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Addressing the challenges of handling missing data in Data science applications
Missing data is a common issue in data science applications that can significantly impact the accuracy and reliability of data analysis and modeling. This paper explores the challenges associated with missing data and presents various approaches and techniques to effectively handle missing data in data science applications. We discuss both traditional statistical methods and advanced machine learning techniques that can be employed to address missing data. Additionally, we highlight the importance of understanding the underlying mechanisms causing missingness and the implications it has on data analysis. Through this paper, we aim to provide a comprehensive overview of the existing methods and methods for dealing with missing data, offering insights into their practical applicability and future research directions in this field.
Beauty in Mathematics
"Rightly viewed, mathematics possesses not only truth, but supreme beauty—a beauty cold and austere, like that of sculpture, devoid of appeal to any part of our weaker nature, devoid of the gorgeous trappings of painting or music, yet sublimely pure, and capable of a stern perfection such as only the greatest art can show." The true spirit of delight, exaltation, and the experience of being more than Man, which is the test of the highest excellence, can be discovered in mathematics just as easily as in poetry."
Automated Sericulture System
This paper is focused on Sericulture which denotes to the rearing of silkworm to produce silk. Parameter like Temperature, Humidity and light intensity are the important factors in the progression of silkworms and suitable encouraging must be done according requisites in every stage. Sericulture alludes to the raising silkworms to deliver silk; India is the second highest producer of silk in delivering 15% of the aggregates silk creation alongside China. Silk is called the queen of tensile properties. Although there are several commercial species of silkworm monitoring is a greatest challenge for the farmer. Silk worms in every stage, especially during the development of larva. Disinfection is one of the reproving parameters to be considered for healthy and successful silk worm rearing, sericulture is the significant occupation in the country side of India. Hence there exists the need of using innovation in sericulture cultivate .Aim of our project is to protect the silkworms from the proper environmental parameters and making the system automated. Automated sericulture system using IOT is to detect the temperature, Humidity, air quality, rain, etc.., through buzzer and automatically switching on exhaust fan and lights. In this project we use mq2 sensor to detect smoke which produces noise through the buzzer. The temperature, water and humidity sensor are also used to sense the parameters respectively and shows real time updates to the user of the server. The sericulture system use to get affected by the existing methods with more human interventions. Our method is automated which can reduce the work of the people. And this system can be used as the base to many other projects like baby monitoring system, green house monitoring system, mushroom and broccoli monitoring system.
A Study of Cyber Security Challenges and its Emerging Trends on Latest Technologies
Cyber security is a critical concern in today's digital age, where organizations and individuals face a multitude of evolving threats. The rapid advancement of technology has brought about new challenges and vulnerabilities that require continuous examination and understanding. This study aims to explore the cyber security challenges and emerging trends arising from the latest technologies, shedding light on the risks and opportunities that accompany these advancements. The study also explores the emerging trends in cyber security, including the integration of machine learning and AI-based solutions. These technologies enhance threat detection and response capabilities by analyzing vast amounts of data, identifying patterns, and enabling proactive mitigation of risks.
Mitigation of Common Mode Voltage in Induction Motor Employing Multilevel Inverter
Induction motor (IM) is a usually a constant speed motor. The Basic technique used to control and run the machine in variable speed drive application can be obtained by two level inverters, which can be controlled digitally with the help of microcontroller using sinusoidal pulse width modulation method. Thereby at the star terminal point of the load there is a voltage existed with respect to system ground. Hence it is defined as “common mode voltage”. Due to the common mode voltage, there is an electromagnetic interference that is induced. Thereby it causes lot of disturbance to the communication and electronic equipment’s, which are nearby to the system. The common mode voltage can be reduced with the help of high-level inverter that can be used for example two-level, three-level, four-level inverters etc. In this proposed system we are reducing the common mode voltage by using two level inverter & three level inverter. In this paper, mitigation of CMV is simulated through MATLAB and implemented by hardware setup.
