## Designing Optimal Key Lengths and Control Laws for Encrypted Control Systems based on Sample Identifying Complexity and Deciphering Time

There has been no systematic methodology of constructing cyber-physical systems that can achieve desired control performance while being protected against eavesdropping attacks . We propose a systematic method for designing the both of an optimal key length and an optimal controller to maximize both of the controlperformance and the difficulty of the identification .…

## ECLIPSE Envisioning Cloud Induced Perturbations in Solar Energy

ECLIPSE is a spatio-temporal neural network architecture that models cloud motion from sky images to predict both future segmented images and corresponding irradiance levels . It is based on the analysis of sequences of ground-taken sky images . It reduces temporal delay while generating visually realistic futures .…

## Fast Falsification of Neural Networks using Property Directed Testing

A falsification algorithm for neuralnetworks directs the search for a counterexample guided by a safetyproperty specification . We evaluate our algorithm on 45 trained neural networkbenchmarks of the ACAS Xu system against 10 safety properties . We show that our procedure detects all the unsafe instances that other tools also report as unsafe .…

dualFace consists of two-stage drawing assistance toprovide global and local visual guidance: global guidance, which helps users draw contour lines of portraits, and local guidance, inspired by traditional artist workflows in portrait drawing . In the stage of local guidance users synthesize detailed portrait images with a deep generative model, but use the synthesized results as detailed drawing guidance .…

## Distributed Eco Driving Algorithm of Vehicle Platoon Using Traffic Light and Road Slope Information

This paper investigates the problem of ecological driving (Eco-driving) of vehicle platoons . To reduce the probability of a platoon stopping at red lights, a two-layer control architecture is proposed . The leader attempts to follow the planning speed profile in real time, while the follower keeps track of the nearest preceding vehicle and leader, to preserve the desired inter-vehicular distances .…

## Vulnerabilities and Open Issues of Smart Contracts A Systematic Mapping

Smart Contracts (SCs) are programs stored in a Blockchain to ensureagreements between two or more parties . Failure or errors in SCs become perpetual once published . Thereliability of SCs is essential to avoid financial losses . This paper conducted asystematic literature mapping identifying initiatives and tools to analyze SCsand how to deal with the identified vulnerabilities.…

## Easy and Efficient Transformer Scalable Inference Solution For large NLP mode

EET achieves a 1.5-15x state-of-art speedup varying with context length . Easy and Efficient Transformer (EET) has a significantperformance improvement over the existing schemes . EET is available on GitHub and is available at:https://://://github.com/NetEase-FuXi/EET. The ultra-large-scale pre-training model can effectively improve the effect of a variety of tasks, and it also brings a heavy computational burden toinference.…

## The uniqueness of observatory publications

Large collections of observatory publications seem to be rare; or at the least rarely digitally described or accessible on the Internet . Notable examples to the contrary are the WoodmanAstronomical Library at Wisconsin-Madison and the Dudley Observatory in Loudonville, New York both in the US .…

## Launching Adversarial Attacks against Network Intrusion Detection Systems for IoT

As the internet continues to be populated with new devices and emergingtechnologies, the attack surface grows exponentially . Technology is shiftingtowards a profit-driven Internet of Things market where security is anafterthought . Traditional defending approaches are no longer sufficient to detect both known and unknown attacks to high accuracy .…

## The Reachability Problem for Petri Nets is Not Primitive Recursive

We present a way to lift up the tower lowerbound of the reachability problem for Petri nets to match the Ackermannian upperbound closing a long standingopen problem . We also prove that the reachable problem in fix dimension is elementary .…

## Syft 0 5 A Platform for Universally Deployable Structured Transparency

Syft is a general-purpose framework that combines a core group of privacy-enhancing technologies that facilitate a universal set of structured transparency systems . This framework is demonstrated through the design and implementation of a novel privacy-preserving inference information flow wherewe pass homomorphically encrypted activation signals through a split neuralnetwork for inference .…

## Finite sample approximations of exact and entropic Wasserstein distances between covariance operators and Gaussian processes

This work studies finite sample approximations of the exact and entropic regularized Wasserstein distances between centered Gaussian processes and, moregenerally, covariance operators of functional random processes . We first show that these distances/divergences are fully represented by reproducing kernelHilbert space (RKHS) covariance and cross-covariance operators associated with the corresponding covariance functions .…

## Improving Botnet Detection with Recurrent Neural Network and Transfer Learning

Botnet detection is a critical step in stopping the spread of botnets and preventing malicious activities . Recent approaches employing machinelearning (ML) showed improved performance than earlier ones, but these ML-based approaches still have significant limitations . To address these challenges, we propose a novel botnetdetection method, built upon Recurrent Variational Autoencoder (RVAE) that captures sequential characteristics of botnet activities .…

