Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimal Pricing in Repeated Posted-Price Auctions with Different Patience of the Seller and the Buyer

We study revenue optimization pricing algorithms for repeated posted-price auctions where a seller interacts with a single strategic buyer that holds a fixed private valuation. When the participants non-equally discount their cumulative utilities, we show that the optimal constant pricing (which offers the Myerson price) is no longer optimal. In the case of more patient seller, we propose a novel multidimensional optimization functional --- a generalization of the one used to determine Myerson's price. This functional allows to find the optimal algorithm and to boost revenue of the optimal static pricing by an efficient low-dimensional approximation. Numerical experiments are provided to support our results.
An Efficient Short Blind Proxy Re-signatures Scheme

The existing proxy re-signature schemes have drawbacks in terms of privacy protection and signature efficiency. Our scheme is based on the proxy re-signature scheme, which combines the main idea of short blind signature and proposes the definition of short blind proxy re-signature scheme. Then, using the signature framework of the random oracle model, we propose a short blind proxy re-signature scheme based on the random oracle model, and prove the security of the scheme under the adaptive chosen-message attacks. The analysis shows that compared with the existing similar schemes, our scheme does not add additional verification information under the premise of shortening the signature length, and the applicability is better in the interactive transmission of devices with limited calculation and transmission performance.
Augmented Immersive Reality (AIR) for Improved Learning Performance: A Quantitative Evaluation

Technology-enhanced learning has attracted increasing attention of educational community focused on improvement of traditional classroom learning. Augmented immersive reality (AIR) technologies enhance users’ perception of reality by augmenting it with computer-generated components such as audio, video, 2/3-D graphics, GPS data, etc. The AIR introduces new dimensions of learning experience that ensure better attention, focus, and entertainment, thereby boosting students’ motivation and attainment. This work presents an award winning AIR-based educational mobile system, code-named AIR-EDUTECH, that was developed to help high school students learn chemistry. The AIR-EDUTECH introduced new AIR features to help students better understand and learn basic concepts of molecular chemistry. It offers immersive 3D visualization and visual interaction with the examined structures that provides a broader and more retentive knowledge and improves intuition around forming basic chemical reactions. The system was introduced and tested in a field study with 45 students in the $11^{th}$ grade chemistry class, and its impact was evaluated by the formal assessment quiz along with the feedback from survey conducted after the trial. Collected data have been subjected to an in-depth multi-modal quantitative analysis that revealed that AIR-EDUTECH stimulated significant improvements in understanding and retention of the taught content as well as turned learning chemistry into a fun, interesting and interactive experience. It also uncovered a hidden structure of taught knowledge dependencies and highlighted the role that AIR technology could play in reinforcing the retention of critical knowledge that may otherwise widen student knowledge gaps.
Innovate to decide : Modelling and experimenting decisional ambidexterity to manage the metabolisms of the innovative organization

It is now common knowledge to develop an ambidextrous organization in a ﬁrm to guarantee a competitive advantage in its environment. Such perspective is rooted in James March’s model (1991) whose purpose is to sustain organizational learning through adaptive mechanisms between agents. This model anchored in the tradition of problem-solving offers a behavioural approach coping with biases and heuristics of bounded rationality. In contrast, with literature models studying the balance between exploration and exploitation activities (ambidexterity), we demonstrate how exploration can be more generative if it uses exploitation constraints as prior knowledge to generate concepts. These rely on positively conditioning them by decision-making parameters contributing to exploitation. New decision situations are designed instead of traditionally selecting explorations. This model - decisional ambidexterity-allows building up projects capable of exploring conditions overcoming limitations and performances of exploitation. A collaborative research conducted at Zodiac Aerospace allowed revealing such new model. It extends organizational ambidexterity into the unknown, more adapted to innovation management & governance, whilst precising how to drive organization metabolisms inducing change among participating organizations in a conglomerate of SMEs.
Unsupervised Context Rewriting for Open Domain Conversation

Context modeling has a pivotal role in open domain conversation. Existing works either use heuristic methods or jointly learn context modeling and response generation with an encoder-decoder framework. This paper proposes an explicit context rewriting method, which rewrites the last utterance by considering context history. We leverage pseudo-parallel data and elaborate a context rewriting network, which is built upon the CopyNet with the reinforcement learning method. The rewritten utterance is beneficial to candidate retrieval, explainable context modeling, as well as enabling to employ a single-turn framework to the multi-turn scenario. The empirical results show that our model outperforms baselines in terms of the rewriting quality, the multi-turn response generation, and the end-to-end retrieval-based chatbots.
Incorporating Visual Semantics into Sentence Representations within a Grounded Space

