Moussab/ORKG-training-evaluation-set huggingface dataset:
Research field: Science
Title: Distributed Group
Support Systems
Abstract: Distributed group support systems are likely to be widely used in the future as a means for dispersed groups of people to work together through computer networks. They combine characteristics of computer-mediated communication systems with the specialized tools and processes developed in the context of group decision support systems, to provide communications, a group memory, and tools and structures to coordinate the group process and analyze data. These tools and structures can take a wide variety of forms in order to best support computer-mediated interaction for different types of tasks and groups. This article summarizes five case studies of different distributed group support systems developed by the authors and their colleagues over the last decade to support different types of tasks and to accommodate fairly large numbers of participants (tens to hundreds). The case studies are placed within conceptual frameworks that aid in classifying and comparing such systems. The results of the case studies demonstrate that design requirements and the associated research issues for group support systems an be very different in the distributed environment compared to the decision room approach.
Extracted statement — Focus Group: EMO
Research field: Science
Title: Migratory environmental history of the grey mullet Mugil cephalus as revealed by otolith Sr:Ca ratios
Abstract: We used an electron probe microanalyzer (EPMA) to determine the migratory environ- mental history of the catadromous grey mullet Mugil cephalus from the Sr:Ca ratios in otoliths of 10 newly recruited juveniles collected from estuaries and 30 adults collected from estuaries, nearshore (coastal waters and bay) and offshore, in the adjacent waters off Taiwan. Mean (±SD) Sr:Ca ratios at the edges of adult otoliths increased significantly from 6.5 ± 0.9 × 10 -3 in estuaries and nearshore waters to 8.9 ± 1.4 × 10 -3 in offshore waters (p < 0.01), corresponding to increasing ambi- ent salinity from estuaries and nearshore to offshore waters. The mean Sr:Ca ratios decreased sig- nificantly from the core (11.2 ± 1.2 × 10 -3 ) to the otolith edge (6.2 ± 1.4 × 10 -3 ) in juvenile otoliths (p < 0.001). The mullet generally spawned offshore and recruited to the estuary at the juvenile stage; therefore, these data support the use of Sr:Ca ratios in otoliths to reconstruct the past salinity history of the mullet. A life-history scan of the otolith Sr:Ca ratios indicated that the migratory environmen- tal history of the mullet beyond the juvenile stage consists of 2 types. In Type 1 mullet, Sr:Ca ratios range between 4.0 × 10 -3 and 13.9 × 10 -3 , indicating that they migrated between estuary and offshore waters but rarely entered the freshwater habitat. In Type 2 mullet, the Sr:Ca ratios decreased to a minimum value of 0.4 × 10 -3 , indicating that the mullet migrated to a freshwater habitat. Most mullet beyond the juvenile stage migrated from estuary to offshore waters, but a few mullet less than 2 yr old may have migrated into a freshwater habitat. Most mullet collected nearshore and offshore were of Type 1, while those collected from the estuaries were a mixture of Types 1 and 2. The mullet spawning stock consisted mainly of Type 1 fish. The growth rates of the mullet were similar for Types 1 and 2. The migratory patterns of the mullet were more divergent than indicated by previous reports of their catadromous behavior.
Extracted statement — Analytical method: EPMA
Research field: Science
Title: Increased attention for computer-tailored health communications: an event-related potential study
Abstract: The authors tested whether individually tailored health communications receive more attention from the reader than nontailored health communications in a randomized, controlled trial among student volunteers (N = 24). They used objective measures of attention allocation during the message exposure. In a between-subjects design, participants had to read tailored or nontailored nutrition education messages and at the same time had to pay attention to specific odd auditory stimuli in a sequence of frequent auditory stimuli (odd ball paradigm). The amount of attention allocation was measured by recording event-related potentials (ERPs; i.e., N100 and P300 ERPs) and reaction times. For the tailored as opposed to the nontailored group, results revealed larger amplitudes for the N100 effect, smaller amplitudes for the P300 effect, and slower reaction times. Resource allocation theory and these results suggest that those in the tailored group allocated more attention resources to the nutrition message than those in the nontailored group.
Extracted statement — has_method: ERP
Research field: Science
Title: An effective Fuzzy Healthy Association Rule Mining Algorithm (FHARM)
Abstract: In this paper we propose an effective and efficient new Fuzzy Healthy Association Rule Mining Algorithm (FHARM) that produces more interesting and quality rules by introducing new quality measures. In this approach, edible attributes are filtered from transactional input data by projections and are then converted to Required Daily Allowance (RDA) numeric values. The averaged RDA database is then converted to a fuzzy database that contains normalized fuzzy attributes comprising different fuzzy sets. Analysis of nutritional information is then performed from the converted normalized fuzzy transactional database. The paper presents various performance tests and interestingness measures to demonstrate the effectiveness of the approach and proposes further work on evaluating our approach with other generic fuzzy association rule algorithms.
