Reply to this student post Coursework Example | Topics and Well Written Essays - 250 words

Reply to this student post - Coursework Example cked by the current healthcares systems considering the efforts she made in trying to make healthcare accessible and affordable to all without biasness. I agree with this statement. The current healthcare system is wanting and only takes care of the interests of financially capable in the society. That notwithstanding, not many can afford health insurance and therefore resort to seeking services at hospital in the event that they need medical assistance. As indicated in the post, Wald managed to create a relationship between public heath care nursing and healthcares insurance. I particularly agree with the fact that this move led to reduced hospital visits and if the same scheme would be implemented today, hospital visits would certainly be reduced as well. This initiative would go a long way in transforming the current healthcare system that is marred with prejudices. However, I fail to agree with the fact that patients need to be educated to ensure their compliance with their care plans. Mush more needs to be done apart from education alone. It would be needless to educate the patients if the healthcare system itself does not have the goodwill to give the patients a chance to be compliant with their care plans and meet their healthcare

Cloning Brachyury from SW480 in pNEB193 plasmid Essay - 3

Cloning Brachyury from SW480 in pNEB193 plasmid - Essay Example igure 2: The total RNA was extracted from SW480 cells by use of Norgen’s Total RNA Purification Kit, the samples were then denatured in rapid Formalin – free RNA loading buffer which had Formalin – Free RNA dye. They were then incubated for 5 minutes at a temperature of 700C. Lane number one was filled with RNA ladder 5 ÃŽ ¼L. The lanes from number 2 to 20 contained 10 ÃŽ ¼L of each of the class samples. The image capture was then done using GelDocEZ system. 3-Table 1: The concentration and purity of the total extracted RNA from the SW480 cells for the sample H was is shown in table 1. The resulting concentration of RNA was 82.88 ng/ul. An RQI of 7.3 indicated that the RNA quality was accepted. The ratio (28S/18S) was 0.93 though the recommended ratio is 2 The plasmid preparation experiment was undertaken before the start of the RNA extraction. The purpose of this experiment was to purify enough linearized phosphatise treated pNEB183 plasmid to be utilised in the ligation reaction. This purification was attained through several steps that started with the purification of the inoculated plasmid from E.coli culture in LB/ampilicin broth. Using Qubit analysis, the concentration of the purified plasmid was calculated to be 5.1 ul. The EcoR1 enzyme was then utilised to digest the circular plasmid into a linear plasmid which was then treated using alkaline phosphatise enzyme to remove the 5’ phosphate group and hinder self – ligation. The sample was then loaded on 0.8% agarose gel so as to visualize and purify the linearized plasmid from the gel by use of purification method as shown in figure 5: In figure 5, two bands were clearly seen in the second lane. The first band was an uncut plasmid. The second band was a linear plasmid. Adequate preparation took place as the linear plasmid could migrate longer on the gel. The second band was bright and shiny. It was 2797 bps in length. It also contained ...ul/mg concentration of plasmid. Using x tracta Gel Extraction

Information Retrieval from Large Databases: Pattern Mining

Information Retrieval from Large Databases: Pattern Mining Efficient Information Retrieval from Large Databases Using Pattern Mining Kalaivani.T, Muppudathi.M Abstract With the widespread use of databases and explosive growth in their sizes are reason for the attraction of the data mining for retrieving the useful informations. Desktop has been used by tens of millions of people and we have been humbled by its usage and great user feedback. However over the past seven years we have also witnessed some changes in how users store and access their own data, with many moving to web based application. Despite the increasing amount of information available in the internet, storing files in personal computer is a common habit among internet users. The motivation is to develop a local search engine for users to have instant access to their personal information.The quality of extracted features is the key issue to text mining due to the large number of terms, phrases, and noise. Most existing text mining methods are based on term-based approaches which extract terms from a training set for describing relevant information. However, the quality of the extract ed terms in text documents may be not high because of lot of noise in text. For many years, some researchers make use of various phrases that have more semantics than single words to improve the relevance, but many experiments do not support the effective use of phrases since they have low frequency of occurrence, and include many redundant and noise phrases. In this paper, we propose a novel pattern discovery approach for text mining.To evaluate the proposed approach, we adopt the feature extraction method for Information Retrieval (IR). Keywords –Pattern mining, Text mining, Information retrieval, Closed pattern. 