Procurement assignment Case Study Example | Topics and Well Written Essays - 2500 words

Procurement assignment - Case Study Example When it comes to getting goods, raw materials and other kinds of specialized services, these organizations tends to rely on the process of procurement, in order to get the best suppliers for the intended services and goods needed for the success of their business goals and objectives (Amaratunga & Baldry 2002, p. 45). The procurement process, as used in such organizations refers to the act of acquiring services, goods and different kinds of works from external sources different from the business. In the process of procurement, it is very important that those particular goods and services as well as other kinds of works be very appropriate, being procured from the best and favorable costs that are according to the needs of the business organisation with respect to their quality and quantity standards. A procurement process that is professionally done enhances success in business functions, something that later becomes a competitive strategy for the particular businesses (Sekaran 2003, p. 23). Public and corporate bodies often define procurement as the processes aimed at promoting open and fair competition for their particular businesses while minimizing exposures to instances of fraud and collisions. This paper examines the process of procurement as done by an engineering firm that was seeking the services of oil explorers in Kazakhstan. Kazakhstan is one of largest countries in Europe, being estimated to have a size that is almost equivalent to that of Western Europe. The country comprises of a highly varied landscape that stretches all the way from the mountainous sections found to the east, going all the way to the vast lowlands that are energy rich to the west. Additionally, it includes the largely industrialized northern lands with their cold climates that go all the way to the steppes of the semi-desert of the central belt, all the way to the very fertile grasslands found to the south. Kazakhstan is a

Home video game industry analysis Essay Example for Free

Home video game industry analysis Essay History In 1949 the video game was thought of for the first time by an engineer named Ralph Baer but it would be years before video games would enter the spotlight. 1 In 1972 Steve Bushnell started the first gaming company Atari. Until 1978 there were very few games for the home system. In 1982 Atari releases a newer version and sales start to sore. In 1985 Nintendo enters the market with the NES. Nintendo still outsells both companies 10 to 1. In 1995 Sega releases Sega Saturn three months before the projected date and there are not enough games released because of this and sales are dismal. The same year Sony releases the Playstation at $100 less than expected with a variety of different game titles, sales are strong. In 1996 Nintendo releases the N64 which is received well by the public. Sega lowers prices to stay competitive. In 1999 Nintendo and Sony are in an intense pricing war on their competing systems. Microsoft also announces they will be entering the market with the X-Box. Nintendo releases the Gamecube and the Gameboy advance the same year. X-Box is released in 2001 and is received well and is out of stock most places. With all of the systems and game prices very high, piracy is becoming more and more of a problem with Mod Chips being developed that allow for pirated games to be played on all consoles. In late 2005 Microsoft releases the X-Box 360. 