Adequacy of Strong Improvement to Explain RAP

Adequacy of Strong Improvement to Explain RAP CASE STUDY OF APPROACH TO CONSIDER UNCERTAIN COMPONENTS FAILURE RATES IN SERIES-PARALLEL RELIABILITY SYSTEMS WITH REDUNDANCY ALLOCATION Abstract The principle reason for this review is to demonstrate the adequacy of strong improvement to explain RAP. The erlang distribution is used to implement robust optimization. The dynamic values attained by the failure rate is found to be a correct one. Another computation technique is introduced to consider dynamic qualities for failure rate in RAP. Also, because of complex redundancy Allocation Problem, two Simulated Annealing (SA) and Ant Colony Optimization (ACO) calculations are intended to decide the strong framework regarding indeterminate qualities for parameters. Another presumption is that every subsystem can have dynamic excess systems. Keeping in mind the end goal to take care of this issue and demonstrate effectiveness of proposed calculations, an issue in writing is unraveled and talked about. INTRODUCTION of Articles The planning for a system to select the components simultaneously is called the Redundancy Allocation Problem. Here these components are joined by several types to maximize the system reliability including all the properties in the system which are obtained. The reliability range should be maximum for different products to design the best system for a problem. The series parallel system can be of three types such as reliability allocation, redundancy allocation, and reliability redundancy allocation. For the first type the reliability limit is reduced for the usage of the resources in components reliability. The other type contains the redundancy limit to increase the reliability of the system to maximize the system level constraints. The failure rate of every components is studied on the journal articles which were in a determinable surrounding. The failure rate is very difficult to determine to be a exact one in practical environment for various factors as it may vary. The failure rates under various factors are affected. The failure rates arent any specified values in this article. The robust optimization is used to solve the reliability allocation problem for failure rates. In this article, the robustness with the redundancy allocation problem is explained and the mathematical model is developed. There are two algorithms used to find the indeterminate qualities for the parameters. The Simulated Annealing and Ant Colony Optimization algorithm is used and tested by the problem. Nomenclature i : index of subsystems where i à ¯Ã¢â€š ¬Ã‚ ½1,2,,si . ni: number of components used in subsystem i . nià ¯Ã¢â€š ¬Ã‚ ­Ãƒ ¯Ã¢â€š ¬Ã‚  :set of components used in all subsystems expect subsystem ri,zi (t) : reliability of component i z for subsystem i at time t à ¯Ã‚ Ã‚ ¬i,zi, Ki,zi : scale and shape parameters for the Gamma distribution of component i z in subsystem i à ¯Ã‚ Ã‚ ¬i,zi(ni, ni-) : function of robust failure rate for component i z in subsystem i . C,W : system level constraint limits for cost and weight, respectively. R(t; z,n) : system reliability at time t for designing vectors z and n . Explanation of the work presented in journal articles ROBUSTNESS DEFINITION IN RELIABILITY ALLOCATION PROBLEM To maximize the total reliability of a robust system the following assumptions are considered Components failure rate are changed as a result of change in system structure The constraints of the problem are predetermined for any changes in system structure. The total components in the subsystem is increasing when we consider the failure rate of this component The increase in the reliability of the component is caused by the decreased failure rate. THE ROBUST MODEL IN RELIABILITY ALOCATION PRROBLEM It is conceivable to execute two unique systems for parts of subsystems in Reliability allocation problem. The first is dynamic methodology in which every single repetitive part will begin to work at the same time from time zero. Interestingly, there are three unique variations of the cool, warm and hot methodologies rather for the second technique which is known as standby technique. In warm variation and in contrast with cool one, it would be more conceivable that segments flop before beginning to work on system. In the event that we utilize hot variation, it would not be essential that segments are working or they are sit and their failure rates will be consistent any way. As indicated by these definitions, we can create same numerical model for two unique techniques of hot standby and dynamic repetition. The repetitive parts are consecutively utilized as a part of the system at segment failure times and each repetitive segment in the standby system can be worked