The Influence of Modern Electronic Media on the Teaching Content of Traditional Design

2021 ◽  
Vol 7 (5) ◽  
pp. 4474-4484
Author(s):  
Yuanting Yang
Keyword(s):  
Differentiated Instruction ◽  
Implementation Process ◽  
Classification Algorithm ◽  
Classification Method ◽  
Theoretical Research ◽  
Computer Design ◽  
The Difference ◽  
Bayes Algorithm ◽  
Student Classification ◽  
Differentiated Teaching

Objectives: At present, most of the researches on differentiated teaching focus on the theoretical research of differentiated instruction, the demonstration of necessity of differentiated instruction, the implementation process of differential teaching, and the implementation of differentiated teaching. Methods: at present, most of the researches on differentiated teaching focus on the theoretical research of differentiated instruction, the demonstration of necessity of differentiated instruction, the implementation process of differential teaching, and the implementation of differentiated teaching. Results: This paper took computer design course as an example, mainly from three aspects: the simple Bias classification algorithm, the student’s difference performance and the difference teaching. Based on the related theories, a student classification method based on Naive Bayes algorithm was proposed. Conclusion: This paper took computer design course as an example, mainly from three aspects: the simple Bias classification algorithm, the student’s difference performance and the difference teaching. Based on the related theories, a student classification method based on Naive Bayes algorithm was proposed.

scholarly journals Differential Classification Method in Different Teaching Models of Accounting Courses Based on Naive Bayesian Classification Algorithm

2019 ◽  
Vol 14 (08) ◽  
pp. 38
Author(s):  
Xiuying Ou
Keyword(s):  
Bayesian Classification ◽  
Classification Algorithm ◽  
Classification Method ◽  
Self Awareness ◽  
Naive Bayesian ◽  
Naïve Bayesian ◽  
Accounting Courses ◽  
Generative Teaching ◽  
The Difference ◽  
Student Classification

Accounting is an important management discipline with strong theoretical foundation and practical operation. Due to the differences between individuals in the process of learning, the mastery of the subject is different. This requires teachers to implement differential teaching from the differences in student personality in the process of teaching. However, when teachers use the concept of difference teaching to teach, the classification of students' differences is mostly calculated by manual quantification such as records, tests, surveys, etc. This kind of measurement and qualitative method not only wastes manpower, but also has personal subjectivity, blindly relies on individual subjective judgment to judge students' advantages and interests, and has accuracy and scientificity. This requires research on students' differential classification methods. Therefore, this paper proposes a student classification method based on naive Bayesian algorithm. It constructs a classifier based on historical data, and then uses a well-structured and stable classifier to classify the actual pre-classification objects, and actually applies it to the teaching of accounting courses, realizing the difference in the teaching process. Provide data support for future differential teaching research. The results show that the naive Bayesian classification algorithm can be used to analyze the difference in personality and learning of students. Presupposition and generative teaching objectivesand students improve their self-awareness to better promote self-development.

Study of Network Public Opinion Classification Method Based on Naive Bayesian Algorithm in Hadoop Environment

2014 ◽  
Vol 519-520 ◽  
pp. 58-61 ◽  
Author(s):  
Jian Xu ◽  
Bin Ma
Keyword(s):  
Public Opinion ◽  
Distributed Storage ◽  
Bayesian Classification ◽  
Classification Algorithm ◽  
Classification Method ◽  
Single Server ◽  
Naive Bayesian ◽  
Naïve Bayesian ◽  
Bayes Algorithm ◽  
Network Public Opinion

In the light of the excellent distributed storage and parallel processing feature of hadoop cluster, a new kind of network public opinion classification method based on Naive Bayes algorithm in hadoop environment is studied. The collected public opinion documents are stored locally according to the HDFS architecture, and whose character words are extracted paralleled in Mapreduce process. Thus the naive Bayesian classification algorithm is parallel encapsulated on cloud computing platform. The MapReduce packaged Naive Bayesian classification algorithm performance is verified and the results show that the algorithm execution speed are significantly improved compared to a single server. Its public opinion classification accuracy rate is more than 85%, which can effectively improve the classification performance of network public opinion and classification efficiency.

