Miracle-dz/UniFAR-FTUs huggingface dataset:
Preliminary Design of an Aircraft Automatic Painting and Paint Removal System

The maintenance of the aircraft finish system is executed completely manually at present, involving a big amount of manual labor for a long time and in a hazardous environment. The automation of the process would be able to dramatically speed it up and to decrease manpower involved, with a consequent contraction in costs and environmental risks. It is at the moment an important challenge within the aerospace industry also because of the expectations of airplanes fleet growth over the coming years. Several solutions are being developed, nevertheless, a system able to achieve the maintenance process automatically is not yet available. Along this thesis, a preliminary design of an automatic system for aircraft painting and paint removal has been carried out. The work points out that a low cost solution for this complex problem is possible. As a preliminary study, this is intended to be a starting point for further development on this subject.
Fraud Detection, Quantum Mechanics, and Complex Systems Lecture 3 Notes for CSSS2010

Disclaimer: Same declaimer as lecture 1 (Complex Systems, Statistical Learning, and Pickles). The material from lecture 1 is freely used. Okay, okay, the quantum part of the title is something of joke, mathematicians simply can’t resist the word quantum! But in all seriousness, I hope to convince you the tools from quantum mechanics play an interesting role in exploring the geometry of a Markov chain. Equally importantly this analogy allows us the opportunity to dwell on a fundamental issue in in the study of complex systems, that the environment is often determined by the objects in the system and visa versa. Here we use the mathematical tools from basic quantum mechanics to discuss and quantify this. Concretely, we view our system as being described by a state in a Hilbert space, which on this case is nothing more more than a complex valued function on the chain’s states viewed as living in C|States| which has been endowed with the natural Hermitian inner-product
Predicting Unmet Need for Social Care

Context: Demographic and other pressures have placed strains on the social (long-term) care systems in many countries. An ageing population and cuts to local authority budgets have put pressure on the availability of local authority funded adult social care in England and have raised concerns about unmet social care needs among older people. To prevent care needs going unmet, it is crucial to understand their predictors. However, research on this topic is limited. Objective(s): To understand the predictors of unmet needs for adult social care in England. Method(s): Using data from the English Longitudinal Study of Ageing (2002–2012), we employed an activities-based approach to develop a definition of unmet social care needs, drawing on available data, previous literature and consultations with social care users and carers. We then used logistic regression to analyse the factors that predict developing an unmet care need over a 10-year period among a sample of those aged 50 and older. Findings: The likelihood of developing unmet care needs does not differ by factors like gender, wealth, social contact, education or health behaviours. The only significant predictors for unmet needs are living alone, being relatively young (though still over 50), not having a longstanding illness, losing a spouse and developing more severe needs. These findings are robust to a variety of model specifications. Limitations: Results of this analysis may be sensitive to the definition of unmet need employed. Implications: These findings contribute to the current debate on the funding and organisation of adult social care in England and will inform policymakers interested in addressing the issue of unmet social care needs among older people.
Bidding Behavior of Generators under Deregulated Environment

In a deregulated electricity marketplace, the electricity price is not determined by a power authority, but by competitive bidding behaviors of power suppliers. A generating company, willing to sell energy through this market, is asked to bid blocks of power along with prices for each trading period. In electricity markets organized as pools, electrical power producers provide offers (called sometimes bids) of power generation in defined price bands for every trading interval. Usually, the price offered reflects the variable cost of generation. Competitive bidding makes power supplies being no longer just the electricity price takers. Each power supplier becomes involved in setting the electricity price. In a perfectly competitive electricity market, any power supplier is not a price maker. Microeconomic theory holds that the optimal bidding strategy for a supplier is to simply bid marginal cost. When a generator bids other than marginal cost, in an effort to exploit imperfections in the market to increase profits, this behavior is called strategic bidding. Since the power market is an oligopoly market rather than a perfect competition market. In such a deregulated electricity market, the formation of bidding strategy is one of the most challenging and important tasks for electricity participants to maximize their profit. Bidding behavior of market participants is determined by several factors such as, the demand variation, generator production cost, operating constraints or some regulatory constraints, other competitors bidding behavior, etc. This paper analyses a typical bidding behavior of generators in a perfect and imperfect electricity market with various uncertainties.
Dealing with DNS Ampliﬁcation Attacks using Response Rate Limiting

