Accounting 201 Final Study Guide Essay Example for Free

Accounting 201 Final Study Guide Essay When are expenses recognized? Name the accounting concepts that answer these questions. What are the four financial statements? What is the purpose for each? Does each report for a period of time or for a point in time? Be able to calculate the change in stockholders’ equity for a period based on information contained in the retained earnings statement. What is GAAP? Who is the body currently responsible for establishing GAAP? What governmental agency has oversight authority over the accounting profession? What is an audit? What is the purpose of an independent audit? Who can perform an audit? What is the sequence of the accounting cycle? Define the following terms related to the accounting cycle: -chart of accounts -journal -ledger -trial balance -adjusting entries -adjusted trial balance -closing entries -post-closing trial balance -posting -journal entry -debit -credit -t-account Be familiar with account classification. What are the five major categories of accounts? What is a contra account? Be able to analyze transactions using the debit/credit rules. What is a compound journal entry? How is an account’s balance determined? What is meant by the term normal balance? Be able to calculate an account balance. When are adjusting entries prepared? Why are they necessary? What are some rules that apply to all adjustments? Review the handout you were give regarding adjusting entries. What do the following accounting concepts mean? -going concern -cost-benefit -materiality -consistency -revenue recognition/realization -matching Which of the accounting concepts listed above form the basis for accrual basis accounting? What are the three closing entries? What is the purpose of closing entries? What is the format for a bank reconciliation? Which reconciling items require that a journal entry be made to recognize them? Be aware of the formulas to calculate some of the commonly used financial ratios, including: -current ratio -working capital -quick ratio How are the following items calculated? -net sales -cost of goods sold What is the difference between a periodic inventory system and a perpetual inventory system? What are internal control procedures? What are the four primary reasons for establishing internal controls? What are some common examples of internal control procedures? Define the following terms with regard to notes receivable/notes payable: -principal -interest -maturity date -maturity value Be able to calculate ending inventory and cost of goods sold under the following inventory cost allocation methods: -average costing -FIFO (first-in, first-out) -LIFO (last-in, first-out) Be able to define the following terms related to long term assets: cost -residual value/salvage value/trade-in value depreciable cost -book value -service life/useful life -depreciation -accumulated depreciation -depletion -amortization Be able to calculate depreciation using the following methods: -straight line -units of production -double declining balance How is the cost of a group/bundled purchase of assets allocated? What is the difference between the direct write off method and the allowance method of recognizing bad debts? Which one is p referred by GAAP? Why? Be able to define the following terms related to bonds payable: -bond indenture -debenture -secured bond coupon bond -registered bond -convertible bond -callable bond -term bond -serial bond -sinking fund When will a bond sell at a discount? At a premium? Be able to determine the issue price of a bond based on its market price quote. What are the rights of bondholders? Of common stockholders? Of preferred stockholders? Be able to define the following terms related to stock: -common stock -preferred stock -dividends in arrears -par value -treasury stock -dividend declaration date -date of record -dividend payment date -stock dividend -stock split -book value

Smart Music Player Integrating Facial Emotion Recognition

Smart Music Player Integrating Facial Emotion Recognition Smart Music Player Integrating Facial Emotion Recognition and Music Mood Classification 1Shlok Gilda, 2Husain Zafar, 3Chintan Soni, 4Kshitija Waghurdekar Department of Computer Engineering, Pune Institute of Computer Technology, Pune, India Abstract Songs, as a medium, have always been a popular choice to depict human emotions. Reliable emotion based classification systems can go a long way in facilitating this. However, research in the field of emotion based music classification has not yielded optimal results. In this paper, we present an affective cross-platform music player, EMP, which recommends music based on the real-time mood of the user. EMP provides smart mood based music recommendation by incorporating the capabilities of emotion context reasoning within our adaptive music recommendation system. Our music player contains three modules: Emotion Module, Music Classification Module and Recommendation Module. The Emotion Module takes an image of the user as an input and makes use of deep learning algorithms to identify the mood of the user with an accuracy of 90.23%. The Music Classification Module makes use of audio features to achieve a remarkable result of 97.69% while classifying songs into 4 different mood c lasses. The Recommendation Module suggests songs to the user by mapping the emotion of the user to the mood of the song, taking into consideration the preferences of the user. Keywords-Recommender systems, Emotion recognition, Music information retrieval, Artificial neural networks, Multi-layer neural network. I. Introduction Current research in the field of music psychology has shown that music induces a clear emotional response in its listeners[1]. Musical preferences have been demonstrated to be highly correlated with personality traits and moods. The meter, timber, rhythm and pitch of music are managed in areas of the brain that deal with emotions and mood[2]. Undoubtedly, a users affective response to a music fragment depends on a large set of external factors, such as gender, age[3], culture[4], preferences, emotion and context[5] (e.g. time