Moussab/ORKG-training-evaluation-set huggingface dataset:
Research field: Science
Title: Selective Hydrogenation of Polyunsaturated Fatty Acids Using Alkanethiol Self-Assembled Monolayer-Coated Pd/Al2O3 Catalysts
Abstract: Pd/Al2O3 catalysts coated with various thiolate self-assembled monolayers (SAMs) were used to direct the partial hydrogenation of 18-carbon polyunsaturated fatty acids, yielding a product stream enriched in monounsaturated fatty acids (with low saturated fatty acid content), a favorable result for increasing the oxidative stability of biodiesel. The uncoated Pd/Al2O3 catalyst quickly saturated all fatty acid reactants under hydrogenation conditions, but the addition of alkanethiol SAMs markedly increased the reaction selectivity to the monounsaturated product oleic acid to a level of 80–90%, even at conversions >70%. This effect, which is attributed to steric effects between the SAMs and reactants, was consistent with the relative consumption rates of linoleic and oleic acid using alkanethiol-coated and uncoated Pd/Al2O3 catalysts. With an uncoated Pd/Al2O3 catalyst, each fatty acid, regardless of its degree of saturation had a reaction rate of ∼0.2 mol reactant consumed per mole of surface palladium per ...
Extracted statement — conv (%): >70
Research field: Science
Title: One-step Synthesis of Core-Gold/Shell- Ceria Nanomaterial and Its Catalysis for Highly Selective Semi- hydrogenation of Alkynes
Abstract: We report a facile synthesis of new core-Au/shell-CeO2 nanoparticles (Au@CeO2) using a redox-coprecipitation method, where the Au nanoparticles and the nanoporous shell of CeO2 are simultaneously formed in one step. The Au@CeO2 catalyst enables the highly selective semihydrogenation of various alkynes at ambient temperature under additive-free conditions. The core-shell structure plays a crucial role in providing the excellent selectivity for alkenes through the selective dissociation of H2 in a heterolytic manner by maximizing interfacial sites between the core-Au and the shell-CeO2.
Extracted statement — catalyst: Au@CeO2
Research field: Science
Title: CTU-Mine: An Efficient High Utility Itemset Mining Algorithm Using the Pattern Growth Approach
Abstract: Frequent pattern mining discovers patterns in transaction databases based only on the relative frequency of occurrence of items without considering their utility. For many real world applications, however, utility of itemsets based on cost, profit or revenue is of importance. The utility mining problem is to find itemsets that have higher utility than a user specified minimum. Unlike itemset support in frequent pattern mining, itemset utility does not have the anti-monotone property and so efficient high utility mining poses a greater challenge. Recent research on utility mining has been based on the candidate-generation-and-test approach which is suitable for sparse data sets with short patterns, but not feasible for dense data sets or long patterns. In this paper we propose a new algorithm called CTU-Mine that mines high utility itemsets using the pattern growth approach. We have tested our algorithm on several dense data sets, compared it with the recent algorithms and the results show that our algorithm works efficiently.
Extracted statement — Algorithm name: CTU-Mine
Research field: Science
Title: Segmentation and wake removal of seafaring vessels in optical satellite images
Abstract: This paper aims at the segmentation of seafaring vessels in optical satellite images, which allows an accurate length estimation. In maritime situation awareness, vessel length is an important parameter to classify a vessel. The proposed segmentation system consists of robust foreground-background separation, wake detection and ship-wake separation, simultaneous position and profile clustering and a special module for small vessel segmentation. We compared our system with a baseline implementation on 53 vessels that were observed with GeoEye-1. The results show that the relative L1 error in the length estimation is reduced from 3.9 to 0.5, which is an improvement of 87%. We learned that the wake removal is an important element for the accurate segmentation and length estimation of ships.
Extracted statement — Satellite sensor: GeoEye-1
Research field: Science
Title: Automatic ship detection in HJ-1A satellite data
Abstract: In this paper, we use HJ-1A satellite data to ship detection and a ship target detection algorithm based on optical remote sensing images of moving window and entropy Maximum is presented. The method uses a moving window to get ship candidates and the Shannon theory to image segmentation. Basic principle is that the entropy of the image segmented by the threshold value is max. After completing the image segmentation, an automatic discriminator is used. The identify algorithm is used to get rid of the false alarm caused by spray, cloudy and solar flare. Some feature is considered include area, length ratio and extent. The detection results indicate that most ship target can be detected without regard to cloudy.
