Interplay between RIS and AI in Wireless Communications Fundamentals Architectures Applications and Open Research Problems

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 .…

Multi Beam Multi Hop Routing for Intelligent Reflecting Surfaces Aided Massive MIMO

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 .…

Sub Gaussian Error Bounds for Hypothesis Testing

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 .…

Task Offloading and Resource Allocation with Multiple CAPs and Selfish Users

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 .…

Design of heterogeneous multi agent system for distributed computation

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 .…

Partially Observable Mean Field Reinforcement Learning

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 .…

Ensembles of Localised Models for Time Series Forecasting

Global ForecastingModels (GFM) are outperforming univariate forecasting models that work on isolated series . GFMs often have the problem of not beinglocalised enough to a particular series, especially in situations wheredatasets are heterogeneous . We propose a new methodology of clustered ensembles where we train multiple GFMs on different clusters of series, obtained by changing the number of clusters and cluster seeds .…

5G MEC Computation Handoff for Mobile Augmented Reality

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 .…

Design and Actuator Optimization of Lightweight and Compliant Knee Exoskeleton for Mobility Assistance of Children with Crouch Gait

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 .…

Inverse reinforcement learning for autonomous navigation via differentiable semantic mapping and planning

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 .…

Adaptive Surgical Robotic Training Using Real Time Stylistic Behavior Feedback Through Haptic Cues

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 .…

Self Adaptive Systems A Systematic Literature Review Across Categories and Domains

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.…

PHP code smells in web apps survival and anomalies

Code smells are considered symptoms of poor design, leading to reduced maintainability . This paper presents a longitudinal study on the survival of codesmells for web apps built with PHP . The survival of localized code smells is around 4 years, while the scattered ones live around 5 years .…

Design of a Dynamic Parameter Controlled Chaotic PRNG in a 65nm CMOS process

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.…

Estimating Experimental Dispersion Curves from Steady State Frequency Response Measurements

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 .…

mathcal L _1 Adaptive Control for Switching Reference Systems Application to Flight Control

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 .…

The Query Complexity of Local Search and Brouwer in Rounds

We study the query complexity of local search and Brouwer fixed-pointcomputation . We present several new algorithms and lower bounds, which characterize the trade-off between the number of rounds of adaptivity and the total number of queries . We mainly focus on studying these problems on the $d$-dimensional grid $[n]^d$ where $d is a constant .…

Data driven topology optimization of spinodoid metamaterials with seamlessly tunable anisotropy

We present a two-scale topology optimization framework for the design ofmacroscopic bodies with an optimized elastic response . The macroscale boundary value problem isdiscretized by finite elements, which in addition to the displacement fieldcontinuously interpolate microscale design parameters . We replace the costly microscale homogenization by a data-drivensurrogate model, using deep neural networks, which accurately and efficientlymaps design parameters onto the effective elasticity tensor .…

Heterogeneous recovery from large scale power failures

Large-scale power failures are induced by nearly all natural disasters from hurricanes to wild fires . A fundamental problem is whether and how recoveryguided by government policies is able to meet the challenge of a wide range ofdisruptions . Prior research on this problem is scant due to lack of sharing large-scale granular data at the operational energy grid, stigma of revealinglimitations of services, and complex recovery coupled with policies and customers .…

Lattice based Signcryption with Equality Test in Standard Model

A signcryption is an integration of public key encryption and adigital signature . The proposed signcryptionscheme is proven to be secure against insider attacks under the learning witherrors assumption and the intractability of the short integer solution problem . A third party can check whether or not two ciphertexts are encrypted from the same message without knowing the message .…

Exploration of Voice User Interfaces for Older Adults A Pilot Study to Address Progressive Vision Loss

Voice User Interfaces (VUIs) are becoming increasingly intuitive and functional . They are especially promising for older adults, also with special needs, as VUIs remove some barriers related to accessto Information and Communications Technology (ICT) solutions . In this pilot study we examine interdisciplinary opportunities in the area of V UIs asassistive technologies, based on an exploratory study with older adults and afollow-up in-depth pilot study .…

Improving Learning Experience in MOOCs with Educational Content Linking

Since its introduction in 2011, there have been over 4000 MOOCs on varioussubjects on the Web, serving over 35 million learners . Since most instruction and knowledge acquisition inMOOCs takes place when learners are surveying course materials, better contentnavigation may help learners find supporting information to resolve theirconfusion and thus improve learning outcome and experience .…

On the importance of functions in data modeling

In this paper, we argue that representing entity properties by tupleattributes is a controversial method conflicting with the principle of tuples immutability . In this approach, immutabletuples are intended for representing the existence of entities while mutablefunctions (mappings between sets) are used for representing entities .…

A stable majority population protocol using logarithmic time and states

We study population protocols, a model of distributed computing appropriate for modeling well-mixed chemical reaction networks and other physical systemswhere agents exchange information in pairwise interactions . The well-studied *majority*problem is that of determining in an initial population of $n$ agents, each with one of two opinions $A$ or $B$ whether there are more $A$, more $B$, or atie .…

Scaling Replicated State Machines with Compartmentalization Technical Report

State machine replication protocols, like MultiPaxos and Raft, are a critical component of many distributed systems and databases . We introduce compartmentalization, the first comprehensivetechnique to eliminate state machine replication bottlenecks . Compartmentalization involves decoupling individual bottlenecked components into distinct components and scaling these components independently .…

Minor Sparsifiers and the Distributed Laplacian Paradigm

We study distributed algorithms built around edge contraction based vertexsparsifiers . We give sublinear round algorithms in the $\textsf{CONGEST$ model for exact mincost flow, negative weight shortest paths, maxflow, andbipartite matching on sparse graphs . For the maxflow problem, this is the firstexact distributed algorithm that applies to directed graphs, while the previouswork by [Ghaffari et al.…