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Nowadays, there has been a rapidly increasing number of scientific submissions in multiple research domains. A large number of journals have various acceptance rates, impact factors, and rankings in different publishers. It becomes time-consuming for many researchers to select the most suitable journal to submit their work with the highest acceptance rate. A paper submission recommendation system is more critical for the research community and publishers as it gives scientists another support to complete their submission conveniently. This paper investigates the submission recommendation system for two main research topics: computer science and applied mathematics. Unlike the previous works (Wang et al., 2018; Son et al., 2020) that extract TF–IDF and statistical features as well as utilize numerous machine learning algorithms (logistics regression and multiple perceptrons) for building the recommendation engine, we present an efficient paper submission recommendation algorithm by using different bidirectional transformer encoders and the Mixture of Transformer Encoders technique. We compare the performance between our methodology and other approaches by one dataset from Wang et al. (2018) with 14012 papers in computer science and another dataset collected by us with 223,782 articles in 178 Springer applied mathematics journals in terms of top K accuracy (K = 1 , 3 , 5 , 10). The experimental results show that our proposed method extensively outperforms other state-of-the-art techniques with a significant margin in all top K accuracy for both two datasets. We publish all datasets collected and our implementation codes for further references. 1 1 https://github.com/BinhMisfit/PSRMTE. • Bidirectional transformer encoders can improve the performance of the paper submission recommendation system. • The Mixture of Transformer Encoders framework shows the efficiency in the paper submission recommendation problem. • Proposed techniques can surpass other recent techniques on two datasets related. [ABSTRACT FROM AUTHOR]

The large number of scientific publications around the world is increasing at a rate of approximately 4%–5% per year. This fact has resulted in the need for tools that deal with relevant and high-quality publications. To address this necessity, search and reference management tools that include some recommendation algorithms have been developed. However, many of these solutions are proprietary tools and the full potential of recommender systems is rarely exploited. There are some solutions which provide recommendations for specific domains, by using ad-hoc resources. Furthermore, some other systems do not consider any personalization strategy to generate the recommendations. This paper presents ArZiGo , a web-based full prototype system for the search, management, and recommendation of scientific articles, which feeds on the Semantic Scholar Open Research Corpus, a corpus that is growing continually with more than 190M papers from all fields of science so far. ArZiGo combines different recommendation approaches within a hybrid system, in a configurable way, to recommend those papers that best suit the preferences of the users. A group of 30 human experts has participated in the evaluation of 500 recommendations in 10 research areas, 7 of which belong to the area of Computer Science and 3 to the area of Medicine, obtaining quite satisfactory results. Besides the appropriateness of the articles recommended, the execution time of the implemented algorithms has also been analyzed. • A web system for the search, management, and recommendation of scientific articles. • A hybrid and multidisciplinary scientific article recommendation system. • A modular and scalable recommendation system. • Use of the Semantic Scholar Open Research Corpus as a corpus of articles. [ABSTRACT FROM AUTHOR]

Since 2000, the field of machine scheduling—an integral part of computer science and operations research—has seen significant advancements. This paper explores the dynamic progression of machine scheduling, offering a detailed overview of its past advancements, current practices, and future directions. Anchoring the research in robust data analysis and statistical methodologies, the paper reveals the subtle yet impactful changes that have characterized the field in the last two decades. It examines the prominence of various scheduling problems, identifies leading research journals, and highlights international contributions and collaborations, thereby offering a thorough guide to the machine scheduling ecosystem. The study delves into specific problem characteristics and assesses performance criteria and solution methods to provide an in-depth view of the field's multifaceted nature. Ultimately, this paper captures the essence of machine scheduling's evolution and suggests new paths for exploration. The insights gained contribute significantly to academic discussions and equip practitioners with a comprehensive understanding of the dynamic landscape of machine scheduling. [ABSTRACT FROM AUTHOR]

In this paper, a novel numerical algorithm for efficient modeling of three-dimensional shape transformation governed by the modified Allen-Cahn (A-C) equation is developed, which has important significance for computer science and graphics technology. The new idea of the proposed method is as follows. Firstly, the operator splitting method is used to decompose the three-dimensional problem into a series of one-dimensional subproblems that can be solved in parallel in the same direction. Secondly, a temporal p-adaptive strategy, which is based on the extrapolation technique, is proposed to improve the convergence order in time and preserve the computational efficiency simultaneously. Finally, a parallel least distance modification technique is developed to force the discrete maximum bound principle. The proposed method achieves high precision and high efficiency at the same time. Numerical examples include the effectiveness of the p-adaptive method and the bound preserving least distance modification, and a series of complex three-dimensional shape transformation modelings. • The operator splitting method is used to solve 3D shape transformation PDE. • A temporal p-adaptive strategy is developed to improve computational efficiency. • A least-distance modification is developed to force the discrete maximum bound. [ABSTRACT FROM AUTHOR]

Influence maximization is an important research area in social network analysis where researchers are concerned with detecting influential nodes. The detection of influential nodes is of great interest in several disciplines including computer science, opinion propagation, political movements, or economics, where systems are often modeled as graphs. The Influence Maximization problem is proved NP-hard. This computational complexity is justified by two main factors. The first factor is about the important size of social networks. Modern social networks like TikTok and Facebook have reached an unprecedented number of users. Dynamic social networks, whose topology or/and informational content is able to evolve, represent the second factor. Maximizing influence in such networks remains a significant task. In this light, several methods have been proposed. Being motivated by this fact, we provide in this paper a detailed survey of influence maximization approaches. Our main concern is to provide a taxonomy of existing models in both static and dynamic networks. In addition, we provide a comparison of the state-of-the-art approaches according to a clear categorization. New trends for detecting influential nodes are also discussed. We provide then some challenges as well as future directions. • Taxonomy of existing IM models in both static and dynamic networks is provided. • A comparison of existing approaches according to a clear categorization is presented. • New trends for detecting influential nodes are also discussed. [ABSTRACT FROM AUTHOR]

