Miracle-dz/UniFAR-FTUs huggingface dataset:
Modelling the ultrasonic response from rough defects using efficient finite element modelling techniques

The work of this Engineering Doctorate addresses the research and development of e cient Finite Element (FE) modelling techniques for calculating the ultrasonic response from rough defects for NonDestructive Evaluation (NDE) applications speci c to the nuclear power generation industry. The project has been carried out in collaboration with Imperial College London and Rolls-Royce allowing for the transfer of novel academic research into an applied industrial context. Within the UK nuclear power generation industry, one of the fundamental principles of regulation and operation is a robust safety culture where the highest levels of quality assurance are applied to safety critical components. This principle places a requirement on NDE to deploy reliable and accurate inspections to ensure the structural integrity of the plant and its components. To achieve this goal, modelling techniques can be used to aid in the design and justi cation of ultrasonic NDE inspections. For smooth, relatively large defects, analytical methods can provide an accurate scattering solution; however, for more realistic rough defects, the limitations of these methods are only applicable for specialised cases of roughness. Defects which possess rough surfaces greatly a ect ultrasonic wave scattering behaviour. Ultrasonic NDE inspections of safety-critical components rely upon this response for detecting and sizing aws. Reliable characterisation is crucial, so it is essential to nd an accurate means to predict any reductions in signal amplitude. An extension of Kirchho theory has formed the basis for many practical applications; however, it is widely recognised that these predictions are pessimistic owing to analytical approximations. As a result, NDE inspections can be overly sensitive, meaning that small and insigni cant indications are incorrectly classed as being potentially hazardous defects. This increases the likelihood of making false-calls and incurring unnecessary expenditure to the programme. A numerical full eld modelling approach does not fall victim to such limitations, and therefore, FE modelling techniques have been developed to deliver a non-conservative methodology for the prediction of expected back-scattering from rough defects. This has been achieved in two parts: improved performance of absorbing boundary methods for use with commercial FE codes, and application of domain linking algorithms to NDE inspection problems. This thesis presents the development of these methods and their application to industrial NDE inspections. Ultimately, the ndings of this work will aid in establishing more reliable, less conservative, reporting thresholds for the inspection of power plant components, reducing false call rates and therefore any unnecessary expenditure.
Design of Single Sign-on for hybrid architecture based on Web service

To solve the problem of user repeated logon from various kinds of applications based on hybrid architecture and in different domains,a single sign-on architecture was proposed.On the basis of analyzing the advantages and disadvantages of existing single sign-on models,combined with the key technology like Web service,Applet and reverse proxy,two core problems such as single sign-on architecture mixing B/S and C/S structure applications and cross-domain single sign-on were resolved.Meanwhile,the security and performance of this architecture were well guaranteed since the reverse proxy and related encryption technology were adopted.The results show that this architecture is of high performance and it is widely applicable.
THE EFFECTS OF FOOD AND DRINK INTAKE TO DRIVING PERFORMANCE: A SYSTEMATIC REVIEW

Human-related factors are considered to be the main cause of traffic incidents or accidents, causing 69.70% of the incidents. Several studies have been conducted to identify the relationship between drowsiness or fatigue and driving performance. Furthermore, a number of other studies not only discussed the symptoms causing drowsiness but also tried to investigate related factors that cause sleepiness or fatigue while driving. On the other hand, some discussed the quantity and quality of sleep as well as food and drink intake before and while driving. This systematic review, which is based on the PRISMA method, aims to map previous studies that investigated the effect of different food/drink consumption, either taken prior to driving or while driving, on the on-road driving characteristics of drivers. Furthermore, this article is expected to serve as a reference for further research that could potentially contribute to minimizing driving errors that lead to incident or accident. From 1871 articles screened, 7 studies related to food/drink intake and driving performance were reviewed. On the basis of the existing studies, no real evidence showing the presence of the association between food intake and the monotony of the road to decrease the driving performance has been found; therefore, further research is needed.
Understanding patients’ trust toward community healthcare providers under different primary care settings in China: Impact of hospital ownership and registration mode

