Optimizing Safe Yield Policy Implementation

The presented method enhances groundwater-mandated safe yield management. It is useful for settings that prevent sustained yield or integrated management. To protect hydraulically connected surface water rights, the Utah government’s Cache Valley groundwater management plan proposes that total pumping increase not exceed 84,431 m³/day. To determine how best to spatially distribute additional allowable pumping, stakeholders quantified limits defining acceptable impacts on selected water resource indicators. A new simulation–optimization (S–O) algorithm used these limits while computing optimal spatially distributed perennial yield or safe yield groundwater pumping extraction strategies. The limits prevent unacceptable decreases in: head and net flow between aquifer and surface waters (rivers, surface/subsurface drains, springs, lakes). The optimization objective function maximizes weighted pumping to provide water for 18 growing municipalities. For 16 perennial yield scenarios, computed optimal pumping increases differ in protectiveness toward senior water rights, and range from 16% to 103% of the state plan-proposed increase. Implementing a protective strategy would achieve 90% of the storage changes needed to reach equilibrium within 23 years. Indicator potentiometric heads would reach equilibrium within 10–40 years. At equilibrium, an optimal Cache Valley perennial yield strategy acceptably minimizes net annual non-pumping discharges. By comparison, multi-period 20-year transient groundwater mining optimizations allow more pumping in early years. Pumping then must decline to satisfy seepage and head constraints through year 20. Adverse seepage impact would increase for years thereafter. For situations governed by safe or perennial yield policy, equilibrium-based (steady-state) optimization is very useful. It effectively develops optimal perennial yield strategies.     

Multi-objective optimization in wire-electro-discharge machining of TiC reinforced composite through Neuro-Genetic technique

This paper proposed a Neuro-Genetic technique to optimize the multi-response of wire electro-discharge machining (WEDM) process. The technique was developed through hybridization of a radial basis function network (RBFN) and non-dominated sorting genetic algorithm (NSGA-II). The machining was done on 5 vol% titanium carbide (TiC) reinforced austenitic manganese steel metal matrix composite (MMC). The proposed Neuro-Genetic technique was found to be potential in finding several optimal input machining conditions which can satisfy wide requirements of a process engineer and help in efficient utilization of WEDM in industry.     

Bipartite coherent-state quantum key distribution with strong reference pulse

We propose an optical scheme for quantum key distribution in which bits are encoded in relative phases of four bipartite weak coherent states ${|\alpha, \alpha\rangle, |-\alpha, -\alpha\rangle, |-\alpha, \alpha\rangle}$ and ${|\alpha, -\alpha \rangle}$ , with respect to a strong reference pulse. We discuss security of the scheme against eavesdropping strategies like, photon number splitting, photon beam splitting and intercept-resend attacks. It is found that present scheme is more sensitive against these eavesdropping strategies than the two-dimensional non-orthogonal state based protocol and BB84 protocol. Our scheme is very simple, requires only passive optical elements like beam splitters, phase shifters and photon detectors, hence is at the reach of presently available technology.     

A multiperiod set covering location model for dynamic redeployment of ambulances

Emergency medical service (EMS) providers continually seek ways to improve system performance particularly the response time to incidents. The demand for ambulances fluctuate throughout the week, depending on the day of week, and even the time of day, therefore EMS operators can improve system performance by dynamic relocation/redeployment of ambulances in response to fluctuating demand patters. The objective of the model is to determine the minimum number of ambulances and their locations for each time cluster in which significant changes in demand pattern occur while meeting coverage requirement with a predetermined reliability. The model is further enhanced by calculating ambulance specific busy probabilities and validated by a comprehensive simulation model. Computational results on experimental data sets and data from an EMS agency are provided.     

Critical Density for Coverage and Connectivity in Three-Dimensional Wireless Sensor Networks Using Continuum Percolation

Although most of the studies on coverage and connectivity in wireless sensor networks (WSNs) considered two-dimensional (2D) settings, such networks can in reality be accurately modeled in a three-dimensional (3D) space. The concepts of continuum percolation theory best fit the problem of connectivity in WSNs to find out whether the network provides long-distance multihop communication. In this paper, we focus on percolation in coverage and connectivity in 3D WSNs. We say that the network exhibits a coverage percolation (respectively, connectivity percolation) when a giant covered region (respectively, giant connected component) almost surely spans the entire network for the first time. Because of the dependency between coverage and connectivity, the problem is not only a continuum percolation problem but also an integrated continuum percolation problem. Thus, we propose an integrated-concentric-sphere model to address coverage and connectivity in 3D WSNs in an integrated way. First, we compute the critical density lambda_C ^con above which coverage percolation in 3D WSNs will almost surely occur. Second, we compute the critical density lambda_c ^con above which connectivity percolation in 3D WSNs will almost surely occur. Third, we compute the critical density lambda_c ^cov-con above which both coverage and connectivity percolation in 3D WSNs will almost surely occur. For each of these three problems, we also compute their corresponding critical network degree. Our results can be helpful in the design of energy-efficient topology control protocols for 3D WSNs in terms of coverage and connectivity.     