Brain Tumor Detection using Convolutional Neural Network
Brain Tumor Detection is one of the maximum important and worrying tasks in the discipline of scientific picture processing, as human-assisted manual type can result in erroneous prediction and prognosis. Brain tumors have excessive range in size and appearance and at instances there's a similarity among tumor and normal tissues and therefore the extraction of tumor areas from MRI scanned pictures turns into unyielding. Tumor can be diagnosed by the use of medical imaging techniques like Magnetic Resonance Imaging (MRI), but the disadvantage is that it can't stumble on tumors which are underneath 3 mm length. To address with this a massive dataset must be surpassed to teach the version to be more correct and efficient. Photo segmentation is a totally essential and critical step in picture processing which determines the achievement of superior degree of picture processing. The contemporary scenario provides structures that come across brain tumors, but handiest use small datasets and photo processing strategies and their accuracy is relatively low as in scientific subject we ought to have peek accuracy. To tackle this, we proposed a way to extract brain tumor from Magnetic Resonance brain pictures (MRI) by way of Fuzzy C-manner clustering algorithm which changed into observed with the aid of traditional classifiers and convolutional neural network.
ASTROPHYSICS
Astrophysics is a branch of space science that applies the laws of physics and chemistry to seek to understand the universe and our place in it. The field explores topics such as the birth, life and death of stars, planets, galaxies, nebulae and other objects in the universe. The Astrophysics creates physical theories of small to medium-size objects and structures in the universe.
AR Assistant for Indoor Navigation
In this study, we discuss the problem of indoor autonomous robotic navigation. By using an Android smartphone and the JAQL robot, a system is created dedicated for indoor navigation based on AR is developed. We want to learn more about how augmented reality can now be implemented to solve the problems of navigating without GPS. We created a smartphone application that serves as the system's eyes and brain at the same time using Google's AR core. We emphasize AR core's features and describe how they were used in all of our tasks. Assessment of the performance of the whole architecture is done and a report of the findings from a series of tests conducted under various conditions in a real-world setting is made. We finish by examining the system's advantages and disadvantages as well as potential future developments.
Image Processing
Image processing entails altering an image's composition to enhance its graphical content for human interpretation and autonomous machine perception. Digital image processing is a subset of the electronic domain in which an image is transformed into a collection of tin y numbers, or pixels, that reflect a physical property, like s cene radiance, are stored in a digital memory, and are then processed by a computer or other digital hardware. Two key application areas have sparked interest in digital i mage processing techniques: improving pictorial information for human interpretation and processing image data for storage, transmission, and representation for autonomous machine perception. Boundaries are described by edges, and as edge detection i s one of the most challenging image processing tasks, it is an issue of fundamental significance .
High Availability and Fault Tolerance in AWS
With the increasing adoption of cloud computing, ensuring high availability and fault tolerance has become paramount for organizations. Amazon Web Services (AWS) offers a robust infrastructure for hosting applications, but it requires careful architectural design and implementation to achieve desired levels of availability and fault tolerance. This research paper explores two innovative concepts, namely Cloud Fractal and Decentralized Replication and Orchestration, and their application in achieving high availability and fault tolerance in AWS. We present a comprehensive analysis of these concepts and provide practical guidelines for their implementation in real-world scenarios. Our findings demonstrate the effectiveness of Cloud Fractal and Decentralized Replication and Orchestration in enhancing the reliability and resilience of AWS deployments. Keywords: Fault Isolation, High Availability, Load Balancing, Auto-scaling, Disaster Recovery, Data Replication, Backup and Restore, Fault Tolerance, Cloud Computing, Amazon Elastic Compute Cloud (EC2), Amazon Relational Database Service (RDS), Amazon Simple Storage Service (S3), AWS Elastic Load Balancer (ELB), Complexity, Operational Management, Cloud Fractal, AWS Lambda, Amazon SQS, Decentralized Replication and Orchestration (DOI).
