Sophistication in Service Exports and Economic Growth

Services can now be stored and traded digitally, and they are not subject to many of the trade barriers that physical exports have to overcome. Services are no longer exclusively an input for trade in goods, but have become a “final export” for direct consumption. It is important to note that services not only have become more tradable, but also can be increasingly unbundled: a single service activity in the global supply chain can now be fragmented and done separately at different geographic locations. This has led to a new channel of growth—what we call service export sophistication.Exports, service exports, outsourcing, trade, growth, india, trade barriers, unbundled, supply chain, sophistication, developing countires

Service export sophistication and economic growth

Can increasing sophistication in service exports lead to economic growth? Although services were historically produced primarily for domestic consumption, they are gradually becoming more productive, tradable and unbundled. The authors construct an index of"service exports sophistication"to document this phenomenon. Panel data estimations indicate a positive association between growth in per capita income and higher sophistication of service exports. The results also suggest that this phenomenon is growing in importance over time. Considering the limits of traditional industrialization in igniting global growth, the results provide an alternative channel.Economic Theory&Research,Public Sector Corruption&Anticorruption Measures,Commodities,Housing&Human Habitats,Banks&Banking Reform

Multi-objective optimization of an industrial styrene reactor using Harmony Search Algorithm

Multi-objective optimization of industrial styrene reactor is done using Harmony Search algorithm. Harmony search algorithm is a recently developed meta-heuristic algorithm which is inspired by musical improvisation process aimed towards obtaining the best harmony. Three objective functions – productivity, selectivity and yield are optimized to get best combination of decision variables for styrene reactor. All possible cases of single and multi-objective optimization have been considered. Pareto optimal sets are obtained as a result of the optimization study. Results reveal that optimized solution using harmony search algorithm gives better operating conditions than industrial practice

A Polynomial Kernel for Deletion to Ptolemaic Graphs

For a family of graphs F, given a graph G and an integer k, the F-Deletion problem asks whether we can delete at most k vertices from G to obtain a graph in the family F. The F-Deletion problems for all non-trivial families F that satisfy the hereditary property on induced subgraphs are known to be NP-hard by a result of Yannakakis (STOC\u2778). Ptolemaic graphs are the graphs that satisfy the Ptolemy inequality, and they are the intersection of chordal graphs and distance-hereditary graphs. Equivalently, they form the set of graphs that do not contain any chordless cycles or a gem as an induced subgraph. (A gem is the graph on 5 vertices, where four vertices form an induced path, and the fifth vertex is adjacent to all the vertices of this induced path.) The Ptolemaic Deletion problem is the F-Deletion problem, where F is the family of Ptolemaic graphs. In this paper we study Ptolemaic Deletion from the viewpoint of Kernelization Complexity, and obtain a kernel with ?(k?) vertices for the problem

FE Analysis Of Flexural Bearing For Linear Compressor

Flexure bearing is a new concept and used for precision applications such as Programmable focusing mechanism (PFM), linear compressor etc. These bearings are compact and inexpensive. A flexure bearing is designed for specific applications. These designed can usually be done with the advanced design tool like FEA. With the advent of computers FEA has become the most suitable tool for the engineering analysis where the conventional approach is not suitable, geometric complexity are involved etc. This paper deals with the study of flexure bearings in linear compressor and makes theoretical analysis on it to calculate axial stiffness, radial stiffness and parasitic motion. Using software’s like CATIA and PROE ,modeling of flexure bearing done. Also make FEM analysis on it by using Ansys software. Then compare result of theoretical and FEM analysis. And lastly, this project considers the fatigue life criteria for flexure bearing and tries to optimize it. Gaurenkar have made design calculation and FE Analysis for flexure bearing to make appropriate model. This bearing contains three slots having 120° apart and 12 peripheral holes are used to clamp the disc rigidly onto a support structure. One central hole made for movement of shaft

