Random Forest outperforms other IDS algorithms in smart grids.
problem Security vulnerabilities in smart grids.
method Comparison of four data mining algorithms (Random Forest, SVM, Neural Network, and KNN) in detecting attacks.
result Random Forest outperforms other algorithms in terms of detection accuracy and efficiency.
Techniques for sampling and visualizing generative model latent spaces.
problem Visualizing and sampling latent spaces of generative models.
method Spherical linear interpolation, J-Diagrams, MINE grids, bias-corrected vectors, synthetic vectors, binary classification.
result Improved visualization and sampling techniques for generative models.
Paper uses DL and image embedding to classify power grid disturbances.
problem Classifying transient disturbances in power grids.
method Transformed time series data into images using Gramian Angular Field, then applied CNN and RNN for classification.
result DL algorithms outperform traditional data mining methods in power grid disturbance classification.
DE outperforms grid search for defect predictor tuning.
problem Finding optimal parameters for defect predictors.
method Compared differential evolution (DE) to grid search for parameter tuning.
result DE was over 210 times faster than grid search.
CURIE uses cellular automata to detect concept drift in data streams.
problem Detecting changes in data distribution (concept drift) in data streams.
method CURIE represents data stream distribution in a cellular automata grid and uses its neighborhood rule to detect changes.
result CURIE, when hybridized with base learners, performs competitively in detection metrics and classification accuracy.
Bayesian deep learning improves geostatistical mapping with auxiliary data.
problem Traditional geostatistical methods are limited in feature learning and uncertainty estimation.
method Deep neural networks learn complex relationships from auxiliary data for probabilistic mapping.
result Deep learning produces detailed, probabilistic maps with uncertainty estimates.
Chronnet models spatiotemporal data using chronological networks.
problem Handling large spatiotemporal datasets efficiently.
method Chronnet: Grid-based network model representing events chronologically.
result Chronnet captures frequent patterns, spatial changes, outliers, and clusters.
Paper details Hilbert-curve for high-performance data mining.
problem Efficiently mapping multi-dimensional data to one dimension.
method Defines Hilbert-curve using finite automaton and context-free grammar.
result Cache-oblivious algorithms for matrix operations and clustering.
Lin-DBSCAN is a fast density-based clustering algorithm for spatial data.
problem Efficient clustering of large datasets without prior knowledge of cluster number and shape.
method Grid-based scan and merge approach to a discrete density model of DBSCAN.
result Lin-DBSCAN outperforms DBSCAN in efficiency and validity for spatial data clustering.
Game-theoretic analysis of mining gaps in blockchain systems.
problem Strategic mining behavior and its impact on blockchain stability.
method Game-theoretic model and Nash equilibrium analysis.
result Mining gaps can destabilize blockchain systems, especially with decreasing block rewards.
Predicts coal mine seismic events up to 8 hours in advance.
problem Early detection of dangerous seismic events in coal mines.
method Ensemble machine learning models trained on various features.
result Best model achieved 0.939 AUC.
We present a grid diagram analogue of Carter, Rieger and Saito's smooth movie theorem. Specifically, we give definitions for grid movies, grid movie isotopies and present a definition of grid planar isotopy as a particular subset of the grid diagram moves: stabilization, destabilization and commutation. We show that gr…
Alpha-GPT mines new trading signals with human-AI interaction.
problem Mining new alphas for effective trading signals.
method Human-AI interaction and prompt engineering algorithmic framework.
result Demonstrates Alpha-GPT's effectiveness in generating creative, insightful, and effective alphas.
The paper explores how mining costs, rewards, and blockchain security are interconnected.
problem Understanding the interdependencies between mining costs, mining rewards, and blockchain security.
method Theoretical derivation and empirical analysis using daily crypto market data and autoregressive distributed lag approach.
result Cryptocurrency price and mining rewards are intrinsically linked to blockchain security outcomes.
Data preprocessing improves data quality for robust data mining.
problem Noisy and incomplete data hinders data mining models.
method Overview of data cleaning, transformation, and preprocessing methods.
result Preprocessing significantly affects data mining model performance.
This paper categorizes and analyzes existing outlying aspect mining methods.
problem Finding unique features in data objects that differ from others.
method Grouping and analyzing existing outlying aspect mining approaches in three categories.
result Comparison of strengths, weaknesses, and time complexities of different techniques.
