The delft network in the netherlands

The delft network in the netherlands 1 About the Delft network Delft is a city located in the Netherlands, having a population of 96168. It is spread over an area of 24 sq.km. (Wikipedia 2009a). The Delft University of Technology is the largest technical university in the Netherlands, with over 15,000 students (Wikipedia 2009b). Due to the significant student population, cycling is an important mode of transport. Delft is bound by freeways on all sides, except the southern, which is delimited by a highway. The hierarchy of roads in Delft is freeways, highways, main roads, and local roads. The railway line cuts across the city, running in the north-south direction from the centre of the city. A main road and a highway are the main linkages between the two freeways on the either side of the railway line. 2 Transport Problem in Delft The railway line passing through Delft is a component of one of the principal railway connections in the Netherlands, connecting Rotterdam and The Hague. The existing 2-track railway line is insufficient, and it has been planned to be upgraded to a 4-track line. However, due to lack of space to build another viaduct, and environmental problems caused by the railway line, it has been proposed to rebuild the railway line in a tunnel. 2020 is envisaged to be a typical year while the construction is in operation. Thus, Links 10486, 9873, and 9827 will be blocked for all traffic. Due to the detours which would result due to the blocked links, cyclists and cars would have to deal with increased travel times. It is anticipated that Mercuriusweg/Abtwoudse Pad or the Ruys de Berenbrouckstraat links would be used in lieu of the blocked links (Chen 2009). 3 Description of Current scenario and Alternate Scenarios 3.1 Description of the Current Situation 2003 Zones 1-7 are the external zones, whereas the rest of the zones are considered as the internal zones. The internal zones are the primary areas of concern. It has also been given that in 2003, zones 23, 24, and 25 are still under development and there is no travel demand from and to these zones (Chen 2009). 3.2 Description of the Zero-Alternative Situation 2020 By 2020, zones 24 and 25 will have been completely developed. However, Zone 23 would still not have been developed. Infrastructure has been upgraded accordingly to connect zones 24 and 25 with the rest of the city. Zone 12 remains the highest trip generating and trip attracting internal zone, as does Zone 1 amongst the external zones. 3.3 Description of Future Situation during Construction 2020 Considering the future scenario for the city of Delft in 2020 during the expansion of the rail line from 2-track to 4-track, it shall be assumed that this project will be in progress and 2020 will be a typical year. It has been given that during the expansion, Links 10486, 9873, and 9827 will be blocked (Chen 2009). The trip generation remains the same as for the zero-alternate scenario for 2020. 4 Modelling for Current Situation 2003 4.1 Trip Generation For performing the trip generation modelling function, the Zonal-based Multiple Regression model has been employed. It takes into account the linear relationships of the socio-economic characteristics of the households in the zones, which affects the trips produced and attracted for each zone (Ortà ºzar and Willumsen 1999). The following functions have been used for the trip generating model in the case of internal zones: Pi = 0.3RESIDENTSi + 0.06JOBSi + 0.03RESEARCHi + 0.03EDUCATIONi Ai = 0.05RESIDENTSi + 0.75JOBSi + 0.3RESEARCHi + 0.3EDUCATIONi Where Pi = production of zone i, Ai = attraction of zone i, RESIDENTSi = number of residents in zone i, JOBSi = number of jobs in zone i, RESEARCHi = research facility space in zone i, EDUCATIONi = amount of educational services offered in zone i. Source: Chen 2009 For the case of external zones, the numbers of trips generated and attracted have been assessed based on the traffic volume counts. These are as indicated in Appendix 1. For the internal zones, it can be seen that the variable of the number of residents living in each zone is the most dominant one affecting the number of trips produced. The variables which are most dominant for trip attraction are number of jobs, and the research facility space in that particular zone respectively. Appendix 2 indicates the trip generation for 2003, including both the internal as well as the external zones. 