Miracle-dz/UniFAR-FTUs huggingface dataset:
Spatial and temporal cross-cutting relationships between fault structures and slope failures along the outer Kumano Basin and Nankai accretionary wedge, SW Japan

Abstract New, high-resolution multi-beam bathymetric data from RV Sonne cruise SO251 show a widely variable surface morphology along the southern Kumano Basin and Nankai accretionary prism off SW Japan. Combined with a three-dimensional seismic volume, these data provide insight into the ubiquitous and varied nature of faulting typical of accretionary prism settings, a high number of submarine landslides across the entire study area that vary both spatially and temporally, a pronounced absence of slide deposit bathymetric manifestations, widely varied slope angles and a potential subducted seamount scar. We have mapped scars of 442 primary and 184 secondary landslides and have measured the areas evacuated by these slides. Most of the slides are completely disintegrative, so surficial landslide deposits are almost absent. The incidence with which temporally sequential slope failures and fault structures cross-cut themselves and one another provides evidence of potential failure pre-conditioning such as gas hydrates, pore fluid overpressures and bottom current activity. Seismic loading and slope over-steepening are then the most likely final trigger mechanisms to slope failure. The majority of observed landslides (64%) occur seawards of the outer ridge, providing insight into the relationship between surficial landsliding and subsurface tectonic processes along this accretionary prism.
Signal Processing: Image Communication

Most of the existing generic object localization algorithms usually give the plausible object locations without taking into consideration the saliency ordering of the proposal set. This paper presents a novel object proposal generation which ranks the key objects according to their saliency score in the proposal pool. First, we formulate a Bayesian framework for generating a probabilistic edgemap which is used to assign a saliency value to the edgelets. A conditional random field is then learnt for edge-labeling by effectively combining the edge features with the relative spatial layout of the edge segments. Lastly, we propose an objectness score for the generated proposal set by analyzing the salient object edge density completely lying within the candidate boxes. Extensive experiments on the benchmark PASCAL VOC 2007 and 2012 datasets demonstrate that the proposed method provides competitive performance against popular generic object detection techniques while using fewer number of proposals. Additionally, we demonstrate the applicability of the generated proposal set for content aware image retargeting.
Trust based Routing using Dominating Set Approach (TRDSA) in Wireless Ad-Hoc Networks

Secure routing protocols for Mobile Ad hoc Networks (MANETs) have been categorized based on the model used for enforcing security, methodology and information they use to make routing decisions. Some protocols are designed from scratch so as to incorporate security solutions and some are designed to provide security mechanisms into the existing routing protocols like DSDV[1], OLSR[2], AODV[3], DSR[4] etc. Several protocols for secure routing in ad-hoc networks have been proposed. But due to their limitations, there is a need to make them robust and more secure so that they can go well with the demanding requirements of ad hoc networks. We propose and design a new protocol Trust based Routing using Dominating Set Approach (TRDSA) which overcomes the shortcomings of existing protocols.
Better than a petaflop: The power of efficient experimental design

Recent advances in high-performance computing have pushed computational capabilities to a petaflop (a thousand trillion operations per second) in a single computing cluster. This breakthrough has been hailed as a way to fundamentally change science and engineering by letting people perform experiments that were previously beyond reach. But for those interested in exploring the I/O behavior of their simulation model, efficient experimental design has a much higher payoff at a much lower cost. A well-designed experiment allows the analyst to examine many more factors than would otherwise be possible, while providing insights that cannot be gleaned from trial-and-error approaches or by sampling factors one at a time. We present the basic concepts of experimental design, the types of goals it can address, and why it is such an important and useful tool for simulation. Ideally, this tutorial will entice you to use experimental designs in your upcoming simulation studies.
LiveRender: A Cloud Gaming System Based on Compressed Graphics Streaming

In cloud gaming systems, the game program runs at servers in the cloud, while clients access game services by sending input events to the servers and receiving game scenes via video streaming. In this paradigm, servers are responsible for all performance-intensive operations, and thus suffer from poor scalability. An alternative paradigm is called graphics streaming, in which graphics commands and data are offloaded to the clients for local rendering, thereby mitigating the server's burden and allowing more concurrent game sessions. Unfortunately, this approach is bandwidth consuming, due to large amounts of graphic commands and geometry data. In this paper, we present LiveRender, an open source gaming system that remedies the problem by implementing a suite of bandwidth optimization techniques including intra-frame compression, inter-frame compression, and caching, establishing what we call compressed graphics streaming. Experiments results show that the new approach is able to reduce bandwidth consumption by 52-73% compared to raw graphics streaming, with no perceptible difference in video quality and reduced response delay. Compared with the video streaming approach, LiveRender achieves a traffic reduction of 40-90% with even improved video quality and substantially smaller response delay, while enabling higher concurrency at the server.
A Hardware Implementation of the Soft Output Viterbi Algorithm for Serially Concatenated Convolutional Codes

