10,302 results
Search Results
2. The role of simulation and modeling in artificial intelligence: A review.
- Author
-
Kumar, Anup
- Subjects
ARTIFICIAL intelligence ,LITERATURE reviews ,DATABASES ,ENERGY consumption ,RESOURCE allocation - Abstract
This paper aims to comprehensively explore the pivotal role of simulation and modeling in the field of Artificial Intelligence (AI). It focuses on elucidating the diverse applications of simulation and modeling in training AI systems, optimizing algorithms, and enhancing decision-making processes. To achieve this objective, we conducted an extensive review of the literature from the Scopus database, employing a well-defined selection process. We utilized keywords such as "simulation," "modeling," "Artificial Intelligence," and related terms to identify relevant papers published within the last 10 years. The selection criteria included assessing the relevance, quality, contribution, and recent citations of the papers. After a rigorous screening process, we selected 40 papers with the highest overall scores for inclusion in our review. The selected papers encompass a wide range of domains where simulation and modeling play a vital role in advancing AI applications. These domains include manufacturing, healthcare, energy consumption prediction, public sector decision-making, education, environmental modeling, and more. Our review highlights how AI leverages simulation and modeling to improve predictive accuracy, optimize resource allocation, and enhance decision-making processes across diverse sectors. We also discuss the potential future directions in the integration of simulation and modeling with AI, emphasizing its significance in various fields. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
3. Social and content aware One-Class recommendation of papers in scientific social networks.
- Author
-
Wang, Gang, He, XiRan, and Ishuga, Carolyne Isigi
- Subjects
INFORMATION technology ,SOCIAL networks ,SPARSE graphs ,HYBRID computers (Computer architecture) ,HYBRID power systems - Abstract
With the rapid development of information technology, scientific social networks (SSNs) have become the fastest and most convenient way for researchers to communicate with each other. Many published papers are shared via SSNs every day, resulting in the problem of information overload. How to appropriately recommend personalized and highly valuable papers for researchers is becoming more urgent. However, when recommending papers in SSNs, only a small amount of positive instances are available, leaving a vast amount of unlabelled data, in which negative instances and potential unseen positive instances are mixed together, which naturally belongs to One-Class Collaborative Filtering (OCCF) problem. Therefore, considering the extreme data imbalance and data sparsity of this OCCF problem, a hybrid approach of Social and Content aware One-class Recommendation of Papers in SSNs, termed SCORP, is proposed in this study. Unlike previous approaches recommended to address the OCCF problem, social information, which has been proved playing a significant role in performing recommendations in many domains, is applied in both the profiling of content-based filtering and the collaborative filtering to achieve superior recommendations. To verify the effectiveness of the proposed SCORP approach, a real-life dataset from CiteULike was employed. The experimental results demonstrate that the proposed approach is superior to all of the compared approaches, thus providing a more effective method for recommending papers in SSNs. [ABSTRACT FROM AUTHOR]
- Published
- 2017
- Full Text
- View/download PDF
4. Physics driven behavioural clustering of free-falling paper shapes
- Author
-
Fumiya Iida, Toby Howison, Josie Hughes, Fabio Giardina, Howison, Toby [0000-0001-8548-5550], Iida, Fumiya [0000-0001-9246-7190], and Apollo - University of Cambridge Repository
- Subjects
Inertia ,Physiology ,Physical system ,Social Sciences ,computer.software_genre ,Systems Science ,01 natural sciences ,010305 fluids & plasmas ,Physical Phenomena ,Physical phenomena ,Medicine and Health Sciences ,Psychology ,Cluster Analysis ,Moment of Inertia ,Multidisciplinary ,Applied Mathematics ,Simulation and Modeling ,theoretical model ,article ,Classical Mechanics ,Dynamical Systems ,Variety (cybernetics) ,Free falling ,machine learning ,Physical Sciences ,Medicine ,physics ,Algorithms ,Research Article ,Paper ,Computer and Information Sciences ,Reynolds Number ,Science ,Fluid Mechanics ,Research and Analysis Methods ,Machine learning ,Continuum Mechanics ,Motion ,Machine Learning Algorithms ,Artificial Intelligence ,0103 physical sciences ,010306 general physics ,Set (psychology) ,Cluster analysis ,Behavior ,Biological Locomotion ,business.industry ,Biology and Life Sciences ,Fluid Dynamics ,Models, Theoretical ,Nonlinear Dynamics ,Artificial intelligence ,business ,computer ,Mathematics - Abstract
Many complex physical systems exhibit a rich variety of discrete behavioural modes. Often, the system complexity limits the applicability of standard modelling tools. Hence, understanding the underlying physics of different behaviours and distinguishing between them is challenging. Although traditional machine learning techniques could predict and classify behaviour well, typically they do not provide any meaningful insight into the underlying physics of the system. In this paper we present a novel method for extracting physically meaningful clusters of discrete behaviour from limited experimental observations. This method obtains a set of physically plausible functions that both facilitate behavioural clustering and aid in system understanding. We demonstrate the approach on the V-shaped falling paper system, a new falling paper type system that exhibits four distinct behavioural modes depending on a few morphological parameters. Using just 49 experimental observations, the method discovered a set of candidate functions that distinguish behaviours with an error of 2.04%, while also aiding insight into the physical phenomena driving each behaviour. © 2019 Howison et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
- Published
- 2019
5. Quantifying the impact of scholarly papers based on higher-order weighted citations.
- Author
-
Bai, Xiaomei, Zhang, Fuli, Hou, Jie, Lee, Ivan, Kong, Xiangjie, Tolba, Amr, and Xia, Feng
- Subjects
CITATION analysis ,SCHOLARLY publishing ,BIBLIOMETRICS ,SIMULATION methods & models ,ALGORITHMS - Abstract
Quantifying the impact of a scholarly paper is of great significance, yet the effect of geographical distance of cited papers has not been explored. In this paper, we examine 30,596 papers published in Physical Review C, and identify the relationship between citations and geographical distances between author affiliations. Subsequently, a relative citation weight is applied to assess the impact of a scholarly paper. A higher-order weighted quantum PageRank algorithm is also developed to address the behavior of multiple step citation flow. Capturing the citation dynamics with higher-order dependencies reveals the actual impact of papers, including necessary self-citations that are sometimes excluded in prior studies. Quantum PageRank is utilized in this paper to help differentiating nodes whose PageRank values are identical. [ABSTRACT FROM AUTHOR]
- Published
- 2018
- Full Text
- View/download PDF
6. Ten Simple Rules for writing algorithmic bioinformatics conference papers
- Author
-
Paul Medvedev
- Subjects
0301 basic medicine ,Computer and Information Sciences ,Computer science ,QH301-705.5 ,Bioinformatics ,Writing ,Gene Identification and Analysis ,Genetic Networks ,Research and Analysis Methods ,Field (computer science) ,03 medical and health sciences ,Cellular and Molecular Neuroscience ,Database and Informatics Methods ,Clustering Algorithms ,0302 clinical medicine ,Computer software ,Genetics ,Humans ,Prototypes ,Biology (General) ,Molecular Biology ,Ecology, Evolution, Behavior and Systematics ,Simple (philosophy) ,Publishing ,Ecology ,Information Dissemination ,Software Tools ,Applied Mathematics ,Simulation and Modeling ,Computational Biology ,Software Engineering ,Biology and Life Sciences ,Congresses as Topic ,030104 developmental biology ,Editorial ,Technology Development ,Computational Theory and Mathematics ,Modeling and Simulation ,Physical Sciences ,Engineering and Technology ,Sequence Analysis ,Sequence Alignment ,030217 neurology & neurosurgery ,Algorithms ,Mathematics ,Network Analysis - Abstract
Author summary Conferences are great venues for disseminating algorithmic bioinformatics results, but they unfortunately do not offer an opportunity to make major revisions in the way that journals do. As a result, it is not possible for authors to fix mistakes that might be easily correctable but nevertheless can cause the paper to be rejected. As a reviewer, I wish that I had the opportunity to tell the authors, “Hey, you forgot to do this really important thing, without which it is hard to accept the paper, but if you could go back and fix it, you might have a great paper for the conference.” This lack of a back and forth can be especially problematic for first-time submitters or those from outside the field, e.g., biologists. In this article, I outline Ten Simple Rules to follow when writing an algorithmic bioinformatics conference paper to avoid having it rejected.
