Authors:Luca Tranchini Abstract: Publication date: December 2017 Source:Journal of Applied Logic, Volume 25, Supplement Author(s): Luca Tranchini We present a multiple-assumption multiple-conclusion system for bi-intuitionistic logic. Derivations in the systems are graphs whose edges are labelled by formulas and whose nodes are labelled by rules. We show how to embed both the standard intuitionistic and dual-intuitionistic natural deduction systems into the proposed system. Soundness and completeness are established using translations with more traditional sequent calculi for bi-intuitionistic logic.
Authors:Ahti-Veikko Pietarinen; Francesco Bellucci Pages: 1 - 22 Abstract: Publication date: December 2017 Source:Journal of Applied Logic, Volume 25 Author(s): Ahti-Veikko Pietarinen, Francesco Bellucci This paper presents two major aspects of Frege's and Peirce's views on assertion and denial: first, their arguments for the notational choices concerning the representation of assertion and denial in Begriffsschrift (BS) and Existential Graphs (EGs), respectively; and second, those properties of BS and EGs which reflect their inventors' views on assertion and denial. We show that while Frege's notation has an ad hoc sign of assertion and an ad hoc sign of negation, Peirce has a sign of assertion which is also a sign of logical conjunction, and a sign of scope which is also a sign of negation.
Authors:Heinrich Wansing Pages: 23 - 46 Abstract: Publication date: Available online 5 December 2017 Source:Journal of Applied Logic Author(s): Heinrich Wansing In this paper it is suggested to generalize our understanding of general (structural) proof theory and to consider it as a general theory of two kinds of derivations, namely proofs and dual proofs. The proposal is substantiated by (i) considerations on assertion, denial, and bi-lateralism, (ii) remarks on compositionality in proof-theoretic semantics, and (iii) comments on falsification and co-implication. The main formal result of the paper is a normal form theorem for the natural deduction proof system N2Int of the bi-intuitionistic logic 2Int. The proof makes use of the faithful embedding of 2Int into intuitionistic logic with respect to validity and shows that conversions of dual proofs can be sidestepped.
Authors:Heinrich Wansing Pages: 23 - 46 Abstract: Publication date: December 2017 Source:Journal of Applied Logic, Volume 25 Author(s): Heinrich Wansing In this paper it is suggested to generalize our understanding of general (structural) proof theory and to consider it as a general theory of two kinds of derivations, namely proofs and dual proofs. The proposal is substantiated by (i) considerations on assertion, denial, and bi-lateralism, (ii) remarks on compositionality in proof-theoretic semantics, and (iii) comments on falsification and co-implication. The main formal result of the paper is a normal form theorem for the natural deduction proof system N2Int of the bi-intuitionistic logic 2Int. The proof makes use of the faithful embedding of 2Int into intuitionistic logic with respect to validity and shows that conversions of dual proofs can be sidestepped.
Authors:Álvaro Herrero; Bruno Baruque; Javier Sedano; Héctor Quintián; Emilio Corchado Pages: 1 - 2 Abstract: Publication date: November 2017 Source:Journal of Applied Logic, Volume 24, Part B Author(s): Álvaro Herrero, Bruno Baruque, Javier Sedano, Héctor Quintián, Emilio Corchado
Authors:Pablo García Bringas; Asier Perallos Ruiz; Antonio D. Masegosa Arredondo; Álvaro Herrero; Héctor Quintián; Emilio Corchado Pages: 1 - 3 Abstract: Publication date: November 2017 Source:Journal of Applied Logic, Volume 24, Part A Author(s): Pablo García Bringas, Asier Perallos Ruiz, Antonio D. Masegosa Arredondo, Álvaro Herrero, Héctor Quintián, Emilio Corchado
Authors:C. Puente; A. Sobrino; J.A. Olivas; E. Garrido Pages: 3 - 14 Abstract: Publication date: November 2017 Source:Journal of Applied Logic, Volume 24, Part B Author(s): C. Puente, A. Sobrino, J.A. Olivas, E. Garrido The objective of this work is to propose a complete system able to extract causal sentences from a set of text documents, select the causal sentences contained, create a causal graph in base to a given concept using as source these causal sentences, and finally produce a text summary gathering all the information connected by means of this causal graph. This procedure has three main steps. The first one is focused in the extraction, filtering and selection of those causal sentences that could have relevant information for the system. The second one is focused on the composition of a suitable causal graph, removing redundant information and solving ambiguity problems. The third step is a procedure able to read the causal graph to compose a suitable answer to a proposed causal question by summarizing the information contained in it.
