Raising Children Essay Example

Raising Children Essay OPINION Raising Successful Children Lizzy Stewart By MADELINE LEVINE * PHRASES like â€Å"tiger mom† and â€Å"helicopter parent† have made their way into everyday language. But does overparenting hurt, or help? Related * Sunday Book Review: ‘Teach Your Children Well’ by Madeline Levine (July 29, 2012) Related in Opinion * Room for Debate: Are Olympic Parents Supportive or Overbearing? (August 2, 2012) While parents who are clearly and embarrassingly inappropriate come in for ridicule, many of us find ourselves drawn to the idea that with just a bit more parental elbow grease, we might turn out children with great talents and assured futures. Is there really anything wrong with a kind of â€Å"overparenting lite†? Parental involvement has a long and rich history of being studied. Decades of studies, many of them by Diana Baumrind, a clinical and developmental psychologist at the University of California, Berkeley, have found that the optimal parent is one who is involved and responsive, who sets high expectations but respects her child’s autonomy. These â€Å"authoritative parents† appear to hit the sweet spot of parental involvement and generally raise children who do better academically, psychologically and socially than children whose parents are either permissive and less involved, or controlling and more involved. Why is this particular parenting style so successful, and what does it tell us about overparenting? For one thing, authoritative parents actually help cultivate motivation in their children. Carol Dweck, a social and developmental psychologist at Stanford University, has done research that indicates why authoritative parents raise more motivated, and thus more successful, children. In a typical experiment, Dr. Dweck takes young children into a room and asks them to solve a simple puzzle. Most do so with little difficulty. But then Dr. Dweck tells some, but not all, of the kids how very bright and capable they are. As it turns out, the children who are not told they’re smart are more motivated to tackle increasingly difficult puzzles. We will write a custom essay sample on Raising Children specifically for you for only $16.38 $13.9/page Order now We will write a custom essay sample on Raising Children specifically for you FOR ONLY $16.38 $13.9/page Hire Writer We will write a custom essay sample on Raising Children specifically for you FOR ONLY $16.38 $13.9/page Hire Writer They also exhibit higher levels of confidence and show greater overall progress in puzzle-solving. This may seem counterintuitive, but praising children’s talents and abilities seems to rattle their confidence. Tackling more difficult puzzles carries the risk of losing one’s status as â€Å"smart† and deprives kids of the thrill of choosing to work simply for its own sake, regardless of outcomes. Dr. Dweck’s work aligns nicely with that of Dr. Baumrind, who also found that reasonably supporting a child’s autonomy and limiting interference results in better academic and emotional outcomes. Their research confirms what I’ve seen in more than 25 years of clinical work, treating children in Marin County, an affluent suburb of San Francisco. The happiest, most successful children have parents who do not do for them what they are capable of doing, or almost capable of doing; and their parents do not do things for them that satisfy their own needs rather than the needs of the child. The central task of growing up is to develop a sense of self that is autonomous, confident and generally in accord with reality. If you treat your walking toddler as if she can’t walk, you diminish her confidence and distort reality. Ditto nightly â€Å"reviews† of homework, repetitive phone calls to â€Å"just check if you’re O. K. † and â€Å"editing† (read: writing) your child’s college application essay. Once your child is capable of doing something, congratulate yourself on a job well done and move on. Continued, unnecessary intervention makes your child feel bad about himself (if he’s young) or angry at you (if he’s a teenager). But isn’t it a parent’s job to help with those things that are just beyond your child’s reach? Why is it overparenting to do for your child what he or she is almost capable of? Think back to when your toddler learned to walk. She would take a weaving step or two, collapse and immediately look to you for your reaction. You were in thrall to those early attempts and would do everything possible to encourage her to get up again. You certainly didn’t chastise her for failing or utter dire predictions about flipping burgers for the rest of her life if she fell again. You were present, alert and available to guide if necessary. But you didn’t pick her up every time. You knew she had to get it wrong many times before she could get it right. HANGING back and allowing children to make mistakes is one of the greatest challenges of parenting. It’s easier when they’re young — tolerating a stumbling toddler is far different from allowing a preteenager to meet her friends at the mall. The potential mistakes carry greater risks, and part of being a parent is minimizing risk for our children. What kinds of risks should we tolerate? If there’s a predator loose in the neighborhood, your daughter doesn’t get to go to the mall. But under normal circumstances an 11-year-old girl is quite capable of taking care of herself for a few hours in the company of her friends. She may forget a package, overpay for an item or forget that she was supposed to call home at noon. Mastery of the world is an expanding geography for our kids, for toddlers, it’s the backyard; for preteens, the neighborhood, for teens the wider world. But it is in the small daily risks — the taller slide, the bike ride around the block, the invitation extended to a new classmate — that growth takes place. In this gray area of just beyond the