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Problem Statement:

A more comprehensive “General Planning Process” could be formed by incorporating Descartes’s four rules that he developed in part two of “Discourse of Method” for applying reason to a problem. Descartes’s came up with four following rules based on his own philosophical reasoning to a problem:

1) First, not to accept anything as true unless it is evident. 2) Second, divide any problem into greatest possible number of parts for adequate analysis. 3) Third, study in order of simplicity. 4) Fourth, constantly review the progress so that nothing has been omitted.
Results:
Currently, general planning process has five steps (1. recognize the problem 2. define the problem 3. develop alternatives 4. evaluate alternatives 5. implement the best option). Using Descartes’s four rules, I would like to propose in according to following tactic: * In addition of recognizing, verify and confirm the problem in step one. * After defining the problem in step two, split the problem into many pieces in step three and analyze each of the pieces exclusively. * After developing alternatives in step four, start with the most clear-cut alternatives and proceed to more complex evaluations in step five. * After implementing the best option in step six, substantiate the whole plan in step seven.
Therefore, the resulting planning process, formed by integrating Descartes’ four rules into the “General Planning Process”, is as follows: 1. Recognize and validate the problem 2. Define the problem 3. Divide the problem into many parts & analyze each part individually 4. Develop alternatives 5. Evaluate alternatives from simplest to difficult ones 6. Implement the best option 7. Quality assurance of the plan

