198,288 research outputs found
Compressed Sensing with Binary Matrices: New Bounds on the Number of Measurements
No full textDue to copyright restrictions and/or publisher's policy full text access from Treasures at UT Dallas is limited to current UTD affiliates (use the provided Link to Article).In this paper we study the problem of compressed sensing using binary measurement matrices. New bounds are derived for the number of measurements that suffice to achieve robust sparse recovery, and the number of measurements needed to achieve sparse recovery. In particular, by interpreting any binary measurement matrix as the biadjacency matrix of an unbalanced bipartite graph, we derive new lower bounds on the number of measurements required by any graph of girth six or larger, in order to satisfy a sufficient condition for sparse recovery. It is shown that the optimal choices for the girth of the graph associated with the measurement matrix are six and eight. Some interesting open problems that arise from our results are pointed out. The proofs of the results presented here are omitted. The reader is directed to (M. Lotfi and M. Vidyasagar, “Compressed sensing using binary matrices of nearly optimal dimensions,” arXiv:1808.03001, 2018) for stronger results than are presented here, as well as their proofs. © 2019 IEEE.Erik Jonsson School of Engineering and Computer Scienc
Closure to "Experimental Study of Central Baffle Flume" by F. Lotfi Kolavani, M. Bijankhan, C. di Stefano, V. Ferro, and A. Mahdavi Mazdeh
No full textThis is a Closure of the discussions on the paper “Experimental Study of Central Baffle Flume”
by F. Lotfi Kolavani, M. Bijankhan, C. Di Stefano, V. Ferro, and A. Mahdavi Mazde
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Single-occupancy simulator for ambient intelligent environment
No full textIn this paper, the simulation of an occupant’s behaviour in a single-occupant ambient intelligent environment is addressed. The algorithm of the simulator is designed flexible enough to accept different environmental profiles including the number of areas and the connections between them along with different occupant’s profiles including expected daily occupancy pattern of him/her and the uncertainty of his/her behaviour to follow this occupancy pattern. The generated occupancy signal by the simulator represents the occupancy of areas by assuming a signal level for the occupancy of each area in a single-occupant environment with the resolution of one minute in a whole day activity of the occupant in the environment. The validity of the simulator will be verified by tuning the simulator’s parameters to occupancy data collected by sensory agents from a real equivalent environment. By applying the generated data from this simulator to the data mining techniques, the ability of different techniques will be investigated
A survey on the construction and demolition waste in Mongolia
No full textn many developing countries, the rapid growth of town and cities has generated a rising levels of waste and illegal dumps have become a serious issue. The booming construction industry in Mongolia has resulted in the production of massive amounts of CDW which is one of the largest waste streams. In Ulaanbaatar (UB) and other cities in Mongolia, the construction waste is dumped illegally. In order to promote the sustainability of the building industry, plenty of regulations focusing on reducing or recycling the CDW have been carried out worldwide. This paper investigates the current CDW management in Mongolia and proposes a quantification of the amount of CDW in UB by using a Material Flow Analysis (MFA). Questionnaire surveys and interviews were conducted with main stakeholders in construction and recycling sector. From the questionnaire results, it is clear that the awareness about the CDW issues in Mongolia is low among the principal stakeholders in the sector, such as Government agencies and construction companies. On the other hand, recycling in Mongolia belongs to an informal sector and the lack of investment constitutes a major problem. In this regards, the technical and non-technical solutions to improve CDW management system are proposed. A stricter control of landfilling for CDW and a creation of a dedicated regulatory framework specific to CDW are needed. To increase the recovery and recycling rates of materials an optimum demolition strategy (for example process, costs, logistics, procedures, timing) is recommended.Materials and Environmen
LOTFI ZADEH: EL GENIO CREADOR DE LA L 3GICA DIFUSA
No full textLotfi Asker Zadeh: matem\ue1tico, ingeniero electricista, inform\ue1tico y profesor Iran\ued- estadounidense de la Universidad de California en Berkeley. Cre\uf3 la teor\ueda de conjuntos borrosos y la l\uf3gica borrosa. Zadeh es uno de los m\ue1s notables genios de la \ue9poca actual. Entre sus otras creaciones est\ue1n el m\ue9todo de la transformada Z, el enfoque de la teor\ueda de sistemas lineales basado en estados, variables ling\ufc\uedsticas, control borroso, razonamiento aproximado, teor\ueda de la posibilidad, \u93soft computing\u94, computaci\uf3n con palabras, teor\ueda computacional de las percepciones, teor\ueda de la granulaci\uf3n de la informaci\uf3n borrosa, teor\ueda generalizada de la incertidumbre, y n\ufameros Z.
Palabras clave: Zadeh, conjuntos borrosos, l\uf3gica borrosa, teor\ueda generalizada de la incertidumbre, n\ufamero Z.
ABSTRACT
Lotfi Asker Zadeh: mathematician, electrical engineer, computer scientist and Iranian-American professor at the University of California in Berkeley. He created the theory of fuzzy sets and fuzzy logic. Zadeh is one of the most remarkable geniuses of the current era. Among his other creations are the Z-transform method, the approach of the theory of linear systems based on states, linguistic variables, fuzzy control, approximate reasoning, theory of possibility, "soft computing", computation with words, computational theory of perceptions, theory of the granulation of fuzzy information, generalized theory of uncertainty, and Z-numbers.