1.Introduction In the past decade, for retrieving an information from the large database a significant number of datamining techniques have been presented that includes association rule mining, sequential pattern mining, and closed pattern mining. These methods are used to find out the patterns in a reasonable time frame, but it is difficult to use the discovered pattern in the field of text mining. Text mining is the process of discovering interesting information in the text documents. Information retrieval provide many methods to find the accurate knowledge form the text documents. The most commonly used method for finding the knowledge is the phrase based approaches, but the method have many problems such as phrases have low frequency of occurrence, and there are large number of noisy phrases among them.If the minimum support is decreased then it will create lot of noisy pattern 2.Pattern Classification Method To find the knowledge effectively without the problem of low frequency and misinterpretation a pattern based approach(Pattern classification method) is discovered in this paper. This approach first find out the common character of pattern and evaluates the weight of the terms based on distribution of terms in the discovered pattern. It solves the problem of misinterpretation. The low frequency problem can also be reduced by using the pattern in the negatively trained examples. To discover patterns many algorithms are used such as Apriori algorithm, FP-tree algorithm, but these algorithms does not tell how to use the discovered patterns effectively. The pattern classification method uses closed sequential pattern to deal with large amount of discovered patterns efficiently. It uses the concept of closed pattern in text mining. 2.1 Preprocessing The first step towards handling and analyzing textual data formats in general is to consider the text based information available in free formatted text documents.Real world databases are highly susceptible to noisy, missing, and inconsistent data due to their huge size. These low quality data will lead to low quality mining results. Initially the preprocessing is done with text document while storing the content into desktop systems.Commonly the information would be processed manually by reading thoroughly and then human domain experts would decide whether the information was good or bad (positive or negative). This is expensive in relation to the time and effort required from the domain experts. This method includes two process. 2.1.1 Removing stop words and stem words To begin the automated text classification process the input data needs to be represented in a suitable format for the application of different textual data mining techniques, the first step is to remove the un-necessary information available in the form of stop words.Stop words are words that are deemed irrelevant even though they may appear frequently in the document. These are verbs, conjunctions, disjunctions and pronouns, etc. (e.g. is, am, the, of, an, we, our). These words need to be removed as they are less useful in interpreting the meaning of text. Stemming is defined as the process of conflating the words to their original stem, base or root. Several words are small syntactic variants of each other since they share a common word stem. In this paper simple stemming is applied where words e.g. ‘deliver’, ‘delivering’ and ‘delivered’ are stemmed to ‘deliver’. This method helps to capture whole information carrying term space and also reduces the dimensions of the data which ultimately affects the classification task. There are many algorithms used to implement the stemming method. They are Snowball, Lancaster and the Porter stemmer. Comparing with others Porter stemmer algorithm is an efficient algorithm. It is a simple rule based algorithm that replaces a word by an another. Rules are in the form of (condition)s1->s2 where s1, s2 are words. The replacement can be done in many ways such as, replacing sses by ss, ies by i, replacing past tense and progressive, cleaning up, replac ing y by i, etc. 2.1.2 Weight Calculation The weight of the each term is calculated by multiplying the term frequency and inverse document frequency. Term frequency find the occurrence of the individual terms and counts. Inverse document frequency is a measure of whether a term is common or rare across all documents. Term Frequency: Tf(t,d)=0.5+0.5*f(t,d)/max{f(w,d):wbelongs to d} Where d represents single document and t represents the terms Inverse Document Frequency: IDF(t,D)= log(Total no of doc./No of doc. Containing the term) Where D represents the total number of documents Weight: Wt=Tf*IDF 2.2 Clustering Cluster is a collection of data objects. Similar to one another within the same