On Generating and Labeling Network Traffic with Realistic Self Propagating Malware

Synthetically produced data containing fabricated or merged network traffic is of limitedvalue as it is easily distinguishable from real traffic by even simple machinelearning (ML) algorithms . Real-world malware is defanged and introduced to simulated, secured nodes within those networks to generate realistic traffic while maintaining sufficient isolation to protect real data and infrastructure .…

CTNet Context based Tandem Network for Semantic Segmentation

Spatial Contextual Module (SCM) leveraged to learn spatial contextual dependency between pixels by exploring thecorrelation between pixels and categories . The Channel ContextualModule (CCM) is introduced to learn the semantic features including thesemantic feature maps and class-specific features . The learned semantic features are used as the prior knowledge to guide the learning of SCM, which can makeSCM obtain more accurate long-range spatial dependency .…

A Polyhedral Approach to Some Max min Problems

We consider a max-min variation of the classical problem of maximizing alinear function over the base of a polymatroid . In our problem we assume that the vector of coefficients of the linear function is not a known parameter of the problem but is some vertices of a simplex .…

Finding Small Multi Demand Set Covers with Ubiquitous Elements and Large Sets is Fixed Parameter Tractable

We study a variant of Set Cover where each element of the universe has somedemand that determines how many times the element needs to be covered . We prove that all three problems are fixed-parameter tractable with respect to the combinedparameter budget, the maximum number of elements missing in one of the sets, and how many sets can be included multiple times .…

Exploiting Underlay Spectrum Sharing in Cell Free Massive MIMO Systems

We investigate the coexistence of underlay spectrum sharing in cell-freemassive multiple-input multiple- input multiple-output (MIMO) systems . A primary system withgeographically distributed primary access points (P-APs) serves a multitude of primary users (PUs) while a secondary system serves a large number of secondary users (SUs) in the same primary/licensed spectrum .…

The principle of weight divergence facilitation for unsupervised pattern recognition in spiking neural networks

Parallels between the signal processing tasks and biological neurons lead to an understanding of the principles of self-organized optimization of input signals . We propose the addition to the well-knownSTDP synaptic plasticity rule to directs the weight modification towards the state associated with the maximal difference between the background noise and related signals .…

Fluid beam interaction Capturing the effect of embedded slender bodies on global fluid flow and vice versa

This work addresses research questions arising from the application of geometrically exact beam theory in the context of fluid-structure interaction(FSI) We propose amixed-dimensional embedded finite element approach for the coupling of one-dimensional equations to a three-dimensional background fluid mesh . Here, the fluid is described by theincompressible isothermal Navier-Stokes equations for Newtonian fluids .…

X METRA ADA Cross lingual Meta Transfer Learning Adaptation to Natural Language Understanding and Question Answering

Meta-learning has garnered attention as a promising technique for enhancing learning under low-resource scenarios . We proposeX-METRA-ADA, a cross-lingual MEta-TRAnsfer learning ADAptation approach for Natural Language Understanding (NLU) We show that our approach outperformsnaive fine-tuning, reaching competitive performance on both tasks for most languages .…

Privacy aware VR streaming

Proactive tile-based virtual reality (VR) video streaming employs the current tracking data of a user to predict future requested tiles . The quality of the experience (QoE) depends on the overall performance of prediction, computing(i.e., rendering) and communication) The researchers found that with DoP, the lengthof the observation window and prediction window of a tile predictor should be variable.…

Prospective Artificial Intelligence Approaches for Active Cyber Defence

Cybercriminals are rapidly developing new malicious tools that leverage AI to enable new classes of adaptive and stealthy attacks . New defensive methods need to be developed to counter these threats . Alan Turing Institute, with expert guidance from UK Cyber Security Centre and Defence Science Technology Laboratory, published a research roadmap for AI for ACD last year .…

Flow based Video Segmentation for Human Head and Shoulders

Flow-based encoder-decodernetwork (FUNet) combines traditional Horn-Schunck optical-flowestimation technique and convolutional neural networks to perform robustreal-time video segmentation . Code and pre-trained models are available on GitHub repository:\url{https://://://www.g.com/kuangzijian/Flow-Based-based-Video-Matting.net . We also introduce a video and image segmentationdataset: ConferenceVideoSegmentationDataset .…

GDPR Compliant Use of Blockchain for Secure Usage Logs

P3 is a pseudonym provisioning system for secure usage logs including a protocol for recording new usages . The unique properties of blockchain enable central requirements of distributed secure logging: Immutability, integrity, and availability . These properties enableGDPR-compliant use of blockchain, as data subjects can exercise their legalrights with regards to their personal data .…