Language grounding is an active field aiming at enriching textual representations with visual information. Generally, textual and visual elements are embedded in the same representation space, which implicitly assumes a one-to-one correspondence between modalities. This hypothesis does not hold when representing words, and becomes problematic when used to learn sentence representations — the focus of this paper — as a visual scene can be described by a wide variety of sentences. To overcome this limitation, we propose to transfer visual information to textual representations by learning an intermediate representation space: the grounded space. We further propose two new complementary objectives ensuring that (1) sentences associated with the same visual content are close in the grounded space and (2) similarities between related elements are preserved across modalities. We show that this model outperforms the previous state-of-the-art on classification and semantic relatedness tasks.
Toward an (even) more comprehensive model of speech production planning

ABSTRACT Since the publication of Speaking in 1989, with its extraordinary goal of modelling the entire process of human speech generation from message conceptualisation to articulation, encompassing results from a wide range of empirical studies, much new information has emerged about three aspects of speech production that were not clearly in focus at that time. This evidence has revealed 1) the systematic patterns of context-governed surface phonetic variation, and the active control of these patterns exercised by speakers and listeners, 2) the depth and pervasiveness of prosodic influences on those patterns, and 3) the close alignment of co-speech gestures with the prosodic structure of an utterance. This paper reviews some of that evidence, and suggests how its implications may constrain models of speech production planning, as those models become more comprehensive in their treatment of higher-level structures, and of aspects of the communicative act beyond the articulation of lexical and syntactic elements.
Morphological study of the palatine mucosa in the type 2 diabetes mellitus model rat

Hyperglycemia is thought to cause hypertrophy of the mucosal epithelium, atrophy of the connective tissue beneath the mucosal epithelium, and diabetic microangiopathy of the capillaries in the spontaneous type 2 diabetes mellitus (DM) rat. To our knowledge, no previous studies have investigated the mucosal epithelium, the connective tissue beneath the mucosal epithelium, or the capillaries of the palatine mucosa in the DM rat. To contribute to knowledge in this field, we investigated the mucosal epithelium (the keratinized, granular, prickle and basal layers), the connective tissue beneath the mucosal epithelium, and capillaries of the palatine mucosa in the DM rat. We then compared morphological differences between normal (N) and DM rats. In addition, we thought that morphological changes might occur in other organs (the palatal gingiva of the maxillary first molar and the lingual gingiva of the mandibular first molar), and we compared morphological differences of other oral organs between N and DM rats.
Viral hepatitis : diagnosis, treatment, prevention

Molecular Diagnostic Testing for Viral Hepatitis: Methods and Applications, Stephen J. Polyak and David R. Gretch Hepatitis A Virus, Manuel Battegay and Stephen M. Feinstone Hepatitis B Virus: Molecular Biology and Immunopathology-Experimental and Clinical Features, Barbara Rehermann and Frank V. Chisari Hepatitis B Virus: Clinical Disease-Prevention and Therapy, Steven A. Rogers, Jules Dienstag, and T. Jake Liang Hepatitis C, Juan I. Estaban, Jordi Gomez, Maria Martell, and Jaime Guardia Hepatitis D Virus, Adrian M. Di Bisceglie Overview of the Epidemiology and Virology of the Hepatitis E Virus, Gregory R. Reyes Other Hepatitis Viruses Including the Hepatitis G Virus, Raymond S. Koff The Role of Hepatitis Viruses in Acute Liver Failure, Christopher J. Tibbs and Roger Williams Hepatocellular Carcinoma and Viral Hepatitis, Brian J. McMahon Extrahepatic Manifestations of Chronic Viral Hepatitis, Richard A. Willson Overlap of Chronic Viral Hepatitis and Autoimmune Hepatitis, Albert J. Czaja Liver Transplantation and Viral Hepatitis B, C, and D, Didier Samuel, Cyrille Feray, and Henri Bismuth Viral Hepatitis in Marrow and Stem-Cell Transplant Patients, Darik Taniguchi and George B. McDonald Viral Hepatitis in the Immunocompromised Host, Gary L. Davis The Role of Iron in Chronic Viral Hepatitis: Implications for Therapy, Kris V. Kowdley
Surface Realisation Using Full Delexicalisation

