Multiobjective Design of Groundwater Monitoring Network Under Epistemic Uncertainty

A methodology is proposed for optimal design of groundwater quality monitoring networks under epistemic uncertainty. The proposed methodology considers spatiotemporal pollutant concentrations as fuzzy numbers. It incorporates fuzzy ordinary kriging (FOK) within the decision model formulation for spatial estimation of contaminant concentration values. A multiobjective monitoring network design model incorporating the objectives of fuzzy mass estimation error and spatial coverage of the designed network is developed. Nondominated Sorting Genetic Algorithm-II (NSGA-II) is used for solving the monitoring network design model. Performances of the proposed model are evaluated for hypothetical illustrative system. Evaluation results indicate that the proposed methodology perform satisfactorily under uncertain system conditions. These performance evaluation results demonstrate the potential applicability of the proposed methodology for optimal groundwater contaminant monitoring network design under epistemic uncertainty.     

Book Reviews

Abstract:

Disruptive technology can be defined as an emerging technology whose arrival in the marketplace signifies the eventual displacement of the dominant technology in that sector. Defining and assessing a set of key metrics for a disruptive technology at its early stages can substantially aid an enterprise to develop requirements, identify, and in turn increase the possibility of the successful launch of a disruptive technology. This article aims at defining a set of key metrics for evaluation of a possible disruptive technology. A case study is subsequently used for demonstrating the metrics identified. The article concludes with its relevance to the engineering management domain and directions for future research.     

Teleportation of a qubit using entangled non-orthogonal states: a comparative study

The effect of non-orthogonality of an entangled non-orthogonal state-based quantum channel is investigated in detail in the context of the teleportation of a qubit. Specifically, average fidelity, minimum fidelity and minimum assured fidelity (MASFI) are obtained for teleportation of a single-qubit state using all the Bell-type entangled non-orthogonal states known as quasi-Bell states. Using Horodecki criterion, it is shown that the teleportation scheme obtained by replacing the quantum channel (Bell state) of the usual teleportation scheme by a quasi-Bell state is optimal. Further, the performance of various quasi-Bell states as teleportation channel is compared in an ideal situation (i.e., in the absence of noise) and under different noise models (e.g., amplitude and phase damping channels). It is observed that the best choice of the quasi-Bell state depends on the amount non-orthogonality, both in noisy and noiseless case. A specific quasi-Bell state, which was found to be maximally entangled in the ideal conditions, is shown to be less efficient as a teleportation channel compared to other quasi-Bell states in particular cases when subjected to noisy channels. It has also been observed that usually the value of average fidelity falls with an increase in the number of qubits exposed to noisy channels (viz., Alice’s, Bob’s and to be teleported qubits), but the converse may be observed in some particular cases.     

Performance analysis of ASR system in hybrid DNN-HMM framework using a PWL euclidean activation function

Automatic Speech Recognition (ASR) is the process of mapping an acoustic speech signal into a human readable text format. Traditional systems exploit the Acoustic Component of ASR using the Gaussian Mixture Model- Hidden Markov Model (GMM-HMM) approach.Deep NeuralNetwork (DNN) opens up new possibilities to overcome the shortcomings of conventional statistical algorithms. Recent studies modeled the acoustic component of ASR system using DNN in the so called hybrid DNN-HMM approach. In the context of activation functions used to model the non-linearity in DNN, Rectified Linear Units (ReLU) and maxout units are mostly used in ASR systems. This paper concentrates on the acoustic component of a hybrid DNN-HMM system by proposing an efficient activation function for the DNN network. Inspired by previous works, euclidean norm activation function is proposed to model the non-linearity of the DNN network. Such non-linearity is shown to belong to the family of Piecewise Linear (PWL) functions having distinct features. These functions can capture deep hierarchical features of the pattern. The relevance of the proposal is examined in depth both theoretically and experimentally. The performance of the developed ASR system is evaluated in terms of Phone Error Rate (PER) using TIMIT database. Experimental results achieve a relative increase in performance by using the proposed function over conventional activation functions.     