Extracted statement — Algorithm name: FHARM
Research field: Science
Title: Design and analysis of a fast local clustering service for wireless sensor networks
Abstract: We present a fast local clustering service, FLOC, that partitions a multi-hop wireless network into nonoverlapping and approximately equal-sited clusters. Each cluster has a clusterhead such that all nodes within unit distance of the clusterhead belong to the cluster but no node beyond distance m from the clusterhead belongs to the cluster. By asserting m /spl ges/ 2, FLOC achieves locality: effects of cluster formation and faults/changes at any part of the network are contained within most m units. By taking unit distance to be the reliable communication radius and m to be the maximum communication radius, FLOC exploits the double-band nature of wireless radio-model and achieves clustering in constant time regardless of the network size. Through simulations and experiments with actual deployments, we analyze the tradeoffs between clustering time and the quality of clustering, and suggest suitable parameters for FLOC to achieve a fast completion time without compromising the quality of the resulting clustering.
Extracted statement — Protocol: FLOC
Research field: Science
Title: The Relationship between CO2 Emission, Energy Consumption, Urbanization and Trade Openness for Selected CEECs
Abstract: This paper investigates the relationship between CO2 emission, real GDP, energy consumption, urbanization and trade openness for 10 for selected Central and Eastern European Countries (CEECs), including, Albania, Bulgaria, Croatia, Czech Republic, Macedonia, Hungary, Poland, Romania, Slovak Republic and Slovenia for the period of 1991–2011. The results show that the environmental Kuznets curve (EKC) hypothesis holds for these countries. The fully modified ordinary least squares (FMOLS) results reveal that a 1% increase in energy consumption leads to a %1.0863 increase in CO2 emissions. Results for the existence and direction of panel Vector Error Correction Model (VECM) Granger causality method show that there is bidirectional causal relationship between CO2 emissions - real GDP and energy consumption-real GDP as well.
Extracted statement — Methodology: FMOLS
Research field: Science
Title: Hardware implementation of a full HD real-time disparity estimation algorithm
Abstract: Disparity estimation is a common task in stereo vision and usually requires a high computational effort. High resolution disparity maps are necessary to provide a good image quality on autostereoscopic displays which deliver stereo content without the need for 3D glasses. In this paper, an FPGA architecture for a disparity estimation algorithm is proposed, that is capable of processing high-definition content in real-time. The resulting architecture is efficient in terms of power consumption and can be easily scaled to support higher resolutions.
Extracted statement — Computational platform: FPGA
Research field: Science
Title: GMM For Offline Signature Forgery Detection
Abstract: As signature continues to play a crucial part in personal identification for number of applications including financial transaction, an efficient signature authentication system becomes more and more important. Various researches in the field of signature authentication has been dynamically pursued for many years and its extent is still being explored. Signature verification is the process which is carried out to determine whether a given signature is genuine or forged. It can be distinguished into two types such as the Online and the Offline. In this paper we presented the Offline signature verification system and extracted some new local and geometric features like QuadSurface feature, Area ratio, Distance ratio etc. For this we have taken some genuine signatures from 5 different persons and extracted the features from all of the samples after proper preprocessing steps. The training phase uses Gaussian Mixture Model (GMM) technique to obtain a reference model for each signature sample of a particular user. By computing Euclidian distance between reference signature and all the training sets of signatures, acceptance range is defined. If the Euclidian distance of a query signature is within the acceptance range then it is detected as an authenticated signature else, a forged signature.
Extracted statement — Classifier: GMM
Research field: Science
Title: Estimating the relationship between economic growth and environmental quality for the brics economies - a dynamic panel data approach
Abstract: It has been forecasted by many economists that in the next couple of decades the BRICS economies are going to experience an unprecedented economic growth. This massive economic growth would definitely have a detrimental impact on the environment since these economies, like others, would extract their environmental and natural resource to a larger scale in the process of their economic growth. Therefore, maintaining environmental quality while growing has become a major challenge for these economies. However, the proponents of Environmental Kuznets Curve (EKC) Hypothesis - an inverted U shape relationship between income and emission per capita, suggest BRICS economies need not bother too much about environmental quality while growing because growth would eventually take care of the environment once a certain level of per capita income is achieved. In this backdrop, the present study makes an attempt to estimate EKC type relationship, if any, between income and emission in the context of the BRICS countries for the period 1997 to 2011. Therefore, the study first adopts fixed effect (FE) panel data model to control time constant country specific effects, and then uses Generalized Method of Moments (GMM) approach for dynamic panel data to address endogeneity of income variable and dynamism in emission per capita. Apart from income, we also include variables related to financial sector development and energy utilization to explain emission. The fixed effect model shows a significant EKC type relation between income and emission supporting the previous literature. However, GMM estimates for the dynamic panel model show the relationship between income and emission is actually U shaped with the turning point being out of sample. This out of sample turning point indicates that emission has been growing monotonically with growth in income. Factors like, net energy imports and share of industrial output in GDP are found to be significant and having detrimental impact on the environment in the dynamic panel model. However, these variables are found to be insignificant in FE model. Capital account convertibility shows significant and negative impact on the environment irrespective of models used. The monotonically increasing relationship between income and emission suggests the BRICS economies must adopt some efficiency oriented action plan so that they can grow without putting much pressure on the environment. These findings can have important policy implications as BRICS countries are mainly depending on these factors for their growth but at the same time they can cause serious threat to the environment.
