Generating adversarial images to monitor the training state of a CNN model

Deep neural networks have shown effectiveness in many applications, however, in regulated applications like automotive or medicine, quality guarantees are required. Thus, it is important to understand the robustness of the solutions to perturbations in the input space. In order to identify the vulnerability of a trained classification model and evaluate the effect of different perturbations in the input on the output class, two different methods to generate adversarial examples were implemented. The adversarial images created were developed into a robustness index to monitor the training state and safety of a convolutional neural network model. In the future work, some generated adversarial images will be included into the training phase to improve the model robustness.

Information and analytical work in the state and municipal administration

The features of information and analytical work in the state and municipal administration bodies of the Russian Federation are revealed. It is shown how the political and managerial process (the cycle of political decision-making) is interconnected with the process of information and analytical activity. Examples of analytical solutions to complex management tasks are given. Meets the requirements of the federal state educational standards of higher education of the latest generation. For students studying in the areas of training "State and municipal management", "Conflictology", "Documentation and archival science". It can be useful for practicing analysts, state and municipal employees.

Legal instruction in the framework of social education of Student Youth

Analyzed is the need to address issues of legal awareness of young people in the framework of their social support. The aim of this article is to conduct a study in problems, needs and interests of youth in the field of law among students of the Kurgan branch of the Russian Academy of National Economy and State Service in direction of training “State and Municipal Administration”. The study served as the basis for development of the project “The Right to Know Law”, which can help to attract the attention of students to the study of the legislation of the Russian Federation, dissemination of legal knowledge. Research methodology: questioning; social design. The questionnaire survey allowed the authors to find out that students have a low level of legal culture, weak legal protection. Based on the study, the authors prepared for implementation the project “The Right to Know the Law”, which include activities aimed at legal education of students. The article describes a social project, the aim of which is to organize and conduct a set of measures for the legal education of youth for students of the Kurgan branch of the Russian Academy of National Economy and the State Service in the direction of training “State and Municipal Administration”. Participants in the “Right to Know Law” project will acquire knowledge in the field of constitutional law, civil law, historical moments of the origin of law, heraldry, vexillology and hymnography, labor relations. The authors of the article believe that their proposed work on legal education helps to reduce social tension in society and increase legal culture, legal awareness of young people.

Errors Behind Asking Open-Ended Questions: A Study in Individual Counseling Class

<p style="text-align: justify;"><em>The skill of asking open-ended questions is one of the most important skills in counseling. </em><em>Asking the right questions may help a counselor to understand the counselee's situation. This study aims to reveal the errors in asking open-ended questions during the implementation of individual counseling conducted by 27 fourth-semester students of the Guidance and Counseling Study Program, Faculty of Tarbiyah and Teaching Training, State Islamic Institute (IAIN) Bukittinggi. The research was conducted through a quantitative approach. This research found that there were some common errors made by students when using open-ended questions; they were 1) 70.37% of students used open-ended questions that were not coherent, 2) 66% of students used open-ended questions “why” in their question, 3) 40.74% used repeated open-ended questions that have the same meaning, 4) 29.62% used open-ended questions that did not in line with the context, 5) 14.81% students used open-tailed questions, 6) 11.11% students used 2 open-ended questions simultaneously at the same time, and 7) there were 11.11% who did not use open-ended questions at all during the counseling process</em></p><div><em><br /></em></div><div><p style="text-align: justify;">Bertanya adalah salah satu keterampilan yang paling penting dalam proses konseling. Pengajuan pertanyaan-pertanyaan yang tepat dapat membantu konselor memahami situasi konseli, alasan konseli menemui konselor, harapan-harapan konseli, dan informasi-informasi yang relevan dengan situasi yang dihadapi oleh konseli saat itu. Keterampilan menggunakan pertanyaan terbuka merupakan salah satu dari keterampilan bertanya yang penting tersebut. Penelitian ini berupaya mengungkapkan pertanyaan-pertanyaan terbuka yang digunakan oleh 27 orang mahasiswa semester IV Program Studi Bimbingan dan Konseling Institut Agama Islam Negeri Bukittinggi dalam pelaksanaan konseling individual. Secara spesifik penelitian ini bertujuan untuk mengungkapkan kesalahan-kesalahan penggunaan pertanyaan terbuka dalam konseling individual yang dilakukan oleh mahasiswa. Penelitian dilakukan melalui pendekatan kuantitatif. Melalui penelitian ini diperoleh informasi bahwa, terdapat beberapa kesalahan umum yang dilakukan mahasiswa pada saat menggunakan pertanyaan terbuka yaitu 1) 70,37% mahasiswa menggunakan pertanyaan terbuka yang tidak runtut, 2) 66% mahasiswa menggunakan pertanyaan terbuka dengan kata tanya mengapa, 3) 40,74% menggunakan pertanyaan terbuka yang berulang dengan makna sama, 4) 29,62 % menggunakan pertanyaan terbuka yang tidak sesuai konteks, 5) 14,81% mahasiswa menggunakan pertanyaan terbuka mengekor, 6) 11,11% mahasiswa menggunakan sekaligus 2 pertanyaan terbuka dalam waktu yang sama, dan 7) terdapat 11,11 persen yang sama sekali tidak menggunakan pertanyaan terbuka selama proses konseling.</p></div>

Al-Kafa’ah al-Ta‘līmiyyah Laday Mu‘allimiy al-Lughah al-‘Arabiyyah wa Atharuhā ‘ala Natā’ij Ta‘allum al-Ṭalabah al-Jāmi‘ah

