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The Neighbor Discovery Protocol (NDP) enables nodes on the same IPv6 link to advertise their existence to their neighbors and learn about their neighbors’ existences in an IPv6 link-local network. Duplicate Address Detection (DAD) on NDP is used to determine whether or not an address requested by a node is already in use by another node. The Neighbor Solicitation (NS) and Neighbor Advertisement (NA) operations are associated to DAD checks in order to ensure that each interface within the transmission session is unique. Unfortunately, NS and NA operations have a significant disadvantage in that they are based on insecure architectures and lack verification procedures for determining whether incoming messages originate from a valid or illegitimate node. This will eventually allow any node in the same link to be manipulated during NS and NA message transmission sessions. Despite some attempts to secure the entire NDP operations, they still suffer from computing resources requirement for their operations. As a result, this study proposes an Initial Neighbor Inspection (INI) on DAD operation. The proposed techniques allow for an initial round of verification of the nodes on the same link before a broadcast request on the existence of neighbors, which is followed by another round of learning about neighbors’ existences. Conclusively, using this idea, as a simple verification will indicate the presence of neighbors, we may restrict solicitation and advertising to only those who are eligible. This means that the computational processing time for NS and NA on DAD operations would not rise.

The adoption of recycling and proper disposal techniques for electronic waste is crucial in advancing sustainable development. The traditional approaches of motivating people for collection of electronic waste are often insufficient due to inadequate methods reaching out, given incentives, calculating appropriate incentives associate to the task of gathering the electronic waste and a lack of transparency in the entire process. Insufficient collection of electronic waste could result in the release of numerous harmful substances into the environment. Prior research studies have been carried out to tackle the issue of electronic waste management in a broad sense. The findings of those studies indicated diverse strategies, each of which is relevant solely to a restricted range of electronic waste reprocessing circumstances. The current study has presented a proposed technique for incentivizing tasks and activities associated to collection of electronic waste through the adoption of vector space technique. Blockchain smart contact technology, has been used to implemented the strategy. The method used involves various well defined mapping of tasks, nature of activities, and their magnitude in order to derived an incentive. Some scenarios for the calculations of incentives are presented, and the findings reveals the based case is by utilizing weighting scale scheme where each tasks and activities are mapped to its associated inventive rather than providing fixed incentive values. Ethereum was used as digital token for each unit of incentive. This concept has contributed in encouraging personal accountability in the management of e-waste collection in order to cultivate sustainable behaviors for a long term solution.

Bitcoin was the first virtual currency to be created in 2009 as a decentralized digital currency that could be transferred from one user to another over the peer-to-peer bitcoin network without the use of intermediaries such as banks and other financial institutions. In terms of finance, governments and other experts are concerned that Bitcoin can be used to avoid currency restrictions, for money manipulation, or criminal activities, and that it may be risky for investors due to the absence of regulations. The purpose of this study is to investigate the factors influencing Bitcoin investment adoption in Covid-19, examine the mediating factors influencing Bitcoin investment adoption in Covid-19, and propose a model of influencing Bitcoin investment adoption in Covid-19. Therefore, a methodological method was employed to accomplish these aims. The theory adopted is the theory of planned behaviour. Purposive sampling was used as the sampling method for the study. A total of 101 full responses were obtained to the web-based questionnaire. Partial Least Squares Structural Equation Modeling (PLS-SEM 3) is utilized to analyze the study's findings. Perceived Behavior Control and Perceived Lack of Alternatives were found to have a favourable association with Intention to Invest in Bitcoin. Meanwhile, Perceived External Pressure has the reverse result, having a marginal influence on the Decision to Invest in Bitcoin. Surprisingly, Perceived Lack of Alternative completely mediates the interaction between Perceived External Pressure and Desire to Invest in Bitcoin. It is anticipated that this analysis would have a clearer picture of Investors' and Consumers' Action on Investing in Bitcoin During Covid-19.

