scholarly journals Can Faulty Modules Be Predicted by Warning Messages of Static Code Analyzer?

2012 ◽  
Vol 2012 ◽  
pp. 1-8
Author(s):  
Osamu Mizuno ◽  
Michi Nakai
Keyword(s):  
Conventional Method ◽  
Detection Method ◽  
Source Code ◽  
Spam Filtering ◽  
Good Source ◽  
Original Source ◽  
Warning Messages ◽  
Spam Filter ◽  
Module Prediction ◽  
Filtering Technique

We have proposed a detection method of fault-prone modules based on the spam filtering technique, “Fault-prone filtering.” Fault-prone filtering is a method which uses the text classifier (spam filter) to classify source code modules in software. In this study, we propose an extension to use warning messages of a static code analyzer instead of raw source code. Since such warnings include useful information to detect faults, it is expected to improve the accuracy of fault-prone module prediction. From the result of experiment, it is found that warning messages of a static code analyzer are a good source of fault-prone filtering as the original source code. Moreover, it is discovered that it is more effective than the conventional method (that is, without static code analyzer) to raise the coverage rate of actual faulty modules.

scholarly journals SPONGY (SPam ONtoloGY): Email Classification Using Two-Level Dynamic Ontology

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Seongwook Youn
Keyword(s):  
Experimental System ◽  
Experimental Results ◽  
The Internet ◽  
Spam Filtering ◽  
Spam Filter ◽  
Spam Filters ◽  
Filtering Technique ◽  
Communication Methods ◽  
Email Classification

Email is one of common communication methods between people on the Internet. However, the increase of email misuse/abuse has resulted in an increasing volume of spam emails over recent years. An experimental system has been designed and implemented with the hypothesis that this method would outperform existing techniques, and the experimental results showed that indeed the proposed ontology-based approach improves spam filtering accuracy significantly. In this paper, two levels of ontology spam filters were implemented: a first level global ontology filter and a second level user-customized ontology filter. The use of the global ontology filter showed about 91% of spam filtered, which is comparable with other methods. The user-customized ontology filter was created based on the specific user’s background as well as the filtering mechanism used in the global ontology filter creation. The main contributions of the paper are (1) to introduce an ontology-based multilevel filtering technique that uses both a global ontology and an individual filter for each user to increase spam filtering accuracy and (2) to create a spam filter in the form of ontology, which is user-customized, scalable, and modularized, so that it can be embedded to many other systems for better performance.

scholarly journals Boyer Moore string-match framework for a hybrid short message service spam filtering technique

2021 ◽  
Vol 10 (3) ◽  
pp. 519
Author(s):  
Arnold Adimabua Ojugo ◽  
David Ademola Oyemade
Keyword(s):  
Network Structure ◽  
Text Message ◽  
Disruptive Technology ◽  
Spam Filtering ◽  
Markov Network ◽  
String Match ◽  
Short Text ◽  
Spam Filter ◽  
Message Service ◽  
Filtering Technique

Advances in technology and the proliferation of mobile device have continued to advance the ubiquitous nature of computing alongside their many prowess and improved features it brings as a disruptive technology to aid information sharing amongst many online users. This popularity, usage and adoption ease, mobility, and portability of the mobile smartphone devices have allowed for its acceptability and popularity. Mobile smartphones continue to adopt the use of short messages services accompanied with a scenario for spamming to thrive. Spams are unsolicited message or inappropriate contents. An effective spam filter studies are limited as short-text message service (SMS) are 140bytes, 160-characters, and rippled with abbreviation and slangs that further inhibits the effective training of models. The study proposes a string match algorithm used as deep learning ensemble on a hybrid spam filtering technique to normalize noisy features, expand text and use semantic dictionaries of disambiguation to train underlying learning heuristics and effectively classify SMS into legitimate and spam classes. Study uses a profile hidden Markov network to select and train the network structure and employs the deep neural network as a classifier network structure. Model achieves an accuracy of 97% with an error rate of 1.2%.

Non-Intrusive Adaptation of System Execution Traces for Performance Analysis of Software Systems

2014 ◽  
pp. 473-493
Author(s):  
Manjula Peiris ◽  
James H. Hill
Keyword(s):  
Performance Analysis ◽  
System Performance ◽  
Source Code ◽  
Software Systems ◽  
Software System ◽  
Original Source ◽  
Performance Properties ◽  
Execution Traces ◽  
Execution Trace ◽  
Analysis Of Performance

This chapter discusses how to adapt system execution traces to support analysis of software system performance properties, such as end-to-end response time, throughput, and service time. This is important because system execution traces contain complete snapshots of a systems execution—making them useful artifacts for analyzing software system performance properties. Unfortunately, if system execution traces do not contain the required properties, then analysis of performance properties is hard. In this chapter, the authors discuss: (1) what properties are required to analysis performance properties in a system execution trace; (2) different approaches for injecting the required properties into a system execution trace to support performance analysis; and (3) show, by example, the solution for one approach that does not require modifying the original source code of the system that produced the system execution.

scholarly journals A Frame Detection Method for Real-Time Hand Gesture Recognition Systems Using CW-Radar

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2321 ◽  
Author(s):  
Myoungseok Yu ◽  
Narae Kim ◽  
Yunho Jung ◽  
Seongjoo Lee
Keyword(s):  
Real Time ◽  
Conventional Method ◽  
Gesture Recognition ◽  
Detection Method ◽  
Recognition System ◽  
Hand Gesture Recognition ◽  
Hand Gesture ◽  
Recognition Probability ◽  
Recognition Systems ◽  
Cw Radar

