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Zone identification is a topic in the area of text mining which helps researchers be benefited by the content of scientific papers in a satisfactory manner. The major aim of zone identification is to classify the sentences of scientific texts into some predefined zone categories which can be useful for summarization as well as information extraction. In this paper, we propose a two-level approach to zone identification within which the first level is in charge of classifying the sentences in a given paper based on some semantic and lexical features. In this respect, several machine learning algorithms such as Simple Logistics, Logistic Model Trees and Sequential Minimal Optimization are applied. The second level is responsible for applying fusion to the classification results obtained for consecutive sentences of the first level in order to make the final decision. The proposed method is evaluated on ART and DRI corpora as two well-known data sets. Results obtained for the accuracy of zone identification for these corpora are respectively 65.75% and 84.15%, which seem to be quite promising compared to those obtained by previous approaches.

Headline generation is a challenging subtask of abstractive text summarization, which its output should be a summary, shorter than one sentence. It would be precious to develop a dataset for the evaluation of abstractive summarization methods on this task in the Persian language. There are several datasets for headline generation in Persian, most of which are not large enough to be used by more sophisticated methods of text summarization, such as deep learning models. Moreover, all of these datasets are focused on daily news and there is no dataset for summarizing scientific Persian papers. In this article, we present “ElmNet,” a headline generation dataset of about 400,000 abstract/headline pairs of scientific papers, gathered from six major publishers for scientific articles in Persian. We, moreover, evaluate the performance of the most important deep learning-based headline generation methods, on the proposed dataset. The results prove the comparability of the performance of the state-of-the-art methods on this task, to their results on the existing English datasets.

Scientific research cooperation and co-authored papers are becoming increasingly popular in the era of big science. However, allocating appropriate credit to each co-author of papers remains a challenge. We consider author contribution declarations according to the contributor roles taxonomy (CRediT) scheme (assigning each co-author to 14 contributor roles) and propose a new method of author contribution to allocate co-authors’ credits reasonably by converting the 14 contributor roles in an article into a binary author-role matrix. Based on the data of PLOS ONE, we further explore the new method’s advantages by comparing with other representative methods: It normalizes the total credits of different articles to 1, avoiding the inflationary bias caused by the increasing number of co-authors; awards different credits per co-author based on the participation rate of contributor roles to avoid the equalization bias; reduces the impact of the increasing number of co-authors on the credit of the first co-author.

Recent advances in telecommunication technology and video conferencing systems have opened a new avenue for surgical instruction called “surgical telementoring.” This report from the Technology Working Group of the SAGES Project 6 Summit reviews the telementoring technology that currently exists and proposes recommendations for minimum technology requirements and future technology development. While also providing insight in regulatory considerations, this review offers what prospective surgical telementoring participants need to know about the underlying technology with a specific focus on safety, reliability, transmission quality, ease of use, and cost. Content experts from around the world, in minimally invasive surgery, surgical mentoring and telementoring, surgical education, business development, healthcare innovation, and regulation were invited to attend a 2-day summit in Los Angeles, USA to outline the current state of surgical telementoring and chart the challenges and opportunities going forward. This article summarizes the discussion, conclusions, and recommendation of the technology group with regard to telementoring technology. This article reviews the technical requirements which can be divided into the following categories: (1) safety, (2) reliability, (3) transmission quality, (4) ease of use, and (5) cost. Telementoring applications are technology driven. Given the pace of change of technology, guiding principles in technology design and selection are warranted (Table 4). Telementoring technologies require two basic components, video capturing and display devices at the transmitting and receiving end, and a telecommunication link between them. Many additional features can be added to this basic setup including multiple cameras or video sources, remote camera zoom and pan, recording and storage of videos and images, and telestration capabilities to mention just a few. In general, the cost of these technologies is feature driven. The education framework for each specific application should determine the need for these features (Schlachta in Surg Endosc https://doi.org/10.1007/s00464-016-4988-5 ).

Since English is probably the most popular second language, helping students learn English through technology is a critical issue in non-English-speaking countries. With the growth of digital pen technologies, developing an interactive learning environment that combines printed textbooks and a digital pen to support English-language classroom learning has become feasible. This work presents an attention-based diagnosing and review mechanism (ADRM) based on brainwave detection to help learners identify the passages with low attention level in a lesson as review targets in order to perform efficiently and accurately review processes while reading paper-based English texts with digital pen support in autonomous learning environments. Based on the true experimental design, this work aims to confirm whether the ADRM improves the review performance and sustained attention of learners while reading paper-based English texts with digital pen support. The research participants were a total of 108 students at an industrial vocational high school in Taipei City, Taiwan. All research participants were male and aged from 17 to 18 years. The experimental group used the ADRM while reading paper-based English texts with digital pen support, whereas the control group used the autonomous review while reading paper-based English texts with digital pen support. Experimental results reveal that the review performance of the experimental group was significantly better than that of the control group, proving that the ADRM improved review performance. The results also show that the field-dependent learners in the experimental group exhibited a great improvement in review performance in comparison with the field-independent learners. Additionally, the low-ability learners in the experimental group exhibited better review performance compared to those in the control group. Furthermore, learners with high attention level in the experimental group have exhibited better review performance and sustained attention than the learners in the control group. This work confirms that developing an ADRM based on brainwave detection to assist learners’ review processes is practicable. However, the usability and acceptability of using ADRM instead of human autonomous review should be further considered in the information society.