Discussion:
René Descartes is the father of modern philosophy. He was in Germany during the war in 1619. On his way to army, due to onset of winter, Descartes holed himself up for a day, alone in a stove-heated room. It is there where he found himself thinking about methods to properly solve or comprehend a subject. Using his mathematical brain, he formulated four rules to apply reason to issues. Over the years, these rules became very crucial step by step formulas to solve geometry and algebra problems. Over the centuries people are utilizing Descartes’s rules to unravel various difficult challenges, and few cases these rules became the template for solutions. Certainly these four rules together are a powerful tool, and unquestionably, their presence will increase the effectiveness of the general planning process. 1. Recognize and validate the problem
"The first was never to accept anything for true which I did not clearly know to be such; that is to say, carefully to avoid precipitancy and prejudice, and to comprise nothing more in my judgment than what was presented to my mind so clearly and distinctly as to exclude all ground of doubt.” (René Descartes, “Discourse on the method”)
By adding the validation component in conjunction with the recognition of the problem in step one, I believe it would craft the first planning step stronger. Though we think that recognizing a problem is obvious; in essence, it is not. Different people in a group might have different outlooks to a potential problem. For some a problem is indeed a problem, for some it may not be the actual issue or problem. Hence, it is very important to verify the subject within the group before declaring the matter a problem. This will help to ensure that no haste conclusion has been made; the problem in question is very clear and no doubt is left in anybody’s mind. Besides, if we fail in step one to correctly establish the problem, the whole planning process virtually becomes worthless. 2. Define the problem
In the original step one, one may need to state the problem in broad terms since the exact problem may not be obvious. It may lack information to define it and one can confuse symptoms with underlying causes. In improved step one, due to the addition of validating the problem, it would help out to define the exact problem, why it is a problem, and a good understanding of the facts relating to it. 3. Divide the problem into many parts & analyze each part individually
“The second, to divide each of the difficulties under examination into as many parts as possible, and as might be necessary for its adequate solution.” (René Descartes, “Discourse on the method”)
The word analysis comes from ‘analyein’, which is Greek for "to break down". Efficient way to analyze a problem is to break down the problem into pieces. The more pieces, the faster the analysis goes. Furthermore, one or few of these pieces could be too big to handle, and breaking them into sub-pieces would be required and need to keep breaking down in this way up to a point where the pieces become too small to break down any further. If we study each piece, independently from the other pieces, might have a better chance of understanding the pieces. As we analyze them, it would become obvious that each of these pieces is a complete item in itself. At the end, after analyzing each piece just add up the answers. The sum of the individual parts should add up to the original problem. In this way, analyzing each individual part separately would help to understand the problem as a whole in a very methodical approach.
Therefore, unlike the previous planning process, adding this step would help to focus more specifically on the real problem, understand the causes, and develop appropriate alternate sources by comprehensively analyzing all attributes of the problem.
4. Develop Alternatives Alternatives describe different “futures” that employ varying strategies and emphasis. This is the most creative part of the planning process. In a systematic manner, alternatives are developed based on the needs defined in the problem statement. However, as a result of the adaptation of Descartes’s rule of breaking a problem into many parts, it allows alternatives to be measured in terms of each broken parts as well. If an alternative is not going to be suitable for a sub-piece of the problem, then that alternative is not going to be a good proposition for the original piece where it derived from and as a result, not going to be a good alternative for the overall parent problem. Therefore, it helps to eliminate alternatives even before wasting any time on them and on the other hand, offer assistance to come up with solid pertinent alternatives for the problem. 5. Evaluate alternatives from simplest to difficult ones
“The third, to conduct my thoughts in such order that, by commencing with objects the simplest and easiest to know, I might ascend by little and little, and, as it were, step by step, to the knowledge of the more complex; assigning in thought a certain order even to those objects which in their own nature do not stand in a relation of antecedence and sequence.” (René Descartes, “Discourse on the method”)
The "best" alternative cannot be developed in the first run. Rather, the alternative that best meets the needs and situation will evolve as a result of the evaluation process. This step – evaluation of alternatives in order of simplicity – is promising enough to generate an effective evaluation process.
Math is built upon simple, self-evident axioms along with some rules of inference, to derive proofs of more complex propositions. Even in any real life situation, starting right off with a complicated task is not a good strategy. A new hire always need to start with something simple so that he or she can gradually ramp up their skills to do more complex work. By the time, this new employee is ready to take ownership of a complex project; the project may not be that complex to him or her as it had been when he or she started the job. Similarly, as we study thru simpler alternatives and gradually move to more complex ones, we may not find those involve alternatives as complicated evaluation anymore. One other example would be evaluating resumes for potential new hires. Start with the simple resumes; it is easy to make decisions whether to discard them or keep them. Then, move on to more experienced resumes. In this way, it is easier to make the list shorter and thus, sound judgment could be made accordingly.
By incorporating this enhanced step into planning process would make the evaluation process less strenuous, ensure that we are discarding ideas appropriately that are not applicable to the problem and provide opportunities for making sound judgment on evaluations. 6. Implement the best option
As step five would offer comprehensive evaluations, hence, it would not be that arduous to implement the best solution for the given problem. If the evaluation process is not thorough, subsequently it is challenging to make decisions on the best option. Thus, suggestions from step five would assist to perk up decisions on step six.
7. Quality assurance of the plan
“And the last, in every case to make enumerations so complete, and reviews so general, that I might be assured that nothing was omitted.” (René Descartes, “Discourse on the method”)

At the end, assuring quality of the plan (step 1 thru 6) will provide the potential for early detection of problems, reduce the cost of lost time and rework. This can save time and money from the rework and enable the ability to make decisions in a more efficient and productive manner. Revisiting the whole planning process step by step would ensure that nothing has been left out from considerations and it is, by all means, a full proof(as best as it could be), complete planning package.

Conclusion: In conclusion, extra effort to validate the subject in question as real problem would help to mitigate any probable future frustration. Consequently, defining the problem would become effortless and complete. Dissecting the problem into parts and sub-parts would ensure proper analysis of the problem; thus cultivating of alternatives would be practical. And starting from the simpler alternative analysis and steadily proceeding to more complex alternative evaluation would provide a much smoother ride on the evaluation process and would present obvious pictures for each of the evaluation. As a result, this will provide transparency to implement the best option based on the evaluations. Last, but not the least, re-visiting all the facts and scopes in each step would be very important for a successful planning process to follow.
Therefore, in a nutshell, Descartes’s four rules will boost the efficiency and effectiveness of the overall plan; and in addition, will generate a more comprehensive general planning process.

