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With the development of computer technology, automatic test paper generation systems have gradually become an effective tool for detecting and maintaining national machine security and protecting the rights and interests of workers. This article achieved multi-level oral scores for different types of questions through online scoring using artificial neural networks in recent years. Based on its specific situation and evaluation index requirements, an analysis module that is reasonable, efficient, and in line with the hierarchical structure and module requirements of national conditions has been designed to complete the research on automatic test paper generation technology, in order to help better manage and allocate human resources and improve production efficiency. Afterwards, this article conducted functional testing on the technical module. The test results showed that the scalability of the system was over 82%. [ABSTRACT FROM AUTHOR]

Methods to rank documents in large-scale citation data are increasingly assessed in terms of their ability to identify small sets of expert-selected papers. Here, we propose an algorithm for the accurate identification of milestone papers from citation networks. The algorithm combines an influence propagation process with game theory concepts. It outperforms state-of-the-art metrics in the identification of milestone papers in aggregate citation network data, while potentially mitigating the ranking's temporal bias compared with metrics that have similar milestone identification performance. The proposed method sheds light on the interplay between ranking accuracy and temporal bias. • We transform citation networks into influence propagation networks by reversing the citation relationships. • We propose a novel diffusion-based metric for ranking papers, combining influence propagation and game theory. • Experiments on APS and DBLP datasets demonstrate the effectiveness of our metric in identifying milestone papers. [ABSTRACT FROM AUTHOR]

This research highlights the underestimated significance of cigarette paper as evidence at crime scenes. The primary objective is to distinguish cigarette paper from similar-looking alternatives, addressing the first research objective. The second objective involves identifying cigarette paper brands using attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy and machine learning (ML) algorithms. Accurate differentiation of cigarette paper from normal paper is emphasized. ATR-FTIR spectroscopy, coupled with principal component analysis (PCA) for dimensionality reduction, is employed for brand identification. Among fifteen ML algorithms compared, the CatBoost classifier excels for both objectives. This research presents a non-destructive, effective method for studying cigarette paper, contributing valuable insights to crime scene investigations. [Display omitted] • Forensic evaluation of cigarette paper utilizing ATR-FTIR spectroscopy and Machine learning algorithms. • Peak characterization and differentiation-distinguishing cigarette paper from other types. • Machine learning algorithm comparison: assessing discrimination across nine cigarette brands. • External validation of the dominant algorithm using unknown samples. [ABSTRACT FROM AUTHOR]

Detecting plagiarism in academic papers is crucial for maintaining academic integrity, preserving the originality of published work, and safeguarding intellectual property. While existing applications excel at text plagiarism detection, they fall short when it comes to image plagiarism. This paper introduces a novel algorithm, named "VIBRANT-WALK," designed to detect image plagiarism in academic manuscripts. The challenge of identifying plagiarized images is formidable, requiring a unique approach. Traditional Computer Vision algorithms, proficient in image similarity tasks, face limitations in determining whether an image has been previously used in an article. To address this, the proposed algorithm leverages a repository of all published article pages, focusing on absolute identicality rather than image similarity. The algorithm comprises two stages. In the first stage, a "Vibrancy Matrix" is created through image preprocessing, aiding in contour determination. The second stage involves pixel-by-pixel comparison with images from published manuscripts. To enhance efficiency, the algorithm initiates comparisons from the pixel with the highest score in the Vibrancy Matrix, followed by pixel comparisons through random walks, significantly reducing complexity. To conduct the study, a custom dataset was compiled from 69 research articles, capturing snapshots of each page and figure. Overall, we present 485 unique test cases where we can test the accuracy and efficiency of the algorithm. The lack of publicly available datasets necessitated this approach. The proposed algorithm outperformed the existing models and algorithms in this field by achieving an overall accuracy of 94.8% on the collated dataset, identifying 460 instances of plagiarism out of the 485 test cases. The algorithm also demonstrated a 100% accuracy rate in avoiding false positives. [ABSTRACT FROM AUTHOR]

With the exponential growth in the number of academic researchers, it is crucial for editors of scientific journals to identify the highest-quality papers. While several measures exist to evaluate a paper's impact post-publication, the challenge of determining the potential impact of a manuscript during the review process remains an understudied issue. In this paper, we propose a reviewer-reputation ranking algorithm to identify high-quality papers based on paper citations, where a reviewer's reputation is computed from the correlation between their past ratings and the current number of citations received by the papers they have evaluated. During the review process, reviewers with high reputation scores are given more weight to determine the quality of papers. We test the algorithm on an artificial network with 200 reviewers and 600 papers, as well as on the American Physical Society (APS) data set, including in the analysis 308,243 papers and 274,154 mutual citations. We compare our approach with two existing methods, demonstrating that our algorithm significantly outperforms the others in identifying manuscripts with the highest quality. Our findings can help improve the impact of scientific journals, thereby contributing to academic and scientific progress. • We propose an algorithm to identify the papers with the highest quality from a large number of submissions. • We compare our new algorithm with other existing methods of aggregating user ratings in various online services. • We test our algorithm both with an artificial network and with the empirical data of the APS data set. • We show that our algorithm outperforms the other methods in identifying the papers with the highest quality. [ABSTRACT FROM AUTHOR]