Wireless Sensor Networks (WSNs) are currently being used in various industries such as healthcare, engineering, the environment and so on. Security is a significant issue for WSN due to its infrastructure and limited physical security. Distributed Denial of Service (DDoS) is one of the most vulnerable attacks that can be defined as attacks launched from multiple ends into a set of legitimate sensor nodes in the WSN to drain their inadequate energy resources. Nowadays, Artificial intelligence techniques are performing better accuracy than the traditional methods to detect intrusion for the various attack. This Systematic Literature Review (SLR) attempts to investigate the current status of DDoS detection techniques and to identify the most capable and effective detection system using artificial intelligence to detect distributed DoS attack. Preferred Reporting Item for Systematic Review and Meta-Analysis (PRISMA) statement is used to conduct this review. Based on 15 out of 983 that met inclusion criteria, Support Vector Machine (SVM) and Artificial Neural Network (ANN) is the most used AI-based techniques to detect distributed denial of service attack in the wireless sensor network. The performance of AI techniques-based detection system for DDoS attack in WSN is remarkable.

Machine learning algorithm integrates with various features and methods for learning. The performance metric has a major role in determining the capacity and ability of any machine learning algorithm. The supervised approach supports learning based on predefined parameters. The classification approach classifies the set of data with labels for training and evaluation purposes. This paper applies method of supervised learning algorithm based on classification approach to analyzed in terms of performance metrics. Some algorithms were applied in the experiment process to determine the clear outcome from them. The analysis gives an outcome based on certain parameters to obtain the results to understand the ability of these algorithm and their implementation in any potential use-cases.

3D maps have become an essential tool for navigation aid. The aim of a navigation aid is to provide an optimal route from the current position to the destination. Unfortunately, most mobile devices' GPS signal accuracy and the display of pathways on 3D maps in the small screen of mobile devices affects the pathway architectural from generating accurate initial positions to destinations. This chapter proposed a technique for visualizing pathway on 3D maps for an interactive user navigation aid in mobile devices. This technique provides visualization of 3D maps in virtual 3D workspace environments which assists a user to navigate to a target location. The Bi-A* path-finding algorithm was used for establishing dynamic target location in Voronoi diagram/Delaunay triangulation. This approach could navigate more than two users in a 3D walk-space and at the same time showing their whereabouts on 3D projections mapped. The map shows the users' location in the scene to navigate from source to the target and the target also moves to the source to meet on the same physical location and image plane.

This research implements the idea of automation using Internet of Things (IoT) in a greenhouse environment. The development is focuses on deployment of agicultural greenhouses into small-scale level transforming it into a smart greenhouse. They are to help in monitoring the greenhouse environment conditions, water irrigation management, image collection using installed cameras as well as predicting diseases in the plants on collected leaf datasets. This research focus on development for the purpose of validating a proposed system design and architecture for a suitable IoT based monitoring for environment conditions, managing water irrigation system and a effective method for detecting leaf diseases on the plants inside a greenhouse environment.

The increasing of the signaling technology motivated the research community to find alternative solutions to replace the sequential computing systems. These systems reached their limits, and it became an infeasible choice to manage the computational grand challenges. Thereby, many types of research have been conducted to improve a system with special characteristics able to cope with the new technology. Massively parallel computer (MPC) systems have been emerged to solve the complex computing challenges in parallel and concurrently. The performance of these systems is affected by the structure of the underlying interconnection network. Therefore, many designs of interconnection networks topologies have been presented looking for an optimal one. In this paper, we present the architecture of MMN which is a hierarchical interconnection network. The static and dynamic performance parameters of MMN have been evaluated in previous studies, and it provided good results compared to the conventional interconnection network topologies. This paper will focus on evaluating and determining the static cost-effective parameter of MMN which is the product of the relation between the node degree, network diameter, wiring complexity, and the total number of nodes in each network.

