PCB CT Image Element Segmentation Model Optimizing the Semantic Perception of Connectivity Relationship

Computed Tomography(CT)is a commonly used technology in Printed Circuit Boards(PCB)non-destructive testing,and element segmentation of CT images is a key subsequent step.With the development of deep learning,researchers began to exploit the“pre-training and fine-tuning”training process for multi-element segmentation,reducing the time spent on manual annotation.However,the existing element segmentation model only focuses on the overall accuracy at the pixel level,ignoring whether the element connectivity relationship can be correctly identified.To this end,this paper proposes a PCB CT image element segmentation model optimizing the semantic perception of connectivity relationship(OSPC-seg).The overall training process adopts a“pre-training and fine-tuning”training process.A loss function that optimizes the semantic perception of circuit connectivity relationship(OSPC Loss)is designed from the aspect of alleviating the class imbalance problem and improving the correct connectivity rate.Also,the correct connectivity rate index(CCR)is proposed to evaluate the model’s connectivity relationship recognition capabilities.Experiments show that mIoU and CCR of OSPC-seg on our datasets are 90.1%and 97.0%,improved by 1.5%and 1.6%respectively compared with the baseline model.From visualization results,it can be seen that the segmentation performance of connection positions is significantly improved,which also demonstrates the effectiveness of OSPC-seg.

Mother-Daughter Relationship and Daughter’s Body Image

The adolescent years are characterized by emotional upheaval and hormonal and physiological changes that often create tension and conflicts between girls and their parents. This research study is based on an analysis of the mother-adolescent daughter relationship, with 46 mother-daughter dyads. This research assessed the effect of the daughter’s body image (independent variable) and her view of her own mother-daughter relationship (independent variable) on her sense of wellbeing (dependent variable). This study used four questionnaires to evaluate the dyadic model: the Modified Gray’s Questionnaire (Body Image), the Leisure Time Exercise Questionnaire (LTEQ), the Mental Health Inventory (MHI) for measurement of the subjective sense of wellbeing, and the Relationship with Mother Questionnaire. Study findings show the importance of the adolescent girl’s positive body image on her sense of wellbeing, as well as the centrality of the mother-daughter relationship in the daughter’s body image and wellbeing.

The Image and Text Relationship in TANG Yin＇s Scroll of Poetry and Painting

This paper seeks to examine the image and text relationship in TANG Yin＇s scroll of poetry and painting from three aspects： The first aspect focuses upon the schema type of its image and text relationship in physical form; the second aspect, explores the text＇s/poetry＇s functions of anchorage and relay while appreciating those images/paintings; the third aspect, traces the semiosis process of image, exploring how image and text as cultural products in the epistemological world mediates with the phenomenological world

Chinese Image in American and British Literature from the Perspective of＂Otherness＂

In the US and British literature, there are many works using China or the Chinese people as depict objects. With the development of American and British literature, the shape of the image of China is diverse. Currently, the research of the image of China or Chinese people in the US and British literature has yielded fruitful results, the majority concentrated on the study before the new century writers and representative works. In the new century, the causes and significance of the image of China and the Chinese people in American literature have the positive impact on self-awareness and self-construction of the China＇ s image.

Relationship Between Tyndall Light Path Attenuation and Concentration Based on Digital Image

When the red laser illuminates the lyosol, the Tyndall effect will form a light path with a certain distance, and the optical properties of the lyosol will have a certain influence on the Tyndall light intensity. This paper mainly aims at the theoretical and experimental studies on the change situation of the lyosol concentration and the attenuation characteristics of the light path when the red laser changes with the distance of the light path in the solution. In order to study the effect of lyosol concentration on the Tyndall light path, digital image technology was applied to the measurement of lyosol concentration. Due to the non-contact property of the image, the liquid concentration can be measured accurately in real time. The attenuation characteristics of the laser in the lyosol were obtained by image processing technology, and the quantitative relationship between the attenuation coefficient of the Tyndall light path and the lyosol concentration was obtained.

Malignant adenomyoepithelioma of the breast:Two case reports and review of the literature

BACKGROUND Malignant adenomyoepithelioma(AME)of the breast is a rare tumor in which malignancy can arise from either epithelial or myoepithelial components,or from both cell types.The incidence and prognosis of malignant AME of the breast are difficult to assess due to its rarity.Therefore,the optimal treatment for this disease is still controversial.CASE SUMMARY We present two middle-aged women(48 and 56 years old)with malignant AME of the breast.Core needle biopsy was performed before surgery.However,breast adenoma and malignant tumors were observed.The preoperative diagnosis of malignant AME of the breast is still challenging for pathologists and clinicians.Both patients underwent mastectomy and sentinel lymph node biopsy,both of which were negative,followed by adjuvant chemotherapy.CONCLUSION The follow-up duration of the two patients was two years and four months,respectively.No signs of relapse or metastasis have been observed thus far.

