Miracle-dz/UniFAR-FTUs huggingface dataset:
Graph Based Measure of Text Semantic Similarity Using WordNet as a Knowledge Base

A substantial part of the available information, is stored in text databases. Typically, only a minor fraction of available documents is appropriate for a user. Hence, to analyze and extract useful information from text documents, generation of the appropriate query document is difficult. This illustrates the importance of similarity of text documents. Several cases of lexical matching techniques offered to determine the similarity between documents that have been successful to a certain boundary and these methods are failing to find the semantic similarity between two texts. Therefore, the semantic similarity approaches were suggested, such as corpusbased methods and knowledge based methods e.g. WordNet based methods. This paper offers a new approach to the problem of text semantic similarity identification. In this work, we investigate a new approach of paraphrase identification in order to measuring the semantic similarity of texts. We present a Graph algorithm for Similarity identification that makes extensive use of word similarity information extracted from WordNet, also we implemented previously published method. Experiments performed on the Microsoft Research Paraphrase Corpus and we show our approach achieves appropriate performance.
A Generalized Natural Balance Model and Balance Booster Filter Design for Three-Level Neutral-Point-Clamped Converters

Three-level neutral point clamped (NPC) inverters exhibit a natural balancing property that can self-regulate the intermediate neutral point voltage to half the overall dc-link voltage. However, the underlying mechanisms of this process are not well understood, its performance under various load conditions has not been properly explored, and the requirements and benefits of (RLC) balance booster filters to enhance the natural balancing response are not clear. This paper presents a generalized model of an NPC natural balancing process that allows these issues to be explored for various load structures and balance booster configurations (i.e., isolated wye, wye with a grounded star point, etc.). The model accurately predicts the dominant balancing time constant, identifies the harmonics that drive the balancing process, and can quantify the steady-state balance booster losses for a designed target natural balance response. Extensive simulation and experimental tests have been performed to validate the theoretical model.
Direct lighting on meso-structured surfaces with area light sources

We present a novel direct lighting rendering method for static scenes with meso-structured surfaces and multiple area light sources. We use coarse geometry models with textures bound on them as inputs. The textures contain not only color maps, but also height field maps to represent the small concave and convex details for meso-structured surfaces. We explore traditional radiosity process as the main frame of our algorithm, and extend radiosity to directional radiosity for approximating light transportation on meso-structured surfaces. In pre-processing step, first, the form factors between the triangles of coarse models and the patches of area light sources are pre-computed. Then the directional radiosity of each triangle is computed by gathering irradiance according to directions sampled uniformly on the hemi-sphere of them. At last, directional radiosity of a vertex is estimated according to the directional radiosity of triangles passing through this vertex. For each frame, we combine relief texture mapping with directional radiosity to shade meso-structured surface. The experiment results show that our method has very similar quality and better time performance for rendering the scenes with meso-structured surfaces and multiple area light sources compared with SM+RTM method.
NLOS detection algorithms for Ultra-Wideband localization

Non Line of Sight (NLOS) channels are one of the major drawbacks for accurate ranging and localization with Ultra-Wideband (UWB) technology. Whereas several proposals exist to detect these situations, a comprehensive overview, investigation and testing of these methods has to the authors' knowledge not yet been prepared. This paper tries to fill this gap with a classification of the algorithms proposed of the UWB and mobile phone community. In addition, one novel method based on the signal power variation is suggested. Afterwards, the methods are evaluated regarding their practicability for real UWB localization systems, which excludes some of them from further investigation. For the remaining algorithms thresholds are proposed, which are strived to be as independent of the system and environment as possible. Finally, the NLOS detection algorithms are tested and compared with both an UWB simulation environment and an UWB localization test bed.
Development of a Preclinical Orthotopic Xenograft Model of Ewing Sarcoma and Other Human Malignant Bone Disease Using Advanced In Vivo Imaging

