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Pebble game rigidity analysis is an efficient method for extracting rigidity and flexibility information of biomolecules without performing costly molecular dynamics simulations. The standard algorithm works on a multi-graph associated to a mechanical model constructed from an arbitrary atom-bond network. Motivated by large scale protein flexibility and simulated unfolding applications, we have developed...
Web spam is a big problem for search engine users in World Wide Web. They use deceptive techniques to achieve high rankings. Although many researchers have presented the different approach for classification and web spam detection still it is an open issue in computer science. Analyzing and evaluating these websites can be an effective step for discovering and categorizing the features of these websites...
In the context of Visualization, Multidimensional Projection techniques are employed to show similarity relations among instances of a multidimensional dataset. Distinct projection techniques use different approaches to perform the dimensionality reduction and, consequently, different metrics are employed to assess projection quality according to similarity and structures preservation. Usually, quality...
Approximately 50,000 to 60,000 new cases of Parkinson's disease (PD) are diagnosed yearly. Despite being non-lethal, PD shortens life expectancy of the ones affected with such disease. As such, researchers from different fields of study have put great effort in order to develop methods aiming the identification of PD in its early stages. This work uses handwriting dynamics data acquired by a series...
A common scenario in Search and Rescue robotics is to map and patrol a disaster site to assess the situation and plan potential missions of rescue teams. Particular importance has to be given to changes in the environment as these may correspond to critical events like building collapses, movement of objects, etc. This paper presents a change detection pipeline for LiDAR-equipped robots to assist...
This survey highlights issues in clustering which hinder in achieving optimal solution or generates inconsistent outputs. We called such malignancies as dark patches. We focus on the issues relating to clustering rather than concepts and techniques of clustering. For better insight into the issues of clustering, we categorize dark patches into three classes and then compare various clustering methods...
In view of the shortcomings of the traditional clustering algorithm in intrusion detection system, this paper proposes a method of selecting the initial clustering center based on density, which can overcome the problem of K value in ordinary K-Means. The improved intrusion detection model can achieve good clustering effect. Compared with the traditional K-Means, it is found that the improved algorithm...
Current hierarchical clustering algorithms face the risk of privacy leakage during the clustering process for big dataset. While differential privacy is a relatively recent development in the field of privacy-preserving data mining, offering more robust privacy guarantees. In the paper, BIRCH algorithm under differential privacy is studied and analyzed. Firstly, Diff-BIRCH algorithm which directly...
The optimal sub-pattern assignment (OSPA) metric is a distance between two sets of points that jointly accounts for the dissimilarity in the number of points and the values of the points in the respective sets. The OSPA metric is often used for measuring the distance between two sets of points in Euclidean space. A common example is in multi-target filtering, where the aim is to estimate the set of...
This paper presents an automatic detection system capable of detecting an automobile dashboard with high accuracy. Since the structure of an automobile dashboard is quite different from general instruments, commonly used algorithms for instrument detection can hardly meet the accuracy and robustness. In this paper, a novel approach is presented to detect an automobile dashboard. The contour retrieving...
The unified Parkinson's disease rating scale (UPDRS) is the most widely employed scale for tracking Parkinson's disease (PD) symptom progression. However, conventional way to achieve UPDRS, mainly based on the physical examinations of clinic patients performed by the trained medical staffs, involves the disadvantages of inconvenience and high medical expense. Hence, in this study, we try to explore...
Indoor positioning systems have been actively studied so far, and recently, many researchers are adopting Wi-Fi signals for their systems. It is mainly because Wi-Fi networks are prevalent in the indoor environments these days; also it is more efficient than other methods as one can estimate his location by simply comparing current RSS (Received Signal Strength) with the fingerprint of Wi-Fi signals...
In this paper a Genetic Algorithm (GA) is used to partition a distribution network with the aim to minimize the energy exchange among the microgrids (i.e. maximize self-consumption) in presence of distributed generation. The proposed GA is tested on the IEEE prototypical network PG & E 69-bus. The microgrid partitioning is tested over a period of one year with hourly sampled data of real household...
Indoor localization system is an important topic in the wireless navigation system. Many technologies, such as Wi-Fi, Bluetooth, and ZigBee, have been developed for the indoor localization system; however, these systems still demonstrate poor accuracy and performance. The indoor localization system using Wi-Fi signals is the best option for indoor localization because most of the buildings are covered...
In this paper, a new pulse separation technique based on fuzzy logic algorithm is proposed. An equivalent Time-Frequency diagram (TF map) is obtained from the feature extraction and clustering of both PD pulse signal and ambient noise signal. Since different kinds of PD types derived from different PD sources, they will form specific clusters in the TF map. It provides a possibility to classify the...
In many applications such as music transcription, audio forensics, and speech source separation, it is needed to decompose a mono recording into its respective sources. These techniques are usually referred to as blind source separation (BSS). One of the methods recently used in BSS is non-negative matrix factorization (NMF) both in supervised and unsupervised learning cases. In this paper, we propose...
Wireless sensor network (WSN) is an inexpensive newfound technology with many applications in various fields (such as biology Environment, war and natural disasters). A network consisting of a large number of sensor nodes and collecting information from the environment in a distributed environment. The main limitations include limited energy, low communication capacity, low storage volume, and low...
Cognition involves dynamic reconfiguration of functional brain networks at sub-second time scale. A precise tracking of these reconfigurations to categorize visual objects remains elusive. Here, we use dense electroencephalography (EEG) data recorded during naming meaningful (tools, animals…) and scrambled objects from 20 healthy subjects. We combine technique for identifying functional brain networks...
In traditional K-means, the target function only considered the intra-cluster similarities and did not take into account the differences among categories. In order to take into account both the firmness in the same cluster and the dispersion between different clusters, a new objective function based on ideal point is given, and the K-means algorithm based on quasi ideal point method is provided. A...
Wireless Sensor Network (WSN) is widely used in IOT, military and environmental application. However, WSN is energy-constrained and the network nodes placed in hostile environment are hard to replace. Therefore, designing an energy-efficient routing algorithm is significant. Many solutions have been proposed to optimize energy consumption in conventional wireless sensor network, but they don't work...
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