Extracted statement — Satellite sensor: HJ-1
Research field: Science
Title: The Effect of Algorithms on Copy Number Variant Detection
Abstract: Background The detection of copy number variants (CNVs) and the results of CNV-disease association studies rely on how CNVs are defined, and because array-based technologies can only infer CNVs, CNV-calling algorithms can produce vastly different findings. Several authors have noted the large-scale variability between CNV-detection methods, as well as the substantial false positive and false negative rates associated with those methods. In this study, we use variations of four common algorithms for CNV detection (PennCNV, QuantiSNP, HMMSeg, and cnvPartition) and two definitions of overlap (any overlap and an overlap of at least 40% of the smaller CNV) to illustrate the effects of varying algorithms and definitions of overlap on CNV discovery. Methodology and Principal Findings We used a 56 K Illumina genotyping array enriched for CNV regions to generate hybridization intensities and allele frequencies for 48 Caucasian schizophrenia cases and 48 age-, ethnicity-, and gender-matched control subjects. No algorithm found a difference in CNV burden between the two groups. However, the total number of CNVs called ranged from 102 to 3,765 across algorithms. The mean CNV size ranged from 46 kb to 787 kb, and the average number of CNVs per subject ranged from 1 to 39. The number of novel CNVs not previously reported in normal subjects ranged from 0 to 212. Conclusions and Significance Motivated by the availability of multiple publicly available genome-wide SNP arrays, investigators are conducting numerous analyses to identify putative additional CNVs in complex genetic disorders. However, the number of CNVs identified in array-based studies, and whether these CNVs are novel or valid, will depend on the algorithm(s) used. Thus, given the variety of methods used, there will be many false positives and false negatives. Both guidelines for the identification of CNVs inferred from high-density arrays and the establishment of a gold standard for validation of CNVs are needed.
Extracted statement — Algorithm: HMMSeg
Research field: Science
Title: A Visual Summary for Linked Open Data sources
Abstract: In this paper we propose LODeX, a tool that produces a representative summary of a Linked open Data (LOD) source starting from scratch, thus supporting users in exploring and understanding the contents of a dataset. The tool takes in input the URL of a SPARQL endpoint and launches a set of predefined SPARQL queries, from the results of the queries it generates a visual summary of the source. The summary reports statistical and structural information of the LOD dataset and it can be browsed to focus on particular classes or to explore their properties and their use. LODeX was tested on the 137 public SPARQL endpoints contained in Data Hub (formerly CKAN), one of the main Open Data catalogues. The statistical and structural information extraction was successfully performed on 107 sources, among these the most significant ones are included in the online version of the tool.
Extracted statement — implementation: LODeX
Research field: Science
Title: A Visual Summary for Linked Open Data sources
Abstract: In this paper we propose LODeX, a tool that produces a representative summary of a Linked open Data (LOD) source starting from scratch, thus supporting users in exploring and understanding the contents of a dataset. The tool takes in input the URL of a SPARQL endpoint and launches a set of predefined SPARQL queries, from the results of the queries it generates a visual summary of the source. The summary reports statistical and structural information of the LOD dataset and it can be browsed to focus on particular classes or to explore their properties and their use. LODeX was tested on the 137 public SPARQL endpoints contained in Data Hub (formerly CKAN), one of the main Open Data catalogues. The statistical and structural information extraction was successfully performed on 107 sources, among these the most significant ones are included in the online version of the tool.
Extracted statement — System: LODeX
Research field: Science
Title: A Study of the Multi-Objective Next Release Problem
Abstract: One of the first issues which has to be taken into account by software companies is to determine what should be included in the next release of their products, in such a way that the highest possible number of customers get satisfied while this entails a minimum cost for the company. This problem is known as the Next Release Problem (NRP). Since minimizing the total cost of including new features into a software package and maximizing the total satisfaction of customers are contradictory objectives, the problem has a multi-objective nature. In this work we study the NRP problem from the multi-objective point of view, paying attention to the quality of the obtained solutions, the number of solutions, the range of solutions covered by these fronts, and the number of optimal solutions obtained.Also, we evaluate the performance of two state-of-the-art multi-objective metaheuristics for solving NRP: NSGA-II and MOCell. The obtained results show that MOCell outperforms NSGA-II in terms of the range of solutions covered, while this latter is able of obtaining better solutions than MOCell in large instances. Furthermore, we have observed that the optimal solutions found are composed of a high percentage of low-cost requirements and, also, the requirements that produce most satisfaction on the customers.
Extracted statement — Algorithm(s): MOCell
Research field: Science
Title: Economic Development and Environmental Quality in Nigeria: Is There an Environmental Kuznets Curve?
