A fast and noise resilient cluster-based anomaly detection

Clustering, while systematically applied in anomaly detection, has a direct impact on the accuracy of the detection methods. Existing cluster-based anomaly detection methods are mainly based on spherical shape clustering. In this paper, we focus on arbitrary shape clustering methods to increase the accuracy of the anomaly detection. However, since the main drawback of arbitrary shape clustering is its high memory complexity, we propose to summarize clusters first. For this, we design an algorithm, called Summarization based on Gaussian Mixture Model (SGMM), to summarize clusters and represent them as Gaussian Mixture Models (GMMs). After GMMs are constructed, incoming new samples are presented to the GMMs, and their membership values are calculated, based on which the new samples are labeled as “normal” or “anomaly.” Additionally, to address the issue of noise in the data, instead of labeling samples individually, they are clustered first, and then each cluster is labeled collectively. For this, we present a new approach, called Collective Probabilistic Anomaly Detection (CPAD), in which, the distance of the incoming new samples and the existing SGMMs is calculated, and then the new cluster is labeled the same as of the closest cluster. To measure the distance of two GMM-based clusters, we propose a modified version of the Kullback–Libner measure. We run several experiments to evaluate the performances of the proposed SGMM and CPAD methods and compare them against some of the well-known algorithms including ABACUS, local outlier factor (LOF), and one-class support vector machine (SVM). The performance of SGMM is compared with ABACUS using Dunn and DB metrics, and the results indicate that the SGMM performs superior in terms of summarizing clusters. Moreover, the proposed CPAD method is compared with the LOF and one-class SVM considering the performance criteria of (a) false alarm rate, (b) detection rate, and (c) memory efficiency. The experimental results show that the CPAD method is noise resilient, memory efficient, and its accuracy is higher than the other methods.     

An Efficient Finite Difference Method for The Time‐Delay Optimal Control Problems With Time‐Varying Delay

In this paper, an efficient finite difference method is presented for the solution of time‐delay optimal control problems with time‐varying delay in the state. By using the Pontryagin's maximum principle, the original time‐delay optimal control problem is first transformed into a system of coupled two‐point boundary value problems involving both delay and advance terms. Then the derived system is converted into a system of linear algebraic equations by using a second‐order finite difference formula and a Hermite interpolation polynomial for the first‐order derivatives and delay terms, respectively. The convergence analysis of the proposed approach is provided. The new scheme is also successful for the optimal control of time‐delay systems affected by external persistent disturbances. Numerical examples are included to demonstrate the validity and applicability of the new technique. Some comparative results are included to illustrate the effectiveness of the proposed method.     

Evolution of quantum correlations in the open quantum systems consisting of two coupled oscillators

The open quantum systems consisting of coupled and uncoupled asymmetric oscillators are considered with an initial quantum-dot trapped-ion coherent state. The quantum correlations between spatial modes of this trapped ion are examined to find their dependence on the temperature, asymmetric parameter, dissipation coefficient and the magnetic field. It is observed that the discord of the initial state is an increasing function of the asymmetric parameter and the magnetic field. Moreover, in the case of two uncoupled modes, entanglement and discord are decreasing functions of temperature and the dissipation coefficient. However, as the temperature and dissipation coefficient increase, the discord fades out faster. In the case of two coupled modes, as the temperature and dissipation coefficient increase, the sudden death of the entanglement and fade out of the discord happen sooner; moreover, as the magnetic field increases, the entanglement sudden death and the discord fade out time occur sooner. Also, with the increase in the asymmetric parameter, the entanglement sudden death is postponed. In addition, in the asymmetric system, appreciable discord can be created in the temperature range 0–10 K, while appreciable entanglement can be created in the temperature range 0–5 mK. Finally, it is observed that non-monotonic evolution of quantum correlations is due to coupling of modes.     

Classifying the Geometric Dilution of Precision of GPS satellites utilizing Bayesian decision theory

The errors resulting from satellite configuration geometry can be determined by Geometric Dilution of Precision (GDOP). Considering optimal satellite subset selection, lower GDOP value usually causes better accuracy in GPS positioning. However, GDOP computation based on complicated transformation and inversion of measurement matrices is a time consuming procedure. This paper deals with classification of GPS GDOP utilizing Parzen estimation based Bayesian decision theory. The conditional probability of each class is estimated by Parzen algorithm. Then based on Bayesian decision theory, the class with maximum posterior probability is selected. The experiments on measured dataset demonstrate that the proposed algorithm lead, in mean classification improvement, to 4.08% in comparison with Support Vector Machine (SVM) and 9.83% in comparison with K-Nearest Neighbour (KNN) classifier. Extra work on feature extraction has been performed based on Principle Component Analysis (PCA). The results demonstrate that the feature extraction approach has best performance respect to all classifiers.     

