Retrieval Functions Research Articles

EMDS-5: Environmental Microorganism image dataset Fifth Version for multiple image analysis tasks.

Environmental Microorganism Data Set Fifth Version (EMDS-5) is a microscopic image dataset including original Environmental Microorganism (EM) images and two sets of Ground Truth (GT) images. The GT image sets include a single-object GT image set and a multi-object GT image set. EMDS-5 has 21 types of EMs, each of which contains 20 original EM images, 20 single-object GT images and 20 multi-object GT images. EMDS-5 can realize to evaluate image preprocessing, image segmentation, feature extraction, image classification and image retrieval functions. In order to prove the effectiveness of EMDS-5, for each function, we select the most representative algorithms and price indicators for testing and evaluation. The image preprocessing functions contain two parts: image denoising and image edge detection. Image denoising uses nine kinds of filters to denoise 13 kinds of noises, respectively. In the aspect of edge detection, six edge detection operators are used to detect the edges of the images, and two evaluation indicators, peak-signal to noise ratio and mean structural similarity, are used for evaluation. Image segmentation includes single-object image segmentation and multi-object image segmentation. Six methods are used for single-object image segmentation, while k-means and U-net are used for multi-object segmentation. We extract nine features from the images in EMDS-5 and use the Support Vector Machine (SVM) classifier for testing. In terms of image classification, we select the VGG16 feature to test SVM, k-Nearest Neighbors, Random Forests. We test two types of retrieval approaches: texture feature retrieval and deep learning feature retrieval. We select the last layer of features of VGG16 network and ResNet50 network as feature vectors. We use mean average precision as the evaluation index for retrieval. EMDS-5 is available at the URL:https://github.com/NEUZihan/EMDS-5.git.

Validation of NOAA CyGNSS Wind Speed Product with the CCMP Data

The National Aeronautics and Space Administration (NASA) Cyclone Global Navigation Satellite System (CyGNSS) mission was launched in December 2016, which can remotely sense sea surface wind with a relatively high spatio-temporal resolution for tracking tropical cyclones. In recent years, with the gradual development of the geophysical model function (GMF) for CyGNSS wind retrieval, different versions of CyGNSS Level 2 products have been released and their performance has gradually improved. This paper presents a comprehensive evaluation of CyGNSS wind product v1.1 produced by the National Oceanic and Atmospheric Administration (NOAA). The Cross-Calibrated Multi-Platform (CCMP) analysis wind (v02.0 and v02.1 near real time) products produced by Remote Sensing Systems (RSS) were used as the reference. Data pairs between the NOAA CyGNSS and RSS CCMP products were processed and evaluated by the bias and standard deviation SD. The CyGNSS dataset covers the period between May 2017 and December 2020. The statistical comparisons show that the bias and SD of CyGNSS relative to CCMP-nonzero collocations when the flag of CCMP winds is nonzero are –0.05 m/s and 1.19 m/s, respectively. The probability density function (PDF) of the CyGNSS winds coincides with that of CCMP-nonzero. Furthermore, the average monthly bias and SD show that CyGNSS wind is consistent and reliable generally. We found that negative deviation mainly appears at high latitudes in both hemispheres. Positive deviation appears in the China Sea, the Arabian Sea, and the west of Africa and South America. Spatial–temporal analysis demonstrates the geographical anomalies in the bias and SD of the CyGNSS winds, confirming that the wind speed bias shows a temporal dependency. The verification and comparison show that the remotely sensed wind speed measurements from NOAA CyGNSS wind product v1.1 are in good agreement with CCMP winds.

An efficient query optimization technique in big data using $$\sigma$$-ANFIS load balancer and CaM-BW optimizer

Big data (BD) is attaining major attention in the information field due to the eruption of data in the preceding decade. Philosophical techniques of “query optimization (QO)” have an essential function in data retrieval as of a BD environment. Numerous cloud-centered distributed data processing platforms were developed to render effective as well as lucrative solutions for BD query optimization. Nevertheless, most techniques brought about higher “energy consumptions (EC)” along with low accuracy level because of the lack of deliberation of energy issues as well as query characteristics, correspondingly. To tackle the issues of query optimization process, this paper proposes an “efficient query optimization (EQO)” utilizing $$\sigma$$ ANFIS load balancer in addition to the CaM-BW optimizer. The proposed technique comprises '2′ phases: (1) BD arrangement and (2) QO. In the initial phase, the BD is arranged by utilizing preprocessing, feature extraction, together with clustering. The MCoV-FCM algorithm takes care of the clustering. In the second phase, the $$\sigma$$ ANFIS load balancer in addition to the CaM-BW optimizer concentrates on disregarding the energy-efficient query plans and enhancing the general query processing performance. Lastly, numerical simulation outcomes are rendered to display the proposed method’s effectiveness.

