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Card-Based Cryptography Meets Formal Verification New Gener. Comput. (IF 0.889) Pub Date : 2021-04-02 Alexander Koch, Michael Schrempp, Michael Kirsten
Card-based cryptography provides simple and practicable protocols for performing secure multi-party computation with just a deck of cards. For the sake of simplicity, this is often done using cards with only two symbols, e.g., \(\clubsuit \) and \(\heartsuit \) . Within this paper, we also target the setting where all cards carry distinct symbols, catering for use-cases with commonly available standard
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Estimation of COVID-19 Under-Reporting in the Brazilian States Through SARI New Gener. Comput. (IF 0.889) Pub Date : 2021-03-14 Balthazar Paixão, Lais Baroni, Marcel Pedroso, Rebecca Salles, Luciana Escobar, Carlos de Sousa, Raphael de Freitas Saldanha, Jorge Soares, Rafaelli Coutinho, Fabio Porto, Eduardo Ogasawara
Due to its impact, COVID-19 has been stressing the academy to search for curing, mitigating, or controlling it. It is believed that under-reporting is a relevant factor in determining the actual mortality rate and, if not considered, can cause significant misinformation. Therefore, this work aims to estimate the under-reporting of cases and deaths of COVID-19 in Brazilian states using data from the
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Semi-supervised Ensemble Learning for Efficient Cancer Sample Classification from miRNA Gene Expression Data New Gener. Comput. (IF 0.889) Pub Date : 2021-03-06 Dikme Chisil B. Marak, Anindya Halder, Ansuman Kumar
Traditional classifiers often fail to produce desired classification accuracy because of inadequate training samples present in microRNA (miRNA) gene expression cancer datasets. In this context, we propose a novel semi-supervised ensemble learning (SSEL) strategy combining the (advantages of) semi-supervised learning and ensemble learning which is able to produce better results than the individual
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Tailored Network Splitting for Community Evolution Prediction in Dynamic Social Networks New Gener. Comput. (IF 0.889) Pub Date : 2021-03-03 Narimene Dakiche, Fatima Benbouzid-Si Tayeb, Karima Benatchba, Yahya Slimani
One of the most challenging issues dealing with dynamic social networks, with evolving community structures, is to understand and model the way in which these structures evolve over time. Studies on tracking and predicting community evolution generally split these networks into time-series of static networks, each including interactions aggregated over discrete time intervals (hours, days, and years)
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Ensemble Methods for Heart Disease Prediction New Gener. Comput. (IF 0.889) Pub Date : 2021-03-01 Talha Karadeniz, Gül Tokdemir, Hadi Hakan Maraş
Heart disease prediction is a critical task regarding human health. It is based on deriving an Machine Learning model from medical parameters to predict risk levels. In this work, we propose and test novel ensemble methods for heart disease prediction. Randomness analysis of distance sequences is utilized to derive a classifier, which is served as a base estimator of a bagging scheme. Method is successfully
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XCOVNet: Chest X-ray Image Classification for COVID-19 Early Detection Using Convolutional Neural Networks New Gener. Comput. (IF 0.889) Pub Date : 2021-02-24 Vishu Madaan, Aditya Roy, Charu Gupta, Prateek Agrawal, Anand Sharma, Cristian Bologa, Radu Prodan
COVID-19 (also known as SARS-COV-2) pandemic has spread in the entire world. It is a contagious disease that easily spreads from one person in direct contact to another, classified by experts in five categories: asymptomatic, mild, moderate, severe, and critical. Already more than 66 million people got infected worldwide with more than 22 million active patients as of 5 December 2020 and the rate is
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Five-Card AND Computations in Committed Format Using Only Uniform Cyclic Shuffles New Gener. Comput. (IF 0.889) Pub Date : 2021-01-18 Yuta Abe, Yu-ichi Hayashi, Takaaki Mizuki, Hideaki Sone
