Leaves play a vital role in the development of a plant, as they are major resource collectors. Adequate models of leaves are therefore required for the modelling of plants. Such models may be used for visualisation purposes only, or they may incorporate leaf function such as photosynthesis. While the modelling of plant architecture has been researched extensively over the last decades, models of leaf surfaces have mostly not been generated with great accuracy or level of detail, and have often been handcrafted. This thesis aims to provide techniques for the creation of detailed, accurate models of leaf surfaces for the plant modelling community; models that may be used as parts of virtual plants for applications in fields as diverse as the arts, agriculture or computer games. These techniques are mathematical methods of surface fitting based on data that has been sampled from real leaves. First, leaf data needs to be collected. The digitising of leaf surfaces is described in detail in this thesis, and issues arising for three data collection techniques are discussed. The laser scanner is selected to sample data from leaf surfaces of four example leaf types. The two surface fitting methods which are applied to the data are finite element interpolation approaches. Since the size of a laser scanned data set can be enormous, an incremental algorithm is used to identify significant points that result in a surface fit that approximates all remaining data points to a specified accuracy. Interpretation of the positions of these points leads to the formulation of guidelines that describe the locations of significant points on a leaf surface. These are the points that should be digitised with a single-point device such as a sonic or magnetic digitiser, possibly the only digitising technique available to a plant scientist. Triangle-based finite element methods lead to surface models with piecewise linear viii boundaries in the triangulation reference plane. This may not be an issue for applications where the boundary of a model is not important. Leaf surfaces, however, possess a specific boundary. To generate a visually realistic model of a leaf surface the boundary needs to be captured; a method is introduced that improves the boundary of a triangle-based interpolant. A new boundary curve is specified that passes through all boundary points, and the surface is extended so that it matches the new curve. Visual criteria are listed for the acceptance or rejection of the boundary, and a preliminary discussion is made of numerical criteria. The research presented in this thesis is the first to model detailed and accurate leaf surfaces based on data points. It delivers a basis for further research both into the application of detailed models as well as into extensions of the presented model.

Background. The main problem that our master thesis is trying to reduce is malware infection. One method that can be used to accomplish this goal is based on the fact that most malware does not want to get caught by security programs and are actively trying to avoid them. To not get caught malware can check for the existence of security-related programs and artifacts before executing malicious code and depending on what they find, they will evaluate if the computer is worth infecting. The idea is that by identifying these checks we could "vaccinate" a system with data-points that trigger these checks and trick the malware into believing that a system is protected and skip it. Objectives. This thesis will research common malware evasion techniques to find what data-points malware avoids and develop a vaccine with the found data-points. To test the effectiveness of the vaccine an experiment will be conducted where malware will be executed on different systems to observe their behavior. Methods. The vaccine concept will be tested by gathering data-points with a background review of related works and performing an experiment. In the experiment a virtual machine without protective measures is used as a baseline which can be compared to a virtual machine with the vaccine. It is also interesting to see how a vaccine compares to an antivirus solution and how / if it would cooperate with an antivirus solution, so two more virtual machines are added to the experiment, one with just an antivirus software installed, and a second one with antivirus installed plus the vaccine. On these four systems, a set of malware will be executed and their behavior and activity (Windows API calls) will also be measured and compared. Results. This experiment showed that our vaccine was effective in reducing malware behavior, 70% of the malware did reduce their activity when exposed to the vaccine compared to the baseline. The results also indicate that the vaccine was effective in cooperation with an antivirus program, 85% of the malware did reduce their activity on this virtual machine compared to the baseline. Conclusions. From the results, we can conclude that of our created systems the system that reduced the most malware activity was the system with antivirus plus vaccine. This shows that vaccination can be a viable option for researchers to further study.