cluster. Cluster analysis will find similarities between data according to the characteristics found in the data and grouping similar data objects into clusters.Clustering is defined as a process of grouping data or information into groups of similar types using some physical or quantitative measures. It is an unsupervised learning. Cluster analysis used in many applications such as, pattern recognition, data analysis and web for information discovery. Cluster analysis support many types of data like, Data matrix, Interval scaled variables, Nominal variables, Binary variables and variables of mixed types. There are many methods used for clustering. The methods are partitioning methods, hierarchical methods, density based methods, grid based methods and model based methods. In this paper partitioning method is proposed for clustering. 2.2.1 Partitioning methods This method classifies the data into k-groups, which together satisfy the following requirements: (1) each group must contain at least one object, (2) each object must belong to exactly one group. Given a database of n objects, a partitioning method constructs k partitions of the data, where each partition represents a cluster and k 2.2.2 K-means algorithm K-means is one of the simplest unsupervised learning algorithms. It takes the input parameter, k, and partitions a set of n objects into k-clusters so that the resulting intra cluster similarity is high but the inter cluster similarity is low. It is centroid based technique. Cluster similarity is measured in regard to the mean value of the objects in a cluster, which can be viewed as the clusters centroid. Input:k: the number of clusters, D: a data set containing n objects. Output: A set of k clusters. Methods: Select an initial partition with k clusters containing randomly chosen samples, and compute the centroids of the clusters. Generate a new partition by assigning each sample to the closest cluster center. Compute new cluster centers as the centroids of the cluster. Repeat steps 2 and 3 until an optimum value of the criterion function is found or until the cluster membership stabilizes. This algorithm faster than hierarchical clustering. But it is not suitable to discover clusters with non-convex shapes. Fig.1. K-Means Clustering 2.3 Classification It predicts categorical class labels and classifies the data based on the training set and the values in classifying the attribute and uses it in classifying the new data. Data classification is a two step process (1) learning, (2) classification. Learning can be classified into two types supervised and unsupervised learning. The accuracy of a classifier refers to the ability of a given classifier to correctly predict the class label of new or previously unseen data. There are many classification methods are available such as, K-nearest neighbor, Genetic algorithm, Rough Set Approach, and Fuzzy Set approaches.The classification technique measures the nearing occurrence. It assumes the training set includes not only the data in the set but also the desired classification for each item. The classification is done through training samples, where the entire training set includes not only the data in the set, but also the desired classification for each item. The Proposed approaches find the minimum distance from the new or incoming instance to the training samples. On the basis of finding the minimum distance only the closest entries in the training set are considered and thenew item is placed into the classwhich contains the most items of the K. Here classify thesimilarity text documents and file indexing is performed to retrieve the file in effective manner. 3. Result and Discussion The input file is given and initial preprocessing is done with that file. To find the match with any other training sample inverse document frequency is calculated. To find the similarities between documents clustering is performed.Then classification is performed to find the input matches with any of the clusters. If it matches the particular cluster file will be listed.Theclassification techniques classify the various file formats and the report is generated as percentage of files available. The graphical representation shows the clear representation of files available in various formats. This method uses least amount of patterns for concept learning compare to other methods such as, Rocchio, Prob, nGram , the concept based models and the most BM25 and SVM models. The proposed model is achieved the high performance and it determined the relevant information what users want. This method reduces the side effects of noisy patterns because the term weight is not only based on term spac e but it also based on patterns. The proper usage of discovered patterns is used to overcome the misinterpretation problem and provide a feasible solution to effectively exploit the vast amount of patterns generated by data mining algorithms. 