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Movie Recommender systems are frequently used in academics and industry to give users with relevant, engaging material based on their rating history. However, most traditional methods suffer from the cold-start problem, which is the initial lack of item ratings and data sparsity. The Hybrid Machine Learning (ML) technique is proposed for a movie recommendation system. Demographic data is collected from the Movie Lens dataset, and attributes are evaluated using the Attribute Analysis module. The Aquila Optimization Algorithm is used to select the best attributes, while Random Forest classifier is used for classification. Data is clustered using Fuzzy Probabilistic Cmeans Clustering Algorithm (FPCCA), and the Correspondence Index Assessment Phase (CIAP) uses Bhattacharyya Coefficient in Collaborative Filtering (BCCF) for similarity index calculation. The Outcomes gives the proposed method obtained low error, such as MAE has 0.44, RMSE has 0.63 compared with the baseline methods. [ABSTRACT FROM AUTHOR]

Objective: Visual aids like length‐frequency histograms are widely used to examine fish population status and trends; however, comparing multiple histograms simultaneously becomes cumbersome and inefficient. Complicating matters further, overlaying covariates on histograms to highlight connections with length frequencies can be challenging. An alternative, and the subject of this Perspective, is to display length distributions as an ordination using similarity indexes; in many cases, this allows for improved visual organization and representation of relationships with covariates. Methods: I review the application of ordination methods for analysis of size structures using alternative visualizations that may facilitate the identification of connections that are concealed when analyzing a series of histograms. After a brief introduction to similarity indexes, types of ordinations, and sample sizes, I examine four case studies to illustrate size structure analysis via similarity indices: (1) unconstrained ordination to identify "bass‐crowded" populations in a set of 34 small fishing lakes, (2) unconstrained ordination to evaluate the effect of three consecutive length limits on a Largemouth Bass Micropterus nigricans population over a span of 28 years, (3) constrained ordination to assess the relationships between fish community size structure and in‐lake and off‐lake environmental descriptors in 30 oxbow lakes, and (4) constrained ordination to identify what aspects of Largemouth Bass size structure were related to six types of reservoir habitats. Result: Size structure analysis via similarity indexes enabled the exploration of extensive length‐frequency data. It is important to acknowledge that ordinations serve solely as a visual aid for assessing size structure—no statistical testing is involved. Conclusion: Ordination techniques and software are advancing at a quick pace, holding great promise for the future of size structure analysis via similarity indices. Impact statementLength ordinations provide a visual representation of complex size structure data, making it easier to understand patterns, relationships, and trends in size structure. The visual representation can facilitate the interpretation and communication of survey results to both experts and nonexperts. [ABSTRACT FROM AUTHOR]

In the current information technology era, plagiarism is a significant and critical issue in research. Plagiarism detection tools are essential in identifying instances of plagiarism. This study compared the similarity index generated by three leading plagiarism detection software platforms: iThenticate, Ouriginal, and Turnitin. Ten original documents (N = 10) were selected for analysis across the three software programs. The process involved first analyzing all documents with Ouriginal, then checking the same documents, followed by iThenticate, and Turnitin. These software programs generated originality reports detailing the number of matching sources, similar word counts, and an overall similarity index as a percentage. To detect notable differences within the dataset, a one-way ANOVA and a Tukey (HSD) post-hoc analysis were conducted. The threshold for statistical significance was established at p<0.05. Statistical analysis revealed that while there was a significant variance in the similarity index across the tools iThenticate, Ouriginal, and Turnitin (F (2, 27) = 5.436, p = .010), there were no notable differences in the sources they matched (F (2, 27) = 1.289, p = .292). This suggests that the plagiarism detection capabilities may vary significantly among these tools, but the sources they identify as matches are largely consistent. However, the average values indicated that Turnitin had the highest mean similarity detection followed by iThenticate, and then Ouriginal. In this study, evaluating the similarity index can help verify the effectiveness of anti-plagiarism tools and safeguard researchers against committing plagiarism. [ABSTRACT FROM AUTHOR]

Long-term occupation of coal gangue dumping sites (CGDS) may destroy ecological environment of nearby area. However, how the CGDS affects the distribution pattern of soil seed banks and vegetation in the nearby area is not clear. In this study, we investigated soil seed bank and vegetation at different distances from the second CGDS of Yangchangwan in Ningdong mining area, Lingwu, Ningxia. The results showed that soil seed bank was mainly distributed in 0-10 cm layer and decreased with increasing soil depth. Species richness of soil seed bank and vegetation first increased and then tended to be stable with increasing distance to the CGDS. The influence range of CGDS on soil seed banks was 300-500 m and was 100-300 m on aboveground vegetation. The CGDS did not affect the vertical distribution pattern of soil seed bank, but significantly affected the horizontal distribution pattern of soil seed banks and aboveground vegetation. The key area of vegetation restoration around the CGDS was between 100 m and 300 m. [ABSTRACT FROM AUTHOR]

