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Human Pose Estimation (HPE) has received considerable attention during the past years, improving its performance thanks to the use of Deep Learning, and introducing new interesting uses, such as its application in Sport and Physical Exercise (SPE). The aim of this systematic review is to analyze the literature related to the application of HPE in SPE, the available data, methods, performance, opportunities, and challenges. One reviewer applied different inclusion and exclusion criteria, as well as quality metrics, to perform the paper filtering through the paper databases. The Association for Computing Machinery Digital Library, Web of Science, and dblp included more than 500 related papers after the initial filtering, finally resulting in 20. In addition, research was carried out regarding the publicly available data related to this topic. It can be concluded that even if related public data can be found, much more data is needed to be able to obtain good performance in different contexts. In relation with the methods of the authors, the use of general purpose systems as base, such as Openpose, combined with other methods and adaptations to the specific use case can be found. Finally, the limitations, opportunities, and challenges are presented. [ABSTRACT FROM AUTHOR]

Comparing two sets of documents to identify new topics is useful inmany applications, like discovering trending topics from sets of scientific papers, emerging topic detection in microblogs, and interpreting sentiment variations in Twitter. In this paper, the main topic-modeling-based approaches to address this task are examined to identify limitations and necessary enhancements. To overcome these limitations, we introduce two separate frameworks to discover emerging topics through a filtered latent Dirichlet allocation (filtered-LDA) model. The model acts as a filter that identifies old topics from a timestamped set of documents, removes all documents that focus on old topics, and keeps documents that discuss new topics. Filtered-LDA also genuinely reduces the chance of using keywords from old topics to represent emerging topics. The final stage of the filter uses multiple topic visualization formats to improve human interpretability of the filtered topics, and it presents the most-representative document for each topic. [ABSTRACT FROM AUTHOR]

The paper presents a bibliometric analysis from 2014 to 2020 of the emerging and engaging field of quantum computing called Quantum Machine Learning (QML). The study discusses the analysis results from the comprehensive high indexed databases worldwide such as Institute of Electrical and Electronics Engineers (IEEE), Scopus, Web of Science (WOS), Google Scholar and the Association for Computing Machinery (ACM). Tools like iMapbuilder, IBM and SPSS Statistics are used to provide meaningful insights and flawless representations of the extracted data. There has been little research to provide a macroscopic overview of renowned authors, subject areas, funding agencies and patent applications related to Quantum Clustering (QC). The result and analysis of this study show an interesting fact, most researchers are now aware of quantum technology from the past few years. The purpose of bibliometric and patentometric analysis papers is to figure out the importance and utility of the QC research area. Most of the countries are taking an initiative to seek attention towards QC but the analysis shows that China and the US are leading. The survey revealed that the maximum numbers of publications of QC are from Physics and Astronomy followed by Computer Science. [ABSTRACT FROM AUTHOR]

Robust sunflowers are a generalization of combinatorial sunflowers that have applications in monotone circuit complexity Rossman (SIAM J. Comput. 43:256–279, 2014), DNF sparsification Gopalan et al. (Comput. Complex. 22:275–310 2013), randomness extractors Li et al. (In: APPROX-RANDOM, LIPIcs 116:51:1–13, 2018), and recent advances on the Erdős-Rado sunflower conjecture Alweiss et al. (In: Proceedings of the 52nd Annual ACM SIGACT Symposium on Theory of Computing, STOC. Association for Computing Machinery, New York, NY, USA, 2020) Lovett et al. (From dnf compression to sunflower theorems via regularity, 2019) Rao (Discrete Anal. 8,2020). The recent breakthrough of Alweiss, Lovett, Wu and Zhang Alweiss et al. (In: Proceedings of the 52nd Annual ACM SIGACT Symposium on Theory of Computing, STOC. Association for Computing Machinery, New York, NY, USA, 2020) gives an improved bound on the maximum size of a w-set system that excludes a robust sunflower. In this paper, we use this result to obtain an exp (n 1 / 2 - o (1)) lower bound on the monotone circuit size of an explicit n-variate monotone function, improving the previous best known exp (n 1 / 3 - o (1)) due to Andreev (Algebra and Logic, 26:1–18, 1987) and Harnik and Raz (In: Proceedings of the Thirty-Second Annual ACM Symposium on Theory of Computing, ACM, New York, 2000). We also show an exp (Ω (n)) lower bound on the monotone arithmetic circuit size of a related polynomial via a very simple proof. Finally, we introduce a notion of robust clique-sunflowers and use this to prove an n Ω (k) lower bound on the monotone circuit size of the CLIQUE function for all k ⩽ n 1 / 3 - o (1) , strengthening the bound of Alon and Boppana (Combinatorica, 7:1–22, 1987). [ABSTRACT FROM AUTHOR]

The paper presents a bibliometric analysis from 2014 to 2020 of the emerging and engaging field of quantum computing called Quantum Machine Learning (QML). The study discusses the analysis results from the comprehensive high indexed databases worldwide such as Institute of Electrical and Electronics Engineers (IEEE), Scopus, Web of Science (WOS), Google Scholar and the Association for Computing Machinery (ACM). Tools like iMapbuilder, IBM and SPSS Statistics are used to provide meaningful insights and flawless representations of the extracted data. There has been little research to provide a macroscopic overview of renowned authors, subject areas, funding agencies and patent applications related to Quantum Clustering (QC). The result and analysis of this study show an interesting fact, most researchers are now aware of quantum technology from the past few years. The purpose of bibliometric and patentometric analysis papers is to figure out the importance and utility of the QC research area. Most of the countries are taking an initiative to seek attention towards QC but the analysis shows that China and the US are leading. The survey revealed that the maximum numbers of publications of QC are from Physics and Astronomy followed by Computer Science. [ABSTRACT FROM AUTHOR]

