Flip-J: Development of the System for Flipped Jigsaw Supported Language Learning

Science.gov (United States)

Yamada, Masanori; Goda, Yoshiko; Hata, Kojiro; Matsukawa, Hideya; Yasunami, Seisuke

2016-01-01

This study aims to develop and evaluate a language learning system supported by the "flipped jigsaw" technique, called "Flip-J". This system mainly consists of three functions: (1) the creation of a learning material database, (2) allocation of learning materials, and (3) formation of an expert and jigsaw group. Flip-J was…

Dramatherapy and Family Therapy in Education: Essential Pieces of the Multi-Agency Jigsaw

Science.gov (United States)

McFarlane, Penny; Harvey, Jenny

2012-01-01

A collaborative therapeutic approach often proves the best way to assess and meet the needs of children experiencing barriers to learning. This book gives a concise overview of drama and family therapy and describes how both therapies can work together to provide essential pieces of the jigsaw of emotional support for troubled children within an…

Promoting Interculturality in Spain: Assessing the Use of the Jigsaw Classroom Method

Science.gov (United States)

Santos Rego, Miguel A.; Moledo, M. Del Mar Lorenzo

2005-01-01

This note examines the effectiveness of a program in Spain that uses the Jigsaw learning technique as an educational intervention. We used a quasi-experimental research design with two groups, two measures and an independent variable (the program). Use of the Jigsaw technique is shown to have been fairly effective on a series of measures.

Robust Sex Differences in Jigsaw Puzzle Solving-Are Boys Really Better in Most Visuospatial Tasks?

Science.gov (United States)

Kocijan, Vid; Horvat, Marina; Majdic, Gregor

2017-01-01

Sex differences are consistently reported in different visuospatial tasks with men usually performing better in mental rotation tests while women are better on tests for memory of object locations. In the present study, we investigated sex differences in solving jigsaw puzzles in children. In total 22 boys and 24 girls were tested using custom build tablet application representing a jigsaw puzzle consisting of 25 pieces and featuring three different pictures. Girls outperformed boys in solving jigsaw puzzles regardless of the picture. Girls were faster than boys in solving the puzzle, made less incorrect moves with the pieces of the puzzle, and spent less time moving the pieces around the tablet. It appears that the strategy of solving the jigsaw puzzle was the main factor affecting differences in success, as girls tend to solve the puzzle more systematically while boys performed more trial and error attempts, thus having more incorrect moves with the puzzle pieces. Results of this study suggest a very robust sex difference in solving the jigsaw puzzle with girls outperforming boys by a large margin.

Robust Sex Differences in Jigsaw Puzzle Solving—Are Boys Really Better in Most Visuospatial Tasks?

Science.gov (United States)

Kocijan, Vid; Horvat, Marina; Majdic, Gregor

2017-01-01

Sex differences are consistently reported in different visuospatial tasks with men usually performing better in mental rotation tests while women are better on tests for memory of object locations. In the present study, we investigated sex differences in solving jigsaw puzzles in children. In total 22 boys and 24 girls were tested using custom build tablet application representing a jigsaw puzzle consisting of 25 pieces and featuring three different pictures. Girls outperformed boys in solving jigsaw puzzles regardless of the picture. Girls were faster than boys in solving the puzzle, made less incorrect moves with the pieces of the puzzle, and spent less time moving the pieces around the tablet. It appears that the strategy of solving the jigsaw puzzle was the main factor affecting differences in success, as girls tend to solve the puzzle more systematically while boys performed more trial and error attempts, thus having more incorrect moves with the puzzle pieces. Results of this study suggest a very robust sex difference in solving the jigsaw puzzle with girls outperforming boys by a large margin. PMID:29109682

Explorers, Detectives, Matchmakers, and Lion Tamers: Understanding Jigsaw Puzzlers' Techniques and Motivations

Science.gov (United States)

Garcia, Angela Cora

2013-01-01

Why do people enjoy jigsaw puzzles, which--challenging and time-consuming as they are--might be considered more like work than play? The author investigates the motivations, preferences, and satisfactions of individuals working on jigsaw puzzles, and she explores how these elements of play relate to the procedures and strategies puzzlers use to…

Solving jigsaw puzzles using image features

DEFF Research Database (Denmark)

Nielsen, Ture R.; Drewsen, Peter; Hansen, Klaus

2008-01-01

In this article, we describe a method for automatic solving of the jigsaw puzzle problem based on using image features instead of the shape of the pieces. The image features are used for obtaining an accurate measure for edge similarity to be used in a new edge matching algorithm. The algorithm i...

Effects of Computer-Assisted Jigsaw II Cooperative Learning Strategy on Physics Achievement and Retention

Science.gov (United States)

Gambari, Isiaka Amosa; Yusuf, Mudasiru Olalere

2016-01-01

This study investigated the effects of computer-assisted Jigsaw II cooperative strategy on physics achievement and retention. The study also determined how moderating variables of achievement levels as it affects students' performance in physics when Jigsaw II cooperative learning is used as an instructional strategy. Purposive sampling technique…

Teaching Chemical Equilibrium with the Jigsaw Technique

Science.gov (United States)

Doymus, Kemal

2008-01-01

This study investigates the effect of cooperative learning (jigsaw) versus individual learning methods on students' understanding of chemical equilibrium in a first-year general chemistry course. This study was carried out in two different classes in the department of primary science education during the 2005-2006 academic year. One of the classes…

Revealing the Relationship between Reading Interest and Critical Thinking Skills through Remap GI and Remap Jigsaw

Science.gov (United States)

Zubaidah, Siti; Corebima, Aloysius Duran; Mahanal, Susriyati; Mistianah

2018-01-01

The aim of this research was to reveal the relationship between student's reading interest and critical thinking skills through Reading Concept Map Group Investigation (Remap GI) and Reading Concept Map Jigsaw (Remap Jigsaw) learning models. To do so, two science classes from first grade of two Senior High Schools in Malang, Indonesia were…

Jigsaw puzzle metasurface for multiple functions: polarization conversion, anomalous reflection and diffusion.

Science.gov (United States)

Zhao, Yi; Cao, Xiangyu; Gao, Jun; Liu, Xiao; Li, Sijia

2016-05-16

We demonstrate a simple reconfigurable metasurface with multiple functions. Anisotropic tiles are investigated and manufactured as fundamental elements. Then, the tiles are combined in a certain sequence to construct a metasurface. Each of the tiles can be adjusted independently which is like a jigsaw puzzle and the whole metasurface can achieve diverse functions by different layouts. For demonstration purposes, we realize polarization conversion, anomalous reflection and diffusion by a jigsaw puzzle metasurface with 6 × 6 pieces of anisotropic tile. Simulated and measured results prove that our method offers a simple and effective strategy for metasurface design.

Cooperative learning in third graders' jigsaw groups for mathematics and science with and without questioning training.

Science.gov (United States)

Souvignier, Elmar; Kronenberger, Julia

2007-12-01

There is much support for using cooperative methods, since important instructional aspects, such as elaboration of new information, can easily be realized by methods like 'jigsaw'. However, the impact of providing students with additional help like a questioning training and potential limitations of the method concerning the (minimum) age of the students have rarely been investigated. The study investigated the effects of cooperative methods at elementary school level. Three conditions of instruction were compared: jigsaw, jigsaw with a supplementary questioning training and teacher-guided instruction. Nine third grade classes from three schools with 208 students participated in the study. In each school, all the three instructional conditions were realized in three different classes. All classes studied three units on geometry and one unit on astronomy using the assigned instructional method. Each learning unit comprised six lessons. For each unit, an achievement test was administered as pre-test, post-test and delayed test. In the math units, no differences between the three conditions could be detected. In the astronomy unit, students benefited more from teacher-guided instruction. Differential analyses revealed that 'experts' learned more than students in teacher-guided instruction, whereas 'novices' were outperformed by the students in the control classes. Even third graders used the jigsaw method with satisfactory learning results. The modest impact of the questioning training and the low learning gains of the cooperative classes in the astronomy unit as well as high discrepancies between learning outcomes of experts and novices show that explicit instruction of explaining skills in combination with well-structured material are key issues in using the jigsaw method with younger students.

PENERAPAN PEMBELAJARAN KOOPERATIF TIPE JIGSAW BERBASIS LESSON STUDY UNTUK MENINGKATAN AKTIVITAS KOLABORATIF MAHASISWA PGSD PADA MATA KULIAH PENDIDIKAN MATEMATIKA I

Directory of Open Access Journals (Sweden)

Ratih Purnamasari

2016-09-01

Full Text Available Abstrak. Penelitian ini bertujuan mengetahui peningkatan aktivitas kolaboratif mahasiswa pada mata kuliah pendidikan matematika I dengan menerapkan pembelajaran kooperatif tipe jigsaw berbasis lesson study. Penelitian dilakukan dengan tahapan-tahapan yang berlaku dalam pembelajaran berbasis lesson study yang terdiri dari plan, do dan see. Lokasi penelitian di FKIP UNPAK dengan waktu pelaksanaan antara bulan Mei-Juni 2013. Subyek penelitian mahasiswa S1 Prodi Pendidikan Guru Sekolah Dasar (PGSD semester VI yang mengambil mata kuliah pendidikan matematika I. Pengumpulan data dengan teknik dokumentasi, observasi, wawancara dan angket. Instrumen meliputi : lembar observasi, pedoman wawancara dan angket. Data hasil observasi dianalisis secara deskriptif kualitatif untuk mengetahui peningkatan aktivitas kolaboratif mahasiswa dalam kerja kelompok. Hasil penelitian menunjukkan penerapan pembelajaran kooperatif tipe jigsaw berbasis lesson study dapat meningkatkan aktivitas kolaboratif mahasiswa dalam kerja kelompok pada mata kuliah pendidikan matematika I, khususnya pada materi KPK, FPB dan pecahan. Hal ini dapat dilihat dari peningkatan ketercapaian indikator kegiatan lesson study di setiap siklusnya, serta hasil angket respon mahasiswa yang mayoritas menyatakan positif terhadap proses pembelajaran yang dilakukan. Selain itu, hasil wawancara terhadap mahasiswa juga menunjukkan bahwa pembelajaran kooperatif tipe jigsaw ternyata dapat meningkatkan motivasi mahasiswa untuk belajar secara berkolaborasi. Alangkah baiknya jika para dosen dalam membelajarkan mata kuliah pendidikan matematika 1 mencoba menggunakan pembelajaran kooperatif tipe jigsaw berbasis lesson study. Kata Kunci: Aktivitas Kolaboratif, Jigsaw, Lesson Study  Abstract. This study aimed to increase collaborative activities of students in the subject of Pendidikan Matematika I by implementing cooperative learning jigsaw-based lesson study. Research carried out by stages that apply in lesson

PENGARUH METODE KOOPERATIF JIGSAW TERHADAP PRESTASI BELAJAR MATA PELAJARAN IPS PADA SISWA KELAS III

Directory of Open Access Journals (Sweden)

Maya Kartika Sari

2016-11-01

Full Text Available This study aims to determine the effect of the use of cooperative learning of jigsaw method in social studies on student achievement of class III SD Pakualaman Bantul and SD Gandok Islamiyah in 2014/2015 school year. This research design uses quantitative research methods. Collecting data in this study uses the test method. The used test methods in this research are the pre-test and post-test given to the experimental group and the control group. While the data analysis is a statistical method t test (t-test.  The results of data analysis t test (t-test obtained value = 3.34. At the significance level (α = 0.05 and with db = 38 obtained value = 1.6859. So that is 3.34 ≥ 1.6859, therefore Ho is rejected H1 accepted. The conclusion of this study is that there is an effect on the use of cooperative learning of jigsaw model in social studies on student achievement of class III SD Islamiyah Pakualaman at school year 2014/2015.   Keywords: Cooperative Model Jigsaw Type, Learning Achievement

Synthesis and characterization of polypropylene/jigsaw wood ash composite

International Nuclear Information System (INIS)

Sudirman; Karo Karo, Aloma; Gunawan, Indra; Handayani, Ari; Hertinvyana, Evi

2002-01-01

The composite of polypropylene (PP) polymer with jigsaw wood ash as filler is the alternative composite material. The dispersion of the filler in the composite is random with the jigsaw wood ash composition of 10,30, and 50% by volume. The characterization of composite are done to measure its mechanical properties, physical properties and microstructure by using XRD and SEM. From this research, it is concluded that increasing filler content of the composite will decrease its mechanical and physical properties. The comparation of different composites are found that tensile strength of PP MF 10 is higher 4.24% compared with PP MF 2 as a matrix. It is also found that melting temperature of PP MF 10 is higher 4.09% compared with PP MF 2 as a matrices and the decomposition temperature different is 0.17%. The degree of crystallinity of composite with PP MF 10 as a matrices is 2.55% higher compared with PP MF 2. The higher degree of crystallinity is increasing the tensile strength

PENGEMBANGAN MODEL KOLABORASI JIGSAW ROLE PLAYING SEBAGAI UPAYA PENINGKATAN KEMAMPUAN BEKERJASAMA SISWA KELAS V SD PADA PELAJARAN IPS

Directory of Open Access Journals (Sweden)

Ika Ari Pratiwi

2015-11-01

Full Text Available Penelitian bertujuan untuk mengembangkan model kolaborasi jigsaw, role playing untuk meningkatkan kemampuan bekerjasama siswa yang valid, efektif dan praktis. Metode penelitian adalah penelitian dan pengembangan (R&D. Tahap uji coba pengembangan terdiri atas uji coba ahli, uji coba skala terbatas dan uji coba skala luas. Keefektifan model kolaborasi jigsaw role playing  diperoleh rata-rata 51,83 dalam kategori baik diterapkan dalam pelajaran IPS, peningkatan kemampuan bekerjasama siswa hasil N-gain = 0,56 dengan kategori sedang, peningkatan hasil belajar IPS N-gain = 0,50 dengan kategori sedang dan hasil ketuntasan klasikal pembelajaran IPS 97,14%.  Hasil respon guru dan siswa terhadap model yang digunakan adalah berkriteria baik. Model final penelitian ini menghasilkan model kolaborasi jigsaw role playing yang dikemas dalam suatu buku pedoman.

Pengaruh Metode Belajar Jigsaw Terhadap Keterampilan Hubungan Interpersonal dan Kerjasama Kelompok pada Mahasiswa Fakultas Psikologi

Directory of Open Access Journals (Sweden)

Asmadi Alsa

2015-11-01

Full Text Available This study aims to test the effect of cooperative learning methods, the jigsaw method to interpersonal relationship skill and teamwork of undergraduate students Faculty of Psychology in University A. This study used experimental method with one group and pre posttest design. There are 63 undergraduate students in Educational Psychology Class of 2008/2009 as the subjects. The measurement instrument was Interpersonal Relationship Skill Scale and Teamwork Scale. Interpersonal relationship and teamwork score compared before and after the learning methods were given and tested using paired samples t test. The result shows that comparing the pretest and posttest score of interpersonal relationship variable, we got t ‐1,748 with p = 0,043 (p < 0,05. This is indicated that jigsaw learning method has significant effect to improving the interpersonal relationship skill in undergraduate students. The analysis result in teamwork variable with comparing the pretest and posttest, we got t ‐3,50 with p = 0,001 (p < 0,01 which means the jigsaw learning method significantly effective to improving teamwork skill in undergraduate student

PENERAPAN COOPERATIVE LEARNING TIPE JIGSAW UNTUK MENINGKATKAN PEMAHAMAN DAN KETERAMPILAN MAHASISWA

Directory of Open Access Journals (Sweden)

Rediana Setiani

2009-06-01

Full Text Available The objectives of this study are: (1 to improve students’ understanding in Accounting Computer subject mahasiswa pada mata kuliah Komputer Akuntansi, (2 to improve students’ skills in Accounting Computer subject. The subject of this research is accounting students of education program that take accounting computer subject. This research is class action research consists of  3 cycles. The given action in the first cycle according to the result of beginning reflection. In every cycle consists of 4 stages that are planning, actuating, observation, and reflection. This research reached standardized indicator that 70% students have minimum score that was 71 (B. It showed that the application of cooperative learning jigsaw type can improve the students’ ability in a computer accounting subject.   Key Words : Cooperative Learning, Jigsaw, the students’ understanding, creativity

PENERAPAN COOPERATIVE LEARNING TIPE JIGSAW UNTUK MENINGKATKAN PEMAHAMAN DAN KETERAMPILAN MAHASISWA

Directory of Open Access Journals (Sweden)

Rediana Setiani

2011-05-01

Full Text Available The objectives of this study are: (1 to improve students’ understanding in Accounting Computer subject mahasiswa pada mata kuliah Komputer Akuntansi, (2 to improve students’ skills in Accounting Computer subject. The subject of this research is accounting students of education program that take accounting computer subject. This research is class action research consists of  3 cycles. The given action in the first cycle according to the result of beginning reflection. In every cycle consists of 4 stages that are planning, actuating, observation, and reflection. This research reached standardized indicator that 70% students have minimum score that was 71 (B. It showed that the application of cooperative learning jigsaw type can improve the students’ ability in a computer accounting subject.   Key Words : Cooperative Learning, Jigsaw, the students’ understanding, creativity

Considering the intrinsic constraints for groups management of TAPPS & Jigsaw CLFPs

NARCIS (Netherlands)

Pérez-Sanagustín, Mar; Burgos, Javier; Hernández-Leo, Davinia; Blat, Josep

2009-01-01

Pérez-Sanagustín, M., Burgos, J., Hernández-Leo, D., & Blat, J. (2009). Considering the intrinsic constraints for groups management of TAPPS & Jigsaw CLFPs. Proceedings of International Conference on Intelligent Networking and Collaborative Systems (INCoS 2009). November, 4-6, 2009, Barcelona,

Jigsaw model of the origin of life

Science.gov (United States)

McGowan, John F.

2002-02-01

It is suggested that life originated in a three-step process referred to as the jigsaw model. RNA, proteins, or similar organic molecules polymerized in a dehydrated carbon-rich environment, on surfaces in a carbon-rich environment, or in another environment where polymerization occurs. These polymers subsequently entered an aqueous environment where they folded into compact structures. It is argued that the folding of randomly generated polymers such as RNA or proteins in water tends to partition the folded polymer into domains with hydrophobic cores and matching shapes to minimize energy. In the aqueous environment hydrolysis or other reactions fragmented the compact structures into two or more matching molecules, occasionally producing simple living systems, also knows as autocatalytic sets of molecules. It is argued that the hydrolysis of folded polymers such as RNA or proteins is not random. The hydrophobic cores of the domains are rarely bisected due to the energy requirements in water. Hydrolysis preferentially fragments the folded polymers into pieces with complementary structures and chemical affinities. Thus the probability of producing a system of matched, interacting molecules in prebiotic chemistry is much higher than usually estimated. Environments where this process may occur are identified. For example, the jigsaw model suggests life may have originated at a seep or carbonaceous fluids beneath the ocean. The polymerization occurred beneath the sea floor. The folding and fragmentation occurred in the ocean. The implications of this hypothesis for seeking life or prebiotic chemistry in the Solar System are explored.

E-LEARNING DENGAN PENDEKATAN KOOPERATIF TIPE JIGSAW UNTUK MENINGKATKAN AKTIVITAS DAN HASIL BELAJAR MAHASISWA

Directory of Open Access Journals (Sweden)

Partono Thomas

2014-06-01

Full Text Available Students in the first semester got difficulty to adapt the learning process in the university (student-oriented which are different with the senior high school (teacher-oriented. Thus, the lecturer needed to solve the problem to sharpen students’ independence by using Jigsaw, a cooperative learning. Then, e-learning was also an important factor to spread the knowledge widely to students. Thus; the combination of Jigsaw and e-learning was expected to improve students’ achievement. The subjects of the study were 40 Economics education students in bachelor degree (S1, Unnes in Curriculum Review class. The objective of the study was to minimize the mistake, improve the students’ interest and study result in understanding the concept of the Standard of National Education through independent learning strategy based on e-learning and cooperative learning of Jigsaw. The result of study showed that students’ activities, interest, attention, participation in discussion and presentation in the classroom increased significantly with the mean 4.14. Then, students’ test results increased from pre-test which was only 74 then rose to 79 in the 1st cycle and 81 in the 2nd cycle with the level of completeness was 87.5%. Furthermore, students thought that the strategy was very good with the score 4.12

Cooperative Learning in Virtual Environments: The Jigsaw Method in Statistical Courses

Science.gov (United States)

Vargas-Vargas, Manuel; Mondejar-Jimenez, Jose; Santamaria, Maria-Letica Meseguer; Alfaro-Navarro, Jose-Luis; Fernandez-Aviles, Gema

2011-01-01

This document sets out a novel teaching methodology as used in subjects with statistical content, traditionally regarded by students as "difficult". In a virtual learning environment, instructional techniques little used in mathematical courses were employed, such as the Jigsaw cooperative learning method, which had to be adapted to the…

Efectos de la aplicación de "jigsaw" sobre la adquisición de competencias en dirección de operaciones || Effects of the "Jigsaw" Technique on Student' Learning Competences within Operations Management

Directory of Open Access Journals (Sweden)

López Vargas, Cristina

2017-12-01

Full Text Available El presente trabajo analiza los efectos de la aplicación de la técnica de "jigsaw", puzzle o rompecabezas de Aronson en la adquisición de competencias por parte de estudiantes universitarios. Más concretamente buscamos determinar qué competencias sistémicas, instrumentales e interpersonales se adquieren más fácilmente al implantar "jigsaw" en el proceso de enseñanza-aprendizaje. Los resultados alcanzados muestran que esta técnica de aprendizaje cooperativo facilita en mayor medida la adquisición de competencias sistémicas e instrumentales en comparación con las interpersonales. Dentro de las competencias sistémicas, la que desarrollan con más facilidad los alumnos es la denominada metareflexión; es decir, el aprendizaje progresivo por repetición. En el grupo de competencias instrumentales, destacan la interacción entre compañeros, las habilidades comunicativas del alumno, la participación, la ayuda en la resolución de conflictos entre compañeros surgidos durante la dinámica y la mejora de la instrucción directa. Finalmente, en relación a las competencias interpersonales, la más desarrollada es el sentido de la responsabilidad del alumno. || The aim of this study was to determine the effects of the cooperative ``jigsaw'' method on generic competence-based training by university students. This specifically sought to understand how systemic, instrumental and interpersonal competences are more easily acquired by adopting ``jigsaw'' in the teaching-learning procedure. The results reveal that this cooperative learning method makes the development of systemic and instrumental competences easier to a greater extent than interpersonal ones. Meta-reflection or progressive rote learning achieved a highest score among systemic competences. Focusing our attention on the instrumental dimension, peer interaction, students' communication skills, participation, resolution of peer conflicts and direct instruction, these competences sty

CO-OP JIGSAW TEAM PROJECTS: A COOPERATIVE TEACHING METHOD TO IMPROVE STUDENTS‘ SPEAKING SKILL (An Experimental Study in a Senior High School

Directory of Open Access Journals (Sweden)

Diaz Innova Citra Arum

2017-12-01

Full Text Available An effective speaking activity involves active students to participate and create a life communication. The ideal condition of English speaking class involves the students‘ effectiveness in participating teaching and learning process. Nevertheless, some problems are emerged and one of them is that they often get nervous to speak in front of many people when they are asked to present their work to their friends. This paper reveals an experiment study in teaching speaking in a senior high school in Lamongan, East Java. It discusses about the effectiveness of cooperative teaching method known as coop jigsaw team projects in teaching speaking. All tenth grade students were used as the population and eighty students were taken as sample being divided into experimental group taught using coop jigsaw team projects and control group taught using direct instruction. Cluster random sampling was applied as the technique to determine sample. To obtain the data of students‘ speaking score, a speaking test was conducted. The score was the average score resulted by two independent examiners. The data were analysed through descriptive and inferential analysis using two-sample t-test. The research hypothesised that coop jigsaw will result a better English speaking score rather than direct instruction method. The research finding using 95% significance level shows that coop jigsaw team projects was more effective in teaching speaking compared to direct instruction for the tenth grade students because the activities in coop jigsaw team project pushed the students to be more active and cooperative in learning speaking.

THE EFFECT OF JIGSAW II TOWARD LEARNING MOTIVATION AND READING COMPREHENSION AT THE SECOND GRADE OF ENGLISH STUDENTS IN STKIP DHARMA BAKTI

Directory of Open Access Journals (Sweden)

eka melati

2016-10-01

Full Text Available In teaching Reading, learning motivation and reading comprehension are essential. Ideally, after students learn the reading skills, both of their learning motivation and reading comprehension are better than before. In fact, the students still face some problems in comprehending the text. The problems are: they got low score of reading comprehension, they are lack of motivation, they are lack of vocabulary mastery, their reading achievement is still low, and the lecturer always uses small group discussion method without any variation. The purpose of this research was to find out the effect of JIgsaw II on learning motivation and reading comprehension.This study was an experimental research. Poupulation of this research was the second grade students of English Department of STKIP Dharma Bakti Lubuk Alung academic year 2010/2011 who was totally 133 students. The sample was selected by cluster random technique. The instruments were questionnaire of learning motivation and test of reading comprehension. The data were analyzed manually by t-test formula.The result of this study were learning motivation of students who were taught by Jigsaw II was better than those who were taught by small group discussion; and reading comprehension of students who taught by Jigsaw II was better than those who taught by small group discussion. It concluded that Jigsaw II produced better result on learning motivation and reading comprehension. It was implied that Jigsaw II could be used as method of teaching reading for English students.Doi: 10.22216/jit.2014.v8i2.211 

Meningkatkan Prestasi Pembelajaran Mata Kuliah Dasar-Dasar Pemasaran Global Melalui Metode Pembelajaran Koorperatif Tipe Jigsaw

Directory of Open Access Journals (Sweden)

Sri Wartini

2007-06-01

Full Text Available Conceptual learning will be more qualified if it is supported by an appropriate and good learning method system. To improve the achievement of students’ study result, it needs the  active students’ involvement  who want to think critically toward the real condition in the field. This class action research has an objective to prove that cooperative method, jigsaw type can be implemented in the learning process on each subject whose conceptual type. The subject of this research was Management Department students, Regular Class, 5th semester with the sum was 67 students who got Basics of Management Subject. This research consisted of 3 cycles and found out that the increase of average for pre test and post test score in cycle 1 was 15%, cycle 2 was 20% and cycle 3 was 25%. Whereas the difference of  average increase among cycles were on cycle 1 to cycle 2 was 5%, cycle 2 to cycle 3 was 10%. The finding means there is an increase of achievement on each cycle was 5%. It is appropriate to the hypothesis. Thus, it proved that cooperative learning method , jigsaw type can be applied well to Global Marketing Subject and finally it can improve the students’ learning achievement. Keywords: cooperative method, jigsaw type

Meningkatkan Prestasi Pembelajaran Mata Kuliah Dasar-Dasar Pemasaran Global Melalui Metode Pembelajaran Koorperatif Tipe Jigsaw

Directory of Open Access Journals (Sweden)

Sri Wartini

2011-06-01

Full Text Available Conceptual learning will be more qualified if it is supported by an appropriate and good learning method system. To improve the achievement of students’ study result, it needs the  active students’ involvement  who want to think critically toward the real condition in the field. This class action research has an objective to prove that cooperative method, jigsaw type can be implemented in the learning process on each subject whose conceptual type. The subject of this research was Management Department students, Regular Class, 5th semester with the sum was 67 students who got Basics of Management Subject. This research consisted of 3 cycles and found out that the increase of average for pre test and post test score in cycle 1 was 15%, cycle 2 was 20% and cycle 3 was 25%. Whereas the difference of  average increase among cycles were on cycle 1 to cycle 2 was 5%, cycle 2 to cycle 3 was 10%. The finding means there is an increase of achievement on each cycle was 5%. It is appropriate to the hypothesis. Thus, it proved that cooperative learning method , jigsaw type can be applied well to Global Marketing Subject and finally it can improve the students’ learning achievement. Keywords: cooperative method, jigsaw type

Meningkatkan Hasil Belajar Matematika Melalui Model Pembelajaran Kooperatif Tipe Jigsaw pada Siswa SMP

Directory of Open Access Journals (Sweden)

Nasruddin Nasruddin

2017-08-01

Full Text Available In this study, we discuss about Jigsaw type cooperative learning model to improve mathematics learning outcomes on the basic competence of cubes and beams of students of class VIIIA SMP. This research is a Classroom Action Research (CAR conducted in SMPN 2 Lasusua Year Learning 2016/2017 even semester. This study uses two cycles, each cycle has procedures such as planning, action, observation and reflection. The results of this study indicate the implementation of cooperative learning model jigsaw type can improve student learning outcomes in mathematics subjects. The value after the first cycle action increased compared with the initial test of 45,85 to 65,75. Furthermore the average score of students after the second cycle action increased compared with the average score of students on the implementation of the first cycle action that is 65,75 to 80,60 and has met the predetermined performance indicators that 85% of students have received a minimum score of 65.

Use of Jigsaw Technique to Teach the Unit "Science within Time" in Secondary 7th Grade Social Sciences Course and Students' Views on This Technique

Science.gov (United States)

Yapici, Hakki

2016-01-01

The aim of this study is to apply the jigsaw technique in Social Sciences teaching and to unroll the effects of this technique on learning. The unit "Science within Time" in the secondary 7th grade Social Sciences text book was chosen for the research. It is aimed to compare the jigsaw technique with the traditional teaching method in…

A Hybrid Approach to Teaching Managerial Economics

Science.gov (United States)

Metzgar, Matthew

2014-01-01

Many institutions in higher education are experimenting with hybrid teaching approaches to undergraduate courses. Online resources may provide a number of advantages to students as compared to in-class approaches. Research regarding the effectiveness of hybrid approaches is mixed and still accumulating. This paper discusses the use of a hybrid…

Hybrid perovskites: Approaches towards light-emitting devices

KAUST Repository

Alias, Mohd Sharizal

2016-10-06

The high optical gain and absorption of organic-inorganic hybrid perovskites have attracted extensive research for photonic device applications. Using the bromide halide as an example, we present key approaches of our work towards realizing efficient perovskites based light-emitters. The approaches involved determination of optical constants for the hybrid perovskites thin films, fabrication of photonic nanostructures in the form of subwavelength grating reflector patterned directly on the hybrid perovskites as light manipulation layer, and enhancing the emission property of the hybrid perovskites by using microcavity structure. Our results provide a platform for realization of hybrid perovskites based light-emitting devices for solid-state lighting and display applications. © 2016 IEEE.

Hybrid perovskites: Approaches towards light-emitting devices

KAUST Repository

Alias, Mohd Sharizal; Dursun, Ibrahim; Priante, Davide; Saidaminov, Makhsud I.; Ng, Tien Khee; Bakr, Osman; Ooi, Boon S.

2016-01-01

The high optical gain and absorption of organic-inorganic hybrid perovskites have attracted extensive research for photonic device applications. Using the bromide halide as an example, we present key approaches of our work towards realizing efficient perovskites based light-emitters. The approaches involved determination of optical constants for the hybrid perovskites thin films, fabrication of photonic nanostructures in the form of subwavelength grating reflector patterned directly on the hybrid perovskites as light manipulation layer, and enhancing the emission property of the hybrid perovskites by using microcavity structure. Our results provide a platform for realization of hybrid perovskites based light-emitting devices for solid-state lighting and display applications. © 2016 IEEE.

PEMBELAJARAN METODE KOOPERATIF TIPE JIGSAW DALAM MENINGKATKAN HASIL BELAJAR BAHASA ARAB (QOWA’ID MAHASISWA PERBANKAN SYARI’AH IAIM NU METRO LAMPUNG TAHUN 2017

Directory of Open Access Journals (Sweden)

Muhammad Syaifullah

2017-11-01

Full Text Available Learning Arabic qowa'id student Syari'ah Banking Second semester Ma'arif Institute of Islamic NU Metro Lampung still not maximized. Students have difficulties to understand Arabic qowa'id material. Student learning motivation is also low. This is what makes researchers want to do research in that class. Problems to be expressed in this research are: (1 How is the application of Arabic qowa'id learning with cooperative model of jigsaw method in class A, second semester of Syari'ah Banking, (2 How to improve learning qowa'id after getting learning with cooperative learning model of jigsaw method, (3 What are the advantages and disadvantages of implementing cooperative Arabic qawaid in class A with jigsaw method. This research is a classroom action research conducted in two cycles. Each cycle is done in a cycle consisting of four stages: planning, execution, observation and reflection. The results of this study indicate an increase from cycle I of cycle II. The average class cycle I is 60.83 and the average of cycle II is 71. The students also show behavior change in the positive direction. Student activity is increasing. The improvement of test result is also followed by behavioral and motivational change based on research which has been done by the researcher that through cooperative learning with jigsaw method, Arabic qowa'id learning becomes more fun and easier for students in learning qowa'id. Suggestions that can be given is a lecturer of Arabic language should be more creative in using techniques and learning methods that involve the active role of student learning so that the learning process to get the maximum value. One alternative of learning Arabic qowa'id is by using cooperative learning jigsaw model.

A Hybrid Approach to Protect Palmprint Templates

Directory of Open Access Journals (Sweden)

Hailun Liu

2014-01-01

Full Text Available Biometric template protection is indispensable to protect personal privacy in large-scale deployment of biometric systems. Accuracy, changeability, and security are three critical requirements for template protection algorithms. However, existing template protection algorithms cannot satisfy all these requirements well. In this paper, we propose a hybrid approach that combines random projection and fuzzy vault to improve the performances at these three points. Heterogeneous space is designed for combining random projection and fuzzy vault properly in the hybrid scheme. New chaff point generation method is also proposed to enhance the security of the heterogeneous vault. Theoretical analyses of proposed hybrid approach in terms of accuracy, changeability, and security are given in this paper. Palmprint database based experimental results well support the theoretical analyses and demonstrate the effectiveness of proposed hybrid approach.

The Effects of Jigsaw Learning on Students' Attitudes in a Vietnamese Higher Education Classroom

Science.gov (United States)

Tran, Van Dat; Lewis, Ramon

2012-01-01

As a part of an experimental study on the effects of jigsaw learning on Vietnamese tertiary students' achievement and knowledge retention, students' attitudes towards six weeks of this kind of instruction were assessed. As noted in our previous report, students in the experimental group (N = 40), who perceived their instruction as more cooperative…

Impact of Expert Teaching Quality on Novice Academic Performance in the Jigsaw Cooperative Learning Method

Science.gov (United States)

Berger, Roland; Hänze, Martin

2015-01-01

We assessed the impact of expert students' instructional quality on the academic performance of novice students in 12th-grade physics classes organized in an expert model of cooperative learning ("jigsaw classroom"). The instructional quality of 129 expert students was measured by a newly developed rating system. As expected, when…

Effects of Jigsaw and Animation Techniques on Students' Understanding of Concepts and Subjects in Electrochemistry

Science.gov (United States)

Doymus, Kemal; Karacop, Ataman; Simsek, Umit

2010-01-01

This study investigated the effect of jigsaw cooperative learning and animation versus traditional teaching methods on students' understanding of electrochemistry in a first-year general chemistry course. This study was carried out in three different classes in the department of primary science education during the 2007-2008 academic year. The…

Instructional Media Production for Early Childhood Education: A. B. C. Jig-Saw Puzzle, a Model

Science.gov (United States)

Yusuf, Mudashiru Olalere; Olanrewaju, Olatayo Solomon; Soetan, Aderonke K.

2015-01-01

In this paper, a. b. c. jig-saw puzzle was produced for early childhood education using local materials. This study was a production based type of research, to serve as a supplemental or total learning resource. Its production followed four phases of development referred to as information, design, production and evaluation. The storyboard cards,…

Effect of Jigsaw II, Reading-Writing-Presentation, and Computer Animations on the Teaching of "Light" Unit

Science.gov (United States)

Koç, Yasemin; Yildiz, Emre; Çaliklar, Seyma; Simsek, Ümit

2016-01-01

The aim of this study is to determine the effect of Jigsaw II technique, reading-writing-presentation method, and computer animation on students' academic achievements, epistemological beliefs, attitudes towards science lesson, and the retention of knowledge in the "Light" unit covered in the 7th grade. The sample of the study consists…

PENINGKATAN PRESTASI BELAJAR SISWA DALAM PEMBELAJARAN KIMIA DENGAN PENERAPAN COOPERATIVE LEARNING MODEL JIGSAW PADA KELAS X IPA3 DI SMA NEGERI 1 PADANG

Directory of Open Access Journals (Sweden)

Prima Aswirna

2012-07-01

Full Text Available The problem of this Classroom Action Research is how Cooperative Learning Model Jigsaw should be implemented in the learning of Chemistry at Grade X, Scince 3 of Senior High School 1 Padang.  This study was done through the following stages such as Planning, Action, Observation, and Evaluation or Reflection.  The results show among other that some important aspects were improved.  The average score of each cycles show improvement in students’ mastery and total average of the three actions become 98 percent.  It can be concluded that Cooperative Learning through Jigsaw technique improved students’ achievement of the subject being investigated.

Hybrid soft computing approaches research and applications

CERN Document Server

Dutta, Paramartha; Chakraborty, Susanta

2016-01-01

The book provides a platform for dealing with the flaws and failings of the soft computing paradigm through different manifestations. The different chapters highlight the necessity of the hybrid soft computing methodology in general with emphasis on several application perspectives in particular. Typical examples include (a) Study of Economic Load Dispatch by Various Hybrid Optimization Techniques, (b) An Application of Color Magnetic Resonance Brain Image Segmentation by ParaOptiMUSIG activation Function, (c) Hybrid Rough-PSO Approach in Remote Sensing Imagery Analysis,  (d) A Study and Analysis of Hybrid Intelligent Techniques for Breast Cancer Detection using Breast Thermograms, and (e) Hybridization of 2D-3D Images for Human Face Recognition. The elaborate findings of the chapters enhance the exhibition of the hybrid soft computing paradigm in the field of intelligent computing.

The Effects of Using Jigsaw Method Based on Cooperative Learning Model in the Undergraduate Science Laboratory Practices

Science.gov (United States)

Karacop, Ataman

2017-01-01

The main aim of the present study is to determine the influence of a Jigsaw method based on cooperative learning and a confirmatory laboratory method on prospective science teachers' achievements of physics in science teaching laboratory practice courses. The sample of this study consisted of 33 female and 15 male third-grade prospective science…

Bio-inspired ``jigsaw''-like interlocking sutures: Modeling, optimization, 3D printing and testing

Science.gov (United States)

Malik, I. A.; Mirkhalaf, M.; Barthelat, F.

2017-05-01

Structural biological materials such as bone, teeth or mollusk shells draw their remarkable performance from a sophisticated interplay of architectures and weak interfaces. Pushed to the extreme, this concept leads to sutured materials, which contain thin lines with complex geometries. Sutured materials are prominent in nature, and have recently served as bioinspiration for toughened ceramics and glasses. Sutures can generate large deformations, toughness and damping in otherwise all brittle systems and materials. In this study we examine the design and optimization of sutures with a jigsaw puzzle-like geometry, focusing on the non-linear traction behavior generated by the frictional pullout of the jigsaw tabs. We present analytical models which accurately predict the entire pullout response. Pullout strength and energy absorption increase with higher interlocking angles and for higher coefficients of friction, but the associated high stresses in the solid may fracture the tabs. Systematic optimization reveals a counter-intuitive result: the best pullout performance is achieved with interfaces with low coefficient of friction and high interlocking angle. We finally use 3D printing and mechanical testing to verify the accuracy of the models and of the optimization. The models and guidelines we present here can be extended to other types of geometries and sutured materials subjected to other loading/boundary conditions. The nonlinear responses of sutures are particularly attractive to augment the properties and functionalities of inherently brittle materials such as ceramics and glasses.

Genetic algorithm and neural network hybrid approach for job-shop scheduling

OpenAIRE

Zhao, Kai; Yang, Shengxiang; Wang, Dingwei

1998-01-01

Copyright @ 1998 ACTA Press This paper proposes a genetic algorithm (GA) and constraint satisfaction adaptive neural network (CSANN) hybrid approach for job-shop scheduling problems. In the hybrid approach, GA is used to iterate for searching optimal solutions, CSANN is used to obtain feasible solutions during the iteration of genetic algorithm. Simulations have shown the valid performance of the proposed hybrid approach for job-shop scheduling with respect to the quality of solutions and ...

Potential-vorticity inversion and the wave-turbulence jigsaw: some recent clarifications

Directory of Open Access Journals (Sweden)

M. E. McIntyre

2008-06-01

Full Text Available Two key ideas stand out as crucial to understanding atmosphere-ocean dynamics, and the dynamics of other planets including the gas giants. The first key idea is the invertibility principle for potential vorticity (PV. Without it, one can hardly give a coherent account of even so important and elementary a process as Rossby-wave propagation, going beyond the simplest textbook cases. Still less can one fully understand nonlinear processes like the self-sharpening or narrowing of jets – the once-mysterious "negative viscosity" phenomenon. The second key idea, also crucial to understanding jets, might be summarized in the phrase "there is no such thing as turbulence without waves", meaning Rossby waves especially. Without this idea one cannot begin to make sense of, for instance, momentum budgets and eddy momentum transports in complex large-scale flows. Like the invertibility principle the idea has long been recognized, or at least adumbrated. However, it is worth articulating explicitly if only because it can be forgotten when, in the usual way, we speak of "turbulence" and "turbulence theory" as if they were autonomous concepts. In many cases of interest, such as the well-studied terrestrial stratosphere, reality is more accurately described as a highly inhomogeneous "wave-turbulence jigsaw puzzle" in which wavelike and turbulent regions fit together and crucially affect each other's evolution. This modifies, for instance, formulae for the Rhines scale interpreted as indicating the comparable importance of wavelike and turbulent dynamics. Also, weakly inhomogeneous turbulence theory is altogether inapplicable. For instance there is no scale separation. Eddy scales are not much smaller than the sizes of the individual turbulent regions in the jigsaw. Here I review some recent progress in clarifying these ideas and their implications.

A Hybrid Approach to the Optimization of Multiechelon Systems

Directory of Open Access Journals (Sweden)

Paweł Sitek

2015-01-01

Full Text Available In freight transportation there are two main distribution strategies: direct shipping and multiechelon distribution. In the direct shipping, vehicles, starting from a depot, bring their freight directly to the destination, while in the multiechelon systems, freight is delivered from the depot to the customers through an intermediate points. Multiechelon systems are particularly useful for logistic issues in a competitive environment. The paper presents a concept and application of a hybrid approach to modeling and optimization of the Multi-Echelon Capacitated Vehicle Routing Problem. Two ways of mathematical programming (MP and constraint logic programming (CLP are integrated in one environment. The strengths of MP and CLP in which constraints are treated in a different way and different methods are implemented and combined to use the strengths of both. The proposed approach is particularly important for the discrete decision models with an objective function and many discrete decision variables added up in multiple constraints. An implementation of hybrid approach in the ECLiPSe system using Eplex library is presented. The Two-Echelon Capacitated Vehicle Routing Problem (2E-CVRP and its variants are shown as an illustrative example of the hybrid approach. The presented hybrid approach will be compared with classical mathematical programming on the same benchmark data sets.

Eksperimentasi Model Pembelajaran Kooperatif Tipe Jigsaw dan Team Assisted Individualized (Tai) pada Materi Sistem Persamaan Linear Dua Variabel (Spldv) Ditinjau dari Adversity Quotient (Aq) Siswa Kelas VIII SMP Negeri Se-kabupaten Karanganyar

OpenAIRE

Pambudi, Pangesti Arum; Mardiyana, Mardiyana; Sari Saputro, Dewi Retno

2016-01-01

The aim of this research was to determine the effect of learning models on mathematics achievement viewed from students' AQ. The learning models compared were Jigsaw cooperative learning, TAI cooperative learning, and direct learning. The type of this research was quasi-experimental research. Population was all of state Junior High School students in Karanganyar Regency on academic year 2015/2016. Samples for group experiment 1 (Jigsaw cooperative learning model) were 98 students, group exper...

Body Fat Percentage Prediction Using Intelligent Hybrid Approaches

Directory of Open Access Journals (Sweden)

Yuehjen E. Shao

2014-01-01

Full Text Available Excess of body fat often leads to obesity. Obesity is typically associated with serious medical diseases, such as cancer, heart disease, and diabetes. Accordingly, knowing the body fat is an extremely important issue since it affects everyone’s health. Although there are several ways to measure the body fat percentage (BFP, the accurate methods are often associated with hassle and/or high costs. Traditional single-stage approaches may use certain body measurements or explanatory variables to predict the BFP. Diverging from existing approaches, this study proposes new intelligent hybrid approaches to obtain fewer explanatory variables, and the proposed forecasting models are able to effectively predict the BFP. The proposed hybrid models consist of multiple regression (MR, artificial neural network (ANN, multivariate adaptive regression splines (MARS, and support vector regression (SVR techniques. The first stage of the modeling includes the use of MR and MARS to obtain fewer but more important sets of explanatory variables. In the second stage, the remaining important variables are served as inputs for the other forecasting methods. A real dataset was used to demonstrate the development of the proposed hybrid models. The prediction results revealed that the proposed hybrid schemes outperformed the typical, single-stage forecasting models.

A Hybrid Approach for Supporting Adaptivity in E-Learning Environments

Science.gov (United States)

Al-Omari, Mohammad; Carter, Jenny; Chiclana, Francisco

2016-01-01

Purpose: The purpose of this paper is to identify a framework to support adaptivity in e-learning environments. The framework reflects a novel hybrid approach incorporating the concept of the event-condition-action (ECA) model and intelligent agents. Moreover, a system prototype is developed reflecting the hybrid approach to supporting adaptivity…

Using hybrid expert system approaches for engineering applications

Science.gov (United States)

Allen, R. H.; Boarnet, M. G.; Culbert, C. J.; Savely, R. T.

1987-01-01

In this paper, the use of hybrid expert system shells and hybrid (i.e., algorithmic and heuristic) approaches for solving engineering problems is reported. Aspects of various engineering problem domains are reviewed for a number of examples with specific applications made to recently developed prototype expert systems. Based on this prototyping experience, critical evaluations of and comparisons between commercially available tools, and some research tools, in the United States and Australia, and their underlying problem-solving paradigms are made. Characteristics of the implementation tool and the engineering domain are compared and practical software engineering issues are discussed with respect to hybrid tools and approaches. Finally, guidelines are offered with the hope that expert system development will be less time consuming, more effective, and more cost-effective than it has been in the past.

Effects of Jigsaw Cooperative Learning and Animation Techniques on Students' Understanding of Chemical Bonding and Their Conceptions of the Particulate Nature of Matter

Science.gov (United States)

Karacop, Ataman; Doymus, Kemal

2013-04-01

The aim of this study was to determine the effect of jigsaw cooperative learning and computer animation techniques on academic achievements of first year university students attending classes in which the unit of chemical bonding is taught within the general chemistry course and these students' learning of the particulate nature of matter of this unit. The sample of this study consisted of 115 first-year science education students who attended the classes in which the unit of chemical bonding was taught in a university faculty of education during the 2009-2010 academic year. The data collection instruments used were the Test of Scientific Reasoning, the Purdue Spatial Visualization Test: Rotations, the Chemical Bonding Academic Achievement Test, and the Particulate Nature of Matter Test in Chemical Bonding (CbPNMT). The study was carried out in three different groups. One of the groups was randomly assigned to the jigsaw group, the second was assigned to the animation group (AG), and the third was assigned to the control group, in which the traditional teaching method was applied. The data obtained with the instruments were evaluated using descriptive statistics, one-way ANOVA, and MANCOVA. The results indicate that the teaching of chemical bonding via the animation and jigsaw techniques was more effective than the traditional teaching method in increasing academic achievement. In addition, according to findings from the CbPNMT, the students from the AG were more successful in terms of correct understanding of the particulate nature of matter.

Teaching research methods in nursing using Aronson's Jigsaw Technique. A cross-sectional survey of student satisfaction.

Science.gov (United States)

Leyva-Moral, Juan M; Riu Camps, Marta

2016-05-01

To adapt nursing studies to the European Higher Education Area, new teaching methods have been included that assign maximum importance to student-centered learning and collaborative work. The Jigsaw Technique is based on collaborative learning and everyone in the group must play their part because each student's mark depends on the other students. Home group members are given the responsibility to become experts in a specific area of knowledge. Experts meet together to reach an agreement and improve skills. Finally, experts return to their home groups to share all their findings. The aim of this study was to evaluate nursing student satisfaction with the Jigsaw Technique used in the context of a compulsory course in research methods for nursing. A cross-sectional study was conducted using a self-administered anonymous questionnaire administered to students who completed the Research Methods course during the 2012-13 and 2013-14 academic years. The questionnaire was developed taking into account the learning objectives, competencies and skills that should be acquired by students, as described in the course syllabus. The responses were compared by age group (younger or older than 22years). A total of 89.6% of nursing students under 22years believed that this methodology helped them to develop teamwork, while this figure was 79.6% in older students. Nursing students also believed it helped them to work independently, with differences according to age, 79.7% and 58% respectively (p=0.010). Students disagreed with the statement "The Jigsaw Technique involves little workload", with percentages of 88.5% in the group under 22years and 80% in older students. Most believed that this method should not be employed in upcoming courses, although there were differences by age, with 44.3% of the younger group being against and 62% of the older group (p=0.037). The method was not highly valued by students, mainly by those older than 22years, who concluded that they did not learn

An energy management approach of hybrid vehicles using traffic preview information for energy saving

International Nuclear Information System (INIS)

Zheng, Chunhua; Xu, Guoqing; Xu, Kun; Pan, Zhongming; Liang, Quan

2015-01-01

Highlights: • Energy management approach of hybrid vehicles using traffic preview information. • Vehicle velocity profile and fuel consumption are optimized at the same time. • It is proved that a further energy saving is achieved by the proposed approach. • The proposed approach is useful especially for autonomous hybrid vehicles. - Abstract: The traffic preview information is very helpful for hybrid vehicles when distributing the power requirement of the vehicle to power sources and when determining the next driving route of the vehicle. In this research, an energy management approach for hybrid vehicles is proposed, which optimizes the vehicle velocity profile while minimizing the fuel consumption with the help of the traffic preview information, so that a further energy saving for hybrid vehicles can be achieved. The Pontryagin’s Minimum Principle (PMP) is adopted on the proposed approach. A fuel cell hybrid vehicle (FCHV) is selected as an example, and the proposed energy management approach is applied to the FCHV in a computer simulation environment for the offline and online cases respectively. Simulation results show that the fuel economy of the FCHV is improved by the proposed energy management approach compared to a benchmark case where the driving cycle is fixed and only the hybrid power split (allocation) ratio is optimized. The proposed energy management approach is useful especially for the autonomous hybrid vehicles.

Having Fun and Accepting Challenges Are Natural Instincts: Jigsaw Puzzles to Challenge Students and Test Their Abilities While Having Fun!

Science.gov (United States)

Rodenbaugh, Hanna R.; Lujan, Heidi L.; Rodenbaugh, David W.; DiCarlo, Stephen E.

2014-01-01

Because jigsaw puzzles are fun, and challenging, students will endure and discover that persistence and grit are rewarded. Importantly, play and fun have a biological place just like sleep and dreams. Students also feel a sense of accomplishment when they have completed a puzzle. Importantly, the reward of mastering a challenge builds confidence…

A hybrid approach for biobjective optimization

DEFF Research Database (Denmark)

Stidsen, Thomas Jacob Riis; Andersen, Kim Allan

2018-01-01

to singleobjective problems is that no standard multiobjective solvers exist and specialized algorithms need to be programmed from scratch.In this article we will present a hybrid approach, which operates both in decision space and in objective space. The approach enables massive efficient parallelization and can...... be used to a wide variety of biobjective Mixed Integer Programming models. We test the approach on the biobjective extension of the classic traveling salesman problem, on the standard datasets, and determine the full set of nondominated points. This has only been done once before (Florios and Mavrotas...

Evaporator modeling - A hybrid approach

International Nuclear Information System (INIS)

Ding Xudong; Cai Wenjian; Jia Lei; Wen Changyun

2009-01-01

In this paper, a hybrid modeling approach is proposed to model two-phase flow evaporators. The main procedures for hybrid modeling includes: (1) Based on the energy and material balance, and thermodynamic principles to formulate the process fundamental governing equations; (2) Select input/output (I/O) variables responsible to the system performance which can be measured and controlled; (3) Represent those variables existing in the original equations but are not measurable as simple functions of selected I/Os or constants; (4) Obtaining a single equation which can correlate system inputs and outputs; and (5) Identify unknown parameters by linear or nonlinear least-squares methods. The method takes advantages of both physical and empirical modeling approaches and can accurately predict performance in wide operating range and in real-time, which can significantly reduce the computational burden and increase the prediction accuracy. The model is verified with the experimental data taken from a testing system. The testing results show that the proposed model can predict accurately the performance of the real-time operating evaporator with the maximum error of ±8%. The developed models will have wide applications in operational optimization, performance assessment, fault detection and diagnosis

DNA is structured as a linear "jigsaw puzzle" in the genomes of Arabidopsis, rice, and budding yeast.

Science.gov (United States)

Liu, Yun-Hua; Zhang, Meiping; Wu, Chengcang; Huang, James J; Zhang, Hong-Bin

2014-01-01

Knowledge of how a genome is structured and organized from its constituent elements is crucial to understanding its biology and evolution. Here, we report the genome structuring and organization pattern as revealed by systems analysis of the sequences of three model species, Arabidopsis, rice and yeast, at the whole-genome and chromosome levels. We found that all fundamental function elements (FFE) constituting the genomes, including genes (GEN), DNA transposable elements (DTE), retrotransposable elements (RTE), simple sequence repeats (SSR), and (or) low complexity repeats (LCR), are structured in a nonrandom and correlative manner, thus leading to a hypothesis that the DNA of the species is structured as a linear "jigsaw puzzle". Furthermore, we showed that different FFE differ in their importance in the formation and evolution of the DNA jigsaw puzzle structure between species. DTE and RTE play more important roles than GEN, LCR, and SSR in Arabidopsis, whereas GEN and RTE play more important roles than LCR, SSR, and DTE in rice. The genes having multiple recognized functions play more important roles than those having single functions. These results provide useful knowledge necessary for better understanding genome biology and evolution of the species and for effective molecular breeding of rice.

Using the jigsaw cooperative learning method to teach medical students about long-term and postacute care.

Science.gov (United States)

Buhr, Gwendolen T; Heflin, Mitchell T; White, Heidi K; Pinheiro, Sandro O

2014-06-01

Since many of the frailest and most vulnerable Americans reside in nursing homes, medical students need focused education and training pertaining to this setting. A unique cooperative learning experience utilizing the jigsaw method was developed to engage and expose students to the institutional long-term and postacute care (LTPAC) setting and the roles of personnel there. To accomplish these goals, small groups of medical students interviewed LTPAC personnel about their role, generally, and in relation to a specific patient case. These groups were then rearranged into new groups containing 1 student from each of the original groups plus a faculty facilitator. Each student in the new groups taught about the role of the LTPAC professional they interviewed. To assess the effectiveness of this learning experience, students and LTPAC personnel provided written feedback and rated the activity using a 5-point Likert scale (1 = worst; 5 = best). Students also took a knowledge test. The activity received ratings from students of 3.65 to 4.12 (mean = 3.91). The knowledge test results indicated that students understood the roles of the LTPAC personnel. In general, the jigsaw exercise was well-received by participants and provided an effective means of introducing medical students to the nursing home environment. Copyright © 2014 American Medical Directors Association, Inc. Published by Elsevier Inc. All rights reserved.

JIGSAW: Acquisition, Display and Analysis system designed to collect data from Multiple Gamma-Ray detectors

International Nuclear Information System (INIS)

Haywood, S.E.; Bamford, G.J.; Rester, A.C.; Coldwell, R.L.

1992-01-01

In this paper, the authors report on work performed to date on JIGSAW - a self contained data acquisition, display and analysis system designed to collect data form multiple gamma-ray detectors. The data acquisition system utilizes commercially available VMEbus and NIM hardware modules and the VME exec real time operating system. A Unix based software package, written in ANSI standard C and with the XII graphics routines, allows the user to view the acquired spectra. Analysis of the histograms can be performed in background during the run with the ROBFIT suite of curve fitting routines

A Hybrid Prognostic Approach for Remaining Useful Life Prediction of Lithium-Ion Batteries

Directory of Open Access Journals (Sweden)

Wen-An Yang

2016-01-01

Full Text Available Lithium-ion battery is a core component of many systems such as satellite, spacecraft, and electric vehicles and its failure can lead to reduced capability, downtime, and even catastrophic breakdowns. Remaining useful life (RUL prediction of lithium-ion batteries before the future failure event is extremely crucial for proactive maintenance/safety actions. This study proposes a hybrid prognostic approach that can predict the RUL of degraded lithium-ion batteries using physical laws and data-driven modeling simultaneously. In this hybrid prognostic approach, the relevant vectors obtained with the selective kernel ensemble-based relevance vector machine (RVM learning algorithm are fitted to the physical degradation model, which is then extrapolated to failure threshold for estimating the RUL of the lithium-ion battery of interest. The experimental results indicated that the proposed hybrid prognostic approach can accurately predict the RUL of degraded lithium-ion batteries. Empirical comparisons show that the proposed hybrid prognostic approach using the selective kernel ensemble-based RVM learning algorithm performs better than the hybrid prognostic approaches using the popular learning algorithms of feedforward artificial neural networks (ANNs like the conventional backpropagation (BP algorithm and support vector machines (SVMs. In addition, an investigation is also conducted to identify the effects of RVM learning algorithm on the proposed hybrid prognostic approach.

Forecasting conditional climate-change using a hybrid approach

Science.gov (United States)

Esfahani, Akbar Akbari; Friedel, Michael J.

2014-01-01

A novel approach is proposed to forecast the likelihood of climate-change across spatial landscape gradients. This hybrid approach involves reconstructing past precipitation and temperature using the self-organizing map technique; determining quantile trends in the climate-change variables by quantile regression modeling; and computing conditional forecasts of climate-change variables based on self-similarity in quantile trends using the fractionally differenced auto-regressive integrated moving average technique. The proposed modeling approach is applied to states (Arizona, California, Colorado, Nevada, New Mexico, and Utah) in the southwestern U.S., where conditional forecasts of climate-change variables are evaluated against recent (2012) observations, evaluated at a future time period (2030), and evaluated as future trends (2009–2059). These results have broad economic, political, and social implications because they quantify uncertainty in climate-change forecasts affecting various sectors of society. Another benefit of the proposed hybrid approach is that it can be extended to any spatiotemporal scale providing self-similarity exists.

Hybrid methodological approach to context-dependent speech recognition

Directory of Open Access Journals (Sweden)

Dragiša Mišković

2017-01-01

Full Text Available Although the importance of contextual information in speech recognition has been acknowledged for a long time now, it has remained clearly underutilized even in state-of-the-art speech recognition systems. This article introduces a novel, methodologically hybrid approach to the research question of context-dependent speech recognition in human–machine interaction. To the extent that it is hybrid, the approach integrates aspects of both statistical and representational paradigms. We extend the standard statistical pattern-matching approach with a cognitively inspired and analytically tractable model with explanatory power. This methodological extension allows for accounting for contextual information which is otherwise unavailable in speech recognition systems, and using it to improve post-processing of recognition hypotheses. The article introduces an algorithm for evaluation of recognition hypotheses, illustrates it for concrete interaction domains, and discusses its implementation within two prototype conversational agents.

