Baseball is a sport of statistics. The industry has accumulated detailed offensive and defensive statistical data for over a century. Experience has shown that data analysis can give a competitive advantage compared to teams without using such analysis. In the last two decades, with the development of machine learning and artificial intelligence, we have had more advanced algorithms to analyze data in baseball. In the following research, we will run different ML models using sci-kit-learn and H2O on Colab, and the Caret package on RStudio to examine the datasets (hitting dataset and salary dataset) and determine the undervalued players by predicting the number of runs scored in the next year. We will compare machine learning regression algorithms and ensemble methods and give comprehensive explanations of the result. The suggestion of which model is superior in terms of prediction accuracy will be determined.

In the modern era, technology has played an inevitable role Population of India is almost equivalent to 17.7% of the world population. On the basis of arable land area, India is placed second largest in the world. Even though India is the second largest producer of rice, biggest problems faced by farmers in our country is lack of knowledge in the technological development. The number of smart phone users will be more than 800 million by the end of 2022. Under this circumstance, Internet of Things (IoTs) has a major role in the agriculture field for productivity by monitoring day to day progress of the field. IoT aims to take internet connectivity to another level by connecting multiple devices at a time to the internet, thereby facilitating man to machine and machine to machine interactions. With the agricultural apps installed in the smart phone, farmers can realize the progress of the crop as well as the schemes and subsidies announced by the authorities. This paper reveals the importance of Internet of Things in the agriculture sector.

The development of Big Data (BD), which is used to obtain numerous data from various domains, is brought about by technological advancement. However, managing the information and extracting knowledge from it is the most challenging and problematic. Thus, this paper proposed a template-centric new Data Acquisition (DAQ) methodology. The stock market data is gathered from several structured or unstructured data sources. After the DAQ criterion, templates are created for the gathered data. The stock market data is collected grounded on its Application Programming Interface (API) and transmitted via the transmission protocols during the DAQ process. To effectively remove redundant data, the transmitted data is pre-processed and stored efficiently in the network for further real-time analysis. Finally, the proposed technique’s performance is evaluated. As per the experimental and empirical evaluation, the proposed system surpasses the other methods.

The Cyber is the term closely relating to or characteristic of the culture of computers or computer networks, information technology, and virtual reality. The Internet is a global network of billions of computers and other electronic devices using standardized communication rules or protocols. A total of 5.07 billion people around the world use the internet today – equivalent to 63.5 percent of the world's total population. Internet users continue to grow too, as of 2022, China had over one billion internet users, more than any other country in the world. India ranked second, as close to 933 million Indians accessed the internet via any device. Cybercrime is criminal activity that either targets or uses a computer, a computer network or a networked device. The slogans used to address data privacy are: “Data privacy belongs to you.” Lock it down, protect it, and block hackers. This paper reveals the issues related to categories & impact of cyber crime, basic cyber laws, security threats and protection which are a warning alarm to internet users.

MRI systems with proprietary hardware must use pulse programming, which is less expensive. Pulse programming consoles use Digital Signal Processor, Complex Programming Logic Device, and microcontrollers, which are typically restricted to particular architectures. General–purpose, extremely affordable electronics board featuring these architectures are now capable enough to be directly implemented in MRI consoles. Here we present the architectural details of various consoles with novel designs and their limitations. Finally, we propose a console design which was created utilising widely accessible Arduino Boards to connect to Pulseq-GPI implementations at a reduced cost of $225

Enterprise application integration quickly arose as a problem for companies and solutions were proposed including point-to-point architecture, ETL (Extract, Transform and Load), EAI (Enterprise Application Integration) and ESBs (Enterprise Service Bus). With the rise of virtualization, how applications in a physical environment could interact with those that are in a virtualized environment. The objective of this paper is to study and define a Service Oriented Architecture (SOA) in a semi-virtualized environment. The authors propose an architecture which allows service integration in a semi-virtualized environment. This study uses a survey-based technique to seek which technology can be used in the considered environment. A state-of-the-art of the various IT designs and solutions enabling SOA implementation is presented. ESB technology has been retained for this study. A literary review is done on ESB to examine how it could be used in the semi-virtualized context. The findings of this study propose an architecture which allows service integration in a semi-virtualized environment. After an in-depth examination of different deployment possibilities and technical solutions proposed for this purpose, a new architecture based on the Enterprise Service Bus (ESB) is proposed for semi-virtualized context. This architecture is organized around two ESB solutions each deployed in an environment and interconnected by a communication bridge which ensures message routing between the two ESB buses. A practical deployment phase is carried out for illustration under Talend Open Studio with encouraging results. The proposed architecture is a good solution for companies whose information systems operate in a semi-virtualized environment.