Cutoff Threshold Decisions for Classification Algorithms with Risk Aversion

2021 ◽  
Author(s):  
Andrea C. Hupman
Keyword(s):  
Risk Aversion ◽  
Risk Attitude ◽  
Classification Algorithm ◽  
Classification Algorithms ◽  
Risk Averse ◽  
Optimal Cutoff ◽  
Data Set ◽  
Risk Neutral ◽  
Bayes Algorithm ◽  
Cutoff Threshold

Classification algorithms predict the class membership of an unknown record. Methods such as logistic regression or the naïve Bayes algorithm produce a score related to the likelihood that a record belongs to a particular class. A cutoff threshold is then defined to delineate the prediction of one class over another. This paper derives analytic results for the selection of an optimal cutoff threshold for a classification algorithm that is used to inform a two-action decision in the cases of risk aversion and risk neutrality. The results provide insight to how the optimal cutoff thresholds relate to the associated costs and the sensitivity and specificity of the algorithm for both the risk neutral and risk averse decision makers. The optimal risk averse threshold is not reliably above or below the optimal risk neutral threshold, but the relation depends on the parameters of a particular application. The results further show the risk averse optimal threshold is insensitive to the size of the data set or the magnitude of the costs, but instead is sensitive to the proportion of positive records in the data and the ratio of costs. Numeric examples and sensitivity analysis derive further insight. Results show the percent value gap from a misspecified risk attitude increases as the specificity of the classification algorithm decreases.

INVESTIGATION OF THE ABSOLUTENESS OF TIME

2021 ◽  
pp. 51-54
Author(s):  
S. Tiguntsev
Keyword(s):  
High Precision ◽  
Gravitational Potential ◽  
High Speed ◽  
Relativistic Effect ◽  
Theoretical Research ◽  
Clock Frequency ◽  
Positioning Systems ◽  
The Earth ◽  
Flow Of Time ◽  
The Difference

In classical physics, time is considered absolute. It is believed that all processes, regardless of their complexity, do not affect the flow of time The theory of relativity determines that the flow of time for bodies depends both on the speed of movement of bodies and on the magnitude of the gravitational potential. It is believed that time in space orbit passes slower due to the high speed of the spacecraft, and faster due to the lower gravitational potential than on the surface of the Earth. Currently, the dependence of time on the magnitude of the gravitational potential and velocity (relativistic effect) is taken into account in global positioning systems. However, studying the relativistic effect, scientists have made a wrong interpretation of the difference between the clock frequency of an orbiting satellite and the clock frequency on the Earth's surface. All further studies to explain the relativistic effect were carried out according to a similar scenario, that is, only the difference in clock frequencies under conditions of different gravitational potentials was investigated. While conducting theoretical research, I found that the frequency of the signal changes along the way from the satellite to the receiver due to the influence of Earth's gravity. It was found that the readings of two high-precision clocks located at different heights will not differ after any period of time, that is, it is shown that the flow of time does not depend on the gravitational potential. It is proposed to conduct full-scale experiments, during which some high-precision clocks are sent aboard the space station, while others remain in the laboratory on the surface of the earth. It is expected that the readings of the satellite clock will be absolutely identical to the readings of the clock in the Earth laboratory.

scholarly journals UPACARA NGAJAGA-JAGA DI PURA DALEM DESA ADAT TIYINGAN KECAMATAN PETANG KABUPATEN BADUNG (Perspektif Pendidikan Agama Hindu)