In this paper, we present a systematic literature review concerning 3D object recognition and classification. We cover articles published between 2006 and 2016 available in three scientific databases (ScienceDirect, IEEE Xplore and ACM), using the methodology for systematic review proposed by Kitchenham. Based on this methodology, we used tags and exclusion criteria to select papers about the topic under study. After the works selection, we applied a categorization process aiming to group similar object representation types, analyzing the steps applied for object recognition, the tests and evaluation performed and the databases used. Lastly, we compressed all the obtained information in a general overview and presented future prospects for the area. [ABSTRACT FROM AUTHOR]

The easy accessibility and simplicity of Short Message Services (SMS) have made it attractive to malicious users thereby incurring unnecessary costing on the mobile users and the Network providers' resources. The aim of this paper is to identify and review existing state of the art methodology for SMS spam based on some certain metrics: AI methods and techniques, approaches and deployed environment and the overall acceptability of existing SMS applications. This study explored eleven databases which include IEEE, Science Direct, Springer, Wiley, ACM, DBLP, Emerald, SU, Sage, Google Scholar, and Taylor and Francis, a total number of 1198 publications were found. Several screening criteria were conducted for relevant papers such as duplicate removal, removal based on irrelevancy, abstract eligibility based on the removal of papers with ambiguity (undefined methodology). Finally, 83 papers were identified for depth analysis and relevance. A quantitative evaluation was conducted on the selected studies using seven search strategies (SS): source, methods/ techniques, AI approach, architecture, status, datasets and SMS spam mobile applications. A Quantitative Analysis (QA) was conducted on the selected studies and the result based on existing methodology for classification shows that machine learning gave the highest result with 49% with algorithms such as Bayesian and support vector machines showing highest usage. Unlike statistical analysis with 39% and evolutionary algorithms gave 12%. However, the QA for feature selection methods shows that more studies utilized document frequency, term frequency and n-grams techniques for effective features selection process. Result based on existing approaches for content-based, non-content and hybrid approaches is 83%, 5%, and 12% respectively. The QA based on architecture shows that 25% of existing solutions are deployed on the client side, 19% on server-side, 6% collaborative and 50% unspecified. This survey was able to identify the status of existing SMS spam research as 35% of existing study was based on proposed new methods using existing algorithms and 29% based on only evaluation of existing algorithms, 20% was based on proposed methods only. This study concludes with very interesting findings which shows that the majority of existing SMS spam filtering solutions are still between the "Proposed" status or "Proposed and Evaluated" status. In addition, the taxonomy of existing state of the art methodologies is developed and it is concluded that 8.23% of Android users actually utilize this existing SMS anti-spam applications. Our study also concludes that there is a need for researchers to exploit all security methods and algorithm to secure SMS thus enhancing further classification in other short message platforms. A new English SMS spam dataset is also generated for future research efforts in Text mining, Tele-marketing for reducing global spam activities. • A comprehensive review of Soft Techniques in SMS Spam Classification (upto May'19). • Overview of the most exploited methods used in feature selection & classification. • Taxonomy of existing state of the art methodologies is developed. • User's acceptability of SMS spam applications on Android App store was evaluated. [ABSTRACT FROM AUTHOR]

A family of ring-based cryptosystems, including the multilinear maps of Garg, Gentry and Halevi [Candidate multilinear maps from ideal lattices, Advances in Cryptology—EUROCRYPT 2013, Lecture Notes in Comput. Sci. 7881, Springer, Heidelberg 2013, 1–17] and the fully homomorphic encryption scheme of Smart and Vercauteren [Fully homomorphic encryption with relatively small key and ciphertext sizes, Public Key Cryptography—PKC 2010, Lecture Notes in Comput. Sci. 6056, Springer, Berlin 2010, 420–443], are based on the hardness of finding a short generator of a principal ideal (short-PIP) in a number field typically in ℚ ⁢ (ζ 2 s) {\mathbb{Q}(\zeta_{2^{s}})}. In this paper, we present a polynomial-time quantum algorithm for recovering a generator of a principal ideal in ℚ ⁢ (ζ 2 s) {\mathbb{Q}(\zeta_{2^{s}})} , and we recall how this can be used to attack the schemes relying on the short-PIP in ℚ ⁢ (ζ 2 s) {\mathbb{Q}(\zeta_{2^{s}})} by using the work of Cramer et al. [R. Cramer, L. Ducas, C. Peikert and O. Regev, Recovering short generators of principal ideals in cyclotomic rings, IACR Cryptology ePrint Archive 2015, https://eprint.iacr.org/2015/313], which is derived from observations of Campbell, Groves and Shepherd [SOLILOQUY, a cautionary tale]. We put this attack into perspective by reviewing earlier attempts at providing an efficient quantum algorithm for solving the PIP in ℚ ⁢ (ζ 2 s) {\mathbb{Q}(\zeta_{2^{s}})}. The assumption that short-PIP is hard was challenged by Campbell, Groves and Shepherd. They proposed an approach for solving short-PIP that proceeds in two steps: first they sketched a quantum algorithm for finding an arbitrary generator (not necessarily short) of the input principal ideal. Then they suggested that it is feasible to compute a short generator efficiently from the generator in step 1. Cramer et al. validated step 2 of the approach by giving a detailed analysis. In this paper, we focus on step 1, and we show that step 1 can run in quantum polynomial time if we use an algorithm for the continuous hidden subgroup problem (HSP) due to Eisenträger et al. [K. Eisenträger, S. Hallgren, A. Kitaev and F. Song, A quantum algorithm for computing the unit group of an arbitrary degree number field, Proceedings of the 2014 ACM Symposium on Theory of Computing—STOC'14, ACM, New York 2014, 293–302]. [ABSTRACT FROM AUTHOR]

