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关键词： 应用型   高校   计算机科学与技术   教学  

摘要： 计算机技术的不断发展和创新,计算机科学与技术已经渗透到了各个行业和领域,为社会进步和企业发展创造了巨大的机会和条件。在数字化转型的加速推进下,企业需要更多满足市场需求的技术和人才,同时也对高校计算机科学与技术应用型人才培养提出更高要求,以适应不断发展的技术和市场趋势。针对当前计算机科学与技术应用人才培养存在的问题,应从人才培养方案、课程体系建设、完善教学方法、加强教师培训等方面着手,更好地满足社会和行业对高素质计算机专业人才的需求。

关键词： Electrical and electronic engineering   Neuroscience   Computer science  

摘要： The human brain's unparalleled efficiency in executing complex cognitive tasks stems from neurons communicating via short, intermittent bursts or spikes. This has inspired Spiking Neural Networks (SNNs), now incorporating neuron models with spike frequency adaptation (SFA). SFA adjusts these spikes' frequency based on recent neuronal activity, much like an athlete's varying sprint speed. SNNs with SFA demonstrate improved computational performance and energy efficiency. This review examines various adaptive neuron models in computational neuroscience, highlighting their relevance in artificial intelligence and hardware integration. It also discusses the challenges and potential of these models in driving the development of energy-efficient neuromorphic systems.

关键词： Computational biology and bioinformatics   Computer science   Machine learning  

摘要： Researchers have a part to play in addressing concerns about government interference in science.

关键词： 混合式教学模式   翻转课堂   中职计算机专业  

摘要： “SPOC十FCM”的混合式教学模式是一种将小规模限制性在线课程与翻转课堂相结合的教学方法,融合了线上和传统教学的优势。文章在中职计算机专业的5门专业课中进行了基于“SPOC十FCM”的混合式教学模式的应用研究,旨在构建并验证适合中职计算机专业的混合式教学模型。

关键词： Clothing   Task analysis   Feature extraction   Semantic segmentation   Electronic mail   Textiles   Computer science   Clothing parsing   semantic segmentation   attention mechanism   phase contour enhancement  

摘要： Clothing parsing is a challenging task. In this task, there are two main inherent challenges, which are the fine-grained parsing of small clothing components and the missegmentation of similar clothing categories. To address these challenges, this paper proposes a phase contour enhancement network for clothing parsing. It achieves improved accuracy while maintaining a relatively small network complexity. Leveraging the distinctive features of phase maps, we introduce the phase contour enhancement attention (PCEA) module to augment the encoder's object edge information. To further enrich the model's feature extraction capacity, we present the dilated convolution pyramid (DCP) module, combining it with a lightweight decoder to achieve improved global context modeling. The synergistic integration of the PCEA and DCP modules enhances the network with remarkable capabilities in capturing intricate contours, effectively surmounting the challenges of fine-grained parsing for small clothing components and mitigating the missegmentation of similar clothing categories. Through extensive experiments on the CFP, Modanet, and DeepFashion2 datasets and further expansion experiments on the LIP dataset, our method demonstrates outstanding performance across multiple evaluation metrics, surpassing state-of-the-art methods for clothing parsing. In conclusion, our phase contour enhancement network exhibits remarkable performance in both clothing parsing tasks and extended human parsing tasks.

关键词： Task analysis   Optimization   Linear programming   Resource management   Uncertainty   Parallel processing   Computer science   Bayes resource allocation   data-driven multiobjective optimization   evolutionary multitasking (EMT)  

摘要： In an era of pervasive digitalization, the growing volume and variety of data streams poses a new challenge to the efficient running of data-driven optimization algorithms. Targeting scalable multiobjective evolution under large-instance data, this article proposes the general idea of using subsampled small-data tasks as helpful minions (i.e., auxiliary source tasks) to quickly optimize for large datasets-via an evolutionary multitasking framework. Within this framework, a novel computational resource allocation strategy is designed to enable the effective utilization of the minions while guarding against harmful negative transfers. To this end, an intertask empirical correlation measure is defined and approximated via Bayes' rule, which is then used to allocate resources online in proportion to the inferred degree of source-target correlation. In the experiments, the performance of the proposed algorithm is verified on: 1) sample average approximations of benchmark multiobjective optimization problems under uncertainty and 2) practical multiobjective hyperparameter tuning of deep neural network models. The results show that the proposed algorithm can obtain up to about 73% speedup relative to existing approaches, demonstrating its ability to efficiently tackle real-world multiobjective optimization involving evaluations on large datasets.