2017 ◽  
Vol 1 (2) ◽  
pp. 63
Author(s):  
Putu Ayu Ariastuti
Keyword(s):  
Religious Education ◽  
Ethics Education ◽  
Implementation Process ◽  
Sampling Technique ◽  
Literature Study ◽  
Educational Values ◽  
Max Scheler ◽  
Process Implementation ◽  
The Difference ◽  
Theory Of Value

<p><em>Ngajaga-jaga ceremony is a religious ceremony performed as a sacrifice to Bhuta Kala which aims to get a good life and achieve happiness and harmony. But the difference that is known is very unique is the ceremonial infrastructure used in the ceremony Ngajaga-jagaused the cow, Isused only bone, tail, and to the burned cow, while the meat is made timbungan. Unique infrastructure, there are also other uniqueness that can be seen from the implementation of the Ngajaga-jaga ceremony, the head of the cow is stolen by a citizen, and who stole the head of the cow Is pursued by the sekaa line by using wood tlugtug. When the thief is captured, the thief will ask a ransom of 200 kepeng bucks.</em></p><p><em>The problems to be discussed include: (1) How is the procession of Ngajaga-jaga ceremony atDalem Temple, Adat Village Tiyingan, Petang District, Badung Regency? (2) What is the function of  Ngajaga-jaga Ceremony atDalem Temple, Adat Village of Tiyingan, Petang District, Badung Regency? (3) What values of Hindu religious education are contained in the Ngajaga-jaga Ceremony at Dalem Temple, Adat Village Tiyingan, Petang District, Badung Regency? This research aims to (1) Know the procession of Ngajaga-jaga ceremony in DalemTemple Adat Tiyingan Village, Petang District, Badung Regency, (2) Understand the function of Ngajaga-jaga ceremony at Dalem TempleAdat Tiyingan Village, Petang Sub-district, Badung Regency 3) Describe the values of Hindu religious education contained in the Ngajaga-jaga ceremony at DalemTemple Adat Tiyingan Village, Petang District Badung Regency. Theories used to analyze the problem are: Structuralism Theory of Ratna, Theory of Functionalism of Kaplan, The Theory of Value of Max Scheler. This type of research is qualitative research. The research location is in Adat Village Tiyingan, while the determination of the informant using purposive sampling technique. The methods used to collect data are: observation, interview, document study, and literature study.</em></p><p><em>The results show (1) Ngajaga-jaga ceremonial procession consists of three parts, namely: preparation process, implementation process and final process. (2) The function of the Ngajaga-jaga ceremony are: (1) Religious Function, consisting of 3 parts: Purgatory Function, Function Offering, Nyomya Bhuta Kala Function, (2) Social Function, (3) Educational Function. (3) Educational Values contained in Ngajaga-jaga ceremonies include: (1) Tattwa Education Value, (2) Value of Ethics Education, (3) Value of Educational Ceremony, (4) Value of Aesthetic Education.</em></p>

scholarly journals Attribute Selection in Naive Bayes Algorithm Using Genetic Algorithms and Bagging for Prediction of Liver Disease

2020 ◽  
Vol 4 (1) ◽  
pp. 76-85
Author(s):  
Dwi Yuni Utami ◽  
Elah Nurlelah ◽  
Noer Hikmah
Keyword(s):  
Genetic Algorithms ◽  
Liver Disease ◽  
Naive Bayes ◽  
Confusion Matrix ◽  
Naïve Bayes ◽  
Attribute Selection ◽  
World Health ◽  
The Difference ◽  
Bayes Algorithm ◽  
Health Organization