of day or location). However, these external variables set aside, humans are able to consistently categorize songs as being happy, sad, enthusiastic or relaxed. Current research in emotion based recommender systems focuses on two main aspects, lyrics[6][12] and audio features[7]. Acknowledging the language barrier, we focus on audio feature extraction and analysis in order to map those features to four basic moods. Automatic music classification using some mood categories yields promising results. Expressions are the most ancient and natural way of conveying emotions, moods and feelings. The facial expression would categorize in 4 different emotions, viz. happy, sad, angry and neutral. The main objective of this paper is to design a cost-effective music player which automatically generates a sentiment aware playlist based on the emotional state of the user. The application designed requires less memory and less computational time. The emotion module determines the emotion of the user. Relevant and critical audio information from a song is extracted by the music classification module. The recommendation module combines the results of the emotion module and the music classification module to recommend songs to the user. This system provides significantly better accuracy and performance than existing systems. II. Related Works Various methodologies have been proposed to classify the behaviour and emotional state of the user. Mase et al. focused on using movements of facial muscles[8] while Tian et al.[9] attempted to recognize Actions Units (AU) developed by Ekman and Friesen in 1978[10] using permanent and transient facial features. With evolving methodologies, the use of Convolutional Neural Networks (CNNs) for emotion recognition has become increasingly popular[11]. Music has been classified using lyrical analysis[6][12]. While this tokenized method is relatively easier to implement, on its own, it is not suitable to classify songs accurately. Another obvious concern with this method is the language barrier which restricts classification to a single language. Another method for music mood classification is using acoustic features like tempo, pitch and rhythm to identify the sentiment conveyed by the song. This method involves extracting a set of features and using those feature vectors to find patterns characteristic to a specific mood. III. Emotion Module In this section, we study the usage of convolutional neural networks (CNNs) to emotion recognition[13][14]. CNNs are known to simulate the human brain when analyzing visuals; however, given the computational requirements and complexity of a CNN, optimizing a network for efficient computation is necessary. Thus, a CNN is implemented to construct a computational model which successfully classifies emotion in 4 moods, namely, happy, sad, angry and neutral, with an accuracy of 90.23%. A.   Dataset Description The dataset we used for training the model is from a Kaggle Facial Expression Recognition Challenge, FER2013[15]. The data consists of 4848 pixel grayscale images of faces. Each of the faces are organized into one of the 7 emotion classes: angry, disgust, fear, happy, sad, surprise, and neutral. For this research, we have made use of 4 emotions: angry, happy, sad and neutral. There is a total of 26,217 images corresponding to these emotions. The breakdown of the images is as follows: happy with 8989 samples, sad with 6077 samples, neutral with 6198 samples, angry with 4953 samples. B. Model Description A multi-layered convolutional neural network is programmed to evaluate the features of the user image[16][17]. The convolutional neural network contains an input layer, some convolutional layers, ReLU layers, pooling layers, and some dense layers (aka. fully-connected layers), and an output layer. These layers are linearly stacked in sequence. 1) Input Layer: The input layer has fixed and predetermined dimensions. So, for pre-processing the image, we used OpenCV for face detection in the image before feeding the image into the layer. Pre-trained filters from Haar Cascades along with Adaboost are used to quickly find and crop the face. The cropped face is then converted into grayscale and resized to 48-by-48 pixels. This step greatly reduces the dimensions from (3, 48, 48) (RGB) to (1, 48, 48) (grayscale) which can be easily fed into the input layer as a numpy array. 2) Convolutional Layers:A set of unique kernels (or feature detectors), with randomly generated weights, are specified as one of the hyperparameters in the Convolution2D layer. Each feature detector is a (3, 3) receptive field, which slides across the original image and computes a feature map. Convolution generates different feature maps for the same input image. Distinct filters are used to perform operations that represent how pixel values are enhanced, for example, blur and edge detection. Filters are applied successively over the entire image, creating a set of feature maps. In our neural network, each convolutional layer generates 128 feature maps. Rectified Linear Unit (ReLU) has been used after every convolution operation. After a set of convolutional layers, a popular pooling method, MaxPooling, was used to reduce the dimensionality of each feature map, all the while retaining the critical information. We used (2, 2) windows which consider only the maximum pixel values within the window from the feature map. The pooled pixels form an image with dimensions reduced by 4. Rectified Linear Unit (ReLU) has been used after every convolution operation. 3) Dense Layers:The output from the convolutional and pooling layers represent high-level features of the input image. The dense layer uses these features for classifying the input image into various classes. The features are transformed through the layers which are connected with trainable weights. The network is trained by forward propagation of training data and then backward propagation of its errors. Our model uses 2 sequential fully connected layers. The network generalizes well to new images and is able to gradually make adjustments until the errors are minimized. A dropout of 20% was applied in order to prevent overfitting of the training data. This helped us control the models sensitivity to noise during training while maintaining the necessary complexity of the architecture. 