In this paper, we discuss methods to assess the interestingness of a query in an environment of data cubes. We assume a hierarchical multidimensional database, storing data cubes and level hierarchies. We start with a comprehensive review of related work in the fields of human behavior studies and computer science. We define the interestingness of a query as a vector of scores along different aspects, like novelty, relevance, surprise and peculiarity and complement this definition with a taxonomy of the information that can be used to assess each of these aspects of interestingness. We provide both syntactic (result-independent) and extensional (result-dependent) checks, measures and algorithms for assessing the different aspects of interestingness in a quantitative fashion. We also report our findings from a user study that we conducted, analyzing the significance of each aspect, its evolution over time and the behavior of the study's participants. [ABSTRACT FROM AUTHOR]

The problem of reducing ϵ -NN to (c , r) -NN is very important in theoretical computer science area and has attracted many research efforts. In this paper a new algorithm for such problem is proposed, which achieves O (log ⁡ n) query time. Comparing with the former algorithms for the same problem, this query time is the lowest, which is the main contribution of this paper. The low query time complexity is achieved by raising the preprocessing time and space complexity. How to reduce the cost added into the two complexities is also discussed in this paper. [ABSTRACT FROM AUTHOR]

In natural language processing (NLP), transformer based models have surpassed recurrent neural networks (RNN) as state of the art, being introduced specifically to address the limitations of RNNs originating from its sequential nature. As a similar sequence modeling problem, transformer methods can be readily adapted for deep learning time series prediction. This paper proposes a sparse transformer based approach for electricity load prediction. The layers of a transformer addresses the shortcomings of RNNs and CNNs by applying the attention mechanism on the entire time series, allowing any data point in the input to influence any location in the output of the layer. This allows transformers to incorporate information from the entire sequence in a single layer. Attention computations can also be parallelized. Thus, transformers can achieve faster speeds, or trade this speed for more layers and increased complexity. In experiments on public datasets, the sparse transformer attained comparable accuracy to an RNN-based SOTA method (Liu et al., 2022) while being up to 5× faster during inference. Moreover, the proposed model is general enough to forecast the load from individual households to city levels as shown in the extensive experiments conducted. [ABSTRACT FROM AUTHOR]

Event sequence data is increasingly available. Many business operations are supported by information systems that record transactions, events, state changes, message exchanges, and similar elements. This observation also applies to various industries, including production, logistics, healthcare, financial services, and education. The variety of application areas explains that techniques for event sequence data analysis have been developed rather independently in different fields of computer science. Most prominent are contributions from information visualization and from process mining. So far, the contributions from these two fields have neither been compared nor have they been mapped to an integrated framework. Such intransparency is problematic since it bears the risk of opportunities of integration are missed and concepts established in one field are independently reinvented in the other one. In this paper, we develop the Event Sequence Visualization framework (ESeVis) that gives due credit to the traditions of both fields. Our mapping study provides an integrated perspective on both fields and identifies potential for synergies for future research. • We propose the ESeVis Framework to categorize visualizations of event sequence data. • We review the literature of event sequence data visualizations. • Instance representations of event sequences are mostly from information visualization. • Process mining focuses on generating formal models. • Potential for synergy of process mining and information visualization. [ABSTRACT FROM AUTHOR]

Highlights • And-cross transitions are a useful abstraction that can make some constructs easier to specify for the modeler. • They can be transformed to and from alternative modeling solutions that require a greater number of transitions. • With fewer transitions, the time taken and memory required to certify a model to be deterministic using formal methods can be much reduced compared to other approaches. This is related to the time and memory required to compute the set of pairs of potentially conflicting transitions. Abstract In this paper, we present an approach to formally encode state machines expressed in Umple for symbolic verification. We illustrate this with a real-world modeling example that encodes and analyzes and-cross transitions. This paper discusses a formal description of our approach to represent state machine systems under analysis (SSUAs); a systematic approach to certifying that SSUAs are deterministic; and an evaluation of performance (memory usage and execution time) on the case study. Method We describe a formalization of state machines in Umple that enables their translation to model checking tools and also to code that is consistent with this. We present three alternative modeling solutions for a sample problem and a solution based on the use of and-cross transitions. State machine models corresponding to these solutions are represented in Umple, a model-oriented programming language. These are automatically transformed to SMV, the input language of the nuXmv (or NuSMV) model checker. By cleanly separating concerns, we systematically integrate components of hierarchical state systems as opposed to the traditional flattening approach, yet manage the complexity introduced by concurrency and and-crossing. We then compose and verify a set of requirements (e.g., correctness, safety, liveliness, etc.) on the resulting systems of all the modeling approaches to empirically compare the different modeling alternatives with the use of and-cross transitions. Results We can encode and formally analyse complex state machines with and-cross transition(s). We observed a large reduction in the number of required transitions for encoding the SSUA, as opposed to the alternative approaches. We asserted that solutions derived from the approaches are identical behavior-wise even though each approach models the SSUA differently. Each of the approaches yielded the same result for potentially conflicting pairs which is a false positive (i.e., the SSUAs are deterministic). We observe that each approach maintains the same global state-space irrespective of the variations in their number of transitions. Furthermore, we observe that it is untrue that a more abstract method applied to an SSUA outperforms its less abstract counterpart whenever parameters (such as execution time, memory usage and the number of Binary Decision Diagrams - BDDs) are the factors under consideration. Contributions A systematic approach to encode state machines with and-cross transitions (including unusual transitions). An enhanced but fully automated approach to discovering nondeterminism in state machines even in the presence of unbounded domains and multiple and-cross transitions within the same enclosing orthogonal state. An empirical study of the impact of abstraction on some performance parameters. We also present an extended formalization of Umple state machines. [ABSTRACT FROM AUTHOR]

Abstract Many metrics have been proposed to measure coupling—the degree of association between modules in a system. They have often been described in different ways, hindering comparison and research. Their definitions are often incomplete regarding language features in some languages, meaning that different tool developers may implement the same metric differently. This complicates comparing results from studies that use different tools. This paper therefore aims to define coupling metrics consistently and unambiguously. The paper describes a model of coupling that uses the reification of the concept of dependency as its fundamental unit. Based on this model, it defines a framework for defining coupling metrics. It shows how to define several well-known coupling metrics in the framework, and how defining different metrics based on the same model facilitates direct comparisons. It discusses how the framework resolves issues due to incomplete metric definitions, such as different language features. This formal framework is sufficiently simple that it can be implemented in such a way as to provide multiple metrics. [ABSTRACT FROM AUTHOR]