PENGARUH MODEL PEMBELAJARAN KOOPERATIF TIPE JIGSAW II TERHADAP PENGUASAAN KONSEP DAN KECEMASAN PESERTA DIDIK SMA KELAS XI PADA MATERI SISTEM KOLOID

Directory of Open Access Journals (Sweden)

Zikra Azizah

2017-08-01

Full Text Available Penelitian ini bertujuan untuk mengetahui pengaruh model pembelajaran kooperatif tipe Jigsaw II terhadap peningkatan penguasaan konsep dan penurunan kecemasan peserta didik. Metode yang digunakan pada penelitian ini adalah kuasi eksperimen dengan desain pretest-posttest, nonequivalent control group design. Subyek penelitian berjumlah 79 peserta didik kelas XI IPA di salah satu SMAN di kota Padang, terdiri dari 40 peserta didik kelas eksperimen dan 39 peserta didik kelas kontrol. Instrumen yang digunakan yaitu tes penguasaan konsep, kuesioner kecemasan, pedoman wawancara, dan lembar observasi peserta didik. Analisis data menggunakan uji perbedaan rata-rata yaitu Uji-t atau uji Mann-Whitney. Skor rata-rata N-Gain penguasaan konsep peserta didik kelas eksperimen sebesar 0,60 dan kelas kontrol sebesar 0,49. Skor rata-rata N-Gain kecemasan peserta didik kelas eksperimen 0,45 dan kelas kontrol sebesar 0,36. Berdasarkan skor N-Gain terdapat perbedaan yang signifikan antara penguasaan konsep dan kecemasan peserta didik kelas eksperimen dan kelas kontrol. Model pembelajaran kooperatif tipe Jigsaw II dapat meningkatkan penguasaan konsep peserta didik dan menurunkan kecemasan peserta didik.

A hybrid agent-based approach for modeling microbiological systems.

Science.gov (United States)

Guo, Zaiyi; Sloot, Peter M A; Tay, Joc Cing

2008-11-21

Models for systems biology commonly adopt Differential Equations or Agent-Based modeling approaches for simulating the processes as a whole. Models based on differential equations presuppose phenomenological intracellular behavioral mechanisms, while models based on Multi-Agent approach often use directly translated, and quantitatively less precise if-then logical rule constructs. We propose an extendible systems model based on a hybrid agent-based approach where biological cells are modeled as individuals (agents) while molecules are represented by quantities. This hybridization in entity representation entails a combined modeling strategy with agent-based behavioral rules and differential equations, thereby balancing the requirements of extendible model granularity with computational tractability. We demonstrate the efficacy of this approach with models of chemotaxis involving an assay of 10(3) cells and 1.2x10(6) molecules. The model produces cell migration patterns that are comparable to laboratory observations.

Hybrid biasing approaches for global variance reduction

International Nuclear Information System (INIS)

Wu, Zeyun; Abdel-Khalik, Hany S.

2013-01-01

A new variant of Monte Carlo—deterministic (DT) hybrid variance reduction approach based on Gaussian process theory is presented for accelerating convergence of Monte Carlo simulation and compared with Forward-Weighted Consistent Adjoint Driven Importance Sampling (FW-CADIS) approach implemented in the SCALE package from Oak Ridge National Laboratory. The new approach, denoted the Gaussian process approach, treats the responses of interest as normally distributed random processes. The Gaussian process approach improves the selection of the weight windows of simulated particles by identifying a subspace that captures the dominant sources of statistical response variations. Like the FW-CADIS approach, the Gaussian process approach utilizes particle importance maps obtained from deterministic adjoint models to derive weight window biasing. In contrast to the FW-CADIS approach, the Gaussian process approach identifies the response correlations (via a covariance matrix) and employs them to reduce the computational overhead required for global variance reduction (GVR) purpose. The effective rank of the covariance matrix identifies the minimum number of uncorrelated pseudo responses, which are employed to bias simulated particles. Numerical experiments, serving as a proof of principle, are presented to compare the Gaussian process and FW-CADIS approaches in terms of the global reduction in standard deviation of the estimated responses. - Highlights: ► Hybrid Monte Carlo Deterministic Method based on Gaussian Process Model is introduced. ► Method employs deterministic model to calculate responses correlations. ► Method employs correlations to bias Monte Carlo transport. ► Method compared to FW-CADIS methodology in SCALE code. ► An order of magnitude speed up is achieved for a PWR core model.

Gold-nanoparticle-mediated jigsaw-puzzle-like assembly of supersized plasmonic DNA origami.

Science.gov (United States)

Yao, Guangbao; Li, Jiang; Chao, Jie; Pei, Hao; Liu, Huajie; Zhao, Yun; Shi, Jiye; Huang, Qing; Wang, Lianhui; Huang, Wei; Fan, Chunhai

2015-03-02

DNA origami has rapidly emerged as a powerful and programmable method to construct functional nanostructures. However, the size limitation of approximately 100 nm in classic DNA origami hampers its plasmonic applications. Herein, we report a jigsaw-puzzle-like assembly strategy mediated by gold nanoparticles (AuNPs) to break the size limitation of DNA origami. We demonstrated that oligonucleotide-functionalized AuNPs function as universal joint units for the one-pot assembly of parent DNA origami of triangular shape to form sub-microscale super-origami nanostructures. AuNPs anchored at predefined positions of the super-origami exhibited strong interparticle plasmonic coupling. This AuNP-mediated strategy offers new opportunities to drive macroscopic self-assembly and to fabricate well-defined nanophotonic materials and devices. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Comparison of two different techniques of cooperative learning approach: Undergraduates' conceptual understanding in the context of hormone biochemistry.

Science.gov (United States)

Mutlu, Ayfer

2018-03-01

The purpose of the research was to compare the effects of two different techniques of the cooperative learning approach, namely Team-Game Tournament and Jigsaw, on undergraduates' conceptual understanding in a Hormone Biochemistry course. Undergraduates were randomly assigned to Group 1 (N = 23) and Group 2 (N = 29). Instructions were accomplished using Team-Game Tournament in Group 1 and Jigsaw in Group 2. Before the instructions, all groups were informed about cooperative learning and techniques, their responsibilities in the learning process and accessing of resources. Instructions were conducted under the guidance of the researcher for nine weeks and the Hormone Concept Test developed by the researcher was used before and after the instructions for data collection. According to the results, while both techniques improved students' understanding, Jigsaw was more effective than Team-Game Tournament. © 2017 by The International Union of Biochemistry and Molecular Biology, 46(2):114-120, 2018. © 2017 The International Union of Biochemistry and Molecular Biology.

The Effect of Jigsaw Technique on 6th Graders' Learning of Force and Motion Unit and Their Science Attitudes and Motivation

Science.gov (United States)

Ural, Evrim; Ercan, Orhan; Gençoglan, Durdu Mehmet

2017-01-01

The study aims to investigate the effects of jigsaw technique on 6th graders' learning of "Force and Motion" unit, their science learning motivation and their attitudes towards science classes. The sample of the study consisted of 49 6th grade students from two different classes taking the Science and Technology course at a government…

Creation and implementation of a flipped jigsaw activity to stimulate interest in biochemistry among medical students.

Science.gov (United States)

Williams, Charlene; Perlis, Susan; Gaughan, John; Phadtare, Sangita

2018-05-06

Learner-centered pedagogical methods that are based on clinical application of basic science concepts through active learning and problem solving are shown to be effective for improving knowledge retention. As the clinical relevance of biochemistry is not always apparent to health-profession students, effective teaching of medical biochemistry should highlight the implications of biochemical concepts in pathology, minimize memorization, and make the concepts memorable for long-term retention. Here, we report the creation and successful implementation of a flipped jigsaw activity that was developed to stimulate interest in learning biochemistry among medical students. The activity combined the elements of a flipped classroom for learning concepts followed by a jigsaw activity to retrieve these concepts by solving clinical cases, answering case-based questions, and creating concept maps. The students' reception of the activity was very positive. They commented that the activity provided them an opportunity to review and synthesize information, helped to gage their learning by applying this information and work with peers. Students' improved performance especially for answering the comprehension-based questions correctly in the postquiz as well as the depth of information included in the postquiz concept maps suggested that the activity helped them to understand how different clinical scenarios develop owing to deviations in basic biochemical pathways. Although this activity was created for medical students, the format of this activity can also be useful for other health-professional students as well as undergraduate and graduate students. © 2018 by The International Union of Biochemistry and Molecular Biology, 2018. © 2018 The International Union of Biochemistry and Molecular Biology.

A Hybrid Approach on Tourism Demand Forecasting

Science.gov (United States)

Nor, M. E.; Nurul, A. I. M.; Rusiman, M. S.

2018-04-01

Tourism has become one of the important industries that contributes to the country’s economy. Tourism demand forecasting gives valuable information to policy makers, decision makers and organizations related to tourism industry in order to make crucial decision and planning. However, it is challenging to produce an accurate forecast since economic data such as the tourism data is affected by social, economic and environmental factors. In this study, an equally-weighted hybrid method, which is a combination of Box-Jenkins and Artificial Neural Networks, was applied to forecast Malaysia’s tourism demand. The forecasting performance was assessed by taking the each individual method as a benchmark. The results showed that this hybrid approach outperformed the other two models

Detection of cardiovascular anomalies: Hybrid systems approach

KAUST Repository

Ledezma, Fernando

2012-06-06

In this paper, we propose a hybrid interpretation of the cardiovascular system. Based on a model proposed by Simaan et al. (2009), we study the problem of detecting cardiovascular anomalies that can be caused by variations in some physiological parameters, using an observerbased approach. We present the first numerical results obtained. © 2012 IFAC.

A HYBRID APPROACH FOR RURAL FEEDER DESIGN

Directory of Open Access Journals (Sweden)

DAMANJEET KAUR

2012-08-01

Full Text Available In this paper, a population based approach for conductor size selection in rural radial distribution system is presented. The proposed hybrid approach implies a particle swarm optimization (PSO approach in combination with mutant property of differential evolution (DE for conductor size selection in radial distribution system. The conductor size for each feeder segment is selected such that the total cost of capital investment and capitalized cost of energy losses is minimized while constraints of voltage at each node and current carrying capacity of conductor is within the limits. The applicability and effectiveness of the proposed method is demonstrated with the help of 32-node test system.

HYBRID EDUCATION: THE ESTIMATION IN THE CATEGORIES OF INFORMATION-AXIOLOGICAL APPROACH

Directory of Open Access Journals (Sweden)

A. S. Kizilova

2018-01-01

Full Text Available Introduction: a hybrid assessment of reality is a new information-axiological level of communication between people. The term "hybrid (hybrid training" has been used as a result of the integration of digital and communication technologies in the form of online courses.Materials and methods: the main Russian forms of education are analyzed. The evaluation of the forms of education in the categories of the information-axiological approach is made on the basis of the following idea: everything is interchangeable, since everything has value. The mixing principles and models used in the process of hybrid formation are considered. Due to the fact that any mixed training requires planning, the analysis of the project and the target group, content analysis and financial analysis in this process is carried out.Results: specific educational methods are studied at the Bauman MSTU, subject to a hybrid assessment in the categories of the information-axiological approach. The analysis showed that the above explanation of the term "hybrid formation" is extremely narrow and one-sided. In particular, the search for information on volunteer education and the search for a socially-based education was conducted not only in the Bauman MSTU, but in Russia as a whole. However, the result was the portals of international student organizations with their own projects. Another example of a different interpretation of the "hybrid education" may be the assumption of quite axiologically new duties.Discussion and Conclusions: hybrid education is not limited to any temporal and territorial framework. It can manifest itself not only in the Internet-sphere, but also in the most diverse spheres of everyday life, with the interaction of various people and entire societies.

A hybrid approach to designing inbound-resupply strategies

NARCIS (Netherlands)

Dullaert, Wout; Vernimmen, Bert; Raa, Birger; Witlox, Frank

A new hybrid approach was developed to determine the optimal inbound-resupply strategy when suppliers ship goods to receivers. The optimal reorder level was calculated on the basis of a simulation of the distribution of demand and the lead time of the various sourcing alternatives. An evolutionary

Influence on Learning of a Collaborative Learning Method Comprising the Jigsaw Method and Problem-based Learning (PBL).

Science.gov (United States)

Takeda, Kayoko; Takahashi, Kiyoshi; Masukawa, Hiroyuki; Shimamori, Yoshimitsu

2017-01-01

Recently, the practice of active learning has spread, increasingly recognized as an essential component of academic studies. Classes incorporating small group discussion (SGD) are conducted at many universities. At present, assessments of the effectiveness of SGD have mostly involved evaluation by questionnaires conducted by teachers, by peer assessment, and by self-evaluation of students. However, qualitative data, such as open-ended descriptions by students, have not been widely evaluated. As a result, we have been unable to analyze the processes and methods involved in how students acquire knowledge in SGD. In recent years, due to advances in information and communication technology (ICT), text mining has enabled the analysis of qualitative data. We therefore investigated whether the introduction of a learning system comprising the jigsaw method and problem-based learning (PBL) would improve student attitudes toward learning; we did this by text mining analysis of the content of student reports. We found that by applying the jigsaw method before PBL, we were able to improve student attitudes toward learning and increase the depth of their understanding of the area of study as a result of working with others. The use of text mining to analyze qualitative data also allowed us to understand the processes and methods by which students acquired knowledge in SGD and also changes in students' understanding and performance based on improvements to the class. This finding suggests that the use of text mining to analyze qualitative data could enable teachers to evaluate the effectiveness of various methods employed to improve learning.

THE APPLICATION OF JIGSAW AND NUMBERED HEADS TOGETHER TECHNIQUES IN IMPROVING STUDENTS’ ABILITY IN SPEAKING SKILL

Directory of Open Access Journals (Sweden)

Siti Aimah

2017-04-01

Full Text Available This research was aimed to investigate how the study of speaking was developed through Jigsaw and Numbered Heads Together techniques and find out the improvement of students’ ability in speaking. For this purpose, 14 students of the second semester students were taken in the academic year of 2012/2013. A classroom action research was conducted in which consisted of two cycles through the stages of planning, action, observation, and reflection. The speaking tests, the observation note, and the questionnaire were taken as the data. The result of this research showed the students’ ability in speaking improved significantly. They were more enthusiastic in joining the class. They could learn together with their team in understanding the material and conveying it to the others well. They were also dared to tell what they wanted to tell the others without any pressuring from anyone else. They tried to snatch away each others in conveying their idea based on the number mentioned by the lecturer. In some cases, they even argued their argumentation attractively. While from the questionnaire which was distributed showed that more than 75% students felt the application of Jigsaw and Numbered Heads Together techniques helped them easily in developing their ability in speaking skill. And more than 80% students agreed those techniques facilitated them on having the accountability in understanding and conveying the material that they had learnt easily to the others. Studying in a team proved that the students enjoyed more in joining the English class. So it is suggested that the English lecturers should use the types of cooperative learning in teaching language skills.

The Effect of Two Different Cooperative Approaches on Students' Learning and Practices within the Context of a WebQuest Science Investigation

Science.gov (United States)

Zacharia, Zacharias C.; Xenofontos, Nikoletta A.; Manoli, Constantinos C.

2011-01-01

The goal of this study was to investigate the effect of two different cooperative learning approaches, namely, the Jigsaw Cooperative Approach (JCA) and the Traditional Cooperative Approach (TCA), on students' learning and practices/actions within the context of a WebQuest science investigation. Another goal of this study was to identify possible…

A hybrid approach to simulate multiple photon scattering in X-ray imaging

International Nuclear Information System (INIS)

Freud, N.; Letang, J.-M.; Babot, D.

2005-01-01

A hybrid simulation approach is proposed to compute the contribution of scattered radiation in X- or γ-ray imaging. This approach takes advantage of the complementarity between the deterministic and probabilistic simulation methods. The proposed hybrid method consists of two stages. Firstly, a set of scattering events occurring in the inspected object is determined by means of classical Monte Carlo simulation. Secondly, this set of scattering events is used as a starting point to compute the energy imparted to the detector, with a deterministic algorithm based on a 'forced detection' scheme. For each scattering event, the probability for the scattered photon to reach each pixel of the detector is calculated using well-known physical models (form factor and incoherent scattering function approximations, in the case of Rayleigh and Compton scattering respectively). The results of the proposed hybrid approach are compared to those obtained with the Monte Carlo method alone (Geant4 code) and found to be in excellent agreement. The convergence of the results when the number of scattering events increases is studied. The proposed hybrid approach makes it possible to simulate the contribution of each type (Compton or Rayleigh) and order of scattering, separately or together, with a single PC, within reasonable computation times (from minutes to hours, depending on the number of pixels of the detector). This constitutes a substantial benefit, compared to classical simulation methods (Monte Carlo or deterministic approaches), which usually requires a parallel computing architecture to obtain comparable results

A hybrid approach to simulate multiple photon scattering in X-ray imaging

Energy Technology Data Exchange (ETDEWEB)

Freud, N. [CNDRI, Laboratory of Nondestructive Testing using Ionizing Radiations, INSA-Lyon Scientific and Technical University, Bat. Antoine de Saint-Exupery, 20, avenue Albert Einstein, 69621 Villeurbanne Cedex (France)]. E-mail: nicolas.freud@insa-lyon.fr; Letang, J.-M. [CNDRI, Laboratory of Nondestructive Testing using Ionizing Radiations, INSA-Lyon Scientific and Technical University, Bat. Antoine de Saint-Exupery, 20, avenue Albert Einstein, 69621 Villeurbanne Cedex (France); Babot, D. [CNDRI, Laboratory of Nondestructive Testing using Ionizing Radiations, INSA-Lyon Scientific and Technical University, Bat. Antoine de Saint-Exupery, 20, avenue Albert Einstein, 69621 Villeurbanne Cedex (France)

2005-01-01

A hybrid simulation approach is proposed to compute the contribution of scattered radiation in X- or {gamma}-ray imaging. This approach takes advantage of the complementarity between the deterministic and probabilistic simulation methods. The proposed hybrid method consists of two stages. Firstly, a set of scattering events occurring in the inspected object is determined by means of classical Monte Carlo simulation. Secondly, this set of scattering events is used as a starting point to compute the energy imparted to the detector, with a deterministic algorithm based on a 'forced detection' scheme. For each scattering event, the probability for the scattered photon to reach each pixel of the detector is calculated using well-known physical models (form factor and incoherent scattering function approximations, in the case of Rayleigh and Compton scattering respectively). The results of the proposed hybrid approach are compared to those obtained with the Monte Carlo method alone (Geant4 code) and found to be in excellent agreement. The convergence of the results when the number of scattering events increases is studied. The proposed hybrid approach makes it possible to simulate the contribution of each type (Compton or Rayleigh) and order of scattering, separately or together, with a single PC, within reasonable computation times (from minutes to hours, depending on the number of pixels of the detector). This constitutes a substantial benefit, compared to classical simulation methods (Monte Carlo or deterministic approaches), which usually requires a parallel computing architecture to obtain comparable results.

Effect of the Jigsaw-Based Cooperative Learning Method on Student Performance in the General Certificate of Education Advanced-Level Psychology: An Exploratory Brunei Case Study

Science.gov (United States)

Azmin, Nur Hafizah

2016-01-01

The mixed-methods study investigated the effect of the jigsaw cooperative learning method on student performance in psychology and their views towards it. Experimental data were obtained via pre-and-post tests and an open-ended questionnaire from 16 conveniently selected students at one Sixth Form College in Brunei. Moreover, the participants…

DyHAP: Dynamic Hybrid ANFIS-PSO Approach for Predicting Mobile Malware.

Science.gov (United States)

Afifi, Firdaus; Anuar, Nor Badrul; Shamshirband, Shahaboddin; Choo, Kim-Kwang Raymond

2016-01-01

To deal with the large number of malicious mobile applications (e.g. mobile malware), a number of malware detection systems have been proposed in the literature. In this paper, we propose a hybrid method to find the optimum parameters that can be used to facilitate mobile malware identification. We also present a multi agent system architecture comprising three system agents (i.e. sniffer, extraction and selection agent) to capture and manage the pcap file for data preparation phase. In our hybrid approach, we combine an adaptive neuro fuzzy inference system (ANFIS) and particle swarm optimization (PSO). Evaluations using data captured on a real-world Android device and the MalGenome dataset demonstrate the effectiveness of our approach, in comparison to two hybrid optimization methods which are differential evolution (ANFIS-DE) and ant colony optimization (ANFIS-ACO).

DyHAP: Dynamic Hybrid ANFIS-PSO Approach for Predicting Mobile Malware.

Directory of Open Access Journals (Sweden)

Firdaus Afifi

Full Text Available To deal with the large number of malicious mobile applications (e.g. mobile malware, a number of malware detection systems have been proposed in the literature. In this paper, we propose a hybrid method to find the optimum parameters that can be used to facilitate mobile malware identification. We also present a multi agent system architecture comprising three system agents (i.e. sniffer, extraction and selection agent to capture and manage the pcap file for data preparation phase. In our hybrid approach, we combine an adaptive neuro fuzzy inference system (ANFIS and particle swarm optimization (PSO. Evaluations using data captured on a real-world Android device and the MalGenome dataset demonstrate the effectiveness of our approach, in comparison to two hybrid optimization methods which are differential evolution (ANFIS-DE and ant colony optimization (ANFIS-ACO.

DyHAP: Dynamic Hybrid ANFIS-PSO Approach for Predicting Mobile Malware

Science.gov (United States)

Afifi, Firdaus; Anuar, Nor Badrul; Shamshirband, Shahaboddin

2016-01-01

To deal with the large number of malicious mobile applications (e.g. mobile malware), a number of malware detection systems have been proposed in the literature. In this paper, we propose a hybrid method to find the optimum parameters that can be used to facilitate mobile malware identification. We also present a multi agent system architecture comprising three system agents (i.e. sniffer, extraction and selection agent) to capture and manage the pcap file for data preparation phase. In our hybrid approach, we combine an adaptive neuro fuzzy inference system (ANFIS) and particle swarm optimization (PSO). Evaluations using data captured on a real-world Android device and the MalGenome dataset demonstrate the effectiveness of our approach, in comparison to two hybrid optimization methods which are differential evolution (ANFIS-DE) and ant colony optimization (ANFIS-ACO). PMID:27611312

A Hybrid Supervised/Unsupervised Machine Learning Approach to Solar Flare Prediction

Science.gov (United States)

Benvenuto, Federico; Piana, Michele; Campi, Cristina; Massone, Anna Maria

2018-01-01

This paper introduces a novel method for flare forecasting, combining prediction accuracy with the ability to identify the most relevant predictive variables. This result is obtained by means of a two-step approach: first, a supervised regularization method for regression, namely, LASSO is applied, where a sparsity-enhancing penalty term allows the identification of the significance with which each data feature contributes to the prediction; then, an unsupervised fuzzy clustering technique for classification, namely, Fuzzy C-Means, is applied, where the regression outcome is partitioned through the minimization of a cost function and without focusing on the optimization of a specific skill score. This approach is therefore hybrid, since it combines supervised and unsupervised learning; realizes classification in an automatic, skill-score-independent way; and provides effective prediction performances even in the case of imbalanced data sets. Its prediction power is verified against NOAA Space Weather Prediction Center data, using as a test set, data in the range between 1996 August and 2010 December and as training set, data in the range between 1988 December and 1996 June. To validate the method, we computed several skill scores typically utilized in flare prediction and compared the values provided by the hybrid approach with the ones provided by several standard (non-hybrid) machine learning methods. The results showed that the hybrid approach performs classification better than all other supervised methods and with an effectiveness comparable to the one of clustering methods; but, in addition, it provides a reliable ranking of the weights with which the data properties contribute to the forecast.

A Theoretical Model of Jigsaw-Puzzle Pattern Formation by Plant Leaf Epidermal Cells.

Science.gov (United States)

Higaki, Takumi; Kutsuna, Natsumaro; Akita, Kae; Takigawa-Imamura, Hisako; Yoshimura, Kenji; Miura, Takashi

2016-04-01

Plant leaf epidermal cells exhibit a jigsaw puzzle-like pattern that is generated by interdigitation of the cell wall during leaf development. The contribution of two ROP GTPases, ROP2 and ROP6, to the cytoskeletal dynamics that regulate epidermal cell wall interdigitation has already been examined; however, how interactions between these molecules result in pattern formation remains to be elucidated. Here, we propose a simple interface equation model that incorporates both the cell wall remodeling activity of ROP GTPases and the diffusible signaling molecules by which they are regulated. This model successfully reproduces pattern formation observed in vivo, and explains the counterintuitive experimental results of decreased cellulose production and increased thickness. Our model also reproduces the dynamics of three-way cell wall junctions. Therefore, this model provides a possible mechanism for cell wall interdigitation formation in vivo.

A hybrid generative-discriminative approach to speaker diarization

NARCIS (Netherlands)

Noulas, A.K.; van Kasteren, T.; Kröse, B.J.A.

2008-01-01

In this paper we present a sound probabilistic approach to speaker diarization. We use a hybrid framework where a distribution over the number of speakers at each point of a multimodal stream is estimated with a discriminative model. The output of this process is used as input in a generative model

The Effect of Using Jigsaw Strategy in Teaching Science on the Acquisition of Scientific Concepts among the Fourth Graders of Bani Kinana Directorate of Education

Science.gov (United States)

Hamadneh, Qaseem Mohammad Salim

2017-01-01

The study aimed to identify the effect of using Jigsaw strategy in teaching science on the acquisition of scientific concepts among the fourth graders of Bani Kinana Directorate of Education compared to the traditional way. The study sample consisted of 70 male and female students, divided into two groups: experimental and control where the…

MODEL PEMBELAJARAN JIGSAW DENGAN STRATEGI METAKOGNITIF UNTUK MENINGKATKAN SELF-EFFICACY DAN KEMAMPUAN PEMECAHAN MASALAH

Directory of Open Access Journals (Sweden)

Purtiana Septi Alfurofika

2013-12-01

Full Text Available Tujuan penelitian ini untuk menghasilkan perangkat pembelajaran matematika model Jigsaw strategi Metakognitif untuk meningkatkan self-efficacy terhadap kemampuan pemecahan masalah dengan materi segi empat kelas VII valid, praktis dan efektif. Penelitian ini merupakan penelitian pengembangan modifikasi Plomp. Jenis perangkat pembelajaran yang dikembangkan adalah silabus, RPP, bahan ajar, LKS, media pembelajaran, Tes Kemampuan Pemecahan Masalah. Teknik pengambilan data menggunakan lembar validasi, lembar pengamatan self-efficacy dan aktifitas, Lembar angket, dan Tes Kemampuan Pemecahan Masalah. Hasil penelitian menunjukkan: (1 perangkat yang dikembangkan valid; (2 pembelajaran praktis ditandai dengan respon positif siswa dan kemampuan guru baik; (3 Efektifitas ditandai dengan (a kemampuan pemecahan masalah mencapai KKM yaitu 83,4 dan ketuntasan klasikal sebesar 90,3%; (b self-efficacy dan aktifitas siswa secara bersama – sama berpengaruh positif terhadap kemampuan pemecahan masalah sebesar 71,9%; dan (c self-efficacy dan aktivitas siswa mengalami peningkatan. Berdasarkan hasil penelitian dapat disimpulkan tujuan pengembangan perangkat tercapai. The aim of this research to produce mathematics’ learning device the Jigsaw model with Metacognitive strategies for increasing self-efficacy towards problem solving ability to quadrilateral of class VII valid, practical and effective. This research is development of modifications Plomp. Kinds of learning devices are developed syllabi, lesson plans, teaching materials, worksheets, instructional media, and problem solving ability test. Technique of data collection by using validation sheet, observation sheet student’s self-efficacy and activity, questionnaire, and problem solving ability test. The results showed: (1 device developed valid; (2 practical learning is characterized by the positive response of students and good teachers ability; (3 effectiveness characterized by (a the ability of problem

Restraining approach for the spurious kinematic modes in hybrid equilibrium element

Science.gov (United States)

Parrinello, F.

2013-10-01

The present paper proposes a rigorous approach for the elimination of spurious kinematic modes in hybrid equilibrium elements, for three well known mesh patches. The approach is based on the identification of the dependent equations in the set of inter-element and boundary equilibrium equations of the sides involved in the spurious kinematic mode. Then the kinematic variables related to the dependent equations are reciprocally constrained and, by application of master slave elimination method, the set of inter-element equilibrium equations is reduced to full rank. The elastic solutions produced by means of the proposed approach verify the homogeneous, the inter-element and the boundary equilibrium equations. Hybrid stress formulation is developed in a rigorous mathematical setting. The results of linear elastic analysis obtained by the proposed approach and by classical displacement based method are compared for some structural examples.

Does the acceptance of hybrid learning affect learning approaches in France?

Science.gov (United States)

Marco, Lionel Di; Venot, Alain; Gillois, Pierre

2017-01-01

Acceptance of a learning technology affects students' intention to use that technology, but the influence of the acceptance of a learning technology on learning approaches has not been investigated in the literature. A deep learning approach is important in the field of health, where links must be created between skills, knowledge, and habits. Our hypothesis was that acceptance of a hybrid learning model would affect students' way of learning. We analysed these concepts, and their correlations, in the context of a flipped classroom method using a local learning management system. In a sample of all students within a single year of study in the midwifery program (n= 38), we used 3 validated scales to evaluate these concepts (the Study Process Questionnaire, My Intellectual Work Tools, and the Hybrid E-Learning Acceptance Model: Learner Perceptions). Our sample had a positive acceptance of the learning model, but a neutral intention to use it. Students reported that they were distractible during distance learning. They presented a better mean score for the deep approach than for the superficial approach (Paffected by acceptance of a hybrid learning model, due to the flexibility of the tool. However, we identified problems in the students' time utilization, which explains their neutral intention to use the system.

Eksperimentasi Model Jigsaw Snowball Drilling dan Peer Tutoring Snowball Drilling pada Materi Pokok Tabung, Kerucut, dan Bola Ditinjau dari Gaya Belajar Siswa

OpenAIRE

P, Nelly Indriastuti; Kusmayadi, Tri Atmojo; Usodo, Budi

2014-01-01

The aims of this research were to determine: (1) which results better mathematics learning achievement between students who were taught by using jigsaw snowball drilling, peer tutoring snowball drilling, or direct instruction, (2) which has better mathematics learning achievement between students with visual learning styles, auditory, or kinesthetic, (3). at each of the learning model, which one has better mathematics learning achievement between student with visual learning style, auditory, ...

A Generalized Hybrid Multiscale Modeling Approach for Flow and Reactive Transport in Porous Media

Science.gov (United States)

Yang, X.; Meng, X.; Tang, Y. H.; Guo, Z.; Karniadakis, G. E.

2017-12-01

Using emerging understanding of biological and environmental processes at fundamental scales to advance predictions of the larger system behavior requires the development of multiscale approaches, and there is strong interest in coupling models at different scales together in a hybrid multiscale simulation framework. A limited number of hybrid multiscale simulation methods have been developed for subsurface applications, mostly using application-specific approaches for model coupling. The proposed generalized hybrid multiscale approach is designed with minimal intrusiveness to the at-scale simulators (pre-selected) and provides a set of lightweight C++ scripts to manage a complex multiscale workflow utilizing a concurrent coupling approach. The workflow includes at-scale simulators (using the lattice-Boltzmann method, LBM, at the pore and Darcy scale, respectively), scripts for boundary treatment (coupling and kriging), and a multiscale universal interface (MUI) for data exchange. The current study aims to apply the generalized hybrid multiscale modeling approach to couple pore- and Darcy-scale models for flow and mixing-controlled reaction with precipitation/dissolution in heterogeneous porous media. The model domain is packed heterogeneously that the mixing front geometry is more complex and not known a priori. To address those challenges, the generalized hybrid multiscale modeling approach is further developed to 1) adaptively define the locations of pore-scale subdomains, 2) provide a suite of physical boundary coupling schemes and 3) consider the dynamic change of the pore structures due to mineral precipitation/dissolution. The results are validated and evaluated by comparing with single-scale simulations in terms of velocities, reactive concentrations and computing cost.

Facile approach to prepare Pt decorated SWNT/graphene hybrid catalytic ink

Energy Technology Data Exchange (ETDEWEB)

Mayavan, Sundar, E-mail: sundarmayavan@cecri.res.in [Centre for Innovation in Energy Research, CSIR–Central Electrochemical Research Institute, Karaikudi 630006, Tamil Nadu (India); Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 305-701 (Korea, Republic of); Mandalam, Aditya; Balasubramanian, M. [Centre for Innovation in Energy Research, CSIR–Central Electrochemical Research Institute, Karaikudi 630006, Tamil Nadu (India); Sim, Jun-Bo [Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 305-701 (Korea, Republic of); Choi, Sung-Min, E-mail: sungmin@kaist.ac.kr [Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 305-701 (Korea, Republic of)

2015-07-15

Highlights: • Pt NPs were in situ synthesized onto CNT–graphene support in aqueous solution. • The as-prepared material was used directly as a catalyst ink without further treatment. • Catalyst ink is active toward methanol oxidation. • This approach realizes both scalable and greener production of hybrid catalysts. - Abstract: Platinum nanoparticles were in situ synthesized onto hybrid support involving graphene and single walled carbon nanotube in aqueous solution. We investigate the reduction of graphene oxide, and platinum nanoparticle functionalization on hybrid support by X-ray photoelectron spectroscopy, Raman spectroscopy, X-ray diffraction, scanning electron microscopy and transmission electron microscopy. The as-prepared platinum on hybrid support was used directly as a catalyst ink without further treatment and is active toward methanol oxidation. This work realizes both scalable and greener production of highly efficient hybrid catalysts, and would be valuable for practical applications of graphene based fuel cell catalysts.

A hybrid clustering approach to recognition of protein families in 114 microbial genomes

Directory of Open Access Journals (Sweden)

Gogarten J Peter

2004-04-01

Full Text Available Abstract Background Grouping proteins into sequence-based clusters is a fundamental step in many bioinformatic analyses (e.g., homology-based prediction of structure or function. Standard clustering methods such as single-linkage clustering capture a history of cluster topologies as a function of threshold, but in practice their usefulness is limited because unrelated sequences join clusters before biologically meaningful families are fully constituted, e.g. as the result of matches to so-called promiscuous domains. Use of the Markov Cluster algorithm avoids this non-specificity, but does not preserve topological or threshold information about protein families. Results We describe a hybrid approach to sequence-based clustering of proteins that combines the advantages of standard and Markov clustering. We have implemented this hybrid approach over a relational database environment, and describe its application to clustering a large subset of PDB, and to 328577 proteins from 114 fully sequenced microbial genomes. To demonstrate utility with difficult problems, we show that hybrid clustering allows us to constitute the paralogous family of ATP synthase F1 rotary motor subunits into a single, biologically interpretable hierarchical grouping that was not accessible using either single-linkage or Markov clustering alone. We describe validation of this method by hybrid clustering of PDB and mapping SCOP families and domains onto the resulting clusters. Conclusion Hybrid (Markov followed by single-linkage clustering combines the advantages of the Markov Cluster algorithm (avoidance of non-specific clusters resulting from matches to promiscuous domains and single-linkage clustering (preservation of topological information as a function of threshold. Within the individual Markov clusters, single-linkage clustering is a more-precise instrument, discerning sub-clusters of biological relevance. Our hybrid approach thus provides a computationally efficient

New MPPT algorithm for PV applications based on hybrid dynamical approach

KAUST Repository

Elmetennani, Shahrazed

2016-10-24

This paper proposes a new Maximum Power Point Tracking (MPPT) algorithm for photovoltaic applications using the multicellular converter as a stage of power adaptation. The proposed MPPT technique has been designed using a hybrid dynamical approach to model the photovoltaic generator. The hybrid dynamical theory has been applied taking advantage of the particular topology of the multicellular converter. Then, a hybrid automata has been established to optimize the power production. The maximization of the produced solar energy is achieved by switching between the different operative modes of the hybrid automata, which is conditioned by some invariance and transition conditions. These conditions have been validated by simulation tests under different conditions of temperature and irradiance. Moreover, the performance of the proposed algorithm has been then evaluated by comparison with standard MPPT techniques numerically and by experimental tests under varying external working conditions. The results have shown the interesting features that the hybrid MPPT technique presents in terms of performance and simplicity for real time implementation.

New MPPT algorithm for PV applications based on hybrid dynamical approach

KAUST Repository

Elmetennani, Shahrazed; Laleg-Kirati, Taous-Meriem; Djemai, M.; Tadjine, M.

2016-01-01

This paper proposes a new Maximum Power Point Tracking (MPPT) algorithm for photovoltaic applications using the multicellular converter as a stage of power adaptation. The proposed MPPT technique has been designed using a hybrid dynamical approach to model the photovoltaic generator. The hybrid dynamical theory has been applied taking advantage of the particular topology of the multicellular converter. Then, a hybrid automata has been established to optimize the power production. The maximization of the produced solar energy is achieved by switching between the different operative modes of the hybrid automata, which is conditioned by some invariance and transition conditions. These conditions have been validated by simulation tests under different conditions of temperature and irradiance. Moreover, the performance of the proposed algorithm has been then evaluated by comparison with standard MPPT techniques numerically and by experimental tests under varying external working conditions. The results have shown the interesting features that the hybrid MPPT technique presents in terms of performance and simplicity for real time implementation.

A hybrid approach for global sensitivity analysis

International Nuclear Information System (INIS)

Chakraborty, Souvik; Chowdhury, Rajib

2017-01-01

Distribution based sensitivity analysis (DSA) computes sensitivity of the input random variables with respect to the change in distribution of output response. Although DSA is widely appreciated as the best tool for sensitivity analysis, the computational issue associated with this method prohibits its use for complex structures involving costly finite element analysis. For addressing this issue, this paper presents a method that couples polynomial correlated function expansion (PCFE) with DSA. PCFE is a fully equivalent operational model which integrates the concepts of analysis of variance decomposition, extended bases and homotopy algorithm. By integrating PCFE into DSA, it is possible to considerably alleviate the computational burden. Three examples are presented to demonstrate the performance of the proposed approach for sensitivity analysis. For all the problems, proposed approach yields excellent results with significantly reduced computational effort. The results obtained, to some extent, indicate that proposed approach can be utilized for sensitivity analysis of large scale structures. - Highlights: • A hybrid approach for global sensitivity analysis is proposed. • Proposed approach integrates PCFE within distribution based sensitivity analysis. • Proposed approach is highly efficient.

Numerical schemes for the hybrid modeling approach of gas-particle turbulent flows

International Nuclear Information System (INIS)

Dorogan, K.

2012-01-01

Hybrid Moments/PDF methods have shown to be well suitable for the description of poly-dispersed turbulent two-phase flows in non-equilibrium which are encountered in some industrial situations involving chemical reactions, combustion or sprays. They allow to obtain a fine enough physical description of the poly-dispersity, non-linear source terms and convection phenomena. However, their approximations are noised with the statistical error, which in several situations may be a source of a bias. An alternative hybrid Moments-Moments/PDF approach examined in this work consists in coupling the Moments and the PDF descriptions, within the description of the dispersed phase itself. This hybrid method could reduce the statistical error and remove the bias. However, such a coupling is not straightforward in practice and requires the development of accurate and stable numerical schemes. The approaches introduced in this work rely on the combined use of the up-winding and relaxation-type techniques. They allow to obtain stable unsteady approximations for a system of partial differential equations containing non-smooth external data which are provided by the PDF part of the model. A comparison of the results obtained using the present method with those of the 'classical' hybrid approach is presented in terms of the numerical errors for a case of a co-current gas-particle wall jet. (author)

A novel hybridization approach for detection of citrus viroids.

Science.gov (United States)

Murcia, N; Serra, P; Olmos, A; Duran-Vila, N

2009-04-01

Citrus plants are natural hosts of several viroid species all belonging to the family Pospiviroidae. Previous attempts to detect viroids from field-grown species and cultivars yielded erratic results unless analyses were performed using Etrog citron a secondary bio-amplification host. To overcome the use of Etrog citron a number of RT-PCR approaches have been proposed with different degrees of success. Here we report the suitability of an easy to handle northern hybridization protocol for viroid detection of samples collected from field-grown citrus species and cultivars. The protocol involves: (i) Nucleic acid preparations from bark tissue samples collected from field-grown trees regardless of the growing season and storage conditions; (ii) Separation in 5% PAGE or 1% agarose, blotting to membrane and fixing; (iii) Hybridization with viroid-specific DIG-labelled probes and detection with anti-DIG-alkaline phosphatase conjugate and autoradiography with the CSPD substrate. The method has been tested with viroid-infected trees of sweet orange, lemon, mandarin, grapefruit, sour orange, Swingle citrumello, Tahiti lime and Mexican lime. This novel hybridization approach is extremely sensitive, easy to handle and shortens the time needed for reliable viroid indexing tests. The suitability of PCR generated DIG-labelled probes and the sensitivity achieved when the samples are separated and blotted from non-denaturing gels are discussed.

Hybrid approaches to nanometer-scale patterning: Exploiting tailored intermolecular interactions

International Nuclear Information System (INIS)

Mullen, Thomas J.; Srinivasan, Charan; Shuster, Mitchell J.; Horn, Mark W.; Andrews, Anne M.; Weiss, Paul S.

2008-01-01

In this perspective, we explore hybrid approaches to nanometer-scale patterning, where the precision of molecular self-assembly is combined with the sophistication and fidelity of lithography. Two areas - improving existing lithographic techniques through self-assembly and fabricating chemically patterned surfaces - will be discussed in terms of their advantages, limitations, applications, and future outlook. The creation of such chemical patterns enables new capabilities, including the assembly of biospecific surfaces to be recognized by, and to capture analytes from, complex mixtures. Finally, we speculate on the potential impact and upcoming challenges of these hybrid strategies.

Short-term electricity prices forecasting in a competitive market by a hybrid intelligent approach

Energy Technology Data Exchange (ETDEWEB)

Catalao, J.P.S. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Center for Innovation in Electrical and Energy Engineering, Instituto Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001 Lisbon (Portugal); Pousinho, H.M.I. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Mendes, V.M.F. [Department of Electrical Engineering and Automation, Instituto Superior de Engenharia de Lisboa, R. Conselheiro Emidio Navarro, 1950-062 Lisbon (Portugal)

2011-02-15

In this paper, a hybrid intelligent approach is proposed for short-term electricity prices forecasting in a competitive market. The proposed approach is based on the wavelet transform and a hybrid of neural networks and fuzzy logic. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Conclusions are duly drawn. (author)

Short-term electricity prices forecasting in a competitive market by a hybrid intelligent approach

International Nuclear Information System (INIS)

Catalao, J.P.S.; Pousinho, H.M.I.; Mendes, V.M.F.

2011-01-01

In this paper, a hybrid intelligent approach is proposed for short-term electricity prices forecasting in a competitive market. The proposed approach is based on the wavelet transform and a hybrid of neural networks and fuzzy logic. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Conclusions are duly drawn. (author)

Advanced control approach for hybrid systems based on solid oxide fuel cells

International Nuclear Information System (INIS)

Ferrari, Mario L.

2015-01-01

Highlights: • Advanced new control system for SOFC based hybrid plants. • Proportional–Integral approach with feed-forward technology. • Good control of fuel cell temperature. • All critical properties maintained inside safe conditions. - Abstract: This paper shows a new advanced control approach for operations in hybrid systems equipped with solid oxide fuel cell technology. This new tool, which combines feed-forward and standard proportional–integral techniques, controls the system during load changes avoiding failures and stress conditions detrimental to component life. This approach was selected to combine simplicity and good control performance. Moreover, the new approach presented in this paper eliminates the need for mass flow rate meters and other expensive probes, as usually required for a commercial plant. Compared to previous works, better performance is achieved in controlling fuel cell temperature (maximum gradient significantly lower than 3 K/min), reducing the pressure gap between cathode and anode sides (at least a 30% decrease during transient operations), and generating a higher safe margin (at least a 10% increase) for the Steam-to-Carbon Ratio. This new control system was developed and optimized using a hybrid system transient model implemented, validated and tested within previous works. The plant, comprising the coupling of a tubular solid oxide fuel cell stack with a microturbine, is equipped with a bypass valve able to connect the compressor outlet with the turbine inlet duct for rotational speed control. Following model development and tuning activities, several operative conditions were considered to show the new control system increased performance compared to previous tools (the same hybrid system model was used with the new control approach). Special attention was devoted to electrical load steps and ramps considering significant changes in ambient conditions

Solving Unconstrained Global Optimization Problems via Hybrid Swarm Intelligence Approaches

Directory of Open Access Journals (Sweden)

Jui-Yu Wu

2013-01-01

Full Text Available Stochastic global optimization (SGO algorithms such as the particle swarm optimization (PSO approach have become popular for solving unconstrained global optimization (UGO problems. The PSO approach, which belongs to the swarm intelligence domain, does not require gradient information, enabling it to overcome this limitation of traditional nonlinear programming methods. Unfortunately, PSO algorithm implementation and performance depend on several parameters, such as cognitive parameter, social parameter, and constriction coefficient. These parameters are tuned by using trial and error. To reduce the parametrization of a PSO method, this work presents two efficient hybrid SGO approaches, namely, a real-coded genetic algorithm-based PSO (RGA-PSO method and an artificial immune algorithm-based PSO (AIA-PSO method. The specific parameters of the internal PSO algorithm are optimized using the external RGA and AIA approaches, and then the internal PSO algorithm is applied to solve UGO problems. The performances of the proposed RGA-PSO and AIA-PSO algorithms are then evaluated using a set of benchmark UGO problems. Numerical results indicate that, besides their ability to converge to a global minimum for each test UGO problem, the proposed RGA-PSO and AIA-PSO algorithms outperform many hybrid SGO algorithms. Thus, the RGA-PSO and AIA-PSO approaches can be considered alternative SGO approaches for solving standard-dimensional UGO problems.

A hybrid, coupled approach for modeling charged fluids from the nano to the mesoscale

Science.gov (United States)

Cheung, James; Frischknecht, Amalie L.; Perego, Mauro; Bochev, Pavel

2017-11-01

We develop and demonstrate a new, hybrid simulation approach for charged fluids, which combines the accuracy of the nonlocal, classical density functional theory (cDFT) with the efficiency of the Poisson-Nernst-Planck (PNP) equations. The approach is motivated by the fact that the more accurate description of the physics in the cDFT model is required only near the charged surfaces, while away from these regions the PNP equations provide an acceptable representation of the ionic system. We formulate the hybrid approach in two stages. The first stage defines a coupled hybrid model in which the PNP and cDFT equations act independently on two overlapping domains, subject to suitable interface coupling conditions. At the second stage we apply the principles of the alternating Schwarz method to the hybrid model by using the interface conditions to define the appropriate boundary conditions and volume constraints exchanged between the PNP and the cDFT subdomains. Numerical examples with two representative examples of ionic systems demonstrate the numerical properties of the method and its potential to reduce the computational cost of a full cDFT calculation, while retaining the accuracy of the latter near the charged surfaces.

Mass Optimization of Battery/Supercapacitors Hybrid Systems Based on a Linear Programming Approach

Science.gov (United States)

Fleury, Benoit; Labbe, Julien

2014-08-01

The objective of this paper is to show that, on a specific launcher-type mission profile, a 40% gain of mass is expected using a battery/supercapacitors active hybridization instead of a single battery solution. This result is based on the use of a linear programming optimization approach to perform the mass optimization of the hybrid power supply solution.

THE COMPARISON OF STUDENTS’ READING COMPREHENSION IN RECOUNT TEXT INSTRUCTION BETWEEN USING STAD AND JIGSAW TECHNIQUE AT DIFFERENT READING FREQUENCY AT THE FIRST GRADE OF SMA N 1 RUMBIA ACADEMIC YEAR 2012/2013

Directory of Open Access Journals (Sweden)

Didik Firnadi -

2014-04-01

Full Text Available Reading as one of the four skills has always been as a part of the syllabus in English instruction. Based on the Pra survey, reading comprehension of the students of the first grade of SMA N 1 Rumbia is still low, most of them still lack structure knowledge and vocabulary, and their reading frequency in reading is still low. There are two techniques presented as a solution in this research. They are STAD Technique and Jigsaw technique. The objective of this research is to find out the difference result of using STAD and Jigsaw technique toward students’ reading comprehension in recount text at different high and low reading frequency and to find out there is significant interaction and comparison of reading comprehension in recount text, learning technique, and different reading frequency at the first grade students of SMA N 1 Rumbia academic year 2012/2013. The method of investigation is held through quantitative research. The researcher uses true experimental research. In this experiment, the the researcher applies factorials design. The research is conducted at the first grade of SMA N 1 Rumbia in academic year 2012/2013. The population in this research is 180 students. It consisted 6 classes and each class consist 30 students. The researcher takes 52 students from total population as the sample, 26 students as experiment class and 26 as control class that match based on classification of student level. The researcher uses cluster random sampling as technique sampling. To analyze data, the researcher uses ANOVA TWO WAYS formula. The researcher got the result of Fhit is 18, 2 and Ftable  is 7, 14. It means that Fhit > Ftable. And the criterion of Ftest is Ha accepted if Fhit  > Ftable. So, there is any difference result of students’ Reading comprehension in recount text using STAD and Jigsaw, and STAD technique is more effective technique than Jigsaw technique toward students Reading comprehension at different reading frequency at the

Comparison of Two Different Techniques of Cooperative Learning Approach: Undergraduates' Conceptual Understanding in the Context of Hormone Biochemistry

Science.gov (United States)

Mutlu, Ayfer

2018-01-01

The purpose of the research was to compare the effects of two different techniques of the cooperative learning approach, namely Team-Game Tournament and Jigsaw, on undergraduates' conceptual understanding in a Hormone Biochemistry course. Undergraduates were randomly assigned to Group 1 (N = 23) and Group 2 (N = 29). Instructions were accomplished…

Hybrid generative-discriminative approach to age-invariant face recognition

Science.gov (United States)

Sajid, Muhammad; Shafique, Tamoor

2018-03-01

Age-invariant face recognition is still a challenging research problem due to the complex aging process involving types of facial tissues, skin, fat, muscles, and bones. Most of the related studies that have addressed the aging problem are focused on generative representation (aging simulation) or discriminative representation (feature-based approaches). Designing an appropriate hybrid approach taking into account both the generative and discriminative representations for age-invariant face recognition remains an open problem. We perform a hybrid matching to achieve robustness to aging variations. This approach automatically segments the eyes, nose-bridge, and mouth regions, which are relatively less sensitive to aging variations compared with the rest of the facial regions that are age-sensitive. The aging variations of age-sensitive facial parts are compensated using a demographic-aware generative model based on a bridged denoising autoencoder. The age-insensitive facial parts are represented by pixel average vector-based local binary patterns. Deep convolutional neural networks are used to extract relative features of age-sensitive and age-insensitive facial parts. Finally, the feature vectors of age-sensitive and age-insensitive facial parts are fused to achieve the recognition results. Extensive experimental results on morphological face database II (MORPH II), face and gesture recognition network (FG-NET), and Verification Subset of cross-age celebrity dataset (CACD-VS) demonstrate the effectiveness of the proposed method for age-invariant face recognition well.

Using Moos To Help Learn English; Video Jigsaw; Practicing Speaking with Follow-Up Interviews and Student-Read Dictations; "Ask the Expert": Oral Presentations that Work; The Medium Is the Message.

Science.gov (United States)

Miller, James; Reynolds, Judith; Noble, P. C.; Altschuler, Lee; Schauber, Holli

2001-01-01

Four short articles provide teaching tips for the English-as-a-Second/Foreign-Language classroom, including the use of Moos, a video jigsaw, practicing oral language skills with interviews and student-read dictations, an ask the expert activity which builds learner confidence in speaking in front of groups of people. (Author/VWL)

A hybrid simulated annealing approach to handle energy resource management considering an intensive use of electric vehicles

DEFF Research Database (Denmark)

Sousa, Tiago; Vale, Zita; Carvalho, Joao Paulo

2014-01-01

The massification of electric vehicles (EVs) can have a significant impact on the power system, requiring a new approach for the energy resource management. The energy resource management has the objective to obtain the optimal scheduling of the available resources considering distributed...... to determine the best solution in a reasonable amount of time. This paper presents a hybrid artificial intelligence technique to solve a complex energy resource management problem with a large number of resources, including EVs, connected to the electric network. The hybrid approach combines simulated...... annealing (SA) and ant colony optimization (ACO) techniques. The case study concerns different EVs penetration levels. Comparisons with a previous SA approach and a deterministic technique are also presented. For 2000 EVs scenario, the proposed hybrid approach found a solution better than the previous SA...

A novel Monte Carlo approach to hybrid local volatility models

NARCIS (Netherlands)

A.W. van der Stoep (Anton); L.A. Grzelak (Lech Aleksander); C.W. Oosterlee (Cornelis)

2017-01-01

textabstractWe present in a Monte Carlo simulation framework, a novel approach for the evaluation of hybrid local volatility [Risk, 1994, 7, 18–20], [Int. J. Theor. Appl. Finance, 1998, 1, 61–110] models. In particular, we consider the stochastic local volatility model—see e.g. Lipton et al. [Quant.

A diagnostic expert system for NPP based on hybrid knowledge approach

International Nuclear Information System (INIS)

Yang, Joon On; Chang, Soon Heung

1989-01-01

This paper describes a diagnostic expert system, HYPOSS (Hybrid Knowledge Based Plant Operation Supporting System), which has been developed to support operators' decision making during the transients of nuclear power plant. HYPOSS adopts the hybrid knowledge approach which combines shallow and deep knowledge to couple the merits of both approaches. In HYPOSS, four types of knowledge are used according to the steps of diagnosis procedure: structural, functional, behavioral and heuristic knowledge. The structural and functional knowledge is represented by three fundamental primitives and five types of functions respectively. The behavioral knowledge is represented using constraints. The inference procedure is based on the human problem solving behavior modeled in HYPOSS. For the validation of HYPOSS, several tests have been performed based on the data produced by a plant simulator. The results of validation studies showed a good applicability of HYPOSS to the anomaly diagnosis of nuclear power plant

Hybrid simulation of reactor kinetics in CANDU reactors using a modal approach

International Nuclear Information System (INIS)

Monaghan, B.M.; McDonnell, F.N.; Hinds, H.W.T.; m.

1980-01-01

A hybrid computer model for simulating the behaviour of large CANDU (Canada Deuterium Uranium) reactor cores is presented. The main dynamic variables are expressed in terms of weighted sums of a base set of spatial natural-mode functions with time-varying co-efficients. This technique, known as the modal or synthesis approach, permits good three-dimensional representation of reactor dynamics and is well suited to hybrid simulation. The hybrid model provides improved man-machine interaction and real-time capability. The model was used in two applications. The first studies the transient that follows a loss of primary coolant and reactor shutdown; the second is a simulation of the dynamics of xenon, a fission product which has a high absorption cross-section for neutrons and thus has an important effect on reactor behaviour. Comparison of the results of the hybrid computer simulation with those of an all-digital one is good, within 1% to 2%

An Adaptive and Hybrid Approach for Revisiting the Visibility Pipeline

Directory of Open Access Journals (Sweden)

Ícaro Lins Leitão da Cunha

2016-04-01

Full Text Available We revisit the visibility problem, which is traditionally known in Computer Graphics and Vision fields as the process of computing a (potentially visible set of primitives in the computational model of a scene. We propose a hybrid solution that uses a dry structure (in the sense of data reduction, a triangulation of the type J1a, to accelerate the task of searching for visible primitives. We came up with a solution that is useful for real-time, on-line, interactive applications as 3D visualization. In such applications the main goal is to load the minimum amount of primitives from the scene during the rendering stage, as possible. For this purpose, our algorithm executes the culling by using a hybrid paradigm based on viewing-frustum, back-face culling and occlusion models. Results have shown substantial improvement over these traditional approaches if applied separately. This novel approach can be used in devices with no dedicated processors or with low processing power, as cell phones or embedded displays, or to visualize data through the Internet, as in virtual museums applications.

A Hybrid Analysis Approach to Improve Financial Distress Forecasting: Empirical Evidence from Iran

Directory of Open Access Journals (Sweden)

Shakiba Khademolqorani

2015-01-01

Full Text Available Bankruptcy prediction is an important problem facing financial decision support for stakeholders of firms, including auditors, managers, shareholders, debt-holders, and potential investors, as well as academic researchers. Popular discourse on financial distress forecasting focuses on developing the discrete models to improve the prediction. The aim of this paper is to develop a novel hybrid financial distress model based on combining various statistical and machine learning methods. Then multiple attribute decision making method is exploited to choose the optimized model from the implemented ones. Proposed approaches have also been applied in Iranian companies that performed previous models and it can be consolidated with the help of the hybrid approach.

A hybrid bio-jetting approach for directly engineering living cells

International Nuclear Information System (INIS)

Kwok, Albert; Irvine, Scott; Arumuganathar, Sumathy; Jayasinghe, Suwan N; McEwan, Jean R

2008-01-01

This paper reports developments on a hybrid cell-engineering protocol coupling both bio-electrosprays and aerodynamically assisted bio-jets for process-handling living cells. The current work demonstrates the ability to couple these two cell-jetting protocols for handling a wide range of cells for deposition. The post-treated cells are assessed for their viability by way of flow cytometry, which illustrates a significant population of viable cells post-treatment in comparison to those controls. This work is the first example of coupling these two protocols for the process handling of living cells. The hybrid protocol demonstrates the achievement of stable cone jetting of a cellular suspension in the single-needle configuration which was previously unachieved with single-needle bio-electrosprays. Furthermore the living cells explored in these investigations expressed GFP, thus demonstrating the ability to couple gene therapy with this hybrid protocol. Hence, this approach could one day be explored for building biologically viable tissues incorporating a therapeutic payload for combating a range of cellular/tissue-based pathologies

Stock selection using a hybrid MCDM approach

Directory of Open Access Journals (Sweden)

Tea Poklepović

2014-12-01

Full Text Available The problem of selecting the right stocks to invest in is of immense interest for investors on both emerging and developed capital markets. Moreover, an investor should take into account all available data regarding stocks on the particular market. This includes fundamental and stock market indicators. The decision making process includes several stocks to invest in and more than one criterion. Therefore, the task of selecting the stocks to invest in can be viewed as a multiple criteria decision making (MCDM problem. Using several MCDM methods often leads to divergent rankings. The goal of this paper is to resolve these possible divergent results obtained from different MCDM methods using a hybrid MCDM approach based on Spearman’s rank correlation coefficient. Five MCDM methods are selected: COPRAS, linear assignment, PROMETHEE, SAW and TOPSIS. The weights for all criteria are obtained by using the AHP method. Data for this study includes information on stock returns and traded volumes from March 2012 to March 2014 for 19 stocks on the Croatian capital market. It also includes the most important fundamental and stock market indicators for selected stocks. Rankings using five selected MCDM methods in the stock selection problem yield divergent results. However, after applying the proposed approach the final hybrid rankings are obtained. The results show that the worse stocks to invest in happen to be the same when the industry is taken into consideration or when not. However, when the industry is taken into account, the best stocks to invest in are slightly different, because some industries are more profitable than the others.

