Miracle-dz/UniFAR-FTUs huggingface dataset:
A Coalgebraic Decision Procedure for NetKAT

Program equivalence is a fundamental problem that has practical applications across a variety of areas of computing including compilation, optimization, software synthesis, formal veriﬁcation, and many others. Equivalence is undecidable in general, but in certain settings it is possible to develop domain-speciﬁc languages that are expressive enough to be practical and yet sufﬁciently restricted so that equivalence remains decidable. In previous work we introduced NetKAT, a domain-speciﬁc language for specifying and verifying network packet-processing functions. NetKAT provides familiar constructs such as tests, assignments, union, sequential composition, and iteration as well as custom primitives for modifying packet headers and encoding network topologies. Semantically, NetKAT is based on Kleene algebra with tests (KAT) and comes equipped with a sound and complete equational theory. Although NetKAT equivalence is decidable, the best known algorithm is hardly practical—it uses Savitch’s theorem to determinize a PSPACE algorithm and requires quadratic space. This paper presents a new algorithm for deciding NetKAT equivalence. This algorithm is based on ﬁnding bisimulations be-tween ﬁnite automata constructed from NetKAT programs. We investigate the coalgebraic theory of NetKAT, generalize the notion of Brzozowski derivatives to NetKAT, develop efﬁcient representations of NetKAT automata in terms of spines and sparse matrices, and discuss the highlights of our prototype implementation.
Support vector machines

Support vector machines (SVMs) are a family of machine learning methods, originally introduced for the problem of classification and later generalized to various other situations. They are based on principles of statistical learning theory and convex optimization, and are currently used in various domains of application, including bioinformatics, text categorization, and computer vision. Copyright © 2009 John Wiley & Sons, Inc.
Cognitive Walkthrough for the Web

The Cognitive Walkthrough for the Web (CWW) is a theory-based usability inspection method for detecting and correcting design errors that interfere with finding information on a website (Blackmon, et al. 2002, 2003). CWW, like the original Cognitive Walkthrough (see 2.), simulates step-by-step user behaviour for a given task and assumes that users perform goal-driven exploration. But CWW is specially tailored to simulate users navigating a website and better fits a realistic website design process, considering three features specific to website design. First, CWW uses realistic narrative descriptions of user goals that incorporate rich information about users' understanding of their tasks and underlying motivation. Second, CWW assumes that generating an action on a webpage (e.g., clicking a link, button, or other widget) is a two-step process. Step one is an attention process that parses a webpage into subregions and attends to the subregion of the page that is semantically most similar to the user goal. Step two is an action selection process that selects and acts on a widget from the attended-to subregion, the widget semantically most similar to the user goal. This two-step CWW web navigation mechanism is derived from a theory of the cognitive processes that control goal driven exploration, CoLiDeS (Kitajima et al., 2000). CoLiDeS, an acronym for Comprehension-based Linked model of Deliberate Search, extends a series of earlier models of performing by exploration based on Kintsch's construction-integration theory of text comprehension and problem solving processes (Kintsch, 1998). CoLiDeS is part of a broad consensus among theorists and website usability experts that problem solving processes, guided by users' goals and information scent, drive users' information-seeking or search behaviours when exploring a new website or carrying out a novel task on a familiar website (see 4. for models of web navigation). Third, the CWW evaluation process can balance competing constraints by working on web pages in relation to a whole set of representative user goals. The CWW evaluation process can start with only a 3 detailed description of the home page and a rough outline of its immediate successor pages, and can then be applied repeatedly to incrementally design and evaluate each successor page down through the hierarchy. CW is a usability evaluation approach that predicts how easy it will be for people to learn to do particular tasks on a computer-based system. It is crucial to design systems for ease of learning, because people generally learn to use …
A suggestive interface for 3D drawing

This paper introduces a new type of interface for 3D drawings that improves the usability of gestural interfaces and augments typical command-based modeling systems. In our suggestive interface, the user gives hints about a disired operation to the system by highlighting related geometric components in the scene. The system then infers possible operations based on the hints and presents the results of these operations as small thumbnails. The user complets the editing operation simply by clicking on the disired thumbnail. The hinting mechanism lets the user specify geometric relations among graphical components in the scene, and the multiple thumbnail suggestions make it possible to define many operations with relatively few distinct hint patterns. The suggestive interface system is implemented as a set o suggestion engines working in parallel, and is easily extended by adding customized engines. Our prototype 3D drawing system, Chateau, shows that a suggestive interface can effectively support construction of various 3D drawings.
A Dissertation Submitted to the Department of Geophysics and the Committee on Graduate Studies of Stanford University in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy

