Academic literature on the topic 'G/PL/I (Computer program language)'

A language is said to be homogeneous when all its words have the same length. Homogeneous languages thus form a monoid under concatenation. It becomes freely commutative under the simultaneous actions of every permutation group on the collection of homogeneous languages of length n ∈ ℕ. One recovers the isothetic regions from (Haucourt 2017, to appear (online since October 2017)) by considering the alphabet of connected subsets of the space |G|, viz the geometric realization of a finite graph G. Factoring the geometric model of a conservative program amounts to parallelize it, and there exists an efficient factoring algorithm for isothetic regions. Yet, from the theoretical point of view, one wishes to go beyond the class of conservative programs, which implies relaxing the finiteness hypothesis on the graph G. Provided that the collections of n-dimensional isothetic regions over G (denoted by |G|) are co-unital distributive lattices, the prime decomposition of isothetic regions is given by an algorithm which is, unfortunately, very inefficient. Nevertheless, if the collections |G| satisfy the stronger property of being Boolean algebras, then the efficient factoring algorithm is available again. We relate the algebraic properties of the collections |G| to the geometric properties of the space |G|. On the way, the algebraic structure |G| is proven to be the universal tensor product, in the category of semilattices with zero, of n copies of the algebraic structure |G|.

There is more than a decade-long history of using static analysis to find bugs in systems such as Linux. Most of the existing static analyses developed for these systems are simple checkers that find bugs based on pattern matching. Despite the presence of many sophisticated interprocedural analyses, few of them have been employed to improve checkers for systems code due to their complex implementations and poor scalability. In this article, we revisit the scalability problem of interprocedural static analysis from a “Big Data” perspective. That is, we turn sophisticated code analysis into Big Data analytics and leverage novel data processing techniques to solve this traditional programming language problem. We propose Graspan , a disk-based parallel graph system that uses an edge-pair centric computation model to compute dynamic transitive closures on very large program graphs. We develop two backends for Graspan, namely, Graspan-C running on CPUs and Graspan-G on GPUs, and present their designs in the article. Graspan-C can analyze large-scale systems code on any commodity PC, while, if GPUs are available, Graspan-G can be readily used to achieve orders of magnitude speedup by harnessing a GPU’s massive parallelism. We have implemented fully context-sensitive pointer/alias and dataflow analyses on Graspan. An evaluation of these analyses on large codebases written in multiple languages such as Linux and Apache Hadoop demonstrates that their Graspan implementations are language-independent, scale to millions of lines of code, and are much simpler than their original implementations. Moreover, we show that these analyses can be used to uncover many real-world bugs in large-scale systems code.

Abstract Separation logic (SL) is a logical formalism for reasoning about programs that use pointers to mutate data structures. It is successful for program verification as an assertion language to state properties about memory heaps using Hoare triples. Most of the proof systems and verification tools for ${\textrm{SL}}$ focus on the decidable but rather restricted symbolic heaps fragment. Moreover, recent proof systems that go beyond symbolic heaps are purely syntactic or labelled systems dedicated to some fragments of ${\textrm{SL}}$ and they mainly allow either the full set of connectives, or the definition of arbitrary inductive predicates, but not both. In this work, we present a labelled proof system, called ${\textrm{G}_{\textrm{SL}}}$, that allows both the definition of cyclic proofs with arbitrary inductive predicates and the full set of SL connectives. We prove its soundness and show that we can derive in ${\textrm{G}_{\textrm{SL}}}$ the built-in rules for data structures of another non-cyclic labelled proof system and also that ${\textrm{G}_{\textrm{SL}}}$ is strictly more powerful than that system.

Python is a relatively new computing language, created by Guido van Rossum [A.S. Tanenbaum, R. van Renesse, H. van Staveren, G.J. Sharp, S.J. Mullender, A.J. Jansen, G. van Rossum, Experiences with the Amoeba distributed operating system, Communications of the ACM 33 (1990) 46–63; also on-line at http://www.cs.vu.nl/pub/amoeba/, which is particularly suitable for teaching a course in computational physics. There are two questions to be considered: (i) For whom is the course intended? (ii) What are the criteria for a suitable language, and why choose Python? The criteria include the nature of the application. High performance computing requires a compiled language, e.g., FORTRAN. For some applications a computer algebra, e.g., Maple, is appropriate. For teaching, and for program development, an interpreted language has considerable advantages: Python appears particularly suitable. Python‟s attractions include (i) its system of modules which makes it easy to extend, (ii) its excellent graphics (VPython module), (iii) its excellent on line documentation, (iv) it is free and can be downloaded from the web. Python and VPython will be described briefly, and some programs demonstrated numerical and animation of some phenomenal physics. In this article, we gave solution of circle polarization by solving Maxwell equation.