A hybrid approach to device integration on a genetic analysis platform

International Nuclear Information System (INIS)

Brennan, Des; Justice, John; Aherne, Margaret; Galvin, Paul; Jary, Dorothee; Kurg, Ants; Berik, Evgeny; Macek, Milan

2012-01-01

Point-of-care (POC) systems require significant component integration to implement biochemical protocols associated with molecular diagnostic assays. Hybrid platforms where discrete components are combined in a single platform are a suitable approach to integration, where combining multiple device fabrication steps on a single substrate is not possible due to incompatible or costly fabrication steps. We integrate three devices each with a specific system functionality: (i) a silicon electro-wetting-on-dielectric (EWOD) device to move and mix sample and reagent droplets in an oil phase, (ii) a polymer microfluidic chip containing channels and reservoirs and (iii) an aqueous phase glass microarray for fluorescence microarray hybridization detection. The EWOD device offers the possibility of fully integrating on-chip sample preparation using nanolitre sample and reagent volumes. A key challenge is sample transfer from the oil phase EWOD device to the aqueous phase microarray for hybridization detection. The EWOD device, waveguide performance and functionality are maintained during the integration process. An on-chip biochemical protocol for arrayed primer extension (APEX) was implemented for single nucleotide polymorphism (SNiP) analysis. The prepared sample is aspirated from the EWOD oil phase to the aqueous phase microarray for hybridization. A bench-top instrumentation system was also developed around the integrated platform to drive the EWOD electrodes, implement APEX sample heating and image the microarray after hybridization. (paper)

Neuro-genetic hybrid approach for the solution of non-convex economic dispatch problem

International Nuclear Information System (INIS)

Malik, T.N.; Asar, A.U.

2009-01-01

ED (Economic Dispatch) is non-convex constrained optimization problem, and is used for both on line and offline studies in power system operation. Conventionally, it is solved as convex problem using optimization techniques by approximating generator input/output characteristic. Curves of monotonically increasing nature thus resulting in an inaccurate dispatch. The GA (Genetic Algorithm) has been used for the solution of this problem owing to its inherent ability to address the convex and non-convex problems equally. This approach brings the solution to the global minimum region of search space in a short time and then takes longer time to converge to near optimal results. GA based hybrid approaches are used to fine tune the near optimal results produced by GA. This paper proposes NGH (Neuro Genetic Hybrid) approach to solve the economic dispatch with valve point effect. The proposed approach combines the GA with the ANN (Artificial Neural Network) using SI (Swarm Intelligence) learning rule. The GA acts as a global optimizer and the neural network fine tunes the GA results to the desired targets. Three machines standard test system has been tested for validation of the approach. Comparing the results with GA and NGH model based on back-propagation learning, the proposed approach gives contrast improvements showing the promise of the approach. (author)

Statistical comparison of a hybrid approach with approximate and exact inference models for Fusion 2+

Science.gov (United States)

Lee, K. David; Wiesenfeld, Eric; Gelfand, Andrew

2007-04-01

One of the greatest challenges in modern combat is maintaining a high level of timely Situational Awareness (SA). In many situations, computational complexity and accuracy considerations make the development and deployment of real-time, high-level inference tools very difficult. An innovative hybrid framework that combines Bayesian inference, in the form of Bayesian Networks, and Possibility Theory, in the form of Fuzzy Logic systems, has recently been introduced to provide a rigorous framework for high-level inference. In previous research, the theoretical basis and benefits of the hybrid approach have been developed. However, lacking is a concrete experimental comparison of the hybrid framework with traditional fusion methods, to demonstrate and quantify this benefit. The goal of this research, therefore, is to provide a statistical analysis on the comparison of the accuracy and performance of hybrid network theory, with pure Bayesian and Fuzzy systems and an inexact Bayesian system approximated using Particle Filtering. To accomplish this task, domain specific models will be developed under these different theoretical approaches and then evaluated, via Monte Carlo Simulation, in comparison to situational ground truth to measure accuracy and fidelity. Following this, a rigorous statistical analysis of the performance results will be performed, to quantify the benefit of hybrid inference to other fusion tools.

Emergence of Life on Earth: A Physicochemical Jigsaw Puzzle.

Science.gov (United States)

Spitzer, Jan

2017-01-01

We review physicochemical factors and processes that describe how cellular life can emerge from prebiotic chemical matter; they are: (1) prebiotic Earth is a multicomponent and multiphase reservoir of chemical compounds, to which (2) Earth-Moon rotations deliver two kinds of regular cycling energies: diurnal electromagnetic radiation and seawater tides. (3) Emerging colloidal phases cyclically nucleate and agglomerate in seawater and consolidate as geochemical sediments in tidal zones, creating a matrix of microspaces. (4) Some microspaces persist and retain memory from past cycles, and others re-dissolve and re-disperse back into the Earth's chemical reservoir. (5) Proto-metabolites and proto-biopolymers coevolve with and within persisting microspaces, where (6) Macromolecular crowding and other non-covalent molecular forces govern the evolution of hydrophilic, hydrophobic, and charged molecular surfaces. (7) The matrices of microspaces evolve into proto-biofilms of progenotes with rudimentary but evolving replication, transcription, and translation, enclosed in unstable cell envelopes. (8) Stabilization of cell envelopes 'crystallizes' bacteria-like genetics and metabolism with low horizontal gene transfer-life 'as we know it.' These factors and processes constitute the 'working pieces' of the jigsaw puzzle of life's emergence. They extend the concept of progenotes as the first proto-cellular life, connected backward in time to the cycling chemistries of the Earth-Moon planetary system, and forward to the ancient cell cycle of first bacteria-like organisms. Supra-macromolecular models of 'compartments first' are preferred: they facilitate macromolecular crowding-a key abiotic/biotic transition toward living states. Evolutionary models of metabolism or genetics 'first' could not have evolved in unconfined and uncrowded environments because of the diffusional drift to disorder mandated by the second law of thermodynamics.

A Hybrid Genetic Algorithm Approach for Optimal Power Flow

Directory of Open Access Journals (Sweden)

Sydulu Maheswarapu

2011-08-01

Full Text Available This paper puts forward a reformed hybrid genetic algorithm (GA based approach to the optimal power flow. In the approach followed here, continuous variables are designed using real-coded GA and discrete variables are processed as binary strings. The outcomes are compared with many other methods like simple genetic algorithm (GA, adaptive genetic algorithm (AGA, differential evolution (DE, particle swarm optimization (PSO and music based harmony search (MBHS on a IEEE30 bus test bed, with a total load of 283.4 MW. Its found that the proposed algorithm is found to offer lowest fuel cost. The proposed method is found to be computationally faster, robust, superior and promising form its convergence characteristics.

A Hybrid approach for aeroacoustic analysis of the engine exhaust system

OpenAIRE

Sathyanarayana, Y; Munjal, ML

2000-01-01

This paper presents a new hybrid approach for prediction of noise radiation from engine exhaust systems. It couples the time domain analysis of the engine and the frequency domain analysis of the muffler, and has the advantages of both. In this approach, cylinder/cavity is analyzed in the time domain to calculate the exhaust mass flux history at the exhaust valve by means of the method of characteristics, avoiding the tedious procedure of interpolation at every mesh point and solving a number...

The business case for condition-based maintenance: a hybrid (non-) financial approach

NARCIS (Netherlands)

Tiddens, W.W.; Tinga, T.; Braaksma, A.J.J.; Brouwer, O.; Cepin, Marko; Bris, Radim

2017-01-01

Although developing business cases is key for evaluating project success, the costs and benefits of condition-based maintenance (CBM) implementations are often not explicitly defined and evaluated. Using the design science methodology, we developed a hybrid business case approach to help managers

A Hybrid PCA-CART-MARS-Based Prognostic Approach of the Remaining Useful Life for Aircraft Engines

Directory of Open Access Journals (Sweden)

Fernando Sánchez Lasheras

2015-03-01

Full Text Available Prognostics is an engineering discipline that predicts the future health of a system. In this research work, a data-driven approach for prognostics is proposed. Indeed, the present paper describes a data-driven hybrid model for the successful prediction of the remaining useful life of aircraft engines. The approach combines the multivariate adaptive regression splines (MARS technique with the principal component analysis (PCA, dendrograms and classification and regression trees (CARTs. Elements extracted from sensor signals are used to train this hybrid model, representing different levels of health for aircraft engines. In this way, this hybrid algorithm is used to predict the trends of these elements. Based on this fitting, one can determine the future health state of a system and estimate its remaining useful life (RUL with accuracy. To evaluate the proposed approach, a test was carried out using aircraft engine signals collected from physical sensors (temperature, pressure, speed, fuel flow, etc.. Simulation results show that the PCA-CART-MARS-based approach can forecast faults long before they occur and can predict the RUL. The proposed hybrid model presents as its main advantage the fact that it does not require information about the previous operation states of the input variables of the engine. The performance of this model was compared with those obtained by other benchmark models (multivariate linear regression and artificial neural networks also applied in recent years for the modeling of remaining useful life. Therefore, the PCA-CART-MARS-based approach is very promising in the field of prognostics of the RUL for aircraft engines.

Fuzzy hybrid MCDM approach for selection of wind turbine service technicians

Directory of Open Access Journals (Sweden)

Goutam Kumar Bose

2016-01-01

Full Text Available This research paper is aimed to present a fuzzy Hybrid Multi-criteria decision making (MCDM methodology for selecting employees. The present study aspires to present the hybrid approach of Fuzzy multiple MCDM techniques with tactical viewpoint to support the recruitment process of wind turbine service technicians. The methodology is based on the application of Fuzzy ARAS (Additive Ratio Assessment and Fuzzy MOORA (Multi-Objective Optimization on basis of Ratio Analysis which are integrated through group decision making (GDM method in the model for selection of wind turbine service technicians’ ranking. Here a group of experts from different fields of expertise are engaged to finalize the decision. Series of tests are conducted regarding physical fitness, technical written test, practical test along with general interview and medical examination to facilitate the final selection using the above techniques. In contrast to single decision making approaches, the proposed group decision making model efficiently supports the wind turbine service technicians ranking process. The effectiveness of the proposed approach manifest from the case study of service technicians required for the maintenance department of wind power plant using Fuzzy ARAS and Fuzzy MOORA. This set of potential technicians is evaluated based on five main criteria.

A decision support system based on hybrid knowledge approach for nuclear power plant operation

International Nuclear Information System (INIS)

Yang, J.O.; Chang, S.H.

1991-01-01

This paper describes a diagnostic expert system, HYPOSS (Hybrid Knowledge Based Plant Operation Supporting System), which has been developed to support operators' decision making during the transients of nuclear power plant. HYPOSS adopts the hybrid knowledge approach which combines shallow and deep knowledge to couple the merits of both approaches. In HYPOSS, four types of knowledge are used according to the steps of diagnosis procedure: structural, functional, behavioral and heuristic knowledge. Frames and rules are adopted to represent the various knowledge types. Rule-based deduction and abduction are used for shallow and deep knowledge based reasoning respectively. The event-based operational guidelines are provided to the operator according to the diagnosed results

A Hybrid Approach to Processing Big Data Graphs on Memory-Restricted Systems

KAUST Repository

Harshvardhan,; West, Brandon; Fidel, Adam; Amato, Nancy M.; Rauchwerger, Lawrence

2015-01-01

that sacrifice performance. In this work, we propose a novel RAM-Disk hybrid approach to graph processing that can scale well from a single shared-memory node to large distributed-memory systems. It works by partitioning the graph into sub graphs that fit in RAM

Mixed H∞ and passive control for linear switched systems via hybrid control approach

Science.gov (United States)

Zheng, Qunxian; Ling, Youzhu; Wei, Lisheng; Zhang, Hongbin

2018-03-01

This paper investigates the mixed H∞ and passive control problem for linear switched systems based on a hybrid control strategy. To solve this problem, first, a new performance index is proposed. This performance index can be viewed as the mixed weighted H∞ and passivity performance. Then, the hybrid controllers are used to stabilise the switched systems. The hybrid controllers consist of dynamic output-feedback controllers for every subsystem and state updating controllers at the switching instant. The design of state updating controllers not only depends on the pre-switching subsystem and the post-switching subsystem, but also depends on the measurable output signal. The hybrid controllers proposed in this paper can include some existing ones as special cases. Combine the multiple Lyapunov functions approach with the average dwell time technique, new sufficient conditions are obtained. Under the new conditions, the closed-loop linear switched systems are globally uniformly asymptotically stable with a mixed H∞ and passivity performance index. Moreover, the desired hybrid controllers can be constructed by solving a set of linear matrix inequalities. Finally, a numerical example and a practical example are given.

A Hybrid Soft Computing Approach for Subset Problems

Directory of Open Access Journals (Sweden)

Broderick Crawford

2013-01-01

Full Text Available Subset problems (set partitioning, packing, and covering are formal models for many practical optimization problems. A set partitioning problem determines how the items in one set (S can be partitioned into smaller subsets. All items in S must be contained in one and only one partition. Related problems are set packing (all items must be contained in zero or one partitions and set covering (all items must be contained in at least one partition. Here, we present a hybrid solver based on ant colony optimization (ACO combined with arc consistency for solving this kind of problems. ACO is a swarm intelligence metaheuristic inspired on ants behavior when they search for food. It allows to solve complex combinatorial problems for which traditional mathematical techniques may fail. By other side, in constraint programming, the solving process of Constraint Satisfaction Problems can dramatically reduce the search space by means of arc consistency enforcing constraint consistencies either prior to or during search. Our hybrid approach was tested with set covering and set partitioning dataset benchmarks. It was observed that the performance of ACO had been improved embedding this filtering technique in its constructive phase.

A hybrid personalized data recommendation approach for geoscience data sharing

Science.gov (United States)

WANG, M.; Wang, J.

2016-12-01

Recommender systems are effective tools helping Internet users overcome information overloading. The two most widely used recommendation algorithms are collaborating filtering (CF) and content-based filtering (CBF). A number of recommender systems based on those two algorithms were developed for multimedia, online sells, and other domains. Each of the two algorithms has its advantages and shortcomings. Hybrid approaches that combine these two algorithms are better choices in many cases. In geoscience data sharing domain, where the items (datasets) are more informative (in space and time) and domain-specific, no recommender system is specialized for data users. This paper reports a dynamic weighted hybrid recommendation algorithm that combines CF and CBF for geoscience data sharing portal. We first derive users' ratings on items with their historical visiting time by Jenks Natural Break. In the CBF part, we incorporate the space, time, and subject information of geoscience datasets to compute item similarity. Predicted ratings were computed with k-NN method separately using CBF and CF, and then combined with weights. With training dataset we attempted to find the best model describing ideal weights and users' co-rating numbers. A logarithmic function was confirmed to be the best model. The model was then used to tune the weights of CF and CBF on user-item basis with test dataset. Evaluation results show that the dynamic weighted approach outperforms either solo CF or CBF approach in terms of Precision and Recall.

A Novel Combined Hybrid Approach to Enable Revascularisation of a Trauma-Induced Subclavian Artery Injury

Directory of Open Access Journals (Sweden)

C.N. Sabbagh

Full Text Available : Introduction: This case highlights the complexity of upper limb revascularization after a subclavian artery traumatic injury and strengthens the role of a hybrid/multi-disciplinary approach to such injuries. Report: A 45-year-old male patient presented with an acute right upper limb following a traumatic injury to the right subclavian artery due to a motor vehicle accident (MVA. Associated injuries included an unstable cervical spine injury, a large open right clavicular injury, and a brain injury, which limited the potential revascularisation options available. The arm was revascularised using a hybrid endovascular/open surgical approach, namely embolization of the proximal subclavian artery (just distal to vertebral artery and a right common femoral artery to distal axillary artery bypass using prosthetic material. Discussion: Blunt injuries to the subclavian artery are often high impact, complex and associated with multiple injuries to surrounding structures, which limit the role of standard procedures used in the elective setting. This case highlights the role of multidisciplinary team involvement, using a hybrid approach and a novel distal inflow site to restore upper limb perfusion. Keywords: Upper limb, Ischemia, Trauma, Revascularization

Hybrid modeling approach to improve the forecasting capability for the gaseous radionuclide in a nuclear site

International Nuclear Information System (INIS)

Jeong, Hyojoon; Hwang, Wontae; Kim, Eunhan; Han, Moonhee

2012-01-01

Highlights: ► This study is to improve the reliability of air dispersion modeling. ► Tracer experiments assumed gaseous radionuclides were conducted at a nuclear site. ► The performance of a hybrid modeling combined ISC with ANFIS was investigated.. ► Hybrid modeling approach shows better performance rather than a single ISC model. - Abstract: Predicted air concentrations of radioactive materials are important for an environmental impact assessment for the public health. In this study, the performance of a hybrid modeling combined with the industrial source complex (ISC) model and an adaptive neuro-fuzzy inference system (ANFIS) for predicting tracer concentrations was investigated. Tracer dispersion experiments were performed to produce the field data assuming the accidental release of radioactive material. ANFIS was trained in order that the outputs of the ISC model are similar to the measured data. Judging from the higher correlation coefficients between the measured and the calculated ones, the hybrid modeling approach could be an appropriate technique for an improvement of the modeling capability to predict the air concentrations for radioactive materials.

A bottom-up approach for the synthesis of highly ordered fullerene-intercalated graphene hybrids

Directory of Open Access Journals (Sweden)

Dimitrios eGournis

2015-02-01

Full Text Available Much of the research effort on graphene focuses on its use as a building block for the development of new hybrid nanostructures with well-defined dimensions and properties suitable for applications such as gas storage, heterogeneous catalysis, gas/liquid separations, nanosensing and biomedicine. Towards this aim, here we describe a new bottom-up approach, which combines self-assembly with the Langmuir Schaefer deposition technique to synthesize graphene-based layered hybrid materials hosting fullerene molecules within the interlayer space. Our film preparation consists in a bottom-up layer-by-layer process that proceeds via the formation of a hybrid organo-graphene oxide Langmuir film. The structure and composition of these hybrid fullerene-containing thin multilayers deposited on hydrophobic substrates were characterized by a combination of X-ray diffraction, Raman and X-ray photoelectron spectroscopies, atomic force microscopy and conductivity measurements. The latter revealed that the presence of C60 within the interlayer spacing leads to an increase in electrical conductivity of the hybrid material as compared to the organo-graphene matrix alone.

Non-adaptive and adaptive hybrid approaches for enhancing water quality management

Science.gov (United States)

Kalwij, Ineke M.; Peralta, Richard C.

2008-09-01

SummaryUsing optimization to help solve groundwater management problems cost-effectively is becoming increasingly important. Hybrid optimization approaches, that combine two or more optimization algorithms, will become valuable and common tools for addressing complex nonlinear hydrologic problems. Hybrid heuristic optimizers have capabilities far beyond those of a simple genetic algorithm (SGA), and are continuously improving. SGAs having only parent selection, crossover, and mutation are inefficient and rarely used for optimizing contaminant transport management. Even an advanced genetic algorithm (AGA) that includes elitism (to emphasize using the best strategies as parents) and healing (to help assure optimal strategy feasibility) is undesirably inefficient. Much more efficient than an AGA is the presented hybrid (AGCT), which adds comprehensive tabu search (TS) features to an AGA. TS mechanisms (TS probability, tabu list size, search coarseness and solution space size, and a TS threshold value) force the optimizer to search portions of the solution space that yield superior pumping strategies, and to avoid reproducing similar or inferior strategies. An AGCT characteristic is that TS control parameters are unchanging during optimization. However, TS parameter values that are ideal for optimization commencement can be undesirable when nearing assumed global optimality. The second presented hybrid, termed global converger (GC), is significantly better than the AGCT. GC includes AGCT plus feedback-driven auto-adaptive control that dynamically changes TS parameters during run-time. Before comparing AGCT and GC, we empirically derived scaled dimensionless TS control parameter guidelines by evaluating 50 sets of parameter values for a hypothetical optimization problem. For the hypothetical area, AGCT optimized both well locations and pumping rates. The parameters are useful starting values because using trial-and-error to identify an ideal combination of control

Approaches to Low Fuel Regression Rate in Hybrid Rocket Engines

Directory of Open Access Journals (Sweden)

Dario Pastrone

2012-01-01

Full Text Available Hybrid rocket engines are promising propulsion systems which present appealing features such as safety, low cost, and environmental friendliness. On the other hand, certain issues hamper the development hoped for. The present paper discusses approaches addressing improvements to one of the most important among these issues: low fuel regression rate. To highlight the consequence of such an issue and to better understand the concepts proposed, fundamentals are summarized. Two approaches are presented (multiport grain and high mixture ratio which aim at reducing negative effects without enhancing regression rate. Furthermore, fuel material changes and nonconventional geometries of grain and/or injector are presented as methods to increase fuel regression rate. Although most of these approaches are still at the laboratory or concept scale, many of them are promising.

A New Hybrid Approach for Wind Speed Prediction Using Fast Block Least Mean Square Algorithm and Artificial Neural Network

Directory of Open Access Journals (Sweden)

Ummuhan Basaran Filik

2016-01-01

Full Text Available A new hybrid wind speed prediction approach, which uses fast block least mean square (FBLMS algorithm and artificial neural network (ANN method, is proposed. FBLMS is an adaptive algorithm which has reduced complexity with a very fast convergence rate. A hybrid approach is proposed which uses two powerful methods: FBLMS and ANN method. In order to show the efficiency and accuracy of the proposed approach, seven-year real hourly collected wind speed data sets belonging to Turkish State Meteorological Service of Bozcaada and Eskisehir regions are used. Two different ANN structures are used to compare with this approach. The first six-year data is handled as a train set; the remaining one-year hourly data is handled as test data. Mean absolute error (MAE and root mean square error (RMSE are used for performance evaluations. It is shown for various cases that the performance of the new hybrid approach gives better results than the different conventional ANN structure.

Control and fault diagnosis based sliding mode observer of a multicellular converter: Hybrid approach

KAUST Repository

Benzineb, Omar

2013-01-01

In this article, the diagnosis of a three cell converter is developed. The hybrid nature of the system represented by the presence of continuous and discrete dynamics is taken into account in the control design. The idea is based on using a hybrid control and an observer-type sliding mode to generate residuals from the observation errors of the system. The simulation results are presented at the end to illustrate the performance of the proposed approach. © 2013 FEI STU.

A hybrid data compression approach for online backup service

Science.gov (United States)

Wang, Hua; Zhou, Ke; Qin, MingKang

2009-08-01

With the popularity of Saas (Software as a service), backup service has becoming a hot topic of storage application. Due to the numerous backup users, how to reduce the massive data load is a key problem for system designer. Data compression provides a good solution. Traditional data compression application used to adopt a single method, which has limitations in some respects. For example data stream compression can only realize intra-file compression, de-duplication is used to eliminate inter-file redundant data, compression efficiency cannot meet the need of backup service software. This paper proposes a novel hybrid compression approach, which includes two levels: global compression and block compression. The former can eliminate redundant inter-file copies across different users, the latter adopts data stream compression technology to realize intra-file de-duplication. Several compressing algorithms were adopted to measure the compression ratio and CPU time. Adaptability using different algorithm in certain situation is also analyzed. The performance analysis shows that great improvement is made through the hybrid compression policy.

Evaluation of wind power generation potential using a three hybrid approach for households in Ardebil Province, Iran

International Nuclear Information System (INIS)

Qolipour, Mojtaba; Mostafaeipour, Ali; Shamshirband, Shahaboddin; Alavi, Omid; Goudarzi, Hossein; Petković, Dalibor

2016-01-01

Highlights: • Technical–economic feasibility of small wind turbines for six areas in Ardabil province of Iran was investigated. • Hybrid approach of Data Envelopment Analysis, Balanced Scorecard, and Game Theory was analyzed. • HOMER software was used for economic evaluation. • Technical–economic feasibility was studied using wind speed data during 2008–2014. • The areas of Airport, Nir, Namin, BilaSavar, Firozabad and Ardabil were ranked from first to last, respectively. - Abstract: The objective of the present paper is to conduct a thorough technical–economic evaluation for the construction of small wind turbines in six areas within Ardabil province of Iran using the Hybrid Optimization of Multiple Energy Resources software, and also to rank these areas by a hybrid approach composed of Data Envelopment Analysis, Balanced Scorecard, and Game Theory methodologies. Higher accuracy of the proposed hybrid approach and its ability to properly detect the relationships between the decision-making components make it preferable over the simple Data Envelopment Analysis method. Technical–economic feasibility study is conducted by analyzing wind speed data for period from 2008 to 2014 using Hybrid Optimization of Multiple Energy Resources software. In the next step, the type of equipment used in the design, benefit, costs, total net costs, depreciation and amount of generated electricity are obtained separately for each location. The results show that; Airport, Nir, Namin, Bilasavar, Firozabad and Ardabil were rank first to last respectively.

A hybrid life cycle and multi-criteria decision analysis approach for identifying sustainable development strategies of Beijing's taxi fleet

International Nuclear Information System (INIS)

Cai, Yanpeng; Applegate, Scott; Yue, Wencong; Cai, Jianying; Wang, Xuan; Liu, Gengyuan; Li, Chunhui

2017-01-01

To identify and evaluate sustainable strategies of taxi fleet in Beijing in terms of economic, policy, and environmental implications, a hybrid approach was developed through incorporating multi-criteria decision analysis (MCDA) methods within a general life-cycle analysis (LCA) framework. The approach can (a) help comprehensive evaluate environmental impacts of multiple types of vehicles, (b) facilitate analysis of environmental, economic and policy features of such vehicles, and (c) identify desirable taxi fleet development strategies for the city. The developed approach represented an improvement of the decision-making capability for taxi implementation based on multiple available technologies and their performance that can be specifically tailored to Beijing. The results demonstrated that the proposed approach could comprehensively reflect multiple implications of strategies for the taxi fleet in Beijing to reduce air pollution in the city. The results also indicated that the electric vehicle powered with the year 2020 electricity projections would be the ideal solution, outranking the other alternatives. The conventional vehicle ranked the lowest among the alternatives. The plug-in hybrid vehicle powered by 2020 electricity projects ranked the third, followed by the plug-in hybrid vehicle ranking the fourth, and the hybrid vehicle ranking the fifth. - Highlights: • An hybrid approach was proposed for evaluating sustainable strategies of Beijing's taxi fleet. • This approach was based on the combination of multi-criteria decision analysis methods and life-cycle assessment. • Environmental, economic and policy performances of multiple strategies were compared. • Detailed responses of taxi drivers and local residents were interviewed. • The electric vehicle would be the ideal solution for Beijing Taxi fleet.

A Gaussian process regression based hybrid approach for short-term wind speed prediction

International Nuclear Information System (INIS)

Zhang, Chi; Wei, Haikun; Zhao, Xin; Liu, Tianhong; Zhang, Kanjian

2016-01-01

Highlights: • A novel hybrid approach is proposed for short-term wind speed prediction. • This method combines the parametric AR model with the non-parametric GPR model. • The relative importance of different inputs is considered. • Different types of covariance functions are considered and combined. • It can provide both accurate point forecasts and satisfactory prediction intervals. - Abstract: This paper proposes a hybrid model based on autoregressive (AR) model and Gaussian process regression (GPR) for probabilistic wind speed forecasting. In the proposed approach, the AR model is employed to capture the overall structure from wind speed series, and the GPR is adopted to extract the local structure. Additionally, automatic relevance determination (ARD) is used to take into account the relative importance of different inputs, and different types of covariance functions are combined to capture the characteristics of the data. The proposed hybrid model is compared with the persistence model, artificial neural network (ANN), and support vector machine (SVM) for one-step ahead forecasting, using wind speed data collected from three wind farms in China. The forecasting results indicate that the proposed method can not only improve point forecasts compared with other methods, but also generate satisfactory prediction intervals.

Heuristic hybrid game approach for fleet condition-based maintenance planning

International Nuclear Information System (INIS)

Feng, Qiang; Bi, Xiong; Zhao, Xiujie; Chen, Yiran; Sun, Bo

2017-01-01

The condition-based maintenance (CBM) method is commonly used to select appropriate maintenance opportunities according to equipment status over a period of time. The CBM of aircraft fleets is a fleet maintenance planning problem. In this problem, mission requirements, resource constraints, and aircraft statuses are considered to find an optimal strategy set. Given that the maintenance strategies for each aircraft are finite, fleet CBM can be treated as a combinatorial optimization problem. In this study, the process of making a decision on the CBM of military fleets is analyzed. The fleet CBM problem is treated as a two-stage dynamic decision-making problem. Aircraft are divided into dispatch and standby sets; thus, the problem scale is significantly reduced. A heuristic hybrid game (HHG) approach comprising a competition game and a cooperative game is proposed on the basis of heuristic rule. In the dispatch set, a competition game approach is proposed to search for a local optimal strategy matrix. A cooperative game method for the two sets is also proposed to ensure global optimization. Finally, a case study regarding a fleet comprising 20 aircraft is conducted, with the results proving that the approach efficiently generates outcomes that meet the mission risk-oriented schedule requirement. - Highlights: • A new heuristic hybrid game method for fleet condition-based maintenance is proposed. • The problem is simplified by hierarchical solving based on dispatch and standby set. • The local optimal solution is got by competition game algorithm for dispatch set. • The global optimal solution is got by cooperative game algorithm between two sets.

Super-resolution nanofabrication with metal-ion doped hybrid material through an optical dual-beam approach

International Nuclear Information System (INIS)

Cao, Yaoyu; Li, Xiangping; Gu, Min

2014-01-01

We apply an optical dual-beam approach to a metal-ion doped hybrid material to achieve nanofeatures beyond the optical diffraction limit. By spatially inhibiting the photoreduction and the photopolymerization, we realize a nano-line, consisting of polymer matrix and in-situ generated gold nanoparticles, with a lateral size of sub 100 nm, corresponding to a factor of 7 improvement compared to the diffraction limit. With the existence of gold nanoparticles, a plasmon enhanced super-resolution fabrication mechanism in the hybrid material is observed, which benefits in a further reduction in size of the fabricated feature. The demonstrated nanofeature in hybrid materials paves the way for realizing functional nanostructures

Modelling biochemical networks with intrinsic time delays: a hybrid semi-parametric approach

Directory of Open Access Journals (Sweden)

Oliveira Rui

2010-09-01

Full Text Available Abstract Background This paper presents a method for modelling dynamical biochemical networks with intrinsic time delays. Since the fundamental mechanisms leading to such delays are many times unknown, non conventional modelling approaches become necessary. Herein, a hybrid semi-parametric identification methodology is proposed in which discrete time series are incorporated into fundamental material balance models. This integration results in hybrid delay differential equations which can be applied to identify unknown cellular dynamics. Results The proposed hybrid modelling methodology was evaluated using two case studies. The first of these deals with dynamic modelling of transcriptional factor A in mammalian cells. The protein transport from the cytosol to the nucleus introduced a delay that was accounted for by discrete time series formulation. The second case study focused on a simple network with distributed time delays that demonstrated that the discrete time delay formalism has broad applicability to both discrete and distributed delay problems. Conclusions Significantly better prediction qualities of the novel hybrid model were obtained when compared to dynamical structures without time delays, being the more distinctive the more significant the underlying system delay is. The identification of the system delays by studies of different discrete modelling delays was enabled by the proposed structure. Further, it was shown that the hybrid discrete delay methodology is not limited to discrete delay systems. The proposed method is a powerful tool to identify time delays in ill-defined biochemical networks.

A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal

International Nuclear Information System (INIS)

Pousinho, H.M.I.; Mendes, V.M.F.; Catalao, J.P.S.

2011-01-01

The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Wind power prediction plays a key role in tackling these challenges. The contribution of this paper is to propose a new hybrid approach, combining particle swarm optimization and adaptive-network-based fuzzy inference system, for short-term wind power prediction in Portugal. Significant improvements regarding forecasting accuracy are attainable using the proposed approach, in comparison with the results obtained with five other approaches.

Dual-acting of Hybrid Compounds - A New Dawn in the Discovery of Multi-target Drugs: Lead Generation Approaches.

Science.gov (United States)

Abdolmaleki, Azizeh; Ghasemi, Jahan B

2017-01-01

Finding high quality beginning compounds is a critical job at the start of the lead generation stage for multi-target drug discovery (MTDD). Designing hybrid compounds as selective multitarget chemical entity is a challenge, opportunity, and new idea to better act against specific multiple targets. One hybrid molecule is formed by two (or more) pharmacophore group's participation. So, these new compounds often exhibit two or more activities going about as multi-target drugs (mtdrugs) and may have superior safety or efficacy. Application of integrating a range of information and sophisticated new in silico, bioinformatics, structural biology, pharmacogenomics methods may be useful to discover/design, and synthesis of the new hybrid molecules. In this regard, many rational and screening approaches have followed by medicinal chemists for the lead generation in MTDD. Here, we review some popular lead generation approaches that have been used for designing multiple ligands (DMLs). This paper focuses on dual- acting chemical entities that incorporate a part of two drugs or bioactive compounds to compose hybrid molecules. Also, it presents some of key concepts and limitations/strengths of lead generation methods by comparing combination framework method with screening approaches. Besides, a number of examples to represent applications of hybrid molecules in the drug discovery are included. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Molecular and morphological approaches for species delimitation and hybridization investigations of two Cichla species

Directory of Open Access Journals (Sweden)

Andrea A. F. Mourão

Full Text Available ABSTRACT The hybridization is a widely-discussed issue in several studies with fish species. For some authors, hybridization may be related with diversification and speciation of several groups, or also with the extinction of populations or species. Difficulties to differentiate species and hybrids may be a problem to correctly apply a management of wild species, because hybrid lineages, especially the advanced ones, may resemble the parental species. The genus Cichla Bloch & Schneider, 1801 constitutes an interesting experimental model, considering that hybridization and taxonomic uncertainties hinder a correct identification. Considering these problems, in this study, we developed genetic methodologies and applied meristic and morphometric approaches in wild samples in order to identify species and for test a possible hybridization between Cichla kelberi Kullander & Ferreira, 2006 and Cichla piquiti Kullander & Ferreira, 2006. For this, C. kelberi, C. piquiti and potential hybrid ( carijó individuals were collected in Paraná and Tietê rivers (SP, Brazil. For meristic and morphometric methods, the individuals were analyzed using the statistical software Pcord 5:31, while for molecular methods, primers for PCR-multiplex were designed and enzyme for PCR-RFLP were selected, under the species-specific nucleotide. All results indicated that the carijó is not an interspecific hybrid, because it presented identical genetic pattern and morphology closed to C. piquiti. Thus, we propose that carijó is a C. piquiti morphotype. In addition, this study promotes a new molecular tool that could be used in future research, monitoring and management programs of the genus Cichla.

A hybrid approach to automatic de-identification of psychiatric notes.

Science.gov (United States)

Lee, Hee-Jin; Wu, Yonghui; Zhang, Yaoyun; Xu, Jun; Xu, Hua; Roberts, Kirk

2017-11-01

De-identification, or identifying and removing protected health information (PHI) from clinical data, is a critical step in making clinical data available for clinical applications and research. This paper presents a natural language processing system for automatic de-identification of psychiatric notes, which was designed to participate in the 2016 CEGS N-GRID shared task Track 1. The system has a hybrid structure that combines machine leaning techniques and rule-based approaches. The rule-based components exploit the structure of the psychiatric notes as well as characteristic surface patterns of PHI mentions. The machine learning components utilize supervised learning with rich features. In addition, the system performance was boosted with integration of additional data to the training set through domain adaptation. The hybrid system showed overall micro-averaged F-score 90.74 on the test set, second-best among all the participants of the CEGS N-GRID task. Copyright © 2017. Published by Elsevier Inc.

A hybrid approach for efficient anomaly detection using metaheuristic methods

Directory of Open Access Journals (Sweden)

Tamer F. Ghanem

2015-07-01

Full Text Available Network intrusion detection based on anomaly detection techniques has a significant role in protecting networks and systems against harmful activities. Different metaheuristic techniques have been used for anomaly detector generation. Yet, reported literature has not studied the use of the multi-start metaheuristic method for detector generation. This paper proposes a hybrid approach for anomaly detection in large scale datasets using detectors generated based on multi-start metaheuristic method and genetic algorithms. The proposed approach has taken some inspiration of negative selection-based detector generation. The evaluation of this approach is performed using NSL-KDD dataset which is a modified version of the widely used KDD CUP 99 dataset. The results show its effectiveness in generating a suitable number of detectors with an accuracy of 96.1% compared to other competitors of machine learning algorithms.

TwitterNEED: a hybrid approach for named entity extraction and disambiguation for tweets

NARCIS (Netherlands)

Habib, Mena Badieh; van Keulen, Maurice

Twitter is a rich source of continuously and instantly updated information. Shortness and informality of tweets are challenges for Natural Language Processing tasks. In this paper, we present TwitterNEED, a hybrid approach for Named Entity Extraction and Named Entity Disambiguation for tweets. We

Hybrid Neural Network Approach Based Tool for the Modelling of Photovoltaic Panels

Directory of Open Access Journals (Sweden)

Antonino Laudani

2015-01-01

Full Text Available A hybrid neural network approach based tool for identifying the photovoltaic one-diode model is presented. The generalization capabilities of neural networks are used together with the robustness of the reduced form of one-diode model. Indeed, from the studies performed by the authors and the works present in the literature, it was found that a direct computation of the five parameters via multiple inputs and multiple outputs neural network is a very difficult task. The reduced form consists in a series of explicit formulae for the support to the neural network that, in our case, is aimed at predicting just two parameters among the five ones identifying the model: the other three parameters are computed by reduced form. The present hybrid approach is efficient from the computational cost point of view and accurate in the estimation of the five parameters. It constitutes a complete and extremely easy tool suitable to be implemented in a microcontroller based architecture. Validations are made on about 10000 PV panels belonging to the California Energy Commission database.

Output Tracking Control of Switched Hybrid Systems: A Fliess Functional Expansion Approach

Directory of Open Access Journals (Sweden)

Fenghua He

2013-01-01

Full Text Available The output tracking problem is investigated for a nonlinear affine system with multiple modes of continuous control inputs. We convert the family of nonlinear affine systems under consideration into a switched hybrid system by introducing a multiple-valued logic variable. The Fliess functional expansion is adopted to express the input and output relationship of the switched hybrid system. The optimal switching control is determined for a multiple-step output tracking performance index. The proposed approach is applied to a multitarget tracking problem for a flight vehicle aiming for one real target with several decoys flying around it in the terminal guidance course. These decoys appear as apparent targets and have to be distinguished with the approaching of the flight vehicle. The guidance problem of one flight vehicle versus multiple apparent targets should be considered if no large miss distance might be caused due to the limitation of the flight vehicle maneuverability. The target orientation at each time interval is determined. Simulation results show the effectiveness of the proposed method.

An Odometry-free Approach for Simultaneous Localization and Online Hybrid Map Building

Directory of Open Access Journals (Sweden)

Wei Hong Chin

2016-11-01

Full Text Available In this paper, a new approach is proposed for mobile robot localization and hybrid map building simultaneously without using any odometry hardware system. The proposed method termed as Genetic Bayesian ARAM which comprises two main components: 1 Steady state genetic algorithm (SSGA for self-localization and occupancy grid map building; 2 Bayesian Adaptive Resonance Associative Memory (ARAM for online topological map building. The model of the explored environment is formed as a hybrid representation, both topological and grid-based, and it is incrementally constructed during the exploration process. During occupancy map building, robot estimated self-position is updated by SSGA. At the same time, robot estimated self position is transmit to Bayesian ARAM for topological map building and localization. The effectiveness of our proposed approach is validated by a number of standardized benchmark datasets and real experimental results carried on mobile robot. Benchmark datasets are used to verify the proposed method capable of generating topological map in different environment conditions. Real robot experiment is to verify the proposed method can be implemented in real world.

Hybrid Approach of Aortic Diseases: Zone 1 Delivery and Volumetric Analysis on the Descending Aorta

Directory of Open Access Journals (Sweden)

José Augusto Duncan

Full Text Available Abstract Introduction: Conventional techniques of surgical correction of arch and descending aortic diseases remains as high-risk procedures. Endovascular treatments of abdominal and descending thoracic aorta have lower surgical risk. Evolution of both techniques - open debranching of the arch and endovascular approach of the descending aorta - may extend a less invasive endovascular treatment for a more extensive disease with necessity of proximal landing zone in the arch. Objective: To evaluate descending thoracic aortic remodeling by means of volumetric analysis after hybrid approach of aortic arch debranching and stenting the descending aorta. Methods: Retrospective review of seven consecutive patients treated between September 2014 and August 2016 for diseases of proximal descending aorta (aneurysms and dissections by hybrid approach to deliver the endograft at zone 1. Computed tomography angiography were analyzed using a specific software to calculate descending thoracic aorta volumes pre- and postoperatively. Results: Follow-up was done in 100% of patients with a median time of 321 days (range, 41-625 days. No deaths or permanent neurological complications were observed. There were no endoleaks or stent migrations. Freedom from reintervention was 100% at 300 days and 66% at 600 days. Median volume reduction was of 45.5 cm3, representing a median volume shrinkage by 9.3%. Conclusion: Hybrid approach of arch and descending thoracic aorta diseases is feasible and leads to a favorable aortic remodeling with significant volume reduction.

A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal

Energy Technology Data Exchange (ETDEWEB)

Pousinho, H.M.I. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Mendes, V.M.F. [Department of Electrical Engineering and Automation, Instituto Superior de Engenharia de Lisboa, R. Conselheiro Emidio Navarro, 1950-062 Lisbon (Portugal); Catalao, J.P.S. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Center for Innovation in Electrical and Energy Engineering, Instituto Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001 Lisbon (Portugal)

2011-01-15

The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Wind power prediction plays a key role in tackling these challenges. The contribution of this paper is to propose a new hybrid approach, combining particle swarm optimization and adaptive-network-based fuzzy inference system, for short-term wind power prediction in Portugal. Significant improvements regarding forecasting accuracy are attainable using the proposed approach, in comparison with the results obtained with five other approaches. (author)

An Introduction to the Hybrid Approach of Neural Networks and the Linear Regression Model : An Illustration in the Hedonic Pricing Model of Building Costs

OpenAIRE

浅野, 美代子; マーコ, ユー K.W.

2007-01-01

This paper introduces the hybrid approach of neural networks and linear regression model proposed by Asano and Tsubaki (2003). Neural networks are often credited with its superiority in data consistency whereas the linear regression model provides simple interpretation of the data enabling researchers to verify their hypotheses. The hybrid approach aims at combing the strengths of these two well-established statistical methods. A step-by-step procedure for performing the hybrid approach is pr...

When Differential Privacy Meets Randomized Perturbation: A Hybrid Approach for Privacy-Preserving Recommender System

KAUST Repository

Liu, Xiao; Liu, An; Zhang, Xiangliang; Li, Zhixu; Liu, Guanfeng; Zhao, Lei; Zhou, Xiaofang

2017-01-01

result. However, none is designed for both hiding users’ private data and preventing privacy inference. To achieve this goal, we propose in this paper a hybrid approach for privacy-preserving recommender systems by combining differential privacy (DP

A Study on a Hybrid Approach for Diagnosing Faults in Nuclear Power Plant

International Nuclear Information System (INIS)

Yang, M.; Zhang, Z.J.; Peng, M.J.; Yan, S.Y.; Wang, H.; Ouyang, J.

2006-01-01

Proper and rapid identification of malfunctions is of premier importance for the safe operation of Nuclear Power Plants (NPP). Many monitoring or/and diagnosis methodologies based on artificial and computational intelligence have been proposed to aid operator to understand system problems, perform trouble-shooting action and reduce human error under serious pressure. However, because no single method is adequate to handle all requirements for diagnostic system, hybrid approaches where different methods work in conjunction to solve parts of the problem interest researchers greatly. In this study, Multilevel Flow Models (MFM) and Artificial Neural Network (ANN) are proposed and employed to develop a fault diagnosis system with the intention of improving the success rate of recognition on the one hand, and improving the understandability of diagnostic process and results on the other hand. Several simulation cases were conducted for evaluating the performance of the proposed diagnosis system. The simulation results validated the effectiveness of the proposed hybrid approach. (authors)

Feature Selection using Multi-objective Genetic Algorith m: A Hybrid Approach

OpenAIRE

Ahuja, Jyoti; GJUST - Guru Jambheshwar University of Sciecne and Technology; Ratnoo, Saroj Dahiya; GJUST - Guru Jambheshwar University of Sciecne and Technology

2015-01-01

Feature selection is an important pre-processing task for building accurate and comprehensible classification models. Several researchers have applied filter, wrapper or hybrid approaches using genetic algorithms which are good candidates for optimization problems that involve large search spaces like in the case of feature selection. Moreover, feature selection is an inherently multi-objective problem with many competing objectives involving size, predictive power and redundancy of the featu...

A hybrid MCDM approach for ranking suppliers by considering ethical factors

OpenAIRE

Azadfallah, Mohammad

2016-01-01

One of the negative effects of cooperating with un-ethically behaving suppliers is that it may devastate the companies' credibility among employees, customers and the public. In this paper, a hybrid Multiple Criteria Decision Making (MCDM) approach (Disjunctive-WPM method) is proposed to resolve this limitation. The proposed methods consist of the following steps: 1. drop unethical solutions and 2. rank the remaining solutions. Therefore, the aim of t...

Hybrid closure of atrial septal defect: A modified approach

Directory of Open Access Journals (Sweden)

Kshitij Sheth

2015-01-01

Full Text Available A 3.5-year-old girl underwent transcatheter closure of patent ductus arteriosus in early infancy during which time her secundum atrial septal defect (ASD was left alone. When she came for elective closure of ASD, she was found to have bilaterally blocked femoral veins. The defect was successfully closed with an Amplatzer septal occluder (ASO; St. Jude Medical, Plymouth, MN, USA using a hybrid approach via a sub-mammary mini-thoracotomy incision without using cardiopulmonary bypass. At the end of 1-year follow-up, the child is asymptomatic with device in a stable position without any residual shunt.

A hybrid approach to parameter identification of linear delay differential equations involving multiple delays

Science.gov (United States)

Marzban, Hamid Reza

2018-05-01

In this paper, we are concerned with the parameter identification of linear time-invariant systems containing multiple delays. The approach is based upon a hybrid of block-pulse functions and Legendre's polynomials. The convergence of the proposed procedure is established and an upper error bound with respect to the L2-norm associated with the hybrid functions is derived. The problem under consideration is first transformed into a system of algebraic equations. The least squares technique is then employed for identification of the desired parameters. Several multi-delay systems of varying complexity are investigated to evaluate the performance and capability of the proposed approximation method. It is shown that the proposed approach is also applicable to a class of nonlinear multi-delay systems. It is demonstrated that the suggested procedure provides accurate results for the desired parameters.

Qualitative Fault Isolation of Hybrid Systems: A Structural Model Decomposition-Based Approach

Science.gov (United States)

Bregon, Anibal; Daigle, Matthew; Roychoudhury, Indranil

2016-01-01

Quick and robust fault diagnosis is critical to ensuring safe operation of complex engineering systems. A large number of techniques are available to provide fault diagnosis in systems with continuous dynamics. However, many systems in aerospace and industrial environments are best represented as hybrid systems that consist of discrete behavioral modes, each with its own continuous dynamics. These hybrid dynamics make the on-line fault diagnosis task computationally more complex due to the large number of possible system modes and the existence of autonomous mode transitions. This paper presents a qualitative fault isolation framework for hybrid systems based on structural model decomposition. The fault isolation is performed by analyzing the qualitative information of the residual deviations. However, in hybrid systems this process becomes complex due to possible existence of observation delays, which can cause observed deviations to be inconsistent with the expected deviations for the current mode in the system. The great advantage of structural model decomposition is that (i) it allows to design residuals that respond to only a subset of the faults, and (ii) every time a mode change occurs, only a subset of the residuals will need to be reconfigured, thus reducing the complexity of the reasoning process for isolation purposes. To demonstrate and test the validity of our approach, we use an electric circuit simulation as the case study.

A hybrid approach to decision making and information fusion: Combining humans and artificial agents

NARCIS (Netherlands)

Groen, Frans C.A.; Pavlin, Gregor; Winterboer, Andi; Evers, Vanessa

This paper argues that hybrid human–agent systems can support powerful solutions to relevant problems such as Environmental Crisis management. However, it shows that such solutions require comprehensive approaches covering different aspects of data processing, model construction and the usage. In

Optimal design of supply chain network under uncertainty environment using hybrid analytical and simulation modeling approach

Science.gov (United States)

Chiadamrong, N.; Piyathanavong, V.

2017-12-01

Models that aim to optimize the design of supply chain networks have gained more interest in the supply chain literature. Mixed-integer linear programming and discrete-event simulation are widely used for such an optimization problem. We present a hybrid approach to support decisions for supply chain network design using a combination of analytical and discrete-event simulation models. The proposed approach is based on iterative procedures until the difference between subsequent solutions satisfies the pre-determined termination criteria. The effectiveness of proposed approach is illustrated by an example, which shows closer to optimal results with much faster solving time than the results obtained from the conventional simulation-based optimization model. The efficacy of this proposed hybrid approach is promising and can be applied as a powerful tool in designing a real supply chain network. It also provides the possibility to model and solve more realistic problems, which incorporate dynamism and uncertainty.

CoFe2O4-TiO2 Hybrid Nanomaterials: Synthesis Approaches Based on the Oil-in-Water Microemulsion Reaction Method

Directory of Open Access Journals (Sweden)

Arturo Adrián Rodríguez-Rodríguez

2017-01-01

Full Text Available CoFe2O4 nanoparticles decorated and wrapped with TiO2 nanoparticles have been prepared by mixing well-dispersed CoFe2O4 with amorphous TiO2 (impregnation approach and growing amorphous TiO2 over the magnetic core (seed approach, respectively, followed by thermal treatment to achieve TiO2 crystallinity. Synthesis strategies were based on the oil-in-water microemulsion reaction method. Thermally treated nanomaterials were characterized in terms of structure, morphology, and composition, to confirm hybrid nanoparticles formation and relate with the synthesis approaches; textural, optical, and magnetic properties were evaluated. X-ray diffraction revealed coexistence of cubic spinel-type CoFe2O4 and tetragonal anatase TiO2. Electron microscopy images depicted crystalline nanoparticles (sizes below 25 nm, with homogeneous Ti distribution for the hybrid nanoparticles synthesized by seed approach. EDX microanalysis and ICP-AES corroborated established chemical composition. XPS evidenced chemical states, as well as TiO2 predominance over CoFe2O4 surface. According to BET measurements, the hybrid nanoparticles were mesoporous. UV-Vis spectroscopy showed optical response along the UV-visible light region. Magnetic properties suggested the breaking order of magnetic domains due to modification with TiO2, especially for mediated seed approach sample. The properties of the obtained hybrid nanoparticles were different in comparison with its individual components. The results highlight the usefulness of designed microemulsion approaches for the straightforward synthesis of CoFe2O4-TiO2 nanostructured hybrids.

Time series analysis of infrared satellite data for detecting thermal anomalies: a hybrid approach

Science.gov (United States)

Koeppen, W. C.; Pilger, E.; Wright, R.

2011-07-01

We developed and tested an automated algorithm that analyzes thermal infrared satellite time series data to detect and quantify the excess energy radiated from thermal anomalies such as active volcanoes. Our algorithm enhances the previously developed MODVOLC approach, a simple point operation, by adding a more complex time series component based on the methods of the Robust Satellite Techniques (RST) algorithm. Using test sites at Anatahan and Kīlauea volcanoes, the hybrid time series approach detected ~15% more thermal anomalies than MODVOLC with very few, if any, known false detections. We also tested gas flares in the Cantarell oil field in the Gulf of Mexico as an end-member scenario representing very persistent thermal anomalies. At Cantarell, the hybrid algorithm showed only a slight improvement, but it did identify flares that were undetected by MODVOLC. We estimate that at least 80 MODIS images for each calendar month are required to create good reference images necessary for the time series analysis of the hybrid algorithm. The improved performance of the new algorithm over MODVOLC will result in the detection of low temperature thermal anomalies that will be useful in improving our ability to document Earth's volcanic eruptions, as well as detecting low temperature thermal precursors to larger eruptions.

Nanotubule and Tour Molecule Based Molecular Electronics: Suggestion for a Hybrid Approach

Science.gov (United States)

Srivastava, Deepak; Saini, Subhash (Technical Monitor)

1998-01-01

Recent experimental and theoretical attempts and results indicate two distinct broad pathways towards future molecular electronic devices and architectures. The first is the approach via Tour type ladder molecules and their junctions which can be fabricated with solution phase chemical approaches. Second are fullerenes or nanotubules and their junctions which may have better conductance, switching and amplifying characteristics but can not be made through well controlled and defined chemical means. A hybrid approach combining the two pathways to take advantage of the characteristics of both is suggested. Dimension and scale of such devices would be somewhere in between isolated molecule and nanotubule based devices but it maybe possible to use self-assembly towards larger functional and logicalunits.

A Hybrid Acoustic and Pronunciation Model Adaptation Approach for Non-native Speech Recognition

Science.gov (United States)

Oh, Yoo Rhee; Kim, Hong Kook

In this paper, we propose a hybrid model adaptation approach in which pronunciation and acoustic models are adapted by incorporating the pronunciation and acoustic variabilities of non-native speech in order to improve the performance of non-native automatic speech recognition (ASR). Specifically, the proposed hybrid model adaptation can be performed at either the state-tying or triphone-modeling level, depending at which acoustic model adaptation is performed. In both methods, we first analyze the pronunciation variant rules of non-native speakers and then classify each rule as either a pronunciation variant or an acoustic variant. The state-tying level hybrid method then adapts pronunciation models and acoustic models by accommodating the pronunciation variants in the pronunciation dictionary and by clustering the states of triphone acoustic models using the acoustic variants, respectively. On the other hand, the triphone-modeling level hybrid method initially adapts pronunciation models in the same way as in the state-tying level hybrid method; however, for the acoustic model adaptation, the triphone acoustic models are then re-estimated based on the adapted pronunciation models and the states of the re-estimated triphone acoustic models are clustered using the acoustic variants. From the Korean-spoken English speech recognition experiments, it is shown that ASR systems employing the state-tying and triphone-modeling level adaptation methods can relatively reduce the average word error rates (WERs) by 17.1% and 22.1% for non-native speech, respectively, when compared to a baseline ASR system.

Effects of age and type of picture on visuospatial working memory assessed with a computerized jigsaw-puzzle task.

Science.gov (United States)

Toril, Pilar; Reales, José M; Mayas, Julia; Ballesteros, Soledad

2017-09-15

We investigated the effect of age and color in a computerized version of the jigsaw-puzzle task. In Experiment 1, young and older adults were presented with puzzles in color and black-and-white line drawings, varying in difficulty from 4 to 9 pieces. Older adults performed the task better with the black-and-white stimuli and younger adults performed better with the color ones. In Experiment 2, new older and young adults identified the same fragmented pictures as fast and accurately as possible. The older group identified the black-and-white stimuli faster than those presented in color, while the younger adults identified both similarly. In Experiment 3A, new older and young groups performed the puzzle task with the same color pictures and their monochrome versions. In Experiment 3B, participants performed a speeded identification task with the two sets. The findings of these experiments showed that older adults have a memory not a perceptual difficulty.

Solving the "Personhood Jigsaw Puzzle" in Residential Care Homes for the Elderly in the Hong Kong Chinese Context.

Science.gov (United States)

Kong, Sui-Ting; Fang, Christine Meng-Sang; Lou, Vivian W Q

2017-02-01

End-of-life care studies on the nature of personhood are bourgeoning; however, the practices utilized for achieving personhood in end-of-life care, particularly in a cultural context in which interdependent being and collectivism prevail, remain underexplored. This study seeks to examine and conceptualize good practices for achieving the personhood of the dying elderly in residential care homes in a Chinese context. Twelve interviews were conducted with both medical and social care practitioners in four care homes to collect narratives of practitioners' practices. Those narratives were utilized to develop an "end-of-life case graph." Constant comparative analysis led to an understanding of the practice processes, giving rise to a process model of "solving the personhood jigsaw puzzle" that includes "understanding the person-in-relationship and person-in-time," "identifying the personhood-inhibiting experiences," and "enabling personalized care for enhanced psychosocial outcomes." Findings show how the "relational personhood" of the elderly can be maintained when physical deterioration and even death are inevitable.

Attention-level transitory response: a novel hybrid BCI approach

Science.gov (United States)

Diez, Pablo F.; Garcés Correa, Agustina; Orosco, Lorena; Laciar, Eric; Mut, Vicente

2015-10-01

Objective. People with disabilities may control devices such as a computer or a wheelchair by means of a brain-computer interface (BCI). BCI based on steady-state visual evoked potentials (SSVEP) requires visual stimulation of the user. However, this SSVEP-based BCI suffers from the ‘Midas touch effect’, i.e., the BCI can detect an SSVEP even when the user is not gazing at the stimulus. Then, these incorrect detections deteriorate the performance of the system, especially in asynchronous BCI because ongoing EEG is classified. In this paper, a novel transitory response of the attention-level of the user is reported. It was used to develop a hybrid BCI (hBCI). Approach. Three methods are proposed to detect the attention-level of the user. They are based on the alpha rhythm and theta/beta rate. The proposed hBCI scheme is presented along with these methods. Hence, the hBCI sends a command only when the user is at a high-level of attention, or in other words, when the user is really focused on the task being performed. The hBCI was tested over two different EEG datasets. Main results. The performance of the hybrid approach is superior to the standard one. Improvements of 20% in accuracy and 10 bits min-1 are reported. Moreover, the attention-level is extracted from the same EEG channels used in SSVEP detection and this way, no extra hardware is needed. Significance. A transitory response of EEG signal is used to develop the attention-SSVEP hBCI which is capable of reducing the Midas touch effect.

An approach for identification of unknown viruses using sequencing-by-hybridization.

Science.gov (United States)

Katoski, Sarah E; Meyer, Hermann; Ibrahim, Sofi

2015-09-01

Accurate identification of biological threat agents, especially RNA viruses, in clinical or environmental samples can be challenging because the concentration of viral genomic material in a given sample is usually low, viral genomic RNA is liable to degradation, and RNA viruses are extremely diverse. A two-tiered approach was used for initial identification, then full genomic characterization of 199 RNA viruses belonging to virus families Arenaviridae, Bunyaviridae, Filoviridae, Flaviviridae, and Togaviridae. A Sequencing-by-hybridization (SBH) microarray was used to tentatively identify a viral pathogen then, the identity is confirmed by guided next-generation sequencing (NGS). After optimization and evaluation of the SBH and NGS methodologies with various virus species and strains, the approach was used to test the ability to identify viruses in blinded samples. The SBH correctly identified two Ebola viruses in the blinded samples within 24 hr, and by using guided amplicon sequencing with 454 GS FLX, the identities of the viruses in both samples were confirmed. SBH provides at relatively low-cost screening of biological samples against a panel of viral pathogens that can be custom-designed on a microarray. Once the identity of virus is deduced from the highest hybridization signal on the SBH microarray, guided (amplicon) NGS sequencing can be used not only to confirm the identity of the virus but also to provide further information about the strain or isolate, including a potential genetic manipulation. This approach can be useful in situations where natural or deliberate biological threat incidents might occur and a rapid response is required. © 2015 Wiley Periodicals, Inc.

A hybrid approach for integrated healthcare cooperative purchasing and supply chain configuration.

Science.gov (United States)

Rego, Nazaré; Claro, João; Pinho de Sousa, Jorge

2014-12-01

This paper presents an innovative and flexible approach for recommending the number, size and composition of purchasing groups, for a set of hospitals willing to cooperate, while minimising their shared supply chain costs. This approach makes the financial impact of the various cooperation alternatives transparent to the group and the individual participants, opening way to a negotiation process concerning the allocation of the cooperation costs and gains. The approach was developed around a hybrid Variable Neighbourhood Search (VNS)/Tabu Search metaheuristic, resulting in a flexible tool that can be applied to purchasing groups with different characteristics, namely different operative and market circumstances, and to supply chains with different topologies and atypical cost characteristics. Preliminary computational results show the potential of the approach in solving a broad range of problems.

