Moussab/ORKG-training-evaluation-set huggingface dataset:
Research field: Science
Title: Mobility-based clustering protocol for wireless sensor networks with mobile nodes
Abstract: In this study, the authors propose a mobility-based clustering (MBC) protocol for wireless sensor networks with mobile nodes. In the proposed clustering protocol, a sensor node elects itself as a cluster-head based on its residual energy and mobility. A non-cluster-head node aims at its link stability with a cluster head during clustering according to the estimated connection time. Each non-cluster-head node is allocated a timeslot for data transmission in ascending order in a time division multiple address (TDMA) schedule based on the estimated connection time. In the steady-state phase, a sensor node transmits its sensed data in its timeslot and broadcasts a joint request message to join in a new cluster and avoid more packet loss when it has lost or is going to lose its connection with its cluster head. Simulation results show that the MBC protocol can reduce the packet loss by 25% compared with the cluster-based routing (CBR) protocol and 50% compared with the low-energy adaptive clustering hierarchy-mobile (LEACH-mobile) protocol. Moreover, it outperforms both the CBR protocol and the LEACH-mobile protocol in terms of average energy consumption and average control overhead, and can better adapt to a highly mobile environment.
Extracted statement — Protocol: MBC
Research field: Science
Title: New insights into the prognostic impact of the karyotype in MDS and correlation with subtypes: evidence from a core dataset of 2124 patients
Abstract: We have generated a large, unique database that includes morphologic, clinical, cytogenetic, and follow-up data from 2124 patients with myelodysplastic syndromes (MDSs) at 4 institutions in Austria and 4 in Germany. Cytogenetic analyses were successfully performed in 2072 (97.6%) patients, revealing clonal abnormalities in 1084 (52.3%) patients. Numeric and structural chromosomal abnormalities were documented for each patient and subdivided further according to the number of additional abnormalities. Thus, 684 different cytogenetic categories were identified. The impact of the karyotype on the natural course of the disease was studied in 1286 patients treated with supportive care only. Median survival was 53.4 months for patients with normal karyotypes (n = 612) and 8.7 months for those with complex anomalies (n = 166). A total of 13 rare abnormalities were identified with good (+1/+1q, t(1q), t(7q), del(9q), del(12p), chromosome 15 anomalies, t(17q), monosomy 21, trisomy 21, and -X), intermediate (del(11q), chromosome 19 anomalies), or poor (t(5q)) prognostic impact, respectively. The prognostic relevance of additional abnormalities varied considerably depending on the chromosomes affected. For all World Health Organization (WHO) and French-American-British (FAB) classification system subtypes, the karyotype provided additional prognostic information. Our analyses offer new insights into the prognostic significance of rare chromosomal abnormalities and specific karyotypic combinations in MDS.
Extracted statement — Disease: MDS
Research field: Science
Title: MLGA: a multilevel cooperative genetic algorithm
Abstract: This paper incorporate the multilevel selection (MLS) theory into the genetic algorithm. Based on this theory, a Multilevel Cooperative Genetic Algorithm (MLGA) is presented. In MLGA, a species is subdivided in a set of populations, each population is subdivided in groups, and evolution occurs at two levels so called individual and group level. A fast population dynamics occurs at individual level. At this level, selection occurs between individuals of the same group. The popular genetic operators such as mutation and crossover are applied within groups. A slow population dynamics occurs at group level. At this level, selection occurs between groups of a population. A group level operator so called colonization is applied between groups in which a group is selected as extinct, and replaced by offspring of a colonist group. We used a set of well known numerical functions in order to evaluate performance of the proposed algorithm. The results showed that the MLGA is robust, and provides an efficient way for numerical function optimization.
Extracted statement — Name: MLGA
Research field: Science
Title: WSN16-5: Distributed Formation of Overlapping Multi-hop Clusters in Wireless Sensor Networks
Abstract: Clustering is a standard approach for achieving efficient and scalable performance in wireless sensor networks. Most of the published clustering algorithms strive to generate the minimum number of disjoint clusters. However, we argue that guaranteeing some degree of overlap among clusters can facilitate many applications, like inter-cluster routing, topology discovery and node localization, recovery from cluster head failure, etc. We formulate the overlapping multi-hop clustering problem as an extension to the k-dominating set problem. Then we propose MOCA; a randomized distributed multi-hop clustering algorithm for organizing the sensors into overlapping clusters. We validate MOCA in a simulated environment and analyze the effect of different parameters, e.g. node density and network connectivity, on its performance. The simulation results demonstrate that MOCA is scalable, introduces low overhead and produces approximately equal-sized clusters.