—The Domain Name System (DNS) provides one of the most fundamental functionalities of the Internet as we know it, which is resolving names into IP addresses and vice-versa. Unfortunately it relies heavily on the UDP transport protocol making it vulnerable to DDoS reﬂection attacks. It also allows attackers to amplify their malicious trafﬁc through DNS servers. Small queries can generate responses many times their size. Combining these two factors made DNS one of the most abused systems by DDoS attacks, that have also been increasing in scale in recent years. As the entity that oversees the critical function of the Top-Level-Domain corresponding to Portugal (.pt), DNS.pt has the responsibility to avoid causing a major economical and social impact in its partners, not only damaging other businesses but also their own reputation. A recently introduced mechanism called Response Rate Limiting has shown to be effective in mitigating these kind of attacks. This work studies its application for the Top-Level Domain of Portugal (.pt), managed by DNS.pt.
Improving block-matching algorithm by selecting sets of disparities minimizing distortion for stereoscopic image coding

—This paper deals with the estimation of a blockwise disparity map in the context of stereoscopic image coding. This disparity map is used to predict one view using the other view as reference. It is generally computed according to the Block Matching algorithm which achieves good performance in terms of bitrate-distortion. Namely, disparities are selected amongst a search area by minimizing a local distortion metric modelling the quality of the prediction. Note that the larger the search area is, the more often a better disparity can be chosen and the lower the global distortion is. On the other hand, using large search areas yield disparity maps containing a higher number of different disparities, and such disparity maps are generally encoded with a larger bitrate. In this paper two algorithms are proposed, they enable to compute collections of good search areas among which one can ﬁnd a speciﬁc search area minimizing the distortion at a given bitrate. Simulations results conﬁrms the beneﬁts of both algorithms.
PATTERN DISCOVERY-A SAX-GA Based Investment Strategy

This paper presents a new computational finance approach, combining a Symbolic Aggregate approXimation (SAX) technique together with an optimization kernel based on genetic algorithms (GA). The SAX representation is used to describe the financial time series, so that, relevant patterns can be efficiently identified. The evolutionary optimization kernel is here used to identify the most relevant patterns and generate investment rules. The proposed approach was tested using real data from S&P500. The achieved results show that the proposed approach outperforms both B&H and other state-of-the-art solutions.
Simplification and Normalization of a Landing Gear’s Expertise Procedure

Maintenance, repair and overhaul of aircraft’s components is a growing competitive market, thus it is key to increase the company’s profitability by improving processes, reduce waste and the Turnaround time (TAT). Lean Thinking tools and principles are essential to achieve such goals in the current production markets, especially in the automotive industry. Their implementation in maintenance is challenging since the component maintained condition plays a massive role, nevertheless they are successfully applied to the maintenance industry and Lean maintenance concept emerged. The present work implements such tools and principles in order to improve OGMA’s landing gear maintenance processes, reduce waste and increase its profit margin. The company in question requested the simplification and normalization of the expertise procedure of the Embraer aircraft’s E190 landing gear. A program was conceived in order to meet the objectives established, using poka-yoke mechanisms to avoid errors. This program, when implemented, will increase the value-adding time of this activity from the current 40% to 93%. In addition, the global maintenance procedure was analysed and a value stream map styled flowchart constructed, which enabled to identify sources of waste and propose solutions that improve such processes that go beyond the elaboration of the expertise report. Such changes when put into practice could produce gains in the order of 20% in the TAT.
Stator Fault Detector for AC Motors

Stator faults, such as the inter-turn, inter-phase, and phase-to-ground short circuits, or a broken connection in one or more phases, constitute the most common cause of failure of three-phase ac motors. In many instances, especially these involving critical drives, an early warning of the impending drive stoppage is crucial, allowing task re-scheduling to avoid costly process interruptions. Although serious faults usually result in immediate tripping of the motor, some of them may spread slowly, so that the motor can still run for certain amount of time. The challenge is to catch a fault as early as possible, utilizing only the stator current and voltage signals [1],[2].
Gonokokken-, Chlamydien- und Ureaplasmen-Infektion bei AIDS

Sexuell übertragbare Infektionen sind auf dem Vormarsch. Neben einer deutlichen Zunahme an Infektionszahlen stellen vermehrte Resistenzen gegen Antiinfektiva und Koinfektionen eine besondere therapeutische Herausforderung dar. Die Früherkennung durch den ersten Ansprechpartner im Gesundheitswesen, also durch den Hausarzt, ist besonders wichtig, um Folgeschäden zu vermeiden und einer epidemiologischen Verbreitung entgegenzuwirken.
Going beyond a positive–negative dichotomy in judgment and decision‐making research: Insights for framing, counterfactual thinking, and ambivalence