Extracted statement — Methodology: GMM
Research field: Science
Title: Are proposed African monetary unions optimal currency areas? Real, monetary and fiscal policy convergence analysis
Abstract: Purpose – A spectre is hunting embryonic African monetary zones: the EMU crisis. This paper assesses real, monetary and fiscal policy convergence within the proposed WAM and EAM zones. The introduction of common currencies in West and East Africa is facing stiff challenges in the timing of monetary convergence, the imperative of central bankers to apply common modeling and forecasting methods of monetary policy transmission, as well as the requirements of common structural and institutional characteristics among candidate states. Design/methodology/approach – In the analysis: monetary policy targets inflation and financial dynamics of depth, efficiency, activity and size; real sector policy targets economic performance in terms of GDP growth at macro and micro levels; while, fiscal policy targets debt-to-GDP and deficit-to-GDP ratios. A dynamic panel GMM estimation with data from different non-overlapping intervals is employed. The implied rate of convergence and the time required to achieve full (100%) convergence are then computed from the estimations. Findings – Findings suggest overwhelming lack of convergence: (1) initial conditions for financial development are different across countries; (2) fundamental characteristics as common monetary policy initiatives and IMF backed financial reform programs are implemented differently across countries; (3) there is remarkable evidence of cross-country variations in structural characteristics of macroeconomic performance; (4) institutional cross-country differences could also be responsible for the deficiency in convergence within the potential monetary zones; (5) absence of fiscal policy convergence and no potential for eliminating idiosyncratic fiscal shocks due to business cycle incoherence. Practical implications – As a policy implication, heterogeneous structural and institutional characteristics across countries are giving rise to different levels and patterns of financial intermediary development. Thus, member states should work towards harmonizing cross-country differences in structural and institutional characteristics that hamper the effectiveness of convergence in monetary, real and fiscal policies. This could be done by stringently monitoring the implementation of existing common initiatives and/or the adoption of new reforms programs. Originality/value – It is one of the few attempts to investigate the issue of convergence within the proposed WAM and EAM unions.
Extracted statement — Methodology: GMM
Research field: Science
Title: Distributed clustering in ad-hoc sensor networks: a hybrid, energy-efficient approach
Abstract: Prolonged network lifetime, scalability, and load balancing are important requirements for many ad-hoc sensor network applications. Clustering sensor nodes is an effective technique for achieving these goals. In this work, we propose a new energy-efficient approach for clustering nodes in ad-hoc sensor networks. Based on this approach, we present a protocol, HEED (hybrid energy-efficient distributed clustering), that periodically selects cluster heads according to a hybrid of their residual energy and a secondary parameter, such as node proximity to its neighbors or node degree. HEED does not make any assumptions about the distribution or density of nodes, or about node capabilities, e.g., location-awareness. The clustering process terminates in O(1) iterations, and does not depend on the network topology or size. The protocol incurs low overhead in terms of processing cycles and messages exchanged. It also achieves fairly uniform cluster head distribution across the network. A careful selection of the secondary clustering parameter can balance load among cluster heads. Our simulation results demonstrate that HEED outperforms weight-based clustering protocols in terms of several cluster characteristics. We also apply our approach to a simple application to demonstrate its effectiveness in prolonging the network lifetime and supporting data aggregation.
Extracted statement — Protocol: HEED
Research field: Science
Title: Control of a batch polymerization system using hybrid neural network - First principle model
Abstract: In this work, the utilization of neural network in hybrid with first principle models for modelling and control of a batch polymerization process was investigated. Following the steps of the methodology, hybrid neural network (HNN) forward models and HNN inverse model of the process were first developed and then the performance of the model in direct inverse control strategy and internal model control (IMC) strategy was investigated. For comparison purposes, the performance of conventional neural network and PID controller in control was compared with the proposed HNN. The results show that HNN is able to control perfectly for both set points tracking and disturbance rejection studies.