China is currently undertaking healthcare reform, and promoting general practitioner (GP) practice is a major improvement. The key to the success of the GP practice is whether or not patients are willing to accept and trust in GPs in community healthcare centers (CHCs). The objective of this study is to evaluate the impact of hospital ownership (public or private) and registration mode (registering with a CHC or a GP on patients’ trust in community health services. A user experiment was conducted, and 204 nonstudent participants were invited to finish simulated registration tasks in a self‐developed online registration system. Patients’ trust in CHCs, GPs, and GPs’ treatment outcomes was measured. The results indicated that patients had a significantly higher level of trust in private CHCs and private sector GPs, but they showed a higher level of trust in the treatment outcomes of public sector GPs due to the influence of their past medical experience seeing community doctors. The registration mode only influenced patients’ trust in GPs’ professional skills, that is, patients had a higher level of trust in GPs’ professional skills when registering with CHCs compared to registering with individual GPs.
Algebra An Approach Via Module Theory

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An insight into Old Hittite metallurgy: alloying practices at Hüseyindede (Çorum, Turkey)

This paper presents archaeological and analytical data on metal artefacts from Hüseyindede (Çorum, Turkey), dated to the Old Hittite period (ca 16th century BC). Hüseyindede, which is set in a rural landscape, demonstrates continuity in alloying traditions from the Early Bronze Age III (ca 26th/25th–22nd/21st century BC) and the Assyrian Trading Colonies period (20th–18th century BC) to the emergence of the Hittites. In addition to known alloying practices of the period, the site presents, for the first time, evidence of the existence of copper-nickel alloys, namely cupronickels, which so far have been documented only at the Late Bronze Age capital of the Hittites, Boğazköy/Hattuša. The Hüseyindede cupronickel objects now pinpoint the presence of this technology to regions spreading out from the Halys basin from the Old Kingdom Hittite period.
Balance with the interactive size effects of display, target, and key spacing in tablet tapping, dragging, and typing tasks

This study aimed to expand the current demonstration of display size effects from pointing tasks to dragging and tap‐typing tasks to investigate the effects of influential factors on the performance of touchscreen tablets. From 7‐ to 11‐in. displays, the index of difficulty was kept constant by increasing the target amplitudes and widths (6.0–9.5 mm) proportionally, and the key spacing were, respectively, 13.5 × 7.3–21.5 × 11.5 mm with 0‐mm key gaps. The results demonstrated that simple task types (complexities) reinforced the display size effects and that the effects interacted with target sizes (including amplitude/width scaling) and key spacing to reflect increasing efficiency and usability with increasing sizes. Gender effects were only significant in subjective assessments. Display sizes approaching 10 in. , target sizes not less than 7 mm (optimal 9–10 mm) and key spacing larger than 17.5 mm induced the effects of motor scale (the scale of the upper limb joint coordination) and interacted with one another to result in the optimal performance and usability.
BLOCKYLAND

Background BLOCKYLAND is a city building game based on the concept of cellular automata (CA), and urban cellular automata. The game has CA-like processes that invert the role of players from passive observers in other CA applications to active thinkers. The processes challenge players to apply logical thinking and decision making from the perspective of serious games. The players’ mission is to build a city by applying the provided CA rules. Two types of CA rules are provided: 1) The logical rule, whereby players apply to build the city according to the preset conditions, and 2) The optional rule, whereby they may apply to upgrade an existing building for an extra score. Aim This article aims to present the design and development of CA-based game, BLOCKYLAND and describe its effectiveness as an instructional tool to enhance logical thinking. Results Results from the mixed-method pilot study show that BLOCKYLAND enhanced players’ logical thinking after the gameplay. Additionally, from the extensive debriefing following the game, participants stated that the game aided them with transforming their game experiences into learning experiences and relating the logical thinking practice into real-life application. Results Conclusion. As a combination of logical thinking practices and a serious game, BLOCKYLAND has several implications for educational stakeholders; both theoretical and practical.
Numerical Simulation-Based Effect Characterization and Design Optimization of a Micro Cross-Flow Turbine

