Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of a bi-directional DC-DC converter topology for low power application

This paper describes a bidirectional DC-DC converter for use in low power applications. The converter is based on a half-bridge in the primary side and on a current fed push-pull in the secondary of a high frequency isolation transformer. In the presence of the DC mains (provided by the AC mains), the converter essentially operates in the buck mode charging the battery. On failure of DC mains the converter operates in the boost mode and thereby the battery supplies the load power. The simple, low part count, galvanically isolated proposed topology provides an attractive solution for use in battery charge/discharge circuits in a DC UPS. Small signal and steady state analysis of both modes of converter operation is shown. Design guidelines are also presented. The concept is evaluated by an experimental setup and key results are presented.
A Survey - Web Information Extraction and Annotation

The tremendous growth in the volume of data and with the terrific growth of number of web pages provides user an easy way to access the information and services. Since all the databases have become web accessible through Html form-based search interfaces. Such data is huge and for applications such as online shopping comparison, article collection etc and the data units returned from the databases are usually encoded into the result pages dynamically for human browsing and cannot be processed by machines. For the encoded data units to be machine processable they need to be extracted out and assigned meaningful labels. Annotation of such collected information leads to several advantages including fast decision making, relevant information visiting, to reduce the time of futile searches, historical data management and elimination of older searches. This paper is intended to provide an alignment of the entire data unit on the search result record and organize them into different group such that the data in the same group have same semantic and we use multiple annotators to produce label for the data units and aggregate the different annotations to determine the most appropriate label for each group. Next an annotation wrapper is constructed to efficiently annotate new result pages from the same web database Keywords— Data alignment, Web database, data annotation, Wrapper generation, Data Extraction
Classification Model for Intent Mining in Personal Website Based on Support Vector Machine

With the rapid growth of personal website influence, the advertisement placing has become an important investment in personal websites. But in order to accurate the advertisement placing, the specific quest for the specific users with their specific interesting need to be concerned. Acquiring, preprocessing and classifying consumption intention of the released information that published in the personal websites is the main task of this essay. We regard consumption intention mining as a binary classification problem, and extract multi-dimensional features from the raw corpus. Finally, we propose models based on SVM, Naive Bayes and deep learning to solve the consumption intention classification problem. The experimental result shows that the deep learning based method achieves the highest F-measure.
Conflict Resolution Algorithms for Super Density Operations Impacted by Off-Nominal Events

In this paper we present an approach for resolving conflicts in Super Density Operations (SDO) impacted by off-nominal events. We describe a dynamic routing algorithm in conjunction with a dynamic stochastic route blockage model to predict and efficiently resolve trajectory conflicts in SDO airspace. The proposed algorithms define new flight trajectories that avoid conflicts with off nominal events caused by irregular aircraft behavior or unexpected weather conditions. The paper describes a mathematical model and a set of algorithms implemented in a prototype simulation system. This prototype was used to conduct a series of simulation studies whose results are described and analyzed.
Students’ Understanding of Institutional Practices: The Missing Dimension in Human Rights Education

This study used task-based group interviews with young adolescents in four countries to investigate their understanding of the causes of human rights violations, means for protecting human rights, and their own potential role in ensuring human rights. Although students recognized the role of personal and institutional factors in both violating and protecting human rights, their ideas for influencing human rights focused primarily on the personal contexts with which they were most familiar. Their understanding of political and economic mechanisms was much less elaborate. These findings suggest the need for curricula that equip students with the complex and specialized knowledge that would enable them to engage in a range of meaningful civic action, both in their lives now and as adults.
Software Development Processes

It is possible to make software by jumping directly on a computer and start hacking away at it. A lot of great software has been written this way. Unless we are software geniouses, however, it pays off to use a more cautious approach. One of Software Engineering’s primary concerns is to establish methods and processes that should be followed in order to develop quality products in the best possible way in a given setting. A prescribed way to do something is called a method. A method that is enacted in a business or organisational setting is a process. Research on methods is called methodology. A lot of people use the words “method” and “methodology” interchangeably, but it makes no harm to be somewhat more precise—besides, the word “method” is shorter, and a lot of ink would have been saved had it been correctly employed where “methodology” is carelessly thrown in. From around the 1970s, Software Engineering has had more than its fair share of methods; methodology was thriving. In technical bookstores the shelves are chock-a-block with books on how to develop supposedly great software the right way. As fashions come and go, that means that some approach and a group of associated methods is fashionable for around seven years. Then a new approach arrives that exposes such deficiencies in the until then fashionable approach that people start wondering how they could have been blind all along. The new approach gains adherents. In about five years, it has entered the mainstream, even being taught in universities. The cycle has been compared to what happens in science. When reading a textbook, one gets the impression that science has been advancing in an orderly pace. That is nonsense. Science advances by leaps and bounds. For some amount of time most scientists work within a given conceptual framework, a socalled paradigm. Then another paradigm appears that supplants the previous one in a process called scientific revolution. In the beginning of the renaissance, this is what happened in astronomy when the Ptolemaic system, with earth at its centre, was supplanted by another world view developed by Copernicus and Galileo. It is usually thought that a paradigm supersedes another paradigm simply because it is better. That is also nonsense. In the beginning, the new paradigm is not better than the old one; it is untested and imprecise, while the old paradigm
XML Keyword Search Algorithm Based on Level-Traverse Encoding

