How to Write a Narrative Easy Guide and Useful Tips

Narrative essays are on the list of basic essays that students have to be familiar with. For some, these are the hardest to write, for they require fantasy and writing style. We examined the tips available online and now offer you the basic rules that professionals at our†¯custom writing service†¯use for writing a narrative essay. To make these guidelines even more valuable, we also share some of our professional†¯essay writing tips†¯that come directly from our experience. Writing a Narrative Essay: Getting Started First of all, let’s take a closer look at narrative essay definition. A narrative essay is a story about your experience, either imaginary, or real. It can also tell a story of somebody’s life. We tell stories every day. So, when you ask â€Å"How to write a narrative essay,† you should think of a story you want to write about and choose the most exciting concept for the thesis. It is a great idea to talk to somebody about the story you are to describe. Your interlocutor can have an absolutely different point of view or memories about the fact. Their perspective can add some interesting details to your essay. Don’t forget to make some notes of the parts that are to be the highlight of the essay and create an outline. Before you start, here a simple steps to writing a narrative story: The planning phase: think about the essay topic and how your life experience correlates with it. Even a small fact, idea, or goal can become good narrative story ideas. Think about your emotions. The more passionate you will be – the more effective your assignment. Another good idea when you are wondering how to start writing a narrative essay is to recall details of your story: people and objects, setting and season, events sequence. Think about the sequence of events and remember; no detail is too small. Remember: the small details reveal big ideas!

The Origin of Eukaryotic Cells essays

The Origin of Eukaryotic Cells essays In the beginning of the creation of Earth volcanoes erupted all over the planet. During this period there was a time where a brief cooling period was allowed to take place. When this period took place evaporation caused a downpour of rain which flooded the ocean creating the ocean. At the time that ocean was averaged at 3,000 degrees Fahrenheit. Around this same time an asteroid so powerful hit the Earth knocking off a large chunk of it. This chunk became the moon which at the time was twice as close as it is today. The hitting of the planet Earth cause such a shake that many new undersea volcanoes began spewing forth molten rock and gasses. These gasses and other particles formed on the oceans surface and with the moon being so close were smashed together by strong and violent waves. Molecules were then washed ashore and exposed to heat and sunlight. Through a series of trial and error bases chemical reactions formed cells. The first ones were simple only with the new permeable membrane so it could absorb nutrients. After absorbing so many amino acids it was able to replicate itself. Bacteria now was growing off the undersea volcanoes vents living off of hydrogen sulfide. Some of these developed hard shells and others with soft membranes. Meanwhile tectonic plates during this time were shifting drastically and created mountain ranges which altered rain patterns and led to the falling of even more rain which created rivers. These rivers washed out new nutrients found in land out to the oceans. Minerals from land reacted with carbon dioxide which resulted in the production of oxygen. As temperatures cooled algae created glucose through photosynthesis and released gross amounts of oxygen into the ocean. The oxygen reacted with the metallic ions found i n the ocean and cause oxidation which caused the sea to turn a rusty red. The sea then turned back to a royal blue now rich w ...

Emerson's Experience Essay Example | Topics and Well Written Essays - 1000 words

Emerson's Experience - Essay Example This is the confusion that confronts human beings and it impacts a perception of the human beings role with respect to nature and the powers that human beings wield in that respect. Human beings are blurred by the present material existence, and therefore, unable to clearly place a difference between productive and unproductive commitments. In fact, human beings are unique and it is expected to use creative energy. However, in the long run a sufficient understanding of daily occupations and activities can provide an effective way of valuing such time distance. Human beings can be blurred by the value and importance of their current lives. Daily preoccupations fill human beings to the extent that very little time is left for reflections. People allocate a lot of significance to the misfortunes of life; on the other hand, these have no eternal meaning. Grief neither brings people close to one that have been lost, nor does it change who they are. In a reflection, the writer refers to his own particular case, his grief at the death of his own son in 1842. In fact, grief does not provide learning lessons to people and even pull human beings closer to a deeper knowledge of the world in the material forms. According to Emerson, temperament and mood are the wholesale component of perspective. Further, dreams and illusion makeup part of human beings that aid in seeing. A highly intelligent person is hopeless if the perception is incomplete by certain temperamental trait that blocks a central distance inside the real horizon of life. A person’ creativity cannot be efficiently utilized if he does not care adequately for the search for truths, even if he is overly sensitive, and unable to reform. Religious sentiment flow can be influenced by mood and temperament cannot be completely separated from moral sentiment. Scientific study of the size and

Violence in the Workplace Essay Example | Topics and Well Written Essays - 750 words

