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The data exchange efficiency of traditional XML is low and its versatility is poor, while JSON has a higher transmission efficiency compared with XML. As a lightweight data-interchange format, JSON is becoming more and more popular, but not as common as XML for its latter appearance in the application of web services. If we directly translate the XML data format into JSON data format, the original...
Location Model is a classification model that capable to deal with mixtures of binary and continuous variables simultaneously. The binary variables create segmentation in the groups called cells whilst the continuous variables measure the differences between groups based on information inside the cells. It is important to note that location model is biased and even impossible to be constructed when...
The increasing of device interoperability creates a new way to design smart houses and to support enhanced living environments having as main aim the increasing of quality of life. In this context more supporting platforms for smart houses were developed, some of them using Cloud systems for remote supervision and control. An important aspect, which is an open issue for both industry and academia,...
Autoencoder is an excellent unsupervised learning algorithm. However, it can not generate kinds of sample data in the decoding process. Variational autoencoder is a typical generative adversarial net which can generate various data to augment the sample data. In this paper, we want to do some research about the information learning in hidden layer. In the simulation, we compare the hidden layer learning...
Internet of Things (IoT) refers to the network, the micro-sensor generated by the information to be collected, processed and used, and then the construction of intelligent families, smart city and wisdom of medical and other living environment. The research contents of this paper are to analyze the driving behavior data through the vehicle preloading equipment, analyze the factors that affect the...
Image stitching technique is to integrate multiple images with overlapping regions into a complete image with a wide viewing angle, less distortion, and no obvious suture. Image stitching could be used for global positioning and robot autonomous navigation without changing the hardware. SIFT feature and SURF feature are the classical algorithm in the image stitching. But they have the long time-consuming...
The administration of hot spring in Taiwan has collected and checked the data of hot spring level these years. Unique temperature and quality of the hot spring usually caused the device recorded and missing data. The data analysis used the gray theory in order to supplement the data of hot spring level.
We investigate the performance of dynamic proactive caching in relay networks where an intermediate relay station caches content for potential future use by end users. A central base station proactively controls the cache allocation such that cached content remains fresh for consumption for a limited number of time slots called proactive service window. With uncertain user demand over multiple data...
With the rapid development of science, the academic community requires higher and higher quality of the published articles. This great responsibility is placed on editorial boards of journals, on program committees of conferences and their members. In addition, with a large number of scientific conferences held each year, searching for experts that would be invited to join the program committees is...
In iMs paper, a novel method for extracting radar fingerprint using the unintentional modulation on radar signals is proposed. Proposed technique decomposes the unintentional modulations into its components using Variational Mode Decomposition (VMD) technique. Then, features that characterize each component are calculated. Simulations using real radar data show that proposed technique can classify...
The aim of of this work is reduction of the in-band interference in the data obtained with the channel probe device in which the Frequency Modulated Continuous Wave (FMCW) signal is used. For this purpose, the minimum norm algorithm and Wiener filter applications were used. The results of examinations, by using more echoes of the channel profile, were compared and it was determined which method is...
Decision guidance models are a means for design space exploration and documentation. In this paper, we present decision guidance models for microservice monitoring. The selection of a monitoring system is an essential part of each microservice architecture due to the high level of dynamic structure and behavior of such a system. We present decision guidance models for generation of monitoring data,...
Many guidelines for safety-critical industries, such as aeronautics, medical devices, and railway communications, specify that traceability must be used to demonstrate that a rigorous development process has been followed and to provide evidence that the developed system is safe for use. However, creating accurate and complete traceability is costly and remains a practical challenge. The significant...
This paper proposes detection of anomaly acoustic scenes based on a temporal dissimilarity model. The periodicity in the temporal variation of acoustic scenes is first pointed out and then used to build a new stochastic model. In the new model, the temporal variation is expressed by dissimilarity between current and previous acoustic scenes. Anomaly acoustic scenes are detected based on the 24-hour...
Modern smartphone applications rely on contextual information while providing the users with relevant and timely content and services. One way of generating such contextual information is by employing learning systems to model user behavior. Motion-based sensors, such as the accelerometer or gyroscope, have been previously employed for recognizing predefined high-level physical activities such as...
Context is a fundamental tool humans use for understanding their environment, and it must be modelled in a way that accounts for the complexity faced in the real world. Current context modelling approaches mostly focus on a priori defined environments, while the majority of human life is in open, and hence complex and unpredictable, environments. We propose a context model where the context is organized...
Traditional ways of understanding customer behaviour are mainly based on predominantly field surveys, which are not effective as they require labor-intensive survey. As mobile devices and ubiquitous sensing technologies are becoming more and more pervasive, user-generated data from these platforms are providing rich information to uncover customer preference. In this study, we propose a shop recommendation...
Following the Service-Oriented Architecture, Cloud services are exposed as Web APIs (Application Program Interface), which serve as the contracts between the service providers and service consumers. With increasing massive and broad applications of Cloud-based development, a large number of diversified APIs are emerging. Due to their wide impacts, any flaw in the cloud APIs may lead to serious consequences...
Feature selection has become a remarkable research topic in recent years. It is an efficient methodology to tackle the information with high dimension. The underlying structure has been neglected by the previous feature choice technique and it determines the feature singly. Considering this truth, we are going to focus on the matter wherever feature possess some cluster structure. To resolve this...
Evolution of Internet of Things (IoT) demands interconnection of many autonomous and heterogeneous devices. Several such devices have very limited power. Every bit transmission consumes power and it is critical. The efficient power usage is a challenge. In this paper, we model an IoT device as a simple Hidden Markov Model (HMM) with a finite number of states and well determined emission probabilities...
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