Algorithms, Volume 12, Issue 4 (April 2019) – 21 articles

Coloring is one of the most famous problems in graph theory. The coloring problem on undirected graphs has been well studied, whereas there are very few results for coloring problems on directed graphs. An oriented k-coloring of an oriented graph $G=(V,A)$ is a partition of the vertex set V into k independent sets such that all the arcs linking two of these subsets have the same direction. The oriented chromatic number of an oriented graph G is the smallest k such that G allows an oriented k-coloring. Deciding whether an acyclic digraph allows an oriented 4-coloring is NP-hard. It follows that finding the chromatic number of an oriented graph is an NP-hard problem, too. This motivates to consider the problem on oriented co-graphs. After giving several characterizations for this graph class, we show a linear time algorithm which computes an optimal oriented coloring for an oriented co-graph. We further prove how the oriented chromatic number can be computed for the disjoint union and order composition from the oriented chromatic number of the involved oriented co-graphs. It turns out that within oriented co-graphs the oriented chromatic number is equal to the length of a longest oriented path plus one. We also show that the graph isomorphism problem on oriented co-graphs can be solved in linear time. Full article

This paper presents a robust and precise tension control method for a roll-to-roll (R2R) system. In R2R processing, robust and precise tension control is very important because improper web tension control leads to deterioration in the quality of web material. However, tension control is not easy because the R2R system has a model variation in which the inertia of the web in roll form is changed and external disturbances caused by web slip and crumpled web. Therefore, a disturbance observer (DOB) was proposed to achieve robustness against model variations and external disturbances. DOB is a robust control method widely used in various fields because of its simple structure and excellent performance. Moreover, the web passes through various process steps to achieve the finished product in the R2R process. Particularly, it is important to track the tension when magnitude of the tension varies during process. Feedforward (FF) controller was applied to minimize the tracking error in the transient section where tension changes. Moreover, the signal processing of a sensor using the Kalman filter (KF) in the R2R system greatly improved control performance. Finally, the effectiveness of the proposed control scheme is discussed using experimental results. Full article

During the last few decades, machine learning has constituted a significant tool in extracting useful knowledge from economic data for assisting decision-making. In this work, we evaluate the performance of weight-constrained recurrent neural networks in forecasting economic classification problems. These networks are efficiently trained with a recently-proposed training algorithm, which has two major advantages. Firstly, it exploits the numerical efficiency and very low memory requirements of the limited memory BFGS matrices; secondly, it utilizes a gradient-projection strategy for handling the bounds on the weights. The reported numerical experiments present the classification accuracy of the proposed model, providing empirical evidence that the application of the bounds on the weights of the recurrent neural network provides more stable and reliable learning. Full article

The horizontal bending angle of scraper conveyor has a great influence on the running resistance, the current consumption, coal winning efficiency of the working surface, etc. Approximately 1–3° is usually the range of horizontal bending angle, but does not indicate the optimum bending angle of the coal mining face. To find the optimal horizontal bending angle, an optimization method is proposed. A mathematical calculation model of the running resistance of the scraper is established based on the direction of the shearer operation. Then, a method of adjusting the step size of the search by inertia weight and expanding fly distance range obeying the t-distribution is proposed based on the basic bat algorithm (BA). Finally, an industrial application was conducted in 21220 Changcun fully mechanized coal mining face, Henan Province. The results show that the current consumption by the scraper conveyor was reduced by 31% when the horizontal bending angle of the S-bending area was 0.66°. Meanwhile, the theoretical current has good consistency with the experimental data, and the average absolute error was 3%. Full article

The grounding grid of a substation is important for the safety of substation equipment. Especially to address the difficulty of parameter design in the auxiliary anode system of a grounding grid, an algorithm is proposed that is an optimization algorithm for the auxiliary anode system of a grounding grid based on improved simulated annealing. The mathematical model of the auxiliary anode system is inferred from the mathematical model of cathodic protection. On that basis, the parameters of the finite element model are optimized with the improved simulated annealing algorithm, thereby the auxiliary anode system of a grounding grid with optimized parameters is structured. Then the algorithm is proven as valid through experiments. The precision of the optimized parameters is improved by about 1.55% with respect to the Variable Metric Method and the Genetic Algorithm, so it can provide a basis for parameter design in the auxiliary anode system of a grounding grid. Full article

In this paper, we propose a novel spatial image error concealment (EC) method based on deep neural network. Considering that the natural images have local correlation and non-local self-similarity, we use the local information to predict the missing pixels and the non-local information to correct the predictions. The deep neural network we utilize can be divided into two parts: the prediction part and the auto-encoder (AE) part. The first part utilizes the local correlation among pixels to predict the missing ones. The second part extracts image features, which are used to collect similar samples from the whole image. In addition, a novel adaptive scan order based on the joint credibility of the support area and reconstruction is also proposed to alleviate the error propagation problem. The experimental results show that the proposed method can reconstruct corrupted images effectively and outperform the compared state-of-the-art methods in terms of objective and perceptual metrics. Full article