Fast and simultaneous identification of multiple viable pathogens on food is critical to public health. Here we report a pathogen identification system using a paper chromogenic array (PCA) enabled by machine learning. The PCA consists of a paper substrate impregnated with 23 chromogenic dyes and dye combinations, which undergo colour changes on exposure to volatile organic compounds emitted by pathogens of interest. These colour changes are digitized and used to train a multi-layer neural network (NN), endowing it with high-accuracy (91–95%) strain-specific pathogen identification and quantification capabilities. The trained PCA–NN system can distinguish between viable Escherichia coli, E. coli O157:H7 and other viable pathogens, and can simultaneously identify both E. coli O157:H7 and Listeria monocytogenes on fresh-cut romaine lettuce, which represents a realistic and complex environment. This approach has the potential to advance non-destructive pathogen detection and identification on food, without enrichment, culturing, incubation or other sample preparation steps. Fast and simultaneous identification of multiple viable pathogens on food is critical to public health. By integrating paper chromogenic arrays (PCAs) and machine learning, a system was developed to automatically recognize PCA patterns on multiplexed viable pathogens with strain-level specificity.

Cancer is characterized as a heterogeneous disease of various types. The early detection and prognosis of a cancer type have turned into a major requirement, as it facilitates successive medical treatment of patients. The research team has classified the cancer patients into high or low-risk groups. This makes it a significant task for the medical teams to study the application of deep learning and machine learning models. As a result, such techniques have been employed for modeling the development and treatment of cancer conditions. Additionally, the machine learning tools can have the ability the significant detection features from complex datasets. Numerous techniques like Support Vector Machines (SVM), Bayesian Networks (BN), Decision Trees (DT), Artificial Neural Networks (ANN), Recurrent Neural Network (RNN), and Deep Neural Network (DNN) has been broadly utilized in cancer research. As per the current survey, the detection rate is about 99.89%, which shows the prediction models' efficiency and precise decision making. However, it is proven that deep learning and machine learning approaches can enhance cancer progression. An adequate level of estimation is required for such approaches for considering the daily medical practice. This survey analyzes and learns the diverse contributions of cancer prediction models using intelligent approaches. Further, the paper tries to categorize the different algorithms, the utilized datasets, and utilized environments. Along with this, various performance measures evaluated in each contribution is sorted out. An extensive search is conducted relevant to machine learning and deep learning methods in cancer susceptibility, recurrence, and survivability prediction, and the existing challenges in this area are clearly described. However, ML models are still in the testing as well as the experimentation phase for cancer prognoses. As the datasets are getting larger with higher quality, researchers are building increasingly accurate models. Moreover, ML models have a long way to go, and most of the models still lack sufficient data and suffer from bias.

With the advent of digital cameras, there has been an explosion in the number of medical specialties using images to diagnose or document disease and guide interventions. In many specialties, these images are not added to the patient’s electronic medical record and are not distributed so that other providers caring for the patient can view them. As hospitals begin to develop enterprise imaging strategies, they have found that there are multiple challenges preventing the implementation of systems to manage image capture, image upload, and image management. This HIMSS-SIIM white paper will describe the key workflow challenges related to enterprise imaging and offer suggestions for potential solutions to these challenges.

The confluence of significant computational power and inexpensive sensors provides the opportunity to reliably collect large volumes of information from the world and extract humanly useful information resources. This paper reviews a coherent body of work over the last 20+ years focused on development of advanced bio-inspired computing techniques, and their applications primarily for human related data in behaviour and human centered computing. We close with a synthesis proposing an experiment analysis methodology combining these tools.

With the speedy progress of network technology and internet applications, protection of digitized data against unauthorized access and modification has become a paramount issue. In order to face this challenge, numerous secret image sharing schemes have been introduced. Secret image sharing scheme is a method used for safeguarding the sensitive digitized image against illegal copying and tempering. The secret image is divided into many random shares in such a way that each share does not reveal any information to the intruders. In this paper, we present a comprehensive survey from over 100 papers which explains the new approaches and challenges. This paper also provides a comparative analysis of different methods based on different properties.

Looking at the past, among the main modalities of transmission of knowledge (alongside with manuscripts and printed treatises and with respect to the various ‘precepts’) we would have found also various professional figures. This is even truer with regard to the training and dissemination of knowledge among military engineers, who used to be real ‘living vehicles’ in national and international cultural systems. This is also true for what concern that circumscribed set of knowledge of geometrical-mathematical theories, including their application to the codes of architectural Representation and Design. This research aims to investigate the example of the military engineer Gaspare Beretta (Milan 1620–1703), whose theoretical production both on architectural graphic and on various applications of Geometry is still unpublished. With the aim of developing the relationship between geometry, architecture and the transmission of knowledge, we will go through his practices of the regular fortress tracing on ‘paper and ground’, in order to verify the resulting connections between geometric reconstruction and Author’s intentions.

