio of the ceramic compact. This loss of Bi₂O₃ has a significant role on the development of the varistor microstructure and more specifically ZnO grain growth, which is strongly enhanced by the presence of the liquid phase, should be particularly affected. In the present paper, X-ray fluorescence analysis is performed to describe the Bi₂O₃ vaporization profile as a function of distance to the outer surface, taking into account its influence on microstructural evolution.     

Augmented grasshopper optimization algorithm by differential evolution: a power scheduling application in smart homes

With the increasing number of electricity consumers, production, distribution, and consumption problems of produced energy have appeared. This paper proposed an optimization method to reduce the peak demand using smart grid capabilities. In the proposed method, a hybrid Grasshopper Optimization Algorithm (GOA) with the self-adaptive Differential Evolution (DE) is used, called HGOA. The proposed method takes advantage of the global and local search strategies from Differential Evolution and Grasshopper Optimization Algorithm. Experimental results are applied in two scenarios; the first scenario has universal inputs and several appliances. The second scenario has an expanded number of appliances. The results showed that the proposed method (HGOA) got better power scheduling arrangements and better performance than other comparative algorithms using the classical benchmark functions. Moreover, according to the computational time, it runs in constant execution time as the population is increased. The proposed method got 0.26?% enhancement compared to the other methods. Finally, we found that the proposed HGOA always got better results than the original method in the worst cases and the best cases.

     

DPV: a taxonomy for utilizing deep learning as a prediction technique for various types of cancers detection

Multimedia Tools and Applications - Deep learning (DL) is a type of machine learning capable of processing large quantities of data to provide analytic results based on a particular...     

A novel secure solution of using mixed reality in data transmission for bowel and jaw surgical telepresence: enhanced rivest cipher RC6 block cipher

Security threats are crucial challenges that deter Mixed reality (MR) communication in medical telepresence. This research aims to improve the security by reducing the chances of types of various attacks occurring during the real-time data transmission in surgical telepresence as well as reduce the time of the cryptographic algorithm and keep the quality of the media used. The proposed model consists of an enhanced RC6 algorithm in combination. Dynamic keys are generated from the RC6 algorithm mixed with RC4 to create dynamic S-box and permutation table, preventing various known attacks during the real-time data transmission. For every next session, a new key is created, avoiding possible reuse of the same key from the attacker. The results obtained from our proposed system are showing better performance compared to the state of art. The resistance to the tested attacks is measured throughout the entropy, Pick to Signal Noise Ratio (PSNR) is decreased for the encrypted image than the state of art, structural similarity index (SSIM) closer to zero. The execution time of the algorithm is decreased for an average of 20%. The proposed system is focusing on preventing the brute force attack occurred during the surgical telepresence data transmission. The paper proposes a framework that enhances the security related to data transmission during surgeries with acceptable performance.

     

Compression based clustering technique for enhancing accuracy in web scale videos

Multimedia Tools and Applications - Detection and clustering of commercial advertisements plays an important role in multimedia indexing also in the creation of personalized user content. In...     

An integrated emotional and physiological assessment for VR-based active shooter incident experiments

Unfortunately, active shooter incidents are on the rise in the United States. With the recent technological advancements, virtual reality (VR) experiments could serve as an effective method to prepare civilians and law enforcement personnel for such scenarios. However, for VR experiments to be effective for active shooter training and research, such experiments must be able to evoke emotional and physiological responses as live active shooter drills and events do. The objective of this study is thus to test the effectiveness of an active shooter VR experiment on emotional and physiological responses. Additionally, we consider different locomotion techniques (i.e., walk-in-place and controller) and explore their impact on users’ sense of presence. The results suggest that the VR active shooter experiment in this study can induce emotional arousal and increase heart rate of the participants immersed in the virtual environment. Furthermore, compared to the controller, the walk-in-place technique resulted in a higher emotional arousal in terms of negative emotions and a stronger sense of presence. The study presents a foundation for future active shooter experiments as it supports the ecological validity using VR for active shooter incident related work for the purposes of training or research.     

Intelligent fault diagnosis for rolling bearings based on graph shift regularization with directed graphs

Graph shift regularization is a new and effective graph-based semi-supervised classification method, but its performance is closely related to the representation graphs. Since directed graphs can convey more information about the relationship between vertices than undirected graphs, an intelligent method called graph shift regularization with directed graphs (GSR-D) is presented for fault diagnosis of rolling bearings. For greatly improving the diagnosis performance of GSR-D, a directed and weighted k-nearest neighbor graph is first constructed by treating each sample (i.e., each vibration signal segment) as a vertex, in which the similarity between samples is measured by cosine distance instead of the commonly used Euclidean distance, and the edge weights are also defined by cosine distance instead of the commonly used heat kernel. Then, the labels of samples are considered as the graph signals indexed by the vertices of the representation graph. Finally, the states of unlabeled samples are predicted by finding a graph signal that has minimal total variation and satisfies the constraint given by labeled samples as much as possible. Experimental results indicate that GSR-D is better and more stable than the standard convolutional neural network and support vector machine in rolling bearing fault diagnosis, and GSR-D only has two tuning parameters with certain robustness.     

Performance Evaluation Indicator (PEI): A new paradigm to evaluate the competence of machine learning classifiers in predicting rockmass conditions

To illustrate an unprejudiced comparison among machine learning classifiers established on proprietary databases, and to guarantee the validity and robustness of these classifiers, a Performance Evaluation Indicator (PEI) and the corresponding failure criterion are proposed in this study. Three types of machine learning classifiers, including the strictly binary classifier, the normal multiclass classifier and the misclassification cost-sensitive classifier, are trained on four datasets recorded from a water drainage TBM project. The results indicate that: (1) the PEI successfully compares the competence of classifiers under different scenarios by isolating the effects of different overlapping-degree of rockmass classes, and (2) the cost-sensitive algorithm is warranted to classify rockmasses when the ratio of inter-class classes is more than 8:1. The contributions of this research are to fill the gap in performance evaluations of a classifier for imbalanced training data, and to identify the best situation to apply this classifier.     

A Building Information Model enabled Multiple Traveling Salesman Problem for building interior patrols

During building emergencies, an effective and visible primary search plan enhances situation awareness and enables a more efficient rescue mission. The aim of the primary search during an emergency is the rapid screening of every space in the building to identify locations of victims and their conditions. Afterwards, first responders can plan for the rescue of those victims. To provide a timely draw up of interior patrol routes and assign rescue teams to conduct the primary search, this study formulates the problem as a multiple traveling salesman problem (M-TSP) where the comprehensive building interior network is given by the building information models (BIMs), while the total traveling costs (lengths) of every rescue team is minimized. To meet the requirement of real-time patrol routes optimization, we employed the branch-and-price algorithm for the enhancement of computation efficiency. In addition, a heuristic method was introduced to provide timely solutions for large-scale networks. A case study is conducted for a single-floor convention center. We utilized BIM to construct a network of nodes and arcs where the decision model requires as input, and the branch-and-price algorithm finds the optimal patrol. The resulting patrol routes can be visualized and serve as guide for rescue teams to conduct the primary search. The integrated approach proposed in this study is practical and can expedite search and rescue missions.