The interface between computer science and the mathematical sciences

The C* Conference on Computer Science and Software Engineering (C3S2E) was established in 2008. C3S2E 2010 is the third annual meeting in the C3S2E conference series and is held in Montréal, Québec, Canada, during May 19-20, 2010. The conference aims to address the need of the academic community in computer science and software engineering. It brings together academics, government and industry professionals to discuss recent progress and challenges in a broad range of areas in the field of computer science and software engineering such as algorithms and theory, artificial intelligence, bioinformatics, computer architecture, computer graphics, computer security, computer vision, data mining, databases, image processing, information retrieval, machine learning, as well as software engineering. C3S2E 2010 also serves as a platform for theoreticians and practitioners to exchange their original research ideas on academic or application aspects of computing and engineering of software systems, present their new findings on theoretical or practical aspects of computer science and software engineering, share their experiences on integrating new technologies into products and applications, discuss their work on applying computing and software engineering to real-life situations, describe their development and operations of challenging computing related systems, and identify unsolved challenges. Although it is the third time C3S2E is held, this comprehensive conference has grown from a Canadian conference into an international conference. For C3S2E 2010, we continue to keep our tradition for inviting international experts in various areas of computer science and software engineering to join our team of international program committee. As a result, our Program Committee consists of professionals from different parts of the world including Australia, Canada, Germany, Hong Kong, Italy, Japan, Portugal, South Korea, Turkey, UAE, and UK. This committee has done an excellent job in finishing the single-blind review and on-line double-blind debate processes in record time. On average, about 90% of reviews were submitted by the due date and about 3.67 reviews were received for each paper. In terms of submissions, we have attracted many high-quality papers submitted by authors globally. The paper selection process was thorough and competitive. On average, each paper was refereed by at least three reviewers, and about 18% of submissions were accepted as full research papers. This year, we have an intensive program that spans over two days. In addition to research papers and student posters, we also include position papers, which allow authors to give their opinions and vision on exploring new concepts and research directions.

Serious game projects require multidisciplinary professionals, including programmers, designers and game designers. In games for health, one more type of professional must be included which is the one with health knowledge. The Jecripe Project has the aim of developing serious games for people with special needs. The professionals from health science are speech therapists and more professionals have the intention to be part of the mentioned project. However, this work presents how a serious game project motivated studies in different Computer Science research areas. We describe the three main studies in the Jecripe Project, each of one in a different area: Computer Vision, Data Mining and Human-Computer Interaction. The intention of the continuation in the project is to perform more studies including the integration of natural user interfaces in games for people with special needs.

Computational Physics holds a pivotal position in interdisciplinary research spanning Mathematics, Astrophysics, and Computational Science, offering solutions to intricate problems.Employing numerical analysis, computational physics harnesses programs and algorithms written in scientific languages like FORTRAN, C/C++, to tackle advanced research challenges.Through computational techniques, we can visualize complex phenomena such as the wave function of particles in a confined space (e. g. , particle in a box problem) or the wave function of a Harmonic Oscillator. Additionally, we can model the trajectories of satellites. These methodologies extend beyond visualization, serving simulation purposes for complex research issues in space exploration. Computational physics significantly contributes to advancing research in mathematical sciences and space exploration, whether theoretical or experimental in nature. This paper delves into the multifaceted applications of computational techniques across various research domains.

