pinecone/core-2020-05-10-deduplication huggingface dataset:
Spectral-spatial MODIS image analysis using swarm intelligence algorithms and region based segmentation for flood assessment

This paper discusses an approach for river mapping and flood evaluation based on multi-temporal time-series analysis of satellite images utilizing pixel spectral information for image clustering and region based segmentation for extracting water covered regions. MODIS satellite images are analyzed at two stages: before flood and during flood. Multi-temporal MODIS images are processed in two steps. In the first step, clustering algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are used to distinguish the water regions from the non-water based on spectral information. These algorithms are chosen since they are quite efficient in solving multi-modal optimization problems. These classified images are then segmented using spatial features of the water region to extract the river. From the results obtained, we evaluate the performance of the methods and conclude that incorporating region based image segmentation along with clustering algorithms provides accurate and reliable approach for the extraction of water covered region
Modeling mechanical properties of low carbon hot rolled steels

Steel is the most important material and it has several applications, and positions second to cement in its consumption in the world. The mechanical properties of steels are very important and vary significantly due to heat treatment, mechanical treatment, processing and alloying elements. The relationships between these parameters are complex, and nonlinear in nature. An artificial neural networks (ANN) model has been used for the prediction of mechanical properties of low alloy steels. The input parameters of the model consist of alloy composition (Al, Al soluble, C, Cr, Cu, Mn, Mo, Nb, Ni, P, S, Si, Ti, V and Nitrogen in ppm) and process parameters (coil target temperature, finish rolling temperature) and the outputs are ultimate tensile strength, yield strength, and percentage elongation. The model can be used to calculate properties of low alloy steels as a function of alloy composition and process parameters at new instances. The influence of inputs on properties of steels is simulated using the model. The results are in agreement with existing experimental knowledge. The developed model can be used as a guide for further alloy developmen
Quasi-based hierarchical clustering for land cover mapping using satellite images

This paper presents an improved hierarchical clustering algorithm for land cover mapping problem using quasi-random distribution. Initially, Niche Particle Swarm Optimization (NPSO) with pseudo/quasi-random distribution is used for splitting the data into number of cluster centers by satisfying Bayesian Information Criteria (BIC). Themain objective is to search and locate the best possible number of cluster and its centers. NPSO which highly depends on the initial distribution of particles in search space is not been exploited to its full potential. In this study, we have compared more uniformly distributed quasi-random with pseudo-random distribution with NPSO for splitting data set. Here to generate quasi-random distribution, Faure method has been used. Performance of previously proposed methods namely K-means, Mean Shift Clustering (MSC) and NPSO with pseudo-random is compared with the proposed approach - NPSO with quasi distribution(Faure). These algorithms are used on synthetic data set and multi-spectral satellite image (Landsat 7 thematic mapper). From the result obtained we conclude that use of quasi-random sequence with NPSO for hierarchical clustering algorithm results in a more accurate data classification
Clustering using Levy Flight Cuckoo Search

In this paper, a comparative study is carried using three nature-inspired algorithms namely Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Cuckoo Search (CS) on clustering problem. Cuckoo search is used with levy flight. The heavy-tail property of levy flight is exploited here. These algorithms are used on three standard benchmark datasets and one real-time multi-spectral satellite dataset. The results are tabulated and analysed using various techniques. Finally we conclude that under the given set of parameters, cuckoo search works efficiently for majority of the dataset and levy flight plays an important role
Transaction Cost, Technology Transfer and Mode of Organization

We develop a monopolistically competitive model for a closed economy without contract incompleteness. We show that if superior technology is not allowed to be transferred, integration would be the best mode of organization given that the transaction cost of intermediate input is sufficiently small. However, transferability of technology calls for adding the dimension of factor intensity of input. We then prove that integration could be the better option only when input production technology is capital-intensive. Thus we validate the empirical claim of Antras (2003) from a perspective other than incomplete contract.
Satisficing and structured individuation: A study of women workers in Calcutta's IT sector

It was initially believed that the rapid growth of the Information Technology (IT) industry in India would generate less exploitative avenues of employment for women. Further, economic empowerment would strengthen the bargaining power of women within the household and improve her self-esteem. However, recent studies argue that the IT sector has been unable to isolate itself from the social context, so that the organizational process continues to be shaped by the conflicting and asymmetrical gender relationships that prevail in Indian society. This leads to the imposition of a dual burden (of work and home commitments) on working women.
Based on a survey of women workers in Calcutta’s IT sector, this paper agues that contextual developments have weakened the patriarchal foundations of the family. This has allowed women workers to break out of a passive mould and attempt to carve out their individual destinies. However, organizational constraints and the family structure impose structural constraints on their agency, so that women workers have to adapt their aspirations to contextual realities. Decision-making of working women may, in this emerging situation, be conceptualized in terms of Simon’s satisficing model.
Cluster Based Term Weighting Model for Web Document Clustering