In card-based cryptography, designing AND protocols in committed format is a major research topic. The state-of-the-art AND protocol proposed by Koch, Walzer, and Härtel in ASIACRYPT 2015 uses only four cards, which is the minimum permissible number. The minimality of their protocol relies on somewhat complicated shuffles having non-uniform probabilities of possible outcomes. Restricting the allowed
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How to Solve Millionaires’ Problem with Two Kinds of Cards New Gener. Comput. (IF 0.889) Pub Date : 2021-01-05 Takeshi Nakai, Yuto Misawa, Yuuki Tokushige, Mitsugu Iwamoto, Kazuo Ohta
Card-based cryptography, introduced by den Boer aims to realize multiparty computation (MPC) by using physical cards. We propose several efficient card-based protocols for the millionaires’ problem by introducing a new operation called Private Permutation (PP) instead of the shuffle used in most of existing card-based cryptography. Shuffle is a useful randomization technique by exploiting the property
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A Heterogeneous Ensemble Forecasting Model for Disease Prediction New Gener. Comput. (IF 0.889) Pub Date : 2021-01-04 Nonita Sharma, Jaiditya Dev, Monika Mangla, Vaishali Mehta Wadhwa, Sachi Nandan Mohanty, Deepti Kakkar
The manuscript presents a bragging-based ensemble forecasting model for predicting the number of incidences of a disease based on past occurrences. The objectives of this research work are to enhance accuracy, reduce overfitting, and handle overdrift; the proposed model has shown promising results in terms of error metrics. The collated dataset of the diseases is collected from the official government
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Card-based Cryptography with Dihedral Symmetry New Gener. Comput. (IF 0.889) Pub Date : 2021-01-04 Kazumasa Shinagawa
It is known that secure computation can be done by using a deck of physical cards. This area is called card-based cryptography. Shinagawa et al. (in: Provable security—9th international conference, ProvSec 2015, Kanazawa, Japan, 2015) proposed regular n-sided polygon cards that enable to compute functions over \({\mathbb {Z}}/n{\mathbb {Z}}\). In particular, they designed efficient protocols for linear
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CCDSF: A Computational Creative Design Systems Framework New Gener. Comput. (IF 0.889) Pub Date : 2020-11-23 Jesús Pérez-Romero, Wendy Aguilar
From a mixed perspective of the fields of computational creativity and design research, we present a formal framework called Computational Creative Design Systems Framework (CCDSF) for describing, analyzing, and modeling Computational Creative Design Systems (CCDSs), either as autonomous agents or as collaborative systems integrating different agents, including both pure computational and human–computer
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Leaps and Bounds: An Introduction to the Field of Computational Creativity New Gener. Comput. (IF 0.889) Pub Date : 2020-11-09 Tony Veale, Rafael Pérez y Pérez
Computers have enhanced productivity and cost-effectiveness in all of the creative industries, and their value as tools is rarely doubted. But can machines serve as more than mere tools, and assume the role and responsibilities of a co-creative partner, or even become goal-setting, autonomous creators in their own right? These are the questions that define the discipline of computational creativity
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Card-Based Cryptographic Logical Computations Using Private Operations New Gener. Comput. (IF 0.889) Pub Date : 2020-10-31 Hibiki Ono, Yoshifumi Manabe
This paper proposes new card-based cryptographic protocols to calculate logic functions with the minimum number of cards using private operations under the semi-honest model. Though various card-based cryptographic protocols were shown, the minimum number of cards used in the protocol has not been achieved yet for many problems. Operations executed by a player where the other players cannot see are
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Exploring Baselines for Combining Full Plots into Multiple-plot Stories New Gener. Comput. (IF 0.889) Pub Date : 2020-10-28 Eugenio Concepción, Pablo Gervás, Gonzalo Méndez
Many of the stories at the core of narrative entertainment involve a number of plot lines that combine to give them interest. The present paper sets out to solve the problem of how several different plot lines, each one of them complete in its own sense, can be combined into a single linear sequence that works reasonably well as a plot. Starting from a brief review of how existing storytelling systems
