Stabilization of large space structures by linear reluctance actuators

Application of magnetic forces are considered for stabilization of vibrations of flexible space structures. Three electromagnetic phenomena are studied, such as: (1) magnetic body force; (2) reluctance torque; and (3) magnetostriction, and their application is analyzed for stabilization of a beam. The magnetic body force actuator uses the force that exists between poles of magnets. The reluctance actuator is configured in such a way that the reluctance of the magnetic circuit will be minimum when the beam is straight. Any bending of the beam increases the reluctance and hence generates a restoring torque that reduces bending. The gain of the actuator is controlled by varying the magnetizing current. Since the energy density of a magnetic device is much higher compared to piezoelectric or thermal actuators, it is expected that the reluctance actuator will be more effective in controlling the structural vibrations

Smart Grid Security: Threats, Challenges, and Solutions

The cyber-physical nature of the smart grid has rendered it vulnerable to a multitude of attacks that can occur at its communication, networking, and physical entry points. Such cyber-physical attacks can have detrimental effects on the operation of the grid as exemplified by the recent attack which caused a blackout of the Ukranian power grid. Thus, to properly secure the smart grid, it is of utmost importance to: a) understand its underlying vulnerabilities and associated threats, b) quantify their effects, and c) devise appropriate security solutions. In this paper, the key threats targeting the smart grid are first exposed while assessing their effects on the operation and stability of the grid. Then, the challenges involved in understanding these attacks and devising defense strategies against them are identified. Potential solution approaches that can help mitigate these threats are then discussed. Last, a number of mathematical tools that can help in analyzing and implementing security solutions are introduced. As such, this paper will provide the first comprehensive overview on smart grid security

Optimal disturbance rejecting control of hyperbolic systems

Optimal regulation of hyperbolic systems in the presence of unknown disturbances is considered. Necessary conditions for determining the optimal control that tracks a desired trajectory in the presence of the worst possible perturbations are developed. The results also characterize the worst possible disturbance that the system will be able to tolerate before any degradation of the system performance. Numerical results on the control of a vibrating beam are presented

"The fruits of independence": Satyajit Ray, Indian nationhood and the spectre of empire

Challenging the longstanding consensus that Satyajit Ray's work is largely free of ideological concerns and notable only for its humanistic richness, this article shows with reference to representations of British colonialism and Indian nationhood that Ray's films and stories are marked deeply and consistently by a distinctively Bengali variety of liberalism. Drawn from an ongoing biographical project, it commences with an overview of the nationalist milieu in which Ray grew up and emphasizes the preoccupation with colonialism and nationalism that marked his earliest unfilmed scripts. It then shows with case studies of Kanchanjangha (1962), Charulata (1964), First Class Kamra (First-Class Compartment, 1981), Pratidwandi (The Adversary, 1970), Shatranj ke Khilari (The Chess Players, 1977), Agantuk (The Stranger, 1991) and Robertsoner Ruby (Robertson's Ruby, 1992) how Ray's mature work continued to combine a strongly anti-colonial viewpoint with a shifting perspective on Indian nationhood and an unequivocal commitment to cultural cosmopolitanism. Analysing how Ray articulated his ideological positions through the quintessentially liberal device of complexly staged debates that were apparently free, but in fact closed by the scenarist/director on ideologically specific notes, this article concludes that Ray's reputation as an all-forgiving, ‘everybody-has-his-reasons’ humanist is based on simplistic or even tendentious readings of his work

Learning in presence of class imbalance and class overlapping by using one-class SVM and undersampling technique

The class imbalance problem engraves the traditional learning models by degrading performance and yielding erroneous outcomes. It is the scenario where one of the class representation is over-shadowed by other classes in a data space. Presence of class imbalance can cause a grave difficulty as misclassification cost of minority class tends to be very high. Presence of overlapping cases along with the case of imbalanced data, can lead to create grim situation for effective learning. In this study, an in-depth analysis of the effects of class imbalance and class overlapping in conventional learning models has been presented. A data level approach is adapted with one-class SVM-based anomaly detection to detect the cases of data overlapping while an adapted Tomek-link undersampling algorithm is defined to treat both overlapped and imbalanced cases. The proposed model evolves to eliminate borderline, redundant and overlapping cases with the account of Tomek-link pair and sparse neighbourhood. The proposed method has been evaluated with six state-of-the-art models for seven binary and two multiclass datasets, with respect to three standard learning models. The proposed model has been evaluated with cost-sensitive learning and extreme learning based approaches for imbalanced class learning. The proficiency of the proposed method over state-of-the-art models is established through experimental analyses

A Case of Protruding Eyeballs and Diminishing Vision

This case report discusses issues related to a 56-year-old man from Bangalore who presented with complaints of a gradual protrusion of his eyeballs along with diminishing vision for the previous month. The approach to diagnosis and management issues around this unusual presentation is dicussed

A review on rainfall forecasting using ensemble learning techniques

Significant challenges to human health and life have arisen as a result of heavy rains. Floods and other natural disasters that affect people all over the world every year are caused by prolonged periods of heavy rainfall. Predictions of rainfall must be accurate in countries like India where agriculture is the primary occupation. The non-linearity of rainfall makes machine learning (ML) methods more efficient than many other approaches. In machine learning (ML), individual classifiers are less accurate than ensemble learning (EL) techniques. In order to better understand the various Machine Learning algorithms and Ensemble Learning techniques that researchers employ to predict rainfall, this review paper has been written.This article reviews ensemble learning algorithms for predicting rainfall. In order to increase the accuracy of rainfall forecasts and consequently avoid the negative effects of heavy precipitation, ensemble learning algorithms have gained popularity. This review article examines and makes reference to the development of ensemble approaches, including bagging, boosting, and stacking. The findings of this survey demonstrate that ensemble techniques are much superior to conventional (individual) model learning in terms of rainfall prediction. Additionally, boosting techniques (such enabling, AdaBoost, and extreme gradient boosting) have been applied more frequently and successfully in scenarios involving rainfall forecasting