just when it is e xchanged on. At the point when the segment in operation falls flat, one of the excess units is changed on to proceed with the system operation. The 1, 2 and 3 equations are as follows 4 5 As per these derivations, a model is introduced in which failure rates will be computed in light of condition (5). This condition helps us to consider new failure rate values instead of steady ones. In addition, these new proposed qualities are more down to earth for genuine issues and will help fashioners to reduce existent crevices amongst hypothesis and practice. Then again, we cover the existent deficiencies which have never been focused on in the writing by building up another technique to compute failure rates. The robust relations are solved by the two algorithms Simulated and Ant Colony Optimizing for the redundancy allocation problem. Discussion of Contributions SIMULATED ANNEALING ALGORITHM FOR RAP Simulated Annealing is a standout amongst the most well-known probabilistic meta-heuristics to locate an adequate answer for advancement issues which was essential proposed by Kirkpatrick, Gelatt and Vecchi. This calculation depends on the relationship between the way toward tempering of solids and the arrangement philosophy of combinatorial advancement issues. One the most essential invaluable of the SA is keeping from rapidly focalizing to nearby ideal arrangement. This normal for SA is multiplied by tolerating better arrangements as well as the more regrettable neighbor arrangements with a specific likelihood to escape from a nearby ideal. It is observable that the likelihood of tolerating a more regrettable arrangement relies on upon the estimation of temperature; thus, while the temperature diminishes, the likelihood of tolerating a more terrible arrangement diminishes too. ANT COLONY OPTIMIZING ALGOROTHM FOR RAP Truly, ACO was firstly presented by Dorigo, Maniezzo and Colorni [3]. Key thought of subterranean insect frameworks depends on conduct of characteristic ants that prevail to discover most limited way from their home to nourishment sources by imparting by means of an aggregate memory that comprises of pheromone trails. Ants have a tendency to take after a way with a high pheromone level when numerous ants move in a typical range and they move arbitrarily when no pheromone is accessible. Then again, ants dont pick their bearings in light of level of pheromone only, but instead consider nearness of home and sustenance source, individually. Discussion of Dificiency and Potential Improvements The improvements to be made on this article are to solve large sized problems the heuristic algorithms were not developed and the flexible model to consider the dynamic values can be improved. An another development to be made is to show a robust model for selecting different types of parts simultaneously. The graphical theory could be used to develop by a new model Summary In this review, a nonlinear numerical model is produced for powerful arrangement parallel system with excess portion issue where, it has never been focused on strong enhancement approaches for this issue. In this model, we show another technique to compute part failure rates which is more versatile to genuine issues. Additionally, we create two reproduced tempering and insect province streamlining calculations which brought about proper arrangements, speedily. The last outcomes demonstrate that ACO calculation can bring about happier arrangements in contrast with SA calculation. There are three major advantages of robust model, The first is that utilizing this model will help us to create adaptable arrangements which are more functional to cover deficiencies amongst hypothesis and practice. The second one is that this model produces arrangements with higher framework dependability as opposed to those ones which have been displayed in writing. At last, the third one is that the created arrangements will be powerful and by changing the conditions, they can even now be proper arrangements which are near ideal arrangements. References [1]Ali Ghafarian Salehi Nezhada,*, Abdolhamid Eshraghniaye Jahromib, Mohammad Hassan Salmanic, Fereshte Ghasemid, an approach to consider uncertain components failure rates in series-parallel reliability systems with redundancy allocation.International Journal of Industrial Engineering (2016) [2] S. Kirkpatrick, C.D.J. Gelatt, M.P. Vecchi, Optimization by simulated annealing, Science. 220 (1983), pp.671-680 [3]M. Dorigo, V. Maniezzo, A. Colorni, Positive feedback as a search strategy, Technical Report. (1991). [4]D.W. Coit, A.E. Smith, Optimization Approaches to the Redundancy Allocation Problem for Series-Parallel Systems, Cited as Proceedings of the Fourth Industrial Engineering Research Conference. (1995).