4) Output Layer:We used softmax as the activation function at the output layer of the dense layer. Thus, the output is represented as a probability distribution for each emotion class. Models with various combinations of hyper-parameters were trained and evaluated utilizing a 4 GiB DDR3 NVIDIA 840M graphics card using the NVIDIA CUDA ® Deep Neural Network library (cuDNN). This greatly reduced training time and increased efficiency in tuning the model. Ultimately, our network architecture consisted of 9 convolutional layers with one max-pooling after every three convolution layers followed by 2 dense layers, as seen in Figure 1. C. Results The final network was trained on 20973 images and tested on 5244 images. At the end, the model achieved an accuracy of 90.23%. Table 1 displays the confusion matrix for the module. Evidently, the system performs very well in classifying images belonging to the angry category. We also note interesting results under happy and sad category owing to the remarkable differences in Action Units as mentioned by Ekman[11]. The F-measure of this system comes out to be 90.12%. IV. Music Classification Module In this section, we describe the procedure that was used to identify the mapping of each song with its mood. We extracted the acoustic features of the songs using LibROSA[18], aubiopitch[19] and other state-of-the art audio extraction algorithms. Based on these features, we trained an artificial neural network which successfully classifies the songs in 4 classes with an accuracy of 92.05%. The classification process is described in Figure 2. A.Dataset Description The dataset comprises of 390 songs spread across four moods. The distribution of the songs is as follows: class A with 100 songs, class B with 93 songs, class C with 100 songs and class D with 97 songs. The songs were manually labelled and the class labels were verified by 10 paid subjects. Class A comprises of exciting and energetic songs, class B has happy and joyful songs, class C consists of sad and melancholy songs, and class D has calm and relaxed songs. 1) Preprocessing: All the songs were down sampled to a uniform bit-rate of 128 kbps, a mono audio channel and resampled at a sampling frequency of 44100 Hz. We further split each song to obtain clips that contained the most meaningful parts of the song. The feature vectors were then standardized so that it had zero mean and a unit variance. 2) Feature Description: We identified several mood sensitive audio features by reading current works[20] and the results from the 2007 MIREX Audio Mood Classification task[21][22]. The candidate features for the extraction process belonged to different classes: spectral (RMSE, centroid, rolloff, MFCC, kurtosis, etc.), rhythmic (tempo, beat spectrum, etc.), tonal mode and pitch. All these descriptions are standard. All the features were extracted using Python 2.7 and relevant packages[18][19]. After identifying all the features, we used Recursive Feature Elimination (or RFE) to select those features that best contribute to the accuracy of the model. RFE works by recursively removing attributes and building a model on those attributes that remain. It uses the model accuracy to identify which attributes (and combination of attributes) contribute the most to predicting the target attribute. The selected features were pitch, spectral rolloff, mel-frequency cepstral coefficients, tempo, root mean square energy, spectral centroid, beat spectrum, zero-cross rate, short-time Fourier transform and kurtosis of the songs. B. Model Description A multi-layered neural network was trained to evaluate the mood associated with the song. The network contains an input layer, multiple hidden layers and a dense output layer. The input layer has fixed and predetermined dimensions. It takes the 10 feature vectors as input and uses ReLU operation to provide non-linearity to the dataset. This ensured that the model performs well in real-world scenarios as well. The hidden layer is a traditional multi-layer perceptron, which allowed us to make combination of features which led to a better classification accuracy. The output layer used a softmax activation function which produces the output as a probability for each mood class. C. Results We achieved an overall classification accuracy of 97.69% and F1 score of 97.692% after 10-fold cross-validation using our neural network. Table 2 displays the confusion matrix. Undoubtedly, the level of performance of the music classification module is exceptionally high. V. Recommendation Module This module is responsible for generating a playlist of relevant songs for the user. It allows the user to modify the playlist based on her/his preferences and modify the class labels of the songs as well. The working of the recommendation module is explained in Figure 3. A. Mapping and Playlist Generation Classified songs are mapped to the users mood. This mapping is as shown in figure 1. The system was developed after referring to the Russell 2-D Valence-Arousal Model and Geneva Emotion Wheel.After the mapping procedure is complete, a playlist of relevant songs is generated. Similar songs are grouped together while generating the playlist. Similarity between songs was calculated by comparing songs over 50ms intervals, centered on each 10ms time window. After empirical observations, we found that the duration of these intervals is on the order of magnitude of a typical song note. Cosine distance function was used to determine the similarity between audio files. Feature values corresponding to an audio file were compared to the values (for the same features) corresponding to audio files belonging to the same class label. The recommendation engine has a twofold mechanism; it recommends songs based on: 1. Users perceived mood. 2. Users preference. Initially, a playlist of all songs belonging to the particular class is generated. The user can mark a song as favorite depending on her/his choice. A