I Am A Rwandan Who Respect Culture And Values Of Rwandans

Concerning my life, I’m a Rwandan who respect culture and values of Rwandans. As a person who is personally responsible for my life, I always do my best to strive for progress and success. Since my childhood, my life was not a very easy one. Consequently, I did not have everything that I needed. Nevertheless, my life’s experience has encouraged me to work hard and take advantage of all opportunities can positively change the course of my live. Being eligible to applying for this scholarship, itself, is a result of my hard work. I am the first born child of my family. I was born in 1994. This is the same year that our country experienced a genocide. My father died when I was three years old. This has negatively impacted my life, because he was the provider of our family. Since then, my mom has had to fill the gap so that we can survive. In addition to that, we lived in a rural area where there was no electricity, and few or no infrastructure at all. In my village, families usually did not send their children to school until they were 10 years old. Back then, no nursery schools were there, we had to start from the first grade of the primary school. My mom would be working at the plantation every day, while I had to stay home alone. At age of five, I had an idea of starting school. One day, after my mom left home, I followed primary school students to school. Arriving at school, they showed me where the first grade class was located and told me to go tell the teacher thatShow MoreRelatedCulture And Identity Of A Refugee Living Essay1613 Words   |  7 PagesIn this paper, I will discuss the importance of culture and identity of a refugee living in Canada, and how her experiences shaped her as a person and her future. I have interviewed a friend and colleague, named Elodie Bambuzuke who was born in Rwanda. 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Financial and Marketing Proposal - 862 Words

Financial and Marketing Proposal John Doe Custom Snowboards Inc. Company History: Founded 1995 by James Rooney and Justin Stringer. Began as a small coat company but quickly expanded into making snowboarding equipment. Mission Statement: Custom Snowboards outfits outdoor enthusiasts with unmatched performance and advanced technology in snowboards and snowboarding equipment. Key competitors: Burton Snowboards, Salomon Snowboards Bonfire Snowboarding. Industry Background Apparel Manufacturing Industry grossed $7.2 Billion, 6% growth - 2008 Company and Industry Background 2007 2006 2005 2004 2003 Net Sales $1,356,039 $1,287,672 $1,555,791 $1,095,307 $951,786 Net Income $144,452 $123,018 $130,736 $138,624 $120,121 Our recommendation is to expand into sports equipment industry by offering a full line of snowboards and snowboard equipment in Europe. Competitive Environment Industry Rivalry: Medium. Products are interchangeable Numerous established competitors Supplier Power: Low. Raw materials (wood) are plentiful, no threat of forward integration. Buyer Power: Low. products sold through many smaller retailers with limited bargaining power. Threat of Entry: Low. High Brand Awareness, economies of scale. Substitutes: Medium. Other extreme sports such as mountain biking, climbing, etc Snow Boarding Equipment Industry Five Force Analysis Sports Equipment Industry Broad Market Narrow MarketShow MoreRelatedMarketing Pl An Organization1658 Words   |  7 PagesWeek 8 Marketing Plan Lacey Davis A marketing plan is a strategic document outlining an organization’s advertising and marketing efforts describing its goals and objectives within a certain time period. **The components and dimensions are important in developing a marketing plan and useful to non-profit and profit organizations. 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Smart Meter for Household Owner and Data - myassignmenthelp

Question: Discuss about theSmart Meter for Household Owner and Data. Answer: Smart meters are the products, designed and developed in the project. The smart meters are preferred by the end users, who are regular users of electricity and energy and so, almost every household in the country would prefer to buy the product. Here, each and every household owner has to provide the basic personal details of him or her and register in the company, before the product is bought. This is the basic data element and apart from that each and every smart meter used by the household owner, generates data, every minute, when it is operated. Here, the individual customers details are considered as the basic or raw data elements. When all the personal details can be integrated with the data of utilization, meter identification number and the corresponding address of the customer and the result can be extracted as important information (Vojdani, 2008). This information can be useful for various uses, both good and bad. The good part is that a meaningful data, such as the overall consumption in an area, in a specific region can be extracted. However, the same data can be extracted for extracting personal data of the customers for various unhealthy practices too. Impact of Data Quality Prroblems Data quality, in the context of the smart meter project refers to the accuracy of the readings. The readings displayed and shown must be accurate, according to the consumption of the energy done, in the respective premises. If this data is not accurate and if the readings show either more or less units of consumption than the amount of energy consumption, actually done, the data quality problems do occur. And these quality problems do either incur the loss to the customer or the business of the company, which produce the smart meters. For Businesses The impact of the data quality problems of the smart meters would have more