Earticle

본 논고는 불교철학의 유식학에서 해명하고 있는 언어와 의식 작용과 의 관계성 및 이를 통해 파악할 수 있는 언어의 본질에 대한 이해가 우리 자신의 사람됨에 미치는 영향을 자기 교육의 관점에서 고찰한 것이다. 이를 위해 다룬 주요 내용은 다음과 같다. 첫째, 우리가 어떤 대상사물을 이해한다는 것은 의식이 그 대상을 지향함으로써 가능한 것인데, 이 때 지향된 그 대상사물이 존재할 수 있는 것은 언어를 자신의 존재 바탕으로 삼아 가능한 것임을 논고하였다. 이로써 대상사물은 의식 내재적인 것임과 아울러, 언어는 인간의 존재방식으로서 사람됨과 밀접한 관련이 있음을 이해할 수 있었다. 둘째, 이러한 언어의 본질에 대한 이해는 현재 자신의 사유를 가능케 하는 언어적 영향력과 의식과의 관계에 대해 성찰할 수 있게 하고, 이러한 성찰은 자신의 사유를 언어적 집착으로 부터의 자유롭게 할 수 있는 자기 교육적 효과가 있음을 논고하였다. 아울러 자신의 사람됨을 새로이 구성할 수 있는 계기가 될 수 있음을 고찰 하였다. 이와 같이 언어의 본질에 대한 이해는 우리의 사람됨을 새로이 구성할 수 있는 계기가 될 수 있다는 점에서 자기 교육을 위한 핵심적인 교육적 과제인 것이다.

The aim of this study was to explore self-learning by our own understanding language which was perceived through understanding relativity between language and consciousness to the doctrine of Consciousness-only. This study was scrutinized in the following sections. First, Paratantrasvabhava(依他性, nature of dependence on others) which is a function of consciousness as well as the basic ground to create language, Parikalpitasvabhava(分別性, nature of mere-imagination) which is presented phenomena as language, and Parinispannasvabhava(眞實性, nature of ultimate reality) which is language as bup_kay(法界) were discussed. Second, It was discussed that understanding the relativity between language and consciousness made us to think about the essence of language. In addition, the understanding of language could be a crucial method to constitute our-mind discussed as well. Third, it was discussed that our understanding about the essence of language has some important meaning in education, as a kind of authentic character of self-learning.

본 연구는 『논어』속에 나타나고 있는 윤리성과 윤리적 리더십을 교사의 평생 학습적 측면에서 고찰하였다. 존경받는 교사가 되기 위해서 갖추어야 할 윤리성과 도덕성을『논어』를 통해 고찰하고 존경받는 교사상을 정립하고자 하였다. 따라서 본 연구의 목적은 『논어』속에 나타나고 있는 평생학습 실천에 관한 공자의 가르침에 대해 살펴보고, 평생학습 실천자로서의 윤리적 리더십을 갖춘 이상적인 교사상을 정립하기 위함이다. 교사란 무엇을 해야 하며, 어떠해야 하는가? 에 대한 해답을 찾기 위해서 다음과 같은 연구문제를 설정하였다. 첫째, 윤리와 윤리적 리더십은 무엇인가? 둘째,『논어』속에 나타나고 있는 교사의 윤리적 리더십은 무엇인가? 셋째,『논어』를 통해 본 평생학습실천적 의미에서 이상적인 교사상은 어떤 모습인가? 『논어』에 비추어 본 이상적인 교사는 자기성찰과 자기학습에 몰두하고 학생들을 이해하고 배려하며, 학생들에게 올바른 태도를 보여주면서 학생들의 행동과 생각에 새로운 변화를 유도하는 사람이다. 본 연구가 가지는 의의는 공자가 지향하는 올바른 교육적 인간상인 ‘군자상’을 바탕으로『논어』속에 나타나는 윤리적 리더 교사로서의 행동 특성과 자질특성을 추출하여 현대사회에서 실천할 수 있는 교사의 윤리적 리더십을 정립하고 학생들이 평생학습을 실천함에 있어서 동일시 대상이 될 수 있는 교사의 평생학습 실천을 돕는데 있다.