## Leaving My Fingerprints Motivations and Challenges of Contributing to OSS for Social Good

Growing interest in open source software has also been attributed to developers deciding to use their technical skills to benefit a commonsocietal good . Researchers conducted 21semi-structured interviews with OSS for Social Good (OSS4SG) contributors . They found that OSS4SG contributors focus less on benefiting themselves by padding their resumewith new technology skills and are more interested in leaving their mark on society at statistically significant levels .…

## Improve Vision Transformers Training by Suppressing Over smoothing

Training vanilla transformers on vision tasks has been shown to yield sub-optimal results . We propose to modify transformer structures by incorporating convolutional layers to improve performance . We show that our proposedtechniques stabilize the training and allow us to train wider and deeper visiontransformers, achieving 85.0\% top-1 accuracy on ImageNet validation set without introducing extra teachers or additional convolution layers .…

## We Haven t Gone Paperless Yet Why the Printing Press Can Help Us Understand Data and AI

This paper argues that the effects of datafication should be understood as a constitutive shift in social and political relations . We use analogy of the printing press toprovide a framework for understanding constitutive change . We highlight thattechnologies such as data fication and AI both disrupted extant power arrangements, leading to decentralization, and triggered a recentralization of power by new actors better adapted toleveraging the new technology .…

## Provenance based Data Skipping TechReport

Database systems analyze queries to determine upfront which data is needed for answering them and use indexes and other physical design techniques to speed-up access to that data . For important classes of queries, e.g.,HAVING and top-k queries, it is impossible to determine up-front what data is relevant .…

## ANT Learning Accurate Network Throughput for Better Adaptive Video Streaming

Adaptive Bit Rate (ABR) decision plays a crucial role for ensuringsatisfactory Quality of Experience (QoE) in video streaming applications . Past network statistics are mainly leveraged for future network bandwidthprediction . This paper proposes to learn the ANT (a.k.a., Accurate Network Throughput) model to characterize the full spectrum of network throughput dynamics in the past forderiving the proper network condition associated with a specific cluster ofnetwork throughput segments (NTS) Each cluster of NTS is then used to generate a dedicated ABR model, by which we wish to better capture the network dynamicsfor diverse connections .…

## Predicting Depressive Symptom Severity through Individuals Nearby Bluetooth Devices Count Data Collected by Mobile Phones A Preliminary Longitudinal Study

The Bluetooth sensor embedded in mobile phones provides an unobtrusive,continuous, and cost-efficient means to capture individuals’ proximityinformation . This paper aims to explore theNBDC data’s value in predicting depressive symptom severity as measured via the8-item Patient Health Questionnaire (PHQ-8) The data used in this paperincluded 2,886 bi-weekly PHQ- 8 records collected from 316 participants in the Netherlands, Spain, and the UK as part of the EU RADAR-CNS study .…

## Intelligent Reflective Transmissive Metasurfaces for Full Dimensional Communications Principles Technologies and Implementation

The concept of intelligent omni-surfaces(IOSs) is able to serve mobile users on both sides of the surface to achieve full-dimensional communications by its reflective and transmissive properties . The working principle of the IOS is introduced and a novel hybridbeamforming scheme is proposed for IOS-based wireless communications .…

## Frequency Superposition A Multi Frequency Stimulation Method in SSVEP based BCIs

The steady-state visual evoked potential (SSVEP) is one of the most widelyused modalities in brain-computer interfaces (BCIs) The existence of harmonics and the limited range of responsiverequencies in SSVEP make it challenging to further expand the number of targets presented .…

## What Makes a Message Persuasive Identifying Adaptations Towards Persuasiveness in Nine Exploratory Case Studies

The ability to persuade others is critical to professional and personalsuccess . We conducted nine exploratory case studies to identify adaptationsthat professional and non-professional writers make in written scenarios to increase their subjective persuasiveness . We identified challengesthat those writers faced and identified strategies to resolve them with artificial language generation, i.e.,…

## Dynamic Degradation for Image Restoration and Fusion

The DDRF-Net is capable of solving twoproblems, i.e., static restoration and fusion, dynamic degradation . In order to solve the static fusion problem of existing methods, dynamic convolution is introduced . In addition, adynamic degradation kernel is proposed to improve the robustness of imagerestoration and fusion .…

## HAO Hardware aware neural Architecture Optimization for Efficient Inference

Automatic algorithm-hardware co-design for DNN has shown great success in improving the performance of DNNs on FPGAs . The solution searched by our algorithm achieves 72.5% top-1 accuracy on ImageNet at framerate 50, which is 60% faster than MnasNet . With lowcomputational cost, our algorithm can generate quantized networks that achievestate-of-the-art accuracy and hardware performance on Xilinx Zynq (ZU3EG) FPGA for image classification on image classification .…