• This paper analyses the state of the art of ensemble classification methods applied in Breast Cancer through a systematic mapping study. • 193 papers published since 2000 were analysed according to nine criteria. • The homogeneous ensemble classification methods were the most investigated. • Several single classification techniques were used for constructing ensemble methods. • Weka Software was the most used tool to build and to evaluate ensemble methods. Ensemble methods consist of combining more than one single technique to solve the same task. This approach was designed to overcome the weaknesses of single techniques and consolidate their strengths. Ensemble methods are now widely used to carry out prediction tasks (e.g. classification and regression) in several fields, including that of bioinformatics. Researchers have particularly begun to employ ensemble techniques to improve research into breast cancer, as this is the most frequent type of cancer and accounts for most of the deaths among women. The goal of this study is to analyse the state of the art in ensemble classification methods when applied to breast cancer as regards 9 aspects: publication venues, medical tasks tackled, empirical and research types adopted, types of ensembles proposed, single techniques used to construct the ensembles, validation framework adopted to evaluate the proposed ensembles, tools used to build the ensembles, and optimization methods used for the single techniques. This paper was undertaken as a systematic mapping study. A total of 193 papers that were published from the year 2000 onwards, were selected from four online databases: IEEE Xplore, ACM digital library, Scopus and PubMed. This study found that of the six medical tasks that exist, the diagnosis medical task was that most frequently researched, and that the experiment-based empirical type and evaluation-based research type were the most dominant approaches adopted in the selected studies. The homogeneous type was that most widely used to perform the classification task. With regard to single techniques, this mapping study found that decision trees, support vector machines and artificial neural networks were those most frequently adopted to build ensemble classifiers. In the case of the evaluation framework, the Wisconsin Breast Cancer dataset was the most frequently used by researchers to perform their experiments, while the most noticeable validation method was k-fold cross-validation. Several tools are available to perform experiments related to ensemble classification methods, such as Weka and R Software. Few researchers took into account the optimisation of the single technique of which their proposed ensemble was composed, while the grid search method was that most frequently adopted to tune the parameter settings of a single classifier. This paper reports an in-depth study of the application of ensemble methods as regards breast cancer. Our results show that there are several gaps and issues and we, therefore, provide researchers in the field of breast cancer research with recommendations. Moreover, after analysing the papers found in this systematic mapping study, we discovered that the majority report positive results concerning the accuracy of ensemble classifiers when compared to the single classifiers. In order to aggregate the evidence reported in literature, it will, therefore, be necessary to perform a systematic literature review and meta-analysis in which an in-depth analysis could be conducted so as to confirm the superiority of ensemble classifiers over the classical techniques. [ABSTRACT FROM AUTHOR]

The audiovisual documents artificially generated/modifiers with deepfakes can be used by disinformation propagation, and have researches for your detection. In order to propose a deepfake detection domain mapping, this study propose the bibliographic analysis (terms/concepts selection) in the Knowledge Organization, Terminology, and Information Architecture theoretical basis. The objectives are: realize terminological mapping on deepfake detection domain and verifier possible theoretical relationship between interdisciplinary basis selected. The inductive method was selected by bibliographic survey and domain mapping from exploratory-descriptive research of applied qualitative, and the theoretical basis was analyzed in reflexive and critical perspective. The bibliographic survey occurred in Web of Science, Scopus (Elsevier), and Association for Computing Machinery repositories. The theoretical-epistemological cut demonstrated application possibilities in web-domains. It was identifiers 22 papers with context and propositions of deepfake detection and others detection techniques of artificial manipulation/generation of audiovisual documents resulting in list with 78 candidate's terms. In conclusion, believe that are necessity of new studies in the domain because the results indicate to a largest domain than exclusively deepfake techniques with Generative Adversarial Networks use. [ABSTRACT FROM AUTHOR]

We consider the point location problem in an arrangement of n arbitrary hyperplanes in any dimension d, in the linear decision tree model, in which we only count linear comparisons involving the query point, and all other operations do not explicitly access the query and are for free. We mainly consider the simpler variant (which arises in many applications) where we only want to determine whether the query point lies on some input hyperplane. We present an algorithm that performs a point location query with O (d 2 log n) linear comparisons, improving the previous best result by about a factor of d. Our approach is a variant of Meiser's technique for point location (Inf Comput 106(2):286–303, 1993) (see also Cardinal et al. in: Proceedings of the 24th European symposium on algorithms, 2016), and its improved performance is due to the use of vertical decompositions in an arrangement of hyperplanes in high dimensions, rather than bottom-vertex triangulation used in the earlier approaches. The properties of such a decomposition, both combinatorial and algorithmic (in the standard real RAM model), are developed in a companion paper (Ezra et al. arXiv:1712.02913, 2017), and are adapted here (in simplified form) for the linear decision tree model. Several applications of our algorithm are presented, such as the k-SUM problem and the Knapsack and SubsetSum problems. However, these applications have been superseded by the more recent result of Kane et al. (in: Proceedings of the 50th ACM symposium on theory of computing, 2018), obtained after the original submission (and acceptance) of the conference version of our paper (Ezra and Sharir in: Proceedings of the 33rd international symposium on computational geometry, 2017). This result only applies to 'low-complexity' hyperplanes (for which the ℓ 1 -norm of their coefficient vector is a small integer), which arise in the aforementioned applications. Still, our algorithm has currently the best performance for arbitrary hyperplanes. [ABSTRACT FROM AUTHOR]