This paper provides a review of the analysis and modeling of human spatial planning, perception, and learning based on the dynamics of agent-environment interactions. The approach stems from an analysis and modeling framework that was previously conceived using interaction patterns emerging from system-wide interactions as the basic unit of analysis. The paper first discusses the rationals for using patterns in agent-environment interactions as units of organization of behavior, and as functional units of the modeling framework. These concepts are then illustrated through two applications using experimental data from a first-person flight simulator that implements agile obstacle navigation tasks. The first application focuses on the analysis of the formation and evolution of interaction patterns over successive trials, and the use of these patterns as basic elements of the task environment representation, enabling the evaluation of the learning process and assessment of the operator performance. The second application focuses on the analysis of interaction patterns as functional units supporting the modeling of the underlying perceptual guidance and control mechanisms. These examples demonstrate the relevance of dynamics in agent-environment interactions for studying a wide range of functions across the human control hierarchy. [ABSTRACT FROM AUTHOR]

This paper is about two generalizations of the mistake bound model to online multiclass classification. In the standard model , the learner receives the correct classification at the end of each round, and in the bandit model , the learner only finds out whether its prediction was correct or not. For a set F of multiclass classifiers, let opt std (F) and opt bandit (F) be the optimal bounds for learning F according to these two models. We show that an opt bandit (F) ≤ (1 + o (1)) (| Y | ln ⁡ | Y |) opt std (F) bound is the best possible up to the leading constant, closing a Θ (log ⁡ | Y |) factor gap. [ABSTRACT FROM AUTHOR]

Pattern languages have been an object of study in various subfields of computer science for decades. This paper introduces and studies a decision problem on patterns called the finite distinguishability problem: given a pattern π , are there finite sets T + and T − of strings such that the only pattern language containing all strings in T + and none of the strings in T − is the language generated by π ? This problem is related to the complexity of teacher-directed learning, as studied in computational learning theory, as well as to the long-standing open question whether the equivalence of two patterns is decidable. We show that finite distinguishability is decidable if the underlying alphabet is of size other than 2 or 3, and provide a number of related results, such as (i) partial solutions for alphabet sizes 2 and 3, and (ii) decidability proofs for variants of the problem for special subclasses of patterns, namely, regular, 1-variable, and non-cross patterns. For the same subclasses, we further determine the values of two complexity parameters in teacher-directed learning, namely the teaching dimension and the recursive teaching dimension. [ABSTRACT FROM AUTHOR]

Combinatorial problems are a fundamental research subject of theoretical computer science, and for a general graph many combinatorial problems are NP-hard and even #P-complete. Thus, it is interesting to seek or design special graphs for which these difficult combinatorial problems can be exactly solved. In this paper, we study some combinatorial problems for the Farey graphs, which are translated from Farey sequences and have received considerable attention from the scientific community. We determine exactly the domination number, the independence number, and the matching number. Moreover, we derive exact or recursive solutions to the number of minimum dominating sets, the number of dominating sets, the number of maximum independent sets, the number of independent sets, the number of maximum matchings, as well as the number of matchings. Finally, we obtain explicit expressions for the number of acyclic orientations and the number of root-connected acyclic orientations. Since the considered combinatorial problems have found wide applications in diverse fields, such as network science and graph data miming, this work is helpful for deepening our understanding of the applications for these combinatorial problems. [ABSTRACT FROM AUTHOR]

• A novel SMO inspired by mimicking behavior to solve optimization problems is presented. • SMO includes a mimic operator to simulate search in the response space. • SMO does not require control operator respect to other Meta heuristic methods. • SMO solve optimization problems with minimum population size. • SMO is compared with 14 well-known and state of the art optimization algorithms. Increase in complexity of real world problems has provided an area to explore efficient methods to solve computer science problems. Meta-heuristic methods based on evolutionary computations and swarm intelligence are instances of techniques inspired by nature. This paper presents a novel social mimic optimization (SMO) algorithm inspired by mimicking behavior to solve optimization problems. The proposed algorithm is evaluated using 23 test functions. Obtained results are compared with 14 known optimization algorithms including Whale optimization algorithm (WOA), Grasshopper optimization algorithm (GOA), Particle Swarm Optimization (PSO), Stochastic fractal search (SFS), Grey Wolf Optimizer (GWO), Optics Inspired Optimization (OIO), League Championship Algorithm (LCA), Wind Driven Optimization (WDO), Harmony search (HS), Firefly Algorithm (FA), Artificial Bee Colony (ABC), Biogeography Based Optimization (BBO), Bat Algorithm (BA), and Teaching Learning Based Optimization (TLBO). Obtained results indicate higher capability of the SMO algorithm in solving high-dimensional decision variables. Furthermore, SMO is used to solve two classic engineering design problems. Three important features of SMO are simple implementation, solving optimization problems with minimum population size and not requiring control parameters. Results of various evaluations show superiority of the proposed method in finding the optimal solution with minimum function evaluations. This superiority is achieved based on reducing number of initial population. The proposed method can be applied to applications like automatic evolution of robotics, automatic control of machines and innovation of machines in finding better solutions with less cost. [ABSTRACT FROM AUTHOR]

• The minimum cycle cover problem. • A simplified approach of analysis. • An O (n 2) time 24/5-approximation algorithm. • A new O (n 3) time 14/3-approximation algorithm. • An improved O (n 5) time 32/7-approximation algorithm. Given an undirected weighted graph G = (V , E) with nonnegative weight function obeying the triangle inequality, a set { C 1 , C 2 , ... , C k } of cycles is called a cycle cover if V ⊆ ⋃ i = 1 k V (C i) and its cost is given by the maximum weight of the cycles. The Minimum Cycle Cover Problem aims to find a cycle cover of cost at most λ with the minimum number of cycles. An O (n 2) 24/5-approximation algorithm and an O (n 5) 14/3-approximation algorithm are given by Yu and Liu (Improved approximation algorithms for some min-max cycle cover problems. Theoretical Computer Science 654 (2016) 45–58). However, the original proofs for approximation ratios are incomplete. In this paper we first present a corrected simplified analysis on the 24/5-approximation algorithm. Based on the simplified approach of analysis and some new observations, we present a new 14/3-approximation algorithm that runs in O (n 3) and give an improved 32/7-approximation algorithm that runs in O (n 5). [ABSTRACT FROM AUTHOR]

