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关键词： Drugs   Predictive models   Magnetic separation   Laplace equations   Bioinformatics   Sodium   Market research   Graph convolutional networks   Computer science   Computational modeling   Drug-drug interactions   directed graphs   graph neural network   magnetic Laplacians   graph signal processing  

摘要： Polypharmacy is a common means of clinical treatments, but detecting drug-drug interactions (DDIs) behind unexpected effects can be costly and faces clinical limitations. Recently, graph neural networks (GNNs) have demonstrated encouraging performance in predicting DDIs. However, most studies overlook the comprehensive aspects of DDIs, such as the coexistence of types of pharmacological changes and the asymmetric roles of drugs. In this article, we define new prediction tasks, taking into account both enhancive or depressive changes and the roles of drugs, and then establish spectral GNNs to predict comprehensive information of DDIs. First, we formally define several tasks, including joint prediction tasks designed to leverage both types and directions. These tasks deduce to sub-tasks in previous studies. Then, we propose a unified framework, the MKMGCN-DDI, via introducing two Magnetic Laplacian matrices to encode comprehension information within DDIs, defining multiple graph filters, and designing multiple-kernel based Magnetic graph convolutional networks (MKMGCN). Experiments across three datasets show that it not only has good adaptability to multiple tasks but also significantly improves results on simple tasks. Case studies on breast neoplasms and lung neoplasms verify its feasibility, as over half of top-10 items are supported.

关键词： Software engineering   Reviews   Software   Oral communication   Ecosystems   Organizations   Computer science   Buildings   Testing   Switches   Journal publication   Conference presentation   Publication for the software engineering community  

摘要： The first journal-first paper presentations in software engineering were held at ICSE in 2015. A decade later journal-first publication in top software engineering journals has become a widely-used means to disseminate research results and has created a steady flow of scientific content to top conferences in the field. We recall the original goals of the journal-first initiative and chart its course over the past 10 years. We conclude with thoughts about how to develop a more consistent journal-oriented publication model for the field of software engineering.

关键词： Formal methods   ACM CS2023   computer-science education  

摘要： Formal Methods (FMs) radically improve the quality of the code artefacts they help to produce. They are simple, probably accessible to first-year undergraduate students and certainly to second-year students and beyond. Nevertheless, in many cases, they are not part of a general recommendation for course curricula, i.e., they are not taught - and yet they are valuable. One reason for this is that teaching "Formal Methods" is often confused with teaching logic and theory. This article advocates what we call FM thinking: the application of ideas from Formal Methods applied in informal, lightweight, practical and accessible ways. We will argue here that FM thinking should be part of the recommended curriculum for every Computer Science student, for even students who train only in that "thinking" will become much better programmers. However, there will be others who, exposed to those ideas, will be ideally positioned to go further into the more theoretical background: why the techniques work, how they can be automated, and how new ones can be developed. Those students would follow subsequently a specialised, more theoretical stream, including topics such as semantics, logics, verification and proof-automation techniques.

关键词： Roads   Planning   Optimization   Costs   Heuristic algorithms   Business   Vehicle dynamics   Complexity theory   Computer science   Computational efficiency   Routing planning   time-dependent road network   dynamic route optimization   fastest path query  

摘要： In the domain of route planning, the critical concern for travel efficiency has shifted towards optimizing travel time over distance due to the rise in congestion and the dynamic nature of modern road networks. Addressing this shift, we introduce Dynamic Route Optimization with Multi-Category Constraints (DROMC) for Point-of-Interest (POI) visits, which seeks to find the most time-efficient path that satisfies a user-defined list of requirements, considering both the spatial and temporal dimensions. This paper proposes a novel approach that leverages a path enumeration algorithm, which iteratively validates the k-fastest paths until all user queries are satisfied, ensuring adherence to time constraints and POI availability. To enhance the algorithm's efficiency, we employ several key methodologies. First, we adapt the kSP algorithm to account for POI-focused path enumeration. We also introduce a Shared Prefix Tree (SPFT) with binary encoding, which significantly improves the storage and retrieval of path information. Moreover, we integrate a grid-based heuristic for quicker computation and implement strategic pruning methods to circumvent redundant calculations and manage POI business hours effectively. Our extensive experiments on real-world networks demonstrate the algorithm's superiority in finding more efficient paths in shorter time frames compared to existing methods.

关键词： Film-based literacy   Media studies   visual literacy   video in school  

摘要： As a high school English and film teacher in the post-quarantine world, Mark Fusco has read about "lost generations" and "learning loss." But he believes these assessments of today's students today are incomplete. What valuable skills did young people actually gain during their time away from school? Fusco has seen a surge in what he calls "film-based literacy." Students' ability to create and assess video content must be better understood and occupy a more central place in our future curricula.