comfortable is where resilience is born. So if children are able to live with mistakes and even failing, why does it drive us crazy? So many parents have said to me, â€Å"I can’t stand to see my child unhappy. † If you can’t stand to see your child unhappy, you are in the wrong business. The small challenges that start in infancy (the first whimper that doesn’t bring you running) present the opportunity for â€Å"successful failures,† that is, failures your child can live with and grow from. To rush in too quickly, to shield them, to deprive them of those challenges is to deprive them of the tools they will need to handle the inevitable, difficult, challenging and sometimes devastating demands of life. While doing things for your child unnecessarily or prematurely can reduce motivation and increase dependency, it is the inability to maintain parental boundaries that most damages child development. When we do things for our children out of our own needs rather than theirs, it forces them to circumvent the most critical task of childhood: to develop a robust sense of self. There is an important distinction between good and bad parental involvement. For example, a young child doesn’t want to sit and do his math homework. Good parents insist on compliance, not because they need their child to be a perfect student but because the child needs to learn the fundamentals of math and develop a good work ethic. Compare this with the parent who spends weeks â€Å"helping† his or her child fill out college applications with the clear expectation that if they both work hard enough, a â€Å"gotta get into† school is a certainty. (While most of my parent patients have graduated from college, it is always a telltale sign of overparenting when they talk about how â€Å"we’re applying to Columbia. †) In both situations parents are using control, in the first case behavioral (sit down, do your math) and in the second psychological (â€Å"we’re applying. †) It is psychological control that carries with it a textbook’s worth of damage to a child’s developing identity. If pushing, direction, motivation and reward always come from the outside, the child never has the opportunity to craft an inside. Having tutors prep your anxious 3-year-old for a preschool interview because all your friends’ children are going to this particular school or pushing your exhausted child to take one more advanced-placement course because it will ensure her spot as class valedictorian is not involved parenting but toxic overparenting aimed at meeting the parents’ need for status or affirmation and not the child’s needs. So how do parents find the courage to discard the malpractice of overparenting? It’s hard to swim upstream, to resist peer pressure. But we must remember that children thrive best in an environment that is reliable, available, consistent and noninterfering. A loving parent is warm, willing to set limits and unwilling to breach a child’s psychological boundaries by invoking shame or guilt. Parents must acknowledge their own anxiety. Your job is to know your child well enough to make a good call about whether he can manage a particular situation. Will you stay up worrying? Probably, but the child’s job is to grow, yours is to control your anxiety so it doesn’t get in the way of his reasonable moves toward autonomy. Parents also have to be clear about their own values. Children watch us closely. If you want your children to be able to stand up for their values, you have to do the same. If you believe that a summer spent reading, taking creek walks and playing is better than a specialized camp, then stick to your guns. Parents also have to make sure their own lives are fulfilling. There is no parent more vulnerable to the excesses of overparenting than an unhappy parent. One of the most important things we do for our children is to present them with a version of adult life that is appealing and worth striving for. Madeline Levine is a clinician, consultant and the author, most recently, of â€Å"Teach Your Children Well: Parenting for Authentic Success. †

Using the PHP Rand() Functions to Generate Random Numbers

Using the PHP Rand() Functions to Generate Random Numbers The rand() function is used in PHP to generate a random integer. The rand() PHP function can also be used to generate a random number within a specific range, such as a number between 10 and 30. If no max limit is specified when using the rand() PHP function, the largest integer that can be returned is determined by the getrandmax() function, which varies by operating system.   For example, in Windows, the largest number that can be generated is 32768. However, you can set a specific range to include higher numbers. Rand() Syntax and Examples The correct syntax for using the rand PHP function is as follows: rand(); or rand(min,max); Using the syntax as described above, we can make three examples for the rand() function in PHP: ?phpecho (rand(10, 30) . br);echo (rand(1, 1000000) . br);echo (rand());? As you can see in these examples, the first rand function generates a random number between 10 and 30, the second between 1 and 1 million, and then third without any maximum or minimum number defined. These are some possible results: 20442549830380191 Security Concerns Using Rand() Function The random numbers generated by this function are not cryptographically secure values, and they should not be used for cryptographic  reasons. If you need secure values, use other random functions such as random_int(), openssl_random_pseudo_bytes(), or random_bytes() Note: Beginning with PHP 7.1.0, the rand() PHP function is an alias of mt_rand(). The mt_rand() function is said to be four times faster and it produces a better random value. However, the numbers it generates are not cryptographically secure. The PHP manual recommends using the  random_bytes() function for cryptographically secure integers.

