No description available.

Thesis (M.S.) - U.S. Naval Postgraduate School, 1966. / Bibliography: leaves 57-[58].

No description available.

Quasi-geostrophic (QG) analysis of the atmosphere utilizes predefined isobaric surfaces to ascertain vertical motion. One equation of the QG system is the omega equation that states that vertical forcing results from differential vorticity advection and thickness advection. Two problems arise when using the QG omega equation: the forcing terms are not independent and must be analyzed simultaneously, and vertical forcing is visually noisy. Both issues are resolved using a smoothing and quantification technique that applies the QG omega equation. The analysis fields from a selection of events were chosen from the North American Mesoscale model. Using a finite differencing methodology dependent on the wavelength of synoptic features, values of vertical forcing were calculated using the omega equation. The calculated omega field correlated well with model omega while also quantifying and visualizing large perturbations in vertical forcing. The method allows for quick diagnosis of forcing type and strength within the atmosphere.

Dans cette thèse, nous proposons une approche méthodologique et algorithmique pour la reconnaissance visuelle d'intentions, basée sur la rotation et le mouvement vertical de la tête et de la main. Le contexte dans lequel cette solution s'inscrit est celui d'une personne handicapée, dont la mobilité est assurée par un fauteuil roulant. Le système proposé constitue une alternative intéressante aux interfaces classiques de type manette, boutons pneumatiques, etc. La séquence vidéo, composée de 10 images, est traitée en utilisant différentes méthodes pour construire ce qui dans cette thèse est désigné par « courbe d'intention ». Une base de règles est également proposée pour classifier chaque courbe d'intention. Pour la reconnaissance basée sur les mouvements de la tête, une approche utilisant la symétrie du visage est proposée pour estimer la direction désirée à partir de la rotation de la tête. Une Analyse en Composantes Principales (ACP) est utilisée pour détecter l'intention de varier la vitesse de déplacement du fauteuil roulant, à partir du mouvement vertical de la tête. Pour la reconnaissance de la direction basée sur la rotation de la main, une approche utilisant à la fois la symétrie verticale de la main et un algorithme d'apprentissage (réseaux neuronaux, machines à vecteurs supports ou k-means), permet d’obtenir les courbes d'intentions exploitées par la suite pour la détection de la direction désirée. Une autre approche, s’appuyant sur l'appariement de gabarits de la région contenant les doigts, est également proposée. Pour la reconnaissance de la vitesse variable basée sur le mouvement vertical de la main, deux approches sont proposées. La première utilise également l'appariement de gabarits de la région contenant les doigts, et la deuxième se base sur un masque en forme d'ellipse, pour déterminer la position verticale de la main. Les résultats obtenus montrent de bonnes performances en termes de classification aussi bien des positions individuelles dans chaque image, que des courbes d'intentions. L’approche de reconnaissance visuelle d’intentions proposée produit dans la très grande majorité des cas un meilleur taux de reconnaissance que la plupart des méthodes proposées dans la littérature. Par ailleurs, cette étude montre également que la tête et la main en rotation et en mouvement vertical constituent des indicateurs d'intention appropriés / In this thesis, a methodological and algorithmic approach is proposed, for visual intention recognition based on the rotation and the vertical motion of the head and the hand. The context for which this solution is intended is that of people with disabilities whose mobility is made possible by a wheelchair. The proposed system is an interesting alternative to classical interfaces such as joysticks and pneumatic switches. The video sequence comprising 10 frames is processed using different methods leading to the construction of what is referred to in this thesis as an “intention curve”. A decision rule is proposed to subsequently classify each intention curve. For recognition based on head motions, a symmetry-based approach is proposed to estimate the direction intent indicated by a rotation and a Principal Component Analysis (PCA) is used to classify speed variation intents of the wheelchair indicated by a vertical motion. For recognition of the desired direction based on the rotation of the hand, an approach utilizing both a vertical symmetry-based approach and a machine learning algorithm (a neural network, a support vector machine or k-means clustering) results in a set of two intention curves subsequently used to detect the direction intent. Another approach based on the template matching of the finger region is also proposed. For recognition of the desired speed variation based on the vertical motion of the hand, two approaches are proposed. The first is also based on the template matching of the finger region, and the second is based on a mask in the shape of an ellipse used to estimate the vertical position of the hand. The results obtained display good performance in terms of classification both for single pose in each frame and for intention curves. The proposed visual intention recognition approach yields in the majority of cases a better recognition rate than most of the methods proposed in the literature. Moreover, this study shows that the head and the hand in rotation and in vertical motion are viable intent indicators

