...Rate = k[NO]2[H2] (b) 0.005 = k(0.075)2(0.400) 0.005 = k(2.25 x 10-3) k = 2.22 M-2 s-1 Question 3 Temperature (K) | Rate constant (M/s) | 1/T (K-1) | ln k | 573 | 2.91 x 10-6 | 0.00175 | -12.75 | 673 | 8.38 x 10-4 | 0.00149 | -7.08 | 773 | 7.65 x 10-2 | 0.00130 | -2.57 | Plot of ln k against 1/T (K-1) Slope of graph, m = -7.08-(-12.75)0.00149-0.00175 = 5.67- 0.00026 = 21807.69 Using Arrhenius equation, m = - Ea8.314 J/Kmol 21807.69 = - Ea8.314 J/Kmol Ea = 181 kJ/mol Question 4 (a) Rate of reaction of NO is second order. Rate of reaction of H2 is first order. Total rate of reaction = third order. (b) If [NO] is doubled, the rate of reaction quadruples. (c) If [H2] is halved, the rate of reaction is halved. Question 5 Initial concentration = Ao Final concentration = A Time, t = 65s – 45s = 20s Use ln A = -kt + ln Ao ln (8.70 x 10-3M) = - (k)(20s) + ln (7.30 x 10-2M) -4.744 = - (k)(20s) + (-2.617) 2.127 = (k)(20s) k = 0.106 s-1 Question 6 The rate law is determined based on the slow reaction since the fast reactions are not in equilibrium. ∴ Rate = k[H2O2][I-] Question 7 (a) Rate = k[A]m[B]n Find m and n. 2 x 10-3 = k(0.10)m(0.10)n ------- (i) 8 x 10-3 = k(0.20)m(0.10)n ------- (ii) (ii) ÷ (i) 4 = 2m ∴ m = 2 8.0 x 10-3 = k(0.20)m(0.10)n ------- (i) 8.0 x 10-3 = k(0.20)m(0.20)n ------- (ii) (ii) ÷ (i) 1 = 2n ∴ n = 0 Rate = k[A]m[B]n = k[A]2[B]0 ...
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...in team games, it can be hard to figure out if a team members’ character attribute development has been successful directly from game logs. Additionally, it can also be hard to figure out how the performance of one team member affects the performance of another. In this paper, we present a data-driven method for automatically discovering patterns in successful team members’ character attribute development in team games. We first represent team members’ character attribute development using time series of informative attributes. We then find the thresholds to separate fast and slow attribute growth rates using clustering and linear regression. We create a set of categorical attribute growth rates by comparing against the thresholds. If the growth rate is greater than the threshold it is categorized as fast growth rate; if the growth rate is less than the threshold it is categorized as slow growth rate. After obtaining the set of categorical attribute growth rates, we build a decision tree on the set. Finally, we characterize the patterns of team success in terms of rules which describe team members’ character attribute growth rates. We present an evaluation of our methodology on three real games: DotA,1 Warcraft III,2 and Starcraft II.3 A standard machine-learning-style evaluation of the experimental results shows the discovered patterns are highly related to successful team strategies and achieve an average 86% prediction accuracy when testing on new game logs...
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...UNIT 17 Objectives INVENTORY MANAGEMENT Upon completion of this unit, you should be able to: understand the meaning of inventory and identify inventory related cost parameters learn about various types of inventory policies appreciate the role of selective inventory management know the exchange curve concept for aggregate inventory planning get a feel of some mathematical models of inventory analysis perform sensitivity analysis on a type of model compute safety stocks understand the problems of slow moving items appreciate the role of computers in inventory control have a brief idea about recent developments in inventory management. Structures 17.1 17.2 17.3 17.4 17.5 17.6 17.7 17.8 17.9 17.10 17.11 17.12 17.13 17.14 Introduction to Inventory Systems Functions of Inventory Classification of Inventory Systems Selective Inventory Management Exchange Curve and Aggregate Inventory Planning Deterministic Inventory Models Probabilistic Inventory Models Inventory Control of Slow Moving Items Recent Developments in Inventory Management Concluding Remarks Summary Key Words Self-assessment Exercises Further Readings 17.1 INTRODUCTION TO INVENTORY SYSTEMS Concept of Inventory . Inventory' may be defined as usable but idle resource'. If resource is some physical and tangible object such as materials, then it is generally termed as stock. Thus stock or inventory are synonymous terms though inventory has wider implications. Broadly speaking, the problem of inventory management is...
