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Showing 1-25 of 3,110 resultsfor "Index Terms":Side Of The Tree
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An Algorithm for Obtaining Simplified Prime Implicant Sets in Fault-Tree and Event-Tree Analysis
IEEE Transactions on Reliability
Cited by: Papers (4)
Some fault trees or event trees use NOT logic in expressing an accident sequence. The number of prime implicant sets (PIS), a generalization of a minimal cut set and includes logical NOT as well as AND and OR, is apt to exceed general computer capacity. In order to deal with this problem, this paper assumes that component failure probability is far smaller than component success probability. Three...Show More
Enhanced Outsourced and Secure Inference for Tall Sparse Decision Trees
Andrew Quijano;Spyros T. Halkidis;Kevin Gallagher;Kemal Akkaya;Nikolaos Samaras
2024 IEEE International Performance, Computing, and Communications Conference (IPCCC)
Year: 2024 | Conference Paper |
A decision tree is an easy-to-understand tool that has been widely used for classification tasks. On the one hand, due to privacy concerns, there has been an urgent need to create privacy-preserving classifiers that conceal the user’s input from the classifier. On the other hand, with the rise of cloud computing, data owners are keen to reduce risk by outsourcing their model, but want security gua...Show More
The longest side elimination solution for solving Steiner minimum tree problems
The 2011 International Conference on Advanced Mechatronic Systems
Year: 2011 | Conference Paper |
The Steiner minimum tree (SMT) problem is one of the classic nonlinear combinatorial optimization problems for centuries. A novel solution, longest side elimination solution method (LSEM), is proposed in this paper. Firstly, the minimum spanning trees is defined as convex road and external side. Secondly, LSESM is constructed for solving the full SMT by using Melzak geometric composition principle...Show More
Leveraging Ensemble Learning for Side Channel Analysis on Masked AES
Feng Gao;Baolei Mao;Lingjuan Wu;Zongmin Wang;Dejun Mu;Wei Hu
2021 7th International Conference on Computer and Communications (ICCC)
Year: 2021 | Conference Paper |
Cited by: Papers (1)
Symmetric cryptographic functions are known to leak secret information through power side channels. Although masking provides an effective mitigation to such leakage, these protection designs are vulnerable to advanced side-channel analysis based on machine learning. In this work, we propose a framework to leverage ensemble learning for power analysis on a masked AES implementation. Before the key...Show More
Using all data to generate decision tree ensembles
This paper develops a new method to generate ensembles of classifiers that uses all available data to construct every individual classifier. The base algorithm builds a decision tree in an iterative manner: The training data are divided into two subsets. In each iteration, one subset is used to grow the decision tree, starting from the decision tree produced by the previous iteration. This fully g...Show More
The storage structure on the data block of the current blockchain systems is still a linked list. This traditional structure is one-way and is not efficient for query operation. In view of this, we proposed a novel searching structure based on a height balanced Binary Search Tree (BST). The data structure we proposed not only retains the characteristics of the traditional ledgers but also adds the...Show More
A novel method to classify organizational data using CIA tree approach
2015 Online International Conference on Green Engineering and Technologies (IC-GET)
Year: 2015 | Conference Paper |
Cited by: Papers (1)
Data classification plays an important role in an organizational information and communication technology. An efficient data classification technique reduces the complexity of data management. Here we focusing the main security threats such as Confidentiality (C), Integrity (I) and Availability (A). A tree approach is used for data classification. CIA tree is a binary tree which each level represe...Show More
Autonomous Demand-Side Management system based on Monte Carlo Tree Search
Edgar Galván-López;Colin Harris;Leonardo Trujillo;Katya Rodriguez-Vazquez;Siobhán Clarke;Vinny Cahill
2014 IEEE International Energy Conference (ENERGYCON)
Year: 2014 | Conference Paper |
Cited by: Papers (16)
Smart Grid (SG) technologies are becoming increasingly dynamic, motivating the use of computational intelligence to support the SG by predicting and intelligently responding to certain requests (e.g, reducing electricity costs given fluctuating prices). The presented work intends to do precisely this, to make intelligent decisions to switch on electric devices at times when the electricity price (...Show More
An Investigation on Electricity Consuming Features for User Classification in Demand-Side Management Schemes
2021 IEEE 5th Conference on Energy Internet and Energy System Integration (EI2)
Year: 2021 | Conference Paper |
