Miracle-dz/UniFAR-FTUs huggingface dataset:
Strengthened Cutset Upper Bounds on the Capacity of the Relay Channel and Applications

We establish new upper bounds on the capacity of the relay channel which are tighter than all previous bounds. The upper bounds use traditional weak converse techniques involving mutual information inequalities and identification of auxiliary random variables via past and future channel random variable sequences. For the relay channel without selfinterference, we show that the new bound is strictly tighter than all previous bounds for the Gaussian relay channel for every set of non-zero channel gains. When specialized to the class of relay channels with orthogonal receiver components, the bound resolves a conjecture by Kim on a class of deterministic relay channels. When further specialized to the class of product-form relay channels with orthogonal receiver components, the bound resolves a generalized version of Cover’s relay channel problem, recovers the recent upper bound for the Gaussian case by Wu et al. and extends it to the nonsymmetric case, and improves upon the recent bounds for the binary symmetric case by Wu et al. and Barnes et al., which are all obtained using non-traditional geometric proof techniques.
A 300 nW, 15 ppm/$^{\circ}$C, 20 ppm/V CMOS Voltage Reference Circuit Consisting of Subthreshold MOSFETs

A low-power CMOS voltage reference was developed using a 0.35 mum standard CMOS process technology. The device consists of MOSFET circuits operated in the subthreshold region and uses no resistors. It generates two voltages having opposite temperature coefficients and adds them to produce an output voltage with a near-zero temperature coefficient. The resulting voltage is equal to the extrapolated threshold voltage of a MOSFET at absolute zero temperature, which was about 745 mV for the MOSFETs we used. The temperature coefficient of the voltage was 7 ppm/degC at best and 15 ppm/degC on average, in a range from - 20 to 80degC. The line sensitivity was 20 ppm/V in a supply voltage range of 1.4-3 V, and the power supply rejection ratio (PSRR) was -45 dB at 100 Hz. The power dissipation was 0.3 muW at 80degC. The chip area was 0.05 mm2 . Our device would be suitable for use in subthreshold-operated, power-aware LSIs.
Broadcasting four types of reports to read only transactions in mobile computing environments

Purpose – Recently the advances in wireless communication technology and the popularity of portable computers have rendered mobile computing environments from which mobile users with battery‐operated palmtops can access the information via wireless channels, without space and time restriction. In mobile computing environments, mobile users cache the data items to use the bandwidth efficiently and improve the response time of mobile transactions. If the data items cached in mobile users are updated at the server, the server broadcasts an invalidation report for maintaining the cache consistency of mobile users. However, this method has an obstacle that does not guarantee the serializable execution of mobile transactions. The purpose of this paper is to propose the four types of reports for mobile transaction (FTR‐MT) method for ensuring the serializable execution of mobile transactions.Design/methodology/approach – The paper describes the FTR‐MT method, which is composed of four types of algorithms, e.g. g.
A reference monitor for workflow systems with constrained task execution

We describe a model, independent of any underlying access control paradigm, for specifying authorization constraints such as separation of duty and cardinality constraints in workflow systems. We present a number of results enabling us to simplify the set of authorization constraints. These results form the theoretical foundation for an algorithm that can be used to determine whether a given constrained workflow can be satisfied: that is, does there exist an assignment of authorized users to workflow tasks that satisfies the authorization constraints? We show that this algorithm can be incorporated into a workflow reference monitor that guarantees that every workflow instance can complete. We derive the computational complexity of our algorithm and compare its performance to comparable work in the literature.
Forked! A demonstration of physics realism in augmented reality

In making fully immersive augmented reality (AR) applications, real and virtual objects will have to be seen to physically interact together in a realistic and believable way. This paper describes Forked! a system that has been developed to show how physical interactions between real and virtual objects can be simulated realistically and believably through appropriate use of a physics engine. The system allows users control a robotic forklift to manipulate virtual crates in an AR environment. The paper also describes a evaluation experiment in which it is shown that the physical interactions between the forklift and the virtual creates are realistic and believable enough to be comparable with the physical interactions between a forklift and real crates.
Security Issues in Language-based Sofware Ecosystems

