Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessing Risk in Healthcare Collaborative Settings

This chapter describes a case study addressing risk assessment in a hospital unit. The objective of the case study was to analyse the impact on collaborative work and work flow after the unit changed its design and installations, and the consequences for risk management. The Software-Hardware-EnvironmentLiveware-Liveware (SHELL) model, a conceptual framework for understanding the interaction between human factors (liveware), computers (software and hardware) and the environment, was used in this study. The outcomes show that the SHELL model is adequate for analyzing the complex issues raised in healthcare collaborative settings. The SHELL analysis highlighted how the relationships among doctors, nurses and assistants – expressed according to the software, hardware, environment and liveware elements – evolved in the new work setting, characterized by new working rooms, glass walls and automatic doors. This analysis shows that even small changes, such as changing the way that computers are used in the work environment, may have a significant impact in a collaborative work setting.
Marine Gelatine from Rest Raw Materials

In recent years, demand for consumption of marine foods, and especially fish, has substantially increased worldwide. The majority of collagen available is sourced from mammalian-derived products. Although fish derived gelatine is a viable alternative to mammalian sourced gelatine, there are certain limitations related to the use of fish gelatine that include odour, colour, functional properties, and consistency in its amino acid composition. Chemicals used for pre-treatment, as well as extraction conditions such as temperature and time, can influence the length of polypeptide chains that result and the functional properties of the gelatine. Compared to traditional sources, gelatines derived from fish show significant differences in chemical and physical properties, and great care should be paid to optimization of the production process in order to obtain a product with the best properties for intended applications. The focus of this review is to explore the feasibility of producing gelatine sourced from marine processing by-products using different pre-treatment and extraction strategies with the aim of improving the techno-functional properties of the final product and improving the clean-label status of gelatines. The bioactivities of gelatine hydrolysates are also discussed.
Enhancing security and privacy protection for MapReduce processing: the initial simulation work flow

MapReduce programming model allows the processing of massive amount of data in parallel through clustering across a distributed system. The tasks for MapReduce have been categorized into areas which are data management and storage, data analytics, on line processing and security and privacy protection. For sensitive data uploaded by users, it must be protected from any unauthorized access to ensure the integrity, authenticity and privacy of the data. It is important that, data at rest, data in transit and nodes is managed securely by ad-dressing the elements of data security and privacy protection which are auditing, access control and privacy. The purpose of this study is to enhance the prominence of security and privacy protection for MapReduce model. An existing study is more specifically tailored to structure based requirements. Whilst, there is a need to continue finding solutions for MapReduce in better handling big data security and privacy protection concerning the unstructured data. This paper presents the initial workflow of the simulation set up of MapReduce processing using the Hadoop platform to demonstrate an enhancement for security and privacy protection access control by implementing Whitelist to control access in MapReduce processing.
Clean-Slate Information-Centric Publish Subscribe Networks

The Internet architecture of today does not seem suited to the current Internet usage, as the application layer is more and more content-centric, while the network layer is ossified around the IP concept. In this chapter, the authors explore a redefinition of the whole Internet architecture where nothing is taken for granted, especially IP addresses. The review focuses on the forwarding and topology components of the EU FP7 PSIRP architecture and on a few of the problematic issues and the ongoing discussions around a pioneering clean-slate design of the way to organize networks. DOI: 10.4018/978-1-4666-1613-4.ch013
Differing signal-meaning dimensionalities facilitates the emergence of structure

Structure of language is not only constrained by cognitive processes, but also by physical aspects of the signalling modality. We test the assumptions surrounding the role which the physical aspects of the signal space will have on the emergence of structure in speech. Here, we use a signal creation task to test whether a signal space and a meaning space having similar dimensionalities will generate an iconic system with signal-meaning mapping and whether, when the topologies differ, the emergence of non-iconic structure is facilitated. In our experiments, signals are created using infrared sensors which use hand position to create audio signals. We find that people take advantage of iconic signal-meaning mappings where possible. Further, we use trajectory probabilities and measures of variance to show that when there is a dimensionality mismatch, more structural strategies are used.
Utilizing LDA Clustering for Technical Term Extraction