A radar altimetry satellite measures the height of sea surface globally. However, tide gauges, measuring Sea Level Height (SLH), are set up on the Earth surface. Hence, SLHs are involved in vertical motion of the Earth crust. In this study, vertical motions of Earth crust have been separated from sea level variations. After clustering of SSH observations with K-means approach, two outlier detection methods Pope and Interquartile (IQR) Tests are implemented in data. Afterwards, each altimetry measurement is relocated to the center point of own cluster by means of geoid height derived from Earth Gravitational Model 2008 (EGM08). Before application of Principal Component Analysis (PCA) to see behavior of SSH inbetween clusters, Lomb Scargle algorithm is run to realize power spectrum of every clustered observations distinctly. Besides, tide gauge measurements are used for extracting 68 constituents with T_Tide program from hourly tide gauge observations. Then, predicted signal is produced by means of classical tidal harmonic analysis. To get monthly and daily mean values of hourly data, MSDOS Processing and Quality Controlling Software (SLPR2) has been run and the results are compared with Permanent Service for Mean Sea Level (PSMSL) monthly mean sea level values. Afterwards, the trends from altimetry, tide gauge and GPS are investigated to reveal vertical land motion. This study shows that sea level is rising every year more or less 7 mm at the Mediterranean coast of Turkey. Although Iskenderun tide gauge subsides 50 mm every year, the other stations do not show huge amount of vertical motion.

Kyoto University (京都大学) / 0048 / 新制・課程博士 / 博士(工学) / 甲第16391号 / 工博第3472号 / 新制||工||1525(附属図書館) / 29022 / 京都大学大学院工学研究科建築学専攻 / (主査)教授 中島 正愛, 教授 河井 宏允, 教授 竹脇 出 / 学位規則第4条第1項該当

Vertikala strukturer i byggnader har blivit väldigt vanligt och mer komplexa, därmed ökar vikten av wayfinding. Syftet med denna studie var att undersöka om en tredimensionell modell av en spiraltrappa ökar spatiala orienteringen när man rör sig vertikalt via den motsvarande existerande trappan. Ett experiment utfördes med 25 deltagare, 13 män and 12 kvinnor, mellan åldrarna 18-29 (M= 23.12, SD= 2.93). Hälften blev fördelade till testgrupp och andra hälften till kontrollgrupp. Båda grupper studerade en karta i 30 sekunder och blev instruerade att gå till ett mål på översta våningen. Testgruppen presenterades med ett visuellt hjälpmedel innan de gick in i trappan, kontrollgruppen såg inte detta hjälpmedel. När deltagarna nått översta våningen var deras uppgift att peka till tre olika platser, målet, starten och till Universum byggnaden med en kompassapplikation. Graderna av fel vid pekandet räknades ut och analyserades. Deltagarna fyllde även i Santa Barbara Sense of Direction skalan för att undersöka deras spatiala förmåga. Andra aspekter som togs i aktsamhet var huruvida de var familjära med byggnaden sedan tidigare och skillnader i utförandet mellan kvinnor och män. Resultatet visade något mindre fel vid pekuppgifterna av testgruppen än kontrollgruppen, dock visades ingen signifikant skillnad i datan. Alternativa tolkningar av resultatet och begränsningar tas upp i diskussionen. / Vertical structures in buildings have become very common and more complex, and thereby the importance of wayfinding increases. The aim of the present study was to investigate whether a three-dimensional model of a spiral staircase will improve spatial orientation when travelling in vertical motion via the corresponding real-world staircase. An experiment was conducted with 25 participants, 13 males and 12 females, between the ages of 18-29 (M= 23.12, SD= 2.93). They were divided into a test-group and a control-group. Both groups studied a map for 30 seconds and were instructed to walk to a goal on the top floor. The test-group was presented with a three-dimensional representation of the staircase as a visual aid before entering the stairs, the control-group was not presented with the aid. When the participants reached the top floor, they were instructed to point to the goal, the start and to the Universum building using a compass application. The pointing error was calculated and analyzed. The participants also filled in the Santa Barbara Sense of Direction scale to assess their spatial ability. Other aspects that was taken into consideration was to what extent the participants were familiar with the building the experiment took place in and differences in performance between men and women. Results show an indication of a smaller pointing error for the test-group than the control-group in all pointing tasks, however there were no statistically significant differences in the data. Alternative interpretations of the results and limitations of the study are discussed.