Distributionally Robust Semi-Supervised Learning for People-Centric Sensing

Semi-supervised learning is crucial for alleviating labelling burdens in people-centric sensing. However, human-generated data inherently suffer from distribution shift in semi-supervised learning due to the diverse biological conditions and behavior patterns of humans. To address this problem, we propose a generic distributionally robust model for semi-supervised learning on distributionally shifted data. Considering both the discrepancy and the consistency between the labeled data and the unlabeled data, we learn the latent features that reduce person-specific discrepancy and preserve task-specific consistency. We evaluate our model in a variety of people-centric recognition tasks on real-world datasets, including intention recognition, activity recognition, muscular movement recognition and gesture recognition. The experiment results demonstrate that the proposed model outperforms the state-of-the-art methods.Comment: 8 pages, accepted by AAAI201

A Comprehensive Study on Knowledge Graph Embedding over Relational Patterns Based on Rule Learning

Knowledge Graph Embedding (KGE) has proven to be an effective approach to solving the Knowledge Graph Completion (KGC) task. Relational patterns which refer to relations with specific semantics exhibiting graph patterns are an important factor in the performance of KGE models. Though KGE models' capabilities are analyzed over different relational patterns in theory and a rough connection between better relational patterns modeling and better performance of KGC has been built, a comprehensive quantitative analysis on KGE models over relational patterns remains absent so it is uncertain how the theoretical support of KGE to a relational pattern contributes to the performance of triples associated to such a relational pattern. To address this challenge, we evaluate the performance of 7 KGE models over 4 common relational patterns on 2 benchmarks, then conduct an analysis in theory, entity frequency, and part-to-whole three aspects and get some counterintuitive conclusions. Finally, we introduce a training-free method Score-based Patterns Adaptation (SPA) to enhance KGE models' performance over various relational patterns. This approach is simple yet effective and can be applied to KGE models without additional training. Our experimental results demonstrate that our method generally enhances performance over specific relational patterns. Our source code is available from GitHub at https://github.com/zjukg/Comprehensive-Study-over-Relational-Patterns.Comment: This paper is accepted by ISWC 202

Complex Organic Molecules Formation in Cold Cores on Stochastically Heated Grains

We investigate the roles of stochastic grain heating in the formation of complex organic molecules (COMs) in cold cores, where COMs have been detected. Two different types of grain-size distributions are used in the chemical models. The first one is the MRN distribution, and the second one considers grain coagulation to study its effects on the chemical evolution in these environments. The macroscopic Monte Carlo method is used to perform the two-phase chemical model simulations. We find that (1) grain coagulation can affect certain gas-phase species, such as CO$_2$ and N$_2$H$^+$, in the cold core environments, which can be attributed to the volatile precursors originating from the small grains with temperature fluctuations; (2) grains with radii around 4.6 $\times$ 10$^{-3}$ $\mu$m contribute most to the production of COMs on dust grains under cold core conditions, while few species can be formed on even smaller grains with radii less than 2 $\times$ 10$^{-3}$ $\mu$m; (3) COMs formed on stochastically heated grains could help explain the observed abundances of gas-phase COMs in cold cores.Comment: 15 pages, 10 figures, 3 tables. Accepted by MNRA

The Application Of The IoT For Minimizing Consumption In Smart Home

Excessive consumption leads to 7 trends of crises, including destruction of the atmosphere, energy crisis, social decline and conflicts. Over consumption also deteriorates human health. To reduce excessive consumption not only can improve health, it can also secure home safety and less energy consumption. The reducing over consumption can benefit human health and environmental protection. This motivates us to devise an innovative smart home App (SHA). After a survey to potential users, it reveals that the new features can help reduce the excessive consumption and deterioration of the human health as well as the transportation, healthcare and destruction of earth environment. Enterprises can also achieve their social responsibility through the implementation and popularization of the SHA as soon as possible

Different Kinds of Singular and Nonsingular Exact Traveling Wave Solutions of the Kudryashov-Sinelshchikov Equation in the Special Parametric Conditions

In this paper, by using the integral bifurcation method, we studied the Kudryashov-Sinelshchikov equation. In the special parametric conditions, some singular and nonsingular exact traveling wave solutions, such as periodic cusp-wave solutions, periodic loop-wave solutions, smooth loop-soliton solutions, smooth solitary wave solutions, periodic double wave solutions, periodic compacton solutions, and nonsmooth peakon solutions are obtained. Further more, the dynamic behaviors of these exact traveling wave solutions are investigated. It is found that the waveforms of some traveling wave solutions vary with the changes of parameters

Topology of nonlinearly charged black hole chemistry via massive gravity

The classification of critical points of charged topological black holes (TBHs) in anti-de Sitter spacetime (AdS) under the Power Maxwell Invariant (PMI)-massive gravity is accomplished within the framework of black hole chemistry (BHC). Considering the grand canonical ensemble (GCE), we show that $d=4$ black hole have only one topological class, whereas $d\ge 5$ black holes belong to two different topology classes. Furthermore, the conventional critical point characterized by negative topological charge coincides with the maximum extreme point of temperature; and the novel critical point featuring opposite topological charge corresponds to the minimum extreme point of temperature. With increasing pressure, new phases emerge at the novel critical point while disappearing from the conventional one. Moreover, a atypical van der Waals (vdW) behavior is found in $d\ge 6$ dimensions, and the anomaly disappears at the traditional critical point. In the limit of nonlinearity parameter $s\to1$, different topology classes are only obtained in the GCE and they may not exist within the canonical ensemble. With the absence of electric potential $\Phi$, the neutral TBHs share the same topological classification results as the charged TBHs in the GCE of Maxwell-massive gravity.Comment: 16pages,22 figure

Joule-Thomson expansion of charged dilatonic black holes

Based on the Einstein-Maxwell theory, the Joule-Thomson (J-T) expansion of charged dilatonic black holes (the solutions are neither flat nor AdS) in $(n+1)$-dimensional spacetime is studied herein. To this end, we analyze the effects of the dimension $n$ and dilaton field $\alpha$ on J-T expansion. An explicit expression for the J-T coefficient is derived, and consequently, a negative heat capacity is found to lead to a cooling process. In contrast to its effect on the dimension, the inversion curve decreases with charge $Q$ at low pressures, whereas the opposite effect is observed at high pressures. We can observe that with an increase in the dimension $n$ or parameter $\alpha$, both the pressure cut-off point and the minimum inversion temperature $T_{min}$ change. Moreover, we analyze the ratio $T_{min}/T_{c}$ numerically and discover that the ratio is independent of charge; however, it depends on the dilaton field and dimension: for $n=3$ and $\alpha=0$, the ratio is 1/2. The dilaton field is found to enhance the ratio. In addition, we identify the cooling-heating regions by investigating the inversion and isenthalpic curves, and the behavior of the minimum inversion mass $M_{min}$ indicates that this cooling-heating transition may not occur under certain special conditions