Abstract: This study utilizes standard- and nested-EKC models to investigate the income-environment relation for Nigeria, between 1960 and 2008. The results from the standard-EKC model provides weak evidence of an inverted-U shaped relationship with turning point (T.P) around $280.84, while the nested model presents strong evidence of an N-shaped relationship between income and emissions in Nigeria, with a T.P around $237.23. Tests for structural breaks caused by the 1973 oil price shocks and 1986 Structural Adjustment are not rejected, implying that these factors have not significantly affected the income-environment relationship in Nigeria. Further, results from the rolling interdecadal analysis shows that the observed relationship is stable and insensitive to the sample interval chosen. Overall, our findings imply that economic development is compatible with environmental improvements in Nigeria. However, tighter and concentrated environmental policy regimes will be required to ensure that the relationship is maintained around the first two-strands of the N-shape
Extracted statement — Shape of EKC: N-shaped
Research field: Science
Title: An introduction to robot component model for opros(open platform for robotic services)
Abstract: The OPRoS(Open Platform for Robotic Service) is a platform for network based intelligent robots supported by the IT R&D program of Ministry of Knowledge Economy of KOREA. The OPRoS technology aims at establishing a component based standard software platform for the robot which enables complicated functions to be developed easily by using the standardized COTS components. The OPRoS provides a software component model for supporting reusability and compatibility of the robot software component in the heterogeneous communication network. In this paper, we will introduce the OPRoS component model and its background.
Extracted statement — Name: OPRoS
Research field: Science
Title: Palladium nanoparticles supported on mpg-C3N4 as active catalyst for semihydrogenation of phenylacetylene under mild conditions
Abstract: Palladium nanoparticles supported on a mesoporous graphitic carbon nitride, Pd@mpg-C3N4, has been developed as an effective, heterogeneous catalyst for the liquid-phase semihydrogenation of phenylacetylene under mild conditions (303 K, atmospheric H2). A total conversion was achieved with high selectivity of styrene (higher than 94%) within 85 minutes. Moreover, the spent catalyst can be easily recovered by filtration and then reused nine times without apparent lose of selectivity. The generality of Pd@mpg-C3N4 catalyst for partial hydrogenation of alkynes was also checked for terminal and internal alkynes with similar performance. The Pd@mpg-C3N4 catalyst was proven to be of industrial interest.
Extracted statement — catalyst: Pd@mpg-C3N4
Research field: Science
Title: SENTINEL-1/2 DATA FOR SHIP TRAFFIC MONITORING ON THE DANUBE RIVER
Abstract: After a long period of drought, the water level of the Danube River has significantly dropped especially on the Romanian sector, in July-August 2015. Danube reached the lowest water level recorded in the last 12 years, causing the blockage of the ships in the sector located close to Zimnicea Harbour. The rising sand banks in the navigable channel congested the commercial traffic for a few days with more than 100 ships involved. The monitoring of the decreasing water level and the traffic jam was performed based on Sentinel-1 and Sentinel-2 free data provided by the European Space Agency and the European Commission within the Copernicus Programme. Specific processing methods (calibration, speckle filtering, geocoding, change detection, image classification, principal component analysis, etc.) were applied in order to generate useful products that the responsible authorities could benefit from. The Sentinel data yielded good results for water mask extraction and ships detection. The analysis continued after the closure of the crisis situation when the water reached the nominal level again. The results indicate that Sentinel data can be successfully used for ship traffic monitoring, building the foundation of future endeavours for a durable monitoring of the Danube River.
Extracted statement — Satellite sensor: Sentinel-2
Research field: Science
Title: A Direct and Fast Methodology for Ship Recognition in Sentinel-2 Multispectral Imagery
Abstract: The European Space Agency satellite Sentinel-2 provides multispectral images with pixel sizes down to 10 m. This high resolution allows for ship detection and recognition by determining a number of important ship parameters. We are able to show how a ship position, its heading, length and breadth can be determined down to a subpixel resolution. If the ship is moving, its velocity can also be determined from its Kelvin waves. The 13 spectrally different visual and infrared images taken using multispectral imagery (MSI) are “fingerprints” that allow for the recognition and identification of ships. Furthermore, the multispectral image profiles along the ship allow for discrimination between the ship, its turbulent wakes, and the Kelvin waves, such that the ship’s length and breadth can be determined more accurately even when sailing. The ship’s parameters are determined by using satellite imagery taken from several ships, which are then compared to known values from the automatic identification system. The agreement is on the order of the pixel resolution or better.
Extracted statement — Satellite sensor: Sentinel-2
Research field: Science
Title: A two-levels hierarchy for low-energy adaptive clustering hierarchy (TL-LEACH)
Abstract: Wireless sensor networks with thousands of tiny sensor nodes are expected to find wide applicability and increasing deployment in coming years, as they enable reliable monitoring and analysis of the environment. In this paper we propose a modification to a well-known protocol for sensor networks called Low Energy Adaptive Clustering Hierarchy (LEACH). This last is designed for sensor networks where end- user wants to remotely monitor the environment. In such situation, the data from the individual nodes must be sent to a central base station, often located far from the sensor network, through which the end-user can access the data. In this context our contribution is represented by building a two-level hierarchy to realize a protocol that saves better the energy consumption. Our TL-LEACH uses random rotation of local cluster base stations (primary cluster-heads and secondary cluster-heads). In this way we build, where it is possible, a two-level hierarchy. This permits to better distribute the energy load among the sensors in the network especially when the density of network is higher. TL- LEACH uses localized coordination to enable scalability and robustness. We evaluated the performances of our protocol with NS-2 and we observed that our protocol outperforms the LEACH in terms of energy consumption and lifetime of the network.