A hybrid approach for minimizing makespan in permutation flowshop scheduling

DEFF Research Database (Denmark)

Govindan, Kannan; Balasundaram, R.; Baskar, N.

2017-01-01

This work proposes a hybrid approach for solving traditional flowshop scheduling problems to reduce the makespan (total completion time). To solve scheduling problems, a combination of Decision Tree (DT) and Scatter Search (SS) algorithms are used. Initially, the DT is used to generate a seed...... solution which is then given input to the SS to obtain optimal / near optimal solutions of makespan. The DT used the entropy function to convert the given problem into a tree structured format / set of rules. The SS provides an extensive investigation of the search space through diversification...

Evaluation and Validation of Assembling Corrected PacBio Long Reads for Microbial Genome Completion via Hybrid Approaches.

Science.gov (United States)

Lin, Hsin-Hung; Liao, Yu-Chieh

2015-01-01

Despite the ever-increasing output of next-generation sequencing data along with developing assemblers, dozens to hundreds of gaps still exist in de novo microbial assemblies due to uneven coverage and large genomic repeats. Third-generation single-molecule, real-time (SMRT) sequencing technology avoids amplification artifacts and generates kilobase-long reads with the potential to complete microbial genome assembly. However, due to the low accuracy (~85%) of third-generation sequences, a considerable amount of long reads (>50X) are required for self-correction and for subsequent de novo assembly. Recently-developed hybrid approaches, using next-generation sequencing data and as few as 5X long reads, have been proposed to improve the completeness of microbial assembly. In this study we have evaluated the contemporary hybrid approaches and demonstrated that assembling corrected long reads (by runCA) produced the best assembly compared to long-read scaffolding (e.g., AHA, Cerulean and SSPACE-LongRead) and gap-filling (SPAdes). For generating corrected long reads, we further examined long-read correction tools, such as ECTools, LSC, LoRDEC, PBcR pipeline and proovread. We have demonstrated that three microbial genomes including Escherichia coli K12 MG1655, Meiothermus ruber DSM1279 and Pdeobacter heparinus DSM2366 were successfully hybrid assembled by runCA into near-perfect assemblies using ECTools-corrected long reads. In addition, we developed a tool, Patch, which implements corrected long reads and pre-assembled contigs as inputs, to enhance microbial genome assemblies. With the additional 20X long reads, short reads of S. cerevisiae W303 were hybrid assembled into 115 contigs using the verified strategy, ECTools + runCA. Patch was subsequently applied to upgrade the assembly to a 35-contig draft genome. Our evaluation of the hybrid approaches shows that assembling the ECTools-corrected long reads via runCA generates near complete microbial genomes, suggesting

Design-order, non-conformal low-Mach fluid algorithms using a hybrid CVFEM/DG approach

Science.gov (United States)

Domino, Stefan P.

2018-04-01

A hybrid, design-order sliding mesh algorithm, which uses a control volume finite element method (CVFEM), in conjunction with a discontinuous Galerkin (DG) approach at non-conformal interfaces, is outlined in the context of a low-Mach fluid dynamics equation set. This novel hybrid DG approach is also demonstrated to be compatible with a classic edge-based vertex centered (EBVC) scheme. For the CVFEM, element polynomial, P, promotion is used to extend the low-order P = 1 CVFEM method to higher-order, i.e., P = 2. An equal-order low-Mach pressure-stabilized methodology, with emphasis on the non-conformal interface boundary condition, is presented. A fully implicit matrix solver approach that accounts for the full stencil connectivity across the non-conformal interface is employed. A complete suite of formal verification studies using the method of manufactured solutions (MMS) is performed to verify the order of accuracy of the underlying methodology. The chosen suite of analytical verification cases range from a simple steady diffusion system to a traveling viscous vortex across mixed-order non-conformal interfaces. Results from all verification studies demonstrate either second- or third-order spatial accuracy and, for transient solutions, second-order temporal accuracy. Significant accuracy gains in manufactured solution error norms are noted even with modest promotion of the underlying polynomial order. The paper also demonstrates the CVFEM/DG methodology on two production-like simulation cases that include an inner block subjected to solid rotation, i.e., each of the simulations include a sliding mesh, non-conformal interface. The first production case presented is a turbulent flow past a high-rate-of-rotation cube (Re, 4000; RPM, 3600) on like and mixed-order polynomial interfaces. The final simulation case is a full-scale Vestas V27 225 kW wind turbine (tower and nacelle omitted) in which a hybrid topology, low-order mesh is used. Both production simulations

Opposition-Based Memetic Algorithm and Hybrid Approach for Sorting Permutations by Reversals.

Science.gov (United States)

Soncco-Álvarez, José Luis; Muñoz, Daniel M; Ayala-Rincón, Mauricio

2018-02-21

Sorting unsigned permutations by reversals is a difficult problem; indeed, it was proved to be NP-hard by Caprara (1997). Because of its high complexity, many approximation algorithms to compute the minimal reversal distance were proposed until reaching the nowadays best-known theoretical ratio of 1.375. In this article, two memetic algorithms to compute the reversal distance are proposed. The first one uses the technique of opposition-based learning leading to an opposition-based memetic algorithm; the second one improves the previous algorithm by applying the heuristic of two breakpoint elimination leading to a hybrid approach. Several experiments were performed with one-hundred randomly generated permutations, single benchmark permutations, and biological permutations. Results of the experiments showed that the proposed OBMA and Hybrid-OBMA algorithms achieve the best results for practical cases, that is, for permutations of length up to 120. Also, Hybrid-OBMA showed to improve the results of OBMA for permutations greater than or equal to 60. The applicability of our proposed algorithms was checked processing permutations based on biological data, in which case OBMA gave the best average results for all instances.

Numerical methodologies for investigation of moderate-velocity flow using a hybrid computational fluid dynamics - molecular dynamics simulation approach

International Nuclear Information System (INIS)

Ko, Soon Heum; Kim, Na Yong; Nikitopoulos, Dimitris E.; Moldovan, Dorel; Jha, Shantenu

2014-01-01

Numerical approaches are presented to minimize the statistical errors inherently present due to finite sampling and the presence of thermal fluctuations in the molecular region of a hybrid computational fluid dynamics (CFD) - molecular dynamics (MD) flow solution. Near the fluid-solid interface the hybrid CFD-MD simulation approach provides a more accurate solution, especially in the presence of significant molecular-level phenomena, than the traditional continuum-based simulation techniques. It also involves less computational cost than the pure particle-based MD. Despite these advantages the hybrid CFD-MD methodology has been applied mostly in flow studies at high velocities, mainly because of the higher statistical errors associated with low velocities. As an alternative to the costly increase of the size of the MD region to decrease statistical errors, we investigate a few numerical approaches that reduce sampling noise of the solution at moderate-velocities. These methods are based on sampling of multiple simulation replicas and linear regression of multiple spatial/temporal samples. We discuss the advantages and disadvantages of each technique in the perspective of solution accuracy and computational cost.

Multilayer Approach for Advanced Hybrid Lithium Battery

KAUST Repository

Ming, Jun

2016-06-06

Conventional intercalated rechargeable batteries have shown their capacity limit, and the development of an alternative battery system with higher capacity is strongly needed for sustainable electrical vehicles and hand-held devices. Herein, we introduce a feasible and scalable multilayer approach to fabricate a promising hybrid lithium battery with superior capacity and multivoltage plateaus. A sulfur-rich electrode (90 wt % S) is covered by a dual layer of graphite/Li4Ti5O12, where the active materials S and Li4Ti5O12 can both take part in redox reactions and thus deliver a high capacity of 572 mAh gcathode -1 (vs the total mass of electrode) or 1866 mAh gs -1 (vs the mass of sulfur) at 0.1C (with the definition of 1C = 1675 mA gs -1). The battery shows unique voltage platforms at 2.35 and 2.1 V, contributed from S, and 1.55 V from Li4Ti5O12. A high rate capability of 566 mAh gcathode -1 at 0.25C and 376 mAh gcathode -1 at 1C with durable cycle ability over 100 cycles can be achieved. Operando Raman and electron microscope analysis confirm that the graphite/Li4Ti5O12 layer slows the dissolution/migration of polysulfides, thereby giving rise to a higher sulfur utilization and a slower capacity decay. This advanced hybrid battery with a multilayer concept for marrying different voltage plateaus from various electrode materials opens a way of providing tunable capacity and multiple voltage platforms for energy device applications. © 2016 American Chemical Society.

A Hybrid Satellite-Terrestrial Approach to Aeronautical Communication Networks

Science.gov (United States)

Kerczewski, Robert J.; Chomos, Gerald J.; Griner, James H.; Mainger, Steven W.; Martzaklis, Konstantinos S.; Kachmar, Brian A.

2000-01-01

Rapid growth in air travel has been projected to continue for the foreseeable future. To maintain a safe and efficient national and global aviation system, significant advances in communications systems supporting aviation are required. Satellites will increasingly play a critical role in the aeronautical communications network. At the same time, current ground-based communications links, primarily very high frequency (VHF), will continue to be employed due to cost advantages and legacy issues. Hence a hybrid satellite-terrestrial network, or group of networks, will emerge. The increased complexity of future aeronautical communications networks dictates that system-level modeling be employed to obtain an optimal system fulfilling a majority of user needs. The NASA Glenn Research Center is investigating the current and potential future state of aeronautical communications, and is developing a simulation and modeling program to research future communications architectures for national and global aeronautical needs. This paper describes the primary requirements, the current infrastructure, and emerging trends of aeronautical communications, including a growing role for satellite communications. The need for a hybrid communications system architecture approach including both satellite and ground-based communications links is explained. Future aeronautical communication network topologies and key issues in simulation and modeling of future aeronautical communications systems are described.

When Differential Privacy Meets Randomized Perturbation: A Hybrid Approach for Privacy-Preserving Recommender System

KAUST Repository

Liu, Xiao

2017-03-21

Privacy risks of recommender systems have caused increasing attention. Users’ private data is often collected by probably untrusted recommender system in order to provide high-quality recommendation. Meanwhile, malicious attackers may utilize recommendation results to make inferences about other users’ private data. Existing approaches focus either on keeping users’ private data protected during recommendation computation or on preventing the inference of any single user’s data from the recommendation result. However, none is designed for both hiding users’ private data and preventing privacy inference. To achieve this goal, we propose in this paper a hybrid approach for privacy-preserving recommender systems by combining differential privacy (DP) with randomized perturbation (RP). We theoretically show the noise added by RP has limited effect on recommendation accuracy and the noise added by DP can be well controlled based on the sensitivity analysis of functions on the perturbed data. Extensive experiments on three large-scale real world datasets show that the hybrid approach generally provides more privacy protection with acceptable recommendation accuracy loss, and surprisingly sometimes achieves better privacy without sacrificing accuracy, thus validating its feasibility in practice.

A Hybrid Approach to Processing Big Data Graphs on Memory-Restricted Systems

KAUST Repository

Harshvardhan,

2015-05-01

With the advent of big-data, processing large graphs quickly has become increasingly important. Most existing approaches either utilize in-memory processing techniques that can only process graphs that fit completely in RAM, or disk-based techniques that sacrifice performance. In this work, we propose a novel RAM-Disk hybrid approach to graph processing that can scale well from a single shared-memory node to large distributed-memory systems. It works by partitioning the graph into sub graphs that fit in RAM and uses a paging-like technique to load sub graphs. We show that without modifying the algorithms, this approach can scale from small memory-constrained systems (such as tablets) to large-scale distributed machines with 16, 000+ cores.

Simulation of a Wall-Bounded Flow using a Hybrid LES/RAS Approach with Turbulence Recycling

Science.gov (United States)

Quinlan, Jesse R.; Mcdaniel, James; Baurle, Robert A.

2012-01-01

Simulations of a supersonic recessed-cavity flow are performed using a hybrid large-eddy/ Reynolds-averaged simulation approach utilizing an inflow turbulence recycling procedure and hybridized inviscid flux scheme. Calorically perfect air enters the three-dimensional domain at a free stream Mach number of 2.92. Simulations are performed to assess grid sensitivity of the solution, efficacy of the turbulence recycling, and effect of the shock sensor used with the hybridized inviscid flux scheme. Analysis of the turbulent boundary layer upstream of the rearward-facing step for each case indicates excellent agreement with theoretical predictions. Mean velocity and pressure results are compared to Reynolds-averaged simulations and experimental data for each case, and these comparisons indicate good agreement on the finest grid. Simulations are repeated on a coarsened grid, and results indicate strong grid density sensitivity. The effect of turbulence recycling on the solution is illustrated by performing coarse grid simulations with and without inflow turbulence recycling. Two shock sensors, one of Ducros and one of Larsson, are assessed for use with the hybridized inviscid flux reconstruction scheme.

Hybrid Optimization-Based Approach for Multiple Intelligent Vehicles Requests Allocation

Directory of Open Access Journals (Sweden)

Ahmed Hussein

2018-01-01

Full Text Available Self-driving cars are attracting significant attention during the last few years, which makes the technology advances jump fast and reach a point of having a number of automated vehicles on the roads. Therefore, the necessity of cooperative driving for these automated vehicles is exponentially increasing. One of the main issues in the cooperative driving world is the Multirobot Task Allocation (MRTA problem. This paper addresses the MRTA problem, specifically for the problem of vehicles and requests allocation. The objective is to introduce a hybrid optimization-based approach to solve the problem of multiple intelligent vehicles requests allocation as an instance of MRTA problem, to find not only a feasible solution, but also an optimized one as per the objective function. Several test scenarios were implemented in order to evaluate the efficiency of the proposed approach. These scenarios are based on well-known benchmarks; thus a comparative study is conducted between the obtained results and the suboptimal results. The analysis of the experimental results shows that the proposed approach was successful in handling various scenarios, especially with the increasing number of vehicles and requests, which displays the proposed approach efficiency and performance.

The hybrid thermography approach applied to architectural structures

Science.gov (United States)

Sfarra, S.; Ambrosini, D.; Paoletti, D.; Nardi, I.; Pasqualoni, G.

2017-07-01

This work contains an overview of infrared thermography (IRT) method and its applications relating to the investigation of architectural structures. In this method, the passive approach is usually used in civil engineering, since it provides a panoramic view of the thermal anomalies to be interpreted also thanks to the use of photographs focused on the region of interest (ROI). The active approach, is more suitable for laboratory or indoor inspections, as well as for objects having a small size. The external stress to be applied is thermal, coming from non-natural apparatus such as lamps or hot / cold air jets. In addition, the latter permits to obtain quantitative information related to defects not detectable to the naked eyes. Very recently, the hybrid thermography (HIRT) approach has been introduced to the attention of the scientific panorama. It can be applied when the radiation coming from the sun, directly arrives (i.e., possibly without the shadow cast effect) on a surface exposed to the air. A large number of thermograms must be collected and a post-processing analysis is subsequently applied via advanced algorithms. Therefore, an appraisal of the defect depth can be obtained passing through the calculation of the combined thermal diffusivity of the materials above the defect. The approach is validated herein by working, in a first stage, on a mosaic sample having known defects while, in a second stage, on a Church built in L'Aquila (Italy) and covered with a particular masonry structure called apparecchio aquilano. The results obtained appear promising.

Early experience with the Occlutech PLD occluder for mitral paravalvar leak closure through a hybrid transapical approach.

Science.gov (United States)

Bedair, Radwa; Morgan, Gareth J; Bapat, Vinayak; Kapetanakis, Stamatis; Goreczny, Sebastian; Simpson, John; Qureshi, Shakeel A

2016-12-10

We sought to evaluate the feasibility and efficacy of hybrid transapical closure of paravalvar mitral leaks using a new Occlutech PLD occluder in patients with heart failure and/or haemolytic anaemia. Retrospective analysis of clinical and procedural data was undertaken for patients who had attempted closure of paravalvar mitral leaks via a hybrid transapical approach with the Occlutech PLD occluder. Eight patients (four males, median age 69 years) underwent closure of 10 mitral paravalvar leaks using eight Occlutech PLD occluders and two AMPLATZER Vascular Plugs (AVP II). Successful deployment, with significant reduction of the paravalvar leak was achieved in seven patients with short procedure (median 131 min) and fluoroscopy times (median 22 min). One patient had mechanical interference with prosthetic valve function, requiring surgery. Another patient with a high EuroSCORE (48.8%) died of multi-organ failure two days after the procedure. Clinical improvement in either heart failure or haemolysis was seen in all discharged patients. In our series of patients with challenging anatomy, the Occlutech PLD occluders performed well when implanted via a hybrid transapical approach. Further work is needed to assess this methodology fully for a wider population and to assess other deployment approaches for this promising new occluder.

A Hybrid Computational Intelligence Approach Combining Genetic Programming And Heuristic Classification for Pap-Smear Diagnosis

DEFF Research Database (Denmark)

Tsakonas, Athanasios; Dounias, Georgios; Jantzen, Jan

2001-01-01

The paper suggests the combined use of different computational intelligence (CI) techniques in a hybrid scheme, as an effective approach to medical diagnosis. Getting to know the advantages and disadvantages of each computational intelligence technique in the recent years, the time has come...

A hybrid modelling approach to simulating foot-and-mouth disease outbreaks in Australian livestock

Directory of Open Access Journals (Sweden)

Richard A Bradhurst

2015-03-01

Full Text Available Foot-and-mouth disease (FMD is a highly contagious and economically important viral disease of cloven-hoofed animals. Australia's freedom from FMD underpins a valuable trade in live animals and animal products. An outbreak of FMD would result in the loss of export markets and cause severe disruption to domestic markets. The prevention of, and contingency planning for, FMD are of key importance to government, industry, producers and the community. The spread and control of FMD is complex and dynamic due to a highly contagious multi-host pathogen operating in a heterogeneous environment across multiple jurisdictions. Epidemiological modelling is increasingly being recognized as a valuable tool for investigating the spread of disease under different conditions and the effectiveness of control strategies. Models of infectious disease can be broadly classified as: population-based models that are formulated from the top-down and employ population-level relationships to describe individual-level behaviour, individual-based models that are formulated from the bottom-up and aggregate individual-level behaviour to reveal population-level relationships, or hybrid models which combine the two approaches into a single model.The Australian Animal Disease Spread (AADIS hybrid model employs a deterministic equation-based model (EBM to model within-herd spread of FMD, and a stochastic, spatially-explicit agent-based model (ABM to model between-herd spread and control. The EBM provides concise and computationally efficient predictions of herd prevalence and clinical signs over time. The ABM captures the complex, stochastic and heterogeneous environment in which an FMD epidemic operates. The AADIS event-driven hybrid EBM/ABM architecture is a flexible, efficient and extensible framework for modelling the spread and control of disease in livestock on a national scale. We present an overview of the AADIS hybrid approach and a description of the model

Hourly forecasting of global solar radiation based on multiscale decomposition methods: A hybrid approach

International Nuclear Information System (INIS)

Monjoly, Stéphanie; André, Maïna; Calif, Rudy; Soubdhan, Ted

2017-01-01

This paper introduces a new approach for the forecasting of solar radiation series at 1 h ahead. We investigated on several techniques of multiscale decomposition of clear sky index K_c data such as Empirical Mode Decomposition (EMD), Ensemble Empirical Mode Decomposition (EEMD) and Wavelet Decomposition. From these differents methods, we built 11 decomposition components and 1 residu signal presenting different time scales. We performed classic forecasting models based on linear method (Autoregressive process AR) and a non linear method (Neural Network model). The choice of forecasting method is adaptative on the characteristic of each component. Hence, we proposed a modeling process which is built from a hybrid structure according to the defined flowchart. An analysis of predictive performances for solar forecasting from the different multiscale decompositions and forecast models is presented. From multiscale decomposition, the solar forecast accuracy is significantly improved, particularly using the wavelet decomposition method. Moreover, multistep forecasting with the proposed hybrid method resulted in additional improvement. For example, in terms of RMSE error, the obtained forecasting with the classical NN model is about 25.86%, this error decrease to 16.91% with the EMD-Hybrid Model, 14.06% with the EEMD-Hybid model and to 7.86% with the WD-Hybrid Model. - Highlights: • Hourly forecasting of GHI in tropical climate with many cloud formation processes. • Clear sky Index decomposition using three multiscale decomposition methods. • Combination of multiscale decomposition methods with AR-NN models to predict GHI. • Comparison of the proposed hybrid model with the classical models (AR, NN). • Best results using Wavelet-Hybrid model in comparison with classical models.

Photo-Ionization of Noble Gases: A Demonstration of Hybrid Coupled Channels Approach

Directory of Open Access Journals (Sweden)

Vinay Pramod Majety

2015-01-01

Full Text Available We present here an application of the recently developed hybrid coupled channels approach to study photo-ionization of noble gas atoms: Neon and Argon. We first compute multi-photon ionization rates and cross-sections for these inert gas atoms with our approach and compare them with reliable data available from R-matrix Floquet theory. The good agreement between coupled channels and R-matrix Floquet theory show that our method treats multi-electron systems on par with the well established R-matrix theory. We then apply the time dependent surface flux (tSURFF method with our approach to compute total and angle resolved photo-electron spectra from Argon with linearly and circularly polarized 12 nm wavelength laser fields, a typical wavelength available from Free Electron Lasers (FELs.

Swarm intelligence-based approach for optimal design of CMOS differential amplifier and comparator circuit using a hybrid salp swarm algorithm

Science.gov (United States)

Asaithambi, Sasikumar; Rajappa, Muthaiah

2018-05-01

In this paper, an automatic design method based on a swarm intelligence approach for CMOS analog integrated circuit (IC) design is presented. The hybrid meta-heuristics optimization technique, namely, the salp swarm algorithm (SSA), is applied to the optimal sizing of a CMOS differential amplifier and the comparator circuit. SSA is a nature-inspired optimization algorithm which mimics the navigating and hunting behavior of salp. The hybrid SSA is applied to optimize the circuit design parameters and to minimize the MOS transistor sizes. The proposed swarm intelligence approach was successfully implemented for an automatic design and optimization of CMOS analog ICs using Generic Process Design Kit (GPDK) 180 nm technology. The circuit design parameters and design specifications are validated through a simulation program for integrated circuit emphasis simulator. To investigate the efficiency of the proposed approach, comparisons have been carried out with other simulation-based circuit design methods. The performances of hybrid SSA based CMOS analog IC designs are better than the previously reported studies.

A Hybrid Column Generation approach for an Industrial Waste Collection Routing Problem

DEFF Research Database (Denmark)

Hauge, Kristian; Larsen, Jesper; Lusby, Richard Martin

2014-01-01

, while empty containers must be returned to the depot to await further assignments. Unlike, the traditional ROROR problem, where vehicles may transport one skip container at a time regardless of whether it is full or not, we consider cases in which a vehicle can transport up to eight containers, at most...... two of which can be full. We propose a Generalized Set Partitioning formulation of the problem and describe a hybrid column generation procedure to solve it. A fast Tabu Search heuristic is used to generate new columns. The proposed methodology is tested on nine data sets, four of which are actual......, real-world problem instances. Results indicate that the hybrid column generation outperforms a purely heuristic approach in terms of both running time and solution quality. High quality solutions to problems containing up to 100 orders can be solved in approximately 15 minutes....

A Hybrid Approach to Cognitive Engineering: Supporting Development of a Revolutionary Warfighter-Centered Command and Control System

National Research Council Canada - National Science Library

Ockerman, Jennifer; McKneely, Jennifer A; Koterba, Nathan

2005-01-01

...) for the requirements analysis and design of revolutionary command and control systems and domains. This hybrid approach uses knowledge elicitation and representation techniques from several current cognitive engineering methodologies...

Insight and Evidence Motivating the Simplification of Dual-Analysis Hybrid Systems into Single-Analysis Hybrid Systems

Science.gov (United States)

Todling, Ricardo; Diniz, F. L. R.; Takacs, L. L.; Suarez, M. J.

2018-01-01

Many hybrid data assimilation systems currently used for NWP employ some form of dual-analysis system approach. Typically a hybrid variational analysis is responsible for creating initial conditions for high-resolution forecasts, and an ensemble analysis system is responsible for creating sample perturbations used to form the flow-dependent part of the background error covariance required in the hybrid analysis component. In many of these, the two analysis components employ different methodologies, e.g., variational and ensemble Kalman filter. In such cases, it is not uncommon to have observations treated rather differently between the two analyses components; recentering of the ensemble analysis around the hybrid analysis is used to compensated for such differences. Furthermore, in many cases, the hybrid variational high-resolution system implements some type of four-dimensional approach, whereas the underlying ensemble system relies on a three-dimensional approach, which again introduces discrepancies in the overall system. Connected to these is the expectation that one can reliably estimate observation impact on forecasts issued from hybrid analyses by using an ensemble approach based on the underlying ensemble strategy of dual-analysis systems. Just the realization that the ensemble analysis makes substantially different use of observations as compared to their hybrid counterpart should serve as enough evidence of the implausibility of such expectation. This presentation assembles numerous anecdotal evidence to illustrate the fact that hybrid dual-analysis systems must, at the very minimum, strive for consistent use of the observations in both analysis sub-components. Simpler than that, this work suggests that hybrid systems can reliably be constructed without the need to employ a dual-analysis approach. In practice, the idea of relying on a single analysis system is appealing from a cost-maintenance perspective. More generally, single-analysis systems avoid

Energy level alignment at hybridized organic-metal interfaces from a GW projection approach

Science.gov (United States)

Chen, Yifeng; Tamblyn, Isaac; Quek, Su Ying

Energy level alignments at organic-metal interfaces are of profound importance in numerous (opto)electronic applications. Standard density functional theory (DFT) calculations generally give incorrect energy level alignments and missing long-range polarization effects. Previous efforts to address this problem using the many-electron GW method have focused on physisorbed systems where hybridization effects are insignificant. Here, we use state-of-the-art GW methods to predict the level alignment at the amine-Au interface, where molecular levels do hybridize with metallic states. This non-trivial hybridization implies that DFT result is a poor approximation to the quasiparticle states. However, we find that the self-energy operator is approximately diagonal in the molecular basis, allowing us to use a projection approach to predict the level alignments. Our results indicate that the metallic substrate reduces the HOMO-LUMO gap by 3.5 4.0 eV, depending on the molecular coverage/presence of Au adatoms. Our GW results are further compared with those of a simple image charge model that describes the level alignment in physisorbed systems. Syq and YC acknowledge Grant NRF-NRFF2013-07 and the medium-sized centre program from the National Research Foundation, Singapore.

Hybrid Wavelet De-noising and Rank-Set Pair Analysis approach for forecasting hydro-meteorological time series

Science.gov (United States)

WANG, D.; Wang, Y.; Zeng, X.

2017-12-01

Accurate, fast forecasting of hydro-meteorological time series is presently a major challenge in drought and flood mitigation. This paper proposes a hybrid approach, Wavelet De-noising (WD) and Rank-Set Pair Analysis (RSPA), that takes full advantage of a combination of the two approaches to improve forecasts of hydro-meteorological time series. WD allows decomposition and reconstruction of a time series by the wavelet transform, and hence separation of the noise from the original series. RSPA, a more reliable and efficient version of Set Pair Analysis, is integrated with WD to form the hybrid WD-RSPA approach. Two types of hydro-meteorological data sets with different characteristics and different levels of human influences at some representative stations are used to illustrate the WD-RSPA approach. The approach is also compared to three other generic methods: the conventional Auto Regressive Integrated Moving Average (ARIMA) method, Artificial Neural Networks (ANNs) (BP-error Back Propagation, MLP-Multilayer Perceptron and RBF-Radial Basis Function), and RSPA alone. Nine error metrics are used to evaluate the model performance. The results show that WD-RSPA is accurate, feasible, and effective. In particular, WD-RSPA is found to be the best among the various generic methods compared in this paper, even when the extreme events are included within a time series.

A hybrid computational approach to estimate solar global radiation: An empirical evidence from Iran

International Nuclear Information System (INIS)

Mostafavi, Elham Sadat; Ramiyani, Sara Saeidi; Sarvar, Rahim; Moud, Hashem Izadi; Mousavi, Seyyed Mohammad

2013-01-01

This paper presents an innovative hybrid approach for the estimation of the solar global radiation. New prediction equations were developed for the global radiation using an integrated search method of genetic programming (GP) and simulated annealing (SA), called GP/SA. The solar radiation was formulated in terms of several climatological and meteorological parameters. Comprehensive databases containing monthly data collected for 6 years in two cities of Iran were used to develop GP/SA-based models. Separate models were established for each city. The generalization of the models was verified using a separate testing database. A sensitivity analysis was conducted to investigate the contribution of the parameters affecting the solar radiation. The derived models make accurate predictions of the solar global radiation and notably outperform the existing models. -- Highlights: ► A hybrid approach is presented for the estimation of the solar global radiation. ► The proposed method integrates the capabilities of GP and SA. ► Several climatological and meteorological parameters are included in the analysis. ► The GP/SA models make accurate predictions of the solar global radiation.

Identifying reports of randomized controlled trials (RCTs) via a hybrid machine learning and crowdsourcing approach.

Science.gov (United States)

Wallace, Byron C; Noel-Storr, Anna; Marshall, Iain J; Cohen, Aaron M; Smalheiser, Neil R; Thomas, James

2017-11-01

Identifying all published reports of randomized controlled trials (RCTs) is an important aim, but it requires extensive manual effort to separate RCTs from non-RCTs, even using current machine learning (ML) approaches. We aimed to make this process more efficient via a hybrid approach using both crowdsourcing and ML. We trained a classifier to discriminate between citations that describe RCTs and those that do not. We then adopted a simple strategy of automatically excluding citations deemed very unlikely to be RCTs by the classifier and deferring to crowdworkers otherwise. Combining ML and crowdsourcing provides a highly sensitive RCT identification strategy (our estimates suggest 95%-99% recall) with substantially less effort (we observed a reduction of around 60%-80%) than relying on manual screening alone. Hybrid crowd-ML strategies warrant further exploration for biomedical curation/annotation tasks. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association.

An integrated optimization approach for a hybrid energy system in electric vehicles

International Nuclear Information System (INIS)

Hung, Yi-Hsuan; Wu, Chien-Hsun

2012-01-01

Highlights: ► Second-order control-oriented dynamics for a battery/supercapacitor EV is modeled. ► Multiple for-loop programming and global searchwith constraints are main design principles of integrated optimization algorithm (IOA). ► Optimal hybridization is derived based on maximizing energy storage capacity. ► Optimal energy management in three EV operation modes is searched based on minimizing total consumed power. ► Simulation results prove that 6+% of total energy is saved by the IOA method. -- Abstract: This paper develops a simple but innovative integrated optimization approach (IOA) for deriving the best solutions of component sizing and control strategies of a hybrid energy system (HES) which consists of a lithium battery and a supercapacitor module. To implement IOA, a multiple for-loop structure with a preset cost function is needed to globally calculate the best hybridization and energy management of the HES. For system hybridization, the optimal size ratio is evaluated by maximizing the HES energy stored capacity at various costs. For energy management, the optimal power distribution combined with a three-mode rule-based strategy is searched to minimize the total consumed energy. Combining above two for-loop structures and giving a time-dependent test scenario, the IOA is derived by minimizing the accumulated HES power. Simulation results show that 6% of the total HES energy can be saved in the IOA case compared with the original system in two driving cycles: ECE and UDDS, and two vehicle weights, respectively. It proves that the IOA effectively derives the maximum energy storage capacity and the minimum energy consumption of the HES at the same time. Experimental verification will be carried out in the near future.

Students' Game Performance Improvements during a Hybrid Sport Education-Step-Game-Approach Volleyball Unit

Science.gov (United States)

Araújo, Rui; Mesquita, Isabel; Hastie, Peter; Pereira, Cristiana

2016-01-01

The purpose of this study was to examine a hybrid combination of sport education and the step-game-approach (SGA) on students' gameplay performance in volleyball, taking into account their sex and skill-level. Seventeen seventh-grade students (seven girls, 10 boys, average age 11.8) participated in a 25-lesson volleyball season, in which the…

An Approach to Evaluate Stability for Cable-Based Parallel Camera Robots with Hybrid Tension-Stiffness Properties

Directory of Open Access Journals (Sweden)

Huiling Wei

2015-12-01

Full Text Available This paper focuses on studying the effect of cable tensions and stiffness on the stability of cable-based parallel camera robots. For this purpose, the tension factor and the stiffness factor are defined, and the expression of stability is deduced. A new approach is proposed to calculate the hybrid-stability index with the minimum cable tension and the minimum singular value. Firstly, the kinematic model of a cable-based parallel camera robot is established. Based on the model, the tensions are solved and a tension factor is defined. In order to obtain the tension factor, an optimization of the cable tensions is carried out. Then, an expression of the system's stiffness is deduced and a stiffness factor is defined. Furthermore, an approach to evaluate the stability of the cable-based camera robots with hybrid tension-stiffness properties is presented. Finally, a typical three-degree-of-freedom cable-based parallel camera robot with four cables is studied as a numerical example. The simulation results show that the approach is both reasonable and effective.

A hybrid modeling approach for option pricing

Science.gov (United States)

Hajizadeh, Ehsan; Seifi, Abbas

2011-11-01

The complexity of option pricing has led many researchers to develop sophisticated models for such purposes. The commonly used Black-Scholes model suffers from a number of limitations. One of these limitations is the assumption that the underlying probability distribution is lognormal and this is so controversial. We propose a couple of hybrid models to reduce these limitations and enhance the ability of option pricing. The key input to option pricing model is volatility. In this paper, we use three popular GARCH type model for estimating volatility. Then, we develop two non-parametric models based on neural networks and neuro-fuzzy networks to price call options for S&P 500 index. We compare the results with those of Black-Scholes model and show that both neural network and neuro-fuzzy network models outperform Black-Scholes model. Furthermore, comparing the neural network and neuro-fuzzy approaches, we observe that for at-the-money options, neural network model performs better and for both in-the-money and an out-of-the money option, neuro-fuzzy model provides better results.

A hybrid system approach to airspeed, angle of attack and sideslip estimation in Unmanned Aerial Vehicles

KAUST Repository

Shaqura, Mohammad; Claudel, Christian

2015-01-01

, low power autopilots in real-time. The computational method is based on a hybrid decomposition of the modes of operation of the UAV. A Bayesian approach is considered for estimation, in which the estimated airspeed, angle of attack and sideslip

Formal verification of dynamic hybrid systems: a NuSMV-based model checking approach

Directory of Open Access Journals (Sweden)

Xu Zhi

2018-01-01

Full Text Available Software security is an important and challenging research topic in developing dynamic hybrid embedded software systems. Ensuring the correct behavior of these systems is particularly difficult due to the interactions between the continuous subsystem and the discrete subsystem. Currently available security analysis methods for system risks have been limited, as they rely on manual inspections of the individual subsystems under simplifying assumptions. To improve this situation, a new approach is proposed that is based on the symbolic model checking tool NuSMV. A dual PID system is used as an example system, for which the logical part and the computational part of the system are modeled in a unified manner. Constraints are constructed on the controlled object, and a counter-example path is ultimately generated, indicating that the hybrid system can be analyzed by the model checking tool.

Prediction of Currency Volume Issued in Taiwan Using a Hybrid Artificial Neural Network and Multiple Regression Approach

Directory of Open Access Journals (Sweden)

Yuehjen E. Shao

2013-01-01

Full Text Available Because the volume of currency issued by a country always affects its interest rate, price index, income levels, and many other important macroeconomic variables, the prediction of currency volume issued has attracted considerable attention in recent years. In contrast to the typical single-stage forecast model, this study proposes a hybrid forecasting approach to predict the volume of currency issued in Taiwan. The proposed hybrid models consist of artificial neural network (ANN and multiple regression (MR components. The MR component of the hybrid models is established for a selection of fewer explanatory variables, wherein the selected variables are of higher importance. The ANN component is then designed to generate forecasts based on those important explanatory variables. Subsequently, the model is used to analyze a real dataset of Taiwan's currency from 1996 to 2011 and twenty associated explanatory variables. The prediction results reveal that the proposed hybrid scheme exhibits superior forecasting performance for predicting the volume of currency issued in Taiwan.

HAMDA: Hybrid Approach for MiRNA-Disease Association prediction.

Science.gov (United States)

Chen, Xing; Niu, Ya-Wei; Wang, Guang-Hui; Yan, Gui-Ying

2017-12-01

For decades, enormous experimental researches have collectively indicated that microRNA (miRNA) could play indispensable roles in many critical biological processes and thus also the pathogenesis of human complex diseases. Whereas the resource and time cost required in traditional biology experiments are expensive, more and more attentions have been paid to the development of effective and feasible computational methods for predicting potential associations between disease and miRNA. In this study, we developed a computational model of Hybrid Approach for MiRNA-Disease Association prediction (HAMDA), which involved the hybrid graph-based recommendation algorithm, to reveal novel miRNA-disease associations by integrating experimentally verified miRNA-disease associations, disease semantic similarity, miRNA functional similarity, and Gaussian interaction profile kernel similarity into a recommendation algorithm. HAMDA took not only network structure and information propagation but also node attribution into consideration, resulting in a satisfactory prediction performance. Specifically, HAMDA obtained AUCs of 0.9035 and 0.8395 in the frameworks of global and local leave-one-out cross validation, respectively. Meanwhile, HAMDA also achieved good performance with AUC of 0.8965 ± 0.0012 in 5-fold cross validation. Additionally, we conducted case studies about three important human cancers for performance evaluation of HAMDA. As a result, 90% (Lymphoma), 86% (Prostate Cancer) and 92% (Kidney Cancer) of top 50 predicted miRNAs were confirmed by recent experiment literature, which showed the reliable prediction ability of HAMDA. Copyright © 2017 Elsevier Inc. All rights reserved.

A simplified computational fluid-dynamic approach to the oxidizer injector design in hybrid rockets

Science.gov (United States)

Di Martino, Giuseppe D.; Malgieri, Paolo; Carmicino, Carmine; Savino, Raffaele

2016-12-01

Fuel regression rate in hybrid rockets is non-negligibly affected by the oxidizer injection pattern. In this paper a simplified computational approach developed in an attempt to optimize the oxidizer injector design is discussed. Numerical simulations of the thermo-fluid-dynamic field in a hybrid rocket are carried out, with a commercial solver, to investigate into several injection configurations with the aim of increasing the fuel regression rate and minimizing the consumption unevenness, but still favoring the establishment of flow recirculation at the motor head end, which is generated with an axial nozzle injector and has been demonstrated to promote combustion stability, and both larger efficiency and regression rate. All the computations have been performed on the configuration of a lab-scale hybrid rocket motor available at the propulsion laboratory of the University of Naples with typical operating conditions. After a preliminary comparison between the two baseline limiting cases of an axial subsonic nozzle injector and a uniform injection through the prechamber, a parametric analysis has been carried out by varying the oxidizer jet flow divergence angle, as well as the grain port diameter and the oxidizer mass flux to study the effect of the flow divergence on heat transfer distribution over the fuel surface. Some experimental firing test data are presented, and, under the hypothesis that fuel regression rate and surface heat flux are proportional, the measured fuel consumption axial profiles are compared with the predicted surface heat flux showing fairly good agreement, which allowed validating the employed design approach. Finally an optimized injector design is proposed.

A Hybrid Multiobjective Evolutionary Approach for Flexible Job-Shop Scheduling Problems

Directory of Open Access Journals (Sweden)

Jian Xiong

2012-01-01

Full Text Available This paper addresses multiobjective flexible job-shop scheduling problem (FJSP with three simultaneously considered objectives: minimizing makespan, minimizing total workload, and minimizing maximal workload. A hybrid multiobjective evolutionary approach (H-MOEA is developed to solve the problem. According to the characteristic of FJSP, a modified crowding distance measure is introduced to maintain the diversity of individuals. In the proposed H-MOEA, well-designed chromosome representation and genetic operators are developed for FJSP. Moreover, a local search procedure based on critical path theory is incorporated in H-MOEA to improve the convergence ability of the algorithm. Experiment results on several well-known benchmark instances demonstrate the efficiency and stability of the proposed algorithm. The comparison with other recently published approaches validates that H-MOEA can obtain Pareto-optimal solutions with better quality and/or diversity.

Time-dependent mass of cosmological perturbations in the hybrid and dressed metric approaches to loop quantum cosmology

Science.gov (United States)

Elizaga Navascués, Beatriz; Martín de Blas, Daniel; Mena Marugán, Guillermo A.

2018-02-01

Loop quantum cosmology has recently been applied in order to extend the analysis of primordial perturbations to the Planck era and discuss the possible effects of quantum geometry on the cosmic microwave background. Two approaches to loop quantum cosmology with admissible ultraviolet behavior leading to predictions that are compatible with observations are the so-called hybrid and dressed metric approaches. In spite of their similarities and relations, we show in this work that the effective equations that they provide for the evolution of the tensor and scalar perturbations are somewhat different. When backreaction is neglected, the discrepancy appears only in the time-dependent mass term of the corresponding field equations. We explain the origin of this difference, arising from the distinct quantization procedures. Besides, given the privileged role that the big bounce plays in loop quantum cosmology, e.g. as a natural instant of time to set initial conditions for the perturbations, we also analyze the positivity of the time-dependent mass when this bounce occurs. We prove that the mass of the tensor perturbations is positive in the hybrid approach when the kinetic contribution to the energy density of the inflaton dominates over its potential, as well as for a considerably large sector of backgrounds around that situation, while this mass is always nonpositive in the dressed metric approach. Similar results are demonstrated for the scalar perturbations in a sector of background solutions that includes the kinetically dominated ones; namely, the mass then is positive for the hybrid approach, whereas it typically becomes negative in the dressed metric case. More precisely, this last statement is strictly valid when the potential is quadratic for values of the inflaton mass that are phenomenologically favored.

A hybrid simulation approach for integrating safety behavior into construction planning: An earthmoving case study.

Science.gov (United States)

Goh, Yang Miang; Askar Ali, Mohamed Jawad

2016-08-01

One of the key challenges in improving construction safety and health is the management of safety behavior. From a system point of view, workers work unsafely due to system level issues such as poor safety culture, excessive production pressure, inadequate allocation of resources and time and lack of training. These systemic issues should be eradicated or minimized during planning. However, there is a lack of detailed planning tools to help managers assess the impact of their upstream decisions on worker safety behavior. Even though simulation had been used in construction planning, the review conducted in this study showed that construction safety management research had not been exploiting the potential of simulation techniques. Thus, a hybrid simulation framework is proposed to facilitate integration of safety management considerations into construction activity simulation. The hybrid framework consists of discrete event simulation (DES) as the core, but heterogeneous, interactive and intelligent (able to make decisions) agents replace traditional entities and resources. In addition, some of the cognitive processes and physiological aspects of agents are captured using system dynamics (SD) approach. The combination of DES, agent-based simulation (ABS) and SD allows a more "natural" representation of the complex dynamics in construction activities. The proposed hybrid framework was demonstrated using a hypothetical case study. In addition, due to the lack of application of factorial experiment approach in safety management simulation, the case study demonstrated sensitivity analysis and factorial experiment to guide future research. Copyright © 2015 Elsevier Ltd. All rights reserved.

OPTIMISATION OF BUFFER SIZE FOR ENHANCING QOS OF VIDEO TRAFFIC USING CROSS LAYERED HYBRID TRANSPORT LAYER PROTOCOL APPROACH

Directory of Open Access Journals (Sweden)

S. Matilda

2011-03-01

Full Text Available Video streaming is gaining importance, with the wide popularity of multimedia rich applications in the Internet. Video streams are delay sensitive and require seamless flow for continuous visualization. Properly designed buffers offer a solution to queuing delay. The diagonally opposite QoS metrics associated with video traffic poses an optimization problem, in the design of buffers. This paper is a continuation of our previous work [1] and deals with the design of buffers. It aims at finding the optimum buffer size for enhancing QoS offered to video traffic. Network-centric QoS provisioning approach, along with hybrid transport layer protocol approach is adopted, to arrive at an optimum size which is independent of RTT. In this combinational approach, buffers of routers and end devices are designed to satisfy the various QoS parameters at the transport layer. OPNET Modeler is used to simulate environments for testing the design. Based on the results of simulation it is evident that the hybrid transport layer protocol approach is best suited for transmitting video traffic as it supports the economical design.

Hybrid discrete PSO and OPF approach for optimization of biomass fueled micro-scale energy system

International Nuclear Information System (INIS)

Gómez-González, M.; López, A.; Jurado, F.

2013-01-01

Highlights: ► Method to determine the optimal location and size of biomass power plants. ► The proposed approach is a hybrid of PSO algorithm and optimal power flow. ► Comparison among the proposed algorithm and other methods. ► Computational costs are enough lower than that required for exhaustive search. - Abstract: This paper addresses generation of electricity in the specific aspect of finding the best location and sizing of biomass fueled gas micro-turbine power plants, taking into account the variables involved in the problem, such as the local distribution of biomass resources, biomass transportation and extraction costs, operation and maintenance costs, power losses costs, network operation costs, and technical constraints. In this paper a hybrid method is introduced employing discrete particle swarm optimization and optimal power flow. The approach can be applied to search the best sites and capacities to connect biomass fueled gas micro-turbine power systems in a distribution network among a large number of potential combinations and considering the technical constraints of the network. A fair comparison among the proposed algorithm and other methods is performed.

Optimal planning approaches with multiple impulses for rendezvous based on hybrid genetic algorithm and control method

Directory of Open Access Journals (Sweden)

JingRui Zhang

2015-03-01

Full Text Available In this article, we focus on safe and effective completion of a rendezvous and docking task by looking at planning approaches and control with fuel-optimal rendezvous for a target spacecraft running on a near-circular reference orbit. A variety of existent practical path constraints are considered, including the constraints of field of view, impulses, and passive safety. A rendezvous approach is calculated by using a hybrid genetic algorithm with those constraints. Furthermore, a control method of trajectory tracking is adopted to overcome the external disturbances. Based on Clohessy–Wiltshire equations, we first construct the mathematical model of optimal planning approaches of multiple impulses with path constraints. Second, we introduce the principle of hybrid genetic algorithm with both stronger global searching ability and local searching ability. We additionally explain the application of this algorithm in the problem of trajectory planning. Then, we give three-impulse simulation examples to acquire an optimal rendezvous trajectory with the path constraints presented in this article. The effectiveness and applicability of the tracking control method are verified with the optimal trajectory above as control objective through the numerical simulation.

Hybrid Engine Powered City Car: Fuzzy Controlled Approach

Science.gov (United States)

Rahman, Ataur; Mohiuddin, AKM; Hawlader, MNA; Ihsan, Sany

2017-03-01

This study describes a fuzzy controlled hybrid engine powered car. The car is powered by the lithium ion battery capacity of 1000 Wh is charged by the 50 cc hybrid engine and power regenerative mode. The engine is operated with lean mixture at 3000 rpm to charge the battery. The regenerative mode that connects with the engine generates electrical power of 500-600 W for the deceleration of car from 90 km/h to 20 km/h. The regenerated electrical power has been used to power the air-conditioning system and to meet the other electrical power. The battery power only used to propel the car. The regenerative power also found charging the battery for longer operation about 40 minutes and more. The design flexibility of this vehicle starts with whole-vehicle integration based on radical light weighting, drag reduction, and accessory efficiency. The energy efficient hybrid engine cut carbon dioxide (CO2) and nitrogen oxides (N2O) emission about 70-80% as the loads on the crankshaft such as cam-follower and its associated rotating components are replaced by electromagnetic systems, and the flywheel, alternator and starter motor are replaced by a motor generator. The vehicle was tested and found that it was able to travel 70 km/litre with the power of hybrid engine.

A promising hybrid approach to SPECT attenuation correction

International Nuclear Information System (INIS)

Lewis, N.H.; Faber, T.L.; Corbett, J.R.; Stokely, E.M.

1984-01-01

Most methods for attenuation compensation in SPECT either rely on the assumption of uniform attenuation, or use slow iteration to achieve accuracy. However, hybrid methods that combine iteration with simple multiplicative correction can accommodate nonuniform attenuation, and such methods converge faster than other iterative techniques. The authors evaluated two such methods, which differ in use of a damping factor to control convergence. Both uniform and nonuniform attenuation were modeled, using simulated and phantom data for a rotating gamma camera. For simulations done with 360 0 data and the correct attenuation map, activity levels were reconstructed to within 5% of the correct values after one iteration. Using 180 0 data, reconstructed levels in regions representing lesion and background were within 5% of the correct values in three iterations; however, further iterations were needed to eliminate the characteristic streak artifacts. The damping factor had little effect on 360 0 reconstruction, but was needed for convergence with 180 0 data. For both cold- and hot-lesion models, image contrast was better from the hybrid methods than from the simpler geometric-mean corrector. Results from the hybrid methods were comparable to those obtained using the conjugate-gradient iterative method, but required 50-100% less reconstruction time. The relative speed of the hybrid methods, and their accuracy in reconstructing photon activity in the presence of nonuniform attenuation, make them promising tools for quantitative SPECT reconstruction

A Game-Theoretic approach to Fault Diagnosis of Hybrid Systems

Directory of Open Access Journals (Sweden)

Davide Bresolin

2011-06-01

Full Text Available Physical systems can fail. For this reason the problem of identifying and reacting to faults has received a large attention in the control and computer science communities. In this paper we study the fault diagnosis problem for hybrid systems from a game-theoretical point of view. A hybrid system is a system mixing continuous and discrete behaviours that cannot be faithfully modeled neither by using a formalism with continuous dynamics only nor by a formalism including only discrete dynamics. We use the well known framework of hybrid automata for modeling hybrid systems, and we define a Fault Diagnosis Game on them, using two players: the environment and the diagnoser. The environment controls the evolution of the system and chooses whether and when a fault occurs. The diagnoser observes the external behaviour of the system and announces whether a fault has occurred or not. Existence of a winning strategy for the diagnoser implies that faults can be detected correctly, while computing such a winning strategy corresponds to implement a diagnoser for the system. We will show how to determine the existence of a winning strategy, and how to compute it, for some decidable classes of hybrid automata like o-minimal hybrid automata.

A hybrid regional approach to model discharge at multiple sub-basins within the Calapooia Watershed, Oregon, USA

Science.gov (United States)

Modeling is a useful tool for quantifying ecosystem services and understanding their temporal dynamics. Here we describe a hybrid regional modeling approach for sub-basins of the Calapooia watershed that incorporates both a precipitation-runoff model and an indexed regression mo...

Dry Port Location Problem: A Hybrid Multi-Criteria Approach

Directory of Open Access Journals (Sweden)

BENTALEB Fatimazahra

2016-03-01

Full Text Available Choosing a location for a dry port is a problem which becomes more essential and crucial. This study deals with the problem of locating dry ports. On this matter, a model combining multi-criteria (MACBETH and mono-criteria (BARYCENTER methods to find a solution to dry port location problem has been proposed. In the first phase, a systematic literature review was carried out on dry port location problem and then a methodological classification was presented for this research. In the second phase, a hybrid multi-criteria approach was developed in order to determine the best dry port location taking different criteria into account. A Computational practice and a qualitative analysis from a case study in the Moroccan context have been provided. The results show that the optimal location is very convenient with the geographical region and the government policies.

A hybrid approach to solving the problem of design of nuclear fuel cells

International Nuclear Information System (INIS)

Montes T, J. L.; Perusquia del C, R.; Ortiz S, J. J.; Castillo, A.

2015-09-01

An approach to solving the problem of fuel cell design for BWR power reactor is presented. For this purpose the hybridization of a method based in heuristic knowledge rules called S15 and the advantages of a meta-heuristic method is proposed. The synergy of potentialities of both techniques allows finding solutions of more quality. The quality of each solution is obtained through a multi-objective function formed from the main cell parameters that are provided or obtained during the simulation with the CASMO-4 code. To evaluate this alternative of solution nuclear fuel cells of reference of nuclear power plant of Laguna Verde were used. The results show that in a systematic way the results improve when both methods are coupled. As a result of the hybridization process of the mentioned techniques an improvement is achieved in a range of 2% with regard to the achieved results in an independent way by the S15 method. (Author)

HyDEn: A Hybrid Steganocryptographic Approach for Data Encryption Using Randomized Error-Correcting DNA Codes

Directory of Open Access Journals (Sweden)

Dan Tulpan

2013-01-01

Full Text Available This paper presents a novel hybrid DNA encryption (HyDEn approach that uses randomized assignments of unique error-correcting DNA Hamming code words for single characters in the extended ASCII set. HyDEn relies on custom-built quaternary codes and a private key used in the randomized assignment of code words and the cyclic permutations applied on the encoded message. Along with its ability to detect and correct errors, HyDEn equals or outperforms existing cryptographic methods and represents a promising in silico DNA steganographic approach.

Hybridization success is largely limited to homoploid Prunus hybrids: a multidisciplinary approach

Czech Academy of Sciences Publication Activity Database

Macková, L.; Vít, Petr; Ďurišová, Ľ.; Eliáš, P. Jr.; Urfus, T.

2017-01-01

Roč. 303, č. 4 (2017), s. 481-495 ISSN 0378-2697 Institutional support: RVO:67985939 Keywords : absolute genome size * interspecific hybridization * embryology Subject RIV: EF - Botanics OBOR OECD: Plant sciences, botany Impact factor: 1.239, year: 2016

A Quantum Hybrid PSO Combined with Fuzzy k-NN Approach to Feature Selection and Cell Classification in Cervical Cancer Detection

Directory of Open Access Journals (Sweden)

Abdullah M. Iliyasu

2017-12-01

Full Text Available A quantum hybrid (QH intelligent approach that blends the adaptive search capability of the quantum-behaved particle swarm optimisation (QPSO method with the intuitionistic rationality of traditional fuzzy k-nearest neighbours (Fuzzy k-NN algorithm (known simply as the Q-Fuzzy approach is proposed for efficient feature selection and classification of cells in cervical smeared (CS images. From an initial multitude of 17 features describing the geometry, colour, and texture of the CS images, the QPSO stage of our proposed technique is used to select the best subset features (i.e., global best particles that represent a pruned down collection of seven features. Using a dataset of almost 1000 images, performance evaluation of our proposed Q-Fuzzy approach assesses the impact of our feature selection on classification accuracy by way of three experimental scenarios that are compared alongside two other approaches: the All-features (i.e., classification without prior feature selection and another hybrid technique combining the standard PSO algorithm with the Fuzzy k-NN technique (P-Fuzzy approach. In the first and second scenarios, we further divided the assessment criteria in terms of classification accuracy based on the choice of best features and those in terms of the different categories of the cervical cells. In the third scenario, we introduced new QH hybrid techniques, i.e., QPSO combined with other supervised learning methods, and compared the classification accuracy alongside our proposed Q-Fuzzy approach. Furthermore, we employed statistical approaches to establish qualitative agreement with regards to the feature selection in the experimental scenarios 1 and 3. The synergy between the QPSO and Fuzzy k-NN in the proposed Q-Fuzzy approach improves classification accuracy as manifest in the reduction in number cell features, which is crucial for effective cervical cancer detection and diagnosis.

Cardiac hybrid imaging

Energy Technology Data Exchange (ETDEWEB)

Gaemperli, Oliver [University Hospital Zurich, Cardiac Imaging, Zurich (Switzerland); University Hospital Zurich, Nuclear Cardiology, Cardiovascular Center, Zurich (Switzerland); Kaufmann, Philipp A. [University Hospital Zurich, Cardiac Imaging, Zurich (Switzerland); Alkadhi, Hatem [University Hospital Zurich, Institute of Diagnostic and Interventional Radiology, Zurich (Switzerland)

2014-05-15

Hybrid cardiac single photon emission computed tomography (SPECT)/CT imaging allows combined assessment of anatomical and functional aspects of cardiac disease. In coronary artery disease (CAD), hybrid SPECT/CT imaging allows detection of coronary artery stenosis and myocardial perfusion abnormalities. The clinical value of hybrid imaging has been documented in several subsets of patients. In selected groups of patients, hybrid imaging improves the diagnostic accuracy to detect CAD compared to the single imaging techniques. Additionally, this approach facilitates functional interrogation of coronary stenoses and guidance with regard to revascularization procedures. Moreover, the anatomical information obtained from CT coronary angiography or coronary artery calcium scores (CACS) adds prognostic information over perfusion data from SPECT. The use of cardiac hybrid imaging has been favoured by the dissemination of dedicated hybrid systems and the release of dedicated image fusion software, which allow simple patient throughput for hybrid SPECT/CT studies. Further technological improvements such as more efficient detector technology to allow for low-radiation protocols, ultra-fast image acquisition and improved low-noise image reconstruction algorithms will be instrumental to further promote hybrid SPECT/CT in research and clinical practice. (orig.)

Hybrid Approximate Dynamic Programming Approach for Dynamic Optimal Energy Flow in the Integrated Gas and Power Systems

DEFF Research Database (Denmark)

Shuai, Hang; Ai, Xiaomeng; Wen, Jinyu

2017-01-01

This paper proposes a hybrid approximate dynamic programming (ADP) approach for the multiple time-period optimal power flow in integrated gas and power systems. ADP successively solves Bellman's equation to make decisions according to the current state of the system. So, the updated near future...

Deterministic linear-optics quantum computing based on a hybrid approach

International Nuclear Information System (INIS)

Lee, Seung-Woo; Jeong, Hyunseok

2014-01-01

We suggest a scheme for all-optical quantum computation using hybrid qubits. It enables one to efficiently perform universal linear-optical gate operations in a simple and near-deterministic way using hybrid entanglement as off-line resources

Deterministic linear-optics quantum computing based on a hybrid approach

Energy Technology Data Exchange (ETDEWEB)

Lee, Seung-Woo; Jeong, Hyunseok [Center for Macroscopic Quantum Control, Department of Physics and Astronomy, Seoul National University, Seoul, 151-742 (Korea, Republic of)

2014-12-04

We suggest a scheme for all-optical quantum computation using hybrid qubits. It enables one to efficiently perform universal linear-optical gate operations in a simple and near-deterministic way using hybrid entanglement as off-line resources.

Targeted and untargeted high resolution mass approach for a putative profiling of glycosylated simple phenols in hybrid grapes.

Science.gov (United States)

Barnaba, Chiara; Dellacassa, Eduardo; Nicolini, Giorgio; Giacomelli, Mattia; Roman Villegas, Tomas; Nardin, Tiziana; Larcher, Roberto

2017-08-01

Vitis vinifera is one of the most widespread grapevines around the world representing the raw material for high quality wine production. The availability of more resistant interspecific hybrid vine varieties, developed from crosses between Vitis vinifera and other Vitis species, has generated much interest, also due to the low environmental effect of production. However, hybrid grape wine composition and varietal differences between interspecific hybrids have not been well defined, particularly for the simple phenols profile. The dynamic of these phenols in wines, where the glycosylated forms can be transformed into the free ones during winemaking, also raises an increasing health interest by their role as antoxidants in wine consumers. In this work an on-line SPE clean-up device, to reduce matrix interference, was combined with ultra-high liquid chromatography-high resolution mass spectrometry in order to increase understanding of the phenolic composition of hybrid grape varieties. Specifically, the phenolic composition of 4 hybrid grape varieties (red, Cabernet Cantor and Prior; white, Muscaris and Solaris) and 2 European grape varieties (red, Merlot; white, Chardonnay) was investigated, focusing on free and glycosidically bound simple phenols and considering compound distribution in pulp, skin, seeds and wine. Using a targeted approach 53 free simple phenols and 7 glycosidic precursors were quantified with quantification limits ranging from 0.001 to 2mgKg -1 and calibration R 2 of 0.99 for over 86% of compounds. The untargeted approach made it possible to tentatively identify 79 glycosylated precursors of selected free simple phenols in the form of -hexoside (N=30), -pentoside (21), -hexoside-hexoside (17), -hexoside-pentoside (4), -pentoside-hexoside (5) and -pentoside-pentoside (2) derivatives on the basis of accurate mass, isotopic pattern and MS/MS fragmentation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Hybrid simulation models of production networks

CERN Document Server

Kouikoglou, Vassilis S

2001-01-01

This book is concerned with a most important area of industrial production, that of analysis and optimization of production lines and networks using discrete-event models and simulation. The book introduces a novel approach that combines analytic models and discrete-event simulation. Unlike conventional piece-by-piece simulation, this method observes a reduced number of events between which the evolution of the system is tracked analytically. Using this hybrid approach, several models are developed for the analysis of production lines and networks. The hybrid approach combines speed and accuracy for exceptional analysis of most practical situations. A number of optimization problems, involving buffer design, workforce planning, and production control, are solved through the use of hybrid models.