favorite song will be assigned a higher priority value in the playlist. Also, the interpretation of the mood of a song can vary from person to person. Understanding this, the user is allowed to change the class label of the songs according to their taste of music. B. Adaptive Music Player We were able to implement an adaptive music player by the use of a very popular online machine learning algorithm, Stochastic Gradient Descent (SGD)[23]. If the user wants to change the class of a particular song, SGD is implemented considering the new label for that specific user only. Multiple single-pass algorithms were analyzed for their performance with our system but SGD performed most efficiently considering the real-time nature of the music player. Parameter updates in SGD occur after processing of every training example from the dataset. This approach yields two advantages over the batch gradient descent algorithm. Firstly, time required for calculating the cost and gradient for large datasets is reduced. Secondly, integration of new data or amendment of existing data is easier. The frequent, highly variant updates demand the learning rate ÃŽÂ ± to be smaller as compared to that of batch gradient descent[23]. VI. Conclusion The results obtained above are very promising. The high accuracy of the application and quick response time makes it suitable for most practical purposes. The music classification module in particular, performs significantly well. Remarkably, it achieves high accuracy in the angry category; it also performs specifically well for the happy and calm categories. Thus, EMP reduces user efforts for generating playlists. It efficiently maps the user emotion to the song class with an excellent overall accuracy, thus achieving optimistic results for 4 moods. References [1] Swathi Swaminathan, E. Glenn Schellenberg. Current Emotion Research in Music Psychology, Emotion Review Vol. 7, No. 2, pp. 189 ­-197, April 2015 [2] How music changes your mood, Examined Existence. [Online]. Available: http://examinedexistence.com/how-music-changes-your-mood/. Accessed: Jan. 13, 2017 [3] Kyogu Lee and Minsu Cho. Mood Classification from Musical Audio Using User Group-dependent Models. [4] Daniel Wolff, Tillman Weyde and Andrew MacFarlane. Culture-aware Music Recommendation [5] Mirim Lee, Jun-Dong Cho. Logmusic: Context-Based Social Music Recommendation Service on Mobile Device, Ubicomp 14 Adjunct, September 13-17, 2014, Seattle, WA, USA. [6] D. Gossi and M. H. Gunes, Lyric-based music recommendation, in Studies in Computational Intelligence. Springer Nature, 2016, pp. 301-310. [7] Bo Shao, Dingding Wang, Tao Li, and Mitsunori Ogihara. Music Recommendation Based on Acoustic Features and User Access Patterns, IEEE TRANSACTIONS ON AUDIO, SPEECH, AND LANGUAGE PROCESSING, VOL. 17, NO. 8, NOVEMBER 2009 [8] Mase K. Recognition of facial expression from optical flow. IEICE Transc., E. 74(10):3474-3483, 0ctober 1991. [9] Tian, Ying-li, Kanade, T. and Cohn, J. Recognizing Lower. Face Action Units for Facial Expression Analysis. Proceedings of the 4th IEEE International Conference on Automatic Face and Gesture Recognition (FG00), March, 2000, pp. 484 490. [10] Ekman, P., Friesen, W. V. Facial Action Coding System: A Technique for Measurement of Facial Movement. Consulting Psychologists Press Palo Alto, California, 1978. [11] Gil Levi and Tal Hassner, Emotion Recognition in the Wild via Convolutional Neural Networks and Mapped Binary Patterns [12] E. E. P. Myint and M. Pwint, An approach for mulit-label music mood classification, 2010 2nd International Conference on Signal Processing Systems, Dalian, 2010, pp. V1-290-V1-294. [13] Peter Burkert, Felix Trier, Muhammad Zeshan Afzal, Andreas Dengel and Marcus Liwicki. DeXpression: Deep Convolutional Neural Network for Expression Recognition [14] Ujjwalkarn, An intuitive explanation of Convolutional neural networks, the data science blog, 2016. [Online]. Available: https://ujjwalkarn.me/2016/08/11/intuitive-explanation-convnets/. Accessed: Jan. 13, 2017. [15] Ian J. Goodfellow et al., Challenges in Representation Learning: A report on three machine learning contests [16] S. Lawrence, C. L. Giles, Ah Chung Tsoi and A. D. Back, Face recognition: a convolutional neural-network approach, in IEEE Transactions on Neural Networks, vol. 8, no. 1, pp. 98-113, Jan 1997. [17] A. KoÅ‚akowska, A. Landowska, M. Szwoch, W. Szwoch, and M. R. WrÃÅ' obel, Human-Computer Systems Interaction: Back-grounds and Applications 3, ch. Emotion Recognition and Its Applications, pp. 51-62. Cham: Springer International Publishing, 2014. [18] Brian McFee, ., Matt McVicar, ., Colin Raffel, ., Dawen Liang, ., Oriol Nieto, ., Eric Battenberg, ., à ¢Ã¢â€š ¬Ã‚ ¦ Adrian Holovaty, . (2015). librosa: 0.4.1 [Data set]. Zenodo. http://doi.org/10.5281/zenodo.32193 [19] The aubio team, Aubio, a library for audio labelling, 2003. [Online]. Available: http://aubio.org/. Accessed: Jan. 13, 2017. [20] E. E. P. Myint and M. Pwint, An approach for mulit-label music mood classification, 2010 2nd International Conference on Signal Processing Systems, Dalian, 2010, pp. V1-290-V1-294. [21] J. S. Downie. The music information retrieval evaluation exchange  Ãƒâ€šÃ‚  Ãƒâ€šÃ‚  Ãƒâ€šÃ‚   (mirex). D-Lib Magazine, 12(12), 2006. [22]  Ãƒâ€šÃ‚   Cyril Laurier, Perfecto Herrera, M Mandel and D Ellis,Audio music mood classification using support vector machine [23] Unsupervised feature learning and deep learning Tutorial, [Online]. Available: http://ufldl.stanford.edu/tutorial/supervised/OptimizationStochasticGradientDescent/. Accessed: Jan. 13, 2017

Animal Influences in Paleolithic, Egyptian and Greek Art Essay