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...imbalance of biochemical cycling. In reality anything that the can cause damage to our natural environment, change the imbalance, or that our natural environment is not familiar with can damage the balance. Cultural eutrophication and fish kills are mainly caused due to the lack of oxygen also known as anoxia. Although eutrophication is naturally occurring, it is a slow and inevitable process. Yet human when humans speed up that process by adding pollutants into our ecosystem, this will cause the death and premature aging of bodies of water due to the contamination with sewage, chemicals, and fertilizers. This will then cause the slow death of that body of water due to anoxia killing all living things within it. The comparison between opportunistic versus equilibrium populations are as follows: opportunistic species use the “r-strategy” and the equilibrium uses the “k-strategy”. In the Opportunistic species, the “r” defines the species instrinsic rate of increase. This species produces millions of sperms and eggs mainly because only a minimal amount will actually become offspring. Whereas, in the equilibrium species, the “k” defines the carrying capacity of the environment. This species, in contrast, produces a small amount of sperm and eggs, thereby, producing less offspring. Both species also have different mannerisms in which they care for their offspring. Where opportunistic spawn and fertilize their eggs in water and equilibrium nest their eggs and brood over them. Examples...
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...Slow Diffusion of Information and Price Momentum in Stocks: Evidence from Options Markets Zhuo Chen∗ Andrea Lu† September 6, 2014 Abstract This paper investigates the source of price momentum in the equity market using information from options markets. The empirical results provide direct evidence of the gradual information diffusion model in Hong and Stein (1999). Consistent with their theory, we show that a successful identification of stocks’ information diffusion stage helps explain momentum profits. We are able to enhance momentum profits by longing winner stocks with higher growth (and shorting loser stocks with larger drop) in call options implied volatility. Our empirical strategy generates a risk-adjusted alpha of 1.8% per month for a hedged winner-minus-loser portfolio over the 1996–2011 period, during which the simple momentum strategy fails to perform. The results are stronger and clearer if we use call options compared with put options, which are consistent with managers’ tendency to reveal good news and hide bad news. Our results are robust to transaction costs, choice of options’ moneyness, elimination of implied volatility persistence, and choice of options’ time-to-maturity. Finally, our results are not driven by existing stock-level characteristics, such as size, trading volume, and analyst coverage. JEL Classification: G10, G11, G12, G13 Keywords: Momentum, Implied Volatility PBC School of Finance, Tsinghua University. Email: chenzh@pbcsf.tsinghua.edu.cn...
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...think of it as the size of the economy. Usually, GDP is expressed as a comparison to the previous quarter or year. The current trends and statistics of the GDP are made up of the economic trends. When looking for trends they look at the unemployment rate the, the exchange rate, and how it’s affecting the stock markets. They can also look at consumer spending generally if the GDP is high then the economy is doing well (Investopedia ULC, 2011). When business make decisions using the GDP, they are looking for economic trends that will coincide with there business type. For example when auto companies forecasted higher gas prices they started to produce fuel efficient cars, and trucks, because consumers want more miles per gallon. Investors use the GDP as a forecasting tool to make important investments decisions with businesses. Investors look at GDP growth to see if the economy is changing rapidly so they can adjust their asset allocation. In addition, investors compare country GDP growth rates to decide where the best opportunities are. GDP is measured by the BEA quarterly. The BEA revises estimates as it receives better data throughout the next quarter. To compute economic growth, it compares each quarter to the previous one (Kimberly Amadeo, 2011). How does the GDP affect us? If the GDP growth rate is speeding up, the Fed may raise interest rates to stem inflation. In this case, you would want to lock in a fixed-rate mortgage, because you know that an...
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...search algorithm makes k-NN computationally tractable even for larger data sets, dealing with as high as 60000 data sets in our case. * KNN algorithm is analytically tractable. * KNN algorithm is highly adaptive to local information. We have used Euclidean distance metrics in our KNN algorithm to estimate the closest data points. Thus the algorithm is able to take full advantage of the local information in the training datasets to form a highly nonlinear, highly adaptive decision boundaries for each data point. * KNN algorithm is easily implemented in parallel. For each data set to be evaluated, it checks against the training data-set for the k nearest neighbors around the data set to be evaluated. Since each of these data set is independent of the others, the search and validation can be implemented in parallel. * Choosing higher value of K will yield smoother decision regions and provide probabilistic information. The disadvantages of KNN algorithm are: * KNN algorithm is computationally very intensive as it needs to search through training datasets (of size 60000) to find the nearest neighbors and determine the closest ones for each of the testing data sets which needs to be classified. * Since the datasets is huge (as we are dealing with 60000 training sets), storage will be a concern as we need to store all the data sets in training sample and use when we need to validate the test datasets. * As dimensionality of k increases, it becomes...
