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Journal articles on the topic 'Co-occurrence database'
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Yamanishi, Ryosuke, Naoki Shino, Yoko Nishihara, Junichi Fukumoto, and Aya Kaizaki. "Alternative-ingredient Recommendation Based on Co-occurrence Relation on Recipe Database." Procedia Computer Science 60 (2015): 986–93. http://dx.doi.org/10.1016/j.procs.2015.08.138.
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Lameijer, Eric-Wubbo, Joost N. Kok, Thomas Bäck, and Ad P. IJzerman. "Mining a Chemical Database for Fragment Co-occurrence: Discovery of “Chemical Clichés”." Journal of Chemical Information and Modeling 46, no. 2 (2006): 553–62. http://dx.doi.org/10.1021/ci050370c.
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Islam, Md Saiful, Md Emdadul Haque, and Md Ekramul Hamid. "Multidimensional Markov Stationary Feature for Image Retrival Systems." Rajshahi University Journal of Science and Engineering 44 (November 19, 2016): 113–22. http://dx.doi.org/10.3329/rujse.v44i0.30396.
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Markov Stationary Features (MSF) not only considers the distribution of colors like histogram method does, also characterizes the spatial co-occurrence of histogram patterns. However, handling large scale database of images, simple MSF method is not sufficient to discriminate the images. In this paper, we have proposed a robust content based image retrieval algorithm that enhances the discriminating capability of the original MSF. The proposed Multidimensional MSF (MMSF) algorithm extends the MSF by generating multiple co-occurrence matrices with different quantization levels of an image. Publicly available WANG1000 and Corel10800 databases are used to evaluate the performance of the proposed algorithm. The experimental result justifies the effectiveness of the proposed method.
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Gollub, Erica L., Ruth Trino, Melinda Salmon, Len Moore, James L. Dean, and Bruce L. Davidson. "Co-occurrence of AIDS and Tuberculosis: Results of a Database"Match" and Investigation." Journal of Acquired Immune Deficiency Syndromes and Human Retrovirology 16, no. 1 (1997): 44–49. http://dx.doi.org/10.1097/00042560-199709010-00007.
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Nguyen, Hoang Duc, Thuong Tien Le, Tuan Hong Do, and Cao Thu Bui. "A NEW DESCRIPTOR FOR IMAGE RETRIEVAL USING CONTOURLET COOCCURRENCE." Science and Technology Development Journal 15, no. 2 (2012): 5–16. http://dx.doi.org/10.32508/stdj.v15i2.1785.
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In this paper, a new descriptor for the feature extraction of images in the image database is presented. The new descriptor called Contourlet Co-Occurrence is based on a combination of contourlet transform and Grey Level Co-occurrence Matrix (GLCM). In order to evaluate the proposed descriptor, we perform the comparative analysis of existing methods such as Contourlet [2], GLCM [14] descriptors with Contourlet Co-Occurrence descriptor for image retrieval. Experimental results demonstrate that the proposed method shows a slight improvement in the retrieval effectiveness.
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Nor Paizin, Muhsin, Siti Maziah Ab Rahman, Khalid Abdul Wahid, Mohd Noor Azam Nafi, Suryani Awang, and Mariam Setapa. "Bibliometric Analysis of Zakat Research in Scopus Database." International Journal of Zakat 6, no. 1 (2021): 13–24. http://dx.doi.org/10.37706/ijaz.v6i1.253.
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Scopus research paper on the zakat was systematically analyzed using the VOSviewer bibliometric measurement. A total of 492 citation data was exported from Scopus on the query of Zakat, and from the initial result, twelve journals were selected in the expanded query process. The journals are Journal of Islamic Accounting and Business Research, International Journal of Islamic and Middle Eastern Finance and Management, International Journal of Innovation Creativity and Change, Advanced Science Letters, and Iop Conference Series Earth and Environmental Science were selected in the query expansion and exported for data visualization in VOSviewer. Results from the journal query returned 492 documents specializing in research of zakat payment. Co-word or co-occurrence analysis was used to identify key themes, and potential future research direction was highlighted.
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NIKAM, SHANKAR BHAUSAHEB, and SUNEETA AGARWAL. "CO-OCCURRENCE PROBABILITIES AND WAVELET-BASED SPOOF FINGERPRINT DETECTION." International Journal of Image and Graphics 09, no. 02 (2009): 171–99. http://dx.doi.org/10.1142/s0219467809003393.
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Perspiration phenomenon is very significant to detect the liveness of a finger. However, it requires two consecutive fingerprints to notice perspiration, and therefore may not be suitable for real time authentications. Some other methods in the literature need extra hardware to detect liveness. To alleviate these problems, in this paper, to detect liveness a new texture-based method using only the first fingerprint is proposed. It is based on the observation that real and spoof fingerprints exhibit different texture characteristics. Textural measures based on gray level co-occurrence matrix (GLCM) are used to characterize fingerprint texture. This is based on structural, orientation, roughness, smoothness and regularity differences of diverse regions in a fingerprint image. Wavelet energy signature is also used to obtain texture details. Dimensionalities of feature sets are reduced by Sequential Forward Floating Selection (SFFS) method. GLCM texture features and wavelet energy signature are independently tested on three classifiers: neural network, support vector machine and K-nearest neighbor. Finally, two best classifiers are fused using the "Sum Rule''. Fingerprint database consisting of 185 real, 90 Fun-Doh and 150 Gummy fingerprints is created. Multiple combinations of materials are used to create casts and moulds of spoof fingerprints. Experimental results indicate that, the new liveness detection method is very promising, as it needs only one fingerprint and no extra hardware to detect vitality.
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Jayadevan, R., and V. S. Sheeba. "A Semantic Image Retrieval Technique Through Concept Co-occurrence Based Database Organization and DeepLab Segmentation." Journal of Computer Science 16, no. 1 (2020): 56–71. http://dx.doi.org/10.3844/jcssp.2020.56.71.
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Milman, Boris L. "Literature-Based Generation of Hypotheses on Chemical Composition Using Database Co-occurrence of Chemical Compounds." Journal of Chemical Information and Modeling 45, no. 5 (2005): 1153–58. http://dx.doi.org/10.1021/ci049716u.
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Ganapathy, Nagarajan, Diana Baumgärtel, and Thomas Deserno. "Automatic Detection of Atrial Fibrillation in ECG Using Co-Occurrence Patterns of Dynamic Symbol Assignment and Machine Learning." Sensors 21, no. 10 (2021): 3542. http://dx.doi.org/10.3390/s21103542.
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Early detection of atrial fibrillation from electrocardiography (ECG) plays a vital role in the timely prevention and diagnosis of cardiovascular diseases. Various algorithms have been proposed; however, they are lacking in considering varied-length signals, morphological transitions, and abnormalities over long-term recordings. We propose dynamic symbolic assignment (DSA) to differentiate a normal sinus rhythm (SR) from paroxysmal atrial fibrillation (PAF). We use ECG signals and their interbeat (RR) intervals from two public databases namely, AF Prediction Challenge Database (AFPDB) and AF Termination Challenge Database (AFTDB). We transform RR intervals into a symbolic representation and compute co-occurrence matrices. The DSA feature is extracted using varied symbol-length V, word-size W, and applied to five machine learning algorithms for classification. We test five hypotheses: (i) DSA captures the dynamics of the series, (ii) DSA is a reliable technique for various databases, (iii) optimal parameters improve DSA’s performance, (iv) DSA is consistent for variable signal lengths, and (v) DSA supports cross-data analysis. Our method captures the transition patterns of the RR intervals. The DSA feature exhibit a statistically significant difference in SR and PAF conditions (p < 0.005). The DSA feature with W=3 and V=3 yield maximum performance. In terms of F-measure (F), rotation forest and ensemble learning classifier are the most accurate for AFPDB (F = 94.6%) and AFTDB (F = 99.8%). Our method is effective for short-length signals and supports cross-data analysis. The DSA is capable of capturing the dynamics of varied-lengths ECG signals. Particularly, the optimal parameters-based DSA feature and ensemble learning could help to detect PAF in long-term ECG signals. Our method maps time series into a symbolic representation and identifies abnormalities in noisy, varied-length, and pathological ECG signals.