Abstract The efficiency of D4 Gaussian elimination on a vector computer, the Cray- 1/S, it examined. The algorithm used in this work is employed routinely in Phillips Petroleum Co. reservoir simulation models. Comparisons of scalar Phillips Petroleum Co. reservoir simulation models. Comparisons of scalar and vector Cray-1/S times are given for various example cases including multiple unknowns per gridblock. Vectorization of the program on the Cray- 1/S is discussed. Introduction In reservoir simulation, the solution of large systems of linear equations accounts for a substantial percentage of the computation time. Methods used today consist of both iterative and direct solution algorithms. Because of the theoretical savings in both storage and computing labor, D4 Gaussian elimination is a popular direct solution algorithm and is used widely on conventional scalar computers. In this paper we investigate the efficiency of the D4 algorithm on a computer with vector processing capabilities-the Cray-1/S. The D4 (or alternate diagonal) algorithm originally was presented by Price and Coats in 1973. Since that time much work has been done on the Price and Coats in 1973. Since that time much work has been done on the algorithm including an investigation by Nolen on the vector performance of D4 on the CDC Star 100 and Cyber 203 on single-unknown-per-gridblock example cases. Levesque has presented a comparison of the Cray-1 and Cyber 205 in reservoir simulation that includes the D4 algorithm. Vector performance of the Cray-1 on linear algebra kernels, both sparse and dense, performance of the Cray-1 on linear algebra kernels, both sparse and dense, also has been reported. Vector performance on these kernels typically is expressed in terms of million floating point operations per second (MFLOPS). Our objective here is to evaluate vector performance on a typical production code written in FORTRAN for a scalar computer. Therefore, performance, or efficiency, will be evaluated in terms of both scalar and vector CPU times on the Cray-1/S. We include vector performance on the original code with automatic vectorization enabled, and vector performance on the same code with minor restructuring, automatic performance on the same code with minor restructuring, automatic vectorization enabled, and the use of Cray assembly language (CAL) basic linear algebra kernels. Example cases for multiple unknowns per gridblock are presented. Reservoir Flow Equations The reservoir flow equations written using a seven-point finite difference formulation can be expressed as ...........................(1) where the terms A, B... G are matrices of order N equal to the number of unknowns per gridblock. represents the vector of unknowns at cell i, j, k, and H is the vector of residuals of the flow equations at cell i, j, k at iteration . Values of N from 1 to 10 typically are encountered depending on the type of simulator and the degree of implicitness used. For example, N is equal to one for an implicit pressure, explicit saturation (IMPES) black-oil model; three for a fully implicit black-oil model; five for an implicit three-component steamflood model and usually 10 or less for an implicit compositional model. Driver Program To facilitate timing studies in this work, a driver program was written to calculate coefficients for the D4 Gaussian elimination routine. Input to the program consists of grid dimensions and the number of unknowns per gridblock. All elements of the off-diagonal matrices (A, C, D... G) were set equal to 1. To guarantee a nonsingular solution, the B matrix was set equal to -5 for one unknown and as below for N unknowns. ............................(2) Right-side coefficients, H, were calculated by assuming a unit solution for . No-flow boundary conditions were used, which require specific matrices, such as A for I = 1 and C for I = NX, to be set equal to zero. Description of Hardware and Software All run times reported in this work were obtained on the Cray-1/S, Serial No. 23, at United Computing Systems in Kansas City, MO. Serial No. 23 contains 1 million 64-bit words of central memory interleaved in 16 memory banks and no input/output (I/O) subsystems. The FORTRAN compiler used was CFT 1.09. CPU times were obtained by calling SECOND, a FORTRAN-callable utility routine that returns CPU time since the start of the job in FPS'S. CPU overhead incurred for each call to SECOND is approximately 2.5 microseconds. For all reported Cray-1/S times, "vector" refers to the original FORTRAN code run with automatic vectorization enabled, which is the normal operating mode. SPEJ p. 121

Introduction. The current level of agricultural production, including horticulture, is determined by intelligent machine technologies and new generation technical means with modern information and instrument support. The implementation of digital intelligent agricultural technologies in industrial gardening requires a fundamental change in the paradigm of technical support, based on the development and application of new automatic and unmanned machines, equipment and software for managing work processes of machines, navigating technical means, controlling the implementation of technological operations, monitoring the yield of agricultural crops, analyzing diseases and pests on plants and other technological functions. Materials and Methods. 3D model is visualized in the computer-aided design “KOMPAS-3D” through using the methods of mathematical modeling, theoretical mechanics and optimal design. A prototype of an automated unit for magnetic pulse processing of plants is made. The program code for calculating the required movement of the actuator rod is developed in the Sublime Text editor. C++programming language was used. The functionality of the computer program is related to the capabilities of controllers STM32, Arduino Mega/ Uno/Nano. Nextion 2.4 (the TFT screen 320x240) for the graphical output and interaction was used. Results. An automated unit with the algorithm of the drive control system of working bodies were developed during the technological operation of magnetic pulse processing of plants, taking into account the agro-technological parameters of garden plantations. A computer program with both automat and remote control was designed for driving the working bodies. Conclusions. The unit allows introducing a new environmentally safe technological method of stimulating vital and growth processes of fruit crops. This device provides the most efficient operation through automatic adjustment to various agro-technological parameters of plantings, providing the required value of magnetic induction in the working area on plant objects in the field. Keywords: magnetic pulse processing, control system, automated unit, irradiation of plants, gardening, low-frequency magnetic field For citation: Smirnov I. G., Khort D. O., Filippov R. A., Kutyrev A. I., Artiushin A. A. Automated Unit for Magnetic-Pulse Processing of Plants in Horticulture. Vestnik Mordovskogo universiteta = Mordovia University Bulletin. 2018; 28(4):624–642. DOI: https://doi.org/10.15507/0236-2910.028.201804.624-642