Analysis of Bronfenbrenner’s ecological theory of development

Unlike other psychologists, Bronfenbrenner studied the child’s environment rather than the child. Bronfenbrenner’s (1979) ecological theory holds that a child’s environment affects the way the child will act. Rather than study the child in a strange environment, the theory studies the child in an environment that the child is comfortable in. When a child in studied in an environment that they are comfortable in, the findings are more accurate. Bronfenbrenner (1979) conducted the â€Å"strange situation experiment† before arriving at this conclusion. In the experiment, children were left with a stranger both in a laboratory setting and later in their homes. The study found that while the children were uncomfortable in both situations because they are left with strangers, they cried three times as much in the laboratory setting than in their own homes. This finding gave Bronfenbrenner (1979) the idea of studying children in familiar settings. Bronfenbrenner (1979) refers to these familiar settings as studying the child in context. Bronfenbrenner’s (1979) ecological theory holds that the various environments in which children are placed or find themselves have a significant effect on them. Consequently children will act according to the environment which they find themselves in. The importance of the environment to the child is illustrated in the fact that preschool children converse better with their parents than with their teachers or other adults whom they are not familiar with. Some of the environments which children find themselves in include the home, school, daycare, etc. Bronfenbrenner’s ecological theory of development holds that there are five levels of environments. These environments are as follows: Microsystem, Mesosystem, Exosystems, Microsystem and Chronosystem. The first environment which children come into contact with is the immediate family into which they are born. However, as they grow, they come in contact with other environments. In the course of this, they are able to make changes in the environment by the choices they make. The environment has an effect on the children and also the various environments as well as other factors have an influence on the children (and students too). The first level of environments is the Microsystems. The Microsystems are settings such as the home, the school, daycare, nursery, etc. This level is the most studied in Bronfenbrenner’s (1979) ecological theory of development because it is the most influential to the child. At this level, the interaction between the child and the environment is referred to as proximal processes. The second level of environments is the Mesosystem. The relationship between Microsystems creates a Mesosystem. For example, collaboration between a child’s (or student’s) teacher and the parents of the child could result in better outcomes. When parents and teachers collaborate to monitor the progress of the student, this speeds up development. On the other hand, poor relationships between two Microsystems can lead to poor performance of the child (or student) in school. For example, a child (student) who lives in an abusive home might not perform well at school. The third level in the ecological model is the Exosystems. Exosystems are the social organizations in which the child (student) interacts. The social organizations which the child and the student belong to, have an effect on the child. Students who belong to the debating society at school may end up developing effective communication skills. Macrosystem is the fourth level in Bronfenbrenner’s ecological theory of development. This level is important because it has an effect on other levels of influence identified in this theory of development. Macrosystems refer to the laws and customs of the culture in which the child (student) is growing up in. These variables are important because they affect the way children (students) behave and the decisions that they make. Culture determines what is right or wrong in a particular society and people conform. The fifth level is the chronosystem. All the levels that have been mentioned earlier make up the Chronosystems and the manner in which all these various levels affect each other. Also the Chronosystems refer to the historical context, meaning the era in which the child was brought up in. Current events and new technologies can also have an effect on the development of the student (or the child)- wars, economic depression, affluence, mobile phones, computers, satellite navigation, etc. An evaluative description of how Bronfenbrenner’s levels of influence have shaped my development (decision to enter graduate school). Microsystem I began to nurture the dream to enter graduate school from the influence in my home. Coming from a home of educated parents, I knew that I had to pursue my career to its peak and beyond- if there is a place to go beyond the peak. Apart from my parents, relatives around me were often conversing about their educational qualification and the next level they were moving to. I really admired them and did not want to be left behind. I remember in primary school that the other children and I will make jokes about the level of education we would attain as we got older. Furthermore, the teachers at school made us aware at an early stage that we needed to excel in order to progress along the various stages of educational attainment. All these influences got into my subconscious and have led to where I am today. Mesosystem My parents worked closely with my teachers in primary school in order keep a close eye on my educational development. My father asked my teachers at primary and secondary school to identify the areas in which I was deficient. Once these areas were identified, my father arranged private lessons at home. Thus, whenever I close from school, my private lessons continued after I had a short rest. Furthermore, my father was very careful about the report cards that the teachers sent home at the end of each term. He wanted to know my behavior and acted upon the observation of the teachers. Most importantly, my father monitored my performance in school and told me right from high school the academic discipline that was best suited for me. He said that I will do well as a business administrator, so I ended up studying for a master’s degree in business administration. Exosystems I attended a Catholic school so we were taught, â€Å"early to bed, early to rise, makes man healthy, wealthy and wise. † The bell rang for Matins and Lauds, very early in the morning. It was a very rigid routine. I was glad to get away from it when there was a vacation but in all this time it has taught me to be organized. The biggest lesson I have learnt is never to procrastinate. What must be done, needs to be done on time and put away. Also, the religious upbringing has taught me contentment even when I lack and never to ask for unnecessary favors from friends or colleagues. Microsystem Culture among black Africans is very strong. Educated Africans take advantage of every opportunity at education and encourage their children to do same. Among this type of Africans, education is regarded as a value that must be pursued if the individual must excel in life. Uneducated people are looked down upon as the â€Å"never do well. † With this mindset, I definitely did not want to stop at a first degree. I needed to enter graduate school in order to realize the ideals of my group and become a respected member of the group. Chronosystem Technological discoveries such as the Internet and mobile phones have made my school work easier and served as an encouragement for me to go on. Without these advances in technology, school work will definitely have been very tedious. I am sure in the past the amount of work which students had to do led to an increase in the drop out level. With the Internet, I am able to do research, collaborate with people, look at what other people are doing round the world, etc. The ease which technology affords has contributed in making me the satisfied graduate student I am today.

