Melanie A. Sutton

Internet Use and Misuse Preliminary Findings from a New Assessment Instrument

The Internet is an affordable and easily accessible technology that has many potential applications to psychology. Interactive technologies engage users psychologically and may facilitate adaptive and maladaptive behaviors. This research explored the Internet-use patterns, psychological characteristics, and negative consequences associated with online activities of 393 college students using the Internet Use Survey (IUS), a self-report instrument designed to administer online. Results indicated that participants spent an average of 3.3 total hours per day on the Internet during the past 12 months and used the medium for multiple purposes. Although participants reported the occurrence of some potentially negative consequences related to Internet use, the prevalence rates for most problematic behaviors were generally low. Exploratory principal component analysis of the IUS subscale that attempts to measure Internet-related impairment revealed four factors: absorption, negative consequences, disrupted sleep, and deception. All of these factors were then significantly related to a measure of boredom proneness. This research supports the necessity for multidimensional assessment (e.g., frequency and context) of Internet usage to enhance our understanding of how this new technology interfaces with users psychologically and behaviorally.

Multiresolution-based segmentation of calcifications for the early detection of breast cancer

Clusters of microcalcifications in a mammogram may be an early indication of breast cancer. Unfortunately, due to size, shape and limited contrast from surrounding normal tissue, microcalcifications can occasionally be hard to detect in computer-aided detection (CAD) systems. These CAD systems can also be slow compared to a radiologists performance when reviewing film-screen mammography. The research described here investigates a rapid, multiresolution-based approach combined with wavelet analysis to provide an accurate segmentation of potential calcifications. An initial multiresolution approach to fuzzy c-means (FCM) segmentation is employed to rapidly distinguish medically significant tissues. Tissue areas chosen for high-resolution analysis are broken into multiple windows. Within each window, wavelet analysis is used to generate a contrast image, and a local FCM segmentation generates an estimate of local intensity. A simple two-rule fuzzy system then combines intensity and contrast information to derive fuzzy memberships of pixels in the high-contrast, bright pixel class. A double threshold is finally applied to this fuzzy membership to detect and segment calcifications. This sequence of steps is shown to approach detection rates of conventional classifier designs and may therefore be useful as a pre-processing module for these systems to improve speed. Results are reported for 25 images obtained from the Digital Database for Screening Mammography (DDSM).

Function from visual analysis and physical interaction: a methodology for recognition of generic classes of objects

The GRUFF-I (Generic Recognition Using Form, Function and Interaction) system reasons about and generates plans for interaction with 3-D shapes for the purpose of generic object recognition. A researcher selects an object and places it in an observation area. An initial intensity and range image are acquired and provided as input to a three-stage recognition system. The first stage builds a 3-D model. The second stage considers the shape-suggested functionality of this model by applying concepts of physics and causation (e.g., to infer stability) to label the objects potential functionality. The third stage uses this labeling to instantiate a plan for interaction to confirm the objects functional use in a task by incorporating feedback from both visual and robotic sensors. Results of this work are presented for eighteen chair-like and cup-like objects. Major conclusions from this work include: (1) metrically accurate representations of the world can be built and used for higher level reasoning, (2) shape-based reasoning prior to interaction-based reasoning provides an efficient methodology for object recognition, in terms of the judicious use of system resources, and (3) interaction-based reasoning helps to confirm the functionality of a categorized object without explicitly determining the objects material composition.

Enhancement and analysis of digital mammograms using fuzzy models

This paper describes our work in enhancing and analyzing digital mammograms form the digital database for screening mammography (DDSM). The DDSM will ultimately contain 3000 cases and provides a unique opportunity for researchers form around the world to compare results on a large, diverse data set. However, the size of the database and images within it require careful consideration of memory limitation issues, display device constraints, etc. We address research problems connected with the modification and application of existing fuzzy modeling approaches to this digital mammography domain. Segmentation and edge detection are sued as benchmark applications for the comparisons we make.

Thermal Tolerance and Metabolic Responses of Two Damselfish Species from a Hyperthermic Rockpool Nursery in Dry Tortugas National Park, USA

Abstract Beachrock formations on Loggerhead Key in Dry Tortugas National Park, USA are an important nursery for many juvenile reef fishes. Wide variations in temperature are common in these areas and can markedly influence fish metabolism and thermal tolerance. We determined routine resting metabolic rate and temperature quotient (Q10) at 24 and 32°C. Thermal tolerance (measured as critical thermal maximum, CTmax) was also measured for sergeant major (Abudefduf saxitilis) and cocoa damselfish (Stegastes variabilis) acclimatized to beachrock nursery temperatures. Sergeant majors occupied shallow rockpool margins that experience rapid, extreme temperature changes. These fish exhibited relatively low metabolic rates, reduced Q10 values (2.40), and relatively high levels of temperature tolerance (CTmax = 40.0°C). Cocoa damselfish selected deeper, more thermally stable rockpool areas. These fish had higher metabolic rates, were more sensitive to temperature increase (Q10 = 2.84), and were less tolerant of high temperatures (CTmax = 38.6°C) than sergeant majors. Metabolic and temperature tolerance adaptations of juvenile sergeant majors and cocoa damselfish allow these fishes to exploit a variety of microhabitats found in beachrock areas on Loggerhead Key.

