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Cellular networks are constantly evolving due to frequent changes in radio access and end user equipment technologies, dynamic applications and associated trafflc mixes. Network upgrades should be performed with extreme caution since millions of users heavily depend on the cellular networks for a wide range of day to day tasks, including emergency and alert notifications. Before upgrading the entire...
In this paper we shall present recent results of two applications for monitoring using acoustical signal classification. The first case study is the problem of context awareness based on acoustic analysis for a service robot. Then we discussed the acoustic classification for wildlife intruder detection. Previous results are briefly recalled and new experimental results are also provided.
Available sensing measurements in modern industrial process include two significant characteristics: distribution and autocorrelation. Different types of sensing measurements exhibit different characteristics. Moreover, different feature extraction methods are suitable for data with corresponding characteristics. This paper proposes a novel dual-step subspace partition method in order to establish...
Cascade is a widely used approach that rejects obvious negative samples at early stages for learning better classifier and faster inference. This paper presents chained cascade network (CC-Net). In this CC-Net, there are many cascade stages. Preceding cascade stages are placed at shallow layers. Easy hard examples are rejected at shallow layers so that the computation for deeper or wider layers is...
Deep Convolutional Neural Networks (CNNs) achieve substantial improvements in face detection in the wild. Classical CNN-based face detection methods simply stack successive layers of filters where an input sample should pass through all layers before reaching a face/non-face decision. Inspired by the fact that for face detection, filters in deeper layers can discriminate between difficult face/non-face...
The classification and identification of the bird species from the visual image is complex compared by using audio song. The knowledge of the features species type is very important as to ensure it is classified to the correct species. Color-based feature extraction is one of the procedure in extracting the color properties from the bird which to represent the species of the bird. However, it is a...
The classification of different odontocetes using écholocation clicks plays a significant role in tracking and detecting animals for research and protection purposes. Echolocation clicks were detected by an automatic method based on the Teager-Kaiser Energy Operator (TKEO). Then, these clicks were represented by their FFT magnitude spectrum. To reduce the influence of high similar clicks among species,...
In order to solve the problem that the accuracy of flaws identification in ultrasonic testing is not high enough due to the error in sensor information acquisition and the noise interference in the detection environment, a method of flaws identification in ultrasonic testing based on evidential reasoning rule (ER rule) is studied. Firstly, ER rule is proposed to consider the reliability and weights...
The interoperability testing of CTCS-3 Level Train Control System guarantees the safe operation of train running on different lines. It makes great sense to achieve automatic analysis of interoperability testing results, which could improve the efficiency and accuracy of testing. In this paper, a research was conducted on automatic analysis of testing results for on-board equipment of train control...
The sheer usage of social media presents an opportunity for an automated analysis of a social media user based on his/her information, activities, or status updates. This opportunity is due to the abundant amount of information shared by the user. This fact is especially true for countries with high number of active social media users such as Indonesia. Extraction of information from social media...
Roller element bearing fault diagnosis is crucial in industry to maintain that the machine is in good condition so that there is no delay of work due to machine breakdown. This paper discusses the use of Extreme Learning Machine (ELM) algorithm to classify bearing faults. The performance of ELM is compared with Back Propagation (BP) algorithm. It was found that the results show that the ELM has smaller...
An image-driven, model-free approach to design control systems for a large class of industrial process is proposed. A mathematical model of the process is replaced by sequences of subsequent images which play the role of the process (plant) states. The length of this sequences depends on the speed of the process dynamics and on the frame rate. Firstly, a learning sequence of the system states is collected...
Human action recognition has been extensively studied with a lot of real life application. Many methods have been proposed and achieved promising results when the input video captured from the same viewpoints. However, their accuracy decreases significantly under viewpoint changing. The reason is that action appearance is quite different when looking from a different angle. To overcome this problem,...
Programmers produce code clones when developing software. By copying and pasting code with or without modification, developers reuse existing code to improve programming productivity. However, code clones present challenges to software maintenance: they may require consistent application of the same or similar bug fixes or program changes to multiple code locations. To simplify the maintenance process,...
Recently, ultrasound imaging of muscle contractions has been used by several research groups to infer volitional motor intent of the user, and has shown promise as a novel muscle computer interface. Learning spatiotemporal features from ultrasound image sequences is challenging because of deformations introduced by probe repositioning. The image features are sensitive to probe placement and even small...
In this paper, a new similar stock prices patterns extraction method is proposed for short-term stock trend forecasting. Different from Euclidean distance and conventional dynamic time warping (DTW) based historical features extraction, the new feature extraction method is developed based on a modified DTW approach, which allows the length of historical sub-sequences to be in a suitable range and...
Previous studies have found that a significant number of bug reports are misclassified between bugs and nonbugs, and that manually classifying bug reports is a timeconsuming task. To address this problem, we propose a bug reports classification model with N-gram IDF, a theoretical extension of Inverse Document Frequency (IDF) for handling words and phrases of any length. N-gram IDF enables us to extract...
In this study, we will present a rule based fuzzy gesture recognition system where a user will interact with a spherical robot with hand gestures performed with a smart phone and the droid will respond by imitating this movements. In this context, we will take up the Gesture Recognition, Fuzzy Logic and Internet of Things (IoT) frameworks to construct such a Human-Machine Interface (HMI). In the proposed...
Data amount becomes rapidly increased in today's era. Data can be in form of text, picture, voice, and video. Social media is one factor of the data increase as everybody expresses, gives opinion, and even complains in social media. The first step is data collection used API twitter with each candidate names on Jakarta Governor Election. The collected data then became input for preprocessing step...
Every organism emits energy around it which comprises UV-radiation, EM-radiation, infrared and thermal radiation. This energy around human body represents health condition of the subject under study. These energy fields are called as aura of the body under consideration. Several types of equipments are there to capture such energy. Kirlian camera captures the distribution of energy radiation around...
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