Titanium Chemical & Physical Properties

Titanium Chemical & Physical Properties Titanium is a strong metal used in human implants, aircraft, and many other products. Here are facts about this useful element: Basic Facts Titanium Atomic Number: 22Symbol: TiAtomic weight: 47.88Discovery: William Gregor 1791 (England)Electron configuration: [Ar] 4s2 3d2Word origin: Latin titans: in mythology, the first sons of Earth Isotopes There are 26 known isotopes of titanium ranging from Ti-38 to Ti-63. Titanium has five stable isotopes with atomic masses 46-50. The most abundant isotope is Ti-48, accounting for 73.8% of all natural titanium. Properties Titanium has a melting point of 1660 /- 10Â °C, boiling point of 3287Â °C, specific gravity of 4.54, with a valence of 2, 3, or 4. Pure titanium is a lustrous white metal with low density, high strength, and high corrosion resistance. It is resistant to dilute sulfuric and hydrochloric acids, moist chlorine gas, most organic acids, and chloride solutions. Titanium is only ductile when it is free of oxygen. Titanium burns in air and is the only element that burns in nitrogen. Titanium is dimorphic, with the hexagonal a form slowly changing to the cubic b form around 880Â °C. The metal combines with oxygen at red heat temperatures and with chlorine at 550Â °C. Titanium is as strong as steel, but it is 45% lighter. The metal is 60% heavier than aluminum, but it is twice as strong. Titanium metal is considered to be physiologically inert. Pure titanium dioxide is reasonably clear, with an extremely high index of refraction and an optical dispersion higher than that of a diamond. Natural titanium becomes highly radioactive upon bombardment with deuterons. Uses Titanium is important for alloying with aluminum, molybdenum, iron, manganese, and other metals. Titanium alloys are used in situations where lightweight strength and ability to withstand temperature extremes are required (e.g., aerospace applications). Titanium may be used in desalination plants. The metal is frequently used for components which must be exposed to seawater. A titanium anode coated with platinum may be used to provide cathodic corrosion protection from seawater. Because it is inert in the body, titanium metal has surgical applications. Titanium dioxide is used to make man-made gemstones, although the resulting stone is relatively soft. The asterism of star sapphires and rubies is a result of the presence of TiO2. Titanium dioxide is used in house paint and artist paint. The paint is permanent and provides good coverage. It is an excellent reflector of infrared radiation. The paint is also used in solar observatories. Titanium oxide pigments account for the largest use of the element. Titanium oxide is used in some cosmetics to disperse light. Titanium tetrachloride is used to iridize glass. Since the compound fumes strongly in air, it is also used to produce smoke screens. Sources Titanium is the 9th most abundant element in the earths crust. It is almost always found in igneous rocks. It occurs in rutile, ilmenite, sphene, and many iron ores and titanates. Titanium is found in coal ash, plants, and in the human body. Titanium is found in the sun and in meteorites. Rocks from the Apollo 17 mission to the moon contained up to 12.1% TiO2. Rocks from earlier missions showed lower percentages of titanium dioxide. Titanium oxide bands are seen in spectra of M-type stars. In 1946, Kroll showed that titanium could be produced commercially by reducing titanium tetrachloride with magnesium. Physical Data Element Classification: Transition MetalDensity (g/cc): 4.54Melting Point (K): 1933Boiling Point (K): 3560Appearance: Shiny, dark-gray metalAtomic Radius (pm): 147Atomic Volume (cc/mol): 10.6Covalent Radius (pm): 132Ionic Radius: 68 (4e) 94 (2e)Specific Heat (20Â °C J/g mol): 0.523Fusion Heat (kJ/mol): 18.8Evaporation Heat (kJ/mol): 422.6Debye Temperature (K): 380.00Pauling Negativity Number: 1.54First Ionizing Energy (kJ/mol): 657.8Oxidation States: 4, 3Lattice Structure: 1.588Lattice Constant (Ã…): 2.950CAS Registry Number: 7440-32-6 Trivia Titanium was discovered in a black sand known as ilmenite. Ilmenite is a mixture of iron oxides and titanium oxides.William Gregor was the pastor of Mannacan parish when he discovered titanium. He named his new metal manaccanite.The German chemist Martin Klaproth rediscovered Gregors new metal and named it titanium after the Titans, Greek mythological beings of the Earth. The name titanium was preferred and ultimately adopted by other chemists but acknowledged Gregor as the original discoverer.Pure titanium metal was not isolated until 1910 by Matthew Hunter119 years after its discovery.Approximately 95% of all titanium is used in the production of titanium dioxide, TiO2. Titanium dioxide is an extremely bright white pigment used in paints, plastics, toothpaste, and paper.Titanium is used in medical procedures because it is non-toxic and non-reactive in the body. References Los Alamos National Laboratory (2001)Crescent Chemical Company (2001)Langes Handbook of Chemistry (1952)CRC Handbook of Chemistry Physics (18th Ed.) International Atomic Energy Agency ENSDF database (Oct 2010)

Faith healing case Essay Example | Topics and Well Written Essays - 750 words

