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Full-Text Articles in Programming Languages and Compilers
Ancr—An Adaptive Network Coding Routing Scheme For Wsns With Different-Success-Rate Links †, Xiang Ji, Anwen Wang, Chunyu Li, Chun Ma, Yao Peng, Dajin Wang, Qingyi Hua, Feng Chen, Dingyi Fang
Ancr—An Adaptive Network Coding Routing Scheme For Wsns With Different-Success-Rate Links †, Xiang Ji, Anwen Wang, Chunyu Li, Chun Ma, Yao Peng, Dajin Wang, Qingyi Hua, Feng Chen, Dingyi Fang
Department of Computer Science Faculty Scholarship and Creative Works
As the underlying infrastructure of the Internet of Things (IoT), wireless sensor networks (WSNs) have been widely used in many applications. Network coding is a technique in WSNs to combine multiple channels of data in one transmission, wherever possible, to save node’s energy as well as increase the network throughput. So far most works on network coding are based on two assumptions to determine coding opportunities: (1) All the links in the network have the same transmission success rate; (2) Each link is bidirectional, and has the same transmission success rate on both ways. However, these assumptions may not be …
Can Syntax Help? Improving An Lstm-Based Sentence Compression Model For New Domains, Liangguo Wang, Jing Jiang, Hai Leong Chieu, Chen Hui Ong, Dandan Song, Lejian Liao
Can Syntax Help? Improving An Lstm-Based Sentence Compression Model For New Domains, Liangguo Wang, Jing Jiang, Hai Leong Chieu, Chen Hui Ong, Dandan Song, Lejian Liao
Research Collection School Of Computing and Information Systems
In this paper, we study how to improve thedomain adaptability of a deletion-basedLong Short-Term Memory (LSTM) neuralnetwork model for sentence compression.We hypothesize that syntactic informationhelps in making such modelsmore robust across domains. We proposetwo major changes to the model: usingexplicit syntactic features and introducingsyntactic constraints through Integer LinearProgramming (ILP). Our evaluationshows that the proposed model works betterthan the original model as well as a traditionalnon-neural-network-based modelin a cross-domain setting.
Infographics: A Practical Guide For Librarians, Darren Sweeper
Infographics: A Practical Guide For Librarians, Darren Sweeper
Sprague Library Scholarship and Creative Works
No abstract provided.
Designing An Intervention For Novice Programmers Based On Meaningful Gamification: An Expert Evaluation, Jenilyn L. Agapito, Ma. Mercedes T. Rodrigo
Designing An Intervention For Novice Programmers Based On Meaningful Gamification: An Expert Evaluation, Jenilyn L. Agapito, Ma. Mercedes T. Rodrigo
Department of Information Systems & Computer Science Faculty Publications
Gamification is defined as the addition of game-like elements and mechanics to non-game contexts to encourage certain desired behaviors. It is becoming a popular classroom intervention used in computer science instruction, including CS1, the first course computer science students take. It is being operationalized to enhance students' learning experience and achievement. However, existing studies have mostly implemented reward-based game elements which have resulted to contrasting behaviors among the students. Meaningful gamification, characterized as the use of game design elements to encourage users build internal motivation to behave in a certain way, is contended to be a more effective approach. The …
Exploratory Analysis Of Discourses Between Students Engaged In A Debugging Task, Ma. Mercedes T. Rodrigo
Exploratory Analysis Of Discourses Between Students Engaged In A Debugging Task, Ma. Mercedes T. Rodrigo
Department of Information Systems & Computer Science Faculty Publications
This paper determined if and how high-performing and low-performing students differed in the language that they used as they collaborated on a debugging task. 180 students worked in pairs to debug 12 small programs with known errors. Students were segregated into high and low achievement levels based on the number of bugs they found. Chat transcripts from the pairs were analyzed using the Linguistic Inquiry and Word Count (LIWC) software. We found that high- and low-performing students only varied in terms of their use of words that implied discrepancy and sadness.