Miracle-dz/UniFAR-FTUs huggingface dataset:
Extending tabletop application design to the classroom

While a number of guidelines exist for the design of learning applications that target a single group working around an interactive tabletop, the same cannot be said for the design of applications intended for use in multi-tabletops deployments in the classroom. Accordingly, a number of these guidelines for single-tabletop settings need to be extended to take account of both the distinctive qualities of the classroom and the particular challenges of having various groups using the same application on multiple tables simultaneously. This paper presents an empirical analysis of the effectiveness of designs for small-group multi-tabletop collaborative learning activities in the wild. We use distributed cognition as a framework to analyze the small number of authentic multi-tabletop deployments and help characterize the technological and educational ecology of these classroom settings. Based on previous research on single-tabletop collaboration, the concept of orchestration, and both first-hand experience and second-hand accounts of the few existing multiple-tabletop deployments to date, we develop a three-dimensional framework of design recommendations for multi-tabletop learning settings.
Architecture for Mobile based Face Detection / Recognition

— In this paper a novel description of Face Detection-Recognition architecture through mobile devices is presented. Since the face detection/recognition is of importance in real-life scenarios, such as for authentication and security services and implementing it in mobile devices would provide a great value to society. This paper presents client-server architecture through the use of Bluetooth Technology through which face detection/recognition phases can be implemented.
Modeling and Mining Optimal Patterns Using Dynamic CSP

We introduce the notion of Optimal Patterns (OPs), defined as the best patterns according to a given user preference, and show that OPs encompass many data mining problems. Then, we propose a generic method based on a Dynamic Constraint Satisfaction Problem to mine OPs, and we show that any OP is characterized by a basic constraint and a set of constraints to be dynamically added. Finally, we perform an experimental study comparing our approach vs adhoc methods on several types of OPs.
Gaussian process for RSS-based localisation

Localisation making use of Wi-Fi Signal Strength is a well established research strand, where various approaches have been proposed by the community. In our work we focus on the problem of localizing a device by considering the Received Signal Strength (RSS) of signals the device receives from the wireless access points around it. We propose a two-parts localization method that makes use of the Gaussian Process technique to interpolate signal vectors received during a training phase in order to estimate the unknown position of the device during test. The proposed method has been tested on four publicly available databases proposed by other authors. The comparison with their results shows the superior performance of our novel approach.
RNS Arithmetic Approach in Lattice-Based Cryptography: Accelerating the "Rounding-off" Core Procedure

Residue Number Systems (RNS) are naturally considered as an interesting candidate to provide efficient arithmetic for implementations of cryptosystems such as RSA, ECC (Elliptic Curve Cryptography), pairings, etc. More recently, RNS have been used to accelerate fully homomorphic encryption as lattice-based cryptogaphy. In this paper, we present an RNS algorithm resolving the Closest Vector Problem (CVP). This algorithm is particularly efficient for a certain class of lattice basis. It provides a full RNS Babai round-off procedure without any costly conversion into alternative positional number system such as Mixed Radix System (MRS). An optimized Cox-Rower architecture adapted to the proposed algorithm is also presented. The main modifications reside in the Rower unit whose feature is to use only one multiplier. This allows to free two out of three multipliers from the Rower unit by reusing the same one with an overhead of 3 more cycles per inner reduction. An analysis of feasibility of implementation within FPGA is also given.
ANALISIS SITUASI PEMBELAJARAN MUSIK DI SEKOLAH DASAR DI WILAYAH KABUPATEN SUMEDANG JAWA BARAT

