The upgrade of the ALICE Inner Tracking System

The upgrade of the Inner Tracking System represents an important part in the overall upgrade strategy of ALICE, which will be implemented during the second long shutdown of the LHC scheduled in 2018-19. In this contribution, a brief overview of the upgraded ITS is presented

Investigation of conventional superconductivity in ternary cerium compounds through high pressure studies

The present investigation focuses on the nature and mechanism of superconductivity in the cerium-containing ternary borides and silicides: CeRu(,3)B(,2), CeOs(,3)B(,2), and CeRu(,3)Si(,2). These are the only ternary cerium compounds where conventional (as opposed to heavy fermion) superconductivity has been observed to date;The closely related crystal structures (all related to the CeCo(,3)B(,2)-type, P6/mmm) enabled the study of the effect on superconductivity of transforming continuously from one system to the other by going across the pseudoternary series Ce (Ru(,1-x)Os(,x))(,3)B(,2) and CeRu(,3)- (B(,x)Si(,1-x))(,2). These pseudoternary systems were subjected to high external pressures using a standard hydrostatic pressure clamp for lower pressures (up to 20 kbar) and a specially designed diamond anvil cell for higher pressures (up to 66 kbar). Trends are presented for the variation of the superconducting transition temperatures with changes in external pressure;Results are also included from measurements of static magnetic susceptibility and electrical resistivity of all of the materials in the;series Ce(Ru(,1-x)Os(,x))(,3)B(,2) and CeRu(,3)(B(,x)Si(,1-x))(,2). These provide some insight into the nature of the cerium valence in these compounds; *DOE Report IS-T-1216. This work was performed under contract No. W-7405-Eng-82 with the U.S. Department of Energy

An Econometric Measurement of the Impact of Marketing Communication on Sales in the Indian Cement Industry

This study analyzes the relationship between net sales revenue and Integrated Marketing Communications (IMC) viz. advertising, sales promotion, personal selling and direct marketing. It attempts to find the existence of a long-term relationship between the two variables and goes on to analyze the impact of one variable on the other and its possible implications. Seven year quarterly data of ten firms in the Indian Cement industry when analyzed reveals that there is no evidence of cointegration between the above mentioned variables, but the Vector Autoregression (VAR) model suggests that although past sales do not influence current advertising, advertising and sales promotion have a significant effect on the sales of cement after one year. The Impulse Response Function (IRF) and Forecast Error Variance Decomposition (FEVD) also support this view. Keywords: Advertising, Cointegration, Forecast Error Variance Decomposition, Impulse Response Function, Net sales, Sales Promotion, Vector Autoregression

Driving pattern analysis to determine driver behaviors for local authority based on cloud using OBD II

Aggressive driving is the main cause of road accidents and it is affected by driving behavior which endanger not only the driver himself but also the people around. It is very significant step to identify such behaviors of the drivers by the local authorities which would help in correcting the behaviors or to understand the root cause of the accidents by analyzing the data recorded by the On Board Diagnostic( OBD ) II device. An aggressive driving behavior is characterized by sudden change inmaneuverings of vehicle which eventually yields non uniform parameters values returned by the ECU (Engine Control Unit) system without any specific reason. In this research work, the real time data is recorded from ECU using OBD II and the accelerometer. The Artificial Intelligenceis used in grouping the different types of data toidentifythe behaviors data on the basis of similarity of datapoints.The purpose of this research work is to identify such drivers and reduce the risk of further accidents.The work identifies the behaviors as bad, normal and aggressive behavior. As the clustering is made on basis crowded data which signifies the similar driving patterns for most of the time in the course of recording, therefore, Density-Based Spatial Clustering of Applications with Noise (DBSCAN) unsupervised learning algorithm was used. The data will be sent to the cloud so that it can be accessed by the authority from any place for further action.ANOVA test is conducted usingIBMSPSS(Statistical Package for the Social Sciences) package to compare and determine the best method to collect data by comparing the means between groups

Visualizing Bivariate Statistics Using Ellipses Over a Scatter Plot

A scatter plot shows the relationship between two quantitative variables and . Sometimes, we can predict one variable as a linear function of the other using the least squares regression lines of on or on . These two regression lines together suffice to identify the mean vector, the coefficient of determination, the correlation coefficient, and the ratio of the standard deviations (SD). So, do our proposed summary ellipses. Additionally, the inner ellipse reveals the SDs and the outer ellipse flags potential outliers

shutterplot: An R Package to Display All Summary Statistics of a Simple Linear Regression Model

