The work is devoted to solving the current scientific and technical problem of constructing a diagnostic decision support system in medicine based on a heterogeneous ensemble classifier model that implements two appro...
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ISBN:
(数字)9798350384499
ISBN:
(纸本)9798350384505
The work is devoted to solving the current scientific and technical problem of constructing a diagnostic decision support system in medicine based on a heterogeneous ensemble classifier model that implements two approaches to formulating a diagnostic conclusion: a probabilistic one based on the analysis of the training sample, and expert information on the structure of symptom complexes. The choice of prototype matching method as a probabilistic component is justified. Formalization of expert information on the structure of symptom complexes was carried out by representing symptom complexes of diseases with numerical intervals of linguistic variables. Options for taking into account expert assessments about the structure of symptom complexes in an ensemble classifier are considered. Test verification of the developed classifier was done on real medical data and confirmed the effectiveness of its work.
Fairness concern behavior, a well-known cognitive bias, refers to a person’s attitude of dissatisfaction for unequal pay-offs in someone’s favor. Against environmental pollution, many firms are focused on green manu...
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We investigated the process of unsupervised generative learning and the structure of informative generative representations of images of handwritten digits (MNIST dataset). Learning models with the architecture of spa...
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Because of the increased market opening and massive data collection brought about by globalization, the need of maintaining control over customs procedures has increased. However, the integration and processing of cus...
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BackgroundThis is the first study to report both cortical and trabecular bone evaluation of mandibles in bruxers, within the knowledge of the authors. The purpose of this study was to evaluate the effects of bruxism o...
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BackgroundThis is the first study to report both cortical and trabecular bone evaluation of mandibles in bruxers, within the knowledge of the authors. The purpose of this study was to evaluate the effects of bruxism on both the cortical and the trabecular bone in antegonial and gonial regions of the mandible, which is the attachment of the masticatory muscles, by using panoramic radiographic *** this study, the data of 65 bruxer (31 female, 34 male) and 71 non-bruxer (37 female, 34 male) young adult patients (20-30 years) were evaluated. Antegonial Notch Depth (AND), Antegonial-Index (AI), Gonial-Index, Fractal Dimension (FD) and Bone Peaks (BP) were evaluated on panoramic radiographic images. The effects of the bruxism, gender and side factors were investigated according to these findings. The statistical significance level was set atP & LE;*** mean AND of bruxers (2.03 & PLUSMN;0.91) was significantly higher than non-bruxers (1.57 & PLUSMN;0.71;P < 0.001). The mean AND of males was significantly higher than females on both sides (P < 0.05). The mean AI of bruxers (2.95 & PLUSMN;0.50) was significantly higher than non-bruxers (2.77 & PLUSMN;0.43;P = 0.019). The mean FD on each side was significantly lower in bruxers than in non-bruxers (P < 0.05). The mean FD of males (1.39 & PLUSMN;0.06) was significantly higher than females (1.37 & PLUSMN;0.06;P = 0.049). BP were observed in 72.5% of bruxers and 27.5% of non-bruxers. The probability of existing BP, in bruxers was approximately 3.4 times higher than in non-bruxers (P = 0.003), in males was approximately 5.5 times higher than in females (P < 0.001).ConclusionAccording to the findings of this study, the morphological differences seen in cortical and trabecular bone in the antegonial and gonial regions of the mandible in bruxers can be emphasized as deeper AND, higher AI, increased of existing BPs, and lower FD, respectively. The appearance of these morphological changes on radiographs may be
A rising variety of platforms and software programs have leveraged repository-stored datasets and remote access in recent years. As a result, datasets are more vulnerable to malicious attacks. As a result, network sec...
A rising variety of platforms and software programs have leveraged repository-stored datasets and remote access in recent years. As a result, datasets are more vulnerable to malicious attacks. As a result, network security has grown in importance as a research topic. The usage of intrusion detection systems is a well-known strategy for safeguarding computer networks. This paper proposes an anomaly detection method that blends rule-based and machine-learning-based methods. In order to construct the appropriate rules, a genetic algorithm is utilized. Principal component analysis is used to extract the relevant features aimed to improve the performance. The suggested method is validated experimentally using the KDD Cup 1999 dataset, which meets the requirement of using appropriate data. The proposed method is applied to detect and analyze four types of attacks in a well-known benchmark dataset: Neptune, Ipsweep, Pod, and Teardrop, utilizing Support Vector Machine, Decision Tree, and Naive Bayes algorithms. After testing the characteristics specified in the training phase, the data is classified into attack categories and normal behavior during the machine learning phase.
An approach for automated knowledge extraction and decision-making from medical images through a workflow for preprocessing of incoming X-ray images, analysis, classification and evaluation of the results is presented...
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The subject of the study is methods of balancing raw data. The purpose of the article is to improve the quality of intrusion detection in computer networks by using class balancing methods. Task: to investigate method...
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Selecting the most relevant subset of features from a dataset is a vital step in data mining and machine *** feature in a dataset has 2n possible subsets,making it challenging to select the optimum collection of featu...
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Selecting the most relevant subset of features from a dataset is a vital step in data mining and machine *** feature in a dataset has 2n possible subsets,making it challenging to select the optimum collection of features using typical *** a result,a new metaheuristicsbased feature selection method based on the dipper-throated and grey-wolf optimization(DTO-GW)algorithms has been developed in this *** can result when the selection of features is subject to metaheuristics,which can lead to a wide range of ***,we adopted hybrid optimization in our method of optimizing,which allowed us to better balance exploration and harvesting chores more *** propose utilizing the binary DTO-GW search approach we previously devised for selecting the optimal subset of *** the proposed method,the number of features selected is minimized,while classification accuracy is *** test the proposed method’s performance against eleven other state-of-theart approaches,eight datasets from the UCI repository were used,such as binary grey wolf search(bGWO),binary hybrid grey wolf,and particle swarm optimization(bGWO-PSO),bPSO,binary stochastic fractal search(bSFS),binary whale optimization algorithm(bWOA),binary modified grey wolf optimization(bMGWO),binary multiverse optimization(bMVO),binary bowerbird optimization(bSBO),binary hysteresis optimization(bHy),and binary hysteresis optimization(bHWO).The suggested method is superior 4532 CMC,2023,vol.74,no.2 and successful in handling the problem of feature selection,according to the results of the experiments.
We explore a continuous aggregated dynamic model for developing two gas fields. The new borehole commissioning rates are the control parameters. Changes in the average flow rate of producing boreholes and current natu...
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ISBN:
(数字)9798350375718
ISBN:
(纸本)9798350375725
We explore a continuous aggregated dynamic model for developing two gas fields. The new borehole commissioning rates are the control parameters. Changes in the average flow rate of producing boreholes and current natural gas production are proportional. It is necessary to solve the problem of maximizing discounted accumulated income for two gas fields. We analyze the optimal control problem with an unrestricted right end and a fixed time. The Pontryagin maximum principle is a main tool for solving the problem. The special optimal control mode is of particular interest. We highlight the critical aspects of all possible optimal controls.
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