- Published
- 2020
7. Physics driven behavioural clustering of free-falling paper shapes.
- Author
-
Howison, Toby, Hughes, Josie, Giardina, Fabio, and Iida, Fumiya
- Subjects
- *
PHYSICS , *SET functions , *MACHINE learning , *PHENOMENOLOGICAL theory (Physics) , *CONTINUUM mechanics - Abstract
Many complex physical systems exhibit a rich variety of discrete behavioural modes. Often, the system complexity limits the applicability of standard modelling tools. Hence, understanding the underlying physics of different behaviours and distinguishing between them is challenging. Although traditional machine learning techniques could predict and classify behaviour well, typically they do not provide any meaningful insight into the underlying physics of the system. In this paper we present a novel method for extracting physically meaningful clusters of discrete behaviour from limited experimental observations. This method obtains a set of physically plausible functions that both facilitate behavioural clustering and aid in system understanding. We demonstrate the approach on the V-shaped falling paper system, a new falling paper type system that exhibits four distinct behavioural modes depending on a few morphological parameters. Using just 49 experimental observations, the method discovered a set of candidate functions that distinguish behaviours with an error of 2.04%, while also aiding insight into the physical phenomena driving each behaviour. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
8. Rendering Technique for Colored Paper Mosaic.
- Author
-
Hutchison, David, Kanade, Takeo, Kittler, Josef, Kleinberg, Jon M., Mattern, Friedemann, Mitchell, John C., Naor, Moni, Nierstrasz, Oscar, Rangan, C. Pandu, Steffen, Bernhard, Sudan, Madhu, Terzopoulos, Demetri, Tygar, Doug, Vardi, Moshe Y., Weikum, Gerhard, Yong Shi, van Albada, Geert Dick, Dongarra, Jack, Sloot, Peter M. A., and Youngsup Park
- Abstract
The work presented in this paper shows the way to generate colored paper mosaics using computer graphics techniques. Following two tasks need to be done to generate colored paper mosaic. The first one is to generate colored paper tile and the other one is to arrange the tile. Voronoi Diagram and Random Point Displacement have been used in this paper to come up with the shape of the tile. And, energy value that the tile has depending on its location is the factor to determine the best positioning of the tile. This paper focuses on representing the overlap among tiles, maintenance of the edge of input image, and various shapes of tiles in the final output image by solving two tasks mentioned above. [ABSTRACT FROM AUTHOR]
- Published
- 2007
- Full Text
- View/download PDF
9. The contribution of cause-effect link to representing the core of scientific paper—The role of Semantic Link Network.
- Author
-
Cao, Mengyun, Sun, Xiaoping, and Zhuge, Hai
- Subjects
- *
COMPLEXITY (Philosophy) , *CAUSATION (Philosophy) , *SEMANTICS , *RESEARCH , *PHILOSOPHY - Abstract
The Semantic Link Network is a general semantic model for modeling the structure and the evolution of complex systems. Various semantic links play different roles in rendering the semantics of complex system. One of the basic semantic links represents cause-effect relation, which plays an important role in representation and understanding. This paper verifies the role of the Semantic Link Network in representing the core of text by investigating the contribution of cause-effect link to representing the core of scientific papers. Research carries out with the following steps: (1) Two propositions on the contribution of cause-effect link in rendering the core of paper are proposed and verified through a statistical survey, which shows that the sentences on cause-effect links cover about 65% of key words within each paper on average. (2) An algorithm based on syntactic patterns is designed for automatically extracting cause-effect link from scientific papers, which recalls about 70% of manually annotated cause-effect links on average, indicating that the result adapts to the scale of data sets. (3) The effects of cause-effect link on four schemes of incorporating cause-effect link into the existing instances of the Semantic Link Network for enhancing the summarization of scientific papers are investigated. The experiments show that the quality of the summaries is significantly improved, which verifies the role of semantic links. The significance of this research lies in two aspects: (1) it verifies that the Semantic Link Network connects the important concepts to render the core of text; and, (2) it provides an evidence for realizing content services such as summarization, recommendation and question answering based on the Semantic Link Network, and it can inspire relevant research on content computing. [ABSTRACT FROM AUTHOR]
- Published
- 2018
- Full Text
- View/download PDF
10. A collaborative approach for research paper recommender system.
- Author
-
Haruna, Khalid, Akmar Ismail, Maizatul, Damiasih, Damiasih, Sutopo, Joko, and Herawan, Tutut
- Subjects
- *
CITATION analysis , *SCIENCE & state , *SOCIAL network analysis , *SOCIAL networks , *COMPUTER networks - Abstract
Research paper recommenders emerged over the last decade to ease finding publications relating to researchers’ area of interest. The challenge was not just to provide researchers with very rich publications at any time, any place and in any form but to also offer the right publication to the right researcher in the right way. Several approaches exist in handling paper recommender systems. However, these approaches assumed the availability of the whole contents of the recommending papers to be freely accessible, which is not always true due to factors such as copyright restrictions. This paper presents a collaborative approach for research paper recommender system. By leveraging the advantages of collaborative filtering approach, we utilize the publicly available contextual metadata to infer the hidden associations that exist between research papers in order to personalize recommendations. The novelty of our proposed approach is that it provides personalized recommendations regardless of the research field and regardless of the user’s expertise. Using a publicly available dataset, our proposed approach has recorded a significant improvement over other baseline methods in measuring both the overall performance and the ability to return relevant and useful publications at the top of the recommendation list. [ABSTRACT FROM AUTHOR]
- Published
- 2017
- Full Text
- View/download PDF
11. The contribution of cause-effect link to representing the core of scientific paper—The role of Semantic Link Network
- Author
-
Xiaoping Sun, Mengyun Cao, and Hai Zhuge
- Subjects
Semantic link ,Computer and Information Sciences ,Lexical semantics ,Computer science ,Science ,lcsh:Medicine ,Social Sciences ,02 engineering and technology ,Semantic data model ,Research and Analysis Methods ,Systems Science ,Automation ,Sociology ,020204 information systems ,0202 electrical engineering, electronic engineering, information engineering ,Question answering ,Psychology ,Syntax ,lcsh:Science ,Data Curation ,Language ,Grammar ,Multidisciplinary ,Information retrieval ,Applied Mathematics ,Simulation and Modeling ,Research ,lcsh:R ,Publications ,Cognitive Psychology ,Biology and Life Sciences ,Linguistics ,Complex Systems ,Reasoning ,Automatic summarization ,Semantics ,Lexical Semantics ,Social Networks ,Physical Sciences ,Cognitive Science ,lcsh:Q ,020201 artificial intelligence & image processing ,Mathematics ,Algorithms ,Network Analysis ,Research Article ,Neuroscience - Abstract
The Semantic Link Network is a general semantic model for modeling the structure and the evolution of complex systems. Various semantic links play different roles in rendering the semantics of complex system. One of the basic semantic links represents cause-effect relation, which plays an important role in representation and understanding. This paper verifies the role of the Semantic Link Network in representing the core of text by investigating the contribution of cause-effect link to representing the core of scientific papers. Research carries out with the following steps: (1) Two propositions on the contribution of cause-effect link in rendering the core of paper are proposed and verified through a statistical survey, which shows that the sentences on cause-effect links cover about 65% of key words within each paper on average. (2) An algorithm based on syntactic patterns is designed for automatically extracting cause-effect link from scientific papers, which recalls about 70% of manually annotated cause-effect links on average, indicating that the result adapts to the scale of data sets. (3) The effects of cause-effect link on four schemes of incorporating cause-effect link into the existing instances of the Semantic Link Network for enhancing the summarization of scientific papers are investigated. The experiments show that the quality of the summaries is significantly improved, which verifies the role of semantic links. The significance of this research lies in two aspects: (1) it verifies that the Semantic Link Network connects the important concepts to render the core of text; and, (2) it provides an evidence for realizing content services such as summarization, recommendation and question answering based on the Semantic Link Network, and it can inspire relevant research on content computing.
- Published
- 2018
12. Quantifying the impact of scholarly papers based on higher-order weighted citations
- Author
-
Feng Xia, Ivan Lee, Jie Hou, Xiangjie Kong, Amr Tolba, Fuli Zhang, Xiaomei Bai, Bai, Xiaomei, Zhang, Fuli, Hou, Jie, Lee, Ivan, Kong, Xiangjie, Tolba, Amr, and Xia, Feng
- Subjects
FOS: Computer and information sciences ,Computer science ,Population Dynamics ,lcsh:Medicine ,law.invention ,Geographical Locations ,Order (exchange) ,law ,Citation analysis ,Digital Libraries (cs.DL) ,lcsh:Science ,GeneralLiterature_REFERENCE(e.g.,dictionaries,encyclopedias,glossaries) ,Multidisciplinary ,Latitude ,Geography ,Applied Mathematics ,Simulation and Modeling ,05 social sciences ,Computer Science - Digital Libraries ,Research Assessment ,Europe ,Longitude ,Physical Sciences ,Citation Analysis ,quantifying the impact ,050904 information & library sciences ,Algorithms ,Research Article ,Cartography ,InformationSystems_INFORMATIONSTORAGEANDRETRIEVAL ,Bibliometrics ,050905 science studies ,Research and Analysis Methods ,weighted citations ,PageRank ,Humans ,Pagerank algorithm ,Information retrieval ,Manuscripts as Topic ,Population Biology ,lcsh:R ,author affiliations ,Biology and Life Sciences ,Models, Theoretical ,Geographic Distribution ,People and Places ,North America ,Earth Sciences ,lcsh:Q ,0509 other social sciences ,Citation ,Mathematics - Abstract
Quantifying the impact of a scholarly paper is of great significance, yet the effect of geographical distance of cited papers has not been explored. In this paper, we examine 30,596 papers published in Physical Review C, and identify the relationship between citations and geographical distances between author affiliations. Subsequently, a relative citation weight is applied to assess the impact of a scholarly paper. A higher-order weighted quantum PageRank algorithm is also developed to address the behavior of multiple step citation flow. Capturing the citation dynamics with higher-order dependencies reveals the actual impact of papers, including necessary self-citations that are sometimes excluded in prior studies. Quantum PageRank is utilized in this paper to help differentiating nodes whose PageRank values are identical. Refereed/Peer-reviewed
- Published
- 2018
13. Social and content aware One-Class recommendation of papers in scientific social networks
- Author
-
Carolyne Isigi Ishuga, XiRan He, and Gang Wang
- Subjects
Optimization ,Computer and Information Sciences ,Computer science ,Science ,Emotions ,lcsh:Medicine ,Social Sciences ,02 engineering and technology ,Research and Analysis Methods ,Social Networking ,Mathematical and Statistical Techniques ,Sociology ,020204 information systems ,0202 electrical engineering, electronic engineering, information engineering ,Collaborative filtering ,Profiling (information science) ,Humans ,Statistical Methods ,Computer Networks ,Cooperative Behavior ,lcsh:Science ,Internet ,Multidisciplinary ,Social Research ,Social network ,business.industry ,Applied Mathematics ,Simulation and Modeling ,lcsh:R ,Publications ,Information technology ,Social Communication ,Data science ,Communications ,Social research ,Social Networks ,Social system ,Physical Sciences ,lcsh:Q ,020201 artificial intelligence & image processing ,The Internet ,business ,Information Technology ,Network Analysis ,Mathematics ,Statistics (Mathematics) ,Algorithms ,Research Article ,Forecasting - Abstract
With the rapid development of information technology, scientific social networks (SSNs) have become the fastest and most convenient way for researchers to communicate with each other. Many published papers are shared via SSNs every day, resulting in the problem of information overload. How to appropriately recommend personalized and highly valuable papers for researchers is becoming more urgent. However, when recommending papers in SSNs, only a small amount of positive instances are available, leaving a vast amount of unlabelled data, in which negative instances and potential unseen positive instances are mixed together, which naturally belongs to One-Class Collaborative Filtering (OCCF) problem. Therefore, considering the extreme data imbalance and data sparsity of this OCCF problem, a hybrid approach of Social and Content aware One-class Recommendation of Papers in SSNs, termed SCORP, is proposed in this study. Unlike previous approaches recommended to address the OCCF problem, social information, which has been proved playing a significant role in performing recommendations in many domains, is applied in both the profiling of content-based filtering and the collaborative filtering to achieve superior recommendations. To verify the effectiveness of the proposed SCORP approach, a real-life dataset from CiteULike was employed. The experimental results demonstrate that the proposed approach is superior to all of the compared approaches, thus providing a more effective method for recommending papers in SSNs.