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Purwandari, Endina Putri, Desi Andreswari, and Ulva Faraditha. "Ekstraksi Fitur Warna dan Tekstur Untuk Temu Kembali Citra Batik Besurek." Pseudocode 7, no. 1 (2020): 17–25. http://dx.doi.org/10.33369/pseudocode.7.1.17-25.
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Abstrak: Batik Besurek merupakan warisan budaya Bengkulu yang mempunyai ciri khas berupa motif huruf Arab gundul yang dipadukan dengan motif bunga Raflesia Arnoldi. Penelitian ini bertujuan mendesain aplikasi temu kembali citra Batik Besurek menggunakan ekstraksi fitur Color Histogram, Gray Level Co-occurrence Matrix, dan Moment Invariant. Citra yang menjadi dataset yaitu citra Batik Besurek yang terdiri dari 5 motif seperti Kaligrafi, Bunga Raflesia, Burung Kuau, Relung Paku, dan Motif Rembulan. Banyaknya macam citra Batik Besurek yang digunakan sebagai database sesuai dengan banyaknya motif Batik Besurek yang ada di Bengkulu dengan jumlah citra yang ada di database adalah 100 citra training, 30 citra uji database, 30 citra uji luar database, 5 citra uji dari internet. Hasil pencarian citra adalah citra yang memiliki kemiripan mendekati citra uji. Semakin kecil selisih kemiripan maka citra training semakin mirip dengan citra uji. Berdasarkan hasil eksperimen menunjukkan tingkat akurasi aplikasi ini mencapai 75% untuk citra tanpa serangan, 77% untuk citra rotasi 90 derajat, 67% untuk citra Blur Gaussian 1, 68% untuk citra dengan noise, dan 67% untuk citra dengan perubahan warna.Kata Kunci: batik besurek, temu kembali citra, tekstur, warna, Gray Level Co-occurrence Matrix
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RAJA SEKAR, J., S. ARIVAZHAGAN, S. SHOBANA PRIYADHARSHINI, and S. SHUNMUGAPRIYA. "IRIS RECOGNITION USING COMBINED STATISTICAL AND CO-OCCURRENCE MULTI-RESOLUTIONAL FEATURES." International Journal of Pattern Recognition and Artificial Intelligence 27, no. 01 (2013): 1356001. http://dx.doi.org/10.1142/s0218001413560016.
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Iris recognition is one of the most reliable personal identification methods. This paper presents a novel algorithm for iris recognition encompassing iris segmentation, fusion of statistical and co-occurrence features extracted from the curvelet and ridgelet transformed images. In this work, the pupil and iris boundaries are detected by using the equation of circle from three points on its circumference. Using Canny edge detection, the iris radius value is empirically chosen based on rigorous experimentation. Eyelash removal is done by using a horizontal 1-D rank filter. Iris normalization is done by mapping the detected iris region from the polar domain to the rectangular domain and the multi-resolution transforms such as curvelet and ridgelet transforms are applied for multi-resolutional feature extraction. The classification is done using Manhattan distance (Md) and multiclass classifier with logistic function and the two results are compared. Here, the benchmark database CASIA-IRIS-V3 (Interval) is used for identification and recognition. It is observed that the ridgelet transform increases the iris recognition rate.
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Sethy, Abhisek, Prashanta Kumar Patra, and Deepak Ranjan Nayak. "Gray-Level Co-occurrence Matrix and Random Forest Based Off-line Odia Handwritten Character Recognition." Recent Patents on Engineering 13, no. 2 (2019): 136–41. http://dx.doi.org/10.2174/1872212112666180601085544.
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Background: In the past decades, handwritten character recognition has received considerable attention from researchers across the globe because of its wide range of applications in daily life. From the literature, it has been observed that there is limited study on various handwritten Indian scripts and Odia is one of them. We revised some of the patents relating to handwritten character recognition. Methods: This paper deals with the development of an automatic recognition system for offline handwritten Odia character recognition. In this case, prior to feature extraction from images, preprocessing has been done on the character images. For feature extraction, first the gray level co-occurrence matrix (GLCM) is computed from all the sub-bands of two-dimensional discrete wavelet transform (2D DWT) and thereafter, feature descriptors such as energy, entropy, correlation, homogeneity, and contrast are calculated from GLCMs which are termed as the primary feature vector. In order to further reduce the feature space and generate more relevant features, principal component analysis (PCA) has been employed. Because of the several salient features of random forest (RF) and K- nearest neighbor (K-NN), they have become a significant choice in pattern classification tasks and therefore, both RF and K-NN are separately applied in this study for segregation of character images. Results: All the experiments were performed on a system having specification as windows 8, 64-bit operating system, and Intel (R) i7 – 4770 CPU @ 3.40 GHz. Simulations were conducted through Matlab2014a on a standard database named as NIT Rourkela Odia Database. Conclusion: The proposed system has been validated on a standard database. The simulation results based on 10-fold cross-validation scenario demonstrate that the proposed system earns better accuracy than the existing methods while requiring least number of features. The recognition rate using RF and K-NN classifier is found to be 94.6% and 96.4% respectively.
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Greve, Katharina, Riccardo De Vita, Seppo Leminen, and Mika Westerlund. "Living Labs: From Niche to Mainstream Innovation Management." Sustainability 13, no. 2 (2021): 791. http://dx.doi.org/10.3390/su13020791.
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Living Labs have received increasing attention over the last decade. However, despite their growing popularity and ability to positively impact organisations’ innovation performance, mainstream innovation management literature has overlooked the diverse and promising Living Labs research landscape. In an effort to move the field forward, this study analyses extant Living Labs literature in the domain of innovation management. The study identifies conceptual bases informing Living Labs research, maps the collaboration between scholars in the field, examines prevailing themes influencing the debate and reveals the influence of Living Labs research on other domains. Bibliometric methods of co-authorship, keyword co-occurrence analysis as well as bibliographic coupling are employed on two databases. Database A includes 97 focal journal articles and Database B includes all cited sources of Database A, totalling 500 documents. This study reveals the rapid growth of the scholarly literature on Living Labs in the innovation management domain, driven by a core group of authors. However, other contributions from highly visible scholars have the potential to connect Living Lab research to mainstream innovation management studies. The study also identifies the influence of Living Labs research in different application fields and potential for its further evolution.
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Martynowicz, Helena, Joanna Smardz, Tomasz Wieczorek, et al. "The Co-Occurrence of Sexsomnia, Sleep Bruxism and Other Sleep Disorders." Journal of Clinical Medicine 7, no. 9 (2018): 233. http://dx.doi.org/10.3390/jcm7090233.