Similar to named entities in general texts, technical terms are critical in scientific writings. They appear in nearly all parts of the document structure, and as such, identifying technical terms in a scientific writing is arguably the first step to analyze the semantic content. We thus focus on technical term extraction in this paper, a task of recognizing technical terms from scientific writings. The motivations behind includes a possibility of assisting researchers in exploring vast amount of scientific publications in their research activities. Technical term extraction would benefit advanced information extraction (IE) systems and eventually lead to computer-aided inference of knowledge contained in these publications. In this paper, we propose a simple unsupervised method for technical term extraction by combining Conditional Random Field (CRF) with extra features obtained from a Latent Dirichlet Allocation (LDA) clustering model. We found that such a combination is promising to improve the performance of technical term extraction. In section 3, the details of our proposed method are described, including the problem formulation and how we incorporate LDA clustering information in the feature set. Section 4 describes the experimental design and settings to investigate the performance of our method. Results of the experiments are provided in section 5, followed by conclusions and discussions for further improvement in section 6.
Texture Retrieval for Multi-source Remote Sensing Image Based on Contourlet Transform and Spectral Histogram

A two-step progressive texture retrieval algorithm for multi-source remotely sensed imagery based on Contourlet transform and spectral histogram is proposed.Firstly,the Contourlet transform is applied to decompose texture features of remotely sensed imagery at different scales and different directions.Then,low-pass signal and high-pass signals are adopted to realize elementary retrieval and exact retrieval relatively.The experiments on texture database obtained from USC and QucikBird images show that the proposed algorithm not only utilizes the advantages of Contourlet on multi-scale and multi-direction texture feature extraction,but also makes full use of the efficiency of spectral histogram on distributed statistical feature representation.On the aspect of precision and efficiency,Contourlet transform outperforms wavelet transform.The proposed method provides a powerful tool for texture retrieval of remote sensing image.
Exponential Reaching Law and Sensorless DTC IM Control with Neural Network Online Parameters Estimation based on MRAS

The most important problem in the control of induction machine (IM) is the change of its parameters, especially the stator resistance and rotor-time constant. The objective of this paper is to implement a new strategy in sensorless direct torque control (DTC) of an IM drive. The rotor flux based model reference adaptive system (MRAS) is used to estimate conjointly the rotor speed, the stator resistance and the inverse rotor time constant, the process of the estimation is performed on-line by a new MRAS-based artificial neural network (ANN) technique. Furthermore, the drive is complemented with a new exponential reaching law (ERL), based on the sliding mode control (SMC) to significantly improve the performances of the system control compared to the conventional SMC which is known to be susceptible to the annoying chattering phenomenon. An experimental investigation was carried out via the Matlab/Simulink with real time interface (RTI) and dSPACE (DS1104) board where the behavior of the proposed method was tested at different points of IM operation.
Modelling and Implementation of Network Coding for Video

In this paper, we investigate Network Coding for Video (NCV) which we apply for video streaming over wireless networks. NCV provides a basis for network coding. We use NCV algorithm to increase throughput and video quality. When designing NCV algorithm, we take the deadline as well as the decodability of the video packet at the receiver. In network coding, different flows of video packets are packed into a single packet at intermediate nodes and forwarded to other nodes over wireless networks. There are many problems that occur during transmission on the wireless channel. Network coding plays an important role in dealing with these problems. We observe the benefits of network coding for throughput increase thanks to applying broadcast operations on wireless networks. The aim of this study is to implement NCV algorithm using C programming language which takes the output of the H.264 video codec generating the video packets. In our experiments, we investigated improvements in terms of video quality and throughput at different scenarios.
Novel Criterion for Reluctance Torque Utility of Permanent Magnet Motors

A novel criterion for the utility of reluctance torque in permanent magnet (PM) motors is developed. The criterion, reluctance torque ratio <italic>α</italic>, can be quantified by using the PM flux linkage Ψ<italic><sub>p</sub></italic> of the stator phase windings, the current <italic>I</italic>, and the direct- and quadrature-axis inductances <italic>L<sub>d</sub></italic> and <italic>L<sub>q</sub></italic>, respectively. It has been shown that the conventional salient-pole ratio is not helpful in clearly judging the utility, while the ratio <italic>α</italic> can be used to make such judgements across various types of motors with different applications and outputs. Through both theoretical consideration and experiments, it has been proved that a motor with large PM flux linkage utilizes little reluctance torque even if the salient-pole ratio <italic>L<sub>q</sub></italic>/<italic>L<sub>d</sub></italic> is over 2.0 and that a large <italic>L<sub>q</sub></italic>/<italic>L<sub>d</sub></italic> increases iron loss, thus decreasing motor efficiency. We have also shown that the above-mentioned loss increase is caused by the significant superposition of <italic>q</italic>-axis flux due to the large <italic>L<sub>q</sub></italic> and have concluded that, in the above-mentioned case, selecting a rotor geometry with less saliency can improve the efficiency. Results are given for two types of four-pole prototype motors with an output power of 0.6 kW, a rated rotation number of 3600 min<sup>−1</sup>, and Y-connection.
A Load Balancer for Bursting Hadoop-based Network Analysis Jobs