Compact Polarimetry Synthetic Aperture Radar Ocean Wind Retrieval: Model Development and Validation

AbstractWe have developed C-band compact polarimetry geophysical model functions for RADARSAT Constellation Mission ocean surface wind speed retrieval. A total of 1594 RADARSAT-2 images acquired in quad-polarization SAR imaging mode were collocated with in situ buoy observations. This dataset is first used to simulate compact polarimetric data and to examine their dependencies on radar incidence angle and wind vectors. We find that right circular transmit, right circular receive (RR-pol) radar backscatters are less sensitive to incidence angles and wind directions but are more dependent on wind speeds, compared to right circular transmit, horizontal receive (RH-pol), right circular transmit, vertical receive (RV-pol), and right circular transmit, left circular receive (RL-pol). Subsequently, the matchup data pairs are used to derive the coefficients of the transfer functions for the proposed compact polarimetric geophysical model (CMOD) functions, and to validate the associated wind speed retrieval accuracy. Statistical comparisons show that the retrieved wind speeds from CMODRH, CMODRV, CMODRL, and CMODRR are in good agreement with buoy measurements, with root-mean-square errors of 1.38, 1.51, 1.47, and 1.25 m s−1, respectively. The results suggest that compact polarimetry is a good alternative to linear polarization for wind speed retrieval. CMODRR is more appropriate to retrieve high wind speeds than CMODRH, CMODRV or CMODRL.

β-Lactolin Enhances Neural Activity, Indicated by Event-Related P300 Amplitude, in Healthy Adults: A Randomized Controlled Trial.

Background:Epidemiological studies have shown that dairy product consumption is beneficial for cognitive function in elderly individuals. β-lactolin is a Gly–Thr–Trp–Tyr lacto-tetrapeptide rich in fermented dairy products that improves memory retrieval, attention, and executive function in older adults with subjective cognitive decline and prevents the pathology of Alzheimer’s disease in rodents. There has been no study on the effects of β-lactolin on neural activity in humans.Objective:We investigated the effects of β-lactolin on neural activity and cognitive function in healthy adults.Methods:In this randomized, double-blind, placebo-controlled study, 30 participants (45–64 years old) consumed β-lactolin or placebo for 6 weeks. Neural activity during auditory and language tasks was measured through 64-channel electroencephalography. Moreover, verbal fluency tests were performed at baseline and after 6 weeks.Results:The β-lactolin group had a significantly higher P300 amplitude at the Cp2 site (a part of the parietal lobe near the center of brain, p = 0.011), and C4 site (the area between the frontal and parietal lobe, p = 0.02) during the auditory tasks after 6 weeks than the placebo group. Thus, β-lactolin supplementation promoted neural activity in the parietal area, which increases concentration and attention during auditory cognitive tasks. Compared with the placebo group, the β-lactolin group also showed significant changes in the scores of verbal fluency test after 6 weeks (p = 0.033).Conclusion:Our findings provide insight into the mechanisms underlying the effects of β-lactolin on attention in healthy adults.

Learning to Rank for Educational Search Engines

In this digital age, there is an abundance of online educational materials in public and proprietary platforms. To allow effective retrieval of educational resources, it is a necessity to build keyword-based search engines over these collections. In modern Web search engines, high-quality rankings are obtained by applying machine learning techniques, known as learning to rank (LTR). In this article, our focus is on constructing machine-learned ranking models to be employed in a search engine in the education domain. Our contributions are threefold. First, we identify and analyze a rich set of features (including click-based and domain-specific ones) to be employed in educational search. LTR models trained on these features outperform various baselines based on ad-hoc retrieval functions and two neural models. As our second contribution, we utilize domain knowledge to build query-dependent ranking models specialized for certain courses or education levels. Our experiments reveal that query-dependent models outperform both the general ranking model and other baselines. Finally, given well-known importance of user clicks in LTR, our third contribution is for handling singleton queries without any click information. To this end, we propose a new strategy to “propagate” click information from the other, similar, queries to the singleton queries. The proposed click propagation approach yields a better ranking performance than the general ranking model and another baseline from the literature. Overall, these findings reveal that both the general and query-dependent ranking models, trained using LTR approaches, yield high effectiveness in educational search, which may ultimately lead to a better learning experience.