2003 histogram.JPGFigure 4-1: Productions and Attractions for the Current Scenario 2003 It can be seen from the Appendix 2 and figure 4-1, Zone 12 is the largest trip generator and attracting external zone. Zone 1 is the highest trip generating and attracting internal zone. 4.2 Trip Distribution and Modal Split The Gravity Model has been employed to generate the trip distribution model. This model is a type of Synthetic Model as â€Å"it estimates trips for each cell in the matrix without directly using the observed trip pattern† (Ortà ºzar and Willumsen 1999 p.159). There are three variants for the Gravity Model function, namely: Exponential Function: f(cij) = exp (-ßcij) Power Function: f(cij) = cij-n Combined Function: cnij exp(-ßcij) Singly constrained versions, in this case destination-constrained, can be produced by making Ai equal to 1, i.e. Ai = 1 and Bj= 1/?iDif(cij) The Combined Function variation of the Gravity Model is the most superior one, as it is the best fit with the actual observed values for trip length distributions of cars (Ortà ºzar and Willumsen 1999). OmniTRANS performs simultaneous modal split, for which the gravity model can be extended to the â€Å"simultaneous gravity model† which is given by: Tijv=p.Qi.Xj.Fv(zijv) Where Tijv= Number of trips from zone I to j via mode v p= Scaling factor Xj= Column Balancing Factor Fv(zijv)= Distribution function taking into account the willingness to travel by mode v given impedance z Appendix 4 indicates the traffic distribution of cars in Delft. 44566 cars have been distributed. As can be seen in Appendix 5, 8635 cyclists have been distributed the entire network of Delft. The modal split indicates that 83.77 percent of the traffic is constituted by cars and 16.23 percent by bicycles. The trip length distribution function for cars can be seen in figure 4-2. This indicates the willingness to travel to a certain distance without any impendence, such as congestion. Hence, in this case the maximum uncongested distance travelled is 10 km. Similarly, figure 4-3 indicates the trip length distribution for bicycles, which experiences its peak at 3 km. The trip time distributions for cars and bicycles have been indicated in Figure 4-4 and Figure 4-5 respectively. These functions, too, follow a similar pattern as that of the Trip Length Distribution. In the case of cars and bicycles, both, the peak is of 12 minutes. The mean trip distance for bicycles is 3.14 km and the mean trip time is 14.22 minutes. Similarly, for cars, the mean distance is 7.59 km and time is 11.12 minutes. Intra-zonal car trips constitute only about 0.57 percent of the total number of trips made by cars, and those made by bicycles constitute about 16.55 percent of the total number of bicycle trips. 4.3 Traffic Assignment 4.3.1.1 Assignment for Cars The General Equilibrium technique of traffic assignment has been used for cars. The condition as given by Wardrop is that â€Å"Under equilibrium conditions, traffic arranges itself in congested networks in such a way that no individual trip maker can reduce his path costs by switching routes† (Ortà ºzar and Willumsen 1999 p.303). Under this traffic assignment model, costs are all perceived in the same way by the trip makers, and hence Stochastic effects are not considered. The following links have the largest traffic flow (for a single direction) of about 7064 cars assigned: 10972, 10973, 11289, 11427, 11428, and 11477. Figure 4-6 represents the traffic assignment for cars in 2003. The colours of the bands, in the graph, indicate the V/C Ratio and the width indicates the traffic load. It reflects that the main road, the east and west freeways crossing the railway are suffering from V/C ratios greater than 1, which requires attention. 4.3.1.2 Assignment for Bicycles The Stochastic Method has been employed for the traffic assignment model for bicycles. This method is superior to the All-Or-Nothing Method, as it takes into account the diversity in the road users perceptions of distance, travel time, generalised costs; and thus considers alternate routes to the best-route choice, given by the All-Or-Nothing technique. This is a suitable model for the traffic assignment of bicycles as this technique does not take into account the congestion effects, which is not calculable since capacities for bicycles are not specified. Link 10850 has been assigned the maximum number of bicycle trips for a single direction, which is 941 trips. Figure 4-7 represents the assignment of bicycles in 2003. Most of the trips are confined to the internal zones. 5 Modelling for Future Situation 2020 The modelling stages for the future scenarios of 2020 will remain the same till the Traffic Assignment Stage, which would differ based on the blocked links for the future construction scenario of 2020. 