Prominent Field Research Articles

Eco-Systems Mapping and Forecasting of Techno-Science Linkages at the Level of Scholarly Journals and Fields

Based on the number of references to patents aggregated at the level of journals, we develop two indicators of linkages between the sciences and technologies: patent intensity (PI) and patent density (PD). Journal maps can be overlaid with the values of PD and PI so that the portfolios can visually be identified and analytically be compared across fields. Distributions of techno-science linkages among journals and groups of journals are analyzed. Chemistry and Nano Science are the most prominent fields in patent references, but these linkages show declining trends. The continuity in terms of citing patents in successive years in these two fields are significantly higher than in other fields. Nano Science is composed of eight subfields, among which the chemistry-related subfields have the highest percentage of journals citing patents in successive years. Patent citations are very specific in domains other than Chemistry and Nano Science; patent citation in the Social Sciences, however, is above expectation.

A probability distribution function for investigating node infection and removal times

AbstractConsidering the important issue of computer infections by worms spread via networks, the theme of source identification has been a prominent research field that aims at investigating infection propagation including acquiring knowledge about the infection and the node removal times when a worm infection happens. This information helps in identifying the patient zero in the worm attack and may be used by computer forensic investigators and network administrators to spot the culprits and to identify related network vulnerabilities. In this paper, we tackle this problem by developing new probabilistic models based on Bayesian networks. We learn a probability distribution to calculate, at every time step, the probability that each node is infected by a scanning worm, using historical data and features extracted from the network and application layers. With the mentioned probability distribution, the node infection status can be inferred using feature values at each time step. We propose a four‐step method to investigate the time of infection and removal of each node probabilistically. First, features are extracted and derived from network traffic data. There are no suitable training and test datasets publicly available for our tests; therefore, we developed the training and test datasets using simulations of the Code Red II worm. Second, a prior model is built using training data. Third, the probabilistic model is built by the estimation of distribution algorithm. Fourth, the infection probability of nodes is inferred given the probability distribution and feature values at each time step. It has already been shown that the number of infectious nodes can be probabilistically approximated backward in time through the stochastic Back‐to‐Origin Markov model. We combine our first model with the prior stochastic Back‐to‐Origin Markov model to develop our second model. To evaluate our first and second models, we conducted experiments that show that these models can pinpoint the source node and the infection time of nodes with acceptable accuracy. It should be noted that our method could be employed with other propagating worm types including ransomware worms.

A New Generalized Projection and Its Application to Acceleration of Audio Declipping

In convex optimization, it is often inevitable to work with projectors onto convex sets composed with a linear operator. Such a need arises from both the theory and applications, with signal processing being a prominent and broad field where convex optimization has been used recently. In this article, a novel projector is presented, which generalizes previous results in that it admits to work with a broader family of linear transforms when compared with the state of the art but, on the other hand, it is limited to box-type convex sets in the transformed domain. The new projector is described by an explicit formula, which makes it simple to implement and requires a low computational cost. The projector is interpreted within the framework of the so-called proximal splitting theory. The convenience of the new projector is demonstrated on an example from signal processing, where it was possible to speed up the convergence of a signal declipping algorithm by a factor of more than two.

Multigroup Classification using Privacy Preserving Data Mining

Getting the useful and important data from a huge amount of information is known as data mining. It is a prominent field for search and research of data. To improve the communication between customers and organizations data mining is used. Preserve the private data is very necessary in data mining. It is the issue on which research developed their research in many different ways. For protecting the survey privacy and to avoid the bias answer the randomized response technique was developed. To prevent the data of the survey certain randomness will add with the answers. To improve the privacy level of the preserve data this research use multigroup methods. In this approach all the survey answer divided in multiple groups and then. For different groups data should randomize differently. Based on this multiple groups the decision tree used to classify the data. One group, two group and three group’s techniques used to preserve the data.

A Survey of Security Services, Attacks, and Applications for Vehicular Ad Hoc Networks (VANETs).

Vehicular ad hoc networks (VANETs) are an emerging type of mobile ad hoc networks (MANETs) with robust applications in intelligent traffic management systems. VANET has drawn significant attention from the wireless communication research community and has become one of the most prominent research fields in intelligent transportation system (ITS) because of the potential to provide road safety and precautionary measures for the drivers and passengers. In this survey, we discussed the basic overview of the VANET from the architecture, communication methods, standards, characteristics, and VANET security services. Second, we presented the threats and attacks and the recent state-of-the-art methods of the VANET security services. Then, we comprehensively reviewed the authentication schemes that can protect vehicular networks from malicious nodes and fake messages. Third, we discussed the latest simulation tools and the performance of the authentication schemes in terms of simulation tools, which was followed by the VANET applications. Lastly, we identified the open research challenges and gave future research directions. In sum, this survey fills the gap of existing surveys and summarizes the latest research development. All the security attacks in VANETs and their related countermeasures are discussed with respect to ensuring secure communication. The authentication schemes and comprehensive applications were introduced and analyzed in detail. In addition, open research challenges and future research directions were issued.