Boolean nested canalizing functions (NCF) have important applications in molecular regulatory networks, engineering and computer science. In the literature, there are two sensitivities to measure the complexity of a Boolean function. One is average sensitivity, the other one is maximal sensitivity. We follow the tradition and omit the word "maximal". In other words, in this paper, sensitivity is always maximal sensitivity. Using the past work of the authors and their coauthors on a characterization of NCF, we obtain the formula of the sensitivity of any NCF. We find that the sensitivity of any NCF is between ⌈ n + 2 2 ⌉ and n. Both lower and upper bounds are tight. We prove that the block sensitivity, hence the l -block sensitivity, is the same as the sensitivity for NCF. It is well known that monotone Boolean functions (MBF) also have this property. We characterize all functions which are both monotone and nested canalizing (MNCF). The closed formula of the cardinality of the set of MNCFs is also provided. • The closed formula of the maximal sensitivity of Boolean nested canalizing functions is obtained. • Both the lower and upper tight bounds of the maximal sensitivity of Boolean nested canalizing functions are computed. • The maximal sensitivity and the block sensitivity of nested canalizing functions are equal. • The algebraic normal forms of monotone nested canalizing functions are provided. • The closed formula of the number of monotone nested canalizing functions is obtained. [ABSTRACT FROM AUTHOR]

• An approximately bisimilar symbolic model is constructed for a safe changeover process. • An automatic controller is designed for safe changeover process for the first time. • The synthesis of the proposed controller in a finite-state space is very fast and flexible. • The error bounds of the proposed controller are adjustable as design parameters. • The effectiveness of the symbolic controller is investigated via numerical simulation. Many process control problems with complex qualitative specifications cannot be addressed via conventional control design methods. Examples of such specifications include logic specifications expressed in the design of start-up, shut-down, changeover, and emergency shutdown operating procedures. In recent years, it has been shown in the control systems and computer science communities that symbolic models provide convenient and powerful mechanisms to synthesize controllers enforcing such qualitative specifications. The use of symbolic models reduces the synthesis of the controllers to a fixed-point computation problem over a finite-state abstract system. In this paper, after explaining the notion of approximate bisimulation for incrementally globally asymptotically stable (δ -GAS) nonlinear control systems, the construction of approximately bisimilar symbolic models for such systems is presented. Then synthesis of time-optimal symbolic controller for this class of systems is performed based on results from the computer science literature. As a benchmark chemical process control problem, an approximately bisimilar symbolic model is constructed for a safe changeover process. Then a symbolic controller is designed and it is refined to a controller to be applied to the original process. Simulation results show the effectiveness of the symbolic controller. Although the construction of the symbolic model may be complex, the synthesis of the controller in a finite-state space is fast and most importantly the error bounds are adjustable as design parameters. [ABSTRACT FROM AUTHOR]

Conceptual modeling is integral to computer science research and is widely adopted in industrial practices, e.g., business process and enterprise architecture management. Providing adequate and usable modeling tools is necessary to adopt modeling languages efficiently. Meta-modeling platforms provide a rich and mature set of functionalities for realizing state-of-the-art modeling tools. These tools, albeit their stability and rich set of features, often lack a modern look and feel considering (i) how they visualize the models, and (i i) how modelers interact with the models. Current web technologies enable much richer, advanced opportunities for visualizing and interacting with conceptual models. However, a structured and comprehensive overview of possible information visualization and interaction techniques linked to conceptual models and modeling tools must be established. This paper aims to fill this gap by presenting an extended taxonomy of advanced information visualization and interaction in conceptual modeling. We present a generic taxonomy that is afterward contextualized within the specific domain of conceptual modeling. The taxonomy serves orientation in the vast developing field of information visualization and interaction and hopefully sparks innovation if future modeling tool development. • We propose a taxonomy for advanced information visualization and interaction in conceptual modeling. • We show the current design space of visualization and interaction in conceptual modeling. • We exemplify the taxonomy dimensions with many illustrative examples. • We discuss opportunities and future research directions. [ABSTRACT FROM AUTHOR]

Many organizations are stuck in the cloudify or not to cloudify limbo, mainly due to concerns related to the security of enterprise sensitive data. Removing this barrier is a key pre-condition to fully unleash the tremendous potential of cloud computing. In this paper, we provide a comprehensive analysis of the main threats that hamper cloud computing adoption on a wide scale, and a right to the point review of the solutions that are currently being provided by the major vendors. The paper also presents the (near) future directions of cloud security research, by taking a snapshot of the main research trends and most accredited approaches. The study is done on a best of breed selection of proprietary and Open Source cloud offerings. The paper is thus a useful navigation tool, that can be used by the IT personnel to gain more insight into the security risks related to the use of cloud computing, as well as to quickly weigh the pros and cons of state of the art solutions. [ABSTRACT FROM AUTHOR]

Home Automation Networks provide a promising opportunity in designing smart home systems and applications. In this context, Machine-to-Machine (M2M) networks are emerging as an efficient means to provide automated communication among distributed ubiquitous devices on in a standardized manner, but none have been adopted universally. In an effort to present the technologies used in the M2M and home integration environment, this paper presents the home area network elements and definitions, and reviews the standards, architectures and initiatives created to enable M2M communication and integration in several different environments, especially at the smart home domain. This paper points out differences between them and identifies trends for the future. [ABSTRACT FROM AUTHOR]

Modern businesses benefit significantly from advances in computer vision technology, one of the important sectors of artificially intelligent and computer science research. Advanced computer vision issues like image processing, object recognition, and biometric authentication can benefit from using deep learning methods. As smart devices and facilities advance rapidly, current networks such as 4 G and the forthcoming 5 G networks may not adapt to the rapidly increasing demand. Classification of images, object classification, and facial recognition software are some of the most difficult computer vision problems that can be solved using deep learning methods. As a new paradigm for 6Core network design and analysis, artificial intelligence (AI) has recently been used. Therefore, in this paper, the 6 G wireless network is used along with Deep Learning to solve the above challenges by introducing a new methodology named Optimizing Computer Vision with AI-enabled technology (OCV-AI). This research uses deep learning – efficiency algorithms (DL-EA) for computer vision to address the issues mentioned and improve the system's outcome. Therefore, deep learning 6 G proposed frameworks (Dl-6 G) are suggested in this paper to recognize pattern recognition and intelligent management systems and provide driven methodology planned to be provisioned automatically. For Advanced analytics wise, 6 G networks can summarize the significant areas for future research and potential solutions, including image enhancement, machine vision, and access control. [ABSTRACT FROM AUTHOR]

