在臺灣國中英語課程的寫作部份，一向只有片段的填空、改寫句子或翻譯等，加強文法及句型結構的練習，而忽略能讓學生自我表達的創意寫作。對英語能力相當有限的國中生而言，若能提供有效、有趣的寫作指導，他們也能應用語言能力並發揮創意，寫出有趣的文章。 本研究在探討由看圖說故事進而寫故事，對國中生寫作能力的影響。本研究以台北市某國中兩班三年級，六十位學生為研究對象，先施以一次先前研究，作為主要研究的設計及實施之參考，再以三個故事為主題進行六篇記敘文的寫作。其中三篇只給作文題目及引導句，稱為題目引導式寫作；另三篇則提供題目加圖片，稱為圖片引導式寫作。整個研究內容另包括三次問卷及一系列的訪談。問卷一及問卷三在了解受測學生在研究前、研究後的寫作態度及動機的轉變；問卷二及訪談旨在了解學生對於圖片做為輔助教材的觀感。 本研究的主要發現如下：（1）圖片有助於學生寫故事的組織及架構，（2）圖片提供語料及文意，有助於學生發展故事內容及長度，（3）圖片刺激學生想像力，增加學生故事的創意，（4）學生在經過圖片式的寫作引導之後，對英文作文表現出比較積極的學習態度及動機。 / For junior high students in Taiwan, writing activities have been restricted to grammar-oriented exercises. Creative writing that engages students in using the target language communicatively has been neglected. Students at this level of proficiency, if provided with effective and stimulating writing instruction, are also able to compose fascinating stories. The purpose of this study is to explore the effectiveness of pictures on junior high students’ narrative writing. Subjects in this study are sixty ninth-graders from two classes in a junior high school in Taipei city. Instruments consist of a pilot study, three student surveys, six narrative writing assignments and a series of one-to-one interviews. Findings are summarized as follows: First, picture aids facilitate students’ organizational skills for story writing. Second, pictorial presentation provides students with linguistic resources that help to enrich their story content. Third, pictorial images stimulate students’ imagination and add creativity to their stories. Furthermore, writing improvements through pictorial instruction also lead to the students’ positive attitude toward writing and stronger motivation as well.

This work introduces technology for rapid pathogen detection using handheld optical immunoassay and wire-guided droplet PCR systems. There have been a number of cases of foodborne or waterborne illness among humans that are caused by pathogens such as Escherichia coli O157:H7, Salmonella typhimurium, Influenza A H1N1, and the norovirus. The current practices to detect such pathogenic agents are: cell/viral culturing, immunoassays, or polymerase chain reactions (PCRs). These methods are essentially laboratory-based methods that are not at all real-time and thus unavailable for early-monitoring of such pathogens. They are also very difficult to be implemented in field, preventing early detection opportunities. This dissertation is divided into three papers that present methodologies towards the expeditious detections of infectious pathogens and the miniaturization of these detection systems towards field-deployable and point-of-care applications. Specifically, the work presented focuses on two methodologies: (1) light scatter detection using immunoagglutination assays with optimized Mie light scatter parameters in a real biological matrix consisting of plant tissue, and (2) wire-guided droplet manipulations for rapid and improved sample analysis, preparation, and PCR thermocycling. Both of these methods carry a collective objective towards providing high impact technologies for addressing the issues of food-related outbreaks and overall public safety. In the first paper, the direct and sensitive detection of foodborne pathogens from fresh produce samples was accomplished using a handheld lab-on-a-chip device, requiring little to no sample processing and enrichment steps for a near-real-time detection and truly field-deployable device. The detection of Escherichia coli K12 and O157:H7 in iceberg lettuce was achieved utilizing optimized Mie light scatter parameters with a latex particle immunoagglutination assay. The system exhibited good sensitivity, with a limit of detection of 10 CFU mL⁻¹ and an assay time of <6 min. Minimal pretreatment with no detrimental effects on assay sensitivity and reproducibility was accomplished with a simple and cost-effective KimWipes filter and disposable syringe. Mie simulations were used to determine the optimal parameters (particle size d, wavelength λ, and scatter angle θ) for the assay that maximize light scatter intensity of agglutinated latex microparticles and minimize light scatter intensity of the tissue fragments of iceberg lettuce, which were experimentally validated. This introduces a powerful method for detecting foodborne pathogens in fresh produce and other potential sample matrices. The integration of a multi-channel microfluidic chip allowed for differential detection of the agglutinated particles in the presence of the antigen, revealing a true field-deployable detection system with decreased assay time and improved robustness over comparable benchtop systems. In the second paper, we demonstrate a novel method of wire-guided droplet manipulations towards very quick RT-PCR. Because typical RT-PCR assays take about 1–2 h for thermocycling, there is a growing need to further speed up the thermocycling to less than 30 min. Additionally, the PCR assay system should be made portable as a point- of-care detection tool. Rapid movements of droplets (immersed in oil) over three different temperature zones make very quick PCR possible, as heating/cooling will be made by convective heat transfer, whose heat transfer coefficients are much higher than that of conduction, the latter of which is used in most conventional PCR systems. A 30-cycle PCR of a 160 bp gene sequence amplified from 2009 H1N1 influenza A (human origin) was successfully demonstrates in 6 min and 50 sec for a very large 10 μL droplet (with additional 4 min for reverse transcription). The proposed system has a potential to become a rapid, portable, point-of-care tool for detecting influenza A. In the third paper, a wire-guided CNC apparatus was used to perform droplet centrifugation, DNA extraction, and VQ-PCR thermocycling on a single superhydrophobic surface measuring 25 mm by 55 mm and a multi-chambered PCB heater. This methodology exhibited no limitations on the complexity and configuration of procedures that it can perform, making it versatile and far-reaching in its applications. The only modification required for adding or implementing changes for a new protocol is through simple pre-defined programming. The highly adaptive and flexible system was used to execute easily pre-programmed droplet movements and manipulations for the rapid detection of Escherichia coli from PCR detection. Serial dilutions were performed to simulate a diluted field sample with a high level of accuracy. Centrifugation of the diluted sample containing E. coli demonstrated a novel approach to sample pre-treatment. Furthermore, the extraction of DNA from the sample droplet containing E. coli was also performed on the same superhydrophobic surface as the previous 2 steps, requiring less than 10 min. Following extraction, the genetic material was amplified using wire-guided droplet PCR thermocycling, successfully completing 30 cycles of Peptidase D (a long 1500 bp sequence) in 10 min. The droplet centrifugation process was determined to greatly improve the positive band intensity over the non-centrifuged sample. Thus, this work demonstrates the adaptability of the system to replace many common laboratory tasks on a single platform (through re-programmability), in rapid succession (using droplets), and with a high level of accuracy and automation.