Animal Influences in Paleolithic, Egyptian and Greek Art There are numerous ways in which animals have resonated within the human mind. Throughout history there have been representations ranging from the realistic, to myths, legends, symbols, and even horrific murderous beasts; at the same time providing fascinating perspectives of our own humanity. Various forms of art have conveyed ideas and concepts of animal’s intelligence, as well as behavior, from generation to generation. Animal art is used as a tool to make the connection between different cultures at different time periods and it relates historical and symbolic meanings. In most cultures animals have been linked with the supernatural forces which were believed to control the natural world and the destiny of humans. They were often revered as the agents. or associates, of gods, and goddesses, and were even the focus of worship as deities. Following the tracks of historical animal art, through the human imagination introduces a trail of creativity and unsurpassed beauty. Paleolithic art: Cave paintings are the earliest known example of human art dating 40,000 to 8,000 BCE. The paintings mainly feature various animals running, sleeping, and eating. Some also contain a few humans, geometrical shapes, and even hand prints. The artist used permanent features like ceilings, floors, and walls of rock shelters and caves as their canvas. Pigments of black, yellow, red, and brown were utilized to display the observations of animals. The painters gathered a great deal of information about finding food, and which foods were safe to eat or to hunt, by closely observing animals. The valuable information was passed to others through the detailes in the... ... Avery, Catherine B. The New Century Classical Handbook. New York, 1962 Beckett, Sister Wendy. The Story of Painting. New York, 1994 Boardman, John, Greek Art. London, 1964 Durant, Will. Our Oriental Heritage. New York, 1935 Fleming, William. Arts & Ideas. New York Gombrich, E. H. The Story of Art. London, 1967 Hall, James. Dictionary of Subjects & Symbolism in Art. New York, 1974 Kirk, G. S. The Nature of Greek Myths. New York, 1975 Janson, H. W. History of Art. New York, 1969 Leroi-Gourhan, Andre. Treasures of Prehistoric Art. New York MacClintock, Dorcas. Animals Observed. New York, 1993 Metropolitan Museum of Art. Treasures of Tutankhamun. New York, 1976 Richter, Gisela M. A. A Handbook of Greek Art. New York, 1987 Scranton, Robert L. Aesthetic Aspects of Ancient Art. Chicago, 1964 Stockstad, Marilyn. Art History. New York, 1995

Environmental Pollution Essay -- essays research papers fc

Environmental Pollution ENVIRONMENTAL POLLUTION Automobiles like these are around the world everyday, and their exhaust destroys our air everyday. Our environment is a major aspect of our life today. Many of us don't take our Earth seriously and think that as long as pollution doesn't hurt them they can go ahead and throw garbage on the ground or spill oil down the drain. Well to many people have that theory and they are killing off our Earth and also physically harming themselves from the air they breath and the water they swim in. Our Earth is fragile like a human and people don't know. There are many different types of environmental pollution (e.g. Water, air, atmospheric.) Scientists believe that all cities with populations exceeding 50,000 have some degree of air pollution. Burning garbage in open dumps causes air pollution, and also it smells pretty bad. Air pollution comes from many different sources. One of the major sources is carbon monoxide which manly comes from automobiles, but also burning of fossil fuels, CFCs etc. Air pollution does not leave the Earth it all gets trapped up in the atmosphere. This doesn't bother most people, and they think that it will not harm them. People burn down forests and people burn fossil fuels, and CFCs from aerosols. Every bit of this harms our atmosphere. Factories and transportation depend on huge amounts of fuel billions of tons of coal and oil are consumed around the world every year. When these fuels burn they introduce smoke and other, less visible, by-products into the atmosphere. Although wind and rain occasionally wash away the smoke given off by power plants and automobiles, the cumulative effect of air pollution poses a grave threat to humans and the environment. A big example of smog is LA you can see the smog just hovering above the city. I don't think any human alive should be subject to that kind of environment. Scientists believe that all cities with populations exceeding 50,000 have some degree of air pollution. Burning garbage in open dumps causes air pollution Scientist have discovered that over the South Pole the ozone has a high level of ozone depletion. A computer-enhanced map, taken from satellite observations of ozone levels in the atmosphere over the South Pole, shows the region of ozone depletion that has begun to appear each spring over Antarctica.  ... ...sp; I think that all kinds of environmental pollution can be stopped if we all use our heads and just think before we throw a piece of trash on the ground, throw it into a nearby garbage can. We should look at our Earth as a precious human being and treat it like it were a child of our own. We should not trash it and take advantage of it. If we abuse our Earth now who knows how it will get back at us in the future. Saving the Earth is such a simple task, and I think everyone should be involved in it rich or poor. If we don't save our Earth now someday it will be to late. There are programs out there that try to save the Earth, but not enough people corporate in these programs. If more people supported and joined into these programs maybe our world wouldn't be in such danger of dying. If our Earth dies it will surely take us all with it. BIBLIOGRAPHY Environmental Health, Carleson Lavonne Chelsea House Publishers, New York 1994 Acid Rain, Tyson Peter Chelsea House Publishers, New York 1992 Clean Water, Barass Karen Chelsea House Publishers, New York 1992 "Environmental Pollution" Comptons Interactive Encyclopedia 1996 "Smog" Encarta Encyclopedia 1996

Health Promotion Essay -- Healthy Lifestyle Essay