A shutterplot depicts all summary statistics in a simple linear regression model. Instead of reporting their numerical values, a shutterplot gives their visual representations. In this paper, we provide a step-by-step description of how the shutterplot package constructs a shutterplot and the options the user has in customizing it

GIplot: An R Package for Visualizing the Summary Statistics of a Quantitative Variable

A GI plot is a graphical tool that pictorially represents the five-number summary, the mean, the standard deviation, the sample size, and flags potential outliers that are c standard deviations away from the mean together with their frequencies. The GI plot was developed by Sarkar and Rashid (2021) as a companion to the boxplot. The purpose of this paper is to provide an overview of the GIplot package and introduce the main functionality of the package using several examples

Leveraging coffee‐ring effect on plasmonic paper substrate for sensitive analyte detection using Raman spectroscopy

Raman spectroscopy has demonstrated immense promise as a molecular fingerprinting tool in biomedical diagnostics. However, the utility of conventional Raman scattering for ultrasensitive measurements of biofluids is limited by intrinsically weak signals and has spurred advances in and wider applications of plasmon‐enhanced measurements. Here, we propose a label‐free methodology that leverages drop coating deposition on a silver ink‐based plasmonic paper substrate with tunable hydrophobic attributes to combine two distinct sources of enhancement, namely, solute preconcentration and excitation of localized surface plasmons. The facile modulation of the hydrophobicity of the plasmonic silver paper facilitates investigations into the coffee‐ring effect that results from the interplay of contact line pinning, solvent evaporation, and capillary flow. We show that the Raman spectra acquired from the hydrated ring deposits show clear enhancement beyond that obtained from surface‐enhancement owing to the presence of the silver nanofilm. In light of the superior sensitivity and lack of substantive sample preparation requirements, our findings open the door for a complementary low‐cost paper‐based analytical device for molecular sensing.We propose a label‐free analytical tool that leverages drop coating deposition on a silver ink‐based plasmonic paper substrate to combine two distinct sources of enhancement for Raman scattering signals. The facile modulation of the hydrophobicity of the plasmonic silver paper facilitates investigations into the coffee‐ring effect that results from the interplay of contact line pinning, solvent evaporation, and capillary flow. Raman spectra acquired show clear enhancement beyond that obtained from surface‐enhancement owing to the presence of the silver nanofilm.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146368/1/jrs5415_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146368/2/jrs5415.pd

Studies On Monolithic Active Pixel Sensors and Detector Performance for the Inner Tracking System Upgrade of ALICE