Authors:Ruben Lostado-Lorza; Ruben Escribano-Garcia; Roberto Fernandez-Martinez; Marcos Illera-cueva; Bryan J. Mac Donald Pages: 4 - 14 Abstract: Publication date: November 2017 Source:Journal of Applied Logic, Volume 24, Part A Author(s): Ruben Lostado-Lorza, Ruben Escribano-Garcia, Roberto Fernandez-Martinez, Marcos Illera-cueva, Bryan J. Mac Donald Double-row tapered roller bearings (TRBs) are mechanical devices designed to support a combination of preload, radial load, axial load and torque. They are widely used in vehicles for high load and moderate rotation speeds. This combination of loads produces high contact stresses on the bearing raceways that are difficult to calculate, and can cause undesirable defects like fatigue spalling and pitting. In recent decades, the Finite Element Method (FEM) has been used to obtain the distribution of the contact stresses on each of the raceways, although this method has the disadvantage of a high computational cost. The myriad of possible combinations of input loads on the TRB (preload, radial load, axial load and torque) makes it much harder to calculate the distribution of these contact stresses. This paper proposes a methodology that combines the FEM and data mining techniques to determine the maximum load capacity in TRBs. First, a three-dimensional finite element (FE) model was generated according to the real materials' properties, geometry and coefficients of friction of all parts that make up the double-row TRB. Subsequently, a Design of Experiment (DoE) was completed that considered a combination of the mentioned input loads, which were simulated in the FE model. Based on the contact stresses obtained from the FE simulations, a group of regression models – linear regression (LR), Gaussian processes (GP), artificial neural networks (ANN), support vector machines (SVM) and regression trees (RT) – were built to predict the contact stresses ratios that act on each of the row of rollers in the outer raceway of the TRB. Finally, the best combination of input loads was achieved by applying evolutionary optimization techniques based on genetic algorithms (GA) to the best regression models previously obtained. The maximum load capacity of the TRB was achieved when the radial load obtained was a maximum, while the stresses ratios of the two contacts in the outer raceway of the TRB were close to 25%.
Authors:Alaa Tharwat; Tarek Gaber; Aboul Ella Hassanien Pages: 15 - 31 Abstract: Publication date: November 2017 Source:Journal of Applied Logic, Volume 24, Part B Author(s): Alaa Tharwat, Tarek Gaber, Aboul Ella Hassanien The number of endangered species has been increased due to shifts in the agricultural production, climate change, and poor urban planning. This has led to investigating new methods to address the problem of plant species identification/classification. In this paper, a plant identification approach using 2D digital leaves images was proposed. The approach used two features extraction methods based on one-dimensional (1D) and two-dimensional (2D) and the Bagging classifier. For the 1D-based methods, Principal Component Analysis (PCA), Direct Linear Discriminant Analysis (DLDA), and PCA+LDA techniques were applied, while 2DPCA and 2DLDA algorithms were used for the 2D-based method. To classify the extracted features in both methods, the Bagging classifier, with the decision tree as a weak learner was used. The five variants, i.e. PCA, PCA+LDA, DLDA, 2DPCA, and 2DLDA, of the approach were tested using the Flavia public dataset which consists of 1907 colored leaves images. The accuracy of these variants was evaluated and the results showed that the 2DPCA and 2DLDA methods were much better than using the PCA, PCA+LDA, and DLDA. Furthermore, it was found that the 2DLDA method was the best one and the increase of the weak learners of the Bagging classifier yielded a better classification accuracy. Also, a comparison with the most related work showed that our approach achieved better accuracy under the same dataset and same experimental setup.