Highlights • We evaluate paper-level impact metrics on field bias, time bias, and ranking performance. • We evaluate mean-based, percentile-based, co-citation-based, and post hoc rescaling approaches to normalise citation scores. • Percentile-based citation scores are less field and time biased than mean-normalised citation counts. • No significant difference in ranking performance exists between percentile- and mean-normalised citation scores. • Citation counts are always less time biased but always more field biased than PageRank. Abstract We evaluate article-level metrics along two dimensions. Firstly, we analyse metrics' ranking bias in terms of fields and time. Secondly, we evaluate their performance based on test data that consists of (1) papers that have won high-impact awards and (2) papers that have won prizes for outstanding quality. We consider different citation impact indicators and indirect ranking algorithms in combination with various normalisation approaches (mean-based, percentile-based, co-citation-based, and post hoc rescaling). We execute all experiments on two publication databases which use different field categorisation schemes (author-chosen concept categories and categories based on papers' semantic information). In terms of bias, we find that citation counts are always less time biased but always more field biased compared to PageRank. Furthermore, rescaling paper scores by a constant number of similarly aged papers reduces time bias more effectively compared to normalising by calendar years. We also find that percentile citation scores are less field and time biased than mean-normalised citation counts. In terms of performance, we find that time-normalised metrics identify high-impact papers better shortly after their publication compared to their non-normalised variants. However, after 7 to 10 years, the non-normalised metrics perform better. A similar trend exists for the set of high-quality papers where these performance cross-over points occur after 5 to 10 years. Lastly, we also find that personalising PageRank with papers' citation counts reduces time bias but increases field bias. Similarly, using papers' associated journal impact factors to personalise PageRank increases its field bias. In terms of performance, PageRank should always be personalised with papers' citation counts and time-rescaled for citation windows smaller than 7 to 10 years. [ABSTRACT FROM AUTHOR]

This article explores the application of DNA computing in recyclable waste paper sorting. The primary challenge in paper recycling is to obtain raw materials with the highest purity. In recycling, waste papers are segregated according to their various grades, and these are subjected to different recycling processes. Highly sorted paper streams facilitate high quality end products, while saving on processing chemicals and energy. In the industry, different sensors are used in paper sorting systems, namely, ultrasonic, lignin, gloss, stiffness, infra-red, mid-infra red, and color sensors. Different mechanical and optical paper sorting systems have been developed based on the different sensors. However, due to inadequate throughput and some major drawbacks related to mechanical paper sorting systems, the popularity of optical paper sorting systems has increased. The automated paper sorting systems offer significant advantages over the manual systems in terms of human fatigue, throughput, speed, and accuracy. This research has two objectives: (1) to use a web camera as an image sensor for the vision system in lieu of different sensors; and (2) to develop a new DNA computing algorithm based on the theme of template matching techniques for segregating recyclable waste papers according to paper grades. Using the concepts of replication and massive parallelism operations, the DNA computing algorithm can efficiently reduce the computational time of the template matching method. This is the main strength of the DNA computing algorithm in actual inspections. The algorithm is implemented by using a silicon-based computer to verify the success rate in paper grade identification. [ABSTRACT FROM AUTHOR]

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.ejor.2007.10.019 Byline: Kazuki Matsumoto (a), Hiroyoshi Miwa (b), Toshihide Ibaraki (b) Keywords: Scheduling; Corrugated paper; Complexity; Contiguous set; Integer programming Abstract: Corrugated paper is produced by gluing three types of papers of the same breadth. Given a set of orders, we first assign each order to one of the standard breadths, and then sequence those assigned to each standard breadth so that they are continuously manufactured from the three rolls of the specified standard breadth equipped in the machine called corrugator. Here we are asked to achieve multi-goals of minimizing total length of roll papers, total loss of papers caused by the differences between standard breadths and real breadths of the orders, and the number of machine stops needed during production. We use integer programming to assign orders to standard breadths, and then develop a special purpose algorithm to sequence the orders assigned to each standard breadth. This is a first attempt to handle scheduling problems of the corrugator machine. Author Affiliation: (a) Department of Applied Mathematics and Physics, Graduate School of Informatics, Kyoto University, Sakyo-ku, Kyoto 606-8501, Japan (b) Department of Informatics, School of Science and Technology, Kwansei Gakuin University, 2-1 Gakuen Sanda, Hyogo 669-1337, Japan Article History: Received 24 March 2007; Accepted 5 October 2007

One important reason for the use of field categorization in bibliometrics is the necessity to make citation impact of papers published in different scientific fields comparable with each other. Raw citations are normalized by using field-categorization schemes to achieve comparable citation scores. There are different approaches to field categorization available. They can be broadly classified as intellectual and algorithmic approaches. A paper-based algorithmically constructed classification system (ACCS) was proposed which is based on citation relations. Using a few ACCS field-specific clusters, we investigate the discriminatory power of the ACCS. The micro study focusses on the topic ‘overall water splitting’ and related topics. The first part of the study investigates intellectually whether the ACCS is able to identify papers on overall water splitting reliably and validly. Next, we compare the ACCS with (1) a paper-based intellectual (INSPEC) classification and (2) a journal-based intellectual classification (Web of Science, WoS, subject categories). In the last part of our case study, we compare the average number of citations in selected ACCS clusters (on overall water splitting and related topics) with the average citation count of publications in WoS subject categories related to these clusters. The results of this micro study question the discriminatory power of the ACCS. We recommend larger follow-up studies on broad datasets. [ABSTRACT FROM AUTHOR]