Digital Application of Intangible Cultural Heritage from the Perspective of Cultural Ecology

This paper explored the digital application of intangible cultural heritage from the perspective of cultural ecology. Through field investigations, combined with cultural ecology theory, an ontology-based semantic web technology was proposed, and Nanjing "Yunjin" brocade weaving technique was selected as the research object. The specific steps were as follows: First, based on the field surveys and cultural ecology theory, the intangible cultural ecological environment was divided into natural and social environments. Next, constructing the intangible cultural heritage ontology was constructed, including the collection and collation of Nanjing Yunjin weaving technique knowledge corpus, based on user needs analysis and corpus analysis, CIDOC CRM was used to create rules to build the ontology. Finally, based on the MediaWiki platform and Semantic MediaWiki, the semantic web model of the intangible cultural heritage was designed, and its semantic retrieval function was realized, thereby achieving the practical application of intangible cultural heritage digitization. Based on the perspective of cultural ecology, a set of intangible digital application models was proposed, which expanded the digital application of the cultural ecology theory, verified the application of this model in the sustainable development of cultural tourism, and provided reference for the sustainable development of cultural tourism.

Analysis of Adaptive Image Retrieval by Transition Kalman Filter Approach based on Intensity Parameter

The information changes in image pixel of retrieved records is very common in image process. The image content extraction is containing many parameters to reconstruct the image again for access the information. The intensity level, edge parameters are important parameter to reconstruct the image. The filtering techniques used to retrieve the image from query images. In this research article, the adaptive function kalman filter function performs for image retrieval to get better accuracy and high reliable compared to previous existing method includes Content Based Image Retrieval (CBIR). The kalman filter is incorporated with adaptive feature extraction for transition framework in the fine tuning of kalman gain. The feature vector database analysis provides transparent to choose the images in retrieval function from query images dataset for higher retrieval rate. The virtual connection is activated once in single process for improving reliability of the practice. Besides, this research article encompasses the adaptive updating prediction function in the estimation process. Our proposed framework construct with adaptive state transition Kalman filtering technique to improve retrieval rate. Finally, we achieved 96.2% of retrieval rate in the image retrieval process. We compare the performance measure such as accuracy, reliability and computation time of the process with existing methods.

An improved BM25 algorithm for clinical decision support in Precision Medicine based on co-word analysis and Cuckoo Search

BackgroundRetrieving gene and disease information from a vast collection of biomedical abstracts to provide doctors with clinical decision support is one of the important research directions of Precision Medicine.MethodWe propose a novel article retrieval method based on expanded word and co-word analyses, also conducting Cuckoo Search to optimize parameters of the retrieval function. The main goal is to retrieve the abstracts of biomedical articles that refer to treatments. The methods mentioned in this manuscript adopt the BM25 algorithm to calculate the score of abstracts. We, however, propose an improved version of BM25 that computes the scores of expanded words and co-word leading to a composite retrieval function, which is then optimized using the Cuckoo Search. The proposed method aims to find both disease and gene information in the abstract of the same biomedical article. This is to achieve higher relevance and hence score of articles. Besides, we investigate the influence of different parameters on the retrieval algorithm and summarize how they meet various retrieval needs.ResultsThe data used in this manuscript is sourced from medical articles presented in Text Retrieval Conference (TREC): Clinical Decision Support (CDS) Tracks of 2017, 2018, and 2019 in Precision Medicine. A total of 120 topics are tested. Three indicators are employed for the comparison of utilized methods, which are selected among the ones based only on the BM25 algorithm and its improved version to conduct comparable experiments. The results showed that the proposed algorithm achieves better results.ConclusionThe proposed method, an improved version of the BM25 algorithm, utilizes both co-word implementation and Cuckoo Search, which has been verified achieving better results on a large number of experimental sets. Besides, a relatively simple query expansion method is implemented in this manuscript. Future research will focus on ontology and semantic networks to expand the query vocabulary.

