دانلود و نمایش مقالات مرتبط با Classification::صفحه 4
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نتیجه جستجو - Classification

تعداد مقالات یافته شده: 909
ردیف عنوان نوع
31 Soft biometric based keystroke classification using PSO optimized neural network
طبقه بندی نرم افزاری بیومتریک با استفاده از شبکه عصبی بهینه شده PSO-2021
In this work, variable length login-id and password belonging to the user were analyzed for bringing forth a more secure verification system. Soft biometrics such as age group and gender are estimated from key- stroke dynamics patterns when he/she types a given password or login id on a keyboard. Experiments were carried on GREYC a web-based keystroke dataset by exploiting the features from DWT of keystroke dynamics and provides classification results using PSO optimized neural network. Experiments done using PSO-NN resulted in 94% accuracy which clearly out performs the BPNN and GA-NN classifiers.© 2021 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the Emerging Trends in Materials Science, Technology and Engineering.
Keywords: Soft biometric | Discrete wavelet transform (DWT) | Genetic Algorithm optimized neural network (GA-NN) | Back propagation neural network (BPNN) | Particle Swarm Optimized neural network(PSO-NN)
مقاله انگلیسی
32 Palm print identification and classification using KNN algorithm
شناسایی و طبقه بندی چاپ کف با استفاده از الگوریتم KNN-2021
The best way of biometric security is face recognition, iris’ recognition, and palm print recognition. Palm recognition is a form of biometric process which is based on the different patterns of different characteristic. As in the case with the patterns in fingers, scanning the palm scanner uses optical, tactile, thermal methods to bring out the details in the patterns of raised areas which are called as ridges and branches called bifurcations, palm recognition is considered as a special type for security purposes as the finger patterns vary from person to person with different characteristics. This is scanned by a scanner or CCD. They can also be used for forensic, criminal, or commercial uses. Palm print gives a better level of accuracy and it is the best biometric way for security purposes. Various classifiers are used to match the palm print with the stored data. This system proposes a KNN classifier to match the current palm print with the existing dataset. This system produces a better result than other matching techniques.© 2021 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the Emerging Trends in Materials Science, Technology and Engineering.
Keywords: Palm print | KNN | Classifier | Accuracy | Biometric
مقاله انگلیسی
33 Construction of carbonate reservoir knowledge base and its application in fracture-cavity reservoir geological modeling
ساخت پایگاه دانش مخزن کربناته و کاربرد آن در مدلسازی زمین شناسی مخزن شکستگی-حفره ای-2021
To improve the efficiency and accuracy of carbonate reservoir research, a unified reservoir knowledge base linking geological knowledge management with reservoir research is proposed. The reservoir knowledge base serves high-quality analysis, evaluation, description and geological modeling of reservoirs. The knowledge framework is divided into three categories: technical service standard, technical research method and professional knowledge and cases related to geological objects. In order to build a knowledge base, first of all, it is necessary to form a knowledge classification system and knowledge description standards; secondly, to sort out theoretical understandings and various technical methods for different geologic objects and work out a technical service standard package according to the technical standard; thirdly, to collect typical outcrop and reservoir cases, constantly expand the content of the knowledge base through systematic extraction, sorting and saving, and construct professional knowledge about geological objects. Through the use of encyclopedia based collaborative editing architecture, knowledge construction and sharing can be realized. Geological objects and related attribute parameters can be automatically extracted by using natural language processing (NLP) technology, and outcrop data can be collected by using modern fine measurement technology, to enhance the efficiency of knowledge acquisition, extraction and sorting. In this paper, the geological modeling of fracture-cavity reservoir in the Tarim Basin is taken as an example to illustrate the construction of knowledge base of carbonate reservoir and its application in geological modeling of fracture-cavity carbonate reservoir.
keywords: knowledge management | reservoir knowledge base | fracture-cavity reservoir | geological modeling | carbonates | paleo-underground river system | Tahe oilfield | Tarim Basin
مقاله انگلیسی
34 Feature based classification of voice based biometric data through Machine learning algorithm
طبقه بندی مبتنی بر ویژگی داده های بیومتریک مبتنی بر صدا از طریق الگوریتم یادگیری ماشین-2021
In the era of big data and growing artificial intelligence, the requirement and necessity of biometric identification increase in a rapid manner. The digitalization and recent Pandemic crisis gives a boost to need to authorized identification which get fulfilled with biometric identification. Our paper focuses on same concept of checking the identification accuracy of machine learning algorithm REPTree on selected bio- metric dataset which is being deployed and evaluated on a data mining tool WEKA. Our target is to achieve more or equal to 95 percentages in order to predict the given sample data is accurately classified into our target variables values i.e. male female. The selected algorithm REPTree is a kind of decision tree classification algorithm which works on same concept as C4.5 and decision tree algorithm with speciality of generation of both kind of output i.e. discrete and continuous. The selection of algorithm gives us ben- efits with achievement of higher accuracy and selection of dataset also become easy with some required modification and pre-processing of data with some dimension reduction filters.© 2021 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the 1st International Con- ference on Computations in Materials and Applied Engineering – 2021.
