Finding Prerequisite Relations between Concepts using Textbook

Previous researchers have focused on finding these relationsusing Wikipedia link structure through unsupervised and supervised learning approaches . In the current work, we have proposed two methods, one isstatistical method and another is learning-based method . We mine the rich andstructured knowledge available in the textbooks to find the content for those concepts and the order in which they are discussed .…

A lightweight cryptography LWC framework to secure memory heap in Internet of Things

Java is the most common platform for embedded applications such as IoT, Wireless Sensors Networks (WSN), Near Field Communications (NFC) and RFID . Object programming languagessuch as Java, SWIFT, PHP and C++ use garbage collection after any object run which creates security loophole for attacks such as Next Memory AddressOccupation (NMAO), memory replay, Learning Tasks Behaviors (LTB) The proposed method prevents directed attack by encrypting the objectGarbage Collection at run time .…

User and Item aware Estimation of Review Helpfulness

In online review sites, the analysis of user feedback for assessing itshelpfulness for decision-making is usually carried out by studying the properties of individual reviews . We propose a novel helpfulness estimation model that extends previous ones with analysis of deviations in rating, length and polarity with respect to the reviews written by the same person, or concerning the same item .…

Escherization with Generalized Distance Functions Focusing on Local Structural Similarity

The Escherization problem involves finding a closed figure that tiles theplane that is most similar to a given goal figure . The proposed distance functions focus on the similarity of local structures in several different manners . Efficient exhaustive and incomplete search algorithms for the formulated problems are also developed to obtain results within a reasonable computation time.…

SIMF Single Instruction Multiple Flush Mechanism for Processor Temporal Isolation

Asingle-instruction multiple-flush (SIMF) mechanism to flush the core-level state is used by operating-system-level solutions . SIMF significantly alleviates the overhead offlushing by more than a factor of two in execution time and reduces dynamic instruction count by orders-of-magnitude . The resultant processor isprototyped on Xilinx ZCU102 FPGA and validated with seL4microkernel, Linux kernel in multi-core scenarios, and a cache timing attack attack .…

Sequential Targeting an incremental learning approach for data imbalance in text classification

Classification tasks require a balanced distribution of data to ensure thelearner to be trained to generalize over all classes . In real-world datasets, the number of instances vary substantially among classes . We propose a novel training method, SequentialTargeting(ST), independent of the effectiveness of the representation method, which limits its efficiency on how effective therepresentation is .…

Exploring Simple Siamese Representation Learning

Siamese networks have become a common structure in various recent models for visual representation learning . These models maximize thesimilarity between two augmentations of one image, subject to certain conditions for avoiding collapsing solutions . Our experiments show thatcollapsing solutions do exist for the loss and structure, but a stop-gradientoperation plays an essential role in preventing collapsing .…

Survey and Open Problems in Privacy Preserving Knowledge Graph Merging Query Representation Completion and Applications

Knowledge Graph (KG) has attracted more and more companies’ attention for itsability to connect different types of data in meaningful ways . However, the data isolation problem limits the performance of KG and prevents its further development . Multiple parties have their own KGs but they cannot share with each other due to regulation or competition reasons .…

Unbalanced Incomplete Multi view Clustering via the Scheme of View Evolution Weak Views are Meat Strong Views do Eat

Incomplete multi-view clustering is an important technique to deal with real-world data . Different views often have distinct incompleteness, which results in strong views (low-incompleteness views) and weak views (high-incomplete views) The UnbalancedIncomplete Multi-view Clustering method (UIMC) improves the clustering performance by up to 40% on three evaluation metrics over other state-of-the-art methods .…

Neural Scene Graphs for Dynamic Scenes

In this work, we present the first neural renderingmethod that decomposes dynamic scenes into scene graphs . We propose a learnedscene graph representation, which encodes object transformation and radiance, to efficiently render novel arrangements and views of the scene . We assessthe proposed method on synthetic and real automotive data, validating that ourapproach learns dynamic scenes – only by observing a video of this scene – andallows for rendering novel photo-realistic views of novel scene compositions with unseen sets of objects at unseen poses .…

Intrinsic Image Decomposition using Paradigms

Paper describes a method that learns intrinsic image decomposition without seeing WHDR annotations, rendered data, or ground truth data . Method relies on paradigms – fake albedos and fake shading fields – togetherwith a novel smoothing procedure that ensures good behavior at short scales on real images .…

A Deep Language independent Network to analyze the impact of COVID 19 on the World via Sentiment Analysis