Scientific Reports 6: Article number: 38171; published online: 02 December 2016; updated: 16 March 2017 The original version of this Article contained errors in the spelling of the authors Chung-Yuh Tzeng and Hsueh-Yao Chu, which were incorrectly given as Chung-Yuh Tseng and Shueh-Yao Chu respectively.

In this work is presented and described an optical system specifically designed and implemented to be applied for the study of the ink---paper interaction at the paper surface, considering the two main directions of the paper sheet (machine and cross directions). This work is particularly concerned with the system description, complete characterization, test, and its usage under real conditions. Concerning the system characterization, the main parameters were addressed and set having in mind its optimization. Relatively to the test of the system, several measurements using specific object samples with known dimensions were carried out to evaluate the accuracy of the obtained results. In terms of its usage under real conditions, an experiment was carried out using a commercial ink and common copy paper to dynamically collect data of its interaction. The collected data, after processing, enabled the determination of the main results of the analyzed ink---paper interaction, which allowed to reach the following conclusions; (1) the implemented system offers two different analysis approaches (qualitative and quantitative), both showing to be in agreement; and (2) the system also shows to be important to identify variations of the ink---paper interaction, manifested in the machine and cross directions of the paper.

This paper studies the model of the digital preservation of paper-cut after analyzing the state-of-the-art of the preservation of intangible cultural heritage at home and abroad, focusing on paper-cutting in Hebei, China in a comprehensive approach of sociology, anthropology, folk art, folklore, communication, computer, and information science. Models, methods, and solutions for the preservation and retention of national and folk cultural heritage are proposed. A virtual multimedia interactive system framework of the digital preservation of national and folk cultural heritage is constructed. The standards of paper-cut digitization are studied. The main content of the paper involves: regulated data collection and recording of the scattered Chinese folk paper-cut works in Hebei; digitization, optimization, compression, classification, icon and pattern extraction, vectorization, and work analysis of the first-hand material. This paper also investigates the demonstration, dissemination, database construction, and retrieval of the classified material, icons, and patterns; the demonstration of the reconstruction and application of icon and pattern database; the design and development of an immersive virtual gaming platform of the multi-media scenes and production process of folk paper-cut.

We describe the development of software that allows and automates the routine inclusion of nondigital paper-based data directly into DICOM examinations. No human intervention is required. The software works by allowing the direct faxing of nondigital paper-based patient data directly into DICOM imaging examinations and is added as the first series in the examination. The software is effective in any typical PACS/DICOM server environment.

As mobile devices, such as e-book readers and tablet computers, have emerged as alternatives to traditional printed media, they are also being increasingly employed as survey administration equipment. However, the question arises as to whether mobile devices are actually more effective than paper for survey administration. To address this question, the current study conducted a between-subjects experiment (N = 60) in which participants were asked to complete a survey questionnaire either on paper or an iPad. The results showed that the mobile device-based survey was more effective than the paper-based survey in encouraging participants to disclose information. In addition, self-disclosure was found to mediate the effects of the survey medium type on perceived security of information, usefulness of the medium, and intention to use the medium in the future.

In the paper we present an approach to the automatic detection and identification of important elements in paper documents. This includes stamps, logos, printed text blocks, signatures and tables. Presented approach consists of two stages. The first one includes object detection by means of AdaBoost cascade of weak classifiers and Haar-like features. Resulting image blocks are, at the second stage, subjected to verification based on selected features calculated from recently proposed low-level descriptors combined with certain classifiers representing current machine-learning approaches. The training phase, for both stages, uses bootstrapping, i.e., integrative process, aiming at increasing the accuracy. Experiments performed on large set of digitized paper documents showed that adopted strategy is useful and efficient.

In this paper, a new programmable structure of paper-based analytical devices and its programming method are represented to be used for the purpose of rapid prototyping without involving the fabrication process. The proposed ready-to-program structure is prefabricated by the screen-printing method before rendering it to the end user. The users can prototype the device rapidly for their specific applications simply by programming the prefabricated device. The proposed programmable device is composed of three different layers patterned on the filter paper substrate including a hydrophobic barrier layer, a path-blocking layer and a heater network layer. The device programming procedure is totally electrical and it is implemented by applying proper DC voltages to several predetermined heater lines. This procedure is applicable manually or automatically using a programmer setup connected to a personal computer (PC). Therefore, the user can configure the device by selecting appropriate heater lines in a simple firmware through the PC. The proposed programmable structure is implemented in four different µPAD patterns for different applications. Biochemical assays of glucose, total protein and albumin are performed on the programmable devices to verify their applicability for bioassays.