关键词： Hypercubes   Fault tolerant systems   Fault tolerance   Reliability   Data centers   Servers   Computer science   Hypercube   double-structure connectivity   fault-tolerance   network reliability  

摘要： Most data center services are finished by the cooperation among the connected servers. However, the malicious attackers always try to divide the network into disconnected components to start some attacks, such as the address resolution protocol (ARP) attack, the denial of service (DoS) attack, the botnet attack, and so on. The connectivity is an excellent indicator to measure the reliability and fault-tolerant ability of the network. Whereas, the traditional connectivity and current conditional connectivity cannot well reflect the fault-tolerant performance of the network when attackers are a block or have a certain structure and the components of the remaining network still have a certain structure. Based on this fact, we propose a new measure: the double-structure connectivity, which can accurately reflect the fault-tolerant ability of the network when attackers are structured and each component of the network has a certain structure after removing the attacked servers. Meanwhile, a hypercube is a high-performance interconnection network that can also be used to design some data center networks. Therefore, we study the double-structure fault-tolerance of the hypercube and determine the double-structure connectivity of distinct structures of the hypercube. Furthermore, we propose algorithms to construct structures of attackers directly to measure the fault-tolerant ability of the hypercube under this attack. Our results can be applied not only to interconnection networks but also to some data center networks.

关键词： Ethics   Education   Computer science   Data science   Philosophical considerations   Information technology   Privacy   ethics   computer science education  

摘要： Editor's notes: The field of ethics is vast and complex, requiring unique skills to ensure ethical outcomes across a person's career and life. This article discusses the objectives, challenges, and lessons learned from teaching a computing ethics course at Colorado State University. -Sudeep Pasricha, Colorado State University, USA -Marilyn Wolf, University of Nebraska-Lincoln, USA

关键词： Training   Computer science   Supervised learning   Psychology   Reinforcement learning   Oral communication   Observers  

摘要： Gustav Fechner's 1860 delineation of psychophysics, the measurement of sensation in relation to its stimulus, is widely considered to be the advent of modern psychological science. In psychophysics, a researcher parametrically varies some aspects of a stimulus and measures the resulting changes in a human subject's experience of that stimulus;doing so gives insight into the determining relationship between a sensation and the physical input that evoked it. This approach is used heavily in perceptual domains, including signal detection, threshold measurement, and ideal observer analysis. Scientific fields, such as vision science, have always leaned heavily on the methods and procedures of psychophysics, but there is now growing appreciation of them by machine learning researchers, sparked by widening overlap between biological and artificial perception [1], [2], [3], [4], [5]. Machine perception that is guided by behavioral measurements, as opposed to guidance restricted to arbitrarily assigned human labels, has significant potential to fuel further progress in artificial intelligence (AI).

关键词： Programming   Robotics   Maker   Pre-service teachers   Teacher education  

摘要： Computer science teaching standards for grades K-8 have been implemented in nearly all U.S. states, and the core subject area teachers (e.g., math, science, English, social studies) have been asked to integrate these standards into their instruction. Thus, it is important that K-8 pre-service teachers of all subjects are both prepared and motivated to teach computer science concepts-such as programming-upon entering the field. However, little is known about how pre-service teachers learn and retain programming knowledge or obtain and sustain their motivation related to programming. Maker-focused educational robotics activities have the potential to both reduce abstract cognitive load and work as motivational tools for STEM learning. The purpose of this study was to examine pre-service teachers' motivational persistence and retention of programming concepts after learning with educational robotics through maker-focused computer science activities. Hands-on maker robotics programming activities were used to teach and motivate pre-service teachers. This quantitative study utilized repeated measures through pre-, post-, and 6-month follow-up surveys and tests. The findings indicated the pre-service teachers' programming comprehension gains exhibited on the posttest deteriorated substantially to near-baseline levels within 6 months of instruction. Conversely, pre-service teachers' motivation related to programming continued to rise after the instruction had concluded. Both the retention of comprehension of programming concepts and motivational persistence findings imply that educator preparation providers should integrate programming instruction throughout their pre-service teacher curricula and support curricular initiatives that call for the integration of computer science instruction across pre-service teacher methods courses to reinforce computer science learning.