In the age of the Internet of Things, all sorts of devices are turning into connected gadgets that can share information to the Internet and improve our lives. Today there are millions of these devices generating unabating amounts of data that need to be processed and analyzed. These large sets of data are also known as Big Data. The ability to take value out of Big Data can be seen as a major asset for competing companies. However, the processing of Big Data is unsuitable for traditional computing systems. Apache Hadoop is a framework that is designed to handle these large data sets. Though, as the number of connected devices grows, so does the amount of streamed data to be processed. Existing infrastructures might not be capable of handling the increased demand for processing power, leading to unwanted delays. Our study introduces High Availability techniques that can be deployed in a Hadoop cluster to reduce downtime and increase throughput. More importantly, it focuses on a specific technique called Cloud Bursting to enhance throughput and avoid server overloads, by leveraging a local private infrastructure through the usage of additional on-demand resources on a public Cloud. This hybrid cloud model is becoming a trend, as it offers scalability when the need arises. We present a Cloud Bursting solution for a Hadoop cluster that processes and analyzes network traffic through the use of the Packet Capture (PCAP) application programming interface (API). We introduce our map-intensive network analysis MapReduce job and present a simple model used to estimate its behavior. Our solution is powered by a custom inter-cluster Load Balancer that decides when to burst jobs. After a series of tests, our Load Balancer shows that in fact the Cloud Bursting technique is a viable option to improve the availability by minimizing job delays and maximizing cluster utilization when peaks of network traffic occur.
Reduced Sensor-Based PMSM Driven Autonomous Solar Water Pumping System

The nonlinear V–I characteristic of solar cell, calls for the use of maximum power point tracking (MPPT) method in order to obtain optimum power from solar photovoltaic (PV) array. Conventional MPPT methods require one voltage and one current sensor. This paper proposes a novel single sensor-based MPPT technique for a PV array fed water pumping using a permanent magnet synchronous motor (PMSM) drive. As the use of encoders, is not preferred for submersible water pumping, this paper uses a sensorless speed and position estimation for speed control of PMSM. The estimation of rotor speed and position, is achieved through the estimation of stator flux from voltages and currents in stationary reference frame. As the conventional flux estimators suffer from the problems, such as saturation, dc drift, and distortion, this paper proposes a mix multi-resonant structure for flux estimation. A sensorless speed control decreases the cost and improves the reliability of the solar water pumping system. The energy extracted from the PV array, is used to drive the PMSM, which rotates the pump coupled to it. Suitability of the proposed system is demonstrated under varying insolation conditions through a prototype developed in the laboratory and utilizing a digital signal processor (dSPACE-1202) for controlling the SWP system.
Extraction scenes point features on noisy digital images

The efficiency of the detector point features to a stationary uncorrelated noise digital television image analysis is produced. Two methods to improve the reliability of the isolation characteristics of the scene on digital images in a stationary uncorrelated noise are presented. The requirements to ensure the necessary level of signal/noise ratio for effective computer analysis of the scene on the image detector television spot features are given. The research results will improve the effectiveness of computer analysis of the scene on the TV picture in the autonomous local navigation and positioning complexes based on vision systems in stationary uncorrelated noise.
Potential and Impact of Incorporating Roof Photovoltaic to Enhance Environmental Sustainability of Historic English Churches in the United Kingdom

The Church of England (CofE) is responding to climate change by taking measures to reduce their CO2 footprint under its flagship programme -‘Shrinking the Footprint’, to facilitate the CO2 emission reduction target of 80 % by 2050. Meeting this target will require both energy efficiency measures and zero carbon energy generation of which solar PV technology is a frontrunner as it has a substantially lower CO2 footprint than grid’s electricity, with no moving parts, low maintenance and a long service life. Conventional church roofs built along the East-West axis offer the ideal pitches and orientation for collecting solar energy. However, within the CofE’s vast estate of over 15,000 church buildings, 78 % of these buildings are listed and hence care must be taken to protect the building fabric. With this context in mind, this study identifies the benefits and concerns associated with the application of rooftop solar PV on historic English Churches and evaluates viable technologies currently available. The specific design and procedural requirements have been investigated and the process map of the implementation methodology established and illustrated through a case study of an existing church. Results showed that rooftop solar PV system has the potential to reduce the GHG emissions substantially, ranging between 75 %–84 % for electricity and between 20 %–27 % for gas based on the current demand and the choice of technology option. Findings on the issues, design options and life cycle environmental impacts are analysed with discussion and recommendation of future adaptation at a national level.
High step‐up cascaded DC–DC converter integrating coupled inductor and passive snubber

