Supporting Clustering with Contrastive Learning

Supporting Clustering with ContrastiveLearning (SCCL) is a novel framework to leverage contrastive learning topromote better separation . SCCL significantly advances the state-of-the-art results on most benchmark datasets with 3%-11% improvement on Accuracy and 4%-15% improvements on Normalized Mutual Information . The framework leverages the strengths of both bottom-up instance discrimination and top-down clustering to achieve better intra-clusters and inter-cluster distances when evaluated with ground truth cluster labels .…

Automated Mapping of Vulnerability Advisories onto their Fix Commits in Open Source Repositories

The lack of comprehensive sources of accurate vulnerability data represents acritical obstacle to studying and understanding software vulnerabilities (andtheir corrections) Inconclusion, our method reduces considerably the effort needed to search OSSrepositories for the commits that fix known vulnerabilities . We evaluated our approach using a prototype implementation named Prospector on a manually curated data set that comprises 2,391 known fix commits .…

U S Broadband Coverage Data Set A Differentially Private Data Release

This paper introduces a publicly available U.S.Broadband Coverage data set that reports broadband coverage percentages at azip code-level . We describe our error rangecalculation method and show that this additional data metric does not induceany privacy losses . We also explain how we used differential privacy to guaranteethat the privacy of individual households is preserved.…

DNN Quantization with Attention

Low-bit quantization of network weights and activations can drastically reduce the memory footprint, complexity, energy consumption and latency of DeepNeural Networks (DNNs) However, it can also cause an aconsiderable drop in accuracy when applied to complex tasks or lightweight DNNs .…

A Challenge Obfuscating Interface for Arbiter PUF Variants against Machine Learning Attacks

Physical unclonable functions are promising candidates as security primitives for resource-constrained IoT devices . Arbiter PUFs (APUFs) are a group of delay-based PUFs which are highly lightweight in resource requirements but suffer from high susceptibility to machine learning attacks . The challenge input interface incurs low resource overhead and improves PUFs’ resistance against machine-learning attacks .…

Transfer Learning for Piano Sustain Pedal Detection

Detecting piano pedalling techniques in polyphonic music remains achallenging task in music information retrieval . In this paper, we propose atransfer learning approach for the detection of sustain-pedal techniques . In the target task, the knowledge learned from the synthesised data can be transferred to detect the sustain pedal in acoustic piano recordings .…

Multimode piezoelectric shunt damping of thin plates with arrays of separately shunted patches method and experimental validation

Two-dimensional thin plates are widely used in many applications . Shuntdamping is a promising way for the attenuation of vibration of theseelectromechanical systems . It enables a compact vibration damping method without adding significant mass and volumetric occupancy . This paper presents a methodology and aformulation for separately shunted piezoelectric patches for achieving higherperformance on vibration attenuation .…

DIALED Data Integrity Attestation for Low end Embedded Devices

The central challenge is how to securelydetect software exploits with minimal overhead . DIALED works in tandem with a companion CFA scheme to detect all (currently known) types of runtime software exploits at low-cost . Such attacks exploit softwarevulnerabilities to corrupt intermediate computation results stored in datamemory, changing neither the program code nor its control flow .…

When Word Embeddings Become Endangered

Big languages such as English and Finnish have many natural languageprocessing (NLP) resources and models, but this is not the case for low-resourced and endangered languages as such resources are so scarce . In this paper, we present a method for constructing word embeddings for endangered languages .…

An Offline Delegatable Cryptocurrency System

Offline delegation offers an efficient way to exchange coins . However, in such an approach, the coins thathave been delegated confront the risk of being spent twice . In DelegaCoin, an owner can delegate his coinsthrough offline-transactions without interacting with the blockchain network .…

Topic Modeling Genre An Exploration of French Classical and Enlightenment Drama

Topic Modeling is used to analyze a collection of French Drama of the Classical Age and the Enlightenment . The aim of this contribution is to discover what semantic types of topics are found in this collection . This contribution showsthat interesting topic patterns can be detected which provide new insights into the structure of French drama as well as into the history of the classical Age and Enlightenment.…

A Multi parameter Persistence Framework for Mathematical Morphology

The field of mathematical morphology offers well-studied techniques for imageprocessing . We demonstrate that morphological operations naturally form amultiparameter filtration and that persistent homology can then be used to extract information about both topology and geometry in the images . For illustration, we apply this framework to analyze noisy binary,grayscale, and color images.…

Towards Efficient Auctions in an Auto bidding World

Auto-bidding has become one of the main options for bidding in online advertisements . Advertisers only need to specify high-level objectives and leave the task of bidding to auto-bidders . In this paper, we propose a family of auctions with boosts to improve welfare in auto-bid environments with both return on ad spend constraints and budget constraints .…

A Multi Tenant Framework for Cloud Container Services

Virtual-Cluster is a new multi-tenant framework that extends Kubernetes . VirtualCluster provides both control plane and data plane isolations while sharing the underlying compute resources among tenants . The new framework preserves API compatibility by avoiding modifying the KuberNETes core components .…

RDMA is Turing complete we just did not know it yet

Remote Direct Memory Access(RDMA) NICs (RNICs) are one such device, allowing applications to offloadremote memory accesses . RDMA still requires CPU intervention for complex offloads, beyond simple remote memory access . RedN can outperform one and two-sided RDMA implementations by up to 3x and 7.8x for key-value get operations and .performance…

The Gradient Convergence Bound of Federated Multi Agent Reinforcement Learning with Efficient Communication