2 The following year Nintendo releases the Wii and Sony releases Playstation 3 and the problem of piracy still continues to this day. SWOT Analysis Industry strengths include well developed brand image for the leading three competitors. Each of the three leading competitors has successfully exploited its target consumers in age categories. They all have excellent advertising campaigns and have high corporate attention and resources. Industry weakness include rising cost of materials and RD, the expenditures for developing additional high tech systems and games for the system at a reasonable price is becoming increasingly difficult leaving much lower profits for corporations. Opportunity exists when entry into the market is preceded by all others in the industry. Industry trends are leaning towards older population who appreciate graphics and complexity of games and have the resources to pay more for those games. Many gamers are ready to upgrade systems as new technology emerges. Threats to the industry include strong market competition, rapid development of technology, the cost of technology and the rating system given to games. Sub-markets are also gaining popularity including the handheld market and online gaming, which threaten market share. Business and Corporate Strategy Corporate and business level strategies for this industry are equivalent. The inferred industry mission is to provide entertainment through interactive technology. The industry as a whole falls into the maturity segment of the life cycle. Generic competitive industry average is differentiation among games, graphics, and abilities/extras of the game console. In the beginning the strategy focused on the hardware to make profits. 3 The strategy has shifted to software for increased growth. Functional strategies include; superior quality in game graphics and well built hardware. Games have evolved from single applications to cartridges to CD-ROM. Graphics have evolved similarly from 8 to 16 to 32 bit. Threats stated in the SWOT analysis can be minimized by staying at the forefront of the competition in RD and finding ways to keep down cost while offering superior products. A venture into a back to the basics approach with the Wii has proved successful to attract female and novice users. Structure and Control Systems Strategic managers in the Video Game industry have developed a set of strategies to build competitive advantage to achieve their goals. Then an organizational structure has been put in place to use resources to create a competitive advantage. To evaluate how well the strategy and structure are working, managers developed specific performance measures. The four building blocks of competitive advantage are efficiency, quality, innovation, and responsiveness to customers. Recommendations With the home video game industry evolving, there are a few things that need to be in mind as you try to improve. You need to stay technologically advanced by continuing to change games, software, and new models. These adjustments require this technology to be low cost to be successful in this industry. If costs are high, not only will the customer be lost but you may lose your competitive edge. Competitive advantage in this industry is a critical factor. If you are ahead in the industry at one point, another company can come out with the next best selling product with new features and graphics capturing market share. Furthermore, being competitive in the sense of efficiency, quality, and response to the customers is critical in this industry. It influences a customer to buy your product rather than the competitors. If you have good quality and low prices, the customers would be willing to upgrade to the newer product line. With the industry constantly changing, you need to be on top of your game to be on top of the home video gaming industry.

Image Deblurring with Sparse Representation

Image Deblurring with Sparse Representation AN APPROACH FOR IMAGE DEBLURRING: BASED ON SPARSE REPRESENTATION AND REGULARIZED FILTER AbstractDeblurring of the image is most the fundamental problem in image restoration. The existing methods utilize prior statistics learned from a set of additional images for deblurring. To overcome this issue, an approach for deblurring of an image based on the sparse representation and regularized filter has been proposed. The input image is split into image patches and processed one by one. For each image patch, the sparse coefficient has been estimated and the dictionaries were learned. The estimation and learning were repeated for all patches and finally merge the patches. The merged patches are subtracted from blurred input