Smart homes and cities is one of the crucial topics for an individual of any age that requires almost zero computer literacy in order to benefit the leisure and luxury offered by smart homes and cities. Benefits offered by smart homes and cities are not only limited to leisure and luxury but other various areas of an individual's life and to aid them with information and communication, intelligent responses with the information collected and analyzed, environmental protection and public safety with surveillance. Internet of things was invented in 1999. Since then, there has been a huge bloom in technologies, keeping in mind the present systematic development in sensors, wireless technology, artificial intelligence, and machines and devices. This paper outlines the working prototypes that have been developed and deployed in developed countries and recommends to the Pacific Island nations to accept these technologies for the betterment of their countries. It will also compare the usage of energy and cost saving in smart cities and how this can be beneficial to the nations in the Pacific.

Cardiac magnetic resonance imaging is a popular non-invasive technique used for assessing the cardiac performance. Automating the segmentation helps in increased diagnosis accuracy in considerably less time and effort. In this paper, a novel approach has been proposed to improve the automated segmentation process by increasing the accuracy of segmentation and laying focus on efficient pre-processing of the cardiac magnetic resonance (MR) image. The pre-processing module in the proposed method includes noise estimation and efficient denoising of images using discrete total variation-based non-local means method. Segmentation accuracy is evaluated using measures such as average perpendicular distance and dice similarity coefficient. The performance of all the segmentation techniques is improved. Further segmentation comparison has also been performed using other state-of-the art noise removal techniques for pre-processing, and it was observed that the proposed pre-processing technique outperformed other noise removal techniques in improving the segmentation accuracy.

Cloud computing has risen as a new computing paradigm providing computing, resources for networking, and storage as a service across the network. Data replication is a phenomenon which brings the available and reliable data (e.g., maybe the databases) nearer to the consumers (e.g., cloud applications) to overcome the bottleneck and is becoming a suitable solution. In this paper, the authors study the performance characteristics of a replicated database in cloud computing data centres which improves QoS by reducing communication delays. They formulate a theoretical queueing model of the replicated system by considering the arrival process as Poisson distribution for both types of client request, such as read and write applications. They solve the proposed model with the help of the recursive method, and the relevant performance matrices are derived. The evaluated results from both the mathematical model and extensive simulations help to study the unveil performance and guide the cloud providers for modelling future data replication solutions.

Vehicular ad hoc networks (VANETs) are part of intelligent transportation systems (ITS) and their main objective is to provide communication between vehicles. As self-organizing and configuring networks, with decentralized control, their performance is totally dependent on the route duration times. This study proposes an analysis of the route duration times in vehicular networks, considering three influential factors: speed, density, and travel orientation. Simulation experiments corroborate that the route duration times increases in denser networks and when vehicles travel in the same direction. However, contrary to common sense, unexpectedly, it is demonstrated that the route duration times in realistic vehicle environments do not decrease as the vehicle speed increases due to the mobility restrictions in this environments (stops at traffic lights and road crossings, braking to avoid collisions, acceleration and deceleration).

The paper presents an approach to generate and optimize test sequences from the input UML activity diagram. For this, an algorithm is proposed called Unified Modelling Language for Test Sequence Generation (UMLTSG) that uses a search-based algorithm, named Test Sequence Prioritization using Ant Colony Optimization (TSP ACO) to generate and optimize test sequences. The algorithms overcome the existing limitations of handling complex decision-making activity such as conditional activity, fork activity, and join the activity. The optimization process helps to reduce the number of processing nodes that leads to minimizing the time and cost. The proposed approach experiments on a well-known application Railway Ticket Reservation System (RTRS). APFD metric measures the effectiveness of our approach and found that the prioritized order of test sequences achieved 20% higher APFD score. Apart from this, the authors have also experimented on six real life case studies and obtained an average of 52.16% reduction in redundant test paths.

Intelligent manufacturing is an important method for transforming and upgrading enterprise intelligence. Studying the influencing factors of enterprises, intelligent manufacturing can help enterprises formulate more targeted intelligent manufacturing development strategies according to their own stage characteristics to accelerate the intelligent development. The concept of intelligent manufacturing ecosystem is proposed. By exploring the evolution process of intelligent manufacturing ecosystems, a three-stage theoretical model of influencing factors of intelligent manufacturing of enterprises is constructed. The theoretical model and related assumptions are verified using the empirical data of manufacturing enterprises of many provinces and cities in China. The results show that most factors in the digital stage, network stage, and intelligent stage significantly affect the development of enterprise intelligent manufacturing systems. This study provides theoretical reference and suggestions for manufacturing enterprises to develop intelligent manufacturing.

Allotment of nurses to patients is a critical task in terms of better treatment. Nurses should be appointed according to a patient's health condition, type of disease, and financial condition. Again, understaffing of nurses may hamper patient health and condition. Similarly, overstaffing of nurses is a waste of manpower. Adequate staffing of nurses is crucial. The authors propose a technique using game theory to meet overstaffing and understaffing of nurses. Game theory plays a vital role to meet the exact requirement. Nash equilibrium can be used for taking all possible decisions, like appointment of nurses in different categories for smooth treatment of patients. However, the final and most suitable decision can be taken using perfect Nash equilibrium. This technique is a perfect technique to implement in case of vital and critical decision points.

Most of the traditional face modeling methods adopt the parameter-based method to construct, but the face model constructed by this method is too smooth and ignores the detailed features of the face. To solve this problem, a virtual face modeling method based on 3D motion capture data is proposed in this paper. In order to improve the deformation method for the realistic modeling purpose, this paper divides the modeling process of personalized face into two parts: overall modification and local deformation. The overall deformation modifies the facial shape and the position of the facial features of Maya universal model. Based on the principle of radial basis function interpolation algorithm, a smooth interpolation function is constructed, and the new position coordinates of non-characteristic points are obtained by solving the linear equations, so that they are more in line with the physiological characteristics of human faces. The end result is a more realistic virtual face that you model.

Economic losses from earthquakes raised many questions regarding the adequacy of the current seismic design and seismic isolation in data centers. Organizations accommodated new explicit seismic isolation applications in their business continuity and disaster recovery plans. These applications aim acceptable damage levels that correspond to acceptable business interruption for data centers in case of an earthquake. In this study, the authors aim to discuss the importance of seismic isolation applications that can be implemented for data centers within business continuity and disaster recovery planning contexts. To provide a clearer aspect on seismic isolation applications, the topic has been discussed within the framework of international standards. They conclude that GSA, ASCE, and Uptime Institute provide internationally recognized standards which make raised floors a good option for data centers. These standards provide technical documentation for service functioning with high levels of availability during an outage.

Recently, many methods have appeared to solve the problem of the evolution of alignment under the change of ontologies. The main challenge for them is to maintain consistency of alignment after applying the change. An alignment is consistent if and only if the ontologies remain consistent even when used in conjunction with the alignment. The objective of this work is to take a step forward by considering the alignment evolution according to the conservativity principle under the change of ontologies. In this context, an alignment is conservative if the ontological change should not introduce new semantic relationships between concepts from one of the input ontologies. The authors give methods for the conservativity violation detection and repair under the change of ontologies and they carry out an experiment on a dataset adapted from the Ontology Alignment Evaluation Initiative. The experiment demonstrates both the practical applicability of the proposed approach and shows the limits of the alignment evolution methods compared to the alignment conservativity under the change of ontologies.