In this thesis we analyze optimal demand management policies for stochastic systems. In the first system considered, a manufacturer decides how to manage demand from customers that differ in their priority level and willingness to pay. He has limited production capacity and predetermined prices throughout the horizon. We find an optimal production and inventory strategy that rations current and future limited capacity between customer classes through reserving inventory for the future and accepting orders now for future delivery. Next, we extend these results to the case when the customers have different tolerance to delayed fulfillment, namely, first-class customers never accept backlogging whereas second-class customers agree to wait one period for a discount. We find an optimal policy similar to the production and inventory strategy that is used for the first system based on threshold values. The third system considers a firm whose recent performance in meeting quoted leadtimes affects future demand arrivals. We assume that the probability of a customer placing an order depends on the quoted leadtime, and both customer arrivals and processing times are stochastic. When capacity of the firm is infinite, we find the optimal leadtime to quote, and when capacity is finite and leadtime is industry-dictated, we determine that the optimal demand acceptance policy does not necessarily have a nice structure. We comment on the structure of the optimal policy for a special case and develop several heuristics for the general case. The final system considered in this thesis is the Sports and Entertainment industry, where demand is managed for a season of several performances by selling season tickets initially and single events later in the selling horizon. We specifically study the optimal time to switch between these market segments dynamically as a function of the state of the system and show that the optimal switching time is a set of time thresholds that depend on the remaining inventory and time left in the horizon.

The object of study in social housing used to point an aging population, and single-parent families. With the international economic recession, lots of money flowing into the housing market that causing the prices stubbornly high. The Youth is unable to find the housing which they can affordable and become the working poor. In order to achieve the goal of living justice, assist and encourage youth people having the home appropriate ownership and proposed housing subsidy policy. In this study, the subjects have chosen for 20-year-old to 45-year-old youth citizens (at least 400 youth citizens) between the Taipei city and Kaohsiung city. We want to know the reaction whether has different of background with public information, policy recognition, current situation, rented of demand and the burden, non-rented of demand and the burden. In conclusion, both regions have the same main housing demand in the rent. Youth people are turly have the application for subsidy demand that Government should expand the service object included in the 20-year-old to 40-year-old single youth population. And encouraged people who is unable to have the ability to apply for subsidies in renting, combined with factors for single young people living considerations resolve youth people of housing demand from the supply side.

Through the use of a stochastic simulation model this project analyzes both the impacts of the expanding biofuels sector on water demand in selected regions of the United States and variations in the profitability of ethanol production due to location differences. Changes in consumptive water use in the Texas High Plains, Southern Minnesota, and the Central Valley of California, as impacted by current and proposed grain-based ethanol plants were addressed. In addition, this research assesses the potential impacts of technologies to reduce consumptive water use in the production of ethanol in terms of water usage and the economic viability of each ethanol facility. This research quantifies the role of corn ethanol production on water resource availability and identifies the alternative water pricing schemes at which ethanol production is no longer profitable. The results of this research show that the expansion of regional ethanol production and the resulting changes in the regional agricultural landscapes do relatively little to change consumptive water usage in each location. The California Central Valley has the highest potential for increased water usage with annual water usage in 2017 at levels 15% higher than historical estimates, whereas Southern Minnesota and the Texas High Plains are predicted to have increases of less than 5% during the same time period. Although water use by ethanol plants is extremely minor relative to consumptive regional agricultural water usage, technological adaptations by ethanol facilities have the potential to slightly reduce water usage and prove to be economically beneficial adaptations to make. The sensitivity of net present value (NPV) with respect to changes in water price is shown to be extremely inelastic, indicating that ethanol producers have the ability to pay significantly more for their fresh water with little impact on their 10 year economic performance.

Since through trips can be a significant portion of travel in a study area, estimating them is an important part of travel demand modeling. In the past, through trips have been estimated using external surveys. Recently, external surveys were suspended in Texas, so Texas transportation planners need a way to estimate through trips without using external surveys. Other research in the area has focused on study areas with a population of less than 200,000, but many Texas study areas have a population of more than 200,000. This research developed a set of two logit models to estimate through trips for a wide range of study area sizes, including larger study areas. The first model estimates the portion of all trips at an external station that are through trips. The second model distributes those through trips at one external station to the other external stations. The models produce separate results for commercial and noncommercial vehicles, and these results can be used to develop through trip tables. For predictor variables, the models use results from a very simple gravity model; the average daily traffic (ADT) at each external station as a proportion of the total ADT at all available external stations; the number of turns on the routes between external station pairs; and whether the route is valid, where a valid route is one that passes through the study area and does not pass through any other external stations. Evaluations of the performance of the models showed that the predictions fit the observations reasonably well; at least 68 percent of the absolute prediction errors for each model and for the models combined were less than 10 percent. These results indicate that the models can be useful for practical applications.

As streaming video and audio over the Internet become popular, the deployment of a large-scale multimedia streaming application requires an enormous amount of server and network resources. In a video-on-demand environment, batching of video requests are often used to reduced I/O demand and improve throughput. Since users may leave if they experience long waits, a good video scheduling policy needs to consider not only the batch size but also the user defection probabilities and wait times. The common scheduling policies are the first-come-first-served (FCFS), the maximum queue length (MQL), and the maximum factored queue length (MFQL). But these schemes may choose the same video and serve the same video requests. Users choosing other video can not receive the video segment and may leave after waiting a long time. In this paper, we propose a batching policy that schedules the video with the concept of the bandwidth balancing scheme in DQDB networks. We refer to this as the SPBB policy. Our goal is to make sure that users can get the video segment and don¡¦t leave the video-on-demand system.