For XML documents, existing keyword retrieval methods encode each node with Dewey encoding, comparing Dewey encodings part by part is necessary in LCA computation. When the depth of XML is large, lots of LCA computations will affect the performance of keyword search. In this paper we propose a novel labeling method called Level-TRaverse (LTR) encoding, combine with the definition of the result set based on Exclusive Lowest Common Ancestor (ELCA),design a query Bottom-Up Level Algorithm(BULA). The experiments demonstrate this method improves the efficiency and the veracity of XML keyword retrieval.
A Novel Last-level Cache Replacement Policy to Improve the Performance of Mobile Systems

Baseline replacement policy which has proven itself over and over again is LRU policy. This algorithm seeks to replace the lines that were used least recently and it performs well by exploiting temporal locality. This work presents a strategy based on access distribution pattern among the lines in the set during the period of two consecutive LRU replacements to help the standard LRU algorithm in deciding the victim blocks more optimally. Our strategy im- proves the second-level cache miss rates over the pure LRU algorithm by 15% on average, leading to the performance improvement by 4.71%.
What can Training Researchers Gain from Examination of Methods for Active-Learning (PBL, TBL, and SBL)

In this paper we examine three “active-learning” methods that have evolved out of learning research in a variety of disciplines - problem-based learning, team-based learning, and studio-based learning. Our goal is to review and contrast these methods to identify their unique and similar features. We additionally outline which of their features holds potential for improving learning in collaborative contexts. We consider their common instructional features and learning principles, to determine which are potentially indicative of effective active learning.
Photocathode Preparation and Characteristics of the Electron Source for the VELA/CLARA Facility

The VELA and CLARA accelerators at Daresbury are test facilities with a focus on FEL research and industrial applications of electron beams. Recently the CLARA front-end has been commissioned with acceleration of beam to 50 MeV. A normal conducting 2.5 cell S-band RF photoelectron source operated at up to 70 MV/m has been used as the injector for both VELA and CLARA front-end. Several different copper cathodes have been used throughout its operational life, employing different preparation techniques. Oxygen plasma treatment is a well-known procedure for removing hydrocarbon contamination from surfaces whereas Argon plasma treatment also removes contaminants and typically leaves a thinner oxide at the surface. In this work we compare photoemitted and dark current, as measured directly after the gun, for these alternate surface preparations and also present results from post-use optical and electron microscopic analysis of the photocathodes. Electromagnetic simulations are used to help explain the results.
A Redundancy-Based Approach to Obstacle Avoidance Applied to Mobile Robot Navigation

In this paper, we propose a framework for visual navigation with simultaneous obstacle avoidance. The obstacles are modeled by using a vortex potential field, derived from an occupancy grid. Kinematic redundancy guarantees that obstacle avoidance and navigation are achieved concurrently, and the whole scheme is merely sensor-based. The problem is solved both in an obstacle-free and in a dangerous context, and the control law is smoothened in the intermediate situations. In a series of simulations, we show that with our framework, a robot can replay a taught visual path while avoiding collisions, even in the presence of visual occlusions.
Cross-Cultural Comparison of the Relationship Between Emotion Regulation Strategies and Perceived Stress in Irish College Students and Chinese International College Students

