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In the tourism industry, the sales of local specialties is an important part, and the package design and integrity of the specialties are very important. This paper first introduced the support vector machine (SVM) algorithm that was used for detecting defects on the surface of paper packages. Then, the design of red wind packages was briefly described, and the simulation experiment was carried out on SVM algorithm using red wine packages with different degrees of surface defects. Proper parameters were tested using the k-fold cross-validation method. The results demonstrated that the properties of paper improved the value of packages and the SVM algorithm had better accuracy than artificial recognition in recognizing different degrees of defects on the surface of packages. In conclusion, this paper describes the application of paper in packages and provides an effective method for the defection of defects on the surface of packages. This study provides an effective references to the improvement of package values and the enhancement of package integrity.

In this paper, we present a system for automatic evaluation of the quality of a question paper. Question paper plays a major role in educational assessment. The quality of a question paper is crucial to fulfilling the purpose of the assessment. In many education sectors, question papers are prepared manually. A prior analysis of a question paper might help in finding the errors in the question paper, and better achieving the goals of the assessment. In this experiment, we focus on higher education in the technical domain. First, we conducted a student survey to identify the key factors that affect the quality of a question paper. The top factors we identified are question relevance, question difficulty, and time requirement. We explored the strategies to handle these factors and implemented them. We employ various concepts and techniques for the implementation. The system finally assigns a numerical quality score against these factors. The system is evaluated using a set of question papers collected from various sources. The experimental results show that the proposed system is quite promising.

PurposeThis study develops an integrated zero waste discharge planning approach for improving resource efficiency in a pulp-and-paper manufacturing firm.Design/methodology/approachThe objectives of this study are to (1) identify the environmental, technical and social metrics in resource efficiency; (2) utilize fuzzy multi-objective programming and the hybrid particle swarm optimization algorithm to solve the fuzzy problem; and (3) develop an assessment for resource efficiency improvement in an industrial case study.FindingsThe findings demonstrate the superiority of hybrid particle swarm optimization algorithm in generating optimal results for a pulp-and-paper manufacturing firm.Practical implicationsThe findings demonstrate the superiority of hybrid particle swarm optimization algorithm in generating optimal results for a pulp-and-paper manufacturing firm.Originality/valueResource efficiency is a multi-objective problem in an uncertain environment. In particular, zero waste discharge planning involves minimizing the total cost and maximizing the waste material recovery rate, wastewater reuse, and waste heat recovery.

In society, there is widespread and growing acceptance of the value of cooperation between industry and universities being collaborative Research and Development (R&D) domain and industrial policy the fuel of knowledge-based economies. In this paper, different domains of cooperation between the University and Industry as well as their generated benefits for each partner are identified. These benefits have been assigned to each domain of cooperation, showing a large number of benefits associated to collaborative R&D. Leading us to make a statement - collaborative R&D is the key cooperation domain for sustainable long-term university-industry partnerships. Suggestions are given about how to continue this research study.

Paper folding-and-punching tests are used to measure spatial abilities in humans. This paper presents a qualitative model for paper folding (QPF) and a computer game (Paper Folding Game) developed to apply and show the reasoning capabilities of the QPF model. This interactive game presents paper-folding activities intended to help users train and understand how to fold a paper to get a specific shape. Then, it presents paper-folding-and-punching tests to the players. The Paper Folding Game can automatically generate paper-folding-and-punching questions with varying degrees of difficulty depending on the number of folds and holes made, thus producing additional levels for training. The reasoning mechanisms in the QPF model are used by the Paper Folding Game to infer the right answer to each paper-folding-and-punching question. This reasoning capability allows the game to provide feedback to the players when they are wrong and also to create other plausible answers automatically, so that random question-answers are shown to the players in the master-mode. The Paper Folding Game has been implemented using Unity engine and it is available to download from GooglePlay and AppleStore for everyone to train their spatial reasoning skills.

We present a short review of several fundamental results, which have been obtained within frameworks of one trend of the wide spread of investigations, carried out during 1970 –2010s under the leadership of doctor of science, corresponding member of the National Academy of Sciences of Belarus P. D. Kukharchik, whose scientific interests were connected with the study of physical properties of heterogeneous dielectric and metal-containing industrial materials by the methods of holography, holographotomography, digital radiography, microwave and infrared introscopy. In this review, by the example of several base problems, we describe the semi-analytical methods of rigorous theoretical simulation of electromagnetic fields, arising under electromagnetic diffraction by slots in perfectly conducting screens of arbitrary thickness in absence and in the presence of plane dielectrics in the plane and cylindrical geometries of electromagnetic propagation. It demonstrates application of the these methods to simulation of processes of moisture measuring of paper sheet using microwave cavities with slots, which are employed on enterprises of pulp and paper industry.

In recent history, the Panama Papers have comprised one of the largest and most influential leaks detailing information on offshore entities, company officers and financial (and legal) intermediaries, and has led to a global exposé of corruption and tax evasion. A systematic analysis of this information can provide valuable insights into the structure and properties of these entities and the relations between them. Network science can be applied as a scientific framework for understanding the structure of such relational, heterogeneous datasets at scale. In this article, we use an existing, relational version of the Panama Papers to selectively construct various networks, and then study the properties of the underlying system using well-defined analytical methods from network science, including degree properties, country assortativity analyses, connectivity and single-point network metrics like transitivity and density. We also illustrate significant structural features in these networks by conducting a triad census and exploring the networks’ core-periphery structure. Together, these results are used to show that the Panama Papers constitute a distinct class of networks that differ significantly from ordinary social and information networks. We also propose, construct and analyze ‘higher-order’ networks from the raw data, such as a ‘social’ network of officers. We confirm that some of these higher-order networks also show significant non-random deviations from expected or typical behavior, including in their degree distributions.

