Miracle-dz/UniFAR-FTUs huggingface dataset:
TopNet: Structural Point Cloud Decoder

3D point cloud generation is of great use for 3D scene modeling and understanding. Real-world 3D object point clouds can be properly described by a collection of low-level and high-level structures such as surfaces, geometric primitives, semantic parts,etc. In fact, there exist many different representations of a 3D object point cloud as a set of point groups. Existing frameworks for point cloud genera-ion either do not consider structure in their proposed solutions, or assume and enforce a specific structure/topology,e.g. a collection of manifolds or surfaces, for the generated point cloud of a 3D object. In this work, we pro-pose a novel decoder that generates a structured point cloud without assuming any specific structure or topology on the underlying point set. Our decoder is softly constrained to generate a point cloud following a hierarchical rooted tree structure. We show that given enough capacity and allowing for redundancies, the proposed decoder is very flexible and able to learn any arbitrary grouping of points including any topology on the point set. We evaluate our decoder on the task of point cloud generation for 3D point cloud shape completion. Combined with encoders from existing frameworks, we show that our proposed decoder significantly outperforms state-of-the-art 3D point cloud completion methods on the Shapenet dataset
An Exploration of the Psychometric Properties of the Self-Sufficiency Matrix Among Individuals and Families Currently or At Risk of Experiencing Homelessness

The homeless service sector has moved toward the implementation of assessment tools to better understand the support service needs of individuals and families. While a variety of assessment tools are available, their psychometric evidence base is limited. The Self-Sufficiency Matrix (SSM) is one assessment that holds promise with regard to its reliability, validity, and potential use as an instrument for triaging services. However, research examining the factor structure of the SSM has been inconsistent across samples. Moreover, it has never been tested among a broad population of both those currently experiencing and at-risk of experiencing homelessness, or examined unaccompanied adults and families with minor children independently. The current study sought to explore the factor structure of the SSM using exploratory and confirmatory factor analysis among a sample of unaccompanied individuals (N = 427) and families (N = 428) experiencing or at-risk of experiencing homelessness. Data were derived from the Homeless Management Information System (HMIS) from a Midwestern metropolitan area and included all individuals and families who participated in the Homelessness Prevention and Rapid Re-Housing Program. Results suggest the SSM is multidimensional and the relation between its items and latent constructs differs across individual and family subgroups. Further, study findings indicate the SSM holds promise with regard to its invariance across racial and gender groups. Results suggest further development and testing of the SSM is necessary to better serve individuals experiencing homelessness. PSYCHOMETRIC PROPERTIES OF THE SELF-SUFFICIENCY MATRIX 2
Heterogeneous Transactional Memory

Over the course of the last decade, concerns with power consumption and demand for increasing processing power have lead micro-architectures to a highly parallel paradigm. Notably the GPU, now uses a versatile manycore architecture, which, along with its raw computation power, led researchers to use them for general purpose computing, Whilst these parallel architectures allow for great peak performances, they also raise complex programming problems, especially in regards to synchronizing accesses to shared data. As a result, applications that strive to exploit the parallelism potential of heterogeneous systems equipped with both GPU and CPUs are notoriously difficult to develop. In this context, Transactional Memory (TM) has been proposed to facilitate concurrent programming. TM is an abstraction that moves the complexity of synchronizing shared data access in multi-threaded systems away to a library. This work proposes Heterogeneous Transactional Memory (HeterosTM) the first (to the best of the author’s knowledge) TM system capable of supporting concurrent execution of applications that exploit both CPUs and GPUs. In order to minimize synchronization overheads, HeterosTM relies on speculative techniques, which aim to amortize the costs of enforcing consistency among transactions executing on the different units. This system’s architecture is presented and the tested. Keywords-Transactional Memory; Graphical Processor Units; General Purpose Computing on GPUs; Heterogeneous System;
Dynamic Signature-based Malware Detection Technique Based on API Call Tracing

The paper presents a method for a malware’s signature generation based on API call tracing. Technique allows malware detection using a proposed form of signature. The main idea of proposed signature generation is a difference between frequency and interaction of a critical API calls performed by malicious program and benign applications in the process of their own execution. Accordingly the program's behavior signature based on API call tracing consists of two components: the call frequency and the nature of the interaction of critical API calls. An analysis of the first component allows determining the distribution of the critical API calls by groups concerning theirs malicious activity and displays the quantitative component of the signature. An analysis of the second component of the signature provides an opportunity to distinguish malware from benign applications not only in the presence of critical API calls, but also in their interaction with each other. The experimental results showed that the effectiveness of the malware detection using proposed signatures is up to 96.56%.
Reconstructing Sediment Supply and Transport Behind the Elwha River Dams