Violence in the Workplace - Essay Example In 2008, Roy observed that workplace violence was assuming great importance for modern businesses. Quoting the U.S. National Institute for Occupational Safety and Health, he observes that on an average working day, 3 people are murdered on the job, 1000000 workers are assaulted and more than 1,000 are murdered every year in the U.S. According to the Labor Department, killing at the work place is the second major contributor to death on the job after road accidents. Statistics show that 111,000 incidents of work-place violence cost employers and others an estimated 6.2 million in 1992. With the issue of violence at the workplace gaining higher attention, many state bodies are coming together to combat this social threat. The 9/11 attacks gave a completely new perspective to violence at the workplace. The incident made the world wake up to the fact that a threat need not be limited to workers only, but could also be in the form of terrorists attacks from outside the workplace. The FBI's National Center for the Analysis of Violence Crime (NCAVC), Critical Incident Response Group (CIRG), coordinated with a select group of experts from law enforcement, private industry, government, law, labor, professional organizations, victim services, the military, academia, mental health, and CIRG's Crisis Negotiations Unit in 2004 and discussed the problem at length. "Workplace Violence: Issues in Response," a document detailing the duties of an employer, employee, the role of the state has been the written outcome of this effort. While there are no written rules about hiring or verifying the credentials of a prospective employee, the agencies have advised employers to exert utmost care in recruiting new people. Also, while businesses are bound by law to safeguard the employees' welfare and security under the Occupational Safety and Health Act, they can in no way guarantee complete safety for the employees from external threats. They can at most ensure that the workplace is "free from recognized hazards " in accordance with the "General Duty Clause." . To properly implement the civil rights requiring employers to protect employees from various forms of violence, it becomes essential fro the employers to pay extra attention to each employee's activities within and outside of the workplace. However, keeping a tab on such activities might lead to issues of privacy, defamation and discrimination against some employees. Not only while hiring, but also while firing employees, organizations have to be very careful th at the disgruntled employee doesn't become a threat to the company. As discussed in the paper, sometimes laws meant to protect an employee's rights become an obstacle in ensuring the employer's rights. The American Disabilities Act might prove a hurdle for an employer if the concerned person shows signs of being a threat to the company, but is not ready for counseling. Thus, while we can safely conclude that instances of violence at the workplace are increasing at a rapid rate, organizations have to be prepared for any kind of emergency. While hiring new people, they should also keep in mind the past records of the employee and take hints

Mystery religions of the Hellenistic era Essay Example | Topics and Well Written Essays - 3500 words

Mystery religions of the Hellenistic era - Essay Example Although the religions were present several years before the Hellenistic era, their popularity increased significantly during this period and even spread through the entire Mediterranean region (Ferguson, 1980, p. 157). The mystery religions were created in several diverse geographical areas including India, Iran, Egypt and Greece, yet all of the mystery religions were based on myths that were very similar to each other. Although they were diverse in geographical origin, heterogeneous in historical development, and theological orientation, during the Hellenistic period the various mysteries shared a similar response to the religious needs of the day, and they resembled each other sufficiently to warrant being classified and discussed together† (Meyer, 1987, p. 4). This paper will mainly focus on the Greek mystery religions in the Hellenistic period. The mystery religions, which were often considered cults, promised their followers good things although most of these promises wer e never fulfilled. Examples of the mystery religions were the worship of single deities like Demeter, Kore, Orpheus, Isis and Cybele (Grant, 1962, p. 98). These figures were taken from ancient myths and legends, telling stories of Demeter, the goddess of grain, and her daughter Kore, also known by the name Persephone, Orpheus and his lute and other major figures. (Tripolitis, 2002, p. 17) They mingle stories about the world of men and the home of the gods on Mount Olympus, relating natural events like the passing of the seasons to myths about the underworld. By attaching stories to these things, people gave meaning to their lives, and through rituals and gifts, felt that they could have some influence on how their crops would turn out, or how they would get through the darkness of winter. Although literature and history do not always recognize the importance of the mystery religions in the Hellenistic era, they were a significant part of the Greek culture and without a doubt influen ced many aspects of life. As a result of this they also affected history and there is plenty of evidence in the form of statues, ritual objects, paintings and other relics which show how these divine figures were part of daily life. Of further importance is the legacy the mystery religions left, and how they affected subsequent religions. It appears that the mystery religions had great similarities with early Christianity. This paper will therefore discuss what the mystery religions were during the Hellenistic era, how much we can find out about them and what they had in common with early Christianity. The background of the mystery religions In comparison to the previous Hellenic culture the Hellenistic society was multicultural, open, and tolerant (Mathews and Platt, 2008, p.87). Before, and during the Hellenistic period the Greek citizens worshiped the Olympian gods and goddesses. Greek religion was an indispensable part of private and public life and the polis and religion could not be separated (Mathews and Platt, p.43). The Hellenistic period, from the time of Alexander the Great through the Ptolemaic, Seleucid, and Antigonid Kingdoms established by his successors, witnessed the transformation of the polis (city-state). It can be argued that Alexander the Great’s conquest of 336-323 B.C.E. was a main factor that initiated the profound changes to the values of the old Greek polis and the Olympian gods and goddesses linked to the polis (Meyer, 1987, p.2). These changes most likely began because of the growing contact with other civilizations, including Egypt and the New East. During this time Macedonia overtook and philosophy, religion and every other aspect of life began to change. Although heirs of the