Superbubbles are a class of induced subgraphs in digraphs that play an essential role in assembly algorithms for high-throughput sequencing data. They are connected with the remainder of the host digraph by a single entrance and a single exit vertex. Linear-time algorithms for the enumeration superbubbles recently have become available. Current approaches require the decomposition of the input digraph into strongly-connected components, which are then analyzed separately. In principle, a single depth-first search could be used, provided one can guarantee that the root of the depth-first search (DFS)-tree is not itself located in the interior or the exit point of a superbubble. Here, we describe a linear-time algorithm to determine suitable roots for a DFS-forest that is guaranteed to identify the superbubbles in a digraph correctly. In addition to the advantages of a more straightforward implementation, we observe a nearly three-fold gain in performance on real-world datasets. We present a reference implementation of the new algorithm that accepts many commonly-used input formats for digraphs. It is available as open source from github. Full article

An improved squirrel search algorithm (ISSA) is proposed in this paper. The proposed algorithm contains two searching methods, one is the jumping search method, and the other is the progressive search method. The practical method used in the evolutionary process is selected automatically through the linear regression selection strategy, which enhances the robustness of squirrel search algorithm (SSA). For the jumping search method, the ‘escape’ operation develops the search space sufficiently and the ‘death’ operation further explores the developed space, which balances the development and exploration ability of SSA. Concerning the progressive search method, the mutation operation fully preserves the current evolutionary information and pays more attention to maintain the population diversity. Twenty-one benchmark functions are selected to test the performance of ISSA. The experimental results show that the proposed algorithm can improve the convergence accuracy, accelerate the convergence speed as well as maintain the population diversity. The statistical test proves that ISSA has significant advantages compared with SSA. Furthermore, compared with five other intelligence evolutionary algorithms, the experimental results and statistical tests also show that ISSA has obvious advantages on convergence accuracy, convergence speed and robustness. Full article

Effective communication in task-oriented situations requires high-level interactions. For human–agent collaboration, tasks need to be coordinated in a way that ensures mutual understanding. Speech Act Theory (SAT) aims to understand how utterances can be used to achieve actions. SAT consists of three components: locutionary act, illocutionary act, and perlocutionary act. This paper evaluates the agent’s verbal communication while collaborating with humans. SAT was used to anatomize the structure of the agent’s speech acts (locutionary acts), the agent’s intention behind the speech acts (illocutionary acts), and the effects on the human’s mental state (perlocutionary acts). Moreover, this paper studies the impact of human perceptions of the agent’s speech acts on the perception of collaborative performance with the agent. Full article

Non-uniquely-decodable (non-UD) codes can be defined as the codes that cannot be uniquely decoded without additional disambiguation information. These are mainly the class of non–prefix–free codes, where a code-word can be a prefix of other(s), and thus, the code-word boundary information is essential for correct decoding. Due to their inherent unique decodability problem, such non-UD codes have not received much attention except a few studies, in which using compressed data structures to represent the disambiguation information efficiently had been previously proposed. It had been shown before that the compression ratio can get quite close to Huffman/Arithmetic codes with an additional capability of providing direct access in compressed data, which is a missing feature in the regular Huffman codes. In this study we investigate non-UD codes in another dimension addressing the privacy of the high-entropy data. We particularly focus on such massive volumes, where typical examples are encoded video or similar multimedia files. Representation of such a volume with non–UD coding creates two elements as the disambiguation information and the payload, where decoding the original data from these elements becomes hard when one of them is missing. We make use of this observation for privacy concerns. and study the space consumption as well as the hardness of that decoding. We conclude that non-uniquely-decodable codes can be an alternative to selective encryption schemes that aim to secure only part of the data when data is huge. We provide a freely available software implementation of the proposed scheme as well. Full article

Quantum annealers such as D-Wave machines are designed to propose solutions for quadratic unconstrained binary optimization (QUBO) problems by mapping them onto the quantum processing unit, which tries to find a solution by measuring the parameters of a minimum-energy state of the quantum system. While many NP-hard problems can be easily formulated as binary quadratic optimization problems, such formulations almost always contain one or more constraints, which are not allowed in a QUBO. Embedding such constraints as quadratic penalties is the standard approach for addressing this issue, but it has drawbacks such as the introduction of large coefficients and using too many additional qubits. In this paper, we propose an alternative approach for implementing constraints based on a combinatorial design and solving mixed-integer linear programming (MILP) problems in order to find better embeddings of constraints of the type $\sum x_i=k$ for binary variables $x_i$. Our approach is scalable to any number of variables and uses a linear number of ancillary variables for a fixed k. Full article

