Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of Geomagnetically Induced Currents on Power Transformers

iii Co-Authorship . iv Dedication . vii Acknowledgements . viii Table of Contents . ix List of Tables . xiii List of Figures . xiv Chapter 1 Introduction . 1 1.1 Background . 1 1.1.1 Effects of GIC . 3 1.1.2 Measurement and Monitoring . 10 1.1.3 Forecasting . 11 1.1.4 Modelling . 12 1.1. 5 System Solution . 14 1.1. 6 Mitigation . 14 1.2 Motivation . 15 1.3 Objective . 16 1.4 Outline . 16 References . 17 Chapter 2 A Software Simulator for Geomagnetically Induced Currents in Electrical Power Systems . 25 2.1 Nomenclature . 25 2.2 Introduction . 26 2.3 Simulation Method . 27 2.3. 1 Mapping Transmission Station Locations . 28 2.3. 2 Modeling of Network Components . 32
Digital image watermarking methods for copyright protection and authentication

The ease of digital media modification and dissemination necessitates content protection beyond encryption. Information hidden as digital watermarks in multimedia enables protection mechanism in decrypted contents. The aims of this research are three-fold: (i) to investigate the strength and limitations of current watermarking schemes, (ii) to design and develop new schemes to overcome the limitations, and (iii) to evaluate the new schemes using application scenarios of copyright protection, tamper detection and authentication. We focus on geometrically robust watermarking and semi-fragile watermarking for digital images. Additionally, hybrid schemes that combine the strength of both robust and semi-fragile watermarks are studied. Robust watermarks are well suited for copyright protection because they stay intact with the image under various manipulations. We investigated two major approaches of robust watermarking. In the synchronization approach, we employed motion estimation for watermark resynchronization. We also developed a novel watermark resynchronization method that has low computational cost using scale normalization and flowline curvature. In another approach, we firstly analyzed and improved a blind watermark detection method. The new method reduces significantly the computational cost of its watermark embedding. Secondly, we created a geometric invariant domain using a combination of transforms, and adapted the blind watermark detection method that we improved. It totally eliminates the need of resynchronization in watermark detection, which is a very desirable achievement that can hardly be found in existing schemes. On the other hand, semi-fragile watermarks are good at content authentication because they can differentiate minor image enhancements from major manipulations. New capabilities of semi-fragile watermarks are identified. Then, we developed a semi-fragile watermarking method in wavelet domain that offers content authentication and tamper localization. Unlike others, our scheme overcomes a major challenge called cropping attack and provides approximate content recovery without resorting to an original image. Hybrid schemes combine robust and semi-fragile watermarks to offer deductive information in digital media forensics. We firstly carried out a pilot study by combining robust and fragile watermarks. Then, we performed a comparative analysis on two implementation methods of a hybrid watermarking scheme. The first method has the robust watermark and the fragile watermark overlapped while the second method uses non-overlapping robust and fragile watermarks. Based on the results of the comparative analysis, we merge our geometric invariant domain with our semi-fragile watermark to produce a hybrid scheme. This hybrid scheme fulfilled the copyright protection, tamper detection, and content authentication objectives when evaluated in an investigation scenario.
IRIS RECOGNITION BORDER-CROSSING SYSTEM IN THE UAE

For the past three years, the United Arab Emirates (UAE) has employed an iris recognition system for all passengers arriving in the UAE by land, sea or air. By looking at an iris camera for a second or two while passing through immigration control, each passenger's iris patterns are encoded mathematically and the resulting image is sent over a distributed communications network to a central database where they are compared with the images from 420,000 people who were expelled from the UAE for various violations. Less than one second is required for each image to be compared against the full database. More than 9,500 people have been caught traveling with forged identities by this system. This article describes the system in detail, including the critical features of the system architecture and the algorithm for encoding and comparing iris patterns. The system operates in an "all against all" identification search mode. The decision thresholds are automatically adjusted according to the size of the enrolled database and thus the number of comparisons performed, so that there is no net accumulation of probability of false matches. This makes the system extremely efficient and accurate. All of the matches made so far between arriving passengers and violators in the database have been confirmed by other records.
Impact of body truck’s microclimate on pig skin temperature during pre-slaughter logistics