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Background: Sleep sex also known as sexsomnia or somnambulistic sexual behavior is proposed to be classified as NREM (non-rapid eye movement) parasomnia (as a clinical subtype of disorders of arousal from NREM sleep—primarily confusional arousals or less commonly sleepwalking), but it has also been described in relation to REM (rapid eye movement) parasomnias. Methods: The authors searched the PubMed database to identify relevant publications and present the co-occurrence of sexsomnia and other sleep disorders as a non-systematic review with case series. Results: In the available literature the comorbidity of sexsomnia and other sleep disorders were reported mainly in case reports and less in case series. Sexsomnia was reported both with one and with multiple sleep-related disorders, with NREM parasomnias and obstructive sleep apnea (OSA) being the most commonly reported. Furthermore, the authors enrich the article with new findings concerning two novel cases of sleep bruxism triggering recurrent sexsomnia episodes. Conclusions: Sexsomnia has still not been reported in the literature as often as other parasomnias. The coexistence of sexsomnia and other sleep-related disorders should be more thoroughly examined. This could help both in sexsomnia as well as other sleep-related disorders management.
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Weng, Ze F., W. D. Sam Motherwell, Frank H. Allen, and Jacqueline M. Cole. "Conformational variability of molecules in different crystal environments: a database study." Acta Crystallographica Section B Structural Science 64, no. 3 (2008): 348–62. http://dx.doi.org/10.1107/s0108768108005442.
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A methodology is described for analysing the Cambridge Structural Database (CSD) in terms of molecular conformations. Molecular species that have more than a single occurrence across the complete CSD are identified, either as the sole crystal component or co-crystallized with other components. Cluster analysis, based on a root-mean-square fit of coordinates and chemical connectivity, is performed to identify conformational variance for each molecule. Results are analysed in terms of the number of discrete conformations observed versus the number of crystal environments and number of acyclic torsion angles in the molecule. Special subsets of environments are also analysed, namely polymorphs, co-crystals and solvates. In general, conformational diversity increases with an increasing number of different crystal environments and with an increasing number of flexible torsion angles. Overall, molecules with one or more acyclic flexible torsion angle are observed to exist in more than one conformation in ca 40% of cases. There is evidence that solvated molecules exhibit more conformational flexibility on average, compared with polymorphs and co-crystals.
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Saher, Liudmyla, Liubov Syhyda, Olena Korobets, and Tamara Berezianko. "Closed-Loop Supply Chain: A bibliometric and visualization analysis." E3S Web of Conferences 234 (2021): 00011. http://dx.doi.org/10.1051/e3sconf/202123400011.
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Nowadays, enterprises have to be good for society, to take care of the environment, and to achieve profit at the same time. And the closed-loop supply chain helps them being so. However, there is a lack of bibliometric and visualization research in the area of “Closed-Loop Supply Chain”. Thus, this research aims to present a bibliometric overview to define the current state of scientific production regarding “Closed-Loop Supply Chain”. The review of 807 publications from the Scopus database (1995–2020) was conducted. Two combinations of words with the logical operator (“supply chain” AND “reverse logistics”) were used. The “title, abstract, keywords” field of search in the Scopus database was done. The visualization of the results was made using VOSviewer program to graphically map the material. The study used the co-occurrence of keywords and co-authorship (country) analyses. As a result, the most productive authors and journals were defined. The most cited studies were determined. Country clusters and keywords (co-occurrence) clusters were represented. The obtained results of the analysis and graphical presentations are relevant, and they form the basis for a better understanding of the concept of Closed-Loop Supply Chain.
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R. Sahrawat, Tammanna, and Devika Talwar. "Network-Centric Identification of Disease Co-Occurrences: A Systems Biology Approach." Sumerianz Journal of Medical and Healthcare, no. 311 (November 28, 2020): 103–10. http://dx.doi.org/10.47752/sjmh.311.103.110.
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Complex diseases that occur by perturbations of molecular pathways and genetic factors result in pathophysiology of diseases. Network-centric systems biology approaches play an important role in understanding disease complexity. Diabetes, cardiovascular disease and depression are such complex diseases that have been reported to be comorbid in various epidemiological studies but there are no reports of the genetic and underlying factors which may be responsible for their reported co-occurrences. The present study was undertaken to investigate the molecular factors responsible for co-occurrence of diabetes, depression and cardiovascular disease using in-silico network systems biology approach. Genes common amongst these three diseases were retrieved from DisGeNET, a database of human diseases and their interactions were retrieved from STRING database. The resulting network containing 99 nodes (which represent genes) and 1252 edges (which represent various interactions between nodes) was analyzed using Cytoscape v: 3.7.2 and its various plug-ins i.e. ClusterONE, Cytohubba, ClueGO and Cluepedia. The hub genes identified in the present study namely IL1B, VEGFA, LEP, CAT, CXCL8, PLG, IL6, IL10, PTGS2, TLR4 and AKT1 were found to be enriched in various metabolic pathways and several mechanisms such as inflammation. These genes and their protein products may act as potential biomarkers for early detection of predisposition to diseases and potential therapeutic targets based on the common molecular underpinnings of co-occurrence of diabetes, depression and cardiovascular disease.
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Gorzeń-Mitka, Iwona, Beata Bilska, Marzena Tomaszewska, and Danuta Kołożyn-Krajewska. "Mapping the Structure of Food Waste Management Research: A Co-Keyword Analysis." International Journal of Environmental Research and Public Health 17, no. 13 (2020): 4798. http://dx.doi.org/10.3390/ijerph17134798.
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Food loss and waste represent a global problem in the ethical, social, environmental, and economic contexts. The aim of this article is to identify leading concepts in studies on food loss and waste in management research by network analysis of the co-occurrence of keywords, via mapping of knowledge domains, a method used in bibliometrics. We analyzed 2202 records from the Scopus database on food waste management with the aid of the VOSviewer software tool. In particular, keyword co-occurrence analysis was adopted to visually explore knowledge bases, topic distribution, and research fronts in the field of food waste management research. Ten representative areas were found concentrated in main keywords, namely, food waste, waste management, food, anaerobic digestion, waste disposal, recycling, waste treatment, municipal solid waste, solid waste, and refuse disposal.
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Marinescu (Repanovici), Raluca, and Anişor Nedelcu. "3D printing new direction and collaboration in scientific research. A scientometric study using Web of Science, Clarivate Analytics database." MATEC Web of Conferences 178 (2018): 07009. http://dx.doi.org/10.1051/matecconf/201817807009.
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A scientometric study to quantify the global research activity in the field of 3D printing has been conducted by the authors. Primary data was acquired as plain text files from Web of Science database (WoS). 11529 results were found. Hereby, the total research productivity, scientific output of countries, individual institution authors, journals and their collaborative networks were assessed. The results - keywords based on co-occurrence and co-citation networks - were visualized by using VOS Viewer, a software tool for constructing and visualizing bibliometric networks.
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Zhu, Shanfeng, Yasushi Okuno, Gozoh Tsujimoto, and Hiroshi Mamitsuka. "Application of a New Probabilistic Model for Mining Implicit Associated Cancer Genes from OMIM and Medline." Cancer Informatics 2 (January 2006): 117693510600200. http://dx.doi.org/10.1177/117693510600200025.