In this era of high power demand along with a need for sustainability, small and micro-scale hydro turbines are indispensable especially for off-grid power generation. These hydro-turbines are more appealing particularly for small-scale enterprises, hospitals, telecommunications, residential buildings and other public institutions located in remote areas that have rich hydropower potential. Due to their simple design, manufacturability and maintainability, micro cross-flow turbines are more feasible and applicable for power generation in undeveloped and developing countries with scattered hydropower resources. Such hydropower generations are environmentally friendly as their construction and operations have no significant effect on the surrounding ecosystem. In order to extract the highest possible power, however, the power generation efficiency of cross-flow turbines are not yet well optimized. In this paper, a numerical based investigation on 3D numerical models and design optimization study that is aimed to improve the turbine’s performance has been studied and reported. A numerical simulation based metamodel assisted optimization approach is deployed to carry out the optimization after the characterization of the design parameters following a previous experimental study on a similar model. The benefits of the approach with regard to computational costs and outcome of the optimization are discussed. Responses from the optimized design is compared against the original design responses at different magnitudes of design parameters. Published experimental test results based on similar conditions are used to verify the models at each stage. The approach is found effective and the optimized model shows a better performance and efficiency than the original models at similar working condition.
Effect of Pt deposition on digital image correlation analysis for residual stress measurement using FIB-DIC ringcore method

— FIB-DIC ringcore milling is an attractive semi-destructive method of measuring microscopic residual stress. Ensuring the accuracy and reliability of DIC analysis of sample surface deformation is critical for correct stress quantification, and relies on achieving reliable correlation between tracking sub-windows in the initial and deformed configurations. One way to improve the correlation is by increasing the image contrast using in-chamber deposition of an array of platinum nano-dots in a specific pattern. We carried out a study of the effect of Pt deposition on the accuracy of DIC analysis by comparing the results from the analysis of an un-patterned surface, and that of a Pt-patterned ring-core milling sequence. The results show that the Pt-patterned ring-core leads to a higher quality DIC analysis compared with the non-patterned case. This is demonstrated by the small relative displacement of markers, small marker ‘cleaning’ ratio, and a narrow distribution and high value of the correlation coefficient. Insufficient surface contrast is therefore identified as the main reason for aberrations and errors in DIC analysis: Pt pattern deposition can be used to ensure improved quality and reliability of DIC analysis. Hence, the utilization of Pt patterning is advised for FIB-DIC ring-core method, particularly for samples with smooth surface.
Statistical Schema Integration across the Deep Web

Schema integration is a central problem for integrating heterogeneous information sources. Traditionally, the problem has been defined and addressed as finding schema mapping between pairs of sources. This paper proposes a fundamentally different approach for schema integration, motivated by integrating large numbers of data sources on the Internet. On this ``deep Web," we observe two distinguishing characteristics that offer a fresh view for rethinking schema integration: First, as the Web scales, there are ample sources that provide structured information in the same domains (e.g., books and automobiles). Second, while sources proliferate, their aggregate schema vocabulary tends to converge at a relatively small size. Motivated by these observations, we propose a novel paradigm, "statistical schema integration": Unlike traditional pairwise mapping, we take a holistic approach to integrate all input schema instances by finding an underlying generative schema model. We define a general statistical framework MGS for such hidden model discovery, consisting of hypothesis modeling, generation, and selection. Guided by the framework, we develop Algorithm MGSac for finding attribute correspondence. We demonstrate our approach over hundreds of real Web sources in four domains and the results show remarkable accuracy.
A 3D assembly model retrieval method based on assembly information

Purpose The purpose of this paper is to propose a three-dimensional (3D) assembly model retrieval method based on assembling semantic information to address semantic mismatches, poor accuracy and low efficiency in existing 3D assembly model retrieval methods. Design/methodology/approach The paper proposes an assembly model retrieval method. First, assembly information retrieval is performed, and 3D models that conform to the design intention of the assembly are found by retrieving the code. On this basis, because there are conjugate subgraphs between attributed adjacency graphs (AAG) that have an assembly relationship, the assembly model geometric retrieval is translated into a problem of finding AAGs with a conjugate subgraph. Finally, the frequent subgraph mining method is used to retrieve AAGs with conjugate subgraphs. Findings The method improved the efficiency and accuracy of assembly model retrieval. Practical implications The examples illustrate the specific retrieval process and verify the feasibility and reasonability of the assembly model retrieval method in practical applications. Originality/value The assembly model retrieval method in the paper is an original method. Compared with other methods, good results were obtained.
Virtual Power Plant Management in Smart Grids with XMPP Based IEC 61850 Communication

