Sunday, May 24, 2020
How to Concentrate in Class
A class can get boring and you can get distracted. Your professor is long-winded, your best friend is hilarious, or your cell phone keeps going off. But learning how to concentrate in class is imperative to getting a good grade and actually learning something. Here are some tips for how to concentrate in class when the distractions seem like too much to handle. How to Concentrate on Class 1. Sit Near the Front The front row isnââ¬â¢t just for the nerds. (Although being a nerd is really, reallyà cool because nerds tend to end up ruling the world).à Sitting in the front of the class will automatically help you concentrate because it takes away any distractions (whisperers, texters, coughers, etc.) in front of you. 2. Participate The people who have learned how to concentrate know that they need to participate actively in class. Engage the teacher in conversation. Raise your hand for every question. Start a discussion. The more engaged you are with the lecture, the more you will want to concentrate on it. So, it is a way of fooling yourself into concentrating. Trick yourself into getting interested even if you cant imagine that you could be. Youll surprise yourself by how interested you really are if you give it a shot. . 3. Take Good Notes Get your pen working to keep your mind focused. Many kinesthetic learners are jittery ââ¬â their brain doesnââ¬â¢t connect that they are working when theyââ¬â¢re just listening. If youââ¬â¢re one of those people, and you can find out here if you are, then move your pen and take good notes during the lecture to help you concentrate. 4. Turn Off Your Phone If you really need to concentrate, then turn off your phone completely. No cheating by setting it to vibrate! Nothing will jar your concentration more than getting a text from a friend or a notification from social media during a lecture. 5. Eat a Healthy Breakfast Hunger can be a big distraction. It is tough to concentrate when you would rather be raiding the buffet at the your local restaurant. Grab some brain food before you head to class in order to get rid of a very obvious distraction. 6. Get a Good Nightââ¬â¢s Sleep For maximum concentration, make sure you have slept at least eight hours. I know it can be tough to do, especially in college, but your concentration will be almost gone if you are fighting fatigue. Get some shut-eye so you can pay attention to the things that matter most. 7. Reward Yourself If you really have trouble focusing in class, then reward yourself at the end of class for paying attention. Indulge in your favorite latte, add five bucks to your ââ¬Å"saving for shoesâ⬠account, or even just give yourself mini rewards throughout the class period like a piece of candy or a brief phone check if youve concentrated for fifteen minutes. Give yourself something to work for besides your good grade if that hasnââ¬â¢t been enough of a motivator. 8. Get the Jitters Out If you are an antsy person ââ¬â one of those kinesthetic learners ââ¬â and your teacher is not able to allow you to move in the classroom, then make sure you have gotten your energy out before class. Run laps around the library. Take the stairs everywhere you go. Ride your bike to class. Use some of your energy beforehand, so you can concentrate during your class period. 9. Change It Up If you can feel your ability to concentrate starting to slip, then change something. Get a new pen from your bag. Cross your other leg. Stretch. Tense and flex your muscles. Take a moment to give yourself a brief break from the monotony. Youââ¬â¢ll be surprised how well this works to get you back on track.