Experimental measurements of shape memory alloys wires Paper deals with examinations of properties of shape memory alloy actuators. Authors describe design of own laboratory stand for obtaining electro-thermo-mechanical characteristics of SMA wires (maximum length 900 mm). The stand allows for semi-automatic measurements of voltage and current (supplying the actuator), temperature of wire and its extension. Data acquisition and control signals are realized by PC computer. All elements of the measuring system are connected by GPIB network (IEEE 488.2 standard). Control program for static measurements was written in G language (LabVIEW environment). Temperature is measured using infrared camera Flir A325. Displacement measurement system contains optical sensor (converting piston movement into series of pulses), pulses counter, PWM signal generator (PWM signal fulfillment is proportional to number of pulses), lowpass filter and buffer conditioning external signal. For dynamic measurements data recording is performed using digital oscilloscope Tektronix MSO 2024 equipped with four separated channels and digital filter. Wide range of examinations of several SMA wires allowed for drawing its exploitative characteristic helpful for practical use. It shows length change of actuator as a function of mechanical load (Fig. 10). Finally some example static as well as dynamic characteristics are presented and short discussion is carried out.

Language makes human communication possible. Apart from everyday applications, language can provide insights into individuals’ thinking and reasoning. Machine-based analyses of text are becoming widespread in business applications, but their utility in learning contexts are a neglected area of research. Therefore, the goal of the present work is to explore machine-assisted approaches to aid in the analysis of students’ written compositions. A method for extracting common topics from written text is applied to 78 student papers on technology and ethics. The primary tool for analysis is the Latent Dirichlet Allocation algorithm. The results suggest that this machine-based topic extraction method is effective and supports a promising prospect for enhancing classroom learning and instruction. The method may also prove beneficial in other applied applications, like those in clinical and counseling practice. References Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent Dirichlet Allocation. Journal of Machine Learning Research 3, 993-1022. Bruner, J. (1990). Acts of meaning. Cambridge, MA: Harvard University Press. Chen, K. Y. M., & Wang, Y. (2007). Latent dirichlet allocation. http://acsweb.ucsd.edu/~yuw176/ report/lda.pdf. Chung, C. K., & Pennebaker, J. W. (2008). Revealing dimensions of thinking in open-ended self-descriptions: An automated meaning extraction method for natural language. Journal of research in personality, 42(1), 96-132. Feldman, S. (1999). NLP meets the Jabberwocky: Natural language processing in information retrieval. Online Magazine, 23, 62-73. Retrieved from: http://www.onlinemag.net/OL1999/ feldmann5.html Mishlove, J. (2010). https://www.youtube.com/watch?v=0XTDLq34M18 (Accessed June 12, 2018). Ostrowski, D. A. (2015). Using latent dirichlet allocation for topic modelling in twitter. In Semantic Computing (ICSC), 2015 IEEE International Conference (pp. 493-497). IEEE. Pennebaker, J. W. (2004). Theories, therapies, and taxpayers: On the complexities of the expressive writing paradigm. Clinical Psychology: Science and Practice, 11(2), 138-142. Pennebaker, J.W., Boyd, R.L., Jordan, K., & Blackburn, K. (2015). The development and psychometric properties of LIWC 2015. Austin, TX: University of Texas at Austin. Pennebaker, J. W., Chung, C. K., Frazee, J., Lavergne, G. M., & Beaver, D. I. (2014). When small words foretell academic success: The case of college admissions essays. PLoS ONE, 9(12), e115844. Pennebaker, J. W., & King, L. A. (1999). Linguistic styles: Language use as an individual difference. Journal of Personality and Social Psychology, 77(6), 1296-1312. Recchia, G., Sahlgren, M., Kanerva, P., & Jones, M. N. (2015). Encoding sequential information in semantic space models: Comparing holographic reduced representation and random permutation. Computational intelligence and neuroscience, 2015, 1-18. Salzmann, Z. (2004). Language, Culture, and Society: An Introduction to Linguistic Anthropology (3rd ed). Westview Press. Schank, R. C., Goldman, N. M., Rieger III, C. J., & Riesbeck, C. (1973). MARGIE: Memory analysis response generation, and inference on English. In IJCAI, 3, 255-261. Taraban, R., Marcy, W. M., LaCour Jr., M. S., & Burgess II, R. A. (2017). Developing machine-assisted analysis of engineering students’ ethics course assignments. Proceedings of the American Society of Engineering Education (ASEE) Annual Conference, Columbus, OH. https://www.asee.org/public/conferences/78/papers/19234/view. Taraban, R., Marcy, W. M., LaCour, M. S., Pashley, D., & Keim, K. (2018). Do engineering students learn ethics from an ethics course? Proceedings of the American Society of Engineering Education – Gulf Southwest (ASEE-GSW) Annual Conference, Austin, TX. http://www.aseegsw18.com/papers.html. Taraban, R., & Marshall, P. H. (2017). Deep learning and competition in psycholinguistic research. East European Journal of Psycholinguistics, 4(2), 67-74. Weizenbaum, J. (1966). ELIZA—a computer program for the study of natural language communication between man and machine. Communications of the ACM, 9(1), 36-45. Winograd, T. (1972). Understanding natural language. New York: Academic Press.

