Using Environmental Science as a Motivational Tool to Teach Physics to Non-Science Majors

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Busch, Hauke C.

2010-01-01

A traditional physical science course was transformed into an environmental physical science course to teach physics to non-science majors. The objective of the new course was to improve the learning of basic physics principles by applying them to current issues of interest. A new curriculum was developed with new labs, homework assignments,…

A Functional Programming Approach to AI Search Algorithms

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Panovics, Janos

2012-01-01

The theory and practice of search algorithms related to state-space represented problems form the major part of the introductory course of Artificial Intelligence at most of the universities and colleges offering a degree in the area of computer science. Students usually meet these algorithms only in some imperative or object-oriented language…

My Science Is Better than Your Science: Conceptual Change as a Goal in Teaching Science Majors Interested in Teaching Careers about Education

Science.gov (United States)

Utter, Brian C.; Paulson, Scott A.; Almarode, John T.; Daniel, David B.

2018-01-01

We argue, based on a multi-year collaboration to develop a pedagogy course for physics majors by experts in physics, education, and the science of learning, that the process of teaching science majors about education and the science of learning, and evidence-based teaching methods in particular, requires conceptual change analogous to that…

Uncovering the lived experiences of junior and senior undergraduate female science majors

Science.gov (United States)

Adornato, Philip

The following dissertation focuses on a case study that uses critical theory, social learning theory, identity theory, liberal feminine theory, and motivation theory to conduct a narrative describing the lived experience of females and their performance in two highly selective private university, where students can cross-register between school, while majoring in science, technology, engineering and mathematics (STEM). Through the use of narratives, the research attempts to shed additional light on the informal and formal science learning experiences that motivates young females to major in STEM in order to help increase the number of women entering STEM careers and retaining women in STEM majors. In the addition to the narratives, surveys were performed to encompass a larger audience while looking for themes and phenomena which explore what captivates and motivates young females' interests in science and continues to nurture and facilitate their growth throughout high school and college, and propel them into a major in STEM in college. The purpose of this study was to uncover the lived experiences of junior and senior undergraduate female science majors during their formal and informal education, their science motivation to learn science, their science identities, and any experiences in gender inequity they may have encountered. The findings have implications for young women deciding on future careers and majors through early exposure and guidance, understanding and recognizing what gender discrimination, and the positive effects of mentorships.

The Challenge of Promoting Algorithmic Thinking of Both Sciences- and Humanities-Oriented Learners

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Katai, Z.

2015-01-01

The research results we present in this paper reveal that properly calibrated e-learning tools have potential to effectively promote the algorithmic thinking of both science-oriented and humanities-oriented students. After students had watched an illustration (by a folk dance choreography) and an animation of the studied sorting algorithm (bubble…

Spatial abilities, Earth science conceptual understanding, and psychological gender of university non-science majors

Science.gov (United States)

Black, Alice A. (Jill)

Research has shown the presence of many Earth science misconceptions and conceptual difficulties that may impede concept understanding, and has also identified a number of categories of spatial ability. Although spatial ability has been linked to high performance in science, some researchers believe it has been overlooked in traditional education. Evidence exists that spatial ability can be improved. This correlational study investigated the relationship among Earth science conceptual understanding, three types of spatial ability, and psychological gender, a self-classification that reflects socially-accepted personality and gender traits. A test of Earth science concept understanding, the Earth Science Concepts (ESC) test, was developed and field tested from 2001 to 2003 in 15 sections of university classes. Criterion validity was .60, significant at the .01 level. Spearman/Brown reliability was .74 and Kuder/Richardson reliability was .63. The Purdue Visualization of Rotations (PVOR) (mental rotation), the Group Embedded Figures Test (GEFT) (spatial perception), the Differential Aptitude Test: Space Relations (DAT) (spatial visualization), and the Bem Inventory (BI) (psychological gender) were administered to 97 non-major university students enrolled in undergraduate science classes. Spearman correlations revealed moderately significant correlations at the .01 level between ESC scores and each of the three spatial ability test scores. Stepwise regression analysis indicated that PVOR scores were the best predictor of ESC scores, and showed that spatial ability scores accounted for 27% of the total variation in ESC scores. Spatial test scores were moderately or weakly correlated with each other. No significant correlations were found among BI scores and other test scores. Scantron difficulty analysis of ESC items produced difficulty ratings ranging from 33.04 to 96.43, indicating the percentage of students who answered incorrectly. Mean score on the ESC was 34

Starting an Actuarial Science Major at a Liberal Arts College

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Mills, Mark A.

2014-01-01

The article provides details of the process of starting an actuarial science major at a small, liberal arts college. Some critique of the major is included, as well as some challenges that may be faced by others wanting to start such a major at their institution.

The Gender Differences: Hispanic Females and Males Majoring in Science or Engineering

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Brown, Susan Wightman

Documented by national statistics, female Hispanic students are not eagerly rushing to major in science or engineering. Using Seidman's in-depth interviewing method, 22 Hispanic students, 12 female and 10 male, majoring in science or engineering were interviewed. Besides the themes that emerged with all 22 Hispanic students, there were definite differences between the female and male Hispanic students: role and ethnic identity confusion, greater college preparation, mentoring needed, and the increased participation in enriched additional education programs by the female Hispanic students. Listening to these stories from successful female Hispanic students majoring in science and engineering, educators can make changes in our school learning environments that will encourage and enable more female Hispanic students to choose science or engineering careers.

Algorithmic Puzzles: History, Taxonomies, and Applications in Human Problem Solving

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Levitin, Anany

2017-01-01

The paper concerns an important but underappreciated genre of algorithmic puzzles, explaining what these puzzles are, reviewing milestones in their long history, and giving two different ways to classify them. Also covered are major applications of algorithmic puzzles in cognitive science research, with an emphasis on insight problem solving, and…

Choices in higher education: Majoring in and changing from the sciences

Science.gov (United States)

Minear, Nancy Ann

This dissertation addresses patterns of retention of undergraduate science, engineering and mathematics (SEM) students, with special attention paid to female and under represented minority students. As such, the study is focused on issues related to academic discipline and institutional retention, rather than the retention of students in the overall system of higher education. While previous retention studies have little to say about rates of retention that are specific to the sciences (or any other specific area of study) or employ models that rely on students' performance at the college level, this work address both points by identifying the post secondary academic performance characteristics of persisters and non-persisters in the sciences by gender, ethnicity and matriculating major as well as identifying introductory SEM course requirements that prevent students from persisting in sciencegender, ethnicity and matriculating major as well as identifying introductory SEM course requirements that prevent students from persisting in science majors. A secondary goal of investigating the usefulness of institutional records for retention research is addressed. Models produced for the entire population and selected subpopulations consistently classified higher-performing (both SEM and non-SEM grade point averages) students into Bachelor of Science categories using the number of Introductory Chemistry courses attempted at the university. For lower performing students, those with more introductory chemistry courses were classified as changing majors out of the sciences, and in general as completing a Bachelor of Arts degree. Performance in gatekeeper courses as a predictor of terminal academic status was limited to Introductory Physics for a small number of cases. Performance in Introductory Calculus and Introductory Chemistry were not consistently utilized as predictor variables. The models produced for various subpopulations (women, ethnic groups and matriculation

Improved Iterative Hard- and Soft-Reliability Based Majority-Logic Decoding Algorithms for Non-Binary Low-Density Parity-Check Codes

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Xiong, Chenrong; Yan, Zhiyuan

2014-10-01

Non-binary low-density parity-check (LDPC) codes have some advantages over their binary counterparts, but unfortunately their decoding complexity is a significant challenge. The iterative hard- and soft-reliability based majority-logic decoding algorithms are attractive for non-binary LDPC codes, since they involve only finite field additions and multiplications as well as integer operations and hence have significantly lower complexity than other algorithms. In this paper, we propose two improvements to the majority-logic decoding algorithms. Instead of the accumulation of reliability information in the existing majority-logic decoding algorithms, our first improvement is a new reliability information update. The new update not only results in better error performance and fewer iterations on average, but also further reduces computational complexity. Since existing majority-logic decoding algorithms tend to have a high error floor for codes whose parity check matrices have low column weights, our second improvement is a re-selection scheme, which leads to much lower error floors, at the expense of more finite field operations and integer operations, by identifying periodic points, re-selecting intermediate hard decisions, and changing reliability information.

Gender Attributions of Science and Academic Attributes: AN Examination of Undergraduate Science, Mathematics, and Technology Majors

Science.gov (United States)

Hughes, W. Jay

Questionnaire data (n = 297) examined the relationship between gender attributions of science and academic attributes for undergraduate science, mathematics, and technology majors from the perspective of gender schema theory. Female and male respondents perceived that (a) the role of scientist was sex typed as masculine, (b) their majors were more valuable for members of their gender than for those of the opposite gender, (c) their majors were more valuable for themselves than for members of their gender in general. Androgynous attributions of scientists and the value of one's major for women predicted value for oneself, major confidence, and career confidence, and masculine attributions of scientists predicted class participation for female respondents. Feminine attributions of scientists predicted graduate school intent; value for women predicted major confidence and subjective achievement, and value for men predicted value for oneself, course confidence, and career confidence for male respondents.

Algorithm integration using ADL (Algorithm Development Library) for improving CrIMSS EDR science product quality

Science.gov (United States)

Das, B.; Wilson, M.; Divakarla, M. G.; Chen, W.; Barnet, C.; Wolf, W.

2013-05-01

Algorithm Development Library (ADL) is a framework that mimics the operational system IDPS (Interface Data Processing Segment) that is currently being used to process data from instruments aboard Suomi National Polar-orbiting Partnership (S-NPP) satellite. The satellite was launched successfully in October 2011. The Cross-track Infrared and Microwave Sounder Suite (CrIMSS) consists of the Advanced Technology Microwave Sounder (ATMS) and Cross-track Infrared Sounder (CrIS) instruments that are on-board of S-NPP. These instruments will also be on-board of JPSS (Joint Polar Satellite System) that will be launched in early 2017. The primary products of the CrIMSS Environmental Data Record (EDR) include global atmospheric vertical temperature, moisture, and pressure profiles (AVTP, AVMP and AVPP) and Ozone IP (Intermediate Product from CrIS radiances). Several algorithm updates have recently been proposed by CrIMSS scientists that include fixes to the handling of forward modeling errors, a more conservative identification of clear scenes, indexing corrections for daytime products, and relaxed constraints between surface temperature and air temperature for daytime land scenes. We have integrated these improvements into the ADL framework. This work compares the results from ADL emulation of future IDPS system incorporating all the suggested algorithm updates with the current official processing results by qualitative and quantitative evaluations. The results prove these algorithm updates improve science product quality.

Cognitive Correlates of Performance in Algorithms in a Computer Science Course for High School

Science.gov (United States)

Avancena, Aimee Theresa; Nishihara, Akinori

2014-01-01

Computer science for high school faces many challenging issues. One of these is whether the students possess the appropriate cognitive ability for learning the fundamentals of computer science. Online tests were created based on known cognitive factors and fundamental algorithms and were implemented among the second grade students in the…

A Module-Based Environmental Science Course for Teaching Ecology to Non-Majors

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Smith, Geoffrey R.

2010-01-01

Using module-based courses has been suggested to improve undergraduate science courses. A course based around a series of modules focused on major environmental issues might be an effective way to teach non-science majors about ecology and ecology's role in helping to solve environmental problems. I have used such a module-based environmental…

Profiles of Motivated Self-Regulation in College Computer Science Courses: Differences in Major versus Required Non-Major Courses

Science.gov (United States)

Shell, Duane F.; Soh, Leen-Kiat

2013-12-01

The goal of the present study was to utilize a profiling approach to understand differences in motivation and strategic self-regulation among post-secondary STEM students in major versus required non-major computer science courses. Participants were 233 students from required introductory computer science courses (194 men; 35 women; 4 unknown) at a large Midwestern state university. Cluster analysis identified five profiles: (1) a strategic profile of a highly motivated by-any-means good strategy user; (2) a knowledge-building profile of an intrinsically motivated autonomous, mastery-oriented student; (3) a surface learning profile of a utility motivated minimally engaged student; (4) an apathetic profile of an amotivational disengaged student; and (5) a learned helpless profile of a motivated but unable to effectively self-regulate student. Among CS majors and students in courses in their major field, the strategic and knowledge-building profiles were the most prevalent. Among non-CS majors and students in required non-major courses, the learned helpless, surface learning, and apathetic profiles were the most prevalent. Students in the strategic and knowledge-building profiles had significantly higher retention of computational thinking knowledge than students in other profiles. Students in the apathetic and surface learning profiles saw little instrumentality of the course for their future academic and career objectives. Findings show that students in STEM fields taking required computer science courses exhibit the same constellation of motivated strategic self-regulation profiles found in other post-secondary and K-12 settings.

Sociocultural Influences On Undergraduate Women's Entry into a Computer Science Major

Science.gov (United States)

Lyon, Louise Ann

Computer science not only displays the pattern of underrepresentation of many other science, technology, engineering, and math (STEM) fields, but has actually experienced a decline in the number of women choosing the field over the past two decades. Broken out by gender and race, the picture becomes more nuanced, with the ratio of females to males receiving bachelor's degrees in computer science higher for non-White ethnic groups than for Whites. This dissertation explores the experiences of university women differing along the axis of race, class, and culture who are considering majoring in computer science in order to highlight how well-prepared women are persuaded that they belong (or not) in the field and how the confluence of social categories plays out in their decision. This study focuses on a university seminar entitled "Women in Computer Science and Engineering" open to women concurrently enrolled in introductory programming and uses an ethnographic approach including classroom participant observation, interviews with seminar students and instructors, observations of students in other classes, and interviews with parents of students. Three stand-alone but related articles explore various aspects of the experiences of women who participated in the study using Rom Harre's positioning theory as a theoretical framework. The first article uses data from twenty-two interviews to uncover how interactions with others and patterns in society position women in relation to a computer science major, and how these women have arrived at the point of considering the major despite messages that they do not belong. The second article more deeply explores the cases of three women who vary greatly along the axes of race, class, and culture in order to uncover pattern and interaction differences for women based on their ethnic background. The final article focuses on the attitudes and expectations of the mothers of three students of contrasting ethnicities and how reported

Using the Geoscience Literacy Frameworks and Educational Technologies to Promote Science Literacy in Non-science Major Undergraduates

Science.gov (United States)

Carley, S.; Tuddenham, P.; Bishop, K. O.

2008-12-01

In recent years several geoscience communities have been developing ocean, climate, atmosphere and earth science literacy frameworks as enhancements to the National Science Education Standards content standards. Like the older content standards these new geoscience literacy frameworks have focused on K-12 education although they are also intended for informal education and general public audiences. These geoscience literacy frameworks potentially provide a more integrated and less abstract approach to science literacy that may be more suitable for non-science major students that are not pursuing careers in science research or education. They provide a natural link to contemporary environmental issues - e.g., climate change, resource depletion, species and habitat loss, natural hazards, pollution, development of renewable energy, material recycling. The College of Exploration is an education research non-profit that has provided process and technical support for the development of most of these geoscience literacy frameworks. It has a unique perspective on their development. In the last ten years it has also gained considerable national and international expertise in facilitating web-based workshops that support in-depth conversations among educators and working scientists/researchers on important science topics. These workshops have been of enormous value to educators working in K-12, 4-year institutions and community colleges. How can these geoscience literacy frameworks promote more collaborative inquiry-based learning that enhances the appreciation of scientific thinking by non-majors? How can web- and mobile-based education technologies transform the undergraduate non-major survey course into a place where learners begin their passion for science literacy rather than end it? How do we assess science literacy in students and citizens?

Survey of Mathematics and Science Requirements for Production-Oriented Agronomy Majors.

Science.gov (United States)

Aide, Michael; Terry, Danny

1996-01-01

Analyzes course requirements to determine the amount of required mathematics and science for production-oriented agronomy majors. Reports that mathematics requirements center around college algebra and statistics; science requirements generally include chemistry, biology, plant physiology, and genetics; and land-grant institutions have a…

Science and the Nonscience Major: Addressing the Fear Factor in the Chemical Arena Using Forensic Science

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Labianca, Dominick A.

2007-01-01

This article describes an approach to minimizing the "fear factor" in a chemistry course for the nonscience major, and also addresses relevant applications to other science courses, including biology, geology, and physics. The approach emphasizes forensic science and affords students the opportunity to hone their analytical skills in an…

CDM: Teaching Discrete Mathematics to Computer Science Majors

Science.gov (United States)

Sutner, Klaus

2005-01-01

CDM, for computational discrete mathematics, is a course that attempts to teach a number of topics in discrete mathematics to computer science majors. The course abandons the classical definition-theorem-proof model, and instead relies heavily on computation as a source of motivation and also for experimentation and illustration. The emphasis on…

Strategic Curricular Decisions in Butler University's Actuarial Science Major

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Wilson, Christopher James

2014-01-01

We describe specific curricular decisions employed at Butler University that have resulted in student achievement in the actuarial science major. The paper includes a discussion of how these decisions might be applied in the context of a new actuarial program.

The Effects of Majoring in Political Science on Political Efficacy

Science.gov (United States)

Dominguez, Casey B. K.; Smith, Keith W.; Williams, J. Michael

2017-01-01

This study tests, and finds support, for the hypotheses that a student who majors in political science will have stronger feelings of political competence and will be more willing to engage in hypothetical political actions than two peer groups: (a) those who major in other fields and (b) those who show an interest in politics but have not studied…

High school and college introductory science education experiences: A study regarding perceptions of university students persisting in science as a major area of study

Science.gov (United States)

Fredrick, L. Denise

The focus of this study was to investigate college students' perception of high school and college introductory science learning experiences related to persistence in science as a major area of study in college. The study included students' perceptions of the following areas of science education: (1) teacher interpersonal relationship with students, (2) teacher personality styles, (3) teacher knowledge of the content, (4) instructional methods, and (5) science course content. A survey research design was employed in the investigative study to collect and analyze data. One hundred ninety two students participated in the research study. A survey instrument entitled Science Education Perception Survey was used to collect data. The researcher sought to reject or support three null hypotheses as related to participants' perceptions of high school and college introductory science education experiences. Using binomial regression analysis, this study analyzed differences between students persisting in science and students not persisting in science as a major. The quantitative research indicated that significant differences exist between persistence in science as a major and high school science teacher traits and college introductory science instructional methods. Although these variables were found to be significant predictors, the percent variance was low and should be considered closely before concluded these as strong predictors of persistence. Major findings of the qualitative component indicated that students perceived that: (a) interest in high school science course content and high school science teacher personality and interpersonal relationships had the greatest effect on students' choice of major area of study; (b) interest in college introductory science course content had the greatest effect on students' choice of major area of study; (c) students recalled laboratory activities and overall good teaching as most meaningful to their high school science

Developing "Green" Business Plans: Using Entrepreneurship to Teach Science to Business Administration Majors and Business to Biology Majors

Science.gov (United States)

Letovsky, Robert; Banschbach, Valerie S.

2011-01-01

Biology majors team with business administration majors to develop proposals for "green" enterprise for a business plan competition. The course begins with a series of student presentations so that science students learn about the fundamentals of business, and business students learn about environmental biology. Then mixed biology-business student…

STAR Algorithm Integration Team - Facilitating operational algorithm development

Science.gov (United States)

Mikles, V. J.

2015-12-01

The NOAA/NESDIS Center for Satellite Research and Applications (STAR) provides technical support of the Joint Polar Satellite System (JPSS) algorithm development and integration tasks. Utilizing data from the S-NPP satellite, JPSS generates over thirty Environmental Data Records (EDRs) and Intermediate Products (IPs) spanning atmospheric, ocean, cryosphere, and land weather disciplines. The Algorithm Integration Team (AIT) brings technical expertise and support to product algorithms, specifically in testing and validating science algorithms in a pre-operational environment. The AIT verifies that new and updated algorithms function in the development environment, enforces established software development standards, and ensures that delivered packages are functional and complete. AIT facilitates the development of new JPSS-1 algorithms by implementing a review approach based on the Enterprise Product Lifecycle (EPL) process. Building on relationships established during the S-NPP algorithm development process and coordinating directly with science algorithm developers, the AIT has implemented structured reviews with self-contained document suites. The process has supported algorithm improvements for products such as ozone, active fire, vegetation index, and temperature and moisture profiles.

The academic majors of students taking American soil science classes: 2004-2005 to 2013-2014 academic years

Science.gov (United States)

Brevik, Eric C.; Vaughan, Karen L.; Parikh, Sanjai J.; Dolliver, Holly; Lindbo, David; Steffan, Joshua J.; Weindorf, David; McDaniel, Paul; Mbila, Monday; Edinger-Marshall, Susan

2017-04-01

Many papers have been written in recent years discussing the interdisciplinary and transdisciplinary aspects of soil science. Therefore, it would make sense that soil science courses would be taken by students in a wide array of academic majors. To investigate this, we collected data from eight different American universities on the declared academic majors of students enrolled in soil science courses over a 10 year time period (2004-2005 to 2013-2014 academic years). Data was collected for seven different classes taught at the undergraduate level: introduction to soil science, soil fertility, soil management, pedology, soil biology/microbiology, soil chemistry, and soil physics. Overall trends and trends for each class were evaluated. Generally, environmental science and crop science/horticulture/agronomy students were enrolled in soil science courses in the greatest numbers. Environmental science and engineering students showed rapid increases in enrollment over the 10 years of the study, while the number of crop science/ horticulture/ agronomy students declined. In the introduction to soil science classes, environmental science and crop science/ horticulture/ agronomy students were enrolled in the greatest numbers, while declared soil science majors only made up 6.6% of the average enrollment. The highest enrollments in soil fertility were crop science/ horticulture/ agronomy students and other agricultural students (all agricultural majors except crop science, horticulture, agronomy, or soil science). In both the soil management and pedology classes, environmental science and other agricultural students were the largest groups enrolled. Other agricultural students and students from other majors (all majors not otherwise expressly investigated) were the largest enrolled groups in soil biology/microbiology courses, and environmental science and soil science students were the largest enrolled groups in soil chemistry classes. Soil physics was the only class

The Soil Moisture Active Passive Mission (SMAP) Science Data Products: Results of Testing with Field Experiment and Algorithm Testbed Simulation Environment Data

Science.gov (United States)

Entekhabi, Dara; Njoku, Eni E.; O'Neill, Peggy E.; Kellogg, Kent H.; Entin, Jared K.

2010-01-01

Talk outline 1. Derivation of SMAP basic and applied science requirements from the NRC Earth Science Decadal Survey applications 2. Data products and latencies 3. Algorithm highlights 4. SMAP Algorithm Testbed 5. SMAP Working Groups and community engagement

Increasing persistence in undergraduate science majors: a model for institutional support of underrepresented students.

Science.gov (United States)

Toven-Lindsey, Brit; Levis-Fitzgerald, Marc; Barber, Paul H; Hasson, Tama

2015-01-01

The 6-yr degree-completion rate of undergraduate science, technology, engineering, and mathematics (STEM) majors at U.S. colleges and universities is less than 40%. Persistence among women and underrepresented minorities (URMs), including African-American, Latino/a, Native American, and Pacific Islander students, is even more troubling, as these students leave STEM majors at significantly higher rates than their non-URM peers. This study utilizes a matched comparison group design to examine the academic achievement and persistence of students enrolled in the Program for Excellence in Education and Research in the Sciences (PEERS), an academic support program at the University of California, Los Angeles, for first- and second-year science majors from underrepresented backgrounds. Results indicate that PEERS students, on average, earned higher grades in most "gatekeeper" chemistry and math courses, had a higher cumulative grade point average, completed more science courses, and persisted in a science major at significantly higher rates than the comparison group. With its holistic approach focused on academics, counseling, creating a supportive community, and exposure to research, the PEERS program serves as an excellent model for universities interested in and committed to improving persistence of underrepresented science majors and closing the achievement gap. © 2015 B. Toven-Lindsey et al. CBE—Life Sciences Education © 2015 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

QUALITATIVE INDICATORS OF EFFICIENCY OF TECHNOLOGIES DEVELOPING ESP COMPETENCE IN STUDENTS MAJORING IN SCIENCES

Directory of Open Access Journals (Sweden)

Наталія Микитинко

2015-05-01

Full Text Available The article is dedicated to identifying and diagnosing qualitative indicators of efficiency of technologies developing ESP competence in students majoring in Sciences, namely: indicators of objective and subjective assessment  of students’ ESP competence, students’ motivation regarding professional choice, organizational features of professional training, its contents, the most popular learning activities, use of active methods of study in educational process. The paradigm of experimental research of efficiency of technologies developing ESP competence in students majoring in Sciences has been defined. Based on the interpretation of the qualitative indicators the hypothesis of efficiency of technologies developing ESP competence in students majoring in Sciences has been proven.

Courses in Modern Physics for Non-science Majors, Future Science Teachers, and Biology Students

Science.gov (United States)

Zollman, Dean

2001-03-01

For the past 15 years Kansas State University has offered a course in modern physics for students who are not majoring in physics. This course carries a prerequisite of one physics course so that the students have a basic introduction in classical topics. The majors of students range from liberal arts to engineering. Future secondary science teachers whose first area of teaching is not physics can use the course as part of their study of science. The course has evolved from a lecture format to one which is highly interactive and uses a combination of hands-on activities, tutorials and visualizations, particularly the Visual Quantum Mechanics materials. Another course encourages biology students to continue their physics learning beyond the introductory course. Modern Miracle Medical Machines introduces the basic physics which underlie diagnosis techniques such as MRI and PET and laser surgical techniques. Additional information is available at http://www.phys.ksu.edu/perg/

Machine learning algorithm accurately detects fMRI signature of vulnerability to major depression

OpenAIRE

Sato, Jo?o R.; Moll, Jorge; Green, Sophie; Deakin, John F.W.; Thomaz, Carlos E.; Zahn, Roland

2015-01-01

Standard functional magnetic resonance imaging (fMRI) analyses cannot assess the potential of a neuroimaging signature as a biomarker to predict individual vulnerability to major depression (MD). Here, we use machine learning for the first time to address this question. Using a recently identified neural signature of guilt-selective functional disconnection, the classification algorithm was able to distinguish remitted MD from control participants with 78.3% accuracy. This demonstrates the hi...

Do Biology Majors Really Differ from Non–STEM Majors?

Science.gov (United States)

Cotner, Sehoya; Thompson, Seth; Wright, Robin

2017-01-01

Recent calls to action urge sweeping reform in science education, advocating for improved learning for all students—including those majoring in fields beyond the sciences. However, little work has been done to characterize the differences—if any exist—between students planning a career in science and those studying other disciplines. We describe an attempt to clarify, in broad terms, how non–STEM (science, technology, engineering, and mathematics) majors differ from life sciences majors, and how they are similar. Using survey responses and institutional data, we find that non–STEM majors are not unilaterally science averse; non–STEM majors are more likely than biology majors to hold misconceptions about the nature of science, yet they are not completely ignorant of how science works; non–STEM majors are less likely than biology majors to see science as personally relevant; and non–STEM majors populations are likely to be more diverse—with respect to incoming knowledge, perceptions, backgrounds, and skills—than a biology majors population. We encourage science educators to consider these characteristics when designing curricula for future scientists or simply for a well-informed citizenry. PMID:28798210

Learning Science by Engaging Religion: A Novel Two-Course Approach for Biology Majors

Science.gov (United States)

Eisen, Arri; Huang, Junjian

2014-01-01

Many issues in science create individual and societal tensions with important implications outside the classroom. We describe one model that directly addresses such tensions by integrating science and religion in two parallel, integrated courses for science majors. Evaluation of the goals of the project--(1) providing students with strategies to…

Motivating Non-Science Majors: The Technology of Electromagnetic Waves

Science.gov (United States)

Henrich, Victor E.

2018-01-01

To address the need for physics courses that stimulate non- STEM majors' interest in, and appreciation of, science, the Department of Applied Physics has developed a popular course for Yale College undergraduates, The Technological World, that explains the physics behind technologies that students use every day. The course provides an in-depth…

Do Biology Students Really Hate Math? Empirical Insights into Undergraduate Life Science Majors' Emotions about Mathematics.

Science.gov (United States)

Wachsmuth, Lucas P; Runyon, Christopher R; Drake, John M; Dolan, Erin L

2017-01-01

Undergraduate life science majors are reputed to have negative emotions toward mathematics, yet little empirical evidence supports this. We sought to compare emotions of majors in the life sciences versus other natural sciences and math. We adapted the Attitudes toward the Subject of Chemistry Inventory to create an Attitudes toward the Subject of Mathematics Inventory (ASMI). We collected data from 359 science and math majors at two research universities and conducted a series of statistical tests that indicated that four AMSI items comprised a reasonable measure of students' emotional satisfaction with math. We then compared life science and non-life science majors and found that major had a small to moderate relationship with students' responses. Gender also had a small relationship with students' responses, while students' race, ethnicity, and year in school had no observable relationship. Using latent profile analysis, we identified three groups-students who were emotionally satisfied with math, emotionally dissatisfied with math, and neutral. These results and the emotional satisfaction with math scale should be useful for identifying differences in other undergraduate populations, determining the malleability of undergraduates' emotional satisfaction with math, and testing effects of interventions aimed at improving life science majors' attitudes toward math. © 2017 L.P. Wachsmuth et al. CBE—Life Sciences Education © 2017 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

China's rise as a major contributor to science and technology.

Science.gov (United States)

Xie, Yu; Zhang, Chunni; Lai, Qing

2014-07-01

In the past three decades, China has become a major contributor to science and technology. China now employs an increasingly large labor force of scientists and engineers at relatively high earnings and produces more science and engineering degrees than the United States at all levels, particularly bachelor's. China's research and development expenditure has been rising. Research output in China has been sharply increasing since 2002, making China the second largest producer of scientific papers after the United States. The quality of research by Chinese scientists has also been improving steadily. However, China's rise in science also faces serious difficulties, partly attributable to its rigid, top-down administrative system, with allegations of scientific misconduct trending upward.

Reforming an Undergraduate Environmental Science Course for Nonscience Majors

Science.gov (United States)

Kazempour, Mahsa; Amirshokoohi, Aidin

2013-01-01

This article discusses the key components of a reform-based introductory undergraduate environmental science course for nonscience majors and elementary teacher candidates as well as the impact of such components on the participants. The main goals for the course were to actively engage the students in their learning and, in doing so, to enhance…

Algorithms

Indian Academy of Sciences (India)

ticians but also forms the foundation of computer science. Two ... with methods of developing algorithms for solving a variety of problems but ... applications of computers in science and engineer- ... numerical calculus are as important. We will ...

AeroADL: applying the integration of the Suomi-NPP science algorithms with the Algorithm Development Library to the calibration and validation task

Science.gov (United States)

Houchin, J. S.

2014-09-01

A common problem for the off-line validation of the calibration algorithms and algorithm coefficients is being able to run science data through the exact same software used for on-line calibration of that data. The Joint Polar Satellite System (JPSS) program solved part of this problem by making the Algorithm Development Library (ADL) available, which allows the operational algorithm code to be compiled and run on a desktop Linux workstation using flat file input and output. However, this solved only part of the problem, as the toolkit and methods to initiate the processing of data through the algorithms were geared specifically toward the algorithm developer, not the calibration analyst. In algorithm development mode, a limited number of sets of test data are staged for the algorithm once, and then run through the algorithm over and over as the software is developed and debugged. In calibration analyst mode, we are continually running new data sets through the algorithm, which requires significant effort to stage each of those data sets for the algorithm without additional tools. AeroADL solves this second problem by providing a set of scripts that wrap the ADL tools, providing both efficient means to stage and process an input data set, to override static calibration coefficient look-up-tables (LUT) with experimental versions of those tables, and to manage a library containing multiple versions of each of the static LUT files in such a way that the correct set of LUTs required for each algorithm are automatically provided to the algorithm without analyst effort. Using AeroADL, The Aerospace Corporation's analyst team has demonstrated the ability to quickly and efficiently perform analysis tasks for both the VIIRS and OMPS sensors with minimal training on the software tools.

Do Biology Majors Really Differ from Non-STEM Majors?

Science.gov (United States)

Cotner, Sehoya; Thompson, Seth; Wright, Robin

2017-01-01

Recent calls to action urge sweeping reform in science education, advocating for improved learning for all students-including those majoring in fields beyond the sciences. However, little work has been done to characterize the differences-if any exist-between students planning a career in science and those studying other disciplines. We describe an attempt to clarify, in broad terms, how non-STEM (science, technology, engineering, and mathematics) majors differ from life sciences majors, and how they are similar. Using survey responses and institutional data, we find that non-STEM majors are not unilaterally science averse; non-STEM majors are more likely than biology majors to hold misconceptions about the nature of science, yet they are not completely ignorant of how science works; non-STEM majors are less likely than biology majors to see science as personally relevant; and non-STEM majors populations are likely to be more diverse-with respect to incoming knowledge, perceptions, backgrounds, and skills-than a biology majors population. We encourage science educators to consider these characteristics when designing curricula for future scientists or simply for a well-informed citizenry. © 2017 S. Cotner et al. CBE—Life Sciences Education © 2017 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Earth Systems Science in an Integrated Science Content and Methods Course for Elementary Education Majors

Science.gov (United States)

Madsen, J. A.; Allen, D. E.; Donham, R. S.; Fifield, S. J.; Shipman, H. L.; Ford, D. J.; Dagher, Z. R.

2004-12-01

With funding from the National Science Foundation, we have designed an integrated science content and methods course for sophomore-level elementary teacher education (ETE) majors. This course, the Science Semester, is a 15-credit sequence that consists of three science content courses (Earth, Life, and Physical Science) and a science teaching methods course. The goal of this integrated science and education methods curriculum is to foster holistic understandings of science and pedagogy that future elementary teachers need to effectively use inquiry-based approaches in teaching science in their classrooms. During the Science Semester, traditional subject matter boundaries are crossed to stress shared themes that teachers must understand to teach standards-based elementary science. Exemplary approaches that support both learning science and learning how to teach science are used. In the science courses, students work collaboratively on multidisciplinary problem-based learning (PBL) activities that place science concepts in authentic contexts and build learning skills. In the methods course, students critically explore the theory and practice of elementary science teaching, drawing on their shared experiences of inquiry learning in the science courses. An earth system science approach is ideally adapted for the integrated, inquiry-based learning that takes place during the Science Semester. The PBL investigations that are the hallmark of the Science Semester provide the backdrop through which fundamental earth system interactions can be studied. For example in the PBL investigation that focuses on energy, the carbon cycle is examined as it relates to fossil fuels. In another PBL investigation centered on kids, cancer, and the environment, the hydrologic cycle with emphasis on surface runoff and ground water contamination is studied. In a PBL investigation that has students learning about the Delaware Bay ecosystem through the story of the horseshoe crab and the biome

Living in a material world: Development and evaluation of a new materials science course for non-science majors

Science.gov (United States)

Brust, Gregory John

This study was designed to discover if there is a difference in the scientific attitudes and process skills between a group of students who were instructed with Living in a Material World and groups of students in non-science majors sections of introductory biology, chemistry, and geology courses at the University of Southern Mississippi (USM). Each of the four courses utilized different instructional techniques. Students' scientific attitudes were measured with the Scientific Attitudes Inventory (SAI II) and their knowledge of science process skills were measured with the Test of Integrated Process Skills (TIPS II). The Group Assessment of Logical Thinking (GALT) was also administered to determine if the cognitive levels of students are comparable. A series of four questionnaires called Qualitative Course Assessments (QCA) were also administered to students in the experimental course to evaluate subtle changes in their understanding of the nature and processes of science and attitudes towards science. Student responses to the QCA questionnaires were triangulated with results of the qualitative instruments, and students' work on the final project. Results of the GALT found a significant difference in the cognitive levels of students in the experimental course (PSC 190) and in one of the control group, the introductory biology (BSC 107). Results of the SAI II and the TIPS II found no significant difference between the experimental group and the control groups. Qualitative analyses of students' responses to selected questions from the TIPS II, selected items on the SAI II, QCA questionnaires, and Materials that Fly project reports demonstrate an improvement in the understanding of the nature and processes of science and a change to positive attitude toward science of students in the experimental group. Students indicated that hands-on, inquiry-based labs and performance assessment were the most effective methods for their learning. These results indicate that science

Introduction to Evolutionary Algorithms

CERN Document Server

Yu, Xinjie

2010-01-01

Evolutionary algorithms (EAs) are becoming increasingly attractive for researchers from various disciplines, such as operations research, computer science, industrial engineering, electrical engineering, social science, economics, etc. This book presents an insightful, comprehensive, and up-to-date treatment of EAs, such as genetic algorithms, differential evolution, evolution strategy, constraint optimization, multimodal optimization, multiobjective optimization, combinatorial optimization, evolvable hardware, estimation of distribution algorithms, ant colony optimization, particle swarm opti

An investigation of factors affecting elementary female student teachers' choice of science as a major at college level in Zimbabwe

Science.gov (United States)

Mlenga, Francis Howard

The purpose of the study was to determine factors affecting elementary female student teachers' choice of science as a major at college level in Zimbabwe. The study was conducted at one of the Primary School Teachers' Colleges in Zimbabwe. A sample of two hundred and thirty-eight female student teachers was used in the study. Of these one hundred and forty-two were non-science majors who had been randomly selected, forty-one were science majors and forty-five were math majors. Both science and math majors were a convenient sample because the total enrollment of the two groups was small. All the subjects completed a survey questionnaire that had sixty-eight items. Ten students from the non-science majors were selected for individual interviews and the same was done for the science majors. A further eighteen were selected from the non-science majors and divided into three groups of six each for focus group interviews. The same was done for the science majors. The interviews were audio taped and transcribed. Data from the survey questionnaires were analyzed using Binary Logistic Regression which predicted factors that affected students' choice of science as a major. The transcribed interview data were analyzed used using domain, taxonomic and componential analyses. Results of the study indicated that elementary female students' choice of science as a major at college level is affected by students' attitudes toward science, teacher behavior, out-of-school experiences, role models, gender stereotyping, parental influence, peer influence, in-school experiences, and societal expectations, namely cultural and social expectations.

8. Algorithm Design Techniques

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education; Volume 2; Issue 8. Algorithms - Algorithm Design Techniques. R K Shyamasundar. Series Article Volume 2 ... Author Affiliations. R K Shyamasundar1. Computer Science Group, Tata Institute of Fundamental Research, Homi Bhabha Road, Mumbai 400 005, India ...

Science Majors and Degrees among Asian-American Students: Influences of Race and Sex in "model Minority" Experiences

Science.gov (United States)

Meng, Yu; Hanson, Sandra L.

Both race and sex continue to be factors that stratify entry into science education and occupations in the United States. Asian-Americans (men and women) have experienced considerable success in the sciences and have earned the label of "model minority." The complexities and patterns involved in this success remain elusive. We use several concepts coming out of the status attainment framework and a multicultural gender perspective to explore the way in which race and sex come together to influence choices of science major and degree. Our sample consists of Asian-American and white students in the National Educational Longitudinal Study. Findings suggest that being male and being Asian-American are both associated with higher chances of pursuing majors and degrees in science. The male advantage is greater than the Asian-American advantage. Findings also suggest that race and sex interact in the science decision. For example, race differences (with an Asian-American advantage) in choice of science major are significant for women but not men. Sex differences (with a male advantage) in choice of science major are significant in the white, but not the Asian-American sample. A different set of race and sex patterns is revealed in the science degree models. Processes associated with family socioeconomic status and student characteristics help to explain race and sex patterns. Findings suggest that when Asian-American youths have closer ties to the Asian culture, they are more likely to choose science majors and degrees. Implications for policy, practice, and research in science education are discussed.

Algorithmic, LOCS and HOCS (chemistry) exam questions: performance and attitudes of college students

Science.gov (United States)

Zoller, Uri

2002-02-01

The performance of freshmen biology and physics-mathematics majors and chemistry majors as well as pre- and in-service chemistry teachers in two Israeli universities on algorithmic (ALG), lower-order cognitive skills (LOCS), and higher-order cognitive skills (HOCS) chemistry exam questions were studied. The driving force for the study was an interest in moving science and chemistry instruction from an algorithmic and factual recall orientation dominated by LOCS, to a decision-making, problem-solving and critical system thinking approach, dominated by HOCS. College students' responses to the specially designed ALG, LOCS and HOCS chemistry exam questions were scored and analysed for differences and correlation between the performance means within and across universities by the questions' category. This was followed by a combined student interview - 'speaking aloud' problem solving session for assessing the thinking processes involved in solving these types of questions and the students' attitudes towards them. The main findings were: (1) students in both universities performed consistently in each of the three categories in the order of ALG > LOCS > HOCS; their 'ideological' preference, was HOCS > algorithmic/LOCS, - referred to as 'computational questions', but their pragmatic preference was the reverse; (2) success on algorithmic/LOCS does not imply success on HOCS questions; algorithmic questions constitute a category on its own as far as students success in solving them is concerned. Our study and its results support the effort being made, worldwide, to integrate HOCS-fostering teaching and assessment strategies and, to develop HOCS-oriented science-technology-environment-society (STES)-type curricula within science and chemistry education.

What does it all mean? Capturing Semantics of Surgical Data and Algorithms with Ontologies

OpenAIRE

Katić, Darko; Maleshkova, Maria; Engelhardt, Sandy; Wolf, Ivo; März, Keno; Maier-Hein, Lena; Nolden, Marco; Wagner, Martin; Kenngott, Hannes; Müller-Stich, Beat Peter; Dillmann, Rüdiger; Speidel, Stefanie

2017-01-01

Every year approximately 234 million major surgeries are performed, leading to plentiful, highly diverse data. This is accompanied by a matching number of novel algorithms for the surgical domain. To garner all benefits of surgical data science it is necessary to have an unambiguous, shared understanding of algorithms and data. This includes inputs and outputs of algorithms and thus their function, but also the semantic content, i.e. meaning of data such as patient parameters. We therefore pr...

Framework for Integrating Science Data Processing Algorithms Into Process Control Systems

Science.gov (United States)

Mattmann, Chris A.; Crichton, Daniel J.; Chang, Albert Y.; Foster, Brian M.; Freeborn, Dana J.; Woollard, David M.; Ramirez, Paul M.

2011-01-01

A software framework called PCS Task Wrapper is responsible for standardizing the setup, process initiation, execution, and file management tasks surrounding the execution of science data algorithms, which are referred to by NASA as Product Generation Executives (PGEs). PGEs codify a scientific algorithm, some step in the overall scientific process involved in a mission science workflow. The PCS Task Wrapper provides a stable operating environment to the underlying PGE during its execution lifecycle. If the PGE requires a file, or metadata regarding the file, the PCS Task Wrapper is responsible for delivering that information to the PGE in a manner that meets its requirements. If the PGE requires knowledge of upstream or downstream PGEs in a sequence of executions, that information is also made available. Finally, if information regarding disk space, or node information such as CPU availability, etc., is required, the PCS Task Wrapper provides this information to the underlying PGE. After this information is collected, the PGE is executed, and its output Product file and Metadata generation is managed via the PCS Task Wrapper framework. The innovation is responsible for marshalling output Products and Metadata back to a PCS File Management component for use in downstream data processing and pedigree. In support of this, the PCS Task Wrapper leverages the PCS Crawler Framework to ingest (during pipeline processing) the output Product files and Metadata produced by the PGE. The architectural components of the PCS Task Wrapper framework include PGE Task Instance, PGE Config File Builder, Config File Property Adder, Science PGE Config File Writer, and PCS Met file Writer. This innovative framework is really the unifying bridge between the execution of a step in the overall processing pipeline, and the available PCS component services as well as the information that they collectively manage.

Informal Learning in Science, Math, and Engineering Majors for African American Female Undergraduates

Science.gov (United States)

McPherson, Ezella

2014-01-01

This research investigates how eight undergraduate African American women in science, math, and engineering (SME) majors accessed cultural capital and informal science learning opportunities from preschool to college. It uses the multiple case study methodological approach and cultural capital as frameworks to better understand the participants'…

Do Biology Students Really Hate Math? Empirical Insights into Undergraduate Life Science Majors' Emotions about Mathematics

Science.gov (United States)

Wachsmuth, Lucas P.; Runyon, Christopher R.; Drake, John M.; Dolan, Erin L.