## A dissemination workshop for introducing young Italian students to NLP

We describe and make available the game-based material developed for alaboratory run at several Italian science festivals to popularize NLP among students .…

## How to Catch Marathon Cheaters New Approximation Algorithms for Tracking Paths

Given an undirected graph, $G$ and vertices, $s$ and $t$ in $G$, thetracking paths problem is known to be NP-complete and has applications to animal migrationtracking and detecting marathon course-cutting . In this paper, we give novel algorithms having approximation ratios of $1+\epsilon)$, $O(\lg OPT)$ and$O\lg n)$, for $H$-minor-free, general, and weighted graphs .…

## Reducing Write Amplification in Log Structured Storage via Inferring Block Invalidation Time

Log-structured storage has been widely deployed in various domains of storagesystems for high performance . However, its garbage collection (GC) incurs severe write amplification (WA) due to frequent rewrites of live data . Guided by this observation, we propose InferBIT, a novel data placement algorithm that aims tominimize WA .…

## Stochastic Recurrent Neural Network for Multistep Time Series Forecasting

Time series forecasting based on deep architectures has been gaining popularity in recent years due to their ability to model complex non-lineartemporal dynamics . The recurrent neural network is one such model capable of handling variable-length input and output . In our model design, the transition function of therecurrent neural network, which determines the evolution of the hidden states, is stochastic rather than deterministic as in a regular recurrent neuralnetwork .…

## Communication Efficient and Personalized Federated Lottery Ticket Learning

LotteryFL relies on unicasttransmission on the downlink, and ignores mitigating stragglers, questioningscalability . CELL is a federated lottery ticket learning algorithm, coinedCELL, which exploits downlink broadcast for communication efficiency. CELL achieves up to 3.6% higher personalized task classification accuracy with 4.3x smaller total communication cost until convergence under the CIFAR-10 dataset .…

## ODDObjects A Framework for Multiclass Unsupervised Anomaly Detection on Masked Objects

ODDObjects is designed to detect anomalies of various categories using unsupervised autoencoders trained on COCO-style datasets . Themethod utilizes autoencoder-based image reconstruction, where highreconstruction error indicates the possibility of an anomaly . The frameworkextends previous work on anomaly detection with autoenoders, comparing state-of-the-art models .…

## Contextualized Keyword Representations for Multi modal Retinal Image Captioning

Medical image captioning automatically generates a medical description to describe the content of a given medical image . A traditional medical imagecaptioning model creates a . medical description only based on a single medical image input . A newend-to-end deep multi-modal medical image caption .…

## Delving into Data Effectively Substitute Training for Black box Attack

Deep models have shown their vulnerability when processing adversarialsamples . As for the black-box attack, training a substitute model for adversarialattacks has attracted wide attention . Previous substitute training approaches focus on stealing the knowledge of the target model based on real training data or synthetic data .…

## Rich Semantics Improve Few shot Learning

Human learning benefits from multi-modal inputs that often appear as richsemantics . This enables us to learn generalizable concepts from very limited visual examples . However, current few-shot learning (FSL) methods use numerical class labels to denote object classes which do not provide rich semantic meanings about the learned concepts .…

## Quadratic Payments with constrained probabilities

“Quadratic Payments: A Primer” is written by Vitalik Buterin . The book focuses on the voting scenario depicted in the book . It aims to create a simple referendum model with more realistic outcome probability and marginal probability qualitativeshapes . It also discusses how quadratic payments can be generalized to take into account these new functions shapes, and the way they are still quadratically is discussed .…

## Deep Learning Empowered Predictive Beamforming for IRS Assisted Multi User Communications

The realization of practical intelligent reflecting surface (IRS) systems critically depends on properbeamforming design exploiting accurate channel state information (CSI) However, channel estimation (CE) in IRS-MUC systems requires a significantlylarge training overhead due to the numerous reflection elements involved inIRS .…

## Semi Decentralized Federated Edge Learning for Fast Convergence on Non IID Data

Federated edge learning (FEEL) has emerged as an effective alternative to reduce the large communication latency in Cloud-based machine learningsolutions . Unfortunately, the learningperformance of FEEL may be compromised due to limited training data in a singleedge cluster . By allowing modelaggregation between different edge clusters, SD-FEEL enjoys the benefit of .…

## Communication Efficient Federated Learning with Dual Side Low Rank Compression

Federated learning (FL) is a promising and powerful approach for training deep learning models without sharing the raw data of clients . We propose a new training method, referred to as federated learning with dual-side low-rank compression . FedDLR reduces the communication overhead during the training stage but also generates a compact model to speed up the inference process .…

