Algorithms for pre-processing and processing stages of x-ray images

Algorithms for pre-processing and processing stages of x-ray images 1.1 Introduction This chapter presents algorithms for pre-processing and processing stages of both cervical and lumbar vertebrae x-ray images. Pre-processing stage here is the process of locating and enhancement the spine regionof interestin the x-ray image, where the processing stage includes the shape boundary representation and segmentation algorithms based feature vectors extraction and morphometric measurement. In this research the spine vertebrae are introduced and the objectives of segmentation algorithm are discussed. Then various general segmentation approaches including those based on the shape boundary extraction are discussed and applied to our spinal x-ray image collection. The current approach is introduced with a flow diagram and then the individual blocks of the segmentation process are taken up and discussed in detail. 1.2 Image Acquisition A digital archive of 17,000 cervical and lumbar spine x-ray images from the second National Health and Nutrition Examination Survey (NHANES II) is maintained by the Lister Hill National Center of Biomedical Communications in the National Library of Medicine (NLM) at the National Institutes of Health (NIH). Among these 17,000 images, approximately 10,000 are cervical spine x-rays and 7,000 are lumbar x-rays. Text data (including gender, age, symptom, etc.) are associated with each image. This collection has long been suggested to be very valuable for research into the prevalence of osteoarthritis and musculoskeletal diseases. It is a goal of intramural researchers to develop a biomedical information resource useful to medical researchers and educators. Figure 3.1 shows two sample images from the database. Spine x-ray images generally have low contrast and poor image quality. They do not provide meaningful information in terms of texture or color. Pathologies found on these spine x-ray images that are of interest to the medical researchers are generally expressed along the vertebral boundary. (a) (b) 1.3 Proposed segmentation scheme The proposed process main stages scheme shown at Figure3.2, followed by a details review of the used methods applied to our spinal images and can be listed as follow: a. Pre-processing stage include image acquisition, region localization (RL) and region localization enhancement. b. Shape boundary representation and segmentation stage; include active shape model (ASM) segmentation based on two shape boundary representation 9-anatomical points and b-spline representation. c. Feature extraction stage; include feature extraction based shape feature vector and morphometric measurement-invariant features for indexing. d. Classification and similarity matching stage; include feature models classifier and similarity matching for diagnosis and retrieval 1.4 Pre-processingstage 1.4.1 Spineregion localization Region localization (RL) refers to the estimation of boundaries within the image that enclose objects of interest at a coarse level of precision. RL is important for assisting human experts in rapid image display and review (independent of its use in initializing a segmentation process). For example, with an algorithm that can rapidly, and with high probability identify the spine region with a marked line passing, this region of interest can be automatically zoomed on the display even though the location and orientation of the spine may vary appreciably in these images. This algorithm assumes that a line passing through the maximum amount of bone structure in the image will lie over a large part of the spine area, given a line passing through the image; Figure 3.3 shows the region localization (RL) selection of both cervical and lumbar images. (a) (b) 1.4.2 Enhancement approach Image enhancement is significant part of AVFAS recognition systems. Changes in lighting conditions produces dramatically decrease of recognition performance, if an image is low contrast and dark, we wish to improve its contrast and brightness. The widespread histogram equalization cannot correctly improve all parts of the image. When the original image is irregularly illuminated, some details on resulting image will remain too bright or too dark. Typically, digitized x-ray images are corrupted by additive noise and de-noising can improve the visibility of some structures in medical x-ray images, thus improving the performance of computer assisted segmentation algorithms. However, image enhancement algorithms generally amplify noise [17, 18]. Therefore, higher de-noising performance is important in obtaining images with high visual quality for that reason different enhancement techniques was implemented i. Adaptive histogram-based equalization ( Filter 1) Adaptive histogram-based equalization (AHE) can be applied to aid in the viewing of key cervical and lumbar vertebrae features, and its an excellent contrast enhancement method for medical image and other initially no visual images. In medical imaging its automatic operation and effective presentation of all contrast available in the image data make it a competitor of the standard contrast enhancement methods. The goal of using adaptive histogram equalization is to obtain a uniform histogram for the output image, so that an optimal overall contrast is perceived. However, the feature of interest in an image might need enhancement locally. Adaptive Histogram Equalization (AHE) computes the histogram of a local window centred at a given pixel to determine the mapping for that pixel, which provides a local contrast enhancement. However, the enhancement is so strong that two major problems can arise: noise amplification in flat regions of the image and ring artifacts at strong edges [12, 13]. Histogram equalization maps the input images intensity values