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An important issue in current medical science research is to find the genes that are strongly related to an inherited disease. A particular focus is placed on cancer-gene relations, since some types of cancers are inherited. As bio-medical databases have grown speedily in recent years, an informatics approach to predict such relations from currently available databases should be developed. Our objective is to find implicit associated cancer-genes from biomedical databases including the literature database. Co-occurrence of biological entities has been shown to be a popular and efficient technique in biomedical text mining. We have applied a new probabilistic model, called mixture aspect model (MAM) [ 48 ], to combine different types of co-occurrences of genes and cancer derived from Medline and OMIM (Online Mendelian Inheritance in Man). We trained the probability parameters of MAM using a learning method based on an EM (Expectation and Maximization) algorithm. We examined the performance of MAM by predicting associated cancer gene pairs. Through cross-validation, prediction accuracy was shown to be improved by adding gene-gene co-occurrences from Medline to cancer-gene co-occurrences in OMIM. Further experiments showed that MAM found new cancer-gene relations which are unknown in the literature. Supplementary information can be found at http://www.bic.kyotou.ac.jp/pathway/zhusf/CancerInformatics/Supplemental2006.html
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Thompson, Alesha K., Michele M. Monti, and Matthew O. Gribble. "Co-Occurrence of Metal Contaminants in United States Public Water Systems in 2013–2015." International Journal of Environmental Research and Public Health 18, no. 15 (2021): 7884. http://dx.doi.org/10.3390/ijerph18157884.
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The United States Environmental Protection Agency monitors contaminants in drinking water and consolidates these results in the National Contaminant Occurrence Database. Our objective was to assess the co-occurrence of metal contaminants (total chromium, hexavalent chromium, molybdenum, vanadium, cobalt, and strontium) over the years 2013–2015. We used multilevel Tobit regression models with state and water system-level random intercepts to predict the geometric mean of each contaminant occurring in each public water system, and estimated the pairwise correlations of predicted water system-specific geometric means across contaminants. We found that the geometric means of vanadium and total chromium were positively correlated both in large public water systems (r = 0.45, p < 0.01) and in small public water systems (r = 0.47, p < 0.01). Further research may address the cumulative human health impacts of ingesting more than one contaminant in drinking water.
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Purnomo, Margo, Erna Maulina, Ahmad Zaki, and Dian Fordian. "STATE-OF-THE-ART DIGITAL ENTREPRENEURSHIP DALAM BISNIS KELUARGA: ANALISIS CO-AUTHORSHIP DAN CO-OCCURRENCE." AdBispreneur 6, no. 1 (2021): 93. http://dx.doi.org/10.24198/adbispreneur.v6i1.31103.
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There are still few in family business studies that discuss the topic of digipreneurship, even though digipreneurship is important for continuity and growth of companies in today's business world. Therefore, the aim of this study is to uncover the state-of-the-art and create research gaps in the literature related to digipreneurship in family business. For this purpose, a bibliometric study using co-authorship and key word co-occurrence analysis conducted in the Scopus database. The results of the co-authorship analysis show that the cohesiveness of collaboration in exploring digipreneurship in family business has been achieved at the state level in the 2017-2020 period, but at the author and organizational level has not been achieved. This indicates that the study of digipreneurship in family business is in early stages of growth. The results of the co-occurrence keyword analysis show that there are three specific domains in the field, namely digital transformation of entrepreneurial-oriented family firms; entrepreneurial knowledge management and digital capabilities in the family business; and transgenerational entrepreneurship in the digital era; Another domain that is important to be developed but has not been identified and has become a research gap is the value chain and internal processes in digipreneurship in family business. Penelitian bisnis keluarga sampai saat ini belum banyak yang membahas topik digipreneurship, padahal digipreneurship penting untuk keberlangsungan dan pertumbuhan perusahaan di dunia bisnis saat ini. Karena itu, tujuan penelitian ini adalah untuk mengungkap state-of-the-art dan memunculkan kesenjangan penelitian dalam literatur terkait dengan digipreneurship dalam bisnis keluarga. Untuk tujuan tersebut, Penulis melakukan penelitian bibliometrik dengan metode analisis co-authorship dan analisis co-occurrence kata kunci pada basis data Scopus. Hasil analisis co-authorship menunjukkan bahwa kohesivitas kolaborasi dalam mengekplorasi digipreneurship dalam bisnis keluarga sudah tercapai di tingkat negara dalam rentang tahun 2017-2020, namun kohesivitas co-authorship di tingkat penulis dan organisasi belum tercapai. Kondisi demikian mengindikasikan bahwa kajian digipreneurship dalam bisnis keluarga masih berada dalam fase awal tumbuh. Hasil analisis co-occurrence kata kunci menunjukkan bahwa ada tiga domain yang khas dalam publikasi ilmiah digipreneurship dalam bisnis keluarga yaitu transformasi digital perusahaan keluarga berorientasi entrepreneurial, manajemen pengetahuan entrepreneurial dan kapabilitas digital dalam bisnis keluarga, dan entrepreneurship transgenerasi pada era digital; Domain lain yang penting untuk dikembangkan namun belum teridentifikasi dan menjadi kesenjangan dalam penelitian ini adalah domain rantai nilai dan proses internal pada digipreneurship dalam bisnis keluarga.
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Huma Sikandar and Umar Haiyat Abdul Kohar. "Global Trend of Social Innovation Research." Asia Proceedings of Social Sciences 8, no. 1 (2021): 1–5. http://dx.doi.org/10.31580/apss.v8i1.1896.
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The aim of this research is to identify the latest trends of the scientific publications in the social innovation literature. This research is conducted through bibliometric analysis of the available data from 1966 to 2019 in the Scopus database. The bibliometric analysis is carried out on all ‘published’ articles in the Scopus database. The search phrase used was “Social Innovation”. Out of 3140 articles, 1280 articles were included in the study based on their relevance to the objectives of this study. This research investigates parameters such as publications in line with the years, subject areas, top journals, top authors and countries contributing to the social innovation field, and also the collaborations of author and co-occurrence of keywords. Results indicate that Frances R. Westley (University of waterloo) is the most productive author in field. Additionally, we found that the most prolific journal is “sustainability” and the most productive country is the United Kingdom. A significant increase in the number of scientific publications in the social innovation field is observed since 2016 which leads to the conclusion that the topic has gained relevance among academicians in recent years. We used VoS Viewer visual bibliometric analyser to identify the co-occurrence of keywords and co-authorship of countries.
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Ding, Wubin, Jiwei Chen, Guoshuang Feng, et al. "DNMIVD: DNA methylation interactive visualization database." Nucleic Acids Research 48, no. D1 (2019): D856—D862. http://dx.doi.org/10.1093/nar/gkz830.
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Abstract Aberrant DNA methylation plays an important role in cancer progression. However, no resource has been available that comprehensively provides DNA methylation-based diagnostic and prognostic models, expression–methylation quantitative trait loci (emQTL), pathway activity-methylation quantitative trait loci (pathway-meQTL), differentially variable and differentially methylated CpGs, and survival analysis, as well as functional epigenetic modules for different cancers. These provide valuable information for researchers to explore DNA methylation profiles from different aspects in cancer. To this end, we constructed a user-friendly database named DNA Methylation Interactive Visualization Database (DNMIVD), which comprehensively provides the following important resources: (i) diagnostic and prognostic models based on DNA methylation for multiple cancer types of The Cancer Genome Atlas (TCGA); (ii) meQTL, emQTL and pathway-meQTL for diverse cancers; (iii) Functional Epigenetic Modules (FEM) constructed from Protein-Protein Interactions (PPI) and Co-Occurrence and Mutual Exclusive (COME) network by integrating DNA methylation and gene expression data of TCGA cancers; (iv) differentially variable and differentially methylated CpGs and differentially methylated genes as well as related enhancer information; (v) correlations between methylation of gene promoter and corresponding gene expression and (vi) patient survival-associated CpGs and genes with different endpoints. DNMIVD is freely available at http://www.unimd.org/dnmivd/. We believe that DNMIVD can facilitate research of diverse cancers.