Extracted statement — Protocol: MOCA
Research field: Science
Title: A Multi-objective Approach to Testing Resource Allocation in Modular Software Systems
Abstract: Nowadays, as the software systems become increasingly large and complex, the problem of allocating the limited testing-resource during the testing phase has become more and more difficult. In this paper, we propose to solve the testing-resource allocation problem (TRAP) using multi-objective evolutionary algorithms. Specifically, we formulate TRAP as two multi-objective problems. First, we consider the reliability of the system and the testing cost as two objectives. In the second formulation, the total testing-resource consumed is also taken into account as the third goal. Two multi-objective evolutionary algorithms, non-dominated sorting genetic algorithm II (NSGA2) and multi-objective differential evolution algorithms (MODE), are applied to solve the TRAP in the two scenarios. This is the first time that the TRAP is explicitly formulated and solved by multi-objective evolutionary approaches. Advantages of our approaches over the state-of-the-art single-objective approaches are demonstrated on two parallel-series modular software models.
Extracted statement — Algorithm(s): MODE
Research field: Science
Title: Ship detection in MODIS imagery
Abstract: Understanding the capabilities of satellite sensors with spatial and spectral characteristics similar to those of MODIS for Maritime Domain Awareness (MDA) is of importance because of the upcoming NPOES with 100 minutes revisit time carrying the MODIS-like VIIRS multispectral imaging sensor. This paper presents an experimental study of ship detection using MODIS imagery. We study the use of ship signatures such as contaminant plumes in clouds and the spectral contrast between the ship and the sea background for detection. Results show the potential and challenges for such approach in MDA.
Extracted statement — Satellite sensor: MODIS
Research field: Science
Title: Single and Multi Objective Genetic Programming for Software Development Effort Estimation
Abstract: The idea of exploiting Genetic Programming (GP) to estimate software development effort is based on the observation that the effort estimation problem can be formulated as an optimization problem. Indeed, among the possible models, we have to identify the one providing the most accurate estimates. To this end a suitable measure to evaluate and compare different models is needed. However, in the context of effort estimation there does not exist a unique measure that allows us to compare different models but several different criteria (e.g., MMRE, Pred(25), MdMRE) have been proposed. Aiming at getting an insight on the effects of using different measures as fitness function, in this paper we analyzed the performance of GP using each of the five most used evaluation criteria. Moreover, we designed a Multi-Objective Genetic Programming (MOGP) based on Pareto optimality to simultaneously optimize the five evaluation measures and analyzed whether MOGP is able to build estimation models more accurate than those obtained using GP. The results of the empirical analysis, carried out using three publicly available datasets, showed that the choice of the fitness function significantly affects the estimation accuracy of the models built with GP and the use of some fitness functions allowed GP to get estimation accuracy comparable with the ones provided by MOGP.
Extracted statement — Algorithm(s): MOGP
Research field: Science
Title: Multihop Routing Protocol with Unequal Clustering for Wireless Sensor Networks
Abstract: In order to prolong the lifetime of wireless sensor networks, this paper presents a multihop routing protocol with unequal clustering (MRPUC). On the one hand, cluster heads deliver the data to the base station with relay to reduce energy consumption. On the other hand, MRPUC uses many measures to balance the energy of nodes. First, it selects the nodes with more residual energy as cluster heads, and clusters closer to the base station have smaller sizes to preserve some energy during intra-cluster communication for inter-cluster packets forwarding. Second, when regular nodes join clusters, they consider not only the distance to cluster heads but also the residual energy of cluster heads. Third, cluster heads choose those nodes as relay nodes, which have minimum energy consumption for forwarding and maximum residual energy to avoid dying earlier. Simulation results show that MRPUC performs much better than similar protocols.
Extracted statement — Protocol: MRPUC
Research field: Science
Title: Chromosomal abnormalities in untreated patients with non-Hodgkin’s lymphoma: associations with histology, clinical characteristics, and treatment outcome. The Nebraska Lymphoma Study Group
Abstract: We describe the chromosomal abnormalities found in 104 previously untreated patients with non-Hodgkin's lymphoma (NHL) and the correlations of these abnormalities with disease characteristics. The cytogenetic method used was a 24- to 48-hour culture, followed by G-banding. Several significant associations were discovered. A trisomy 3 was correlated with high-grade NHL. In the patients with an immunoblastic NHL, an abnormal chromosome no. 3 or 6 was found significantly more frequently. As previously described, a t(14;18) was significantly correlated with a follicular growth pattern. Abnormalities on chromosome no. 17 were correlated with a diffuse histology and a shorter survival. A shorter survival was also correlated with a +5, +6, +18, all abnormalities on chromosome no. 5, or involvement of breakpoint 14q11-12. In a multivariate analysis, these chromosomal abnormalities appeared to be independent prognostic factors and correlated with survival more strongly than any traditional prognostic variable. Patients with a t(11;14)(q13;q32) had an elevated lactate dehydrogenase (LDH). Skin infiltration was correlated with abnormalities on 2p. Abnormalities involving breakpoints 6q11-16 were correlated with B symptoms. Patients with abnormalities involving breakpoints 3q21-25 and 13q21-24 had more frequent bulky disease. The correlations of certain clinical findings with specific chromosomal abnormalities might help unveil the pathogenetic mechanisms of NHL and tailor treatment regimens.