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Learning Disjunctive Logic Programs from Nondeterministic Interpretation Transitions New Gener. Comput. (IF 0.889) Pub Date : 2020-10-24 Yi Huang, Yisong Wang, Jia-Huai You, Mingyi Zhang, Ying Zhang
Inductive logic programming (ILP) is a framework of learning logic programs from examples and background knowledge. In some real-world applications, we are particularly interested in learning aspects of system dynamics that are characterized by state transitions for which logic programs are shown to be expressive. In this work, we study this particular form of ILP—learning logic programs from state/interpretation
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Physical Zero-Knowledge Proof for Numberlink Puzzle and k Vertex-Disjoint Paths Problem New Gener. Comput. (IF 0.889) Pub Date : 2020-10-22 Suthee Ruangwises, Toshiya Itoh
Numberlink is a logic puzzle with an objective to connect all pairs of cells with the same number by non-crossing paths in a rectangular grid. In this paper, we propose a physical protocol of zero-knowledge proof for Numberlink using a deck of cards, which allows a prover to convince a verifier that he/she knows a solution without revealing it. In particular, the protocol shows how to physically count
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Quantitative Characteristics of Human-Written Short Stories as a Metric for Automated Storytelling New Gener. Comput. (IF 0.889) Pub Date : 2020-10-14 Carlos León, Pablo Gervás, Pablo Delatorre, Alan Tapscott
Evaluating the extent to which computer-produced stories are structured like human-invented narratives can be an important component of the quality of a story plot. In this paper, we report on an empirical experiment in which human subjects have invented short plots in a constrained scenario. The stories were annotated according to features commonly found in existing automatic story generators. The
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Bisociative Literature-Based Discovery: Lessons Learned and New Word Embedding Approach New Gener. Comput. (IF 0.889) Pub Date : 2020-10-06 Nada Lavrač, Matej Martinc, Senja Pollak, Maruša Pompe Novak, Bojan Cestnik
The field of bisociative literature-based discovery aims at mining scientific literature to reveal yet uncovered connections between different fields of specialization. This paper outlines several outlier-based literature mining approaches to bridging term detection and the lessons learned from selected biomedical literature-based discovery applications. The paper addresses also new prospects in bisociative
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Visual Blending for Concept Representation: A Case Study on Emoji Generation New Gener. Comput. (IF 0.889) Pub Date : 2020-09-23 João M. Cunha, Nuno Lourenço, Pedro Martins, Penousal Machado
The emoji connection between visual representation and semantic knowledge, together with its large conceptual coverage have the potential to be exploited in computational approaches to the visual representation of concepts. An example of a system that explores this potential is Emojinating—a system that uses a process of visual blending of existing emoji to represent concepts. In this paper, we use
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Analyzing Promising Researchers Using Network Centralities of Co-authorship Networks from Academic Literature New Gener. Comput. (IF 0.889) Pub Date : 2020-09-19 Masanori Fujita, Hiroto Inoue, Takao Terano
We propose a new way of using the betweenness centrality measure with co-author networks from an academic literature database to evaluate young researchers. It is difficult to discover and evaluate promising young researchers with indexes based on the number of cited papers, such as the h-index to which published papers introduce a lag and whose impact only becomes apparent after they have been cited
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Towards a Methodology for Field Work in Computational Creativity New Gener. Comput. (IF 0.889) Pub Date : 2020-09-07 Rafael Pérez y Pérez, Margareta Ackerman
