The Effect of Neural Entropy during Deep Brain Stimulation of Cortex-Basal Ganglia Network Model.

Researchers reported decreased nerve entropy Patients with Parkinson's disease (PD) have abnormalities in their basal ganglia (BG). Studies of local field potentials (LFPs) recorded from the hypothalamus and single unit recordings of GP neurons showed this reduction to be significant. According to this hypothesis, these changes are consistent with changes in the ability of the basal ganglion network to encode PD information. Our deep brain stimulation of cortical basal ganglia (DBS) model includes single LFP recordings and shows how entropy changes during DBS. In addition to the extracellular stimulation of supplied STN fibers and LFP mimetics, which are detected differently on a registered electrode, this model includes osteoclast activation and anti-apoptosis. In the DBS network, the firing pattern fluctuated between high-frequency and low-frequency stimuli, since gp neurons in the network showed a decrease in entropy when a high-frequency stimulus was applied and an increase in entropy when a low-frequency stimulus was applied. Second hand. Changes in neural entropy after DBS have been reported experimentally. The simulation results were consistent

Optical Character Recognition of Indian Language Manuscripts using Convolutional Neural Networks

India's constitution has 22 languages written in 17 different scripts. These materials have a limited lifespan, and as generations pass, these materials deteriorate, and the vital knowledge is lost. This work uses digital texts to convey information to future generations. Optical Character Recognition (OCR) helps extract information from scanned manuscripts (printed text). This paper proposes a simple and effective solution of optical character recognition (OCR) Sanskrit Character from text document images using long short-term memory (LSTM) and neural networks of Sanskrit Characters. Existing methods focuses only upon the single touching characters. But our main focus is to design a robust method using Bidirectional Long Short-Term Memory (BLSTM) architecture for overlapping lines, touching characters in middle and upper zone and half character which would increase the accuracy of the present OCR system for recognition of poorly maintained Sanskrit literature.

Efficient Feature Descriptor using Gabor Filter and Principal Component Analysis for Glaucoma Diagnosis

An automated Computer Aided Diagnosis (CAD) system for glaucoma diagnosis using fundus images is developed. The various glaucoma image classification schemes using the supervised and unsupervised learning approaches are reviewed. The research paper involves three stages of glaucoma disease diagnosis. First, the pre-processing stage the texture features of the fundus image is recorded with a two-dimensional Gabor filter at various sizes and orientations. The image features are generated using higher order statistical characteristics, and then Principal Component Analysis (PCA) is used to select and reduce the dimension of the image features. For the performance study, the Gabor filter based features are extracted from the RIM-ONE and HRF database images, and then Support Vector Machine (SVM) classifier is used for classification. Final stage utilizes the SVM classifier with the Radial Basis Function (RBF) kernel learning technique for the efficient classification of glaucoma disease with accuracy 90%.

The Impact of Chinese Seals on the Structure, Design, and Usage of the Īl-Khānids Seals and Coins

Il-Khanid seals and coins are a type of seal featuring figurative patterns typically characterized by the Rectangular style of Kufic script, the absence of figures, extensive use of calligraphy, geometric, and abstract patterns. Although it is based on the Persian seal-carving tradition, the Īl-Khānids seals and coins exhibit various elements from the Chinese seals (印章), and also similar in their style to the Mongolian writing systems. While the Silk Road, the central path for trade and economic purposes, brought together China and Persia, the two nations had strong influences regarding culture, tradition, and religion, and Persian art has applied many Chinese artistic elements, particularly in the art of seal making. Indeed, the historical evidence suggests that the Mongolian Empire employed the Chinese seals (印章) throughout their territory, stretching from China to Persia. The intercultural influences through the Silk Road seem to be well-rooted in Central Asia, and for the first time, Chinese culture is seen abundantly in the Īl-Khānids seal history, as well as the Rectangular style of Kufic script on the seals and coins, influenced by the Uighur script. This paper uses an interdisciplinary approach to analyse the Chinese and the Īl-Khānids seals and coins to survey transmission of the Chinese tradition through Silk Road cultural exchanges. The results show that there exists a strong possibility that the manner in which the writing of Arabic characters in the Rectangular Kufic writing system was inserted at the top to the bottom unexpectedly followed the style of Mongolian words.

Using Internet of Things application for Monitoring Photo-Voltaic Panel Based on Ask Sensors Cloud

Internet of Things (IOT) devices and monitoring systems are essential for the accurate, reliable, and proper functioning of photovoltaic (PV) solar energy systems. The data acquisition and monitoring system ensure adequate operation and ascertain system malfunctions before they become significant problems. The IOT integrates ordinary items using modern technology in the physical scope. It is all feasible to utility voltage, current, temperature, and humidity sensors. The current research focuses on developing a cost-effective, accessible, and steadfast data monitoring system. A microcontroller-based data logger is stored in a cloud. The data can be downloaded directly from the website using the IoT technique because photovoltaic (PV) panels are built-in faraway locations and humans cannot reach them. The suggested system demonstrates the online utilization of solar PV power.