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...United States GDP (Gross Domestic Product) Growth Rate grew only 0.1%. This type of growth makes our economy look worse than it really is performing. There were many different factors that helped hold back the economic growth. One major factor was weather. Weather actually decreased consumption of housing and goods, although it did boost spending on utilities. During 2013, exports to China and business investments on aircraft were very high. A partial pullback in these areas also contributed to an abysmal GDP Growth Rate. The stockpiling of inventories dropped by the extensively as they were moving at unsustainable rates at the end of 2013. U.S. GDP only grew in 2013 at a rate of 1.9%. There are many factors that will only allow slow growth in the GDP. These factors or forces are the following: • Washington’s attempt to cut government spending. • High structural unemployment. • Personal consumption is at 70% of the current GDP. There are a few forces that are worrying analysts about the growth of the United States GDP growth rate. These forces while they will only happen in certain scenarios will also weigh on the GDP growth rate. Below are the forces that and what their effects are on the GDP growth rate. A cutback on the quantitative easing by the Federal Reserve is huge fear of analysts. The cutback will result in higher interest rates on loans and mortgages making getting a loan for individuals and business more expensive. The key here is that this will...
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...Queuing Theory Queuing Theory • Queuing theory is the mathematics of waiting lines. • It is extremely useful in predicting and evaluating system performance. • Queuing theory has been used for operations research. Traditional queuing theory problems refer to customers visiting a store, analogous to requests arriving at a device. Long Term Averages • Queuing theory provides long term average values. • It does not predict when the next event will occur. • Input data should be measured over an extended period of time. • We assume arrival times and service times are random. • • • • Assumptions Independent arrivals Exponential distributions Customers do not leave or change queues. Large queues do not discourage customers. Many assumptions are not always true, but queuing theory gives good results anyway Queuing Model Q W λ Tw Tq S Interesting Values • Arrival rate (λ) — the average rate at which customers arrive. • Service time (s) — the average time required to service one customer. • Number waiting (W) — the average number of customers waiting. • Number in the system (Q) — the average total number of customers in the system. More Interesting Values • Time in the system (Tq) the average time each customer is in the system, both waiting and being serviced. Time waiting (Tw) the average time each customer waits in the queue. Tq = Tw + s Arrival Rate • The arrival rate, λ, is the average rate new customers arrive measured in arrivals per time period....
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...Bio present speech (Kevin = K , Tasha = T) All: good afternoon. K : Lets get started. We are group 3 and our topic is Chronic myeloid leukemia (CML). My name is Kevin.(I am … x 8) T: Here are our presentation rundown. (show 5-8 seconds) And now, Gerard and Jerry will talk about Discovery of Philadelphia chromosome and Molecular mechanisms of the initiation of Philadelphia chromosome-induced CML. … K: Tsaha, after hearing the causes, symptoms, treatments as well as their limitations, anymore to share? T: it seems that you're quite curious about cml. Why not tell more about how cml is diagnosed? K: Sure. From the clinical and laboratory perspective, here are some poor prohnosis characteristics. •Older age •Anemia •Poor performance status •Symptomatic presentation •Enlarged liver (Hepatomegaly) •Enlarged spleen (Splenomegaly) •Deficiency of blood platelets → bleeding into tissues → bruising → slow blood clotting after injury T: Let me add some complement. From the therapy associated perspective, here are some poor prohnosis characteristics. •Longer time to hematologic remission with myelo-suppression therapy •Short duration of remission •High total dose of hydroxyurea or busulfan •Poor suppression of Ph-positive cells by chemotherapy or interferon alfa therapy K: lets move on to the diagnosis part. We can obtain blood samples and bone marrow samples and undergo observation...
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...this manual or the other documentation provided with your Nikon product are trademarks or registered trademarks of their respective holders. AVC Patent Portfolio License This product is licensed under the AVC Patent Portfolio License for the personal and non-commercial use of a consumer to (i) encode video in compliance with the AVC standard (“AVC video”) and/or (ii) decode AVC video that was encoded by a consumer engaged in a personal and non-commercial activity and/or was obtained from a video provider licensed to provide AVC video. No license is granted or shall be implied for any other use. Additional information may be obtained from MPEG LA, L.L.C. See http://www.mpegla.com. Introduction First Steps Basic Photography and Playback: A (Auto) Mode More on Shooting More on Playback Editing Pictures Movie Recording and Playback Connecting to Televisions, Computers and Printers Basic Camera Setup Caring for the Camera Technical Notes and Index i For Your Safety To prevent damage to your Nikon product or injury to yourself or to others, read the following safety precautions in their entirety before using this equipment. Keep these safety instructions where all those who use the product will read them. The consequences that could result from failure to...