This study was examined to research ideal teachers' ethics and ethical leadership from practical perspectives of lifelong learning through the lens of the Analects of Confucius. This research tried to define the concept of teachers' ethical leadership, by examining contemplated, derived ethics and moralities that teachers have to be a respected teacher focused on the Analects of Confucius. Therefore, the purpose of this study is to explore the teachings of Confucius on practices of lifelong learning and to found the ideal, ethical leader-teacher as a practical-minded person. I established the following questions to seek the answers about what teacher should do and who he or she is as a revered person. First, what are ethics and ethical leadership? Second, what is teachers‘ ethical leadership shown and surveyed in the Analects of Confucius? Third, what is an ideal teacher through the lens of the Analects of Confucius from perspectives from practical meanings of lifelong learning? The ideal teacher shown in the Analects of Confucius is a person that can concentrate on self-examination and self-learning and understand and care for his or her students and lead their ideas and behaviors to new changes by showing them a right and correct attitude. The two significances of this study are to construct teachers' ethical leadership to be practicable, feasible in our modern society and help school teachers to put lifelong learning into practice in order to be objects of student's target identification, by extracting from the Analects of Confucius his or her behavior and qualification features as a leader-teacher, centered on 'Gunja Sang' or ‘a saint's image' that Confucius supports and aims for.

With the increasing sophistication of cyber threats, traditional Intrusion Detection Systems (IDS) often fail to adapt to evolving attack patterns, leading to high false positive rates and inadequate detection of zero-day attacks. This study proposes the Deep Q-Learning Intrusion Detection System (DQ-IDS), a novel reinforcement learning (RL)-based approach designed to dynamically learn network attack behaviors and continuously enhance detection performance. Unlike conventional machine learning (ML) and deep learning (DL)-based IDS models that depend on static, pre-trained classifiers, DQ-IDS employs Deep Q-Networks (DQN) with experience replay and adaptive ε-greedy exploration to autonomously classify benign and malicious network traffic. The integration of experience replay mitigates catastrophic forgetting, while adaptive exploration ensures an optimal trade-off between learning efficiency and threat detection. A reward-driven training mechanism reinforces correct classifications and penalizes errors, thereby reducing both false positive and false negative rates. Extensive empirical evaluations on real-world network datasets demonstrate that DQ-IDS achieves a detection accuracy of 97.18%, significantly outperforming conventional IDS solutions in both attack detection and computational efficiency. This work introduces a paradigm shift toward adaptive, self-learning cybersecurity systems capable of real-time, robust threat mitigation in dynamic network environments.

디지털콘텐츠 산업의 핵심 요소인 게임·애니메이션·영상은 그 수요의 확대에 따라 관련 인력 양성이 갈수록 전문화되고 있다. 게임·애니메이션·영상 분야의 교육은 창의적 사고와 융합적 태도 그리고 문제해결 능력이 중요시 되는 창의 융합 참여형 인재양성에 있다. 이에 본 논문은 게임·애니메이션·영상 분야 창의융합 참여형 인재 양성을 위한 프리 프러덕션 중심의 PBSL(Project based Self Learning) 수업모형을 제시하고자 한다. 이를 위한 연구의 전개는 창의 융합 인재의 구성요소와 프로젝트 수업의 특성, 그리고 관련 직무 역량에 대해 문헌을 중심으로 고찰하였으며, 이에 따른 PBSL수업모형의 핵심요소는 창의성, 융합적 태도, 자율성으로 분류 하였다. 이를 기초하여, 창의적 사고와 융합적 태도 그리고, 학생들의 자율성이 실현될 수 있는 프로젝트 형의 ‘Project Based Self Learning’ 수업모형을 개발한다. PBSL을 적용한 D대학교 <콘텐츠워크샾> 수업에 대해 사례분석하고, 설문조사를 진행한 결과 자율성 측면이 창의성과 융합적 태도에 비해 만족도가 높게 나왔으며, 이는, 학생 스스로 프로젝트 진행에 대한 자율성과 동기부여가 향상되었음 을 알 수 있다. 다만, 만족도가 낮게 분석된 융합적 측면에 대한 추후 보완이 필요하다.