Abstrak Penelitian ini membahas tentang kondisi objektif proses pembelajaran musik di tingkat Sekolah Dasar di wilayah Kabupaten Sumedang. Berdasarkan hasil analisis data, ditemukan permasalahan yang terjadi pada proses pembelajaran musik di Sekolah Dasar khususnya yang ada di Kabupaten Sumedang adalah kesulitan yang dialami oleh guru ketika mengajarkan musik. Hal ini terjadi karena guru yang ada sebagian besar bukan lulusan kesenian, sehingga guru tidak paham dengan materi yang harus diajarkan. Penelitian ini menggunakan pendekatan kualitatif dan kuantitatif dengan metode studi kasus terhadap proses pembelajaran musik di tingkatan Sekolah Dasar di wilayah Kabupaten Sumedang. Data ini diperoleh dari hasil observasi dan wawancara kepada Ketua KKKS (Kelompok Kerja Kepala Sekolah) di tiap kecamatan yang berada di wilayah Kabupaten Sumedang. Data pendukung lainnya didapatkan dari Dinas Pendidikan Kabupaten Sumedang dokumen yang berisi data guru SD keseluruhan yang berada di Kabupaten Sumedang, baik negeri maupun swasta. Selanjutnya, data ini dianalisis untuk mengetahui jumlah guru seni yang mempunyai latar belakang dari sekolah atau institusi seni (lulusan seni), dan bagaimana kondisi sebenarnya mengenai pembelajaran seni musik yang dilaksanakan di SD-SD yang ada. Kata Kunci : pembelajaran musik, guru, sekolah dasar Abstract. This study discusses the objective condition of the learning process of music at elementary school level in Sumedang regency. Based on the results of data analysis, found the problems that occur in the process of learning music in elementary schools, especially in Sumedang is the difficulty experienced by teachers when teaching music. This happens because most of the teachers are not art graduates, so the teacher does not understand the material that must be taught. This research uses qualitative and quantitative approach with case study method to the learning process of music at elementary level in Sumedang regency. This data is obtained from observations and interviews to the Head of KKKS (Working Group of Principals) in each sub-district located in Sumedang Regency. Other supporting data are obtained from the Education Office of Sumedang District documents containing the data of all elementary teachers in Sumedang District, both public and private. Furthermore, this data is analyzed to determine the number of art teachers who have backgrounds from schools or art institutions (art graduates), and how the actual conditions about music art learning are implemented in existing SDs. Keyword : music teaching, teacher, elementary school
Personality and victimization in the Americas

Victimization is associated with traumatic harm, bringing inherent importance to efforts to understand why victimization occurs. Past research has shown that economic and demographic factors affect the probability that individuals will experience bribery, crime, and discrimination. We build on this foundation by arguing that a fuller account of victimization must include the impact of differences in personality. To test our hypotheses, we utilize survey data from 22 nations in the Americas. Results show that openness and extraversion increase the probability of victimization and agreeableness decreases it.
Sensitivity of Automated MT Evaluation Metrics on Higher Quality MT Output: BLEU vs Task-Based Evaluation Methods

We report the results of our experiment on assessing the ability of automated MT evaluation metrics to remain sensitive to variations in MT quality as the average quality of the compared systems goes up. We compare two groups of metrics: those, which measure the proximity of MT output to some reference translation, and those which evaluate the performance of some automated process on degraded MT output. The experiment shows that proximity-based metrics (such as BLEU) loose sensitivity as the scores go up, but performance-based metrics (e.g., Named Entity recognition from MT output) remain sensitive across the scale. We suggest a model for explaining this result, which attributes stable sensitivity of performance-based metrics to measuring cumulative functional effect of different language levels, while proximity-based metrics measure structural matches on a lexical level and therefore miss higher-level errors that are more typical for better MT systems. Development of new automated metrics should take into account possible decline in sensitivity on higher-quality MT, which should be tested as part of meta-evaluation of the metrics.
Planetary Kantsaywhere

On the leading edges of multidimensional cultural evolution in an urbanizing capitalism that is becoming ever more cosmopolitan and competitive, universities promise contradictory blends of diversity, inclusion, and fair, open access to the inherent exclusivity of the means of production of inequality: human capital. In this paper, we extend David Harvey’s theorization of the urbanization of consciousness and accumulation by dispossession in order to diagnose the dangerous contradictions of transnationalizing educational meritocracies in contemporary cognitive capitalism. Competition is intensified through informational automation and infinitely expanding fields of quantified, bell-curve sifting and sorting of human aspirations and cognitive labor: so-called ‘world-class’ universities are sites of astonishing brilliance and pervasive anxiety, depression, and suicide. Cycles of valorization and devalorization of embodied human capital are accelerating with the systemic overproduction of competitive human achievement, creativity, and excellence. New scales of competition are reconfiguring inter- and intra-generational inequalities, sustaining a mirage of attainable, multidimensional perfection on the receding horizons of planetary human possibility. Today’s constellations of capital, code, and competition are producing an evolving planetary ethos best described as accumulation by cognitive dispossession; while some of its technologies are genuinely new, the essential logic is just a transnational, multicultural, and pseudo-postcolonial update of the utopian perfection portrayed in Francis Galton’s stillborn 1911 eugenics novel Kantsaywhere.
A new cooperative technique for wireless communications with improved diversity-multiplexing tradeoff

In this work we present a new diversity-multiplexing scheme for the uplink transmission of a cooperative system consisting of single-antenna source and relay nodes and a multi-antenna destination node. The proposed technique is based on the singular value decomposition of the channel matrix and, for the same rate, it exhibits higher diversity gain as compared to the existing schemes. Moreover compared with these techniques it is highly reconfigurable and has a lower complexity receiver structure. We evaluate the performance of the new technique via theoretical analysis and simulations.
Minimal models for precipitating turbulent convection