The Lisp programming language is often described as the first functional programming language and also as an important early AI language. In the history of functional programming, however, it occupies a rather anomalous position, as the circumstances of its development do not fit well with the widely accepted view that functional languages have been developed through a theoretically-inspired project of deriving practical programming languages from the lambda calculus. This paper examines the origins of Lisp in the early AI programming work of the mid-to-late 1950s, and in particular in the work of Allen Newell, Cliff Shaw and Herbert Simon. Their 1956 program, the Logic Theory Machine, introduced new ideas about data and program structures that were articulated in response to perceived limitations in existing programming technique. Later writers, notably John Backus, have described these features as constituting a 'programming language style' distinct from the traditional style that preceded it. The paper examines the origins of the earlier style in practices of manual computation, analyses the key technical differences between it and the style first manifested in the Logic Theory Machine, and concludes that programming practice and experience play a large and underappreciated role in the development of programming styles and languages. [ABSTRACT FROM AUTHOR]

The author reflects on the benefits of presenting articles in "ACM Transactions on Database Systems" (TODS) at the Association for Computing Machinery (ACM) Special Interest Group on Management of Data (SIGMOD) conference. He discusses the differences between journal and conference publications and cites the benefits of presenting TODS articles at the ACM SIGMOD conference including presentation by talk, as poster, or both, funds to attend conference, and increased visibility of the article.

Let B = (X , Y , E) be a bipartite graph. A half-square of B has one color class of B as vertex set, say X; two vertices are adjacent whenever they have a common neighbor in Y. Every planar graph is a half-square of a planar bipartite graph, namely of its subdivision. Until recently, only half-squares of planar bipartite graphs, also known as map graphs (Chen et al., in: Proceedings of the thirtieth annual ACM symposium on the theory of computing, STOC '98, pp 514–523. 10.1145/276698.276865, 1998; J ACM 49(2):127–138. 10.1145/506147.506148, 2002), have been investigated, and the most discussed problem is whether it is possible to recognize these graphs faster and simpler than Thorup's O (n 120) -time algorithm (Thorup, in: Proceedings of the 39th IEEE symposium on foundations of computer science (FOCS), pp 396–405. 10.1109/SFCS.1998.743490, 1998). In this paper, we identify the first hardness case, namely that deciding if a graph is a half-square of a balanced bisplit graph is NP-complete. (Balanced bisplit graphs form a proper subclass of star convex bipartite graphs). For classical subclasses of tree convex bipartite graphs such as biconvex, convex, and chordal bipartite graphs, we give good structural characterizations of their half-squares that imply efficient recognition algorithms. As a by-product, we obtain new characterizations of unit interval graphs, interval graphs, and of strongly chordal graphs in terms of half-squares of biconvex bipartite, convex bipartite, and of chordal bipartite graphs, respectively. Good characterizations of half-squares of star convex and star biconvex bipartite graphs are also given, giving linear-time recognition algorithms for these half-squares. [ABSTRACT FROM AUTHOR]

Purpose: This paper reviews the altered cerebrospinal fluid dynamics that can be associated with paediatric Chiari I malformation and we present our own institutional experience. Methods: We conducted a thorough review of the literature and retrospectively analyzed all cases of operatively managed paediatric Chiari 1 malformation at our institution between February 2006 and February 2019. Results: Acquired Chiari malformation (ACM) can radiologically mimic Chiari I and has been associated with both intracranial hypotension (either secondary to lumboperitoneal shunting or spontaneous CSF hypotension) and idiopathic intracranial hypertension (IIH). At our institution, 61 paediatric cases (range, 2–15 years) underwent foramen magnum decompression (FMD) for Chiari I malformation. Whilst 80% (50/61) of cases underwent FMD with no preceding or post-operative problems of CSF dynamics, 8% (5/61) of cases had hydrocephalus at initial presentation requiring CSF diversion followed by FMD for persistent Chiari, and 10% (6/61) developed hydrocephalus following FMD and required long-term CSF diversion. Conclusions: In paediatric ACM, the management of intracranial hypotension involves thorough radiological assessment and inclusion/adjustment of a valve in the case of lumboperitoneal shunting or epidural blood patch or interventional techniques in the case of spontaneous CSF leak. Thereby, unwarranted posterior fossa decompression surgery is avoided. In the case of IIH and Chiari I malformation, children who have recurrent symptoms despite adequate posterior fossa decompression surgery (failed Chiari), there is a strong role for intracranial pressure monitoring as raised intracranial pressure may indicate long-term CSF diversion. [ABSTRACT FROM AUTHOR]

