For the English Catholic Sports College, based in Westgate, see Ursuline College, Westgate-on-Sea.Ursuline College is a small, Roman Catholic liberal arts women's college in Pepper Pike, Ohio, United States. It was founded in 1871 by the Ursuline Sisters of Cleveland and is one of the oldest institutions of higher education for women in the United States. Ursuline College offers a diverse spectrum of undergraduate and graduate studies within the Catholic tradition of education. The College offers 30 undergraduate, 11 graduate programs, and a Doctorate of Nursing Practice. Although Ursuline College is considered to be a college that focuses primarily on the liberal arts, the institution also offers courses such as nursing and business administration. The school is widely recognized for its Art Therapy program, Breen School of Nursing, and teaching certification program. The campus is situated approximately 10 miles outside of Cleveland and 30 miles outside of Akron. Ursuline's campus is quite spacious and meticulously landscaped, featuring 12 educational buildings such as the Matthew J. O'Brien Recreation Complex, and the newer Bishop Anthony M. Pilla Center. The Pilla Center is quintessentially the essence of the Ursuline College Campus, acting as the social catalyst for students to meet and exchange ideas in the confines of a spectacularly engineered building. The main gathering space has a delightful view of the lake, and is two stories high with crystalline glass windows on adjacent sides, and a luminescent stained glass window that faces the main quadrangle. The building provides a space for commuters on the go, as well as resident students and faculty, for a place to converse or grab some sustenance on the way to class. Additionally, the college's Florence O'Donnell Wasmer Gallery is host to changing display of both professional and student artwork exhibits, and remains open for public consumption Tuesday through Sunday in the afternoon. Wikipedia.
News Article | November 9, 2016
AccreditedSchoolsOnline.org, the Community for Accredited Online Schools has released it’s ranking of the 2016-2017 Best Paralegal Schools in the U.S. Using more than a dozen unique statistics from both online and on-campus Paralegal programs across the country, the higher education resource provider awarded top marks to Madonna University, Hampton University, Colorado Mountain College, Utah Valley University and Mount Saint Joseph University for four-year schools and Metropolitan Community College, Cape Fear Community College, Cincinnati State Technical and Community College, Johnson County Community College and South Piedmont Community College for two-year schools. “Earning a paralegal degree can open many doors for students interested in law,” said Doug Jones, CEO and Founder of the Community for Accredited Online Schools. “These schools are going above and beyond to provide their students the stepping stones to success, whether they plan to go on to law school or begin a paralegal career immediately after graduation.” Schools earning a spot on the Best Paralegal Schools ranking are required to meet several standards. Each must hold regional accreditation and be registered as public or private not-for-profit institutions. Schools must also provide career placement services to students after graduation. The Community for Accredited Online Schools analyzes school-specific statistics, such as graduation rates, student teacher ratios and financial aid availability, to determine a score and rank for each qualifying college. The Best Two-Year and Four-Year Schools with Paralegal Programs in the U.S. are listed alphabetically below. Rankings and school scores can be found at the link below, along with details on the data and methodology used: Baker College of Auburn Hills Bay Path University College of Our Lady of the Elms College of Saint Mary College of Southern Nevada Colorado Mountain College Daemen College Davenport University Eastern Kentucky University Gannon University Hampton University Highline College Humphreys College – Stockton, Modesto Campuses Husson University Idaho State University Lewis-Clark State College Liberty University Madonna University Marian University Marist College Midland College Missouri Western State University Mount Saint Joseph University Pennsylvania College of Technology Roger Williams University Saint Mary of the Woods College St Petersburg College State College of Florida - Manatee-Sarasota Suffolk University Texas State University Touro College University of Akron Main Campus University of Alaska Fairbanks University of Arkansas - Fort Smith University of Cincinnati - Clermont College University of Cincinnati - Main Campus University of Detroit Mercy University of Great Falls University of Hartford University of La Verne University of Louisville University of North Georgia University of Toledo Ursuline College Utah Valley University Washburn University Webster University Wesley College Widener University - Delaware Campus William Woods University About Us: The Community for Accredited Online Schools (AccreditedSchoolsOnline.org) was founded in 2011 to provide students and parents with quality data and information about pursuing an affordable education that has been certified by an accrediting agency. Our community resource materials and tools span topics such as college accreditation, financial aid, opportunities available to veterans, people with disabilities, as well as online learning resources. We feature higher education institutions that have developed online learning programs that include highly trained faculty, new technology and resources, and online support services to help students achieve educational success. environments that include highly trained faculty, new technology and resources, and online support services to help students achieve educational and career success.