Key areas of digital contents, the games and animation industries are increasingly expanding. Therefore, training of a specialized workforce is required in accordance with these enterprises’ growing demand. Education in the field of games and animation lies in cultivating talents with creative thinking, collaboration, and problem-solving skills. Thus, this paper aims to propose a PBSL teaching model for creative convergent talent through game and animation projects. The study will focus on the characteristics of creative convergence talents, project teaching, and related job competencies for game and animation education. Based on literature research, a 'Project Based Self Learning' instructional model is presented, in which creative thinking and collaboration competencies are explained in a way they can be performed by the learner. As a case study, D University’s <Content Workshop> class was applied with PBSL. A survey showed that the autonomy aspects were higher than the creativity and convergence attitudes, indicating that the students improved their autonomy and motivation. However, the team composition needs further supplementation.

The coronavirus pandemic has brought about dramatic changes in education, evidenced most clearly by the increase in e-learning. Thus, to identify how learners' attitudes toward e-learning are affected by diverse factors, this study examined the effects of perceived system quality and usefulness, the self-management of learning, and self-efficacy. A total of 236 college students participated in the survey. Multiple regression analysis was performed to test the study's proposed hypotheses. The study findings suggested that learners' attitudes toward e-learning are positively influenced by perceived e-learning usefulness, self-management of learning, and self-efficacy. However, the perceived system quality had no influence and no statistical significance.

Purpose: Competency in physical assessment is an important component of nursing practice. However, some physical assessment skills are not being utilized within the current teacher-centered, content-heavy curriculum. This study was conducted to identify the effects of student-centered, self-directed learning in the physical assessment class. Methods: An experimental study with a post-test only control group design was used to compare an intervention group that was provided self-directed learning classes and a control group that was provided traditional lecture and practice classes. Competency in physical assessment, academic self-confidence, and learning satisfaction were evaluated. Collected data were analyzed using $x^2$-test (Fisher's exact test) and independent t-test. Results: Competency in physical assessment was significantly higher in the experimental group. However, academic self-confidence and learning satisfaction were not significantly different between the groups. Conclusion: The findings in this study indicate that self-directed learning can improve nursing students competency in physical assessment and that self-directed learning is a good education method to improve nursing students' competency in physical assessment during clinical practice and perform quality patient care by making active use of physical assessment skills.

Many deep learning approaches have been studied for image classification in computer vision. However, there are not enough data to generate accurate models in medical fields, and many datasets are not annotated. This study presents a new method that can use both unlabeled and labeled data. The proposed method is applied to classify cervix images into normal versus cancerous, and we demonstrate the results. First, we use a patch self-supervised learning for training the global context of the image using an unlabeled image dataset. Second, we generate a classifier model by using the transferred knowledge from self-supervised learning. We also apply attention learning to capture the local features of the image. The combined method provides better performance than state-of-the-art approaches in accuracy and sensitivity.