2017-01-01

Undergraduate life science majors are reputed to have negative emotions toward mathematics, yet little empirical evidence supports this. We sought to compare emotions of majors in the life sciences versus other natural sciences and math. We adapted the Attitudes toward the Subject of Chemistry Inventory to create an Attitudes toward the Subject of…

Science Café Course: An Innovative Means of Improving Communication Skills of Undergraduate Biology Majors

Directory of Open Access Journals (Sweden)

Anna Goldina

2013-12-01

Full Text Available To help bridge the increasing gap between scientists and the public, we developed an innovative two-semester course, called Science Café. In this course undergraduate biology majors learn to develop communication skills to be better able to explain science concepts and current developments in science to non-scientists. Students develop and host outreach events on various topics relevant to the community, thereby increasing interactions between budding scientists and the public. Such a Science Cafe course emphasizes development of science communication skills early, at the undergraduate level and empowers students to use their science knowledge in every day interactions with the public to increase science literacy, get involved in the local community and engage the public in a dialogue on various pressing science issues. We believe that undergraduate science majors can be great ambassadors for science and are often overlooked since many aspire to go on to medical/veterinary/pharmacy schools. However, science communication skills are especially important for these types of students because when they become healthcare professionals, they will interact with the public as part of their everyday jobs and can thus be great representatives for the field.

Python algorithms mastering basic algorithms in the Python language

CERN Document Server

Hetland, Magnus Lie

2014-01-01

Python Algorithms, Second Edition explains the Python approach to algorithm analysis and design. Written by Magnus Lie Hetland, author of Beginning Python, this book is sharply focused on classical algorithms, but it also gives a solid understanding of fundamental algorithmic problem-solving techniques. The book deals with some of the most important and challenging areas of programming and computer science in a highly readable manner. It covers both algorithmic theory and programming practice, demonstrating how theory is reflected in real Python programs. Well-known algorithms and data struc

The Science Teaching Self-Efficacy of Prospective Elementary Education Majors Enrolled in Introductory Geology Lab Sections

Science.gov (United States)

Baldwin, Kathryn A.

2014-01-01

This study examined prospective elementary education majors' science teaching self-efficacy while they were enrolled in an introductory geology lab course for elementary education majors. The Science Teaching Efficacy Belief Instrument Form B (STEBI-B) was administered during the first and last lab class sessions. Additionally, students were…

Machine learning algorithm accurately detects fMRI signature of vulnerability to major depression.

Science.gov (United States)

Sato, João R; Moll, Jorge; Green, Sophie; Deakin, John F W; Thomaz, Carlos E; Zahn, Roland

2015-08-30

Standard functional magnetic resonance imaging (fMRI) analyses cannot assess the potential of a neuroimaging signature as a biomarker to predict individual vulnerability to major depression (MD). Here, we use machine learning for the first time to address this question. Using a recently identified neural signature of guilt-selective functional disconnection, the classification algorithm was able to distinguish remitted MD from control participants with 78.3% accuracy. This demonstrates the high potential of our fMRI signature as a biomarker of MD vulnerability. Crown Copyright © 2015. Published by Elsevier Ireland Ltd. All rights reserved.

Who Owns Educational Theory? Big Data, Algorithms and the Expert Power of Education Data Science

Science.gov (United States)

Williamson, Ben

2017-01-01

"Education data science" is an emerging methodological field which possesses the algorithm-driven technologies required to generate insights and knowledge from educational big data. This article consists of an analysis of the Lytics Lab, Stanford University's laboratory for research and development in learning analytics, and the Center…

A New Approach to Teaching Science to Elementary Education Majors in Response to the NGSS

Science.gov (United States)

Brevik, C.; Daniels, L.; McCoy, C.

2015-12-01

The Next Generation Science Standards (NGSS) place an equal emphasis on science process skills and science content. The goal is to have K-12 students "doing" science, not just "learning about" science. However, most traditional college science classes for elementary education majors place a much stronger emphasis on science content knowledge with the hands-on portion limited to a once-a-week lab. The two models of instruction are not aligned. The result is that many elementary school teachers are unprepared to offer interactive science with their students. Without additional coaching, many teachers fall back on the format they learned in college - lecture, handouts, homework. If we want teachers to use more hands-on methods in the classroom, these techniques should be taught to elementary education majors when they are in college. Dickinson State University has begun a collaboration between the Teacher Education Department and the Department of Natural Sciences. The physical science course for elementary education majors has been completely redesigned to focus equally on the needed science content and the science process skills emphasized by the NGSS. The format of the course has been adjusted to more closely mirror a traditional K-5 classroom; the course meets for 50 minutes five days a week. A flipped-classroom model has been adopted to ensure no content is lost, and hands-on activities are done almost every day as new concepts are discussed. In order to judge the effectiveness of these changes, a survey tool was administered to determine if there was a shift in the students' perception of science as an active instead of a passive field of study. The survey also measured the students' comfort-level in offering a hands-on learning environment in their future classrooms and their confidence in their ability to effectively teach science concepts to elementary students. Results from the first year of the study will be presented.

11th Biennial Conference on Emerging Mathematical Methods, Models and Algorithms for Science and Technology

CERN Document Server

Manchanda, Pammy; Bhardwaj, Rashmi

2015-01-01

The present volume contains invited talks of 11th biennial conference on “Emerging Mathematical Methods, Models and Algorithms for Science and Technology”. The main message of the book is that mathematics has a great potential to analyse and understand the challenging problems of nanotechnology, biotechnology, medical science, oil industry and financial technology. The book highlights all the features and main theme discussed in the conference. All contributing authors are eminent academicians, scientists, researchers and scholars in their respective fields, hailing from around the world.

In Pursuit of LSST Science Requirements: A Comparison of Photometry Algorithms

Science.gov (United States)

Becker, Andrew C.; Silvestri, Nicole M.; Owen, Russell E.; Ivezić, Željko; Lupton, Robert H.

2007-12-01

We have developed an end-to-end photometric data-processing pipeline to compare current photometric algorithms commonly used on ground-based imaging data. This test bed is exceedingly adaptable and enables us to perform many research and development tasks, including image subtraction and co-addition, object detection and measurements, the production of photometric catalogs, and the creation and stocking of database tables with time-series information. This testing has been undertaken to evaluate existing photometry algorithms for consideration by a next-generation image-processing pipeline for the Large Synoptic Survey Telescope (LSST). We outline the results of our tests for four packages: the Sloan Digital Sky Survey's Photo package, DAOPHOT and ALLFRAME, DOPHOT, and two versions of Source Extractor (SExtractor). The ability of these algorithms to perform point-source photometry, astrometry, shape measurements, and star-galaxy separation and to measure objects at low signal-to-noise ratio is quantified. We also perform a detailed crowded-field comparison of DAOPHOT and ALLFRAME, and profile the speed and memory requirements in detail for SExtractor. We find that both DAOPHOT and Photo are able to perform aperture photometry to high enough precision to meet LSST's science requirements, and less adequately at PSF-fitting photometry. Photo performs the best at simultaneous point- and extended-source shape and brightness measurements. SExtractor is the fastest algorithm, and recent upgrades in the software yield high-quality centroid and shape measurements with little bias toward faint magnitudes. ALLFRAME yields the best photometric results in crowded fields.

China’s rise as a major contributor to science and technology

Science.gov (United States)

Xie, Yu; Zhang, Chunni; Lai, Qing

2014-01-01

In the past three decades, China has become a major contributor to science and technology. China now employs an increasingly large labor force of scientists and engineers at relatively high earnings and produces more science and engineering degrees than the United States at all levels, particularly bachelor’s. China’s research and development expenditure has been rising. Research output in China has been sharply increasing since 2002, making China the second largest producer of scientific papers after the United States. The quality of research by Chinese scientists has also been improving steadily. However, China’s rise in science also faces serious difficulties, partly attributable to its rigid, top–down administrative system, with allegations of scientific misconduct trending upward. PMID:24979796

The influences and experiences of African American undergraduate science majors at predominately White universities

Science.gov (United States)

Blockus, Linda Helen

The purpose of this study is to describe and explore some of the social and academic experiences of successful African American undergraduate science majors at predominately White universities with the expectation of conceptualizing emerging patterns for future study. The study surveyed 80 upperclass African Americans at 11 public research universities about their perceptions of the influences that affect their educational experiences and career interests in science. The mailed survey included the Persistence/ voluntary Dropout Decision Scale, the Cultural Congruity Scale and the University Environment Scale. A variety of potential influences were considered including family background, career goals, psychosocial development, academic and social connections with the university, faculty relationships, environmental fit, retention factors, validation, participation in mentored research projects and other experiences. The students' sources of influences, opportunities for connection, and cultural values were considered in the context of a research university environment and investigated for emerging themes and direction for future research. Results indicate that performance in coursework appears to be the most salient factor in African American students' experience as science majors. The mean college gpa was 3.01 for students in this study. Challenging content, time demands, study habits and concern with poor grades all serve to discourage students; however, for most of the students in this study, it has not dissuaded them from their educational and career plans. Positive course performance provided encouragement. Science faculty provide less influence than family members, and more students find faculty members discouraging than supportive. Measures of faculty relations were not associated with academic success. No evidence was provided to confirm the disadvantages of being female in a scientific discipline. Students were concerned with lack of minority role models

Advanced placement math and science courses: Influential factors and predictors for success in college STEM majors

Science.gov (United States)

Hoepner, Cynthia Colon

President Obama has recently raised awareness on the need for our nation to grow a larger pool of students with knowledge in science mathematics, engineering, and technology (STEM). Currently, while the number of women pursuing college degrees continues to rise, there remains an under-representation of women in STEM majors across the country. Although research studies offer several contributing factors that point to a higher attrition rate of women in STEM than their male counterparts, no study has investigated the role that high school advanced placement (AP) math and science courses play in preparing students for the challenges of college STEM courses. The purpose of this study was to discover which AP math and science courses and/or influential factors could encourage more students, particularly females, to consider pursuing STEM fields in college. Further, this study examined which, if any, AP math or science courses positively contribute to a student's overall preparation for college STEM courses. This retrospective study combined quantitative and qualitative research methods. The survey sample consisted of 881 UCLA female and male students pursuing STEM majors. Qualitative data was gathered from four single-gender student focus groups, two female groups (15 females) and two male groups (16 males). This study examined which AP math and science courses students took in high school, who or what influenced them to take those courses, and which particular courses influenced student's choice of STEM major and/or best prepared her/him for the challenges of STEM courses. Findings reveal that while AP math and science course-taking patterns are similar of female and male STEM students, a significant gender-gap remains in five of the eleven AP courses. Students report four main influences on their choice of AP courses; self, desire for math/science major, higher grade point average or class rank, and college admissions. Further, three AP math and science courses were

A Low-Tech, Hands-On Approach To Teaching Sorting Algorithms to Working Students.

Science.gov (United States)

Dios, R.; Geller, J.

1998-01-01

Focuses on identifying the educational effects of "activity oriented" instructional techniques. Examines which instructional methods produce enhanced learning and comprehension. Discusses the problem of learning "sorting algorithms," a major topic in every Computer Science curriculum. Presents a low-tech, hands-on teaching method for sorting…

Emphasizing Astrobiology: Highlighting Communication in an Elective Course for Science Majors

Science.gov (United States)

Offerdahl, Erika G.; Prather, Edward E.; Slater, Timothy F.

2004-01-01

The project described here involved the design, implementation, and evaluation of an upper level, undergraduate elective course for science majors. Specific course goals were to help students gain an appreciation of the interdisciplinary nature of astrobiology, understand key ideas in astrobiology, and develop the skills necessary to communicate…

Science or liberal arts? Cultural capital and college major choice in China.

Science.gov (United States)

Hu, Anning; Wu, Xiaogang

2017-12-19

Previous studies on major East Asian societies such as Japan and Korea generally fail to find a strong effect of cultural capital in educational inequality, partly due to the characteristic extreme focus on standardized test and curriculum. This study shifts attention to the horizontal stratification of education by investigating the association between family background, cultural capital, and college major choice in contemporary China. Based on analysis of data from the Beijing College Students Panel Survey (BCSPS), we found that, on average, cultural capital significantly mediates the relationship between family background and college major preference. Those with greater endowment of cultural capital are more likely to come from socio-economically advantaged families, and, at the same time, demonstrate a stronger propensity to major in liberal arts fields rather than science, technology, engineering and mathematics (STEM) fields. Further analyses reveal that the association between cultural capital and academic field choice comes into being by way of performance in the Chinese test in the national college entrance examination and of the non-cognitive dispositions, such as self-efficacy and self-esteem. Our findings better our understanding of formation of the horizontal stratification of higher education. © London School of Economics and Political Science 2017.

Food for thought: understanding the value, variety and usage of management algorithms for major depressive disorder.

Science.gov (United States)

Katzman, Martin A; Anand, Leena; Furtado, Melissa; Chokka, Pratap

2014-12-01

By 2020, depression is projected to be among the most important contributors to the global burden of disease. A plethora of data confirms that despite the availability of effective therapies, major depressive disorder continues to exact an enormous toll; this, in part, is due to difficulties reaching complete remission, as well as the specific associated costs of both the disorder's morbidity and mortality. The negative effects of depression include those on patients' occupational functioning, including absenteeism, presenteeism, and reduced opportunities for educational and work success. The use of management algorithms has been shown to improve treatment outcomes in major depressive disorder and may be less costly than "usual care" practices. Nevertheless, many patients with depression remain untreated. As well, even those who are treated often continue to experience suboptimal quality of life. As such, the treatment algorithms in this article may improve outcomes for patients suffering with depression. This paper introduces some of the principal reasons underlying these treatment gaps and examines measures or recommendations that might be changed or strengthened in future practice guidelines to bridge them. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

At the Crossroads of Art and Science: A New Course for University Non-Science Majors

Science.gov (United States)

Blatt, S. Leslie

2004-03-01

How much did Seurat know about the physics, physiology, and perceptual science of color mixing when he began his experiments in pointillism? Did Vermeer have a camera obscura built into his studio to create the perfect perspective and luminous effects of his canvases? Early in the 20th century, consequences of the idea that "no single reference point is to be preferred above any other" were worked out in physics by Einstein (special and general relativity), in art by Picasso (early cubism), and in music by Schoenberg (12-tone compositions); did this same paradigm-shifting concept arise, in three disparate fields, merely by coincidence? We are developing a new course, aimed primarily at non-science majors, that addresses questions like these through a combination of hands-on experiments on the physics of light, investigations in visual perception, empirical tests of various drawing and painting techniques, and field trips to nearby museums. We will show a few examples of the kinds of art/science intersections our students will be exploring, and present a working outline for the course.

Variations in Primary Teachers’ Responses and Development during Three Major Science In- Service Programmes

Directory of Open Access Journals (Sweden)

Anthony Pell

2011-01-01

Full Text Available This paper reports on how different types of teachers responded to in-service aimed at developing investigative-based science education (IBSE in primary schools, and the extent to which they applied their new skills in the classroom. Common items from evaluation questionnaires allowed data to be combined from three major in-service programmes. Using complete data sets from 120 teachers, cluster analysis enabled three teacher types to be identified: a small group of ‘science unsures’, with low attitude scores and little confidence, who showed no response to the innovation; ‘holistic improvers’, who showed the largest improvement in science teaching confidence; and ‘high level, positive progressives’, who were very positive to science teaching throughout and showed gains in confidence in teaching physics and chemistry, as well as in demonstrating the relevance of science to their pupils. Taking account of these teacher types alongside interviews and observations, nine developmental stages in how teachers apply their new expertise in the classroom and the whole school are suggested. Major factorsinfluencing application in the classroom are the teachers’ initial science knowledge and pedagogical expertise, and motivating feedback to teachers when pupils responded positively to the innovation. Assessing teachers’ initial level of subject knowledge and science pedagogical expertise to inform the approach and amount of in-service provision is important. Subsequent mentoring as well as support from the school principal when teachers first try IBSE with pupils promotes successful implementation in the classroom.

6. Algorithms for Sorting and Searching

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education; Volume 2; Issue 3. Algorithms - Algorithms for Sorting and Searching. R K Shyamasundar. Series Article ... Author Affiliations. R K Shyamasundar1. Computer Science Group, Tata Institute of Fundamental Research, Homi Bhabha Road, Mumbai 400 005, India ...

Comparison between iterative wavefront control algorithm and direct gradient wavefront control algorithm for adaptive optics system

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Cheng, Sheng-Yi; Liu, Wen-Jin; Chen, Shan-Qiu; Dong, Li-Zhi; Yang, Ping; Xu, Bing

2015-08-01

Among all kinds of wavefront control algorithms in adaptive optics systems, the direct gradient wavefront control algorithm is the most widespread and common method. This control algorithm obtains the actuator voltages directly from wavefront slopes through pre-measuring the relational matrix between deformable mirror actuators and Hartmann wavefront sensor with perfect real-time characteristic and stability. However, with increasing the number of sub-apertures in wavefront sensor and deformable mirror actuators of adaptive optics systems, the matrix operation in direct gradient algorithm takes too much time, which becomes a major factor influencing control effect of adaptive optics systems. In this paper we apply an iterative wavefront control algorithm to high-resolution adaptive optics systems, in which the voltages of each actuator are obtained through iteration arithmetic, which gains great advantage in calculation and storage. For AO system with thousands of actuators, the computational complexity estimate is about O(n2) ˜ O(n3) in direct gradient wavefront control algorithm, while the computational complexity estimate in iterative wavefront control algorithm is about O(n) ˜ (O(n)3/2), in which n is the number of actuators of AO system. And the more the numbers of sub-apertures and deformable mirror actuators, the more significant advantage the iterative wavefront control algorithm exhibits. Project supported by the National Key Scientific and Research Equipment Development Project of China (Grant No. ZDYZ2013-2), the National Natural Science Foundation of China (Grant No. 11173008), and the Sichuan Provincial Outstanding Youth Academic Technology Leaders Program, China (Grant No. 2012JQ0012).

Beliefs and Attitudes about Science and Mathematics in Pre-Service Elementary Teachers, STEM, and Non-STEM Majors in Undergraduate Physics Courses

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Michaluk, Lynnette; Stoiko, Rachel; Stewart, Gay; Stewart, John

2018-04-01

Elementary teachers often hold inaccurate beliefs about the Nature of Science (NoS) and have negative attitudes toward science and mathematics. Using a pre-post design, the current study examined beliefs about the NoS, attitudes toward science and mathematics, and beliefs about the teaching of mathematics and science in a large sample study ( N = 343) of pre-service teachers receiving a curriculum-wide intervention to improve these factors in comparison with Science, Technology, Engineering, and Mathematics (STEM) and non-STEM majors in other physics courses ( N = 6697) who did not receive the intervention, over a 10-year period. Pre-service teachers evidenced initially more negative attitudes about mathematics and science than STEM majors and slightly more positive attitudes than non-STEM majors. Their attitudes toward mathematics and science and beliefs about the NoS were more similar to non-STEM than STEM majors. Pre-service teachers initially evidenced more positive beliefs about the teaching of mathematics and science, and their beliefs even increased slightly over the course of the semester, while these beliefs in other groups remained the same. Beliefs about the NoS and the teaching of mathematics and science were significantly negatively correlated for STEM and non-STEM majors, but were not significantly correlated for pre-service teachers. Beliefs about the NoS and attitudes toward mathematics and science were significantly positively correlated for both pre-service teachers and STEM students pursing the most mathematically demanding STEM majors. Attitudes toward science and mathematics were significantly positively correlated with accurate beliefs about the teaching of mathematics and science for all student groups.

Pharmacogenetics-based warfarin dosing algorithm decreases time to stable anticoagulation and the risk of major hemorrhage: an updated meta-analysis of randomized controlled trials.

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Wang, Zhi-Quan; Zhang, Rui; Zhang, Peng-Pai; Liu, Xiao-Hong; Sun, Jian; Wang, Jun; Feng, Xiang-Fei; Lu, Qiu-Fen; Li, Yi-Gang

2015-04-01

Warfarin is yet the most widely used oral anticoagulant for thromboembolic diseases, despite the recently emerged novel anticoagulants. However, difficulty in maintaining stable dose within the therapeutic range and subsequent serious adverse effects markedly limited its use in clinical practice. Pharmacogenetics-based warfarin dosing algorithm is a recently emerged strategy to predict the initial and maintaining dose of warfarin. However, whether this algorithm is superior over conventional clinically guided dosing algorithm remains controversial. We made a comparison of pharmacogenetics-based versus clinically guided dosing algorithm by an updated meta-analysis. We searched OVID MEDLINE, EMBASE, and the Cochrane Library for relevant citations. The primary outcome was the percentage of time in therapeutic range. The secondary outcomes were time to stable therapeutic dose and the risks of adverse events including all-cause mortality, thromboembolic events, total bleedings, and major bleedings. Eleven randomized controlled trials with 2639 participants were included. Our pooled estimates indicated that pharmacogenetics-based dosing algorithm did not improve percentage of time in therapeutic range [weighted mean difference, 4.26; 95% confidence interval (CI), -0.50 to 9.01; P = 0.08], but it significantly shortened the time to stable therapeutic dose (weighted mean difference, -8.67; 95% CI, -11.86 to -5.49; P pharmacogenetics-based algorithm significantly reduced the risk of major bleedings (odds ratio, 0.48; 95% CI, 0.23 to 0.98; P = 0.04), but it did not reduce the risks of all-cause mortality, total bleedings, or thromboembolic events. Our results suggest that pharmacogenetics-based warfarin dosing algorithm significantly improves the efficiency of International Normalized Ratio correction and reduces the risk of major hemorrhage.

Female and male Hispanic students majoring in science or engineering: Their stories describing their educational journeys

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Brown, Susan Wightman

National statistics clearly demonstrate an underrepresentation of minorities in the fields of science and engineering. Blacks, Hispanics, American Indians, and Asians do not typically choose science or engineering as their college major; therefore, there is a very small representation of these minorities in the science and engineering labor force. The decision not to major in science and engineering may begin as soon as the child can begin to recognize role models in the media. News stories, magazine articles, television programs, teachers, parents, administrators, and other agencies have painted the picture of a scientist or engineer as being dominantly a White male. Schools have continued society's portrayal by using curriculum, textbooks, role models, instructional strategies, and counseling that continues to encourage the White male to succeed in science and engineering, but discourages the minority students, male and female, from succeeding in these fields. In this qualitative study, 22 Hispanic students, 12 female and 10 male, who are majoring in science or engineering, were interviewed using Seidman's in-depth interviewing technique. These students were shadowed in their college science or engineering classes; their high school and college transcripts were analyzed; and, a focus group was brought together at the end of the interviewing process in order to allow interaction between the participants. The goal was to explore the educational journeys of the 22 Hispanic students. What made a difference in the journeys of these 22 students so that they could succeed in majors that have historically discouraged minority students? Seven themes emerged: family support, honors program, challenging and interactive curriculum, college preparation in high school courses, caring and kind teachers, small class size, and small communities. Gender comparison of the educational journeys documents these differences between the females and males: college preparation, mentoring

Research and Teaching: Using Twitter in a Nonscience Major Science Class Increases Journal of College Science Teaching

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Halpin, Patricia A.

2016-01-01

Nonscience majors often rely on general internet searches to locate science information. This practice can lead to misconceptions because the returned search information can be unreliable. In this article the authors describe how they used the social media site Twitter to address this problem in a general education course, BSCI 421 Diseases of the…

Eating disorder risk, exercise dependence, and body weight dissatisfaction among female nutrition and exercise science university majors.

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Harris, Natalie; Gee, David; d'Acquisto, Debra; Ogan, Dana; Pritchett, Kelly

2015-09-01

Past research has examined eating disorder risk among college students majoring in Nutrition and has suggested an increased risk, while other studies contradict these results. Exercise Science majors, however, have yet to be fully examined regarding their risk for eating disorders and exercise dependence. Based on pressures to fit the image associated with careers related to these two disciplines, research is warranted to examine the potential risk for both eating disorder and exercise dependence. The purpose of this study is to compare eating disorder risk, exercise dependence, and body weight dissatisfaction (BWD) between Nutrition and Exercise Science majors, compared to students outside of these career pathways. Participants (n = 89) were divided into three groups based on major; Nutrition majors (NUTR; n = 31), Exercise Science majors (EXSC; n = 30), and other majors (CON; n = 28). Participants were given the EAT-26 questionnaire and the Exercise Dependence Scale. BWD was calculated as the discrepancy between actual BMI and ideal BMI. The majority of participants expressed a desire to weigh less (83%) and EXSC had significantly (p = .03) greater BWD than NUTR. However, there were no significant differences in eating disorder risk or exercise dependence among majors. This study suggested there was no significant difference in eating disorder risk or exercise dependence between the three groups (NUTR, EXSC, and CON).

Green Chemistry and Sustainability: An Undergraduate Course for Science and Nonscience Majors

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Gross, Erin M.

2013-01-01

An undergraduate lecture course in Green Chemistry and Sustainability has been developed and taught to a "multidisciplinary" group of science and nonscience majors. The course introduced students to the topics of green chemistry and sustainability and also immersed them in usage of the scientific literature. Through literature…

Models of science dynamics encounters between complexity theory and information sciences

CERN Document Server

Börner, Katy; Besselaar, Peter

2012-01-01

Models of science dynamics aim to capture the structure and evolution of science. They are developed in an emerging research area in which scholars, scientific institutions and scientific communications become themselves basic objects of research. In order to understand phenomena as diverse as the structure of evolving co-authorship networks or citation diffusion patterns, different models have been developed. They include conceptual models based on historical and ethnographic observations, mathematical descriptions of measurable phenomena, and computational algorithms. Despite its evident importance, the mathematical modeling of science still lacks a unifying framework and a comprehensive research agenda. This book aims to fill this gap, reviewing and describing major threads in the mathematical modeling of science dynamics for a wider academic and professional audience. The model classes presented here cover stochastic and statistical models, game-theoretic approaches, agent-based simulations, population-dy...

Recruitment of Early STEM Majors into Possible Secondary Science Teaching Careers: The Role of Science Education Summer Internships

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Borgerding, Lisa A.

2015-01-01

A shortage of highly qualified math and science teachers pervades the U.S. public school system. Clearly, recruitment of talented STEM educators is critical. Previous literature offers many suggestions for how STEM teacher recruitment programs and participant selection should occur. This study investigates how early STEM majors who are not already…

Nature-inspired optimization algorithms

CERN Document Server

Yang, Xin-She

2014-01-01

Nature-Inspired Optimization Algorithms provides a systematic introduction to all major nature-inspired algorithms for optimization. The book's unified approach, balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with well-chosen case studies to illustrate how these algorithms work. Topics include particle swarm optimization, ant and bee algorithms, simulated annealing, cuckoo search, firefly algorithm, bat algorithm, flower algorithm, harmony search, algorithm analysis, constraint handling, hybrid methods, parameter tuning

Research in applied mathematics, numerical analysis, and computer science

Science.gov (United States)

1984-01-01

Research conducted at the Institute for Computer Applications in Science and Engineering (ICASE) in applied mathematics, numerical analysis, and computer science is summarized and abstracts of published reports are presented. The major categories of the ICASE research program are: (1) numerical methods, with particular emphasis on the development and analysis of basic numerical algorithms; (2) control and parameter identification; (3) computational problems in engineering and the physical sciences, particularly fluid dynamics, acoustics, and structural analysis; and (4) computer systems and software, especially vector and parallel computers.

Perceptions of psychology as a science among university students: the influence of psychology courses and major of study.

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Bartels, Jared M; Hinds, Ryan M; Glass, Laura A; Ryan, Joseph J

2009-10-01

The goal was to examine the relationship between the number of psychology courses students have taken and their perceptions of psychology as a science. Additionally, differences in perceptions of psychology among psychology, education, and natural science majors were examined. Results indicated that students who had taken four or more psychology courses had more favorable perceptions of psychology as a science compared to those who had taken no courses or one course and those who had taken two to three courses. No significant differences in overall perceptions of psychology emerged among students in the three majors.

Consideration of learning orientations as an application of achievement goals in evaluating life science majors in introductory physics

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Mason, Andrew J.; Bertram, Charles A.

2018-06-01

When considering performing an Introductory Physics for Life Sciences course transformation for one's own institution, life science majors' achievement goals are a necessary consideration to ensure the pedagogical transformation will be effective. However, achievement goals are rarely an explicit consideration in physics education research topics such as metacognition. We investigate a sample population of 218 students in a first-semester introductory algebra-based physics course, drawn from 14 laboratory sections within six semesters of course sections, to determine the influence of achievement goals on life science majors' attitudes towards physics. Learning orientations that, respectively, pertain to mastery goals and performance goals, in addition to a learning orientation that does not report a performance goal, were recorded from students in the specific context of learning a problem-solving framework during an in-class exercise. Students' learning orientations, defined within the context of students' self-reported statements in the specific context of a problem-solving-related research-based course implementation, are compared to pre-post results on physics problem-solving items in a well-established attitudinal survey instrument, in order to establish the categories' validity. In addition, mastery-related and performance-related orientations appear to extend to overall pre-post attitudinal shifts, but not to force and motion concepts or to overall course grade, within the scope of an introductory physics course. There also appears to be differentiation regarding overall course performance within health science majors, but not within biology majors, in terms of learning orientations; however, health science majors generally appear to fare less well on all measurements in the study than do biology majors, regardless of learning orientations.

The Texas Medication Algorithm Project (TMAP) schizophrenia algorithms.

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Miller, A L; Chiles, J A; Chiles, J K; Crismon, M L; Rush, A J; Shon, S P

1999-10-01

In the Texas Medication Algorithm Project (TMAP), detailed guidelines for medication management of schizophrenia and related disorders, bipolar disorders, and major depressive disorders have been developed and implemented. This article describes the algorithms developed for medication treatment of schizophrenia and related disorders. The guidelines recommend a sequence of medications and discuss dosing, duration, and switch-over tactics. They also specify response criteria at each stage of the algorithm for both positive and negative symptoms. The rationale and evidence for each aspect of the algorithms are presented.

Male Saudi Arabian freshman science majors at Jazan University: Their perceptions of parental educational practices on their science achievements

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Alrehaly, Essa D.

Examination of Saudi Arabian educational practices is scarce, but increasingly important, especially in light of the country's pace in worldwide mathematics and science rankings. The purpose of the study is to understand and evaluate parental influence on male children's science education achievements in Saudi Arabia. Parental level of education and participant's choice of science major were used to identify groups for the purpose of data analysis. Data were gathered using five independent variables concerning parental educational practices (attitude, involvement, autonomy support, structure and control) and the dependent variable of science scores in high school. The sample consisted of 338 participants and was arbitrarily drawn from the science-based colleges (medical, engineering, and natural science) at Jazan University in Saudi Arabia. The data were tested using Pearson's analysis, backward multiple regression, one way ANOVA and independent t-test. The findings of the study reveal significant correlations for all five of the variables. Multiple regressions revealed that all five of the parents' educational practices indicators combined together could explain 19% of the variance in science scores and parental attitude toward science and educational involvement combined accounted for more than 18% of the variance. Analysis indicates that no significant difference is attributable to parental involvement and educational level. This finding is important because it indicates that, in Saudi Arabia, results are not consistent with research in Western or other Asian contexts.

Using the Theme of Mass Extinctions to Teach Science to Non-Science Major College and University Students

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Boness, D. A.

2013-12-01

The general public is heavily exposed to "news" and commentary---and arts and entertainment---that either inadvertently misrepresents science or even acts to undermine it. Climate change denial and evolution denial is well funded and pervasive. Even university-educated people get little exposure to the aims, methods, debates, and results of scientific inquiry because unless they earn degrees in science they typically only take one or two introductory science courses at the university level. This presentation reports the development of a new, non-science major Seattle University course on mass extinctions throughout earth history. Seattle University is an urban, Jesuit Catholic university. The topic of mass extinctions was chosen for several reasons: (1) To expose the students to a part of current science that has rich historical roots yet by necessity uses methods and reasoning from geology, geophysics, oceanography, physics, chemistry, biology, and astronomy. This multidisciplinary course provides some coverage of sciences that the student would not typically ever see beyond secondary school. (2) To enable the students to learn enough to follow some of the recent and current debates within science (e.g., mass extinctions by asteroid impact versus massive volcanism, ocean anoxia, and ocean acidification), with the students reading some of the actual literature, such as articles in Science, Nature, or Nature Geoscience. (3) To emphasize the importance of "deep time" as evolutionary biological processes interact with massive environmental change over time scales from hundreds of millions of years down to the seconds and hours of an asteroid or comet strike. (4) To show the effects of climate change in the past, present, and future, due to both natural and anthropogenic causes. (5) To help the student critically evaluate the extent to which their future involves a human-caused mass extinction.

An Informal Science Education Program's Impact on STEM Major and STEM Career Outcomes

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Habig, Bobby; Gupta, Preeti; Levine, Brian; Adams, Jennifer

2018-04-01

While there is extensive evidence that STEM careers can be important pathways for augmenting social mobility and for increasing individual prestige, many youth perceive a STEM trajectory as an unattractive option. In the USA, women and members of historically marginalized racial and ethnic groups continue to be underrepresented across STEM disciplines. One vehicle for generating and sustaining interest in STEM is providing youth long-term access to informal science education (ISE) institutions. Here, we incorporate triangulation methods, collecting and synthesizing both qualitative and quantitative data, to examine how participation in a longitudinal ISE out-of-school time (OST) program facilitated by the American Museum of Natural History (AMNH) impacted the STEM trajectories of 66 alumni. Findings revealed that 83.2% of alumni engaged in a STEM major, and 63.1% in a STEM career, the majority whom were females and/or members of historically underrepresented racial and ethnic groups. Based on interviews with a purposeful sample of 21 AMNH alumni, we identified four program design principles that contributed to persistence in STEM: (1) affording multiple opportunities to become practitioners of science; (2) providing exposure to and repeated experiences with STEM professionals such as scientists, educators, and graduate students to build social networks; (3) furnishing opportunities for participants to develop shared science identities with like-minded individuals; and (4) offering exposure to and preparation for a variety of STEM majors and STEM careers so that youth can engage in discovering possible selves. These findings support our central thesis that long-term engagement in ISE OST programs fosters persistence in STEM.

Science and the major racket sports: a review.

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Lees, Adrian

2003-09-01

The major racket sports include badminton, squash, table tennis and tennis. The growth of sports science and the commercialization of racket sports in recent years have focused attention on improved performance and this has led to a more detailed study and understanding of all aspects of racket sports. The aim here, therefore, is to review recent developments of the application of science to racket sports. The scientific disciplines of sports physiology and nutrition, notational analysis, sports biomechanics, sports medicine, sports engineering, sports psychology and motor skills are briefly considered in turn. It is evident from these reviews that a great deal of scientific endeavour has been applied to racket sports, but this is variable across both the racket sports and the scientific disciplines. A scientific approach has helped to: implement training programmes to improve players' fitness; guide players in nutritional and psychological preparation for play; inform players of the strategy and tactics used by themselves and their opponents; provide insight into the technical performance of skills; understand the effect of equipment on play; and accelerate the recovery from racket-arm injuries. Racket sports have also posed a unique challenge to scientists and have provided vehicles for developing scientific methodology. Racket sports provide a good model for investigating the interplay between aerobic and anaerobic metabolism and the effect of nutrition, heat and fatigue on performance. They have driven the development of mathematical solutions for multi-segment interactions within the racket arm during the performance of shots, which have contributed to our understanding of the mechanisms of both performance and injury. They have provided a unique challenge to sports engineers in relation to equipment performance and interaction with the player. Racket sports have encouraged developments in notational analysis both in terms of analytical procedures and the

When Are Students Ready for Research Methods? A Curriculum Mapping Argument for the Political Science Major

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Bergbower, Matthew L.

2017-01-01

For many political science programs, research methods courses are a fundamental component of the recommended undergraduate curriculum. However, instructors and students often see these courses as the most challenging. This study explores when it is most appropriate for political science majors to enroll and pass a research methods course. The…

Citizen Science- Lessons learned from non-science majors involved in Globe at Night and the Great Worldwide Star Count

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Browning, S.

2011-12-01

Non-science majors often misunderstand the process of science, potentially leading to a fear or mistrust of scientific inquiry and current scientific theory. Citizen science projects are a critical means of reaching this audience, as many will only take a limited number of science courses during their undergraduate careers. For the past three years, our freshman Earth Science students have participated in both Globe at Night and the Great Worldwide Star Count, citizen science programs that encourage simple astronomical observations which can be compiled globally to investigate a number of issues. Our focus has been introducing students to the effect of light pollution on observational astronomy in an effort to highlight the effect of increasing urbanization in the U.S. on amateur astronomy. These programs, although focused on astronomy, often awaken natural curiosity about the Earth and man's effect on the natural world, a concept that can easily be translated to other areas of Earth science. Challenges encountered include content specific issues, such as misinterpreting the location or magnitude of the constellation being observed, as well as student disinterest or apathy if the project is not seen as being vital to their performance in the course. This presentation reports on lessons learned in the past three years, and offers suggestions for engaging these students more fully in future projects.

New Optimization Algorithms in Physics

CERN Document Server

Hartmann, Alexander K

2004-01-01

Many physicists are not aware of the fact that they can solve their problems by applying optimization algorithms. Since the number of such algorithms is steadily increasing, many new algorithms have not been presented comprehensively until now. This presentation of recently developed algorithms applied in physics, including demonstrations of how they work and related results, aims to encourage their application, and as such the algorithms selected cover concepts and methods from statistical physics to optimization problems emerging in theoretical computer science.

Efficacy Expectations and Vocational Interests as Mediators between Sex and Choice of Math/Science College Majors: A Longitudinal Study

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Lapan; Shaughnessy; Boggs

1996-12-01

A longitudinal study was conducted to test the mediational role of efficacy expectations in relation to sex differences in the choice of a math/science college major. Data on 101 students were gathered prior to their entering college and then again after they had declared a major 3 years later. Path analytic results support the importance of both math self-efficacy beliefs and vocational interest in mathematics in predicting entry into math/science majors and mediating sex differences in these decisions. Also, students who described themselves as more extroverted were less likely to take additional math classes in high school. Students with stronger artistic vocational interests chose majors less related to math and science. School personnel are strongly encouraged to develop programs that challenge the crystallization of efficacy beliefs and vocational interest patterns before students enter college.

Intending to Stay: Images of Scientists, Attitudes Toward Women, and Gender as Influences on Persistence among Science and Engineering Majors

Science.gov (United States)

Wyer, Mary

Contemporary research on gender and persistence in undergraduate education in science and engineering has routinely focused on why students leave their majors rather than asking why students stay. This study compared three common ways of measuring persistence-commitment to major, degree aspirations, and commitment to a science or engineering career-and emphasized factors that would encourage students to persist, including positive images of scientists and engineers, positive attitudes toward gender equity in science and engineering, and positive classroom experiences. A survey was administered in classrooms to a total of 285 female and male students enrolled in two required courses for majors. The results indicate that the different measures of persistence were sensitive to different influences but that students' gender did not interact with their images, attitudes, and experiences in predicted ways. The study concludes that an individual student's gender may be a more important factor in explaining why some female students leave their science and engineering majors than in explaining why others stay.

Are We Teaching Them Anything?: A Model for Measuring Methodology Skills in the Political Science Major

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Siver, Christi; Greenfest, Seth W.; Haeg, G. Claire

2016-01-01

While the literature emphasizes the importance of teaching political science students methods skills, there currently exists little guidance for how to assess student learning over the course of their time in the major. To address this gap, we develop a model set of assessment tools that may be adopted and adapted by political science departments…

Major Links.

Science.gov (United States)

Henderson, Tona

1995-01-01

Provides electronic mail addresses for resources and discussion groups related to the following academic majors: art, biology, business, chemistry, computer science, economics, health sciences, history, literature, math, music, philosophy, political science, psychology, sociology, and theater. (AEF)

SeaWiFS Technical Report Series. Volume 42; Satellite Primary Productivity Data and Algorithm Development: A Science Plan for Mission to Planet Earth

Science.gov (United States)

Falkowski, Paul G.; Behrenfeld, Michael J.; Esaias, Wayne E.; Balch, William; Campbell, Janet W.; Iverson, Richard L.; Kiefer, Dale A.; Morel, Andre; Yoder, James A.; Hooker, Stanford B. (Editor);

Combinatorial optimization algorithms and complexity

CERN Document Server

Papadimitriou, Christos H

1998-01-01

This clearly written, mathematically rigorous text includes a novel algorithmic exposition of the simplex method and also discusses the Soviet ellipsoid algorithm for linear programming; efficient algorithms for network flow, matching, spanning trees, and matroids; the theory of NP-complete problems; approximation algorithms, local search heuristics for NP-complete problems, more. All chapters are supplemented by thought-provoking problems. A useful work for graduate-level students with backgrounds in computer science, operations research, and electrical engineering.

Encyclopedia of Complexity and Systems Science

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Meyers, Robert A

2009-01-01

Encyclopedia of Complexity and Systems Science provides an authoritative single source for understanding and applying the concepts of complexity theory together with the tools and measures for analyzing complex systems in all fields of science and engineering. The science and tools of complexity and systems science include theories of self-organization, complex systems, synergetics, dynamical systems, turbulence, catastrophes, instabilities, nonlinearity, stochastic processes, chaos, neural networks, cellular automata, adaptive systems, and genetic algorithms. Examples of near-term problems and major unknowns that can be approached through complexity and systems science include: The structure, history and future of the universe; the biological basis of consciousness; the integration of genomics, proteomics and bioinformatics as systems biology; human longevity limits; the limits of computing; sustainability of life on earth; predictability, dynamics and extent of earthquakes, hurricanes, tsunamis, and other n...

Modifying ``Six Ideas that Shaped Physics'' for a Life-Science major audience at Hope College

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Mader, Catherine

2005-04-01

The ``Six Ideas That Shaped Physics'' textbook has been adapted and used for use in the algebra-based introductory physics course for non-physics science majors at Hope College. The results of the first use will be presented. Comparison of FCI for pre and post test scores will be compared with results from 8 years of results from both the algebra-based course and the calculus-based course (when we first adopted ``Six Ideas that Shaped Physcs" for the Calculus-based course). In addition, comparison on quantitative tests and homework problems with prior student groups will also be made. Because a large fraction of the audience in the algebra-based course is life-science majors, a goal of this project is to make the material relevant for these students. Supplemental materials that emphasize the connection between the life sciences and the fundamental physics concepts are being be developed to accompany the new textbook. Samples of these materials and how they were used (and received) during class testing will be presented.

Super-Encryption Implementation Using Monoalphabetic Algorithm and XOR Algorithm for Data Security

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Rachmawati, Dian; Andri Budiman, Mohammad; Aulia, Indra

2018-03-01

The exchange of data that occurs offline and online is very vulnerable to the threat of data theft. In general, cryptography is a science and art to maintain data secrecy. An encryption is a cryptography algorithm in which data is transformed into cipher text, which is something that is unreadable and meaningless so it cannot be read or understood by other parties. In super-encryption, two or more encryption algorithms are combined to make it more secure. In this work, Monoalphabetic algorithm and XOR algorithm are combined to form a super- encryption. Monoalphabetic algorithm works by changing a particular letter into a new letter based on existing keywords while the XOR algorithm works by using logic operation XOR Since Monoalphabetic algorithm is a classical cryptographic algorithm and XOR algorithm is a modern cryptographic algorithm, this scheme is expected to be both easy-to-implement and more secure. The combination of the two algorithms is capable of securing the data and restoring it back to its original form (plaintext), so the data integrity is still ensured.

Reflections of Practical Implementation of the academic course Analysis and Design of Algorithms taught in the Universities of Pakistan

Directory of Open Access Journals (Sweden)

Faryal Shamsi

2017-12-01

Full Text Available This Analysis and Design of Algorithm is considered as a compulsory course in the field of Computer Science. It increases the logical and problem solving skills of the students and make their solutions efficient in terms of time and space.  These objectives can only be achieved if a student practically implements what he or she has studied throughout the course. But if the contents of this course are merely studied and rarely practiced then the actual goals of the course is not fulfilled. This article will explore the extent of practical implementation of the course of analysis and design of algorithm. Problems faced by the computer science community and major barriers in the field are also enumerated. Finally, some recommendations are made to overcome the obstacles in the practical implementation of analysis and design of algorithms.