ALICE (A Large Ion Collider Experiment) is a general-purpose, heavy-ion detector at the CERN LHC designed to study the physics of strongly interacting matter, and in particular the properties of the Quark-Gluon Plasma (QGP), using Pb-Pb collisions at unprecedented energy densities. During the first three years of operation, it has demonstrated very good capabilities for measurements at high energy Pb-Pb collisions. But there are certain measurements like high precision measurements of rare probes over a wide range of momenta, which would require high statistics and are not satisfactory or even possible with the current experimental setup. These measurements would help to achieve the long term physics goals of ALICE and would go a long way forward in understanding and characterizing the Quark Gluon Plasma (QGP). To enhance its physics capabilities, ALICE has formulated an upgrade of its detectors, motivated by an upgrade of the LHC during the LHC Long Shutdown 2 (2018-2020). The LHC upgrade features which primarily motivated the ALICE upgrade programme are, in particular, Pb-Pb collisions with a high interaction rate of up to 50 kHz corresponding to an instantaneous luminosity, L = 6 × 1027cm−2s−1 and, the installation of a narrower beam pipe. Accordingly, ALICE would require detector upgrades to cope with the upgrade scenario. These upgrades should help to improve tracking and vertexing capabilities, radiation hardness and allow readout of all interactions to accumulate enough statistics for the upgrade physics programme. The objective is to accumulate 10 nb−1 of Pb–Pb collisions, recording about 1011 interactions. Within this upgrade strategy, the Inner Tracking System (ITS) upgrade forms an important cornerstone, providing improved vertexing and readout capabilities. The new ITS will have a barrel geometry consisting of seven layers of Monolithic Active Pixel Sensors (MAPS) with high granularity which would cater to the material budget, readout and radiation hardness requirements for the upgrade. The geometry is optimized for high efficiency, both in standalone tracking and ITS-TPC combined tracking. TowerJazz 0.18 μm technology is selected for designing the pixels for ITS upgrade. This technology provides attractive features like the option to implement a deep pwell allowing the implementation of a full CMOS process in the pixel. The ongoing research and development on these pixels investigates different design strategies and would converge towards the final design of the detector by the end of 2014. Several prototypes have been designed to investigate and validate the different design strategies and the different components of the pixel detector using this technology. The work presented in this thesis can be categorized in two parts. The first part concerns the results of characterization of some of the pixel prototype circuits developed for the ITS upgrade, in particular MIMOSA32, MIMOSA32Ter and Explorer-1. The second part discusses the detector performance studies of the upgraded ITS. MIMOSA32 and MIMOSA32Ter were one of the first prototypes designed with the TowerJazz technology in the upgrade programme. The motivation was to validate the technology. This thesis includes the results of tests and characterization of pixel structures of these prototypes and qualifies the technology in terms of charge collection and radiation tolerance and the usage of the deep p-well structure. This provides a starting point for future prototypes where the deep p-well could be implemented in a full CMOS process, thus allowing in-pixel sophisticated signal processing circuits. The Explorer prototypes are developed at CERN with the main motivation towards developing a detector with low power density, lower than the maximum permissible limits for the upgrade programme. This would provide a margin to reduce the material budget of the detection layers, improving the detector performance. The Explorer prototypes are designed to study the ratio of the collected charge to the input capacitance (Q/C), in particular, its dependence on the size of the collection diode and its distance to the adjacent p-well of the input transistors. The Explorer prototypes allows the application of a back-bias voltage which has an effect on the signal collection properties. In a pixel detector, improvement of the Q/C ratio enhances the signal amplitude at the collection node of the pixel circuit which is connected to the analog frontend. This would help in optimizing the analog frontend to improve the signal to noise ratio of the detector, which has a direct consequence in minimizing the power consumption of the detector. This thesis includes the test and characterization of Explorer-1 prototype circuits with different starting materials. The results show that Q/C improves with higher back bias voltage and increased spacing between the collection electrode and the adjacent p-well. With these results, the future prototypes of Explorer could concentrate on Optimizing the size of the input transistors to study its effects on the Random Telegraph Signal noise. In parallel, optimization of the signal processing circuits would also be carried out in other prototypes. The second part of the thesis studies the performance of a baseline configuration of the upgraded detector in terms of impact parameter resolution, momentum resolution and tracking efficiency both in standalone tracking mode and ITS-TPC combined tracking. The performance is compared with the current ITS to study the improvements in the upgraded ITS. The performance is affected by the radial position and material budget of the layers and the detector intrinsic resolution. The detector specifications in this regard are still evolving specially for the Outer Barrel (the outermost four layers). The studies show the effects of variation of the specifications in terms of material budget and intrinsic resolution on the detector performance. This would help to finalize the detector specifications for an optimized detector performance. The thesis also concludes that a reduction in the beam pipe radius (lower than the baseline upgrade scenario) would not affect detector performance but may facilitate the installation of the Inner Barrel. Redundancy studies show that the presence of a dead layer can degrade the detector performance significantly. This defines a key requirement of easy and rapid accessibility to the detector in the design of the upgraded ITS. The ITS upgrade timeline foresees the finalization of the final pixel architecture in late 2014. Mass production of the final circuit is planned for 2015. The construction of the detector modules, tests, assembling and pre-commissioning will be carried out throughout 2016-2017 followed by the installation of the detector in the ALICE cavern in 2018

IoT-Based Weather Monitoring System

Weather is hard to predict and has great significance in many regular activities. A weather station is an instrument or device that provides weather information in a local area. It serves a valuable role in the field of agriculture, industry, etc. for making informed decisions. The current weather stations available in the market are expensive and sometimes bulky also which causes inconvenience. The IoT-based weather station designed in the present work uses sensors and other components centrally controlled by a Raspberry Pi to detect, record and display various weather parameters such as temperature, humidity, wind speed, etc. in a specific location. The prototype design includes three DHT11 sensors for measuring temperature, a BME280 sensor for pressure and humidity, a cup anemometer for wind speed, and a rain gauge for determining the amount of rainfall. This work can be further extended to predict the weather as well