Wednesday, May 13, 2020
Anatomical Directional Terms and Body Planes
Anatomical directional terms are like the directions on a compass rose of a map. Like the directions, North, South, East and West, they can be used to describe the locations of structures in relation to other structures or locations in the body. This is particularly useful when studying anatomy as it provides a common method of communication that helps to avoid confusion when identifying structures. Also as with a compass rose, each directional term often has a counterpart with converse or opposite meaning. These terms are very useful when describing the locations of structures to be studied in dissections. Anatomical directional terms can also be applied to the planes of the body. Body planes are used to describe specific sections or regions of the body. Below are examples of some commonly used anatomical directional terms and planes of the body. Anatomical Directional Terms Anterior: In front of, frontPosterior: After, behind, following, toward the rearDistal: Away from, farther from the originProximal: Near, closer to the originDorsal: Near the upper surface, toward the backVentral: Toward the bottom, toward the bellySuperior: Above, overInferior: Below, underLateral: Toward the side, away from the mid-lineMedial: Toward the mid-line, middle, away from the sideRostral: Toward the frontCaudal: Toward the back, toward the tailBilateral: Involving both sides of the bodyUnilateral: Involving one side of the bodyIpsilateral: On the same side of the bodyContralateral: On opposite sides of the bodyParietal: Relating to a body cavity wallVisceral: Relating to organs within body cavitiesAxial: Around a central axisIntermediate: Between two structures Anatomical Body Planes Imagine a person standing in an upright position. Now imagine dissecting this person with imaginary vertical and horizontal planes. This is the best way to describe anatomical planes. Anatomical planes can be used to describe any body part or an entire body. (View a detailed body plane image.) Lateral Plane or Sagittal Plane: Imagine a vertical plane that runs through your body from front to back or back to front. This plane divides the body into right and left regions. Median or Midsagittal Plane: Sagittal plane that divides the body into equal right and left regions.Parasagittal Plane: Sagittal plane that divides the body into unequal right and left regions. Frontal Plane or Coronal Plane: Imagine a vertical plane that runs through the center of your body from side to side. This plane divides the body into front (anterior) and back (posterior) regions. Transverse Plane: Imagine a horizontal plane that runs through the midsection of your body. This plane divides the body into upper (superior) and lower (inferior) regions. Anatomical Terms: Examples Some anatomical structures contain anatomical terms in their names that help identify their position in relation to other body structures or divisions within the same structure. Some examples include the anterior and posterior pituitary, superior and inferior venae cavae, the median cerebral artery, and the axial skeleton. Affixes (word parts that are attached to base words) are also useful in describing the position of anatomical structures. These prefixes and suffixes give us hints about the locations of body structures. For example, the prefix (para-) means near or within. The parathyroid glands are located on the posterior side of the thyroid. The prefix epi- means upper or outermost. The epidermis is the outermost skin layer. The prefix (ad-) means near, next to, or toward. The adrenal glands are located atop the kidneys. Anatomical Terms: Resources Understanding anatomical directional terms and body planes will make it easier to study anatomy. It will help you to be able to visualize positional and spatial locations of structures and navigate directionally from one area to another. Another strategy that can be employed to help you visualize anatomical structures and their positions is to use study aids such as anatomy coloring books and flashcards. It may seem a bit juvenile, but coloring books and review cards actually help you to visually comprehend the information.
Wednesday, May 6, 2020
Does Things Change in Poor Area of China Free Essays
Does things change in poor areas? When I was young ,my mother often told me itââ¬â¢s very bitter for them to go to school, they had to get up very early in the morning,then prepared for their brakefast by themselves and did some housework . they couldnââ¬â¢t leave until they finished all of that. They even couldnââ¬â¢t have lunch because proverty. We will write a custom essay sample on Does Things Change in Poor Area of China or any similar topic only for you Order Now But now ,things about education has changed. Student can get a better care. Now government pay more attention to education,especially in poor areas. Our country has done a lot to improve the education in our country. And they had realized the importance of education for the development of a country since the setting of our country. But they couldnââ¬â¢t do much to poor areas. But now ,with the development of economy, we have enough money to pay for fees for education. Everything has changed in poor areas. Carations from the government push the process of education development in poor areas. Government can support these areas with enough money and good teachers. As a result ,children in poor areas can get the same education resourses as others in rich places. From china daily ,children in guizhou now can get free lunch and beautiful classroom because the aid. Whatââ¬â¢s more, their family donââ¬â¢t need to care about the payments. In this way ,more children can get the opportunity to know more about the world. In fect, there are so many photographers who care about poor areas. They use their camara to tell people what is going on in poor areas, and try to tell the