Improved Temperature Sounding and Quality Control Methodology Using AIRS/AMSU Data: The AIRS Science Team Version 5 Retrieval Algorithm

Science.gov (United States)

Susskind, Joel; Blaisdell, John M.; Iredell, Lena; Keita, Fricky

2009-01-01

This paper describes the AIRS Science Team Version 5 retrieval algorithm in terms of its three most significant improvements over the methodology used in the AIRS Science Team Version 4 retrieval algorithm. Improved physics in Version 5 allows for use of AIRS clear column radiances in the entire 4.3 micron CO2 absorption band in the retrieval of temperature profiles T(p) during both day and night. Tropospheric sounding 15 micron CO2 observations are now used primarily in the generation of clear column radiances .R(sub i) for all channels. This new approach allows for the generation of more accurate values of .R(sub i) and T(p) under most cloud conditions. Secondly, Version 5 contains a new methodology to provide accurate case-by-case error estimates for retrieved geophysical parameters and for channel-by-channel clear column radiances. Thresholds of these error estimates are used in a new approach for Quality Control. Finally, Version 5 also contains for the first time an approach to provide AIRS soundings in partially cloudy conditions that does not require use of any microwave data. This new AIRS Only sounding methodology, referred to as AIRS Version 5 AO, was developed as a backup to AIRS Version 5 should the AMSU-A instrument fail. Results are shown comparing the relative performance of the AIRS Version 4, Version 5, and Version 5 AO for the single day, January 25, 2003. The Goddard DISC is now generating and distributing products derived using the AIRS Science Team Version 5 retrieval algorithm. This paper also described the Quality Control flags contained in the DISC AIRS/AMSU retrieval products and their intended use for scientific research purposes.

Finding Relevance, Competence, and Enjoyment: The Development of Domain Identification and Interest in First-Year Science Majors

Science.gov (United States)

Ruff, Chloe

2016-01-01

The purpose of this qualitative study was to examine how first-year college students perceive their development of domain identification with, and interest in, their prospective science major during their initial year of college. Four themes emerged from the coding and analysis of interviews with eight first-year science students: Self-Definition…

Using a dynamic, introductory-level volcanoes class as a means to introduce non-science majors to the geosciences

Science.gov (United States)

Cook, G. W.

2012-12-01

At the University of California, San Diego, I teach a quarter-long, introductory Earth Science class titled "Volcanoes," which is, in essence, a functional class in volcanology designed specifically for non-majors. This large-format (enrollment ~ 85), lecture-based class provides students from an assortment of backgrounds an opportunity to acquire much-needed (and sometimes dreaded) area credits in science, while also serving as an introduction to the Earth Science major at UCSD (offered through Scripps Institution of Oceanography). The overall goal of the course is to provide students with a stimulating and exciting general science option that, using an inherently interesting topic, introduces them to the fundamentals of geoscience. A secondary goal is to promote general science and geoscience literacy among the general population of UCSD. Student evaluations of this course unequivocally indicate a high degree of learning and interest in the material. The majority of students in the class (>80%) are non-science majors and very few students (degree-seeking students. In addition, only a handful of students have typically had any form of geology class beyond high school level Earth Science. Consequently, there are challenges associated with teaching the class. Perhaps most significantly, students have very little background—background that is necessary for understanding the processes involved in volcanic eruptions. Second, many non-science students have built-in anxieties with respect to math and science, anxieties that must be considered when designing curriculum and syllabi. It is essential to provide the right balance of technical information while remaining in touch with the audience. My approach to the class involves a dynamic lecture format that incorporates a wide array of multimedia, analogue demonstrations of volcanic processes, and small-group discussions of topics and concepts. In addition to teaching about volcanoes—a fascinating subject in and of

Consideration of Learning Orientations as an Application of Achievement Goals in Evaluating Life Science Majors in Introductory Physics

Science.gov (United States)

Mason, Andrew J.; Bertram, Charles A.

2018-01-01

When considering performing an Introductory Physics for Life Sciences course transformation for one's own institution, life science majors' achievement goals are a necessary consideration to ensure the pedagogical transformation will be effective. However, achievement goals are rarely an explicit consideration in physics education research topics…

Family matters: Familial support and science identity formation for African American female STEM majors

Science.gov (United States)

Parker, Ashley Dawn

This research seeks to understand the experiences of African American female undergraduates in STEM. It investigates how familial factors and science identity formation characteristics influence persistence in STEM while considering the duality of African American women's status in society. This phenomenological study was designed using critical race feminism as the theoretical framework to answer the following questions: 1) What role does family play in the experiences of African American women undergraduate STEM majors who attended two universities in the UNC system? 2) What factors impact the formation of science identity for African American women undergraduate STEM majors who attended two universities in the UNC system? Purposive sampling was used to select the participants for this study. The researcher conducted in-depth interviews with 10 African American female undergraduate STEM major from a predominantly White and a historically Black institution with the state of North Carolina public university system. Findings suggest that African American families and science identity formation influence the STEM experiences of the African American females interviewed in this study. The following five themes emerged from the findings: (1) independence, (2) support, (3) pressure to succeed, (4) adaptations, and (5) race and gender. This study contributes to the literature on African American female students in STEM higher education. The findings of this study produced knowledge regarding policies and practices that can lead to greater academic success and persistence of African American females in higher education in general, and STEM majors in particular. Colleges and universities may benefit from the findings of this study in a way that allows them to develop and sustain programs and policies that attend to the particular concerns and needs of African American women on their campuses. Finally, this research informs both current and future African American female

The design and results of an algorithm for intelligent ground vehicles

Science.gov (United States)

Duncan, Matthew; Milam, Justin; Tote, Caleb; Riggins, Robert N.

2010-01-01

This paper addresses the design, design method, test platform, and test results of an algorithm used in autonomous navigation for intelligent vehicles. The Bluefield State College (BSC) team created this algorithm for its 2009 Intelligent Ground Vehicle Competition (IGVC) robot called Anassa V. The BSC robotics team is comprised of undergraduate computer science, engineering technology, marketing students, and one robotics faculty advisor. The team has participated in IGVC since the year 2000. A major part of the design process that the BSC team uses each year for IGVC is a fully documented "Post-IGVC Analysis." Over the nine years since 2000, the lessons the students learned from these analyses have resulted in an ever-improving, highly successful autonomous algorithm. The algorithm employed in Anassa V is a culmination of past successes and new ideas, resulting in Anassa V earning several excellent IGVC 2009 performance awards, including third place overall. The paper will discuss all aspects of the design of this autonomous robotic system, beginning with the design process and ending with test results for both simulation and real environments.

Development of GPS Receiver Kalman Filter Algorithms for Stationary, Low-Dynamics, and High-Dynamics Applications

Science.gov (United States)

2016-06-01

Filter Algorithms for Stationary, Low-Dynamics, and High-Dynamics Applications Executive Summary The Global Positioning system ( GPS ) is the primary...software that may need to be developed for performance prediction of current or future systems that incorporate GPS . The ultimate aim is to help inform...Defence Science and Technology Organisation in 1986. His major areas of work were adaptive tracking , sig- nal processing, and radar systems engineering

Partitional clustering algorithms

CERN Document Server

2015-01-01

This book summarizes the state-of-the-art in partitional clustering. Clustering, the unsupervised classification of patterns into groups, is one of the most important tasks in exploratory data analysis. Primary goals of clustering include gaining insight into, classifying, and compressing data. Clustering has a long and rich history that spans a variety of scientific disciplines including anthropology, biology, medicine, psychology, statistics, mathematics, engineering, and computer science. As a result, numerous clustering algorithms have been proposed since the early 1950s. Among these algorithms, partitional (nonhierarchical) ones have found many applications, especially in engineering and computer science. This book provides coverage of consensus clustering, constrained clustering, large scale and/or high dimensional clustering, cluster validity, cluster visualization, and applications of clustering. Examines clustering as it applies to large and/or high-dimensional data sets commonly encountered in reali...

Enabling high performance computational science through combinatorial algorithms

International Nuclear Information System (INIS)

Boman, Erik G; Bozdag, Doruk; Catalyurek, Umit V; Devine, Karen D; Gebremedhin, Assefaw H; Hovland, Paul D; Pothen, Alex; Strout, Michelle Mills

2007-01-01

The Combinatorial Scientific Computing and Petascale Simulations (CSCAPES) Institute is developing algorithms and software for combinatorial problems that play an enabling role in scientific and engineering computations. Discrete algorithms will be increasingly critical for achieving high performance for irregular problems on petascale architectures. This paper describes recent contributions by researchers at the CSCAPES Institute in the areas of load balancing, parallel graph coloring, performance improvement, and parallel automatic differentiation

Enabling high performance computational science through combinatorial algorithms

Energy Technology Data Exchange (ETDEWEB)

Boman, Erik G [Discrete Algorithms and Math Department, Sandia National Laboratories (United States); Bozdag, Doruk [Biomedical Informatics, and Electrical and Computer Engineering, Ohio State University (United States); Catalyurek, Umit V [Biomedical Informatics, and Electrical and Computer Engineering, Ohio State University (United States); Devine, Karen D [Discrete Algorithms and Math Department, Sandia National Laboratories (United States); Gebremedhin, Assefaw H [Computer Science and Center for Computational Science, Old Dominion University (United States); Hovland, Paul D [Mathematics and Computer Science Division, Argonne National Laboratory (United States); Pothen, Alex [Computer Science and Center for Computational Science, Old Dominion University (United States); Strout, Michelle Mills [Computer Science, Colorado State University (United States)

2007-07-15

The Combinatorial Scientific Computing and Petascale Simulations (CSCAPES) Institute is developing algorithms and software for combinatorial problems that play an enabling role in scientific and engineering computations. Discrete algorithms will be increasingly critical for achieving high performance for irregular problems on petascale architectures. This paper describes recent contributions by researchers at the CSCAPES Institute in the areas of load balancing, parallel graph coloring, performance improvement, and parallel automatic differentiation.

Review of applications of TLBO algorithm and a tutorial for beginners to solve the unconstrained and constrained optimization problems

Directory of Open Access Journals (Sweden)

R. Venkata Rao

2016-01-01

Full Text Available The teaching-learning-based optimization (TLBO algorithm is finding a large number of applications in different fields of engineering and science since its introduction in 2011. The major applications are found in electrical engineering, mechanical design, thermal engineering, manufacturing engineering, civil engineering, structural engineering, computer engineering, electronics engineering, physics, chemistry, biotechnology and economics. This paper presents a review of applications of TLBO algorithm and a tutorial for solving the unconstrained and constrained optimization problems. The tutorial is expected to be useful to the beginners.

A review on quantum search algorithms

Science.gov (United States)

Giri, Pulak Ranjan; Korepin, Vladimir E.

2017-12-01

The use of superposition of states in quantum computation, known as quantum parallelism, has significant advantage in terms of speed over the classical computation. It is evident from the early invented quantum algorithms such as Deutsch's algorithm, Deutsch-Jozsa algorithm and its variation as Bernstein-Vazirani algorithm, Simon algorithm, Shor's algorithms, etc. Quantum parallelism also significantly speeds up the database search algorithm, which is important in computer science because it comes as a subroutine in many important algorithms. Quantum database search of Grover achieves the task of finding the target element in an unsorted database in a time quadratically faster than the classical computer. We review Grover's quantum search algorithms for a singe and multiple target elements in a database. The partial search algorithm of Grover and Radhakrishnan and its optimization by Korepin called GRK algorithm are also discussed.

Map of the Physical Sciences

Energy Technology Data Exchange (ETDEWEB)

Boyack, Kevin W.

1999-07-02

Various efforts to map the structure of science have been undertaken over the years. Using a new tool, VxInsight{trademark}, we have mapped and displayed 3000 journals in the physical sciences. This map is navigable and interactively reveals the structure of science at many different levels. Science mapping studies are typically focused at either the macro-or micro-level. At a macro-level such studies seek to determine the basic structural units of science and their interrelationships. The majority of studies are performed at the discipline or specialty level, and seek to inform science policy and technical decision makers. Studies at both levels probe the dynamic nature of science, and the implications of the changes. A variety of databases and methods have been used for these studies. Primary among databases are the citation indices (SCI and SSCI) from the Institute for Scientific Information, which have gained widespread acceptance for bibliometric studies. Maps are most often based on computed similarities between journal articles (co-citation), keywords or topics (co-occurrence or co-classification), or journals (journal-journal citation counts). Once the similarity matrix is defined, algorithms are used to cluster the data.

Research in progress in applied mathematics, numerical analysis, fluid mechanics, and computer science

Science.gov (United States)

1994-01-01

This report summarizes research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics, fluid mechanics, and computer science during the period October 1, 1993 through March 31, 1994. The major categories of the current ICASE research program are: (1) applied and numerical mathematics, including numerical analysis and algorithm development; (2) theoretical and computational research in fluid mechanics in selected areas of interest to LaRC, including acoustics and combustion; (3) experimental research in transition and turbulence and aerodynamics involving LaRC facilities and scientists; and (4) computer science.

Combinatorial algorithms enabling computational science: tales from the front

International Nuclear Information System (INIS)

Bhowmick, Sanjukta; Boman, Erik G; Devine, Karen; Gebremedhin, Assefaw; Hendrickson, Bruce; Hovland, Paul; Munson, Todd; Pothen, Alex

2006-01-01

Combinatorial algorithms have long played a crucial enabling role in scientific and engineering computations. The importance of discrete algorithms continues to grow with the demands of new applications and advanced architectures. This paper surveys some recent developments in this rapidly changing and highly interdisciplinary field

Combinatorial algorithms enabling computational science: tales from the front

Energy Technology Data Exchange (ETDEWEB)

Bhowmick, Sanjukta [Mathematics and Computer Science Division, Argonne National Laboratory (United States); Boman, Erik G [Discrete Algorithms and Math Department, Sandia National Laboratories (United States); Devine, Karen [Discrete Algorithms and Math Department, Sandia National Laboratories (United States); Gebremedhin, Assefaw [Computer Science Department, Old Dominion University (United States); Hendrickson, Bruce [Discrete Algorithms and Math Department, Sandia National Laboratories (United States); Hovland, Paul [Mathematics and Computer Science Division, Argonne National Laboratory (United States); Munson, Todd [Mathematics and Computer Science Division, Argonne National Laboratory (United States); Pothen, Alex [Computer Science Department, Old Dominion University (United States)

2006-09-15

Combinatorial algorithms have long played a crucial enabling role in scientific and engineering computations. The importance of discrete algorithms continues to grow with the demands of new applications and advanced architectures. This paper surveys some recent developments in this rapidly changing and highly interdisciplinary field.

Intending to stay: Positive images, attitudes, and classroom experiences as influences on students' intentions to persist in science and engineering majors

Science.gov (United States)

Wyer, Mary Beth

2000-10-01

Contemporary research on persistence in undergraduate education in science and engineering has focused primarily on identifying the structural, social, and psychological barriers to participation by students in underrepresented groups. As a result, there is a wealth of data to document why students leave their majors, but there is little direct empirical data to support prevailing presumptions about why students stay. Moreover, researchers have used widely differing definitions and measures of persistence, and they have seldom explored field differences. This study compared three ways of measuring persistence. These constituted three criterion variables: commitment to major, degree aspirations, and commitment to a science/engineering career. The study emphasized social factors that encourage students to persist, including four predictor variables---(1) positive images of scientists/engineers, (2) positive attitudes toward gender and racial equality, (3) positive classroom experiences, and (4) high levels of social integration. In addition, because researchers have repeatedly documented the degree to which women are more likely than men to drop out of science and engineering majors, the study examined the potential impact of gender in relation to these predictor variables. A survey was administered in the classroom to a total of 285 students enrolled in a required course for either a biological sciences and or an engineering major. Predictor variables were developed from standard scales, including the Images of Science/Scientists Scale, the Attitudes toward Women Scale, the Women in Science Scale, and the Perceptions of Prejudice Scale. Based on logistic regression models, results indicate that positive images of scientists and engineers was significantly related to improving the odds of students having a high commitment to major, high degree aspirations, and high commitment to career. There was also evidence that positive attitudes toward gender and racial equality

Distance majorization and its applications.

Science.gov (United States)

Chi, Eric C; Zhou, Hua; Lange, Kenneth

2014-08-01

The problem of minimizing a continuously differentiable convex function over an intersection of closed convex sets is ubiquitous in applied mathematics. It is particularly interesting when it is easy to project onto each separate set, but nontrivial to project onto their intersection. Algorithms based on Newton's method such as the interior point method are viable for small to medium-scale problems. However, modern applications in statistics, engineering, and machine learning are posing problems with potentially tens of thousands of parameters or more. We revisit this convex programming problem and propose an algorithm that scales well with dimensionality. Our proposal is an instance of a sequential unconstrained minimization technique and revolves around three ideas: the majorization-minimization principle, the classical penalty method for constrained optimization, and quasi-Newton acceleration of fixed-point algorithms. The performance of our distance majorization algorithms is illustrated in several applications.

Summary of research in applied mathematics, numerical analysis, and computer sciences

Science.gov (United States)

1986-01-01

The major categories of current ICASE research programs addressed include: numerical methods, with particular emphasis on the development and analysis of basic numerical algorithms; control and parameter identification problems, with emphasis on effective numerical methods; computational problems in engineering and physical sciences, particularly fluid dynamics, acoustics, and structural analysis; and computer systems and software, especially vector and parallel computers.

Design and Evaluation of a One-Semester General Chemistry Course for Undergraduate Life Science Majors

Science.gov (United States)

Schnoebelen, Carly; Towns, Marcy H.; Chmielewski, Jean; Hrycyna, Christine A.

2018-01-01

The chemistry curriculum for undergraduate life science majors at Purdue University has been transformed to better meet the needs of this student population and prepare them for future success. The curriculum, called the 1-2-1 curriculum, includes four consecutive and integrated semesters of instruction in general chemistry, organic chemistry, and…

An Expert System toward Buiding An Earth Science Knowledge Graph

Science.gov (United States)

Zhang, J.; Duan, X.; Ramachandran, R.; Lee, T. J.; Bao, Q.; Gatlin, P. N.; Maskey, M.

2017-12-01

In this ongoing work, we aim to build foundations of Cognitive Computing for Earth Science research. The goal of our project is to develop an end-to-end automated methodology for incrementally constructing Knowledge Graphs for Earth Science (KG4ES). These knowledge graphs can then serve as the foundational components for building cognitive systems in Earth science, enabling researchers to uncover new patterns and hypotheses that are virtually impossible to identify today. In addition, this research focuses on developing mining algorithms needed to exploit these constructed knowledge graphs. As such, these graphs will free knowledge from publications that are generated in a very linear, deterministic manner, and structure knowledge in a way that users can both interact and connect with relevant pieces of information. Our major contributions are two-fold. First, we have developed an end-to-end methodology for constructing Knowledge Graphs for Earth Science (KG4ES) using existing corpus of journal papers and reports. One of the key challenges in any machine learning, especially deep learning applications, is the need for robust and large training datasets. We have developed techniques capable of automatically retraining models and incrementally building and updating KG4ES, based on ever evolving training data. We also adopt the evaluation instrument based on common research methodologies used in Earth science research, especially in Atmospheric Science. Second, we have developed an algorithm to infer new knowledge that can exploit the constructed KG4ES. In more detail, we have developed a network prediction algorithm aiming to explore and predict possible new connections in the KG4ES and aid in new knowledge discovery.

FIREWORKS ALGORITHM FOR UNCONSTRAINED FUNCTION OPTIMIZATION PROBLEMS

Directory of Open Access Journals (Sweden)

Evans BAIDOO

2017-03-01

Full Text Available Modern real world science and engineering problems can be classified as multi-objective optimisation problems which demand for expedient and efficient stochastic algorithms to respond to the optimization needs. This paper presents an object-oriented software application that implements a firework optimization algorithm for function optimization problems. The algorithm, a kind of parallel diffuse optimization algorithm is based on the explosive phenomenon of fireworks. The algorithm presented promising results when compared to other population or iterative based meta-heuristic algorithm after it was experimented on five standard benchmark problems. The software application was implemented in Java with interactive interface which allow for easy modification and extended experimentation. Additionally, this paper validates the effect of runtime on the algorithm performance.

Fractal Landscape Algorithms for Environmental Simulations

Science.gov (United States)

Mao, H.; Moran, S.

2014-12-01

Natural science and geographical research are now able to take advantage of environmental simulations that more accurately test experimental hypotheses, resulting in deeper understanding. Experiments affected by the natural environment can benefit from 3D landscape simulations capable of simulating a variety of terrains and environmental phenomena. Such simulations can employ random terrain generation algorithms that dynamically simulate environments to test specific models against a variety of factors. Through the use of noise functions such as Perlin noise, Simplex noise, and diamond square algorithms, computers can generate simulations that model a variety of landscapes and ecosystems. This study shows how these algorithms work together to create realistic landscapes. By seeding values into the diamond square algorithm, one can control the shape of landscape. Perlin noise and Simplex noise are also used to simulate moisture and temperature. The smooth gradient created by coherent noise allows more realistic landscapes to be simulated. Terrain generation algorithms can be used in environmental studies and physics simulations. Potential studies that would benefit from simulations include the geophysical impact of flash floods or drought on a particular region and regional impacts on low lying area due to global warming and rising sea levels. Furthermore, terrain generation algorithms also serve as aesthetic tools to display landscapes (Google Earth), and simulate planetary landscapes. Hence, it can be used as a tool to assist science education. Algorithms used to generate these natural phenomena provide scientists a different approach in analyzing our world. The random algorithms used in terrain generation not only contribute to the generating the terrains themselves, but are also capable of simulating weather patterns.

Research in progress and other activities of the Institute for Computer Applications in Science and Engineering

Science.gov (United States)

1993-01-01

This report summarizes research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics and computer science during the period April 1, 1993 through September 30, 1993. The major categories of the current ICASE research program are: (1) applied and numerical mathematics, including numerical analysis and algorithm development; (2) theoretical and computational research in fluid mechanics in selected areas of interest to LaRC, including acoustic and combustion; (3) experimental research in transition and turbulence and aerodynamics involving LaRC facilities and scientists; and (4) computer science.

Planning Readings: A Comparative Exploration of Basic Algorithms

Science.gov (United States)

Piater, Justus H.

2009-01-01

Conventional introduction to computer science presents individual algorithmic paradigms in the context of specific, prototypical problems. To complement this algorithm-centric instruction, this study additionally advocates problem-centric instruction. I present an original problem drawn from students' life that is simply stated but provides rich…

The Big Crunch: A Hybrid Solution to Earth and Space Science Instruction for Elementary Education Majors

Science.gov (United States)

Cervato, Cinzia; Kerton, Charles; Peer, Andrea; Hassall, Lesya; Schmidt, Allan

2013-01-01

We describe the rationale and process for the development of a new hybrid Earth and Space Science course for elementary education majors. A five-step course design model, applicable to both online and traditional courses, is presented. Assessment of the course outcomes after two semesters indicates that the intensive time invested in the…

Computational Modeling of Teaching and Learning through Application of Evolutionary Algorithms

Directory of Open Access Journals (Sweden)

Richard Lamb

2015-09-01

Full Text Available Within the mind, there are a myriad of ideas that make sense within the bounds of everyday experience, but are not reflective of how the world actually exists; this is particularly true in the domain of science. Classroom learning with teacher explanation are a bridge through which these naive understandings can be brought in line with scientific reality. The purpose of this paper is to examine how the application of a Multiobjective Evolutionary Algorithm (MOEA can work in concert with an existing computational-model to effectively model critical-thinking in the science classroom. An evolutionary algorithm is an algorithm that iteratively optimizes machine learning based computational models. The research question is, does the application of an evolutionary algorithm provide a means to optimize the Student Task and Cognition Model (STAC-M and does the optimized model sufficiently represent and predict teaching and learning outcomes in the science classroom? Within this computational study, the authors outline and simulate the effect of teaching on the ability of a “virtual” student to solve a Piagetian task. Using the Student Task and Cognition Model (STAC-M a computational model of student cognitive processing in science class developed in 2013, the authors complete a computational experiment which examines the role of cognitive retraining on student learning. Comparison of the STAC-M and the STAC-M with inclusion of the Multiobjective Evolutionary Algorithm shows greater success in solving the Piagetian science-tasks post cognitive retraining with the Multiobjective Evolutionary Algorithm. This illustrates the potential uses of cognitive and neuropsychological computational modeling in educational research. The authors also outline the limitations and assumptions of computational modeling.

Interdisciplinary Project Experiences: Collaboration between Majors and Non-Majors

Science.gov (United States)

Smarkusky, Debra L.; Toman, Sharon A.

2014-01-01

Students in computer science and information technology should be engaged in solving real-world problems received from government and industry as well as those that expose them to various areas of application. In this paper, we discuss interdisciplinary project experiences between majors and non-majors that offered a creative and innovative…

STEPS at CSUN: Increasing Retention of Engineering and Physical Science Majors

Science.gov (United States)

Pedone, V. A.; Cadavid, A. C.; Horn, W.

2012-12-01

STEPS at CSUN seeks to increase the retention rate of first-time freshman in engineering, math, and physical science (STEM) majors from ~55% to 65%. About 40% of STEM first-time freshmen start in College Algebra because they do not take or do not pass the Mathematics Placement Test (MPT). This lengthens time to graduation, which contributes to dissatisfaction with major. STEPS at CSUN has made substantial changes to the administration of the MPT. Initial data show increases in the number of students who take the test and who place out of College Algebra, as well as increases in overall scores. STEPS at CSUN also funded the development of supplemental labs for Trigonometry and Calculus I and II, in partnership with similar labs created by the Math Department for College Algebra and Precalculus. These labs are open to all students, but are mandatory for at-risk students who have low scores on the MPT, low grades in the prerequisite course, or who failed the class the first time. Initial results are promising. Comparison of the grades of 46 Fall 2010 "at-risk" students without lab to those of 36 Fall 2011 students who enrolled in the supplementary lab show D-F grades decreased by 10% and A-B grades increased by 27%. A final retention strategy is aimed at students in the early stages of their majors. At CSUN the greatest loss of STEM majors occurs between sophomore-level and junior-level coursework because course difficulty increases and aspirations to potential careers weaken. The Summer Interdisciplinary Team Experience (SITE) is an intensive 3-week-long summer program that engages small teams of students from diverse STEM majors in faculty-mentored, team-based problem solving. This experience simulates professional work and creates strong bonds between students and between students and faculty mentors. The first two cohorts of students who have participated in SITE indicate that this experience has positively impacted their motivation to complete their STEM degree.

Engaging Non-Science Majors Through Citizen Science Projects In Inquiry-Based Introductory Geoscience Laboratory Courses

Science.gov (United States)

Humphreys, R. R.; Hall, C.; Colgan, M. W.; Rhodes, E.

2010-12-01

Although inquiry-based/problem-based methods have been successfully incorporated in undergraduate lecture classes, a survey of commonly used laboratory manuals indicates that few non-major geoscience laboratory classes use these strategies. The Department of Geology and Environmental Geosciences faculty members have developed a successful introductory Environmental Geology Laboratory course for undergraduate non-majors that challenges traditional teaching methodology as illustrated in most laboratory manuals. The Environmental Geology lab activities employ active learning methods to engage and challenge students. Crucial to establishing an open learning environment is capturing the attention of non-science majors from the moment they enter the classroom. We use catastrophic ‘gloom and doom’ current events to pique the imagination with images, news stories, and videos. Once our students are hooked, we can further the learning process with use of other teaching methods: an inquiry-based approach that requires students take control of their own learning, a cooperative learning approach that requires the participation of all team members in peer learning, and a problem/case study learning approach that primarily relies on activities distilled from current events. The final outcome is focused on creating innovative methods to communicate the findings to the general public. With the general public being the audience for their communiqué, students are less intimated, more focused, and more involved in solving the problem. During lab sessions, teams of students actively engage in mastering course content and develop essential communication skills while exploring real-world scenarios. These activities allow students to use scientific reasoning and concepts to develop solutions for scenarios such as volcanic eruptions, coastal erosion/sea level rise, flooding or landslide hazards, and then creatively communicate their solutions to the public. For example, during a two

Research and Teaching: Factors Related to College Students' Understanding of the Nature of Science--Comparison of Science Majors and Nonscience Majors

Science.gov (United States)

Partin, Matthew L.; Underwood, Eileen M.; Worch, Eric A.

2013-01-01

To develop a more scientifically literate society, students need to understand the nature of science, which may be affected by controversial topics such as evolution. There are conflicting views among researchers concerning the relationships between understanding evolution, acceptance of evolution, and understanding of the nature of science. Four…

COMPUTATIONAL SCIENCE CENTER

International Nuclear Information System (INIS)

DAVENPORT, J.

2006-01-01

Computational Science is an integral component of Brookhaven's multi science mission, and is a reflection of the increased role of computation across all of science. Brookhaven currently has major efforts in data storage and analysis for the Relativistic Heavy Ion Collider (RHIC) and the ATLAS detector at CERN, and in quantum chromodynamics. The Laboratory is host for the QCDOC machines (quantum chromodynamics on a chip), 10 teraflop/s computers which boast 12,288 processors each. There are two here, one for the Riken/BNL Research Center and the other supported by DOE for the US Lattice Gauge Community and other scientific users. A 100 teraflop/s supercomputer will be installed at Brookhaven in the coming year, managed jointly by Brookhaven and Stony Brook, and funded by a grant from New York State. This machine will be used for computational science across Brookhaven's entire research program, and also by researchers at Stony Brook and across New York State. With Stony Brook, Brookhaven has formed the New York Center for Computational Science (NYCCS) as a focal point for interdisciplinary computational science, which is closely linked to Brookhaven's Computational Science Center (CSC). The CSC has established a strong program in computational science, with an emphasis on nanoscale electronic structure and molecular dynamics, accelerator design, computational fluid dynamics, medical imaging, parallel computing and numerical algorithms. We have been an active participant in DOES SciDAC program (Scientific Discovery through Advanced Computing). We are also planning a major expansion in computational biology in keeping with Laboratory initiatives. Additional laboratory initiatives with a dependence on a high level of computation include the development of hydrodynamics models for the interpretation of RHIC data, computational models for the atmospheric transport of aerosols, and models for combustion and for energy utilization. The CSC was formed to bring together

The Effect of a Computer Program Designed with Constructivist Principles for College Non-Science Majors on Understanding of Photosynthesis and Cellular Respiration

Science.gov (United States)

Wielard, Valerie Michelle

2013-01-01

The primary objective of this project was to learn what effect a computer program would have on academic achievement and attitude toward science of college students enrolled in a biology class for non-science majors. It became apparent that the instructor also had an effect on attitudes toward science. The researcher designed a computer program,…

Multimodal optimization by using hybrid of artificial bee colony algorithm and BFGS algorithm

Science.gov (United States)

Anam, S.

2017-10-01

Optimization has become one of the important fields in Mathematics. Many problems in engineering and science can be formulated into optimization problems. They maybe have many local optima. The optimization problem with many local optima, known as multimodal optimization problem, is how to find the global solution. Several metaheuristic methods have been proposed to solve multimodal optimization problems such as Particle Swarm Optimization (PSO), Genetics Algorithm (GA), Artificial Bee Colony (ABC) algorithm, etc. The performance of the ABC algorithm is better than or similar to those of other population-based algorithms with the advantage of employing a fewer control parameters. The ABC algorithm also has the advantages of strong robustness, fast convergence and high flexibility. However, it has the disadvantages premature convergence in the later search period. The accuracy of the optimal value cannot meet the requirements sometimes. Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm is a good iterative method for finding a local optimum. Compared with other local optimization methods, the BFGS algorithm is better. Based on the advantages of the ABC algorithm and the BFGS algorithm, this paper proposes a hybrid of the artificial bee colony algorithm and the BFGS algorithm to solve the multimodal optimization problem. The first step is that the ABC algorithm is run to find a point. In the second step is that the point obtained by the first step is used as an initial point of BFGS algorithm. The results show that the hybrid method can overcome from the basic ABC algorithm problems for almost all test function. However, if the shape of function is flat, the proposed method cannot work well.

A cross-disciplinary introduction to quantum annealing-based algorithms

Science.gov (United States)

Venegas-Andraca, Salvador E.; Cruz-Santos, William; McGeoch, Catherine; Lanzagorta, Marco

2018-04-01

A central goal in quantum computing is the development of quantum hardware and quantum algorithms in order to analyse challenging scientific and engineering problems. Research in quantum computation involves contributions from both physics and computer science; hence this article presents a concise introduction to basic concepts from both fields that are used in annealing-based quantum computation, an alternative to the more familiar quantum gate model. We introduce some concepts from computer science required to define difficult computational problems and to realise the potential relevance of quantum algorithms to find novel solutions to those problems. We introduce the structure of quantum annealing-based algorithms as well as two examples of this kind of algorithms for solving instances of the max-SAT and Minimum Multicut problems. An overview of the quantum annealing systems manufactured by D-Wave Systems is also presented.

Advanced Placement Math and Science Courses: Influential Factors and Predictors for Success in College STEM Majors

Science.gov (United States)

Hoepner, Cynthia Colon

2010-01-01

President Obama has recently raised awareness on the need for our nation to grow a larger pool of students with knowledge in science mathematics, engineering, and technology (STEM). Currently, while the number of women pursuing college degrees continues to rise, there remains an under-representation of women in STEM majors across the country.…

Biomedical Science Undergraduate Major: A New Pathway to Advance Research and the Health Professions.

Science.gov (United States)

Gunn, John S; Ledford, Cynthia H; Mousetes, Steven J; Grever, Michael R

2018-01-01

Many students entering professional degree programs, particularly M.D., Ph.D., and M.D./Ph.D., are not well prepared regarding the breadth of scientific knowledge required, communication skills, research experience, reading and understanding the scientific literature, and significant shadowing (for M.D.-related professions). In addition, physician scientists are a needed and necessary part of the academic research environment but are dwindling in numbers. In response to predictions of critical shortages of clinician investigators and the lack of proper preparation as undergraduates for these professions, the Biomedical Science (BMS) undergraduate major was created at The Ohio State University to attract incoming college freshmen with interests in scientific research and the healthcare professions. The intent of this major was to graduate an elite cohort of highly talented individuals who would pursue careers in the healthcare professions, biomedical research, or both. Students were admitted to the BMS major through an application and interview process. Admitted cohorts were small, comprising 22 to 26 students, and received a high degree of individualized professional academic advising and mentoring. The curriculum included a minimum of 4 semesters (or 2 years) of supervised research experience designed to enable students to gain skills in clinical and basic science investigation. In addition to covering the prerequisites for medicine and advanced degrees in health professions, the integrated BMS coursework emphasized research literacy as well as skills related to work as a healthcare professional, with additional emphasis on independent learning, teamwork to solve complex problems, and both oral and written communication skills. Supported by Ohio State's Department of Internal Medicine, a unique clinical internship provided selected students with insights into potential careers as physician scientists. In this educational case report, we describe the BMS

Separated Representations and Fast Algorithms for Materials Science

National Research Council Canada - National Science Library

Beylkin, Gregory; Monzon, Lucas; Perez, Fernando

2007-01-01

...) and to develop and test algorithms for computing multiparticle wave functions both based on representing operators and functions of many variables as short sums of separable functions the so-called...

Experimental Methods for the Analysis of Optimization Algorithms

DEFF Research Database (Denmark)

, computational experiments differ from those in other sciences, and the last decade has seen considerable methodological research devoted to understanding the particular features of such experiments and assessing the related statistical methods. This book consists of methodological contributions on different...... in algorithm design, statistical design, optimization and heuristics, and most chapters provide theoretical background and are enriched with case studies. This book is written for researchers and practitioners in operations research and computer science who wish to improve the experimental assessment......In operations research and computer science it is common practice to evaluate the performance of optimization algorithms on the basis of computational results, and the experimental approach should follow accepted principles that guarantee the reliability and reproducibility of results. However...

Advanced Methodologies for NASA Science Missions

Science.gov (United States)

Hurlburt, N. E.; Feigelson, E.; Mentzel, C.

2017-12-01

Most of NASA's commitment to computational space science involves the organization and processing of Big Data from space-based satellites, and the calculations of advanced physical models based on these datasets. But considerable thought is also needed on what computations are needed. The science questions addressed by space data are so diverse and complex that traditional analysis procedures are often inadequate. The knowledge and skills of the statistician, applied mathematician, and algorithmic computer scientist must be incorporated into programs that currently emphasize engineering and physical science. NASA's culture and administrative mechanisms take full cognizance that major advances in space science are driven by improvements in instrumentation. But it is less well recognized that new instruments and science questions give rise to new challenges in the treatment of satellite data after it is telemetered to the ground. These issues might be divided into two stages: data reduction through software pipelines developed within NASA mission centers; and science analysis that is performed by hundreds of space scientists dispersed through NASA, U.S. universities, and abroad. Both stages benefit from the latest statistical and computational methods; in some cases, the science result is completely inaccessible using traditional procedures. This paper will review the current state of NASA and present example applications using modern methodologies.

SIAM Conference on Computational Science and Engineering

Energy Technology Data Exchange (ETDEWEB)

None, None

2005-08-29

The Second SIAM Conference on Computational Science and Engineering was held in San Diego from February 10-12, 2003. Total conference attendance was 553. This is a 23% increase in attendance over the first conference. The focus of this conference was to draw attention to the tremendous range of major computational efforts on large problems in science and engineering, to promote the interdisciplinary culture required to meet these large-scale challenges, and to encourage the training of the next generation of computational scientists. Computational Science & Engineering (CS&E) is now widely accepted, along with theory and experiment, as a crucial third mode of scientific investigation and engineering design. Aerospace, automotive, biological, chemical, semiconductor, and other industrial sectors now rely on simulation for technical decision support. For federal agencies also, CS&E has become an essential support for decisions on resources, transportation, and defense. CS&E is, by nature, interdisciplinary. It grows out of physical applications and it depends on computer architecture, but at its heart are powerful numerical algorithms and sophisticated computer science techniques. From an applied mathematics perspective, much of CS&E has involved analysis, but the future surely includes optimization and design, especially in the presence of uncertainty. Another mathematical frontier is the assimilation of very large data sets through such techniques as adaptive multi-resolution, automated feature search, and low-dimensional parameterization. The themes of the 2003 conference included, but were not limited to: Advanced Discretization Methods; Computational Biology and Bioinformatics; Computational Chemistry and Chemical Engineering; Computational Earth and Atmospheric Sciences; Computational Electromagnetics; Computational Fluid Dynamics; Computational Medicine and Bioengineering; Computational Physics and Astrophysics; Computational Solid Mechanics and Materials; CS

Principal component analysis networks and algorithms

CERN Document Server

Kong, Xiangyu; Duan, Zhansheng

2017-01-01

This book not only provides a comprehensive introduction to neural-based PCA methods in control science, but also presents many novel PCA algorithms and their extensions and generalizations, e.g., dual purpose, coupled PCA, GED, neural based SVD algorithms, etc. It also discusses in detail various analysis methods for the convergence, stabilizing, self-stabilizing property of algorithms, and introduces the deterministic discrete-time systems method to analyze the convergence of PCA/MCA algorithms. Readers should be familiar with numerical analysis and the fundamentals of statistics, such as the basics of least squares and stochastic algorithms. Although it focuses on neural networks, the book only presents their learning law, which is simply an iterative algorithm. Therefore, no a priori knowledge of neural networks is required. This book will be of interest and serve as a reference source to researchers and students in applied mathematics, statistics, engineering, and other related fields.

Implementation of a Program on Experiencing and Application of Research Reactor for University Students Majoring in Science and Technology

Energy Technology Data Exchange (ETDEWEB)

Seo, K. W.; Han, K. W.; Won, J. Y.; Ju, Y. C.; Ji, Y. J.; Oh, S. Y

2007-05-15

This report was written as following contents, to develop a program for university students majoring in science and technology, which is intended to provide the students with opportunities to obtain hands on experience and knowledge on various nuclear technology, through experiments using HANARO and its facilities. Thus obtain experience and knowledge are expected to be a great help for their current study and for their selection of a specific future study area. The purpose of this research is as follows: - development of various curricula for specific research using HANARO and continuous operation of the developed curricula to provided university students with opportunities to use HANARO as part of their university study. - continuous operation of research reactor experimental programs for university students in nuclear field to make contribution to cultivating specialists. - development and operation of training programs of experiments using research reactor for university students majoring in nuclear engineering and also for university students majoring in diverse fields of science and technology such as physics, advanced metallurgy, mechanical engineering, energy engineering, radiological science, nanoscience, etc. to cultivate future potential users of HANARO as well as broadening the user group. As a whole, 263 students from 15 universities have completed the courses of the programs developed and offered by this project. Also, 5 textbooks have been developed to support the programs.

Implementation of a Program on Experiencing and Application of Research Reactor for University Students Majoring in Science and Technology

International Nuclear Information System (INIS)

Seo, K. W.; Han, K. W.; Won, J. Y.; Ju, Y. C.; Ji, Y. J.; Oh, S. Y.

2007-05-01

This report was written as following contents, to develop a program for university students majoring in science and technology, which is intended to provide the students with opportunities to obtain hands on experience and knowledge on various nuclear technology, through experiments using HANARO and its facilities. Thus obtain experience and knowledge are expected to be a great help for their current study and for their selection of a specific future study area. The purpose of this research is as follows: - development of various curricula for specific research using HANARO and continuous operation of the developed curricula to provided university students with opportunities to use HANARO as part of their university study. - continuous operation of research reactor experimental programs for university students in nuclear field to make contribution to cultivating specialists. - development and operation of training programs of experiments using research reactor for university students majoring in nuclear engineering and also for university students majoring in diverse fields of science and technology such as physics, advanced metallurgy, mechanical engineering, energy engineering, radiological science, nanoscience, etc. to cultivate future potential users of HANARO as well as broadening the user group. As a whole, 263 students from 15 universities have completed the courses of the programs developed and offered by this project. Also, 5 textbooks have been developed to support the programs

A comparative study of traditional lecture methods and interactive lecture methods in introductory geology courses for non-science majors at the college level

Science.gov (United States)

Hundley, Stacey A.

In recent years there has been a national call for reform in undergraduate science education. The goal of this reform movement in science education is to develop ways to improve undergraduate student learning with an emphasis on developing more effective teaching practices. Introductory science courses at the college level are generally taught using a traditional lecture format. Recent studies have shown incorporating active learning strategies within the traditional lecture classroom has positive effects on student outcomes. This study focuses on incorporating interactive teaching methods into the traditional lecture classroom to enhance student learning for non-science majors enrolled in introductory geology courses at a private university. Students' experience and instructional preferences regarding introductory geology courses were identified from survey data analysis. The information gained from responses to the questionnaire was utilized to develop an interactive lecture introductory geology course for non-science majors. Student outcomes were examined in introductory geology courses based on two teaching methods: interactive lecture and traditional lecture. There were no significant statistical differences between the groups based on the student outcomes and teaching methods. Incorporating interactive lecture methods did not statistically improve student outcomes when compared to traditional lecture teaching methods. However, the responses to the survey revealed students have a preference for introductory geology courses taught with lecture and instructor-led discussions and students prefer to work independently or in small groups. The results of this study are useful to individuals who teach introductory geology courses and individuals who teach introductory science courses for non-science majors at the college level.

Using game theory for perceptual tuned rate control algorithm in video coding

Science.gov (United States)

Luo, Jiancong; Ahmad, Ishfaq

2005-03-01

This paper proposes a game theoretical rate control technique for video compression. Using a cooperative gaming approach, which has been utilized in several branches of natural and social sciences because of its enormous potential for solving constrained optimization problems, we propose a dual-level scheme to optimize the perceptual quality while guaranteeing "fairness" in bit allocation among macroblocks. At the frame level, the algorithm allocates target bits to frames based on their coding complexity. At the macroblock level, the algorithm distributes bits to macroblocks by defining a bargaining game. Macroblocks play cooperatively to compete for shares of resources (bits) to optimize their quantization scales while considering the Human Visual System"s perceptual property. Since the whole frame is an entity perceived by viewers, macroblocks compete cooperatively under a global objective of achieving the best quality with the given bit constraint. The major advantage of the proposed approach is that the cooperative game leads to an optimal and fair bit allocation strategy based on the Nash Bargaining Solution. Another advantage is that it allows multi-objective optimization with multiple decision makers (macroblocks). The simulation results testify the algorithm"s ability to achieve accurate bit rate with good perceptual quality, and to maintain a stable buffer level.

Gender equity in STEM: The role of dual enrollment science courses in selecting a college major

Science.gov (United States)

Persons, Christopher Andrew

A disproportionately low number of women, despite rigorous high school preparation and evidenced interest in STEM through voluntary participation in additional coursework, declare a STEM-related college major. The result of this drop in participation in STEM-related college majors is a job market flooded with men and the support of an incorrect stereotype: STEM is for men. This research seeks to assess the effects, if any, that Dual Enrollment (DE) science courses have on students' self-identified intent to declare a STEM-related college major as well as the respective perceptions of both male and female students. Self-Determination Theory and Gender Equity Framework were used respectively as the theoretical frames. High school students from six schools in two district participated in an online survey and focus groups in this mixed methods study. The results of the research identified the role the DE course played in their choice of college major, possible interventions to correct the underrepresentation, and societal causes for the stereotype.