This thesis outlines the hardware design of a soft output Viterbi algorithm decoder for use in a serially concatenated convolutional code system. Convolutional codes and their related structures are described, as well as the algorithms used to decode them. A decoder design intended for a field-programmable gate array is presented. Simulations of the proposed design are compared with simulations of a software reference decoder that is known to be correct. Results of the simulations are shown and interpreted, and suggestions for future improvements are given.
Layout Based Spam Filtering

Due to the constant increase in the volume of information available to applications in fields varying from medical diagnosis to web search engines, accurate support of similarity becomes an important task. This is also the case of spam filtering techniques where the similarities between the known and incoming messages are the fundaments of making the spam/not spam decision. We present a novel approach to filtering based solely on layout, whose goal is not only to correctly identify spam, but also warn about major emerging threats. We propose a mathematical formulation of the email message layout and based on it we elaborate an algorithm to separate different types of emails and find the new, numerically relevant spam types. Keywords— Clustering, layout, k-means, spam.
PHyTM: Persistent Hybrid Transactional Memory.

The availability of hardware transactional memory (HTM) and the feasibility of persistent hardware transactions make them a natural choice for in-memory database synchronization. However, limitations on the size of hardware transactions and the lack of progress guarantees by modern HTM implementations prevent some applications from obtaining the benefit of hardware transactional memory. In this paper, we study persistent hybrid TM, which allows hardware assisted ACID transactions to execute concurrently with pure software transactions. This allows applications to gain the benefit of persistent HTM while accommodating unbounded transactions with a high degree of concurrency. Our experiments demonstrate that PHyTM is fast and scalable for realistic workloads.
Application of Artiﬁcial Neural Networks to Predict the Intrinsic Solubility of Drug-Like Molecules

: Machine learning (ML) approaches are receiving increasing attention from pharmaceutical companies and regulatory agencies, given their ability to mine knowledge from available data. In drug discovery, for example, they are employed in quantitative structure–property relationship (QSPR) models to predict biological properties from the chemical structure of a drug molecule. In this paper, following the Second Solubility Challenge (SC-2), a QSPR model based on artiﬁcial neural networks (ANNs) was built to predict the intrinsic solubility ( logS 0 ) of the 100-compound low-variance tight set and the 32-compound high-variance loose set provided by SC-2 as test datasets. First, a training dataset of 270 drug-like molecules with logS 0 value experimentally determined was gathered from the literature. Then, a standard three-layer feed-forward neural network was deﬁned by using 10 ChemGPS physico-chemical descriptors as input features. The developed ANN showed adequate predictive performances on both of the SC-2 test datasets. Beneﬁts and limitations of ML approaches have been highlighted and discussed, starting from this case-study. The main ﬁndings conﬁrmed that ML approaches are an attractive and promising tool to predict logS 0 ; however, many aspects, such as data quality, molecular descriptor computation and selection, and assessment of applicability domain, are crucial but often neglected, and should be carefully considered to improve predictions based on ML.
Strengthen the Security of Cyberspace with Device-Independent Quantum Randomness

With the advancement of the information age, the risk of information security keeps increasing. Randomness is the core of network and information system security, and it is the basic support of the entire network trust system. In this paper, we introduce the concept of Device-Independent Quantum Random Number Generator (DIQRNG), which provides randomness with the highest security level. To better integrate with Information and Communications Technology (ICT) systems, we propose the principle and architectural framework of a randomness beacon based on DIQRNG. It is a public service that can be applied in multiple scenarios, such as contract signing and confidential disclosure. Its related application cases are also currently being studied in the ITU QIT4N focus group.
Analytical and Numerical Modelling of Consolidation by Sand Drains beneath a Circular Embankment

In the analysis of axisymmetric problems, it is often imperative that aspects of geometry, material properties and loading characteristics are either maintained as constants or represented by continuous functions in the circumferential direction. In the case of radial consolidation beneath a circular embankment by vertical drains (i.e. circular oil tanks or silos), the discrete system of vertical drains can be substituted by continuous concentric rings of equivalent drain walls. An equivalent value for the coefficient of permeability of the soil is obtained by matching the degree of consolidation of a unit cell model. A rigorous solution to the continuity equation of radial drainage towards cylindrical drain walls is presented and verified by comparing its results with existing unit cell model. The proposed model is then adopted to analyse the consolidation process by vertical drains at the Ska-Edeby circular test embankment (Area II). The calculated values of settlement, lateral displacement and excess pore water pressure indicate good agreement with the field measurements.
Analysis of VR Sickness and Gait Parameters During Non-Isometric Virtual Walking with Large Translational Gain