Abstract Object-oriented programming is widely used in both the industry and the education areas. The most-common model of object-oriented programming is the class-based one. However, popular languages not implementing this model are gaining traction as time goes by. This alternative model is the prototype-based one, with one key characteristic: there are no classes. In this paper, a visual tool is proposed as a vehicle for learning the prototype-based object-oriented programming, present, for instance, in Self, Lua, or JavaScript. This software has been in use for three years in a subject of the Computer Science Engineering degree, at the University of Vigo. Highlights • Pooi is an interactive environment which updates with each instruction. • The system sports an diagram viewer, an object inspector, and a REPL. • The software was designed for undergraduate students of computer science engineering. • This tool has been used successfully in lecturing object-oriented programming. • Pooi is free, offering also the sources, and a set of tutorials and examples: http://jbgarcia.webs.uvigo.es/prys/pooi/. [ABSTRACT FROM AUTHOR]

Abstract In this paper we study the approximation ratio of the solutions achieved after an ϵ -approximate one-round walk in non-atomic congestion games. Prior to this work, the solution concept of one-round walks had been studied for atomic congestion games with linear latency functions only (Christodoulou et al. [1] , Bilò et al. [2]). We give an explicit formula to determine the approximation ratio for non-atomic congestion games having general latency functions. In particular, we focus on polynomial latency functions, and, we prove that the approximation ratio is exactly ((1 + ϵ) (p + 1)) p + 1 for every polynomial of degree p. Then, we show that, by resorting to static (resp. dynamic) resource taxation, the approximation ratio can be lowered to (1 + ϵ) p + 1 (p + 1) p (resp. (1 + ϵ) p + 1 (p + 1) !). [ABSTRACT FROM AUTHOR]

Abstract Since the 80s, model checking (MC) has been applied to the automatic verification of hardware/software systems. Point-based temporal logics, such as LTL , CTL , CTL ⁎ , and the like, are commonly used in MC as the specification language; however, there are some inherently interval-based properties of computations, e.g., temporal aggregations and durations, that cannot be properly dealt with by these logics, as they model a state-by-state evolution of systems. Recently, an MC framework for the verification of interval-based properties of computations, based on Halpern and Shoham's interval temporal logic (HS , for short) and its fragments, has been proposed and systematically investigated. In this paper, we focus on the boundaries that separate tractable and intractable HS fragments in MC. We first prove that MC for the logic BE of Allen's relations started-by and finished-by is provably intractable, being Expspace -hard. Such a lower bound immediately propagates to full HS. Then, in contrast, we show that other noteworthy HS fragments, i.e., the logic A A ‾ B B ‾ (resp., A A ‾ E E ‾) of Allen's relations meets , met-by , starts (resp., finishes), and started-by (resp., finished-by), are well-behaved, and turn out to have the same complexity as LTL (Pspace -complete). Halfway are the fragments A A ‾ B B ‾ E ‾ and A A ‾ E B ‾ E ‾ , whose Expspace membership and Pspace hardness are already known. Here, we give an original proof of Expspace membership, that substantially simplifies the complexity of the constructions previously used for such a result. Contraction techniques—suitably tailored to each HS fragment—are at the heart of our results, enabling us to prove a pair of remarkable small-model properties. [ABSTRACT FROM AUTHOR]

Abstract This paper studies the well-known problem of gathering multiple mobile agents moving in a graph, but unlike previous results, we consider the problem in the presence of an adversarial mobile entity which we call the malicious agent. The malicious entity can occupy any empty node and prevent honest mobile agents from entering this node. This new adversarial model is interesting as it models transient mobile faults that can appear anywhere in a network. Moreover, our model lies between the less powerful delay-fault model , where the adversary can block an agent for only a finite time, and the more powerful but static fault model of black holes that can even destroy the agents. We study the problem for ring networks and we provide a complete characterization of the solvability of gathering, depending on the size n of the ring and the number of agents k. We consider both oriented or unoriented rings with either synchronous or asynchronous agents. We prove that in an unoriented ring network with asynchronous agents the problem is not solvable when k is even, while for synchronous agents the problem is unsolvable when both n is odd and k is even. We then present algorithms that solve gathering for all the remaining cases, thus completely solving the problem. Finally, we provide a proof-of-concept implementation of the synchronous algorithms using programmable Lego Mindstorms EV3 robots. [ABSTRACT FROM AUTHOR]

Abstract A locally connected spanning tree (LCST) T of a graph G is a spanning tree of G such that, for each node, its neighborhood in T induces a connected subgraph in G. The problem of determining whether a graph contains an LCST or not has been proved to be NP-complete, even if the graph is planar or chordal. The main result of this paper is a simple linear time algorithm that, given a maximal planar chordal graph, determines in linear time whether it contains an LCST or not, and produces one if it exists. We give an analogous result for the case when the input graph is a maximal outerplanar graph. [ABSTRACT FROM AUTHOR]

• Presenting a method for automatic generation of program code for process models. • Ontology captures model information and equations for the modelled domain. • Model generated in a graph-based model environment reflecting the ontology information. • Equations translated to output format using language templates for the mathematical operators. The implementation of coded mathematical process models is regarded as a cumbersome and challenging task, reasons being that the modeller needs to have expertise both in modelling and computer science. Our ProcessModellerSuite implements a staged approach to modelling starting with the formulation of a context-dependent ontology defining a structure against which the mathematical representation of the principal model components is defined. Process models are then generated by interactively constructing a graph of communicating principle components, which enables the generation of arbitrary complex process models and intermediate storage of customised unit models. This storage of unit models forms the equivalent of the traditional unit-operations libraries, by allowing for insertion of the unit models into other graphs. A task builder combines the information from the graph with the used model components to automatically generate executable program code of the process model, which will be the topic of this paper. [ABSTRACT FROM AUTHOR]

