Essence of Upbringing Process and the Competence Approach in Training

Research relevance: understanding of teaching concept related to main function of а teacher in teaching and educating students. In the learning process, teacher should pay special attention to students’ cognitive activity development and try to use it more in learning process, using innovative technologies and interactive methods. Research objectives: consider issues from the concept of teaching, “learning” and “competence” and their essence, to reveal the importance of the competence-based approach in teaching. Research materials and methods: article analyzes essence of learning process and authors give their point of view. Research results: educational process essence and importance of learning based on modern competencies revealed. Conclusions: learning competence includes set of a student’s educational achievements, expressed by level of basic and subject competence at a certain stage in educational process.

Research on a Convolution Kernel Initialization Method for Speeding Up the Convergence of CNN

This paper presents a convolution kernel initialization method based on the local binary patterns (LBP) algorithm and sparse autoencoder. This method can be applied to the initialization of the convolution kernel in the convolutional neural network (CNN). The main function of the convolution kernel is to extract the local pattern of the image by template matching as the target feature of subsequent image recognition. In general, the Xavier initialization method and the He initialization method are used to initialize the convolution kernel. In this paper, firstly, some typical sample images were selected from the training set, and the LBP algorithm was applied to extract the texture information of the typical sample images. Then, the texture information was divided into several small blocks, and these blocks were input into the sparse autoencoder (SAE) for pre-training. After finishing the training, the weight values of the sparse autoencoder that met the statistical features of the data set were used as the initial value of the convolution kernel in the CNN. The experimental result indicates that the method proposed in this paper can speed up the convergence of the network in the network training process and improve the recognition rate of the network to an extent.

The Optimization Analysis of Phishing Email Filtering in Network Fraud based on Improved Bayesian Algorithm

Mail transmission was not only the main function of information system, but also the main way of network virus and Trojan horse transmission, which has a key impact on the running state of information. In order to deal with the threats of network viruses and Trojans and improve the level of e-mail management, this paper studies the filtering of information system, and proposes a phishing e-mail filtering method based on Improved Bayesian model. MATLAB simulation results show that the consistency p between the amount of data sent by e-mail and the amount received is good, the consistency rate reached 92.3%. the data security level is 95%, encryption proportion / data proportion ratio under Bayesian optimization are higher than those of unfiltered method，which up to 97.2%. Therefore, the Bayesian optimization model constructed in this paper can meet the needs of phishing email filtering in information communication at this stage.

STUDI EMPIRIS TENTANG PENGAWASAN KERJA, PENGALAMAN KERJA, DAN KEMAMPUAN KERJA SERTA PENGARUHNYA TERHADAP MOTIVASI BERPRESTASI KARYAWAN

Human assets as one of the elements of manufacturing are the riding pressure of each organisation. They have a main function in understanding the organisation's goals. Companies ought to constantly inspire them to offer the excellent paintings effects in order that organisation sports aren't hampered consistent with their workload and responsibilities. Good paintings effects are primarily based totally at the lifestyles of a cause for fulfillment and there are numerous variables that have effect on this. This studies targets to research and decide the impact of labor supervision, paintings revel in, and paintings cappotential on fulfillment motivation. This quantitative studies takes the populace targeted on personnel who paintings withinside the manufacturing phase of a multinational organisation in Sidoarjo. Respondents on this observe have been a hundred and twenty respondents. The analytical device used, particularly SPSS model 25 program. The sampling method on this observe the usage of purposive sampling method. The analytical device used is more than one linear regression analysis. The effects confirmed that each one hypotheses have been demonstrated correct. Work supervision has a massive effective impact on fulfillment motivation. Work revel in and paintings cappotential even have a massive have effect on fulfillment motivation. The 3 of them offer a massive impact concurrently on fulfillment motivation. Keywords: job supervision, work experience, work ability, achievement motivation.