government. Yes , government can help poor place, but they donââ¬â¢t have enough information. These special people just contribute themselves to the development of poor areas. They even organize activities to collect money for the education of poor places. Most of them will spend most of their time to do that. Thanks to them ,these places canââ¬â¢t perfect their education fast without them. Thanks to the government and people who contribute themselves to education of poor areas, now children can get more opportuties to get formillar with the world. And things have changed to the good side. New word; Principal : main, or most important poverty-stricken : extremely poor malnourished: weak or sick because you do not eat enough or do not eat enough of the right foods poverty: a lack of something, especially ideas or feelings allowance: an amount of something that you are officially allowed by a particular set of rules or by the law; a tax exemption administration : the government of a country; the activity of governing a country or region; a department of the U. S. overnment launched : to start a major activity such as a military attack, a public investigation, or a new career or project; to start selling a new product or service to the public remote : far away from other cities, towns, or people; far away in distance or space; far away in the past or future rural: relating to parts of a country that are not near cities and where the population is low; typical of the countryside Sentence The central government launched a program in October that aims to improve nutrition for rural students in poor areas. When it was introduced, Xinglong school would receive packed bread and milk from the Dafang county education administration every day, but it did not work out, After raising the problem with the education administration, the school was allowed to provide hot lunches, with a daily allowance of 3 yuan (50 US cents) per child. Although many students are malnourished due to poverty, free school lunches will make them healthier, he added. Unlike many students in urban areas of China, where child obesity is becoming a problem, How to cite Does Things Change in Poor Area of China, Essay examples
Monday, May 4, 2020
Business Growth and Organisation Business Enterprises
Question: Discuss about the Business Growth and Organisation for Business Enterprises. Answer: Introduction: The biggest challenge in the growth of the organization is to manage big data available within the enterprise. To use the techniques of business intelligence, it is worth important to know about the big data management (Richard, 2014). They play a core value in in the growth of the business. With the integration of the process like storage, analysis, and use of application is a driving feature in improving the quality of the products and services offered by the organization. Customer satisfaction can be improved by improving the storing management of big data. The enhancement in the volume of data results into the key management of the big data. The process of business intelligence can be achieved by the combination of operational data and analytical tools used for presenting the complex data to the decision makers and planners. With the proper management of big data, the quality of the product and delivery time offered by the organization can be improved which result into the improv ement in managerial work (Chen, 2011). BI focuses on the strategy development and in the operation of decision making. The use of BI is the strategy development of the organization can be carried out in the following areas such as management of the performance, operational activities between customer and business, development of application for the specific purpose of the organization, collection of reports from the management for the growth of the business, accessing of the data for answering the non-regular question. In this paper, we will focus on the case study of big data analysis by the organization of Tata consultancy. Tata consultancy focuses to provide services to the widely spread organization. They have their share in the market of UK. The organization is associated with the generation of big data related with network operation and services provided to the customer. Identification and development of business strategy: The business strategy can be developed for the organization of Tata consultancy by going through the following phases: Analysis: The solution to the business problem helps in providing the justification of cost and benefits. Key performance indicator plays a key role in the requirement analysis of the Tata consultancy organization. Designing: The solution can be achieved by focusing on the functional deliverables of the project through prototyping. Development: The meta-model should be prepared on the basis of metadata collected on the basis of big data available in the company (Sun, 2014). Deployment: The development of the design schema helps in accessing the requirement of the Tata consultancy organization. Evolution: The success of the application helps to measure the proper management of the big data. From the research, it has been observed that the strategy which is used by the Tata consultancy is to generate maximum amount information, searching through the historical business records, use of big data management helps to provide information with no delay in time, facilitate the process of decision making, report is generated by dividing the organization into different structure and lastly, analysing the data. Data integration is the key step to resolve the problem occurred in the business (Alfawaz, 2011). In case of an emergency, alerts should be generated by doing proper monitoring of the processes. The management of big data results into the automation in the delivery process of information (Rao, 2011). Instant information can be provided to the customer, geography, and the product. Alignment