Image-guided surgeries employ advanced imaging and computing technologies to assist the surgeon when direct visualization is inadequate or unavailable. As modern surgeries continue to move toward minimally invasive procedures, tracked ultrasound (US), an emerging technology that uniquely combines US imaging and position tracking, has been increasingly used for intraoperative guidance in surgical interventions. The intrinsic accuracy of a tracked US system is primarily determined by a unique procedure called ``probe calibration", where a spatial registration between the coordinate systems of the transducer (provided by a tracking device affixed to the probe) and the US image plane must be established prior to imaging. Inaccurate system calibration causes misalignments between the US image and the surgical end-effectors, which may directly contribute to treatment failure. The probe calibration quality is further reduced by the "elevation beamwidth" or "slice thickness", a unique feature of the ultrasound beam pattern that gives rise to localization errors and imaging uncertainties. In this thesis, we aim to provide an automated, pure-computation-based, intraoperative calibration solution that also incorporates the slice thickness to improve the calibration accuracy, precision and reliability. The following contributions have been made during the course of this research. First, we have designed and developed an automated, freehand US calibration system with instant feedback on its calibration accuracy. The system was able to consistently achieve submillimeter accuracy with real-time performance. Furthermore, we have developed a novel beamwidth-weighted calibration framework (USB-FW) that incorporates US slice thickness to improve the estimation of calibration parameters. The new framework provides an effective means of quality control for calibration results. Extensive phantom validation demonstrated that USB-FW introduces statistically significant reduction (p = 0.001) in the calibration errors and produces calibration outcomes that are less variable than a conventional, non-beamwidth-weighted calibration. Finally, we were the first to introduce an automated, intraoperative Transrectal Ultrasound (TRUS) calibration technology for needle guidance in prostate brachytherapy. Our tests with multiple commercial TRUS scanners and brachytherapy stepper systems demonstrated that the proposed method is practical in use and can achieve high calibration accuracy, precision and robustness. / Thesis (Ph.D, Computing) -- Queen's University, 2012-10-22 16:18:55.439