Evaluation of Algorithms for Compressing Hyperspectral Data

Science.gov (United States)

Cook, Sid; Harsanyi, Joseph; Faber, Vance

2003-01-01

With EO-1 Hyperion in orbit NASA is showing their continued commitment to hyperspectral imaging (HSI). As HSI sensor technology continues to mature, the ever-increasing amounts of sensor data generated will result in a need for more cost effective communication and data handling systems. Lockheed Martin, with considerable experience in spacecraft design and developing special purpose onboard processors, has teamed with Applied Signal & Image Technology (ASIT), who has an extensive heritage in HSI spectral compression and Mapping Science (MSI) for JPEG 2000 spatial compression expertise, to develop a real-time and intelligent onboard processing (OBP) system to reduce HSI sensor downlink requirements. Our goal is to reduce the downlink requirement by a factor > 100, while retaining the necessary spectral and spatial fidelity of the sensor data needed to satisfy the many science, military, and intelligence goals of these systems. Our compression algorithms leverage commercial-off-the-shelf (COTS) spectral and spatial exploitation algorithms. We are currently in the process of evaluating these compression algorithms using statistical analysis and NASA scientists. We are also developing special purpose processors for executing these algorithms onboard a spacecraft.

Fault-tolerant search algorithms reliable computation with unreliable information

CERN Document Server

Cicalese, Ferdinando

2013-01-01

Why a book on fault-tolerant search algorithms? Searching is one of the fundamental problems in computer science. Time and again algorithmic and combinatorial issues originally studied in the context of search find application in the most diverse areas of computer science and discrete mathematics. On the other hand, fault-tolerance is a necessary ingredient of computing. Due to their inherent complexity, information systems are naturally prone to errors, which may appear at any level - as imprecisions in the data, bugs in the software, or transient or permanent hardware failures. This book pr

Journal of Earth System Science | Indian Academy of Sciences

Indian Academy of Sciences (India)

Home; Journals; Journal of Earth System Science. J C Joshi. Articles written in Journal of Earth System Science. Volume 126 Issue 1 February 2017 pp 3. Optimisation of Hidden Markov Model using Baum–Welch algorithm for prediction of maximum and minimum temperature over Indian Himalaya · J C Joshi Tankeshwar ...

Data structures and algorithm analysis in C++

CERN Document Server

Shaffer, Clifford A

2011-01-01

With its focus on creating efficient data structures and algorithms, this comprehensive text helps readers understand how to select or design the tools that will best solve specific problems. It uses Microsoft C++ as the programming language and is suitable for second-year data structure courses and computer science courses in algorithm analysis.Techniques for representing data are presented within the context of assessing costs and benefits, promoting an understanding of the principles of algorithm analysis and the effects of a chosen physical medium. The text also explores tradeoff issues, f

Data structures and algorithm analysis in Java

CERN Document Server

Shaffer, Clifford A

2011-01-01

With its focus on creating efficient data structures and algorithms, this comprehensive text helps readers understand how to select or design the tools that will best solve specific problems. It uses Java as the programming language and is suitable for second-year data structure courses and computer science courses in algorithm analysis. Techniques for representing data are presented within the context of assessing costs and benefits, promoting an understanding of the principles of algorithm analysis and the effects of a chosen physical medium. The text also explores tradeoff issues, familiari

ICASE Computer Science Program

Science.gov (United States)

1985-01-01

The Institute for Computer Applications in Science and Engineering computer science program is discussed in outline form. Information is given on such topics as problem decomposition, algorithm development, programming languages, and parallel architectures.

Effects of visualization on algorithm comprehension

Science.gov (United States)

Mulvey, Matthew

Computer science students are expected to learn and apply a variety of core algorithms which are an essential part of the field. Any one of these algorithms by itself is not necessarily extremely complex, but remembering the large variety of algorithms and the differences between them is challenging. To address this challenge, we present a novel algorithm visualization tool designed to enhance students understanding of Dijkstra's algorithm by allowing them to discover the rules of the algorithm for themselves. It is hoped that a deeper understanding of the algorithm will help students correctly select, adapt and apply the appropriate algorithm when presented with a problem to solve, and that what is learned here will be applicable to the design of other visualization tools designed to teach different algorithms. Our visualization tool is currently in the prototype stage, and this thesis will discuss the pedagogical approach that informs its design, as well as the results of some initial usability testing. Finally, to clarify the direction for further development of the tool, four different variations of the prototype were implemented, and the instructional effectiveness of each was assessed by having a small sample participants use the different versions of the prototype and then take a quiz to assess their comprehension of the algorithm.

Algorithms in invariant theory

CERN Document Server

Sturmfels, Bernd

2008-01-01

J. Kung and G.-C. Rota, in their 1984 paper, write: "Like the Arabian phoenix rising out of its ashes, the theory of invariants, pronounced dead at the turn of the century, is once again at the forefront of mathematics". The book of Sturmfels is both an easy-to-read textbook for invariant theory and a challenging research monograph that introduces a new approach to the algorithmic side of invariant theory. The Groebner bases method is the main tool by which the central problems in invariant theory become amenable to algorithmic solutions. Students will find the book an easy introduction to this "classical and new" area of mathematics. Researchers in mathematics, symbolic computation, and computer science will get access to a wealth of research ideas, hints for applications, outlines and details of algorithms, worked out examples, and research problems.

Genetic algorithms and genetic programming for multiscale modeling: Applications in materials science and chemistry and advances in scalability

Science.gov (United States)

Sastry, Kumara Narasimha

2007-03-01

Effective and efficient rnultiscale modeling is essential to advance both the science and synthesis in a, wide array of fields such as physics, chemistry, materials science; biology, biotechnology and pharmacology. This study investigates the efficacy and potential of rising genetic algorithms for rnultiscale materials modeling and addresses some of the challenges involved in designing competent algorithms that solve hard problems quickly, reliably and accurately. In particular, this thesis demonstrates the use of genetic algorithms (GAs) and genetic programming (GP) in multiscale modeling with the help of two non-trivial case studies in materials science and chemistry. The first case study explores the utility of genetic programming (GP) in multi-timescaling alloy kinetics simulations. In essence, GP is used to bridge molecular dynamics and kinetic Monte Carlo methods to span orders-of-magnitude in simulation time. Specifically, GP is used to regress symbolically an inline barrier function from a limited set of molecular dynamics simulations to enable kinetic Monte Carlo that simulate seconds of real time. Results on a non-trivial example of vacancy-assisted migration on a surface of a face-centered cubic (fcc) Copper-Cobalt (CuxCo 1-x) alloy show that GP predicts all barriers with 0.1% error from calculations for less than 3% of active configurations, independent of type of potentials used to obtain the learning set of barriers via molecular dynamics. The resulting method enables 2--9 orders-of-magnitude increase in real-time dynamics simulations taking 4--7 orders-of-magnitude less CPU time. The second case study presents the application of multiobjective genetic algorithms (MOGAs) in multiscaling quantum chemistry simulations. Specifically, MOGAs are used to bridge high-level quantum chemistry and semiempirical methods to provide accurate representation of complex molecular excited-state and ground-state behavior. Results on ethylene and benzene---two common

The Employment Outlook for Social Science Majors in the South.

Science.gov (United States)

Galambos, Eva C.

This assessment of the future job market for social science graduates is made both generically and separately for certain disciplines. The definition of the social sciences follows the USOE definition and includes: anthropology, archeology, economics, history, geography, political science, sociology, criminology, international relations, urban…

Algorithmic psychometrics and the scalable subject.

Science.gov (United States)

Stark, Luke

2018-04-01

Recent public controversies, ranging from the 2014 Facebook 'emotional contagion' study to psychographic data profiling by Cambridge Analytica in the 2016 American presidential election, Brexit referendum and elsewhere, signal watershed moments in which the intersecting trajectories of psychology and computer science have become matters of public concern. The entangled history of these two fields grounds the application of applied psychological techniques to digital technologies, and an investment in applying calculability to human subjectivity. Today, a quantifiable psychological subject position has been translated, via 'big data' sets and algorithmic analysis, into a model subject amenable to classification through digital media platforms. I term this position the 'scalable subject', arguing it has been shaped and made legible by algorithmic psychometrics - a broad set of affordances in digital platforms shaped by psychology and the behavioral sciences. In describing the contours of this 'scalable subject', this paper highlights the urgent need for renewed attention from STS scholars on the psy sciences, and on a computational politics attentive to psychology, emotional expression, and sociality via digital media.

Does Personality Matter? Applying Holland's Typology to Analyze Students' Self-Selection into Science, Technology, Engineering, and Mathematics Majors

Science.gov (United States)

Chen, P. Daniel; Simpson, Patricia A.

2015-01-01

This study utilized John Holland's personality typology and the Social Cognitive Career Theory (SCCT) to examine the factors that may affect students' self-selection into science, technology, engineering, and mathematics (STEM) majors. Results indicated that gender, race/ethnicity, high school achievement, and personality type were statistically…

COMPUTATIONAL SCIENCE CENTER

Energy Technology Data Exchange (ETDEWEB)

DAVENPORT, J.

2006-11-01

Computational Science is an integral component of Brookhaven's multi science mission, and is a reflection of the increased role of computation across all of science. Brookhaven currently has major efforts in data storage and analysis for the Relativistic Heavy Ion Collider (RHIC) and the ATLAS detector at CERN, and in quantum chromodynamics. The Laboratory is host for the QCDOC machines (quantum chromodynamics on a chip), 10 teraflop/s computers which boast 12,288 processors each. There are two here, one for the Riken/BNL Research Center and the other supported by DOE for the US Lattice Gauge Community and other scientific users. A 100 teraflop/s supercomputer will be installed at Brookhaven in the coming year, managed jointly by Brookhaven and Stony Brook, and funded by a grant from New York State. This machine will be used for computational science across Brookhaven's entire research program, and also by researchers at Stony Brook and across New York State. With Stony Brook, Brookhaven has formed the New York Center for Computational Science (NYCCS) as a focal point for interdisciplinary computational science, which is closely linked to Brookhaven's Computational Science Center (CSC). The CSC has established a strong program in computational science, with an emphasis on nanoscale electronic structure and molecular dynamics, accelerator design, computational fluid dynamics, medical imaging, parallel computing and numerical algorithms. We have been an active participant in DOES SciDAC program (Scientific Discovery through Advanced Computing). We are also planning a major expansion in computational biology in keeping with Laboratory initiatives. Additional laboratory initiatives with a dependence on a high level of computation include the development of hydrodynamics models for the interpretation of RHIC data, computational models for the atmospheric transport of aerosols, and models for combustion and for energy utilization. The CSC was formed to

Document Organization Using Kohonen's Algorithm.

Science.gov (United States)

Guerrero Bote, Vicente P.; Moya Anegon, Felix de; Herrero Solana, Victor

2002-01-01

Discussion of the classification of documents from bibliographic databases focuses on a method of vectorizing reference documents from LISA (Library and Information Science Abstracts) which permits their topological organization using Kohonen's algorithm. Analyzes possibilities of this type of neural network with respect to the development of…

An Implementation of RC4+ Algorithm and Zig-zag Algorithm in a Super Encryption Scheme for Text Security

Science.gov (United States)

Budiman, M. A.; Amalia; Chayanie, N. I.

2018-03-01

Cryptography is the art and science of using mathematical methods to preserve message security. There are two types of cryptography, namely classical and modern cryptography. Nowadays, most people would rather use modern cryptography than classical cryptography because it is harder to break than the classical one. One of classical algorithm is the Zig-zag algorithm that uses the transposition technique: the original message is unreadable unless the person has the key to decrypt the message. To improve the security, the Zig-zag Cipher is combined with RC4+ Cipher which is one of the symmetric key algorithms in the form of stream cipher. The two algorithms are combined to make a super-encryption. By combining these two algorithms, the message will be harder to break by a cryptanalyst. The result showed that complexity of the combined algorithm is θ(n2 ), while the complexity of Zig-zag Cipher and RC4+ Cipher are θ(n2 ) and θ(n), respectively.

An Affinity Propagation Clustering Algorithm for Mixed Numeric and Categorical Datasets

Directory of Open Access Journals (Sweden)

Kang Zhang

2014-01-01

Full Text Available Clustering has been widely used in different fields of science, technology, social science, and so forth. In real world, numeric as well as categorical features are usually used to describe the data objects. Accordingly, many clustering methods can process datasets that are either numeric or categorical. Recently, algorithms that can handle the mixed data clustering problems have been developed. Affinity propagation (AP algorithm is an exemplar-based clustering method which has demonstrated good performance on a wide variety of datasets. However, it has limitations on processing mixed datasets. In this paper, we propose a novel similarity measure for mixed type datasets and an adaptive AP clustering algorithm is proposed to cluster the mixed datasets. Several real world datasets are studied to evaluate the performance of the proposed algorithm. Comparisons with other clustering algorithms demonstrate that the proposed method works well not only on mixed datasets but also on pure numeric and categorical datasets.

Outcome of a 4-step treatment algorithm for depressed inpatients

NARCIS (Netherlands)

Birkenhäger, T.K.; Broek, W.W. van den; Moleman, P.; Bruijn, J.A.

2006-01-01

Objective: The aim of this study was to examine the efficacy and the feasibility of a 4-step treatment algorithm for inpatients with major depressive disorder. Method: Depressed inpatients, meeting DSM-IV criteria for major depressive disorder, were enrolled in the algorithm that consisted of

Marshall Rosenbluth and the Metropolis algorithm

International Nuclear Information System (INIS)

Gubernatis, J.E.

2005-01-01

The 1953 publication, 'Equation of State Calculations by Very Fast Computing Machines' by N. Metropolis, A. W. Rosenbluth and M. N. Rosenbluth, and M. Teller and E. Teller [J. Chem. Phys. 21, 1087 (1953)] marked the beginning of the use of the Monte Carlo method for solving problems in the physical sciences. The method described in this publication subsequently became known as the Metropolis algorithm, undoubtedly the most famous and most widely used Monte Carlo algorithm ever published. As none of the authors made subsequent use of the algorithm, they became unknown to the large simulation physics community that grew from this publication and their roles in its development became the subject of mystery and legend. At a conference marking the 50th anniversary of the 1953 publication, Marshall Rosenbluth gave his recollections of the algorithm's development. The present paper describes the algorithm, reconstructs the historical context in which it was developed, and summarizes Marshall's recollections

Applying Clustering Methods in Drawing Maps of Science: Case Study of the Map For Urban Management Science

Directory of Open Access Journals (Sweden)

Mohammad Abuei Ardakan

2010-04-01

Full Text Available The present paper offers a basic introduction to data clustering and demonstrates the application of clustering methods in drawing maps of science. All approaches towards classification and clustering of information are briefly discussed. Their application to the process of visualization of conceptual information and drawing of science maps are illustrated by reviewing similar researches in this field. By implementing aggregated hierarchical clustering algorithm, which is an algorithm based on complete-link method, the map for urban management science as an emerging, interdisciplinary scientific field is analyzed and reviewed.

Science and technology planning in LDCs: major policy issues

Energy Technology Data Exchange (ETDEWEB)

Wionczek, M S

1979-05-01

Science in the less-developed countries (LDCs) should be underplanned rather than overplanned. Furthermore, the planning should be directed to the outer fringes of the scientific endeavor and to its infrastructure and not to the substance of scientific research itself. Planning of applied research and technological development in the LDC is another story. It cannot be done without entering into the substantive problems of applied research and technological development. Attempts to set the broad overall national targets for science and technology (S and T) expenditures -in terms of the proportion of the (GNP) or the per capita income- which do not consider the science and technology system's financial and human resources absorption capacity, are useless. 8 references.

An Innovative Thinking-Based Intelligent Information Fusion Algorithm

Directory of Open Access Journals (Sweden)

Huimin Lu

2013-01-01

Full Text Available This study proposes an intelligent algorithm that can realize information fusion in reference to the relative research achievements in brain cognitive theory and innovative computation. This algorithm treats knowledge as core and information fusion as a knowledge-based innovative thinking process. Furthermore, the five key parts of this algorithm including information sense and perception, memory storage, divergent thinking, convergent thinking, and evaluation system are simulated and modeled. This algorithm fully develops innovative thinking skills of knowledge in information fusion and is a try to converse the abstract conception of brain cognitive science to specific and operable research routes and strategies. Furthermore, the influences of each parameter of this algorithm on algorithm performance are analyzed and compared with those of classical intelligent algorithms trough test. Test results suggest that the algorithm proposed in this study can obtain the optimum problem solution by less target evaluation times, improve optimization effectiveness, and achieve the effective fusion of information.

Cuckoo search and firefly algorithm theory and applications

CERN Document Server

2014-01-01

Nature-inspired algorithms such as cuckoo search and firefly algorithm have become popular and widely used in recent years in many applications. These algorithms are flexible, efficient and easy to implement. New progress has been made in the last few years, and it is timely to summarize the latest developments of cuckoo search and firefly algorithm and their diverse applications. This book will review both theoretical studies and applications with detailed algorithm analysis, implementation and case studies so that readers can benefit most from this book.  Application topics are contributed by many leading experts in the field. Topics include cuckoo search, firefly algorithm, algorithm analysis, feature selection, image processing, travelling salesman problem, neural network, GPU optimization, scheduling, queuing, multi-objective manufacturing optimization, semantic web service, shape optimization, and others.   This book can serve as an ideal reference for both graduates and researchers in computer scienc...

A neural algorithm for a fundamental computing problem.

Science.gov (United States)

Dasgupta, Sanjoy; Stevens, Charles F; Navlakha, Saket

2017-11-10

Similarity search-for example, identifying similar images in a database or similar documents on the web-is a fundamental computing problem faced by large-scale information retrieval systems. We discovered that the fruit fly olfactory circuit solves this problem with a variant of a computer science algorithm (called locality-sensitive hashing). The fly circuit assigns similar neural activity patterns to similar odors, so that behaviors learned from one odor can be applied when a similar odor is experienced. The fly algorithm, however, uses three computational strategies that depart from traditional approaches. These strategies can be translated to improve the performance of computational similarity searches. This perspective helps illuminate the logic supporting an important sensory function and provides a conceptually new algorithm for solving a fundamental computational problem. Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Once upon an algorithm how stories explain computing

CERN Document Server

Erwig, Martin

2017-01-01

How Hansel and Gretel, Sherlock Holmes, the movie Groundhog Day, Harry Potter, and other familiar stories illustrate the concepts of computing. Picture a computer scientist, staring at a screen and clicking away frantically on a keyboard, hacking into a system, or perhaps developing an app. Now delete that picture. In Once Upon an Algorithm, Martin Erwig explains computation as something that takes place beyond electronic computers, and computer science as the study of systematic problem solving. Erwig points out that many daily activities involve problem solving. Getting up in the morning, for example: You get up, take a shower, get dressed, eat breakfast. This simple daily routine solves a recurring problem through a series of well-defined steps. In computer science, such a routine is called an algorithm. Erwig illustrates a series of concepts in computing with examples from daily life and familiar stories. Hansel and Gretel, for example, execute an algorithm to get home from the forest. The movie Groundho...

Advanced algorithms for information science

International Nuclear Information System (INIS)

Argo, P.; Brislawn, C.; Fitzgerald, T.J.; Kelley, B.; Kim, W.H.; Mazieres, B.; Roeder, H.; Strottman, D.

1998-01-01

This is the final report of a one-year, Laboratory Directed Research and Development (LDRD) project at Los Alamos National Laboratory (LANL). In a modern information-controlled society the importance of fast computational algorithms facilitating data compression and image analysis cannot be overemphasized. Feature extraction and pattern recognition are key to many LANL projects and the same types of dimensionality reduction and compression used in source coding are also applicable to image understanding. The authors have begun developing wavelet coding which decomposes data into different length-scale and frequency bands. New transform-based source-coding techniques offer potential for achieving better, combined source-channel coding performance by using joint-optimization techniques. They initiated work on a system that compresses the video stream in real time, and which also takes the additional step of analyzing the video stream concurrently. By using object-based compression schemes (where an object is an identifiable feature of the video signal, repeatable in time or space), they believe that the analysis is directly related to the efficiency of the compression

Advanced algorithms for information science

Energy Technology Data Exchange (ETDEWEB)

Argo, P.; Brislawn, C.; Fitzgerald, T.J.; Kelley, B.; Kim, W.H.; Mazieres, B.; Roeder, H.; Strottman, D.

1998-12-31

This is the final report of a one-year, Laboratory Directed Research and Development (LDRD) project at Los Alamos National Laboratory (LANL). In a modern information-controlled society the importance of fast computational algorithms facilitating data compression and image analysis cannot be overemphasized. Feature extraction and pattern recognition are key to many LANL projects and the same types of dimensionality reduction and compression used in source coding are also applicable to image understanding. The authors have begun developing wavelet coding which decomposes data into different length-scale and frequency bands. New transform-based source-coding techniques offer potential for achieving better, combined source-channel coding performance by using joint-optimization techniques. They initiated work on a system that compresses the video stream in real time, and which also takes the additional step of analyzing the video stream concurrently. By using object-based compression schemes (where an object is an identifiable feature of the video signal, repeatable in time or space), they believe that the analysis is directly related to the efficiency of the compression.

CATEGORIES OF COMPUTER SYSTEMS ALGORITHMS

Directory of Open Access Journals (Sweden)

A. V. Poltavskiy

2015-01-01

Full Text Available Philosophy as a frame of reference on world around and as the first science is a fundamental basis, "roots" (R. Descartes for all branches of the scientific knowledge accumulated and applied in all fields of activity of a human being person. The theory of algorithms as one of the fundamental sections of mathematics, is also based on researches of the gnoseology conducting cognition of a true picture of the world of the buman being. From gnoseology and ontology positions as fundamental sections of philosophy modern innovative projects are inconceivable without development of programs,and algorithms.

Verification of ICESat-2/ATLAS Science Receiver Algorithm Onboard Databases

Science.gov (United States)

Carabajal, C. C.; Saba, J. L.; Leigh, H. W.; Magruder, L. A.; Urban, T. J.; Mcgarry, J.; Schutz, B. E.

2013-12-01

NASA's ICESat-2 mission will fly the Advanced Topographic Laser Altimetry System (ATLAS) instrument on a 3-year mission scheduled to launch in 2016. ATLAS is a single-photon detection system transmitting at 532nm with a laser repetition rate of 10 kHz, and a 6 spot pattern on the Earth's surface. A set of onboard Receiver Algorithms will perform signal processing to reduce the data rate and data volume to acceptable levels. These Algorithms distinguish surface echoes from the background noise, limit the daily data volume, and allow the instrument to telemeter only a small vertical region about the signal. For this purpose, three onboard databases are used: a Surface Reference Map (SRM), a Digital Elevation Model (DEM), and a Digital Relief Maps (DRMs). The DEM provides minimum and maximum heights that limit the signal search region of the onboard algorithms, including a margin for errors in the source databases, and onboard geolocation. Since the surface echoes will be correlated while noise will be randomly distributed, the signal location is found by histogramming the received event times and identifying the histogram bins with statistically significant counts. Once the signal location has been established, the onboard Digital Relief Maps (DRMs) will be used to determine the vertical width of the telemetry band about the signal. University of Texas-Center for Space Research (UT-CSR) is developing the ICESat-2 onboard databases, which are currently being tested using preliminary versions and equivalent representations of elevation ranges and relief more recently developed at Goddard Space Flight Center (GSFC). Global and regional elevation models have been assessed in terms of their accuracy using ICESat geodetic control, and have been used to develop equivalent representations of the onboard databases for testing against the UT-CSR databases, with special emphasis on the ice sheet regions. A series of verification checks have been implemented, including

Comparison of tracking algorithms implemented in OpenCV

Directory of Open Access Journals (Sweden)

Janku Peter

2016-01-01

Full Text Available Computer vision is very progressive and modern part of computer science. From scientific point of view, theoretical aspects of computer vision algorithms prevail in many papers and publications. The underlying theory is really important, but on the other hand, the final implementation of an algorithm significantly affects its performance and robustness. For this reason, this paper tries to compare real implementation of tracking algorithms (one part of computer vision problem, which can be found in the very popular library OpenCV. Moreover, the possibilities of optimizations are discussed.

The Quantitative Analysis of User Behavior Online - Data, Models and Algorithms

Science.gov (United States)

Raghavan, Prabhakar

By blending principles from mechanism design, algorithms, machine learning and massive distributed computing, the search industry has become good at optimizing monetization on sound scientific principles. This represents a successful and growing partnership between computer science and microeconomics. When it comes to understanding how online users respond to the content and experiences presented to them, we have more of a lacuna in the collaboration between computer science and certain social sciences. We will use a concrete technical example from image search results presentation, developing in the process some algorithmic and machine learning problems of interest in their own right. We then use this example to motivate the kinds of studies that need to grow between computer science and the social sciences; a critical element of this is the need to blend large-scale data analysis with smaller-scale eye-tracking and "individualized" lab studies.

Data streams: algorithms and applications

National Research Council Canada - National Science Library

Muthukrishnan, S

2005-01-01

... massive data sets in general. Researchers in Theoretical Computer Science, Databases, IP Networking and Computer Systems are working on the data stream challenges. This article is an overview and survey of data stream algorithmics and is an updated version of [175]. S. Muthukrishnan Rutgers University, New Brunswick, NJ, USA, muthu@cs...

Computer sciences

Science.gov (United States)

Smith, Paul H.

1988-01-01

The Computer Science Program provides advanced concepts, techniques, system architectures, algorithms, and software for both space and aeronautics information sciences and computer systems. The overall goal is to provide the technical foundation within NASA for the advancement of computing technology in aerospace applications. The research program is improving the state of knowledge of fundamental aerospace computing principles and advancing computing technology in space applications such as software engineering and information extraction from data collected by scientific instruments in space. The program includes the development of special algorithms and techniques to exploit the computing power provided by high performance parallel processors and special purpose architectures. Research is being conducted in the fundamentals of data base logic and improvement techniques for producing reliable computing systems.

Fellowship | Indian Academy of Sciences

Indian Academy of Sciences (India)

Fellow Profile. Elected: 2014 Section: Engineering & Technology. Garg, Prof. Naveen Ph.D. (IIT, Delhi). Date of birth: 12 March 1971. Specialization: Approximation Algorithms, Combinatorial Optimisation, Graph Theory & Algorithms Address: Department of Computer Science & Engineering, Indian Institute of Technology, ...

Resonance – Journal of Science Education | Indian Academy of ...

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education; Volume 1; Issue 1. Algorithms Introduction to Algorithms. R K Shyamasundar. Series Article Volume 1 ... Author Affiliations. R K Shyamasundar1. Computer Science Group, Tata Institute of Fundamental Research, Homi Bhabha Road, Bombay 400 005, India.

Age at Menarche and Choice of College Major: Implications for STEM Majors

Science.gov (United States)

Brenner-Shuman, Anna; Waren, Warren

2013-01-01

Even though boys and girls in childhood perform similarly in math and spatial thinking, after puberty fewer young women pursue majors that emphasize abilities such as science, technology, engineering, and math (STEM) in college. If postpubertal feminization contributes to a lower likelihood of choosing STEM majors, then young women who enter…

A Major in Science? Initial Beliefs and Final Outcomes for College Major and Dropout

OpenAIRE

Ralph Stinebrickner; Todd R. Stinebrickner

2014-01-01

Taking advantage of unique longitudinal data, we provide the first characterization of what college students believe at the time of entrance about their final major, relate these beliefs to actual major outcomes, and provide an understanding of why students hold the initial beliefs about majors that they do. The data collection and analysis are based directly on a conceptual model in which a student's final major is best viewed as the end result of a learning process. We find that students en...

The Conceptions of Learning Science by Laboratory among University Science-Major Students: Qualitative and Quantitative Analyses

Science.gov (United States)

Chiu, Yu-Li; Lin, Tzung-Jin; Tsai, Chin-Chung

2016-01-01

Background: The sophistication of students' conceptions of science learning has been found to be positively related to their approaches to and outcomes for science learning. Little research has been conducted to particularly investigate students' conceptions of science learning by laboratory. Purpose: The purpose of this research, consisting of…

Gems of combinatorial optimization and graph algorithms

CERN Document Server

Skutella, Martin; Stiller, Sebastian; Wagner, Dorothea

2015-01-01

Are you looking for new lectures for your course on algorithms, combinatorial optimization, or algorithmic game theory?  Maybe you need a convenient source of relevant, current topics for a graduate student or advanced undergraduate student seminar?  Or perhaps you just want an enjoyable look at some beautiful mathematical and algorithmic results, ideas, proofs, concepts, and techniques in discrete mathematics and theoretical computer science?   Gems of Combinatorial Optimization and Graph Algorithms is a handpicked collection of up-to-date articles, carefully prepared by a select group of international experts, who have contributed some of their most mathematically or algorithmically elegant ideas.  Topics include longest tours and Steiner trees in geometric spaces, cartograms, resource buying games, congestion games, selfish routing, revenue equivalence and shortest paths, scheduling, linear structures in graphs, contraction hierarchies, budgeted matching problems, and motifs in networks.   This ...

Improved algorithm for quantum separability and entanglement detection

International Nuclear Information System (INIS)

Ioannou, L.M.; Ekert, A.K.; Travaglione, B.C.; Cheung, D.

2004-01-01

Determining whether a quantum state is separable or entangled is a problem of fundamental importance in quantum information science. It has recently been shown that this problem is NP-hard, suggesting that an efficient, general solution does not exist. There is a highly inefficient 'basic algorithm' for solving the quantum separability problem which follows from the definition of a separable state. By exploiting specific properties of the set of separable states, we introduce a classical algorithm that solves the problem significantly faster than the 'basic algorithm', allowing a feasible separability test where none previously existed, e.g., in 3x3-dimensional systems. Our algorithm also provides a unique tool in the experimental detection of entanglement

Understanding molecular simulation: from algorithms to applications

NARCIS (Netherlands)

Frenkel, D.; Smit, B.

2002-01-01

Second and revised edition Understanding Molecular Simulation: From Algorithms to Applications explains the physics behind the "recipes" of molecular simulation for materials science. Computer simulators are continuously confronted with questions concerning the choice of a particular technique

CryoSat-2 science algorithm status, expected future improvements and impacts concerning Sentinel-3 and Jason-CS missions

Science.gov (United States)

Cullen, R.; Wingham, D.; Francis, R.; Parrinello, T.

2011-12-01

With CryoSat-2 soon to enter its second year of post commissioning operations there is now sufficient experience and evidence showing improvements of the SIRAL's (Synthetic interferometric radar altimeter) SAR and SARIn modes over conventional pulse-width limited altimeters for both the targeted marine/land ice fields but also for non mission relevant surfaces such as the ocean, for example. In the process of understanding the CryoSat data some side effects of the end-to-end platform measurement and ground retrieval system have been identified and whilst those key to mission success are understood and are being handled others, remain open and pave the way to longer term fine-tuning. Of interest to the session will be a summary of the manditory changes made during 2011 to all the modes of CryoSat-2 science processing with a view to longer term algorithm improvements that could benefit the planned mid-to-late nominal operations re-processing. Since some of the science processor improvements have direct implication to the SAR mode processing of Sentinel-3 and Jason-CS science then these will also be highlighted. Finally a summary of the CryoSat-2 in-orbit platform and payload performances and their stability will also be provided. Expectations of the longer term uses of CryoSat's primary sensor (SIRAL) and its successors will be discussed.

The experiences of female high school students and interest in STEM: Factors leading to the selection of an engineering or computer science major

Science.gov (United States)

Genoways, Sharon K.

STEM (Science, Technology, Engineering and Math) education creates critical thinkers, increases science literacy, and enables the next generation of innovators, which leads to new products and processes that sustain our economy (Hossain & Robinson, 2012). We have been hearing the warnings for several years, that there simply are not enough young scientists entering into the STEM professional pathways to replace all of the retiring professionals (Brown, Brown, Reardon, & Merrill, 2011; Harsh, Maltese, & Tai, 2012; Heilbronner, 2011; Scott, 2012). The problem is not necessarily due to a lack of STEM skills and concept proficiency. There also appears to be a lack of interest in these fields. Recent evidence suggests that many of the most proficient students, especially minority students and women, have been gravitating away from science and engineering toward other professions. (President's Council of Advisors on Science and Technology, 2010). The purpose of this qualitative research study was an attempt to determine how high schools can best prepare and encourage young women for a career in engineering or computer science. This was accomplished by interviewing a pool of 21 women, 5 recent high school graduates planning to major in STEM, 5 college students who had completed at least one full year of coursework in an engineering or computer science major and 11 professional women who had been employed as an engineer or computer scientist for at least one full year. These women were asked to share the high school courses, activities, and experiences that best prepared them to pursue an engineering or computer science major. Five central themes emerged from this study; coursework in physics and calculus, promotion of STEM camps and clubs, teacher encouragement of STEM capabilities and careers, problem solving, critical thinking and confidence building activities in the classroom, and allowing students the opportunity to fail and ask questions in a safe environment. These

[Algorithms of artificial neural networks--practical application in medical science].

Science.gov (United States)

Stefaniak, Bogusław; Cholewiński, Witold; Tarkowska, Anna

2005-12-01

Artificial Neural Networks (ANN) may be a tool alternative and complementary to typical statistical analysis. However, in spite of many computer applications of various ANN algorithms ready for use, artificial intelligence is relatively rarely applied to data processing. This paper presents practical aspects of scientific application of ANN in medicine using widely available algorithms. Several main steps of analysis with ANN were discussed starting from material selection and dividing it into groups, to the quality assessment of obtained results at the end. The most frequent, typical reasons for errors as well as the comparison of ANN method to the modeling by regression analysis were also described.

Engineering of Algorithms for Hidden Markov models and Tree Distances

DEFF Research Database (Denmark)

Sand, Andreas

Bioinformatics is an interdisciplinary scientific field that combines biology with mathematics, statistics and computer science in an effort to develop computational methods for handling, analyzing and learning from biological data. In the recent decades, the amount of available biological data has...... speed up all the classical algorithms for analyses and training of hidden Markov models. And I show how two particularly important algorithms, the forward algorithm and the Viterbi algorithm, can be accelerated through a reformulation of the algorithms and a somewhat more complicated parallelization...... contribution to the theoretically fastest set of algorithms presently available to compute two closely related measures of tree distance, the triplet distance and the quartet distance. And I further demonstrate that they are also the fastest algorithms in almost all cases when tested in practice....

The Applications of Genetic Algorithms in Medicine

Directory of Open Access Journals (Sweden)

Ali Ghaheri

2015-11-01

Full Text Available A great wealth of information is hidden amid medical research data that in some cases cannot be easily analyzed, if at all, using classical statistical methods. Inspired by nature, metaheuristic algorithms have been developed to offer optimal or near-optimal solutions to complex data analysis and decision-making tasks in a reasonable time. Due to their powerful features, metaheuristic algorithms have frequently been used in other fields of sciences. In medicine, however, the use of these algorithms are not known by physicians who may well benefit by applying them to solve complex medical problems. Therefore, in this paper, we introduce the genetic algorithm and its applications in medicine. The use of the genetic algorithm has promising implications in various medical specialties including radiology, radiotherapy, oncology, pediatrics, cardiology, endocrinology, surgery, obstetrics and gynecology, pulmonology, infectious diseases, orthopedics, rehabilitation medicine, neurology, pharmacotherapy, and health care management. This review introduces the applications of the genetic algorithm in disease screening, diagnosis, treatment planning, pharmacovigilance, prognosis, and health care management, and enables physicians to envision possible applications of this metaheuristic method in their medical career.

The Applications of Genetic Algorithms in Medicine.

Science.gov (United States)

Ghaheri, Ali; Shoar, Saeed; Naderan, Mohammad; Hoseini, Sayed Shahabuddin

2015-11-01

A great wealth of information is hidden amid medical research data that in some cases cannot be easily analyzed, if at all, using classical statistical methods. Inspired by nature, metaheuristic algorithms have been developed to offer optimal or near-optimal solutions to complex data analysis and decision-making tasks in a reasonable time. Due to their powerful features, metaheuristic algorithms have frequently been used in other fields of sciences. In medicine, however, the use of these algorithms are not known by physicians who may well benefit by applying them to solve complex medical problems. Therefore, in this paper, we introduce the genetic algorithm and its applications in medicine. The use of the genetic algorithm has promising implications in various medical specialties including radiology, radiotherapy, oncology, pediatrics, cardiology, endocrinology, surgery, obstetrics and gynecology, pulmonology, infectious diseases, orthopedics, rehabilitation medicine, neurology, pharmacotherapy, and health care management. This review introduces the applications of the genetic algorithm in disease screening, diagnosis, treatment planning, pharmacovigilance, prognosis, and health care management, and enables physicians to envision possible applications of this metaheuristic method in their medical career.].

Environmentally induced nonstationarity in LIGO science run data

International Nuclear Information System (INIS)

Stone, Robert; Mukherjee, Soma

2009-01-01

NoiseFloorMon is a data monitoring tool (DMT) implemented at the LIGO sites to monitor instances of non-stationarity in the gravitational-wave data that are correlated with physical environmental monitors. An analysis of the fifth science run is nearly complete, and test runs preceding the sixth science run have also been analyzed. These analyses have identified time intervals in the gravitational-wave channel that indicate non-stationarity due to seismic activity, and these intervals are referred to as data quality flags. In the analyses conducted to date the majority of time segments identified as non-stationary were due to seismic activity at the corner station and the x-arm end station. We present the algorithm and its performance, and discuss the potential for an on-site pipeline that automatically generates data quality flags for use in future data runs.

An Investigation of Task and Ego Oriented Goals of the Students Majoring at the Faculty of Sport Sciences

Science.gov (United States)

Belli, Emre

2015-01-01

The aim of this study is to explore the task and ego oriented goals of the students majoring at the Faculty of Sports Sciences at Ataturk University. For data collection, "The Task and Ego Orientation in Sport Questionnaire", which was developed by Duda (1) and adapted into Turkish by Toros and Yetim (2), was used in the current study to…

Comparison Of Hybrid Sorting Algorithms Implemented On Different Parallel Hardware Platforms

Directory of Open Access Journals (Sweden)

Dominik Zurek

2013-01-01

Full Text Available Sorting is a common problem in computer science. There are lot of well-known sorting algorithms created for sequential execution on a single processor. Recently, hardware platforms enable to create wide parallel algorithms. We have standard processors consist of multiple cores and hardware accelerators like GPU. The graphic cards with their parallel architecture give new possibility to speed up many algorithms. In this paper we describe results of implementation of a few different sorting algorithms on GPU cards and multicore processors. Then hybrid algorithm will be presented which consists of parts executed on both platforms, standard CPU and GPU.

Rational use of cognitive resources: levels of analysis between the computational and the algorithmic.

Science.gov (United States)

Griffiths, Thomas L; Lieder, Falk; Goodman, Noah D

2015-04-01

Marr's levels of analysis-computational, algorithmic, and implementation-have served cognitive science well over the last 30 years. But the recent increase in the popularity of the computational level raises a new challenge: How do we begin to relate models at different levels of analysis? We propose that it is possible to define levels of analysis that lie between the computational and the algorithmic, providing a way to build a bridge between computational- and algorithmic-level models. The key idea is to push the notion of rationality, often used in defining computational-level models, deeper toward the algorithmic level. We offer a simple recipe for reverse-engineering the mind's cognitive strategies by deriving optimal algorithms for a series of increasingly more realistic abstract computational architectures, which we call "resource-rational analysis." Copyright © 2015 Cognitive Science Society, Inc.

STEM for Non-STEM Majors: Enhancing Science Literacy in Large Classes

Science.gov (United States)

Jin, Guang; Bierma, Tom

2013-01-01

This study evaluated a strategy using "clickers," POGIL (process oriented guided inquiry learning), and a focused science literacy orientation in an applied science course for non-STEM undergraduates taught in large classes. The effectiveness of these interventions in improving the science literacy of students was evaluated using a…

Genetic algorithms and fuzzy multiobjective optimization

CERN Document Server

Sakawa, Masatoshi

2002-01-01

Since the introduction of genetic algorithms in the 1970s, an enormous number of articles together with several significant monographs and books have been published on this methodology. As a result, genetic algorithms have made a major contribution to optimization, adaptation, and learning in a wide variety of unexpected fields. Over the years, many excellent books in genetic algorithm optimization have been published; however, they focus mainly on single-objective discrete or other hard optimization problems under certainty. There appears to be no book that is designed to present genetic algorithms for solving not only single-objective but also fuzzy and multiobjective optimization problems in a unified way. Genetic Algorithms And Fuzzy Multiobjective Optimization introduces the latest advances in the field of genetic algorithm optimization for 0-1 programming, integer programming, nonconvex programming, and job-shop scheduling problems under multiobjectiveness and fuzziness. In addition, the book treats a w...

Assessment of Teaching Methods and Critical Thinking in a Course for Science Majors

Science.gov (United States)

Speck, Angela; Ruzhitskaya, L.; Whittington, A. G.

2014-01-01

Ability to think critically is a key ingredient to the scientific mindset. Students who take science courses may or may not be predisposed to critical thinking - the ability to evaluate information analytically. Regardless of their initial stages, students can significantly improve their critical thinking through learning and practicing their reasoning skills, critical assessments, conducting and reflecting on observations and experiments, building their questioning and communication skills, and through the use of other techniques. While, there are several of teaching methods that may help to improve critical thinking, there are only a few assessment instruments that can help in evaluating the efficacy of these methods. Critical thinking skills and improvement in those skills are notoriously difficult to measure. Assessments that are based on multiple-choice questions demonstrate students’ final decisions but not their thinking processes. In addition, during the course of studies students may develop subject-based critical thinking while not being able to extend the skills to the general critical thinking. As such, we wanted to design and conduct a study on efficacy of several teaching methods in which we would learn how students’ improve their thinking processes within a science discipline as well as in everyday life situations. We conducted a study among 20 astronomy, physics and geology majors-- both graduate and undergraduate students-- enrolled in our Solar System Science course (mostly seniors and early graduate students) at the University of Missouri. We used the Ennis-Weir Critical Thinking Essay test to assess students’ general critical thinking and, in addition, we implemented our own subject-based critical thinking assessment. Here, we present the results of this study and share our experience on designing a subject-based critical thinking assessment instrument.

ON A NUMERICAL ALGORITHM FOR UNCERTAIN SYSTEM ∫ Φ ...

African Journals Online (AJOL)

Administrator

Science World Journal Vol 7 (No 1) 2012 www.scienceworldjournal.org. ISSN 1597-6343. On a Numerical Algorithm for Uncertain System. Newton's Algorithm. Step 1 Calculate. )(),().(k k k. xAxgxF. Step 2. Check if ε. <. )(k xg for a predetermined ,ε if so stop, else. Step3. Set k k. PxA. )( = )(k xg. -. Step4. Set k k k. Px x. +. = +1.

Automated training for algorithms that learn from genomic data.

Science.gov (United States)

Cilingir, Gokcen; Broschat, Shira L

2015-01-01

Supervised machine learning algorithms are used by life scientists for a variety of objectives. Expert-curated public gene and protein databases are major resources for gathering data to train these algorithms. While these data resources are continuously updated, generally, these updates are not incorporated into published machine learning algorithms which thereby can become outdated soon after their introduction. In this paper, we propose a new model of operation for supervised machine learning algorithms that learn from genomic data. By defining these algorithms in a pipeline in which the training data gathering procedure and the learning process are automated, one can create a system that generates a classifier or predictor using information available from public resources. The proposed model is explained using three case studies on SignalP, MemLoci, and ApicoAP in which existing machine learning models are utilized in pipelines. Given that the vast majority of the procedures described for gathering training data can easily be automated, it is possible to transform valuable machine learning algorithms into self-evolving learners that benefit from the ever-changing data available for gene products and to develop new machine learning algorithms that are similarly capable.

The Undergraduate Statistics Major--A Prelude to Actuarial Science Training.

Science.gov (United States)

Ratliff, Michael I.; Williams, Raymond E.

Recently there has been increased interest related to the Actuarial Science field. An actuary is a business professional who uses mathematical skills to define, analyze, and solve financial and social problems. This paper examines: (1) the interface between Statistical and Actuarial Science training; (2) statistical courses corresponding to…

Imaging sciences workshop

Energy Technology Data Exchange (ETDEWEB)

Candy, J.V.