In this paper, we develop new tools and connections for exponential time approximation. In this setting, we are given a problem instance and an integer r > 1 , and the goal is to design an approximation algorithm with the fastest possible running time. We give randomized algorithms that establish an approximation ratio of r for maximum independent set in O ∗ (exp (O ~ (n / r log 2 r + r log 2 r))) time, r for chromatic number in O ∗ (exp (O ~ (n / r log r + r log 2 r))) time, (2 - 1 / r) for minimum vertex cover in O ∗ (exp (n / r Ω (r))) time, and (k - 1 / r) for minimum k-hypergraph vertex cover in O ∗ (exp (n / (k r) Ω (k r))) time. (Throughout, O ~ and O ∗ omit polyloglog (r) and factors polynomial in the input size, respectively.) The best known time bounds for all problems were O ∗ (2 n / r) (Bourgeois et al. in Discret Appl Math 159(17):1954–1970, 2011; Cygan et al. in Exponential-time approximation of hard problems, 2008). For maximum independent set and chromatic number, these bounds were complemented by exp (n 1 - o (1) / r 1 + o (1)) lower bounds (under the Exponential Time Hypothesis (ETH)) (Chalermsook et al. in Foundations of computer science, FOCS, pp. 370–379, 2013; Laekhanukit in Inapproximability of combinatorial problems in subexponential-time. Ph.D. thesis, 2014). Our results show that the naturally-looking O ∗ (2 n / r) bounds are not tight for all these problems. The key to these results is a sparsification procedure that reduces a problem to a bounded-degree variant, allowing the use of approximation algorithms for bounded-degree graphs. To obtain the first two results, we introduce a new randomized branching rule. Finally, we show a connection between PCP parameters and exponential-time approximation algorithms. This connection together with our independent set algorithm refute the possibility to overly reduce the size of Chan's PCP (Chan in J. ACM 63(3):27:1–27:32, 2016). It also implies that a (significant) improvement over our result will refute the gap-ETH conjecture (Dinur in Electron Colloq Comput Complex (ECCC) 23:128, 2016; Manurangsi and Raghavendra in A birthday repetition theorem and complexity of approximating dense CSPs, 2016). [ABSTRACT FROM AUTHOR]

Active contour model (ACM) is an effective method for image segmentation that has been widely used in various research fields. For images with severe intensity inhomogeneity, most existing ACMs show a poor segmentation performance. Moreover, robustness of these models to initial contour and noise is unsatisfactory. To seek better approaches to these issues, this paper proposes an ACM driven by pre-fitting bias correction and optimized fuzzy c-means (FCM) algorithm, which is robust and achieves a fast segmentation. Firstly, an optimized FCM algorithm is presented, by which bias field is pre-estimated. Secondly, a criterion function for local intensity is defined, then integrated with respect to the center for a global criterion. Thirdly, the above theory is introduced into ACM according to the property of level set function. Fourthly, a novel regularization method is proposed for variational level set. Experiments on real and synthetic images prove that the proposed model can effectively segment images with severe intensity inhomogeneity. Compared with the bias correction model, there is no more time-consuming convolutions in iterations so that computational amount of our model is enormously reduced. Furthermore, the model has better robustness to both noise and initialization, segmentation efficiency and accuracy than most region-based models. [ABSTRACT FROM AUTHOR]

With advances in base technologies for moving objects, many studies have been conducted on the construction of databases of the trajectories of moving objects, including the diverse applications related to the trajectories. Most previous studies deal with whole trajectory matching, which finds the trajectories T in the database similar to a given query trajectory Q 'as a whole.' However, we often want to find those T containing the sub-trajectories T sub (⊆ T) that are similar to Q. This problem is known as sub-trajectory matching and is more complicated than whole trajectory matching since the query trajectory Q can be of any length and the matching sub-trajectories T sub can be at any position in the data trajectories T. In this paper, we present a novel indexing-based sub-trajectory matching algorithm using multi-segment approximation. Our algorithm partitions a data trajectory into multiple component segments and then stores the individual segments in an index. The query trajectory is also partitioned into its component segments, and the search for similar segments for each query segment is efficiently performed using the index. The sub-trajectories similar to the query trajectory are reconstructed by our 'stitching' algorithm using the individual segments retrieved from the index. Our stitching algorithm is novel and innovative in the sense that it facilitates segment-wise partitioning and indexing of data trajectories. Without stitching, only trajectory-wise operations would be affordable, which causes severe storage space overhead and degradation in search performance. Our study is the first that uses indexing in sub-trajectory matching. We define a (multi-segment) trajectory similarity measure that extends a widely used single-segment similarity measure proposed by Lee et al. (in: Proceedings of ACM SIGMOD international conference on management of data (SIGMOD), 2007; in: Proceedings of IEEE international conference on data engineering (ICDE), 2008; Proc VLDB Endow (PVLDB) 1(1):1081–1094, 2008) by using the Hausdorff distance. We perform extensive experiments to compare our method with EDS (Xie, in: Proceedings of ACM SIGMOD international conference on management of data (SIGMOD), 2014), which has been proved to outperform all representative point-based measures in terms of accuracy and performance. The accuracy of our similarity measure is better than EDS by up to 52.0%, and our algorithm significantly outperforms that using EDS by up to 22,543 times. The performance of our algorithm is linearly scalable in the size of the database, which is an essential property for handling large-scale databases. [ABSTRACT FROM AUTHOR]

In this paper, we propose new exact and approximation algorithms for the weighted matroid intersection problem. Our exact algorithm is faster than previous algorithms when the largest weight is relatively small. Our approximation algorithm delivers a (1 - ϵ) -approximate solution with a running time significantly faster than most known exact algorithms. The core of our algorithms is a decomposition technique: we decompose an instance of the weighted matroid intersection problem into a set of instances of the unweighted matroid intersection problem. The computational advantage of this approach is that we can make use of fast unweighted matroid intersection algorithms as a black box for designing algorithms. More precisely, we show that we can solve the weighted matroid intersection problem via solving W instances of the unweighted matroid intersection problem, where W is the largest given weight, assuming that all given weights are integral. Furthermore, we can find a (1 - ϵ) -approximate solution via solving O (ϵ - 1 log r) instances of the unweighted matroid intersection problem, where r is the smaller rank of the two given matroids. Our algorithms make use of the weight-splitting approach of Frank (J Algorithms 2(4):328–336, 1981) and the geometric scaling scheme of Duan and Pettie (J ACM 61(1):1, 2014). Our algorithms are simple and flexible: they can be adapted to special cases of the weighted matroid intersection problem, using specialized unweighted matroid intersection algorithms. In addition, we give a further application of our decomposition technique: we solve efficiently the rank-maximal matroid intersection problem, a problem motivated by matching problems under preferences. [ABSTRACT FROM AUTHOR]

