A Novel Adaptive Feature Fusion Strategy for Image Retrieval

In the era of big data, it is challenging to efficiently retrieve the required images from the vast amount of data. Therefore, a content-based image retrieval system is an important research direction to address this problem. Furthermore, a multi-feature-based image retrieval system can compensate for the shortage of a single feature to a certain extent, which is essential for improving retrieval system performance. Feature selection and feature fusion strategies are critical in the study of multi-feature fusion image retrieval. This paper proposes a multi-feature fusion image retrieval strategy with adaptive features based on information entropy theory. Firstly, we extract the image features, construct the distance function to calculate the similarity using the information entropy proposed in this paper, and obtain the initial retrieval results. Then, we obtain the precision of single feature retrieval based on the correlation feedback as the retrieval trust and use the retrieval trust to select the effective features automatically. After that, we initialize the weights of selected features using the average weights, construct the probability transfer matrix, and use the PageRank algorithm to update the initialized feature weights to obtain the final weights. Finally, we calculate the comprehensive similarity based on the final weights and output the detection results. This has two advantages: (1) the proposed strategy uses multiple features for image retrieval, which has better performance and more substantial generalization than the retrieval strategy based on a single feature; (2) compared with the fixed-feature retrieval strategy, our method selects the best features for fusion in each query, which takes full advantages of each feature. The experimental results show that our proposed method outperforms other methods. In the datasets of Corel1k, UC Merced Land-Use, and RSSCN7, the top10 retrieval precision is 99.55%, 88.02%, and 88.28%, respectively. In the Holidays dataset, the mean average precision (mAP) was 92.46%.

Diagnostic value of RNA for hepatocellular carcinoma: a network meta-analysis

Aim: The aim of this study was to evaluate the capacity of RNA in the diagnosis of hepatocellular carcinoma (HCC). Methods: A systematic review was conducted from PubMed, Cochrane Library, EMBASE and Web of Science databases via well-designed retrieval strategy. Subsequently, the network meta-analysis was performed by the STATA software. Results: Through statistical analysis, the three hypotheses of the network meta-analysis were established. In view of these hypotheses, the diagnostic efficacy of the three markers in HCC (HCC vs healthy people) may be consistent, and the cumulative ranking results showed such a trend: circular RNA >long noncoding RNA >microRNA. Conclusion: Circular RNA may be most effective for diagnosing HCC across the three types of RNA.

Why Do Some Older Adults Avoid Memory Retrieval When Acquiring a New Skill?

Older adults are slower to acquire new cognitive skills requiring a shift from controlled (algorithmic) processing to automatic responding based on retrieving newly unitized information from memory. Research demonstrates that older adults’ delayed retrieval shift is a strategic avoidance of relying on memory when doing so would be successful, not just a function of age-related slowing in rates of associative learning. Older adults’ retrieval avoidance can be reduced by financial incentives to respond rapidly, recognition probes that demonstrate the accessibility of correct information, and other experimental manipulations. Item-level strategy reports show an exponential rise in retrieval strategy use with practice but not for all participants. A proportion of the older samples are retrieval strategy avoidant across the entire course of skill acquisition task practice. The chapter comments on the motivational nature of retrieval strategy avoidance and the possible practical consequences of a retrieval avoidance mode for older adults.

Who does SEO in Spain? A cybermetric methodology for the construction of company universes

Due to their widespread use, search engines, and specifically Google, are extremely important to attract qualified traffic and thereby achieve the commercial objectives of corporations. Search engine optimization (SEO) allows enhanced connection of corporate websites with their audiences through search engines, using certain keywords. This study describes a methodology to determine the most important Spanish companies offering SEO services to third parties, representing an exploratory study of applied cybermetrics for the construction of a universe of companies. One of the relevant results of this work is the design of an information retrieval strategy based on a statistical analysis of search terms and the performance of geolocated searches in all the provincial capitals and Spanish cities with more than 100,000 inhabitants. After cleaning and reviewing the unique URLs, it is concluded that there are 1,043 companies offering SEO services in Spain positioned in Google. These are basically companies with more than one person, operating from a single location, and that offer other services in their portfolio together with SEO. In addition to providing a starting point for future research on the SEO sector in Spain, this research proposes a methodology for the creation of study universes of brands or companies.