Keywords: Prediction | Biometric data | Voice samples | Male | Female | Cost complexity pruning (CCP) | Dimension reduction
مقاله انگلیسی
35 Knowledge of healthcare providers in the management of anaphylaxis
آگاهی از ارائه دهندگان خدمات بهداشتی در مدیریت آنافیلاکسی-2021
Introduction: Anaphylaxis is defined as a severe, life-threatening systemic hypersensitivity reaction. Early diagnosis and treatment of a severe allergic reaction requires recognition of the signs and symptoms, as well as classification of severity. It is a clinical emergency, and healthcare providers should have the knowledge for recognition and management. The aim of the study is to evaluate the level of knowledge in the management of anaphylaxis in healthcare providers.
Methods: It is an observational, descriptive, cross-sectional study conducted among healthcare providers over 18 years old via a Google Forms link and shared through different social media platforms. A 12-item questionnaire was applied which included the evaluation of the management of anaphylaxis, from June 2020 to May 2021.
Results: A total of 1023 surveys were evaluated; 1013 met inclusion criteria and were included in the statistical analysis. A passing grade was considered with 8 or more correct answers out of 12; the overall approval percentage was 28.7%. The group with the highest percentage of approval in the questionnaire was health-care providers with more than 30 years of work experience. There was a significant difference between the proportions of approval between all specialty groups, and in a post-hoc analysis, allergy and immunology specialists showed greater proportions of approval compared to general medicine practitioners (62.9% vs 25%; p¼<0.001).
Conclusions: It is important that healthcare providers know how to recognize, diagnose, and treat anaphylaxis, and later refer them to specialists in Allergy and Clinical Immunology in order to make a personalized diagnosis and treatment.
Keywords: Anaphylaxis | Epinephrine | Healthcare providers | Knowledge
مقاله انگلیسی
36 GaitCode: Gait-based continuous authentication using multimodal learning and wearable sensors
GaitCode: احراز هویت پیوسته مبتنی بر راه رفتن با استفاده از یادگیری چند حالته و حسگرهای پوشیدنی-2021
The ever-growing threats of security and privacy loss from unauthorized access to mobile devices have led to the development of various biometric authentication methods for easier and safer data access. Gait-based authentication is a popular biometric authentication as it utilizes the unique patterns of human locomotion and it requires little cooperation from the user. Existing gait-based biometric authentication methods however suffer from degraded performance when using mobile devices such as smart phones as the sensing device, due to multiple reasons, such as increased accelerometer noise, sensor orientation and positioning, and noise from body movements not related to gait. To address these drawbacks, some researchers have adopted methods that fuse information from multiple accelerometer sensors mounted on the human body at different lo- cations. In this work we present a novel gait-based continuous authentication method by applying multimodal learning on jointly recorded accelerometer and ground contact force data from smart wearable devices. Gait cycles are extracted as a basic authentication element, that can continuously authenticate a user. We use a network of auto-encoders with early or late sensor fusion for feature extraction and SVM and soft max for classification. The effectiveness of the proposed approach has been demonstrated through extensive experiments on datasets collected from two case studies, one with commercial off-the-shelf smart socks and the other with a medical-grade research prototype of smart shoes. The evaluation shows that the proposed approach can achieve a very low Equal Error Rate of 0.01% and 0.16% for identification with smart socks and smart shoes respectively, and a False Acceptance Rate of 0.54%–1.96% for leave-one-out authentication.