Science Friction Lab Report

I. Purpose/Problem/Question Which type of friction is the largest force – static, sliding, or rolling? Which is the smallest? II. Background Information From our previous activities that we did in class, I know that static friction is a very large force. The force is larger than rolling, sliding, and fluid friction. I also learned that rolling friction is the smallest type of force. This information may connect to my final analysis. III. Hypothesis If static friction is the largest force, then either sliding or rolling friction have to be the smallest force. IV. Experiment Materials * Scissors String * Textbook (covered) * Spring scale (force meter) * 3 to 4 wooden or metal rods Procedure Cut a piece of string, and tie it in a loop that fits in the textbook. Hook the string to the spring scale. Practice the three steps several times before you collect data. To measure next the static friction between the book and the table, pull the spring scale very slowly. Record the largest force on the scale before the book starts to move. After the book begins to move, you can determine the sliding friction. Record the force required to keep the book sliding at a slow, constant speed.Place two or three rods under the book to act as rollers. Make sure the rollers are evenly spaced. Place another roller in front of the book so that the book will roll onto it. Pull the spring scale slowly, Measure the force needed to keep the book rolling at a constant speed. V. Data/Results | Trial 1| Trial 2| Trial 3| Average| Static Friction | 4 N| 7 N| 6 N| 5. 67 N| Rolling Friction| 1 N| 2 N| 1 N| 1. 33 N| Sliding Friction| 4 N| 4 N| 5 N| 4. 33 N| Experimental Error: No cover on textbook. VI. Analysis I found out that static friction has the most amount of force than the others.The smallest amount of force was the rolling friction. It was by far a smaller force than static friction. Static friction had an average of 5. 67 N of force while rolling friction only had an average of 1. 33 N of force. Just for the record, sliding friction had an average of 4. 33 N of force. In this experiment, I learned that static friction has more force than I thought it did. In the beginning, I thought it was a very small force because I connected the word â€Å"static† to the static we watch on television when there is no connection.That is why I though that it was a weak force. It turned out to be the other way around. I did do one experimental error which was that there was no cover on the textbook I was using. Some other experimental errors could have been that the wooden planks were defected or the spring scale was defected. Some human errors might have been that I read the spring scale wrong. Another error would be that when I calculated static friction, the book might’ve slid without me noticing. The results I came up with at the end turned out to be the way I predicted.My results did in fact support my hypothesis. VII. Conclusion After all the experimentat ion, I figured out that static friction is the largest force of rolling and sliding friction, and that rolling friction is the smallest of the forces. VIII. Post Lab Questions Q: Which type of friction was the largest? Which was the smallest? A: The largest type of friction was static friction. The smallest was rolling friction. Q: Do the results support your hypothesis? If not, how would you revise or retest your hypothesis?A: The results do support my hypothesis. Q: Compare your results with those of another group. Are there any differences? By working together, design a way to improve the experiment and resolve possible differences. A: In the group that I compared with, the results were not that different. The results were infact very similar. The only thing that had a big jump was the average of the static friction. My average was 5. 67 N and his was 7. 33 N. I think this is because I did not have a cover on the textbook, but he did.

Top Three Trends in your profession and associated...

Briana Berry Week 4 February 16,2015 Top Three Trends in your profession and associated industry-Annotated Bibliography The top three trends in the Cyber Security field are salary, career advancement, and the need for predictions of the future in how information is exchanged. Cyber-crimes are becoming more popular and because of the many attacks that are happening much more frequently it has caused for a higher demand in cyber security professionals. Companies spend millions of dollars to correct security breaches within their organization. Back in 2008 the salary range for IT security professionals were in the $80,000 to $90,000 pay range per year, whereas in surveys from 2014 it shows these professionals earning $100,000 or more a†¦show more content†¦Email propagation of malicious code is the most frequently used technique by cyber-attackers†¨. Executives state that the majority of cyber threats originate from China†¨ and that organizations are conducting periodic review of systems and administrative logs, and adopted computer security policies, to counter cyber-attacks over the next two years. This article supports my third trend on predictions of the future in how information is exchanged. Ben-Asher, N., Gonzalez, C. (2015). Effects of cyber security knowledge on attack detection. Computers in Human Behavior, 48, 51-61. This study investigates how knowledge in network operations and information security influence the detection of intrusions in a simple network. A Intrusion Detection System (IDS) was developed to examine how individuals detect malicious events and declare an attack based on a sequence of network events. The results indicate that more knowledge in cyber security facilitated the correct detection of malicious events and decreased the false classification of benign events as malicious. While knowledge of cyber security helps in the detection of malicious events, situated knowledge regarding a specific network at hand is needed to make accurate detection decisions. Responses from participants that have knowledge in cyber security indicated that they were able to distinguish between different types of cyber-attacks, whereas novice participants were not sensitive to the attackShow MoreRelatedSports17369 Words   |  70 Pagesand/or in the classroom, and most are meant to get you both thin king and talking about sportscasting-related issues. There also are a number of bibliographic lists, encouraging further research on various topics, along with an approach to reporting on your reading that encourages critical thinking. Exercise 1.4 is a â€Å"Fill in the blanks,† with the answers on the next page, as is Exercise 2.3 â€Å"Sport history firsts,† and the essays in Exercise 2.4 have suggested inclusions for answers. 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