Wuhan experienced an outbreak of novel coronavirus, which soon spread all over the world, resulting in a deadly pandemic that infected millions of people around the globe . We propose a deep language-independent Multilevel Attention-basedConv-BiGRU network (MACBiG-Net), which includes embedding layer, word-levelencoded attention, and sentence-level encoded attention mechanism to extract positive, negative, and neutral sentiments .…

Collaborative Storytelling with Large scale Neural Language Models

Storytelling plays a central role in human socializing and entertainment . We present a collaborative storytelling system which works with a human storyteller to create a story by generating new utterances based on the story so far . We constructed the storytelling system by tuning apublicly-available large scale language model on a dataset of writing prompts and their accompanying fictional works .…

Graph Signal Recovery Using Restricted Boltzmann Machines

We propose a model-agnostic pipeline to recover graph signals from an expertsystem by exploiting the content addressable memory property of restrictedBoltzmann machine and the representational ability of a neural network . We show that denoising the representationslearned by the deep neural networks is usually more effective than denoising the data itself .…

Certified Monotonic Neural Networks

Existing methods for learning monotonicneural networks either require specifically designed model structures to ensure monotonicity, which can be too restrictive/complicated . Compared to prior works, ourapproach does not require human-designed constraints on the weight space and yields more accurate approximation .…

PIFE PIC Parallel Immersed Finite Element Particle In Cell For 3 D Kinetic Simulations of Plasma Material Interactions

PIFE-PIC is a novel three-dimensional (3-D) ParallelImmersed-Finite-Element (IFE) Particle-in-Cell (PIC) simulation model . A simulation of theorbital-motion-limited (OML) sheath of a dielectric sphere immersed in astationary plasma is carried out to validate the code package . A large-scale simulation ofplasma charging at a lunar crater containing 2 million PIC cells (10 millionFE/IFE cells) and about 520 million particles, running for 20,000 PIC steps in about 109 wall-clock hours, is presented to demonstrate the high-performance computing capability of Pife-Pic .…

PSD2 Explainable AI Model for Credit Scoring

The aim of this paper is to develop and test advanced analytical methods to improve the prediction accuracy of Credit Risk Models, preserving at the sametime the model interpretability . The project focuses on applying an explainable machine learning model to PSD2-related databases .…

Double Self weighted Multi view Clustering via Adaptive View Fusion

Multi-view clustering has been applied in many real-world applications where original data often contain noises . DSMC performs double self-weighted operations to remove redundant features and noises from each graph, thereby obtaining robustgraphs . The method uses an adaptive multiplegraphs fusion to fuse the features in the different graphs to integratethesese graphs for clustering .…

Improvement of Classification in One Stage Detector

RetinaNet proposed Focal Loss for classification task and improved one-stagedetectors greatly . Most ofpredicted boxes whose IoU with ground-truth boxes are greater than 0.5, while their classification scores are lower than .5 . Our method can not only improve classification task, but also easemisalignment of classification and localization .…

Synthetic Image Rendering Solves Annotation Problem in Deep Learning Nanoparticle Segmentation

Nanoparticles occur in various environments as a consequence of man-madeprocesses, which raises concerns about their impact on the environment and human health . To allow for proper risk assessment, a precise and statisticallyrelevant analysis of particle characteristics (such as e.g. size, shape and composition) is required that would greatly benefit from automated imageanalysis procedures .…

Born Identity Network Multi way Counterfactual Map Generation to Explain a Classifier s Decision

There exists an apparent negative correlation between performance andinterpretability of deep learning models . We propose Born Identity Network (BIN) which is a post-hocapproach for producing multi-way counterfactual maps . Counterfactual maptransforms an input sample to be classified as a target label, similarto how humans process knowledge through counterfactsual thinking .…

Planning Folding Motion with Simulation in the Loop Using Laser Forming Origami and Thermal Behaviors as an Example

Recent works have shown success in estimating foldability of adesign using robot motion planners . However, many foldable structures areactuated using physically coupled reactions (i.e., folding originated fromthermal, chemical, or electromagnetic loads) Therefore, a reliable foldabilityanalysis must consider additional constraints that resulted from these criticalphenomena .…

Identification of NARX Models for Compesation Design

This report presents the modeling results for three systems, two numerical examples and one experimental . In the numerical examples, we use mathematical modelspreviously obtained in the literature as the systems to be identified . For each example, a NonlinearAutoRegressive model with eXogenous inputs (NARX) is identified using twowell-established techniques together, the Error Reduction Ratio (ERR) method tohierarchically select the regressors and the Akaike’s Information Criterion (AIC) to truncate the number of terms .…