Handling of pigs under hot weather conditions face a critical challenge in meeting thermal comfort and animal welfare standards. Moreover, climate variation affects production and pre-slaughter logistics. This study assesses the thermal comfort of pigs during pre-slaughter procedures under different weather conditions. The case study was conducted at two commercial pig farms in Southeastern Brazil. The bioclimatic index more accurately indicated the pigs' thermal comfort than the temperature-humidity index. The length of the transportation journey critically affected the pigs' thermal comfort, as shown by the rise in pigs' skin temperature (1.56 °C and 1.64 °C on pigs from Farm 2 and Farm 1, respectively). The pigs reached the critical upper limit of the thermoneutral zone under hot weather conditions. Adequate microclimate control during the pre-slaughter management procedures might improve pig welfare. To increase the animals' thermal comfort, both farms should reschedule their transportation to a cooler time of the day. Both farms should also improve their pre-slaughter management processes by training workers to comply with animal welfare requirements and reduce loss.
A Reinforcement Learning Algorithm for Automated Detection of Skin Lesions

Skin cancers are increasing at an alarming rate, and detection in the early stages is essential for advanced treatment. The current segmentation methods have limited labeling ability to the ground truth images due to the numerous noisy expert annotations present in the datasets. The precise boundary segmentation is essential to correctly locate and diagnose the various skin lesions. In this work, the lesion segmentation method is proposed as a Markov decision process. It is solved by training an agent to segment the region using a deep reinforcement-learning algorithm. Our method is similar to the delineation of a region of interest by the physicians. The agent follows a set of serial actions for the region delineation, and the action space is defined as a set of continuous action parameters. The segmentation model learns in continuous action space using the deep deterministic policy gradient algorithm. The proposed method enables continuous improvement in performance as we proceed from coarse segmentation results to finer results. Finally, our proposed model is evaluated on the International Skin Imaging Collaboration (ISIC) 2017 image dataset, Human against Machine (HAM10000), and PH2 dataset. On the ISIC 2017 dataset, the algorithm achieves an accuracy of 96.33% for the naevus cases, 95.39% for the melanoma cases, and 94.27% for the seborrheic keratosis cases. The other metrics are evaluated on these datasets and rank higher when compared with the current state-of-the-art lesion segmentation algorithms.
Improving Die Rework Capability: Opportunities for Using 3D Non-Contact Measurement Technology to Reduce Die Tryout Iterations to Resolve Dimensional Issues

This report summarizes automotive body die tryout performance, based on a survey of and interviews with die manufacturing experts from automotive body manufacturers and die suppliers. The report explores opportunities for more effectively integrating new 3D noncontact optical measurement technologies during the die tryout process to improve performance. It provides basic guidelines for optical measurement data collection for stamping dies and resultant parts as well as analysis methods. For medium-complexity parts, the study participants estimate that a typical number of die tryout iterations is five to nine over a nine to 14 week period using typical North American tolerances and part acceptance criteria. The key enablers to reduce die tryout time were advancements in die forming and simulation software, particularly for complex materials, as well as advancements in virtual assembly tools.
A Review of Bankruptcy Prediction Studies: 1930 to Present