An Architectural Framework for Accurate Characterization of Network Traffic

In networks carrying large volume of traffic, accurate traffic characterization is necessary for understanding the dynamics and patterns of network resource usage. Previous approaches to flow characterization are based on random sampling of the packets (e.g., Cisco's NetFlow) or inferring characteristics solely based on long lived flows (LLFs) or on lossy data structures (e.g., bloom filters, hash tables). However, none of these approaches takes into account the heavy-tailed nature of the Internet traffic and separates the estimation algorithm from the flow measurement architecture.In this paper, we propose an alternate approach to traffic characterization by closely linking the flow measurement architecture with the estimation algorithm. Our measurement framework stores complete information related to short lived flows (SLFs) while collecting partial information related to LLFs. For real-time separation of LLFs and SLFs, we propose a novel algorithm based on typical sequences from Information theory. The distribution (pdf) and sample space of the underlying traffic is estimated using the non-parametric Parzen window technique and likelihood function defined over the Coupon collector problem. We validate the accuracy and performance of our estimation technique using traffic traces from the internal LAN in our laboratory and from National Library for Applied Network Research (NLANR).     

Video Data Delivery using Slotted Patching

In the request-based scheme, a patching channel is initiated on arrival of a request in an interarrival time of two adjacent multicast channels. If two requests are received in a short duration in an interarrival time, two patching channels are needed to service them. Both these channels deliver almost the same data, thus, wasting the bandwidth. This problem may be addressed in two ways: using higher level patching technique, or forcing the first request to wait for the second one. Using higher level patching technique makes the system more complex and thus usually not preferred. In the second case, the bandwidth usage certainly reduces, but the length of the waiting time by the first request for the second request is the main issue. In this paper, this issue is addressed by dividing the video duration into uniform time slots such that there is at least one request in a time slot for initiating the patching channel. The proposed scheme is named as Video Data Delivery using Slotted Patching. In this scheme, the patching channels download much less video data than the request-based scheme and thus require less bandwidth. This scheme may not provide immediate services to all users unlike the request-based scheme, but the user's waiting can be made arbitrarily small without using much resources unlike the request-based scheme.     

An electromyographic investigation of asymmetric lifting and moving of a load: III. Models for determining muscle activity based on anthropometric characteristics

Regression models for six muscles, the left and right iliocostalis, the left and right erector spinae, and the left and right external oblique, were developed for asymmetry and height effects for floor and knuckle lifts. The models were based on participant anthropometric and other measures. Stepwise regression was performed for developing the prediction models. The models developed were discrete in terms of specific height and asymmetry. © 2009 Wiley Periodicals, Inc.     

Stabilizing adaptive controller for uncertain dynamical systems: An LMI approach

Adaptive stabilization of a class of linear systems with matched and unmatched uncertainties is considered in this paper. The proposed controller indeed stabilizes the uncertain system for any positive values of its non-adaptive gain that may be tuned to enhance dynamic response of system. The performance of uncertain system along with the Algebraic Riccati Equation that arises from the adaptive stabilizing controller is now formulated as a multi-objective Linear Matrix Inequality optimization problem. The decay rate and a factor governing the ultimate bound of the system states are considered to characterize the closed loop system performance. Finally, the effectiveness of the proposed controller is illustrated via stabilizing a mass-spring system. Recommended by Editorial Board member Gang Tao under the direction of Editor Young Il Lee. The authors would like to thank the reviewers for their valuable comments and suggestions that have improved the quality of this paper. Sandip Ghosh received the B.E. in Electrical Engineering from Bengal Engineering College (D.U.), Howrah, and Master in Control System Engineering from Jadavpur University, Kolkata, India, in 1999 and 2003 respectively. Presently he is pursuing the Ph.D. degree at Indian Institute of Technology, Kharagpur, India. His research interests include adaptive control, robust control and control of time-delay systems. Sarit K. Das is a Professor of Electrical Engineering Department, Indian Institute of Technology, Kharagpur, India. He received the Ph.D. degree in 1985 from the same department. His research interests include design of periodic controller, decoupling of multivariable systems, modeling and robust control of complex systems. Goshaidas Ray is a Professor of Electrical Engineering Department, Indian Institute of Technology, Kharagpur, India. He received the Ph.D. degree in 1982 from Indian Institute of Technology Delhi, India. His research interests include modeling, estimation, model-based control, intelligent control, robotic systems and distributed control systems.