Miracle-dz/UniFAR-FTUs huggingface dataset:
Ultrahigh-definition video system with 4000 scanning lines

An ultrahigh-definition video system is considered to be a prospective candidate for future broadcasting services providing a high sensation of reality. This paper will discuss the design considerations in the construction of an experimental ultrahigh-definition video system with 4000 scanning lines. The scanning parameters were determined based on the relationship between the sensation of reality and the viewing angle. The camera system was developed based on the four-CCD (charge-coupled device) image-acquisition technology: two 2.5-in. 8M-pixel CCDs are used for green, and one each for red and blue. The four-CCD beamsplitting system incorporates two-dimensional pixel offset to form a Bayer color-sampling pattern with the CCDs. A 4000-scanning-line display system was also developed. It is similar to the imaging system, which uses four 8M-pixel LCDs to realize a 4000-scanning-line system, one each for red and blue, and two for green with diagonal pixel offset. The viewing angle is more than 100° horizontally, at a standard viewing position of 3 m from a 320-in. (7 x 4 m) screen.
Keyword Extraction from Multiple Words for Report Recommendations in Media Wiki

This paper addresses the problem of multiple words search, with the goal of using these multiple word search to retrieve, relevant wiki page which will be recommended to end user. However, the existing system provides a link to wiki page for only a single keyword only which is available in Wikipedia. Therefore it is difficult to get the correct result when search input has multiple keywords or a sentence. We have introduced a ‘FastStringSearch’ technique which will provide option for efficient search with multiple key words and which will increase the flexibility for the end user to get his expected content easily.
From Homeschool to the Community College: A Multiple Case Study

The number of U.S. homeschooled students has steadily risen from the 1980’s to the present, and many eventually choose to attend community colleges (Cogan, 2010; Mason, 2004; Ray, 2004a; Sorey & Duggan, 2008a). Presently, limited research explores the homeschooled population’s transition to the first year of college experience. This is a comprehensive examination of community college homeschooled student transition. This study describes how three homeschooled community college students transitioned from their home environments to a mid-sized, Mid Atlantic community college setting using Tinto’s college adjustment framework of separation, transition, and incorporation in the analysis of their experiences(Tinto, 1993, 1997).
The Design of Electronic Scales Based on AT89C2051 Microcontroller

In recent years,the emergence of new single—chip computer and IC technology development,product design to update and develop the stock controller provides high performance conditions. In this paper,electronic scales system is designed based on pressure sensor,A/D converter,AT89C2051 microcontroller and LED display. It explained from hardware structure,connectivity and software parts of the circuit. This electronic system is called simple structure,low cost and high precision.
An Overview of Three-Dimensional Imaging Technology and Technical Characteristics of SAR

Conventional synthetic aperture radar (SAR) can realize two-dimensional imaging, but can not gain height information of the scene. SAR combined with other technologies can achieve three dimensional imaging of high resolution and becomes a hotspot gradually. Several types of three dimensional SAR including interferometric SAR (InSAR), bistatic/multistatic SAR, complex path SAR and array SAR are introduced. And the technical characteristics and corresponding problems about their development are analyzed, which can provide reference for the new three dimensional imaging technology of SAR.
Sistematización de competencias en la enseñanza de lengua B para Traducción e Interpretación en el EEES a partir de un modelo de competencia traductora

“Systematization of competences in the teaching of Language B in Translation and Interpreting Studies within the EHEA taking as a basis a translation competence model”. The objective of this article is to offer a model of competences for the teaching of the Language B in Translation and Interpreting degrees within the European Higher Education Area (EHEA). To date, foreign language subjects have not received due attention in the field of research and the guidelines offered thus far in official documents have been very vague and general, not taking account of the training and professional primera Recibido / Received: 15/03/2018 Aceptado / Accepted: 05/06/2018 Para enlazar con este artículo / To link to this article: http://dx.doi. org/10.6035/MonTI.2019. 11.3 Para citar este artículo / To cite this article: Cerezo Herrero, Enrique. (2019) “Sistematización de competencias en la enseñanza de lengua B para Traducción e Interpretación en el EEES a partir de un modelo de competencia traductora. ” In: Tolosa Igualada, Miguel & Álvaro Echeverri (eds.) 2019. Porque algo tiene que cambiar. La formación de traductores e intérpretes: Presente & futuro / Because something should change: Present & Future Training of Translators and Interpreters. MonTI 11, pp. 77-107. 78 Enrique Cerezo Herrero MonTI 11 (2019: 77-107). ISSN 1889-4178 needs of the students. With the aim of reverting this situation, it is necessary to establish a competence-based model in accordance with translation practice. For this purpose, in this work we will take as a reference the Translation Competence Model proposed by PACTE group. The systematization of competences proposed in this paper is expected to shed light on a fundamental sub-discipline in translation pedagogy and provide lecturers with a sound foundation regarding the nature of Language B subjects in Translation and Interpreting degrees. Palabras clave: traducción, lengua, competencia traductora, subcompetencias, formación
Experimental evaluation of massive MIMO at 20 GHz band in indoor environment