One form of early mathematical recognition is to introduce the concept of geometric shapes. Geometry is an important scientific discipline for present and future life by developing various ways that fit 21st century skills. This study aims to overcome the problem of early mathematical recognition of early childhood on geometry, especially how to recognize geometric forms based on computer learning. A total of 24 children aged 4-5 years in kindergarten has to carrying out 2 research cycles with a total of 5 meetings. Treatment activities in each learning cycle include mentioning, grouping and imitating geometric shapes. There were only 7 children who were able to recognize the geometric shapes in the pre-research cycle (29.2%). An increase in the number of children who are able to do activities well in each research cycle includes: 1) The activities mentioned in the first cycle and 75% in the second cycle; 2) Classifying activities in the first cycle were 37.5% and 75% in the second cycle; 3) Imitation activities in the first cycle 54.2% and 79.2% in the second cycle. The results of data acquisition show that computer learning application can improve the ability to recognize geometric shapes, this is because computer learning provides software that has activities to recognize geometric shapes with the animation and visuals displayed. Keywords: Early Childhood Computer Learning, Geometry Forms, Early Math Skills Reference Alia, T., & Irwansyah. (2018). Pendampingan Orang Tua pada Anak Usia Dini dalam Penggunaan Teknologi Digital. A Journal of Language, Literature, Culture and Education, 14(1), 65– 78. https://doi.org/10.19166/pji.v14i1.639 Ameliola, S., & Nugraha, H. D. (2013). Perkembangan Media Informasi dan Teknologi Terhadap Anak di Era Globalisasi. International Conferences in Indonesian Studies : “Etnicity and Globalization.” Anderson, L. W., Krathwohl, D. R., & Bloom, B. S. (2001). A taxonomy for learning, teaching, and assessing: a revision of Bloom’s taxonomy of educational objectives. New York: Longman. Arikunto, S. (2010). Prosedur Penelitian Suatu Pendekatan Praktik. Jakarta: Asdi Mahasatya. Arsyad, N., Rahman, A., & Ahmar, A. S. (2017). Developing a self-learning model based on open-ended questions to increase the students’ creativity in calculus. Global Journal of Engineering Education, 19(2), 143–147. https://doi.org/10.26858/gjeev19i2y2017p143147 Asiye, I., Ahmet, E., & Abdullah, A. (2018). Developing a Test for Geometry and Spatial Perceptions of 5-6 Year-Old. Kastamonu Education Journal, 26(1). Aslan, D., & Yasare, A. (2007). Three to Six Years OldChildren’s Recognition of Geometric Shapes. International Journal of Early Years Education, 15 :1, 83–104. Ben-Yehoshua, D., Yaski, O., & Eilam, D. (2011). Spatial behavior: the impact of global and local geometry. Animal Cognition Journal, 13(3), 341–350. https://doi.org/10.1007/s10071- 010-0368-z Charlesworth, R., & Lind, K. K. (2010). Math and Sciend for Young Children. Canada: Wadsworth/Cengage Learning. Chen, J.-Q., & Chang, C. (2006). using computers in early childhood classrooms teachers’ attitudes,skills and practices. Early Childhood Research. Clements, D. H., & Samara. (2003). Strip mining for gold: Research and policy in educational technology—a response to “Fool’s Gold.” Association for the Advancement of Computing in Education (AACE) Journal, 11(1), 7–69. Cohen, L., & Manion, L. (1994). Research Methods in Education (fourth edi). London: Routledge. Conorldi, C., Mammarela, I. C., & Fine, G. G. (2016). Nonverbal Learning Disability (J. P. Guilford, Ed.). New York. Corey, S. M. (1953). Action Research to Improve School Practice. New York: Teachers College, Columbia University. Couse, L. J., & Chen, D. W. (2010). A tablet computer for young children? Exploring its viability for early childhood education. Journal of Research on Technology in Education, 43(1), 75– 98. https://doi.org/10.1080/15391523.2010.10782562 Delima, R., Arianti, N. K., & Pramudyawardani, B. (2015). Identifikasi Kebutuhan Pengguna Untuk Aplikasi Permainan Edukasi Bagi Anak Usia 4 sampai 6 Tahun. Jurnal Teknik Informatika Dan Sistem Informasi, 1(1). Depdiknas. (2007). Permainan Berhitung Permulaan Di Taman Kanak-kanak. In Pedoman Pembelajaran. Jakarta: Depdiknas. Djadir, Minggi, I., Ja’faruddin., Zaki, A., & Sidjara, S. (2017). Sumber Belajar PLPG 2017: Bangun Datar. In Modul PLPG. Jakarta: Kementrian Pendidikan dan Kebudayaan Direktorat Jenderal Guru dan Tenaga Kependidikan.Dooley, T., Dunphy, E., & Shiel, G. (2014). Mathematics in Early Childhood and Primary Education (3-8 years). Duncan, G. J., Dowsett, C. J., Claessens, A., Magnuson, K., Huston, A. C., Klebanov, P., ... Japel, C. (2007). School Readiness and Later Achievement. Developmental Psychology, 43(6), 1428–1446. https://doi.org/10.1037/0012-1649.43.6.1428 Duncan, G. J., & Magnuson, K. (2011). The nature and impact of early achievement skills, attention skills, and behavior problems. Whither Opportunity?: Rising Inequality, Schools, and Children’s Life Chances, (0322356), 47–69. Edwards, S. (2009). Early Childhood Education and Care: a sociocultural Approach. New South Wales: Pademelon Press. Feliyanah, Norman, S., & Yulidesni. (2014). Meningkatkan Kemampuan Matematika dengan Menggunakan Teknik Mengurutkan dan Membandingkan. Universitas Bengkulu. Gardner, H. (2011). Frame of Mind ; The theory of Multiple Intelegences. New York: Basic Book. Gimbert, B., & Cristol, D. (2004). Teaching Curriculum with Technology: Enhancing Children’s Technological Competence During Early Childhood. Early Childhood Education Journal, 31(1). Gulay, H. (2011a). The evaluation of the relationship between the computer using habits and proso_cial and aggressive behaviours of 5–6 years old children. International Journal of Academic Research, 3(2), 252. Gulay, H. (2011b). The evaluation of the relationship between the computer using habits and proso_cial and aggressive behaviours of 5–6 years old children. International Journal of Academic Research, 3(2), 252–257. Gunawan, I., & Palupi, A. R. (2012). Taksonomi Bloom-Revisi Ranah Kognitif; Kerangka Landasan untuk Pembelajaran, Pengajaran, dan Penilaian. Jurnal Pendidikan Dasar Dan Pembelajaran, 2 No.2, 100–108. Inan, H. Z., & Dogan-Temur, O. (2010). Understanding