image the deblur kernel to be obtained. The deblur kernel then applied to regularized filter algorithm the original image to be recovered without blurring. The proposed deblur algorithm has been simulated using MATLAB R2013a (8.1.0.604). The metrics and visual analysis shows that the proposed approach gives better performance compared to existing methods. Keywords-Image deblurring, Dictionary learning based image sparse representation, Regularized filter. I. INTRODUCTION Deblurring is one of the problems in image restoration. The image deblurring due to camera shake. The image blur can be modelled by a latent image convolving with a kernel K. B = K à ¢Ã…  -I + n, (1) where B, I and n represent the input blurred image, latent image and noise respectively. The à ¢Ã…  - denotes convolution operator and the deblurring problem in image is thus posed as deconvolution problem [13]. The process of removing blurring artifacts from images caused by motion blur is called deblurring. The blur is typically modeled as the convolution of a point spread function with a latent input image, where both the latent input image and the point spread function are unknown. Image deblurring has received a lot of attention in computer vision community. Deblurring is the combination of two sub-problems: Point spread function (PSF) estimation and non-blind image deconvolution. These problems are both independently in computer graphics, computer vision, and image processing [13]. Finding a sparse representation of input data in the form of a linear combination of basic elements. It is called sparse dictionary learning and this is learning method. These elements are compose a dictionary. Atoms in the dictionary are not required to be orthogonal [10]. One of the key principles of dictionary learning is that the dictionary has to be inferred from the input data. The sparse dictionary learning method has been stimulated by the signal processing to represent the input data using as few possible components. To unblurred an image the non-blind deconvolution blur Point Spread Function (PSF) has been used [14]. The previous works to restore an image based on Richardson-Lucy (RL) or Weiner à ¯Ã‚ ¬Ã‚ ltering have more noise sensitivity [15 16]. Total Variation regularizer heavy-tailed normal image priors and Hyper-Laplacian priors were also widely studied [17]. Blind deconvolution can be performing iteratively, whereby each iteration improves the estimation of the PSF [8]. In [3] found that a new iterative optimization to solve the kernel estimation of images. To deblur images with very large blur kernels is very difficult. to reduce this difficulty using the iterative methods to deblur the image. From [1] found that to solve the kernel estimation and large scale optimization is used unnatural l0 sparse representation [1]. The properties for latent text image and the difficulty of applying the properties to text image de-blurring is discussed in [2]. Two motion blurred images with different blur directions and its restoration quality is superior than when using only a single image [5]. A deblurring methods can be modelled as the observed blurry image as the convolution of a latent image with a blur kernel [6]. The camera moves primarily forward or backward caused by a special type of motion blur it is very difficult to handle. To solve this type of blur is distinctive practical importance. A solution to solve using depth variation [8]. The feature-sign search for solving the l1-least squares problem to learn coefficients of problem optimization [9][10] and a Lagrange dual method for the l2-constrained least squares problem to learn the bases for any sparsity penalty function. II. IMAGE DEBLURRING WITH DICTIONARY LEARNING To estimate the deblur kernel, an iterative method to alternately estimate the unknown variables, one at a time, which divides the optimization problem into several simple ones in each iteration. Were performed more importantly, the dictionary D is learned from the input image during this optimization process. The algorithm iteratively optimizes one of K, D, ÃŽÂ ± by