for the businesses in different ways. For example, if the smart meter shows lesser consumption of energy than the energy consumed actually, by the appliances operated and used by customer, the total billing at the end of the period of month, the customer pays lesser than what he or she has consumed. The business has to lose the difference of payment, between what actually consumed and what is paid. Eventually, the business of the energy supplier incurs the losses. Such data quality problems would always create conflict between the customers and energy Supplier Company. On the other hand, the data quality problem occurs, in terms of showing utility than the actual energy consumption, the customer would be annoyed and may get reluctant to pay. If the difference is small, the customer might not notice and may pay the bill to the energy supplying company. Eventually, the company may get profits, with more payment of bill, for less energy supplied by them. However, this practice may gradually, decrease the levels of trust on the energy supplier company, for charging more for the consumption of the energy or may develop mistrust over the quality of the services of the smart meter company (Tuan, 2009). Other data quality problems, such as database mis-integration would mismatch the name of the customer and the respective bill number. Eventually, customers trust would be declined, resulting in switching to other company of smart meter. In any instance, the business would have serious impact, when the quality of the data displayed and obtained by the smart meter is deteriorated and inaccurate. For Individuals Here, the individuals are the customers, who buy the smart meter and receive the services from the United Energy. The data quality problems reflect directly on these individuals, as they get either less or more energy utility bill than they actually consumed for. The customer feels happy, for lesser bill and gets unhappy and annoyed, when they get more bills (Suriyakala, 2007). In each of the case, the trust on the services of smart meter would decline, undoubtedly. The other kind of data quality problems associated can be the mis-integration of data. The names of the energy consumer and the bill may not match and it may lead to the frustration of the consumer. Eventually, the consumer may withdraw to receive the services from the company of smart meter and may switch to another company, which would also impact the business of the smart meter business. Ethical Issues form Data Quality Problems Privacy The ethical issues from data quality problems are arise from the privacy issues. Apart from the utility companies, certain sections of individuals and people may be interested to steal the data of the end users. These sections of people may include civil litigants, ex-spouses, extortionists, illegal consumers of energy, political leaders having vested interests, terrorists, and thieves for various purposes like the status levels and for their presence at the homes, etc. Individuals are very prone to threats, resulted from the negative uses of their private or personal data. The customers, who are individuals, may get serious security and privacy risks, since their data can be easily transmitted and shared among various parties and business people (Hafner et al., 2006). The usage of the personal data of the individuals can be used in anyways by the other individuals, who are hackers and attackers and business people, where the usage is limited to their imagination. In addition to these concerns, the personal data of teh customer may also be used integrated and extracted as the information, in the way hackers want. The major concern from this aspect is that this data can reveal the information, regarding the presence of the customers, at respective homes and the kind of appliances they have been using in their homes. Eventually, it is very easy for the customers, to get reluctant to share their personal data and buy the smart meter product, which would impact the sale and the overall success of the smart meter project. And if the customers take the connection of the smart meters, they would be reluctant and unwilling to share and communicate their data about energy consumption, along with the data of smart meter of their neighbours. This aspect and concern would impact the choice of parameters for transmission and authentication administration, for accessing such information (Bennet Highfill, 2008). Data Ownership Once the smart meter project gets commenced, each and every piece of data collected from the customers, vendors and any kind of data, except allowed for advertising purpose should be carefully exposed to the world. Each and every piece of the data completely owned by United Energy company, which is the key stakeholder of the company. The company has to follow and abide to the policies set locally and nationally, Australian Communication and Media Authority(Cohen, 2010). So, any of the complaints and concerns regarding the privacy and security of the data must be addressed and accountable by United Energy company. Even if the customer data is hacked or breached, the company would be responsible. If the company sells the customer or any personal data to the third party, the company has to compensate with respective punishment, if such facts are proved by the regulation authority. Responsibilities of Data Quality Problems The data quality problems may be arising from various factors, such as management, organization and technical factors. Management Factors Most usually, data quality problems are occurred because of the management factors. Usually, organizational and technical factors are anticipated most often and the viable and accurate technical methods and organizational procedures are followed (Samarakoon Ekanayaka, 