The Elwha River watershed in Washington State’s Olympic National Park is predominantly a steep mountainous landscape where dominant geomorphic processes include landslides, debris flows, and gullying. The removal of the two massive hydropower dams along the Elwha River in 2013 marked the largest global dam removal in history. Over the centurylong lifespan of the dams, approximately 21 million cubic meters of sediment was impounded behind them. In this study, we test different approaches to reconstructing sediment supply and delivery to the Elwha dams throughout their lifespan. Available observational data that aid in this approach include DEM, channel morphology, meteorology, and streamflow and sediment discharge. We analyze the performance of three numerical modeling constructs — Cases I, II, and III — in predicting historic reservoir sediment yields in the Elwha River watershed. In Case I, we use a sediment rating curve approach and improve upon a published sediment rating curve (Curran et al., 2009) for the Elwha River using a modified, calibrated version of the Wilcock & Crowe (2003) sediment transport equation. In Cases II and III we use a network model that we have developed which connects processes of sediment supply from hillslopes with sediment detachment and transport at stream links of a channel network. The model is driven by streamflow and sediment forcings which can be of varying complexity. In Case II, the network model is driven by stochastic streamflow forcings that require simple input data and parameterization. In Case III, the network model is driven by physically-based model outputs of streamflow from a physically-based distributed model, DHSVM. Using these three cases, we strive to answer the questions: Is using a watershed network model warranted in predicting dam sedimentation? If so, what level of complexity is needed in the driving streamflow and sediment forcings? Is a rating curve approach adequate and robust enough for predicting dam sedimentation, particularly with expected changes in environmental conditions? Cases I, II, and III in this report require further calibration before these questions can fully be answered, however are valuable “proof-of-concept” models. We show that our uncalibrated modeling results along with the insights we have developed provide a promising path in moving forward to answer these questions.
GPU-based volume-oriented rendering of functionally defined objects

Volume graphics research involves "re-inventing" computer graphics for volumes and it is applicable to the majority of computer graphics applications. Many applications will be impacted by volume graphics. These include, but not limited to, flight simulations, mission planning, biomedical, environment, industrial and CAD applications. This paper presents a new representation scheme for freeform surfaces it is possible to combine basic surface and perturbation functions. Terrain is represented for the base of scalar perturbation functions.
1990-An 24 a AndApplication of a discontinuous Galerkin method for waveguide analysis /

A novel full-wave method to perform mode analysis on waveguides is introduced in this dissertation. The core of the method is based on an Interior Penalty Discontinuous Galerkin (IPDG) discretization of the vector wave equation. With an appropriate penalty function a spurious-free and high accuracy method is achieved. The efficiency of the proposed method was proved in several waveguides, including intricate optical waveguides with leaky modes and also on plasmonic waveguides. The obtained results were compared with the state-of-the-art mode solvers described in the literature. Also, a discussion on the importance of this new approach is presented. Moreover, the results indicate that the proposed method is more accurate than the previous approaches based on Finite Elements Methods. The main contributions of this work are: the development of a novel robust and accurate method for the analysis of arbitrary waveguides, a new penalty function for the IPDG was proposed and practical applications of the methods are discussed. In addition, in the appendix an application of modal analysis on 3D electromagnetic simulations with a Discontinuous Galerkin method is detailed.
The media coverage of the UK Budget : explaining the variation in the attention given to different type of policy decisions

This paper explores the ‘selection bias’ of the media reporting of the policy decisions presented in the Annual Budget in the UK. Using automated content analysis, this study analyses over 4,000 articles of press coverage of six ‘crisis’ Budgets, from 2008 to 2012 (with two in 2010). It identifies which factors explain the difference in prominence given by the media coverage to a wide range of policy decisions: from an increase in VAT to the reduction of corporation tax to changes in several benefit indexation mechanisms. The analysis shows that the salience of policy decisions in the coverage is determined by its cost, whether is negative (i.e. tax hikes and spending cuts) or positive, the income group that is most affected by it, and the degree of attention given to it by the government. Moreover, although there are some differences, by and large the same factors apply regardless of which party/ies is in government and for both broadsheets and tabloids.
The Market for English Premier League Odds12