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Yang, Yang, and Xiangyu Zhu. "Status and Trend of Research on the Funding and Management of Basic Research in China: An Analysis Based on Knowledge Maps of Core Journal Database of China National Knowledge Infrastructure in 1992-2019." International Journal of Emerging Technologies in Learning (iJET) 16, no. 06 (2021): 201. http://dx.doi.org/10.3991/ijet.v16i06.21095.
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This paper aims to clarify the current status, hotspots, historical evolution and development trend of the research on funding and management of basic research in China. Firstly, 736 relevant papers indexed during 1992-2019 in the core journal database of China National Knowledge Infrastructure (CNKI) were analyzed in details. Using the information visualization software CiteSpaceV5.6.R3, the institutional cooperation co-occurrence map, author cooperation co-occurrence map, keyword co-occurrence map, and keyword timeline view maps were plotted through content mining. The results show that: the research institutions in the research field of basic research funding and management have formed three core cooperation networks, and the institutions in Beijing attract the most attention; most of the prolific and active authors choose teamwork over independent research; the research topics mainly fall into four aspects of basic research: input, subjects, results, and talents; the research hotspots are in line with policies and demands, and evolve through three stages: exploration and gradual progress, adjustment and development, and expansion and acceleration. The research results open up a new direction for relevant studies, and provide a reference for innovative parties to implement basic research.
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Türk, Abdullah, and Kağan Cenk Mızrak. "Bibliometric analysis of research in the field of organizational communication in the web of science database." Business & Management Studies: An International Journal 9, no. 3 (2021): 1173–85. http://dx.doi.org/10.15295/bmij.v9i3.1832.
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For organizations, communication is one of the most critical factors affecting their continuity, goals, and success levels. Organizational communication directs the relationship between internal and external stakeholders of the organization by taking a role in all organizational action and managerial processes. In this context, it also affects organizational outcomes. Effectively and efficiently channelling intra-organizational communication for organizational success is also effective in employees' understanding of their duties and responsibilities within the organization and activating their knowledge skills and abilities in line with the organisation's goals. At this point, it can be said that organizational communication adds mobility to businesses through self-expression. From this perspective, it understands the communication subject's development processes that play a crucial role for organizations in the literature and revealing its relationship with other variables will bring a systematic and holistic perspective to the relevant literature. With the bibliometric analysis method made for this purpose, it is aimed to create a perspective on how organizational communication offers mobility to businesses, the development, quality and quantity of the process. In this context; Distribution of studies on organizational communication by years, co-authorship of authors, co-authorship of organizations, co-authorship of countries, citation of authors, bibliographic coupling of documents, co-citation of authorship, co-citation of sources, co- The maps of occurrence of keywords were created, and the levels of contribution to the literature and the areas where the subject interacts were conveyed.
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Gudanowska, Alicja Ewa. "A Map of Current Research Trends within Technology Management in the Light of Selected Literature." Management and Production Engineering Review 8, no. 1 (2017): 78–88. http://dx.doi.org/10.1515/mper-2017-0009.
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Abstract The objective of the analysis conducted and described in this article was to take a closer perspective of the contemporary research trends that refer to the discipline of technology management. The Author based the analysis on keywords defined by the authors of the publications that refer issues of technology management. Scopus was the database which provided data for the analysis. The Author focused on publications indexed in the selected database in 2011-2016. The resulting database keywords have been ordered and partially aggregated. Based on them, the VOSviewer tool was used to prepare a graphical presentation of frequency and co-occurrence with the rest of the analysed group. The analysis led to an indication of current research trends within the discipline of technology management.
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Fan, Zhi Guo, and Wen Long Zheng. "The Analysis of Research Hotspot of Chinese Cultural and Creative Industry - Based on Co-Words Method." Advanced Materials Research 798-799 (September 2013): 924–29. http://dx.doi.org/10.4028/www.scientific.net/amr.798-799.924.
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Based on the journal resource from the cqvip database, taking "cultural and creative industry" as the keyword, the paper retrieved all the relevant "CSSCI" documents from 1989 to 2012. After getting the keywords co-occurrence matrix through BIBCOMB software, the paper focused on the keywords analysis which was obtained by the software UCINET and NETDRAW. Then it comes to the conclusion, which shows that development countermeasures, cultural area, cultural creativity and influential factors are the hotspots in present research.
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Abdulla, Beshaier A., Yossra H. Ali, and Nuha J. Ibrahim. "Extract the Similar Images Using the Grey Level Co-Occurrence Matrix and the Hu Invariants Moments." Engineering and Technology Journal 38, no. 5A (2020): 719–27. http://dx.doi.org/10.30684/etj.v38i5a.519.
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In the last years, many types of research have introduced different methods and techniques for a correct and reliable image retrieval system. The goal of this paper is a comparison study between two different methods which are the Grey level co-occurrence matrix and the Hu invariants moments, and this study is done by building up an image retrieval system employing each method separately and comparing between the results. The Euclidian distance measure is used to compute the similarity between the query image and database images. Both systems are evaluated according to the measures that are used in detection, description, and matching fields which are precision, recall, and accuracy, and addition to that mean square error (MSE) and structural similarity index (SSIM) is used. And as it shows from the results the Grey level co-occurrence matrix (GLCM) had outstanding and better results from the Hu invariants moment method.
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Sedighi, Mehri. "Application of word co-occurrence analysis method in mapping of the scientific fields (case study: the field of Informetrics)." Library Review 65, no. 1/2 (2016): 52–64. http://dx.doi.org/10.1108/lr-07-2015-0075.
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Purpose – The purpose of this article is to investigate the use of word co-occurrence analysis method in mapping of the scientific fields with emphasis on the field of Informetrics. Design/methodology/approach – This is an applied study using scientometrics, co-word analysis and network analysis and its steps are summarised as follows: collecting the data related to the Informetrics field indexed in Web of Science (WOS) database, refining and standardising the keywords of the extracted articles from WOS and preparing a selected list of these keywords, drawing the word co-occurrence map in the Informetrics field and analysing of results. Findings – Based on the resulted maps the concepts such as information science, library, bibliometric analysis, innovation and text mining are the most widely used topics in the field of Informetrics. The co-word occurrence maps drawn at different periods show the changes and stabilities in the concepts related to the field of Informetrics. A number of topics such as “bibliometric analysis” are present in all years, whereas others such as “innovation” have disappeared. New topics emerge as a recombination of existing topics and in interaction with new (technological) developments. Originality/value – The results of these analytical studies can be used as a guide for determining research priorities in the scientific fields, and also for planning and management in academic institutions.
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Yu, Pei, and Peng Sun. "Progress in environmental gentrification research and hotspot analysis based on CiteSpace analysis." E3S Web of Conferences 251 (2021): 02071. http://dx.doi.org/10.1051/e3sconf/202125102071.