Assalamu’alaikum Wr. Wb. and Greetings.I am pleased and honored to welcome you at the First International Conference on Computer Science and Applied Mathematic (ICCSAM 2018), which was held this year by AMIK and STIKOM Tunas Bangsa Pematangsiantar in collaboration with the Indonesian Computer and Information Professional Association (IPKIN), Indonesian Mathematical Society (INDOMS) and Bank Muamalat. As Chair of the Foundation, I would like to convey a greeting Welcome to Parapat City Lake Toba to presenters from various countries and especially those I respect for the presence of scientists in the field of Computer and Mathematical Sciences and industry practitioners in the 2018 ICCSAM event.I see that this activity is designed to enhance the exchange of knowledge and new discoveries in computer science and mathematics and related fields in industry. I hope that scientists in the field of computer science and mathematics and those who work in the industry can share knowledge and work together as a team that has mutual relations with each other. I am very pleased to say that the theme of this conference, “Advancing Computability Innovation” is very much in line with the objectives of AMIK and STIKOM conferences and missions, namely “to become a Science and Technology based Study Program that meets industrial needs and functions as a research center in Information Data Science. The conference was held in response to output and aoutcame which had a significant contribution in the field of computer science and mathematics as an inseparable unit of science towards the development of local and global industries. It is our happiness and honor to welcome distinguished professors present to convey their expertise at this conference.I hope this meeting will enable the development of productive dialogue between participants from various countries. They also provide invaluable opportunities for networking among participants, institutions and industries. I also hope that diversity in these fields can reveal more opportunities for researchers and practitioners from all over the world to start a lot of research related to the industry in the future.I would like to congratulate AMIK and STIKOM Tunas Bangsa for starting this conference with a synergistic contribution from dedicated partners namely the USU Faculty of Mathematics and Natural Sciences, USU’s Faculty of Computer and Information Technology, the Indonesian Computer and Informatics Professional Association (IPKIN), Indonesian Mathematical Society (INDOMS), Bank Muamalat, Malaysia Pahang University (UMP), University of Essex, United Kingdom, Ankara, Turkey and Institute of Applied Mathematics Middle East Technical University to all delegates for their full support, cooperation and contribution to the 2018 ICCSAM. I also want to thank the Organizing Committee for their perseverance and extraordinary efforts. Various sponsors are also rewarded for their contributions. I really hope that all participants will get a pleasant stay here at NIAGARA HOTEL and bring back unforgettable experiences and valuable knowledge from this conference.Thanks.H. Ahmad Ridwansyah Putra

In this paper, we propose a calibration estimator of population mean in stratified sampling using the known mean and variance information from multi-auxiliary variables. The problem of determining the optimum calibrated weights is formulated as a Nonlinear Programming Problem (NLPP) that is solved using the Lagrange multiplier technique. Numerical example with real data is presented to illustrate the computational details of the proposed estimator. A comparison study is also carried out using real and simulated data to evaluate the performance and the usefulness of the proposed estimator. The study reveals that the proposed estimator with multi-auxiliary information is more efficient estimator of the population mean as it provides least estimated variance and highest gain in relative efficiency (RE). References Jean Claude Deville and Carl Erik Sarndal. Calibration estimators in survey sampling. Journal of the American statistical Association, 87(418):376–382, 1992. doi:10.1080/01621459.1992.10475217 . Victor M Estevao and Carl Erik Sarndal. Survey estimates by calibration on complex auxiliary information. International Statistical Review, 74(2):127–147, 2006. doi:110.1111/j.1751-5823.2006.tb00165.x Patrick J Farrell and Sarjinder Singh. Model-assisted higher-order calibration of estimators of variance. Australian and New Zealand Journal of Statistics, 47(3):375–383, 2005. doi:10.1111/j.1467-842X.2005.00402.x Wolfram Research, Inc. Mathematica, Version 11.3. Champaign, IL, 2018. Jong Min Kim, Engin A Sungur, and Tae Young Heo. Calibration approach estimators in stratified sampling. Statistics and probability letters, 77(1):99–103, 2007. doi:10.1016/j.spl.2006.05.015 Phillip S Kott. Using calibration weighting to adjust for nonresponse and coverage errors. Survey Methodology, 32(2):133, 2006. Dinesh K Rao. Mathematical programing in stratified random sampling. PhD thesis, School of Computing, Information and Mathematical Sciences, The University of the South Pacific, Fiji, February 2017. Dinesh K. Rao, Tokaua. Tekabu, and Mohammad G M Khan. New calibration estimators in stratified sampling. In Proceedings of Asia-Pacific World Congress on Computer Science and Engineering, pages 66–70. IEEE, 2016. Gurmindar K Singh, Dinesh K Rao, and Mohammed GM Khan. Calibration estimator of population mean in stratified random sampling. In Proceedings of Asia-Pacific World Congress on Computer Science and Engineering (APWC on CSE), pages 1–5. IEEE, 2014. Sarjindar Singh, Stephen Horn, and Frank Yu. Estimation of variance of general regression estimator: Higher level calibration approach. Survey Methodology, 24:41–50, 1998. Sarjinder Singh. Advanced Sampling Theory With Applications: How Michael Selected Amy, volume I and II. Kluwer Academic Publishers, Netherlands, 2003. Sarjinder Singh. On the calibration of design weights using a displacement function. Metrika, 75(1):85–107, 2012. doi:10.1007/s00184-010-0316-6 Sarjinder Singh, Stephen Horn, Sadeq Chowdhury, and Frank Yu. Theory and methods: Calibration of the estimators of variance. Australian and New Zealand Journal of Statistics, 41(2):199–212, 1999. doi:10.1111/1467-842X.00074 D S Tracy, S Singh, and R Arnab. Note on calibration in stratified and double sampling. Survey Methodology, 29(1):99–104, 2003. Changbao Wu and Randy R Sitter. A model-calibration approach to using complete auxiliary information from survey data. Journal of the American Statistical Association, 96(453):185–193, 2001. doi:10.1198/016214501750333054

