Miracle-dz/UniFAR-FTUs huggingface dataset:
Die Romanistische Abteilung der Savigny-Zeitschrift im Nationalsozialismus

The Savigny Journal’s Romanist section during the age of National Socialism As it was the proclaimed aim of the NSDAP to purge the German legal system of its ‘materialistic’ Roman heritage, Romanists were faced with adverse ideological circumstances In a process called ‘Gleichschaltung’, which aimed to bring all sectors of German society into line with National Socialist principles, publishing behaviour and scientific discourse about Roman law experienced significant changes A series of the discipline’s most prominent exponents, among them two editors and many contributors of the Savigny Journal, were forced to withdraw from the public academic scene and ultimately emigrate on account of their Jewish ancestry Those who took their place and those who had retained their positions found different means and modes of adaptating to the prevalent zeitgeist
Soft-sensing Method Based on Lazy Learning Algorithm

In view of lots of unmeasured variables in industrial process,a soft sensing method using lazy learning is presented.The k-vector nearest neighbor is used to generate a neighbor of current regime in order to enhance the predictive capability of the original algorithm.The complexity of the algorithm is decreased by recursive least squares and the optimal solution is addressed by PRESS.Using this method to model ester rate of a local chemical plant,this paper obtains the maximum inaccuracy of 0.874 2%. The simulation results show that the perfect generalization performance can meet highprecision measuring requirements and the method is very understandable and easy to be implemented.
1-D integral image for enhancing efficiency and effectiveness of probabilistic occupancy map-based people localization approach

The popularity of vision-based surveillance systems arouses much research attention in improving the accuracy and efficiency of people localization. Using probabilistic occupancy map (POM) becomes one of the mainstream approaches to people localization due to its great localization accuracy under severe occlusions and lighting changes. However, to enable the usage of rectangular human models and the subsequent 2-D integral image computation, it is assumed that videos are taken at head or eye level. Even so, the computation complexity is still high. Moreover, surveillance videos are often taken from security cameras located at a higher-up location with an oblique viewing angle, so that human models may be quadrilateral and the pixel-based 2-D integral image cannot be utilized. Accordingly, we propose the use of 1-D integral images which are produced for foreground object(s) in an image along equally-spaced line samples originated from the vanishing point of vertical lines (VPVL). Experimental results show that the proposed approach does improve the efficiency and effectiveness of the POM approach in more general camera configurations.
EETA: An Energy Efficient Transmission Alignment for Wireless Sensor Network Applications

Energy conserving MAC protocols performing adaptive duty-cycling mechanism have been widely studied to improve the energy efficiency in Wireless Sensor Networks (WSNs). In particular, several asynchronous Low Power Listening (LPL) MAC protocols such as B-MAC, X-MAC and ContikiMAC transmit a long preamble or consecutive data packets for an efficient rendezvous between senders and receivers. However, the rendezvous results in the challenging problem of unnecessary channel utilization since the senders occupy a large portion of the medium. Furthermore, when a traffic generation time overlaps with other neighbouring nodes, they frequently encounter spatially-correlated contention incurring excessive channel contention. In this paper, we propose a novel traffic distribution scheme called an Energy Efficient Transmission Alignment (EETA), that shifts a traffic generation time of the application layer. By using a MAC layer feedback including contention information, the cross-layer framework determines whether the node delays its transmission or not. EETA is robust from the heavy contending environment due to its traffic distribution feature. We evaluate the performance of EETA through diverse experiments on the TelosB platform. The results show that EETA improves the overall energy efficiency by up to 35%, and reduces the latency by up to 48% compared to the existing scheme.
A Kind of Web Spreadsheets Based on POI

With the development of Internet,Web application has been more popular and complicated.Dynamic Web spreadsheets is a typical case.With the development of developing technology,some open source projects become more infective for open and free,and are implemented in many projects.This paper introduces a kind of open source implementing dynamic spreadsheets on Web based on POI engine,describes the display theory of POI.This paper gives a typical application,analyses with an example in a practical project and finds a way to develop dynamic spreadsheets.
Underspecified discourse representation

This paper proposes an approach to discourse structure that builds on syntactic structure to derive that part of discourse structure that can be captured without taking recourse to deep semantic or conceptual knowledge. This contribution is typically only partial; we intend to capture this partiality in terms of underspecified constraints that describe (but do not enumerate) the structures a given discourse might have. This allows a rather straightforward interface from syntax to discourse and yields a clean interface to modules of discourse resolution.
The Large Group: Dynamics and Therapy