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With the advent of the post-industrial era, environmental improvements and sustainable initiatives that lack sufficient attention to the social justice aspects of environmental changes generates environmental gentrification. The purpose of this paper is to systematically explore the frontiers of gentrification research and the knowledge base of environmental gentrification. Therefore, based on Web of Science Core Collection Database, this paper analysed the progress and hotpots of environmental gentrification using CiteSpace, identified keywords relevant to environmental gentrification and their frequency of co-occurrence using the function of keyword co-occurrence analysis, recognized top ten clusters using the function of cluster analysis. Environmental gentrification is the frontier on gentrification research, which knowledge base and hotpots research should arouse our attention. This paper can help readers to understand the status quo and development trend of environmental gentrification better, recognize defect in the development of environmental gentrification, and provide a promising direction for future research.
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Chen, Li-Ping, Li-Peng Yu, Meng-Chao Hao, Yu-Sen Li, and Qi-Wu Wang. "Advances and prospects in heat pipe: A critical eview." E3S Web of Conferences 252 (2021): 03023. http://dx.doi.org/10.1051/e3sconf/202125203023.
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As an efficient heat transfer element, the heat pipe has excellent thermal conductivity. It has important application value in chemical, building materials, metallurgy, power engineering, bioengineering and other fields. In order to systematically analyze the development trend of heat pipe, the paper takes the literature on heat pipe from 2010 to 2020 included in the Web of Science database as the data source, and analyzes the collected data with information visualization software CiteSpace to draw out the heat pipe technology countries, institutions, research authors distribution network map, showing the technology research power distribution and cooperation in scientific research. The use of software co-occurrence analysis of the hot science and technology of heat pipe technology, at the same time, the key words co-occurrence network diagram and literature citation network are used to analyze the research hotspots, research frontiers and trends of heat pipe technology.
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Lou, Yan, Shang Zhang, and Lu Cheng Huang. "Research on Identifying Experts in Biomaterials Field Based on CiteSpaceII." Applied Mechanics and Materials 577 (July 2014): 1231–35. http://dx.doi.org/10.4028/www.scientific.net/amm.577.1231.
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Based on the original literature on biomaterials included in Web of Science between the year 1985 and 2012, this paper conducts the author co-occurrence and co-citation analysis, makes the high-frequency co-authors map and co-citation map, and shows the researchers distribution, with the information visualization software CiteSpaceII. By detecting the leading researchers in the biomaterials field, it helps the researchers to comprehend the research fronts and hot research topics quickly, identify classic literature efficiently, and write the literature review in their research activities easily. It provides the experts research direction to view related documents in the vast amounts of data. Moreover, the research result of this paper can provide a basis for relevant government departments to establish the expert database in the biomaterials field.
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Escoriza, Daniel. "Ship rats and island reptiles: patterns of co-existence in the Mediterranean." PeerJ 8 (March 19, 2020): e8821. http://dx.doi.org/10.7717/peerj.8821.
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Background The western Mediterranean archipelagos have a rich endemic fauna, which includes five species of reptiles. Most of these archipelagos were colonized since early historic times by anthropochoric fauna, such as ship rats (Rattus rattus). Here, I evaluated the influence of ship rats on the occurrence of island reptiles, including non-endemic species. Methodology I analysed a presence-absence database encompassing 159 islands (Balearic Islands, Provence Islands, Corso-Sardinian Islands, Tuscan Archipelago, and Galite) using Bayesian-regularized logistic regression. Results The analysis indicated that ship rats do not influence the occurrence of endemic island reptiles, even on small islands. Moreover, Rattus rattus co-occurred positively with two species of non-endemic reptiles, including a nocturnal gecko, a guild considered particularly vulnerable to predation by rats. Overall, the analyses showed a very different pattern than that documented in other regions of the globe, possibly attributable to a long history of coexistence.
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Vasumathi, R., and S. Murugan. "Mining of High Average-Utility Pattern Using Multiple Minimum Thresholds in Big Data." Asian Journal of Computer Science and Technology 8, S2 (2019): 57–60. http://dx.doi.org/10.51983/ajcst-2019.8.s2.2024.
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In the past years most of the research have been conducted on high average-utility itemset mining (HAUIM) with wide applications. However, most of the methods are used for centralized databases with a single machine performing the mining job. Existing algorithms cannot be applied for big data. We try to solve this issue, by developing a new method for mining high average-utility itemset mining in big data. Map Reduce also used in this paper. Many algorithms were proposed only mine HAUIs using a single minimum high average-utility threshold. In this paper we also try solve this by mining HAUIs multiple minimum high average-utility thresholds. We have developed two pruning methods namely Reduction of utility co-occurrence pruning Method (RUCPM) and Pruning without Scanning Database (PWSD).
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Žukauskas, Mindaugas, and Renata Korsakienė. "KONFLIKTŲ SPRENDIMAS IR LYDERYSTĖ: BIBLIOMETRINĖ ANALIZĖ / CONFLICT RESOLUTION AND LEADERSHIP: A BIBLIOMETRIC ANALYSIS." Mokslas - Lietuvos ateitis 11 (June 14, 2019): 1–8. http://dx.doi.org/10.3846/mla.2019.9241.
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Conflict resolution and leadership is growing research topic in academic literature. The demand of leaders of organizations to manage conflicts requires further analysis of this topic. It is necessary for better understanding of conflict resolution relationship with leadership. Bibliometrical analysis reveals this relationship. The study analyses 526 references collected from the Web of Science database and uses the VOSviewer program to graphically map the material. The bibliometric analysis involves co-occurrence of keywords, co-citation and co-authorship. The results identify the leading trends and development status in terms of impact, main journals, authors, papers, topics and countries. The analysis and graphical presentations are relevant for researchers and practitioners for better understanding of the state of the art of concflict resolution and leadership.
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Cui, Yaqiang, Qihong Gan, Xiaoli Huang, Yu Qi, Chunyan Wang, and Jianlin Tian. "Research Progress and Trends of Domestic Smart Learning Environment." Review of Educational Theory 2, no. 2 (2019): 46. http://dx.doi.org/10.30564/ret.v2i2.760.
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In order to explore the main progress and current status of domestic research on smart learning environment, this paper takes 260 core and CSSCI journal papers included in the CNKI database as the research objects, and uses CiteSpace visual analysis software and uses bibliometrics and knowledge graph analysis as the main research methods, summarizes and analyzes the time distribution of the literature, the distribution of institutions and authors, co-occurrence and clustering of keywords, and research hotspots, etc.
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Goksu, Idris, Omer Kocak, Ali Gunduz, and Yuksel Goktas. "Instructional Design Studies Between 1975 and 2019." International Journal of Online Pedagogy and Course Design 11, no. 1 (2021): 73–92. http://dx.doi.org/10.4018/ijopcd.2021010105.
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This study aimed to examine the bibliometric results (co-authorship, citation, co-occurrence, bibliographic coupling, and co-citation) of publications in the field of instructional design. The study includes the publications in the database of the Web of Science in the period between 1975 and 2019. It was found through co-authorship analysis that 9,344 authors who had written in the field of instructional design functioned as co-authors and had links. There were studies on an instructional design from 103 different countries. It was also found that keywords such as e-learning and online learning were frequently used and that the studies published in recent years prioritized the keywords of the massive open online courses, mobile learning, flipped classroom, gamification, and augmented reality. While the most published authors were F. Paas and J. van Merrienboer in the field, the author who was the most cited was J. Sweller.