so that the histogram of the resulting image will have an approximately uniform distribution [9-11].The histogram of a digital image with gray levels in the range [0, L-1] is a discrete function Where is the gray level, is the number of pixels in the image with that gray level, is the total number of pixels in the image, and k =0, 1, 2 L-1, basically gives an estimate of the probability of occurrence of gray level The local contrast of the object in the image is increased by applied histogram equalization, especially when the applied data of the image is represented by close contrast values. Through this adjustment the intensity can be better distributed on the histogram, this allows for areas of lower local contrast to gain a higher contrast without affecting the global contrast. (a) (b) ii. Adaptive contrast enhancement The idea is to enhance contrast locally analyzing local grey differences taking into account mean grey level. First we apply local adaptive contrast enhancement. Parameters are set to amplify local features and diminish mean brightness in order to obtain more contrast resulting image. After that we apply histogram equalization. Adaptive gamma value Gamma correction Gamma correction operation performs nonlinear brightness adjustment. Brightness for darker pixels is increased, but it is almost the same for bright pixels. As result more details are visible. 1.5 Shape boundary segmentation Shape boundary segmentation presented at this work is a hierarchical segmentation algorithm tailored to the segmentation of cervical and lumbar vertebrae in digitized x-ray images. The algorithm employs the both shape boundary representation schemes, 9-anatomical points representation (9-APR) and B-spline representation (B-SR) to obtain a suitable initialization for segmentation stage that utilize active shape models (ASMs) proposed by Cootes et al. The advantage of using ASMs in medical image segmentation applications is that rather than creating models that are purely data driven, ASMs gain a priori knowledge through a thorough observation of the shape variation across a training set. 1.5.1 Shape boundary representation Shape is an important characteristic for describing pertinent pathologies in various types of medical image and its a particular challenges regarding vertebra boundary segmentation in spine x-ray images. It was realized that the shape representation method would need to serve the dual purpose of providing a rich description of the vertebra shape while being acceptable to the end user community consisting of medical professionals. In order to model the spinal vertebra shape we presented by term of set points chosen to place point around the boundary , this must be done for each shape at training stage and the labelling point its important. Two schemes list has been used at this stage to determine a vertebra boundary shape in terms of list points i. 9-anatomical point representation (9-APR) We obtained segmentation data created by medical expertise at an early state of our segmentation work; the purpose of this task was to acquire reference data as a guideline for validating vertebrae segmentation algorithms. These data consisted of (x, y) coordinates for specific geometric locations on the vertebrae; a maximum of 9-anatomical points representation (9-APR) assigned and marked by board certificate radiologist that is indicative of the pathology found to be consistently and reliably detectable per vertebra were collected . Figure 3.7 shows below the points were placed manually on each vertebrae and which is the interest to medical researchers. Points 1, 3, 4, and 6 are indicative of the four corners of the vertebral body as seen in a projective sagittal view. Points 4 and 3 mark the upper and lower posterior corners of the vertebra, respectively; Points 6 and 1 mark the upper and lower anterior corners of the vertebra, respectively. Points 5 and 2 are the median along the upper and lower vertebra edge in the sagittal view; Point 8 is the median along the anterior vertical edge of the vertebra in the sagittal view. Note that Points 7 and 9 mark the upper and lower anterior osteophytes, so if osteophyte(s) are not present on the vertebra, then these points (7-9) coincide with points 6 and 1, respectively. ii. B-spline representation (B-SR) Representation of curves using piecewise polynomial interpolation to obtain curves is widely used in computer graphics .B-spline are piecewise polynomial curves whose shape is closely related to their control polygon a chain of vertices giving a polygonal representation of curves. B-splines of the third order are most common because this is the lowest order which includes the changes of curvatures. The Advantage of using B-spline techniques at this research is to enhance the 9-anatomical points, B-spline curves require more information (i.e., the degree of the curve and a knot vector) and a more complex theory than Bà ©zier curves. But, it has more advantages to offset this shortcoming. * B-spline curve can be a Bà ©zier curve. * B-spline curves satisfy all important properties that Bà ©zier curves have. * B-spline curves provide more control flexibility than Bà ©zier curves can do. * The degree of a B-spline curve is separated from the number of control points. More precisely [ReF]. We can use lower degree curves and still maintain a large number of control points and also we can change the position of a control point without globally changing the shape of the whole curve (local modification property). Since B-spline curves satisfy the strong convex hull property, they have a finer shape control. Moreover, there are other techniques for designing and editing the shape of a curve such as changing knots. B-spline is a generalization of the Bezier curve [Ref] , let a vector known as the knot vector be defined, Where, is a no decreasing sequence with and define control points, Define the degree as ,The knots are called internal knots. 