The objective of this study was to analyze the influence of physical education classes based on Flipped Learning on self-directed learning abilities and learning attitude towards these classes, for middle school students. The study selected 90 students as an experimental group (3 classes) and 97 students as a control group (3 classes), among 240 students of the first-year students attending a middle school located at Jeonju City of South Korea, applying convenience sampling, one of the non-probability sampling methods. For the experimental group, 36 sessions of physical education classes were held for 14 weeks, while the control group received teacher-centered classes. Comparing the results with the control group, the experimental group showed significant differences in terms of all sub factors of self-directed learning abilities, namely; desire for learning, learning objective establishment, basic self-management abilities, selection of learning strategy and self-reflection. Moreover, the experimental group manifested significant differences in terms of all sub factors of attitude towards the physical education subjects, namely; positive emotions, negative emotions, health & physical strength, interpersonal relations, physical activities & movements, and active participation & positive performance. From the findings, it can be considered that physical education classes based on Flipped Learning contributed to improving self-directed learning abilities and attitude towards physical education classes. This result can serve as a significant basic material for designing and performing classes in raising the understanding of Flipped Learning and effectively applying Flipped Learning in physical education classes.

Purpose: The purpose of this study was to identify the effects simulation-based education combined team-based learning (SBE combined TBL) compared to simulation-based education (SBE) on undergraduate nursing students. Methods: A non-equivalent control group design with pre-and posttest measures was used. The participants in the study were 181 students. The SBE combined TBL group consisted of 84 senior students in 2013, and the SBE group consisted of 97 seniors in 2014. Collected data were analyzed using chi-square, independent t-test and ANCOVA with the statistical package SPSS 22.0 for Windows. Results: There was a significant improvement in communication skills, nursing performance confidence, team efficacy, and team performance scores in the SBE combined TBL group compared to the SBE group (t=2.45, p=.015; F=4.30, p=.040; t=3.06, p=.003; t=8.77, p<.001). However, there was no statistically significant difference in self-directed learning between the groups. Conclusion: SBE combined TBL compared to SBE is an effective teaching and learning method to enhance various positive educational outcomes for nursing students. Therefore, we suggest that future studies investigate the development of an integrated course in which team-based learning is applied to theoretical sessions and simulation-based training.

In this study, we present a novel approach for enhancing chest X-ray image classification (normal, Covid-19, edema, mass nodules, and pneumothorax) by combining contrastive learning and machine learning algorithms. A vast amount of unlabeled data was leveraged to learn representations so that data efficiency is improved as a means of addressing the limited availability of labeled data in X-ray images. Our approach involves training classification algorithms using the extracted features from a linear fine-tuned Momentum Contrast (MoCo) model. The MoCo architecture with a Resnet34, Resnet50, or Resnet101 backbone is trained to learn features from unlabeled data. Instead of only fine-tuning the linear classifier layer on the MoCopretrained model, we propose training nonlinear classifiers as substitutes for softmax in deep networks. The empirical results show that while the linear fine-tuned ImageNet-pretrained models achieved the highest accuracy of only 82.9% and the linear fine-tuned MoCo-pretrained models an increased highest accuracy of 84.8%, our proposed method offered a significant improvement and achieved the highest accuracy of 87.9%.

Purpose: Nursing students' competence in virtual simulation-based learning is a key factor in its success. This study explored the validity and reliability of a virtual-simulation-based learning competency self-evaluation tool for nursing students. Methods: Data were collected from a web-based survey. First, 11 nursing professors participated in a focus group interview, and 7 simulation education experts participated in the preliminary item content validity. The participants in these two aspects were not the same. Then, a preliminary survey was conducted with 15 fourth-year nursing students in I City. Next, based on these three efforts, a final survey comprising 20 evaluation items was developed. This survey was administered to third- and fourth-year nursing students at four nursing colleges in Korean provinces (Seoul, Gyeonggi, Gangwon, and Gyeongsan-do); 222 complete questionnaires were used for the final analysis. Further, Kirkpatrick’s evaluation model was used for four steps each of tool development and verification processes of the associated psychometric aspects, for a total of eight steps. An exploratory factor analysis was performed on the collected survey data, and verify the tool's validity and reliability. Results: Four factors comprising 15 items explained 66.59% of the variance: learning preparation and start-up (4 items), nursing assessment (3 items), data interpretation (3 items), and problem solving (5 items). The Cronbach's α of the tool was 0.74, and that of the factors ranged from 0.72 to 0.80. Conclusions: The tool's validity and reliability were demonstrated using established methodologies. This tool can be useful for evaluating Korean nursing students' virtual simulation learning competence.