Authors:Raúl F. Roldán; Rosa Basagoiti; Leandro C. Coelho Pages: 15 - 24 Abstract: Publication date: November 2017 Source:Journal of Applied Logic, Volume 24, Part A Author(s): Raúl F. Roldán, Rosa Basagoiti, Leandro C. Coelho The integration of the different processes and players that compose the supply chain (SC) is essential to obtain a better coordination level. Inventory control and distribution management are the two processes that researchers have identified as the key to gain or lose in efficiency and effectiveness in the field of logistics, with a direct effect on the synchronization and overall performance of SCs. In practical situations demand is often not deterministic, and lead times are also variable, yielding a complex stochastic problem. In order to analyze the recent developments in the integration of these processes, this paper analyzes the state of the art of the information management in the SC, the relationship between inventory policies and available demand information, and the use of optimization methods to provide good solutions for the problem in single and multi depot versions.
Authors:Katarzyna Grzybowska; Gábor Kovács Pages: 25 - 38 Abstract: Publication date: November 2017 Source:Journal of Applied Logic, Volume 24, Part A Author(s): Katarzyna Grzybowska, Gábor Kovács The process description languages, which are used in business, may be useful in logistics processes. The planning, organisation, direction and the control of the logistics processes might be more efficient if these formal languages are applied. During the logistics processes, many problems might arise, which should have already been addressed in the planning phase. In our days, the symptomatic treatment is a common practice, but it does not provide predictability. The obvious solution would be process control, in order to handle the main sources of faults and to give a correct list of what needs to be done during the logistics process. The process description languages may be useful not only in standardisation, but they may also help to avoid losses. Simulation experiments, on the basis of built model, also allow for the elimination of problems, standardisation and the limitation of losses. The aim of the article is a discussion of selected coordination mechanisms in the supply chain, its modelling in the form of a reference, as well as a discussion of the simulation experiment with the use of the FlexSim tool.
Authors:S. Valero; E. del Val; J. Alemany; V. Botti Pages: 32 - 44 Abstract: Publication date: November 2017 Source:Journal of Applied Logic, Volume 24, Part B Author(s): S. Valero, E. del Val, J. Alemany, V. Botti Multi-agent system paradigm has been envisioned as an appropriate solution for challenges in the area of smart-environments. Specifically, MAS add new capabilities such as adaption, reorganization, learning, coordination, etc. These features allow to deal with open issues in the context of smart-homes such as multi-occupancy, activity tracking or profiling activities and behaviors from multiple residents. In this paper, we present Magentix2 as a suitable MAS platform for the development of dynamic smart environments. Specifically, the use of Magentix2 (http://gti-ia.upv.es/sma/tools/magentix2/index.php) facilitates the management of the multiple occupancy in smart living spaces. Normative virtual organizations provide the possibility of defining a set of norms and organizational roles that facilitate the regulation and control of the actions that can be carried out by internal and external agents depending on their profile. Moreover, Magentix2 provides a tracing service to keep track of activities carried out in the system. We illustrate the applicability and benefits of Magentix2 in a set of scenarios in the context of smart-homes.
Authors:Victor V. Kashirin; Anastasia A. Lantseva; Sergey V. Ivanov; Sergey V. Kovalchuk; Alexander V. Boukhanovsky Pages: 39 - 49 Abstract: Publication date: November 2017 Source:Journal of Applied Logic, Volume 24, Part A Author(s): Victor V. Kashirin, Anastasia A. Lantseva, Sergey V. Ivanov, Sergey V. Kovalchuk, Alexander V. Boukhanovsky Thorough studies of technological and biological systems have revealed that the inherent networking structures of those systems possess similar topological properties, like node degree distribution or small-world effect, regardless of the context to which those systems are related. Based on that knowledge, there have been numerous attempts to develop models that capture particular topological properties of observed complex networks, although little attention has been paid to developing models with specific functional properties. The present paper proposes a method for the simulation of networks' structures with functional characteristics of interest using a heuristic evolutionary approach and utilizing a Simulated Annealing algorithm. An experimental study is carried out with a US air transportation network and synthetic social networks with known properties.
Authors:D. Nasonov; A. Visheratin; N. Butakov; N. Shindyapina; M. Melnik; A. Boukhanovsky Pages: 50 - 61 Abstract: Publication date: November 2017 Source:Journal of Applied Logic, Volume 24, Part A Author(s): D. Nasonov, A. Visheratin, N. Butakov, N. Shindyapina, M. Melnik, A. Boukhanovsky The optimal workflow scheduling is one of the most important issues in heterogeneous distributed computational environments. Existing heuristic and evolutionary scheduling algorithms have their advantages and disadvantages. In this work we propose a hybrid algorithm based on heuristic methods and genetic algorithm (GA) that combines best characteristics of both approaches. We propose heuristic algorithm called Linewise Earliest Finish Time (LEFT) as an alternative for HEFT in initial population generation for GA. We also experimentally show efficiency of described hybrid schemas GAHEFT, GALEFT, GACH for traditional workflow scheduling as well as for variable workload in dynamically changing heterogeneous computational environment.