It is tedious and error-prone to query search engines manually in order to accumulate a large body of factual information. Search engines retrieve and rank potentially relevant documents for human perusal, but do not extract facts, or fuse information from multiple documents. This paper introduces DynamicView, a Semantic Web application for researchers to query, browse and visualize distribution and evolution of research areas in computer science. Present and historical web pages of top 20 universities in USA and China are analyzed, and research areas of faculties in computer science are extracted automatically by segmentation based algorithm. Different ontologies of ACM and MST classification systems are combined by SKOS vocabularies, and the classification of research areas is learned from the ACM Digital Library. Query results including numbers of researchers and their locations are visualized in SVG map and animation. Interestingly, great differences of hot topics do exist between the two countries, and the number of researchers in certain areas changed greatly from the year 2000 to 2005.

Note from the EditorsToo often, biology has been considered by both students and faculty as the ideal major for the scientifically inclined but mathematically challenged, even though the advantage of quantitative approaches in biology has always been apparent.Increasingly, biologists are utilizing mathematical skills to create simulations or manage and query large data sets.The need for basic mathematical and computer science (CS) literacy among biologists has never been greater.But does this require a fundamental change in the organization of the undergraduate biology curriculum?What is the utility of math/CS in different areas of biology?How can we best provide math/CS instruction to biologists so that the utility is appreciated?Do all biology students require a stronger math/CS foundation, or only those interested in research careers?Given the speed at which technology changes, what is the best preparation?Three different points of view are offered below.Dr. Roger Brent, President and Director of the Molecular Sciences Institute, reflects on the "innumeracy" common among biologists and argues that significant insights into biological problems may be gained from better mathematical intuition.

The lecture “Music, Mathematics and Computer Science” is subdivided into two parts. The fi rst part, “Music, Mathematics and Computer Science: History of Interaction” (see ICONI journal, No. 3, 2020) examines the processes of interconnection and interpenetration of various fi elds of music, mathematics and computer science, spanning the period from Ancient Times to the turn of the 20th and 21st centuries. The second part of the lecture: “Music, Mathematics and Computer Science: Particular Features of Functioning of Computer-Musical Technologies” is devoted to examining various aspects of developing and applying computer-musical technologies in contemporary musical practice, including musical composition, performance and the sphere of music education

There has been much debate in the past few years about the appropriate mathematics requirements for an undergraduate computer science major. The discussion has focused primarily on two issues: (1) the underlying mathematical content of computer science courses and (2) the content of mathematics courses which would serve as appropriate cognate requirements for computer science major programs. While this discussion has been helpful, it has been too narrowly focused--it has not started from an understanding of the relationship between the disciplines of mathematics and computer science, but rather has sought to identify mathematical prerequisites that computer science majors need in order to take existing computer science courses. This paper is a small step in seeking to apply an understanding of the relationship between the disciplines of mathematics and computer science to the undergraduate computer science curriculum.