Multiagent systems can be seen as an approach to software engineering for the design and development of complex, distributed software. Generally speaking, multiagent systems provide two main abstractions for modularizing the software: the agents and the environment where agents operate. In this paper, we argue that also the social relationships among the agents should be expressed explicitly and become first-class objects both at design- and at development-time. In particular, we propose to represent social relationships as commitments that are reified as resources in the agents’ environment and can be directly manipulated by the agents via standard operations. We demonstrate that this view induces an agent programming schema that is substantially independent of the actual agent platform, provided that commitments are available as explained. The paper exemplifies the schema on two agent platforms, JADE and JaCaMo, where commitments are made available via the 2COMM library. Full article

As a typical landmark in human lungs, the detection of pulmonary fissures is of significance to computer aided diagnosis and surgery. However, the automatic detection of pulmonary fissures in CT images is a difficult task due to complex factors like their 3D membrane shape, intensity variation and adjacent interferences. Based on the observation that the fissure object often appears as thin curvilinear structures across 2D section images, we present an efficient scheme to solve this problem by merging the fissure line detection from multiple cross-sections in different directions. First, an existing oriented derivative of stick (ODoS) filter was modified for pulmonary fissure line enhancement. Then, an orientation partition scheme was applied to suppress the adhering clutters. Finally, a multiple section model was proposed for pulmonary fissure integration and segmentation. The proposed method is expected to improve fissure detection by extracting more weak objects while suppressing unrelated interferences. The performance of our scheme was validated in experiments using the publicly available open Lobe and Lung Analysis 2011 (LOLA11) dataset. Compared with manual references, the proposed scheme achieved a high segmentation accuracy, with a median F₁-score of 0.8916, which was much better than conventional methods. Full article

The paper deals with the Bamboo Garden Trimming (BGT) problem introduced in [Gąsieniec et al., SOFSEM’17]. The problem is difficult to solved due to its close relationship to Pinwheel scheduling. The garden with n bamboos is an analogue of a system of n machines that have to be attended (e.g., serviced) with different frequencies. During each day, bamboo $b_i$ grows an extra height $h_i,$ for $i=1,\dots ,n$ and, on the conclusion of the day, at most one bamboo has its entire height cut.The goal is to design a perpetual schedule of cuts to keep the height of the tallest ever bamboo as low as possible. The contribution in this paper is twofold, and is both theoretical and experimental. In particular, the focus is on understanding what has been called priority schedulings, i.e., cutting strategies where priority is given to bamboos whose current height is above a threshold greater than or equal to $H={\sum }_{i=1}^n{h}_i$ . Value H represents the total daily growth of the system and it is known that one cannot keep bamboos in the garden below this threshold indefinitely. As the first result, it is proved that, for any distribution of integer growth rates $h_1,\dots ,h_n$ and any priority scheduling, the system stabilises in a fixed cycle of cuts. Then, the focus is on the so-called $\mathtt{ReduceMax}$ strategy, a greedy priority scheduling that each day cuts the tallest bamboo, regardless of the growth rates distribution. $\mathtt{ReduceMax}$ is known to provide a $O(logn)$ -approximation, with respect to the lower bound H. One of the main results achieved is that, if $\mathtt{ReduceMax}$ stabilises in a round-robin type cycle, then it guarantees 2-approximation. Furthermore, preliminary results are provided relating the structure of the input instance, in terms of growth rates, and the behavior of $\mathtt{ReduceMax}$ when applied to such inputs. Finally, a conjecture that $\mathtt{ReduceMax}$ is 2-approximating for the BGT problem is claimed, hence an extended experimental evaluation was conducted to support the conjecture and to compare $\mathtt{ReduceMax}$ with other relevant scheduling algorithms. The obtained results show that $\mathtt{ReduceMax}$ : (i) provides 2-approximation in all considered inputs; and (ii) always outperforms other considered strategies, even those for which better worst case approximation guarantees have been proven. Full article

A multi-track string is a tuple of strings of the same length. Given the pattern and text of two multi-track strings, the permuted pattern matching problem is to find the occurrence positions of all permutations of the pattern in the text. In this paper, we propose several algorithms for permuted pattern matching. Our first algorithm, which is based on the Knuth–Morris–Pratt (KMP) algorithm, has a fast theoretical computing time with $O\left(mk\right)$ as the preprocessing time and $O(nklog\sigma )$ as the matching time, where n, m, k, $\sigma$ , and $\mathit{occ}$ denote the length of the text, the length of the pattern, the number of strings in the multi-track, the alphabet size, and the number of occurrences of the pattern, respectively. We then improve the KMP-based algorithm by using an automaton, which has a better experimental running time. The next proposed algorithms are based on the Boyer–Moore algorithm and the Horspool algorithm that try to perform pattern matching. These algorithms are the fastest experimental algorithms. Furthermore, we propose an extension of the AC-automaton algorithm that can solve dictionary matching on multi-tracks, which is a task to find multiple multi-track patterns in a multi-track text. Finally, we propose filtering algorithms that can perform permuted pattern matching quickly in practice. Full article