Authors:José R. Villar; Manuel Menéndez; Enrique de la Cal; Javier Sedano; Víctor M. González Pages: 54 - 61 Abstract: Publication date: November 2017 Source:Journal of Applied Logic, Volume 24, Part B Author(s): José R. Villar, Manuel Menéndez, Enrique de la Cal, Javier Sedano, Víctor M. González Human-activity recognition and seizure-detection techniques have gathered pace with the widespread availability of wearable devices. A study of the literature shows various studies for 3D accelerometer-based seizure detection that describe the selection of acceleration variables and controlled transformations, while discarding the remaining input variable contributions. The aim of this research is to evaluate feature extraction based on different techniques and with the advantage of an overview of all information on the problem. Three feature extraction techniques – namely, Locally Linear Embedding, Principal Component Analysis (PCA) and a Distance-Based PCA – are analyzed and their outcomes compared against K-Nearest Neighbor and Decision Trees. A realistic experimentation simulating epileptic mioclonic convulsions was performed. The PCA-based methods were found to produce solutions that managed the problem perfectly well, either learning specific models for each individual or learning generalized models.
Authors:Pablo Garcia-Aunon; Matilde Santos Peñas; Jesus Manuel de la Cruz García Pages: 62 - 75 Abstract: Publication date: November 2017 Source:Journal of Applied Logic, Volume 24, Part B Author(s): Pablo Garcia-Aunon, Matilde Santos Peñas, Jesus Manuel de la Cruz García In order to steer an Unmanned Aerial Vehicle (UAV) and make it follow a desired trajectory, a high level controller is needed. Depending on the control algorithm, one or more parameters have to be tuned, having their values high impact on the performance. In most of the works, these parameters are taken as constant. In this paper, we apply fuzzy logic to select the parameters of the control law and compare this approach with the tuning by constant parameters and with another adjusting method based on the kinematic analysis of the equations of the UAV. After many simulations of the quadrotor following randomly generated paths, we have proved that the fuzzy tuning law is not only a good and feasible solution, but also more general as it can be applied to any trajectory.
Authors:Pedro Luis Galdámez; William Raveane; Angélica González Arrieta Pages: 62 - 70 Abstract: Publication date: November 2017 Source:Journal of Applied Logic, Volume 24, Part A Author(s): Pedro Luis Galdámez, William Raveane, Angélica González Arrieta The process of precisely recognize people by ears has been getting major attention in recent years. It represents an important step in the biometric research, especially as a complement to face recognition systems which have difficult in real conditions. This is due to the great variation in shapes, variable lighting conditions, and the changing profile shape which is a planar representation of a complex object. An ear recognition system involving a convolutional neural networks (CNN) is proposed to identify a person given an input image. The proposed method matches the performance of other traditional approaches when analyzed against clean photographs. However, the F1 metric of the results shows improvements in specificity of the recognition. We also present a technique for improving the speed of a CNN applied to large input images through the optimization of the sliding window approach.
Authors:Luis Martí; Nayat Sanchez-Pi; José Manuel Molina López; Ana Cristina Bicharra Garcia Pages: 71 - 84 Abstract: Publication date: November 2017 Source:Journal of Applied Logic, Volume 24, Part A Author(s): Luis Martí, Nayat Sanchez-Pi, José Manuel Molina López, Ana Cristina Bicharra Garcia Anomaly detection has to do with finding patterns in data that do not conform to an expected behavior. It has recently attracted the attention of the research community because of its real-world application. The correct detection unusual events empower the decision maker with the capacity to act on the system in order to correctly avoid, correct, or react to the situations associated with them. Petroleum industry is one of such real-world application scenarios. In particular, heavy extraction machines for pumping and generation operations like turbomachines are intensively monitored by hundreds of sensors each that send measurements with a high frequency for damage prevention. For dealing with this and with the lack of labeled data, in this paper we describe a combination of a fast and high quality segmentation algorithm with a one-class support vector machine approach for efficient anomaly detection in turbomachines. As a result we perform empirical studies comparing our approach to another using Kalman filters in a real-life application related to oil platform turbomachinery anomaly detection.