ACM Reference Format: Carlos A. Tirado Cortes, Hsiang-Ting Chen, and Chin-Teng Lin. 2019. Analysis of VR Sickness and Gait Parameters During Non-Isometric Virtual Walking with Large Translational Gain. In 25th ACM Symposium on Virtual Reality Software and Technology (VRST ’19), November 12–15, 2019, Parramatta, NSW, Australia. ACM, New York, NY, USA, 2 pages. https: //doi.org/10.1145/3359996.3364741
Stacked Ensembles of Information Extractors for Knowledge-Base Population by Combining Supervised and Unsupervised Approaches

The UTAustin team participated in two main tasks this year the Cold Start Slot Filling (CSSF) task and the Slot-Filler Validation/Ensembling task, which was divided into the filtering and ensembling subtasks. Our system uses stacking to ensemble multiple systems for the KBP slot filling task, as described in our ACL 2015 paper. We expand the stacking approach by allowing the classifier to also utilize additions features that are relevant to making a final decision. Stacking relies on supervised training and hence requires common systems from the 2014 data to be used as training. However, that approach has limitations on performance and therefore we propose a novel approach of combining the supervised approach with an unsupervised approach on the remaining systems. We believe this combination approach gives our best run for the ensembling task. In this paper, we also discuss strategies to handle Cold Start data which comes from multiple hops.
Enriched Event Streams: A General Platform For Empirical Studies On In-IDE Activities Of Software Developers

Current studies on software development either focus on the change history of source code from version-control systems or on an analysis of simplistic in-IDE events without context information. Each of these approaches contains valuable information that is unavailable in the other case. This work proposes enriched event streams, a solution that combines the best of both worlds and provides a holistic view on the in-IDE software development process. Enriched event streams not only capture developer activities in the IDE, but also specialized context information, such as source-code snapshots for change events. To enable the storage of such code snapshots in an analyzable format, we introduce a new intermediate representation called Simplified Syntax Trees (SSTs) and build C A RET, a platform that offers reusable components to conveniently work with enriched event streams. We implement FEEDBAG++, an instrumentation for VISUAL STUDIO that collects enriched event streams with code snapshots in the form of SSTs and share a dataset of enriched event streams captured in an ongoing field study from 81 users and representing 15K hours of active development. We complement this with a dataset of 69M lines of released source code extracted from 360 GITHUB repositories. To demonstrate the usefulness of our platform, we use it to conduct studies on the in-IDE development process that are both concerned with source-code evolution and the analysis of developer interactions. In addition, we build recommendation systems for software engineering and analyze and improve current evaluation techniques.
Task Similarity Aware Meta Learning: Theory-inspired Improvement on MAML (Supplementary File)

This supplementary document contains the technical proofs of the results and some additional experimental results of the UAI’21 paper entitled “Task Similarity Aware Meta Learning: Theory-inspired Improvement on MAML”. It is structured as follows. Appendix A ﬁrst provides more experimental details and presents more experimental results, including results on miniImageNet, robustness of initialization number, and comparison between TSA-MAML and MAML using larger model. Appendix B provides more theoretical results of MAML by analyzing its convergence behaviors. Then Appendix C gives the proofs of the main results in Sec. 3.2, including Theorems 1 and 2. Finally, in Appendix D we presents the proofs of Corollary 1 in Sec. 4. Appendix E presents the proof of the convergence of the MAML algorithm in Theorem 4.
Scanless fast handoff technique based on global Path-Cache

Wireless LANs (WLANs) have been widely adopted and are more convenient as they are inter-connected as wireless campus networks and wireless mesh networks. However, time-sensitive multimedia applications, which have become more popular, could suffer from long end-to-end latency in WLANs. This is due mainly to handoff delay, which in turn is caused by channel scanning. This paper proposes a technique called Global Path-Cache (GPC) that provides fast handoffs in WLANs. GPC properly captures the dynamic behavior of the network and MSs, and provides accurate next-AP predictions to minimize the handoff latency. Moreover, the handoff frequencies are treated Weetit Wanalertlak and Ben Lee School of Electrical Engineering and Computer Science Oregon State University Corvallis, OR, 97331, USA Tel. : 1-541-737-3148 E-mail: {wanalewe,benl}@eecs.orst. edu Chansu Yu Department of Electrical and Computer Engineering Cleveland State University Cleveland, OH 44115, USA and WCU Division of IT Convergence Engineering Pohang University of Science and Technology (POSTECH) San 31, Hyoja, Pohang, Gyeongbuk, Korea 790-784 E-mail: c.yu91@csuohio.edu Myungchul Kim Department of Computer Science Korea Advanced Institute of Science and Technology (KAIST) 119 Munji-ro, Yuseong-gu, Daejeon, 305-702, Korea E-mail: mckim@cs.kaist. ac.kr Seung-Min Park and Won-Tae Kim Electronics Telecommunications Research Institute (ETRI) Daejeon, Korea E-mail: {minpark,wtkim}@etri.re. kr 2 Weetit Wanalertlak et al. as time-series data, thus GPC calibrates the prediction models based on short term and periodic behaviors of mobile users. Our simulation study shows that GPC virtually eliminates the need to scan for APs during handoffs and results in much better overall handoff delay compared to existing methods.
ECG-based personal identification using empirical mode decomposition and Hilbert transform