Communication plays a key role in the effective management of virtual power plants (VPPs). For effective and stable operation of VPPs, a reliable, secure, and standardized communication infrastructure is required. In the literature, efforts were made to develop this based on industry standards, such as the IEC 60870-5-104, OpenADR 2.0b and IEC 61850. Due to its global acceptance and strong object-oriented information models, IEC 61850 standard-based communication is preferred for smart grid operations, including VPPs. However, communication models based on IEC 61850 present cybersecurity and scalability challenges. To address this issue, this paper presents an eXtensible Message Presence Protocol (XMPP)-based IEC 61850 communication for VPPs. Firstly, a full mapping of IEC 61850 messages for VPP energy management is carried out. Secondly, XMPP-based single- and multiple-domain communications are demonstrated. Finally, a federation concept has been added to facilitate communication in multi-domain communication networks. These models show that a standard communication model can be implemented with IEC 61850 and XMPP, not only for VPPs but other wide-area communication implementations in smart grids. This not only facilitates plug-and-play (PnP) with easy component additions but secures smart grid communication against cyber-attacks.
Fundamentals of Data Mining and Data Warehousing

It is generally observed throughout the world that in the last two decades, while the average speed of computers has almost doubled in a span of around eighteen months, the average speed of the network has doubled merely in a span of just eight months! In order to improve the performance, more and more researchers are focusing their research in the field of computers and its related technologies. Data mining is one such area that extracts useful information from the huge amount of data present in the dataset. The discovered knowledge can be applied in various application areas such as marketing, fraud detection and customer retention in product based companies and so on. It discovers implicit, previously unknown and potentially useful information out of dataset. Recent trends in data mining include web mining where it discovers knowledge from web based information to improve the page layout, structure and its contents.
Inferring the Demographics of Search Users

Knowing users’ views and demographic traits oers a great potential for personalizing web search results or related services such as query suggestion and query completion. Such signals however are often only available for a small fraction of search users, namely those who log in with their social network account and allow its use for personalization of search results. In this paper, we oer a solution to this problem by showing how user demographic traits such as age and gender, and even political and religious views can be eciently and accurately inferred based on their search query histories. This is accomplished in two steps; we rst train predictive models based on the publically available myPersonality dataset containing users’ Facebook Likes and their demographic information. We then match Facebook Likes with search queries using Open Directory Project categories. Finally, we apply the model trained on Facebook Likes to large-scale query logs of a commercial search engine while explicitly taking into account the dierence between the traits distribution in both datasets. We nd that the accuracy of classifying age and gender, expressed by the area under the ROC curve (AUC), are 77% and 84% respectively for predictions based on Facebook Likes, and only degrade to 74% and 80% when based on search queries. On a US state-by-state basis we nd a Pearson correlation of 0 :72 for political views between the predicted scores and Gallup data, and 0:54 for aliation with Judaism between predicted scores and data from the US Religious Landscape Survey. We conclude that it is indeed feasible to infer important demographic data of users from their query history based on labelled Likes data and believe that this approach could provide valuable information for personalization and monetization even in the absence of demographic data.
Design and development of reconfigurable embedded system for real‐time acquisition and processing of multichannel ultrasonic signals

The study proposes a novel hardware-based architecture of the reconfigurable embedded system for the multi-channel immersion ultrasonic system. It provides the addressing-based analogue multiplexing scheme, which requires only one data acquisition unit and common on-chip storage for the multi-channel imaging system. It also provides unique channel reconfigurable facility to the user to modify the number of channels (up to 256 for pulse-echo and 512 for transmit-receive mode by installing only the partial front-end hardware (pulser, pre-amplifier) and without modifying the remaining data acquisition hardware (common-amplifier, digitiser) and back-end embedded system. The developed system further supports dynamic on-line reconfiguration of the analogue front-end hardware, real-time hardware-based data processing, and data transfer operation. The authors have implemented the addressing-based reconfigurable architecture of the coherent averaging for noise reduction. For the experimentation, the complete four-channel ultrasonic imaging system for immersion testing has been designed, developed, and evaluated in the laboratory. Furthermore, this study describes the capability of the proposed system by performing multi-channel real-time data acquisition, hardware-based coherent averaging, channel multiplexing-demultiplexing, reconfigurable control, and software-based post-processing. Here, they present the performance evaluation of the developed multi-channel system by carrying out the B-scan and C-scan image acquisition of the water-immersed mechanical components.