2009). So, the management factors that are responsible for data quality problems, can be, Human error in data entry, retrieval, etc. Changes to source systems Mixed expectations by the customers System errors External data Manual errors, while writing the applications Workforce management Daily workflow Billing systematic Asset management Organization Factors Procedures and methods effective implementation, even when the customer base is increased, unexpectedly Organizational methods that are prone to security and privacy risks of the personal and potential data Choice of parameters offered and employed Data storage, maintenance and management Weaker authentication Design, development, utilization, deployment and maintenance of smart meters Technology Factors Implementation of the technology accurately The degree and levels of testing to ensure the accuracy of the technology implemented Improper infrastructure for new technology synchronization Ways of networking the appliances and devices with smart network, in communication network Deployment of communication network at certain regions and localities, issued from certain terrestrial difficulties Insecured collaborative operations High traffic, and limit over transmission of data, because of low bandwidth Integration of devices for the operation of demodulation, modulation, etc. Transmission of energy consumption data over the networks of public communication Quality of implemented software Weaker protocols Error handling Improper session management Limitation in data capacity, network coverage, propagation issues, etc. Safety and accommodation issues in data concentrators Though there are many technical challenges and factors, the probability of these factors is less, as they are one time set and used (Han Lim, 2010). Project Issues Potential Security Issues During Project There are many issues that should be addressed, arise especially, from the privacy and security effects, related to the smart meters. The smart meters can be exposed to cyber attacks. The solution for such potential security issues can be obtained by the cyber security experts. According to these experts, the smart meters in Germany and UK are well secured with increased cyber security, relatively and attacks to these smart meters need considerably more financial resources and efforts. Recovery Plans Security protocols can be a better solution to the potential security issues of the smart meters, such as protection from new exploits and malicious attacks. However, there are many challenges to such solution, such as long spans of operational life and limited computational resources. There can be certain solutions that the smart meters can be connected through wireless-only, having no control, monitoring or safety features of home energy. For example, kill switch can be one of the solutions, through it works as the final alternative solution. The data recovery is an important aspect for the smart meter, to ensure that the data related to the customers, in terms of their data related to the electricity consumption as well as their individual data would be protected with enough care and recovered, if the data is lost. The security issues can be encountered with the Intrusion Detection System. It can enable verification method, by network traffic analysis in real time, so that any possible anomalies can be detected. Once the exploits that are leveraged by attackers, get identified, the risk of theft of data, by the attackers and can also mitigate the attacks of denial-of-service, by hackers. Better security can be gained by the architecture of centralized IDS, which is also cost effective. The smart meter project can also be effected by the customers, who can manipulate the readings of the utility of their electricity. It is possible, technically that the devices can be reprogrammed by the customers, so that the results shown would be incorrect and benefit the customers, by showing lesser utilities of energy (Lee lai, 2009). Hence, the program written and executed in the smart meters, should be read-only with no option of reprogramming to the end-users or even by the unauthorized programmers. Kind of Information Containing The information containing is the data about the personal information, such as name, address, contact number, profession, etc. The data obtained and collected from the smart meters can make the business to make use of the data and become monopoly, and can become current energy data control. In addition the energy suppliers become monopoly and can start any new clauses for the energy data control, as they contain ongoing and existing communication channels with energy consumers that would be very difficult and expensive to replicate for other organizations. Hence, the framework of data privacy states that consent has to be verified and validated against the matching energy consumer by taking reasonable steps. Then the feedback has to be provided on a regular basis back to the energy consumer, as a feedback. So, obtaining and maintaining consent cost for smart meter data usage is higher, for the companies and organizations that wish to use the data of the smart meters, significantly, in the public interest, such as for benefit of energy suppliers. Key Backup and Recovery Requirements Backup has to be done every end of the day and copy of the updated database has to be maintained by the administrator and the operations manager, every day. Day to day files can also be updated into the Google drives, if the volume is enough and permitted. Recommendations to solve the problems The United Energy Company has to enable the technical, organizational and legal resources so that the standards can be complied, needed for accessing or using the data of the smart meter and maintain the quality of data. The