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关键词： 计算机科学导论   课程思政   专业认证  

摘要： 对标工程教育专业认证标准中的毕业要求,分析其涵盖的专业技能要求与人文素养,结合计算机科学导论课程特点,深挖课程知识点蕴含的思政元素.重点关注专业认证与课程思政的相容性,设计相关联的思政案例,将思政教育融入专业课教学中,践行价值引领和专业技能传授的融合思政育人理念.充分发挥了专业课堂的主渠道作用,为思政教育融入专业课教学起到了很好的示范作用.

关键词： Clustering algorithms   Big Data   Collaboration   Image edge detection   Detection algorithms   Computer science   Data mining   Community detection   temporal networks   stable community   structural graph clustering   density-based clustering  

摘要： Community detection is a fundamental task in graph data mining. Most existing studies in contact networks, collaboration networks, and social networks do not utilize the temporal information associated with edges for community detection. In this article, we study a problem of finding stable communities in a temporal network, where each edge is associated with a timestamp. Our goal is to identify the communities in a temporal network that are stable over time. To efficiently find the stable communities, we develop a new community detection algorithm based on the density-based graph clustering framework. We also propose several carefully-designed pruning techniques to significantly speed up the proposed algorithm. We conduct extensive experiments on four real-life temporal networks to evaluate our algorithm. The results demonstrate the effectiveness and efficiency of the proposed algorithm.

关键词： Quality assurance   information security   cryptographic algorithms   education programs  

摘要： Improving the quality assurance (QA) processes and acquiring accreditation are top priorities for academic programs. The learning outcomes (LOs)assessment and continuous quality improvement represent core components ofthe quality assurance system (QAS). Current assessment methods suffer deficiencies related to accuracy and reliability, and they lack well-organized processes forcontinuous improvement planning. Moreover, the absence of automation, andintegration in QA processes forms a major obstacle towards developing efficientquality system. There is a pressing need to adopt security protocols that providerequired security services to safeguard the valuable information processed byQAS as well. This research proposes an effective methodology for LOs assessment and continuous improvement processes. The proposed approach ensuresmore accurate and reliable LOs assessment results and provides systematic wayfor utilizing those results in the continuous quality improvement. This systematicand well-specified QA processes were then utilized to model and implement automated and secure QAS that efficiently performs quality-related processes. Theproposed system adopts two security protocols that provide confidentiality, integrity, and authentication for quality data and reports. The security protocols avoidthe source repudiation, which is important in the quality reporting system. This isachieved through implementing powerful cryptographic algorithms. The QASenables efficient data collection and processing required for analysis and interpretation. It also prepares for the development of datasets that can be used in futureartificial intelligence (AI) researches to support decision making and improve thequality of academic programs. The proposed approach is implemented in a successful real case study for a computer science program. The current study servesscientific programs struggling to achieve academic accreditation, and gives rise tofully automating and integrating the

关键词： 大数据背景   计算机科学与技术   专业教学   教学改革  

摘要： 随着科学技术水平的不断升高,我国也迎来了大数据时代。在这样的时代背景下,国家和各个企业对于计算机人才需求越来越多。当代高校计算机科学与技术专业教学模式过于单一,教学理念过于陈旧,学生很难在学习过程中产生兴趣。文章在深入分析大数据概念后,结合当代计算机科学与技术专业教学存在的问题,从教学体系、教学理念和教学模式等方面给出改革策略。

关键词： 鲁艺红色音乐文化   艺术传承   创新发展  

摘要： 延安鲁艺创立在革命战争年代,其所创造的红色音乐文化呈现出了鲜明的民族精神烙印。鲁艺红色音乐文化有着丰富的内涵、独到的特色和高度的传承意义,经历了一系列的历史演变,成为了新时代弘扬中国红色音乐文化的宝贵资源。然而,随着时代的发展,网络文化不断涌现,鲁艺红色音乐文化被尘封于记忆中,在传承和发展中更存在着资源开发及管理缺位、传播内容及渠道单一等问题。基于此,应坚持以科学的思想为引领,从历史中获得启示,推动鲁艺红色音乐文化重回大众视野。

