Miracle-dz/UniFAR-FTUs huggingface dataset:
Probabilistic Scene Grammars: A General-Purpose Framework For Scene Understanding

of “Probabilistic Scene Grammars: A General-Purpose Framework For Scene Understanding” by Jeroen Chua, Ph.D., Brown University, May 2018. We propose a general-purpose probabilistic framework for scene understanding tasks. We show that several classical scene understanding tasks can be modeled and addressed under a common representation, approximate inference scheme, and learning algorithm. We refer to this approach as the Probabilistic Scene Grammar (PSG) framework. The PSG framework models scenes using probabilistic grammars which capture relationships between objects in terms of compositional rules that provide important contextual cues for inference with ambiguous data. We show how to represent the distribution defined by a probabilistic grammar using a factor graph. We also show how to estimate the parameters of a grammar using an approximate version of ExpectationMaximization, and describe an approximate inference scheme using Loopy Belief Propagation with an efficient message-passing scheme. Inference with Loopy Belief Propagation naturally combines bottom-up and top-down contextual information and leads to a robust algorithm for aggregating evidence. To demonstrate the generality of the approach, we evaluate the PSG framework on the scene understanding tasks of contour detection, face localization, and binary image segmentation. The results of the PSG framework are competitive with algorithms specialized for these scene understanding tasks. Probabilistic Scene Grammars: A General-Purpose Framework For Scene Understanding by Jeroen Chua B. A. Sc. , University of Toronto, 2010 M. A. Sc. ,University of Toronto, 2012 A dissertation submitted in partial fulfillment of the requirements for the Degree of Doctor of Philosophy in the Department of Computer Science at Brown University Providence, Rhode Island May 2018 c © Copyright 2018 by Jeroen Chua This dissertation by Jeroen Chua is accepted in its present form by the Department of Computer Science as satisfying the dissertation requirement for the degree of Doctor of Philosophy. Date Professor Pedro Felzenszwalb, Director Recommended to the Graduate Council Date Professor Erik Sudderth, Reader Date Professor Stuart Geman, Reader Approved by the Graduate Council Date Andrew G. Campbell Dean of the Graduate School
Cryptography for Efficiency: New Directions in Authenticated Data Structures

of “Cryptography for Efficiency: New Directions in Authenticated Data Structures” by Charalampos Papamanthou, Ph.D., Brown University, May 2011. Cloud computing has emerged as an important new computational and storage medium and is increasingly being adopted both by companies and individuals as a means of reducing operational and maintenance costs. However, remotely-stored sensitive data may be lost or modified and third-party computations may not be performed correctly due to errors, opportunistic behavior, or malicious attacks. Thus, while the cloud is an attractive alternative to local trusted computational resources, users need integrity guarantees in order to fully adopt this new paradigm. Specifically, they need to be assured that uploaded data has not been altered and outsourced computations have been performed correctly. Tackling the above problems requires the design of protocols that, on the one hand, are provably secure and at the same time remain highly efficient, otherwise the main purpose of adopting cloud computing, namely efficiency and scalability, is defeated. It is therefore essential that expertise in cryptography and efficient algorithmics be combined to achieve these goals. This thesis studies techniques allowing the efficient verification of data integrity and computations correctness in such adversarial environments. Towards this end, several new authenticated data structures for fundamental algorithmics and computation problems, e.g., hash table queries and set operations, are proposed. The main novelty of this work lies in employing advanced cryptography such as lattices and bilinear maps, towards achieving high efficiency, departing from traditional hash-based primitives. As such, the proposed techniques lead to efficient solutions that introduce minimal asymptotic overhead and at the same time enable highly-desirable features such as optimal verification mechanisms and parallel authenticated data structures algorithms. The small asymptotic overhead does translate into significant practical savings, yielding efficient protocols and system prototypes. Cryptography for Efficiency: New Directions in Authenticated Data Structures by Charalampos Papamanthou B.Sc., Applied Informatics, University of Macedonia, 2003 M.Sc., Computer Science, University of Crete, 2005 M.Sc., Computer Science, Brown University, 2007 A dissertation submitted in partial fulfillment of the requirements for the Degree of Doctor of Philosophy in the Department of Computer Science at Brown University Providence, Rhode Island May 2011 c © Copyright 2011 by Charalampos Papamanthou This dissertation by Charalampos Papamanthou is accepted in its present form by the Department of Computer Science as satisfying the dissertation requirement for the degree of Doctor of Philosophy. Date Roberto Tamassia, Director Recommended to the Graduate Council Date Michael T. Goodrich, Reader University of California, Irvine Date Anna Lysyanskaya, Reader Date Franco P. Preparata, Reader Approved by the Graduate Council Date Peter M. Weber Dean of the Graduate School iii
Small‐signal stability‐constrained optimal power flow analysis of multiterminal VSC‐HVDC systems with large‐scale wind farms