Abstract: A method for the comparison of paper structure using light transmission images and frequency analysis was developed. The resolution of the light transmission images and the algorithm for the feature extraction were greatly improved to enhance the visibility of peaks in the 2D power spectrum that results from frequency analysis. A comparison method based on correlation measures how well the spectra match as a function of the orientation of the paper, yielding an objective and quantitative measure of similarity between 0 and 1. A technical validation was carried out with 25 different papers showing the potential of this method with common copy papers. Finally, the method was applied in a case. [Copyright &y& Elsevier]

Accurate characterization is an important issue in paper currency recognition system. This paper proposes a robust paper currency recognition method based on Hidden Markov Model (HMM). By employing HMM, the texture characteristics of paper currencies are modeled as a random process. The proposed algorithm can be used for distinguishing paper currency from different countries. A similarity measure has been used for the classification in the proposed algorithm. To evaluate the performance of the proposed algorithm, experiments have been conducted on more than 100 denominations from different countries. The results indicate 98% accuracy for recognition of paper currency. [Copyright &y& Elsevier]

Abstract: More than just being a substrate, paper can also provide evidence for the provenance of documents. An earlier paper described a method to compare paper structure, based on the Fourier power spectra of light transmission images. Good results were obtained by using the 2D correlation of images derived from the power spectra as a similarity score, but the method was very computationally intensive. Different comparison algorithms are evaluated in this paper, using information theoretical criteria. An angular invariant algorithm turned out to be as effective as the original one but 4 orders of magnitude faster, making the use of much larger databases possible. [Copyright &y& Elsevier]

In the work presented in this paper, we analyse ranking algorithms that can be applied to bibliographic citation networks and rank academic entities such as papers and authors. We evaluate how well these algorithms identify important and high-impact entities. The ranking algorithms are computed on the Microsoft Academic Search (MAS) and the ACM digital library citation databases. The MAS database contains 40 million papers and over 260 million citations that span across multiple academic disciplines, while the ACM database contains 1.8 million papers from the computing literature and over 7 million citations. We evaluate the ranking algorithms by using a test data set of papers and authors that won renowned prizes at numerous computer science conferences. The results show that using citation counts is, in general, the best ranking metric to measure high-impact. However, for certain tasks, such as ranking important papers or identifying high-impact authors, algorithms based on PageRank perform better. [ABSTRACT FROM AUTHOR]

Abstract: In school, at least in the US, we were taught to multiply by hand according to a standard algorithm. Most people find that algorithm difficult to use, and many children fail to learn it. We propose a new way to make sense of this difficulty: to treat explicit computation as perceptually supported physical and mental action. Based on recent work in neuroscience, we trace the flow of arithmetic information to emphasize demands on visual working memory and attention. We predict that algorithms that make moderate demands on memory and attention will work better than others that make stronger demands. We suggest that the judicious use of spatial schemas can reduce such cognitive demands. Experimental evidence from children in an inner-city school supports this claim. Our work suggests new ways to think about instruction. The goal should be to minimize demands that present obstacles and maximize instead what human eyes, bodies, and brains do well. [Copyright &y& Elsevier]

Abstract: There are a number of issues which are involved with organizing a conference. Among these issues, assigning conference-papers to reviewers is one of the most difficult tasks. Assigning conference-papers to reviewers is automatically the most crucial part. In this paper, we address this issue of paper-to-reviewer assignment, and we propose a method to model the reviewers, based on the matching degree between the reviewers and the papers by combining a preference-based approach and a topic-based approach. We explain the assignment algorithm and show the evaluation results in comparison with the Hungarian algorithm. [Copyright &y& Elsevier]

Abstract: Recommendation algorithms have been researched extensively to help people deal with abundance of information. In recent years, the incorporation of multiple relevance criteria has attracted increased interest. Such multi-criteria recommendation approaches are researched as a paradigm for building intelligent systems that can be tailored to multiple interest indicators of end-users – such as combinations of implicit and explicit interest indicators in the form of ratings or ratings on multiple relevance dimensions. Nevertheless, evaluation of these recommendation techniques in the context of real-life applications still remains rather limited. Previous studies dealing with the evaluation of recommender systems have outlined that the performance of such algorithms is often dependent on the dataset – and indicate the importance of carrying out careful testing and parameterization. Especially when looking at large scale datasets, it becomes very difficult to deploy evaluation methods that may help in assessing the effect that different system components have to the overall design. In this paper, we study how layered evaluation can be applied for the case of a multi-criteria recommendation service that we plan to deploy for paper recommendation using the Mendeley dataset. The paper introduces layered evaluation and suggests two experiments that may help assess the components of the envisaged system separately. [Copyright &y& Elsevier]

Abstract: A new approach of paper defect recognition is proposed. To implement this method, computer is used to acquire paper image and the subtraction algorithm is used to determine if the image contains defect at first. For the image with paper defect, wavelet packet decomposition is applied to extracting the feature vector of the defect. A BP neural network is designed for recognizing the defect type according to the feature vector. This approach provides a unified detection algorithm for different types of paper defects. The experiment data prove this method is valid and can be applied in modern paper defect inspection system. [Copyright &y& Elsevier]