à ¯Ã‚ ¬Ã‚ xing the other two, and à ¯Ã‚ ¬Ã‚ nally obtains the deblurring kernel. With the estimated kernel, any standard deconvolution algorithm to recover the latent image can be applied. The initial dictionary and the initial kernel value is convoluted and this result will be called as dictionary and this dictionary is subtracted by blur image. Fig.1 block diagaram for deblurring algorithm is shown in below A. Estimate Sparse Coefficient To follow the below algorithm to estimating the sparse coefficients of the given input blurred image. ALGORITHM I Step 1: Get the blurred input image B Step 2: Spilt the B into four patches as p1,p2,p3,p4. Step 3: Consider first image patch p1 and find the sparse coefficient to fix K using Gaussian kernel and D as identity matrix. ÃŽÂ ±(n+1) = argmin||ÃŽÂ ±||1 (2) s.t. b =(K(n) à ¢Ã…  -D(n))ÃŽÂ ± (3) Step 4: For each iteration the ÃŽÂ ± value should be updated into D Step 5: Take N iterations to estimating the ÃŽÂ ±(n+1). Step 6: Repeat the above 5 steps to all image patches and estimate the ÃŽÂ ±(n+1). B. Updating Dictonary In the knowledge of previous algorithm using the sprase coefficient to updating the dictionary of the image. ALGORITHM II Step 1: To update the dictionary, deconvolve blurred image with kernel up to Last iteration using any deconvolution algorithm and get Ip. Step 2: Ip image is split into four patches. Step 3: Update the dictionary using ÃŽÂ ±(n+1) and D. D(n+1) = min||Ip à ¢Ã‹â€ Ã¢â‚¬â„¢D(n)ÃŽÂ ±(n+1)||22.(4) Step 4: Repeat the steps 1 to 3 to all image patches and estimating the D(n+1). C.Recovering Deblur Image Consider previous algorithm to estimate the deblur kernel of the image and finally to recovered the deblur image. ALGORITHM III Step 1: Find the latent image patch using Ip(n+1) = D(n+1)ÃŽÂ ±(n+1)(5) Step 2: Merge the all image patches of Ip. Step 3: The reconstructed image is subtracted from the blurred input image to obtain the deblur kernel. Step 4: Perform the deconvolution with the input blurred image and Deblur kernel using wiener deconvolution method. Step 5: Apply the regularization filter to the wiener deconvolution image to recover the original image. After that the RMSE, PSNR, SSIM and visual perception were analyzed for various images. III. SIMULATION RESULTS To implement the deblur algorithm is simulated using MATLAB R2013a (8.1.0.604). The root mean square error, power to signal noise ratio, structural similarity index metric and visual perception were analyzed for various images. From the analysis, it is observed that the deblurring were efficiently performed. Also carry out experiments with images blurred by randomly generated kernel. The existing deblurring algorithms are usually developed to deal with motion blur problems in which the kernels are oriented and simple. However, the camera shakes are complex and cannot be modeled well with simple blur kernels. This algorithm is able to recover the latent image with more details and better contrast. The initial kernel K0 is set to be theGaussian kernel with à Ã†â€™ =1, and ÃŽâ€Å" is set as 1 and identity matrix I. The colour images are used for experiments and crop a small portion ( e.g. 512ÃÆ'-512 pixels) of the tested image to estimate kernel using the algorithm as given in Chapter 2.The regularized filter algorithm has been used to reconstruct image I. The à ¯Ã‚ ¬Ã‚ nal deblurred image can be recovered once the deblur kernel is estimated. (a) (b) (c) Fig.2. Experimentel results of deblurring algorithm. (a) blurred image (original size is 256 ÃÆ'- 256);(b) deblurred image 1;(c)final deblurred image; A. Performance Measurement The root mean square error(RMSE), power to signal noise ratio(PSNR), structural similarity index metric(SSIM) and visual perception were analyzed for various images. From the analysis, it is observed that the deblurring were efficiently performed for the use sparse representation of the image. If the accuracy of the estimated kernel is improved at each iteration, the proposed algorithm will à ¯Ã‚ ¬Ã‚ nd a reasonably good solution. Further reducing the RMSE comparable to other methods. TABLE