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Inclusion of mobile nodes (MNs) in Internet of Things (IoT) further increases the challenges such as frequent network disconnection and intermittent connectivity because of high mobility rate of nodes. This paper aims to propose a proactive mobility and congestion aware route prediction mechanism (PMCAR) to find the congestion free route from leaf to destination oriented directed acyclic graph root (DODAG-ROOT) which considers number of MNs connected to a static node. This paper compares the proposed technique (PMCAR) with RPL (OF0) which considers the HOP-COUNT to determine the path from leaf to DODAG-ROOT. The authors performed a simulation with the proposed technique in MATLAB to present the benefits in terms of packet loss and energy consumption.

In this pandemic situation, mobile and IoT play major role in predicting and preventing the CoronaVirus Disease of 2019 (COVID-19). Huge amount of computations is happening with the data generated in this pandemic with the help of mobile devices. To route the data to remote locations through the network, it is necessary to have proper routing mechanism without congestion. In this paper, PMCAR mechanism is introduced to achieve the same. Internet of mobile Things (IoMT) is an extension of IoT that consists of static embedded devices and sensors. IoMT includes MNs which sense data and transfer it to the DODAG-ROOT. The nodes in the IoMT are characterised by low power, low memory, low computing power and low bandwidth support. Several challenges are encountered by routing protocols defined for IPV6 over low power wireless personal area networks to ensure reduced packet loss, less delay, less energy consumption and guaranteed quality of service.

The results obtained shows a significant improvement compared to the existing approach such as RPL (OF0). The proposed route prediction mechanism can be applied largely to medical applications which are delay sensitive, particularly in pandemic situations where the number of patients involved and the data gathered from them flows towards a central root for analysis. Support of data transmission from the patients to the doctors without much delay and packet loss will make the response or decisions available more quickly which is a vital part of medical applications.

The computational technologies in this COVID-19 pandemic situation needs timely data for computation without delay. IoMT is enabled with various devices such as mobile, sensors and wearable devices. These devices are dedicated for collecting the data from the patients or any objects from different geographical location based on the predetermined time intervals. Timely delivery of data is essential for accurate computation. So, it is necessary to have a routing mechanism without delay and congestion to handle this pandemic situation. The proposed PMCAR mechanism ensures the reliable delivery of data for immediate computation which can be used to make decisions in preventing and prediction.

An issue that tends to be ignored in information retrieval is the issue of updating inverted files. This is largely because inverted files were devised to provide fast query service, and much work has been done with the emphasis strongly on queries. This paper aims to study the effect of using parallel methods for the update of inverted files in order to reduce costs, by looking at two types of partitioning for inverted files: document identifier and term identifier.

Raw update service and update with query service are studied with these partitioning schemes using an incremental update strategy. The paper uses standard measures used in parallel computing such as speedup to examine the computing results and also the costs of reorganising indexes while servicing transactions.

Empirical results show that for both transaction processing and index reorganisation the document identifier method is superior. However, there is evidence that the term identifier partitioning method could be useful in a concurrent transaction processing context.

There is an increasing need to service updates, which is now becoming a requirement of inverted files (for dynamic collections such as the web), demonstrating that a shift in requirements of inverted file maintenance is needed from the past.

The paper is of value to database administrators who manage large‐scale and dynamic text collections, and who need to use parallel computing to implement their text retrieval services.

The purpose of this paper is to introduce a new similarity method to gauge the differences between two subject hierarchical structures.

In the proposed similarity measure, nodes on two hierarchical structures are projected onto a two-dimensional space, respectively, and both structural similarity and subject similarity of nodes are considered in the similarity between the two hierarchical structures. The extent to which the structural similarity impacts on the similarity can be controlled by adjusting a parameter. An experiment was conducted to evaluate soundness of the measure. Eight experts whose research interests were information retrieval and information organization participated in the study. Results from the new measure were compared with results from the experts.

The evaluation shows strong correlations between the results from the new method and the results from the experts. It suggests that the similarity method achieved satisfactory results.

Hierarchical structures that are found in subject directories, taxonomies, classification systems, and other classificatory structures play an extremely important role in information organization and information representation. Measuring the similarity between two subject hierarchical structures allows an accurate overarching understanding of the degree to which the two hierarchical structures are similar.

Both structural similarity and subject similarity of nodes were considered in the proposed similarity method, and the extent to which the structural similarity impacts on the similarity can be adjusted. In addition, a new evaluation method for a hierarchical structure similarity was presented.

In this paper methods for both speeding up passage processing and examining more passages using parallel computers are explored. The number of passages processed are varied in order to examine the effect on retrieval effectiveness and efficiency. The particular algorithm applied has previously been used to good effect in Okapi experiments at TREC. This algorithm and the mechanism for applying parallel computing to speed up processing are described.

