Transfer Learning for Human & AI

A novel chaotic map is introduced using a voltage controlled negative differential resistance (NDR) circuit . The three tunable parameters are the gain of atransimpedance amplifier (TIA) and top-gate voltage ofn-channel G4FET . Twomethods are proposed for buildingchaotic oscillators using thisdiscrete map .…

The most considerableadvantage to IoT in healthcare is that it supports doctors in undertaking extrasignificant clinical work in a profession that already is experiencing aworldwide professional hard work shortage . Healthcare IoT also canbolster affected person pride by permitting patients to spend more timeinteracting with their medical doctors due to the fact docs aren’t as taken with the mundane and rote aspects of their career .…

COVID-19 has started mutating which is evident with the insurgence of its new variants . Governments,hospitals, schools, industries, and humans, in general, are looking for apotential solution in the vaccine which will eventually be available but itstimeline for eradicating the virus is yet unknown .…

This paper studies worst-case robust optimal tracking using noisy input-output data . We utilize behavioral system theory to represent systemtrajectories, while avoiding explicit system identification . We assume that therecent output data used in the data-dependent representation are noisy and we provide a non-conservative design procedure for robust control based onoptimization with a linear cost and LMI constraints .…

Phoenix monitors device-side cellular network traffic for performingsignature-based unexpected behavior detection . Phoenix can be manually-crafted by a network security expert or can be automatically synthesized using anoptional component of Phoenix . Phoenix was able to identify all 15 representative n-dayvulnerabilities and unsafe practices of 4G LTE networks considered in ourevaluation with a high packet processing speed (~68000 packets/second) whileinducing only a moderate amount of energy overhead (~4mW).…

This article surveys existing jamming attacks andanti-jamming strategies in wireless local area networks (WLANs), cellularnetworks, cognitive radio networks (CRNs) and Bluetooth networks . It offers insights on the design of jamming-resilient wireless networking systems . An outlook on promising antijamming techniques is offered at the end of this article to delineate important research directions .…

The rapid growth of GPS technology and mobile devices has led to a massive accumulation of location data . One of the major usages of such data is travel time prediction, atypical service provided by GPS navigation devices and apps .…

Differential privacy (DP) is a mathematical concept that provides robust privacy guarantee against a wide range of privacy attacks . Homogeneity attack allows adversaries to obtain the exact values on the sensitive attributes for his targets without having to re-identify them from released data .…

Current open source applications which allow for cross-platform datavisualization of OLAP cubes feature issues of high overhead and inconsistency due to data oversimplification . To improve upon this issue, there is a need tocut down the number of pipelines that the data must travel between for these operations and create a single, unified application .…

We introduce the “moment rank” and “unitary rank” of numerical sequences . We show that both parameters can becharacterized by a broad set of criteria involving moments of measures, typesof recurrence relations, Hankel matrix factorizations, Waring rank, analyticproperties of generating functions, and algebraic properties of polynomialideals .…

Sage is a machine learning-driven root cause analysis system for cloud microservices . Sage leverages unsupervised ML models to identify the root cause of QoS violations . Sage consistently achieves over 93% accuracy incorrectly identifying the root . accuracy of correctly identifying QoS .…

With web and mobile platforms becoming more prominent devices, there are currently few systems which are not without flaw . In order to increase the performance of these systems and decrease errors of dataoversimplification, we seek to understand how other programming languages can be used across these platforms which provide data and type safety, as well as concurrency .…

Smart home solutions increasingly rely on a variety of sensors for behavioral analytics and activity recognition to provide context-aware applications and personalized care . Optimizing the sensor network is one of the most important approaches to ensure classification accuracy and the system’s efficiency .…

OralViewer is the first interactive application that enables dentist’s demonstration of dental surgeries in 3D to promote patients’understanding . It takes a single 2D panoramic dental X-ray toreconstruct patient-specific 3D teeth structures, which are then assembled with registered gum and jaw bone models for complete oral cavity modeling .…

Intelligent reflecting surface (IRS) is envisioned to play a significant role in future wireless communication systems as an effective means of reconfiguring the radio signal propagation environment . We aim to select optimal IRSs and their beam routing path for each of the users, along with the active/passive beamforming at the BS/IRSs, such that the minimum received signal power among all users is maximized .…

Future wireless communication networks are expected to fulfill theunprecedented performance requirements to support our highly digitized and data-driven society . Among many potential technologies, reconfigurableintelligent surface (RIS) and artificial intelligence (AI) have attractedextensive attention . This paperexplores the road to implementing the combination of RIS and AI; specifically,integrating AI-enabled technologies into RIS-based frameworks for maximizing the practicality of RIS to facilitate the realization of smart radiopropagation environments .…

