Wireless Sensor Networks (WSNs) have emerged as a prominent technology in various applications, including environmental monitoring, healthcare, and industrial automation. Energy efficient and reliable data routing is a fundamental challenge in WSNs due to the limited resources, energy constraints, and dynamic network conditions. This research paper presents a comprehensive survey of routing protocols in wireless sensor networks. Furthermore, the survey explores the strengths and weaknesses of different routing protocols, considering various factors such as network size, energy efficiency, scalability, and fault tolerance. It discusses the trade-offs involved in selecting a routing protocol and the impact of network dynamics on their performance. In this paper, the energy efficient routing protocols are surveyed with respect to their key features, and they are compared with each other. Challenging research issues of designing RL-based routing algorithms in WSNs are also discussed.

Electronic information is an asset for any organization, and even in the case of an individual, their data can be quite significant to them, which they cannot afford to lose. Information security has become very important in today’s computing world, and it demands potential counters to ever-evolving threats. An IDS is a security mechanism that examines the traffic of all users and applications in the system and detects instant attacks. IDS aim to detect attacks on the system from inside or outside. A typical IDS system examines and analyzes network traffic to detect and analyze attacks, and also to prevent any security violations by generating alarms for network administrator. In this dissertation paper we analyze the different mechanism as used previously by researchers and in currently using for identify the intrusion detection in a network. The proposed mechanism is based on the machine learning based classification model to improve the accuracy rate and performance parameters using the random forest and gradient boost decision trees. The results are compared here in performance parameters based evaluation to identify normal and abnormal attack.

The term "sentiment analysis" refers to one of the many specialized subfields that fall under the umbrella of "opinion mining." Textual information can be structured, semi-structured, or unstructured depending on the type of research being conducted in this discipline of social psychology. The goal of this research is to determine how members of the general public feel and think about a particular subject. This thesis contains a study that utilizes sentiment analysis, and the primary emphasis of that study is the database of IMDB movie reviews. In the work that we completed for our thesis, we offer a novel approach to an improved version of the Naive Bayes algorithm. This method was developed by us. TF-IDF is utilized in order to attain this goal successfully. The comparison is done out using datasets of specific sizes, and it is carried out on the basis of certain parameters, including mean square error, accuracy, precision, recall, and F1 score. The comparison between our work and other categorization algorithms has been completed, and our results have been proved to have a higher level of accuracy.

E-commerce has flourished in the recent decades. As an 16 increasing number of people are accustomed to online transactions, this has contributed to the prevalence of card payments. Unfortunately, the prevailing emergence of spending behavior has become an ideal condition for the increase in fraudulent activities. Fraud detection is to identify, monitor, and prevent potentially fraudulent activities from complex data. The recent development and success in AI, especially machine learning, provides a new data-driven way to deal with fraud. Machine Learning is considered as one of the most successful technique used for creating a fraud detection algorithm for fraud identification.

With respect to the importance of patient safety as a key component of healthcare, this study aims to identify competent nurses who can very well manage IV Cannulation insertion and its maintenance in each shift to enhance patient quality care and reduce the number of patient complaints caused by IV Cannulation by providing hands-on training to the nurses with simulation techniques. In view of the increased number of complaints, the campaign named “Confident to Cannulate” began which focused more on the complainant areas. A total of 1150 nurses were trained and were included in both pre and post-training practice check. Considering the study findings, it was observed that the campaign aids in reducing the number of patient complaints caused by IV Cannulation, the cannulation skills of Nurses improved from 20% to 87%, and also it helps in reducing phlebitis incidents in the hospital. Three nurses were found more efficient in IV cannulation and these three were selected and will be added to the IV Cannulation team.

As a payment instrument that provides credit services, credit cards bring great convenience to modern life. Credit card and debit card transactions are divided into online spending and offline payments. With the popularity of online transactions and the development of Internet technology, credit/debit card fraud cases are rapidly increasing. The detection and identification of credit/debit card fraud can help maintain the normal development of the credit card financial industry system, which is of great significance to the national economic development and social stability. This study makes a major contribution to research on the detection of Credit Card fraud transactions through Machine Learning Algorithms such as random forest, support vector machines, and multi layer perceptron.

There has been a worldwide energy crisis in recent years, leading to an increase in the demand for renewable energy resources. By using a hybrid power system, we can meet the need for energy while reducing our reliance on fossil fuels. This will help us to address the global energy crisis in a sustainable way. The non-renewable sources are going to be exhausted in a few decades more over it pollutes the environment in extreme level. The use of hybrid power systems can be beneficial to society in this case, as it supplies power at a constant rate and also can be eco-friendly when renewable source is available.

In this study, dense graded bituminous blend specimens are created using natural aggregate as coarse aggregates, bottom ash as exceptional aggregates, fly ash as filler, and sisal fiber as an additive. The proportion of mixture for dense graded bituminous macadam (DBM) grading has been accounted for in accordance with MORTH having nominal maximum aggregate size (NMAS) of 26.5 mm. To reinforce the mixture, slow-setting emulsion (SS-1)-coated sisal fiber is added in varying percentages of 0%, 0.25%, 0.5%, 0.75%, and 1% by weight of the mixture, with varying lengths of 5 mm, 10 mm, 15 mm, and 20 mm. On the initial stage of the research, specimens were prepared with two types of paving bitumen, VG30 and VG10. VG30 bitumen exhibited superior Marshall Characteristics in the initial trials and was therefore considered for the next phase of testing. Specific tests with Marshall Test outcomes were used to determine the marshal characteristics, most effective binder content, and most effective fiber content as well as the finest fiber length. Marshall balances as high as 15kN were obtained with a bitumen content of 5.57 percent, a fiber content of zero percent, and a fiber length of 10 millimeters. In addition, for the purpose of delivering the performance of the pavement, a number of overall performance evaluations, including a moisture susceptibility test, oblique tensile strength (ITS), creep test, and tensile energy ratio of bitumen mixtures, were conducted. Coal ash as a good mélange and filler, stabilized with natural sisal fiber and SS- 1 emulsion in advance, has been discovered to result in engineering properties that are not only high-quality, however also vastly superior. Utilization of non-traditional combinations, such as coal ash and natural fiber, may therefore aid in the discovery of a new method of bituminous pavement construction. By substituting natural sources of sand and stone soil for coal ash, it is possible to find a cost-effective method for its reuse. Coal ash dumping is a major concern for anyone concerned with its disposal and environmental contamination.