Extracted statement — Disease: NHL
Research field: Science
Title: An econometric study of carbon dioxide (CO2) emissions, energy consumption, and economic growth of Pakistan
Abstract: Purpose – The purpose of this paper is to examine the relationship among environmental pollution, economic growth and energy consumption per capita in the case of Pakistan. The per capital carbon dioxide (CO2) emission is used as the environmental indicator, the commercial energy use per capita as the energy consumption indicator, and the per capita gross domestic product (GDP) as the economic indicator.Design/methodology/approach – The investigation is made on the basis of the environmental Kuznets curve (EKC), using time series data from 1971 to 2006, by applying different econometric tools like ADF Unit Root Johansen Co‐integration VECM and Granger causality tests.Findings – The Granger causality test shows that there is a long term relationship between these three indicators, with bidirectional causality between per capita CO2 emission and per capita energy consumption. A monotonically increasing curve between GDP and CO2 emission has been found for the sample period, rejecting the EKC relationship, i...
Extracted statement — Methodology: OLS
Research field: Science
Title: Object oriented ship detection from VHR satellite images
Abstract: Within today's security environment and with increasing worldwide travel and transport of dangerous goods the need of vessel traffic services, ship routing and monitoring of ship movements on sea and along coastlines becomes more time consuming and an important responsibility for coastal authorities. This paper describes the architecture of a ship detection prototype based on an object-oriented methodology to support these monitoring tasks. The system’s architecture comprises a fully-automatic coastline detection tool, a tool for fully or semiautomatic ship detection in off-shore areas and a semi-automatic tool for ship detection within harbour-areas. Its core is based on the client-server environment of the first object-oriented image analysis software on the market named eCognition. The described ship detection system has been developed for panchromatic VHR satellite image data and has proven its capabilities on Ikonos and QuickBird imagery under different weather conditions and for various regions of the world. With the capability of eCognition to combine raster data with imported thematic data it is possible to work with available non-remote sensing based data e.g. detailed harbour GIS information in ESRI shape file format or weather information, which can be attached to the results. Finally the system’s ability of generating customized reports in HTML format and the possibility of exporting results in standard raster or vector format offers new opportunities in the direction of an interoperability of technology where a great number of heterogeneous networks and operators are involved in the surveillance process.
Extracted statement — Band: PAN
Research field: Science
Title: Ship detection and classification from overhead imagery
Abstract: This paper presents a sequence of image-processing algorithms suitable for detecting and classifying ships from nadir panchromatic electro-optical imagery. Results are shown of techniques for overcoming the presence of background sea clutter, sea wakes, and non-uniform illumination. Techniques are presented to measure vessel length, width, and direction-of-motion. Mention is made of the additional value of detecting identifying features such as unique superstructure, weaponry, fuel tanks, helicopter landing pads, cargo containers, etc. Various shipping databases are then described as well as a discussion of how measured features can be used as search parameters in these databases to pull out positive ship identification. These are components of a larger effort to develop a low-cost solution for detecting the presence of ships from readily-available overhead commercial imagery and comparing this information against various open-source ship-registry databases to categorize contacts for follow-on analysis.
Extracted statement — Band: PAN
Research field: Science
Title: Enhanced ship detection from overhead imagery
Abstract: In the authors' previous work, a sequence of image-processing algorithms was developed that was suitable for detecting and classifying ships from panchromatic Quickbird electro-optical satellite imagery. Presented in this paper are several new algorithms, which improve the performance and enhance the capabilities of the ship detection software, as well as an overview on how land masking is performed. Specifically, this paper describes the new algorithms for enhanced detection including for the reduction of false detects such as glint and clouds. Improved cloud detection and filtering algorithms are described as well as several texture classification algorithms are used to characterize the background statistics of the ocean texture. These detection algorithms employ both cloud and glint removal techniques, which we describe. Results comparing ship detection with and without these false detect reduction algorithms are provided. These are components of a larger effort to develop a low-cost solution for detecting the presence of ships from readily-available overhead commercial imagery and comparing this information against various open-source ship-registry databases to categorize contacts for follow-on analysis.