4. Conclusion Storing huge amount of files in personal computers is a common habit among internet users, which is essentially justified for the following reasons, 1) The information will not always permanent 2) The retrieval of information differs based on the different query search 3) Location same sites for retrieving information is difficult to remember 4) Obtaining information is not always immediate. But these habits have many drawbacks. It is difficult to find when the data is required.In the Internet, the use of searching techniques is now widespread, but in terms of personal computers, the tools are quite limited. The normal â€Å"Search or â€Å"Find† options take several hours to produce the search result. It acquires more time to predict the desire result where the time consumption is high.The proposed system provides accurate result comparing to normal search.All files are indexed and clustered using the efficient k means techniques so the information retrieved in efficient manner. The best and advanced clustering gadget provides optimized time results.Downtime and power consumption is reduced. 5.References [1]K. Aas and L. Eikvil, ‘’Text Categorization: A Survey,’’ Technical Report NR 941, Norwegian Computing Centre, 1999. [2] R. Agarwal and R.Srikanth, ‘’Fast Algorithm for Mining Association Rules in Large Databases, ‘’ Proc. 20th Int’l Conf. Very Large Data Bases(VLDB’94), pp.478-499, 1994. [3] H. Ahonen, O. Heinonen, M. Klemettinen, and A.I. Verkamo, â€Å"Applying Data Mining Techniques for Descriptive Phrase Extraction in Digital Document Collections,† Proc. IEEE Int’l Forum on Research and Technology Advances in Digital Libraries (ADL ’98), pp. 2-11, 1998. [4] R. Baeza-Yates and B. Ribeiro-Neto, Modern Information Retrieval. Addison Wesley, 1999. [5] N. Cancedda, N. Cesa-Bianchi, A. Conconi, and C. Gentile, â€Å"Kernel Methods for Document Filtering,† TREC, trec.nist.gov/ pubs/trec11/papers/kermit.ps.gz, 2002. [6] N. Cancedda, E. Gaussier, C. Goutte, and J.-M. Renders, â€Å"Word- Sequence Kernels,† J. Machine Learning Research, vol. 3, pp. 1059- 1082, 2003. [7] M.F. Caropreso, S. Matwin, and F. Sebastiani, â€Å"Statistical Phrases in Automated Text Categorization,† Technical Report IEI-B4-07- 2000, Instituto di Elaborazionedell’Informazione, 2000. [8] C. Cortes and V. Vapnik, â€Å"Support-Vector Networks,† Machine Learning, vol. 20, no. 3, pp. 273-297, 1995. [9] S.T. Dumais, â€Å"Improving the Retrieval of Information from External Sources,† Behavior Research Methods, Instruments, and Computers, vol. 23, no. 2, pp. 229-236, 1991. [10] J. Han and K.C.-C. Chang, â€Å"Data Mining for Web Intelligence,† Computer, vol. 35, no. 11, pp. 64-70, Nov. 2002. [11] J. Han, J. Pei, and Y. Yin, â€Å"Mining Frequent Patterns without Candidate Generation,† Proc. ACM SIGMOD Int’l Conf. Management of Data (SIGMOD ’00), pp. 1-12, 2000. [12] Y. Huang and S. Lin, â€Å"Mining Sequential Patterns Using Graph Search Techniques,† Proc. 27th Ann. Int’l Computer Software and Applications Conf., pp. 4-9, 2003. [13] N. Jindal and B. Liu, â€Å"Identifying Comparative Sentences in Text Documents,† Proc. 29th Ann. Int’l ACM SIGIR Conf. Research and Development in Information Retrieval (SIGIR ’06), pp. 244-251, 2006. [14] T. Joachims, â€Å"A Probabilistic Analysis of the Rocchio Algorithm with tfidf for Text Categorization,† Proc. 14th Int’l Conf. Machine Learning (ICML ’97), pp. 143-151, 1997. [15] T. Joachims, â€Å"Text Categorization with Support Vector Machines: Learning with Many Relevant Features,† Proc. European Conf. Machine Learning (ICML ’98),, pp. 137-142, 1998. [16] T. Joachims, â€Å"Transductive Inference for Text Classification Using Support Vector Machines,† Proc. 16th Int’l Conf. Machine Learning (ICML ’99), pp. 200-209, 1999. [17] W. Lam, M.E. Ruiz, and P. Srinivasan, â€Å"Automatic Text Categorization and Its Application to Text Retrieval,† IEEE Trans. Knowledge and Data Eng., vol. 11, no. 6, pp. 865-879, Nov./Dec. 1999. [18] D.D. Lewis, â€Å"An Evaluation of Phrasal and Clustered Representations on a Text Categorization Task,† Proc. 15th Ann. Int’l ACM SIGIR Conf. Research and Development in Information Retrieval (SIGIR ’92), pp. 37-50, 1992. [19] D.D. Lewis, â€Å"Feature Selection and Feature Extraction for Text Categorization,† Proc. Workshop Speech and Natural Language, pp. 212-217, 1992. [20] D.D. Lewis, â€Å"Evaluating and Optimizing Automous Text Classification Systems,† Proc. 18th Ann. Int’l ACM SIGIR Conf. Research and Development in Information Retrieval (SIGIR ’95), pp. 246-254, 1995. [21] G. Salton and C. Buckley, â€Å"Term-Weighting Approaches in Automatic Text Retrieval,† Information Processing and Management: An Int’l J., vol. 24, no. 5, pp. 513-523, 1988. [22] F. Sebastiani, â€Å"Machine Learning in Automated Text Categorization,† ACM Computing Surveys, vol. 34, no. 1, pp. 1-47, 2002. [23] Y. Yang, â€Å"An Evaluation of Statistical Approaches to Text Categorization,† Information Retrieval, vol. 1, pp. 69-90, 1999. [24] Y. Yang and X. Liu, â€Å"A Re-Examination of Text Categorization Methods,† Proc. 22nd Ann. Int’l ACM SIGIR Conf. Research and Development in Information Retrieval (SIGIR ’99), pp. 42-49, 1999. : .