1.5.2 Modelling Shape Variations In ASM, an object shape is represented by a set of landmark points and requires a good initialization of an objects pose in an image (i.e., location, size, and angle of rotation); therefore, we used the two schemes representation (9-APR B-SR) in our proposed segmentation technique to create this initialization. Several instances of the same object class are included in a training set and in order to model the variations we need to align the set of shapes. i. Training set In order to build a model that is flexible enough to cover the most typical variations of vertebrae, a sufficiently large training set has to be used. For the purpose of the investigation reported in this work, we locate the shape (by eye) and its important that the two schemes representations are accurately located and that there is an exact correspondence between labels in different instances of training shapes. In this research a set of 1100 vertebra for both cervical (400 vertebral) and lumbar (710 vertebra) has been used. ii. Aligning trainshapes The model that will be used to describe a shape and its typical appearances is based on the variations of the spatial position of each landmark point within the training set. Each point will thus have a certain distribution in the image space and therefore the shape model is being referred to as a Point Distribution Model (PDM). In order to obtain the PDM, we use the two shape representation, to align the shapes, and finally, to summarize the landmark variations in a compact form. In what follows, these steps are being described in some detail. We achieve the required alignment by scaling, rotating and translating the training shapes so that they correspond as closely as possible. 1.7 Shape boundary Indexing The shape analysis described here is related to the statistical analysis of vertebrae shapes to shape similarity matching and recognition. Three schemes of shape analysis implemented at this stage. First scheme is the shape analysis based feature vectors extraction includes statistical shape feature (SSF) and Gabor wavelets features (GWF). Second scheme is the shape analysis based morphometric measurement based angles measurement index (AMI) and intra-bone ratio measurement (IBRM). Last is the analysis based similarity matching, the index output result from each analysis will be considered as input to the classifier systems those schemes outlined are described below. Feature vector is an n-dimensional vector of numerical features represents object shape. Statistical models captured from active shape model, Gabor wavelets filter bank require a numerical representation of vertebrae shape based on both boundary shape representation (9-anatomical point model ,B-spline curve), since such representations facilitate processing and statistical analysis. Figure below shows schematic pattern recognition system based feature vectors. 1.7.1 Statistical shapefeatures(SSF) Each vertebral in the training set, when aligned can be represented by a single points in 2n dimensional space (eq2).Thus a set of N example shapes gives base on each shape boundary representation cloud of N point in this 2n dimensional space. We assume that these points lie within some region of the space which call the Allowed Shape Domain and that the points give an indication of the shape and size of this region. Every 2n-D point within this domain gives a set of landmarks whose shape is broadly similar to that of those in the original training set. Thus by moving about the Allowable shape domain we can generate new shapes in systematic way .The approach given below attempts to model the shape of this cloud in high dimensional space and hence to capture the relationship between the positions of the individual landmark points. 1.7.2 Gabor wavelets features(GWF) The objectives of this stage is to explore the feasibility of using Gabor wavelet-constructed spatial filters to extract feature-based vector from shape boundary consisting of cervical and lumbar vertebrae, and to use these extracted feature vectors to train and test with different classifier. To evaluate the robustness of the method, so many analysis based filter and mask size was experimented to select the suitable Gabor mask that will be convolute with the two vertebra shape boundary extracted. In order to briefly describe Gabor wavelets and provide a rationale for this stage of work, the Short Time Fourier Transform (STFT) and Gabor Transform need to be explained first. The Fourier transform is a fundamental tool of classical signal analysis. i. Gabor wavelets filter bank The Gabor wavelet function used in this research for AOs feature extraction was same as Naghdy (1996) used and was defined. Where: the different choices of frequency j and orientation constructed a set of filters. ii. Filter frequency and mask size analysis As the frequency of the sinusoid changes, the window size will be changed. (Fig. 3.28, 3.29, 3.30 and 3.32) shows real and imaginary parts of eight two-dimensional wavelets filters. When j is changed from 1 to 4, the sinusoid frequency is reduced whereas the Gaussian window size increases. In comparison, for the Gabor transform, Gaussin window size will remain same. iii. Convolution vertebral region with the filter bank The elementary Gabor wavelet functions were used to construct spatial domain filters, Each filter was made of a pair of filters, which were the real and imaginary part of the complex sinusoid. These pair was convolved with the green channel signal of texture image separately. The reason of choosing the green channel to do convolution was that the green channel was found to have the best texture quality, which means the best contrast level between plants and soil, among