Liver disease is an inflammatory disease of the liver and can cause the liver to be unable to function as usual and even cause death. According to WHO (World Health Organization) data, almost 1.2 million people per year, especially in Southeast Asia and Africa, have died from liver disease. The problem that usually occurs is the difficulty of recognizing liver disease early on, even when the disease has spread. This study aims to compare and evaluate Naive Bayes algorithm as a selected algorithm and Naive Bayes algorithm based on Genetic Algorithm (GA) and Bagging to find out which algorithm has a higher accuracy in predicting liver disease by processing a dataset taken from the UCI Machine Learning Repository database (GA). University of California Invene). From the results of testing by evaluating both the confusion matrix and the ROC curve, it was proven that the testing carried out by the Naive Bayes Optimization algorithm using Algortima Genetics and Bagging has a higher accuracy value than only using the Naive Bayes algorithm. The accuracy value for the Naive Bayes algorithm model is 66.66% and the accuracy value for the Naive Bayes model with attribute selection using Genetic Algorithms and Bagging is 72.02%. Based on this value, the difference in accuracy is 5.36%.Keywords: Liver Disease, Naïve Bayes, Genetic Agorithms, Bagging.

scholarly journals An Intrusion Detection Model based on Hybrid Classification algorithm

2018 ◽  
Vol 246 ◽  
pp. 03027
Author(s):  
Manfu Ma ◽  
Wei Deng ◽  
Hongtong Liu ◽  
Xinmiao Yun
Keyword(s):  
Intrusion Detection ◽  
Detection Rate ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Classification Algorithm ◽  
Data Set ◽  
Detection Model ◽  
Performance Requirements ◽  
Hybrid Classification ◽  
Bayes Algorithm

Due to using the single classification algorithm can not meet the performance requirements of intrusion detection, combined with the numerical value of KNN and the advantage of naive Bayes in the structure of data, an intrusion detection model KNN-NB based on KNN and Naive Bayes hybrid classification algorithm is proposed. The model first preprocesses the NSL-KDD intrusion detection data set. And then by exploiting the advantages of KNN algorithm in data values, the model calculates the distance between the samples according to the feature items and selects the K sample data with the smallest distance. Finally, by naive Bayes to get the final result. The experimental results on the NSL-KDD dataset show that the KNN-NB algorithm can meet the requirement of balanced performance than the traditional KNN and Naive Bayes algorithm in term of accuracy, sensitivity, false detection rate, specificity, and missed detection rate.

scholarly journals KLASIFIKASI TEKS MENGGUNAKAN CHI SQUARE FEATURE SELECTION UNTUK MENENTUKAN KOMIK BERDASARKAN PERIODE, MATERI DAN FISIKDENGAN ALGORITMA NAIVEBAYES

Compiler ◽  
2016 ◽  
Vol 5 (2) ◽  
Author(s):  
Siti Anisah ◽  
Anton Setiawan Honggowibowo ◽  
Asih Pujiastuti
Keyword(s):  
Feature Selection ◽  
Error Rate ◽  
Classification System ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Chi Square ◽  
Oracle Database ◽  
Category O ◽  
The Difference ◽  
Bayes Algorithm

A comic has its own characteristics compared the other types of books. The difference between comic and other books can be seen from the category o f period, material and physical. Comicand other booksneeded an application o f classification system. Looking for the problem, classification system was made using Chi Square Feature Selection and Naive Bayes algorithm to determine the comic based on the period, material and physical. Delphi programming language and Oracle Database are used to build the Classification System. Chi Square Feature Selection acquired trait a comic is in 0.10347 and which not comic is in 1.9531. Furthermore, data is classified by the Naive Bayes algorithm. From 120 titles o f comic that consists 60 titles o f comic and non comicused to build classesfor trainand 60 titles o f comic and non comic used to test. The results o f Naive Bayesalgorithm for comic is 96,67%with 3.33% error rate, and non comic is 90% with 10% error rate. The classification to determine comic is good.

scholarly journals Obtaining and Use of Compost from the Organic Component of Household Waste

2021 ◽  
Vol 24 (3) ◽  
pp. 87-96
Author(s):  
Zosya Masliukova ◽  
Hennadiy Chetveryk ◽  
Anthony Neokleous ◽  
Finn Otto
Keyword(s):  
Food Waste ◽  
Crop Yields ◽  
Raw Material ◽  
Organic Component ◽  
Theoretical Research ◽  
Practical Significance ◽  
Household Waste ◽  
Industrial Processing ◽  
The Difference ◽  
Garden Waste