Faith healing case - Essay Example He provided the boy’s parents with information regarding the treatment that is available, and then explained to them the procedures that would have to be undertaken. The parents discussed the matter between themselves for two hours, and then told the physician that they had reached the decision to take their son to a faith healing service instead of seeking medical intervention. The physician tried to convince them of the futility of this action but to no avail. The parents left with their son after the physician gave them a return appointment, but they did not honor it. II. Ethical Question to be Answered Were the parents morally justified to deny their son much needed medical treatment in favor of faith healing? III. Proposed Answers to Ethical Question It is not morally permissible for the 10 year old boy’s parents to deny him medical treatment for leukemia, with the sole reason that the treatment will eventually fail to work, and they would have to take their son to a faith healing service after all. As much as medical treatment for the treatment of cancer is not completely effective, it is still the best shot at recovery that a patient could obtain since it has worked in numerous cases. Faith in the ability of God to heal cannot be disputed, but it has failed to provide positive results in many cases. It is morally wrong to deny a minor incapable of making important decisions for himself, necessary treatment that may save his life. Another matter that needs to be considered is the possibility that the boy might have opted for medical treatment if he were of age. Cancer therapy, including that specialized for leukemia, has proved effective in many cases, and there is evidence in terms of scientific studies and physicians’ reports to prove it. On the other hand, the boy’s parents would be at a loss at providing credible evidence to prove that faith healing is effective at curing cancer. IV. Objections to Proposed Answers and Respo nses to the Objections Objection (1): Parents have the authority to opt out of medical treatment for their child who is a minor in favor of other legal options, if the medical treatment has

Story-truth versus Happening-truth Essay Example | Topics and Well Written Essays - 2250 words

Story-truth versus Happening-truth - Essay Example Story-truth, on the other hand, allows the listener to be there, with the narrator in the present, and see how things were. Story-truth allows for the emotion of war to be the truth, and not just the action. O'Brien uses both types of truth in his writing, to emphasis the difference, and to help the reader see that through emotion, difficult circumstances, and distant reality that story-truth comes much closer to actual truth than happening-truth. O'Brien regularly uses story-truth as a way to show the emotional connections between the soldiers, and also the emotional burden that they share both when a fellow soldier dies, and when one of them kills an enemy soldier. One of the clearest examples of story-truth is in the description of the young Vietnamese soldier that was killed near My Khe. The first time the reader sees the story, they read about the other soldiers applauding the kill, and how well he had done, while he focuses on the injuries, and the shapes they represented to him. While the other soldiers saw his work as successful, he could only imagine what the young man had been like before he died. We are even taken into the other soldier's life, and shown that he is a pacifist, who does not want to be there (a reflection of O'Brien's own desire not to be there). The second time the reader encounters the story, the actual kill is described, the throwing of the grenade and the shock when the man actually died. The thi rd time, the reader is told that O'Brien did not actually throw the grenade, he had only watched. The happening-truth would only tell the reader how the man had died. By creating a story-truth, the reader is allowed to see that the whole troop could feel the young man's death, and how profound an impact that had on even those who did not make the kill. O'Brien, for example, feels as if he did, simply by being there and not stopping it. The story comes to life, and in many ways, who had killed the man no longer matters. What matters is how the men felt, and reacted to the event. That man may never have even existed, or been a compilation of several kills, but the feelings would have been the same each time. Those are the story-truth, and the real truth, because they are what last. During the story, O'Brien allows the reader to see that war is not all medals and victory. He allows the reader inside, to see the tragedy, the death, and the plain humanity of those who go to war. For Vietnam, especially, many of the men fighting did not want to be there, and when they returned home, they did not know what to do with themselves. In Speaking of Courage, a story-truth, O'Brien takes a story about one man, and his hopelessness after the war, and helps his readers to feel the despair, and the strong feeling of being lost so many soldiers have when they return. His character imagines a conversation about the war, in which he could have won a medal. Except that nobody asked to hear the story. For the veterans, few people want to remember the war, and they had no way to share all the turmoil inside. These circumstances are impossible to show in happening-truth, since they only share the physical happenings. By making the story universal, everyone feels what it is like to be lost, and trapped inside their head. Throughout the book, a sort of distant reality is created for the reader. Distant, because although you can see the pain, and feel the emotion, it is hazy, and unclear what really happened. Did Tim

Optimal Reactive Power Planning By Using Evolutionary Engineering Essay

Optimal Reactive Power Planning By Using Evolutionary Engineering Essay This paper presents a methodology for solving Optimal Reactive Power Planning (ORPP) problem by using Evolutionary Programming (EP) Optimization Technique in order to improve the voltage stability and minimize the losses in the power system. This study has developed the Evolutionary Programming (EP) Optimization Technique using MATLAB software. The study tested two fitness functions namely total loss minimization and the voltage stability improvement in power system with two different mutation technique. Comparison in the results obtained was made in order to determine the best fitness function and the best mutation technique to be used for solving ORPP and hence the voltage stability is improved. The proposed technique was tested on the IEEE 26 bus reliability test system. Keywords: Optimal Reactive Power Planning (ORPP), Voltage Stability Improvement, Evolutionary Programming (EP) I. INTRODUCTION In general, the problem of optimal reactive power planning (ORPP) can be defined as to determine the amount and location of shunt reactive power compensation devices needed for minimum cost while keeping an