red, blue and MExG channels. This scenario is absolutely sensor dependent and may not be the case for other sensors. For one frequency level, the filtering output was the modulation of the average of the convolution output from real and imaginary filter masks on all convolved pixels in the green channel image, which was computed. iv. Gabor wavelets filer bank block diagram 1.8 Shape boundary morphometric measurement 1.8.1 Morphometric measurement-invariant features For efficient image retrieval, it is important that the pathological features of interest be detected with high accuracy. In this stage of Automatic Vertebral Fracture Assessment System techniques, new morphometric measurement-invariant features were investigated for the detection of anterior osteophytes, including lumbar and cervical vertebrae. The goal in this stage of work is to investigate a measurement algorithm for high accuracy and avoid the complex calculation. Two approaches morphometric measurement-invariant features were developed based: 1) Angles invariant features (A-IF) 2) Intra-distance ratio invariant features (ID-IF) The results of this morphometric extraction geometries calculation will produce a signal of two index based on angle and distance measurement that can be used to distinguish between the anterior osteoporosis classes and their severity implemented as input for classifier algorithm. Figure below show the block diagram of the shape analyses based morphometric technique. Stage 1: AOs detection Two classification schemes for anterior osteophytes were established by a medical expert to evaluate the accuracy of the PSM algorithm. The first is Macnabs classification, established by Macnab and his coworkers in 1956 on radiological and pathological bases [6, 7].Two types of osteophytes are adapted from Macnabs classification: claw and traction, as shown in Figure 1. Their visual characteristics are: 1. Claw spur rises from the vertebral rim and curves toward the adjacent disk. It is often triangular in shape and curved at the tips. 2. Traction spur protrudes horizontally, is moderately thick, does not curve at the tips, and never extends across the intervertebral disk space. The second classification is a grading system which was defined by the medical expert consistent with reasonable criteria for assigning severity levels to anterior osteophytes (AO). Three grades of AO are slight, moderate, and severe, also shown in Table 1. Their visual characteristics are: 1. Slight grade includes normal, where the corner angles on the vertebral boundary are approximately right angles. It may have a slight protuberance, where the tip of the osteophyte is round and no narrowing is observed at the base of the protuberance. 2. Moderate grade is characterized by evident protuberance from the ideal horizontal or vertical edge of the vertebra. The bounding edges of the AO form an angle of at least 45 degrees and the osteophyte has a relatively wider base than severe grade. 3. Severe grade is characterized by presence of hook, the angle is less than 45 degrees and has a narrow base, or protrudes far (about 1/3 of the length of the horizontal border) from the normal (ideal 90 degree) vertebral corner. Angles invariant features (A-IF) We explore three main angles for measurement that make sense of difference between the AO classes from the 9-anatomical landmarks model. Shape below show the angle of interest selected that will be used next as input for our classifier system to make decision (a) Turning Angle (b) Intra-Distance Across the Shape Turn Angle (TA) To capture the characteristics of shape in local regions, we use two different features. The first is Turn Angle (TA). Turn Angle is also called Turning Angle or Bent Angle. It is defined as follows [3]: if the points on the polygon are ordered in the counterclockwise direction, and the polygon is traversed in this direction, the Turn Angle is the angle between the direction vector for the current polygon segment and the next one; the sense of the Turn Angle is calculated such that a clockwise turn gives a negative angle whereas a counterclockwise turn gives a positive angle. Figure 3 (a) shows an example. For an arbitrary shape, the Turn Angle feature could be calculated from the approximating polygon for that shape. Turn Angle for a polygon with n vertices is simply a vector in Rn . For example, if the vertebra is represented as a polygon with 72 vertices (our sparse representation), the Turn Angle is a 72-element vector. If the polygon has the concept of an initial vertex, similarity computation is straightforward, e.g., with a Euclidean metric. If there is no initial vertex, similarity between two shapes may be computed by a combinatorial comparison of distances between possibly-matching sets of vertices. This computation may be optimized by dynamic programming. Intra-distance ratio invariant features (ID-IF) Distance across the shape [4] is another local shape feature. DAS is defined, for each vertex P in a polygon, as the length of the angle bisector at P, measured as the line segment from P to the intersecting side of the polygon. For Example, the interior bisector of angle à ¢Ã‹â€ Ã‚  P2P3P4 in the figure 3 (b) intersects the contour at point I3. The length of P3I3 is the DAS at point P3. If the bisector intersects the shape multiple times, the distance to the closest intersection is used. Similarly as for turn angle, if we represent the vertebra shape as a polygon with 72 sample points, the DAS feature may be calculated on those 72 points. Where, V: is called as vertical angle calculated between the points 7-8-9 H: is called as horizontal angle calculated between the points 1-2-3 C: is called as corner angle calculated between the points 8-9-1 Angle formula calculation between these three points coordinates as follow 1.9 Operation Step 1: Calculate the