Functional heterogeneity in the left lateral posterior parietal cortex during visual and haptic crossmodal dot-surface matching.

BackgroundVision and touch are thought to contribute information to object perception in an independent but complementary manner. The left lateral posterior parietal cortex (LPPC) has long been associated with multisensory information processing, and it plays an important role in visual and haptic crossmodal information retrieval. However, it remains unclear how LPPC subregions are involved in visuo‐haptic crossmodal retrieval processing.MethodsIn the present study, we used an fMRI experiment with a crossmodal delayed match‐to‐sample paradigm to reveal the functional role of LPPC subregions related to unimodal and crossmodal dot‐surface retrieval.ResultsThe visual‐to‐haptic condition enhanced the activity of the left inferior parietal lobule relative to the haptic unimodal condition, whereas the inverse condition enhanced the activity of the left superior parietal lobule. By contrast, activation of the left intraparietal sulcus did not differ significantly between the crossmodal and unimodal conditions. Seed‐based resting connectivity analysis revealed that these three left LPPC subregions engaged distinct networks, confirming their different functions in crossmodal retrieval processing.ConclusionTaken together, the findings suggest that functional heterogeneity of the left LPPC during visuo‐haptic crossmodal dot‐surface retrieval processing reflects that the left LPPC does not simply contribute to retrieval of past information; rather, each subregion has a specific functional role in resolving different task requirements.

Noncomputerised Circadian Interventions for Improving Working Memory Performance among Children

Working Memory provides a mental workspace for tasks requiring both processing and storage. Working memory is a cognitive system whose essential function is to facilitate and beautify the potential of encoding, storage, and retrieval functions that are imperative for gaining knowledge and processing of facts. It has been prompted that various mediations applied within day-to-day contexts of children have the potential to improve working memory and generate transfer to real-world skills, anyway little is known about the effectiveness of these interventions among children. This review focuses to detect deliberately the adequacy of intervention or interventional package on working memory performance of children to identify their effects on Working Memory, advantages extended to near-and far-transfer capability of interventions, and gains sustained overtime and dosage of it. Literature searches were conducted across 10 electronic data bases using consistent keywords. Papers were screened by title and abstract (n=964) and judged against predefined eligibility criteria (n=63). Eighteen papers were included in the appraisal. Different working memory interventional approaches were included such as adapting the surroundings to decrease working memory loads; direct working memory training with and without tactics mandate and coaching competencies which circuitously effect on working memory (athletics, lexical apprehension, astonishing man-made play, and self-possession). Both direct training on working memory undertakings and rehearsing certain abilities that may likewise affect randomly on working memory which delivered refinement on working memory errands. Hardly, any research articulated dosage impact, estimated outlying shift of outcomes (n=4), or tried the solidness of valid statements after added time (n=4). The absence of an unmistakable hypothetical structure brought about uncertain forecasts about instructing and switch impacts. Methodological difficulties likewise compel the intensity of the proof, including: small-scale sample sizes; oversight of blinding of members and result assessors; and shortfall of active control group

Reducing Errors in Velocity–Azimuth Display (VAD) Wind and Deformation Retrievals from Airborne Doppler Radars in Convective Environments

AbstractThe present study describes methods to reduce the uncertainty of velocity–azimuth display (VAD) wind and deformation retrievals from downward-pointing, conically scanning, airborne Doppler radars. These retrievals have important applications in data assimilation and real-time data processing. Several error sources for VAD retrievals are considered here, including violations to the underlying wind field assumptions, Doppler velocity noise, data gaps, temporal variability, and the spatial weighting function of the VAD retrieval. Specific to airborne VAD retrievals, we also consider errors produced due to the radar scans occurring while the instrument platform is in motion. While VAD retrievals are typically performed using data from a single antenna revolution, other strategies for selecting data can be used to reduce retrieval errors. Four such data selection strategies for airborne VAD retrievals are evaluated here with respect to their effects on the errors. These methods are evaluated using the second hurricane nature run numerical simulation, analytic wind fields, and observed Doppler radar radial velocities. The proposed methods are shown to reduce the median absolute error of the VAD wind retrievals, especially in the vicinity of deep convection embedded in stratiform precipitation. The median absolute error due to wind field assumption violations for the along-track and for the across-track wind is reduced from 0.36 to 0.08 m s−1 and from 0.35 to 0.24 m s−1, respectively. Although the study focuses on Doppler radars, the results are equally applicable to conically scanning Doppler lidars as well.