I:RMSE VALUES UNDER DIFFERENT ALGORITHMS Image Fergus [11] Shan [12] Zhe Hu [13] Deblur Image(1) Deblur Image(2) Barbara 5.53 7.02 4.61 3.51 1.27 Koala 5.41 6.57 5.10 3.21 1.06 Castle 1 7.87 7.46 6.73 3.12 1.05 TABLE 2:PSNR VALUES UNDER DIFFERENT ALGORITHMS Image Fergus [11] Shan [12] Zhe Hu [13] Deblur Image(1) Deblur Image(2) Barbara 33.27 31.20 34.85 37.21 46.03 Koala 33.46 31.77 33.97 37.87 47.54 Castle 1 30.21 30.67 31.57 38.23 47.57 RMSE and PSNR comparison for different deblurring methods shown in the table. The experiments are conducted using four test images, namely Barbara, koala, castle1. TABLE 3:SSIM VALUES FOR OUR ALGORITHMS Image Deblur Image(1) Deblur Image(2) Barbara 0.7354 0.5427 Koala 0.7592 0.5486 Castle 1 0.8124 0.6495 From the analysis, it is observed that the deblurring were efficiently performed. Because of the ssim value should be less than 1. IV. CONCULSION AND FUTURE WORK In this paper, we propose an effective deblurring algorithm with dictionary learning using one single image were simulated. By decomposing the blind deconvolution problem into three portions deblurring and learning sparse dictionary from the image, our method is able to estimate blur kernels and thereby deblurred images. Experimental results show that this algorithm achieves favourable performance. In future the deblurring algorithm is to be implement on FPGA with suitable architectures. V. REFERENCES [1] L. Xu, S. Zheng, and J. Jia, Unnatural 0 sparse representation for natural image deblurring, in Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR), Jun. 2013, pp. 1107-1114. [2] H. Cho, J. Wang, and S. Lee, Text image deblurring using text specià ¯Ã‚ ¬Ã‚ c properties, in Proc. Eur. Conf. Comput. Vis. (ECCV), Oct. 2012, pp. 524-537. [3] L. Xu and J. Jia, Two-phase kernel estimation for robust motion deblurring, in Proc. Eur. Conf. Comput. Vis. (ECCV), Sep. 2010, pp. 157-170. [4] J. P. Oliveira, M. A. T. Figueiredo, and J. M. Bioucas-Dias, Parametric blur estimation for blind restoration of natural images: Linear motion and out-of-focus, IEEE Trans. Image Process., vol. 23, no. 1, pp. 466-477, Jan. 2014. [5] H. Zhang, D. Wipf, and Y. Zhang, Multi-observation blind deconvolution with an adaptive sparse prior, IEEE Trans. Pattern Anal. Mach. Intell., vol. 36, no. 8, pp. 1628-1643, Aug. 2014. [6] O. Whyte, J. Sivic, A. Zisserman, and J. Ponce, Non-uniform deblurring for shaken images, Int. J. Comput. Vis., vol. 98, no. 2, pp. 168-186, 2012. [7] A. Gupta, N. Joshi, C. L. Zitnick, M. Cohen, and B. Curless, Single image deblurring using motion density functions, in Proc. 11th Eur. Conf. Comput. Vis.(ECCV), Sep. 2010, pp. 171-184. [8] S. Zheng, L. Xu, and J. Jia, Forward motion deblurring, in Proc. IEEE Int. Conf. Comput. Vis. (ICCV), Dec. 2013, pp. 1465-1472. [9] T. Goldstein and S. Osher, The split Bregman method for L1-regularized problems, SIAM J. Imag. Sci., vol. 2, no. 2, pp. 323-343, 2009. [10] H. Lee, A. Battle, R. Raina, and A. Y. Ng, Efà ¯Ã‚ ¬Ã‚ cient sparse coding algorithms, in Advances in Neural Information Processing Systems 19. Cambridge, MA, USA: MIT Press, 2007, pp. 801-808. [11] R. Fergus, B. Singh, A. Hertzmann, S. T. Rowels, and W. T. Freeman. Removing camera shake from a single photograph. In SIGGRAPH, 2006. [12] Q. Shan, J. Jia, and A. Agarwala. High-quality motion deblurring from a single image. In SIGGRAPH, 2008. [13] Z. Hu, J.-B. Huang, and M.-H. Yang, Single image deblurring with adaptive dictionary learning, in Proc. 17th IEEE Int. Conf. Image Process. (ICIP), Sep. 2010, pp. 1169-1172. [14] L.Lucy.An iterative technique for the rectià ¯Ã‚ ¬Ã‚ cation of observed distributions. Astronomical Journal, 79(6):745-754, 1974. [15] W. Richardson. Bayesian-based iterative method of image restoration. Journal of the Optical Society of America, 62(1):55-59, 1972. [16] N.Wiener, Extrapolation, Interpolation and Smoothing of Stationary Time Series. MIT Press, 1964. [17] A. Levin, Y. Weiss, F. Durand, and W. T. Freeman, Understanding blind deconvolution algorithms, IEEE Trans. Pattern Anal. Mach. Intell., vol. 33, no. 12, pp. 2354-2367, Dec. 2011.