Extracted statement — Protocol: TL-LEACH
Research field: Semantic Web
Title: A method for re-engineering a thesaurus into an ontology
Abstract: The construction of complex ontologies can be faci lit ted by adapting existing vocabularies. There is little clarity and i fact little consensus as to what modifications of vocabularies are necessary in orde r to re-engineer them into ontologies. In this paper we present a method that provides clear steps to follow when re-engineering a thesaurus. The method makes u se of top-level ontologies and was derived from the structural differences bet we n thesauri and ontologies as well as from best practices in modeling, some of wh ich ave been advocated in the biomedical domain. We illustrate each step of our m ethod with examples from a re-engineering case study about agricultural fertil izers based on the AGROVOC thesaurus. Our method makes clear that re-engineeri ng thesauri requires far more than just a syntactic conversion into a formal lang uage or other easily automatable steps. The method can not only be used for re-engin ering thesauri, but does also summarize steps for building ontologies in general, and can hence be adapted for the re-engineering of other types of vocabularies o r terminologies.
Extracted statement — data source: AGROVOC
Research field: Semantic Web
Title: Multimedia ontology learning for automatic annotation and video browsing
Abstract: In this work, we offer an approach to combine standard multimedia analysis techniques with knowledge drawn from conceptual metadata provided by domain experts of a specialized scholarly domain, to learn a domain-specific multimedia ontology from a set of annotated examples. A standard Bayesian network learning algorithm that learns structure and parameters of a Bayesian network is extended to include media observables in the learning. An expert group provides domain knowledge to construct a basic ontology of the domain as well as to annotate a set of training videos. These annotations help derive the associations between high-level semantic concepts of the domain and low-level MPEG-7 based features representing audio-visual content of the videos. We construct a more robust and refined version of this ontology by learning from this set of conceptually annotated videos. To encode this knowledge, we use MOWL, a multimedia extension of Web Ontology Language (OWL) which is capable of describing domain concepts in terms of their media properties and of capturing the inherent uncertainties involved. We use the ontology specified knowledge for recognizing concepts relevant to a video to annotate fresh addition to the video database with relevant concepts in the ontology. These conceptual annotations are used to create hyperlinks in the video collection, to provide an effective video browsing interface to the user.
Extracted statement — Output format: MOWL
Research field: Semantic Web
Title: An Innovative Statistical Tool for Automatic OWL-ERD Alignment
Abstract: Aligning two representations of the same domain with different expressiveness is a crucial topic in nowadays semantic web and big data research. OWL ontologies and Entity Relation Diagrams are the most widespread representations whose alignment allows for semantic data access via ontology interface, and ontology storing techniques. The term ""alignment" encompasses three different processes: OWL-to-ERD and ERD-to-OWL transformation, and OWL-ERD mapping. In this paper an innovative statistical tool is presented to accomplish all the three aspects of the alignment. The main idea relies on the use of a HMM to estimate the most likely ERD sentence that is stated in a suitable grammar, and corresponds to the observed OWL axiom. The system and its theoretical background are presented, and some experiments are reported.
Extracted statement — Output format: OWL
Research field: Semantic Web
Title: Mapping ER Schemas to OWL Ontologies
Abstract: As the Semantic Web initiative gains momentum, a fundamental problem of integrating existing data-intensive WWW applications into the Semantic Web emerges. In order for today’s relational database supported Web applications to transparently participate in the Semantic Web, their associated database schemas need to be converted into semantically equivalent ontologies. In this paper we present a solution to an important special case of the automatic mapping problem with wide applicability: mapping well-formed Entity-Relationship (ER) schemas to semantically equivalent OWL Lite ontologies. We present a set of mapping rules that fully capture the ER schema semantics, along with an overview of an implementation of the complete mapping algorithm integrated into the current SFSU ER Design Tools software.
Extracted statement — Output format: OWL
Research field: Semantic Web
Title: Automatic Domain Ontology Construction Based on Thesauri
Abstract: The research on the automatic ontology construction has become very popular. It is very useful for the ontology construction to reengineer the existing knowledge resource, such as the thesauri. But many relationships in the thesauri are incorrect or are defined too broadly. Accordingly, extracting ontological relations from the thesauri becomes very important. This paper proposes the method to reengineer the thesauri to ontology, and especially the method to how to obtain the correct semantic relations. The test result shows the accuracy of the semantic relations is86.23%, and one is the hierarchical relations with 89.02%, and the other is non-hierarchical relations with 83.44%.
Extracted statement — Output format: OWL