Keywords: Biometric authentication | Gait authentication | Autoencoders | Sensor fusion | Multimodal learning | Wearable sensors
مقاله انگلیسی
37 EBAPy: A Python framework for analyzing the factors that have an influence in the performance of EEG-based applications
EBAPy: یک چارچوب پایتون برای تجزیه و تحلیل عوامل موثر بر عملکرد برنامه های مبتنی بر EEG-2021
EBAPy is an easy-to-use Python framework intended to help in the development of EEG-based applications. It allows performing an in-depth analysis of factors that influence the performance of the system and its computational cost. These factors include recording time, decomposition level of Discrete Wavelet Transform, and classification algorithm. The ease-of-use and flexibility of the presented framework have allowed reducing the development time and evaluating new ideas in developing biometric systems using EEGs. Furthermore, different applications that classify EEG signals can use EBAPy because of the generality of its functions. These new applications will impact human–computer interaction in the near future.Code metadataCurrent code version v1.1Permanent link to code/repository used for this code version https://github.com/SoftwareImpacts/SIMPAC-2021-2Permanent link to Reproducible Capsule https://codeocean.com/capsule/4497139/tree/v1Legal Code License MITCode versioning system used gitSoftware code languages, tools, and services used Python Compilation requirements, operating environments & dependencies If available Link to developer documentation/manualSupport email for questions dustin.carrion@gmail.com
Keywords: EEG-based applications | Recording time | Discrete wavelet transform
مقاله انگلیسی
38 Cultural consensus knowledge of rice farmers for climate risk management in the Philippines
دانش اجماع فرهنگی کشاورزان برنج برای مدیریت ریسک آب و هوایی در فیلیپین-2021
Despite efforts and investments to integrate weather and climate knowledges, often dichotomized into the scientific and the local, a top-down practice of science communication that tends to ignore cultural consensus knowledge still prevails. This paper presents an empirical application of cultural consensus analysis for climate risk management. It uses mixed methods such as focus groups, freelisting, pilesorting, and rapid ethnographic assessment to understand farmers’ knowledge of weather and climate conditions in Barangay Biga, Oriental Mindoro, Philippines. Multi-dimensional scaling and aggregate proximity matrix of items are generated to assess the similarity among the different locally perceived weather and climate conditions. Farmers’ knowledge is then qualitatively compared with the technical classification from the government’s weather bureau. There is cultural agreement among farmers that the weather and climate con- ditions can be generally grouped into wet, dry, and unpredictable weather (Maria Loka). Damaging hazards belong into two subgroups on the opposite ends of the wet and dry scale, that is, tropical cyclone is grouped together with La Ni˜na, rainy season, and flooding season, while farmers perceive no significant difference between El Ni˜no, drought, and dry spells. Ethnographic information reveals that compared to the technocrats’ reductive knowledge, farmers imagine weather and climate conditions (panahon) as an event or a phenomenon they are actively experiencing by observing bioindicators, making sense of the interactions between the sky and the landscape, and the agroecology of pest and diseases, while being subjected to agricultural regulations on irrigation, price volatility, and control of power on subsidies and technologies. This situated local knowledge is also being informed by forecasts and advisories from the weather bureau illustrating a hybrid of technical science, both from the technocrats and the farmers, and personal experiences amidst agricultural precarities. Speaking about the hybridity of knowledge rather than localizing the scientific obliges technocrats and scientists to productively engage with different ways of knowing and the tensions that mediate farmers’ knowledge as a societal experience.
keywords: دانش اجماع | پیش بینی آب و هوا | کشاورزی | خطر ابتلا به آب و هوا | Consensus knowledge | Weather forecasting | Agriculture | Climate risk
مقاله انگلیسی
39 How to select a Supply Chain Finance solution?
چگونه می توان یک راه حل تامین مالی برای زنجیره تامین را انتخاب کرد؟-2021
In the complex picture of Supply Chain Finance (SCF), there is still a need for a model supporting managerial decisions in selecting the most suitable financing solution. The objective of the presented exploratory work is to bring together the relational aspects between buyers and suppliers, and the characteristics of SCF solutions. Based on expert interviews and a focus group, the main result consists of a classification model of buyer-led SCF solutions, according to the characteristics of the relationship between a buyer and its suppliers, in terms of bargaining power and cumulative transaction value. The model thus describes the logics behind the adoption by a buyer firm of one or more SCF solutions to be implemented with different suppliers.
Keywords: SCF | Decision making | Bargaining power
مقاله انگلیسی
40 How viable is password cracking in digital forensic investigation? Analyzing the guessability of over 3:9 billion real-world accounts
شکستن رمز عبور در تحقیقات پزشکی قانونی دیجیتال چقدر قابل اجرا است؟ تجزیه و تحلیل قابلیت حدس زدن بیش از 3:9 میلیارد حساب در دنیای واقعی-2021
Passwords have been and still remain the most common method of authentication in computer systems. These systems are therefore privileged targets of attackers, and the number of data breaches in the last few years attests to that. A detailed analysis of such data can provide insight on password trends and patterns users follow when they create a password. To this end, this paper presents the largest and most comprehensive analysis of real-world passwords to date e associated with over 3.9 billion accounts from Have I Been Pwned. This analysis includes statistics on use and most common patterns found in passwords and innovates with a breakdown of the constituent fragments that make each password. Furthermore, a classification of these fragments according to their semantic meaning, provides insight on the role of context in password selection. Finally, we provide an in-depth analysis on the guessability of these real-world passwords.
keywords: Password security | Password-based authentication | Context-based password cracking | Password strength meters
مقاله انگلیسی
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