This work proposes a methodology for conducting field work in computational creativity, referring to field work as the effort of actively making a system or its artifacts widely accessible outside the academic world. Field work aims to study how creative computer agents and/or their products influence society, and how the dynamics that arise from the interaction between people and those inventive machines
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Enhanced Prediction of Intra-day Stock Market Using Metaheuristic Optimization on RNN–LSTM Network New Gener. Comput. (IF 0.889) Pub Date : 2020-09-05 Krishna Kumar, Md. Tanwir Uddin Haider
Deep Learning provides useful insights by analyzing information especially in the field of finance with advanced computing technology. Although, RNN–LSTM network with the advantage of sequential learning has achieved great success in the past for time series prediction. Conversely, developing and selecting the best computational optimized RNN–LSTM network for intra-day stock market forecasting is a
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The Show Must Go On: On the Use of Embodiment, Space and Gesture in Computational Storytelling New Gener. Comput. (IF 0.889) Pub Date : 2020-09-05 Philipp Wicke, Tony Veale
Stories are made to be told, yet the computational generation of stories has principally focused on stories as textual artifacts, rather than on the telling, or indeed the performance, of stories. The performative aspect of stories, in which a teller brings a tale to life, requires more than the written word. We humans use our bodies to enact a story, through the apt use of motion, space, timing and
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Knowledge-Based Sentiment Analysis and Visualization on Social Networks New Gener. Comput. (IF 0.889) Pub Date : 2020-08-30 Julio Vizcarra, Kouji Kozaki, Miguel Torres Ruiz, Rolando Quintero
A knowledge-based methodology is proposed for sentiment analysis on social networks. The work was focused on semantic processing taking into account the content handling the public user’s opinions as excerpts of knowledge. Our approach implements knowledge graphs, similarity measures, graph theory algorithms, and a disambiguation process. The results obtained were compared with data retrieved from
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Jaccard Guided Perturbation for Eigenvector Localization New Gener. Comput. (IF 0.889) Pub Date : 2020-07-13 Debasis Mohapatra
Understanding the role of network for epidemic spread is a major concern in the study of complex network and disease spread. Localization of Principal EigenVector (PEV) of the network’s adjacency matrix has been explored in recent past by many researchers. Most of the previous works suggest the localization of PEV through maximization of inverse participation ratio (IPR). The network with maximum IPR
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An Intelligent System to Generate Chord Progressions from Colors with an Artificial Immune System New Gener. Comput. (IF 0.889) Pub Date : 2020-06-25 María Navarro-Cáceres, José A. Castellanos-Garzón, Javier Bajo
Synesthesia is a neurological phenomenon in which stimulation of one sensory or cognitive pathway leads to automatic, involuntary experiences in a second sensory or cognitive pathway. Many synesthetes used their capabilities as inspiration for their works. Drawing on this phenomenon, this paper presents a model able to create chord progressions using colors as the synesthetic input. In particular,
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SimiT: A Text Similarity Method Using Lexicon and Dependency Representations New Gener. Comput. (IF 0.889) Pub Date : 2020-06-17 Emrah Inan
Semantic textual similarity methods are becoming increasingly crucial in text mining research areas such as text retrieval and summarization. Existing methods of text similarity have often been computed by their shallow or syntactic representation rather than considering their semantic content and meanings. This paper focuses mainly on computing the similarity between sentences without a supervised
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Correction to: Special Issue on Molecular Robotics New Gener. Comput. (IF 0.889) Pub Date : 2020-05-30 Satoshi Murata
The article “Special Issue on Molecular Robotics”, written by Satoshi Murata was originally published electronically on the publisher's internet portal (currently SpringerLink) on 18th May 2020 with open access.