1994-11-15

This workshop on the Imaging Sciences sponsored by Lawrence Livermore National Laboratory contains short abstracts/articles submitted by speakers. The topic areas covered include the following: Astronomical Imaging; biomedical imaging; vision/image display; imaging hardware; imaging software; Acoustic/oceanic imaging; microwave/acoustic imaging; computed tomography; physical imaging; imaging algorithms. Selected papers are indexed separately for inclusion in the Energy Science and Technology Database.

Personality, academic majors and performance

DEFF Research Database (Denmark)

Vedel, Anna; Thomsen, Dorthe Kirkegaard; Larsen, Lars

2015-01-01

Personality–performance research typically uses samples of psychology students without questioning their representativeness. The present article reports two studies challenging this practice. Study 1: group differences in the Big Five personality traits were explored between students (N = 1067......) in different academic majors (medicine, psychology, law, economics, political science, science, and arts/humanities), who were tested immediately after university enrolment. Study 2: six and a half years later the students’ academic records were obtained, and predictive validity of the Big Five personality...... traits and their subordinate facets was examined in the various academic majors in relation to Grade Point Average (GPA). Significant group differences in all Big Five personality traits were found between students in different academic majors. Also, variability in predictive validity of the Big Five...

Enabling Earth Science Through Cloud Computing

Science.gov (United States)

Hardman, Sean; Riofrio, Andres; Shams, Khawaja; Freeborn, Dana; Springer, Paul; Chafin, Brian

2012-01-01

Cloud Computing holds tremendous potential for missions across the National Aeronautics and Space Administration. Several flight missions are already benefiting from an investment in cloud computing for mission critical pipelines and services through faster processing time, higher availability, and drastically lower costs available on cloud systems. However, these processes do not currently extend to general scientific algorithms relevant to earth science missions. The members of the Airborne Cloud Computing Environment task at the Jet Propulsion Laboratory have worked closely with the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) mission to integrate cloud computing into their science data processing pipeline. This paper details the efforts involved in deploying a science data system for the CARVE mission, evaluating and integrating cloud computing solutions with the system and porting their science algorithms for execution in a cloud environment.

On a numerical algorithm for uncertain system | Abiola | Science ...

African Journals Online (AJOL)

A numerical method for computing stable control signals for system with bounded input disturbance is developed. The algorithm is an elaboration of the gradient technique and variable metric method for computing control variables in linear and non-linear optimization problems. This method is developed for an integral ...

Trends in Gender Segregation in the Choice of Science and Engineering Majors*

Science.gov (United States)

Mann, Allison; DiPrete, Thomas A.

2013-01-01

Numerous theories have been put forward for the high and continuing levels of gender segregation in science, technology, engineering, and mathematics (STEM) fields, but research has not systematically examined the extent to which these theories for the gender gap are consistent with actual trends. Using both administrative data and four separate longitudinal studies sponsored by the U.S. Department of Education’s National Center for Education Statistics (NCES), we evaluate several prominent explanations for the persisting gender gap in STEM fields related to mathematics performance and background and general life goals, and find that none of them are empirically satisfactory. Instead, we suggest that the structure of majors and their linkages to professional training and careers may combine with gender differences in educational goals to influence the persisting gender gap in STEM fields. An analysis of gendered career aspirations, course-taking patterns, and pathways to medical and law school supports this explanation. PMID:24090849

Trends in gender segregation in the choice of science and engineering majors.

Science.gov (United States)

Mann, Allison; Diprete, Thomas A

2013-11-01

Numerous theories have been put forward for the high and continuing levels of gender segregation in science, technology, engineering, and mathematics (STEM) fields, but research has not systematically examined the extent to which these theories for the gender gap are consistent with actual trends. Using both administrative data and four separate longitudinal studies sponsored by the U.S. Department of Education's National Center for Education Statistics (NCES), we evaluate several prominent explanations for the persisting gender gap in STEM fields related to mathematics performance and background and general life goals, and find that none of them are empirically satisfactory. Instead, we suggest that the structure of majors and their linkages to professional training and careers may combine with gender differences in educational goals to influence the persisting gender gap in STEM fields. An analysis of gendered career aspirations, course-taking patterns, and pathways to medical and law school supports this explanation. Copyright © 2013 Elsevier Inc. All rights reserved.

2nd International Conference on Harmony Search Algorithm

CERN Document Server

Geem, Zong

2016-01-01

The Harmony Search Algorithm (HSA) is one of the most well-known techniques in the field of soft computing, an important paradigm in the science and engineering community.  This volume, the proceedings of the 2nd International Conference on Harmony Search Algorithm 2015 (ICHSA 2015), brings together contributions describing the latest developments in the field of soft computing with a special focus on HSA techniques. It includes coverage of new methods that have potentially immense application in various fields. Contributed articles cover aspects of the following topics related to the Harmony Search Algorithm: analytical studies; improved, hybrid and multi-objective variants; parameter tuning; and large-scale applications.  The book also contains papers discussing recent advances on the following topics: genetic algorithms; evolutionary strategies; the firefly algorithm and cuckoo search; particle swarm optimization and ant colony optimization; simulated annealing; and local search techniques.   This book ...

The Kepler Science Operations Center Pipeline Framework Extensions

Science.gov (United States)

Klaus, Todd C.; Cote, Miles T.; McCauliff, Sean; Girouard, Forrest R.; Wohler, Bill; Allen, Christopher; Chandrasekaran, Hema; Bryson, Stephen T.; Middour, Christopher; Caldwell, Douglas A.;

Sadhana | Indian Academy of Sciences

Indian Academy of Sciences (India)

It may help the engineers to carry out type synthesis of the mechanisms. Volume 40 Issue 2 April 2015 pp 549-575 Mechanical Sciences. Analysis of double support phase of biped robot and multi-objective optimization using genetic algorithm and particle swarm optimization algorithm · Rega Rajendra Dilip Kumar Pratihar.

The Impact of Transformational Leadership, Experiential Learning, and Reflective Journaling on the Conservation Ethic of Tertiary-Level Non-Science Majors

Science.gov (United States)

Reynolds, Bradley Robert

2013-01-01

The impact of transformational leadership, experiential learning, and reflective journaling on the conservation ethic of non-science majors in a general education survey course was investigated. The main research questions were: (1) Is the Conservation of Biodiversity professor a transformational leader? (2) Is there a difference in the…

An optimization algorithm for a capacitated vehicle routing problem ...

Indian Academy of Sciences (India)

Pinar Kirci

PINAR KIRCI. Engineering Sciences Department, Istanbul University, Istanbul, Turkey .... In VRP solution methods, tabu search algorithm belongs to ..... systems which are considered in statistical mechanics is ..... Procedia-Social Behav. Sci.

Stereotype threat's effect on women's achievement in chemistry: The interaction of achievement goal orientation for women in science majors

Science.gov (United States)

Conway-Klaassen, Janice Marjorie

"Stereotype threat is being at risk of confirming, as a self-characteristic, a negative stereotype about one's group" (C. M. Steele & Aronson, 1995, p. 797). A stereotype threat effect then is described as the detrimental impact on a person's performance or achievement measurements when they are placed in a stereotype threat environment. For women, the negative stereotype that exists in our culture states that women are typically not as capable as men in mathematics or science subjects. This study specifically explored the potential impact of stereotype threat on women who have chosen a science-based college major. They were tested in the domain of chemistry, which is related to mathematics and often involves high level of mathematics skills. I attempted to generate a stereotype threat in the participants through describing a chemistry challenge exam as either one that had consistently shown a gender bias against women and to create a nullification effect by describing the exam as one that had shown no gender bias in the past. In the third experimental condition acting as a control, participants received only generic instructions related to taking the test itself. The second part of this study investigated whether stereotype threat effects could impact women's achievement goal orientations. In previous studies performance avoidance goal orientations have been associated with individuals placed in a stereotype threat environment. The findings on the stereotype threat effect were not significant for the chemistry challenge test achievement scores. This may be due to several factors. One factor may be the design of the chemistry challenge test and the instructions for the test. The other factor may be the women in this study. As individuals who have chosen a science based major, they may have developed coping skills and strategies that reduced the impact of a stereotype threat. It is also possible that the testing environment itself generated an implicit stereotype

Integrated Lecture and Laboratory Chemistry Components of Science Education Program for Early and Middle Childhood Education Majors

Science.gov (United States)

Lunsford, S. K.

2004-05-01

Two new chemistry courses were developed for early childhood and middle childhood education majors. The results of a pre- and posttest in the courses indicate success in developing student content knowledge and ability to problem solve. In addition these courses are designed to develop preservice teachers' understanding of the National Science Education Standards and foster support for implementing these standards in their classrooms. These courses provide materials, resources, and guidance in implementing the standards in their future teaching careers.

Is normal science good science?

Directory of Open Access Journals (Sweden)

Adrianna Kępińska

2015-09-01

Full Text Available “Normal science” is a concept introduced by Thomas Kuhn in The Structure of Scientific Revolutions (1962. In Kuhn’s view, normal science means “puzzle solving”, solving problems within the paradigm—framework most successful in solving current major scientific problems—rather than producing major novelties. This paper examines Kuhnian and Popperian accounts of normal science and their criticisms to assess if normal science is good. The advantage of normal science according to Kuhn was “psychological”: subjective satisfaction from successful “puzzle solving”. Popper argues for an “intellectual” science, one that consistently refutes conjectures (hypotheses and offers new ideas rather than focus on personal advantages. His account is criticized as too impersonal and idealistic. Feyerabend’s perspective seems more balanced; he argues for a community that would introduce new ideas, defend old ones, and enable scientists to develop in line with their subjective preferences. The paper concludes that normal science has no one clear-cut set of criteria encompassing its meaning and enabling clear assessment.

Algorithmic paranoia and the convivial alternative

Directory of Open Access Journals (Sweden)

Dan McQuillan

2016-11-01

Full Text Available In a time of big data, thinking about how we are seen and how that affects our lives means changing our idea about who does the seeing. Data produced by machines is most often ‘seen’ by other machines; the eye is in question is algorithmic. Algorithmic seeing does not produce a computational panopticon but a mechanism of prediction. The authority of its predictions rests on a slippage of the scientific method in to the world of data. Data science inherits some of the problems of science, especially the disembodied ‘view from above’, and adds new ones of its own. As its core methods like machine learning are based on seeing correlations not understanding causation, it reproduces the prejudices of its input. Rising in to the apparatuses of governance, it reinforces the problematic sides of ‘seeing like a state’ and links to the recursive production of paranoia. It forces us to ask the question ‘what counts as rational seeing?’. Answering this from a position of feminist empiricism reveals different possibilities latent in seeing with machines. Grounded in the idea of conviviality, machine learning may reveal forgotten non-market patterns and enable free and critical learning. It is proposed that a programme to challenge the production of irrational pre-emption is also a search for the possibility of algorithmic conviviality.

Digital and discrete geometry theory and algorithms

CERN Document Server

Chen, Li

2014-01-01

This book provides comprehensive coverage of the modern methods for geometric problems in the computing sciences. It also covers concurrent topics in data sciences including geometric processing, manifold learning, Google search, cloud data, and R-tree for wireless networks and BigData.The author investigates digital geometry and its related constructive methods in discrete geometry, offering detailed methods and algorithms. The book is divided into five sections: basic geometry; digital curves, surfaces and manifolds; discretely represented objects; geometric computation and processing; and a

High-order hydrodynamic algorithms for exascale computing

Energy Technology Data Exchange (ETDEWEB)

Morgan, Nathaniel Ray [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2016-02-05

Hydrodynamic algorithms are at the core of many laboratory missions ranging from simulating ICF implosions to climate modeling. The hydrodynamic algorithms commonly employed at the laboratory and in industry (1) typically lack requisite accuracy for complex multi- material vortical flows and (2) are not well suited for exascale computing due to poor data locality and poor FLOP/memory ratios. Exascale computing requires advances in both computer science and numerical algorithms. We propose to research the second requirement and create a new high-order hydrodynamic algorithm that has superior accuracy, excellent data locality, and excellent FLOP/memory ratios. This proposal will impact a broad range of research areas including numerical theory, discrete mathematics, vorticity evolution, gas dynamics, interface instability evolution, turbulent flows, fluid dynamics and shock driven flows. If successful, the proposed research has the potential to radically transform simulation capabilities and help position the laboratory for computing at the exascale.

Bulletin of Materials Science | Indian Academy of Sciences

Indian Academy of Sciences (India)

Home; Journals; Bulletin of Materials Science; Volume 24; Issue 4. Evaluation of solid–liquid interface profile during continuous casting by a spline based formalism. S K Das. Metals and Alloys Volume ... Keywords. Continuous casting; solidification; solid–liquid interface; front tracking algorithm; phase change; heat transfer.

Bringing Up Girls in Science (BUGS): The Effectiveness of an Afterschool Environmental Science Program for Increasing Female Students' Interest in Science Careers

Science.gov (United States)

Tyler-Wood, Tandra; Ellison, Amber; Lim, Okyoung; Periathiruvadi, Sita

2012-02-01

Bringing Up Girls in Science (BUGS) was an afterschool program for 4th and 5th grade girls that provided authentic learning experiences in environmental science as well as valuable female mentoring opportunities in an effort to increase participants' academic achievement in science. BUGS participants demonstrated significantly greater amounts of gain in science knowledge as measured by the Iowa Test of Basic Skills in Science (ITBS-S). The original BUGS participants and contrasts have now completed high school and entered college, allowing researchers to assess the long-term impact of the BUGS program. Fourteen former BUGS participants completed two instruments to assess their perceptions of science and science, technology, engineering, and mathematics (STEM) careers. Their results were compared to four contrast groups composed entirely of females: 12 former BUGS contrasts, 10 college science majors, 10 non-science majors, and 9 current STEM professionals. Results indicate that BUGS participants have higher perceptions of science careers than BUGS contrasts. There were no significant differences between BUGS participants, Science Majors, and STEM professionals in their perceptions of science and STEM careers, whereas the BUGS contrast group was significantly lower than BUGS participants, Science Majors, and STEM Professionals. Additional results and implications are discussed within.

Operation of the Institute for Computer Applications in Science and Engineering

Science.gov (United States)

1975-01-01

The ICASE research program is described in detail; it consists of four major categories: (1) efficient use of vector and parallel computers, with particular emphasis on the CDC STAR-100; (2) numerical analysis, with particular emphasis on the development and analysis of basic numerical algorithms; (3) analysis and planning of large-scale software systems; and (4) computational research in engineering and the natural sciences, with particular emphasis on fluid dynamics. The work in each of these areas is described in detail; other activities are discussed, a prognosis of future activities are included.

Solving Optimization Problems via Vortex Optimization Algorithm and Cognitive Development Optimization Algorithm

Directory of Open Access Journals (Sweden)

Ahmet Demir

2017-01-01

Full Text Available In the fields which require finding the most appropriate value, optimization became a vital approach to employ effective solutions. With the use of optimization techniques, many different fields in the modern life have found solutions to their real-world based problems. In this context, classical optimization techniques have had an important popularity. But after a while, more advanced optimization problems required the use of more effective techniques. At this point, Computer Science took an important role on providing software related techniques to improve the associated literature. Today, intelligent optimization techniques based on Artificial Intelligence are widely used for optimization problems. The objective of this paper is to provide a comparative study on the employment of classical optimization solutions and Artificial Intelligence solutions for enabling readers to have idea about the potential of intelligent optimization techniques. At this point, two recently developed intelligent optimization algorithms, Vortex Optimization Algorithm (VOA and Cognitive Development Optimization Algorithm (CoDOA, have been used to solve some multidisciplinary optimization problems provided in the source book Thomas' Calculus 11th Edition and the obtained results have compared with classical optimization solutions. 

Comparison between iterative wavefront control algorithm and direct gradient wavefront control algorithm for adaptive optics system

International Nuclear Information System (INIS)

Cheng Sheng-Yi; Liu Wen-Jin; Chen Shan-Qiu; Dong Li-Zhi; Yang Ping; Xu Bing

2015-01-01

Among all kinds of wavefront control algorithms in adaptive optics systems, the direct gradient wavefront control algorithm is the most widespread and common method. This control algorithm obtains the actuator voltages directly from wavefront slopes through pre-measuring the relational matrix between deformable mirror actuators and Hartmann wavefront sensor with perfect real-time characteristic and stability. However, with increasing the number of sub-apertures in wavefront sensor and deformable mirror actuators of adaptive optics systems, the matrix operation in direct gradient algorithm takes too much time, which becomes a major factor influencing control effect of adaptive optics systems. In this paper we apply an iterative wavefront control algorithm to high-resolution adaptive optics systems, in which the voltages of each actuator are obtained through iteration arithmetic, which gains great advantage in calculation and storage. For AO system with thousands of actuators, the computational complexity estimate is about O(n 2 ) ∼ O(n 3 ) in direct gradient wavefront control algorithm, while the computational complexity estimate in iterative wavefront control algorithm is about O(n) ∼ (O(n) 3/2 ), in which n is the number of actuators of AO system. And the more the numbers of sub-apertures and deformable mirror actuators, the more significant advantage the iterative wavefront control algorithm exhibits. (paper)

Novel quantum inspired binary neural network algorithm

Indian Academy of Sciences (India)

This parameter is taken as the threshold of neuron for learning of neural network. This algorithm is tested with three benchmark datasets and ... Author Affiliations. OM PRAKASH PATEL1 ARUNA TIWARI. Department of Computer Science and Engineering, Indian Institute of Technology Indore, Indore 453552, India ...

A not quite random walk: Experimenting with the ethnomethods of the algorithm

Directory of Open Access Journals (Sweden)

Malte Ziewitz

2017-11-01

Full Text Available Algorithms have become a widespread trope for making sense of social life. Science, finance, journalism, warfare, and policing—there is hardly anything these days that has not been specified as “algorithmic.” Yet, although the trope has brought together a variety of audiences, it is not quite clear what kind of work it does. Often portrayed as powerful yet inscrutable entities, algorithms maintain an air of mystery that makes them both interesting and difficult to understand. This article takes on this problem and examines the role of algorithms not as techno-scientific objects to be known, but as a figure that is used for making sense of observations. Following in the footsteps of Harold Garfinkel’s tutorial cases, I shall illustrate the implications of this view through an experiment with algorithmic navigation. Challenging participants to go on a walk, guided not by maps or GPS but by an algorithm developed on the spot, I highlight a number of dynamics typical of reasoning with running code, including the ongoing respecification of rules and observations, the stickiness of the procedure, and the selective invocation of the algorithm as an intelligible object. The materials thus provide an opportunity to rethink key issues at the intersection of the social sciences and the computational, including popular concerns with transparency, accountability, and ethics.

Automatic design of decision-tree induction algorithms

CERN Document Server

Barros, Rodrigo C; Freitas, Alex A

2015-01-01

Presents a detailed study of the major design components that constitute a top-down decision-tree induction algorithm, including aspects such as split criteria, stopping criteria, pruning, and the approaches for dealing with missing values. Whereas the strategy still employed nowadays is to use a 'generic' decision-tree induction algorithm regardless of the data, the authors argue on the benefits that a bias-fitting strategy could bring to decision-tree induction, in which the ultimate goal is the automatic generation of a decision-tree induction algorithm tailored to the application domain o

Tenth workshop on the algorithmic foundations of robotics (WAFR)

CERN Document Server

Lozano-Perez, Tomas; Roy, Nicholas; Rus, Daniela; Algorithmic foundations of robotics X

2013-01-01

Algorithms are a fundamental component of robotic systems. Robot algorithms process inputs from sensors that provide noisy and partial data, build geometric and physical models of the world, plan high-and low-level actions at different time horizons, and execute these actions on actuators with limited precision. The design and analysis of robot algorithms raise a unique combination of questions from many elds, including control theory, computational geometry and topology, geometrical and physical modeling, reasoning under uncertainty, probabilistic algorithms, game theory, and theoretical computer science. The Workshop on Algorithmic Foundations of Robotics (WAFR) is a single-track meeting of leading researchers in the eld of robot algorithms. Since its inception in 1994, WAFR has been held every other year, and has provided one of the premiere venues for the publication of some of the eld's most important and lasting contributions. This books contains the proceedings of the tenth WAFR, held on June 13{15 201...

Betweenness-based algorithm for a partition scale-free graph

International Nuclear Information System (INIS)

Zhang Bai-Da; Wu Jun-Jie; Zhou Jing; Tang Yu-Hua

2011-01-01

Many real-world networks are found to be scale-free. However, graph partition technology, as a technology capable of parallel computing, performs poorly when scale-free graphs are provided. The reason for this is that traditional partitioning algorithms are designed for random networks and regular networks, rather than for scale-free networks. Multilevel graph-partitioning algorithms are currently considered to be the state of the art and are used extensively. In this paper, we analyse the reasons why traditional multilevel graph-partitioning algorithms perform poorly and present a new multilevel graph-partitioning paradigm, top down partitioning, which derives its name from the comparison with the traditional bottom—up partitioning. A new multilevel partitioning algorithm, named betweenness-based partitioning algorithm, is also presented as an implementation of top—down partitioning paradigm. An experimental evaluation of seven different real-world scale-free networks shows that the betweenness-based partitioning algorithm significantly outperforms the existing state-of-the-art approaches. (interdisciplinary physics and related areas of science and technology)

ESA is now a major player in global space science

Science.gov (United States)

1997-07-01

cosmos after its February 1997 refurbishment. Europe's astronomers make outstanding use of their right to make observations with Hubble, guaranteed by ESA's participation. ESA's table d'h^te for space scientists To provide world-class opportunities in space for Europe's scientific community is one of ESA's primary duties. The successes summarized here are not a matter of luck, but of decades of sustained planning and effort. Although ESA's science budget is small as compared with NASA=s equivalent programme, and is even being squeezed, yet every one of ESA's missions is first in its class. * 3- The scientists of ESA's member states draw up the table d'h^te, with a balanced menu of research opportunities in Solar System exploration and in astronomy. ESA coordinates the technological and scientific efforts across Europe needed to accomplish the missions, after many years of preparation and sometimes adversity. One of ESA's strengths is that it sticks to its promises, and maintains a balance with several small missions, remaining alert to new tasks for short-term projects. Besides the spacecraft mentioned earlier, ESA is actively working on: * Rosetta. As the successor to the very successful comet mission Giotto, which intercepted Halley's Comet in 1986 and Comet Grigg-Skjellerup in 1992, Rosetta will confirm ESA's role as the world leader in comet science. To be launched in 2003, Rosetta will rendezvous with Comet Wirtanen, and fly in close orbit around it as it makes its closest approach to the Sun ten years later. * Integral. Adapted from the XMM spacecraft to save money, Integral will go into orbit in 2001 and renew ESA's role in gamma-ray astronomy, pioneered in its COS-B mission some twenty years ago. Gamma-rays reveal the most violent events in the Universe, including the gamma-ray bursts that are exciting astronomers greatly at present. * FIRST and Planck Surveyor. FIRST is a long-standing major project to extend the scope of infrared space astronomy to wavelengths

The JPSS Ground Project Algorithm Verification, Test and Evaluation System

Science.gov (United States)

Vicente, G. A.; Jain, P.; Chander, G.; Nguyen, V. T.; Dixon, V.

2016-12-01

The Government Resource for Algorithm Verification, Independent Test, and Evaluation (GRAVITE) is an operational system that provides services to the Suomi National Polar-orbiting Partnership (S-NPP) Mission. It is also a unique environment for Calibration/Validation (Cal/Val) and Data Quality Assessment (DQA) of the Join Polar Satellite System (JPSS) mission data products. GRAVITE provides a fast and direct access to the data and products created by the Interface Data Processing Segment (IDPS), the NASA/NOAA operational system that converts Raw Data Records (RDR's) generated by sensors on the S-NPP into calibrated geo-located Sensor Data Records (SDR's) and generates Mission Unique Products (MUPS). It also facilitates algorithm investigation, integration, checkouts and tuning, instrument and product calibration and data quality support, monitoring and data/products distribution. GRAVITE is the portal for the latest S-NPP and JPSS baselined Processing Coefficient Tables (PCT's) and Look-Up-Tables (LUT's) and hosts a number DQA offline tools that takes advantage of the proximity to the near-real time data flows. It also contains a set of automated and ad-hoc Cal/Val tools used for algorithm analysis and updates, including an instance of the IDPS called GRAVITE Algorithm Development Area (G-ADA), that has the latest installation of the IDPS algorithms running in an identical software and hardware platforms. Two other important GRAVITE component are the Investigator-led Processing System (IPS) and the Investigator Computing Facility (ICF). The IPS is a dedicated environment where authorized users run automated scripts called Product Generation Executables (PGE's) to support Cal/Val and data quality assurance offline. This data-rich and data-driven service holds its own distribution system and allows operators to retrieve science data products. The ICF is a workspace where users can share computing applications and resources and have full access to libraries and

A Modularity Degree Based Heuristic Community Detection Algorithm

Directory of Open Access Journals (Sweden)

Dongming Chen

2014-01-01

Full Text Available A community in a complex network can be seen as a subgroup of nodes that are densely connected. Discovery of community structures is a basic problem of research and can be used in various areas, such as biology, computer science, and sociology. Existing community detection methods usually try to expand or collapse the nodes partitions in order to optimize a given quality function. These optimization function based methods share the same drawback of inefficiency. Here we propose a heuristic algorithm (MDBH algorithm based on network structure which employs modularity degree as a measure function. Experiments on both synthetic benchmarks and real-world networks show that our algorithm gives competitive accuracy with previous modularity optimization methods, even though it has less computational complexity. Furthermore, due to the use of modularity degree, our algorithm naturally improves the resolution limit in community detection.

Selecting a general-purpose data compression algorithm

Science.gov (United States)

Mathews, Gary Jason

1995-01-01

The National Space Science Data Center's Common Data Formate (CDF) is capable of storing many types of data such as scalar data items, vectors, and multidimensional arrays of bytes, integers, or floating point values. However, regardless of the dimensionality and data type, the data break down into a sequence of bytes that can be fed into a data compression function to reduce the amount of data without losing data integrity and thus remaining fully reconstructible. Because of the diversity of data types and high performance speed requirements, a general-purpose, fast, simple data compression algorithm is required to incorporate data compression into CDF. The questions to ask are how to evaluate and compare compression algorithms, and what compression algorithm meets all requirements. The object of this paper is to address these questions and determine the most appropriate compression algorithm to use within the CDF data management package that would be applicable to other software packages with similar data compression needs.

A Non-science Major Undergraduate Seminar on the NASA Earth Observing System (EOS): A Student Perspective

Science.gov (United States)

Weatherford, V. L.; Redemann, J.

2003-12-01

Titled "Observing Climate Change From Space-what tools do we have?", this non-science major freshman seminar at UCLA is the culmination of a year-long interdisciplinary program sponsored by the Institute of the Environment and the College Honors programs at the University. Focusing on the anthropogenic and natural causes of climate change, students study climate forcings and learn about satellite and other technological means of monitoring climate and weather. NASA's Terra satellite is highlighted as one of the most recent and comprehensive monitoring systems put into space and the role of future NASA platforms in the "A-train"-constellation of satellites is discussed. Course material is typically presented in a Power-Point presentation by the instructor, with assigned supplementary reading to stimulate class discussion. In addition to preparing lectures for class presentation, students work on a final term paper and oral presentation which constitutes the majority of their grade. Field trips to the San Gabriel mountains to take atmospheric measurements with handheld sunphotometers and to JPL, Pasadena (CA) to listen to a NASA scientist discuss the MISR instrument aboard the Terra satellite help bring a real-world perspective to the science learned in the classroom. In this paper, we will describe the objectives and structure of this class and present measurement results taken during the field trip to the San Gabriel Mountains. In this context we will discuss the potential relevance of hands-on experience to meeting class objectives and give a student perspective of the overall class experience.

How the “Queen Science” Lost Her Crown: A Brief Social History of Science Fairs and the Marginalization of Social Science

Directory of Open Access Journals (Sweden)

Jonathan Marx

2004-10-01

Full Text Available Science fairs at one time started out with an interest of increasing participation in the sciences. But as time has passed, the definition of science has been narrowed to the point where any possible social science project has been eliminated in favor of the bench sciences only. Even here, natural curiosity of students has been deemphasized. It is not surprising that science majors in the USA are becoming fewer and fewer given the narrowing of the disciplines. Young people are discouraged from majoring in science by the science establishment.

Computer science and operations research

CERN Document Server

Balci, Osman

1992-01-01

The interface of Operation Research and Computer Science - although elusive to a precise definition - has been a fertile area of both methodological and applied research. The papers in this book, written by experts in their respective fields, convey the current state-of-the-art in this interface across a broad spectrum of research domains which include optimization techniques, linear programming, interior point algorithms, networks, computer graphics in operations research, parallel algorithms and implementations, planning and scheduling, genetic algorithms, heuristic search techniques and dat

Comparative Results of AIRS AMSU and CrIS/ATMS Retrievals Using a Scientifically Equivalent Retrieval Algorithm

Science.gov (United States)

Susskind, Joel; Kouvaris, Louis; Iredell, Lena

2016-01-01

The AIRS Science Team Version 6 retrieval algorithm is currently producing high quality level-3 Climate Data Records (CDRs) from AIRSAMSU which are critical for understanding climate processes. The AIRS Science Team is finalizing an improved Version-7 retrieval algorithm to reprocess all old and future AIRS data. AIRS CDRs should eventually cover the period September 2002 through at least 2020. CrISATMS is the only scheduled follow on to AIRSAMSU. The objective of this research is to prepare for generation of a long term CrISATMS level-3 data using a finalized retrieval algorithm that is scientifically equivalent to AIRSAMSU Version-7.

Algorithm Animations for Teaching and Learning the Main Ideas of Basic Sortings

Science.gov (United States)

Végh, Ladislav; Stoffová, Veronika

2017-01-01

Algorithms are hard to understand for novice computer science students because they dynamically modify values of elements of abstract data structures. Animations can help to understand algorithms, since they connect abstract concepts to real life objects and situations. In the past 30-35 years, there have been conducted many experiments in the…

Computer-based Astronomy Labs for Non-science Majors

Science.gov (United States)

Smith, A. B. E.; Murray, S. D.; Ward, R. A.

1998-12-01

We describe and demonstrate two laboratory exercises, Kepler's Third Law and Stellar Structure, which are being developed for use in an astronomy laboratory class aimed at non-science majors. The labs run with Microsoft's Excel 98 (Macintosh) or Excel 97 (Windows). They can be run in a classroom setting or in an independent learning environment. The intent of the labs is twofold; first and foremost, students learn the subject matter through a series of informational frames. Next, students enhance their understanding by applying their knowledge in lab procedures, while also gaining familiarity with the use and power of a widely-used software package and scientific tool. No mathematical knowledge beyond basic algebra is required to complete the labs or to understand the computations in the spreadsheets, although the students are exposed to the concepts of numerical integration. The labs are contained in Excel workbook files. In the files are multiple spreadsheets, which contain either a frame with information on how to run the lab, material on the subject, or one or more procedures. Excel's VBA macro language is used to automate the labs. The macros are accessed through button interfaces positioned on the spreadsheets. This is done intentionally so that students can focus on learning the subject matter and the basic spreadsheet features without having to learn advanced Excel features all at once. Students open the file and progress through the informational frames to the procedures. After each procedure, student comments and data are automatically recorded in a preformatted Lab Report spreadsheet. Once all procedures have been completed, the student is prompted for a filename in which to save their Lab Report. The lab reports can then be printed or emailed to the instructor. The files will have full worksheet and workbook protection, and will have a "redo" feature at the end of the lab for students who want to repeat a procedure.

Algorithmic aspects for the reconstruction of spatio-spectral data cubes in the perspective of the SKA

Science.gov (United States)

Mary, D.; Ferrari, A.; Ferrari, C.; Deguignet, J.; Vannier, M.

2016-12-01

With millions of receivers leading to TerraByte data cubes, the story of the giant SKA telescope is also that of collaborative efforts from radioastronomy, signal processing, optimization and computer sciences. Reconstructing SKA cubes poses two challenges. First, the majority of existing algorithms work in 2D and cannot be directly translated into 3D. Second, the reconstruction implies solving an inverse problem and it is not clear what ultimate limit we can expect on the error of this solution. This study addresses (of course partially) both challenges. We consider an extremely simple data acquisition model, and we focus on strategies making it possible to implement 3D reconstruction algorithms that use state-of-the-art image/spectral regularization. The proposed approach has two main features: (i) reduced memory storage with respect to a previous approach; (ii) efficient parallelization and ventilation of the computational load over the spectral bands. This work will allow to implement and compare various 3D reconstruction approaches in a large scale framework.

Gender Differences in Self-Efficacy and Sense of Class and School Belonging for Majors in Science, Technology, Engineering, and Mathematics (STEM) Disciplines

Science.gov (United States)

Hogue, Barbara A.

Research into women's underrepresentation in science, technology, engineering, and mathematics (STEM) disciplines has become a topic of interest due to the increasing need for employees with technical expertise and a shortage of individuals to fill STEM jobs. The discrepancy in women's representation between STEM and other fields cannot adequately be explained by factors such as women's need to balance work and family (medicine and law are both extremely demanding careers), women's fear of competition (admissions into medical and law schools are highly competitive), or women's inability to excel in science (e.g., entry into medicine requires excellent achievement in the basic sciences). The purpose of this study is to gain a deeper understanding of the role and/or impact a sense of belonging has inside and outside of STEM classrooms. Research questions focused on the role and/or impact of belonging contributes to students' self-efficacy beliefs as a STEM major. Bandura's self-efficacy theory serves as the theoretical framework. Data sources include close-ended surveys of 200 sophomore- and junior-level college students majoring in a STEM discipline. A quantitative exploratory approach allowed participants' responses to be analyzed using both correlation and multiple regression analyses to understand whether a student's sense of belonging is associated with his or her self-efficacy beliefs. Findings suggested that positive support systems impact students' self-efficacy and play a role in fostering students' motivation and decision to major in STEM disciplines. This study contributes to positive social change by providing empirical evidence faculty and administrators may use to promote university-based STEM support programs reflecting the impact belonging has on students' self-efficacy and potentially increasing the number of students majoring in STEM disciplines.

Benchmarking homogenization algorithms for monthly data

Science.gov (United States)

Venema, V. K. C.; Mestre, O.; Aguilar, E.; Auer, I.; Guijarro, J. A.; Domonkos, P.; Vertacnik, G.; Szentimrey, T.; Stepanek, P.; Zahradnicek, P.; Viarre, J.; Müller-Westermeier, G.; Lakatos, M.; Williams, C. N.; Menne, M. J.; Lindau, R.; Rasol, D.; Rustemeier, E.; Kolokythas, K.; Marinova, T.; Andresen, L.; Acquaotta, F.; Fratiannil, S.; Cheval, S.; Klancar, M.; Brunetti, M.; Gruber, C.; Prohom Duran, M.; Likso, T.; Esteban, P.; Brandsma, T.; Willett, K.

2013-09-01

The COST (European Cooperation in Science and Technology) Action ES0601: Advances in homogenization methods of climate series: an integrated approach (HOME) has executed a blind intercomparison and validation study for monthly homogenization algorithms. Time series of monthly temperature and precipitation were evaluated because of their importance for climate studies. The algorithms were validated against a realistic benchmark dataset. Participants provided 25 separate homogenized contributions as part of the blind study as well as 22 additional solutions submitted after the details of the imposed inhomogeneities were revealed. These homogenized datasets were assessed by a number of performance metrics including i) the centered root mean square error relative to the true homogeneous values at various averaging scales, ii) the error in linear trend estimates and iii) traditional contingency skill scores. The metrics were computed both using the individual station series as well as the network average regional series. The performance of the contributions depends significantly on the error metric considered. Although relative homogenization algorithms typically improve the homogeneity of temperature data, only the best ones improve precipitation data. Moreover, state-of-the-art relative homogenization algorithms developed to work with an inhomogeneous reference are shown to perform best. The study showed that currently automatic algorithms can perform as well as manual ones.

An Evaluation of Concurrent Priority Queue Algorithms

Science.gov (United States)

1991-02-01

path pronlem are testedi A! -S7 ?o An Evaluation of Concurrent Priority Queue Algorithms bv Qin Huang BS. Uiversity - of Science andi Technology of China...who have always supported me through my entire career and made my life more enjoyable. This research was supported in part by the Advanced Research

Optimization of Algorithms Using Extensions of Dynamic Programming

KAUST Repository

AbouEisha, Hassan M.

2017-04-09

We study and answer questions related to the complexity of various important problems such as: multi-frontal solvers of hp-adaptive finite element method, sorting and majority. We advocate the use of dynamic programming as a viable tool to study optimal algorithms for these problems. The main approach used to attack these problems is modeling classes of algorithms that may solve this problem using a discrete model of computation then defining cost functions on this discrete structure that reflect different complexity measures of the represented algorithms. As a last step, dynamic programming algorithms are designed and used to optimize those models (algorithms) and to obtain exact results on the complexity of the studied problems. The first part of the thesis presents a novel model of computation (element partition tree) that represents a class of algorithms for multi-frontal solvers along with cost functions reflecting various complexity measures such as: time and space. It then introduces dynamic programming algorithms for multi-stage and bi-criteria optimization of element partition trees. In addition, it presents results based on optimal element partition trees for famous benchmark meshes such as: meshes with point and edge singularities. New improved heuristics for those benchmark meshes were ob- tained based on insights of the optimal results found by our algorithms. The second part of the thesis starts by introducing a general problem where different problems can be reduced to and show how to use a decision table to model such problem. We describe how decision trees and decision tests for this table correspond to adaptive and non-adaptive algorithms for the original problem. We present exact bounds on the average time complexity of adaptive algorithms for the eight elements sorting problem. Then bounds on adaptive and non-adaptive algorithms for a variant of the majority problem are introduced. Adaptive algorithms are modeled as decision trees whose depth

Theoretical computer science and the natural sciences

Science.gov (United States)

Marchal, Bruno

2005-12-01

I present some fundamental theorems in computer science and illustrate their relevance in Biology and Physics. I do not assume prerequisites in mathematics or computer science beyond the set N of natural numbers, functions from N to N, the use of some notational conveniences to describe functions, and at some point, a minimal amount of linear algebra and logic. I start with Cantor's transcendental proof by diagonalization of the non enumerability of the collection of functions from natural numbers to the natural numbers. I explain why this proof is not entirely convincing and show how, by restricting the notion of function in terms of discrete well defined processes, we are led to the non algorithmic enumerability of the computable functions, but also-through Church's thesis-to the algorithmic enumerability of partial computable functions. Such a notion of function constitutes, with respect to our purpose, a crucial generalization of that concept. This will make easy to justify deep and astonishing (counter-intuitive) incompleteness results about computers and similar machines. The modified Cantor diagonalization will provide a theory of concrete self-reference and I illustrate it by pointing toward an elementary theory of self-reproduction-in the Amoeba's way-and cellular self-regeneration-in the flatworm Planaria's way. To make it easier, I introduce a very simple and powerful formal system known as the Schoenfinkel-Curry combinators. I will use the combinators to illustrate in a more concrete way the notion introduced above. The combinators, thanks to their low-level fine grained design, will also make it possible to make a rough but hopefully illuminating description of the main lessons gained by the careful observation of nature, and to describe some new relations, which should exist between computer science, the science of life and the science of inert matter, once some philosophical, if not theological, hypotheses are made in the cognitive sciences. In the

Using rapidly-exploring random tree-based algorithms to find smooth and optimal trajectories

CSIR Research Space (South Africa)

Matebese, B

2012-10-01

Full Text Available -exploring random tree-based algorithms to fi nd smooth and optimal trajectories B MATEBESE1, MK BANDA2 AND S UTETE1 1CSIR Modelling and Digital Science, PO Box 395, Pretoria, South Africa, 0001 2Department of Applied Mathematics, Stellenbosch University... and complex environments. The RRT algorithm is the most popular and has the ability to find a feasible solution faster than other algorithms. The drawback of using RRT is that, as the number of samples increases, the probability that the algorithm converges...

A branch and bound algorithm for the global optimization of Hessian Lipschitz continuous functions

KAUST Repository

Fowkes, Jaroslav M.

2012-06-21

We present a branch and bound algorithm for the global optimization of a twice differentiable nonconvex objective function with a Lipschitz continuous Hessian over a compact, convex set. The algorithm is based on applying cubic regularisation techniques to the objective function within an overlapping branch and bound algorithm for convex constrained global optimization. Unlike other branch and bound algorithms, lower bounds are obtained via nonconvex underestimators of the function. For a numerical example, we apply the proposed branch and bound algorithm to radial basis function approximations. © 2012 Springer Science+Business Media, LLC.

Next Generation Suspension Dynamics Algorithms

Energy Technology Data Exchange (ETDEWEB)

Schunk, Peter Randall [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Higdon, Jonathon [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Chen, Steven [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2014-12-01

This research project has the objective to extend the range of application, improve the efficiency and conduct simulations with the Fast Lubrication Dynamics (FLD) algorithm for concentrated particle suspensions in a Newtonian fluid solvent. The research involves a combination of mathematical development, new computational algorithms, and application to processing flows of relevance in materials processing. The mathematical developments clarify the underlying theory, facilitate verification against classic monographs in the field and provide the framework for a novel parallel implementation optimized for an OpenMP shared memory environment. The project considered application to consolidation flows of major interest in high throughput materials processing and identified hitherto unforeseen challenges in the use of FLD in these applications. Extensions to the algorithm have been developed to improve its accuracy in these applications.

Information content of ozone retrieval algorithms

Science.gov (United States)

Rodgers, C.; Bhartia, P. K.; Chu, W. P.; Curran, R.; Deluisi, J.; Gille, J. C.; Hudson, R.; Mateer, C.; Rusch, D.; Thomas, R. J.

1989-01-01

The algorithms are characterized that were used for production processing by the major suppliers of ozone data to show quantitatively: how the retrieved profile is related to the actual profile (This characterizes the altitude range and vertical resolution of the data); the nature of systematic errors in the retrieved profiles, including their vertical structure and relation to uncertain instrumental parameters; how trends in the real ozone are reflected in trends in the retrieved ozone profile; and how trends in other quantities (both instrumental and atmospheric) might appear as trends in the ozone profile. No serious deficiencies were found in the algorithms used in generating the major available ozone data sets. As the measurements are all indirect in someway, and the retrieved profiles have different characteristics, data from different instruments are not directly comparable.

Computing handbook computer science and software engineering

CERN Document Server

Gonzalez, Teofilo; Tucker, Allen

2014-01-01

Overview of Computer Science Structure and Organization of Computing Peter J. DenningComputational Thinking Valerie BarrAlgorithms and Complexity Data Structures Mark WeissBasic Techniques for Design and Analysis of Algorithms Edward ReingoldGraph and Network Algorithms Samir Khuller and Balaji RaghavachariComputational Geometry Marc van KreveldComplexity Theory Eric Allender, Michael Loui, and Kenneth ReganFormal Models and Computability Tao Jiang, Ming Li, and Bala

COALA-System for Visual Representation of Cryptography Algorithms

Science.gov (United States)

Stanisavljevic, Zarko; Stanisavljevic, Jelena; Vuletic, Pavle; Jovanovic, Zoran

2014-01-01

Educational software systems have an increasingly significant presence in engineering sciences. They aim to improve students' attitudes and knowledge acquisition typically through visual representation and simulation of complex algorithms and mechanisms or hardware systems that are often not available to the educational institutions. This paper…

Measuring the Impact of App Inventor for Android and Studio-Based Learning in an Introductory Computer Science Course for Non-Majors

Science.gov (United States)

Ahmad, Khuloud Nasser

2012-01-01

A reexamination of the traditional instruction of introductory computer science (CS) courses is becoming a necessity. Introductory CS courses tend to have high attrition rates and low success rates. In many universities, the CS department suffered from low enrollment for several years compared to other majors. Multiple studies have linked these…

Experimental methods for the analysis of optimization algorithms

CERN Document Server

Bartz-Beielstein, Thomas; Paquete, Luis; Preuss, Mike

2010-01-01

In operations research and computer science it is common practice to evaluate the performance of optimization algorithms on the basis of computational results, and the experimental approach should follow accepted principles that guarantee the reliability and reproducibility of results. However, computational experiments differ from those in other sciences, and the last decade has seen considerable methodological research devoted to understanding the particular features of such experiments and assessing the related statistical methods. This book consists of methodological contributions on diffe

Science self-efficacy of African Americans enrolled in freshman level physical science courses in two historically black institutions

Science.gov (United States)

Prihoda, Belinda Ann

2011-12-01

Science education must be a priority for citizens to function and be productive in a global, technological society. African Americans receive fewer science degrees in proportion to the Caucasian population. The primary purposes of this study were to determine the difference between the pretest and posttest science self-efficacy scores of African-American nonscience majors, the difference between the pretest and posttest science self-efficacy scores of African-American science majors, the relationship between science self-efficacy and course grade, the relationship between gender and science self-efficacy score, and the relationship between science self-efficacy score and course withdrawal. This study utilized a Likert survey instrument. All participants were enrolled in freshman level courses in the physical sciences at a historically black institution: a college or university. Participants completed the pretest survey within two weeks after the 12th class day of the semester. Initially, 458 participants completed the pretest survey. The posttest was administered within two weeks before the final exam. Only 245 participants completed the posttest survey. Results indicate that there is a difference in science self-efficacy of science majors and nonscience majors. There was no significant difference between the pretest and posttest science self-efficacy scores of African-American science majors and nonscience majors. There was no significant relationship between science self-efficacy and course grade, gender and science self-efficacy score, and course withdrawal and science self-efficacy score.

developed algorithm for the application of british method of concret

African Journals Online (AJOL)

t-iyke

Most of the methods of concrete mix design developed over the years were geared towards manual approach. ... Key words: Concrete mix design; British method; Manual Approach; Algorithm. ..... Statistics for Science and Engineering.