This paper presents an end-to-end de-identification framework to automatically remove Protected Health Information (PHI) from hospital discharge summaries . The majority of false positives and false negatives were related to the person category . The final model in our framework was an ensemble which combined six single models using both balanced and imbalanced datasets for training majority voting .…

MinHash and HyperLogLog are sketching algorithms that have become indispensable for set summaries in big data applications . MinHash is suitablefor the fast comparison of sets as it allows estimating the Jaccard similarityand other joint quantities . This work presents a new data structure called SetSketch that is able to continuously fill the gap between both use cases .…

Traditional multi-agent reinforcement learning algorithms are not scalable to environments with more than a few agents . These algorithms areexponential in the number of agents . In the first setting, only agents in a fixed neighbourhood are visible, while in the second setting, the visibility of agents is determined atrandom based on distances .…

In this paper, we introduce the locally conservative enriched immersed immersed finiteelement method (EIFEM) to tackle the elliptic problem with interface . We have alsoconstructed and analyzed an auxiliary space preconditioner for the resultingsystem based on the application of algebraic multigrid method .…

Methods for stochastic trace estimation often require repeated evaluationof expressions of the form $z^T p_n(A)z$ . Weshow explains how to evaluate these expressions using only $lceil n/2\rceil$matrix-vector products . This reduces the cost of existing traceestimation algorithms that use Chebyshev interpolation or Taylor series .…

A group behavior of a heterogeneous multi-agent system is studied which obeys an “average of individual vector fields” under strong couplings among the agents . A few applications are discussed including estimation of thenumber of agents in a network, distributed least-squares or median solver, distributed optimization, distributed state estimation, and robustsynchronization of coupled oscillators .…

We interpret likelihood-based test functions from a geometric perspective . The Kullback-Leibler (KL) divergence is adopted to quantify the distance from a distribution to another . An error bound for binary hypothesistesting can be obtained in terms of the sub-Gaussian norm and the KLdivergence .…

We present unconditionally energy stable Runge-Kutta (RK) discontinuousGalerkin (DG) schemes for solving a class of fourth order gradient flows . Ouralgorithm is geared toward arbitrarily high order approximations in both space and time, while energy dissipation remains preserved without imposing any restriction on time steps and meshes .…

Chunking data is obviously no new concept; however, I had never found any structures that used chunking as the basis of their implementation . By using chunking and concurrency to my advantage, I came up with thechunk list – a dynamic list-based data structure that would separate largeamounts of data into specifically sized chunks, each of which should be able to be searched at the exact same time by searching each chunk on a separatethread .…

Motivated by the recent trend of integrating artificial intelligence into theInternet-of-Things (IoT) We consider the problem of scheduling packets from multiple sensing sources to a central controller over a wireless network . Here, UCBestimates balance the tradeoff between exploration and exploitation in learningand are critical for yielding a small cumulative regret .…

Terrain adaptation is an essential capability for a ground robot to effectively traverse unstructured off-road terrain in real-world fieldenvironments such as forests . However, the expected robot behaviors generatedby terrain adaptation methods cannot always be executed accurately due to setbacks such as wheel slip and reduced tire pressure .…

Federated learning (FL) can empower Internet-of-Vehicles (IoV) networks byleveraging smart vehicles to participate in the learning process with minimum data exchanges and privacy disclosure . The collected data and learnedknowledge can help the vehicular service provider improve the globalmodel accuracy, e.g.,…

The combination of 5G and Multi-access Edge Computing (MEC) can significantly reduce application delay by lowering transmission delay and bringing capabilities closer to the end user . 5G MEC couldenable excellent user experience in applications like Mobile Augmented Reality(MAR), which are computation-intensive, and delay and jitter-sensitive .…

Recently there has been increasing activity to build dedicated Ising Machinesto accelerate the solution of combinatorial optimization problems . A common theme of such Ising Machines is to tailor the physics of underlying hardware to themathematics of the Ising model .…

This article aims to provide a simple step-by-step guide highlighting the steps needed to verify a control system with formal verification tools . We design the plant and the controller, we use Simulink for simulation and we employ a reachability analysis tool, SpaceEx, for formal verification .…

Current AI-generated music lacks fundamental principles of good compositionaltechniques . By narrowing down implementation issues both programmatically andmusically, we can create a better understanding of what parameters are necessary for a generated composition .…

The performance of an accurate driving stress levels classification system depends on hyperparameter optimization choicessuch as data segmentation . The most accurate builtmodel applied to the public dataset and our dataset, based on the selectedwindowing hyperparameters, achieved 92.12% and 77.78% accuracy, respectively .…

Pediatric exoskeletons offer great promise to increase mobility for children with crouch gait caused by cerebral palsy . A lightweight, compliant and user-specific actuator is critical for maximizing the benefits of anexoskeleton to users . We developed alightweight (1.65 kg unilateral mass) and compliant pediatric knee exoskeleton with a bandwidth of 22.6 Hz that can provide torque assistance to children withcrouch gait using high torque density motor .…