- Published
- 2017
14. Genealogical Trees of Scientific Papers.
- Author
-
Waumans, Michaël Charles and Bersini, Hugues
- Subjects
- *
GENEALOGY , *SCIENCE databases , *CITATION analysis , *EVOLUTIONARY algorithms , *SOCIAL networks - Abstract
Many results have been obtained when studying scientific papers citations databases in a network perspective. Articles can be ranked according to their current in-degree and their future popularity or citation counts can even be predicted. The dynamical properties of such networks and the observation of the time evolution of their nodes started more recently. This work adopts an evolutionary perspective and proposes an original algorithm for the construction of genealogical trees of scientific papers on the basis of their citation count evolution in time. The fitness of a paper now amounts to its in-degree growing trend and a “dying” paper will suddenly see this trend declining in time. It will give birth and be taken over by some of its most prevalent citing “offspring”. Practically, this might be used to trace the successive published milestones of a research field. [ABSTRACT FROM AUTHOR]
- Published
- 2016
- Full Text
- View/download PDF
15. A collaborative approach for research paper recommender system
- Author
-
Tutut Herawan, Khalid Haruna, Joko Sutopo, Maizatul Akmar Ismail, and Damiasih Damiasih
- Subjects
Computer and Information Sciences ,Science Policy ,Computer science ,Social Sciences ,lcsh:Medicine ,02 engineering and technology ,Recommender system ,Research and Analysis Methods ,Bioinformatics ,Field (computer science) ,Database and Informatics Methods ,Open Science ,Sociology ,Open Data ,Citation analysis ,020204 information systems ,0202 electrical engineering, electronic engineering, information engineering ,Collaborative filtering ,Computer Networks ,Cooperative Behavior ,lcsh:Science ,Publishing ,Internet ,Metadata ,Social Research ,Multidisciplinary ,business.industry ,Applied Mathematics ,Simulation and Modeling ,Research ,lcsh:R ,Novelty ,Research Assessment ,Data science ,Open data ,Social Networks ,Citation Analysis ,Information Retrieval ,Physical Sciences ,lcsh:Q ,020201 artificial intelligence & image processing ,The Internet ,business ,Mathematics ,Algorithms ,Network Analysis ,Research Article - Abstract
Research paper recommenders emerged over the last decade to ease finding publications relating to researchers' area of interest. The challenge was not just to provide researchers with very rich publications at any time, any place and in any form but to also offer the right publication to the right researcher in the right way. Several approaches exist in handling paper recommender systems. However, these approaches assumed the availability of the whole contents of the recommending papers to be freely accessible, which is not always true due to factors such as copyright restrictions. This paper presents a collaborative approach for research paper recommender system. By leveraging the advantages of collaborative filtering approach, we utilize the publicly available contextual metadata to infer the hidden associations that exist between research papers in order to personalize recommendations. The novelty of our proposed approach is that it provides personalized recommendations regardless of the research field and regardless of the user's expertise. Using a publicly available dataset, our proposed approach has recorded a significant improvement over other baseline methods in measuring both the overall performance and the ability to return relevant and useful publications at the top of the recommendation list.
- Published
- 2017
16. Genealogical Trees of Scientific Papers
- Author
-
Hugues Bersini and Michael Waumans
- Subjects
Databases, Factual ,Condensation ,Psychologie appliquée ,Social Sciences ,lcsh:Medicine ,Bioinformatics ,Biochemistry ,01 natural sciences ,Field (computer science) ,Mathematical and Statistical Techniques ,Sociology ,Citation analysis ,lcsh:Science ,Fluids ,Multidisciplinary ,Applied Mathematics ,Simulation and Modeling ,Physics ,Publications ,05 social sciences ,Sciences bio-médicales et agricoles ,Condensed Matter Physics ,Genealogy ,Curve Fitting ,Pedigree ,Trace (semiology) ,Social Networks ,Social system ,Physical Sciences ,Social Systems ,Learning to rank ,Gases ,Journal Impact Factor ,050904 information & library sciences ,Biologie ,Phase Transitions ,Algorithms ,Network Analysis ,Research Article ,Computer and Information Sciences ,States of Matter ,Science ,Biology ,Research and Analysis Methods ,Protein Domains ,0103 physical sciences ,Humans ,010306 general physics ,lcsh:R ,Perspective (graphical) ,Biology and Life Sciences ,Proteins ,Popularity ,lcsh:Q ,0509 other social sciences ,Citation ,Mathematical Functions ,Mathematics - Abstract
Many results have been obtained when studying scientific papers citations databases in a network perspective. Articles can be ranked according to their current in-degree and their future popularity or citation counts can even be predicted. The dynamical properties of such networks and the observation of the time evolution of their nodes started more recently. This work adopts an evolutionary perspective and proposes an original algorithm for the construction of genealogical trees of scientific papers on the basis of their citation count evolution in time. The fitness of a paper now amounts to its in-degree growing trend and a "dying" paper will suddenly see this trend declining in time. It will give birth and be taken over by some of its most prevalent citing "offspring". Practically, this might be used to trace the successive published milestones of a research field., SCOPUS: ar.j, info:eu-repo/semantics/published
- Published
- 2016
17. Evaluating a Simulated Student Using Real Students Data for Training and Testing$^{\thanks{The research presented in this paper is supported by National Science Foundation Award No. REC-0537198.}}$.
- Author
-
Carbonell, Jaime G., Siekmann, Jörg, Conati, Cristina, McCoy, Kathleen, Paliouras, Georgios, Matsuda, Noboru, Cohen, William W., Sewall, Jonathan, Lacerda, Gustavo, and Koedinger, Kenneth R.
- Abstract
SimStudent is a machine-learning agent that learns cognitive skills by demonstration. It was originally developed as a building block of the Cognitive Tutor Authoring Tools (CTAT), so that the authors do not have to build a cognitive model by hand, but instead simply demonstrate solutions for SimStudent to automatically generate a cognitive model. The SimStudent technology could then be used to model human students' performance as well. To evaluate the applicability of SimStudent as a tool for modeling real students, we applied SimStudent to a genuine learning log gathered from classroom experiments with the Algebra I Cognitive Tutor. Such data can be seen as the human students' "demonstrations" of how to solve problems. The results from an empirical study show that SimStudent can indeed model human students' performance. After training on 20 problems solved by a group of human students, a cognitive model generated by SimStudent explained 82% of the problem-solving steps performed correctly by another group of human students. [ABSTRACT FROM AUTHOR]
- Published
- 2007
- Full Text
- View/download PDF
18. Predicting translational progress in biomedical research.
- Author
-
Hutchins, B. Ian, Davis, Matthew T., Meseroll, Rebecca A., and Santangelo, George M.