The recycling of waste paper has been an effective way to achieve the environmental-friendly growth of papermaking industry. Focusing on the mixed-pulping process which has been generally employed, to ensure the required properties of the deinking pulp (DIP) and minimize the purchase cost of waste paper, an intelligent model scheduling the mixing ratio of waste paper was developed in the study. Primarily, driven by the field data of mixing ratio of waste paper and DIP properties, the prediction models of DIP properties were developed by SVM, GA-SVM, and BP-NN algorithms. Subsequently, based on the best prediction model, the scheduling model for the mixing ratio of waste paper was set up by NSGAII algorithm. The experimental results showed that, based on the obtained best BP-NN prediction model of DIP properties, the developed NSGAII scheduling model for the ratio of waste paper could achieve excellent scheduling results under the rigorous constraints and multi-objective. Compared with the previous study, the developed prediction and scheduling models in this study reduced the purchase cost of waste paper by 2.16%, and improved the acceptable proportion of DIP property from 56.07% to 100%.

Abstract writing is a very important since it is the piece of formal writing which should attract the attention of the reader and make him/her read the rest of the paper. Thus, it must be clear, concise, coherent, and powerful enough to attract the reader and provide him/her with the key information about the content of a research paper. All university students have to write an abstract in English in their qualification papers. However, non-native students of English usually have difficulties in writing an abstract in English. For example, the Czech students lack formal writing skills in English since the skill of formal writing is not developed enough in their native language, i.e. Czech. Therefore, the aim of this article is to discuss the use of an off-line scaffolding tool, which can help students develop an abstract in English, as well as to demonstrate how this tool can be incorporated in the whole Course of Practical English taught at the Faculty of Informatics and Management of the University of Hradec Kralove in the Czech Republic. The application was developed for students as support to a face-to-face class instruction, which proved to be insufficient in teaching students how to write an abstract in English. The application reflects the structure and sentence functions of the abstract and provides students with a model abstract, as well as with additional formulations. Overall, the application was designed with the purpose to enhance student’s skill of writing an abstract in English, as well as to lead students to successfully complete the task by making the application user-friendly - easy-to-use, accessible and transferrable as far as the knowledge is concerned. The application aims to enhance students’ autonomous learning by tailoring the content to their specific needs and making it accessible anytime and from anywhere.

This paper presents the design and analysis of a paper-based chipless RFID sensor for wetness content measurement in plant leaves. The sensor is designed using a passive microwave resonator to measure the ambient physical parameter. The resonator is designed with a rectangular loop inductively coupled with an interdigital capacitor. The experimental analysis of the designed sensor is illustrated here to prove its efficacy. The resonator provides adequate backscattered signal for wireless measurement in the microwave frequency band. When interrogated with a couple of UWB antennas and a VNA, it yields accurate leaf wetness response of the plant. The commercial competence of this sensing device is validated through its experimental analysis on three different types of leaf samples. This sensor is suitable for plant health monitoring in any small-scale gardening applications such as nurseries and greenhouses.

The Gaussian wiretap channel with noncausal state interference available at the transmitter, which is also called the dirty paper wiretap channel (DP-WTC), has been extensively studied in the literature. Recently, it has been shown that taking actions on the corrupted state interference of the DP-WTC (also called the action-dependent DP-WTC) helps to increase the secrecy capacity of the DP-WTC. Subsequently, it has been shown that channel feedback further increases the secrecy capacity of the action-dependent DP-WTC (AD-DP-WTC), and a sub-optimal feedback scheme is proposed for this feedback model. In this paper, a two-step hybrid scheme and a corresponding new lower bound on the secrecy capacity of the AD-DP-WTC with noiseless feedback are proposed. The proposed new lower bound is shown to be optimal (achieving the secrecy capacity) and tighter than the existing one in the literature for some cases, and the results of this paper are further explained via numerical examples.

Rapid increase in scholarly publications on the web has posed a new challenge to the researchers in finding highly relevant and important research articles associated with a particular area of interest. Even a highly relevant paper is sometimes missed especially for novice researchers due to lack of knowledge and experience in finding and accessing the most suitable articles. Scholarly recommender system is a very appropriate tool for this purpose that can enable researchers to locate relevant publications easily and quickly. However, the main downside of the existing approaches is that their effectiveness is dependent on priori user profiles and thus, they cannot recommend papers to the new users. Furthermore, the system uses both public and non-public metadata and therefore, the system is unable to find similarities between papers efficiently due to copyright restrictions. Considering the above challenges, in this research work, a novel hybrid approach is proposed that separately combines a Content Based Filtering (CBF) recommender module and a Collaborative Filtering (CF) recommender module. Unlike previous CBF and CF approaches, public contextual metadata and paper-citation relationship information are effectively incorporated into these two approaches separately to enhance the recommendation accuracy. In order to verify the effectiveness of the proposed approach, publicly available datasets were employed. Experimental results demonstrate that the proposed approach outperforms the baseline approaches in terms of standard metrics (precision, recall, F1-measure, mean average precision, and mean reciprocal rank), indicating that the proposed approach is more efficient in recommending scholarly publications.