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...Internet Abuse in the Workplace Internet abuse in the workplace is an issue that impacts employers in various ways including time, money, and productivity. Monitoring websites have found “that more than 50% of employees use the Internet for personal reasons during an average work day” (Young, 2010, p. 34). Research shows that employees are spending about 3.24 hours on non-work related websites in an average day (Young, 2011). Internet abuse issues are so prevalent that employers are faced with how to enforce internet policies and finding ways to restrict and manage this problem. This essay will address how Internet abuse impacts productivity, customer service skills, draining on network resources and legal liabilities. Productivity and customer services suffer when personal internet use is abused during work hours. Internet abuse distracts employees and may reduce productivity and customer service. In result, this can lead to a company’s reputation being damaged or even destroyed (Young, 2010). Employees that surf the internet can slow down response time in assisting customers or fail to meet deadlines and may fail to complete a task effectively (Young, 2010). If these problems are not addressed, they can cause an employee to produce unsatisfactory products or expectations which overtime can hurt or destroy the employer’s creditability. To help prevent an employer from losing their creditability employers are becoming proactive and implementing policies that help employees...
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...production of a product divided by its stoichiometric coefficient. A 0.3187 M 0.3629 M 1min rate of consumption of A = = = 8.93 105 M s 1 t 8.25 min 60 s rate of reaction = rate of consumption of A2 = 8.93 105 M s 1 4.46 105 M s 1 2 1B (E) We use the rate of reaction of A to determine the rate of formation of B, noting from the balanced equation that 3 moles of B form (+3 moles B) when 2 moles of A react (–2 moles A). (Recall that “M” means “moles per liter.”) 0.5522 M A 0.5684 M A 3moles B rate of B formation= 1.62 104 M s 1 60s 2 moles A 2.50 min 1min 2A (M) (a) The 2400-s tangent line intersects the 1200-s vertical line at 0.75 M and reaches 0 M at 3500 s. The slope of that tangent line is thus 0 M 0.75 M slope = = 3.3 104 M s 1 = instantaneous rate of reaction 3500 s 1200 s The instantaneous rate of reaction = 3.3 104 M s 1 . (b) At 2400 s, H 2 O 2 = 0.39 M. At 2450 s, H 2 O 2 = 0.39 M + rate t At 2450 s, H 2 O 2 = 0.39 M + 3.3 10 4 mol H 2 O 2 L1s 1 50s = 0.39 M 0.017 M = 0.37 M 2B (M) With only the data of Table 14.2 we can use only the reaction rate during the first 400 s, H 2 O 2 /t = 15.0 104 M s 1 , and the initial concentration, H 2 O 2 0 = 2.32 M. We calculate the change in H 2 O 2 and add it to H 2 O 2 0 to determine H 2 O 2 100 . H 2 O 2 = rate of reaction of H 2 O 2 t =...
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...Kill Bill (2001) have emerged showing women in a new light. Similarly, films such as Gladiator (2000) and Finding Nemo (2003) have showed a softer side of males that is rarely shown on screen. So what is have the film industry progressed towards a fairer and more accurate of gender in movies? Literature Review In recent studies, Gilpatric (2010) uses violence as a tool of measure to demonstrate that movies are still depicting gender stereotypes in violent female action character. This is backed by Sternheimer (2003) as she argues that even though females appear to be independent, they are still dependent on males which reinforces traditional gender stereotype. Nevertheless, there has been a noticeable trend that there is a fairer portrayal of gender in films in recent years (Nelmes, 2007). Such a trend is evident in Finding Nemo as Brydon (2009) claim that even Disney, the champions of gender stereotype, has the capacity to steer away from traditional gender roles. Heroines in films have “cross[ed] variable gender boundaries” (Brown, 2003, p. 52). In another article, Brown (2003) introduced the concept of dominatrix which the use of the strengths of masculine and feminine...
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...1.0 Super Capacitor Lab 2.0 Flywheel Lab 3.0 Introduction to Labview 1.0 SUPER CAPACITOR LAB The aim of this task is to observe charge and discharge characteristics of a super capacitor, after that to compare achieved and theoretical characteristics. 1. 1: Recording the Supercapacitors Charge Characteristic PANASONIC - EECHW0D306 - CAPACITOR, RADIAL, 30F, 2.3V Farnell 1305076 Using the battery discharge test PCB setup the charging experiment as shown below but DO NOT connect the capacitor. The current may exceed 500 mA so SET THE AMMETER TO THE 10A RANGE (using the correct terminal). Turn on the 5V supply and check the voltmeter reading is between 2.0V & 2.3V, record this value. If the voltage is correct switch off the supply and connect the capacitor observing the correct polarity. Now Turn on the 5V supply, this will immediately start charging the capacitor. Record in your logbook the voltage and current at 30 second intervals for ten minutes. Continue to record the voltage and current at one minute intervals until the capacitor reaches the voltage recorded above. It is important to record the time from the moment of connecting the current meter whenever recording values, rather than the interval. ************************************************************************ Table 1.1 Achieved results from capacitor charging Time, min | Voltage , V | Current , A | 0.5 | 0.53 | 0.45 | 1 | 0.82 | 0.43 | 1.5 | 1.08 | 0.4 | 2 | 1.26...
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