Substantial batch effects in TCGA exome sequences undermine pan-cancer analysis of germline variants

BackgroundIn recent years, research on cancer predisposition germline variants has emerged as a prominent field. The identity of somatic mutations is based on a reliable mapping of the patient germline variants. In addition, the statistics of germline variants frequencies in healthy individuals and cancer patients is the basis for seeking candidates for cancer predisposition genes. The Cancer Genome Atlas (TCGA) is one of the main sources of such data, providing a diverse collection of molecular data including deep sequencing for more than 30 types of cancer from > 10,000 patients.MethodsOur hypothesis in this study is that whole exome sequences from blood samples of cancer patients are not expected to show systematic differences among cancer types. To test this hypothesis, we analyzed common and rare germline variants across six cancer types, covering 2241 samples from TCGA. In our analysis we accounted for inherent variables in the data including the different variant calling protocols, sequencing platforms, and ethnicity.ResultsWe report on substantial batch effects in germline variants associated with cancer types. We attribute the effect to the specific sequencing centers that produced the data. Specifically, we measured 30% variability in the number of reported germline variants per sample across sequencing centers. The batch effect is further expressed in nucleotide composition and variant frequencies. Importantly, the batch effect causes substantial differences in germline variant distribution patterns across numerous genes, including prominent cancer predisposition genes such as BRCA1, RET, MAX, and KRAS. For most of known cancer predisposition genes, we found a distinct batch-dependent difference in germline variants.ConclusionTCGA germline data is exposed to strong batch effects with substantial variabilities among TCGA sequencing centers. We claim that those batch effects are consequential for numerous TCGA pan-cancer studies. In particular, these effects may compromise the reliability and the potency to detect new cancer predisposition genes. Furthermore, interpretation of pan-cancer analyses should be revisited in view of the source of the genomic data after accounting for the reported batch effects.

Computer Vision in Autonomous Unmanned Aerial Vehicles—A Systematic Mapping Study

Personal assistant robots provide novel technological solutions in order to monitor people’s activities, helping them in their daily lives. In this sense, unmanned aerial vehicles (UAVs) can also bring forward a present and future model of assistant robots. To develop aerial assistants, it is necessary to address the issue of autonomous navigation based on visual cues. Indeed, navigating autonomously is still a challenge in which computer vision technologies tend to play an outstanding role. Thus, the design of vision systems and algorithms for autonomous UAV navigation and flight control has become a prominent research field in the last few years. In this paper, a systematic mapping study is carried out in order to obtain a general view of this subject. The study provides an extensive analysis of papers that address computer vision as regards the following autonomous UAV vision-based tasks: (1) navigation, (2) control, (3) tracking or guidance, and (4) sense-and-avoid. The works considered in the mapping study—a total of 144 papers from an initial set of 2081—have been classified under the four categories above. Moreover, type of UAV, features of the vision systems employed and validation procedures are also analyzed. The results obtained make it possible to draw conclusions about the research focuses, which UAV platforms are mostly used in each category, which vision systems are most frequently employed, and which types of tests are usually performed to validate the proposed solutions. The results of this systematic mapping study demonstrate the scientific community’s growing interest in the development of vision-based solutions for autonomous UAVs. Moreover, they will make it possible to study the feasibility and characteristics of future UAVs taking the role of personal assistants.

Responsibility, planning and risk management: moralizing everyday finance through financial education.

The individualization, privatization and marketization of risk management represent a fundamental dimension of the financialization of everyday life. As individuals are required to engage with financial products and services as the main way of protecting themselves from risks and uncertainties, their economic welfare and security are construed as depending largely on their own financial decisions. Within this setting, the concept of financial literacy and accompanying practices of financial education have emerged as a prominent institutional field handling the formulation and communication of the attributes and dispositions that arguably constitute the proper financial actor. This article analyzes financial education programmes currently conducted by state agencies in Israel, examining the notions and principles they articulate when defining and explaining proper financial conduct. The study indicates that moral themes and categories occupy a salient place in the formulation of the character traits that constitute the desired literate financial actor. Notions of individual responsibility, planning ahead and rational risk management are presented not merely as instrumental resources, but as moral imperatives. Through these notions, the programmes moralize a broad array of everyday practices of personal finance such as saving, investing, borrowing and budget management, thereby connecting the sphere of financial matters to the domain of moral virtues. Offering a representation of particular modes of financial conduct as constitutive components of morally virtuous personhood, these practices imbue the financial field as a whole, especially its current generalized logic of individualized and marketized risk management, with moral meanings, hence contributing to the normalization and depoliticization of the financialization of everyday life.