Fish Recognition and Classification System Architecture

Fish Recognition and Classification System Architecture 1.1 Introduction In the previous chapter, the architecture and the approaches of object recognition and classification system were shown in details. Moreover, the features of shape characters of fish that will be used for classification stage are provided. Therefore, this chapter focuses on some background of literature approaches on related work and concepts in the field of object recognition and classification. In particular, a main component to design fish recognition and classification system architecture is used; it will show these experiments history of development in several cases. The following literature review is divided into four main sections. The fish recognition and classification, first aspect is covered. The second aspect relates with image segmentation techniques to segment underwater images are presented. Investigates most of the feature extraction and selection by shape representation and description, the third aspect is applied. Finally, the classifiers technique for object recognition and classification in aspect of support vector machine is reported. 1.2 Fish Recognition and Classification Recently, there were many researchers who attempted to design and apply the interaction between an underwater environment and learning techniques to develop the recognition and classification system in order to classify the fish. Therefore, Castignolles et al., (1994) used off-line method detection with static thresholds to segment the images that recorded by S-video tapes and enhance image contrast by using background lighting. Furthermore, to recognize the species a Bayes classifier was tested after extract twelve geometrical features from fish images. However, this method needs control on the light of background, determine the value of threshold and multiple imaging. Moreover, where fish are lined up close to each other, the applications tend to be impractical for the real-time. The moment-invariant for features extraction is fast and very easy to implement. Therefore, Zion et al. (1999) stated the features extraction from dead fish tails by using moment-invariants in order to identify of species. Moreover, the image area is used to estimate fish mass. Furthermore, the accuracy of 99%, 93% and 93%, respectively, for grey mullet, St. Peters fish and carp is got for identification of fish species. Therefore, later Zion et al., (2000) tested this method with live fish swimming in clean water. The accuracies were 100%, 91% and 91%, respectively for fish species identification. However, the features of the tail in the image which were extracted by the moment-invariant are strongly affects by the water opaqueness and fish motion. This method needs clear environments and all features appear clearly. An automatic system to select the desirable features for recognition and classification object is needed. Therefore, Chan et al., (1999) developed a 3D point distribution model (PDM) in order to extract the lateral length measurement automatically from the images without an extensive user interaction to locate individual landmark points on the fish by using an n-tuple classifier as a tool to initiate the model. Moreover, the WISARD architecture is used as a Look-Up Table (LUT) which holds information about the pattern that the classifier tries to recognize, in order to assess the performance and usefulness of the n-tuple classifier in the application of fish recognition. However, this method needs to fix the pre-defined threshold value, amount of prior knowledge for the fish and the bigger training set. Determine the landmarks as tips of snout or fins for fish are very important to recognize the fish. Therefore, Cardin Friedland (1999) stated the morphometric analysis by biometric interpretation of fish homologous landmarks as tips of snout or fins for fish stock discrimination. However, they did not refer to algorithms for determining landmarks and the external points are not satisfactory because their locations are subjective. From other aspect, Cardin (2000) reviewed the landmarks of shape by using morph metric methods for stock identification of fish. Moreover, Winans (1987) used the fins points, extremities point and arbitrarily landmarks in order to identify the fish from those points. Therefore, the attachment of fin membranes were found to be more effective for finfish group discrimination than landmarks located on extremities. Furthermore, Bookstein, (1990) stated the homologous landmarks were found to be more effective in describing shape than other arbitrarily located landmarks. However, these methods should be considered fish sample size, life history, stage of development and the features discriminating power. Fourier descriptor for geometric features description is very famous algorithm. Therefore, Cadieux et al., (2000) stated the Fourier descriptors of silhouette contours, the geometric features described by seven of moment-invariants stated by Hu (1962) are developed in order to count fish by species from fish ways mounted next to river. Therefore, the 78% of accuracy is achieved by using a majority vote of three classification methods. However, this method needs sensors that generate silhouette contours as the fish swim between them and the hardware based on a commercial biomass counter. The manual measurement for the landmarks points is more accurate to identify the object. Therefore, Tillett et al., (2000) proposed the modification of point distribution model (PDM) in order to segmented fish images by means is proposed. Moreover, the edge and its proximity in order to attract landmarks are considered. Furthermore, the average accuracy of 95% by estimating fish length to manual measurement is compared. However, this method required manual placement of the PDM in an initial position close to the centre of the fish, thereby affecting the accuracy of the final fitting. Also, neighboring fish images forced the PDM away from the correct edges and fish whose orientation was very different from the initial PDM or were smaller than the initial values could not be correctly fitted. The combining of more than one classifier is important to get more accuracy to classify the objects. Therefore, Cedieux et al., (2000) proposed intelligent system by combining the result of three classifiers in order to recognize the fish. Therefore, Byes maximum quantification classifier, a learning vector classifier and One-class-One-Network of neural network classifier are used by analysis algorithm of an infrared silhouette sensor to acquire the fish and the majority vote. Moreover, the results depended on at least two from three classifiers should be show the same result. However, this method needs other approach for feature selection in order to improve the recognition performance and to optimize the selection of relevant characteristics for fish classification. Moreover, it needs more computational to identify and classify the object. Detection, representation the features of object and then the classification are the main steps for any recognition and classification system. Therefore, Tidd Wilder (2001) stated a machine vision system to detect and classify fish in an estuary by using a video sync