A Hybrid Retrieval Strategy for Case-based Reasoning Using Soft Likelihood Functions

Case-based reasoning (CBR) is the retrieval of one or more similar cases from an existing case base for the problem to be solved according to the characteristics of the new problem. The core idea of CBR is that similar cases have similar solutions, so whether the CBR system can play a powerful advantage depends on the quality of case retrieval strategy. At present, the commonly used case retrieval algorithm is based on the mean operator method, which is very hard, and a certain local similarity is low will affect the overall result. In order to calculate the global similarity of cases from a new and softer point of view, this paper introduces the soft likelihood functions into case retrieval, combines the soft likelihood functions with KNN, and proposes a hybrid retrieval strategy. The core of the retrieval strategy is to define the global similarity through SLFs, aggregate the local similarity and characteristic similarity together, and also take the attitude characteristics of decision makers into consideration. Through simulation experiments on real data sets, the accuracy rate is more than 81%, which verifies the effectiveness of the retrieval strategy.

The influence of the number of part-set cues on order retention

Across seven experiments, the present article examined the influence of the number of part-set cues on order retention, as assessed by both reconstruction of order and serial recall tests. Historically, part-set cueing facilitation occurs when half of the items are provided as valid part-set cues on tests of order memory. Using a variety of list lengths (10 or 16), numbers of cues (0–14), and types of cues (full or partial), the present experiments showed disparate effects of the number of part-set cues on reconstruction and serial recall tasks. On reconstruction tests, a minimum number of full cues was required before part-set cueing facilitation was produced and the magnitude of facilitation increased as the number of cues increased. Generally, partial cues did not influence order retention until almost the entire list was provided as partial cues. On serial recall tests, part-set cueing facilitation was only evident with a few full cues. In contrast, part-set cueing impairment was the norm when many partial cues were provided. These results were largely consistent with predictions of the retrieval strategy disruption hypothesis, as well as with an anchoring account of part-set cueing for order.

Ground-based Fourier transform infrared (FTIR) O₃ retrievals from the 3040 cm⁻¹ spectral range at Xianghe, China

In this study, we present O3 retrievals from ground-based Fourier transform infrared (FTIR) solar absorption measurements between June 2018 and December 2019 at Xianghe, China (39.75∘ N, 116.96∘ E). The FTIR spectrometer at Xianghe is operated with indium gallium arsenide (InGaAs) and indium antimonide (InSb) detectors, recording the spectra between 1800 and 11 000 cm−1. As the harmonized FTIR O3 retrieval strategy (Vigouroux et al., 2015) within the Network for the Detection of Atmospheric Composition Change (NDACC) uses the 1000 cm−1 spectral range, we apply the O3 retrieval in the 3040 cm−1 spectral range at Xianghe. The retrieved O3 profile is mainly sensitive to the vertical range between 10 and 40 km, and the degrees of freedom for signal is 2.4±0.3 (1σ), indicating that there are two individual pieces of information in partial columns between the surface and 20 km and between 20 and 40 km. According to the optimal estimation method, the systematic and random uncertainties of the FTIR O3 total columns are about 13.6 % and 1.4 %, respectively. The random uncertainty is consistent with the observed daily standard deviation of the FTIR retrievals. To validate the FTIR O3 total and partial columns, we apply the same O3 retrieval strategy at Maïdo, Réunion (a.k.a. Reunion Island; 21.08∘ N, 55.38∘ E). The FTIR O3 (3040 cm−1) measurements at Xianghe and Maïdo are then compared with the nearby ozonesondes at Beijing (39.81∘ N, 116.47∘ E) and at Gillot (20.89∘ S, 55.53∘ E), respectively, as well as with co-located TROPOspheric Monitoring Instrument (TROPOMI) satellite measurements at both sites. In addition at Maïdo, we compare the FTIR O3 (3040 cm−1) retrievals with the standard NDACC FTIR O3 measurements using the 1000 cm−1 spectral range. It was found that the total columns retrieved from the FTIR O3 3040 cm−1 measurements are underestimated by 5.5 %–9.0 %, which is mainly due to the systematic uncertainty in the partial column between 20 and 40 km (about −10.4 %). The systematic uncertainty in the partial column between surface and 20 km is relatively small (within 2.4 %). By comparison with other measurements, it was found that the FTIR O3 (3040 cm−1) retrievals capture the seasonal and synoptic variations of the O3 total and two partial columns very well. Therefore, the ongoing FTIR measurements at Xianghe can provide useful information on the O3 variations and (in the future) long-term trends.