Massive multiple input multiple output (MIMO) improves transmission rate without increasing the complexity on signal processing by employing a large number of antennas at a base station. The effect of applying massive MIMO to small cells at the 2-GHz band has been reported. However, the primary targets of massive MIMO are small cells at a highfrequency band, because antenna size is considerably large when considering massive MIMO in a macro frequency band. In this study, measurements are performed for actual propagation channels using a wideband channel sounder with a horn antenna in the 20-GHz band in an actual indoor propagation environment. Moreover, the performance of interference rejection is evaluated using a virtual circular array antenna with 24 elements.
Comparative Study of Frequency Vs SpacialDomain for Multi Sensor Image Fusion

In the field of remote sensing, satellite imaging and medical imaging, images captured are often noisy, blurred and may exhibit in-sufficient resolution. Due to this instability, super imposing of Multi-sensor images has become imperative to obtain clear image, which is more appropriative for human visual perception. Image fusion has become a discipline, which demands more formal solution in different situations. Several situations in image processing require both high Spatial and high Spectral information in single image itself. This paper reviews the existing advanced pixel based Spatial domain image fusion techniques such as Average and Weighted Average method, Select Maximum, Brovey Transform, Intensity Hue Saturation(IHS), Principal Component Analysis (PCA) and Frequency domain image fusion techniques such as Fast Fourier Transform, Laplacian Pyramid, Local regression, Smoothing filter (SF), etc. Our paper is organized in the following way: Section-1: Gives introduction to image fusion. Section-2: Provides details of different fusion techniques used in both Spatial and Frequency domain. Section-3: Provides details of Measuring Techniques. Section-4: Provides comparisons of fusion methods in Spatial and Frequency domain. Finally, Section-5: Provides a Summary of the paper and its main conclusions.
SAT Based Attacks on SipHash

SAT Based Attacks on SipHash Santhosh Kantharaju Siddappa Supervising Professor: Prof. Alan Kaminsky SipHash is a proposed pseudorandom function (PRF) that is optimized for small message inputs. It is intended to be used as a message-authentication code (MAC). It uses a 128-bit secret key to compute the tag of a message. This project uses SAT based attacks on the primitive to perform partial key recovery and compares the effectiveness of these attacks against standard brute force approach that involves trying all possible combinations for the key bits. The primitive is converted into CNF and fed to an off-the-shelf SAT solver. The solver uses clause learning and if satisfiable, returns a set of values for the missing key bits. It also reports the number of conflicts that occurred before a solution was found. This is repeated several times for varying number of missing key bits and different versions of SipHash. It is then compared to the number of attempts to retrieve the missing key bits using brute force and the results are analyzed to check the effectiveness of SAT based attacks.
Radiometric normalization with multi-image pseudo-invariant features

Radiometric image normalization is one of the basic pre-processing methods used in satellite time series analysis. This paper presents a new multi-image approach able to estimate the parameters of relative radiometric normalization through a multiple and simultaneous regression with a dataset of a generic number of images. The method was developed to overcome the typical drawbacks of standard one-to-one techniques, where image pairs are independently processed. The proposed solution is based on multi-image pseudo-invariant features incorporated into a unique regression solved via Least Squares. Results for both simulated and real data are presented and discussed.
THE IMPLEMENTATION OF THE MIND MAPPING TECHNIC INTO THE PROCESS OF TEACHING CADETS ENGLISH FOR PROFESSIONAL PURPOSES

The article is devoted to the problem of the mind mapping technic implementation into the process of teaching English for specific purposes at the higher educational establishments of the Ministry of Internal Affairs of Ukraine. The definition of the main notion «a mind map» is accurately analysed. The main concept and its modifications are worked out. The peculiarities of the terms «a mind (a mental) map» and «a concept map» are defined. The benefits of including such a form of cognitive process which is characterized by another level of mental literacy and two-dimensional thought are worked out. The preferences of the mind mapping usage in the organization of the educational process including the peculiarities of the cadets’ daily routine and the specific characteristics of performing the service duties are shown. The advantages of this technic’s implementation including the successful combinations of individual and group work are encountered. The possibility of the interdisciplinary usage of the formed skills and abilities is used. The positive features of the method’s and its modifications usage while teaching the educational discipline «English for specific purposes» are underlined by the possibilities of their introducing practically in all kinds of the cadets’ activity (reading, speaking writing and listening). The motivational aspect of the auditory is also studied. The pattern of the mind map’s building in the process of the English language study is presented. It includes three main steps: brainstorm, an organization of information and completing the mind map. Detailed elements of the work on every level and links between all the items are introduced. The personal results of the authors’ implementation of the mind mapping technic on the initial level of the English language study by the cadets of the National Academy of Internal Affairs are introduced and worked out. The benefits of the mind mapping gradual implementation into the educational process at the higher educational establishment of the Ministry of Internal Affairs of Ukraine are grounded. The ways of conducting further research in this field and the most perspective directions of this study are proposed.
PPI Network Clustering Based on Artificial Bee Colony and Breadth First Traverse Algorithm