Authors:Ángel Arroyo; Álvaro Herrero; Verónica Tricio; Emilio Corchado Pages: 76 - 89 Abstract: Publication date: November 2017 Source:Journal of Applied Logic, Volume 24, Part B Author(s): Ángel Arroyo, Álvaro Herrero, Verónica Tricio, Emilio Corchado A comprehensive analysis of clustering techniques is presented in this paper through their application to data on meteorological conditions. Six partitional and hierarchical clustering techniques (k-means, k-medoids, SOM k-means, Agglomerative Hierarchical Clustering, and Clustering based on Gaussian Mixture Models) with different distance criteria, together with some clustering evaluation measures (Calinski–Harabasz, Davies–Bouldin, Gap and Silhouette criterion clustering evaluation object), present various analyses of the main climatic zones in Spain. Real-life data sets, recorded by AEMET (Spanish Meteorological Agency) at four of its weather stations, are analyzed in order to characterize the actual weather conditions at each location. The clustering techniques process the data on some of the main daily meteorological variables collected at these stations over six years between 2004 and 2010.
Authors:Dragan Simić; Ilija Kovačević; Vasa Svirčević; Svetlana Simić Pages: 85 - 96 Abstract: Publication date: November 2017 Source:Journal of Applied Logic, Volume 24, Part A Author(s): Dragan Simić, Ilija Kovačević, Vasa Svirčević, Svetlana Simić Supplier assessment and selection mapping as an essential component of supply chain management are usually multi-criteria decision-making problems. Decision making is the thought process of selecting a logical choice from the available options. This is generally made under fuzzy environment. Fuzzy decision-making is a decision process using the sets whose boundaries are not sharply defined. The aim of this paper is to show how fuzzy set theory, fuzzy decision-making and hybrid solutions based on fuzzy can be used in the various models for supplier assessment and selection in a 50 year period.
Authors:Pavel Brandstetter; Martin Kuchar Pages: 97 - 108 Abstract: Publication date: November 2017 Source:Journal of Applied Logic, Volume 24, Part A Author(s): Pavel Brandstetter, Martin Kuchar High power of modern digital signal processors and their decreasing prices enable practical implementation of different speed estimators which are used in the sensorless control of AC drives. The paper describes application possibilities of artificial neural networks for the sensorless speed control of the A.C. induction motor drive. In the sensorless control structure of the A.C. drive, there is implemented the speed estimator which uses two different artificial neural networks for speed estimation. The first speed estimator uses a multilayer feedforward artificial neural network. Its properties are compared with the speed estimator using a radial basis function neural network. The sensorless A.C. drive was simulated in program Matlab-Simulink. The main goal of many simulations was finding suitable structure of the artificial neural network with required number of neuron units which will ensure good control characteristics and simultaneously will enable a practical implementation of the artificial neural network in the digital signal processor control system.
Authors:Amira Sayed A. Aziz; Sanaa EL-Ola Hanafi; Aboul Ella Hassanien Pages: 109 - 118 Abstract: Publication date: November 2017 Source:Journal of Applied Logic, Volume 24, Part A Author(s): Amira Sayed A. Aziz, Sanaa EL-Ola Hanafi, Aboul Ella Hassanien In a previous research, a multi-agent artificial immune system for network intrusion detection and classification was proposed and tested, where a multi-layer detection and classification process was executed on each agent, for each host in the network. In this paper, we show the experiments that were held to chose the appropriate classifiers by testing different classifiers and comparing them to increase the detection accuracy and obtain more information on the detected anomalies. It will be shown that no single classifier should be used for all types of attacks, due to different classification rates obtained. This is due to attacks representations in the train set and dependency between features used to detect them. It will also be shown that a basic and simple classifier such as Naive Bayes has better classification results in the case of low-represented attacks, and the basic decision trees such as Naive-Bayes Tree and Best-First Tree give very good results compared to well-known J48 (Weka implementation of C4.5) and Random Forest decision trees. Based on these experiments and their results, Naive Bayes and Best-First tree classifiers were selected to classify the anomaly-detected traffic. It was shown that in the detection phase, 90% of anomalies were detected, and in the classification phase, 88% of false positives were successfully labeled as normal traffic connections, and 79% of DoS and Probe attacks were labeled correctly, mostly by NB, NBTree, and BFTree classifiers.