A significant number of papers in the field of scientometrics addressed the comparisons of various similarity indexes. However, there is still a debate on the appropriateness of an index compared to others, beacause of the assessment differences reported in the literature. The objective of this paper is to make a comparative analysis of the five most used similarity indexes for the three scientometric analysis types: co-word, co-citation and co-authorship. A total of 388 papers addressing similarity indexes in scientometric analysis over three decades were retrieved from the Web of Science and examined; of which 49 were retained as the most relevant according to selective criteria. The approach consisted of building cross matrices for the five indexes (Jaccard, Dice-Sorensson, Salton, Pearson, and Association Strength) for the three types of scientometric analysis. For each of these analyses, a distinction is made between papers according to their theoretical or empirical results. Furthermore, papers are classified according to the mathematical formula of the similarity index being used (vector vs non vector). In the 49 relevant papers being selected, the comparative analysis showed that there is still no consensus on the appropriateness of an index for co-word and co-authorship analyses, while for co-citation, Salton is the widely preferred one. The Association Strength is the less covered and compared to other indexes for the three analysis types. An open source computer program was developed as a tool to facilitate empirical comparative studies of indexes. It allows generating normalized matrix of any chosen index for the two mathematical variants. [ABSTRACT FROM AUTHOR]

Bats are a highly diverse order with substantial economic and ecological value. Similarly, forests in South Africa form a valuable biome supporting unique biotic diversity, yet forest bat communities have not previously been surveyed. We sampled 17 forests, of seven forest types and three forest groups, in the Eastern Cape and southern KwaZulu-Natal provinces, located within the Maputaland-Pondoland-Albany global biodiversity hotspot. We utilized capture and acoustic survey methods to compile the first bat species inventory for these forests. Species identification was performed with a combined approach of morphology, echolocation, and DNA barcodes. With this we contributed novel DNA barcodes to the Barcode of Life Data System. A total of 25 species was recorded, with range extensions southward into the Eastern Cape for six species, indicating the region to be more diverse than previously thought. Updated modelled distribution maps for these species are presented. We compiled the first reference call library of hand released bats for South African forest habitats, and the southeast region of the country. We compared species richness, diversity, and dissimilarity of the forest types and found that Scarp forests host the highest species richness and diversity. Patterns of species assemblage similarities between forest groups are attributed to forest biogeographical history and historical dispersal routes of forest fauna. A comprehensive survey, such as this, may assist in the compilation and implementation of forest conservation management plans and future monitoring programs. [ABSTRACT FROM AUTHOR]

Copyright of Formación Universitaria is the property of Centro de Informacion Tecnologica (CIT) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Plagiarism has grown to such an alarming rate that the academic community finds it difficult to spot an authentic work among the plethora of published literature. Antiplagiarism softwares have become popular as a solution to overcome this problem. This study aims to describe various aspects of plagiarism, to assess the contribution of PhD theses in ShodhGanga by the universities in Kerala, to identify the subject wise contribution of PhD theses in various universities in Kerala during 2010-17,to find the extend of similarity of content in the PhD theses of the Universities in Kerala and to rank the universities in Kerala with respect to the similarity index. The study is based on 70 PhD theses of three Universities in Kerala viz. University of Kerala, M.G University and University of Calicut selected at random by simple random sample method from the theses available in ShodhGanga. The theses selected were tested by using Urkund, anti-plagiarism software maintained by INFLIBNET. It was found that Science subjects show least similarity index whereas Social Science subjects have the highest similarity rate. Faculty of Arts (26.6%) has a high degree of similarity followed by Humanities (26%) and lowest in Science (16%).Among the Universities University of Calicut occupied the top position with 21 % similarity index in its PhD theses followed by M.G University having 20.4% and the University of Kerala has least with 17.9% of similarity index. The paper points out the importance of user awareness programmes and training programmes on anti-plagiarism for the research guides, research scholars and library staff members. [ABSTRACT FROM AUTHOR]

