Persistent Habits, optimal Monetary Policy Inertia and Interest Rate Smoothing

Dynamic stochastic general equilibrium models featuring imperfect competition and nominal rigidities have become central for the analysis of the monetary transmission mechanism and for understanding the conduct of monetary policy. However, it is agreed that the benchmark model fails to generate the persistence of output and inflation that is observed in the data. Moreover, it cannot provide a theoretically well-grounded justification for the interest rate smoothing behaviour of monetary authorities. This paper attempts to overcome these deficiencies by embedding a multiplicative habit specification in a New Keynesian model. We show that this particular form of habit formation can explain why monetary authorities smooth interest rates

A Novel Method on Customer Requirements Preferences Based on Common Set of Weight

Abstract: Quality function deployment (QFD) has been widely used as a multi-functional design tool to translate lingual voice of customer requirements (CRs) to a product's technical attributes in the design, development of products, process planning and production planning strategies. Even though QFD efforts have been extensively used, assessing information from participant experts is still difficult task in QFD planning. The proposed voting methodology uses common set of weight (CSW) method as a well known technique in data envelopment analysis (DEA) to aggregate each of the requirements expressed by customers and comparisons among the product produced by own company with competitive products. Using such flexible method can reduce cognitive burden of designers and engineers on the presence of lack of enough data and different points of voters' view. Based on the dominance concepts of DEA with incomplete information, we developed a systematic two phase method for prioritizing customers' requirements with a numerical example

Broadcast Scheduling for Push Broadcast Systems with Arbitrary Cost Functions

In this report the problem of broadcast scheduling in Push broadcast systems is studied. We introduce an optimization approach that leads to well justified policies for Push broadcast systems with generalized cost functions. In particular, we apply our results to a Push broadcast system with different deadlines associated to the files while allowing the files to have unequal demand rates and lengths. We will show that our proposed policy covers some of the previously investigated Push systems as special cases and is applicable to a wide range of cost functions assigned to the files. We also calculate the optimal average cost for our experimental settings and show, through extensive simulation studies, that our results closely match that value for each experiment

A Dynamic Optimization Approach to the Scheduling Problem in Satellite and Wireless Broadcast Systems

The continuous growth in the demand for access to information andthe increasing number of users of the information delivery systemshave sparked the need for highly scalable systems with moreefficient usage of the bandwidth. One of the effective methods forefficient use of the bandwidth is to provide the information to agroup of users simultaneously via broadcast delivery. Generally,all applications that deliver the popular data packages (trafficinformation, weather, stocks, web pages) are suitable candidatesfor broadcast delivery and satellite or wireless networks withtheir inherent broadcast capability are the natural choices forimplementing such applications.In this report, we investigate one of the most important problemsin broadcast delivery i.e., the broadcast scheduling problem. Thisproblem arises in broadcast systems with a large number of datapackages and limited broadcast channels and the goal is to findthe best sequence of broadcasts in order to minimize the average waiting time of the users.We first formulate the problem as a dynamic optimization problemand investigate the properties of the optimal solution. Later, weuse the bandit problem formulation to address a version of theproblem where all packages have equal lengths. We find anasymptotically optimal index policy for that problem and comparethe results with some well-known heuristic methods

Physics-Informed Echo State Networks for Chaotic Systems Forecasting

We propose a physics-informed Echo State Network (ESN) to predict the evolution of chaotic systems. Compared to conventional ESNs, the physics-informed ESNs are trained to solve supervised learning tasks while ensuring that their predictions do not violate physical laws. This is achieved by introducing an additional loss function during the training of the ESNs, which penalizes non-physical predictions without the need of any additional training data. This approach is demonstrated on a chaotic Lorenz system, where the physics-informed ESNs improve the predictability horizon by about two Lyapunov times as compared to conventional ESNs. The proposed framework shows the potential of using machine learning combined with prior physical knowledge to improve the time-accurate prediction of chaotic dynamical systems.Comment: 7 pages, 3 figure

Physics-Informed Echo State Networks for Chaotic Systems Forecasting

We propose a physics-informed Echo State Network (ESN) to predict the evolution of chaotic systems. Compared to conventional ESNs, the physics-informed ESNs are trained to solve supervised learning tasks while ensuring that their predictions do not violate physical laws. This is achieved by introducing an additional loss function during the training of the ESNs, which penalizes non-physical predictions without the need of any additional training data. This approach is demonstrated on a chaotic Lorenz system, where the physics-informed ESNs improve the predictability horizon by about two Lyapunov times as compared to conventional ESNs. The proposed framework shows the potential of using machine learning combined with prior physical knowledge to improve the time-accurate prediction of chaotic dynamical systems

UAV Placement for Enhanced Connectivity in wireless Ad-hoc Networks

In this paper we address the problem of providing full connectivity in large (wide area) ad hoc networks by placing advantaged nodes like UAVs (as relay nodes) in appropriate places. We provide a formulation where we can treat the connectivity problem as a clustering problem with a summation-form distortion function. We then adapt the Deterministic Annealing clustering algorithm to our formulation and using that we nd the minimum number of UAVs required to provide connectivity and their locations. Furthermore, we describe enhancements that can be used to extend the basic connectivity problem to support notions of reliable connectivity that can lead to improved network performance. We establish the validity of our algorithm and compare its performance with optimal (exhaustive search) as well as non-opitmal (hard clustering) algorithms.We show that our algorithm is nearoptimal both for the basic connectivity problem as well as extended notions of connectivity

Interactive Data Services in Wireless Access Networks: Capacity Planning and Protocols

In this paper, we study the capacity planning in wireless access network for interactive data services such as web browsing. A closed queuing model has been developed which can capture the bottleneck effects in both the forward and the reverse channels. The model can be used to calculate the average throughput, the average response time and the number of users the system can support. We evaluate the performance of several MAC protocols such as slotted Aloha, static TDMA, Aloha/periodic stream and combined free demand assignment multiple access (CFDAMA) using realistic web traffic models. Based on the performance evaluation, we propose a new MAC protocol and a new transport layer protocol. Our new MAC protocol called combined polling free demand assignment multiple access (CPFDAMA) explores the correlation between forward channel data packets and reverse channel acknowledgement packets. Our new transport layer protocol called RWBP uses per-flow queuing, round robin scheduling and receiver window backpressure for congestion management. RWBP can eliminate congestion losses inside the wireless networks. Our protocol suite outperforms the proposed protocols in term of both channel utilization and response time. Our results can be used for service providers to dimension their networks and provide quality of service to a certain number of users

Providing Full Connectivity in Large Ad-Hoc Networks by Dynamic Placement of Aerial Platforms

In this paper we address the problem of providing full connectivity to disconnected ground MANET nodes by dynamically placing unmanned aerial vehicles (UAVs) to act as relay nodes. We provide a heuristic algorithm to find the minimal number of such aerial vehicles required to provide full connectivity and find the corresponding locations for these aerial platforms (UAVs). We also track the movement of the ground nodes and update the location of the UAVs. We describe a communication framework that enables the ground nodes to communicate with its peer ground nodes as well as the UAVs that act as relay nodes. The communication architecture is designed to work with existing MANET routing protocols