Extracted statement — Types: HNN
Research field: Science
Title: Organizational Resilience
and Using Information
and Communication
Technologies to Rebuild
Communication Structures
Abstract: This study employs the perspective of organizational resilience to examine how information and communication technologies (ICTs) were used by organizations to aid in their recovery after Hurricane Katrina. In-depth interviews enabled longitudinal analysis of ICT use. Results showed that organizations enacted a variety of resilient behaviors through adaptive ICT use, including information sharing, (re)connection, and resource acquisition. Findings emphasize the transition of ICT use across different stages of recovery, including an anticipated stage. Key findings advance organizational resilience theory with an additional source of resilience, external availability. Implications and contributions to the literature of ICTs in disaster contexts and organizational resilience are discussed.
Extracted statement — Technology: ICT
Research field: Science
Title: An Enhanced Spatio-spectral Template for Automatic Small Recreational Vessel Detection
Abstract: This paper examines the performance of a spatiospectral template on Ikonos imagery to automatically detect small recreational boats. The spatiospectral template is utilized and then enhanced through the use of a weighted Euclidean distance metric adapted from the Mahalanobis distance metric. The aim is to assist the Canadian Coast Guard in gathering data on recreational boating for the modeling of search and rescue incidence risk. To test the detection accuracy of the enhanced spatiospectral template, a dataset was created by gathering position and attribute data for 53 recreational vessel targets purposely moored for this research within Cadboro Bay, British Columbia, Canada. The Cadboro Bay study site containing the targets was imaged using Ikonos. Overall detection accuracy was 77%. Targets were broken down into 2 categories: 1) Category A-less than 6 m in length, and Category B-more than 6 m long. The detection rate for Category B targets was 100%, while the detection rate for Category A targets was 61%. It is important to note that some Category A targets were intentionally selected for their small size to test the detection limits of the enhanced spatiospectral template. The smallest target detected was 2.2 m long and 1.1 m wide. The analysis also revealed that the ability to detect targets between 2.2 and 6 m long was diminished if the target was dark in color.
Extracted statement — Satellite sensor: IKONOS
Research field: Science
Title: Online prediction of polymer product quality in an industrial reactor using recurrent neural networks
Abstract: In this paper, internally recurrent neural networks (IRNN) are used to predict a key polymer product quality variable from an industrial polymerization reactor. IRNN are selected as the modeling tools for two reasons: 1) over the wide range of operating regions required to make multiple polymer grades, the process is highly nonlinear; and 2) the finishing of the polymer product after it leaves the reactor imparts significant dynamics to the process by "mixing" effects. IRNN are shown to be very effective tools for predicting key polymer quality variables from secondary measurements taken around the reactor.
Extracted statement — Types: IRN
Research field: Science
Title: LCM: A Link-Aware Clustering Mechanism for Energy-Efficient Routing in Wireless Sensor Networks
Abstract: In wireless sensor networks, nodes in the area of interest must report sensing readings to the sink, and this report always satisfies the report frequency required by the sink. This paper proposes a link-aware clustering mechanism, called LCM, to determine an energy-efficient and reliable routing path. The LCM primarily considers node status and link condition, and uses a novel clustering metric called the predicted transmission count (PTX), to evaluate the qualification of nodes for clusterheads and gateways to construct clusters. Each clusterhead or gateway candidate depends on the PTX to derive its priority, and the candidate with the highest priority becomes the clusterhead or gateway. Simulation results validate that the proposed LCM significantly outperforms the clustering mechanisms using random selection and by considering only link quality and residual energy in the packet delivery ratio, energy consumption, and delivery latency.
Extracted statement — Protocol: LCM
Research field: Science
Title: Energy-efficient communication protocol for wireless microsensor networks
Abstract: Wireless distributed microsensor systems will enable the reliable monitoring of a variety of environments for both civil and military applications. In this paper, we look at communication protocols, which can have significant impact on the overall energy dissipation of these networks. Based on our findings that the conventional protocols of direct transmission, minimum-transmission-energy, multi-hop routing, and static clustering may not be optimal for sensor networks, we propose LEACH (Low-Energy Adaptive Clustering Hierarchy), a clustering-based protocol that utilizes randomized rotation of local cluster based station (cluster-heads) to evenly distribute the energy load among the sensors in the network. LEACH uses localized coordination to enable scalability and robustness for dynamic networks, and incorporates data fusion into the routing protocol to reduce the amount of information that must be transmitted to the base station. Simulations show the LEACH can achieve as much as a factor of 8 reduction in energy dissipation compared with conventional outing protocols. In addition, LEACH is able to distribute energy dissipation evenly throughout the sensors, doubling the useful system lifetime for the networks we simulated.
Extracted statement — Protocol: LEACH