关键词： 唇腭裂   语音评价   腭裂语音   声学特征   人工智能   在线平台  

摘要： 唇腭裂术后针对性的语音治疗是唇腭裂综合序列治疗的重要组成部分,主观语音评价是目前应用最广泛的评价体系,由于无法避免主观倾向的局限性,精准的腭裂语音诊疗仍有进一步完善的空间。随着医工交叉的广泛推进,计算机科学已成为前沿医疗的基石,人工智能在言语障碍领域已开展初步的临床应用。对于腭裂语音的计算机辅助识别和评价技术已有较多研究成果,辅音省略、咽擦音等代偿性发音错误是关键的识别分析特征,结合软硬件技术的系统能达到较高的识别准确度;但目前研究大多仅局限于独立的声学特征辨别,有待进一步开发多参数的分析函数来避免普遍评价的系统偏差;且计算机科学在腭裂语音评价及治疗方面仍缺乏治疗方案的尝试,在线诊疗平台未得到充分使用,因此运用人工智能媒介与主观评价体系的结合应是唇腭裂综合序列治疗的前景模式之一。

关键词： Training   Classification algorithms   Takagi-Sugeno model   Neural networks   Fuzzy sets   Computer science   Benchmark testing   Adversarial Takagi-Sugeno-Kang (TSK) fuzzy classifier   deep fuzzy classifiers   fuzzy rules   gradient guided learning   large-scale datasets   stacked generalization principle  

摘要： While our recent deep fuzzy classifier DSA-FC, which stacks adversarial interpretable Takagi-Sugeno-Kang fuzzy subclassifiers, shares its promising classification, its training speed will become very slow and even intolerable for large-scale datasets, due to successive training on all training samples with their random gradient based updates along each layer of its stacked structure. In order to circumvent this bottleneck issue, a fast training algorithm FTA is developed in this study by downsizing fuzzy rules with the proposed gradient guided learning for each subclassifier at each layer of DSA-FC on large-scale datasets. The core of FTA is to assure fast training of each subclassifier at each layer of DSA-FC, which first generates first-order smooth gradient guided information by means of the proposed top-k fuzzy rules selected from all fuzzy rules in each subclassifier, and then quickly updates the current inputs in terms of such information, which will be taken as the inputs of the subclassifier at the next layer. Our theoretical analysis reveals that the proposed gradient guided learning indeed enhances the generalization capability of a deep fuzzy classifier with or without adversarial attacks on outputs. Experimental results on large datasets demonstrate that FTA indeed trains the deep fuzzy classifier DSA-FC quickly with enhanced generalization capability.

关键词： artificial intelligence   image processing   food quality   computer science   marketing  

摘要： Hazelnut is a product with high nutritional and economic value. In maintaining the quality value of hazelnut, the classification process is of great importance. In the present day, the quality classification of hazelnuts and other crops is performed in general manually, and so it is difficult and costly. Performing this classification with modern agricultural techniques is much more important in terms of quality. This study was based on a model intended to detect hazelnut quality. The model is about the establishment of an artificial intelligence-based classification system that can detect the hidden defects of hazelnuts. In the developed model, the visuals used in the dataset are divided into training and test groups. In the model, hazelnuts are divided into 5 classes according to their quality using AlexNet architecture and modern deep learning (DL) techniques instead of traditional hazelnut classification methods. In this model developed based on artificial intelligence, a very good approach was presented with the accurate classification of 99%. Moreover, the values regarding precision and recall were also determined at 98.7% and 99.6%, respectively. This study is important in terms of becoming widespread information technology use and computer-assisted applications in the agricultural economics field such as product classification, quality, and control.