At the current time, finding an alternative computing device with extreme computation power is the main concern of the research community. Therefore, building a computer device able to execute extremely difficult calculations in a short period of time is required. Presently, the massively parallel computer (MPC) systems are considered the highest computing devices, and the existence of these systems is important to execute many operations in many sectors such as engineering and science. These devices are built based on an internal network called interconnection network has a particular design represented by the network topology. The cost of these networks is influenced highly by the price of the processing elements (PEs) and the communication links. Thus, the design of these topologies has a crucial impact on the network cost and performance. In this paper, we have proposed a new design of topology for the MPC systems; this topology has been evaluated statically in previous work, and it showed good results. Therefore, in this paper, we will focus on analysing the cost effectivity of this network to examine if it is a cost-beneficial network before going to the implementation step to assure that the profit of this network deserves the cost.

This paper presents a Multilayer Perception Neural Network developed to identify human subjects using electrocardiogram (ECG) signals. We use the amplitude values of Q, R and S as a features for our experiments. In this study, a total of 87 dataset were collected among 14 subjects from the Physikalisch-Technische Bundesanstalt (PTB) database. Out of the 14 subjects, Q-R-S feature points were taken from different day and time sessions to perform classification with MLP. Out of this data, 66 % is used as training dataset while the remaining 34 % is used for testing. Our method yields 96 % accuracy and demonstrates that the use of three fiducial points is sufficient to identify a subject despite the common practice of taking more feature points.

Robustness is one of the most important properties of watermarking, the watermark should be readable from images that underwent common attacks such as lossy compression or Joint Photographic Experts Group (JPEG). While many publications consider the relation between smoothness and quality of the images, few studies only concentrate on the relation between smoothness and watermarking robustness. This study focuses on watermark robustness on different smooth areas. The effectiveness of lossy compression on different smooth intensity areas was tested, and the average of pixel value change before and after compression for each field of smoothness intensity was found to embed the watermark objects within less effective areas.

Over the years an increasing demand for an automated security system begins to emerge. Many applications that help in protecting life and properties are being developed. Most of them are aimed at improving the work of security personnel and security agencies. However, security is a responsibility of everyone not only the security agencies or security personnel alone. This paper present an interactive security monitoring system based on passive infrared motion detection sensor, which will capture the image of any intruding persons and share it to the entire people that are using the system on both Android platform and in an online portal display. The people on the system can communicate with each other and post information to a commonly accessible board in the online system to discuss any issues or to see if anyone recognizes the felons/intruder on the images. Images of interest can then be transmitted to law enforcement authorities. This could be use in anywhere that needs to be protected against intruder. It will be best use in kindergarten, primary school and or in a neighborhood. That is why we call it neighborhood watch security system (NWSS). Preliminaries evaluation indicated an accurate image captured in a real time with an avoidance of false alarm.

The dynamics of watermark features after embedded into audio streams through digital watermarking techniques are unstable. The audio streams exits as a series of waveform amplitude of sound over the range of information it contains. Within this range, there are variations of the presentation of the stream taken per second and given in hertz. The precision of the stream representations is measured by the number of bits per stream. The fact that the streams bits are high is a sign for data already existing which means that within empty streams additional information can be embedded. In general, added information is described as noise and these audio streams are considered as noise tolerant. Watermarks are embedded into a spatial or transformed domain with the effect that the presentation of some bit streams will be affected. This paper investigates the dynamics of watermarks embedded in an audio stream, the contained file being noise intolerant. The watermark file is embedded in several positions within the audio signal stream by spread spectrum techniques. The most suitable positions for embedding the watermark is identified which ensures a strong and robust watermark as a result.

Mobile user navigation system explore and apply the emerging of 3D visualization system for visualizing and navigating conveniently in an environment. The important consideration in visualization navigation is the real time operation and the application device's computational complexity capabilities. Currently more and new research are encourage on 3D application for mobile device that will give user truly and accurately virtual reality 3D environment in real time for user to find its path to navigate from one location to other location in an environment. Unfortunately, there is no commonly agreed way to determine the accurate 3D visualization and navigation system accompanying with the increasing activity of people among cities and countries around the world, the requirement for navigating people's movement grows with unexpected speed. This paper provides a framework for the improved 3D visualization and navigation system. The framework will provide some contributions for consolidation of visualization navigation applications and techniques on mobile devices for user within an environment.