Environmental pollution and climate change is the ultimate result of rapid urbanization. The change in environmental conditions due to undesirable human activities increases local ambient temperature hence it is leading to a rise in the river water temperature. Tapi river is the main source of drinking water for Surat city, Gujarat, India. A stretch of river Tapi has been studied from Kamrej to Causeway which has a stretch of about 22.39 km. The river water quality was found to be degraded due to the excessive discharge of pollutants from various points and non-point sources. Extreme discharge of pollutants into the river decreases the dissolved oxygen (DO) concentration. At the same time due to the increase in temperature, the process of transformation of atmospheric O2 gas into dissolved form also becomes very slow. In this study, the QUAL2Kw one - dimension water quality model was applied to assess the DO and BOD at various locations. The QUAL2Kw model was calibrated and validated with observed data. The calibrated model was applied to evaluate the effects of temperature on the DO and BOD of the Tapi river. The conditions of maximum, minimum, and average temperature for March, April, and May from the year 1991 to 2021 were considered. The result revealed that the full stretch of 22.39 km was not able to maintain minimum dissolved oxygen (DO) concentration, hence biochemical oxygen demand (BOD) has subsequently increased downstream of the river stretch. It was also observed that DO and BOD levels tremendously fluctuate ambient temperature.

Titanium-Niobium (Ti-Nb) based alloys are predominantly used as an implant material within the Bio-medical field due to their unique characteristics such as non-toxicity, better Osseo-integration, high resistance to corrosion, high strength to weight quantitative relation and biocompatibility. This paper proposes to optimize the control parameters for multi-response optimization of Ti-6Al-7Nb bio-medical alloy based Grey Relational Analysis combined with the Taguchi approach. Wear rate (WR), coefficient of friction (COF), and frictional force were the response characteristics studied (FF). The Taguchi methodology is used in conjunction with the grey interpersonal evaluation as a performance index to determine the best set of control parameters. Applied Load, Rotational Speed, and Time were the control parameters evaluated. Experimentations are designed using L9 Taguchi's orthogonal array and carried out on a pin-on-disc setup in agreement by ASTM G99. The experimental outcomes display that the applied load has the greatest impact on the Ti-6Al-7Nb bio-medical alloy's various wear characteristics. This approach has been successfully rummage-sale to recover the wear response of Ti-6Al-7Nb bio-medical alloy.

Cognitive radio technology is growing positive solution for the effective utilization of the bandwidth for IoT device networks. The fixed spectrum allocation scheme leads to insufficient spectrum utilization, to overcome this problem, the stochastic resource allocation algorithm is proposed in the present work. This method of internet spectrum allocation considerably increases the performance of IoT sensor network by utilizing the internet spectrum by non-cognitive inactive IoT sensors (white space/spectrum holes) by continuous spectrum sensing. In this paper we have discussed the effective resource allocation for interweave and underlay conditions and also at variable interference constraints (short time and longtime spectrum sensing) of IoT network. The arecanut plantation for agriculture scenario is considered in the present paper and the sensor environment simulation is performed using MATLAB.

Due to the fact that most offices and educational institutions now operate from home, the work-from-home and study-from-home cultures have made it difficult to interact with persons who are deaf or hard of hearing. These people communicate within their society using sign language, which is not widely understood by others. Most of the time, as a result of this, they miss out on the opportunity to express their point in front of every one since they are ignored/passed over without receiving the necessary attention. In real-time, having an independent translator that can process photos and interpret signs quickly at the speed of streaming images is critical. We'll utilize TensorFlow Object Detection and Python to bridge the gap by creating an end-to-end bespoke object detection model that not only translates sign language in real time but also speaks it to others.