adequate voltage profile. The ORPP is one of the most challenging problems since objective functions, the operation cost and the investment cost of new reactive power sources, should be minimized simultaneously [1]. Transmission loss can be minimised by performing reactive power planning which involves optimisation process. The ORPP is a large-scale nonlinear optimization problem with a large number of variables and uncertain parameters. Various mathematical optimization algorithms have been developed for the ORPP, which in most cases; use nonlinear [2], linear [3], or mixed integer programming [4], and decomposition methods [5-8]. However, these conventional techniques are known to converge to a local optimal solution rather than the global one for problems such as ORPP which have many local minima. Recently, evolutionary algorithms (EAs) have been used for optimization; in particular both the genetic algorithm and evo1ution programming have been used in the ORPP problem. The EA is a powerful optimization technique analogous to the natural selection process in genetics. It is useful especially when other optimization methods fail in finding the optimal solution [1]. Evolutionary Programming (EP) optimization technique is recently applied in solving electric power system optimization problems. It is part of the Evolutionary Algorithm (EA) optimization techniques under the artificial intelligence hierarchy. Optimization is an important issue in power system operation and planning particularly in the area of voltage stability studies [9]. In this study, EP engine was initially developed to implement the optimisation process considering two mutation techniques, each with two different objective functions. Comparative studies performed in this study aimed to identify the most suitabl e mutation technique with the best objective function for minimising transmission loss in power system and also improving the voltage stability. The parameters for this problem are: generated reactive power (Qg), injected reactive power (Qinj) and transformer tap (T). Validation on the effectiveness of the proposed technique was conducted on the IEEE-26 reliability test system. Figure 1: The IEEE 26 bus test system II. OBJECTIVES The two objective functions of this study are: To obtain the total loss minimization To improve the voltage stability Where: Total_Loss is total loss minimization LQNmax is voltage stability improvement III. BACKGROUND STUDIES A. Optimal Reactive Power Planning (ORPP) Optimal Reactive Power Planning (ORPP) is a sub-problem of Optimal Power Flow solution which has been widely used in power system operation and planning to determine the optimal control parameter settings, in order to minimize or maximize the desired objective function while satisfying a set of systems constraint. Reactive Power Planning (RPP) involves in optimizing the transformer tap setting, injection of reactive power at generator and load bus so as to fulfill the objective function. Since the OPF approach is commonly concerned with the security and economic operation of the power system, Economic Dispatch (ED) technique is also adopted in RPP scheme. The value of active power generated by the generator is also adjusted in the approach. [11] ORPP is a nonlinear programming problem which has the following mathematical formulation: Maximize or minimize f(x, u) (3) subject to g(x, u) =0 (4) hmin à ¢Ã¢â‚¬ °Ã‚ ¤ h(x, u) à ¢Ã¢â‚¬ °Ã‚ ¥ hmax (5) where u is the vector of control variables and x is the vector of dependent variables. f(x, u) is the objective function, while g(x, u) is the nodal power constraints with hmin à ¢Ã¢â‚¬ °Ã‚ ¤ h(x, u) à ¢Ã¢â‚¬ °Ã‚ ¥ hmax are the inequality constraints of the dependent and independent variables. B. Evolutionary Programming (EP) EP is one of the popular techniques which fall under the Evolutionary Computation in Artificial Intelligence (AI) hierarchy and increasingly applied for solving power system optimization problem in recent years. A new population is formed from an existing population through the use of a mutation operator. This operator produces a new solution by perturbing each component of an existing solution by a random amount. The degree of optimality is measured by the fitness, which can be defined as the objective function of the problem [12]. Through the use of a ranking scheme, the candidate solutions in each population were sorted in ascending order according to the number of the best population. The best population form a resultant population is referred as the next generation. The ranking scheme must have more optimal solutions which has a greater chance of survival than the poorer solutions. It is a stochastic optimization strategy, which based on the mechanics of natural selections-mutation, competition and evolution. This technique stressed on the behavioural linkage between parents and their offspring. In general, EP consists of 3 major steps which briefly discussed as follow [12], [13]: i. Initialization The initial population of ÃŽÂ ¼ individuals consists of (xi, ÆÅ ¾i), ˆ¦i à ¢Ã¢â‚¬Å¡Ã‚ ¬ {1, 2,à ¢Ã¢â€š ¬Ã‚ ¦ÃƒÅ½Ã‚ ¼} are generated randomly based on its limit, whereby xi denotes the control variable and ÆÅ ¾i is the strategic parameter with respect to xi. The fitness is calculated for each individual based on its objective function, f(xi). ii. Mutation a) First Mutation Technique Each parent (xi, ÆÅ ¾i), i=1,à ¢Ã¢â€š ¬Ã‚ ¦, ÃŽÂ ¼, creates a single offspring (xi, ÆÅ ¾i), where xi and ÆÅ ¾i are given by: xi (j) = xi (j) + ÆÅ ¾i (j) Nj (0, 1) (6) ÆÅ ¾i (j) = ÆÅ ¾i (j) exp (à Ã¢â‚¬Å¾ N (0, 1) + à Ã¢â‚¬Å¾ Nj (0, 1)) (7) and à Ã¢â‚¬Å¾ = ((2(n)  ½)  ½)-1 (8) à Ã¢â‚¬Å¾= ((2n)  ½)-1 (9) xi (j), xi'(j), ÆÅ ¾i(j) and ÆÅ ¾i'(j) are the j-th component of the vectors xi, xi, ÆÅ ¾i and ÆÅ ¾i respectively. N(0,1) represents a normally distributed one-dimensional random number with mean zero and standard deviation 1. Nj(0,1) denotes that the random number is generated anew for each value of j. Subsequently, the fitness is calculated for each offspring. b) Proposed Mutation Technique The proposed mutation rule was inspired by neural network back propagation learning. The following three equations are employed for perturbing the parents to generate their offspring: In these equations, xij [k] [k] is the jth variable of an ith individual at the kth generation. The learning rate, ÆÅ ¾, and the momentum rate, ÃŽÂ ±, are real-valued constants that are determined empirically. |.