Authors:Mar Lopez; Javier Carbo; Jose M. Molina; Juanita Pedraza Pages: 119 - 131 Abstract: Publication date: November 2017 Source:Journal of Applied Logic, Volume 24, Part A Author(s): Mar Lopez, Javier Carbo, Jose M. Molina, Juanita Pedraza In this paper we present an integral solution for law-compliance privacy-protection into trust models for agent systems. Several privacy issues are concerned into trust relationships. Specifically, we define which privacy rights must legally be guaranteed in trusting communities of agents. From them, we describe additional interaction protocols that are required to implement such guarantees. Next, we apply additional message exchanges into a specific application domain (the Agent Trust and Reputation testbed) using JADE agent platform. The decisions about how to apply these control mechanisms (about when to launch the corresponding JADE protocol) has been efficiently carried out by neural computing. It uses past behavior of agents to decide (classify) which agents are worthy to share privacy with, considering which number of past interactions we should take into account. Furthermore, we also enumerate the corresponding privacy violations that would have taken place if these control mechanisms (in form of interaction protocols) were ignored or misused. From the possible existence of privacy violations, a regulatory structure is required to address (prevent and fix) the corresponding harmful consequences. We use Islander (an electronic institution editor) to formally define the scenes where privacy violation may be produced, attached to the ways to repair it: the defeasible actions that could voluntarily reduce or eliminate the privacy damage, and the obligations that the electronic institution would impose as penalties.
Authors:Carlos Ansótegui; Maria Luisa Bonet; Jesús Giráldez-Cru; Jordi Levy Pages: 27 - 39 Abstract: Publication date: September 2017 Source:Journal of Applied Logic, Volume 23 Author(s): Carlos Ansótegui, Maria Luisa Bonet, Jesús Giráldez-Cru, Jordi Levy The success of portfolio approaches in SAT solving relies on the observation that different SAT solvers may dramatically change their performance depending on the class of SAT instances they are trying to solve. In these approaches, a set of features of the problem is used to build a prediction model, which classifies instances into classes, and computes the fastest algorithm to solve each of them. Therefore, the set of features used to build these classifiers plays a crucial role. Traditionally, portfolio SAT solvers include features about the structure of the problem and its hardness. Recently, there have been some attempts to better characterize the structure of industrial SAT instances. In this paper, we use some structure features of industrial SAT instances to build some classifiers of industrial SAT families of instances. Namely, they are the scale-free structure, the community structure and the self-similar structure. First, we measure the effectiveness of these classifiers by comparing them to other sets of SAT features commonly used in portfolio SAT solving approaches. Then, we evaluate the performance of this set of structure features when used in a real portfolio SAT solver. Finally, we analyze the relevance of these features on the analyzed classifiers.
Authors:Jordi Montserrat-Adell; Núria Agell; Mónica Sánchez; Francesc Prats; Francisco Javier Ruiz Pages: 40 - 50 Abstract: Publication date: September 2017 Source:Journal of Applied Logic, Volume 23 Author(s): Jordi Montserrat-Adell, Núria Agell, Mónica Sánchez, Francesc Prats, Francisco Javier Ruiz Hesitant linguistic term sets have been introduced to capture the human way of reasoning using linguistic expressions involving different levels of precision. In this paper, a lattice structure is provided to the set of hesitant fuzzy linguistic term sets by means of the operations intersection and connected union. In addition, in a group decision making framework, hesitant fuzzy linguistic descriptions are defined to manage situations in which decision makers are assessing different alternatives by means of hesitant fuzzy linguistic term sets. Based on the introduced lattice structure, two distances between hesitant fuzzy linguistic descriptions are defined. These metric structures allow distances between decision makers to be computed. A centroid of the decision making group is proposed for each distance to model group representatives in the considered group decision making framework.