Previous studies have shown that there is an association between the use of emotion regulation strategies and mental health. However, less is known about the association between emotion regulation strategies and perceived stress in college students, and less is known about whether cultural differences influence this association. The current study examined if differences exist in the habitual use of emotion regulation strategies between Irish college students (n=74) and Chinese international college students (n=96) studying in Ireland, and investigated the relationship between emotion regulation strategies and perceived stress in these two student populations. Chinese students reported more frequent use of both cognitive reappraisal and expressive suppression compared with Irish students. There was a statistically significant negative association between the habitual use of cognitive reappraisal and levels of stress in both Irish and Chinese students. In addition, there was a statistically significant moderator effect of culture on the association between expressive suppression and perceived stress. There was a significant positive relationship between the habitual use of expressive suppression and levels of stress in Irish college students, whereas this relationship was absent in Chinese students. The findings highlight the effects of emotion regulation on levels of stress and the importance of cultural context when investigating the association between emotion regulation strategies and perceived stress.
Operational Hydrological Modelling of Small Watershed using QPE from Dual-Pol Radar in Brazil

Among other applications, radar-rainfall (RR) and QPE (Quantitative Precipitation Estimation) based on radar reflectivity, dual polarization variables, and multi-sensor information, provide important information for land surface hydrology, such as flood forecasting. Therefore, we developed a flood alert system using rainfall-runoff model forced with RR and QPE, and tipping-bucket observations to forecast river water levels (using rating-curves). In this study, we used an hourly dataset from an S-Band dual-polarimetric radar with two tropical R(Z) relations based distrometer data, a polarimetric R(Z,ZDR) algorithm from the literature and a multi-sensor approach using radar, satellite and rain gauge. Two hydrological models were used and calibrated using observed discharge time-series. Although our previous studies indicated accurate RR-based simulations, in some cases floods were not detected when using catchment-lumped rainfall derived from multi-sensor QPE. In this study, we advance further in this subject using improved R(Z,ZDR) relations and QPE for the period of 2016-2017 and flood event-based rainfall-runoff calibration. Thus, we focused on the development (and timing) of floods in the Marrecas River can be complex and strongly related to storms spatiotemporal distribution. To explore this aspect, we also perform a first analysis in using RR in rainfall-runoff model with a nested catchment discretization.
Section Code Task Model for Heterogenous Processor In Real Time System

Even thou there are many schedulers available, almost every scheduler are not giving the maximum performance when used in real time system when there is an overload. To overcome this, an innovative approach has been used in this paper which gives the maxim um utility when compared to the other related schedulers available. The program is split and grouped together in the initial stage, and a section code is tested for the entire cluster of code and using the feedback loop the miss ratio is identified. The ma jor work of the paper is selecting the desired algorithm and fixing to the desired core in the heterogeneous multicore processor. So if a deadline is not met by any one of the core, then the scheduler submits it to the next core of high or low end speed using the feedback control framework This gives a wider spectrum when double check is done for each code before it is used in the real time system avoiding the miss ratio and obtaining the maximum utility. The paper uses operating system scheduler algorithm over the control system methodology for its design and scheduling.
A Syntactic Word Prediction System for Disabled People

People who have lost the use of their voice through disease or accident often require a prosthesis to help them carry out conversations with those around them. Unfortunately, the drawback of such systems is that they are prohibitively slow and the user can often find themselves getting left behind in a conversation. Prediction systems which attempt to guess what the user will say next can help improve this speed, but these also suffer disadvantages. Inaccurate modelling can result in the prediction of unusable words unnecessarily increasing cognitive load on the user. A system is required which will only produce syntactically correct predictions. Windmill is a MS-Windows system which aims to fulfil this requirement using an augmented phrase structure grammar to parse semi-complete sentences. The system is designed as an expert system with a rule base providing possible sentence-completion sequences from which parts of speech for the next word can be deduced. A type-tagged lexicon is then consulted to obtain words which fit these types. A statistical method, based on frequency and recency of usage, is applied to this output to produce an ordered prediction list the top five words of which are offered to the user. Initial results from Windmill indicate a potential of up to 63\% keystroke saving using a simulation test platform. This shows that syntactic processing is a viable option in efforts to improve the communication rate of non-vocal people.
Fractal connection structure: effect on generalization in supervised feed-forward networks

Fractal connection structure within the layers of a multilayered feedforward net has been studied in this paper. Fractal connection structure ensures modularity, easy hardware implementation and resembles biological neural system more closely than fully connected layered architecture. Simulation on sonar signal for underwater target classification problem shows that fractal net with fractal dimension around . 9 with average connectivity 80% performs better than the fully connected net of same size (same number of neurons) in terms of classification accuracy and generalization behaviour to unseen samples.
Verbal Phrase Translation