Abstract: The paper describes a system for executable papers for publishers enabling them to reuse content and to generate further advances of science and engineering. The executable algorithmic descriptions within a paper are presented in natural language sentences and basic code, thereby making long term compatibility absolute. Authors are required to use publicly numerical libraries on the Internet or references to publications with executable papers. As used by authors the system automatically creates a web of algorithmic knowledge on the Internet. Novelty of new algorithms in publications can be evaluated by automated tools available to authors, reviewers and readers of scientific papers published. [Copyright &y& Elsevier]

Abstract: This paper studies how missing data in the PageRank algorithm influences the result of papers ranking and proposes PrestigeRank algorithm on that basis. We make use of PrestigeRank to give the ranking of all papers in physics in the Chinese Scientific and Technology Papers and Citation Database (CSTPCD) published between 2004 and 2006. We compared PrestigeRank result with PageRank and citation ranking. We found PrestigeRank is significantly correlated with PageRank and citation counts. We also used paper citation networks to rank journals, and compared the result with that of journal citation networks. We proposed PR sum , PR ave , and compared both of them with citation counts and impact factor. It indicates PR sum , PR ave can reflect journal''s authority favorably. We also discuss the advantages and disadvantages, application scope and application prospects of PrestigeRank in the evaluation of papers and journals. [Copyright &y& Elsevier]

Abstract: A lot of work has been done in the field of multi-valued model checking home and abroad. But some research works are not perfect. Some problems in the semantic definitions of temporal operators and corresponding model checking algorithms are found in the paper “Model Checking Using Partial Kripke Structure with 3-Valued Temporal Logic”. Some counterexamples are given to show these errors. On the basis of the discussion, some sound semantic definitions of temporal operators and correct algorithms of model checking for some temporal operators are given. [Copyright &y& Elsevier]

Abstract: Combining previous image mosaicing algorithms, this paper puts forward a kind of damaged text restore image processing algorithm. The algorithm can restore the shredder pieces tape. A series of tapes which are obtained by scanner are treated through image processing such as binary, segmentation, denoising and enhancement and so on, Then we can get the ideal original text image from some leaflet tapes image. Experimental results show that such algorithm has certain effectiveness. [Copyright &y& Elsevier]

• We compare the performance of global metrics and their local variants in the identification of expert-selected milestone papers on two distinct citation datasets. • We obtain a family of local variants of PageRank (LeaderRank) with a tunable degree of locality and find they can generate highly correlated scores with the scores by the original metrics. • The local variants of PageRank (LeaderRank) perform similarly well as the original global PageRank (LeaderRank) algorithms in the identification of seminal papers. • The local variants of PageRank (LeaderRank) perform significantly better than local metrics such as citation count, h-index and semi-local centrality. • Compared to network-based global metrics, the proposed local estimates provide a better trade-off between performance and computational efficiency. Recent works aimed to understand how to identify "milestone" scientific papers of great significance from large-scale citation networks. To this end, previous results found that global ranking metrics that take into account the whole network structure (such as Google's PageRank) outperform local metrics such as the citation count. Here, we show that by leveraging the recursive equation that defines the PageRank algorithm, we can propose a family of local impact metrics. Our results reveal that the obtained PageRank-based local metrics outperform the citation count and other local metrics in identifying the seminal papers. Compared with global metrics, these local metrics can reach similar performance in the identification of seminal papers in shorter computational time, without requiring the whole network topology. Our findings could help to better understand the nature of groundbreaking research from citation network analysis and find practical applications in large-scale data. [ABSTRACT FROM AUTHOR]

Abstract: The automatic control of product moisture content in the paper industry is based upon online moisture measurement. Furthermore, the automatic control of other quality variables such as coat weight may also rely on the moisture measurement. The integrity of infrared radiation (IR) based online moisture measurement systems was studied by performing basic calibrations at the mills with references sealed between two glass plates. The calibrations were performed according to the EN ISO/IEC 17025 standard which is a requirement for calibration laboratories. The observed measurement errors were 2.9% moisture in the first time calibrations at the 95% confidence level. It is demonstrated that these errors can be reduced to under 0.5% moisture by applying traceable methods in the basic calibration, thus improving the integrity of online moisture measurements. Also a standardised algorithm, based on the experience from the performed calibrations, is proposed to ease the adjustment of different moisture measurement systems. [Copyright &y& Elsevier]

The present comment concerns the correct presentation of an algorithm proposed in the above paper for the glow-curve deconvolution in the case of continuous distribution of trapping states. Since most researchers would use directly the proposed algorithm as published, they should be notified of its correct formulation during the fitting of TL glow curves of materials with continuous trap distribution using this Equation. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) powered by high level synthesis (HLS) provides huge opportunity of progress in the area of hardware design. However, the present era of hardware design involves globalization which poses security threat to the design integrators that rely on third party intellectual property (IP) cores for increasing design productivity at reduced design time. This paper presents for the first time in the literature, a low cost optimized hardware Trojan secured HLS approach for hardware (or application specific core) designs that is based on single or nested loop control data flow graphs (CDFG) applications. The paper presents multiple novel vendor allocation schemes (each with its own attribute of delay and area) as security constraint that yield Trojan secured schedules at behavioral level. Demonstration of the proposed approach on a nested loop case study asserts our proposed theory. Results on standard benchmarks indicate significant reduction in final solution cost compared to a similar approach. [ABSTRACT FROM AUTHOR]