International audience; This paper focuses on the problem of the hierarchical multi‐label classification of research papers, which is the task of assigning the set of relevant labels for a paper from a hierarchy, using reduced amounts of labelled training data. Specifically, we study leveraging unlabelled data, which are usually plentiful and easy to collect, in addition to the few available labelled ones in a semi‐supervised learning framework for achieving better performance results. Thus, in this paper, we propose a semi‐supervised approach for the hierarchical multi‐label classification task of research papers based on the well‐known Co‐training algorithm, which exploit content and bibliographic coupling information as two distinct papers' views. In our approach, two hierarchical multi‐label classifiers, are learnt on different views of the labelled data, and iteratively select their most confident unlabelled samples, which are further added to the labelled set. The success of our suggested Co‐training‐based approach lies in two main components. The first is the use of two suggested selection criteria (i.e., Maximum Agreement and Labels Cardinality Consistency) that enforce selecting confident unlabelled samples. The second is the appliance of an oversampling method that rebalances the labels distribution of the initial labelled set, which reduces the reinforcement of the label imbalance issue during the Co‐training learning. The proposed approach is evaluated using a collection of scientific papers extracted from the ACM digital library. Performed experiments show the effectiveness of our approach with regards to several baseline methods.

When conducting a search for research papers, the search should return comprehensive results related to the user’s query. In general, a user inputs a Boolean query that reflects the information need, and the search engine ranks the research papers based on the query. However, it is difficult to anticipate all possible terms that authors of relevant papers might have used. Moreover, general query-based ranking methods emphasize how to rank the relevant documents at the top of the results, but require some means of guaranteeing the comprehensiveness of the results. Therefore, two ranking methods that consider the comprehensiveness of relevant papers are proposed. The first uses a topic-based Boolean query search. This search converts every word in the abstract set and query into a topic via topic analysis by Latent Dirichlet Allocation (LDA) and conducts a search at the topic level. The topic assigned to synonyms of a search term is expected to be the same as that assigned to the search term. Each paper is ranked based on the number of times it is matched with each topic-based Boolean query search executed for various LDA parameter settings. The second is a hybrid method that emphasizes better results from our topic-based ranking result and a general query-based ranking result. This method is based on the observation that the paper sets retrieved by our method and by a general ranking method will be different. Through experiments using the NTCIR-1 and -2 datasets, the effectiveness of our topic-based and hybrid methods are demonstrated.

With the increasing advance of computer and information technologies, numerous research papers have been published online as well as offline, and as new research fields have been continuingly created, users have a lot of trouble in finding and categorizing their interesting research papers. In order to overcome the limitations, this paper proposes a research paper classification system that can cluster research papers into the meaningful class in which papers are very likely to have similar subjects. The proposed system extracts representative keywords from the abstracts of each paper and topics by Latent Dirichlet allocation (LDA) scheme. Then, the K-means clustering algorithm is applied to classify the whole papers into research papers with similar subjects, based on the Term frequency-inverse document frequency (TF-IDF) values of each paper.

There is a lot of investment in research on displaying texture through a stylus pen. However, little is known about the effect of a stylus pen that can provide the texture of pen and paper on user experience. This study investigated whether there is a change in user experience when using a stylus pen that can provide pen-and-paper texture compared with a typical stylus pen. Experiments involving writing and drawing tasks using three tools (a stylus pen that can provide pen-and-paper texture, a typical stylus pen, and analogue pen and paper) were conducted, and user experiences were compared. After a literature review that examined the factors affecting the experience of using a pen, the experiments were conducted to measure usability and emotions. We found little difference between the typical stylus pen and the stylus pen in providing texture in respect of completion time and amount of error. However, the stylus pen that can provide texture showed results closer to those of the analogue pen and paper, and better results than those of the typical stylus pen in respect of familiarity and overall satisfaction of the usability and emotional variables. Therefore, this study confirmed that user experience is improved when using a stylus pen that can provide the texture of pen and paper. Daar is al baie belê en nagevors in die nabootsing van die pen-op-papier gevoel van 'n elektroniese stilus. Daar is egter weinige inligting beskikbaar oor die effek wat tekstuur op gebruikers-ervaring het. Hierdie studie ondersoek of daar n verandering in gebruikerservaring is wanneer n stilus met pen-op-papier terugvoer gebruik word teenoor n tipiese stilus wat nie terugvoer aan die gebruiker lewer nie. Eksperimente wat skryf en teken-take insluit is met drie gereedskapstukke (n stilus met pen-op-papier terugvoer, n tipiese stilus, en n konvensionele pen op papier) uitgevoer. Na n literatuurstudie van stapel gestuur is, is die eksperimente uitgevoer om die bruikbaarheid en subjektiewe terugvoer van die gebruiker te bepaal. Die resultate toon min verskil tussen n tipiese stilus en een met die pen-op-papier gevoel, beide in terme van die tyd om die take te voltooi en die aantal foute begaan. Die stilus met pen-op-papier terugvoer se vertoning was nader aan die van n tradisionele pen, asook beter subjektiewe terugvoer van die gebruiker in terme van vertroudheid en algehele bevrediging. Die gevolgtrekking is dus dat n stilus met pen-op-papier terugvoer gebruikerservaring verbeter.