of business objective and Strategy: Business objective Big data volume Big data velocity Big data variety Big data value Objective of having knowledge of the market Data of customer Data of competitor Direct communication between commodity Use of social media Surveys Analysis of the market Availability of demographic data Data used for benchmarking Trends in the data High value should be given to the data Data of customer Data of competitor Objective of having knowledge of human Based on experience Collaboration for data integrity Decision based on real time analysis Based on skills Based on experience Based on tactics knowledge Value given to heuristics Objective of having Procedural knowledge Use of Standards Use of using the standards and others Use of standard for material Volume of field data Use of knowledge for designing Use of material Variety in design Use of CAD / CAE Proper analysis should be done Manufacturing of the product Data used by CAD / CAE Best practices used for collecting the data gathering Test and validation practices used Data used for serving Data used for manufacturing of the process Objective of having technological knowledge Designing of knowledge Analysing Standard of material Verification and validation of the data Safety and security provided to the system Acquisition of real time data Helps in measuring cost Helps in measuring reliability of the system Packaging of the system Use of ergonomics Value given to patents Required Technology Stack: The focus should be given on four different modules which are discussed below: Analysis of Portfolio: These decisions are made by the top level management. The company should focus on customer, product, and supply. Ethical decision should be taken for allocating the resources. Scenario: The transformation of decision should be taken from strategic to tactical. The simulation of What if procedure for maintaining the structure of value chain (Mohamed, 2009). The result of this analysis helps in understanding the threats occurred in the company. Value: It helps in balancing the outcomes which can result into the creation of conflict. The reliability of the company can be improved by focusing on the investment on inventory. The consequence of this phase is to optimize the tactical plan. Situation: The analysis of this phase results into the analysis of action plan and business policy. The model above shows the technological approach for incorporation between structured and unstructured information. Hadoop is a technique which is used for analysing and managing the big data of the enterprise. Investment is the unifying element at syntactical level. The next level in the model is the foundational investment. Data analytics and master data management: Master data management is the mechanism through which standards, processes, governance, tools, and policies can be defined to manage critical data. Mastering of data is the collection of reference model and analytical data. The reference model emphasis on business objects used for transaction. Decision making is the key process of analytical data. The objective of importing MDM within the infrastructure of Tata consultancy services results into the processes like collection, aggregation, consolidation, matching, assuring the quality of the project, and distribution of data throughout the organization. Master data management make use of three processes for transferring the big data. Firstly, consolidation of the data focuses on collecting master data from different sources and integrating into single operational data store. Secondly, federation of the data is used for representing the virtual data to more than on one system. Number of destination can be used for providing virtual data . Lastly, the propagation of data is used for replicating the data from one system to another system. The process of business intelligence can be achieved by the combination of operational data and analytical tools used for presenting the complex data to the decision makers and planners. In the legacy system point to point interface is used. Areas of business where big data is more prominent can be summarised below: Particulars Application Advantage Ecosystem for value Capabilities of the ecosystem Focus should be given on political and economic factors which are responsible for upstream and downstream of processes Ecosystem used for capturing knowledge Data used by the third party New opportunities should be created within the organization of Tata consulting services Mitigation of the risk should be enforced Services and products used by organization New channels should be enforced for creating products and services Process of monetization should be applied on the dataset Big data play a role of core component in the development of products and services Experience should be measured for developing new products Services offered by the Tata consultancy can be enhanced Use of data for the management of portfolio Market association Multiple channels can be enhanced View of the customers should be taken into consideration Market should be fragmented into smaller market At every individual level, process of segmentation should be performed Awareness for the context Advantageous for the user of big data Acquisition, services, retention, marketing, and etc. should be used for managing new customer Organization culture Transformation in the culture of the employees Data should be given importance Knowledge should be pooled Sharing of knowledge should be supported Employees concern should be mitigated Efficiency should be improved Support of NoSQL for Big Data Analytics: In todays era, every organization changes his methodologies to implement NoSQL for handling big data of the organization. The companies like Google, Amazon, Facebook, and etc. has changed their technique from RDBMS to NoSQL. On the basis of market research and other consultation, Tata consultancy services