Background. The knowledge of the age, growth, and feeding ecology of fish species is essential for conservation, monitoring, and management activities required for the sustainable use of fish stocks. The objective of this work was to describe the growth and feeding of Pagellus acarne from the Gulf of İzmir, central Aegean Sea. The information provided in this study contributes to the knowledge which is for sustainable management applications. Material and methods. The study was carried out to investigate the growth and feeding characteristics of axillary seabream, Pagellus acarne (Risso, 1827), in the Gulf of İzmir, the central Aegean Sea, from commercial trawl fishery between October 2012 and September 2013. Age and growth were determined by annuli counts of sagittal otoliths. Length-weight relation and the von Bertalanffy equation were used to evaluate the fish growth. Percentages by number, weight, and frequency of each food category were determined, and the index of relative importance (%IRI) was calculated to define the main food categories. A similarity of diet was also examined according to a season and fish size. Results. A total of 2036 specimens' were analysed. The lengths ranged from 7.5 to 22.0 cm and the weights ranged from 4.55 to 138.45 g. For the age determination, a total of 547 left sagittal otoliths were extracted. The age ranged from 0 to 4 years. Von Bertalanffy growth parameters were determined from mean lengths of age groups and the following parameters were obtained: L∞= 27.75 cm, 22.45 cm, and 25.61 cm; k = 0.201 year-1, 0.341 year-1, and 0.249 year-1; t0 = -2.347 years, -1.554 years, and -1.938 years; φ' = 2.190, 2.235, and 2.213 for females, males, and both sexes combined, respectively. Stomach content analyses revealed that Pagellus acarne was defined as a carnivorous, euryphagous, and zooplanktivorous species, and Copepoda (Harpacticoida), Polychaeta, and Decapoda were the most important prey groups. Conclusion. This study provides the age, growth, and the first detailed information on the feeding composition of axillary seabream from the central Aegean Sea. Results reported in this work will contribute to management strategies and regulations needed for sustainable conservation for the remaining stocks of the species. [ABSTRACT FROM AUTHOR]

[Display omitted] • A cheap and fast method for the designing of polymer donors is introduced. • Machine learning models are trained for the prediction of energy levels. • Finger print based chemical similarity is performed. • Unique building units are reported. In present work, machine learning models are trained for the prediction of energy levels. Two large databases are explored in the search of efficient building blocks. Three polymers are selected as standard. New building blocks are selected on the basis of similarity index. New polymers are designed by keep the synthetic aspects in mind. Their energy levels are predicted using machine learning. Few best polymers are selected for density functional theory-based analysis. Detailed electronic and graphic properties are calculated. This study is an attempt to highlight how data-driven strategies can help to find unique building blocks and designing new-polymers. [ABSTRACT FROM AUTHOR]

A tumor is uncontrolled growth of the abnormal tissue in the body. If this phenomenon is in brain is brain tumor. A tumor may lead to cancer. Image processing techniques are applied to magnetic resonance (MR) images to detect tumor and edema. The main objective of this paper is to present the automatic segmentation method which separates non-enhancing brain tumors from healthy tissues in MR images by locating tumor position in the brain and to give complete statistical analysis of the tumor. By applying the algorithm presented in this paper we can determine the area of the tumor in the brain along with the area length in the vertical and horizontal planes, sensitivity of the tumor, specificity, similarity index can also be find. The knowledge of this information regarding tumor in the brain is important for diagnosis, planning, and treatment. The proposed algorithm can also be applied to the ground truth images. With the proposed algorithm the tumor detection and localization system was found to be able to accurately detect and localize brain tumor and processing time is less. This will help the physicians in analysing the brain tumors accurately and efficiently. [ABSTRACT FROM AUTHOR]

Social networking sites have gained much popular- ity in the recent years. With millions of people connected virtually generate loads of data to be analyzed to infer mean- ingful associations among links. Link prediction algorithm is one such problem, wherein existing nodes, links and their attributes are analyzed to predict the possibility of potential links, which are likely to happen over a period of time. In this survey, the local structure based link prediction algorithms ex- isting in literature with their features and also the possibility of future research directions is reported and discussed. This survey serves as a starting point for beginners interested in understanding link prediction or similarity index algorithms in general and local structure based link prediction algorithms in particular. [ABSTRACT FROM AUTHOR]

Facial expression is an essential and impressive means of human contact. This is important connection of information for knowing emotional case and motive. A facial expression pursues not only emotions, but other creative action, social cooperation and psychological characteristics. Appearance based facial expression recognition systems are analyzed and have pulled widen application. A new study of bit intensity with coefficient feature vector for facial expression recognition proposed in this paper. All the binary patterns from gray color intensity values are grouped into possible number of attributes according to their similarity. Each attributes count the frequency number of similarity from binary patterns. Each image divided into equal sized blocks and extracts 4-bit binary patterns in two distinct directions for a pixel by measuring the gray color intensity values with its neighbouring pixels. For evaluation the proposed descriptors, JAFFE dataset and Support Vector Machine were applied. Proposed method has achieved excellent achievement in terms of efficiency, robustness and lessens execution time. [ABSTRACT FROM AUTHOR]