Purpose The current study aimed to examine the casual relationships among belongingness during clinical practice, stress, satisfaction with clinical practice, and self-esteem, which are factors affecting the selfdirected learning that results from the clinical practice of advanced practice nurse (APN) students. Methods Data were collected between April 5 and May 19, 2010, from 202 students in 11 APN training institutions located in and outside of Seoul, who were selected using convenience sampling. For hypothesis testing, the collected data were analyzed using AMOS 8.0. Results Analysis of the path coefficients in this study showed that 37% of the variation in self-directed learning could be explained by variations in the model. Self-esteem and belongingness during clinical practice directly affected the self-directed learning of APN students, and belongingness also had an indirect effect via self-esteem. However, stress and satisfaction with clinical practice had no significant mediating effect on self-directed learning. At the same time, belongingness during clinical practice was found to be a good predictive factor to explain stress and satisfaction with clinical practice. Conclusions This study demonstrated the hierarchical relationship among belongingness, self-esteem,and self-directed learning based on the conceptual framework developed by Levett-Jones and Lathlean,thus proving the usefulness of this framework for application in the field. Therefore, this study found that there are needs of high self-esteem and belongingness in order to improve self-directed learning for APN students in clinical practice. [Asian Nursing Research 2011;5(1):48?59]

Deepfake detection is increasingly critical due to the rise of manipulated media. Existing methods often require extensive datasets and struggle with interpretability issues. To address these issues, this study introduces a novel one-class approach for detecting and localizing deepfake artifacts in videos, using authentic images to generate manipulated data for training. By integrating segmentation and leveraging convolutional neural networks with visual transformers, the method predicts both the presence and location of the generated manipulations. Experiments on seven deepfake datasets and emerging diffusion-based manipulations show that our approach consistently outperforms existing methods, demonstrating superior accuracy and localization capabilities.

The purpose of this study was to explore the effects of problem-based learning (PBL) and a mobile application on self-directed learning and learner recognition in a college course. To achieve this, the study reviewed the literature and case studies on mobile technology and problem-based learning, identifying directions and strategies for course design, including three stages of using a mobile application to enhance interaction and communication. This approach was implemented in the class over the course of a semester. The results revealed that the course effectively promoted self-directed learning among learners. Additionally, a qualitative analysis of learners' experiences with the PBL course using the mobile application highlighted the need for efficient and highly accessible IT learning tools. It also indicated that individual data exploration and integration can be quite challenging. Therefore, it is essential to select and utilize appropriate IT learning tools and provide AI literacy training to enhance the technological capabilities of both learners and instructors. This will facilitate the use of various applications to boost learner participation, motivation, and interaction, thereby improving the effectiveness of classes that employ mobile applications based on PBL.

This exploratory mixed-methods study examined the experiences of first-year engineering students in integrating problem-based learning (PBL) and practical learning. It also explored how these experiences relate to students' self-efficacy, peer evaluation, and early academic adjustment. The study involved 16 first-year engineering students enrolled in two project-based courses. Quantitative analyses assessed the reliability and construct validity of self-, peer-, and team-evaluation instruments, while qualitative data from 32 semi-structured interviews were analyzed using thematic analysis. The qualitative findings revealed several recurring themes, including authentic engagement in problem exploration, collaborative idea development, peer interaction, and emerging academic confidence. Quantitative results showed a relatively strong alignment between self-assessment and peer-assessment scores, whereas the relationship between individual self-perceptions and team-level evaluations was more variable. Given the small sample size and single-institution context, these findings should be interpreted with caution. Nevertheless, the study offers valuable insights into how integrated PBL and practical learning environments may enhance collaborative engagement and knowledge application among first-year university students. The implications for instructional design and multi-source evaluation practices in project-based learning contexts are discussed.