Al6061-Basalt and Zircon Hybrid composite Material Corrosion Resistance in Acid Media
The present investigation is an attempt made to develop Al6061/Basalt/Zirconium oxide Hybrid Metal Matrix Composites (MMCs) by liquid metallurgy technique (stir casting) and to study the wear properties of Al6061/Basalt/Zirconium oxide reinforced hybrid metal matrix composites. The composite is prepared by using Liquid Metallurgy Route (Stir Casting Technique), although other processing technique such as powder metallurgy delivers better mechanical properties in MMCs, Liquid state has some significant focal points, for example, better matrix molecule holding, simpler control of matrix structure, ease of handling, closer to net shape and wide choice of material. Al6061 is taken as a base material (matrix) and Basalt (1– 10%) and Zirconium oxides (2%) are used as reinforcements. Corrosion analysis for Aluminum Metal Matrix Composites (MMCs) was done in acid (HCl) media at room temperature & different time intervals. The results were tabulated & it was found that the MMC containing 4% basalt underwent maximum corrosion at room temperature. SEM is done for all the samples the results are tabulated.
Enhancing Cyber Security through the utilization of Blockchain Technology
In today's digital era, cybersecurity is a matter of utmost importance as both organizations and individuals confront growing risks from unauthorized access attempts aimed at sensitive data and systems. Blockchain technology, initially developed as the foundation for cryptocurrencies like Bitcoin, has emerged as a promising solution to enhance cybersecurity. Operating as a distributed ledger that records transactions across multiple computers, blockchain brings forth several essential characteristics that can contribute to bolstering cybersecurity. While blockchain technology offers numerous advantages in terms of cybersecurity, it also introduces its own set of challenges and considerations, including scalability, privacy, and the potential vulnerabilities of smart contracts. The implementation of cybersecurity solutions based on blockchain necessitates meticulous design, robust key management, and a comprehensive understanding of the specific use case and associated risks. Overall, the incorporation of blockchain technology in cybersecurity holds the potential to elevate transparency, integrity, and resilience, empowering organizations and individuals to mitigate the risks posed by cyber threats and improve their overall security stance. This paper, which involves the analysis of 15 researchers, explores various use cases for applying blockchain in the field of cybersecurity. A significant focus among the researchers centers on leveraging blockchain to safeguard IoT devices, networks, and data. Furthermore, the paper delves into how blockchain can offer security measures for three problematic areas within IT that have been identified by previous studies.
Waste Management Using IoT
The growing population and the need to improve livability in cities have led to the development of smart cities usingemerging technologies such as the Internet of Things (IoT). Wastemanagement is a critical aspect of a smart city as it impacts thehealth of citizens and the environment. To address this issue, ourresearch focuses on using IoT to collect data and applying multi-agent deep reinforcement learning algorithms to extract meaningfulinsights from the data. The data is used to provide notifications, extract insights, and predict waste fill levels to optimize wastecollection routes. Our proposed framework is hardware-agnosticand can effectively interface with a wide variety of hardware while keeping the architecture abstracted.
Towards Strong AI with Analog Neural Chips
Applied AI chips with neural networks fail to capture and scale different forms of human intelligence. In this study, the definition of a strong AI system in hardware and architecture for building neuro memristive strong AI chips is proposed. The architecture unit consists of loop and hoop networks that are built on recurrent and feed forward information propagation concepts. Applying the principle that ’every brain is different’; we build a strong network that can take different structural and functional forms. The strong networks are building using hybrids of loop and hoop networks having generalization abilities, with higher levels of randomness incorporated to introduce greater flexibility in creating different neural architectures.