kindergarten teachers’ perspectives of teaching basic geometric shapes: A phenomenographic research. ZDM - International Journal on Mathematics Education, 42(5), 457–468. https://doi.org/10.1007/s11858-010- 0241-1 Jackman, H. I., Beaver, N. H., & Wyatt, S. S. (2014). Early Childhood Curriculum: A child’s connection to the world. (sixth edit). Canada: Cengage Learning. Kennedy, L. M., Tipps, S., & Johnson, A. (2008). Guiding Children’s Learning of Mathematic (Eleventh E; Belmot, Ed.). CA: Thomson Wadsworth. Mackintosh, B. B., & McCoy, D. C. (2019). Exploring Social Competence as a Mediator of Head Start’s Impact on Children’s Early Math Skills: Evidence from the Head Start Impact Study. Early Education and Development, 30(5), 655–677. https://doi.org/10.1080/10409289.2019.1576156 Martin, M. O., Mullis, I. V. S., Foy, P., & Stanco, G. M. (2011). Results in Science. Mirawati. (2017). Matematika Kreatif; Pembelajaran Matematika bagi Anak Usia Dini Melalui Kegiatan yang Menyenangkan dan Bermakna. Jurnal Anak Usia Dini Dan Pendidikan Anak Usia Dini, 3. Mohammad, M., & Mohammad, H. (2012). Computer integration into the early childhood curriculum. Education, 133(1), 97–116. National Research Council. (2009). Mathematics Learning in Early Chidhood Paths Toward Excellence and Equity (C. T. Cross, T. Woods, & H. Schweingruber, Eds.). Washinton D.C: The National Academies Press. Norton, A., & Nurnberger-Haag, J. (2018). Bridging frameworks for understanding numerical cognition. Journal of Numerical Cognition, 4(1), 1–8. https://doi.org/10.5964/jnc.v4i1.160 Novitasari, D. R. (2010). Pembangunan Media Pembelajaran Bahasa Inggris Untuk Siswa Kelas 1 Pada Sekolah Dasar Negeri 15 Sragen. Sentra Penelitian Engineering Dan Edukas, Volume 2 N. Papadakis, S., Kalogiannakis, M., & Zaranis, N. (2017). Improving Mathematics Teaching in Kindergarten with Realistic Mathematical Education. Early Childhood Education Journal, 45(3), 369–378. https://doi.org/10.1007/s10643-015-0768-4 Papalia, Old, & Feldman. (2009). Human Development (Psikologi Perkembangan (Kesembilan). Jakarta: Kencana. Paquette, K. R., Fello, S. E., & Jalongo, M. R. (2007). The talking drawings strategy: Using primary children’s Illustrations and oral language to improve comprehension of expository text. Early Childhood Education Journal, 35(1), 65–73. https://doi.org/10.1007/s10643- 007-0184-5 Putra, L. D., & Ishartiwi. (2015). Pengembangan Multimedia Pembelajaram Interaktif Mengenal Angka dan Huruf untuk Anak Usia Dini. Jurnal Inovasi Teknologi Pendidikan, 2(2). Rich, B., & Thomas, C. (2009). Geometry: Includes Plane, Analytic, and Transformational Geometries. . (4th Editio). New York: McGraw-Hill. Rochanah, L. (2016). Pemanfaatan Media Berbasis Komputer Untuk Meningkatkan Kemampuan Huruf pada Anak Usia Dini (Urgensi Media Berbasis Komputer pada Peningkatan Kemampuan Mengenal Huruf ). Jurnal Program Studi PGRA, Volume 2 N, 1–8. Runtukahu, T., & Kandou, S. (2014). Pembelajaran matematika dasar bagi anak berkesulitan belajar. Yogyakarta: Ar-ruzz Media. Santrock, J. W. (2016). Children (Thirteenth). New York: McGraw-Hill Education. Sarama, J., & Clements, D. H. (2006). Mathematics, Young Students, and Computers: Software, Teaching Strategies and Professional Development. The Mathematics Educato, 9(2), 112– 134. Schoenfeld, A. H., & Stipek, D. (2011). Math Matters. Barkeley, California.Shilpa, S., & Sunita, M. (2013). A Study About Role of Multimedia in Early Childhood Education. International Journal of Humanities and Social Science Invention, 2(6). Siswono, T. Y. E. (2012). Belajar dan Mengajar Matematika Anak Usia Dini. Universitas Negeri Surabaya.Smaldino, S. E., Russel, J. D., & Lowther, D. L. (2014). Instructional Technology & Media for Learning (9th ed.). Jakarta: Kencana Prenada Media Group. Sudaryanti. (2006). Pengenalan Matematika Anak Usia Dini. Yogyakarta: FIP UNY. Sufa, F. F., & Setiawan, H. Y. (2017). Analisis Kebutuhan Anak Usia 4-6 Tahun Pada Pembelajaran Berbasis Komputer Pada Anak Usia Dini. Research Fair Unisri, 1(1). Suharjana, A. (2008). Pengenalan Bangun Ruang dan Sifat-sifatnya di SD. Yogyakarta: Pusat Pengembangan dan Pemberdayaan Pendidik dan Tenaga Kependidikan Matematika. Sujiono, Y . N. (2014). Batasan dan Dasar T eori Pengembangan Kognitif. In Hakikat Pengembangan Kognitif (p. 12). Suryana, D. (2013). Pendidikan Anak Usia Dini (teori dan praktik pembelajaran). Padang: UNP Press. Susperreguy, M. I., & Davis-Kean, P. E. (2016). Maternal Math Talk in the Home and Math Skills in Preschool Children. Early Education and Development, 27(6), 841–857. https://doi.org/10.1080/10409289.2016.1148480 Suwarna. (2010). Pengembangan Multimedia Pembelajaran untuk Pembinaan Kreativitas Melukis di Taman Kanak-kanak. Jurnal Universitas Negeri Yogyakarta. Suziedelyte, A. (2012). Can video games affect children’s cognitive and non-cognitive skills? UNSW Australian School of Business Research Paper. https://doi.org/10.2139/ssrn.2140983 Tarigan, D. (2006). Pembelajaran Matematika Realistik. Jakarta: Departeman Pendidikan Nasional, Direktorat Jendral Pendidikan Tunggi, Direktorat Pembinaan Pendidikan Tenaga Kependidikan dan Ketenaga Perguruan Tinggi. Tatang, S. (2012). Ilmu Pendidikan. Bandung: Pustaka Setia.Trawick, M. (2007). Enemy Line ; Warfare, Childhood, and Play in Batticaloa. London: University of California Press. Trifunović, A., Čičević, S., Lazarević, D., Mitrović1, S., & Dragovi, M. (2018). Comparing Tablets (Touchscreen Devices and PCs in Preschool Children Education: Testing Spatial Relationship Using Geometric Syimbols Traffic Signs. IETI Transections on Economics and Safety, 2(1), 35–41. https://doi.org/10.6722/TES.201808_2(1).0004 Vitianingsih, A. V. (2016). Game Edukasi Sebagai Media Pembelajaran Pendidikan Anak Usia Dini. Jurnal INFORM, 1 No. 1. Wang, F., & Kinzie, M. B. (2010). Applying Technology to Inquiry- Based Learning in Early Childhood Education. Early Childhood Education Journal. Weil, M., Calhoun, E., & Joyce, B. (2011). Models of Teaching. New York.: New York. Zack, N. (2014). Philosophy of Science and Race. New York: Routledge. Zare, Sarikhani, Salarii, & Mansouri. (2016). The Impact Of E-learning on University Student’s Academic Achievement and Creativity. Journal of Technical Education and Training (JTET), 8(11).