Horizontal angle and this calculation based on the Step 2: Calculate the Horizontal angle and this calculation based on the Step 3: Calculate the Horizontal angle and this calculation based on the Step 4: build the rule base and evaluate the result by visual inspection Intra-Distance ratio Measurement (I-DRM) Inter-bone ration is another morphometric measurement issue, it was explored based on the shape distance here we focused Where, : Represents the distance posterior height calculated between the points 3-4 : Represents the distance medial height calculated between the points 5-2 : Represents the distance interior height calculated between the points 1-6 : Represents the distance calculated between the points 8-mp, where mp Midpoint between the points 3-4, the Midpoint (mp) coordinates calculation formula as the following: With; (, ) is the point 3 coordinate, (,) is the point 4 coordinate Given the two points (, ) and (,), the distance between these points is given by the formula: The normal vertebra was estimated to have the following ratio distance Distance () =Distance () =Distance () Base on this estimation by expert radiologist we develop another rule base decision system that can work properly to and true classify the normal and abnormal and bone The criteria of the X= Stage 2: AOsLocation Detection of the Ao position conduct us to determine the location either upper or lower AO a) b) The position of the AO is determined by sample way calculation based of angles too Stage 3: Disc space narrowing (DSN) Stage 4 Stage 5:Subluxation/Spondylolisthesis Segmentation and Pre-processing The vertebra shapes were segmented using an active contours method modified to constrain evolving contour points to follow orthogonal curves [18], to avoid convergence to a self-intersecting solution contour at vertebra corners [9]. The solution contours have 36 points. Nine of these 36 points were distinguished as geometrical or anatomical reference points, with relative locations that are approximately constant across the veterbra shapes. The nine points, shown in Figure 2 were either manually marked by experts, or extracted automatically or semi-automatically by specialized algorithms [9]. For the current work, we preprocess these segmented shapes by curve smoothing (to reduce noise), fitting (for smoothness), interpolation, and re-sampling (for larger number of evenly distributed points) to obtain the final shape contour description. The curve fitting and interpolation are done with the natural cubic spline algorithm. Then the shape contour is resampled by equal arc length sampling. Finally, the vertebra whole shape is represented by two boundary point sets with different resolutions. The dense sampling set contains 180 points, and the superior and the inferior anterior corners are represented by 60 points, respectively. The sparse sampling set contains 72 points, with the superior and the inferior anterior corners represented by 25 points, respectively.

Compensation and Benefits

Compensation and benefits From Wikipedia, the free encyclopedia (Redirected from Compensation & Benefits) Jump to: navigation, search Compensation and benefits (abbreviated â€Å"C&B†) is a sub-discipline of human resources, focused on employee compensation and benefits policy-making. It is also known in the UK as â€Å"total reward† and as â€Å"remuneration† in Australia and New Zealand.Contents[hide] * 1 The basic components of employee compensation and benefits * 2 Variable pay * 3 Benefits * 4 Equity-based compensation * 5 Organizational place * 6 Main influencers * 7 Bonus plans| [edit] The basic components of employee compensation and benefits Employee compensation and benefits are basically divided into four categories: 1. Guaranteed pay – monetary (cash) reward paid by an employer to an employee based on employee/employer relations. The most common form of guaranteed pay is the basic salary. . Variable pay – monetary (cash) reward paid by a n employer to an employee that is contingent on discretion, performance or results achieved. The most common forms are bonuses and sales incentives. 3. Benefits – programs an employer uses to supplement employees’ compensation, such as paid time-off, medical insurance, company car, and more. 4. Equity-based compensation – a plan using the employer’s share as compensation. The most common examples are stock options. Guaranteed pay Guaranteed pay is a monetary (cash) reward.The basic element of the guaranteed pay is the base salary, paid based on an hourly, daily, weekly, bi-weekly or a monthly rate. The base salary is typically used by employees for ongoing consumption. Many countries dictate the minimum base salary defining a minimum wage. Individual skills and level of experience of employees leave room for differentiation of income-levels within the job-based pay structure. In addition to base salary, there are other pay elements which are paid based so lely on employee/employer relations, such salary and seniority allowance. edit] Variable pay Variable pay is a monetary (cash) reward that is contingent on discretion, performance or results achieved. There are different types of variable pay plans, such as bonus schemes, sales incentives (commission), overtime pay, and more. An example where this type of compensation plan is prevalent is the real estate industry and real estate agents. A common variable pay plan might be the sales person receives 50% of every dollar they bring in up to a level of revenue at which they then bump up to 85% for every dollar they bring in going forward.Typically, this type of plan is based on an annual period of time requiring a â€Å"resetting† each year back to the starting point of 50%. Sometimes this type of plan is administered so that the sales person never resets and never falls down to a lower level. It also includes Performance Linked