Moussab/ORKG-training-evaluation-set huggingface dataset:
Research field: Science
Title: Segmentation of Ocular Pathologies Using Deep Convolutional Neural Network
Abstract: Diabetes Mellitus (DM) is a chronic, progressive and life-threatening disease. The ocular manifestations of DM, Diabetic Retinopathy (DR) and Diabetic Macular Edema (DME), are the leading causes of blindness in the adult population throughout the world. Early diagnosis of DR and DM through screening tests and successive treatments can reduce the threat to visual acuity. In this context, we propose an encoder decoder based semantic segmentation network SOP-Net (Segmentation of Ocular Pathologies Using Deep Convolutional Neural Network) for simultaneous delineation of retinal pathologies (hard exudates, soft exudates, hemorrhages, microaneurysms). The proposed semantic segmentation framework is capable of providing segmentation results at pixel-level with good localization of object boundaries. SOP-Net has been trained and tested on IDRiD dataset which is publicly available with pixel level annotations of retinal pathologies. The network achieved average accuracies of 98.98%, 90.46%, 96.79%, and 96.70% for segmentation of hard exudates, soft exudates, hemorrhages, and microaneurysms. The proposed methodology has the capability to be used in developing a diagnostic system for organizing large scale ophthalmic screening programs.
Extracted statement — contains: Data
Research field: Science
Title: Falcon 2.0: An Entity and Relation Linking Tool over Wikidata
Abstract: The Natural Language Processing (NLP) community has significantly contributed to the solutions for entity and relation recognition from a natural language text, and possibly linking them to proper matches in Knowledge Graphs (KGs). Considering Wikidata as the background KG, there are still limited tools to link knowledge within the text to Wikidata. In this paper, we present Falcon 2.0, the first joint entity and relation linking tool over Wikidata. It receives a short natural language text in the English language and outputs a ranked list of entities and relations annotated with the proper candidates in Wikidata. The candidates are represented by their Internationalized Resource Identifier (IRI) in Wikidata. Falcon 2.0 resorts to the English language model for the recognition task (e.g., N-Gram tiling and N-Gram splitting), and then an optimization approach for the linking task. We have empirically studied the performance of Falcon 2.0 on Wikidata and concluded that it outperforms all the existing baselines. Falcon 2.0 is open source and can be reused by the community; all the required instructions of Falcon 2.0 are well-documented at our GitHub repository (https://github.com/SDM-TIB/falcon2.0). We also demonstrate an online API, which can be run without any technical expertise. Falcon 2.0 and its background knowledge bases are available as resources at https://labs.tib.eu/falcon/falcon2/.
Extracted statement — contains: Data
Research field: Science
Title: OER Recommendations to Support Career Development
Abstract: This Work in Progress Research paper departs from the recent, turbulent changes in global societies, forcing many citizens to re-skill themselves to (re)gain employment. Learners therefore need to be equipped with skills to be autonomous and strategic about their own skill development. Subsequently, high-quality, on-line, personalized educational content and services are also essential to serve this high demand for learning content. Open Educational Resources (OERs) have high potential to contribute to the mitigation of these problems, as they are available in a wide range of learning and occupational contexts globally. However, their applicability has been limited, due to low metadata quality and complex quality control. These issues resulted in a lack of personalised OER functions, like recommendation and search. Therefore, we suggest a novel, personalised OER recommendation method to match skill development targets with open learning content. This is done by: 1) using an OER quality prediction model based on metadata, OER properties, and content; 2) supporting learners to set individual skill targets based on actual labour market information, and 3) building a personalized OER recommender to help learners to master their skill targets. Accordingly, we built a prototype focusing on Data Science related jobs, and evaluated this prototype with 23 data scientists in different expertise levels. Pilot participants used our prototype for at least 30 minutes and commented on each of the recommended OERs. As a result, more than 400 recommendations were generated and 80.9% of the recommendations were reported as useful.
Extracted statement — contains: Data
Research field: Science
Title: Message Passing for Hyper-Relational Knowledge Graphs
Abstract: Hyper-relational knowledge graphs (KGs) (e.g., Wikidata) enable associating additional key-value pairs along with the main triple to disambiguate, or restrict the validity of a fact. In this work, we propose a message passing based graph encoder - StarE capable of modeling such hyper-relational KGs. Unlike existing approaches, StarE can encode an arbitrary number of additional information (qualifiers) along with the main triple while keeping the semantic roles of qualifiers and triples intact. We also demonstrate that existing benchmarks for evaluating link prediction (LP) performance on hyper-relational KGs suffer from fundamental flaws and thus develop a new Wikidata-based dataset - WD50K. Our experiments demonstrate that StarE based LP model outperforms existing approaches across multiple benchmarks. We also confirm that leveraging qualifiers is vital for link prediction with gains up to 25 MRR points compared to triple-based representations.