Background:The use of eHealth tools (internet, mobile applications, connected devices) in chronic diseases and in the field of rheumatoid arthritis (RA) is growing (1). eHealth may improve the overall care of patients suffering from chronic diseases (2,3).Objectives:The main objective of this study was to describe the use of eHealth by RA patients in France. The secondary objectives were to identify differences in demographic and disease characteristics between patients using eHealth tools or not. We also assessed patients’ expectations about digital devices.Methods:We conducted a cross-sectional, multicenter study. Patients with RA according to the ACR / EULAR 2010 criteria were recruited in 5 university hospitals (Bordeaux, Clermont-Ferrand, Limoges, Montpellier and Toulouse). Patients completed an anonymous self-questionnaire including demographic data, assessment about the use of eHealth (access, support, frequency of use, type of use, reason for use). The treating rheumatologist of the patient filled in an independent medical questionnaire collecting the disease characteristics, the activity of RA and the treatments. Data were collected from December 2018 to July 2019.Results:The questionnaires were completed by 575 patients, with an average age of 62±13 years, 78% of whom were women. 473 (82%) patients had access to eHealth through a computer (n=402, 86%), a tablet (n=188, 40%) and/or a smartphone (n=221, 47%). Among them, 36% (170/473) used internet for health in general and 29% (134/473) specifically for RA. Regarding the use of eHealth for RA, all patients used it to learn about their disease and 66% (89/134) as a tool to help monitoring RA. Most of them (n=87/125, 70%) had a paper medical record, 24/125 patients (19%) used a digital tool (spreadsheet n=10, 8% and / or mobile application n=9, 7% and / or website n=5, 4%) and 31/125 patients (25%) did not use any tool to monitor their RA. Few patients (16/126, 13%) used numeric reminders for their treatments. A specific application for RA was used by 27/127 patients (21%) using eHealth. Age, level of study, employment, treatment, comorbidities, membership of a patient association group and patient education program were associated with the use of eHealth for RA in univariate analysis. In multivariate analysis, membership of patient’s association (OR: 5.8 [3.0-11.2]), bDMARDs use (OR: 0.6 [0.4-1]) and comorbidities (OR: 0.7 [0.6-0.8]) remained associated with eHealth use for RA. According to the patients, recommendation by a doctor (n=225/330, 68%), ease of use (n=105/330, 32%) and data security (n=69/330, 21%) were the factors that would favor the use of eHealth.Conclusion:To date, few patients used eHealth for their disease. The use of a reliable and validated eHealth tool in RA could therefore be promoted by rheumatologist and might optimize the therapeutic adherence.References:[1]Mosa ASM, Yoo I, Sheets L. A systematic review of healthcare applications for smartphones. BMC Med Inform Decis Mak. 10 juill 2012;12:67.[2]Lorig KR, Ritter PL, Laurent DD, Plant K. The internet-based arthritis self-management program: a one-year randomized trial for patients with arthritis or fibromyalgia. Arthritis Rheum. 15 juill 2008;59(7):1009‑17.[3]Charpentier G, Benhamou P-Y, Dardari D, Clergeot A, Franc S, Schaepelynck-Belicar P, et al. The Diabeo software enabling individualized insulin dose adjustments combined with telemedicine support improvesDisclosure of Interests:Marion Magnol: None declared, Eleonore Berard: None declared, Claire Rempenault: None declared, Benjamin Castagne: None declared, marine pugibet: None declared, Cédric Lukas: None declared, Anne Tournadre: None declared, Pascale Vergne-Salle: None declared, Thomas Barnetche: None declared, Marie-Elise Truchetet: None declared, Adeline Ruyssen-Witrand Grant/research support from: Abbvie, Pfizer, Consultant of: Abbvie, BMS, Lilly, Mylan, Novartis, Pfizer, Sandoz, Sanofi-Genzyme