Academic research is crucial to the development of science and technology and is an important factor that affects national strength. When writing an academic research paper, a rhetorical structure is typically used to present the paper's ideas, but this task is quite difficult for junior researchers. To solve this problem, some studies have adopted text mining to assist with the writing, but the existing methods still require human intervention to generate sentences. Recently, due to the increasing maturity of deep learning technology and the ability to address the problem of automatic text generation, progress has been made in this area. The highly complex deep learning operations can correctly generate sequences and find correlations between sequences. When a user provides a few keywords and key sentences, the proposed algorithm can generate an introduction section for the user. The results show that the generated introduction is more coherent, clearer, and more fluent than existing summarization methods. In addition, the method proposed in this study improves the accuracy compared with traditional text extraction methods. The manuscript produced by this study has been evaluated to show that the study can produce a comprehensive introduction compared with previous studies. • The proposed framework can generate a comprehensive introduction based on users' brief inputs. • This paper demonstrates a three-testing-threshold approach to check the content quality. • The introduction generated through this method has less than 3% similarity to the original text by comparison. [ABSTRACT FROM AUTHOR]

Abstract: Surface roughness is one of the most important attributes of paper and its measurement is normally used in quality control applications. Currently, measurement of surface roughness is done by using air leakage, optical, or subjective methods. In this article, an acoustical method for the determination of surface roughness of papers is described. The method is applied off-line and uses the friction noise recorded when a small brush slide over the surface of the paper. The analysis is done consider the friction noise ranging from 300Hz to 10kHz. Considering that friction noise is associated to surface roughness, a signal analysis algorithm was developed to take advantage of this fact. The algorithm consists of a frequency-domain feature extraction routine and an artificial neural network that represents the variation of the spectral features in a roughness scale. The results show that an affordable and efficient friction noise based system can be used for measuring surface roughness of tissue papers and other soft surfaces as an alternative to other methods. [Copyright &y& Elsevier]

Abstract: We introduce an algorithm for approximating a 2-manifold 3D mesh by a set of developable surfaces. Each developable surface is a generalized cylinder represented as a strip of triangles not necessarily taken from the original mesh. Our algorithm is automatic, creates easy-to-assemble pieces, and provides global error bounds. The algorithm consists of three stages. In the first stage, the mesh is segmented into meaningful components. The second stage approximates each of the mesh components in 3D by a set of triangle strips with smooth (non-jagged) boundaries that guarantee a maximal user-defined error relative to the original mesh. Finally, these strips are unfolded to the plane, resulting in flat patterns, which may be cut and assembled from paper. The approximation quality is controlled by a user-supplied parameter specifying the allowed Hausdorff distance between the input mesh and its piecewise-developable approximation. The strips generated by our algorithm may be parameterized to conform with the parameterization of the original mesh, if given, to facilitate texture mapping. We demonstrate this by physically assembling paper-craft models from the strips generated by our algorithm when run on several polygonal 3D mesh data sets. [Copyright &y& Elsevier]

Abstract: In this paper, we focus on the proposed algorithms to solve a linear programming problem with the convex combination of the max–min and the max–average composition and the max–star composition, respectively. They have been proposed by Ghodousian and Khorram [A. Ghodousian, E. Khorram, Solving a linear programming problem with the convex combination of the max–min and the max–average fuzzy relation equations, Appl. Math. Comput. 180 (2006) 411–418] and Khorram et al. [E. Khorram, A. Ghodousian, A. Abbasi Molai, Solving linear optimization problems with max–star composition equation constraints, Appl. Math. Comput. 179 (2006) 654–661], respectively. Firstly, we show that the “Tabular method algorithm” in the first paper and the “First procedure” in the second paper may not lead to the optimal solutions of the two models in some cases. Secondly, we generalize the proposed algorithm by Abbasi Molai and Khorram [A. Abbasi Molai, E. Khorram, A modified algorithm for solving the proposed models by Ghodousian and Khorram and Khorram and Ghodousian, Appl. Math. Comput. 190 (2007) 1161–1167] to solve the two models. In fact, it modifies the presented algorithms in the two papers. Finally, some numerical examples are given to illustrate the purposes. [Copyright &y& Elsevier]

This paper introduces a new approach for improving the performance and versatility of Layered Manufacturing (LM), which is an emerging technology that makes it possible to build physical prototypes of 3D parts directly from their computer models using a “3D printer” attached to a personal computer.Current LM processes work by viewing the computer model as a single, monolithic unit. By contrast, the approach proposed here decomposes the model into a small number of pieces, by intersecting it with a suitably chosen plane, builds each piece separately using LM, and then glues the pieces together to obtain the physical prototype. This approach allows large models to be built quickly in parallel. Furthermore, it is very efficient in its use of so-called support structures that are generated by the LM process.This paper presents the first provably correct and efficient geometric algorithms to decompose polyhedral models so that the support requirements (support volume and area of contact) are minimized. Algorithms based on the plane-sweep paradigm are first given for convex polyhedra. These algorithms run in O(nlogn) time for n-vertex convex polyhedra and work by generating expressions for the support volume and contact-area as a function of the height of the sweep plane, and optimizing them during the sweep. These algorithms are then generalized to non-convex polyhedra, which are considerably more difficult due to the complex structure of the supports. It is shown that, surprisingly, non-convex polyhedra can be handled by first identifying certain critical facets using a technique called cylindrical decomposition, and then applying the algorithm for convex polyhedra to these critical facets. The resulting algorithms run in O(n2logn) time. Also given is a method for controlling the size of the decomposition, so that the number of pieces generated is within a user-specified limit. Experimental results show that the proposed approach can achieve significant reduction in support requirements in both the convex and the non-convex case. [Copyright &y& Elsevier]

