As advances in the technologies of predicting protein interactions, huge data sets portrayed as networks have been available. Identification functional modules from such is crucial for understanding principles cellular organization and functions. However, interaction produced by high-throughput experiments are generally associated with high false positives, which makes it difficult to identify accurately. In this paper, we propose a fast hierarchical clustering algorithm HC-PIN based on...

Essential proteins are indispensable for cellular life. It is of great significance to identify essential that can help us understand the minimal requirements life and also very important drug design. However, identification based on experimental approaches typically time-consuming expensive. With development high-throughput technology in post-genomic era, more protein-protein interaction data be obtained, which make it possible study from network level. There have been a series...

In contrast to traditional recommender systems which usually pay attention users' general and long-term preferences, sequential recommendation (SR) can model dynamic intents based on their behaviour sequences suggest the next item(s) them. However, most of existing models learn ranking score an item only its relevance property, personalized user demands in terms different learning objectives, such as diversity, tail novelty or recency, have been played essential roles multi-objective (MOR),...

Abstract This study examined ways in which high school students used mobile devices physics classrooms and after school, the impact of in‐class after‐school technology use on their learning performance interest. We collected data from 803 freshmen China they had for over five months. A fixed‐effects model was employed to control undetected variances. Results indicated that frequently class school. Students also perceived as very useful learning, perception usefulness positively correlated...

Abstract Mobile technology has been increasingly adopted in science education. We generally assume that more innovative use of mobile leads to a greater learning outcome. Yet, there is lack empirical research support this assumption. To fill the gap, we drew upon data from 803 high school students who had used devices for five months physics classrooms. Using SAMR model (ie, Substitution, Augmentation, Modification, and Redefinition), distinguished their uses into two levels: Substitution...

Requirements classification is a significant task for requirements engineering, which time-consuming and challenging. The traditional models usually rely on manual pre-processing have poor generalization capability. Moreover, these ignore the sentence structure syntactic information in requirements. To address problems, we propose an automatic based BERT graph attention network (GAT), called DBGAT. We construct dependency parse trees then utilize GAT mining implicit feature of In addition,...

Vehicle routing problems (VRPs) are essential in logistics. In the literature, many exact and heuristic optimization algorithms have been proposed to solve VRPs. These traditional approaches, however, generally start from scratch ignore experiences of solving related VRPs, which may lead unnecessary computational costs searching repeated reduce efficiency vehicle routing. Recently, transfer (TO) has presented speed up by reusing knowledge learned similarly solved However, existing TO methods...

Spark has grown both in popularity and complexity recent years. In order to use available resources an efficient way, users need understand how the behavior of their applications is affected by size datasets various configuration settings. Indeed, allows specify many parameters understanding impact these choices with respect application execution time not easy. An accurate estimate important for cluster capacity planning and/or runtime scheduling. this work we propose a gray-box approach...

In this work, we propose a novel sidechain structure via an optimized two-way peg protocol for device authentication in the smart community order to overcome limitations of existing approaches. The proposed scheme uses private side blockchains distribute and manage local registration processes, addition mainchain block circulate information record with other systems. More importantly, system prevent worthless injection attack during sharing procedure between main chain blockchains....

MapReduce programming model is widely used for large scale and one-time data-intensive distributed computing, but lacks flexibility efficiency of processing small incremental data. IncMR framework proposed in this paper incrementally new data a set, which takes state as implicit input combines it with Map tasks are created according to splits instead entire while reduce fetch their inputs including the intermediate results map from designate nodes or local nodes. Data locality considered one...

Camera calibration, as a fundamental issue in computer vision, is indispensable many visual surveillance applications. Firstly, calibrated camera can help to deal with perspective distortion of object appearance on image plane. Secondly, makes it possible recover metrics from images which are robust scene or view an gle changes. In addition, cameras, we make use prior information 3D models estimate pose objects and detection tracking more noise occlusions. this paper, propose automatic...

Coarse-grained (CG) models are valuable tools for the study of functions large biomolecules on length and time scales. The definition CG representations huge is always a formidable challenge. In this work, we propose new method called fluctuation maximization coarse-graining (FM-CG) to construct sites biomolecules. defined residual in FM-CG converges maximal value as number increases, allowing an optimal model be rigorously basis maximum. More importantly, developed robust algorithm stepwise...

To improve traffic safety in undersea tunnels, the speed control effect of optical illusion deceleration markings (OIDMs) V-shaped tunnels and their applicability to drivers were explored. In this study, UC-Win/Road software was used build a simulation scenario, Jiaozhou Bay tunnel Qingdao, China, selected as simulated road section. Four kinds OIDMs research objects. According physiological psychological response characteristics visual recognition process vehicle driving parameters, three...

To date, transfer learning (TL) has been successfully applied for enhancing the performance of reinforcement (RL), and many RL (TRL) approaches have proposed in literature. However, most existing TRL consider knowledge between tasks sharing same state-action space. These methods thus may fail cases where available conducting possess heterogeneous spaces, which is common real-world applications. across problem domains challenging since differences lie spaces are natural barriers tasks. This...

Elementary school students often exhibit a variety of conceptions associated with algebraic thinking that their teachers fail to recognize or understand. It is crucial elementary possess knowledge the student and also have abilities address varying states conceptions. Otherwise, who are not provided opportunities think algebraically may continue struggle algebra throughout school. The purpose this study, therefore, was develop provide initial validity evidence for an assessment tool grades....

Parallel/Distributed computing frameworks, such as MapReduce and Dryad, have been widely adopted to analyze massive data. Traditionally, these frameworks depend on manual configuration acquire network proximity information optimize the data placement task scheduling. However, this approach is cumbersome, inflexible or even infeasible in largescale deployments, for example, across multiple datacenters. In paper, we address problem by utilizing Software-Defined Networking (SDN) capability. We...

Evolutionary multitasking (EMT) has attracted much attention in the community of evolutionary computation recently. It intends to improve performance optimization on multiple problems via knowledge learning and transfer across them while processes progress online. Existing EMT paradigms can be classified as explicit (EEMT) implicit (IEMT) according mechanisms adopted transfer. With additional modules, EEMT often brings flexible algorithmic designs effective against IEMT. However, most...

This paper introduces SATformer, a novel Transformer-based approach for the Boolean Satisfiability (SAT) problem. Rather than solving problem directly, SATformer approaches from opposite direction by focusing on unsatisfiability. Specifically, it models clause interactions to identify any unsatisfiable sub-problems. Using graph neural network, we convert clauses into embeddings and employ hierarchical model understand correlation. is trained through multi-task learning approach, using...

The deeper the combination of art and technology, more extensive cooperation between artists technologists. In many cases, creation New Media Art requires However, since is an emerging form, process cocreating two at exploration stage. Especially in areas with underdeveloped there exist problems two, such as a lack complete understanding factors involved reasonable planning for process. Therefore, this study analyzes that affect collaboration creating Art. Common are collected from...