The usage of psychological networks that conceptualize psychological behavior as a complex interplay of psychological and other components has gained increasing popularity in various fields of psychology. While prior publications have tackled the topics of estimating and interpreting such networks, little work has been conducted to check how accurate (i.e., prone to sampling variation) networks are estimated, and how stable (i.e., interpretation remains similar with less observations) inferences from the network structure (such as centrality indices) are. In this tutorial paper, we aim to introduce the reader to this field and tackle the problem of accuracy under sampling variation. We first introduce the current state-of-the-art of network estimation. Second, we provide a rationale why researchers should investigate the accuracy of psychological networks. Third, we describe how bootstrap routines can be used to (A) assess the accuracy of estimated network connections, (B) investigate the stability of centrality indices, and (C) test whether network connections and centrality estimates for different variables differ from each other. We introduce two novel statistical methods: for (B) the correlation stability coefficient, and for (C) the bootstrapped difference test for edge-weights and centrality indices. We conducted and present simulation studies to assess the performance of both methods. Finally, we developed the free R-package bootnet that allows for estimating psychological networks in a generalized framework in addition to the proposed bootstrap methods. We showcase bootnet in a tutorial, accompanied by R syntax, in which we analyze a dataset of 359 women with posttraumatic stress disorder available online., Comment: Accepted for publication in Behavior Research Methods

We present a method of setting up a website using the Drupal CMS to publish CRM data. Our setup requires basic technical expertise by researchers who are then able to publish their records in both a human accessible way through HTML and a machine friendly format through RDFa. We begin by examining previous work on Drupal and the CRM and identifying useful patterns. We present the Drupal modules that are required by our setup and we explain why these are sustainable. We continue by giving guidelines for setting up Drupal to serve CRM data easily and we describe a specific installation for our case study which is related to decorated papers alongside our CRM mapping. We finish with highlighting the benefits of our method (i.e. speed and user-friendliness) and we refer to a number of issues which require further work (i.e. automatic validation, UI improvements and the provision for SPARQL endpoints).

To assess the equivalence of patient-reported outcome (PRO) survey responses across Web, interactive voice response system (IVRS), and paper modes of administration. Postoperative colorectal cancer patients with home Web/e-mail and phone were randomly assigned to one of the eight study groups: Groups 1–6 completed the survey via Web, IVRS, and paper, in one of the six possible orders; Groups 7–8 completed the survey twice, either by Web or by IVRS. The 20-item survey, including the MSKCC Bowel Function Instrument (BFI), the LASA Quality of Life (QOL) scale, and the Subjective Significance Questionnaire (SSQ) adapted to bowel function, was completed from home on consecutive days. Mode equivalence was assessed by comparison of mean scores across modes and intraclass correlation coefficients (ICCs) and was compared to the test–retest reliability of Web and IVRS. Of 170 patients, 157 completed at least one survey and were included in analysis. Patients had mean age 56 (SD = 11), 53 % were male, 81 % white, 53 % colon, and 47 % rectal cancer; 78 % completed all assigned surveys. Mean scores for BFI total score, BFI subscale scores, LASA QOL, and adapted SSQ varied by mode by less than one-third of a score point. ICCs across mode were: BFI total score (Web–paper = 0.96, Web–IVRS = 0.97, paper–IVRS = 0.97); BFI subscales (range = 0.88–0.98); LASA QOL (Web–paper = 0.98, Web–IVRS = 0.78, paper–IVRS = 0.80); and SSQ (Web–paper = 0.92, Web–IVRS = 0.86, paper–IVRS = 0.79). Mode equivalence was demonstrated for the BFI total score, BFI subscales, LASA QOL, and adapted SSQ, supporting the use of multiple modes of PRO data capture in clinical trials.

OBJECTIVES: Medical records are legal documentation of patients’ care hence must be accurate and complete for both medical and legal purposes. Electronic patient record (EPR) systems aim to improve the accuracy of documentation, provide better organisation and access of data. This study compares the completeness of traditional note records and EPR in glaucoma patients. METHODS: Using criteria from the April 2009 National Institute for Health and Care Excellence (NICE) guidelines completeness of data entry was compared between EPR and paper notes in three units. Moorfields Eye Hospital (City Road) uses the Openeyes EPR. Bedford Hospital (Moorfields Eye Centre) and Western Eye Hospital use the Medisoft EPR. The standard was set at 100% compliance for predetermined parameters. RESULTS: One hundred seventy paper notes and 270 electronic records were analysed. With the exception of central corneal thickness (p = 0.31), all other key parameters were more consistently recorded in the paper records than in the EPR. Intraocular pressure (p = 0.004), anterior chamber configuration and depth assessments using gonioscopy (p

Exploring massive mobile data for location-based services becomes one of the key challenges in mobile data mining. In this paper, we investigate a problem of finding a correlation between the collective behavior of mobile users and the distribution of points of interest (POIs) in a city. Specifically, we use large-scale cell tower data dumps collected from cell towers and POIs extracted from a popular social network service, Weibo. Our objective is to make use of the data from these two different types of sources to build a model for predicting the POI densities of different regions in the covered area. An application domain that may benefit from our research is a business recommendation application, where a prediction result can be used as a recommendation for opening a new store/branch. The crux of our contribution is the method of representing the collective behavior of mobile users as a histogram of connection counts over a period of time in each region. This representation ultimately enables us to apply a supervised learning algorithm to our problem in order to train a POI prediction model using the POI data set as the ground truth. We studied 12 state-of-the-art classification and regression algorithms; experimental results demonstrate the feasibility and effectiveness of the proposed method.