signal to drive and direct the strobe lighting through a fiber bundle into a 30 cmÃÆ'-30 cmÃÆ'-30 cm field of view in a water tank. Moreover, to segment fish images and eliminate partial fish segments, the window-based segmentation algorithm and an aspect ratio are used by means of the segment aspect ratio and a length test. Furthermore, Bayes classifier is used to classify three fish species from extracted fish image area and aspect ratio. However, this method is tested on only 10 images of each of the species, and needs more computation. Moreover, they concluded that the system and method have the potential to operate in situ. The monitoring objects in underwater is difficult problem. Therefore, Rife Rock (2001) proposed Remotely Operated Vehicles (ROV) in order to follow the marine animal in underwater. However, this method needs continuous hours of the pieces movements. Locating the critical points of object is very important to determine the length, weight and the area of the objects. Therefore, Martinez et al., (2003) stated an underwater stereo vision system is used to calculate the weight of fish from their length by using a prior knowledge of the species in order to find points of the fish image and linking them with real-world coordinates. Moreover, in order to find caudal fin points and the tip of the head, the template matching with several templates is used. Furthermore, accuracy of 95% and 96% for estimated fish weight is reported. However, this method needs a prior knowledge of the species, critical points to calculate the length and only used to find the weight. The shape of object is very important feature to recognize and identify the objects. Therefore, Lee et al., (2003) developed automated Fish Recognition and Monitoring (FIRM) system, as shape analysis algorithm in order to locate critical landmark points by using a curvature function analysis. Moreover, the contour is extracted based on these landmark points. Furthermore, from this information species classification, species composition, densities, fish condition, size, and timing of migrations can be estimated. However, this method utilizes high-resolution images and determines the location for the critical points of fish shape. In a conventional n-tuple classifier, the n-tuple is formed by selecting multiple sets of n distinct locations from the pattern space. Therefore, Tillett Lines (2004) proposed an n-tuple binary pattern classifier with the difference between two successive frames in order to locate the initial fish image for detecting the fish head. Moreover, the dead fish hanging in a tank are used to estimate the mean mass. However, the estimation accuracy was low for live fish images due to poorer imaging conditions and larger fish population density. The different features can used together to classify the object. Therefore, Chambah et al., (2004) proposed Automatic Color Equalization (ACE) in order to recognize the fish spaces. Furthermore, the segmentation by using background subtraction was presented. The geometric features, color features, texture features and motion features are used. Then, Bayes classifier is used to classify the selected fishes to one of the learned species. However, this method depends on the color features that need lightness constancy and color constancy to extract visual information from the environment efficaciously. The semi-local invariants recognition is based on the idea that a direct search for visual correspondence is the key to successful recognition. Therefore, Lin et al., (2005) proposed neighbor pattern classifier by semi-local invariants recognition to recognize the fish. Moreover, when they compare it with integral invariants, they found it less mismatching. Furthermore, they compare wavelet-based invariants with summation invariants and found it has more strong immunity to noise. However, this method needs some critical point of the fish shape. The Bayesian filter was originally intended for statistical recognition techniques, and is known to be a very effective approach. Therefore, Erikson et al. (2005) proposed fish tracking by using Bayesian filtering technique. Moreover, this method models fish as an ellipse having eight parameters. However, this method considers only counting the fish without looking into its type. Furthermore, the fish may be having varying in number of the parameters. From other aspect, Lee et al., (2008) stated several shape descriptors, such as Fourier descriptors, polygon approximation and line segments in order to categorize the fish by using contour representation that extracted from their critical landmark points. However, the main difficulty of this method is that landmark points sometimes cannot be located very accurately. Moreover, it needs a high quality image for analysis. Table 1.1: Critical Analysis of Relevant Approaches Author Algorithm Remarks Castignolles et al. 1994 Off-line method This method needs control on the light of background, determine the value of threshold. Moreover, where fish are lined up close to each other, the applications tend to be impractical for the real-time. Zion et al., 1999 Moment-invariants The features of the tail in the image which were extracted by the moment-invariant are strongly affects by the water opaqueness and fish motion. Therefore, this method needs clear environments and all features appear clearly. Chan et al. 1999 PDM this method needs to fix the pre-defined threshold value, amount of prior knowledge for the fish and the bigger training set. Cardin and Friedland 1999 Morphometric analysis They did not refer to algorithms for determining landmarks and the external points are not satisfactory because their locations are subjective. Cardin 2000 Develop Morphometric analysis These methods should be considered fish sample size, life history, stage of development and the features discriminating power. Cadieux et al. 2000 Fourier descriptor This method needs sensors that generate silhouette contours as the fish swim between them and the hardware based on a commercial biomass counter. Tillett et al. 2000 Modify PDM This method required manual placement of the PDM in an initial position close to the centre of the fish, thereby affecting the accuracy of the final fitting. Also, neighboring fish images forced the PDM away from the correct edges and fish whose orientation was very different from the initial PDM or were smaller than the initial values could not be correctly fitted. Cedieux et al. 2000 Intelligent System This method needs other approach for feature selection in order to improve the recognition performance and to optimize the selection of relevant characteristics for fish classification. Moreover, it needs more computational to identify and classify the object. Tidd and Wilder 2001 Machine Vision System This method is tested on only 10 images of each of the species, and needs more computation. Moreover, they concluded that the system and method have the potential to operate in situ. Rife and Rock 2001 ROV This method needs continuous hours of the pieces movements. Martinez et al., 2003 Template Matching This method needs a prior knowledge of the species, critical points to calculate the length and only used to find the weight. Lee et al. 2003 FIRM This method utilizes high-resolution images and determines the location for the critical points of fish shape. Tillett and Lines 2004 n-tuple The estimation accuracy was low for live fish images due to poorer imaging conditions and larger fish population density. Chambah et. al. 2004 ACE This method depends on the color features that need lightness constancy and color constancy to extract visual information from the environment efficaciously. Lin et al., 2005 Neighbor Pattern Classifier This method needs some critical point of the fish shape. Erikson et al. 2005 Bayesian Filtering Technique This method considers only counting the fish without looking into its type. Furthermore, the fish may be having varying in number of the parameters. Lee et al. 2008 Several Shape Descriptors The main difficulty of this method is that landmark points sometimes cannot be located very accurately. Moreover, it needs a high quality image for analysis. 