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An automatic computer vision algorithm that detects individual paper fibres from an image, assesses the possibility of grasping the detected fibres with microgrippers and detects the suitable grasping points is presented. The goal of the algorithm is to enable automatic fibre manipulation for mechanical characterisation, which has traditionally been slow manual work. The algorithm classifies the objects in images based on their morphology, and detects the proper grasp points from the individual fibres by applying given geometrical constraints. The authors test the ability of the algorithm to detect the individual fibres with 35 images containing more than 500 fibres in total, and also compare the graspability analysis and the calculated grasp points with the results of an experienced human operator with 15 images that contain a total of almost 200 fibres. The detection results are outstanding, with fewer than 1% of fibres missed. The graspability analysis gives sensitivity of 0.83 and specificity of 0.92, and the average distance between the grasp points of the human and the algorithm is 220 µm. Also, the choices made by the algorithm are much more consistent than the human choices. [ABSTRACT FROM AUTHOR]

Nowadays, with the development of computer science and technology, computer intelligent algorithms are more and more widely used in various industries. Every calculation formula in the computer intelligent algorithm has systematic logic and singleness, in order to expound the dynamic algorithm of football training optimized by the computer intelligent algorithm in detail. In this paper, the monitoring system using the computer intelligent algorithm can dynamically observe people or objects and systematically analyze them. This paper mainly studies the research of a football training dynamic monitoring system based on the computer intelligent algorithm and the design and optimization of the computer intelligent dynamic monitoring system in football training. Finally, the overall composition of the computer intelligent dynamic monitoring system and the application of the optimized computer intelligent dynamic monitoring system to the analysis of sample data are studied. [ABSTRACT FROM AUTHOR]

Real social networks contain many communities, where members within each community are densely connected with each other, while they are sparsely connected with the members outside of the community. Since each member can join multiple communities simultaneously, communities in social networks are usually overlapping with each other. How to efficiently and effectively identify overlapping communities in a large social network becomes a fundamental problem in the big data era. Most existing studies on community finding focused on non-overlapping communities based on several well-known community fitness metrics. However, recent investigations have shown that these fitness metrics may suffer free rider and separation effects where the overlapping region of two communities always belongs to the denser one, rather to both of them. In this paper, we study the overlapping community detection problem in social networks that not only takes the quality of the found overlapping communities but also incorporate both free rider and separation effects on the found communities into consideration. Specifically, in this paper, we first propose a novel community fitness metric - triangle based fitness metric, for overlapping community detection that can minimize the free rider and separation effects on found overlapping communities, and show that the problem is NP-hard. We then propose an efficient yet scalable algorithm for the problem that can deliver a feasible solution. We finally validate the effectiveness of the proposed fitness metric and evaluate the performance of the proposed algorithm, through conducting extensive experiments on real-world datasets with over 100 million vertices and edges. Experimental results demonstrate that the proposed algorithm is very promising. [ABSTRACT FROM AUTHOR]

The triangle partition problem is a generalization of the well-known graph matching problem consisting of finding the maximum number of independent edges in a given graph, i.e., edges with no common node. Triangle partition instead aims to find the maximum number of disjoint triangles. The triangle partition problem is known to be NP-complete. Thus, in this paper, the focus is on the local maximization variant, called maximal triangle partition (MTP). Thus, paper presents a new self-stabilizing algorithm for MTP that converges in O( m) moves under the unfair distributed daemon. [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]

In this paper, we propose two sequence allocation schemes to overcome the drawbacks that protocol sequence allocation in vehicular ad hoc networks heavily relies on the help of roadside units and that lots of sequence resource is wasted owing to the one-to-one scheme. Specifically, the rectangle-cell (R-C) scheme is proposed for neighboring nodes to occupy sequences without overlapping on straight roads. Furthermore, the hexagon-cell (H-C) scheme is proposed to handle the sequence allocation problem on city roads. The sum of generalized prime sequences which builds the foundations for the proposed schemes is fully studied. Besides, the algorithms for vehicles to generate cell marks and occupy sequences without any inter-vehicle interference are given in detail. Simulation results show that both the R-C scheme and the H-C scheme can take full advantage of the sequence resource and exhibit their superiority in sequence utilization and throughput compared to the one-to-one scheme. [ABSTRACT FROM AUTHOR]