Most of today's graph analytics systems model static graphs and do not support business use cases that require the ability to: (i) query the dynamic graph data for a time-evolving system, (ii) carry out investigations on its historical evolution, and (iii) audit past business decisions made with potentially stale or incorrect data. This position paper presents our vision for bi-temporal dynamic graph analytics, and sketches a design for a system that efficiently supports these requirements.

Continuous production of an integrated pulp and paper mill depends on the availability of paper machines. Reliability and maintainability are essential for accomplishing the availability of paper machines. This study investigates the reliability, availability and maintainability (RAM) characteristics of a 120 tonnes per day paper machine from a paper mill in southern region of India. The paper machine is divided into five subsystems for failure analysis. The data was analyzed for trend and serial correlation tests for validating the inference of independent and identical distribution of failure and repair information before each sub system is best fitted to the theoretical probability distributions. Reliability and maintainability of the paper machine has been evaluated at various times which are useful for establishing the preventive maintenance schedules for improving availability of the paper machine. Wire part is found to be more critical subsystem from all points of view and require improvement by 4% and 1.5% in maintainability and availability point of view. The results of the analysis are presented to maintenance department for their active consideration.Keywords: Paper machine, reliability, maintainability, availability, mean time between failures (MTBF), mean time to repair(MTTR), independent and identically distributed(IID)

Cyber-physical systems theory offers a powerful framework for modeling, analyzing, and designing real engineering systems integrating communication, control, and computation functionalities (the cyber part) within a natural and/or man-made system governed by the laws of physics (the physical part). New methodological developments in cyber-physical systems theory are required by traditional application domains such as manufacturing, transportation, and energy systems, which are currently experiencing significant and – to some extent – revolutionary changes to address the needs of our modern society. The goal of this position paper is to provide the cyber-physical systems community, and especially young researchers, a clear view on what are research directions worth pursuing motivated by the challenges posed by modern applications.

Paper waste in the mockups design with regular, irregular, and amorphous patterns is a critical problem in digital printing presses. Paper waste reduction directly impacts production costs, generating business and environmental benefits. This problem can be mapped to the two-dimensional irregular bin-packing problem. In this paper, an iterated local search algorithm using a novel neighborhood structure to detect overlaps between amorphous shapes is introduced. This algorithm is used to solve the paper waste problem, modeled as one 2D irregular bin-packing problem. The experimental results show that this approach works efficiently and effectively to detect and correct the overlaps between regular, irregular, and amorphous figures.

Prediction and detection of skin diseases have always been a challenging and critical task for health care professionals. There are many clinics and skin practitioners who are offering their services at exorbitant costs. At the same time, skin condition prevails in our country in every part. In the current scenario majority of the skincare practitioners are using traditional methods to diagnose the disease which may take a considerable amount of time. Skin Diseases are serious problems in recent times as it is a matter of environmental factors, socioeconomic factors, lack of full diet, etc. This paper is a comparative study about understanding various skin diseases related to normal skin issues as well as cosmetology. A comparison between oily, dry, and normal skin is also projected in this study. A survey of different papers is done on basis of technologies used, results with accuracy, ethical conduct, number of diseases diagnosed, datasets, etc are done.

The metal casting industry, Nitikan is a micro business whose production process is carried out manually. The equipment used is simple and without considering the user's health. This can be seen in the product finishing process that uses a sanding machine. The equipment is not designed according to the user's posture so the operator bends in doing work movements, of course this is very risky to experience lower back pain injuries. This study aims to analyze the work activities of the finishing process using the Rapid Entire Body Assessment (REBA) and Rapid Upper Limb Assessment (RULA) approach and design work tools that can be applied to improve work posture. The results of data processing and analysis obtained a Rapid Entire Body Assessment score on a sandpaper machine single head of 5 and a Rapid Upper Limb Assessment score of 4, the score indicates that the work position has the potential to experience a risk of low back pain, so there must be an improvement in work posture. Work posture improvement is done by designing a tool in the form of a sandpaper machine that takes into account ergonomic dimensions to reduce the risk of lower back injury. The final result after the improvement is obtained Rapid Entire Body Assessment score of 3 and Rapid Upper Limb Assessment score of 4. This shows that the risk of lower back injuries can be minimized.

The paper drying process has the highest level of energy consumption in the pulp and paper production process. Analysis and optimization of the energy system during the paper drying process is critical for improving the energy efficiency of the entire paper mill. In the existing model for the paper drying process, the solution requires accurate boundary conditions such as the air temperature and humidity of the pocket area and the cylinder surface temperature, which are very difficult to obtain in the papermaking process. This can result in significant deviations between the model solution and the actual production process. This paper focuses on the single-tier dryer cylinder-based paper drying process that has been widely used with high-speed papermaking machines in recent years. A mathematical model is proposed based on real-time data. The verification via industrial production demonstrates that the proposed model is reliable for the paper drying process. Based on the simulation results, two optimization operations have been proposed. The energy consumption decreases from 1.51 t steam/t paper to 1.44 t steam/t paper, 4.6% of the steam and 1.26 × 106 RMB can be saved for a medium-scale paper mill with the annual production capacity of 105 t paper.