To meet the rising demand for high reliability in complex multidisciplinary engineering systems, more attention has been paid to reliability-based multidisciplinary design optimization (RBMDO). In this paper, a sequential optimization and fuzzy reliability analysis (SOFRA) method for multidisciplinary systems is developed to decouple the fuzzy reliability analysis from the optimization. In SOFRA, the multidisciplinary design optimization (MDO) and fuzzy reliability analysis are conducted in a sequential manner. Furthermore, a novel adaptive collocation method (ACM) is proposed to conduct the fuzzy reliability analysis for multidisciplinary systems. The ACM arranges points adaptively at the axis of the membership to obtain more accurate results. The shifting distance of the constraint is calculated by the bi-section method. Both numerical and engineering examples are used to demonstrate the validity of the proposed method. [ABSTRACT FROM AUTHOR]

The ability to process large amounts of data and to extract useful insights from data has revolutionised society. This phenomenon—dubbed as Big Data—has applications for a wide assortment of industries, including the construction industry. The construction industry already deals with large volumes of heterogeneous data; which is expected to increase exponentially as technologies such as sensor networks and the Internet of Things are commoditised. In this paper, we present a detailed survey of the literature, investigating the application of Big Data techniques in the construction industry. We reviewed related works published in the databases of American Association of Civil Engineers (ASCE), Institute of Electrical and Electronics Engineers (IEEE), Association of Computing Machinery (ACM), and Elsevier Science Direct Digital Library. While the application of data analytics in the construction industry is not new, the adoption of Big Data technologies in this industry remains at a nascent stage and lags the broad uptake of these technologies in other fields. To the best of our knowledge, there is currently no comprehensive survey of Big Data techniques in the context of the construction industry. This paper fills the void and presents a wide-ranging interdisciplinary review of literature of fields such as statistics, data mining and warehousing, machine learning, and Big Data Analytics in the context of the construction industry. We discuss the current state of adoption of Big Data in the construction industry and discuss the future potential of such technologies across the multiple domain-specific sub-areas of the construction industry. We also propose open issues and directions for future work along with potential pitfalls associated with Big Data adoption in the industry. [ABSTRACT FROM AUTHOR]

An analytical coordination model (ACM) for a pharmaceutical multinational corporation (MNC) supply chain is presented in this paper. To improve the supply chain performance, we study the coordination among the supply chain parties from the strategic to operational levels. The Supply Chain Operations Reference (SCOR) model is adopted to support the MNC to choose and refine the supply chain management strategies. An optimal integer-ratio inventory coordination (IIC) policy is devised to coordinate the inventory replenishment at the tactical and operational levels. By combining the SCOR model and IIC policy, a systematic approach is proposed. We focus on the derivation and analysis of the total operational cost (TOC) of the supply chain based on cost performance metrics across three levels of the SCOR model version 10. The TOC is proven to reach its global minimum after the integer constraint is relaxed. The findings reinforce the proposition that the adoption of an ACM based on the metrics of the SCOR model is promising to assist decision makers in improving the supply chain performance. Numerical experiments are conducted to show how to compute the optimal TOC in practice. The computational results demonstrated that the TOC savings through the SCOR-based ACM are significant. [ABSTRACT FROM AUTHOR]

Highlights • CS was use as source of aluminosilicate for development of ACM. • The mixes were activated using alkali content of 5% and 7% by weight of binder. • Addition of mineral admixtures in alkali-activated CS improves its performance. • MK was found to be more effective than FA. Abstract The paper presents results of an investigation conducted to study the feasibility of use of Copper Slag (CS) as aluminosilicate material for developing Alkali-activated Cementitious Material (ACM). The effect of addition of mineral admixtures such as Fly Ash (FA) and Metakaolin (MK) on the performance of alkali-activated CS was also investigated. In addition to a control mix which was prepared using 100% CS; two other mixes were also prepared by replacing CS with 30% FA and 30% MK respectively. These mixes were activated using alkali content of 5% and 7% by weight of binder. Sodium hydroxide and sodium silicate were used as alkali-activators. Compressive strength tests were performed on alkali-activated cement mixes at different curing ages. The pore-size distribution, mineralogy and microstructure of selected alkali-activated cement mixes were determined using Mercury Intrusion Porosimetry (MIP), X-ray Diffraction (XRD) and Scanning Electron Microscopy (SEM) with Energy Dispersive X-ray Spectroscopy (EDS). Test results indicate that CS has great potential as aluminosilicate material for developing ACM. Further, the addition of mineral admixtures in alkali-activated CS cement improves its performance; however, the addition of MK was found to be more effective than FA in terms of compressive strength and microstructure development. [ABSTRACT FROM AUTHOR]