Nowadays, reading on screens is an essential part of our daily life. Tablet computers, with great portability, usability, and interactivity, have become a popular mobile device for learning and reading. However, there were few studies to explore the effects on reading using tablet computers, and the difference between computer-based reading and paper-based reading is still not clear. Therefore, this study focused on to investigate the effects of reading comprehension across paper, tablets, and computers. Moreover, the user familiarity was regarded as a potential issue to affect the reading on digital devices. Accordingly, this study took into account to figure out the effects and impacts of the user familiarity on reading comprehension while reading on tablets. Two question types of reading comprehension, multiple choice questions as the shallow level comprehension and summarization as deep level comprehension, were considered to test the reading comprehension. Data from 90 college students were used in the data analysis. It was indicated that the paper group performed significantly better than the computer-based reading on the shallow level comprehension. This finding confirmed and eliminated the factors of reading in paper and computer for the previous studies. For example, the way of navigation was still the main reason to affect the process of reading. However, the switch between the reading and test media was not the reason to affect the reading comprehension. In order to figure out why there was no difference between tablets and the other two media platforms, the tablet familiarity was evaluated to find out whether the familiarity affect reading comprehension or not. The result showed that the high level of tablet familiarity group performed significantly better than low level group on deep level comprehension. For this result, it could conclude that if providing students enough and appropriate training, they could have higher familiarity with tablets and then gain better reading comprehension using tablets.

Desktop-publishing software and hardware has progressed to the point that many widely used word-processing programs are capable of printing high-quality digital images with many shades of gray from black to white. Accordingly, it should be relatively easy to print digital medical images on paper for reports, instructional materials, and in research notes. Components were assembled that were necessary for extracting image data from medical imaging devices and converting the data to a form usable by word-processing software. A system incorporating these components was implemented in a medical setting and has been operating for 18 months. The use of this system by medical staff has been monitored.

It is a pleasure and a privilege to present to the readers of the Springer Journal on Analog Integrated Circuits and Signal Processing (ALOG) a selection of the papers from the 4th edition of the Latin America Symposium on Circuits and Systems—LASCAS 2013, held in February 2013 in the historical Peruvian city of Cuzco. The LASCAS Symposium is the premier event in circuits and systems in that region of the Americas. The papers selected by the Guest Editors fall in the focus of this Journal, and are among the 10 % top quality of the 155 papers submitted to LASCAS 2013, and were selected by rigorous reviewing. While LASCAS contemplates applications and digital systems, most of the papers in this Special Issue address analog circuits and systems, the themes of interest to ALOG Journal readers. From the 119 papers which were accepted and published in the IEEE LASCAS Proceedings, a total of 27 works were nominated and invited to submit a substantially improved manuscript on the same subject to this Special Issue of LASCAS 2013. The quality screening took advantage of the reviews and paper ratings for each of those 119 papers, which were narrowed down to 23 extended manuscripts. These went through a second-round of peer-review process and 14 papers, substantially extended versions from the LASCAS Symposium, were finally selected for this Special Issue, as the highlights from the flagship Latin American Symposium on Circuits and Systems. The papers in this Special Issue come from the Americas (North and South) and Europe. The 14 selected papers cover a wide range of topics, from analog circuits design at ultra-low voltages, to amplifiers design, integrated circuits, wireless, and digital systems design, and up to topics at the application of communications and arithmetic circuits. The first 3 papers in the Special Issue deal with low voltage analog CMOS design. The paper ‘‘Fully Integrated Inductive Ring Oscillators Operating at VDD below 2kT/ q’’ by M. Machado et alli presents oscillators with two inductive loading schemes to work under extremely low DC supplies. H. Hernandez et alli propose and show in their paper a silicon implementation of ‘‘A fully Integrated Boost Converter For Thermoelectric Energy Harvesting’’ which upconverts from very low voltage supplies. The paper ‘‘Sub-1 V Band-Gap Based and MOS ThresholdVoltage Based Voltage References in 0.13 lm CMOS’’ by D.M. Colombo et alli explores and compares low-voltage DC reference circuits with different circuit approaches possible in standard CMOS, compared to diode-based BGRs. Two papers on DC and instrumentation amplifiers designs target improvements on either DC gain or CMRR. H. Gomez-Ortiz introduces a ‘‘Robust to PVT Enhanced DC Gain Amplifier Using No Miller Capacitor Feedforward Compensation’’ in his paper, where a feedforward scheme improves DC gain and common mode range. C. Silva-Cardenas Maestria de Ingenieria de las Telecomunicaciones, Pontificia Universidad Catolica del Peru, Ave. Universitaria 1801, Lima 32, Peru e-mail: csilva@pucp.edu

What happened The Information Commissioner’s Office (ICO) published a 50-page paper on 27 July entitled ‘Big data and data protection’. The paper gives an overview of the privacy issues that arise from using big data and suggests how to comply with the Data Protection Act 1998. The ICO states that the paper’s aim is to ensure that the different privacy risks of big data are considered alongside its benefits. It emphasizes that the ‘benefits cannot simply be traded with privacy rights’. The paper invited comments by 12 September 2014 and asked for feedback on three specific questions