TV commercials play an important role for consumers¡¦ purchasing behavior. As the competition being fierce in the financial goods market, the banks weight the commercial effect with the sales of issued cards. What kind of commercials elicit the most effective advertising result? A successful commercial precisely transmits the message to the target consumers, and it must be logical and convincing for consumers¡¦ demand. What kind of TV commercials will attract the desire of purchasing? This study is based on content analysis approach to analyze 49 TV commercials about cash cards in Taiwan, intends to probe the commercial types for the corporations to meet the consumers¡¦ need efficiently. After statistical analysis, find it as follows mainly: 1. Cash card commercials are mostly drama-oriented expression, and the main purpose is for promotion or service. The ¡¥static¡¦ type is vocal and narrative. 2. Commercial contexts are physical surroundings indoors and outdoors, designed for the interpersonal interaction of more than three people, with voice-over to communicate, and provide abundant information. 3. Commercials show the most powerful influence on symbolic needs, which are the needs for social relationship and the sense of self-achievement. 4. Commercials shape the cash cards as perceptual and low-involvement goods.

Three different topics associated with their respective applications are proposed in this thesis. The first application is the implementation of a fast tagged sorter. A novel and high-speed realization of the tagged sorting algorithm is presented. Meanwhile, the problems to detect whether the queue is empty or full is also resolved without increasing any hardware cost. The second topic is focused on the implementation of a fast dynamic 64-bit comparator with small transistor count. The entire 64-bit comparator is composed of equality comparators and zero/one detectors, which are proposed by C.-F. Wu. The problem to handle a large fan-in requirement is also resolved in our design. The third topic is to carry out a power demand monitor system for factories. Not only can it monitor the factory¡¦s power network with a graphical user interface, but also can turn off the unessential equipments automatically when the total power consumed by the factory is larger than what was expected.

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Video on demand (VoD) services are becoming more and more popular today. As high bandwidth communication infrastructure is being established in many countries around the world, high bandwidth communication lines will reach millions of family in the near future. Due to the increasing improvement of communication technology, more and more families enjoy the VoD services which are provided by telecommunication companies and cable TV provider via the Internet. In such a case, scalability and fault tolerance will be the key issues. We propose an architecture for VoD services which is based on multi-server circumstance. In our proposed architecture, each movie is replicated on a subset of the servers. When a server crashes or disconnects from its clients, it is replaced by another server in a transparent way. Regarding of load balancing problem, clients are also migrated from one server to another when a new server is brought up. The benefit of our service is to use common hardware and general network technologies (e.g. TCP/IP). In addition, we provide a machine-independent environment to let the servers and clients execute on any machine through the network. Furthermore, we can get the media players from a web browser by utilizing the cross-platform characteristics of Java. The client host does not need to install any relevant applications. Since Java Media Framework (JMF) provides a unified architecture and messaging protocol for managing the acquisition, processing, and delivery of time-based media data. It can support many standard media content types, such as AIFF, AVI, MIDI, MPEG, QuickTime, and WAV. Using JMF, we can create applets and applications to present, manipulate, and store time-based media.

The requirements of network technologies are considered significantly important, because modern enterprises face the trend of e-commerce and widely use the conveniences of Internet communications. Internet Data Center (IDC) provides services to satisfy customers' requirements. Hence, IDC becomes a new area of markets in the world. Due to the market is so small in Taiwan, enterprises cannot get profits, even that they loss business. To alleviate the above problem, we study three frameworks of fundamental services IDC, including infrastructure, superintendence and add-value service. The goal is to find the important services for customer demand by comparing the customer satisfaction between before and after of the rent. We also compare the differences between fundamental factors and service factors, the correlation between integrated service and service factors, and the differences between satisfaction and expecting before and after of the rent. The purpose of our survey is to provide feasible suggestions to IDC managers so that they can not only survive but also get profits. The results have been shown as follows: 1.The important services of customer demand include: (a)power, air-condition, bandwidth fire suppression system under the infrastructure service. (b)anti-virus protection and DOS attacks prevention under the monitoring service. (c)storage backup, remote backup and firewall protection under the add-value service. 2.The high demands for quality of service (QoS) include: (a)power, air-condition, fire suppression system, security access control system and TV security monitoring under the infrastructure service. (b)storage backup remote backup and firewall protection under the add-value service. 3.The unsatisfaction for quality of service include: (a)security access control system, TV security monitoring, temperature & humidity control, and web hosting under infrastructure service. (b)anti-virus protection, DOS attacks prevention under the monitoring service. (c)the cache service under add-value service. 4. We compare the differences between expected QoS and satisfaction. The results are shown in Figure 5.1.2, Figure 5.1.3, and Figure 5.1.4 respectively. 5. We compare the differences between the expected service and satisfaction before and after of the rent. The results are shown that four items are ¡§significant difference¡¨, including (a)air-condition, UPS under the infrastructure. (b)application system hosting, DNS under add-value service. In contrast, six items are no ¡§significant difference¡¨, including (a)security access control and TV security monitoring under infrastructure. (b)server monitoring under the monitoring service, the contracts of various QoS, consultant, systems integration, total solution, remote backup and the whole service. 6. We compare the correlation between the whole service and service factor. The results are shown that six items are ¡§high correlation¡¨, including (a)equipment security under the factor of service demand. (b)equipment security, equipment service, monitoring service under the expected factor for QoS. (c)equipment security and integrated service under the satisfaction factor for QoS.