Analysis of the 1.3–1.7 yr Oscillation Relationship between Solar and Geomagnetic Activities

The study on the 1.3–1.7 yr period of the solar and geomagnetic activities is very important for understanding the possible physical processes in the solar-terrestrial coupling system. The sunspot is the most prominent magnetic field structure in the solar photosphere, and the Ap index is an important indicator for the global geomagnetic activity level. The 1.3–1.7 yr period for the sunspot number and the geomagnetic Ap index is obtained by the synchro-squeezing wavelet transform, and the phase relationship between them is studied by the cross-correlation analysis. The main results are as follows: (1) The 1.3–1.7 yr period of the geomagnetic Ap index and sunspot number exhibits an intermittent evolutionary characteristics, and changes continuously with the time; (2) the geomagnetic Ap index has a higher periodic component in the odd solar cycles than the neighboring even solar cycles, which is characterized by fluctuations; (3) the phase relationship between the geomagnetic Ap index and the sunspot number is not always invariant, in most cases the geomagnetic Ap index lags behind the sunspot number, except in the 18th and 22th solar cycles.

Improving public data for building segmentation from Convolutional Neural Networks (CNNs) for fused airborne lidar and image data using active contours

Robust and reliable automatic building detection and segmentation from aerial images/point clouds has been a prominent field of research in remote sensing, computer vision and point cloud processing for a number of decades. One of the largest issues associated with deep learning methods is the high quantity of data required for training. To help address this we present a method to improve public GIS building footprint labels by using Morphological Geodesic Active Contours (MorphGACs). We demonstrate by improving the quality of building footprint labels for detection and semantic segmentation, more robust and reliable models can be obtained. We evaluate these methods over a large UK-based dataset of 24556 images containing 169835 building instances. This is achieved by training several Mask/Faster R-CNN and RetinaNet deep convolutional neural networks. Networks are supplied with both RGB and fused RGB-lidar data. We offer quantitative analysis on the benefits of the inclusion of depth data for building segmentation. By employing both methods we achieve a detection accuracy of 0.92 (mAP@0.5) and segmentation f1 scores of 0.94 over a 4911 test images ranging from urban to rural scenes.

PTMphinder: an R package for PTM site localization and motif extraction from proteomic datasets.

BackgroundMass-spectrometry-based proteomics is a prominent field of study that allows for the unbiased quantification of thousands of proteins from a particular sample. A key advantage of these techniques is the ability to detect protein post-translational modifications (PTMs) and localize them to specific amino acid residues. These approaches have led to many significant findings in a wide range of biological disciplines, from developmental biology to cancer and infectious diseases. However, there is a current lack of tools available to connect raw PTM site information to biologically meaningful results in a high-throughput manner. Furthermore, many of the available tools require significant programming knowledge to implement.ResultsThe R package PTMphinder was designed to enable researchers, particularly those with minimal programming background, to thoroughly analyze PTMs in proteomic data sets. The package contains three functions: parseDB, phindPTMs and extractBackground. Together, these functions allow users to reformat proteome databases for easier analysis, localize PTMs within full proteins, extract motifs surrounding the identified sites and create proteome-specific motif backgrounds for statistical purposes. Beta-testing of this R package has demonstrated its simplicity and ease of integration with existing tools.ConclusionPTMphinder empowers researchers to fully analyze and interpret PTMs derived from proteomic data. This package is simple enough for researchers with limited programming experience to understand and implement. The data produced from this package can inform subsequent research by itself and also be used in conjunction with other tools, such as motif-x, for further analysis.

