AI Risk Skepticism

In this work, we survey skepticism regarding AI risk and show parallels with other types of scientific skepticism . We start by classifying different types of AI Risk skepticism and analyze their root causes . We conclude by suggestingsome intervention approaches, which may be successful in reducing AI risks .…

Data Driven Model Order Reduction for Problems with Parameter Dependent Jump Discontinuities

We propose a data-driven model order reduction (MOR) technique for partial differential equations that exhibit parameter-dependentjump-discontinuities . We build upon themethodology of approximating the map between the parameter domain and theexpansion coefficients of the reduced basis via regression . The online stagequeries the regression model for the expansion coefficients and recovers areduced approximation for the solution .…

Event Argument Extraction using Causal Knowledge Structures

The existing works exhibit poor capabilities to extract causal event arguments like Reason and After Effects . Most of the existing works model thistask at a sentence level, restricting the context to a local scope . In our work, we propose an externalknowledge aided approach to infuse document-level event information to aid theextraction of complex event arguments .…

Graph Vulnerability and Robustness A Survey

The study of network robustness is a critical tool in the characterizationand sense making of complex interconnected systems such as infrastructure,communication and social networks . This survey guides researchers and practitioners in navigating theexpansive field, while summarizing answers to key questions .…

AI Assisted MAC for Reconfigurable Intelligent Surface Aided Wireless Networks Challenges and Opportunities

Recently, significant research attention has been devoted to the study ofreconfigurable intelligent surfaces (RISs) RISs are capable of reconfiguring the wireless propagation environment by exploiting the unique properties ofmetamaterials-based integrated large arrays of inexpensive antennas . The medium access control (MAC) of multiple usersaccessing an RIS-enabled channel is still in its infancy, while many open issues remain to be addressed .…

Seniors acceptance of virtual humanoid agents

This paper reports on a study conducted as part of the EU EMPATHIC project . The data shows that seniors’ favorite technological device is the smartphone . Seniors with technological experience felt less motivated and judged the proposed agents less captivating, exciting, and appealing .…

Estimating the electrical power output of industrial devices with end to end time series classification in the presence of label noise

The proposed approach targets to gradually correct themislabelled data samples during training in a self-supervised fashion, without any prior assumption on the amount of label noise . We benchmark our approach on several time-series classification datasets and find it to be comparable and sometimes better than state-of-the-art methods .…

Curious Exploration and Return based Memory Restoration for Deep Reinforcement Learning

The proposed method can be utilized to train agents in environments with fairly complex state and action spaces . The main challenge of using such a rewardfunction is the high sparsity of positive reward signals . To address this problem, we use a simple prediction-based exploration strategy (called CuriousExploration) along with a Return-based Memory Restoration (RMR) technique which tends to remember more valuable memories .…

Benchmarking as Empirical Standard in Software Engineering Research

In empirical software engineering, benchmarks can be used for comparing methods, techniques and tools . The recent ACM SIGSOFTEmpirical Standards for Software Engineering Research do not include an explicit checklist for benchmarking . In this paper, we discuss benchmarks forsoftware performance and scalability evaluation as example research areas in software engineering .…

Child Robot Interaction Studies During COVID 19 Pandemic

The coronavirus disease (COVID-19) pandemic affected our lives deeply, just like everyone else, justlike everyone else . The children also suffered from the restrictions due to the restrictions . The precautions due to COVirus disease also introduced new constraints in the social robotics research .…

Fast mixing via polymers for random graphs with unbounded degree

The polymer model framework is a classical tool from statistical mechanic . It has recently been used to obtain approximation algorithms for spin systemson classes of bounded-degree graphs . The edge perspective allows us to bound the growthrate of the number of polymers in terms of the total degree of the polymers, which in turn can be related more easily to the expansion properties of the underlying graph .…

QDOT Quantized Dot Product Kernel for Approximate High Performance Computing

Error sensitive applications in high-performance computing are unable to benefit from existing approximatecomputing strategies that are not developed with guaranteed error bounds . Using qdot for the dot products in CG can result in amajority of components being perforated or quantized to half precision withoutincreasing the iteration count required for convergence to the same solution as CG using a double precision dot product .…

CARL DTN Context Adaptive Reinforcement Learning based Routing Algorithm in Delay Tolerant Network

Delay/Disruption-Tolerant Networks (DTN) invented to describe and cover all types of long-delay, disconnected, intermittently connected networks . The term is characterized by frequent network partitioning, intermittentconnectivity, large or variable delay, asymmetric data rate, and low transmission reliability . In DTNthere is a trade-off off between delivery ratio and overhead .…

Data driven discovery of physical laws with human understandable deep learning

There is an opportunity for deep learning to revolutionize science and technology by revealing its findings in a human interpretable manner . Wedevelop a novel data-driven approach for creating a human-machine partnershipto accelerate scientific discovery . By collecting physical system responses,under carefully selected excitations, we train rational neural networks tolearn Green’s functions of hidden partial differential equation .…

GODSAC Graph Optimized DSAC for Robot Relocalization

Deep learning based camera pose estimation from monocular camera images has a recent uptake in Visual SLAM research . GODSAC* outperforms the state-of-the-artapproaches in pose estimation accuracy, as we demonstrate in our experiments . The approach augments posepredictions from a trained neural network with noisy odometry data through theoptimization of a pose graph .…