The paper considers a distributed version of deep reinforcement learning(DRL) for multi-agent decision-making process in the paradigm of federatedlearning . Since the deep neural network models in federated learning are trained locally and aggregated iteratively through a central server, frequentinformation exchange incurs a large amount of communication overheads .…

Analysis of an exactly mass conserving space time hybridized discontinuous Galerkin method for the time dependent Navier Stokes equations

We introduce and analyze a space-time hybridized discontinuous Galerkin method for the evolutionary Navier–Stokes equations . Key features of thenumerical scheme include point-wise mass conservation, energy stability, and pressure robustness . We prove that there exists a solution to the resulting nonlinear algebraic system in two and three spatial dimensions .…

How Do Software Developers Use GitHub Actions to Automate Their Workflows

GitHub introduced GitHub Actions, a feature providing automated workflows for repository maintainers . Our research is the first to investigate how developers use Actions and how several activityindicators change after their adoption . Our results indicate that although only a small subset of repositories adopted GitHub Actions to date, there is a positive perception of the technology .…

Complex Factoid Question Answering with a Free Text Knowledge Graph

DELFT builds a free-text knowledge graph fromWikipedia, with entities as nodes and sentences in which entities co-occur asedges . For each question, DELFT finds the subgraph linking question entitynodes to candidates using text sentences as edges . A novel graph neural network reasons over thefree-text graph-combining evidence on the nodes via information along edgesentences-to select a final answer .…

Row Polymorphic Types for Strategic Rewriting

We present a type system for strategy languages that express programtransformations as compositions of rewrite rules . Our row-polymorphic typesystem assists compiler engineers to write correct strategies by . statically rejecting compositions of rewrites that otherwise would . otherwise would failduring rewriting at runtime .…

Using Meta learning to Recommend Process Discovery Methods

Process discovery methods have obtained remarkable achievements in ProcessMining, delivering comprehensible process models to enhance managementcapabilities . But selecting the suitable method for a specific event loghighly relies on human expertise, hindering its broad application . Solutionsbased on Meta-learning (MtL) have been promising for creating systems with reduced human assistance .…

Female ICT participation in South Eastern Nigerian Tertiary Institutions Inhibiting Factors

The study examined the participation of female students of South EasternNigerian tertiary institutions in Information and Communication Technologies(ICTs) The study discussed the attendant gender divide in ICTs participation . Findings suggest that high cost of ICT and highlevel of male dominance, which made females think that ICT is for males were the major reasons for low female participation .…

Characterising the Knowledge about Primitive Variables in Java Code Comments

Little work has been conducted on how often these variables are documented in code comments and what types of knowledge the comments provide about variables of primitive types . Primitive types are fundamental components available in any programminglanguage . We present an approach fordetecting primitive variables and their description in comments using lexicalmatching and advanced matching .…

Facility Reallocation on the Line

We consider a multi-stage facility reallocation problems on the real line, where a facility is being moved between time stages based on the locations of $n$ agents . Westudy this problem both in the offline setting and online setting . In the online setting the algorithm does not know these future locations and must decide the location of the facility on astage-per-stage basis .…

Spoken Digit Classification by In Materio Reservoir Computing with Neuromorphic Atomic Switch Networks

Atomic Switch Networks (ASN) comprising silver iodide (AgI) junctions, amaterial previously unexplored as functional memristive elements within highly-interconnected nanowire networks, were employed as a neuromorphicsubstrate for physical Reservoir Computing . This new class of ASN-based devices has been physically characterized and utilized to classify spoken digitaudio data, demonstrating the utility of substrate-based device architectures .…

Using an Epidemiological Model to Study the Spread of Misinformation during the Black Lives Matter Movement

The proliferation of social media platforms like Twitter has heightened theconsequences of the spread of misinformation . To understand and model thespread of misinformation, in this paper, we leveraged the SEIZ (Susceptible,Exposed, Infected, Skeptics) epidemiological model . Applying a mathematical model can help to understand the trends and dynamics of spread ofmisinformation on Twitter and ultimately help to develop techniques to quicklyidentify and control it .…

Is radicalization reinforced by social media censorship

Understanding how beliefs are accepted, spread, and intensified is critical for any attempt to mitigate radicalization and avoid increased political polarization . This article presents an agent-based model of a social media network that enables investigation of the effects of censorship on the amount of dissenting information to which agents become exposed and thecertainty of their radicalized views .…

CubeFlow Money Laundering Detection with Coupled Tensors

Money laundering (ML) is the behavior to conceal the source of money achievedby illegitimate activities . CubeFlow is a scalable, flow-based approach to spot fraud from a mass of transactions by modeling them as two coupled tensors and applying a novelmulti-attribute metric which can reveal the transfer chains accurately .…

Epidemic Spreading and Digital Contact Tracing Effects of Heterogeneous Mixing and Quarantine Failures

Contact tracing via digital tracking applications installed on mobile phones is an important tool for controlling epidemic spreading . Our results are based on a combination of explicitsimulations and mean-field analysis . They indicate that there can be majordifferences in the epidemic size and epidemic probabilities which are equivalent in the normal SIR processes.…

TeCoMiner Topic Discovery Through Term Community Detection

TeCoMiner is not based on some generative probabilistic model but ontopological considerations about co-occurrence networks of terms . We outlinethe methods used for identifying topics, describe the features of the tool, andsketch an application, using a corpus of policy related scientific news on environmental issues published by the European Commission over the last decade .…