We develop a probabilistic representation of real-time betting odds for English Premier League (EPL) soccer games and derive new empirical insights from the betting market efficiency. We use market odds data for different outcomes of win, loss, draw, and particularly the score difference. We show how a difference in Poisson processes (a.k.a. Skellam process) provides a dynamic probabilistic model for the evolution of score predictions implied by odds. As the game evolves, we use the updated market odds to re-estimate the Skellam process and to recalculate the prediction matrix of odds implied final scores. The Skellam interpretation enables us to understand the mechanism of the real-time betting market, and the evolution of odds implied volatility in the perspective of the Black-Scholes-Merton model. We verify the Skellam assumption through odds data of the win, loss, and draw for 1520 EPL games from 2012 to 2016, as well as odds data of the score difference for 18 games in the season 2016-2017. To demonstrate the flexibility of our model by showing how quickly the odds change as the score progresses, we apply it to an EPL game between Everton and West Ham in the season 20152016. Finally, we conclude with directions for future research.
Management of the Net Asset Value in the Real Estate Sector : An Empirical Evidence 1

The aim of this study is to examine whether fund ma nagers strategically run the net asset value of the real estate investment funds under the i management and which factors may influence their decisions. The legal framework of t he Portuguese real estate investment funds allows fund managers to show some discretion in valuing properties opening room for empirical study on earnings management for this sector.
Implementation of Schoof ’ s Algorithm on the Windows Platforms

In FIPS 186-2, NIST (National Institute of Standards and Technology) recommends ten secure elliptic curve parameters over binary field.If the user can randomly produce parameters over binary field, the cryptosystem will be more secure. One of the important steps is to count the number of points on an elliptic curve over binary field and find the curve of prime order. The study designed the graphic user’s interface to implement Schoof’s algorithm on Windows platforms. The system uses C++ Builder to design the interface and MIRACL as embedded function library. Besides counting points on an elliptic curve, the system can search out secure parameters of the elliptic curve over binary field. This can provide users convenient way for building up secure elliptic curve cryptosystems.
MODELING OF ELECTRONIC STATES OF A SINGLE DONOR IN MIS-STRUCTURE USING THE FINITE DIFFERENCE METHOD

Abstract: Numerical modeling of electronic state evolution due to external electric field in the structure metal-insulator-semiconductor with solitary donor center is carried out. Considering a nanometer disc-shaped gate as a source of the electric field, the problem for the Laplace equation in infinite multilayered medium is solved to determine the gate potential. The energy spectrum of a bound electron is calculated from the problem for the stationary Schrödinger equation. Finite difference schemes are constructed to solve both the problems. Difference scheme for the Schrödinger equation takes into account cusp condition for the wave function at the donor location. To solve the problem for the Laplace equation, asymptotic boundary conditions for approximating the potential at large distances from the gate are proposed. On the basis of calculation results, a controlling parameter is suggested, which allows to determine the localization of electron wave function regardless of insulator thickness and permittivity.
Improved Storage for Efficient Private Information Retrieval

We consider the problem of private information retrieval from N storage- constrained databases. In this problem, a user wishes to retrieve a single message out of M messages (of size L) without revealing any information about the identity of the message to individual databases. Each database stores $\mu M L$ symbols, i.e., a $\mu$ fraction of the entire library, where $\frac{1}{N} \leq \mu \leq 1. $ Our goal is to characterize the optimal tradeoff curve for the storage cost (captured by $\mu$) and the normalized download cost $(D / L). $ We show that the download cost can be reduced by employing a hybrid storage scheme that combines MDS coding ideas with uncoded partial replication ideas. When there is no coding, our scheme reduces to Attia-Kumar-Tandon storage scheme, which was initially introduced by Maddah-AliNiesen in the context of the caching problem, and when there is no uncoded partial replication, our scheme reduces to Banawan-Ulukus storage scheme; in general, our scheme outperforms both.
Normally-Off Operation of AlGaN/GaN Heterojunction Field-Effect Transistor with Clamping Diode

This paper reports a new method to enable the normally-off operation of AlGaN/GaN heterojunction field-effect transistors (HFETs). A capacitor was connected to the gate input node of a normally-on AlGaN/GaN HFET with a Schottky gate where the Schottky gate acted as a clamping diode. The combination of the capacitor and Schottky gate functioned as a clamp circuit to downshift the input signal to enable the normally-off operation. The normally-off operation with a virtual threshold voltage of 5.3 V was successfully demonstrated with excellent dynamic switching characteristics.
Cooperative Mapping for Automated Vehicles Research

Localization is essential for automated vehicles, even for simple tasks such as lanekeeping. Some automated vehicle systems use their sensors to perceive their surroundings on-the-fly, such as the early variants of the Tesla Autopilot, while others such as the Waymo car navigate within a prior map. The latter approach is beneficial in that it helps the system to expect the expected, that is, it relieves the system of perceiving static features. However, making and updating such accurate prior maps using a specialized vehicle fleet is expensive and cumbersome. Techniques for Simulatneous Localization And Mapping (SLAM) are an attractive solution to this problem. SLAM uses visual and other sensors for creating and updating maps as the robot/vehicle navigates within the map. This project explores the possibility of using multiple vehicles to perform cooperative SLAM for improving and updating the map formed using optical cameras, radar, IMU, and GNSS. It is assumed that raw data from these sensors can be shared among the vehicles over a wireless link either via V2V or V2I communications.
Evaluation and development of confidence indicators based on harmonised business and consumer surveys