We present the results of the user studies of the CareMe prototype telecare service for supporting older adults with remote telecare services. The CareMe solution targets older adults who are capable of living independently and outside of a dedicated medical institution or a nursing home, but require occasional medical attention, and formal or informal care. The studies were conducted between November 2013 and March 2014 and followed the participatory design approach. The research questions focused on understanding the difference in the participatory design approach when older adults use paper prototypes vs interactive prototypes, and the difference when older adults use interactive prototypes with poor interface design vs interactive prototypes with rich interface design. In total, 45 older adults living in Slovenia participated in the field trial. They were retired, 32 of whom were nursing home residents and 13 were living independently at home. The study sample's age distribution was between 64 and 91 years. The analysis of the filed trial results indicated the importance of the factors that influence users' decision about how and when they use new technology, i.e., the perceived usefulness and the perceived ease-of-use. Main insights gained from the studies show, that it is very difficult to keep older people focused on the topics of discussion and that they have often difficulties to clearly present/express their ideas. Furthermore, abstract concepts, such as paper only prototypes proved to be challenging to cope with, whereas using real applications and services when trying out scenarios using interactive prototypes provided much better experience and feedback.

We consider the problem of generating balanced training samples from an unlabeled data set with an unknown class distribution. While random sampling works well when the data are balanced, it is very ineffective for unbalanced data. Other approaches, such as active learning and cost-sensitive learning, are also suboptimal as they are classifier-dependent and require misclassification costs and labeled samples, respectively. We propose a new strategy for generating training samples, which is independent of the underlying class distribution of the data and the classifier that will be trained using the labeled data. Our methods are iterative and can be seen as variants of active learning, where we use semi-supervised clustering at each iteration to perform biased sampling from the clusters. We provide several strategies to estimate the underlying class distributions in the clusters and to increase the balancedness in the training samples. Experiments with both highly skewed and balanced data from the UCI repository and a private data set show that our algorithm produces much more balanced samples than random sampling or uncertainty sampling. Further, our sampling strategy is substantially more efficient than active learning methods. The experiments also validate that, with more balanced training data, classifiers trained with our samples outperform classifiers trained with random sampling or active learning.

The purpose of this study is to investigate student designers’ attitude and choices towards the use of computers and paper sketches when involved in a graphic design process. 65 computer graphic technology undergraduates participated in this research. A mixed method study with survey and in-depth interviews was applied to answer the research questions. This result shows that sketches and computers as design tools help students generate ideas in the early stage of design. Students’ preferences to use sketches or computers differ, since each tool has its own advantages and disadvantages.

The authors revisit their 1991 Bigglestone Award winning Fire Technology paper “Fire Risk Analysis: General Conceptual Framework for Describing Models” and comment on what has changed, what has evolved, and what has remained the same in our understanding of good practice in the conduct of fire risk analysis. Also, the authors refer to the present issues and the future prospects in this regard.

Mobile devices have been used as tools for navigation and geographic information retrieval with some success. However, screen size, glare, and the cognitive demands of the interface are often cited as weaknesses when compared with traditional tools such as paper maps and guidebooks. In this paper, a simple mixed media approach is presented which tries to address some of these concerns by combining paper maps with electronic guide resources. Information about a landmark or region is accessed by waving a handheld computer equipped with an radio frequency identification (RFID) reader above the region of interest on a paper map. We discuss our prototyping efforts, including lessons learned about using RFID for mixed media interfaces. We then present and discuss evaluations conducted in the field and in a comparative, exploratory study. Results indicate that the method is promising for tourism and other activities requiring mobile, geographically-related information access.

This paper considers a web-hosting application where a web server hosts a website for a client organisation. Users that access this web server are sensitive to the quality of service (QoS) they receive (such as response time and request loss). In the current state of practice, web-hosting services charge clients only based on the amount of information stored but do not negotiate any quality of service details. This is changing as users expect good QoS. From a cost standpoint, these web server farms consume a lot of electric power which needs to be incorporated in the price charged to clients. In addition, the internet domain in the web server farm vicinity experiences severe congestion. This paper considers two main parameters that the web servers tune, namely, caching strategy which is a one-time decision and the processing speed to run the web server which can be tuned from time to time. A detailed methodology is presented which web servers can incorporate to make the above decisions. Based on the dynamics between the three players (users, clients and web servers), it is shown that the price and web server settings could both either stabilise or oscillate between several points, indicating chaos.

Body Area Networks (BAN) which consist of RF-enabled wearable and implantable sensory nodes are poised to be a promising interdisciplinary technology with novel uses in pervasive healthcare, personal entertainment and consumer electronics. The papers which appear in this special issue have been carefully selected from the best IEEE PIMRC 2009 conference papers addressing some of the most challenging issues in BAN such as propagation modeling, physical, and medium access control layers. Papers presented here propose models, algorithms and protocols exhibiting advance research in this promising field.