A new high step-up cascaded DC–DC converter is proposed in this study, which is composed of one cascaded boost converter, one diode–capacitor structure and a coupled inductor with extended voltage-doubling cell. The proposed converter can achieve high-voltage gain by adjusting the duty cycle and the turns ratio of the coupled inductor, which avoids the circuit operating at the extreme duty cycle. Moreover, a passive clamped circuit is utilised to decrease the voltage stresses on the power devices and absorb the energy of leakage inductance of the coupled inductor to increase voltage gain. Thus, it reduces the conduction losses and alleviates the reverse-recovery problem of diodes. In conclusion, the proposed converter can achieve high-voltage gain and improve efficiency. The operating principle and steady-state analysis of the proposed converter is illustrated in detail in this study. Finally, experimental results of a prototype circuit with input voltage 40 V, output voltage 300 V and output power 200 W are presented to verify the analysis results of the proposed converter.
Multiplexing Optical Fiber Macro-Bend Load Sensors

This paper shows the multiplexing prospects of a load sensing array composed of six in-series optical fiber macro-bends. These fiber loops were individually embedded in silicone elastomer to constitute six sensor elements. Load configurations combining 0.0, 0.5, 1.0, and 1.5 kg were applied on the sensors to study the device performance. The sensor array, composed of standard fibers for optical communications, is spectrally interrogated in the visible window of the electromagnetic spectrum in a multimodal regime of operation. A simple linear regression model was used to estimate an unknown load configuration applied to the array from its associated transmittance spectrum. A sample space of 411 load configurations was used for training and testing the system. The ability of reconstruction was assessed by comparing the actual and predicted configurations of loads. A mean absolute error of 0.12 kg for the estimate was found under the testing conditions. In order to decrease the dimensionality of the dataset, principal component analysis and a discarding variable method were employed. Under 39% of data reduction, no significant impairment on the sensor array performance was observed.
Obstacle Avoidance Path Planning Design for Autonomous Driving Vehicles Based on an Improved Artificial Potential Field Algorithm

Obstacle avoidance systems for autonomous driving vehicles have significant effects on driving safety. The performance of an obstacle avoidance system is affected by the obstacle avoidance path planning approach. To design an obstacle avoidance path planning method, firstly, by analyzing the obstacle avoidance behavior of a human driver, a safety model of obstacle avoidance is constructed. Then, based on the safety model, the artificial potential field method is improved and the repulsive field range of obstacles are rebuilt. Finally, based on the improved artificial potential field, a collision-free path for autonomous driving vehicles is generated. To verify the performance of the proposed algorithm, co-simulation and real vehicle tests are carried out. Results show that the generated path satisfies the constraints of roads, dynamics, and kinematics. The real time performance, effectiveness, and feasibility of the proposed path planning approach for obstacle avoidance scenarios are also verified.
Underwater Robotics Complex for Inspection and Laser Cleaning of Ships from Biofouling

The survey of an underwater part of ships is the mandatory procedure by rules of the Russian Maritime Register of Shipping. Periodic cleaning of the ship’s hull from biofouling increases efficiency of its motion. Inspection of the underwater part of the ship during afloat is currently carried out by divers with the underwater video system, devices for non-destructive testing of hull structures, and tools for cleaning surfaces from products of biological fouling and corrosion. The purpose of this study was to develop a new technical tool for remote surveying and cleaning of ship’s hull using a remotely operated vehicle (ROV) equipped with underwater laser cleaning equipment. The design of the vehicle for inspection and laser cleaning of ships has been developed during the research. The algorithms for trajectory controlling of the vehicle over the hull surface based on wheel and propulsion system has been proposed. The navigation data for the trajectory planning was received from combination of wheel and visual odometry. The proposed technical solutions allow the hull of the ship to be inspected and cleaned effectively and safely without being placed in the dry dock as well as to quickly assess the condition of the surface with the binding of the results to the ship’s drawing.
Pulse Doppler Radar Principles Technology Applications

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Matched NGD circuit with resistor‐connected coupled lines

A negative group delay (NGD) circuit with simple structure has been proposed by using an open-circuited resonator and a pair of short-circuited coupled lines which are connected with two shunt resistors. The centre frequency of the NGD circuit is dominantly controlled by the open-circuited resonator, while the shunt resistors connected coupled lines are utilised for port matching, which greatly attenuates S 11 of the circuit. The proposed NGD circuit has been fabricated and measured, and the experiment shows an NGD time of - 4.6 ns, an NGD bandwidth of 120 MHz, and an S 11 attenuation of >33 dB. The experimental results approach to the prediction.