In this paper we consider the properties of the most popular algorithms for genomic similarity search. All these methods use some type of heuristics to improve the speed of search that has negative impact upon the accuracy. Some of these methods split the content into small pieces of data, some of them use hashing, while some of them utilize the computational benefits of suffix tree. In many cases the output depends of the userproved parameters that define the sensitivity and the range of search. [ABSTRACT FROM AUTHOR]

The accuracy and diversity of recommendation algorithms have always been the research hotspot of recommender systems. A good recommender system should not only have high accuracy and diversity, but also have adequate robustness against spammer attacks. However, the issue of recommendation robustness has received relatively little attention in the literature. In this paper, we systematically study the influences of different spammer behaviors on the recommendation results in various recommendation algorithms. We further propose an improved algorithm by incorporating the inner-similarity of user’s purchased items in the classic KNN approach. The new algorithm effectively enhances the robustness against spammer attacks and thus outperforms traditional algorithms in recommendation accuracy and diversity when spammers exist in the online commercial systems. [ABSTRACT FROM AUTHOR]

Flash storage devices are widely used for mobile consumer electronics due to small size, low power consumption, and high performance. Generally, the flash storage device consists of NAND flash memories. Compared to traditional magnetic disks, NAND flash memory requires an additional erase operation and its blocks have limited erase cycles. For extending its endurance, various wearleveling algorithms have been proposed. However, they invoke many read/write/erase operations and use many memory resources for managing their block states because they do not consider the property of the flash translation layer. To solve these problems, a new wear-leveling algorithm for the log-based flash translation layer is proposed in this paper. In the log-based flash translation layer, since log blocks are frequently updated and erased, the cold block rarely removed is reserved for a next log block so that all the blocks are evenly erased. In addition, the proposed algorithm reduces the usage of memory resources by exploiting k-bitwise erase table that only needs small k-bit erase flags for managing its block erase state. Through various experiments with related wear-leveling algorithms, this paper shows the superiority of the proposed wear-leveling algorithm. [ABSTRACT FROM AUTHOR]

In many applications, top-k query is an important operation to return a set of interesting points in a potentially huge data space. It is analyzed in this paper that the existing algorithms cannot process top- k query on massive data efficiently. This paper proposes a novel table-scan-based T2S algorithm to efficiently compute top-k results on massive data. T2S first constructs the presorted table, whose tuples are arranged in the order of the round-robin retrieval on the sorted lists. T2S maintains only fixed number of tuples to compute results. The early termination checking for T2S is presented in this paper, along with the analysis of scan depth. The selective retrieval is devised to skip the tuples in the presorted table which are not top-k results. The theoretical analysis proves that selective retrieval can reduce the number of the retrieved tuples significantly. The construction and incremental-update/batch-processing methods for the used structures are proposed in this paper. The extensive experimental results, conducted on synthetic and real-life data sets, show that T2S has a significant advantage over the existing algorithms. [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]

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]

Literature search is one of the most important steps of academic research. With more than 100,000 papers published each year just in computer science, performing a complete literature search becomes a Herculean task. Some of the existing approaches and tools for literature search cannot compete with the characteristics of today’s literature, and they suffer from ambiguity and homonymy. Techniques based on citation information are more robust to the mentioned issues. Thus, we recently built a Web service called the advisor, which provides personalized recommendations to researchers based on their papers of interest. Since most recommendation methods may return redundant results, diversifying the results of the search process is necessary to increase the amount of information that one can reach via an automated search. This article targets the problem of result diversification in citation-based bibliographic search, assuming that the citation graph itself is the only information available and no categories or intents are known. The contribution of this work is threefold. We survey various random walk--based diversification methods and enhance them with the direction awareness property to allow users to reach either old, foundational (possibly well-cited and well-known) research papers or recent (most likely less-known) ones. Next, we propose a set of novel algorithms based on vertex selection and query refinement. A set of experiments with various evaluation criteria shows that the proposed γ-RLM algorithm performs better than the existing approaches and is suitable for real-time bibliographic search in practice. [ABSTRACT FROM AUTHOR]