Non-hormonal options for the relief of menopausal disorders

Woman’s nature is unique. Taking into account some historical milestones, it can be noted that the role of women in society has undergone large-scale changes. The woman took a confident position in society. Its main function remains unchanged and it consists in procreation and procreation. A woman’s activity is consistent with the work of her reproductive system (RS). The gradual decrease, and then the cessation of the work of the ovaries, contributes to the life order and health of the fair sex. Menopause is a natural stage in a woman’s life, which corresponds to the peak of social self-realization. However, in some cases, hormonal changes characteristic of this period can serve as a favorable background for the formation of a number of pathological changes. The growing estrogen deficiency is becoming a pathogenetic impetus for the development of a wide range of climacteric disorders. Vasomotor symptoms and hyperhidrosis are the most frequent companions of women during the perimenopausal transition and early postmenopause. Maintaining optimal activity and the full quality of life of patients should be the goal of correcting the negative manifestations of estrogen deficiency and the complications associated with it. Compensating for estrogen deficiency with menopausal hormone therapy (HRT) is the benchmark for menopausal problems. However, there are a number of patients who have contraindications to prescribing HRT or who refuse to receive it for some reason. For this category of patients, alternative methods of diet correction. Combinations of plant extracts with vitamins and minerals have been successfully used in clinical practice for a long time. The article will provide information on the most studied phytoestrogens contained in soy.

Adipocyte Utx Deficiency Promotes High-Fat Diet-Induced Metabolic Dysfunction in Mice

While the main function of white adipose tissue (WAT) is to store surplus of energy as triacylglycerol, that of brown adipose tissue (BAT) is to burn energy as heat. Epigenetic mechanisms participate prominently in both WAT and BAT energy metabolism. We previously reported that the histone demethylase ubiquitously transcribed tetratricopeptide (Utx) is a positive regulator of brown adipocyte thermogenesis. Here, we aimed to investigate whether Utx also regulates WAT metabolism in vivo. We generated a mouse model with Utx deficiency in adipocytes (AUTXKO). AUTXKO animals fed a chow diet had higher body weight, more fat mass and impaired glucose tolerance. AUTXKO mice also exhibited cold intolerance with an impaired brown fat thermogenic program. When challenged with high-fat diet (HFD), AUTXKO mice displayed adipose dysfunction featured by suppressed lipogenic pathways, exacerbated inflammation and fibrosis with less fat storage in adipose tissues and more lipid storage in the liver; as a result, AUTXKO mice showed a disturbance in whole body glucose homeostasis and hepatic steatosis. Our data demonstrate that Utx deficiency in adipocytes limits adipose tissue expansion under HFD challenge and induces metabolic dysfunction via adipose tissue remodeling. We conclude that adipocyte Utx is a key regulator of systemic metabolic homeostasis.

Voluntary Behavior and Training Conditions Modulate in vivo Extracellular Glucose and Lactate in the Mouse Primary Motor Cortex

Learning or performing new behaviors requires significant neuronal signaling and is metabolically demanding. The metabolic cost of performing a behavior is mitigated by exposure and practice which result in diminished signaling and metabolic requirements. We examined the impact of novel and habituated wheel running, as well as effortful behaviors on the modulation of extracellular glucose and lactate using biosensors inserted in the primary motor cortex of mice. We found that motor behaviors produce increases in extracellular lactate and decreases in extracellular glucose in the primary motor cortex. These effects were modulated by experience, novelty and intensity of the behavior. The increase in extracellular lactate appears to be strongly associated with novelty of a behavior as well as the difficulty of performing a behavior. Our observations are consistent with the view that a main function of aerobic glycolysis is not to fuel the current neuronal activity but to sustain new bio-infrastructure as learning changes neural networks, chiefly through the shuttling of glucose derived carbons into the pentose phosphate pathway for the biosynthesis of nucleotides.