This dissertation addresses the problem of seismic noise attenuation by using inversion. Two types of noise are considered. First, spiky noise, which is attenuated with a robust error measure called the Huber norm. This norm treats small residual with the `2 norm and large residuals with the `1 norm. It is continuous everywhere and can be minimized with a standard gradient-based solver. In this thesis, the well-known quasi-Newton method L-BFGS is used. The Huber norm and the L-BFGS solver are flexible enough to be used in many different situations, such as velocity analysis and regridding of noise bathymetry data. Another powerful application of the Huber norm is adaptive subtraction of surface-related multiples. In this case, weak multiples in the vicinity of strong primaries are better removed with the Huber norm than with `2. Second, coherent noise, which is attenuated by making the residual components of any least-squares fitting of contaminated data independent and identically distributed (IID). To achieve this goal, a weighting and a modeling approach are introduced. The weighting approach aims at approximating the inverse data covariance operator (or matrix) with multidimensional prediction-error filters (PEFs). The modeling approach introduces a coherent noise modeling operator inside the inversion. The modeling technique converges usually better than the weighting approach and yields smaller residuals. One advantage of the weighting approach, however, is that it can be used to separate nonstationary signal and non-stationary noise with PEFs. In this case, the separation is called pattern-based because it involves the multivariate noise and signal spectra that PEFs approximate. For removal of surface-related multiples, this technique proves being more robust to v modeling inadequacies than adaptive subtraction with the `2 norm, as exemplified on marine 2-D and 3-D field data examples.
Visual-spatial perception: a comparison between instruments frequently used in the primary care setting and a computerized cognitive assessment battery

Background: The development of screening instruments will help the primary care team to determine when further comprehensive cognitive assessment is necessary. Design: A retrospective analysis based on medical records. Patients and setting: Patients referred to a comprehensive geriatric assessment unit. Analysis: Cognitive screening and assessment included visual-spatial components: the Mini Mental State Examination, the Clock Drawing Test, the Montreal Cognitive Assessment Test, and the Neurotrax (Mindstreams) computerized cognitive assessment battery. Results: The average age of the 190 eligible patients was 81.09 ± 5.42 years. Comparing the individual tests with that of the visual-spatial index of Neurotrax, we found the Trail Making B test to be most sensitive (72.4%) and the Cube Test to have the highest specificity (72.8%). A combination of tests resulted in higher sensitivity and lower specificity. Conclusion: The use of a combination of visual-spatial tests for screening in neurocognitive disorders should be evaluated in further prospective studies.
DIFFERENTIAL MICROSCOPY IN OFF-AXIS TRANSMISSION ELECTRON MICROSCOPE HOLOGRAPHY

Differential microscopy is realized by conventional off-axis electron holography with an electron biprism behind the specimen. Two phase images reconstructed from two holograms obtained with slightly different potentials of the electron biprism are utilized to make a one-dimensional differential image. Polystyrene latex particles which are charged by electron irradiation and a barium ferrite particle which has a single magnetic domain were used to demonstrate that the differential image is independent of the distortion of the reference wave.
Joint COCO and LVIS workshop at ECCV 2020: LVIS Challenge Track Technical Report: Seesaw Loss for Long-Tailed Instance Segmentation

This report presents the approach used in the submission of the LVIS Challenge 2020 of team MMDet. In the submission, we propose Seesaw Loss that dynamically rebalances the penalty to each category according to a relative ratio of cumulative training instances between different categories. Furthermore, we propose HTC-Lite, a light-weight version of Hybrid Task Cascade (HTC) which replaces the semantic segmentation branch by a global context encoder. Seesaw Loss improves the strong baseline by 6.9% AP on LVIS v1 val split. With a single model, and without using external data and annotations except for standard ImageNet-1k classification dataset for backbone pre-training, our submission achieves 38.92% AP on the test-dev split of the LVIS v1 benchmark.
Kobe University, NICT and University of Siegen at TRECVID 2016 AVS Task

We submit the following three runs for the TRECVID 2016 AVS task. 1) kobe nict siegen D M 1: This combines the results of several small-scale multi-layer neural networks, called micro neural networks (microNNs). Although a large number of concepts are necessary for treating various queries, the computational cost of preparing detectors for all these concepts is huge. Thus we use microNNs as lightweight concept detectors. The input of each microNN is a vector of outputs extracted by a pre-trained convolutional neural network (CNN), which is fine-tuned to a target concept using ImageNet and/or IACC video data. Fine-tuning is carried out using imbalanced numbers of positive and negative data. 2) kobe nict siegen D M 2: This is identical to kobe nict siegen D M 1 except that fine-tuning is performed using the same numbers of positive and negative data. 3) kobe nict siegen D M 3: This combines the results of several long short-term memory (LSTM) networks for different concepts. The input of each LSTM is a vector of outputs extracted by a pre-trained CNN, which is finetuned to a target concept using ImageNet and/or IACC video data. The numbers of positive and negative data are imbalanced for fine-tuning. The results of these runs validate the efficiency of training microNNs for various concepts and their usefulness for achieving reasonable retrieval performances. Furthermore, LSTMs significantly improve the retrieval results for some queries.
Conceptual Evaluation of Weblog as a Computer Mediated Communication Application

