the Tecnologico de Monterrey has implemented the Tec21 Educational Model, based on four fundamental pillars: Challenge-based learning (CBL), Flexibility, inspiring trained teachers and a comprehensive educational expe...
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Food security is always one of the most important factors in human lives, and crop diseases are one of the major threats which may bring potential damage. Nowadays, withthe proliferation of smartphones and the advanc...
ISBN:
(纸本)9781450397940
Food security is always one of the most important factors in human lives, and crop diseases are one of the major threats which may bring potential damage. Nowadays, withthe proliferation of smartphones and the advancement of machine learning methods, it is more likely to achieve rapid identification of disease diagnosis by a smartphone-assisted application supported by deep learning trained models. By comparing different datasets and different kinds of CNN frameworks, this paper trained deep convolutional neural networks based on plant leaves’ images to identify species and detect diseases. Furthermore, this paper found the best combination of different datasets withthe highest accuracy. the highest accuracy this work got is 97.37%, using ResNet-9 along with Transfer Learning. Nevertheless, these training datasets are too straightforward to deal withthe more complex real-world situation. Besides, two-dimensional datasets from time to time have such limited information; therefore, more information is needed to diagnose plants’ diseases. For future extension, this work can apply not only image datasets but also environmental factors, such as soil structure and image background, to construct a more precise model to diagnose plant diseases. Hence, the concept of Point Cloud will be discussed in this paper. this work can be viewed as the first step to build an Energy-friendly plant disease classification application supporting sustainability.
Pipeline leak detection technology is one of the core issues in the field of pipeline safety research. based on the classification of hardware-based and software-based methods, this paper summarizes the current mainst...
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the emergence of smart environments built on top of Internet of things (IoT) solutions demand new skills and knowledge for developers. Dealing with inherent complexity of IoT architecture, constrained device limitatio...
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A knowledge-based methodology is proposed for the identification of type and level of violence presented implicitly in shared comments on social media. the work was focused on the semantic processing taking into accou...
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ISBN:
(数字)9783030414078
ISBN:
(纸本)9783030414078;9783030414061
A knowledge-based methodology is proposed for the identification of type and level of violence presented implicitly in shared comments on social media. the work was focused on the semantic processing taking into account the content and handling comments as excerpts of knowledge. Our approach implements similarity measures, conceptual distances, graph theory algorithms, knowledge graphs and disambiguation processes. the methodology is composed for four stages. In the (1) "knowledge base construction" the types and levels of violence are described as well as the knowledge graphs' administration. Mechanisms of inclusion and extraction were developed for the knowledge base's handling and content understanding. the (2) "social media data collection" retrieves comments and maps the social graph's structure. In the (3) "knowledge processing stage" the comments are transformed to formal representations as extracts of knowledge (graphs). Finally in the (4) "violence domain identification" the comments are classified by their type and level of violence. the evaluation was carried out comparing our methodology withthe baselines: (1) a dataset with comments labeled by crowdFlower users, (2) news from social network Twitter, (3) a similar research and (4) typical lexical matching.
Withthe emergence and further integration of computer technology, software radio technology and network information technology, signal analysis and processing are inseparable from the critical moment of modulation re...
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the proceedings contain 23 papers. the special focus in this conference is on Structured Object-Oriented Formal Language and Method. the topics include: Solving constraint optimization problems based on mathematica an...
ISBN:
(纸本)9783030414177
the proceedings contain 23 papers. the special focus in this conference is on Structured Object-Oriented Formal Language and Method. the topics include: Solving constraint optimization problems based on mathematica and abstraction;a forward chaining heuristic search with spatio-temporal control knowledge;Formal development and verification of reusable component in PAR platform;a new mutant generation algorithm based on basic path coverage for mutant reduction;formal specification and model checking of a ride-sharing system in maude;Model checking python programs with MSVL;prediction of function removal propagation in linux evolution;regression models for performance ranking of configurable systems: a comparative study;combining model learning and model checking to analyze java libraries;data provenance based system for classification and linear regression in distributed machine learning;A formal technique for concurrent generation of software’s functional and security requirements in SOFL specifications;metamorphic testing in fault localization of model transformations;a fault localization method based on dynamic failed execution blocks;adaptive random testing by bisection and comprehensive distance;CMM: A combination-based mutation method for SQL injection;distortion and faults in machine learning software;A divide & conquer approach to testing concurrent java programs with JPF and maude;An approach to modeling and verifying multi-level interrupt systems with TMSVL;towards formal verification of neural networks: a temporal logic based framework;UMC4M: A verification tool via program execution;parallel runtime verification approach for alternate execution of multiple threads.
this paper focusses on the ongoing discussion of developing a single relationship that can accurately predict the shear capacity of slender, reinforced concrete (RC) beams without stirrups. To date, the main approach ...
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How to use meaningful learning features to predict learning outcomes is a key issue in learning analytics. With feature engineering, this study constructed a feature set, including eight effective learning features ab...
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ISBN:
(纸本)9781728191713
How to use meaningful learning features to predict learning outcomes is a key issue in learning analytics. With feature engineering, this study constructed a feature set, including eight effective learning features about interactions of student-student, student-teacher, student-content, and student-interface. the trace data of 108 middle school students on the E-cloudbag LMS was collected and analyzed, which proved that the feature set can effectively predict the students' learning outcomes. the random forest algorithm achieved the best prediction effect, and the prediction accuracy rate was 73.15%. At the same time, this study used a k-means clustering algorithm to cluster 108 students into four categories, and analyzed the differences between four types of students in regard to learning patterns and learning outcomes. the results showed that LMS usage, speed of completing assignments, academic procrastination, peer emotion and social network size were important factors influencing learning outcomes.
Human action recognition is an active research topic in computer vision. It is a challenging task to model various actions, varying with time resolution, visual appearance and others. For each action category, a large...
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