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Modeling and Analysis of Stochastic Reaction Kinetics in Biomolecular Systems New Gener. Comput. (IF 0.889) Pub Date : 2020-05-16 Yutaka Hori
Chemical reactions in small-volume reactors such as biological cells are highly variable due to the stochastic collision events of the small number of molecules. To analyze and design these stochastic biomolecular reactions, computational tools have been developed based on rigorous mathematical foundations. This paper reviews fundamental theory and computational tools for the modeling, analysis, and
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Programming Methods for DNA-Based Reaction–Diffusion Systems New Gener. Comput. (IF 0.889) Pub Date : 2020-05-11 Keita Abe, Satoshi Murata
In this tutorial, recent development of pattern generation algorithms based on DNA computing will be overviewed. Natural pattern generation, especially in biological organisms, are often driven by spatio-temporal chemical reactions. Various reaction–diffusion systems have been proposed to generate artificial patterns out of DNA sequences. To program DNA reaction–diffusion systems, in addition to the
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Chemotaxis-Inspired Control for Multi-Agent Coordination: Formation Control by Two Types of Chemotaxis Controllers New Gener. Comput. (IF 0.889) Pub Date : 2020-05-05 Shinsaku Izumi, Shun-ichi Azuma
This paper investigates the control of multi-agent systems inspired by chemotaxis of microorganisms. Chemotaxis is a biological phenomenon wherein organisms in an environment are attracted to food but move away from toxins. The problem addressed here is a formation control problem, i.e., a design problem of distributed controllers wherein the relative positions of agents become the desired positions
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Distributed Computing Theory for Molecular Robot Systems New Gener. Comput. (IF 0.889) Pub Date : 2020-05-03 Yukiko Yamauchi
Distributed computation consists of local computations and their interactions. We consider a molecular robot system as a distributed system composed of mobile computing entities with very weak capabilities, i.e., computing entities are anonymous (indistinguishable), oblivious (memory-less), and uniform (following a common local computation rule). The key property of such a distributed system is self-organization
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Existing Business Process Models for Model Construction of Multidimensional Business Knowledge: An MDA-Based Transformation Methodology New Gener. Comput. (IF 0.889) Pub Date : 2020-04-30 Sonya Ouali, Mohamed Mhiri, Faiez Gargouri
Owing to the absolute significance of the business process management, companies have become thoroughly oriented toward a good modeling of the business processes. Although the business process modeling is a substantial part in workflow automation, business process designers often misunderstand domain concepts or relationships due to their lack of precise business knowledge. Such a semantic equivocation
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Unifying Parsing and Reflective Printing for Fully Disambiguated Grammars New Gener. Comput. (IF 0.889) Pub Date : 2020-04-29 Zirun Zhu, Hsiang-Shang Ko, Yongzhe Zhang, Pedro Martins, João Saraiva, Zhenjiang Hu
Language designers usually need to implement parsers and printers. Despite being two closely related programs, in practice they are often designed separately, and then need to be revised and kept consistent as the language evolves. It will be more convenient if the parser and printer can be unified and developed in a single program, with their consistency guaranteed automatically. Furthermore, in certain
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Renewal of the Major Fields of New Generation Computing Vol. 38 (2020) New Gener. Comput. (IF 0.889) Pub Date : 2020-04-04 Masayuki Numao, Yutaka Matsuo, Shinnosuke Seki
The editorial board would like to introduce a new area editor, Shinnosuke Seki, who is establishing a new area for the journal: “Theory of Natural Computing”. He welcomes theoretical studies on internationally accepted models of computation, including cellular automata, chemical reaction networks, Lindenmayer (L-) systems, Nubot models, Oritatami systems, P systems (membrane computing), reaction systems
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XOR Gate Design Toward a Practical Complete Set for DNA Computing New Gener. Comput. (IF 0.889) Pub Date : 2020-03-21 Katsuhiro Nishijima, Takashi Nakakuki
Practical design of the XOR gate is an important milestone in the field of DNA computing. In this study, we aim to develop an enzyme-free XOR gate driven by a toehold-mediated strand displacement mechanism possessing the true detection property. The advantages of our design are as follows: dual-rail logic is not required, the explicit use of the NOT gate is avoided, the circuit structure is simple
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Designing Dynamical Molecular Systems with the PEN Toolbox New Gener. Comput. (IF 0.889) Pub Date : 2020-03-19 Nathanael Aubert-Kato, Leo Cazenille
This tutorial paper focuses on the design, simulation, and optimization of polymerase–exonuclease–nickase (PEN) toolbox systems. The PEN toolbox is a molecular programming framework that relies on the interaction between DNA molecules and enzymes to produce highly non-linear dynamic systems. The flip side of that expressivity is that the design of systems relies heavily on trial-and-error, thus calling