A Jointly Design for STAR RIS enhanced NOMA CoMP Networks A Simultaneously Signal Enhancement and Cancellation based SSECB Design

In this letter, a novel simultaneously transmitting and reflecting (STAR)reconfigurable intelligent surfaces (RISs) design is proposed in anon-orthogonal multiple access (NOMA) enhanced coordinated multi-pointtransmission (CoMP) network . We propose a novelsimultaneously-signal-enhancement-and-cancellation-based (SSECB) design, where the inter-cell interferences and desired signals can be simultaneouslyeliminated and boosted .…

Security Properties for Stack Safety

“stack safety” is associated with avariety of compiler, run-time, and hardware mechanisms for protecting stackmemory . We propose a formal characterization of stack safety, formulated with concepts from language-based security . We use these properties to validatethe stack-safety “micro-policies” proposed by Roessler and DeHon [2018].…

OR Net Pointwise Relational Inference for Data Completion under Partial Observation

Current methods fail to perceive datarelativity under partial observation . Omni-Relational Network (OR-Net) to model the pointwise relativity in two aspects . It is demonstrated that the proposed OR-Net can be wellgeneralized for data completion tasks of various modalities, including functionregression, image completion on MNIST and CelebA datasets, and also sequentialmotion generation conditioned on the observed poses .…

Model Checking Quantum Continuous Time Markov Chains

A real-time system, we specify the temporal properties on QCTMC by signal temporal logic (STL) To effectivelycheck the atomic propositions in STL, we develop a state-of-art real rootisolation algorithm under Schanuel’s conjecture . Further, we check the generalSTL formula by interval operations with a bottom-up fashion, whose querycomplexity turns out to be linear in the size of the input formula by calling the real root isolation algorithm .…

Synthesizing Abstract Transformers

This paper addresses the problem of creating abstract transformersautomatically . The method we present provides the basis for creating a tool toautomate the construction of program analyzers in a fashion similar to the wayyacc automates parsers . We used it to create a set of replacement abstracttransformers for those used in an existing analyzer, and obtained essentially identical performance .…

Rate Splitting Multiple Access for Enhanced URLLC and eMBB in 6G

Rate-Splitting Multiple Access (RSMA) is a flexible and robust multipleaccess scheme for downlink multi-antenna wireless networks . RSMA relies onRate-splitting (RS) at the transmitter and Successive Interference Cancellation (SIC) at receivers . We present the optimal system designsemploying RSMA that target short-packet and low-latency communications as well as robust communications with high-throughput under the practical and importantsetup of imperfect Channel State Information at Transmitter (CSIT) originating from user mobility and feedback latency in the network .…

Deployment Archetypes for Cloud Applications

Survey paper explores six Cloud-based deployment archetypes to achieve highavailability, low end-user latency, and acceptable costs . These are (1) Zonal,(2) Regional, (3) Multi-Regional, (4) Global, (5) Hybrid, and (6) Multi Multi-Clouddeployment archetypes . This enables application owners to better examine the tradeoffsof each deployment model and what is needed for achieving the availability andlatency goals for their application .…

Lecture Notes on Voting Theory

Lectures were developed for the course Computational SocialChoice of the Artificial Intelligence MSc programme at the University of Groningen . They cover mathematical and algorithmic aspects of voting theory .…

Intelligent Reflecting Surface Assisted Secret Key Generation In Multi antenna Network

Physical-layer key generation (PKG) can generate symmetric keys between twocommunication ends based on the reciprocal uplink and downlink channels . Bysmartly reconfiguring the radio signal propagation, intelligent reflectingsurface (IRS) is able to improve the secret key rate of PKG . IRS-assistedmultiple-input single-output (MISO) system aims to maximize the secretkey rate by optimally designing the IRS passive beamforming .…

Adapting CRISP DM for Idea Mining A Data Mining Process for Generating Ideas Using a Textual Dataset

Data mining project managers can benefit from using standard data miningprocess models . The CRISP-IM facilitates idea generation, through theuse of Dynamic Topic Modeling (DTM) and unsupervised machine learning, and statistical analysis on a dataset of scholarly articles. The adaptedCRISp-IM can be used to guide the process of identifying trends using scholarlyliterature datasets or temporally organized patent or any other textual dataset to elicit ideas.…

Probabilistic Analysis of Operating Modes in Cache Enabled Full Duplex D2D Networks

Cache-enabled Device-to-Device (D2D) communication is one of the key enablers of the fifth generation (5G) cellular network . But conventional half-duplex(HD) communication may not be sufficient to provide fast enough content delivery over D2D links . In-band full-duple (FD) can provide more content deliveryopportunities, thus resulting improved spectral efficiency and latency reduction .…

Normalization of regressor excitation as a part of dynamic regressor extension and mixing procedure

The method of excitation normalization of the regressor is used in theestimation loop to solve the plant identification problem . It is based on the dynamic regressor extension and mixing procedure . Its application allows to obtain the same upper bound of the parameter identification error for the scalar regressors with different excitation levels, using a constant value of the adaptation rate for all of them .…

Distributed Energy Trading Management for Renewable Prosumers with HVAC and Energy Storage

Heating, ventilating, and air-conditioning (HVAC) systems consume a largeamount of energy in residential houses and buildings . Effective energymanagement of HVAC is a cost-effective way to improve energy efficiency and reduce the energy cost of residential users . This work develops a noveldistributed method for the residential transactive energy system that enables multiple users to interactively optimize their energy management .…