Game theory shows miners' hardware improvements don't centralize mining.
problem Decentralization of cryptocurrency mining.
method Game-theoretical model of mining efficiency and competition.
result Advancements in mining hardware efficiency do not lead to centralization.
The paper introduces triple grid diagrams to construct Lagrangian surfaces in complex projective space.
problem Constructing Lagrangian surfaces in complex projective space.
method Defining and analyzing triple grid diagrams to determine Lagrangian caps and surfaces.
result Triple grid diagrams can determine closed Lagrangian surfaces in CP2 under certain conditions. DataLearner simplifies data mining on Android devices.
problem Lack of general-purpose data-mining tools for mobile devices.
method Augments Weka engine with Charles Sturt University algorithms, providing 40 mining algorithms.
result Delivers classification accuracy similar to PCs/laptops with acceptable speed and battery life.
Half grid diagrams prove every link can be represented by a special type of grid diagram.
problem Representing links using grid diagrams and related invariants.
method Defining half grid diagrams and constructing canonical pairs, proving equivalence to Jones' construction, relating to classical link invariants.
result Established a new method to relate the oriented Thompson index to classical link invariants and provided bounds for knot invariants.
Agent-based model simulates Bitcoin mining economics.
problem Modeling the economics of Bitcoin mining.
method Agent-based artificial market model of Bitcoin mining and transactions.
result Model reproduces key financial features of Bitcoin.
Grid homology confirms the Upsilon invariant in knot theory.
problem Verifying the equivalence of Upsilon invariants in knot theory.
method Reconstructed Upsilon invariant using grid homology and proved equivalence.
result Upsilon invariants in knot Floer and grid homology are equivalent.
GridPyM handles grid diagrams for knot theory.
problem Handling grid diagrams for knot theory.
method Generates and simplifies grids, models local transformations.
result Models local transformations between grid diagrams.
This paper analyzes the profitability of selfish mining on blockchain, considering the risk of ruin.
problem The profitability of selfish mining on blockchain, considering the risk of ruin.
method Formulated a stochastic model and used tools from applied probability and analysis to determine expected profit.
result Explicit expressions for expected profit under different scenarios were derived, identifying conditions for selfish mining as a strategic advantage.
Grid homology theory for spatial graphs extends skein sequence.
problem No specific problem stated; focuses on extending a sequence.
method Defined grid homology theory for spatial graphs and extended skein sequence.
result Skein exact sequence extended to grid homology for spatial graphs.
New method finds grid diagrams for many fibered knots.
problem Detecting fibered knots using grid diagrams.
method Developed an efficient method to identify grid diagrams with unique maximal Alexander grading states.
result Found suitable grid diagrams for 5385 of 5397 fibered prime knots with crossing number ≤ 13.
Extends knot invariant to filtered grid complexes.
problem Knot invariants and grid complexes.
method Combining Ozsváth-Szabó-Stipsicz crossing-change maps with Alishahi-Eftekhary l(K) invariant.
result Combinatorial formulation of knot invariant.
MINE uses neural networks to estimate mutual information efficiently.
problem Estimating mutual information between high-dimensional variables.
method Gradient descent over neural networks for mutual information estimation.
result MINE is linearly scalable in dimensionality and sample size, and is strongly consistent.
Grid homology properties for MOY graphs studied.
problem Defining and studying properties of grid homology for MOY graphs.
method Defined grid homology from Harvey and O'Donnol's work. Studied properties using oriented skein relation, edge contraction, and parallel edge unification.
result Properties of grid homology for MOY graphs were studied and defined.
Paper mines rank data patterns from rankings.
problem Mining rank data patterns from rankings.
method Proposes algorithms for frequent rankings and dependencies.
result Experimental validation of algorithms on synthetic and real data.
Agricultural research has been profited by technical advances such as automation, data mining. Today, data mining is used in a vast areas and many off-the-shelf data mining system products and domain specific data mining application soft wares are available, but data mining in agricultural soil datasets is a relatively…
Grid homology invariant proved for lens space links.
problem Proving combinatorial invariance of grid homology for lens space links.
method Combining combinatorial methods with sign assignments to prove invariance.
result Grid homology is a link invariant for lens space links.