This paper describes approaches to the use of wearables and related monitoring and diagnostic tools to glean and present data to patients and their caregivers in the form of Personal Health Dashboard. Raw data from devices such as fitness watches, blood glucose and blood pressure monitors can be analyzed by machine learning algorithms ensembles over the cloud or at the edge, and the resulting patterns can be presented to allow for actionable responses. The advent of low-cost computational, sensing, monitoring and diagnostic tools allow for cost-effective solutions that can have wide adaptability. The paper draws from prior and ongoing research conducted by the team to present these positions in the advancement of healthcare.

PurposeThis position paper urges a drive towards clarity in the key definitions, terminologies and habits of speech associated with digital engineering and building information modelling (BIM). The ultimate goal of the paper is to facilitate the move towards arriving at an ideal definition for both concepts.Design/methodology/approachThis paper takes the “explanation building” review approach in providing prescriptive guidelines to researchers and industry practitioners. The aim of the review is to draw upon existing studies to identify, describe and find application of principles in a real-world context.FindingsThe paper highlights the definitional challenges surrounding digital engineering and BIM in Australia, to evoke a debate on BIM and digital engineering boundaries, how and why these two concepts may be linked, and how they relate to emerging concepts.Originality/valueThis is the first scholarly attempt to clarify the definition of digital engineering and address the confusion between the concepts of BIM and digital engineering.

This work aims at developing sustainable processes for pulp and paper industry by integration of the biorefinery concept to an existing pulp and paper process. A systematic methodology employing a superstructure-based process synthesis approach is employed with support from computer-aided tools to determine potential pathways for a long-term sustainable growth objective. A superstructure of the multi-product biorefinery process network for the pulp and paper industry is developed. It is divided into three sub-networks, a chemical pulping section, a biochemical production section and a black liquor utilization section. Superstructure optimization is performed with the objective to maximize profit to determine optimal integrated networks for three scenarios. The obtained results provide useful insights for further development of the optimal networks as sustainable integrated biorefinery combined with pulp and paper mills.

A Non-Orthogonal Unicast and Multicast (NOUM) transmission system allows a multicast stream intended to all receivers to be jointly transmitted with unicast streams in the same time-frequency resource blocks. While the capacity of the two-user multi-antenna NOUM with perfect Channel State Information at the Transmitter (CSIT) is known and achieved by Dirty Paper Coding (DPC)-assisted NOUM with Superposition Coding (SC), the capacity and the capacity-achieving strategy of the multi-antenna NOUM with partial CSIT remain unknown. In this work, we focus on the partial CSIT setting and make two major contributions. First, we show that linearly precoded Rate-Splitting (RS), relying on splitting unicast messages into common and private parts, encoding the common parts together with the multicast message and linearly precoding at the transmitter, can achieve larger rate regions than DPC-assisted NOUM with partial CSIT. Second, we study Dirty Paper Coded Rate-Splitting (DPCRS), that marries RS and DPC. We show that the rate region of DPCRS-assisted NOUM is enlarged beyond that of conventional DPC-assisted NOUM and that of linearly precoded RS-assisted NOUM with partial CSIT., 6 pages, 3 figures, accepted by 54th Annual Asilomar Conference on Signals, Systems, and Computers

Activating flux is made up of inorganic material mixed with a volatile medium. The objective of this study is to identify and review the literature in activating flux, and different type of welding techniques. For that purpose, a structured review method is adopted and the Scopus database is used as a primary source for the selection of papers. The papers were identified using the string term of “Activating flux” OR “Activated flux” in the title of papers. And a total of 238 papers were identified for the study. Besides the above few other papers were also reviewed and the materials used, the type of flux used, and the findings of different combinations were highlighted in the form of tables. The findings of the study provide a comprehensive understanding of the different type of welding techniques focusing on TIG welding, and the different combination of flux used and their impact was summarized.

In heterogeneous networks where macro cells and metro cells use the same frequency band to communicate with their respective users, the major problem limiting performance is the interference caused by macro cells to metro cells. The information theoretic result known as dirty paper coding provides a way to address this problem and significantly improve the performance of heterogeneous networks with co-channel deployment. In this paper, we show how a simple dirty paper coding scheme employing Tomlinson-Harashima pre-coding with partial interference pre-subtraction can be employed by metro cells to mitigate the interference caused by macro cells. A performance study included in this paper shows that the proposed dirty paper coding scheme can lead to significant improvement in user rate statistics.

A 3D modeling system with all-inclusive functionality is too demanding for a casual 3D modeler to learn. There has been a shift towards more approachable systems, with easy-to-learn, intuitive interfaces. However, most modeling systems still employ mouse and keyboard interfaces, despite the ubiquity of tablet devices and the benefits of multi-touch interfaces. We introduce an alternative 3D modeling and fabrication paradigm using developable surfaces, inspired by traditional papercrafting, and we implement it as a complete system designed for a multi-touch tablet, allowing a user to fabricate 3D scenes. We demonstrate the modeling and fabrication process of assembling complex 3D scenes from a collection of simpler models, in turn shaped through operations applied to virtual paper. Our fabrication method facilitates the assembly of the scene with real paper by automatically converting scenes into a series of cutouts with appropriately added fiducial markers and supporting structures. Our system assists users in creating occluded supporting structures to help maintain the spatial and rigid properties of a scene without compromising its aesthetic qualities. We demonstrate several 3D scenes modeled and fabricated in our system, and evaluate the faithfulness of our fabrications relative to their virtual counterparts and 3D-printed fabrications.