The relevance of the study is conditioned by the need to develop and implement technological solutions for processing food and garden waste into compost. The purpose of this study is to investigate the methods of obtaining compost from the organic component of household waste and analyse composts for compliance with the requirements for their use as fertilisers. Theoretical research on the issues of the application of an organic component of a firm household waste as a raw material for compost production is carried out. According to statistical information on the accumulation of household waste in Ukraine, the amount of food and garden waste in the regions of Ukraine has been calculated. Modern methods of industrial processing of food and garden waste into compost are analysed, and the most effective technology from the standpoint of ecology and energy saving is determined. Data on the influence of composted digestate on crop yields are given. Composts were analysed for compliance with the requirements for their use as fertilisers The data show that the difference between the content of heavy metals in the composted digestate and compost from food waste is not significant and both composts meet the German quality requirements of compost. Data on the influence of composted digestate from food waste on the growth of winter grain yields are given. It has been found that the use of composts can supplement conventional mineral fertilisers in crop cultivation. The practical significance of the study is to determine the prospects of obtaining fertiliser from the organic component of solid waste and to determine its effectiveness when applied to the soil

scholarly journals Multispectral Image under Tissue Classification Algorithm in Screening of Cervical Cancer

2022 ◽  
Vol 2022 ◽  
pp. 1-9
Author(s):  
Pei Wang ◽  
Shuwei Wang ◽  
Yuan Zhang ◽  
Xiaoyan Duan
Keyword(s):  
Cervical Cancer ◽  
Clinical Application ◽  
Sensitivity And Specificity ◽  
Statistical Difference ◽  
Multispectral Imaging ◽  
Classification Algorithm ◽  
Multispectral Image ◽  
Multispectral Images ◽  
Tissue Classification ◽  
The Difference

The objectives of this study were to improve the efficiency and accuracy of early clinical diagnosis of cervical cancer and to explore the application of tissue classification algorithm combined with multispectral imaging in screening of cervical cancer. 50 patients with suspected cervical cancer were selected. Firstly, the multispectral imaging technology was used to collect the multispectral images of the cervical tissues of 50 patients under the conventional white light waveband, the narrowband green light waveband, and the narrowband blue light waveband. Secondly, the collected multispectral images were fused, and then the tissue classification algorithm was used to segment the diseased area according to the difference between the cervical tissues without lesions and the cervical tissues with lesions. The difference in the contrast and other characteristics of the multiband spectrum fusion image would segment the diseased area, which was compared with the results of the disease examination. The average gradient, standard deviation (SD), and image entropy were adopted to evaluate the image quality, and the sensitivity and specificity were selected to evaluate the clinical application value of discussed method. The fused spectral image was compared with the image without lesions, it was found that there was a clear difference, and the fused multispectral image showed a contrast of 0.7549, which was also higher than that before fusion (0.4716), showing statistical difference ( P < 0.05 ). The average gradient, SD, and image entropy of the multispectral image assisted by the tissue classification algorithm were 2.0765, 65.2579, and 4.974, respectively, showing statistical difference ( P < 0.05 ). Compared with the three reported indicators, the values of the algorithm in this study were higher. The sensitivity and specificity of the multispectral image with the tissue classification algorithm were 85.3% and 70.8%, respectively, which were both greater than those of the image without the algorithm. It showed that the multispectral image assisted by tissue classification algorithm can effectively screen the cervical cancer and can quickly, efficiently, and safely segment the cervical tissue from the lesion area and the nonlesion area. The segmentation result was the same as that of the doctor's disease examination, indicating that it showed high clinical application value. This provided an effective reference for the clinical application of multispectral imaging technology assisted by tissue classification algorithm in the early screening and diagnosis of cervical cancer.

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