The G-Net research group at Ball State University previously developed a graph editor, written in Java, with limited algorithm support. This editor was modified until the code had the instability of a legacy system. It was decided that, rather than continue working with the old system, a new version would be created.The enhancements planned for this new version were more efficient data structures, easy addition of new algorithms, and animated algorithm output. Additionally, the new version was to be written in compliance with the latest Java standards. This paper describes the structure of this new program, Jedit3.1. An overview of the structure of the program and detailed descriptions of the material that future programmers will need to understand in order to add new algorithms is included. Appropriate descriptions are included for files that future programmers should understand but not necessarily modify.
Department of Computer Science

There are increasing demands for graphics-oriented software packages for graph theory teaching and research. G-Net, a departmental research project headed by Dr. Jay Bagga, is an effort to create a software package that comprises of a graph database, a graph editor, 'and a collection of graph algorithms. Also, with widespread use of the World Wide Web, the graph editor should be accessible through the Web. Taking these issues into consideration Jedit (Java Graph editor) is developed. This thesis concentrates on the design and implementation of a graph editor and a graph object (Jgraph). Jgraph is developed in java to implement the graph algorithms in future. One of the unique features of this graph editor is that it can be used as stand-alone application or as an applet for the Web. In addition, it also provides a friendly user interface.
Department of Computer Science