Language-based ecosystems (LBE), i.e., software ecosystems based on a single programming language, are very common. Examples include the npm ecosystem for JavaScript, and PyPI for Python. These environments encourage code reuse between packages, and incorporate utilities - package managers - for automatically resolving dependencies. However, the same aspects that make these systems popular - ease of publishing code and importing external code - also create novel security issues, which have so far seen little study. We present an a systematic study of security issues that plague LBEs. These issues are inherent to the ways these ecosystems work and cannot be resolved by fixing software vulnerabilities in either the packages or the utilities, e.g., package manager tools, that build these ecosystems. We systematically characterize recent security attacks from various aspects, including attack strategies, vectors, and goals. Our characterization and in-depth analysis of npm and PyPI ecosystems, which represent the largest LBEs, covering nearly one million packages indicates that these ecosystems make an opportune environment for attackers to incorporate stealthy attacks. Overall, we argue that (i) fully automated detection of malicious packages is likely to be unfeasible; however (ii) tools and metrics that help developers assess the risk of including external dependencies would go a long way toward preventing attacks.
Domain Specific Languages for Interactive Web Services

This dissertation shows how domain specific languages may be applied to the domain of interactive Web services to obtain flexible, safe, and efficient solutions. We show how each of four key aspects of interactive Web services involving sessions, dynamic creation of HTML/XML documents, form field input validation, and concurrency control, may benefit from the design of a dedicated language. Also, we show how a notion of metamorphic syntax macros facilitates integration of these individual domain specific languages into a complete language. The result is a domain specific language, <bigwig>, that supports virtually all aspects of the development of interactive Web services and provides flexible, safe, and efficient solutions.
MultiProperties

Properties, which occur in C#, provide good support for features of objects with singular multiplicity and allow straightforward implementation and use of an object's encapsulated state. If, however, used for features with a higher multiplicity, usually represented by collection objects, they fail to provide a natural approach to proper encapsulation of the one-to-many aspect of such characteristics.
High‐latitude dayside electric fields and currents during strong northward interplanetary magnetic field: Observations and model simulation

On July 23, 1983, the Interplanetary Magnetic Field turned strongly northward, becoming about 22 nT for several hours. Using a combined data set of ionospheric convection measurements made by the Sondre Stromfjord incoherent scatter radar and convection inferred from Greenland magnetometer measurements, we observe the onset of the reconfiguration of the high-latitude ionospheric currents to occur about 3 min following the northward IMF encountering the magnetopause. The large-scale reconfiguration of currents, however, appears to evolve over a period of about 22 min. Using a computer model in which the distribution of field-aligned current in the polar cleft is directly determined by the strength and orientation of the interplanetary electric field, we are able to simulate the time-varying pattern of ionospheric convection, including the onset of high-latitude “reversed convection” cells observed to form during the interval of strong northward IMF. These observations and the simulation results indicate that the dayside polar cap electric field observed during strong northward IMF is produced by a direct electrical current coupling with the solar wind.
Exact Decoding for Phrase-Based Statistical Machine Translation

The combinatorial space of translation derivations in phrase-based statistical machine translation is given by the intersection between a translation lattice and a target language model. We replace this intractable intersection by a tractable relaxation which incorporates a low-order upperbound on the language model. Exact optimisation is achieved through a coarseto-fine strategy with connections to adaptive rejection sampling. We perform exact optimisation with unpruned language models of order 3 to 5 and show searcherror curves for beam search and cube pruning on standard test sets. This is the first work to tractably tackle exact optimisation with language models of orders higher than 3.
Combined Approach for Supporting the Business Process Model Lifecycle

Business processes evolve throughout their lifecycle of change. Business Process Modeling (BPM 2 ) notations such as BPMN are used to effectively conceptualize and communicate important process characteristics to relevant stakeholders. Agent-oriented conceptual modeling notations, such as i*, effectively capture and communicate organizational context. In this paper we argue that the management of change throughout the business process model lifecycle can be more effectively supported by combining notations. In particular, we identify two potential sources of process change, one occurring within the organizational context and the other within the operational context. As such the focus in this paper is on the co-evolution of operational (BPMN) and organizational (i*) models. Our intent is to provide a way of expressing changes, which arise in one model, effectively in the other model. We present constrained development methodologies capable of guiding an analyst when reflecting changes from an i* model to a BPMN model and vice-versa.
Volcanic ash layers from the Last Glacial Termination in the NGRIP ice core

The tephrochronological record of the 1400–1640 m depth (∼10 000–16 000 calendar ice core years before present) of the NGRIP ice core has been established by particle screening of selected samples. Ash was identified in 20 samples. Correlation with ice, marine and terrestrial records from volcanic source regions in the northern hemisphere positively identifies the Saksunarvatn Ash and the Vedde Ash (Ash Zone 1). Major element chemistry of the remaining identified ash layers mainly points towards an Icelandic origin. This tephrochronological record provides new important marker horizons for correlating the timing of the climatic changes associated with the Last Glacial Termination within the North Atlantic region, as well as outlining more details concerning the frequency and composition of volcanic eruptions occurring at this deglaciation. Copyright © 2005 John Wiley & Sons, Ltd.
University of Toronto