Funding information Center for Social and Economic Behavior (CSEB), Grant/Award Number: Rd09-2019-SGSparks Abstract Many areas of judgment and decision-making research have historically relied on a simple positive–negative dichotomy (e.g., positive vs. negative framing). Although this classic assumption about the conceptual space has contributed to some of the field's more impactful findings (e.g., framing effects), it may also have mistakenly led us to believe that these findings told a complete story about biases in processing positive and negative information. Building on a tradition of theoretical accounts outlining how positive and negative information is more complex, the first part of this paper considers how the following three elements jointly help to tell a more complete story about framing effects: (a) regulatory focus theory's concept of the domain (loss vs. gain) of an outcome, (b) the sequencing of positive and negative frames, and (c) the asymmetric influences of positive and negative evaluative processes. Next, the paper reviews research that has contributed to integrating these elements, highlighting opportunities for further integration to generate new insights for framing effects, risky decision-making, counterfactual thinking, and ambivalence. The reviewed studies suggest that a more sophisticated conceptualization of positive and negative information contributes to a deeper understanding of the basic processes that govern human judgment and decision-making. DOI: 10.1111/spc3.12519
An Impact on Teacher Qualifications on Student Achievement in Science: A Study on the G.C.E (O/L) in Trincomalee District

The purpose of this study was to investigate an impact of teacher qualifications on student achievement in science based on the G.C. E (O/L) performance in Trincomalee division. Teacher qualification is very important because of, it directlyaffects to student performance. Student performance was considered as the dependent variable, and teacher educational qualification, subject major, teaching experience and professional development, were considered as the independent variables.The researcher selected all the teachers who taught science subject for the G.C. E (O/L) classes in the Trincomalee Division for this research study. One questionnaire was used to collect the data from the teachers. 53 questionnaires were distributed among the science teachers in Trincomalee Division. The response rate of the teachers was 100%. The science students achievement were analysis through GCE (O/L) result. The average grade of each teacher’s students was used as the achievement of the teacher’s students. Respondents were analyzed for their level of student’s performance on five point likert scale as the scaling method. The measurement scale for independent variables were “interval”. The data was analyzed using Statistical Package for Social Sciences (SPSS) Version 16. Mean Score and Standard deviation were used for Univariate analysis and correlation and simple regression were used for bivariate analysis. Multiple regressions was used to multivariate analysis. The Hypotheses were tested using the Pearson Product Movement Correlation Coefficient (r) beta value (β) and p value.The result indicated that teaching experience, educational qualification and subject major were strong significant positive predictors of student performance in science. Based on this it can be argued that these factors were highly influenced on the student performance in science.In addition to these three factors (Teaching experience, educational qualification and subject major) and other factor of professional development were also positively and significantly influenced on student performance. The selected four factors have significantly explained 58 % variance of student performance in science.
Effect of pH on Cu-S TiO2 Photocatalytic Performance toward Phenol Photodegradation and Cr(VI) Photoreductionby Visible Light Irradiation

Research on the effect of pH on Cu-S TiO2 photocatalytic activity in degradation of phenol and Cr(VI) reduction has been done. The treatment was performed by irradiating sample by visible light. The photocatalyst used was Cu-S TiO2 nanocrystalline of8.77 nm with band gap of 1.9 eV. The process was conducted in a close reactor equipped with 4 tungsten lamps of 15 W, with pH variation and for 6 hours. The sample contains 50 mL phenol solution and 50 mL Cr(VI) of 50 ppm. Result shows that phenol photodegradation and Cr (VI) photoreduction increase as pH increment from 2-4, followed by a decreasing trend to pH 12. Existence of the two analytes in one chamber make the photodegradation and photoreduction process occur synergetic.
An evidence-based framework for economic evaluation of outpatient electronic drug prescribing An eHealth technology assessment tool

Context: Health care decision makers have a limited supply of resources for an unlimited pool of eHealth technologies. With the sustainability and solidarity of NHS based health systems increasingly under pressure, it is desirable that decision processes be both transparent and evidence-based. Despite the promise in solving problems with quality, safety, and efficiency in health care, eHealth systems are rarely assessed for their impacts and benefits. Objectives: Review of available literature on electronic drug prescribing (ePrescribing) and proposal of an evidence-based framework for economic evaluation of outpatient ePrescribing systems. Methods: Literature review on costs, benefits, and evaluation of ePrescribing. Assessment of studies based on principles of economic evaluation. Development of a framework based on critical appraisal of the literature. Results: Application of economic evaluation principles to the assessment of ePrescribing systems is very limited. Still, the evidence indicates that benefits outweigh costs of ePrescribing, and that the technology has great potential. Concerning existing frameworks for evaluation of eHealth, we found they are too generic, do not promote straightforward application to the evaluation of ePrescribing, and do not adequately structure the evaluation problem. We thus propose a framework for specific economic evaluation of ePrescribing, and provide a descriptive application of the model to the Portuguese health system. Conclusions: The lack of systematic methods results in scattered evidence and multiple terminologies. The incorporation of a problem structuring step and available evidence on costs and benefits into the proposed framework might be of value; further research is needed to confirm this. Future studies on economic evaluation of eHealth technologies and systems are desirable.
PREDICTORS OF FUNCTIONAL OUTCOMES IN TRAUMATIC BRAIN INJURY AT 4 MONTHS POST INJURY IN SOUTH INDIAN POPULATION