This volume is one of two special journal issues compiled from the best papers presented at the fourth Robotics: Science and Systems (RSS) conference, held in Zurich in June 2008. As indicated by its title, RSS is a meeting that values research papers focusing on the development of, and experimentation with, new complex robotic systems in real-world environments as much as it values new theoretical and algorithmic advances. The second special issue will be published by the International Journal of Robotics Research. The Zurich meeting of RSS received 163 submitted papers. After a rigorous review process, 40 papers were accepted covering a wide range of topics, from autonomous driving, to micro-robotics, to design of manipulators for use in functional magnetic resonance imaging, to grasping and manipulation. Following the tradition of RSS, there were a number of invited speakers who are global leaders in research areas on the frontiers of robotics. As an indication of the quality and inspirational value of the program, RSS Zurich was well attended, with nearly six times as many attendees as papers. Papers selected for a special issue were selected first, and then partitioned into two groups for the two special issues. The papers selected for this special issue of Autonomous Robots have a common theme close to the focus of this journal: the study of problems related to mobile robots or

The value of coronal incisions in maxillofacial surgery has been well documented. The incision provides excellent access to the upper facial skeleton aiding in adequate access, good anatomic reduction of fractures and hidden scar. The associated bleeding with raising a bicoronal flap is a matter of concern to beginner surgeons. This often prevents the regular use of this approach. Textbooks have recommended the use of Raney clips but these are not available routinely in India and are expensive. We have utilized simple stationary paper clips, autoclaved and used for surgery. This not only provide haemostasis but also aids in holding the flap during dissection. This technique would be of great help to young surgeons and in developing countries where economics plays a major role in surgery.

This study investigated HyperCard as a tool for assessment in science education and determined whether or not a HyperCard assessment instrument could differentiate between expert and novice student performance (balancing stoichiometric equations) in science education. Five chemical equations were presented by traditional pen-paper and by a HyperCard (Hyperequation) program. Thirty honors (expert) and 30 regular (novice) chemistry students were randomly divided into HyperCard and traditional pen-paper groups of 15 students each. Scoring was based on five dependent variables: performance scores, number of attempts, rate of attempts, time on task, and correctness. Correlation results indicated that students with high performance scores correctly balanced more equations, required fewer attempts to balance equations, and required less time per attempt than did students with low performance scores. MANOVA results showed that performance scores and correctness scores for both experts and novice were significantly higher on HyperCard compared to pen-paper assessment; the novice scores on HyperCard nearly equaled the expert pen-paper assessment scores. Significant interactions were found for time on task and for correctness. The results suggest that HyperCard can be a suitable tool for assessment in science education and that such an instrument can differentiate between expert and novice student performance.

Discussion-based exercises are a prevalent form of training in emergency management, aimed at improving coordinative decision making between the various agencies involved in disaster response. In each exercise, small multi-agency groups of decision makers discuss potential courses of action within a fictitious disaster scenario presented as a textual narrative supported by visual materials. We present a cognitive engineering analysis of the problem of designing disaster scenarios for effective discussion-based exercises. The analysis was carried out through the development of a pilot authoring environment to establish and address the requirements of a training organisation in the UK. The pilot authoring environment embodies a simple theoretical model of the exercise process in which facts of a disaster scenario afford discussion of pertinent issues which are elicited by considerations fed to trainees. This representational scheme allows the authoring environment to complement and extend authors’ mental models of exercises, and thereby enhance five aspects of authoring: rationalisation; continuity of rationale; evolution; adaptability; and the integration of evaluation feedback.

This special issue of Analog Integrated Circuits and Signal Processing presents the extended versions of selected papers from the 30th NORCHIP conference which was held in Copenhagen, Denmark, November 12–13, 2012. The 30th NORCHIP conference had about 70 participants and 57 papers were presented during the 2 days the conference lasted whereof 37 papers were presented in 13 lecture sessions, 16 papers were presented in two poster sessions and four invited presentations were given. From the contributed papers seven papers have been selected for this special issue. The selection of the papers for this special issue is based on quality criteria and they reflect the topics in analog circuit design highlighted during the conference and the selected papers all contain contributions that will be of interest to the reader. The two first papers present two RF receivers. In the first paper I. Din, J. Wernehag, S. Andersson, H. Sjoland and S. Mattisson present a SAW-less receiver based on a new architecture for the noise amplification including a new technique for harmonic rejection. The receiver operates in the frequency range 500 MHz–2.5 GHz and shows a NF comparable to state-of-the art. In second paper S. Sudalaiyandi, H. A. Hjortland and T. S. Lande describe a continuous time RAKE receiver for an ultra-wide band impulse radio system. The receiver uses a continuous time coding scheme that uses coherent symbol detection. A demonstrator IC shows that the system can achieve a high precision localization of *1.4 cm without any clock synchronization and consumes 5.29 mW. The third paper by D. Svard, C. Jansson and A. Alvandpour present an IC for reading out the content from an infrared focal array. The chip demonstrates a complete readout circuitry for a 32 9 32 array with a dynamic range of 97 dB and using 170 mW at 60 frames per second. The fourth paper deals with a low power current reference. In the paper by F. Cucchi, S. Pascoli and G. Iannaccone a current reference that consumes 288 nA from a 1 V supply is presented. The circuit is based on a conventional bipolar bandgap reference and shows a trade-off between power consumption and process variability. The paper describes how to design the bandgap reference to achieve low spread in the reference current and a prototype IC demonstrates 1.4 % variation in the reference current over 23 samples from a single batch. The remaining papers all concern data conversion. In the fifth paper S. Balasubramanian and W. Khalil present the architectural trends in current steering digital-to-analog converters. Some of the fundamental challenges designing such digital-to-analog converters are highlighted and the latest research that address these are discussed. The next papers also concern data conversion but they present specific implementations of data converters. In the sixth paper A. F, Yeknami and A. Alvandpour present a low power discrete time sigma-delta modulator. The analog-to-digital data converter is intended for medical implant and shows a SNDR of 76 dB using only 2.1 lW. The last paper selected from the NORCHIP conference ‘‘A 2-D GRO Vernier Time-to-Digital Converter with Large Input Range and Small Latency’’ by P. Lu, A. Liscidini and P. Andreaniaaa has been printed in the August 2013 volume of the Journal and thus the reader is referred hereto. The paper presents a GRO-based Vernier time-to-digital converter with reduced I. Jorgensen (&) Technical University of Denmark, Department of Electrical Engineering, Orsteds Plads, Building 349, 2800 Kongens Lyngby, Denmark e-mail: ihhj@elektro.dtu.dk URL: www.elektro.dtu.dk