Atherosclerosis is often diagnosed using an ultrasound (US) examination in the carotid and femoral arteries and the abdominal aorta. A decision to operate requires two measures of disease severity: the degree of stenosis measured using B-mode US; and the blood flow patterns in the artery measured using spectral Doppler US. However other biomechanical factors such as wall shear stress (WSS) and areas of flow recirculation are also important in disease development and rupture. These are estimated using an image-guided modelling approach, where a three-dimensional computational mesh of the artery is simulated. To generate a patient-specific arterial 3D computational mesh, a 3D ultrasound (3DUS) system was developed. This system uses a standard clinical US scanner with an optical position sensor to measure the position of the transducer; a video capture card to record video images from the scanner; and a PC running Stradwin software to reconstruct 3DUS data. The system was characterised using an industry-standard set of calibration phantoms, giving a reconstruction accuracy of ± 0.17 mm with a 12MHz linear array transducer. Artery movements from pulsatile flow were reduced using a retrospective gating technique. The effect of pressure applied to the transducer moving and deforming the artery was reduced using an image-based rigid registration technique. The artery lumen found on each 3DUS image was segmented using a semi-automatic segmentation technique known as ShIRT (the Sheffield Image Registration Toolkit). Arterial scans from healthy volunteers and patients with diagnosed arterial disease were segmented using the technique. The accuracy of the semi-automatic technique was assessed by comparing it to manual segmentation of each artery using a set of segmentation metrics. The mean accuracy of the semi-automatic technique ranged from 85% to 99% and depended on the quality of the images and the complexity of the shape of the lumen. Patient-specific 3D computational artery meshes were created using ShIRT. An idealised mesh was created using key features of the segmented 3DUS scan. This was registered and deformed to the rest of the segmented dataset, producing a mesh that represents the shape of the artery. Meshes created using ShIRT were compared to meshes created using the Rhino solid modelling package. ShIRT produced smoother meshes; Rhino reproduced the shape of arterial disease more accurately. The use of 3DUS with image-guided modelling has the potential to be an effective tool in the diagnosis of atherosclerosis. Simulations using these data reflect in vivo studies of wall shear stress and recirculation in diseased arteries and are comparable with results in the literature created using MRI and other 3DUS systems.

Ultrasound imaging is a rapid and noninvasive tool ideal for the imaging of soft tissue infections and is associated with a change of clinician management plans in 50% of cases. We developed a realistic skin abscess diagnostic and therapeutic training model using fresh frozen cadavers and common, affordable materials. Details for construction of the model and suggested variations are presented. This cadaver-based abscess model produces high-quality sonographic images with internal echogenicity similar to a true clinical abscess, and is ideal for teaching sonographic diagnostic skills in addition to the technical skills of incision and drainage or needle aspiration.

<p>A tenet of modern radiotherapy (RT) is to identify the treatment target accurately, following which the high-dose treatment volume may be expanded into the surrounding tissues in order to create the clinical and planning target volumes. Respiratory motion can induce errors in target volume delineation and dose delivery in radiation therapy for thoracic and abdominal cancers. Historically, radiotherapy treatment planning in the thoracic and abdominal regions has used 2D or 3D images acquired under uncoached free-breathing conditions, irrespective of whether the target tumor is moving or not. Once the gross target volume has been delineated, standard margins are commonly added in order to account for motion. However, the generic margins do not usually take the target motion trajectory into consideration. That may lead to under- or over-estimate motion with subsequent risk of missing the target during treatment or irradiating excessive normal tissue. That introduces systematic errors into treatment planning and delivery. In clinical practice, four-dimensional (4D) imaging has been popular in For RT motion management. It provides temporal information about tumor and organ at risk motion, and it permits patient-specific treatment planning. The most common contemporary imaging technique for identifying tumor motion is 4D computed tomography (4D-CT). However, CT has poor soft tissue contrast and it induce ionizing radiation hazard. In the last decade, 4D magnetic resonance imaging (4D-MRI) has become an emerging tool to image respiratory motion, especially in the abdomen, because of the superior soft-tissue contrast. Recently, several 4D-MRI techniques have been proposed, including prospective and retrospective approaches. Nevertheless, 4D-MRI techniques are faced with several challenges: 1) suboptimal and inconsistent tumor contrast with large inter-patient variation; 2) relatively low temporal-spatial resolution; 3) it lacks a reliable respiratory surrogate. In this research work, novel 4D-MRI techniques applying MRI weightings that was not used in existing 4D-MRI techniques, including T2/T1-weighted, T2-weighted and Diffusion-weighted MRI were investigated. A result-driven phase retrospective sorting method was proposed, and it was applied to image space as well as k-space of MR imaging. Novel image-based respiratory surrogates were developed, improved and evaluated.</p> / Dissertation

