Bring the world together one note at a time': a qualitative study of intercultural practice and identity development of musicians

Musicians face particular communication and identity challenges when working with music and people from other cultural groups. Those challenges impede efforts to promote intergroup projects and rapport. Intercultural communication studies have made significant contributions in understanding how people work and live across cultures but do not explicate the unique ways in which professional musicians engage internationally. Thus, there is a need to research musicians’ intercultural practice and identity development. This qualitative study addresses the gap through three research questions: 1) What aspects of intercultural communication and identity processes are significant to musicians when they begin intercultural music practice? 2) What challenges do musicians report during intercultural music projects? 3) What keeps musicians engaged in intercultural music practice in the long term? Semi-structured interviews were conducted with 17 music professionals engaged in intercultural music-making with questions about their projects and experiences. These were complemented with field notes from observations of six respondents’ live concerts. Recordings and written accounts relating to participants were also collected from the internet to inform the analysis. Purposive sampling and theory-led thematic analysis were guided by a priori themes developed from Young Yun Kim’s and Etienne Wenger’s theoretical framework. Kim’s Integrative Theory of Communication and Cross-cultural Adaptation and Wenger’s Communities of Practice theory place individuals’ music careers into intercultural and social learning contexts. The theoretical notion of boundaries - boundary crossing and boundary learning - has also been used to address socio-cultural differences that result in discontinuities in activities and interactions. Codes were arranged under a three-part dynamic of encounter, stress, and learning, which describes how individuals cross groups and work on differences perceived. The findings delineate how musicians experience and learn at musical and cultural boundaries mixedly. Music enabled them to coordinate temporarily by providing non-verbal routines, working arrangements, enjoyments, and promising identities essential in motivating individuals to start intercultural music practice. However, language proficiency, social communication, and cultural adaptations become more critical as musicians work long-term across cultures, organise complicated projects, and negotiate nuanced meanings. Although respondents may state cosmopolitan ideals and intercultural objectives, their focus often gravitated back towards musical issues that emerged in their performance and organising work. Finally, respondents’ experiences suggest that organisers with intergroup mediation objectives should consider arranging language training and designing for meaningful intercultural experiences. It is beneficial for musicians to know what cross-cultural communication and adaptation would be expected and how to seek cultural informants’ help. The findings contribute to theory by offering a novel manifestation of professional musicians’ intercultural activities as boundary phenomena. The diverse cultural experiences told from the musicians’ perspectives enriches our social and psychological understanding of intercultural challenges. These musicians’ projects and words demonstrate how crossing boundaries, with mutual interest and creative adaptation in musical activities, opens up possibilities for new intercultural collaborations, rapport, ideas, and identities

Mastering Strategy Card Game (Hearthstone) with Improved Techniques

Strategy card game is a well-known genre that is demanding on the intelligent game-play and can be an ideal test-bench for AI. Previous work combines an end-to-end policy function and an optimistic smooth fictitious play, which shows promising performances on the strategy card game Legend of Code and Magic. In this work, we apply such algorithms to Hearthstone, a famous commercial game that is more complicated in game rules and mechanisms. We further propose several improved techniques and consequently achieve significant progress. For a machine-vs-human test we invite a Hearthstone streamer whose best rank was top 10 of the official league in China region that is estimated to be of millions of players. Our models defeat the human player in all Best-of-5 tournaments of full games (including both deck building and battle), showing a strong capability of decision making.Comment: cog2023 ful

Security Verification of Low-Trust Architectures

Low-trust architectures work on, from the viewpoint of software, always-encrypted data, and significantly reduce the amount of hardware trust to a small software-free enclave component. In this paper, we perform a complete formal verification of a specific low-trust architecture, the Sequestered Encryption (SE) architecture, to show that the design is secure against direct data disclosures and digital side channels for all possible programs. We first define the security requirements of the ISA of SE low-trust architecture. Looking upwards, this ISA serves as an abstraction of the hardware for the software, and is used to show how any program comprising these instructions cannot leak information, including through digital side channels. Looking downwards this ISA is a specification for the hardware, and is used to define the proof obligations for any RTL implementation arising from the ISA-level security requirements. These cover both functional and digital side-channel leakage. Next, we show how these proof obligations can be successfully discharged using commercial formal verification tools. We demonstrate the efficacy of our RTL security verification technique for seven different correct and buggy implementations of the SE architecture.Comment: 19 pages with appendi