1.3 Image Segmentation Techniques Basically, there are different techniques that would help to solve the image segmentation problems. Therefore, Jeon et al., (2006) categorized these techniques into, thresholding approaches, contour approaches, region approaches, clustering approaches and other optimization approaches using a Bayesian framework, neural networks. Moreover, the clustering techniques can be categorized into two general groups: partitional and hierarchical clustering algorithms. Furthermore, partitional clustering algorithms such as K-means and EM clustering are widely used in many applications such as data mining, compression, image segmentation and machine learning (Coleman Andrews 1979; Carpineto Romano 1996; Jain et al., 1999; Zhang 2002a; Omran et al., 2006). Therefore, this research will focus on the literature review relates with image segmentation techniques to segment fish of underwater images by using k-means algorithm and background subtraction approaches. 1.3.1 K-Means Algorithm for Image Segmentation In general, the standard K-means clustering algorithm is employed in order to cluster a given dataset into k groups. Therefore, the standard K-means algorithm consists of four steps: Initialization, Classification, Centroid computation and Convergence condition. Moreover, several methods attempt to improve the standard K-means algorithm related to several aspects associated to each of the algorithm steps. Furthermore, regarding the computational of the algorithm the steps that need more improvements are initialization and convergence condition (Amir 2007 Joaquà ­n et al., 2007). Therefore, the following sections will be focused on this step in order to represent and address the review for this step. 1.3.1.1 The Initialization Step of K-Means Algorithm Basically, the earliest reference to initialize the K-means algorithm was by Forgy in 1965 that choose points randomly and used as the seeds. Therefore, MacQueen, introduced to determine a set of cluster seeds by using an online learning strategy (MacQueen 1967 Stephen 2007). However, this method can be choosing the point near a cluster centre or outlying point. Moreover, repeating the runs is the increased time taken to obtain a solution. The approach in order to divide the dataset to classes without prior knowledge of classes is required. Therefore, Tou Gonzales (1974) suggested the Simple Cluster Seeking (SCS) method by Calculating the distance between the first instance in the database and the next point in the database, if it is greater than some threshold then select it as the second seed, otherwise move to the next instance in the database and repeat until K seeds are chosen. However, this method depends on the value of threshold, the order of pattern vectors to be processed and repeating the runs is the increased time taken to reach the seeds chosen. For optimal partition of dataset which can achieve better variation equalization than standard. Therefore, Linde et al., (1980) proposed a Binary Splitting (BS) method, based on the first run for K = 1, Then split into two clusters until convergence is reached and the cycle of split and converge is repeated until a fixed number of clusters is reached, or until each cluster contains only one point. However, this method increased the computational complexity by split and the algorithm must be run again. Good initial seeds for clustering algorithm are significant in order to rapidly converge to the global optimal structure. Therefore, Kaufman Rousseeuw (1990) suggested selecting the first seed as the most centrally located instance, then the next seed selected based on the greatest reduction in the distortion and continue until K seeds are chosen. However, this method needs more computation in choosing each seed. In order to select the optimal seed artificial intelligence (AI) is used. Therefore, Babu Murty (1993) and Jain et al., (1996) proposed a method by using genetic algorithms based on the various seed selections as population, and then the fitness of each seed selection is assessed by running the K-means algorithm until convergence and then calculating the Distortion value, in order to select of near optimal seed. However, this method should be run K-means for each solution of each generation. Moreover, a genetic algorithms result depends on the choice of population size, and crossover and mutation probabilities. Enhancement approach in order to improve the clustering quality and overcome computational complexity is required. Therefore, Huang Harris (1993) stated the Direct Search Binary Splitting (DSBS) method, based on Principle Component Analysis (PCA), in order to enhance splitting step in Binary Splitting algorithm. However, this method also required more computational to reach k seeds chosen. Calculating the distance between all points of dataset in order to select the seed is used. Therefore, Katsavounidis et al. (1994) proposed the algorithm as the KKZ algorithm based on preferably one on the edge of the data as the first seed. Then, chosen the second seed based on the point which is furthest from the first seed. Moreover, choosing the furthest point from its nearest seed is repeated until K seeds are chosen. However, this method obvious pitfall from any noise in the data as preferably seed. In order to increase the speed of the algorithm based on divide the whole input domain into subspaces is required. Therefore, Daoud Roberts (1996) proposed approach to divide the whole input domain into two disjoint volumes, and then this subspace is assumed that the points are randomly distributed and that the seeds will be placed on a regular grid. However, this methods refers at the end into randomly choose. The mean of the any dataset is important value in order to estimate the seed depends on it. Therefore, Thiesson et al., (1997) suggested approach to calculate the mean of the entire dataset based on randomly running time of the algorithm to produce the K seeds. However, this method uses the random way to repeat the steps until reach the desirable clusters. In order to find better clustering initialization of k-means algorithm, Forgys method is used. Therefore, Bradley Fayyad (1998) presented a technique that begins by randomly breaking the data into 10, or so, subsets. Then it performs a K-means clustering on each of the ten subsets, all starting at the same set of initial seeds, which are chosen