SFTRD: A novel information propagation model in heterogeneous networks: Modeling and restraining strategy

With the rapid growth of mobile devices, the platform of online social networks plays a prominent field for information spreading whether they are objective facts or fake news. To some degree, it can enable people to obtain more information faster and easier than before. However, the dynamical process of different information diffusion may generate different social influence. Especially, the negative information spreading may lead to economic losses or bring a serious social security threat. To explore the same information diffusion to different aspects, we propose an information propagation model SFTRD based on heterogeneous OSNs. SFTRD model not only considers the evolution of the same information, and also considers how to block the negative information spreading widely. Based on the theoretical analysis, the stability of equilibrium is performed by suitable analytical methods. The global asymptotic stability of the endemic equilibrium is studied by a geometric approach. The restrain strategies of spreading truth or blocking negative information are discussed by the optimal control theoretical. An optimal control method of SFTRD model is formulated, which minimizes the rumor-restraining cost within an expected time period. To validate the theoretical analysis of the proposed model, a set of numerical experiments are carried out with different parameter settings. Based on the theoretical analysis and numerical experiments, we can find that the process of information propagation is affected by various factors and we should explorer different inhibition strategies.

Process Technology, Applications and Thermal Resistivity of Basalt Fiber Reinforced SiOC Composites

Promising lightweight composite materials, bridging the gap between Polymer and Ceramic Matrix Composites, are manufactured as polymer derived ceramics by the use of polysiloxanes and basalt fibers. Such competitive free formable Hybrid Composites are supposed to be capable for lightweight applications in a temperature range between 300 °C and 850 °C and short time exposure up to over 1000 °C, even in oxidative atmosphere. Cheap raw materials like basalt fibers and siloxane resins in combination with performing manufacturing technologies can establish completely new markets for intermediate temperature composites. These attributes enable the Hybrid Composites as ideal material for fire retardant applications in automotive engineering and public transportation, as well as in fire protection systems in electrical and civil engineering applications. In this study, the most prominent fields of application and engineering solutions for Hybrid-CMC are reviewed and the results of the thermal resistivity analysis effectuated on basalt fiber reinforced SiOC samples are presented. This study consisted of several air exposures between 1 h and 50 h and temperatures in the range of 650 °C to 1100 °C. Remaining mechanical resistance was characterized by Impulse Excitation Technique (IET) and Interlaminar Shear Strength (ILSS) tests. Basalt fiber reinforced samples exhibited a decent level of mechanical performance even after the most demanding exposures. Due to the poor oxidation resistance of carbon fibers, Cf/SiOC composites were completely degraded after long-term exposure at 500 °C in air.

Nonradiating photonics with resonant dielectric nanostructures

AbstractNonradiating sources of energy have traditionally been studied in quantum mechanics and astrophysics but have received very little attention in the photonics community. This situation has changed recently due to a number of pioneering theoretical studies and remarkable experimental demonstrations of the exotic states of light in dielectric resonant photonic structures and metasurfaces, with the possibility to localize efficiently the electromagnetic fields of high intensities within small volumes of matter. These recent advances underpin novel concepts in nanophotonics and provide a promising pathway to overcome the problem of losses usually associated with metals and plasmonic materials for the efficient control of light-matter interaction at the nanoscale. This review paper provides a general background and several snapshots of the recent results in this young yet prominent research field, focusing on two types of nonradiating states of light that both have been recently at the center of many studies in all-dielectric resonant meta-optics and metasurfaces: opticalanapolesand photonicbound states in the continuum. We discuss a brief history of these states in optics, as well as their underlying physics and manifestations, and also emphasize their differences and similarities. We also review some applications of such novel photonic states in both linear and nonlinear optics for the nanoscale field enhancement, a design of novel dielectric structures with high-Qresonances, nonlinear wave mixing, and enhanced harmonic generation, as well as advanced concepts for lasing and optical neural networks.

Subsurface Sediment Mobilization in the Southern Chryse Planitia on Mars

AbstractThe southern part of the smooth plain of Chryse Planitia on Mars hosts a large population of kilometer‐sized (from ~0.2 to ~20 km) landforms spread over a wide area. Based on the investigation of a small part of this area, Komatsu et al. (2016, https://doi.org/10.1016/j.icarus.2015.12.032) proposed that the edifices may be the result of the subsurface sediment mobilization. We mapped the full extent of these landforms within Chryse Planitia and performed a morphological and spatial analysis in an attempt to further test this hypothesis. We identified a total number of 1,318 of these objects, which we grouped into five different morphological classes. The edifices can be observed over an area of 700,000 km2 near the termini of the large outflow channels, Ares, Simud, and Tiu Valles, with a nonrandom spatial distribution. The features are clustered and anticorrelated to the ancient highlands, which form erosional remnants shaped by the outflow events. This suggests a genetic link between the distribution of the edifices and the presence of the sedimentary deposits on which they are superposed. Such distribution is consistent with the previous notion that subsurface sediment mobilization may be the mechanism for their formation and is less consistent with the alternative igneous volcanic hypothesis. We also propose a scenario in which the large morphologic variability can be explained by variations of the water content within the ascending mud and by variations in the effusion rates. The edifices may represent one of the most prominent fields of sedimentary volcanism detected on Mars.