Adolf Hitler Essay -- essays research papers

ADOLF HITLER ESSAY 8   Ã‚  Ã‚  Ã‚  Ã‚  Defeat in WWI shocked the German people. Despair increased as the army returned to a bankrupt country. Millions of Germans could find no jobs. A weak republic had replaced the defeated empire.   Ã‚  Ã‚  Ã‚  Ã‚  After the war Hitler returned to Munich and joined a small nationalist group called the German Workers’ Party. In 1920 this group changed its name to the Nationalist Socialist German Workers’ Party, which became known as the Nazi Party. The Nazis called for the union into one nation of all Germans, including those in other countries. They favored the creation of a strong central government and cancellation of the Versailles Treaty.   Ã‚  Ã‚  Ã‚  Ã‚  Hitler was a skillful schemer, politician, and organizer. He became a leader of the Nazis and built up party membership quickly. Hitler attacked the government, and declared that only the Nazi party could assure jobs for the workers and greatness for Germany. He also organized a private army of men who became known as Storm Troopers. They fought Communists and others who tried to break up the Nazi rallies. By Oct, 1923, the Storm Troops numbered 15,000 men, armed with machine guns and rifles. Hitler used brown-shirted uniforms and the swastika emblem to give his followers a sense of unity.   Ã‚  Ã‚  Ã‚  Ã‚   On Nov. 8, 1923, at a rally in a Munich beer hall, Hitler proclaimed a Nazi revolution. The next day he tried to seize the Bavarian...

Watershed Management

Society and Polity 2010 Watershed Management – A Hope for Sustainable Development Table of Contents Watershed2 Integrated Watershed Management2 Categorization of Watersheds2 Need for Watershed Management:3 Characteristics of Watershed Management:3 Successful case of Watershed management in Maharashtra3 Approaches/methods used for people's participation4 Persuasion4 Gandhian Approach4 Creation of a common platform4 Selfless leadership5 Identification of the most pressing common problem5 Achievements at Ralegan Siddhi5 ————————————————-Watershed Management: A Hope for Sustainable Development Watershed A Watershed is defined as a topographically delineated geographical area in which the entire run-off tends to converge, through the existing drainage system, to the common outlet of the area for subsequent disposal. In other words, a watershed is an independent drainage u nit. Integrated Watershed Management It is the process of creating and implementing plans, programs, and projects to sustain and enhance watershed functions that affect the plant, animal, and human communities within a watershed boundary Categorization of WatershedsWatersheds are categorized on the basis of the following criteria: * Based on Size: Based on size, the watersheds can be classified into micro, mini and large watersheds. The watersheds with area less than 500 ha are called as micro watersheds. The watersheds with area more than 500 ha but less than 2000 ha are called as mini watersheds. The watersheds with area more than 2000 ha are called as large watersheds. * Based on Drainage: Based on drainage, watersheds can be classified into drains and streams. Drains refer to the smaller water channels whereas streams refer to the larger water channels. Based on Shape: Based on shape, watersheds can be classified into two types namely fan-shaped and fern-shaped. Fan shaped water sheds are those which are circular or nearly circular in shape. Fern shaped watersheds are those which are elongated in shape. * Based on Other Criteria: Watersheds can also be classified according to other factors viz. altitude (high watersheds and flat watersheds), moisture content (arid watersheds and wet watersheds), type of soil (black-soil watersheds and red-soil watersheds), etc. Need for Watershed Management:Watersheds are an asset and therefore they need to be managed properly so that we are able to utilize them in the years to come. They act as a source of water for the people living in and around watershed areas. They help in maintaining the nutrients of the soil, thereby supporting the agriculture sector to give a sustained yield. They also act as a good source of irrigation for the fields throughout the year. Since they support vegetation, they also help in reducing soil erosion as the roots of the vegetation hold together the top layer of the fertile soil.They also hel p in the development of the forests as they act as good source of water for the forest flora and fauna. Objectives: * Water has multiples uses and must be managed in an integrated way. * Water should be managed at the lowest appropriate level. * Water allocation should take account of the interests of all who are affected. * Water should be recognised and treated as an economic good. Strategies: * A long term, viable sustainable future for basin stake holders. * Equitable access to water resources for water users. The application of principles of demand management for efficient utilisation. * Prevention of further environmental degradation (short term) and the restoration of degraded resources (long term). Characteristics of Watershed Management: * Allowing an