Ewing sarcoma and osteosarcoma represent the two most common primary bone tumours in childhood and adolescence, with bone metastases being the most adverse prognostic factor. In prostate cancer, osseous metastasis poses a major clinical challenge. We developed a preclinical orthotopic model of Ewing sarcoma, reflecting the biology of the tumour-bone interactions in human disease and allowing in vivo monitoring of disease progression, and compared this with models of osteosarcoma and prostate carcinoma. Human tumour cell lines were transplanted into non-obese diabetic/severe combined immunodeficient (NSG) and Rag2−/−/γc−/− mice by intrafemoral injection. For Ewing sarcoma, minimal cell numbers (1000–5000) injected in small volumes were able to induce orthotopic tumour growth. Tumour progression was studied using positron emission tomography, computed tomography, magnetic resonance imaging and bioluminescent imaging. Tumours and their interactions with bones were examined by histology. Each tumour induced bone destruction and outgrowth of extramedullary tumour masses, together with characteristic changes in bone that were well visualised by computed tomography, which correlated with post-mortem histology. Ewing sarcoma and, to a lesser extent, osteosarcoma cells induced prominent reactive new bone formation. Osteosarcoma cells produced osteoid and mineralised “malignant” bone within the tumour mass itself. Injection of prostate carcinoma cells led to osteoclast-driven osteolytic lesions. Bioluminescent imaging of Ewing sarcoma xenografts allowed easy and rapid monitoring of tumour growth and detection of tumour dissemination to lungs, liver and bone. Magnetic resonance imaging proved useful for monitoring soft tissue tumour growth and volume. Positron emission tomography proved to be of limited use in this model. Overall, we have developed an orthotopic in vivo model for Ewing sarcoma and other primary and secondary human bone malignancies, which resemble the human disease. We have shown the utility of small animal bioimaging for tracking disease progression, making this model a useful assay for preclinical drug testing.
The influence of core musculature engagement on hip and knee kinematics in women during a single leg squat.

PURPOSE/BACKGROUND Excessive frontal plane motion and valgus torques have been linked to knee injuries, particularly in women. Studies have investigated the role of lower extremity musculature, yet few have studied the activation of trunk or "core" musculature on hip and knee kinematics. Therefore, this study evaluated the influence of intentional core engagement on hip and knee kinematics during a single leg squat. METHODS Participants (n = 14) performed a single leg squat from a 6 inch step under 2 conditions: core intentionally engaged (CORE) and no intentional core engagement (NOCORE). Participants were also evaluated for core activation ability using Sahrmann's model, and the resulting scores were used to divide participants into low (LOWCORE) and high scoring (HIGHCORE) groups. All trials were captured using 3-D motion analysis, and data were normalized for height and time. Paired t-tests and repeated measures, mixed model MANOVAs were used to assess condition and group differences. RESULTS The CORE condition, compared to NOCORE, was characterized by smaller right [t(13) = 3.03, p = . 01] and left [t(13) = 3.04, p = . 01] hip frontal plane displacement and larger knee flexion range of motion [t(13) = 3.08, p = . 009]. Subsequent MANOVAs and follow-up analyses revealed that: (1) the CORE condition demonstrated smaller right and left hip medial-lateral displacement in the LOWCORE group (p = .001), but not in the HIGHCORE group; (2) the CORE condition showed larger overall knee flexion range of motion across LOWCORE and HIGHCORE groups (p = .021); and (3) the HIGHCORE group exhibited less knee varus range of motion across CORE and NOCORE conditions (p = .028). CONCLUSIONS Intentional core activation influenced hip and knee kinematics during single leg squats, with greater positive effect noted in the LOWCORE group. These findings may have implications for preventing and rehabilitating knee injuries among women. LEVEL OF EVIDENCE 2B, Cohort laboratory study, mixed model design.
Lepton Number as the Fourth Color

Universal strong, weak, and electromagnetic interactions of leptons and hadrons are generated by gauging a non-Abelian renormalizable anomaly-free subgroup of the fundamental symmetry structure $\mathrm{SU}{(4)}_{L}\ifmmode\times\else\texttimes\fi{}\mathrm{SU}{(4)}_{R}\ifmmode\times\else\texttimes\fi{}\mathrm{SU}({4}^{\ensuremath{'}})$, which unites three quartets of "colored" baryonic quarks and the quartet of known leptons into 16-folds of chiral fermionic multiplets, with lepton number treated as the fourth "color" quantum number. Experimental consequences of this scheme are discussed. These include (1) the emergence and effects of exotic gauge mesons carrying both baryonic as well as leptonic quantum numbers, particularly in semileptonic processes, (2) the manifestation of anomalous strong interactions among leptonic and semileptonic processes at high energies, (3) the independent possibility of baryon-lepton number violation in quark and proton decays, and (4) the occurrence of ($V+A$) weak-current effects.
A stereovision based approach for detecting and tracking lane and forward obstacles on mobile devices