Visual computing is a discipline in computer science that allows computers to acquisite, process, and analyze visual data. In the application field of medicine, it enables to development of new methods for the visualization, detection, and analysis of diseases. Therefore, it plays a significant role in developing the understanding of diseases. Taking the fact that cancer is currently one of the deadliest and most frequent diseases around the world into consideration, it is crucial to generate effective methods for the study of cancer in order to provide appropriate management strategies for the disease and treatment methods. Research has shown that methods based on visual computing can detect, classify, and analyze the cancerous tissues in a patient successfully with high accuracy. This paper focuses on the PET/CT, CAD, CNN, and ST-Net visual computing models by evaluating their working mechanisms, their efficacy in the use of cancer with the help of previous research made in the literature, and their limitations in a medical approach.

Computers and computing are topics of discussion in many curriculum areas in secondary school. The four courses recommended by this task group, however, have computing as their primary content. The courses are: Introduction to Computer Science I (a full year course)Introduction to Computer Science II (a full year course)Introduction to a High-level Computer Language (a half-year course)Applications and Implications of Computers (a half-year course)Courses 1 and 2 are designed for students with a serious interest in computer science. Course 1 can serve as a single introductory course for some students and also act as a prerequisite for Course 2. At the end of two years of study, students should be prepared to be placed in second level computer science classes in post-secondary educational institutions or to take the Advanced Placement Exam available through the College Entrance Exam Board.Courses 1 and 2 will require a significant amount of equipment for each student enrolled. Computers, either microcomputers or a timesharing system with convenient storage for files (disks) and high-speed printers are necessary.Courses 3 and 4 are designed to be of general interest to any student at the secondary level. Course 3 is a course about programming. It is a general introduction to the process of writing programs in a high-level computer language. It requires extensive hardware facilities, as students will need to practice using whichever computer language is chosen for the instruction.Course 4 includes information about the ways computers are used and about the impact of computer use on people's lives. Because students in this course will be using a computer to learn about applications, teaching this course requires extensive software in addition to hardware.Courses 1, 3 and 4 have been designed assuming no prerequisite courses and are not interdependent.Teachers of all four of these courses should be qualified in the content area and preferably certified to teach about computing and computer science. The discipline of computer science has been evolving over several years and will continue to change. Courses in computer science will similarly continue to change. Well trained teachers are the cornerstone of effective instruction in such a fluid environment.

The field of mobile robotics has a long tradition and due to recent developments, we expect a huge potential for the future. Expertise in the area of mobile robotics is important for computer science students. The topic has many connections to different other computer science areas such as computer vision, algorithms, planning, world modeling and machine learning but is also related to basic fields such as mathematics, geometry, statistics, graph theory and optimization techniques. Students have to consider hardware and real-time issues, meanwhile they have to deal with uncertainty of data that are based on sensors. Software development differs from typical desktop, office or client-server developments that often are in focus of computer science studies. As a consequence, academic courses on mobile robotics differ in many ways from other courses. A major issue: we have to get the students very quickly to a point to achieve progress in their projects. Moreover, the teacher has to have an environment to manage the different facets of the complex topics.