adequate supply of water that is sustainable over many years. * Maintains water quality at level that meets government standards and other social water quality objectives. * Allows sustainable economic development over the sho rt and long term. Successful case of Watershed management in Maharashtra Development fundamentally refers to human beings.It should be a human experience to meet people's physical, mental and emotional aspirations and potentials, not just in economic terms but should also lead to a sense of self-sufficiency and fulfilment. Ralegan Siddhi, often termed as an oasis of greenery surrounded by dry and bare hilly tracts is a unique example of transformation from poverty to plenty and a living model of people's participation in natural resource management in a watershed. Ralegan Siddhi is a small village with an area of 982 ha in Parner county (taluka) of Ahmadnagar district, Maharashtra, India.It is a drought-prone and resource poor area with annual rainfall ranging between 50-700 mm and temperature varying between 28Â °C and 44Â °C. The village is surrounded by small hillocks on the northeast and southern sides. The land is undulating and slopes vary from 3-15%. The 1991 Census enumera ted a population of 1,982 living in 310 households (presently estimated to be around 325). The sex-ratio being 902 females per 1,000 males (1,029 in 1971; 1,013 in 1981). The continued decrease in the ratio is explained as the return of male folk to the village with improvement in the socio-economic conditions of the village.Backward classes (scheduled castes and scheduled tribes) constitute only 14. 23% of the total population. Marathas of Khatri caste out-number other castes and constitute nearly two-third of the families. Among others are the backward castes including Mhar, Chamar, Bharhadi, Pardi, Sutar, Barber, Fishermen, Matang etc. By 1975, prior to intervention by Mr. Anna Hazare, the village had become quite notorious with all sorts of social evils, moral down fall and with badly shattered economic conditions. In general, the village presented the profile of a poverty-stricken and debt-ridden society.Scarcity of water was key to distress which limited the prospects of agric ulture. The water table was below 20 m, most of the wells used to dry up during summer and the drinking water had to be fetched from the neighbouring villages. The high rate of surface run off, due to high degree of slope and lack of vegetative cover had washed away the top fertile layer of the soils. Barely 20 ha of the village area was under irrigation. As a consequence the agricultural production was too meagre to support and sustain the livelihoods of the people particularly the resource poor farmers.Not even 30% of the food grain requirements could be met from rain-fed mono-cropping practised in the village. Approaches/methods used for people's participation The approaches/methods used by him for the participation of farmers in natural resource management works are highlighted below. Persuasion First of all, Anna went through a careful envisioning of the deteriorating situation in village life and decided to initiate through religion-moral undercurrent by persuading the people for reconstruction of Sant Yadava Baba temple.But he failed to impress and influence the people at large, primarily because the people were too busy with their own business and the worldly affairs. Gandhian Approach The second step was to set up examples by self-practising rather than mere preaching as Mahatma Gandhi used to do. Initially it went on unnoticed but in due course it gathered momentum. Particularly, he tried to organize the youths of the village under ‘Tarun Mandal' (youth organization). Besides, participation from all the sections of society was ensured and encouraged.Creation of a common platform Keeping all the differences and disparities aside, a common platform and meeting ground was created in the form of Sant Yadav Baba's temple. People started sitting in groups during evenings and discussing about the affairs of the village and common concern. Thus, the process of friendship, cooperation and communication started. Selfless leadership Anna himself invested all the money he had (Rs. 20,000) for purchasing building materials for the temple before asking others to contribute. Identification of the most pressing common problemThe main reason of disintegration, division and distress of the village society was the lack of a sound livelihood support system. The economy of the village was agrarian and shortage of water for irrigation was the major constraint to its development. Thus, assured availability of water was collectively identified as the top priority in a meeting of villagers. Achievements at Ralegan Siddhi Successful abolition of social evils like alcoholism, dowry, corruption and the caste system. These changes paved the way for positive steps to development.Regeneration of watershed resources through people's participation, a living example of watershed development and management. Development of agriculture and allied sectors by better farming practices and cropping patterns, judicious use of water