| denotes an absolute value and N represents the normal distribution. Άxij [k] is the amount of change in an individual, which is proportional to the temporal error, and it drives the individual to evolve close to the best individual at the next generation. It may be viewed as a tendency of the other individuals to take after or emulate the best individual in the current generation. sxij [k] is the evolution tendency or momentum of previous evolution. It accumulates evolution information and tends to accelerate convergence when the evolution trajectory is moving in a consistent direction [14]. The best individual is mutated only by the momentum. This expands the exploitation range and increases the possibility for escaping from local minima. acci[k] in (10) is defined as follows. acci[k] = 1; if the current update has improved cost, 0; otherwise. (10) iii. Combination and Selection In combination stage, the union of parents and offspring are ranked in ascending or descending order according to its fitness and purpose of the optimisation. Hence, the top ÃŽÂ ¼ individuals are selected to be parents for the next generation. The process of mutation, combination and selection are repeated until the stopping criterion is met. In this paper, the stopping criterion is taken to be the convergence of fitness value. IV. METHODOLOGY Figure 3 explained the overall methodology for the evolutionary programming optimization technique to solve ORPP. The produced offspring vector must satisfy and consider the constraints as at the initialization. The main concept of EP is the mutation process. Then continues with learning about the MATLAB software and tested the IEEE 26-Bus Test System to observe initial values which are total power loss, initial minimum and maximum voltages and the initial line stability index (LQP LQN). These initial values have been taken by considering the unstable transmission lines in the test system (IEEE 26-BUS). The unstable line means the line stability index value is close to 1.00. The unstable voltage is when the value is not within the range of (0.90à ¢Ã¢â‚¬ °Ã‚ ¤Và ¢Ã¢â‚¬ °Ã‚ ¤1.10). Figure 3: The flow chart for the EP optimization technique The EP program was developed and the analysis of the result is tested based on objective function of the project such as minimize total loss and the voltage stability improvement. Then, the program has been run for five times for each type of objective function. Finally, this project has been concluded and the report has been written. A. Development of EP for Optimal Reactive Power Planning The optimal reactive power planning problems has been tested on the IEEE 26 bus test system. The two objective functions tested are: Fitness1 = Total_Loss; Fitness2 = LQNmax; To find the solution of the problem, the parameters d were decided. The parameters were: Reactive Power of Generator Bus Table 1 shows the parameters and size of reactive power of generation bus. There are five generator buses in IEEE 26-bus test system: Bus 2, 3, 4, 5 and 26. The size of each bus is as below. Table 1: Parameters and size of reactive power of generator bus Parameter Bus Size (MVar) Qg2 2 0 to 50 Qg3 3 0 to 40 Qg4 4 0 to 35 Qg5 5 0 to 30 Qg26 26 0 to 20 2. Injected Reactive Power to the Bus Table 2 shows the parameters and size of injected reactive power to the bus. It shows that there is nine buses have been injected by reactive power. The buses are as below. The unit of the injected reactive power is in MVar. Table 2: Parameters and size of injected reactive power to the bus Parameter Bus Size (MVar) C1 1 0 to 9 C4 4 0 to 9 C5 5 0 to 9 C6 6 0 to 9 C9 9 0 to 9 C11 11 0 to 9 C12 12 0 to 9 C15 15 0 to 9 C19 19 0 to 9 3. Transformer Tap at the Transmission Line Table 3 shows the parameters and size of transformer tap at transmission line. It shows that there is seven transformer tap change at transmission line in IEEE 26-bus test system. The size of each transformer tap is (0.9 to 1.2). Table 3: Parameters and size of transformer tap at the transmission line Parameter Line Size (p.u) T1 2-3 0.9 to 1.2 T2 2-13 0.9 to 1.2 T3 3-13 0.9 to 1.2 T4 4-8 0.9 to 1.2 T5 4-12 0.9 to 1.2 T6 6-19 0.9 to 1.2 T7 7-9 0.9 to 1.2 The EP process is initialization, mutation, rank and selection and convergence test. 4.1.1 Initialization Initial population of size 20 is formed by a set of randomly generated actual value. Each member is tested using equation (12) (17) as below. Equations (12) (16) are the generation constraints. The bus voltage limits in equation (17) are stated in order to avoid any violation to the system operation. The total loss limit in equation (18) is stated in order to avoid the losses greater than the initial values. 0MVar à ¢Ã¢â‚¬ °Ã‚ ¤ Qg2 à ¢Ã¢â‚¬ °Ã‚ ¤ 50MVar (12) 0MVar à ¢Ã¢â‚¬ °Ã‚ ¤ Qg3 à ¢Ã¢â‚¬ °Ã‚ ¤ 40MVar (13) 0MVar à ¢Ã¢â‚¬ °Ã‚ ¤ Qg4 à ¢Ã¢â‚¬ °Ã‚ ¤ 35MVar (14) 0MVar à ¢Ã¢â‚¬ °Ã‚ ¤ Qg5 à ¢Ã¢â‚¬ °Ã‚ ¤ 30MVar (15) 0MVar à ¢Ã¢â‚¬ °Ã‚ ¤ Qg26 à ¢Ã¢â‚¬ °Ã‚ ¤ 20MVar (16) 0.90V à ¢Ã¢â‚¬ °Ã‚ ¤Ãƒ ¢Ã¢â‚¬ Ã¢â‚¬Å¡Và ¢Ã¢â‚¬ Ã¢â‚¬Å¡Ãƒ ¢Ã¢â‚¬ °Ã‚ ¤ 1.10V (17) Total Losses à ¢Ã¢â‚¬ °Ã‚ ¤ 16 (18) The generated random numbers must be smaller than the initial solution set in order to make sure that fitness will be improved. Only the member that satisfy the constraints are included in the initial population set. 4.1.2 Mutation Mutation is a method to execute the random number to produce offspring. An offspring vector Li is created from each parent vector by adding Gaussian random with zero mean and standard deviation. 4.1.3 Rank and Selection The offspring populations generated form mutation process is merged with the parent populations. The selection process is to generate a new 20 populations based on the objective function of total losses minimization and the voltage stability improvement. All of members were sorted in ascending order to produce the best twenty or the strongest twenty populations for next generation. 