One of the most well-known bankruptcy prediction models was developed by Altman [1968] using multivariate discriminant analysis. Since Altman's model, a multitude of bankruptcy prediction models have flooded the literature. The primary goal of this paper is to summarize and analyze existing research on bankruptcy prediction studies in order to facilitate more productive future research in this area. This paper traces the literature on bankruptcy prediction from the 1930's, when studies focused on the use of simple ratio analysis to predict future bankruptcy, to present. The authors discuss how bankruptcy prediction studies have evolved, highlighting the different methods, number and variety of factors, and specific uses of models. Analysis of 165 bankruptcy prediction studies published from 1965 to present reveals trends in model development. For example, discriminant analysis was the primary method used to develop models in the 1960's and 1970's. Investigation of model type by decade shows that the primary method began to shift to logit analysis and neural networks in the 1980's and 1990's. The number of factors utilized in models is also analyzed by decade, showing that the average has varied over time but remains around 10 overall. Analysis of accuracy of the models suggests that multivariate discriminant analysis and neural networks are the most promising methods for bankruptcy prediction models. The findings also suggest that higher model accuracy is not guaranteed with a greater number of factors. Some models with two factors are just as capable of accurate prediction as models with 21 factors.
Clinically Relevant Postoperative Pancreatic Fistula rates in two methods of pancreatico-jejunal anastomosis compared: Evolution of surgical technique in a single centre over time

Background:Pancreaticoduodenectomy remains the gold standard for management of patients with pancreatic head and periampullary neoplasms. Despite the low mortality, overall morbidity remains high, principally due to the development of a clinically relevant postoperative pancreatic fistula (CR-POPF). The aim of the present study is to compare rates of CR-POPF in two groups of patients treated with two different pancreaticojejunostomy techniques. Methods:Among 264 consecutive patients submitted to surgery for pancreatic neoplasm, 142 pancreaticoduodenectomies with end-to-side pancreaticojejunostomy were analysed. The first group of patients underwent a direct mucosa-to-mucosa anastomosis as described by Longmire and Traverso. In the second group, a duct-to-mucosa anastomosis with an outer seromuscolar and inner full thickness layer as described by Z’graggen, Shrikhande and Buchler was performed. Results:Mortality was 2,8% in the first group (2/71) and zero in the second. In group 1°, 48.5% of patients suffered one or more grade II-V Clavien-Dindo complications; in group 2°, complications were observed in 26,7% of patients. Clinically relevant POPF occurred in 12 patients in group 1° (17%) and in 4 patients in group 2° (5,6%). Conclusions:Changing pancreaticojejunostomy techniques may produce different outcomes. In our experience, a standardized duct-to-mucosa anastomosis, as performed in group 2, significantly reduced the rate of CR-POPF.
Performance of Geometry among the Secondary School Students of Bhurbandha CD Block of Morigaon District, Assam, India

The aim of the paper is to examine the geometrical performance, gender wise variation in learning geometry of the students of secondary level and their learning environment. The data is collected from some selected schools of Bhurbanhda CD Block of Morigaon district of Assam. To know the performance in geometry and the problems faced by the students to understand the geometry, a test was taken and a question paper of 25 marks and scheduled questionnaire was prepared. Also a discussion was conducted with the teachers to find out the problems of the students in learning mathematics when it is connected to geometry. To analyze the data, simple statistical method is used. After the study it is found that the fundamental knowledge in geometry is very poor among most of students in secondary level. As it is observed in most of the cases students have great difficulty in geometry part of their mathematics curriculum. So it is very important to improve performance in geometry to improve mathematics as a whole. To improve the knowledge of geometry among the students, government should think of it as a matter of urgency, send mathematics teachers for training and seminars for effective teaching and learning.
N+3 Aircraft Concept Designs and Trade Studies. Volume 2; Appendices-Design Methodologies for Aerodynamics, Structures, Weight, and Thermodynamic Cycles

MIT, Aerodyne Research, Aurora Flight Sciences, and Pratt & Whitney have collaborated to address NASA s desire to pursue revolutionary conceptual designs for a subsonic commercial transport that could enter service in the 2035 timeframe. The MIT team brings together multidisciplinary expertise and cutting-edge technologies to determine, in a rigorous and objective manner, the potential for improvements in noise, emissions, and performance for subsonic fixed wing transport aircraft. The collaboration incorporates assessment of the trade space in aerodynamics, propulsion, operations, and structures to ensure that the full spectrum of improvements is identified. Although the analysis focuses on these key areas, the team has taken a system-level approach to find the integrated solutions that offer the best balance in performance enhancements. Based on the trade space analyses and system-level assessment, two aircraft have been identified and carried through conceptual design to show both the in-depth engineering that underpins the benefits envisioned and also the technology paths that need to be followed to enable, within the next 25 years, the development of aircraft three generations ahead in capabilities from those flying today.
Improving The Constructability Of A Design Solution Through An Integrated System