A meaning preserving translation usually involves long distance relationships between words. The CPA approach builds patterns centred on verbs, which capture the normal usage. Aligning the patterns between a source and a target language allows a meaning maintaining translation of the verbal phrases. In this paper we present a pilot study of translation from English to Italian using CPA patterns. The results obtained show that the results are judged much more positively than the baseline translation offered by the Google translator.
Tillage Operational Analysis Based on Soil Moisture Content, Machine Speed, and Disc Space of Compact Disc Harrow

Tillage is an integral part of agricultural production and has been a prominent aspect of technological development in the evolution of agriculture. Gill and Vandenberg (1968) defined tillage as a process aimed at creating a desired final soil condition for seeds from some undesirable initial soil condition through the manipulation of agricultural soil. According to Abdalla (2014), soil tillage consists of breaking the compact surface of the earth to a certain depth and loosening the soil mass to obtain a good soil condition for plant growth. To ensure normal plant growth, the soil must be prepared in such conditions that plant roots have enough air, water, and nutrients (Gill and McCreery, 1960; Gill and Vandenberg, 1968; McKyes, 1985; Boydas and Turgut, 2007). Ati et al. (2015) explained that well-aggregated soil provides better moisture retention, adequate aeration, and easy penetration for plant roots. Tillage plays an important role in controlling weeds and managing crop residue through the turning or inversion of the soil (Raney and Zingg, 1957). Numerous factors affect tillage operations. According to Naderloo et al. (2009), the tillage depth, working tool Tillage Operational Analysis Based on Soil Moisture Content, Machine Speed, and Disc Space of Compact Disc Harrow
Improving pose estimation by building dedicated datasets and using orientation

Markerless pose estimation systems are useful for various applications including humancomputer interaction, activity recognition, security, gait analysis, and computer-assisted medical interventions. They have attracted much interest since the release of low-cost depth cameras such as Microsoft’s Kinect camera. Shotton et al. and Girshick et al. pioneered tractable methods that infer a full-body pose reconstruction in real-time. Details of these methods are given in [1]. Despite this technological breakthrough, the accuracy of human pose estimation from single depth images remains insufficient for some applications. Our work aims at building a simulation environment to create images databases suited for any camera position and improving the mainstream machine learning-based pose estimation algorithms. Database
A Component-Based Reconfigurable Sensor Network Monitor for Adapting Time-Critical Requirements

Sensor data can be useful in various applications, but it is also critical in some areas, such as health, safety and finance. In particular, in a time critical environment, temporal correlation of streaming sensor data should be monitored. A run-time monitor is embedded in the server for such applications, in order to detect erroneous conditions, and perform appropriate reactions in a timely manner. However, modification of the monitor may require stop and restart of the server, in order to take effect. This kind of option is not permissible where the server should be performing continuously. In this paper, we propose a component based reconfigurable sensor network monitor designed for handling time critical requirements. In order to allow dynamic modification, we implement both the server and the monitor on the Fractal Component model, which enables us to reconfigure the system architecture in run-time. For detecting violation of the timing condition, we specify timing constraints, and design the monitor on Fractal Aspect Component. The architecture can be formally verified by Fractal-ADL and Alloy. We demonstrate the feasibility of the proposed framework, by developing a smart cruise control system. We aim to provide guidance to construct a monitoring system in a dynamic and time critical environment.
Governing nature-based tourism mobility in National Park Torres del Paine, Chilean Southern Patagonia

ABSTRACT Nature-based tourism is a mobile activity shaped by the capacity of tourists for displacement and the socio-material infrastructure allowing flows. However, the literature has scarcely addressed aspects of mobility in governing nature-based tourism. Taking the case of the National Park Torres del Paine we explore three aspects of mobility in nature-based tourism using the concepts of routes, frictions, and rhythms. Our findings show that the movement of tourists challenges spatially bounded forms of governance. Instead, we argue, new mobility-sensitive forms of nature-based tourism governance are needed that can complement the use of fixed-boundary conservation enclosures.
THE ROLE OF TEACHER IMMEDIACY AS A MOTIVATIONAL FACTOR IN STUDENT LEARNING

This research uses the structural equation modeling (SEM) analysis to find the correlation between the variables of Teaching effectiveness, Teacher behavior and affective learning and that of Student motivation in learning, Teacher immediacy and learning outcomes and Student learning outcomes. A model is built so that to confirm that teachers produce the intermediate influence and also motivate the learning outcomes, cognitive ones especially. Data obtained here in the course of survey proves to be consistent with our initial model. The results show that the immediate teachers’ function is to be the means of increasing students’ motivation to learn, and that such motivation, in its turn, increases students’ cognitive abilities.