Bi-combustion synthesis technique for the reduction of crystallite size of nanophosphors - a modified version

Nanophase materials, in recent times, have attracted many a researcher all over the world, on account of their exceptionally high efficiency in terms of morphological and optical behavior. In the nano-range order, various physical and chemical methods are employed to produce materials commercially, but the reported methods owing to their own physical conditions, limit the crystallite sizes to a certain nano-order. To prevail over this size-related limitation, a new modified bi-combustion synthesis technique (B-CST) has been introduced, which aids inthe formation of nanomaterials, with an average size of 10-20 nm, without using any ball milling process. In order to scrutinize the crystallite sizes of SrAl2O4: Eu2+, Dy3+ phosphors synthesized by CST and B-CST, the X-ray diffraction (XRD) technique is used to determine the crystalline phase only while high-resolution transmission electron microscopy (HRTEM) is used, which is the most sought-after method world-wide and is vigorously used to determine the crystallite size.

An Ensemble Approach to Control Network Traffic on IoT

Cyber security is most widely seen in many domains. From various domains these attacks plays the major role in damaging the servers and making websites unavailable. Many challenges are facing with the various cyber attacks.Internet of Things (IoT) is most widely used to define as a pervasive network of a (broad) range of connected smart nodes that offer diverse digital services, including the collection of environmental and user data. Detection of cyber attacks is difficult task and this may cause the loss of data packets and may interrupt the server. In this paper, the Enhancement is developed to handle the attack packets effectively. This is the window based application i,e based on the window size the data is processed. The Enhancement is called as an Amplified and Forward for Bi- Directional traffic from Attacks. This is very significant model to detect the several types of attacks that occur in IoT. Results show the performance of proposed system.

Geomatic Assessment Of Rainwater Harvesting Potential System At Cmr College Of Engineering & Technology

CMRCET campus comprises about 10 of acres land, where water is the natural resource which is being always in high demands. If the demand is not met, then it will lead to water scarcity. Therefore, RWHS can be considered as a best solution for fighting against scarcity of water. Our present study deals with the identification of the study area boundary and marking it as a Polygon in GIS, Rooftops of various block entities, paths and pavements were digitized using the Polygon vector in GIS. GIS technique is employed for locating boundaries of the study area and for calculating the areas of various types of rooftops and paths. With the application of GIS, it is possible to assess the total potential of water that can be harvested. Potential of rainwater harvesting refers to the capacity of an individual catchment that harnesses the water falling on the catchment during a particular year considering all rainy days. This present study will enable us to identify the suitable type of water harvesting structure along with the number of structures required. Our aim is to maximize water storage and minimize the runoff through drains without making use of it. Thus, Rainwater Harvesting and Conservation aim at the optimum utilization of the rain water.

Design and Analysis of Mathematical Model for the Concentration of Pollution and River Water Quality

This paper mainly focuses on the recent advances in the mathematical models that provide the ability to predict the contaminant concentration levels of river water. The study represents an attempt for the researchers to study the problem of pollution, and we think that these mathematical analyses would provide better planning for water quality control. The model consists of a pair of coupled reaction Advection-diffusion equations for the pollutant and dissolved oxygen concentrations. Numerical solutions are obtained and some important inferences are drawn through simulation study. The Advection-Diffusion equation is characterized by the reaction term whenever it depends on concentration of the contaminants and in this case the original single Advection-diffusion equation will evolve to be a system of equations. It is no ticked that the higher are diffusion and reaeration coefficients, the faster is the river purity.

Image Restoration using Recent Techniques: A Survey

Image Restoration is one of the challenging and essential milestones in the image processing domain. Digital image processing is a technique for manipulating digital images using a variety of computer algorithms. The process of transforming the degraded or damaged image to the original image can be known as Image Restoration. The image restoration process improves image quality by converting the degraded image into the original clean image. The techniques for image restoration are comprised of predefined parameters through which digital image gets processed for refinements. The purpose of restoration is to start with the acquired image and then estimate the original image as accurately as possible. A degraded image can be contaminated by any of a blur or noise or both. Many factors can contribute to image degradation, including poor capture, poor lighting, and poor eyesight. Medical science, defensive sensor systems, forensic detections, and astrology all rely on image restoration for accuracy. This paper discusses various image restoration techniques using recent trends for performance improvements.