Essay --

Chapter Four: Related work there are several work and study on text category with Arabic text and every work take the study from some points and leave others depend on type of study. in [68] make classification for Arabic text and the result was that very robust and reliable without morphological analysis, in [71] make comparative study using N-Gram and using two measures, Manhattan measure and Dice’s measure and make comparison between them and the result was the N-Gram with Dice's measure better than using Manhattan measure and make experimental on four category, in other [83] Text Classification from Labeled and Unlabeled Documents using EM, Been proposed Algorithm used expectation - maximization with the naive Bayes classifier to learn from the documents labeled and non-labeled, The first step classifier using trains and documents named, and labels potentially Unnamed documents. And then trained on the new classifier using the labels for all the documents, and is repeated to convergence. many rese arches are proposed and presented for the problem of the Arabic text classification In this section we mention the main algorithms of these studies such as: Decision tree [36], KNN [37,38,39,40], NB [17,41,42], N-Gram frequency [5,45],Rocchio [4], SVM [19,21,43], and distance based classifier [ 46,47,48]. †¢ Syiam et. al. [40] presented an intelligent Arabic text categorization system that used the KNN and Rocchio profile-based [50] classifiers to classify a set of Arabic text documents collected from three Egyptians news paper called Al Ahram, Al Gomhoria, and Al Akhbar during the period from August 1998 to September 2004. the corpus contains 1132 documents with 39468 words and cover six topics. Three approaches were adopted as pre... ... Agency website. The corpus contain 1562 documents of different lengths belongs to six categories. The documents were normalized and preprocessed by removing digits, foreign words, punctuation marks, and stop-words. The Chi square method was used for feature selection with various numbers of words ranging from 10 to 1000. The corpus was spied such as 70% of the documents were used for training the classifier while the remaining 30% of documents were used for testing. Three evaluation measures precision, recall, and F-measure were used to evaluate the performance of the NB classifier. Results showed that the NB classifier work well when the number of words grows. The NB classifier reach its peak for precision and F-measure when the number of selected words equal 800 words, while the peak for the recall measure was when the number of selected words equal to 700 words.

Communication Unit Essay

To build relationships – by smiling, waving or simply saying hello when building a relationship with a new child, new member of staff or new parents settling into our setting. †¢Maintaining relationships – by simply saying hello or goodbye to people and children in our setting is maintaining a relationship which involves a lot of our language and communication use. To gain and share information – which helps us in the way we work. Information we gain and share not only comes from the children but from the parents, families, colleagues and other professionals. †¢To gain reassurance and acknowledgement – by giving children praise, physical reassurance, making eye contact or showing interest in what activity they are doing as well as providing colleagues with reassurance and acknowledgment in sharing new ideas and information. To express needs and feelings – this includes colleagues, parents and children as we need to be able to express our n eeds and feelings in order for needs to be met and for the effective running of the setting. †¢To share ideas and thoughts – this includes colleagues, parents and children such as creative ideas and thoughts. (A. C 2) It is important to establish good relationships with children, parent, colleagues and other professionals to ensure the effective running of our setting which allows for us to plan and meet their individual needs. Those with good communication skills such as body language, facial expressions and ways in which others listen and talk to you, will have strong relationships with parents, colleagues, children and other professionals. Some ways that communication affects relationships are: †¢Sharing and gaining information – as we need to be able to share and gain information to help the effective running of the setting which may include information on how the child is feeling, what interests them, any information to do with their health and welfare such as any allergies, or conditions i. . asthma, learning needs i. e. referrals to speech and language therapist. †¢Settling in – as children would feel uncomfortable settling in until they are comfortable with us which means that finding ways to communicate with the child is important to start building a relationship with them which will help settle them. It is not only the child who may find it hard but their parents also so it is important to find ways to communicate with the parents to build a relationship where they have total confidence and trust in us to care for their child. Supporting children’s play and learning – this depends on the quality of the relationship between adult and child as children play and learn more effectively when they are relaxed and comfortable with those around them. They will also benefit from playing and learning activities with adults through good communication which can allow adults to help them learn new vocabulary, develop different concepts and express ideas. †¢As children get older they will move between different setting s s uch as from day nursery to nursery school which means they will be around different carers during a day. This can be made easier if all adults involved share a good relationship which allows them to communicate easily. †¢Effective teams – as we often work with other professionals it is important for us to work well together and build strong professional relationships as the quality of relationships with other professionals can be enhanced or threatened depending on how we speak to them, react to their ideas or suggestions and the tone in which we speak to them. It is important to have a good relationship as if the relationship has broken down then the quality of service for children and their families is likely to be less effective. Outcome 2: Be able to meet the communication and language needs, wishes and preferences of individuals (A. C 1) This will be seen in observation. (A. C 2) There are a number of factors that early years workers need to consider in promoting effective communication with others as it is essential to consider different communication methods which are the right