On the Role of Constraints in Optimization under Uncertainty

This thesis addresses the problem of industrial real-time process optimization that suffers from the presence of uncertainty. Since a process model is typically used to compute the optimal operating conditions, both plant-model mismatch and process disturbances can result in suboptimal or, worse, infeasible operation. Hence, for practical applications, methodologies that help avoid re-optimization during process operation, at the cost of an acceptable optimality loss, become important. The design and analysis of such approximate solution strategies in real-time optimization (RTO) demand a careful analysis of the components of the necessary conditions of optimality. This thesis analyzes the role of constraints in process optimality in the presence of uncertainty. This analysis is made in two steps. Firstly, a general analysis is developed to quantify the effect of input adaptation on process performance for static RTO problems. In the second part, the general features of input adaptation for dynamic RTO problems are analyzed with focus on the constraints. Accordingly, the thesis is organized in two parts: For static RTO, a joint analysis of the model optimal inputs, the plant optimal inputs and a class of adapted inputs, and For dynamic RTO, an analytical study of the effect of local adaptation of the model optimal inputs. The first part (Chapters 2 and 3) addresses the problem of adapting the inputs to optimize the plant. The investigation takes a constructive viewpoint, but it is limited to static RTO problems modeled as parametric nonlinear programming (pNLP) problems. In this approach, the inputs are not limited to being local adaptation of the model optimal inputs but, instead, they can change significantly to optimize the plant. Hence, one needs to consider the fact that the set of active constraints for the model and the plant can be different. It is proven that, for a wide class of systems, the detection of a change in the active set contributes only negligibly to optimality, as long as the adapted solution remains feasible. More precisely, if η denotes the magnitude of the parametric variations and if the linear independence constraint qualification (LICQ) and strong second-order sufficient condition (SSOSC) hold for the underlying pNLP, the optimality loss due to any feasible input that conserves only the strict nominal active set is of magnitude O(η2), irrespective of whether or not there is a change in the set of active constraints. The implication of this result for a static RTO algorithm is to prioritize the satisfaction of only a core set of constraints, as long as it is possible to meet the feasibility requirements. The second part (Chapters 4 and 5) of the thesis deals with a way of adapting the model optimal inputs in dynamic RTO problems. This adaptation is made along two sets of directions such that one type of adaptation does not affect the nominally active constraints, while the other does. These directions are termed the sensitivity-seeking (SS) and the constraint-seeking (CS) directions, respectively. The SS and CS directions are defined as elements of a fairly general function space of input variations. A mathematical criterion is derived to define SS directions for a general class of optimal control problems involving both path and terminal constraints. According to this criterion, the SS directions turn out to be solutions of linear integral equations that are completely defined by the model optimal solution. The CS directions are then chosen orthogonal to the subspace of SS directions, where orthogonality is defined with respect to a chosen inner product on the space of input variations. It follows that the corresponding subspaces are infinite-dimensional subspaces of the function space of input variations. It is proven that, when uncertainty is modeled in terms of small parametric variations, the aforementioned classification of input adaptation leads to clearly distinguishable cost variations. More precisely, if η denotes the magnitude of the parametric variations, adaptation of the model optimal inputs along SS directions causes a cost variation of magnitude O(η2). On the other hand, the cost variation due to input adaptation along CS directions is of magnitude O(η). Furthermore, a numerical procedure is proposed for computing the SS and CS components of a given input variation. These components are projections of the input variation on the infinite-dimensional subspaces of SS and CS directions. The numerical procedure consists of the following three steps: approximation of the optimal control problem by a pNLP problem, projection of the given direction on the finite-dimensional SS and CS subspaces of the pNLP and, finally, reconstruction of the SS and CS components of the original problem from those of the pNLP

Epidemiology and pattern of paediatric trauma in one of the biggest trauma centres of India

Background: The objective of the study was to assess the epidemiology and pattern of trauma in paediatric patients coming to a tertiary care trauma centre in Purvanchal region of country.Methods: Study was conducted at Trauma Centre, Institute of Medical Sciences, BHU. A retrospective data was collected from the emergency entry record book for the paediatric patients coming to emergency with trauma from January to December 2018. A total of 328 patients were included in study. Patient with accidental hanging and those of sexual assault and drowning were not taken in study.Results: Patients in the age group of above 6 years were most numerous 61%. Boys were more commonly injured then girls of same age group with M: F being 1.4:1.  Fall was the most common mode of injury overall 45.12% and for the children below 6 years of age 63%. However, RTA was the most common cause in children of above 6 years age group 40.5%, closely followed by fall. Home was found to be the most common location of injury. Females outnumbered males in case of assault injury (7 of 12). Musculoskeletal injury was most common 42%, head injury 27%, polytrauma 12%, while superficial injuries in form of abrasion, contusion etc were 19%. Of all 42% were taken inpatient, 50% discharged on OPD basis and 8% went LAMA.   Conclusions: Most of the times the paediatric traumas occur in foreseeable circumstances, most of them occurring at home or around it suggesting the need for more supervision during playing and identification of specific risk factors for these injuries in our setting. Planning of strategies should be according to the epidemiological trends

A Review on Image Processing

Image Processing involves changing the nature of an image in order to improve its pictorial information for human interpretation, for autonomous machine perception. Digital image processing is a subset of the electronic domain wherein the image is converted to an array of small integers, called pixels, representing a physical quantity such as scene radiance, stored in a digital memory, and processed by computer or other digital hardware. Interest in digital image processing methods stems from two principals applications areas: improvement of pictorial information for human interpretation; and processing of image data for storage, transmission, and representation for autonomous machine perception. Edges characterize boundaries and edge detection is one of the most difficult tasks in image processing hence it is a problem of fundamental importance in image processing. In this paper investigates different steps of digital image processing.like, a high-speed non-linear Adaptive median filter implementation is presented. Then Adaptive Median Filter solves the dual purpose of removing the impulse noise from the image and reducing distortion in the image. The Image Processing Toolbox software is a collection of functions that extend the capability of the MATLAB numeric computing environment. The toolbox supports a wide range of image processing operations on the given image. Index Terms — Image Enhancement, Feature Extraction

Dentigerous Cyst: A Review of Literature

A dentigerous cyst is a developmental cyst of odontogenic origin which develops around the fully-formed crown of an unerupted tooth. The significance of keratinization in odontogenic cysts is not fully known, but keratinization is the final product of epithelial cell differentiation. However, dentigerous cysts, thought to arise from reduced enamel epithelium, are products of end cells, i.e. cells that have completed synthesis (enamel formation). It is possible that the dentigerous cyst is a primordial variant, arising from more primitive cells of the developing enamel organ