Artificial Intelligence : The Supermind - A Review

Artificial intelligence (AI) is one of the most important technologies in the world today. In the future, intelligent machines will replace or enhance human capabilities in many areas. Artificial Intelligence is impacting the future of virtually every industry and every human being. AI has acted as the main driver of emerging technologies like big data, robotics, and IoT, and it will continue to act as a technological innovator for the foreseeable future. AI is simply the study of how to make computer do things which at the moment people do the better. There are many ways to define AI, but one simple definition is “intelligence demonstrated by machines”. Primary goal of AI is to improve computer behaviour so that it can be called intelligent. AI is ubiquitous and is not only limited to computer science but has evolved to include other areas like health, security, education, music, art, and business application. This paper gives an overview of how the AI actually works, its scopes , the different applications of AI, its advantages and disadvantages and many more topics which will give a clear understanding inspite of the boundlessness of AI.

A Linear Regression Model for THD Sensitivity in PV Based Microgrid with Varying Insolation Levels

Solar PV systems can be used for powering small microgrids in rural area of developing countries. Generally, a solar power microgrid consists of a PV array, an MPPT, a dc-dc converter and an inverter, particularly as the general loads are A.C in nature. In a PV system, reactive current, unbalancing in currents, and harmonics are generated due to the power electronics-based converters as well as nonlinear loads (computers induction motors etc). Thus, estimation of the harmonics levels measured by the Total Harmonic Distortion (THD) is an essential aspect of performance assessment of a solar powered microgrid. A major issue that needs to be examined is the impact of PV system control parameters on the THD. In this paper, we take up this assessment for a small PV based rural microgrid with varying levels of solar irradiance. A Simulink model has been developed for the study from which the THD at equilibrium conditions is estimated. This data is in turn used to design a generalized Linear Regression Model, which can be used to observe the sensitivity of three control variables on the magnitude of the THD. These variables are: Solar Irradiance levels, Power Factor (PF) of connected load magnitude of the connected load (in kVA) The results obtained show that the greatest sensitivity is obtained for load kVA variation.

Yognidra to Minimizing Stress during Pandemic: A Meta Analysis

The COVID-19 pandemic has had an influence on people's physical, emotional, and social health all across the world. Due to mental health issues that resulted in anxiety, sadness, and post-traumatic stress disorder symptoms among a variety of demographic groups, including healthcare staff, the general public, patients, and those who were confined. Yoganidra Meditation is an excellent meditative relaxation method for relieving stress and tension and achieving profound psychological and physiological benefits. According to studies, Yognidra can also be utilized as a therapeutic approach to treat psychological problems such as anxiety, anger, and sleeplessness, as well as psychosomatic illnesses such as asthma, coronary heart disease, cancer, and hypertension. The purpose of the study is to critically analyze the findings of other researchers on the application of Yognidra to reliving the stress of an individual. The study is a conceptual and qualitative Meta-analysis, and it deals with global stress management.

Estimation of Parameters of PTRC SRGM using Non-informative Priors

Reliability is an essentially important characteristic of software. The reliability of software has been assessed by considering Poisson Type occurrence of software failures and the failure intensity of one parameter say (η_1 ) Rayleigh class. Here, it is assumed that the software contains fixed number of inherent faults say (η_0 ). The scale parameter of Rayleigh density (η_1 ) and fixed number of inherent faults contained in software are the parameters of interest. The failure intensity and mean failure function of this Poisson Type Rayleigh Class (PTRC) Software Reliability Growth Model (SRGM) have been studied. The estimates of above parameters can be obtained by using maximum likelihood method. Bayesian technique has been used to about estimates of η_0 and η_1 if prior knowledge about these parameters is available. The prior knowledge about these parameters is considered in the form of non- informative priors for both the parameters. The proposed Bayes estimators are compared with their corresponding maximum likelihood estimators on the basis of risk efficiencies under squared error loss. The Monte Carlo simulation technique is used for calculating risk efficiencies. It is seen that both the proposed Bayes estimators can be preferred over corresponding MLEs for the proper choice of the values of execution time.

Spectral Emission Mask Shaping for OFDM in Cognitive Radios

Orthogonal frequency division multiplexing (OFDM) is characterized by spectral efficiency. It enables flexible and agile spectrum allocation. But still it lags as it suffers from spectral leakage in the form of large side lobes. It leads to inter-channel interference if not handled carefully.in proposed system spectral emission mask system is implemented to combat spectral leakage and ultimately avoiding adjacent channel interference. A spectral mask, also known as a channel mask or transmission mask is a mathematically-defined set of lines applied to the levels of radio (or optical) transmissions. The spectral mask is generally intended to reduce adjacent-channel interference by limiting excessive radiation at frequencies beyond the necessary bandwidth. The proposed system is implemented over MATLAB platform using script language.