This paper presents SmartCoDrive, an Android application which performs driving assistance functions: 3D lane detection and tracking, forward obstacle detection, obstacle tracking. With this mobile application we wish to increase the adoption rate of driving assistance systems and to provide a viable and cheap solution for every driver, that will be able to use his own tablet or smartphone as a personal driving assistant. The mobile application is deployed on a tablet equipped with dual back-facing cameras. The visual information from the two cameras, along with the data received from the Controller Area Network bus of the vehicle enable a thorough understanding of the 3D environment. First, we develop the sparse 3D reconstruction algorithm. Then, using monocular vision we perform lane markings detection. Obstacle detection is done by combining the superpixel segmentation with 3D information and the tracking algorithm is based on the Kalman Filter. Since the processing capabilities of the mobile platforms are limited, different optimizations are carried out in order to obtain a real-time implementation. The Android application may be used in urban traffic that is characterized by low-speed and short-medium distances to obstacles.
A system for heuristic modifications on PLA-specifications

When specifying a PLA for the implementation of a numerical function, usually an adhoc procedure is followed: Generating real values, some type of scaling, rounding to integers, and finally binary coding. Examining the numerical exactness of the performed steps in detail, some kind of blurring can always be recognized. In fact, designers have to accept such unavoidable effects. In many practical applications a good compromise can be achieved between a reasonable decrease of PLA costs and art acceptable amount of implicated deviation. We introduce in this paper the optimization tool HOPE which includes the described heuristics. It is applicable in any design procedure which needs PLAs and uses ESPRESSO as an integral part.
Implications of Error Analysis Studies for Academic Interventions

We reviewed 13 studies that focused on analyzing student errors on achievement tests from the Kaufman Test of Educational Achievement–Third edition (KTEA-3). The intent was to determine what instructional implications could be derived from in-depth error analysis. As we reviewed these studies, several themes emerged. We explain how a careful analysis of errors is key to planning the most appropriate instructional interventions.
Creating bridges: Music-Oriented Counseling for Parents of children with Autism Spectrum Disorder

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Comparing Abstractive and Extractive Summarization of Evaluative Text: Controversiality and Content Selection

One of the main aspects of the so-called “Web 2.0” is increased participation by website users, or a blurring of the distinction between the content provider and the content receiver. One form that this user interaction can take is the sharing of comments on products that users have purchased or services that they have used. Examples abound on websites such as amazon.com, flixster.com, and chapters.indigo. ca. The need for efficient and effective multi-document summarization of these user reviews and other kinds of evaluative text containing opinions and preferences is thus ever-growing. This thesis examines two canonical strategies for summarization: summarization by extraction, which consists of concatenating source sentences into a summary, and summarization by abstraction, which involves generating novel sentences for the summary (Hahn and Mani, 2000). The first part of this thesis compares the two summarization strategies when they are applied to the domain of summarizing evaluative text (e.g. user reviews). We report on the results of a user study which examines the interaction of the summarization strategy with the controversiality of the opinions in the corpus. We then propose a clustering framework for summarization content selection that allows us to combine the two strategies in order to capitalize on the strengths of each. We apply this framework to the summarization of evaluative text, using a clustering paradigm from the field of location theory called the p-median problem (Resende and Werneck, 2004).
ASpli : An integrative R package for analysing alternative splicing using RNAseq 2 2 Getting started

3 Running ASpli 2 3.1 To BIN or not to BIN . 2 3.2 Read Counting . 3 3.2. 1 Mapping file and bam loading . 4 3.2. 2 Overlap features and read alignments . 4 3.3 Alternative splicing analysis and discovery using junction . 5 3.4 Estimating differential gene expression and bin/junction usage . 6 3.4. 1 Differential gene expression (DE) . 6 3.4. 2 Differential junctions and bin usage (DU) . 6 3.5 Output and results . 7 3.6 Plots . 8
Recovery-based resilient latency-insensitive systems

As the interconnect delay is becoming a larger fraction of the clock cycle time, the conventional global stalling mechanism, which is used to correct error in general synchronous circuits, would be no longer feasible because of the expensive timing cost for the stalling signal to travel across the circuit. In this paper, we propose recovery-based resilient latency-insensitive systems (RLISs) that efficiently integrate error-recovery techniques with latency-insensitive design to replace the global stalling. We first demonstrate a baseline RLIS as the motivation of our work that uses additional output buffer which guarantees that only correct data can enter the output channel. However this baseline RLIS suffers from performance degradations even when errors do not occur. We propose a novel improved RLIS that allows erroneous data to propagate in the system. Equipped with improved queues that prevent accumulation of erroneous data, the improved RLIS retains the system performance. We provide theoretical study that analyzes the impact of errors on system performance and the queue sizing problem. We also theoretically prove that the improved RLIS performs no worse than the global stalling mechanism. Experimental results show that the improved RLIS has 40.3% and even 3.1% throughput improvements compared to the baseline RLIS and the infeasible global stalling mechanism respectively, with less than 10% hardware overhead.
Prajna: Towards Recognizing Whatever You Want from Images without Image Labeling