Background: Goals of Rehabilitation after Traumatic Brain Injury (TBI) focus on preventing complications and improving the level of functional independence. The expectation of TBI survivors and family members following rehabilitation are focused on the quality of outcomes such as reintegration into the community, return to work, and maximal functional capacity. Multiple factors may affect recovery after TBI when interacting with the primary condition and predicting the degree of recovery helps in framing realistic goals. The purpose of this study was to analyze the factors influencing the functional outcome in TBI patients at four months post-injury. Methodology: This observational study was carried out in the Neurosurgery outpatient department when TBI patients returned for review at four months post-injury. 50 TBI patients who were able to follow commands participated in this study. Factors like Admission Glasgow coma scale (GCS), Discharge GCS, Length of Hospitalization, Associated fractures of the upper and lower limb, Co-morbid conditions like Diabetes and Hypertension were obtained from the discharge summary of the patient. Caregiver literacy was obtained from the person who took care of the patient completely. Admission CT scan was graded using the Marshall CT classification. Finally, all these factors were compared to the functional status of the patient evaluated using the Barthel Index. Results: Logistic regression was used to predict the factors affecting the functional outcome. Beta value of Caregiver literacy, Discharge GCS, and Co-morbid conditions was . 561, . 369 and . 234, respectively which influences the functional outcome of TBI patients at four months post-injury. Conclusion: The study concludes that caregiver literacy, Discharge GCS, and Co-morbid conditions influence the functional outcome of TBI patients, which emphasizes the need for awareness and education of the caregiver and along with post-discharge rehabilitation program specific exercises addressing the co-morbid conditions would enhance the recovery.
Learning to Generate Multi-Hop Knowledge Paths for Commonsense Question Answering

Commonsense question answering (QA) requires a model of general background knowledge about how the world operates and how people interact with each other before reasoning. Prior works focus primarily on manually curated commonsense knowledge graphs, but these knowledge graphs are incomplete and thus may not contain the necessary knowledge for answering the questions. In this paper, we propose to learn a multi-hop knowledge path generator to generate structured evidence dynamically according to the questions. Our generator uses a pre-trained language model as the backbone, leveraging a large amount of unstructured knowledge stored in the language model to supplement the incompleteness of the knowledge base. The experiments on two commonsense QA datasets demonstrate the eﬀectiveness of our method, which improves over strong baselines and also provides human interpretable explanations for the predictions
Current and future patterns of forest fire occurrence in China

Forest fire patterns are likely to be altered by climate change. We used boosted regression trees modelling and the MODIS Global Fire Atlas dataset (2003–15) to characterise relative influences of nine natural and human variables on fire patterns across five forest zones in China. The same modelling approach was used to project fire patterns for 2041–60 and 2061–80 based on two general circulation models for two representative concentration pathways scenarios. The results showed that, for the baseline period (2003–15) and across the five forest zones, climate variables explained 37.4–43.5% of the variability in fire occurrence and human activities were responsible for explaining an additional 27.0–36.5% of variability. The fire frequency was highest in the subtropical evergreen broadleaf forests zone in southern China, and lowest in the warm temperate deciduous broadleaved mixed-forests zone in northern China. Projection results showed an increasing trend in fire occurrence probability ranging from 43.3 to 99.9% and 41.4 to 99.3% across forest zones under the two climate models and two representative concentration pathways scenarios relative to the current climate (2003–15). Increased fire occurrence is projected to shift from southern to central-northern China for both 2041–60 and 2061–80.
Study of a Human-Robot Interactive System for Operations at Sea

This paper presents an architecture for the positioning and estimation systems required to position and guide a human diver along a desired path underwater. The overall system incorporates devices carried by the diver and a group of autonomous marine robotic vehicles located at the sea surface. To accomplish the system’s goal, it is necessary to determine the diver’s position and provide in real time the directions that the diver should follow. To achieve this, the diver’s estimated position is calculated based on the transmission time elapsed during the message exchange between the vehicles and the diver. Trilateration and Kalman Filter techniques are used to estimate the diver’s position. Furthermore, the location algorithms are prepared to handle some message losses to make the system robust to communication failures and delays. A simulator was created using Matlab and Simulink to evaluate the cooperative vehicle navigation and motion control algorithms on several realistic scenarios.