The term weight is based on the frequency with which the term appears in that document. The term weighting scheme measures the importance of a term with respect to a document and a collection. A term with higher weight is more important than a term with lower weight. A document ranking model uses these term weights to find the rank of a document in a collection. We propose a cluster-based term weighting models based on the TF-IDF model. This term weighting model update the inter-cluster and intra-cluster frequency components uses the generated clusters as a reference in improving the retrieved relevant documents. These inter cluster and intra-cluster frequency components are used for weighting the importance of a term in addition to the term and document frequency components
Is Direct FDI in Healthcare Desirable in a Developing Economy?

We develop a three-sector general equilibrium model and attempt to examine the impact of FDI in healthcare sector on the welfare and human capital stock of the economy. The greater the size of the healthcare sector the higher and better would be the medical facilities available to each member of the population. Better medical facilities must produce positive effects on workers’ general health and productivity.  The greater the size of the healthcare sector the higher is the efficiency of labour. There are two types of capital: capital of type K and capital of type N. While capital of type K is used in production of all the sectors of the economy, capital of type N is specific to the healthcare sector. Our analysis finds that an FDI of capital of type N although raises the human capital formation may lower social welfare. On the contrary, an inflow of foreign capital of type K is likely to be welfare-improving. Although these effects crucially hinge on different structural factors e.g. the degree of labour market imperfection, trade-related and technological factors these can at least question the desirability of allowing the entry of foreign capital in the healthcare sector directly.
Do key performance indicators matter on public procurement rules 2008? an empirical study on Local Government Engineering Department, Bangladesh

This article was published in the Journal of Public Procurement [ © 2015 by PrAcademics Press ] and the Article's website is at: http://pracademics.com/attachments/article/1208/Artile%205_Rahman-Das.pdfThis study focuses on the importance of transparency and accountability of Local Government Engineering Department (LGED)’s procurement performance based on 45 predetermined Key Performance Indicators (KPIs). The main objectives of this study are to find the extent of compliance of PPR 2008 by LGED and to identify gaps in compliance and scope of improvement for implementation. For this study, a questionnaire survey method collected data from different stakeholders related to procurement activities of LGED. Key informant interviews were also conducted with senior officers of LGED and IMED. The study result shows a clear adherence to the rules of PPR 2008 by LGED in operating its procurement functions except when paying interest for delayed payment. This study was confined to compliance issues covering 11 KPIs set by the Central Procurement Technical Unit (CPTU).Publishe
Automotive Industry Response to its Global QMS Standard ISO/TS-16949

With increasing globalization, the intense competition and customer-pressure have spurred many producers from developing/ emerging countries to adopt the best management and organizational practices. The quality issues are paramount for automotive manufacturing. The multiplicity of Quality Management System (QMS) Standards prevalent till the 1990s finally gave way to development of a harmonized automotive industry-specific QMS, namely ISO/TS-16949. This paper analyzes the major factors motivating firms to adopt this Standard: its quality signaling function, especially in international business, and facilitative role in moving up the supply chain. We investigate the inter-national and inter-regional concentration of ISO/TS-16949 certificates and relate those changes to the automotive industry dynamics. Among the top certifying nations - China, India and Brazil included - these certificates and ‘cars and commercial vehicles’ produced are highly correlated. A moderate-to-high worldwide growth of this certification is probable in near future with its gaining popularity among Tier-2 suppliers and for two/ three-wheeler automotive production. The Indian evidence indicates a sizeable proportion of car and commercial vehicle plants being ISO/TS-16949 certified and a high certification incidence among large and medium-large auto component firms. We suggest the creation of a Centre to encourage and prepare SMEs and provide financial assistance for ISO/TS-16949 certification.
Social Entrepreneurship—Building\ud
Sustainability Through Business Models\ud
and Measurement of Social Impact

Social entrepreneurshipSocial entrepreneurship is gaining unprecedented momentum in the recent years and it is overwhelming to learn how social entrepreneurs are able to create both social and economic value overcoming all odds and sustain and grow their ventures. Social enterprise can be a for-profit or a not-for- profit venture in their constitution. This research study presents a comparative case analysis of four social ventures two of them are not-for-profit organisations and depend mainly on philanthropic partners for funding. The other two are for-profit social venturesNot-for-profit Social venture and create products and services which are commercially viable. Three of the founders are Ashoka fellows and one is a national award winning social entrepreneur, all based in India. Irrespective of the nature of enterprise, developing a viable business modelBusiness model is crucial for the sustainabilitySustainability of the venture. Analysis of these organisations’ business models reveals different patterns. The findings suggest that successful social entrepreneurial organisations proactively create their own ways to partner with multiple stakeholders who share their social visionVision ; deploy resources effectively as an integral part of the business model; and integrate the target group into the social value network
Integrated Pest Management (IPM) for Reducing Pesticide Residues in Crops and Natural Resources