Cyber-archaeology represents the marriage of archaeology, computer science, engineering, and the natural sciences with the aim of taking advantage of constantly evolving technologies for digital data capture, curation, analyses and dissemination. Digital data collection tools are perhaps the most rapidly changing arenas of development in cyber-archaeology and are becoming affordable tools for every archaeologist. In this paper, we examine two users' approaches to produce point cloud models of archaeological sites using structure from motion (SfM) photography. The experiment took place at the Fountain of Peirene in ancient Corinth, Greece. Their implementation of the technology and their results are compared to highlight the very important role the photo-shooting session can play in the final outcome of the SfM reconstruction. We correlate the users' approaches to the applied algorithms' robust features and known limitations to provide a technical explanation of how archaeologists can significantly improve their success in SfM. As new algorithms and software emerge making SfM a common tool in archaeological documentation the methodology presented in this paper will enable archaeologists to meet the high demand for digital documentation on a global scale. [ABSTRACT FROM AUTHOR]

A hypergraph is one of the most developing area for modeling various practical problems in different fields, including computer science, biological sciences, social networks and psychology. Our main discussion in this research paper is to apply the notion of intuitionistic fuzzy sets to extend the theory of hypergraphs. We introduce the concept of isomorphism, dual intuitionistic fuzzy hypergraph, intuitionistic fuzzy line graph and 2-section of an intuitionistic fuzzy hypergraph. We present some applications of intuitionistic fuzzy hypergraphs in planet surface networks, selection of authors of of intersecting communities in a social network and grouping of incompatible chemical substances. We design certain algorithms to construct dual intuitionistic fuzzy hypergraph, intuitionistic fuzzy line graph and the selection of objects in decision-making problems. [ABSTRACT FROM AUTHOR]

Crowdsourcing has been shown to be effective in a wide range of applications, and is seeing increasing use. A large-scale crowdsourcing task often consists of thousands or millions of atomic tasks, each of which is usually a simple task such as binary choice or simple voting. To distribute a large-scale crowdsourcing task to limited crowd workers, a common practice is to pack a set of atomic tasks into a task bin and send to a crowd worker in a batch. It is challenging to decompose a large-scale crowdsourcing task and execute batches of atomic tasks, which ensures reliable answers at a minimal total cost. Large batches lead to unreliable answers of atomic tasks, while small batches incur unnecessary cost. In this paper, we investigate a general crowdsourcing task decomposition problem, called the Smart Large-scAle task DE composer (SLADE) problem, which aims to decompose a large-scale crowdsourcing task to achieve the desired reliability at a minimal cost. We prove the NP-hardness of the SLADE problem and propose solutions in both homogeneous and heterogeneous scenarios. For the homogeneous SLADE problem, where all the atomic tasks share the same reliability requirement, we propose a greedy heuristic algorithm and an efficient and effective approximation framework using an optimal priority queue (OPQ) structure with provable approximation ratio. For the heterogeneous SLADE problem, where the atomic tasks can have different reliability requirements, we extend the OPQ-based framework leveraging a partition strategy, and also prove its approximation guarantee. Finally, we verify the effectiveness and efficiency of the proposed solutions through extensive experiments on representative crowdsourcing platforms. [ABSTRACT FROM AUTHOR]

In this paper, a couple of new algorithms for independent component analysis (ICA) are proposed. In the proposed methods, the independent sources are assumed to follow a predefined distribution of the form f ( s ) = α exp ( − β | s | p ) and a maximum likelihood estimation is used to separate the sources. In the first method, a gradient ascent method is used for the maximum likelihood estimation, while in the second, a non-iterative algorithm is proposed based on the relaxation of the problem. The maximization of the log-likelihood of the estimated source X T w given the parameter p and the data X is shown to be equivalent to the minimization of l p -norm of the projected data X T w . This formulation of ICA has a very close relationship with the Lp-PCA where the maximization of the same objective function is solved. The proposed algorithm solves an approximation of the l p -norm minimization problem for both super-( p  < 2) and sub-Gaussian ( p  > 2) cases and shows superior performance in separating independent sources than the state of the art algorithms for ICA computation. [ABSTRACT FROM AUTHOR]

Referring to the issue that the hop value of the range-free DV-hop positioning algorithm could not reflect the distance between two nodes within the communication range, this paper proposes an algorithm named as HCRDV-Hop. According to the proposed algorithm, the distance measured by hops between two nodes is re-treated as the specific value with dividing the received signal strength (denoted as RSSI) between nodes with the maximum average signal strength of nodes (RSSImax). Based on that, we also introduce the mathematical reasoning as well as provide the implementation procedures of the proposed algorithm. Moreover, the simulation verification is then elaborated in order to evaluate the algorithm performance. According to the simulation result, we discover that the proposed HCRDV-Hop algorithm reveals better performance in the distribution of node positioning deviations and the relative positioning deviations. [ABSTRACT FROM AUTHOR]

