Besides steering the incoming signals toward a receiver, a reconfigurable intelligent surface (RIS) can simultaneously serve as a backscatter node to communicate additional data by modulating the same signal. Quadratu...
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Besides steering the incoming signals toward a receiver, a reconfigurable intelligent surface (RIS) can simultaneously serve as a backscatter node to communicate additional data by modulating the same signal. Quadrature reflection modulation (QRM) is a promising contender among index modulation (IM)-based techniques for implementing RIS-based backscatter communications (RIS-BackCom). In this paper, we demonstrate that the error performance of RIS-QRM heavily relies on the employed indexing scheme, which configures each RIS element into one of the two orthogonally-reflecting modes of QRM to encode the transmitted data onto the reflection pattern of RIS elements. In this context, we present an efficient guideline for designing indexing schemes that ensure the resulting channel-dependent QRM symbols are evenly spaced with maximum separation. Following this guideline, we propose two specific indexing techniques: the incremental and uniform indexing schemes, both of which substantially enhance the error performance of RIS-QRM without increasing detection complexity. We derive a closed-form expression for the bit error probability (BEP) of RIS-QRM with the incremental indexing scheme. Furthermore, we propose a low-complexity detector for RIS-BackCom systems employing RIS-QRM. Extensive computer simulations illustrate the effectiveness of our proposed schemes in improving the error performance of RIS-QRM-based BackCom systems.
This study aims to develop an LSM tree that uses two different kinds of probabilistic data structures (PDS). These two data structures are the Bloom Filters and the state-of-the-art Cuckoo Filter released in 2014 by F...
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This study aims to develop an LSM tree that uses two different kinds of probabilistic data structures (PDS). These two data structures are the Bloom Filters and the state-of-the-art Cuckoo Filter released in 2014 by Fan. Cuckoo filters are a perfect choice for saving space and also for deleting keys that are not needed in the algorithm so the filters are synchronized with the keys of all the SSTables. The implementation in this study of Cuckoo filters showed three main advantages (1) Keys that are deleted in the SSTables are immediately reflected in the Cuckoo Filters (2) When SSTables are merged, Cuckoo Filters are also merged by measuring its load factor for availability (3) The performance of Cuckoo Filters compared to Bloom filters after deleting and query shows better performance despite that cuckoo filters are also being updated. This approach is expected to reduce storage space and the amount of time for queries and deletions on the overall data structure. This new optimized LSM tree is expected to be implemented in HBase as future work to check its performance with a real-world database for more empirical results.
A scanning laboratory Laue transmission setup is developed to probe extended quasi-monocrystalline samples. Orientation mapping is achieved by controlling the collimation of the incident beam and scanning the position...
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A scanning laboratory Laue transmission setup is developed to probe extended quasi-monocrystalline samples. Orientation mapping is achieved by controlling the collimation of the incident beam and scanning the position of the specimen. An automated indexing algorithm for transmission Laue patterns is presented, together with a forward simulation model adapted for a laboratory setup. The effect of the main parameters of the system is studied with the aim of achieving exposure times of the order of one second. Applications are presented to probe the orientation of an extended part and detect disoriented regions within the bulk. Finally, the analysis of diffraction spot shapes shows that the misorientation within the illuminated volume can be measured, and a new method is proposed to evaluate its complete mean lattice rotation tensor.
In the emerging field of big data, a large volume of data has to be managed, operating on data of huge volume becomes easier when it's sorted and structured. The data can be structured using a simple algorithm i.e...
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ISBN:
(纸本)9781509047970
In the emerging field of big data, a large volume of data has to be managed, operating on data of huge volume becomes easier when it's sorted and structured. The data can be structured using a simple algorithm i.e. index algorithm which stores and categories data on basis of their application. This in turn will be very beneficial on business level as well as on software level.
We study the problem of indexing irreducible polynomials over finite fields, and give the first efficient algorithm for this problem. Specifically, we show the existence of poly(n, logq)-size circuits that compute a b...