The Ultimate Bond

Being introduced in India in 1956 as an easy –to-use white glue for carpenters in replacement of Saresh (fat-based adhesives), the ULTIBOND company started its journey and never looked back. As The ULTIBOND Company was well known to recognize the need of their product and convert it into a marvelous opportunity, the company started manufacturing AI glue products for students as well as for professional and educational institutes. In order to shift end-users from natural glues and other synthetic adhesives available at the time, AI glue embarked on a bold marketing game plan. Instead of selling through stores, AI glue approached carpenters directly. This direct marketing initiative was one of the most successful strategies employed by the company and helped the brand gain a strong foothold in the white glue market. By 1965, the brand was big enough to develop its own manufacturing plant in Maharashtra. Primarily the company decided to enter into the retail market with a packaging of 33 grams collapsible tube in early 1970’s, later came up with many other unique packaging styles to cater the need and requirements of different segments of its customer base.

Soil Structure Interaction in High-Rise Buildings for Dynamic Loads

Soil-structure interaction(SSI) analysis is the study of the dynamic response of a structure as influenced by the interaction with the surrounding soil. The SSI response is sensitive to the characteristics of the soil, structures, and ground motion, as well as the depth of embedment. The concept of soil-structure interaction was introduced , and the research methods were discussed. This report presents a synthetic of the body of knowledge contained in SSI literature, which has been distilled into a concise narrative and harmonized under a consistent set of variables and units. Specific techniques are described by which SSI phenomena can be simulated in engineering practice, and recommendations for modeling seismic soil-structure interaction effects on building structures are provided. An attempt was made to summarize the all terms in this area of study.

A Comparative Performance Study of Classification Models for Opinion Mining

Opinion mining has become a major part in today's economy. People would want to know more about a product and the customers opinion before buying it. Companies would also want to know the opinions of the customers. Therefore, analyzing the customer’s opinion is important. A new customer would consider a product as good by analyzing the opinions of other customers. The opinions are collected from various areas, which include blogs, web forums, and product review sites. Classifying these large set of opinions requires a good classifier. In view of this, a comparative study of three classification techniques - Naive Bayes classifier with Kernel Density Estimation (KDE), Support Vector Machine (SVM), Decision Tree and KNN was made. To evaluate the classifier accuracy, precision, recall and F-measure techniques are used. Experimental results show that the Naive Bayes with Kernel Density Estimation (KDE) classifier achieved higher accuracy among others.

Blue Eyes Technology

The Blue Eyes technology aims at creating computational machines that have perceptual and sensory ability like those of human beings. It uses non-obtrusive sensing method, employing most modern video cameras and microphones to identify the user’s actions through the use of imparted sensory abilities. The machine can understand what a user wants, where he is looking at, and even realize his physical or emotional states. The Blue Eyes Technology developed is intended to be a complex solution for monitoring and recording the operator’s conscious brain involvement as well as his/her physiological condition. This shows yet another development in the field of Brain Computer Interface. The basic idea behind this technology is to give the computer the human power. We all have some perceptual abilities. That is we can understand each other’s feelings. For example we can understand one’s emotional state by analysing his facial expression. If we add these perceptual abilities of human to computers would enable computers to work together with human beings as intimate partners. The “BLUE EYES” technology aims at creating computational machines that have perceptual and sensory ability like those of human beings. This paper discusses the concept of blue eyes technology.

A Comparative Study of Fundamental and Technical Analysis on Private Sector Banks

All investment is the allocation of money to assets that are expected to yield some gain over a period of time. One of the best high risk and return investments was buying shares in stock exchange. Through these fundamental and technical analysis helps to reduce the risk. The fundamental analysis is used to understand the trend and growth of the economic, industry and company. For this analysis investor used many tools like EPS, PE ratio, Book value, ROE, etc. The technical analysis is used to understand price moment of the stocks and index. For this analysis investor used many tools like Trend, Support and Resistance, RSI, MACD, etc. From this study investors can able to understand and find low risk stocks in Nifty Private Bank. There is no analysis tools and strategy to find the risk free stock. This analysis helps to find the profitable stocks in Nifty Private Bank.