LetSIP learns relevant patterns for user interests in data mining.
problem Redundancy in pattern mining makes it hard for analysts to identify relevant patterns.
method Combines pattern sampling with interactive data mining, using user feedback to learn sampling distribution.
result Favourable trade-offs in quality-diversity and exploitation-exploration compared to existing methods.
New trading strategy beats traditional grid in crypto markets.
problem Low expected return of traditional grid trading strategy.
method Dynamic Grid Trading (DGT) strategy that adapts to market conditions.
result DGT strategy outperforms traditional grid and buy-and-hold strategies.
New method constructs moduli spaces of Lagrangian surfaces in CP^2 from grid diagrams.
problem Constructing explicit examples of triple grid diagrams for Lagrangian surfaces in CP^2.
method Elegant geometric construction reducing to linear algebra.
result Explicit construction of moduli space of triple grid diagrams.
Develops equivariant grid homology for strongly invertible knots.
problem Invariants of strongly invertible knots.
method Equivariant grid diagrams and mapping cones.
result Equivariant unknotting numbers and genus bounds.
This paper tracks coin circulation in Bitcoin to identify miners and analyze mining pool structures.
problem Identifying and understanding Bitcoin miners and their profit distribution schemes.
method Constructs fresh coin circulation networks and uses a heuristic algorithm to compare networks from different mining pools.
result Infers common profit distribution schemes of Bitcoin mining pools and observes an increasing trend in miner numbers.
Computes homology of an obstruction chain complex in grid homology.
problem Computing the homology of an obstruction chain complex in grid homology.
method Defined and computed the homology of the obstruction chain complex of the full grid.
result Results about the existence of sign assignments in grid homology.
Study shows Bitcoin mining with surplus electricity can boost KEPCO's financial stability.
problem Improving energy resource efficiency and reducing KEPCO's debt.
method Utilized surplus electricity for Bitcoin mining using Antminer S21 XP Hyd, analyzed with Random Forest Regressor and Long Short-Term Memory models.
result Bitcoin mining with surplus electricity generates economic revenue, minimizes energy loss, and resolves payment issues for KEPCO.
Grid homology shows knot unknotting lower bound.
problem Knot unknotting number determination
method Grid homology analysis
result Torsion homology classes order bounds unknotting number
SKI accelerates GP inference with sparse grids to handle higher dimensions.
problem SKI scales poorly in high dimensions due to dense grid size.
method Sparse grids within SKI framework, novel matrix-vector multiplication algorithm.
result SKI can be scaled to higher dimensions while maintaining accuracy.
The paper develops algorithms to accurately identify power grid topology.
problem Identifying the exact topology of a power grid in real-time.
method Graphical model framework for topology estimation using voltage measurements.
result Exact extraction of operational topology is theoretically guaranteed for grid topologies without three-node cycles.
This work improves deep metric learning by online soft mining and class-aware attention.
problem Slow convergence and poor performance due to a large fraction of trivial samples in deep metric learning.
method Online Soft Mining (OSM) and Class-Aware Attention (CAA) to select and focus on relevant samples.
result Significantly outperforms state-of-the-art methods on fine-grained visual categorization and video-based person re-identification datasets.
System detects power grid health using AI and machine learning.
problem Detecting and preventing power grid malfunctions.
method Artificial intelligence, machine learning, recurrent neural networks, SVM, LSTM.
result High accuracy in detecting grid health, scalable for complex architectures.
A new framework for mining high utility patterns in interval-based sequences.
problem Mining patterns in events that persist over varying time intervals and considering event utility.
method Integrates utility into interval-based sequences and proposes HUIPMiner algorithm with pruning strategy.
result HUIPMiner efficiently finds high utility patterns in real datasets.
This paper improves image generation models using a multi-grid method.
problem Improving image generation models.
method A multi-grid method for learning energy-based generative ConvNet models.
result The multi-grid method outperforms traditional models.
A new model for efficient sequential pattern mining without specific encoding schemes.
problem Mining relevant sequential patterns efficiently and effectively.
method Subsequence interleaving model based on probabilistic sequence database.
result Efficient inference through submodular optimization, resulting in low spuriousness and redundancy.
Data-driven method estimates urban MV and LV grid topology using smart meter data.
problem Reliability issues in urban distribution grids due to distributed energy resources.
method Probabilistic graphical model with group lasso regularization.
result Highly accurate topology estimation in various grid configurations.