Research on Improving the Teaching Effectiveness of Ideological and Political Courses in Universities by Using New Media In the Context of the Normalization of Epidemic Prevention and Control

This article takes the normalization of epidemic prevention and control as an inspection perspective, and relies on the rich new media resources of universities, through the docking with the teaching of ideological and political courses in universities, and builds a new bridge between new media and university students in ideological and political thinking, and innovative ideas Political education methods, expand ideological and political education channels, and improve the effectiveness of college ideological and political education

Image Segmentation of Cucumber Seedlings Based on Genetic Algorithm

To solve the problems of the low target-positioning accuracy and weak algorithm robustness of target-dosing robots in greenhouse environments, an image segmentation method for cucumber seedlings based on a genetic algorithm was proposed. Firstly, images of cucumber seedlings in the greenhouse were collected under different light conditions, and grayscale histograms were used to evaluate the quality of target and background sample images. Secondly, the genetic algorithm was used to determine the optimal coefficient of the graying operator to further expand the difference between the grayscale of the target and background in the grayscale images. Then, the Otsu algorithm was used to perform the fast threshold segmentation of grayscale images to obtain a binary image after coarse segmentation. Finally, morphological processing and noise reduction methods based on area threshold were used to remove the holes and noise from the image, and a binary image with good segmentation was obtained. The proposed method was used to segment 60 sample images, and the experimental results show that under different lighting conditions, the average F1 score of the obtained binary images was over 94.4%, while the average false positive rate remained at about 1.1%, and the image segmentation showed strong robustness. This method can provide new approaches for the accurate identification and positioning of targets as performed by target-dosing robots in a greenhouse environment

Image Segmentation of Cucumber Seedlings Based on Genetic Algorithm

To solve the problems of the low target-positioning accuracy and weak algorithm robustness of target-dosing robots in greenhouse environments, an image segmentation method for cucumber seedlings based on a genetic algorithm was proposed. Firstly, images of cucumber seedlings in the greenhouse were collected under different light conditions, and grayscale histograms were used to evaluate the quality of target and background sample images. Secondly, the genetic algorithm was used to determine the optimal coefficient of the graying operator to further expand the difference between the grayscale of the target and background in the grayscale images. Then, the Otsu algorithm was used to perform the fast threshold segmentation of grayscale images to obtain a binary image after coarse segmentation. Finally, morphological processing and noise reduction methods based on area threshold were used to remove the holes and noise from the image, and a binary image with good segmentation was obtained. The proposed method was used to segment 60 sample images, and the experimental results show that under different lighting conditions, the average F1 score of the obtained binary images was over 94.4%, while the average false positive rate remained at about 1.1%, and the image segmentation showed strong robustness. This method can provide new approaches for the accurate identification and positioning of targets as performed by target-dosing robots in a greenhouse environment

Path Tracking of a 4WIS–4WID Agricultural Machinery Based on Variable Look-Ahead Distance

Aiming to solve the problem of the low path-tracking accuracy of mobile robots in agricultural environments, the authors of this paper propose a path-tracking method for agricultural machinery based on variable look-ahead distance. A kinematic model of the four wheel independent steering–four wheel independent drive (4WIS–4WID) structure based on pure pursuit was constructed to obtain the functional equation of the current position and the four-wheel steering angle. The fuzzy controller, which takes the lateral deviation and heading deviation as input and the look-ahead distance in a pure pursuit model as output, was designed to obtain the look-ahead distance that changes dynamically with the deviation of mobile agricultural machinery. The path-tracking performance of 4WIS–4WID agricultural machinery in three scenarios (1 m, −90°; 1 m, 0°; and 0 m, 90°) with different initial deviations was tested using a pure pursuit model based on a variable look-ahead distance. The obtained field test results showed an average deviation of 19.7 cm, an average tracking time of 5.1 s, an average stability distance of 203.9 cm, and a steady state deviation of 3.1 cm. The results showed that the proposed method presents a significant path-tracking performance advantage over a fixed look-ahead distance pure tracking model and can be a reference for high-quality path-tracking methods in automatic navigation research