Metabolic Thermal Sensitivity Optimizes Sea Krait Amphibious Physiology

Abstract Yellow-lipped Sea Kraits (Laticauda colubrina) are tropical amphibious snakes that divide their time between land and sea. When moving between habitats, the kraits experience rapid and sometimes extreme shifts in body temperature that can have profound metabolic effects. We quantified cutaneous and pulmonary oxygen uptake in sea kraits from Hoga Island, southeast Sulawesi, Indonesia, at temperatures commonly encountered in aquatic (27.6°C) and aerial (35.2°C) habitats. Total oxygen uptake rate was 49.14 mL Kg−1 h−1 at 27.6°C and 115.27 mL Kg−1 h−1 at 35.2°C. Pulmonary and cutaneous uptake rates were 44.58 and 104.70, and 4.56 and 10.57 mL Kg−1 h−1, at 27.6 and 35.2°C, respectively. Sea kraits had a temperature coefficient (Q10) of approximately 3, suggesting that metabolic rates triple with every 10°C temperature increase. High Q10 values may minimize time on land by increasing digestion and nutrient absorption rates as well as promoting faster healing and injury recovery times. Cooler reef temperatures would decrease metabolic demand, thus increasing submergence and foraging times.

Exploiting Context in Function-Based Reasoning

This paper presents the framework of the new context-based reasoning components of the GRUFF (Generic Recognition Using Form and Function) system. This is a generic object recognition system which reasons about and generates plans for understanding 3-D scenes of objects. A range image is generated from a stereo image pair and is provided as input to a multi-stage recognition system. A 3-D model of the scene, extracted from the range image, is processed to identify evidence of potential functionality directed by contextual cues. This recognition process considers the shape-suggested functionality by applying concepts of physics and causation to label an objects potential functionality. The methodology for context-based reasoning relies on determining the significance of the accumulated functional evidence derived from the scene. For example, functional evidence for a chair or multiple chairs along with a table, in set configurations, is used to infer the existence of scene concepts such as office or meeting room space. Results of this work are presented for scene understanding derived from both simulated and real sensors positioned in typical office and meeting room environments.

Image Processing in Medicine

Image processing covers a lot of territory, including its use as an enabling technology for the more ambitious undertaking which is nowadays called computer vision (Jain et al., 1995). A comprehensive survey of fuzzy models for image processing and computer vision would require its own volume (cf. Chapter 5 of Bezdek et al., 1999). This chapter is confined to applications of image processing in medical domains that are not based on neural network models or mathematical morphology. Others chapters of this handbook address these topics. Even these strict constraints leave us in the unenviable position of having to choose from more excellent work than we have space to review, and the perhaps inexcusable position of being ignorant about some work of which we are simply unaware. With apologies to the many authors of papers in either category, we offer a snapshot of the use of fuzzy models for image processing in computational medicine.

Function-based reasoning for goal-oriented image segmentation

Function-based object recognition provides the framework to represent and reason about object functionality as a means to recognize novel objects and produce plans for interaction with the world. When function can be perceived visually, function-based computer vision is consistent with Gibsons theory of affordances. Objects are recognized by their functional attributes. These attributes can be segmented out of the scene and given symbolic labels which can then be used to guide the search space for additional functional attributes. An example of such affordance-driven scene segmentation would be the process of attaching symbolic labels to the areas that afford sitting (functional seats) and using these areas to guide parameter selection for deriving nearby surfaces that potentially afford back support. The Generic Recognition Using Form and Function (GRUFF) object recognition system reasons about and generates plans for understanding 3-D scenes of objects by performing such a functional attribute-based labelling process. An avenue explored here is based on a novel approach of autonomously directing image acquisition and range segmentation by determining the extent to which surfaces in the scene meet specified functional requirements, or provide affordances associated with a generic category of objects.

Internet forewarning effects on ratings of attraction

This study investigates interpersonal attraction and the use of forewarning messages on the Internet. Male and female participants observed four photographs of the opposite sex on-line. Half of the participants were given a forewarning about the use of deception on the Internet before they rated the person depicted in the target photo. The control group was not exposed to the forewarning but instead read a general statement describing the Internet. Participants rated the photos for attractiveness, how likely they would be to engage in an on-line conversation with the person in the photo, and how likely they would be to accept a date with the person in the photo. The target photos attractiveness and socioeconomic status were varied. The results indicated that a forewarning message might induce cautiousness among those using the Internet. Experimental group participants rated target photos as less attractive compared to those who were not shown a forewarning message, and were less likely to want to converse with or date the people depicted in the on-line photos. The implications of these findings in regard to Internet social behavior are discussed.