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...អាណាចក្រភ្នំ អាណាចក្រភ្នំ គស​ 50-630 ទីតាំង * ៣០០លី លិចលីនីយ(ជនជាតិចាម) * ៧០០០លី Jenan(តុងកឹង) * ឈូងសមុទ្រធំមួយ * ទន្លេរធំមួយ លិចនឹងពាយព្យគឺសមុទ្រ * ១លី=៥៧៦ម=១៧២៨គម=> 1. កម្ពុជា 2. កម្ពុជាក្រោម 3. ថៃ(ភាគកណ្តាល) រាជវង្សមាន៖ 1. លីវយី(៥០-៦៨) 2. ហ៊ុនទៀន(៦៨) 3. ហ៊ុនប៉ានហួង៖ដែលជាមេទ័ពបានប្រើល្បិចវាយក្រុងទាំង៧នឹងបានដណ្តើមអំណាចពីព្រះ បាទហ៊ុនទៀន 4. ហ៊ុនប៉ានប៉ាង៖ជាកូនហ៊ុនប៉ានហួង 5. ហ្វាន់ជេម៉ាន់៖ជាអ្នកសំលាប់សោយរាជ្យបន្តរឺក៍ហ៊ុនប៉ានប៉ាងផ្ទេរអំណាចអោយ 6. គិនចេង(២២៥)៖ត្រូវជាកូនរបស់របស់ហ្វាន់ជេម៉ាន់ពីព្រោះគាត់បានស្លាប់ពេលវាយ នៅ គិនស៊ីន 7. ហ្វានឆាន(២២៥-២៤៥)៖បានសំលាប់គិនចេងដើម្បីសោយរាជ្យបន្តដែលត្រូវជាក្មួយហ្វាន់ជេម៉ាន់នឹងត្រូវជាបងប្អូនគិនចេង 8. ហ្វានឆាង(២៤៥-២៥០)៖ជាកូនពៅរបស់ហ្វានជេម៉ាន់បានមកសងសឹកនឹងសោយរាជ្យបន្ត 9. ហ្វានស៊ីយ៉ុន(២៥០-២៨៩)៖បានសំលាប់ហ្វានឆាងសោយរាជ្យបន្ត 10. ធៀនឈូឆានតាន(៣៥៧) 11. កៅណ្ឌិន្យ(៣៥៧)៖គាត់មានកូនពីរគឺស្រីឥន្រ្ទវរ្ម័ននឹងស្រេស្ធវរ្ម័ន 12. កៅណ្ឌិន្យជ័យវរ្ម័ន(៤៤២-៥១៤)៖មានបុត្រាពីរគឺគុណវរ្ម័នជាប្អូននឹងរុទ្រវរ្ម័នជាបងក៍ប៉ុន្តែគុណវរ្ម័នជាអ្នកសោយរាជ្យដែលត្រូវជាកូនកុលប្រភាវតីជាមហេសីរីឯរុទ្រវរ្ម័នជាកូនស្នំ។ដោយមិនសុខចិត្តព្រោះខ្លួនជាបងមិនបានសោយរាជ្យក៍ប្រើល្បិចសំលាប់ប្អូនដើម្បី សោយរាជ្យម្តង។ 13. គុណវរ្ម័ន 14. ចេនឡា ចេនឡា រុទ្រវរ្ម័ន(៥១៤-៥៥៦) គស ៥៥០-៨០២ 15. ឥសីកម្ពុស្វយម្ហូវ៖ 16. ស្រុតវរ្ម័ន៖ 17. ស្រស្ធវរ្ម័ន៖ 18. វីរវរ្ម័ន៖ 19. ភវរ្ម័ន(៩០០-៩២២)៖ * ទីតាំងរបស់ចេនឡានៅត្រង់តំបន់បាសាក់តាមដងទន្លេរមេគង្គដែលច្ចុប្បន្ននៅភាគ អាគ្នេយ៍ប្រទេសឡាវ...