using Forgys method. However, this method needs to determine the size of the subset and used the same initial seed for each subset. A way of reducing the time complexity of initialization for k-means algorithm calculation is to use structures like k-d trees. Therefore, Likas et al., (2003) stated a global K-means algorithm which aims to gradually increase the number of seeds until K is found, by using the kd-tree to create K buckets and use the centroids of each bucket as seeds. However, this method needs to test the results to reach the best number of clusters. The performance of iterative clustering algorithms depends highly on initial cluster centers. Therefore, Mitra et al., (2002) and Khan Ahmad (2004) proposed a Cluster Centre Initialization Method (CCIA) based on the Density-based Multi Scale Data Condensation (DBMSDC) by estimating the density of the dataset at a point, and then sorting the points according to their density and examining each of the attributes individually to extract a list of possible seed locations. The process is repeated until a desired number of points remain. However, this method depends on other approach to reach the desired seeds, which lead to more computation complexity. On the other read, in order to reduce the time complexity of initialization for k-means algorithm calculation is to use structures like k-d trees. Therefore, Stephen Conor (2007) presented a technique for initializing the K-means algorithm based on incorporate kd-trees in order to obtain density estimates of the dataset. And then by using the distance and the density information sequentially to select K seeds. However, this method occasionally failed to provide the lowest value of distortion. Table 1.2: Critical Analysis of Relevant Approaches Author Algorithm Remarks Forgy 1965 and MacQueen 1967 Random initial K-means This method can be choosing the point near a cluster centre or outlying point. Moreover, repeating the runs is the increased time taken to obtain a solution. Tou and Gonzales 1974 SCS This method depends on the value of threshold, the order of pattern vectors to be processed and repeating the runs is the increased time taken to reach the seeds chosen. Linde et al., 1980 BS This method increased the computational complexity by split and the algorithm must be run again. Kaufman and Rousseeuw 1990 Selecting the first seed. This method needs more computation in choosing each seed. Babu and Murty 1993 GA This method should be run K-means for each solution of each generation. Moreover, a genetic algorithms result depends on the choice of population size, and crossover and mutation probabilities. Huang and Harris 1993 DSBS This method also required more computational to reach k seeds chosen. Katsavounidis et al. 1994 KKZ This method obvious pitfall from any noise in the data as preferably seed. Daoud and Roberts 1996 two disjoint volumes This methods refers at the end into randomly choose. Thiesson et al. 1997 the mean of dataset This method uses the random way to repeat the steps until reach the desirable clusters. Bradley and Fayyad 1998 randomly breaking technique This method needs to determine the size of subset and the same initial seed for each subset. Likas et al. 2003 Global K-means This method needs to test the results to reach the best number of clusters. Khan and Ahmad 2004 CCIA This method depends on other approach to reach the desired seeds, which lead to more computation complexity. Stephen and Conor 2007 kd-trees This method occasionally failed to provide the lowest value of distortion. 1.3.2 Background Subtraction for Image Segmentation The basic approach for automatic object detection and segmentation methods is the background subtraction. Moreover, it is a commonly used class of techniques for segmenting out objects of a scene for different applications. Therefore, Wren et al., (1997) proposed running Gaussian Average based on ideally fitting a Gaussian probability density function on the last n pixels values in order to model the background independently at each pixel location. Moreover, to increase the speed the standard deviation is computed. Therefore, the advantage of the running average is given by the low memory requirement instead of the buffer with the last n pixel values are used. However, the empirical weight as a tradeoff between stability and quick update is often chosen. The detection of objects is usually approached by background subtraction based on multi-valued background. Therefore, Stauffer Grimson (1999) proposed the multi-valued background model in order to describe the foreground and the background values. Moreover, the probability of observing a certain pixel value at specific time by means of a mixture of Gaussians is described. However, this method needs assigning the new observed pixel value to the best matching distribution and estimating the updated model parameters. Density estimators can be a valuable component in an application like in the use of object tracking. Therefore, Elgammal et al. (2000) proposed a non-parametric model based on Kernel Density Estimation (KDE) by using the last n background values, in order to model the background distribution. Moreover, the sum of Gaussian kernels centered as one sample data by the most recent n background values as background is given. However, complete model estimation also requires the estimation of summation of Gaussian kernels. The eigen-decomposition methods are computationally demanding by involving the computation of each eigenvector and corresponding eigenvalues. Therefore, Oliver et al., (2000) proposed eigen backgrounds approach based on eigenvalues decomposition by using the whole image instead of blocks of image. Moreover, this method can be improving its efficiency, but depend on the images used for the training set. However, this method not explicitly specified what images should be part of the initial sample, and whether and how such a model should be updated over time. In order to generate and select of a plurality of temporal pixel samples derived from incoming image, the temporal median filter is used. Therefore, Lo Velastin (2001) proposed temporal median filter based on the median value of the last n frames as the background model. Moreover, Cucchiara et al. (2003) developed the temporal median filter by computing the last n frames, sub-sampled frames and the time of the last computed median value in order to compute the median on a special set of values. However, the disadvantage of the temporal median filter approach, the computation by a buffer with the recent pixel values is required. Moreover, the median filter does not provide a deviation measure for adapting the subtraction threshold. The information of the difference frames is accumulated, in order to construct a reliable background image. Therefore, Seki et al., (2003) proposed the background subtraction based on co-occurrence of image variations. Moreover, it works on blocks of N x N pixels treated as an N2 component vector, instead of working at pixel resolution. However, this method offers good accuracy against reasonable time and memory complexity. Furthermore, a certain update rate would be needed to cope with more extended illumination changes. Background modeling of a moving object requires sequential density estimatio