Social media as a bridge to e-commerce adoption in Indonesia: A research framework for repurchase intention

Consumers today are individuals who fulfill life needs such as shopping using e-commerce. In its fulfillment, consumers can change in terms of purchasing decisions from one e-commerce to another e-commerce. This requires the company to always have a good strategy to compete in a healthy manner in terms of business. To learn about the importance of social media marketing activity, this study will find out how much influence the social media marketing activity received by e-commerce companies has on brand equity, customer relationships and repurchase intention. In addition, the study will learn how much influence brand equity and customer relationship have on an e-commerce company's repurchase intention. In this study, the survey is conducted by distributing questionnaires to respondents online where the research sample has several questions related to the habits and behavior of respondents. This research uses a sample of 210 people who are domiciled in Indonesia. In the research model, the study uses Structural Equation Modeling (SEM) analysis and the software used for this research is IBM SPSS AMOS. The results of the influence of social media marketing activities have the largest positive influence on customer relationships, brand equity is the main and biggest factor that positively and significantly affects repurchase intention in this research model. The accumulated experience and knowledge of consumers about a brand is a factor that can influence consumers to repurchase the same brand. Brand equity not only provides immediate benefits, but also long-term benefits by retaining consumers to continue to repurchase their products. A strong brand will make consumers always remember the brand. The study explains that customer relationships do not have any significant effect on repurchase intention. The main function of customer relationships at first and now is to try to reach their consumers more broadly, especially related to purchases, but this is not proven in repurchases, especially in this study. Customer relationships in the study did not have any significant effect on repurchase intention.

High intensity proton beam impact at 440 GeV/c on Mo and Cu coated CfC/graphite and SiC/SiC absorbers for beam intercepting devices

Beam Intercepting Devices (BIDs) are essential protection elements for the operation of the Large Hadron Collider (LHC) complex. The LHC internal beam dump (LHC Target Dump Injection or LHC TDI) is the main protection BID of the LHC injection system; its main function is to protect LHC equipment in the event of a malfunction of the injection kicker magnets during beam transfer from the SPS to the LHC. Several issues with the TDI were encountered during LHC operation, most of them due to outgassing from its core components induced by electron cloud effects, which led to limitations of the injector intensity and hence had an impact on LHC availability. The absorbing cores of the TDIs, and of beam intercepting devices in general, need to deal with high thermo-mechanical loads induced by the high intensity particle beams. In addition, devices such as the TDI — where the absorbing materials are installed close to the beam, are important contributors to the accelerator impedance budget. To reduce impedance, the absorbing materials that make up the core must be typically coated with high electrical conductivity metals. Beam impact testing of the coated absorbers is a crucial element of development work to ensure their correct operation. In the work covered by this paper, the behaviour of several metal-coated absorber materials was investigated when exposed to high intensity and high energy proton beams in the HiRadMat facility at CERN. Different coating configurations based on copper and molybdenum, and absorbing materials such as isostatic graphite, Carbon Fibre Composite (CfC) and Silicon Carbide reinforced with Silicon Carbide fibres (SiC-SiC), were tested in the facility to assess the TDI's performance and to extract information for other BIDs using these materials. In addition to beam impact tests and an extensive Post Irradiation Examination (PIE) campaign to assess the performance of the coatings and the structural integrity of the substrates, extensive numerical simulations were carried out.

Attention graph: Learning effective visual features for large-scale image classification

In recent years, the research of deep learning has received extensive attention, and many breakthroughs have been made in various fields. On this basis, a neural network with the attention mechanism has become a research hotspot. In this paper, we try to solve the image classification task by implementing channel and spatial attention mechanism which improve the expression ability of neural network model. Different from previous studies, we propose an attention module consisting of channel attention module (CAM) and spatial attention module (SAM). The proposed module derives attention graphs from channel dimension and spatial dimension respectively, then the input features are selectively learned according to the importance of the features. Besides, this module is lightweight and can be easily integrated into image classification algorithms. In the experiment, we combine the deep residual network model with the attention module and the experimental results show that the proposed method brings higher image classification accuracy. The channel attention module adds weight to the signals on different convolution channels to represent the correlation. For different channels, the higher the weight, the higher the correlation which required more attention. The main function of spatial attention is to capture the most informative part in the local feature graph, which is a supplement to channel attention. We evaluate our proposed module based on the ImageNet-1K and Cifar-100 respectively. Through a large number of comparative experiments, our proposed model achieved outstanding performance.