Thank you for reading the large group dynamics and therapy. Maybe you have knowledge that, people have search hundreds times for their chosen books like this the large group dynamics and therapy, but end up in malicious downloads. Rather than enjoying a good book with a cup of coffee in the afternoon, instead they juggled with some malicious bugs inside their laptop. the large group dynamics and therapy is available in our book collection an online access to it is set as public so you can download it instantly. Our books collection spans in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Kindly say, the the large group dynamics and therapy is universally compatible with any devices to read.
Reducing late-timing failure at scale:straggler root-cause analysis in cloud datacenters

Task stragglers hinder effective parallel job execution in Cloud datacenters, resulting in late-timing failures due to the violation of specified timing constraints. Straggler-tolerant methods such as speculative execution provide limited effectiveness due to (i) lack of precise straggler root-cause knowledge and (ii) straggler identification occurring too late within a job lifecycle. This paper proposes a method to ascertain underlying straggler root-causes by analyzing key parameters within large-scale distributed systems, and to determine the correlation between straggler occurrence and factors including resource contention, task concurrency, and server failures. Our preliminary study of a production Cloud datacenter indicates that the dominate straggler root-cause is resultant of high temporal resource contention. The result can assist in enhancing straggler prediction and mitigation for tolerating late-timing failures within large-scale distributed systems.
A Scribble-Based Interface for Mesh Segmentation

This paper presents a method for three-dimensional mesh surface models segmentation that combines interactive part selection with region growth. First, some mesh vertices are selected as object and background seeds using scribble-based selection methods, and the others are unknown region. Then, the mesh model can be automatically cut into two parts using region growth. The result is directly affected by the vertices on the part boundaries. As a result, the improved-methods set the vertices that are both adjacent to object and background as special vertices, and use cutting results as object and background seeds to do the region growth again. The experiments show that the result is more accurate because most vertices of the object and background are selected as seeds. Key words—mesh segmentation; scribble-based; boundaries; the region growth
Love hurts : explorations of love, validation, and conflict

This paper considers how love may be conceptualiseda personal construct theory perspective, part icularly in relation to experiences of validation and invalidation. This model is applied to writings abo ut love, and the findings of a repertory grid and interview exploration of love, indicating differences in stud ents’ construing of romantically and platonically loved figu res and relationships between grid scores and a mea sure of love styles, are presented. Illustrations are provi ded from the clinical setting indicating how client s’ relationship problems may be explained in terms of their co nstructions concerning love.
Listening practice through a virtual platform in an EFL Class

The English language learning field nowadays finds itself growing with the emerging new technologies, however it is such a wide field that small parts of it need more attention depending on who is learning the language and its context. To make a contribution to this field this research found some aspects to reinforce in children who are learning English as a foreign language, they presented a need to rehearse their listening skill making their learning more difficult to carry on. As a way to solve the situation this research decided to implement a technological strategy to get seventh-graders to rehearse their listening skills and subs kills looking for the contributions of a virtual learning platform to the listening rehearsal. Therefore, this research followed a qualitative, action-research line. The participants of the research were 39 seventh graders of a private institution in Soacha, Cundinamarca (Colombia) and the pedagogical intervention was held during some of their English classes. To develop the research there were used the computers of the informatics room of the institution to work with a serial of 6 activities uploaded in the virtual learning platform “QUIA”. These activities were designed thinking of the English level of the students as well as the topics they were familiarized to and tasks as a methodology to use them with the technological tool. Within this activities besides of the task cycle (pre-while-post) the second main point was the content of audio material graded specifically to suit the population. After the pedagogical intervention, through interviews, questionnaires and student’s results gathered in QUIA, it was found that students improved their listening in terms of vocabulary, pronunciation and even activation of prior knowledge to learn, besides of finding the tool engaging and as a different way to get more curious about the knowledge they are learning. Listening practice through a virtual platform in an EFL Class 4 Hence, it was determined that a virtual learning platform does contribute to the listening skill of high school students by making use of task based learning as teaching method, also it was found that learning languages through technological devices are a way to save time when grading with virtual learning platforms and a way to engage students in learning languages actively. As A further research it is proposed to make a research about the role of feedback and how to give it properly to students after rehearsing their listening in the platform.
Competing Target Hypotheses in the Falko Corpus: A Flexible Multi-Layer Corpus Architecture

