Simplification and generalization of large scale data for roads : a comparison of two filtering algorithms

This paper reports the results of an in-depth study which investigated two algorithms for line simplification and caricatural generalization (namely, those developed by Douglas and Peucker, and Visvalingam, respectively) in the context of a wider program of research on scale-free mapping. The use of large-scale data for man-designed objects, such as roads, has led to a better understanding of the properties of these algorithms and of their value within the spectrum of scale-free mapping. The Douglas-Peucker algorithm is better at minimal simplification. The large-scale data for roads makes it apparent that Visvalingam's technique is not only capable of removing entire scale-related features, but that it does so in a manner which preserves the shape of retained features. This technique offers some prospects for the construction of scale-free databases since it offers some scope for achieving balanced generalizations of an entire map, consisting of several complex lines. The results also suggest that it may be easier to formulate concepts and strategies for automatic segmentation of in-line features using large-scale road data and Visvalingam's algorithm. In addition, the abstraction of center lines may be facilitated by the inclusion of additional filtering rules with Visvalingam's algorithm

Cartographic Algorithms: Problems of Implementation and Evaluation and the Impact of Digitising Errors

Cartographic generalisation remains one of the outstanding challenges in digital cartography and Geographical Information Systems (GIS). It is generally assumed that computerisation will lead to the removal of spurious variability introduced by the subjective decisions of individual cartographers. This paper demonstrates through an in‐depth study of a line simplification algorithm that computerisation introduces its own sources of variability. The algorithm, referred to as the Douglas‐Peucker algorithm in cartographic literature, has been widely used in image processing, pattern recognition and GIS for some 20 years. An analysis of this algorithm and study of some implementations in wide use identify the presence of variability resulting from the subjective decisions of software implementors. Spurious variability in software complicates the processes of evaluation and comparison of alternative algorithms for cartographic tasks. No doubt, variability in implementation could be removed by rigorous study and specification of algorithms. Such future work must address the presence of digitising error in cartographic data. Our analysis suggests that it would be difficult to adapt the Douglas‐Peucker algorithm to cope with digitising error without altering the method. Copyright © 1991, Wiley Blackwell. All rights reserve

Line generalisation by repeated elimination of points

This paper presents a new approach to line generalisation which uses the concept of ‘effective area’ for progressive simplification of a line by point elimination. Two coastlines are used to compare the performance of this, with that of the widely used Douglas-Peucker, algorithm. The results from the area-based algorithm compare favourably with manual generalisation of the same lines. It is capable of achieving both imperceptible minimal simplifications and caricatural generalisations. By careful selection of cutoff values, it is possible to use the same algorithm for scale-dependent and scale-independent generalisations. More importantly, it offers scope for modelling cartographic lines as consisting of features within features so that their geometric manipulation may be modified by application- and/or user-defined rules and weights. The paper examines the merits and limitations of the algorithm and the opportunities it offers for further research and progress in the field of line generalisation. © 1993 Maney Publishing

The Impact Of The National Lock Down On Migrant Workers

A migrant worker is a person who either migrates within their home country or outside it to pursue work. Migrant workers usually do not have the intention to stay permanently in the country or region in which they work. The International Labour Organization estimated in 2014 there were 232 million international migrants worldwide who were outside their home country for at least 12 months and approximately half of them were estimated to be economically active, i.e. being employed or seeking employment (Mainstreaming of Migration in Development Policy and Integrating Migration in the Post-2015 UN Development Agenda).In India about 120 million people or more are estimated to migrate from rural areas to urban labour markets, industries and farms. Migration has become essential for people from regions that face frequent shortages of rainfall or suffer floods, or where population densities are high in relation to land. Areas facing unresolved social or political conflicts also become prone to high out migration. Poverty, lack of local options and the availability of work elsewhere become the trigger and the pull for rural migration respectively. During this after the their widespread of pandemic Covid-19 every one and especially migrant workers wish to go back to their home station because the workers think their lives are importantthanearningmoneyfortheir livelihood. Beside the migrant workers were scared that COVID-19 would take a couple of more years to subside and the safest thing was to be at home. Somanymigrantworkersexpresseda fear of returning their native place. The purposes of this paper are to examine the problems and challenges faced by migrant workers while travelling to their hometown and the measures taken by Government of India to ensure their safety. The present study is based on primary data collected from the sample population who moved from Chennai district of Tamilnadu to their native rural areas. Structured Questionnaire was used for survey and information were collected with the sample respondents through telephonic conversation. Chi- Square test has been employed to identify the issues and challenges of migrant workers