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Perryman, Carol. "Thematic Categorization and Analysis of Peer Reviewed Articles in the LISA Database, 2004-2005." Evidence Based Library and Information Practice 4, no. 1 (2009): 36. http://dx.doi.org/10.18438/b89042.
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A Review of: 
 Gonzalez-Alcaide, Gregorio, Lourdes Castello-Cogolles, Carolina Navarro-Molina, et al. “Library and Information Science Research Areas: Analysis of Journal Articles in LISA.” Journal of the American Society for Information Science and Technology 59.1 (2008): 150-4.
 
 Objective – To provide an updated categorization of Library and Information Science (LIS) publications and to identify trends in LIS research.
 
 Design – Bibliometric study.
 
 Setting – The Library and Information Science Abstracts (LISA) database via the CSA Illumina interface.
 
 Subjects – 11,273 item records published from 2004-2005 and indexed in LISA.
 
 Methods – First, a search was set up to retrieve all records from 2004-2005, limited to peer review items (called “arbitrated works” by the authors (150)) and excluding book reviews. Second, thematic descriptor terms used for the records were identified. Frequency counts for descriptor term occurrence were compiled using Microsoft Access and Pajek software programs. From the results of this search, the top terms were analyzed using the Kamada-Kawai algorithm in order to eliminate descriptor term co-occurrence frequencies under 30. A cluster analysis was used to depict thematic foci for the remaining records, providing a co-word network that visually identified topic areas of most frequent publication. Conclusions were drawn from these findings, and recommendations for further research were provided.
 
 Main Results – The authors identified 18 “thematic research core fields” (152) clustered around three large categories, “World Wide Web”, “Education”, and “Libraries”, plus 12 additional peripheral categories, and provided a schematic of field interrelationships.
 
 Conclusion – Domains of greatest focus for research “continue to be of practical and applied nature,” (153) but include increased emphasis on the World Wide Web and communications technologies, as well as on user studies. A table of the most frequently occurring areas of research along with their top three descriptor terms is provided (Table 1, 152) (e.g., “World Wide Web” as the top area of research, with “online information retrieval” (268 occurrences), “searching” (132 occurrences), and “web sites” (115 occurrences)).
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Mezaal, Yaqeen. "Face Recognition Approach Based on the Integration of Image Preprocessing, CMLABP and PCA Methods." Iraqi Journal for Electrical and Electronic Engineering 13, no. 1 (2017): 104–13. http://dx.doi.org/10.37917/ijeee.1.12.
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Face recognition technique is an automatic approach for recognizing a person from digital images using mathematical interpolation as matrices for these images. It can be adopted to realize facial appearance in the situations of different poses, facial expressions, ageing and other changes. This paper presents efficient face recognition model based on the integration of image preprocessing, Co-occurrence Matrix of Local Average Binary Pattern (CMLABP) and Principle Component Analysis (PCA) methods respectively. The proposed model can be used to compare the input image with existing database images in order to display or record the citizen information such as name, surname, birth date, etc. The recognition rate of the model is better than 99%. Accordingly, the proposed face recognition system is functional for criminal investigations. Furthermore, it has been compared with other reported works in the literature using diverse databases and training images.
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Mezaal, Yaqeen. "Face Recognition Approach Based on the Integration of Image Preprocessing, CMLABP and PCA Methods." Iraqi Journal for Electrical and Electronic Engineering 13, no. 1 (2017): 104–13. http://dx.doi.org/10.37917/ijeee.13.1.12.
Full textAbstract:
Face recognition technique is an automatic approach for recognizing a person from digital images using mathematical interpolation as matrices for these images. It can be adopted to realize facial appearance in the situations of different poses, facial expressions, ageing and other changes. This paper presents efficient face recognition model based on the integration of image preprocessing, Co-occurrence Matrix of Local Average Binary Pattern (CMLABP) and Principle Component Analysis (PCA) methods respectively. The proposed model can be used to compare the input image with existing database images in order to display or record the citizen information such as name, surname, birth date, etc. The recognition rate of the model is better than 99%. Accordingly, the proposed face recognition system is functional for criminal investigations. Furthermore, it has been compared with other reported works in the literature using diverse databases and training images.
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Bindu, Hima, and Manjunathachari K. "Hybrid feature descriptor and probabilistic neuro-fuzzy system for face recognition." Sensor Review 38, no. 3 (2018): 269–81. http://dx.doi.org/10.1108/sr-06-2017-0115.
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Purpose This paper aims to develop the Hybrid feature descriptor and probabilistic neuro-fuzzy system for attaining the high accuracy in face recognition system. In recent days, facial recognition (FR) systems play a vital part in several applications such as surveillance, access control and image understanding. Accordingly, various face recognition methods have been developed in the literature, but the applicability of these algorithms is restricted because of unsatisfied accuracy. So, the improvement of face recognition is significantly important for the current trend. Design/methodology/approach This paper proposes a face recognition system through feature extraction and classification. The proposed model extracts the local and the global feature of the image. The local features of the image are extracted using the kernel based scale invariant feature transform (K-SIFT) model and the global features are extracted using the proposed m-Co-HOG model. (Co-HOG: co-occurrence histograms of oriented gradients) The proposed m-Co-HOG model has the properties of the Co-HOG algorithm. The feature vector database contains combined local and the global feature vectors derived using the K-SIFT model and the proposed m-Co-HOG algorithm. This paper proposes a probabilistic neuro-fuzzy classifier system for the finding the identity of the person from the extracted feature vector database. Findings The face images required for the simulation of the proposed work are taken from the CVL database. The simulation considers a total of 114 persons form the CVL database. From the results, it is evident that the proposed model has outperformed the existing models with an improved accuracy of 0.98. The false acceptance rate (FAR) and false rejection rate (FRR) values of the proposed model have a low value of 0.01. Originality/value This paper proposes a face recognition system with proposed m-Co-HOG vector and the hybrid neuro-fuzzy classifier. Feature extraction was based on the proposed m-Co-HOG vector for extracting the global features and the existing K-SIFT model for extracting the local features from the face images. The proposed m-Co-HOG vector utilizes the existing Co-HOG model for feature extraction, along with a new color gradient decomposition method. The major advantage of the proposed m-Co-HOG vector is that it utilizes the color features of the image along with other features during the histogram operation.
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Su, Ching Hun, Huang Sen Chiu, and Tsai Ming Hsieh. "Content Based Images Retrieval Based on HSV Color Space and GLCM." Applied Mechanics and Materials 644-650 (September 2014): 4287–90. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.4287.
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We propose a practical image retrieval scheme to retrieve images efficiently. We succeed in transferring the image retrieval problem to sequences comparison and subsequently using the color sequences comparison along with the texture feature of Gray Level Co-occurrence matrix to compare the images of database. Thus the computational complexity is decreased obviously. Our results illustrate it has virtues of both the content based image retrieval system and a text based image retrieval system. Experimental results reveal that proposed scheme is better than the conventional methodologies.
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Rekis, Toms. "Crystallization of chiral molecular compounds: what can be learned from the Cambridge Structural Database?" Acta Crystallographica Section B Structural Science, Crystal Engineering and Materials 76, no. 3 (2020): 307–15. http://dx.doi.org/10.1107/s2052520620003601.