Error annotation is a key feature of modern learner corpora. Error identification is always based on some kind of reconstructed learner utterance (target hypothesis). Since a single target hypothesis can only cover a certain amount of linguistic information while ignoring other aspects, the need for multiple target hypotheses becomes apparent. Using the German learner corpus Falko as an example we therefore argue for a flexible multi-layer standoff corpus architecture where competing target hypotheses can be coded simultaneously. Surface differences between the learner text and the target hypotheses can then be exploited for automatic error annotation.
Blind and reference channel-based time interleaved ADC calibration schemes: a comparison

Many digital background calibration techniques exist which correct for offset, gain, timing and bandwidth mismatches in time-interleaved (TI) ADCs. Some require an additional reference channel, whereas others are blind and rely on the presence of a band where no signal is present (usually around the Nyquist frequency) or exploit other properties of the input signal. Blind calibration techniques, which don’t use a reference channel, are suitable for correction of commercial TI-ADCs, or TI-ADC systems using commercial ADCs as channels. Techniques employing additional channels require a more complex layout (especially for the clock tree) and need an additional ADC, whose overhead cost is significant, especially for 2- or 4- channel TI-ADCs. However, we show that the estimation process is faster and more accurate when a reference channel is present, and many different error models can be used (exploiting different points in the accuracy / complexity trade-off).
Research on mass dynamic customization system

Supply chain system of mass customization has limitations,such as small optional scope of customized user and long delivery time and so on.Based on this,this paper puts forward mass dynamic customization system,then analyzes the process of mass dynamic customization,finally,builds prototype of mass dynamic system and analyzes function and feature of different subsystem.At the same time the paper analyzes the algorithm of supply chain based on dynamic CODP.Finally,through a toy factory to illustrate the effectiveness and practicality of mass dynamic customization system.
Mappability estimate: a measure of the goodness of a processor-algorithm pair

A quick way of measuring the goodness of a processor-algorithm pair is presented. The main emphasis in this paper is in the reasoning of the mappability factors of a processor and an algorithm. Typical algorithm properties and how they affect the usability of the corresponding architecture characteristics are considered. The mappability estimation approach is demonstrated using MiBench benchmark algorithms and the Simplescalar processor simulator with ARM instruction set. The estimation results are consistent with the simulations and the estimates correctly predicted the most suitable architectures for three of the four algorithms.
Understanding Spatial Knowledge: An Ontology-Based Representation for Object Identification

<Summary> Spatial descriptions are one of the most effective methods to enable interlocutors to identify which object is being discussed in discourse. In this paper, we propose a framework that can identify an object whose positional relation with another object is indicated verbally by a human. To this end, we construct a spatial knowledge ontology. The ontology is enriched by Description Logic (DL) of concepts, which allows discovering hidden knowledge. We also propose a Spatial Object Dataset that is specifically tailored for our experiments with ontological structures. The dataset currently contains 130 objects and in total of 720 images for object recognition and 360 scenes for spatial recognition. Preliminary experimental results confirmed that the system was able to correctly recognizes human descriptions and identify unknown objects and that understanding human spatial descriptions is efficient for human-machine interaction.
DICTDIS: Dictionary Constrained Disambiguation for Improved NMT

Domain-specific neural machine translation (NMT) systems (\eg, in educational applications) are socially significant with the potential to help make information accessible to a diverse set of users in multilingual societies. It is desirable that such NMT systems be lexically constrained and draw from domain-specific dictionaries. Dictionaries could present multiple candidate translations for a source word/phrase due to the polysemous nature of words. The onus is then on the NMT model to choose the contextually most appropriate candidate. Prior work has largely ignored this problem and focused on the single candidate constraint setting wherein the target word or phrase is replaced by a single constraint. In this work we present \dictdis, a lexically constrained NMT system that disambiguates between multiple candidate translations derived from dictionaries. We achieve this by augmenting training data with multiple dictionary candidates to actively encourage disambiguation during training by implicitly aligning multiple candidate constraints. We demonstrate the utility of \dictdis\ via extensive experiments on English-Hindi and English-German sentences in a variety of domains including regulatory, finance, engineering. We also present comparisons on standard benchmark test datasets. In comparison with existing approaches for lexically constrained and unconstrained NMT, we demonstrate superior performance with respect to constraint copy and disambiguation related measures on all domains while also obtaining improved fluency of up to 2-3 BLEU points on some domains.
Vehicle Trajectory-Based Location Verification for VANETs