OVERVIEW OF LAW ENFORCEMENT INTELLIGENCE :: essays research papers

27 Jan 2002 OVERVIEW OF LAW ENFORCEMENT INTELLIGENCE Intelligence collecting and analyzing have been around since even Biblical times and is often referred to as the second oldest profession. Since the early 1900s, law enforcement officials have begun to utilize the value of the intelligence collection methods. One of the first well-known uses of intelligence by law enforcement was during the â€Å"Black Hand† investigations, which lasted from 1905 to 1909. The investigations resulted in the deportation of 500 people and arrest of thousands of others. In the 1920s and 1930s, intelligence was used to collect information on citizens thought to be anarchists and mobsters, and by the 1940s and 1950s; law enforcement agencies began to utilize intelligence methods in the fight against organized crime. By 1967, the President’s Commission on Organized Crime helped to develop the Racketeering Influenced and Corrupt Organization (RICO). In 1986, the heads of five Mafia families were convicted of violating the RICO. Other types of activities that intelligence is used against are outlaw motorcycle gangs, Russian and Asian organized crime, and street gangs. Some of the duties that fall under the intelligence process for law enforcement are collection, evaluation, integration, and dissemination. Intelligence analysts can assist in investigation or prosecution as well. One of the main problems that analysts seem to be having in the law enforcement field is first getting into the job and then, once they are working, making it up to the higher-level management positions. Many have confused information with intelligence. Information is only raw data, while intelligence is a process of changing this raw data into useable information in order to draw conclusions about unknown events in the past, present, or future.   Ã‚  Ã‚  Ã‚  Ã‚  The different types of intelligence collection and analyzing methods are termed â€Å"disciplines†. There are five different types of disciplines: Imagery Intelligence (IMINT), Signals Intelligence (SIGINT), Measures and Signals Intelligence (MASINT), Human Intelligence (HUMINT), and Open Source Intelligence (OSINT). These five disciplines are what compiles the raw information data that intelligence analysts use to draw conclusions.   Ã‚  Ã‚  Ã‚  Ã‚  IMINT is the method of using pictures to draw information. The pictures can be taken as electro-optical, infrared, radar, or multi-spectral. The greatest advantage is that a picture can speak a thousand words. A disadvantage is that a picture is a moment frozen in time, and the information may change after the snapshot is taken.   Ã‚  Ã‚  Ã‚  Ã‚  SIGINT is the method of taking information from transmissions. Within SIGINT there are three categories as well: Communications Intelligence (COMINT), Telemetry Intelligence (TELINT), and Electronic Intelligence (ELINT).

DQs and Summary Essay

DQ 1: Differentiate between the scientific method and applied research. Which one is most often used in business? Provide an example of either that might be appropriate from your current or previous place of employment DQ 2: You are the manager of a hotel. There have been several complaints from guests relating to employee attitude. Provide a description of three different types of research that might be appropriate for this situation DQ 3: Why do some senior executives feel more comfortable relying with quantitative data than qualitative data? How might a qualitative research company lessen the senior-level executive Business – Risk Management and Insurance DQ-1) Unfortunately, a quick scan of the business news will normally result in reports of unethical business behavior. To prove this point, let’s start with a review of the news for stories about fraud and other unethical behavior in business. You can use the University Library to start your search. Once you have located an article share it with the class by developing a summary of the important information. Make sure that you give credit to your source. DQ-2) Go to Course Home and review the Course Project tab. Then download the Course Project template from Doc Sharing. In this graded discussion, we will be examining the operation of the Accounting Information System (AIS) with the use of problems and exercises from your textbook. The goal is to cover all of the requirements to ensure an opportunity for your successful completion of Course Project 1. Let’s start with a review of the three requirements of Part A of the Course Project. Explain why it is important to analyze each financial transaction of a business and to report it in the Accounting Information System. You can have a ton of fun in college, but it also involves a lot of work. Stay focused on the end result: a diploma. There will be many roadblocks along the way, and how you choose to approach them is important. Use the tips you have seen here to make college work on your behalf. Business – Risk Management and Insurance

Clara Hale essays

Clara Hale essays Black History Month is a great time to celebrate out history, achievements, and accomplishments. February should not be the only time but it is certainly a good time to start. Many blacks have done extraordinary things. I admired Clara McBride Hale. She works with crack-addicted and HIV-positive babies. Clara McBride Hale was born in Elizabeth City, North Carolina. She has suffered lots in her lifetime. She became an orphan at 16, and a widow at the age of 27. She only had her children, and she kept them close. She adopted a third child, and raised him as her own. She became affectionately known as Mother Hale to all in the neighborhood. She began staying at home and caring for the neighborhood kids charging only $2 per week. She later became a licensed foster parent. Hale House was started when Claras daughter, Lorraine noticed a crack-addict mother with a newborn. She directed her to her mothers house, and this baby was the first of thousands of children to reap the love, support, devotion, and care from the arms of Mother Hale. Hale House is Americas first and best known child care agency to gain worldwide recognition when Ronald Reagan introduced Mother Hale as he gave his 1986 State of Union Address. She was called an American hero, and was appointed to the National Drug-Free America Task Force. Many of the children come to Hale House from prisons, police stations and hospitals. They get their funding mostly from private donations and times do get very rough. Hale House is still in operation today. It has become a national role model for children without families. It is a great place to keep these children to keep them out of alleys, garbage cans, and many places where mothers abandon their newborn children. Sadly, Mother Hale passed away in 1993. In her honor, a life-sized statue was built for her in Harlem. Her dream and devotion lives on in the lives of the children she has ...