## Boolean Reasoning Based Biclustering for Shifting Pattern Extraction

Shifting patterns are interesting as they account constantfluctuations in data, i.e. they capture situations in which all the values inthe pattern move up or down for one dimension maintaining the range amplitudefor all the dimensions . The induction of shifting patterns by means of Boolean reasoning is due to theability of finding all inclusion–maximal {\delta-shifting patterns .…

## Efficient Hyperparameter Optimization for Physics based Character Animation

Physics-based character animation has seen significant advances in recent years with the adoption of Deep Reinforcement Learning (DRL) However,DRL-based learning methods are usually computationally expensive . Tuninghyperparameters for these methods often requires repetitive training of controlpolicies . In this work, we propose a novel Curriculum-based Multi-Fidelity Bayesian Optimization framework .…

## Inner ear Augmented Metal Artifact Reduction with Simulation based 3D Generative Adversarial Networks

Metal Artifacts creates often difficulties for a high quality visual assessment of post-operative imaging in CT . A vastbody of methods have been proposed to tackle this issue, but their performance is usually insufficient when imaging tiny implants . We propose a 3D metal artifact reduction algorithm based on a generative adversarial neural network .…

## International Migration in Academia and Citation Performance An Analysis of German Affiliated Researchers by Gender and Discipline Using Scopus Publications 1996 2020

Germany has become a major country of immigration, as well as a researchpowerhouse in Europe . As Germany spends a higher fraction of its GDP onresearch and development than most countries with advanced economies, there is an expectation that Germany should be able to attract and retain internationalscholars who have high citation performance .…

## MDETR Modulated Detection for End to End Multi Modal Understanding

MDETR is an end-to-end modulated detector thatdetects objects in an image conditioned on a raw text query . We use a transformer-based architecture to reason jointly over text and image by fusing the two modalities at an early stage of the model .…

## Represent Items by Items An Enhanced Representation of the Target Item for Recommendation

Item-based collaborative filtering (ICF) has been widely used in industrial applications such as recommender system and online advertising . In this paper, we propose an enhanced representation of the target item which distills relevant information from the co-occurrence items . With the enhanced representation, CER has strongerrepresentation power for the tail items compared to the state-of-the-art ICFmethods.…

## I am Definitely Manipulated Even When I am Aware of it It s Ridiculous Dark Patterns from the End User Perspective

Online services pervasively employ manipulative designs (i.e., dark patterns) to influence users to purchase goods and subscriptions, spend more time on-site, or accept the harvesting of their personal data . We asked: are users aware of the presence of dark patterns?…

## Linearly Stabilized Schemes for the Time Integration of Stiff Nonlinear PDEs

In many applications, the governing PDE to be solved numerically contains a stiff component . When this component is linear, an implicit time stepping method is often preferred . If the stiff component is nonlinear, the complexity and costper step of using an implicit method is heightened, and explicit methods may be preferred .…

## To mock a Mocking bird Studies in Biomimicry

This paper dwells on certain novel game-theoretic investigations inbio-mimicry . The model is used to study the situation where multi-armedbandit predators with zero prior information are introduced into the ecosystem . The prey can be either nutritious or toxic to the predator, but the prey may signal (possibly) deceptively without revealing its true “type” The model uses a model to study a panmictic ecosystem occupied by species of prey with a relatively short lifespan, which evolve mimicry signals over generations .…

## Wasserstein distance estimates for the distributions of numerical approximations to ergodic stochastic differential equations

We present a framework that allows for the non-asymptotic study of the $2$-Wasserstein distance between the invariant distribution of an ergodicstochastic differential equation and the distribution of its numericalapproximation in the strongly log-concave case . This allows us to study in aunified way a number of different integrators proposed in the literature for the overdamped and underdamped Langevin dynamics .…

## Short term forecast of EV charging stations occupancy probability using big data streaming analysis

An extended collection and processing of information regarding charging of electric vehicles may turn each electric vehicle charging station into a valuable source of streaming data . Chargingpoint operators may profit from all these data for optimizing their operationand planning activities .…

## Stronger Bounds for Weak Epsilon Nets in Higher Dimensions

Given a finite point set $P$ in ${\mathbb R}^d$ and $piercing$d\geq 3$is a weak$epsilon-net of cardinality . This is the first improvement of the bound of $O$ that was obtained in 1994 by Chazelle,Edelsbrunner, Grigni, Guibas, Sharir, and Welzl for general point sets indimension $d=3$…

## Isabelle s Metalogic Formalization and Proof Checker

Isabelle is a generic theorem prover with a fragment of higher-order logic as a metalogic for defining object logics . Isabelle also provides proof terms . We use Isabelle/HOL to create an executable (but inefficient) proof term checker . We integrate the proof checker with Isabelle and run it on a range of logics and theories to check the correctness of all proofs .…