Authors:Eva Armengol; Josep Puyol-Gruart Pages: 51 - 69 Abstract: Publication date: September 2017 Source:Journal of Applied Logic, Volume 23 Author(s): Eva Armengol, Josep Puyol-Gruart Most of reasoning for decision making in daily life is based on preferences. As other kinds of reasoning processes, there are many formalisms trying to capture preferences, however none of them is able to capture all the subtleties of the human reasoning. In this paper we analyze how to formalize the preferences expressed by humans and how to reason with them to produce rankings. Particularly, we show that qualitative preferences are best represented with a combination of reward logics and conditional logics. We propose a new algorithm based on ideas of similarity between objects commonly used in case-based reasoning. We see that the new approach produces rankings close to the ones expressed by users.
Authors:Ahti-Veikko Pietarinen; Francesco Bellucci Abstract: Publication date: Available online 5 December 2017 Source:Journal of Applied Logic Author(s): Ahti-Veikko Pietarinen, Francesco Bellucci This paper presents two major aspects of Frege's and Peirce's views on assertion and denial: first, their arguments for the notational choices concerning the representation of assertion and denial in Begriffsschrift (BS) and Existential Graphs (EGs), respectively; and second, those properties of BS and EGs which reflect their inventors' views on assertion and denial. We show that while Frege's notation has an ad hoc sign of assertion and an ad hoc sign of negation, Peirce has a sign of assertion which is also a sign of logical conjunction, and a sign of scope which is also a sign of negation.
Authors:Massimiliano Carrara; Daniele Chiffi; Ciro De Florio Abstract: Publication date: Available online 5 December 2017 Source:Journal of Applied Logic Author(s): Massimiliano Carrara, Daniele Chiffi, Ciro De Florio The aim of this paper is twofold: First, we present and develop a system of logic for pragmatics including the act of denial. Second, we analyse in our framework the so-called paradox of assertability. We show that it is possible to yield sentences that are not assertable. Moreover, under certain conditions, a symmetric result can be obtained: There is a specular paradox of deniability. However, this paradox is based on the problematic principle of classical denial equivalence.
Authors:Michael Gabbay Abstract: Publication date: Available online 2 December 2017 Source:Journal of Applied Logic Author(s): Michael Gabbay In this short paper I note that a key metatheorem does not hold for the bilateralist inferential framework: harmony does not entail consistency. I conclude that the requirement of harmony will not suffice for a bilateralist to maintain a proof theoretic account of classical logic. I conclude that a proof theoretic account of meaning based on the bilateralist framework has no natural way of distinguishing legitimate definitional inference rules from illegitimate ones (such as those for tonk). Finally, as an appendix to the main argument, I propose an alternative non-bilateral formal solution to the problem of providing a proof-theoretic account of classical logic.
Authors:Bjørn Jespersen; Massimiliano Carrara; Marie Duží Abstract: Publication date: Available online 2 December 2017 Source:Journal of Applied Logic Author(s): Bjørn Jespersen, Massimiliano Carrara, Marie Duží The standard rule of single privative modification replaces privative modifiers by Boolean negation. This rule is valid, for sure, but also simplistic. If an individual a instantiates the privatively modified property (MF) then it is true that a instantiates the property of not being an F, but the rule fails to express the fact that the properties (MF) and F have something in common. We replace Boolean negation by property negation, enabling us to operate on contrary rather than contradictory properties. To this end, we apply our theory of intensional essentialism, which operates on properties (intensions) rather than their extensions. We argue that each property F is necessarily associated with an essence, which is the set of the so-called requisites of F that jointly define F. Privation deprives F of some but not all of its requisites, replacing them by their contradictories. We show that properties formed from iterated privatives, such as being an imaginary fake banknote, give rise to a trifurcation of cases between returning to the original root property or to a property contrary to it or being semantically undecidable for want of further information. In order to determine which of the three forks the bearers of particular instances of multiply modified properties land upon we must examine the requisites, both of unmodified and modified properties. Requisites underpin our presuppositional theory of positive predication. Whereas privation is about being deprived of certain properties, the assignment of requisites to properties makes positive predication possible, which is the predication of properties the bearers must have because they have a certain property formed by means of privation.