Optimizing Spatial Relationships in GCN to Improve the Classification Accuracy of Remote Sensing Images

Semantic segmentation of remote sensing images is one of the core tasks of remote sensing image interpretation.With the continuous develop-ment of artificial intelligence technology,the use of deep learning methods for interpreting remote-sensing images has matured.Existing neural networks disregard the spatial relationship between two targets in remote sensing images.Semantic segmentation models that combine convolutional neural networks(CNNs)and graph convolutional neural networks(GCNs)cause a lack of feature boundaries,which leads to the unsatisfactory segmentation of various target feature boundaries.In this paper,we propose a new semantic segmentation model for remote sensing images(called DGCN hereinafter),which combines deep semantic segmentation networks(DSSN)and GCNs.In the GCN module,a loss function for boundary information is employed to optimize the learning of spatial relationship features between the target features and their relationships.A hierarchical fusion method is utilized for feature fusion and classification to optimize the spatial relationship informa-tion in the original feature information.Extensive experiments on ISPRS 2D and DeepGlobe semantic segmentation datasets show that compared with the existing semantic segmentation models of remote sensing images,the DGCN significantly optimizes the segmentation effect of feature boundaries,effectively reduces the noise in the segmentation results and improves the segmentation accuracy,which demonstrates the advancements of our model.

Analysis of the Image of China in Japanese Literature

Due to the established narrative patterns and powerful and profound ideological influences of classical Chinese literature,the image of China has been reinterpretation during the process of imagination,construction,and experience of Japanese writer or researcher,with many distortions and misinterpretations.The image of China in Japanese literature is an impression and illusion formed by the combination of cultural awareness and literary classics.The following article will analyze and sort out the Chinese image in Japanese literature.

On Chinese Image of American Literature in the 20^(th) Century

Due to the influence and control of many factors such as geographical location and historical conditions,many of the 20thCentury American literature works portray distorted Chinese image different from reality. In American literature,China doesn't exist as a real country with a geographical location,but it exists in a virtual space in the world composed of cultural imagination. Literature is the reflected thought that can accommodate numerous social fields,and American literature can mostly reflect the overall cognition of different fields for Chinese image. This paper analyzes the characterization and cognition of Chinese image in the20thCentury American literature works,understanding the history and features of Chinese image in the 20thCentury American literature works,in order to obtain the enlightenment of how to better establish Chinese image.

Patients’ Experiences of Trust in the Patient-Nurse Relationship——A Systematic Review of Qualitative Studies

Aims and Objectives: To report a synthesis of the literature on the meaning of trust in the context of patients’ experiences of nursing. The review question was “How do patients describe the meaning of trust in the nursing relationship?” Background: Trust is essential in nursing as it has the potential to create opportunities for the human being to gain faith, hope and meaning in life as well as open up for new experiences. Trust is an interpersonal and essential element of all patient-nurse relationships and requires nurses to create a trusting relationship with the patients. Design: Systematic qualitative literature review. Methods: Systematic searches were conducted for the period January 2002 to December 2012, updated in January 2014. 20 papers were included. Results: Four categories emerged: Attitudes related to trust, indicating that trust is fundamental and existential;Experiences of trust, concerning how trust can be sensed;The patient-nurse relationship, revealing the qualities of the person who creates trust;and Where trust occurs, illuminating the contextual relevancies of trust. Conclusions: Patients’ experiences of trust in nursing are dependent on the nurses’ knowledge, level of commitment in the dialogue to creating and developing the relationship and contextual issues. Implications for nursing practice: Reflection on a trusting relationship with the patient is necessary for a deeper conceptual understanding of trust in nursing. Clinical nurse researchers nurse supervisors, managers and nurse educatorsshould discuss different areas of trust during nursing supervision and focus-group meetings as well as with nursing graduates to ensure that nurses develop knowledge of how to create a trusting patient-nurse relationship.

Two new approaches for image registration based onspatial-temporal relationship

How to improve the probability of registration and precision of localization is a hard problem, which is desiderated to solve. The two basic approaches (normalized cross-correlation and phase correlation) for image registration are analysed, two improved approaches based on spatial-temporal relationship are presented. This method adds the correlation matrix according to the displacements in x- cirection and y- directions, and the registration pose is searched in the added matrix. The method overcomes the shortcoming that the probability of registration decreasing with area increasing owing to geometric distortion, improves the probability and the robustness of registration.