Investigation on the pesticide residues during 2006–2009 in various crops and natural resources (soil and water) in the study village (Kothapally, Telangana State (TS)) indicated the presence of a wide range of insecticidal residues. Pooled data of the 80 food crop and cotton samples, two rice grain samples (3 %) showed beta endosulfan residues, and two (3 %) soil samples showed alpha and beta endosulfan residues. In vegetables of the 75 tomato samples, 26 (35 %) were found contaminated with residues of which 4 % had residues above MRLs. Among the 80 brinjal samples, 46 (56 %) had residues, of these 4 % samples had residues above MRLs. Only 13 soil samples from vegetable fields were found contaminated. The frequency of contamination in brinjal fields was high and none of the pulses and cotton samples revealed any pesticide contamination. IPM fields showed substantial reduction sprays which in-turn reflected in lower residues. Initial studies on water analysis indicated the presence of residues in all water sources with higher in bore wells compared to open wells, however, by 2009 the water bodies reflected no residues above the detectable level
Efficient quality of multimedia experience using perceptual quality metrics

Although there are very few metrics which correlate well with the Human Visual System (HVS), most of them do not. We extensively studied about the Video Quality Assessment (VQA) of 2D svideos for enhancing the Quality of Experience (QoE) using better Quality of Service (QoS). We propose a solution which helps us to find a high correlation between HVS and the objective metrics using Perceptual Quality Metrics (PQM). The motive behind this work is to introduce an objective metric that is adequate to predict the Mean Opinion Score (MOS) of distorted video sequences based on the Full Reference (FR) method
Convergence Analysis of Backpropagation Algorithm for Designing an
  Intelligent System for Sensing Manhole Gases

Human fatalities are reported due to the excessive proportional presence of
hazardous gas components in the manhole, such as Hydrogen Sulfide, Ammonia,
Methane, Carbon Dioxide, Nitrogen Oxide, Carbon Monoxide, etc. Hence,
predetermination of these gases is imperative. A neural network (NN) based
intelligent sensory system is proposed for the avoidance of such fatalities.
Backpropagation (BP) was applied for the supervised training of the neural
network. A Gas sensor array consists of many sensor elements was employed for
the sensing manhole gases. Sensors in the sensor array are responsible for
sensing their target gas components only. Therefore, the presence of multiple
gases results in cross sensitivity. The cross sensitivity is a crucial issue to
this problem and it is viewed as pattern recognition and noise reduction
problem. Various performance parameters and complexity of the problem
influences NN training. In present chapter the performance of BP algorithm on
such a real life application problem was comprehensively studied, compared and
contrasted with the several other hybrid intelligent approaches both, in
theoretical and in the statistical sense
Dark matter and the LHC

An abundance of astrophysical evidence indicates that the bulk of matter in the universe is made up of massive, electrically neutral particles that form the dark matter (DM). While the density of DM has been precisely measured, the identity of the DM particle (or particles) is a complete mystery. In fact, within the laws of physics as we know them (the Standard Model, or SM), none of the particles have the right properties to make up DM. Remarkably, many new physics extensions of the SM -- designed to address theoretical issues with the electroweak symmetry breaking sector -- require the introduction of new particles, some of which are excellent DM candidates. As the LHC era begins, there are high hopes that DM particles, along with their associated new matter states, will be produced in pp collisions. We discuss how LHC experiments, along with other DM searches, may serve to determine the identity of DM particles and elucidate the associated physics. Most of our discussion centers around theories with weak-scale supersymmetry, and allows for several different DM candidate particles
Using Tau Polarization for Charged Higgs Boson and SUSY Searches at LHC

The $\tau$ polarization can be easily measured at LHC in the 1-prong hadronic $\tau$ decay channel by measuring what fraction of the $\tau$-jet momentum is carried by the charged track. A simple cut requiring this fraction to be >0.8 retains most of the polarization of $\tau=$+1 $\tau$-jet signal while suppressing the polarization of $\tau=$-1 $\tau$-jet background and practically eliminating the fake $\tau$ background. This can be utilized to extract the charged Higgs signal. It can be also utilized to extract the SUSY signal in the stau NLSP region, and in particular the stau co-annihilaton region
Heavy Ions at LHC: A Quest for Quark-Gluon Plasma

Quantum Chromo Dynamics (QCD), the theory of strong interactions, predicts a transition of the usual matter to a new phase of matter, called Quark-Gluon Plasma (QGP), at sufficiently high temperatures. The non-perturbative technique of defining a theory on a space-time lattice has been used to obtain this and other predictions about the nature of QGP. Heavy ion collisions at the Large Hadron Collider in CERN can potentially test these predictions and thereby test our theoretical understanding of confinement. This brief review aims at providing a glimpse of both these aspects of QGP
An Outlook on Correlations in Stock Prices