News Article | February 17, 2017
The Community for Accredited Online Schools, a leading resource provider for higher education information, has ranked the best two- and four-year colleges with online programs in the state of Ohio for 2017. Among four-year schools a total of 41 made the list, with University of Akron, University of Toledo, University of Cincinnati, Ohio University and Ashland University coming in as the top five schools. The state’s top 18 two-year schools were also honored, with Sinclair College, Cincinnati State Technical and Community College, Belmont College, Edison State Community College and Columbus State Community College taking the top five spots. Schools were ranked based on over a dozen different data points. “Student enrollment in schools within the University System of Ohio has grown 8 percent over the past decade,” said Doug Jones, CEO and founder of AccreditedSchoolsOnline.org. “As more students pursue post-secondary degrees, the schools on our list are providing more flexible, high-quality learning opportunities outside the traditional classroom.” To be included on the Best Online Schools list, colleges must meet specific base requirements, including being institutionally accredited and public or private not-for-profit institutions. Each college is scored based on additional criteria that includes its employment and counseling resources, student/teacher ratios, graduation rates and financial aid availability. For more details on where each school falls in the rankings and the data and methodology used to determine the lists, visit: Ohio’s Best Online Four-Year Schools for 2017 include the following: Ashland University Baldwin Wallace University Bowling Green State University-Main Campus Case Western Reserve University Cedarville University Cleveland State University Defiance College Franciscan University of Steubenville Franklin University God’s Bible School and College Hiram College Kent State University at Kent Kent State University at Salem Kettering College Malone University Miami University-Oxford Mount Carmel College of Nursing Mount Saint Joseph University Mount Vernon Nazarene University Muskingum University Notre Dame College Ohio Christian University Ohio University-Main Campus Otterbein University Shawnee State University The University of Findlay Tiffin University Union Institute & University University of Akron Main Campus University of Cincinnati-Main Campus University of Dayton University of Mount Union University of Northwestern Ohio University of Rio Grande University of Toledo Urbana University Ursuline College Walsh University Wright State University-Lake Campus Wright State University-Main Campus Youngstown State University Ohio’s Best Online Two-Year Schools for 2017 include the following: Belmont College Bowling Green State University-Firelands Central Ohio Technical College Cincinnati State Technical and Community College Clark State Community College Columbus State Community College Cuyahoga Community College Edison State Community College Hocking College Lakeland Community College Lorain County Community College Marion Technical College North Central State College Northwest State Community College Rhodes State College Sinclair College Stark State College University of Akron Wayne College ### About Us: AccreditedSchoolsOnline.org was founded in 2011 to provide students and parents with quality data and information about pursuing an affordable, quality education that has been certified by an accrediting agency. Our community resource materials and tools span topics such as college accreditation, financial aid, opportunities available to veterans, people with disabilities, as well as online learning resources. We feature higher education institutions that have developed online learning programs that include highly trained faculty, new technology and resources, and online support services to help students achieve educational success.
Wu C.-F.,Ursuline College |
Lin C.-J.,National Chin - Yi University of Technology |
Lee C.-Y.,University for Information Science and Technology
IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews | Year: 2012
Most traffic accidents resulted from distraction, inattention to surrounding cars, and driving fatigue. In order to protect drivers, a real-time lane-detection and front-vehicle distance measurement system that uses a mounted camera inside a vehicle has been designed for safe driving. For lane detection, the lane-boundary information is derived from the fan-scanning-detection method. The system calculates the departure degree according to the angular relationship of the boundaries and sends a suitable warning signal to drivers. For front-vehicle distance measurement, we use the front vehicles shadow underneath it to identify the position of the front vehicle. The real distance is estimated by the use of the functional neurofuzzy network. The experimental results show that the system works successfully in real-time environment. © 2012 IEEE.