communication style, although most of our communication is based on face to face interactions there are certain factors we need to consider when using this communication style such as: Environment which is important to think about the location as in a busy and loud environment it is hard to communicate and have a conversation such as for parents and young people we may choose a quiet place whereas with toddlers and young children we need to provide a welcoming and friendly place. Proximity, orientation and posture which helps us to be sensitive towards other peoples needs such as children who we may have a strong positive relationship with may feel better having us close to them but with children who we do not know this might scare or push them away which also requires us o be observe when communicating. Also how to position your body when communicating as to not be so direct when standing right in front of a child or adult as this makes it uneasy to break eye contact which could make the encounter uncomfortable where standing at a slight angle allows it to be less direct and at ease to break off eye contact, although it is not only how you position your body but o n posture also whether standing or sitting as you do not want to seem bored by maybe being slouched down. It is important to think about what signals we give out. Listening skills which is also known as active listening which requires not only listening but observing body language, gestures, facial expressions and other signals that are being sent out by the child or adult. By giving your full attention to the other person is not just listening to what they are saying but on how they say it which is important when encouraging young children’s speech and dealing with parents. Time it is important to not rush communication as children and adults need time to think of how to respond and what they would like to communicate in conversation. A. C 3) This will be seen in observation. (A. C 4) This will be seen in observation. Outcome 3: Be able to overcome barriers to communication (A. C 1) Communication is based on sharing and is important to remember when promoting effective communication is that not everyone shares the same views and experiences such as childhoods, culture, family background or linguistic knowledge. Therefore we can not be sure that our own personal styles of communication will be effective. A number of factors that can affect people’s communication are: Culture and family background affects the way in which people communicate as in some cultures eye contact is interpreted differently and is not essential in the way they communicate as well as family background as each family is different and share their own ways of communicating together such as children who hear bad language at home and repeat it not realising or a child who hears more than one language at home. Some children may come from a loud and confident family whereas another may come from a shy and timid family which affects the way they communicate in childhood and in adulthood. Personality can affect the way in which children and adults communicate as early on we can see children who are more daring and outgoing yet they may not have developed language. Identifying and observing a person’s personality is important to communication as a child or adult may seem not interested or bored where it is actually they do not like to speak in groups or to people they do not know. Literacy which involves reading and writing as some may have developed these to a higher level whereas others may find them difficult for different reasons such as learning difficulties or language barriers. ICT knowledge which involves sending and receiving emails, having internet phone conversations or accessing and uploading photos or video clips. Although some people may share them same difficulties they may have with literacy and may or may not prefer this type. Confidence and self-esteem are the main factors in the kinds and styles in which people communicate which could lead on from previous experiences they have encountered such as a child was made fun of because they said or spelt a word wrong so in later life they avoid spelling and writing, where a child who listens may become a confident adult who will share their opinions and views. A. C 2) Some potential barriers to effective communication are: Information the sender may want to send but have language difficulties and is unable to express themselves in spoken or written forms. They may also not understand others needs. ( Encoding as the sender may send out an inappropriate method of communication such as a written formal le tter rather than a verbal conversation. The sender could also may have difficulty in choosing appropriate words or use an inappropriate tone of voice. The sender may write illegibly or have language difficulties and are unable to express themselves. ( Transfer such as emails may not be received, post may go missing, background noise may interfere, verbal or written messages sent through children may not come across fully, voice mail may not be listened to by recipient or verbal messages sent by an adult may not come across fully. ( Reception as people suffer from hearing difficulties they may not realise that the communication was meant for them or a person with a visual impairment may not be able to see facial expressions. Gestures or written messages clearly. ( Decoding the recipient may not understand or hear the message correctly because of language difficulties, may not have the time or experience to fully understand the intended message, their past experiences influence how they receive and interpret messages, the relationship between sender and recipient may influence communication whether the sender is someone the recipient does not know or the recipient may be distracted and not listen fully to the message. ( Feedback may not be seen which means the sender may not realise that there are difficulties in their method of communication, they may not show any facial expressions or may interpret the recipient reaction wrong. ( Response may not be sent back and the message has not been received or fully understood or the sender may respond negatively as method of communication is misunderstood or unclear. (A. C 3) This will be seen in observation. (A. C 4) This will be seen in observation. (A. C 5) There will be a time when extra support may be needed to share effective communication with a child or adult and to meet their needs which include: Speech and Language Services which we may need the support of such as speech and language therapists who help us find was of communicating with children and young people. They would also provide us with support, guidance and suggestions of resources