Weblog is fast becoming an unprecedented mode of communication and self-expression for both individuals and communities. It offers users an avenue to express their opinions regarding anything that come to their minds, from current news items to documenting their lives and thoughts. Bewildered by its rapid growth and widespread popularization, researchers have sought to understand the “exquisiteness” of weblog as a form of computer-mediated communication (CMC). Despite the increasing effort to understand weblog as an informal channel of communique, our understanding of weblog remains modest, mainly because much of the extant research has been directed towards categorizing different forms of weblog based on content analyses and identifying factors that motivate people to blog. However, establishing weblog as a CMC application is crucial for providing the basis for cumulative research tradition. This paper draws from CMC theories – media richness and media synchronicity, to assess weblog and seeks to identify research directions.
In silico repurposed drugs against monkeypox virus

Monkeypox is an emerging epidemic of concern. The disease is caused by the monkeypox virus and an increasing global incidence with a 2022 outbreak that has spread to Europe amid the COVID-19 pandemic. The new outbreak is associated with novel, previously undiscovered mutations and variants. Currently the US Food and Drug Administration (FDA) approved poxvirus treatment involves use of tecovirimat. However, there is limited pharmacopoeia otherwise, and limited research interest in monkeypox. In this study, virtual screening and molecular dynamics were employed to explore the potential repurposing of multiple drugs previously approved by the FDA or other jurisdictions for other applications. Several drugs are predicted to tightly bind to viral proteins which are crucial in viral replication, including molecules which show high potential for binding the monkeypox D13L capsid protein, whose inhibition has previously been demonstrated to suppress viral replication. historical sample). using ExPASY translate tool MultAlin
Human capital value creation practices of software and service exporter firms in India

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Hyperspectral Imaging for Ink Mismatch Detection

The discovery of ink mismatch provides important clues to pre-writing examiners to indicate whether a particular manuscript is written by a specific pen, or if a particular part of a note (e.g., signature) is written on a different ink compared to any other ink. In this paper, we show that the hyperspectral image (HSI) of the handwritten notes differs between visually similar inks. For this purpose, we have created the first hyperspectral data domain for a handwritten image in various blue and black inks, containing 33 visual reference bands. In unsupervised clustering technique, visual responses of inks fall into different groups to allow the separation of two different inks from the text of the questions. The same method when used in the RGB scan of these outputs fails to accurately distinguish the ink because it is very difficult to separate the ink from the optical range. HSI overcomes RGB deficiencies and allows better discrimination between inks.
An architecture for exploiting multi-core processors to parallelize network intrusion prevention

It is becoming increasingly difficult to implement effective systems for preventing network attacks, due to the combination of (1) the rising sophistication of attacks requiring more complex analysis to detect, (2) the relentless growth in the volume of network traffic that we must analyze, and, critically, (3) the failure in recent years for uniprocessor performance to sustain the exponential gains that for so many years CPUs enjoyed (ldquoMoorepsilas Lawrdquo). For commodity hardware, tomorrowpsilas performance gains will instead come from multicore architectures in which a whole set of CPUs executes concurrently. Taking advantage of the full power of multi-core processors for network intrusion prevention requires an indepth approach. In this work we frame an architecture customized for parallel execution of network attack analysis. At the lowest layer of the architecture is an ldquoActive Network Interfacerdquo (ANI), a custom device based on an inexpensive FPGA platform. The ANI provides the inline interface to the network, reading in packets and forwarding them after they are approved. It also serves as the front-end for dispatching copies of the packets to a set of analysis threads. The analysis itself is structured as an event-based system, which allows us to find many opportunities for concurrent execution, since events introduce a natural, decoupled asynchrony into the flow of analysis while still maintaining good cache locality. Finally, by associating events with the packets that ultimately stimulated them, we can determine when all analysis for a given packet has completed, and thus that it is safe to forward the pending packet - providing none of the analysis elements previously signaled that the packet should instead be discarded.
Greedy Clustering with Sample-Based Heuristics for K-Anonymisation