Present: Professor W. Raymond Cummins, Chair Professor Brian Corman, ViceChair Professor C. David Naylor, President Professor Vivek Goel, VicePresident and Provost Professor John Challis, VicePresident, Research and Associate Provost Professor S. Zaky, ViceProvost, Planning and Budget Professor Rona Abramovitch Mr. Navine K. Aggarwal Professor Stewart Aitchison Mrs. Mubarka Alam Professor Jan Angus Professor Gage Averill Professor George Baird Professor Clare Beghtol Professor Katherine Berg Professor Donald Brean Professor Philip H. Byer Mr. Blake Chapman Mr. Ewen Weili Chen Professor David Clandfield Professor John Coleman Professor David Cook
Approximate query service on autonomous IoT cameras

Elf is a runtime for an energy-constrained camera to continuously summarize video scenes as approximate object counts. Elf's novelty centers on planning the camera's count actions under energy constraint. (1) Elf explores the rich action space spanned by the number of sample image frames and the choice of per-frame object counters; it unifies errors from both sources into one single bounded error. (2) To decide count actions at run time, Elf employs a learning-based planner, jointly optimizing for past and future videos without delaying result materialization. Tested with more than 1,000 hours of videos and under realistic energy constraints, Elf continuously generates object counts within only 11% of the true counts on average. Alongside the counts, Elf presents narrow errors shown to be bounded and up to 3.4X smaller than competitive baselines. At a higher level, Elf makes a case for advancing the geographic frontier of video analytics.
Rhythmic Till Sedimentation: Evidence for Repeated Hydraulic Lifting of a Stagnant Ice Mass

The youngest sedimentary facies exposed in erosional hummocky terrain in south-central Alberta, Canada, is composed of alternating beds of massive silty clay diamicton, and sorted sand and/or silt. Diamicton beds are similar in thickness (5-20 cm), both laterally and vertically, within the sequence, and sedimentary structures and consistent clast orientations support a subglacial origin for both the diamicton and the sorted sediment. Alternation between diamicton and sorted strata document rhythmic sedimentary sequences: deposition of melt-out till followed by current deposition. Laterally extensive sorted beds indicate that the currents responsible for sand and silt deposition must have flowed as a sheet. This flow was shallow, no more than 20 cm, indicated by scours below boulders that were suspended from the base of glacial ice. Sheet flow requires that the water was stored beneath the ice prior to drainage. Consequently, some of the diamicton may have been deposited by rain-out through the shallow stored water and, hence, each diamicton bed may represent a combination of direct melt-out onto the bed and rain-out through the water column. Inferred cycles of water accumulation and drainage may have been annual.
Sparse Bayesian Learning with Diagonal Quasi-Newton Method For Large Scale Classification

—Sparse Bayesian Learning (SBL) constructs an extremely sparse probabilistic model with very competitive generalization. However, SBL needs to invert a big covariance matrix with complexity 𝑶(𝑴 𝟑 ) ( M : feature size) for updating the regularization priors, making it difficult for practical use. There are three issues in SBL: 1) Inverting the covariance matrix may obtain singular solutions in some cases, which hinders SBL from convergence; 2) Poor scalability to problems with high dimensional feature space or large data size; 3) SBL easily suffers from memory overflow for large-scale data. This paper addresses these issues with a newly proposed diagonal Quasi-Newton (DQN) method for SBL called DQN-SBL where the inversion of big covariance matrix is ignored so that the complexity and memory storage are reduced to 𝑶(𝑴) . The DQN-SBL is thoroughly evaluated on non-linear classifiers and linear feature selection using various benchmark datasets of different sizes. Experimental results verify that DQN-SBL receives competitive generalization with a very sparse model and scales well to large-scale problems.
Predicting transcription factor affinities to DNA from a biophysical model

MOTIVATION Theoretical efforts to understand the regulation of gene expression are traditionally centered around the identification of transcription factor binding sites at specific DNA positions. More recently these efforts have been supplemented by experimental data for relative binding affinities of proteins to longer intergenic sequences. The question arises to what extent these two approaches converge. In this paper, we adopt a physical binding model to predict the relative binding affinity of a transcription factor for a given sequence. RESULTS We find that a significant fraction of genome-wide binding data in yeast can be accounted for by simple count matrices and a physical model with only two parameters. We demonstrate that our approach is both conceptually and practically more powerful than traditional methods, which require selection of a cutoff. Our analysis yields biologically meaningful parameters, suitable for predicting relative binding affinities in the absence of experimental binding data. AVAILABILITY The C source code for our TRAP program is freely available for non-commercial use at http://www.molgen. mpg.de/~manke/papers/TFaffinities/
Adaptive Smoothing for Path Integral Control