Abstract: In this paper we provide a computational approach to the shape of curves which are rational in polar coordinates, i.e. which are defined by means of a parametrization where both , are rational functions. Our study includes theoretical aspects on the shape of these curves, and algorithmic results which eventually lead to an algorithm for plotting the “interesting parts” of the curve, i.e. the parts showing the main geometrical features. [Copyright &y& Elsevier]

[Display omitted] • Two colorimetric paper-based sensors for creatinine determination are developed. • Signal readout is achieved with a smartphone with a self-written application. • App relies on computer-vision to enable automatic detection of the zone of interest. • The utility of the platform to determine creatinine in undiluted urine is proved. Creatinine is a clinically significant analyte used to diagnose kidney condition. However, the literature still lacks in creatinine sensors fulfilling point-of-care testing requirements. In this paper, we have developed colorimetric paper-based creatinine sensors adhering to point-of-care testing principles. The signal readout is accomplished with a smartphone modified with 3D-printed elements and processed with a self-written application compromising computer vision algorithm for automatic detection of the colored zone. Two colorimetric methods – routinely used Jaffé method and an alternative one with 3,5-dinitrobenzoic acid were both tested and compared. Hue channel intensity from HSV color space and green channel from RGB color space was used as the analytical signal in Jaffé and 3,5-dinitrobenzoate method, respectively. For both kinds of sensors the linear range of the response covered the range significant for urinary analysis, with precision, expressed as RSD, below 5%. Limit of quantification for Jaffé method was 1.05 mmol·L−1 whereas it was 0.82 mmol·L−1 for 3,5-dinitrobenzoate method. The utility of the developed sensors to selectively quantify creatinine in undiluted urine was proved using artificial urine samples and the obtained recoveries were in the range from 70 to 129 %. [ABSTRACT FROM AUTHOR]

Abstract: In-cell adaptive touch technology for use in an electrophoretic display (EPD) has been developed and implemented in 11.5in. UXGA flexible electronic paper display. Here, two types of a-Si:H photo-sensor arrays fabricated on a stainless steel substrate at the process temperature of 250°C have been used along with an overall capacitive sensor formed on top of the flexible panel. Thus, we can resolve the sensing issue of normal photo-sensor array as well as maintain the feature of low power consumption in the EPD. Moreover, new touch algorithm adapted depending upon the amount of light intensity has been applied to enhance touch sensitivity regardless of environmental light conditions. [ABSTRACT FROM AUTHOR]

Abstract: In a recent paper (Computer Aided Geometric Design 23 (3), 243–260), Yang presented a novel kind of nonlinear and geometry driven subdivision scheme for curve interpolation. The author declared that this scheme was shape preserving when all free parameters were explicitly selected by some specific rules. In this note, we demonstrate that the author (a) ignored the consistency of the definition to straight edges, and also (b) did not give a perfect scheme and proof for the shape preserving subdivision. [Copyright &y& Elsevier]

Most classification algorithms are “passive”, in that they assign a class label to each instance based only on the description given, even if that description is incomplete. By contrast, an active classifier can—at some cost—obtain the values of some unspecified attributes, before deciding upon a class label. This can be useful, for instance, when deciding whether to gather information relevant to a medical procedure or experiment. The expected utility of using an active classifier depends on both the cost required to obtain the values of additional attributes and the penalty incurred if the classifier outputs the wrong classification. This paper analyzes the problem of learning optimal active classifiers, using a variant of the probably-approximately-correct (PAC) model. After defining the framework, we show that this task can be achieved efficiently when the active classifier is allowed to perform only (at most) a constant number of tests. We then show that, in more general environments, this task of learning optimal active classifiers is often intractable. [Copyright &y& Elsevier]

Cutting force is a significant indicator for in-process monitoring of cutting status. Although dynamometers are widely used in cutting force measurement, they are not suitable for nano-cutting due to insufficient sensitivities and low integrating possibilities. This paper presents a smart tool holder composed by piezoelectric ceramics and a flexible hinge, which could be integrated with a fast tool servo (FTS), for three-axial cutting force measurements in micro/nano-cutting. An algorithm was developed for enabling its quasi-static force measurement. Experiments were performed to verify the capabilities of cutting force measurement, demonstrating a high measurement sensitivity for indicating the micro/nano-cutting status. [ABSTRACT FROM AUTHOR]