Extracted statement — contains: Data
Research field: Science
Title: Identifying Software Project Risks: An International Delphi Study”
Abstract: Advocates of software risk management claim that by identifying and analyzing threats to success (i.e., risks) action can be taken to reduce the chance of failure of a project. The first step in the risk management process is to identify the risk itself, so that appropriate countermeasures can be taken. One problem in this task, however, is that no validated lists are available to help the project manager understand the nature and types of risks typically faced in a software project. This paper represents a first step toward alleviating this problem by developing an authoritative list of common risk factors. We deploy a rigorous data collection method called a "ranking-type" Delphi survey to produce a rank-order list of risk factors. This data collection method is designed to elicit and organize opinions of a panel of experts through iterative, controlled feedback. Three simultaneous surveys were conducted in three different settings: Hong Kong, Finland, and the United States. This was done to broaden our view of the types of risks, rather than relying on the view of a single culture-an aspect that has been ignored in past risk management research. In forming the three panels, we recruited experienced project managers in each country. The paper presents the obtained risk factor list, compares it with other published risk factor lists for completeness and variation, and analyzes common features and differences in risk factor rankings in the three countries. We conclude by discussing implications of our findings for both research and improving risk management practice.
Extracted statement — esearch method & question set: Delphi
Research field: Science
Title: Prioritizing Clinical Information System Project Risk Factors: A Delphi Study
Abstract: Identifying the risks associated with the implementation of clinical information systems (CIS) in health care organizations can be a major challenge for managers, clinicians, and IT specialists, as there are numerous ways in which they can be described and categorized. Risks vary in nature, severity, and consequence, so it is important that those considered to be high-level risks be identified, understood, and managed. This study addresses this issue by first reviewing the extant literature on IT/CIS project risks, and second conducting a Delphi survey among 21 experts highly involved in CIS projects in Canada. In addition to providing a comprehensive list of risk factors and their relative importance, this study is helpful in unifying the literature on IT implementation and health informatics. Our risk factor-oriented research actually confirmed many of the factors found to be important in both these streams.
Extracted statement — esearch method & question set: Delphi
Research field: Science
Title: Facility location in humanitarian relief
Abstract: In this study, we consider facility location decisions for a humanitarian relief chain responding to quick-onset disasters. In particular, we develop a model that determines the number and locations of distribution centres in a relief network and the amount of relief supplies to be stocked at each distribution centre to meet the needs of people affected by the disasters. Our model, which is a variant of the maximal covering location model, integrates facility location and inventory decisions, considers multiple item types, and captures budgetary constraints and capacity restrictions. We conduct computational experiments to illustrate how the proposed model works on a realistic problem. Results show the effects of pre- and post-disaster relief funding on relief system's performance, specifically on response time and the proportion of demand satisfied. Finally, we discuss the managerial implications of the proposed model.
Extracted statement — Uncertainty on the first-stage: Demand
Research field: Science
Title: Stochastic network design for disaster preparedness
Abstract: This article introduces a risk-averse stochastic modeling approach for a pre-disaster relief network design problem under uncertain demand and transportation capacities. The sizes and locations of the response facilities and the inventory levels of relief supplies at each facility are determined while guaranteeing a certain level of network reliability. A probabilistic constraint on the existence of a feasible flow is introduced to ensure that the demand for relief supplies across the network is satisfied with a specified high probability. Responsiveness is also accounted for by defining multiple regions in the network and introducing local probabilistic constraints on satisfying demand within each region. These local constraints ensure that each region is self-sufficient in terms of providing for its own needs with a large probability. In particular, the Gale–Hoffman inequalities are used to represent the conditions on the existence of a feasible network flow. The solution method rests on two pillars. A preprocessing algorithm is used to eliminate redundant Gale–Hoffman inequalities and then proposed models are formulated as computationally efficient mixed-integer linear programs by utilizing a method based on combinatorial patterns. Computational results for a case study and randomly generated problem instances demonstrate the effectiveness of the models and the solution method.