As a solution for the large‐scale wind power transmission in a power system model in East Japan, multiterminal VSC‐HVDC systems are proposed to be installed in the system model. To evaluate the effectiveness of the systems, small‐signal stability‐constrained optimal power flow (SSSC‐OPF) analysis in mixed AC/multiterminal VSC‐HVDC systems is developed. It is revealed by SSSC‐OPF analysis that the system reinforced only by an AC system is exposed to unstable operations. In contrast, mixed AC/multiterminal VSC‐HVDC systems do not suffer from such unstable system operations. On top of that, the differences in multiterminal VSC‐HVDC systems with different configurations are also discussed. Different annual fuel costs and wind power hosting capacity results are obtained due to AC transmission line capacities and interarea oscillation modes. The best multiterminal VSC‐HVDC system among all simulated multiterminal VSC‐HVDC systems is also concluded. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
Nonparametric lack-of-fit tests in presence of heteroscedastic variances

It is essential to test the adequacy of a specified regression model in order to have correct statistical inferences. In addition, ignoring the presence of heteroscedastic errors of regression models will lead to unreliable and misleading inferences. In this dissertation, we consider nonparametric lack-of-fit tests in presence of heteroscedastic variances. First, we consider testing the constant regression null hypothesis based on a test statistic constructed using a k-nearest neighbor augmentation. Then a lack-of-fit test of nonlinear regression null hypothesis is proposed. For both cases, the asymptotic distribution of the test statistic is derived under the null and local alternatives for the case of using fixed number of nearest neighbors. Numerical studies and real data analyses are presented to evaluate the performance of the proposed tests. Advantages of our tests compared to classical methods include: (1) The response variable can be discrete or continuous and can have variations depend on the predictor. This allows our tests to have broad applicability to data from many practical fields. (2) Using fixed number of k-nearest neighbors avoids slow convergence problem which is a common drawback of nonparametric methods that often leads to low power for moderate sample sizes. (3) We obtained the parametric standardizing rate for our test statistics, which give more power than smoothing based nonparametric methods for intermediate sample sizes. The numerical simulation studies show that our tests are powerful and have noticeably better performance than some well known tests when the data were generated from high frequency alternatives. Based on the idea of the Least Squares Cross-Validation (LSCV) procedure of Hardle and Mammen (1993), we also proposed a method to estimate the number of nearest neighbors for data augmentation that works with both continuous and discrete response variable. NONPARAMETRIC LACK-OF-FIT TESTS IN PRESENCE OF HETEROSCEDASTIC VARIANCES by Mohammed Mahmoud Gharaibeh B.S., Yarmouk University, Jordan, 1999 M.S., Yarmouk University, Jordan, 2002 A DISSERTATION submitted in partial fulfillment of the requirements for the degree DOCTOR OF PHILOSOPHY Department of Statistics College of Arts and Sciences KANSAS STATE UNIVERSITY Manhattan, Kansas 2014 Approved by: Major Professor Haiyan Wang
Large-scale Data Harvesting for Biographical Data