- Subjects
MEDICAL research ,SCIENTIFIC community ,SCIENTIFIC discoveries ,MACHINE learning ,CLINICAL trials ,FALSE discovery rate ,THERAPEUTICS - Abstract
Fundamental scientific advances can take decades to translate into improvements in human health. Shortening this interval would increase the rate at which scientific discoveries lead to successful treatment of human disease. One way to accomplish this would be to identify which advances in knowledge are most likely to translate into clinical research. Toward that end, we built a machine learning system that detects whether a paper is likely to be cited by a future clinical trial or guideline. Despite the noisiness of citation dynamics, as little as 2 years of postpublication data yield accurate predictions about a paper's eventual citation by a clinical article (accuracy = 84%, F1 score = 0.56; compared to 19% accuracy by chance). We found that distinct knowledge flow trajectories are linked to papers that either succeed or fail to influence clinical research. Translational progress in biomedicine can therefore be assessed and predicted in real time based on information conveyed by the scientific community's early reaction to a paper. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
19. Identifying Anomalous Citations for Objective Evaluation of Scholarly Article Impact.
- Author
-
Bai, Xiaomei, Xia, Feng, Lee, Ivan, Zhang, Jun, and Ning, Zhaolong
- Subjects
APPLIED mathematics ,CONFLICT of interests ,RESEARCH grants ,CITATION analysis ,RANKING (Statistics) - Abstract
Evaluating the impact of a scholarly article is of great significance and has attracted great attentions. Although citation-based evaluation approaches have been widely used, these approaches face limitations e.g. in identifying anomalous citations patterns. This negligence would inevitably cause unfairness and inaccuracy to the article impact evaluation. In this study, in order to discover the anomalous citations and ensure the fairness and accuracy of research outcome evaluation, we investigate the citation relationships between articles using the following factors: collaboration times, the time span of collaboration, citing times and the time span of citing to weaken the relationship of Conflict of Interest (COI) in the citation network. Meanwhile, we study a special kind of COI, namely suspected COI relationship. Based on the COI relationship, we further bring forward the COIRank algorithm, an innovative scheme for accurately assessing the impact of an article. Our method distinguishes the citation strength, and utilizes PageRank and HITS algorithms to rank scholarly articles comprehensively. The experiments are conducted on the American Physical Society (APS) dataset. We find that about 80.88% articles contain contributed citations by co-authors in 26,366 articles and 75.55% articles among these articles are cited by the authors belonging to the same affiliation, indicating COI and suspected COI should not be ignored for evaluating impact of scientific papers objectively. Moreover, our experimental results demonstrate COIRank algorithm significantly outperforms the state-of-art solutions. The validity of our approach is verified by using the probability of Recommendation Intensity. [ABSTRACT FROM AUTHOR]
- Published
- 2016
- Full Text
- View/download PDF
20. Modeling User's Opinion Relevance to Recommending Research Papers.
- Author
-
Ardissono, Liliana, Brna, Paul, Mitrovic, Antonija, Cazella, Sílvio César, and Alvares, Luis Otávio Campos
- Abstract
Finding the right material on the Web could be a worthwhile result. Users waste too much time to discover the useful information. Recommender system can provide some shortcuts to the user, but if the recommendation is based on people's opinion, one question remains — how relevant is a user's opinion? This paper presents a model to define the user's relevance opinion in a recommender system. This metric aims to help the target user to decide in what recommendation he should focus his attention. Beyond the model, we present a real experiment using an e-government database. Keywords: User modeling, Authority, Recommender System. [ABSTRACT FROM AUTHOR]
- Published
- 2005
- Full Text
- View/download PDF
21. Exploring the role of interdisciplinarity in physics: Success, talent and luck.
- Author
-
Pluchino, Alessandro, Burgio, Giulio, Rapisarda, Andrea, Biondo, Alessio Emanuele, Pulvirenti, Alfredo, Ferro, Alfredo, and Giorgino, Toni
- Subjects
FORTUNE ,PHYSICS ,SCIENCE & state ,OCCUPATIONAL achievement ,ABILITY - Abstract
Although interdisciplinarity is often touted as a necessity for modern research, the evidence on the relative impact of sectorial versus to interdisciplinary science is qualitative at best. In this paper we leverage the bibliographic data set of the American Physical Society to quantify the role of interdisciplinarity in physics, and that of talent and luck in achieving success in scientific careers. We analyze a period of 30 years (1980-2009) tagging papers and their authors by means of the Physics and Astronomy Classification Scheme (PACS), to show that some degree of interdisciplinarity is quite helpful to reach success, measured as a proxy of either the number of articles or the citations score. We also propose an agent-based model of the publication-reputation-citation dynamics which reproduces the trends observed in the APS data set. On the one hand, the results highlight the crucial role of randomness and serendipity in real scientific research; on the other, they shed light on a counterintuitive effect indicating that the most talented authors are not necessarily the most successful ones. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
22. Requirements Elicitation and Elaboration in Task-Based Design Needs More Than Task Modelling: A Case Study.
- Author
-
Hutchison, David, Kanade, Takeo, Kittler, Josef, Kleinberg, Jon M., Mattern, Friedemann, Mitchell, John C., Naor, Moni, Nierstrasz, Oscar, Pandu Rangan, C., Steffen, Bernhard, Sudan, Madhu, Terzopoulos, Demetri, Tygar, Doug, Vardi, Moshe Y., Weikum, Gerhard, Coninx, Karin, Luyten, Kris, Schneider, Kevin A., Dittmar, Anke, and Gellendin, Andreas
- Abstract
In this paper, a small case study is presented to illustrate our conceptual understanding of a task-based requirements process. We argue that sub-models as known in model-based design (e.g. task models, dialog models) support the reflection about an existing work situation at a conceptual level and allow a formal specification of requirements. However, it is also shown that the integration of complementary analysis approaches facilitates a richer consideration of social as well as technical aspects. An intertwined creation of models differing in their focus and in the degree of abstraction and formality supports a more effective requirements elicitation and elaboration. In addition, the paper discusses some crucial issues in task- and model-based design such as the ‘myth' of generalised task models, the different roles of task and dialog models, or the influence of intentions on models of current situations. We hope to contribute to a further clarification of the problem space. [ABSTRACT FROM AUTHOR]
- Published
- 2007
- Full Text
- View/download PDF
23. Map-matching algorithm based on the junction decision domain and the hidden Markov model.
- Author
-
Qi, Hui, Di, Xiaoqiang, and Li, Jinqing
- Subjects
HIDDEN Markov models ,ALGORITHMS ,ERROR rates - Abstract
Map-matching technology is a key and difficult technology in the development of vehicle navigation systems. Only by correctly identifying the road segment on which the vehicle is traveling can the navigation system make the right decision. At the same time, the complexity of the road network structure and a variety of error factors have introduced great challenges to map matching and have attracted the attention of many researchers as well. This paper analyzes various map-matching algorithms, determines that the key to the matching performance is the junction matching, performs an in-depth study on the junction-matching problem, and puts forward the junction decision domain model. The model mainly involves information regarding the width of the road segment, the angle between two road segments, the accuracy of GPS and the accuracy of the road network. In this paper, we use this model to improve the map-matching algorithm based on a hidden Markov model (HMM). The experimental results show that the improved matching algorithm can effectively reduce the error rate of junction matching and improve the matching performance of a navigation system. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
24. Introduction to the ICCS 2007 Workshop on Dynamic Data Driven Applications Systems.
- Author
-
Hutchison, David, Kanade, Takeo, Kittler, Josef, Kleinberg, Jon M., Mattern, Friedemann, Mitchell, John C., Naor, Moni, Nierstrasz, Oscar, Rangan, C. Pandu, Steffen, Bernhard, Sudan, Madhu, Terzopoulos, Demetri, Tygar, Doug, Vardi, Moshe Y., Weikum, Gerhard, Shi, Yong, van Albada, Geert Dick, Dongarra, Jack, Sloot, Peter M. A., and Darema, Frederica
- Abstract
This is the 5th International Workshop on Dynamic Data Driven Applications Systems (DDDAS), organized in conjunction with ICCS. The DDDAS concept entails the ability to dynamically incorporate data into an executing application simulation, and in reverse, the ability of applications to dynamically steer measurement processes. Such dynamic data inputs can be acquired in real-time on-line or they can be archival data. DDDAS is leading to new capabilities by improving applications modeling and systems management methods, augmenting the analysis and prediction capabilities of simulations, improving the efficiency of simulations and the effectiveness of measurement systems. The scope of the present workshop provides examples of research and technology advances enabled through DDDAS and driven by DDDAS. The papers presented in this workshop represent ongoing multidisciplinary research efforts by an international set of researchers from academe, industry, national and research laboratories. [ABSTRACT FROM AUTHOR]
- Published
- 2007
- Full Text
- View/download PDF
25. A differential privacy protecting K-means clustering algorithm based on contour coefficients.
- Author
-
Zhang, Yaling, Liu, Na, and Wang, Shangping
- Subjects
K-means clustering ,INFORMATION storage & retrieval systems ,MACHINE learning ,COMPUTER algorithms ,DATA analysis - Abstract
This paper, based on differential privacy protecting K-means clustering algorithm, realizes privacy protection by adding data-disturbing Laplace noise to cluster center point. In order to solve the problem of Laplace noise randomness which causes the center point to deviate, especially when poor availability of clustering results appears because of small privacy budget parameters, an improved differential privacy protecting K-means clustering algorithm was raised in this paper. The improved algorithm uses the contour coefficients to quantitatively evaluate the clustering effect of each iteration and add different noise to different clusters. In order to be adapted to the huge number of data, this paper provides an algorithm design in MapReduce Framework. Experimental finding shows that the new algorithm improves the availability of the algorithm clustering results under the condition of ensuring individual privacy without significantly increasing its operating time. [ABSTRACT FROM AUTHOR]