Incentive whcih is variable and may range from 130% to 0% as per performance of the indiviudal as per his KRA. [edit] Benefits There is a wide variety of employee benefits, such as paid time-off, insurances (life insurance, medical/dental insurance, and work disability insurance), pension plan, company car, and more.A benefit plan is designed to address a specific need and is often provided not in the form of cash. Many countries dictate different minimum benefits, such as minimum paid time-off, employer’s pension contribution, sick pay, and more. [edit] Equity-based compensation Equity based compensation is an employer compensation plan using the employer’s shares as employee compensation. The most common form is stock options, yet employers use additional vehicles such as restricted stock, restricted stock units (RSU), employee stock purchase plan (ESPP), and stock appreciation rights (SAR).The classic objectives of equity based compensation plans are retention, attraction of new hires and aligning employees’ a nd shareholders’ interests. [edit] Organizational place In most companies, compensation & benefits (C&B) is a sub-function of the human-resources function. HR organizations in big companies are typically divided into three: HR business partners (HRBPs), HR centers of excellence, and HR shared services. C&B is an HR center of excellence, like staffing and organizational development (OD). [edit] Main influencersEmployee compensation and benefits main influencers can be divided into two: internal (company) and external influencers. The most important internal influencers are the business objectives, labor unions, internal equity (the idea of compensating employees in similar jobs and similar performance in a similar way), organizational culture and organizational structure. The most important external influencers are the state of the economy, inflation, unemployment rate, the relevant labor market, labor law, tax law, and the relevant industry habits and trends. edit] Bonus plan s Bonus plans are variable pay plans. They have three classic objectives: 1. Adjust labor cost to financial results – the basic idea is to create a bonus plan where the company is paying more bonuses in ‘good times’ and less (or no) bonuses in ‘bad times’. By having bonus plan budget adjusted according to financial results, the company’s labor cost is automatically reduced when the company isn’t doing so well, while good company performance drives higher bonuses to employees. . Drive employee performance – the basic idea is that if an employee knows that his/her bonus depend on the occurrence of a specific event (or paid according to performance, or if a certain goal is achieved), then the employee will do whatever he/she can to secure this event (or improve their performance, or achieve the desired goal). In other words, the bonus is creating an incentive to improve business performance (as defined through the bonus plan). 3.Emp loyee retention – retention is not a primary objective of bonus plans, yet bonuses are thought to bring value with employee retention as well, for three reasons: a) a well designed bonus plan is paying more money to better performers; a competitor offering a competing job-offer to these top performers is likely to face a higher hurdle, given that these employees are already paid higher due to the bonus plan. b) if the bonus is paid annually, employee is less inclined to leave the company before bonus payout; often the reason for leaving (e. g. dispute with the manager, competing job offer) ‘goes away' by the time the bonus is paid. he bonus plan ‘buy' more time for the company to retain the employee. c) employees paid more are more satisfied with their job (all other things being equal) thus less inclined to leave their employer. The concept saying bonus plans can improve employee performance is based on the work of Frederic Skinner, perhaps the most influential p sychologist of the 20th century. Using the concept of Operant Conditioning, Skinner claimed that an organism (animal, human being) is shaping his/her voluntary behavior based on its extrinsic environmental consequences – i. . reinforcement or punishment. This concept captured the heart of many, and indeed most bonus plans nowadays are designed according to it, yet since the late 1940s a growing body of empirical evidence suggested that these if-then rewards do not work in a variety of settings common to the modern workplace. Research even suggested that these type of bonus plans have the potential of damaging employee performance. Retrieved from â€Å"http://en. wikipedia. org/w/index. php? title=Compensation_and_benefits&oldid=478107814† View page ratingsRate this page Rate this page Page ratings What's this? Current average ratings. 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Your ratings have been saved.Did you know that you can edit this page? Edit this pageMaybe later Categories: * Human resource management * Employment compensation Personal tools * Log in / create account Namespaces * Article * Talk Variants Views * Read * Edit * View history Actions Search ————————————————- Top of Form Bottom of Form Navigation * Main page * Contents * Featured content * Current events * Random article * Donate to Wikipedia Interaction * Help * About Wikipedia * Community portal * Recent changes * Contact Wikipedia Toolbox What links here * Related changes * Upload file * Special pages * Permanent link * Cite this page * Rate this page Print/export * Create a book * Download as PDF * Printable version * This page was last modified on 21 February 2012 at 18:25. * Text is available under the Creative Commons Attribution-ShareAlike License; additional terms may apply. See Terms of use for details. 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Gre Analytical Writing Argument Topics Essay Samples Pdf - Is it a Scam?