Surface realisation (SR) maps a meaning representation to a sentence and can be viewed as consisting of three subtasks: word ordering, morphological inflection and contraction generation (e.g., clitic attachment in Portuguese or elision in French). We propose a modular approach to surface realisation which models each of these components separately, and evaluate our approach on the 10 languages covered by the SR’18 Surface Realisation Shared Task shallow track. We provide a detailed evaluation of how word order, morphological realisation and contractions are handled by the model and an analysis of the differences in word ordering performance across languages.
Game Theory Meets Embeddings: a Unified Framework for Word Sense Disambiguation

Game-theoretic models, thanks to their intrinsic ability to exploit contextual information, have shown to be particularly suited for the Word Sense Disambiguation task. They represent ambiguous words as the players of a non cooperative game and their senses as the strategies that the players can select in order to play the games. The interaction among the players is modeled with a weighted graph and the payoff as an embedding similarity function, that the players try to maximize. The impact of the word and sense embedding representations in the framework has been tested and analyzed extensively: experiments on standard benchmarks show state-of-art performances and different tests hint at the usefulness of using disambiguation to obtain contextualized word representations.
Surround Modulation: A Bio-inspired Connectivity Structure for Convolutional Neural Networks

Numerous neurophysiological studies have revealed that a large number of the primary visual cortex neurons operate in a regime called surround modulation. Surround modulation has a substantial effect on various perceptual tasks, and it also plays a crucial role in the efficient neural coding of the visual cortex. Inspired by the notion of surround modulation, we designed new excitatory-inhibitory connections between a unit and its surrounding units in the convolutional neural network (CNN) to achieve a more biologically plausible network. Our experiments show that this simple mechanism can considerably improve both the performance and training speed of traditional CNNs in visual tasks. We further explore additional outcomes of the proposed structure. We first evaluate the model under several visual challenges, such as the presence of clutter or change in lighting conditions and show its superior generalization capability in handling these challenging situations. We then study possible changes in the statistics of neural activities such as sparsity and decorrelation and provide further insight into the underlying efficiencies of surround modulation. Experimental results show that importing surround modulation into the convolutional layers ensues various effects analogous to those derived by surround modulation in the visual cortex.
Perceptual Quality Assessment of 3d Point Clouds

The real-world applications of 3D point clouds have been growing rapidly in recent years, but effective approaches and datasets to assess the quality of 3D point clouds are largely lacking. In this work, we construct so far the largest 3D point cloud database with diverse source content and distortion patterns, and carry out a comprehensive subjective user study. We construct 20 high quality, realistic, and omni-directional point clouds of diverse contents. We then apply downsampling, Gaussian noise, and three types of compression algorithms to create 740 distorted point clouds. Based on the database, we carry out a subjective experiment to evaluate the quality of distorted point clouds, and perform a point cloud encoder comparison. Our statistical analysis find that existing point cloud quality assessment models are limited in predicting subjective quality ratings. The database will be made publicly available to facilitate future research.
Behavioral Medicine: A Social Worker's Guide

1. Behavioral Medicine and Managed Care: Implications for Social Work Practice 2. The Integrated Service Delivery System 3. Managed Care, Assessment Instruments, and Helping Professionals 4. Development of Managed Information Systems For Human Services: A Practical Guide 5. Psychosocial Treatment Configurations 6. Behavior Health: Adolescent 7. Adult Behavioral Health 8. Prevention: Cost Saving for Reducing Health Care Costs Summary: Emerging Trends
Multiclass Learning from Contradictions

We introduce the notion of learning from contradictions, a.k. a Universum learning, for multiclass problems and propose a novel formulation for multiclass universum SVM (MU-SVM). We show that learning from contradictions (using MU-SVM) incurs lower sample complexity compared to multiclass SVM (M-SVM) by deriving the Natarajan dimension for sample complexity for PAC-learnability of MU-SVM. We also propose an analytic span bound for MU-SVM and demonstrate its utility for model selection resulting in $\sim 2-4 \times$ faster computation times than standard resampling techniques. We empirically demonstrate the efficacy of MU- SVM on several real world datasets achieving $>$ 20\% improvement in test accuracies compared to M-SVM. Insights into the underlying behavior of MU-SVM using a histograms-of-projections method are also provided.
Predicting User Satisfaction of Non-volitional Enterprise Systems: An Example From Telecomunications