Issues And Challenges Of Hand Washing With Particular Reference To Prevention Of Covid -19

Hand washing also known as hand hygiene, is the act of cleaning one’s hands with soap and water to remove viruses/bacteria/germs/ microorganisms. If water and soap are not available, hands can be cleaned with ash although the benefits and harms are uncertain for reducing the spread of viral or bacterial infections. This is especially important for people who handle food or work in the medical field, but also an important practice for the general public. Hand hygiene is one of the most important element of infection control activities

BIOLOGICAL AND DOCKING STUDIES OF NOVEL AROYLHYDRAZONES

Objective: Novel aroylhydrazone schiff bases were synthesized and were screened for their biological activities.Methods: Using HCl as a catalyst, all the compounds were synthesized at room temperature and were characterized by IR and NMR techniques. The synthesized Schiff bases were screened for antibacterial, antifungal activities. In silico molecular docking, method was performed to study their anti-tuberculosis activity against enoyl acyl carrier protein reductase (InhA) from Mycobacterium tuberculosis (PDB id: 2NSD). Results: Compound P1 showed good antibacterial activity against gram positive (S. aureus) and gram negative (E. coli) bacterial strains and compound J1 showed good antifungal activity against A. niger. Molecular docking results reveal that compound B1 made two numbers of electrostatic interactions with 2NSD with more negative C docker interaction value. This indicated that the compound B1 was more active with minimum binding potential which is comparable with that of standard compound isoniazid.Conclusion: Aroylhydrazones having good biologically activities compared to that of standards were prepared

A SURVEY ON PRIVACY PRESERVING TECHNIQUES FOR SOCIAL NETWORK DATA

In this era of 20th century, online social network like Facebook, twitter, etc. plays a very important role in everyone's life. Social network data, regarding any individual organization can be published online at any time, in which there is a risk of information leakage of anyone's personal data. So preserving the privacy of individual organizations and companies are needed before data is published online. Therefore the research was carried out in this area for many years and it is still going on. There have been various existing techniques that provide the solutions for preserving privacy to tabular data called as relational data and also social network data represented in graphs. Different techniques exists for tabular data but you can't apply directly to the structured complex graph  data,which consists of vertices represented as individuals and edges representing some kind of connection or relationship between the nodes. Various techniques like K-anonymity, L-diversity, and T-closeness exist to provide privacy to nodes and techniques like edge perturbation, edge randomization are there to provide privacy to edges in social graphs. Development of new techniques by  Integration to exiting techniques like K-anonymity ,edge perturbation, edge randomization, L-Diversity are still going on to provide more privacy to relational data and social network data are ongoingin the best possible manner.Â

Covid – 19: Impact On The Indian Economy

The onset of COVID-19, the global economy is set to undergo a sharp double-dip recession. As many international agencies have already forecasted, the global growth could be -3 per cent in 2020, which is a decline of about 6 percentage points from the baseline projection of positive 3 per cent growth with no pandemic. Such swings in growth forecasts are unprecedented, and this is due to both health scare with lots of deaths and infections and also due to the lockdown of a major part of the global economy. Added to this, the pandemic appears to be more severe in the industrialized economy. While the forecasts for 2021 suggest a sharp rebound, the trends suggest that the world may need to endure this for a longer period than expected. Unlike the global economy, Indian economy was already in a slowdown phase before the pandemic affected and there were expectations that the economy is on a recovery path. But, with the COVID-19 such hopes are not only dented rather down turn turning out to be much deeper. There are various forecasts that suggest a sharper slowdown. Some forecasts even suggest a negative growth, which was not heard in the past five decades. With the lockdown and with increasing infections, the uncertainty in the economy has increased manifolds. There are also discussions about the shapeoftherecovery–VorUorW. But, in our view, the most probabilistic recovery could see an elongated U shape