With the advances in distributed computation, machine learn-ing and deep neural networks, we enter into an era that it is possible to build a real world image recognition system. There are three essential components to build a real-world image recognition system: 1) creating representative features, 2) de-signing powerful learning approaches, and 3) identifying massive training data. While extensive researches have been done on the first two aspects, much less attention has been paid on the third. In this paper, we present an end-to-end Web knowledge discovery system, Prajna. Starting from an arbi-trary set of entities as inputs, Prajna automatically crawls im-ages from multiple sources, identifies images that have relia-bly labeled, trains models and build a recognition system that is capable of recognizing any new images of the entity set. Due to the high cost of manual data labeling, leveraging the massive yet noisy data on the Internet is a natural idea, but the practical engineering aspect is highly challenging. Prajna fo-cuses on separating reliable training data from extensive noisy data, which is a key to the capability of extending an image recognition system to support arbitrary entities. In this paper, we will analyze the intrinsic characteristics of Internet image data, and find ways to mine accurate and informative infor-mation from those data to build a training set, which is then used to train image recognition models. Prajna is capable of automatically building an image recognition system for those entities as long as we can collect sufficient number of images of the entities on the Web.
Decor: a tool for the detection of design defects

Software engineers often need to identify design defects, recurring design problems that hinder the development process, to improve and assess the quality of their systems. However, this is di±cult because of the lack of specifications and tools. We propose Decor, a method to specify design defects systematically and to generate automatically detection algorithms. With this method, software engineers analyse and specify design defects at a high-level of abstraction using a unified vocabulary and dedicated language for generating detection algorithms
A Pixel Value Ordering Predictor for High-Capacity Reversible Data Hiding

Reversible data hiding (RDH), also known as lossless data embedding, is increasingly attracting more attentions of academic and industry researchers intrigued by their affordances and reach. Recently, various pixel value ordering (PVO) predictors for RDH methods with remarkable embedding performance have been proposed. These PVO-based schemes have good performance in high fidelity images but low in the embedding capacity. Therefore, this paper proposed an extension of PVO RDH. Instead of modifying the maximum and minimum values of each block, we design a scheme to all pixels within every block to improve the payload but reserved good image quality. As a result, the proposed scheme is significantly better than that of the Li et al. method in terms of embedding capacity while keeping distortion low.
Architecture and evaluation of Maestro 2 high speed cluster network

Cluster computers have become the vehicle of choice to build high performance computing environments. To fully exploit the computing power of these environments, one must utilize high performance network and protocol technologies, since the communication patterns of parallel applications running on clusters require low latency and high throughput, not achievable by using wideor local-area network technologies. This paper identifies the main drawbacks of conventional network technologies, and the techniques proposed to solve them within a new network solution called Maestro, in an original version and with an enhanced architecture called Maestro2. This paper describes the design and the implementation of Maestro2 technology and the novel techniques used by Maestro2 to extract maximum performance from the physical medium. Experimental results, clearly show that Maestro2 is a promising technology, presenting very good results both in terms of latency and throughput, using both specialized communications libraries (proprietary MMP or standardized MPI) and well known communications protocols (TCP/IP).
Stability and Variability in Aesthetic Experience: A Review

Based on psychophysics’ pragmatic dualism, we trace the cognitive neuroscience of stability and variability in aesthetic experience. With regard to different domains of aesthetic processing, we touch upon the relevance of cognitive schemata for aesthetic preference. Attitudes and preferences are explored in detail. Evolutionary constraints on attitude formation or schema generation are elucidated, just as the often seemingly arbitrary influences of social, societal, and cultural nature are. A particular focus is put on the concept of critical periods during an individual’s ontogenesis. The latter contrasting with changes of high frequency, such as fashion influences. Taken together, these analyses document the state of the art in the field and, potentially, highlight avenues for future research.
ICT and Social Capital in the Knowledge Economy

This study explores the way in which the New Zealand public sector is approaching the development of a national knowledge economy through its use of knowledge management, information and communication technologies (ICT), and social capital. To date, public sector knowledge management initiatives have largely followed an ICT-based approach, but there is growing awareness of the need to address the cultural and organizational aspects of knowledge management, including the role of social capital