Optical hybrid quantum teleportation and its applications

Science.gov (United States)

Takeda, Shuntaro; Okada, Masanori; Furusawa, Akira

2017-08-01

Quantum teleportation, a transfer protocol of quantum states, is the essence of many sophisticated quantum information protocols. There have been two complementary approaches to optical quantum teleportation: discrete variables (DVs) and continuous variables (CVs). However, both approaches have pros and cons. Here we take a "hybrid" approach to overcome the current limitations: CV quantum teleportation of DVs. This approach enabled the first realization of deterministic quantum teleportation of photonic qubits without post-selection. We also applied the hybrid scheme to several experiments, including entanglement swapping between DVs and CVs, conditional CV teleportation of single photons, and CV teleportation of qutrits. We are now aiming at universal, scalable, and fault-tolerant quantum computing based on these hybrid technologies.

Combination of Biorthogonal Wavelet Hybrid Kernel OCSVM with Feature Weighted Approach Based on EVA and GRA in Financial Distress Prediction

Directory of Open Access Journals (Sweden)

Chao Huang

2014-01-01

Full Text Available Financial distress prediction plays an important role in the survival of companies. In this paper, a novel biorthogonal wavelet hybrid kernel function is constructed by combining linear kernel function with biorthogonal wavelet kernel function. Besides, a new feature weighted approach is presented based on economic value added (EVA and grey relational analysis (GRA. Considering the imbalance between financially distressed companies and normal ones, the feature weighted one-class support vector machine based on biorthogonal wavelet hybrid kernel (BWH-FWOCSVM is further put forward for financial distress prediction. The empirical study with real data from the listed companies on Growth Enterprise Market (GEM in China shows that the proposed approach has good performance.

Identification and Prediction of Large Pedestrian Flow in Urban Areas Based on a Hybrid Detection Approach

Directory of Open Access Journals (Sweden)

Kaisheng Zhang

2016-12-01

Full Text Available Recently, population density has grown quickly with the increasing acceleration of urbanization. At the same time, overcrowded situations are more likely to occur in populous urban areas, increasing the risk of accidents. This paper proposes a synthetic approach to recognize and identify the large pedestrian flow. In particular, a hybrid pedestrian flow detection model was constructed by analyzing real data from major mobile phone operators in China, including information from smartphones and base stations (BS. With the hybrid model, the Log Distance Path Loss (LDPL model was used to estimate the pedestrian density from raw network data, and retrieve information with the Gaussian Progress (GP through supervised learning. Temporal-spatial prediction of the pedestrian data was carried out with Machine Learning (ML approaches. Finally, a case study of a real Central Business District (CBD scenario in Shanghai, China using records of millions of cell phone users was conducted. The results showed that the new approach significantly increases the utility and capacity of the mobile network. A more reasonable overcrowding detection and alert system can be developed to improve safety in subway lines and other hotspot landmark areas, such as the Bundle, People’s Square or Disneyland, where a large passenger flow generally exists.

Towards a comprehensive theory for He II: I. A zero-temperature hybrid approach

International Nuclear Information System (INIS)

Ghassib, H.B.; Khudeir, A.M.

1982-09-01

A simple hybrid approach based on a gauge theory as well as a Hartree formalism, is presented for He II at zero temperature. Although this is intended to be merely a first step in an all-embracing theory, it already resolves quite neatly several old inconsistencies and corrects a few errors. As an illustration of its feasibility, a crude but instructive calculation is performed for the static structure factor of the system at low momentum transfers. A number of planned extensions and generalizations are outlined. (author)

Deducing hybrid performance from parental metabolic profiles of young primary roots of maize by using a multivariate diallel approach.

Directory of Open Access Journals (Sweden)

Kristen Feher

Full Text Available Heterosis, the greater vigor of hybrids compared to their parents, has been exploited in maize breeding for more than 100 years to produce ever better performing elite hybrids of increased yield. Despite extensive research, the underlying mechanisms shaping the extent of heterosis are not well understood, rendering the process of selecting an optimal set of parental lines tedious. This study is based on a dataset consisting of 112 metabolite levels in young roots of four parental maize inbred lines and their corresponding twelve hybrids, along with the roots' biomass as a heterotic trait. Because the parental biomass is a poor predictor for hybrid biomass, we established a model framework to deduce the biomass of the hybrid from metabolite profiles of its parental lines. In the proposed framework, the hybrid metabolite levels are expressed relative to the parental levels by incorporating the standard concept of additivity/dominance, which we name the Combined Relative Level (CRL. Our modeling strategy includes a feature selection step on the parental levels which are demonstrated to be predictive of CRL across many hybrid metabolites. We demonstrate that these selected parental metabolites are further predictive of hybrid biomass. Our approach directly employs the diallel structure in a multivariate fashion, whereby we attempt to not only predict macroscopic phenotype (biomass, but also molecular phenotype (metabolite profiles. Therefore, our study provides the first steps for further investigations of the genetic determinants to metabolism and, ultimately, growth. Finally, our success on the small-scale experiments implies a valid strategy for large-scale experiments, where parental metabolite profiles may be used together with profiles of selected hybrids as a training set to predict biomass of all possible hybrids.

Hybrid Air Quality Modeling Approach for use in the Hear-road Exposures to Urban air pollutant Study(NEXUS)

Science.gov (United States)

The paper presents a hybrid air quality modeling approach and its application in NEXUS in order to provide spatial and temporally varying exposure estimates and identification of the mobile source contribution to the total pollutant exposure. Model-based exposure metrics, associa...

A hybrid filtering approach for storage optimization in main-memory cloud database

Directory of Open Access Journals (Sweden)

Ghada M. Afify

2015-11-01

Full Text Available Enterprises and cloud service providers face dramatic increase in the amount of data stored in private and public clouds. Thus, data storage costs are growing hastily because they use only one single high-performance storage tier for storing all cloud data. There’s considerable potential to reduce cloud costs by classifying data into active (hot and inactive (cold. In the main-memory databases research, recent works focus on approaches to identify hot/cold data. Most of these approaches track tuple accesses to identify hot/cold tuples. In contrast, we introduce a novel Hybrid Filtering Approach (HFA that tracks both tuples and columns accesses in main-memory databases. Our objective is to enhance the performance in terms of three dimensions: storage space, query elapsed time and CPU time. In order to validate the effectiveness of our approach, we realized its concrete implementation on Hekaton, a SQL’s server memory-optimized engine using the well-known TPC-H benchmark. Experimental results show that the proposed HFA outperforms Hekaton approach in respect of all performance dimensions. In specific, HFA reduces the storage space by average of 44–96%, reduces the query elapsed time by average of 25–93% and reduces the CPU time by average of 31–97% compared to the traditional database approach.

Hybrid x-space: a new approach for MPI reconstruction.

Science.gov (United States)

Tateo, A; Iurino, A; Settanni, G; Andrisani, A; Stifanelli, P F; Larizza, P; Mazzia, F; Mininni, R M; Tangaro, S; Bellotti, R

2016-06-07

Magnetic particle imaging (MPI) is a new medical imaging technique capable of recovering the distribution of superparamagnetic particles from their measured induced signals. In literature there are two main MPI reconstruction techniques: measurement-based (MB) and x-space (XS). The MB method is expensive because it requires a long calibration procedure as well as a reconstruction phase that can be numerically costly. On the other side, the XS method is simpler than MB but the exact knowledge of the field free point (FFP) motion is essential for its implementation. Our simulation work focuses on the implementation of a new approach for MPI reconstruction: it is called hybrid x-space (HXS), representing a combination of the previous methods. Specifically, our approach is based on XS reconstruction because it requires the knowledge of the FFP position and velocity at each time instant. The difference with respect to the original XS formulation is how the FFP velocity is computed: we estimate it from the experimental measurements of the calibration scans, typical of the MB approach. Moreover, a compressive sensing technique is applied in order to reduce the calibration time, setting a fewer number of sampling positions. Simulations highlight that HXS and XS methods give similar results. Furthermore, an appropriate use of compressive sensing is crucial for obtaining a good balance between time reduction and reconstructed image quality. Our proposal is suitable for open geometry configurations of human size devices, where incidental factors could make the currents, the fields and the FFP trajectory irregular.

Detection of cardiovascular anomalies: Hybrid systems approach

KAUST Repository

Ledezma, Fernando; Laleg-Kirati, Taous-Meriem

2012-01-01

In this paper, we propose a hybrid interpretation of the cardiovascular system. Based on a model proposed by Simaan et al. (2009), we study the problem of detecting cardiovascular anomalies that can be caused by variations in some physiological

Genomic networks of hybrid sterility.

Science.gov (United States)

Turner, Leslie M; White, Michael A; Tautz, Diethard; Payseur, Bret A

2014-02-01

Hybrid dysfunction, a common feature of reproductive barriers between species, is often caused by negative epistasis between loci ("Dobzhansky-Muller incompatibilities"). The nature and complexity of hybrid incompatibilities remain poorly understood because identifying interacting loci that affect complex phenotypes is difficult. With subspecies in the early stages of speciation, an array of genetic tools, and detailed knowledge of reproductive biology, house mice (Mus musculus) provide a model system for dissecting hybrid incompatibilities. Male hybrids between M. musculus subspecies often show reduced fertility. Previous studies identified loci and several X chromosome-autosome interactions that contribute to sterility. To characterize the genetic basis of hybrid sterility in detail, we used a systems genetics approach, integrating mapping of gene expression traits with sterility phenotypes and QTL. We measured genome-wide testis expression in 305 male F2s from a cross between wild-derived inbred strains of M. musculus musculus and M. m. domesticus. We identified several thousand cis- and trans-acting QTL contributing to expression variation (eQTL). Many trans eQTL cluster into eleven 'hotspots,' seven of which co-localize with QTL for sterility phenotypes identified in the cross. The number and clustering of trans eQTL-but not cis eQTL-were substantially lower when mapping was restricted to a 'fertile' subset of mice, providing evidence that trans eQTL hotspots are related to sterility. Functional annotation of transcripts with eQTL provides insights into the biological processes disrupted by sterility loci and guides prioritization of candidate genes. Using a conditional mapping approach, we identified eQTL dependent on interactions between loci, revealing a complex system of epistasis. Our results illuminate established patterns, including the role of the X chromosome in hybrid sterility. The integrated mapping approach we employed is applicable in a broad

A novel approach identifying hybrid sterility QTL on the autosomes of Drosophila simulans and D. mauritiana.

Science.gov (United States)

Dickman, Christopher T D; Moehring, Amanda J

2013-01-01

When species interbreed, the hybrid offspring that are produced are often sterile. If only one hybrid sex is sterile, it is almost always the heterogametic (XY or ZW) sex. Taking this trend into account, the predominant model used to explain the genetic basis of F1 sterility involves a deleterious interaction between recessive sex-linked loci from one species and dominant autosomal loci from the other species. This model is difficult to evaluate, however, as only a handful of loci influencing interspecies hybrid sterility have been identified, and their autosomal genetic interactors have remained elusive. One hindrance to their identification has been the overwhelming effect of the sex chromosome in mapping studies, which could 'mask' the ability to accurately map autosomal factors. Here, we use a novel approach employing attached-X chromosomes to create reciprocal backcross interspecies hybrid males that have a non-recombinant sex chromosome and recombinant autosomes. The heritable variation in phenotype is thus solely caused by differences in the autosomes, thereby allowing us to accurately identify the number and location of autosomal sterility loci. In one direction of backcross, all males were sterile, indicating that sterility could be entirely induced by the sex chromosome complement in these males. In the other direction, we identified nine quantitative trait loci that account for a surprisingly large amount (56%) of the autosome-induced phenotypic variance in sterility, with a large contribution of autosome-autosome epistatic interactions. These loci are capable of acting dominantly, and thus could contribute to F1 hybrid sterility.

A novel approach identifying hybrid sterility QTL on the autosomes of Drosophila simulans and D. mauritiana.

Directory of Open Access Journals (Sweden)

Christopher T D Dickman

Full Text Available When species interbreed, the hybrid offspring that are produced are often sterile. If only one hybrid sex is sterile, it is almost always the heterogametic (XY or ZW sex. Taking this trend into account, the predominant model used to explain the genetic basis of F1 sterility involves a deleterious interaction between recessive sex-linked loci from one species and dominant autosomal loci from the other species. This model is difficult to evaluate, however, as only a handful of loci influencing interspecies hybrid sterility have been identified, and their autosomal genetic interactors have remained elusive. One hindrance to their identification has been the overwhelming effect of the sex chromosome in mapping studies, which could 'mask' the ability to accurately map autosomal factors. Here, we use a novel approach employing attached-X chromosomes to create reciprocal backcross interspecies hybrid males that have a non-recombinant sex chromosome and recombinant autosomes. The heritable variation in phenotype is thus solely caused by differences in the autosomes, thereby allowing us to accurately identify the number and location of autosomal sterility loci. In one direction of backcross, all males were sterile, indicating that sterility could be entirely induced by the sex chromosome complement in these males. In the other direction, we identified nine quantitative trait loci that account for a surprisingly large amount (56% of the autosome-induced phenotypic variance in sterility, with a large contribution of autosome-autosome epistatic interactions. These loci are capable of acting dominantly, and thus could contribute to F1 hybrid sterility.

Electrical potential-assisted DNA hybridization. How to mitigate electrostatics for surface DNA hybridization.

Science.gov (United States)

Tymoczko, Jakub; Schuhmann, Wolfgang; Gebala, Magdalena

2014-12-24

Surface-confined DNA hybridization reactions are sensitive to the number and identity of DNA capture probes and experimental conditions such as the nature and the ionic strength of the electrolyte solution. When the surface probe density is high or the concentration of bulk ions is much lower than the concentration of ions within the DNA layer, hybridization is significantly slowed down or does not proceed at all. However, high-density DNA monolayers are attractive for designing high-sensitivity DNA sensors. Thus, circumventing sluggish DNA hybridization on such interfaces allows a high surface concentration of target DNA and improved signal/noise ratio. We present potential-assisted hybridization as a strategy in which an external voltage is applied to the ssDNA-modified interface during the hybridization process. Results show that a significant enhancement of hybridization can be achieved using this approach.

Optimizing Thermal-Elastic Properties of C/C–SiC Composites Using a Hybrid Approach and PSO Algorithm

Science.gov (United States)

Xu, Yingjie; Gao, Tian

2016-01-01

Carbon fiber-reinforced multi-layered pyrocarbon–silicon carbide matrix (C/C–SiC) composites are widely used in aerospace structures. The complicated spatial architecture and material heterogeneity of C/C–SiC composites constitute the challenge for tailoring their properties. Thus, discovering the intrinsic relations between the properties and the microstructures and sequentially optimizing the microstructures to obtain composites with the best performances becomes the key for practical applications. The objective of this work is to optimize the thermal-elastic properties of unidirectional C/C–SiC composites by controlling the multi-layered matrix thicknesses. A hybrid approach based on micromechanical modeling and back propagation (BP) neural network is proposed to predict the thermal-elastic properties of composites. Then, a particle swarm optimization (PSO) algorithm is interfaced with this hybrid model to achieve the optimal design for minimizing the coefficient of thermal expansion (CTE) of composites with the constraint of elastic modulus. Numerical examples demonstrate the effectiveness of the proposed hybrid model and optimization method. PMID:28773343

Integrated approach for fusion multi-physics coupled analyses based on hybrid CAD and mesh geometries

Energy Technology Data Exchange (ETDEWEB)

Qiu, Yuefeng, E-mail: yuefeng.qiu@kit.edu; Lu, Lei; Fischer, Ulrich

2015-10-15

Highlights: • Integrated approach for neutronics, thermal and structural analyses was developed. • MCNP5/6, TRIPOLI-4 were coupled with CFX, Fluent and ANSYS Workbench. • A novel meshing approach has been proposed for describing MC geometry. - Abstract: Coupled multi-physics analyses on fusion reactor devices require high-fidelity neutronic models, and flexible, accurate data exchanging between various calculation codes. An integrated coupling approach has been developed to enable the conversion of CAD, mesh, or hybrid geometries for Monte Carlo (MC) codes MCNP5/6, TRIPOLI-4, and translation of nuclear heating data for CFD codes Fluent, CFX and structural mechanical software ANSYS Workbench. The coupling approach has been implemented based on SALOME platform with CAD modeling, mesh generation and data visualization capabilities. A novel meshing approach has been developed for generating suitable meshes for MC geometry descriptions. The coupling approach has been concluded to be reliable and efficient after verification calculations of several application cases.

“ELEPHANT TRUNK” AND ENDOVASCULAR STENTGRAFTING – A HYBRID APPROACH TO THE TREATMENT OF EXTENSIVE THORACIC AORTIC ANEURYSM

Directory of Open Access Journals (Sweden)

Tomáš Holubec

2013-01-01

Full Text Available A hybrid approach to elephant trunk technique for treatment of thoracic aortic aneurysms combines a conventional surgical and endovascular therapy. Compared to surgery alone, there is a presumption that mortality and morbidity is reduced. We present a case report of a 42-year-old man with a giant aneurysm of the entire thoracic aorta, significant aortic and tricuspid regurgitation and ventricular septum defect. The patient underwent multiple consecutive operations and interventions having, among others, finally replaced the entire thoracic aorta with the use of the hybrid elephant trunk technique.

A Practical Approach to Improve Optical Channel Utilization Period for Hybrid FSO/RF Systems

Directory of Open Access Journals (Sweden)

Ahmet Akbulut

2014-01-01

Full Text Available In hybrid FSO/RF systems, mostly a hard switching mechanism is preferred in case of the FSO signal level falls below to the predefined threshold. In this work, a computationally simple approach is proposed to increase the utilization of the FSO channels bandwidth advantage. For the channel, clear air conditions have been supposed with the atmospheric turbulence. In this approach, FSO bit rate is adaptively changed to achieve desired BER performance. An IM/DD modulation, OOK (NRZ format has been used to show the benefit of the proposed method. Furthermore, to be more realistic with respect to the atmospheric turbulence variations within a day, some experimental observations have been followed up.

A hybrid least squares support vector machines and GMDH approach for river flow forecasting

Science.gov (United States)

Samsudin, R.; Saad, P.; Shabri, A.

2010-06-01

This paper proposes a novel hybrid forecasting model, which combines the group method of data handling (GMDH) and the least squares support vector machine (LSSVM), known as GLSSVM. The GMDH is used to determine the useful input variables for LSSVM model and the LSSVM model which works as time series forecasting. In this study the application of GLSSVM for monthly river flow forecasting of Selangor and Bernam River are investigated. The results of the proposed GLSSVM approach are compared with the conventional artificial neural network (ANN) models, Autoregressive Integrated Moving Average (ARIMA) model, GMDH and LSSVM models using the long term observations of monthly river flow discharge. The standard statistical, the root mean square error (RMSE) and coefficient of correlation (R) are employed to evaluate the performance of various models developed. Experiment result indicates that the hybrid model was powerful tools to model discharge time series and can be applied successfully in complex hydrological modeling.

Hydrogen atom as a quantum-classical hybrid system

International Nuclear Information System (INIS)

Zhan, Fei; Wu, Biao

2013-01-01

Hydrogen atom is studied as a quantum-classical hybrid system, where the proton is treated as a classical object while the electron is regarded as a quantum object. We use a well known mean-field approach to describe this hybrid hydrogen atom; the resulting dynamics for the electron and the proton is compared to their full quantum dynamics. The electron dynamics in the hybrid description is found to be only marginally different from its full quantum counterpart. The situation is very different for the proton: in the hybrid description, the proton behaves like a free particle; in the fully quantum description, the wave packet center of the proton orbits around the center of mass. Furthermore, we find that the failure to describe the proton dynamics properly can be regarded as a manifestation of the fact that there is no conservation of momentum in the mean-field hybrid approach. We expect that such a failure is a common feature for all existing approaches for quantum-classical hybrid systems of Born-Oppenheimer type.

Aerodynamic Shape Optimization Design of Wing-Body Configuration Using a Hybrid FFD-RBF Parameterization Approach

Science.gov (United States)

Liu, Yuefeng; Duan, Zhuoyi; Chen, Song

2017-10-01

Aerodynamic shape optimization design aiming at improving the efficiency of an aircraft has always been a challenging task, especially when the configuration is complex. In this paper, a hybrid FFD-RBF surface parameterization approach has been proposed for designing a civil transport wing-body configuration. This approach is simple and efficient, with the FFD technique used for parameterizing the wing shape and the RBF interpolation approach used for handling the wing body junction part updating. Furthermore, combined with Cuckoo Search algorithm and Kriging surrogate model with expected improvement adaptive sampling criterion, an aerodynamic shape optimization design system has been established. Finally, the aerodynamic shape optimization design on DLR F4 wing-body configuration has been carried out as a study case, and the result has shown that the approach proposed in this paper is of good effectiveness.

Hybrid Arrays for Chemical Sensing

Science.gov (United States)

Kramer, Kirsten E.; Rose-Pehrsson, Susan L.; Johnson, Kevin J.; Minor, Christian P.

In recent years, multisensory approaches to environment monitoring for chemical detection as well as other forms of situational awareness have become increasingly popular. A hybrid sensor is a multimodal system that incorporates several sensing elements and thus produces data that are multivariate in nature and may be significantly increased in complexity compared to data provided by single-sensor systems. Though a hybrid sensor is itself an array, hybrid sensors are often organized into more complex sensing systems through an assortment of network topologies. Part of the reason for the shift to hybrid sensors is due to advancements in sensor technology and computational power available for processing larger amounts of data. There is also ample evidence to support the claim that a multivariate analytical approach is generally superior to univariate measurements because it provides additional redundant and complementary information (Hall, D. L.; Linas, J., Eds., Handbook of Multisensor Data Fusion, CRC, Boca Raton, FL, 2001). However, the benefits of a multisensory approach are not automatically achieved. Interpretation of data from hybrid arrays of sensors requires the analyst to develop an application-specific methodology to optimally fuse the disparate sources of data generated by the hybrid array into useful information characterizing the sample or environment being observed. Consequently, multivariate data analysis techniques such as those employed in the field of chemometrics have become more important in analyzing sensor array data. Depending on the nature of the acquired data, a number of chemometric algorithms may prove useful in the analysis and interpretation of data from hybrid sensor arrays. It is important to note, however, that the challenges posed by the analysis of hybrid sensor array data are not unique to the field of chemical sensing. Applications in electrical and process engineering, remote sensing, medicine, and of course, artificial

Hybrid Approach for Biliary Interventions Employing MRI-Guided Bile Duct Puncture with Near-Real-Time Imaging

Energy Technology Data Exchange (ETDEWEB)

Wybranski, Christian, E-mail: Christian.Wybranski@uk-koeln.de [University Hospital of Cologne, Department of Diagnostic and Interventional Radiology (Germany); Pech, Maciej [Otto-von-Guericke University Medical School, Department of Radiology and Nuclear Medicine (Germany); Lux, Anke [Otto-von-Guericke University Medical School, Institute of Biometry and Medical Informatics (Germany); Ricke, Jens; Fischbach, Frank; Fischbach, Katharina [Otto-von-Guericke University Medical School, Department of Radiology and Nuclear Medicine (Germany)

2017-06-15

ObjectiveTo assess the feasibility of a hybrid approach employing MRI-guided bile duct (BD) puncture for subsequent fluoroscopy-guided biliary interventions in patients with non-dilated (≤3 mm) or dilated BD (≥3 mm) but unfavorable conditions for ultrasonography (US)-guided BD puncture.MethodsA total of 23 hybrid interventions were performed in 21 patients. Visualization of BD and puncture needles (PN) in the interventional MR images was rated on a 5-point Likert scale by two radiologists. Technical success, planning time, BD puncture time and positioning adjustments of the PN as well as technical success of the biliary intervention and complication rate were recorded.ResultsVisualization even of third-order non-dilated BD and PN was rated excellent by both radiologists with good to excellent interrater agreement. MRI-guided BD puncture was successful in all cases. Planning and BD puncture times were 1:36 ± 2.13 (0:16–11:07) min. and 3:58 ± 2:35 (1:11–9:32) min. Positioning adjustments of the PN was necessary in two patients. Repeated capsular puncture was not necessary in any case. All biliary interventions were completed successfully without major complications.ConclusionA hybrid approach which employs MRI-guided BD puncture for subsequent fluoroscopy-guided biliary intervention is feasible in clinical routine and yields high technical success in patients with non-dilated BD and/or unfavorable conditions for US-guided puncture. Excellent visualization of BD and PN in near-real-time interventional MRI allows successful cannulation of the BD.

A hybrid wavelet transform based short-term wind speed forecasting approach.

Science.gov (United States)

Wang, Jujie

2014-01-01

It is important to improve the accuracy of wind speed forecasting for wind parks management and wind power utilization. In this paper, a novel hybrid approach known as WTT-TNN is proposed for wind speed forecasting. In the first step of the approach, a wavelet transform technique (WTT) is used to decompose wind speed into an approximate scale and several detailed scales. In the second step, a two-hidden-layer neural network (TNN) is used to predict both approximated scale and detailed scales, respectively. In order to find the optimal network architecture, the partial autocorrelation function is adopted to determine the number of neurons in the input layer, and an experimental simulation is made to determine the number of neurons within each hidden layer in the modeling process of TNN. Afterwards, the final prediction value can be obtained by the sum of these prediction results. In this study, a WTT is employed to extract these different patterns of the wind speed and make it easier for forecasting. To evaluate the performance of the proposed approach, it is applied to forecast Hexi Corridor of China's wind speed. Simulation results in four different cases show that the proposed method increases wind speed forecasting accuracy.

AEROSTATIC AND AERODYNAMIC MODULES OF A HYBRID BUOYANT AIRCRAFT: AN ANALYTICAL APPROACH

Directory of Open Access Journals (Sweden)

Anwar Ul Haque

2015-05-01

Full Text Available An analytical approach is essential for the estimation of the requirements of aerodynamic and aerostatic lift for a hybrid buoyant aircraft. Such aircrafts have two different modules to balance the weight of aircraft; aerostatic module and aerodynamic module. Both these modules are to be treated separately for estimation of the mass budget of propulsion systems and required power. In the present work, existing relationships of aircraft and airship are reviewed for its further application for these modules. Limitations of such relationships are also disussed and it is precieved that it will provide a strating point for better understanding of design anatomy of such aircraft.

A New Hybrid Approach for Augmented Reality Maintenance in Scientific Facilities

Directory of Open Access Journals (Sweden)

Héctor Martínez

2013-09-01

Full Text Available Maintenance in scientific facilities is a difficult issue, especially in large and hazardous facilities, due to the complexity of tasks and equipment. Augmented reality is a technology that has already shown great promise in the maintenance field. With the help of augmented reality applications, maintenance tasks can be carried out faster and more safely. The problem with current applications is that they are small-scale prototypes that do not easily scale to large facility maintenance applications. This paper presents a new hybrid approach that enables the creation of augmented reality maintenance applications for large and hazardous scientific facilities. In this paper, a new augmented reality marker and the algorithm for its recognition is proposed. The performance of the algorithm is verified in three test cases, showing promising results in two of them. Improvements in robustness in the third test case in which the camera is moving quickly or when light conditions are extreme are subject to further studies. The proposed new approach will be integrated into an existing augmented reality maintenance system.

Scalar field dark matter in hybrid approach

NARCIS (Netherlands)

Friedrich, Pavel; Prokopec, Tomislav

2017-01-01

We develop a hybrid formalism suitable for modeling scalar field dark matter, in which the phase-space distribution associated to the real scalar field is modeled by statistical equal-time two-point functions and gravity is treated by two stochastic gravitational fields in the longitudinal gauge (in

Hybrid approach to structure modeling of the histamine H3 receptor: Multi-level assessment as a tool for model verification.

Directory of Open Access Journals (Sweden)

Jakub Jończyk

Full Text Available The crucial role of G-protein coupled receptors and the significant achievements associated with a better understanding of the spatial structure of known receptors in this family encouraged us to undertake a study on the histamine H3 receptor, whose crystal structure is still unresolved. The latest literature data and availability of different software enabled us to build homology models of higher accuracy than previously published ones. The new models are expected to be closer to crystal structures; and therefore, they are much more helpful in the design of potential ligands. In this article, we describe the generation of homology models with the use of diverse tools and a hybrid assessment. Our study incorporates a hybrid assessment connecting knowledge-based scoring algorithms with a two-step ligand-based docking procedure. Knowledge-based scoring employs probability theory for global energy minimum determination based on information about native amino acid conformation from a dataset of experimentally determined protein structures. For a two-step docking procedure two programs were applied: GOLD was used in the first step and Glide in the second. Hybrid approaches offer advantages by combining various theoretical methods in one modeling algorithm. The biggest advantage of hybrid methods is their intrinsic ability to self-update and self-refine when additional structural data are acquired. Moreover, the diversity of computational methods and structural data used in hybrid approaches for structure prediction limit inaccuracies resulting from theoretical approximations or fuzziness of experimental data. The results of docking to the new H3 receptor model allowed us to analyze ligand-receptor interactions for reference compounds.

A diagnostic expert system for the nuclear power plant b ased on the hybrid knowledge approach

International Nuclear Information System (INIS)

Yang, J.O.; Chang, S.H.

1989-01-01

A diagnostic expert system, the hybrid knowledge based plant operation supporting system (HYPOSS), which has been developed to support operators' decisionmaking during the transients of the nuclear power plant, is described. HYPOSS adopts the hybrid knowledge approach, which combines both shallow and deep knowledge to take advantage of the merits of both approaches. In HYPOSS, four types of knowledge are used according to the steps of diagnosis procedure. They are structural, functional, behavioral, and heuristic knowledge. The structural and functional knowledge is represented by three fundamental primitives and five types of functions, respectively. The behavioral knowledge is represented using constraints. The inference procedure is based on the human problem-solving behavior modeled in HYPOSS. The event-based operational guidelines are provided to the operator according to the diagnosed results. If the exact anomalies cannot be identified while some of the critical safety functions are challenged, the function-based operational guidelines are provided to the operator. For the validation of HYPOSS, several tests have been performed based on the data produced by a plant simulator. The results of validation studies show good applicability of HYPOSS to the anomaly diagnosis of nuclear power plant

Process planning optimization on turning machine tool using a hybrid genetic algorithm with local search approach

Directory of Open Access Journals (Sweden)

Yuliang Su

2015-04-01

Full Text Available A turning machine tool is a kind of new type of machine tool that is equipped with more than one spindle and turret. The distinctive simultaneous and parallel processing abilities of turning machine tool increase the complexity of process planning. The operations would not only be sequenced and satisfy precedence constraints, but also should be scheduled with multiple objectives such as minimizing machining cost, maximizing utilization of turning machine tool, and so on. To solve this problem, a hybrid genetic algorithm was proposed to generate optimal process plans based on a mixed 0-1 integer programming model. An operation precedence graph is used to represent precedence constraints and help generate a feasible initial population of hybrid genetic algorithm. Encoding strategy based on data structure was developed to represent process plans digitally in order to form the solution space. In addition, a local search approach for optimizing the assignments of available turrets would be added to incorporate scheduling with process planning. A real-world case is used to prove that the proposed approach could avoid infeasible solutions and effectively generate a global optimal process plan.

A hybrid wavelet de-noising and Rank-Set Pair Analysis approach for forecasting hydro-meteorological time series.

Science.gov (United States)

Wang, Dong; Borthwick, Alistair G; He, Handan; Wang, Yuankun; Zhu, Jieyu; Lu, Yuan; Xu, Pengcheng; Zeng, Xiankui; Wu, Jichun; Wang, Lachun; Zou, Xinqing; Liu, Jiufu; Zou, Ying; He, Ruimin

2018-01-01

Accurate, fast forecasting of hydro-meteorological time series is presently a major challenge in drought and flood mitigation. This paper proposes a hybrid approach, wavelet de-noising (WD) and Rank-Set Pair Analysis (RSPA), that takes full advantage of a combination of the two approaches to improve forecasts of hydro-meteorological time series. WD allows decomposition and reconstruction of a time series by the wavelet transform, and hence separation of the noise from the original series. RSPA, a more reliable and efficient version of Set Pair Analysis, is integrated with WD to form the hybrid WD-RSPA approach. Two types of hydro-meteorological data sets with different characteristics and different levels of human influences at some representative stations are used to illustrate the WD-RSPA approach. The approach is also compared to three other generic methods: the conventional Auto Regressive Integrated Moving Average (ARIMA) method, Artificial Neural Networks (ANNs) (BP-error Back Propagation, MLP-Multilayer Perceptron and RBF-Radial Basis Function), and RSPA alone. Nine error metrics are used to evaluate the model performance. Compared to three other generic methods, the results generated by WD-REPA model presented invariably smaller error measures which means the forecasting capability of the WD-REPA model is better than other models. The results show that WD-RSPA is accurate, feasible, and effective. In particular, WD-RSPA is found to be the best among the various generic methods compared in this paper, even when the extreme events are included within a time series. Copyright © 2017 Elsevier Inc. All rights reserved.

The Jigsaw Puzzle of mRNA Translation Initiation in Eukaryotes: A Decade of Structures Unraveling the Mechanics of the Process.

Science.gov (United States)

Hashem, Yaser; Frank, Joachim

2018-03-01

Translation initiation in eukaryotes is a highly regulated and rate-limiting process. It results in the assembly and disassembly of numerous transient and intermediate complexes involving over a dozen eukaryotic initiation factors (eIFs). This process culminates in the accommodation of a start codon marking the beginning of an open reading frame at the appropriate ribosomal site. Although this process has been extensively studied by hundreds of groups for nearly half a century, it has been only recently, especially during the last decade, that we have gained deeper insight into the mechanics of the eukaryotic translation initiation process. This advance in knowledge is due in part to the contributions of structural biology, which have shed light on the molecular mechanics underlying the different functions of various eukaryotic initiation factors. In this review, we focus exclusively on the contribution of structural biology to the understanding of the eukaryotic initiation process, a long-standing jigsaw puzzle that is just starting to yield the bigger picture. Expected final online publication date for the Annual Review of Biophysics Volume 47 is May 20, 2018. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Hybrid Type II fuzzy system & data mining approach for surface finish

Directory of Open Access Journals (Sweden)

Tzu-Liang (Bill Tseng

2015-07-01

Full Text Available In this study, a new methodology in predicting a system output has been investigated by applying a data mining technique and a hybrid type II fuzzy system in CNC turning operations. The purpose was to generate a supplemental control function under the dynamic machining environment, where unforeseeable changes may occur frequently. Two different types of membership functions were developed for the fuzzy logic systems and also by combining the two types, a hybrid system was generated. Genetic algorithm was used for fuzzy adaptation in the control system. Fuzzy rules are automatically modified in the process of genetic algorithm training. The computational results showed that the hybrid system with a genetic adaptation generated a far better accuracy. The hybrid fuzzy system with genetic algorithm training demonstrated more effective prediction capability and a strong potential for the implementation into existing control functions.

Genomic networks of hybrid sterility.

Directory of Open Access Journals (Sweden)

Leslie M Turner

2014-02-01

Full Text Available Hybrid dysfunction, a common feature of reproductive barriers between species, is often caused by negative epistasis between loci ("Dobzhansky-Muller incompatibilities". The nature and complexity of hybrid incompatibilities remain poorly understood because identifying interacting loci that affect complex phenotypes is difficult. With subspecies in the early stages of speciation, an array of genetic tools, and detailed knowledge of reproductive biology, house mice (Mus musculus provide a model system for dissecting hybrid incompatibilities. Male hybrids between M. musculus subspecies often show reduced fertility. Previous studies identified loci and several X chromosome-autosome interactions that contribute to sterility. To characterize the genetic basis of hybrid sterility in detail, we used a systems genetics approach, integrating mapping of gene expression traits with sterility phenotypes and QTL. We measured genome-wide testis expression in 305 male F2s from a cross between wild-derived inbred strains of M. musculus musculus and M. m. domesticus. We identified several thousand cis- and trans-acting QTL contributing to expression variation (eQTL. Many trans eQTL cluster into eleven 'hotspots,' seven of which co-localize with QTL for sterility phenotypes identified in the cross. The number and clustering of trans eQTL-but not cis eQTL-were substantially lower when mapping was restricted to a 'fertile' subset of mice, providing evidence that trans eQTL hotspots are related to sterility. Functional annotation of transcripts with eQTL provides insights into the biological processes disrupted by sterility loci and guides prioritization of candidate genes. Using a conditional mapping approach, we identified eQTL dependent on interactions between loci, revealing a complex system of epistasis. Our results illuminate established patterns, including the role of the X chromosome in hybrid sterility. The integrated mapping approach we employed is

The Importance of Being Hybrid for Spatial Epidemic Models:A Multi-Scale Approach

Directory of Open Access Journals (Sweden)

Arnaud Banos

2015-11-01

Full Text Available This work addresses the spread of a disease within an urban system, definedas a network of interconnected cities. The first step consists of comparing two differentapproaches: a macroscopic one, based on a system of coupled Ordinary DifferentialEquations (ODE Susceptible-Infected-Recovered (SIR systems exploiting populations onnodes and flows on edges (so-called metapopulational model, and a hybrid one, couplingODE SIR systems on nodes and agents traveling on edges. Under homogeneous conditions(mean field approximation, this comparison leads to similar results on the outputs on whichwe focus (the maximum intensity of the epidemic, its duration and the time of the epidemicpeak. However, when it comes to setting up epidemic control strategies, results rapidlydiverge between the two approaches, and it appears that the full macroscopic model is notcompletely adapted to these questions. In this paper, we focus on some control strategies,which are quarantine, avoidance and risk culture, to explore the differences, advantages anddisadvantages of the two models and discuss the importance of being hybrid when modelingand simulating epidemic spread at the level of a whole urban system.

Nafion–clay hybrids with a network structure

KAUST Repository

Burgaz, Engin; Lian, Huiqin; Alonso, Rafael Herrera; Estevez, Luis; Kelarakis, Antonios; Giannelis, Emmanuel P.

2009-01-01

Nafion-clay hybrid membranes with a unique microstructure were synthesized using a fundamentally new approach. The new approach is based on depletion aggregation of suspended particles - a well-known phenomenon in colloids. For certain concentrations of clay and polymer, addition of Nafion solution to clay suspensions in water leads to a gel. Using Cryo-TEM we show that the clay particles in the hybrid gels form a network structure with an average cell size in the order of 500 nm. The hybrid gels are subsequently cast to produce hybrid Nafion-clay membranes. Compared to pure Nafion the swelling of the hybrid membranes in water and methanol is dramatically reduced while their selectivity (ratio of conductivity over permeability) increases. The small decrease of ionic conductivity for the hybrid membranes is more than compensated by the large decrease in methanol permeability. Lastly the hybrid membranes are much stiffer and can withstand higher temperatures compared to pure Nafion. Both of these characteristics are highly desirable for use in fuel cell applications, since a) they will allow the use of a thinner membrane circumventing problems associated with the membrane resistance and b) enable high temperature applications. © 2009 Elsevier Ltd. All rights reserved.

Nafion–clay hybrids with a network structure

KAUST Repository

Burgaz, Engin

2009-05-01

Nafion-clay hybrid membranes with a unique microstructure were synthesized using a fundamentally new approach. The new approach is based on depletion aggregation of suspended particles - a well-known phenomenon in colloids. For certain concentrations of clay and polymer, addition of Nafion solution to clay suspensions in water leads to a gel. Using Cryo-TEM we show that the clay particles in the hybrid gels form a network structure with an average cell size in the order of 500 nm. The hybrid gels are subsequently cast to produce hybrid Nafion-clay membranes. Compared to pure Nafion the swelling of the hybrid membranes in water and methanol is dramatically reduced while their selectivity (ratio of conductivity over permeability) increases. The small decrease of ionic conductivity for the hybrid membranes is more than compensated by the large decrease in methanol permeability. Lastly the hybrid membranes are much stiffer and can withstand higher temperatures compared to pure Nafion. Both of these characteristics are highly desirable for use in fuel cell applications, since a) they will allow the use of a thinner membrane circumventing problems associated with the membrane resistance and b) enable high temperature applications. © 2009 Elsevier Ltd. All rights reserved.

Epitaxial growth of hybrid nanostructures

Science.gov (United States)

Tan, Chaoliang; Chen, Junze; Wu, Xue-Jun; Zhang, Hua

2018-02-01

Hybrid nanostructures are a class of materials that are typically composed of two or more different components, in which each component has at least one dimension on the nanoscale. The rational design and controlled synthesis of hybrid nanostructures are of great importance in enabling the fine tuning of their properties and functions. Epitaxial growth is a promising approach to the controlled synthesis of hybrid nanostructures with desired structures, crystal phases, exposed facets and/or interfaces. This Review provides a critical summary of the state of the art in the field of epitaxial growth of hybrid nanostructures. We discuss the historical development, architectures and compositions, epitaxy methods, characterization techniques and advantages of epitaxial hybrid nanostructures. Finally, we provide insight into future research directions in this area, which include the epitaxial growth of hybrid nanostructures from a wider range of materials, the study of the underlying mechanism and determining the role of epitaxial growth in influencing the properties and application performance of hybrid nanostructures.

A new hybrid support vector machine–wavelet transform approach for estimation of horizontal global solar radiation

International Nuclear Information System (INIS)

Mohammadi, Kasra; Shamshirband, Shahaboddin; Tong, Chong Wen; Arif, Muhammad; Petković, Dalibor; Ch, Sudheer

2015-01-01

Highlights: • Horizontal global solar radiation (HGSR) is predicted based on a new hybrid approach. • Support Vector Machines and Wavelet Transform algorithm (SVM–WT) are combined. • Different sets of meteorological elements are used to predict HGSR. • The precision of SVM–WT is assessed thoroughly against ANN, GP and ARMA. • SVM–WT would be an appealing approach to predict HGSR and outperforms others. - Abstract: In this paper, a new hybrid approach by combining the Support Vector Machine (SVM) with Wavelet Transform (WT) algorithm is developed to predict horizontal global solar radiation. The predictions are conducted on both daily and monthly mean scales for an Iranian coastal city. The proposed SVM–WT method is compared against other existing techniques to demonstrate its efficiency and viability. Three different sets of parameters are served as inputs to establish three models. The results indicate that the model using relative sunshine duration, difference between air temperatures, relative humidity, average temperature and extraterrestrial solar radiation as inputs shows higher performance than other models. The statistical analysis demonstrates that SVM–WT approach enjoys very good performance and outperforms other approaches. For the best SVM–WT model, the obtained statistical indicators of mean absolute percentage error, mean absolute bias error, root mean square error, relative root mean square error and coefficient of determination for daily estimation are 6.9996%, 0.8405 MJ/m 2 , 1.4245 MJ/m 2 , 7.9467% and 0.9086, respectively. Also, for monthly mean estimation the values are 3.2601%, 0.5104 MJ/m 2 , 0.6618 MJ/m 2 , 3.6935% and 0.9742, respectively. Based upon relative percentage error, for the best SVM–WT model, 88.70% of daily predictions fall within the acceptable range of −10% to +10%

A hybrid particle–field molecular dynamics approach: a route toward efficient coarse-grained models for biomembranes

International Nuclear Information System (INIS)

Milano, Giuseppe; De Nicola, Antonio; Kawakatsu, Toshihiro

2013-01-01

This paper gives an overview of the coarse-grained models of phospholipids recently developed by the authors in the frame of a hybrid particle–field molecular dynamics technique. This technique employs a special class of coarse-grained models that are gaining popularity because they allow simulations of large scale systems and, at the same time, they provide sufficiently detailed chemistry for the mapping scheme adopted. The comparison of the computational costs of our approach with standard molecular dynamics simulations is a function of the system size and the number of processors employed in the parallel calculations. Due to the low amount of data exchange, the larger the number of processors, the better are the performances of the hybrid particle–field models. This feature makes these models very promising ones in the exploration of several problems in biophysics. (paper)

A frequency domain approach to analyzing passive battery-ultracapacitor hybrids supplying periodic pulsed current loads

International Nuclear Information System (INIS)

Kuperman, Alon; Aharon, Ilan; Kara, Avi; Malki, Shalev

2011-01-01

Highlights: → Passive battery-ultracapacitor hybrids are examined. → Frequency domain analysis is employed. → The ultracapacitor branch operates as a low-pass filter for the battery. → The battery supplies the average load demand. → Design requirements are discussed. - Abstract: A Fourier-based analysis of passive battery-ultracapacitor hybrid sources is introduced in the manuscript. The approach is first introduced for a general load, and then is followed by a study for a case of periodic pulsed current load. It is shown that the ultracapacitor branch is perceived by the battery as a low-pass filter, which absorbs the majority of the high frequency harmonic current and letting the battery to supply the average load demand in addition to the small part of dynamic current. Design requirements influence on the ultracapacitor capacitance and internal resistance choice are quantitatively discussed. The theory is enforced by simulation and experimental results, showing an excellent agreement.

Weighted hybrid technique for recommender system

Science.gov (United States)

Suriati, S.; Dwiastuti, Meisyarah; Tulus, T.

2017-12-01

Recommender system becomes very popular and has important role in an information system or webpages nowadays. A recommender system tries to make a prediction of which item a user may like based on his activity on the system. There are some familiar techniques to build a recommender system, such as content-based filtering and collaborative filtering. Content-based filtering does not involve opinions from human to make the prediction, while collaborative filtering does, so collaborative filtering can predict more accurately. However, collaborative filtering cannot give prediction to items which have never been rated by any user. In order to cover the drawbacks of each approach with the advantages of other approach, both approaches can be combined with an approach known as hybrid technique. Hybrid technique used in this work is weighted technique in which the prediction score is combination linear of scores gained by techniques that are combined.The purpose of this work is to show how an approach of weighted hybrid technique combining content-based filtering and item-based collaborative filtering can work in a movie recommender system and to show the performance comparison when both approachare combined and when each approach works alone. There are three experiments done in this work, combining both techniques with different parameters. The result shows that the weighted hybrid technique that is done in this work does not really boost the performance up, but it helps to give prediction score for unrated movies that are impossible to be recommended by only using collaborative filtering.

Achieving a hybrid brain-computer interface with tactile selective attention and motor imagery

Science.gov (United States)

Ahn, Sangtae; Ahn, Minkyu; Cho, Hohyun; Jun, Sung Chan

2014-12-01

Objective. We propose a new hybrid brain-computer interface (BCI) system that integrates two different EEG tasks: tactile selective attention (TSA) using a vibro-tactile stimulator on the left/right finger and motor imagery (MI) of left/right hand movement. Event-related desynchronization (ERD) from the MI task and steady-state somatosensory evoked potential (SSSEP) from the TSA task are retrieved and combined into two hybrid senses. Approach. One hybrid approach is to measure two tasks simultaneously; the features of each task are combined for testing. Another hybrid approach is to measure two tasks consecutively (TSA first and MI next) using only MI features. For comparison with the hybrid approaches, the TSA and MI tasks are measured independently. Main results. Using a total of 16 subject datasets, we analyzed the BCI classification performance for MI, TSA and two hybrid approaches in a comparative manner; we found that the consecutive hybrid approach outperformed the others, yielding about a 10% improvement in classification accuracy relative to MI alone. It is understood that TSA may play a crucial role as a prestimulus in that it helps to generate earlier ERD prior to MI and thus sustains ERD longer and to a stronger degree; this ERD may give more discriminative information than ERD in MI alone. Significance. Overall, our proposed consecutive hybrid approach is very promising for the development of advanced BCI systems.

An Approach to Management of Health Care and Medical Diagnosis Using of a Hybrid Disease Diagnosis System

Directory of Open Access Journals (Sweden)

Hodjat Hamidi

2017-02-01

Full Text Available Introduction: In order to simplify the information exchange within the medical diagnosis process, a collaborative software agent’s framework is presented. The purpose of the framework is to allow the automated information exchange between different medicine specialists. Methods: This study presented architecture of a hybrid disease diagnosis system. The architecture employed a learning algorithm and used soft computing to build a medical knowledge base. These machine intelligences are combined in a complementary approach to overcome the weakness of each other. To evaluate the hybrid learning algorithm and compare it with other methods, 699 samples were used in each experiment, where 60% was for training, 20% was for cross validation, and 20% for testing. Results: The results were obtained from the experiments on the breast cancer dataset. Different methods of soft computing system were merged to create diagnostic software functionality. As it is shown in the structure, the system has the ability to learn and collect knowledge that can be used in the detection of new images. Currently, the system is at the design stage. The system is to evaluate the performance of hybrid learning algorithm. The preliminary results showed a better performance of this system than other methods. However, the results can be tested with hybrid system on larger data sets to improve hybrid learning algorithm. Conclusion: The purpose of this paper was to simplify the diagnosis process of a patient by splitting the medical domain concepts (e.g., causes, effects, symptoms, tests in human body systems (e.g., respiratory, cardiovascular, though maintaining the holistic perspective through the links between common concepts.

Comparing Hybrid Learning with Traditional Approaches on Learning the Microsoft Office Power Point 2003 Program in Tertiary Education

Science.gov (United States)

Vernadakis, Nikolaos; Antoniou, Panagiotis; Giannousi, Maria; Zetou, Eleni; Kioumourtzoglou, Efthimis

2011-01-01

The purpose of this study was to determine the effectiveness of a hybrid learning approach to deliver a computer science course concerning the Microsoft office PowerPoint 2003 program in comparison to delivering the same course content in the form of traditional lectures. A hundred and seventy-two first year university students were randomly…

Leadership, clinician managers and a thing called "hybridity".

Science.gov (United States)

Fulop, Liz

2012-01-01

In many countries leadership theories and leadership development programs in healthcare have been dominated by individualistic and heroic approaches that focus on developing the skills and competencies of health professionals. Alternative approaches have been proffered but mainly in the form of post-heroic and distributed forms of leadership. The notion of "hybridity" has emerged to challenge the assumptions of distributed leadership. The paper seeks to explore how the concept of hybridity can be used to re-theorize leadership in healthcare as it relates to clinician managers (or hybrid-professional managers). The theoretical developments are explored and empirical material is presented from research in Australian public hospitals to support the case for the existence of hybridized forms of leadership in healthcare. The paper discusses whether hybridity needs re-theorizing to adequately account for clinician leadership. It contributes to debates surrounding the role of clinician leadership in healthcare reform particularly in relation to those doctors who occupy management positions at the division or unit levels as distinct to CEOs. The study uses qualitative research, i.e. interactive interviews to present accounts of how healthcare professionals describe leadership. It undertakes both deductive and inductive theme analysis of the interview material. There is support for hybridized configurations of leadership in interview materials of healthcare professionals but other aspects were also noted that cannot be explained by this approach alone. The paper is the first to examine the concept of hybridity in the context of clinician leadership. Many approaches to leadership in healthcare fail to address the complexity of leadership within the ranks of clinician managers and thus are unable to deal adequately with the role of leadership in healthcare reform and change.

Hybrid spacecraft attitude control system

Directory of Open Access Journals (Sweden)

Renuganth Varatharajoo

2016-02-01

Full Text Available The hybrid subsystem design could be an attractive approach for futurespacecraft to cope with their demands. The idea of combining theconventional Attitude Control System and the Electrical Power System ispresented in this article. The Combined Energy and Attitude ControlSystem (CEACS consisting of a double counter rotating flywheel assemblyis investigated for small satellites in this article. Another hybrid systemincorporating the conventional Attitude Control System into the ThermalControl System forming the Combined Attitude and Thermal ControlSystem (CATCS consisting of a "fluid wheel" and permanent magnets isalso investigated for small satellites herein. The governing equationsdescribing both these novel hybrid subsystems are presented and theironboard architectures are numerically tested. Both the investigated novelhybrid spacecraft subsystems comply with the reference missionrequirements.The hybrid subsystem design could be an attractive approach for futurespacecraft to cope with their demands. The idea of combining theconventional Attitude Control System and the Electrical Power System ispresented in this article. The Combined Energy and Attitude ControlSystem (CEACS consisting of a double counter rotating flywheel assemblyis investigated for small satellites in this article. Another hybrid systemincorporating the conventional Attitude Control System into the ThermalControl System forming the Combined Attitude and Thermal ControlSystem (CATCS consisting of a "fluid wheel" and permanent magnets isalso investigated for small satellites herein. The governing equationsdescribing both these novel hybrid subsystems are presented and theironboard architectures are numerically tested. Both the investigated novelhybrid spacecraft subsystems comply with the reference missionrequirements.

Simulation-based model checking approach to cell fate specification during Caenorhabditis elegans vulval development by hybrid functional Petri net with extension

Directory of Open Access Journals (Sweden)

Ueno Kazuko

2009-04-01

Full Text Available Abstract Background Model checking approaches were applied to biological pathway validations around 2003. Recently, Fisher et al. have proved the importance of model checking approach by inferring new regulation of signaling crosstalk in C. elegans and confirming the regulation with biological experiments. They took a discrete and state-based approach to explore all possible states of the system underlying vulval precursor cell (VPC fate specification for desired properties. However, since both discrete and continuous features appear to be an indispensable part of biological processes, it is more appropriate to use quantitative models to capture the dynamics of biological systems. Our key motivation of this paper is to establish a quantitative methodology to model and analyze in silico models incorporating the use of model checking approach. Results A novel method of modeling and simulating biological systems with the use of model checking approach is proposed based on hybrid functional Petri net with extension (HFPNe as the framework dealing with both discrete and continuous events. Firstly, we construct a quantitative VPC fate model with 1761 components by using HFPNe. Secondly, we employ two major biological fate determination rules – Rule I and Rule II – to VPC fate model. We then conduct 10,000 simulations for each of 48 sets of different genotypes, investigate variations of cell fate patterns under each genotype, and validate the two rules by comparing three simulation targets consisting of fate patterns obtained from in silico and in vivo experiments. In particular, an evaluation was successfully done by using our VPC fate model to investigate one target derived from biological experiments involving hybrid lineage observations. However, the understandings of hybrid lineages are hard to make on a discrete model because the hybrid lineage occurs when the system comes close to certain thresholds as discussed by Sternberg and Horvitz in

Program Hybrid/GDH. Revision

International Nuclear Information System (INIS)

Blann, M.; Bisplinghoff, J.

1975-10-01

This code is the most recent in a series of codes for doing a-priori pre-equilibrium decay calculations. It has been written to permit the user to exercise many options at time of execution. It will, for example, permit calculation with either Hybrid model or the geometry dependent Hybrid model (GDH). Intranuclear transition rates can be calculated using either a nucleon-nucleon scattering approach (improved over earlier results) or based on the imaginary optical potential. Transition rates based on exciton lifetimes can be selected (as suggested in the Hybrid model formulation) or an average lifetime for each n-exciton configuration may be selected

Design Procedure for Hybrid Ventilation

DEFF Research Database (Denmark)

Heiselberg, Per; Tjelflaat, Per Olaf

Mechanical and natural ventilation systems have developed separately during many years. The natural next step in this development is development of ventilation concepts that utilises and combines the best features from each system into a new type of ventilation system - Hybrid Ventilation....... Buildings with hybrid ventilation often include other sustainable technologies and an energy optimisation requires an integrated approach in the design of the building and its mechanical systems. Therefore, the hybrid ventilation design procedure differs from the design procedure for conventional HVAC....... The first ideas on a design procedure for hybrid ventilation is presented and the different types of design methods, that is needed in different phases of the design process, is discussed....

Optimal control of hybrid vehicles

CERN Document Server

Jager, Bram; Kessels, John

2013-01-01

Optimal Control of Hybrid Vehicles provides a description of power train control for hybrid vehicles. The background, environmental motivation and control challenges associated with hybrid vehicles are introduced. The text includes mathematical models for all relevant components in the hybrid power train. The power split problem in hybrid power trains is formally described and several numerical solutions detailed, including dynamic programming and a novel solution for state-constrained optimal control problems based on Pontryagin’s maximum principle.   Real-time-implementable strategies that can approximate the optimal solution closely are dealt with in depth. Several approaches are discussed and compared, including a state-of-the-art strategy which is adaptive for vehicle conditions like velocity and mass. Two case studies are included in the book: ·        a control strategy for a micro-hybrid power train; and ·        experimental results obtained with a real-time strategy implemented in...

Original Framework for Optimizing Hybrid Energy Supply

Directory of Open Access Journals (Sweden)

Amevi Acakpovi

2016-01-01

Full Text Available This paper proposes an original framework for optimizing hybrid energy systems. The recent growth of hybrid energy systems in remote areas across the world added to the increasing cost of renewable energy has triggered the inevitable development of hybrid energy systems. Hybrid energy systems always pose a problem of optimization of cost which has been approached with different perspectives in the recent past. This paper proposes a framework to guide the techniques of optimizing hybrid energy systems in general. The proposed framework comprises four stages including identification of input variables for energy generation, establishment of models of energy generation by individual sources, development of artificial intelligence, and finally summation of selected sources. A case study of a solar, wind, and hydro hybrid system was undertaken with a linear programming approach. Substantial results were obtained with regard to how load requests were constantly satisfied while minimizing the cost of electricity. The developed framework gained its originality from the fact that it has included models of individual sources of energy that even make the optimization problem more complex. This paper also has impacts on the development of policies which will encourage the integration and development of renewable energies.

A Short-Term and High-Resolution System Load Forecasting Approach Using Support Vector Regression with Hybrid Parameters Optimization

Energy Technology Data Exchange (ETDEWEB)

Jiang, Huaiguang [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2017-08-25

This work proposes an approach for distribution system load forecasting, which aims to provide highly accurate short-term load forecasting with high resolution utilizing a support vector regression (SVR) based forecaster and a two-step hybrid parameters optimization method. Specifically, because the load profiles in distribution systems contain abrupt deviations, a data normalization is designed as the pretreatment for the collected historical load data. Then an SVR model is trained by the load data to forecast the future load. For better performance of SVR, a two-step hybrid optimization algorithm is proposed to determine the best parameters. In the first step of the hybrid optimization algorithm, a designed grid traverse algorithm (GTA) is used to narrow the parameters searching area from a global to local space. In the second step, based on the result of the GTA, particle swarm optimization (PSO) is used to determine the best parameters in the local parameter space. After the best parameters are determined, the SVR model is used to forecast the short-term load deviation in the distribution system.