The invention comprises 2,3-dimercapto-quinoxalines of the general formula: wherein R represents a hydrogen or halogen atom or a nitro, trifluoromethyl, C1-C4 alkyl or C1-C4 alkoxy radical; R1 represents a hydrogen atom or a hydroxy, alkyl, cycloalkyl, aryl, chloroaryl, aralkyl, alkylsulphonyl, arylsulphonyl or primary or secondary amino radical; and R2 represents a hydrogen atom or an acyl, alkyl, cycloalkyl, aralkyl, aryl, alkoxy, alkylmercapto, arylmercapto or a primary or secondary amino radical. They may be prepared by reacting a 2,3-dimercapto-quinoxaline of the general formula: or an alkali metal or ammonium salt thereof, with a compound of the general formula: in an aqueous or aqueous organic medium at -20 DEG to + 100 DEG C. and preferably in the presence of an acid-binding agent. The compounds of the formula: wherein R1 and R2 represent alkyl, cycloalkyl, aryl, chloroaryl or aralkyl radicals, may also be prepared by reacting the 2,3-dimercapto-quinoxaline starting material specified above with two molecules of a carbodiimide of the general formula: R1-N=C=N-R2. Several examples are given and the compounds of the invention are stated to be pest control agents (see Division A5). ALSO:Compounds of the general formula wherein R represents a hydrogen or halogen atom or a nitro, trifluoromethyl, C1 to C4 alkyl or C1-C4 alkoxy radical; R1 represents a hydrogen atom or a hydroxy, alkyl, cycloalkyl, aryl, chloroaryl, aralkyl, alkylsulphonyl, arylsulphonyl or primary or secondary amino radical; and R2 represents a hydrogen atom or an acyl, alkyl, cycloalkyl, aralkyl, aryl, alkoxy, aryloxy, alkylmercapto, arylmercapto, or primary or secondary amino radical, are stated to be pest control agents which may be employed in admixture with solid or liquid, diluents or carriers.
Prediction model development of preterm birth using time series technology based machine learning (Preprint)

BACKGROUND Globally, the trends of preterm birth rate have been increasing over time. Ultrasonography cervical length assessment is considered to be the most effective screening method, however, universal cervical length screening in the whole population remains controversial because of the cost budget. OBJECTIVE In this work, obstetric data are used to analyze and assess the risk of preterm birth. The purpose is to screen high-risk groups of preterm birth in the early and second trimester of pregnancy, and targeted cervical screening is more in line with health economics. METHODS This study attempts to use continuous electronic medical records(EMRs) data of pregnant women to construct a preterm birth predicting classifier based on long short-term memory (LSTM) networks. The clinical data were collected from 5187 Chinese pregnant women with natural vaginal delivery, including more than 25,000 obstetric EMRs during the early trimester to 28 weeks of gestation. The area under ROC curve, accuracy, sensitivity and specificity were used to assess the performance of prediction model. RESULTS Compared with traditional cross-sectional study, LSTM model in time series study has better overall prediction ability, which has a lower misdiagnosis rate with the same detection rate, and the accuracy was 0.739, sensitivity was 0.407, specificity was 0.982, and AUC was 0.651. Feature importance identification indicated that blood pressure, blood glucose, lipids, uric acid and other metabolic factors were the important factors related to preterm birth. CONCLUSIONS The results of this study are helpful to the formulation of guidelines for the prevention and treatment of preterm birth, and it can assist the clinicians to make correct decisions during the obstetric examinations. For the preterm birth prediction scenario, time series model has certain advantages.
KINEMATIC COMPARISON OF GRAB AND TRACK STARTS IN SWIMMING