The global deployment of smart meters has resulted in massive recorded data. By analyzing the data, we can capture users' electricity consumption behaviour. Data obtained contributes to the scheme design for the demand-side management (DSM) and the balance between the supply and demand sides in the power grid. For extracting consumption behaviour from smart metering data originally for billing pur...Show More
Divide & Conquer Classification and Optimization by Genetic Algorithm
Hamid Parvin;Hosein Alizadeh;Mohsen Moshki;Behrouz Minaei-Bidgoli;Naser Mozayani
2008 Third International Conference on Convergence and Hybrid Information Technology
Year: 2008 | Conference Paper |
Cited by: Papers (8)
In this paper, a new approach for improving the performance of recognition system is proposed. The main idea of proposed approach is using pairwise classifiers. Firstly, a multi class classifier is trained and its confusion matrix is derived. Then, the error between metaclasses is derived. In each level, our objective is to minimize the error between metaclasses in the evaluation dataset. This met...Show More
An interpretable model for predicting side effects of analgesics for osteoarthritis
Liangliang Liu;Jianxin Wang;Min Li;Fang-Xiang Wu;Hong-Dong Li;Ying Yu;Zhihui Fei
2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
Year: 2017 | Conference Paper |
Osteoarthritis (OA) is the most common type of arthritis. Analgesics are widely used in the process of the treatment of arthritis. Analgesics are particularly used by OA patients which may increase the risk of cardiovascular disease by 20% to 50% overall. In this study, we proposed an interpretable model to predict side effects of analgesics on cardiovascular disease for OA patients. One task of o...Show More
Tree Search in Major/Minor Loop Magnetic Bubble Memories
IEEE Transactions on Computers
Cited by: Papers (4)
In this paper we analyze various search schemes in a major/minor loop bubble memory. Specifically, we study balanced tree search, one-sided height-balanced tree search, and one-sided K-Keight-balanced tree search. Two parameters are of interest in the present framework, namely, the number of comparisons and the amount of record movement required for a search. One-sided height- balanced tree search...Show More
Derivation of a parallel algorithm for balancing binary trees
A recent trend in program methodologies is to derive efficient parallel programs from sequential programs. This study explores the question of transforming a sequential algorithm into an efficient parallel algorithm by considering the problem of balancing binary search trees. The derivation of the parallel algorithm makes use of stepwise refinement. The authors first derive a new iterative balanci...Show More
A Dynamic Tree-Based Data Structure for Access Privacy in the Cloud
Sabrina De Capitani di Vimercati;Sara Foresti;Riccardo Moretti;Stefano Paraboschi;Gerardo Pelosi;Pierangela Samarati
2016 IEEE International Conference on Cloud Computing Technology and Science (CloudCom)
Year: 2016 | Conference Paper |
Cited by: Papers (6)
We present a novel approach for guaranteeing access privacy to data stored at an external cloud provider. Our solution relies on the grouping of resources into buckets then organized with a binary search tree. The tree is built on an index computed in a non-invertible non-order preserving way, and supports efficient key-based retrieval. Our approach to provide access privacy builds on this data or...Show More
On the Monte Carlo Boolean decision tree complexity of read-once formulae
[1991] Proceedings of the Sixth Annual Structure in Complexity Theory Conference
Year: 1991 | Conference Paper |
In the Boolean decision tree model there is at least a linear gap between the Monte Carlo and the Las Vegas complexity of a function depending on the error probability. The author proves for a large class of read-once formulae that this trivial speed-up is the best that a Monte Carlo algorithm can achieve. For every formula F belonging to that class it is shown that the Monte Carlo complexity of F...Show More
Tree parsing is an important problem in statistical machine translation. In this context, one is given (a) a synchronous grammar that describes the translation from one language into another and (b) a recognizable set of trees; the aim is to construct a finite representation of the set of those derivations that derive elements from the given set, either on the source side (input restriction) or on...Show More
Effective LAI and CHP of a Single Tree From Small-Footprint Full-Waveform LiDAR
Karolina D. Fieber;Ian J. Davenport;Mihai A. Tanase;James M. Ferryman;Robert J. Gurney;Jeffrey P. Walker;Jorg M. Hacker
This letter has tested the canopy height profile (CHP) methodology as a way of effective leaf area index (LAIe) and vertical vegetation profile retrieval at a single-tree level. Waveform and discrete airborne LiDAR data from six swaths, as well as from the combined data of six swaths, were used to extract the LAIe of a single live Callitris glaucophylla tree. LAIe was extracted from raw waveform a...Show More