In this paper, a method to detect frames was described that can be used as hand gesture data when configuring a real-time hand gesture recognition system using continuous wave (CW) radar. Detecting valid frames raises accuracy which recognizes gestures. Therefore, it is essential to detect valid frames in the real-time hand gesture recognition system using CW radar. The conventional research on hand gesture recognition systems has not been conducted on detecting valid frames. We took the R-wave on electrocardiogram (ECG) detection as the conventional method. The detection probability of the conventional method was 85.04%. It has a low accuracy to use the hand gesture recognition system. The proposal consists of 2-stages to improve accuracy. We measured the performance of the detection method of hand gestures provided by the detection probability and the recognition probability. By comparing the performance of each detection method, we proposed an optimal detection method. The proposal detects valid frames with an accuracy of 96.88%, 11.84% higher than the accuracy of the conventional method. Also, the recognition probability of the proposal method was 94.21%, which was 3.71% lower than the ideal method.

scholarly journals Antioxidant Capacity Determination in Plants and Plant-Derived Products: A Review

2016 ◽  
Vol 2016 ◽  
pp. 1-36 ◽  
Author(s):  
Aurelia Magdalena Pisoschi ◽  
Aneta Pop ◽  
Carmen Cimpeanu ◽  
Gabriel Predoi
Keyword(s):  
Antioxidant Capacity ◽  
Detection Method ◽  
Extraction Procedure ◽  
Capacity Assessment ◽  
Original Source ◽  
Advantages And Disadvantages ◽  
Extraction Step ◽  
The Matrix ◽  
Oxidative Species ◽  
Capacity Determination

The present paper aims at reviewing and commenting on the analytical methods applied to antioxidant and antioxidant capacity assessment in plant-derived products. Aspects related to oxidative stress, reactive oxidative species’ influence on key biomolecules, and antioxidant benefits and modalities of action are discussed. Also, the oxidant-antioxidant balance is critically discussed. The conventional and nonconventional extraction procedures applied prior to analysis are also presented, as the extraction step is of pivotal importance for isolation and concentration of the compound(s) of interest before analysis. Then, the chromatographic, spectrometric, and electrochemical methods for antioxidant and antioxidant capacity determination in plant-derived products are detailed with respect to their principles, characteristics, and specific applications. Peculiarities related to the matrix characteristics and other factors influencing the method’s performances are discussed. Health benefits of plants and derived products are described, as indicated in the original source. Finally, critical and conclusive aspects are given when it comes to the choice of a particular extraction procedure and detection method, which should consider the nature of the sample, prevalent antioxidant/antioxidant class, and the mechanism underlying each technique. Advantages and disadvantages are discussed for each method.

Improved Bayesian-Based Spam Filtering Approach

2013 ◽  
Vol 401-403 ◽  
pp. 1885-1891
Author(s):  
Xue Jiang ◽  
Jun Kai Yi
Keyword(s):  
Beneficial Effect ◽  
Experimental Result ◽  
Bayesian Filtering ◽  
Actual Situation ◽  
Spam Filtering ◽  
Bayesian Filter ◽  
Filtering Algorithm ◽  
Spam Filter ◽  
Filter Approach ◽  
Filtering Approach

Bayesian filtering approach is widely used in the field of anti-spam now. However, the two assumptions of this algorithm are significantly different with the actual situation so as to reduce the accuracy of the algorithm. This paper proposes a detailed improvement on researching of Bayesian Filtering Algorithm principle and implement method. It changes the priori probability of spam from constant figure to the actual probability, improves selection and selection rules of the token, and also adds URL and pictures to the detection content. Finally it designs a spam filter based on improved Bayesian filter approach. The experimental result of this improved Bayesian Filter approach indicates that it has a beneficial effect in the spam filter application.

scholarly journals Efficient Movement Compensation and Detection Algorithm using Blob Detection and Modified Kalman Filter

2020 ◽  
Vol 9 (5) ◽  
pp. 1187-1193
Keyword(s):  
Kalman Filter ◽  
Video Sequence ◽  
Detection Method ◽  
Detection Algorithm ◽  
Movement Detection ◽  
Blob Detection ◽  
Modified Kalman Filter ◽  
Filtering Technique ◽  
Movement Compensation ◽  
Time Required

In various real time applications such as security and surveillance etc., detection of movement from video sequence is commonly used. In such applications, time required to detect the movement and its accuracy is very crucial. In this paper, an efficient motion compensation and detection algorithm using Blob detection and modified Kalman filter techniques is proposed. The method is mainly based on Kalman filtering technique which is modified to compensate and detect the unwanted movement caused by the camera. Also the shadow effect caused by the variation in the intensity of light and object is removed using thresholding technique. Accuracy of movement detection is improved by implementing the blob detection method. The experimental results obtained from the developed algorithm is compared with few methods existing in the literature for validation.

scholarly journals A POSITION DETECTION METHOD OF DEVICES ON CONDUCTIVE CLOTHES BY CONTROLLING LED BLINKING

2013 ◽  
Vol 11 (02) ◽  
pp. 1350020
Author(s):  
NAOYA ISOYAMA ◽  
TSUTOMU TERADA ◽  
JUNICHI AKITA ◽  
MASAHIKO TSUKAMOTO
Keyword(s):  
Conventional Method ◽  
Experimental Evaluation ◽  
Detection Method ◽  
Communication Channels ◽  
Wearable Computing ◽  
Power Supplies ◽  
Conductive Fabric ◽  
Position Detection

Various wearable computing devices face problems with their power supplies, communication channels, and placement. Conductive clothes can resolve these problems, but it is still difficult to know the positions of devices on the conductive fabric. Therefore, we propose a method to detect the positions of such devices by using a camera. To detect the positions, our method blinks the LEDs on the devices according to their ID. Additionally, we propose several methods to shorten the time for detection. An experimental evaluation confirmed that compared with conventional method our methods reduce the time to detect the positions of the devices.

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