Abstract Simulations of precipitating convection would typically use a non-Boussinesq dynamical core such as the anelastic equations, and would incorporate water substance in all of its phases: vapour, liquid and ice. Furthermore, the liquid water phase would be separated into cloud water (small droplets suspended in air) and rain water (larger droplets that fall). Depending on environmental conditions, the moist convection may organize itself on multiple length and time scales. Here we investigate the question, what is the minimal representation of water substance and dynamics that still reproduces the basic regimes of turbulent convective organization? The simplified models investigated here use a Boussinesq atmosphere with bulk cloud physics involving equations for water vapour and rain water only. As a first test of the minimal models, we investigate organization or lack thereof on relatively small length scales of approximately 100 km and time scales of a few days. It is demonstrated that the minimal models produce either unorganized (‘scattered’) or organized convection in appropriate environmental conditions, depending on the environmental wind shear. For the case of organized convection, the models qualitatively capture features of propagating squall lines that are observed in nature and in more comprehensive cloud resolving models, such as tilted rain water profiles, low-altitude cold pools and propagation speed corresponding to the maximum of the horizontally averaged, horizontal velocity.
The Impact of Transformational Leadership on Individual and Team Performance: Evidence from Knowledge Work Teams

The current study explored the effect of transformational leadership of knowledge work team leaders on team members' individual performance, which included both in-role behavior and organizational citizenship behavior(OCB), and team performance. Survey data was collected from a sample of 54 knowledge work teams in high-tech organizations in four cities of China. The results of hierarchical regression showed that relationship-oriented transformational leadership behaviors had a significant effect on team members' OCB with leader-member exchange(LMX) as the mediator, and task-oriented transformational leadership behaviors had a significant effect on team members' in-role behavior. Team- level OCB mediated the relationship between transformational leadership and team performance.
Title: a Transactional Model of Sleep-wake Regulation in Preterm and Low Birthweight Infants

Goodlin-Jones, Burnham, and Anders’(2000) transactional model of infant sleep-wake regulation implicates parent, child and dyadic characteristics in the development of infant sleepwake regulation (Figure 1). Within this model, dynamic processes between proximal and distal factors influence the development of infant sleep patterns and ultimately infant sleep problems. In the present study, we tested the applicability of this transactional model in a sample of infants born preterm or low birthweight (PT LBW). Infants born PT LBW are at increased risk not only for developmental difficulties but also for parental interaction and regulatory problems (Vergara & Bigsby, 2004). Research on PT LBW infants consistently indicates that they do not show the full range of joint attention and interactional skills seen in infants born full-term, therefore placing them at risk for interactional difficulties. Similarly, maternal characteristics like depression and contextual stressors may influence the quality of dyadic interactions. Within this study, we focused on the maternal characteristics of age, education, income and depression; the infant characteristics of gestational age and birthweight; and the dyadic characteristics of parent-child interaction quality and nighttime feeding route.
Cross-Origin JavaScript Capability Leaks: Detection, Exploitation, and Defense

We identify a class of Web browser implementation vulnerabilities, cross-origin JavaScript capability leaks, which occur when the browser leaks a JavaScript pointer from one security origin to another. We devise an algorithm for detecting these vulnerabilities by monitoring the "points-to" relation of the JavaScript heap. Our algorithm finds a number of new vulnerabilities in the opensource WebKit browser engine used by Safari. We propose an approach to mitigate this class of vulnerabilities by adding access control checks to browser JavaScript engines. These access control checks are backwardscompatible because they do not alter semantics of the Web platform. Through an application of the inline cache, we implement these checks with an overhead of 1-2% on industry-standard benchmarks.
Characterizing Two Inter-specific Bin Maps for the Exploration of the QTLs/Genes that Confer Three Soybean Evolutionary Traits

