1,720,989 research outputs found
Enhancing soybean classification with modified inception model: A transfer learning approach
No full textThe impact of deep learning (DL) is substantial across numerous domains, particularly in agriculture. Within this context, our study focuses on the classification of problematic soybean seeds. The dataset employed encompasses five distinct classes, totaling 5513 images. Our model, based on the InceptionV3 architecture, undergoes modification with the addition of five supplementary layers to enhance efficiency and performance. Techniques such as transfer learning, adaptive learning rate adjustment (to 0.001), and model checkpointing are integrated to optimize accuracy. During initial evaluation, the InceptionV3 model achieved 88.07% accuracy in training and 86.67% in validation. Subsequent implementation of model tuning strategies significantly improves performance. Augmenting the architecture with additional layers, including Average Pooling, Flatten, Dense, Dropout, and Softmax, plays a pivotal role in enhancing accuracy. Evaluation metrics, including precision, recall, and F1-score, underscore the model’s effectiveness. Precision ranges from 0.9706 to 1.0000, while recall values demonstrate a high capture rate across all classes. The F1-score, reflecting a balance between precision and recall, exhibits remarkable performance across all classes, with values ranging from 0.9851 to 1.0000. Comparative analysis with existing studies reveals competitive accuracy of 98.73% achieved by our proposed model. While variations exist in specific purposes and datasets among studies, our model showcases promising performance in soybean seed classification, contributing to advancements in agricultural technology for crop health assessment and management
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Covıd-19'Un Tüketici Çevrimiçi Satın Alma Davranışı Üzerindeki Etkisini Araştırmak İçin Yapay Zekadan Yararlanma: Konya İli ÖrneğiLeveraging Aı To Study The Impact Of Covıd-19 On Consumer Online Purchase Behaviour: A Study Of Konya
No full textKaratay İslam İktisadı ve Finans DergisiKaratay Journal of Islamic Economics and FinanceBu makale, COVID-19 sağlık krizinin tüketicilerin çevrimiçi alışveriş davranışları üzerindeki etkisini ele almayı ve e-ticaret platformunun seçimine yönelik karar vermeyi etkileyen faktörlere odaklanmayı amaçlamaktadır. Çalışma, Konya Ticaret Odası’ndan çevrimiçi olarak uygulanan bir ankete verilen yanıtların yorumlanmasına dayanmaktadır. Kolaylık, popülerlik, aşinalık, faydalar ve şeffaflık açısından bir e-ticaret platformunu diğerine tercih etme sorunu ortaya çıkmaktadır. Çalışma aynı zamanda farklı nesillerin çevrimiçi alışveriş platformlarını, ürün öğelerini seçmeye yönelik davranışlarını ve katılımcıların yerel (Yalnızca Konya’dan) çevrimiçi perakendecileri destekleme istekliliğini etkileyen ana faktörleri de araştırmaktadır. Çalışma, yerel tedarikçilerden alışveriş yapma olasılığı en yüksek olası müşterileri bulmak ve belirlemek için yapay zeka tekniklerine işaret ediyor. Müşterilerin ülke çapındaki muadili yerine bölgesel olarak yerel tedarikçileri tercih etme olasılığını tahmin eden bir AI (Yapay Zeka) modeli geliştirilmiştir. Eğitimli model, test setinde 0,91 doğruluk bildirmiştir; bu, müşterinin verileri göz önüne alındığında, modelin insanların 91’inin yerel bir tedarikçiden satın almaya istekli olduğunu tahmin ettiği anlamına geliyor. Bu model, satışları artıran belirli bir zamanda belirli kişilere yönelik hedefli reklamlar için kullanılabilir. Araştırma betimsel bir araştırma yöntemini benimsemiş ve Konya Ticaret Odası üyeleri tarafından temsil edilen Konya’da yaşayan insanların tutumlarını betimlemeyi amaçlamaktadır.The paper intends to address the impact of the COVID-19 crisis upon consumer online shopping behaviour, focusing on the factors that affect the decision making towards the choice of e-commerce platform. The study relies on interpreting answers received from the Konya Chamber of Commerce to a questionnaire applied online. The problem of choosing one e-commerce platform over another in terms of convenience, popularity, familiarity, benefits, and transparency is introduced. The study also investigates the main factors that influence different generations’ behaviour towards choosing the online shopping platforms, product items, and respondents’ willingness to support the local (Only from Konya) online retailers. The study implies AI techniques to find and identify the prospective customers most likely to shop from the local suppliers. An AI model has been developed that predicts the customers’ likelihood of preferring regionally local suppliers over the nationwide counterpart. The trained model reported an accuracy of 0.91 on the testing set, which means that given the customer’s data, the model predicts that 91 of the people are willing to buy from a local supplier. This model can be used for targeted advertisement for specific people at a specific time which improve the sales. The study adopts a descriptive research method and aims at describing the attitude of people living in Konya, represented by the members of the Konya Chamber of Commerce
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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