Researchers from academia and the corporate-sector rely on scholarly digital libraries to access articles. Attackers take advantage of innocent users who consider the articles' files safe and thus open PDF-files with little concern. In addition, researchers consider scholarly libraries a reliable, trusted, and untainted corpus of papers. For these reasons, scholarly digital libraries are an attractive-target and inadvertently support the proliferation of cyber-attacks launched via malicious PDF-files. In this study, we present related vulnerabilities and malware distribution approaches that exploit the vulnerabilities of scholarly digital libraries. We evaluated over two-million scholarly papers in the CiteSeerX library and found the library to be contaminated with a surprisingly large number (0.3-2%) of malicious PDF documents (over 55% were crawled from the IPs of US-universities). We developed a two layered detection framework aimed at enhancing the detection of malicious PDF documents, Sec-Lib, which offers a security solution for large digital libraries. Sec-Lib includes a deterministic layer for detecting known malware, and a machine learning based layer for detecting unknown malware. Our evaluation showed that scholarly digital libraries can detect 96.9% of malware with Sec-Lib, while minimizing the number of PDF-files requiring labeling, and thus reducing the manual inspection efforts of security-experts by 98%.

Aiming at the problem of easy tampering and difficult integrity authentication of paper text documents, this paper proposes a robust content authentication method for printed documents based on text watermarking scheme resisting print-and-scan attack. Firstly, an authentication watermark signal sequence related to content of text document is generated based on the Logistic chaotic map model; then, the authentication watermark signal sequence is embedded into printed paper document by using a robust text watermarking scheme; finally, the watermark information is extracted from scanned image of paper document, and compared with the authentication watermark information calculated in real time by the text document content obtained by OCR technology, thereby performing content integrity authentication of the paper text documents. Experimental results show that our method can achieve the robust content integrity authentication of paper text documents, and can also accurately locate the tampering position. In addition, the document after embedding the watermark information has a good visual effect, and the text watermarking scheme has a large information capacity.

This short paper presents an architectural overview of an agent-based framework called iv4XR for automated testing that is currently under development by an H2020 project with the same name. The framework's intended main use case of is testing the family of Extended Reality (XR) based systems (e.g. 3D games, VR sytems, AR systems), though the approach can indeed be adapted to target other types of interactive systems. The framework is unique in that it is an agent-based system. Agents are inherently reactive, and therefore are arguably a natural match to deal with interactive systems. Moreover, it is also a natural vessel for mounting and combining different AI capabilities, e.g. reasoning, navigation, and learning.

This white paper argues that formal methods need to be better rooted in higher education curricula for computer science and software engineering programmes of study. To this end, it advocates

Nowadays, recommender system has become one of the main tools to search for users’ interested papers. Since one paper often contains only a part of keywords that a user is interested in, recommender system returns a set of papers that satisfy the user’s need of keywords. Besides, to satisfy the users’ requirements of further research on a certain domain, the recommended papers must be correlated. However, each paper of an existing paper citation network hardly has cited relationships with others, so the correlated links among papers are very sparse. In addition, while a mass of research approaches have been put forward in terms of link prediction to address the network sparsity problems, these approaches have no relationship with the effect of self-citations and the potential correlations among papers (i.e., these correlated relationships are not included in the paper citation network as their published time is close). Therefore, we propose a link prediction approach that combines time, keywords, and authors’ information and optimizes the existing paper citation network. Finally, a number of experiments are performed on the real-world Hep-Th datasets. The experimental results demonstrate the feasibility of our proposal and achieve good performance.

Dirty paper coding is an interference pre-cancellation method for known interference at the transmitter and serves as a basic building block in the digital watermarking system. In this letter, we investigate the dirty paper model in the simplest digital communication system, where both the codeword and the interference are binary. For watermark embedment, we derive the relevant coding, the constant coding, and the symmetric relevant coding when the encoder focuses on the binary codeword and interference. The channel capacity is analyzed and the optimal parameter is discussed in the case.

This study investigates multi-layer coding over a dirty-paper channel. First, it is demonstrated that superposition coding in such channel still achieves the capacity of interference-free additive white Gaussian noise channel when the transmitter is non-causally aware of interference signal. Then, the problem is extended to the dirty-paper block fading channel, where it is shown that in the lack of channel information at the transmitter, the so-called broadcast approach maximises the average achievable rate of such channel.