Introduction The computing sciences are complex fields that combine both theoretical and practical components. Students successfully completing an undergraduate computer science program should have instruction in both the mathematical and theoretical foundations of computing as well as the more practical aspects of how to effectively use computers to solve problems. Software engineering, as its name implies, is more directed toward the practical aspects of how to successfully develop complex systems that meet user requirements and are reliable, usable, and maintainable. Computing Curricula 2005 recognizes the need for more extensive education to produce professional engineers than what can be reasonably provided in a typical computer science program (ACM, 2005). As such, they propose engineering be treated as a totally separate discipline within computer science education. However, while there has been some debate about the exact role engineering should have in a computer science program (Curran, 2003), the ACM Curricula has maintained the importance of engineering to all computer science students and has kept it as a core element in computer science education (ACM, 2008). For purposes of this paper, we will focus on the teaching of engineering within the computer science discipline. Unlike other topics in the computer science major, the techniques and principles taught in engineering are often first developed and refined in industry before arriving in the classroom. As commercial development techniques and tools evolve, so pedagogical methodologies change. Computer science educators have taken different approaches to teaching engineering over the years, both as a result of changing methodologies as well as individual beliefs about what teaching methods work best in a particular academic environment. This paper is a case study in applying current productivity tools (specifically Redmine) in a engineering course at our institution. The objectives of the study are to investigate how to integrate the tools into the existing structure and evaluate their impact. We describe our experience in recently changing our approach to teaching engineering to be more aligned with current tools and how to effectively use them in an academic environment. The paper begins with an overview of engineering teaching methods, then describes our traditional approach and motivation for changing, how the new approach was integrated into the course, our experience with the change, and, finally, our plans for the future Software Engineering Education Background Software Engineering is defined as the application of a systematic, disciplined, quantifiable approach to the development, operation and maintenance of software (Petkovic, Thompson, & Todtenhoefer, 2006, p. 294). The need to teach engineering in colleges has been identified for decades. Stiller & LeBlanc (2002) point out as far back as the early 1990's, ACM Computing Curricula suggested that the at least one engineering course should be required in accredited computer science programs. They point out that the number of large projects in industry demand this and suggest that the proof of the success of these accredited computer science programs should be seen in the reduction of failure in the design and operation of large computer programs. Software engineering programs can be thought of as a replacement for the old apprenticeship programs which taught the trades to workman (Stroulia, Bauer, Craig, Reid, & Wilson, 2011). The issue, however, is how to bring this effect into the classroom. Many educators feel that current practices of teaching engineering are not adequately preparing students for the real world of development. Nurkkala & Brandle (2011) summarize the problems with current teaching approaches: * No product--students are creating projects, not commercial grade products * Short duration--single semester, or two-semester, courses impose an artificial time constraint * High turnover--new students each semester means the talent pool remains shallow and student skills are not developing based on previous experience * Low complexity--by necessity given time constraints and skill sets * No maintenance--as a result of short duration, students do not experience a key aspect of development, the maintenance phase * No customer--most engineering projects do not interface with a real customer To address these shortcomings, different approaches to teaching engineering have emerged and been proposed in the literature. …

Geographical AnalysisVolume 8, Issue 1 p. 77-93 Free Access Surface Networks John L. Pfaltz, John L. Pfaltz This research was supported in part by National Science Foundation Grant DCR-74–13353. John L. Pfaltz is associate professor, Department of Applied Mathematics and Computer Science, University of Virginia.Search for more papers by this author John L. Pfaltz, John L. Pfaltz This research was supported in part by National Science Foundation Grant DCR-74–13353. John L. Pfaltz is associate professor, Department of Applied Mathematics and Computer Science, University of Virginia.Search for more papers by this author First published: January 1976 https://doi.org/10.1111/j.1538-4632.1976.tb00530.xCitations: 66 John L. Pfaltz is associate professor, Department of Applied Mathematics and Computer Science, University of Virginia. This research was supported in part by National Science Foundation Grant DCR-74–13353. AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Citing Literature Volume8, Issue1January 1976Pages 77-93 ReferencesRelatedInformation

It is with great pleasure that I welcome you to SIGMETRICS 2008. Performance modeling and measurement are critical in the design and development of information technologies, ranging from computer systems to computer networks and the World Wide Web. Over the past decades we have seen an increasing influence of the modeling and measurement work in various disciplines in computer science. As a result, our community has been growing with broader application backgrounds and technical interests. This year's conference program is particularly exciting, with a number of new features. For the first time, the main conference has grown to a program of three full days with 36 papers. Also for the first time, we have a demo competition and a student thesis panel. In addition, there are three keynotes given by illustrious scholars from academia, François Baccelli (member of the French Academy of Sciences); from a funding agency, Jeannette Wing (Assistant Director of the Computer and Information Science and Engineering Directorate of the National Science Foundation); and from industry, Harrick Vin (Vice President of Research and Development at Tata Consultancy Services). Also new this year is a panel on Performance Analysis in the Real World, where all the panelists come from industrial production environments and will provide an industrial perspective of performance modeling and analysis. The conference program is further augmented with stimulating tutorials and workshops. This year, there are nine excellent tutorials on topics ranging from analysis and control techniques to performance engineering methodology and network economics. The MAthematical performance Modeling and Analysis (MAMA) workshop continues its success with its 10th edition in 2008. The Workshop on Hot Topics in METRICS (HotMetrics) will be inaugurated immediately after the main conference, in parallel with the third International Workshop on Feedback Control Implementation and Design in Computing Systems and Networks (FeBID). These tutorials and workshops complement the main conference and significantly enhance SIGMETRICS 2008.