MIS versus Computer Science: An Empirical Comparison of the Influences on the Students’ Choice of Major

A history of declining enrollments in university Management Information Systems (MIS) and computer science (CS) departments in the U.S. considerably impacts both college departments and business organizations that hire graduates. In order to reverse the enrollment trend, an understanding of the important similarities and differences that shape a student’s decision to major in MIS or CS will allow departments to better promote their major, formulate more effective strategies for reaching interested and undecided students, and enhance the fit between student and career. This study directly compared important influences on choice of major for 205 MIS and CS majors at four US universities. Results indicate that the most important influences for both MIS and CS students are interest in technology and monetary compensation. MIS majors, however, are significantly more influenced by others, especially college instructors, parents, friends, and the desire to interact with others. They are also more interested in business and business organizations. CS majors, on the other hand, are more interested in the technology itself and tend to choose CS as a major either in high school or shortly thereafter. Based on these findings, recommendations are provided to aid college departments in attracting and retaining appropriate majors

The interplay of intrinsic excitability and network topology in spatiotemporal pattern generation in neural networks

http://deepblue.lib.umich.edu/bitstream/2027.42/109555/1/12868_2014_Article_3550.pd

SELECTING A BUSINESS MAJOR WITHIN THE COLLEGE OF BUSINESS

This study employed a survey in examining the important influences that shape a student’s selection of a major in the College of Business (COB). In particular, it compared these influences, by major, to assess which items were most (and least) important to the students majoring in accounting, general business, finance, management, marketing, and MIS. The influences, totaling 37, included internal influences (e.g., interest in the field), external influences (e.g., projected salary), and interpersonal influences (influence of significant others). Some of the findings were consistent with those of prior studies. For example, interesting work was highly important for all business majors, and specific interpersonal influences such as parents, high school teachers, and peers were relatively unimportant. The findings presented herein suggest that the overall impact of interpersonal influence may have been underestimated in previous studies. Unlike many previous studies, this study showed that job availability and job security were more important to students than interest in the field. This study augments the extant literature in that the survey was conducted right after the 2009 recession, which allowed an analysis of student decision making during a period of high unemployment and lingering economic uncertainty. Implications and suggestions for further research are discussed

Network topology and intrinsic excitability of the existing network drive integration patterns in a model of adult neurogenesis

http://deepblue.lib.umich.edu/bitstream/2027.42/112379/1/12868_2013_Article_3276.pd

Modeling the formation and dynamics of cortical waves induced by cholinergic modulation

http://deepblue.lib.umich.edu/bitstream/2027.42/134563/1/12868_2015_Article_4163.pd

Connexin 43 gap junctions contribute to brain endothelial barrier hyperpermeability in familial cerebral cavernous malformations type III by modulating tight junction structure

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154657/1/fsb2fj201700699r-sup-0003.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154657/2/fsb2fj201700699r.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154657/3/fsb2fj201700699r-sup-0002.pd

Active sensors for health monitoring of aging aerospace structures

A project to develop non-intrusive active sensors that can be applied on existing aging aerospace structures for monitoring the onset and progress of structural damage (fatigue cracks and corrosion) is presented. The state of the art in active sensors structural health monitoring and damage detection is reviewed. Methods based on (a) elastic wave propagation and (b) electro-mechanical (NM) impedance technique are sighted and briefly discussed. The instrumentation of these specimens with piezoelectric active sensors is illustrated. The main detection strategies (E/M impedance for local area detection and wave propagation for wide area interrogation) are discussed. The signal processing and damage interpretation algorithms are tuned to the specific structural interrogation method used. In the high-frequency EIM impedance approach, pattern recognition methods are used to compare impedance signatures taken at various time intervals and to identify damage presence and progression from the change in these signatures. In the wave propagation approach, the acoustic-ultrasonic methods identifying additional reflection generated from the damage site and changes in transmission velocity and phase are used. Both approaches benefit from the use of artificial intelligence neural networks algorithms that can extract damage features based on a learning process. Design and fabrication of a set of structural specimens representative of aging aerospace structures is presented. Three built-up specimens, (pristine, with cracks, and with corrosion damage) are used. The specimen instrumentation with active sensors fabricated at the University of South Carolina is illustrated. Preliminary results obtained with the E/M impedance method on pristine and cracked specimens are presented

The Role of Native Language and the Fundamental Design of the Auditory System in Detecting Rhythm Changes

Accepted December 13, 2018Purpose: We investigated whether rhythm discrimination is mainly driven by the native language of the listener or by the fundamental design of the human auditory system and universal cognitive mechanisms shared by all people irrespective of rhythmic patterns in their native language. Method: In multiple experiments, we asked participants to listen to 2 continuous acoustic sequences and to determine whether their rhythms were the same or different (AX discrimination). Participants were native speakers of 4 languages with different rhythmic properties (Spanish, French, English, and German) to understand whether the predominant rhythmic patterns of a native language affect sensitivity, bias, and reaction time in detecting rhythmic changes in linguistic (Experiment 2) and in nonlinguistic (Experiments 1 and 2) acoustic sequences. We examined sensitivity and bias measures, as well as reaction times. We also computed Bayes factors in order to assess the effect of native language. Results: All listeners performed better (i.e., responded faster and manifested higher sensitivity and accuracy) when detecting the presence or absence of a rhythm change when the 1st stimulus in an AX test pair exhibited regular rhythm (i.e., a syllable-timed rhythmic pattern) than when the 1st stimulus exhibited irregular rhythm (i.e., stress-timed rhythmic pattern). This result pattern was observed both on linguistic and nonlinguistic stimuli and was not modulated by the native language of the participant. Conclusion: We conclude that rhythm change detection is a fundamental function of a processing system that relies on general auditory mechanisms and is not modulated by linguistic experience.The authors acknowledge support from Spanish Ministry of Economy and Competitiveness Grant PSI2017-82563-P (awarded to A. G. S.), the “Severo Ochoa” Programme for Centres/Units of Excellence in R&D Grant SEV-2015-490 (BCBL), and the Basque Foundation for Science Grant IKERBASQUE (awarded to A. G. S. and M. O.). D. M. G. was supported by Grant PIA/Basal FB0003 from the Chilean Research Council. L. P. was supported by the Spanish Ministry of Economy and Competitiveness via Juan de la Cierva fellowship