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Knowledge-Driven Intelligent Survey Systems Towards Open Science New Gener. Comput. (IF 0.889) Pub Date : 2020-03-11 Elspeth Edelstein, Jeff Z. Pan, Ricardo Soares, Adam Wyner
In this paper, we propose Knowledge Graph (KG), an articulated underlying semantic structure, as a semantic bridge between humans, systems, and scientific knowledge. To illustrate our proposal, we focus on KG-based intelligent survey systems. In state-of-the-art systems, information is hard-coded or implicit, making it hard for researchers to reuse, customise, link, or transmit structured knowledge
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Augmenting Linked Data Ontologies with New Object Properties New Gener. Comput. (IF 0.889) Pub Date : 2020-02-08 S. Subhashree, P. Sreenivasa Kumar
Although several RDF knowledge bases are available through the Linked Open Data (LOD) initiative, the ontology schema of such linked datasets is not very rich. In particular, they lack object properties. The problem of finding new object properties between any two given classes has not been investigated in detail in the context of Linked Data. In the first part of this paper, we present DARO (Detecting
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Evaluation of Generalization Performance of Visuo-Motor Learning by Analyzing Internal State Structured from Robot Motion New Gener. Comput. (IF 0.889) Pub Date : 2020-01-22 Hiroshi Ito, Kenjiro Yamamoto, Hiroki Mori, Tetsuya Ogata
To provide robots with the flexibility they need to cope with various environments, motion generation techniques using deep learning have been proposed. Generalization in deep learning is expected to enable flexible processing in unknown situations and flexible motion generation. Motion generation models have been proposed to realize specific robot tasks, and their operation successes in unknown situations
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Neuro-SERKET: Development of Integrative Cognitive System Through the Composition of Deep Probabilistic Generative Models New Gener. Comput. (IF 0.889) Pub Date : 2020-01-22 Tadahiro Taniguchi, Tomoaki Nakamura, Masahiro Suzuki, Ryo Kuniyasu, Kaede Hayashi, Akira Taniguchi, Takato Horii, Takayuki Nagai
This paper describes a framework for the development of an integrative cognitive system based on probabilistic generative models (PGMs) called Neuro-SERKET. Neuro-SERKET is an extension of SERKET, which can compose elemental PGMs developed in a distributed manner and provide a scheme that allows the composed PGMs to learn throughout the system in an unsupervised way. In addition to the head-to-tail
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Attentional Reinforcement Learning in the Brain New Gener. Comput. (IF 0.889) Pub Date : 2020-01-02 Hiroshi Yamakawa
Recently, attention mechanisms have significantly boosted the performance of natural language processing using deep learning. An attention mechanism can select the information to be used, such as by conducting a dictionary lookup; this information is then used, for example, to select the next utterance word in a sentence. In neuroscience, the basis of the function of sequentially selecting words is
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Development and Evaluation of a New Platform for Accelerating Cross-Domain Data Exchange and Cooperation New Gener. Comput. (IF 0.889) Pub Date : 2019-11-29 Daiji Iwasa, Teruaki Hayashi, Yukio Ohsawa
The technologies for collecting and analyzing data are developing significantly, enabling us to gain new knowledge from various types of data. Recently, the considerably increasing expectation for cross-domain data exchange and cooperation has attracted attention from data markets. However, as we lack data-utilization knowledge, an accurate evaluation of data is difficult; a non-price indicator for
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A Survey on Modeling Language Evolution in the New Millennium New Gener. Comput. (IF 0.889) Pub Date : 2019-11-25 Arianna D’Ulizia, Fernando Ferri, Patrizia Grifoni
Language is a complex evolving system and it is not a trivial task to model the dynamics of processes occurring during its evolution. Therefore, modeling language evolution has attracted the interest of several researchers giving rise to a lot of models in the literature of the last millennium. This work reviews the literature devoted to computationally represent the evolution of human language through
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Mining High-Average Utility Itemsets with Positive and Negative External Utilities New Gener. Comput. (IF 0.889) Pub Date : 2019-11-07 Irfan Yildirim, Mete Celik
High-utility itemset mining (HUIM) is an emerging data mining topic. It aims to find the high-utility itemsets by considering both the internal (i.e., quantity) and external (i.e., profit) utilities of items. High-average-utility itemset mining (HAUIM) is an extension of the HUIM, which provides a more fair measurement named average-utility, by taking into account the length of itemsets in addition
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EmbNum+: Effective, Efficient, and Robust Semantic Labeling for Numerical Values New Gener. Comput. (IF 0.889) Pub Date : 2019-11-04 Phuc Nguyen, Khai Nguyen, Ryutaro Ichise, Hideaki Takeda