Wu C.-F.,Ursuline College |
Lin C.-J.,National Chin - Yi University of Technology
International Journal of Innovative Computing, Information and Control | Year: 2013
This study proposes a real-time video stabilization method to eliminate unwanted vibration, preserve the intended movement of camera, and improve the stability of the captured video sequence. The proposed method uses a functional neural fuzzy network to learn the characteristics of different vibrations and then choose the adequate compen-sation weight for two different methods to calculate the correction vector. Experimental results show that the proposed method has superior performance over other motion com-pensation methods. © 2013 ICIC International.
Wei L.-Y.,Yuanpei University |
Chen T.-L.,Ursuline College |
Ho T.-H.,Yuanpei University
Expert Systems with Applications | Year: 2011
In recent years, many academy researchers have proposed several forecasting models based on technical analysis to predict models such as Engle (1982) and Cheng, Chen, and Wei (2010). After reviewing the literature, two major drawbacks are found in past models: (1) the forecasting models based on artificial intelligence algorithms (AI), such as neural networks (NN) and genetic algorithms (GAs), produce complex and unintelligible rules; and (2) statistic forecasting models, such as time series, require some basic assumptions for variables and build forecasting models based on mathematic equations, which are not easily understandable by stock investors. In order to refine these drawbacks of past models, this paper has proposed a model, based on adaptive-network- based fuzzy inference system which uses multi-technical indicators, to predict stock price trends. Three refined processes have proposed in the hybrid model for forecasting: (1) select essential technical indicators from popular indicators by a correlation matrix; (2) use the subtractive clustering method to partition technical indicator value into linguistic values based on an data discretization method; (3) employ a fuzzy inference system (FIS) to extract rules of linguistic terms from the dataset of the technical indicators, and optimize the FIS parameters based on an adaptive network to produce forecasts. A six-year period of the TAIEX is employed as experimental database to evaluate the proposed model with a performance indicator, root mean squared error (RMSE). The experimental results have shown that the proposed model is superior to two listing models (Chen's and Yu's models). © 2011 Elsevier Ltd. All rights reserved. © 2011 Elsevier Ltd. All rights reserved.
Lee H.-C.,Ursuline College |
Chen T.-F.,National Chung Cheng University
Computers and Mathematics with Applications | Year: 2010
The paper concerns a nonlinear weighted least-squares finite element method for the solutions of the incompressible Stokes equations based on the application of the least-squares minimization principle to an equivalent first order velocity-pressure-stress system. Model problem considered is the flow in a planar channel. The least-squares functional involves the L 2-norms of the residuals of each equation multiplied by a nonlinear weighting function and mesh dependent weights. Using linear approximations for all variables, by properly adjusting the importance of the mass conservation equation and a carefully chosen nonlinear weighting function, the least-squares solutions exhibit optimal L 2-norm error convergence in all unknowns. Numerical solutions of the flow pass through a 4 to 1 contraction channel will also be considered. © 2009 Elsevier Ltd. All rights reserved.
Cheng C.-H.,National Yunlin University of Science and Technology |
Chen T.-L.,Ursuline College |
Wei L.-Y.,Yuanpei University
Information Sciences | Year: 2010
In the stock market, technical analysis is a useful method for predicting stock prices. Although, professional stock analysts and fund managers usually make subjective judgments, based on objective technical indicators, it is difficult for non-professionals to apply this forecasting technique because there are too many complex technical indicators to be considered. Moreover, two drawbacks have been found in many of the past forecasting models: (1) statistical assumptions about variables are required for time series models, such as the autoregressive moving average model (ARMA) and the autoregressive conditional heteroscedasticity (ARCH), to produce forecasting models of mathematical equations, and these are not easily understood by stock investors; and (2) the rules mined from some artificial intelligence (AI) algorithms, such as neural networks (NN), are not easily realized. In order to overcome these drawbacks, this paper proposes a hybrid forecasting model, using multi-technical indicators to predict stock price trends. Further, it includes four proposed procedures in the hybrid model to provide efficient rules for forecasting, which are evolved from the extracted rules with high support value, by using the toolset based on rough sets theory (RST): (1) select the essential technical indicators, which are highly related to the future stock price, from the popular indicators based on a correlation matrix; (2) use the cumulative probability distribution approach (CDPA) and minimize the entropy principle approach (MEPA) to partition technical indicator value and daily price fluctuation into linguistic values, based on the characteristics of the data distribution; (3) employ a RST algorithm to extract linguistic rules from the linguistic technical indicator dataset; and (4) utilize genetic algorithms (GAs) to refine the extracted rules to get better forecasting accuracy and stock return. The effectiveness of the proposed model is verified with two types of performance evaluations, accuracy and stock return, and by using a six-year period of the TAIEX (Taiwan Stock Exchange Capitalization Weighted Stock Index) as the experiment dataset. The experimental results show that the proposed model is superior to the two listed forecasting models (RST and GAs) in terms of accuracy, and the stock return evaluations have revealed that the profits produced by the proposed model are higher than the three listed models (Buy-and-Hold, RST and GAs). © 2010 Elsevier Inc. All rights reserved.