This paper explores automatic methods to identify relevant biography candidates in large databases, and extract biographical information from encyclopedia entries and databases. In this work, relevant candidates are deﬁned as people who have made an impact in a certain country or region within a pre-deﬁned time frame. We investigate the case of people who had an impact in the Republic of Austria and died between 1951 and 2019. We use Wikipedia and Wikidata as data sources and compare the performance of our information extraction methods on these two databases. We demonstrate the usefulness of a natural language processing pipeline to identify suitable biography candidates and, in a second stage, extract relevant information about them. Even though they are considered by many as an identical resource, our results show that the data from Wikipedia and Wikidata differs in some cases and they can be used in a complementary way providing more data for the compilation of biographies.
Measuring temporal and spatial travel efficiency for transit route system using low-frequency bus automatic vehicle location data

Although the bus probe data have been widely adopted for examining the transit route efficiency, this application cannot guarantee the accuracy in special temporal and spatial segments due to the inadequate probe samples. This study evaluates the feasibility of automatic vehicle location data as probes for the bus route travel time evaluation. Our techniques explore the minimum requirement of transit automatic vehicle location data to recover the bus trajectories in various spatial–temporal dimensions along the scheduled transit routes. First, a three-dimensional tensor is established to infer the uncovered link traveling information in current time slots and the last short-term period. Then, a general form is proposed to calculate the local mean travel speed and the average link travel time in each separated time slot of day. Finally, a case study has been conducted using field transit automatic vehicle location data running on a bus route corridor in Edmonton, Canada. The results demonstrate the effectiveness and efficiency of low-frequency bus automatic vehicle location data as probes for transit route efficiency measurement by comparing with baseline approaches. This work also supports the feasibility of using automatic vehicle location–equipped buses as customized buses for choosing alternate path based on evaluating the current transit efficiency on all routes.
Semantic Three-Dimensional Understanding of Dynamic Scenes

2013 – 2018 Ph.D. Thesis Research@ Brown University Providence, RI ∠ 3D object detection and layout prediction on RGB-D images ∠ Proposed theCloudsofOrientedGradients (COG)descriptor for 3Dobject detection systems, oral presentation at CVPR, T-PAMI special issue on RGB-D vision ∠ Advisor : Prof. Erik Sudderth Ph.D. Research@ Brown University Providence, RI ∠ Attribute-based image editing algorithms ∠ Dataset and algorithm for style transformation, oral presentation at SIGGRAPH ∠ Advisor : Prof. James Hays
On Scalable Transaction Execution in Partitioned Main Memory Database Management Systems

of “On Scalable Transaction Execution in Partitioned Main Memory Database Management Systems” by Andrew Pavlo, Ph.D., Brown University, May 2014. An emerging class of distributed database management systems (DBMS) seek to provide high-performance transaction processing for data-intensive applications while maintaining strong consistency guarantees. These systems achieve this by storing databases in a cluster of shared-nothing, main memory partitions. This partitioning enables them to eschew much of the legacy, disk-oriented architecture that slows down traditional systems, such as heavy-weight concurrency control algorithms, thereby allowing for the efficient execution of single-partition transactions. But many applications cannot be partitioned such that all of their transactions execute in this manner; these multi-partition transactions require expensive coordination that inhibits performance. In this dissertation, we study the problem of scalable transaction execution for modern on-line transaction processing (OLTP) applications. We present the design of H-Store, a distributed, main memory DBMS that is optimized for short-lived, write-heavy transactional workloads. We then present domain-specific applications of optimization and machine learning techniques to improve the performance of fast database systems like H-Store. Our first contribution is an approach for automatically generating a database design for an OLTP application that both minimizes both the amount of cross-node communication and skew in the cluster. We then present a Markov model-based approach for automatically selecting which optimizations to enable at run time for new transaction requests based on their most likely behavior. Finally, we present a method for using these models to schedule speculative transactions and queries whenever a DBMS stalls because of a multi-partition transaction. All together, these allow enable H-Store to support transactional workloads that are beyond what single-node systems can handle. On Scalable Transaction Execution in Partitioned Main Memory Database Management Systems
Shape Models of the Human Body for Distributed Inference