5.1 Trip Generation The Zonal-based Multiple Regression model has been employed. The functions are the same as those for 2003. However, forecasts for the number of residents, jobs, and the research facility space and education building space in 2020 are different from the current year. Also, it has been given that the productions and attractions generated by the external zones is to be assumed to grow by 15 percent from 2020 to 2003 (Chen 2009). The above figure 5-1 illustrates that Zone 1 still remains the highest trip production and attraction external zone; and Zone 12 continues to remain the highest trip producing and attracting internal zone. The same is reflected through Appendix 3. 5.2 Trip Distribution and Modal Split The Gravity Model has been employed for the trip distribution. A total of about 54380 cars have been distributed, and about 10413 bicycles. The modal split for 2020 demonstrates that about 83.5 percent of the trips would be by cars, and the remaining 16.5 percent by bicycles. For cars, the intra-zonal trips constitute about 0.54 percent, whereas for the bicycles, intra-zonal trips constitute about 15.71 percent of the trips. Trip length distribution function (indicated in Figure 5-2 and 5-3) and the trip time distribution functions (indicated in Figure 5-4 and 5-5) have been generated. The maximum uncongested distance remains the same for both cars and bicycles, as in 2003, as also the maximum uncongested time in the case for cars. For bicycles, the maximum time has reduced to 8 minutes. The mean trip distance for bicycles is 3.26 km and the mean time is 14.75 minutes. Similarly, for cars, the mean distance is 7.56 km and time is 11 minutes. 5.3 Traffic Assignment for Zero-Alternative Situation 5.3.1 Traffic Assignment for Cars The General Equilibrium model has been employed. The following links have the maximum numbers of cars assigned, i.e. about 8346 cars, to them for one direction: Links 10972, 10973, 11289, 11427, 11428, 11477, and 11478. Figure 5-6 represents the assignment for cars. The colours of the bands, in the graph, indicate the V/C Ratio and the width indicates the load of traffic. The freeways continue to have high V/C ratios, as well as the main roads crossing the railway. 5.3.2 Traffic Assignment for Bicycles For the traffic assignment modelling for bicycles, the Stochastic Method has been used again. Link 10850 has been assigned the maximum number of bicycle trips (114 trips). Figure 5-7 represents the bicycle assignment. 5.4 Traffic Assignment for Future Construction Situation In the future situation during construction, the decision to upgrade the railways from two tracks to four tracks has been made. This would result in the closing of Links 9827, 9873, and 10486. 5.4.1 Traffic Assignment for Cars It has been calculated that links 11283, 11407, 11463, and 11464 have the maximum load, of 10723 cars in one direction. Figure 5-8 represents the car assignment considering future construction. The cross-railway link south of zone 17 experiences a greater load, whereby there is a reduction in the northern cross-link. 5.4.2 Traffic Assignment for Bicycles The Stochastic model employed for assigning the bicycle traffic that Link 10452 the maximum load, in one direction, of 1446.54 bicycles. Figure 5-9 represents the assignment for bicycles. 6 Analysis 6.1 Trip Generation Amongst the internal zones, which are of primary concern, Zone 12 is the zone which remains the highest trip producing and attracting zone. This is supported by the fact that Zone 12 has the highest number of residents living in it, and the maximum number of jobs existing in this zone. This zone is located at the heart of the city, adjacent to the railway line and the main road connecting the two freeways. All the internal zones have experienced a growth rate for the number of trips generated and produced by about 11 percent. Zone 1 also remains the highest trip producing and attracting external zone. This may be accounted by the fact that Zone 1 is directly connected to Delft by the railway line, and thus could perhaps be an important junction or location. 