The correct location information of vehicles plays an important role in the maintenance of the normal operation of vehicle Ad-hoc networks(VANETs) and the position spoofing from malicious node will seriously affect many applications of VANETs.Therefore,the detection of the position spoofing by location verification is an important issue.The traditional location algorithm in WSN and MANET no longer applies to VANETs.In this paper,a vehicle trajectory-based location verification scheme is proposed to locate and track continuously the vehicle and draw the trajectory.The inosculation is calculated and the position spoofing is detected by comparing with the trajectory and speed of the neighbor vehicle.The simulation results show that false negative rate and false positive rate are low.When the cheating distance of malicious node is 30 m,false negative and false positive rate are close to 0.
Error analysis and estimation for the finite volume method with applications to fluid flows

The accuracy of numerical simulation algorithms is one of main concerns in modern Computational Fluid Dynamics. Development of new and more accurate mathematical models requires an insight into the problem of numerical errors. In order to construct an estimate of the solution error in Finite Volume calculations, it is first necessary to examine its sources. Discretisation errors can be divided into two groups: errors caused by the discretisation of the solution domain and equation discretisation errors. The first group includes insufficient mesh resolution, mesh skewness and non-orthogonality. In the case of the second order Finite Volume method, equation discretisation errors are represented through numerical diffusion. Numerical diffusion coefficients from the discretisation of the convection term and the temporal derivative are derived. In an attempt to reduce numerical diffusion from the convection term, a new stabilised and bounded second-order differencing scheme is proposed. Three new methods of error estimation are presented. The Direct Taylor Series Error estimate is based on the Taylor series truncation error analysis. It is set up to enable single-mesh single-run error estimation. The Moment Error estimate derives the solution error from the cell imbalance in higher moments of the solution. A suitable normalisation is used to estimate the error magnitude. The Residual Error estimate is based on the local inconsistency between face interpolation and volume integration. Extensions of the method to transient flows and the Local Residual Problem error estimate are also given. Finally, an automatic error-controlled adaptive mesh refinement algorithm is set up in order to automatically produce a solution of pre-determined accuracy. It uses mesh refinement and unrefinement to control the local error magnitude. The method is tested on several characteristic flow situations, ranging from incompressible to supersonic flows, for both steady-state and transient problems.
Computer Vision System for Defect Detection of Hot Rolling Products

— Detecting defect is the most required and important step in the production process. Computer aided defect detection can provide precise and fast solution. Detecting the defective products during production process is both cost-effective and prevents time-loss. In this study, a system is developed to detect defects during hot rolling operation using image processing methods.The rail and profile images are obtained by CMOS camera when they are rolled. By analyzing these images, different types of defects could be identifiedby using the different gray values for defective and non-defective regions. Defective areas cannot be seen clearly on the images with gray values. Therefore, image processing algorithms haveto be used on the obtained images. Defective regionscan be indicated by using colored segmentation. This study is applied in rolling mill of KarabukInc and is shown anfeature identification for rail and profile surface’s defects.
Problemas parabólicos no lineales provenientes de modelos financieros: existencia y aproximación numérica de las soluciones

En la presente tesis estudiamos dos problemas nolineales que se obtienen luego de realizar variaciones en la teoria estandar de valuacion de activos financieros. Especificamente, consideramos modelos que incluyan los costos de transaccion en su derivacion y presentamos las ecuaciones diferenciales en derivadas parciales correspondientes. Una vez determinadas las ecuaciones, estudiamos la existencia de solucion utilizando dos metodologias. En la Seccion 2 demostramos la existencia de por lo menos una solucion debil viscosa utilizando el metodo de Perron. En la Seccion 3, probamos la existencia de solucion usando el Teorema de punto fijo de Schauder. En una segunda instancia nos abocamos a desarrollar esquemas numericos para estudiar el comportamiento de las soluciones en diversos escenarios. Para ello, utilizamos el metodo de Alternating Direction Implicit (ADI) en la primera seccion y desarrollamos un esquema numerico con una cuadricula no uniforme en la segunda. Finalmente, estudiamos el comportamiento de las soluciones ante la presencia de diversos escenarios financieros y analizamos como las modificaciones hechas en la teoria afectan la valuacion final de un activo financiero.