Adaptive Image Transformations for Transfer-based Adversarial Attack

Adversarial attacks provide a good way to study the robustness of deep learning models. One category of methods in transfer-based black-box attack utilizes several image transformation operations to improve the transferability of adversarial examples, which is effective, but fails to take the specific characteristic of the input image into consideration. In this work, we propose a novel architecture, called Adaptive Image Transformation Learner (AITL), which incorporates different image transformation operations into a unified framework to further improve the transferability of adversarial examples. Unlike the fixed combinational transformations used in existing works, our elaborately designed transformation learner adaptively selects the most effective combination of image transformations specific to the input image. Extensive experiments on ImageNet demonstrate that our method significantly improves the attack success rates on both normally trained models and defense models under various settings.Comment: 34 pages, 7 figures, 11 tables. Accepted by ECCV202

The role of acupoint stimulation as an adjunct therapy for lung cancer: A systematic review and meta-analysis

Background: Lung cancer is the leading cause of death in cancer patients. Clinical studies showed that a variety of acupoint stimulations have been extensively used for lung cancer patients, including needle insertion, injection with herbal extraction, plaster application, and moxibustion. However, the role of acupoint stimulation in lung cancer treatment was not fully reviewed. Methods: In the present study, we conducted a systematic review and meta-analysis on the role of acupoint stimulation in lung cancer treatment by electronic and manual searching in seven databases, including Ovid (Ovid MEDLINE, AMED, CAB Abstracts, EMBASE), EBSCOhost research databases (Academic Search premier, MEDLINE, CIHAHL Plus), PreQuest (British Nursing Index, ProQuest Medical Library, ProQuest Dissertations & Theses A&I, PsycINFO), and ISI web of knowledge (Web of Science, BIOSIS Citation Index, Biological Abstracts, Chinese Science Citation Database), CNKI, Wanfang Data, and CQVIP. Results: Our study showed that acupoint stimulation has strong immunomodulatory effect for lung cancer patients as demonstrated by the significant increase of IL-2, T cell subtypes (CD3+ and CD4+, but not CD8+ cells), and natural killer cells. Further analysis revealed that acupoint stimulation remarkably alleviates the conventional therapy-induced bone marrow suppression (hemoglobin, platelet, and WBC reduction) in lung cancer patients, as well as decreases nausea and vomiting. The pooled studies also showed that acupoint stimulation can improve Karnofsky performance status, immediate tumor response, quality of life (EORCT-QLQ-C30), and pain control of cancer patients. Conclusions: Acupoint stimulation is found to be effective in lung cancer treatment, further confirmatory evaluation via large scale randomized trials is warranted. © 2013 Chen et al.; licensee BioMed Central Ltd.published_or_final_versio

Customer Satisfaction in Post COVID-19: A Case Study of Chinese Restaurants in Ratchada Phitset District

Purpose: The research paper is to identify the determinant factors influencing customer satisfaction in the case of Ratchada Phiset district, Bangkok, Thailand Chinese restaurants by examining some attributes, including word of mouth, perceived quality, and expectation. Research design, data and methodology: 150 samples for investigation with employed convenience sample techniques and used an online questionnaire to collect the data. After collecting data, both descriptive statistics and inferential statistics were used to explain significant aspects. Results: The major findings are as follows: 1) Word of mouth has a significant influence on perceived quality. 2) Word of mouth has a significant influence on expectations. 3) Perceived quality and expectations have a significant influence on customer satisfaction. Conclusions: The research findings have met the research objectives. Chinese restaurants can improve customer satisfaction by creating special dishes, implementing personalized services, establishing customer databases, and implementing restaurant membership systems

CCLAP: Controllable Chinese Landscape Painting Generation via Latent Diffusion Model

With the development of deep generative models, recent years have seen great success of Chinese landscape painting generation. However, few works focus on controllable Chinese landscape painting generation due to the lack of data and limited modeling capabilities. In this work, we propose a controllable Chinese landscape painting generation method named CCLAP, which can generate painting with specific content and style based on Latent Diffusion Model. Specifically, it consists of two cascaded modules, i.e., content generator and style aggregator. The content generator module guarantees the content of generated paintings specific to the input text. While the style aggregator module is to generate paintings of a style corresponding to a reference image. Moreover, a new dataset of Chinese landscape paintings named CLAP is collected for comprehensive evaluation. Both the qualitative and quantitative results demonstrate that our method achieves state-of-the-art performance, especially in artfully-composed and artistic conception. Codes are available at https://github.com/Robin-WZQ/CCLAP.Comment: 8 pages,13 figure