As the core of rational utilization of computing resources, the scheduling algorithm has gained the interest of many researchers. Aimed at meta-job scheduling in heterogeneous environments, this paper puts forward three algorithms: the meta-job scheduling algorithm based on deviation (MaxD-min heuristic), the meta-job scheduling algorithm based on relative deviation (MaxRD-min heuristic), and the Cordwood algorithm (CA). The former two Algorithm are improvements of the classic Min-min algorithm. The latter CA algorithm is a new method that tries to place each building block on the tray with minimal amount of Sufferage. The result of experimenting shows that the three algorithms, in comparison to Min-Min and Max-Min algorithm, can effectively reduce the total span of scheduling (makespan). [ABSTRACT FROM AUTHOR]

Co-training is a framework for semi-supervised learning that has attracted much attention due to its good performance and easy adaptation for various learning algorithms. In a recent work, Caldas et al. proposed a co-training-based method using the recently proposed supervised learning method named minimal learning machine (MLM). Although the proposed method, referred to as Co-MLM, presented results that are comparable to other semi-supervised algorithms, using MLM as a base learner resulted in a formulation with heavy computational cost. Aiming to mitigate this problem, in this paper, we propose an improved variant of Co-MLM with reduced computational cost on both training and testing phases. The proposed method is compared to Co-MLM and other Co-training-based semi-supervised methods, presenting comparable performances. [ABSTRACT FROM AUTHOR]

Recent smart devices have adopted heterogeneous multi-core processors which have high-performance big cores and low-power small cores. Unfortunately, the conventional task scheduler for heterogeneous multi-core processors does not provide appropriate amount of CPU resources for multimedia applications (whose QoS is important to users), resulting in energy waste; it often executes multimedia applications and non-multimedia applications on the same core. In this paper, we propose an advanced task scheduler for heterogeneous multi-core processors, which provides appropriate amount of CPU resources for multimedia applications. Our proposed task scheduler isolates multimedia applications from non-multimedia applications at runtime, exploiting the fact that multimedia applications have a specific thread for video/audio playback (to play video/audio, a multimedia application should use a function that generates the specific thread). Since multimedia applications usually require a smaller amount of CPU resources than non-multimedia applications due to dedicated hardware decoders, our proposed task scheduler allocates the former to the small cores and the latter to the big cores. In our experiments on an Android-based development board, our proposed task scheduler saves system-wide (not just CPU) energy consumption by 8.9 percent, on average, compared to the conventional task scheduler, preserving QoS of multimedia applications. In addition, it improves performance of non-multimedia applications by 13.7 percent, on average, compared to the conventional task scheduler. [ABSTRACT FROM PUBLISHER]

Abstract: This paper describes a novel algorithm for numerical optimization, called Simple Adaptive Climbing (SAC). SAC is a simple efficient single-point approach that does not require a careful fine-tunning of its two parameters. SAC algorithm shares many similarities with local optimization heuristics, such as random walk, gradient descent, and hill-climbing. SAC has a restarting mechanism, and a powerful adaptive mutation process that resembles the one used in Differential Evolution. The algorithms SAC is capable of performing global unconstrained optimization efficiently in high dimensional test functions. This paper shows results on 15 well-known unconstrained problems. Test results confirm that SAC is competitive against state-of-the-art approaches such as micro-Particle Swarm Optimization, CMA-ES or Simple Adaptive Differential Evolution. [Copyright &y& Elsevier]

Abstract: A breakthrough in the field of text algorithms was the discovery of the fact that the maximal number of runs in a word of length n is and that they can all be computed in time. We study some applications of this result. New simpler time algorithms are presented for classical textual problems: computing all distinct k-th word powers for a given k, in particular squares for , and finding all local periods in a given word of length n. Additionally, we present an efficient algorithm for testing primitivity of factors of a word and computing their primitive roots. Applications of runs, despite their importance, are underrepresented in existing literature (approximately one page in the paper of Kolpakov and Kucherov, 1999 [25,26]). In this paper we attempt to fill in this gap. We use Lyndon words and introduce the Lyndon structure of runs as a useful tool when computing powers. In problems related to periods we use some versions of the Manhattan skyline problem. [Copyright &y& Elsevier]