- Published
- 2018
- Full Text
- View/download PDF
26. Application-aware deadline constraint job scheduling mechanism on large-scale computational grid.
- Author
-
Tang, Xiaoyong and Liao, Xiaoyi
- Subjects
PRODUCTION scheduling ,GRID computing ,COMPUTATIONAL fluid dynamics ,ANT algorithms ,GENETIC algorithms - Abstract
Recently, computational Grids have proven to be a good solution for processing large-scale, computation intensive problems. However, the heterogeneity, dynamics of resources and diversity of applications requirements have always been important factors affecting their performance. In response to these challenges, this work first builds a Grid job scheduling architecture that can dynamically monitor Grid computing center resources and make corresponding scheduling decisions. Second, a Grid job model is proposed to describe the application requirements. Third, this paper studies the characteristics of commercial interconnection networks used in Grids and forecast job transmission time. Fourth, this paper proposes an application-aware job scheduling mechanism (AJSM) that includes periodic scheduling flow and a heuristic application-aware deadline constraint job scheduling algorithm. The rigorous performance evaluation results clearly demonstrate that the proposed application-aware job scheduling mechanism can successful schedule more Grid jobs than the existing algorithms. For successful scheduled jobs, our proposed AJSM method is the best algorithm for job average processing time and makespan. [ABSTRACT FROM AUTHOR]
- Published
- 2018
- Full Text
- View/download PDF
27. A review of the mechanical integrity and electrochemical performance of flexible lithium-ion batteries
- Author
-
Shokrieh, Ahmad, Mirzaei, Amir Hossein, Mao, Lijuan, Shokrieh, Mahmood M., and Wei, Zhixiang
- Published
- 2023
- Full Text
- View/download PDF
28. Empirical Paradigm: Position Paper.
- Author
-
Hutchison, David, Kanade, Takeo, Kittler, Josef, Kleinberg, Jon M., Mattern, Friedemann, Mitchell, John C., Naor, Moni, Nierstrasz, Oscar, Rangan, C. Pandu, Steffen, Bernhard, Sudan, Madhu, Terzopoulos, Demetri, Tygar, Doug, Vardi, Moshe Y., Weikum, Gerhard, Basili, Victor R., Rombach, Dieter, Schneider, Kurt, Kitchenham, Barbara, and Pfahl, Dietmar
- Abstract
The distinction between "exploratory" and "confirmatory" work is crucial but is too often blurred in current literature. The term "exploratory" refers to empirical work that has as a goal the discovery of new and unforeseen insight. "Confirmatory" research, on the other hand, normally begins with some type of hypothesis or proposition (that has some type of support in previous literature), the confirmation of which is the aim of the study. [ABSTRACT FROM AUTHOR]
- Published
- 2007
- Full Text
- View/download PDF
29. ExpertiseNet: Relational and Evolutionary Expert Modeling.
- Author
-
Ardissono, Liliana, Brna, Paul, Mitrovic, Antonija, Song, Xiaodan, Tseng, Belle L., Lin, Ching-Yung, and Sun, Ming-Ting
- Abstract
We develop a novel user-centric modeling technology, which can dynamically describe and update a person's expertise profile. In an enterprise environment, the technology can enhance employees' collaboration and productivity by assisting in finding experts, training employees, etc. Instead of using the traditional search methods, such as the keyword match, we propose to use relational and evolutionary graph models, which we call ExpertiseNet, to describe and find experts. These ExpertiseNets are used for mining, retrieval, and visualization. We conduct experiments by building ExpertiseNets for researchers from a research paper collection. The experiments demonstrate that expertise mining and matching are more efficiently achieved based on the proposed relational and evolutionary graph models. [ABSTRACT FROM AUTHOR]
- Published
- 2005
- Full Text
- View/download PDF
30. An Objective Evaluation Approach for Safety-Relevant Steering Feedback on a Test Bench.
- Author
-
Haas, Alexander, Menze, Gregor, Sieberg, Philipp Maximilian, and Schramm, Dieter
- Subjects
PSYCHOLOGICAL feedback ,POWER steering ,BENCHES ,AUTOMOBILE steering gear ,ELECTRIC power ,TRANSFER functions - Abstract
Since electric power steering has replaced hydraulic power steering in passenger cars, steering feedback has become a challenging task in steering system development. Test benches represent a valid approach for improving steering feedback since they allow investigations without the real vehicle. To improve the applicability of feedback evaluations on a steering test bench, this paper aims to identify improvements in the current evaluation technique to obtain objective parameters that correlate with a subjective evaluation of safety-relevant steering feedback. Therefore, a previously reported approach of a chirp rack force excitation, using the magnitude of the transfer function from the rack force to steering wheel torque to describe steering feedback, is compared to a similar identification approach in which a pseudo-random-binary-sequence signal is utilized. To reflect realistic applications, driving maneuvers are transferred to the test bench to identify relevant objective data. For a valid representation of the steering wheel operation, a human grip model is implemented and compared to a fixed steering wheel angle control. It is shown that the random signal represents a valid and, on average, improved approach to objectively evaluating the steering feedback. Furthermore, a recommendation can be made to include the human grip model in the feedback evaluation tests, as the identified correlation results are improved by its inclusion. The identified parameters and methods represent an improvement for future steering feedback development. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
31. A two-stage filter for removing salt-and-pepper noise using noise detector based on characteristic difference parameter and adaptive directional mean filter
- Author
-
Yufeng Nie and Hongjin Ma
- Subjects
Computer and Information Sciences ,Imaging Techniques ,Computer science ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Equipment ,Color ,lcsh:Medicine ,Transportation ,Image Analysis ,02 engineering and technology ,Digital Imaging ,Research and Analysis Methods ,Infographics ,Mathematical and Statistical Techniques ,Filter Paper ,Image Interpretation, Computer-Assisted ,Computer Science::Multimedia ,Photography ,0202 electrical engineering, electronic engineering, information engineering ,Median filter ,lcsh:Science ,Multidisciplinary ,Pixel ,Data Visualization ,Applied Mathematics ,Simulation and Modeling ,Detector ,lcsh:R ,Digital imaging ,020206 networking & telecommunications ,Salt-and-pepper noise ,White noise ,Filter (signal processing) ,Image Enhancement ,Charts ,Boats ,Laboratory Equipment ,Noise ,Computer Science::Computer Vision and Pattern Recognition ,Physical Sciences ,Engineering and Technology ,020201 artificial intelligence & image processing ,lcsh:Q ,Mathematical Functions ,Algorithm ,Mathematics ,Algorithms ,Research Article - Abstract
In this paper, a two-stage filter for removing salt-and-pepper noise using noise detector based on characteristic difference parameter and adaptive directional mean filter is proposed. The first stage firstly detects the noise corrupted pixels by combining characteristic difference parameter and gray level extreme, then develops an improved adaptive median filter to firstly restore them. The second stage introduces a restoration scheme to further restore the noise corrupted pixels, which firstly divides them into two types and then applies different restoration skills for the pixels based on the classification result. One type of pixels is restored by the mean filter and the other type of pixels is restored by the proposed adaptive directional mean filter. The new filter firstly adaptively selects the optimal filtering window and direction template, then replaces the gray level of noise corrupted pixel by the mean value of pixels on the optimal template. Experimental results show that the proposed filter outperforms many existing main filters in terms of noise suppression and detail preservation.
- Published
- 2018
32. Applications of Agent Based Simulation.
- Author
-
Carbonell, Jaime G., Siekmann, Jorg, Antunes, Luis, Takadama, Keiki, Davidsson, Paul, Holmgren, Johan, Kyhlbäck, Hans, Mengistu, Dawit, and Persson, Marie
- Abstract
This paper provides a survey and analysis of applications of Agent Based Simulation (ABS). A framework for describing and assessing the applications is presented and systematically applied. A general conclusion from the study is that even if ABS seems a promising approach to many problems involving simulation of complex systems of interacting entities, it seems as the full potential of the agent concept and previous research and development within ABS often is not utilized. We illustrate this by providing some concrete examples. Another conclusion is that important information of the applications, in particular concerning the implementation of the simulator, was missing in many papers. As an attempt to encourage improvements we provide some guidelines for writing ABS application papers. [ABSTRACT FROM AUTHOR]
- Published
- 2007
- Full Text
- View/download PDF
33. eCSM: Semantic Classification Model for Educational Repositories.