Bringing compassion into information systems research: A research agenda and call to action

In this article, we assert that compassion-driven approaches are the sustainable way for information and communication technologies to contribute to economic value. We urge future information systems research to emphasize, with equal vigor, the joint goals of compassion and financial gains from information and communication technologies. We present a broad agenda for future information systems research based on this premise. We also discuss how certain core assumptions underlying traditional information systems research—so far, driven primarily by economic value as outcome—would need to change in order to support this new agenda emphasizing compassion and economic value as complementary and synergistic outcomes. We provide a brief concrete illustration of this proposed agenda, and its underlying revised assumptions, by drawing on the example of a prominent field of study in information systems research, namely health information systems research.

Theoretical Analysis of the Optical Response of Silicon/Silica/Gold Multishell Nanoparticles in Biological Tissue

The scattering and absorption efficiencies of light by a single silicon/silica/gold spherical multishell in biological tissues are analyzed theoretically in the framework of Lorenz–Mie theory and finite-difference time-domain formalism. We first revised the ideal case of a concentric silicon/gold nanoshell, analyzed the effect of growing a silica layer of uniform thickness around the silicon core, and then examined the effect of an offset of the gold shell with respect to the centre of the silicon/silica nanoshell. Our simulation showed that the silicon/gold nanoshell in the biological tissue supports significant absorption and scattering resonances in the biological spectral window. On the contrary, the growth of a silica layer on the silicon core surface leads to a blueshift of these resonances accompanied by a slight increase of their magnitudes. The offset of the gold shell with respect to the silicon/silica core results in a redshift of the absorption and scattering resonances supported by the concentric silicon/silica/gold multishell within the biological window, accompanied by a decrease in their amplitudes. On the contrary, the gold shell offset gives rise to a more prominent electric field enhancement at the silicon/silica/gold multishell-biological tissue interface. Our simulation thus shows that silicon/silica/gold multishell nanoparticles are potential candidates in bioimaging and photothermal therapy applications.

SEMANTIC PHOTOGRAMMETRY – BOOSTING IMAGE-BASED 3D RECONSTRUCTION WITH SEMANTIC LABELING

Abstract. Automatic semantic segmentation of images is becoming a very prominent research field with many promising and reliable solutions already available. Labelled images as input for the photogrammetric pipeline have enormous potential to improve the 3D reconstruction results. To support this argument, in this work we discuss the contribution of image semantic labelling towards image-based 3D reconstruction in photogrammetry. We experiment semantic information in various steps starting from feature matching to dense 3D reconstruction. Labelling in 2D is considered as an easier task in terms of data availability and algorithm maturity. However, since semantic labelling of all the images involved in the reconstruction may be a costly, laborious and time consuming task, we propose to use a deep learning architecture to automatically generate semantically segmented images. To this end, we have trained a Convolutional Neural Network (CNN) on historic building façade images that will be further enriched in the future. The first results of this study are promising, with an improved performance on the quality of the 3D reconstruction and the possibility to transfer the labelling results from 2D to 3D.

Cloud Computing-Positive Impacts and Challenges in Business Perspective

Due to rapid growth of computing resources over the past years, cloud computing has been treated as a prominent research field and this technology appeared as a new solution in the IT field. Many businesses including small, medium and enterprise are migrating to this technology for so many reasons such as computing resources, reduced total cost of ownership, on demand services, increased revenue and many more. Cloud Computing offers number of advantages of cloud migration that motivated the business enterprises to adopt this change. There are so many challenges for the companies adopting cloud computing like interoperability, portability, organizational aspects and the most important challenge is the security and privacy of the information. There are different solutions or suggestions that a company should follow to overcome various challenges and issues.

Improving the visibility of developmental biology: time for induction and specification.

Developmental biology is a prominent field that has captured the imagination of many scientists. Over the years, research in the area has seen a steady number of amazing accomplishments, with peaks in activity following the development and application of new technologies. Although the field continues to flourish and produce excellent work, I have recently noticed difficulty with its perception and visibility. Having joined the developmental biology community during the early 1990s, and contributing since as a stem cell researcher, cancer biologist and an MD, I have a unique perspective on these challenges. Here, I discuss these issues and challenges and offer potential solutions for a field that is very important to me.