we can use to help aid us in communicating with children and young people such as the picture exchange communication system (PECS) or provide training in visual systems like makaton. Speech and language therapists work closely with infants, children and adults who have various levels of speech, language and communication problems. They would also work with people who have swallowing difficulties. They would assess the clients needs before developing individual treatment programmes which would enable the client to improve as much as possible involving families, carers and teachers. Speech and language therapists usually work as part of a multidisciplinary team with other health professionals such as doctors, occupational therapists, psychologists and physiotherapists and may also liaise with professionals in education and social services. Speech and language therapists job responsibilities include: †¢ identifying children’s development †¢ Identifying their speech and communication difficulties/disorders †¢ Assess and treat swallowing and communication difficulties caused by congenital problems like cleft palate or acquired disorders from a stroke or injury †¢ Devise, implement and revise treatment programmes †¢ Monitor and evaluating clients progress Advocacy Services as part of the united nations convention on the rights of the child we are obliged to share information with children and young people on matters that are important to them. The child would then be assigned an advocate who’s job role is to put forward the child’s best interests and to relay to others the feelings and needs of the child or young person. Advocates are particularly essential for children and young people who are in local authority care or for children and young people with communication difficulties. One type of children’s advocate represents or gives voice to an individual or group whose concerns and interests are not being heard. A child advocate will try to prevent children from being harmed and may try to obtain justice for those who have already been injured in some way. A child advocate may also seek to ensure that children have access to positive influences or services which will benefit their lives such as education, child care and proper parenting. Another form of child advocacy happens at the policy level and aims at changing the policies of governments or even trans national policies. These advocates do lobbying, policy research, file lawsuits and engage in other types of policy change techniques. Outcome 4: Be able to apply principles and practices relating to confidentiality (A. C 1) Confidentiality is data protection and is about respecting people‘s right to privacy and keeping information safe which they have provided and not share with other people or pass on personal information about the families and children you are working with, except when it is in a child’s best interest to do so e. g. here are concerns about a child’s welfare as they are showing signs of abuse so I would approach my boss or manager about it but not discuss it with anyone else unless it concerns them or if a parent has asked for the contact details of another child’s family where I could not give that information as I do not have consent to give it out nor do I have access to such information. Otherwise as a main rule it is essential to consider all gained inf ormation as confidential. Most settings have a confidentiality policy to help ensure that this applied which all employees MUST read and apply to their work. Congeniality is very important when working with children and young people that there is a legislation that covers all the stored information. That legislation is Data Protection Act 1998. The Data Protection Act 1998 covers both electronic records and paper based records. It strictly regulates the keeping of records, passing of information and the storing of data. The act was created to protect people’s confidential and personal information from being shared without consent. Any work settings that collect and store information about children, young people and their families must register with the Data Protection Commission and anyone who has access to any of the information must follow the acts principles. All information stored must also be up to date and access secured. (A. C 2) This will be seen in observation. (A. C 3) When working in early years settings parent and children have a right to confidentiality although there may be some times when the need to maintain confidentiality will be breached if disclosing concerns such as if there are concerns about a child’s welfare e. g. abuse. Where abuse of a child or young person is suspected all settings should have a designated person/s to deal with child protection issues. If you have concerns that a child is being abused it is our job to disclose this information to the designated person of the setting unless you think by disclosing the information will put the child/young person in further danger which can be very hard to work out so having colleagues to discuss this will help you come to a quick and more accurate conclusion. This can become very difficult if you feel that there is a child or young person abuse issue and the designated person thinks that there isn’t. I think if you have a doubt then it is better to be safe than sorry and maybe monitor the child gathering more information but if the child is in significant danger then report it to the safeguarding board immediately. Parents will have had a copy of the child protection policy which states that information regarding every child will be disclosed if it is deemed that any child is in significant harm or danger which gives us the right to report any kind of abuse to the safeguarding board without the parents, carers or guardians permission. However it is important to follow the right steps whilst reporting a case of abuse or a suspected case, we need to gather the correct information such as if a child or young person discloses information to you do not promise to keep a secret because we will have to disclose the information given and this will make the child think that they cannot trust that person anymore as they trusted you in the first place to disclose the information. Also a main feature of sexual abuse is that the abuser asks the child to keep this a secret between them. Breaching confidentiality is very serious and most settings have a procedure in which you should follow in the case that breaching confidentiality arises. Information should be passed quickly and directly to the person in charge of dealing with such concerns although confidentiality is still upheld so that other staff, parents, etc do not know anything about the concerns UNLESS they do need to know.