Background In recent years high throughput methods have led to a massive expansion in the free text literature on molecular biology. Automated text mining has developed as an application technology for formalizing this wealth of published results into structured database entries. However, database curation as a task is still largely done by hand, and although there have been many studies on automated approaches, problems remain in how to classify documents into top-level categories based on the type of organism being investigated. Here we present a comparative analysis of state of the art supervised models that are used to classify both abstracts and full text articles for three model organisms. Results Ablation experiments were conducted on a large gold standard corpus of 10,000 abstracts and full papers containing data on three model organisms (fly, mouse and yeast). Among the eight learner models tested, the best model achieved an F-score of 97.1% for fly, 88.6% for mouse and 85.5% for yeast using a variety of features that included gene name, organism frequency, MeSH headings and term-species associations. We noted that term-species associations were particularly effective in improving classification performance. The benefit of using full text articles over abstracts was consistently observed across all three organisms. Conclusions By comparing various learner algorithms and features we presented an optimized system that automatically detects the major focus organism in full text articles for fly, mouse and yeast. We believe the method will be extensible to other organism types.

Secondary 5 students from four schools in Hong Kong were required to classify 18 paper and pencil physics problems in terms of whether the problems contain necessary and sufficient, missing or irrelevant information for their solution. Students' ability to denote missing information correlated rather highly with the solution rates of the problems. In another test, students were asked to classify whether the problems in each of six pairs were similar to or different from each other according to students' self-determined criteria. Students who used a deep structure (i.e. used the underlying physics principles) to classify the problems have significantly higher scores in detecting missing and irrelevant information and in the solution rates than those who used surface structure or features for classification. It is argued that a student who is able to identify what information is sufficient, missing or irrelevant for solving a problem understands the problem structure and so is better able to solve it. Such a student is likely to adopt a deep structure in categorizing physics problems. This latter result corroborates with the findings of the expert-novice research paradigm.

We describe the organization and several components of an automated document processing system that begins with digitized images of documents and produces representations at higher levels. Such representations inlcude: the visual sketch (connected components extracted from the background), physical layout (spatial extents of blocks corresponding to text, graphics), logical layout (grouping of strings into words and phrases), and block primitives (e.g., recognised characters and words in text blocks, recognition of hand-drawn line drawings i.e. schematic electronic circuits). We describe algorithms for deriving several of the representations and describe the interaction of different modules. The methods are illustrated with examples.

This issue of Autonomous Robots is the second of two special journal issues compiled from selected papers presented at the sixth Robotics: Science and Systems (RSS) Conference, held at the Universidad de Zaragoza, Zaragoza, Spain in June 2010. The first special issue was recently published by the International Journal of Robotics Research. RSS is a single-track conference, with the aim of bringing together researchers from all areas of robotics, showcasing the most recent and significant advances in the field, and providing a forum for academic discourse for the robotics community. The conference brought together 315 researchers from academic institutions and industry from around the world. The conference program featured 40 papers, each carefully chosen in a rigorous review process from 239 submissions, four invited talks by leading scientists from research fields related or relevant to robotics, and two Early Career Spotlight Presentations by promising young researchers from our community. The technical program covered a wide range of research areas, including control, sensing, perception, manipulation, mechanical design, actuation, machine learning, motion planning, probabilistic robotics, and planning. The presentations addressed an equally broad range of robot types, including swimming, diving, driving, and flying robots, as well as many application areas, including autonomous driving, exoskeletons, mobile manipulation, and molecular biology. The broad scope of the conference is reflected in the papers selected for this volume. The papers present a novel