DMT of Multihop Networks: End Points and Computational Tools

In this paper, the diversity-multiplexing gain tradeoff (DMT) of single-source, single-sink (ss-ss), multihop relay networks having slow-fading links is studied. In particular, the two end-points of the DMT of ss-ss full-duplex networks are determined, by showing that the maximum achievable diversity gain is equal to the min-cut and that the maximum multiplexing gain is equal to the min-cut rank, the latter by using an operational connection to a deterministic network. Also included in the paper, are several results that aid in the computation of the DMT of networks operating under amplify-and-forward (AF) protocols. In particular, it is shown that the colored noise encountered in amplify-and-forward protocols can be treated as white for the purpose of DMT computation, lower bounds on the DMT of lower-triangular channel matrices are derived and the DMT of parallel MIMO channels is computed. All protocols appearing in the paper are explicit and rely only upon AF relaying. Half-duplex networks and explicit coding schemes are studied in a companion paper.

Knowledge-Based Approach Using Support Vector Machine for Transmission Line Distance Relay Co-ordination

In this paper, knowledge-based approach using Support Vector Machines (SVMs) are used for estimating the coordinated zonal settings of a distance relay. The approach depends on the detailed simulation studies of apparent impedance loci as seen by distance relay during disturbance, considering various operating conditions including fault resistance. In a distance relay, the impedance loci given at the relay location is obtained from extensive transient stability studies. SVMs are used as a pattern classifier for obtaining distance relay co-ordination. The scheme utilizes the apparent impedance values observed during a fault as inputs. An improved performance with the use of SVMs, keeping the reach when faced with different fault conditions as well as system power flow changes, are illustrated with an equivalent 265 bus system of a practical Indian Western Grid.

Scheduling identical parallel machines with machine eligibility restrictions to minimize total weighted flowtime in automobile gear manufacturing

In this paper, we address a scheduling problem for minimizing total weighted flowtime, observed in automobile gear manufacturing. Specifically, the bottleneck operation of the pre-heat treatment stage of gear manufacturing process has been dealt with in scheduling. Many real-life scenarios like unequal release times, sequence dependent setup times, and machine eligibility restrictions have been considered. A mathematical model taking into account dynamic starting conditions has been proposed. The problem is derived to be NP-hard. To approach the problem, a few heuristic algorithms have been proposed. Based on planned computational experiments, the performance of the proposed heuristic algorithms is evaluated: (a) in comparison with optimal solution for small-size problem instances and (b) in comparison with the estimated optimal solution for large-size problem instances. Extensive computational analyses reveal that the proposed heuristic algorithms are capable of consistently yielding near-statistically estimated optimal solutions in a reasonable computational time.

Design for sustainability: The role of CAD

The term design in this paper particularly refers to the process (verb) and less-to the outcome or product. Design comprises a complex set of activities today involving both man and machine. Sustainability is a fundamental paradigm and carries significance in any process, natural or manmade, and its outcome. In simple terms, sustainability implies a state of sustainable living, viz, health and continuity, nurtured by diversity and evolution (innovations) in an ever-changing world. Design, in a similar line, has been comprehensively investigated and its current manifestations including design-aids (Computer Aided Design) have been evaluated in terms of sustainability. The paper investigates the rationale of sustainability to design as a whole - its purpose, its adoption in the natural world, its relevance to humankind and the technologies involved. Throughout its history, technology has been used to aid design. But in the current context of advanced algorithms and computational capacity, design no longer remains an exclusively animate faculty. Given this scenario, investigating sustainability in the light of advanced design aids such as CAD becomes pertinent. Considering that technology plays a part in design activities, the paper explores where technology must play a part and to what degree amongst the various activities that comprise design. The study includes an examination of the morphology of design and the development of a systems-thinking integrated forecasting model to evaluate the implications of CAD tools in design and sustainability. The results of the study along with a broad range of recommendations have been presented. (c) 2012 Elsevier Ltd. All rights reserved.

Decentralized linear quadratic power system stabilizers for multi-machine power systems

Linear quadratic stabilizers are well-known for their superior control capabilities when compared to the conventional lead-lag power system stabilizers. However, they have not seen much of practical importance as the state variables are generally not measurable; especially the generator rotor angle measurement is not available in most of the power plants. Full state feedback controllers require feedback of other machine states in a multi-machine power system and necessitate block diagonal structure constraints for decentralized implementation. This paper investigates the design of Linear Quadratic Power System Stabilizers using a recently proposed modified Heffron-Phillip's model. This model is derived by taking the secondary bus voltage of the step-up transformer as reference instead of the infinite bus. The state variables of this model can be obtained by local measurements. This model allows a coordinated linear quadratic control design in multi machine systems. The performance of the proposed controller has been evaluated on two widely used multi-machine power systems, 4 generator 10 bus and 10 generator 39 bus systems. It has been observed that the performance of the proposed controller is superior to that of the conventional Power System Stabilizers (PSS) over a wide range of operating and system conditions.