Probabilistic boosting-tree: learning discriminative models for classification, recognition, and clustering
Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1
Year: 2005 | Conference Paper |
In this paper, a new learning framework - probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the probabilistic boosting-tree automatically constructs a tree in which each node combines a number of weak classifiers (evidence, knowledge,) into a strong classifier (a conditional posterior probability). It approaches the ...Show More
Efficient Selection on Spatial Modulation Antennas: Learning or Boosting
In this letter, a novel deep learning-based transmit antenna selection (TAS) scheme for the multiple-input multiple-output (MIMO) with spatial modulation (SM) system is proposed. We formulate the generalized TAS pipeline in both neural networks (NN) and gradient boosting decision trees (GBDT), in which the importance of different features reflecting the different elements from channel state inform...Show More
Crystallization and inner stresses can influence electrical aging properties of insulating material. Heat treatment is one of the most important processes in production of insulating material. This paper presents the growing properties of electrical trees in low density polyethylene (LDPE). The LDPE specimens used for electrical tree experiments are obtained by four different heat treatment proces...Show More
Convex hull calculation approach based on BST
2018 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus)
Year: 2018 | Conference Paper |
Cited by: Papers (1)
The paper describes new algorithm based on binary search tree using, which have average case time complexity O(N*log(H)) where N is the size of the input set of points and H is the number of vertices found to be on the convex hull. The algorithm calculates the approximate center and stores all convex hull points in balanced binary search tree by the angle from it. Implementation of the new algorit...Show More
Boolean Operations on Polygonal Meshes Using OBB Trees
2009 International Conference on Environmental Science and Information Application Technology
Year: 2009 | Conference Paper |
Cited by: Papers (2)
Algorithms for Boolean operations using BSP trees and other algorithms have problems with efficiency and robustness. In order to improve the speed and correctness of operations, a new algorithm for Boolean operations on polygonal meshes was presented. In this algorithm, a fast collision detection algorithm based on oriented bounding box (OBB) was employed, which speed up the intersection test betw...Show More
Graceful Cascading Labelling Algorithm: Construction of Graceful Labelling of Trees
2021 2nd International Conference on Robotics, Electrical and Signal Processing Techniques (ICREST)
Year: 2021 | Conference Paper |
The Graceful Labelling of trees is one of the most challenging conjectures in Graph Theory, proudly known as the 'Disease' of Graph Theory which remains a challenge as it remains unsolved. To counter the conjecture, an algorithm is proposed to construct a Graceful Binary Tree and a Graceful Caterpillar Tree. Here, the algorithm puts forward a solution to graceful labelling problem through a very e...Show More
The automatic generation of graphical user interfaces
[Proceedings] COMPEURO 88 - System Design: Concepts, Methods and Tools
Year: 1988 | Conference Paper |
The author deals with the properties of a tool called G/sup 2/F (an editor generator for two-dimensional graphical formulas). G/sup 2/F makes it possible to define two-dimensional grammars graphically and to generate a corresponding syntax-directed editor. It facilitates syntactic-correctness-preserving operations on the abstract syntax trees of formulas and produces hardcopies of whole operation ...Show More
Using data mining for assessing diagnosis of breast cancer
Medhat Mohamed Ahmed Abdelaal;Hala Abou Sena;Muhamed Wael Farouq;Abdel-Badeeh Mohamed Salem
Proceedings of the International Multiconference on Computer Science and Information Technology
Year: 2010 | Conference Paper |
Cited by: Papers (13)
The capability of the classification SVM, Tree Boost and Tree Forest in analyzing the DDSM dataset was investigated for the extraction of the mammographic mass features along with age that discriminates true and false cases. In the present study, SVM technique shows promising results for increasing diagnostic accuracy of classifying the cases witnessed by the largest area under the ROC curve (area...Show More
Standards Dictionary Terms
- AASF:
- AATF:
- CBC band:
- CBC base layer:
- CBC bitplane vector:
- CBC enhancement layer:
- CBC sublayer:
- Context-dependent Bitplane Coding (CBC):
- FLPVQ:
- Fast Fourier Transformation (FFT):
- Hann window:
- IFLPVQ:
- IMDCT:
- LPC:
- LSB:
- MDCT:
- MSB:
- Nyquist sampling:
- Parcor coefficients:
- analysis filterbank:
- ancillary data:
- audio buffer:
- back flashover (lightning)
- bitrate:
- bitstream:
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