Model-based design approaches for plug-in hybrid vehicle design

Energy Technology Data Exchange (ETDEWEB)

Mendes, C.J. [CrossChasm Technologies, Cambridge, ON (Canada); Stevens, M.B.; Fowler, M.W. [Waterloo Univ., ON (Canada). Dept. of Chemical Engineering; Fraser, R.A. [Waterloo Univ., ON (Canada). Dept. of Mechanical Engineering; Wilhelm, E.J. [Paul Scherrer Inst., Villigen (Switzerland). Energy Systems Analysis

2007-07-01

A model-based design process for plug-in hybrid vehicles (PHEVs) was presented. The paper discussed steps between the initial design concept and a working vehicle prototype, and focused on an investigation of the software-in-the-loop (SIL), hardware-in-the-loop (HIL), and component-in-the-loop (CIL) design phases. The role and benefits of using simulation were also reviewed. A method for mapping and identifying components was provided along with a hybrid control strategy and component-level control optimization process. The role of simulation in component evaluation, architecture design, and de-bugging procedures was discussed, as well as the role simulation networks can play in speeding deployment times. The simulations focused on work performed on a 2005 Chevrolet Equinox converted to a fuel cell hybrid electric vehicle (FCHEV). Components were aggregated to create a complete virtual vehicle. A simplified vehicle model was implemented onto the on-board vehicle control hardware. Optimization metrics were estimated at 10 alpha values during each control loop iteration. The simulation was then used to tune the control system under a variety of drive cycles and conditions. A CIL technique was used to place a physical hybrid electric vehicle (HEV) component under the control of a real time HEV/PHEV simulation. It was concluded that controllers should have a standardized component description that supports integration into advanced testing procedures. 4 refs., 9 figs.

Implementation and Operational Research: Cost and Efficiency of a Hybrid Mobile Multidisease Testing Approach With High HIV Testing Coverage in East Africa.

Science.gov (United States)

Chang, Wei; Chamie, Gabriel; Mwai, Daniel; Clark, Tamara D; Thirumurthy, Harsha; Charlebois, Edwin D; Petersen, Maya; Kabami, Jane; Ssemmondo, Emmanuel; Kadede, Kevin; Kwarisiima, Dalsone; Sang, Norton; Bukusi, Elizabeth A; Cohen, Craig R; Kamya, Moses; Havlir, Diane V; Kahn, James G

2016-11-01

In 2013-2014, we achieved 89% adult HIV testing coverage using a hybrid testing approach in 32 communities in Uganda and Kenya (SEARCH: NCT01864603). To inform scalability, we sought to determine: (1) overall cost and efficiency of this approach; and (2) costs associated with point-of-care (POC) CD4 testing, multidisease services, and community mobilization. We applied microcosting methods to estimate costs of population-wide HIV testing in 12 SEARCH trial communities. Main intervention components of the hybrid approach are census, multidisease community health campaigns (CHC), and home-based testing for CHC nonattendees. POC CD4 tests were provided for all HIV-infected participants. Data were extracted from expenditure records, activity registers, staff interviews, and time and motion logs. The mean cost per adult tested for HIV was $20.5 (range: $17.1-$32.1) (2014 US$), including a POC CD4 test at $16 per HIV+ person identified. Cost per adult tested for HIV was $13.8 at CHC vs. $31.7 by home-based testing. The cost per HIV+ adult identified was $231 ($87-$1245), with variability due mainly to HIV prevalence among persons tested (ie, HIV positivity rate). The marginal costs of multidisease testing at CHCs were $1.16/person for hypertension and diabetes, and $0.90 for malaria. Community mobilization constituted 15.3% of total costs. The hybrid testing approach achieved very high HIV testing coverage, with POC CD4, at costs similar to previously reported mobile, home-based, or venue-based HIV testing approaches in sub-Saharan Africa. By leveraging HIV infrastructure, multidisease services were offered at low marginal costs.

A Hybrid Node Scheduling Approach Based on Energy Efficient Chain Routing for WSN

Directory of Open Access Journals (Sweden)

Yimei Kang

2014-04-01

Full Text Available Energy efficiency is usually a significant goal in wireless sensor networks (WSNs. In this work, an energy efficient chain (EEC data routing approach is first presented. The coverage and connectivity of WSNs are discussed based on EEC. A hybrid node scheduling approach is then proposed. It includes sleep scheduling for cyclically monitoring regions of interest in time-driven modes and wakeup scheduling for tracking emergency events in event-driven modes. A failure rate is introduced to the sleep scheduling to improve the reliability of the system. A wakeup sensor threshold and a sleep time threshold are introduced in the wakeup scheduling to reduce the consumption of energy to the possible extent. The results of the simulation show that the proposed algorithm can extend the effective lifetime of the network to twice that of PEAS. In addition, the proposed methods are computing efficient because they are very simple to implement.

Hybridization and genome evolution I: The role of contingency during hybrid speciation

Directory of Open Access Journals (Sweden)

Fabrice EROUKHMANOFF, Richard I. BAILEY, Glenn-Peter SæTRE

2013-10-01

Full Text Available Homoploid hybrid speciation (HHS involves the recombination of two differentiated genomes into a novel, functional one without a change in chromosome number. Theoretically, there are numerous ways for two parental genomes to recombine. Hence, chance may play a large role in the formation of a hybrid species. If these genome combinations can evolve rapidly following hybridization and sympatric situations are numerous, recurrent homoploid hybrid speciation is a possibility. We argue that three different, but not mutually exclusive, types of contingencies could influence this process. First, many of these “hopeful monsters” of recombinant parent genotypes would likely have low fitness. Only specific combinations of parental genomic contributions may produce viable, intra-fertile hybrid species able to accommodate potential constraints arising from intragenomic conflict. Second, ecological conditions (competition, geography of the contact zones or the initial frequency of both parent species might favor different outcomes ranging from sympatric coexistence to the formation of hybrid swarms and ultimately hybrid speciation. Finally, history may also play an important role in promoting or constraining recurrent HHS if multiple hybridization events occur sequentially and parental divergence or isolation differs along this continuum. We discuss under which conditions HHS may occur multiple times in parallel and to what extent recombination and selection may fuse the parent genomes in the same or different ways. We conclude by examining different approaches that might help to solve this intriguing evolutionary puzzle [Current Zoology 59 (5: 667-674, 2013].　

Agricultural Tractor Selection: A Hybrid and Multi-Attribute Approach

Directory of Open Access Journals (Sweden)

Jorge L. García-Alcaraz

2016-02-01

Full Text Available Usually, agricultural tractor investments are assessed using traditional economic techniques that only involve financial attributes, resulting in reductionist evaluations. However, tractors have qualitative and quantitative attributes that must be simultaneously integrated into the evaluation process. This article reports a hybrid and multi-attribute approach to assessing a set of agricultural tractors based on AHP-TOPSIS. To identify the attributes in the model, a survey including eighteen attributes was given to agricultural machinery salesmen and farmers for determining their importance. The list of attributes was presented to a decision group for a case of study, and their importance was estimated using AHP and integrated into the TOPSIS technique. In this case, one tractor was selected from a set of six alternatives, integrating six attributes in the model: initial cost, annual maintenance cost, liters of diesel per hour, safety of the operator, maintainability and after-sale customer service offered by the supplier. Based on the results obtained, the model can be considered easy to apply and to have good acceptance among farmers and salesmen, as there are no special software requirements for the application.

"Elephant trunk" and endovascular stentgrafting : a hybrid approach to the treatment of extensive thoracic aortic aneurysm

OpenAIRE

Holubec, Tomás; Raupach, Jan; Dominik, Jan; Vojácek, Jan

2013-01-01

A hybrid approach to elephant trunk technique for treatment of thoracic aortic aneurysms combines a conventional surgical and endovascular therapy. Compared to surgery alone, there is a presumption that mortality and morbidity is reduced. We present a case report of a 42-year-old man with a giant aneurysm of the entire thoracic aorta, significant aortic and tricuspid regurgitation and ventricular septum defect. The patient underwent multiple consecutive operations and interventions having, am...

A Hybrid Heuristic Optimization Approach for Leak Detection in Pipe Networks Using Ordinal Optimization Approach and the Symbiotic Organism Search

Directory of Open Access Journals (Sweden)

Chao-Chih Lin

2017-10-01

Full Text Available A new transient-based hybrid heuristic approach is developed to optimize a transient generation process and to detect leaks in pipe networks. The approach couples the ordinal optimization approach (OOA and the symbiotic organism search (SOS to solve the optimization problem by means of iterations. A pipe network analysis model (PNSOS is first used to determine steady-state head distribution and pipe flow rates. The best transient generation point and its relevant valve operation parameters are optimized by maximizing the objective function of transient energy. The transient event is created at the chosen point, and the method of characteristics (MOC is used to analyze the transient flow. The OOA is applied to sift through the candidate pipes and the initial organisms with leak information. The SOS is employed to determine the leaks by minimizing the sum of differences between simulated and computed head at the observation points. Two synthetic leaking scenarios, a simple pipe network and a water distribution network (WDN, are chosen to test the performance of leak detection ordinal symbiotic organism search (LDOSOS. Leak information can be accurately identified by the proposed approach for both of the scenarios. The presented technique makes a remarkable contribution to the success of leak detection in the pipe networks.

Operation management of daily economic dispatch using novel hybrid particle swarm optimization and gravitational search algorithm with hybrid mutation strategy

Science.gov (United States)

Wang, Yan; Huang, Song; Ji, Zhicheng

2017-07-01

This paper presents a hybrid particle swarm optimization and gravitational search algorithm based on hybrid mutation strategy (HGSAPSO-M) to optimize economic dispatch (ED) including distributed generations (DGs) considering market-based energy pricing. A daily ED model was formulated and a hybrid mutation strategy was adopted in HGSAPSO-M. The hybrid mutation strategy includes two mutation operators, chaotic mutation, Gaussian mutation. The proposed algorithm was tested on IEEE-33 bus and results show that the approach is effective for this problem.

Developing hybrid approaches to predict pKa values of ionizable groups

Science.gov (United States)

Witham, Shawn; Talley, Kemper; Wang, Lin; Zhang, Zhe; Sarkar, Subhra; Gao, Daquan; Yang, Wei

2011-01-01

Accurate predictions of pKa values of titratable groups require taking into account all relevant processes associated with the ionization/deionization. Frequently, however, the ionization does not involve significant structural changes and the dominating effects are purely electrostatic in origin allowing accurate predictions to be made based on the electrostatic energy difference between ionized and neutral forms alone using a static structure. On another hand, if the change of the charge state is accompanied by a structural reorganization of the target protein, then the relevant conformational changes have to be taken into account in the pKa calculations. Here we report a hybrid approach that first predicts the titratable groups, which ionization is expected to cause conformational changes, termed “problematic” residues, then applies a special protocol on them, while the rest of the pKa’s are predicted with rigid backbone approach as implemented in multi-conformation continuum electrostatics (MCCE) method. The backbone representative conformations for “problematic” groups are generated with either molecular dynamics simulations with charged and uncharged amino acid or with ab-initio local segment modeling. The corresponding ensembles are then used to calculate the pKa of the “problematic” residues and then the results are averaged. PMID:21744395

A hybrid approach to predict the relationship between tablet tensile strength and compaction pressure using analytical powder compression.

Science.gov (United States)

Persson, Ann-Sofie; Alderborn, Göran

2018-04-01

The objective was to present a hybrid approach to predict the strength-pressure relationship (SPR) of tablets using common compression parameters and a single measurement of tablet tensile strength. Experimental SPR were derived for six pharmaceutical powders with brittle and ductile properties and compared to predicted SPR based on a three-stage approach. The prediction was based on the Kawakita b -1 parameter and the in-die Heckel yield stress, an estimate of maximal tensile strength, and a parameter proportionality factor α. Three values of α were used to investigate the influence of the parameter on the SPR. The experimental SPR could satisfactorily be described by the three stage model, however for sodium bicarbonate the tensile strength plateau could not be observed experimentally. The shape of the predicted SPR was to a minor extent influenced by the Kawakita b -1 but the width of the linear region was highly influenced by α. An increased α increased the width of the linear region and thus also the maximal predicted tablet tensile strength. Furthermore, the correspondence between experimental and predicted SPR was influenced by the α value and satisfactory predictions were in general obtained for α = 4.1 indicating the predictive potential of the hybrid approach. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Optimum design of brake friction material using hybrid entropy-GRA approach

Directory of Open Access Journals (Sweden)

Kumar Naresh

2016-01-01

Full Text Available The effect of Kevlar and natural fibres on the performance of brake friction materials was evaluated. Four friction material specimens were developed by varying the proportion of Kevlar and natural fibres. Two developed composite contained 5-10 wt.% of Kevlar fibre while in the other two the Kevlar fibre was replaced with same amount of natural fibre. SAE J661 protocol was used for the assessment of the tribological properties on a Chase testing machine. Result shows that the specimens containing Kevlar fibres shows higher friction and wear performance, whereas Kevlar replacement with natural fibre resulted in improved fade, recovery and friction fluctuations. Further hybrid entropy-GRA (grey relation analysis approach was applied to select the optimal friction materials using various performance defining attributes (PDA including friction, wear, fade, recovery, friction fluctuations and cost. The friction materials with 10 wt% of natural fibre exhibited the best overall quality.

Modular approach for conversion to the ion-hybrid wave and α gyroresonance

International Nuclear Information System (INIS)

Kaufman, A.N.; Morehead, J.J.; Brizard, A.J.; Tracy, E.R.

1997-01-01

Linear conversion of an incoming magnetosonic wave (a.k.a. fast or compressional wave) to an ion-hybrid wave can be considered as a 3-step process in ray phase space. This is demonstrated by casting the cold-fluid model into the Friedland-Kaufman normal form for linear mode conversion. First, the incoming magnetosonic ray (MSR) converts a fraction of its action to an intermediate ion-hybrid ray (IHR), with the transmitted ray proceeding through the conversion layer. The IHR propagates in k-space to a second conversion point, where it converts in turn a fraction of its action into a reflected MSR, with the remainder of the its action constituting the converted IHR. The modular approach gives exact agreement with the more standard Budden formulation for the transmission, reflection and conversion coefficients, but has the important advantage of exposing the intermediate IHR. The existence of the intermediate IHR has important physical consequences as it can resonate with α particles. We estimate the time-integrated damping coefficient between the two conversions and show that ∫γdt is of order -100, thus the IH wave is completely annihilated between conversions and transfers its energy to the α close-quote s. This suggests that proposals to use the IH mode for current drive or DT heating are likely to fail in the presence of fusion α close-quote s. copyright 1997 American Institute of Physics

PV-wind hybrid system performance. A new approach and a case study

International Nuclear Information System (INIS)

Arribas, Luis; Cano, Luis; Cruz, Ignacio; Mata, Montserrat; Llobet, Ermen

2010-01-01

Until now, there is no internationally accepted guideline for the measurement, data exchange and analysis of PV-Wind Hybrid Systems. As there is a need for such a tool, so as to overcome the barrier that the lack of confidence due to the absence of reliability means for the development of the market of Hybrid Systems, an effort has been made to suggest one tool for PV-Wind Hybrid Systems. The suggested guidelines presented in this work are based on the existing guidelines for PV Systems, as a PV-Wind Hybrid system can be roughly thought of as a PV System to which wind generation has been added. So, the guidelines for PV Systems are valid for the PV-Wind System, and only the part referred to wind generation should be included. This has been the process followed in this work. The proposed method is applied to a case study, the CICLOPS Project, a 5 kW PV, 7.5 kW Wind Hybrid system installed at the Isolated Wind Systems Test Site that CIEMAT owns in CEDER (Soria, Spain). This system has been fully monitored through a year and the results of the monitoring activity, characterizing the long-term performance of the system are shown in this work. (author)

PV-wind hybrid system performance. A new approach and a case study

Energy Technology Data Exchange (ETDEWEB)

Arribas, Luis; Cano, Luis; Cruz, Ignacio [Departamento de Energias Renovables, CIEMAT, Avda. Complutense 22, 28040 Madrid (Spain); Mata, Montserrat; Llobet, Ermen [Ecotecnia, Roc Boronat 78, 08005 Barcelona (Spain)

2010-01-15

Until now, there is no internationally accepted guideline for the measurement, data exchange and analysis of PV-Wind Hybrid Systems. As there is a need for such a tool, so as to overcome the barrier that the lack of confidence due to the absence of reliability means for the development of the market of Hybrid Systems, an effort has been made to suggest one tool for PV-Wind Hybrid Systems. The suggested guidelines presented in this work are based on the existing guidelines for PV Systems, as a PV-Wind Hybrid system can be roughly thought of as a PV System to which wind generation has been added. So, the guidelines for PV Systems are valid for the PV-Wind System, and only the part referred to wind generation should be included. This has been the process followed in this work. The proposed method is applied to a case study, the CICLOPS Project, a 5 kW PV, 7.5 kW Wind Hybrid system installed at the Isolated Wind Systems Test Site that CIEMAT owns in CEDER (Soria, Spain). This system has been fully monitored through a year and the results of the monitoring activity, characterizing the long-term performance of the system are shown in this work. (author)

Hybrid energy system evaluation in water supply system energy production: neural network approach

Energy Technology Data Exchange (ETDEWEB)

Goncalves, Fabio V.; Ramos, Helena M. [Civil Engineering Department, Instituto Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001, Lisbon (Portugal); Reis, Luisa Fernanda R. [Universidade de Sao Paulo, EESC/USP, Departamento de Hidraulica e Saneamento., Avenida do Trabalhador Saocarlense, 400, Sao Carlos-SP (Brazil)

2010-07-01

Water supply systems are large consumers of energy and the use of hybrid systems for green energy production is this new proposal. This work presents a computational model based on neural networks to determine the best configuration of a hybrid system to generate energy in water supply systems. In this study the energy sources to make this hybrid system can be the national power grid, micro-hydro and wind turbines. The artificial neural network is composed of six layers, trained to use data generated by a model of hybrid configuration and an economic simulator - CES. The reason for the development of an advanced model of forecasting based on neural networks is to allow rapid simulation and proper interaction with hydraulic and power model simulator - HPS. The results show that this computational model is useful as advanced decision support system in the design of configurations of hybrid power systems applied to water supply systems, improving the solutions in the development of its global energy efficiency.

A hybrid computational-experimental approach for automated crystal structure solution

Science.gov (United States)

Meredig, Bryce; Wolverton, C.

2013-02-01

Crystal structure solution from diffraction experiments is one of the most fundamental tasks in materials science, chemistry, physics and geology. Unfortunately, numerous factors render this process labour intensive and error prone. Experimental conditions, such as high pressure or structural metastability, often complicate characterization. Furthermore, many materials of great modern interest, such as batteries and hydrogen storage media, contain light elements such as Li and H that only weakly scatter X-rays. Finally, structural refinements generally require significant human input and intuition, as they rely on good initial guesses for the target structure. To address these many challenges, we demonstrate a new hybrid approach, first-principles-assisted structure solution (FPASS), which combines experimental diffraction data, statistical symmetry information and first-principles-based algorithmic optimization to automatically solve crystal structures. We demonstrate the broad utility of FPASS to clarify four important crystal structure debates: the hydrogen storage candidates MgNH and NH3BH3; Li2O2, relevant to Li-air batteries; and high-pressure silane, SiH4.

Improved Wetland Classification Using Eight-Band High Resolution Satellite Imagery and a Hybrid Approach

Directory of Open Access Journals (Sweden)

Charles R. Lane

2014-12-01

Full Text Available Although remote sensing technology has long been used in wetland inventory and monitoring, the accuracy and detail level of wetland maps derived with moderate resolution imagery and traditional techniques have been limited and often unsatisfactory. We explored and evaluated the utility of a newly launched high-resolution, eight-band satellite system (Worldview-2; WV2 for identifying and classifying freshwater deltaic wetland vegetation and aquatic habitats in the Selenga River Delta of Lake Baikal, Russia, using a hybrid approach and a novel application of Indicator Species Analysis (ISA. We achieved an overall classification accuracy of 86.5% (Kappa coefficient: 0.85 for 22 classes of aquatic and wetland habitats and found that additional metrics, such as the Normalized Difference Vegetation Index and image texture, were valuable for improving the overall classification accuracy and particularly for discriminating among certain habitat classes. Our analysis demonstrated that including WV2’s four spectral bands from parts of the spectrum less commonly used in remote sensing analyses, along with the more traditional bandwidths, contributed to the increase in the overall classification accuracy by ~4% overall, but with considerable increases in our ability to discriminate certain communities. The coastal band improved differentiating open water and aquatic (i.e., vegetated habitats, and the yellow, red-edge, and near-infrared 2 bands improved discrimination among different vegetated aquatic and terrestrial habitats. The use of ISA provided statistical rigor in developing associations between spectral classes and field-based data. Our analyses demonstrated the utility of a hybrid approach and the benefit of additional bands and metrics in providing the first spatially explicit mapping of a large and heterogeneous wetland system.

A new hybrid BCI paradigm based on P300 and SSVEP.

Science.gov (United States)

Wang, Minjue; Daly, Ian; Allison, Brendan Z; Jin, Jing; Zhang, Yu; Chen, Lanlan; Wang, Xingyu

2015-04-15

P300 and steady-state visual evoked potential (SSVEP) approaches have been widely used for brain-computer interface (BCI) systems. However, neither of these approaches can work for all subjects. Some groups have reported that a hybrid BCI that combines two or more approaches might provide BCI functionality to more users. Hybrid P300/SSVEP BCIs have only recently been developed and validated, and very few avenues to improve performance have been explored. The present study compares an established hybrid P300/SSVEP BCIs paradigm to a new paradigm in which shape changing, instead of color changing, is adopted for P300 evocation to decrease the degradation on SSVEP strength. The result shows that the new hybrid paradigm presented in this paper yields much better performance than the normal hybrid paradigm. A performance increase of nearly 20% in SSVEP classification is achieved using the new hybrid paradigm in comparison with the normal hybrid paradigm. All the paradigms except the normal hybrid paradigm used in this paper obtain 100% accuracy in P300 classification. The new hybrid P300/SSVEP BCIs paradigm in which shape changing, instead of color changing, could obtain as high classification accuracy of SSVEP as the traditional SSVEP paradigm and could obtain as high classification accuracy of P300 as the traditional P300 paradigm. P300 did not interfere with the SSVEP response using the new hybrid paradigm presented in this paper, which was superior to the normal hybrid P300/SSVEP paradigm. Copyright © 2014 Elsevier B.V. All rights reserved.

Hybrid spacecraft attitude control system

OpenAIRE

Renuganth Varatharajoo; Ramly Ajir; Tamizi Ahmad

2016-01-01

The hybrid subsystem design could be an attractive approach for futurespacecraft to cope with their demands. The idea of combining theconventional Attitude Control System and the Electrical Power System ispresented in this article. The Combined Energy and Attitude ControlSystem (CEACS) consisting of a double counter rotating flywheel assemblyis investigated for small satellites in this article. Another hybrid systemincorporating the conventional Attitude Control System into the ThermalControl...

The new era of cardiac surgery: hybrid therapy for cardiovascular disease.

Science.gov (United States)

Solenkova, Natalia V; Umakanthan, Ramanan; Leacche, Marzia; Zhao, David X; Byrne, John G

2010-11-01

Surgical therapy for cardiovascular disease carries excellent long-term outcomes but it is relatively invasive. With the development of new devices and techniques, modern cardiovascular surgery is trending toward less invasive approaches, especially for patients at high risk for traditional open heart surgery. A hybrid strategy combines traditional surgical treatments performed in the operating room with treatments traditionally available only in the catheterization laboratory with the goal of offering patients the best available therapy for any set of cardiovascular diseases. Examples of hybrid procedures include hybrid coronary artery bypass grafting, hybrid valve surgery and percutaneous coronary intervention, hybrid endocardial and epicardial atrial fibrillation procedures, and hybrid coronary artery bypass grafting/carotid artery stenting. This multidisciplinary approach requires strong collaboration between cardiac surgeons, vascular surgeons, and interventional cardiologists to obtain optimal patient outcomes.

Combining PCI and CABG: the role of hybrid revascularization.

Science.gov (United States)

Green, Kelly D; Lynch, Donald R; Chen, Tyffany P; Zhao, David

2013-04-01

Hybrid coronary revascularization combines the benefits of both percutaneous coronary intervention (PCI) and coronary artery bypass grafting (CABG) in the treatment of multivessel coronary artery disease (CAD) by combining the benefits of the LIMA-to-LAD graft and drug eluting stent (DES) to non-LAD regions. Through this approach, a patient receives the long-term benefit of the LIMA graft and avoids the morbidity of a full sternotomy and saphenous vein grafts. Available data related to outcomes following hybrid revascularization is limited to small studies. In this review we seek to provide an overview of hybrid revascularization in the era of modern drug eluting stent technology, discuss appropriate patient selection, and comment on future trial design. Additionally, we review the recent literature pertaining to the hybrid approach.

A hybrid approach for short-term forecasting of wind speed.

Science.gov (United States)

Tatinati, Sivanagaraja; Veluvolu, Kalyana C

2013-01-01

We propose a hybrid method for forecasting the wind speed. The wind speed data is first decomposed into intrinsic mode functions (IMFs) with empirical mode decomposition. Based on the partial autocorrelation factor of the individual IMFs, adaptive methods are then employed for the prediction of IMFs. Least squares-support vector machines are employed for IMFs with weak correlation factor, and autoregressive model with Kalman filter is employed for IMFs with high correlation factor. Multistep prediction with the proposed hybrid method resulted in improved forecasting. Results with wind speed data show that the proposed method provides better forecasting compared to the existing methods.

An Approach for Designing Thermal Management Systems for Electric and Hybrid Vehicle Battery Packs

International Nuclear Information System (INIS)

Pesaran, Ahmad A.; Keyser, Matthew; Burch, Steve

1999-01-01

If battery packs for electric vehicles (EVs) and hybrid electric vehicles (HEVs) are to operate effectively in all climates, thermal management of the packs is essential. In this paper, we will review a systematic approach for designing and evaluating battery pack thermal management systems. A thermal management system using air as the heat transfer medium is less complicated than a system using liquid cooling/heating. Generally, for parallel HEVs, an air thermal management system is adequate, whereas for EVs and series HEVs, liquid-based systems may be required for optimum thermal performance. Further information on battery thermal management can be found on the Web site www.ctts.nrel.gov/BTM

Application of Hybrid Dynamical Theory to the Cardiovascular System

KAUST Repository

Laleg-Kirati, Taous-Meriem

2014-10-14

In hybrid dynamical systems, the state evolves in continuous time as well as in discrete modes activated by internal conditions or by external events. In the recent years, hybrid systems modeling has been used to represent the dynamics of biological systems. In such systems, discrete behaviors might originate from unexpected changes in normal performance, e.g., a transition from a healthy to an abnormal condition. Simplifications, model assumptions, and/or modeled (and ignored) nonlinearities can be represented by sudden changes in the state. Modeling cardiovascular system (CVS), one of the most fascinating but most complex human physiological systems, with a hybrid approach, is the focus of this chapter. The hybrid property appears naturally in the CVS thanks to the presence of valves which, depending on their state (closed or open), divide the cardiac cycle into four phases. This chapter shows how hybrid models can be used for modeling the CVS. In addition, it describes a preliminary study on the detection of some cardiac anomalies based on the hybrid model and using the standard observer-based approach.

Novel approach for streamflow forecasting using a hybrid ANFIS-FFA model

Science.gov (United States)

Yaseen, Zaher Mundher; Ebtehaj, Isa; Bonakdari, Hossein; Deo, Ravinesh C.; Danandeh Mehr, Ali; Mohtar, Wan Hanna Melini Wan; Diop, Lamine; El-shafie, Ahmed; Singh, Vijay P.

2017-11-01

The present study proposes a new hybrid evolutionary Adaptive Neuro-Fuzzy Inference Systems (ANFIS) approach for monthly streamflow forecasting. The proposed method is a novel combination of the ANFIS model with the firefly algorithm as an optimizer tool to construct a hybrid ANFIS-FFA model. The results of the ANFIS-FFA model is compared with the classical ANFIS model, which utilizes the fuzzy c-means (FCM) clustering method in the Fuzzy Inference Systems (FIS) generation. The historical monthly streamflow data for Pahang River, which is a major river system in Malaysia that characterized by highly stochastic hydrological patterns, is used in the study. Sixteen different input combinations with one to five time-lagged input variables are incorporated into the ANFIS-FFA and ANFIS models to consider the antecedent seasonal variations in historical streamflow data. The mean absolute error (MAE), root mean square error (RMSE) and correlation coefficient (r) are used to evaluate the forecasting performance of ANFIS-FFA model. In conjunction with these metrics, the refined Willmott's Index (Drefined), Nash-Sutcliffe coefficient (ENS) and Legates and McCabes Index (ELM) are also utilized as the normalized goodness-of-fit metrics. Comparison of the results reveals that the FFA is able to improve the forecasting accuracy of the hybrid ANFIS-FFA model (r = 1; RMSE = 0.984; MAE = 0.364; ENS = 1; ELM = 0.988; Drefined = 0.994) applied for the monthly streamflow forecasting in comparison with the traditional ANFIS model (r = 0.998; RMSE = 3.276; MAE = 1.553; ENS = 0.995; ELM = 0.950; Drefined = 0.975). The results also show that the ANFIS-FFA is not only superior to the ANFIS model but also exhibits a parsimonious modelling framework for streamflow forecasting by incorporating a smaller number of input variables required to yield the comparatively better performance. It is construed that the FFA optimizer can thus surpass the accuracy of the traditional ANFIS model in general

A cost-emission model for fuel cell/PV/battery hybrid energy system in the presence of demand response program: ε-constraint method and fuzzy satisfying approach

International Nuclear Information System (INIS)

Nojavan, Sayyad; Majidi, Majid; Najafi-Ghalelou, Afshin; Ghahramani, Mehrdad; Zare, Kazem

2017-01-01

Highlights: • Cost-emission performance of PV/battery/fuel cell hybrid energy system is studied. • Multi-objective optimization model for cost-emission performance is proposed. • ε-constraint method is proposed to produce Pareto solutions of multi-objective model. • Fuzzy satisfying approach selected the best optimal solution from Pareto solutions. • Demand response program is proposed to reduce both cost and emission. - Abstract: Optimal operation of hybrid energy systems is a big challenge in power systems. Nowadays, in addition to the optimum performance of energy systems, their pollution issue has been a hot topic between researchers. In this paper, a multi-objective model is proposed for economic and environmental operation of a battery/fuel cell/photovoltaic (PV) hybrid energy system in the presence of demand response program (DRP). In the proposed paper, the first objective function is minimization of total cost of hybrid energy system. The second objective function is minimization of total CO_2 emission which is in conflict with the first objective function. So, a multi-objective optimization model is presented to model the hybrid system’s optimal and environmental performance problem with considering DRP. The proposed multi-objective model is solved by ε-constraint method and then fuzzy satisfying technique is employed to select the best possible solution. Also, positive effects of DRP on the economic and environmental performance of hybrid system are analyzed. A mixed-integer linear program is used to simulate the proposed model and the obtained results are compared with weighted sum approach to show the effectiveness of proposed method.

Hybrid Design Thinking in a Consummate Marriage of People and Technology

NARCIS (Netherlands)

Wendrich, Robert E.; Sugiyama, K.

2013-01-01

In this paper we take a hybrid design tool approach to integrate existing and new advances in HCI, problem-solving, decision-making, mind-mapping, universal access in conjunction with multi-disciplinary and cross-domain areas based on holistic and interactive systems. Our hybrid approach constitutes

Modelling the solar wind interaction with Mercury by a quasi-neutral hybrid model

Directory of Open Access Journals (Sweden)

E. Kallio

2003-11-01

Full Text Available Quasi-neutral hybrid model is a self-consistent modelling approach that includes positively charged particles and an electron fluid. The approach has received an increasing interest in space plasma physics research because it makes it possible to study several plasma physical processes that are difficult or impossible to model by self-consistent fluid models, such as the effects associated with the ions’ finite gyroradius, the velocity difference between different ion species, or the non-Maxwellian velocity distribution function. By now quasi-neutral hybrid models have been used to study the solar wind interaction with the non-magnetised Solar System bodies of Mars, Venus, Titan and comets. Localized, two-dimensional hybrid model runs have also been made to study terrestrial dayside magnetosheath. However, the Hermean plasma environment has not yet been analysed by a global quasi-neutral hybrid model. In this paper we present a new quasi-neutral hybrid model developed to study various processes associated with the Mercury-solar wind interaction. Emphasis is placed on addressing advantages and disadvantages of the approach to study different plasma physical processes near the planet. The basic assumptions of the approach and the algorithms used in the new model are thoroughly presented. Finally, some of the first three-dimensional hybrid model runs made for Mercury are presented. The resulting macroscopic plasma parameters and the morphology of the magnetic field demonstrate the applicability of the new approach to study the Mercury-solar wind interaction globally. In addition, the real advantage of the kinetic hybrid model approach is to study the property of individual ions, and the study clearly demonstrates the large potential of the approach to address these more detailed issues by a quasi-neutral hybrid model in the future.Key words. Magnetospheric physics (planetary magnetospheres; solar wind-magnetosphere interactions – Space plasma

Hybrid Modelling of Individual Movement and Collective Behaviour

KAUST Repository

Franz, Benjamin

2013-01-01

Mathematical models of dispersal in biological systems are often written in terms of partial differential equations (PDEs) which describe the time evolution of population-level variables (concentrations, densities). A more detailed modelling approach is given by individual-based (agent-based) models which describe the behaviour of each organism. In recent years, an intermediate modelling methodology - hybrid modelling - has been applied to a number of biological systems. These hybrid models couple an individual-based description of cells/animals with a PDE-model of their environment. In this chapter, we overview hybrid models in the literature with the focus on the mathematical challenges of this modelling approach. The detailed analysis is presented using the example of chemotaxis, where cells move according to extracellular chemicals that can be altered by the cells themselves. In this case, individual-based models of cells are coupled with PDEs for extracellular chemical signals. Travelling waves in these hybrid models are investigated. In particular, we show that in contrary to the PDEs, hybrid chemotaxis models only develop a transient travelling wave. © 2013 Springer-Verlag Berlin Heidelberg.

Optimal design of permanent magnet flux switching generator for wind applications via artificial neural network and multi-objective particle swarm optimization hybrid approach

International Nuclear Information System (INIS)

Meo, Santolo; Zohoori, Alireza; Vahedi, Abolfazl

2016-01-01

Highlights: • A new optimal design of flux switching permanent magnet generator is developed. • A prototype is employed to validate numerical data used for optimization. • A novel hybrid multi-objective particle swarm optimization approach is proposed. • Optimization targets are weight, cost, voltage and its total harmonic distortion. • The hybrid approach preference is proved compared with other optimization methods. - Abstract: In this paper a new hybrid approach obtained combining a multi-objective particle swarm optimization and artificial neural network is proposed for the design optimization of a direct-drive permanent magnet flux switching generators for low power wind applications. The targets of the proposed multi-objective optimization are to reduce the costs and weight of the machine while maximizing the amplitude of the induced voltage as well as minimizing its total harmonic distortion. The permanent magnet width, the stator and rotor tooth width, the rotor teeth number and stator pole number of the machine define the search space for the optimization problem. Four supervised artificial neural networks are designed for modeling the complex relationships among the weight, the cost, the amplitude and the total harmonic distortion of the output voltage respect to the quantities of the search space. Finite element analysis is adopted to generate training dataset for the artificial neural networks. Finite element analysis based model is verified by experimental results with a 1.5 kW permanent magnet flux switching generator prototype suitable for renewable energy applications, having 6/19 stator poles/rotor teeth. Finally the effectiveness of the proposed hybrid procedure is compared with the results given by conventional multi-objective optimization algorithms. The obtained results show the soundness of the proposed multi objective optimization technique and its feasibility to be adopted as suitable methodology for optimal design of permanent

Mobile phone use while driving: a hybrid modeling approach.

Science.gov (United States)

Márquez, Luis; Cantillo, Víctor; Arellana, Julián

2015-05-01

The analysis of the effects that mobile phone use produces while driving is a topic of great interest for the scientific community. There is consensus that using a mobile phone while driving increases the risk of exposure to traffic accidents. The purpose of this research is to evaluate the drivers' behavior when they decide whether or not to use a mobile phone while driving. For that, a hybrid modeling approach that integrates a choice model with the latent variable "risk perception" was used. It was found that workers and individuals with the highest education level are more prone to use a mobile phone while driving than others. Also, "risk perception" is higher among individuals who have been previously fined and people who have been in an accident or almost been in an accident. It was also found that the tendency to use mobile phones while driving increases when the traffic speed reduces, but it decreases when the fine increases. Even though the urgency of the phone call is the most important explanatory variable in the choice model, the cost of the fine is an important attribute in order to control mobile phone use while driving. Copyright © 2015 Elsevier Ltd. All rights reserved.

A hybrid ensemble learning approach to star-galaxy classification

Science.gov (United States)

Kim, Edward J.; Brunner, Robert J.; Carrasco Kind, Matias

2015-10-01

There exist a variety of star-galaxy classification techniques, each with their own strengths and weaknesses. In this paper, we present a novel meta-classification framework that combines and fully exploits different techniques to produce a more robust star-galaxy classification. To demonstrate this hybrid, ensemble approach, we combine a purely morphological classifier, a supervised machine learning method based on random forest, an unsupervised machine learning method based on self-organizing maps, and a hierarchical Bayesian template-fitting method. Using data from the CFHTLenS survey (Canada-France-Hawaii Telescope Lensing Survey), we consider different scenarios: when a high-quality training set is available with spectroscopic labels from DEEP2 (Deep Extragalactic Evolutionary Probe Phase 2 ), SDSS (Sloan Digital Sky Survey), VIPERS (VIMOS Public Extragalactic Redshift Survey), and VVDS (VIMOS VLT Deep Survey), and when the demographics of sources in a low-quality training set do not match the demographics of objects in the test data set. We demonstrate that our Bayesian combination technique improves the overall performance over any individual classification method in these scenarios. Thus, strategies that combine the predictions of different classifiers may prove to be optimal in currently ongoing and forthcoming photometric surveys, such as the Dark Energy Survey and the Large Synoptic Survey Telescope.

A Hybrid Metaheuristic-Based Approach for the Aerodynamic Optimization of Small Hybrid Wind Turbine Rotors

DEFF Research Database (Denmark)

Herbert-Acero, José F.; Martínez-Lauranchet, Jaime; Probst, Oliver

2014-01-01

of the sectional blade aerodynamics. The framework considers an innovative nested-hybrid solution procedure based on two metaheuristics, the virtual gene genetic algorithm and the simulated annealing algorithm, to provide a near-optimal solution to the problem. The objective of the study is to maximize...

Hybrid e-learning tool TransLearning

NARCIS (Netherlands)

Meij, van der Marjoleine G.; Kupper, Frank; Beers, P.J.; Broerse, Jacqueline E.W.

2016-01-01

E-learning and storytelling approaches can support informal vicarious learning within geographically widely distributed multi-stakeholder collaboration networks. This case study evaluates hybrid e-learning and video-storytelling approach ‘TransLearning’ by investigation into how its storytelling

Hybrid colloidal plasmonic-photonic crystals.

Science.gov (United States)

Romanov, Sergei G; Korovin, Alexander V; Regensburger, Alois; Peschel, Ulf

2011-06-17

We review the recently emerged class of hybrid metal-dielectric colloidal photonic crystals. The hybrid approach is understood as the combination of a dielectric photonic crystal with a continuous metal film. It allows to achieve a strong modification of the optical properties of photonic crystals by involving the light scattering at electronic excitations in the metal component into moulding of the light flow in series to the diffraction resonances occurring in the body of the photonic crystal. We consider different realizations of hybrid plasmonic-photonic crystals based on two- and three-dimensional colloidal photonic crystals in association with flat and corrugated metal films. In agreement with model calculations, different resonance phenomena determine the optical response of hybrid crystals leading to a broadly tuneable functionality of these crystals. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Sequence-dependent theory of oligonucleotide hybridization kinetics

International Nuclear Information System (INIS)

Marimuthu, Karthikeyan; Chakrabarti, Raj

2014-01-01

A theoretical approach to the prediction of the sequence and temperature-dependent rate constants for oligonucleotide hybridization reactions has been developed based on the theory of relaxation kinetics. One-sided and two-sided melting reaction mechanisms for oligonucleotide hybridization reactions have been considered, analyzed, modified, and compared to select a physically consistent as well as robust model for prediction of the relaxation times of DNA hybridization reactions that agrees with the experimental evidence. The temperature- and sequence-dependent parameters of the proposed model have been estimated using available experimental data. The relaxation time model that we developed has been combined with the nearest neighbor model of hybridization thermodynamics to estimate the temperature- and sequence-dependent rate constants of an oligonucleotide hybridization reaction. The model-predicted rate constants are compared to experimentally determined rate constants for the same oligonucleotide hybridization reactions. Finally, we consider a few important applications of kinetically controlled DNA hybridization reactions

Block copolymer-nanoparticle hybrid self-assembly

KAUST Repository

Hoheisel, Tobias N.; Hur, Kahyun; Wiesner, Ulrich B.

2015-01-01

© 2014 Published by Elsevier Ltd. Polymer-inorganic hybrid materials provide exciting opportunities as they may display favorable properties from both constituents that are desired in applications including catalysis and energy conversion and storage. For the preparation of hybrid materials with well-defined morphologies, block copolymer-directed nanoparticle hybrids present a particularly promising approach. As will be described in this review, once the fundamental characteristics for successful nanostructure formation at or close to the thermodynamic equilibrium of these nanocomposites are identified, the approach can be generalized to various materials classes. In addition to the discussion of recent materials developments based on the use of AB diblock copolymers as well as ABC triblock terpolymers, this review will therefore emphasize progress in the fundamental understanding of the underlying formation mechanisms of such hybrid materials. To this end, critical experiments for, as well as theoretical progress in the description of these nanostructured block copolymer-based hybrid materials will be discussed. Rather than providing a comprehensive overview, the review will emphasize work by the Wiesner group at Cornell University, US, on block copolymer-directed nanoparticle assemblies as well as their use in first potential application areas. The results provide powerful design criteria for wet-chemical synthesis methodologies for the generation of functional nanomaterials for applications ranging from microelectronics to catalysis to energy conversion and storage.

A Hybrid ICA-SVM Approach for Determining the Quality Variables at Fault in a Multivariate Process

Directory of Open Access Journals (Sweden)

Yuehjen E. Shao

2012-01-01

Full Text Available The monitoring of a multivariate process with the use of multivariate statistical process control (MSPC charts has received considerable attention. However, in practice, the use of MSPC chart typically encounters a difficulty. This difficult involves which quality variable or which set of the quality variables is responsible for the generation of the signal. This study proposes a hybrid scheme which is composed of independent component analysis (ICA and support vector machine (SVM to determine the fault quality variables when a step-change disturbance existed in a multivariate process. The proposed hybrid ICA-SVM scheme initially applies ICA to the Hotelling T2 MSPC chart to generate independent components (ICs. The hidden information of the fault quality variables can be identified in these ICs. The ICs are then served as the input variables of the classifier SVM for performing the classification process. The performance of various process designs is investigated and compared with the typical classification method. Using the proposed approach, the fault quality variables for a multivariate process can be accurately and reliably determined.

Evolution of Humans: Understanding the Nature and Methods of Science through Cooperative Learning

Science.gov (United States)

Lee, Yeung Chung

2011-01-01

This article describes the use of an enquiry-based approach to the study of human evolution in a practical context, integrating role-playing, jigsaw cooperative learning and scientific argumentation. The activity seeks to unravel the evolutionary relationships of five hominids and one ape from rather "messy" evidence. This approach enhanced the…

Hybrid wind–photovoltaic–diesel–battery system sizing tool development using empirical approach, life-cycle cost and performance analysis: A case study in Scotland

International Nuclear Information System (INIS)

Gan, Leong Kit; Shek, Jonathan K.H.; Mueller, Markus A.

2015-01-01

Highlights: • Methods of sizing a hybrid wind–photovoltaic–diesel–battery system is described. • The hybrid system components are modelled using empirical data. • Twenty years lifecycle cost of the hybrid system is considered. • The trade-offs between battery storage capacity and diesel fuel usage is studied. • A hybrid system sizing tool has been developed as a graphical user interface (GUI). - Abstract: The concept of off-grid hybrid wind energy system is financially attractive and more reliable than stand-alone power systems since it is based on more than one electricity generation source. One of the most expensive components in a stand-alone wind-power system is the energy storage system as very often it is oversized to increase system autonomy. In this work, we consider a hybrid system which consists of wind turbines, photovoltaic panels, diesel generator and battery storage. One of the main challenges experienced by project managers is the sizing of components for different sites. This challenge is due to the variability of the renewable energy resource and the load demand for different sites. This paper introduces a sizing model that has been developed and implemented as a graphical user interface, which predicts the optimum configuration of a hybrid system. In particular, this paper focuses on seeking the optimal size of the batteries and the diesel generator usage. Both of these components are seen to be trade-offs from each other. The model simulates real time operation of the hybrid system, using the annual measured hourly wind speed and solar irradiation. The benefit of using time series approach is that it reflects a more realistic situation; here, the peaks and troughs of the renewable energy resource are a central part of the sizing model. Finally, load sensitivity and hybrid system performance analysis are demonstrated.

PV-hybrid and mini-grid

Energy Technology Data Exchange (ETDEWEB)

NONE

2010-07-01

Within the 5th European PV-hybrid and mini-grid conference 29th and 30th April, 2010 in Tarragona (Spain) the following lectures were held: (1) Overview of IEA PVPS Task 11 PV-hybrid systems within mini grids; (2) Photovoltaic revolution for deployment in developing countries; (3) Legal and financial conditions for the sustainable operation of mini-grids; (4) EU instruments to promote renewable energies in developing countries; (5) PV hybridization of diesel electricity generators: Conditions of profitability and examples in differential power and storage size ranges; (6) Education suit of designing PV hybrid systems; (7) Sustainable renewable energy projects for intelligent rural electrification in Laos, Cambodia and Vietnam; (8) Techno-economic feasibility of energy supply of remote villages in Palestine by PV systems, diesel generators and electric grid (Case studies: Emnazeil and Atouf villages); (9) Technical, economical and sustainability considerations of a solar PV mini grid as a tool for rural electrification in Uganda; (10) Can we rate inverters for rural electrification on the basis of energy efficiency?; (11) Test procedures for MPPT charge controllers characterization; (12) Energy storage for mini-grid stabilization; (13) Redox flow batteries - Already an alternative storage solution for hybrid PV mini-grids?; (14) Control methods for PV hybrid mini-grids; (15) Partial AC-coupling in mini-grids; (15) Normative issues of small wind turbines in PV hybrid systems; (16) Communication solutions for PV hybrid systems; (17) Towards flexible control and communication of mini-grids; (18) PV/methanol fuel cell hybrid system for powering a highway security variable message board; (19) Polygeneration smartgrids: A solution for the supply of electricity, potable water and hydrogen as fuel for transportation in remote Areas; (20) Implementation of the Bronsbergen micro grid using FACDS; (21) A revisited approach for the design of PV wind hybrid systems; (22

A new hybrid algorithm using thermodynamic and backward ray-tracing approaches for modeling luminescent solar concentrators

Energy Technology Data Exchange (ETDEWEB)

Lo, Ch. K.; Lim, Y. S.; Tan, S. G.; Rahman, F. A. [Faculty of Engineering and Science, University Tunku Abdul Rahman, Jalan Genting Klang, 53300, Kuala Lumpur (Malaysia)

2010-12-15

A Luminescent Solar Concentrator (LSC) is a transparent plate containing luminescent material with photovoltaic (PV) cells attached to its edges. Sunlight entering the plate is absorbed by the luminescent material, which in turn emits light. The emitted light propagates through the plate and arrives at the PV cells through total internal reflection. The ratio of the area of the relatively cheap polymer plate to that of the expensive PV cells is increased, and the cost per unit of solar electricity can be reduced by 75%. To improve the emission performance of LSCs, simulation modeling of LSCs becomes essential. Ray-tracing modeling is a popular approach for simulating LSCs due to its great ability of modeling various LSC structures under direct and diffuse sunlight. However, this approach requires substantial amount of measurement input data. Also, the simulation time is enormous because it is a forward-ray tracing method that traces all the rays propagating from the light source to the concentrator. On the other hand, the thermodynamic approach requires substantially less input parameters and simulation time, but it can only be used to model simple LSC designs with direct sunlight. Therefore, a new hybrid model was developed to perform various simulation studies effectively without facing the issues arisen from the existing ray-tracing and thermodynamic models. The simulation results show that at least 60% of the total output irradiance of a LSC is contributed by the light trapped and channeled by the LSC. The novelty of this hybrid model is the concept of integrating the thermodynamic model with a well-developed Radiance ray-tracing model, hence making this model as a fast, powerful and cost-effective tool for the design of LSCs. (authors)

Hybrid Lanczos-type product methods

Energy Technology Data Exchange (ETDEWEB)

Ressel, K.J. [Swiss Center for Scientific Computing, Zuerich (Switzerland)

1996-12-31

A general framework is proposed to construct hybrid iterative methods for the solution of large nonsymmetric systems of linear equations. This framework is based on Lanczos-type product methods, whose iteration polynomial consists of the Lanczos polynomial multiplied by some other arbitrary, {open_quotes}shadow{close_quotes} polynomial. By using for the shadow polynomial Chebyshev (more general Faber) polynomials or L{sup 2}-optimal polynomials, hybrid (Chebyshev-like) methods are incorporated into Lanczos-type product methods. In addition, to acquire spectral information on the system matrix, which is required for such a choice of shadow polynomials, the Lanczos-process can be employed either directly or in an QMR-like approach. The QMR like approach allows the cheap computation of the roots of the B-orthogonal polynomials and the residual polynomials associated with the QMR iteration. These roots can be used as a good approximation for the spectrum of the system matrix. Different choices for the shadow polynomials and their construction are analyzed. The resulting hybrid methods are compared with standard Lanczos-type product methods, like BiOStab, BiOStab({ell}) and BiOS.

A hybrid nudging-ensemble Kalman filter approach to data assimilation. Part I: application in the Lorenz system

Directory of Open Access Journals (Sweden)

Lili Lei

2012-05-01

Full Text Available A hybrid data assimilation approach combining nudging and the ensemble Kalman filter (EnKF for dynamic analysis and numerical weather prediction is explored here using the non-linear Lorenz three-variable model system with the goal of a smooth, continuous and accurate data assimilation. The hybrid nudging-EnKF (HNEnKF computes the hybrid nudging coefficients from the flow-dependent, time-varying error covariance matrix from the EnKF's ensemble forecasts. It extends the standard diagonal nudging terms to additional off-diagonal statistical correlation terms for greater inter-variable influence of the innovations in the model's predictive equations to assist in the data assimilation process. The HNEnKF promotes a better fit of an analysis to data compared to that achieved by either nudging or incremental analysis update (IAU. When model error is introduced, it produces similar or better root mean square errors compared to the EnKF while minimising the error spikes/discontinuities created by the intermittent EnKF. It provides a continuous data assimilation with better inter-variable consistency and improved temporal smoothness than that of the EnKF. Data assimilation experiments are also compared to the ensemble Kalman smoother (EnKS. The HNEnKF has similar or better temporal smoothness than that of the EnKS, and with much smaller central processing unit (CPU time and data storage requirements.

THEORIZING HYBRIDITY: INSTITUTIONAL LOGICS, COMPLEX ORGANIZATIONS, AND ACTOR IDENTITIES: THE CASE OF NONPROFITS

Science.gov (United States)

SKELCHER, CHRIS; SMITH, STEVEN RATHGEB

2015-01-01

We propose a novel approach to theorizing hybridity in public and nonprofit organizations. The concept of hybridity is widely used to describe organizational responses to changes in governance, but the literature seldom explains how hybrids arise or what forms they take. Transaction cost and organizational design literatures offer some solutions, but lack a theory of agency. We use the institutional logics approach to theorize hybrids as entities that face a plurality of normative frames. Logics provide symbolic and material elements that structure organizational legitimacy and actor identities. Contradictions between institutional logics offer space for them to be elaborated and creatively reconstructed by situated agents. We propose five types of organizational hybridity – segmented, segregated, assimilated, blended, and blocked. Each type is theoretically derived from empirically observed variations in organizational responses to institutional plurality. We develop propositions to show how our approach to hybridity adds value to academic and policy-maker audiences. PMID:26640298

THEORIZING HYBRIDITY: INSTITUTIONAL LOGICS, COMPLEX ORGANIZATIONS, AND ACTOR IDENTITIES: THE CASE OF NONPROFITS.

Science.gov (United States)

Skelcher, Chris; Smith, Steven Rathgeb

2015-06-01

We propose a novel approach to theorizing hybridity in public and nonprofit organizations. The concept of hybridity is widely used to describe organizational responses to changes in governance, but the literature seldom explains how hybrids arise or what forms they take. Transaction cost and organizational design literatures offer some solutions, but lack a theory of agency. We use the institutional logics approach to theorize hybrids as entities that face a plurality of normative frames. Logics provide symbolic and material elements that structure organizational legitimacy and actor identities. Contradictions between institutional logics offer space for them to be elaborated and creatively reconstructed by situated agents. We propose five types of organizational hybridity - segmented, segregated, assimilated, blended, and blocked. Each type is theoretically derived from empirically observed variations in organizational responses to institutional plurality. We develop propositions to show how our approach to hybridity adds value to academic and policy-maker audiences.

Hybrid Ground-Source Heat Pump Installations: Experiences, Improvements, and Tools

Energy Technology Data Exchange (ETDEWEB)

Scott Hackel; Amanda Pertzborn

2011-06-30

One innovation to ground-source heat pump (GSHP, or GHP) systems is the hybrid GSHP (HyGSHP) system, which can dramatically decrease the first cost of GSHP systems by using conventional technology (such as a cooling tower or a boiler) to meet a portion of the peak heating or cooling load. This work uses three case studies (two cooling-dominated, one heating-dominated) to demonstrate the performance of the hybrid approach. Three buildings were studied for a year; the measured data was used to validate models of each system. The models were used to analyze further improvements to the hybrid approach, and establish that this approach has positive impacts, both economically and environmentally. Lessons learned by those who design and operate the systems are also documented, including discussions of equipment sizing, pump operation, and cooling tower control. Finally, the measured data sets and models that were created during this work are described; these materials have been made freely available for further study of hybrid systems.

Hybrid Models of Alternative Current Filter for Hvdc

Directory of Open Access Journals (Sweden)

Ufa Ruslan A.

2017-01-01

Full Text Available Based on a hybrid simulation concept of HVDC, the developed hybrid AC filter models, providing the sufficiently full and adequate modeling of all single continuous spectrum of quasi-steady-state and transient processes in the filter, are presented. The obtained results suggest that usage of the hybrid simulation approach is carried out a methodically accurate with guaranteed instrumental error solution of differential equation systems of mathematical models of HVDC.

A systematic approach of bottom-up assessment methodology for an optimal design of hybrid solar/wind energy resources – Case study at middle east region

International Nuclear Information System (INIS)

Ifaei, Pouya; Karbassi, Abdolreza; Jacome, Gabriel; Yoo, ChangKyoo

2017-01-01

Highlights: • Proposing DaSOSaCa flowchart as a novel hybrid solar/wind assessment approach. • Calculating four key parameters to generate synthetic wind hourly data for Iran. • Proposing technical and economic hybrid solar/wind GIS maps of Iran. • Revising renewable energies management plans of Iran by macroeconomic evaluation. - Abstract: In the current study, an algorithm-based data processing, sizing, optimization, sensitivity analysis and clustering approach (DaSOSaCa) is proposed as an efficient simultaneous solar/wind assessment methodology. Accordingly, data processing is performed to obtain reliable high quality meteorological data among various datasets, which are used for hybrid photovoltaic/wind turbine/storage/converter system optimal design for consequent sites in a large region. The optimal hybrid systems are consequently simulated to meet hourly power demand in various sites. The solar/wind fraction and net present cost of the systems are then used as the technical and economic clustering variables, respectively. The clustering results are finally used as input to obtain novel hybrid solar/wind GIS maps. Iran is selected as the case study to validate the proposed methodology and detail its applicability. Ten minute annual global horizontal radiation, wind speed, and temperature data are analyzed, and the optimal, robust hybrid systems are simulated for various sites in order to classify the country. The generated GIS maps show that Iran can be efficiently clustered into four technical and five economic clusters under optimal conditions. The clustering results prove that Iran is mainly a solar country with approximately 74% solar power fraction under optimum conditions. A macroeconomic evaluation using DaSOSaCa also reveals that the nominal discount rate is recommended to be greater than 20% considering the current economic situation for the renewable energy sector in Iran. An environmental analysis results show that an average 106.68 tonCO 2

Hybridized centroid technique for 3D Molodensky-Badekas ...

African Journals Online (AJOL)

In view of this, the present study developed and tested two new hybrid centroid techniques known as the harmonic-quadratic mean and arithmetic-quadratic mean centroids. The proposed hybrid approaches were compared with the geometric mean, harmonic mean, median, quadratic mean and arithmetic mean. In addition ...

Towards a Pattern Language for Hybrid Education

DEFF Research Database (Denmark)

Köppe, Christian; Nørgård, Rikke Toft; Pedersen, Alex Young

2018-01-01

In this paper we offer an initial framework for a pattern language of hybrid education. With the term hybrid education, we imply the use of educa- tional design patterns that actively strive to cut across, circumventing or upheave traditional dichotomies within education such as physical-digital......, academic-nonacademic, online-offline, formal-informal, learning-teaching and individual-collective. In doing so, hybrid education invites uncertainty, open-endedness, risk-taking, experimentation, critical creativity, disruption, dialogue and democracy (back) into the heart of education. Accordingly we see...... on teaching to the test, playing it safe, rankings or gaming the system approaches. Rather, hybrid education focuses on open-endedness, risk-taking, relational entanglements, experimentation, exploration and empathy. In this way, designing for hybrid education is in this paper achieved, partly by taking...

Optical Code-Division Multiple-Access and Wavelength Division Multiplexing: Hybrid Scheme Review

OpenAIRE

P. Susthitha Menon; Sahbudin Shaari; Isaac A.M. Ashour; Hesham A. Bakarman

2012-01-01

Problem statement: Hybrid Optical Code-Division Multiple-Access (OCDMA) and Wavelength-Division Multiplexing (WDM) have flourished as successful schemes for expanding the transmission capacity as well as enhancing the security for OCDMA. However, a comprehensive review related to this hybrid system are lacking currently. Approach: The purpose of this paper is to review the literature on OCDMA-WDM overlay systems, including our hybrid approach of one-dimensional coding of SAC OCDMA with WDM si...

Transcatheter pulmonary valve replacement by hybrid approach using a novel polymeric prosthetic heart valve: proof of concept in sheep.