Leader election is, together with consensus, one of the most central problems in distributed computing. This paper presents a distributed algorithm, called STT , for electing deterministically a leader in an arbitrary network, assuming processors have unique identifiers of size O (log n) , where n is the number of processors. It elects a leader in O (D + log n) rounds, where D is the diameter of the network, with messages of size O(1). Thus it has a bit round complexity of O (D + log n) . This substantially improves upon the best known algorithm whose bit round complexity is O (D log n) . In fact, using the lower bound by Kutten et al. (J ACM 62(1):7:1–7:27, 2015) and Kutten et al. (Theor Comput Sci 561:134–143, 2015) and a result of Dinitz and Solomon (Theor Comput Sci 384(2–3):168–183, 2007), we show that the bit round complexity of STT is optimal (up to a constant factor), which is a significant step forward in understanding the interplay between time and message optimality for the election problem. Our algorithm requires no knowledge on the graph such as n or D, and the pipelining technique we introduce to break the O (D log n) barrier is general. [ABSTRACT FROM AUTHOR]

In the classical binary search in a path the aim is to detect an unknown target by asking as few queries as possible, where each query reveals the direction to the target. This binary search algorithm has been recently extended by Emamjomeh-Zadeh et al. (in: Proceedings of the 48th annual ACM SIGACT symposium on theory of computing, STOC 2016, Cambridge, pp. 519–532, 2016) to the problem of detecting a target in an arbitrary graph. Similarly to the classical case in the path, the algorithm of Emamjomeh-Zadeh et al. maintains a candidates' set for the target, while each query asks an appropriately chosen vertex—the "median"—which minimises a potential Φ among the vertices of the candidates' set. In this paper we address three open questions posed by Emamjomeh-Zadeh et al., namely (a) detecting a target when the query response is a direction to an approximately shortest path to the target, (b) detecting a target when querying a vertex that is an approximate median of the current candidates' set (instead of an exact one), and (c) detecting multiple targets, for which to the best of our knowledge no progress has been made so far. We resolve questions (a) and (b) by providing appropriate upper and lower bounds, as well as a new potential Γ that guarantees efficient target detection even by querying an approximate median each time. With respect to (c), we initiate a systematic study for detecting two targets in graphs and we identify sufficient conditions on the queries that allow for strong (linear) lower bounds and strong (polylogarithmic) upper bounds for the number of queries. All of our positive results can be derived using our new potential Γ that allows querying approximate medians. [ABSTRACT FROM AUTHOR]

In this paper we study the arithmetically Cohen-Macaulay (ACM) property for sets of points in multiprojective spaces. Most of what is known is for ℙ1 × ℙ1 and, more recently, in (ℙ1) r . In ℙ1 × ℙ1 the so called inclusion property characterises the ACM property. We extend the definition in any multiprojective space and we prove that the inclusion property implies the ACM property in ℙm × ℙn. In such an ambient space it is equivalent to the so-called (⋆)-property. Moreover, we start an investigation of the ACM property in ℙ1 × ℙn. We give a new construction that highlights how different the behavior of the ACM property is in this setting. [ABSTRACT FROM AUTHOR]

In this paper, we develop a novel angle-domain adaptive filtering (ADAF)-based frequency synchronization method for the uplink of a massive multiple-input multiple-output multiuser network, which is applicable for users with either separate or overlapped angle-of-arrival (AoA) regions. For each user, we first introduce the angle-constraining matrix (ACM), which consists of a set of selected match-filter beamformers pointing to the AoAs of the interested user. Then, the adaptive beamformers can be acquired by appropriately designing the ADAF vectors. Such beamformer can achieve two-stage adaptive multiuser interference (MUI) suppression, i.e., inherently suppressing the MUI from non-overlapping users by ACM in the first stage and substantially mitigating the MUI from adjacent overlapping users by ADAF vectors in the second stage. For both separate and mutually overlapping users, the carrier frequency offset (CFO) estimation and subsequent data detection can be performed independently for each user, which significantly reduces computational complexity. Moreover, ADAF is rather robust to imperfect AoA knowledge and side cluster of scatterers, making itself promising for multiuser uplink transmission. We also analyze the performance of CFO estimation and obtain an approximated closed-form expression of mean-squared error. The effectiveness of the proposed method and its superiority over the existing methods are demonstrated by numerical results. [ABSTRACT FROM AUTHOR]

A set D ⊆ V for the graph G = (V , E) is called a dominating set if any vertex v ∈ V \ D has at least one neighbor in D. Fomin et al. [Combinatorial bounds via measure and conquer: Bounding minimal dominating sets and applications, ACM Transactions on Algorithms (TALG) 5(1) (2008) 9] gave an algorithm for enumerating all minimal dominating sets with n vertices in O (1. 7 1 5 9 n) time. It is known that the number of minimal dominating sets for interval graphs and trees on n vertices is at most 3 n / 3 ≈ 1. 4 4 2 2 n . In this paper, we introduce the domination cover number as a new criterion for evaluating the dominating sets in graphs. The domination cover number of a dominating set D , denoted by 𝒞 D (G) , is the summation of the degrees of the vertices in D. Maximizing or minimizing this parameter among all minimal dominating sets has interesting applications in many real-world problems, such as the art gallery problem. Moreover, we investigate this concept for different graph classes and propose some algorithms for finding the domination cover number in trees and block graphs. [ABSTRACT FROM AUTHOR]

The FM index (Ferragina and Manzini in J ACM 52(4):552–581, 2005) is a widely-used compressed data structure that stores a string T in a compressed form and also supports fast pattern matching queries. In this paper, we describe new FM-index variants that combine nice theoretical properties, simple implementation and improved practical performance. Our main theoretical result is a new technique called fixed block compression boosting, which is a simpler and faster alternative to optimal compression boosting and implicit compression boosting used in previous FM-indexes. We also describe several new techniques for implementing fixed-block boosting efficiently, including a new, fast, and space-efficient implementation of wavelet trees. Our extensive experiments show the new indexes to be consistently fast and small relative to the state-of-the-art, and thus they make a good "off-the-shelf" choice for many applications. [ABSTRACT FROM AUTHOR]

