This thesis is concerned with intensity characteristics of conditioned stimuli in acquisition of a conditioned emotional response (CER) in rats. A comparison was made of CSs which differed (between groups) with respect to amount and direction of change in white noise from a constant background stimulation level. The measure of conditioning was the degree to which the CS disrupted ongoing, food-motivated, bar-pressing activity. The major findings were (1) that rate of conditioning was a monotonic increasing function of amount of intensity change in either direction; and (2) an increase in noise intensity from background X to CS Y produced more rapid acquisition of the CER than did a decrease from background Y to CS X. (3) During pretests, a noise increase produced a small, but reliable, Increase in rate of bar-pressing, while a noise decrease produced a slight suppression. / Thesis / Master of Arts (MA)

Change of direction speed (CODS) is an important determinant of performance in many sports. Greater stiffness of the lower limb should be beneficial to CODS, but this had not been well investigated. The purpose of this thesis was to establish the relationship between vertical stiffness, vertical stiffness asymmetries and CODS, with a view to augmenting CODS performance. The pilot study and studies 1-2 sought to determine the most reliable and ecologically valid method to assess stiffness in athletes required to perform changes of direction. The pilot study reported that the use of ultrasonography to determine Achilles tendon stiffness did not demonstrate appropriate reliability for inclusion in subsequent studies. Coefficients of variation (CVs) in excess of 27% were reported during an isometric plantar flexion task. Study 1 reported that CVs for vertical stiffness were lower when assessed during unilateral drop jumping (~7%) than during bilateral drop jumping (~12%) or bilateral hopping (~14%). Study 2 reported that the expression of vertical stiffness (P = 0.033) and vertical stiffness symmetry angle (P = 0.006) was significantly different across three performance tasks: unilateral drop jumping, bilateral drop jumping and bilateral hopping. Asymmetry percentages between compliant and stiff limbs were 5.6% (P < 0.001; d: 0.22), 23.3% (P = 0.001; d = 0.86) and 12.4% (P = 0.001; d = 0.39), respectively. Given the findings of studies 1 and 2, this thesis demonstrated the reliability and validity of a novel method by which to assess vertical stiffness - the unilateral drop jump. This task was used in subsequent studies to measure vertical stiffness. Study 3 sought to determine if vertical stiffness and vertical stiffness asymmetries influenced CODS performance determined during a 90o cutting task. Multiple regression analyses reported that mean vertical stiffness and asymmetry in jump height explained 63% (r2 = 0.63; P = 0.001) of CODS performance. Study 3 was the first investigation to demonstrate the importance of vertical stiffness to CODS performance. Study 4 sought to determine if acute exercise interventions designed to augment vertical stiffness would improve CODS. Unilateral and bilateral ‘stiffness’ interventions were evaluated against a control condition. CODS performances following the unilateral intervention were significantly faster than control (1.7%; P= 0.011; d = -1.08), but not significantly faster than the bilateral intervention (1.0% faster; P = 0.14; d = -0.59). Versus control, vertical stiffness was 14% greater (P = 0.049; d = 0.39) following the unilateral intervention. Study 4 demonstrated that a novel unilateral ‘stiffness’ intervention improved vertical stiffness and CODS performance. This highlights that the potential applicability of unilateral stiffness interventions in the pre-performance preparation of athletes.

自民國69年政府開放國人出國觀光之後，由於國民所得的提高、台幣的升 值及其它種種社經有利因素的影響，使得每年出國觀光人數穩定的成長， 而在民國76年開放國人赴大陸探親之後，出國觀光人數更呈直線上升，這 對於提高國家知名度以及展示國家整體經濟實力有極為明顯的助益。出國 觀光旅客人數的多寡直接或間接影響本地觀光業者及政府相關單位對觀光 業軟、硬體設施的投資以及整體策略的規劃，舉凡國際航線的開拓、航空 公司航線的增減、導遊人員的培訓以及政府駐外單位的配合措施，在在都 有賴於對未來需求的精確預測，過於粗略或不當的預測，不僅將造成大量 觀光資源的閒置與浪費，也將使得政府與觀光業者在這場日趨激烈的觀光 事業競爭中處於極不利的地位。本研究搜集並參考近十年來國內外學者在 觀光旅遊預測模式方面的研究，針對出國觀光旅客整體及各主要市場需求 ，尋找並建立適當之長短期預測模式。我們考慮下列六種模式：簡算法、 單變量時間序列模式、轉移函數模式、時間趨勢模式、指數平滑法以及計 量經濟模式，同時利用各類模式選取準則如AIC、SBC等來選取最佳模式， 或以平均絕對百分誤差(MA PE)、根均方百分誤差(RMSPE)、方向變化誤 差(Direction of Change Erro r)以及趨勢變化誤差(Trend Change Error)來評估各模式預測能力，從中選出最佳模式並進行預測整合分析。

Face recognition is one of the most natural activities performed by the human beings. It has wide range of applications in the areas of Human Computer Interaction, Surveillance, Security etc. Face information of people can be obtained in a non-intrusive manner, without violating privacy. But, robust face recognition which is invariant under varying pose, illumination etc is still a challenging problem. The main aim of this thesis is to explore the usefulness of smile profile of human beings as an extra aid in recognizing people by faces. Smile profile of a person is the sequence of images captured by a camera when the person voluntarily smiles. Using sequence of images instead of a single image will increase the required computational resources significantly. The challenge here is to design a feature extraction technique from a smile sample, which is useful for authentication and is also efficient in terms of storage and computational aspects. There are some experimental evidences which support the claim that facial expressions have some person specific information. But, to the best of our knowledge, systematic study of a particular facial expression for biometrical purposes has not been done so far. The smile profile of human beings, which is captured under some reasonably controlled setup, is used for first time for face recognition purpose. As a first step, we applied two of the recent subspace based face classifiers on the smile samples. We were not able to obtain any conclusive results out of this experiment. Next we extracted features using only the difference vectors obtained from smile samples. The difference vectors depend only on the variations which occur in the corresponding smile profile. Hence any characterization we obtain from such features can be fully attributed to the smiling action. The feature extraction technique we employed is very much similar to PCA. The smile signature that we have obtained is named as Principal Direction of Change(PDC). PDC is a unit vector (in some high dimensional space) which represents the direction in which the major changes occurred during the smile. We obtained a reasonable recognition rate by applying Nearest Neighbor Classifier(NNC) on these features. In addition to that, these features turn out to be less sensitive to the speed of smiling action and minor variations in face detection and head orientation, while capturing the pattern of variations in various regions of face due to smiling action. Using set of experiments on PDC based features we establish that smile has some person specific characteristics. But the recognition rates of PDC based features are less than the recent conventional techniques. Next we have used PDC based features to aid a conventional face classifier. We have used smile signatures to reject some candidate faces. Our experiments show that, using smile signatures, we can reject some of the potential false candidate faces which would have been accepted by the conventional face classifier. Using this smile signature based rejection, the performance of the conventional classifier is improved significantly. This improvement suggests that, the biometric information available in smile profiles does not exist in still images. Hence the usefulness of smile profiles for biometric applications is established through this experimental investigation.