Extracted statement — Uncertainty on the first-stage: Demand
Research field: Science
Title: Two-Stage Multiobjective Optimization for Emergency Supplies Allocation Problem under Integrated Uncertainty
Abstract: <jats:p>This paper proposes a new two-stage optimization method for emergency supplies allocation problem with multisupplier, multiaffected area, multirelief, and multivehicle. The triplet of supply, demand, and the availability of path is unknown prior to the extraordinary event and is descriptive with fuzzy random variable. Considering the fairness, timeliness, and economical efficiency, a multiobjective expected value model is built for facility location, vehicle routing, and supply allocation decisions. The goals of proposed model aim to minimize the proportion of demand nonsatisfied and response time of emergency reliefs and the total cost of the whole process. When the demand and the availability of path are discrete, the expected values in the objective functions are converted into their equivalent forms. When the supply amount is continuous, the equilibrium chance in the constraint is transformed to its equivalent one. To overcome the computational difficulty caused by multiple objectives, a goal programming model is formulated to obtain a compromise solution. Finally, an example is presented to illustrate the validity of the proposed model and the effectiveness of the solution method.</jats:p>
Extracted statement — Uncertainty on the first-stage: Demand
Research field: Science
Title: Social Media and Disasters: A Functional Framework for Social Media Use in Disaster Planning, Response, and Research
Abstract: A comprehensive review of online, official, and scientific literature was carried out in 2012-13 to develop a framework of disaster social media. This framework can be used to facilitate the creation of disaster social media tools, the formulation of disaster social media implementation processes, and the scientific study of disaster social media effects. Disaster social media users in the framework include communities, government, individuals, organisations, and media outlets. Fifteen distinct disaster social media uses were identified, ranging from preparing and receiving disaster preparedness information and warnings and signalling and detecting disasters prior to an event to (re)connecting community members following a disaster. The framework illustrates that a variety of entities may utilise and produce disaster social media content. Consequently, disaster social media use can be conceptualised as occurring at a number of levels, even within the same disaster. Suggestions are provided on how the proposed framework can inform future disaster social media development and research.
Extracted statement — paper:publised_in: Disasters
Research field: Science
Title: Design of a Resilient Information System   for Disaster Response
Abstract: The devastating 2011 Great East Japan Earthquake made people aware of the importance of Information and Communication Technology (ICT) for sustaining life during and soon after a disaster. The difficulty in recovering information systems, because of the failure of ICT, hindered all recovery processes. The paper explores ways to make information systems resilient in disaster situations. Resilience is defined as quickly regaining essential capabilities to perform critical post disaster missions and to smoothly return to fully stable operations thereafter. From case studies and the literature, we propose that a frugal IS design that allows creative responses will make information systems resilient in disaster situations. A three-stage model based on a chronological sequence was employed in structuring the proposed design principles.
Extracted statement — Emergency Type: earthquake
Research field: Science
Title: Outdoor natural science learning with an RFID-supported immersive ubiquitous learning environment
Abstract: Despite their successful use in many conscientious studies involving outdoor learning applications, mobile learning systems still have certain limitations. For instance, because students cannot obtain real-time, contextaware content in outdoor locations such as historical sites, endangered animal habitats, and geological landscapes, they are unable to search, collect, share, and edit information by using information technology. To address such concerns, this work proposes an environment of ubiquitous learning with educational resources (EULER) based on radio frequency identification (RFID), augmented reality (AR), the Internet, ubiquitous computing, embedded systems, and database technologies. EULER helps teachers deliver lessons on site and cultivate student competency in adopting information technology to improve learning. To evaluate its effectiveness, we used the proposed EULER for natural science learning at the Guandu Nature Park in Taiwan. The participants were elementary school teachers and students. The analytical results revealed that the proposed EULER improves student learning. Moreover, the largely positive feedback from a post-study survey confirms the effectiveness of EULER in supporting outdoor learning and its ability to attract the interest of students.
Extracted statement — Educational context: Elementary
Research field: Science
Title: An Econometric Analysis for CO<sub>2</sub> Emissions, Energy Consumption, Economic Growth, Foreign Trade and Urbanization of Japan
Abstract: This paper examines the dynamic causal relationship between carbon dioxide emissions, energy consumption, economic growth, foreign trade and urbanization using time series data for the period of 1960-2009. Short-run unidirectional causalities are found from energy consumption and trade openness to carbon dioxide emissions, from trade openness to energy consumption, from carbon dioxide emissions to economic growth, and from economic growth to trade openness. The test results also support the evidence of existence of long-run relationship among the variables in the form of Equation (1) which also conform the results of bounds and Johansen conintegration tests. It is found that over time higher energy consumption in Japan gives rise to more carbon dioxide emissions as a result the environment will be polluted more. But in respect of economic growth, trade openness and urbanization the environmental quality is found to be normal good in the long-run.
