Analyzing the Performance and Efficiency of IT-Compliant Audit Module Using Clustering Methods

Human beings have a knack for errors. Counter-effective actions rendered to specify and rectify such errors in a minimum period of time are required when effectiveness and swift advancement depends on the capability of acknowledging the faults and errors and repair quickly. The software as audit module application in IT complaint is in review in this commentary as is another significant instrument created in the field of data analysis that digs deep into quickly and successfully assessing the imprecisions or grievances identified by the users in a certain company. The target of this study is to evaluate the statistical significance in relationship between client reporting attitude and client reliability and to evaluate the impact of strong responsiveness on client reliability, to measure the statistically noteworthy effect of client grievance conduct on service quality, and to test the impact of service quality on client dedication.

Semantic Analysis of Videos for Tags Prediction and Segmentation

Due to the growing volume of multimedia data generated these days, it has become extremely difficult to manually analyze the data and extract useful information from it. Especially the analysis of videos pertaining to different fields such as surveillance, videos, social media, education, etc. cannot be done efficiently by manual methods. This requires automatic analysis algorithms that can intelligently analyze videos and derive salient information from them. This information can be useful in a number of tasks such as video segmentation, incident detection, anomaly detection, query-based video retrieval, and content censorship. This chapter provides a detailed review of the techniques proposed for video analysis to provide a compact set of video tags. This chapter considers it a joint tag-segmentation problem and critically analyzes the relevant literature to highlight their respective pros and cons. At the end, potential research areas in this domain and suggestions for improvement are discussed.

A Survey on Intrusion Detection in Wired and Wireless Network for Future IoT Deployment

An intrusion detection system (IDS) works as an alarm mechanism for computer systems. It detects any malicious activity that happened to the computer system and it alerts an alarm message to notify the user there is malicious activity. There are IDS that are able to take action when malicious or anomalous networks are detected, which include suspending the traffic sent from suspicious IP addresses. The problem statement for this project is to find out the most accurate machine learning algorithm and the types of IDS with different placement strategies. When it comes to the deployment of a wireless network, IDS is not as easy a task as deploying a traditional network IDS. There are many unexpected complexities of the problem of reliable intrusion detection in a wireless network. The motivation of this research is to find the most suitable classification techniques that are able to increase the accuracy of an IDS. Machine learning is useful for the upcoming trend; it provides better accuracy in the detection of malicious traffic.

A Survey on Algorithms in Deep Learning

In the last couple of years, artificial neural networks have gained considerable momentum. Their results could be enhanced if the number of layers could be made deeper. Of late, a lot of data has been generated, which has led to big data. This comes along with many challenges like quality, which is one of the most important ones. Deep learning models can improve the quality of data. In this chapter, an attempt has been made to review deep supervised and deep unsupervised learning algorithms and the various activation functions used. Challenges in deep learning have also been discussed.

Analysis of Climate Prediction and Climate Change in Pakistan Using Data Mining Techniques

Weather forecasting is a significant meteorological task and has arisen in the last century from a rational and revolutionary point of view among the most difficult problems. The authors are researching the use of information mining techniques in this survey to measure maximum temperature, precipitation, dissipation, and wind speed. This was done using vector help profiles, decision tree, and weather data obtained in Pakistan in 2015 and 2019. For the planning of workbook accounts, an information system for meteorological information was used. The presentations of these calculations considered using standard implementing steps as well as the estimate that gave the best results for generating disposal rules for intermediate environment variables. Likewise, a prophetic network model for the climate outlook program, contradictory results, and true climate information for the projected periods have been created. The results show that with sufficient information on cases, data mining strategies can be used to estimate the climate and environmental change that it focuses on.

ACO-Based Algorithms in Wireless Sensor Networks

Wireless sensor networks (WSN) offer great expertise that club the sensing, execution, communication, and network technology along with microelectronics and micro-mechanical devices together to study the environment. It is a new concept and a consequence of few steps in the communication field. If the original prospect of this new network works according to the planned concept, it will recover the examining and control systems used these days in the environment for consumer, medical, industries, and military sectors. The wireless technology gives the advantage of decrease in cost that cabling operation has in recent systems and also makes it possible to perform measurements in unreachable places. Many applications can work on the concept of this technology.

A Process Framework to Migrate Legacy Application to Cloud

An enterprise has a challenge in keeping pace with the quickly evolving technology. The biggest challenge comes in terms of legacy application migration to technologies like cloud. Legacy application migration should be well thought out at the very start (i.e., pre-migration and supported by migration framework). In this chapter, the author proposes a legacy application migration framework with a focus on pre-migration area. A robust technical and business analysis of existing/legacy applications, based on the enterprise's focus parameters, during pre-migration sets the migration path for subsequent area of framework. The proposed pre-migration mathematical assessment helps an enterprise to understand a legacy application's current state and also helps in unearthing the information with respect to candidate application and helps in taking well-informed decisions like GO or NO-GO w.r.t legacy application migration. Considering application migration a journey, it is important that it reaches its destination, so pre-migration is an important area of the migration journey.

Comprehensive Survey of Routing Protocols for Wireless Body Area Networks (WBANs)

Wireless body area networks (WBANs) are one of the applications of IoT that deal with the remote transmission of patient data. The health-related data is of highly sensitive nature. The loss of critical data packets might lead a patient to an embarrassing position. Therefore, WBANs require a secure and efficient data transmission mechanism. However, wireless transmission traditionally remains vulnerable to many security attacks such as node misbehavior attack. Routing protocols play a key role in the extended network lifetime. However, efficient data routing in WBAN is a challenging task. In addition, sensor nodes due to wireless communication produce electromagnetic radiation that is absorbed by the human body and results in temperature rise. Therefore, routing protocols along with security issues must consider temperature rise to ensure safe wireless transmission. In this chapter, the authors present a comprehensive review of most relevant security and privacy concerns and relevant routing protocols addressing the aforementioned routing issues.

Cloud-Based IoT Architecture for Green Buildings

Green building (GB) is a game changer as the world is moving towards conserving its resources. Green building management systems available nowadays are too expensive and cannot cater to small or medium-sized buildings. Internet of things-based systems use simple, low-cost sensors, signal processing, and high-level learning methods. Studies on building occupancy and human activities help improve design and push the energy conservation levels. With huge amounts of data and improved learning systems, the impetus is to capture the information and use it well to improve design and justify the green building concept. Cloud-based architecture helps to monitor, capture, and process the data, which acts as input to intelligent learning systems, which in turn help to improve the design and performance of current green building management systems. This chapter discusses role of cloud-based internet of things architecture in improving design and performance of current building management systems.

Internet of Things (IoT) and PKI-Based Security Architecture

The internet of things (IoT) is described as the arrangement of physical articles—contraptions, automobiles, structures, and various things—fixed with equipment, programming, devices, and framework accessibility that engages these things to accumulate and exchange data. Practically paying little mind to industry, IoT is anticipated to be the absolute most significant factor affecting basic business rationale in the coming decades. PKI is the best alternative for arrangement suppliers to secure information and associated gadgets. When effectively executed, PKI can fabricate and bolster security and trust in IoT biological systems. PKI's job in IoT gives solid personality validation and makes the establishment of trust that frameworks, gadgets, applications, and clients need to securely connect and trade delicate information. PKI and the brought forth trust networks spread the basic security necessities IoT tasks need, giving the encryption, confirmation, and information respectability that make the establishment of trust. This chapter explores PKI-based security architecture.