company has to go automate data profiling. The project management has to maek collaboration among the information workers, such as data stewards, business analysis, decision makers, data analysts. The company has to provide data issues view in the context (Tuan, 2009). So, technical data quality has to be set standards and monitoring for the formats, content, structure and integrity. Business data quality has to be standardized and monitored with data domains, business rules, and business context and reference data. References Bennett C. and Highfill, D. 2008. Networking AMI smart meters, in Proc. IEEE Energy 2030 Conference, Atlanta, GA. pp. 1 8 Britton J. 2016. Smart Meter Data and Public Interest Issues: The Sub-National Perspective. Cohen, F. 2010. The smarter grid, IEEE Security Privacy, vol. 8, pp. 60 63. DECC. 2014. DECC Smart Meter Impact Assessment. Deconinck G. and Decroix, B. 2009. Smart metering tariff schemes combined with distributed energy resources, in Proc. Fourth International Conference on Critical Infrastructures, Linkoping, Sweden., pp. 1 8. Hafner, A. Lima, C.R.E. and Lopes, H.S. 2006. An electric energy quality meter using hardware reconfigurable computing, in Proc. IEEE Conference on Industrial Electronics and Applications, Singapore. pp. 1 6. Hafner, A. Lima, C.R.E. and Lopes, H.S. 2006. An electric energy quality meter using hardware reconfigurable computing, in Proc. IEEE Conference on Industrial Electronics and Applications, Singapore. pp. 1 6. Han D.M. and Lim, J.H. 2010. Smart home energy management system using IEEE 802.15.4 and zigbee communication, IEEE Trans. on Consumer Electronics, vol. 56, pp. 1403 1410. Il-Kwon, Y. Nam-Joon, J. and Young-Il, K. 2009. Status of advanced metering infrastructure development in Korea, in Proc. Transmission Distribution Conference Exposition: Asia and Pacific, Seoul, South Korea. pp. 1 3 Lee P.K. and Lai, L.L 2009. Smart metering in micro-grid applications in Proc. IEEE Power Energy Society General Meeting, Calgary, Canada., pp. 1 5 Samarakoon K. and Ekanayake, J. 2009. Demand side primary frequency response support through smart meter control, in Proc. 44th International Universities Power Engineering Conference (UPEC), Glasgow, UK. pp. 1 5. Sang, C.H. Yamazaki, T. and Minsoo, H 2009. Determining location of appliances from multi-hop tree structures of power strip type smart meters, IEEE Transactions on Consumer Electronics, vol. 55, pp. 2314 2322. Suriyakala C.D. and Sankaranarayanan, P.E. 2007. "Smart multiagent architecture for congestion control to access remote energy meters," in Proc. International Conference on Computational Intelligence and Multimedia Applications, Sivakasi, India., pp. 24-28. Tuan, D. 2009. The Energy Web: Concept and challenges to overcome to make large scale renewable and distributed energy resources a true reality, in Proc. 7th IEEE International Conference on Industrial Informatics, Cardiff , UK. Valigi E. and Marino, E. 2009. Networks optimization with advanced meter infrastructure and smart meters, in Proc. International Conference and Exhibition on Electricity Distribution, Prague, Czech Republic. pp.1 4. Vojdani, A. 2008. Smart Integration, IEEE Power Energy Magazine, vol. 6, pp. 71 79.

Journal of Seismology for Project Management - myassignmenthelp

Question: Discuss about theJournal of Seismology for Project Management Journal. Answer: This paper explores the approaches of identifying the components of a project. The product-based planning is a significant part of the PRINCE2 method which is used in recognizing the deliverables of a project (Bentley, 2010). On the other hand, the work or activity-based approach involves designing the office in a way that the work and the activities are supported instead of creating boundaries around the users (Engestrm, 2014). The two approaches compares since they are concerned on the project deliverables. However, I prefer the work or activity-based approach since it is designed for the office and every individual engages in the activities. Key reasons why the project estimates go wrong are the false analogies, the case where the project was estimated by decree, the false precision, subjectivity, the too coarse grained and the neglecting coordination (Flyvbjerg, 2014). Various methods of project estimation are the expert judgment method, the analogous or comparative method, the top-down, the bottom-up, and the parametric method of estimation. I think the expert judgment is better for project estimation since it is common. People can easily understand the needs which needs to be delivered. At the same time, experts can be found who should work on a certain project. There are various risk identification tools and techniques. They include the reviews for documentation, the Delphi method, and information searching methods, interviewing, and brainstorming (Bommer, Crowley Pinho, 2015). Risk mitigation involves employing strategies to minimize the negative impacts. The main response strategies for risk mitigation are: avoidance which involves the elimination of risky tasks examples time and resources. Acceptance involves risk planning for the project examples the costs, time, and resources. Prepare and monitor used for main risks, an example is monitoring schedule for an x personnel and it exceeds the y personnel. References Bentley, C. (2010). Prince2: a practical handbook. Routledge. Bommer, J. J., Crowley, H., Pinho, R. (2015). A risk-mitigation approach to the management of induced seismicity. Journal of Seismology, 19(2), 623-646. Engestrm, Y. (2014). Activity theory and learning at work. In Ttigkeit-Aneignung-Bildung (pp. 67-96). Springer Fachmedien Wiesbaden. Flyvbjerg, B. (2014). What you should know about megaprojects and why: An overview. Project Management Journal, 45(2), 6-19.