Auction-Based On-Demand P2P Min-Cost Media Streaming with Network Coding

Realizing on-demand media streaming in a Peer-to-Peer (P2P) fashion is more challenging than in the case of live media streaming, since only peers with close-by media play progresses may help each other in obtaining the media content. The situation is further complicated if we wish to pursue low aggregated link cost in the transmission. In this paper, we present a new algorithmic perspective toward on-demand P2P streaming protocol design. While previous approaches employ streaming trees or passive neighbor reconciliation for media content distribution, we instead coordinate the streaming session as an auction where each peer participates locally by bidding for and selling media flows encoded with network coding. We show that this auction approach is promising in achieving low-cost on-demand streaming in a scalable fashion. It is amenable to asynchronous, distributed, and lightweight implementations, and is flexible to provide support for random-seek and pause functionalities. Through extensive simulation studies, we verify the effectiveness and performance of the proposed auction approach, focusing on the optimality in overall streaming cost, the convergence speed, and the communication overhead.     

Nowcasting lightning flash rate and peak wind gusts associated with severe thunderstorms using remotely sensed TRMM-LIS data

The momentous weather hazards during the pre-monsoon season (April–May) over Kolkata (22° 32′ N, 88° 20′ E), India, is mostly due to lightning flashes and surface wind gusts associated with severe thunderstorms. A multi-layer perceptron (MLP) model is developed to forecast the lightning flash rate and peak wind gusts which accompany severe thunderstorms. Meteorological parameters derived from radiosonde weather observations from 1998 to 2009 are taken as input whereas lightning data from the Lightning Imaging Sensor (LIS) and wind gusts from a ground-based observatory are taken as the target output parameters. The skill of the MLP model is compared with the multiple linear regression (MLR) analysis method, and it is observed that the MLP model provides better and more accurate forecasts than the MLR analysis method. The results also reveal that the forecast accuracy is more for surface wind gusts than for the lightning flash rate, both during training and validation of the model. The MLP model forecast is validated with the India Meteorological Department (IMD) weather observations as well as Doppler weather radar and satellite imagery of 2008 and 2009 thunderstorms.     

Multi-objective efficient design space exploration and architectural synthesis of an application specific processor (ASP)

As the growth of system complexity rapidly increases, the gap between Electronic System Level (ESL) and the Register Transfer Level (RTL) must be filled. Currently, Very Large Scale Integration (VLSI) and System-on-Chip (SoC) designs are multi-objective in nature, requiring simultaneous fulfillment of multiple parameters. Extensive research on Design Space Exploration (DSE) problems and synthesis of an application specific processor (ASP) design have been done until now but none of the prior works have focused explicitly on integrating a fast multi-objective architecture exploration mechanism with the architectural synthesis stages to formalize the design methodology of an application specific processor in case of multiple objectives. This paper proposes a design methodology of a multi-objective application specific processor by integrating an efficient multi-objective (area occupied, execution time and power consumption) exploration approach with the architecture synthesis process, useful for portable devices and many high end applications. The formalized steps of the design methodology for the ASP guarantees the designer an error free approach to design the system with strict limitations on compound operational constraints. The results of implementation of the designed ASP using the proposed design methodology in FPGA and ASIC have also been shown.     

On Quantification of Groundwater Dynamics Under Long-term Land Use Land Cover Transition

Water Resources Management - The groundwater consumption for agriculture has increased since the green revolution, and its depletion severely threatens food security, especially in major...     

A distortion corrected single camera-based weight estimation technique for industrial objects

This paper describes a unique single camera-based dimensional measurement with a self-calibration method of image-based measurement. The system has been designed and implemented in one of the integrated steel plants in India. The purpose of the system is to obtain the frontal cross-sectional area of an ingot irrespective of its distance from the camera head. Automatic calibration is achieved by attaching a magnetic template of known area. This self-calibrating system is further refined to correct for the various distortions arising out of lens characteristics. The results obtained through field trials have been reported and found to be quite encouraging.