Algorithms, architectures and information systems security

CERN Document Server

Sur-Kolay, Susmita; Nandy, Subhas C; Bagchi, Aditya

2008-01-01

This volume contains articles written by leading researchers in the fields of algorithms, architectures, and information systems security. The first five chapters address several challenging geometric problems and related algorithms. These topics have major applications in pattern recognition, image analysis, digital geometry, surface reconstruction, computer vision and in robotics. The next five chapters focus on various optimization issues in VLSI design and test architectures, and in wireless networks. The last six chapters comprise scholarly articles on information systems security coverin

Truth in advertising: Reporting performance of computer programs, algorithms and the impact of architecture

Directory of Open Access Journals (Sweden)

Scott Hazelhurst

2010-11-01

Full Text Available The level of detail and precision that appears in the experimental methodology section computer science papers is usually much less than in natural science disciplines. This is partially justified by different nature of experiments. The experimental evidence presented here shows that the time taken by the same algorithm varies so significantly on different CPUs that without knowing the exact model of CPU, it is difficult to compare the results. This is placed in context by analysing a cross-section of experimental results reported in the literature. The reporting of experimental results is sometimes insufficient to allow experiments to be replicated, and in some case is insufficient to support the claims made for the algorithms. New standards for reporting on algorithms results are suggested.

Levels of abstraction in students' understanding of the concept of algorithm : the qualitative perspective

NARCIS (Netherlands)

Perrenet, J.C.; Kaasenbrood, E.J.S.

2006-01-01

In a former, mainly quantitative, study we defined four levels of abstraction in Computer Science students' thinking about the concept of algorithm. We constructed a list of questions about algorithms to measure the answering level as an indication for the thinking level. The answering level

A Faster Algorithm for Computing Motorcycle Graphs

KAUST Repository

Vigneron, Antoine E.; Yan, Lie

2014-01-01

We present a new algorithm for computing motorcycle graphs that runs in (Formula presented.) time for any (Formula presented.), improving on all previously known algorithms. The main application of this result is to computing the straight skeleton of a polygon. It allows us to compute the straight skeleton of a non-degenerate polygon with (Formula presented.) holes in (Formula presented.) expected time. If all input coordinates are (Formula presented.)-bit rational numbers, we can compute the straight skeleton of a (possibly degenerate) polygon with (Formula presented.) holes in (Formula presented.) expected time. In particular, it means that we can compute the straight skeleton of a simple polygon in (Formula presented.) expected time if all input coordinates are (Formula presented.)-bit rationals, while all previously known algorithms have worst-case running time (Formula presented.). © 2014 Springer Science+Business Media New York.

A Faster Algorithm for Computing Motorcycle Graphs

KAUST Repository

Vigneron, Antoine E.

2014-08-29

We present a new algorithm for computing motorcycle graphs that runs in (Formula presented.) time for any (Formula presented.), improving on all previously known algorithms. The main application of this result is to computing the straight skeleton of a polygon. It allows us to compute the straight skeleton of a non-degenerate polygon with (Formula presented.) holes in (Formula presented.) expected time. If all input coordinates are (Formula presented.)-bit rational numbers, we can compute the straight skeleton of a (possibly degenerate) polygon with (Formula presented.) holes in (Formula presented.) expected time. In particular, it means that we can compute the straight skeleton of a simple polygon in (Formula presented.) expected time if all input coordinates are (Formula presented.)-bit rationals, while all previously known algorithms have worst-case running time (Formula presented.). © 2014 Springer Science+Business Media New York.

Approximate Computing Techniques for Iterative Graph Algorithms

Energy Technology Data Exchange (ETDEWEB)

Panyala, Ajay R.; Subasi, Omer; Halappanavar, Mahantesh; Kalyanaraman, Anantharaman; Chavarria Miranda, Daniel G.; Krishnamoorthy, Sriram

2017-12-18

Approximate computing enables processing of large-scale graphs by trading off quality for performance. Approximate computing techniques have become critical not only due to the emergence of parallel architectures but also the availability of large scale datasets enabling data-driven discovery. Using two prototypical graph algorithms, PageRank and community detection, we present several approximate computing heuristics to scale the performance with minimal loss of accuracy. We present several heuristics including loop perforation, data caching, incomplete graph coloring and synchronization, and evaluate their efficiency. We demonstrate performance improvements of up to 83% for PageRank and up to 450x for community detection, with low impact of accuracy for both the algorithms. We expect the proposed approximate techniques will enable scalable graph analytics on data of importance to several applications in science and their subsequent adoption to scale similar graph algorithms.

Linear programming mathematics, theory and algorithms

CERN Document Server

1996-01-01

Linear Programming provides an in-depth look at simplex based as well as the more recent interior point techniques for solving linear programming problems. Starting with a review of the mathematical underpinnings of these approaches, the text provides details of the primal and dual simplex methods with the primal-dual, composite, and steepest edge simplex algorithms. This then is followed by a discussion of interior point techniques, including projective and affine potential reduction, primal and dual affine scaling, and path following algorithms. Also covered is the theory and solution of the linear complementarity problem using both the complementary pivot algorithm and interior point routines. A feature of the book is its early and extensive development and use of duality theory. Audience: The book is written for students in the areas of mathematics, economics, engineering and management science, and professionals who need a sound foundation in the important and dynamic discipline of linear programming.

Transforming Elementary Science Teacher Education by Bridging Formal and Informal Science Education in an Innovative Science Methods Course

Science.gov (United States)

Riedinger, Kelly; Marbach-Ad, Gili; McGinnis, J. Randy; Hestness, Emily; Pease, Rebecca

2011-01-01

We investigated curricular and pedagogical innovations in an undergraduate science methods course for elementary education majors at the University of Maryland. The goals of the innovative elementary science methods course included: improving students' attitudes toward and views of science and science teaching, to model innovative science teaching…

Comparative Results of AIRS/AMSU and CrIS/ATMS Retrievals Using a Scientifically Equivalent Retrieval Algorithm

Science.gov (United States)

Susskind, Joel; Kouvaris, Louis; Iredell, Lena

2016-01-01

The AIRS Science Team Version-6 retrieval algorithm is currently producing high quality level-3 Climate Data Records (CDRs) from AIRS/AMSU which are critical for understanding climate processes. The AIRS Science Team is finalizing an improved Version-7 retrieval algorithm to reprocess all old and future AIRS data. AIRS CDRs should eventually cover the period September 2002 through at least 2020. CrIS/ATMS is the only scheduled follow on to AIRS/AMSU. The objective of this research is to prepare for generation of long term CrIS/ATMS CDRs using a retrieval algorithm that is scientifically equivalent to AIRS/AMSU Version-7.

The NPOESS Preparatory Project Science Data Segment: Brief Overview

Science.gov (United States)

Schweiss, Robert J.; Ho, Evelyn; Ullman, Richard; Samadi, Shahin

2006-01-01

The NPOESS Preparatory Project (NPP) provides remotely-sensed land, ocean, atmospheric, ozone, and sounder data that will serve the meteorological and global climate change scientific communities while also providing risk reduction for the National Polar-orbiting Operational Environmental Satellite System (NPOESS), the U.S. Government s future low-Earth orbiting satellite system monitoring global weather and environmental conditions. NPOESS and NPP are a new era, not only because the sensors will provide unprecedented quality and volume of data but also because it is a joint mission of three federal agencies, NASA, NOAA, and DoD. NASA's primary science role in NPP is to independently assess the quality of the NPP science and environmental data records. Such assessment is critical for making NPOESS products the best that they can be for operational use and ultimately for climate studies. The Science Data Segment (SDS) supports science assessment by assuring the timely provision of NPP data to NASA s science teams organized by climate measurement themes. The SDS breaks down into nine major elements, an input element that receives data from the operational agencies and acts as a buffer, a calibration analysis element, five elements devoted to measurement based quality assessment, an element used to test algorithmic improvements, and an element that provides overall science direction. This paper will describe how the NPP SDS will leverage on NASA experience to provide a mission-reliable research capability for science assessment of NPP derived measurements.

DNA Cryptography and Deep Learning using Genetic Algorithm with NW algorithm for Key Generation.

Science.gov (United States)

Kalsi, Shruti; Kaur, Harleen; Chang, Victor

2017-12-05

Cryptography is not only a science of applying complex mathematics and logic to design strong methods to hide data called as encryption, but also to retrieve the original data back, called decryption. The purpose of cryptography is to transmit a message between a sender and receiver such that an eavesdropper is unable to comprehend it. To accomplish this, not only we need a strong algorithm, but a strong key and a strong concept for encryption and decryption process. We have introduced a concept of DNA Deep Learning Cryptography which is defined as a technique of concealing data in terms of DNA sequence and deep learning. In the cryptographic technique, each alphabet of a letter is converted into a different combination of the four bases, namely; Adenine (A), Cytosine (C), Guanine (G) and Thymine (T), which make up the human deoxyribonucleic acid (DNA). Actual implementations with the DNA don't exceed laboratory level and are expensive. To bring DNA computing on a digital level, easy and effective algorithms are proposed in this paper. In proposed work we have introduced firstly, a method and its implementation for key generation based on the theory of natural selection using Genetic Algorithm with Needleman-Wunsch (NW) algorithm and Secondly, a method for implementation of encryption and decryption based on DNA computing using biological operations Transcription, Translation, DNA Sequencing and Deep Learning.

Globalization and Science Education

Science.gov (United States)

Bencze, J. Lawrence; Carter, Lyn; Chiu, Mei-Hung; Duit, Reinders; Martin, Sonya; Siry, Christina; Krajcik, Joseph; Shin, Namsoo; Choi, Kyunghee; Lee, Hyunju; Kim, Sung-Won

2013-06-01

Processes of globalization have played a major role in economic and cultural change worldwide. More recently, there is a growing literature on rethinking science education research and development from the perspective of globalization. This paper provides a critical overview of the state and future development of science education research from the perspective of globalization. Two facets are given major attention. First, the further development of science education as an international research domain is critically analyzed. It seems that there is a predominance of researchers stemming from countries in which English is the native language or at least a major working language. Second, the significance of rethinking the currently dominant variants of science instruction from the perspectives of economic and cultural globalization is given major attention. On the one hand, it is argued that processes concerning globalization of science education as a research domain need to take into account the richness of the different cultures of science education around the world. At the same time, it is essential to develop ways of science instruction that make students aware of the various advantages, challenges and problems of international economic and cultural globalization.

Benchmark Framework for Mobile Robots Navigation Algorithms

Directory of Open Access Journals (Sweden)

Nelson David Muñoz-Ceballos

2014-01-01

Full Text Available Despite the wide variety of studies and research on mobile robot systems, performance metrics are not often examined. This makes difficult to establish an objective comparison of achievements. In this paper, the navigation of an autonomous mobile robot is evaluated. Several metrics are described. These metrics, collectively, provide an indication of navigation quality, useful for comparing and analyzing navigation algorithms of mobile robots. This method is suggested as an educational tool, which allows the student to optimize the algorithms quality, relating to important aspectsof science, technology and engineering teaching, as energy consumption, optimization and design.

Why They Leave: The Impact of Stereotype Threat on the Attrition of Women and Minorities from Science, Math and Engineering Majors

Science.gov (United States)

Beasley, Maya A.; Fischer, Mary J.

2012-01-01

This paper examines the effects of group performance anxiety on the attrition of women and minorities from science, math, and engineering majors. While past research has relied primarily on the academic deficits and lower socioeconomic status of women and minorities to explain their absence from these fields, we focus on the impact of stereotype…

Solving Multiobjective Optimization Problems Using Artificial Bee Colony Algorithm

Directory of Open Access Journals (Sweden)

Wenping Zou

2011-01-01

Full Text Available Multiobjective optimization has been a difficult problem and focus for research in fields of science and engineering. This paper presents a novel algorithm based on artificial bee colony (ABC to deal with multi-objective optimization problems. ABC is one of the most recently introduced algorithms based on the intelligent foraging behavior of a honey bee swarm. It uses less control parameters, and it can be efficiently used for solving multimodal and multidimensional optimization problems. Our algorithm uses the concept of Pareto dominance to determine the flight direction of a bee, and it maintains nondominated solution vectors which have been found in an external archive. The proposed algorithm is validated using the standard test problems, and simulation results show that the proposed approach is highly competitive and can be considered a viable alternative to solve multi-objective optimization problems.

Algorithms for energy efficiency in wireless sensor networks

Energy Technology Data Exchange (ETDEWEB)

Busse, M

2007-01-21

The recent advances in microsensor and semiconductor technology have opened a new field within computer science: the networking of small-sized sensors which are capable of sensing, processing, and communicating. Such wireless sensor networks offer new applications in the areas of habitat and environment monitoring, disaster control and operation, military and intelligence control, object tracking, video surveillance, traffic control, as well as in health care and home automation. It is likely that the deployed sensors will be battery-powered, which will limit the energy capacity significantly. Thus, energy efficiency becomes one of the main challenges that need to be taken into account, and the design of energy-efficient algorithms is a major contribution of this thesis. As the wireless communication in the network is one of the main energy consumers, we first consider in detail the characteristics of wireless communication. By using the embedded sensor board (ESB) platform recently developed by the Free University of Berlin, we analyze the means of forward error correction and propose an appropriate resync mechanism, which improves the communication between two ESB nodes substantially. Afterwards, we focus on the forwarding of data packets through the network. We present the algorithms energy-efficient forwarding (EEF), lifetime-efficient forwarding (LEF), and energy-efficient aggregation forwarding (EEAF). While EEF is designed to maximize the number of data bytes delivered per energy unit, LEF additionally takes into account the residual energy of forwarding nodes. In so doing, LEF further prolongs the lifetime of the network. Energy savings due to data aggregation and in-network processing are exploited by EEAF. Besides single-link forwarding, in which data packets are sent to only one forwarding node, we also study the impact of multi-link forwarding, which exploits the broadcast characteristics of the wireless medium by sending packets to several (potential

Algorithms for energy efficiency in wireless sensor networks

Energy Technology Data Exchange (ETDEWEB)

Busse, M.

2007-01-21

The recent advances in microsensor and semiconductor technology have opened a new field within computer science: the networking of small-sized sensors which are capable of sensing, processing, and communicating. Such wireless sensor networks offer new applications in the areas of habitat and environment monitoring, disaster control and operation, military and intelligence control, object tracking, video surveillance, traffic control, as well as in health care and home automation. It is likely that the deployed sensors will be battery-powered, which will limit the energy capacity significantly. Thus, energy efficiency becomes one of the main challenges that need to be taken into account, and the design of energy-efficient algorithms is a major contribution of this thesis. As the wireless communication in the network is one of the main energy consumers, we first consider in detail the characteristics of wireless communication. By using the embedded sensor board (ESB) platform recently developed by the Free University of Berlin, we analyze the means of forward error correction and propose an appropriate resync mechanism, which improves the communication between two ESB nodes substantially. Afterwards, we focus on the forwarding of data packets through the network. We present the algorithms energy-efficient forwarding (EEF), lifetime-efficient forwarding (LEF), and energy-efficient aggregation forwarding (EEAF). While EEF is designed to maximize the number of data bytes delivered per energy unit, LEF additionally takes into account the residual energy of forwarding nodes. In so doing, LEF further prolongs the lifetime of the network. Energy savings due to data aggregation and in-network processing are exploited by EEAF. Besides single-link forwarding, in which data packets are sent to only one forwarding node, we also study the impact of multi-link forwarding, which exploits the broadcast characteristics of the wireless medium by sending packets to several (potential

Examining Preservice Science Teacher Understanding of Nature of Science: Discriminating Variables on the Aspects of Nature of Science

Science.gov (United States)

Jones, William I.

This study examined the understanding of nature of science among participants in their final year of a 4-year undergraduate teacher education program at a Midwest liberal arts university. The Logic Model Process was used as an integrative framework to focus the collection, organization, analysis, and interpretation of the data for the purpose of (1) describing participant understanding of NOS and (2) to identify participant characteristics and teacher education program features related to those understandings. The Views of Nature of Science Questionnaire form C (VNOS-C) was used to survey participant understanding of 7 target aspects of Nature of Science (NOS). A rubric was developed from a review of the literature to categorize and score participant understanding of the target aspects of NOS. Participants' high school and college transcripts, planning guides for their respective teacher education program majors, and science content and science teaching methods course syllabi were examined to identify and categorize participant characteristics and teacher education program features. The R software (R Project for Statistical Computing, 2010) was used to conduct an exploratory analysis to determine correlations of the antecedent and transaction predictor variables with participants' scores on the 7 target aspects of NOS. Fourteen participant characteristics and teacher education program features were moderately and significantly ( p Middle Childhood with a science concentration program major or in the Adolescent/Young Adult Science Education program major were more likely to have an informed understanding on each of the 7 target aspects of NOS. Analyses of the planning guides and the course syllabi in each teacher education program major revealed differences between the program majors that may account for the results.

Algorithms for Calculating Alternating Infinite Series

International Nuclear Information System (INIS)

Garcia, Hector Luna; Garcia, Luz Maria

2015-01-01

This paper are presented novel algorithms for exact limits of a broad class of infinite alternating series. Many of these series are found in physics and other branches of science and their exact values found for us are in complete agreement with the values obtained by other authors. Finally, these simple methods are very powerful in calculating the limits of many series as shown by the examples

Journal of Earth System Science | Indian Academy of Sciences

Indian Academy of Sciences (India)

Home; Journals; Journal of Earth System Science; Volume 124; Issue 5 ... water cycles and predict the effect of climate change on terrestrial ecosystems, it is ... Application of ANN and fuzzy logic algorithms for streamflow modelling of Savitri .... Influence of nutrient input on the trophic state of a tropical brackish water lagoon.

Fellowship | Indian Academy of Sciences

Indian Academy of Sciences (India)

Duke). Date of birth: 24 May 1962. Specialization: Algorithms (Sequential & Parallel), Probabilistic Analysis & Randomization and Computational Geometry Address: Department of Computer Science & Engineering, Indian Institute of Technology, ...

Optimization in optical systems revisited: Beyond genetic algorithms

Science.gov (United States)

Gagnon, Denis; Dumont, Joey; Dubé, Louis

2013-05-01

Designing integrated photonic devices such as waveguides, beam-splitters and beam-shapers often requires optimization of a cost function over a large solution space. Metaheuristics - algorithms based on empirical rules for exploring the solution space - are specifically tailored to those problems. One of the most widely used metaheuristics is the standard genetic algorithm (SGA), based on the evolution of a population of candidate solutions. However, the stochastic nature of the SGA sometimes prevents access to the optimal solution. Our goal is to show that a parallel tabu search (PTS) algorithm is more suited to optimization problems in general, and to photonics in particular. PTS is based on several search processes using a pool of diversified initial solutions. To assess the performance of both algorithms (SGA and PTS), we consider an integrated photonics design problem, the generation of arbitrary beam profiles using a two-dimensional waveguide-based dielectric structure. The authors acknowledge financial support from the Natural Sciences and Engineering Research Council of Canada (NSERC).

Computational Science and Innovation

International Nuclear Information System (INIS)

Dean, David Jarvis

2011-01-01

Simulations - utilizing computers to solve complicated science and engineering problems - are a key ingredient of modern science. The U.S. Department of Energy (DOE) is a world leader in the development of high-performance computing (HPC), the development of applied math and algorithms that utilize the full potential of HPC platforms, and the application of computing to science and engineering problems. An interesting general question is whether the DOE can strategically utilize its capability in simulations to advance innovation more broadly. In this article, I will argue that this is certainly possible.

Development and Implementation of an Integrated Science Course for Elementary Eduation Majors

Science.gov (United States)

Gunter, Mickey E.; Gammon, Steven D.; Kearney, Robert J.; Waller, Brenda E.; Oliver, David J.

1997-02-01

Currently the scientific community is trying to increase the general populationapos;s knowledge of science. These efforts stem from the fact that the citizenry needs a better understanding of scientific knowledge to make informed decisions on many issues of current concern. The problem of scientific illiteracy begins in grade school and can be traced to inadequate exposure to science and scientific thinking during the preparation of K - 8 teachers. Typically preservice elementary teachers are required to take only one or two disconnected science courses to obtain their teaching certificates. Also, introductory science courses are often large and impersonal, with the result that while students pass the courses, they may learn very little and retain even less.

Mars: A Freshmen Year Seminar of Science and Science-fiction

Science.gov (United States)

Svec, Michael; Moffett, D. A.; Winiski, M.

2013-06-01

"Mars: On the shoulder of giants" is a freshmen year seminar developed collaboratively between the physics, education, and center for teaching and learning. This course focuses on how scientific knowledge is developed through the lens of our changing view of Mars throughout history. Analyses of current studies of Mars are juxtaposed against historical understanding and perceptions of the planet found in scientific and popular literature of the day, as well as the movies. Kim Stanley Robinson’s "Red Mars" provides a unifying story throughout the course complimented by Fredrick Taylor’s "The Scientific Exploration of Mars" and Hartmann’s "A Traveler’s Guide to Mars." Based on the three-years of experience, the authors advocate the use of the speculative science-fiction novel and argue for its use in high school and undergraduate courses including those for science majors. Many of the students who selected this seminar went on to major in science and in subsequent interviews discussed the influence of science fiction on their decision to major in science. Science fiction provided story, science, and speculation that became a rich medium for critical-thinking skills and critical literacy. Student reflections indicated that science fiction served as a reminder of why they study science, a source for imagination, and exploration of science as a human endeavor. Based on this experience, we propose five elements for selecting science-fiction for inclusion in science classes: 1) Provides a deep description of the science content or technologies, 2) Describes science and technologies are plausible or accurate to the time period, 3) Contains a novum or plausible innovation that plays a key element in the speculation, 4) Exploration of the impact on society or humanity, and, 5) Shows science and technology as human endeavors.

Separated Representations and Fast Algorithms for Materials Science

Science.gov (United States)

2007-10-29

Quantum Chemisty , 127 (1999), pp. 143–269. [28] A. Smilde, R. Bro, and P. Geladi, Multi-way Analysis. Applications in the Chemical Sciences, John...Advances in highly correlated approaches. Advances in Quantum Chemisty , 127:143–269, 1999. [58] Age Smilde, Rasmus Bro, and Paul Geladi. Multi-way Analysis

Resonance – Journal of Science Education | Indian Academy of ...

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education; Volume 12; Issue 4. Decoding Reed–Solomon Codes Using Euclid's Algorithm. Priti Shankar. General Article Volume 12 ... Author Affiliations. Priti Shankar1. Department of Computer Science and Automation, Indian Institute of Science, Bangalore 560 012, India.

Creating Engaging Online Learning Material with the JSAV JavaScript Algorithm Visualization Library

Science.gov (United States)

Karavirta, Ville; Shaffer, Clifford A.

2016-01-01

Data Structures and Algorithms are a central part of Computer Science. Due to their abstract and dynamic nature, they are a difficult topic to learn for many students. To alleviate these learning difficulties, instructors have turned to algorithm visualizations (AV) and AV systems. Research has shown that especially engaging AVs can have an impact…

Plagiarism Detection Algorithm for Source Code in Computer Science Education

Science.gov (United States)

Liu, Xin; Xu, Chan; Ouyang, Boyu

2015-01-01

Nowadays, computer programming is getting more necessary in the course of program design in college education. However, the trick of plagiarizing plus a little modification exists among some students' home works. It's not easy for teachers to judge if there's plagiarizing in source code or not. Traditional detection algorithms cannot fit this…

Women planning to major in computer science: Who are they and what makes them unique?

Science.gov (United States)

Lehman, Kathleen J.; Sax, Linda J.; Zimmerman, Hilary B.

2016-12-01

Despite the current growing popularity of the computer science (CS) major, women remain sorely underrepresented in the field, continuing to earn only 18% of bachelor's degrees. Understanding women's low rates of participation in CS is important given that the demand for individuals with CS training has grown sharply in recent years. Attracting and retaining more women to high-paying fields like CS may also help narrow the gender pay gap. Further, it is important that women participate in developing new technology so that technology advances serve the needs of both women and men. This paper explores the background characteristics, career aspirations, and self-perceptions of 1636 female first-year college students in the United States who intend to major in CS and compares them with 4402 male CS aspirants as well as with 26,642 women planning to major in other STEM sub-fields. The findings reveal a unique profile of women who pursue the CS major and notes many significant differences between men and women in CS and between women in CS and those in other STEM fields. For instance, women in CS tend to earn lower high school grades than women in other STEM fields, but earn higher SAT verbal scores. They also rate themselves higher than men in CS and women in other STEM fields on measures of their artistic ability, but rate themselves lower on other self-ratings, including academic and leadership ability. Further, women in CS are more likely to be undecided in their career plans than men in CS and women in other STEM fields. Understanding the unique characteristics of women in CS will help inform policies and recruitment programs designed to address the gender gap in computing.

Value-added Data Services at the Goddard Earth Sciences Data and Information Services Center

Science.gov (United States)

Leptoukh, G. G.; Alcott, G. T.; Kempler, S. J.; Lynnes, C. S.; Vollmer, B. E.

2004-05-01

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), in addition to serving the Earth Science community as one of the major Distributed Active Archive Centers (DAACs), provides much more than just data. Among the value-added services available to general users are subsetting data spatially and/or by parameter, online analysis (to avoid downloading unnecessary all the data), and assistance in obtaining data from other centers. Services available to data producers and high-volume users include consulting on building new products with standard formats and metadata and construction of data management systems. A particularly useful service is data processing at the DISC (i.e., close to the input data) with the users' algorithms. This can take a number of different forms: as a configuration-managed algorithm within the main processing stream; as a stand-alone program next to the on-line data storage; as build-it-yourself code within the Near-Archive Data Mining (NADM) system; or as an on-the-fly analysis with simple algorithms embedded into the web-based tools. Partnerships between the GES DISC and scientists, both producers and users, allow the scientists concentrate on science, while the GES DISC handles the of data management, e.g., formats, integration and data processing. The existing data management infrastructure at the GES DISC supports a wide spectrum of options: from simple data support to sophisticated on-line analysis tools, producing economies of scale and rapid time-to-deploy. At the same time, such partnerships allow the GES DISC to serve the user community more efficiently and to better prioritize on-line holdings. Several examples of successful partnerships are described in the presentation.

Metaheuristic algorithms for building Covering Arrays: A review

Directory of Open Access Journals (Sweden)

Jimena Adriana Timaná-Peña

2016-09-01

Full Text Available Covering Arrays (CA are mathematical objects used in the functional testing of software components. They enable the testing of all interactions of a given size of input parameters in a procedure, function, or logical unit in general, using the minimum number of test cases. Building CA is a complex task (NP-complete problem that involves lengthy execution times and high computational loads. The most effective methods for building CAs are algebraic, Greedy, and metaheuristic-based. The latter have reported the best results to date. This paper presents a description of the major contributions made by a selection of different metaheuristics, including simulated annealing, tabu search, genetic algorithms, ant colony algorithms, particle swarm algorithms, and harmony search algorithms. It is worth noting that simulated annealing-based algorithms have evolved as the most competitive, and currently form the state of the art.

A Chinese text classification system based on Naive Bayes algorithm

Directory of Open Access Journals (Sweden)

Cui Wei

2016-01-01

Full Text Available In this paper, aiming at the characteristics of Chinese text classification, using the ICTCLAS(Chinese lexical analysis system of Chinese academy of sciences for document segmentation, and for data cleaning and filtering the Stop words, using the information gain and document frequency feature selection algorithm to document feature selection. Based on this, based on the Naive Bayesian algorithm implemented text classifier , and use Chinese corpus of Fudan University has carried on the experiment and analysis on the system.

Practical mathematical optimization basic optimization theory and gradient-based algorithms

CERN Document Server

Snyman, Jan A

2018-01-01

This textbook presents a wide range of tools for a course in mathematical optimization for upper undergraduate and graduate students in mathematics, engineering, computer science, and other applied sciences. Basic optimization principles are presented with emphasis on gradient-based numerical optimization strategies and algorithms for solving both smooth and noisy discontinuous optimization problems. Attention is also paid to the difficulties of expense of function evaluations and the existence of multiple minima that often unnecessarily inhibit the use of gradient-based methods. This second edition addresses further advancements of gradient-only optimization strategies to handle discontinuities in objective functions. New chapters discuss the construction of surrogate models as well as new gradient-only solution strategies and numerical optimization using Python. A special Python module is electronically available (via springerlink) that makes the new algorithms featured in the text easily accessible and dir...

Algorithms for Academic Search and Recommendation Systems

DEFF Research Database (Denmark)

Amolochitis, Emmanouil

2014-01-01

are part of a developed Movie Recommendation system, the first such system to be commercially deployed in Greece by a major Triple Play services provider. In the third part of the work we present the design of a quantitative association rule mining algorithm. The introduced mining algorithm processes......In this work we present novel algorithms for academic search, recommendation and association rules mining. In the first part of the work we introduce a novel hierarchical heuristic scheme for re-ranking academic publications. The scheme is based on the hierarchical combination of a custom...... implementation of the term frequency heuristic, a time-depreciated citation score and a graph-theoretic computed score that relates the paper’s index terms with each other. On the second part we describe the design of hybrid recommender ensemble (user, item and content based). The newly introduced algorithms...

Science and Community Engagement: Connecting Science Students with the Community

Science.gov (United States)

Lancor, Rachael; Schiebel, Amy

2018-01-01

In this article we describe a course on science outreach that was developed as part of our college's goal that all students participate in a meaningful community engagement experience. The Science & Community Engagement course provides a way for students with science or science-related majors to learn how to effectively communicate scientific…

Information dynamics algorithm for detecting communities in networks

Science.gov (United States)

Massaro, Emanuele; Bagnoli, Franco; Guazzini, Andrea; Lió, Pietro

2012-11-01

The problem of community detection is relevant in many scientific disciplines, from social science to statistical physics. Given the impact of community detection in many areas, such as psychology and social sciences, we have addressed the issue of modifying existing well performing algorithms by incorporating elements of the domain application fields, i.e. domain-inspired. We have focused on a psychology and social network-inspired approach which may be useful for further strengthening the link between social network studies and mathematics of community detection. Here we introduce a community-detection algorithm derived from the van Dongen's Markov Cluster algorithm (MCL) method [4] by considering networks' nodes as agents capable to take decisions. In this framework we have introduced a memory factor to mimic a typical human behavior such as the oblivion effect. The method is based on information diffusion and it includes a non-linear processing phase. We test our method on two classical community benchmark and on computer generated networks with known community structure. Our approach has three important features: the capacity of detecting overlapping communities, the capability of identifying communities from an individual point of view and the fine tuning the community detectability with respect to prior knowledge of the data. Finally we discuss how to use a Shannon entropy measure for parameter estimation in complex networks.

Improved algorithm for solving nonlinear parabolized stability equations

Science.gov (United States)

Zhao, Lei; Zhang, Cun-bo; Liu, Jian-xin; Luo, Ji-sheng

2016-08-01

Due to its high computational efficiency and ability to consider nonparallel and nonlinear effects, nonlinear parabolized stability equations (NPSE) approach has been widely used to study the stability and transition mechanisms. However, it often diverges in hypersonic boundary layers when the amplitude of disturbance reaches a certain level. In this study, an improved algorithm for solving NPSE is developed. In this algorithm, the mean flow distortion is included into the linear operator instead of into the nonlinear forcing terms in NPSE. An under-relaxation factor for computing the nonlinear terms is introduced during the iteration process to guarantee the robustness of the algorithm. Two case studies, the nonlinear development of stationary crossflow vortices and the fundamental resonance of the second mode disturbance in hypersonic boundary layers, are presented to validate the proposed algorithm for NPSE. Results from direct numerical simulation (DNS) are regarded as the baseline for comparison. Good agreement can be found between the proposed algorithm and DNS, which indicates the great potential of the proposed method on studying the crossflow and streamwise instability in hypersonic boundary layers. Project supported by the National Natural Science Foundation of China (Grant Nos. 11332007 and 11402167).

Teaching Science as Science Is Practiced: Opportunities and Limits for Enhancing Preservice Elementary Teachers' Self-Efficacy for Science and Science Teaching

Science.gov (United States)

Avery, Leanne M.; Meyer, Daniel Z.

2012-01-01

Science teaching in elementary schools, or the lack thereof, continues to be an area of concern and criticism. Preservice elementary teachers' lack of confidence in teaching science is a major part of this problem. In this mixed-methods study, we report the impacts of an inquiry-based science course on preservice elementary teachers' self-efficacy…

Citizen science projects for non-science astronomy students

OpenAIRE

Barmby, Pauline; Gallagher, S. C.; Cami, J.

2014-01-01

A poster from the 2011 Western Conference on Science Education, describing the use of citizen science project Galaxy Zoo in a non-majors astronomy course. Lots more on this topic at https://www.zooniverse.org/education  

Efficient Implementation of Nested-Loop Multimedia Algorithms

Directory of Open Access Journals (Sweden)

Kittitornkun Surin

2001-01-01

Full Text Available A novel dependence graph representation called the multiple-order dependence graph for nested-loop formulated multimedia signal processing algorithms is proposed. It allows a concise representation of an entire family of dependence graphs. This powerful representation facilitates the development of innovative implementation approach for nested-loop formulated multimedia algorithms such as motion estimation, matrix-matrix product, 2D linear transform, and others. In particular, algebraic linear mapping (assignment and scheduling methodology can be applied to implement such algorithms on an array of simple-processing elements. The feasibility of this new approach is demonstrated in three major target architectures: application-specific integrated circuit (ASIC, field programmable gate array (FPGA, and a programmable clustered VLIW processor.

The GOLD Science Data Center - Algorithm Heritage, Data Product Descriptions and User Services

Science.gov (United States)

Lumpe, J. D.; Foroosh, H.; Eastes, R.; Krywonos, A.; Evans, J. S.; Burns, A. G.; Strickland, D. J.; Daniell, R. E.; England, S.; Solomon, S. C.; McClintock, W. E.; Anderson, D. N.

2013-12-01

The Global-scale Observations of the Limb and Disk (GOLD) instrument is an imaging spectrograph to be launched onboard a commercial communications satellite in 2017. From its vantage point in geosynchronous orbit GOLD will image the Earth in the far-ultraviolet from 132 to 162 nm. The instrument consists of two independent optical channels, allowing for simultaneous implementation of multiple measurement sequences with different temporal sampling and spectral resolution. In addition to continuously scanning the disk of the Earth, GOLD will also perform routine limb scan and stellar occultation measurements. These measurements will be used to retrieve a variety of data products characterizing the temperature and composition of the thermosphere-ionosphere, and their response to geomagnetic storms and solar forcing. Primary data products include: daytime neutral temperatures near 160 km altitude; daytime O/N2 column density ratios; nighttime peak electron density; thermospheric O2 density profiles (day and night); daytime exospheric neutral temperature on the limb; atmospheric tides from temperature perturbations; and the location and evolution of ionospheric bubbles. GOLD data will be processed at the Science Data Center (SDC) located at the University of Central Florida. The SDC will also serve as the primary gateway for distribution of GOLD data products to end-users. In this talk we summarize the heritage and theoretical basis of the GOLD retrieval algorithms and describe the full range of GOLD data products that will be available at the SDC, including estimates of data latency and quality.

Parallel algorithms for geometric connected component labeling on a hypercube multiprocessor

Science.gov (United States)

Belkhale, K. P.; Banerjee, P.

1992-01-01

Different algorithms for the geometric connected component labeling (GCCL) problem are defined each of which involves d stages of message passing, for a d-dimensional hypercube. The major idea is that in each stage a hypercube multiprocessor increases its knowledge of domain. The algorithms under consideration include the QUAD algorithm for small number of processors and the Overlap Quad algorithm for large number of processors, subject to the locality of the connected sets. These algorithms differ in their run time, memory requirements, and message complexity. They were implemented on an Intel iPSC2/D4/MX hypercube.

Structure-preserving algorithms for oscillatory differential equations II

CERN Document Server

Wu, Xinyuan; Shi, Wei

2015-01-01

This book describes a variety of highly effective and efficient structure-preserving algorithms for second-order oscillatory differential equations. Such systems arise in many branches of science and engineering, and the examples in the book include systems from quantum physics, celestial mechanics and electronics. To accurately simulate the true behavior of such systems, a numerical algorithm must preserve as much as possible their key structural properties: time-reversibility, oscillation, symplecticity, and energy and momentum conservation. The book describes novel advances in RKN methods, ERKN methods, Filon-type asymptotic methods, AVF methods, and trigonometric Fourier collocation methods.  The accuracy and efficiency of each of these algorithms are tested via careful numerical simulations, and their structure-preserving properties are rigorously established by theoretical analysis. The book also gives insights into the practical implementation of the methods. This book is intended for engineers and sc...

Optimisation of Hidden Markov Model using Baum–Welch algorithm

Indian Academy of Sciences (India)

Home; Journals; Journal of Earth System Science; Volume 126; Issue 1. Optimisation of Hidden Markov Model using Baum–Welch algorithm for prediction of maximum and minimum temperature over Indian Himalaya. J C Joshi Tankeshwar Kumar Sunita Srivastava Divya Sachdeva. Volume 126 Issue 1 February 2017 ...

Algorithms and architectures of artificial intelligence

CERN Document Server

Tyugu, E

2007-01-01

This book gives an overview of methods developed in artificial intelligence for search, learning, problem solving and decision-making. It gives an overview of algorithms and architectures of artificial intelligence that have reached the degree of maturity when a method can be presented as an algorithm, or when a well-defined architecture is known, e.g. in neural nets and intelligent agents. It can be used as a handbook for a wide audience of application developers who are interested in using artificial intelligence methods in their software products. Parts of the text are rather independent, so that one can look into the index and go directly to a description of a method presented in the form of an abstract algorithm or an architectural solution. The book can be used also as a textbook for a course in applied artificial intelligence. Exercises on the subject are added at the end of each chapter. Neither programming skills nor specific knowledge in computer science are expected from the reader. However, some p...

AntStar: Enhancing Optimization Problems by Integrating an Ant System and A⁎ Algorithm

Directory of Open Access Journals (Sweden)

Mohammed Faisal

2016-01-01

Full Text Available Recently, nature-inspired techniques have become valuable to many intelligent systems in different fields of technology and science. Among these techniques, Ant Systems (AS have become a valuable technique for intelligent systems in different fields. AS is a computational system inspired by the foraging behavior of ants and intended to solve practical optimization problems. In this paper, we introduce the AntStar algorithm, which is swarm intelligence based. AntStar enhances the optimization and performance of an AS by integrating the AS and A⁎ algorithm. Applying the AntStar algorithm to the single-source shortest-path problem has been done to ensure the efficiency of the proposed AntStar algorithm. The experimental result of the proposed algorithm illustrated the robustness and accuracy of the AntStar algorithm.

a pyramid algorithm for the haar discrete wavelet packet transform

African Journals Online (AJOL)

PROF EKWUEME

computer-aided signal processing of non-stationary signals, this paper develops a pyramid algorithm for the discrete wavelet packet ... Edith T. Luhanga, School of Computational and Communication Sciences and Engineering, Nelson Mandela African. Institute of ..... Mathematics, Washington University. 134. EDITH T.

Journal of Earth System Science | Indian Academy of Sciences

Indian Academy of Sciences (India)

Home; Journals; Journal of Earth System Science; Volume 109; Issue 4. Volume 109, Issue 4. December 2000, pages 393-551. pp 393-394. Editorial · V K Gaur · More Details Fulltext PDF. pp 395-405. Analysis of pathfinder SST algorithm for global and regional conditions · Ajoy Kumar P Minnett G Podesta R Evans K ...

Using Infiniscope Exploratory Activities in an Online Astronomy Lab Course for Non-Science Majors

Science.gov (United States)

Knierman, Karen; Anbar, Ariel; Tamer, A. Joseph; Hunsley, Diana; Young, Patrick A.; Center for Education Through eXploration

2018-01-01

With the growth of online astronomy courses, it has become necessary to design different strategies for students to engage meaningfully with astronomy content. In contrast to some of the previously designed “cookbook”-style lab exercises, the strategy of these Infiniscope activities is to provide an experience where the students explore and discover the content for themselves. The Infiniscope project was created by ASU’s School of Earth and Space Exploration and NASA’s Science Mission Directorate as part of the NASA Exploration Connection project. As part of this project, online activities on topics such as asteroids and Kuiper Belt objects, eclipses, and Kepler’s Laws were designed and created for middle school (grades 6-8) and informal education settings. This poster discusses adapting these activities to the undergraduate non-science major setting. In fall 2017, the Infiniscope activities, such as Small Worlds and Kepler’s Laws, will be incorporated into an Arizona State University online astronomy course, AST 113, which is the laboratory component for the Introduction to Solar System Astronomy course sequence. This course typically enrolls about 800-900 students per semester with a combination of students who are online only as well as those who also take in person classes. In this type of class, we cannot have any in-person required sessions and all content must be delivered online asynchronously. The use of the Infiniscope exploratory exercises will provide students with the ability to use NASA data in a hands-on manner to discover the solar system for themselves.

Parallel asynchronous systems and image processing algorithms

Science.gov (United States)

Coon, D. D.; Perera, A. G. U.

1989-01-01

A new hardware approach to implementation of image processing algorithms is described. The approach is based on silicon devices which would permit an independent analog processing channel to be dedicated to evey pixel. A laminar architecture consisting of a stack of planar arrays of the device would form a two-dimensional array processor with a 2-D array of inputs located directly behind a focal plane detector array. A 2-D image data stream would propagate in neuronlike asynchronous pulse coded form through the laminar processor. Such systems would integrate image acquisition and image processing. Acquisition and processing would be performed concurrently as in natural vision systems. The research is aimed at implementation of algorithms, such as the intensity dependent summation algorithm and pyramid processing structures, which are motivated by the operation of natural vision systems. Implementation of natural vision algorithms would benefit from the use of neuronlike information coding and the laminar, 2-D parallel, vision system type architecture. Besides providing a neural network framework for implementation of natural vision algorithms, a 2-D parallel approach could eliminate the serial bottleneck of conventional processing systems. Conversion to serial format would occur only after raw intensity data has been substantially processed. An interesting challenge arises from the fact that the mathematical formulation of natural vision algorithms does not specify the means of implementation, so that hardware implementation poses intriguing questions involving vision science.

Efficient Parallel Algorithm For Direct Numerical Simulation of Turbulent Flows

Science.gov (United States)

Moitra, Stuti; Gatski, Thomas B.

1997-01-01

A distributed algorithm for a high-order-accurate finite-difference approach to the direct numerical simulation (DNS) of transition and turbulence in compressible flows is described. This work has two major objectives. The first objective is to demonstrate that parallel and distributed-memory machines can be successfully and efficiently used to solve computationally intensive and input/output intensive algorithms of the DNS class. The second objective is to show that the computational complexity involved in solving the tridiagonal systems inherent in the DNS algorithm can be reduced by algorithm innovations that obviate the need to use a parallelized tridiagonal solver.