A growing demand is witnessed in both industry and academia for employingDeep Learning (DL) in various domains to solve real-world problems . Like any software systems, DRL applications canfail because of faults in their programs . In this paper, we present the first attempt to categorize faults occurring in DRL programs .…

Conventional audio coding technologies commonly leverage human perception ofsound to reduce the bitrate while preserving theperceptual quality of the decoded audio signals . For neural audio codecs, objective nature of the loss function usually leads to suboptimalsound quality as well as high run-time complexity due to the large model size .…

A self-adaptive system is characterized by being context-aware and can act on that awareness . The underlying goal of a SAS is the sustainedachievement of its goals despite changes in its environment . We characterize the maturation process of theresearch area from theoretical papers over practical implementations to moreholistic and generic approaches, frameworks, and exemplars, applied to areassuch as networking, web services, and robotics, with much of the recent workfocusing on IoT and IaaS.…

This work examines the dynamics of sharing petitions on social media in order to garner signatures and, ultimately, agovernment response . Using 20 months of Twitter data, we perform analyses of networks constructed of petitions and supporters on Twitter . We find that Twitter users do not exclusively share petitions on one issue nor do they share exclusively popular petitions .…

Users increasingly face multiple interface features on one hand, and constraints on available resources (e.g., time, attention) on the other . Building on microeconomic theory,and focusing on social information features, users’ interface choices were conceptualized as an exchange of resources in return for goods (social information features) We studied how sensitive users’ well-being is to features’ type, and to their cost level and type .…

This paper investigates the cooperative planning and control problem formultiple connected autonomous vehicles (CAVs) In theexisting literature, most of the methods suffer from significant problems incomputational efficiency . The resulting subproblems can be solved by using effective optimization methods in a parallel framework .…

This paper presents a framework for the design and analysis of an $\mathcal{L}_1$ adaptive controller with a switching reference system . The analysis uses a switched reference system that assumesperfect knowledge of uncertainties and uses a corresponding non-adaptivecontroller . Simulations of the short period dynamics of a transport class aircraft during the approach phase illustrate the theoretical results .…

This paper presents a zonal Volt/VAR control scheme that coordinatesPhotovoltaic (PV) inverters for providing voltage regulation on 3-phaseunbalanced distribution feeders . In each zone, a rule-based voltage controller will dispatch PV smart inverters toprovide reactive power control for correcting the over/under voltages .…

The Pacific Northwest Smart Grid Demonstration was an electricity gridmodernization project conducted in the Northwest U.S. This paper presents theanalysis of renewable generation at the Renewable Energy Park located in the city of Ellensburg, WA . The community energy park concept is an intriguingmodel for community investment in renewable resources .…

Dispersion curves characterize the frequency dependence of the phase and thegroup velocities of propagating elastic waves . The advantages of this approach over other traditionally used methods stem from the need to conduct only steady-state experiments . The data-driven model (using the out-of-plane FRFs) estimates the anti-symmetric ($A_0$) group velocity with a maximum error of $4\%$ over a 40~kHz frequency band .…

In this work, we consider a multi-user mobile edge computing system with multiple computing access points (CAPs) Each mobile user has multipleddependent tasks that must be processed in a round-by-round schedule . In everyround, a user may process their individual task locally, or choose to offload their task to one of the $M$ CAPs or the remote cloud server, in order to reduce their processing cost .…

This paper focuses on inverse reinforcement learning for autonomousnavigation using distance and semantic category observations . The objective isto infer a cost function that explains demonstrated behavior while relying only on the expert’s observations and state-control trajectory . We develop a mapencoder, that infers semantic category probabilities from the observationsequence, and a cost encoder, defined as a deep neural network over these features .…

Surgical skill directly affects surgical procedure outcomes; thus, effectivetraining is needed to ensure satisfactory results . We propose a framework to enable user-adaptive training using near-real-time detection of performance, based on intuitive styles of surgicalmovements . We evaluate the ability of three types of force feedback (spring, damping, and spring plusdamping feedback), computed based on prior user positions, to improve different behaviors of the user during kinematically constrained reaching movement tasks .…

In this paper, a distributed formation flight control topology forLeader-Follower formation structure is presented . Such topology depends in the first place on online generation of the trajectories that should be followed by the agents in the formation . The trajectory of each agent is planned during execution depending on its neighbors .…

In this paper, we present the design of a new chaotic map circuit with a 65nmCMOS process . We propose two designs of dynamicparameter-controlled chaotic map (DPCCM)-based pseudo-random number generators . The wider chaotic range and lower-overhead, offered byour designs, can be highly suitable for various applications such as, logicobfuscation, chaos-based cryptography, re-configurable random numbergeneration,and hard-ware security for resource-constrained edge devices likeIoT.…