Context-Aware Conversational Recommendation of Trigger-Action Rules in IoT Programming

2021 ◽  
Vol 31 (10) ◽  
pp. 1517-1538
Author(s):  
Mingxin Zhao ◽  
Qinyue Wu ◽  
Enze Ma ◽  
Beijun Shen ◽  
Yuting Chen
Keyword(s):  
Real Data ◽  
End Users ◽  
User Preferences ◽  
Phase Method ◽  
Semantic Features ◽  
Context Aware ◽  
Two Phase ◽  
The Arts ◽  
Iot Devices ◽  
Trigger Action

Trigger-action (TA) programming is a programming paradigm that allows end-users to automate and connect IoT devices and online services using if-trigger-then-action rules. Early studies have demonstrated this paradigms usability, but more recent work has also highlighted complexities that arise in realistic scenarios. To facilitate end-users in TA programming, we propose AutoTAR, a context-aware conversational recommendation technique for recommending TA rules. AutoTAR leverages a TA knowledge graph to encode semantic features and abstract functionalities of rules, and then takes a two-phase method to recommend TA rules to end-users: during the context-aware recommendation phase, it elicits user preferences from programming context and recommends the top-N rules using a mixed content and collaborative technique; during the conversational recommendation phase, it justifies recommendations by iteratively raising questions and collecting feedback from end-users. We evaluate AutoTAR on Mturk and real data collected from the IFTTT community. The results show that our method outperforms state-of-the-arts significantly — its context-aware recommendation outperforms RecRules by 26% on R@5 and 21% on NDCG@5; its conversational recommendation outperforms LARecommender (a conversational recommender with the LA model) by 67.64% on accuracy. In addition, AutoTAR is effective in solving three problems frequently occurring in TA rule recommendations, i.e., the cold-start problem, the repeat-consumption problem, and the incomplete-intent problem.

Peristaltic Carreau-Yasuda nanofluid flow and mixed heat transfer analysis in an asymmetric vertical and tapered wavy wall channel

2020 ◽  
Vol 1 (1) ◽  
pp. 128-140 ◽  
Author(s):  
Mohammad Hatami ◽  
◽  
D Jing ◽  
Keyword(s):  
Heat Transfer ◽  
Least Square Method ◽  
Weissenberg Number ◽  
Least Square ◽  
Heat Transfer Analysis ◽  
Phase Method ◽  
Nanofluid Flow ◽  
Two Phase ◽  
Nanoparticles Concentration ◽  
The Right

In this study, two-phase asymmetric peristaltic Carreau-Yasuda nanofluid flow in a vertical and tapered wavy channel is demonstrated and the mixed heat transfer analysis is considered for it. For the modeling, two-phase method is considered to be able to study the nanoparticles concentration as a separate phase. Also it is assumed that peristaltic waves travel along X-axis at a constant speed, c. Furthermore, constant temperatures and constant nanoparticle concentrations are considered for both, left and right walls. This study aims at an analytical solution of the problem by means of least square method (LSM) using the Maple 15.0 mathematical software. Numerical outcomes will be compared. Finally, the effects of most important parameters (Weissenberg number, Prandtl number, Brownian motion parameter, thermophoresis parameter, local temperature and nanoparticle Grashof numbers) on the velocities, temperature and nanoparticles concentration functions are presented. As an important outcome, on the left side of the channel, increasing the Grashof numbers leads to a reduction in velocity profiles, while on the right side, it is the other way around.

The Method of Dynamic Reserves Prediction for a Constant Volume Gas Reservoir

2013 ◽  
Vol 275-277 ◽  
pp. 456-461
Author(s):  
Lei Zhang ◽  
Lai Bing Zhang ◽  
Bin Quan Jiang ◽  
Huan Liu
Keyword(s):  
Pressure Drop ◽  
Material Balance ◽  
Production Method ◽  
Gas Production ◽  
Constant Volume ◽  
Phase Method ◽  
Gas Reservoirs ◽  
Two Phase ◽  
Material Balance Method ◽  
Unit Pressure