Developing techniques for k-anonymising data has received much recent attention from the database research community. Good k-anonymisations should retain data utility and preserve privacy, but these are conflicting requirements and can only be traded-off. A method proposed recently attempted to achieve a balance between these two requirements, but its efficiency and effectiveness depend heavily on several empirically set parameters. In this paper, we propose sampling-based heuristics to optimally set up these parameters. We test the effectiveness of our methods by evaluating anonymisations in terms of accuracy in query answering and ability to prevent linking attacks.
The University of Birmingham ( Live System ) Sensitivity encoding for fast 1 H MR spectroscopic imaging water reference acquisition

• You may freely distribute the URL that is used to identify this publication. • Users may download and print one copy of the publication from the public portal for the purpose of private study or non-commercial research. • If a Creative Commons licence is associated with this publication, please consult the terms and conditions cited therein. • Unless otherwise stated, you may not further distribute the material nor use it for the purposes of commercial gain.
Code Based Software Security Assessments — Cobassa 2005 — Contents Code Based Software Security Assessments 1 Schedule 3 Pattern Matching Security Properties of Code Using Dependence Graphs Hardware-based Control Flow Monitoring to Prevent Malicious Control Flow Redirection towards Disk-level Malwar

Background Our technological society has become more and more dependent on software that is used to automate everyday processes. This dependence increasingly exposes us to the security threats that originate from malicious software (malware) such as computer viruses and worms and software vulnerability exploits such as remote execution of code or denial of service attacks. Moreover, this exposure is not limited to computer systems but is spreading to common appliances such as mobile phones, PDAs and consumer electronics such as media centers, personal video recorders, etc. since a growing number of these products are made extensible and adaptable by means of embedded software. The proliferation of malware and exploits requires that action is taken to tackle these issues and evaluate software security to prevent the damage and costs (e.g., data loss, productivity loss, recovery time) that result from security incidents. This calls for measures to assure that a software system has the desired security properties, i.e. that it is free of malware and vulnerabilities. Objectives The purpose of this workshop is to bring together practitioners, researchers, academics, and students to discuss the state-of-the-art of software security assessments based on reverse engineering of source or binary code (as oppposed to software security assessments that look at the software proces that was applied). This includes research on topics like source & binary code analysis techniques for the detection of software vulnerabilities (e.g. detect if code has potential buffer overflow problems) or analysis for the detection of malicious behaviour (e.g. detect if code contains exploit/virus/worm). CoBaSSA topics of interest include, but are not limited to: • Mitigating stack-or heap-based buffer overflow attacks • Re-modularizing legacy code for privilege separation • Code tamper-proofing and obfuscation • Detecting vulnerabilities in trust management and authentication • Best practices practices for secure coding • Analysis of computer virus and worm code • Binary code disassembly and anti-debugging • Race condition detection • Copy protection schemes • Analysis of the implementation of cryptographic algorithms All accepted position papers are available in digital proceedings from the workshop's web-page: The workshop's results will be summarized in a workshop report that will also be available from this website.
ITAndroids Humanoid Team Description Paper for RoboCup 2017

ITAndroids is a robotics competition group associated to the Autonomous Computational Systems Lab (LAB-SCA) at Aeronautics Institute of Technology (ITA). ITAndroids is a strong team in Latin America, especially in the simulation leagues. Our Humanoid KidSize team has worked with low cost humanoids robots since 2013. However, the group recently received a financial aid from ITA to acquire a Robotis OP2 robot and material to build 4 more robots. This paper describes our recent efforts, including the software development and our new robot design based on the DARwIn-OP project.
Snap-together motion: assembling run-time animations

Many virtual environments and games must be populated with synthetic characters to create the desired experience. These characters must move with sufficient realism, so as not to destroy the visual quality of the experience, yet be responsive, controllable, and efficient to simulate. In this paper we present an approach to character motion called Snap-Together Motion that addresses the unique demands of virtual environments. Snap-Together Motion (STM) pre-processes a corpus of motion capture examples into a set of short clips that can be concatenated to make continuous streams of motion. The result process is a simple graph structure that facilitates efficient planning of character motions. A user-guided process selects "common" character poses and the system automatically synthesizes multi-way transitions that connect through these poses. In this manner well-connected graphs can be constructed to suit a particular application, allowing for practical interactive control without the effort of manually specifying all transitions.
QoS support in Object-Based Storage Devices

Quality of Service (QoS) is an essential aspect of any large storage system. The object-based storage model is an emerging distributed storage architecture that differs from the NAS and SAN storage models. The difference warrants a reexamination of how to provide QoS support under the new object-based model. In this position paper we examine the way in which QoS is achieved in existing distributed storage systems, outline the issues in providing QoS support in our object-based storage system, and describe the design of OBIS, a mode-changing disk scheduler that can provide the underlying QoS support for objectbased storage devices.