6.2 Trip Distribution and Modal Split The trip distribution can be reflected through the study of the matrices given in Appendix 4 to 7. For 2003, the maximum number of car trips has been of the nature Internal-to-External, with the most dominant one being from Zone 15 to Zone 1. This has not changed for 2020. For 2003 and 2020, the most dominant character of bicycle trips is Internal-to-Internal, with maximum trips being made within Zone 12. This is as should be expected, since long distance travel by bicycles is not likely to be made except in rare circumstances. The maximum number of bicycle trips may also be attributed to the fact that Zone 12 is the Delft City Centre. The maximum growth (4.8 times) for car trips has been seen for the pair Zone 7-Zone 1, and the maximum for bicycles (0.15 times) has been for the pair Zone 5-Zone 12. On studying the zone-to-zone average travel distance and time, it can be seen from Appendix 8 and 9 that the maximum increase for trip distance has been from zone 7 to 15 (46.86 percent) and maximum increase in time has been for the pair zone 18 to 22 (48.67 percent). The maximum increase (48.78 percent) in cost has been experienced for zone 11 to 22. The modal split indicates a marginal change from 2003 to 2005, whereby there is a decrease from approximately 83.77 to 83.5 percent for cars. Intra-zonal trips made in 2020 have experienced a fall from 2003. This may indicate greater travel distances and time, and thus greater generalized costs in the future. 6.3 Traffic Assignment On comparing the figures indicating the traffic assignments for the three scenarios, it can be seen that the maximum car trips load remains on the freeways defining Delft on the eastern and western sides. The main difference can be seen between the zero-alternative and construction situation for 2020. Due to the blocked links, car traffic has been assigned to the links 1164, 11645, and Westvest-Hooikade particularly have experienced a significant increase, whereas the Westlandseweg links have experienced a decrease in the load of trips. Also, as was expected, there was an increased use of the Ruys-de-Berenbrouckstraat, and Abtwoudse links. However, the Mercuriusweg saw a decrease in the traffic load as compared to the zero-alternative scenario, which goes against as was anticipated. In the case of assigned bicycle trips, due to the blocked links, the Hof-van-Delftlaan link has seen a substantial increase in the traffic load. The share of the railway crossing traffic has been seen to change for all the three scenarios. This has been indicated in figure 6-1. There is a decrease in the share from 2003 to the Zero-Alternative scenario. However, comparing the future construction scenario with the Zero-Alternative, there has been an increase in the share, for both cars and bicycles. 7 Conclusions Zones 1 and 12 being of prime importance, also supported by their connectivity will continue to dominate as the zones attracting and generating the maximum traffic. Since maximum bicycle traffic load is concentrated in Zone 12, measures may be taken to restrict the entry of cars in this area so as to ensure a more safe environment, which would even benefit the households, as the maximum percentage are located in this zone. Increased generalised costs must be taken into account, based on the above analysis. Links which are experiencing greater traffic loads due to construction works have been identified, and relief measures for these should be planned, particularly for the freeways on the eastern and western side of the city. 8 Strengths and Weaknesses of OmniTRANS The strength of OmniTRANS is that it helps in the rapid and accurate transport modeling procedures. Also, the data can be very easily examined on the transport network map, rather than just being confined to tables and numbers, which makes analysis tedious. Also, a number of variables can be studied, which can be further sorted out based on the direction for any particular link. The weaknesses could be cited as only being able to employ the use of the Simultaneous Gravity Model being available for trip distribution stage. Also, only limited types of traffic assignment models can be performed (such as Stochastic, All-or-Nothing, and Equilibrium). Public transport modelling is also not performed by the software (OmniTRANS 2009). References CHEN, H. 2009. Handout: Coursework Description, lecture notes distributed in TRAN5020 Principles of Transport Modelling. University of Leeds, 3 November 2009. OMNITRANS. 2009. Whats New in OT5 [online]. [Accessed on 1st December 2009]. Available from http://www.omnitrans-international.com/resources/brochures/whats%20new%202008.pdf. ORTÚZAR, J. WILLUMSEN, L.G. 1999. Modelling Transport. West Sussex: Wiley. WIKIPEDIA. 2009a. Delft [online]. [Accessed on 10 November 2009]. Available from: http://en.wikipedia.org/wiki/Delft. WIKIPEDIA. 2009b. Delft University of Technology [online]. [Accessed on 10 November 2009]. Available from: http://en.wikipedia.org/wiki/Delft_University_of_Technology.