Sharpnack P.A.,Ursuline College
Journal of holistic nursing : official journal of the American Holistic Nurses' Association | Year: 2011
Self-transcendence, the ability to expand one's relationship to others and the environment, has been found to provide hope which helps a person adapt and cope with illness. Spiritual well-being, the perception of health and wholeness, can boost self-confidence and self esteem. The purpose of this descriptive correlational study was to describe the relationship between self-transcendence and spiritual well-being in adult Amish. A random sample of Old Order Amish was surveyed by postal mail; there were 134 respondents. Two valid and reliable questionnaires were used to measure the key variables. The participants had high levels of self-transcendence and spiritual well-being and there was a statistically significant positive relationship between the two variables. The findings from this study will increase nurses' awareness of the holistic nature of the Amish beliefs and assist nurses in serving this population. Additional research is needed to develop further understanding of the study variables among the Amish.
Chou I.-C.,Ursuline College
Computer Assisted Language Learning | Year: 2012
Undoubtedly, new areas of functionality for electronic texts will come to the fore and create new reading habits and expectations for dealing and interacting with text as electronic texts become dominant in the academic world. These new forms of reading will gradually become as natural as the different activities readers now take for granted, such as searching an online catalog or browsing the web. However, little research has concerned what and how graduate students actually read on a computer screen. This study, therefore, investigated the on-screen reading behaviors of five English-as-a-second-language graduate students in different academic disciplines. The results showed that students had low preference and tendency toward reading texts that required careful reading on a computer screen because they believed that reading screen-based texts limited their use of strategies. However, most students chose online articles when searching for references. In addition, students' on-screen reading behaviors were influenced by several factors, such as their reading purposes, opportunity to read screen-based texts, applications of reading strategies and second-language proficiency. By making sense of on-screen reading occurring specifically in the academic context, this study hopes to enhance teachers' and researchers' understanding and to provide the basis for improved pedagogical practices in education. © 2012 Copyright Taylor and Francis Group, LLC.
Shie J.-S.,Ursuline College
Journal of Pragmatics | Year: 2011
The New York Times (NYT) publishes the Times Supplement (TS) in Taiwan every week. Although TS news articles are edited lightly from their corresponding NYT articles, TS headlines are often rewritten heavily. This paper addresses the cognitive, pragmatic, and rhetorical roles of conceptual metaphors and metonymies in TS and NYT headlines, focusing on variations in non-lexicalized metaphors and metonymies (namely those which have not been adopted into the lexicon). A textual survey and stylistic analysis were conducted on a corpus of 605 pairs of corresponding NYT and TS news articles. The results of the textual survey show that non-lexicalized metaphors and metonymies occur in more NYT headlines than TS headlines. Thus the degree of non-lexicalized figurations is reduced to make TS headlines more accessible to the TS reader. The stylistic analysis demonstrates that non-lexicalized metaphors and metonymies have some notable functions to fulfill in the headlines. Chief among them are: (i) metaphors and metonymies foreground a pragmatically relevant or stylistically interesting aspect of the story, (ii) metaphors and metonymies guide pragmatic inferencing in text interpretation, and (iii) metonymies create referential variety and enhance cohesion and coherence. © 2010 Elsevier B.V.