In Path Integral control problems a representation of an optimally controlled dynamical system can be formally computed and serve as a guidepost to learn a parametrized policy. The Path Integral Cross-Entropy (PICE) method tries to exploit this, but is hampered by poor sample eﬃciency. We propose a model-free algorithm called ASPIC (Adaptive Smoothing of Path Integral Control) that applies an inf-convolution to the cost function to speedup convergence of policy optimization. We identify PICE as the inﬁnite smoothing limit of such technique and show that the sample eﬃciency problems that PICE suﬀers disappear for ﬁnite levels of smoothing. For zero smoothing, ASPIC becomes a greedy optimization of the cost, which is the standard approach in current reinforcement learning. ASPIC adapts the smoothness parameter to keep the variance of the gradient estimator at a predeﬁned level, independently of the number of samples. We show analytically and empirically that intermediate levels of smoothing are optimal, which renders the new method superior to both PICE and direct cost optimization.
Synchronization of Elliptic Bursters

Periodic bursting behavior in neurons is a recurrent transition between a quiescent state and repetitive spiking. When the transition to repetitive spiking occurs via a subcritical Andronov--Hopf bifurcation and the transition to the quiescent state occurs via fold limit cycle bifurcation, the burster is said to be of elliptic type (also known as a "subHopf/fold cycle" burster). Here we study the synchronization dynamics of weakly connected networks of such bursters. We find that the behavior of such networks is quite different from the behavior of weakly connected phase oscillators and resembles that of strongly connected relaxation oscillators. As a result, such weakly connected bursters need few (usually one) bursts to synchronize, and synchronization is possible for bursters having quite different quantitative features. We also find that interactions between bursters depend crucially on the spiking frequencies. Namely, the interactions are most effective when the presynaptic interspike frequency matches the frequency of postsynaptic oscillations. Finally, we use the FitzHugh--Rinzel, Morris--Lecar, and Hodgkin--Huxley models to illustrate our major results.
Boosting Adversarial Attack with Similar Target

Deep neural networks are vulnerable to adversarial examples, posing a threat to the models’ applications and raising security concerns. An intriguing property of adversarial examples is their strong transferability. Several methods have been proposed to enhance transferability, including ensemble attacks which have demonstrated their efficacy. However, prior approaches simply average logits, probabilities, or losses for model ensembling, lacking a comprehensive analysis of how and why model ensembling significantly improves transferability. In this paper, we propose a similar targeted attack method named Similar Target (ST). By promoting cosine similarity between the gradients of each model, our method regularizes the optimization direction to simultaneously attack all surrogate models. This strategy has been proven to enhance generalization ability. Experimental results on Ima-geNet validate the effectiveness of our approach in improving adversarial transferability. Our method outperforms state-of-the-art attackers on 18 discriminative classifiers and adversar-ially trained models.
A Comparison of Classification Methods for Expression Quantitative Trait Loci

The functional impact of regulatory variation in the human genome remains largely unexplored. One group of regulatory variants called expression quantitative trait loci (eQTLs) has become the focus of recent large scale efforts to identify variants that effect gene regulation [2, 6, 9, 10]. eQTLs refer to non-coding variants that influence the expression of a nearby gene such that individuals homozygous for one allele of the gene will show decreased expression relative to individuals homozygous for the other allele. In addition to influencing expression, eQTLs are enriched for disease causing variants and variants that influence molecular phenotypes such as chromatin modifications [2, 4]. Thus, these variants are of important biological interest for addressing disease etiology. Until recently, the study of eQTLs has focused primarily on discovery using simple linear models [2, 6, 9, 10]. Only a handful of studies have sought to build more complex models for the purpose of eQTL classification [2, 4]; these studies have been limited in the scope of models investigated. In this project, we examine four main classification methods for eQTL detection: 1) logistic regression, 2) decision trees and random forests, 3) support vector machines (SVM), and 4) neural networks. Our goal is to build a classification model to predict whether a variant influences gene expression using only publicly available genomic annotation. This model will therefore be able to classify eQTLs rapidly without the need of gene expression data, greatly improving our ability to interpret functional variation in the noncoding genome. In addition, by examining which features/annotations are most informative for eQTL classification, we can make meaningful inferences regarding the underlying biology of eQTLs.
Discourse Strategies for Attention-Limited Agents

This paper presents results on the role of limited attention and inference in dialogue and the eect of discourse strategies that interact with these limitations. These factors are explored through a dialogue simulation environment , Design-World, in which two ar-ticial agents collaborate to perform a simple design task. The results are based on several experiments carried out in this environment. These experimental results demonstrate that discourse strategies that incorporate redundant information can be benecial when agents have limited resources for attention and inference.