Security concerns give biometrics an important role in security solutions. There is strong evidence that we can use electrocardiogram (ECG) signals to identify individuals. In other words, they contain sufficient discriminative information to allow the identification of individuals from a large population. Therefore, this paper presents an individual identification system using 20 healthy subjects from Physikalisch-Technische Bundesanstalt (PTB) database. In this way, Empirical mode decomposition (EMD) is used to decompose our signals to their base component. Then, the instantaneous frequency of the last component is computed by using Hilbert transform. Finally, 1 nearest neighbor (1NN) classifier is utilized to identify the accuracy of our method. With this procedure, we obtained a high identification rate (93.22%).
Uniform Generation of Np-witnesses Using an Np-oracle Work Done While Being on a Sabbatical Leave at Mit

A Uniform Generation procedure for NP is an algorithm which given any input in a xed NP-language, outputs a uniformly distributed NP-witness for membership of the input in the language. We present a Uniform Generation procedure for NP that runs in probabilistic polynomial-time with an NP-oracle. This improves upon results of Jerrum, Valiant and Vazirani, which either require a P2 oracle or obtain only almost uniform generation. Our procedure utilizes ideas originating in the works of Sipser, Stockmeyer, and Jerrum, Valiant and Vazirani. Dept. of Computer Science & Engineering, University of California at San Diego, 9500 Gilman Drive, La Jolla, California 92093, USA. E-Mail: mihir@cs.ucsd. edu. URL: http://www-cse.ucsd. edu/users/mihir. Supported in part by NSF CAREER Award CCR-9624439 and a 1996 Packard Foundation Fellowship in Science and Engineering. yDepartment of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel. E-Mail: oded@wisdom.weizmann. ac.il. Work done while being on a sabbatical leave at MIT. zIBM Haifa Research Lab, MATAM, Haifa 31905, Israel. Email: erezp@haifa.vnet. ibm.com.
What Accounts For the Rise in Wage Inequality in Italy? Evidence from Administrative Matched Employer-Employee Data, 1985-1996

This paper provides new empirical evidence on the changes in the Italian wage distribution using administrative data from 1985 to 1996. Various statistical indicators are used to document a slight, but not negligible, increase in wage inequality. Standard decompositions of inequality indices by population subgroups shed light on the underlying causes of the observed distributional changes. Following Junh et al. (1993), econometric-type decompositions are also employed to disentangle the effects of observable quantities, prices and unobservable factors on inequality trends. The changing prices of observable characteristics are found to play a major role in accounting for the observed inequality increase.
Title : A Principled Approach to Selective Context Sensitivity for Pointer Analysis

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Communications of the IIMA Communications

Financial articles can move stock prices. The terms used in an article can be a predictor of both price direction and the magnitude of movement. By investigating the usage of terms in financial news articles and coupling them with a discrete machine-learning algorithm, we can build a model of short-term price movement. From our research, we investigated the terms creating the largest price movements amongst five part of speech textual representations; bag of words, noun phrases, named entities, proper nouns and verbs.
A New Wave Equation Based Source Location Method with Full-waveform Inversion

Locating the source of a passively recorded seismic event is still a challenging problem, especially when the velocity is unknown. Many imaging approaches to focus the image do not address the velocity issue and result in images plagued with illumination artifacts. We develop a waveform inversion approach with an additional penalty term in the objective function to reward the focusing of the source image. This penalty term is relaxed early to allow for data fitting, and avoid cycle skipping, using an extended source. At the later stages the focusing of the image dominates the inversion allowing for high resolution source and velocity inversion. We also compute the source location explicitly and numerical tests show that we obtain good estimates of the source locations with this approach.
CONTRIBUTION TO THE GENESIS OF THERMAL WATER OF THE NORTH-EAST PERIMETER OF THE ZENICA-SARAJEVO BASIN, BOSNIA AND HERZEGOVINA

The phenomena of thermal waters in the northeastern periphery of the Zenica-Sarajevo basin is caused by the geological structure, structural-tectonic and hydrogeological characteristics of the terrain. The genesis had not been fully addressed before. This paper presents the study of the genesis of thermal waters based on the geological structure, structural-tectonic and hydrogeological characteristics of the terrain, and physiochemical and isotopic composition of water. The results provide a new contribution to the structure of this part of the Zenica-Sarajevo basin and create a more realistic foundation for the future research of thermal water in this area.