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Atypical sequences are subsequences of long sequences that deviate from the ‘normal’ data. In previous papers we have developed an information-theoretic approach to such sequences for discrete and real-valued data. In the current paper we extend the principle of real-valued data that follows vector Gaussian models, which allows for finding relationship between data. We include a simple application...
Finding substantial features is a significant approach to cope the challenges of video anomaly detection and localization. The specific important representation are selected to detect an event in video. State-of-the-art models explore this fashion by do seeking interest points both spatially and temporally. However, it has to very selective towards undesired object or background. Selective Spatio-Temporal...
Efficient online algorithms are developed to perform dictionary learning (DL) for the features lifted to a high-dimensional space via nonlinear mapping. Inspired by recent works on batch kernelized DL with promising performance for real-world learning tasks, two kernel DL formulations are put forth, amenable to online processing. The first formulation aims at faithfully representing the high-dimensional...
This paper focuses on increasing the data storage capacity with less storage space of QR code by applying compression techniques. Further data capacity can be increased by applying multiplexing techniques i.e. Grouping of bits into codeword and providing security by replacing the codeword by special type of character. As there are varieties of medium for information sharing over distances. Thus QR...
With network coding, data flows from the source to the destinations may be jointly coded in some intermediate nodes to achieve the maximum network capacity. There is scarcely any theory to systematically model and evaluate the loss of network coding. Without such a theory, the analysis of network coding under various settings is far from practical. To fill the vacancy, we introduce a loss model into...
High Efficiency Video Coding (HEVC) is a novel video compression standard. It provides significantly better performance than its predecessor, but introduces high computational complexity due its hierarchical block structure. Determining Coding Units (CU), Prediction Units (PU), and Transform Units (TU) size is a time consuming process, as block partitioning decisions are based on rate-distortion optimization...
Differential Evolution (DE), an optimization algorithm under the roof of Evolutionary Algorithms (EAs), is well known for its efficiency in solving optimization problems which are non-linear and non-differentiable. DE has many good qualities such as algorithmic simplicity, robustness and reliability. DE also has the quality of solving the given problem with few control parameters (NP — population...
The High Efficiency Video Coding (HEVC) standard achieves higher encoding efficiency than previous standards such as H.264/AVC. One key contributor to this improvement is the intra-prediction method that supports a large number of prediction directions at a cost of high computational complexity. Within the context of mobile devices with limited power and computational capabilities, reductions on encoding...
In recent years, the distinctive advancement of handling huge data promotes the evolution of ubiquitous computing and analysis technologies. With the constantly upward system burden and computational complexity, adaptive coding has been a fascinating topic for pattern analysis, with outstanding performance. In this work, a continuous hashing method, termed continuous random hashing (CRH), is proposed...
Considerable research effort has been focused on the translation of non-binary CSP into an equivalent binary CSP. Most of this work has been devoted to studying the binary encoding of non-binary CSP. Three encodings have been proposed, namely dual encoding, hidden variable encoding and double encoding. Unfortunately, such encodings do not allow to use some properties and interesting results defined...
Solvers for the maximum satisfiability (MaxSAT) problem -- a well-known optimization variant of Boolean satisfiability (SAT) -- are finding an increasing number of applications. Preprocessing has proven an integral part of the SAT-based approach to efficiently solving various types of real-world problem instances. It was recently shown that SAT preprocessing for MaxSAT becomes more effective by re-using...
This paper proposes a new hybrid encoding of finite linear CSP to SAT integrating order and log encodings. The former maintains bound consistency by unit propagation and works well for instances with small/middle domain sized variables and/or arity of constraints. The latter generates smaller CNF and is suitable for instances with larger domain sized variables, but its performance is not good in general...
Preferences can be expressed as wishes, constraints or both. Generally, wishes and constraints do not complement each other. A different reasoning principle is applied to rank-order the set of options depending on whether preferences refer to wishes or constraints. Consequently, these two types of preferences have been characterized by two separate sets of postulates offering a normative view of the...
We propose and empirically evaluate a theoretical framework of how to use coding guides for automatic coding (scoring) and how, in turn, automatic coding can enhance the use of coding guides. We adopted a recently described baseline approach to automatically classify responses. Well-established coding guides from PISA, comprising reference responses, and its German sample from 2012 were used for evaluation...
We analyze postings in the Turn to Islam forum using techniques based on singular value decomposition (SVD) and the deep learning technique of stacked denoising autoencoders (SDAE). Models based on frequent words and jihadist language intensity are used, and the results compared. Our main conclusion is that SDAE approaches, while clearly discovering structure in document-word matrices, do not yet...
The Slepian-Wolf (SW) coding system is a source coding system with two encoders and a decoder, where these encoders independently encode input sequences emitted from two correlated sources into fixed-length codewords, and the decoder reconstructs all input sequences from the codewords. In this paper, we consider the situation in which the SW coding system is asynchronous, i.e., each encoder runs with...
Polar codes for channels with memory are considered in this paper. Şaşoğlu proved that Arikan's polarization applies to finite-state memory channels but practical decoding algorithms of polar codes for such channels have been unknown. This paper proposes a generalization of successive cancellation algorithm for channels with memory where the complexity is polynomial in the number of states. In addition,...
A source coding problem over a noiseless broadcast channel where the source is preinformed about the contents of the cache of all receivers, is an index coding problem. Furthermore, if each message is requested by one receiver, then we call this an index coding problem with a unicast message setting. This problem can be represented by a directed graph. In this paper, we first define a structure (we...
Error and erasure exponents for the asymmetric broadcast channel are analyzed. The focus of the error analysis is on the main receiver where, nominally, both messages are to be decoded. A two-step decoding algorithm is proposed and analyzed. This receiver first attempts to decode both messages, failing which, it attempts to decode only the message representing the coarser information, i.e., the cloud...
We consider a content delivery network where multiple servers are connected to multiple cache-enabled clients. Clients request their corresponding contents from the servers and servers collaboratively transmit packets to fulfill all the requests. It is assumed that some contents are stored in the caches in off-peak time of the network without knowing the actual requests, the so called cache content...
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