tempcolon Comparing Language in Shakespeares Tempest and Aime Cesaire

Colonial Language in Shakespeare's The Tempest and Aime Cesaire's A Tempest      Ã‚  Ã‚   Language and literature are the most subtle and seductive tools of domination. They gradually shape thoughts and attitudes on an almost subconscious level. Perhaps Gayatri Chakravorty Spivak states this condition most succinctly in her essay "The Burden of English" when she writes, "Literature buys your assent in an almost clandestine way...for good or ill, as medicine or poison, perhaps always a bit of both"(137). By examining Shakespeare's "The Tempest" and Cesaire's "A Tempest", the diabolic and diagnostic functions of language and literature can be explored. Both plays place characters who are foreign to each other in equally unknown and foreign environments. Shakespeare allows Prospero the sorcerer to dominate his foreign environment and all who inhabit it, while Caliban in Cesaire's play uses the foreign language of his master, Prospero, to stage an open revolt. Placed within a post-colonial context, Cesaire ultimately expands upon the actions and characters create d by Shakespeare in order to posit a plausible modern explanation for the role of language and literature in the progression from fictional to actual, all too real, colonies.   Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚   Slavery is a central issue in both plays, especially in defining the relationship between Prospero and Caliban. Prospero, a European of high social and intellectual stature, is placed within an unfamiliar and hostile environment. Caliban befriends Prospero and gives him the necessary skills to survive. In return, Prospero teaches Caliban an European language. Ironically, this knowledge of language provides the basis for both slavery and revolt. Though physically enslaved because of an attempt... ...le it may be impossible to separate the poisonous properties of language and literature from the medicinal ones, Cesaire seems to attempt to identify the former and espouse the latter. Though the scope and influence of language and literature may be wider than that of colonialism, the same essential hurtful and hopeful paradox rests at the core of each concept.   Works Cited Cesaire, Aime. A Tempest. Trans Richard Miller, New York: Ubu Repertory Theatre Publications, 1992. Shakespeare, William. "The Tempest." Rpt in William Shakespeare: The Complete Works. Ed. Peter Alexander, London: Collins Clear Type Press, 1989. Spivak, Gayatri Chakravorty. "The Burden of English." Orientalism and the Postcolonial Predicament: Perspectives on South Asia. Carol A. Breckinridge and Peter van der Veer Eds.   Philadelphia: U. of Pennsylvania Press, 1993. 134-57.

Emotions Paper Essay

Emotions are personal experiences that are hard wired into every single human being on the planet. Yet, somehow people seem to have little control over them. After studying all the different kinds of emotions people can feel, I did a three day inventory of the emotions I experienced. In this paper, I will discuss how hard or easy it is to identify emotions and the methods I used to identify my emotions. I will analyze the types of emotions I felt and whether they were primary or secondary. Were they the typical emotions I experience every day? Do I give in to any emotional fallacies? How freely I express my emotions and what I have learned from doing this exercise. During the three day inventory, I sometimes had a hard time identifying the emotion I was feeling. I often had to refer back to the list of different emotions. While I looked at the list of emotions, I tried to think about what I was feeling physiologically during that time. I examined my actions nonverbally and then cognitively I put a label on the emotion. For example, on the first day of my inventory I got woken up before eight in the morning by uncertain noises coming from my bathroom. When I opened the door to the bathroom, I found both of my kids laughing and splashing in the toilet using a toilet brush. The first emotion I realized I felt at the time was annoyance that somebody woke me up so early. I recognized that due to cognitive interpretation. The second emotion I felt after opening the door to the bathroom was anger at my kids for playing in my bathroom even though they know better. I cognitively new it was anger because nonverbally I raised my voice, physiologically my heart rate and breathing increased, and after I punished them I realized my hands were shaking. All of those signs led me to believe that I was annoyed and angr y. Within three days I experienced eleven different emotions. Five of those emotions were primary and six of the emotions were secondary. Determination, one of the secondary emotions I experienced was facilitative, because being determined made me want to try harder to finish the task I was doing. For example, when I was trying to do homework with my kids I was determined to get it done, so I kept going until it was completed. Fear and anger were two emotions I experienced that are debilitative because I had a hard time controlling my rational behavior. For example, I experienced fear because a huge dog was loose at the park. For a minute I just froze and stared at it,  not doing anything until my son saw it and started screaming. That got me to start thinking again and we left the park. The emotion of fear became debilitative for me because the dog was loose with no owner. If the dog was loose but had somebody with him my emotion of fear wouldn’t have been