Health by definition is the complete physical, mental and social well-being (Burch, 2001). In the past health has been defined as the absence of disease. Health promotion enables people the ability and resources to improve and control their overall health. Being able to adjust and adapt to various social and physical environments in day-to-day activities is a trait of a healthy individual. Health promotion is not just the responsibility of those individuals in the health field. An individual?s well-being reflects whether or not that person has a healthy lifestyle. Therefore health promotion becomes an issue for employers, retailers, sports and policy makers among others because issues such as safety and environmental factors will have an influence on the well-being of an individual (Ottawa Charter, 1986). Collaborative and coordinated efforts to provide safer goods and services, and a cleaner, more enjoyable environment should be the goal for all. The goal of all involved sho uld be to provide a healthier environment that will provide a better well-being for the population. Promoting health requires the detection of any barriers that would hinder the health promotion process and removal of them. Promoting health is, also, educating the public to current health issues. There are various aspects of health promotion. Health promotion can be applied to any group or environment. A few of the more popular places and populations we see health promotion being addressed more often are the workplace, community, among adolescent, and the elderly. However, I believe the most effective and important place to begin health promotion is within our school systems. Promoting a healthy lifestyle, bettering quality of life, and prev... ...r 1, 2001 from Expanded Academic Index ASAP database. Manson, S. M., (1997). One small step for Science, one giant lead for prevention. American Journal of Community Psychology, 25, 2, 215. Retrieved October 1, 2001 from Expanded Academic Index ASAP database. 1Center for Disease Control, (2001). Healthy Aging: Preventing Disease and Improving Quality of Life Among Older Americans. Retrieved October 1, 2001 from http://www.cdc.gov/nccdphp/aag-aging.htm 2Center for Disease Control (2001). School Health Programs: An investment in Our Nation?s Future. Retrieved October 1, 2001 from http://www.cdc.gov/nccdphp/dash/ataglanc.htm Healthy People, (2001). http://www.health.gov/healthypeople/ Ottawa Charter for Health Promotion (1986). First International Conference of Health Promotion. Retrieved October 1, 2001 from http://www.who.dk/policy/ottawa.htm

Comparative Commentary Text 1 Those Winter Sundays, Text 2 The Boat Essay

Text 1 and Text 2, both have the common theme of fathers. Text 1 is a poem titled â€Å"Those Winter Sundays† by Robert Hayden, while Text 2 is an extract of the short story â€Å"The Boat† by Alistair Macloed. The purpose of Hayden is to tell the story and to tell younger people to appreciate their father; on the other hand Alistair MacLoed’s purpose was to entertain the audience. The common theme are the fathers, both texts narrate the story and the relationship between a father and a son. Both texts show how they treated their fathers in a careless way but then realized they shouldn’t have. In text 1 he realizes too late, and he can’t do anything to change it, however in text 2 the character realizes just on time and starts loving his father and appreciating what he does. There are several other similarities and differences like the fact that both fathers do hard work and they probably belong to the working class or even to the poorer class. This can be seen as in text 1 the father had hands that â€Å"ached from labour in the weekday†; in text 2 the father is a â€Å"fisherman†. Both fathers dedicate lots of their time and effort to their families, in text 1 the father wakes up really early so he can warm the room for his children to wake up into a comfortable room while in text 2 the father sacrificed his â€Å"dreams and inclinations† and lived a life doing what he really did not want for the benefit of the family. Similarities are also found in the tone. The tone in both texts is regretful. In text 1 the regretful tone is suggested through the description of the father, â€Å"Cracked hands that ached† as this increases our empathy towards the father, furthermore in text 2 the regretful tone is suggested through the description of the father’s action as â€Å"he burned and reburned over and over again†. This is also to increase empathy. Increasing the empathy helps us connect more to the author and be able to understand his regret. Another way through which regret is portrayed in text 1 is thought Robert Hayden’s last lines, with the rhetorical question at the end â€Å"What did I know,† This quote shows how Hayden has now realized how much effort his father had put into the family, this also shows how Hayden feels that it is too late to do something now that he has realized. In text 2 the tone of regret is portrayed not only through the description of the father but also through how the short story develops. The structure of text 1 is very different to text 2, first of all the fact that text 1 is a poem and text 2 a short story. As it was already mentioned, the regretful tone in text 2 is transmitted through the development of the story; the story is structured in paragraphs. The structure of the short story is very important as it starts by setting the scene as it describes the â€Å"good summer†. In the second paragraph Alistair MacLoed describes the father and how he suffers and keeps on working, â€Å"his lips still cracked so that they bled when he smiled†, this starts creating a tone of guilt as the character saw his dad suffer and did nothing. In the third paragraph we notice some transformation as he starts to realize the hard work his father does but it’s in the last paragraph is where we see the biggest change as he changes his attitude and starts loving his father. Structure is also very important in text1, the poem. It is a short poem that contains 3 stan zas. There is no rhyme in the poem as rhyme introduces a happy, joyful connotation; Robert Hayden decided not to include rhyme as this poem corresponds to a melancholic and sad relationship between father and son. When it comes to sentence lengths, text 1 contains 5 sentences, they are very different in sentence length as we have a very short one, â€Å"No one ever thanked him.