In recent years, there has been an increasing interest in numerical semantic labeling, in which the meaning of an unknown numerical column is assigned by the label of the most relevant columns in predefined knowledge bases. Previous methods used the p value of a statistical hypothesis test to estimate the relevance and thus strongly depend on the distribution and data domain. In other words, they are
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Interconnection of Biological Knowledge Using NikkajiRDF and Interlinking Ontology for Biological Concepts New Gener. Comput. (IF 0.889) Pub Date : 2019-09-27 Tatsuya Kushida, Kouji Kozaki, Takahiro Kawamura, Yuka Tateisi, Yasunori Yamamoto, Toshihisa Takagi
We investigated the interconnection on knowledge of biological molecules, biological phenomena, and diseases to efficiently collect information regarding the functions of chemical compounds and gene products, roles, applications, and involvements in diseases using knowledge graphs (KGs) developed from Resource Description Framework (RDF) data and ontologies. NikkajiRDF linked open data provide information
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A Semi-automated Ontology Construction for Legal Question Answering New Gener. Comput. (IF 0.889) Pub Date : 2019-09-06 Biralatei Fawei, Jeff Z. Pan, Martin Kollingbaum, Adam Z. Wyner
The internet and the development of the semantic web have created the opportunity to provide structured legal data on the web. However, most legal information is in text. It is difficult to automatically determine the right natural language answer about the law to a given natural language question. One approach is to develop systems of legal ontologies and rules. Our example ontology represents semantic
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Semantic Representation for Age Word Problems with Schemas New Gener. Comput. (IF 0.889) Pub Date : 2019-09-05 Sowmya S. Sundaram, Savitha Sam Abraham
A method of representing algebraic age word problems for automated solving has been proposed. Schemas pertinent to the domain have been represented as logical predicates and functions and used as an intermediate representation. Though data-driven methods have dominated the paradigm for solving word problems recently, we demonstrate that representing these word problems formally has advantages. We illustrate
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Concurrent Treaps and Impact of Locking Objects New Gener. Comput. (IF 0.889) Pub Date : 2019-09-04 Praveen Alapati, Madhu Mutyam, Swamy Saranam
We propose algorithms to perform operations concurrently on treaps in a shared memory multi-core environment. Concurrent treaps hold the advantage of using nodes’ priority for maintaining the height of the treaps. To achieve synchronization, concurrent treaps make use of fine-grained locking mechanism along with logical ordering and physical ordering of nodes’ keys. We initially study the throughput
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An Ontology-Based Kinematics Problem Solver Using Qualitative and Quantitative Knowledge New Gener. Comput. (IF 0.889) Pub Date : 2019-09-03 Savitha Sam Abraham, Sowmya S. Sundaram
One of the major tasks involved in the development of a knowledge-based problem solver is domain knowledge representation and reasoning. In this paper, we address this task for a knowledge-based kinematics word problem solver that solves problems from the domain of kinematics automatically, where solving each problem involves identifying the value of a specific unknown quantity referred to, within
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Query Extension Suggestions for Visual Query Systems Through Ontology Projection and Indexing New Gener. Comput. (IF 0.889) Pub Date : 2019-09-03 Vidar N. Klungre, Ahmet Soylu, Ernesto Jimenez-Ruiz, Evgeny Kharlamov, Martin Giese
Ontology-based visual query formulation is a viable alternative to textual query editors in the Semantic Web domain for extracting data from structured data sources in terms of the skills and knowledge required. A visual query system is at any moment responsible for providing the user with query extension suggestions; however, suggestions leading to empty results are often not useful. To this end,
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A Semantic-Based Framework for Rice Plant Disease Management New Gener. Comput. (IF 0.889) Pub Date : 2019-09-03 Watanee Jearanaiwongkul, Chutiporn Anutariya, Frederic Andres
Rice plant diseases can cause damages and yield losses. To reduce the productivity losses, farmers need to observe and decide suitable treatments for the diseases recognized from the abnormal characteristics appeared in their farms. Traditionally, farmers identify potential diseases from their experiences or by consulting other experts. However, this approach has certain disadvantages due to varying
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MAAI: Dynamic Equilibrium in Architecture New Gener. Comput. (IF 0.889) Pub Date : 2019-08-26 Haruyuki Fujii
This paper tries to express MAAI in architectural activity and its relation with computing. The notion of dynamic equilibrium has been employed as a metaphoric expression of MAAI. Architectural activity is assumed to be composed of the creation of architectural space, utilization of it, and inquiry into it. Some types of dynamic equilibrium are introduced as they are associated with this activity.