Submitted to the faculty of the School of Informatics in partial fulfillment of the requirements for the degree Master of Science in Chemical Informatics (Laboratory Informatics Specialization)Indiana University May 2006 / The Zymark™ System is a lab automation workstation that uses the Caliper Life Sciences (Hopkinton, MA) Zymate XP robot. At Indiana University-Purdue University Indianapolis, a Zymate is used in a course, INFO I510 Data Acquisition and Laboratory Automation, to demonstrate the fundamentals of laboratory robotics. This robot has been re-engineered to function with National Instruments™ graphical software program LabVIEW™. LabVIEW is an excellent tool for robotic control. Based on changing conditions, it is able to dynamically use data from any source to modify the operating parameters of a robot. For dynamically changing information, storage of that information must be readily accessible. For example, there is a need to continuously store and update the calibration data of the robot, populate the setting of each axis and positioning inside the workplace, and also store robot positioning information. This can be achieved by using a database which allows for robotic control data to be easily searched and accessed. To address this need, an interface was developed which would allow full, dynamic communication between any LabVIEW program (called “virtual instruments,” or VIs) and the database. This has been accomplished by developing a set of subVIs that can be dropped into the calling robotic control VIs. With these subVIs, a user has the ability to create table and column information, delete a table, retrieve table information by clicking a particular table name on the user interface, or query using any SQL-specific combination of columns or tables within the database. For robot functionality, subVIs were created to store and retrieve data such as calibration data points and regression calculations. / Chemical Informatics

本研究藉由整合相關之單一受試實驗研究結果來探討行為改變技術對學業行為影響之效果。研究中用來計算效應量的方法有兩種：未重疊資料百分率（Percentage of Nonoverlapping Data, PND）、超過基線中點資料百分率（Percentage of Data Points Exceeding the Median of Preceding Baseline Phase, PEM）。為了檢視超過基線中點資料百分率方法應用在單一受試實驗研究統合分析上之可行性，本研究以各原研究作者之判斷為效標，對超過基線中點資料百分率與未重疊資料百分率之效度進行比較。 一共有98篇單一受試實驗研究納入統合分析。實驗的介入處理共分成：1.電腦輔助教學、2.合作學習、3.精熟學習、4.增強、5.自我控制訓練、6.情境學習、7.社會學習、8.策略教學、9.其他。研究顯示各種介入處理對於受試的學習行為皆產生正向效果。此外，超過基線中點資料百分率方法亦獲得支持適用於單一受試實驗研究之量化統合分析。 / The purpose of this study is to investigate the effect of behavioral modification on academic behaviors by aggregating relevant conclusions of primary single-subject researches. Two approaches are used to generate estimations of effect sizes: the PND (Percentage of Nonoverlapping Data) approach, and the PEM (Percentage of Data Points Exceeding the Median of Preceding Baseline Phase). To test the applicability of the PEM approach, the validity of the PEM scores is compared with that of the PND scores by using the judgments of original authors as a validity criterion. A total of 98 studies are reviewed. Treatments include (a) computer assisted instruction; (b) cooperative learning; (c) mastery learning; (d) reinforcement; (e) self-control training; (f) situated learning; (g) social learning; (h) strategy instruction; and (i) others. Results indicate that all kinds of interventions produce positive effects on participants’ academic behaviors. In addition, the PEM approach is shown to be an appropriate method for a quantitative synthesis of single-subject researches.

本研究使用PND和PEM對106篇單一受試研究進行後設分析，藉以了解實驗處理對於搗亂行為的影響效果。當研究者以原作者對於實驗處理效果的判斷作為效標時，使用PEM進行後設分析的效度是可以被接受的。本研究並分析實驗處理、研究特徵和受試者特徵與處理效果的關係，獲得下列研究結果：1.不同的實驗處理對降低搗亂行為有不同影響效果；2.研究設計、治療者身分、實驗情境、性別、受試者症狀特徵、搗亂行為種類對實驗處理效果有顯著影響。本研究建議學校人員接受有關於矯正搗亂行為的行為改變技術訓練是必要的，教師如能在教室活動中發展合適的課程和教導學生適當的溝通反應將有助於降低搗亂行為。 / A meta-analysis of 106 single-subject studies was conducted utilizing the PND and PEM approaches to investigate treatment effectiveness in reducing disruptive behavior. The validity of the PEM approach was acceptable based on original authors’ judgments of treatment effect. Variables were analyzed for covariation between treatment effectiveness and interventions, study characteristics, and subject characteristics. The following results were obtained: (a) interventions had significant influence on treatment effectiveness; (b) study design, intervenor, setting, sex, diagnosis, and target behaviors showed systematic relation to treatment outcomes. Suggestions are made that it is necessary for staff in schools to receive adequate training in treating disruptive behavior with the use of behavior modification techniques, and it is potentially useful for the reduction of disruptive behavior if teachers develop suitable curriculum and teach appropriate communicative responses in classroom activities.