Wavelet analysis can de-noise an economic time series while retaining underlying structure in that series. The method retains both the time localization, and shape of the structure. New data added to the end of a series cause little revision in the previously de-noised series. We introduce wavelet analysis and present results for the EU11 industrial production and consumer confidence survey areas. We also give an example of the extension of de-noised data. * Visiting Professor for Theoretical Physics at the Technical University of Munich. His main fields of research are on nonlinear dynamical systems, with experience in neural networks and macroscopic quantum phenomena (superconducting Josephson effect). Present research is on wavelet analysis methods and hierarchical information storage systems.
RECOGNITION WITH CONVOLUTIONAL SEQUENCE-TO-SEQUENCE MODELS First

Optical Music Recognition (OMR) is an important technology within Music Information Retrieval. Deep learning models show promising results on OMR tasks, but symbol-level annotated data sets of sufficient size to train such models are not available and difficult to develop. We present a novel deep learning architecture called a Convolutional Sequence-to-Sequence model to both move towards an end-to-end trainable OMR pipeline, and improve the learning process by training on full sentences of sheet music instead of individually labeled symbols. The model is trained and evaluated on a human generated data set, with various image augmentations based on real-world scenarios. This data set is the first publicly available set in OMR research with sufficient size to train and evaluate deep learning models. With the introduced augmentations a pitch recognition accuracy of 81% and a duration accuracy of 94% is achieved, resulting in a note level accuracy of 80%.
Load Identification Method Based on Interval Analysis and Tikhonov Regularization and Its Application

In order to study the dynamic force identification method of an end-plate pick of shearer, a dynamic force identification technique based on interval theory was proposed. The dynamic force interval identification model is established by describing and quantifying the identified parameters. By using the interval analysis method of the first-order Taylor expansion, the dynamic force identification is transformed into two kinds of deterministic inverse problems at the midpoint of the uncertain parameter and its gradient identification. The Tikhonov regularization method is used to solve two kinds of deterministic problems, and the upper and lower boundaries of dynamic force of the end-plate pick are determined. The results show that the deviations between the identified dynamic force and the actual dynamic force are basically within 2% and 5%, and the average uncertainties are up to 7% and 10%. Therefore, the proposed method can effectively determine the upper and lower boundaries of dynamic force of the end-plate pick, improve the solving efficiency, and provide a new research method for studying the coal rock mechanism of the pick cutting load.
Effective Method of Feature Selection on Features Possessing Group Structure

Feature selection has become an interesting research topic in recent years. It is an effective method to tackle the data with high dimension. The underlying structure has been ignored by the previous feature selection method and it determines the feature individually. Considering this fact we focus on the problem where feature possess some group structure. To solve this problem we present group feature selection method at group level to execute feature selection. Its objective is to execute the feature selection in within the group and between the group of features that select discriminative features and remove redundant features to obtain optimal subset. We demonstrate our method on benchmark data sets and perform the task to achieve classification accuracy. Keywords— feature selection, group structure, redundant, classification.
Lexical Accuracy and Reaction Time in Second Language Reading Proficiency in Indonesia

This article examines the degree to which lexical performance as reflected in accuracy and response time contributes to the L2 reading proficiency. The use of response time as proficiency indicator has been much neglected in L2 reading research. This study argues that lexical response time and lexical accuracy can mirror the development of L2 reading proficiency. One hundred and forty one university students (n=141) in Indonesia voluntarily participated in this study. Online time-yes/no test was used as a measure lexical performance and reading test was to assess L2 reading proficiency. This study revealed that performance for both lexical accuracy and response time significantly predict L2 reading proficiency, indicating that response time as elicited from online time-based testing can be taken into account as one of the L2 proficiency indexs to examine L2 development. Theoretical and practical implication of this study are discussed.
Avan Simulation Team

This paper presents an overview of Avan’s approach to build multi-agent systems and activities in RoboCup. Our scientific approach in working on multi-agent systems and distributed intelligence is based on Planning. We have paid attention to 3T as a known autonomous agent control architecture. In this way some strategies have been selected to provide significant assistance in the design of autonomous intelligent control. The most important items are: Modularity for simplifying both design and control, Hierarchically Organized Action Selection for focusing attention and providing prioritization when different modules conflict, and Environment Monitoring System for allowing attention to shift and priorities to be reevaluated [1].