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Temporal Link Prediction: A Survey New Gener. Comput. (IF 0.889) Pub Date : 2019-08-13 Aswathy Divakaran, Anuraj Mohan
The evolutionary behavior of temporal networks has gained the attention of researchers with its ubiquitous applications in a variety of real-world scenarios. Learning evolutionary behavior of networks is directly related to link prediction problem, as the addition or removal of new links or edges over time leads to the network evolution. With the rise of large-scale temporal networks such as social
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Whole-Cell Modeling and Simulation: A Brief Survey New Gener. Comput. (IF 0.889) Pub Date : 2019-08-12 Nayana G. Bhat, S. Balaji
Gaining knowledge and engineering of biological systems require comprehensive models of cellular physiology with 100% predictability. The whole-cell models direct experiments in molecular biological science and empower simulation and computer-aided design in synthetic biology. Whole-cell modeling and simulation help in personalized medical treatment building a biological system through cell interactions
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TOMS: A Linked Open Data System for Collaboration and Distribution of Cultural Heritage Artifact Collections of National Museums in Thailand New Gener. Comput. (IF 0.889) Pub Date : 2019-08-10 Weeraphan Chanhom, Chutiporn Anutariya
The cultural heritage artifacts that have been collected in national museums serve as important resources for learning, and contribute to the country’s development. In this work, we present TOMS (Thailand Open Museum System), a semantic-based application designed to enable collaboration and the sharing of a wide range of information among national museums. This is accomplished by using linked open
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How Could and Should “Maai”, Empathetic Relation from Second-Person’s Viewpoint, Be Studied? New Gener. Comput. (IF 0.889) Pub Date : 2019-07-24 Masaki Suwa
“Maai” is a concept that represents a relation holding spatially and temporarily among more than two people or things, at least one of which is a human being. Forming a state of “maai” means to read the intentions or movements of the other, make adjustment of physical and/or mental distance, and organize a proper way of being there physically and mentally. In the modern era in which people make free
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Field Interaction Analysis: A Second-Person Viewpoint Approach to Maai New Gener. Comput. (IF 0.889) Pub Date : 2019-07-24 Katsuya Takanashi, Yasuharu Den
In this article, we investigate a second-person viewpoint approach to an interactive phenomenon called maai, in which interactants’ own perception and sense of relation to each other are central. In the basic ideas of conversation analysis (CA), one of the powerful methodologies for the second-person viewpoint approach to social interaction, it is paramount that analysts can descriptively trace participants’
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Phenomenology of Ma and Maai: An Interpretation of Zeami’s Body Cosmology from a Phenomenological Point of View New Gener. Comput. (IF 0.889) Pub Date : 2019-07-02 Tetsuya Kono
In this paper, I shall try to clarify from the standpoint of phenomenology, the essential features of the phenomenon of ma (間) and maai (間合い). I shall delineate their cultural and philosophical implications by interpreting the treatises of Noh by Motokiyo Zeami. Zeami was the most important Noh performer, playwright, and esthetic theorist. Ma is the physical/mental distance that prepares the advent
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