The clustering of protein-protein interaction ( PPI) network is one of the principal methods to reveal and research the protein function. The traditional clustering methods are inefficient for PPI network due to its special characters. Therefore,a clustering method is proposed based on the optimal search of artificial bee colony ( ABC) algorithm and the breadth first traverse ( BFT) clustering algorithm. To avoid noisy interference on experimental results,the distance-density algorithm is used to roughly determine the number of clustering in the preprocessing stage. Then,the initial clustering center is determined based on the comprehensive feature value of nodes in the network. The BFT algorithm is used in the clustering process and the improved ABC algorithm is employed to automatically search the optimal merging threshold. Finally,the performance of the proposed algorithm is estimated by precision and recall and some key parameters of the algorithm is analyzed. The experimental results show that the proposed algorithm improves the clustering effect of the PPI network efficiently.
Application of TrTCM Algorithm in the QoS Design of Underground Network Substation

The article analyzed the principle of TrTCM algorithm and the method of its software implementation in QoS design of substation. In addition, the calculating results based on actual data of the substation are also given. Analyzed results and practical application all indicate that TrTCM algorithm introduced optimizes the QoS of network.
Memory Overcommit… without the commitment

Valuable resources in physical servers are often underutilized and virtualization can be employed to consolidate multiple physical servers so that resources are more fully utilized. If a VMM creates the illusion that there are more instances (or bandwidth) of a resource than actually physically available, that resource is considered to be overcommitted (or oversubscribed). For example, if three uniprocessor servers are virtualized (as guests) and consolidated onto one dual-processor server, the CPU resource is considered overcommitted. If all three guests each need to run workloads that always require an entire CPU, these guests would be considered poor candidates for virtualization. But, virtualization works most of the time because most resources on many physical servers are badly underutilized.
Semantic annotation method for images by Web background knowledge

In the procedure of semantic annotation methods for images based on content, it is ordinary that identical or similar visual features may have different semantics. Aiming that problem, an image semantic relation model based on Web background knowledge is proposed. The Web page properties related with images are extracted and exploited to compute the semantic relation between images and annotating Keywords, and then the semantics of Web images to be annotated are determined. Experiment proves the efficiency of the method proposed.
GodisOmetre – providing feedback on student learning

In the Bologna process, the use of explicit learning goals and formative assessment are central elements in improving student learning. Ideally, formative assessment provides feedback to the student about how his present state relates to the learning goals and enables him to reflect on and regulate his learning. However, we found that it was easier said than done – not just to carry out, but in particular to make students realize the importance of learning goals and formative assessment for their learning process. The GodisOmetre is an attempt to motivate students to become self-regulated learners and to encourage and facilitate reflection. It is a way to make more explicit to students our detailed learning goals and reward also the “good processes” that lead to those goals and not just the “good results” in themselves. Processes and results are defined, as are their reward value and a public score chart is kept – and in the end the earned value is paid out. In this paper, we describe the GodisOmetre and the didactic ideas and philosophy behind it. We also discuss the lessons learned through two years of use and how it has been improved through trial-and-error and feedback from the students. (Less)
A Framework of Automatic Case Frame Construction From a Raw Corpus

In order to let computers understand text, identifying various types of relations in the text is a necessary step. In natural language processing (NLP), case frames are a very essential knowledge base which represents the relations between a predicate and its arguments. Case frames can support various types of NLP applications, such as parsing, machine translation, recognizing textual entailment and paraphrasing. For instance, in the classical example of parsing, “saw a girl with a telescope,” there is an ambiguity problem of which argument the prepositional phrase, “with a telescope,” is modifying. It would be easy to judge that the prepositional phrase belongs to the verb if knowledge of a case frame “see someone/something with telescope,” is available. For NLP applications in multiple languages and multilingual applications, compilation of large-scale case frames in these languages is important. Manually compiling this kind of knowledge in multiple languages would be too costly and would be limited by low coverage. In this paper, we propose a framework for automatically constructing case frames in multiple languages. In this framework, we extract reliable predicate-argument structures from large corpora by small sets of linguistic rules specific to each language, and apply clustering to produce case frames. Even though the grammars in different languages are quite dissimilar, we show that extracting predicate-argument structures to build case frames is achieved by one common way. In practice, we construct case frames of Chinese and English.
A New Method to Increase Training Speed in SVM