We present an outlook of the studies on correlations in the price timeseries
of stocks, discussing the construction and applications of "asset tree". The
topic discussed here should illustrate how the complex economic system
(financial market) enrichens the list of existing dynamical systems that
physicists have been studying for long.Comment: 6 pages, RevTeX format. To appear in the Conference Proceedings of
  ECONOPHYS-KOLKATA II: International Workshop on Econophysics of Stock Markets
  and Minority Games", February 14-17, 2006, SINP, Kolkata, as a book chapter
  in Eds. A. Chatterjee and B.K. Chakrabarti, Econophysics of Stock and other
  Markets, (Springer-Verlag (Italia), Milan, 2006
The Power (Law) of Indian Markets: Analysing NSE and BSE trading
  statistics

The nature of fluctuations in the Indian financial market is analyzed in this
paper. We have looked at the price returns of individual stocks, with
tick-by-tick data from the National Stock Exchange (NSE) and daily closing
price data from both NSE and the Bombay Stock Exchange (BSE), the two largest
exchanges in India. We find that the price returns in Indian markets follow a
fat-tailed cumulative distribution, consistent with a power law having exponent
$\alpha \sim 3$, similar to that observed in developed markets. However, the
distributions of trading volume and the number of trades have a different
nature than that seen in the New York Stock Exchange (NYSE). Further, the price
movement of different stocks are highly correlated in Indian markets.Comment: 10 pages, 7 figures, to appear in Proceedings of International
  Workshop on "Econophysics of Stock Markets and Minority Games"
  (Econophys-Kolkata II), Feb 14-17, 200
Why do Hurst exponents of traded value increase as the logarithm of
  company size?

The common assumption of universal behavior in stock market data can
sometimes lead to false conclusions. In statistical physics, the Hurst
exponents characterizing long-range correlations are often closely related to
universal exponents. We show, that in the case of time series of the traded
value, these Hurst exponents increase logarithmically with company size, and
thus are non-universal. Moreover, the average transaction size shows scaling
with the mean transaction frequency for large enough companies. We present a
phenomenological scaling framework that properly accounts for such
dependencies.Comment: 10 pages, 4 figures, to appear in the Proceedings of the
  International Workshop on Econophysics of Stock Markets and Minority Games,
  Calcutta, 200
Robust Control and Monetary Policy Delegation

This paper adapts in a simple static context the Rogoff's (1985) analysis of monetary policy delegation to a conservative central banker to the robust control framework. In this framework, uncertainty means that policymakers are unsure about their model, in the sense that there is a group of approximate models that they also consider as possibly true, and their objective is to choose
a rule that will work under a range of di¤erent model specifications. We find that robustness reveals the emergence of a precautionary behaviour in the case
of unstructured model uncertainty, reducing thus government's willingness to delegate monetary policy to a conservative central banker.
Uncovering the Internal Structure of the Indian Financial Market:
  Cross-correlation behavior in the NSE

The cross-correlations between price fluctuations of 201 frequently traded
stocks in the National Stock Exchange (NSE) of India are analyzed in this
paper. We use daily closing prices for the period 1996-2006, which coincides
with the period of rapid transformation of the market following liberalization.
The eigenvalue distribution of the cross-correlation matrix, $\mathbf{C}$, of
NSE is found to be similar to that of developed markets, such as the New York
Stock Exchange (NYSE): the majority of eigenvalues fall within the bounds
expected for a random matrix constructed from mutually uncorrelated time
series. Of the few largest eigenvalues that deviate from the bulk, the largest
is identified with market-wide movements. The intermediate eigenvalues that
occur between the largest and the bulk have been associated in NYSE with
specific business sectors with strong intra-group interactions. However, in the
Indian market, these deviating eigenvalues are comparatively very few and lie
much closer to the bulk. We propose that this is because of the relative lack
of distinct sector identity in the market, with the movement of stocks
dominantly influenced by the overall market trend. This is shown by explicit
construction of the interaction network in the market, first by generating the
minimum spanning tree from the unfiltered correlation matrix, and later, using
an improved method of generating the graph after filtering out the market mode
and random effects from the data. Both methods show, compared to developed
markets, the relative absence of clusters of co-moving stocks that belong to
the same business sector. This is consistent with the general belief that
emerging markets tend to be more correlated than developed markets.Comment: 15 pages, 8 figures, to appear in Proceedings of International
  Workshop on "Econophysics & Sociophysics of Markets & Networks"
  (Econophys-Kolkata III), Mar 12-15, 200