Online learning is becoming ubiquitous worldwide because of its accessibility anytime and from anywhere. However, it cannot be successfully implemented without understanding constructs that may affect its adoption. Unlike previous literature, this research extends the Unified Theory of Acceptance and Use of Technology with three well-known theories, namely compatibility, online self-efficacy, and knowledge sharing and acquisition to examine online learning adoption. A total of 264 higher education students took part in this research. Partial Least Squares-Structural Equation Modeling was used to evaluate the proposed theoretical model. The findings suggested that performance expectancy and compatibility were significant predictors of behavioral intention, whereas behavioral intention, facilitating conditions, and compatibility had a significant and direct effect on online learning's actual use. The results also showed that knowledge acquisition, knowledge sharing, and online self-efficacy were determinates of performance expectancy. Finally, online self-efficacy was a predictor of effort expectancy. The proposed model achieved a high fit and explained 47.7%, 75.1%, 76.1%, and 71.8% of the variance of effort expectancy, performance expectancy, behavioral intention, and online learning actual use, respectively. This study has many theoretical and practical implications that have been discussed for further research.

Background: Deficiencies in the ability to maintain balance are common in elderly. Augmented feedback such as knowledge of results (KR) can accelerate learning and mastering a motor skill in older people. Objects: We designed this study to examine whether one session of Wii-Fit game with self-regulated KR is effective for elderly people, and to compare the effect of two different timings of self-regulated KR conditions. Methods: Thirty-nine community-dwelling elders, not living in hospice care or a nursing home, participated in this study. During acquisition, two groups of volunteers were trained in 10 blocks of a dynamic balancing task under the following 2 conditions, respectively: (a) a pre-trial self-regulated KR ($n_1=18$), or (b) a post-trial self-regulated KR ($n_2=21$). Immediate retention tests and delayed retention tests of balancing performance were administered in 15 minutes and 24 hours following acquisition period, respectively. Results: In both groups, significant improvements of balancing performances scores were observed during the acquisition period. Regardless of the group, mean of balancing performance scores on retention tests were well-maintained from the final session. There were no significant differences between groups in balancing performance scores during the acquisition period (p>.05); however, the post-trial self-regulated KR group exhibited significantly higher balancing performance scores in both the immediate retention test and delayed retention test than that of the pre-trial self-regulated KR group (p<.05). Conclusion: Therefore, subjects who regulated their feedback after a dynamic balancing task, during the acquisition period, experienced more efficient motor learning during the retention period than did subjects who regulated their feedback before a dynamic balancing task. Accordingly, in case of presenting the KR of motor learning in clinical settings to elders who reduced dynamic balance abilities, the requesting time of KR is imperative according to self-estimation processes as well as types of KR and practice.

PurposeThis study aimed to classify self-care patterns among Korean adults with prediabetes using an unsupervised machine learning approach. The classification was grounded in Orem’s Self-Care Theory, focusing on self-care demands, self-care agencies, and self-care behaviors. MethodsA secondary data analysis was conducted using the 2023 Korea National Health and Nutrition Examination Survey. Variables were selected and categorized according to the theoretical components of Orem’s model. Principal component analysis was applied for dimensionality reduction, followed by K-means clustering to identify distinct self-care pattern groups. All variables were standardized using min-max normalization. Group differences were examined using analysis of variance and the chi-square test. ResultsThree self-care pattern groups were identified: the high self-care performance group, the latent self-care risk group, and the self-care vulnerable group. These groups exhibited distinct profiles across self-care demands, agencies, and behaviors. Significant intergroup differences were also observed in education level, income, health literacy, fasting blood glucose, and hemoglobin A1c levels. ConclusionSelf-care patterns among adults with prediabetes can be effectively classified through unsupervised learning techniques. The findings highlight the importance of developing tailored nursing interventions that consider multidimensional self-care profiles. This study underscores the applicability of Orem’s Self-Care Theory and demonstrates the potential of machine learning in identifying at-risk subgroups for early intervention.