4.1.4 Convergence test The stopping criteria in order to obtain the optimal solution are by looking at the difference in maximum fitness and minimum fitness which must less then certain values. If not achieved, the process will be repeated until it converged. Where: Total_Lossmax- Total_Lossmin LQNmax LQNmin V. RESULTS AND DISCUSSION An EP optimization technique has been developed in this study and tested on IEEE 26-bus test system. The objective function is to minimize the total power loss and to improve the voltage stability in power system. The program has been developed to find the optimal value of control variables based on each objective functions. However, before this program was run, load flow solution for the IEEE 26-bus test system was obtained to determine the initial values. The initial total power loss and stability index is 18.986 MW and 0.754 respectively. For each objective function the program was run five times and the results were tabulated in tables according to the objective function. Then the best result for each objective function was selected and tabulated in Table 1 in the Appendix A in order to make a comparison between the two objective functions. According to the result which tabulated in Table 1 in the Appendix A, it was found that EP optimization technique with voltage stability improvement as the objective function give the best result which is total power loss of 14.462 MW and stability index of 0.717. The EP optimization technique with total power loss minimization as the objective function give results 14.987 MW. The EP optimization technique using proposed mutation rule with voltage stability improvement as objective function, the result MW and for the total power loss and stability index respectively. According Table 4, the total power loss and stability index is 15.534 MW and 0.734 respectively. The result after solve the Optimal Reactive Power Planning (ORPP) is 13.019 MW and 0.699. The percentage reduction for total power loss and stability index after solves the ORPP is 16.19 % and 4.77 %. Table 4: Comparison results before and after solves the Optimal Reactive Power Planning Terms Before Solve ORPP After Solve ORPP Total Power Loss (MW) 15.534 13.019 Stability Index, LQNmax 0.734 0.699 VI. CONCLUSION An evolutionary programming optimization technique has been developed to optimize the real power of generator bus, the reactive power and transformer tap control variables for minimal total cost of generation, total power loss and voltage stability improvement. In this paper, the total cost minimization is the best objective function for minimization of total cost, total power loss and stability index is reduced. The percentage reduction for the total cost and total power loss is acceptable. The percentage reduction of stability index is the highest. The percentage reduces for the total cost, total power loss and stability index is 7.77 %, 16.19 % and 4.77 % respectively. This is the acceptable and reasonable percentage reduction as compared to other objective functions. Therefore voltage stability improvement may not have to be the objective function in order to improve the voltage stability condition of a power system in solving the OPF. VII. FUTURE DEVELOPMENT For future development, the other optimization techniques are proposed to be implemented in solving the ORPP in order to minimize the total power system losses and especially to improve the voltage stability in larger power system. Further modification should be included to get more accurate results for example using different mutation rules and selection strategies. VIII. REFERENCES [1] Kwang. Y. Lee and Frank F. Yang Department of Electrical Engineering The Pennsylvania State University University Park, PA 16802, Optimal Reactive Power Planning Using Evolutionalry Algorithms: A Comparative Study for Evolutionary Programming, Evolutionary Strategy, Genetic Algorithm, and Linear Programming; IEEE Transactions on Power Systems, Vol. 13, No. 1, February 1998 [2] R. Billington and S. S. Sachdev, Optimum network VAR planning by nonlinear programming IEEE Trans. on Power Appar. and Syst., Vol. PAS-92, pp. 6 [3] T. Heydt and W. M. Grady, Optimal Var siting using linear load flow formulation, IEEE Trans. on Power Appar. and Syst., pp. 1214-1222. Vol. PAS-102, No. 5, May 1983. [3] K. Aoki, M. Fan, and A. Nishkori, Optimal Var planning by approximation method for recursive mixed integer linear planning, IEEE Trans. on Power Syst.,Vol. PWRS-3, No. 4, pp. 1741-1747, November 1988. [4] K. Y. Lee, Y. M. Park, and J. L. Oritz, A united approach to optimal real and reactive power dispatch, IEEE Trans. on Power Appar. and Syst., Vol. PAS-104, pp. 1147-1153, May 1985. [SI K. Y. Lee, J. L. Ortiz, Y. M. Park, andL. G. Pond, An optimization technique for reactive power planning of subtransmission network under normal operation, IEEE Trans. on Power Syst., Vol. PWRS-1, pp. 153-159, May 1986. [6] M. K. Mangoli, K. Y. Lee, and Y. M. Park, Operational real and reactive power control using linear programming, Electric Power Systems Research,[7] M. K. Mangoli, K. Y. Lee, andY. M. Park, Optimal long-term reactive power planning using decomposition techniques, Electric Power System Research, Vol. 26, Rana Mukerji, Wendell Neugebauer, Richard P. Ludorf and Armand Catelli, Evaluation of Wheeling and Non-Utility Generation (NUG) Options using Optimal Power Flows, IEEE Transaction on Power Systems, Vol. 7, No. 1, February 1992. [3] Kessel and Glavitsch> Estimating the Voltage Stability of a Power System, IEEE Transaction on Power Delivery, Vol. PWRD-1, NO. 3, July 1986, pp 346-352. [4] Jason Yuryevich and Kit Po Wong, Evolutionary Programming Based Optimal Power Flow Algorithm, IEEE Transaction on Power Systems, Vol. 14, No. 4, November 1999, pp 1245-1250. [5] A.M. Chebbo, M.R. Irving. M.J.H Collapse Proximity Indicator: Behaviour and Implications, IEE Proceedings -C, Vol. 139, No. 3, May 1992. [6] Mahmoud Moghavvemi, New Method for Indicating Voltage Stability Condition in Power System, Proceedings of IEE International Power Engineering