The United States-Japanese missile defense cooperation signals yet another step in Japan's continuing trend of "normalization" and official acknowledgement that Japan has a significant military force. This thesis analyzes the current status of the Japanese missile defense debate and assesses factors shaping the Japanese commitment to joint missile defense with the United States. Three major inter-related trends mark the course of Japanese post- Cold War SDF evolution, relations with the United States and the missile defense debate. These include a willingness to relax legal considerations on the use of military force, the expansion of the roles for the JSDF, and the responsiveness of Japanese decision makers to external factors, notably the requirement to improve relations with the United States and the threat perceived from North Korea. This represents a shift to a more military-based security outlook away from the traditional notion of "comprehensive security." These trends point invariably to the amendment of Article 9 of the Japanese Constitution. To maximize U.S. interests, Washington must pursue a balanced and limited missile defense in East Asia and actively undertake measures to avoid the perception of a threat to Chinese nuclear deterrence.

In this thesis, a multiple hypotheses tracking (MHT) algorithm is developed to successfully track multiple ballistic missiles within the boost phase. The success of previous work on the MHT algorithm and its application in other scientific fields enables this study to realize an efficient form of the algorithm and examine its feasibility in tracking multiple crossing ballistic missiles even though various accelerations due to staging are present. A framework is developed for the MHT, which includes a linear assignment problem approach used to search the measurement-to-contact association matrix for the set of exact N-best feasible hypotheses. To test the new MHT, an event in which multiple ballistic missiles have been launched and threaten the North American continent is considered. To aid in the interception and destruction of the threat far from their intended targets, the research focuses on the boost-phase portion of the missile flight. The near-simultaneous attacks are detected by a network of radar sensors positioned near the missile launch sites. Each sensor provides position reports or track files for the MHT routine to process. To quantify the performance of the algorithm, data from the National Air and Space Intelligence Center's IMPULSE ICBM model is used and demonstrates the feasibility of this approach. This is especially significant to the U.S. Missile Defense Agency since the IMPULSE model represents the cognizant analyst's accurate representation of the ballistic threats in a realistic environment. The results show that this new algorithm works exceptionally well in a realistic environment where complex interactions of missile staging, non-linear thrust profiles and sensor noise can significantly degrade the track algorithm performance especially in multiple target scenarios.

A novel series of near-infrared fluorescent contrast agents was developed and characterized. Their physicochemical and optical properties were measured. By altering functional groups of cyanine fluorophores, the selective targeting of endocrine glands, exocrine glands, cartilage and bone using NIR fluorescence to visualize the targeted tissue has been reported. These agents have high specificity for tissue targeting inherent to the chemical structure of the fluorophore. After a single low-dose intravenous injection these agents have high specificity for tissue targeting inherent to the chemical structure of the fluorophore. The results lay the foundation for future improvements in optical imaging in endocrine surgery, tissue engineering, joint surgery, and cartilage-specific drug development.

Objectives. The goal in radiotherapy is to deliver adequate radiation to the tumor volume while limiting damage to the surrounding healthy tissue. However, this goal is challenged by respiratory-induced motion. The objective of this work was to identify whether motion in electronic portal images can be tracked with an optical flow algorithm and whether a neural network can predict tumor motion. Methods. A multi-resolution optical flow algorithm that incorporates weighting based on the differences between image frames was used to automatically sample the vectors corresponding to the motion. The global motion was obtained by computing the average weighted mean from the set of vectors. The algorithm was evaluated using tumor trajectories taken from seven lung cancer patients, a 3D printed patient tumor and a virtual dynamic multi-leaf collimator (DMLC) system. The feasibility of detecting and tracking motion at the field edge was examined with a proof-of-concept implementation that included (1) an algorithm that detected local motion, and (2) a control algorithm that adapted the virtual MLC. To compensate for system latency, a generalized neural network, using both offline (treatment planning data) and online (during treatment delivery) learning, was implemented for tumor motion prediction. Results and Conclusions. The algorithm tracked the global motion of the target with an accuracy of around 0.5 mm. While the accuracy is similar to other methods, this approach does not require manual delineation of the target and can, therefore, provide real-time autonomous motion estimation during treatment. Motion at the treatment field edge was tracked with an accuracy of -0.4 ± 0.3 mm. This proof-of-concept simulation demonstrated that it is possible to adapt MLC leaves based on the motion detected at the field edges. Unplanned intrusions of external organs-at-risk could be shielded. A generalized network with a prediction error of 0.59 mm, and a shorter initial learning period (compared to previous studies) was achieved. This network may be used as a plug-and-play predictor in which tumor position could be predicted at the start of treatment and the need for pretreatment data and optimization for individual patients may be avoided. / February 2017