have start making use of NoSQL for handling big data of the enterprise. NoSQL is useful for handling unstructured data processes which are dynamic nature and provide support to cloud based processes. There were some drawbacks in the traditional system like SQL and RDBMS which have been overcome by the implementation of NoSQL within the organization. The evaluation of NoSQL helps in handling the techniques of cloud computing and big data. It is preferred by the organization because the rate of increase in the availability of the data is becoming high. So, the need of managing this big data is also become a necessity for doing planning and control for the organization. The data is not handled by the SQL and RDBMS. Therefore, not only SQL comes into existence. It supports the processing of real data. NoSQl works on the collection of data where due to the large abundance of data, the data is get duplicated. It provides the solution to the two major problem of the organization which are categorised as scalability and the support of simplifying the development process of the organization. The use of NoSQL results into faster and cheaper accessing of the information (Lane, 2007). It requires minimum coding for organization the big data of Tata consultancy services enterprise. The NoSQL database is used by the organization of Tata consultancy because it makes use of big data for the development of the application and the related databases. It provides flexible data model for the architecture of the database which is the basic requirement in handling the big data. For access the big data, continuous application should be available. Hadoop is the base of messaging infra structure which makes use of NoSQL for handling big data (Perkins, 2011). It is used for the generation of data, storage, monitoring, and logging with the proposed system. For the analysing of big data, NoSQL plays a major role in handling data. NoSQL Databases and big data: NoSQL is useful for handling unstructured data processes which are dynamic nature and provide support to cloud based processes. There were some drawbacks in the traditional system like SQL and RDBMS which have been overcome by the implementation of NoSQL within the organization. The two main reason for which data consultancy services makes use of NoSQL for handling big data of the organization is fast accessibility of inserted data and scalability for managing large volumes of data. For operating the workloads of the big data, No SQL database is used for addressing broad sets of applications (Mark, 2011. The use of NoSQL results into faster and cheaper accessing of the information. It requires minimum coding for organization the big data of Tata consultancy services enterprise. The table below shows that NoSQL is efficient in handling operational and analytical data. Particulars Operational Analytical Latency period 1 ms 100 ms 1 min 100 min Concurrency control 1000 100,000 1 10 Pattern of access Write and read function Read function Form of Queries Selective Unselective Scope of data Operational data Retrospective data End user End user are the customer End user are the data scientist Technology used NoSQl Map reduce technique Role of Social media in the decision making process: The organization makes use of social media in the following cases which are summarised below: In monitoring the working practices of the professionals Accessing the information which cannot be access from other means Deals as a showcase for the organization Helps in the professional development Helps in finding the feedback and reviews on the services provided by the organization Collaboration speed can be increased to a high extent Research can be done to take decision of the business. Cost can be reduced which was being spent on the traditional networking system of the organization Process of decision making can be accelerated by using the peer input Reliability of the information can be improved Travel cost can be reduced Helps in increasing the rate of content sharing Helps in the use of forum Competitive intelligence can be enhanced Working practices of the organization can be improved Member directory helps in giving the details of the member associated with the organization. Replacement of emails can be done by using the social media within the organization Predictive model can be developed Increment in the sale of services Brings cooperation among the employees Becoming the network access point for the professionals Development of trust Helps in taking decision for the welfare of the organization and employees Big Data value creation process: Use case: Tata consultancy focuses to provide services to the widely spread organization. They have their share in the market of UK. The organization is associated with the generation of big data related with network operation and services provided to the customer. Value Creation: With the exploitation of data, 20 % of the revenue can be increased. Internal opportunities of the organization provided 65% of data and 35% can be achieved by external opportunities associated with the organization (Danchev, 2009). The value for the business can be created by focusing on three sources firstly, licensing of data, secondly, data products, and thirdly, offerings provided to data services. Internal value can be improved by network operation External value can be improved by the services provided to other organization Opportunities for substantial revenue play a key role in data analytics Offerings provided to public services Improvements in the quality of service Provides satisfaction to the customer Automated travel analysis mechanism should be used Helps in ensuring the quality of the data Permission platforms should be organized Anonymization should be applied Value of sharing can be improved Partnership can be developed Enhancement in the public and private value Strategy for organizational change Helps in