The rapid pace of technological change has seen information and communication technologies become the digital backbone of developed nations’ economies and a pre-requisite for global trade. Some enterprise systems are however more than mere facilitators, they provide the bedrock without which organizations could not function; we term these mandatory systems “non-volitional” (NVS). With hyper-growth in demand for connectivity, telecommunications are typical of sectors where NVS shape the fiercely competitive landscape. Among them, Billing & Revenue Management Systems (BRMS) are a form of credit, providers deliver a service and subscribers later pay for that service. As such, they are “business critical”, meaning failures may affect an organization’s ability to conduct its core business. Failures also impact user satisfaction, a key measure of information systems success. However, relatively few studies empirically test this notion; fewer still evaluate it at organizational (rather than individual) level, while there is a dearth of literature investigating non-volitional systems and, to the best of our knowledge, none whatsoever consider ways of predicting user satisfaction for BRMS. According to a renowned and widely cited conceptual model, user satisfaction is influenced by information, system, and service quality respectively. To test this theory for telecoms BRMS, we applied structural equation modelling to investigate which of these dimensions has the most effect. The results indicate that information quality, system quality, service quality, and user satisfaction are all valid measures of BRMS success. Hypothesized relationships between the four success dimensions were significantly substantiated. The study also identified five measures of information quality, four measures of system quality, four measures of service quality, and four measures of user satisfaction. Once the proposed model had been successfully validated, we tested the level of significance among user satisfaction and the three quality dimensions. Findings showed that service quality had the strongest influence on user satisfaction, with information quality second. This is quite different from other applications considered in our literature review which mostly have information quality as having the strongest impact (knowledge management systems apart).
NumNet: Machine Reading Comprehension with Numerical Reasoning

Numerical reasoning, such as addition, subtraction, sorting and counting is a critical skill in human’s reading comprehension, which has not been well considered in existing machine reading comprehension (MRC) systems. To address this issue, we propose a numerical MRC model named as NumNet, which utilizes a numerically-aware graph neural network to consider the comparing information and performs numerical reasoning over numbers in the question and passage. Our system achieves an EM-score of 64.56% on the DROP dataset, outperforming all existing machine reading comprehension models by considering the numerical relations among numbers.
Low-Complexity Transform Adjustments for Video Coding

Recent video codecs with multiple separable transforms can achieve significant coding gains using asymmetric trigonometric transforms (DCTs and DSTs), because they can exploit diverse statistics of residual block signals. However, they add excessive computational and memory complexity on large transforms (32-point and larger), since their practical software and hardware implementations are not as effi-cient as of the DCT-2. This article introduces a novel technique to design low-complexity approximations of trigonometric transforms. The proposed method uses DCT-2 computations, and applies orthogonal "adjustments" to approximate the most important basis vectors of the desired transform. Experimental results on the Versatile Video Coding (VVC) reference software show that the proposed approach significantly reduces the computational complexity, while providing practically identical coding efficiency.
Cultural intelligence as education contents: Exploring the pedagogical aspects of effective functioning in higher education

Academic discussions on cultural intelligence (CQ) are now paying attention to their potential utilization from various angles. The field of study is expanded not only in business administration but also in psychology, education, tourism, communication, and arts. This is due to the widespread study of global communication competence in multicultural situations because of the deepening of globalization. In this paper, we try to find a way to utilize cultural intelligence model proposed by David Livermore. The aim is to develop education contents for the improvement of cultural intelligence of university students. The target is limited to university students and aims to develop education contents to enhance their cultural intelligence. The main purpose of the study was to measure and analyze the cultural intelligence of university students. For that, the level of cultural intelligence of Korean university freshmen was measured and analyzed. The individual level of the four areas constituting the cultural intelligence was identified, and the difference between the male and female was examined. At the same time, the differences in cultural intelligence were analyzed according to the duration of multicultural contact and experience in the case of foreign language lectures taught by foreigners. Finally, we analyzed how the correlation between the four areas that comprise cultural intelligence is occurring, and as a result, the content and results of this study are expected to be an important foundation for the direction of future development of education contents in universities.
Effects of Aromatherapy Massage on Pain, Physical Function, Sleep Disturbance and Depression in Elderly Women with Osteoarthritis

Purpose: This study was to investigate the effects of aromatherapy massage on pain, physical function, sleep disturbance and depression in elderly women with osteoarthritis. Method: The study design was a quasi-experiment design with a non-equivalent control group pre and post-test. The study pool included elderly female patients older than 65years old suffering from osteoarthritis. Results: Pain in the experimental group after the aromatherapy massage was significantly decreased than that in the control group. The physical disability in the experimental group after the aromatherapy massage was significantly decreased than that in the control group. The sleep disturbance in the experimental group after the aromatherapy massage was significantly decreased than that in the control group. The depression in the experimental group after the aromatherapy massage was significantly decreased than that in the control group. Conclusion: Aromatherapy may be adopted as an effective nursing intervention for osteoarthritis.