Highlights • An architectural assumption management process with guidelines is developed. • Two case studies were conducted to validate the process. • The process can help to make architectural assumptions explicit. • The process can help to identify and reduce invalid architectural assumptions. Abstract Context Architectural assumption management is critical to the success of software development projects. In this paper, we propose an Architectural Assumption Management (AAM) process, comprised of four AAM activities: Architectural Assumption Making, Description, Evaluation, and Maintenance. Objective Evaluating the AAM process in architectural assumption management, regarding the ease of understanding and the effort of conducting the AAM process, as well as the effectiveness of using the AAM process to make architectural assumptions explicit and to identify and reduce invalid architectural assumptions. Method An explanatory study with 88 first-year master students in software engineering, and an exploratory study with five practitioners from five companies. Results (1) the ease of understanding the AAM process is moderate for first-year master students but easy for practitioners; (2) the effort of conducting the AAM process is moderate for first-year master students; (3) Making and Evaluation took the students more time than Description and Maintenance; (4) the practitioners considered Evaluation as the most time consuming activity; (5) the AAM process can help to make architectural assumptions explicit and to identify and reduce invalid architectural assumptions in projects. The majority of the students and practitioners agreed that Architectural Assumption Evaluation is the most helpful activity for all these three aspects. For other activities, there are different opinions about their helpfulness; and (6) there are various factors identified that can impact the aforementioned results. Being aware of and properly adjusting these factors can facilitate the application of the AAM process in projects. Conclusions The AAM process aims at systematically managing architectural assumptions in software development. The results of the case studies provide preliminary empirical evidence for the evaluation of the AAM process. [ABSTRACT FROM AUTHOR]

Abstract In environmental psychology research, the most commonly used methods are phenomenological interviews and psychometric scales. Recently, with the development of wearable bio-sensing devices, a new approach based on bio-sensing data is becoming possible. In this study, we examined the feasibility of using wearable biosensors to document affective experience during in-situ walk. An eight-channelled Procomp multi-bio-sensing devices (EKG, EEG, skin conductance, temperature, facial EMG, respiration) were used, in addition with a GPS tracker, to measure the in situ physiological affective responses to environmental stimuli. This pilot experiment revealed consistent results between bio-sensing measures and two traditional methods, i.e. phenomenological interviews and psychological Likert scale rating, which indicated that mobile bio-sensing could be a promising method in measuring in-situ affective responses to environmental stimuli as well as diagnosing potential environmental stressor. This new bio-sensory method, as exemplified in this paper, could help identifying negative stressful stimuli and providing evidence-based diagnosis to support design strategies. [ABSTRACT FROM AUTHOR]

Abstract The third Generation Partnership Project (3GPP) has successfully launched 4G data on mobile communication by utilizing the Long Term Evolution (LTE). The multimedia processing such as video calling/conferencing, video transmission/reception in mobile communication are in need of multiple user support, speed, high data transmission rate, low data loss rate and high throughput. In this paper an enhanced scheduling algorithm known as, EM-LWDF (Modified Largest Weighted Delay First) is proposed in combination of time/frequency scheduling for LTE. The proposed scheduling algorithm is evaluated under various simulation scenarios and compared with conventional algorithm such as PF, M-LWDF, EXP/PF, and proposed +LWDF. The evaluation is made in terms of system throughput, fairness index and Packet Loss Rate (PLR) and the evaluation results shows that the proposed scheduling algorithm shows remarkable performance improvement. [ABSTRACT FROM AUTHOR]

Compositional Game Theory is a new, recently introduced model of economic games based upon the computer science idea of compositionality. In it, complex and irregular games can be built up from smaller and simpler games, and the equilibria of these complex games can be defined recursively from the equilibria of their simpler subgames. This paper extends the model by providing a final coalgebra semantics for infinite games. In the course of this, we introduce a new operator on games to model the economic concept of subgame perfection. [ABSTRACT FROM AUTHOR]

The paper reports on the 40 years of development of Computer Graphics and, more recently, Visual computing (VC) at the Technische Universität Darmstadt in Germany, from its beginning in 1975 to the leading “Computer Graphics and Visual Computing Hub” in Europe as of 2014. This development is described along three axes. First, the institutional development and its rational to establish Computer Graphics as a discipline of Computer Science and as an enabling technology for developing our Knowledge Society, are described. Second, the scientific and technological impact based on the teaching activities and the large number of theses submitted in Darmstadt for the area during these 40 years are addressed. Finally, the research road maps of the Computer Graphics and Visual Computing Hub in Darmstadt are presented relatively to the different stages of CG and VC research, relatively to a scientific view to the large number of projects implemented over these 40 years and, finally, also relatively to the project results as seen from the media. In order to manage the quantity as well as the complexity of the information available, the description of these road maps is divided in four time periods: 1975–1984, 1985–1994, 1995–2004 and 2004–2015. The paper also gives the view of the authors on how they see the future of Computer Graphics and Visual Computing. At the end, the paper includes an extensive list of references for the reported content. [ABSTRACT FROM AUTHOR]

Icon plays a critical role in computer interface design. Studies on icon taxonomy explain the way in which various types of icon represent the objects and provide designers creation rules by which icons are more in line with users’ cognitive psychology. However, along with larger and larger use of icons, the previous classification criterion causes the boundary between categories blur. What’s more, Single classification standard is not able to well illustrate the icons applied in today’s computer applications. The purpose of this paper is to present an objective-oriented icon taxonomy which proposes to categorize icons into action icon and knowledge icon. To assess this proposition, we analyzed a sample of icons that applied in computer interface and suggest precise application domains to both action icon and knowledge icon categories. The results of this practice manifested that action icon and knowledge icon implied a high relation with applied environment and explicated the development trace of computer icons. This work is one of the first to point out the notion of knowledge icon and to highlight the importance of objective of icon application. Findings in this paper could enrich icon use in computer interface design, especially provides possible way to improve online knowledge sharing by visual tool like icon. [ABSTRACT FROM AUTHOR]

