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By analyzing the disadvantages of the traditional KNN using lazy learning that directly classify the data based on the K neighboring classes using the majority voting method, a new Sigmoid weighted classification algorithm WKS (Weighted KNN Based On Sigmoid) was proposed. WKS provides a new method for learning and training, since each training data di ∊ D contributes to the correct classification...
Test cases are an essential tool in software quality assurance: they ensure that code behaves as specified in the requirement. However, writing test cases does not have only benefits, it comes with a cost: the programmer has to formulate the test cases and maintain them when the tested source code changes. Particularly for start-ups or small enterprises such costs become prohibitive, which often prefer...
In this paper, we present a new data mining framework for discovering sequence effects. In particular, we focus on the sequences consisting of actions that are taken in chronological order, like sequences of clinical procedures or marketing actions. Each sequence is associated with a binary outcome, a success or a failure. We investigate the hypothesis that certain subsequences of actions contribute...
While training a model with data from a dataset, we have to think of an ideal way to do so. The training should be done in such a way that while the model has enough instances to train on, they should not over-fit the model and at the same time, it must be considered that if there are not enough instances to train on, the model would not be trained properly and would give poor results when used for...
Graphs are a fundamental model to describe complex statistical relationships over many scientific domains. In this context, graphs are commonly used to investigate relational phenomena which are not directly observable. Our work formulates a Latent Network Inference problem and develops inference methods in a common context for scientific applications where there is an absence of ground truth.
Understanding how to properly use APIs of large libraries is difficult, error prone, and time consuming. Software developers resort to study to learn APIs. Several approaches have been proposed to mine these examples, but the sources from which they mine examples as well as their mining approaches hamper their applicability in some practical scenarios. Unit test cases seem to be an additional source...
Classification is the process of dividing the data into number of groups which are either dependent or independent of each other and each group acts as a class. The task of Classification can be done by using several methods using different types of classifiers. But classification cannot be done easily when it is to be applied on text documents that is: document classification. The main purpose of...
In contemporary society, an increasing number of people are involved in the biomedical research. However there is still a large amount of biological knowledge in the various unstructured documents so that it is difficult to analyze biological data. How to identify biological terms effectively from text is one of the important problems in the area of bioinformatics. Nowadays the precision of the best...
Service-oriented computing advocates the development of new software or services on the basis of existing services. This paradigm shows a great potential of achieving high productivity and low cost, but it faces a challenge in efficiently and correctly using existing services in producing a new application and ensuring its reliability. Building a formal model using a formal specification language...
What is a cloud application precisely? In this paper, we formulate a computing cloud as a kind of graph, a computing resource such as services or intellectual property access rights as an attribute of a graph node, and the use of a resource as a predicate on an edge of the graph. We also propose to model cloud computation semantically as a set of paths in a subgraph of the cloud such that every edge...
When large data repositories are coupled with geographic distribution of data, users and systems, it is necessary to combine different technologies for implementing high-performance distributed knowledge discovery systems. On the other hand, computational grid is emerging as a very promising infrastructure for high-performance distributed computing. Grid applications such as astronomy, chemistry,...
Since 1980’ s, there are lots of algorithms & models merge in the scope of criminal information analyzing along with the even rapid development of computer science. However, we find in Chinese the study on the scope of social public order comprehensive status is still a blank field. In this paper an urban crime distribution vector generation algorithm based on exponential attenuation also is put...
Separation of Concerns' has long been a key issue in the field of Software Engineering. While developing a large complex and scalable Software, it can be observed that certain concerns have a tendency to get interleaved with the Core-Functionalities in such a way that they become inseparable. As a result of which the coder, who is supposed to be responsible only with the Core-Functionalities, is bound...
The testing activities of the Software Verification and Validation (SV&V) team at Research In Motion (RIM) are requirements-based, which is commonly known as requirements-based testing (RBT). This paper proposes a novel approach to enhance the current RBT process at RIM, by utilizing historical testing data from previous releases, static analysis of the modified source code, and real-time execution...
Translation-based steganography (TBS) is a kind of famous text steganography. In this paper, we examine the robustness of TBS and give an effective detection algorithm for TBS. Our algorithm can not only distinguish between natural language text and stego-text which was generated by TBS, but also can distinguish between machine translated text and stego-text. The detection accuracy increases as the...
In traditional TOA or TDOA-based cellular localization, if mobile terminal (MT) can not connect well with 3 or more than 3 BSs, the localization will fail, or positioning accuracy is very poor. To solve this problem in 4G wireless networks, the cooperative group localization (CGL) scheme is proposed in this paper, where it is assumed that different MTs can directly communicate with each other in a...
Currently network security of institutions highly depend on firewalls, which are used to separate untrusted network from trusted one by enforcing security policies. Security policies used in firewalls are ordered set of rules where each rule is represented as a predicate and an action. This paper proposes modeling of firewall rules via directed acyclic graphs (DAG), from which test cases can be automatically...
Low dose rate (LDR) and high dose rate (HDR) total ionizing dose (TED) test results, drift calculations and an enhanced low dose rate sensitivity (ELDRS) characterization are presented for National Semiconductor's "ELDRS-free" bipolar reference, LM136-2.5 and compared to data from older versions of the product.
It can improve the recognition rate and segmentation accuracy of moving objects in strong wind and no buildings to extract the features of trees. In this paper, the similarity criterion about the pore texture feature matching of tree crown is proposed by analyzing the pore texture feature and experimenting. The feature difference matrix of 5times5 pixels is chosen as the basic operator of tree features...
New radiation-hardened operational amplifiers have been ELDRS and SEE characterized. This paper presents the TID results at high and low dose rates up to 300 krad(Si) and the SEE test results.
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