by introducing drip irrigation system, yield enhancement etc. as a result the village where nearly three-fourth population was below poverty line, has become self sufficient and is surplus in food grains, today. Conclusion * Improving agricultural productivity. * Improving vegetative covers. * Increasing fodder & food availability. Reducing soil erosion & nutrient loss. * Improve water availability of surface & groundwater. * Enhancing quality of life among local communities.The case study shows the success of Gandhian approach to people's participation in watershed management. Since 1975, this has resulted into participation of all the 325 village families, renovation of a temple, stopping illicit liquor distillation, water harvesting in 4 small watersheds, construction of many check dams, plantation of five hundred thousand forest trees, controlled grazing, raising of ground water level rom 20 m depth to 6. 5 m, sale of onions worth Rs. 80 million in 1995 alone (exchange rate in June 1995 1 US$ = Rs. 31. 3), so lar street lights, village toilets, biogas, organic farming, introduction of livestock, a full high school, institutionalization of decision making at village assembly level, local voluntary organizational capacity building, acceptance and application of voluntary code of conduct, formation of different action committees, etc. References

Putting grammar in its place - Emphasis

Putting grammar in its place Putting grammar in its place For a writing-training company, we run surprisingly few grammar and punctuation courses. To be more precise, we run few courses that focus solely on grammar and punctuation even though more people come to us asking for training in just this area than in any other. And why? Are we phasing the subjects out? Do we not think them important? Has everyone, including us, given up caring? Goodness, no. The fact that our clients often dont end up taking a grammar and punctuation course is not because were keeping it all for ourselves. Rather, its that when they describe their needs in more detail, it often turns out that theyre looking for something broader than just grammar and punctuation. Grammar can be a red herring Most people have a clear idea of what punctuation is, but grammars a little tougher to define. Putting it broadly, grammar is the structure of language: things such as different word classes (verbs, nouns, adjectives, etc) and how words relate to each other or change to show different inflections (such as number, tense and case). However, thanks to the promulgation of so-called rules such as dont start a sentence with a conjunction or dont split infinitives, grammar can seem like a narrow set of procedures that you have to master in order to write well. Peevish articles that get passed around online only add to the misapprehensions (many have cited this one, to which writer and editor Stan Carey has written this comprehensive reply). Such articles tend to further muddy already murky waters by confusing personal preferences or long-standing superstitions (which are usually just extremely old personal preferences) with genuine guidance on rules that will give your writing real clarity. For example, contrast the rule about misplaced modifiers, where the writer inadvertently modifies the wrong part of the sentence, with the superstition that its wrong to put prepositions at the end of a sentence. It does make sense to avoid misplaced modifiers, such as: Showing strong growth, the chief executive presented an impressive set of results. These can bewilder your reader or undermine your writing (not to mention anger chief executives who dont care to have attention drawn to their waistlines). Ending on a preposition, however, is no barrier to clarity. When people approach us with grammar and punctuation on their minds, it may be that theyve noticed errant apostrophes in their teams work, that the writing isnt following a logical structure, or simply that theyre not getting the results they want. Improving writing skills can make a great difference, but theres more to it than blindly following prescriptive mandates. The bigger picture On her academic writing blog, Explorations of style, English language lecturer Rachael Cayley points out that fretting about grammar in isolation, as if it were some loose screw that needed tightening, misses the point and can actually be counterproductive. Improving your writing isnt just fiddling with technicalities and arcane rules, she says. It is a matter of thinking deeply about your ideas and your communicative intent. Theres plenty more to think about when it comes to good writing: planning; structuring (yes, sentences, but also your entire document); drawing the reader in and keeping them hooked; building your argument; picking the best word for the job; and always (always!) considering the needs of the reader. So were not saying grammar isnt important. Of course it is. Its just not the whole story. If you want to have a chat about where grammar fits into your companys story, or how you can get the results youre looking for, call us on +44 (0)1273 732 888. Or take a look online at the courses we offer.