Annual wild soybean (Glycine soja Sieb. and Zucc.), the wild progenitor of the cultivated soybean [Glycine max (L.) Merr. ], is valuable for improving the later. The construction of a linkage map is crucial for studying the genetic differentiation between these species, but marker density is the main factor limiting the accuracy of such a map. Recent advances in next-generation sequencing technologies allow for the generation of high-density linkage maps. Here, two sets of inter-specific recombinant inbred line populations, named NJIRNP and NJIR4P, composed of 284 and 161 lines, respectively, were generated from the same wild male parent, PI 342618B, and genotyped by restriction-site-associated DNA sequencing. Two linkage maps containing 5,728 and 4,354 bins were constructed based on 89,680 and 80,995 single nucleotide polymorphisms, spanning a total genetic distance of 2204.6 and 2136.7 cM, with an average distance of 0.4 and 0.5 cM between neighboring bins in NJRINP and NJRI4P, respectively. With the two maps, seven well-studied loci, B1 for seed bloom; G and I for seed coat color; E2, E3, qDTF16.1 and two linked FLOWERING LOCUS T for days to flowering, were detected. In addition, two SB and two DTF loci were newly identified in wild soybean. Using two high-density maps, the mapping resolution was enhanced, e.g., G was narrowed to a region of 0.4 Mb on chromosome 1, encompassing 54 gene models, among which only Glyma01g40590 was predicted to be involved in anthocyanin accumulation, and its interaction with I was verified in both populations. In addition, five genes, Glyma16g03030, orthologous to Arabidopsis Phytochrome A (PHYA); Glyma13g28810, Glyma13g29920, and Glyma13g30710 predicted to encode the APETALA 2 (AP2) domain; and Glyma02g00300, involved in response to red or far red light, might be candidate DTF genes. Our results demonstrate that RAD-seq is a cost-effective approach for constructing high-density and high-quality bin maps that can be used to map QTLs/genes into such small enough regions that their candidate genes can be predicted.
This Paper Is Included in the Proceedings of the 12th Usenix Symposium on Operating Systems Design and Implementation (osdi '16). Network Requirements for Resource Disaggregation Network Requirements for Resource Disaggregation

Traditional datacenters are designed as a collection of servers, each of which tightly couples the resources required for computing tasks. Recent industry trends suggest a paradigm shift to a disaggregated datacenter (DDC) architecture containing a pool of resources, each built as a standalone resource blade and interconnected using a network fabric. A key enabling (or blocking) factor for disaggregation will be the network – to support good application-level performance it becomes critical that the network fabric provide low latency communication even under the increased traffic load that disaggregation introduces. In this paper, we use a workload-driven approach to derive the minimum latency and bandwidth requirements that the network in disaggregated datacenters must provide to avoid degrading application-level performance and explore the feasibility of meeting these requirements with existing system designs and commodity networking technology.
Using motif information to improve anytime time series classification

Anytime algorithm for time series classification requires the ordering heuristic of the instances in the training set. To establish the ordering, the algorithm must compute the distance between every pair of time series in the training set. And this step incurs a high computational cost, especially when Dynamic Time Warping distance is used. In this paper, we present an method to speed up the computation of this step. Our method hinges on the ordering of time series motifs detected by a previous task rather than ordering the original time series. Experimental results show that our new ordering method improves remarkably the efficiency of the anytime algorithm for time series classification without sacrificing its accuracy.
Discrete relative states to learn and recognize goals-based behaviors of groups

In a crisis management context, situation awareness is challenging due to the complexity of the environment and the limited resources available to the security forces. The different emerging threats are difficult to identify and the behavior of the crowd (separated in groups) is difficult to interpret and manage. In order to solve this problem, the authors propose a method to detect threat and understand the situation by analyzing the collective behavior of groups inside the crowd and detecting their goals. This is done according to a set of learned, goal-based, group behavior models and observation sequences of the group. The proposed method computes the group estimated state before using Hidden Markov Model to recognize the goal by the group behavior. A realistic emergency scenario is simulated to demonstrate the performance of the algorithms, where a suicide-bomber wearing a concealed bomb enters a busy urban street. The proposed algorithms achieve the detection of the dangerous person in the crowd, in order to raise an alert and also predict casualties by identifying which groups did not notice the threat. Complex Event Processing is used to compare and evaluate the results. The algorithms were found more precise and more tolerant to noisy observations.
Bipolar Transurethral Incision of Bladder Neck Stenoses with Mitomycin C Injection

Introduction. To determine the efficacy of bipolar transurethral incision with mitomycin C (MMC) injection for the treatment of refractory bladder neck stenosis (BNS). Materials and Methods. Patients who underwent bipolar transurethral incision of BNS (TUIBNS) with MMC injection at our institution from 2013 to 2014 were retrospectively reviewed. A total of 2 mg of 40% mitomycin C solution was injected in four quadrants of the treated BNS. Treatment failure was defined as the need for subsequent intervention. Results. Thirteen patients underwent 17 bipolar TUIBNS with MMC injection. Twelve (92%) patients had failed a mean of 2.2 ± 1.1 prior endoscopic procedures. Median follow-up was 16.5 months (IQR: 14–18.4 months). Initial success was 62%; five (38%) patients had a recurrence with a median time to recurrence of 7.3 months. Four patients underwent a repeat procedure, 2 (50%) of which failed. Overall success was achieved in 77% (10/13) of patients after a mean of 1.3 ± 0.5 procedures. BNS recurrence was not significantly associated with history of pelvic radiation (33% versus 43%, p = 0.9). There were no serious adverse events. Conclusions. Bipolar TUIBNS with MMC injection was comparable in efficacy to previously reported techniques and did not result in any serious adverse events.