Smart Navigation and Inspection System for Aquaculture Development under Controlled Parameters
Aquaculture is a rapidly growing industry that provides a critical source of food for millions of people worldwide. However, fish farmers face significant challenges such as environmental pollution, disease control, and inadequate water quality control systems. To address these challenges, intelligent monitoring and control systems are necessary. One promising technology that can improve monitoring efficiency and reduce human error is the use of autonomous underwater vehicles (AUVs) in cage aquaculture. AUVs can operate in harsh and challenging environments, collect data on water quality, temperature, and other environmental factors, and provide detailed information on fish health and behavior. Implementing AUVs in cage aquaculture can improve sustainability by reducing waste and minimizing environmental pollution, and aid in surveillance activities to detect illegal fishing and other unauthorized activities. Additionally, AUVs can assist in infrastructure inspection to identify and repair damaged equipment. In conclusion, the aquaculture industry faces significant challenges that can lead to substantial losses. Intelligent monitoring and control systems, along with the use of AUVs, can help mitigate these challenges by providing real-time information on fish health, cage condition, and the environment. Implementing these technologies can promote a more sustainable and profitable aquaculture industry, ensuring a reliable source of food for millions of people worldwide.
The Impact of Social media on Mental Health
Social media has become an integral part of our lives, with over 3.6 billion people using it worldwide. While social media can be a great way to stay connected with friends and family, it can also have a negative impact on mental health. Research findings have consistently demonstrated a correlation between social media usage and heightened levels of anxiety, depression, as well as feelings of loneliness. This is likely due to a number of factors, including the comparison trap, cyberbullying, and the constant stream of information
Challenges and Open Issues in Cloud Computing and 5G Integration
Both cloud computing and 5G have the potential to completely disrupt a number of industries, including telecommunications, healthcare, finance, and transportation. Enhanced connectivity, faster data transmission, lower latency, and higher scalability are all promised by the union of cloud computing and 5G. However, the combination of these two technologies also brings about a number of difficulties and unresolved problems. In order to provide insights into potential solutions, this article attempts to investigate the main concerns and obstacles at the junction of cloud computing and 5G. In order to understand the challenges and opportunities that lie ahead, it looks into network design, security and privacy, resource management, and application development. We can enable the seamless integration of cloud computing and 5G, releasing their full potential, by addressing these difficulties.
Examination Scheduling for an Educational Institution that follows a Choice-based credit system
Examination scheduling is a common as well as an important activity in an educational institution. In examination scheduling, courses are allocated a time slot in such a way that no student is assigned to attend more than one examination at a time. Further, the scheduling includes allocation of physical resources like exam room, invigilator to an examination without any conflicts. The complexity of an examination scheduling depends on many factors like nature of educational program, number of students, number of staff, time limit and availability of other resources. In this study, we developed a solution for examination scheduling in an educational system that follows a choice-based credit system. We used heuristic searching in multiple stages to arrive an optimal solution. We used Prolog, a logical programming language, SQL, PHP and HTML to develop this software. Also in this solution we limit ourselves to allocation of time slots to a course and we don’t include allocation of other physical resources like class rooms, invigilators.
A Novel Framework for the Psychology of Decision Making
Decision making is a complex process influenced by cognitive, affective, and contextual factors. We propose a novel framework that integrates insights from cognitive psychology, social psychology, and neuroscience. The framework consists of three main components: information processing, evaluation, and decision. We discuss how each component contributes to the decision-making process and how they interact with each other. The framework can be used to understand and improve decision making by identifying and addressing potential biases and errors.
Handwritten Digit Recognition using Machine Learning with Python
Handwritten Digit Recognition is one of the essentially significant issues in pattern recognition applications. The main purpose of this project is to build an automatic handwritten digit recognition method for the recognition of handwritten digit strings. This paper proposes a simple convolution neural network approach to handwritten digit recognition. Convolutional Neural Network model is implemented using MNIST dataset. This dataset consists 60,000 small square 28×28pixel grayscale images of handwritten single digits between 0 and 9. The applications of digit recognition include postal mail sorting, check processing, form data entry, etc. The core of the issue exists in the capacity to foster a proficient calculation that can perceive manually written digits and which is put together by clients by the method of a scanner, tablet, and other computerized gadgets.