With the surging energy price and environmental concerns, measures to improve energy efficiency have attracted increasing concerns of the manufacture sector, especially energy-intensive manufacturing industries such as tissue paper mills. Energy-efficiency scheduling, as a novel energy-efficient method, has attracted the attention of an increasing number of researchers in recent years. Drying process is the most energy-intensive production process in tissue paper mills, which has a great energy-saving potential. This paper aims to reduce the energy costs for the tissue paper mill, consisting of processing energy cost and set-up energy cost, through integrating drying process optimization with energy-efficient scheduling. First, the energy cost model and the scheduling model were built. Then, the energy cost of the drying process of every job in a given scheduling problem was optimized using particle swarm optimization (PSO). Afterwards, the energy cost was further optimized using energy-efficiency scheduling. In addition, a hybrid non-dominated sorting genetic algorithm II (NSGA-II) was utilized to solve the energy-efficiency scheduling problem. Finally, several real scheduling problems from a real tissue paper mill were addressed using the proposed approach to demonstrate its effectiveness in energy saving. The experiment result showed that there is a great energy-saving potential in the drying process, accounting for up to 12.53% of the total energy consumption. Moreover, the maximum energy saving ratio of the proposed approach could reach 9.03%. On the whole, the proposed approach can provide a new energy-saving method for tissue paper mills or other manufacturing industries.

Internet of Things (IoT) devices are increasingly being found in civilian and military contexts, ranging from smart cities and smart grids to Internet-of-Medical-Things, Internet-of-Vehicles, Internet-of-Military-Things, Internet-of-Battlefield-Things, etc. In this paper, we survey articles presenting IoT security solutions published in English since January 2016. We make a number of observations, including the lack of publicly available IoT datasets that can be used by the research and practitioner communities. Given the potentially sensitive nature of IoT datasets, there is a need to develop a standard for sharing IoT datasets among the research and practitioner communities and other relevant stakeholders. Thus, we posit the potential for blockchain technology in facilitating secure sharing of IoT datasets (e.g., using blockchain to ensure the integrity of shared datasets) and securing IoT systems, before presenting two conceptual blockchain-based approaches. We then conclude this paper with nine potential research questions. Keywords: Blockchain, Blockchain security, Collaborative security, Internet-of-military things, IoT dataset, IoT self-healing, IoT security, Intrusion-prevention system, Predictive IoT security, Predictive security

Proportional–Integral–Derivative controller technique continues to provide the easiest and effective solutions to most of the industrial applications in recent years. However PID controller is poorly tuned in practice compared to most other tuning methods and is complicated with poor performance. This research presents a multi objective optimization approach involving Genetic Algorithm, Evolutionary Programming, Particle Swarm Optimization and Bacterial foraging optimization. The proposed multi objective optimization algorithm is used to tune the PID controller parameters and their performances have been compared with the conventional methodologies like Ziegler Nichols method. The results proved that the use of multi objective optimization approach based controller tuning improves the performance of process in terms of time domain specifications and performance index, set point tracking and regulatory changes and also provides stability. This paper describes the various multi objective optimization algorithms and its implementation to tune the PID Controller used in paper machine DCS as real time processing of a Pulp and paper industry processes.

The security of critical infrastructures is of paramount importance nowadays due to the growing complexity of components and applications. This paper collects the contributions to the industry dissemination session within the 14th International Conference on Critical Information Infrastructures Security (CRITIS 2019). As such, it provides an overview of recent practical experience reports in the field of critical infrastructure protection (CIP), involving major industry players. The set of cases reported in this paper includes the usage of serious gaming for training infrastructure operators, integrated safety and security management in the chemical/process industry, risks related to the cyber-economy for energy suppliers, smart troubleshooting in the Internet of Things (IoT), as well as intrusion detection in power distribution Supervisory Control And Data Acquisition (SCADA). The session has been organized to stimulate an open scientific discussion about industry challenges, open issues and future opportunities in CIP research.

Electryo is a paper-based voting protocol that implements the Selene mechanism for individual verifiability. This short paper aims to provide the first formal model of Electryo, with security proofs for vote-privacy and individual verifiability. In general, voting protocols are complex constructs, involving advanced cryptographic primitives and strong security guarantees, posing a serious challenge when wanting to analyse and prove security with formal verification tools. Here we choose to use the \({{\,\mathrm{\textsc {Tamarin}}\,}}\) prover since it is one of the more advanced tools and is able to handle many of the primitives we encounter in the design and analysis of voting protocols.

One of the benefits of Internet of Vehicles (IoV) is improved traffic safety and efficiency, for example due to the capability to share vehicular messages in real-time. While most of the vehicular messages only need to be shared by nearby vehicles, some messages (e.g., announcement messages) may need to be more broadly distributed, for example to vehicles in a wider region. Finding a single trusted entity to store and distribute such messages can be challenging, and vehicles may not be inclined to participate (e.g., generation and distribution of announcement messages) unless they can benefit from such participation. In addition, achieving both security and privacy can be challenging. In this paper, we propose a blockchain based secure data sharing system to address the above challenges in an IoV setting. Specifically, in our system, announcement messages are stored using blockchain. To encourage/incentivize participation, vehicles that faithfully broadcast the announcement messages and/or contribute to the block generation will be rewarded by some cryptocurrency. Our system is also designed to be privacy-preserving and realizes both priori and posteriori countermeasures.

Success management can bring valuable contributions to improve project results and stakeholders’ relationships. However, the success management process must be explicitly integrated into project management approaches, guides and methodologies (such as PMBOK, PRINCE2 or PM2), which is not currently happening. The purpose of this position paper is to discuss the need and importance for this integration and to present a first proposal on how this can be operationalized. To support the position, the methodology of the European Union PM2 was used. The result of the integration demonstrates that it is possible to advance management and raise the level of project success.