<p class="ABSTRACT">This study aims to discuss the correlation between pedagogic competence of lecturer of Arabic language especially lecturer who tries competence of language material with student learning result in Arabic language departement, Faculty of Education and Teacher Training, State Islamic University Maulana Malik Ibrahim Malang. In this study researchers used a quantitative approach and this type of research is descriptive and correlation. Instruments used in data collection are interviews, observations, questionnaires and documents. The result of the research is pedagogic competence of lecturer of language competence which includes on the ability of learning method development, implementation in learning process and implementation of evaluation is in good and based on the data analysis that has been done by the researcher showed that the condition of pedagogic competence of lecturer of language competence influence the student learning result, it is based on result of t test which amounted to 9,548 with result of sig 0,000 and t value (9,548)&gt; t table (); it can be concluded that ho is rejected and ha is accepted.<strong></strong></p>

Research and Analysis of Sports Training Real-Time Monitoring System Based on Mobile Artificial Intelligence Terminal

With the rapid development of artificial intelligence, related technologies and applications come into being, and industries based on artificial intelligence are booming, among which image recognition and target tracking technologies are widely used in various fields, especially in the fields of security monitoring and augmented reality. In this paper, combined with the characteristics of athletes, based on mobile artificial intelligence terminal technology, the C/S mode of athlete training process monitoring system is developed and designed, which uses GPS to obtain the real-time position information of athletes and provide real-time guidance for athletes. In order to reveal the changing rules of various indexes of athletes in training state, the author makes synchronous tracking analysis from the aspects of individual sports function characteristics of athletes, training plan arrangement of coaches, brain function state, routine physiological and biochemical indexes, nutrition regulation, and injury conditions.

Impact of using modern technology in training on sports performance

Introduction: The close relationship between technology and sports is not necessarily modern. The ancient Greeks had the idea of sculpting and making an extraordinarily aerodynamic object in the form of a disc, an early masterpiece that has remained largely unchanged to this day.Purpose: This paper aims to show the importance of monitoring training using technological tools, so as to result in a beneficial effect on athletes.Materials and methods: In order to carry out this research, 32 athletes, boxing practitioners for at least two years, and with at least one year of preparation for participating in domestic and international competitions, were selected. Subjects were divided into two groups, one that was subjected to research (experimental) composed of 12 athletes aged 15 to 18 years, and the other composed of 20 athletes aged between 15 and 18 years.Results: The average scores for the four parameters of the experiment group (N= 12) (Forced expiratory volume in one second (FEV1), M = 6.95, AS = 0.53; peak expiratory flow (PEF) M = 9.43, AS = 1.35; Right direct punch (MYO_DRP) M = 588.33, AS = 181.94; respectively the left direct punch (MYO_STG) M = 546.75, AS = 136.82) were significantly higher than those of the control group (N=20) (FEV, M = 5.46, AS = 1.22; PEF M = 7.33, AS = 1.43; MYO_DRP M = 426.55, AS = 151.68; MYO_STG M = 406.50, AS = 139.13, respectively).Conclusions: Based on the analysed data, we can say that our hypothesis that continuous implementation and monitoring of training plans using technological means will lead to the improvement of the indices pursued in the research, is confirmed. Thus, the group that underwent a training regime using certain technological tools recorded significantly higher values at the end of the programme in comparison with the control group. However, we could see that the use of devices during training, which require them to be fitted every time on the athlete, leads to an extension of training duration and takes the athlete out of the training state. To remove this shortcoming it would be useful to integrate these equipments into a system that incorporates them all.

Improving Neural Machine Translation by Filtering Synthetic Parallel Data

Synthetic data has been shown to be effective in training state-of-the-art neural machine translation (NMT) systems. Because the synthetic data is often generated by back-translating monolingual data from the target language into the source language, it potentially contains a lot of noise—weakly paired sentences or translation errors. In this paper, we propose a novel approach to filter this noise from synthetic data. For each sentence pair of the synthetic data, we compute a semantic similarity score using bilingual word embeddings. By selecting sentence pairs according to these scores, we obtain better synthetic parallel data. Experimental results on the IWSLT 2017 Korean→English translation task show that despite using much less data, our method outperforms the baseline NMT system with back-translation by up to 0.72 and 0.62 Bleu points for tst2016 and tst2017, respectively.

Interpreting chest X-rays via CNNs that exploit disease dependencies and uncertainty labels

Chest radiography is one of the most common types of diagnostic radiology exams, which is critical for screening and diagnosis of many different thoracic diseases. Specialized algorithms have been developed to detect several specific pathologies such as lung nodule or lung cancer. However, accurately detecting the presence of multiple diseases from chest X-rays (CXRs) is still a challenging task. This paper presents a supervised multi-label classification framework based on deep convolutional neural networks (CNNs) for predicting the risk of 14 common thoracic diseases. We tackle this problem by training state-of-the-art CNNs that exploit dependencies among abnormality labels. We also propose to use the label smoothing technique for a better handling of uncertain samples, which occupy a significant portion of almost every CXR dataset. Our model is trained on over 200,000 CXRs of the recently released CheXpert dataset and achieves a mean area under the curve (AUC) of 0.940 in predicting 5 selected pathologies from the validation set. This is the highest AUC score yet reported to date. The proposed method is also evaluated on the independent test set of the CheXpert competition, which is composed of 500 CXR studies annotated by a panel of 5 experienced radiologists. The performance is on average better than 2.6 out of 3 other individual radiologists with a mean AUC of 0.930, which ranks first on the CheXpert leaderboard at the time of writing this paper.