Deep learning predicts real-time parking occupancy using multiple data sources.
problem Predicting real-time parking occupancy in spatio-temporal networks.
method Graph-Convolutional Neural Networks (GCNN) for spatial relations, Recurrent Neural Networks (RNN) with Long-Short Term Memory (LSTM) for temporal features, multiple data sources.
result The model outperforms other methods with an average testing MAPE of 10.6%.
Queuing model predicts truck parking occupancy.
problem Real-time probabilistic forecasting of truck parking occupancy.
method Non-homogeneous queuing model with time-varying service times, verified using empirical data.
result Lower bound for real-time prediction algorithms characterized.
Model predicts parking area states up to 60 mins ahead.
problem Predicting parking area states for urban traffic management.
method Neural Network-based model using real-time and historic data.
result Model outperforms naive models by over 150% at 60 mins prediction.
Paper tackles dynamic pricing in a geometrically decaying environment, achieving better occupancy with lower rates.
problem Minimizing expected loss in a dynamically changing environment with decisions dependent on the data distribution.
method Introduces algorithms for information and loss function settings, using repeated decision deployment to allow mixing of the environment.
result Iteration complexity matches first and zero order stochastic gradient methods up to logarithmic factors.
AI helps Vancouver identify where off-street parking saves time and space.
problem On-street parking inefficiencies and associated costs in Vancouver.
method Developed AI models for on-street and off-street parking, comparing time costs.
result Many areas off-street parking saves time and space, aligning with city goals.
Study shows visual feedback and monetary incentives reduce plugload energy consumption in commercial buildings.
problem Mitigating energy consumption in commercial buildings through occupant plugload control.
method Field experiments with visual feedback and monetary incentives in government and university buildings.
result Mean energy reduction of ~9.52% in office environments and ~21.61% in university environments with visual feedback.
SHARE predicts city-wide parking availability using a hierarchical graph neural network.
problem Predicting city-wide parking availability is challenging due to spatial and temporal autocorrelation.
method SHARE uses a hierarchical graph convolution structure with contextual and soft clustering blocks, a recurrent neural network, and a parking availability approximation module.
result SHARE outperforms state-of-the-art baselines in predicting city-wide parking availability.
Detects parking spaces in parcels using satellite images.
problem Locating parking spaces in urban areas using satellite imagery.
method Used Feature Pyramid based Mask RCNN for localizing parking spaces and vehicles in parking lots.
result Average class accuracy of 97.56% for parking spaces and vehicles.
Study models parking duration using machine learning and interpretable methods.
problem Parking issues in developing countries like India.
method Artificial neural networks (ANNs) for capturing relationships; Garson algorithm and LIME for model interpretation.
result LIME shows higher prediction accuracy and can be universally adopted.
This study predicts parking availability using multi-source data and a self-supervised learning enhanced transformer.
problem Accurate parking availability prediction to support urban planning and management.
method Proposes SST-iTransformer, a self-supervised learning enhanced spatio-temporal inverted transformer, integrating multi-source data.
result SST-iTransformer achieves state-of-the-art performance in parking availability prediction.
The paper defines and analyzes Poissonian occupation times for negative Lévy processes.
problem Analyzing the time spent below zero for Lévy processes with interruptions.
method Introduces Poissonian occupation times for spectrally negative Lévy processes.
result Extends results on continuous observation to interrupted observation.
Here we draw a handlebody picture for the exotic CP^2 # 2(-CP^2) constructed by Akhmedov and Park.
Here we draw a handlebody picture for the exotic CP^2 # 3(-CP^2), constructed by Akhmedov and Park.
In this paper, first we consider the existence and non-existence of Einstein metrics on the topological 4-manifolds $3\mathbb{CP}^2 # k \bar{\mathbb{CP}}^2$ (for k∈11,13,14,15,16,17,18) by using the idea of Răsdeaconu and Şuvaina (2009) and the constructions in Park, Park, and Shin (arXiv:0906.5195v2) and…
In a recent paper, Park constructs certain exotic simply-connected four-manifolds with small Euler characteristics. Our aim here is to prove that the four-manifolds in his constructions are minimal.