- Author
-
Hutchison, David, Kanade, Takeo, Kittler, Josef, Kleinberg, Jon M., Mattern, Friedemann, Mitchell, John C., Naor, Moni, Nierstrasz, Oscar, Rangan, C. Pandu, Steffen, Bernhard, Sudan, Madhu, Terzopoulos, Demetri, Tygar, Doug, Vardi, Moshe Y., Weikum, Gerhard, Shi, Yong, van Albada, Geert Dick, Dongarra, Jack, Sloot, Peter M. A., and Dongwon Jeong
- Abstract
This paper proposes a new classification model for management of resources in an educational repository. To facilitate usability of educational resources, a proper classification model should be provided. If no classification model, it causes several issues such as inefficient management of educational resources, incorrect retrieval, and low usability. To achieve the goal of this paper, the model should support a classification mechanism in multiple viewpoints. The proposed model enables more precise and systematic management of implementation resources, and also increases the ease of usability. [ABSTRACT FROM AUTHOR]
- Published
- 2007
- Full Text
- View/download PDF
34. Critical Systems Development Using Modeling Languages - CSDUML 2006 Workshop Report.
- Author
-
Hutchison, David, Kanade, Takeo, Kittler, Josef, Kleinberg, Jon M., Mattern, Friedemann, Mitchell, John C., Naor, Moni, Nierstrasz, Oscar, Rangan, C. Pandu, Steffen, Bernhard, Sudan, Madhu, Terzopoulos, Demetri, Tygar, Doug, Vardi, Moshe Y., Weikum, Gerhard, Kühne, Thomas, Georg, Geri, Houmb, Siv Hilde, France, Robert, and Zschaler, Steffen
- Abstract
The CSDUML 2006 workshop is a continuation of the series regarding development of critical systems using modeling languages. The report summarizes papers presented and discussion at the workshop. [ABSTRACT FROM AUTHOR]
- Published
- 2007
- Full Text
- View/download PDF
35. The Impact of Soft Error Event Topography on the Reliability of Computer Memories.
- Author
-
Ogden, Christopher and Mascagni, Michael
- Subjects
SOFT errors ,COMPUTER science ,RELIABILITY in engineering ,MONTE Carlo method ,COMPUTER storage devices ,ANALYSIS of variance - Abstract
The frequency, nature, and scope of Soft Error Events (SEEs) is becoming an increasingly significant reliability concern as transistors continuously scale down into ever smaller nanometer memory chip geometries. As part of the on-going research efforts required to address this steadily developing situation, two significant research questions were addressed by the research work presented within this paper. The first research question addressed the possibility of crafting a novel methodology whose application would consistently lead to the creation of viable Monte Carlo SEE Simulators. Each of these Monte Carlo SEE Simulators would need to be capable of adequately profiling SEEs as well as simulating and modeling their impacts on the reliability of a variety of simulated 45-nm SRAM computer memories. The Standard 2-Parameter Weibull Soft Error Event (S2P-WSE) Simulator proposed within this paper as a direct application of this novel methodology successfully produced simulation results that were comparatively equivalent both directly and statistically to the results calculated by the empirically validated Weibull Row-Clustered Soft Error Reliability (WRCSER) model. This WRCSER Model was independently developed and empirically validated against proprietary reliability datasets obtained from testing a CISCO 45-nm SRAM computer memory device in a laboratory setting. The S2P-WSE Simulator itself was validated by means of a Kruskal–Wallis ANOVA test and by direct comparison of both the model and the simulator as a function of their respective failure probability and reliability results on 45-nm SRAM simulated computer memory devices subjected to the same SEE impacts over the course of an entire simulation run. The second research question sought to determine the significance of SEE topography versus a Row-Depth-Only bit error severity assumption on the reliability of simulated 45-nm SRAM computer memories shielded from the accumulating impacts of SEEs by variable error-correction codes, row-depth interleaving distances, and periodic scrubbing time intervals. The simulation runs for both the S2P-WSE Simulator and the T2P-WSE Simulator were carefully setup to ensure that only the potentially divergent factor between the results generated by the two simulators was the T2P-WSE Simulator's stochastically estimated topographical shape for each SEE impacting the simulated computer memory device. The work within this paper successfully demonstrated through direct plots of the two simulators’ failure probability and reliability results and the results of the Kruskal–Wallis ANOVA tests that the topography of SEEs does represent a significant impact on the overall failure probability and reliability of 45-nm SRAM computer memory devices. [ABSTRACT FROM PUBLISHER]
- Published
- 2017
- Full Text
- View/download PDF
36. Can editors save peer review from peer reviewers?
- Author
-
D’Andrea, Rafael and O’Dwyer, James P.
- Subjects
PROFESSIONAL peer review ,JOB performance ,EDITORS ,PUBLISHING ,STANDARDS - Abstract
Peer review is the gold standard for scientific communication, but its ability to guarantee the quality of published research remains difficult to verify. Recent modeling studies suggest that peer review is sensitive to reviewer misbehavior, and it has been claimed that referees who sabotage work they perceive as competition may severely undermine the quality of publications. Here we examine which aspects of suboptimal reviewing practices most strongly impact quality, and test different mitigating strategies that editors may employ to counter them. We find that the biggest hazard to the quality of published literature is not selfish rejection of high-quality manuscripts but indifferent acceptance of low-quality ones. Bypassing or blacklisting bad reviewers and consulting additional reviewers to settle disagreements can reduce but not eliminate the impact. The other editorial strategies we tested do not significantly improve quality, but pairing manuscripts to reviewers unlikely to selfishly reject them and allowing revision of rejected manuscripts minimize rejection of above-average manuscripts. In its current form, peer review offers few incentives for impartial reviewing efforts. Editors can help, but structural changes are more likely to have a stronger impact. [ABSTRACT FROM AUTHOR]
- Published
- 2017
- Full Text
- View/download PDF
37. Analysis of consensus sorting via the cycle metric.
- Author
-
Avramovic, Ivan and Richards, Dana S.
- Abstract
Sorting is studied in this paper as an archetypal example to explore the optimizing power of consensus. In conceptualizing the consensus sort, the classical hill-climbing method of optimization is paired with the modern notion that value and fitness can be judged by data mining. Consensus sorting is a randomized sorting algorithm which is based on randomly selecting pairs of elements within an unsorted list (expressed in this paper as a permutation), and deciding whether to swap them based on appeals to a database of other permutations. The permutations in the database are all scored via some adaptive sorting metric, and the decision to swap depends on whether the database consensus suggests a better score as a result of swapping. This uninformed search process does not require the definition of the concept of sorting, but rather depends on selecting a metric which does a good job of distinguishing a good path to the goal, a sorted list. A previous paper has shown that the ability of the algorithm to converge on the goal depends strongly on the metric which is used, and analyzed the performance of the algorithm when number of inversions was used as a metric. This paper continues by analyzing the performance of a much more efficient metric, the number of cycles in the permutation. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
38. Spaceborne SAR Imaging Algorithm for Coherence Optimized.
- Author
-
Qiu, Zhiwei, Yue, Jianping, Wang, Xueqin, and Yue, Shun
- Subjects
SYNTHETIC aperture radar ,COHERENCE (Optics) ,SIGNAL-to-noise ratio ,INTERFEROMETRY ,COMPUTER algorithms ,SIGNAL processing - Abstract
This paper proposes SAR imaging algorithm with largest coherence based on the existing SAR imaging algorithm. The basic idea of SAR imaging algorithm in imaging processing is that output signal can have maximum signal-to-noise ratio (SNR) by using the optimal imaging parameters. Traditional imaging algorithm can acquire the best focusing effect, but would bring the decoherence phenomenon in subsequent interference process. Algorithm proposed in this paper is that SAR echo adopts consistent imaging parameters in focusing processing. Although the SNR of the output signal is reduced slightly, their coherence is ensured greatly, and finally the interferogram with high quality is obtained. In this paper, two scenes of Envisat ASAR data in Zhangbei are employed to conduct experiment for this algorithm. Compared with the interferogram from the traditional algorithm, the results show that this algorithm is more suitable for SAR interferometry (InSAR) research and application. [ABSTRACT FROM AUTHOR]
- Published
- 2016
- Full Text
- View/download PDF
39. Co-fermentation of cellobiose and xylose by mixed culture of recombinant Saccharomyces cerevisiae and kinetic modeling
- Author
-
Na Wei, Guanyu Zhang, Baotong Zhu, Yingying Chen, and Ying Wu
- Subjects
Metabolic Processes ,0301 basic medicine ,Cellobiose ,Cellulosic sugars ,Density ,Biomass ,lcsh:Medicine ,Yeast and Fungal Models ,Xylose ,Biochemistry ,chemistry.chemical_compound ,Xylose metabolism ,Materials Physics ,Bioenergy ,lcsh:Science ,Multidisciplinary ,Organic Compounds ,Simulation and Modeling ,Physics ,Monosaccharides ,Eukaryota ,food and beverages ,Pulp and paper industry ,Chemistry ,Metabolic Engineering ,Experimental Organism Systems ,Cell Processes ,Cellulosic ethanol ,Physical Sciences ,Engineering and Technology ,Research Article ,Materials Science ,Material Properties ,Carbohydrates ,Lignocellulosic biomass ,Saccharomyces cerevisiae ,Fuels ,Research and Analysis Methods ,Models, Biological ,Cell Growth ,Saccharomyces ,03 medical and health sciences ,Model Organisms ,Materials by Attribute ,Ethanol ,Organic Chemistry ,lcsh:R ,Chemical Compounds ,Organisms ,Fungi ,Biology and Life Sciences ,Cell Biology ,Coculture Techniques ,Yeast ,Energy and Power ,Kinetics ,Metabolism ,030104 developmental biology ,chemistry ,Biofuels ,Alcohols ,Fermentation ,lcsh:Q - Abstract
Efficient conversion of cellulosic sugars in cellulosic hydrolysates is important for economically viable production of biofuels from lignocellulosic biomass, but the goal remains a critical challenge. The present study reports a new approach for simultaneous fermentation of cellobiose and xylose by using the co-culture consisting of recombinant Saccharomyces cerevisiae specialist strains. The co-culture system can provide competitive advantage of modularity compared to the single culture system and can be tuned to deal with fluctuations in feedstock composition to achieve robust and cost-effective biofuel production. This study characterized fermentation kinetics of the recombinant cellobiose-consuming S. cerevisiae strain EJ2, xylose-consuming S. cerevisiae strain SR8, and their co-culture. The motivation for kinetic modeling was to provide guidance and prediction of using the co-culture system for simultaneous fermentation of mixed sugars with adjustable biomass of each specialist strain under different substrate concentrations. The kinetic model for the co-culture system was developed based on the pure culture models and incorporated the effects of product inhibition, initial substrate concentration and inoculum size. The model simulations were validated by results from independent fermentation experiments under different substrate conditions, and good agreement was found between model predictions and experimental data from batch fermentation of cellobiose, xylose and their mixtures. Additionally, with the guidance of model prediction, simultaneous co-fermentation of 60 g/L cellobiose and 20 g/L xylose was achieved with the initial cell densities of 0.45 g dry cell weight /L for EJ2 and 0.9 g dry cell weight /L SR8. The results demonstrated that the kinetic modeling could be used to guide the design and optimization of yeast co-culture conditions for achieving simultaneous fermentation of cellobiose and xylose with improved ethanol productivity, which is critically important for robust and efficient renewable biofuel production from lignocellulosic biomass.