PurposeThe industry is relying on the preventive maintenance techniques that can minimize failures and provide industrial plants with effective equipment, but in many companies the maintenance tasks are performed very frequently and not as per plan and do not take into consideration the conditions of the plant and equipments. The failure of each and every component needs to be studied in order to choose the best maintenance strategy. This paper presents a fuzzy VIKOR (Multicriteria Optimization and Compromise Solution) technique which is used in developing a comprehensive approach for maintenance strategy selection in the Deinking plant of the paper industry to choose the appropriate maintenance strategy thereby reducing the unnecessary cost incurred on the maintenance.Design/methodology/approachIn this paper, the Fuzzy VIKOR based methodology was applied for determining the maintenance criticality index of the deinking plant of the paper industry. The effect of failure of components were evaluated by three maintenance experts on five performance criteria that is chance of failure, chance of non-detection, downtime length, severity, spare part criticality. The components were ranked according to the maintenance criticality index and thereby implementing the appropriate maintenance strategy.FindingsThe Fuzzy VIKOR technique was applied to calculate the ranking of various components of paper industry based on the views and judgment of three maintenance experts. The proposed technique suggested the appropriate maintenance strategy for various components taking into consideration the maintenance criticality index of the components.Originality/valueThe proposed technique will help the maintenance managers to solve a discrete problem with non-commensurable and conflicting criteria. The study will help the industries to reduce the unnecessary maintenance tasks and thereby reduce the maintenance cost. This will help the maintenance practitioners in choosing the best and most effective strategy for the organization with regard to the market and company situation especially in the changing business requirement of Industry 4.0.

Background In Software Engineering (SE), conference publications have high importance both in effective communication and in academic careers. Researchers actively discuss how a paper should be organized to be accepted in mainstream conferences. Aiming This work tackles the problem of generalizing and characterizing the type of papers accepted at SE conferences. Method The paper offers a new perspective in the analysis of SE literature: a categorization scheme for SE papers is obtained by merging, extending and revising related proposals from a few existing studies. The categorization scheme is used to classify the papers accepted at three top-tier SE conferences during five years (2012–2016). Results While a broader experience is certainly needed for validation and fine-tuning, preliminary outcomes can be observed relative to what problems and topics are addressed, what types of contributions are presented and how they are validated. Conclusions The results provide insights to paper writers, paper reviewers and conference organizers in focusing their future efforts, without any intent to provide judgments or authoritative guidelines.

Globally, the recommendation services have become important due to the fact that they support e-commerce applications and different research communities. Recommender systems have a large number of applications in many fields, including economic, education, and scientific research. Different empirical studies have shown that the recommender systems are more effective and reliable than the keyword-based search engines for extracting useful knowledge from massive amounts of data. The problem of recommending similar scientific articles in scientific community is called scientific paper recommendation. Scientific paper recommendation aims to recommend new articles or classical articles that match researchers' interests. It has become an attractive area of study since the number of scholarly papers increases exponentially. In this paper, we first introduce the importance and advantages of the paper recommender systems. Second, we review the recommendation algorithms and methods, such as Content-based, collaborative filtering, graph-based, and hybrid methods. Then, we introduce the evaluation methods of different recommender systems. Finally, we summarize the open issues in the paper recommender systems, including cold start, sparsity, scalability, privacy, serendipity, and unified scholarly data standards. The purpose of this survey is to provide comprehensive reviews on the scholarly paper recommendation. Refereed/Peer-reviewed

We present a mixed reality-based assistive system for shading paper sketches. Given a paper sketch made by an artist, our interface helps inexperienced users to shade it appropriately. Initially, using a simple Delaunay-triangulation based inflation algorithm, an approximate depth map is computed. The system then highlights areas (to assist shading) based on a rendering of the 2.5-dimensional inflated model of the input contour. With the help of a mixed reality system, we project the highlighted areas back to aid users. The hints given by the system are used for shading and are smudged appropriately to apply an artistic shading to the sketch. The user is given flexibility at various levels to simulate conditions such as height and light position. Experiments show that the proposed system aids novice users in creating sketches with impressive shading.

With this position paper, we want to draw the attention of the community toward theoretical work and practical opportunities that have been overlooked so far regarding concepts, principles, and design knowledge for the user experience of Augmented and Mixed Reality content, I/O devices, interactions, applications, and systems. Despite considerable innovations in commercial products and research prototypes enabling Augmented and Mixed Reality worlds, how to design great user experiences in such worlds has been overall neglected at core, while the information and knowledge currently available to practitioners cover usability aspects mostly. Therefore, we advocate for theoretical foundations of the user experience in Augmented and Mixed Reality and propose several directions for more scientific research in this regard.

Paper-based digital microfluidic biochip (PB-DMFB) technology provides a promising solution to many biochemical applications. However, PB-DMFB manufacturing process may suffer from potential security threats. For example, both Trojan insertion and man-in-the-middle attack may affect the functionality of PB-DMFBs. To ensure the correct functionality of PB-DMFBs, we propose a watermarking scheme to hides information in the PB-DMFB layout, which allows users to check design integrity and authenticate the source of the PB-DMFB design. As a result, it serves as a first countermeasure against both Trojan insertion and man-in-the-middle attacks for PB-DMFBs.