Directory of Open Access Journals (Sweden)

Ben Zhang

Full Text Available Since 2000, transcatheter pulmonary valve replacement has steadily advanced. However, the available prosthetic valves are restricted to bioprosthesis which have defects like poor durability. Polymeric heart valve is thought as a promising alternative to bioprosthesis. In this study, we introduced a novel polymeric transcatheter pulmonary valve and evaluated its feasibility and safety in sheep by a hybrid approach.We designed a novel polymeric trileaflet transcatheter pulmonary valve with a balloon-expandable stent, and the valve leaflets were made of 0.1-mm expanded polytetrafluoroethylene (ePTFE coated with phosphorylcholine. We chose glutaraldehyde-treated bovine pericardium valves as control. Pulmonary valve stents were implanted in situ by a hybrid transapical approach in 10 healthy sheep (8 for polymeric valve and 2 for bovine pericardium valve, weighing an average of 22.5±2.0 kg. Angiography and cardiac catheter examination were performed after implantation to assess immediate valvular functionality. After 4-week follow-up, angiography, echocardiography, computed tomography, and cardiac catheter examination were used to assess early valvular function. One randomly selected sheep with polymeric valve was euthanized and the explanted valved stent was analyzed macroscopically and microscopically.Implantation was successful in 9 sheep. Angiography at implantation showed all 9 prosthetic valves demonstrated orthotopic position and normal functionality. All 9 sheep survived at 4-week follow-up. Four-week follow-up revealed no evidence of valve stent dislocation or deformation and normal valvular and cardiac functionality. The cardiac catheter examination showed the peak-peak transvalvular pressure gradient of the polymeric valves was 11.9±5.0 mmHg, while that of two bovine pericardium valves were 11 and 17 mmHg. Gross morphology demonstrated good opening and closure characteristics. No thrombus or calcification was seen macroscopically

A hybrid training approach for leaf area index estimation via Cubist and random forests machine-learning

KAUST Repository

McCabe, Matthew

2017-12-06

With an increasing volume and dimensionality of Earth observation data, enhanced integration of machine-learning methodologies is needed to effectively analyze and utilize these information rich datasets. In machine-learning, a training dataset is required to establish explicit associations between a suite of explanatory ‘predictor’ variables and the target property. The specifics of this learning process can significantly influence model validity and portability, with a higher generalization level expected with an increasing number of observable conditions being reflected in the training dataset. Here we propose a hybrid training approach for leaf area index (LAI) estimation, which harnesses synergistic attributes of scattered in-situ measurements and systematically distributed physically based model inversion results to enhance the information content and spatial representativeness of the training data. To do this, a complimentary training dataset of independent LAI was derived from a regularized model inversion of RapidEye surface reflectances and subsequently used to guide the development of LAI regression models via Cubist and random forests (RF) decision tree methods. The application of the hybrid training approach to a broad set of Landsat 8 vegetation index (VI) predictor variables resulted in significantly improved LAI prediction accuracies and spatial consistencies, relative to results relying on in-situ measurements alone for model training. In comparing the prediction capacity and portability of the two machine-learning algorithms, a pair of relatively simple multi-variate regression models established by Cubist performed best, with an overall relative mean absolute deviation (rMAD) of ∼11%, determined based on a stringent scene-specific cross-validation approach. In comparison, the portability of RF regression models was less effective (i.e., an overall rMAD of ∼15%), which was attributed partly to model saturation at high LAI in association

A hybrid training approach for leaf area index estimation via Cubist and random forests machine-learning

Science.gov (United States)

Houborg, Rasmus; McCabe, Matthew F.

2018-01-01

With an increasing volume and dimensionality of Earth observation data, enhanced integration of machine-learning methodologies is needed to effectively analyze and utilize these information rich datasets. In machine-learning, a training dataset is required to establish explicit associations between a suite of explanatory 'predictor' variables and the target property. The specifics of this learning process can significantly influence model validity and portability, with a higher generalization level expected with an increasing number of observable conditions being reflected in the training dataset. Here we propose a hybrid training approach for leaf area index (LAI) estimation, which harnesses synergistic attributes of scattered in-situ measurements and systematically distributed physically based model inversion results to enhance the information content and spatial representativeness of the training data. To do this, a complimentary training dataset of independent LAI was derived from a regularized model inversion of RapidEye surface reflectances and subsequently used to guide the development of LAI regression models via Cubist and random forests (RF) decision tree methods. The application of the hybrid training approach to a broad set of Landsat 8 vegetation index (VI) predictor variables resulted in significantly improved LAI prediction accuracies and spatial consistencies, relative to results relying on in-situ measurements alone for model training. In comparing the prediction capacity and portability of the two machine-learning algorithms, a pair of relatively simple multi-variate regression models established by Cubist performed best, with an overall relative mean absolute deviation (rMAD) of ∼11%, determined based on a stringent scene-specific cross-validation approach. In comparison, the portability of RF regression models was less effective (i.e., an overall rMAD of ∼15%), which was attributed partly to model saturation at high LAI in association with

A hybrid training approach for leaf area index estimation via Cubist and random forests machine-learning

KAUST Repository

McCabe, Matthew; McCabe, Matthew

2017-01-01

With an increasing volume and dimensionality of Earth observation data, enhanced integration of machine-learning methodologies is needed to effectively analyze and utilize these information rich datasets. In machine-learning, a training dataset is required to establish explicit associations between a suite of explanatory ‘predictor’ variables and the target property. The specifics of this learning process can significantly influence model validity and portability, with a higher generalization level expected with an increasing number of observable conditions being reflected in the training dataset. Here we propose a hybrid training approach for leaf area index (LAI) estimation, which harnesses synergistic attributes of scattered in-situ measurements and systematically distributed physically based model inversion results to enhance the information content and spatial representativeness of the training data. To do this, a complimentary training dataset of independent LAI was derived from a regularized model inversion of RapidEye surface reflectances and subsequently used to guide the development of LAI regression models via Cubist and random forests (RF) decision tree methods. The application of the hybrid training approach to a broad set of Landsat 8 vegetation index (VI) predictor variables resulted in significantly improved LAI prediction accuracies and spatial consistencies, relative to results relying on in-situ measurements alone for model training. In comparing the prediction capacity and portability of the two machine-learning algorithms, a pair of relatively simple multi-variate regression models established by Cubist performed best, with an overall relative mean absolute deviation (rMAD) of ∼11%, determined based on a stringent scene-specific cross-validation approach. In comparison, the portability of RF regression models was less effective (i.e., an overall rMAD of ∼15%), which was attributed partly to model saturation at high LAI in association

Incorporating historical information in biosimilar trials: Challenges and a hybrid Bayesian-frequentist approach.

Science.gov (United States)

Mielke, Johanna; Schmidli, Heinz; Jones, Byron

2018-05-01

For the approval of biosimilars, it is, in most cases, necessary to conduct large Phase III clinical trials in patients to convince the regulatory authorities that the product is comparable in terms of efficacy and safety to the originator product. As the originator product has already been studied in several trials beforehand, it seems natural to include this historical information into the showing of equivalent efficacy. Since all studies for the regulatory approval of biosimilars are confirmatory studies, it is required that the statistical approach has reasonable frequentist properties, most importantly, that the Type I error rate is controlled-at least in all scenarios that are realistic in practice. However, it is well known that the incorporation of historical information can lead to an inflation of the Type I error rate in the case of a conflict between the distribution of the historical data and the distribution of the trial data. We illustrate this issue and confirm, using the Bayesian robustified meta-analytic-predictive (MAP) approach as an example, that simultaneously controlling the Type I error rate over the complete parameter space and gaining power in comparison to a standard frequentist approach that only considers the data in the new study, is not possible. We propose a hybrid Bayesian-frequentist approach for binary endpoints that controls the Type I error rate in the neighborhood of the center of the prior distribution, while improving the power. We study the properties of this approach in an extensive simulation study and provide a real-world example. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A HYBRID GENETIC ALGORITHM-NEURAL NETWORK APPROACH FOR PRICING CORES AND REMANUFACTURED CORES

Directory of Open Access Journals (Sweden)

M. Seidi

2012-01-01

Full Text Available

ENGLISH ABSTRACT:Sustainability has become a major issue in most economies, causing many leading companies to focus on product recovery and reverse logistics. Remanufacturing is an industrial process that makes used products reusable. One of the important aspects in both reverse logistics and remanufacturing is the pricing of returned and remanufactured products (called cores. In this paper, we focus on pricing the cores and remanufactured cores. First we present a mathematical model for this purpose. Since this model does not satisfy our requirements, we propose a simulation optimisation approach. This approach consists of a hybrid genetic algorithm based on a neural network employed as the fitness function. We use automata learning theory to obtain the learning rate required for training the neural network. Numerical results demonstrate that the optimal value of the acquisition price of cores and price of remanufactured cores is obtained by this approach.

AFRIKAANSE OPSOMMING: Volhoubaarheid het ‘n belangrike saak geword in die meeste ekonomieë, wat verskeie maatskappye genoop het om produkherwinning en omgekeerde logistiek te onder oë te neem. Hervervaardiging is ‘n industriële proses wat gebruikte produkte weer bruikbaar maak. Een van die belangrike aspekte in beide omgekeerde logistiek en hervervaardiging is die prysbepaling van herwinne en hervervaardigde produkte. Hierdie artikel fokus op die prysbepalingsaspekte by wyse van ‘n wiskundige model.

Introgressive hybridization in Iberian cyprinid fishes:a cytogenomic approach to homoploid Leuciscinae

OpenAIRE

Pereira, Carla Sofia Alves, 1983-

2013-01-01

Tese de doutoramento, Biologia (Biologia Evolutiva), Universidade de Lisboa, Faculdade de Ciências, 2013 Hybridization is currently a well-recognized process amongst animals responsible for biodiversity, evolution and speciation processes while defying most species concepts. Hybridization is prevalent among fishes, particularly cyprinids, which therefore constitute good models of study (1) to access general patterns of genomic variation, (2) to identify the genetic basis and the evolutiona...

Two-dimensional Semiconductor-Superconductor Hybrids

DEFF Research Database (Denmark)

Suominen, Henri Juhani

This thesis investigates hybrid two-dimensional semiconductor-superconductor (Sm-S) devices and presents a new material platform exhibiting intimate Sm-S coupling straight out of the box. Starting with the conventional approach, we investigate coupling superconductors to buried quantum well....... To overcome these issues we integrate the superconductor directly into the semiconducting material growth stack, depositing it in-situ in a molecular beam epitaxy system under high vacuum. We present a number of experiments on these hybrid heterostructures, demonstrating near unity interface transparency...

Hybrid video-assisted and limited open (VALO) resection of superior sulcus tumors.

Science.gov (United States)

Nun, Alon Ben; Simansky, David; Rokah, Merav; Zeitlin, Nona; Avi, Roni Ben; Soudack, Michalle; Golan, Nir; Apel, Sarit; Bar, Jair; Yelin, Alon

2016-06-01

To compare the postoperative recovery of patients with superior sulcus tumors (Pancoast tumors) following conventional open surgery vs. a hybrid video-assisted and limited open approach (VALO). The subjects of this retrospective study were 20 patients we operated on to resect a Pancoast tumor. All patients received induction chemo-radiation followed by surgery, performed via either a conventional thoracotomy approach (n = 10) or the hybrid VALO approach (n = 10). In the hybrid VALO group, lobectomy and internal chest wall preparation were performed using a video technique, with rib resection and specimen removal through a limited incision. There was no mortality in either group. Two patients from the thoracotomy group required mechanical ventilation, but there was no major morbidity in the hybrid VALO group. The operative times were similar for the two procedures. The average length of hospital stay was shorter and the average pain scores were significantly lower in the hybrid VALO group. The incidence of chronic pain was 10 % in the hybrid VALO group vs. 50 % in the thoracotomy group. Hybrid VALO resection of Pancoast tumors is feasible and safe, resulting in faster patient recovery and a significantly lower incidence of severe chronic pain than open thoracotomy. We conclude that centers experienced with video-assisted lobectomy should consider hybrid VALO surgery as the procedure of choice for Pancoast tumors.

A hybrid mammalian cell cycle model

Directory of Open Access Journals (Sweden)

Vincent Noël

2013-08-01

Full Text Available Hybrid modeling provides an effective solution to cope with multiple time scales dynamics in systems biology. Among the applications of this method, one of the most important is the cell cycle regulation. The machinery of the cell cycle, leading to cell division and proliferation, combines slow growth, spatio-temporal re-organisation of the cell, and rapid changes of regulatory proteins concentrations induced by post-translational modifications. The advancement through the cell cycle comprises a well defined sequence of stages, separated by checkpoint transitions. The combination of continuous and discrete changes justifies hybrid modelling approaches to cell cycle dynamics. We present a piecewise-smooth version of a mammalian cell cycle model, obtained by hybridization from a smooth biochemical model. The approximate hybridization scheme, leading to simplified reaction rates and binary event location functions, is based on learning from a training set of trajectories of the smooth model. We discuss several learning strategies for the parameters of the hybrid model.

Modelling the solar wind interaction with Mercury by a quasi-neutral hybrid model

Directory of Open Access Journals (Sweden)

E. Kallio

Full Text Available Quasi-neutral hybrid model is a self-consistent modelling approach that includes positively charged particles and an electron fluid. The approach has received an increasing interest in space plasma physics research because it makes it possible to study several plasma physical processes that are difficult or impossible to model by self-consistent fluid models, such as the effects associated with the ions’ finite gyroradius, the velocity difference between different ion species, or the non-Maxwellian velocity distribution function. By now quasi-neutral hybrid models have been used to study the solar wind interaction with the non-magnetised Solar System bodies of Mars, Venus, Titan and comets. Localized, two-dimensional hybrid model runs have also been made to study terrestrial dayside magnetosheath. However, the Hermean plasma environment has not yet been analysed by a global quasi-neutral hybrid model.

In this paper we present a new quasi-neutral hybrid model developed to study various processes associated with the Mercury-solar wind interaction. Emphasis is placed on addressing advantages and disadvantages of the approach to study different plasma physical processes near the planet. The basic assumptions of the approach and the algorithms used in the new model are thoroughly presented. Finally, some of the first three-dimensional hybrid model runs made for Mercury are presented.

The resulting macroscopic plasma parameters and the morphology of the magnetic field demonstrate the applicability of the new approach to study the Mercury-solar wind interaction globally. In addition, the real advantage of the kinetic hybrid model approach is to study the property of individual ions, and the study clearly demonstrates the large potential of the approach to address these more detailed issues by a quasi-neutral hybrid model in the future.

Key words. Magnetospheric physics

Interactive Digital Storytelling: Towards a Hybrid Conceptual Approach

OpenAIRE

Spierling, Ulrike

2005-01-01

1 Introduction In this contribution, Interactive Digital Storytelling is viewed as a hybrid form of game design and cinematic storytelling for the understanding and making of future learning and entertainment applications. The paper shall present formal design models that provide a conceptual bridge between both traditional linear narrative techniques as well as agent-based emergent conversations with virtual characters. In summary, a theoretical classification of thinking models for authors ...

Genomic Prediction of Barley Hybrid Performance

Directory of Open Access Journals (Sweden)

Norman Philipp

2016-07-01

Full Text Available Hybrid breeding in barley ( L. offers great opportunities to accelerate the rate of genetic improvement and to boost yield stability. A crucial requirement consists of the efficient selection of superior hybrid combinations. We used comprehensive phenotypic and genomic data from a commercial breeding program with the goal of examining the potential to predict the hybrid performances. The phenotypic data were comprised of replicated grain yield trials for 385 two-way and 408 three-way hybrids evaluated in up to 47 environments. The parental lines were genotyped using a 3k single nucleotide polymorphism (SNP array based on an Illumina Infinium assay. We implemented ridge regression best linear unbiased prediction modeling for additive and dominance effects and evaluated the prediction ability using five-fold cross validations. The prediction ability of hybrid performances based on general combining ability (GCA effects was moderate, amounting to 0.56 and 0.48 for two- and three-way hybrids, respectively. The potential of GCA-based hybrid prediction requires that both parental components have been evaluated in a hybrid background. This is not necessary for genomic prediction for which we also observed moderate cross-validated prediction abilities of 0.51 and 0.58 for two- and three-way hybrids, respectively. This exemplifies the potential of genomic prediction in hybrid barley. Interestingly, prediction ability using the two-way hybrids as training population and the three-way hybrids as test population or vice versa was low, presumably, because of the different genetic makeup of the parental source populations. Consequently, further research is needed to optimize genomic prediction approaches combining different source populations in barley.

High-density hybrid interconnect methodologies

International Nuclear Information System (INIS)

John, J.; Zimmermann, L.; Moor, P.De; Hoof, C.Van

2003-01-01

Full text: The presentation gives an overview of the state-of-the-art of hybrid integration and in particular the IMEC technological approaches that will be able to address future hybrid detector needs. The dense hybrid flip-chip integration of an array of detectors and its dedicated readout electronics can be achieved with a variety of solderbump techniques such as pure Indium or Indium alloys, Ph-In, Ni/PbSn, but also conducting polymers... Particularly for cooled applications or ultra-high density applications, Indium solderbump technology (electroplated or evaporated) is the method of choice. The state-of-the-art of solderbump technologies that are to a high degree independent of the underlying detector material will be presented and examples of interconnect densities between 5x1E4cm-2 and 1x1E6 cm-2 will be demonstrated. For several classes of detectors, flip-chip integration is not allowed since the detectors have to be illuminated from the top. This applies to image sensors for EUV applications such as GaN/AlGaN based detectors and to MEMS-based sensors. In such cases, the only viable interconnection method has to be through the (thinned) detector wafer followed by a solderbump-based integration. The approaches for dense and ultra-dense through-the-wafer interconnect 'vias' will be presented and wafer thinning approaches will be shown

The Effect of Teaching Methods and Learning Styles on Students’ English Achievement (An Experimental Study at Junior High School 1 Pasangkayu

Directory of Open Access Journals (Sweden)

Syahrul Munir

2019-10-01

Full Text Available The objectives of the research are to determine the effects of teaching methods (STAD and jigsaw and learning styles (visual, auditory, and kinesthetic on students’ English achievement. This research is an experimental study conducted at Junior High School Pasangkayu in 2014 with 213 sample which is selected stratified-randomly (n = 68. The results of the research are as follow: (1 English achievement of students taught with STAD is better than those of taught with jigsaw; (2 there is no significant difference in  English achievement among visual, auditory, and kinesthetic students; (3 there is any significant effect of interaction among teaching method and learning styles on students’ learning English achievement. The research also find out that for visual students, studying English achievement of students taught with STAD is better than that of students taught with jigsaw; for auditory students, learning English achievement  of students taught with jigsaw is better than that of students taught with STAD; and for kinesthetic students, English achievement of students taught with STAD is better than that of students taught with jigsaw. To sum up, STAD is more effective than jigsaw in improving students’ English achievement. STAD is suitable to improve English achievement of visual and kinesthetic students, and jigsaw is suitable to improve English achievement of auditory students.

Cardiac surgery or interventional cardiology? Why not both? Let's go hybrid.

Science.gov (United States)

Papakonstantinou, Nikolaos A; Baikoussis, Nikolaos G; Dedeilias, Panagiotis; Argiriou, Michalis; Charitos, Christos

2017-01-01

A hybrid strategy, firstly performed in the 1990s, is a combination of tools available only in the catheterization laboratory with those available only in the operating room in order to minimize surgical morbidity and face with any cardiovascular lesion. The continuous evolution of stent technology along with the adoption of minimally invasive surgical approaches, make hybrid approaches an attractive alternative to standard surgical or transcatheter techniques for any given set of cardiovascular lesions. Examples include hybrid coronary revascularization, when an open surgical anastomosis of the left internal mammary artery to the left anterior descending coronary artery is performed along with stent implantation in non-left anterior descending coronary vessels, open heart valve surgery combined with percutaneous coronary interventions to coronary lesions, hybrid aortic arch debranching combined with endovascular grafting for thoracic aortic aneurysms, hybrid endocardial and epicardial atrial fibrillation procedures, and carotid artery stenting along with coronary artery bypass grafting. The cornerstone of success for all of these methods is the productive collaboration between cardiac surgeons and interventional cardiologists. The indications and patient selection of these procedures are still to be defined. However, high-risk patients have already been shown to benefit from hybrid approaches. Copyright © 2016 Japanese College of Cardiology. Published by Elsevier Ltd. All rights reserved.

Stability Analysis for Hybrid Automata Using Conservative Gains

NARCIS (Netherlands)

Langerak, Romanus; Engell, S.; Guegen, H.; Polderman, Jan W.; Krilavicius, T.; Zaytoon, J.

2003-01-01

This paper presents a stability analysis approach for a class of hybrid automata. It is assumed that the dynamics in each location of the hybrid automaton is linear and asymptotically stable, and that the guards on the transitions are hyperplanes in the state space. For each pair of ingoing and

Statistical sampling approaches for soil monitoring

NARCIS (Netherlands)

Brus, D.J.

2014-01-01

This paper describes three statistical sampling approaches for regional soil monitoring, a design-based, a model-based and a hybrid approach. In the model-based approach a space-time model is exploited to predict global statistical parameters of interest such as the space-time mean. In the hybrid

Disease processes as hybrid dynamical systems

Directory of Open Access Journals (Sweden)

Pietro Liò

2012-08-01

Full Text Available We investigate the use of hybrid techniques in complex processes of infectious diseases. Since predictive disease models in biomedicine require a multiscale approach for understanding the molecule-cell-tissue-organ-body interactions, heterogeneous methodologies are often employed for describing the different biological scales. Hybrid models provide effective means for complex disease modelling where the action and dosage of a drug or a therapy could be meaningfully investigated: the infection dynamics can be classically described in a continuous fashion, while the scheduling of multiple treatment discretely. We define an algebraic language for specifying general disease processes and multiple treatments, from which a semantics in terms of hybrid dynamical system can be derived. Then, the application of control-theoretic tools is proposed in order to compute the optimal scheduling of multiple therapies. The potentialities of our approach are shown in the case study of the SIR epidemic model and we discuss its applicability on osteomyelitis, a bacterial infection affecting the bone remodelling system in a specific and multiscale manner. We report that formal languages are helpful in giving a general homogeneous formulation for the different scales involved in a multiscale disease process; and that the combination of hybrid modelling and control theory provides solid grounds for computational medicine.

Engineering of a novel adjuvant based on lipid-polymer hybrid nanoparticles: A quality-by-design approach.

Science.gov (United States)

Rose, Fabrice; Wern, Jeanette Erbo; Ingvarsson, Pall Thor; van de Weert, Marco; Andersen, Peter; Follmann, Frank; Foged, Camilla

2015-07-28

The purpose of this study was to design a novel and versatile adjuvant intended for mucosal vaccination based on biodegradable poly(DL-lactic-co-glycolic acid) (PLGA) nanoparticles (NPs) modified with the cationic surfactant dimethyldioctadecylammonium (DDA) bromide and the immunopotentiator trehalose-6,6'-dibehenate (TDB) (CAF01) to tailor humoral and cellular immunity characterized by antibodies and Th1/Th17 responses. Such responses are important for the protection against diseases caused by intracellular bacteria such as Chlamydia trachomatis and Mycobacterium tuberculosis. The hybrid NPs were engineered using an oil-in-water single emulsion method and a quality-by-design approach was adopted to define the optimal operating space (OOS). Four critical process parameters (CPPs) were identified, including the acetone concentration in the water phase, the stabilizer [polyvinylalcohol (PVA)] concentration, the lipid-to-total solid ratio, and the total concentration. The CPPs were linked to critical quality attributes consisting of the particle size, polydispersity index (PDI), zeta-potential, thermotropic phase behavior, yield and stability. A central composite face-centered design was performed followed by multiple linear regression analysis. The size, PDI, enthalpy of the phase transition and yield were successfully modeled, whereas the models for the zeta-potential and the stability were poor. Cryo-transmission electron microscopy revealed that the main structural effect on the nanoparticle architecture is caused by the use of PVA, and two different morphologies were identified: i) A PLGA core coated with one or several concentric lipid bilayers, and ii) a PLGA nanoshell encapsulating lipid membrane structures. The optimal formulation, identified from the OOS, was evaluated in vivo. The hybrid NPs induced antibody and Th1/Th17 immune responses that were similar in quality and magnitude to the response induced by DDA/TDB liposomes, showing that the adjuvant

A hybrid solution approach for a multi-objective closed-loop logistics network under uncertainty

Science.gov (United States)

Mehrbod, Mehrdad; Tu, Nan; Miao, Lixin

2015-06-01

The design of closed-loop logistics (forward and reverse logistics) has attracted growing attention with the stringent pressures of customer expectations, environmental concerns and economic factors. This paper considers a multi-product, multi-period and multi-objective closed-loop logistics network model with regard to facility expansion as a facility location-allocation problem, which more closely approximates real-world conditions. A multi-objective mixed integer nonlinear programming formulation is linearized by defining new variables and adding new constraints to the model. By considering the aforementioned model under uncertainty, this paper develops a hybrid solution approach by combining an interactive fuzzy goal programming approach and robust counterpart optimization based on three well-known robust counterpart optimization formulations. Finally, this paper compares the results of the three formulations using different test scenarios and parameter-sensitive analysis in terms of the quality of the final solution, CPU time, the level of conservatism, the degree of closeness to the ideal solution, the degree of balance involved in developing a compromise solution, and satisfaction degree.

Using a Hybrid Approach for a Leadership Cohort Program

Science.gov (United States)

Norman, Maxine A.

2013-01-01

Because information technology continues to change rapidly, Extension is challenged with learning and using technology appropriately. We assert Extension cannot shy away from the challenges but must embrace technology because audiences and external forces demand it. A hybrid, or blended, format of a leadership cohort program was offered to public…

A Two-Step Hybrid Approach for Modeling the Nonlinear Dynamic Response of Piezoelectric Energy Harvesters

Directory of Open Access Journals (Sweden)

Claudio Maruccio

2018-01-01

Full Text Available An effective hybrid computational framework is described here in order to assess the nonlinear dynamic response of piezoelectric energy harvesting devices. The proposed strategy basically consists of two steps. First, fully coupled multiphysics finite element (FE analyses are performed to evaluate the nonlinear static response of the device. An enhanced reduced-order model is then derived, where the global dynamic response is formulated in the state-space using lumped coefficients enriched with the information derived from the FE simulations. The electromechanical response of piezoelectric beams under forced vibrations is studied by means of the proposed approach, which is also validated by comparing numerical predictions with some experimental results. Such numerical and experimental investigations have been carried out with the main aim of studying the influence of material and geometrical parameters on the global nonlinear response. The advantage of the presented approach is that the overall computational and experimental efforts are significantly reduced while preserving a satisfactory accuracy in the assessment of the global behavior.

Dynamical coupling of plasmons and molecular excitations by hybrid quantum/classical calculations: time-domain approach

International Nuclear Information System (INIS)

Sakko, Arto; Rossi, Tuomas P; Nieminen, Risto M

2014-01-01

The presence of plasmonic material influences the optical properties of nearby molecules in untrivial ways due to the dynamical plasmon-molecule coupling. We combine quantum and classical calculation schemes to study this phenomenon in a hybrid system that consists of a Na 2 molecule located in the gap between two Au/Ag nanoparticles. The molecule is treated quantum-mechanically with time-dependent density-functional theory, and the nanoparticles with quasistatic classical electrodynamics. The nanoparticle dimer has a plasmon resonance in the visible part of the electromagnetic spectrum, and the Na 2 molecule has an electron-hole excitation in the same energy range. Due to the dynamical interaction of the two subsystems the plasmon and the molecular excitations couple, creating a hybridized molecular-plasmon excited state. This state has unique properties that yield e.g. enhanced photoabsorption compared to the freestanding Na 2 molecule. The computational approach used enables decoupling of the mutual plasmon-molecule interaction, and our analysis verifies that it is not legitimate to neglect the backcoupling effect when describing the dynamical interaction between plasmonic material and nearby molecules. Time-resolved analysis shows nearly instantaneous formation of the coupled state, and provides an intuitive picture of the underlying physics. (paper)

Polymer Combustion as a Basis for Hybrid Propulsion: A Comprehensive Review and New Numerical Approaches

Directory of Open Access Journals (Sweden)

Vasily Novozhilov

2011-10-01

Full Text Available Hybrid Propulsion is an attractive alternative to conventional liquid and solid rocket motors. This is an active area of research and technological developments. Potential wide application of Hybrid Engines opens the possibility for safer and more flexible space vehicle launching and manoeuvring. The present paper discusses fundamental combustion issues related to further development of Hybrid Rockets. The emphasis is made on the two aspects: (1 properties of potential polymeric fuels, and their modification, and (2 implementation of comprehensive CFD models for combustion in Hybrid Engines. Fundamentals of polymeric fuel combustion are discussed. Further, steps necessary to accurately describe their burning behaviour by means of CFD models are investigated. Final part of the paper presents results of preliminary CFD simulations of fuel burning process in Hybrid Engine using a simplified set-up.

Interactions among biotic and abiotic factors affect the reliability of tungsten microneedles puncturing in vitro and in vivo peripheral nerves: A hybrid computational approach

Energy Technology Data Exchange (ETDEWEB)

Sergi, Pier Nicola, E-mail: p.sergi@sssup.it [Translational Neural Engineering Laboratory, The Biorobotics Institute, Scuola Superiore Sant' Anna, Viale Rinaldo Piaggio 34, Pontedera, 56025 (Italy); Jensen, Winnie [Department of Health Science and Technology, Fredrik Bajers Vej 7, 9220 Aalborg (Denmark); Yoshida, Ken [Department of Biomedical Engineering, Indiana University - Purdue University Indianapolis, 723 W. Michigan St., SL220, Indianapolis, IN 46202 (United States)

2016-02-01

Tungsten is an elective material to produce slender and stiff microneedles able to enter soft tissues and minimize puncture wounds. In particular, tungsten microneedles are used to puncture peripheral nerves and insert neural interfaces, bridging the gap between the nervous system and robotic devices (e.g., hand prostheses). Unfortunately, microneedles fail during the puncture process and this failure is not dependent on stiffness or fracture toughness of the constituent material. In addition, the microneedles' performances decrease during in vivo trials with respect to the in vitro ones. This further effect is independent on internal biotic effects, while it seems to be related to external biotic causes. Since the exact synergy of phenomena decreasing the in vivo reliability is still not known, this work explored the connection between in vitro and in vivo behavior of tungsten microneedles through the study of interactions between biotic and abiotic factors. A hybrid computational approach, simultaneously using theoretical relationships and in silico models of nerves, was implemented to model the change of reliability varying the microneedle diameter, and to predict in vivo performances by using in vitro reliability and local differences between in vivo and in vitro mechanical response of nerves. - Highlights: • We provide phenomenological Finite Element (FE) models of peripheral nerves to study the interactions with W microneedles • We provide a general interaction-based approach to model the reliability of slender microneedles • We evaluate the reliability of W microneedels to puncture in vivo nerves • We provide a novel synergistic hybrid approach (theory + simulations) involving interactions among biotic and abiotic factors • We validate the hybrid approach by using experimental data from literature.

Interactions among biotic and abiotic factors affect the reliability of tungsten microneedles puncturing in vitro and in vivo peripheral nerves: A hybrid computational approach

International Nuclear Information System (INIS)

Sergi, Pier Nicola; Jensen, Winnie; Yoshida, Ken

2016-01-01

Tungsten is an elective material to produce slender and stiff microneedles able to enter soft tissues and minimize puncture wounds. In particular, tungsten microneedles are used to puncture peripheral nerves and insert neural interfaces, bridging the gap between the nervous system and robotic devices (e.g., hand prostheses). Unfortunately, microneedles fail during the puncture process and this failure is not dependent on stiffness or fracture toughness of the constituent material. In addition, the microneedles' performances decrease during in vivo trials with respect to the in vitro ones. This further effect is independent on internal biotic effects, while it seems to be related to external biotic causes. Since the exact synergy of phenomena decreasing the in vivo reliability is still not known, this work explored the connection between in vitro and in vivo behavior of tungsten microneedles through the study of interactions between biotic and abiotic factors. A hybrid computational approach, simultaneously using theoretical relationships and in silico models of nerves, was implemented to model the change of reliability varying the microneedle diameter, and to predict in vivo performances by using in vitro reliability and local differences between in vivo and in vitro mechanical response of nerves. - Highlights: • We provide phenomenological Finite Element (FE) models of peripheral nerves to study the interactions with W microneedles • We provide a general interaction-based approach to model the reliability of slender microneedles • We evaluate the reliability of W microneedels to puncture in vivo nerves • We provide a novel synergistic hybrid approach (theory + simulations) involving interactions among biotic and abiotic factors • We validate the hybrid approach by using experimental data from literature

Numerical Prediction of Combustion-induced Noise using a hybrid LES/CAA approach

Science.gov (United States)

Ihme, Matthias; Pitsch, Heinz; Kaltenbacher, Manfred

2006-11-01

Noise generation in technical devices is an increasingly important problem. Jet engines in particular produce sound levels that not only are a nuisance but may also impair hearing. The noise emitted by such engines is generated by different sources such as jet exhaust, fans or turbines, and combustion. Whereas the former acoustic mechanisms are reasonably well understood, combustion-generated noise is not. A methodology for the prediction of combustion-generated noise is developed. In this hybrid approach unsteady acoustic source terms are obtained from an LES and the propagation of pressure perturbations are obtained using acoustic analogies. Lighthill's acoustic analogy and a non-linear wave equation, accounting for variable speed of sound, have been employed. Both models are applied to an open diffusion flame. The effects on the far field pressure and directivity due to the variation of speed of sound are analyzed. Results for the sound pressure level will be compared with experimental data.

A hybrid stochastic hierarchy equations of motion approach to treat the low temperature dynamics of non-Markovian open quantum systems

Science.gov (United States)

Moix, Jeremy M.; Cao, Jianshu

2013-10-01

The hierarchical equations of motion technique has found widespread success as a tool to generate the numerically exact dynamics of non-Markovian open quantum systems. However, its application to low temperature environments remains a serious challenge due to the need for a deep hierarchy that arises from the Matsubara expansion of the bath correlation function. Here we present a hybrid stochastic hierarchical equation of motion (sHEOM) approach that alleviates this bottleneck and leads to a numerical cost that is nearly independent of temperature. Additionally, the sHEOM method generally converges with fewer hierarchy tiers allowing for the treatment of larger systems. Benchmark calculations are presented on the dynamics of two level systems at both high and low temperatures to demonstrate the efficacy of the approach. Then the hybrid method is used to generate the exact dynamics of systems that are nearly impossible to treat by the standard hierarchy. First, exact energy transfer rates are calculated across a broad range of temperatures revealing the deviations from the Förster rates. This is followed by computations of the entanglement dynamics in a system of two qubits at low temperature spanning the weak to strong system-bath coupling regimes.

A deep learning / neuroevolution hybrid for visual control

DEFF Research Database (Denmark)

Poulsen, Andreas Precht; Thorhauge, Mark; Funch, Mikkel Hvilshj

2017-01-01

This paper presents a deep learning / neuroevolution hybrid approach called DLNE, which allows FPS bots to learn to aim & shoot based only on high-dimensional raw pixel input. The deep learning component is responsible for visual recognition and translating raw pixels to compact feature...... representations, while the evolving network takes those features as inputs to infer actions. The results suggest that combining deep learning and neuroevolution in a hybrid approach is a promising research direction that could make complex visual domains directly accessible to networks trained through evolution....

Innovative molecular approach to the identification of Colossoma macropomum and its hybrids

Directory of Open Access Journals (Sweden)

Fátima Gomes

2012-06-01

Full Text Available Tambaqui (Colossoma macropomum is the fish species most commonly raised in the Brazilian fish farms. The species is highly adaptable to captive conditions, and is both fast-growing and relatively fecund. In recent years, artificial breeding has produced hybrids with Characiform species, known as "Tambacu" and "Tambatinga". Identifying hybrids is a difficult process, given their morphological similarities with the parent species. This study presents an innovative molecular approach to the identification of hybrids based primarily on Multiplex PCR of a nuclear gene (α-Tropomyosin, which was tested on 93 specimens obtained from fish farms in northern Brazil. The sequencing of a 505-bp fragment of the Control Region (CR permitted the identification of the maternal lineage of the specimen, all of which corresponded to C. macropomum. Unexpectedly, only two CR haplotype were found in 93 samples, a very low genetic diversity for the pisciculture of Tambaqui. Multiplex PCR identified 42 hybrids, in contrast with 23 identified by the supplier on the basis of external morphology. This innovative tool has considerable potential for the development of the Brazilian aquaculture, given the possibility of the systematic identification of the genetic traits of both fry-producing stocks, and the fry and juveniles raised in farms.O Tambaqui (Colossoma macropomum é a espécie de peixe mais comumente cultivada em pisciculturas no Brasil. A espécie é altamente adaptada às condições de cativeiro, apresentando rápido crescimento e alta fecundidade. Nos últimos anos tem ocorrido o cruzamento artificial entre espécies de Characiformes, produzindo os híbridos "Tambacu" e "Tambatinga". A identificação de híbridos é uma tarefa difícil, em virtude da grande similaridade morfológica entre as espécies parentais. O presente estudo apresenta uma abordagem molecular inovadora para identificação de híbridos com base em PCR Multiplex de um gene nuclear (�

Computing all hybridization networks for multiple binary phylogenetic input trees.

Science.gov (United States)

Albrecht, Benjamin

2015-07-30

The computation of phylogenetic trees on the same set of species that are based on different orthologous genes can lead to incongruent trees. One possible explanation for this behavior are interspecific hybridization events recombining genes of different species. An important approach to analyze such events is the computation of hybridization networks. This work presents the first algorithm computing the hybridization number as well as a set of representative hybridization networks for multiple binary phylogenetic input trees on the same set of taxa. To improve its practical runtime, we show how this algorithm can be parallelized. Moreover, we demonstrate the efficiency of the software Hybroscale, containing an implementation of our algorithm, by comparing it to PIRNv2.0, which is so far the best available software computing the exact hybridization number for multiple binary phylogenetic trees on the same set of taxa. The algorithm is part of the software Hybroscale, which was developed specifically for the investigation of hybridization networks including their computation and visualization. Hybroscale is freely available(1) and runs on all three major operating systems. Our simulation study indicates that our approach is on average 100 times faster than PIRNv2.0. Moreover, we show how Hybroscale improves the interpretation of the reported hybridization networks by adding certain features to its graphical representation.

Infrared exploration of the architectural heritage: from passive infrared thermography to hybrid infrared thermography (HIRT approach

Directory of Open Access Journals (Sweden)

Sfarra, S.

2016-09-01

Full Text Available Up to now, infrared thermographic approaches have been considered either passive or active. In the latter case, the heat flux is historically attributed to a non-natural heat source. The use of the sun has recently been incorporated into the active approach thanks to multi-temporal inspections. In this paper, an innovative hybrid thermographic (HIRT approach is illustrated. It combines both the time component and the solar source to obtain quantitative information such as the defect depth. Thermograms were obtained by inspecting the facade of the Santa Maria Collemaggio church (L’Aquila, Italy, whereas quantitative results related to the sub-superficial discontinuities were obtained thanks to the use of advanced techniques. Experimental results linked to passive approach (i.e., the mosaicking procedure of the thermograms performed by selecting a set of historic churches are also included in order to explain, when and where, the hybrid procedure should be used.Hasta la fecha, los enfoques sobre la termografía infrarroja han sido considerados, o pasivos, o activos. En este último caso, el flujo de calor se obtiene a través de una fuente de calor no natural. El uso de energía solar ha sido recientemente incorporado al enfoque activo gracias a los estudios multitemporales. En este trabajo, se ilustra un enfoque innovador de la termografía híbrida (HIRT. Se combina tanto el componente de tiempo y la fuente de energía solar para recuperar la información cuantitativa así como la profundidad del defecto. Las imágenes térmicas se obtuvieron mediante el análisis de la fachada de la Iglesia de Santa María Collemaggio (L’Aquila, Italia, mientras que los resultados cuantitativos inherentes a las discontinuidades sub-superficiales se obtuvieron gracias al uso de otras técnicas avanzadas. Los resultados experimentales vinculados al enfoque pasivo (es decir, el proceso de mosaico de las imágenes térmicas derivan de un conjunto de Iglesias

Evolutionary Design of Both Topologies and Parameters of a Hybrid Dynamical System

DEFF Research Database (Denmark)

Dupuis, Jean-Francois; Fan, Zhun; Goodman, Erik

2012-01-01

This paper investigates the issue of evolutionary design of open-ended plants for hybrid dynamical systems--i.e. both their topologies and parameters. Hybrid bond graphs are used to represent dynamical systems involving both continuous and discrete system dynamics. Genetic programming, with some...... of hybrid dynamical systems that fulfill predefined design specifications. A comprehensive investigation of a case study of DC-DC converter design demonstrates the feasibility and effectiveness of the HBGGP approach. Important characteristics of the approach are also discussed, with some future research...

Mathematical Modeling of Hybrid Electrical Engineering Systems

Directory of Open Access Journals (Sweden)

A. A. Lobaty

2016-01-01

Full Text Available A large class of systems that have found application in various industries and households, electrified transportation facilities and energy sector has been classified as electrical engineering systems. Their characteristic feature is a combination of continuous and discontinuous modes of operation, which is reflected in the appearance of a relatively new term “hybrid systems”. A wide class of hybrid systems is pulsed DC converters operating in a pulse width modulation, which are non-linear systems with variable structure. Using various methods for linearization it is possible to obtain linear mathematical models that rather accurately simulate behavior of such systems. However, the presence in the mathematical models of exponential nonlinearities creates considerable difficulties in the implementation of digital hardware. The solution can be found while using an approximation of exponential functions by polynomials of the first order, that, however, violates the rigor accordance of the analytical model with characteristics of a real object. There are two practical approaches to synthesize algorithms for control of hybrid systems. The first approach is based on the representation of the whole system by a discrete model which is described by difference equations that makes it possible to synthesize discrete algorithms. The second approach is based on description of the system by differential equations. The equations describe synthesis of continuous algorithms and their further implementation in a digital computer included in the control loop system. The paper considers modeling of a hybrid electrical engineering system using differential equations. Neglecting the pulse duration, it has been proposed to describe behavior of vector components in phase coordinates of the hybrid system by stochastic differential equations containing generally non-linear differentiable random functions. A stochastic vector-matrix equation describing dynamics of the

Application of Genomic In Situ Hybridization in Horticultural Science

Directory of Open Access Journals (Sweden)

Fahad Ramzan

2017-01-01

Full Text Available Molecular cytogenetic techniques, such as in situ hybridization methods, are admirable tools to analyze the genomic structure and function, chromosome constituents, recombination patterns, alien gene introgression, genome evolution, aneuploidy, and polyploidy and also genome constitution visualization and chromosome discrimination from different genomes in allopolyploids of various horticultural crops. Using GISH advancement as multicolor detection is a significant approach to analyze the small and numerous chromosomes in fruit species, for example, Diospyros hybrids. This analytical technique has proved to be the most exact and effective way for hybrid status confirmation and helps remarkably to distinguish donor parental genomes in hybrids such as Clivia, Rhododendron, and Lycoris ornamental hybrids. The genome characterization facilitates in hybrid selection having potential desirable characteristics during the early hybridization breeding, as this technique expedites to detect introgressed sequence chromosomes. This review study epitomizes applications and advancements of genomic in situ hybridization (GISH techniques in horticultural plants.

Hybrid Magnetics and Power Applications

DEFF Research Database (Denmark)

Mo, Wai Keung; Paasch, Kasper

2017-01-01

A hybrid magnetic approach, merging two different magnetic core properites such as ferrite and iron powder cores, is an effective solution for power converter applications. It can offer similar magnetic properties to that of magnetic powder cores but showing less copper loss than powder cores....... In order to prevent ferrite core saturation, placing an effective air gap within the ferrite core is a key method to obtain optimum hybrid magnetic performance. Furthermore, a relatively large inductance at low loading current is an excellent way to minimze power loss in order to achieve high efficiency...

Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat

KAUST Repository

Liu, Guozheng

2016-07-06

Bread-making quality traits are central targets for wheat breeding. The objectives of our study were to (1) examine the presence of major effect QTLs for quality traits in a Central European elite wheat population, (2) explore the optimal strategy for predicting the hybrid performance for wheat quality traits, and (3) investigate the effects of marker density and the composition and size of the training population on the accuracy of prediction of hybrid performance. In total 135 inbred lines of Central European bread wheat (Triticum aestivum L.) and 1,604 hybrids derived from them were evaluated for seven quality traits in up to six environments. The 135 parental lines were genotyped using a 90k single-nucleotide polymorphism array. Genome-wide association mapping initially suggested presence of several quantitative trait loci (QTLs), but cross-validation rather indicated the absence of major effect QTLs for all quality traits except of 1000-kernel weight. Genomic selection substantially outperformed marker-assisted selection in predicting hybrid performance. A resampling study revealed that increasing the effective population size in the estimation set of hybrids is relevant to boost the accuracy of prediction for an unrelated test population.

Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat.

Directory of Open Access Journals (Sweden)

Guozheng Liu

Full Text Available Bread-making quality traits are central targets for wheat breeding. The objectives of our study were to (1 examine the presence of major effect QTLs for quality traits in a Central European elite wheat population, (2 explore the optimal strategy for predicting the hybrid performance for wheat quality traits, and (3 investigate the effects of marker density and the composition and size of the training population on the accuracy of prediction of hybrid performance. In total 135 inbred lines of Central European bread wheat (Triticum aestivum L. and 1,604 hybrids derived from them were evaluated for seven quality traits in up to six environments. The 135 parental lines were genotyped using a 90k single-nucleotide polymorphism array. Genome-wide association mapping initially suggested presence of several quantitative trait loci (QTLs, but cross-validation rather indicated the absence of major effect QTLs for all quality traits except of 1000-kernel weight. Genomic selection substantially outperformed marker-assisted selection in predicting hybrid performance. A resampling study revealed that increasing the effective population size in the estimation set of hybrids is relevant to boost the accuracy of prediction for an unrelated test population.

Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat

KAUST Repository

Liu, Guozheng; Zhao, Yusheng; Gowda, Manje; Longin, C. Friedrich H.; Reif, Jochen C.; Mette, Michael F.

2016-01-01

Bread-making quality traits are central targets for wheat breeding. The objectives of our study were to (1) examine the presence of major effect QTLs for quality traits in a Central European elite wheat population, (2) explore the optimal strategy for predicting the hybrid performance for wheat quality traits, and (3) investigate the effects of marker density and the composition and size of the training population on the accuracy of prediction of hybrid performance. In total 135 inbred lines of Central European bread wheat (Triticum aestivum L.) and 1,604 hybrids derived from them were evaluated for seven quality traits in up to six environments. The 135 parental lines were genotyped using a 90k single-nucleotide polymorphism array. Genome-wide association mapping initially suggested presence of several quantitative trait loci (QTLs), but cross-validation rather indicated the absence of major effect QTLs for all quality traits except of 1000-kernel weight. Genomic selection substantially outperformed marker-assisted selection in predicting hybrid performance. A resampling study revealed that increasing the effective population size in the estimation set of hybrids is relevant to boost the accuracy of prediction for an unrelated test population.

Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat

Science.gov (United States)

Liu, Guozheng; Zhao, Yusheng; Gowda, Manje; Longin, C. Friedrich H.; Reif, Jochen C.; Mette, Michael F.

2016-01-01

Bread-making quality traits are central targets for wheat breeding. The objectives of our study were to (1) examine the presence of major effect QTLs for quality traits in a Central European elite wheat population, (2) explore the optimal strategy for predicting the hybrid performance for wheat quality traits, and (3) investigate the effects of marker density and the composition and size of the training population on the accuracy of prediction of hybrid performance. In total 135 inbred lines of Central European bread wheat (Triticum aestivum L.) and 1,604 hybrids derived from them were evaluated for seven quality traits in up to six environments. The 135 parental lines were genotyped using a 90k single-nucleotide polymorphism array. Genome-wide association mapping initially suggested presence of several quantitative trait loci (QTLs), but cross-validation rather indicated the absence of major effect QTLs for all quality traits except of 1000-kernel weight. Genomic selection substantially outperformed marker-assisted selection in predicting hybrid performance. A resampling study revealed that increasing the effective population size in the estimation set of hybrids is relevant to boost the accuracy of prediction for an unrelated test population. PMID:27383841

Hybrid Thermochemical/Biological Processing

Science.gov (United States)

Brown, Robert C.

The conventional view of biorefineries is that lignocellulosic plant material will be fractionated into cellulose, hemicellulose, lignin, and terpenes before these components are biochemically converted into market products. Occasionally, these plants include a thermochemical step at the end of the process to convert recalcitrant plant components or mixed waste streams into heat to meet thermal energy demands elsewhere in the facility. However, another possibility for converting high-fiber plant materials is to start by thermochemically processing it into a uniform intermediate product that can be biologically converted into a bio-based product. This alternative route to bio-based products is known as hybrid thermochemical/biological processing. There are two distinct approaches to hybrid processing: (a) gasification followed by fermentation of the resulting gaseous mixture of carbon monoxide (CO), hydrogen (H2), and carbon dioxide (CO2) and (b) fast pyrolysis followed by hydrolysis and/or fermentation of the anhydrosugars found in the resulting bio-oil. This article explores this "cart before the horse" approach to biorefineries.

Spin injection across a hybrid heterojunction: Theoretical understanding and experimental approach (invited)

DEFF Research Database (Denmark)

Hu, C.M.; Nitta, J.; Jensen, Ane

2002-01-01

Spin injection across a hybrid ferromagnet/semiconductor junction has proven to be difficult, unlike in an all-metal junction used in giant magnetoresistance devices. The difference responsible is highlighted in a simple model. We perform spin-injection-detection experiments on devices with two...... ferromagnetic contacts on a two-dimensional electron gas confined in an InAs quantum well. We demonstrate that spin injection allows the hybrid device to combine both the advantage of the ferromagnet as well as that of the semiconductor....

Conceptual design of distillation-based hybrid separation processes.

Science.gov (United States)

Skiborowski, Mirko; Harwardt, Andreas; Marquardt, Wolfgang

2013-01-01

Hybrid separation processes combine different separation principles and constitute a promising design option for the separation of complex mixtures. Particularly, the integration of distillation with other unit operations can significantly improve the separation of close-boiling or azeotropic mixtures. Although the design of single-unit operations is well understood and supported by computational methods, the optimal design of flowsheets of hybrid separation processes is still a challenging task. The large number of operational and design degrees of freedom requires a systematic and optimization-based design approach. To this end, a structured approach, the so-called process synthesis framework, is proposed. This article reviews available computational methods for the conceptual design of distillation-based hybrid processes for the separation of liquid mixtures. Open problems are identified that must be addressed to finally establish a structured process synthesis framework for such processes.

Aeroacoustic analysis of the human phonation process based on a hybrid acoustic PIV approach

Science.gov (United States)

Lodermeyer, Alexander; Tautz, Matthias; Becker, Stefan; Döllinger, Michael; Birk, Veronika; Kniesburges, Stefan

2018-01-01

The detailed analysis of sound generation in human phonation is severely limited as the accessibility to the laryngeal flow region is highly restricted. Consequently, the physical basis of the underlying fluid-structure-acoustic interaction that describes the primary mechanism of sound production is not yet fully understood. Therefore, we propose the implementation of a hybrid acoustic PIV procedure to evaluate aeroacoustic sound generation during voice production within a synthetic larynx model. Focusing on the flow field downstream of synthetic, aerodynamically driven vocal folds, we calculated acoustic source terms based on the velocity fields obtained by time-resolved high-speed PIV applied to the mid-coronal plane. The radiation of these sources into the acoustic far field was numerically simulated and the resulting acoustic pressure was finally compared with experimental microphone measurements. We identified the tonal sound to be generated downstream in a small region close to the vocal folds. The simulation of the sound propagation underestimated the tonal components, whereas the broadband sound was well reproduced. Our results demonstrate the feasibility to locate aeroacoustic sound sources inside a synthetic larynx using a hybrid acoustic PIV approach. Although the technique employs a 2D-limited flow field, it accurately reproduces the basic characteristics of the aeroacoustic field in our larynx model. In future studies, not only the aeroacoustic mechanisms of normal phonation will be assessable, but also the sound generation of voice disorders can be investigated more profoundly.

Personalizing Medicine Through Hybrid Imaging and Medical Big Data Analysis

Directory of Open Access Journals (Sweden)

Laszlo Papp

2018-06-01

Full Text Available Medical imaging has evolved from a pure visualization tool to representing a primary source of analytic approaches toward in vivo disease characterization. Hybrid imaging is an integral part of this approach, as it provides complementary visual and quantitative information in the form of morphological and functional insights into the living body. As such, non-invasive imaging modalities no longer provide images only, but data, as stated recently by pioneers in the field. Today, such information, together with other, non-imaging medical data creates highly heterogeneous data sets that underpin the concept of medical big data. While the exponential growth of medical big data challenges their processing, they inherently contain information that benefits a patient-centric personalized healthcare. Novel machine learning approaches combined with high-performance distributed cloud computing technologies help explore medical big data. Such exploration and subsequent generation of knowledge require a profound understanding of the technical challenges. These challenges increase in complexity when employing hybrid, aka dual- or even multi-modality image data as input to big data repositories. This paper provides a general insight into medical big data analysis in light of the use of hybrid imaging information. First, hybrid imaging is introduced (see further contributions to this special Research Topic, also in the context of medical big data, then the technological background of machine learning as well as state-of-the-art distributed cloud computing technologies are presented, followed by the discussion of data preservation and data sharing trends. Joint data exploration endeavors in the context of in vivo radiomics and hybrid imaging will be presented. Standardization challenges of imaging protocol, delineation, feature engineering, and machine learning evaluation will be detailed. Last, the paper will provide an outlook into the future role of hybrid

Genome-Wide Prediction of the Performance of Three-Way Hybrids in Barley

Directory of Open Access Journals (Sweden)

Zuo Li

2017-03-01

Full Text Available Predicting the grain yield performance of three-way hybrids is challenging. Three-way crosses are relevant for hybrid breeding in barley ( L. and maize ( L. adapted to East Africa. The main goal of our study was to implement and evaluate genome-wide prediction approaches of the performance of three-way hybrids using data of single-cross hybrids for a scenario in which parental lines of the three-way hybrids originate from three genetically distinct subpopulations. We extended the ridge regression best linear unbiased prediction (RRBLUP and devised a genomic selection model allowing for subpopulation-specific marker effects (GSA-RRBLUP: general and subpopulation-specific additive RRBLUP. Using an empirical barley data set, we showed that applying GSA-RRBLUP tripled the prediction ability of three-way hybrids from 0.095 to 0.308 compared with RRBLUP, modeling one additive effect for all three subpopulations. The experimental findings were further substantiated with computer simulations. Our results emphasize the potential of GSA-RRBLUP to improve genome-wide hybrid prediction of three-way hybrids for scenarios of genetically diverse parental populations. Because of the advantages of the GSA-RRBLUP model in dealing with hybrids from different parental populations, it may also be a promising approach to boost the prediction ability for hybrid breeding programs based on genetically diverse heterotic groups.

A NoSQL–SQL Hybrid Organization and Management Approach for Real-Time Geospatial Data: A Case Study of Public Security Video Surveillance

Directory of Open Access Journals (Sweden)

Chen Wu

2017-01-01

Full Text Available With the widespread deployment of ground, air and space sensor sources (internet of things or IoT, social networks, sensor networks, the integrated applications of real-time geospatial data from ubiquitous sensors, especially in public security and smart city domains, are becoming challenging issues. The traditional geographic information system (GIS mostly manages time-discretized geospatial data by means of the Structured Query Language (SQL database management system (DBMS and emphasizes query and retrieval of massive historical geospatial data on disk. This limits its capability for on-the-fly access of real-time geospatial data for online analysis in real time. This paper proposes a hybrid database organization and management approach with SQL relational databases (RDB and not only SQL (NoSQL databases (including the main memory database, MMDB, and distributed files system, DFS. This hybrid approach makes full use of the advantages of NoSQL and SQL DBMS for the real-time access of input data and structured on-the-fly analysis results which can meet the requirements of increased spatio-temporal big data linking analysis. The MMDB facilitates real-time access of the latest input data such as the sensor web and IoT, and supports the real-time query for online geospatial analysis. The RDB stores change information such as multi-modal features and abnormal events extracted from real-time input data. The DFS on disk manages the massive geospatial data, and the extensible storage architecture and distributed scheduling of a NoSQL database satisfy the performance requirements of incremental storage and multi-user concurrent access. A case study of geographic video (GeoVideo surveillance of public security is presented to prove the feasibility of this hybrid organization and management approach.

Multimodal Logistics Network Design over Planning Horizon through a Hybrid Meta-Heuristic Approach

Science.gov (United States)

Shimizu, Yoshiaki; Yamazaki, Yoshihiro; Wada, Takeshi

Logistics has been acknowledged increasingly as a key issue of supply chain management to improve business efficiency under global competition and diversified customer demands. This study aims at improving a quality of strategic decision making associated with dynamic natures in logistics network optimization. Especially, noticing an importance to concern with a multimodal logistics under multiterms, we have extended a previous approach termed hybrid tabu search (HybTS). The attempt intends to deploy a strategic planning more concretely so that the strategic plan can link to an operational decision making. The idea refers to a smart extension of the HybTS to solve a dynamic mixed integer programming problem. It is a two-level iterative method composed of a sophisticated tabu search for the location problem at the upper level and a graph algorithm for the route selection at the lower level. To keep efficiency while coping with the resulting extremely large-scale problem, we invented a systematic procedure to transform the original linear program at the lower-level into a minimum cost flow problem solvable by the graph algorithm. Through numerical experiments, we verified the proposed method outperformed the commercial software. The results indicate the proposed approach can make the conventional strategic decision much more practical and is promising for real world applications.

A Hybrid Generalized Hidden Markov Model-Based Condition Monitoring Approach for Rolling Bearings.

Science.gov (United States)

Liu, Jie; Hu, Youmin; Wu, Bo; Wang, Yan; Xie, Fengyun

2017-05-18

The operating condition of rolling bearings affects productivity and quality in the rotating machine process. Developing an effective rolling bearing condition monitoring approach is critical to accurately identify the operating condition. In this paper, a hybrid generalized hidden Markov model-based condition monitoring approach for rolling bearings is proposed, where interval valued features are used to efficiently recognize and classify machine states in the machine process. In the proposed method, vibration signals are decomposed into multiple modes with variational mode decomposition (VMD). Parameters of the VMD, in the form of generalized intervals, provide a concise representation for aleatory and epistemic uncertainty and improve the robustness of identification. The multi-scale permutation entropy method is applied to extract state features from the decomposed signals in different operating conditions. Traditional principal component analysis is adopted to reduce feature size and computational cost. With the extracted features' information, the generalized hidden Markov model, based on generalized interval probability, is used to recognize and classify the fault types and fault severity levels. Finally, the experiment results show that the proposed method is effective at recognizing and classifying the fault types and fault severity levels of rolling bearings. This monitoring method is also efficient enough to quantify the two uncertainty components.

A Hybrid Generalized Hidden Markov Model-Based Condition Monitoring Approach for Rolling Bearings

Directory of Open Access Journals (Sweden)

Jie Liu

2017-05-01

Full Text Available The operating condition of rolling bearings affects productivity and quality in the rotating machine process. Developing an effective rolling bearing condition monitoring approach is critical to accurately identify the operating condition. In this paper, a hybrid generalized hidden Markov model-based condition monitoring approach for rolling bearings is proposed, where interval valued features are used to efficiently recognize and classify machine states in the machine process. In the proposed method, vibration signals are decomposed into multiple modes with variational mode decomposition (VMD. Parameters of the VMD, in the form of generalized intervals, provide a concise representation for aleatory and epistemic uncertainty and improve the robustness of identification. The multi-scale permutation entropy method is applied to extract state features from the decomposed signals in different operating conditions. Traditional principal component analysis is adopted to reduce feature size and computational cost. With the extracted features’ information, the generalized hidden Markov model, based on generalized interval probability, is used to recognize and classify the fault types and fault severity levels. Finally, the experiment results show that the proposed method is effective at recognizing and classifying the fault types and fault severity levels of rolling bearings. This monitoring method is also efficient enough to quantify the two uncertainty components.

A hybrid stochastic approach for self-location of wireless sensors in indoor environments.