Suite of tools for statistical N-gram language modeling for pattern mining in whole genome sequences

Genome sequences contain a number of patterns that have biomedical significance. Repetitive sequences of various kinds are a primary component of most of the genomic sequence patterns. We extended the suffix-array based Biological Language Modeling Toolkit to compute n-gram frequencies as well as n-gram language-model based perplexity in windows over the whole genome sequence to find biologically relevant patterns. We present the suite of tools and their application for analysis on whole human genome sequence.

Computational tools for mechanistic discrimination in the reductive and metathesis coupling reactions mediated by titanium(IV) isopropoxide

A theoretical study has been carried out at the B3LYP/LANL2DZ level to compare the reactivity of phenyl isocyanate and phenyl isothiocyanate towards titanium(IV) alkoxides. Isocyanates are shown to favour both mono insertion and double insertion reactions. Double insertion in a head-to-tail fashion is shown to be more exothermic than double insertion in a head-to-head fashion. The head-to-head double insertion leads to the metathesis product, a carbodiimide, after the extrusion of carbon dioxide. In the case of phenyl isothiocyanate, calculations favour the formation of only mono insertion products. Formation of a double insertion product is highly unfavourable. Further, these studies indicate that the reverse reaction involving the metathesis of N,N-'-diphenyl carbodiimide with carbon dioxide is likely to proceed more efficiently than the metathesis reaction with carbon disulphide. This is in excellent agreement with experimental results as metathesis with carbon disulphide fails to occur. In a second study, multilayer MM/QM calculations are carried out on intermediates generated from reduction of titanium(IV) alkoxides to investigate the effect of alkoxy bridging on the reactivity of multinuclear Ti species. Bimolecular coupling of imines initiated by Ti(III) species leads to a mixture of diastereomers and not diastereoselective coupling of the imine. However if the reaction is carried out by a trimeric biradical species, diastereoselective coupling of the imine is predicted. The presence of alkoxy bridges greatly favours the formation of the d,l (+/-) isomer, whereas the intermediate without alkoxy bridges favours the more stable meso isomer. As a bridged trimeric species, stabilized by bridging alkoxy groups, correctly explains the diastereoselective reaction, it is the most likely intermediate in the reaction.

A stylometric study and assessment of machine translators

In this work we present a statistical approach inspired by stylometry -measurement of author style- to study the characteristics of machine translators. Our approach quantifies the style of a translator in terms of the properties derived from the distribution of stopwords in its output - a standard approach in modern stylometry. Our study enables us to match translated text to the source machine translator that generated them. Also, the stylometric closeness of human generated text to that generated by machine translators provides handles to assess the quality of machine translators.

Parametric study of the behavior of double toggle switching mechanisms

The paper identified and characterized a special multi-degree of freedom toggle behavior, called double toggle, observed in a typical MCCB switching mechanism. For an idealized system, the condition of toggle sequence is derived geometrically. The existing tools available in a multi-body dynamics package are used for exploring the dynamic behavior of such systems parametrically. The double toggle mechanism is found to make the system insensitive to the operator's behavior; however, the system is vulnerable under extreme usage. The linkage kinematics and stopper locations are found to have dominant role on the behavior of the system. It is revealed that the operating time is immune to the inertial property of the input link and sensitive to that of the output link. Novel designs exploiting this observation, in terms of spring and toggle placements, to enhance switching performance have also been reported in the paper. Detailed study revealed that strategic placement of the spring helps in selective alteration of system performance. Thus, the study establishes the critical importance of the kinematic design of MCCB over the dynamic parameters. (C) 2013 Elsevier Ltd. All rights reserved.

Identification of coherent synchronous generators in a multi- machine power system using support vector clustering

This paper illustrates the application of a new technique, based on Support Vector Clustering (SVC) for the direct identification of coherent synchronous generators in a large interconnected Multi-Machine Power Systems. The clustering is based on coherency measures, obtained from the time domain responses of the generators following system disturbances. The proposed clustering algorithm could be integrated into a wide-area measurement system that enables fast identification of coherent clusters of generators for the construction of dynamic equivalent models. An application of the proposed method is demonstrated on a practical 15 generators 72-bus system, an equivalent of Indian Southern grid in an attempt to show the effectiveness of this clustering approach. The effects of short circuit fault locations on coherency are also investigated.

