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关键词： Computer science   Quantum chemistry   Quantum simulation  

摘要： Quantum computing is moving beyond its early stage and seeking for commercial applications in chemical and biomedical sciences. In the current noisy intermediate-scale quantum computing era, the quantum resource is too scarce to support these explorations. Therefore, it is valuable to emulate quantum computing on classical computers for developing quantum algorithms and validating quantum hardware. However, existing simulators mostly suffer from the memory bottleneck so developing the approaches for large-scale quantum chemistry calculations remains challenging. Here we demonstrate a high-performance and massively parallel variational quantum eigensolver (VQE) simulator based on matrix product states, combined with embedding theory for solving large-scale quantum computing emulation for quantum chemistry on HPC platforms. We apply this method to study the torsional barrier of ethane and the quantification of the protein-ligand interactions. Our largest simulation reaches 1000 qubits, and a performance of 216.9 PFLOP/s is achieved on a new Sunway supercomputer, which sets the state-of-the-art for quantum computing emulation for quantum chemistry.

关键词： Statistical tests  

摘要： This paper presents general equations of environmental issues, environmental quality and environmental destruction. The paper employed the concepts of the Ideal Gas equation, Malthus model, IPAT model and population dynamics to relate human population and resource depletion in order to estimate environmental issues over time. This resulted in the generation of three equations;equations for estimating environmental issues, environmental quality and environmental destruction. The dataset on global population growth and resource records was obtained from World Bank and Food and Agricultural Organisation Indicators to test and validate the equations. The findings of the study demonstrated that the models are ecologically efficient and sound. However, the only limitation of the models is that they are resource, population and time-dependent. © 2023, The Authors. All rights reserved.

关键词： Teacher professional development   computer science online   teacher knowledge and skills   teacher recommendations  

摘要： Based on a current Research to Practice Partnership (RPP) between a southeastern public university and a state virtual public school in the United States, ten high school teachers from a virtual school who teach Computer Science (CS) online participated in a summer workshop to collaborate through a participatory action research project regarding design, facilitation, and evaluation strategies to be included in effective professional development. The questions were posed through an online collaborative Jamboard during the summer workshop. The teacher posts were qualitatively analyzed to identify common themes. Recommendations for professional development on design included CS content, how to teach CS, and CS tools and activities. For facilitation, they recommended resources for supplemental instruction and feedback tools for providing feedback in various modalities and a tool repository. For assessment, they recommended content knowledge assessments, including lab assignments, single and pair programming, and coding assessments. Overall recommendations for a professional development course to teach CS online were also offered.

关键词： Tensors   Matrix decomposition   Computer science   Task analysis   Knowledge discovery   Data engineering   Computer vision   Tensor factorization   tensor-train   uncertain data   interval-valued data  

摘要： In many fields of computer science, tensor decomposition techniques are increasingly being adopted as the core of many applications that rely on multi-dimensional datasets for implementing knowledge discovery tasks. Unfortunately, a major shortcoming of state-of-the-art tensor analyses is that, despite their effectiveness when the data is certain, these operations become difficult to apply, or altogether inapplicable, in the presence of uncertainty in the data, a circumstance common to many real-world scenarios. In this paper we propose a way to address this issue by extending the known Tensor-Train technique for tensor factorization in order to deal with uncertain data, here modeled as intervals. Working with interval-valued data, however, presents numerous challenges, since many algebraic operations that form the building blocks of the factorization process, as well as the properties that make these procedures useful for knowledge discovery, cannot be easily extended from their scalar counterparts, and often require some approximation (including, though it is not only the case, for keeping computational costs manageable). These challenges notwithstanding, our proposed techniques proved to be reasonably effective, and are supported by a thorough experimental validation.