In view of that the rational exchange protocol was a dynamic game model, under complete imperfect information dynamic game, this paper introduced the maximum entropy principle to solve the problem of strategy behavior inference of rational party. Based on information entropy, this paper extended a rational exchange protocols model in which a new fairness description was given combined with a desired payoff function and an expected equilibrium. In addition, it constructed a new rational exchange protocol based on the maximum entropy principle, which was proved secure and fair. Meanwhile, made analysis of the exchange process by game tree. Results show that the proposed protocol can achieve expected equilibrium. Without the participation of the trusted third party, the protocol can achieve rational fairness and be beautifully adapted to the real environment. [ABSTRACT FROM AUTHOR]

According to the virtualization technology of cloud computing, it can solve the problems that the electronic cash systems exist leakage of privacy, non-standard transactions and high cost in the traditional network. In the existing work, considering merchants and customers used the same bank to restrict the widespread use of electronic cash in a certain degree, the paper presented an multi-bank electronic cash payment scheme for trusted cloud platform based on TPM. Considering the efficiency and security from the electronic cash payment of the scheme, the scheme used the group signature and elliptic curve algorithm ECC to improve the execution efficiency of the protocol, and used the privacy protection and remote attestation function of TPM to achieve security. Finally, the paper analyzed the safety and efficiency of the scheme. [ABSTRACT FROM AUTHOR]

In order to realize intelligence management of guide sign system, this paper proposed an algorithm for deploying guide signs using guide sign data model from the perspective of road guiding levels. The algorithm took road intersection as research object, and guide sign information was classified into two categories, namely, connection signs and direction signs according to the relationship of guide signs information and road network topology. Moreover, the paper illustrated the selection principles of directional signs based on road guiding levels, and constructed deployment algorithm model for directional signs. Finally, a case study was conducted: the deployment model was tested in Guangzhou Higher Education Mega Center. The result revealed that the data model could support the automatic deployment, analysis and evaluation for guide signs. [ABSTRACT FROM AUTHOR]

Aim at the problem for how to analyze the propensity to spread of shortage of supplies in emergency logistics decision support system, this paper proposed a new model to study the propensity to spread of shortage of supplies for emergency logistics network. This paper, by the mechanism of viral spreading and introducing the parameter of time "t", it constructed SI-SIRS ( susceptible infective and susceptible infective recover susceptible) model to analyze the scale-free network which included 61 nodes. Case analysis shows that SIRS effectively depicts the spread behavior of shortage of supplies in emergency logistics network. Propensities to spread of shortage of supplies are effected by node self-spread ability, network topology, individual nodes differences and responding mechanism of emergency logistics. [ABSTRACT FROM AUTHOR]

Direction is a key factor of accessibility research. Therefore, this paper proposed a calculation method on space-time accessibility considering the direction of travel. First, it constructed an experiential hierarchy of road network using experiential taxi routes. Second, it used the Dijkstra algorithm based on hierarchical road network to compute the travel time between each OD, and then used a grid method and inverse distance weighting method to render the isochrones maps of Guangzhou CBD. Finally, the paper analyzed the accessibility of it in different direction of travel and different time periods. The experimental results prove that accessibility in different direction, especially in peak time, is quite different. [ABSTRACT FROM AUTHOR]

Community structure is one of the most important and basic topologic properties of complex network. The rational division of community structure in complex network is the main purpose of the complex network's community division research. This paper mainly researched the division of community structure in complex network based on the theory of supernetwork and standardized degree centrality. Based on the lack of GN algorithm, this paper proposed a new comprehensive algorithm to divide community structure from the perspective of supernetwork. Finally, the new comprehensive algorithm is illustrated through examples. [ABSTRACT FROM AUTHOR]

An understanding of how individuals shape and impact the evolution of society is vastly limited due to the unavailability of large-scale reliable datasets that can simultaneously capture information regarding individual movements and social interactions. We believe that the popular Indian film industry, “Bollywood”, can provide a social network apt for such a study. Bollywood provides massive amounts of real, unbiased data that spans more than 100 years, and hence this network has been used as a model for the present paper. The nodes which maintain a moderate degree or widely cooperate with the other nodes of the network tend to be more fit (measured as the success of the node in the industry) in comparison to the other nodes. The analysis carried forth in the current work, using a conjoined framework of complex network theory and random matrix theory, aims to quantify the elements that determine the fitness of an individual node and the factors that contribute to the robustness of a network. The authors of this paper believe that the method of study used in the current paper can be extended to study various other industries and organizations. [ABSTRACT FROM AUTHOR]