Technological and methodological aspects of using reference and search tools in maintaining the database of Dubna University faculty’s publications

The author discusses the experience of building, maintaining and using the bibliographical database of science publications by the faculty of the state Dubna University. She analyzes in detail MegaPro ALIS retrieval functionality and describes different types of the system’s dictionaries and guides, their advantages and drawbacks in terms of entering data into bibliographic entry. The algorithm of using outer tables for reference when entering repeated subfields in one-click or entering data into several subfields of the bibliographic records. The example is given how hierarchical data of organization structure is used as an outer dictionary.Feasibility of using the directories of faculty authors and journals/other sources of information in publication databases is substantiated; example is given how to use them when entering several subfields of MARC21 fields 100, 700 and 773. The methodological solutions for maintaining directories of faculty authors and journals (and other information sources) are discussed.User and program interface for retrieving publications by author’s affliation, academic degree or title, institution, information source specific data are discussed as a result of building database of publications. The author emphasizes that the dictionaries may be used as supplementary information resources to support faculty publication activities and to integrate them into other university systems.

Construction and Application of Metal Equipment Supervision Management Information System

Thermal power plant contains a large number of metal equipment. The data of construction, overhaul, maintenance and operation of metal equipment can fully reflect the safety status of the equipment. Aiming at a large number of metal supervision data of thermal power plants in Inner Mongolia, according to the requirements of national and industrial standards, a metal supervision and management information system including various data of metal equipment design, manufacturing, installation, use, inspection, transformation and repair, life assessment and other stages is established to realize the whole life cycle management of supervision equipment in thermal power plants. At the same time, make full use of the big data retrieval function of the system, realize the big data comparison of the same type of equipment or the same type of fault, provide sufficient information for the technical supervision and failure analysis personnel, and further improve the technical supervision and technical service quality.

Ontology modeling and case database construction of subway emergency plan knowledge

In order to improve the effectiveness and timeliness of the subway emergency plan knowledge, it is necessary to standardize and semantically express the emergency plan knowledge and promote the emergency response work to play a more efficient and timely role. Firstly, an ontology-based emergency planning knowledge modeling is proposed, and a unified and standardized metrology database for the emergency planning ontology is constructed. Secondly, drawing on the case reasoning method MyCBR, combined with the established subway operation accident case knowledge base, a case retrieval method based on semantic similarity is proposed to achieve efficient retrieval of subway emergency accident cases. Finally, Protégé software and MyCBR are used to realize the emergency reasoning knowledge reasoning and case retrieval function, which significantly improves the application efficiency of emergency response knowledge.

A Comprehensive Review of the Worldwide Existing Tsunami Databases

Tsunami databases contain general information of historical tsunamis, which provides valuable and fundamental data to tsunami-related researches. Nevertheless, before adopting the information stored in various tsunami databases, users should be familiar with these databases’ individual features due to their inhomogeneity in data storage. To this end, a comprehensive review of the worldwide existing tsunami databases was conducted in this study. Two kinds of existing databases are recognized, i.e. the individual database and the organizational database. The individual tsunami databases are generally simple and descriptive with less information about tsunami and associated earthquake. Update of individual database is also out of date. Nevertheless, the organizational tsunami databases, with the retrieval function and timely update, are more sophisticated with significant research orientated information, upon which we can obtain the detailed characteristics of a specified tsunami event. In addition, a further comparison is made between two main organizational databases, i.e. the databases of NTL/WLD and NGDC/WDS. In which, the number of recorded tsunami wave heights per event and the number of definite tsunami events per decade both witness an apparent increase after 1900s, and the landslide-generated tsunamis are found to gradually increase after 1960s. The total tsunami events per decade fluctuate around one hundred since 1990s, whereas the definite tsunami events per decade experience a linear increase in this period. It turns out that though quite a part of the data in NTL/WLD is referred to NGDC/WDS, they do collect different tsunami events, and even for the same event, their recording datasets are still not consistent with each other. Figuring out the structural features of different databases and unveiling their connections and differences facilitate relevant research for disaster prevention and mitigation.

