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

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

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

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

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

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

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

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

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

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,

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

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.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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,

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

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.

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

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

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

“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

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’

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

Recently, world-class human players have been outperformed in a number of complex two-person games (Go, Chess, Checkers) by Deep Reinforcement Learning systems. However, the data efficiency of the learning systems is unclear given that they appear to require far more training games to achieve such performance than any human player might experience in a lifetime. In addition, the resulting learned strategies

Professor Koichi Furukawa, an eminent computer scientist and former Editor-in-Chief of the New Generation Computing journal, passed away on January 31, 2017. His passing was a surprise, and we were all shocked and saddened by the news. To remember the deceased, this article reviews the great career and contributions of Professor Koichi Furukawa, focusing on his research activities on the foundation

Given an observation or a goal, abduction infers candidate hypotheses to explain the observation or to achieve the goal. In this paper, we consider disjunctive abduction, in which disjunctions play important roles in abduction. Machine-oriented intelligent systems can utilize disjunctive abduction in many ways. For example, consider the case in which multiple explanations exist for an observation.

Dr. Furukawa had a sharp view in pinpointing that the crucial issue in skill science lies in discovering missing parts, that it is an act of abductive thinking, and that logic programming can be best used to encourage people, who intend to learn embodied skills, to think and feel more than without it. In the wake of the grief that our communities lost Dr. Furukawa, discussions on implications that

Skill is an action requiring intelligence. It has been debated whether motions require representations because they are thought to describe procedures. The dichotomy between thought and execution has puzzled us because we are unsure how thinking process intervenes with execution and how execution is understood by thinking process. We have in other words no logical theory of executions. We propose an

We argue that studies on embodied knowledge should deal with the process of how knowledge is learned, if we consider the essential meaning of the notion of “embodiment”. In other words, those studies are supposed to deal with the flow of time as the learner lives a life, because learning of embodied knowledge is intrinsically embedded in minds, social contexts, and life. Then, in examinations of learning

A knowledge push system as a proactive method of knowledge management, and is an effective way to push knowledge to designers in the product design process. Knowledge push can help to improve design efficiency and quality, but the knowledge pushed to designers is less applicable in engineering scenarios. To improve the quality of knowledge push, we propose the trust-aware and item-cluster strategies

In this paper, we propose a decision-tree modeling in the framework of membrane computing. We propose an algorithm to obtain a P system that is equivalent to any decision tree taken as input. In our case, and unlike previous proposals, we formulate the concepts of decision trees endogenously, since there is no external agent involved in the modeling. The tree structure can be defined naturally by the

In this paper, we present a time series structure analysis method of a meeting using text data and a method for the visualization of state transitions. Our method evaluates and visualizes the convergence/divergence of the meeting in a time series using text data from the meeting. It is important to facilitate and review meetings for improving efficiency. Therefore, it is important not only to review

In this paper, we consider the implementation of a cellular automaton by DNA computing. The proposed system is a reaction–diffusion system built on a structured hydrogel matrix that mimics cellular compartments of biological tissues. Since the cellular automaton is materialized by a hydrogel matrix, the system is called gellular automaton which is theoretically capable of pattern formation and computation

Neural network is one of the best tools for data mining tasks due to its high accuracy. However, one of the drawbacks of neural network is its black box nature. This limitation makes neural network useless for many applications which require transparency in their decision-making process. Many algorithms have been proposed to overcome this drawback by extracting transparent rules from neural network

Thanks to a number of efficient implementations, the use of logic formalisms for problem-solving has been increased in several real-world domains. This is the case, for instance, of action languages, such as planning domain definition language (PDDL), or answer set programming (ASP), which is a well-established declarative problem-solving paradigm that became widely used in AI and recognized as a powerful

Metaphors convey unspoken emotions and perceptions by creatively applying an evocative concept from the source domain to illustrate some latent idea in the target domain. Prior research on nominal metaphor interpretation focused on identifying those properties of the source domain which are highly related to the target domain concepts to discover the most likely sense of the metaphor’s usage. In this

When implementing a programming language, we often write a parser and a pretty-printer. However, manually writing both programs is not only tedious but also error-prone; it may happen that a pretty-printed result is not correctly parsed. In this paper, we propose FliPpr, which is a program transformation system that uses program inversion to produce a CFG parser from a pretty-printer. This novel approach

Reversible computation has attracted increasing interest in recent years. In this paper, we show how to model reversibility in concurrent computation as realised abstractly in terms of event structures. Two different forms of event structures are considered, namely event structures defined by causation and prevention relations and event structures given by an enabling relation with prevention. We then

Although the vertex-centric model originating from Pregel has been well studied, its applications are limited and biased. While PageRank, which can be formalized as a network flow problem, is one of the most common (or overused) applications, the maximum flow problem, which is the most fundamental problem on flow networks, has never been dealt with. In this work, in order to analyze the applicability