- Published
- 2018
40. Explicit model predictive control for linear time-variant systems with application to double-lane-change maneuver.
- Author
-
Lee, Junho and Chang, Hyuk-Jun
- Subjects
CHANGE theory ,ECOLOGICAL succession ,LANE changing ,METAPHYSICS ,EXTENSION (Philosophy) - Abstract
Explicit model predictive control (eMPC) has been proposed to reduce the huge computational complexity of MPC while maintaining the performance of MPC. Therefore, this control method has been more widely employed in the automotive industry than MPC. In this paper, an eMPC is designed to perform a double-lane-change (DLC) maneuver. This task has been employed to demonstrate the efficacy of controllers in an autonomous driving situation. In this sense, the proposed controller shows better performance than a driver model designed in CarSim at a high vehicle longitudinal velocity. The main contribution of this paper is to present an eMPC for discrete-time linear time-variant (LTV) systems so that the proposed controller can be robust against parameter variation. In a state-space representation of the vehicle, the longitudinal velocity of the vehicle is assumed to be a constant so that the whole system is linear time-invariant (LTI). However, it is inevitable that this velocity varies in an actual driving situation. Therefore, an eMPC controller is designed using an add-on unit to consider the varying parameter without modification of the eMPC solution. The CarSim simulation results of eMPC show enhanced performance compared to that of eMPC for the LTI system. [ABSTRACT FROM AUTHOR]
- Published
- 2018
- Full Text
- View/download PDF
41. Scholarly Context Adrift: Three out of Four URI References Lead to Changed Content.
- Author
-
Jones, Shawn M., Van de Sompel, Herbert, Shankar, Harihar, Klein, Martin, Tobin, Richard, and Grover, Claire
- Subjects
UNIFORM Resource Identifiers ,ONTOLOGIES (Information retrieval) ,WIKIS ,BLOGS ,WEBSITES - Abstract
Increasingly, scholarly articles contain URI references to “web at large” resources including project web sites, scholarly wikis, ontologies, online debates, presentations, blogs, and videos. Authors reference such resources to provide essential context for the research they report on. A reader who visits a web at large resource by following a URI reference in an article, some time after its publication, is led to believe that the resource’s content is representative of what the author originally referenced. However, due to the dynamic nature of the web, that may very well not be the case. We reuse a dataset from a previous study in which several authors of this paper were involved, and investigate to what extent the textual content of web at large resources referenced in a vast collection of Science, Technology, and Medicine (STM) articles published between 1997 and 2012 has remained stable since the publication of the referencing article. We do so in a two-step approach that relies on various well-established similarity measures to compare textual content. In a first step, we use 19 web archives to find snapshots of referenced web at large resources that have textual content that is representative of the state of the resource around the time of publication of the referencing paper. We find that representative snapshots exist for about 30% of all URI references. In a second step, we compare the textual content of representative snapshots with that of their live web counterparts. We find that for over 75% of references the content has drifted away from what it was when referenced. These results raise significant concerns regarding the long term integrity of the web-based scholarly record and call for the deployment of techniques to combat these problems. [ABSTRACT FROM AUTHOR]
- Published
- 2016
- Full Text
- View/download PDF
42. An Intelligent System for Container Image Recognition Using ART2-Based Self-organizing Supervised Learning Algorithm.
- Author
-
Tzai-Der Wang, Xiaodong Li, Shu-Heng Chen, Xufa Wang, Abbass, Hussein, Iba, Hitoshi, Guoliang Chen, Xin Yao, Kwang-Baek Kim, Young Woon Woo, and Hwang-Kyu Yang
- Abstract
This paper proposed an automatic recognition system of shipping container identifiers using fuzzy-based noise removal method and ART2-based self-organizing supervised learning algorithm. Generally, identifiers of a shipping container have a feature that the color of characters is black or white. Considering such a feature, in a container image, all areas excepting areas with black or white colors are regarded as noises, and areas of identifiers and noises are discriminated by using a fuzzy-based noise detection method. Noise areas are replaced with a mean pixel value of the whole image and areas of identifiers are extracted by applying the edge detection by Sobel masking operation and the vertical and horizontal block extraction in turn to the noise-removed image. Extracted areas are binarized by using the iteration binarization algorithm, and individual identifiers are extracted by applying 8-directional contour tracking method. This paper proposed an ART2-based self-organizing supervised learning algorithm for the identifier recognition, which creates nodes of the hidden layer by applying ART2 between the input and the hidden layers and improves the performance of learning by applying generalized delta learning and Delta-bar-Delta algorithm between the hidden and the output layers. Experiments using many images of shipping containers showed that the proposed identifier extraction method and the ART2-based self-organizing supervised learning algorithm are more improved compared with the methods previously proposed. [ABSTRACT FROM AUTHOR]
- Published
- 2006
- Full Text
- View/download PDF
43. Effects of Automated Vehicle Models at the Mixed Traffic Situation on a Motorway Scenario.
- Author
-
Fang, Xuan, Li, Hexuan, Tettamanti, Tamás, Eichberger, Arno, and Fellendorf, Martin
- Subjects
AUTONOMOUS vehicles ,VEHICLE models ,MOTOR vehicle driving ,TRAFFIC congestion ,CRUISE control ,EXPRESS highways ,TRAFFIC safety - Abstract
There is consensus in industry and academia that Highly Automated Vehicles (HAV) and Connected Automated Vehicles (CAV) will be launched into the market in the near future due to emerging autonomous driving technology. In this paper, a mixed traffic simulation framework that integrates vehicle models with different automated driving systems in the microscopic traffic simulation was proposed. Currently, some of the more mature Automated Driving Systems (ADS) functions (e.g., Adaptive Cruise Control (ACC), Lane Keeping Assistant (LKA), etc.) are already equipped in vehicles, the very next step towards a higher automated driving is represented by Level 3 vehicles and CAV which show great promise in helping to avoid crashes, ease traffic congestion, and improve the environment. Therefore, to better predict and simulate the driving behavior of automated vehicles on the motorway scenario, a virtual test framework is proposed which includes the Highway Chauffeur (HWC) and Vehicle-to-Vehicle (V2V) communication function. These functions are implemented as an external driver model in PTV Vissim. The framework uses a detailed digital twin based on the M86 road network located in southwestern Hungary, which was constructed for autonomous driving tests. With this framework, the effect of the proposed vehicle models is evaluated with the microscopic traffic simulator PTV Vissim. A case study of the different penetration rates of HAV and CAV was performed on the M86 motorway. Preliminary results presented in this paper demonstrated that introducing HAV and CAV to the current network individually will cause negative effects on traffic performance. However, a certain ratio of mixed traffic, 60% CAV and 40% Human Driver Vehicles (HDV), could reduce this negative impact. The simulation results also show that high penetration CAV has fine driving stability and less travel delay. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
44. Generation of Binary Tree-Child phylogenetic networks.
- Author
-
Cardona, Gabriel, Pons, Joan Carles, and Scornavacca, Celine
- Subjects
BOTANY ,PHYSICAL sciences ,BINARY number system ,LIFE sciences ,PLANT anatomy ,GRAPH theory - Abstract
Phylogenetic networks generalize phylogenetic trees by allowing the modelization of events of reticulate evolution. Among the different kinds of phylogenetic networks that have been proposed in the literature, the subclass of binary tree-child networks is one of the most studied ones. However, very little is known about the combinatorial structure of these networks. In this paper we address the problem of generating all possible binary tree-child (BTC) networks with a given number of leaves in an efficient way via reduction/augmentation operations that extend and generalize analogous operations for phylogenetic trees, and are biologically relevant. Since our solution is recursive, this also provides us with a recurrence relation giving an upper bound on the number of such networks. We also show how the operations introduced in this paper can be employed to extend the evolutive history of a set of sequences, represented by a BTC network, to include a new sequence. An implementation in python of the algorithms described in this paper, along with some computational experiments, can be downloaded from . [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