A new fuzzy decision-making procedure applied to emergency electric power distribution scheduling

In this paper a new fuzzy decision-making procedure is developed. Two levels of weightings, called upper and lower weights, are proposed to calculate the fuzzy weightings of different criteria. The preference table is introduced to calculate the upper and lower weights. Also a new method is developed to determine the expected preference values of different alternatives. These values are used for generating the priority list of alternatives. The procedure is applied for providing an emergency electric power distribution, scheduling time table. The IEEE 14-bus standard system and a 14-bus system with four power plants are considered as case studies. Using fuzzy decision-making procedure, the regions with more priorities are more connected to the distribution net, while the maximum consumption criterion is also reasonably respected.     

Microencapsulation of Nigella sativa seeds oil containing thymoquinone by spray‐drying for functional yogurt production

The present work reports on the microencapsulation of Nigella sativa seeds oil containing thymoquinone (TQ) by spray‐drying, using modified starch (MS) and maltodextrin (MD) mixture as wall materials aimed at producing functional yogurt. First, the impact of different ratios of MS/MD on microencapsulation efficiency (ME) and TQ retention was investigated. The highest ME (90.10%) was found in microcapsules prepared from emulsion with 80/20 ratio of MS/MD; however, the microcapsules prepared with 50/50 ratio was selected for considering TQ stability under storage conditions and functional yogurt production due to an acceptable ME (89.48%) and better TQ retention (61.12%). The results showed that the microcapsules stored at refrigerator temperature had the highest content of TQ after 4 weeks. Moreover, the results of chemical and sensory analysis suggest that N. sativa seeds oil microcapsules can be used for producing functional yogurt due to high stability of TQ and proper chemical and sensory properties.     

Preparation of immunomagnetic beads coupled with a rhodamine hydrazine immunosensor for the detection of Mycobacterium avium subspecies paratuberculosis in bovine feces,milk, and colostrum

The aim of this study was to develop and evaluate a method for detecting Mycobacterium avium ssp. paratuberculosis (MAP) bacteria in bovine fecal, milk, and colostrum samples using immunomagnetic beads (IMB) and a rhodamine hydrazone immunosensor. Immunomagnetic beads were prepared by using purified antibodies from hyperimmunized sera that were coupled to Fe nanoparticles with diethylene triamine pentaacetic acid (DTPA) or ethyl (dimethyl aminopropyl) carbodiimide (EDC)-N-hydroxy succinimide (NHS) as linkers. Rhodamine hydrazone particles were synthesized and coupled to IgY anti-MAP antibodies using DTPA or EDC-NHS linkers. Separation efficiency of the IMB was tested on bovine fecal, milk, and colostrum samples experimentally contaminated with MAP. The studied methods were evaluated on their ability to detect MAP and separate bacteria in complex mediums. The ELISA results indicated 95% efficacy in antibody coupling to IMB, with the DTPA-IMB method being more efficient than the EDC-NHS-IMB method. By using the DTPA-IMB method, MAP bacteria were successfully recovered from fecal, milk, and colostrum samples. The DTPA-IMB method used in combination with the rhodamine hydrazone immunosensor had a limit of detection equal to 30 and 30,000 MAP cells/mL using chromogenic and fluorescent properties, respectively. Combining the DTPA-IMB separation method with the rhodamine hydrazone immunosensor provides a fast, sensitive, and cost-beneficial method for detecting MAP in bovine feces, milk, and colostrum.     

Knowledge mapping of the Iranian nanoscience and technology: a text mining approach

Nanoscience and technology (NST) is a relatively new interdisciplinary scientific domain, and scholars from a broad range of different disciplines are contributing to it. However, there is an ambiguity in its structure and in the extent of multidisciplinary scientific collaboration of NST. This paper investigates the multidisciplinary patterns of Iranian research in NST based on a selection of 1,120 ISI??indexed articles published during 1974?C2007. Using text mining techniques, 96 terms were identified as the main terms of the Iranian publications in NST. Then the scientific structure of the Iranian NST was mapped through multidimensional scaling, based upon the co-occurrence of the main terms in the academic publications. The results showed that the NST domain in Iranian publications has a multidisciplinary structure which is composed of different fields, such as pure physics, analytical chemistry, chemistry physics, material science and engineering, polymer science, biochemistry and new emerging topics.     

Tokamak edge plasma rotation in the presence of the biased electrode

Electrode biasing system was designed, constructed, and installed on the IR-T1 tokamak, and then biasing experiments were carried out. Also, using a Mach probes the effects of radial electric field (produced by biased electrode) on the poloidal and toroidal components of the edge plasma velocity were investigated. The results showed an increase in both toroidal and poloidal components of the edge plasma velocity during biasing regime. Results compared and discussed. During positive biasing, increased E_r tends to slow the poloidal rotation in the electron diamagnetic drift direction, i.e., to speed up rotation in the ion diamagnetic drift direction. An increased toroidal rotation velocity has the opposite effect on the poloidal rotation.