Gre Analytical Writing Argument Topics Essay Samples Pdf - Is it a Scam? The Truth About Gre Analytical Writing Argument Topics Essay Samples Pdf You might also see concept essay. To help you produce a productive essay outline here are tips that will be able to help you. You could also see travel essay. You might also see student essay. You will need to read several GRE sample essays depending on the Issue task before you find it possible to grasp the way by which your response ought to be framed in order to accomplish a superior score in this test section. The issue essay in GRE needs an adequate amount of prep before the actual test. You will get your essay scores approximately 10-15 days following your test date. The perfect way to find out how to find a high Analytical Writing score is to examine a GRE essay sample, but doing so with no guidance can be overwhelming. If you want to know more regarding the GRE essay length, we've completed a distinct post on that. In several other tests, you will be shown the gre essay topics to write about. Not only do you have to read through GRE sample essays, but you also ought to look for topics on which you are able to write GRE sample essays yourself and have them evaluated. At this time you must un derstand that writing a very good gre essay is dependent on the kind of topic you select, so you need to consider certain things before you select a topic. You could also see scholarship essay. The essay graders know that you simply get 30 minutes to compose each AWA essay and in addition, they know that you won't have the ability to cover every potential argument, reason and rebuttal. Bear in mind that lots of distinct essays can make high scores. Take advantage of these essays to rate your own degree of writing. Where to Find Gre Analytical Writing Argument Topics Essay Samples Pdf Arguments are normally not well-supported or can be readily refuted, therefore, your very first sentence can produce the point that the argument isn't well-reasoned, as it leaves out factors that would want to get considered. Reasoning plays an important role in deciding the general caliber of your essay. So, it's safe to say that in case you write no less than a few sentences in English, you will receive a score of 1.0. Now, you've got to be in a position to understand the differences between both topics you'll be presented with. It is possible to then practice replicating successful connections between ideas in your practice essays. In essence you're interpreting the info. Well thankfully, there are a number of options that you are able to consider. Lies You've Been Told About Gre Analytical Writing Argument Topics Essay Samples Pdf While reading, it's also wise to make note of all of the unfamiliar words and later learn them. Just take a couple of minutes to plan your response and compose an outline before starting your essay. Also a reminder that you could work with me if you're searching for issue essay feedback. The action of writing down the definition can help you remember this, and you may incorporate an illustration of the way the word is utilized to boost your odds of memorising it for use in essays. Whispered Gre Analytical Writing Argument Topics Essay Samples Pdf Secrets So long as you use sensible reasoning, good grammar and provided that you are able to defend your point intelligently and utilize pre cise vocabulary to convey meaning effectively, you ought to be alright. You will be supplied an issue statement that produces a claim that can be seen from a number of different angles. There is, in addition, the dilemma of grammar. Between grammar and style, it is much easier to improve. New Questions About Gre Analytical Writing Argument Topics Essay Samples Pdf The argument is weakened by the presence of several facets which may have directly or indirectly affected the normal property values of the Brookville community in the past seven decades. Be aware that you're NOT being requested to present your own views about the topic. Try to remember that there's no correct or wrong reaction. Obviously, it's one of the most essential facets, but it isn't the only aspect.

Life in a Metro - 2100 Words

LIFE IN A METRO Life in a metro is a term used for life of people in a metropolitan city. Metropolitan cities are those big cities which have all the modern amenities, good infrastructure and a modern outlook. They are the cities which don’t portray any specific religion or caste; people from all parts of country come to these cities to have a nice rich life-style. Metropolitan cities are the cities which help the country with lot of financial economy. These cities portray the spirit of young, educated and rich country. They have a lot of companies and software parks which earns a lot of money for the country and generate lots and lots of job opportunities for people. Talent is cherished in right spirit in these cities. Metropolitan†¦show more content†¦Your children will attend schools in downtown and will have to use public transportation. In the suburbs there are certain transportation methods available like buses and trains, while in the inner city you have one extra which is the metro. At the privacy of your own apartment in the inner city you can stay home on the computer or watch movies in your living room. In the inner city you will also not feel safe, as it will be full of different problems downtown every day. At the privacy of your house in the suburb you can enjoy washing your car in your drive way, you can spend the afternoon planting in your front and backyard, you can enjoy a sunny day swimming in your pool and tanning, you can enjoy an afternoon outside doing your barbecue, or doing certain activities like walking your dog, or going biking to one of the parks near you. Most people in the inner city use public transportation, as it is faster then driving a car. Karachi is the biggest city in Pakistan and also one of the most thickly populated cities in the world. Its population has increased rapidly and accordingly has given rise to many social problems. People