Deductive Synthesis of the Unification Algorithm,

Science.gov (United States)

1981-06-01

DEDUCTIVE SYNTHESIS OF THE I - UNIFICATION ALGORITHM Zohar Manna Richard Waldinger I F? Computer Science Department Artificial Intelligence Center...theorem proving," Artificial Intelligence Journal, Vol. 9, No. 1, pp. 1-35. Boyer, R. S. and J S. Moore [Jan. 19751, "Proving theorems about LISP...d’Intelligence Artificielle , U.E.R. de Luminy, Universit6 d’ Aix-Marseille II. Green, C. C. [May 1969], "Application of theorem proving to problem

PSO-Based Algorithm Applied to Quadcopter Micro Air Vehicle Controller Design

Directory of Open Access Journals (Sweden)

Huu-Khoa Tran

2016-09-01

Full Text Available Due to the rapid development of science and technology in recent times, many effective controllers are designed and applied successfully to complicated systems. The significant task of controller design is to determine optimized control gains in a short period of time. With this purpose in mind, a combination of the particle swarm optimization (PSO-based algorithm and the evolutionary programming (EP algorithm is introduced in this article. The benefit of this integration algorithm is the creation of new best-parameters for control design schemes. The proposed controller designs are then demonstrated to have the best performance for nonlinear micro air vehicle models.

Simultaneous reconstruction of temperature distribution and radiative properties in participating media using a hybrid LSQR-PSO algorithm

Science.gov (United States)

Niu, Chun-Yang; Qi, Hong; Huang, Xing; Ruan, Li-Ming; Wang, Wei; Tan, He-Ping

2015-11-01

A hybrid least-square QR decomposition (LSQR)-particle swarm optimization (LSQR-PSO) algorithm was developed to estimate the three-dimensional (3D) temperature distributions and absorption coefficients simultaneously. The outgoing radiative intensities at the boundary surface of the absorbing media were simulated by the line-of-sight (LOS) method, which served as the input for the inverse analysis. The retrieval results showed that the 3D temperature distributions of the participating media with known radiative properties could be retrieved accurately using the LSQR algorithm, even with noisy data. For the participating media with unknown radiative properties, the 3D temperature distributions and absorption coefficients could be retrieved accurately using the LSQR-PSO algorithm even with measurement errors. It was also found that the temperature field could be estimated more accurately than the absorption coefficients. In order to gain insight into the effects on the accuracy of temperature distribution reconstruction, the selection of the detection direction and the angle between two detection directions was also analyzed. Project supported by the Major National Scientific Instruments and Equipment Development Special Foundation of China (Grant No. 51327803), the National Natural Science Foundation of China (Grant No. 51476043), and the Fund of Tianjin Key Laboratory of Civil Aircraft Airworthiness and Maintenance in Civil Aviation University of China.

Major Challenges for the Modern Chemistry in Particular and Science in General.

Science.gov (United States)

Uskokovíc, Vuk

2010-11-01

In the past few hundred years, science has exerted an enormous influence on the way the world appears to human observers. Despite phenomenal accomplishments of science, science nowadays faces numerous challenges that threaten its continued success. As scientific inventions become embedded within human societies, the challenges are further multiplied. In this critical review, some of the critical challenges for the field of modern chemistry are discussed, including: (a) interlinking theoretical knowledge and experimental approaches; (b) implementing the principles of sustainability at the roots of the chemical design; (c) defining science from a philosophical perspective that acknowledges both pragmatic and realistic aspects thereof; (d) instigating interdisciplinary research; (e) learning to recognize and appreciate the aesthetic aspects of scientific knowledge and methodology, and promote truly inspiring education in chemistry. In the conclusion, I recapitulate that the evolution of human knowledge inherently depends upon our ability to adopt creative problem-solving attitudes, and that challenges will always be present within the scope of scientific interests.

Journal of Applied Sciences and Environmental Management - Vol ...

African Journals Online (AJOL)

Journal of Applied Sciences and Environmental Management. ... AFRICAN JOURNALS ONLINE (AJOL) · Journals · Advanced Search · USING ... Journal of Applied Sciences and Environmental Management - Vol 22, No 4 (2018) ... Evaluating the effect of mobility speed on the performance of three handover algorithms in ...

Exploring the undergraduate experience of Latina students in Science, Technology, Engineering, and Mathematics (STEM) majors: Motivators and strategies for achieving baccalaureate attainment

Science.gov (United States)

Carbajal, Sandy C.

Drawing from Latino/a Critical Race Theory and the related Community Cultural Wealth (CCW) model, I concentrate on three forms of CCW---aspirational, navigational, and resistance capital---for this qualitative study on the undergraduate experience of Latina students in Science, Technology, Engineering, and Mathematics (STEM) majors, focusing on strategies and achieving baccalaureate attainment. I interviewed ten Latina students and asked them questions regarding their educational experiences in STEM majors, what contributed to their degree completion, and the strategies they employed for achieving baccalaureate attainment. I identified and described six themes within the study (the underrepresentation of Latinas in STEM majors, the lack of preparation by academic programs for upper division courses, motivators, involvement, time management, and support networks) that, when combined, contributed to participants' degree attainment. This study concludes with implications for policy and practice that would allow universities to better assist Latinas in STEM majors to achieve baccalaureate attainment.

Preemptive Online Scheduling: Optimal Algorithms for All Speeds

Czech Academy of Sciences Publication Activity Database

Ebenlendr, Tomáš; Jawor, W.; Sgall, Jiří

2009-01-01

Roč. 53, č. 4 (2009), s. 504-522 ISSN 0178-4617 R&D Projects: GA MŠk(CZ) 1M0545; GA ČR GA201/05/0124; GA AV ČR IAA1019401 Institutional research plan: CEZ:AV0Z10190503 Keywords : anline algorithms * scheduling Subject RIV: IN - Informatics, Computer Science Impact factor: 0.917, year: 2009

A simple algorithm for measuring particle size distributions on an uneven background from TEM images

DEFF Research Database (Denmark)

Gontard, Lionel Cervera; Ozkaya, Dogan; Dunin-Borkowski, Rafal E.

2011-01-01

Nanoparticles have a wide range of applications in science and technology. Their sizes are often measured using transmission electron microscopy (TEM) or X-ray diffraction. Here, we describe a simple computer algorithm for measuring particle size distributions from TEM images in the presence of a...... application to images of heterogeneous catalysts is presented.......Nanoparticles have a wide range of applications in science and technology. Their sizes are often measured using transmission electron microscopy (TEM) or X-ray diffraction. Here, we describe a simple computer algorithm for measuring particle size distributions from TEM images in the presence...

A generic algorithm for layout of biological networks.

Science.gov (United States)

Schreiber, Falk; Dwyer, Tim; Marriott, Kim; Wybrow, Michael

2009-11-12

Biological networks are widely used to represent processes in biological systems and to capture interactions and dependencies between biological entities. Their size and complexity is steadily increasing due to the ongoing growth of knowledge in the life sciences. To aid understanding of biological networks several algorithms for laying out and graphically representing networks and network analysis results have been developed. However, current algorithms are specialized to particular layout styles and therefore different algorithms are required for each kind of network and/or style of layout. This increases implementation effort and means that new algorithms must be developed for new layout styles. Furthermore, additional effort is necessary to compose different layout conventions in the same diagram. Also the user cannot usually customize the placement of nodes to tailor the layout to their particular need or task and there is little support for interactive network exploration. We present a novel algorithm to visualize different biological networks and network analysis results in meaningful ways depending on network types and analysis outcome. Our method is based on constrained graph layout and we demonstrate how it can handle the drawing conventions used in biological networks. The presented algorithm offers the ability to produce many of the fundamental popular drawing styles while allowing the exibility of constraints to further tailor these layouts.

Algebraic dynamics algorithm: Numerical comparison with Runge-Kutta algorithm and symplectic geometric algorithm

Institute of Scientific and Technical Information of China (English)

WANG ShunJin; ZHANG Hua

2007-01-01

Based on the exact analytical solution of ordinary differential equations,a truncation of the Taylor series of the exact solution to the Nth order leads to the Nth order algebraic dynamics algorithm.A detailed numerical comparison is presented with Runge-Kutta algorithm and symplectic geometric algorithm for 12 test models.The results show that the algebraic dynamics algorithm can better preserve both geometrical and dynamical fidelity of a dynamical system at a controllable precision,and it can solve the problem of algorithm-induced dissipation for the Runge-Kutta algorithm and the problem of algorithm-induced phase shift for the symplectic geometric algorithm.

Algebraic dynamics algorithm:Numerical comparison with Runge-Kutta algorithm and symplectic geometric algorithm

Institute of Scientific and Technical Information of China (English)

2007-01-01

Based on the exact analytical solution of ordinary differential equations, a truncation of the Taylor series of the exact solution to the Nth order leads to the Nth order algebraic dynamics algorithm. A detailed numerical comparison is presented with Runge-Kutta algorithm and symplectic geometric algorithm for 12 test models. The results show that the algebraic dynamics algorithm can better preserve both geometrical and dynamical fidelity of a dynamical system at a controllable precision, and it can solve the problem of algorithm-induced dissipation for the Runge-Kutta algorithm and the problem of algorithm-induced phase shift for the symplectic geometric algorithm.

DIDADTIC TOOLS FOR THE STUDENTS’ ALGORITHMIC THINKING DEVELOPMENT

Directory of Open Access Journals (Sweden)

T. P. Pushkaryeva

2017-01-01

thinking and increase the level of understanding and learning of educational material on algorithms and programming.Scientific novelty. The developed tools and methods for developing algorithmic style of thinking during the educational process of training in programming is fundamentally different from existing ones that are aimed at kinesthetic channels of perception and activation of motor-memory area. According to the latest statistics, over 40% of people have kinesthetic sensing of the world; however, researchers have not treated this phenomenon in much detail. On the whole, the use efficiency of the didactic means when training graduates of engineering specialties has been proved in the course of the carried out experiment on kinesthetic tools introduction into educational process with the subsequent diagnostics of the levels of AT skills development, and the quality of training in programming among the students of theSiberianFederalUniversity.Practical significance. The proposed tools and methods for developing algorithmic thinking can be used in the training process in the school course of computer science, as well as university courses of programming of various kinds. The presented kinesthetic tools can be used for other technical and natural-science specialities (e.g. Mathematics after applying specific content adaptation.

The Contribution of Science-Rich Resources to Public Science Interest

Science.gov (United States)

Falk, John H.; Pattison, Scott; Meier, David; Bibas, David; Livingston, Kathleen

2018-01-01

This preliminary study examined the effect that five major sources of public science education--schools, science centers, broadcast media, print media, and the Internet--had on adults' science interest "values" and "cognitive predispositions." Over 3,000 adults were sampled in three U.S. metropolitan areas: Los Angeles,…

The Algorithm for Algorithms: An Evolutionary Algorithm Based on Automatic Designing of Genetic Operators

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Dazhi Jiang

2015-01-01

Full Text Available At present there is a wide range of evolutionary algorithms available to researchers and practitioners. Despite the great diversity of these algorithms, virtually all of the algorithms share one feature: they have been manually designed. A fundamental question is “are there any algorithms that can design evolutionary algorithms automatically?” A more complete definition of the question is “can computer construct an algorithm which will generate algorithms according to the requirement of a problem?” In this paper, a novel evolutionary algorithm based on automatic designing of genetic operators is presented to address these questions. The resulting algorithm not only explores solutions in the problem space like most traditional evolutionary algorithms do, but also automatically generates genetic operators in the operator space. In order to verify the performance of the proposed algorithm, comprehensive experiments on 23 well-known benchmark optimization problems are conducted. The results show that the proposed algorithm can outperform standard differential evolution algorithm in terms of convergence speed and solution accuracy which shows that the algorithm designed automatically by computers can compete with the algorithms designed by human beings.

Science-Technology-Society literacy in college non-majors biology: Comparing problem/case studies based learning and traditional expository methods of instruction

Science.gov (United States)

Peters, John S.

This study used a multiple response model (MRM) on selected items from the Views on Science-Technology-Society (VOSTS) survey to examine science-technology-society (STS) literacy among college non-science majors' taught using Problem/Case Studies Based Learning (PBL/CSBL) and traditional expository methods of instruction. An initial pilot investigation of 15 VOSTS items produced a valid and reliable scoring model which can be used to quantitatively assess student literacy on a variety of STS topics deemed important for informed civic engagement in science related social and environmental issues. The new scoring model allows for the use of parametric inferential statistics to test hypotheses about factors influencing STS literacy. The follow-up cross-institutional study comparing teaching methods employed Hierarchical Linear Modeling (HLM) to model the efficiency and equitability of instructional methods on STS literacy. A cluster analysis was also used to compare pre and post course patterns of student views on the set of positions expressed within VOSTS items. HLM analysis revealed significantly higher instructional efficiency in the PBL/CSBL study group for 4 of the 35 STS attitude indices (characterization of media vs. school science; tentativeness of scientific models; cultural influences on scientific research), and more equitable effects of traditional instruction on one attitude index (interdependence of science and technology). Cluster analysis revealed generally stable patterns of pre to post course views across study groups, but also revealed possible teaching method effects on the relationship between the views expressed within VOSTS items with respect to (1) interdependency of science and technology; (2) anti-technology; (3) socioscientific decision-making; (4) scientific/technological solutions to environmental problems; (5) usefulness of school vs. media characterizations of science; (6) social constructivist vs. objectivist views of theories; (7

El desempeño del docente en el proceso de desarrollo de habilidades de trabajo con algoritmos en la disciplina Álgebra Lineal / Teachers' performance and the process of developing skills to work with algorithms in Linear Algebra

Directory of Open Access Journals (Sweden)

Ivonne Burguet Lago

2018-05-01

Full Text Available ABSTRACT The paper describes a proposal of professional pedagogical performance tests to assess teachers’ role in the process of developing the skill of working with algorithms in Linear Algebra. It aims at devising a testing tool to assess teachers’ performance in the skill-developing process. This tool is a finding of Cuba theory of Advanced Education, systematically used in recent years. The findings include the test design and the illustration of its use in a sample of 22 Linear Algebra teachers during the first term of the 2017-2018 academic year at Informatics Sciences Engineering major. Keywords: ABSTRACT The paper describes a proposal of professional pedagogical performance tests to assess teachers’ role in the process of developing the skill of working with algorithms in Linear Algebra. It aims at devising a testing tool to assess teachers’ performance in the skill-developing process. This tool is a finding of Cuba theory of Advanced Education, systematically used in recent years. The findings include the test design and the illustration of its use in a sample of 22 Linear Algebra teachers during the first term of the 2017-2018 academic year at Informatics Sciences Engineering major.

A simpler and elegant algorithm for computing fractal dimension in ...

Indian Academy of Sciences (India)

Chaotic systems are now frequently encountered in almost all branches of sciences. Dimension of such systems provides an important measure for easy characterization of dynamics of the systems. Conventional algorithms for computing dimension of such systems in higher dimensional state space face an unavoidable ...

Hypersensitivity to local anaesthetics--update and proposal of evaluation algorithm

DEFF Research Database (Denmark)

Thyssen, Jacob Pontoppidan; Menné, Torkil; Elberling, Jesper

2008-01-01

of patients suspected with immediate- and delayed-type immune reactions. Literature was examined using PubMed-Medline, EMBASE, Biosis and Science Citation Index. Based on the literature, the proposed algorithm may safely and rapidly distinguish between immediate-type and delayed-type allergic immune reactions....

Using the Humanities to Teach Neuroscience to Non-majors.

Science.gov (United States)

McFarlane, Hewlet G; Richeimer, Joel

2015-01-01

We developed and offered a sequence of neuroscience courses geared toward changing the way non-science students interact with the sciences. Although we accepted students from all majors and at all class levels, our target population was first and second year students who were majoring in the fine arts or the humanities, or who had not yet declared a major. Our goal was to engage these students in science in general and neuroscience in particular by teaching science in a way that was accessible and relevant to their intellectual experiences. Our methodology was to teach scientific principles through the humanities by using course material that is at the intersection of the sciences and the humanities and by changing the classroom experience for both faculty and students. Examples of our course materials included the works of Oliver Sacks, V.S. Ramachandran, Martha Nussbaum, Virginia Woolf and Karl Popper, among others. To change the classroom experience we used a model of team-teaching, which required the simultaneous presence of two faculty members in the classroom for all classes. We changed the structure of the classroom experience from the traditional authority model to a model in which inquiry, debate, and intellectual responsibility were central. We wanted the students to have an appreciation of science not only as an endeavor guided by evidence and experimentation, but also a public discourse driven by creativity and controversy. The courses attracted a significant number of humanities and fine arts students, many of whom had already completed their basic science requirement.

Using the Humanities to Teach Neuroscience to Non-majors

Science.gov (United States)

McFarlane, Hewlet G.; Richeimer, Joel

2015-01-01

We developed and offered a sequence of neuroscience courses geared toward changing the way non-science students interact with the sciences. Although we accepted students from all majors and at all class levels, our target population was first and second year students who were majoring in the fine arts or the humanities, or who had not yet declared a major. Our goal was to engage these students in science in general and neuroscience in particular by teaching science in a way that was accessible and relevant to their intellectual experiences. Our methodology was to teach scientific principles through the humanities by using course material that is at the intersection of the sciences and the humanities and by changing the classroom experience for both faculty and students. Examples of our course materials included the works of Oliver Sacks, V.S. Ramachandran, Martha Nussbaum, Virginia Woolf and Karl Popper, among others. To change the classroom experience we used a model of team-teaching, which required the simultaneous presence of two faculty members in the classroom for all classes. We changed the structure of the classroom experience from the traditional authority model to a model in which inquiry, debate, and intellectual responsibility were central. We wanted the students to have an appreciation of science not only as an endeavor guided by evidence and experimentation, but also a public discourse driven by creativity and controversy. The courses attracted a significant number of humanities and fine arts students, many of whom had already completed their basic science requirement. PMID:26240533

Research of Improved Apriori Algorithm Based on Itemset Array

Directory of Open Access Journals (Sweden)

Naili Liu

2013-06-01

Full Text Available Mining frequent item sets is a major key process in data mining research. Apriori and many improved algorithms are lowly efficient because they need scan database many times and storage transaction ID in memory, so time and space overhead is very high. Especially, they are lower efficient when they process large scale database. The main task of the improved algorithm is to reduce time and space overhead for mining frequent item sets. Because, it scans database only once to generate binary item set array, it adopts binary instead of transaction ID when it storages transaction flag, it adopts logic AND operation to judge whether an item set is frequent item set. Moreover, the improved algorithm is more suitable for large scale database. Experimental results show that the improved algorithm has better efficiency than classic Apriori algorithm.

Testing a Firefly-Inspired Synchronization Algorithm in a Complex Wireless Sensor Network.

Science.gov (United States)

Hao, Chuangbo; Song, Ping; Yang, Cheng; Liu, Xiongjun

2017-03-08

Data acquisition is the foundation of soft sensor and data fusion. Distributed data acquisition and its synchronization are the important technologies to ensure the accuracy of soft sensors. As a research topic in bionic science, the firefly-inspired algorithm has attracted widespread attention as a new synchronization method. Aiming at reducing the design difficulty of firefly-inspired synchronization algorithms for Wireless Sensor Networks (WSNs) with complex topologies, this paper presents a firefly-inspired synchronization algorithm based on a multiscale discrete phase model that can optimize the performance tradeoff between the network scalability and synchronization capability in a complex wireless sensor network. The synchronization process can be regarded as a Markov state transition, which ensures the stability of this algorithm. Compared with the Miroll and Steven model and Reachback Firefly Algorithm, the proposed algorithm obtains better stability and performance. Finally, its practicality has been experimentally confirmed using 30 nodes in a real multi-hop topology with low quality links.

Stemming of Slovenian library science texts

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Polona Vilar

2002-01-01

Full Text Available The theme of the article is the preparation of a stemming algorithm for Slovenian library science texts. The procedure consisted of three phases: learning, testing and evaluation.The preparation of the optimal stemmer for Slovenian texts from the field of library science is presented, its testing and comparison with two other stemmers for the Slovenian language: the Popovič stemmer and the Generic stemmer. A corpus of 790.000 words from the field of library science was used for learning. Lists of stems, word endings and stop-words were built. In the testing phase, the component parts of the algorithm were tested on an additional corpus of 167.000 words. In the evaluation phase, a comparison of the three stemmers processing the same word corpus was made. The results of each stemmer were compared with an intellectually prepared control result of the stemming of the corpus. It consisted of groups of semantically connected words with no errors. Understemming was especially monitored – the number of stems for semantically connected words, produced by an algorithm. The results were statistically processed with the Kruskal-Wallis test. The Optimal stemmer produced the best results.It matched best with the reference results and also gave the smallest number of stems for one semantic meaning. The Popovič stemmer followed closely. The Generic stemmer proved to be the least accurate. The procedures described in the thesis can represent a platform for the development of the tools for automatic indexing and retrieval for library science texts in Slovenian language.

Science teacher’s idea about environmental concepts in science learning as the first step of science teacher training

Science.gov (United States)

Tapilouw, M. C.; Firman, H.; Redjeki, S.; Chandra, D. T.

2018-05-01

To refresh natural environmental concepts in science, science teacher have to attend a teacher training. In teacher training, all participant can have a good sharing and discussion with other science teacher. This study is the first step of science teacher training program held by education foundation in Bandung and attended by 20 science teacher from 18 Junior High School. The major aim of this study is gathering science teacher’s idea of environmental concepts. The core of questions used in this study are basic competencies linked with environmental concepts, environmental concepts that difficult to explain, the action to overcome difficulties and references in teaching environmental concepts. There are four major findings in this study. First finding, most environmental concepts are taught in 7th grade. Second finding, most difficult environmental concepts are found in 7th grade. Third finding, there are five actions to overcome difficulties. Fourth finding, science teacher use at least four references in mastering environmental concepts. After all, teacher training can be a solution to reduce difficulties in teaching environmental concepts.

A Data Forward Stepwise Fitting Algorithm Based on Orthogonal Function System

Directory of Open Access Journals (Sweden)

Li Han-Ju

2017-01-01

Full Text Available Data fitting is the main method of functional data analysis, and it is widely used in the fields of economy, social science, engineering technology and so on. Least square method is the main method of data fitting, but the least square method is not convergent, no memory property, big fitting error and it is easy to over fitting. Based on the orthogonal trigonometric function system, this paper presents a data forward stepwise fitting algorithm. This algorithm takes forward stepwise fitting strategy, each time using the nearest base function to fit the residual error generated by the previous base function fitting, which makes the residual mean square error minimum. In this paper, we theoretically prove the convergence, the memory property and the fitting error diminishing character for the algorithm. Experimental results show that the proposed algorithm is effective, and the fitting performance is better than that of the least square method and the forward stepwise fitting algorithm based on the non-orthogonal function system.

The Fusion Science Research Plan for the Major U.S. Tokamaks. Advisory report

International Nuclear Information System (INIS)

1996-01-01

In summary, the community has developed a research plan for the major tokamak facilities that will produce impressive scientific benefits over the next two years. The plan is well aligned with the new mission and goals of the restructured fusion energy sciences program recommended by FEAC. Budget increases for all three facilities will allow their programs to move forward in FY 1997, increasing their rate of scientific progress. With a shutdown deadline now established, the TFTR will forego all but a few critical upgrades and maximize operation to achieve a set of high-priority scientific objectives with deuterium-tritium plasmas. The DIII-D and Alcator C-Mod facilities will still fall well short of full utilization. Increasing the run time in vii DIII-D is recommended to increase the scientific output using its existing capabilities, even if scheduled upgrades must be further delayed. An increase in the Alcator C-Mod budget is recommended, at the expense of equal and modest reductions (~1%) in the other two facilities if necessary, to develop its capabilities for the long-term and increase its near-term scientific output.

Content-based and algorithmic classifications of journals: Perspectives on the dynamics of scientific communication and indexer effects

NARCIS (Netherlands)

Rafols, I; Leydesdorff, L.

2009-01-01

The aggregated journal-journal citation matrix—based on the Journal Citation Reports (JCR) of the Science Citation Index—can be decomposed by indexers or algorithmically. In this study, we test the results of two recently available algorithms for the decomposition of large matrices against two

Citizen Science: The Small World Initiative Improved Lecture Grades and California Critical Thinking Skills Test Scores of Nonscience Major Students at Florida Atlantic University.

Science.gov (United States)

Caruso, Joseph P; Israel, Natalie; Rowland, Kimberly; Lovelace, Matthew J; Saunders, Mary Jane

2016-03-01

Course-based undergraduate research is known to improve science, technology, engineering, and mathematics student achievement. We tested "The Small World Initiative, a Citizen-Science Project to Crowdsource Novel Antibiotic Discovery" to see if it also improved student performance and the critical thinking of non-science majors in Introductory Biology at Florida Atlantic University (a large, public, minority-dominant institution) in academic year 2014-15. California Critical Thinking Skills Test pre- and posttests were offered to both Small World Initiative (SWI) and control lab students for formative amounts of extra credit. SWI lab students earned significantly higher lecture grades than control lab students, had significantly fewer lecture grades of D+ or lower, and had significantly higher critical thinking posttest total scores than control students. Lastly, more SWI students were engaged while taking critical thinking tests. These results support the hypothesis that utilizing independent course-based undergraduate science research improves student achievement even in nonscience students.

A Systematic Approach to Modified BCJR MAP Algorithms for Convolutional Codes

Directory of Open Access Journals (Sweden)

Patenaude François

2006-01-01

Full Text Available Since Berrou, Glavieux and Thitimajshima published their landmark paper in 1993, different modified BCJR MAP algorithms have appeared in the literature. The existence of a relatively large number of similar but different modified BCJR MAP algorithms, derived using the Markov chain properties of convolutional codes, naturally leads to the following questions. What is the relationship among the different modified BCJR MAP algorithms? What are their relative performance, computational complexities, and memory requirements? In this paper, we answer these questions. We derive systematically four major modified BCJR MAP algorithms from the BCJR MAP algorithm using simple mathematical transformations. The connections between the original and the four modified BCJR MAP algorithms are established. A detailed analysis of the different modified BCJR MAP algorithms shows that they have identical computational complexities and memory requirements. Computer simulations demonstrate that the four modified BCJR MAP algorithms all have identical performance to the BCJR MAP algorithm.

Algorithms for Bayesian network modeling and reliability assessment of infrastructure systems

International Nuclear Information System (INIS)

Tien, Iris; Der Kiureghian, Armen

2016-01-01

Novel algorithms are developed to enable the modeling of large, complex infrastructure systems as Bayesian networks (BNs). These include a compression algorithm that significantly reduces the memory storage required to construct the BN model, and an updating algorithm that performs inference on compressed matrices. These algorithms address one of the major obstacles to widespread use of BNs for system reliability assessment, namely the exponentially increasing amount of information that needs to be stored as the number of components in the system increases. The proposed compression and inference algorithms are described and applied to example systems to investigate their performance compared to that of existing algorithms. Orders of magnitude savings in memory storage requirement are demonstrated using the new algorithms, enabling BN modeling and reliability analysis of larger infrastructure systems. - Highlights: • Novel algorithms developed for Bayesian network modeling of infrastructure systems. • Algorithm presented to compress information in conditional probability tables. • Updating algorithm presented to perform inference on compressed matrices. • Algorithms applied to example systems to investigate their performance. • Orders of magnitude savings in memory storage requirement demonstrated.

Investigation of energy windowing algorithms for effective cargo screening with radiation portal monitors

International Nuclear Information System (INIS)

Hevener, Ryne; Yim, Man-Sung; Baird, Ken

2013-01-01

Radiation portal monitors (RPMs) are distributed across the globe in an effort to decrease the illicit trafficking of nuclear materials. Many current generation RPMs utilizes large polyvinyltoluene (PVT) plastic scintillators. These detectors are low cost and reliable but have very poor energy resolution. The lack of spectroscopic detail available from PVT spectra has restricted these systems primarily to performing simple gross counting measurements in the past. A common approach to extend the capability of PVT detectors beyond simple “gross-gamma” use is to apply a technique known as energy windowing (EW) to perform rough nuclide identification with limited spectral information. An approach to creating EW algorithms was developed in this work utilizing a specific set of calibration sources and modified EW equations; this algorithm provided a degree of increased identification capability. A simulated real-time emulation of the algorithm utilizing actual port-of-entry RPM data supplied by ORNL provided an extensive proving ground for the algorithm. This algorithm is able to identify four potential threat nuclides and the major NORM source with a high degree of accuracy. High-energy masking, a major detriment of EW algorithms, is reduced by the algorithm's design. - Highlights: • Gross counting algorithms do not produce detailed screenings. • Energy windowing algorithms enhance nuclide identification capability. • Proper use of EW algorithm can identify multiple threat nuclides. • Utilizing specific set of calibration sources is important for nuclide identification

Benchmarking monthly homogenization algorithms

Science.gov (United States)

Venema, V. K. C.; Mestre, O.; Aguilar, E.; Auer, I.; Guijarro, J. A.; Domonkos, P.; Vertacnik, G.; Szentimrey, T.; Stepanek, P.; Zahradnicek, P.; Viarre, J.; Müller-Westermeier, G.; Lakatos, M.; Williams, C. N.; Menne, M.; Lindau, R.; Rasol, D.; Rustemeier, E.; Kolokythas, K.; Marinova, T.; Andresen, L.; Acquaotta, F.; Fratianni, S.; Cheval, S.; Klancar, M.; Brunetti, M.; Gruber, C.; Prohom Duran, M.; Likso, T.; Esteban, P.; Brandsma, T.

2011-08-01

The COST (European Cooperation in Science and Technology) Action ES0601: Advances in homogenization methods of climate series: an integrated approach (HOME) has executed a blind intercomparison and validation study for monthly homogenization algorithms. Time series of monthly temperature and precipitation were evaluated because of their importance for climate studies and because they represent two important types of statistics (additive and multiplicative). The algorithms were validated against a realistic benchmark dataset. The benchmark contains real inhomogeneous data as well as simulated data with inserted inhomogeneities. Random break-type inhomogeneities were added to the simulated datasets modeled as a Poisson process with normally distributed breakpoint sizes. To approximate real world conditions, breaks were introduced that occur simultaneously in multiple station series within a simulated network of station data. The simulated time series also contained outliers, missing data periods and local station trends. Further, a stochastic nonlinear global (network-wide) trend was added. Participants provided 25 separate homogenized contributions as part of the blind study as well as 22 additional solutions submitted after the details of the imposed inhomogeneities were revealed. These homogenized datasets were assessed by a number of performance metrics including (i) the centered root mean square error relative to the true homogeneous value at various averaging scales, (ii) the error in linear trend estimates and (iii) traditional contingency skill scores. The metrics were computed both using the individual station series as well as the network average regional series. The performance of the contributions depends significantly on the error metric considered. Contingency scores by themselves are not very informative. Although relative homogenization algorithms typically improve the homogeneity of temperature data, only the best ones improve precipitation data

An Improved Parallel DNA Algorithm of 3-SAT

Directory of Open Access Journals (Sweden)

Wei Liu

2007-09-01

Full Text Available There are many large-size and difficult computational problems in mathematics and computer science. For many of these problems, traditional computers cannot handle the mass of data in acceptable timeframes, which we call an NP problem. DNA computing is a means of solving a class of intractable computational problems in which the computing time grows exponentially with problem size. This paper proposes a parallel algorithm model for the universal 3-SAT problem based on the Adleman-Lipton model and applies biological operations to handling the mass of data in solution space. In this manner, we can control the run time of the algorithm to be finite and approximately constant.

Sustainable logistics and transportation optimization models and algorithms

CERN Document Server

Gakis, Konstantinos; Pardalos, Panos

2017-01-01

Focused on the logistics and transportation operations within a supply chain, this book brings together the latest models, algorithms, and optimization possibilities. Logistics and transportation problems are examined within a sustainability perspective to offer a comprehensive assessment of environmental, social, ethical, and economic performance measures. Featured models, techniques, and algorithms may be used to construct policies on alternative transportation modes and technologies, green logistics, and incentives by the incorporation of environmental, economic, and social measures. Researchers, professionals, and graduate students in urban regional planning, logistics, transport systems, optimization, supply chain management, business administration, information science, mathematics, and industrial and systems engineering will find the real life and interdisciplinary issues presented in this book informative and useful.

Fellowship | Indian Academy of Sciences

Indian Academy of Sciences (India)

Radhakrishnan, Prof. Jaikumar Ph.D. (Rutgers), FNA. Date of birth: 30 May 1964. Specialization: Algorithms, Information Theory, Computational Complexity, Combinatorics and Quantum Computing Address: Professor, School of Technology & Computer Science, Tata Institute of Fundamental Research, Homi Bhabha Road, ...

Student and high-school characteristics related to completing a science, technology, engineering or mathematics (STEM) major in college

Science.gov (United States)

LeBeau, Brandon; Harwell, Michael; Monson, Debra; Dupuis, Danielle; Medhanie, Amanuel; Post, Thomas R.

2012-04-01

Background: The importance of increasing the number of US college students completing degrees in science, technology, engineering or mathematics (STEM) has prompted calls for research to provide a better understanding of factors related to student participation in these majors, including the impact of a student's high-school mathematics curriculum. Purpose: This study examines the relationship between various student and high-school characteristics and completion of a STEM major in college. Of specific interest is the influence of a student's high-school mathematics curriculum on the completion of a STEM major in college. Sample: The sample consisted of approximately 3500 students from 229 high schools. Students were predominantly Caucasian (80%), with slightly more males than females (52% vs 48%). Design and method: A quasi-experimental design with archival data was used for students who enrolled in, and graduated from, a post-secondary institution in the upper Midwest. To be included in the sample, students needed to have completed at least three years of high-school mathematics. A generalized linear mixed model was used with students nested within high schools. The data were cross-sectional. Results: High-school predictors were not found to have a significant impact on the completion of a STEM major. Significant student-level predictors included ACT mathematics score, gender and high-school mathematics GPA. Conclusions: The results provide evidence that on average students are equally prepared for the rigorous mathematics coursework regardless of the high-school mathematics curriculum they completed.

Decision algorithms in fire detection systems

Directory of Open Access Journals (Sweden)

Ristić Jovan D.

2011-01-01

Full Text Available Analogue (and addressable fire detection systems enables a new quality in improving sensitivity to real fires and reducing susceptibility to nuisance alarm sources. Different decision algorithms types were developed with intention to improve sensitivity and reduce false alarm occurrence. At the beginning, it was free alarm level adjustment based on preset level. Majority of multi-criteria decision work was based on multi-sensor (multi-signature decision algorithms - using different type of sensors on the same location or, rather, using different aspects (level and rise of one sensor measured value. Our idea is to improve sensitivity and reduce false alarm occurrence by forming groups of sensors that work in similar conditions (same world side in the building, same or similar technology or working time. Original multi-criteria decision algorithms based on level, rise and difference of level and rise from group average are discussed in this paper.

Research on parallel algorithm for sequential pattern mining

Science.gov (United States)

Zhou, Lijuan; Qin, Bai; Wang, Yu; Hao, Zhongxiao

2008-03-01

Sequential pattern mining is the mining of frequent sequences related to time or other orders from the sequence database. Its initial motivation is to discover the laws of customer purchasing in a time section by finding the frequent sequences. In recent years, sequential pattern mining has become an important direction of data mining, and its application field has not been confined to the business database and has extended to new data sources such as Web and advanced science fields such as DNA analysis. The data of sequential pattern mining has characteristics as follows: mass data amount and distributed storage. Most existing sequential pattern mining algorithms haven't considered the above-mentioned characteristics synthetically. According to the traits mentioned above and combining the parallel theory, this paper puts forward a new distributed parallel algorithm SPP(Sequential Pattern Parallel). The algorithm abides by the principal of pattern reduction and utilizes the divide-and-conquer strategy for parallelization. The first parallel task is to construct frequent item sets applying frequent concept and search space partition theory and the second task is to structure frequent sequences using the depth-first search method at each processor. The algorithm only needs to access the database twice and doesn't generate the candidated sequences, which abates the access time and improves the mining efficiency. Based on the random data generation procedure and different information structure designed, this paper simulated the SPP algorithm in a concrete parallel environment and implemented the AprioriAll algorithm. The experiments demonstrate that compared with AprioriAll, the SPP algorithm had excellent speedup factor and efficiency.

Evaluation of a Cross Layer Scheduling Algorithm for LTE Downlink

Directory of Open Access Journals (Sweden)

A. Popovska Avramova

2013-06-01

Full Text Available The LTE standard is a leading standard in the wireless broadband market. The Radio Resource Management at the base station plays a major role in satisfying users demand for high data rates and quality of service. This paper evaluates a cross layer scheduling algorithm that aims at minimizing the resource utilization. The algorithm makes decisions based on channel conditions, the size of transmission buffers and different quality of service demands. Simulation results show that the new algorithm improves the resource utilization and provides better guarantees for service quality.

Content-based and algorithmic classifications of journals: perspectives on the dynamics of scientific communication and indexer effects

NARCIS (Netherlands)

Rafols, I.; Leydesdorff, L.; Larsen, B.; Leta, J.

2009-01-01

The aggregated journal-journal citation matrix—based on the Journal Citation Reports (JCR) of the Science Citation Index—can be decomposed by indexers and/or algorithmically. In this study, we test the results of two recently available algorithms for the decomposition of large matrices against two

Improved Algorithms OF CELF and CELF++ for Influence Maximization

Directory of Open Access Journals (Sweden)

Jiaguo Lv

2014-06-01

Full Text Available Motivated by the wide application in some fields, such as viral marketing, sales promotion etc, influence maximization has been the most important and extensively studied problem in social network. However, the most classical KK-Greedy algorithm for influence maximization is inefficient. Two major sources of the algorithm’s inefficiency were analyzed in this paper. With the analysis of algorithms CELF and CELF++, all nodes in the influenced set of u would never bring any marginal gain when a new seed u was produced. Through this optimization strategy, a lot of redundant nodes will be removed from the candidate nodes. Basing on the strategy, two improved algorithms of Lv_CELF and Lv_CELF++ were proposed in this study. To evaluate the two algorithms, the two algorithms with their benchmark algorithms of CELF and CELF++ were conducted on some real world datasets. To estimate the algorithms, influence degree and running time were employed to measure the performance and efficiency respectively. Experimental results showed that, compared with benchmark algorithms of CELF and CELF++, matching effects and higher efficiency were achieved by the new algorithms Lv_CELF and Lv_CELF++. Solutions with the proposed optimization strategy can be useful for the decisionmaking problems under the scenarios related to the influence maximization problem.

How social networks influence female students' choices to major in engineering

Science.gov (United States)

Weinland, Kathryn Ann

Scope and Method of Study: This study examined how social influence plays a part in female students' choices of college major, specifically engineering instead of science, technology, and math. Social influence may show itself through peers, family members, and teachers and may encompass resources under the umbrella of social capital. The purpose of this study was to examine how female students' social networks, through the lens of social capital, influence her major choice of whether or not to study engineering. The variables of peer influence, parental influence, teacher/counselor influence, perception of engineering, and academic background were addressed in a 52 question, Likert scale survey. This survey has been modified from an instrument previously used by Reyer (2007) at Bradley University. Data collection was completed using the Dillman (2009) tailored design model. Responses were grouped into four main scales of the dependent variables of social influence, encouragement, perceptions of engineering and career motivation. A factor analysis was completed on the four factors as a whole, and individual questions were not be analyzed. Findings and Conclusions: This study addressed the differences in social network support for female freshmen majoring in engineering versus female freshmen majoring in science, technology, or math. Social network support, when working together from all angles of peers, teachers, parents, and teachers/counselors, transforms itself into a new force that is more powerful than the summation of the individual parts. Math and science preparation also contributed to female freshmen choosing to major in engineering instead of choosing to major in science, technology, or math. The STEM pipeline is still weak and ways in which to reinforce it should be examined. Social network support is crucial for female freshmen who are majoring in science, technology, engineering, and math.

An algorithm for preferential selection of spectroscopic targets in LEGUE

International Nuclear Information System (INIS)

Carlin, Jeffrey L.; Newberg, Heidi Jo; Lépine, Sébastien; Deng Licai; Chen Yuqin; Fu Xiaoting; Gao Shuang; Li Jing; Liu Chao; Beers, Timothy C.; Christlieb, Norbert; Grillmair, Carl J.; Guhathakurta, Puragra; Han Zhanwen; Hou Jinliang; Lee, Hsu-Tai; Liu Xiaowei; Pan Kaike; Sellwood, J. A.; Wang Hongchi

2012-01-01

We describe a general target selection algorithm that is applicable to any survey in which the number of available candidates is much larger than the number of objects to be observed. This routine aims to achieve a balance between a smoothly-varying, well-understood selection function and the desire to preferentially select certain types of targets. Some target-selection examples are shown that illustrate different possibilities of emphasis functions. Although it is generally applicable, the algorithm was developed specifically for the LAMOST Experiment for Galactic Understanding and Exploration (LEGUE) survey that will be carried out using the Chinese Guo Shou Jing Telescope. In particular, this algorithm was designed for the portion of LEGUE targeting the Galactic halo, in which we attempt to balance a variety of science goals that require stars at fainter magnitudes than can be completely sampled by LAMOST. This algorithm has been implemented for the halo portion of the LAMOST pilot survey, which began in October 2011.

K-6 Science Curriculum.

Science.gov (United States)

Blueford, J. R.; And Others

A unified science approach is incorporated in this K-6 curriculum mode. The program is organized into six major cycles. These include: (1) science, math, and technology cycle; (2) universe cycle; (3) life cycle; (4) water cycle; (5) plate tectonics cycle; and (6) rock cycle. An overview is provided of each cycle's major concepts. The topic…

An improvement of the fast uncovering community algorithm

International Nuclear Information System (INIS)

Wang Li; Wang Jiang; Shen Hua-Wei; Cheng Xue-Qi

2013-01-01

Community detection methods have been used in computer, sociology, physics, biology, and brain information science areas. Many methods are based on the optimization of modularity. The algorithm proposed by Blondel et al. (Blondel V D, Guillaume J L, Lambiotte R and Lefebvre E 2008 J. Stat. Mech. 10 10008) is one of the most widely used methods because of its good performance, especially in the big data era. In this paper we make some improvements to this algorithm in correctness and performance. By tests we see that different node orders bring different performances and different community structures. We find some node swings in different communities that influence the performance. So we design some strategies on the sweeping order of node to reduce the computing cost made by repetition swing. We introduce a new concept of overlapping degree (OV) that shows the strength of connection between nodes. Three improvement strategies are proposed that are based on constant OV, adaptive OV, and adaptive weighted OV, respectively. Experiments on synthetic datasets and real datasets are made, showing that our improved strategies can improve the performance and correctness. (interdisciplinary physics and related areas of science and technology)

Fast algorithms for chiral fermions in 2 dimensions

Directory of Open Access Journals (Sweden)

Hyka (Xhako Dafina

2018-01-01

Full Text Available In lattice QCD simulations the formulation of the theory in lattice should be chiral in order that symmetry breaking happens dynamically from interactions. In order to guarantee this symmetry on the lattice one uses overlap and domain wall fermions. On the other hand high computational cost of lattice QCD simulations with overlap or domain wall fermions remains a major obstacle of research in the field of elementary particles. We have developed the preconditioned GMRESR algorithm as fast inverting algorithm for chiral fermions in U(1 lattice gauge theory. In this algorithm we used the geometric multigrid idea along the extra dimension.The main result of this work is that the preconditioned GMRESR is capable to accelerate the convergence 2 to 12 times faster than the other optimal algorithms (SHUMR for different coupling constant and lattice 32x32. Also, in this paper we tested it for larger lattice size 64x64. From the results of simulations we can see that our algorithm is faster than SHUMR. This is a very promising result that this algorithm can be adapted also in 4 dimension.

An efficient non-dominated sorting method for evolutionary algorithms.

Science.gov (United States)

Fang, Hongbing; Wang, Qian; Tu, Yi-Cheng; Horstemeyer, Mark F

2008-01-01

We present a new non-dominated sorting algorithm to generate the non-dominated fronts in multi-objective optimization with evolutionary algorithms, particularly the NSGA-II. The non-dominated sorting algorithm used by NSGA-II has a time complexity of O(MN(2)) in generating non-dominated fronts in one generation (iteration) for a population size N and M objective functions. Since generating non-dominated fronts takes the majority of total computational time (excluding the cost of fitness evaluations) of NSGA-II, making this algorithm faster will significantly improve the overall efficiency of NSGA-II and other genetic algorithms using non-dominated sorting. The new non-dominated sorting algorithm proposed in this study reduces the number of redundant comparisons existing in the algorithm of NSGA-II by recording the dominance information among solutions from their first comparisons. By utilizing a new data structure called the dominance tree and the divide-and-conquer mechanism, the new algorithm is faster than NSGA-II for different numbers of objective functions. Although the number of solution comparisons by the proposed algorithm is close to that of NSGA-II when the number of objectives becomes large, the total computational time shows that the proposed algorithm still has better efficiency because of the adoption of the dominance tree structure and the divide-and-conquer mechanism.