45. Prediction model for the water jet falling point in fire extinguishing based on a GA-BP neural network.
- Author
-
Zhang, ChaoYi, Zhang, Ruirui, Dai, ZhiHui, He, BingYang, and Yao, Yan
- Subjects
WATER jets ,PREDICTION models ,ARTIFICIAL neural networks ,GENETIC algorithms ,BACK propagation ,AUTOMATIC train control - Abstract
Past research on the process of extinguishing a fire typically used a traditional linear water jet falling point model and the results ignored external factors, such as environmental conditions and the status of the fire engine, even though the water jet falling point location prediction was often associated with these parameters and showed a nonlinear relationship. This paper constructed a BP (Back Propagation) neural network model. The fire gun nozzle characteristics were included as model inputs, and the water discharge point coordinates were the model outputs; thus, the model could precisely predict the water discharge point with small error and high precision to determine an accurate firing position and allow for the timely adjustment of the spray gun. To improve the slow convergence and local optimality problems of the BP neural network (BPNN), this paper further used a genetic algorithm to optimize the BPNN (GA-BPNN). The BPNN can be used to optimize the weights in the network to train them for global optimization. A genetic algorithm was introduced into the neural network approach, and the water jet landing prediction model was further improved. The simulation results showed that the prediction accuracy of the GA-BP model was better than that of the BPNN alone. The established model can accurately predict the location of the water jet, making the prediction results more useful for firefighters. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
46. Biometric recognition via texture features of eye movement trajectories in a visual searching task.
- Author
-
Li, Chunyong, Xue, Jiguo, Quan, Cheng, Yue, Jingwei, and Zhang, Chenggang
- Subjects
EYE movements ,BIOMETRIC identification ,FEATURE extraction ,TEXTURE analysis (Image processing) ,TASK performance - Abstract
Biometric recognition technology based on eye-movement dynamics has been in development for more than ten years. Different visual tasks, feature extraction and feature recognition methods are proposed to improve the performance of eye movement biometric system. However, the correct identification and verification rates, especially in long-term experiments, as well as the effects of visual tasks and eye trackers’ temporal and spatial resolution are still the foremost considerations in eye movement biometrics. With a focus on these issues, we proposed a new visual searching task for eye movement data collection and a new class of eye movement features for biometric recognition. In order to demonstrate the improvement of this visual searching task being used in eye movement biometrics, three other eye movement feature extraction methods were also tested on our eye movement datasets. Compared with the original results, all three methods yielded better results as expected. In addition, the biometric performance of these four feature extraction methods was also compared using the equal error rate (EER) and Rank-1 identification rate (Rank-1 IR), and the texture features introduced in this paper were ultimately shown to offer some advantages with regard to long-term stability and robustness over time and spatial precision. Finally, the results of different combinations of these methods with a score-level fusion method indicated that multi-biometric methods perform better in most cases. [ABSTRACT FROM AUTHOR]
- Published
- 2018
- Full Text
- View/download PDF
47. The structural balance analysis of complex dynamical networks based on nodes' dynamical couplings.
- Author
-
Gao, Zilin and Wang, Yinhe
- Subjects
MATHEMATICAL models ,DYNAMICS ,NEURAL circuitry ,COMPUTER networks ,COMPUTATIONAL complexity ,SOCIAL networks ,SYNAPSES - Abstract
The nodes and their connection relationships are the two main bodies for dynamic complex networks. In existing theoretical researches, the phenomena of stabilization and synchronization for complex dynamical networks are generally regarded as the dynamic characteristic behaviors of the nodes, which are mainly caused by coupling effect of connection relationships between nodes. However, the connection relationships between nodes are also one main body of a time-varying dynamic complex network, and thus they may evolve with time and maybe show certain characteristic phenomena. For example, the structural balance in the social networks and the synaptic facilitation in the biological neural networks. Therefore, it is important to investigate theoretically the reasons in dynamics for the occurrence. Especially, from the angle of large-scale systems, how the dynamic behaviors of nodes (such as the individuals, neurons) contribute to the connection relationships is one of worthy research directions. In this paper, according to the structural balance theory of triad proposed by F. Heider, we mainly focus on the connection relationships body, which is regarded as one of the two subsystems (another is the nodes body), and try to find the dynamic mechanism of the structural balance with the internal state behaviors of the nodes. By using the Riccati linear matrix differential equation as the dynamic model of connection relationships subsystem, it is proved under some mathematic conditions that the connection relationships subsystem is asymptotical structural balance via the effects of the coupling roles with the internal state of nodes. Finally, the simulation example is given to show the validity of the method in this paper. [ABSTRACT FROM AUTHOR]
- Published
- 2018
- Full Text
- View/download PDF
48. Effects of Pyrolysis Temperature on Product Yields and Energy Recovery from Co-Feeding of Cotton Gin Trash, Cow Manure, and Microalgae: A Simulation Study
- Author
-
Renato O. Arazo, Muhammad Anwar Baig, Hamid Iqbal, Sergio C. Capareda, and Muhammad Usman Hanif
- Subjects
Hot Temperature ,Calorific Value ,Biomass ,lcsh:Medicine ,Plant Science ,02 engineering and technology ,Physical Chemistry ,Biochemistry ,Plant Energy Production ,Microalgae ,0202 electrical engineering, electronic engineering, information engineering ,Bioenergy ,lcsh:Science ,Fluids ,Energy recovery ,Multidisciplinary ,Plant Biochemistry ,Physics ,Simulation and Modeling ,Syngas ,Pulp and paper industry ,Lipids ,Renewable energy ,Chemistry ,Biofuel ,Physical Sciences ,Engineering and Technology ,Alternative Energy ,Research Article ,States of Matter ,020209 energy ,Materials Science ,Fuels ,Raw material ,Research and Analysis Methods ,Biogas ,Animals ,Cotton Fiber ,Materials by Attribute ,business.industry ,lcsh:R ,Correction ,Biology and Life Sciences ,Liquids ,Manure ,Energy and Power ,Chemical Properties ,Agronomy ,Biofuels ,Alternative energy ,Environmental science ,Cattle ,lcsh:Q ,business ,Oils ,Cow dung - Abstract
The intensive search of new and cleaner energy catches interest in recent years due to huge consumption of fossil fuels coupled with the challenge of energy and environmental sustainability. Production of renewable and environmentally benign energy from locally available raw materials is coming in the frontline. In this work, conversion of the combined biomass (cotton gin trash, cow manure, and Microalgae [Nannochloropsis oculata]) through batch pyrolysis has been investigated. The effect of temperature to the production of energy fuels such as bio-oil, char, and biogas have been simulated considering the yield and energy content as responses. Result of the investigation generally revealed that the proportions of the different biomass did not significantly affect the product yield and energy recovery. Significant effect of temperature is evident in the simulation result of energy recovery whereby maximum conversion was achieved at 400°C for char (91 wt%), 600°C for syngas (22 wt%), and 551°C for bio-oil (48 wt%). Overall energy conversion efficiency of 75.5% was obtained at 589°C in which 15.6 MJ/kg of mixed biomass will be elevated to pyrolysis products.
- Published
- 2016
49. Computational Time Reversal—A Frontier in Electromagnetic Structure Synthesis and Design.
- Author
-
Hoefer, Wolfgang J. R.
- Subjects
ELECTROMAGNETIC waves ,ELECTROMAGNETISM ,TIME reversal ,ELECTROMAGNETIC fields ,TRANSMISSION line matrix methods - Abstract
Microwave component design by electromagnetic structure synthesis is attractive because the electromagnetic field has the inherent property to minimize loss, sensitivity to tolerances, and vulnerability to field breakdown. However, it is conceptually and computationally challenging, and its technical possibilities have thus been explored only tentatively so far. This paper introduces a first, but critical new step towards systematic electromagnetic structure synthesis, based on computational time reversal, and employing the time and space discrete transmission line matrix (TLM) method. The novelty of this paper resides in the exploitation of the scattering nature of the TLM model, which allows the near-field of a source or a scatterer to propagate into the far-field and back. By ignoring the conventional restriction that spatial wavelengths must always be much larger than the space discretization step, one can reconstruct multiple impulsive sources with the spatial and temporal resolution of the TLM algorithm. This crucial insight promises to be the key to a successful synthesis strategy. This paper describes the reconstruction of electromagnetic sources through computational time reversal, demonstrates the self-consistency of this procedure by means of a validation example, and outlines the next steps towards a full electromagnetic synthesis capability. [ABSTRACT FROM PUBLISHER]
- Published
- 2015
- Full Text
- View/download PDF
50. Bi-Objective Flexible Job-Shop Scheduling Problem Considering Energy Consumption under Stochastic Processing Times.
- Author
-
Yang, Xin, Zeng, Zhenxiang, Wang, Ruidong, and Sun, Xueshan
- Subjects
ENERGY consumption ,GENETIC algorithms ,MANUFACTURING industries ,MATHEMATICAL optimization ,STOCHASTIC processes - Abstract
This paper presents a novel method on the optimization of bi-objective Flexible Job-shop Scheduling Problem (FJSP) under stochastic processing times. The robust counterpart model and the Non-dominated Sorting Genetic Algorithm II (NSGA-II) are used to solve the bi-objective FJSP with consideration of the completion time and the total energy consumption under stochastic processing times. The case study on GM Corporation verifies that the NSGA-II used in this paper is effective and has advantages to solve the proposed model comparing with HPSO and PSO+SA. The idea and method of the paper can be generalized widely in the manufacturing industry, because it can reduce the energy consumption of the energy-intensive manufacturing enterprise with less investment when the new approach is applied in existing systems. [ABSTRACT FROM AUTHOR]
- Published
- 2016
- Full Text
- View/download PDF
Discovery Service for Jio Institute Digital Library
For full access to our library's resources, please sign in.