Abstract: Introduction: Guidelines for the treatment of patients in severe hypothermia and mainly in hypothermic cardiac arrest recommend the rewarming using the extracorporeal circulation (ECC). However, guidelines for the further in-hospital diagnostic and therapeutic approach of these patients, who often suffer from additional injuries—especially in avalanche casualties, are lacking. Lack of such algorithms may relevantly delay treatment and put patients at further risk. Together with a multidisciplinary team, the Emergency Department at the University Hospital in Bern, a level I trauma centre, created an algorithm for the in-hospital treatment of patients with hypothermic cardiac arrest. This algorithm primarily focuses on the decision-making process for the administration of ECC. The Bernese Hypothermia Algorithm: The major difference between the traditional approach, where all hypothermic patients are primarily admitted to the emergency centre, and our new algorithm is that hypothermic cardiac arrest patients without obvious signs of severe trauma are taken to the operating theatre without delay. Subsequently, the interdisciplinary team decides whether to rewarm the patient using ECC based on a standard clinical trauma assessment, serum potassium levels, core body temperature, sonographic examinations of the abdomen, pleural space, and pericardium, as well as a pelvic X-ray, if needed. During ECC, sonography is repeated and haemodynamic function as well as haemoglobin levels are regularly monitored. Standard radiological investigations according to the local multiple trauma protocol are performed only after ECC. Transfer to the intensive care unit, where mild therapeutic hypothermia is maintained for another 12h, should not be delayed by additional X-rays for minor injuries. Discussion: The presented algorithm is intended to facilitate in-hospital decision-making and shorten the door-to-reperfusion time for patients with hypothermic cardiac arrest. It was the result of intensive collaboration between different specialties and highlights the importance of high-quality teamwork for rare cases of severe accidental hypothermia. Information derived from the new International Hypothermia Registry will help to answer open questions and further optimize the algorithm. [Copyright &y& Elsevier]

Abstract: The aim of this note is to show that the optimization algorithm proposed in may not lead to the optimal solution in some cases. In fact, the optimization problem remains open if we do not apply the branch-and-bound method to solve it or compute all the objective values of minimal solutions of the feasible domain. [Copyright &y& Elsevier]

The smart car collects the signal through the infrared sensor, and obtains the gray map in front of the car, according to the gray map, the tracking is judged.Due to the complexity of the environment, many gray-scale maps are difficult to trace, and even cannot be judged, which brings great uncertainty to the operation of the smart car.The paper designs a method to improve the infrared tracking accuracy of smart cars.First, determine the level of contrast in this graph.By improving the brightness in the grayscale image, the gray signal around the tracking line is eliminated, and then the tracking line is highlighted by increasing the contrast.Therefore, it effectively overcomes the shortcomings of poor practicality of smart cars and improves the infrared tracking accuracy of smart cars. [ABSTRACT FROM AUTHOR]

Abstract: In this paper we present a novel approximate algorithm to calculate the top-k closest pairs join query of two large and high dimensional data sets. The algorithm has worst case time complexity and space complexity and guarantees a solution within a factor of the exact one, where t ∈{1,2,…,∞} denotes the Minkowski metrics L t of interest and d the dimensionality. It makes use of the concept of space filling curve to establish an order between the points of the space and performs at most d +1 sorts and scans of the two data sets. During a scan, each point from one data set is compared with its closest points, according to the space filling curve order, in the other data set and points whose contribution to the solution has already been analyzed are detected and eliminated. Experimental results on real and synthetic data sets show that our algorithm behaves as an exact algorithm in low dimensional spaces; it is able to prune the entire (or a considerable fraction of the) data set even for high dimensions if certain separation conditions are satisfied; in any case it returns a solution within a small error to the exact one. [Copyright &y& Elsevier]

There are two well known transformations from non-binary constraints to binary constraints applicable to constraint satisfaction problems (CSPs) with finite domains: the dual transformation and the hidden (variable) transformation. We perform a detailed formal comparison of these two transformations. Our comparison focuses on two backtracking algorithms that maintain a local consistency property at each node in their search tree: the forward checking and maintaining arc consistency algorithms. We first compare local consistency techniques such as arc consistency in terms of their inferential power when they are applied to the original (non-binary) formulation and to each of its binary transformations. For example, we prove that enforcing arc consistency on the original formulation is equivalent to enforcing it on the hidden transformation. We then extend these results to the two backtracking algorithms. We are able to give either a theoretical bound on how much one formulation is better than another, or examples that show such a bound does not exist. For example, we prove that the performance of the forward checking algorithm applied to the hidden transformation of a problem is within a polynomial bound of the performance of the same algorithm applied to the dual transformation of the problem. Our results can be used to help decide if applying one of these transformations to all (or part) of a constraint satisfaction model would be beneficial. [Copyright &y& Elsevier]