This work is a study of binary data, especially binary images sources of information widely used. In general, comparing two binary images that represent the same content is not always easy because an image can undergo transformations like: Translation, rotation, affinity, resolution change and scale or change in appearance. In this paper, we will try to solve the translation and rotation problems. For translation case, the similarity indices are used between the image rows or blocks. In the case of rotation, first the coordinate's contours are extracted, then we compute the covariance matrix used in the Principal Components Analysis (PCA) and the corresponding eigen values which are invariant to this type of movement. We also, compare our approach having complexity 0(M+N) to Hausdorff Distance (HD) that has complexity of O(M×N) for an M ×N image. In our approach, HD is used only to compare distance between ID signatures. [ABSTRACT FROM AUTHOR]

Copyright of Review of Hydrobiology is the property of NK Yayincilik Egitim Hizmetleri and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Antropo is the property of Antropo and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract: One of the main applications of citation is to find articles that are relevant to a particular article. However, not all citations are equally relevant to the target article. This paper presents an approach to identify the most relevant citation(s). To this end, the Normalized Similarity Index (NSI) is proposed to quantify the similarity between the source and target of a citation base on the co-citations and references shared by them. To validate the method, NSI was calculated for five citation networks and was compared with the peer review grades for the relevancy between the source and the target articles. The results showed a significant correlation between the NSI ranks and those of peer review. Also, combined linkage (CL) and weighted direct citation (WDC) were calculated from the same data. According to the results of comparison between the NSI with other similarity measures, in most cases, NSI did better than others at reproducing the peer rankings. Our principal conclusion is that the NSI can be used to prioritize the citations of given highly cited article, and represent knowledge flow from the target article. [Copyright &y& Elsevier]

Real time estimation of target quality variables using soft sensor relevant to time varying process conditions will be a significant step forward in effective implementation of Industry 4.0. Generalized Regression neural network (GRNN) has been used as a steady state quality monitoring soft sensor with reasonable estimation accuracy. However, the accurate prediction capability of GRNN has rarely been explored in a time varying environment. This article reports design of adaptive soft sensor using GRNN as a local model in Just-in-Time learning (JITL-GRNN) framework. The JITL-GRNN adaptive soft sensing technique is further investigated in various dimensions such as, the effect of different similarity index criteria and relevant dataset size on model prediction accuracy and model computation time. Performance of the proposed JITL-GRNN soft sensor is investigated by assessing its prediction accuracy on two benchmark industrial datasets. In addition, dynamic Non-linear autoregressive with exogenous inputs (NARX) neural network model is also developed and the performance of NARX model was compared with the proposed JITL-GRNN model. Results show that the JITL-GRNN adaptive soft sensor has at par or better prediction capability than the NARX model and many other models reported in literature. • Use of GRNN as an adaptive soft sensor. • Integration of GRNN in Just-in-Time learning method (JITL-GRNN). • Investigation of effect of Similarity index method used in the JITL framework. • Investigation of relevant dataset size on model accuracy and model computation time. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents an approach to similarity based approximate reasoning that elucidates the connection between similarity and existing approaches to inference in approximate reasoning methodology. A set of axioms is proposed to get a reasonable measure of similarity between two fuzzy sets. The similarity between the fact(s) and the antecedent of a rule is used to modify the relation between the antecedent and the consequent of the rule. An inference is drawn using the well-known projection operation on the domain of the consequent. Zadeh''s compositional rule of inference and existing similarity based reasoning techniques are considered for a new similarity based approximate reasoning technique. The proposed mechanism is used to develop a modified fuzzy control system. A new defuzzification scheme is proposed. Simulation results are presented for the well-known inverted pendulum problem. [Copyright &y& Elsevier]

Abstract: Studies have been conducted between March 1993 and March 1994 in the Ashar canal, a backwater of the Shatt al-Arab River, Iraq. Using artificial substrates, the colonization and development of seventy-five diatom species belonging to twenty genera could be revealed. Taxa apportionment varied seasonally as well as within each season. A few species have been found during all experiments. These are Amphora ovalis, Bacillaria paradoxa, Cocconeis placentula var. euglypta, Cyclotella meneghiniana, Cymbella ventricosa, Navicula tripunctata var. schizonemoides, Rhoicosphenia curvata, and Synedra ulna. The occurrence of B. paradoxa in Experiment 1 (March–April 1993) and Experiment 4 (end of January to beginning of March 1994) was higher than 50%. Similarity of species increased towards the end of each season, and the communities from experiments 1 and 4 were more similar than others. The experiments also suggest that week 4 represents the equilibrium phase while week 6 reflects the increase in biological interactions. The results could also indicate the sequence of primary colonizers and the community development towards the equilibrium. [Copyright &y& Elsevier]