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A detailed study on chiral compound structures found in the Cambridge Structural Database (CSD) is presented. Solvates, salts and co-crystals have intentionally been excluded, in order to focus on the most basic structures of single enantiomers, scalemates and racemates. Similarity between the latter and structures of achiral monomolecular compounds has been established and utilized to arrive at important conclusions about crystallization of chiral compounds. For example, the fundamental phenomenon of conglomerate formation and, in particular, their frequency of occurrence is addressed. In addition, rarely occurring kryptoracemates and scalemic compounds (anomalous racemates) are discussed. Finally, an extended search of enantiomer solid solutions in the CSD is performed to show that there are up to 1800 instances most probably hiding among the deposited crystal structures, while only a couple of dozen have been previously known and studied.
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Pico-Saltos, Roberto, Paúl Carrión-Mero, Néstor Montalván-Burbano, Javier Garzás, and Andrés Redchuk. "Research Trends in Career Success: A Bibliometric Review." Sustainability 13, no. 9 (2021): 4625. http://dx.doi.org/10.3390/su13094625.
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The purpose of this article is to provide an overview of academic research on professional success, using the bibliometric analysis to understand the evolution of this field between the years 1990 and 2020. The information was obtained from the publications indexed in the Scopus database, under a rigorous bibliometric process that comprises five parts: (i) criteria search of the field, (ii) selection of database and documents, (iii) inclusion and selection criteria, (iv) software and data selection, and (v) analysis and results. The results show professional success as a scientific discipline in full exponential growth, which allows us to consider the main contributions of authors, institutions, and international contributions, as well as to consider the main themes that have shaped the intellectual structure of the subject through their visualization using bibliometric maps of co-citation and co-occurrence, which combined showed eight main lines of research. The results obtained allowed us to identify patterns of convergence and divergence in various topics, which allows obtaining current and diverse information on the state of the research field’s art.
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Nazar, Rogelio, Irene Renau, Nicolas Acosta, Hernan Robledo, Maha Soliman, and Sofıa Zamora. "Corpus-Based Methods for Recognizing the Gender of Anthroponyms." Names 69, no. 3 (2021): 16–27. http://dx.doi.org/10.5195/names.2021.2238.
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This paper presents a series of methods for automatically determining the gender of proper names, based on their co-occurrence with words and grammatical features in a large corpus. Although the results obtained were for Spanish given names, the method presented here can be easily replicated and used for names in other languages. Most methods reported in the literature use pre-existing lists of first names that require costly manual processing and tend to become quickly outdated. Instead, we propose using corpora. Doing so offers the possibility of obtaining real and up-to-date name-gender links. To test the effectiveness of our method, we explored various machine-learning methods as well as another method based on simple frequency of co-occurrence. The latter produced the best results: 93% precision and 88% recall on a database of ca. 10,000 mixed names. Our method can be applied to a variety of natural language processing tasks such as information extraction, machine translation, anaphora resolution or large-scale delivery or email correspondence, among others.
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Varsha P. S., Shahriar Akter, Amit Kumar, Saikat Gochhait, and Basanna Patagundi. "The Impact of Artificial Intelligence on Branding." Journal of Global Information Management 29, no. 4 (2021): 221–46. http://dx.doi.org/10.4018/jgim.20210701.oa10.
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Understanding the growth paths of artificial intelligence (AI) and its impact on branding is extremely pertinent of technology-driven marketing. This explorative research covers a complete bibliometric analysis of the impact of AI on branding. The sample for this research included all 117 articles from the period of 1982-2019 in the Scopus database. A bibliometric study was conducted using co-occurrence, citation analysis and co-citation analysis. The empirical analysis investigates the value propositions of AI on branding. The study revealed the nine clusters of co-occurrence: Social Media Analytics and Brand Equity; Neural Networks and Brand Choice; Chat Bots-Brand Intimacy; Twitter, Facebook, Instagram-Luxury Brands; Interactive Agent-Brand Love and User Choice; Algorithm Recommendations and E-Brand Experience; User-Generated Content-Brand Sustainability; Brand Intelligence Analytics; and Digital Innovations and Brand Excellence. The findings also identify four clusters of citation analysis—Social Media Analysis and Brand Photos, Network Analysis and E-Commerce, Hybrid Simulating Modelling, and Real-time Knowledge-Based Systems—and four clusters of co-citation analysis: B2B Technology Brands, AI Fostered E-Brands, Information Cascades and Online Brand Ratings, and Voice Assistants-Brand Eureka Moments. Overall, the study presents the patterns of convergence and divergence of themes, narrowing to the specific topic, and multidisciplinary engagement in research, thus offering the recent insights in the field of AI on branding.
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Chiu, Weisheng, Thomas Chun Man Fan, Sang-Back Nam, and Ping-Hung Sun. "Knowledge Mapping and Sustainable Development of eSports Research: A Bibliometric and Visualized Analysis." Sustainability 13, no. 18 (2021): 10354. http://dx.doi.org/10.3390/su131810354.
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The rapid expansion of the eSports industry has attracted scholars’ attention in recent years. However, little research has investigated the evolution of the extant eSports literature. This study aimed to explore the existing knowledge base of eSports and its research networks across authors, journals, institutions, and countries by performing a bibliometric analysis. A total of 260 studies published between 2010 and 2021 were extracted from the Scopus database, which is one of the largest abstract and citation databases. Then, they were analyzed using VOSviewer. Specifically, a series of analyses were conducted: (1) citation analysis, (2) co-occurrence analysis of keywords, and (3) co-citation analysis. The findings revealed that the existing eSports literature mainly revolves around eSports games and activities closely related to eSports. Moreover, the most influential authors and publications were identified. In addition, the studies have been published in journals of various disciplines (e.g., technology and psychology), and the concepts and theories in sport-related fields (e.g., sports management) have been extensively applied in eSports research. This study’s findings contribute to a better understanding of eSports research, which can further provide directions for the sustainable development of eSports research.
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Di Fabio, José Luis, María de los Ángeles Cortés Castillo, and Elwyn Griffiths. "Landscape of research, production, and regulation in venoms and antivenoms: a bibliometric analysis." Revista Panamericana de Salud Pública 45 (May 18, 2021): 1. http://dx.doi.org/10.26633/rpsp.2021.55.
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Objective. To assess the productivity and visibility in research, clinical studies, treatment, use and production of antivenoms against poisonous snakes, scorpions and spiders. Method. Bibliometric analysis of research and other activities. Articles on venoms and antivenoms published between 2000 and 2020 were retrieved from the Scopus database. The records were analyzed by bibliometric indicators including number of documents per year, journals, authors, and citation frequency. VOSviewer® v.1.6.13 was used to construct bibliometric networks for country co-authorships and co-occurrence of terms. Results. Australia, Brazil, Costa Rica and India were among the six top countries with most documents and were selected for more detailed analysis. Costa Rica was the country with the largest percentage of its publications dedicated to antivenom production and venomics. Only a few papers dealt with the issues of quality, safety, and efficacy of antivenoms or the role of the national regulatory authorities. The use of VOSviewer® allowed visualization through joint publications of networking between countries. Visualization by co-occurrence of terms showed differences in the research carried out. Conclusions. Working in a collaborative and coordinated manner these four countries could have a major impact on envenoming globally. Attention should be given not only to antivenom production but also to strengthening regulatory oversight of antivenom products.