Extracted statement — Band: PAN
Research field: Science
Title: Using SPOT-5 HRG Data in Panchromatic Mode for Operational Detection of Small Ships in Tropical Area
Abstract: Nowadays, there is a growing interest in applications of space remote sensing systems for maritime surveillance which includes among others traffic surveillance, maritime security, illegal fisheries survey, oil discharge and sea pollution monitoring. Within the framework of several French and European projects, an algorithm for automatic ship detection from SPOT–5 HRG data was developed to complement existing fishery control measures, in particular the Vessel Monitoring System. The algorithm focused on feature–based analysis of satellite imagery. Genetic algorithms and Neural Networks were used to deal with the feature–borne information. Based on the described approach, a first prototype was designed to classify small targets such as shrimp boats and tested on panchromatic SPOT–5, 5–m resolution product taking into account the environmental and fishing context. The ability to detect shrimp boats with satisfactory detection rates is an indicator of the robustness of the algorithm. Still, the benchmark revealed problems related to increased false alarm rates on particular types of images with a high percentage of cloud cover and a sea cluttered background.
Extracted statement — Band: PAN
Research field: Science
Title: Fully automated procedure for ship detection using optical satellite imagery
Abstract: Ship detection from remote sensing imagery is a crucial application for maritime security which includes among others traffic surveillance, protection against illegal fisheries, oil discharge control and sea pollution monitoring. In the framework of a European integrated project GMES-Security/LIMES, we developed an operational ship detection algorithm using high spatial resolution optical imagery to complement existing regulations, in particular the fishing control system. The automatic detection model is based on statistical methods, mathematical morphology and other signal processing techniques such as the wavelet analysis and Radon transform. This paper presents current progress made on the detection model and describes the prototype designed to classify small targets. The prototype was tested on panchromatic SPOT 5 imagery taking into account the environmental and fishing context in French Guiana. In terms of automatic detection of small ship targets, the proposed algorithm performs well. Its advantages are manifold: it is simple and robust, but most of all, it is efficient and fast, which is a crucial point in performance evaluation of advanced ship detection strategies.
Extracted statement — Band: PAN
Research field: Science
Title: A complete processing chain for ship detection using optical satellite imagery
Abstract: Ship detection from remote sensing imagery is a crucial application for maritime security, which includes among others traffic surveillance, protection against illegal fisheries, oil discharge control and sea pollution monitoring. In the framework of a European integrated project Global Monitoring for Environment and Security (GMES) Security/Land and Sea Integrated Monitoring for European Security (LIMES), we developed an operational ship detection algorithm using high spatial resolution optical imagery to complement existing regulations, in particular the fishing control system. The automatic detection model is based on statistical methods, mathematical morphology and other signal-processing techniques such as the wavelet analysis and Radon transform. This article presents current progress made on the detection model and describes the prototype designed to classify small targets. The prototype was tested on panchromatic Satellite Pour l'Observation de la Terre (SPOT) 5 imagery taking into account the environmental and fishing context in French Guiana. In terms of automatic detection of small ship targets, the proposed algorithm performs well. Its advantages are manifold: it is simple and robust, but most of all, it is efficient and fast, which is a crucial point in performance evaluation of advanced ship detection strategies.
Extracted statement — Band: PAN
Research field: Science
Title: Ship detection in satellite imagery using rank-order grayscale hit-or-miss transforms
Abstract: Ship detection from satellite imagery is something that has great utility in various communities. Knowing where ships are and their types provides useful intelligence information. However, detecting and recognizing ships is a difficult problem. Existing techniques suffer from too many false-alarms. We describe approaches we have taken in trying to build ship detection algorithms that have reduced false alarms. Our approach uses a version of the grayscale morphological Hit-or-Miss transform. While this is well known and used in its standard form, we use a version in which we use a rank-order selection for the dilation and erosion parts of the transform, instead of the standard maximum and minimum operators. This provides some slack in the fitting that the algorithm employs and provides a method for tuning the algorithm's performance for particular detection problems. We describe our algorithms, show the effect of the rank-order parameter on the algorithm's performance and illustrate the use of this approach for real ship detection problems with panchromatic satellite imagery.
Extracted statement — Band: PAN
Research field: Science
Title: Characterization of a Bayesian Ship Detection Method in Optical Satellite Images
Abstract: This letter presents the experimental results obtained for an automatic predetection of small ships (about 5 &times; 5 pixels) in high-resolution optical satellite images. Our images are panchromatic SPOT 5 images, whose resolution is 5 m per pixel. Our detection method is based on the Bayesian decision theory and does not need any preprocessing. Here, we describe the method precisely and the tuning of its two parameters, namely, the size of the analysis window and the threshold used to make a decision. Both are fixed from the receiver operating-characteristic curves that we draw from different sets of tests. Finally, the overall results of the method are given for a set of images, as close as possible to the operational conditions.
Extracted statement — Band: PAN