Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has 350 images. Three fully connected (FC) layers were utilized for feature extraction, namely fc6, fc7, and fc8. The classifiers employed were support vector machine (SVM), k-nearest neighbors (KNN), and Naive Bayes. The study demonstrated that the most effective feature extraction layer was fc6, achieving an accuracy of 90.7% with SVM. SVM outperformed KNN and Naive Bayes, exhibiting an accuracy of 90.7%, sensitivity of 83.5%, specificity of 93.7%, and F1-score of 83.5%. This research successfully addressed the challenges in classifying cassava species by leveraging deep learning and machine learning methods, specifically with SVM and the fc6 layer of AlexNet. The proposed approach holds promise for enhancing plant classification techniques, benefiting researchers, farmers, and environmentalists in plant species identification, ecosystem monitoring, and agricultural management.
Electronic Health Record (EHR) systems are used as an efficient and effective method of exchanging patients’ health information with doctors and other key stakeholders in the health sector to obtain improved patient treatment decisions and diagnoses. As a result, questions regarding the security of sensitive user data are highlighted. To encourage people to move their sensitive health records to cloud networks, a secure authentication and access control mechanism that protects users’ data should be established. Furthermore, authentication and access control schemes are essential in the protection of health data, as numerous responsibilities exist to ensure security and privacy in a network. So, the main goal of our s
... Show MoreSupport vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca
... Show MoreThe research aims to evaluate the current book chemistry fourth grade scientific questions on the classification according to Gallagher And Aschner levels of its four reflexion A cognitive thinking, thinking Convergent , Divergent thinking and osteopathic thinking and evaluating those questions in terms of standards of honesty, inclusiveness and objectivity . The research sample included a book of chemistry for fourth grade scientific for the academic year (2016 - 2017), the same research community and the number of sub - prime questions amounted to (354) Question distributed to the chapters of the book adult (6) chapters, the researchers ends of chapters by classification questions by finding the relative weight of the are
... Show MoreThis paper aims to add to the growing body of cognitive translation studies that deal with the translation of emotions and the factors of evaluating the translation process-oriented. Cognitive appraisal is one of the tokens that includes three paradigms of assessing the performance of translation, it can be addressed from the perspective of emotions, intuitions, and individual styles of the SL and the method of transfer into TL. The study hypothesized that translators create a similar emotional charge due to their mental capability to build the same emotional effect in the TL audience. The study also proposed that the applicability of cognitive appraisal is a valuable method of evaluating the translation process, as pertinent to TPR. The
... Show MoreTime and space are indispensable basics in cinematic art. They contain the characters, their actions and the nature of events, as well as their expressive abilities to express many ideas and information. However, the process of collecting space and time in one term is space-time, and it is one of Einstein’s theoretical propositions, who sees that Time is an added dimension within the place, so the study here differs from the previous one, and this is what the researcher determined in the topic of his research, which was titled (The Dramatic Function of Space-Time Variables in the Narrative Film), Which included the following: The research problem, which crystallized in the following question: What is the dramatic function of the tempor
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