Characterization of maximum hands-off control

Maximum hands-off control aims to maximize the length of time over which zero actuator values are applied to a system when executing specified control tasks. To tackle such problems, recent literature has investigated optimal control problems which penalize the size of the support of the control function and thereby lead to desired sparsity properties. This article gives the exact set of necessary conditions for a maximum hands-off optimal control problem using an $L_0$-(semi)norm, and also provides sufficient conditions for the optimality of such controls. Numerical example illustrates that adopting an $L_0$ cost leads to a sparse control, whereas an $L_1$-relaxation in singular problems leads to a non-sparse solution.Comment: 6 page

A Novel Method to Estimate the Damage Severity Using Spatial Wavelets and Local Regularity Algorithm

 In the process of structural damage detection using continuous wavelet transform (CWT), the perturbation or damage is located by identifying the defects locally in the input signal data.  In this work the damage identification procedure using continuous wavelet transform is developed. This method is studied numerically using a simple beam model. The influence of reduced spatial sampling using fundamental mode shape is investigated in detail. The method is also investigated to ascertain the smallest level of damage identified using strain energy mode shape data

Septoplasty with Adenoidectomy: A Combined Procedure for Nasal Obstruction in Children

Nasal obstruction in children is caused by numerous and diverse factors but the symptoms are essentially snoring, mouth breathing, sleep disturbances and rhinorrhea. The commonest causes of nasal obstruction in children are septal deviation and adenoid hypertrophy. Nasal septal deviation in children is usually due to some form of injury. Performing septoplasty alone in this age group without addressing adenoid may lead to recurrence of symptom i.e., nasal obstruction may lead to failure of procedure so we combine both procedures in single sitting. So we have conducted a study of combined septoplasty with adenoidectomy for relief of nasal obstruction in children aged 9-15 years

Attribute Selection Algorithm with Clustering based Optimization Approach based on Mean and Similarity Distance

With hundreds or thousands of attributes in high-dimensional data, the computational workload is challenging. Attributes that have no meaningful influence on class predictions throughout the classification process increase the computing load. This article's goal is to use attribute selection to reduce the size of high-dimensional data, which will lessen the computational load. Considering selected attribute subsets that cover all attributes. As a result, there are two stages to the process: filtering out superfluous information and settling on a single attribute to stand in for a group of similar but otherwise meaningless characteristics. Numerous studies on attribute selection, including backward and forward selection, have been undertaken. This experiment and the accuracy of the categorization result recommend a k-means based PSO clustering-based attribute selection. It is likely that related attributes are present in the same cluster while irrelevant attributes are not identified in any clusters. Datasets for Credit Approval, Ionosphere, Annealing, Madelon, Isolet, and Multiple Attributes are employed alongside two other high-dimensional datasets. Both databases include the class label for each data point. Our test demonstrates that attribute selection using k-means clustering may be done to offer a subset of characteristics and that doing so produces classification outcomes that are more accurate than 80%

A Multi-layer Routing Protocol for Mobility Management in Wireless Mesh Networks

AbstractIn the recent trends, Wireless Mesh networks are proven to be one of the emerging fields in the wireless networks. WMNs comprises of Gateways (GWs), Mesh Clients (MCs) and Mesh Routers (MRs). However, it is challenging job to provide seamless connectivity when MC moves around the network. The recent advances in the field of wireless technology created a chance to overwhelmed the disadvantages of wired and wireless networks. The mobility management in the WMNs motivated the researchers to concentrate. In this paper, we are proposing a model called as multi-layer routing protocol for WMNs. This protocol works with the data link layer and network layer for data frame transmission. The proposed algorithm is implemented with intra domain for experimental evaluation. The experimental results show the effectiveness of the routing protocol

Consciousness Levels Detection Using Discrete Wavelet Transforms on Single Channel EEG Under Simulated Workload Conditions

EEG signal is one of the most complex signals having the lowest amplitude which makes it challenging for analysis in real-time. The different waveforms like alpha, beta, theta and delta were studied and selected features were related with the consciousness levels. The consciousness levels detection is useful for estimating the subjects’ performance in certain selected tasks which requires high alertness. This estimation was performed by analyzing signal properties of the EEG using features extracted through discrete wavelet transform with a moving window of 10 seconds with 90% overlap. The EEG signal is decomposed in to wavelets and the average energy and power of the coefficients related to the EEG bands is taken as the features. The data is collected from standard EEG machine from the volunteers as per the protocol. C3 and C4 locations (unipolar) of the standard 10-20 electrode system were selected. The central region of the brain is most optimal location for the consciousness levels detection. The estimation of the data using Discrete Wavelet Transform (DWT) energy, power features provided better accuracy when the central regions were chosen. An accuracy of 99% was achieved when the algorithm was implemented using a classifier based on linear kernel support vector machines (SVM)