With the increasing use of the Internet improved Internet technologies as well as web-based applications, the uses of e-Learning have also increased the effectiveness of e-Learning has become one of the most practically and theoretically important issues in both Educational Engineering and Information Systems. This study suggests a research model, based on an e-Learning success model, the relationship of the e-leaner's self-regulated learning strategy and the quality perception of the e-Learning environment. This research model focuses on the learning environment and on self regulated learning strategy. The former consists of LMS, learning contents and interaction that are provided by e-Learning and the latter refers to the learners' self-regulated learning strategy. We will show the validity of the model empirically. As result, most of the hypotheses except for H6 suggested in this model were accepted.

This research delved into the impact of SRL strategies-based instruction on EFL students’ L2 writing performance, academic self-efficacy, and use of SRL strategies. To this end, 50 Iranian EFL learners, including 25 males and 25 females, attended the study. The experimental group was provided with a four-month SRL strategies-based intervention which followed the Self-Regulated Strategy Development model adapted from Harris and Graham (1996), and the control group took the traditional writing course needed by the university curriculum with the same length. All the students were required to accomplish pre- and post-writing tests as well as self-report questionnaires, including the Writing Strategies for Self-Regulated Learning Questionnaire and the second Language Writer Self-Efficacy Scale, at the beginning and the end of the instruction. The outcomes showed that the experimental group outperformed the control group in the post-writing test. Experimental group 's levels of linguistic self-efficacy and performance self-efficacy were remarkably higher than their counterparts in the control group. The study further implies that the instruction might contribute to the increased application of SRL strategies in EFL writing classes in a way that students might become more self-directed and self-regulated in their overall language performance in general and their written performances in particular.

و یلیصحت یدمآراکدوخ ،یاھ یژتارتسا زا هدافتسا تسا ھتخادرپ .زومآ نابز هاجنپدندوب مق هاگشناد رد یسیلگنا تایبدا ھتشر رد لیصحت لاح رد ھک نیا رددندرک تکرش قیقحتشزومآ تحت هام راھچ یشیامزآ هورگ . یمیظنتدوخ دربھار ھعسوت لدم قبط ھک تفرگ رارق روحم یژتارتسا ) ماھارگ و سیرھ1996 تدم نامھ ھب لرتنک هورگ یارب هاگشناد یسرد ھمانرب قبط یتنس یراتشون هرود و دوب ( راھچ ھئارا هامشیپ ات دش ھتساوخ نایوجشناد ھمھ زا .دشسپ و نومزآنومزآشسرپ و راتشون یاھھماندوخ یاھ شرازگ شسرپ لماش یھد ھمانیمیظنتدوخ یریگدای یارب راتشون یاھ یژتارتسا هورگ ھک داد ناشن جیاتن .دنھد ماجنا ار مود نابز هدنسیون یدمآراکدوخ رایعم و سپ رد لرتنک هورگ زا یرتھب درکلمع یشیامزآ هورگ یدرکلمع یدمآراکدوخ و ینابز یدمآراکدوخ حطس .تشاد راتشون نومزآشیامزآ یژتارتسا زا هدافتسا شیازفا ثعاب روحم یژتارتسا شزومآ زا هدافتسا ھک دش شرازگ نینچمھ .تشاد یریگمشچ شیازفا ی یاھلاعف و یم یشزومآ نینچ ھک تسا نیا زا یکاح ام جیاتن .دش روکذم یاھ یژتارتسا زا هدافتسا رد وجشناد ندش رت ھب دناوت نابز نازومآشیب یاکتا ردیگدای ھب رتو هدرک کمک ملعم زا یریگدای یاجب یدرف یرزومآ نابز یم ھنلااعف ار دوخ یریگدای دنیآرف دناوت رت .دنک یبایزرا