Being one of the most important factors of economic growth of the country, innovations became one of the key vectors in Russian economic policy. In this field technology parks are one of the most effective instruments which can provide growth of innovative activity in sectors, regions and economies. In this paper, we m…
NDI learns from expert demonstrations by estimating occupancy measures.
problem Imitation Learning (IL) for complex systems.
method Density estimation of expert's occupancy measure followed by RL.
result NDI achieves state-of-the-art performance on control tasks.
Paper analyzes AI's impact on job tasks, predicting future demands.
problem AI's impact on job tasks and potential technological unemployment.
method Dynamic task shares analysis using ARIMA model on large job postings dataset.
result AI has risen in high wage occupations, predicting future task demands.
FORE evaluates occupancy ratios without requiring Bellman completeness.
problem Offline reinforcement learning occupancy ratio estimation.
method Fitted occupancy-ratio evaluation (FORE) using adjoint Bellman recursion.
result FORE achieves convergence in KL without Bellman completeness.
As a generalization of slant Riemannian maps (Sahin), semi-slant Riemannian maps (Park), almost h-slant submersions (Park 2012), and almost h-semi-slant submersions (Park 2011), we introduce the notion of almost h-semi-slant Riemannian maps from almost quaternionic Hermitian manifolds to Riemannian manifolds. We invest…
In this paper, results of J. Park and of B.D Park and Szabo on simply connected symplectic 4-manifolds are re-proven and extended to non-simply connected manifolds using Luttinger surgeries.
The increasing illegal parking has become more and more serious. Nowadays the methods of detecting illegally parked vehicles are based on background segmentation. However, this method is weakly robust and sensitive to environment. Benefitting from deep learning, this paper proposes a novel illegal vehicle parking detec…
A new method learns continuous occupancy fields efficiently using the Ising model.
problem Efficiently learning continuous occupancy fields for robot navigation.
method Generalizes the Ising model to model continuous occupancy fields, using a unique kernel for range measurements.
result The method is computationally efficient and requires only a small number of hyperparameters.
Subspace clustering aims to find groups of similar objects (clusters) that exist in lower dimensional subspaces from a high dimensional dataset. It has a wide range of applications, such as analysing high dimensional sensor data or DNA sequences. However, existing algorithms have limitations in finding clusters in non-…
In this short paper, in order to price occupation-time options, such as (double-barrier) step options and quantile options, we derive various joint distributions of a mixed-exponential jump-diffusion process and its occupation times of intervals.
New PCA method detects faults using occupation kernels.
problem Fault detection in dynamical systems.
method Occupation kernel PCA for irregularly sampled data.
result Validation of reconstruction error approach for fault detection.
Paper calculates the distribution of time spent below zero in risk models.
problem Analyzing time spent below zero in risk models.
method Analytical expressions for the distribution of occupation times.
result Improved understanding of risk processes by providing distribution formulas.
Paper develops multilingual job classification for ISCO and KZiS.
problem Classifying job advertisements for accurate occupation coding.
method Transformer architecture for hierarchical multi-class classification.
result Hierarchical structure improves prediction accuracy by 1-2 percentage points.
We generalise theorems of Khodorovskiy and Park-Park-Shin, and give new topological proofs of those theorems, using embedded surfaces in the 4-ball and branched double covers. These theorems exhibit smooth codimension-zero embeddings of certain rational homology balls bounded by lens spaces.
In an article from 2008, A. Akhmedov and B. D. Park constructed irreducible symplectic 4-manifolds homeomorphic but not diffeomorphic to the manifolds CP^2#3CP^2bar and 3CP^2#5CP^2bar. These manifolds are constructed by using generalized fibre sums. In this note we describe an explicit splitting of the second (co-)homo…
Study measures gender bias in machine translation using multiple reference points.
problem Measuring and identifying gender bias in machine translation.
method Used an optimal non-biased translator, reference points from occupational statistics and survey.
result Found bias against both genders, but more against women, and found occupations have a greater effect than adjectives.
The Frenet frame generalizes the Park transform for multi-phase circuits.
problem Generalizing the Park transform for multi-phase circuits.
method Using the Frenet frame and Cartan's moving frames.
result The Frenet frame provides a new approach to circuit analysis.