EBI Special Order Analysis

This case study focuses on a business opportunity that has recently been offered to the Earth Baby Inc. (EBB). It concerns a business proposal that will increase the company's sales dimensions while also adding integral quality to its value chain through an alliance with a retail discount business, I. E. Great Deal Inc. (GUI).This analysis will take into consideration one or more strategic measures that should perhaps be taken by EBB in order to assist in identifying and mainlining risk and in order to insure that the proposed business agreement is in the best interest of the company. Aside from the more familiar decisional strategy which has always proven to be reliably effective, e. G. , a SOOT Analysis, an examination of the possible benefits arising from the use of an available heuristic approach that utilizes-foresight and hindsight Judgment parameters'-will be discussed.Keywords: EBB, GUI, SOOT, availability heuristic, hindsight bias, foresight knowledge The proposed opportunit y that has presented itself to EBB entails increasing the company's market share of baby food products through Geld's distribution chain and there resources. The proposed venture will offer EBB an increased profit percentage only if the company agrees to alter its current food processing formulas as well as turn-over a substantial portion of its branding rights to GUI.It is in the best interest of EBB at this time to conduct a comprehensive risk analysis with regards to the changes that will be made concerning the impact upon Bi's new product formula, new business environment and customer base along with branding techniques, marketing strategies and supply chain activities. Risk Analysis Conducting a thorough SOOT analysis would be advisable at first in order to assess Bi's internal strengths and weaknesses and how they will measure up against the- opportunities which may inadvertently turn into threats-with respects to the changes that will occur within Bi's newly adopted business environment.EBB will be challenged to weigh those resources that make up the force behind its competitive advantage(s) because it will be risking the success of its current business strategies against the sum of those changes that will impact it, should the company accept Geld's proposal (Bateman & Snell, 2009). Bi's management might consider backing up the information it garnered from a SOOT analysis with another method that examines the potential of risk involved with regard to opting for a reconfigured or otherwise entirely new and untried business strategy.A method that undertakes the available heuristic approach has been shown to provide business decisions makers with unique way -if optimal results are obtained- of incorporating intuitive Judgment-, referred to as-‘hindsight bias'- and integrating the more positive properties of this mind set with more quantifiable intellectual data referred to as -foresight knowledge'- with respects to formulating new strategies under th e constraints of various risks.This method gauges the two schools of thought by measuring and matching up- and then mapping and mathematically analyzing -the positive relationships between probable outcomes of certain risk factors, as in this case-they may pertain to and/or have- significant bearing on a number of business decisions, their outcomes, and their consequences based primarily upon their -perceived and qualitative'- susceptibility to risks.Conclusion Although at this Juncture, Bi's decision to employ the use of the availability heuristic may seem precarious, however the opportunity to identify and neutralize the risks of he proposal while also discovering some new and innovative strategies does present itself. A safer strategic analysis could be provided through the use of one or more of the conventionally known analytical tools, e. G.SOOT or Porters Five Forces. In any event it would be within Bi's very best interest to thoroughly investigate all the avenues of risks as well as opportunities before making a final decision to accept Geld's business proposal.