Highlights Although fabrication of colorimetric paper-based analytical devices (PADs) has drawn increasing attention recently, the signal readout method is still a crucial challenge on the way to practical exploitations. We herein introduce an integration of digital image processing with a model PAD for easing and improving the signal readout procedure. The colorimetric detection mechanism of PAD relies on in-situ induced yellowish silver nanoparticles via the interaction of silver ions, poly(vinyl alcohol), and ammonia with isoniazid. The observed color value is related with the concentration of isoniazid. The proposed algorithm is based on mathematical morphology recognition, and minimizes the errors arising from manual area selection. Besides, it allows the recognition of both circle and square shapes in 96-well plate and A4 size array designs. Since this algorithm automatically provides the blank-corrected numerical matrixes and image profiles of red, green and blue channels, further investigations such as outlier classification, construction of regression/prediction models and calculation of detection limit can be easily performed. Comparison of signal readout results of the developed algorithm with ImageJ software demonstrates significant improvements in analysis speed, reproducibility, accuracy and color values. Therefore, application of the proposed algorithm is promising as a robust technique for practical applications. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, two examples are given where the cluster labeling algorithm of Al-Futaisi and Patzek for arbitrary networks produces incorrect results. The reason for this is pointed out, and an improvement to the algorithm is proposed so that such errors can be avoided in future. [Copyright &y& Elsevier]

Abstract: For positive integers , an -labeling of a digraph D is a function f from into the set of nonnegative integers such that if x is adjacent to y in D and if x is of distance two to y in D. Elements of the image of f are called labels. The -labeling problem is to determine the -number of a digraph D, which is the minimum of the maximum label used in an -labeling of D. This paper studies -numbers of digraphs. In particular, we determine -numbers of digraphs whose longest dipath is of length at most 2, and -numbers of ditrees having dipaths of length 4. We also give bounds for -numbers of bipartite digraphs whose longest dipath is of length 3. Finally, we present a linear-time algorithm for determining -numbers of ditrees whose longest dipath is of length 3. [Copyright &y& Elsevier]

Abstract: In this paper, we will derive a solver for a symmetric strongly nonsingular higher order generator representable semiseparable plus band matrix. The solver we will derive is based on the Levinson algorithm, which is used for solving strongly nonsingular Toeplitz systems. In the first part an solver for a semiseparable matrix of semiseparability rank p is derived, and in a second part we derive an solver for a band matrix with bandwidth . Both solvers are constructed in a similar way: firstly a Yule–Walker-like equation needs to be solved, and secondly this solution is used for solving a linear equation with an arbitrary right-hand side. Finally, a combination of the above methods is presented to solve linear systems with semiseparable plus band coefficient matrices. The overall complexity of this solver is plus lower order terms. In the final section numerical experiments are performed. Attention is paid to the timing and the accuracy of the described methods. [Copyright &y& Elsevier]

Abstract: Any set of C 2 planar boundary data (two points with associated velocities and acceleration vectors) can be interpolated by a PH curve of degree 9. In the generic case there are four such curves [R.T. Farouki, J. Manjunathaiah, S. Jee, Design of rational cam profiles with Pythagorean Hodograph curves, Mech. Mach. Theory 33 (1998) 669–682]. In this paper we give a detailed description and a qualitative analysis of these solutions. In particular we label the four solutions and compare their fairness from the point of view of possible application. For this purpose we consider the Hermite data taken from an analytical curve and study the behavior of the solutions for decreasing step-size h. This allows us to identify explicitly the solution which—for sufficiently small step-size—matches the shape of the curve with a high precision (the approximation order is 6). Consequently we are able to develop a highly robust, fast and precise algorithm converting analytical curves or curves described in G-code into a C 2 continuous PH spline curve of degree 9. [Copyright &y& Elsevier]

Consistency control at the outlet of blow tanks and hi-density towers, the so-called double-dilution problem, is an area where further control development is needed. The task is to coordinate the manipulation of two input variables, coarse and fine dilution, to control the consistency, while simultaneously mid-ranging the fine dilution to keep it from saturating. This is made difficult by process nonlinearities, complex dynamics and tight manipulated variable saturation constraints. To address these problems, a model-based predictive controller (MPC) was applied to blow tank consistency control in a pulp mill. One of the unique features of the proposed MPC algorithm is that it is well suited to run on standard distributed control system (DCS) hardware of the type that already exists in most process plants. Several control strategies were tested, including MPC and the previously implemented scheme, with and without a ratio control scheme aimed at removing the dominant process nonlinearity. The results of a mill trial indicate that both controllers, when implemented as ratio controllers, give excellent disturbance rejection for production rate changes, keeping the consistency within 0.1% of target. However, MPC outperformed the conventional strategy in its response to setpoint changes and unmeasured disturbances, and was able to cope with actuator failure. [Copyright &y& Elsevier]

The present paper studies digital topological rough set structures associated with Khalimsky (K -, for brevity) topology. We further explore their properties related to topological (closure and interior) operators. In addition, we find that the K -topological rough set structures have their own features different from certain theoretical properties of the H -rough set structure in [9] w.r.t. the topological operators. More precisely, whereas the H -rough set structure is a topological operator, K -topological concept approximations are proved not to be topological operators. Thus, this paper proposes an alternative approach to the K -topological concept approximations so that we finally have new types of topological operators. Furthermore, it appears that this new ones are smoothly matched with the earlier H -rough set structure from the viewpoint of topological operators. Therefore, they can facilitate the study of continuous-oriented or digital-oriented rough sets, which can be used in applied sciences without any limitations of the cardinalities of the universe and a target set. Besides, they can support certain decision rules with no restriction to anything continuous or discrete (or digital). In addition, we introduce the notion of K -definability of a target subset of a universal set and write an algorithm for estimating the roughness of the above new concept approximations. In this paper each set need not be finite and a covering is locally finite. [ABSTRACT FROM AUTHOR]