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In this paper, a novel algorithm is developed for the design of minimum-phase FIR filters with sparse impulse responses. Traditional minimum-phase FIR filter design approaches are based on autocorrelation sequences of impulse responses and design problems are formulated as a semidefinite program. To achieve sparse designs, l1 norm of filter coefficients is incorporated in the objective function as...
This paper proposes an approach of recommending micro-learning path based on improved ant colony optimization algorithm. Micro-learning is a new learning style, which can be used to support learning in short time because of its micro-learning units. Each micro-learning unit consists of a small knowledge unit that can be learned at fragmented time. Meanwhile, micro-learning is more flexible than other...
As technology has advanced nowadays, it is common for a system to be optimized under more than one objective function, which leads to inconclusive results if two contradictory objectives exist. Traditional approaches suggest a simple aggregation of multiple objectives into one via a linear combination, but it is hard to justify the weights quantitatively. This paper proposes a systematic therapy to...
In order to reduce decision rule effectively, a decision rule reduction method based on core value and a decision rule prioritizing method were provided. The results show that effective decision rule reduction can be gotten through above methods and all of these help to improve decision ability.
Locality-based feature learning has drawn more and more attentions recently. However, most of locality-based feature learning methods only consider a kind of local neighbor information, and such the locality-based methods are difficult to well reveal intrinsic geometrical structure of raw high-dimensional data. In this paper, we propose a novel multi-locality correlation feature learning algorithm...
'Crime analysis plays a major part in crime prevention and safety of people in a country. The paper focuses on state based frequent crime pattern knowledge discovery and prevention. Our work concentrates on Finding frequent crimes state wise using FP Max a bottom up approach which uses linked lists for reduction of space complexity. The generated frequent crime sets of state will be undergone through...
Weighted item-set mining is used to find the profitable connection between the data. There are two types of items contained in dataset i.e. frequent and infrequent. Infrequent item-sets are nothing but items which are rarely found in database. Mining frequent items in data mining are very helpful for retrieving the related data present in the dataset. Using transactional dataset as an input dataset...
The problem of generating large frequent itemset for the generation of association rules in the transactional database is considered. Previous work in this field already proposes many algorithms like Apriori, FP-growth, and their variations. Reverse-Apriori which is also a variation of Apriori for finding large frequent itemset in reverse manner, it has its own advantages and limitations like Apriori...
Binary relevance (BR) is a well-known framework for multi-label classification. It decomposes multi-label classification into binary (one-vs-rest) classification subproblems, one for each label. The BR approach is a simple and straightforward way for multi-label classification, but it still has several drawbacks. First, it does not consider label correlations. Second, each binary classifier may suffer...
Mining based on opinions can extract useful information from users' comments. After doing cluster and analysis on the information, users can get a detailed understanding of the commodity, then determine to buy the commodity or not. In this paper, firstly, we extract evaluation objects and evaluation words, then cluster the evaluation objects. Next based on SO-PMI algorithm, judge the polarity of evaluation...
This is a work to develop an interactive email application. An email system is considered as a personal private property nowadays. It is not easy for people with disability to use normal devices for checking their emails. Users need more interaction with their emails. This interactive technology is based on eye blink detection; hence persons with disabilities can also efficiently use this system....
This study focuses on the negotiation in the financial markets, specifically in programming an algorithm to trade automatically (without human intervention) in the foreign exchange market (Forex). The platform used in this study was the Meta Trader (version 5), which allows for this kind of negotiation. The main objective was to conclude about the effectiveness of anewly developed strategy for automatic...
One of the major subjects of study in computational biology is finding the similarity between DNA sequences. Several techniques exist that are either based on alignment between sequences or are alignment-free. This paper demonstrates two techniques that are alignment-free. The first one is based on a graphical representation of the difference between DNA sequences, while the other one is based on...
In this article, we propose a registration algorithm to estimate geometric transformation between two images. It is a method based on the Analytical Fourier Mellin Transform (AFMT) phase correlation. We are interested in geometric distortions caused by the effects of similarities. As an application, we propose the mosaicing. The method performance was evaluated on simulated and real images.
Ternary perfect sequences, which include the binary perfect sequences as special cases, are introduced. The new notions of elementary transformations on ternary perfect sequences are brought forward. Necessary conditions for ternary perfect sequences with k zero elements are proposed. It is proved that there exist no ternary perfect sequences of even lengths with one zero element, and no ternary perfect...
This paper proposes an project based on chosen-message exponent extraction against RSA hardware implementation. The intercepting of the similar characteristic curve can help make the template of the exponential matching more accuracy and more efficient In the meantime it can improve the accuracy of attack.
For high safe and high efficiency encryption system was designed by using the negative selection algorithms of Artificial Immunity Theory, and its safe was demonstrated. It is a new method based on the negative selection algorithm and extracts the encryption factor from the plaintext. Encryption factor as a key group is expanded by the way of the m-sequence and generates pseudo-random key sequence...
This paper analyzes the PageRank algorithm, find out its disadvantages and put forward an improved PageRank algorithm. Based on the behavior of user clicks, this algorithm on the one hand collects the clicks of result pages and the recently click time of result pages, on the other hand set the weight of clicks and click time as formula parameters of PageRank algorithm, and verify this algorithm does...
Low support makes dramatic increase in the number of itemsets and brings less efficient frequent itemset mining. Correlation measures introduced to restrict the number of frequent itemsets generated in order to improve the efficiency of mining under certain conditions. An improved FP-Tree algorithm using node linked list FP-Tree is proposed. This algorithm exploits efficient pruning strategies using...
Nowadays, worms and other outside threats in the network recognized to be a serious and unexpected behavior. The main issue was addressed based on the behavioral patterns of worms that reflect application communications typical of worms. This representation of worm's behavior differs from those used in contemporary enterprise postures, which reliance on a particular type of signature-based intrusion...
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