of this metropolis are becoming more and more concerned about solving these serious problems, some of which are discussed below. The ever-increasing rush of heavy traffic on the roads is resulting in heavy loss of human life. One day or the other, people suffer form accidents due to reckless driving. Some lose their vehicles and some go to theShow MoreRelatedMetro 2033, by Dmitry Glukhovsky1455 Words   |  6 Pages250 warheads can level cities with a single, grand explosion, and one warhead can contaminate 250 miles of air and land, making it inhospitable for thousands of years. In Metro: 2033, the worst scenario has been realized: the 2013 nuclear war has annihilated most of humanity, and the few thousand people living in the Moscow Metro (ÐÅ"Ð ¾Ã' Ã ºÃ ¾Ã ²Ã' Ã ºÃ ¾Ã µ Ð ¼Ã µÃ'‚Ã'€Ð ¾) are struggling to survive mutant attacks, believing again in ancient superstitions and fears, warring over such things as religion, ideology, and raceRead MoreThe World s Urban Population1581 Words   |  7 Pages(Agarwal, 2013). â€Æ' 1.1 Research Question †¢ Is optimum land utilization is done along the metro corridor? †¢ Is there proper parking facility along the metro corridor? †¢ Is elevation pattern creating the theme of overall stretch? †¢ Is environment appealing along the metro corridor? †¢ Is the importance of Public spaces is taken into concern while designing metro corridor? †¢ Is there safe environment along metro corridors? 1.2 Aim Find out the factor of TOD (Transit oriented development) which affectingRead MoreA Brief Note On The Population Of Noida1413 Words   |  6 Pages POPULATION OF NOIDA: RIDERSHIP AT VARIOUS METRO STATIONS THE PIE CHART IS REPRESENTING THE NUMBER OF PASSENGERS USING THE PARTICULAR METRO STATION PER DAY Ridership of different metro Stations per month SECTOR 18 – 22974 BOTANICAL GARDEN - 22000-25000 (Approx.) NOIDA CITY CENTER - 25000 (Approx.) FUTURE PROJECTIONS According to UN Asia Pacific Human Development New Delhi is going to be largest city in terms of population with 26 million by the year 2020 followed by TOKYO atRead MoreThe Delhi Metro Project Management1238 Words   |  5 Pages. The Delhi metro project is an exemplary tale of the way a project of that magnitude was handled. It’s the best project management carried out for a Govt. sector project, in India, which was completed in time and within the budget. The first step in the project management of any project is to constitute a project team. And DMRC did it exactly the way it was required. THE TEAM (During phase 1and Phase2) Chairman- Ramachandran 1. Managing Director – Dr. E. Sreedharan 2. Total No. of Directors -Read MoreThe Construction Of Quito Metro Railway System1566 Words   |  7 Pages26, 2015, Mauricio Rodas the mayor of Quito signed the contract that will change the city of Quito for the better. The contract permitted the construction for the second phase of the Quito Metro line. In 2013 they had started the construction of the two main stations in the north and south of the city. Quito Metro is an underground railroad system that will provide faster transportation to travel around the city of Quito. Quito is the capital of Ecuador and it situated on the northwest of the continentRead MoreProtecting Floodplains by Aaron Dante Mamiit668 Words   |  3 PagesProtecting Floodplains by Aaron Dante Mamiit Flooding is a constant issue faced by Metro Manila. Although there are times when flooding is merely an inconvenient and annoying event, there are also times when it develops into something much more frightening and dangerous. But why is Metro Manila so badly plagued by floods anyway? One of the reasons why Metro Manila constantly battles with the flood problem is because a large part of it is situated on a floodplain. What are floodplains? FloodplainsRead MoreSolid Waste Management1455 Words   |  6 PagesMinistry of Environment (Ministry of Environment). The Integrated Solid Waste and Resource Management Plan aims to avoid â€Å"waste through an aggressive waste reduction campaign and through the recovery of materials from the waste that remains† (ISWRMP Metro Vancouver 2010). Reaching the goal of avoiding waste requires reduction in the generation of waste from the source. Hence, the Zero Waste Vancouver evolved as an update to the Solid Waste Management Plan. More accurately, it evolved as a notion followingRead MoreBuilding A Large Network Of Streets Between The Main And Local Streets1688 Words   |  7 Pagesemergency personal and vehicles (Metro.17) Drawbacks include the fact that this strategy may in fact create more congestion than relieve it, thus continue to concentrate air toxins in major travel corridors.(Metro.17). There are also community impacts such as home or store displacement, noise, litter and waste. This strategy rates 1 start on the climate benefit scale, would cost 12 billion in operations, maintenance, etc., and would produce 8.8 billion in capital (Metro.17). There is also backlash fromRead MorePersuasive Essay On Food Deserts774 Words   |  4 Pagesnot resources but resourcefulness that ultimately makes the difference.† That one quote summarizes the difference between wanting a change and actually working for a change. You simply have to use the resources around you to make an effort in your life and make things work. Someone in Roswell and someone in Atlanta does not eat the same thing for their meals. As a matter of fact, here, candy, chips, chocolate, and cookies are just a few of the things that our generation calls â€Å"breakfast† insteadRead MoreFicial Metro : Last Light Soundtrack1493 Words   |  6 Pagesofficial Metro: Last Light soundtrack was composed by Ukraine composer Alexey Omelchuk. Omelchuk is famous for composing music for video games such as Alexander, Cossacks II: Napoleonic Wars, Heroes of Annihilated Empires, S.T.A.L.K.E.R.: Clear Sky, S.T.A.L.K.E.R.: Call of Pripyat, Metro 2033 and most recently Metro: Last Light. He was working with GSC Game World, and after the company was dissolved in 2011, he went to worked one of its successor 4A Games. The original soundtrack for Metro: Last Light