Da Vinci Code Reflection Surban Essays

Da Vinci Code Reflection Surban Essays Da Vinci Code Reflection Surban Essay Da Vinci Code Reflection Surban Essay It is a well written novel for those who like mystery, codes, secrets and many more like Robert London which is so familiar with Indiana Jones but a smarter version of him and that is why even though it is a very controversial novel to my religion it still amazes me for it is thrilling at the same time it has hidden lessons for all humanity to realize and that is that faith is something you believe in and not what others believe. Although it is an amazing novel with exciting plots, I realize that this is a fictional novel where the facts are not all true but it makes me interested in something more than just the novel. The Dad Vinci infuses both actual historic evidence and imaginary made up evidence so well that it is official for the uneducated people to interpret between what exists in our reality and what is simply something in the reality in which these characters live in. But, The Dad Vinci Code has some limitations like there are serious historical and theological inaccuracies in novel that create false impressions about Jesus, the Christian faith, and the Church. For example, the idea that the divinity of Christ was virtually created by the Council of Nicola is a complete misunderstanding and that is why people think that this novel is mom kind of a threat to the church or even the religion itself for it conveys messages that would deteriorate the image of the Catholic Church. It is not that I find the idea scandalous in any way. I just think it lacks any historical source and frankly, these fictional elements do not overly worry me because I think the film on the whole conveys an important message loud and clear-?that Jesus of Nazareth was an extraordinary teacher and prophet, but a human being, not a God-?and that his resurrection freed Christianity of a rang turn it took many centuries ago and allow us to discover him anew and hear his message unclouded by spiritual belief for the novel I think never wanted to offend the Catholic for the novel just wanted to portray something that the author himself would want to address to the people. Also, in some sense, it is also some kind of test for me because with all the things that the novel would show, it would really test your faith to God and the Church itself because even though that you know that it covers a fictional base, some loud really be persuaded about its contents like the fresco of Leonardo Dad Vinci. Who would have thought that there was a woman in the portrait and that there was no cup? M just saying that the novel has some kind of strong influence to people that the content is true in some ways even though it is real and some may even think about it for a moment and say to themselves 00 nag non?! or Really?! . I on the other hand, after watching The Dad Vinci Code, I still believe in one God even though there are sometimes that doubt my faith and religion but know to myself that I will come back to God or He alone guides me and always helps me in my life for He acts like an inspiration for me to live my life. In the end, I know that the novel is so good and very thrilling but would like to suggest that Catholics and other Christians should genuinely care about the ways in which Jesus and the Christian community are portrayed in modern media We should care enough to re-commit ourselves to Christ, to strive to make the Church a vital and credible witness to the living Christ, and to show by our lives what our faith means to us. Ultimately, we should care because we have a deep love for Christ.

Movie analysis project Essay Example | Topics and Well Written Essays - 750 words

Movie analysis project - Essay Example Communication is extremely important in any relationship and though there were a number of factors that contributed to the break-down of Gary and Brooke’s relationships; however the main factor that gave rise to all other issues is the breakdown of communication between the two protagonists. The break-up highlights the importance of communication and how a simple argument over something as inconsequential as ‘doing the dishes’ resulted in dire consequences. To analyze the communication pattern between the two protagonists, the substance of this prose will first analyze their individual communicating patterns that eventually led to the clash. Jennifer is basically a recognition seeker, who is driven by the desire to be appreciated by her significant other, and she actively exhibits her demands. On the other hand, Vince Vaughn character Gary is boorish and a typical slob. Unlike Brooke, Gary is passive and is more of a confrontation avoider that eventually leads to the problem exacerbating as a result. He is inconsiderate that causes him to disregard most of the things Brooke does for him out of love. As mentioned earlier, both characters break off their relationship in the heat of an argument and instead of talking things out amongst themselves, they approach their respective friends who give them really bad advice. Since, both Brooke and Gary are living in the same condominium; they do not communicate with each other or resolve the key issues in their relationship. Their friends and peers push them up the wrong; the sensible decision in this situation would have been to discuss and talk things out maturely. Despite the fact that both the protagonists were not straight forward with each other, Brooke did try to salvage the relationship, even though the methods were not that effective; especially with someone like Gary who is not emotionally candid and keeps his feelings bottled up most of the time. Fromm trying to make Gary jealous to strutti ng around naked around the house, Brooke remained unsuccessful in winning back Gary, who was bothered by what Brooke was doing yet remained passive about it. The final blow to their relationship, when Brooke invited Gary to a concert with him and she thought that this gesture of hers will finally make him realize how much Brooke wants their relationship to last; however, once again Gary fails to understand the significance of this gesture and a s a result Brooke decides to cease all attempts and leaves him. This is a clear example of lack of communication between the two characters and misunderstandings between that led to the separation. Misunderstandings encircle their relationship and the situation was aggravated by friends and peers, who acted as inept arbitrators. Though, both characters loved each other but the main source of conflict arose from inability to understand each other’s needs. Gary never understood Brooke’s need for appreciation and she never understo od that Gary did not want to be hassled by questions after a long day at the job; in other words both needed ample amount of space in their relationships that could have led to effective communication and they could have avoided several arguments and even the one that led to the break-up. The movie also shows

Proposal Letter and Article Summary Essay Example | Topics and Well Written Essays - 1000 words

Proposal Letter and Article Summary - Essay Example Upon a critical review, of the request for Proposal, our skilled team of Information Technology experts developed a comprehensive structure that will aid in the equipment of the latest computer system. New desktop computers from IBM will be purchased and installed. Our supplier chain will be able to provide sealed pricing proposals of the latest branded and generic (IBM clone) desktop systems, as well as laptops. These computers will have to be networked in order to allow for information sharing and tighten security. Our team has developed a plan that integrates networking of the computers, configuration, installation of software and antivirus software, and training will provided to the staff in order to give them a hands-on experience on this new technology. We have already sent a catalogue of desktop computers and laptops from our supply chain to Kathy Hennig, the senior Purchaser at C.P.M., which has been approved. Smartechs Corporation specializes in software development and supplies computers and computer accessories to our esteemed customers. We also provide training solutions to our customers on Internet security, networking, and basic computer use, and software. As implied in our name, which means â€Å"smart technicians,† we are a dynamic company who believe in embracing technology for future change and success.