We present an "opportunistic" transmission scheduling policy that exploits time-varying channel conditions and maximizes the system performance stochastically under a certain resource allocation constraint. establish optimality of scheme also every user experiences improvement over any nonopportunistic when users have independent values. demonstrate via simulation results is robust to estimation errors works well for nonstationary scenarios, resulting in improvements 20%-150% compared with...

Distributed power-control algorithms for systems with hard signal-to-interference ratio (SIR) constraints may diverge when infeasibility arises. We present a framework called utility-based power control (UBPC) by reformulating the problem using softened SIR requirement (utility) and adding penalty on consumption (cost). Under this framework, goal is to maximize net utility, defined as utility minus cost. Although UBPC still noncooperative distributed in nature, some degree of cooperation...

Automated pavement crack image segmentation is challenging because of inherent irregular patterns, lighting conditions, and noise in images. Conventional approaches require a substantial amount feature engineering to differentiate regions from non-affected regions. In this paper, we propose deep learning technique based on convolutional neural network perform tasks Our approach requires minimal compared other machine techniques. We U-Net-based architecture which replace the encoder with...

Design-build (DB) and design-bid-build (DBB) are two principal project delivery systems used in many countries. This paper reports on models constructed to predict performance of DB DBB projects 11 areas, using project-specific data collected from 87 building projects. The study included collecting, checking, validating industry data, the statistical development multivariate linear regression for predicting performance. Robust developed construction speeds Gross floor area is most...

A path-planning algorithm to guide unmanned aerial vehicles (UAVs) for tracking multiple ground targets based on the theory of partially observable Markov decision processes (POMDPs) is presented. variety features interest are shown be easy incorporate into framework by plugging in appropriate models, which demonstrates power and flexibility POMDP framework. Specifically, it how following appropriately formulating action space, transition law, objective function: 1) control UAVs with both...

Distributed power control algorithms for systems with hard SIR constraints may diverge when infeasibility arises. We present a framework called utility-based (UBPC) by reformulating the problem using softened requirement (utility) and adding penalty on consumption (cost). Under this framework, goal is to maximize net utility, defined as utility minus cost. Although UBPC still non-cooperative distributed in nature, some degree of cooperation emerges: user will automatically decrease its...

Under a Bayesian framework, we formulate the fully sequential sampling and selection decision in statistical ranking as stochastic control problem, derive associated Bellman equation. Using value function approximation, an approximately optimal allocation policy. We show that this policy is not only computationally efficient but also possesses both one-step-ahead asymptotic optimality for independent normal distributions. Moreover, proposed easily generalizable approximate dynamic...

<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Goal:</i> The purpose of this article is to introduce a new strategy identify areas with high human density and mobility, which are at risk for spreading COVID-19. Crowded regions actively moving people (called xmlns:xlink="http://www.w3.org/1999/xlink"/> <bold xmlns:xlink="http://www.w3.org/1999/xlink">at-risk</b> regions) susceptible the disease, especially if they contain asymptomatic...

Multiple-access interference (MAI) in a code-division multiple-access (CDMA) system plays an important role performance analysis and characterization of fundamental limits. We study the behavior output MAI minimum mean-square error (MMSE) receiver employed uplink direct-sequence (DS)-CDMA system. focus on imperfect power-controlled systems with random spreading, establish that synchronous (1) MMSE is asymptotically Gaussian, (2) for almost every realization signatures received powers,...

We describe a novel method for authenticating multicast packets that is robust against packet loss. Our focus to minimize the size of communication overhead required authenticate packets. approach encode hash values and signatures with Rabin's Information Dispersal Algorithm (IDA) construct an authentication scheme amortizes single signature operation over multiple This strategy especially efficient in terms space overhead, because just essential elements needed (i.e., one per group packets)...

Applications such as e-commerce payment protocols, electronic contract signing, and certified e-mail delivery require that fair exchange be assured. A fair-exchange protocol allows two parties to items in a way so either each party gets the other's item, or neither does. We describe novel method of constructing very efficient protocols by distributing computation RSA signatures. Specifically, we employ multisignatures based on RSA-signature scheme. To date, vast majority use zero-knowledge...

We describe a novel method for authenticating multicast packets that is robust against packet loss. Our main focus to minimize the size of communication overhead required authenticate packets. approach encode hash values and signatures with Rabin's Information Dispersal Algorithm (IDA) construct an authentication scheme amortizes single signature operation over multiple This strategy especially efficient in terms space overhead, because just essential elements needed (i.e., one per group...

Existing fuzzy control methods do not perform well when applied to systems containing nonlinearities arising from unknown deadzones. In particular, we show that a usual "fuzzy PD" controller system with deadzone suffers poor transient performance and large steady-state error. this paper, propose novel two-layered logic for controlling The structure consists of logic-based precompensator followed by PD controller. Our proposed exhibits superior compared controllers. addition, the is robust...

This paper discusses the application of theory partially observable Markov decision processes (POMDPs) to design guidance algorithms for controlling motion unmanned aerial vehicles (UAVs) with onboard sensors improve tracking multiple ground targets. While POMDP problems are intractable solve exactly, principled approximation methods can be devised based on that characterizes optimal solutions. A new method called nominal belief-state optimization (NBO), combined other application-specific...

The introduction of the partial information decomposition generated a flurry proposals for defining an intersection that quantifies how much "the same information" two or more random variables specify about target variable. As yet, none is wholly satisfactory. A palatable measure would provide principled way to quantify slippery concepts, such as synergy. Here, we introduce based on G\'acs-K\"orner common variable first satisfy coveted monotonicity property. Our imperfect, too, and suggest...

Real-time pricing (RTP) is a utility-offered dynamic program to incentivize customers make changes in their energy usage. A home management system (HEMS) automates the usage smart response utility signals. We present three new HEMS techniques - one myopic approach and two non-myopic partially observable Markov decision process (POMDP) approaches for minimizing household electricity bill such RTP market. In simulation study, we compare performance of methods with mathematical lower bound...

We study the problem of sensor-scheduling for target tracking to determine which sensors activate over time trade off performance with sensor usage costs. approach this by formulating it as a partially observable Markov decision process (POMDP), and develop Monte Carlo solution method using combination particle filtering belief-state estimation sampling based Q-value approximation lookahead. To evaluate effectiveness our approach, we consider simple scheduling involving multiple single target.

A class of neural networks that solve linear programming problems is analyzed. The considered are modeled by dynamic gradient systems constructed using a parametric family exact (nondifferentiable) penalty functions. It proved for given problem and sufficiently large parameters, any trajectory the network converges in finite time to its solution set. For analysis, Lyapunov-type theorems developed convergence nonsmooth sliding mode invariant sets. results illustrated via numerical simulation examples.

The use of unmanned aerial systems (UASs) in both the public and military environments is predicted to grow significantly. As demand for UASs grows, availability more robust capable vehicles that can perform multiple mission types will be needed. In sector, used agriculture, forestry, search rescue missions. Militaries continue UAS capabilities diverse operations around world. Significant research has been performed continues progress areas autonomous control. A majority work focuses on...