The effective use of GPUs for accelerating applications depends on a number of factors including effective asynchronous use of heterogeneous resources, reducing data transfer between CPU and GPU, increasing occupancy of GPU kernels, overlapping data transfers with computations, reducing GPU idling and kernel optimizations. Overcoming these challenges require considerable effort on the part of the application developers. Most optimization strategies are often proposed and tuned specifically for individual applications. Message-driven executions with over-decomposition of tasks constitute an important model for parallel programming and provide multiple benefits including communication-computation overlap and reduced idling on resources. Charm++ is one such message-driven language which employs over decomposition of tasks, computation-communication overlap and a measurement-based load balancer to achieve high CPU utilization. This research has developed an adaptive runtime framework for efficient executions of Charm++ message-driven parallel applications on GPU systems. In the first part of our research, we have developed a runtime framework, G-Charm with the focus primarily on optimizing regular applications. At runtime, G-Charm automatically combines multiple small GPU tasks into a single larger kernel which reduces the number of kernel invocations while improving CUDA occupancy. G-Charm also enables reuse of existing data in GPU global memory, performs GPU memory management and dynamic scheduling of tasks across CPU and GPU in order to reduce idle time. In order to combine the partial results obtained from the computations performed on CPU and GPU, G-Charm allows the user to specify an operator using which the partial results are combined at runtime. We also perform compile time code generation to reduce programming overhead. For Cholesky factorization, a regular parallel application, G-Charm provides 14% improvement over a highly tuned implementation. In the second part of our research, we extended our runtime to overcome the challenges presented by irregular applications such as a periodic generation of tasks, irregular memory access patterns and varying workloads during application execution. We developed models for deciding the number of tasks that can be combined into a kernel based on the rate of task generation, and the GPU occupancy of the tasks. For irregular applications, data reuse results in uncoalesced GPU memory access. We evaluated the effect of altering the global memory access pattern in improving coalesced access. We’ve also developed adaptive methods for hybrid execution on CPU and GPU wherein we consider the varying workloads while scheduling tasks across the CPU and GPU. We demonstrate that our dynamic strategies result in 8-38% reduction in execution times for an N-body simulation application and a molecular dynamics application over the corresponding static strategies that are amenable for regular applications.

A CNC machine can be programmed in different ways to machine a workpiece. In addition to creating the cutting program, many other factors also need to be considered or programmed. These include workholding devices, cutting tools, machining conditions as well as the machining strategy. The first generation CNCs were programmed manually and punched tapes were used as a medium for transferring the machine control data (MCD), that is, G-codes into a controller. Tapes were later replaced by RS232 cables, floppy disks, and finally standard computer network cables. Today’s CNC machines are controlled directly from files created by CAD/CAM or CAM software packages, so that a part or assembly can go directly from design to manufacturing without the need of producing a drafted paper drawing of the component. This means that for the first time, bringing design and manufacturing under the same automation regime becomes a reachable target. Error detection features give CNC machines the ability to alert the operator in different ways including giving a ring to the operation’s mobile phone if it detects that a tool has broken. While the machine is awaiting replacement on the tool, it would run other parts that are already loaded up to that tool and wait for the operator. The focus of this chapter is on a detailed account of the basics of CNC programming, and the emphasis is on G-code and Automatic Programming Tool (APT). G-code is still the dominant manual programming language for CNC machine tools. It is also the main form of control commands many CAD/CAM (or CAM) systems output. APT was developed soon after G-codes and CNC machine tools were developed to alleviate the drudgery work of straight G-code programming. Modern CAD/CAM systems these days are now becoming the main-stream tools for CNC programming.

Abstract In an effort to make microfluidic research more attractive and cost-effective, micromilled polymethyl methacrylate (PMMA) has gained interests as an alternative method to the conventional cleanroom-based micromolds fabrication technologies. The most enabling aspects of micromilling are flexibility on the design changes and the ability to fabricate three-dimensional structures. However, the major drawback of micromilling based micromold fabrication is the presence of burrs and tool marks on the surface after machining. High surface roughness on replicated polymer results in poor bonding strength and optical clarity. The roughness of micromilled surface strongly depends on the machining parameters such as tool size, spindle speed, feed rate, width of cut, and depth of cut. Thus, it is crucial to optimize the machining parameters to obtain a good surface finish. Although the optimal fabrication parameters are used to machine the micromold, the surface roughness of micromilled mold is still relative high compared to the surface of unprocessed PMMA. In this paper, we first optimize the micromilling parameters of Computer Numerical Control (CNC) milling machine to achieve the best possible of surface roughness. We have optimized the machining parameters for a flat endmill with 100 μm, 200 μm, and 400 μm in diameter of spindle speed, feed rate, width of cut, and the depth of cut respectively at 18000 rpm, 20 mm/min, 30 μm, and 20 μm. Then, a method to polish the structured surface of the micromilled mold was developed using the rotary magnetic field. By modifying the CNC program language G-code, we were able to control the polishing path, polishing force and time precisely. Consequently, the burrs and tool marks are completely removed, such that the roughness of the surface is decreased from 350 nm Ra to 30 nm Ra, and 1200 nm Rz to 300 nm Rz while the profile of microstructures is not deteriorated. Finally, we demonstrate our mold fabrication scheme by building a microfluidic immunoassay device with four Quake’s valves and showed the sequential assay process successfully.