Routing protocols in wireless sensor networks (WSN) are a crucial challenge for which the goal is maximizing the system lifetime. Since the sensor nodes are with limited capabilities, these routing protocols should be simple, scalable, energy‐efficient, and robust to deal with a very large number of nodes, and also self‐configurable to node failures and changes of the network topology dynamically. The purpose of this paper is to present a new algorithm for cluster forming in WSN based on the node energy required to transmit to the base station.

Rotation selection of cluster‐head considering the remoteness of the nodes to the sink, and the network node residual energy.

The simulation results show that this algorithm allows network stability extension compared to the most known clustering algorithm.

Giving a probability to become cluster‐head based on the remoteness of the node to the sink.

To remanufacture a disused part, a hybrid process needs to be taken in part production. Therefore, a reasonable machining route is necessary to be developed for the hybrid process. This paper aims to develop a novel process planning algorithm for additive and subtractive manufacturing (ASM) system to achieve this purpose.

First, a skeleton of the model is generated by using thinning algorithm. Then, the skeleton tree is constructed based on topological structure and shape feature. Further, a feature matching algorithm is developed for recognizing the different features between the initial model and the final model based on the skeleton tree. Finally, a reasonable hybrid machining route of the ASM system is generated in consideration of the machining method of each different sub-feature.

This paper proposes a hybrid process planning algorithm for the ASM system. Further, it generates new process planning insights on the hybrid process service provider market.

The proposed process planning algorithm enables engineers to obtain a proper hybrid machining route before product fabrication. And thereby, it extends the machining capability of the hybrid process to manufacture some parts accurately and efficiently.

This study addresses one gap in the hybrid process literature. It develops the first hybrid process planning strategy for remanufacturing of disused parts based on skeleton tree matching, which generates a more proper hybrid machining route than the currently available hybrid strategy studies. Also, this study provides technical support for the ASM system to repair damaged parts.

This paper describes voltage collapse in power system networks and how it could lead to a collapse of the whole system. Discusses the effect of machine learning and artificial intelligence, leading to new methods. Spotlight, the fuzzy decision tree (FDT) method and its application to voltage collapse assessments. Concludes that FDT can identify and group data sets, giving a new understanding of its application in voltage collapse analysis.

Organizations involved in facility management (FM) can use building information modeling (BIM) as a knowledge repository to document evolving facility information and to support decisions made by the facility managers during the operational life of a facility. Despite ongoing advances in FM technologies, FM practices in most facilities are still labor intensive, time consuming and often rely on unreliable and outdated information. To address these shortcomings, the purpose of this study is to propose an automated approach that demonstrates the potential of using BIM to develop algorithms that automate decision-making for FM applications.

A BIM plug-in tool is developed that uses a fault detection and diagnostics (FDD) algorithm to automate the process of detecting malfunctioning heating, ventilation, and air conditioning (HVAC) equipment. The algorithm connects to a complaint ticket database and automates BIM to determine potentially damaged HVAC system components and develops a plan of action for the facility inspectors accordingly. The approach has been implemented as a case study in an operating facility to improve the process of HVAC system diagnosis and repair.

By implementing the proposed application in a case study, the authors found that automated BIM approaches such as the one developed in this study, can be highly beneficial in FM practices by increasing productivity and lowering costs associated with decision-making.

This study introduces an innovative approach that leverages BIM for automated fault detection in operational buildings. FM personnel in charge of HVAC inspection and repair can highly benefit from the proposed approach, as it eliminates the time required to locate HVAC equipment at fault manually.

This paper discusses the issues involved in the development of combined finite/discrete element methods; both from a fundamental theoretical viewpoint and some related algorithmic considerations essential for the efficient numerical solution of large scale industrial problems. The finite element representation of the solid region is combined with progressive fracturing, which leads to the formation of discrete elements, which may be composed of one or more deformable finite elements. The applicability of the approach is demonstrated by the solution of a range of examples relevant to various industrial sections.

Office documents are widely used in our daily activities, so the number of them has been increasing. A demand for sophisticated search for office documents becomes more important. The recent file format of office documents is based on a package of multiple XML files. These XML files include not only body text but also page structure data and style data. The purpose of this paper is to utilize them to find similar office documents.

The authors propose SOS, a similarity search method based on structures and styles of office documents. SOS needs to compute similarity values between multiple pairs of XML files included in the office documents. We also propose LAX+, which is an algorithm to calculate a similarity value for a pair of XML files, by extending existing XML leaf node clustering algorithm.

SOS and LAX+ are evaluated by using three types of office documents (docx, xlsx and pptx) in our experiments. The results of LAX+ and SOS are better than ones of the existing algorithms.

Existing text‐based search engines do not take structure and style of documents into account. SOS can find similar documents by calculating similarities between multiple XML files corresponding to body texts, structures and styles.