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General

...– – – – • – – • – • • • • – – – – • • • – – – – – – Wood Stick Holder Premium Wood Stick Holder Glow in the Dark Stick Holder Brass Burner Premium Brass Burner Aroma Ring Votive Holder NIPPON KODO INCENSE HERB & EARTH STICKS STICKS Classic STICKS CONES AFRICAN AMERICAN Family Unity – – Rhythm Sensuality Spirituality • • • • Bergamot Cedar • • • Fashion & Style • Number 4 - 100-st Number 6 - 100-st Chamomile Frankincense Jasmine Lavender Orange Patchouli Peppermint Rose Sandalwood Vanilla GONESH DIFFUSER SETS 3 fl.oz. Coconut Lime Mango Peach Sweet Apple Vanilla Cream REFILLS - 6 oz Coconut Lime Mango Peach Sweet Apple Vanilla Cream HOLIDAY TRADITIONS Number 8 - 100-st Number 10 Number 12 Number 14 Variety 1 (6,8,12) - 30 st Variety 2 (2,4,10) - 30 st MORNING STAR STICKS GONESH® EXTRA RICH Amber Apple Cider Jasmine Lavender Sandalwood Christmas Dream (Winter) Nutcracker Dance (Winter) Snowy Sensations (Winter) Holiday Memories (Winter) SCENTED REEDS & OILS REEDS OILS Black Cherry Cedarwood Cherry Blossom Cinnamon Coconut Dragon’s Blood...

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Robotics Collision Lab

...Mr. Weidenboerner Period 7 Purpose: To explore sensors and use them to knock down a box filled with bean bags without going over the edge of a precipice. Hypothesis: I think that designs with a high point of impact and and sensor placed out in front of the robot will have the best results. Group 2 | Trial | Distance from the Egde | 1 | 28 mm | 2 | 32 mm | 3 | 35 mm | 4 | 22 mm | 5 | fail | Average | 32 mm | Competion | Group | Average | 1 | 23 mm | 2 | 32 mm | 3 | fail | 4 | 7 mm | Program Flow: 1. #Include “Main.h” 2. 3. void main (void) 4. { 5. int limitswitch; 6. 7. // 0 is pressed 8. // 1 is not pressed 9. Wait (5000) 10. while (1==1) 11. { 12. limitswitch = Get DigitalInput (1); 13. if (limitswitch==1) 14. { 15. Set Motor (1.0); 16. Set Motor (10.0); 17. Wait (200) 18. } 19. else 20. } 21. Set Motor (1.-40); 22. Set Motor (10.40); 23. } 24. } 25. } Results: Group 1 cam in second place with an average of 23 mm from 5 trials. Group 2 (my group), came in third place with an average of 32 mm from the edge of the table. Group 3 came in last place with one fail and not having completed the rest of the trials yet. Group 4 came in first place with an average of 7 mm from the edge of the table. Conclusion: I think that...

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Raw Data

...@; do rep=1 to 3; do s1=1 to 3; do s2=1 to 2; input y @@; output; end;end;end; datalines; 1 1 12 13 14 15 23 22 15 16 17 18 24 15 26 25 18 19 20 21 1 2 23 10 23 20 15 33 26 13 26 23 16 12 18 36 29 16 29 26 1 3 21 15 34 23 16 19 24 18 37 26 17 17 19 22 27 21 40 29 2 1 13 18 23 14 18 21 16 21 26 17 19 20 21 24 19 24 29 20 2 2 16 16 13 25 19 21 19 19 16 28 20 18 22 24 22 22 19 31 2 3 17 24 15 17 19 21 20 27 18 20 20 26 22 24 23 30 21 23 ; proc print; run; /* lets consider A and B are random, and of course rep, samoplings ( s1 and s2 ) all are random */ proc glm; class a b rep s1 s2; model y=a b a*b rep(a*b) s1(rep*a*b); random a b a*b rep(a*b) s1(rep*a*b); run; proc varcomp method=type1; class a b rep s1 s2; model y=a b a*b rep(a*b) s1(rep*a*b); run; output: The SAS System 10:46 Wednesday, November 16, 2011 21 Obs a b rep s1 s2 y 1 1 1 1 1 1 12 2 1 1 1 1 2 13 3 1 1 1 2 1 14 4 1 1 1 2 2 15 5 1 1 1 3 1 23 6 1 1 1 3 2 22 7 1 1 2 1 1 15 8 1 1 2 1 2 16 ...

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