关键词： 大数据   计算机科学与技术   人工智能   课程体系  

摘要： 大数据时代,对计算机科学与技术专业学生大数据应用能力的培养已成为其复杂工程能力培养的重要且势在必行的目标。结合人工智能在大数据下的实际应用,对面向大数据应用能力培养的计算机科学与技术专业人工智能课程体系改革进行初步探索,让计算机科学与技术专业学生对大数据应用有系统、清晰的认识,为培养具有大数据应用能力的计算机科学与技术专业人才提供支持,为计算机科学与技术专业培养具有复杂工程能力的应用型人才提供思路。

关键词： 计算机技术   实践教学   模块化   复合架构  

摘要： 阐述计算机技术课程体系的设计,在课程设计中增加了研究性、创新性、综合性的内容,探讨复合架构的课程体系教学实践,包括分层次、多形式、模块化的实践教学。

关键词： Indexes   Heuristic algorithms   Costs   Computer science   Computational efficiency   Social networking (online)   Data mining   Dynamic set similarity join   log filter   adaptive method  

摘要： set similarity join finds all pairs of similar sets from two collections of sets. It has many real world applications, such as personalized recommendation and community mining. In this paper, we study the problem of computing the similarity join in a dynamic context, where the sets are updated dynamically. This, however, is inefficient with the state-of-the-art join methods, because they usually assume that data collections are static and have to compute the join result from scratch whenever a set is updated. To address this issue, we propose ALJoin, an adaptive filtering approach that computes the join result incrementally based on the update logs. We first investigate the effect of set updates on the similarity values, and on this basis we propose to build a neighborhood index for each set. The neighborhood index of a specific set consists of any other sets that can be transformed into its similar sets within a threshold number of update operations. ALJoin then uses this index to effectively identify both similar and dissimilar set pairs based on their update logs. To efficiently build the neighborhood index, we devise several filtering techniques and propose a lazy-forward method to reduce the computational cost. In addition, to improve the efficiency on varying workloads, we propose an analytical cost model, and design an online algorithm with performance guarantees to dynamically consolidate the update logs and adapt the neighborhood indexes. We evaluated our method using four real-world datasets. Experimental results show that our approach outperforms existing methods by up to 3:7 x .

关键词： Vehicles   Roads   Servers   Indexes   Maintenance engineering   Computer science   Euclidean distance   Location-based service   ridesharing   order dispatch   query processing   optimization  

摘要： the continued proliferation of mobile Internet and geo-locating technologies, carpooling as a green transport mode is widely accepted and becoming tremendously popular worldwide. In this paper, we focus on a popular carpooling service called ride hitching, which is typically implemented using a publish/subscribe approach. In a ride hitching service, drivers subscribe ride orders published by riders and continuously receive matching ride orders until one is picked. The current systems (e.g., Didi Hitch) adopt a threshold-based approach to filter ride orders. That is, a new ride order will be sent to all subscribing drivers whose planned trips can match the ride order within a pre-defined detour threshold. A limitation of this approach is that it is difficult for drivers to specify a reasonable detour threshold in practice. In addressing this problem, we propose a novel type of top -k subscription queries called Top -k Ride Subscription (TkRS) query, which continuously returns the best k ride orders that match drivers' trip plans to them. We propose two efficient algorithms to enable the top -k result maintenance. We also design a novel hybrid grid index and a two-level buffer structure to efficiently track the top -k results for all TkRS queries. Finally, extensive experiments on real-life datasets suggest that our proposed algorithms are capable of achieving desirable performance in practical settings.

摘要： Most programs in computer science undergraduate programs have evolved from a mathematics program, an engineering program, or some other combination. In computer science education, we will often exploit problems from mathematics with computational solutions to introduce and develop a deep understanding of computational concepts and skills related to program development and analysis. However, it needs to be clarified the degree to which students in undergraduate computer science programs see this connection between what they are learning and the role that mathematics can play in increasing the understanding of that learning. Do they view the mathematics they encounter as one of the unavoidable burdens that the major makes them endure to get a degree but will not need much after graduation? Or do they see mathematical learning and inventive thinking as something that they will need to do on a continuing basis even after graduation? The authors developed an instrument that could be used to gather evidence to understand better how our students look at the role of mathematics in their computer science courses and projects. Beginning in the fall of 2021 a survey instrument was developed and administered to students primarily at Haverford College. Students who completed the initial prototype survey were enrolled in an accelerated CS1-CS2 course where they had experience with programming before attending college. It is also assumed that they have been exposed to mathematics throughout their education. It should also be clear that in this context mathematics is defined expansively to include algebraic and other numerical manipulations of data, as well as problem-solving techniques to divide and conquer complicated problems, appreciating and understanding the use of abstraction [2], reasoning about the state of various parts of computation through the out the execution process, as well as this distinction between verification by proof versus testing. At Drexel University, stud