In a recent paper (M. Barash, A. Okhotin, “An extension of context-free grammars with one-sided context specifications”, Inform. and Comput. , 2014), the authors introduced an extension of the context-free grammars equipped with an operator for referring to the left context of the substring being defined. This paper proposes a more general model, in which context specifications may be two-sided, that is, both the left and the right contexts can be specified by the corresponding operators. The paper gives the definitions, presents several examples of grammars and establishes a basic normal form theorem. This normal form, in particular, leads to a simple parsing algorithm working in time O ( n 4 ) , where n is the length of the input string. [ABSTRACT FROM AUTHOR]

The International Planning Competition is organized in the context of the International Conference on Automated Planning and Scheduling (ICAPS) and it is considered a reference source for the planning and scheduling community. The competition is typically organized every two years and deals with relevant issues for the community such as the definition of evaluation standards, the publication of benchmarks and the collection and dissemination of data about state-of-the-art planners. This paper focuses on the deterministic part, the longest-running part of the International Planning Competition. The paper describes its format, the participants, the selection of benchmarks and the generated results accompanied with analysis from different perspectives. The paper also examines the results of a brand new track created to explore the potential of planners that exploit the power of multi-core processors. Overall, the results of the competition indicate significant progress with respect to previous competitions, but they also reveal that some issues remain open and need further research, such as the coverage of temporal planners when concurrency is required and the performance in the multi-core track. As a novelty, all the data and the software generated for running the competition have been made publicly available allowing researchers to reproduce the competition and to carry out different analysis of the results. [ABSTRACT FROM AUTHOR]

Induction plays a key role in reasoning in many areas of mathematics and computer science. A central problem in the automation of proof by induction is the non-analytic nature of induction invariants. In this paper we present an algorithm for proving universal statements by induction that separates this problem into two phases. The first phase consists of a structural analysis of witness terms of instances of the universal statement. The result of such an analysis is a tree grammar which induces a quantifier-free unification problem which is solved in the second phase. Each solution to this problem is an induction invariant. The arguments and techniques used in this paper heavily exploit a correspondence between tree grammars and proofs already applied successfully to the generation of non-analytic cuts in the setting of pure first-order logic. [ABSTRACT FROM AUTHOR]

Many problems in Computer Science can be abstracted to the following question: given a set of objects and rules respectively, which new objects can be produced? In the paper, we consider a succinct version of the question: given a set of binary strings and several operations like conjunction and disjunction , which new binary strings can be generated? Although it is a fundamental problem, to the best of our knowledge, the problem hasn't been studied yet. In this paper, an O ( m 2 n ) algorithm is presented to determine whether a string s is representable by a set W , where n is the number of strings in W and each string has the same length m . However, looking for the minimum subset to represent a given string is shown to be NP -hard. Also, finding the smallest subset to represent each string in the original set is NP -hard. We establish tight inapproximability results and approximation algorithms for these NP -hard problems. In addition, we prove that counting the number of representable strings is # P -complete. We then explore how the problems change when the operator negation is available. For example, if the operator negation can be used, the counting problem is as simple as some power of 2. This difference may help us to better understand the problem. [ABSTRACT FROM AUTHOR]

Finding heavy-elements (heavy-hitters) in streaming data is one of the central, and well-understood tasks. Despite the importance of this problem, when considering the sliding windows model of streaming (where elements eventually expire) the problem of finding L 2 -heavy elements has remained completely open despite multiple papers and considerable success in finding L 1 -heavy elements. Since the L 2 -heavy element problem doesn't satisfy certain conditions, existing methods for sliding windows algorithms, such as smooth histograms or exponential histograms are not directly applicable to it. In this paper, we develop the first polylogarithmic-memory algorithm for finding L 2 -heavy elements in the sliding window model. Our technique allows us not only to find L 2 -heavy elements, but also heavy elements with respect to any L p with 0 < p ≤ 2 on sliding windows. By this we completely “close the gap” and resolve the question of finding L p -heavy elements in the sliding window model with polylogarithmic memory, since it is well known that for p > 2 this task is impossible. We demonstrate a broader applicability of our method on two additional examples: we show how to obtain a sliding window approximation of the similarity of two streams, and of the fraction of elements that appear exactly a specified number of times within the window (the α -rarity problem). In these two illustrative examples of our method, we replace the current expected memory bounds with worst case bounds. [ABSTRACT FROM AUTHOR]

The problem of automated theorem finding is one of the 33 basic research problems in automated reasoning which was originally proposed by Wos in 1988, and it is still an open problem. To solve the problem, an approach of forward deduction based on the strong relevant logics was proposed. Following the approach, this paper presents a systematic methodology for automated theorem finding. To show the effectiveness of our methodology, the paper presents two case studies, one is automated theorem finding in NBG set theory and the other is automated theorem finding in Peano's arithmetic. Some known theorems have been found in our case studies. [ABSTRACT FROM AUTHOR]

In the Closest String problem we are given an alphabet Σ, a set of strings S = { s 1 , s 2 , … , s k } over Σ such that | s i | = n and an integer d . The objective is to check whether there exists a string s over Σ such that d H ( s , s i ) ≤ d , i ∈ { 1 , … , k } , where d H ( x , y ) denotes the number of places strings x and y differ at. Closest String is a prototype string problem. This problem together with several of its variants such as Distinguishing String Selection and Closest Substring have been extensively studied from parameterized complexity perspective. These problems have been studied with respect to parameters that are combinations of k , d , | Σ | and n . However, surprisingly the kernelization question for these problems (for the versions when they admit fixed-parameter tractable algorithms) is not studied at all. In this paper we fill this gap in the literature and do a comprehensive study of these problems from kernelization complexity perspective. We settle almost all the problems by either obtaining a polynomial kernel or showing that the problem does not admit a polynomial kernel under a standard assumption in complexity theory. [ABSTRACT FROM AUTHOR]

As a fundamental subject of theoretical computer science, the maximum independent set (MIS) problem not only is of purely theoretical interest, but also has found wide applications in various fields. However, for a general graph determining the size of a MIS is NP-hard, and exact computation of the number of all MISs is even more difficult. It is thus of significant interest to seek special graphs for which the MIS problem can be exactly solved. In this paper, we address the MIS problem in the pseudofractal scale-free web and the Sierpiński gasket, which have the same number of vertices and edges. For both graphs, we determine exactly the independence number and the number of all possible MISs. The independence number of the pseudofractal scale-free web is as twice as the one of the Sierpiński gasket. Moreover, the pseudofractal scale-free web has a unique MIS, while the number of MISs in the Sierpiński gasket grows exponentially with the number of vertices. [ABSTRACT FROM AUTHOR]