Image Retrieval Based on Objects’ Spatial Orientation Relationships

A new concept of characteristic scanning radial (CSR) is proposed for thesegmented image on the basis of two shape-specific points of its shape-objects. Subsequently, twocharacteristic attribute sequences (CAS) of relative distance and relative direction are derived torepresent the spatial orientation relationships among objects of the image. A novel image retrievalalgorithm is presented using these two CASs. The proposed retrieval approach not only satisfies thetransformational invariance, butalso attains the quantitative comparison of matching. Experimentsidentify the effectiveness and efficiency of the algorithm adequately.

Cystic teratoma of the parotid gland:A case report

BACKGROUND Teratoma is a common tumor,but rarely occurs in the parotid region.Only nine cases have been reported in the current literature.Although it is generally detected in infancy or childhood,it is commonly asymptomatic.Computed tomography(CT)and magnetic resonance imaging(MRI)have important roles in the diagnosis of teratoma.CASE SUMMARY A 36-year-old man developed a lump located below the left auricular lobule 3 years ago.Physical examination revealed a nearly-circular tumor in the left parotid gland region with a defined border,firm texture,and significant movement.Calcification,fat,keratinized substances,and typical fat-liquid levels was observed on CT and MRI.A diagnosis of cystic teratoma of the parotid gland was established preoperatively and confirmed by postoperative pathology.Following surgery,the patient developed temporary facial paralysis.There was no recurrence of teratoma during the 15-mo follow-up period.CONCLUSION When an asymptomatic mass in the parotid region is identified,parotid gland teratoma should be included in the differential diagnosis.Imaging examinations are helpful in the diagnosis.

Topology and Semantic Information Fusion Classification Network Based on Hyperspectral Images of Chinese Herbs

Most methods for classifying hyperspectral data only consider the local spatial relation-ship among samples,ignoring the important non-local topological relationship.However,the non-local topological relationship is better at representing the structure of hyperspectral data.This paper proposes a deep learning model called Topology and semantic information fusion classification network(TSFnet)that incorporates a topology structure and semantic information transmis-sion network to accurately classify traditional Chinese medicine in hyperspectral images.TSFnet uses a convolutional neural network(CNN)to extract features and a graph convolution network(GCN)to capture potential topological relationships among different types of Chinese herbal medicines.The results show that TSFnet outperforms other state-of-the-art deep learning classification algorithms in two different scenarios of herbal medicine datasets.Additionally,the proposed TSFnet model is lightweight and can be easily deployed for mobile herbal medicine classification.

Study on the Strategy of International Publicity Translation in Our Country from the Perspective of National Image

Along with the advent of the age of globalization, our country and international community are becoming more closely, and comprehensive national strength and infl uence is also greatly growing. Strengthening external propaganda has become a strategic task in the current development of our country. The translation work has been paid more and more attention, and it has an important role in shaping the image of our country. But from the current point of view, there are still some common problems. In this paper, from the perspective of the national image, we analyze the relationship between foreign publicity translation strategies and national image, and we also analyze the status quo of the translation of foreign propaganda in China, then we put forward the strategy of publicity translation.

The Literature Criticism Approach Applied in English Teaching

Aimed at the negligence of literature side in foreign language teaching, the reduction of literary texts in foreign language teaching for non-foreign language majors, and the minimized proportion of literary criticism in the related teachers books, this paper stressed the dialectic complementary relationship between foreign language teaching and literature teaching, advances the application of the literature criticism approach with an attached analytic case study and a summary of the advantage of the approach.

区域敏感的场景图生成方法

针对基于关系边界框提取的谓词特征粒度相对较粗的问题,提出区域敏感的场景图生成(region-sensitive scene graph generation,RS-SGG)方法。谓词特征提取模块将关系边界框分为4个区域,基于自注意力机制抑制关系边界框中与关系分类无关的背景区域。关系特征解码器在进行关系预测时不仅考虑了物体对的视觉特征和语义特征,也考虑了物体对的位置特征。在视觉基因组(visual genome,VG)数据集上分别计算了RS-SGG方法针对场景图生成、场景图分类和谓词分类3个子任务的图约束召回率和无图约束召回率,并与主流的场景图生成方法进行了比较。实验结果表明,RS-SGG的图约束召回率和无图约束召回率均优于主流方法。此外,可视化实验结果也进一步证明了所提出方法的有效性。