The purpose of this study was to compare takeoff and entry characteristics of track starts performed with normal and restricted spacing of the feet to grab starts. Track starts produced a faster (p = 0.06) and steeper (p = 0.07) entry further from the block (p = 0.18) than grab starts despite similar takeoff speeds and angles. Differences contributing to the improved entry characteristics included increased takeoff height (p = 0.01) and lowered entry height (p = 0.2). Little difference was found in takeoff and entry trunk orientation. These data suggest that track starts offer performance advantages over the grab start. Furthermore, these advantages were not diminished by restricting the spacing of the feet in the track start suggesting that the track start can be performed on shorter starting blocks without diminishing performance.
Decomposing Perceived Behavioural Control: Addressing Financial Literacy in Determining Muslims’ Intention to Purchase Unsought Products

Purpose: This paper addresses the importance of planning for unanticipated risks which may lead to losses in peoples’ lives and in this study, the lives of Muslim consumers when they are not managing unanticipated risks well. The need to purchase unsought products like life insurance/Takaful dictates the relevance of financial literacy in affecting perceived behavioural control that may influence purchase intention. Design/methodology/approach: This study uses Structural Equation Modelling as means of assessing the proposed framework. Using the Decomposed Theory of Planned Behaviour (DTPB) as the basis, this paper examines the relevance of determinants affecting perceived behavioural control in influencing purchase intention of unsought goods with financial literacy as a new determinant in the DTPB framework. Findings: The findings reveal that financial literacy, resource facilitating condition and self-efficacy affect perceived behavioural control which ultimately influence purchase intention. Practical implications: By examining financial literacy, resource facilitating condition and self-efficacy on perceived behavioural control, the study validated the importance of these constructs in affecting consumers’ perceived behavioural control and purchase intention. This study would be useful to life insurance operators, as the findings can be inputs for
Energy-led, non-domestic building refurbishment : decision support for a whole-building approach to improvement of operational performance

Pressure is growing upon non-domestic building owners and occupiers to measure and improve the energy performance, and associated carbon emission levels, of the portfolio in which they operate. In line with this, the need for energy-led refurbishment of existing buildings is increasingly evident, with approximately 60% of the current building stock expected to still exist in 2050 and less than 1% being replaced annually. However, energy-led refurbishment of existing non-domestic property faces a number of barriers, including an ill-defined decision-making process and a lack of low carbon skills required to guide building owners in this complex transition. This thesis examines first, the need for a re-alignment of disciplines within the construction industry to fulfil the growing requirement for low carbon skills, specific to energy-led refurbishment. A comprehensive desk study was undertaken, evaluating the competencies of the established construction industry professions, as defined by their governing bodies. This was supported by structured interviews with users of large, nondomestic property and industry professionals to establish whether a need existed and how they proposed it be fulfilled. A deficiency in expertise was identified, and from this a competency specification for professionals leading energy-led refurbishment in existing, non-domestic property has been developed. Second, this thesis explores the different forms of automated decision support within the construction sector, identifying opportunities for a structured decision-making approach to energy-led refurbishment. An optimum decision support tool (DST) process was proposed, consisting of seven steps from assessment of the existing building’s state through to continuous evaluation and improvement of the refurbished building. A key module within this process was developed in detail to address the complex multiple attribute decision making (MADM) approach required during selection of energy performance improvement measure (EPIM). A set of assessment criteria, addressing a variety of performance characteristics, was designed using an online Delphi survey with a select group of ‘energy in buildings’ experts. The criteria range from short term impact (EPIM installation) to long term impact (EPIM operation and disposal) upon the existing property’s performance. Subsequent weighting of the assessment criteria in terms of their relative importance was undertaken using the same expert group through a paired comparison survey methodology. This revealed the relative importance of each criterion, consequently aiding prioritisation of EPIMs within the optimum DST and supporting decision-making.