Key words: Zadeh, fuzzy sets, fuzzy logic, generalized theory of uncertainty, Z-number. <br
Numerical modelling of the dehydration of waste concrete fines: An attempt to close the recycling loop
No full textThe ever-increasing interest on sustainable raw materials has urged the quest for recycled materials that can be used as a partial or total replacement of fine fractions in the production of concrete. This paper demonstrates a modelling study of recycled concrete waste fines and the possibility of turning them into active constituents for the production of concrete. When construction demolition waste (CDW) fines with particle size 0 - 4mm are exposed to a hot environment, different reactions will occur, especially dehydration and phase changes. A one- dimensional (1D) transient model is developed to predict the conversion of the hydrated concrete fines into their dehydrated state, in which the key processes inside the particle and at the boundary layer outside the particle are properly addressed. The model predicts a final composition of the particle that resembles cement clinker, which means a high potential for reuse in manufacturing concrete. Finally, model results for the mass loss during conversion are experimentally validated using thermogravimetric study.Materials and Environmen
The influence of parent concrete and milling intensity on the properties of recycled aggregates
No full textThe C2CA concrete recycling process consists of a combination of smart demolition, gentle grinding of the crushed concrete in an autogenous mill, and a novel dry classification technology called ADR to remove the fines. The` main factors in the C2CA process which influence the properties of Recycled Aggregates or Recycled Aggregate Concrete (RAC) include the type of Parent Concrete (PC), the intensity of autogenous milling and ADR cut-size point. This study aims to investigate the influence of PC and intensity of the autogenous milling on the quality of the produced recycled aggregates. Three types of concrete which are frequently demanded in the Dutch market were cast as PC and their fresh and hardened properties were tested. After near one year curing of PC samples, they were recycled independently while the aforementioned recycling factors were varied. The effects of different recycling variables on the water absorption, density, crushing resistance and durability of produced recycled aggregates were investigated. According to the results, type of the parent concrete is the predominant factor influencing the properties of the recycled aggregates. Milling intensity was found to be effective on improving the properties of recycled aggregates coming from weaker parent concrete. The experimental results suggest that among various milling intensities, milling at medium shear and medium compression improves the overall quality of RAMaterials and Environmen
Deterministic Compressed Sensing Using Binary Measurement Matrices
No full textThe fundamental objective of compressed sensing is to recover a high dimensional but low
complexity vector or matrix from only a few linear measurements. In most of the initial
publications in the field of compressed sensing, the emphasis is on using random matrices
such as Gaussian, Bernoulli, etc. The limitations of this framework include high memory
requirements, and CPU time. This dissertation mainly focuses on binary measurement
matrices and highlights the superiority of binary matrices in terms of CPU time, complexity,
and the required memory compared to the random measurement matrices.
In the first part of the dissertation (Chapter 2), we present a new recovery algorithm for compressed sensing that makes use of binary measurement matrices and achieves exact recovery
of ultra sparse vectors, in a single pass and without any iterations. Due to its non-iterative
nature, our algorithm is hundreds of times faster than iterative algorithms such as `1-norm
minimization, and methods based on expander graphs. Our algorithm can accommodate
nearly sparse vectors, in which case it recovers the index set of the largest components, and
can also accommodate shot noise measurements.
In the second part of the dissertation (Chapter 3), we focus on using binary measurement
matrices to solve the problem of compressed sensing while `1-norm minimization (basis pursuit) is considered as the recovery algorithm. We derive new upper and lower bounds on the
number of measurements to achieve robust sparse recovery with binary matrices. We prove
sufficient conditions for a column-regular binary matrix to satisfy the robust null space property (RNSP) and derive universal lower bounds on the number of measurements that any
binary matrix needs to have in order to satisfy the weaker sufficient condition based on the
RNSP. Then we show that binary matrices that are bi-adjacency matrices of bipartite graphs
of girth six are optimal. Two classes of binary matrices, namely parity check matrices of
array codes, and the matrices based on Euler Squares, have girth six and are nearly optimal
in the sense of almost satisfying the lower bound. In principle randomly generated Gaussian
measurement matrices are “order-optimal”; however in practice, Gaussian matrices require
more measurements than binary matrices when n < 106
.
We then compare the phase transition behavior of the `1-norm minimization formulation
using binary parity check matrix of the array code and the Gaussian matrices, and show
that the phase transitions of both matrices are almost the same and the recovery using basis
pursuit with binary matrices is hundreds of times faster than with Gaussian matrices. In
addition, the required memory is less than when using Gaussian matrices. This suggests
that binary matrices are a viable alternative to Gaussian matrices for compressed sensing
using basis pursuit. This study can be extended to other recovery algorithms using binary
matrices
Dr. Duane M. Jackson, Morehouse College, July 2011
No full textThis video is a conversation with Dr. Duane M. Jackson. Dr. Jackson talks about his paper, "Recall and the Serial Position Effect: The Role of Primacy and Recency on Accounting Students' Performance." Jackie Daniel, AUC Woodruff Library, is the interviewer
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