Science.gov (United States)

Lloret, Jaime; Tomas, Jesus; Garcia, Miguel; Canovas, Alejandro

2009-01-01

Indoor location systems, especially those using wireless sensor networks, are used in many application areas. While the need for these systems is widely proven, there is a clear lack of accuracy. Many of the implemented applications have high errors in their location estimation because of the issues arising in the indoor environment. Two different approaches had been proposed using WLAN location systems: on the one hand, the so-called deductive methods take into account the physical properties of signal propagation. These systems require a propagation model, an environment map, and the position of the radio-stations. On the other hand, the so-called inductive methods require a previous training phase where the system learns the received signal strength (RSS) in each location. This phase can be very time consuming. This paper proposes a new stochastic approach which is based on a combination of deductive and inductive methods whereby wireless sensors could determine their positions using WLAN technology inside a floor of a building. Our goal is to reduce the training phase in an indoor environment, but, without an loss of precision. Finally, we compare the measurements taken using our proposed method in a real environment with the measurements taken by other developed systems. Comparisons between the proposed system and other hybrid methods are also provided.

A hybrid classical-quantum approach for ultra-scaled confined nanostructures : modeling and simulation*

Directory of Open Access Journals (Sweden)

Pietra Paola

2012-04-01

Full Text Available We propose a hybrid classical-quantum model to study the motion of electrons in ultra-scaled confined nanostructures. The transport of charged particles, considered as one dimensional, is described by a quantum effective mass model in the active zone coupled directly to a drift-diffusion problem in the rest of the device. We explain how this hybrid model takes into account the peculiarities due to the strong confinement and we present numerical simulations for a simplified carbon nanotube. Nous proposons un modèle hybride classique-quantique pour décrire le mouvement des électrons dans des nanostructures très fortement confinées. Le transport des particules, consideré unidimensionel, est décrit par un modèle quantique avec masse effective dans la zone active couplé à un problème de dérive-diffusion dans le reste du domaine. Nous expliquons comment ce modèle hybride prend en compte les spécificités de ce très fort confinement et nous présentons des résultats numériques pour un nanotube de carbone simplifié.

Reliable Radiation Hybrid Maps: An Efficient Scalable Clustering-based Approach

Science.gov (United States)

The process of mapping markers from radiation hybrid mapping (RHM) experiments is equivalent to the traveling salesman problem and, thereby, has combinatorial complexity. As an additional problem, experiments typically result in some unreliable markers that reduce the overall quality of the map. We ...

Activity Recognition Using Hybrid Generative/Discriminative Models on Home Environments Using Binary Sensors

Directory of Open Access Journals (Sweden)

Araceli Sanchis

2013-04-01

Full Text Available Activities of daily living are good indicators of elderly health status, and activity recognition in smart environments is a well-known problem that has been previously addressed by several studies. In this paper, we describe the use of two powerful machine learning schemes, ANN (Artificial Neural Network and SVM (Support Vector Machines, within the framework of HMM (Hidden Markov Model in order to tackle the task of activity recognition in a home setting. The output scores of the discriminative models, after processing, are used as observation probabilities of the hybrid approach. We evaluate our approach by comparing these hybrid models with other classical activity recognition methods using five real datasets. We show how the hybrid models achieve significantly better recognition performance, with significance level p < 0:05, proving that the hybrid approach is better suited for the addressed domain.

Hybrid stochastic simplifications for multiscale gene networks

Directory of Open Access Journals (Sweden)

Debussche Arnaud

2009-09-01

Full Text Available Abstract Background Stochastic simulation of gene networks by Markov processes has important applications in molecular biology. The complexity of exact simulation algorithms scales with the number of discrete jumps to be performed. Approximate schemes reduce the computational time by reducing the number of simulated discrete events. Also, answering important questions about the relation between network topology and intrinsic noise generation and propagation should be based on general mathematical results. These general results are difficult to obtain for exact models. Results We propose a unified framework for hybrid simplifications of Markov models of multiscale stochastic gene networks dynamics. We discuss several possible hybrid simplifications, and provide algorithms to obtain them from pure jump processes. In hybrid simplifications, some components are discrete and evolve by jumps, while other components are continuous. Hybrid simplifications are obtained by partial Kramers-Moyal expansion 123 which is equivalent to the application of the central limit theorem to a sub-model. By averaging and variable aggregation we drastically reduce simulation time and eliminate non-critical reactions. Hybrid and averaged simplifications can be used for more effective simulation algorithms and for obtaining general design principles relating noise to topology and time scales. The simplified models reproduce with good accuracy the stochastic properties of the gene networks, including waiting times in intermittence phenomena, fluctuation amplitudes and stationary distributions. The methods are illustrated on several gene network examples. Conclusion Hybrid simplifications can be used for onion-like (multi-layered approaches to multi-scale biochemical systems, in which various descriptions are used at various scales. Sets of discrete and continuous variables are treated with different methods and are coupled together in a physically justified approach.

A Frequency Control Approach for Hybrid Power System Using Multi-Objective Optimization

Directory of Open Access Journals (Sweden)

Mohammed Elsayed Lotfy

2017-01-01

Full Text Available A hybrid power system uses many wind turbine generators (WTG and solar photovoltaics (PV in isolated small areas. However, the output power of these renewable sources is not constant and can diverge quickly, which has a serious effect on system frequency and the continuity of demand supply. In order to solve this problem, this paper presents a new frequency control scheme for a hybrid power system to ensure supplying a high-quality power in isolated areas. The proposed power system consists of a WTG, PV, aqua-electrolyzer (AE, fuel cell (FC, battery energy storage system (BESS, flywheel (FW and diesel engine generator (DEG. Furthermore, plug-in hybrid electric vehicles (EVs are implemented at the customer side. A full-order observer is utilized to estimate the supply error. Then, the estimated supply error is considered in a frequency domain. The high-frequency component is reduced by BESS and FW; while the low-frequency component of supply error is mitigated using FC, EV and DEG. Two PI controllers are implemented in the proposed system to control the system frequency and reduce the supply error. The epsilon multi-objective genetic algorithm ( ε -MOGA is applied to optimize the controllers’ parameters. The performance of the proposed control scheme is compared with that of recent well-established techniques, such as a PID controller tuned by the quasi-oppositional harmony search algorithm (QOHSA. The effectiveness and robustness of the hybrid power system are investigated under various operating conditions.

Hybrid mimics and hybrid vigor in Arabidopsis

Science.gov (United States)

Wang, Li; Greaves, Ian K.; Groszmann, Michael; Wu, Li Min; Dennis, Elizabeth S.; Peacock, W. James

2015-01-01

F1 hybrids can outperform their parents in yield and vegetative biomass, features of hybrid vigor that form the basis of the hybrid seed industry. The yield advantage of the F1 is lost in the F2 and subsequent generations. In Arabidopsis, from F2 plants that have a F1-like phenotype, we have by recurrent selection produced pure breeding F5/F6 lines, hybrid mimics, in which the characteristics of the F1 hybrid are stabilized. These hybrid mimic lines, like the F1 hybrid, have larger leaves than the parent plant, and the leaves have increased photosynthetic cell numbers, and in some lines, increased size of cells, suggesting an increased supply of photosynthate. A comparison of the differentially expressed genes in the F1 hybrid with those of eight hybrid mimic lines identified metabolic pathways altered in both; these pathways include down-regulation of defense response pathways and altered abiotic response pathways. F6 hybrid mimic lines are mostly homozygous at each locus in the genome and yet retain the large F1-like phenotype. Many alleles in the F6 plants, when they are homozygous, have expression levels different to the level in the parent. We consider this altered expression to be a consequence of transregulation of genes from one parent by genes from the other parent. Transregulation could also arise from epigenetic modifications in the F1. The pure breeding hybrid mimics have been valuable in probing the mechanisms of hybrid vigor and may also prove to be useful hybrid vigor equivalents in agriculture. PMID:26283378

Hybrid Approach To Steganography System Based On Quantum Encryption And Chaos Algorithms

Directory of Open Access Journals (Sweden)

ZAID A. ABOD

2018-01-01

Full Text Available A hybrid scheme for secretly embedding image into a dithered multilevel image is presented. This work inputs both a cover image and secret image, which are scrambling and divided into groups to embedded together based on multiple chaos algorithms (Lorenz map, Henon map and Logistic map respectively. Finally, encrypt the embedded images by using one of the quantum cryptography mechanisms, which is quantum one time pad. The experimental results show that the proposed hybrid system successfully embedded images and combine with the quantum cryptography algorithms and gives high efficiency for secure communication.

DSP Control of Line Hybrid Active Filter

DEFF Research Database (Denmark)

Dan, Stan George; Benjamin, Doniga Daniel; Magureanu, R.

2005-01-01

Active Power Filters have been intensively explored in the past decade. Hybrid active filters inherit the efficiency of passive filters and the improved performance of active filters, and thus constitute a viable improved approach for harmonic compensation. In this paper a parallel hybrid filter...... is studied for current harmonic compensation. The hybrid filter is formed by a single tuned Le filter and a small-rated power active filter, which are directly connected in series without any matching transformer. Thus the required rating of the active filter is much smaller than a conventional standalone...... active filter. Simulation and experimental results obtained in laboratory confirmed the validity and effectiveness of the control....

Assume-Guarantee Abstraction Refinement Meets Hybrid Systems

Science.gov (United States)

Bogomolov, Sergiy; Frehse, Goran; Greitschus, Marius; Grosu, Radu; Pasareanu, Corina S.; Podelski, Andreas; Strump, Thomas

2014-01-01

Compositional verification techniques in the assume- guarantee style have been successfully applied to transition systems to efficiently reduce the search space by leveraging the compositional nature of the systems under consideration. We adapt these techniques to the domain of hybrid systems with affine dynamics. To build assumptions we introduce an abstraction based on location merging. We integrate the assume-guarantee style analysis with automatic abstraction refinement. We have implemented our approach in the symbolic hybrid model checker SpaceEx. The evaluation shows its practical potential. To the best of our knowledge, this is the first work combining assume-guarantee reasoning with automatic abstraction-refinement in the context of hybrid automata.

Hybrid antibiotics - clinical progress and novel designs.

Science.gov (United States)

Parkes, Alastair L; Yule, Ian A

2016-07-01

There is a growing need for new antibacterial agents, but success in development of antibiotics in recent years has been limited. This has led researchers to investigate novel approaches to finding compounds that are effective against multi-drug resistant bacteria, and that delay onset of resistance. One such strategy has been to link antibiotics to produce hybrids designed to overcome resistance mechanisms. The concept of dual-acting hybrid antibiotics was introduced and reviewed in this journal in 2010. In the present review the authors sought to discover how clinical candidates described had progressed, and to examine how the field has developed. In three sections the authors cover the clinical progress of hybrid antibiotics, novel agents produced from hybridisation of two or more small-molecule antibiotics, and novel agents produced from hybridisation of antibiotics with small-molecules that have complementary activity. Many key questions regarding dual-acting hybrid antibiotics remain to be answered, and the proposed benefits of this approach are yet to be demonstrated. While Cadazolid in particular continues to progress in the clinic, suggesting that there is promise in hybridisation through covalent linkage, it may be that properties other than antibacterial activity are key when choosing a partner molecule.

Is there a prospect for hybrid aortic arch surgery?

Science.gov (United States)

Bashir, Mohamad; Harky, Amer; Bilal, Haris

2018-05-16

The surge of endovascular repair of aortic aneurysm in current modern aortic surgery practice has been the key for surgical management of elective cases of thoracic aortic aneurysms. This has paved way for the combined hybrid approach to be amongst the armamentarium for the management of aortic arch disease. The pivotal understanding of the aortic arch natural history coupled with device technology advancement allowed surgeons insight into delivery of hybrid surgery with acceptable morbidity and mortality results. This review article provides current insights into hybrid technique of aortic arch aneurysm repair and the evidences behind its applicability to arch surgery. It is aimed to highlight the challenges encountered for this innovative approach and correlate its challenges to those that are met by the conventional open aortic arch repair.

A practical multi-objective design approach for optimum exhaust heat recovery from hybrid stand-alone PV-diesel power systems

International Nuclear Information System (INIS)

Yousefi, Moslem; Kim, Joong Hoon; Hooshyar, Danial; Yousefi, Milad; Sahari, Khairul Salleh Mohamed; Ahmad, Rodina Binti

2017-01-01

Highlights: • Heat recovery exchanger is designed based on practical conditions of a hybrid power system. • Off-the-grid electricity system modeling and analysis using micro-grid analysis software HOMER. • NSGA-II is used for the multi-objective design optimization task. • A new local search is proposed to incorporate the engineering knowledge in NSGA-II. • The proposed approach outperforms the existing ones. - Abstract: Integration of solar power and diesel generators (DGs) together with battery storage has proven to be an efficient choice for stand-alone power systems (SAPS). For higher energy efficiency, heat recovery from exhaust gas of the DG can also be employed to supply all or a portion of the thermal energy demand. Although the design of such heat recovery systems (HRSs) has been studied, the effect of solar power integration has not been taken into account. In this paper, a new approach for practical design of these systems based on varying engine loads is presented. Fast and elitist non-dominated sorting genetic algorithm (NSGA-II) equipped with a novel local search was used for the design process, considering conflicting objectives of annual energy recovery and total cost of the system, and six design variables. An integrated power system, designed for a remote SAPS, was used to evaluate the design approach. The optimum power supply system was first designed using the commercial software Hybrid Optimization of Multiple Energy Resources (HOMER), based on power demand and global solar energy in the region. Heat recovery design was based on the outcome of HOMER for DG hourly load, considering different power scenarios. The proposed approach improves the annual heat recovery of the PV/DG/battery system by 4%, PV/battery by 1.7%, and stand-alone DG by 1.8% when compared with a conventional design based on nominal DG load. The results prove that the proposed approach is effective and that load calculations should be taken into account prior to

Polemological Paradigm of Hybrid War Research

Directory of Open Access Journals (Sweden)

Roman Dodonov

2017-09-01

Full Text Available This article is devoted to the methodological problems and manipulative mechanisms of hybrid warfare. Owing to the polemological (from πολέμιος — war and λόγος — study approach the authors managed to systematize and summarize the theories of war and peace, clarify contemporary western concepts of warfare, outline the specifi cs of the Russian view on the hybrid war concept, assess the signifi cance of information and manipulation technologies for hybrid wars, analyze a number of geopolitical and socio-cultural dimensions of modern hybrid wars. The polemology is a branch of science, which studies the nature of armed confl icts and wars, their role in time and space, cycles, intensity, scope, scale, and causative relations and their classifi cation. Polemology deals with the wars and armed confl icts of the past, present and future. Novel hybrid wars take a respective place among them. They involve using all available warfare, regular and irregular, cyber and those allowing for the use of weapons of mass destruction, and also information, psychological and propaganda war using the latest information and media technologies. According to the classical approach, the state is the only subject of military actions, but today its role has changed dramatically under the infl uence of other political and economic supranational and trans-border factors. For the purpose of studying wars and armed confl icts from the polemological perspective it means the need to focus on social changes in all the areas of human life, on considering various elements of the political, economic or even technological context, which infl uence the war as a social phenomenon.

Hybrid Swarm Intelligence Optimization Approach for Optimal Data Storage Position Identification in Wireless Sensor Networks

Science.gov (United States)

Mohanasundaram, Ranganathan; Periasamy, Pappampalayam Sanmugam

2015-01-01

The current high profile debate with regard to data storage and its growth have become strategic task in the world of networking. It mainly depends on the sensor nodes called producers, base stations, and also the consumers (users and sensor nodes) to retrieve and use the data. The main concern dealt here is to find an optimal data storage position in wireless sensor networks. The works that have been carried out earlier did not utilize swarm intelligence based optimization approaches to find the optimal data storage positions. To achieve this goal, an efficient swam intelligence approach is used to choose suitable positions for a storage node. Thus, hybrid particle swarm optimization algorithm has been used to find the suitable positions for storage nodes while the total energy cost of data transmission is minimized. Clustering-based distributed data storage is utilized to solve clustering problem using fuzzy-C-means algorithm. This research work also considers the data rates and locations of multiple producers and consumers to find optimal data storage positions. The algorithm is implemented in a network simulator and the experimental results show that the proposed clustering and swarm intelligence based ODS strategy is more effective than the earlier approaches. PMID:25734182

Relative efficiency of hydrogen technologies for the hydrogen economy : a fuzzy AHP/DEA hybrid model approach

International Nuclear Information System (INIS)

Lee, S.

2009-01-01

As a provider of national energy security, the Korean Institute of Energy Research is seeking to establish a long term strategic technology roadmap for a hydrogen-based economy. This paper addressed 5 criteria regarding the strategy, notably economic impact, commercial potential, inner capacity, technical spinoff, and development cost. The fuzzy AHP and DEA hybrid model were used in a two-stage multi-criteria decision making approach to evaluate the relative efficiency of hydrogen technologies for the hydrogen economy. The fuzzy analytic hierarchy process reflects the uncertainty of human thoughts with interval values instead of clear-cut numbers. It therefore allocates the relative importance of 4 criteria, notably economic impact, commercial potential, inner capacity and technical spin-off. The relative efficiency of hydrogen technologies for the hydrogen economy can be measured via data envelopment analysis. It was concluded that the scientific decision making approach can be used effectively to allocate research and development resources and activities

Relative efficiency of hydrogen technologies for the hydrogen economy : a fuzzy AHP/DEA hybrid model approach

Energy Technology Data Exchange (ETDEWEB)

Lee, S. [Korea Inst. of Energy Research, Daejeon (Korea, Republic of). Energy Policy Research Division; Mogi, G. [Tokyo Univ., (Japan). Dept. of Technology Management for Innovation, Graduate School of Engineering; Kim, J. [Korea Inst. of Energy Research, Daejeon (Korea, Republic of)

2009-07-01

As a provider of national energy security, the Korean Institute of Energy Research is seeking to establish a long term strategic technology roadmap for a hydrogen-based economy. This paper addressed 5 criteria regarding the strategy, notably economic impact, commercial potential, inner capacity, technical spinoff, and development cost. The fuzzy AHP and DEA hybrid model were used in a two-stage multi-criteria decision making approach to evaluate the relative efficiency of hydrogen technologies for the hydrogen economy. The fuzzy analytic hierarchy process reflects the uncertainty of human thoughts with interval values instead of clear-cut numbers. It therefore allocates the relative importance of 4 criteria, notably economic impact, commercial potential, inner capacity and technical spin-off. The relative efficiency of hydrogen technologies for the hydrogen economy can be measured via data envelopment analysis. It was concluded that the scientific decision making approach can be used effectively to allocate research and development resources and activities.

A Model-Based Approach for Bridging Virtual and Physical Sensor Nodes in a Hybrid Simulation Framework

Directory of Open Access Journals (Sweden)

Mohammad Mozumdar

2014-06-01

Full Text Available The Model Based Design (MBD approach is a popular trend to speed up application development of embedded systems, which uses high-level abstractions to capture functional requirements in an executable manner, and which automates implementation code generation. Wireless Sensor Networks (WSNs are an emerging very promising application area for embedded systems. However, there is a lack of tools in this area, which would allow an application developer to model a WSN application by using high level abstractions, simulate it mapped to a multi-node scenario for functional analysis, and finally use the refined model to automatically generate code for different WSN platforms. Motivated by this idea, in this paper we present a hybrid simulation framework that not only follows the MBD approach for WSN application development, but also interconnects a simulated sub-network with a physical sub-network and then allows one to co-simulate them, which is also known as Hardware-In-the-Loop (HIL simulation.

A facile approach to fabricate flexible all-solid-state supercapacitors based on MnFe2O4/graphene hybrids

Science.gov (United States)

Cai, Weihua; Lai, Ting; Dai, Wanlin; Ye, Jianshan

2014-06-01

A critical challenge for the construction of flexible electrochemical capacitors is the preparation of flexible electrodes with large specific capacitance and robust mechanical strength. Here, we demonstrate a facile approach to make high performance and flexible electrodes by dropping MnFe2O4/graphene hybrid inks onto flexible graphite sheets (as current collectors and substrates) and drying under an infrared lamp. MnFe2O4/graphene hybrid inks are synthesized by immobilizing the MnFe2O4 microspheres on the graphene nanosheets via a simple solvothermal route. Electrochemical studies show that MnFe2O4/graphene exhibits a high capacitance of 300 F g-1 at a current density of 0.3 A g-1. In addition, the excellent electrochemical performance of a supercapacitor consisting of a sandwich structure of two pieces of MnFe2O4/graphene hybrids modified electrodes separated by polyvinyl alcohol (PVA)-H2SO4 gel electrolyte is further explored. Our studies reveal that the flexible supercapacitor device with 227 μm thickness can achieve a maximum specific capacitance of 120 F g-1 at a current density of 0.1 A g-1 and excellent cycle performance retaining 105% capacitance after 5000 cycles. This research may offer a method for the fabrication of lightweight, stable, flexible and high performance energy storage devices.

Novel brewing yeast hybrids: creation and application.

Science.gov (United States)

Krogerus, Kristoffer; Magalhães, Frederico; Vidgren, Virve; Gibson, Brian

2017-01-01

The natural interspecies Saccharomyces cerevisiae × Saccharomyces eubayanus hybrid yeast is responsible for global lager beer production and is one of the most important industrial microorganisms. Its success in the lager brewing environment is due to a combination of traits not commonly found in pure yeast species, principally low-temperature tolerance, and maltotriose utilization. Parental transgression is typical of hybrid organisms and has been exploited previously for, e.g., the production of wine yeast with beneficial properties. The parental strain S. eubayanus has only been discovered recently and newly created lager yeast strains have not yet been applied industrially. A number of reports attest to the feasibility of this approach and artificially created hybrids are likely to have a significant impact on the future of lager brewing. De novo S. cerevisiae × S. eubayanus hybrids outperform their parent strains in a number of respects, including, but not restricted to, fermentation rate, sugar utilization, stress tolerance, and aroma formation. Hybrid genome function and stability, as well as different techniques for generating hybrids and their relative merits are discussed. Hybridization not only offers the possibility of generating novel non-GM brewing yeast strains with unique properties, but is expected to aid in unraveling the complex evolutionary history of industrial lager yeast.

Online Assessment of Human-Robot Interaction for Hybrid Control of Walking

Directory of Open Access Journals (Sweden)

Ana de-los-Reyes

2011-12-01

Full Text Available Restoration of walking ability of Spinal Cord Injury subjects can be achieved by different approaches, as the use of robotic exoskeletons or electrical stimulation of the user’s muscles. The combined (hybrid approach has the potential to provide a solution to the drawback of each approach. Specific challenges must be addressed with specific sensory systems and control strategies. In this paper we present a system and a procedure to estimate muscle fatigue from online physical interaction assessment to provide hybrid control of walking, regarding the performances of the muscles under stimulation.

Assessment of regions priority for implementation of solar projects in Iran: New application of a hybrid multi-criteria decision making approach

International Nuclear Information System (INIS)

Vafaeipour, Majid; Hashemkhani Zolfani, Sarfaraz; Morshed Varzandeh, Mohammad Hossein; Derakhti, Arman; Keshavarz Eshkalag, Mahsa

2014-01-01

Highlights: • The economic, environmental, technical, social and risk criteria are considered. • Prioritization of regions for construction of solar power plants in Iran is assessed. • A hybrid MCDM approach ranked 25 scattered cities all around the country. • SWARA ranked the identified criteria, and WASPAS prioritized the alternatives. • Considering the ranked cities, a comprehensive GIS map of the country is provided. - Abstract: One of the promising ways to shift towards sustainable development has been the utilization of solar energy worldwide. Based on its geographical specifications, Iran enjoys high solar potential to implement feasible solar energy projects. However, to obtain the best productivity and payback, identification and prioritization of suitable regions for construction of expensive solar power plants is a delicate issue. In contrast with common assumptions, identifying appropriate geographical regions for implementation of such projects is not only associated with the amount of received solar radiation, but also there are many economic, environmental, technical, social and risk criteria (and their relevant sub-criteria) which must be taken into account. To address the complicated nature of the prioritization challenge caused by existence of various indicators, this paper applies a hybrid Multi-Criteria Decision Making (MCDM) approach and prioritizes 25 scattered cities all around the country for implementation of future solar power plants. For this, both quantitative and qualitative effective indicators are identified to be considered as the inputs to the utilized hybrid model. The Step-wise Weight Assessment Ratio Analysis (SWARA, proposed in 2010) method is employed to rank the identified criteria, and the Weighted Aggregates Sum Product Assessment (WASPAS, proposed in 2012) is applied to evaluate and prioritize the alternatives (cities) where Yazd city ranked first. Eventually via considering the ranked cities, a comprehensive GIS

Covercrete with hybrid functions - A novel approach to durable reinforced concrete structures

Energy Technology Data Exchange (ETDEWEB)

Tang, L.; Zhang, E.Q. [Chalmers University of Technology, SE-412 96 Gothenburg (Sweden); Fu, Y. [KTH Royal Institute of Technology, SE-106 91 Stockholm (Sweden); Schouenborg, B.; Lindqvist, J.E. [CBI Swedish Cement and Concrete Research Institute, c/o SP, Box 857, SE-501 15 Boraas (Sweden)

2012-12-15

Due to the corrosion of steel in reinforced concrete structures, the concrete with low water-cement ratio (w/c), high cement content, and large cover thickness is conventionally used for prolonging the passivation period of steel. Obviously, this conventional approach to durable concrete structures is at the sacrifice of more CO{sub 2} emission and natural resources through consuming higher amount of cement and more constituent materials, which is against sustainability. By placing an economically affordable conductive mesh made of carbon fiber or conductive polymer fiber in the near surface zone of concrete acting as anode we can build up a cathodic prevention system with intermittent low current density supplied by, e.g., the solar cells. In such a way, the aggressive negative ions such as Cl{sup -}, CO{sub 3}{sup 2-}, and SO{sub 4}{sup 2-} can be stopped near the cathodic (steel) zone. Thus the reinforcement steel is prevented from corrosion even in the concrete with relatively high w/c and small cover thickness. This conductive mesh functions not only as electrode, but also as surface reinforcement to prevent concrete surface from cracking. Therefore, this new type of covercrete has hybrid functions. This paper presents the theoretical analysis of feasibility of this approach and discusses the potential durability problems and possible solutions to the potential problems. (Copyright copyright 2012 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

Optimization of the fission--fusion hybrid concept

International Nuclear Information System (INIS)

Saltmarsh, M.J.; Grimes, W.R.; Santoro, R.T.

1979-04-01

One of the potentially attractive applications of controlled thermonuclear fusion is the fission--fusion hybrid concept. In this report we examine the possible role of the hybrid as a fissile fuel producer. We parameterize the advantages of the concept in terms of the performance of the fusion device and the breeding blanket and discuss some of the more troublesome features of existing design studies. The analysis suggests that hybrids based on deuterium--tritium (D--T) fusion devices are unlikely to be economically attractive and that they present formidable blanket technology problems. We suggest an alternative approach based on a semicatalyzed deuterium--deuterium (D--D) fusion reactor and a molten salt blanket. This concept is shown to emphasize the desirable features of the hybrid, to have considerably greater economic potential, and to mitigate many of the disadvantages of D--T-based systems

A novel hybrid approach for predicting wind farm power production based on wavelet transform, hybrid neural networks and imperialist competitive algorithm

International Nuclear Information System (INIS)

Aghajani, Afshin; Kazemzadeh, Rasool; Ebrahimi, Afshin

2016-01-01

Highlights: • Proposing a novel hybrid method for short-term prediction of wind farms with high accuracy. • Investigating the prediction accuracy for proposed method in comparison with other methods. • Investigating the effect of six types of parameters as input data on predictions. • Comparing results for 6 & 4 types of the input parameters – addition of pressure and air humidity. - Abstract: This paper proposes a novel hybrid approach to forecast electric power production in wind farms. Wavelet transform (WT) is employed to filter input data of wind power, while radial basis function (RBF) neural network is utilized for primary prediction. For better predictions the main forecasting engine is comprised of three multilayer perceptron (MLP) neural networks by different learning algorithms of Levenberg–Marquardt (LM), Broyden–Fletcher–Goldfarb–Shanno (BFGS), and Bayesian regularization (BR). Meta-heuristic technique Imperialist Competitive Algorithm (ICA) is used to optimize neural networks’ weightings in order to escape from local minima. In the forecast process, the real data of wind farms located in the southern part of Alberta, Canada, are used to train and test the proposed model. The data are a complete set of six meteorological and technical characteristics, including wind speed, wind power, wind direction, temperature, pressure, and air humidity. In order to demonstrate the efficiency of the proposed method, it is compared with several other wind power forecast techniques. Results of optimizations indicate the superiority of the proposed method over the other mentioned techniques; and, forecasting error is remarkably reduced. For instance, the average normalized root mean square error (NRMSE) and average mean absolute percentage error (MAPE) are respectively 11% and 14% lower for the proposed method in 1-h-ahead forecasts over a 24-h period with six types of input than those for the best of the compared models.

HyLTL: a temporal logic for model checking hybrid systems

Directory of Open Access Journals (Sweden)

Davide Bresolin

2013-08-01

Full Text Available The model-checking problem for hybrid systems is a well known challenge in the scientific community. Most of the existing approaches and tools are limited to safety properties only, or operates by transforming the hybrid system to be verified into a discrete one, thus loosing information on the continuous dynamics of the system. In this paper we present a logic for specifying complex properties of hybrid systems called HyLTL, and we show how it is possible to solve the model checking problem by translating the formula into an equivalent hybrid automaton. In this way the problem is reduced to a reachability problem on hybrid automata that can be solved by using existing tools.

Travelling Waves in Hybrid Chemotaxis Models

KAUST Repository

Franz, Benjamin

2013-12-18

Hybrid models of chemotaxis combine agent-based models of cells with partial differential equation models of extracellular chemical signals. In this paper, travelling wave properties of hybrid models of bacterial chemotaxis are investigated. Bacteria are modelled using an agent-based (individual-based) approach with internal dynamics describing signal transduction. In addition to the chemotactic behaviour of the bacteria, the individual-based model also includes cell proliferation and death. Cells consume the extracellular nutrient field (chemoattractant), which is modelled using a partial differential equation. Mesoscopic and macroscopic equations representing the behaviour of the hybrid model are derived and the existence of travelling wave solutions for these models is established. It is shown that cell proliferation is necessary for the existence of non-transient (stationary) travelling waves in hybrid models. Additionally, a numerical comparison between the wave speeds of the continuum models and the hybrid models shows good agreement in the case of weak chemotaxis and qualitative agreement for the strong chemotaxis case. In the case of slow cell adaptation, we detect oscillating behaviour of the wave, which cannot be explained by mean-field approximations. © 2013 Society for Mathematical Biology.

What controls the hybridization thermodynamics of spherical nucleic acids?

Science.gov (United States)

Randeria, Pratik S; Jones, Matthew R; Kohlstedt, Kevin L; Banga, Resham J; Olvera de la Cruz, Monica; Schatz, George C; Mirkin, Chad A

2015-03-18

The hybridization of free oligonucleotides to densely packed, oriented arrays of DNA modifying the surfaces of spherical nucleic acid (SNA)-gold nanoparticle conjugates occurs with negative cooperativity; i.e., each binding event destabilizes subsequent binding events. DNA hybridization is thus an ever-changing function of the number of strands already hybridized to the particle. Thermodynamic quantification of this behavior reveals a 3 orders of magnitude decrease in the binding constant for the capture of a free oligonucleotide by an SNA conjugate as the fraction of pre-hybridized strands increases from 0 to ∼30%. Increasing the number of pre-hybridized strands imparts an increasing enthalpic penalty to hybridization that makes binding more difficult, while simultaneously decreasing the entropic penalty to hybridization, which makes binding more favorable. Hybridization of free DNA to an SNA is thus governed by both an electrostatic barrier as the SNA accumulates charge with additional binding events and an effect consistent with allostery, where hybridization at certain sites on an SNA modify the binding affinity at a distal site through conformational changes to the remaining single strands. Leveraging these insights allows for the design of conjugates that hybridize free strands with significantly higher efficiencies, some of which approach 100%.

variability of in vitro and phenological behaviours of cocoa hybrids

African Journals Online (AJOL)

ACSS

analyse the variability of the in vitro and phenological behaviours of 6 cocoa ... The 4 aforementioned hybrids could be used to produce cocoa aroma, ... hybrids using a multivariate approach. .... 3 clusters and variables was assessed through ... function, and (iv) analysis of the representation quality. Thus, the number of ...

Identification of hybrid node and link communities in complex networks.

Science.gov (United States)

He, Dongxiao; Jin, Di; Chen, Zheng; Zhang, Weixiong

2015-03-02

Identifying communities in complex networks is an effective means for analyzing complex systems, with applications in diverse areas such as social science, engineering, biology and medicine. Finding communities of nodes and finding communities of links are two popular schemes for network analysis. These schemes, however, have inherent drawbacks and are inadequate to capture complex organizational structures in real networks. We introduce a new scheme and an effective approach for identifying complex mixture structures of node and link communities, called hybrid node-link communities. A central piece of our approach is a probabilistic model that accommodates node, link and hybrid node-link communities. Our extensive experiments on various real-world networks, including a large protein-protein interaction network and a large network of semantically associated words, illustrated that the scheme for hybrid communities is superior in revealing network characteristics. Moreover, the new approach outperformed the existing methods for finding node or link communities separately.

Identification of hybrid node and link communities in complex networks

Science.gov (United States)

He, Dongxiao; Jin, Di; Chen, Zheng; Zhang, Weixiong

2015-03-01

Identifying communities in complex networks is an effective means for analyzing complex systems, with applications in diverse areas such as social science, engineering, biology and medicine. Finding communities of nodes and finding communities of links are two popular schemes for network analysis. These schemes, however, have inherent drawbacks and are inadequate to capture complex organizational structures in real networks. We introduce a new scheme and an effective approach for identifying complex mixture structures of node and link communities, called hybrid node-link communities. A central piece of our approach is a probabilistic model that accommodates node, link and hybrid node-link communities. Our extensive experiments on various real-world networks, including a large protein-protein interaction network and a large network of semantically associated words, illustrated that the scheme for hybrid communities is superior in revealing network characteristics. Moreover, the new approach outperformed the existing methods for finding node or link communities separately.

Concurrent Coronary Artery and Valvular Heart Disease - Hybrid Treatment Strategies in 2013.

Science.gov (United States)

Grubb, Kendra J; Nazif, Tamim; Williams, Mathew R; George, Isaac

2013-08-01

Concomitant coronary artery disease (CAD) and valvular heart disease is an increasingly common problem in the ageing population. Hybrid procedures combine surgical and transcatheter approaches to facilitate minimally invasive surgery or to transform a single high-risk open surgery into two less risky procedures. In ideal circumstances, this strategy may decrease the surgical risk in elderly, high-risk and reoperative surgical candidates, while improving patient comfort, convenience and cost-effectiveness. Hybrid procedures can be performed in a staged fashion or as a 'one-stop' procedure in a hybrid operating suite. Increasing evidence supports the safety and short-term efficacy of hybrid valve repair or replacement and coronary revascularisation procedures. Nevertheless, important questions remain, including the optimal timing of the individual procedures and the optimal antiplatelet therapy after percutaneous coronary intervention. With ongoing advances in procedural techniques and anticoagulation strategies, as well as the accumulation of long-term outcomes data, hybrid approaches to concomitant CAD and valvular heart disease will likely become increasingly common.

A new adaptive hybrid electromagnetic damper: modelling, optimization, and experiment

International Nuclear Information System (INIS)

Asadi, Ehsan; Ribeiro, Roberto; Behrad Khamesee, Mir; Khajepour, Amir

2015-01-01

This paper presents the development of a new electromagnetic hybrid damper which provides regenerative adaptive damping force for various applications. Recently, the introduction of electromagnetic technologies to the damping systems has provided researchers with new opportunities for the realization of adaptive semi-active damping systems with the added benefit of energy recovery. In this research, a hybrid electromagnetic damper is proposed. The hybrid damper is configured to operate with viscous and electromagnetic subsystems. The viscous medium provides a bias and fail-safe damping force while the electromagnetic component adds adaptability and the capacity for regeneration to the hybrid design. The electromagnetic component is modeled and analyzed using analytical (lumped equivalent magnetic circuit) and electromagnetic finite element method (FEM) (COMSOL ® software package) approaches. By implementing both modeling approaches, an optimization for the geometric aspects of the electromagnetic subsystem is obtained. Based on the proposed electromagnetic hybrid damping concept and the preliminary optimization solution, a prototype is designed and fabricated. A good agreement is observed between the experimental and FEM results for the magnetic field distribution and electromagnetic damping forces. These results validate the accuracy of the modeling approach and the preliminary optimization solution. An analytical model is also presented for viscous damping force, and is compared with experimental results The results show that the damper is able to produce damping coefficients of 1300 and 0–238 N s m −1 through the viscous and electromagnetic components, respectively. (paper)

Adsorption mechanism of magnetically separable Fe_3O_4/graphene oxide hybrids

International Nuclear Information System (INIS)

Ouyang, Ke; Zhu, Chuanhe; Zhao, Ya; Wang, Leichao; Xie, Shan; Wang, Qun

2015-01-01

Graphical abstract: A recyclable Fe_3O_4/graphene oxide (GO) magnetic hybrid was successfully synthesized via a facile one-pot polylol approach and exhibited an effective adsorption of BPA in aqueous solution. - Highlights: • Magnetically separable Fe_3O_4/GO hybrids were synthesized via a facile one-pot polylol approach. • The Fe_3O_4/GO hybrid could be easily recovered and met the need of magnetic separation, exhibiting excellent reproducibility and reusability. • The hybrids showed excellent adsorption ability for bisphenol A in aqueous solution. • The effect of pH value, temperature and coexisting ions on the adsorption was studied. • π–π interactions were postulated to be the primary mechanisms of adsorption of BPA on Fe_3O_4/GO hybrids. - Abstract: A reclaimable Fe_3O_4/graphene oxide (GO) magnetic hybrid was successfully synthesized via a facile one-pot polyol approach and employed as a recyclable adsorbent for Bisphenol A (BPA) in aqueous solutions. The maximum adsorption capacity (q_m) of the Fe_3O_4/GO hybrid for BPA was 72.80 mg/g at 273 K. The kinetics of the adsorption process and the adsorption isotherm data were fitted using the Freundlich equation and a pseudo-second-order kinetic model. The results of the thermodynamic parameters ΔH°, ΔS° and ΔG° showed that the adsorption process was exothermic and spontaneous. Furthermore, the reusability of the samples was investigated, and the results indicated that the samples exhibited high stability. The magnetic characterization demonstrated that hybrids were superparamagnetic and could be recovered conveniently by magnetic separation. The strong π–π interaction was determined to be the predominant driving force behind the adsorption of BPA onto the Fe_3O_4/GO hybrid. Therefore, the Fe_3O_4/GO hybrid could be regarded as a potential adsorbent for wastewater treatment and purification processes.

Proposed prediction algorithms based on hybrid approach to deal with anomalies of RFID data in healthcare

Directory of Open Access Journals (Sweden)

A. Anny Leema

2013-07-01

Full Text Available The RFID technology has penetrated the healthcare sector due to its increased functionality, low cost, high reliability, and easy-to-use capabilities. It is being deployed for various applications and the data captured by RFID readers increase according to timestamp resulting in an enormous volume of data duplication, false positive, and false negative. The dirty data stream generated by the RFID readers is one of the main factors limiting the widespread adoption of RFID technology. In order to provide reliable data to RFID application, it is necessary to clean the collected data and this should be done in an effective manner before they are subjected to warehousing. The existing approaches to deal with anomalies are physical, middleware, and deferred approach. The shortcomings of existing approaches are analyzed and found that robust RFID system can be built by integrating the middleware and deferred approach. Our proposed algorithms based on hybrid approach are tested in the healthcare environment which predicts false positive, false negative, and redundant data. In this paper, healthcare environment is simulated using RFID and the data observed by RFID reader consist of anomalies false positive, false negative, and duplication. Experimental evaluation shows that our cleansing methods remove errors in RFID data more accurately and efficiently. Thus, with the aid of the planned data cleaning technique, we can bring down the healthcare costs, optimize business processes, streamline patient identification processes, and improve patient safety.

Piezoelectric touch-sensitive flexible hybrid energy harvesting nanoarchitectures

International Nuclear Information System (INIS)

Choi, Dukhyun; Kim, Eok Su; Kim, Tae Sang; Lee, Sang Yoon; Choi, Jae-Young; Kim, Jong Min; Lee, Keun Young; Lee, Kang Hyuck; Kim, Sang-Woo

2010-01-01

In this work, we report a flexible hybrid nanoarchitecture that can be utilized as both an energy harvester and a touch sensor on a single platform without any cross-talk problems. Based on the electron transport and piezoelectric properties of a zinc oxide (ZnO) nanostructured thin film, a hybrid cell was designed and the total thickness was below 500 nm on a plastic substrate. Piezoelectric touch signals were demonstrated under independent and simultaneous operations with respect to photo-induced charges. Different levels of piezoelectric output signals from different magnitudes of touching pressures suggest new user-interface functions from our hybrid cell. From a signal controller, the decoupled performance of a hybrid cell as an energy harvester and a touch sensor was confirmed. Our hybrid approach does not require additional assembly processes for such multiplex systems of an energy harvester and a touch sensor since we utilize the coupled material properties of ZnO and output signal processing. Furthermore, the hybrid cell can provide a multi-type energy harvester by both solar and mechanical touching energies.

Hybrid Fourier pseudospectral/discontinuous Galerkin time-domain method for wave propagation

Science.gov (United States)

Pagán Muñoz, Raúl; Hornikx, Maarten

2017-11-01

The Fourier Pseudospectral time-domain (Fourier PSTD) method was shown to be an efficient way of modelling acoustic propagation problems as described by the linearized Euler equations (LEE), but is limited to real-valued frequency independent boundary conditions and predominantly staircase-like boundary shapes. This paper presents a hybrid approach to solve the LEE, coupling Fourier PSTD with a nodal Discontinuous Galerkin (DG) method. DG exhibits almost no restrictions with respect to geometrical complexity or boundary conditions. The aim of this novel method is to allow the computation of complex geometries and to be a step towards the implementation of frequency dependent boundary conditions by using the benefits of DG at the boundaries, while keeping the efficient Fourier PSTD in the bulk of the domain. The hybridization approach is based on conformal meshes to avoid spatial interpolation of the DG solutions when transferring values from DG to Fourier PSTD, while the data transfer from Fourier PSTD to DG is done utilizing spectral interpolation of the Fourier PSTD solutions. The accuracy of the hybrid approach is presented for one- and two-dimensional acoustic problems and the main sources of error are investigated. It is concluded that the hybrid methodology does not introduce significant errors compared to the Fourier PSTD stand-alone solver. An example of a cylinder scattering problem is presented and accurate results have been obtained when using the proposed approach. Finally, no instabilities were found during long-time calculation using the current hybrid methodology on a two-dimensional domain.

Hybrid approaches to clinical trial monitoring: Practical alternatives to 100% source data verification

Directory of Open Access Journals (Sweden)

Sourabh De

2011-01-01

Full Text Available For years, a vast majority of clinical trial industry has followed the tenet of 100% source data verification (SDV. This has been driven partly by the overcautious approach to linking quality of data to the extent of monitoring and SDV and partly by being on the safer side of regulations. The regulations however, do not state any upper or lower limits of SDV. What it expects from researchers and the sponsors is methodologies which ensure data quality. How the industry does it is open to innovation and application of statistical methods, targeted and remote monitoring, real time reporting, adaptive monitoring schedules, etc. In short, hybrid approaches to monitoring. Coupled with concepts of optimum monitoring and SDV at site and off-site monitoring techniques, it should be possible to save time required to conduct SDV leading to more available time for other productive activities. Organizations stand to gain directly or indirectly from such savings, whether by diverting the funds back to the R&D pipeline; investing more in technology infrastructure to support large trials; or simply increasing sample size of trials. Whether it also affects the work-life balance of monitors who may then need to travel with a less hectic schedule for the same level of quality and productivity can be predicted only when there is more evidence from field.

Hybrid approaches to clinical trial monitoring: Practical alternatives to 100% source data verification.

Science.gov (United States)

De, Sourabh

2011-07-01

For years, a vast majority of clinical trial industry has followed the tenet of 100% source data verification (SDV). This has been driven partly by the overcautious approach to linking quality of data to the extent of monitoring and SDV and partly by being on the safer side of regulations. The regulations however, do not state any upper or lower limits of SDV. What it expects from researchers and the sponsors is methodologies which ensure data quality. How the industry does it is open to innovation and application of statistical methods, targeted and remote monitoring, real time reporting, adaptive monitoring schedules, etc. In short, hybrid approaches to monitoring. Coupled with concepts of optimum monitoring and SDV at site and off-site monitoring techniques, it should be possible to save time required to conduct SDV leading to more available time for other productive activities. Organizations stand to gain directly or indirectly from such savings, whether by diverting the funds back to the R&D pipeline; investing more in technology infrastructure to support large trials; or simply increasing sample size of trials. Whether it also affects the work-life balance of monitors who may then need to travel with a less hectic schedule for the same level of quality and productivity can be predicted only when there is more evidence from field.

A Hybrid Stochastic Approach for Self-Location of Wireless Sensors in Indoor Environments

Directory of Open Access Journals (Sweden)

Alejandro Canovas

2009-05-01

Full Text Available Indoor location systems, especially those using wireless sensor networks, are used in many application areas. While the need for these systems is widely proven, there is a clear lack of accuracy. Many of the implemented applications have high errors in their location estimation because of the issues arising in the indoor environment. Two different approaches had been proposed using WLAN location systems: on the one hand, the so-called deductive methods take into account the physical properties of signal propagation. These systems require a propagation model, an environment map, and the position of the radio-stations. On the other hand, the so-called inductive methods require a previous training phase where the system learns the received signal strength (RSS in each location. This phase can be very time consuming. This paper proposes a new stochastic approach which is based on a combination of deductive and inductive methods whereby wireless sensors could determine their positions using WLAN technology inside a floor of a building. Our goal is to reduce the training phase in an indoor environment, but, without an loss of precision. Finally, we compare the measurements taken using our proposed method in a real environment with the measurements taken by other developed systems. Comparisons between the proposed system and other hybrid methods are also provided.

Hybride zelf(re)presentatie in de dagboeken van Hennie Aucamp ...

African Journals Online (AJOL)

Hybride zelf(re)presentatie in de dagboeken van Hennie Aucamp. Jihie Moon. Abstract. English Title: Hybrid self–(re)presentation in the diaries of Hennie Aucamp. English Abstract. This article on Hennie Aucamp approaches his journals as ego-documents. The positional dilemma and identity crisis of Afrikaners in the new ...

Fluorescence in situ hybridization on formalin-fixed and paraffin-embedded tissue

DEFF Research Database (Denmark)

Laub Petersen, Bodil; Zeuthen, Mette Christa; Pedersen, Sanni

2004-01-01

Fluorescence in situ hybridization (FISH) is widely used to study numerical and structural genetic abnormalities in both metaphase and interphase cells. The technique is based on the hybridization of labeled probes to complementary sequences in the DNA or RNA of the cells. Interphase FISH is most...... in time lapse between removal of tissue and fixation, duration of fixation, enzymatic pretreatment, hybridization conditions, and posthybridization washing conditions are important factors in the hybridization. In this study, we have listed the results of a systematic approach to improve FISH on isolated...

Draft Sequencing of the Heterozygous Diploid Genome of Satsuma (Citrus unshiu Marc. Using a Hybrid Assembly Approach

Directory of Open Access Journals (Sweden)

Tokurou Shimizu

2017-12-01

Full Text Available Satsuma (Citrus unshiu Marc. is one of the most abundantly produced mandarin varieties of citrus, known for its seedless fruit production and as a breeding parent of citrus. De novo assembly of the heterozygous diploid genome of Satsuma (“Miyagawa Wase” was conducted by a hybrid assembly approach using short-read sequences, three mate-pair libraries, and a long-read sequence of PacBio by the PLATANUS assembler. The assembled sequence, with a total size of 359.7 Mb at the N50 length of 386,404 bp, consisted of 20,876 scaffolds. Pseudomolecules of Satsuma constructed by aligning the scaffolds to three genetic maps showed genome-wide synteny to the genomes of Clementine, pummelo, and sweet orange. Gene prediction by modeling with MAKER-P proposed 29,024 genes and 37,970 mRNA; additionally, gene prediction analysis found candidates for novel genes in several biosynthesis pathways for gibberellin and violaxanthin catabolism. BUSCO scores for the assembled scaffold and predicted transcripts, and another analysis by BAC end sequence mapping indicated the assembled genome consistency was close to those of the haploid Clementine, pummel, and sweet orange genomes. The number of repeat elements and long terminal repeat retrotransposon were comparable to those of the seven citrus genomes; this suggested no significant failure in the assembly at the repeat region. A resequencing application using the assembled sequence confirmed that both kunenbo-A and Satsuma are offsprings of Kishu, and Satsuma is a back-crossed offspring of Kishu. These results illustrated the performance of the hybrid assembly approach and its ability to construct an accurate heterozygous diploid genome.

Improved signal processing approaches in an offline simulation of a hybrid brain–computer interface

Science.gov (United States)

Brunner, Clemens; Allison, Brendan Z.; Krusienski, Dean J.; Kaiser, Vera; Müller-Putz, Gernot R.; Pfurtscheller, Gert; Neuper, Christa

2012-01-01

In a conventional brain–computer interface (BCI) system, users perform mental tasks that yield specific patterns of brain activity. A pattern recognition system determines which brain activity pattern a user is producing and thereby infers the user’s mental task, allowing users to send messages or commands through brain activity alone. Unfortunately, despite extensive research to improve classification accuracy, BCIs almost always exhibit errors, which are sometimes so severe that effective communication is impossible. We recently introduced a new idea to improve accuracy, especially for users with poor performance. In an offline simulation of a “hybrid” BCI, subjects performed two mental tasks independently and then simultaneously. This hybrid BCI could use two different types of brain signals common in BCIs – event-related desynchronization (ERD) and steady-state evoked potentials (SSEPs). This study suggested that such a hybrid BCI is feasible. Here, we re-analyzed the data from our initial study. We explored eight different signal processing methods that aimed to improve classification and further assess both the causes and the extent of the benefits of the hybrid condition. Most analyses showed that the improved methods described here yielded a statistically significant improvement over our initial study. Some of these improvements could be relevant to conventional BCIs as well. Moreover, the number of illiterates could be reduced with the hybrid condition. Results are also discussed in terms of dual task interference and relevance to protocol design in hybrid BCIs. PMID:20153371

VLSI Implementation of Hybrid Wave-Pipelined 2D DWT Using Lifting Scheme

Directory of Open Access Journals (Sweden)

G. Seetharaman

2008-01-01

Full Text Available A novel approach is proposed in this paper for the implementation of 2D DWT using hybrid wave-pipelining (WP. A digital circuit may be operated at a higher frequency by using either pipelining or WP. Pipelining requires additional registers and it results in more area, power dissipation and clock routing complexity. Wave-pipelining does not have any of these disadvantages but requires complex trial and error procedure for tuning the clock period and clock skew between input and output registers. In this paper, a hybrid scheme is proposed to get the benefits of both pipelining and WP techniques. In this paper, two automation schemes are proposed for the implementation of 2D DWT using hybrid WP on both Xilinx, San Jose, CA, USA and Altera FPGAs. In the first scheme, Built-in self-test (BIST approach is used to choose the clock skew and clock period for I/O registers between the wave-pipelined blocks. In the second approach, an on-chip soft-core processor is used to choose the clock skew and clock period. The results for the hybrid WP are compared with nonpipelined and pipelined approaches. From the implementation results, the hybrid WP scheme requires the same area but faster than the nonpipelined scheme by a factor of 1.25–1.39. The pipelined scheme is faster than the hybrid scheme by a factor of 1.15–1.39 at the cost of an increase in the number of registers by a factor of 1.78–2.73, increase in the number of LEs by a factor of 1.11–1.32 and it increases the clock routing complexity.

A novel hybrid approach with multidimensional-like effects for compressible flow computations

Science.gov (United States)

Kalita, Paragmoni; Dass, Anoop K.

2017-07-01

A multidimensional scheme achieves good resolution of strong and weak shocks irrespective of whether the discontinuities are aligned with or inclined to the grid. However, these schemes are computationally expensive. This paper achieves similar effects by hybridizing two schemes, namely, AUSM and DRLLF and coupling them through a novel shock switch that operates - unlike existing switches - on the gradient of the Mach number across the cell-interface. The schemes that are hybridized have contrasting properties. The AUSM scheme captures grid-aligned (and strong) shocks crisply but it is not so good for non-grid-aligned weaker shocks, whereas the DRLLF scheme achieves sharp resolution of non-grid-aligned weaker shocks, but is not as good for grid-aligned strong shocks. It is our experience that if conventional shock switches based on variables like density, pressure or Mach number are used to combine the schemes, the desired effect of crisp resolution of grid-aligned and non-grid-aligned discontinuities are not obtained. To circumvent this problem we design a shock switch based - for the first time - on the gradient of the cell-interface Mach number with very impressive results. Thus the strategy of hybridizing two carefully selected schemes together with the innovative design of the shock switch that couples them, affords a method that produces the effects of a multidimensional scheme with a lower computational cost. It is further seen that hybridization of the AUSM scheme with the recently developed DRLLFV scheme using the present shock switch gives another scheme that provides crisp resolution for both shocks and boundary layers. Merits of the scheme are established through a carefully selected set of numerical experiments.

Monthly reservoir inflow forecasting using a new hybrid SARIMA genetic programming approach

Science.gov (United States)

Moeeni, Hamid; Bonakdari, Hossein; Ebtehaj, Isa

2017-03-01

Forecasting reservoir inflow is one of the most important components of water resources and hydroelectric systems operation management. Seasonal autoregressive integrated moving average (SARIMA) models have been frequently used for predicting river flow. SARIMA models are linear and do not consider the random component of statistical data. To overcome this shortcoming, monthly inflow is predicted in this study based on a combination of seasonal autoregressive integrated moving average (SARIMA) and gene expression programming (GEP) models, which is a new hybrid method (SARIMA-GEP). To this end, a four-step process is employed. First, the monthly inflow datasets are pre-processed. Second, the datasets are modelled linearly with SARIMA and in the third stage, the non-linearity of residual series caused by linear modelling is evaluated. After confirming the non-linearity, the residuals are modelled in the fourth step using a gene expression programming (GEP) method. The proposed hybrid model is employed to predict the monthly inflow to the Jamishan Dam in west Iran. Thirty years' worth of site measurements of monthly reservoir dam inflow with extreme seasonal variations are used. The results of this hybrid model (SARIMA-GEP) are compared with SARIMA, GEP, artificial neural network (ANN) and SARIMA-ANN models. The results indicate that the SARIMA-GEP model ( R 2=78.8, VAF =78.8, RMSE =0.89, MAPE =43.4, CRM =0.053) outperforms SARIMA and GEP and SARIMA-ANN ( R 2=68.3, VAF =66.4, RMSE =1.12, MAPE =56.6, CRM =0.032) displays better performance than the SARIMA and ANN models. A comparison of the two hybrid models indicates the superiority of SARIMA-GEP over the SARIMA-ANN model.

A Hybrid Approach for Thread Recommendation in MOOC Forums

OpenAIRE

Ahmad. A. Kardan; Amir Narimani; Foozhan Ataiefard

2017-01-01

Recommender Systems have been developed to provide contents and services compatible to users based on their behaviors and interests. Due to information overload in online discussion forums and users diverse interests, recommending relative topics and threads is considered to be helpful for improving the ease of forum usage. In order to lead learners to find relevant information in educational forums, recommendations are even more needed. We present a hybrid thread recommender system for MOOC ...

A hybrid approach for fusing 4D-MRI temporal information with 3D-CT for the study of lung and lung tumor motion

Energy Technology Data Exchange (ETDEWEB)

Yang, Y. X.; Van Reeth, E.; Poh, C. L., E-mail: clpoh@ntu.edu.sg [School of Chemical and Biomedical Engineering, Nanyang Technological University, Singapore 637459 (Singapore); Teo, S.-K. [Institute of High Performance Computing, Agency for Science, Technology and Research, Singapore 138632 (Singapore); Tan, C. H. [Department of Diagnostic Radiology, Tan Tock Seng Hospital, Singapore 308433 (Singapore); Tham, I. W. K. [Department of Radiation Oncology, National University Cancer Institute, Singapore 119082 (Singapore)

2015-08-15

Purpose: Accurate visualization of lung motion is important in many clinical applications, such as radiotherapy of lung cancer. Advancement in imaging modalities [e.g., computed tomography (CT) and MRI] has allowed dynamic imaging of lung and lung tumor motion. However, each imaging modality has its advantages and disadvantages. The study presented in this paper aims at generating synthetic 4D-CT dataset for lung cancer patients by combining both continuous three-dimensional (3D) motion captured by 4D-MRI and the high spatial resolution captured by CT using the authors’ proposed approach. Methods: A novel hybrid approach based on deformable image registration (DIR) and finite element method simulation was developed to fuse a static 3D-CT volume (acquired under breath-hold) and the 3D motion information extracted from 4D-MRI dataset, creating a synthetic 4D-CT dataset. Results: The study focuses on imaging of lung and lung tumor. Comparing the synthetic 4D-CT dataset with the acquired 4D-CT dataset of six lung cancer patients based on 420 landmarks, accurate results (average error <2 mm) were achieved using the authors’ proposed approach. Their hybrid approach achieved a 40% error reduction (based on landmarks assessment) over using only DIR techniques. Conclusions: The synthetic 4D-CT dataset generated has high spatial resolution, has excellent lung details, and is able to show movement of lung and lung tumor over multiple breathing cycles.

Infectious disease modeling a hybrid system approach

CERN Document Server

Liu, Xinzhi

2017-01-01

This volume presents infectious diseases modeled mathematically, taking seasonality and changes in population behavior into account, using a switched and hybrid systems framework. The scope of coverage includes background on mathematical epidemiology, including classical formulations and results; a motivation for seasonal effects and changes in population behavior, an investigation into term-time forced epidemic models with switching parameters, and a detailed account of several different control strategies. The main goal is to study these models theoretically and to establish conditions under which eradication or persistence of the disease is guaranteed. In doing so, the long-term behavior of the models is determined through mathematical techniques from switched systems theory. Numerical simulations are also given to augment and illustrate the theoretical results and to help study the efficacy of the control schemes.

Hybrid attacks on model-based social recommender systems

Science.gov (United States)

Yu, Junliang; Gao, Min; Rong, Wenge; Li, Wentao; Xiong, Qingyu; Wen, Junhao

2017-10-01

With the growing popularity of the online social platform, the social network based approaches to recommendation emerged. However, because of the open nature of rating systems and social networks, the social recommender systems are susceptible to malicious attacks. In this paper, we present a certain novel attack, which inherits characteristics of the rating attack and the relation attack, and term it hybrid attack. Furtherly, we explore the impact of the hybrid attack on model-based social recommender systems in multiple aspects. The experimental results show that, the hybrid attack is more destructive than the rating attack in most cases. In addition, users and items with fewer ratings will be influenced more when attacked. Last but not the least, the findings suggest that spammers do not depend on the feedback links from normal users to become more powerful, the unilateral links can make the hybrid attack effective enough. Since unilateral links are much cheaper, the hybrid attack will be a great threat to model-based social recommender systems.

Bounded Model Checking and Inductive Verification of Hybrid Discrete-Continuous Systems

DEFF Research Database (Denmark)

Becker, Bernd; Behle, Markus; Eisenbrand, Fritz

2004-01-01

We present a concept to signicantly advance the state of the art for bounded model checking (BMC) and inductive verication (IV) of hybrid discrete-continuous systems. Our approach combines the expertise of partners coming from dierent domains, like hybrid systems modeling and digital circuit veri...