as intense. To my surprise the emotions I experienced in the three days were mostly intense. Out of the eleven emotions I experienced, only three were mild. For example, on day one I felt happy about taking the kids to grandpa’s house, but I wasn’t so excited that I was jumping up and down. It was a mild happiness. An example of my intense emotion is when I got angry. On day one in the evening of day one my kids would not listen when told multiple times to pick up their toys. It got to the point that I raised my voice at them and my hands started shaking. Then I had to call my husband to intervene because I needed time to calm down. The emotions I experienced during the inventory were mostly typical. However, there were a couple of emotions that I don’t experience often. One of the emotions I don’t usually experience is being exhausted. Typically, I don’t feel exhausted, especially in the afternoon. After examining why I felt that way I realized it’s because I was starting to get sick. The next day, I felt another emotion I typically don’t feel or experience often. I was trying to do homework and I felt miserable because I was nauseas and I had a fever. Typically, when I do homework I feel motivated or excited that I am almost done. That same day in the evening I felt helpless which is also out of the ordinary for me. I felt that way because I had a ton of stuff I needed to do and I couldn’t do any of it. My typical emotions during the day are happy, irritated, annoyed, proud, loved, determined, scared, and excited. Studying the subject of emotions and doing this inventory made me realize I have some fallacies I tend to fall into almost every day. The first fallacy that applies to me is â€Å"fallacy of approval.† For example, when I go somewhere with my kids or husband and I have to choose what I am going to wear. I realized that a lot of the time it takes me up to an hour to decide because I want people to approve of what I am wearing. The other fallacy that applies to me is â€Å"fallacy of causation.† For example, when my kids are playing the noise they make sometimes irritates me, because I want it to be quiet in the house. So, I say to them â€Å"you guys are irritating me,† instead  of taking responsibility and saying â€Å"I am getting irritated with the loud noise.† In my opinion I don’t express my emotions freely. No one has ever told me that I am easy to read or that my emotions show on my face. When in public I only show emotions that are appropriate. If I am angry at the person or upset with someone I tend to hide my emotion until I feel comfortable telling them. Most freely I express my emotions at home, because that’s where I feel most comfortable. The least freely where I express my emotions are out in public, because of the fallacy of approval. It matters what people think of me. Doing this exercise has taught me that there are different kinds of emotions. Primary emotions are emotions that are hard wired into human beings, and secondary emotions make up primary emotions. I learned how to analyze what emotion I am feeling. I don’t think I have ever done that consciously before. It made me really think about my reactions, what’s happening in my body, and how I am feeling. I learned the valence of emotion. One emotion that you would usually think is negative can be both positive and negative. Also, I learned the word fallacy and how it relates to emotions. Last, I learned the difference between emotion and mood which I before I thought was the same thing.

Essay on Religion in Jane Eyre by Charlotte Bronte

Religion in Jane Eyre by Charlotte Bronte In Jane Eyre Charlotte Bronte intertwines various religious ideas in her mid-nineteenth century English setting. Throughout the novel, Jane Eyre blends various religious insights which she has learned from different sources. While Jane was young, she had only a Biblical textbook outlook on life combined with the miserable emotional conditions of her surroundings. This in turn led to Jane being quite mean with Mrs. Reed. When Jane eventually goes off to Lowood and meets Helen Burns, she learns of her religious philosophy far more than the words would mean. Over the course of many years Jane then applies the basis of Helens religious philosophy and adjusts it for herself in relation to the†¦show more content†¦Helen Burns is probably the turning point of life for Jane, although we dont see it happening immediately. When Jane explains to Helen what she feels about being good she says, you are good to those who are good to you. It is all I ever desire to be. If people were alway s kind and obedient to those who are cruel and unjust, the wicked people would have it all their own way. Helen tells the little untaught girl, about life: It is not violence that best overcomes hate - nor vengeance that most certainly heals injury, and Love your enemies; bless them that curse you; do good to them that hate you and despitefully use you. Jane is incredibly confused by this statement; she cannot understand how she could ever love someone she hates so dearly, as in this case Mrs. Reed and her son, John. So Jane quickly responds with, Then I should love Mrs. Reed, which I cannot do: I should bless her son John, which is impossible. Although Jane does not yet comprehend Helen Burns words at this time, she will eventually learn the basis of what Helen is saying later in adult life; as shown when Jane returns of to Gateshead to Mrs. Reed?s deathbed showing forgiveness and compassion. 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