Authors:R.A. Abstract: Publication date: November 2017 Source:Journal of Applied Logic, Volume 24, Part B Author(s): D. Álvarez, R.A. Fernández, L. Sánchez We present a new approach for off-line intelligent word recognition based on a fuzzy classification model. First, we segment a word into its single characters, and label each pixel as vertical or as horizontal so that we can group all the pixels into vertical or horizontal strokes. Then, we use dynamic zoning to obtain the locations of the connections between the vertical strokes – which are the main strokes – and the horizontal ones. These features let us construct the representative string of a character using a regular grammar and, subsequently, use a Deterministic Finite Automaton to check them out. To accomplish the recognition, we use a Fuzzy Lattice Reasoning classifier. The combination of the representative strings and the fuzzy classifier provides promising performance rates.
Authors:Torra Abstract: Publication date: September 2017 Source:Journal of Applied Logic, Volume 23 Author(s): Vicenç Torra Microaggregation has been proven to be an effective method for data protection in the areas of Privacy Preserving Data Mining (PPDM) and Statistical Disclosure Control (SDC). This method consists of applying a clustering method to the data set to be protected, and then replacing each of the data by the cluster representative. In this paper we propose a new method for microaggregation based on fuzzy clustering. This new approach has been defined with the main goal of being nondeterministic on the assignment of cluster centers to the original data, and at the same time being simple in its definition. Being nondeterministic permits us to overcome some of the attacks standard microaggregation suffers.
Authors:Sergio Mota Abstract: Publication date: Available online 14 March 2017 Source:Journal of Applied Logic Author(s): Sergio Mota This paper is devoted to three main aims: (I) to present the conceptual relations between recursion, on the one hand, and inductive definitions and mathematical induction, on the other; as well as among recursion and self-involvement. In order to receive the original and primary use of recursion in cognitive science, it is important to bear in mind the conceptual relations and distinctions between them. (II) To analyze the interpretation of recursion from two different approaches. The first one, mainly represented by Chomsky, emphasizes the origin of recursion in the formal sciences, and applies it to characterize the mechanical procedure which underlies the language faculty. On this view, recursion is a property of the mind/brain. The second one disregards this conception of recursion and redefines it in terms of either the processing of self-embedded structures (e.g. [20]) or the ability to represent multiple hierarchical levels using the same rule (e.g. [45]); or as follows: recursion refers to the ability to embed structures within structures of the same kind (e.g. [48]). (III) To discuss whether or not this change in the meaning of recursion is more suitable than the original one for empirical research.
Authors:Khaza Anuarul Hoque; Otmane Ait Mohamed; Yvon Savaria Abstract: Publication date: Available online 4 March 2017 Source:Journal of Applied Logic Author(s): Khaza Anuarul Hoque, Otmane Ait Mohamed, Yvon Savaria SRAM-based FPGAs are increasingly popular in the aerospace industry due to their field programmability and low cost. However, they suffer from cosmic radiation induced Single Event Upsets (SEUs). In safety-critical applications, the dependability of the design is a prime concern since failures may have catastrophic consequences. An early analysis of the relationship between dependability metrics, performability-area trade-off, and different mitigation techniques for such applications can reduce the design effort while increasing the design confidence. This paper introduces a novel methodology based on probabilistic model checking, for the analysis of the reliability, availability, safety and performance-area tradeoffs of safety-critical systems for early design decisions. Starting from the high-level description of a system, a Markov reward model is constructed from the Control Data Flow Graph (CDFG) and a component characterization library targeting FPGAs. The proposed model and exhaustive analysis capture all the failure states (based on the fault detection coverage) and repairs possible in the system. We present quantitative results based on an FIR filter circuit to illustrate the applicability of the proposed approach and to demonstrate that a wide range of useful dependability and performability properties can be analyzed using the proposed methodology. The modeling results show the relationship between different mitigation techniques and fault detection coverage, exposing their direct impact on the design for early decisions.
Authors:Xin Sun; Livio Robaldo Abstract: Publication date: Available online 4 March 2017 Source:Journal of Applied Logic Author(s): Xin Sun, Livio Robaldo Input/output logic is a formalism in deontic logic and normative reasoning. Unlike deontic logical frameworks based on possible-world semantics, input/output logic adopts norm-based semantics in the sense of [13], specifically operational semantics. It is well-known in theoretical computer science that complexity is an indispensable component of every logic. So far, previous literature in input/output systems focuses on proof theory and semantics, while neglects complexity. This paper adds the missing component by giving the complexity results of main decision problems in input/output logic. Our results show that input/output logic is coNP hard and in the 2nd level of the polynomial hierarchy.
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