Conference, IPEC97, Singapore, pp. 223-227. [7] Jason Yuryevich, Student Member IEEE, Evolutionary Programming Based Optimal Power Flow Algorithm, IEEE Transactions on Power Systems, Vol. 14, No. 4, November 1999. [8] Salami, M. and Cain, G., Multiple Genetic Algorithm Processor for The Economic Power Dispatch Problem, Proceeding of the genetic algorithm in engineering systems: Innovations and Applications, Conference Publication No. 414, IEE, 1995, pp 188-193. [9] I Musirin and T K Abdul Rahman, On-Line Voltage Stability Index for Voltage Collapse Prediction in Power System, presented at Brunei International Conference on Engineering and Technology 2001 (BICET2001), Brunei. October 2001. [10] Toro, V.D., Electric Power System, Prentice Hall, Englewood Cliffs, New Jersey, 1992. [11] Whats Evolutionary Programming, http://www.faqs.org/faqs/ai-faq/genetic/part2/section-3.html. [12] Leandro Nunes de Castro and Fernando Jose Von Zuben, Artificial Immune System:Part 1- Basic Theory and Applications, Technical report TR-DCA 01/99. 1999. [13] Slobodan Pajic, Dr Kevin A. Clements, Dr. Paul W. Davis and Dr Alexander E. Emanuel, Sequential Quadratic Programming Base Contingency Constraint Optimal Power Flow, Degree of Master of Science in Electrical and Computer Engineering, Worcester Polytechnic Institute, April, 29 2003. [14] Fogel , D.B. : A comparison of evolutionary programming and genetic algorithms on selected constrained optimization problems, Simulation, June,1995,pp.397-404. [15] Yao, X., Liu, Y. and Lin, G., (1999) Evolutionary programming made faster, IEEE Trans. Evolutionary Computation. vol. 3, no. 2, pp. 82-102. [16] Miller, R.H. and Malinnowski, J.H., Power System Operation, McGraw-Hill, Inc., 1994. Appendix A Table 1: Results of EP Optimization Technique Objective Function Control Variables/ Parameters of OPF Total Cost ($/h) Total Power Loss (MW) Stability Index, LQNmax Time Taken (s) Real Power of Generator Bus (MW) Injected Reactive Power (Mvar) Transformer Tap (p.u) Pg2 Pg3 Pg4 Pg5 Pg26 C1 C4 C5 C6 C9 C11 C12 C15 C19 T1 T2 T3 T4 T5 T6 T7 Total Power Loss Minimization 163.12 281.14 146.07 147.94 92.11 5.95 4.79 0.39 5.39 5.23 1.40 4.23 5.43 3.83 0.96 0.99 1.04 0.96 0.96 0.96 0.91 15449.1 12.132 0.767 11843 Voltage Stability Improvement 110.35 287.28 128.95 163.42 97.14 1.24 1.28 2.36 1.05 2.58 0.76 4.50 2.19 2.39 0.94 1.00 0.96 1.11 1.05 0.90 0.98 15523.1 14.461 0.713 6358

Principles of Diversity, Equality and Inclusion in Adult Social Care Settings

Understand the importance of diversity, equality and inclusionDiversity means understanding that each individual is unique and that we recognise our individual differences this can include race, gender, religious beliefs, age, sex orientation or any other differences. Equality means equal rights for people no matter what differences they may have and that they should all be treated fairly and that nothing should be lacking in their care and all care plans should be followed.Inclusion is based on the idea of allowing everyone to access to any service regardless their gender, religion or age and what they want and be included. Discrimination means when someone is taking less care of one person or is in less favour then someone else due to probably a disability or religion etc.Direct discrimination can occur in the work setting if the service you provide for one service user is less then the other due to their gender, age, religion, race or mental health or could be they are told they c ant do anything as they are in a wheelchair or not fit enough.Indirect discrimination can occur if someone has learning difficulty or English is not their first language and you leave them notes, which they cannot understand, or when the local authority sends leaflets for their services and they are not easy to read. 1.3Practises that support diversity, equality and inclusion to reduce the likelihood of discrimination may include encouraging everyone to say what there views are having them to listen to so that it can help to respect and help to resolve peoples differences and it helps an individual to be fully involved not only in their lives but in everyone’s else’s lives too.Know how to work in an inclusive wayThese are some of the key legislation and codes of practice relating to diversity, equality, inclusion and discrimination in adult social care settings:The Disability Discrimination Act 2005The Special Educational Needs and Disability Act 2001The Race Relations (Amendment) Act 2000Convention on the Rights of the Child (UN, 1989)The Human Rights Act 1998The Sex Discrimination Act 1975 (as amended)Employment Equality Regulations 2003You can interact with an individual in an inclusive way by making them feel comfortable and asking general questions about them. Treating them equally, be respectful and listen to them carefully, not making them feel small and encourage to ask questions and give suggestions.The ways in which discrimination may be challenged by gathering evidence, and if I witnessed discrimination is going on I would report it to the office to my supervisor or manager, I would also speak to the person that is being discriminating that they will try to sort everything out and they are not alone. Outcome 3 Know how to access information, advice and support about diversity, equality, inclusion and discrimination.Sources of information, advice and support about diversity, equality, inclusion and discrimination on government web sites that list all the current legislations in place to protect the rights of an individual. You can obtain leaflets to show service users about their rights, read books, or even can contact certain age groups, such as AGE UK who can supply materials to hand out to service user’s on discrimination, equality etc..If I think someone is being a victim of discrimination, I would report this straightaway to my manager or supervisor, even if I was in this situation I would do the same, I would also look through my policy and procedures which should include policies related to inclusion and diversity, if I encounter problems I would refer to my own policies, as to the actions to take as an employee.