A generalized multidimensional index structure for multimedia data to support content-based similarity searches in a collaborative search environment

Since multimedia data, such as images and videos, are way more expressive and informative than ordinary text-based data, people find it more attractive to communicate and express with them. Additionally, with the rising popularity of social networking tools such as Facebook and Twitter, multimedia information retrieval can no longer be considered a solitary task. Rather, people constantly collaborate with one another while searching and retrieving information. But the very cause of the popularity of multimedia data, the huge and different types of information a single data object can carry, makes their management a challenging task. Multimedia data is commonly represented as multidimensional feature vectors and carry high-level semantic information. These two characteristics make them very different from traditional alpha-numeric data. Thus, to try to manage them with frameworks and rationales designed for primitive alpha-numeric data, will be inefficient. An index structure is the backbone of any database management system. It has been seen that index structures present in existing relational database management frameworks cannot handle multimedia data effectively. Thus, in this dissertation, a generalized multidimensional index structure is proposed which accommodates the atypical multidimensional representation and the semantic information carried by different multimedia data seamlessly from within one single framework. Additionally, the dissertation investigates the evolving relationships among multimedia data in a collaborative environment and how such information can help to customize the design of the proposed index structure, when it is used to manage multimedia data in a shared environment. Extensive experiments were conducted to present the usability and better performance of the proposed framework over current state-of-art approaches.

A generalized adaptive mathematical morphological filter for LIDAR data

Airborne Light Detection and Ranging (LIDAR) technology has become the primary method to derive high-resolution Digital Terrain Models (DTMs), which are essential for studying Earth's surface processes, such as flooding and landslides. The critical step in generating a DTM is to separate ground and non-ground measurements in a voluminous point LIDAR dataset, using a filter, because the DTM is created by interpolating ground points. As one of widely used filtering methods, the progressive morphological (PM) filter has the advantages of classifying the LIDAR data at the point level, a linear computational complexity, and preserving the geometric shapes of terrain features. The filter works well in an urban setting with a gentle slope and a mixture of vegetation and buildings. However, the PM filter often removes ground measurements incorrectly at the topographic high area, along with large sizes of non-ground objects, because it uses a constant threshold slope, resulting in "cut-off" errors. A novel cluster analysis method was developed in this study and incorporated into the PM filter to prevent the removal of the ground measurements at topographic highs. Furthermore, to obtain the optimal filtering results for an area with undulating terrain, a trend analysis method was developed to adaptively estimate the slope-related thresholds of the PM filter based on changes of topographic slopes and the characteristics of non-terrain objects. The comparison of the PM and generalized adaptive PM (GAPM) filters for selected study areas indicates that the GAPM filter preserves the most "cut-off" points removed incorrectly by the PM filter. The application of the GAPM filter to seven ISPRS benchmark datasets shows that the GAPM filter reduces the filtering error by 20% on average, compared with the method used by the popular commercial software TerraScan. The combination of the cluster method, adaptive trend analysis, and the PM filter allows users without much experience in processing LIDAR data to effectively and efficiently identify ground measurements for the complex terrains in a large LIDAR data set. The GAPM filter is highly automatic and requires little human input. Therefore, it can significantly reduce the effort of manually processing voluminous LIDAR measurements.

Examination of the overlap between DSM-111-R overanxious disorder and DSM-IV generalized anxiety disorder in childhood

Since DSM-III-R criteria for Overanxious Disorder (OAD) was subsumed under Generalized Anxiety Disorder (GAD) in DSM-IV, three studies have investigated the overlap between the diagnoses. Although two studies have identified children meeting both OAD and GAD criteria (OAD/GAD group), a third study has identified children who met criteria for OAD, but not GAD (OAD group). Based on finding these two groups of children, we examined whether children in the OAD group (n= 30) could be differentiated from children in the OAD/GAD group (n=81) based on self and parent report of anxious symptoms and level of functional impairment. Conditional probability rates were also calculated for each of the DSM anxious symptoms to determine their overall clinicalutility. Findings revealed that the OAD group of children experienced fewer anxious symptoms than children in the OAD/GAD group, though both groups showed some amount of impairment. The implications for research and practice are discussed.

Mother-Infant Reciprocity and the Development of Joint Attention in 12 Month Old Infants

Social contingency is the ability to connect social stimuli, such as those behaviors performed by oneself and those performed by others. Detecting social contingencies occurs by means of reciprocity through shared experiences with others. Reciprocity denotes a circumstance in which two individuals participate in a collaborative exchange, and is distinguished from an event in which two individuals engage in separate, unrelated activities. Specifically, reciprocity incorporates joint attention (JA), which occurs when two individuals simultaneously and visually attend to the same item. JA is facilitated by gazing and pointing, whereby one individual initiates the action and the second individual follows suit by, for example, gaze-following. However, little is known about the role the mother may play in the development of JA. The purpose of our study was to investigate social contingency between mothers and infants engaging in dyadic interactions. Thirty-three 12-month-old typically developing infants (M = 12.2, SD = .19; N = 19 males) were filmed for 10 minutes during free play with their mothers and toys provided by an experimenter. Reciprocity was measured by coding mother-infant interactions when a precise chain of events occurred: (1) mother initiated a bid by introducing a toy/activity or request to the infant, (2) infant accepted the bid/request by engaging in play with the given toy/activity, and (3) mother persisted by continuing to engage in play with said toy/activity. We computed a Pearson Correlation to assess the relation between the mothers’ initiations of JA and their infants’ responses to JA. We found a moderately positive correlation between the two variables (r= 0.37, p<.05). Our findings suggest that reciprocity, an important component of social relationships, during parent-infant dyads may serve as a scaffold for joint attention abilities, which have been linked to social and language development.