Extracted statement — Shape of EKC: emissions
Research field: Science
Title: The environmental Kuznets curve at different levels of economic development: a counterfactual quantile regression analysis for CO2emissions
Abstract: This paper applies the quantile fixed effects technique in exploring the CO2 environmental Kuznets curve within two groups of economic development (OECD and Non-OECD countries) and six geographical regions West, East Europe, Latin America, East Asia, West Asia and Africa. A comparison of the findings resulting from the use of this technique with those of conventional fixed effects method reveals that the latter may depict a flawed summary of the prevailing incomeemissions nexus depending on the conditional quantile examined. We also extend the Machado and Mata decomposition method to the Kuznets curve framework to explore the most important explanations for the CO2 emissions gap between OECD and Non-OECD countries. We find a statistically significant OECD-Non-OECD emissions gap and this contracts as we ascent the emissions distribution. The decomposition further reveals that there are non-income related factors working against the Non-OECD group's greening. We tentatively conclude that deliberate and systematic mitigation of current CO2 emissions in the Non-OECD group is required. JEL Classification: Q56, Q58.
Extracted statement — Shape of EKC: emissions
Research field: Science
Title: Robust Facial Features Localization on Rotation Arbitrary Multi-View face in Complex Background
Abstract: Focused on facial features localization on multi-view face arbitrarily rotated in plane, a novel detection algorithm based improved SVM is proposed. First, the face is located by the rotation invariant multi-view (RIMV) face detector and its pose in plane is corrected by rotation. After the searching ranges of the facial features are determined, the crossing detection method which uses the brow-eye and nose-mouth features and the improved SVM detectors trained by large scale multi-view facial features examples is adopted to find the candidate eye, nose and mouth regions,. Based on the fact that the window region with higher value in the SVM discriminant function is relatively closer to the object, and the same object tends to be repeatedly detected by near windows, the candidate eyes, nose and mouth regions are filtered and merged to refine their location on the multi-view face. Experiments show that the algorithm has very good accuracy and robustness to the facial features localization with expression and arbitrary face pose in complex background.
Extracted statement — Challenges: expression
Research field: Science
Title: Comprehensive database for facial expression analysis
Abstract: Within the past decade, significant effort has occurred in developing methods of facial expression analysis. Because most investigators have used relatively limited data sets, the generalizability of these various methods remains unknown. We describe the problem space for facial expression analysis, which includes level of description, transitions among expressions, eliciting conditions, reliability and validity of training and test data, individual differences in subjects, head orientation and scene complexity image characteristics, and relation to non-verbal behavior. We then present the CMU-Pittsburgh AU-Coded Face Expression Image Database, which currently includes 2105 digitized image sequences from 182 adult subjects of varying ethnicity, performing multiple tokens of most primary FACS action units. This database is the most comprehensive testbed to date for comparative studies of facial expression analysis.
Extracted statement — Variations: expression
Research field: Science
Title: A high-resolution 3D dynamic facial expression database
Abstract: Face information processing relies on the quality of data resource. From the data modality point of view, a face database can be 2D or 3D, and static or dynamic. From the task point of view, the data can be used for research of computer based automatic face recognition, face expression recognition, face detection, or cognitive and psychological investigation. With the advancement of 3D imaging technologies, 3D dynamic facial sequences (called 4D data) have been used for face information analysis. In this paper, we focus on the modality of 3D dynamic data for the task of facial expression recognition. We present a newly created high-resolution 3D dynamic facial expression database, which is made available to the scientific research community. The database contains 606 3D facial expression sequences captured from 101 subjects of various ethnic backgrounds. The database has been validated through our facial expression recognition experiment using an HMM based 3D spatio-temporal facial descriptor. It is expected that such a database shall be used to facilitate the facial expression analysis from a static 3D space to a dynamic 3D space, with a goal of scrutinizing facial behavior at a higher level of detail in a real 3D spatio-temporal domain.
Extracted statement — Variations: expression
Research field: Science
Title: Annotated facial landmarks in the wild: A large-scale, real- world database for facial landmark localization
Abstract: Face alignment is a crucial step in face recognition tasks. Especially, using landmark localization for geometric face normalization has shown to be very effective, clearly improving the recognition results. However, no adequate databases exist that provide a sufficient number of annotated facial landmarks. The databases are either limited to frontal views, provide only a small number of annotated images or have been acquired under controlled conditions. Hence, we introduce a novel database overcoming these limitations: Annotated Facial Landmarks in the Wild (AFLW). AFLW provides a large-scale collection of images gathered from Flickr, exhibiting a large variety in face appearance (e.g., pose, expression, ethnicity, age, gender) as well as general imaging and environmental conditions. In total 25,993 faces in 21,997 real-world images are annotated with up to 21 landmarks per image. Due to the comprehensive set of annotations AFLW is well suited to train and test algorithms for multi-view face detection, facial landmark localization and face pose estimation. Further, we offer a rich set of tools that ease the integration of other face databases and associated annotations into our joint framework.
Extracted statement — Variations: expression