GANs improve building performance model accuracy by integrating occupant behaviors.
problem Discrepancies between design and operation performance in buildings.
method Generative Adversarial Networks (GANs) to learn mixture models combining existing BPMs with occupant behaviors.
result Augmented BPMs significantly outperform existing BPMs in achieving specified performance targets.
Study shows gender bias in occupation classification tasks.
problem Gender bias in machine learning for occupation classification.
method Analyzed impact of explicit gender indicators in semantic representations of biographies.
result True positive rates differ between genders, correlating with existing gender imbalances.
Digital tools may hinder or facilitate multidisciplinary collaboration in occupational health.
problem Challenges in multidisciplinary collaboration in occupational health.
method Study of a precursor SPSTI's digital tools and their impacts.
result Digital tools can act as both brakes and levers for multidisciplinary dynamics.
We show that deformations of a coisotropic submanifold inside a fibrewise entire Poisson manifold are controlled by the L∞-algebra introduced by Oh-Park (for symplectic manifolds) and Cattaneo-Felder. In the symplectic case, we recover results previously obtained by Oh-Park. Moreover we consider the extended de…
A new method estimates SDEs using occupation kernels.
problem Learning multivariate stochastic differential equations (SDEs).
method Two-step procedure: estimate drift, then diffusion. Occupation kernels used in RKHS.
result Validated on simulated and real-world data.
ROCK method generalizes MOCK for learning dynamical systems efficiently.
problem Learning dynamical systems from data efficiently.
method Variational formulation in Reproducing Kernel Hilbert Spaces.
result ROCK method is more computationally efficient and performs better on benchmarks.
Spacematch matches office workers with suitable workspaces based on their preferences.
problem Matching workers with suitable workspaces in ABW environments.
method Developed a web-based mobile app to collect occupant preferences and IoT sensors for real-time environmental feedback.
result Occupant preferences can be segmented and matched to build a recommendation platform.
There are two natural simplicial complexes associated to the noncrossing partition lattice: the order complex of the full lattice and the order complex of the lattice with its bounding elements removed. The latter is a complex that we call the noncrossing partition link because it is the link of an edge in the former. …
ParK efficiently solves kernel ridge regression for large datasets.
problem Large-scale kernel ridge regression efficiency and accuracy.
method Partitioning feature space with random projections and iterative optimization.
result Provably maintains statistical accuracy with reduced space and time complexity.
Method learns SDEs from data snapshots.
problem Learning drift and diffusion of SDEs from data.
method Two-step process: learn drift by expected value, learn diffusion by SDP.
result Validated on examples and simulations.
Study predicts room occupancy using machine learning, achieving high accuracy.
problem Efficient room occupancy management for energy conservation.
method Leveraged diverse machine learning models, focusing on Random Forest.
result Random Forest model achieved highest predictive accuracy.
We find the optimal investment strategy to minimize the expected time that an individual's wealth stays below zero, the so-called {\it occupation time}. The individual consumes at a constant rate and invests in a Black-Scholes financial market consisting of one riskless and one risky asset, with the risky asset's price…
We introduce cylindrical projections to simulate infinite-dimensional occupation flows of diffusions.
problem Computational intractability of infinite-dimensional occupation flows of diffusions.
method Introduce cylindrical projections to approximate the occupation flow via a finite-dimensional system.
result Strong convergence of cylindrical projections to the initial process with derived rates.
A generalized gamification framework is introduced as a form of smart infrastructure with potential to improve sustainability and energy efficiency by leveraging humans-in-the-loop strategy. The proposed framework enables a Human-Centric Cyber-Physical System using an interface to allow building managers to interact wi…
Develops a new calculus for stochastic processes with occupation flows.
problem Analyzing the behavior of stochastic processes with occupation flows.
method Itô calculus for occupied processes, Feynman-Kac approach.
result Unified Markovian lifts for pricing financial derivatives.
We study the role that Hamiltonian and symplectic diffeomorphisms play in the deformation problem of coisotropic submanifolds. We prove that the action by Hamiltonian diffeomorphisms corresponds to the gauge-action of the L∞-algebra of Oh and Park. Moreover we introduce the notion of extended gauge-equivalence …