【正文】 n。 win: for j:=0 to do 太原科技大學華科學院學士學位論文 29 for i:=0 to do begin count1:=count1+1。你勝利了，恭喜 :)39。拼圖 39。 :=TRUE。 :=false。 exit。 if [i,j]inttostr(count1) then exit。 為降低游戲難度 ，系統(tǒng)特別設計了顯示位置功能。 如圖 所示： 太原科技大學華科學院學士學位論文 30 圖 about 提示界面 7. 游戲開始后，時間會一直累加直到游戲結(jié)束；玩家每移動一步，步數(shù)加一。根據(jù)此數(shù)字，可直接點擊鼠標右鍵，將小圖片直接放到正確的位置，此功能可大大降低游戲的難度。 若不選擇顯示位置時 ，界面顯示如圖 所示 ： 太原科技大學華科學院學士學位論文 31 圖 不顯示位置的拼圖界面 若選擇顯示位置時 ，界面所示如圖 所示： 圖 顯示位置的拼圖界面 當游戲結(jié)束時，系統(tǒng)會彈出一個標有 “你勝利了，恭喜 ”的窗口，提示玩家游戲結(jié)束。在這段時間里不斷的發(fā)現(xiàn)自己的問題，然后找出問題產(chǎn)生的原因，根據(jù)相關的辦法解決問題。雖然其中還有很多不足的地方，我們將不斷的學習完善該系統(tǒng)。只要做好了這些準備工作，做起系統(tǒng)來才會得心 應手，不能再像以前那樣，想到那里就做到那里。 由于缺乏經(jīng)驗和水平欠缺，設計以前應該找出要用到的相關知識，認真對待設計中的每一個問題，從方法到具體技術，對不懂的地方應該多參考資料 。對 軟件的操作更加熟練。從這里走出，對我的人生來說將是踏 上新的征程。 在這次課程設計的撰寫過程中，我得到了許多人的幫助。在此期間，我不僅學到了許多新的知識，而且也開闊了視野，提高了自 己的設計能力。同時也感謝學院為我提供良好的做畢業(yè)設計的環(huán)境。 太原科技大學華科學院學士學位論文 35 參考文獻 [1] 王學慶． Delphi 7 數(shù)據(jù)庫設計實例導航．北京：科學出版社． 2020 [2] 付軍． Delphi7 實例編程 100 例．北京：中國鐵道出版社． 2020 [3] 張瀚文 齊錦剛 delphi 數(shù)據(jù)庫系統(tǒng)開發(fā)實例與解析 [M] 2020 年 1 月 [4] 王棟 清華大學出版社 程序設計實例訓教程 [M]2020 年 3 月 [6] 王興晶 尹立宏 電子工業(yè)出版社 delphi 基礎教程 [M]2020 年 8 月 太原科技大學華科學院學士學位論文 36 附錄 Ⅰ DATA WAREHOUSING Data warehousing provides architectures and tools for business executives to systematically anize, understand, and use their data to make strategic decisions. A large number of anizations have found that data warehouse systems are valuable tools in today39。s operational databases. Data warehouse systems allow for the integration of a variety of application systems. They support information processing by providing a solid platform of consolidated, historical data for analysis. According to W. H. Inmon, a leading architect in the construction of data warehouse systems, “a data warehouse is a subjectoriented, integrated, timevariant, and nonvolatile collection of data in support of management39。s take a closer look at each of these key features. (1).Subjectoriented: A data warehouse is anized around major subjects, such as customer, vendor, product, and sales. Rather than concentrating on the daytoday operations and transaction processing of an anization, a data warehouse focuses on the modeling and analysis of data for decision makers. Hence, data warehouses typically provide a simple and concise view around particular subject issues by excluding data that are not useful in the decision support process. (2) Integrated: A data warehouse is usually constructed by integrating multiple heterogeneous sources, such as relational databases, flat files, and online transaction records. Data cleaning and data integration techniques are applied to ensure consistency in naming conventions, encoding structures, attribute measures, and so on. (3).Timevariant: Data are stored to provide information from a historical perspective (., the past 510 years). Every key structure in the data warehouse contains, either implicitly or explicitly, an element of time. (4)Nonvolatile: A data warehouse is always a physically separate store of data transformed from the application data found in the operational environment. Due to this separation, a data warehouse does not require transaction processing, recovery, and concurrency control mechanisms. It usually requires only two operations in data accessing: initial loading of data and access of data. In sum, a data warehouse is a semantically consistent data store that serves as a physical implementation of a decision support data model and stores the information on which an enterprise needs to make strategic decisions. A data warehouse is also often viewed as an architecture, constructed by integrating data from multiple heterogeneous sources to support structured and/or ad hoc queries, analytical reporting, and decision making. 太原科技大學華科學院學士學位論文 37 “OK, you now ask, “what, then, is data warehousing? Based on the above, we view data warehousing as the process of constructing and using data warehouses. The construction of a data warehouse requires data integration, data cleaning, and data consolidation. The utilization of a data warehouse often necessitates a collection of decision support technologies. This allows “knowledge workers (., managers, analysts, and executives) to use the warehouse to quickly and conveniently obtain an overview of the data, and to make sound decisions based on information in the warehouse. Some authors use the term “data warehousing to refer only to the process of data warehouse construction, while the term warehouse DBMS is used to refer to the management and utilization of data warehouses. We will not make this distinction here. “How are anizations using the information from data warehouses? Many anizations are using this information to support business decision making activities, including: (1) increasing customer focus, which includes the analysis of customer buying patterns (such as buying preference, buying time, budget cycles, and appetites for spending), (2) repositioning products and managing product portfolios by paring the performance of sales by quarter, by year, and by geographic regions, in order to finetune production strategies, (3) analyzing operations and looking for sources of profit, (4) managing the customer relationships, making environmental corrections, and managing the cost of corporate assets. Data warehousing is also very useful from the point of view of heterogeneous database integration. Many anizations typically collect diverse kinds of data and maintain large databases from multiple, heterogeneous, autonomous, and distributed information sources. To integrate such data, and provide easy and efficient access to it is highly desirable, yet challenging. Much effort has