† and really long ones as the 4th sentence, which takes up 6 lines. The poem isn’t structured as a poem but as a narrative, if the same text would not be in stanzas it would be a narrative. However in Text 2, as the text is structured in paragraphs, we can see how the sentences change depending on which paragraph they are in. For example, in paragraph 2, the one that tells us the dad’s sacrifices the sentences are long and the use lots of â€Å"and†, this gives a sense of continuous and a sense of repetition, which makes you feel the father’s pain. It is a very effective sentence a s it increases the empathy. Both texts have similarities and differences regarding language. Text 1 ends with a rhetorical question, this rhetorical question increases the regret already portrayed in the poem and the feeling of guilt as it is already too late to change anything and previously he hadn’t noticed his father’s effort. The diction through out the poem is quite simple, as the poem is directed to young people. Robert Hayden used imagery to create empathy towards the father as he is described as waking up in the â€Å"blueblack cold† and his â€Å"cracked hands that ached†. The use of the words â€Å"chronic angers† suggest tension in the family and opens the possibility of a long lasting fight happening inside the house, â€Å"speaking indifferently to him† also adds into the suggestion of tension in the house and the use of the word â€Å"indifferently† creates guilt as he treated his dad in an indifferent way. Furthermore Alistair MacLoed, the author of text 2 uses common diction through out the short story, the diction in both texts is very similar. MacLoed uses several times the word â€Å"and† there are several purposes for the use of the word â€Å"and†, at the beginning, when describing the father’s effort the word â€Å"and† is used for repetition as it increases the effect of empathy in the sentence. Later on in the story the word â€Å"and† is used to link ideas and to establish a good relationship between father and son as the text reads with a happier but still regretful tone. In conclusion both texts have clear similarities and differences as they both shared the topic of fathers and their relationship with their sons, though they have different purposes and therefore differences.

Project Management Essay

First, develop project selection criteria and a high level process for applying the criteria and managing the portfolio. The criteria should be consistent with the business environment for the industry, consistent with your company’s overall mission/strategies, and consistent with the mission and strategies of your strategic business unit. You are proposing a process, not individual projects. The deliverable for Part 1 is a written proposal for the project selection criteria and a high level description of a proposed portfolio management process. You may also be expected to make an informal presentation of the report in class. The proposal should be in the form of a memorandum to your Vice President (your instructor) outlining your proposal. The memorandum should be no more than 10 pages, including any figures and tables. It should be double-spaced, 10 or 12 point font with one-inch margins. This is a summary for an executive, so be concise, to the point, and leave out the fluff. If you don’t need 10 pages to document your proposal fully, I am sure that your Vice President will be happy with less as long as it is complete. Using appropriate grammar, spelling, punctuation, and sentence structure will be part of your grade. The actual proposal should include the following: 1. A description of the proposed portfolio process. You are explaining it to the executives. 2. The reasons it was selected (tie to strategies as appropriate. ) 3. A description of the proposed selection criteria. How will the process be applied in your SBU? 4. The method for applying the selection criteria, and the justification for both. How are you going to score the projects and evaluate the scores? This is not a complete project proposal or even a complete status report. You are making a specific proposal to management of a â€Å"Project Portfolio Evaluation and Selection Process†. All reports and memos to executives should include an executive summary at the beginning. This one is no exception. The discussion of the organization should be limited to how the SBU organization supports projects and the PPM process. It is not necessary to discuss the total company. Pay attention to the specifics requested in the deliverables. Do NOT make your memo a list of questions and answers. That is not the way a business memo is written. It is easy to select a process that is presented in a reference but you must propose one that works for your SBU. When you think you are finished put yourself in the role of someone who was not working on the solution and read your presentation. You can assume you know the basics of PPM. †¢Does your presentation provide a good description of the process and how it will be applied? †¢Are there obvious questions that it raises that are not answered? This is not a classroom assignment, it is a business memo. Also it is not a research report and you are not trying to demonstrate your academic expertise and how well you are read. Part 2 In Part 1 of the project, the new Vice President (your instructor) of your Strategic Business Unit had asked you to create a portfolio management process and project selection criteria for use by the SBU. It is now time to apply this process in selecting this year’s projects for your portfolio. In the annual budget cycle, your SBU was allocated $24 million dollars of funding uniformly spread over the next year for your portfolio. This means you have $6 million dollars to spend any given quarter. You may select any of the below projects to be included in your portfolio, but you cannot spend more than the allotted dollars allocated to your SBU. Your task is to select those projects, using your selection criteria, that most benefit the overall company without exceeding you quarterly budget of $6 million dollars. You must also lay out a plan for what quarter your selected projects will start in. Below are your possible projects: Project Call Center Currently you have no call center to address customer complaints or accept orders. Customers must use the internet to fill out an online form to address their complaints or service needs. These forms are processed by employees in your department. Currently the turnaround time on any given form is between four to eight hours. This creates a number of other customer complaints. Project Call Center is designed to reduce this turnaround time by 75% by creating and staffing a call center in Tampa. Building acquisition, building renovations, building fit out, IT system upgrades, and hiring and training of staff are estimated to cost $8. 