The developing interest for administrations with high information rates and high ghastly productivity is the way to quick mechanical advancement in the field of remote correspondence. Over the most recent two decades, remote correspondence has encountered a monstrous development with a mission to furnish new administrations with high information rates. Numerous new remote frameworks. These systems must have the capacity to give high information rate at passable bit error rate (BER), and least postponement. Orthogonal Frequency Division Multiplexing (OFDM) in conjunction with different radio wires MIMO-OFDM is one of such innovation anticipated that would give coveted administration measures. This paper presents, a new partial transmit sequence (PTS) technique, based on PTS with DWT and DCT technique, for two antennas STBC MIMO-OFDM system, is proposed and implemented which can achieve better PAPR performance at much less complexity.

In radio, multiple-input and multiple-output, or MIMO, is the use of multiple antennas at both the transmitter and receiver to improve communication performance. The terms input and output refer to the radio channel carrying the signal, not to the devices having antennas. MIMO technology has attracted attention in wireless communications, because it offers significant increases in data throughput and link range without additional bandwidth or increased transmit power. It achieves this goal by spreading the same total transmit power over the antennas to achieve an array gain that improves the spectral efficiency (more bits per second per hertz of bandwidth) and/or to achieve a diversity gain that improves the link reliability (reduced fading). In this work, present the literature works for wireless communication in MIMO using multiple sub-standards.

Mobile Ad-hoc Networks (MANETs) are a form of a network where the mobility of nodes is relatively high, making them ideal for mobile applications. In MANETs, nodes can move about quite a bit, which is why they're referred to as "moving networks". There is no set infrastructure in MANETs. Thus, nodes can come and go as they want. In theory, the computing power of each node should be equal. For a network to function correctly, mobile devices must work together to find and maintain routes for packets as they travel between them and their intended destinations. With mobile nodes, routes are constantly changing and need to be updated. This necessitates complicated routing algorithms. Since MANETs are dynamic, maintaining routes is challenging. When it comes to routing, it's all about finding the best way for data packets to go across a network. Routing information is critical to network communication's throughput, reliability, and congestion characteristics. In this paper, present the literature works for wireless communication using routing protocol for reactive routing techniques.

The stock market is often used in investment programs that promise high returns, but it also carries some risk. By their very nature, stock returns are highly volatile. These depend on various factors such as previous stock prices, current market trends, financial news and social media. Many methods such as technical analysis, fundamental analysis, time series analysis, and statistical analysis are used to predict stock values, but none of these methods have proven to be effective forecasting tools. This article examines various machine learning techniques and algorithms used to improve stock price prediction accuracy.

ELECTION is a process of establishing democracy in the country. It is also one of the most challenging task, one whose constraints are remarkably strict. There has been the extensive adoption of Direct-recording electronic (DRE) for voting at polling stations around the world. Starting with the seminal work by Chaum, published in IEEE Security & Privacy in 2004, research on end-to-end (E2E) E-voting has become a thriving field. Informally, the notion of being E2E verifiable refers to have two properties: First, each voter is able to verify if their vote has been cast as intended, recorded as cast. Second, anyone can verify if all votes are tallied as recorded. By contrast, in the traditional paper-based voting system, a voter cannot verify how their vote is recorded and tallied in the voting process. In traditional voting process, a voter goes to polling station and shows his/her voter Identity card and after finding his/her name in eligible voters list he is a given to vote the candidate of his choice. In the case of EVM(Electronic Voting Machine) their security is a big challenge before the officials. Thus the system depends on the trustworthy individual at the polling stations and during counting, thus leading to the introduction of the automated paperless secure e-voting system. This work mainly focuses on developing an E-Voting system which is much more secure, verifiable and does not involve the requirement of too many trustworthy individuals at every level. We aim at using Blockchain to make voting much secure and also using ring signature and Fingerprint Authentication for additional security.

Cooling towers are used in a variety of applications; from the 400-foot-tall towers at nuclear power plants to small 4 foot cooling boxes used by neighborhood dry cleaners. The most common use is in large building central cooling systems, but also used for refrigeration, cold storage facilities, dry cleaning, medical equipment, manufacturing and industry. Cooling towers are generally the most efficient means to remove large amounts of heat from air and equipment. Unfortunately, cooling towers use large amounts of water when properly maintained, and can waste greater amounts of water when not maintained properly through wasteful practices, inefficient equipment and leaks. Industrial cooling towers are used to remove surplus heat from water. In this study, a review study is carried out to investigate different types of cooling towers, their application, performance, usage and working principles, which can be useful in the field of nuclear plants as well as other energy stations. A number of investigations have been considered to reveal differences between the used cooling towers and finally a Fluent simulation has been carried out to examine major contours and flow field around the cooling tower.