The Ensemble Empirical Mode Decomposition (EEMD) algorithm has been used in bearing fault diagnosis. In order to overcome the blindness in the selection of white noise amplitude coefficient e in EEMD, an improved artificial bee colony algorithm (IABC) is proposed to obtain it adaptively, which providing a new idea for the selection of EEMD parameters. In the improved algorithm, chaos initialization is introduced in the artificial bee colony (ABC) algorithm to insure the diversity of the population and the ergodicity of the population search process. On the other hand, the collecting bees are divided into two parts in the improved algorithm, one part collects the optimal information of the region according to the original algorithm, the other does Levy flight around the current global best solution to improve its global search capabilities. Four standard test functions are used to show the superiority of the proposed method. The application of the IABC and EEMD algorithm in bearing fault diagnosis proves its effectiveness. Full article

The differential evolution (DE) algorithm is a popular and efficient evolutionary algorithm that can be used for single objective real-parameter optimization. Its performance is greatly affected by its parameters. Generally, parameter control strategies involve determining the most suitable value for the current state; there is only a little research on parameter combination and parameter distribution which is also useful for improving algorithm performance. This paper proposes an idea to use parameter region division and parameter strategy combination to flexibly adjust the parameter distribution. Based on the idea, a group-based two-level parameter combination framework is designed to support various modes of parameter combination, and enrich the parameter distribution characteristics. Under this framework, two customized parameter combination strategies are given for a single-operation DE algorithm and a multi-operation DE algorithm. The experiments verify the effectiveness of the two strategies and it also illustrates the meaning of the framework. Full article

Background: The existing contract net protocol has low overall efficiency during the bidding and release period, and a large amount of redundant information is generated during the negotiation process. Methods: On the basis of an ant colony algorithm, the dynamic response threshold model and the flow of pheromone model were established, then the complete task allocation process was designed. Three experimental settings were simulated under different conditions. Results: When the number of agents was 20 and the maximum load value was $L_{\max }=3$ , the traffic and run-time of task allocation under the improved contract net protocol decreased. When the number of tasks and $L_{\max }$ was fixed, the improved contract net protocol had advantages over the dynamic contract net and classical contract net protocols in terms of both traffic and run-time. Setting up the number of agents, tasks and $L_{\max }$ to improve the task allocation under the contract net not only minimizes the number of errors, but also the task completion rate reaches 100%. Conclusions: The improved contract net protocol can reduce the traffic and run-time compared with classical contract net and dynamic contract net protocols. Furthermore, the algorithm can achieve better assignment results and can re-forward all erroneous tasks. Full article

There are two main challenges in wireless multimedia sensors networks: energy constraints and providing DiffServ. In this paper, a joint flow control, routing, scheduling, and power control scheme based on a Lyapunov optimization framework is proposed to increase network lifetime and scheduling fairness. For an adaptive distribution of transmission opportunities, a differentiated queueing services (DQS) scheme is adopted for maintaining data queues. In the Lyapunov function, different types of queues are normalized for a unified dimension. To prolong network lifetime, control coefficients are designed according to the characteristics of the wireless sensor networks. The power control problem is proved to be a convex optimization problem and two optimal algorithms are discussed. Simulation results show that, compared with existing schemes, the proposed scheme can achieve a better trade-off between QoS performances and network lifetime. The simulation results also show that the scheme utilizing the distributed media access control scheme in scheduling performs best in the transmission of real-time services. Full article

We propose in this paper a two-phase approach that decomposes the process of solving the three-dimensional single Container Loading Problem (CLP) into subsequent tasks: (i) the generation of blocks of boxes and (ii) the loading of blocks into the container. The first phase is deterministic, and it is performed by means of constructive algorithms from the literature. The second phase is non-deterministic, and it is performed with the use of Generate-and-Solve (GS), a problem-independent hybrid optimization framework based on problem instance reduction that combines a metaheuristic with an exact solver. Computational experiments performed on benchmark instances indicate that our approach presents competitive results compared to those found by state-of-the-art algorithms, particularly for problem instances consisting of a few types of boxes. In fact, we present new best solutions for classical instances from groups BR1 and BR2. Full article