APPLICATIONS OF SPECTRAL ANALYSIS

The basic concepts and application of spectral analysis are explained. Stationary time series and autocorrelation are first defined. Autocorrelation is related to the familiar concepts of variance and covariance. The use of autocorrelation analysis is explained in estimating the interdependent relationship of a time series over discrete time lags. In order to measure the behavior of the time series using autocorrelation, it would be necessary to examine a very large number of autocorrelation lags. Alternatively, the technique of Fourier analysis can be used to transform the autocorrelation function of the time series into a continuous function, termed a spectrum. The spectrum has a one to one correspondence to the autocorrelation for the time series and has the advantage of representing all possible autocorrelations over the discrete time lags. The spectrum can then be examined as a measure of the behavior of the time series. Spectral analysis indicates the reliability of the analysis of autocorrelated variables when familiar statistical techniques such as sample means and variances are used. The application of spectral analysis to management science problems in three general areas is illustrated: (1) inventory demand, (2) transportation simulation, and (3) stock market price behavior. Spectral analysis was used to detect cycles and trends in the data. Analyses were focused on the spectrum which provides a measure of the relative contribution of cycles in a band of frequencies to the total variance of the data.     

Cultural Connection Predicts Perceptions of Financial Security for Māori

This paper examines the impact of relative income on income satisfaction with given absolute income. We conducted an experiment in China where participants earned three different levels of income according to their relative performance in a task. While the treatment group was informed about their relative income, the control group only knew their own absolute income. We found that while controlling for absolute income and other factors, information about relative income increases the satisfaction of the high-income group and reduces the satisfaction of the low-income group. Relative income may interact with individual characteristics, such as gender, to affect income satisfaction. We also found that relative income treatment significantly increases income satisfaction inequality, primarily by causing social comparisons among different income groups, which has some welfare implications.     

Integrationspotenziale des Internets für türkische Jugendliche in Wien am Beispiel von Online-Spielen und digitalen Freundschaftsnetzwerken

Based on a cohort of young Austrians of Turkish descent, this paper links the debate on the integration of the second generation (or the lack thereof) with the controversial discourse about the potential usefulness and risks of new media and technologies, specifically the Internet. Various studies have concluded either that the new media and technologies are positive integrative aspects of the society or have devastating impacts on different groups. On the one hand, the Internet allows young people to discover new experiences and gain additional often unorthodox knowledge; on the other hand, observers have warned about the segregating effects of new technologies. A ?digital divide“ has been opened between privileged users and the underprivileged masses, according to these more cautious voices. This divide has caused social deprivation and disintegration amongst the most vulnerable groups, in particular, older people, economically insecure groups and immigrants. Thus, various media life-styles establish a continuum between a media and information elite on the one end and the entertainment under-class on the other. Semi structured interviews with young Turks in Vienna show the positive and negative effects of playing Online Role Playing Games on the Internet in opposition to so-called Social Network Sites such as Netlog.     

Mental health citizen surveys: a comparison of two within household telephone sampling techniques.

Two within household telephone sampling techniques for collecting citizen survey data for community mental health center's needs assessments were compared on the basis of respondent demographic characteristics; response, completion, and refusal rates; and, administrative costs. Initially, all households were chosen via random digit dialing. Then, one technique allowed the surveyor to interview any adult member of a household who answered the phone. The other technique used was developed by Troldahl and Carter and required the use of a reference table procedure to determine the appropriate respondent. While more expensive, the Troldahl-Carter method produced significantly better representativeness of the population for a rural county. Factors relating to a decision regarding which technique to employ are discussed.     

Internet Technology in Service of Personal Health Care Management: Patient Perspective

Internet technology has become an informational resource for most health care consumers. Online information, discussion, and support groups, in the form of message boards, listservs, and chat rooms are emerging as parts of virtual self-health-care network. This paper examines the extent to which participation in online health discussion groups was reported to be helpful in increasing medical knowledge and in enhancing the participatory patient role of health care consumers in interaction with health care service professionals. Data for this study was collected from 350 patients who participated in Internet discussion groups for cancer patients. The findings of the study indicated the important impact of Internet health discussion groups on health care management practices as perceived by health care consumers, including empowerment through knowledge and proactive participation in cancer care management. This research contributes to understanding the patient perspective and assesses the perceived importance of Internet groups by health care consumers.     

Methods for spatial and temporal land use and land cover assessment for urban ecosystems and application in the greater Baltimore-Chesapeake region

Understanding contemporary urban landscapes requires multiple sets of spatially and temporally compatible data that can integrate historical land use patterns and disturbances to land cover. This paper presents three principal methods: (1) core analysis; (2) historic mapping; and (3) gradient analysis, to link spatial and temporal data for urban ecosystems and applies their use in the Baltimore-Chesapeake region. Paleoecological evidence derived from the geochronology of sediment cores provides data on long-term as well as recent changes in vegetative land cover. This information, combined with contemporary vegetation maps, provides a baseline for conducting trend analyses to evaluate urbanization of the landscape. A 200-year historical land use database created from historical maps, census data, and remotely sensed data provides a spatial framework for investigating human impacts on the region. A geographic information system (GIS) integrates core analyses with historic data on land use change to yield a comprehensive land use and land cover framework and rates of change. These data resources establish the regional foundation for investigating the ecological components of an urban ecosystem. Urban-rural gradient analyses and patch analyses are proposed as the most appropriate methods for studying the urban ecosystem as they link ecological and social patterns and processes for varying degrees of urbanization.