关键词： African Canadian   Black Canadian   Black culture   family members   substance abuse   substance use   substance use disorders  

摘要： While previous research explored the utilization of culturally supportive resources in multiethnic communities, there is a paucity of information regarding culturally relevant resources for Black Canadian family members. The study explored Black family members' experiences and interpretations regarding access to culturally supportive resources for family members and their relatives who suffer from substance use disorders. Black family members are defined as African Canadians, Caribbean Canadians, or Caribbean Blacks. A focused ethnography was conducted with a purposive sample of 26 Black family members in Ontario, Canada. The interviews were conducted from June to September 2021. Seventeen participants originated from parts of Africa, and nine were from different parts of the Caribbean. The participants comprised mothers (n = 5), fathers (n = 2), step-fathers (n = 1), husbands (n = 1), wives (n = 2), uncles (n = 5), aunties (n = 2), siblings (n = 5), in-laws (n = 2), and guardians (n = 1). Leininger's four Phases of Ethnonursing Qualitative Data Analysis were used for data analysis. Three themes were generated: (1) Navigating Existing Options and Resources for Families and Their Relatives;(2) Drawing upon Religion and Spirituality as Perceived Resources;and (3) Call for Culturally Relevant Programs for Substance Use Disorders Harm Reduction. Participants described experiencing a lack of culturally relevant resources and subsequently opting to navigate other resources. One such option was to send their relatives back to their country of origin to access cultural rehabilitation treatment options. There is a significant need for guidelines and policies regarding creating timely access to culturally relevant resources in Canada that support families and their relatives towards harm reduction and recovery outcomes.

关键词： Software development management   Software engineering   Internet   Software   Delays   Graphical models   Employment   Computer science   Systematic literature review   Surveys   Collaboration   coordination   global software development  

摘要： In this retrospective, we reflect on the motivation, findings, and impact of our 2003 paper. We see evidence of influence in increasing the visibility of the topic of global software development (GSD), the use of version data for software engineering research, and using a mixed methods empirical approach. These topics have all continued to grow in importance in software engineering, as revealed by citation counts, but radical changes in business and technical environments have substantially changed how the challenges of GSD manifest. We see evidence of this in the paper's "life cycle," as citation counts grew for its first decade, and declined for its second. We consider this a marker of progress, and a very good thing for the field.

关键词： Software   Data collection   Software engineering   Software reliability   Reliability   Software testing   Software algorithms   Software systems   Genetics   Computer science   Automated test data generation   search-based test generation   fitness function   dynamic data flow analysis   alternating variable method   search-based software engineering  

摘要： Generating test data is a critical component of software testing, essential for ensuring the proper functioning of software systems. Automated test data generation, in particular, can greatly improve the efficiency and accuracy of the testing process. In 1990, the paper "Automated Software Test Data Generation," published in IEEE Transactions on Software Engineering (Korel, 1990), introduced a novel approach to automated test data generation, focusing on actual program execution, fitness function minimization methods, and dynamic data flow analysis. This paper discusses the impact of the 1990 IEEE TSE publication (Korel, 1990) on automated test data generation and software engineering.

关键词： Vectors   Transformers   Recommender systems   Feature extraction   Knowledge graphs   Oral communication   Accuracy   Computer science   Training   Timing   Conversational recommender systems   dialog generation   entity focus   latent variables   recommendation  

摘要： Conversational recommendation is one system that can extract the user's preferences and recommend suitable items in a similar way to human-like responses. Existing methods often use the feature extraction combined with the Transformer model to extract user preferences and make recommendations. However, these methods have two limitations. First, they do not consider the order in which entities appear, thus affecting the extraction of user preferences. Second, the generated responses lack diversity that affects the users' experience to the system. To this end, we propose a conversational recommendation model with User Entity focus and Multi-Granularity latent variable enhancement (UEMG). In UEMG, we design a novel neural network that utilizes Bi-GRU to capture the appearing orders of entities in dialogues, and leverages Transformer to capture the global dependencies of entities, and then combines them to extract user preferences. For the second issue, to improve the diversity of dialogue generation, we propose a multi-granularity latent variable mechanism, which can extract more entities from the context information and the knowledge graphs, respectively. We conducted extensive experiments on publicly available dialogue generation datasets. Experimental results demonstrate that compared to current state-of-the-art methods, UEMG achieves 9.7% improvements in recommendation performance and 23% improvements in dialogue generation.

关键词： Encoding   Decoding   Servers   Resource management   Accuracy   Codes   Vectors   Optimization   Numerical stability   Computer science   Distributed gradient descent   distributed matrix multiplication   binary erasure codes   straggler mitigation   numerical accuracy   fractional repetition codes  

摘要： This paper addresses the gradient coding and coded matrix multiplication problems in distributed optimization and coded computing. We present a computationally efficient coding method which overcomes the drawbacks of the Fractional Repetition Coding gradient coding method proposed by Tandon et al., and can also be leveraged by coded computing networks whose servers are of heterogeneous nature. Specifically, we propose a construction for fractional repetition gradient coding;while ensuring that the generator matrix remains close to perfectly balanced for any set of coding parameters, as well as a low complexity decoding step. The proposed binary encoding avoids operations over the real and complex numbers which inherently introduce numerical and rounding errors, thereby enabling accurate distributed encodings of the partial gradients. We then make connections between gradient coding and coded matrix multiplication. Specifically, we show that any gradient coding scheme can be extended to coded matrix multiplication. Furthermore, we show how the proposed binary gradient coding scheme can be used to construct two different coded matrix multiplication schemes, each achieving different trade-offs.