Research on Reading Subject Recommendation of Library Based on Data Analysis

In the era of big data, users’ demands are increasingly diversified and personalized. Digital library introduces user portraits to establish intelligent reading recommendation system, which can comprehensively grasp users’ dynamic demands and form accurate and intelligent resource recommendation service mode. This paper introduces the characteristics and application advantages of user portrait, and analyses the methods of user portrait in Digital Library under the big data environment. On the basis of in-depth analysis of library book retrieval function, this paper makes clear that the library subject reading recommendation system includes the modules of data collection, recommendation engine, front-end display and background management. The design and implementation of the recommendation system are introduced in detail. The research results of this paper have certain practical significance for the exploration of the recommendation system of university library.

Transparent inorganic multicolour displays enabled by zinc-based electrochromic devices

Electrochromic displays have been the subject of extensive research as a promising colour display technology. The current state-of-the-art inorganic multicolour electrochromic displays utilize nanocavity structures that sacrifice transparency and thus limit their diverse applications. Herein, we demonstrate a transparent inorganic multicolour display platform based on Zn-based electrochromic devices. These devices enable independent operation of top and bottom electrochromic electrodes, thus providing additional configuration flexibility of the devices through the utilization of dual electrochromic layers under the same or different colour states. Zn–sodium vanadium oxide (Zn–SVO) electrochromic displays were assembled by sandwiching Zn between two SVO electrodes, and they could be reversibly switched between multiple colours (orange, amber, yellow, brown, chartreuse and green) while preserving a high optical transparency. These Zn–SVO electrochromic displays represent the most colourful transparent inorganic-based electrochromic displays to date. In addition, the Zn–SVO electrochromic displays possess an open-circuit potential (OCP) of 1.56 V, which enables a self-colouration behaviour and compelling energy retrieval functionality. This study presents a new concept integrating high transparency and high energy efficiency for inorganic multicolour displays.

Frontal aslant tracts as correlates of lexical retrieval in MS

ABSTRACT Introduction Previous studies reveal that a newly described white matter pathway, the frontal aslant tract (FAT), connecting inferior and superior frontal gyri has a role in speech and language functions. We explored the role of this tract in a phonemic and semantic fluency tasks in a cohort of multiple sclerosis patients diagnosed with cognitive impairment. Methods Thirty-five MS patients with varying degrees of cognitive impairment underwent diffusion tensor imaging and the Controlled Associated Word Test. Fractional anisotropy (FA) of FAT and arcuate fasciculus (AF) were obtained through a supervised, atlas-based tissue segmentation and parcellation method. Phonemic and semantic fluency scores were obtained from COWAT. We ran a multivariate regression model, and partial correlation analyses adjusted for age, education, and lesion load, and corrected for multiple comparisons. False discovery rate (FDR) was used for the correction of multiple comparisons. Results Bilateral FAT FA showed significant association with phonemic verbal fluency task (Left; r = 0.46, p = 0.0058 and right; r = 0.46, p = 0.0059) but not semantic fluency task and this relation remained significant after FDR correction (p = 0.02 bilaterally). Although left AF showed some significant association with phonemic fluency task, this relation was insignificant after FDR correction. Conclusion We show that bilateral FAT are correlates of phonemic verbal fluency task but not semantic in an MS cohort with cognitive impairment. This finding suggests that FAT is more specialized in lexical retrieval function as semantic fluency test encompasses all the functions except the lexical retrieval.

Development of Arduino UNO Based Automated Storage and Retrieval System

Automated storage and retrieval system (AS/RS) is prototyped to take account of effect of various dwell point strategies and locations of input-output station on expected travel time and throughput of system. The effect of shape function on expected cycle time and throughput of system. Arduino UNO microcontroller is used to control and operate storage and retrieval functions. Arduino UNO software provides complete package of flexible programming platform for control operation of input output devices. Android interfacing to control system provides smarter rand easily accessible human control panel.