of “Shape Models of the Human Body for Distributed Inference” by Silvia Zuffi, Ph.D., Brown University, May 2015 In this thesis we address the problem of building shape models of the human body, in 2D and 3D, which are realistic and efficient to use. We focus our efforts on the human body, which is highly articulated and has interesting shape variations, but the approaches we present here can be applied to generic deformable and articulated objects. To address efficiency, we constrain our models to be part-based and have a tree-structured representation with pairwise relationships between connected parts. This allows the application of methods for distributed inference based on message passing. To address realism, we exploit recent advances in computer graphics that represent the human body with statistical shape models learned from 3D scans. We introduce two articulated body models, a 2D model, named Deformable Structures (DS), which is a contour-based model parameterized for 2D pose and projected shape, and a 3D model, named Stitchable Puppet (SP), which is a mesh-based model parameterized for 3D pose, pose-dependent deformations and intrinsic body shape. We have successfully applied the models to interesting and challenging problems in computer vision and computer graphics, namely pose estimation from static images, pose estimation from video sequences, pose and shape estimation from 3D scan data. This advances the state of the art in human pose and shape estimation and suggests that carefully defined realistic models can be important for computer vision. More work at the intersection of vision and graphics is thus encouraged.
Research on an Optimal Path Planning Method Based on A* Algorithm for Multi-View Recognition

: In order to obtain the optimal perspectives of the recognition target, this paper combines the motion path of the manipulator arm and camera. A path planning method to ﬁnd the optimal perspectives based on an A* algorithm is proposed. The quality of perspectives is represented by means of multi-view recognition. A binary multi-view 2D kernel principal component analysis network (BM2DKPCANet) is built to extract features. The multi-view angles classiﬁer based on BM2DKPCANet + Softmax is established, which outputs category posterior probability to represent the perspective recognition performance function. The path planning problem is transformed into a multi-objective optimization problem by taking the optimal view recognition and the shortest path distance as the objective functions. In order to reduce the calculation, the multi-objective optimization problem is transformed into a single optimization problem by fusing the objective functions based on the established perspective observation directed graph model. An A* algorithm is used to solve the single source shortest path problem of the fused directed graph. The path planning experiments with different numbers of view angles and different starting points demonstrate that the method can guide the camera to reach the viewpoint with higher recognition accuracy and complete the optimal observation path planning.
Prospection of Indigenous Yeasts from Uruguayan Tannat Vineyards with a View to Their Oenological Applications

Prospection of yeasts from oenological environments can provide knowledge of new native strains that are capable of ferment must and positively in�uence the composition and sensory characteristics of the wine. This work is addressed to the biotechnological characterization of indigenous yeast of Tannat must, an emblematic and widespread vineyard of Uruguay. Fifty-three yeast strains were morphologically characterized and further identi�ed by ampli�cation and sequencing of ITS and D1-D2 regions, grouping into a total of �fteen species. A representative strain of each species was selected and evaluated for its technological traits. In presence of ethanol (6 to 16% v/v) and SO2 (40 mg/L), native Saccharomyces cerevisiae T19-3FS presented the best growth rates and minors lag phase. Of the non-Saccharomyces strains, S. bacillaris T19-3MS stood out for its behavior in vini�cation conditions, more closely related with Saccharomyces strains. S. cerevisiae T19-3FS, S. bacillaris T19-3MS, S. diversa T19-1FS and P. terricola T19-1FN conducted a successful fermentation process reaching �nal ethanol concentration ≥ 10% v/v, and showed K + R phenotype, highlighting its potential use in pure starter cultures for the production of �nished wines. It also notes that S. diversa T19-1FS exhibits BGL activity making it interesting to explore its possible activity onto non-volatile glycosides during fermentation, to enhance aromatic compounds. Regarding the rest of the NS yeast studied, they could be good candidates for use in mixed-fermentations with Saccharomyces.
THE EFFECT OF SOME HORMONES ON THE IN VITRO CULTURE OF DATE PALM ( PHOENIX DACTYLIFERA L.) OF BOU-SAÂDA, ALGERIA