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We study the problem of indexing irreducible polynomials over finite fields, and give the first efficient algorithm for this problem. Specifically, we show the existence of poly(n, logq)-size circuits that compute a bijection between {1, . . . , vertical bar S vertical bar} and the set S of all irreducible, monic, univariate polynomials of degree n over a finite field F-q. This has applications to pseudorandomness, and answers an open question of Alon, Goldreich, Hastad, and Peralta (1992). Our approach uses a connection between irreducible polynomials and necklaces (equivalence classes of strings under cyclic rotation). Along the way, we give the first efficient algorithm for indexing necklaces of a given length over a given alphabet, which may be of independent interest.
Database cracking has been an area of active research in recent years. The core idea of database cracking is to create indexes adaptively and incrementally as a side-product of query processing. Several works have pro...
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Database cracking has been an area of active research in recent years. The core idea of database cracking is to create indexes adaptively and incrementally as a side-product of query processing. Several works have proposed different cracking techniques for different aspects including updates, tuple-reconstruction, convergence, concurrency-control, and robustness. However, there is a lack of any comparative study of these different methods by an independent group. In this paper, we conduct an experimental study on database cracking. Our goal is to critically review several aspects, identify the potential, and propose promising directions in database cracking. With this study, we hope to expand the scope of database cracking and possibly leverage cracking in database engines other than MonetDB. We repeat several prior database cracking works including the core cracking algorithms as well as three other works on convergence (hybrid cracking), tuple-reconstruction (sideways cracking), and robustness (stochastic cracking) respectively. We evaluate these works and show possible directions to do even better. We further test cracking under a variety of experimental settings, including high selectivity queries, low selectivity queries, and multiple query access patterns. Finally, we compare cracking against different sorting algorithms as well as against different main-memory optimised indexes, including the recently proposed Adaptive Radix Tree (ART). Our results show that: (i) the previously proposed cracking algorithms are repeatable, (ii) there is still enough room to significantly improve the previously proposed cracking algorithms, (iii) cracking depends heavily on query selectivity, (iv) cracking needs to catch up with modern indexing trends, and (v) different indexing algorithms have different indexing signatures.
The scale and growth rate of text collection bring new challenges for index construction. To tackle this problem, an efficient indexing algorithm, the Fine Granularity Pipeline (FGP), is proposed to improve the indexi...
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ISBN:
(数字)9783642340383
ISBN:
(纸本)9783642340376
The scale and growth rate of text collection bring new challenges for index construction. To tackle this problem, an efficient indexing algorithm, the Fine Granularity Pipeline (FGP), is proposed to improve the indexing performance for multi-core platform. Compared to the Simple Pipeline (SP) algorithm, compressing and parsing are divided in the FGP to get more balanced pipeline stages. Evaluations for three collections from Terabyte track in the TREC 2011 over Intel Woodcrest platform showed that the performance improvements of the FGP were over 45% and 17% compared to indexing in Indri 2.4 and the SP with three cores.
The predictability of memory access patterns in embedded systems can be successfully exploited to devise effective application-specific cache optimizations. In this paper, an improved indexing scheme for direct-mapped...
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The predictability of memory access patterns in embedded systems can be successfully exploited to devise effective application-specific cache optimizations. In this paper, an improved indexing scheme for direct-mapped caches, which drastically reduces the number of conflict misses by using application-specific information, is proposed. The indexing scheme is based on the selection of a subset of the address bits. With respect to similar approaches, the solution has two main strengths. First, owing to an analytical model for the conflict-miss conditions of a given trace, it provides a symbolic algorithm to compute the optimum solution (i.e., the subset of address bits to be used as cache index that minimize the number of conflict misses). Second, owing to a reconfigurable bit selector that can be programmed at run time, it allows the optimal cache indexing to fit to a given application. Results show an average reduction of conflict misses of 24%, measured over a set of standard benchmarks, and for different cache configurations.
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