5 million dollars. This $8.5 million dollars can be paid evenly in any two quarters in the next year. In addition, seven new employees will need to be hired at $40,000 burdened labor costs per year to staff the call center. Management of this project could easily be done with the current in-house staff. Most of the work of this project would be outsourced and will have minimal impact on day-to-operations. Project Ordering Upgrade Currently ordering processing is done online. The software and hardware used in this system are about ten years old. As such, order processing is a long, arduous process for the fifteen person staff. Upgrading this process to a state of the art system would cost approximately $2. 5 million dollars, and it is a onetime pay in full internal charge to your SBU. It would also result in a reduction in the fifteen person staff by 7 individuals and reduce order processing time by 50%. Each individual in this department is paid $35,000 burdened labor costs a year. Most of the work of this project could be done internally with existing staff. One weekend of operations will be impacted by the project in its entirety. Project Rocky The Alaskan cruise ship industry is booming. For some reason, people like to look at icebergs. Unfortunately, our company is servicing no cruise ships in Alaska. Project Rocky is to expand into the Alaskan market. This project will require the acquisition of property in Alaska, renovation of that property, and staffing of the facility. This project is seen as a major money maker for the company and has a NPV of $19 million dollars over five years. Its costs would be $13 million dollars to initially set up the project and $400,000 a year to operate the facility. This initial cost can be spread evenly over each of four quarters of the entire year. These initial costs should be recovered within the first two or three years of operation. Most of the work of this project would be outsourced and management of the project would likely be difficult. Project Europa The Mediterranean cruise ship industry is booming. Unfortunately, our company is servicing no cruise ships in the entire European area. Project Europa is to expand into the Mediterranean market. This project will require the acquisition of property in Italy, renovation of that property, and staffing of the facility. The current governmental overspending and austerity issues may impact this project. However, this project is seen as a major money maker for the company and has a NPV of $15 million dollars over seven years. Its costs would be $11 million dollars to initially set up the project and $500,000 a year to operate the facility. This initial cost can be spread evenly over each of the four quarters of the entire year. These initial costs should be recovered within the first three years of operation. Most of the work of this project would be outsourced and management of the project would be extremely difficult. Project Robot Our key distribution center is in St. Petersburg, Florida. It has a staff of 100 individuals to process the linens for the Florida cruise industry. Automation would allow us to reduce staff by 35 individuals. The average burdened labor costs of each of these individuals is $45,000 dollars a year. The cost of such automation would be in the neighborhood of $17 million dollars. This initial cost can be spread evenly over the entire year. This project would also likely disrupt the facility for about 3 months while the work is being done. Upon completion, the newly remodeled facility will be 1/3 smaller allowing our need for warehousing space to be reduced by 1/3. This would allow us to sublet this space for an estimated $2 million dollars a year in revenue. Most of the work of this project would be outsourced. Project Tableware In order to become the provider of choice for the cruise industry, our company needs to expand to more than just linens. A suggestion was made to expand into supplying tableware to the cruise industry, as much tableware is lost every cruise to breakage. Currently this need is supplied by a number of smaller companies that we could easily compete with. This project would involve creating a Just In Time process to receive and supply the cruise ships. It would also involve the need for a minimal warehouse facility. This project is likely to cost $5.5 million dollars and have a NPV of $1 million dollars over five years. All initial costs can be spread over any two quarters of the upcoming year. It would likely take four years to recover the initial costs of this project. It would further cost approximately $300,000 dollars a year to operate this facility. All of the work of this project would be outsourced. Your Assignment Your task is to use your portfolio process to determine which of the above projects best fit into your portfolio and create a time based plan by quarters as to when each project selected should begin and be paid for. Once this is accomplished, you need to write an internal memo to your Vice President denoting the projects selected, the time based plan in quarters, and why you chose as you did. The document should be double-spaced, 10 or 12 point font with one inch margins. This is a Recommendation Memo for an executive, so be concise and to the point. If you don’t need more than eight pages to document your plan adequately, I am sure that your manager will be happy with it as long as it is complete. The use of appropriate grammar, spelling, punctuation, and sentence structure is part of your grade. Submit This Document to the Dropbox by the end of Week 5.