Does science education need the history of science?

Science.gov (United States)

Gooday, Graeme; Lynch, John M; Wilson, Kenneth G; Barsky, Constance K

2008-06-01

This essay argues that science education can gain from close engagement with the history of science both in the training of prospective vocational scientists and in educating the broader public about the nature of science. First it shows how historicizing science in the classroom can improve the pedagogical experience of science students and might even help them turn into more effective professional practitioners of science. Then it examines how historians of science can support the scientific education of the general public at a time when debates over "intelligent design" are raising major questions over the kind of science that ought to be available to children in their school curricula. It concludes by considering further work that might be undertaken to show how history of science could be of more general educational interest and utility, well beyond the closed academic domains in which historians of science typically operate.

Advances in software science and technology

CERN Document Server

Ohno, Yoshio; Kamimura, Tsutomu

1991-01-01

Advances in Software Science and Technology, Volume 2 provides information pertinent to the advancement of the science and technology of computer software. This book discusses the various applications for computer systems.Organized into four parts encompassing 12 chapters, this volume begins with an overview of categorical frameworks that are widely used to represent data types in computer science. This text then provides an algorithm for generating vertices of a smoothed polygonal line from the vertices of a digital curve or polygonal curve whose position contains a certain amount of error. O

The CCSDS Lossless Data Compression Algorithm for Space Applications

Science.gov (United States)

Yeh, Pen-Shu; Day, John H. (Technical Monitor)

2001-01-01

In the late 80's, when the author started working at the Goddard Space Flight Center (GSFC) for the National Aeronautics and Space Administration (NASA), several scientists there were in the process of formulating the next generation of Earth viewing science instruments, the Moderate Resolution Imaging Spectroradiometer (MODIS). The instrument would have over thirty spectral bands and would transmit enormous data through the communications channel. This was when the author was assigned the task of investigating lossless compression algorithms for space implementation to compress science data in order to reduce the requirement on bandwidth and storage.

GLOA: A New Job Scheduling Algorithm for Grid Computing

Directory of Open Access Journals (Sweden)

Zahra Pooranian

2013-03-01

Full Text Available The purpose of grid computing is to produce a virtual supercomputer by using free resources available through widespread networks such as the Internet. This resource distribution, changes in resource availability, and an unreliable communication infrastructure pose a major challenge for efficient resource allocation. Because of the geographical spread of resources and their distributed management, grid scheduling is considered to be a NP-complete problem. It has been shown that evolutionary algorithms offer good performance for grid scheduling. This article uses a new evaluation (distributed algorithm inspired by the effect of leaders in social groups, the group leaders' optimization algorithm (GLOA, to solve the problem of scheduling independent tasks in a grid computing system. Simulation results comparing GLOA with several other evaluation algorithms show that GLOA produces shorter makespans.

Detection of Illegitimate Emails using Boosting Algorithm

DEFF Research Database (Denmark)

Nizamani, Sarwat; Memon, Nasrullah; Wiil, Uffe Kock

2011-01-01

and spam email detection. For our desired task, we have applied a boosting technique. With the use of boosting we can achieve high accuracy of traditional classification algorithms. When using boosting one has to choose a suitable weak learner as well as the number of boosting iterations. In this paper, we......In this paper, we report on experiments to detect illegitimate emails using boosting algorithm. We call an email illegitimate if it is not useful for the receiver or for the society. We have divided the problem into two major areas of illegitimate email detection: suspicious email detection...

Algorithm For Hypersonic Flow In Chemical Equilibrium

Science.gov (United States)

Palmer, Grant

1989-01-01

Implicit, finite-difference, shock-capturing algorithm calculates inviscid, hypersonic flows in chemical equilibrium. Implicit formulation chosen because overcomes limitation on mathematical stability encountered in explicit formulations. For dynamical portion of problem, Euler equations written in conservation-law form in Cartesian coordinate system for two-dimensional or axisymmetric flow. For chemical portion of problem, equilibrium state of gas at each point in computational grid determined by minimizing local Gibbs free energy, subject to local conservation of molecules, atoms, ions, and total enthalpy. Major advantage: resulting algorithm naturally stable and captures strong shocks without help of artificial-dissipation terms to damp out spurious numerical oscillations.

Applied Computational Mathematics in Social Sciences

CERN Document Server

Damaceanu, Romulus-Catalin

2010-01-01

Applied Computational Mathematics in Social Sciences adopts a modern scientific approach that combines knowledge from mathematical modeling with various aspects of social science. Special algorithms can be created to simulate an artificial society and a detailed analysis can subsequently be used to project social realities. This Ebook specifically deals with computations using the NetLogo platform, and is intended for researchers interested in advanced human geography and mathematical modeling studies.

Photometric Analysis in the Kepler Science Operations Center Pipeline

Science.gov (United States)

Twicken, Joseph D.; Clarke, Bruce D.; Bryson, Stephen T.; Tenenbaum, Peter; Wu, Hayley; Jenkins, Jon M.; Girouard, Forrest; Klaus, Todd C.

2010-01-01

We describe the Photometric Analysis (PA) software component and its context in the Kepler Science Operations Center (SOC) pipeline. The primary tasks of this module are to compute the photometric flux and photocenters (centroids) for over 160,000 long cadence (thirty minute) and 512 short cadence (one minute) stellar targets from the calibrated pixels in their respective apertures. We discuss the science algorithms for long and short cadence PA: cosmic ray cleaning; background estimation and removal; aperture photometry; and flux-weighted centroiding. We discuss the end-to-end propagation of uncertainties for the science algorithms. Finally, we present examples of photometric apertures, raw flux light curves, and centroid time series from Kepler flight data. PA light curves, centroid time series, and barycentric timestamp corrections are exported to the Multi-mission Archive at Space Telescope [Science Institute] (MAST) and are made available to the general public in accordance with the NASA/Kepler data release policy.

Exploring the Relationships between Self-Efficacy and Preference for Teacher Authority among Computer Science Majors

Science.gov (United States)

Lin, Che-Li; Liang, Jyh-Chong; Su, Yi-Ching; Tsai, Chin-Chung

2013-01-01

Teacher-centered instruction has been widely adopted in college computer science classrooms and has some benefits in training computer science undergraduates. Meanwhile, student-centered contexts have been advocated to promote computer science education. How computer science learners respond to or prefer the two types of teacher authority,…

Application of Genetic Algorithms in Seismic Tomography

Science.gov (United States)

Soupios, Pantelis; Akca, Irfan; Mpogiatzis, Petros; Basokur, Ahmet; Papazachos, Constantinos

2010-05-01

In the earth sciences several inverse problems that require data fitting and parameter estimation are nonlinear and can involve a large number of unknown parameters. Consequently, the application of analytical inversion or optimization techniques may be quite restrictive. In practice, most analytical methods are local in nature and rely on a linearized form of the problem in question, adopting an iterative procedure using partial derivatives to improve an initial model. This approach can lead to a dependence of the final model solution on the starting model and is prone to entrapment in local misfit minima. Moreover, the calculation of derivatives can be computationally inefficient and create instabilities when numerical approximations are used. In contrast to these local minimization methods, global techniques that do not rely on partial derivatives, are independent of the form of the data misfit criterion, and are computationally robust. Such methods often use random processes to sample a selected wider span of the model space. In this situation, randomly generated models are assessed in terms of their data-fitting quality and the process may be stopped after a certain number of acceptable models is identified or continued until a satisfactory data fit is achieved. A new class of methods known as genetic algorithms achieves the aforementioned approximation through novel model representation and manipulations. Genetic algorithms (GAs) were originally developed in the field of artificial intelligence by John Holland more than 20 years ago, but even in this field it is less than a decade that the methodology has been more generally applied and only recently did the methodology attract the attention of the earth sciences community. Applications have been generally concentrated in geophysics and in particular seismology. As awareness of genetic algorithms grows there surely will be many more and varied applications to earth science problems. In the present work, the

Communicating Science: The Profile of Science Journalists in Spain

Science.gov (United States)

Cassany, Roger; Cortiñas, Sergi; Elduque, Albert

2018-01-01

Science journalists are mainly responsible for publicly communicating science, which, in turn, is a major indicator of the social development of democratic societies. The transmission of quality scientific information that is rigorously researched and understandable is therefore crucial, and demand for this kind of information from both…

An empirical study on SAJQ (Sorting Algorithm for Join Queries

Directory of Open Access Journals (Sweden)

Hassan I. Mathkour

2010-06-01

Full Text Available Most queries that applied on database management systems (DBMS depend heavily on the performance of the used sorting algorithm. In addition to have an efficient sorting algorithm, as a primary feature, stability of such algorithms is a major feature that is needed in performing DBMS queries. In this paper, we study a new Sorting Algorithm for Join Queries (SAJQ that has both advantages of being efficient and stable. The proposed algorithm takes the advantage of using the m-way-merge algorithm in enhancing its time complexity. SAJQ performs the sorting operation in a time complexity of O(nlogm, where n is the length of the input array and m is number of sub-arrays used in sorting. An unsorted input array of length n is arranged into m sorted sub-arrays. The m-way-merge algorithm merges the sorted m sub-arrays into the final output sorted array. The proposed algorithm keeps the stability of the keys intact. An analytical proof has been conducted to prove that, in the worst case, the proposed algorithm has a complexity of O(nlogm. Also, a set of experiments has been performed to investigate the performance of the proposed algorithm. The experimental results have shown that the proposed algorithm outperforms other Stable–Sorting algorithms that are designed for join-based queries.

GPU-based fast pencil beam algorithm for proton therapy

International Nuclear Information System (INIS)

Fujimoto, Rintaro; Nagamine, Yoshihiko; Kurihara, Tsuneya

2011-01-01

Performance of a treatment planning system is an essential factor in making sophisticated plans. The dose calculation is a major time-consuming process in planning operations. The standard algorithm for proton dose calculations is the pencil beam algorithm which produces relatively accurate results, but is time consuming. In order to shorten the computational time, we have developed a GPU (graphics processing unit)-based pencil beam algorithm. We have implemented this algorithm and calculated dose distributions in the case of a water phantom. The results were compared to those obtained by a traditional method with respect to the computational time and discrepancy between the two methods. The new algorithm shows 5-20 times faster performance using the NVIDIA GeForce GTX 480 card in comparison with the Intel Core-i7 920 processor. The maximum discrepancy of the dose distribution is within 0.2%. Our results show that GPUs are effective for proton dose calculations.

Medical image segmentation using genetic algorithms.

Science.gov (United States)

Maulik, Ujjwal

2009-03-01

Genetic algorithms (GAs) have been found to be effective in the domain of medical image segmentation, since the problem can often be mapped to one of search in a complex and multimodal landscape. The challenges in medical image segmentation arise due to poor image contrast and artifacts that result in missing or diffuse organ/tissue boundaries. The resulting search space is therefore often noisy with a multitude of local optima. Not only does the genetic algorithmic framework prove to be effective in coming out of local optima, it also brings considerable flexibility into the segmentation procedure. In this paper, an attempt has been made to review the major applications of GAs to the domain of medical image segmentation.

Extreme-scale Algorithms and Solver Resilience

Energy Technology Data Exchange (ETDEWEB)

Dongarra, Jack [Univ. of Tennessee, Knoxville, TN (United States)

2016-12-10

A widening gap exists between the peak performance of high-performance computers and the performance achieved by complex applications running on these platforms. Over the next decade, extreme-scale systems will present major new challenges to algorithm development that could amplify this mismatch in such a way that it prevents the productive use of future DOE Leadership computers due to the following; Extreme levels of parallelism due to multicore processors; An increase in system fault rates requiring algorithms to be resilient beyond just checkpoint/restart; Complex memory hierarchies and costly data movement in both energy and performance; Heterogeneous system architectures (mixing CPUs, GPUs, etc.); and Conflicting goals of performance, resilience, and power requirements.

Algorithmic-Reducibility = Renormalization-Group Fixed-Points; ``Noise''-Induced Phase-Transitions (NITs) to Accelerate Algorithmics (``NIT-Picking'') Replacing CRUTCHES!!!: Gauss Modular/Clock-Arithmetic Congruences = Signal X Noise PRODUCTS..

Science.gov (United States)

Siegel, J.; Siegel, Edward Carl-Ludwig

2011-03-01

Cook-Levin computational-"complexity"(C-C) algorithmic-equivalence reduction-theorem reducibility equivalence to renormalization-(semi)-group phase-transitions critical-phenomena statistical-physics universality-classes fixed-points, is exploited with Gauss modular/clock-arithmetic/model congruences = signal X noise PRODUCT reinterpretation. Siegel-Baez FUZZYICS=CATEGORYICS(SON of ``TRIZ''): Category-Semantics(C-S) tabular list-format truth-table matrix analytics predicts and implements "noise"-induced phase-transitions (NITs) to accelerate versus to decelerate Harel [Algorithmics(1987)]-Sipser[Intro. Theory Computation(1997) algorithmic C-C: "NIT-picking" to optimize optimization-problems optimally(OOPO). Versus iso-"noise" power-spectrum quantitative-only amplitude/magnitude-only variation stochastic-resonance, this "NIT-picking" is "noise" power-spectrum QUALitative-type variation via quantitative critical-exponents variation. Computer-"science" algorithmic C-C models: Turing-machine, finite-state-models/automata, are identified as early-days once-workable but NOW ONLY LIMITING CRUTCHES IMPEDING latter-days new-insights!!!

The National Science Foundation and the History of Science

Science.gov (United States)

Rothenberg, Marc

2014-01-01

The National Science Foundation (NSF) is the major funder of the history of science in the United States. Between 1958 and 2010, the NSF program for the history of science has given 89 awards in the history of astronomy. This paper analyzes the award recipients and subject areas of the awards and notes significant shifts in the concentration of award recipients and the chronological focus of the research being funded.

An algorithm for discovering Lagrangians automatically from data

Directory of Open Access Journals (Sweden)

Daniel J.A. Hills

2015-11-01

Full Text Available An activity fundamental to science is building mathematical models. These models are used to both predict the results of future experiments and gain insight into the structure of the system under study. We present an algorithm that automates the model building process in a scientifically principled way. The algorithm can take observed trajectories from a wide variety of mechanical systems and, without any other prior knowledge or tuning of parameters, predict the future evolution of the system. It does this by applying the principle of least action and searching for the simplest Lagrangian that describes the system’s behaviour. By generating this Lagrangian in a human interpretable form, it can also provide insight into the workings of the system.

A modular and parameterisable classification of algorithms

NARCIS (Netherlands)

Nugteren, C.; Corporaal, H.

2011-01-01

Multi-core and many-core were already major trends for the past six years, and are expected to continue for the next decades. With this trend of parallel computing, it becomes increasingly difficult to decide on which architecture to run a certain application or algorithm. Additionally, it brings

Development and validation of an algorithm for laser application in wound treatment

Directory of Open Access Journals (Sweden)

Diequison Rite da Cunha

2017-12-01

Full Text Available ABSTRACT Objective: To develop and validate an algorithm for laser wound therapy. Method: Methodological study and literature review. For the development of the algorithm, a review was performed in the Health Sciences databases of the past ten years. The algorithm evaluation was performed by 24 participants, nurses, physiotherapists, and physicians. For data analysis, the Cronbach’s alpha coefficient and the chi-square test for independence was used. The level of significance of the statistical test was established at 5% (p<0.05. Results: The professionals’ responses regarding the facility to read the algorithm indicated: 41.70%, great; 41.70%, good; 16.70%, regular. With regard the algorithm being sufficient for supporting decisions related to wound evaluation and wound cleaning, 87.5% said yes to both questions. Regarding the participants’ opinion that the algorithm contained enough information to support their decision regarding the choice of laser parameters, 91.7% said yes. The questionnaire presented reliability using the Cronbach’s alpha coefficient test (α = 0.962. Conclusion: The developed and validated algorithm showed reliability for evaluation, wound cleaning, and use of laser therapy in wounds.

Teaching Physics to Environmental Science Majors Using a Flipped Course Approach

Science.gov (United States)

Hill, N. B.; Riha, S. J.; Wysocki, M. W.

2014-12-01

Coursework in physics provides a framework for quantitative reasoning and problem solving skill development in budding geoscientists. To make physical concepts more accessible and relevant to students majoring in environmental science, an environmental physics course was developed at Cornell University and offered for the first time during spring 2014. Principles of radiation, thermodynamics, and mechanics were introduced and applied to the atmosphere, hydrosphere, and lithosphere to describe energy and mass transfers in natural and built environments. Environmental physics was designed as a flipped course where students viewed online material outside of class and worked in groups in class to solve sustainability problems. Experiential learning, just-in-time teaching, and peer collaboration strategies were also utilized. In-class problems were drawn from both local and global environmental sustainability concerns. Problems included an investigation of Cornell's lake source cooling system, calculations on the energy consumed in irrigation with groundwater in the southwestern United States, and power generated by wind turbines at various locations around the world. Class attendance was high, with at least 84% of students present at each meeting. Survey results suggest that students enjoyed working in groups and found the in-class problems helpful for assimilating the assigned material. However, some students reported that the workload was too heavy and they preferred traditional lectures to the flipped classroom. The instructors were able to actively engage with students and quickly identify knowledge and skill gaps that needed to be addressed. Overall, the integration of current environmental problems and group work into an introductory physics course could help to inspire and motivate students as they advance their ability to analyze problems quantitatively.

ESHOPPS: A COMPUTATIONAL TOOL TO AID THE TEACHING OF SHORTEST PATH ALGORITHMS

Directory of Open Access Journals (Sweden)

S. J. de A. LIMA

2015-07-01

Full Text Available The development of a computational tool called EShoPPS – Environment for Shortest Path Problem Solving, which is used to assist students in understanding the working of Dijkstra, Greedy search and A*(star algorithms is presented in this paper. Such algorithms are commonly taught in graduate and undergraduate courses of Engineering and Informatics and are used for solving many optimization problems that can be characterized as Shortest Path Problem. The EShoPPS is an interactive tool that allows students to create a graph representing the problem and also helps in developing their knowledge of each specific algorithm. Experiments performed with 155 students of undergraduate and graduate courses such as Industrial Engineering, Computer Science and Information Systems have shown that by using the EShoPPS tool students were able to improve their interpretation of investigated algorithms.

Hybrid Modeling KMeans – Genetic Algorithms in the Health Care Data

Directory of Open Access Journals (Sweden)

Tessy Badriyah

2013-06-01

Full Text Available K-Means is one of the major algorithms widely used in clustering due to its good computational performance. However, K-Means is very sensitive to the initially selected points which randomly selected, and therefore it does not always generate optimum solutions. Genetic algorithm approach can be applied to solve this problem. In this research we examine the potential of applying hybrid GA- KMeans with focus on the area of health care data. We proposed a new technique using hybrid method combining KMeans Clustering and Genetic Algorithms, called the “Hybrid K-Means Genetic Algorithms” (HKGA. HKGA combines the power of Genetic Algorithms and the efficiency of K-Means Clustering. We compare our results with other conventional algorithms and also with other published research as well. Our results demonstrate that the HKGA achieves very good results and in some cases superior to other methods. Keywords: Machine Learning, K-Means, Genetic Algorithms, Hybrid KMeans Genetic Algorithm (HGKA.

Sources of Science Teaching Self-Efficacy for Preservice Elementary Teachers in Science Content Courses

Science.gov (United States)

Menon, Deepika; Sadler, Troy D.

2018-01-01

Self-efficacy beliefs play a major role in determining teachers' science teaching practices and have been a topic of great interest in the area of preservice science teacher education. This qualitative study investigated factors that influenced preservice elementary teachers' science teaching self-efficacy beliefs in a physical science content…

NASA-HBCU Space Science and Engineering Research Forum Proceedings

International Nuclear Information System (INIS)

Sanders, Y.D.; Freeman, Y.B.; George, M.C.

1989-01-01

The proceedings of the Historically Black Colleges and Universities (HBCU) forum are presented. A wide range of research topics from plant science to space science and related academic areas was covered. The sessions were divided into the following subject areas: Life science; Mathematical modeling, image processing, pattern recognition, and algorithms; Microgravity processing, space utilization and application; Physical science and chemistry; Research and training programs; Space science (astronomy, planetary science, asteroids, moon); Space technology (engineering, structures and systems for application in space); Space technology (physics of materials and systems for space applications); and Technology (materials, techniques, measurements)

Dynamical Consensus Algorithm for Second-Order Multi-Agent Systems Subjected to Communication Delay

International Nuclear Information System (INIS)

Liu Chenglin; Liu Fei

2013-01-01

To solve the dynamical consensus problem of second-order multi-agent systems with communication delay, delay-dependent compensations are added into the normal asynchronously-coupled consensus algorithm so as to make the agents achieve a dynamical consensus. Based on frequency-domain analysis, sufficient conditions are gained for second-order multi-agent systems with communication delay under leaderless and leader-following consensus algorithms respectively. Simulation illustrates the correctness of the results. (interdisciplinary physics and related areas of science and technology)

U.S. Institutional Research Productivity in Major Science Education Research Journals: Top 30 for 2000's

Science.gov (United States)

Barrow, Lloyd H.; Tang, Nai-en

2013-01-01

VonAalst (2010) used Google Scholar to identify the top four science education research journals: "Journal of Research in Science Teaching," "Science Education," "International Journal of Science Education," and "Journal of Science Teacher Education." U.S. institutional productivity for 2000-2009 for the…

Algorithms

Indian Academy of Sciences (India)

polynomial) division have been found in Vedic Mathematics which are dated much before Euclid's algorithm. A programming language Is used to describe an algorithm for execution on a computer. An algorithm expressed using a programming.

Career Preparation and the Political Science Major: Evidence from Departments

Science.gov (United States)

Collins, Todd A.; Knotts, H. Gibbs; Schiff, Jen

2012-01-01

We know little about the amount of career preparation offered to students in political science departments. This lack of information is particularly troubling given the state of the current job market and the growth of applied degree programs on university campuses. To address this issue, this article presents the results of a December 2010 survey…

Robot Science Autonomy in the Atacama Desert and Beyond

Science.gov (United States)

Thompson, David R.; Wettergreen, David S.

2013-01-01

Science-guided autonomy augments rovers with reasoning to make observations and take actions related to the objectives of scientific exploration. When rovers can directly interpret instrument measurements then scientific goals can inform and adapt ongoing navigation decisions. These autonomous explorers will make better scientific observations and collect massive, accurate datasets. In current astrobiology studies in the Atacama Desert we are applying algorithms for science autonomy to choose effective observations and measurements. Rovers are able to decide when and where to take follow-up actions that deepen scientific understanding. These techniques apply to planetary rovers, which we can illustrate with algorithms now used by Mars rovers and by discussing future missions.

Data-Driven Participation: Algorithms, Cities, Citizens, and Corporate Control

Directory of Open Access Journals (Sweden)

Matthew Tenney

2016-07-01

Full Text Available In this paper, we critically explore the interplay of algorithms and civic participation in visions of a city governed by equation, sensor and tweet. We begin by discussing the rhetoric surrounding techno-enabled paths to participatory democracy. This leads to us interrogating how the city is impacted by a discourse that promises to harness social/human capital through data science. We move to a praxis level and examine the motivations of local planners to adopt and increasingly automate forms of VGI as a form of citizen engagement. We ground theory and praxis with a report on the uneven impacts of algorithmic civic participation underway in the Canadian city of Toronto.

High-order quantum algorithm for solving linear differential equations

International Nuclear Information System (INIS)

Berry, Dominic W

2014-01-01

Linear differential equations are ubiquitous in science and engineering. Quantum computers can simulate quantum systems, which are described by a restricted type of linear differential equations. Here we extend quantum simulation algorithms to general inhomogeneous sparse linear differential equations, which describe many classical physical systems. We examine the use of high-order methods (where the error over a time step is a high power of the size of the time step) to improve the efficiency. These provide scaling close to Δt 2 in the evolution time Δt. As with other algorithms of this type, the solution is encoded in amplitudes of the quantum state, and it is possible to extract global features of the solution. (paper)

Major Practicum as a Learning Site for Exercise Science Professionals: A Pilot Study

Science.gov (United States)

Tinning, Richard; Jenkins, David; Collins, Jessie; Rossi, Tony; Brancato, Tania

2012-01-01

Exercise science is now an integral part of the allied health framework in Australia and graduates from accredited programmes are equipped with skills recognised as being important in the prevention and management of lifestyle-related diseases. This pilot study sought to determine the experiences of 11 final-year exercise science students in their…

Big Science

Energy Technology Data Exchange (ETDEWEB)

Anon.

1986-05-15

Astronomy, like particle physics, has become Big Science where the demands of front line research can outstrip the science budgets of whole nations. Thus came into being the European Southern Observatory (ESO), founded in 1962 to provide European scientists with a major modern observatory to study the southern sky under optimal conditions.

CombiMotif: A new algorithm for network motifs discovery in protein-protein interaction networks

Science.gov (United States)

Luo, Jiawei; Li, Guanghui; Song, Dan; Liang, Cheng

2014-12-01

Discovering motifs in protein-protein interaction networks is becoming a current major challenge in computational biology, since the distribution of the number of network motifs can reveal significant systemic differences among species. However, this task can be computationally expensive because of the involvement of graph isomorphic detection. In this paper, we present a new algorithm (CombiMotif) that incorporates combinatorial techniques to count non-induced occurrences of subgraph topologies in the form of trees. The efficiency of our algorithm is demonstrated by comparing the obtained results with the current state-of-the art subgraph counting algorithms. We also show major differences between unicellular and multicellular organisms. The datasets and source code of CombiMotif are freely available upon request.

Major Depressive Disorder

Directory of Open Access Journals (Sweden)

G Grobler

2013-08-01

Full Text Available The treatment guideline draws on several international guidelines: (iPractice Guidelines of the American Psychiatric Association (APAfor the Treatment of Patients with Major Depressive Disorder, SecondEdition;[1](ii Clinical Guidelines for the Treatment of DepressiveDisorders by the Canadian Psychiatric Association and the CanadianNetwork for Mood and Anxiety Treatments (CANMAT;[2](iiiNational Institute for Clinical Excellence (NICE guidelines;[3](iv RoyalAustralian and New Zealand College of Psychiatrists Clinical PracticeGuidelines Team for Depression (RANZCAP;[4](v Texas MedicationAlgorithm Project (TMAP Guidelines;[5](vi World Federation ofSocieties of Biological Psychiatry (WFSBP Treatment Guideline forUnipolar Depressive Disorder;[6]and (vii British Association forPsychopharmacology Guidelines.[7

Sadhana | Indian Academy of Sciences

Indian Academy of Sciences (India)

The availability of high performance computers and development of efficient algorithms has led to the emergence of computational materials science as the third branch of materials research complementing the traditional theoretical and experimental approaches. It has created new virtual realities in materials design that ...

Sadhana | Indian Academy of Sciences

Indian Academy of Sciences (India)

Logo of the Indian Academy of Sciences. Indian Academy of ... 2013 pp 571-589. An evolutionary approach for colour constancy based on gamut mapping constraint satisfaction ... A new colour constancy algorithm based on automatic determination of gray framework parameters using neural network · Mohammad Mehdi ...

Sadhana | Indian Academy of Sciences

Indian Academy of Sciences (India)

Home; Journals; Sadhana. Vivek J Pandya. Articles written in Sadhana. Volume 40 Issue 1 February 2015 pp 139-153 Electrical and Computer Sciences. Simulation and comparison of perturb and observe and incremental conductance MPPT algorithms for solar energy system connected to grid · Sachin Vrajlal Rajani ...

Sadhana | Indian Academy of Sciences

Indian Academy of Sciences (India)

Home; Journals; Sadhana. Sachin Vrajlal Rajani. Articles written in Sadhana. Volume 40 Issue 1 February 2015 pp 139-153 Electrical and Computer Sciences. Simulation and comparison of perturb and observe and incremental conductance MPPT algorithms for solar energy system connected to grid · Sachin Vrajlal Rajani ...

Zombie algorithms: a timesaving remote sensing systems engineering tool

Science.gov (United States)

Ardanuy, Philip E.; Powell, Dylan C.; Marley, Stephen

2008-08-01

In modern horror fiction, zombies are generally undead corpses brought back from the dead by supernatural or scientific means, and are rarely under anyone's direct control. They typically have very limited intelligence, and hunger for the flesh of the living [1]. Typical spectroradiometric or hyperspectral instruments providess calibrated radiances for a number of remote sensing algorithms. The algorithms typically must meet specified latency and availability requirements while yielding products at the required quality. These systems, whether research, operational, or a hybrid, are typically cost constrained. Complexity of the algorithms can be high, and may evolve and mature over time as sensor characterization changes, product validation occurs, and areas of scientific basis improvement are identified and completed. This suggests the need for a systems engineering process for algorithm maintenance that is agile, cost efficient, repeatable, and predictable. Experience on remote sensing science data systems suggests the benefits of "plug-n-play" concepts of operation. The concept, while intuitively simple, can be challenging to implement in practice. The use of zombie algorithms-empty shells that outwardly resemble the form, fit, and function of a "complete" algorithm without the implemented theoretical basis-provides the ground systems advantages equivalent to those obtained by integrating sensor engineering models onto the spacecraft bus. Combined with a mature, repeatable process for incorporating the theoretical basis, or scientific core, into the "head" of the zombie algorithm, along with associated scripting and registration, provides an easy "on ramp" for the rapid and low-risk integration of scientific applications into operational systems.

Non-Science Majors' Critical Evaluation of Websites in a Biotechnology Course

Science.gov (United States)

Halverson, Kristy L.; Siegel, Marcelle A.; Freyermuth, Sharyn K.

2010-12-01

Helping students develop criteria for judgment and apply examination skills is essential for promoting scientific literacy. With the increasing availability of the Internet, it is even more essential that students learn how to evaluate the science they gather from online resources. This is particularly true because publishing information on the web is not restricted to experts, and content quality can vary greatly across websites. The responsibility of evaluating websites falls upon the user. Little research has examined undergraduates' evaluation of web sites in science classes. The purpose of this study was to investigate on which websites college students selected and how they evaluated the websites used when developing individual positions about stem-cell research. We used a qualitative approach in search of patterns in undergraduates' website selection and evaluation criteria. We found that students used a variety of web resources from eleven types of websites to complete their independent research report. Students also used eleven evaluation criteria to evaluate these sources, some useful (e.g., credibility) and some not useful (e.g., readability). We found that university students struggled with critically evaluating online resources. Undergraduates need prompts to learn how to critically evaluate the science content provided within websites. This type of scaffold can facilitate useful evaluation and promote critical thinking required for becoming scientifically literate.

Computer Labs | College of Engineering & Applied Science

Science.gov (United States)

Engineering Concentration on Ergonomics M.S. Program in Computer Science Interdisciplinary Concentration on Structural Engineering Laboratory Water Resources Laboratory Computer Science Department Computer Science Academic Programs Computer Science Undergraduate Programs Computer Science Major Computer Science Tracks

Computer Resources | College of Engineering & Applied Science

Science.gov (United States)

Engineering Concentration on Ergonomics M.S. Program in Computer Science Interdisciplinary Concentration on Structural Engineering Laboratory Water Resources Laboratory Computer Science Department Computer Science Academic Programs Computer Science Undergraduate Programs Computer Science Major Computer Science Tracks

Computer Science | Classification | College of Engineering & Applied

Science.gov (United States)

Engineering Concentration on Ergonomics M.S. Program in Computer Science Interdisciplinary Concentration on Structural Engineering Laboratory Water Resources Laboratory Computer Science Department Computer Science Academic Programs Computer Science Undergraduate Programs Computer Science Major Computer Science Tracks

Flocking algorithm for autonomous flying robots.

Science.gov (United States)

Virágh, Csaba; Vásárhelyi, Gábor; Tarcai, Norbert; Szörényi, Tamás; Somorjai, Gergő; Nepusz, Tamás; Vicsek, Tamás

2014-06-01

Animal swarms displaying a variety of typical flocking patterns would not exist without the underlying safe, optimal and stable dynamics of the individuals. The emergence of these universal patterns can be efficiently reconstructed with agent-based models. If we want to reproduce these patterns with artificial systems, such as autonomous aerial robots, agent-based models can also be used in their control algorithms. However, finding the proper algorithms and thus understanding the essential characteristics of the emergent collective behaviour requires thorough and realistic modeling of the robot and also the environment. In this paper, we first present an abstract mathematical model of an autonomous flying robot. The model takes into account several realistic features, such as time delay and locality of communication, inaccuracy of the on-board sensors and inertial effects. We present two decentralized control algorithms. One is based on a simple self-propelled flocking model of animal collective motion, the other is a collective target tracking algorithm. Both algorithms contain a viscous friction-like term, which aligns the velocities of neighbouring agents parallel to each other. We show that this term can be essential for reducing the inherent instabilities of such a noisy and delayed realistic system. We discuss simulation results on the stability of the control algorithms, and perform real experiments to show the applicability of the algorithms on a group of autonomous quadcopters. In our case, bio-inspiration works in two ways. On the one hand, the whole idea of trying to build and control a swarm of robots comes from the observation that birds tend to flock to optimize their behaviour as a group. On the other hand, by using a realistic simulation framework and studying the group behaviour of autonomous robots we can learn about the major factors influencing the flight of bird flocks.

A Stereo Dual-Channel Dynamic Programming Algorithm for UAV Image Stitching.

Science.gov (United States)

Li, Ming; Chen, Ruizhi; Zhang, Weilong; Li, Deren; Liao, Xuan; Wang, Lei; Pan, Yuanjin; Zhang, Peng

2017-09-08

Dislocation is one of the major challenges in unmanned aerial vehicle (UAV) image stitching. In this paper, we propose a new algorithm for seamlessly stitching UAV images based on a dynamic programming approach. Our solution consists of two steps: Firstly, an image matching algorithm is used to correct the images so that they are in the same coordinate system. Secondly, a new dynamic programming algorithm is developed based on the concept of a stereo dual-channel energy accumulation. A new energy aggregation and traversal strategy is adopted in our solution, which can find a more optimal seam line for image stitching. Our algorithm overcomes the theoretical limitation of the classical Duplaquet algorithm. Experiments show that the algorithm can effectively solve the dislocation problem in UAV image stitching, especially for the cases in dense urban areas. Our solution is also direction-independent, which has better adaptability and robustness for stitching images.

Control algorithms for autonomous robot navigation

International Nuclear Information System (INIS)

Jorgensen, C.C.

1985-01-01

This paper examines control algorithm requirements for autonomous robot navigation outside laboratory environments. Three aspects of navigation are considered: navigation control in explored terrain, environment interactions with robot sensors, and navigation control in unanticipated situations. Major navigation methods are presented and relevance of traditional human learning theory is discussed. A new navigation technique linking graph theory and incidental learning is introduced

Gender, Families, and Science: Influences on Early Science Training and Career Choices

Science.gov (United States)

Hanson, Sandra L.

This research examines the effects of gender and a number of family experiences on young people's chances of going into postsecondary science training and science occupations in the years immediately following high school. Data came from the nationally representative, longitudinal High School and Beyond survey. Results show that gender plays a significant role in choices involving early science training and occupations - especially training. Amongst young men and women with comparable resources and qualifications, young women are less likely to make the science choice. The family experiences and expectations examined here are not a major factor in understanding gender differences in access to science training and occupations. Although much of the literature describes the domains of science and of family as being at odds, results from this research suggest that family experiences play a rather minimal role in predicting who will enter science training or occupations in the early post-high school years. When family variables do have an effect, they are not always negative and the nature of the effect varies by the time in the life cycle that the family variable is measured, by type of family experience (orientation vs. procreation), by outcome (science major vs. science occupation), and by gender.

Fast parallel MR image reconstruction via B1-based, adaptive restart, iterative soft thresholding algorithms (BARISTA).

Science.gov (United States)

Muckley, Matthew J; Noll, Douglas C; Fessler, Jeffrey A

2015-02-01

Sparsity-promoting regularization is useful for combining compressed sensing assumptions with parallel MRI for reducing scan time while preserving image quality. Variable splitting algorithms are the current state-of-the-art algorithms for SENSE-type MR image reconstruction with sparsity-promoting regularization. These methods are very general and have been observed to work with almost any regularizer; however, the tuning of associated convergence parameters is a commonly-cited hindrance in their adoption. Conversely, majorize-minimize algorithms based on a single Lipschitz constant have been observed to be slow in shift-variant applications such as SENSE-type MR image reconstruction since the associated Lipschitz constants are loose bounds for the shift-variant behavior. This paper bridges the gap between the Lipschitz constant and the shift-variant aspects of SENSE-type MR imaging by introducing majorizing matrices in the range of the regularizer matrix. The proposed majorize-minimize methods (called BARISTA) converge faster than state-of-the-art variable splitting algorithms when combined with momentum acceleration and adaptive momentum restarting. Furthermore, the tuning parameters associated with the proposed methods are unitless convergence tolerances that are easier to choose than the constraint penalty parameters required by variable splitting algorithms.

Introduction: Commercialization of Academic Science and a New Agenda for Science Education

Science.gov (United States)

Irzik, Gürol

2013-01-01

Certain segments of science are becoming increasingly commercialized. This article discusses the commercialization of academic science and its impact on various aspects of science. It also aims to provide an introduction to the articles in this special issue. I briefly describe the major factors that led to this phenomenon, situate it in the…

Markov chains models, algorithms and applications

CERN Document Server

Ching, Wai-Ki; Ng, Michael K; Siu, Tak-Kuen

2013-01-01

This new edition of Markov Chains: Models, Algorithms and Applications has been completely reformatted as a text, complete with end-of-chapter exercises, a new focus on management science, new applications of the models, and new examples with applications in financial risk management and modeling of financial data.This book consists of eight chapters.  Chapter 1 gives a brief introduction to the classical theory on both discrete and continuous time Markov chains. The relationship between Markov chains of finite states and matrix theory will also be highlighted. Some classical iterative methods

A Teaching Approach from the Exhaustive Search Method to the Needleman-Wunsch Algorithm

Science.gov (United States)

Xu, Zhongneng; Yang, Yayun; Huang, Beibei

2017-01-01

The Needleman-Wunsch algorithm has become one of the core algorithms in bioinformatics; however, this programming requires more suitable explanations for students with different major backgrounds. In supposing sample sequences and using a simple store system, the connection between the exhaustive search method and the Needleman-Wunsch algorithm…

Journal of Earth System Science | Indian Academy of Sciences

Indian Academy of Sciences (India)

Home; Journals; Journal of Earth System Science. Samir M Zaid. Articles written in Journal of Earth System Science. Volume 126 Issue 4 June 2017 pp 50. Provenance of coastal dune sands along Red Sea, Egypt · Samir M Zaid · More Details Abstract Fulltext PDF. Texture, mineralogy, and major and trace element ...

A spectral algorithm for the seriation problem

Energy Technology Data Exchange (ETDEWEB)

Atkins, J.E. [Michigan Univ., Ann Arbor, MI (United States). Dept. of Mathematics; Boman, E.G. [Stanford Univ., CA (United States). Dept. of Computer Science; Hendrickson, B. [Sandia National Labs., Albuquerque, NM (United States)

1994-11-01

Given a set of objects and a correlation function f reflecting the desire for two items to be near each other, find all sequences {pi} of the items so that correlation preferences are preserved; that is if {pi}(i) < {pi}(j) < {pi}(k) then f(i,j) {ge} f(i,k) and f(j,k) {ge} f(i,k). This seriation problem has numerous applications, for instance, solving it yields a solution to the consecutive ones problem. We present a spectral algorithm for this problem that has a number of interesting features. Whereas most previous applications of spectral techniques provided bounds or heuristics, our result is an algorithm for a nontrivial combinatorial problem. Our analysis introduces powerful tools from matrix theory to the theoretical computer science community. Also, spectral methods are being applied as heuristics for a variety of sequencing problems and our result helps explain and justify these applications. Although the worst case running time for our approach is not competitive with that of existing methods for well posed problem instances, unlike combinatorial approaches our algorithm remains a credible heuristic for the important cases where there are errors in the data.

Online Planning Algorithm

Science.gov (United States)

Rabideau, Gregg R.; Chien, Steve A.

2010-01-01

AVA v2 software selects goals for execution from a set of goals that oversubscribe shared resources. The term goal refers to a science or engineering request to execute a possibly complex command sequence, such as image targets or ground-station downlinks. Developed as an extension to the Virtual Machine Language (VML) execution system, the software enables onboard and remote goal triggering through the use of an embedded, dynamic goal set that can oversubscribe resources. From the set of conflicting goals, a subset must be chosen that maximizes a given quality metric, which in this case is strict priority selection. A goal can never be pre-empted by a lower priority goal, and high-level goals can be added, removed, or updated at any time, and the "best" goals will be selected for execution. The software addresses the issue of re-planning that must be performed in a short time frame by the embedded system where computational resources are constrained. In particular, the algorithm addresses problems with well-defined goal requests without temporal flexibility that oversubscribes available resources. By using a fast, incremental algorithm, goal selection can be postponed in a "just-in-time" fashion allowing requests to be changed or added at the last minute. Thereby enabling shorter response times and greater autonomy for the system under control.

Report of the surface science workshop

International Nuclear Information System (INIS)

Somorjai, G.A.; Yates, J.T. Jr.; Clinton, W.

1977-03-01

A three-day workshop was held to review the various areas of energy development and technology in which surface science plays major roles and makes major contributions, and to identify the major surface-science-related problem areas in the fields with ERDA's mission in the fossil, nuclear, fusion, geothermal, and solar energy technologies and in the field of environmental control. The workshop activities are summarized

An evaluation of community college student perceptions of the science laboratory and attitudes towards science in an introductory biology course

Science.gov (United States)

Robinson, Nakia Rae

The science laboratory is an integral component of science education. However, the academic value of student participation in the laboratory is not clearly understood. One way to discern student perceptions of the science laboratory is by exploring their views of the classroom environment. The classroom environment is one determinant that can directly influence student learning and affective outcomes. Therefore, this study sought to examine community college students' perceptions of the laboratory classroom environment and their attitudes toward science. Quantitative methods using two survey instruments, the Science Laboratory Environment Instrument (SLEI) and the Test of Science Related Attitudes (TORSA) were administered to measure laboratory perceptions and attitudes, respectively. A determination of differences among males and females as well as three academic streams were examined. Findings indicated that overall community college students had positive views of the laboratory environment regardless of gender of academic major. However, the results indicated that the opportunity to pursue open-ended activities in the laboratory was not prevalent. Additionally, females viewed the laboratory material environment more favorably than their male classmates did. Students' attitudes toward science ranged from favorable to undecided and no significant gender differences were present. However, there were significantly statistical differences between the attitudes of nonscience majors compared to both allied health and STEM majors. Nonscience majors had less positive attitudes toward scientific inquiry, adoption of scientific attitudes, and enjoyment of science lessons. Results also indicated that collectively, students' experiences in the laboratory were positive predicators of their attitudes toward science. However, no laboratory environment scale was a significant independent predictor of student attitudes. .A students' academic streams was the only significant

Development of an Interdisciplinary Undergraduate Major in The Earth System, Environment and Society

Science.gov (United States)

Wuebbles, D. J.

2003-12-01

Humanity faces great challenges in the 21st Century to understand and limit our impact on the Earth System. To address these challenges, it is essential to understand the nature and implications of environmental change, and the complexity of the Earth system. We need to educate citizens that have the background to make new developments in understanding technical aspects of the Earth System, and to develop an understanding the interactions between society and the Earth System sufficient to make informed policy choices. Traditional disciplinary departments and majors don't fully address this; teaching and research talent in the study of the Earth System is spread over many disciplinary-oriented departments. At the University of Illinois, we are currently developing a new cross-disciplinary undergraduate major being called The Earth system, environment and Society. This development is co-sponsored by a number of departments centered in the College of Liberal Arts & Sciences (but including other departments throughout the university). Our intention is that this major will be a catalyst for bringing together the many disciplines involved in Earth System Science education. The curriculum and course for study will focus on the science and human dimensions of the Earth system, with special emphasis on the processes and issues related to the environment across a range of spatial scales from local and regional to global. Along with meeting the requirements expected of all students in a liberal arts and sciences major, students in The Earth System, Environment and Society major will be required to complete a core set of courses designed to introduce students to all of the different components of the Earth System (students will choose from course options in both the sciences and the social sciences). After completing the core courses, students will then focus their studies on one of the two options within the major, Science of the Earth System (this option will emphasize the