The accurate prediction of the dynamic reserves of gas reservoirs is the important research content of the development of dynamic analysis of gas reservoirs. It is of great significance to the stable and safe production and the formulation of scientific and rational development programs of gas reservoirs. The production methods of dynamic reserves of gas reservoirs mainly include material balance method, unit pressure drop of gas production method and elastic two-phase method. To clarify the characteristics of these methods better, in this paper, we took two typeⅠwells of a constant volume gas reservoir as an example, the dynamic reserves of single well controlled were respectively calculated, and the results show that the order of the calculated volume of the dynamic reserves by using different methods is material balance method> unit pressure drop of gas production method >elastic two-phase method. Because the material balance method is a static method, unit pressure drop of gas production method and elastic two-phase method are dynamic methods, therefore, for typeⅠwells of constant volume gas reservoirs, when the gas wells reached the quasi-steady state, the elastic two-phase method is used to calculate the dynamic reserves, and when the gas wells didn’t reach the quasi-steady state, unit pressure drop of gas production method is used to calculate the dynamic reserves. The conclusion has some certain theoretical value for the prediction of dynamic reserves for constant volume gas reservoirs.

scholarly journals Protected Gold Nanoparticles with Thioethers and Amines As Surrogate Ligands

2013 ◽  
Vol 2013 ◽  
pp. 1-4 ◽  
Author(s):  
M. Rafiq H. Siddiqui
Keyword(s):  
Gold Nanoparticles ◽  
Variable Temperature ◽  
Size Control ◽  
Analytical Techniques ◽  
High Resolution Electron Microscopy ◽  
Phase Method ◽  
Two Phase ◽  
H Nmr ◽  
Resolution Electron ◽  
Vis Spectroscopy

Dodecyl sulfide, dodecyl amine, and hexylamine were shown to act as surrogate ligands (L) via metastable gold nanoparticles. By collating analytical and spectroscopic data obtained simultaneously, empirical formula Au24L was assigned. These impurity-free nanoparticles obtained in near quantitative yields showing exceptional gold assays (up to 98%Au) were prepared by a modification of the two-phase method. Replacement reactions on the Au24L showed that Au:L ratios may be increased (up to Au55:L (L= (H25C12)2S)) or decreased (Au12:L (L= H2NC12H25and H2NC6H13)) as desired. This work encompassing the role of analytical techniques used, that is, elemental analysis, variable temperature1H NMR, FAB mass spectrometry, UV-Vis spectroscopy, thin film X-ray diffraction, and high-resolution electron microscopy (HREM) has implications in the study of size control, purity, stability, and metal assays of gold nanoparticles.

An Efficient Two-phase Method for Prime Compilation of Non-clausal Boolean Formulae

2021 ◽  
Author(s):  
Weilin Luo ◽  
Hai Want ◽  
Hongzhen Zhong ◽  
Ou Wei ◽  
Biqing Fang ◽  
...  
Keyword(s):  
Phase Method ◽  
Two Phase

A New Two-Phase Method for Damage Detection in Skeletal Structures

2018 ◽  
Vol 43 (S1) ◽  
pp. 49-65 ◽  
Author(s):  
A. Kaveh ◽  
S. R. Hosseini Vaez ◽  
P. Hosseini ◽  
M. A. Fathali
Keyword(s):  
Damage Detection ◽  
Phase Method ◽  
Two Phase ◽  
Skeletal Structures

scholarly journals Context-Aware Community Construction in Proximity-Based Mobile Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-18 ◽  
Author(s):  
Na Yu ◽  
Qi Han
Keyword(s):  
Social Networking ◽  
Mobile Devices ◽  
Mobile Networks ◽  
Context Aware ◽  
Two Phase ◽  
Space And Time ◽  
Shared Information ◽  
Influence Graph ◽  
Social Applications ◽  
Share Information

Sensor-equipped mobile devices have allowed users to participate in various social networking services. We focus on proximity-based mobile social networking environments where users can share information obtained from different places via their mobile devices when they are in proximity. Since people are more likely to share information if they can benefit from the sharing or if they think the information is of interest to others, there might exist community structures where users who share information more often are grouped together. Communities in proximity-based mobile networks represent social groups where connections are built when people are in proximity. We consider information influence (i.e., specify who shares information with whom) as the connection and the space and time related to the shared information as the contexts. To model the potential information influences, we construct an influence graph by integrating the space and time contexts into the proximity-based contacts of mobile users. Further, we propose a two-phase strategy to detect and track context-aware communities based on the influence graph and show how the context-aware community structure improves the performance of two types of mobile social applications.

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