Background: Discovering biomarkers is a fundamental step to understand and deal with genetic diseases. Methods using classic Computer Science algorithms have been adapted in order to support processing large biological data sets, aiming to find useful information to understand causing conditions of diseases such as cancer. Results: This paper describes some promising biomarker discovery methods based on several grid architectures. Each technique has some features that make it more suitable for a particular grid architecture. This matching depends on the parallelizing capabilities of the method and the resource availability in each processing/storage node. Conclusion: The study described in this paper analyzed the performance of biomarker discovery methods in different grid architectures. We have found some methods are more suited for certain grid architectures, resulting in significant performance improvement and producing more accurate results. [ABSTRACT FROM AUTHOR]

Abstract: There are many folded states consistent with a given mountain–valley pattern of equidistant creases on a long paper strip. We would like to fold a paper strip such that the number of paper layers between each pair of hinged paper segments, called the crease width at the crease point, is minimized. This problem is called the stamp folding problem and there are two variants of this problem: minimization of the maximum crease width, and minimization of the total crease width. This optimization problem was recently introduced and investigated from the viewpoint of the counting problem. However, its computational complexity is not known. In this paper, we first show that the minimization problem of the maximum crease width is strongly NP-complete. Hence we cannot solve the problem in polynomial time unless P=NP. We next propose an algorithm that solves the minimization problem. The algorithm itself is a straightforward one, but its analysis is not trivial. We show that this algorithm runs in time where is the number of creases and is the total crease width. [Copyright &y& Elsevier]

: In computational science literature including, e.g., bioinformatics, computational statistics or machine learning, most published articles are devoted to the development of “new methods”, while comparison studies are generally appreciated by readers but surprisingly given poor consideration by many journals. This paper stresses the importance of neutral comparison studies for the objective evaluation of existing methods and the establishment of standards by drawing parallels with clinical research. The goal of the paper is twofold. Firstly, we present a survey of recent computational papers on supervised classification published in seven high-ranking computational science journals. The aim is to provide an up-to-date picture of current scientific practice with respect to the comparison of methods in both articles presenting new methods and articles focusing on the comparison study itself. Secondly, based on the results of our survey we critically discuss the necessity, impact and limitations of neutral comparison studies in computational sciences. We define three reasonable criteria a comparison study has to fulfill in order to be considered as neutral, and explicate general considerations on the individual components of a “tidy neutral comparison study”. R codes for completely replicating our statistical analyses and figures are available from the companion website http://www.ibe.med.uni-muenchen.de/organisation/mitarbeiter/020_professuren/boulesteix/plea2013. [ABSTRACT FROM AUTHOR]

In this paper, we develop two automated authorship attribution schemes, one based on Multiple Discriminant Analysis (MDA) and the other based on a Support Vector Machine (SVM). The classification features we exploit are based on word frequencies in the text. We adopt an approach of preprocessing each text by stripping it of all characters except a-z and space. This is in order to increase the portability of the software to different types of texts. We test the methodology on a corpus of undisputed English texts, and use leave-one-out cross validation to demonstrate classification accuracies in excess of 90%. We further test our methods on the Federalist Papers, which have a partly disputed authorship and a fair degree of scholarly consensus. And finally, we apply our methodology to the question of the authorship of the Letter to the Hebrews by comparing it against a number of original Greek texts of known authorship. These tests identify where some of the limitations lie, motivating a number of open questions for future work. An open source implementation of our methodology is freely available for use at https://github.com/matthewberryman/author-detection. [ABSTRACT FROM AUTHOR]

Node location is of great significance as a supporting technology of wireless sensor network (WSN). The information without position would be greatly devalued. So this paper is about location algorithm for nodes of ship-borne WSN based on research on structure of ship and work environment of ship-borne WSN. The whole location process consists of two steps: one is location algorithm among cabins (LAAC), and the other one is location algorithm in the cabin (LAIC). LAAC refers to location with the topology of ship-borne WSN. We can learn which cabin the node lies in. LAIC refers to location based on received signal strength indication (RSSI), we can get distance relationship between nodes by RSSI, and then obtain the specific location by solving this distance relationship. In the last part, this paper verifies the designed location algorithm by experimenting on "A" ship. Experiments show that the location algorithm designed by this paper is feasible. [ABSTRACT FROM AUTHOR]