In this paper, we investigate special arrangements of lines in multiprojective spaces. In particular, we characterize codimension 2 arithmetically Cohen–Macaulay (ACM) varieties in ℙ 1 × ℙ 1 × ℙ 1 , called varieties of lines. We also describe their ACM property from a combinatorial algebra point of view. [ABSTRACT FROM AUTHOR]

Online social networks have continued to attract increased attention since the introduction of this concept nearly three decades ago. Consequently, a study about the workings of online social networks may help in understanding the structure of human society and the characteristics of generic complex networks. Over the past few years, interest in neighboring nodes, which are the number of nodes between any two nodes, the number of neighbors and how many triangles are present in a social network have produced the concepts of a six-degree separation (Milgram, Psychol Today 2(1):60–67, 1967; Backstrom et al., Proceedings of the 4th annual ACM web science conference, p 33–42, 2012), a heavy tail in the degree distribution (Barabási, Albert, Science 286(5439):509–512, 1999) and a high clustering coefficient (Luce, Perry, Psychometrika 14(2):95–116, 1949; Watts, Strogatz, Nature 393(6684):440–442, 1998; Amaral et al., Proc Natl Acad Sci USA 97(21):11149–11152, 2000). In a similar manner, researchers have also been curious about how many polygons are present in a given online social network. Although much effort has been expended (Dantzig et al., International symposium on theory of graphs, p 77–83, 1967; Kamae, IEEE Trans Circuit Theory 14(2):166–171, 1967; Gotlieb, Corneil, Commun ACM 10(12):780–783, 1967; Welch, J ACM 13(2):205–210, 1966; Tiernan, Commun ACM 13(12):722–726, 1970; Tarjan, SIAM J Comput 2(3):211–216, 1973; Johnson, SIAM J Comput 4:77–84, 1975; Mateti, Deo, SIAM J Comput 5(5):90–99, 1976; Marinari et al., Europhys Lett 73(3):301–307, 2005), studying this subject, the inability to enumerate polygons has stymied an in depth understanding of the properties of polygons in an online social network. In the study described in this paper, the estimated number of polygons in an online social network is revealed. It was found that in the current widely used online social networks, e.g., Facebook, Twitter, the number of polygons increases drastically when the length of a polygon is below a set value and then it decreases rapidly. The average length of the network polygons was calculated and it was found that online social networks contain a relatively large average length of polygons. Based on this perspective, a massive labyrinth of polygons would make the online social networks appear to be very complicated. To further investigate this area, a generalized clustering coefficient was explored. Results showed that the generalized clustering coefficient appeared to descend exponentially with the length of polygon and expeditiously approached zero. This result suggested that the polygons with large lengths should be ignored in many scenarios. Since the polygons with lengths greater than five appeared to have little impact on the network, the online social networks appeared to be less complex than anticipated. The polygon is one of the fundamental problems in graph theory and complex networks, so that the work reported here may be beneficial for many disciplines, including transportation [7], engineering [8], computer science [9–16], physics (Birmelé et al., Proceedings of the 24th annual ACM–SIAM symposium on discrete algorithms, p 1884–1896, 2013), sociology (Motter, Albert, Phys Today 65:43, 2012), epidemiology (Feld, Am J Sociol 96(6):1464–1477, 1991; Cohen et al., Phys Rev Lett 91(24):12343, 2002), psychology (Sun et al., Sci Rep 4(6188):5099–5099, 2014), biology (Feiler, Kleinbaum, Psychol Sci, 2015), medicine (Kincaid, Pilette, Comput Appl Biosci Cabios 8:267–273, 1992), geography (Kim et al., Lancet 386(9989):145–153, 2015), etc. [ABSTRACT FROM AUTHOR]

In the popular imagination, the relevance of Turing's theoretical ideas to people producing actual machines was significant and appreciated by everybody involved in computing from the moment he published his 1936 paper ‘On Computable Numbers’. Careful historians are aware that this popular conception is deeply misleading. We know from previous work by Campbell-Kelly, Aspray, Akera, Olley, Priestley, Daylight, Mounier-Kuhn, Haigh, and others that several computing pioneers, including Aiken, Eckert, Mauchly, and Zuse, did not depend on (let alone were they aware of) Turing's 1936 universal-machine concept. Furthermore, it is not clear whether any substance in von Neumann's celebrated 1945 ‘First Draft Report on the EDVAC’ is influenced in any identifiable way by Turing's work. This raises the questions: (i) When does Turing enter the field? (ii) Why did the Association for Computing Machinery (ACM) honor Turing by associating his name to ACM's most prestigious award, the Turing Award? Previous authors have been rather vague about these questions, suggesting some date between 1950 and the early 1960s as the point at which Turing is retroactively integrated into the foundations of computing and associating him in some way with the movement to develop something that people call computer science. In this paper, based on detailed examination of hitherto overlooked primary sources, attempts are made to reconstruct networks of scholars and ideas prevalent in the 1950s, and to identify a specific group ofactors interested in theorizing about computations in computers and attracted to the idea of language as a frame in which to understand computation. By going back to Turing's 1936 paper and, more importantly, to re-cast versions of Turing's work published during the 1950s (Rosenbloom, Kleene, Markov), I identify the factors that made this group of scholars particularly interested in Turing's work and provided the original vector by which Turing became to be appreciated in retrospect as the father of computer science. [ABSTRACT FROM PUBLISHER]