Detector Free Weakly Supervised Grounding by Separation

Weakly Supervisedphrase-Grounding (WSG) deals with the task of using this data to learn to localize (or to ground) arbitrary text phrases in images without any additionalannotations . Most recent SotA methods for WSG assume the existence of a pre-trained object detector, relying on it to produce the ROIs for localization .…

Computing homotopy classes for diagrams

We present an algorithm that computes the set $[X,Y]^A_G$ of homotopyclasses of equivariant maps . For fixed $n = \operatorname{dim} X, the algorithm runsin polynomial time . The algorithm can be utilized to compute homotopopy invariants in theequivariant setting . Further, one can apply the result to solve problems from computational topology .…

Numerical solution of internal wave systems in the intermediate long wave and the Benjamin Ono regimes

The paper is concerned with the numerical approximation of the IntermediateLong Wave and Benjamin-Ono systems . The paper focuses on two issues of approximation . The second issue concerns the numerical generation of solitary-wavesolutions of the systems . We use acceleration techniques to improve thecomputation of the approximate solitary waves and check their performance withnumerical examples.…

A monolithic and a partitioned Reduced Basis Method for Fluid Structure Interaction problems

The aim of this work is to present a brief report concerning the various aspects of the Reduced Basis Method within Fluid-Structure Interaction problems . The toy problem that we consider is the Turek-Hron benchmark testcase, with a fluid Reynolds number Re = 100, which is known to lead to the formation of Karman vortexes in the fluid, and a periodically oscillatingbehaviour in the structure .…

Inferring Drop in Binary Parsers from Program Executions

We present BIEBER (Byte-IdEntical Binary parsER), the first system to modeland regenerate a working parser from instrumented program executions . Toachieve this, BIEber exploits the regularity (e.g., header fields andarray-like data structures) that is commonly found in file formats . Separate backends (C and Perl in our prototype) can translate the IR intothe same language as the original program (for a safer drop-in replacement), or port to a different language .…

On the Impact of Word Error Rate on Acoustic Linguistic Speech Emotion Recognition An Update for the Deep Learning Era

Text encodings from automatic speech recognition (ASR) transcripts and audiorepresentations have shown promise in speech emotion recognition (SER) eversince . Yet, it is challenging to explain the effect of each information stream on the SER systems . More clarification is required for analysing the impact of ASR’s word error rate (WER) on linguistic emotion recognition per seand in the context of fusion with acoustic information exploitation in the age of deep ASR systems .…

Robust Online Algorithms for Dynamic Choosing Problems

Semi-online algorithms that are allowed to perform a bounded amount of repacking achieve guaranteed good worst-case behaviour in a more realisticsetting . We present a framework for choosing problems that allows usto transfer offline algorithms into $(\alpha-epsilon) algorithms with amortized migration$O(1/\epSilon) We complement these positive results with lower bounds with lowerbounds that show that our results are tight in the sense that no amortization of $o(1)$ is possible .…

Towards Autonomous Robotic Precision Harvesting

A walking harvester performs the challenging task of autonomous navigation and tree grabbing in a confined, GPS denied forestenvironment . Strategies for mapping, localization, planning, and control are proposed and integrated into a fully autonomous system . The mission starts with a human or a mobile robot mapping the area of interest using a custom-madesensor module .…

Meshfree Approximation for Stochastic Optimal Control Problems

In this work, we study the gradient projection method for solving a class of class of stochastic control problems by using a mesh free approximation approach to implement spatial dimension approximation . We also present several numerical experiments to validate the theoretical results of our approach and demonstrate the convergence of our meshfree approximation approach .…

Market Value of Differentially Private Smart Meter Data

This paper proposes a framework to investigate the value of sharingprivacy-protected smart meter data between domestic consumers and load servingentities . The framework consists of a discounted differential privacy model toensure individuals cannot be identified from aggregated data . It also includes a ANN-basedshort-term load forecasting to quantify the impact of data availability and privacy protection on the forecasting error and an optimal procurement day-ahead and balancing markets to assess the market value of the privacy-utility trade-off .…

Towards Solving Multimodal Comprehension

This paper targets the problem of procedural multimodal machine comprehension(M3C) This task requires an AI to comprehend given steps of multimodalinstructions and then answer questions . Yagcioglu etal. [35] introduced RecipeQA dataset to evaluate M3C . We hypothesized that naturally occurring bias present in the dataset affects even the bestperforming model .…

Coresets for k ell Median Clustering under the Fréchet Distance

We present an algorithm for computing $epsilon-coresets for $(k,\ell)$-median clustering of polygonal curves under the Fr\’echet distance . We restrict the complexity,i.e., number of vertices, of the center curves to be at most $\ell$ each, to suppress overfitting . We achieve this result by applying the improved $ebsilon$-coreset framework by Braverman et al.…