In binary classification,the training speed of SVM on large dataset is very slow.So the method of choosing some useful data can decrease the number of training data and accelerate the training speed. This paper proposes a new method using Mahalanobis distance and aσmethod to choose useful data. During the course of choosing data,we determine the position relation between the data and the dataset according to Mahalanobis distance between the data and the dataset.Then we can choose the data useful to construct the hyperplane.Our method avoids the shortcoming of strong randomicity in other methods before.We also take into account of the proportion of data chosen when choosing data.By adjusting the value of a,we can control the number of data chosen,in case of the dataset being too small or too large. So this method can accelerate the training speed greatly.
Improved Geometric Anisotropic Diffusion Filter for Radiography Image Enhancement

AbstractIn radiography imaging, contrast, sharpness and noise there are three fundamental factors that determine the image quality. Removing noise while preserving and sharpening image contours is a complicated task particularly for images with low contrast like radiography. This paper proposes a new anisotropic diffusion method for radiography image enhancement. The proposed method is based on the integration of geometric parameters derived from the local pixel intensity distribution in a nonlinear diffusion formulation that can concurrently perform the smoothing and the sharpening operations. The main novelty of the proposed anisotropic diffusion model is the ability to combine in one process noise reduction, edge preserving and sharpening. Experimental results using both synthetic and real welding radiography images prove the efficiency of the proposed method in comparison with other anisotropic diffusion methods.
The classical reception of the hybrid minotaur

This thesis offers an interpretation of the myth of Theseus and the Minotaur that accounts for its popularity in fifth century Athens. The myth of the Minotaur had particular political resonance in Classical Athens because of the Minotaur’s hybrid character and eastern connotations. In the wake of the Persian wars, Theseus came to embody Athenian democratic and anti-Barbarian ideals. His canonical opponent, the Minotaur, represented the enemy of the Athenian citizen: an eastern hybrid such as the Persian/Carian/Lycian groups of Anatolia and the east. By aligning the Minotaur with his Near Eastern origins, the story of Theseus sailing to confront the Minotaur can be viewed as the story of Greeks, specifically Athenians, facing what was for them, very real threats from the east. By integrating iconographical and mythological evidence for the myths of Theseus and placing the Minotaur myth within the wider historical and political context of fifth century Athens, this thesis shows that the hybrid Minotaur was a stand in for the Persians.
Pose-varied Face Recognition Based on Facial Pose Correction and Virtual Samples

Improving the multi-gesture recognition accuracy in the study of face recognition.The recognition rate will decline sharply when there are large variation of face pose,especially when the training samples are small,the identification may be impossible.In order to solve the problem of lack of training samples,firstly this paper transforms the pose-varied face images to frontal face images and the texture information of faces is kept based on sine transform(ST). Secondly,polynomial transform is used to generate virtual samples when only having single training sample.Finally,combining the subspace feature extraction methods with pose-varied face recognition strategy,the simulation is conducted and the recognition rates have increased by 19 percentage points.
Aman-machinemixsuppliestheMeteoSwissWEB&APPwith forecastdata

Since Autumn 2014, a new system is operationally producing forecast data for the MeteoSwiss WEBsite and for the smartphone APP. This system, called Data4WEB, combines high resolution meteorological fields coming from the ECMWF IFS model together with the expertise of bench forecasters, in order to provide the WEB and the APP with very localized forecasts but which remain under the supervision of MeteoSwiss forecasters. This “man-machine” system allows the forecaster to influence the NWP fields at a regional scale for correcting, whenever necessary, errors or bias of the model.
MPreplay: Architecture Support for Deterministic Replay of Message Passing Programs on Message Passing Many-Core Processors

While a lot o f work has been focused on design and programming o f shared memory multi-core architectures, message passing architectures are increasingly being con­ sidered an attractive design point for many-core [10] and application-specific [2] processors. A big concern with message passing architectures, however, is programmabil­ ity and debuggability on such machines and the signifi­ cant overhead o f providing support for the same at software level. In this paper, we take a first look at providing hard­ ware support for debugging and replay o f message passing programs on message passing architectures. We propose a hardware framework for logging races between messages to allow deterministic replay o f message passing programs. One implementation o f the framework is based on Netzer algorithm [19] for software-based logging and uses vector timestamps. The other implementation is based on a novel algorithm that uses scalar timestamps. We show that the two implementations have small time and space overhead. We discuss similar hardware support for allowing incremental replay o f message passing programs.