Support vector machine based high speed protection relay for EHV/UHV transmission line

This paper presents a fast and accurate relaying technique for a long 765kv UHV transmission line based on support vector machine. For a long EHV/UHV transmission line with large distributed capacitance, a traditional distance relay which uses a lumped parameter model of the transmission line can cause malfunction of the relay. With a frequency of 1kHz, 1/4th cycle of instantaneous values of currents and voltages of all phases at the relying end are fed to Support Vector Machine(SVM). The SVM detects fault type accurately using 3 milliseconds of post-fault data and reduces the fault clearing time which improves the system stability and power transfer capability. The performance of relaying scheme has been checked with a typical 765kV Indian transmission System which is simulated using the Electromagnetic Transients Program(EMTP) developed by authors in which the distributed parameter line model is used. More than 15,000 different short circuit fault cases are simulated by varying fault location, fault impedance, fault incidence angle and fault type to train the SVM for high speed accurate relaying. Simulation studies have shown that the proposed relay provides fast and accurate protection irrespective of fault location, fault impedance, incidence time of fault and fault type. And also the proposed scheme can be used as augmentation for the existing relaying, particularly for Zone-2, Zone-3 protection.

Support vector clustering-based direct coherency identification of generators in a multi-machine power system

This study investigates the application of support vector clustering (SVC) for the direct identification of coherent synchronous generators in large interconnected multi-machine power systems. The clustering is based on coherency measure, which indicates the degree of coherency between any pair of generators. The proposed SVC algorithm processes the coherency measure matrix that is formulated using the generator rotor measurements to cluster the coherent generators. The proposed approach is demonstrated on IEEE 10 generator 39-bus system and an equivalent 35 generators, 246-bus system of practical Indian southern grid. The effect of number of data samples and fault locations are also examined for determining the accuracy of the proposed approach. An extended comparison with other clustering techniques is also included, to show the effectiveness of the proposed approach in grouping the data into coherent groups of generators. This effectiveness of the coherent clusters obtained with the proposed approach is compared in terms of a set of clustering validity indicators and in terms of statistical assessment that is based on the coherency degree of a generator pair.

A Committee Machine Approach for Compressed Sensing Signal Reconstruction

Although many sparse recovery algorithms have been proposed recently in compressed sensing (CS), it is well known that the performance of any sparse recovery algorithm depends on many parameters like dimension of the sparse signal, level of sparsity, and measurement noise power. It has been observed that a satisfactory performance of the sparse recovery algorithms requires a minimum number of measurements. This minimum number is different for different algorithms. In many applications, the number of measurements is unlikely to meet this requirement and any scheme to improve performance with fewer measurements is of significant interest in CS. Empirically, it has also been observed that the performance of the sparse recovery algorithms also depends on the underlying statistical distribution of the nonzero elements of the signal, which may not be known a priori in practice. Interestingly, it can be observed that the performance degradation of the sparse recovery algorithms in these cases does not always imply a complete failure. In this paper, we study this scenario and show that by fusing the estimates of multiple sparse recovery algorithms, which work with different principles, we can improve the sparse signal recovery. We present the theoretical analysis to derive sufficient conditions for performance improvement of the proposed schemes. We demonstrate the advantage of the proposed methods through numerical simulations for both synthetic and real signals.

Multi-site downscaling of maximum and minimum daily temperature using support vector machine

Climate change impact assessment studies involve downscaling large-scale atmospheric predictor variables (LSAPVs) simulated by general circulation models (GCMs) to site-scale meteorological variables. This article presents a least-square support vector machine (LS-SVM)-based methodology for multi-site downscaling of maximum and minimum daily temperature series. The methodology involves (1) delineation of sites in the study area into clusters based on correlation structure of predictands, (2) downscaling LSAPVs to monthly time series of predictands at a representative site identified in each of the clusters, (3) translation of the downscaled information in each cluster from the representative site to that at other sites using LS-SVM inter-site regression relationships, and (4) disaggregation of the information at each site from monthly to daily time scale using k-nearest neighbour disaggregation methodology. Effectiveness of the methodology is demonstrated by application to data pertaining to four sites in the catchment of Beas river basin, India. Simulations of Canadian coupled global climate model (CGCM3.1/T63) for four IPCC SRES scenarios namely A1B, A2, B1 and COMMIT were downscaled to future projections of the predictands in the study area. Comparison of results with those based on recently proposed multivariate multiple linear regression (MMLR) based downscaling method and multi-site multivariate statistical downscaling (MMSD) method indicate that the proposed method is promising and it can be considered as a feasible choice in statistical downscaling studies. The performance of the method in downscaling daily minimum temperature was found to be better when compared with that in downscaling daily maximum temperature. Results indicate an increase in annual average maximum and minimum temperatures at all the sites for A1B, A2 and B1 scenarios. The projected increment is high for A2 scenario, and it is followed by that for A1B, B1 and COMMIT scenarios. Projections, in general, indicated an increase in mean monthly maximum and minimum temperatures during January to February and October to December.