In the combinatorial study of words, the Parikh matrix mapping was introduced by Mateescu et al. in 2001 as a natural expansion of the classical Parikh mapping. Solving the general injectivity problem of Parikh matrices remains as one of the most sought after triumph among researchers in this area of study. In this paper, we tackle this problem by extending Şerbǎnuţǎ's work regarding prints and M -unambiguity to the context of strong M -equivalence. Consequently, we obtain results on the finiteness of strongly M -unambiguous prints for any finite alphabet. Finally, a related conjecture by Şerbǎnuţǎ is conclusively addressed. [ABSTRACT FROM AUTHOR]

Remediation actions are performed in scenarios in which consequences of a problem should be promptly mitigated when its cause takes too long to be addressed or is unknown. Such scenarios are recurrent in the real world, including in the context of computer science. Existing approaches that address these scenarios are application-specific. Nevertheless, the reasoning about remediation actions as well as cause identification and resolution, in order to address problems permanently, can be abstracted in such a way that they can be incorporated to autonomous software components, often referred to as agents. They can thus autonomously deal with these scenarios, which we refer to as critical cause-effect situations . In this paper, we propose a domain-independent extension to the belief-desire-intention (BDI) architecture that provides such agents with this automated reasoning. Our work provides an extensible solution to this recurrent problem-solving strategy and allows agents to flexibly deal with resource-constrained scenarios. This solution removes the need for manually implementing the coordination of actions performed by agents, using causal models to capture the knowledge required to carry out this task. Therefore, it not only allows the development of systems with remediative behaviour, but also enables the reduction of development effort by means of a reusable infrastructure that can be used in several different domains. Our approach was evaluated based on an existing solution in the network resilience domain, which showed that our extended agent can autonomously address a network challenge, with a reduction in the development effort and no impact in agent performance. [ABSTRACT FROM AUTHOR]

Dealing with context dependent knowledge is a well-known area of study that roots in John McCarthy's seminal work. More recently, the Contextualized Knowledge Repository (CKR) framework has been conceived as a logic-based approach in which knowledge bases have a two layered structure, modeled by a global context and a set of local contexts. The global context not only contains the meta-knowledge defining the properties of local contexts, but also holds the global (context independent) object knowledge that is shared by all of the local contexts. In many practical cases, however, it is desirable to leave the possibility to “override” the global object knowledge at the local level: in other words, it is interesting to recognize the pieces of knowledge that can admit exceptional instances in the local contexts that do not need to satisfy the general axiom. To address this need, we present in this paper an extension of CKR in which defeasible axioms can be included in the global context. The latter are verified in the local contexts only for the instances for which no exception to overriding exists, where exceptions require a justification in terms of facts that are provable from the knowledge base. We formally define this semantics and study some semantic and computational properties, where we characterize the complexity of the major reasoning tasks, among them satisfiability testing, instance checking, and conjunctive query answering. Furthermore, we present a translation of extended CKRs with knowledge bases in the Description Logic SROIQ -RL under the novel semantics to datalog programs under the stable model (answer set) semantics. We also present an implementation prototype and examine its scalability with respect to the size of the input CKR and the amount (level) of defeasibility in experiments. Finally, we compare our representation approach with some major formalisms for expressing defeasible knowledge in Description Logics and contextual knowledge representation. Our work adds to the body of results on using deductive database technology such as SQL and datalog in these areas, and provides an expressive formalism (in terms of intrinsic complexity) for exception handling by overriding. [ABSTRACT FROM AUTHOR]

This survey paper attempts to study the existence, importance and impact of the notion of context in modern humanistic computing. Given its inherent diversity, the term is nowadays widely acknowledged among computer science tasks and has become a major topic of interest in several of its sub-fields, ranging from contextual semantics to social networks, social media and recently emerged innovative applications, such as travel routing. We start by presenting a brief review of contextual semantics as nowadays they are considered suitable for most common content analysis problems. Focus is also given within the next survey sections on the impact of context within the social networks and media field that came into sight over the last years. A short, closing discussion on the identified challenges and potential future research directions concludes this survey. [ABSTRACT FROM AUTHOR]

In recent years, monotonic ordinal classification has increased the focus of attention for machine learning community. Real life problems frequently have monotonicity constraints. Many of the monotonic classifiers require that the input data sets satisfy the monotonicity relationships between its samples. To address this, a conventional strategy consists of relabeling the input data to achieve complete monotonicity. As an alternative, we explore the use of preprocessing algorithms without modifying the class label of the input data. In this paper we propose the use of training set selection to choose the most effective instances which lead the monotonic classifiers to obtain more accurate and efficient models, fulfilling the monotonic constraints. To show the benefits of our proposed training set selection algorithm, called MonTSS, we carry out an experimentation over 30 data sets related to ordinal classification problems. [ABSTRACT FROM AUTHOR]

Let P be an orthogonal polygon with n vertices. A sliding camera travels back and forth along an orthogonal line segment s ⊆ P corresponding to its trajectory . The camera sees a point p ∈ P if there is a point q ∈ s such that p q ‾ is a line segment normal to s that is completely contained in P . In the Minimum-Cardinality Sliding Cameras (MCSC) problem , the objective is to find a set S of sliding cameras of minimum cardinality to guard P (i.e., every point in P can be seen by some sliding camera in S ), while in the Minimum-Length Sliding Cameras (MLSC) problem the goal is to find such a set S so as to minimize the total length of trajectories along which the cameras in S travel. In this paper, we answer questions posed by Katz and Morgenstern (2011) by presenting the following results: (i) the MLSC problem is polynomially tractable even for orthogonal polygons with holes, (ii) the MCSC problem is NP -complete when P is allowed to have holes, and (iii) an O ( n 3 log ⁡ n ) -time 2-approximation algorithm for the MCSC problem on [NE]-star-shaped orthogonal polygons with n vertices (similarly, [NW]-, [SE]-, or [SW]-star-shaped orthogonal polygons). [ABSTRACT FROM AUTHOR]