The Oasis of Bou-Saada is gradually deteriorating due to the attack of insect pests such as white scale Parlatoria blanchardi Targ. , the palm worm Myeloïs ceratoniae Zell and some fungal pests. In addition, polluted irrigation water coming from the wadi Bou-Saada has seriously damaged the oasis palm. Consequently, 23 promising date palm varieties are facing extinction. The Rehabilitation of the oasis palms of Bou-Saâda requires mass propagation of the endangered date palm varieties to conserve the fauna and the genotypes. The Tissue Culture technique is the only method through which date palm oases Bou-Saâda can be restored in a short period as compared to growing the trees through seeds or offshoots. As the first phase of conservation of the oases, this research project was initiated whereas propagation of two highly promising varieties Deglet-Nour and Mech-Degla was carried out through tissue culture technique on MS medium using various concentrations of three different hormones (AIB, GA3, 2,4-D) to obtain organogenesis. Results revealed that the growth in length of explants of the variety Deglet-Nour and its overall development was better as compared to the variety Mech-Degla with the AIB (2mg/l). The GA3 hormone performed the best in relation to the development of organogenesis in the two varieties followed by AIB hormone than the 2,4-D with overall mean lengths of 1.36, 1,26 and 0.84 centimetres, respectively. The formation of the callus was noticed only in the case of the variety Deglet-Nour .
AmpFuzz: Fuzzing for Amplification DDoS Vulnerabilities

Amplification DDoS attacks remain a prevalent and severe threat to the Internet, with recent attacks reaching the Tbps range. However, all amplification attack vectors known to date were either found by researchers through laborious manual analysis or could only be identified postmortem following large attacks. Ideally, though, an attack vector is discovered and mitigated before the first attack can occur. To this end, we present A MP F UZZ , the first systematic approach to finding amplification vectors in UDP services in a protocol-agnostic way. A MP F UZZ is based on the state-of-the-art greybox fuzzing boosted by a novel technique to make fuzzing UDP-aware, which significantly increases performance. We evaluate A MP F UZZ on 28 Debian network services, where we (re-)discover 7 known and 6 previously unreported amplification vulnerabilities. ⊛ The author contributed while being employed at CISPA.
Effect of IBA on rooting of Acid lime ( Citrus aurantifolia Swingle) stem cuttings cv. PKM1

Effect of various concentrations of IBA and semi hard wood cuttings on the performance of rooting in acid lime ( Citrus aurantifolia Swingle) cv. PKM1 under mist was studied in the Horticulture College and Institute, Agricultural University, Periyakulam. The treatments of five IBA concentrations (500, 1000, 1500, 2000 and 2500 ppm) along with a control were prepared and treated with semi hardwood cuttings as quick dip method. The study was laid out in a Completely Randomized Block Design (CRD) with six treatments and five replications. The results revealed that cuttings treated with IBA of 2000 ppm (T 5 ) recorded the highest values of all the traits viz . , success per cent (80.72%), least number of days for sprouting (6.85 days), number of sprouts per cuttings (4.30), plant height (47.76 cm), shoot length (23.65 cm), number of leaves (43.52), root length (26.15 cm), fresh root weight (4.50 g) and dry root weight (1.80 g) followed by T4 (1500 ppm of IBA). Control (T1) (without IBA treatment) observed the lowest values of the traits like success per cent of cuttings (26.14%), longest days for sprouting (13.50 days), number of sprouts per cuttings (1.50), plant height (25.48 cm), shoot length (13.00 cm), number of leaves (22.15), root length (15.80 cm), fresh root weight (1.95 g) and dry root weight (0.85 g). It is suggested that semi-hardwood cutting treated with 2000 ppm (T 5 ) concentration of IBA gives the overall best performance for mass multiplication of acid lime.