gathering domain knowledge The table below shows the relation between big data and value creation: Quality of data should be ensured Legal data should be promoted Platforms for permission Portals for providing permissions Sharing of value Created value should be shared with the originator of the data Data partnership should be enhanced Partnership should be developed with the third party Public and private value should be created Management of data among the employees and customer Regulation and legislation Changes should be done under the legislation Strategy for corporate analytics Clear articulation of the value should be created Organizational change Organizational change should be promoted with the organizational culture Analytical strategy Articulation of analytical strategy for creating value for the organization Structure of the team The team should be comprised of data analyst and IT specialists. Ethics Ethics should be followed in making use of data for carrying out the business activity Reflection: Particulars Description Data Data related with profile of the customer and demographic location. Generation of data in the interaction on consultant services Tracking of location of the customer Creation of Value Internal value can be improved by network operation External value can be improved by the services provided to other organization Opportunities for substantial revenue plays a key role in data analytics Offerings provided to public services Management of the organization Joint venture can be established with the function of global analytics External projects should be emphasized Management of the network Process Core areas of the network and customer should be summarized by analysing the big data by using the technique of NoSQL External projects should be emphasized IT skills should be developed People Technical skills should be developed among the employees for handling big data and using the techniques which helps in facilitating the handling of big data Problem solving, knowledge of the business, and communication are the pillars of handling big data related with people Technology Makes use of NoSQL Challenges Management of network ad customer is the biggest challenge which come forward in the growth of the organization Proper communication should be carried out for handling the big data of the organization Strategy should be changed according to the change in organizational culture Innovation should be handled by the organization effectively for the betterment of the organization Use of robust data policy Conclusion: In this paper, we will focus on the case study of big data analysis by the organization of Tata consultancy. From the research, it has been noticed that the biggest challenge in the growth of the organization is to manage big data available within the enterprise. To use the techniques of business intelligence, it is worth important to know about the big data management. it has been observed that the strategy which is used by the Tata consultancy is to generate maximum amount information, searching through the historical business records, use of big data management helps to provide information with no delay in time, facilitate the process of decision making, report is generated by dividing the organization into different structure and lastly, analysing the data. In this paper, the focus is also given on the use of master data management by the organization. Master data management is the mechanism through which standards, processes, governance, tools, and policies can be defined to man age critical data. Mastering of data is the collection of reference model and analytical data. The value for the Tata consultancy can be created by focusing on three sources firstly, licensing of data, secondly, data products, and thirdly, offerings provided to data services. References Richard, V. (2014).Creating business value from big data and business analytics. 1st ed. [ebook] Available at: https://www2.hull.ac.uk/hubs/pdf/NEMODE%20big%20data%20scientist%20report%20final.pdf [Accessed 11 Oct. 2016]. Chen, H. (2011).Business intelligence and analytics: From big data to big impact. 1st ed. [ebook] Available at: https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.717.5529rep=rep1type=pdf [Accessed 11 Oct. 2016]. Sun, Z. (2014).Big data analytics as a service for business intelligence. 1st ed. [ebook] Available at: https://www.researchgate.net/publication/282867145_Big_Data_Analytics_as_a_Service_for_Business_Intelligence [Accessed 11 Oct. 2016]. Rao, A. (2011).Big data and business intelligentce. 1st ed. [ebook] Available at: https://www.researchgate.net/publication/282867145_Big_Data_Analytics_as_a_Service_for_Business_Intelligence [Accessed 11 Oct. 2016]. Mohamed, A. (2009).Big data analytics in manufacturing: Driving new level of management productivity. 1st ed. [ebook] Available at: https://eprints.utm.my/36474/1/SCIE-09.pdf [Accessed 11 Oct. 2016]. Alfawaz, M. (2011).An Introduction to NoSQL data management for big data. 1st ed. [ebook] Available at: https://eprints.qut.edu.au/41777/1/Salahuddin_Alfawaz_Thesis.pdf [Accessed 10 Oct. 2016]. Lane, J. (2007).Why NoSql is better for Big Data Management. 1st ed. [ebook] Available at: https://eprints.qut.edu.au/16486/1/Tim_Lane_Thesis.pdf [Accessed 11 Oct. 2016]. Perkins, T. (2015).3Key elements for successfully creating values in big data journey. 1st ed. [ebook] Available at: https://www.lse.ac.uk/intranet/LSEServices/policies/pdfs/school/infSecPol.pdf [Accessed 11 Oct. 2016]. Mark, K. (2011).Four strategy to create value for big data. 1st ed. [ebook] Available at: https://www.cse.dmu.ac.uk/~bstahl/index_html_files/2011_ISS_policies_ISJ.pdf [Accessed 11 Oct. 2016]. Danchev, M. (2009).Understanding the value creation process. 1st ed. [ebook] Available at: https://www.windowsecurity.com/pages/security-policy.pdf [Accessed 11 Oct. 2016].
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